S.

No Volume-8 Issue-5S, March 2019, ISSN: 2278-3075 (Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page

No.

1.

Authors: Asraful Syifaa’ Ahmad , Rohayanti Hassan, Mohamad Nazir Ahmad

Paper Title: Fake Fingerprint Detection Approaches: A Systematic Review

Abstract: Fake fingerprint detection refers to the recognition of a fingerprint image that was created by using a

fake fingerprint. These situation are causes the most reliable biometric technology which is fingerprint recognition

vulnerable. Therefore, this review presents a collection of the latest literature identified with the fake fingerprint

detection and simply center around software-based methodologies. A systematic literature to assessed are

performed by examining 146 essential investigations begin with the gross collection of 24 analyze about the papers

to decide an scientific categorization, methodologies, on-line open database, and also drawbacks of the fake

fingerprint. Besides, 14 techniques focusing in software-methodologies briefly described. Moreover, a few

constraints on the fake finger-print images are uncovered and databases that usually utilized by researcher is

distinguished. Thus, this review gives an outline of knowledge into the present comprehension of fake fingerprint

detection acknowledgement other than distinguishing upcoming research prospects.

Keywords: Fake fingerprint, fingerprint recognition, liveness detection, LivDet database, systematic literature

review.

References: 1. Z. Xia, R. Lv, Y. Zhu, P. Ji, H. Sun, and Y. Q. Shi, “Fingerprint liveness detection using gradient-based texture features,” Signal, Image

Video Process., vol. 11, pp. 1–8, 2016.

2. A. Al-Ajlan, “Survey on fingerprint liveness detection,” 2013 Int. Work. Biometrics Forensics, 2013, pp. 1–5, 2013.

3. A. Rattani, Z. Akhtar, and G. Foresti, “A preliminary study on identifying fabrication material from fake fingerprint images,” Proc. - 2015

IEEE Symp. Ser. Comput. Intell. SSCI 2015, pp. 362–366, 2016.

4. A. Toosi, S. Cumani, and A. Bottino, “On Multiview Analysis for Fingerprint Liveness Detection,” in Progress in Pattern Recognition,

Image Analysis, Computer Vision, and Applications: 20th Iberoamerican Congress, CIARP 2015, Montevideo, Uruguay, November 9-12,

2015, Proceedings, A. Pardo and J. Kittler, Eds. Cham: Springer International Publishing, 2015, pp. 143–150.

5. E. Marasco and A. Ross, “A Survey on Antispoofing Schemes for Fingerprint Recognition Systems,” ACM Comput. Surv., vol. 47, no. 2,

pp. 1–36, 2014.

6. U. Uludag and A. K. Jain, “Attacks on biometric systems: a case study in fingerprints,” Proc. SPIE 5306, Secur. Steganography,

Watermarking Multimed. Contents, p. 622, 2004.

7. N. K. Ratha, J. H. Connell, and R. M. Bolle, “An Analysis of Minutiae Matching Strength,” Audio- Video-Based Biometric Pers.

Authentication, vol. 2091, pp. 223–228, 2001.

8. A. Hadid, N. Evans, S. Marcel, and J. Fierrez, “Biometrics Systems Under Spoofing Attack: An evaluation methodology and lessons

learned,” IEEE Signal Process. Mag., vol. 32, no. 5, pp. 20–30, 2015.

9. E. Park, W. Kim, Q. Li, H. Kim, and J. Kim, “Fingerprint liveness detection using CNN features of random sample patches: Liveness

detection using CNN features,” Lect. Notes Informatics (LNI), Proc. - Ser. Gesellschaft fur Inform., vol. P-260, 2016.

10. G. Arunalatha and M. Ezhilarasan, “Fingerprint Spoof Detection Using Quality Features,” Int. J. Secur. Its Appl., vol. 9, no. 10, pp. 83–

94, 2015.

11. V. Mura, F. R. L. Ghiani, G.L. Marcialis, D. A. Yambay, and S. A. S. Clarkson, “Livdet 2015 fingerprint liveness detection competition

2015,” Int. Conf. Biometrics 2013, 2013.

12. L. Ghiani, V. Mura, S. Tocco, G. L. Marcialis, F. Roli, D. Yambay, and S. Schuckers, “LivDet 2013 - Iris Liveness Detection Competition

2013,” Biometrics Theory Appl. Syst., 2013.

13. P. Achimugu, A. Selamat, R. Ibrahim, and M. Naz, “A systematic literature review of software requirements prioritization research,” Inf.

Softw. Technol., vol. 56, no. 6, pp. 568–585, 2014.

14. E. Fielt, W. Bandara, S. Miskon, and G. Gable, “Exploring shared services from an is perspective: A literature review and research

agenda,” Commun. Assoc. Inf. Syst., vol. 34, no. 1, pp. 1001–1040, 2014.

15. E. D. Madyatmadja and H. Prabowo, “Participation to Public e-Service Development : A Systematic Literature Review,” Int. Conf.

Commun. Eng., vol. 8, no. 3, pp. 139–143, 2016.

16. J. Galbally, F. Alonso-Fernandez, J. Fierrez, and J. Ortega-Garcia, “A high performance fingerprint liveness detection method based on

quality related features,” Futur. Gener. Comput. Syst., vol. 28, no. 1, pp. 311–321, 2012.

17. P. Lapsley, J. L. Alexander, D. Pare, and N. Hoffman, “Anti-fraud biometric scanner that accurately detects blood flow,” 1998.

18. A. Antonelli, R. Cappelli, D. Maio, and D. Maltoni, “Fake finger detection by skin distortion analysis,” IEEE Trans. Inf. Forensics Secur.,

vol. 1, no. 3, pp. 360–373, 2006.

19. D. Baldisserra, A. Franco, D. Maio, and D. Maltoni, “Fake Fingerprint Detection by Odor Analysis,” Adv. Biometrics, pp. 265–272, 2006.

20. S. Kim, B. Park, B. S. Song, and S. Yang, “Deep belief network based statistical feature learning for fingerprint liveness detection,”

Pattern Recognit. Lett., vol. 77, pp. 58–65, 2016.

21. Z. Akhtar, C. Micheloni, and G. L. Foresti, “Biometric Liveness Detection: Challenges and Research Opportunities,” IEEE Secur. Priv.,

vol. 13, no. 5, pp. 63–72, 2015.

22. R. F. Nogueira, R. de Alencar Lotufo, and R. C. Machado, “Fingerprint Liveness Detection using Convolutional Networks,” Ieee Trans.

Inf. Forensics Secur., vol. 11, no. 6, pp. 1206–1213, 2016.

23. [23] C. Wang, K. Li, Z. Wu, and Q. Zhao, “A DCNN Based Fingerprint Liveness Detection Algorithm with Voting Strategy,” Springer

Int. Publ. Switz. 2015, pp. 241–249, 2015.

24. J. Galbally, S. Marcel, and J. Fierrez, “Image Quality Assessment for Fake Biometric Detection : Application to Iris , Fingerprint , and

Face Recognition,” IEEE Trans. Image Process., vol. 23, no. 2, pp. 710–724, 2014.

25. A. Bhanarkar, P. Doshi, A. Abhyankar, and A. Bang, “Joint time frequency analysis based liveness fingerprint detection,” 2013 IEEE 2nd

Int. Conf. Image Inf. Process. IEEE ICIIP 2013, pp. 166–169, 2013.

26. D. Gragnaniello, G. Poggi, C. Sansone, and L. Verdoliva, “Local contrast phase descriptor for fingerprint liveness detection,” Pattern

Recognit., vol. 48, no. 4, pp. 1046–1054, 2015.

27. D. Gragnaniello, G. Poggi, C. Sansone, and L. Verdoliva, “Fingerprint liveness detection based on Weber Local image Descriptor,” 2013

IEEE Work. Biometric Meas. Syst. Secur. Med. Appl. BioMS 2013 - Proc., 2013.

28. R. Dubey, J. Goh, and V. Thing, “Fingerprint Liveness Detection From Single Image Using Low Level Features and Shape Analysis,”

1-8

IEEE Trans. Inf. Forensics Secur., vol. 6013, no. c, pp. 1–1, 2016.

29. Z. Akhtar, C. Micheloni, and G. L. Foresti, “Correlation Based Fingerprint Liveness Detection,” IEEE, pp. 305–310, 2015.

30. X. Jia, X. Yang, K. Cao, Y. Zang, N. Zhang, R. Dai, X. Zhu, and J. Tian, “Multi-scale local binary pattern with filters for spoof fingerprint

detection,” Inf. Sci. (Ny)., vol. 268, pp. 91–102, 2014.

31. S. Mohammadi and M. Hariri, “New Approaches to Fingerprint Authentication Using Software Methods Based on Fingerprint Texture,”

in 2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), 2015, pp. 1088–1092.

32. B. Tan and S. Schuckers, “New approach for liveness detection in fingerprint scanners based on valley noise analysis,” J. Electron.

Imaging, vol. 17, no. 1, p. 11009, 2008.

33. Y. S. Moon, J. S. Chen, K. C. Chan, K. So, and K. C. Woo, “Wavelet based fingerprint liveness detection,” Trans. Korean Inst. Electr.

Eng., vol. 57, no. 6, pp. 982–984, 2008.

34. R. Derakhshani, S. A. C. Schuckers, L. A. Hornak, and L. O’Gorman, “Determination of vitality from a non-invasive biomedical

measurement for use in fingerprint scanners,” Pattern Recognit., vol. 36, no. 2, pp. 383–396, 2003.

35. A. Abhyankar and S. Schuckers, “Integrating a wavelet based perspiration liveness check with fingerprint recognition,” Pattern Recognit.,

vol. 42, no. 3, pp. 452–464, 2009.

36. “LivDet - Liveness Detection Competitions.” [Online]. Available: http://livdet.org/. [Accessed: 08-Feb-2017].

37. “ATVS - Biometric Recognition Group » Databases » ATVS-FFp.” [Online]. Available: http://atvs.ii.uam.es/ffp_db.html. [Accessed: 08-

Feb-2017].

38. Hatim Mohamad Tahir, Emmanuel O.C. Mkpojiogu, “Towards Secure Data Circulation in Mobile Cloud Computing”, International

Innovative Research Journal of Engineering and Technology, Vol: 4, Issue: 1, p. 18-23, Sep 2018.

2.

Authors: N.A. Mohd Jelani, A.N. Zulkifli, S. Ismail, M.F. Yusoff

Paper Title: A Study of Trainees Satisfaction using the Virtual Taekwondo Training Environment (VT 2E)

Prototype

Abstract: Taekwondo is one among the foremost common martial arts that has a many of followers all around

the globe. Usually, a taekwondo work part takes place throughout a hall or massive high areas among the presence

of a trainers’. This can be foremost common coaching (training) approach for Taekwondo. However, this method

has few drawbacks in approaching independent coaching. Taekwondo trainees would like independent coaching to

enhance their skilled and performance. Even though there have some kinds of advantageous taekwondo work

materials obtainable on the market an internet, most of them need as far as three-dimensional visual image. This

paper presents the Virtual Taekwondo Training Environment (VT2E) model, a new supplementary self-reliant

taekwondo coaching approach. The objective of this paper is to regardless of whether or not the intervention of the

new taekwondo work approaches by virtual reality contributed to the trainees’ satisfaction in self-directed training.

The study was administered among a sample of forty six World Taekwondo Federation (WTF) trainees. Pearson

Correlation and Regression analyses were used to verify the results of participating, Presence, Utility and Easy Use

on trainees’ satisfaction in using the VT2E example. The results offer empirical support for the positive and

statistically necessary links within Utility and Easy Use and trainees’ satisfaction for taekwondo training. Be that

as it may participating and Presence didn’t have positive and important relationships with learners’ satisfaction for

independent coaching.

Keywords: Martial Arts, Taekwondo Training, Self-reliant coaching, Virtual Reality.

References: 1. T. S.-Y. Langford, "Building A Sustainable Business Model: An Analysis of Martial Arts Organizations from a System and a System of

Systems Perspective," California State University, East Bay, 2014.

2. S. S. Fong, S. S. Ng, and L. M. Chung, "Health through martial arts training: Physical fitness and reaction time in adolescent Taekwondo

practitioners," 2013.

3. M. Haddad, I. Ouergui, N. Hammami, and K. Chamari, "Physical Training in Taekwondo: Generic and Specific Training," Performance

Optimization in Taekwondo: From Laboratory to Field, pp. 85, 2015.

4. N. A. Sani, M. A. Hendrawan, and F. Samopa, "Development Of Basic Taekwondo Training System Application Based On Real Time

Motion Capture Using Microsoft Kinect," ISICO 2015, 2015.

5. J. C. Chan, H. Leung, J. K. Tang, and T. Komura, "A virtual reality dance training system using motion capture technology," IEEE

Transactions on Learning Technologies, vol. 4, pp. 187-195, 2011.

6. J. W. Lussier and S. B. Shadrick, "Components of effective training," DTIC Document 2006.

7. T. Komura, B. Lam, R. W. Lau, and H. Leung, "e-Learning martial arts," presented at International Conference on Web-Based Learning,

2006.

8. N. Gotoda, K. Matsuura, K. Nakagawa, and C. Miyaji, "Design of tennis training with shot-timing feedback based on trajectory prediction

of ball," presented at Naka Workshop Proc. of ICCE2013, 2013.

9. J. Falah, S. Khan, T. Alfalah, S. F. Alfalah, W. Chan, D. K. Harrison, and V. Charissis, "Virtual Reality medical training system for

anatomy education," presented at Science and Information Conference (SAI), 2014, 2014.

10. F. Anderson, T. Grossman, J. Matejka, and G. Fitzmaurice, "YouMove: enhancing movement training with an augmented reality mirror,"

presented at Proceedings of the 26th annual ACM symposium on User interface software and technology, 2013.

11. K. Witte, P. Emmermacher, N. Bandow, and S. Masik, "Usage of virtual reality technology to study reactions in karate-kumite,"

International Journal of Sports Science and Engineering, vol. 6, pp. 017-024, 2012.

12. S. Aukstakalnis and D. Blatner, Silicon Mirage; The Art and Science of Virtual Reality: Peachpit Press, 1992.

13. J. Seibert, "An exploratory study on virtual reality head mounted displays and their impact on player presence.," 2014.

14. G. H. Cho, G. Hwangbo, and H. S. Shin, "The effects of virtual reality-based balance training on balance of the elderly," Journal of

physical therapy science, vol. 26, pp. 615-617, 2014

15. W. Xiaoling, Z. Peng, W. Zhifang, S. Yan, L. Bin, and L. Yangchun, "Development an interactive VR training for CNC machining,"

presented at Proceedings of the 2004 ACM SIGGRAPH international conference on Virtual Reality continuum and its applications in

industry, 2004.

16. M. F. Levin, "Can virtual reality offer enriched environments for rehabilitation?," Expert review of neurotherapeutics, 2014.

17. J. Goulding, W. Nadim, P. Petridis, and M. Alshawi, "Construction industry offsite production: A virtual reality interactive training

environment prototype," Advanced Engineering Informatics, vol. 26, pp. 103-116, 2012.

18. H. J. Yap, Z. Taha, H. K. Choo, and C. K. Kok, "Virtual Reality-based Training System for Metal Active Gas Welding," 2014.

19. E. D. Ragan, D. A. Bowman, R. Kopper, C. Stinson, S. Scerbo, and R. P. McMahan, "Effects of field of view and visual complexity on

9-15

virtual reality training effectiveness for a visual scanning task," IEEE transactions on visualization and computer graphics, vol. 21, pp.

794-807, 2015.

20. D. Villani, C. Repetto, P. Cipresso, and G. Riva, "May I experience more presence in doing the same thing in virtual reality than in

reality? An answer from a simulated job interview," Interacting with Computers, vol. 24, pp. 265-272, 2012.

21. B. Z. Perez, M. M. Marin, and E. I. Perez, "Developing a virtual environment for safety training," presented at Electronics, Robotics and

Automotive Mechanics Conference (CERMA 2007), 2007.

22. L. Liu, G. X. Yin, K. Sha, and B. Gao, "Analysis of the Virtual System of Sports Scene Based on Virtual Reality Technology," presented

at Applied Mechanics and Materials, 2014.

23. G. M. Reger, A. A. Rizzo, and G. A. Gahm, "Initial development and dissemination of virtual reality exposure therapy for combat-related

PTSD," in Future Directions in Post-Traumatic Stress Disorder: Springer, 2015, pp. 289-302.

24. P. Dev and W. L. Heinrichs, "Learning medicine through collaboration and action: collaborative, experiential, networked learning

environments," Virtual Reality, vol. 12, pp. 215-234, 2008.

25. M. Pérez-Ramírez and N. J. Ontiveros-Hernández, "Virtual reality as a comprehensive training tool," WILE-MICAI. Guanajuato, Mexico,

2009.

26. V. S. Pantelidis, "Reasons to use virtual reality in education and training courses and a model to determine when to use virtual reality,"

Themes in Science and Technology Education, vol. 2, pp. 59-70, 2010.

27. G. H. Cho, G. Hwangbo, and H. S. Shin, "The effects of virtual reality-based balance training on balance of the elderly," Journal of

physical therapy science, vol. 26, pp. 615-617, 2014.

28. J. C. Yang, C. H. Chen, and M. C. Jeng, "Integrating video-capture virtual reality technology into a physically interactive learning

environment for English learning," Computers & Education, vol. 55, pp. 1346-1356, 2010.

29. A. Casu, L. D. Spano, F. Sorrentino, and R. Scateni, "RiftArt: Bringing Masterpieces in the Classroom through Immersive Virtual

Reality.," presented at Eurographics Italian Chapter Conference, 2015.

30. P. Xia, A. n. M. Lopes, M. T. Restivo, and Y. Yao, "A new type haptics-based virtual environment system for assembly training of

complex products," The International Journal of Advanced Manufacturing Technology, vol. 58, pp. 379-396, 2012.

31. Y. Li, K. Brodlie, and N. Phillips, "Web-based VR training simulator for percutaneous rhizotomy," Studies in health technology and

informatics, pp. 175-181, 2000.

32. P. T. Chua, R. Crivella, B. Daly, N. Hu, R. Schaaf, D. Ventura, T. Camill, J. Hodgins, and R. Pausch, "Training for physical tasks in

virtual environments: Tai Chi," presented at Virtual Reality, 2003. Proceedings. IEEE, 2003.

33. J. Bailenson, K. Patel, A. Nielsen, R. Bajscy, S.-H. Jung, and G. Kurillo, "The effect of interactivity on learning physical actions in virtual

reality," Media Psychology, vol. 11, pp. 354-376, 2008.

34. B. Bideau, R. Kulpa, N. Vignais, S. b. Brault, F. Multon, and C. Craig, "Using virtual reality to analyze sports performance," IEEE

Computer Graphics and Applications, vol. 30, pp. 14-21, 2010.

35. J. C. Chan, H. Leung, J. K. Tang, and T. Komura, "A virtual reality dance training system using motion capture technology," IEEE

Transactions on Learning Technologies, vol. 4, pp. 187-195, 2011.

36. K. Hachimura, H. Kato, and H. Tamura, "A prototype dance training support system with motion capture and mixed reality technologies,"

presented at Robot and Human Interactive Communication, 2004. ROMAN 2004. 13th IEEE International Workshop on, 2004.

37. T. S. Mujber, T. Szecsi, and M. S. Hashmi, "Virtual reality applications in manufacturing process simulation," Journal of materials

processing technology, vol. 155, pp. 1834-1838, 2004.

38. B.-g. Oh and S.-h. Lee, "Impact of Factors Related to Taekwondo Participants' Exercise Experience on Their Satisfaction with Acceptance

of WOM Information, and Spread by WOM," Indian Journal of Science and Technology, vol. 8, pp. 46, 2015.

39. M. P. Arnone, R. V. Small, S. A. Chauncey, and H. P. McKenna, "Curiosity, interest and engagement in technology-pervasive learning

environments: a new research agenda," Educational Technology Research and Development, vol. 59, pp. 181-198, 2011.

40. A. Bierbaum, C. Just, P. Hartling, K. Meinert, A. Baker, and C. Cruz-Neira, "VR Juggler: A virtual platform for virtual reality application

development," presented at Virtual Reality, 2001. Proceedings. IEEE, 2001.

41. B. G. Witmer and M. J. Singer, "Measuring presence in virtual environments: A presence questionnaire," Presence: Teleoperators and

virtual environments, vol. 7, pp. 225-240, 1998.

42. D. A. Bowman and R. P. McMahan, "Virtual reality: how much immersion is enough?," Computer, vol. 40, 2007.

43. F. D. Davis, "Perceived usefulness, perceived ease of use, and user acceptance of information technology," MIS quarterly, pp. 319-340,

1989

44. C. Lee, C. Chai, T. Teo, and D. Chen, "Preparing pre-service teachers’ for the integration of ICT based studentcentred learning (SCL)

curriculum," Journal of Education, vol. 13, pp. 15-28, 2008.

45. J. Webster, L. K. Trevino, and L. Ryan, "The dimensionality and correlates of flow in human-computer interactions," Computers in

human behavior, vol. 9, pp. 411-426, 1993.

46. F. D. Davis, "User acceptance of information technology: system characteristics, user perceptions and behavioral impacts," 1993.

47. S. W. Chou and C. H. Liu, "Learning effectiveness in a Web-based virtual learning environment: a learner control perspective," Journal of

computer assisted learning, vol. 21, pp. 65-76, 2005.

48. [48] E. M. Van Raaij and J. J. Schepers, "The acceptance and use of a virtual learning environment in China," Computers & Education,

vol. 50, pp. 838-852, 2008.

49. H. Taherdoost, S. Sahibuddin, and N. Jalaliyoon, "Smart card security; Technology and adoption," International Journal of Security, vol.

5, pp. 74-84, 2011.

50. J. Pallant, SPSS survival manual: McGraw-Hill Education (UK), 2013.

51. N. R. Draper and H. Smith, Applied regression analysis: John Wiley & Sons, 2014.

52. B. H. Cohen, Explaining psychological statistics: John Wiley & Sons, 2008.

53. J. Blackledge and M. Barrett, "Evaluation of a prototype desktop virtual reality model developed to enhance electrical safety and design in

the built environment," 2012.

54. P.-C. Sun, R. J. Tsai, G. Finger, Y.-Y. Chen, and D. Yeh, "What drives a successful e-Learning? An empirical investigation of the critical

factors influencing learner satisfaction," Computers & education, vol. 50, pp. 1183-1202, 2008.

55. E. A.-L. Lee, K. W. Wong, and C. C. Fung, "How does desktop virtual reality enhance learning outcomes? A structural equation modeling

approach," Computers & Education, vol. 55, pp. 1424-1442, 2010.

56. J. B. Arbaugh, "Virtual classroom characteristics and student satisfaction with internet-based MBA courses," Journal of management

education, vol. 24, pp. 32-54, 2000.

57. Z. Merchant, E. T. Goetz, W. Keeney-Kennicutt, O.-m. Kwok, L. Cifuentes, and T. J. Davis, "The learner characteristics, features of

desktop 3D virtual reality environments, and college chemistry instruction: A structural equation modeling analysis," Computers &

Education, vol. 59, pp. 551-568, 2012.

58. K. Mania and A. Chalmers, "The effects of levels of immersion on memory and presence in virtual environments: A reality centered

approach," CyberPsychology & Behavior, vol. 4, pp. 247-264, 2001

59. R. Moreno and R. E. Mayer, "Learning science in virtual reality multimedia environments: Role of methods and media.," Journal of

educational psychology, vol. 94, pp. 598, 2002.

60. Y. H. Cho, S. Y. Yim, and S. Paik, "Physical and social presence in 3D virtual role-play for pre-service teachers," The Internet and Higher

Education, vol. 25, pp. 70-77, 2015.

3.

Authors: ChenKim Lim, KianLam Tan, Vicknesh Suppramaniam, HweiTeeng Chong

Paper Title: L-Germs: L-System Based Plant Modeling and Music Score Generation through Scientific Pitch

Notation

Abstract: The mission for photo-realism plants modeling areas yet open test. Within the L-System, non-regular

and complex plant turn out to be all more numerically sensible. In any case, some control parameters should be

adjusted again and to get the correct L-System axioms and productions protocols so as produce the good plants

modeling. In this paper, an cross-compiling l-Systems stage are created for developing plant models from squiggly

structures of computer graphics application to genuine numerically based representations. The determinations are

worked using enabling the standards JSON IDE (Java Script Object Notation Integrated Development

Environment) within primitive custom-made to L-Systems algorithms. Besides, from plant modeled, a music score

based on scientific pitch notation is generated. Toward the finish of this paper, various outlined programming

precedentis gives through graphic interpretations on L-System.

Keywords: l-System, Plants modeling, L-System Fractal, Turtles Graphic, Scientific Pitch Notation.

References: 1. Pradal, C., Coste, J., Baty, G., Ribes, S., Boudon, F., & Godin, C. (2016). OpenAleaLab: An open-source multi-paradigm-multi-language

software framework for modeling morphogenesis.

2. Prince, D. R., Fletcher, M. E., Shen, C., & Fletcher, T. H. (2014). Application of L-systems to geometrical construction of chamise and

juniper shrubs. Ecological modelling, 273, 86-95.

3. Prusinkiewicz, P., &Lindenmayer, A. (2012). The algorithmic beauty of plants. Springer Science & Business Media.

4. J. Mishra and S.N. Mishra (2016). L-System Fractals. Mathematics in Science and Engineering, vol. 209, 1-258.

5. Prusinkiewicz, P., & Hanan, J. (2013). Lindenmayer systems, fractals, and plants (Vol. 79). Springer Science & Business Media.

6. Togelius, J., Shaker, N., & Dormans, J. (2016). Grammars and L-systems with applications to vegetation and levels. In Procedural

Content Generation in Games (pp. 73-98). Springer International Publishing.

7. Caldwell, M. (2015). An Investigation into Animating Plant Structures within Real-time Constraints (Doctoral dissertation, University of

Huddersfield).

8. Favorskaya, M. N., & Jain, L. C. (2017). Tree Modelling in Virtual Reality Environment. In Handbook on Advances in Remote Sensing

and Geographic Information Systems (pp. 141-179). Springer International Publishing.

9. Togelius, J., Shaker, N., &Dormans, J. (2016). Grammars and L-systems with applications to vegetation and levels. In Procedural Content

Generation in Games (pp. 73-98). Springer International Publishing.

10. Veenstra, F., Faina, A., Stoy, K., &Risi, S. (2016). Generating artificial plant morphologies for function and aesthetics through evolving

L-Systems. In Proceedings of the Artificial Life Conference (pp. 692-699).

11. Nakano, R. (2014). Emergent Induction of Deterministic Context-Free L-system Grammar. In Innovations in Bio-inspired Computing and

Applications (pp. 75-84). Springer, Cham.

12. Pradal, C., Coste, J., Baty, G., Ribes, S., Boudon, F., & Godin, C. (2016). OpenAleaLab: An open-source multi-paradigm-multi-language

software framework for modeling morphogenesis.

13. Lim, C. K., Tan, K. L., Yusran, H., &Suppramaniam, V. (2017). LSound: An L-System Framework for Score Generation+ C1:

C31. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2-11), 159-163.

16-22

4.

Authors: Nadzirah Zainordin, Syuhaida Ismail

Paper Title: Review on the Strength and Weaknesses of Sustainability Implementation for Higher Education

Institution

Abstract: Sustainability evaluation for Higher Educational Institution had been as of late executed far and wide.

There are various Higher Education Institutions guarantee their enthusiasm to accept and rehearse thatidea inside

the institutions. This may be demonstrated dependent upon the Declaration, Charters and Initiatives (DCIs) created

by this interested Higher Educational Institution. Nonetheless, using submitting that enthusiasm on which

manageability evaluation in Higher Educational Institution, there may various instruments worked as marker to

quantify the maintainability rehearses in the institutions. Consequently, through extensive literature survey, this

study explores the strength-ness and weakness of the current maintainability evaluation in Advanced Educational

Institution use assessing announcement created previous concerning supportability in Higher Educational

Institution. Around twenty inquire about to analyze paper distributed inside an previous ten years may utilized in

introducing all the significant literatures, investigating and turning off within the discoveries of what is the markers

may be considering for maintainability evaluation in Higher Educational Institution dependent upon the

comparable of the strength-ness and weakness talked about before. These papers are relied upon to associate as far

as upgrading the current information in maintainability evaluation in Higher Educational Institution on its usage.

Keywords: Sustainable Indicators; Sustainability Tools; Sustainable implemenmtation for higher education

References: 1. Abdul Ghapor. S., Abd Aziz. M., Abdul Razak. D., AbidinSanusi. Z., (2015). Implementing Education for Sustainable De-velopment in

Higher Education: Case Study of Albukhary International University Malaysia.

2. AASHE (2011). Techinical manual STARS.

3. AUA (2012). Alternative university appraisal model for ESD in Higher Education Institutions, pp 0-35.

4. Calder, W., Clugston, R.M., (2003). International efforts to promote higher education for sustainable development. Planning for higher

education 31, 30-44.

5. Cortese, A.D., 2003. The critical role of higher education in creating sustainable future. Planning for Higher Education. Vol. 31 No. 3,

pp.15-22.

6. Folke, C. Carpenter, S., Elmqvist, T., Gunderson, L., Holling, C. S. and Walker B., 2002.

7. Resilience and Sustainable Development: Building Adaptive Capacity in a World of Transformations, Ambio, 31(5), 473-40.

8. FabricionCaserejos, Laura Morten Gustavan, Mauricio NogueiraFrota (2017), Higher Education Institutions in the United States:

23-27

Commitment and coherency to sustainability vis-à-vis dimension of the institutional environment, Journal of Cleaner Production.

9. Francisco Urquiza Gomez, Cesar Saez-Navarrete, SolangeRencoretLioi, VartanInshanogluMarzuca (2015). Adaptable mdoel for assessing

sustainability in higher education. Journal of Cleaner Production 107, 475-485.

10. Karatzoglou, B., (2013). An in-depth literature review of the evolving roles and contributions of universities to education for sustainable

development. Journal of Cleaner Production 49, 44-53.

11. Lozano, R., 2004. A tool for easy benchmarking sustainability reports in universities. Environmental Management Sustainable University

Monterrey, Mexico.

12. Lozano, R. (2006). A tool for a Graphical Assessment of Sustainability in Universities (GASU). Journal of Cleaner Production, 14(9-11),

963–972.

13. Lozano, R., Ceulemans, K., Alonso-Almeida, M., Huisigh, D., Lozano, F., Tom Waas, Huge, J., 2015. A review of commitment and

implementation of sustainable development in higher eductaion: results from a worldwide survey. Journal of Cleaner Production. 1-18.

14. Lozano, R., Peattie, K., (2011). Assessing Cardiff University’s Curricula Contribution to Sustainable Development using the STAUNCH

System. Journal of Education for Sustainable Development.

15. Masaru Yarime, Yuko Tanaka (2012). The issues and methodologies in sustainability assessment tools for higher education institutions: a

review of recent trends and future challengers. Journal of Education for Sustainable Development 6(1), 63-67.

16. Schriberg, M., (2002). Institutional assessment tools for sustainability in higher education: strength, weaknesses and implication for

practices and theory. International Journal Sustainable Higher Education 3(3), 254-270.

17. United Nations (2012), Report of the United Nations Conference on Sustainable Development, United Nation New York, NY, USA. Pp.

1-126.

18. ULSF (2001). Sustainability assessment questionnaire (SAQ) for colleges and universities. Universitas Indonesia (2012). Green Metric

World University ranking.

19. UNEP (1972). Declaration of the United Conference on the Human Environment.

20. UNESCO (1984). The Luneberg Declaration.

21. UNESCO (1997). Educating for sustainable future: a transdisciplinary vision for concerted action in development.

22. Velaquez, L., Munguia, N., Sanchez, M., (2005). Deterring sustainability in higher education institutions: an appraisal of the factors which

influence sustainability in higher education institutions. International Journal of Sustainability in Higher Education 6(4), 383-391

23. Wright, T. (2012). The evolution of sustainability declaration in higher education in Corcoran. Higher Education and the lenges of

Sustainability. Kluwer Academic Publisher. The Netherland.

5.

Authors: Hapini Awang, Wan Rozaini Sheik Osman, Zahurin Mat Aji

Paper Title: Model to Evaluate Virtual Learning Environment among Malaysian Teachers

Abstract: The sophisticated improvement of Information and Communication Technology (ICT) has sparked

new inventions in teaching and learning approach. These positive technological advantages therefore inspired the

Malaysian Ministry of Education (MOE) to invest in digitalizing the Malaysian schools, including the

implementation of Frog Virtual Learning Environments (VLE). Despite this huge investment, the ratio of usage is

relatively low, especially among the teachers. This evidence indicates that there is an urgent requirement to

conduct a post-implementation evaluation to investigate the factors behind the issue. Therefore, this study is

conducted to develop a conceptual model based on the updated DeLone and McLean IS Success Model to evaluate

the Frog VLE success among Malaysian teachers. As the study is still in the early stage, this paper will present the

initial investigation that leads to the development of the conceptual model, including background of the study, the

objectives, literature review and research methodology that the study wishes to employ. Based on this conceptual

model, 14 hypotheses have been proposed.

Keywords: DeLone and McLean IS Success Model, Evaluation of IS Success, Frog VLE, Learning Management

System, Jel classification: A29, O33

References: 1. Berns, A., Gonzalez-Pardo, A., & Camacho, D. (2013). Game-like language learning in 3-D virtual environments. Computers &

Education, 60(1), 210-220.

2. Wilson, B. G. (1996). Constructivist learning environments: Case studies in instructional design. Educational Technology.

3. Ahmad, R., Piccoli, G., & Ives, B. (1998, December). Effectiveness of virtual learning environments in basic skills business education: A

field study in progress. In Proceedings of the international conference on Information systems (pp. 352-357). Association for Information

Systems.

4. Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment

of effectiveness in basic IT skills training. MIS quarterly, 401-426.

5. Abdelhag, M. E., & Osman, S. E. F. (2014). SOA for Effective Data Integration of Virtual Learning Environment Systems. International

Journal, 4(6).

6. Nor Fadzleen, S. and Halina, M. D. (2013). “Knowledge Management Enhancement in Virtual Learning Environment (VLE) in Malaysian

Schools,” in International Conference on Virtual Learning Environment (ICVLE). pp. 1–9.

7. Uzunboylu, H., Bicen, H., & Cavus, N. (2011). The efficient virtual learning environment: A case study of web 2.0 tools and Windows

live spaces. Computers & Education, 56(3), 720-726.

8. Halonen, R., Thomander, H., & Laukkanen, E. (2012). DeLone & McLean IS success model in evaluating knowledge transfer in a virtual

learning environment. In Societal Impacts on Information Systems Development and Applications (pp. 100-113). IGI Global.

Kementerian Pendidikan Malaysia, “Perkhidmatan 1Bestarinet,” Putrajaya, Malaysia, 2014.

9. Kementerian Pendidikan Malaysia, “Perancangan Pelaksanaan Peluasan Sistem Pengurusan Sekolah sebagai Penyelesaian kepada

Menangani Isu Beban Tugas Guru dan Pengintegrasian Satu Data Pendidikan KPM,” 2013.

10. Abdullah, N., Mohamed Noh, N., Yusuff, N., Azmah, N., & Mansor, R. (2013). Aplikasi Persekitaran Pengajaran Maya (FROG VLE)

Dalam Kalangan Guru Sains. Jurnal Pendidikan Sains & Matematik Malaysia, 3(2), 63-76.

11. Cheok, M. L., & Wong, S. L. (2014). Predictors Of E-Learning Satisfaction Among The Malaysian Secondary School Teachers. Icce

2014, 33.

12. Kementerian Kewangan Malaysia, “Maklum Balas Ke Atas Laporan Ketua Audit Negara 2013 Siri 3,” Putrajaya, Malaysia, 2014.

13. Cheok, M. L., & Wong, S. L. (2016). Frog Virtual Learning Environment for Malaysian Schools: Exploring Teachers’ Experience. In ICT

in Education in Global Context (pp. 201-209). Springer Singapore.

14. Eom, S., Ashill, N. J., Arbaugh, J. B., & Stapleton, J. L. (2012). The role of information technology in e-learning systems success. Human

Systems Management, 31(3-4), 147-163.

28-37

15. Mohammadi, H. (2015). Factors affecting the e-learning outcomes: An integration of TAM and IS success model. Telematics and

Informatics, 32(4), 701-719.

16. Abuhmaid, A. (2011). ICT training courses for teacher professional development in Jordan. TOJET: The Turkish Online Journal of

Educational Technology, 10(4).

17. Raman, K., & Yamat, H. (2014). Barriers Teachers Face in Integrating ICT during English Lessons: A Case Study. Malaysian Online

Journal of Educational Technology, 2(3), 11-19.

18. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of

acceptance and use of technology.

19. Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of

management information systems, 19(4), 9-30.

20. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems

research, 3(1), 60-95.

21. AlAwadhi, S., & Morris, A. (2008, January). The Use of the UTAUT Model in the Adoption of E-government Services in Kuwait. In

Hawaii International Conference on System Sciences, Proceedings of the 41st Annual (pp. 219-219). Ieee.

22. Jurisch, M. C., Kautz, M., Wolf, P., & Krcmar, H. (2015, January). An international survey of the factors influencing the intention to use

open government. In System Sciences (HICSS), 2015 48th Hawaii International Conference on (pp. 2188-2198). IEEE.

Chang, H. H., Wang, Y. H., & Yang, W. Y. (2009). The impact of e-service quality, customer satisfaction and loyalty on e-marketing:

Moderating effect of perceived value. Total Quality Management, 20(4), 423-443.

23. Dai, C. Y., Kao, M. T., Harn, C. T., Yuan, Y. H., & Chen, W. F. (2011, August). The research on user satisfaction of easy teaching Web

of Taipei assessed via information quality, system quality, and Technology Acceptance Model. In Computer Science & Education

(ICCSE), 2011 6th International Conference on (pp. 758-762). IEEE.

24. Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 351-370.

25. Hassan, J., & Kamisah, S. N. (2010). Halangan terhadap penggunaan komputer dan ICT di dalam pengajaran dan pembelajaran (P&P) di

kalangan guru di sekolah menengah kebangsaan luar Bandar di daerah Kulai Jaya Johor.

26. M. J. Nor Azlah, K. Fariza, N. A. Mohd Jaafar, F. Khalid, M. J. Nor Azlah, K. Fariza, N. A. Mohd Jaafar, and F. Khalid,(2014).

“Keberkesanan Kemahiran Komunikasi Di Kalangan Guru Dalam Penggunaan Persekitaran Pembelajaran Maya (Frog VLE),” Pengajaran

Sumber Dan Teknol. Mklm. Impaknya ke atas Penyelid. Dalam Pendidik. 2014, vol. 11, pp. 63–69.

27. M. Ummu Salma and K. Fariza. (2014). “Tahap Pengetahuan Guru Sekolah Rendah dalam Penggunaan VLE-Frog untuk Pengajaran &

Pembelajaran,” in The 4th International Conference on Learner Diversity (ICELD 2014), 2014, pp. 780–788.

28. Al-Debei, M. M., Jalal, D., & Al-Lozi, E. (2013). Measuring web portals success: a respecification and validation of the DeLone and

McLean information systems success model. International Journal of Business Information Systems, 14(1), 96-133.

29. Al Zoubib, A. I. S., & Jali, M. Z. (2014, June). An integrated success adoption model for examining E-learning among adult workers in

Jordan. In Computer and Information Sciences (ICCOINS), 2014 International Conference on (pp. 1-4). IEEE.

30. Hosnavi, R., & Ramezan, M. (2010). Measuring the effectiveness of a human resource information system in National Iranian Oil

Company: An empirical assessment. Education, Business and Society: Contemporary Middle Eastern Issues, 3(1), 28-39.

31. Alshibly, H. H. (2014). Evaluating E-HRM success: A Validation of the Information Systems Success Model. International Journal of

Human Resource Studies, 4(3), 107.

32. Chen, J. V., Jubilado, R. J. M., Capistrano, E. P. S., & Yen, D. C. (2015). Factors affecting online tax filing–An application of the IS

Success Model and trust theory. Computers in Human Behavior, 43, 251-262.

33. Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information systems

research, 16(1), 85-102.

34. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information

technologies. Decision sciences, 28(3), 557-582.

35. Mardiana, S., Tjakraatmadja, J. H., & Aprianingsih, A. (2015). DeLone-McLean information system success model revisited: The

separation of intention to use-use and the integration of technology acceptance models. International Journal of Economics and Financial

Issues, 5(1S).

36. Wu, D., Hiltz, S. R., & Bieber, M. (2010). Acceptance of educational technology: field studies of asynchronous participatory

examinations. Communications of the Association for Information Systems, 26(1), 21.

37. Ramayah, T., Ahmad, N. H., & Lo, M. C. (2010). The role of quality factors in intention to continue using an e-learning system in

Malaysia. Procedia-Social and Behavioral Sciences, 2(2), 5422-5426.

38. Chen, C. W. D., & Cheng, C. Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the

DeLone and McLean model. Behaviour & Information Technology, 28(4), 335-345.

39. Iivari, J. (2005). An empirical test of the DeLone-McLean model of information system success. ACM Sigmis Database, 36(2), 8-27.

40. Halawi, L. A., McCarthy, R. V., & Aronson, J. E. (2008). An empirical investigation of knowledge management systems' success. Journal

of Computer Information Systems, 48(2), 121-135.

41. Teo, T. S., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of management

information systems, 25(3), 99-132.

42. Klein, R. (2007). An empirical examination of patient-physician portal acceptance. European Journal of Information Systems, 16(6), 751-

760.

43. Choe, J. M. (1996). The relationships among performance of accounting information systems, influence factors, and evolution level of

information systems. Journal of Management Information Systems, 12(4), 215-239.

44. Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of

pre-adoption and post-adoption beliefs. MIS quarterly, 183-213.

45. 1BestariNet, (2012). “1BestariNet - Kementerian Pendidikan Malaysia: Soalan Lazim,” 2012. [Online]. Available:

http://1bestarinet.net/?page_id=21. [Accessed: 24-Sep-2016].

46. Fang, Y. H., Chiu, C. M., & Wang, E. T. (2011). Understanding customers' satisfaction and repurchase intentions: An integration of IS

success model, trust, and justice. Internet Research, 21(4), 479-503.

47. Zheng, Y., Zhao, K., & Stylianou, A. (2013). The impacts of information quality and system quality on users' continuance intention in

information-exchange virtual communities: An empirical investigation. Decision Support Systems, 56, 513-524.

48. Hsieh, J. J., Rai, A., Petter, S., & Zhang, T. (2012). Impact of user satisfaction with mandated CRM use on employee service quality. MIS

Quarterly, 36(4).

49. Ainin, S., Bahri, S., & Ahmad, A. (2012). Evaluating portal performance: A study of the National Higher Education Fund Corporation

(PTPTN) portal. Telematics and Informatics, 29(3), 314-323.

50. Bossen, C., Jensen, L. G., & Udsen, F. W. (2013). Evaluation of a comprehensive EHR based on the DeLone and McLean model for IS

success: approach, results, and success factors. International journal of medical informatics, 82(10), 940-953.

51. Urbach, N., & Müller, B. (2012). The updated DeLone and McLean model of information systems success. In Information systems theory

(pp. 1-18). Springer New York.

52. Aggelidis, V. P., & Chatzoglou, P. D. (2012). Hospital information systems: Measuring end user computing satisfaction (EUCS). Journal

of biomedical informatics, 45(3), 566-579.

53. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

54. Petter, S., DeLone, W., & McLean, E. (2008). Measuring information systems success: models, dimensions, measures, and

interrelationships. European journal of information systems, 17(3), 236-263.

55. Lin, P. C., Lu, H. K., & Liu, C. H. I. A. (2013). Towards an education behavioral intention model for e-learning systems: An extension of

UTAUT. Journal of Theoretical and Applied Information Technology, 47(3), 1120-1127.

56. Taylor, R. N. (1975). Age and experience as determinants of managerial information processing and decision making performance.

Academy of Management Journal, 18(1), 74-81.

57. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view.

MIS quarterly, 425-478.

58. Jennings, J. M., & Jacoby, L. L. (1993). Automatic versus intentional uses of memory: aging, attention, and control. Psychology and

aging, 8(2), 283.

59. Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and age differences in employee decisions about new technology: An

extension to the theory of planned behavior. IEEE transactions on engineering management, 52(1), 69-84.

60. Hindman, D. B. (2000). The rural-urban digital divide. Journalism & Mass Communication Quarterly, 77(3), 549-560.

61. Venkatesh, V., & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in

technology acceptance and usage behavior. MIS quarterly, 115-139.

62. Meyers-Levy, J., & Tybout, A. M. (1989). Schema congruity as a basis for product evaluation. Journal of consumer research, 16(1), 39-

54.

63. Meyers-Levy, J., & Maheswaran, D. (1991). Exploring differences in males' and females' processing strategies. Journal of Consumer

Research, 18(1), 63-70.

64. Levy, J. A. (1988). Intersections of gender and aging. The Sociological Quarterly, 29(4), 479-486.

65. Hutchinson, J. W. (1987). Dimensions of Consumer Expertise," Journal of Consumer Research, 13 (March), 411-454., J. Wesley

Hutchinson, and John G. Lynch (1990). Memory and Decision Making,” in Handbook

66. 0fC0n-sumer Theory and Research, ed. Harold H. Kassarjian and Thomas S. Robertson, Englewood Clifi" s, NJ: Prentice-Hall, 1-49.

67. Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior eSzajna, B. (1996). Empirical evaluation of the revised technology

acceptance model. Management science, 42(1), 85-92.

68. Thompson, R. L., Higgins, C. A., & Howell, J. M. (1994). Influence of experience on personal computer utilization: testing a conceptual

model. Journal of management information systems, 11(1), 167-187.

69. Yuker, H. E. (1984). Faculty Workload: Research, Theory, and Interpretation. ASHE-ERIC Higher Education Research Report No. 10,

1984. Association for the Study of Higher Education, Department PR-10, One Dupont Circle, Suite 630, Washington, DC.

70. Hu, P. J. H., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school teachers: a longitudinal study. Information &

management, 41(2), 227-241.

71. Ballet, K., & Kelchtermans, G. (2009). Struggling with workload: Primary teachers’ experience of intensification. Teaching and teacher

education, 25(8), 1150-1157.

72. Inan, F. A., & Lowther, D. L. (2010). Factors affecting technology integration in K-12 classrooms: A path model. Educational Technology

Research and Development, 58(2), 137-154.

73. Anuar and Mohd Nordin,(2015). “Amalan Kaizen Dalam Sistem Pengurusan Sekolah di Malaysia,” Res. Publ., no. September, 2015.

74. Creswell, J. W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

75. Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach. John Wiley & Sons.

76. J. J. Shaughnessy, E. B. Zechmeister, and J. S. Zechmeister. (2012). Research Methods in Psychology, 9th ed. New York: McGraw-Hill,

2012.

77. Dwivedi, Y. K., Papazafeiropoulou, A., Brinkman, W. P., & Lal, B. (2010). Examining the influence of service quality and secondary

influence on the behavioural intention to change internet service provider. Information Systems Frontiers, 12(2), 207-217.

78. Armstrong, D. J., Brooks, N. G., & Riemenschneider, C. K. (2015). Exhaustion from Information System Career Experience: Implications

for Turn-Away Intention. MIS Quarterly, 39(3).

79. Seddon, P., & Kiew, M. Y. (1996). A partial test and development of DeLone and McLean's model of IS success. Australasian Journal of

Information Systems, 4(1).

80. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-

152.

81. Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modeling and regression: Guidelines for research practice.

Communications of the association for information systems, 4(1), 7.

82. Aliza Sarlan, “To Propose Prediction Analysis Algorithm based on k-means and SVM Classification”, International Innovative Research

Journal of Engineering and Technology, Vol: 4, No: 1, p. 13-17, Sep 2018.

6.

Authors: Jafri Zulkepli, Tillal Eldabi

Paper Title: Hybrid Simulation for Sustainability of Decision Making

Abstract: Using a single simulation technique is not always viable enough to cope with complex system needs.

Discrete Event Simulation is normally applied for queuing system processes and for analysing individual criteria.

On other hand, system dynamics is utilised to assess continuous and qualitative variables such as levels of stress.

When combined in a hybrid model, these two techniques are capable to produce reliable outputs that will enhance

the knowledge of the decision makers. There are two types of hybrid interaction, cyclic and parallel. Currently,

simulation software does not support automated interaction, therefore, hybridisation is usually developed through

manual linking of models. This paper is an extension paper from two previous papers that developed healthcare

processes using hybrid simulation techniques to assess its viability over single technique usage. Based on the

results from hybrid, it shows a marked difference compared with results from single techniques. Therefore, we

conclude that hybrid simulation will gave better outputs for decision makers to consider.

Keywords: Decision Making; Discrete Even Simulation; Healthcare; Hybrid Simulation;System Dynamics

References: 1. A. Sweester. “A comparison of system dynamics and discrete event simulation”. In: International Conference of System Dynamics

Society and 5th Australian and New Zealand Systems Conference 1999. (1999)

2. D. C. Lane. “You just don’t understand: modes of failure and success in the discourse between system dynamics” LSE OR Dept Working

paper LSEOR 00-34, London School of Economic. (2000)

3. S. Brailsford and N. Hilton (2001) “A comparison of discrete event simulation and system dynamics for modelling healthcare systems”

In: Riley J (ed). Proceedings of ORAHS 2000, Glasgow, Scotland. 2001, pp. 18 – 39.

4. J. D. W. Morecroft and S. Robinson. “Explaining puzzling dynamics: comparing the use of system dynamics and discrete event

38-42

simulation” In: J. D. Sterman, M. P. Repenning, R. S. Langer, J. I. Rowe, J. M. Yarni (eds). Proceeding of the 23rd International

conference of the system dynamics society, system dynamic society, Boston, MA. 2005.

5. S. Brailsford. “System dynamics: what’s in it for healthcare simulation modellers” In: S. J. Mason, R.R. Hill, L. Monch, O. Rose, T.

Jefferson, J.W. Fowler (eds). Proceeding of the 2008 Winter simulation conference. 2008, pp 1478 – 1483.

6. K. Chahal. “A generic framework for hybrid simulation in healthcare” PhD Thesis. Brunel University, West London. (2009)

7. J. Zulkepli & T. Eldabi. “Developing integrated patient pathways using hybrid simulation”. In AIP Conference Proceedings (Vol. 1782,

No. 1, p. 040022). AIP Publishing. 2016

8. J. Zulkepli, T. Eldabi & N. Mustafee . “Hybrid simulation for modelling large systems: an example of integrated care model”

In Simulation Conference (WSC), Proceedings of the 2012 Winter. 2012, pp. 1-12.

9. J. Zulkepli & T. Eldabi . “Towards a framework for conceptual model hybridization in healthcare”. In Proceedings of the 2015 Winter

Simulation Conference. 2015, pp. 1597-1608

10. T. R. Rohleder, D. P. Bischak & L. B. Baskin, "Modeling patient service centers with simulation and system dynamics." Health Care

Management Science, vol. 10, no. 1, 2007, pp. 1–12.

11. N. Ahmad, N. A. Ghani, A. A. Kamil & R. M. Tahar. "Evaluating emergency department resource capacity using simulation." Modern

Applied Science, vol. 6, no. 11, 2012.

12. S. C. Brailsford, S. M. Desai, & J. Viana. "Towards the holy grail: combining system dynamics and discrete-event simulation in

healthcare." In Proceedings Winter Simulation Conference, 2010.

13. J. Viana, S. C. Brailsford, V. Harindra, & P. R. Harper. "Combining discrete-event simulation and system dynamics in a healthcare

setting: A composite model for Chlamydia infection." European Journal of Operational Research, vol. 237, no. 1, 2014, pp. 196–206.

14. J. Zulkepli. “A theoretical framework for hybrid simulation in modelling complex patient pathways”. PhD Thesis Brunel University.

2012

15. K. Pouliakas and I. Theodossiou. Confronting objections to performance pay: the impact of individual and gain‐sharing incentives on job

satisfaction. Scottish journal of political economy, vol. 56 no. 5, 2009, pp 662-684.

16. W. D. McCausland, K. Pouliakas, & I. Theodossiou. "Some are punished and some are rewarded: A study of the impact of performance

pay on job satisfaction." International journal of manpower, vol. 26, no. 7/8, 2005, pp. 636 – 659.

17. K. Chahal, T. Eldabi & A. Mandal. ”Understanding the impact of whiteboard on A&E department using hybrid simulation”. In: Pro

18. ceeding of 27th International Conference of the system dynamics society. Albuquerque, New Mexico, USA, 2009.

19. M. Elf & M. Putilova. “The care planning process – a case for system dynamics”. Proceedings of the 25th International Conference of the

System Dynamic Society, vol. 25, no. 1, 2005, pp. 1 – 18.

20. Aiken, L. H., S. P. Clarke, D. M. Sloane, J. Sochalski and J. H. Silber. Hospital nurse staffing and patient mortality, nurse burnout, and

job dissatisfaction. Jama, vol. 288, no. 16, 2002, 1987-1993.

7.

Authors: Sharifah NajlaaHanini Syed Abdullah, Nazrina Aziz, Mohd AzriPawan Teh

Paper Title: Time Truncated Two Sided Modified Chain Sampling Plans for Exponential Distribution

Abstract: In this paper, Two Sided Modified Chain Sampling Plans (TSMChSP) for Exponential distribution is

presented. The decision of acceptance lot can be made by ensuring no defects in both preceding and succeeding

samples. The design parameters such as the minimum sample size and operating characteristic values are

calculated to ensure the consumer’s risk at a specified quality level. The main purpose of this article is to produce

the TSMChSP for Exponential distributions. An example is provided for illustrative purpose.Then, the article

moving on further to compare the performances of TSMChSP and TSChSP, based on two criteria, which are the

number of minimum sample size, n and the probability of lot acceptance, L(p). The article concluded that, the

TSMChSP has a better performance compared to the TSChSP in both criteria.

Keywords: Two sided Modified Chain Sampling Plan (TSMChSP), Consumer’s risk, Operating characteristic

values, Exponential distribution, Minimum size

References: 1. Dodge, H. F, Chain Sampling Inspection Plan, Industrial Qual-ity Control, 11, No.4 (1955), 10-13

2. D. C. Montgomery, Statistical Quality Control: A Modern Introduction, 6th ed. Arizona: Wiley, 2009.

3. Epstein, B., 1954. Truncated life tests in the exponential case. Ann. Math. Stat., 25: 555-564.

4. Mughal, A.R., Z. Zain and N. Aziz, 2015c. New two sided complete group chain sampling plan for Pareto distribution of the 2nd kind. Int.

J. Appl. Eng. Res., 10(12): 31855-31860

5. M. A. P. Teh, N. Aziz and Z. Zain, Time truncated group chain sampling plans for Exponential distribution, Global Journal of Pure and

Applied Mathematics, 119, No. 3 (2018), 491-500. DOI: 10.12732/ijpam.v119i3.9

6. A. R. S. Ramaswamy and S. Jayasri, “Time Truncated Chain Sampling Plans for Generalized Rayleigh Distribution,” International

Refereed Journal of Engineering and Science, 3, No 2 (2014), 49-53.

7. A. R. S. Ramaswamy and S. Jayasri, Time Truncated Chain Sampling Plans for Generalized Exponential Distribution (International Journal

of Computational Engineering Research, 2012), pp. 1402–1407.

8. Aslam, M., Kundu, D., and Ahmad, M., “Time Truncated Ac-ceptance Sampling Plan for Generalized Exponential Distribu-tion,” J. Appl.

Stat., Vol. 37, 2010, pp. 555–566

9. Mughal, A.R, Z. Zain, and N. Aziz, “Time truncated group chain sampling strategy for pareto distribution of the 2nd kind,” Research

Journal of Applied Sciences, Engineering and Technology, vol. 10, pp. 471-474, June. 2016.

10. M. A. P. Teh, N. Aziz, and Z. Zain, “Time truncated group chain sampling plans for rayleigh distribution,” Global Journal of Pure and

Applied Mathematics, vol. 12, pp. 3693-3699, Aug. 2016.

11. M. A. P. Teh, N. Aziz, and Z. Zain, “Group chain sampling plans based on truncated life tests for log-logistic distribution,” International

Journal of Applied Engineering Research, vol. 11, pp. 8971-8974, Oct. 2016.

12. M. A. P. Teh, N. Aziz, and Z. Zain, “Group chain sampling plans based on truncated life test for inverse rayleigh distribution,” Research

Journal of Applied Sciences, vol. 11, pp. 1432-1435, Nov. 2016.

13. Mughal, A.R., 2011. A hybrid economic group acceptance sampling plan for exponential lifetime distribution. Econ. Qual. Control, 26:

163-171.

14. Mughal, A.R. and M. Aslam, 2011. Efficient group acceptance sampling plans for family Pareto distribution. Cont. J. Appl. Sci., 6(3): 40-

52.

15. Mughal, A.R., M. Hanif, M. Ahmed and A. Rehman, 2011. Economic reliability acceptance sampling plans from truncated life tests based

on the burr type XII percentiles. Pak. J. Commerc. Soc. Sci., 5(1): 166-176.

16. Mughal, A.R., Z. Zain and N. Aziz, 2015a. Time Truncated group chain sampling strategy for Pareto distribution of the 2nd kind. Res. J.

Appl. Sci. Eng. Technol., 10(4): 471-474.

43-47

17. Mughal, A.R., Z. Zain and N. Aziz, 2015b. Group acceptance sampling plan for re-submitted lots under generalized Pareto distribution.

Res. J. Appl. Sci. Eng. Technol., 10(5): 599-606.

18. Mughal, A.R., Z. Zain and N. Aziz, 2015c. New two sided complete group chain sampling plan for Pareto distribution of the 2nd kind. Int.

J. Appl. Eng. Res., 10(12): 31855-31860.

19. Mughal, A.R., Z. Zain and N. Aziz, 2015d. Economic reliability GASP for Pareto distribution of the 2nd kind using Poisson and weighted

Poisson distribution. Res. J. Appl. Sci., 10(8): 306-310.

20. Mughal, A. R., Zain, Z., and Aziz, N. (2016 a). Time Truncated Efficient Testing Strategy for Pareto distribution of the 2nd

kind using Weighted Poisson & Poisson distribution. SainsMalaysiana, 45(11), 1763-1772.

21. Devaarul. S and Vijila. M, Modified Complete Chain Sampling Plans For Inexpensive or Non-Destructive Products p – MCChSP (c1, c2, i,

j), International Journal of Applied Engineering Research, 2018, 3(2): 78-82

22. Vijila. M and DevaArul.S, Construction and Selection of Two Sided Complete Chain Sampling Plans – CCHSP (0,1) Indexed Through

AOQL, International Journal of Scientific Research and Management (IJSRM), 5, No 10 (2017), 7303-7307

23. A. F. Jamaludin, Z. Zain, N. Aziz, A Modified Group chain sampling plans for Lifetimes following a Rayleigh Distribution, Global Journal

of Pure and Applied Mathematics, 12, No. 5 (2016), 3941-4947.

24. A. F. Jamaludin, Z. Zain, N. Aziz, A Time Truncated Modified Group chain sampling plans based on exponential distribution, International

Conference on Mathematics, Statistics and their Applications, 2017), pp. 050023-1-050023-6

8.

Authors: Norazura Ahmad, Jafri Zulkepli, Razamin Ramli, Noraida Abdul Ghani, Aik Howe Teo

Paper Title: A System Dynamics Model to Understand the Effects of Returning Patients Toward Emergency

Department Density

Abstract: As an integrated unit in the hospital, emergency department (ED) also depends on other unit like labs

and wards. Due to this relationship, sometimes problems in ED not only originated from the department itself, but

may also come from other units. The complex interactions of patients and resources in the ED are no longer just

about clinical and medical issues, but the efficient health delivery and resource management is actually an

engineering problem. One possible engineering tool to understand the complex behaviour of the health care system

is using computer simulation modelling. This paper presents the development of a system dynamics (SD)

simulation model to understand the effect of retreated patients to the ED. SD is used to model the complexity of

many relationships in ED admission. The base case result shows that ED admission is also influenced by

readmission resulted from non-recovery level after discharged from hospital.

Keywords: Emergency Department; Returning Patients; Stock Flow Models.

References: 1. Malaysia Health Insurance (2015). http://www.malaysia-health-insurance.com/information/cost/

2. E. M. W. Kolb, T. Lee & J. Peck, “Effect of coupling between emergency department and inpatient unit on the overcrowding in

emergency department,” Proceedings of the 2007 Winter Simulation Conference, (2007), pp. 1586-1593.

3. M. M. Gunal & M. Pidd, “Interconnected DES models of emergency, outpatient and inpatient departments of a hospital,” Proceedings of

the 2006 Winter Simulation Conference, (2006), pp. 446-452.

4. J. K Cochran & K. T. Roche, “A multi class queing network analysis methodology for improving hospital emergency deprtment

performance,” Computers and Operation Research, 36, (2009), pp. 1497-1512.

5. I. W. Gibson, “An approach to hospital planning and design using discrete evnt simulation,” Proceedings of the 2007 Winter Simulation

Conference, (2007), pp. 1501-1509.

6. S. Brenner, Z. Zeng, Y. Liu, J. Wang, J. Li & P. K. Howard, “Modelling

7. and analysis of the emergency department at University of Kentucky Chandler using simulations,” Journal of Emergency Nursing, vol. 36,

no. 4, (2010), pp. 303-310.

8. A. K. Sabbatini, K.. Kocher, A. Basu & R. Y. Hsia, “In-hospital outcomes and costs among patients hospitalized during a return visit to

the emergency department,” JAMA, vol. 315, no. 7, (2016), pp. 663-671.

9. S. Mahmoudi, H. R. Taghipour, H. R. Javadzadeh, M. R. Ghane, H. Goordazi & M. H. K. Motamedi, “ospital readmission through the

emergency department,” Trauma Mon, vol. 21, no. 2, (2016).

10. G. T. Adamiak & I. Karlberg, “Impact of physician training level on emergency readmission within internal medicine,” International

Journal of Technology Assessment in Health Care, vol. 20, no. 4, (2004), pp. 516-523.

11. A. F. Mathis, “30-day readmission and emergency department visits: Experience of diabetes and abdominal surgery patient,” ProQuest

dissertation publishing, (2013).

12. L. Calder, A. Pozgay, S. Riff, D. Rothwell, E. Youngson, N. Mojaverian, A. Winn & A. Forster, “Adverse events in patients with return

emergency department visits,” BMJ Quality & Safety Online First, vol. 0, (2014), pp.1-7.

13. B. C. Sun, R. Y. Hsia, R.E. Weiss, D. Zingmond, L. J. Liang, W. Han, H. McCreath & S. M. Asch, “Effect of emergency department

crowding on outcomes of admitted patients”, Ann Emerg Med, vol. 61, no. 6, (2013), pp.605-611.

14. J. Sterman, “Business dynamics: systems thinking and modelling for a complex world,” Boston, USA : McGraw-Hill, (2000).

15. K. E. Maani, & R. Y. Cavana, “System thinking and modelling: Understanding change and complexity,” New Zealand:Pearson Education

New Zealand Limited, (2000).

16. N. Ahmad, J. Zulkepli, R. Ramli, N. A. Ghani, & Teo, A. H., “Understanding the dynamic effects of returning patients toward emergency

department density,” AIP Conference Proceedings 1905, 040003, (2017).

17. J. Zulkepli, “A theoretical framework for hybrid simulation in modeling complex patient pathways,” PhD Thesis, unpublished, (2012).

18. J. Zulkepli, T. Eldabi, & N. Mustafee, “Hybrid simulation for modelling large systems: an example of integrated care model,” Proceedings

of the 2012 Winter, (2012), pp. 1-12.

19. H. Sapiri, J. Zulkepli, N. Ahmad, N. Zainal-Abidin, & N. N. Hawari, “Introduction to system dynamics modelling and Vensim Software,”

1st ed., Sintok: UUM Press, (2017).

48-52

9.

Authors: Muhammad Zulqarnain Hakim Abd Jalal, Wan Laailatul Hanim Mat Desa, Mohd Kamal Mohd

Nawawi, Ruzelan Khalid, Razamin Ramli, Waleed Khalid Abduljabbar

Paper Title: Road Traffic Congestion Solution using Discrete-Event Simulation

Abstract: The increasing number of vehicles in developing areas indirectly become one of the causes for road traffic

congestion (RTC) to occur. RTC can also be caused by a temporary obstruction, a permanent capacity bottleneck in the network

itself, stochastic fluctuation in demand within a network, leading to spillback and queue propagation. Inefficient management of

traffic light control (TLC) to the existing system in term of cycle time contributes to the RTC in a developing town in Malaysia,

53-57

Changloon, especially during peak hours that lead to environmental pollution and long average waiting time. This situation

negatively affects the road users and the people surrounding. A discrete-event simulation (DES) model was developed using

ARENA software to represent the real TLC system condition during peak hours. From the simulation model, the TLC which

causing the bottleneck was identified. The total of three scenarios were developed with modification on elements such as road

structure and cycle time of TLC. All scenarios recorded with improvement for total average waiting time and average number

in queue. The findings of this study can be used as a guideline for authorities to improve road traffic at Changloon town during

peak hours.

Keywords: Cycle time; discrete-event simulation; road traffic congestion; traffic light control; waiting time

References: 1. Ismail R, Hafezi MH, Nor RM & Ambak K (2012), Passengers preference and satisfaction of public transport in Malaysia, Australian

Journal of Basic and Applied Sciences 6, 410–416.

2. Road Transport Department Malaysia (2015), Total Vehicle Registration Based on Year, available on line: http://www.jpj.gov.my

3. Ferreira M, Fernandes R, Conceição H, Viriyasitavat W & Tonguz OK (2010), Self-organized traffic control, Proceedings of the seventh

ACM international workshop on VehiculAr InterNETworking-VANET’10

4. Kamrani M, Hashemi Esmaeil Abadi SM & Rahimpour Golroudbary S (2014), Traffic simulation of two adjacent unsignalized T-

junctions during rush hours using Arena software, Simulation Modelling Practice and Theory, 49, 167–179.

5. Qi L, Zhou M & Luan W (2018), A Two-level Traffic Light Control Strategy for Preventing Incident-Based Urban Traffic Congestion,

IEEE Transactions on Intelligent Transportation Systems, 19, 13–24.

6. Sánchez-Medina JJ, Galán-Moreno MJ & Rubio-Royo E (2010), Traffic signal optimization in la Almozara District in Saragossa under

congestion conditions, using genetic algorithms, traffic microsimulation, and cluster computing, IEEE Transactions on Intelligent

Transportation Systems, 11, 132–141.

7. Yousef KM, Al-Karaki JN & Shatnawi AM (2010), Intelligent Traffic Light Flow Control System Using Wireless Sensors Networks,

Information Science and Engineering, 26, 753–768.

8. Barrachina J, Garrido P, Fogue M, Martinez FJ, Cano JC, Calafate CT & Manzoni P (2012), D-RSU: a density-based approach for road

side unit deployment in urban scenarios, International workshop on ipv6-based vehicular networks (Vehi6), collocated with the 2012

IEEE intelligent vehicles symposium, 1–6.

9. Kok AL, Hans EW & Schutten JMJ (2012), Vehicle routing under time-dependent travel times: The impact of congestion avoidance,

Computers and Operations Research, 39, 910–918.

10. Jain V, Sharma A & Subramanian L (2012), Road traffic congestion in the developing world, Proceedings of the 2nd ACM Symposium

on Computing for Development - ACM DEV ’12.

11. Downie A (2008), The World’s Worst Traffic Jams, Time Magazine, available on line:

http://content.time.com/time/world/article/0,8599,1733872,00.html

12. Su B, Huang H & Li Y (2016), Integrated simulation method for waterlogging and traffic congestion under urban rainstorms, Natural

Hazards, 81, 23–40.

13. Huang Y, Weng Y & Zhou M (2014), Modular Design of Urban Traffic-Light Control Systems Based on Synchronized Timed Petri Nets,

IEEE Transactions on Intelligent Transportation Systems, 15, 530–539.

14. Tan KK, Khalid M & Yusof R (1996), Intelligent traffic lights control by fuzzy logic, Malaysian Journal of Computer Science, 9, 29–35.

15. Adam I, Wahab A, Yaakop M, Salam AA & Zaharudin Z (2014), Adaptive Fuzzy Logic Traffic Light Management System, 4th

International Conference on Engineering Technology and Technopreneuship, 340–343.

16. Hewage KN & Ruwanpura JY (2004), Optimization of traffic signal light timing using simulation, Proceedings - Winter Simulation

Conference, 2, 1428–1433.

17. Maidstone R (2012), Discrete Event Simulation, System Dynamics and Agent Based Simulation: Discussion and Comparison, System, 1–

6.

18. Nawawi MKM, Jamil FC & Hamzah FM (2015), Evaluating performance of container terminal operation using simulation, AIP

Conference Proceedings, 1660.

19. Jalal MZHA, Nawawi MKM, Desa WLHM, Khalid R, Abduljabbar WK & Ramli R (2017), Green supply chain: Simulating road traffic

congestion, Journal of Physics: Conference Series, 890, 012111.

10.

Authors: Muhammad Farouk, Nazrina Aziz, Zakiyah Zain

Paper Title: The New Two-sided Group Chain Sampling Plan for Pareto Distribution of the 2nd Kind

Abstract: The new two-sided complete group chain acceptance sampling plan was first introduced in 2015. The

advantage of the plan is that it enables simultaneous multiple inspection of products and minimized the decrease of

probability of lot acceptance for zero-acceptance-number, while improving both producer’s and consumer’s risks.

This study proposes a new approach called the new two-sided group chain sampling plan, which emphasized on

consumer protection. The number of optimal groups is determined from observing various consumers’ risks, test

termination time and mean ratio. A time-truncated life test is performed with pre-specified parameters and the

operating characteristics values of the plan under various parameters are measured.

Keywords: Probability of Lot Acceptance; Pareto Distribution of the 2nd Kind; Truncated Life Test; The New

Two-Sided Group Chain Sampling Plan

References: 1. Dodge, H. F. (1955). Chain sampling inspection plan. Industry Quality Control, 11(4), pp. 10-13.

2. Aslam, M., & Jun, C. H. (2009). A group acceptance sampling plan for truncated life test having Weibull distribution. Journal of Applied

Statistics, 36(9), pp. 1021-1027.

3. Aslam, M., Kundu, D., Jun, C. H., & Ahmad, M. (2011). Time Truncated Group Acceptance Sampling Plans for Generalized Exponential

Distribution. Journal of Testing and Evaluation, 39(4).

4. Ramaswamy, A. R. S., &Sutharani, R. (2013). Designing Group Acceptance Sampling Plans for the Weibull Distribution and Gamma

Distribution Using Minimum Angle Method. International Journal of Mathematics and Statistics Studies, 1(4), pp. 23-36.

5. Mughal, A. R., Zain, Z., & Aziz, N. (2015a). Time truncated group chain sampling strategy for Pareto distribution of the 2nd kind.

Research Journal of Applied Sciences, Engineering and Technology, 10(4), pp. 471-474.

6. Teh, M. A. P., Aziz, N., & Zain, Z. (2016). Time truncated group chain sampling plans for Rayleigh distribution. Global Journal of Pure

and Applied Mathematics, 12 (4), pp. 3693-3699.

58-62

7. Teh, M. A. P., Aziz, N., & Zain, Z. (2018). Group chain sampling plans based on truncated life test for Exponential distribution.

International Journal of Pure and Applied Mathematics, 119 (3), pp. 491-500.

8. Teh, M. A. P., Aziz, N., & Zain, Z. (2016). Group chain sampling plans based on truncated life test for Inverse Rayleigh distribution.

Research Journal of Applied Sciences, 11 (11), pp. 1432-1435.

9. Teh, M. A. P., Aziz, N., & Zain, Z. (2016). Group chain sampling plans based on truncated life tests for Log-Logistic distribution.

International Journal of Applied Engineering Research, 11 (16), pp. 8971-8974.

10. Deva Arul, S. & Rebecca, I.E.K. (2012). Two-sided complete chain sampling plans for attribute quality characteristics (CChSP-0,1).

Karunya Journal of Research. 3(1), pp. 8-16.

11. Mughal, A. R., Zain, Z., & Aziz, N. (2015b). Modified Group Chain Sampling Strategy for Pareto Distribution of the 2nd Kind. Research

Journal of Applied Sciences, Engineering and Technology.

12. Jamaludin, A. J., Zain, Z. & Aziz, N. (2016). A modified group chain sampling plans for lifetimes following a Rayleigh distribution. Global

Journal of Pure and Applied Mathematics, 12 (5), pp. 3941-3947.

13. Mughal, A.R., Zain, Z., & Aziz, N. (2015c). New Two-Sided Complete Group Chain Sampling Plan for Pareto Distribution of the 2nd

Kind. Research India Publication. 10 (12), pp. 31855-31860.

11.

Authors: MohdAzriPawan Teh, Nazrina Aziz, Zakiyah Zain

Paper Title: Constructing Group Chain Acceptance Sampling Plans (GChSP) for Gamma Distribution

Abstract: This article develops group chain acceptance sampling plans (GChSP) for Gamma distribution when the

life test is truncated at a pre-specified time. The Gamma distribution is chosen as most electronic products such as

carbon-film resistors, light-emitting diodes and integrated logic family follow this distribution. The design

parameters such as the total of minimum groups, g and probability of lot acceptance, L(p) are calculated by

minimizing the consumer’s risk, β at a certain specified design parameter. Quality parameter is describe in terms

of mean with assumption that the test termination time, t0, the specified constant, a, the number of allowable

preceding lots, iand the number of products, r are pre-fixed. An example is given for determination purpose for the

GChSP. The article continues with performances comparison between the GChSP and the group acceptance

sampling plan (GSP). The article concludes that the GChSP has better performances compared to the GSP in terms

of the number of minimum groups, g, the probability of lot acceptance, L(p), the cost and the inspection time.

Keywords: Group chain acceptance sampling plan (GOhSP); Consumer’s risk; Gamma distribution; probability

of lot acceptance; number of minimum groups

References: 1. T. T. Allen, Introduction to Engineering Statistics and Six Sigma: Statistical Quality Control and Design of Experiments and Systems.

London: Springer, 2006.

2. D. C. Montgomery, Statistical Quality Control: A Modern Introduction, 6th ed. Arizona: Wiley, 2009.

3. S. S. Gupta, and P. A. Groll, “Gamma distribution in acceptance sampling based on life tests,” Journal of the American Statistical

Association, vol 56, pp. 942-970, Dec. 1961.

4. M. Aslam, C. H. Jun, and M. Ahmad, “A group sampling plan based on truncated life tests for gamma distributed items,” Pakistan Journal

of Statistics, vol. 25, pp. 333-340, Jan. 2009.

5. P. Anburajan, and A. R. S. Ramaswamy, “A two stage group acceptance sampling plans based on truncated life tests using log-logistic and

gamma distributions,” Journal of Progressive in Mathematics, vol. 2, pp. 107-117, July. 2016.

6. A. R. Mughal, Z. Zain, and N. Aziz, “Time truncated group chain sampling strategy for pareto distribution of the 2nd kind,” Research

Journal of Applied Sciences, Engineering and Technology, vol. 10, pp. 471-474, June. 2016.

7. M. A. P. Teh, N. Aziz, and Z. Zain, “Time truncated group chain sampling plans for rayleigh distribution,” Global Journal of Pure and

Applied Mathematics, vol. 12, pp. 3693-3699, Aug. 2016.

8. M. A. P. Teh, N. Aziz, and Z. Zain, “Group chain sampling plans based on truncated life tests for log-logistic distribution,” International

Journal of Applied Engineering Research, vol. 11, pp. 8971-8974, Oct. 2016.

9. M. A. P. Teh, N. Aziz, and Z. Zain, “Group chain sampling plans based on truncated life test for inverse rayleigh distribution,” Research

Journal of Applied Sciences, vol. 11, pp. 1432-1435, Nov. 2016.

10. G. J. Husak, J. Michaelsen, and C. Funk, “Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring

applications,” International Journal of Climatology, vol. 27, pp. 935-944, Dec. 2006.

11. M. Rohan, A. Fairweather, and N. Grainger, “Using gamma distribution to determine half-life rotenone, applied in freshwater,” Science of

The Total Environment, vol. 257-258, pp. 246-251, Sept. 2015.

12. A. R. S. Ramaswamy, and R. Sutharani, “Designing group acceptance sampling plans for the weibull distribution and gamma distribution

using minimum angle method,” International Journal of Mathematics and Statistics Studies, vol. 1, pp. 23-36, Dec. 2013.

13. M. A. P. Teh, N. Aziz, and Z. Zain, “Group chain sampling plans based on truncated life test for exponential distribution,” International

Journal of Pure and Applied Mathematics, vol. 119, pp. 491-500, Aug. 2018.

63-66

12.

Authors: Mok Kaie Yan, Carolyn Loong Yook Lean

Paper Title: Product Development of Chia Seeds Enriched Vegetable Balls: Effects on the Physicochemical

Properties

Abstract: Over the last decade, the market for vegetarian food and consumers‘ demand for functional food has been

growing along with the rising health awareness. Chia seeds with profound nutritional benefits are getting more recognized due

to their high alpha-linolenic acid, high dietary fiber and high protein. They have the potential to be food additive for industrial

uses due to their water holding capacity and amazing gelling properties. In this study, vegetable balls incorporated with chia

seeds were developed using allergen-free plant-derived ingredients as the base, while eggplant and chia seeds were used as the

major binder. Chia seeds gel was incorporated at 0% (control), 10% (F1), 20% (F2) and 30% (F3) to substitute eggplant in the

vegetable balls. The effects of chia seeds incorporation on the proximate composition (moisture, protein, fat, ash, carbohydrates

and dietary fiber), cooking characteristics (cooking yield and moisture retention) and physical properties (texture, colour, pH

and water activity) of vegetable balls were then investigated. Results indicated that F3 had significantly lower moisture content

(59.85%), higher protein (5.89%), fat (2.99%) and ash content (3.19%) in comparison to the control. Total dietary fiber of F3

(14.5%) was higher than control (12.3%). There were no statistical differences in cooking yield, moisture retention, pH and

water activity. Texture of F3 was significantly softer, less springy, more cohesive and adhesive than control, associated with the

water holding capacity of the seeds. For colour, F3 had significantly higher L* value than control. F3 could represent a healthy

66-72

and nutritional snacks food to the existing food industry and vegetarian market.

Keywords: Chia seeds; Vegetable balls; Chia seeds gel; fiber.

References: 1. B. Yannick, D. Benoit, and G. Maurice, J. Am. Heart Assoc. 5, e003661 (2018).

2. M.S. Coelho and M.M. Salas-Mellado, J. Food Nutr. Res. 2, 263 (2014).

3. R. Ayerza Jr and W. Coates, Ann. Nutr. Metab. 51, 27 (2007).

4. M.E. Oliva, M.R. Ferreira, A. Chicco, and Y.B. Lombardo, Prostaglandins, Leukot. Essent. Fat. Acids 89, 279 (2013).

5. H. Poudyal, S.K. Panchal, J. Waanders, L. Ward, and L. Brown, J. Nutr. Biochem. 23, 153 (2012).

6. A. Creus, M.R. Ferreira, M.E. Oliva, and Y.B. Lombardo, J. Clin. Med. 5, 18 (2016).

7. M.R. Segura-Campos, N. Ciau-Solís, G. Rosado-Rubio, L. Chel-Guerrero, and D. Betancur-Ancona, Int. J. Food Sci. 2014, (2014).

8. A.J. Lee, M. Thalayasingam, and B.W. Lee, Asia Pac. Allergy 3, 3 (2013).

9. B. Shreve, N. Thiex, and M. Wolf, (2006).

10. S.S. Nielsen, in Food Anal. Lab. Man. (Springer, 2010), pp. 47–53.

11. H.T. Lawless and H. Heymann, Sensory Evaluation of Food: Principles and Practices (Springer Science & Business Media, 2010).

12. N. Huda, Y.H. Shen, Y.L. Huey, and R.S. Dewi, Pakistan J. Nutr. 9, 1183 (2010).

13. A.K. Verma, V. Pathak, V.P. Singh, and P. Umaraw, J. Appl. Anim. Res. 44, 409 (2016).

14. R. Rendón-Villalobos, A. Ortíz-Sánchez, J. Solorza-Feria, and C.A. Trujillo-Hernández, Czech J. Food Sci. 30, (2012).

15. V.A. Barrientos, A. Aguirre, and R. Borneo, Int. J. Food Stud. 1, (2012).

16. M. Rodrigues Oliveira, M. Ercolani Novack, C. Pires Santos, E. Kubota, and C. Severo da Rosa, Semin. Ciências Agrárias 36, (2015).

17. P. Walters and J. Byl, Christian Paths to Health and Wellness (Human Kinetics, 2013).

18. Y. Ding, H.-W. Lin, Y.-L. Lin, D.-J. Yang, Y.-S. Yu, J.-W. Chen, S.-Y. Wang, and Y.-C. Chen, J. Food Drug Anal. 26, 124 (2018).

19. P.L. Pizarro, E.L. Almeida, N.C. Sammán, and Y.K. Chang, LWT-Food Sci. Technol. 54, 73 (2013).

20. N. Huda, Y.H. Shen, Y.L. Huey, R. Ahmad, and A. Mardiah, Am. J. Food Technol 5, 13 (2010).

21. E. Iglesias-Puig and M. Haros, Eur. Food Res. Technol. 237, 865 (2013).

22. S.R. Knowles and A.A. Mikocka-Walus, Psychological Aspects of Inflammatory Bowel Disease: A Biopsychosocial Approach

(Routledge, 2014).

23. Y.P. Timilsena, R. Adhikari, S. Kasapis, and B. Adhikari, Int. J. Biol. Macromol. 81, 991 (2015).

24. S. Ramos, P. Fradinho, P. Mata, and A. Raymundo, J. Sci. Food Agric. 97, 1753 (2017).

25. H. Oh, B.B. Choi, and Y.S. Kim, J. Korean Soc. Food Sci. Nutr. (2017).

26. M.H.F. Felisberto, A.L. Wahanik, C.R. Gomes-Ruffi, M.T.P.S. Clerici, Y.K. Chang, and C.J. Steel, LWT-Food Sci. Technol. 63, 1049

(2015).

13.

Authors: Liew Zhe Aun, Michelle Soo Oi Yoon

Paper Title: Traditional Morphometrics of Monogeneans (Metahaliotrema Spp.) from Scats Off Matang, Perak

Abstract: Monogenean was parasites that found on the marine or freshwater fish gill and skin as their host.

They used their haptoral organs which are anchors, bars and hooks to attach the host gill or skin. In this study,

Metahaliotrema species of monogenean was observed. Metahaliotrema species mostly found the fish called

Scatophagus argus. In this study, the specimens of Metahaliotrema from the host Scatophagus argus at Matang,

Perak was analyzed. There were three species of Metahaliotrema species could be found in the host fish i.e.

Metahaliotrema mizellei, Metahaliotrema filamentosum and Metahaliotrema ypsilocleithrum. The morphometrics

measurement of specimen’s hard parts such as anchors, bars, copulatory organ and hook were be observed and

measured using the software Leica QWin. The morphometrics information was analyzed based on morphometrics

variables by using R to differentiate the Metahaliotrema species. The results show that the Metahaliotrema species

were able to be differentiated by the morphometrics method. The measurement of all hard parts together was the

best way to distinguish between the monogenean species. The measurementsof only the bars showed no

differentiation at all.

Keywords: Morphometrics; monogenean species; Data analysis; cluster.

References: 1. K. Buchmann and T. Lindenstrøm, Int. J. Parasitol. 32, 309 (2002).

2. T. Öztürk and A. Özer, Turkish J. Fish. Aquat. Sci. 14, 367 (2014).

3. S. Yamaguti, Acta Med. Okayama 8, (1953).

4. D.C. Kritsky, H. Van Nguyen, N.D. Ha, and R.A. Heckmann, Syst. Parasitol. 93, 321 (2016).

5. J.K. Park, K.H. Kim, S. Kang, W. Kim, K.S. Eom, and D.T.J. Littlewood, BMC Evol. Biol. 7, 11 (2007).

6. A. Henderson, Bot. J. Linn. Soc. 151, 103 (2006).

7. T. Poisot and Y. Desdevises, Biol. J. Linn. Soc. 99, 559 (2010).

8. C. Hahn, T.A. Bakke, L. Bachmann, S. Weiss, and P.D. Harris, Parasitol. Int. 60, 480 (2011).

9. M.P. Robertson, N. Caithness, and M.H. Villet, Divers. Distrib. 7, 15 (2001).

10. E. V Dmitrieva, P.I. Gerasev, D.I. Gibson, N. V Pronkina, and P. Galli, Syst. Parasitol. 81, 203 (2012).

11. O.Y.M. Soo and L.H.S. Lim, Raffles Bull. Zool. 60, (2012).

12. O.Y.M. Soo and L.H.S. Lim, J. Helminthol. 89, 131 (2015).

73-76

14.

Authors: Baskaran , AK Muhammaddul Qawiy , Mohammad Taha

Paper Title: An Inhibitive Method to Determine Heavy Metals using A Cysteine ProteaseFicin

Abstract: Ficin was assessed for its capacity to distinguish chosen substantial metals utilizing a Bradford-protease-casein

measure framework. The premise of the protein measure utilizing casein as a substrate depends upon the powerlessness of the

Bradford reagent to recolor polypeptide with not exactly an atomic load of two kilodalton. Casein is recolored by the Bradford

reagent giving a dim blue shading. Its debasement item is be that as it may, isn't recolored by the reagent and the arrangement

stays dark colored in shading. Within the sight of substantial metals that hinder protease action, casein would stay undigested

and the shading after brooding would stay blue. These advancement considers incorporate ideal chemical, substrate, pH,

77-81

temperature and hatching time. The ideal convergence of compound, substrate, temperature and hatching time for protease is

comparable at 0.2mg/ml protease, 2mg/ml casein, 30oC and 25 minutes of brooding for protease test after a time of substantial

metals hatching. Ficin is ideal from pH 6 to 7. For ficin 3 overwhelming metals demonstrate some restraint of proteolytic action

utilizing an institutionalized substantial metals fixation at 1mg/L. The restraint appeared by the substantial metals on ficin

action are 92.4% for mercury, 98% for silver and 91.9% for copper. The IC50 estimations of mercury, silver and copper for

ficinis 0.0852, 0.09918 and 0.043mg/L individually. The breaking points of discovery (LOD), for mercury, silver and copper

were 0.002 mg l-1, 0.0002 mg l-1 and 0.006 mg l-1 individually. The breaking points of quantitation (LOQ) for mercury, silver

and copper were 0.044 mg l-1, 0.0188 mg l-1 and 0.025 mg l-1 individually. The upside of the protease bioassay contrasted

with other bioassay lies on its speed, economy, effortlessness, dependability in extreme conditions, for example, pH and

temperature and in addition moderately impedance free from cleansers, solvents and pesticides.

Keywords: ProteaseFicin; Inhibitive protein test; buffer; reagent; heavy metals solutions.

References: 1. U. Förstner and G.T.W. Wittmann, Metal Pollution in the Aquatic Environment (Springer Science & Business Media, 2012).

2. T. Tsubaki and K. Irukayama, MinamataDisease. Methylmercury Poisoning in Minamata and Niigata, Japan. (North-Holland Publishing

Company, PO Box 211, Amsterdam, The Netherlands., 1977).

3. S. Rodriguez-Mozaz, M.J.L. de Alda, and D. Barcelo, Anal. Bioanal. Chem. 386, 1025 (2006).

4. M.Y. Shukor, L.G. Tham, M.I.E. Halmi, I. Khalid, G. Begum, and M.A. Syed, J. Environ. Biol. 34, 967 (2013).

5. A.S. Aqlima, J. Environ. Bioremediation Toxicol. 1, 20 (2014).

6. T.K. velKrawczyk, M. Moszczyńska, and M. Trojanowicz, Biosens. Bioelectron. 15, 681 (2000).

7. G.L. Turdean, Int. J. Electrochem. 2011, (2011).

8. A. Amine, H. Mohammadi, I. Bourais, and G. Palleschi, Biosens. Bioelectron. 21, 1405 (2006).

9. M.E. Ghica and C.M.A. Brett, Microchim. Acta163, 185 (2008).

10. Y. Shukor, N.A. Baharom, F.A. Rahman, M.P. Abdullah, N.A. Shamaan, and M.A. Syed, Anal. Chim. Acta566, 283 (2006).

11. M.Y. Shukor, N. Masdor, N.A. Baharom, J.A. Jamal, M.P.A. Abdullah, N.A. Shamaan, and M.A. Syed, Appl. Biochem. Biotechnol. 144,

283 (2008).

12. M.Y. Shukor, N.A. Baharom, N.A. Masdor, M.P.A. Abdullah, N.A. Shamaan, J.A. Jamal, and M.A. Syed, J. Environ. Biol. 30, 17 (2009).

15.

Authors: Natalia Santoso, Nyam Kar Lin

Paper Title: Effect of Total Solids Content in Feed Emulsion on the Physico-Chemical Properties and Thermal

Stability of Freeze-Dried Roselle Extract

Abstract: Roselle anthocyanin has some potentials in the development of natural food colorants and as a source

of antioxidant. Nevertheless, during processing or storage, some factors affects its stability and leads to the

degradation. The purpose of this work is to analyze the effect of total solids content on the physico-chemical

properties of freeze-dried roselle extract (FDRE) and compare the thermal stability with roselle extract under

controlled temperature (80°C and 126°C) and period (0, 20, 40, 60, 80 min). Physico-chemical properties were

done from the form of roselle extract, roselle pre-mix solution, and FDRE while thermal stability was done on

roselle extract and FDRE following the first order of degradation kinetics. FDRE with 17%, 23%, and 28% total

solids content (TSC) were prepared. Results proved that freeze-drying improved the physico-chemical properties

and thermal stability of FDRE. Encapsulation efficiency represented that TSC of 28% was the best formulation

among others and it affected the half-life of FDRE. At 80°C, TSC of 28% (277.26 min) had the half life 4 times

longer than TSC 17% (67.96 min) while at 126°C, the half life of 28% TSC (154.03 min) was 2 times longer than

17% TSC (70.73 min).

Keywords: Roselle; roselle extract; chemical properties of roselle extract; freeze-dried roselle

References: 1. Agócs and J. Deli, J. Food Compos. Anal. 24, 757 (2011).

2. E. Pojer, F. Mattivi, D. Johnson, and C.S. Stockley, Compr. Rev. Food Sci. Food Saf. 12, 483 (2013).

3. K.A. Selim, K.E. Khalil, M.S. Abdel-Bary, and N.A. Abdel-Azeim, in Alex J Food Sci Technol. Conf (2008), pp. 7–20.

4. K.B. Mgaya, S.F. Remberg, B.E. Chove, and T. Wicklund, African J. Food, Agric. Nutr. Dev. 14, (2014).

5. K. Muzaffar, G.A. Nayik, and P. Kumar, J. Nutr. Food Sci. 1 (2015).

6. G. Özkan and S.E. Bilek, Int. J. Nutr. Food Sci. 3, 145 (2014).

7. N.V.N. Jyothi, P.M. Prasanna, S.N. Sakarkar, K.S. Prabha, P.S. Ramaiah, and G.Y. Srawan, J. Microencapsul. 27, 187 (2010).

8. S. Shukla and G.K. Road, 2, 3061 (2011).

9. R. Klinjapo and W. Krasaekoopt, in Handb. Food Bioeng., edited by A.M. Grumezescu and A.M.B.T.-N. and A.F.A. and F.D. Holban

(Academic Press, 2018), pp. 457–494.

10. M. Mishra, Handbook of Encapsulation and Controlled Release (CRC Press, 2015).

11. M. Betz and U. Kulozik, Procedia Food Sci. 1, 2047 (2011).

12. A. Nafiunisa, N. Aryanti, D.H. Wardhani, and A.C. Kumoro, in J. Phys. Conf. Ser. (IOP Publishing, 2017), p. 12084.

13. J. Lee, R.W. Durst, and R.E. Wrolstad, J. AOAC Int. 88, 1269 (2005).

14. Y.Y. Thoo, S.K. Ho, J.Y. Liang, C.W. Ho, and C.P. Tan, Food Chem. 120, 290 (2010).

15. S.K. Ng, Y.H. Choong, C.P. Tan, K. Long, and K.L. Nyam, LWT-Food Sci. Technol. 58, 627 (2014).

16. P.J. Tsai and H.-P. Huang, Food Res. Int. 37, 313 (2004).

17. Santos-Buelga and G. Williamson, Methods in Polyphenol Analysis (Royal Society of chemistry, 2003).

18. L.H. Skibsted, in Oxid. Foods Beverages Antioxid. Appl. Underst. Mech. Oxid. Antioxid. Act. (Elsevier, 2010), pp. 3–35.

19. S.B. Kedare and R.P. Singh, J. Food Sci. Technol. 48, 412 (2011).

20. J. Pokorny and S. Schmidt, Phytochem. Funct. Foods 298 (2003).

21. R. Akbari, A. Hatamzadeh, R. Sariri, and D. Bakhshi, Aust. J. Crop Sci. 7, 941 (2013).

22. R. Kasım, M. Suuml, and M.U. Kasım, African J. Plant Sci. 5, 323 (2011).

23. M. Ahmed, M.S. Akter, K.-B. Chin, and J.-B. Eun, Food Sci. Biotechnol. 18, 1487 (2009).

24. S. Damodaran and K.L. Parkin, Fennema’s Food Chemistry (CRC press, 2017).

25. R.L. Bradley, in Food Anal. (Springer, 2010), pp. 85–104.

82-87

26. G.C. S Anselmo, M.E.R. M Cavalcanti Mata, P. Campus de Arruda, and M. Coelho Sousa, Rev. Biol. e Ciências Da Terra 6, (2006).

27. C.A. Nayak and N.K. Rastogi, Dry. Technol. 28, 1396 (2010).

28. R. V Tonon, C. Brabet, and M.D. Hubinger, Food Res. Int. 43, 907 (2010).

29. N. Yousf, F. Nazir, R. Salim, H. Ahsan, and A. Sirwal, J. Pharmacogn. Phytochem. 6, 2165 (2017).

30. A. Parikh, S. Agarwal, and K. Raut, System 4, 6 (2014).

31. T. Laokuldilok and N. Kanha, J. Food Process. Preserv. 41, e12877 (2017).

32. Z. Idham, I.I. Muhamad, and M.R. Sarmidi, J. Food Process Eng. 35, 522 (2012).

33. Ş. Kara and E.A. Erçelebi, J. Food Eng. 116, 541 (2013).

34. Z. Zoric, V. Dragovic-Uzelac, S. Pedisic, Z. Kurtanjek, and I.E. Garofulic, Food Technol. Biotechnol. 52, 101 (2014).

35. S.J. Grabowski, Hydrogen Bonding: New Insights (Springer, 2006).

36. Shen, L. Zhang, J. Xue, S. Guan, Q. Liu, and R. Xiao, Carbohydr. Polym. 127, 363 (2015).

37. G.L. Arueya and B. Akomolafe, IOSR J. Environ. Sci. Toxicol. Food Technol.(IOSR-JESTFT) 8, 112 (2014).

16.

Authors: Siti Salwa Abd Gani, Nor Fadzillah Mokhtar, Uswatun Hasanah Zaidan, Farrah Payyadhah Borhan,

Khalijah Talha, Nur Fauwizah Azahar

Paper Title: Optimization of Moisturizing Clay Soap Containing Pitaya (Hylocereus Polyrhizus) Seed Extract using

D-Optimal Mixture Experimental Design

Abstract: Pitaya seed oil, extracted from red pitaya seeds, was utilized as a major antioxidant source in soap

formulation for skin application. Bentonite (grey clay powder) with various beneficial properties also was

incorporated in the formulation to enhance the positive effect toward skin’s structure. The influence of the main

compositions of soap formulation containing different fatty acid and oils (cocoa butter, virgin coconut oil, olive

oil, palm oil) on the hardness of the soap that undergoes saponification process was investigated by employing D-

optimal mixture experimental design. Analysis of variance (ANOVA) was carried out and the polynomial

regression for prepared soap hardness in terms of the six design factors was developed by utilizing the

experimental data. Results revealed that the best soap formulation included 9.027% A, 29.098% B, 19.588% C,

9.223% D, 23.860% E and 9.204% F. The results showed that the hardness of the soap was greatly affected by the

different in the level of fatty acid and oils in the formulation. Depending on the appropriate level of those six

variables, the production of moisturizing clay soap containing pitaya seed extract with the most desirable

properties which is much better than those of commercial ones is possible.

Keywords: pitaya, mixture design, saponification, clay JEL classification: I11, I12

References: 1. Adnan, L., Osman, A., & Abdul Hamid, A. (2011). Antioxidant activity of different extracts of red pitaya (Hylocereus polyrhizus) seed.

International Journal of Food Properties, 14(6), 1171-1181.

2. Ariffin, A. A., Bakar, J., Tan, C. P., Rahman, R. A., Karim, R., & Loi, C. C. (2009). Essential fatty acids of pitaya (dragon fruit) seed oil.

Food Chemistry, 114(2), 561-564.

3. Borhan, F. P., Abd Gani, S. S., & Shamsuddin, R. (2014). The use of D-optimal mixture design in optimising okara soap formulation for

stratum corneum application. The Scientific World Journal, 2014.

4. Carretero, M. I. (2002). Clay minerals and their beneficial effects upon human health. A review. Applied Clay Science, 21(3), 155-163.

5. DebMandal, M., & Mandal, S. (2011). Coconut (Cocos nucifera L.: Arecaceae): in health promotion and disease prevention. Asian Pacific

Journal of Tropical Medicine, 4(3), 241-247.

6. Draelos, Z. D. (2008). The cosmeceutical realm. Clinics in Dermatology, 26(6), 627-632.

7. Ginn, M. E., Steinhauer, R. C., Liebman, I., & Jungermann, E. (1968). Effect of tallow-coconut fatty acid ratios on properties of bar soaps.

Journal of the American Oil Chemists' Society, 45(10), 666-669.

8. Girgis, A. Y. (2003). Production of high quality castile soap from high rancid olive oil. Grasas y aceites, 54(3), 226-233.

9. Girgis, A. Y., El-Aziz, N. A., & El-Salam, S. A. (1998). Physical and chemical characteristics of toilet soap made from apricot kernel oil

and palm stearin. Grasas y Aceites, 49(5-6), 434-439.

10. Kamairudin, N., Gani, S. S. A., Masoumi, H. R. F., & Hashim, P. (2014). Optimization of natural lipstick formulation based on pitaya

(Hylocereus polyrhizus) seed oil using D-optimal mixture experimental design. Molecules, 19(10), 16672-16683.

11. Kamoun, A., Chaabouni, M., Sergent, M., & Phan-Tan-Luu, R. (2002). Mixture design applied to the formulation of hydrotropes for

liquid detergents. Chemometrics and Intelligent Laboratory Systems, 63(1), 69-79.

12. Kuntom, A., & Kifli, H. (1998). Properties of soaps derived from distilled palm stearin and palm kernel fatty acids. Journal of Surfactants

and Detergents, 1(3), 329-334.

13. Kuntom, A., Ahmad, I., Kifli, H., & Shariff, Z. M. (1999). Effects of superfatting agents on cracking phenomena in toilet soap. Journal of

Surfactants and Detergents, 2(3), 325-329.

14. Lim, H. K., Tan, C. P., Karim, R., Ariffin, A. A., & Bakar, J. (2010). Chemical composition and DSC thermal properties of two species of

Hylocereus cacti seed oil: Hylocereus undatus and Hylocereus polyrhizus. Food Chemistry, 119(4), 1326-1331.

15. Masoumi, H. R. F., Kassim, A., Basri, M., Abdullah, D. K., & Haron, M. J. (2011). Multivariate optimization in the biosynthesis of a

triethanolamine (TEA)-based esterquat cationic surfactant using an artificial neural network. Molecules, 16(7), 5538-5549.

16. Mohamad Zen, N. I., Abd Gani, S. S., Shamsudin, R., & Fard Masoumi, H. R. (2015). The use of D-optimal mixture design in optimizing

development of okara tablet formulation as a dietary supplement. The Scientific World Journal, 2015.

17. Morganti, P., & Sud, M. (2008). Cosmeceuticals. Clinics in dermatology, 26(4), 317.

18. Mukherjee, P. K., Maity, N., Nema, N. K., & Sarkar, B. K. (2011). Bioactive compounds from natural resources against skin aging.

Phytomedicine, 19(1), 64-73.

19. Preetha, J. P., & Karthika, K. (2009). Cosmeceuticals–an evolution. Int J ChemTech Res, 1(4), 1217-1223.

20. Silva, P. S., Oliveira, S. M., Farias, L., Fávaro, D. I., & Mazzilli, B. P. (2011). Chemical and radiological characterization of clay minerals

used in pharmaceutics and cosmetics. Applied Clay Science, 52(1), 145-149.

21. Singhal, M., Khanna, S., & Nasa, A. (2011). Cosmeceuticals for the skin: An overview. Asian J Pharm Clin Res, 4(2), 1-6.

22. Tarmizi, A. H. A., Lin, S. W., & Kuntom, A. (2008). Palm-based standard reference materials for iodine value and slip melting point.

Analytical chemistry insights, 3, 127.

23. Tenore, G. C., Novellino, E., & Basile, A. (2012). Nutraceutical potential and antioxidant benefits of red pitaya (Hylocereus polyrhizus)

extracts. Journal of functional foods, 4(1), 129-136.

88-96

17.

Authors: Zul Zakiyuddin Ahmad Rashid, Hamimah Adnan, Norazian Mohd Yusuwan, Nor Azmi Bakhary

Paper Title: Risk Management on Design Works in Malaysia

Abstract: Construction project is shrouded with various aspects of risks related to design professionals and

design works. The parties involved must be able to manage the risks to complete a construction project

successfully. This study aims to assess factors, associated with design professionals and design works, under the

traditional procurement route in Malaysia. The study has also investigated the role of Malaysian law in

corresponding to the practices of standard risk management by the parties involved. An in-depth, semi-structured

interview was applied to gather the information from practitioners involved in design for more than 10 years. The

findings showed that the level of understanding among the respondents can be improved. Several aspects of the

law of contract, tort, and statutory provisions have to be addressed to correspond to design risk management needs.

The law has been considered as an efficient force in ensuring proper risk management practice among the

designers. The lack of effort undermined the crucial role of the law itself. It was found out that there are certain

aspects of the law that are not being fully understood by the respondents; therefore, this factor also leads to the

occurrence of design related risks.

Keywords: Construction, Design Risk, Law, Risk Management

References: 1. Bolam v Friern Hospital Management Committe (1957). 1 WLR 582.

2. Bunni, Nael G. Risk and insurance in construction. Routledge, 2003.

3. Cornes, David. “The Concept of Design, Construction Contract Policy.” Improved Procedures and Practice (1989): 68.

4. Dey, Prasanta. “Managing risks of large scale construction projects.” Cost engineering 51, no. 6 (2009): 23-27.

5. Edwards, Leslie. Practical risk management in the construction industry. Thomas Telford, 1995.

6. Gangolells, Marta, Miquel Casals, Nuria Forcada, Xavier Roca, and Alba Fuertes. “Mitigating construction safety risks using prevention

through design.” Journal of safety research 41, no. 2 (2010): 107-122.

7. Gue See-Sew and Wong Shiao Yun. Slope Engineering Design and Construction Practice in Malaysia. (2008). Available at

http://www.gnpgeo.com.my/download/publication/2009_10.pdf

8. Hedley Bryne v Heller (1964). AC 465. Independent Broadcasting Authority v EMI Electronics & BICC Construction (1980) 14 BLR 1

9. Ismail, F., Yusuwan, N. M., & Baharuddin, H. E. A. “Management factors for successful IBS projects implementation.” Procedia-Social

and Behavioral Sciences, 68 (2012): 99-107. Doi: 10.1016/j.sbspro.2012.12.210

10. Kamar, K. A. M., Hamid, Z. A., & Alshawi, M. “The Critical Success Factors (CSFs) to the Implementation of Industrialized Building

System (IBS) in Malaysia.” In Proceedings: TG57-Special Track, 18th CIB World Building Congress, Rotterdam: CIB. (2010).

11. Nawi, M. N. M., Haron, A. T., Hamid, Z. A., Kamar, K. A. M., & Baharuddin, Y. “Improving Integrated Practice through Building

Information Modeling-Integrated Project Delivery (BIM-IPD) for Malaysian Industrialised Building System (IBS) Construction Projects.”

Malaysia Construction Research Journal (MCRJ), 15 no. 2 (2014): 29-38.

12. Nawi, M. N. M., Lee, A., Kamar, K. A. M., & Hamid, Z. A. “A critical literature review on the concept of team integration in

industrialised building System (IBS) project.” Malaysian Construction Research Journal, 9 (2011): 1-17.

13. Nawi, M. N. M., Lee, A., Kamar, K. A. M., & Hamid, Z. A. “Critical success factors for improving team integration in Industrialised

Building System (IBS) construction projects: The Malaysian case.” Malaysian Construction Research Journal, 10 (2012): 44-62.

14. Raquib, M. A. “Analyzing The Concept of Risk and Risk Management to the Formulation of Laws and Regulations and Establishment of

a Legal Framework.” In International Conference on Law and Commerce. 2002.

15. Sew, Ir Dr Gue See, and Ir Tan Yean Chin. “Landslides: Case Histories, Lessons Learned And Mitigation Measures.” Landslide, Sinkhole,

Structure Failure: MYTH or SCIENCE (2006).

16. Turner v Garland and Christopher. Hudson’s Building Contracts, 4th Edition 2 (1853): 1.

97-105

18.

Authors: Azizah Che Omar

Paper Title: Instrument for Measuring the Influencing of iTV Advertising Design Model toward Impulse Purchase

Tendency

Abstract: Conceptual design model of Interactive Television Advertising Toward Influencing Impulse

Purchase Tendency (iTVAdIP) is proposed to provide guideline for advertising designers to develop iTV

advertisements which embed elements that are perceived could influence impulse purchase tendency. Previous

literature studied on the factors of impulse purchase in different advertising mediums like website, mobile,

traditional retail store and traditional television. However, none of the impulse purchase model is dedicated

towards influencing impulse purchase tendency for interactive TV advertising. Therefore, this study focuses on the

influencing measurement of iTVAdIP design model through reliable constructs. These constructs are collected and

formed based on literature study and content analysis. An influencing instrument was developed based on these

constructs and a pilot study was conducted to assess the research feasibility and adequacy of the instrument. The

methods and results of the pilot study are also presented in this paper, indicating that these constructs are valid,

reliable, and practical to be used for measurement of the proposed model.

Keywords: Advertising, Interactive Television, Impulse Purchase, Influencing, Measurement.

References: 1. Interactive Advertising Bureau, IAB. An Interactive Advertising Overview. Retrieved from

http://www.iab.net/media/file/iTVCommitteeWhitePaperv7.pdf, 2011

2. Advertising Forecast Advertising Forecast Magnaglobal. Retrieved from http://www.neoadvertising.com/ch/wp-

content/uploads/2011/06/2011-MAGNAGLOBAL-Advertising-Forecast-Abbreviated.pdf, 2011

3. The Nielsen Company. Global advertising: Consumers trust real friends and virtual strangers the most. Retrieved from

http://blog.nielsen.com/nielsenwire/consumer/global-advertising-consumers- trust-real-friends-and-virtual-strangers-the-most/

4. Azizah, C.O., Norshuhada, S., Siti Mahfuzah, S., Ariffin, A.M., and Sabrina, M.R. “Identification of Research Gap: T-Commerce Impulse

Purchase for iTV advertising”. International Conference on Informatics and Creative Multimedia 2013 (ICICM'13). Kuala Lumpur,

Malaysia. 3-6 September 2013. 119-122. 2013.

5. Siti Mahfuzah, S., Sabrina, M.R., Ariffin, A.M., and Azizah, C.O. Diffusion of iTV advertising in Malaysia: the industry players’

perspectives. International Conference on Informatics and Creative Multimedia 2013 (ICICM'13). Kuala Lumpur, Malaysia. 3-6

106-112

September 2013. 99-103.

6. Azizah, C.O., Norshuhada, S. and Siti Mahfuzah, S. “Impulse Purchase in iTV Advertising: a Conceptual Model of Gap Analysis”.

International Journal of Computer Application, 2014, 91(11), pp. 20-26.

7. Azizah, C.O., Norshuhada, S. and Siti Mahfuzah, S. “Conceptual Design Model of Interactive Television Advertising Towards Impulse

Purchase”. ARPN Journal of Engineering and Applied Sciences. 2015, 10(3): 1427-1437.

8. Azizah, C.O., Norshuhada, S. and Siti Mahfuzah, S. “Conceptual Design Model of Interactive Television Advertising: Experts Review on

Impulse Purchase Tendency”. International Journal of Conceptions on Management and Social Sciences. 2015, 3(2), pp. 40-45.

9. Maes, A., & Poels, G. Evaluating quality of conceptual models based on user perceptions. In D.W.Embey, A. Olive, & S.Ram (Eds.),

Conceptual Modeling ER 2006 (pp. 54-67).Verlag Berlin Heidelberg: Springer International Publishing. 2006, doi: 10.1007/11901181_6

10. Denise, W., Deirdre, R., & Seamus, H. Determining The Influence Of Information Quality And System Quality On The Success Of A

Knowledge Management System Within A Large Multinational Software Organisation, 2009

11. Barclay, C, & Osei B, Kwek M. An Exploratory Evaluation Of Three I.S. Project Performance Measurement Methods. ECIS 2009

Proceedings, 63 .http://aisel.aisnet.org/ecis2009/

12. Riemenschneider, C. K., Hardgrave, B. C., & Davis F. D. Explaining software developer acceptance of methodologies: A comparison of

five theoretical models. IEEE Transactions on Software Engineering, 2002, 28(12), 1135-1145. DOI:10.1109/TSE.2002.1158287

13. Kuan, T, H. Conceptual model of digital storytelling. (Master dissertation, Universiti Utara Malaysia, 2013).

14. Bonner, N. Acceptance of systems development methodologies: Testing a theoretically integrated model. (Doctoral dissertation,

University of Texas Arlington, 2008)

15. Syamsul Bahrin, Z., & Norshuhada, S. Instrument for Measuring the Applicability of Mobile Game-Based Learning Engineering Model,

Journal of Convergence Information Technology (JCIT), 2014, 9(1), 108-116.

16. Kunda, G. A social-technical approach to selecting software supporting COTS-Based Systems. (PhD dissertation, Universiti of York,

2011).

17. Kitchenham B. Evaluating software engineering methods and tool, ACM SIGSOFT software engineering Notes, 1998, 23(5), 21-24.

18. Garrity E. J. and Sanders L. G. Dimensions of Information Systems success In Garrity E. J. and Sanders L. G. (eds.), Information Systems

Success Measurement ,1998, (pp. 13-45). Hershey: Idea Group Publishing (IGP)

19. Kashif, M., & Samira S.C. Evaluating the functionality of conceptual models. In C.A. Heuser & G.Pernul (Eds.), Advances in Conceptual

Modeling - Challenging Perspectives (pp. 222-231). Berlin: Springer Berlin Heidelberg, 2009, doi: 10.1007/978-3-642-04947-7_27

20. Veryard, R. What are methodologies good for data processing, 1985, 27(6), 9-12.

21. Moore, G. C. Benbasat, I. Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation.

Information Systems Research, 1991, 2(3), 192−222

22. Lang, M., & Barry, C. Techniques and methodologies for multimedia systems development: a survey of industrial practice. In N. L.

Russo, et al. (Eds.), Realigning Research and Practice in Information Systems Development, Proceedings of IFIP WG 8.2 Conference,

2001, (pp 77-86). Boston: Kluwer.

23. Guay, F., Vallerand, R.J., & Blanchard, C.M. On the assessment of state intrinsic and extrinsic motivation: The situational motivation

scale (SIMS). Motivation and Emotion, 2000, 24,175–213.

24. Nguyen., Y. L. Factors that Contributing to the Success of DACUM Process Implementation in Technical Vocational School of Post

Telecommunication and Informatics, Vietnam. (Master dissertation, Shu-Te University, 2011).

25. Azizah C O, Shuhada S, Sarif S M, and. Muin M A A. Instrument for measuring the influencing of conceptual design model of ITV

advertising toward impulse purchase. J. Fundam. Appl. Sci., 2018, 10(4S), 977-1002.

26. Sekaran, U., & Bougie, R. (2010). Research Methods for Business: A Skill Building Approach (5th ed). USA: John Wiley & Sons.

27. Sekaran, U. (1992). Research methods for business: a skill-building approach (2nd). USA: John Wiley & Sons.

28. U. Sekaran,(2003). Research methods for business: a skills-building approach, 4th ed, John Wiley & Sons, Inc. USA.

29. J. Pallant, “A step by step guide to data analysis using SPSS”. Open University Press, McGraw-Hill Education, Philadelphia, USA, 2001.

30. Hair, Jr., J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6th ed). USA: Pearson-

Prentice Hall.

19.

Authors: Mohamed Najib Salleh, Halim Mad Lazim, Mohd Nizam Saad

Paper Title: MyMIS: An Appointment System for Outpatient Department

Abstract: This paper had discussed on the development of MyMIS, which is an appointment system for

outpatient department. The main objective of the system is to manage the flow of patients at the department. The

system was developed based on the patients and staffs requirement. MyMIS is generated in the format of

PreHypertext (PHP) and Apache application server was used to run and read the system. MySQL database was

selected to store all the patients and appointment information. The system effectiveness was verified through

ARENA simulation model. Results show the system can reduce significantly waiting time at the outpatient

department. Even though the system is developed for UUM Health Center, it can also be used by other medical

centers as well. It is hope that the system will help government to meet their target of serving patients within 30

minutes.

Keywords: Appointment system, outpatient department, waiting time.

References: 1. J. Kujala, P. Lillrank, V. Kronstöm, A. Peltokorpi, “Time based management of patient processes”, Journal of Health, Organization and

Management Vol. 20, No. 6, 2006, pp. 512-524.

2. Z.C. Zhu, B. H. Heng, and K. L. Teow. "Simulation study of the optimal appointment number for outpatient clinics." International Journal

of Simulation Modelling Vol. 8, No.3, 2009, pp. 156-165.

3. N. Hazilah and P. S. Nooi, “Patient satisfaction as an indicator of service quality”, The Asian Journal of Quality, Vol 10, No. 1, 2009, pp

77-87.

4. M. S. Pillay, et al. "Hospital waiting time: the forgotten premise of healthcare service delivery?." International journal of health care

quality assurance Vol. 24 No. 7, 2011, pp. 506-522.

5. J. O’Brien-Bell, “Doing more with less in the ER”, Medical Post, Vol. 41 No. 1, 2005, pp. 11

6. A.M. Garber, “Corporate treatment for ills of academic medicine”, The New England Journal of Medicine, Vol. 351 No 16, 2005, pp. 197-

201

7. M.N. Salleh, N. Yusof, H. Ali, “Development of an appointment system model for outpatient department in government hospital”,

Proceeding of International Conference on Technology and Operations Management 2010, Langkawi, Malaysia

8. Cao, Wenjun, et al. "A web-based appointment system to reduce waiting for outpatients: A retrospective study." BMC health services

research Vol. 11, No. 1, 2011, pp. 318.

113-119

9. T. Albert and L. Zirimenya, Streamlining patients appointment system at Reach out Mbuya HIV/AIDS Initiative Banda Site, report

prepared and submitted in fulfilment of the requirements of the Mediumterm HIV/AIDS Fellowship Program at Makerere University

School of Public Health.

10. LaGanga, Linda R., and Stephen R. Lawrence. "Clinic overbooking to improve patient access and increase provider

productivity*." Decision Sciences Vol. 38, No 2, 2007, pp. 251-276.

11. Wang, Wen-Ya, and Diwakar Gupta. "Adaptive appointment systems with patient preferences." Manufacturing & Service Operations

Management Vol 13, No. 3, 2011, pp. 373-389.

12. K. E. Kendall & J. E. Kendall, System Analysis and Design (8th). New Jersey: Prentice Hall, 2011.

13. G.B. Shelly & H.J. Rosenblatt, System Analysis and Design (9th). Massachussetts: Course Technology, 2012.

14. A. Cooper, R. Reimann, & D. Cronin, About Face 3: The Essentials of Interaction Design. New York: Wiley, 2007.

15. L. Youn-Kyung, S. Erik, & T. Josh, “The anatomy of prototypes: Prototypes as filters, prototypes as manifestations of design ideas”. ACM

Trans. Comput.-Hum. Interact.2008, 15(2), 1-27.

16. S. R. Nicholson, Dreamweaver MX2004 and Database. Boston: New Riders Publishing, 2004.

20.

Authors: Nur Azzah Abu Bakar, Noraziah ChePa, Mohamad Asad Razali

Paper Title: Requirement Model for MyBazaar Tax: A Mobile Tax Solution for Night Market Hawkers

Abstract: The introduction of e-Filing system by the Malaysian government has been seemed as a solution to

problems that arose due to the use of paper-based income tax filing. The number of taxpayers submitting their

Income Tax Return Forms through e-Filing is increasing every year. However, this does not eliminate the need for

the Inland Revenue Board Malaysia (IRBM) personnel to pay regular visits to the night market venues in order to

assess the eligibility of the night market hawkers to pay tax, and the amount they should be charged. This has been

exacerbated by the practice of the hawkers who do not always keep their business record in a systematic manner;

most still employ traditional way of keeping the amount of their revenue and expenditure in books or pile of

papers. This paper presents the requirement model for MyBazaar Tax, a mobile-based application which is

developed as a single platform for the night market hawkers to keep their business records. At the same time,

MyBazaar Tax apps will also make the process easy for the IRBM personnel to gather tax-related information

from the hawkers. The methodology used in this study consists of four phases: requirement gathering; requirement

modeling; prototyping and evaluation. UML notation is used in modeling the requirements through the use of use

cases, sequence diagram and class diagram. The model presented in this paper could be used as a reference model

for developers in developing similar apps to cater the needs of other small business operators.

Keywords: MyBazaar Tax, e-Filing System, Self-Tax Computation, Mobile Tax Apps.

References: 1. D. Stoilova and N. Patonov, “an Empirical Evidence for the Impact of Taxation on Economy,” vol. 3, no. 27, 2012.

2. T. Santhanamery and T. Ramayah, “Continued Usage Intention of E-Filing System in Malaysia: The Role of Optimism Bias,” Procedia -

Soc. Behav. Sci., vol. 65, no. ICIBSoS, pp. 397–403, 2012.

3. L. E. Chen and Jeyapalan Kasipillai, “Relevant Areas for Research to Gain Insight into Taxation Issues,” MTRF Rep., no. March, pp. 1–

171, 2014.

4. S. Nor’Azimaton, A. Nawawi, and P. S. Ahmad Saiful Azlin, “E-filing Acceptance by the Individual Taxpayers – A Preliminary

Analysis,” J. Adm. Sci., vol. 13, no. 2, pp. 1–14, 2016.

5. MD. Aminul Islam, “Factors Affecting User Satisfaction in the Malaysian Income Tax e-Filing System,” African J. Bus. Manag., vol. 6,

no. 21, pp. 6447–6455, 2012.

6. T. Santhanamery and T. Ramayah, “Understanding the Effect of Demographic and Personality Traits on the E-Filing Continuance Usage

Intention in Malaysia,” Glob. Bus. Rev., vol. 16, no. 1, pp. 1–20, 2015.

7. N. H. Hassan and M. R. Palil, “Faktor Mempengaruhi Masyarakat Menggunakan Perkhidmatan e-Kerajaan : Kajian Terhadap Penggunaan

e-Filing,” Pros. Persidang. Kebangs. Ekon. Malaysia VI (PERKEM VI), vol. 1, pp. 203–210, 2011.

8. D. L. Hoffman, T. P. Novak, and M. Peralta, “Building Consumer Trust Online,” Commun. ACM, vol. 42, no. 4, pp. 80–85, 1999.

9. J. Bowden-Davis, "The 10 Best Mobile Tax Apps to Use This Season," Supermoney, 2016. Retrieved from

https://www.supermoney.com/2014/02/10-mobile-tax-apps/

10. K. Yakal, "The Best Mobile Tax Apps of 2018," PC Magazine Asia, April, 2018. Retrieved from

https://sea.pcmag.com/software/19828/guide/the-best-mobile-tax-apps-of-2018

11. Y. Yukio, "Profiles of Hawkers Working in Rizal Park, Manila, Philippines: Socia-economic Status, Migration Motivations and the Sale

of Goods," Ritsumeikan International Affairs, 10, pp. 303-320, 2011.

12. N. Backhaus, "Managing Diversity: the Management of a Malaysian Hawker Place," Malaysian Management Journal, vol. 19, pp. 65-76,

2015.

120-126

21.

Authors: Mohd Nizam Omar, Ali Yusny Daud, Osman Ghazali

Paper Title: A Stepping Stone Perspective to Detection of Network Threats: Spam Detection

Abstract: This paper examines one of the novel applications of the concept of stepping stone detection to address

network threats known as spam. Previous research has been identified in several applications such as spam,

backdoors, intrusions of proxy servers and denial of service attacks as a possible solution that can be solved by

using a stepping stone perspective against network threats. In this paper, an experiment has been conducted as to

proof two formulas that generated to solve spam problem. Through the control environment and the development

of special prototype to detect spam, the result shows that both formulas in detecting spam attack can be used to

detect spam successfully. The successful result of the experiment proofs that one of the identified application

really works in the real experiment testbed. By producing another solution to detect spam in this research hopefully

can contribute another solution to detect a spam problem.

Keywords: Stepping stone, SSD, SPAM, DoS attacks

127-132

References: 1. S. Staniford-Chen and L.T. Herberlein, “Holding Intruders Accountable on the Internet”, Proc. 1995 IEEE Symposium on Security and

Privacy, 1995, pp. 39-49.

2. S. Robert, C. Jie, J. Ping and C. Weifeng, “A Survey of Research in Stepping Stone Detection”, International Journal of Electronic

Commerce Studies”, Vol. 2, No. 2, pp. 103 – 126, 2001.

3. Y. Zhang and V. Paxson, “Detecting Stepping Stones”, Proc. 9th USENIX Security Symposium, 2000, pp. 67-81.

4. L. Zhang, A. G. Persaud, A. Johson, Y. Guan, “Stepping Stone Attack Attribution in Non-Cooperative IP Networks”, in Proc. Of the 25th

IEEE International Performance Computing and Conference (IPCCC 2006), 2006.

5. J. Yang, and S.S. Huang, “Matching TCP/IP to Detect Stepping-Stone Intrusion”, International Journal of Computer Science and Network

Security (IJCSNS), vol. 6, no. 10, Oct. 2006, pp. 269-276.

6. K. Yoda and H. Etoh, “Finding Connection Chain for Tracing Intruders”, Proc. 6th European Symposium on Research in Computer

Security (LNCS 1985), 2000, pp. 31-42.

7. J. Yang, and S.S. Huang, “Matching TCP/IP to Detect Stepping-Stone Intrusion”, International Journal of Computer Science and Network

Security (IJCSNS), vol. 6, no. 10, Oct. 2006, pp. 269-276.

8. D.L. Donoho, A.G. Flesia, U. Shankar, V. Paxson, J. Coit, and S. Staniford, “Multiscale stepping-stone detection: Detecting pairs of

jittered interactive streams by exploiting maximum tolerable delay”, Proc. 5th International Symposium on Recent Advances in Intrusion

Detection (RAID 2002), 2002, pp. 49-64

9. X. Wang, D.S. Reeves, and S.F. Wu, “Inter-packet delay based correlation for tracing encrypted connection through stepping stone”, Proc.

7th European Symposium on Research in Computer Security (ESORICS 2002), 2002, pp. 244-263.

10. Y. Jianhua, and S.S. Huang, “A Real-Time Algorithm to Detect Long Connection Chains of Interactive Terminal Session”, Proc. 3rd

International Conference on Information Security (Infosecu ‘04), 2004, pp. 198 – 203.

11. S. Jianhua, J. Hai, C. Hao and H. Zong-Fen, MA-IDS: A Distributed Intrusion Detection System Based on Data Mining, Wuhan

University Jornal of Natural Science (WUJNS), 10(1), pp. 111-114.

12. W. T. Strayer, C. E. Jones, I. Castineyra, J. B Levin and R. R Hain, “An Integrated architecture for attack attribution”, BBN Technologies,

Technical Report. BBN REPORT-8384, 2003.

13. A. Blum, D. Song, and S. Benkataraman, “Detection of Interactive Stepping Stone: Algorithm and Confidence Bounds”, Lecture Notes in

Computer Science, Springer Berlin / Heidelberg, Volume 3224/2004, pg. 258-277, October 1, 2004.

14. A. Almulhem and I. Traore, “A Survey of Connection-chains Detection Technique”, 2007IEEE Pacific Rim Conference on

Communications, Computers and Signal Processing, Victoria, B. C, Canada, 22 – 24 August 2007, pp. 219 – 222.

15. X. Jianqiang, Z Lingeng, B. Aswegan, D. Daniels, J. T. Y. Guan,. (2006) A Testbed for Evaluation and Analysis of Stepping Stone Attack

Attribution Techniques. Proc. 2nd International Conference on Testbeds and Research Infrastructures for the Development of Networks

and Communities (TRIDENTCOM 2006), 1-3 March 2006, Barcelona, Spain, pp. 369-379.

16. M. Venkateshaiah, “Evading Existing Stepping Stone Detection Methods”, Master Thesis, University of Texas at Arlington, December

2006.

17. A. Almulhem, Detection and Analysis of Connection Chains in Network Forensics, Ph.D. Dissertation, Department of Electrical and

Computer Engineering, University of Victoria, Canada.

18. H. Wu, and S., S. Huang, Stepping Stone Intrusion Detection Using Neural Network Approach, Novel Algorithm and Techniques in

Telecommunications, Automation and Industrial Electronics, pp. 358-363.

19. M. Venkateshaiah, and M. Wright, Evading Stepping Stone Detection Under the Cloak of Streaming Media, Technical Report,

Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, 2007.

20. J. Yang, and S. S. Huang and D. W. Ming. A Clustering-Partitioning Algorithm to Find TCP Packet Round-Trip Time for Intrusion

Detection, Proceeding of 20th International Conference on Advanced Information Networking and Applications (AINA 2009), Bradford,

UK, pp. 231-236.

21. J. Yang, and S. S. Huang, S. S. Mining TCP/IP packet to detect stepping-stone intrusion. Computer & Security, 26(7-8), pp.479-484.

22. H. Wu, and S. S. Huang. Neural Network-based Detection of Stepping Stone Intrusion. Expert Systems with Applications, 32(2), pp.1431-

1437.

23. A. Almulhem and I. Traore. Detecting Connection-Chains: A Data Mining Approach, International Journal of Network Security, 10(1),

pp.62–74.

24. J. Yang and S. S. Huang. A Real-Time Algorithm to Detect Long Connection Chains of Interactive Terminal Session. Proceeding of The

3rd International Conference on Information Security (InfoSecu04). 14-16 November 2004, Shanghai, China, pp. 198-203.

25. J. Yang and S. S. Huang. Matching TCP Packets and Its Application to the Detection of Long Connection Chains on the Internet. The 19th

International Conference on Advanced Information Networking and Application (AINA 05), 28-30 March 2005, Taipei, Taiwan, pp.1005-

1010.

26. X. Wang and D. S. Reeves. Robust correlation of encrypted attack traffic through stepping stones by manipulation of interpacket delays,

The 10th ACM Conference on Computer and Communication Security (CCS 2003), 27-30 October 2003, Washington D.C., USA, pp. 20-

29.

27. B. Whitworth and E. Whitworth, "Spam and the social-technical gap," Computer, vol. 37, pp. 38-45, 2004.

28. M. Sahami, S. Dumais, D. Heckerman, and E. Horvitz, "A Bayesian Approach to Filtering Junk E-Mail," in Learning for Text

Categorization: Papers from the 1998 Workshop, 1998.

29. D. D'Ambra, "Killer spam: clawing at your door", Inf. Prof. 4, vol. 28, no. 4, 2007.

30. Z. Le, Z. Jing and Y. Tianshun, "An Evaluation of Statistical Spam Filtering Techinques", ACM Transactions on Asian Language

Information Processing (TALIP) vol. 3, 2004, pp. 243-269.

31. M.N. Marsono, M. Watheq, and F. Gebali, "Binary LNS-based naïve Bayes inference engine for spam control: noise analysis and FPGA

implementation", IET Comput. Digit. Tech, vol. 56, no. 2, 2008.

32. O. O. Abiona, T. Anjali, L. O. Kehinde, "Simulation of a cyclic multicast proxy server," IEEE International Conference on

Electro/Information Technology, 2008. EIT 2008., vol., no., pp.102-107, 18-20 May 2008

33. O. Angela, R. Gibert, B. Jay and W. Joshua. Wireshark & Ethereal Network Protocol Analyzer Toolkit (Jay Beale's Open Source

Security), Syngress Publishing, Inc., 800 Hingham Street, Rockland, MA 02370.

34. R. Chetan and D. V. Ashoka, "Data mining based network intrusion detection system: A database centric approach," Computer

Communication and Informatics (ICCCI), 2012 International Conference on , vol., no., pp.1-6, 10-12 Jan. 2012

35. F. Desheng, Z. Shu and G. Ping, "The Design and Implementation of a Distributed Network Intrusion Detection System Based on Data

Mining," Software Engineering, 2009. WCSE '09. WRI, World Congress on,Vol. 3, no., pp. 446-450, 19-21 May 2009

36. L. Lei, Y. De-Zhang and S. Fang-Cheng, "A novel rule-based Intrusion Detection System using data mining," Computer Science and

Information Technology (ICCSIT), 2010 3rd IEEE International Conference on,Vol. 6, no., pp. 169-172, 9-11 July 2010

37. H. Agrawal, J. Alberi, L. Bahler, W. Conner, J. Micallef, A. Virodov, S. R. Snyder, "Preventing insider malware threats using program

analysis techniques," MILITARY COMMUNICATIONS CONFERENCE, 2010 - MILCOM 2010, vol., no., pp. 936-941, Oct. 31 2010-

Nov. 3 2010

38. S. Rahul, “Effectiveness of Antivirus in Detecting Web Application Backdoors”, retrieved from

http://www.chmag.in/article/feb2011/effectiveness-antivirus-detecting-web-application-backdoors, July 30, 2012.

39. Fang-Yie Leu; Zhi-Yang Li; "Detecting DoS and DDoS Attacks by Using an Intrusion Detection and Remote Prevention System,"

Information Assurance and Security, 2009. IAS '09. Fifth International Conference on,Vol. 2, no., pp. 251-254, 18-20 Aug. 2009

40. Mehdi Ebady Manna, Angela Amphawan; “Review of SYN-flooding attack detection mechanism”, International Journal of Distributed

and Parallel Systems (IJDPS) Vol.3, No.1, pp. 99-117, January 2012

41. Salah, K.; Sattar, K.; Sqalli, M.; Al-Shaer, E.; , "A probing technique for discovering last-matching rules of a network firewall,"

Innovations in Information Technology, 2008. IIT 2008. International Conference on, vol., no., pp. 578-582, 16-18 Dec. 2008

42. Bose, S.; Kannan, A. , "Detecting Denial of Service Attacks using Cross Layer based Intrusion Detection System in Wireless Ad Hoc

Networks," International Conference on Signal Processing, Communications and Networking, 2008. ICSCN '08., vol., no., pp.182-188, 4-

6 Jan. 2008.

43. Jin Li; Yong Liu; Lin Gu; , "DDoS attack detection based on neural network," Aware Computing (ISAC), 2010 2nd International

Symposium on , vol., no., pp.196-199, 1-4 Nov. 2010.

22.

Authors: Mazni Omar, Abdulkadir Osman Mohamed

Paper Title: A Requirements Modeling for E-Learning Management System (eLMS)

Abstract: Nowadays, technology simplifies the learning process and assists in the communication between

learners, lecturers, and administrators of universities and other educational organisations. At present, most of the

universities in Somalia still use the face-to-face teaching approach and lecturers do not have an electronic

repository for the learning materials. This demonstrates that an e-Learning model that is able to fulfil the users’

requirements is lacking. This shortcoming is addressed in this study by developing a requirements model for an e-

Learning Management System (eLMS) to improve the quality of the learning process. To achieve this objective, a

design research methodology was adopted. During the modelling process, the Web Application Extension (WAE)

for the Unified Modeling Language (UML) model was used to design the requirements model for the proposed

eLMS. The significance of this model is that it facilitates the interaction between students, lecturers, and

administrators, thus enhancing the learning process at the university. In addition, the proposed model will be a

useful reference for other researchers working in a similar domain, or for developers who are interested in

developing similar models. Additionally, the expected output of this research is the eLMS system that will enable

students, lecturers, and administrators to communicate with each other.

Keywords: e-Learning Management System (eLMS); Requirement Engineering; Unified Modeling

Language(UML); Web Application Extension(WAE); Learning Management System(LMS)

References: 1. M. Ajmal, "Implementation of Quality Assurance and Accreditation Policy in Open Distance Learning Teacher Education Programs in

Pakistan," Journal of Contemporary Teacher Education, vol. 1, pp. 67-78, 2017.

2. H. Richard, and A. Haya, A, "Examining student decision to adopt web 2.0 technologies: theory and empirical tests," Journal of

computing in higher education, vol., pp. 183-198, 2009.

3. M. Prensky, "Digital natives, digital immigrants," On the horizon (NCB University Press), vol. 9, pp. 1-6, 2001.

4. S. Banerjee and S. Karforma, "Object oriented modeling for authentication of certificate in e-learning using digital watermarking,"

International Journal of Advanced Research in Computer Science, vol. 8, pp. 54-57, 2017.

5. E. Syrtsova, O. Tokmakova, I. Merkulova, and O. Sinitsyna, "E-Learning System Development in Accordance with the Requirements of

EFQUEL: Vyatka State University Experience," International Journal for Quality Research, vol. 11, pp. 379-396, 2017.

6. C. Goumopoulos, P. Nicopolitidis, D. Gavalas, and A. Kameas, "A distance learning curriculum on pervasive computing," International

Journal of Continuing Engineering Education and Life Long Learning, vol. 27, pp. 122-146, 2017.

7. S.K. Pande, "Enhancing Learning Opportunities Through Development of Open and Distance Education in Africa,“ Optimizing Open and

Distance Learning in Higher Education Institutions, vol. 71, 2017.

8. A. Almohammad, J. F. Ferreira, A. Mendes, and P. White, "Hierarchical Requirements Modeling and Test Generation for Industrial

Control Systems," in 4th International Workshop on Requirements Engineering and Testing (RET17), Lisbon, Portugal, 2017, pp. 351-

358.

9. A. Vegendla, A. N. Duc, S. Gao, and G. Sindre, "A Systematic Mapping Study on Requirements Engineering in Software Ecosystems,"

Journal of Information Technology Research (JITR), vol. 11, pp. 49-69, 2018.

10. S. D. Axinte, G. Petrica, and I.-D. Barbu, "E-learning platform development model," in 2017 10th International Symposium on Advanced

Topics in Electrical Engineering (ATEE), Bucharest, Romania 2017, pp. 687-692.

11. D. Barker, "Requirements modeling technology: A vision for better, faster, and cheaper systems," in VHDL International Users Forum

Fall Workshop, Orlando, Florida, 2000, pp. 3-6.

12. S. Chumpia, "Requirement Model for Hatyai Technical College Social Network Learning Site," Masters thesis, College of Arts and

Sciences, Universiti Utara Malaysia, Malaysia, 2011.

13. J. Badriyah, "Requirement Model for Storing and Retrieving ISO Document: Teaching and Learning Process," Master thesis, Faculty of

Information Technology, Universiti Utara Malaysia, Malaysia, 2004.

14. Rizal, "A Generic Requirement Model for E-Learning Management System," Masters thesis, College of Arts and Sciences, Universiti

Utara Malaysia, Malaysia, 2010.

15. A. Aljumaah, "Modeling students acceptance of E-learning: A case of the KS university," in 2010 Fifth International Conference on

Digital Information Management (ICDIM), Ontario, Canada, 2010, pp. 460-464.

16. J. Rubagiza, E. Were, and R. Sutherland, "Introducing ICT into schools in Rwanda: Educational challenges and opportunities,"

International Journal of Educational Development, vol. 31, pp. 37-43, 2011.

17. A. A. Abdisamed, "E-Learning Management System for Simad University in Somalia," Masters thesis, College of Arts and Sciences,

Universiti Utara Malaysia, Malaysia, 2011.

18. N. M. Nor, "A requirements model for employees training management system: applying WAE-UML," in International Conference on

Information Management and Engineering 2009 (ICIME'09), Kuala Lumpur, Malaysia, 2009, pp. 569-573.

19. M. Brumbulli, B. Topçiu, and A. Dalaçi, "SMIS: A Web-Based school management information system," in International Scientific

Conference Computer Science, Kavala, Greece, 2008, pp. 564-569.

20. G. O. Ouma, F. M. Awuor, and B. Kyambo, "E-Learning Readiness in Public Secondary Schools in Kenya," European Journal of Open,

Distance and E-learning, vol. 16, pp. 97-110, 2013.

21. D. Xanthidis, S. W. Wali, and P. Nikolaidis, "E-Learning in Saudi Universities, Challenges and Issues," in 2013 Fourth International

Conference on e-Learning" Best Practices in Management, Design and Development of e-Courses: Standards of Excellence and

Creativity", Manama, Bahrain, 2013, pp. 473-478.

22. W. Titthasiri, "A Comparison of E-Learning and Traditional Learning: Experimental Approach," in International Conference on Mobile

133-142

Learning, E-Society and E-LearningTechnology (ICMLEET), Singapore, 2013, pp. 67-74.

23. P. Behar, "Constructing pedagogical models for e-learning," International Journal of Advanced Corporate Learning (iJAC), vol. 4, pp.

16-22, 2011.

24. H. S. Al-Khalifa, "A first step in evaluating the usability of Jusur learning management system," presented at the 3rd Annual Forum on e-

Learning Excellence in the Middle East 2010: Bringing Global Quality to a Local Context, Dubai, U.A.E., 2010.

25. National Centre for e-learning and Distance Learning: JUSUR LMS System", (2009, Dec. 05). [Online]. Accessed on: Nov. 3, 2017.

Available: http://www.elc.edu.sa/portal/index.php?mod=content&page=27

26. H. S. Al-Khalifa, "E-learning in Saudi Arabia," in E-Learning Practices, Cases on Challenges Facing E-Learning and National

Development: Institutional Studies and Practices vol. 1, U. Demiray, Ed., ed Eskisehir, Turkey Anadolu University, 2010, pp. 745-772.

27. O. I. Al-Salum, (2009, August. ). Deficiencies in the Jusur Learning Management System, Information Technology. Accessed on Sept.

28, 2017. [Online]. Available: http://www.alriyadh.com/450962

28. G. Kariuki, "Growth and improvement of information communication technology in Kenya," International Journal of Education and

Development using ICT, vol. 5, pp. 146-160, 2009.

29. M. Waema, "A brief history of the development of an ICT policy in Kenya," At the Crossroads: ICT policy making in East Africa, pp. 25-

43, 2005.

30. Constitution of Kenya, "A Policy Framework for Education and Training: Reforming Education and Training in Kenya.," vol. 35, The

Ministry of Education Science and Technology, Ed., ed, 2012, pp. 1-7.

31. J. Zake. (2009, April. ). Challenges to e-learning in developing communities of Africa. Accessed on Aug. 28, 2014. [Online]. Available:

http://ernwaca.org/panaf/spip.php?article676

32. G. Ssekakubo, H. Suleman, and G. Marsden, "Issues of adoption: have e-learning management systems fulfilled their potential in

developing countries?," in Proceedings of the South African Institute of Computer Scientists and Information Technologists conference on

knowledge, innovation and leadership in a diverse, multidisciplinary environment, Cap Town, South Africa, 2011, pp. 231-238.

33. G. N. Sammour, "Elearning Systems Based on the Semantic Web," International Journal of Emerging Technologies in Learning (iJET),

vol. 1, pp. 1-7, 2006.

23.

Authors: Ali Yusny Daud, Osman Ghazali, Mohd Nizam Omar

Paper Title: Stepping Stone Detection: Measuring the SSD Capability

Abstract: The performance of Stepping Stone Detection (SSD) is measured by the accuracy to detect attacks

that were initiated using stepping-stone hosts. The pattern of the attacks needs to be recognized to implement the

detection. To evaluate the SSD, a variation of metrics have been used by many researchers but a benchmark should

be introduced in calculating the measures. In this paper, we review the approaches used in evaluating the SSD and

proposed the beneficial insights metrics in evaluating the effectiveness of SSD.

Keywords: Stepping Stones, Intrusion, False Negative Rates, False Positive Rates, Percentage of Success.

References: 1. Z. Lu and Y. Zhou, “The Evaluation Model for Network Security,” in 2014 Fourth International Conference on Communication Systems

and Network Technologies, 2014, pp. 690–694.

2. S. H. S. Huang, H. Zhang, and M. Phay, “Detecting stepping-stone intruders by identifying crossover packets in SSH connections,” in

Proceedings of the International Conference on Advanced Information Networking and Applications (AINA), 2016, pp. 1043–1050.

3. J. Yang, Y. Zhang, and G. Zhao, “Integrate stepping-stone intrusion detection technique into cybersecurity curriculum,” Proc. 31st IEEE

Int. Conf. Adv. Inf. Netw. Appl. Work. WAINA 2017, pp. 1–6, 2017.

4. S. Staniford-Chen and L. T. Heberlein, “Holding intruders accountable on the internet,” in Security and Privacy, 1995, 1995, pp. 39–49.

5. O. Al-Jarrah and A. Arafat, “Network Intrusion Detection System using Attack Behavior Classification,” 2014 5th Int. Conf. Inf.

Commun. Syst. ICICS 2014. IEEE Comput. Soc. https//doi.org/10.1109/IACS.2014.6841978, 2014.

6. S. Anwar, J. M. Zain, M. F. Zolkipli, Z. Inayat, A. N. Jabir, and J. B. Odili, “Response option for attacks detected by intrusion detection

system,” in 2015 4th International Conference on Software Engineering and Computer Systems, ICSECS 2015: Virtuous Software

Solutions for Big Data, 2015, pp. 195–200.

7. S. Anwar et al., “From intrusion detection to an intrusion response system: Fundamentals, requirements, and future directions,”

Algorithms, vol. 10, no. 2, 2017.

8. G. Gu, P. Fogla, D. Dagon, W. Lee, and B. Skorić, “Measuring intrusion detection capability: An information-theoretic approach,” in

Proceedings of the 2006 ACM Symposium on Information, computer and communications security, 2006, pp. 90–101.

9. G. Kumar, “Evaluation Metrics for Intrusion Detection Systems - A Study,” Int. J. Comput. Sci. Mob. Appl., vol. 2, no. 11, pp. 11–17,

2014.

10. R. Mitchell and I. Chen, “A Survey of Intrusion Detection Techniques for Cyber-Physical Systems,” ACM Comput. Surv., vol. 46, no. 4,

p. 55:1-29, 2014.

11. R. Zuech, T. M. Khoshgoftaar, and R. Wald, “Intrusion detection and Big Heterogeneous Data: a Survey,” J. Big Data, vol. 2, no. 1, 2015.

12. R. Kumar and B. B. Gupta, “Stepping stone detection techniques: Classification and state-of-the-art,” in Proceedings of the international

conference on recent cognizance in wireless communication & image processing, 2016, pp. 523–533.

13. A. Kampasi, Y. Zhang, G. Di Crescenzo, A. Ghosh, and R. Talpade, “Improving stepping stone detection algorithms using anomaly

detection techniques,” Rep. TR-07-28 (regular report), no. The University of Texas at Austin, 2007.

14. G. Di Crescenzo, A. Ghosh, A. Kampasi, R. Talpade, and Y. Zhang, “Detecting anomalies in active insider stepping stone attacks,” J.

Wirel. Mob. Networks, Ubiquitous Comput. Dependable Appl., vol. 2, no. 1, pp. 103–120, 2011.

143-146

24.

Authors: Ali Yusny Daud, Osman Ghazali, Mohd Nizam Omar, Dahliyusmanto, Devi Willieam Anggara

Paper Title: A Study on the Performance Metrics for Evaluating Stepping Stone Detection (SSD)

Abstract: A good SSD managed to detect attacks that were initiated using stepping-stone hosts with high

accuracy. In evaluating the SSD, various metrics have been used by many researchers but a benchmark should be

introduced in calculating the measures. The performance metrics are used to evaluate Stepping Stone Detection

(SSD) to recognize the best configurations or which SSD is better. The stepping stone attacks have pattern that

needs to be recognized for the detection to be successful. In this paper, we analyze the approaches used in

evaluating the SSD and suggested the beneficial insights metrics in evaluating the effectiveness or the accuracy of

the SSD.

147-149

Keywords: SSD, SSD Evaluation, FNR, FPR.

References: 1. Z. Lu and Y. Zhou, “The Evaluation Model for Network Security,” in 2014 Fourth International Conference on Communication Systems

and Network Technologies, 2014, pp. 690–694.

2. S. H. S. Huang, H. Zhang, and M. Phay, “Detecting stepping-stone intruders by identifying crossover packets in SSH connections,” in

Proceedings of the International Conference on Advanced Information Networking and Applications (AINA), 2016, pp. 1043–1050.

3. M. B. James Temperton, “The security flaws at the heart of the Panama Papers,” wired.co.uk, 2016.

4. R. Kumar and B. B. Gupta, “Stepping stone detection techniques: Classification and state-of-the-art,” in Proceedings of the international

conference on recent cognizance in wireless communication & image processing, 2016, pp. 523–533.

5. S. Staniford-Chen and L. T. Heberlein, “Holding intruders accountable on the internet,” in Security and Privacy, 1995, 1995, pp. 39–49.

6. J. Yang, Y. Zhang, and G. Zhao, “Integrate stepping-stone intrusion detection technique into cybersecurity curriculum,” Proc. 31st IEEE

Int. Conf. Adv. Inf. Netw. Appl. Work. WAINA 2017, pp. 1–6, 2017.

7. S. Anwar, J. M. Zain, M. F. Zolkipli, Z. Inayat, A. N. Jabir, and J. B. Odili, “Response option for attacks detected by intrusion detection

system,” in 2015 4th International Conference on Software Engineering and Computer Systems, ICSECS 2015: Virtuous Software

Solutions for Big Data, 2015, pp. 195–200.

8. S. Anwar et al., “From intrusion detection to an intrusion response system: Fundamentals, requirements, and future directions,”

Algorithms, vol. 10, no. 2, 2017.

9. G. Gu, P. Fogla, D. Dagon, W. Lee, and B. Skorić, “Measuring intrusion detection capability: An information-theoretic approach,” in

Proceedings of the 2006 ACM Symposium on Information, computer and communications security, 2006, pp. 90–101.

10. R. Mitchell and I. Chen, “A Survey of Intrusion Detection Techniques for Cyber-Physical Systems,” ACM Comput. Surv., vol. 46, no. 4,

p. 55:1-29, 2014.

11. A. Kampasi, Y. Zhang, G. Di Crescenzo, A. Ghosh, and R. Talpade, “Improving stepping stone detection algorithms using anomaly

detection techniques,” Rep. TR-07-28 (regular report), no. The University of Texas at Austin, 2007.

12. G. Di Crescenzo, A. Ghosh, A. Kampasi, R. Talpade, and Y. Zhang, “Detecting anomalies in active insider stepping stone attacks,” J.

Wirel. Mob. Networks, Ubiquitous Comput. Dependable Appl., vol. 2, no. 1, pp. 103–120, 2011.

25.

Authors: Rizinoor Che Mat, Gonesh Chandra Saha

Paper Title: Exploring the potential of web based 3D visualization of GIS data in Coconut plantation management

Abstract: Coconut is one of the main agricultural plantation crops in many countries and known as “tree of

life”. Coconut is universally facing major challenges due to poor agricultural practices and farm management,

especially in the northern part of Malaysia. The objective of this paper is to explore the potential for web-based 3D

visualization of GIS data in the management of coconut planting in terms of problems and issues. The data

collected from a field observation will be used in this study as the source of primary data for the planting of

coconut. Other than that, by interviewing with coconut palm manager, the problems and issues of managing

coconut plantation were gathered. The results showed that the main problems for the introduction of new

technologies could be highlighted due to the problem of manual cultivation practices and the lack of proper

management practices. Besides that, lack of awareness of the farmers regarding the potential of the new

technologies which could be utilised for managing and monitoring coconut plantation. The results of this study

may help to identify the appropriate problem and problems in the implementation of web-based 3D visualization of

GIS data for the management of coconut planting.

Keywords: 3D Visualization, Coconut, Plantation Management, GIS, problems.

References: 1. Naik, J Nehru, “Growth Trends in Area, Production and Productivity of Coconut in Major Growing Countries.” IOSR Journal of

Humanities And Social Science vol. 22, no. 12, pp. 47–56, 2017.https://doi.org/10.9790/0837-2209124756.

2. Obiniyi, Afolayan, “A Web-Based Farm 3D Visualization Management System.” Journal of Computer Science & Systems Biology, vol.

8, no. 1, pp. 49–54,2015. https://doi.org/10.4172/jcsb.1000170.

3. Yoshida, Koshi, Kenji Tanaka, RyunosukeHariya, IssakuAzechi, Toshiaki Iida, Shigeya Maeda, and HisaoKuroda, “Contribution of ICT

monitoring system in agricultural water management and environmental conservation”. In Serviceology for Designing the Future,

Springer, Tokyo, Japan, 359–369,2016.

4. Huang, Yan Bo, Steven J. Thomson, W. Clint Hoffmann, Yu Bin Lan, and Bradley K. Fritz, “Development and Prospect of Unmanned

Aerial Vehicle Technologies for Agricultural Production Management.” International Journal of Agricultural and Biological Engineering

vol. 6, no.3, pp. 1–10,2013. https://doi.org/10.3965/j.ijabe.20130603.001.

5. Mat, Ruzinoor Che, Norani Nordin, Abdul Nasir Zulkifli, and Shahrul Azmi Mohd Yusof, “Suitability of Online 3D Visualization

Technique in Oil Palm Plantation Management.” In AIP Conference Proceedings 1761, pp. 1–5,2016. https://doi.org/10.1063/1.4960871.

6. Mbaluka, Damaris, and George Okeyo. “Application of Geographical Information System ( GIS ) and Mobile Application in Livestock

Disease Management in Developing Countries.” International Journal of Science and Research (IJSR) vol. 5, no. 11, pp. 183–88. ,2016.

https://doi.org/10.21275/ART20162668.

7. ESRI, “GIS Solution for Agriculture.” Retrieved from http://www.esri.com/library/brochures/pdfs/gis-sols-for-agriculture.pdf on

09.09.17.

8. Brion, Jewarde D, and Francis F Balahadia, “Application of Remote Sensing and GIS for Climate Change and Agriculture in

Philippines.”,2017.

9. Johnson S, Yespolov T (2013). The role of Extension system and GIS Technology in formation and Predicting Global Agricultural Policy:

Precision Agriculture in Coming Fast, International Scientific Electronic Journal 4:1-12.

10. Hada, Edyta, “GIS SYSTEM FOR 3D VISUALIZATION OF HYDRODYNAMIC MODELING OF FLOOD FLOWS IN RIVER

VALLEYS ISOK - IT SYSTEM OF COUNTRY PROTECTION AGAINST EXTREME HAZARDS FLOOD MODELLING AND

VISUALIZATION Hydrodynamic Modeling,” 1–5,2014.

11. Al-Rawabdeh, Abdulla, Nadhir Al-Ansari, Hussain Attya, and Sven Knutsson, “GIS Applications for Building 3D Campus, Utilities and

Implementation Mapping Aspects for University Planning Purposes.” Journal of Civil Engineering and Architecture,vol.8,no. 74, pp. 19–

28,2014.https://doi.org/10.17265/1934-7359/2014.01.003.

12. Kumar, Vikas, and Vishal Dave, “KrishiMantra : Agricultural Recommendation System ∗ Categories and Subject Descriptors.”,2013.

13. Bröring, Arne, David Vial, and Thorsten Reitz.,“Processing Real-Time Sensor Data Streams for 3D Web Visualization.” In Proceedings

of the 5th ACM SIGSPATIAL International Workshop on GeoStreaming- IWGS’14, no. November: 72–80, 2014,

150-156

https://doi.org/10.1145/2676552.2676556.

14. Kemec, S, and S Duzgun, “3D Visualization for Urban Earthquake Risk.” Geohazards, ECI Symposium Series P07, 2006.

http://dc.engconfintl.org/geohazards/37/.

15. Herman, L., and T. Řezník, “3D Web Visualization of Environmental Information - Integration of Heterogeneous Data Sources When

Providing Navigation and Interaction.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences -

ISPRS Archives 40 (3W3), pp. 479–85. https://doi.org/10.5194/isprsarchives-XL-3-W3-479-2015.

16. Bareth, Georg, “3D Data Acquisition to Monitor Cropping Systems : Sensors and Methods,” pp. 85–91,2015.

17. Mocanu, Mariana, Valentin Cristea, CatalinNegru, Florin Pop, Vlad Ciobanu, and CiprianDobre, “Cloud-Based Architecture for Farm

Management.” In Proceedings - 2015 20th International Conference on Control Systems and Computer Science, CSCS 2015, pp. 814–19.

https://doi.org/10.1109/CSCS.2015.55.

18. Liang, Jianming, Jianhua Gong, Jieping Zhou, Abdoul Nasser Ibrahim, and Ming Li, “An Open-Source 3D Solar Radiation Model

Integrated with a 3D Geographic Information System.” Environmental Modelling & Software vol. 64, pp. 94–101, 2015

https://doi.org/10.1016/j.envsoft.2014.11.019.

19. Ying, Shen, RenzhongGuo, Lin Li, and Biao He, “Application of 3D GIS to 3D Cadastre in Urban Environment.” In Proceedings of the

3rd International Workshop on 3D Cadastres: Developments and Practices, no. October: 253–72,2012.

20. Jain, Yash, Amita Sharma, and Sanjay Chaudhary, “Spatial Analysis For Generating Recommendations For Agricultural Crop

Production.”, 2012.

21. Dinkov, Davis, RumianaVatsevaEng Davis Dinkov, and RumianaVatseva, “3D Modelling and Visualization for Landscape Simulation,”

no. June: 13–17, 2016. https://cartography-gis.com/docsbca/iccgis2016/ICCGIS2016-33.pdf.

22. Junge, B., T. Alabi, K. Sonder, S. Marcus, R. Abaidoo, D. Chikoye, and K. Stahr. 2010. Use of Remote Sensing and Gis for Improved

Natural Resources Management: Case Study from Different Agroecological Zones of West Africa. International Journal of Remote

Sensing 31 (23): 6115–41. https://doi.org/10.1080/01431160903376415.

23. Yusoff, Noryusdiana Mohamad, Farrah Melissa Muharam, and Siti Khairunniza-Bejo, “Towards the Use of Remote-Sensing Data for

Monitoring of Abandoned Oil Palm Lands in Malaysia: A Semi-Automatic Approach”. International Journal of Remote Sensing, vol. 38,

no.2, pp. 432–49, 2017. https://doi.org/10.1080/01431161.2016.1266111.

24. Miao, Ru, Jia Song, and Yunqiang Zhu, “3D Geographic Scenes Visualization Based on WebGL.” 2017 6th International Conference on

Agro-Geoinformatics, Agro-Geoinformatics2017. https://doi.org/10.1109/Agro-Geoinformatics.2017.8046999.

25. Mat, Ruzinoor Che, Abdul Rashid Mohamed Shariff, Biswajeet Pradhan, Ahmad Rodzi Mahmud, and Mohd Shafry Mohd Rahim “An

Effective Visualization and Comparison of Online Terrain Draped with Multi-Sensor Satellite Images.” Arabian Journal of Geosciences,

vol. 6 no. 12, pp.4881–89, 2013.https://doi.org/10.1007/s12517-012-0722-3.

26. Ruzinoor CM, Shariff ARM, Mahmud AR, Pradhan B, Rahim MSM, “Development of Online 3D Terrain for Oil Palm Plantation.” In:

World Engineering Congress (WEC 2010), Kuching Sarawak, Malaysia.

27. Ruzinoor, C. M., A. R M Shariff, A. R. Mahmud, and B. Pradhan, “Online 3D Terrain Visualization: Implementation and Testing.”

Journal of Applied Sciences, 2011. https://doi.org/10.3923/jas.2011.3247.3257.

28. Adam, H., Collin, M., Richaud, F., Beulé, T., Cros, D., Omoré, A., Nodichao, L., Nouy, B. and Tregear, J.W., “Environmental regulation

of sex determination in oil palm: current knowledge and insights from other species”. Annals of botany, vol. 108, no. 8, pp.1529-

1537,2011.

29. Ruzinoor C M and M Mohd Hafiz, "Using game engine for online 3D terrain visualization withoil palm tree data," Journal of

Telecommunication, Electronic and Computer Engineering,vol. 10, p. 93-97, 2018.

26.

Authors: Sook-Chin Chew, Choon-Hui Tan, Liew-Phing Pui, Pei-Nee Chong, Baskaran Gunasekaran, Nyam Kar

Lin

Paper Title: Encapsulation Technologies: A Tool for Functional Foods Development

Abstract: There is a growing demand for functional foods in the market with the increasing of world’s

population. The main targets for this trend in consumption are foods containing plant extracts with antioxidant

properties, polyunsaturated fatty acids, probiotics, vitamins and minerals. Although many of these components are

unstable under normal conditions or have a residual taste, their application is limited. It is therefore necessary to

use techniques which can protect the stability of these functional components, enable their application in various

food matrices and enable them to be better absorbed in our gastrointestinal tract. Various sectors of the food

industry have a demand for the enrichment of foods with functional compounds. This review aims at highlighting

the importance and application of various encapsulating techniques of probiotics, unsaturated oils, flavours, and

fruit juice. The methods and wall materials used in different encapsulation techniques would discuss in this review.

Encapsulation technology is an emerging technology that can guarantee the stability of these functional ingredients

and allow their application in variety of food matrices.

Keywords: Encapsulation technology, nanometer, nano-encapsulation

References: 1. D.R. Dias, D.A. Botrel, R.V.D.B. Fernandes, and S.V. Borges, Curr. Opin. Food Sci. 13, 31 (2017).

2. F.J. Rodrigues, M.F. Cedran, and S. Garcia, Food Bioprocess Technol. 11, 1605 (2018).

3. P.N. Ezhilarasi, P. Karthik, N. Chhanwal, and C. Anandharamakrishnan, Food Bioprocess Technol. 6, 628 (2013).

4. R.B. and R.S.S. R. Vidhyalakshmi and Indian, Adv. Biol. Res. (Rennes). (2009).

5. J. Charve and G.A. Reineccius, J. Agric. Food Chem. 57, 2486 (2009).

6. A. Gharsallaoui, G. Roudaut, O. Chambin, A. Voilley, and R. Saurel, Food Res. Int. 40, 1107 (2007).

7. J.G. Dorsey, John Wiley Sons Ltd Chichester, West Sussex. 11231 (2000).

8. V. Nedovic, A. Kalusevic, V. Manojlovic, S. Levic, and B. Bugarski, Procedia Food Sci. 1, 1806 (2011).

9. G.B. Celli, A. Ghanem, and M.S.-L. Brooks, Food Bioprocess Technol. 8, 1825 (2015).

10. Y. Gong, Y. Wu, C. Zheng, L. Fan, F. Xiong, and J. Zhu, AAPS PharmSciTech 13, 961 (2012).

11. L. de Souza Simões, D.A. Madalena, A.C. Pinheiro, J.A. Teixeira, A.A. Vicente, and Ó.L. Ramos, Adv. Colloid Interface Sci. 243, 23

(2017).

12. W.H. Organization, Diet, Nutrition, and the Prevention of Chronic Diseases: Report of a Joint WHO/FAO Expert Consultation (World

Health Organization, 2003).

13. M.L. Jiménez-Pranteda, A. Pérez-Davó, M. Monteoliva-Sánchez, A. Ramos-Cormenzana, and M. Aguilera, Food Anal. Methods 8, 272

(2015).

14. H. Majamaa and E. Isolauri, J. Allergy Clin. Immunol. 99, 179 (1997).

157-163

15. H.A. Malchow, J. Clin. Gastroenterol. 25, (1997).

16. H.K. Solanki, D.D. Pawar, D.A. Shah, V.D. Prajapati, G.K. Jani, A.M. Mulla, and P.M. Thakar, Biomed Res. Int. 2013, (2013).

17. M.J. Martín, F. Lara-Villoslada, M.A. Ruiz, and M.E. Morales, Innov. Food Sci. Emerg. Technol. 27, 15 (2015).

18. A. Das, S. Ray, U. Raychaudhuri, and R. Chakraborty, Int. J. Agric. Environ. Biotechnol. 7, 47 (2014).

19. E.J. Olguín, Biotechnol. Adv. 30, 1031 (2012).

20. A. Mortazavian, S.H. Razavi, M.R. Ehsani, and S. Sohrabvandi, Iran. J. Biotechnol. 5, 1 (2007).

21. M. Chávarri, I. Marañón, R. Ares, F.C. Ibáñez, F. Marzo, and M. del C. Villarán, Int. J. Food Microbiol. 142, 185 (2010).

22. R.S.G. da Silva and L.A.A. Pinto, Food Eng. Rev. 4, 165 (2012).

23. F.P. De Castro-Cislaghi, C.D.R.E. Silva, C.B. Fritzen-Freire, J.G. Lorenz, and E.S. Sant’Anna, J. Food Eng. 113, 186 (2012).

24. D. Calvet, J.Y. Wong, and S. Giasson, Macromolecules 37, 7762 (2004).

25. H. Gao, Y. Yu, B. Cai, and M. Wang, Chinese Sci. Bull. 49, 1117 (2004).

26. S. Gouin, Trends Food Sci. Technol. 15, 330 (2004).

27. T. Heidebach, P. Först, and U. Kulozik, Crit. Rev. Food Sci. Nutr. 52, 291 (2012).

28. H.Y. Im, J. Kim, and H. Sah, Biomacromolecules 11, 776 (2010).

29. W. Krasaekoopt, B. Bhandari, and H.C. Deeth, LWT - Food Sci. Technol. 39, 177 (2006).

30. K. Kailasapathy, LWT - Food Sci. Technol. 39, 1221 (2006).

31. Y. Kim, S. Oh, H.S. Yun, S. Oh, and S.H. Kim, 51, 123 (2010).

32. A. Homayouni, A. Azizi, M.R. Ehsani, M.S. Yarmand, and S.H. Razavi, Food Chem. 111, 50 (2008).

33. K. Sultana, G. Godward, N. Reynolds, R. Arumugaswamy, P. Peiris, and K. Kailasapathy, Int. J. Food Microbiol. 62, 47 (2000).

34. M.A. Khosravi Zanjani, B. Ghiassi Tarzi, A. Sharifan, and N. Mohammadi, Iran. J. Pharm. Res. IJPR 13, 843 (2014).

35. T.W. Yeung, E.F. Üçok, K.A. Tiani, D.J. McClements, and D.A. Sela, Front. Microbiol. 7, 494 (2016).

36. S. Mathews, Int. J. Curr. Microbiol. Appl. Sci. 6, 2080 (2017).

37. L.K. Sarao and M. Arora, Crit. Rev. Food Sci. Nutr. 57, 344 (2017).

38. S.-C. Chew, C.-P. Tan, K. Long, and K.-L. Nyam, Ind. Crops Prod. 89, 59 (2016).

39. P.J. Velasco, C. Dobarganes, G. Márquez-ruiz, I. De, G. Csic, A. Padre, and G. Tejero, 54, 209 (2012).

40. S.-C. Chew and K.-L. Nyam, J. Food Eng. 175, 43 (2016).

41. H.C.F. Carneiro, R. V Tonon, C.R.F. Grosso, and M.D. Hubinger, J. Food Eng. 115, 443 (2013).

42. V.Y. Ixtaina, L.M. Julio, J.R. Wagner, S.M. Nolasco, and M.C. Tomás, Powder Technol. 271, 26 (2015).

43. S.K. Ng, P.Y. Wong, C.P. Tan, K. Long, and K.L. Nyam, Eur. J. Lipid Sci. Technol. 115, 1309 (2013).

44. S. Shamaei, S.S. Seiiedlou, M. Aghbashlo, E. Tsotsas, and A. Kharaghani, Innov. Food Sci. Emerg. Technol. 39, 101 (2017).

45. S.-K. Ng, L.-Y.L. Jessie, C.-P. Tan, K. Long, and K.-L. Nyam, J. Am. Oil Chem. Soc. 90, 1023 (2013).

46. S.-K. Ng, Y.-H. Choong, C.-P. Tan, K. Long, and K.-L. Nyam, LWT-Food Sci. Technol. 58, 627 (2014).

47. A. Goyal, V. Sharma, M.K. Sihag, S.K. Tomar, S. Arora, L. Sabikhi, and A.K. Singh, Powder Technol. 286, 527 (2015).

48. J.D. Estrada, C. Boeneke, P. Bechtel, and S. Sathivel, J. Dairy Sci. 94, 5760 (2011).

49. P. Calvo, Á.L. Castaño, M. Lozano, and D. González-Gómez, Food Res. Int. 45, 256 (2012).

50. J.-H. Ahn, Y.-P. Kim, E.-M. Seo, Y.-K. Choi, and H.-S. Kim, J. Food Eng. 84, 327 (2008).

51. B. Wang, B. Adhikari, and C.J. Barrow, Food Chem. 158, 358 (2014).

52. P. Kaushik, K. Dowling, S. McKnight, C.J. Barrow, and B. Adhikari, Food Res. Int. 86, 1 (2016).

53. J.K. Rutz, C.D. Borges, R.C. Zambiazi, M.M. Crizel-Cardozo, L.S. Kuck, and C.P.Z. Noreña, Food Chem. 220, 59 (2017).

54. X. Yang, N. Gao, L. Hu, J. Li, and Y. Sun, J. Food Eng. 161, 87 (2015).

55. Y.P. Timilsena, R. Adhikari, C.J. Barrow, and B. Adhikari, Food Hydrocoll. 66, 71 (2017).

56. E. Morales, M. Rubilar, C. Burgos-Díaz, F. Acevedo, M. Penning, and C. Shene, Food Hydrocoll. 70, 321 (2017).

57. J.A. Piornos, C. Burgos-Díaz, E. Morales, M. Rubilar, and F. Acevedo, Food Hydrocoll. 63, 139 (2017).

58. S.-C. Chew, C.-P. Tan, K. Long, and K.-L. Nyam, Ind. Crops Prod. 76, 230 (2015).

59. D. Sun-Waterhouse, L. Penin-Peyta, S.S. Wadhwa, and G.I.N. Waterhouse, Food Bioprocess Technol. 5, 3090 (2012).

60. D. Sun-Waterhouse, J. Zhou, G.M. Miskelly, R. Wibisono, and S.S. Wadhwa, Food Chem. 126, 1049 (2011).

61. G.I.N. Waterhouse, W. Wang, and D. Sun-Waterhouse, Food Chem. 142, 27 (2014).

62. S.-C. Chew and K.-L. Nyam, J. Am. Oil Chem. Soc. 93, 607 (2016).

63. M.-H. Leong, C.-P. Tan, and K.-L. Nyam, J. Food Sci. 81, C2367 (2016).

64. A.M. Cheong, K.W. Tan, C.P. Tan, and K.L. Nyam, Ind. Crops Prod. 80, 77 (2016).

65. A.M. Cheong, K.W. Tan, C.P. Tan, and K.L. Nyam, Food Hydrocoll. 52, 934 (2016).

66. A.M. Cheong, C.P. Tan, and K.L. Nyam, Ind. Crops Prod. 87, 1 (2016).

67. A.Madene, M. Jacquot, J. Scher, and S. Desobry, Int. J. Food Sci. Technol. 41, 1 (2006).

68. X. Jun-xia, Y. Hai-yan, and Y. Jian, Food Chem. 125, 1267 (2011).

69. F. Paulo and L. Santos, Mater. Sci. Eng. C 77, 1327 (2017).

70. M. Li, O. Rouaud, and D. Poncelet, Int. J. Pharm. 363, 26 (2008).

71. J. Aguiar, B.N. Estevinho, and L. Santos, Trends Food Sci. Technol. 58, 21 (2016).

72. Y. Lv, F. Yang, X. Li, X. Zhang, and S. Abbas, Food Hydrocoll. 35, 305 (2014).

73. G.A. Rocha-Selmi, F.T. Bozza, M. Thomazini, H.M.A. Bolini, and C.S. Fávaro-Trindade, Food Chem. 139, 72 (2013).

74. S. Wang and T. Langrish, Food Res. Int. 42, 13 (2009).

75. M.I. Teixeira, L.R. Andrade, M. Farina, and M.H.M. Rocha-Leão, Mater. Sci. Eng. C 24, 653 (2004).

76. P. Vitaglione, A.D. Troise, A.C. De Prisco, G.L. Mauriello, V. Gokmen, and V. Fogliano, in edited by L.M.C.B.T.-M. and M. for F.A.

Sagis (Academic Press, San Diego, 2015), pp. 301–311.

77. A. Sultana, A. Miyamoto, Q. Lan Hy, Y. Tanaka, Y. Fushimi, and H. Yoshii, J. Food Eng. 199, 36 (2017).

78. K.D. Rubiano, J.A. Cárdenas, and H.J. Ciro V., Ing. y Compet. 17, 77 (2015).

79. N. Sosa, C. Schebor, and O.E. Pérez, Food Bioprod. Process. 92, 266 (2014).

80. D. Borrmann, A.P.T.R. Pierucci, S.G.F. Leite, and M.H.M. da R. Leão, Food Bioprod. Process. 91, 23 (2013).

81. A.T. Getachew and B.-S. Chun, LWT - Food Sci. Technol. 70, 126 (2016).

82. L.C. Machado, V.B. Pelegati, and A.L. Oliveira, J. Supercrit. Fluids 107, 260 (2016).

83. R. Murugesan and V. Orsat, Dry. Technol. 29, 1729 (2011).

84. T.C. Kha, M.H. Nguyen, and P.D. Roach, J. Food Eng. 98, 385 (2010).

85. Tontul and A. Topuz, Trends Food Sci. Technol. 63, 91 (2017).

86. A.M. Goula and K.G. Adamopoulos, Innov. Food Sci. Emerg. Technol. 11, 342 (2010).

87. K. Muzaffar and P. Kumar, Powder Technol. 279, 179 (2015).

88. S.Y. Quek, N.K. Chok, and P. Swedlund, Chem. Eng. Process. Process Intensif. 46, 386 (2007).

Authors: Sook-Chin Chew, Chin Ping Tan, Nyam Kar Lin

Paper Title: Quality of Chemical Re-fined Kenaf (Hibiscus cannabinus L.) Seed oil during Accelerated Storage

Abstract: In accelerated stockpiling at 65 oC for 24 days, an oxidative stability test was performed on crudes

27.

and re-fined kenaf seed oil. The outcomes revealed which refined oil underwent higher oxidation than the crude

oil, as indicated by the peroxide value (40.55 meq/kg), p-Anisidine value (18.78) and total oxidation value (99.87)

in re-fined oils at day 24. A free fatty acid value in the refined oil did not differ significantly and remained less

than 1% during accelerated storage. After accelerated storage, the phenolic substance and anti-oxidant movement

of re-fined oil was altogether lesser than crude oil. During accelerated storage, refined oil decreased by 67%

tocopherol substance and 12.1 % phytosterol substance. After storage, there was no huge contrast in a content of

tocopherol and phytosterol for crude and re-fined oils. The rate of tocopherol and phytosterol degradation in re-

fined oil during storage was lesser than in unrefined petroleum (crude oil). Un-saturated fatty acids decreased

slightly during storage, together with a slight increase in saturated fats in kenaf seed oil. The refining process

reduced the oxidative steadiness of kenaf seed oil, but the refined oil could able to maintain good quality in the

estimation of Free Fatty Acid (FFA) and a composition of fatty acid, and to protect tocopherols and phytosterols.

Keywords: kenaf seeds, phenolic and accelerated stockpiling.

References: 1. K.L. Nyam, C.P. Tan, O.M. Lai, K. Long, and Y.B. Che Man, LWT - Food Sci. Technol. 42, 1396 (2009).

2. A.M. Cheong, C.P. Tan, and K.L. Nyam, Ind. Crops Prod. 87, 1 (2016).

3. S.C. Chew, C.-P. Tan, K. Long, and K.-L. Nyam, Ind. Crops Prod. 76, 230 (2015).

4. M. Leja, I. Kamińska, M. Kramer, A. Maksylewicz-Kaul, D. Kammerer, R. Carle, and R. Baranski, Plant Foods Hum. Nutr. 68, 163

(2013).

5. Emmanuel O. Aluyor* and Mudiakeoghene Ori-Jesu, African J. Biotechnol. Vol. 7 (25, pp. 4836 (2008).

6. M. Hassan El-Mallah, ; Safinaz, M. El-Shami, ; Minar, M.M. Hassanien, and A.G. Abdel-Razek, (2011).

7. S.-C. Chew, C.-P. Tan, K. Long, and K.-L. Nyam, Ind. Crops Prod. 89, 59 (2016).

8. Suliman TE, Jiang J, Liu YU. Chemical refining of sunflower oil: effect on oil stability, total tocopherol, free fatty acids and colour. Int J

Eng Sci Technol. 2013;5(2):449-54.

9. Y. Liu, R. Mo, D. Zhong, D. Shen, Z. Ni, and F. Tang, J. Food Sci. 80, T1926 (2015).

10. H. Yin and S. Sathivel, J. Food Sci. 75, E163 (2010).

11. Raikos, V. Konstantinidi, and G. Duthie, Int. J. Food Sci. Technol. 50, 2316 (2015).

12. A Richards, C. Wijesundera, and P. Salisbury, J. Am. Oil Chem. Soc. 82, 869 (2005).

13. C.P. Tan, Y.B. Che Man, J. Selamat, and M.S.A. Yusoff, Food Chem. 76, 385 (2002).

14. S.C. Chew and K.L. Nyam, J. Food Eng. 175, 43 (2016).

15. S. Iqbal and M.I. Bhanger, Food Chem. 100, 246 (2007).

16. F.M. Nor, S. Mohamed, N.A. Idris, and R. Ismail, Food Chem. 110, 319 (2008).

17. P. Zacchi and R. Eggers, Eur. J. Lipid Sci. Technol. 110, 111 (2008).

18. F. Kreps, L. Vrbiková, and Š. Schmidt, Eur. J. Lipid Sci. Technol. 116, 1572 (2014).

19. F.D. Gunstone, Bailey’s Ind. Oil Fat Prod. (2005).

20. F. Gutiérrez, T. Arnaud, and A. Garrido, J. Sci. Food Agric. 81, 1463 (2001).

21. K.L. Nyam, M.M. Wong, K. Long, and C.P. Tan, Int. Food Res. J. 20, 695 (2013).

22. S.M. Ghazani, G. García-Llatas, and A.G. Marangoni, J. Am. Oil Chem. Soc. 90, 743 (2013).

23. A S., A. C.P., and C. H.A.B., Trop. J. Pharm. Res. 16, 305 (2017).

24. H.T. Vu, C.J. Scarlett, and Q. V Vuong, J. Funct. Foods 40, 238 (2018).

25. B.B. Surjadinata and L. Cisneros-Zevallos, Food Chem. 134, 615 (2012).

26. M.H. Bruscatto, R.C. Zambiazi, M. Sganzerla, V.R. Pestana, D. Otero, R. Lima, and F. Paiva, J. Chromatogr. Sci. 47, 762 (2009).

27. Karabulut, A. Topcu, A. Yorulmaz, A. Tekin, and D.S. Ozay, Eur. J. Lipid Sci. Technol. 107, 476 (2005).

28. F. Ntanios, Eur. J. Lipid Sci. Technol. 103, 102 (2001).

164-168

28.

Authors: Hala A. Hashim, Akram H Shather, Ali F. Jameel, Azizan Saaban

Paper Title: Numerical Solution of First Order Nonlinear Fuzzy Initial Value Problems by Six- Stage Fifth Order

Runge Kutta Method

Abstract: The point of this paper is to present and analyze a numerical method to illuminate fuzzy initial value

problems (FIVPs) including nonlinear fuzzy differential equations. The primary thought is based reformulate the

six stages Runge Kutta strategy of order five (RK65) from crisp case to fuzzy case by taking the advantage of

fuzzy set theory properties. It is appeared that the comes about demonstrate that the strategy is exceptionally

compelling and basic to apply and fulfil the properties of the fuzzy solution. The capability of RK65 is outlined by

fathoming to begin with arrange nonlinear FIVP taken after by usage of the convergence theory. Thus, the strategy

can be executed and utilized to allow a numerical solution of nonlinear FIVPs.

Keywords: Fuzzy set theory, Fuzzy differential equations, Six- Stage Fifth Order Runge Kutta Method.

References: 1. Ali, Jameel, Anakira, N R,Alomari, AK, Hashim, I and Shakhatreh MA. “ Numerical solution of n’th order fuzzy initial value problems

by six stages ,”Journal of Nonlinear Science and Applications 9, no. 2 (2016):627–640.

2. Abbasbandy S, Allahvinloo T, andDarabi P. “Numerical solution of n-order fuzzy differential equations by RungeKutta method,”

Mathematical and Computational Applications 16, no. 4 (2011): 935–946, 2011.

3. Ali, Jameel, Anakira, N R, Alomari, A K, Hashim, I, and Momani, S.“A New Approximation Method for Solving Fuzzy Heat

Equations,”Journal of Computational and Theoretical Nanoscience 13, no. 11(2016): 7825-7832.

4. Seikkala, S.“On the Fuzzy initial value problem,”Fuzzy sets and systems14,no. 3 (1987):319-330.

5. Omer, A, and Omer, O.“A pray and predator model with fuzzy initial values,”Hacettepe Journal of Mathematics and Statistics 14, no. 3

(2013): 387– 395.

6. Smita, T, and Chakraverty, S.” Numerical solution of fuzzy arbitrary order predator-prey equations,”Applications and Applied

Mathematics8, no. 1(2013): 647-673.

7. Abbod M F, Von Keyserlingk, D G, and Mahfouf M. ” Survey of utilization of fuzzy technology in medicine and healthcare,”Fuzzy sets

and systems 120, no 2(2001): 331-3491.

169-173

8. El Naschie M S.“From Experimental Quantum Optics to Quantum Gravity Via a Fuzzy Kahler Manifold,”Chaos, Solitons & Fractals 25,

no. 5 (2005): 969-977.

9. Ali F J, Ahmad I I, and Amir S, “Numerical solution of fuzzy IVP with trapezoidal and triangular fuzzy numbers by using fifth order

Runge-Kutta method,”World Applied Sciences Journal 17, no. 12 (2012):1667-1674.

10. Duraisamy C, and Usha, B. “Numerical Solution of Fuzzy Differential Equations by Runge-Kutta Method of Order Four,”European

Journal of Scientific Research 67, No.2, pp. 324-337, 2012.

11. V. Nirmala, S. Chenthur Pandian, New Multi-Step Runge –Kutta Method For Solving Fuzzy Differential Equations, Mathematical Theory

and Modeling, Vol.1, no.3 (2011): 16-22.

12. Ramli, A, Ahmad, R R, Din A,and Salleh, A R. “Third-order Composite Runge Kutta Method for Solving Fuzzy Differential

Equations,”Global Journal of Pure and Applied Mathematics22, no. 3 (2016): 2753-2764.

13. Julyan H E, Oreste P.”The dynamics of Runge–Kutta methods,”International Journal of Bifurcation and Chaos 2, no. 3 (1992): 27–449.

14. Bodjanova, S.” Median Alpha-Levels of A Fuzzy Number,” Fuzzy Sets and Systems157, no. 7 (2006): 879-891, 2006.

15. Dubois D, Prade H, “Towards fuzzy differential calculus, Part 3: Differentiation,”Fuzzy Sets and Systems 8, no. 3(1982): 225-233.

16. Fard, O S. “ An iterative scheme for the solution of generalized system of linear fuzzy differential equations,”World Applied Sciences

Journal 7, no. 12 (2009):1597-1160.

17. Faranak, R, Fudziah I, Ali, A,and Soheil S.”Numerical solution of second-order fuzzy differential equation using improved Runge-Kutta

Nystrom method,”Mathematical Problems in Engineering 2013, (2013): pp 1-10.

18. Kaleva, O.” Fuzzy differential equation,”Fuzzy Sets and Systems 24, no. 3 (1987): 301-317.

19. Mansour, S S, and Ahmady, N.“A numerical method for solving Nth-order fuzzy differential equation by using Characterization

theorem,”Communications in Numerical Analysis2012, (2012): 1-12.

20. Zadeh, L A. “Toward a generalized theory of uncertainty,”Inform Sciences172, no. 2 (2005):1–40.

21. Emre S. “Comparison of Runge-Kutta methods of order 4 and 5 on Lorenz equation,”international journal arts sciences1, no. 1(2004) 61-

69.

29.

Authors: Joel C. De Goma, Joel Roy V. Jamias, Anthony H. Kwong, Jessica Mae S. Salvador

Paper Title: Real-Time Facial Feature Point Detection and Tracking using Rule-based Approach and Integral

Projection

Abstract: The face is a basis of how one can describe emotions of another as it is a medium of communication.

Through looking at the face of the person, one can detect what kind of feeling he is portraying. It may be a case for

humans; however, computers cannot detect the emotion of humans simply by looking at their faces, computers rely

on the positioning of the feature points of the eyes, and mouth in order to determine the emotion. In this

connection, this study aims to create a system wherein it can detect the features and track points of the face in a

real-time video. The authors attempt to combine different algorithms in order to detect and track the feature points

in the face. Based on the results of the conducted tests, the setup has recorded an overall success rate of 44.56 %.

This is due to the large skin range that was used in the program.

Keywords: Balasuriya’s study, Khandait’s study, Padilla’s study

References: 1. A.K. Jain and S.Z. Li, Handbook of Face Recognition (Springer, 2011).

2. S.P. Khandait, P.D. Khandait, and R.C. Thool, Int. J. Recent Trends Eng. 2, 179 (2009).

3. J.H. Lai, P.C. Yuen, W.S. Chen, S. Lao, and M. Kawade, in Recognition, Anal. Track. Faces Gestures Real-Time Syst. 2001. Proceedings.

IEEE ICCV Work. (IEEE, 2001), pp. 168–174.

4. C. Kotropoulos and I. Pitas, in Image Process. 1997. Proceedings., Int. Conf. (IEEE, 1997), pp. 105–108.

5. L.S. Balasuriya, (2000).

6. R. Padilla, C.F.F. Costa Filho, and M.G.F. Costa, World Acad. Sci. Eng. Technol. 64, (2012).

7. H.K. Saini and O. Chand, Skin (Los. Angeles). 3, 1781 (2013).

8. D. Vukadinovic and M. Pantic, in Syst. Man Cybern. 2005 IEEE Int. Conf. (IEEE, 2005), pp. 1692–1698.

9. L. Zhao and J. Tao, in Int. Conf. Image Vis. Comput. Hamilton, New Zeal. (2007), pp. 7–12.

10. A.R. Dixon and E.E. Telles, Annu. Rev. Sociol. (2017).

11. Q. Wu and W. Yang, in Comput. Vis. Concepts, Methodol. Tools, Appl. (IGI Global, 2018), pp. 397–420.

12. S. Coşar and M. Çetin, Image Vis. Comput. 29, 335 (2011).

13. Z. Huang, R. Wang, S. Shan, and X. Chen, in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (2015), pp. 140–149.

174-178

30.

Authors: Ian Paolo I. Azusano, Raymund Angelo C. Memije, Lemmuel L. Tayo

Paper Title: Characterization of Bacterial Cellulose (Nata De Coco)/Pva Composite for Drug Delivery Application

Abstract: Numerous innovations in the field of biomedical engineering include the use of synthetic polymers

as a drug carrier for drug delivery systems. In this study, polyvinyl alcohol (PVA), with its properties of being a

biocompatible, non-toxic, non-carcinogenic polymer, were infused into nata de coco, a bacterial cellulose, by

immersing nata de coco slabs into PVA solutions to investigate its capability as a component in drug delivery

systems. Different PVA concentrations were prepared to see any effect to the bacterial cellulose. The composites

were characterized by analyzing the functional groups present, water uptake capacity and kinetics of methylene

blue release. Effect of varying PVA concentration was not seen due to inconsistent amount of pure bacterial

cellulose and water on tested samples. Study on the kinetics of methylene blue, modeled as a drug, loaded into the

nata de coco/PVA composite was analyzed using Power Law Model. Results showed that the governing diffusion

mechanism involved in the release of methylene blue from the composite samples were mainly ‘non-Fickian

(anomalous). Tests performed, confirmed the capability of PVA to reinforce the bacterial cellulose matrix. Results

showed that composites with high amount of PVA in their matrix released smaller amounts of methylene blue.

Results showed that composites with high amount of PVA in their matrix released smaller amounts of methylene

blue. PVA absorbed less water as the hydroxyl groups of BC were bonded to PVA PVA may have changed the

morphological structure of bacterial cellulose affecting the diffusion mechanism of the methylene blue release.

Findings of this study, based on nata de coco/PVA composites can be used for future studies of drug delivery

179-186

systems.

Keywords: Bioactive polymers, Pharmaceutical products, Porosity

References: 1. S. Yamanaka and J. Sugiyama, Cellulose 7, 213 (2000).

2. Y. Feng, X. Zhang, Y. Shen, K. Yoshino, and W. Feng, Carbohydr. Polym. 87, 644 (2012).

3. I. Mihaela Jipa, L. Dobre, M. Stroescu, A. Stoica-Guzun, S. Jinga, and T. Dobre, Mater. Lett. 66, 125 (2012).

4. A. Stoica-Guzun, M. Stroescu, I. Jipa, L. Dobre, and T. Zaharescu, Radiat. Phys. Chem. 84, 200 (2013).

5. J. Kim, Z. Cai, and Y. Chen, J. Nanotechnol. Eng. Med. 1, 11006 (2009).

6. R.D. Pavaloiu, A. Stoica-Guzun, M. Stroescu, S.I. Jinga, and T. Dobre, Int. J. Biol. Macromol. 68, 117 (2014).

7. T.G. Chiciudean, A. Stoica, T. Dobre, and M. Van Tooren, UPB Bul. Stiint. Ser. B Chem. Mater. Sci. 73, 17 (2011).

8. A.F. Leitão, S. Gupta, J.P. Silva, I. Reviakine, and M. Gama, Colloids Surfaces B Biointerfaces 111, 493 (2013).

9. G.F. Picheth, C.L. Pirich, M.R. Sierakowski, M.A. Woehl, C.N. Sakakibara, C.F. de Souza, A.A. Martin, R. da Silva, and R.A. de Freitas,

Int. J. Biol. Macromol. 104, 97 (2017).

10. M.S. Peresin, Y. Habibi, A.-H. Vesterinen, O.J. Rojas, J.J. Pawlak, and J. V Seppala, Biomacromolecules 11, 2471 (2010).

11. C. Castro, A. Vesterinen, R. Zuluaga, G. Caro, I. Filpponen, O.J. Rojas, G. Kortaberria, and P. Gañán, Cellulose 21, 1745 (2014).

12. R. Elhajjar, C.-T. Law, and A. Pegoretti, Prog. Mater. Sci. 97, 204 (2018).

13. N. Bharath and G.J. W., Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 376, 20170050 (2018).

14. G.F. Perotti, H.S. Barud, Y. Messaddeq, S.J.L. Ribeiro, and V.R.L. Constantino, Polymer (Guildf). 52, 157 (2011).

15. G. Yang, Y. Yao, and C. Wang, Mater. Lett. 209, 11 (2017).

16. A. El Aissaoui and A. El Afif, J. Memb. Sci. 543, 172 (2017).

17. D. Onggo, I. Mulyani, F.J. Valverde-Muñoz, J.A. Real, and G. Molnar, Cellulose 24, 2205 (2017).

18. L.O.A.N.R. and M.N.R. and P.E.S. and L.O.A. and U.E. Rusbandi, IOP Conf. Ser. Mater. Sci. Eng. 223, 12061 (2017).

19. R. Ghanbari, S. Assenza, A. Saha, and R. Mezzenga, Langmuir 33, 3491 (2017).

20. T. Yan, K. Schröter, F. Herbst, W.H. Binder, and T. Thurn-Albrecht, Macromolecules 50, 2973 (2017).

21. S.P. Lin, I. Loira Calvar, J.M. Catchmark, J.-R. Liu, A. Demirci, and K.-C. Cheng, Cellulose 20, 2191 (2013).

22. J. Miao, M. Tsige, and P.L. Taylor, J. Chem. Phys. 147, 44904 (2017).

23. F. Ganji, F.S. VASHEGHANI, and F.E. VASHEGHANI, (2010).

24. D.L. Munday and P.J. Cox, Int. J. Pharm. 203, 179 (2000).

25. A. Prades, M. Dornier, N. Diop, and J.-P. Pain, Fruits 67, 87 (2012).

31.

Authors: NurnasranPuteh, Mohd. ZabidinHusin, Hatim Mohamad Tahir, Azham Hussain

Paper Title: Building a Question Classification Model for a Malay Question Answering System

Abstract: Question answering system (QAS) is an example of an application of natural language processing

where it is able to automatically return a specific answer to a question given in a natural language by a human.

One of the important tasks in QAS is Question Classification which is the task to identify the semantic type of the

required answer for the question posed to the QAS. Identifying the correct answer type is an important process

before the required correct answer can be retrieved by the system. In this paper we presents a model of Answer

Type Classification using machine learning approach targeted for a Malay QAS for the Quran, which is a

restricted-domain QAS. The performance of the classification model using three different machine learning

classification algorithms, namely Naïve Bayes, Random Forest and Support Vector Machine (SVM), are then

evaluated. The results show that the classifier based on SVM has the best overall results in terms of accuracy,

precision, recall and F1-score.

Keywords: Malay Question Answering, Question classification, Machine learning, Quran, QAS

References: 1. Abdullah, M. T., Ahmad, F., Mahmod, R., &TengkuSembok, T. M.(2005). Improvement of Malay Information Retrieval Using Local

Stop Word. International Advanced Technology Congress, Dec 6-8, Malaysia.

2. Ahmad, N. D., Bennett, B., & Atwell, E. (2017). Retrieval Performance for Malay Quran. International Journal on Islamic Applications

in Computer Science And Technology, Vol. 5, Issue 2, 13-25

3. Al-Shawakfa, E. (2016). A Rule-Based Approach to Understand Questions in Arabic Question Answering. Jordanian Journal of

Computers and Information Technology (JJCIT), Vol. 2, No. 3, pp. 210–231.

4. Ask Islam. (n.d.). Retrieved July 30 2018, fromhttp://www.askislam.org/literature_and_languages/quran/index.html.

5. Back to Jannah. (2018). Retrieved July 30 2018, from https://backtojannah.com/100-questions-on-quran/.

6. Basheerpkm. (2007, March 13). Retrieved July 30 2018, http://turntoislam.com/community/threads/100-questions-on-quran.10052/.

7. Cortes, C. & Vapnik, V. N. (1995). Support vector machines.Machine Learning 20: 273–297.

8. Devi, R., &Dua, M. (2016). Performance Evaluation of Different Similarity Functions and Classification Methods Using Web Based

Hindi Language Question Answering System. In Procedia Computer Science, Vol. 92, 520–525.

9. Gusmita, R. H., Durachman, Y., Harun, S., Firmansyah, A. F., Sukmana, H. T., &Suhaimi, A. (2014). A rule-based question answering

system on relevant documents of Indonesian Quran Translation. In International Conference on Cyber and IT Service Management,

CITSM 2014, 104–107.

10. Hirschman, L. &Gaizauskas, R. (2001). Natural language question answering: the view from here. Natural Language Engineering 7 (4):

275-300. Cambridge University Press.

11. Info Dan SoalJawabMengenal Al-Quran. (2011, August 25).Retrieved July 30 2018, https://shafiqolbu.wordpress.com/2011/08/25/info-

dan-soal-jawab-mengenal-al-quran/.

12. Jurafsky, D.,& Martin, J. H. (2009). Speech and Language Processing. Prentice Hall.

13. Mishra, A., &Jain, S. K. (2016). A survey on question answering systems with classification. Journal of King Saud University-Computer

and Information Sciences 28, 3, 345–361.

14. Li, X.,& Roth, D. (2002). Learning question classifiers. In Proceedings of the 19th international conference on Computational linguistics,

COLING ’02 Association for Computational Linguistics, 1–7.

15. Li, X.,& Roth, D. (2004). Learning question classifiers: The role of semantic information. In Proceedings International Conference on

Computational Linguistics, 556–562.

16. Loni, B. (2011). A Survey of State-of-the-Art Methods on Question Classification. Literature Survey. Published on TU Delft Repository.

187-200

17. Molla, D., &Vicedo, J. L. (2007). Question answering in restricted domains: An overview. Computational Linguistics 33(1):41-61.

18. Prager, J., Radev, D., Brown, E., Coden, A., &Samn, V. (1999). The use of predictive annotation for question answering in TREC8, NIST

Special Publication 500-246: The Eighth Text REtrieval Conference (TREC 8).

19. Radev, D., Fan, W., Qi, H., Wu, H.,& Grewal, A. (2002). Probabilistic question answering on the web, InProceedings of the eleventh

international conference on World Wide Web (WWW2002), Hawaii.

20. Roth, D. (1998). Learning to resolve natural language ambiguities: A unified approach. In Proceedings of the fifteenth national/tenth

conference on Artificial intelligence/Innovative applications of artificial intelligence, AAAI ’98/IAAI ’98. American Association for

Artificial Intelligence, 806–813.

21. Santosh, K. R., Singh, S., & Joshi B. P. (2010). A semantic approach for question classification using wordnet and wikipedia. Pattern

Recognition Letters Volume 31, Issue 13:1935–1943.

22. Sherkat, E.,&Farhoodi, M. (2014). A Hybrid Approach for Question Classification in Persian Automatic Question Answering Systems. In

Proceedings of 4th International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, 279-284.

23. Silva, J.,Coheur, L., Mendes, A. C., &Wichert, A.(2011). From symbolic to sub-symbolic information in question classification. Artificial

Intelligence Review, 35(2):137–154.

24. Suara Islam, SoalJawabTentang Al Quran. (2016, November 2).Retrieved July 30 2018, https://suaraislam.net/2016/11/02/soal-jawab-

tentang-al-quran/.

25. Witten, I., &Frank, E. (2017). Data Mining Practical Machine Learning Tools and Techniques. Morgan Kaufmann, San Francisco, CA.

Fourth edition.

26. Zhang, D.,&Lee, W. S. (2003). Question classification using support vector machines. In Proceedings of the 26th annual international

ACM SIGIR conference on Research and development in information retrieval, SIGIR ’03, 26–32.

27. Zhang, K.,&Zhao, J. (2010). A Chinese question-answering system with question classification and answer clustering. In Proceedings of

the 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010, Vol. 6, 2692–2696.

32.

Authors: Balogun Abdullateef Oluwagbemiga, Basri Shuib, Said Jadid Abdulkadir, Garba Mariam,

AlmomaniMalek Ahmad Thabeb

Paper Title: A Hybrid ant Colony Tabu Search Algorithm for Solving Next Release Problems

Abstract: Next Release Problem (NRP) is a challenge in software engineering to define which set of

requirements are to be developed in the next release of a software product taking in consideration several

constraints such as the cost of development, user’s significance, and constraints related to scheduling,

dependencies between requirements and available expertise. Solving this problem will help software engineers to

make decisions on the set of requirements to include as features in the next release of a software product. This

paper proposes a hybrid of Ant Colony Optimization (ACO) algorithm and Tabu Search (TS) for solving NRP

using a cost-value model for requirements. A fitness function with two objectives was considered to maximize

users’ satisfaction and to minimize the cost of developing the requirements requested by users. The hybrid Ant

Colony Optimization Tabu Search (ACOTS) algorithm is based on Ant Colony Optimization (ACO) algorithm

while it employs the history keeping strategy of Tabu Search (TS) when constructing new solutions (local search

spaces) for each initial solution generated by each ant. The procedure of the hybrid algorithm starts by generating

random solutions that serve as a pivot for all ants of the colony which is based on the pheromone information, the

set objectives in the fitness function and problem specific local heuristic information associated with each of the

objectives. The output of the hybrid ACOTS is a set of promising optimal values which are the total number of the

set of requirements from which a subset is to be selected. The results of the experiments showed that the

application of ACOTS yielded larger and better sets of results than existing methods (ACS, Ant System and Tabu

Search). The application of ACOTS also enables an easier parameter tuning (budget, number of requirements).

Keywords: Requirement Engineering, Next Release Problem, Metaheuristics, Optimization

References: 1. Adenso-Diaz, B., & Laguna, M. (2006). Fine-tuning of algorithms using fractional experimental designs and local search. Operations

research, 54(1), 99-114.

2. Almeida, J. C., Pereira, F. d. C., Reis, M. V., & Piva, B. (2018). The Next Release Problem: Complexity, Exact Algorithms, and

Computations. Paper presented at the International Symposium on Combinatorial Optimization.

3. Araújo, A. A., Paixao, M., Yeltsin, I., Dantas, A., & Souza, J. (2017). An architecture based on interactive optimization and machine

learning applied to the next release problem. Automated Software Engineering, 24(3), 623-671.

4. Bagnall, A. J., Rayward-Smith, V. J., & Whittley, I. M. (2001). The next release problem. Information and Software Technology, 43(14),

883-890.

5. Balogun, A., Mabayoje, M., Makinwa, M., & Bajeh, A. (2016). Solving the Next Release Problem using a Hybrid Metaheuristic. Annals

Computer Science Series, 14(2), 101–116.

6. Braude, E. J., & Bernstein, M. E. (2016). Software engineering: modern approaches: Waveland Press.

7. Buede, D. M., & Miller, W. D. (2016). The engineering design of systems: models and methods: John Wiley & Sons.

8. Cai, X., Cheng, X., Fan, Z., Goodman, E., & Wang, L. (2017). An adaptive memetic framework for multi-objective combinatorial

optimization problems: studies on software next release and traveling salesman problems. Soft Computing, 21(9), 2215-2236.

9. Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions

on evolutionary computation, 6(2), 182-197.

10. del Sagrado, J., del Aguila, I. M., & Orellana, F. J. (2015). Multi-objective ant colony optimization for requirements selection. Empirical

Software Engineering, 20(3), 577-610.

11. Dick, J., Hull, E., & Jackson, K. (2017). Requirements engineering: Springer.

12. Doerner, K. F., & Maniezzo, V. (2018). Metaheuristic search techniques for multi-objective and stochastic problems: a history of the

inventions of Walter J. Gutjahr in the past 22 years. Central European Journal of Operations Research, 26(2), 331-356.

13. Dorigo, M., & Stützle, T. (2019). Ant colony optimization: overview and recent advances Handbook of metaheuristics (pp. 311-351):

Springer.

14. Drias, Y., Kechid, S., & Pasi, G. (2016). A novel framework for medical web information foraging using hybrid ACO and Tabu Search.

Journal of medical systems, 40(1), 5.

15. Durillo, J. J., Zhang, Y., Alba, E., Harman, M., & Nebro, A. J. (2011). A study of the bi-objective next release problem. Empirical

Software Engineering, 16(1), 29-60.

201-208

16. Engin, O., & Güçlü, A. (2018). A new hybrid ant colony optimization algorithm for solving the no-wait flow shop scheduling problems.

Applied Soft Computing, 72, 166-176.

17. Finkelstein, A., & Lim, S. L. (2012). StakeRare: using social networks and collaborative filtering for large-scale requirements elicitation.

IEEE transactions on software engineering(3), 707-735.

18. Gendreau, M., & Potvin, J.-Y. (2019). Tabu Search Handbook of Metaheuristics (pp. 37-55): Springer.

19. Glover, F. (1990). Tabu search—part II. ORSA Journal on Computing, 2(1), 4-32.

20. Glover, F., Laguna, M., & Martí, R. (2018). Principles and Strategies of Tabu Search. Handbook of Approximation Algorithms and

Metaheuristics: Methodologies and Traditional Applications, 1.

21. Harman, M., & Jones, B. F. (2001). Search-based software engineering. Information and Software Technology, 43(14), 833-839.

22. Jiang, H., Zhang, J., Xuan, J., Ren, Z., & Hu, Y. (2010). A hybrid ACO algorithm for the next release problem. Paper presented at the

Software Engineering and Data Mining (SEDM), 2010 2nd International Conference on.

23. Kleijnen, J. P. (2015). Design and analysis of simulation experiments. Paper presented at the International Workshop on Simulation.

24. Layton, M. C., & Ostermiller, S. J. (2017). Agile project management for dummies: John Wiley & Sons.

25. Li, L., Harman, M., Wu, F., & Zhang, Y. (2016). The value of exact analysis in requirements selection. IEEE Transactions on Software

Engineering, PP (99), 1-1.

26. Li, Y., Zhang, M., Yue, T., Ali, S., & Zhang, L. (2017). Search-Based Uncertainty-Wise Requirements Prioritization. Paper presented at

the Engineering of Complex Computer Systems (ICECCS), 2017 22nd International Conference on.

27. Lim, S. L. (2011). Social networks and collaborative filtering for large-scale requirements elicitation. University of New South Wales.

28. McMullen, P. R. (2017). Ant-Colony Optimization for the System Reliability Problem with Quantity Discounts. American Journal of

Operations Research, 7(02), 99.

29. Poongothai, M., & Rajeswari, A. (2016). A hybrid ant colony tabu search algorithm for solving task assignment problem in heterogeneous

processors. Paper presented at the Proceedings of the International Conference on Soft Computing Systems.

30. Salhi, S. (2017). Population-Based Heuristics Heuristic Search (pp. 77-128): Springer.

31. Srivastava, P. R., Varshney, A., Nama, P., & Yang, X.-S. (2012). Software test effort estimation: a model based on cuckoo search.

International Journal of Bio-Inspired Computation, 4(5), 278-285.

32. Stützle, T., & López-Ibáñez, M. (2019). Automated Design of Metaheuristic Algorithms Handbook of Metaheuristics (pp. 541-579):

Springer.

33. van den Akker, M., Brinkkemper, S., Diepen, G., & Versendaal, J. (2005). Determination of the Next Release of a Software Product: an

Approach using Integer Linear Programming. Paper presented at the CAiSE Short Paper Proceedings.

34. Veerapen, N., Ochoa, G., Harman, M., & Burke, E. K. (2015). An integer linear programming approach to the single and bi-objective next

release problem. Information and Software Technology, 65, 1-13.

35. Wu, J., Wu, G., & Wang, J. (2017). Flexible Job-shop Scheduling Problem Based on Hybrid ACO Algorithm. International Journal of

Simulation Modelling, 16(3), 497-505.

36. Zhang, Y., Harman, M., Ochoa, G., Ruhe, G., & Brinkkemper, S. (2018). An Empirical Study of Meta-and Hyper-Heuristic Search for

Multi-Objective Release Planning. ACM Transactions on Software Engineering and Methodology (TOSEM), 27(1), 3.

33.

Authors: Noraziah ChePa, Nooraini Yusoff, Norhayati Ahmad

Paper Title: Exploring the Determinants for Grading Malaysian Rice

Abstract: Rice plays a significant role in Malaysian economy especially for states in the Northern Region.

Rice grading is important in determining rice quality and its subsequent price in the market. It is an important

process applied in the rice production industry with the purpose of ensuring that the rice produced for the market

meets the quality requirements of consumer. Two important aspects that need to be considered in determining rice

grades are grading technique and determinants to be used for grading (usually referred as rice attributes). This

article proposes the list of determinants to be used in grading Malaysian rice. Determinants were explored through

combination of extensive literature review and series of interview with the domain experts and practitioners. The

proposed determinants are believed to be beneficial to BERNAS in improving the current Malaysian rice grading

process.

Keywords: Rice grading, Malaysian rice, rice grade, grade determinants

References: 1. IRRI. IRRI Rice Knowledge Bank, 2006.

2. BERNAS. Rice Background, 2011.

3. M. Gummert and J. Rickman. Rice Quality, 2011.

4. H. M. G. GAZETT. Essential (Control of Supply of Rice) Regulations 1974, Rice (Grade and Price Control) Order 1992.1992.

5. BERNAS. Rice Types in Malaysia, 2011.

6. L. Pabamalie and H. L. Premaratne, "A Grain Quality Classification System," in IEEE Conference Publications, 2010.

7. S. J. Rad, F. A. Tab and K. Mollazade, "Classification of rice varieties using optimal color and texture features and BP Neural networks,"

in IEEE Conference Publications, 2011.

8. O. C. Agustin and B. -J. Oh, "Automatic Milled Rice Quality Analysis," in IEEE Conference Publications, 2008.

9. B. Verma, "Image Processing Techniques for Grading & Classification of Rice," in IEEE Conference Publications. 2010.

10. J. D. Guzman and E. K. Peralta, "Classification of Philippine Rice Grains Using Machine Vision and Artificial Neural Networks," in

World Conference On Agricultural Information and It, 2008.

11. R. C. Chakraborty. "Fundamentals of Neural Networks Artificial Intelligent,". 2010

12. J. M. Bishop and R. J. Mitchell, "Neural Networks an Introduction," in IET Conference Publications, 1991.

13. R. E. Uhrig, "Introduction to Artificial Neural Networks," in IEEE Conference publication, 1995.

14. J. Paliwal, N. S. Visen and D. S. Jayas. "Evaluation of Neural Networks Architectures for Cereal Grain Grading Using Morphological

Features,", 2001.

15. M. Gummert. Measuring the Moisture Content, 2011.

16. N. Sidnal, V.U. Patil, and P. Patil, “Grading and Quality Testing of Food Grains Using Neural Network”. International Journal of

Research in Engineering and Technology. 2013.

17. Z. Effendi, R. Ramli, and J.A. Ghani, “A Back Propagation Neural Networks for Grading Jatropha curcas Fruits Maturitiy”. American

Journal of Applied Sciences. 7(3), 2010, 390.

18. IRRIRice Knowledge Bank.. “Standards and grades for milled rice”, 2009.

19. J.F. Rickman, M. Gummert, M. Fitzgerald, and M.A. Bell,. Brown Rice, 2005.

209-213

34.

Authors: Ammar K Alazzawi, Helmi Md Rais, Shuib Basri

Paper Title: Parameters Tuning of Hybrid Artificial Bee Colony Search based Strategy for t-way Testing

Abstract: Hybrid Artificial Bee Colony (HABC) Strategy is latterly developed based on hybridize of an

artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. In order to ensure that

HABC could perform for t-way testing as useful as other strategies to generate best performance, there are a

number of parameters of an HABC algorithm such as the number of colony size (NBees), the number of food

source, limit, the number of cycles (maxCycle), weight factor (w) and learning factors (C1, C2) that required to be

tuned. In this paper, the process of parameters tuning for hybrid artificial bee colony algorithm has been shown as

well as t-way testing, where has been adopted a standard covering array CA (N, 2, 57). The obtained experiment

results illustrate that HABC strategy can generate the most minimum and sufficiently results compared to other

strategies.

Keywords: t-way test, Artificial Bee Colony, Bat-Testing

References: 1. B. S. Ahmed, L. M. Gambardella, W. Afzal, and K. Z. Zamli, "Handling constraints in combinatorial interaction testing in the presence of

multi objective particle swarm and multithreading," Information and Software Technology, vol. 86, pp. 20-36, 2017.

2. B. S. Ahmed, K. Z. Zamli, and C. P. Lim, "Constructing a t-way interaction test suite using the particle swarm optimization approach,"

International Journal of Innovative Computing, Information and Control, vol. 8, pp. 431-451, 2012.

3. X. Chen, Q. Gu, A. Li, and D. Chen, "Variable strength interaction testing with an ant colony system approach," in Software Engineering

Conference, 2009. APSEC'09. Asia-Pacific, 2009, pp. 160-167.

4. R. A. Alsewari and K. Z. Zamli, "Design and implementation of a harmony-search-based variable-strength t-way testing strategy with

constraints support," Information and Software Technology, vol. 54, pp. 553-568, 2012.

5. Nasser, Y. A. Alsariera, K. Z. Zamlifll, and B. Al—Kazcmi, "Late acceptance hill climbing based strategy for addressing constraints

within combinatorial test data generation," 2014.

6. K. Alazzawi, H. M. Rais, and S. Basri, "Artificial Bee Colony Algorithm for t-Way Test Suite Generation," in 2018 4th International

Conference on Computer and Information Sciences (ICCOINS), 2018, pp. 1-6.

7. A. A. Alsewari, A. K. Alazzawi, T. H. Rassem, M. N. Kabir, A. A. B. Homaid, Y. A. Alsariera, et al., "ABC Algorithm for Combinatorial

Testing Problem," Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 9, pp. 85-88, 2017.

8. K. Alazzawi, A. A. B. Homaid, A. A. Alomoush, and A. A. Alsewari, "Artificial Bee Colony Algorithm for Pairwise Test Generation,"

Journal of Telecommunication, Electronic and Computer Engineering (JTEC), vol. 9, pp. 103-108, 2017.

9. Y. A. Alsariera and K. Z. Zamli, "A real-world test suite generation using the bat-inspired t-way strategy," presented at the In the 10th

Asia Software Testing Conference (SOFTEC2017), 2017.

10. Y. A. Alsariera, H. S. Alamri, and K. Z. Zamli, "A Bat-Inspired Testing Strategy for Generating Constraints Pairwise Test Suite,"

presented at the The 5th International Conference on Software Engineering & Computer Systems (ICSECS), 2017.

11. Y. A. Alsariera, A. Nasser, and K. Z. Zamli, "Benchmarking of Bat-inspired interaction testing strategy," International Journal of

Computer Science and Information Engineering (IJCSIE), vol. 7, pp. 71-79, 2016.

12. Y. A. Alsariera and K. Z. Zamli, "A bat-inspired strategy for t-way interaction testing," Advanced Science Letters, vol. 21, pp. 2281-2284,

2015.

13. Y. A. Alsariera, M. A. Majid, and K. Z. Zamli, "Adopting the bat-inspired algorithm for interaction testing," presented at the The 8th

edition of annual conference for software testing, 2015.

14. Y. A. Alsariera, M. A. Majid, and K. Z. Zamli, "SPLBA: An interaction strategy for testing software product lines using the Bat-inspired

algorithm," in Software Engineering and Computer Systems (ICSECS), 2015 4th International Conference on, 2015, pp. 148-153.

15. Y. A. Alsariera, M. A. Majid, and K. Z. Zamli, "A bat-inspired Strategy for Pairwise Testing," ARPN Journal of Engineering and Applied

Sciences, vol. 10, pp. 8500-8506, 2015.

16. J. Stardom, Metaheuristics and the search for covering and packing arrays: Simon Fraser University, 2001.

17. R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proceedings of the sixth international symposium on

micro machine and human science, 1995, pp. 39-43.

18. D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Technical report-tr06, Erciyes university, engineering

faculty, computer engineering department2005.

19. K. M. Passino, "Biomimicry of bacterial foraging for distributed optimization and control," IEEE control systems, vol. 22, pp. 52-67,

2002.

20. D. Karaboga and B. Akay, "A survey: algorithms simulating bee swarm intelligence," Artificial Intelligence Review, vol. 31, pp. 61-85,

2009.

21. X. Yan, Y. Zhu, and W. Zou, "A hybrid artificial bee colony algorithm for numerical function optimization," in Hybrid Intelligent

Systems (HIS), 2011 11th International Conference on, 2011, pp. 127-132.

22. M. S. Kıran and M. Gündüz, "A novel artificial bee colony-based algorithm for solving the numerical optimization problems,"

International Journal of Innovative Computing, Information & Control, vol. 8, pp. 6107-6121, 2012.

23. Z. N. Alqattan and R. Abdullah, "A comparison between artificial bee colony and particle swarm optimization algorithms for protein

structure prediction problem," in International Conference on Neural Information Processing, 2013, pp. 331-340.

24. Yilmaz, M. B. Cohen, and A. A. Porter, "Covering arrays for efficient fault characterization in complex configuration spaces," IEEE

Transactions on Software Engineering, vol. 32, pp. 20-34, 2006.

25. M. B. Cohen, P. B. Gibbons, W. B. Mugridge, and C. J. Colbourn, "Constructing test suites for interaction testing," in Software

Engineering, 2003. Proceedings. 25th International Conference on, 2003, pp. 38-48.

26. M. Cohen, S. R. Dalal, J. Parelius, and G. C. Patton, "The combinatorial design approach to automatic test generation," IEEE software,

vol. 13, pp. 83-88, 1996.

27. A W. Williams, Software component interaction testing: Coverage measurement and generation of configurations: University of Ottawa

(Canada), 2002.

28. K. Z. Bell and M. A. Vouk, "On effectiveness of pairwise methodology for testing network-centric software," in Information and

Communications Technology, 2005. Enabling Technologies for the New Knowledge Society: ITI 3rd International Conference on, 2005,

pp. 221-235.

29. K. J. Nurmela, "Upper bounds for covering arrays by tabu search," Discrete applied mathematics, vol. 138, pp. 143-152, 2004.

214-222

35. Authors: Qotadeh Saber, Huda Ibrahim, Mawarny Md. Rejab

Paper Title: Establishing Technology for Smart City Development in Jordan’s Amman-King Hussain Business Park

Abstract: Global ever-increasing population and fast urbanization have created many problems. Many studies

have identified smart city development as a vibrant solution to the problem. Review of the existing studies

signified that smart cities’ development have many models and dimensions. However, this study explored and

identified technology-based smart city development model, given the fact that technology is regarded as an enabler

that can connect physical distances in a many way, which consequently creates opportunities for quickened social

and economic practices for people. This study used grounded theory because there no stander for smart city

development framework. This study applies semi-structured interviews with 30 government officials, policy

makers and regulators in several trips to the field to saturate categories. The result revealed the category

“establishing technology” describing how Jordan’s Amman, King Hussein Business Park(KHBP) is a blend of

technology-based dimensions: technology infrastructure, smart facilities, international IT companies, and

applications.Based on this result, technology could be considered a crucial process to achieve smart city

development, and the discovery of new technology promotes technology infrastructure, smart facilities, and

applications which could be facilitated by international IT companies. Overall, this study generates a model that

could be tagged “a technology-based smart city development dimensions” which could be examined and adopted

by future study.

Keywords: Smart City Development, technology, smart facilities, grounded theory, Jordan

References: 1. Alawadhi, S., Aldama-Nalda, A., Chourabi, H., Gil-Garcia, J. R., Leung, S., Mellouli, S., & Walker, S. (2012, September). Building

understanding of smart city initiatives. In International Conference on Electronic Government (pp. 40-53). Springer Berlin Heidelberg.

2. Albino, V., Berardi, U., &Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban

Technology, 22(1), 3-21.

3. Albino, V., Berardi, U., &Dangelico, R. M. (2015). Smart cities: Definitions, dimensions, performance, and initiatives. Journal of Urban

Technology, 22(1), 3-21.

4. Alnsour, J. A. (2016). Managing urban growth in the city of Amman, Jordan. Cities, 50, 93-99.

5. Appelman, J. H., Osseyran, A., &Warnier, M. (Eds.). (2013). Green ICT & Energy: From smart to wise strategies. CRC Press.

6. Barrionuevo, J. M., Berrone, P. &Ricart, J. E. (2012). Smart Cities, Sustainable Progress. IESE Insight, 14, 50-57.

7. Bifulco, F., Tregua, M., Amitrano, C. C., &D'Auria, A. (2016). ICT and sustainability in smart cities management. International Journal

of Public Sector Management.

8. Bossaerts, P. L., Frydman, C., & Ledyard, J. (2014). The speed of information revelation and eventual price quality in markets with

insiders. Review of Finance, 18(1), 1-22.

9. Charmaz, K. (1990). ‘Discovering chronic illness: using grounded theory. Social science & medicine, 30(11), 1161-1172.

10. Charmaz, K., & Belgrave, L. L. (2015). Grounded theory. The Blackwell encyclopedia of sociology. America: John Wiley & Sons, Ltd.

11. Chourabi, H., Nam, T., Walker, S., Gil-Garcia, J. R., Mellouli, S., Nahon, K. & Scholl, H. J. (2012, January). Understanding smart cities:

An integrative framework. In System Science (HICSS), 2012 45th Hawaii International Conference on (pp. 2289-2297). IEEE.

12. Cocchia, A. (2014). Smart and digital city: a systematic literature review. In Smart city. Springer International Publishing. 13-43.

13. Creswell, J. W. (1998). Qualitative Inquiry and Research Design: Choosing Among Five Traditions. Thousand Oaks, CA: Sage. J. M.

Corbin and A. Strauss, “Grounded theory research: Procedures, canons, and evaluative criteria, Qualitative sociology, vol. 13, no. 1, pp.

3–21, 1990.

14. Da Cruz, N. F., & Marques, R. C. (2014). Scorecards for sustainable local governments. Cities, 39, 165- 170.

15. Desouza, K. C., &Flanery, T. H. (2013). Designing, planning, and managing resilient cities: A conceptual framework. Cities, 35, 89-99.

16. DOI: 10.1002/9781405165518.wbeosg070.pub2Abuhmaid, A. (2011). ICT training courses for teacher professional development in

Jordan. TOJET: The Turkish Online Journal of Educational Technology, 10(4).

17. Eger, J. M. (2009). Smart Growth, Smart Cities, and the Crisis at the Pump A Worldwide

18. Fassam, L., Copsey, S. and Gough, A. (2015) Network Northamptonshire: total transport smart city procurement theoretical framework

for sustainable economic and social change. In: 8th European Conference on ICT 4 Transport Logistics: Intelligent Logistics Solutions - a

Catalyst for Digital Economy. France: ECITL. p. 30.

19. King, N., 2004. Using templates in the thematic analysis of the text. In: Cassell, S., Symon, G. (Eds.), Essential Guide to Qualitative

Methods in Organizational Research. Sage Publications, London, pp. 256–270.

20. Komninos, N., Pallot, M., &Schaffers, H. (2013). Special issue on smart cities and the future internet in Europe. Journal of the Knowledge

Economy, 4(2), 119-134.

21. Kourtit, K., Macharis, C., & Nijkamp, P. (2014). A multi-actor multi-criteria analysis of the performance of global cities. Applied

Geography, 49, 24-36.

22. Kramers, A., Höjer, M., Lövehagen, N., &Wangel, J. (2014). Smart sustainable cities–Exploring ICT solutions for reduced energy use in

cities.Environmental modelling & software, 56, 52-62.

23. Lazaroiu, G.C., &Roscia, M. (2012). Definition methodology for the smart cities model. Energy, 47(1), 326-332.

24. Meaton, J. &Alnsour, J. (2012) Spatial & Environmental Planning Challenges in Amman, Jordan. Planning Practice & Research, 27(3),

376–386.

25. Morandi, C., & Rolando, A. (2016). How Can ICTs Be Drivers of Spatial Innovation? Urban Digital Nodes for the Smart Region Between

Milan and Turin. In from Smart City to Smart Region (pp. 1-18). Springer International Publishing.

26. Obijiofor, L. (2015). New Technologies and the Socioeconomic Development of Africa. In New Technologies in Developing Societies, 19,

50.

27. Phenomenon. I-Ways, Vol. 32(1), 47-53.

28. Pike Research on Smart Cities [dedicates entire section to World sensing]. [Online]. 2011;

Available:http://www.pikeresearch.com/research/smart-cities.

29. Sujata, J., Saksham, S., Tanvi, G., & Shreya (2016). Developing smart cities: An integrated framework. Procedia Computer Science, 93,

902–909.

30. Wakabi, W., &Grönlund, A. (2015). Enhancing Social Accountability through ICT: Success Factors and Challenges. Conference for E-

Democracy and Open Government, 239.

31. Wolfram, M. (2012). Deconstructing smart cities: An intertextual reading of concepts and practices for integrated urban and ICT

development.

32. Zhang, S. (2017). The Role of Information and Communication Technology for Smart City Development in China. Unpublished

Dissertation, Tallinn University of Technology.

223-230

36.

Authors: Olanrewaju Abdus-Samad Temitope, Ahmad Rahayu, MassudiMahmudin

Paper Title: Influencer Selection on Social networks based on Information Requirement and Diffusion Cost

Abstract: Viral marketing is vital to the success of business in this age. Information diffusion on social

networks for viral marketing involves selecting a seed set of influencers (nodes) to be infected which leads to an

activation process in the network with the aim of infecting a maximum number of nodes. The existing models have

selected the influencers based on the node properties (centralities) but do not take into consideration the diffusion

cost in spreading the information. In addition, the influencers are selected without considering the need for

diffusing information. This study proposes a general additive model that uses a tuneable weight on four centralities

in selecting influencers. Our results shed more light on the trade-off between the outreach of information and the

diffusion cost incurred. The results demonstrated that selecting the top influencers using a single metrics is not

necessarily effective when diffusing information. This study also discovered a positive effect in an increase of the

size of the influencers does not always yield an increase in the relative outreach depending on the type of the

network.

Keywords: Social networks, centrality, information diffusion, diffusion cost.

References: 1. M. Lister. (2018). 40 Essential Social Media Marketing Statistics for 2018. Available:

https://www.wordstream.com/blog/ws/2017/01/05/social-media-marketing-statistics

2. A. Guille, H. Hacid, and C. Favre, "Predicting the temporal dynamics of information diffusion in social networks," arXiv preprint

arXiv:1302.5235, 2013.

3. Q. Wang, Y. Jin, S. Cheng, and T. Yang, "ConformRank: A conformity-based rank for finding top-k influential users," Physica A:

Statistical Mechanics and its Applications, vol. 474, pp. 39-48, 2017.

4. Q. Wang, Y. Jin, Z. Lin, S. Cheng, and T. Yang, "Influence maximization in social networks under an independent cascade-based model,"

Physica A: Statistical Mechanics and its Applications, vol. 444, pp. 20-34, 2016.

5. L. Alsuwaidan, "Toward Information Diffusion Model for Viral Marketing in Business," International journal of advanced computer

science and applications, vol. 7, 2016.

6. K. K. Kapoor, K. Tamilmani, N. P. Rana, P. Patil, Y. K. Dwivedi, and S. Nerur, "Advances in social media research: past, present and

future," Information Systems Frontiers, vol. 20, no. 3, pp. 531-558, 2018.

7. A. Sela, D. Goldenberg, I. Ben-Gal, and E. Shmueli, "Active viral marketing: Incorporating continuous active seeding efforts into the

diffusion model," Expert Systems with Applications, vol. 107, pp. 45-60, 2018.

8. F. Morone and H. a. Makse, "Influence maximization in complex networks through optimal percolation:supplementary information,"

Current Science, vol. 93, pp. 17-19, 2015.

9. A. S. T. Olanrewaju and R. Ahmad, "Examining the information dissemination process on social media during the Malaysia 2014 floods

using Social Network Analysis (SNA)," Journal of Information and Communication Technology, vol. 17, pp. 141-166, 2018.

10. S. Peng, Y. Zhou, L. Cao, S. Yu, J. Niu, and W. Jia, "Influence analysis in social networks: a survey," Journal of Network and Computer

Applications, 2018.

11. S. M. H. Bamakan, I. Nurgaliev, and Q. Qu, "Opinion leader detection: A methodological review," Expert Systems with Applications,

2018.

12. W. Chen, L. V. S. Lakshmanan, and C. Castillo, "Information and Influence Propagation in in Social Networks," Synthesis Lectures on

Data Management, 2013.

13. Q. Liu, B. Xiang, E. Chen, H. Xiong, F. Tang, and J. Xu Yu, "Influence Maximization over Large-Scale Social Networks : A Bounded

Linear Approach," in Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge

Management, ed, 2014, pp. 171-180.

14. J. Cheng, L. Adamic, P. A. Dow, J. M. Kleinberg, and J. Leskovec, "Can cascades be predicted?," in Proceedings of the 23rd international

conference on World wide web, ed, 2014, pp. 925-936.

15. M. Gladwell, The tipping point: How little things can make a big difference. Little Brown, 2006.

16. A. Mochalova and A. Nanopoulos, "On The Role Of Centrality In Information Diffusion In Social Networks," in ECIS, 2013, p. 101.

17. Y. Li, M. Qian, D. Jin, P. Hui, and A. V. Vasilakos, "Revealing the efficiency of information diffusion in online social networks of

microblog," Information Sciences, vol. 293, pp. 383-389, 2015.

18. L. Weng, F. Menczer, and Y.-Y. Ahn, "Virality Prediction and Community Structure in Social Networks," Scientific Reports, vol. 3, p.

2522, 2013.

19. S. Pei, L. Muchnik, S. Tang, Z. Zheng, and H. A. Makse, "Exploring the complex pattern of information spreading in online blog

communities.," PloS one, vol. 10, p. e0126894, 2015.

20. S. Pei, L. Muchnik, J. Andrade, S. José, Z. Zheng, and H. A. Makse, "Searching for superspreaders of information in real-world social

media," Scientific Reports, vol. 4, pp. 1-12, 2014.

21. S. Pei and H. A. Makse, "Spreading dynamics in complex networks," Journal of Statistical Mechanics: Theory and Experiment, vol. 2013,

p. P12002, 2013.

22. X. Chen, G. Song, X. He, and K. Xie, "On Influential Nodes Tracking in Dynamic Social Networks," arXiv preprint arXiv:1602.04490,

pp. 613-621, 2015.

23. J. Goldenberg, B. Libai, and E. Muller, "Using complex systems analysis to advance marketing theory development: Modeling

heterogeneity effects on new product growth through stochastic cellular automata," Academy of Marketing Science Review, vol. 9, pp. 1-

18, 2001.

24. D. Kempe, J. Kleinberg, and T. Eva, "Maximizing the Spread of Influence through a Social Network," in Proceedings of the ninth ACM

SIGKDD international conference on Knowledge discovery and data mining, ed, 2003, pp. 137-146.

25. B. Chang, T. Xu, Q. Liu, and E.-H. Chen, "Study on information diffusion analysis in social networks and its applications," International

Journal of Automation and Computing, pp. 1-26, 2018.

26. M. Heidari, M. Asadpour, and H. Faili, "SMG: Fast scalable greedy algorithm for influence maximization in social networks," Physica A:

Statistical Mechanics and its Applications, vol. 420, pp. 124-133, 2015.

27. Y. Li, J. Fan, Y. Wang, and K.-L. Tan, "Influence maximization on social graphs: A survey," IEEE Transactions on Knowledge and Data

231-245

Engineering, 2018.

28. M. Hosseini-Pozveh, K. Zamanifar, and A. R. Naghsh-Nilchi, "A community-based approach to identify the most influential nodes in

social networks," Journal of Information Science, vol. 43, no. 2, pp. 204-220, 2017.

29. Y. Feng, B. Bai, and W. Chen, "Information diffusion efficiency in online social networks," in IEEE International Conference on Digital

Signal Processing (DSP), 2015, ed, 2015, pp. 1138-1142.

30. F. Stonedahl, W. Rand, and U. Wilensky, "Evolving viral marketing strategies," Proceedings of the 12th Annual Conference on Genetic

and Evolutionary Computation, pp. 1195-1202, 2010.

31. N. Agarwal, H. Liu, L. Tang, and P. S. Yu, "Modeling blogger influence in a community," Social Network Analysis and Mining, vol. 2,

pp. 139-162, 2012.

32. Y. Du, C. Gao, Y. Hu, S. Mahadevan, and Y. Deng, "A new method of identifying influential nodes in complex networks based on

TOPSIS," Physica A: Statistical Mechanics and its Applications, vol. 399, pp. 57-69, 2014.

33. J. Hu, Y. Du, H. Mo, D. Wei, and Y. Deng, "A modified weighted TOPSIS to identify influential nodes in complex networks," Physica A:

Statistical Mechanics and its Applications, vol. 444, pp. 73-85, 2016.

34. T. Bian, J. Hu, and Y. Deng, "Identifying influential nodes in complex networks based on AHP," Physica A: Statistical Mechanics and its

Applications, vol. 479, pp. 422-436, 2017.

35. Q. Ma and J. Ma, "Identifying and ranking influential spreaders in complex networks with consideration of spreading probability,"

Physica A: Statistical Mechanics and its Applications, vol. 465, pp. 312-330, 2017.

36. J. L. Iribarren and E. Moro, "Affinity Paths and Information Diffusion in Social Networks," Social Networks, vol. 33, pp. 134-142, 2011.

37. A. Kupavskii, A. Umnov, G. Gusev, and P. Serdyukov, "Predicting the Audience Size of a Tweet.," in ICWSM 2013 International

Conference on Weblogs and Social Media, ed, 2013, pp. 693-696.

38. Y. Lim, A. Ozdaglar, and A. Teytelboym, "A simple model of cascades in networks.," Technical report, LIDS, 2015. 6. 2, 7.1., 2015.

39. A. Pérez-Foguet, R. Giné-Garriga, and M. I. Ortego, "Compositional data for global monitoring: The case of drinking water and

sanitation," Science of the total environment, vol. 590, pp. 554-565, 2017.

40. M. Velasquez and P. T. Hester, "An analysis of multi-criteria decision making methods," International Journal of Operations Research,

vol. 10, no. 2, pp. 56-66, 2013.

41. G.-H. Tzeng and J.-J. Huang, Multiple attribute decision making: methods and applications. Chapman and Hall/CRC, 2011.

42. R. A. Irizarry, "Additive Models , GAM , and Neural Networks," in Statistical Learning: Algorithmic and Nonparametric Approaches, ed:

John Hopkins University, 2006, pp. 210-245.

43. L. Lü, D. Chen, X.-L. Ren, Q.-M. Zhang, Y.-C. Zhang, and T. Zhou, "Vital nodes identification in complex networks," Physics Reports,

vol. 650, pp. 1-63, 2016.

44. D. J. Watts and P. S. Dodds, "Influentials, networks, and public opinion formation.," Journal of consumer research, vol. 34, pp. 441-458,

2007.

45. J. R. Lee and C. W. Chung, "A fast approximation for influence maximization in large social networks," in Proceedings of the companion

publication of the 23rd international conference on World wide web companion, ed: International World Wide Web Conferences Steering

Committee, 2014, pp. 1157-1162.

46. H. Zhang, D. T. Nguyen, H. Zhang, and M. T. Thai, "Least Cost Influence Maximization Across Multiple Social Networks," IEEE/ACM

Transactions on Networking, pp. 1-11, 2015.

47. Z. Wang, E. Chen, Q. Liu, Y. Yang, Y. Ge, and B. Chang, "Maximizing the Coverage of Information Propagation in Social Networks,"

presented at the International Joint Conference on Artificial Intelligence, 2015.

48. C. T. Li, Y.-J. Lin, and M.-Y. Yeh, "Forecasting participants of information diffusion on social networks with its applications,"

Information Sciences, vol. 422, pp. 432-446, 2018.

49. J. Leskovec and K. Andrej, "Stanford Large Network Dataset Collection," SNAP Datasets, 2014.

50. J. R. Lee and C. W. Chung, "A query approach for influence maximization on specific users in social networks," IEEE Transactions on

Knowledge and Data Engineering, vol. 27, pp. 340-353, 2015.

37.

Authors: Suresh K. Kaliappan, Ahmer A. Siyal, Zakaria Man, Mark Lay, Rashid Shamsuddin

Paper Title: Application of Organic Additives as Pore Forming Agents for Geopolymer Composites

Abstract: Geopolymer is a relatively new type of material derivable from aluminosilicate precursors such as

fly-ash, clays and mining slags is often regarded as a green material. The structure of geopolymer consists of a

negatively charged aluminosilicate network where the charge balancing cations (Na+, K+, or Ca2+) can be

exchanged from solution, therefore offers adjustable properties. Due to its porosity, geopolymer is a good

adsorbent material. The porosity can be enhanced using pore forming agents, however research in this field

remains limited. This work investigated the potential of corn oil, waste cooking oil (palm) and starch as organic

pore forming agents (POF) for fly-ash geopolymers to create pores of various size ranges in the matrices.

Highlights of results include pristine geopolymer had a compressive strength of 30.93 MPa, corn oil as PFA

induced the highest porosity of 26.6% with compressive strength of 9.9 MPa, followed by palm oil at 21.3 % and

9.0 MPa and starch at 17.9 % and 20.41 MPa. The pores were combination of voids and tunnels in the composites

as confirmed by SEM.

Keywords: Geopolymer, aluminium, graphite, silica fume.

References: 1. Esther Obonyo , E.K., Uphie C. Melo and Cristina Leonelli Advancing the Use of Secondary Inputs in Geopolymer Binders for

Sustainable Cementitious Composites: A Review. Sustainability, 2011. 3(2): p. 410-423.

2. Tang, Q., et al., Study on synthesis and characterization of ZSM-20 zeolites from metakaolin-based geopolymers. Applied Clay Science,

2016. 129: p. 102-107.

3. Helmut Foll, J.C., and Stefan Frey, Porous and Nanoporous Semiconductors and Emerging Applications. Journal of Nanomaterials, 2006.

Volume 2006: p. Pages 1–10.

4. Badanoiu, A.I., et al., Preparation and characterization of foamed geopolymers from waste glass and red mud. Construction and Building

Materials, 2015. 84: p. 284-293.

5. Obradović, N., et al., Formation of Porous Wollastonite-based Ceramics after Sintering With Yeast as the Pore-forming Agent. Vol. 49.

246-250

2017. 235-246.

6. Shamsuddin, R.M., C.J.R. Verbeek, and M.C. Lay, Settling of Bentonite Particles in Gelatin Solutions for Stickwater Treatment. Procedia

Engineering, 2016. 148: p. 194-200.

7. Böke, N., et al., New synthesis method for the production of coal fly ash-based foamed geopolymers. Construction and Building

Materials, 2015. 75: p. 189-199.

8. Zhang, J., et al., Synthesis of a self-supporting faujasite zeolite membrane using geopolymer gel for separation of alcohol/water mixture.

Materials Letters, 2014. 116: p. 167-170.

9. Alsafi, S., et al., Collapsibility potential of gypseous soil stabilized with fly ash geopolymer; characterization and assessment.

Construction and Building Materials, 2017. 137: p. 390-409.

10. Zhuang, X.Y., et al., Fly ash-based geopolymer: clean production, properties and applications. Journal of Cleaner Production, 2016. 125:

p. 253-267.

11. Bai, C. and P. Colombo, High-porosity geopolymer membrane supports by peroxide route with the addition of egg white as surfactant.

Ceramics International, 2017. 43(2): p. 2267-2273.

12. Rashid, K. and R. Waqas, Compressive strength evaluation by non-destructive techniques: An automated approach in construction

industry. Journal of Building Engineering, 2017. 12: p. 147-154.

13. Krause, F.F., et al., Atomic resolution elemental mapping using energy-filtered imaging scanning transmission electron microscopy with

chromatic aberration correction. Ultramicroscopy, 2017. 181: p. 173-177.

38.

Authors: Abdul Rehman Gilal, Mazni Omar, Ruqaya Gilal, Ahmed Waqas, Sharjeel Afridi, Jafreezal Jaafar

Paper Title: A Decision Tree Model for Software Development Teams

Abstract: Different theoretical personality models for team composition proved to be inconsistent, posing

validity challenges and missing guidance for personnel selection in software development. Due to these impacting

issues, this study has produced a decision tree model for software team composition for effective team

performance. The model is based on personality types (i.e., collected using Myer Briggs Type Indicator (MBTI)),

gender and team role (i.e., only team leader and programmer) to predict team performance (i.e., effective or

ineffective). Experimental data, collected from software engineering students of UniversitiTeknologi Petronas

(UTP) Malaysia, was used to develop and validate the model. In order to develop and validate the model, C4.5

algorithm and 10-fold cross validation methods were used respectively. The results indicate thatJudging-

Perceiving (JP) personality pair isone of the significant attributes to identify the team performance.At the end, the

model was observed acceptable during validation process by obtaining satisfactoryprediction accuracy 70.48%.

Keywords: Team composition; decision tree; Personality; MBTI

References: 1. R. Gilal, J. Jaafar, M. Omar, S. Basri, and A. Waqas, “A Rule-Based Model for Software Development Team Composition: Team Leader

Role with Personality Types and Gender Classification,” Inf. Softw. Technol., vol. 74, pp. 105–113, 2016.

2. R. R. Nelson, “IT Project Management: Infamous Failures, Classic Mistakes, and Best Practices,” MIS Q. Exec., vol. 6, pp. 67–78, 2007.

3. L. F. Capretz and F. Ahmed, “Making Sense of Software Development and Personality Types,” IT Prof., vol. 12, no. February, pp. 6–13,

2010.

4. M. Omar and S.-L. Syed-Abdullah, “Identifying Effective S oftware Engineering ( SE ) Team Personality Types Composition using

Rough Set Approach,” in IEEE, 2010, pp. 1499–1503.

5. A. R. Gilal, J. Jaafar, L. F. Capretz, M. Omar, S. Basri, and I. A. Aziz, “Finding an effective classification technique to develop a software

team composition model,” J. Softw. Evol. Process, vol. 30, no. 1, 2018.

6. S. B. Kotsiantis, “Supervised Machine Learning: A Review of classification Techniques,” in Supervised Machine Learning: A Review of

classification Techniques, 2007, pp. 249–268.

7. A.R. Gilal, J. Jaafar, M. Omar, and M. Z. Tunio, “Impact of Personality and Gender Diversity on Software Development Teams’

Performance,” in International Conference on Computer, Communication, and Control Technology (I4CT 2014), 2014, no. 2014 IEEE

2014, pp. 261–265.

8. E. M. Trauth, “Theorizing gender and information technology research,” Encycl. Gend. Inf. Technol., vol. 2, pp. 1154–1159, 2006.

9. J. E. Stake and H. Eisele, “Gender and personality.,” Handb. Gend. Res. Psychol. Vol 2 Gend. Res. Soc. Appl. Psychol., pp. 19–40, 2010.

10. F. S. Khan, R. M. Anwer, O. Torgersson, and G. Falkman, “Data mining in oral medicine using decision trees,” World Acad. Sci. Eng.

Technol., vol. 37, pp. 225–230, 2008.

11. D. Braha and A. Shmilovici, “On the use of decision tree induction for discovery of interactions in a photolithographic process,” IEEE

Trans. Semicond. Manuf., vol. 16, pp. 644–652, 2003.

12. S. Y. Lee, S. Kim, S. S. Kim, S. J. Cha, Y. K. Kwon, B. R. Moon, and B. J. Lee, “Application of Decision Tree for the Classification of

Antimicrobial Peptide,” Genomics Inform., vol. 2, pp. 121–125, 2004.

13. N. Fang and J. Lu, “Work in progress - A decision tree approach to predicting student performance in a highenrollment, high-impact, and

core engineering course,” in Proceedings - Frontiers in Education Conference, FIE, 2009.

14. N. T. Nghe, P. Janecek, and P. Haddawy, “A comparative analysis of techniques for predicting academic performance,” Proc. - Front.

Educ. Conf. FIE, p. T2G7-T2G12, 2007.

15. Q. A. Al-Radaideh, A. A. Ananbeh, and E. M. Al-Shawakfa, “A classification model for predicting the suitable study track for school

students,” Int. J. Res. Rev. Appl. Sci, vol. 8, no. 2, pp. 247–252, 2011.

16. H. Witten, E. Frank, and M. a Hall, Data Mining: Practical Machine Learning Tools and Techniques (Google eBook). 2011.

17. A. R. Gilal, J. Jaafar, S. Basri, M. Omar, and A. Abro, “Impact of software team composition methodology on the personality preferences

of Malaysian students,” in 2016 3rd International Conference on Computer and Information Sciences, ICCOINS 2016 - Proceedings,

2016.

18. Jaafar, A. R. Gilal, M. Omar, S. Basri, I. Abdul Aziz, and M. H. Hasan, “A Rough-Fuzzy Inference System for Selecting Team Leader for

Software Development Teams,” in Advances in Intelligent Systems and Computing, vol. 661, Springer, Cham, 2017, pp. 304–314.

19. R. Gilal, J. Jaafar, S. Basri, M. Omar, and M. Z. Tunio, “Making Programmer Suitable for Team-Leader: Software Team Composition

Based on Personality Types,” in International Symposium on Mathematical Sciences & Computing Research (iSMSC) 2015 (iSMSC’ 15),

2015.

20. X. Wu, V. Kumar, Q. J. Ross, J. Ghosh, Q. Yang, H. Motoda, G. J. McLachlan, A. Ng, B. Liu, P. S. Yu, Z. H. Zhou, M. Steinbach, D. J.

251-255

Hand, and D. Steinberg, “Top 10 algorithms in data mining,” Knowl. Inf. Syst., vol. 14, pp. 1–37, 2008.

21. E. B. Hunt, J. Marin, and P. J. Stone, “Experiments in induction.,” 1966.

22. R. Quinlan, “Discovering Rules by Induction from large collections of examples,” in Expert Systems in the micro-electronic age, 1979,

pp. 168–201.

23. J. R. Quinlan, “C4. 5: Programming for machine learning,” Morgan Kauffmann, p. 38, 1993.

24. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Trees, vol. 19. 1984.

25. R. Kohavi, “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection,” Int. Jt. Conf. Artif. Intell., vol. 14,

pp. 1137–1143, 1995.

26. Hubert and S. Engelen, “Fast cross-validation of high-breakdown resampling methods for PCA,” Comput. Stat. Data Anal., vol. 51, pp.

5013–5024, 2007.

27. B. Myers, M. H. McCaulley, N. L. Quenk, and A. L. Hammer, MBTI manual: A guide to the development and use of the Myers-Briggs

Type Indicator, vol. 3. Consulting Psychologists Press Palo Alto, CA, 1998.

39.

Authors: Salah Mortada, Azham Hussain

Paper Title: The Evaluation of EMGS Mobile Application: Users Experience

Abstract: There is an increase in advancement of mobile applications as of late. This makes the usability

assessment of these mobile applications an essential feature in the extent and application of innovative expertise.

In this paper, an evaluation on usability of EMGS application utilizing 20 users who performed 5 assignments on

the EMGS mobile application. A survey with administering questionnaires was distributed to operators to view

their perception on how easy they find the EMGS application. The findings show that users are pleased with the

EMGS mobile application. All the usability factors such as perceived efficiency, ease of use, usefulness and user

satisfaction, reveals that users enjoy the experience they have with the mobile application.

Keywords: EMGCS APP, Mobile Application, Usability Testing

References: 1. A. Hussain, E. O. C. Mkpojiogu, and F. M. Kamal, “A Systematic Review on Usability Evaluation Methods for M-Commerce Apps,” J.

Telecommun. Electron. Comput. Eng., vol. 8, no. February 2017, pp. 29–34, 2016.

2. E. O. C. Mkpojiogu, N. L. Hashim, and R. Adamu, “Observed Demographic Differentials in User Perceived Satisfaction on the Usability

of Mobile Banking Applications,” Proc. Knowl. Manag. Int. Conf. 2016, no. August, pp. 263–268, 2016.

3. A. Hussain, E. O. C. Mkpojiogu, and F. Hassan, “Usability dimensions and sub-dimensions for the evaluation of m-learning apps for

children: A systematic review,” J. Teknol. (Sciences Eng., 2018.

4. É. De Technologie and S. Université, “THE STATE OF THE ART OF MOBILE APPLICATION USABILITY EVALUATION Fatih

Nayebi , Jean-Marc Desharnais , Alain Abran,” Electr. Comput. Eng. (CCECE), 2012 25th IEEE Can. Conf., pp. 1–4, 2012.

5. A. Hussain, E. O. C. Mkpojiogu, and Z. Hussain, “Usability evaluation of a web-based health awareness portal on smartphone devices

using ISO 9241-11 model,” J. Teknol., vol. 77, no. 4, pp. 1–5, 2015.

6. A. Hussain and E. O. C. Mkpojiogu, “The effect of responsive web design on the user experience with laptop and smartphone devices,” J.

Teknol., vol. 77, no. 4, pp. 41–47, 2015.

7. C. M. Wang and C. H. Huang, “A study of usability principles and interface design for mobile e-books,” Ergonomics, vol. 58, no. 8, pp.

1253–1265, 2015.

8. J. Teknologi, A. Hussain, and E. O. C. Mkpojiogu, “an Application of the Iso/Iec 25010 Standard in the Quality-in-Use Assessment of an

Online Health Awareness System 1.0 Introduction,” J. Teknol., vol. 77, no. 5, pp. 2180–3722, 2015.

9. H. Hoehle and V. Venkatesh, “Research Article Mobile Application Usability : Conceptualization,” MIS Q., vol. 39, no. 2, pp. 435–472,

2015.

10. A. Hussain, E. O. Mkpojiogu, S. Mortada, and W. S. Yue, “Mobile Experience Evaluation of an e-Reader App,” J. Telecommun. Electron.

Comput. Eng., vol. 10, no. 10, pp. 11–15, 2018.

11. A. Hussain, E. O. C. Mkpojiogu, J. Musa, and S. Mortada, “A user experience evaluation of Amazon Kindle mobile application,” AIP

Conf. Proc., vol. 1891, 2017.

12. Al-Hijaj Asaad Abdul-Kareem, Jabbar Ayad Mohammed and Kh Hayder Naser, “Design and Developing Online Iraqi Bus Reservation

System By Using Unified Modeling Language,” Int. J., vol. 2, no. 3, pp. 2305–1493, 2013.

13. A. Behler and B. Lush, “Are you ready for E-readers?,” Ref. Libr., vol. 52, no. 1, pp. 75–87, 2011.

14. R. Budiu and J. Nielsen, “Ipad app and website usability: research findings a year after launch,” Nielsen Norman Gr., pp. 1–116, 2011.

15. A. M. M. Habbal, S. Hassan, and A. M. Jabbar, “JDNA: JAVA-BASED NS-2 ANALYZER,” Wulfenia J., vol. 19, no. 9, 2012.

16. D. Z. and B. Adipat, “Challenges, Methodologies, and Issues in the Usability Testing of Mobile Applications,” Int. J. Human- Comput.

Interact., vol. 120, no. 1, pp. 146–152, 2009.

17. H. N. Khraibet, A. H. Mousa, and M. Shahbani, “Intelligent Iraqi Health System ( Iihs ) Using Online Analytical Process ( Olap ) Model,”

Proc. 4th Int. Conf. Comput. Informatics, ICOCI, no. 072, pp. 201–207, 2013.

18. G. Golovchinsky, “Reading in the office,” Proceeding 2008 ACM Work. Res. Adv. large Digit. B. Repos. - BooksOnline ’08, p. 21, 2008.

19. D. Rubin, J., & Chisnell, Handbook of Usability Testing, Second Edition: How to Plan, Design, and Conduct Effective Tests, vol. 17, no.

2. 2008.

20. N. Ahmad, M. W. Boota, and A. H. Masoom, “Smart Phone Application Evaluation with Usability Testing Approach,” J. Softw. Eng.

Appl., vol. 07, no. 12, pp. 1045–1054, 2014.

21. A. Zaman and M. Bhuiyan, “Usabilty evaluation of the MumIES (Multimodal Interface based Education and Support) system for the

children with special needs in Bangladesh,” Int. Conf. Informatics, Electron. Vision, ICIEV 2014, pp. 1–4, 2014.

22. M. Shahbani and H. N. Khraibet, “GRADUATE ENTREPRENEUR ANALYTICAL REPORTS (GEAR) USING DATA WAREHOUSE

MODEL: A CASE STUDY AT CEDI, UNIVERSITI UTARA MALAYSIA (UUM).,” Proc. 3rd Int. Conf. Comput. Informatics, ICOCI,

pp. 8–9, 2011.

23. R. Gafni, “Usability Issues in Mobile-Wireless Information Systems.,” Issues Informing Sci. Inf. Technol., vol. 6, pp. 754–769, 2009.

24. Y. S. Ryu, “Development of Usability Questionnaires for Electronic Mobile Products and Decision Making Methods,” Ind. Syst. Eng., no.

July, 2005.

256-260

40.

Authors: Abdulhamza A.Hussain A.karim

Paper Title: Computation & Control of Transient Voltages in Power System using Laplace Transform

Abstract: With the recent developments and improvements in Extra High Voltage (EHV), circuit breakers, 261-265

over voltages caused by energisation or de-energisation of lines can be made so low that the limiting factor

determining the reduction in the line insulation might be considered the overvoltage produced by single line-to-

ground faults. On lines insulated for levels below twice the normal line-to-ground crest voltage, such faults could

develop into double line-to-ground faults, which would be particularly objectionable if single-pole switching were

to be employed. This paper presents a mathematical analysis of transient due to fault initiation at any point on the

double circuit Extra High Voltage transmission system, using the Fast Fourier Transform technique.

Keywords: EHV transmission lines, Transient over voltages, Line-to-ground faults, Fast Fourier Transform.

References: 1. A. Clerici, and A. Tashini," Overvoltage due to line energisation and re-energisation versus overvoltages caused by faults and fault clearing

in EHV systems", IEEE Trans., vol. PAS 89, 1970, pp 932-939.

2. M. Sanaye – Pasand, M.R. Dadashzadeh and M. Kholayar, " Limltation of transmission line switching overvoltages using switchsync

relays ", Proc.Int. Conf. On Power systems Transients, Monteral, Canada, 2006, paper 87.

3. A. Hayati Soloot, A. Gholami, G. Agheb, A. Ghorbandaeipour, and P. Mokhtari, " Investigation of Transmission Line Overvoltages and

their Deduction Approach ", world Academy of Science, Engineering and Technology, 29, 2009.

4. E.W. Kimbark, and A.C. Legate, "Fault surges versus switching surges a study of transient overvoltages caused by line-to-ground faults",

Ibid, vol. PAS-87, 1968, pp 1762-1769.

5. B. Gustavsen, J. Mahseredjian, " Simulation of Internal voltages on Transmission Lines by an Extended Method of Characteristics

Approach " IEEE Trans. Power Delivery, vol.22, pp 1736-1742, July, 2007.

6. M. S. Mamis and M. Kksal," Computational of transmission line transients by using Fast Inverse Laplace Transform", Mathematical and

Computational Applications, vol. 2, no. 2, 1997, pp 61-69.

7. A. Ametanti," The application of Fast foruier transform to electrical transmission phenomena", Int. J. Elect. Educ., vol. 10, 1973, pp 277-

287.

8. L. M. Wedepohl, and S.E.T. Mohammaed," Multi conductor transmission lines theory of natural modes and Fourier integral applied to

transient analysis", Proc. IEE, 116, No. 9, 1969.

9. R. Malasubramanian and S. Gupta," Calculation of transient due to fault initiation on a double-circuit transmission lines" Proc. IEE, vol.

123, no. 6, 1976, pp 537-542.

10. A. T. Johns and R. K. Aggarawal, "Fault induced overvoltages on double-circuit EHV transmission lines" IEEE, Winter meeting, N. Y. ,

Feb. ,1978.

11. R. H. Galloway," Calculation of electrical parameters for short and long polyphase transmission lines". Ibid, vol. Pas. 111, 1964, no. 12, pp

2051-2059.

41.

Authors: Syamim Jaafar, Nor Aini Salleh, Morni Kaspin, Noraimi Abdullah

Paper Title: Measuring Validity and Reliability of the instrument on Property Manager’s Competencies in

Managing Green Office Building

Abstract: The property management profession has expanded in parallel with the current technological

revolution. The green building development in Malaysia has giving property management play an important part as

to sustain the "greenness" of green building for its whole life cycle. However, the research on the property

manager's competencies in managing green building is rarely done. Hence, the instrument is new construction and

need to test the validity and reliability to prove the originality and accuracy of the construct. Thus, this paper

presents the reliability and validity of the property manager's knowledge, skill, ability, and other characteristics.

Fifty-Six items are identified and validated by three expert property manager who experiences in managing green

office building. Then, a survey was conducted among property manager who currently manage green office

building at Penang, Perak and Kelantan area. A non-random sample of 15 property managers was selected. The

results found the level reliability using Cronbach Alpha index for each construct are 0.916 (knowledge), 0.911

(skill), 0.888 (ability), 0.867 (other characteristics). It believes the findings on validity and reliability of

instruments are promising an essential competencies needed by the property manager in managing the green

building.

Keywords: property manager, competencies, green office building, validity and reliability

References: 1. Aghili, N., Abdul Hakim, M., & Sheau-ting, L. (2016). Key Practice for Green Building Management In Malaysia. MATEC Web of

Conferences, 40, 1–5.

2. Alwin, D. F. (2007). Margins of Error: A Study of Reliability of Survey Measurement. Hokoben, New Jersey: John Wiley & Sons, Inc.

3. Bennett, R., Wallace, J., & Williamson, I. (2008). Organising Land Information for Sustainable Land Administration. Land Use Policy,

25(1), 126–138. https://doi.org/10.1016/j.landusepol.2007.03.006

4. Bernsen, P., Segers, M., & Tillema, H. H. (2009). Learning Under Pressure: Learning Strategies, Workplace Climate, and Leadership

Style in The Hospitality Industry. International Journal of Human Resources Development and Management, 9(4), 358.

5. Boyatzis, R. E. (1982). The Competent Manager: A Model for Effective Performance. John Wiley & Sons.

6. Brown, S. (2010). Likert Scale Examples for Surveys. Iowa State University, 1–4.

7. Chouhan, V. S., & Srivastava, S. (2014). Understanding Competencies and Competency Modeling ― A Literature Survey. IOSR Journal

of Business and Management, 16(1), 14–22.

8. Clark, E., & Hinxman, L. (2009). Developing A Framework of Competencies For Facilities Management. Facilities, 17(7/8), 246–252.

9. Dawes, J. (2008). Do Data Characteristics Change According to the Number of Scale Points Used? An Experiment Using 5-Point, 7-Point

and 10-Point Scales. International Journal of Market Research, 50(1), 61–104.

10. Delmas, M. A., & Pekovie, S. (2012). Environmental Standards and Labor Productivity: Understanding the Mechanisms That Sustain

Sustainability. Journal of Organizational Behavior, 30(8), 1151–1163. https://doi.org/10.1002/job.617

11. Donellan, J. (1998). Educational Requirements For Management-Level Positions in Shopping Centers. Journal of Shopping Center

Research.

12. Friedman, L., & Fleishman, E. A. (1992). Cognitive And Interpersonal Abilities Related To The Primary Activities Of R & D Managers.

Journal of Engineering and Technology Management, 9, 211–242.

266-273

13. GBI. (2017). Executive Summary of Green Building Index 2017.

14. Gurjit, S. (1996). Property Management in Malaysia. Federal Publication Sdn. Bhd.

15. Hammersley, C. H., & Tynon, J. F. (1998). Job competency analyses of the entry-level resort and commercial recreation professionals.

Journal of Applied Recreation Research, 23(3), 225–41.

16. Heale, R., & Twycross, A. (2015). Validity and reliability in quantitative studies. CrossMark, 18(3), 66–67. https://doi.org/10.1136/eb-

2015-102129

17. Hertzog, M. A. (2008). Considerations in Determining Sample Size for Pilot Studies. Research in Nursing & Health, 31(4), 341–354.

https://doi.org/10.1002/nur

18. Hoffmann, T. (2008). The meanings of competency. Journal of European Industrial Training, 23(6), 275–285.

19. Howe, J. C., & Gerrard, M. B. (2012). The Law of Green Buildings: Regulatory and Legal Issues in Design, Construction, Operations, and

Financing. Natural Resources & Environment, 27(2), 1–2.

20. Hwang, B., & Ng, W. J. (2013). Project Management Knowledge and Skills for Green Construction : Overcoming Challenges.

International Journal of Project Management, 272–284. https://doi.org/10.1016/j.ijproman.2012.05.004

21. Izran Sarrazin, M., Nurul Nadiah, Z., Shardy, A., Neo Bee, W., & Nur Aqlima, R. (2014). Critical Factors That Lead To Green Building

Operations And Maintenance Problem In Malaysia. Theoretical and Empirical Researches in Urban Management, 9(2), 68–86.

22. Johnson, G. A., & Brooks, G. P. (2010). Initial scale development: Sample size for pilot studies. Educational and Psychological

Measurement, 70(3), 394–400.

23. Johns, R. (2010). Likert Items and Scales, 1(March), 1–11.

24. Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert Scale : Explored and Explained. British Journal of Applied Science &

Technology, 7(4), 396–403.

25. Kay, C., & Moncarz, E. (2004). Knowledge, Skills, and Abilities for Lodging Management. Cornell Hotel and Restaurant Administration

Quarterly, 45(3), 285–298.

26. Lo, K. K., Hui, E. C., & Zhang, K. V. (2014). The Benefits of Sustainable Office Buildings in the People's Republic of China (PRC):

Revelation of Tenants and Property Managers. Journal of Facilities Management, 12(4), 337–352. https://doi.org/10.1108/JFM-10-2012-

0048

27. Loqman, M. A. A., Asmoni, M. N. A., & Shaari, N. (2017). Exploring Competencies for Green Building Project Manager. Internal

Journal of Real Estate Studies, 11(3).

28. Mansfield, R. S. (1996). Building competency models: Approaches for HR Professionals. Human Resource Management, 35(1), 7–18.

29. Mariah, A., Hakim, M. A., Maimunah, S., & Shahril, A. R. M. (2014). Requisite Facilities Management Competencies for Sustainable

Development at Higher Education Institutions. Journal of Sustainability Science and Management, 9(2), 71–89.

30. McClelland, D. C. (1973). “Testing for competence rather than for ‘intelligence’ ”: Reply. American Psychologist, 29(1), 59–59.

https://doi.org/10.1037/h0038240

31. Miller, N. G., Pogue, D., Saville, J., & Tu, C. (2010). The Operations and Management of Green Buildings in the United States. Of

Sustainable Real Estate, Vol. 2, No. 1, 2(1).

32. Miller, N., Pogue, D., Gough, Q., & Davis, S. (2009). Green Buildings and Productivity. The Journal of Sustainable Real Estate, 1(1), 65–

89. Retrieved from

33. Mirabile, R. (1997). Everything You Wanted To Know About Competency Modelling. Training & Development, 51(8), 73–77.

https://doi.org/10.1038/299285a0

34. Mohd Zaki, A., Nor’ Aini, Y., & Shardy, A. (2012). Exploring Malaysia Mall Manager’s KSAOs. Procedia-Social and Behavior Sciences,

62, 144–158. https://doi.org/10.1016/j.sbspro.2012.09.024

35. Mohmad, M. D., Othman, M. Y., & Syed Ahmad Qusoiri, S. A. K. (2008). Model Kompetemsi Pengurus Projek Awam: Mengenal Pasti

Kompetensi Yang Kritikal Untuk Jurutera Daerah Jabatan Kerja Raya Malaysia.

36. Parry, S. B. (1996). The Quest for Competencies. Training, 33, 48–54,56.

37. Pheng, L. S., & Lee, S. H. S. (1993). The effectiveness of the Managing Agent: Property Management and Maintenance. Facilities, 11(9),

5–15.

38. Polit, D. F., & Beck, C. T. (2006). The Content Validity Index: Are You Sure You Know What’s Being Reported? Critique and

Recommendations. Research in Nursing & Health, 31(4), 341–354. https://doi.org/10.1002/nur

39. Poon, J., & Brownlow, M. (2014). Competency Expectations For Property Professionals In Australia. Journal of Property Investment &

Finance, 32(3), 256–281.

40. Raja Mazyani, R. M., & Abdul Hakim, M. (2015). Facilities Management Relevant Competencies for Malaysian Public School. Jurnal

Teknologi (Science & Engineering), 2, 73–78.

41. Rajadurai, J. (2010). Speaking English and the Malay Community: The struggle for Participation and the Negotiation of Identities.

Indonesia and the Malay World, 38(111), 289–301.

42. Razali, M. N., Kamarudin, N., Zainuddin, A. Z., & Othman, S. H. (2015). Green property management for commercial buildings, 168,

133–143. https://doi.org/10.2495/SD150121

43. Revilla, M. A., Saris, W. E., & Krosnick, J. A. (2014). Choosing the Number of Categories in Agree-Disagree Scales. Sociological

Methods and Research, 43(1), 73–97. https://doi.org/10.1177/0049124113509605

44. Ruban, A. (2016). Property Managers Must be More Proactive, Forum Told. Malaymail Online, pp. 1–2. Retrieved from

www.themalaymailonlin.com/print/malaysia/property-managers-must-be-more-proactive-forum-told

45. Sangoseni, O., Hellman, M., & Hill, C. (2013). Development and Validation of a Questionnaire to Assess the Effect of Online Learning

on Behaviors, Attitudes, and Clinical Practices of Physical Therapists in the United States Regarding Evidenced-based Clinical Practice.

The Internet Journal of Allied Health Sciences and Practice, 11(2), 1–12.

46. Sekaran, U. (2003). Research Methods For Business - A Skill Building Approach (Fourth Edi). United State of America: John Wiley &

Sons.

47. Shenkel, W. M. (1980). Modern Real Estate Principles (Revised ed). Irwan-Dorsey.

48. Siciliano, G., Tutterow, V., & de Los Reyes, P. (2013). Recommendations on Job-Specific Knowledge and Skill Areas for Energy

Management System Implementation in Industry and Commercial Buildings: Results from a Global Superior Energy Performance Multi-

Country Analysis. ACEEE Summer Study on Energy Efficiency in Industry, 1–12.

49. Smallwood, J., Sauntson, D., Short, D., Cranfield, P., & EERE. (2008). Green Building Management Toolkit. Better Building Partnership.

50. Spencer, L. M., & Spencer, S. M. (1993). Competence at Work : Models for Superior Performance. John Wiley & Sons, 1–372.

51. Syamim, J., & Aini, S. N. (2017). A Review of Property Manager ’ s Competency in Managing Green Building. Malaysian Journal of

Sustainable Environment (MySE), 3(2), 1–29.

52. Szu-Fang, C. (2013). Essential Skills for Leadership Effectiveness in Diverse Workplace Development. Online Journal for Workforce

Education and Development, 6(1).

53. Tajuddin, A. J. A. (2015). A Malaysian Professional Communication Skills in English Framework for English for Occupational Purposes

Courses. Ph.D. Thesis. The University of Nottingham.

54. Tas, R. F., Labrecque, S. V, & Clayton, H. R. (1996). Property-Management Competencies for Management Trainees, 90–96.

55. Thorncrof, M. (1965). Principles of Estate Management. London: Estate Gazette, Ltd.

56. Ulrich, D., Brockbank, W., Yeung, A. K., & Lake, D. G. (1995). Dave Ulrich, Wayne Brockbank, Arthur K. Yeung, and Dale, 34(4), 473–

495.

57. Woodruffe, C. (1993). What Is Meant by a Competency? Leadership & Organization Development Journal, 14(1), 29–36.

https://doi.org/10.1108/eb053651

58. Zarita, A. B., Hwa, T. K., & Sharuzaman, M. S. (2016). A Competency Framework for the Property Management Industry. Environment-

Behaviour Proceedings Journal, 4(1), 27–30.

42.

Authors: Nur Amierah Harun, Asmalia Che Ahmad, Faridah Ismail, Siti Akhtar Mahyuddin

Paper Title: Potential Supply and Demand of Construction Waste in Secondary Market

Abstract: The Issue Of Construction Waste Disposal Management Has Recently Gained Widespread

Attention. It Is Critical To Perform The Sustainable Construction Waste Management And Waste Minimization Is

The Best Strategies In Managing It. Optimization Of Waste Minimization Strategy Can Produced A Large Amount

Of Secondary Material Supply. This Supply Can Be Used To Stimulate Local Industry Activity Such As Reuse

And Recycling Business. Therefore, This Paper Aim To Investigate The Potential Supply And Demand For

Construction Waste In Secondary Market. Secondary Industries, Non-Governmental Support And Incentives

Dominates The Ranking Of The Potential Supply And Demand Element. Without These Supply And Demand

Influential Factors, Valuable Construction Waste Will Never Be Marketable And The Material Life-Cycle Will

End At The Landfill. It Is Expected That The Potential Supply And Demand Will Be Practical In The Secondary

Market Development.

Keywords: Construction waste, secondary market, supply and demand

References: 1. Marie, I. and Quiasrawi, H. (2012). Closed-loop recycling of recycled concrete aggregates. Journal of Cleaner Production, 37, 243-248.

2. Tam, V. W. Y. (2011). “Rate of Reusable and Recyclable Waste in

3. Construction”. The Open Waste Management Journal, 4(1), 28-32.

4. Gambin, N., Leo, C. and Rahman, A. (2010). Management of C & D Waste. Journal of Environmental Research and Development, 5(1),

96-104.

5. Oyenuga, A. A., Bhamidiarri, R. &Naoum, S. G. (2015). Challenges in Managing Construction and Dmolition Waste. Journal of Solid

Waste Technology and Management.

6. Jereme, I. A., Siwar, C. &MahmudulAlam, M. (2015). Waste Recycling in Malaysia: Transition from Developing to Developed Country.

Indian Journal of Education and Information Management, 4(1).

7. Brennan, J., Ding, G., Wonschik, C. R. &Vessalas, K. (2014). A Closed-loop System of Construction and Demolition Waste Recycling.

The 31st International Symposium on Automation and Robotics in Construction and Mining, 499-505.

8. Macozoma, D. S. (2010). Secondary Construction Materials Markets: Where We Are and the Way Forward. Pretoria, South Africa.

9. Mohd Nasir, S. R., Othman, N. H., Mat Isa, C. M. &Che Ibrahim, C. K. (2015). The Challenges of Construction Waste Management in

Kuala Lumpur. Journal of Technology, 115-119.

10. Department of Sustainable, Environment, Water, Population and Communities (2012). Construction and Demolition Waste Guide-

Recycling and Re-use Across the Supply Chain. Australian Government. Canberra.

11. Akintoye, A. (2000). Analysis of Factor Influencing Project Cost Estimating Practice. Journal of Construction Engineering and

Management, 18(1), 77-89.

12. Berawi, M. A., Berawi, A. R. B. &Hadwart, K. A. (2012). African Journal of Business Management, 6(5), 1932-1944.

13. Hiete, M., Stengel, J., Ludwig, J. &Schultmann, F. (201). Matching Construction and Demolition Waste Supply to Recycling Demand: A

Regional Management Chain Model. Building Research and Information, 39(4), 333-351.

14. The Flemish Construction Confederation (2018).

274-277

43.

Authors: Kartina Alauddin, UmamahSakinah Mamat, Ani SaifuzaAbd Shukor

Paper Title: Knowledge Management Implementation in Consulting Firms: An Investigation in Quantity Surveying

Profession

Abstract: In construction Industry, Quantity Surveying (QS) profession has been identified as a one of

significant team members who provides expert advice and professional knowledge to clients. However, the nature

of construction project teams works as disparate collection of separate organizations, the project teams especially

QS suffers to getting integration from other members. It still contributed to an unwillingness to share knowledge

between them, resulting to cause a poor knowledge flow internal and external of QS firms. This study is aimed at

investigating the implementation of Knowledge Management (KM) in QS profession with a view to creating KM

practice in QS firms in Klang Valley. A questionnaire survey was used as the data collection instruments. Data

collected were analysed using frequency, percentage and Mean score. The findings showed that the QS aware to

the knowledge management application in the firm. In addition, The KM roles in sharing the knowledge were

developed thoroughly in the firms. Effectiveness in KM also has been achieved. The study concludes that KM

activities have a positive influence on knowledge creation, knowledge storage and knowledge transfer. The study

recommends that this research should cover to the other area in Malaysia.

Keywords: knowledge management, Quantity Surveying, implementation, consulting firms

References: 1. AgopSarkisSarkisyan, E. and Marinova, N. (2003). Intellectual and Knowledge Based Assets of the Organizations and Contemporary

Technologies for Their Management. In: International Conference on Computer Systems and Technologies - CompSysTech’2003.

2. Alauddin, K., London, K and Maqsood, T., (2012), The Development of an Intellectual Capital Project Success Framework, Third

International Conference on Construction in Developing

3. Atapattu, C. and Senaratne, S. (2013), A Tool For Effective Transferring Of Knowledge And Technology in Contracting

Organizations- dl.lib.mrt.ac.lk

4. Bakri, AS, Ingirige, MJB and Amaratunga, RDG 2010, Key issues for implementing knowledge management in relational contracting

project settings , in: CIB 2010, 10th – 13th May 2010, University of Salford

5. Bhojaraju, G. (2005). Knowledge Management: Why Do We Need It For Corporate.

278-285

6. Malaysian Journal of Library & Information Science, 10(2), pp.37-50.

7. Bratianu, C. (2010). A critical analysis of the Nonaka’s model of knowledge dynamics.pp.115--120.

8. Chen, L. and Mohamed, S. (2013), Impact of Organizational Cultural Factors on Knowledge Management in Construction, The Joint

International Conference on Construction, Culture, Innovation and Management (CCIM), The British University in Dubai, The

Conference Centre, Knowledge Village, Dubai.

9. Cheng, L.Y and Yun, L.H. (2011), Developing Project Communities of Practice- Based Knowledge Management System in Construction,

Automation in Construction, pp 422-432

10. Davis, R., Watson, P. and Man, C.L.(2007), Knowledge Management For The Quantity Surveying Profession, Strategic Integration of

Surveying Services FIG Working Week 2007 Hong Kong SAR, China 13-17 May 2007, pp 1-6

11. Fadhilah, M.N. and Egbu C. (2010), An Insight Into Knowledge Sharing Practices in Quantity Surveying Firms in Malaysia, Procs 26th

Annual ARCOM Conference, 6-8 September 2010, Leeds, UK, Association of Researchers in Construction Management, pp

779-788

12. Frost, A. (2014). Knowledge Management Tools. [online] Knowledge-management- tools.net. Available at: http://www.knowledge-

management-tools.net/ [Accessed 17 July 2014].

13. Hey, J. (2004). The Data, Information, Knowledge, Wisdom chain : The Metaphorical Link. Intergovernmental Oceanographic

Commission

14. Irani, Z. (2005), Management of Knowledge in Project Environment, Elsevier Butterworth-Heinemann, pp 103-131

15. Koenig, M.E.D (2012), What is KM? Knowledge Management Explained, KM World Magazine. Online : http://www.kmworld.com.

Accessed : 18th March 2014

16. Ly, E, Anumba, C J and Carrillo, P M (2005) Knowledge Management Practices of Construction Project Managers. In: Khosrowshahi, F

(Ed.), 21st Annual ARCOM Conference, 7-9 September 2005, SOAS, University of London. Association of Researchers in Construction

Management, Vol. 1, 517-26.

17. Maarouf, R. (2011). Quantity surveying role in construction projects-a comparison of roles in Sweden and the UK.

18. Martensson, M. (2000), A Critical Knowledge Management as A Managemnet Tool, Journal of Knowledge Management 4(3), pp 204-216

19. Mohajan, H (2016): Knowledge is an Essential Element at Present World. International Journal of Publication and Social Studies , Vol. 1,

No. 1: pp. 31-51.

20. Muzani, M., Fara, D.M., Mohd, S. M. and Syamsul, H.M (2012), Exploiting Intranet Technology In Facilitating Knowledge Management

Among Quantity Surveying’s Consulting Firms, 2012 IEEE Colloqium on Humanities, Science and Engineering Research (CHUSER

2012), December 3-4,2012,Kota Kinabalu,Sabah, pp 341- 345

21. Nonaka, I. (1997). Organizational Knowledge Creation, Knowledge Advantage Conference, November 11-12

22. Patrick, .S.W.F. and Sonia K.Y.C. (2006), A Framework of Knowledge Processes For Professional Quantity Surveying Firms in

Hong Kong, Joint International Conference on Computing and Decision Making in Civil and Building Engineering June 14-16, 2006 -

Montréal, Canada, pp 268- 277

23. Senaratne, S. and Sabesan, S. (2008), Managing Knowledge as Quantity Surveyors : An Exploratory Case Study in Sri Lanka, Built

Environment 8(2), pp 41-46

24. Smith, E. (2001). The Role Of Tacit And Explicit Knowledge In The Workplace. Journal of knowledge Management, 5(4),

pp.311 321.

25. Stuhlman, Daniel D. Knowledge management terms. Chicago, Stuhlman Management Consutants, 2012. Available at

:http://home.earthlink.net/~ddstuhlman/defin1.htm [Accessed 17 Jul. 2014].

26. Sveiby, K. E., (1997), The New Organisational Wealth: Managing and Measuring Knowledge-Based Assets, San Francissco, Berret

Koehler

27. Thayaparan, Menaha&Siriwardena, Mohan &Amaratunga, Dilanthi&Malalgoda, Chamindi&Keraminiyage, Kaushal. (2011). Lifelong

Learning And The Changing Role Of Quantity Surveying Profession, 15th Pacific Association of Quantity Surveyors Congress, 23-26

July, Colombo, Sri Lanka

44.

Authors: Nur Azfahani Ahmad, Asmalia Che Ahmad, Hugh Byrd, Nur Huzeima Hussain

Paper Title: Establishing Solar Village Communities in Malaysia towards a Self-Sufficient Electricity Lifestyle: The

Feasibility Study

Abstract: The application of solar PV in rural Malaysia, especially for the village communities are still at its

early stages due to the system’s high cost and limited access on the technology. Moreover, the widespread access

to conventional electricity generated from fossil fuels resulted in greater dependent on electricity and the

appliances that it powers. The situation has now changed as the resources to produce electricity cannot be

sustained and may create energy insecurity issue in the near future. This paper will try to identify whether solar

PVs can practically supplement the grid electricity supply to rural communities towards establishing a more self-

sufficient electricity lifestyles. The objective of this study is to allow village communities to gain benefit from this

technology. Through a case study and feasibility study, the potential of supplementing households’ electricity

needs are identified. It is found that through Community-Based Approach mechanism, village communities can

have the opportunity to access solar electricity and become resilient if there will be any energy insecurity issues in

the future.

Keywords: Community-based approach, photovoltaic, solar electricity, self-sufficient electricity, rural

communities.

References: 1. Shafie, S.M., et al., Current energy usage and sustainable energy in Malaysia: A review. Renewable and Sustainable Energy Reviews,

2011. 15(9): p. 4370-4377.

2. KeTTHA, National Energy Balance 2011 Malaysia, G.T.a.W. Ministry of Energy, Editor 2012, KeTTHA: Kuala Lumpur. p. 65.

3. Ahmad, N.A., et al., Solar Village in Malaysia – A Route Map for Financing Mechanism. MATEC Web Conf., 2016. 66: p. 00057.

4. Alam, S.S., et al., A Survey on Renewable Energy Development in Malaysia: Current Status, Problems and Prospects. 2016. 17(1): p. 5.

5. Kardooni, R., S.B. Yusoff, and F.B. Kari, Barriers to Renewable Energy Development: Five Fuel Policy in Malaysia. Energy &

Environment, 2015. 26(8): p. 1353-1361.

6. Selamat, S., and A. Abidin, C. Z, Renewable Energy and Kyoto Protocol: Adoption in Malaysia. 2010.

7. Jalal, T.S. and P. Bodger. National Energy Policies and the electricity sector in Malaysia. in Energy and Environment, 2009. ICEE 2009.

3rd International Conference 2009.

8. Ahmad, N.A. and H. Byrd. Power from the People: The Empowerment of Distributed Generation of Solar Electricity for Rural

286-290

Communities in Malaysia. in The Asian Conference on Sustainability, Energy and the Environment 2013. 2013. Osaka, Japan: ACSEE.

Ahmad, N.A. and H. Byrd, Empowering Distributed Solar PV Energy For Malaysian Rural Housing: Towards Energy Security And

Equitability Of Rural Communities. International Journal of Renewable Energy Development (IJRED), 2013. 2(1): p. 59-68.

9. Matthewman, S. and H. Byrd, Blackouts: a sociology of electrical power failure Social Space (Przestrzeń Społeczna), 2014.

10. Epstein, J., Thailand Suffers Power Outage, Leading Many to Question What Happened to Its Power Protection Plan, in Power

Protection2013, Technology Marketing Corp: US. p. 3.

11. Romero, J.J., Blackouts illuminate India's power problems. IEEE Spectrum, 2012. 49(10): p. 11-12.

12. Oh, T.H., S.Y. Pang, and S.C. Chua, Energy policy and alternative energy in Malaysia: Issues and challenges for sustainable growth.

Renewable and Sustainable Energy Reviews, 2010. 14(4): p. 1241-1252.

13. Byrd, H., The Potential of PVs In Developing Countries: Maintaining An Equitable Society In The Face Of Fossil Fuel Depletion, in

International Conference on Environment 2010, USM, Editor 2010, USM: Penang.

14. Rahman Mohamed, A. and K.T. Lee, Energy for sustainable development in Malaysia: Energy policy and alternative energy. Energy

Policy, 2006. 34(15): p. 2388-2397.

15. Fayaz, H., et al. Solar energy policy: Malaysia vs developed countries. in Clean Energy and Technology (CET), 2011 IEEE First

Conference 2011.

16. TNB. Pricing and Tariff. 2016 [cited 2016 2 Sept]; Available from: http://www.tnb.com.my/residential/pricing-tariffs.

17. Muhammad-Sukki, F., et al., An evaluation of the installation of solar photovoltaic in residential houses in Malaysia: Past, present, and

future. Energy Policy, 2011. 39(12): p. 7975-7987.

18. Bosch Energy, Bosch Solar Energy AG Solar Panel Price, 2010.

19. MBIPV. PV System Cost. 2011; Available from: http://www.mbipv.net.my/content.asp?zoneid=4&categoryid=12.

20. Brumback, E., Utility co-op offers community-based approach to access solar energy, in MiBiz2013: Michigan.

21. Musall, F.D. and O. Kuik, Local acceptance of renewable energy—A case study from southeast Germany. Energy Policy, 2011. 39(6): p.

3252-3260.

22. Iler, S., Assessing The Potential For Community Solar in Durham, North Carolina in the Nicholas School of the Environment2012, Duke

University: North Carolina.

23. Frame, D., et al. A community based approach for sustainable off-grid PV systems in developing countries. in Power and Energy Society

General Meeting, 2011 IEEE. 2011.

24. Westmill. Westmill Solar Coop. 2013 [cited 2014 19 Feb 2014]; Available from: http://www.westmillsolar.coop/.

25. JFS. Japanese NPO Starts Residential Solar Co-Ownership Project. Energy 2012; Available from:

http://www.japanfs.org/en/pages/031892.html.

26. SolarShare. Invest in a Brighter Future. 2013 [cited 2014 19 Feb 2014]; Available from: http://www.solarbonds.ca/.

27. Martinot, E., No Rooftop Left Behind, in Solar Journal2014: UK.

28. PowerGen. Micro Grids. 2014 17/7/2014]; Available from: http://powergen-renewable-energy.com/micro-grids/.

29. UBBL, Uniform Building By-laws, 1984 [G.N. 5178/85] (as at 10th November 1994). 1994, Kuala Lumpur: International Law Book

Services,

30. Legal Research Board of Malaysia,.

31. Haw, L.C., K. Sopian, and Y. Sulaiman. Public Response to Residential Building Integrated

32. Photovoltaic System (BIPV) in Kuala Lumpur Urban Area. in the 4th IASME / WSEAS International Conference on ENERGY &

ENVIRONMENT (EE'09). 2009. Cambridge, UK.

33. Ahmad, N.A. and H. Byrd. Photovoltaics in Malaysia: Challenges and Strategies Towards Resilient Rural Areas in Malaysia. in

International Malaysia-Auckland Research Conference (iMARCA 2012). 2012. Auckland: The University of Auckland.

34. Fadzil, S.F.S. and H. Byrd, Energy and Building Control Systems in The Tropics. 2012, Penang, Malaysia: USM.

35. HSM. How to Make Money From Home Solar Energy 2013 [cited 9 Dec 2013; Available from: http://www.homesolarmalaysia.com/.

36. EcoDirect. 4000 Watt Micro Inverter Solar Panel Kit. 2014 14/07/2014]; Available from: http://www.ecodirect.com/4kW-Micro-Inverter-

Solar-Panel-Kit-p/eco-4000w-micro.htm.

37. Mahmud, A.M. Evaluation of the solar hybrid system for rural schools in Sabah, Malaysia. in Power and Energy (PECon), 2010 IEEE

International Conference on. 2010.

45.

Authors: Siti Sarah Januri, Zulkifli Mohd Nopiah, Ahmad Kamal Ariffin Mohd Ihsan, Nurulkamal Masseran,

Shahrum Abdullah

Paper Title: The Analysis of Fatigue Lifetime using Markov Chain Model based on Randomization Paris Law

Equation

Abstract: The experimental data of fatigue crack growth scatter even under identical experimental conditions,

including constant amplitude loading. Thus, it is important to take into account the data scatter of crack growth

rates by using statistical approach analysis. In this study, the distribution of the fatigue crack growth life was

estimated using Markov chain approach based on the modified Paris law equation to consider the variability in the

growth of the fatigue crack. In this regard, in the Markov Chain model, the Paris law equation was integrated with

the probability distribution of the initial crack length to calculate the probability transition matrix. The result shows

that the initial probability distribution was represented by lognormal distribution and it can be said that the initial

crack will happen only in state 1 and state 2. The consideration of probability distribution into Paris law equation

to represent the physical meaning of fatigue crack growth process. The fatigue life estimation using the Markov

chain model are found to be agreed well with experimental results and the value of R2 showed the model is good.

The results provide a reliable prediction and show excellent agreement between proposed model and experimental

result. This indicates that the model can be an effective tool for safety analysis of structure.

Keywords: Fatigue crack growth, Markov Chain model, probability distribution, randomization Paris law

equation

References: 1. Alkhateb, H., Al-Ostaz, A., & Alzebdeh, K. I. (2009). Developing a stochastic model to predict the strength and crack path of random

composites. Composites Part B: Engineering, 40(1), 7–16. http://doi.org/10.1016/j.compositesb.2008.09.001

291-295

2. Anderson, K. V, & Daniewicz, S. R. (2018). Statistical analysis of the in fl uence of defects on fatigue life using a Gumbel distribution.

International Journal of Fatigue, 112(August 2017), 78–83. http://doi.org/10.1016/j.ijfatigue.2018.03.008

3. Becker, T. L., Cannon, R. M., & Ritchie, R. O. (2002). Statistical fracture modeling: Crack path and fracture criteria with application to

homogeneous and functionally graded materials. Engineering Fracture Mechanics (Vol. 69). http://doi.org/10.1016/S0013-

7944(02)00047-4

4. Castro, I. T. (2011). A periodic inspection and replacement policy for systems subject to competing failure modes due to degradation and

traumatic events. Reliability Engineering & System Safety, 96, 497–508. http://doi.org/10.1016/j.ress.2010.12.018

5. Doh, J., & Lee, J. (2018). Bayesian estimation of the lethargy coefficient for probabilistic fatigue life model. Journal of Computational

Design and Engineering, 5(2), 191–197. http://doi.org/10.1016/j.jcde.2017.10.002

6. Drewniak, J., & Hojdys, L. (2015). The Method of Analysis of Fatigue Crack Growth by Bogdanow-Kozin Model. Machine Dynamics

Research, 39(4), 125–132.

7. Ellyin, F. (1997). Fatigue Damage , Crack Growth and Life Prediction. Chapman & Hall, 2-6 Boundary Row, London SE18HN, UK.

8. Gansted, L., Brincker, R., & Hansen, L. P. (1991). Fracture mechanical Markov chain crack growth model. Engineering Fracture

Mechanics, 38(6), 475–489. http://doi.org/10.1016/0013-7944(91)90097-K

9. He, P., Hong, R., Wang, H., & Lu, C. (2018). Fatigue life analysis of slewing bearings in wind turbines. International Journal of Fatigue,

111(February), 233–242. http://doi.org/10.1016/j.ijfatigue.2018.02.024

10. Januri, S. S., Nopiah, Z. M., Akramin, M., Romlay, M., Kamal, A., & Mohd, A. (2017). Statistical distribution for initial crack and

number of loading in fatigue crack growth process. International Journal of Advanced and Applied Sciences, (x), 1–9.

11. Kocańda, D., & Jasztal, M. (2012). Probabilistic predicting the fatigue crack growth under variable amplitude loading. International

Journal of Fatigue, 39, 68–74. http://doi.org/10.1016/j.ijfatigue.2011.03.011

12. Kozin, F., & Bogdanoff, J. L. (1983). On the probabilistic modeling of fatigue crack growth. Engineering Fracture Mechanics, 18(3), 623–

632. http://doi.org/10.1016/0013-7944(83)90055-3

13. Lan, C., Bai, N., Yang, H., Liu, C., Li, H., & Spencer, B. F. (2018). Weibull modeling of the fatigue life for steel rebar considering

corrosion effects. International Journal of Fatigue, 111(February), 134–143. http://doi.org/10.1016/j.ijfatigue.2018.02.009

14. Le, K., Fouladirad, M., Barros, A., & Levrat, E. (2013). Remaining useful life estimation based on stochastic deterioration models : A

comparative study. Reliability Engineering & System Safety, 112, 165–175. http://doi.org/10.1016/j.ress.2012.11.022

15. Li, B. C., Jiang, C., Han, X., & Li, Y. (2015). A new approach of fatigue life prediction for metallic materials under multiaxial loading.

International Journal of Fatigue, 78, 1–10. http://doi.org/10.1016/j.ijfatigue.2015.02.022

16. Makkonen, M. (2009). Predicting the total fatigue life in metals. International Journal of Fatigue, 31(7), 1163–1175.

http://doi.org/10.1016/j.ijfatigue.2008.12.008

17. Morgantini, M., Mackenzie, D., Comlekci, T., & Van Rijswick, R. (2018). The Effect of Mean Stress on Corrosion Fatigue Life. Procedia

Engineering, 213(2017), 581–588. http://doi.org/10.1016/j.proeng.2018.02.053

18. Rastogi, R., Ghosh, S., Ghosh, A. K., Vaze, K. K., & Singh, P. K. (2016). Fatigue crack growth prediction in nuclear piping using Markov

chain Monte Carlo simulation. Fatigue & Fracture of Engineering Materials & Structures. http://doi.org/10.1111/ffe.12486

19. Sanches, R. F., de Jesus, A. M. P., Correia, J. a. F. O., da Silva, a. L. L., & Fernandes, a. a. (2015). A probabilistic fatigue approach for

riveted joints using Monte Carlo simulation. Journal of Constructional Steel Research, 110, 149–162.

http://doi.org/10.1016/j.jcsr.2015.02.019

20. Wu, W. F., & Ni, C. C. (2003). A study of stochastic fatigue crack growth modeling through experimental data. Probabilistic Engineering

Mechanics, 18(2), 107–118. http://doi.org/10.1016/S0266-8920(02)00053-X

21. Wu, W. F., & Ni, C. C. (2004). Probabilistic models of fatigue crack propagation and their experimental verification. Probabilistic

Engineering Mechanics, 19, 247–257. http://doi.org/10.1016/j.probengmech.2004.02.008

22. Zhou, B. R. R., Serban, N., & Gebraeel, N. (2011). DEGRADATION MODELING APPLIED TO RESIDUAL LIFETIME. The Annals

of Applied Statistics, 5(2), 1586–1610. http://doi.org/10.1214/10-AOAS448

46.

Authors: M. F. Rajemi, M.T Abu Seman

Paper Title: Sustainable Energy Efficiency for MIG Welding Process

Abstract: Sustainable manufacturing emphasizes on the needs of an energy efficient process that optimise

energy consumptions. Reduction in electrical energy consumption will diminish the carbon emission in generating

electricity at the power plant. Welding is one of the most important joining technologies in manufacturing. Metal

Inert Gas Welding (MIG) / Metal Active Gas (MAG) is one of the popular welding processes. In welding, the

process parameters were not set to optimise electrical energy consumption for overall procedure. In this research,

an optimized electrical energy consumption in welding process was determined. This was based on the optimised

welding parameter model. The electrical energy consumed were summarised in a single energy map. This model

produces good quality and energy efficient welding process. With reference to the design of experiments by

Taguchi technique, three parameters which include the current, voltage and wire feed rate were varied to obtain an

optimum energy efficient process and good quality of welding. The electrical energy consumed during the process

were calculated and recorded. The data were used to obtain an optimised electrical energy consumption based on

different welding parameters. The optimized welding parameters were used to develop a suitable welding

parameters model which optimised the electrical energy consumption for the welding process. The reduction of

electrical energy consumption benefits the industries in having to reduce the overall cost of welding process.

Keywords: Sustainable manufacturing, MIG, Electrical energy

References: 1. Erdil, N. O., Aktas, C. B., & Arani, O. M. (2018). Embedding sustainability in lean six sigma efforts. Journal of Cleaner Production, 198,

520-529. doi: https://doi.org/10.1016/j.jclepro.2018.07.048

2. Jogi, B. F., Awale, A. S., Nirantar, S. R., & Bhusare, H. S. (2018). Metal Inert Gas (MIG) Welding Process Optimization using Teaching-

Learning Based Optimization (TLBO) Algorithm. Paper presented at the Materials Today: Proceedings.

3. Lokesh, S., Niresh, J., Neelakrishnan, S., & Rahul, S. P. D. (2018). Optimisation Of Cutting Parameters Of Composite Material Laser

Cutting Process By Taguchi Method. IOP Conference Series: Materials Science and Engineering, 324(1), 012054.

4. Rajemi, M. F., Mativenga, P. T., & Aramcharoen, A. (2010). Sustainable machining: Selection of optimum turning conditions based on

296-300

minimum energy considerations. Journal of Cleaner Production, 18(10-11), 1059-1065. doi: 10.1016/j.jclepro.2010.01.025

47.

Authors: Mohd Hanizun Hanafi, Mohd Umzarulazijo Umar, Mohd Nasrun Mohd Nawi, Siti Nur Fazillah Mohd

Fauzi

Paper Title: Managerial and Technical Perceptions in Decision Making Process of Adaptive Reuse: Malaysian

Heritage Building

Abstract: Adaptive reuse is a process of rebranding heritage buildings without jeopardizing their authentic

values. There is a need for a proper guideline for authorities and private sectors to adaptively reuse a building.

With this in mind, this paper evaluated and compared the perceptions of two groups of stakeholders in the

conservation industry (managerial and technical groups) on the important components that should be taken into

account before an adaptive reuse of a building. Questionnaires containing adaptive reuse projects were sent to the

experts of the groups. The data obtained from the survey were evaluated through a descriptive analysis and t-test

technique using SPSS software. The preliminary findings indicate that physical and technological aspects are two

(2) important components that should be taken into consideration. Apart from that, this report acknowledges these

components from both the managers and technocrats’ point of view. All in all, this study may be used as a

blueprint for the authorities and private sectors in the execution of adaptive reuse of a building. A Good Abstract

Should Consist Of Introduction, Problem Statement, Quantitative Results & Discussion And Quantitative

Conclusion.

Keywords: Highway traffic flow, unmanned aerial vehicle, quadrotor, real time video Keywords Required : 5.

References: 1. Adair, Alastair, Jim Berry, and Stanley McGreal. 2003. “Financing Property’s Contribution to Regeneration.” Urban Studies 40 (5–

6):1065–80. https://doi.org/10.1080/0042098032000074326.

2. Ahmad, A Ghafar. 2006. “The Framework of Historical Building Conservation.” Sejarah@Malaysia, 2006.

http://www.hbp.usm.my/conservation/.

3. Ahmad, A. G. 2009. "Treatment of Rising Damp and Replastering at Heritage Buildings." Paper presented at the Bengkel Bersiri 2009,

Konservasi Bangunan Warisan Siri 2: Lepaan Kapur, Dewan Pusat Pelancongan Negeri Perak, Ipoh, July 17-19

4. Akhtarkavan, M., A. Alikhani, J. Ghiasvand, and H. Akhtarkavan. 2008. "Assessing Sustainable Adaptive Re-Use Of Historical

Buildings." Paper presented at the WSEAS International Conference Proceedings on Cultural Heritage and Tourism (CUHT'2008),

Heraklion, Crete Island, Greece, July 22-24.

5. Ariffin, A. B., M. S. M. Zahari, S. M. Radzi, & M. Z. Kutut. 2017. "Adaptive Reuse of Historical Buildings and Local Residents Actual

Visitation." Journal of Tourism, Hospitality & Culinary Arts (JTHCA) 9 (2): 35-46

6. Anakkayan, Brit, Farid Wajdi, and Nor Hanizaishak. 2013. “The 3 Rd International Building Control Conference 2013 Conservation Plan

for Historic Buildings from Building Control Administration Perspective,” no. 1998.

7. Brundtland, G. H. 1987. Report of the World Commission on Environment and Development:" our Common Future.": Oxford: Oxford

University Press

8. Bullen, Peter, and Peter Love. 2011. “Factors Influencing the Adaptive Re‐use of Buildings.” Journal of Engineering, Design and

Technology 9 (1):32–46. https://doi.org/10.1108/17260531111121459.

9. Bullen, P., and P. Love. 2011a. "Factors Influencing the Adaptive Re-use of Buildings." Journal of Engineering, Design and Technology 9

(1): 32-46.

10. Bullen, P., and P. Love. 2011b. "A New Future for The Past: A Model for Adaptive Reuse Decision-Making." Built Environment Project

and Asset Management 1 (1): 32-44.

11. Bullen, P. A., and P. E. D. Love. 2011c. "Adaptive reuse of heritage buildings." Structural Survey 29 (5): 411-421.

12. Bullen, P. A., and P. E. D. Love. 2010. "The Rhetoric of Adaptive Reuse or Reality of Demolition: Views from the Field." Cities, 27 (4):

215-224. doi: https://doi.org/10.1016/j.cities.2009.12.005

13. Chileshe, N., F. Fester, and T. C. Haupt. 2005. "Desirable Construction Management Skills in the South African Construction Industry:

Methodology for Assessment." In Proceedings of 3rd Postgraduate Conference on Contruction Industry Development, Johannesburg (pp.

9-11).

14. Clark, J. 2013. Adaptive Reuse of Industrial Heritage: Opportunities and Challenges. Melbourne :Heritage Councils of Victoria. Retrieved

on 15 March 2018, from http://heritagecouncil.vic.gov.au

15. Cohen, J. 1988. Statistical Power Analysis for The Behavioral Science. 2nd ed. Hillsdale : Erlbaum Associates.

16. Conejos, Sheila, Craig Langston, and Jim Smith. 2011. “Improving the Implementation of Adaptive Reuse Strategies for Historic

Buildings.” Sustainable Development 52:11. http://epublications.bond.edu.au/sustainable_development/52.

17. Conejos, Sheila, Craig Langston, and Jim Smith. 2013. “AdaptSTAR Model: A Climate-Friendly Strategy to Promote Built Environment

Sustainability.” Habitat International 37. https://doi.org/10.1016/j.habitatint.2011.12.003.

18. Fournier, Donald F, and Karen Zimnicki. 2004. “Integrating Sustainable Design Principles into the Adaptive Reuse of Historical

Properties,” no. May.

19. Ghafar, A., and B. Nurwati. 2003. "Adaptive Re-use for Sustainable Heritage Tourism in Malaysia." Tourism (Zagreb) 51 (2): 205-214.

20. Grammenos, F, and P Russell. 1997. “Building Adaptability: A View from the Future.” In Buildings and the Environment. International

Conference.

21. Hanafi, Mohd Hanizun, Mohd Umzarulazijo Umar, Arman Abdul Razak, and Zul Zakiyudin Abdul Rashid. 2018. “Essential Entities

towards Developing an Adaptive Reuse Model for Organization Management in Conservation of Heritage Buildings in Malaysia.”

Environment-Behaviour Proceedings Journal 3 (7):265. https://doi.org/10.21834/e-bpj.v3i7.1241.

22. Harun, S. N. 2011. “Heritage Building Conservation in Malaysia: Experience and Challenges.” Procedia Engineering 20:41–53.

https://doi.org/10.1016/j.proeng.2011.11.137.

23. Hasbollah, Hasif Rafidee Bin. 2015. “A Conceptual Framework for Conserving Heritage Buildings in Malaysia from the Perspective of

Facilities Management.” International Journal of Economics and Financial Issues 5 (Special Issue):45–51. https://doi.org/10.1108/JFM-

06-2013-0031.

24. Heritage Act. 2005. “National Heritage Act 2005 (Act 645).”

25. Hudson, John, and Philip James. 2007. “The Changing Framework for Conservation of the Historic Environment.” Structural Survey 25

(3/4):253–64. https://doi.org/10.1108/02630800710772836.

26. Ijla, A., and T. Brostrom. 2015. "The Sustainable Viability of Adaptive Reuse of Historic Buildings: The Experiences of Two World

Heritage Old Cities; Bethlehem in Palestine and Visby in Sweden." International Invention Journal of Arts and Social Sciences 2 (4): 52-

66.

27. Ismail, I. R. 2015. Sustainable Development: Issues and Challenges Associate in Malaysia. Centre For Global Sustainability Studies

301-307

(CGSS), USM.

28. Jokilehto, Jukka. 1988. “Conservation Principles And Their Theoretical Background.” Durability of Building Materials.

29. Kalaci, E., and S. Dervishi. 2014. "Implementation Challenges to the Adaptive Reuse of a Heritage Building in Tirana, Albania." Paper

presented at the Proceedings of the 2nd ICAUD International Conference in Architecture and Urban Design, Epoka University, Tirana,

Albania, May 08-10 May.

30. Klein, G. A., R. Calderwood, and D. Macgregor. 1989. "Critical decision method for eliciting knowledge." IEEE Transactions on

Systems, Man, And Cybernetics 19 (3): 462-472.

31. Kamal, Kamarul Syahril, Lilawati Ab Wahab, and Ghafar Ahmad. 2008. “Pilot Survey on the Conservation of Historical Buildings in

Malaysia,” no. Icbedc:104–15. https://doi.org/10.5897/JAERD12.088.

32. Kit, T.E. 2001. National Conservation Legislation in Malaysia. Faculty of Built Environment, University of Malaya, Malaysia.

33. Langston, C., F. K. W. Wong., E. C. M. Hui, and L. Shen. 2008. "Strategic Assessment of Building Adaptive Reuse Opportunities in

Hong Kong." Building and Environment 43 (10): 1709-1718.

34. Langston, Craig. 2012. “Validation of the Adaptive Reuse Potential (ARP) Model Using IconCUR.” Facilities 30 (3/4):105–23.

https://doi.org/10.1108/02632771211202824.

35. Langston, Craig, Francis K.W. Wong, Eddie C.M. Hui, and Li-Yin Shen. 2008. “Strategic Assessment of Building Adaptive Reuse

Opportunities in Hong Kong.” Building and Environment 43 (10):1709–18. https://doi.org/10.1016/j.buildenv.2007.10.017.

36. Louis, C., M. Lawrence, and M. Keith. 2007. Research Methods in Education. New York: Routledge.

37. Malhotra, M. K., and V. Grover. 1998. "An Assessment of Survey Research in POM: From Constructs to Theory." Journal of Operations

Management 16 (4): 407-425.

38. M Feilden, Bernard. 2003. “Conservation of Historic Buildings.” Book.

39. Mısırlısoy, D., and K. Gunce. 2016. "Adaptive Reuse Strategies for Heritage Buildings: A Holistic Approach." Sustainable Cities and

Society 26: 91-98.

40. Mofidi, S M, A M Moradi, M Akhtarkavan, and H Akhtarkavan. 2008. “Assessing Challenges in Developing Sustainable Adaptation

Strategies by Considering Climate Changes.”

41. Mohamed, N., and K. Alauddin. 2016. "The Criteria For Decision Making In Adaptive Reuse Towards Sustainable Development." Paper

presented at the MATEC Web of Conferences, The 4th International Building Control Conference 2016 (IBCC, 2016), Kuala Lumpur,

Malaysia, Mac 7-8.

42. Mohd Umzarulazijo Umar, Mohd Hanizun Hanafi, Normah Abdul Latip. 2015. “Analysis of Non-Destructive Testing of Historic

Building Structures.” Aust. J. Basic & Appl. Sci 9(7) (April 2015):336–320. http://ajbasweb.com/old/ajbas/2015/April/326-330.pdf.

43. Nepravishta, F. 2015. "Industrial Heritage in Albania and the Opportunities for Regeneration and Adaptive Re-use." Journal of

International Academic Research for Multidisciplinary 3(6): 381-391.

44. Osbourn, Derek. 1985. “Introduction to Building.” Procedings of the 1982 Winter Simulation Conference Higland CHao Madrigal

Editors.

45. Pallant, J. 2013. SPSS Survival Manual. UK: McGraw-Hill Education.

46. Pilowtowiez.G. 1995. Eco-Interior: A Guide to Environmentally Conscious Interior Design. New York. John Wiley & Son Inc.

47. Plevoets, B., and K. Van Cleempoel. 2011. “Adaptive Reuse as a Strategy towards Conservation of Cultural Heritage: A Literature

Review.” In WIT Transactions on The Built Environment, 118:155–64. WIT Press. https://doi.org/10.2495/STR110131.

48. Rani, Prihatmanti. 2015. “The Impact of Adaptive Reusing Heritage Building as Assessed by the Indoor Air Quality Case

Study:UNESCO World Heritage Site Penang.” Procedia - Social and Behavioral Sciences 179:297–307.

https://doi.org/10.1016/j.sbspro.2015.02.433.

49. Sanchez, B., and C. Haas. 2018. "A Novel Selective Disassembly Sequence Planning Method for Adaptive Reuse of Buildings." Journal

of Cleaner Production 183: 998-1010.

50. Schmutz, Vaughn, and Michael Elliott. 2016. “Tourism and Sustainability in the Evaluation of World Heritage Sites, 1980–2010.”

Sustainability 8 (3):261. https://doi.org/10.3390/su8030261.

51. Shehada, Ziad M.M., Yahaya Bin Ahmad, Naziaty Mohd Yaacob, and Nila Inangda Manyam Keumala. 2015. “Developing Methodology

for Adaptive Re-Use: Case Study of Heritage Buildings in Palestine.” Archnet-IJAR 9 (2):216–29.

52. Smith, Jim. 2005. “Cost Budgeting in Conservation Management Plans for Heritage Buildings.” Structural Survey 23 (2):101–10.

https://doi.org/10.1108/02630800510593675.

53. Sodangi, Mahmoud, Mohd Faris Khamdi, Arazi Idrus, Dabo B. Hammad, and Abdullahi Ahmedumar. 2014. “Best Practice Criteria for

Sustainable Maintenance Management of Heritage Buildings in Malaysia.” In Procedia Engineering, 77:11–19. Elsevier.

https://doi.org/10.1016/j.proeng.2014.07.017.

54. Sweden, ICOMOS, Central Board of National Antiquities, Swedish National Commission for UNESCO, and Svenska Unescorådet. 1994.

“Information as an Instrument for Protection against War Damages to the Cultural Heritage.” Svenska Unescorådets Skriftserie, 0348-

8705 ; 4/01994 NV - 21 Cm.

55. UNESCO. 2015. “List of Factors Affecting the Properties.” United Nations Educational,

48.

Authors: Mohd WiraMohdShafiei, VignesPonniah, Radzi Ismail, Mohandass Mohan

Paper Title: A Comparison of Criteria between GreenRe and International Green Rating Tools in Green

Construction Projects: A Review

Abstract: The global construction sector are moving towards sustainable development by implementation of

green rating tool to monitor the overall process of construction activities. Existence of green rating tool during the

construction and operation period will significantly reduce the emission of carbon contributed from construction

industry. Besides that monitoring process by the green rating tool for the newly constructed green building also

able to promote the usage of energy saving related technologies during the operation period of the constructed

green building by the end user’s. However despite the advent made for the establishment of green rating tools

globally, not much had been done to determine, review, compare and identify the differences and similarities

between green rating tools. Therefore, the objective of this paper is to compare the GreenRe rating tool to other

international green rating tools. Three international green rating tools, Building Research Establishment

Environmental Assessment Methodology (BREEAM) (UK), Green Star (Australia) and Leadership in Energy and

Environmental Design (LEED) (US) will be compared to Malaysian rating tool, GreenRe. The findings from this

study through the comparison of international and Malaysian rating tool will reveal the rating systems available in

terms of their similarities and differences which will help to improve the effectiveness of green building

assessment methods in Malaysia towards achieving goals of green development in Malaysian construction

industry. Furthermore, research findings in this study will act as a stepping stone to guide the establisher and

assessors of GreenRe to improve the green rating tool system towards perfection in Malaysian green construction

308-312

industry.

Keywords: Green rating tools, sustainable development, Malaysian construction industry

References: 1. Awbi, H. 2010. Basic Concepts for Natural Ventilation of Buildings (https://www.reading.ac.uk/tsbe) retrieved on 12 February 2017

2. Bahaudin, A.Y., Elias, E.M., Saifudin, A.M. 2014. A Comparison of the Green Building’s Criteria(http://www.e3s-conferences.org)

retrieved on 6 January 2017

3. BRE Global Limited. 2011. BREEAM New Construction, Non Domestic Buildings, Technical Manual

(http://www.breeam.org/BreamGeneralPrint/breeam_non_dom_manual_3_0.pdf) retrieved on 10 January 2017

4. Chua, S.C., Oh,T.H. (2011). Green progress and prospect in Malaysia, Renewable and Sustainable Energy Reviews, Vol. 15, pp. 2850–

2861

5. Fine Homebuilding Magazine. 2017. Energy Efficiency Ratio and Seasonal Energy Efficiency Ratio (www.finehomebuilding.com)

retrieved on 14 February 2017

6. GreenReSdn Bhd. 2017. Total Certified Projects (http://www.greenre.org/) retrieved on 10 January 2017

7. GreenReSdn Bhd. 2017. Rating Tool Based on Five Pillars ((http://www.greenre.org/) retrievedon 10 January 2017)

8. Green Building Council of Australia. 2017. (http://new.gbca.org.au/greenstar/ratingsystem/performance) retrieved on 12 January 2017.

9. Green Building Council of Australia. 2013. The Value of Green Star - A Decade of Environmental

Benefits(http://www.gbca.org.au/uploads/194/34754/The_Value_of_Green_Star_A_Decade_of_Environmental_Benefits.pdf) retrieved on

12 January 2017

10. Ho, C.S., Fong W.K. 2007. Planning for Low Carbon Cities. The Case of Iskandar Development Region, Malaysia

(http://eprints.utm.my/6475/) retrieved on 19 September 2012

11. Hong Kong Institute of Architecture (2017). Calculation and Application of OTTV and U-value

(minisite.proj.hkedcity.net/hkiakit/GetResources.html?id=4061) retrieved on 18 September 2017.

12. Leadership in Energy and Environmental Design. LEED. 2017. (http://www.usgbc.org/leed), retrieved on 5 January 2017

13. Parlimen of Australia. 2013. Mandatory Renewable Energy Target

(http://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/Browse_by_Topic/ClimateChange/Govern

ance/Domestic/national/Mandatory, retrieved on 12 January 2013.

14. Singh, M.K., Mahapatra, S., Teller, J. (2013). Study on

15. Indoor Thermal Comfort in the Residential Buildings of Liege,Belgium(https://orbi.ulg. ac.be/ bitstream /2268 /155634 /1/5_si.pdf)

retrieved on 12 September 2017.

49.

Authors: Vignes Ponniah, Mohd Wira Mohd Shafiei, Radzi Ismail, Gunavathy Kanniyapan, Mohandass Mohan

Paper Title: Analysis on Comparison of Factors Influencing the Success of Sustainable Construction

Abstract: Malaysia started to implement several national policies related to sustainable development since

1980’s such as National Energy Policy (1980), National Depletion Policy (1980), Four Fuel Diversification Policy

(1981) and Fifth Fuel Policy (2000). Subsequently, sustainable construction already started to evolve since the

beginning of Eight Malaysia Plan by integration of social, economic and environment. But sustainable

development in Malaysia is still in initial stage as more research and development in terms of facilities and

renewable energy resources are needed. Based on the previous researchers, there are six factors which influenced

the development of sustainable construction. The six factors are factor related to project, factor related to project

manager, factors related to project team, factor related to material and equipment, factors related to client and

factors related external. Furthermore, identification of success factors will eventually leads to development of

theoretical framework of success factors of sustainable construction. The findings from this study through the

identification and comparison of success factors will reveal the weakness and advantages of existing factors and

help to improve the success factors of theoretical framework. This research study uses survey method or

questionnaire for data collection process. There are total of 120 questionnaires distributed to respondents which

consists of contractors in location around Peninsular Malaysia. The research data have been analysed with factor

analysis method using Smart PLS.

Keywords: Critical success factors, sustainable construction, Malaysian construction industry

References: 1. Bahaudin, A.Y., Elias, E.M., Saifudin, A.M.,(2014) A Comparison of the Green Building’s Criteria (http://www.e3s-conferences.org or

http://dx.doi.org/10.1051/e3sconf/20140301015) retrieved on 6 January 2017

2. Bakar, K.A. (2011). Green Technology Readiness in Malaysia: Sustainability for Business Development. International Conference on

Business and Economics Research 2, 1120-1129.

3. BRE Global Limited (2011). BREEAM New Construction, Non Domestic Buildings, Technical Manual

4. (http://www.breeam.org/breeamGeneralPrint/breeam_non_dom_manual_3_0.pdf) retrieved on 10 January 2017

5. Chua, S.C., Oh,T.H. (2011). Green progress and prospect in Malaysia, Renewable and Sustainable

6. Energy Reviews, Vol. 15, pp. 2850– 2861

7. Fornel, C., and Lacker, D.F. (1981). Evaluating Structural Equation Model with Unobservable Variables and Measurement Error. Journal

of Marketing Research, 18(1), 39-50.

8. GreenRe Sdn Bhd (2017) Total Certified Projects http://www.greenre.org/) retrieved on 10 January 2017

9. GreenRe Sdn Bhd (2017) Rating tool based on five pillars ((http://www.greenre.org/) retrieved on 10 January 2017)

10. Green Building Council of Australia (2017). (http://new.gbca.org.au/green-star/rating-system/performance) retrieved on 12 January 2017

11. Green Building Council of Australia (2013). The Value of Green Star - A Decade of Environmental Benefits

(http://www.gbca.org.au/uploads/194/34754/The_Value_of_Green_Star_A_Decade_of_Environmental_Benefits.pdf) retrieved on 12

January 2017

12. Hair, J.F.J., Black, W., Babin, B., Anderson, R.E., & Tatham (2006). Multivariate Data Analysis. New Jersey. Pearson Education.

13. Ho, C.S., Fong W.K. (2007). Planning for Low Carbon Cities. The Case of Iskandar Development Region, Malaysia

(http://eprints.utm.my/6475/) retrieved on 19 September 2012

14. Leadership in Energy and Environmental Design (LEED) (2017). (http://www.usgbc.org/leed), retrieved on 5 January 2017

313-321

15. Parlimen of Australia (2013), Mandatory Renewable Energy Target,

16. (http://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/Browse_by_Topic/ClimateChange/Govern

ance/Domestic/national/Mandatory, retrieved on 12 January 2017

17. Peter, J. P., & Churchill, G. A. (1986). Relationships among Research Design Choices and Psychometric Properties of Rating Scales.

Journal of Marketing Research, 23(1), 1–10.

18. Puvanasvaran, A.P., Zain, M.F.Y., Al-Hayali, Z.A., & Mukapit, M. (2012). Sustainability of Green Technology in Malaysia Industry.

International Conference on Design and Concurrent Engineering 1, 160-165.

19. Rossiter, J. R. (2002). The C-OAR-SE Procedure for Scale Development in Marketing. International Journal of Research in Marketing,

19(1), 305 – 335.

20. Wold, H. (1981). The Fix‐Point Approach to Interdependent Systems: Review and Current Outlook in H. Wold (Ed.), The Fix‐Point

Approach to Interdependent Systems. Amsterdam. North‐Holland Publication.

50.

Authors: Andi Ardillah Rahman, Ridwan M. Thaha, Suriah

Paper Title: Implementation of GBSD Program Strategy (Clearance Drainage Movement) towards Community

Behaviour in Flood Preventation in Makassar City

Abstract: The aim of this study is to determine GBSD program implementation toward community in

Makassar city. This study used qualitative research with case study approach and was conducted from April to

May 2016 in Gowa district at Public Works Office of Makassar city, Buloa sub district, Tallo sub district and

Maradekaya sub district. Data collection was done by in-depth interview and focus discussion group (FGD) from

executor, chairman and secretary of GBSD program, community and community leaders. The socialization had

been done to community about GBSD program through mass communication, media and interpersonal

communication. The sufficient in human resource also contributed in GBSD program implementation whereas the

lack in financial resource is not affected in GBSD program implementation. Besides, the skill in implementing

agency and understanding standard of operations (SOP) also contributed in GBSD program success. The

community knowledge and attitude also help in program implementation. The community had maintained drainage

system cleanliness even though they had no knowledge of GBSD program. The community’s actions toward

GBSD program had maintained the drainage system cleanliness but there is still waste and rubbish in the drainage

system.

Keywords: Community behaviour; flood preventation; GBSD strategies; implementation

References: 1. Pustaka.pu.go.id - Kementerian Pekerjaan Umum dan ... [Internet]. [Cited 2016Jan29]. Available from: http://pustaka.pu.go.id/

2. Mahardy AI. Analisis Dan Pemetaan Daerah Rawan Banjir Di Kota Makassar Berbasis Spatial. Tugas Akhir, Jurusan Sipil Fakultas

Teknik Universitas Hasanuddin, Makassar. 2014.

3. Selatan DK. Profil Dinas Kesehatan Provinsi Sulawesi Selatan 2014.

4. Susanto E. Masyarakat Daerah Aliran Sungai Code Dalam Menanggulangi Dampak Bencana Banjir. Jurnal Penelitian Humaniora.

2010;15(1).

5. Reizkapuni R, Rahdriawan M. Pemberdayaan Masyarakat dalam Penanggulangan Banjir Rob Di Kelurahan Tanjung Mas Kota Semarang.

Teknik PWK (Perencanaan Wilayah Kota). 2014;3(1):154-64.

6. Sasikome JR, Kumaat L, Mulyadi N. 1 Pengaruh Penyuluhan Bencana Banjir Terhadap Kesiapsiagaan Siswa SMP Katolik Soegiyo

Pranoto Manado Menghadapi Banjir. JURNAL KEPERAWATAN. 2015 May 7;3(2).

7. Alfiadi, H. S. Faktor-faktor yang mempengaruhi implementasi kebijaksaan penanganan sampah studi di Kota Sintang Kabupaten Sintang.

2013;

8. Djafar MI, Mantu FN, Patellongi IJ. Pengaruh penyuluhan tentang kesiapsiagaan bencana banjir terhadap pengetahuan dan sikap kepala

keluarga di Desa Romang Tangaya Kelurahan Tamangapa Kecamatan Manggala Kota Makassar. Jurnal. Makasar: Universitas Hasanudin.

2011.

9. Raya HA, Kusbandrijo B. Implementasi Kebijakan Pemkot Surabaya Dalam Penanganan Banjir (Studi di Dinas Bina Marga dan

Pematusan). JPAP: Jurnal Penelitian Administrasi Publik. 2015 May 21;1(01).

10. Astuti EW. Implementasi Program Pengendalian Banjir Oleh Dinas Bina Marga Dan Pengairan Di Kota Samarinda.

11. Ramadhanni RF, Setiyono B, Manar DG. Implementasi Program Penanganan Banjir Rob Di Wilayah Pesisir Kota Pekalongan. Journal of

Politic and Government Studies. 2015 Sep 30;5(4):261-70.

12. Merlyn Y, Saleh E, Taqwa R. Partisipasi Masyarakat Dalam Menunjang Kinerja Sistem Drainase (Studi Kasus Sungai Bendung

Palembang). Jurnal Penelitian Universitas Jambi: Seri Sains. 2015 Jun 30;17(1).

322-325

51.

Authors: Defiana, Nyam Kar Lin

Paper Title: Effects of Binary Solvent Extraction System and Extraction Time on Antioxidant Activity from Roselle

(Hibiscus Sabdariffa L.) Seeds

Abstract: Roselle (Hibiscus sabdariffa L.) has been broadly utilized in nourishment industry, particularly its

petal part. Notwithstanding, the roselle seeds are considered as waste despite the fact that it was conceivably

recognizable as cancer prevention agent sources. The point of this investigation was to decide the best parameter

(term and dissolvable) for removing Roselle (Hibiscus sabdariffa L.) seeds by a beat ultrasonic-helped extraction.

The cell reinforcement exercises of ultrasonic-helped Roselle (Hibiscus sabdariffa L.) seeds were assessed by a

2,2-diphenyl-1-picrylhydrazyl (DPPH) radical rummaging limit test, 2,2'- azino-bis(3-ethylbenzothiazoline-6-

sulphonic corrosive) (ABTS) radical searching limit examine, ferric diminishing cancer prevention agent control

(FRAP) measure, and 𝛽-carotene fading hindrance test. Add up to phenolic content (TPC) and aggregate flavonoid

content (TFC) assessments were done to decide the phenolic and flavonoid substance in Roselle (Hibiscus

sabdariffa L.) seeds separate. The outcome displayed that the best extraction parameter utilized 80% ethanol for 10

minutes.

Keywords: Binary; solvent; Roselle; extraction system; Antioxidant

326-330

References: 1. A. Golmohamadi, G. Möller, J. Powers, C. Nindo, Ultrason. Sonochem.2013;20(1316).

2. S. Skrovankova, D. Sumczynski, J. Mlcek, T. Jurikova, J. Sochor, Int. J. Mol. Sci.2015;16.

3. I. Amin, L. Cheww, J. Food Technol.2006;4(10).

4. A. Djeridane, M. Yousfi, B. Nadjemi, D. Boutassouna, P. Stocker, N. Vidal, Food Chem.2006;97(654).

5. M.S. Brewer, Compr. Rev. Food Sci. Food Saf. 2011;10(221).

6. N. Mohd-Esa, F.S. Hern, A. Ismail, C.L. Yee, Food Chem. 2010;122(1055).

7. P.J. Tsai, J. McIntosh, P. Pearce, B. Camden, B.R. Jordan, Food Res. Int. 2002;35(351).

8. K.L. Nyam, C.P. Tan, O.M. Lai, K. Long, Y.B. Che Man, LWT - Food Sci. Technol.2009;42(1396).

9. N.I. Yusoff , C.P. Leo, J. Food Qual. 2017, (2017).

10. I. Aguiló-Aguayo, J. Walton, I. Viñas, B.K. Tiwari, LWT-Food Sci. Technol. 2017;77(92).

11. F. Chen, Y. Sun, G. Zhao, X. Liao, X. Hu, J. Wu, Z. Wang, Ultrason. Sonochem. 2007;14(767).

12. S. Rodrigues, G.A.S. Pinto, J. Food Eng. 2007;80(869).

13. Y. Wong, H. Lau, C. Tan, K. Long, K. Nyam, The Scientific World Journal 2014, (2014).

14. Y.Y. Thoo, S.K. Ho, J.Y. Liang, C.W. Ho, C.P. Tan, Food Chem. 2010;120(290).

15. M. Chandel, U. Sharma, N. Kumar, B. Singh, S. Kaur, Asian Pac. J. Trop. Med.2012;5(977).

16. M. Vasconcelos, F. Arruda, D. de Alencar, S. Saker-Sampaio, M. Albuquerque, H. dos Santos, P. Bandeira, O. Pessoa, B. Cavada, M.

Henriques, M. Pereira, E. Teixeira, Biomed Research International 2014, (2014).

17. S. Al-Okbi, A. Abdel-Raze, S. Mohammed, M. Ottai, Journal Of Biological Sciences.2017;17.

18. V. Bewick, L. Cheek, J. Ball, Critical Care.2004;8.

19. A. Javier David Vega, R. Hector, L. Juan Jose, L. Maria L, H. Paola, Á. Raúl, O. Carlos Enrique, Czech Journal Of Food Sciences.

2017;35.

20. Y. Thoo, S. Ho, F. Abas, O. Lai, C. Ho, C. Tan, Molecules. 2013;18.

21. I. Fidrianny, A. Rahmawati, R. Hartati, Rasayan Journal Of Chemistry. 2018;11.

22. Z.-S. Zhang, D. Li, L.-J. Wang, N. Ozkan, X.D. Chen, Z.-H. Mao, H.-Z. Yang, Sep. Purif. Technol. 2007;57(17).

23. N.E. Durling, O.J. Catchpole, J.B. Grey, R.F. Webby, K.A. Mitchell, L.Y. Foo, N.B. Perry, Food Chem. 2007;101(1417).

24. B. Sultana, F. Anwar, M. Ashraf, Molecules. 2009;14. 25. V.L. Baker, M.O. Gvakharia, H.M. Rone, J.R. Manalad, G.D. Adamson, Fertil. Steril. 2008;90(537).

26. N. Jadid, D. Hidayati, S.R. Hartanti, B.A. Arraniry, R.Y. Rachman, W. Wikanta, AIP Conf. Proc. 2017;1854(20019).

27. M. Ahmed, H. Fatima, M. Qasim, B. Gul, Ihsan-ul-Haq, BMC Complement. Altern. Med.2017;17(386).

28. S. Galili, R. Hovav, in edited by R.R.B.T.-P. in P. Watson (Academic Press, San Diego, 2014), pp. 305–323.

29. J. Wang, B. Sun, Y. Cao, Y. Tian, X. Li, Food Chem. 2008;106(804).

30. J.E. MbossoTeinkela, X. SiweNoundou, E.L. Nguemfo, F. Meyer, R. Wintjens, M. Isaacs, A.E. MpondoMpondo, H.C. Hoppe, R.W.M.

Krause, A.G.B. Azebaze, Saudi J. Biol. Sci. 2018;25(117).

31. E. Hainida, A. Ismail, N. Hashim, N. Mohd.-Esa, A. Zakiah, J. Sci. Food Agric. 2008;88(1043).

32. R.L. Prior, H. Hoang, L. Gu, X. Wu, M. Bacchiocca, L. Howard, M. Hampsch-Woodill, D.Huang, B. Ou, R. Jacob, J. Agric. Food Chem.

2003;51(3273).

33. W. Huang, A. Xue, H. Niu, Z. Jia, J. Wang, Food Chem. 2009;114(1147).

34. C.H. Chan, R. Yusoff, G.-C. Ngoh, Chem. Eng. Res. Des. 2014;92(1169).

35. C.C. Xu, B. Wang, Y.Q. Pu, J.S. Tao, T. Zhang, Chin. J. Nat. Med. 2017;15(721).

36. D.M. Kasote, S.S. Katyare, M. V Hegde, H. Bae, Int. J. Biol. Sci. 2015;11(982).

37. Z. Sadeghi, J. Valizadeh, O. AzyzianShermeh, M. Akaberi, Avicenna J. Phytomedicine. 2015;5(1).

38. A.I. Cissouma, F. Tounkara, M. Nikoo, N. Yang, X. Xu, Adv. J. Food Sci. Technol. 2013;5(1483).

52.

Authors: Ima Fatima, Dermawan Wibisono, Akbar Adhiutama

Paper Title: Conceptual Framework of Performance Management System for Construction Companies in

Indonesia

Abstract: Different factors determine a company's success. The quality of the company's performance

management system (PMS) is one factor that supports this success. Performance management is essentially the

systematic process by which the company involves its employees in the achievement of organizational missions

and objectives. Facing tighter business competition, performance management can be the best approach to increase

employee motivation, boost productivity, and produce tangible impacts on improving the performance and

development of the company's business. This paper presents an alternative framework of performance management

system for corporate level for construction companies in Indonesia. In the development of the proposed alternative

PMS, one of the performance management system approaches, namely the Knowledge - Based Performance

Management System (KBPMS). The proposed framework is expected to be more suitable for construction

companies in Indonesia, especially in facing global challenges and to be more competitive in this industry business

competition.

Keywords: Conceptual framework, construction industry, construction companies, knowledge-based

performance management system (KBPMS), performance management system (PMS).

References: 1. Alarcón, L., & Serpell, A. (1996). Performance measuring, benchmarking, and modelling of project performance. Proceedings for the 5th

International Conference of the International Group for Lean Construction (IGLC-5), The University of Birmingham, UK.

2. Alarcón, L., Grillo, A., Freire, J., & Diethelm, S. (2001). Learning from collaborative benchmarking in the construction

industry.Proceedings for the 9th International Conference of the International Group for Lean Construction (IGLC-9), Singapore, 6–8

August 2001.

3. Amaratunga, D. (2000). Assessment of facilities management performance.Journal of Property Management, 18(4), 258–266.

4. Barros Neto, J.P. (2002). The Relationship between strategy and lean construction. Proceeding for 10th Conference of International Group

for Lean Construction (IGLC-10), Gramado, Brazil.

5. Bititci., U. S., Carrie, A. S., &McDevitt, L. G. (1997). Integrated performance measurement systems: Adevelopment guide.International

Journal of Operations and Production Management, 17(6),522–535.

6. Bowen, P. A., Cattel, K. S., Hall, K. A., Edwards P. J., &Pearl, R. G. (2002). Perceptions of time, cost and quality management on

331-338

building projects.Australasian Journal of Construction Economics and Building, 2(2), 48–56.

7. Fatima, I., & Wibisono, D. (2017). Main performance indicators for a construction company in Indonesia. Asia Pacific Journal of

Advanced Business and Social Studies, 3(2), 77–89.

8. Ferreira, A., & Otley, D. (2009). The design and use of performance management systems: An extended framework for

analysis.Management Accounting Research, 20, 263–282.

9. Forbes, L. H., Ahmed, S. M.,& Barcala, M. (2002). Adapting lean construction theory for practical application in developing

countries.Proceedings for the first CIB W107 International Conference: Creating a sustainable construction industry in developing

countries, Stellenbosch, South Africa, 11–13 November 2002.

10. Hendry, C., Bradley, P., & Perkins, S. (1997). Missed a motivator?.People Management, 15 May,20–5.

11. Johnson, G., Scholes, K., &Whittington, R. (2005).Exploring corporate strategy: Text and cases (7th ed.), New Jersey, Prentice-Hall

Financial Times, Pearson Education Limited.

12. Kaglioglou, M., Cooper, R., &Aouad, G. (2001). Performance management in construction: A conceptual framework.Journal of

Construction Management and Economy, 19, 85–95.

13. Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard - Measures that drive performance. Harvard Business Review, 7(1), 47–54.

14. Kaplan, R. S., & Norton, D. P. (1996). The balanced scorecard: Translating strategy into action, President and Fellows of Harvard

College, USA.

15. Kaplan, R. S.,&Norton, D. P. (2000). The strategy-focused organization: How balanced scorecard companies thrive in the new business

environment, Boston, MA: Harvard Business School Press.

16. Lantelme, E. M. V., &Formoso, C. T. (2000). Improving performance through measurement: The application of lean production and

organisational learning principles.Proceedings for 8th International Conference of the International Group for Lean Construction,

University of Sussex, Brighton.

17. Love, P.E.D., Li, H., Irani, Z., and Holt, G. D. (2000). Rethinking TQM: Toward a framework for facilitating learning and change in

construction organisations. Total Quality Management. Bi-monthly for Total Quality Management (Special Issue), 12(2), 107–116. MCB

Press. ISSN: 0954- 478X. DOI: http://dx.doi.org/10.1108/09544780010318361.

18. Lynch, R. L, &Cross, K. F. (1995). Measure up!: Yardsticks for continuous improvement,Blackwell (USA).

19. National Institutes of Standards and Technology (NIST). (2011). Criteria for performance excellence program.

20. Neely, A., Mills, J., Platts, K., Gregory, M., &Richards, H. (1996). Performance measurement system design: Should process based

approaches be adopted?. International Journal of Production Economics, 46-47, 423-431.

21. Neely, A., Gregory, M., &Platts, K. (1995). Performance measurement system design: A literature review and research agenda.

International Journal of Operation and Product Management, 15(4), 80–116.

22. Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M., & Kennerley, M. (2000). Performance measurement system

design: Developing and testing a process-based approach. International Journal of Operation and Product Management, 20(10), 1119–

1145.

23. Neely, A.,& Adams, C. (2001). Perspectives on performance: the performance prism. Journal of Cost Management, 15, 7–15.

24. Oackland, J., &Marosszeky, M. (2006). Total quality in the construction supply chain.(1sted.),Great Britain, Elsevier Ltd.

25. Rahayu, R.S, & Wibisono, D. (2013). Proposed performance management system for Department of Transportation West Java Province in

land transportation sector.The Indonesian Journal of Business Administration, 2(13), 1718–1737.

26. Robinson, H. S, Carrillo, P.M, Anumba, C.J., & Al-Ghassani, A.M. (2005). Review and implementation of performance management

models in construction engineering organisations. Journal of Construction Innovation, 5(4), 203–217.

27. Saaty, T.L. (1980).The Analytic Hierarchy Process,New York, USA. McGraw-Hill Company,

28. Saaty, T.L. (1996).Decision making with dependence and feedback: The analytic network process, Pittsburgh, USA, RWS Publications,

29. Saaty, T.L. (2008). Decision making with the Analytical Hierarchy Process.International Journal Services Sciences, 1(1), 83–98.

30. Sammerville, J., & Robertson, H. W. (2000). A scorecard approach to benchmarking for total quality construction.International Journal

of Quality & Reliability Management, 17(4/5),453–466.

31. Stoop, P.P.M. (1996).Performance management in manufacturing: a method for short term performance evaluation and diagnosis.

Unpublished Ph.D. thesis, Technische Universiteit Eindhoven, Netherland in Wibisono, D. (2006).Konsep, desain, teknik meningkatkan

daya saing perusahaan, Jakarta, Penerbit Erlangga,

32. Wang, O., El-Gafy, M., &Zha, J. (2010). Bi-level framework for measuring performance to improve productivity of construction

enterprises.Construction Resource Congress, 2, 970–979.

33. Wheelen, & Hunger. (2012). Strategic management and business policy: Toward global sustainability(13thed.), New Jersey, Prentice Hall.

34. Wibisono, D. (2006).Manajemen kinerja: Konsep, desain, teknik meningkatkan daya saing perusahaan,Jakarta, Penerbit Erlangga,

35. Wibisono, D. (2011).Manajemen kinerja korporasi & organisasi: Panduan penyusunan indicator, Jakarta, Penerbit Erlangga,

36. Wibisono, D.,&Kosasih, O. (2011). Perancangan sistem manajemen kinerja perusahaan: Studi kasus Perusahaan Dago Engineering.Jurnal

Manajemen Teknologi, 9(1), ISSN: 1412–1700.

37. Wibisono, D. (2012). How to create a world class company: Panduan bagi manajer dan direktur, Jakarta, Gramedia Pustaka Utama.

53.

Authors: P.M.Mahalakshmi, P.Thangavelu

Paper Title: Properties of Multisets

Abstract: The combinatorial properties of multisets are characterized. Some concepts in multiset topological

spaces are discussed.

Keywords: Multisets, absolute mset, topology, multiset topology, open mset.

References: 1. Blizard, Wayne D, Multiset theory, Notre Dame Journal of Formal Logic 30(1) (1989),

2. 36–66.

3. Blizard, Wayne D, The development of multiset theory, Modern Logic 1(4), (1991),

4. 319–352.

5. Girish, K.P. and Sunil Jacob John, Multiset topologies induced by multiset relations, Information Sciences 188 (2012), 298 –313.

6. Girish, K.P. and Sunil Jacob John, On multiset topologies, Theory and Applications of Mathematics & Computer Science, 2(2012), 37-52.

7. Padmapriya R, Contributions to topology generated by fuzzy sets and multisets, Ph.D thesis, Bharathiar University, Coimbatore,

Tamilnadu, India, 2016.

8. WildbergerN.J., A New Look at Multisets, Preprint, University of NewSouth Wales, Sydney, Australia, (2003), 1-21.

339-342

Authors: D.S Subhagya, Keshavamurthy. C

Paper Title: Motion Artifact Detection Model using Machine Learning Technique for Classifying Abnormalities in

Human Being

54.

Abstract: Obtaining an exact measurement of oxygen saturation (SpO2) using a finger-probe based pulse

oximeter is dependent on both artifact-free infrared (IR) and red (R) Photoplethysmographic signals. However, in

actual real-time environment condition, these Photoplethysmographic signals are corrupted due to presence of

motion artifact (MA) signal that is produced due to the movement/motion from either hand or finger. To address

this motion artifacts interference, the cause of the contamination of Photoplethysmographic signals by the motion

artifacts signal is observed. The motion artifact signal is established to resemble similar to an additive noise.

Motion and noise artifacts enforce constraints on the usability of the Photoplethysmographic, predominantly in the

setting of sleep disorder detection and ambulatory monitoring. Motion and noise artifacts can alter

Photoplethysmographic, resulting wrong approximation of physiological factors such as arterial oxygen saturation

and heart rate. For overcoming research challenges, this manuscript present a novel hybrid approach for detection

of artifacts. Firstly, this work present an accurate SpO2 measurement model. Secondly, present an adaptive filter

and adaptive threshold model to detect artifact and obtain derivative of correlation coefficient (CC) for labelling

artifacts respectively. Lastly, Enhanced Support Vector Machine (ESVM) Model is presented to perform

classification. Experiment are conducted on both real-time and simulated dataset set. Our hybrid approach attain

significant performance in term of accuracy, sensitivity, specificity and positive prediction.

Keywords: Artifact detection, Machine learning, PPG, SVM.

References: 1. J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiological Measurement, vol. 28, no. 3, p.

R1, 2007.

2. S. Sinchai, P. Kainan, P. Wardkein and J. Koseeyaporn, "A Photoplethysmographic Signal Isolated From an Additive Motion Artifact by

Frequency Translation," in IEEE Transactions on Biomedical Circuits and Systems. doi: 10.1109/TBCAS.2018.2829708, 2018.

3. AJubran, “Pulse oximetry,” Intensive Care Med., vol. 30, no. 11, pp. 2017–2020, 2004.

4. J. A. Kline et al., “Use of pulse oximetry to predict in-hospital complications in normotensive patients with pulmonary embolism,” Amer.

J. Med., vol. 115, no. 3, pp. 203–208, 2003.

5. A Bakr and H. Habib, “Combining pulse oximetry and clinical examination in screening for congenital heart disease,” Pediatr Cardiol,

vol. 26, no. 6, pp. 832–835, 2005.

6. G. I. Parameswaran, K. Brand, and J. Dolan, “Pulse oximetry as a potential screening tool for lower extremity arterial disease in

asymptomatic patients with diabetes mellitus,” Archives Internal Med., vol. 165, no. 4, pp. 442–446, 2005.

7. J. Masip et al., “Pulse oximetry in the diagnosis of acute heart failue,” Revista Espa de Cardiol., vol. 65, no. 10, pp. 879–884, 2012.

8. S. A. Shah, C. Velardo, O. J. Gibson, H. Rutter, A. Farmer, and L.Tarassenko, “Personalized alerts for patients with copd using pulse

oximetry and symptom scores,” in Proc. Conf. IEEE Eng. Med. Biol. Soc., Chicago, USA, pp. 3164–3167, 2014.

9. H.-W. Chen, L.-C. Weng, T.-M. Wang, and K.-F. Ng, “Potential use of pulse oximetry for the diagnosis of testicular torsion,” JAMA

Pediatr, vol. 168, no. 6, pp. 578–579, 2014.

10. M. Bargrizan, M. A. Ashari, M. Ahmadi, and R. Jamileh, “The use of pulse oximetry in evaluation of pulp vitality in immature permanent

teeth,” Dent Traumatol, vol. 165, no. 4, pp. 43–47, 2016.

11. Z. Zhang, Z. Pi, and B. Liu, “Troika: A general framework for heart rate monitoring using wrist-type photoplethysmographic signals

during intensive physical exercise,” IEEE Transactions on Biomedical Engineering, vol. 62, no. 2, pp. 522–531, Feb 2015.

12. M. R. Ram, K. V. Madhav, E. H. Krishna, N. R. Komalla, and K. A. Reddy, “A novel approach for motion artifact reduction in ppg

signals based on as-lms adaptive filter,” IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 5, pp. 1445–1457, May

2012.

13. A Wood, Physiology, Biophysics, and Biomedical Engineering, ser. Series in Medical Physics and Biomedical Engineering. CRC Press,

2016.

14. T. Schck, C. Sledz, M. Muma, and A. M. Zoubir, “A new method for heart rate monitoring during physical exercise using

photoplethysmographic signals,” in 2015 23rd European Signal Processing Conference (EUSIPCO), pp. 2666–2670, 2015.

15. E. Gil, P. Laguna, J. Martinez, O. Prez, A. Alberola, and L.Sornmo, “Heart rate turbulence analysis based on photoplethysmography,”

IEEE Transactions on Biomedical Engineering, vol. 60, no. 11, 2013.

16. A Garde, W. Karlen, J. M. Ansermino, and G. A. Dumont, “Estimating respiratory and heart rates from the correntropy spectral density of

the photoplethysmogram,” PLoS ONE, vol. 9, no. 1, 2014.

17. M. R. Ram, K. Madhav, H. Krishmaa, N. R. Komalla, and K. A. Reddy, “A novel approach for motion artifact reduction in ppg signals

based on as-lms adaptive filter,” IEEE Tr. Instru. and Meas., vol. 61, no. 5, 2012.

18. Q. Wang, P. Yang, and Y. Zhang, “Artifact reduction based on empirical mode decomposition (emd) in photoplethysmography for pulse

rate detection,” in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, pp. 959–

962, 2010.

19. P. Addison and J. Watson, “Signal processing techniques for determining signal quality using a wavelet transform ratio surface,” 2010.

20. J. W. Chong, D. K. Dao, S. M. A. Salehizadeh, D. D. McManus, C. E. Darling, K. H. Chon, and Y. Mendelson, “Photoplethysmograph

signal reconstruction based on a novel hybrid motion artifact detection reduction approach. part i: Motion and noise artifact detection,”

Annals of Biomedical Engineering, vol. 42, no. 11, pp. 2238–2250, 2014.

21. J. A. Sukor, S. J. Redmond, and N. H. Lovell, “Signal quality measures for pulse oximetry through waveform morphology analysis,”

Physiological Measurement, vol. 32, no. 3, p. 369, 2011.

22. S. J. Barker and N. K. Shah, “The Effects of Motion on the Performance of Pulse Oximeters in Volunteers (Revised publication),"

Anesthesiology, vol. 86, p. 101, Jan. 1997.

23. M. T. Petterson and V. L. Begnoche, “The effect of motion on pulse oximetry and its clinical significance," Anesthesia & Analgesia,

2007.

24. A Pantelopoulos and N. G. Bourbakis, \A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis," Systems,

Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, vol. 40, no. 1, pp. 1-12, 2010.

25. J. G. Webster, Design of pulse oximeters. CRC Press, 1997.

26. J. Yan and G. Bin, “Research on an anti-motion interference algorithm of blood oxygen saturation based on AC and DC analysis,” vol. 23,

no. s2, pp. S285–S291, 2015.

27. J. M. Goldman, M. T. Petterson, R. J. Kopotic, and S. J. Barker, “Masimo signal extraction pulse oximetry,” vol. 16, no. 7, pp. 475–483,

2000.

28. F. Peng, Z. Zhang, X. Gou, H. Liu, and W. Wang, “Motion artifact removal from photoplethysmographic signals by combining temporally

constrained independent component analysis and adaptive filter,” vol. 13, no. 1, p. 50, 2014.

29. Y.-S. Yan and Y.-T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Transactions on information

technology in biomedicine, vol. 12, no. 3, pp. 399–405, 2008.

343-350

30. R. Yousefi, M. Nourani, S. Ostadabbas, and I. Panahi, “A motion-tolerant adaptive algorithm for wearable photoplethysmographic

biosensors,” vol. 18, no. 2, pp. 670–681, 2014.

31. A Uncini, Fundamentals of Adaptive Signal Processing, ser. Signals and Communication Technology. Springer International Publishing,

2014.

32. D. G. Jang, U. Farooq, S. H. Park, and M. Hahn, “A robust method for pulse peak determination in a digital volume pulse waveform with

a wandering baseline,” IEEE Transactions on Biomedical Circuits and Systems, vol. 8, no. 5, pp. 729–737, Oct 2014.

33. E. Gil, P. Laguna, J. Martinez, O. Prez, A. Alberola, and L.Sornmo,“Heart rate turbulence analysis based on photoplethysmography,”

IEEE Transactions on Biomedical Engineering, vol. 60, no. 11, Nov. 2013.

34. Q. Li and G. D. Clifford, “Dynamic time warping and machine learning for signal quality assessment of pulsatile signals,” Physiological

Measurement, vol. 33, no. 9, p. 1491, 2012.

35. J. A. Sukor, S. J. Redmond, and N. H. Lovell, “Signal quality measures for pulse oximetry through waveform morphology analysis,”

Physiological Measurement, vol. 32, no. 3, p. 369, 2011.

36. M. Elgendi, I. Norton, M. Brearley, D. Abbott, and D. Schuurmans, “Systolic peak detection in acceleration photoplethysmograms

measured from emergency responders in tropical conditions,” PLoS ONE, vol. 8, pp. 1–11, 10 2013.

37. J. Allen, “Photoplethysmography and its application in clinical physiological measurement,” Physiological Measurement, vol. 28, no. 3, p.

R1, 2007.

38. Park, J. U., Lee, H. K., Lee, J., Urtnasan, E., Kim, H., and Lee, K. J., Automatic classification of apnea/hypopnea events through

sleep/wake states and severity of SDB from a pulse oximeter. Physiol. Meas. 36(9):2009–2025, 2015.

39. J. F. Morales et al., "Sleep Apnea Hypopnea Syndrome classification in SpO2 signals using wavelet decomposition and phase space

reconstruction," 2017 IEEE 14th International Conference on Wearable and Implantable Body Sensor Networks (BSN), Eindhoven, pp.

43-46, 2017.

40. G. C. Gutiérrez-Tobal et al., "Analysis and classification of oximetry recordings to predict obstructive sleep apnea severity in children,"

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, pp. 4540-4543,

2015.

41. S. Gutta, Q. Cheng, H. D. Nguyen and B. A. Benjamin, "Cardiorespiratory Model-Based Data-Driven Approach for Sleep Apnea

Detection," in IEEE Journal of Biomedical and Health Informatics, vol. 22, no. 4, pp. 1036-1045, July 2018.

42. D. Dao et al., "A Robust Motion Artifact Detection Algorithm for Accurate Detection of Heart Rates From Photoplethysmographic

Signals Using Time–Frequency Spectral Features," in IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 5, pp. 1242-1253,

Sept. 2017.

43. Erdenebayar, U., Park, J. U., Jeong, P., and Lee, K. J., Obstructive sleep apnea screening using a piezo-electric sensor. J. Korean Med.

Sci. 32(6):893–899, 2017.

55.

Authors: Marimuthu. R, Elsie Rezinold, Mayank Rathi

Paper Title: Design of Efficient Approximate Compressor for Digital Image Processing

Abstract: For various error tolerant applications like multimedia and signal processing, approximate computing

is the most suited computing technique. With the cost of accuracy, approximate computing gives us faster and

efficient results with possibly low power consumption. A new approach and design towards optimizing the partial

products reduction stage of a compressor-based multiplier have been introduced in this paper. Two new designs of

4:2 compressors and six new designs of approximate multipliers using the approximate compressors have been

proposed. The results of the simulation of the proposed designs show that there has been a significant improvement

in the accuracy with reduction in power and time consumption when we compare to the previous approximate

designs. An image processing application is used to prove the efficiency of the proposed designs.

Keywords: Approximate Compressors, Digital Image Processing, Edge Detection.

References: 1. S Sakthikumaran, S. Salivahanan, and V. S. Kanchana Bhaaskaran, “16-Bit RISC Processor Design for Convolution Application”, in proc.

of international conference on Recent Trends in Information Technology (ICRTIT), Chennai, India, June 2011, pp. 394-397.

2. Donald Donglong Chen, Nele Mentens, Frederik Vercauteren, Sujoy Sinha Roy, Ray C. C. Cheung, Derek Pao, and Ingrid Verbauwhede,

“High-Speed Polynomial Multiplication Architecture for Ring-LWE and SHE Cryptosystems”, IEEE Transactions on Circuits and

Systems I: Regular Papers, vol, 62, no.1, pp. 157-166, Jan. 2015.

3. Reza Azarderakhsh, and Arash Reyhani-Masoleh, “Parallel and High-Speed Computations of Elliptic Curve Cryptography Using Hybrid-

Double Multipliers”, IEEE Transactions on Parallel and Distributed Systems, vol. 26, no, 6, pp. 1668-1677, June 2015.

4. P.C.H. Meier, R.A. Rutenbar, and L.R. Carley, “Exploring multiplier architecture and layout for low power”, in proc. of IEEE Custom

Integrated Conference, San Diego, CA, USA, May.1996, pp. 513-516.

5. J. Gu and C. H. Chang, “Ultra low-voltage, low-power 4-2 compressor for high speed multiplications,” in Proc. 36th IEEE Int. Symp.

Circuits Syst., Bangkok, Thailand, May 2003, pp. 321-324.

6. M. Margala and N. G. Durdle, “Low-power low-voltage 4-2 compressors for VLSI Applications,” in Proc. IEEE Alessandro Volta

Memorial Workshop Low-Power Design, March 1999, pp. 84–90.

7. K. Prasad and K. K. Parhi, “Low-power 4-2 and 5-2 compressors,” in Proc. 35th Asilomar Conf. Signals, Syst. Comput., 2001, vol. 1, pp.

129–133.

8. Amir Momeni, Jie Han, Paolo Montuschi, and Fabrizio Lombardi, “Design and Analysis of Approximate Compressors for Multiplication”

IEEE Transactions on Computers in 2014.

9. Wong Seng Yue, “Application of Energy Conservation Techniques in Industries and Institution”, International Innovative Research

Journal of Engineering and Technology, Vol: 4, No: 2, p. 7-16, Dec 2018.

351-355

56.

Authors: V.Kavitha, K.Subramanian

Paper Title: Modelling and Simulation of Power Quality Disturbance using MATLAB/SIMULINK

Abstract: Power quality is a very important part to achieve the good quality of the supply. Power quality is

defined as the in all electrical networks or any grids its giving perfect along with pure sinusoidal wave form and

free noise without any disturbance. To improve the power quality we need some analyzes and research on power

quality disturbance perfectly. According to this paper mainly identify the power quality disturbance and harmonic

disturbances by changing the short term voltage a little movements. Mainly the wave will analyzed through the

four transform equations. . The simulation results and the theoretical analysis show that the model in this paper

356-359

could simulate the voltage change and harmonic disturbance well, which can provide data and basis for detection

and identification of PQ and further control measures.

Keywords: Power quality, three phase universal bridge, Distributed parameters line, fault breaker.

References: 1. F. Jurado, N. Acero, and B. Ogayar, “Application of signal processing tools for power quality analysis,” in Proc. of Canadian Conf.

Electricaland Computer Engineering, May 2002, vol. 1, pp. 82–87.

2. O. Poisson, P. Rioual, and M. Meunier, “Detection and measurement of power quality disturbances using wavelet transform,” IEEE

Trans. Power Del., vol. 15, no. 3, pp. 1039–1044, Jul. 2000.

3. S. Santoso, W. M. Grady, E. J. Powers, J. Lamoree, and S. C. Bhatt, “Characterization of distribution power quality events with Fourier

andwavelet transforms,” IEEE Trans. Power Del., vol. 15, no. 1, pp. 247–254, Jan. 2000.

4. A. M. Gaouda, S. H. Kanoun, M. M. A. Salama, and A. Y. Chikhani, “Pattern recognition applications for power system disturbance

5. classification,” IEEE Trans. Power Del., vol. 17, no. 3, pp. 677–683, Jul. 2002.

6. Z.-L.Gaing, “Wavelet-based neural network for power disturbance recognition and classification,” IEEE Trans. Power Del., vol. 19, no. 4,

pp.1560–1568.

7. S. Santoso, E. J. Powers, W. M. Grady, and A. C. Parsons, “Power quality disturbance waveform recognition using wavelet-based neural

8. classifier- part I: Theoretical foundation,” IEEE Trans. Power Del., vol. 15, no. 1, pp. 222–228, Oct. 2004.

9. M.H.J. Bollen, "What is Power Quality", Electric Power Systems Research, vol.66, pp.5-14, July 2003.

57.

Authors: Niveditha.N, Swathy.S, Kalviananth, Velayuthan.T

Paper Title: Bus Tracking with QR code and RFID

Abstract: In this paper using RFID (Radio Frequency ID) for developing bus tracking systems. This project

addresses two major problems: unnecessary waiting time for bus, higher cost for the tracking system. To reduce

the waiting time, passengers can track the buses in their places and known about where their bus is located. If

passengers are not known about the bus number they can also scan the QR code placed in all the bus stops. By

scan the code they can get the information about the bus number and recently crossed bus stop of that bus. The bus

tracking system requires installing RFID tags on all buses and RFID readers on bus stops for tracking.

Keywords: QR code, RFID

References: 1. ImanM.AlmomaniNourY.Alkhalil,EnasM.Ahmad,Rania M. Jodeh” GPS Vehicle Tracking and Management System”,IEEE Jordan

Conference on Applied Electrical Engineering and Computing Technologies (AEECT) 2011.

2. KunalMaurya, Mandip Singh, Neelu Jain, “Real Time Vehicle Tracking System using GSM and GPS technology- an Anti -Theft Tracking

System”, International Journal of electronics and computer science engineering. ISSN 227-1956/V1N3-1103- 1107.

3. T. Le-Tien, V. Phung-The, “Routing and Tracking System for Mobile Vehicles in Large Area”, Fifth IEEE International Symposium on

Electronic Design, Test & Applications, pp. 297-300, 2010.

4. F.M. Franczyk, J.D. Vanstone, “Vehicle warning system”, Patent number: 7362239, Issue date: 22 April 2008.

5. T. Nikolaos and T. Kiyoshi, “QR-code calibration for mobile augmented reality applications: Linking a unique physical location to the

digital world,” in Proc. ACM SIGGRAPH 2010 Posters, ser. SIGGRAPH ’10, 2010.

6. T.-W. Kan, C.-H.Teng, and W.-S. Chou, “Applying QR code in augmented reality applications,” in Proc. ACM VRCAI ’09, pp. 253- 257,

2009.

7. S. Eken, A. Sayar, “A Smart bus tracking system based on location aware services and QR codes,” IEEE International Symposium on

Innovations in Intelligent and Applications Proceedings, pp: 299-309, 2014.

8. R. Manikandan, S. Niranjani, “Implementation on real time transportation information using GSM query response system,” Contemporary

Engineering Sciences, Vol. 7, No.11, pp: 509-514, 2014.

9. G. Raja, D. NaveenKumar, G. Dhanateja, G. V. Karthik, Y. Vijay Kumar, “Bus Position monitoring system to facilitate the passengers,”

International Journal of Engineering Science and Advanced Technology(IJESAT), Volume-3, Issue-3, pp: 132-135, 2014.

10. Vishal Bharte, KaustubhPatil, LalitJadhav, Dhaval Joshi , “ Bus Monitoring System Using Polyline Algorithm ,” International Journal of

Scientific and Research Publications, Volume 4, Issue 4, April 2014.

11. Wong Seng Yue, “Application of Energy Conservation Techniques in Industries and Institution”, International Innovative Research

Journal of Engineering and Technology, Vol: 4, No: 2, p. 7-16, Dec 2018.

360-362

58.

Authors: Gnanamurugan.S, Sivakumar.P, K. Ramash Kumar, S. Balakumar

Paper Title: On the Performance of Rectangular Microstrip Patch Antenna using Rogers RT/Duriod 5880

Abstract: The widely researched area in communication systems is wireless technology. The study of

communication systems is incomplete without understanding the operation of the antennas. In the recent years of

development in communication systems the important needs are lightweight, compact and cost-effective antennas

that are capable of maintaining high performance over a wide spectrum of frequencies. This technological trend

has focused much effort into the design of a Micro strip patch antenna, because they will provide high frequency

and less bandwidth. This paper presents a design and simulation of rectangular micro strip patch antenna at 2.5

GHz frequency range for wireless communication that provides a radiation pattern along a wide angle of beam.

The designing process uses the Rogers RT/duriod 5880 material is used as the substrate and coaxial probe feed

method is used to gives the excitation value of the antenna compare with FR4 Epoxy. This antenna has many

practical applications like WLAN, WI-FI, etc. so the HFSS software is used to design and implement the antenna.

Keywords: Micro strip patch antenna, Radiation pattern, Ansoft HFSS (High Frequency Structural Simulator).

References: 1. R.Nagendra, T.Venkateswarulu “Design and development of compact microstrip patch dual band antenna for wireless applications”,

363-367

Alexandria University, Alexandria Engineering Journal (ELSEVIER), 5-May 2017.

2. L. Chandiea and K. Anusudha,“Performance Analysis of Pentagon Shaped Microstrip Patch Antenna”, IEEE International Conference on

Computer,Communication and Signal Processing -2017.

3. Haq Nawaz and Ibrahim Tekin,“Double Differential Fed, Dual Polarized Patch Antenna with 90dB Interport RF Isolation for 2.4GHz In-

Band Full Duplex Transceiver”-IEEE 2017.

4. Houda Werfelli, Khaoula Tayari, Mondher Chaoui, Mongi Lahiani, Hamadi Ghariani,“Design of Rectangular Microstrip Patch Antenna”,

in 2nd International Conference on Advanced Technologies for Signal and Image Processing(ATSIP) -March 2016.

5. Vasujadevi Midasala, .P. Siddaiah “Microstrip Patch Antenna Array Design to improve Better Gains” in Interational Conference on

Computational Modeling and Security, Procedia Computer Science 85-2016.

6. T. Srisuji and C. Nandagopal,“Analysis on Microstrip Patch Antennas for Wireless Communication”,IEEE Sponsored 2nd International

Conference on Electronics and Communication System-2015.

7. S Gnanamurugan , Dr.P.sivakumar “Performance Enhancement Of Micro Strip PatchAntenna For Wireless Applications” International

Journal of Pure and Applied Mathematics, Volume 118 No. 20 2018, 465-471

8. S Gnanamurugan , Dr.P.sivakumar “Performance Analysis Of Rectangular Micro Strip Patch Antenna For Wireless Application using

FGPA ” Artificial Intelligence for cloud-based internet of Things (IOT) in Autosoft Journal (Accepted paper)

9. S.Sinan Gultekina, Dilek Uzera, Ozgur Dundar “A Microstrip Patch Antenna Design for Breast Cancer Detection”, World Conference on

Technology, Innovation and Entrepreneurship(ELSEVIER)-2015.

10. Dhivya N, Pooja Jayakumar, Prashanth Mohan, Rekha Zacharia, Vishnupriya Vasudevan, G. Prabha" Comparative Study Of Slotted

Microstrip Antenna Fed Via A Microstrip Feed Line" Proceedings of 1st IRF International Conference, Coimbatore, 9th March-2014.

11. Ameneh Nejati, Ramezan Ali Sadeghzadeh, Fatemeh Geran, “Effect of Photonic Crystal and Frequency Selective Surface Implementation

on Gain Enhancement in the Microstrip Patch antenna at Terahertz Frequency in Physica B449-2014.

12. Chandrasekhar Rao, A.TathaBabu, S.Haritha, K.Suresh, Gopi, “Performance analysis of slotted rectangular patch antenna using co-axial

and strip line feed” in IJREAT volume 1, issue 3 – July 2013.

13. Werfelli Houda, Mondher Chaoui, Hamadi Ghariani, and Mongi Lahiani. "Design of a pulse generator for UWB communications", 10th

International Multi-Conferences on Systems Signals & Devices 2013 (SSD13), 2013.

14. Atinder pal singh, Ravinder Kumar, HatejSingh Dadhwal,”Design of edge fed rectangular micro strip patch antenna for WLAN

applications using Ansoft HFSS” in VSRD – IJEECE, volume 2,Issue 4 – April 2012.

15. A. Chen, Y. Zhang, Z. Chen, C. Yang, Development of a Ka-Band Wideband Circularly Polarized 64-Element Micro strip Antenna Array

With Double Application of the Sequential Rotation Feeding Technique, IEEE Antennas and Wireless Propagation Letters, Vol. 10, 2011.

16. Mustafa K. Taher Al-Nuaimi and William G. Whittow " On The Miniaturization of Microstrip Line-Fed Slot Antenna Using Various

Slots" Final author version. IEEE Loughborough Antennas and Propagation Conference (LAPC), Loughborough, UK, 2011.

17. A. Chen, Y. Zhang, Z. Chen, S. Chao, A Ka-Band High Gain Circularly Polarized Micro strip Antenna Array, IEEE Antennas and

Wireless Propagation Letters, Vol. 9, 2010.

18. Mahdi Ali, Abdennacer Kachouri and Mounir Samet "Novel method for planar microstrip antenna matching impedance", Journal Of

Telecommunications, May 2010.

19. Aruna Rani, R.K. Dawre "Design and Analysis of Rectangular and U Slotted Patch for Satellite Communication" International Journal of

Computer Applications , December 2010.

20. Severn Shelly, Joseph Costantine, Christos G, Christodoulou, Dimitris E. Anagnostou, James C.Lyke “IEEE antennas and wireless

propagation letters” volume 9, 2010.

21. Yong-Xin Guo; Kah- Wee Khoo; Ling Chuen Ong "Wide band Circularly Polarized Patch Antenna Using Broadband Baluns "Antennas

and Propagation, IEEE Transactions on Volume 56, Issue2, Feb. 2008.

59.

Authors: Divyabharathi P, Abirami M, Puvaneshwari S, Vikram N

Paper Title: Ring Structured Patch Antenna for Wideband Applications

Abstract: In this paper Ring shaped patch antenna is designed which is suitable for wireless communications.

The antenna is resonates frequency between 2 to 5 GHz that can be useful for the applications such as WLAN,

WIFI etc. In this microstrip patch antenna slots are introduced to operate the antenna in different frequencies. This

design achieves high bandwidth which is applicable to use with various wireless applications. FR4 substrate is

used as dielectric material for this design. The material which is used for substrate has thickness and dielectric

constant about 1.6 mm and 4.4 respectively. Different experiments are carried out with patch antenna to achieve

better performance of the patch antenna. Simulation work will be done using ADS tool.

Keywords: Microstrip patch antenna, ADS tool, Ring shaped antenna, wireless application, FR4 Substrate, slots.

References: 1. HefiliaAsokan and SrivatsunGopalakrishnan, A Miniaturized inductive – Loaded narrow strip wide band-notched ultra-wideband

monopole antenna with dual-mode resonator, AEU - International Journal of Electronics and Communications, February 2018.

2. Noor M.Awad Mohamed and K.Abdelazeez, Multi slot microstrip antenna for ultra-wide band applications, Journal of King Saud

University - Engineering Sciences Volume 30, Issue 1, January 2018, Pages 38-45.

3. Manisha Gupta and Vinita Mathur, Koch boundary on the square patch microstrip antenna for ultra wideband applications, Alexandria

Engineering Journal 2017.

4. AzadehPiroo, Mohammad Naser-Moghadas, Ferdows B. Zarrab, and Alireza Sharif, A Dual Band Slot Antenna for Wireless Applications

with Circular Polarization, Progress In Electromagnetics Research C, Vol. 71, 69–77, 2017.

5. DeepanshuKaushalT and Shanmuganantham, Parametric enhancement of a novel microstrip patch antenna using Circular SRR Loaded

Fractal Geometry, Alexandria Engineering Journal 12 September 2017.

6. NarinderSharma and VipulSharma, A design of Microstrip Patch Antenna using hybrid fractal slot for wideband applications, Ain Shams

Engineering Journal, 22 July 2017.

7. BharathiAnantha, LakshminarayanaMerugu and P.V.D.SomasekharRao, A novel single feed frequency and polarization reconfigurable

microstrip Patch antenna, AEU - International Journal of Electronics and Communications Volume 72, February 2017, Pages 8-16.

8. R.V.S.RamKrishna, RajKumar and NagendraKushwaha, A circularly polarized slot antenna for high gain applications, AEU -

International Journal of Electronics and Communications Volume 68, Issue 11, November 2014, Pages 1119-1128.

9. Sumitha Mathew, R.Anitha,Vinesh P.V.,K.Vasudevan, Circularly polarized sector- shaped patch antenna for WLANApplications,

International Conference on Information and Communication Technologies (ICICT 2014)

10. Lee KF, Luk KM. Microstrip patch antennas. London: Imperial College Press; 2011.

11. Yahya R, Denidni TA. Design of a new dual-polarized ultra-wideband planar CPW fed antenna In: IEEE international symposium on

antennas and propagation. 2011. p. 1770–2.

368-370

60.

Authors: Jebitha J, R. Elanthirayan

Paper Title: Comparison of Buck Converter and Resonant Buck Converter

Abstract: The purpose of this paper is to compare the performance of the conventional buck converter and the

resonant buck converter. The input supply given to the power electronics converter will be the battery of 48VThe

resistive load is connected at the output of the converter. The dc-dc converter is controlled by using the PWM

technique. In resonant converter with respect to the load the power electronics switches will not experience any

current stress or voltage stress. Simulation outputs are provided. Simulation is done by MATLAB/SIMULINK

software.

Keywords: Zero Voltage Switching (ZVS), Zero Current Switching (ZCS), Insulated Gate Bipolar Transistor

(IGBT), Metal Oxide Semiconductor Field Effect Transistor (MOSFET), Pulse Width Modulation (PWM).

References: 1. Y. C. Chuang and Yu-Lung Ke, ―A Novel High-Efficiency Battery Charger With a Buck Zero-Voltage-Switching Resonant Converter,”

IEEE Trans. on energy conversion, vol. 22, no. 4, December 2007

2. Y.C.Chuang, “High-Efficiency ZCS Buck Converter for Rechargeable Batteries,” IEEE Trans. Power Electron., vol. 57, no. 7,pp. 2463-

2472, Jul. 2010

3. Shen-Yaur Chen and Jin-Jia Chen “Study of the Effect and Design Criteria of the Input Filter for Buck Converters with Peak Current-

Mode Control Using a Novel System Block Diagram,”IEEE Trans. Power electronics,2010

4. Wen Chung Chen, TsorngJuu Liang, Lung Sheng Yang,JiannFuh Chen “Current-Fed DC-DC Converter with ZCS for High Voltage

Applications,”IEEE Trans. Power electronics,2010

5. K. Liu, R. Oruganti, and F. C. Lee, "Resonant Switches – Topologies and Characteristics," IEEE Power Electronics Specialists

Conference, 1985 Record, pp. 106-1 16 (IEEE Publication 85-1 17-0).

6. K. H. Liu and F. C. Lee, "Zem Voltage Switching Technique in DCDC Converters,'' IEEE Power

7. Rashid H.Muhammad, Power Electronics – Circuits, Devices and Applications, Prentice Hall India, 2004

8. Bimbra P. S., Power Electronics, Khanna Publishers, 2007

9. Muhammad SaadRahman, Master thesis in Electronic Devices at Linköping Institute of Technology, Buck Converter Design Issues

10. YaliXiong, Shan Sun, HongweiJia, Patrick Shea and Z. John Shen, IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 24,

NO. 2, FEBRUARY 2009, New Physical Insights on Power MOSFET Switching Losses.

11. Wilson Eberle, Zhiliang Zhang, Yan-Fei Liu and Paresh C. Sen ; IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 24, NO.

3, MARCH 2009, A Practical Switching Loss Model for Buck Voltage Regulators.

371-375

61.

Authors: Jebitha J, R G Nirmala

Paper Title: Simulation of Interleaved Flyback Converter with Incremental Conductance MPPT for Solar PV Array

using MATLAB/SIMULINK

Abstract: The simulation of an interleaved flyback converter with solar system as input source is discussed in

this paper. The interleaved flyback converter topology is adopted to prevent the generation of excess heat in

devices, to avoid large voltage ripple in the load and also to minimise the size of the filtering elements. The control

of the converter circuit is performed using Maximum Power Point Tracking (MPPT) controllers to get maximum

power from the solar panel. In Maximum Power Point Tracking we used incremental conductance algorithm. This

method is widely implemented because it has the higher steady-state accuracy and environmental adaptability.

Simulation was performed with different duty cycle to study the output voltage variations thus the results obtained

can be analysed. The design has been tested through simulation in MATLAB/SIMULINK model.

Keywords: Incremental Conductance (InC) algorithm, Maximum Power Point Tracking (MPPT).

References: 1. Double Voltage Step-up Photovoltaic Micro inverter Diana Lopez, Freddy Flores-Bahamonde, HuguesRenaudineau, Samir Kour

Electronics Engineering Department, Universidad Tecnica Federico Santa Maria, Valparaiso, Chile.

2. Novel Control Scheme for Interleaved Flyback Converter Based Solar PV Micro inverter to Achieve High Efficiency Tirthasarathi Lodh;

Nataraj Pragallapati, Member, IEEE and Vivek Agarwal, Fellow, IEEE.

3. Y. S. Noh, B. Y. Choi, S. R. Lee, J. K. Eom and C. Y. Won, "An Optimal Method to Design a Trap-CL Filter for a PV AC-Module Based

on Flyback Inverter," IEEE Transactions on Industry Applications, vol. 52, no. 2, pp. 1632-1641, March-April 2016.

4. O. Deleage, J. C. Crebier, M. Brunet, Y. Lembeye and H. T. Manh, "Design and Realization of Highly Integrated Isolated DC/DC

Microconverter," IEEE Transactions on Industry Applications, vol. 47, no. 2, pp. 930-938, March-April 2011

5. S. Poshtkouhi and O. Trescases, "Flyback Mode for Improved Low-Power Efficiency in the Dual-Active-Bridge Converter for

Bidirectional PV Microinverters With Integrated Storage," IEEE Transactions on Industry Applications, vol. 51, no. 4, pp. 3316-3324,

July-Aug. 2015.

6. A. Mukherjee, M. Pahlevaninezhad and G. Moschopoulos, "Single Stage Flyback Microinverters in Solar Energy Systems," Intelec 2013;

35th International Telecommunications Energy Conference, SMART POWER AND EFFICIENCY, Hamburg, Germany, 2013, pp. 1-6.

7. Rashid H.Muhammad, Power Electronics – Circuits, Devices and Applications, Prentice Hall India, 2004

8. Bimbra P. S., Power Electronics, Khanna Publishers, 2007

9. Muhammad SaadRahman, Master thesis in Electronic Devices at Linköping Institute of Technology, Buck Converter Design Issues

10. YaliXiong, Shan Sun, HongweiJia, Patrick Shea and Z. John Shen, IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 24,

NO. 2, FEBRUARY 2009, New Physical Insights on Power MOSFET Switching Losses.

11. Wilson Eberle, Zhiliang Zhang, Yan-Fei Liu and Paresh C. Sen ; IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 24, NO.

3, MARCH 2009, A Practical Switching Loss Model for Buck Voltage Regulators.

12. J.Appelbaum- “Starting and steady-state characteristics of DC motors powered by solar generators”, IEEE Trans., EC-I (1986)17 25.

13. H.Altas,A.M. Sharaf- “A Photovoltaic Array Simulation Model for MATLAB-Simulink GUI Environment”, IEEE, (ICCEP '07), June14-

16, 2007, Ischia, Italy

14. WZ Faro, M.K.Balaehander-“Dynamic performance of a DC shuntmotor connected to a PV array”, IEEE Transaction, EC-3 (1988)613-

617.

376-378

15. M. Buresch-“PV Energy Systems Design and Installation”,McGraw-Hill, New York, 1983.

16. Carratero-“A new approach to obtain I-V and P-V curves of photovoltaic modules by using DC/DC converters”,Rec. IEEE PVSpecialist

Conference, 2005, pp.1769-1722.

62.

Authors: Anbu.G, Ajith H, Ezhilan V, Magesh Gowtham T, Pradeep L, Sathish Bharathi M

Paper Title: Design of Variable Adaptive Suspension – A Review

Abstract: The design of adaptive suspension system for ride comfort and performance is discussed .The

drawbacks of various suspension system and methods to overcome them are listed along with various material

which have desirable characteristics are describe in brief .Section are devoted for describing road surfaces,

modeling vehicle and setting of performance criteria .The active, passive and slow adaption of variable stiffness

suspension are compared for optimal performance and comfort.

Keywords: Suspension system, Variable stiffness and MRdampers.

References: 1. N Lavanya, P Sampath Rao, M Pramod Reddy, Design and Analysis of A Suspension Coil Spring For Automotive Vehicle ISSN : 2248-

9622, Vol. 4, Issue 9( Version 5), September 2014, pp.151-157

2. R. S. SHARP a & D. A. CROLLA ,Road Vehicle Suspension System Design - a review Department of Mechanical Engineering,

University of Leeds, Leeds, LS2 9JT, U.K Published online: 27 Jul 2007

3. Weichao Sun, Huijun Gao, Okyay Kaynak, Finite Frequency Control for Vehicle Active Suspension Systems, IEEE Transactions on

control systems technology, Vol. 19, no. 2, march 2011

4. Huijun Gao, James Lam, Changhong wang, Multi-Objective Control of Vehicle active suspension systems via Load dependent controllers,

Journals of Sound and Vibration 290(2006) 654-675

5. G Z Yao , F F Yap, G Chen, W H Li, S H Yeo, MR damper and its application for semi-active control of vehicle suspension system,

Mechatronics 12 (2002) 963–973

6. G Priyandoko, M Mailah, H Jamaluddin ,Vehicle active suspension system using skyhook adaptive neuro active force control, Mechanical

Systems and Signal Processing 23 (2009) 855–868

7. C Kim, P I Ro, A sliding mode controller for vehicle active suspension systems with non-linearities, Proc Instn Mech engrs Vol 212 part

D, Jan 24, 2015

8. Dean Karnopp, Donald Margolis, Adaptive Suspension Concepts for Road Vehicles, Vehicle System Dynamics, 13 (1984). pp. 145-1150

9. Xubin Song, Mehdi Ahmadian, Steve Southward, Lane R. Miller, An Adaptive Semiactive Control, Algorithm for Magneto rheological

Suspension Systems, Journal of Vibration and Acoustics, OCTOBER 2005, Vol. 127 / 493-502

10. Weichao Sun, Huijun Gao, Okyay Kaynak, Adaptive Backstepping Control for Active Suspension Systems With Hard Constraint

IEEE/ASME Transactions on Mechatronics, Vol 18, No. 3, June 2013

11. Myoungho Sunwoo, Ka C Cheok, N. J. Huang , Model Reference Adaptive Control for Vehicle Active Suspension Systems ,IEEE

Transactions on Industrial Electronics, Vol. 38, No. 3, June 1991 ,217

12. Lalitkumar Maikulal Jugulkar, Shankar Singh, Suresh Maruti Sawant, Analysis of suspension with variable stiffness and variable damping

force for automotive aplicationsAdvances in Mechanical Engineering 2016, Vol. 8(5) 1–1

13. A Hac, Adaptive Control of Vehicle Suspension, Vehicle System Dynamics, 16(1987), pp.57-74

14. R S Sharp ,A Hassan , An Evaluation of passive Automotive Suspension Systems with Variable Stiffness and Damping Parameters,

Vehicle System Dynamics, 15 (1986). pp. 335-350

15. H P Monner, Smart materials for active noise and vibration reduction,Keynote Paper Novem – Noise and Vibration: Emerging Methods,

Saint-Raphaël, France, 18-21 April 2005

16. Anne-Marie Albanese, Kenneth A Cunefare, Smart fabric adaptive stiffness for active vibration absorbers Vol-5383, 490-497, Jan 2015

17. Boyce S. Chang, Ravi Tutika, Joel Cutinho, Stephanie Oyola-Reynoso, Jiahao Chen, Michael D. Bartlett, Martin M. Thuo, Mechanically

triggered composite stiffness tuning through thermodynamic relaxation (ST3R),The Royal Society of Chemistry, Volume 5,Number

3,May 2018,Pages 416-422

18. Bryan E Schubert, Dario Floreano, Variable stiffness material based on rigid low-melting-point-alloy micro structures embedded in soft

poly (dimethylsiloxane) (PDMS)

19. Yanqing Liu, Hiroshi Matsuhisa, Hideo Utsuno, Semi-active Vibration isolation system with variable stiffness and damping control,

Journal of sound and Vibration,313,(2008) ,16-28

20. Junjiro Onoda,Takao Endo, Hidehiko Tamaoki, Naoyuki Watanabe, Vibration Suppression by Variable-Stiffness Members, AIAA

Journal, Vol.29, No 6, June 1991

21. J A Tamboli, S G Joshi, Optimum Design of a Passive Suspension system of a vehicle subjected to Actual random Road Excitations,

Journal of Sound and Vibration, (1999), 219(2) 193-205

22. P L Walsh , J S Lamancusa, A Variable Stiffness Vibration Absorber for Minimization of Transient Vibrations, Journal of Sound and

Vibration, (1992), 158(2), 195-211

23. Mia Yu, X M Dong, S B Choi, C R Liao, Human simulated intelligent control of Vehicle suspension system with MR dampers, Journal of

Sound and Vibration, 319, (2009), 753-767

24. D. Fischer, R. Isermann Mechatronic semi active and active vehicle suspensions, Control Engineering Practice 12 (2004) 1353–136

25. Ian Fialho and Gary J. Road Adaptive Active Suspension Design Using Linear Parameter-Varying Gain-SchedulingIEEE Transactions On

Control Systems Technology, Vol. 10, No. 1, January 2002.

379-382

63.

Authors: Naresh. C, Karthikeyan. R

Paper Title: Simulation and Performance of Modified Coupled Inductor based SEPIC Converter with High Static

Gain

Abstract: This paper proposes amodified SEPIC converter in coupled inductor based high gain dc-dc

converter. The proposed topology presents low switch voltage and high efficiency for low input voltage, low ripple

current and high output voltage applications. Two alternatives with and without magnetic coupling are analyzed.

The magnetic coupling allows increasing the static gain with a reduced switch voltage. The theoretical analysis and

experimental results are presented. The efficiency obtained with the prototype without magnetic coupling was

81%, 83.2%.With magnetic coupling85.5% was improved to nominal output power. Efficiency equal to 85% was

obtained with the prototype model.

383-389

Keywords: Multi-Converter System, Single-Ended Primary Inductance Converter (SEPIC).Coupled inductor,

Pulse width modulation (PWM).

References: 1. -M.Castilla, -L.G.deVicuna, -J.M.Guerrero, -J.Matas, &-J.Miret,‘-Design-of-voltagemode-hysteretic –controllers-for-synchronous-buck-

converters –supplying-microprocessor-loads’, -IEE-Proceedings on-Electrical-Power-Applications, -Vol-152, -No-5, -pp-1171– 1178, -

Sep-2005.

2. M.Castilla,-L.G.deVicuna,-J.M.Guerrero,-J.Miret,& -N.Berbel, ‘-Simple-low-cost-hysteretic-controller for-single-phase-synchronous-

buck-converter’, -IEEE-Trans..,on-P.E,-Vol-22,-No-4,-pp-1232– 1241, -Jul-2007.

3. M.Castilla,-L.G.deVicuna,-J.M.Guerrero,-J.Matas,&-J. Miret, ‘-Designing-VRM-hysteretic-controllers-for optimal-transient-response’,-

IEEE-Tran..,-on-I.E, -Vol.-54, -No-3, -pp-1726–1738, Jun-2007.

4. M.P.KaŸmierkowski,-L.Malesani, “-Current-Control Techniques-for-Three-Phase-Voltage-Source-PWM-Converters:-A-Survey,”-in-

IEEE-Trans..,-on-I.E, -Vol-45, -No-5, -Oct-1998, pp-691-703.

5. M.P.KaŸmierkowski,-M.A.Dzieniakowski, “-Review of-Current-Regulation-Methods-For-VS-PWM- Inverters,”-in-Proc.-of-IEEE-

International –Symposium-on-I.E,-ISIE’93,1-3.-Jun-1993, -Budapest, -Hungary, pp.-448-456

6. D.M.Brod, -A.W.Novotny, “-Current-Control of-VSI—PWM-Inverters,”-in-IEEE-Trans..,-on-I.A, -Vol-IA-21, -No-4, -May/Jun-1985, -

pp-562-570

7. SanjayaManiktala, “-Voltage-mode, -Current-mode &-Hysteretic-control,” -Mi-crosemi, -technical-note -TN-203, -2012.

8. Lo, Yu Kang, Yu Chen Liu, Jing Yuan Lin, Chung Yi Lin and Shih Jen Cheng, "Analysis and design of an active clamping zero voltage

switching isolated inverse SEPIC converter", International Journal of Circuit Theory and Applications, Vol.40, No.3, pp.287-305, 2012

9. Sabzali, Ahmad J., Esam H. Ismail and Hussain M. Behbehani, "High voltage step up integrated double Boost–Sepic DC–DC converter

for fuel cell and photovoltaic applications", Renewable Energy, Vol.82, pp.44-53, 2015

10. Chiu, Huang Jen and Shih Jen Cheng, "Design considerations of an SEPIC PFC converter for driving multiple lighting LED lamps",

International Journal of Circuit Theory and Applications, Vol.37, No.8, pp.928-940, 2009

11. Yao, Jia, Alexander Abramovitz and Keyue Ma Smedley, "Analysis and design of charge pump assisted high step up tapped inductor

SEPIC converter with an “inductorless” regenerative snubber", IEEE Transactions on Power Electronics, Vol.30, No.10, pp.5565-5580,

2015

12. Di Capua, Giulia, and Nicola Femia, “A critical investigation of coupled inductors SEPIC design issues", IEEE Transactions on Industrial

Electronics, Vol.61, No.6, pp.2724-2734, 2014

13. Tsang, K. M. and W. L. Chan, "Fast acting regenerative DC electronic load based on a SEPIC converter", IEEE transactions on power

electronics, Vol.27, No.1, pp.269-275, 2012

14. Park, Ki Bum, Gun Woo Moon and MyungJoongYoun, "Nonisolated high step up boost converter integrated with sepic converter", IEEE

transactions on Power Electronics, Vol.25, No.9, pp.2266-2275, 2010

15. Veerachary, Mummadi, "Two loop controlled buck–SEPIC converter for input source power management", IEEE transactions on

industrial electronics, Vol.59, no.11, pp.4075-4087, 2012

16. Bianchin, Carlos Gabriel, Roger Gules, Alceu Andre Badin, and Eduardo Felix RibeiroRomaneli, "High power factor rectifier using the

modified SEPIC converter operating in discontinuous conduction mode", IEEE Transactions on Power Electronics, Vol.30, No.8,

pp.4349-4364, 2015.

64.

Authors: S.Dhandayuthapani, K.Anisha

Paper Title: SMC Shunt Active Filter in IEEE Thirty Bus System with Improved Dynamic Time Response

Abstract: This paper aims on improve the dynamic performance of closed loop controlled shunt active filter

with PI, SMC is connected to IEEE 30 bus system. It has been drawn that with none control mechanism, the

output voltage cannot be controlled and it will provides a giant deviation in output voltage in terms of error signal

and that will decline the output current, as a result steady state error will increase, which will reduce the

performance. So, it is mandatory to maintain the output voltage and that can be achieved by a proper

feedback control system. This Paper, demonstrates the comparison of time domain parameters and how the results

improve in presence of controller circuit for the IEEE 30 bus system.

Keywords: IEEE Thirty bus system; Slide Mode Controller (SMC); Time domain parameters.

References: 1. Attia Sahara, Abdelhalim Kessa , Lazhar Rahmani, Jean-Paul Gaubert, “ Improved Sliding Mode Controller for Shunt Active Power

Filter”. J Electr Eng Technol.Vol 11(3), 709-716,2015

2. Bhattacharjee.K. “Harmonic Mitigation by SRF Theory Based Active Power Filter using Adaptive Hysteresis Control”. Conference Power

and Energy Systems: Towards Sustainable Energy, 1- 6,2014

3. Bhattacharya,s., Divan,D.M.,1995. “Hybrid series active/parallel passive power line conditioner with controlled harmonic injection”.U. S.

patent 5 465 203,1995

4. ChaouiAbdelmadjid., KrimFateh., Gaubert Jean Paul., Rambault Laurent. “DPC controlled three phase active filter for power quality

improvement”. Electrical Int J Electr Power Energy System.30.476-85,2008

5. Dhandayuthapani,S.,Anisha,K.“Proportional Resonant Controlled Shunt Active Filter in IEEE Thirty Bus System with Improved Dynamic

Time Response”.International Journal of Engg.and Tech.334-339,2018

6. Hamoudi, F.,Chaghi,A., Adli,M., Amimeur ,H. “A Sliding Mode Control for Four wire Shunt Active Filter”. Journal of Electrical

Engineering, Vol 62, No. 5, 267-273,2011

7. Mansoor, A.,Gardy, W.M.,Staats, P.T.,Thallam, R.S., Doyle, M.T., and Samotyj, M. “Predicting the net harmonic current produced by

large numbers of distributed single phase computer loads”. IEEE Trans. Power Delivery, Vol-10, 2001-2006,1994

8. Parmod Kumar, Alka Mahajan “Soft Computing Techniques for the control of an Active Power Filter”. IEEE Transaction on Power

Delivery, Vol-24, 452-461,2009

9. Salmeron,P., Litran, S.P.“Improvement of the Electric Power Quality Using Series Active and Shunt Passive Filters”. IEEE Transaction

on Power Delivery, vol. 25, no. 2, 1058-1067,2010

10. Suresh Mikkili., Panda A.K. “Real time implementation of PI&FLC based SHAF control strategies for Power quality improvement” Int J

Electr Power Energy Systems 43(1) 1114-26,2012

11. Suresh Mikkili, Panda,A.K. “Performance analysis and real time implementation of shunt active filter Current control strategy with type-1

and type-2 FLC triangular M.F. International Transactions on Electrical Energy Systems, John-Wiley, Vol-24, Issue-3, 347–362, 2014

12. Rudnick, H., Juan Dixon , Luis Moran , “Active power filters as a solution to power quality problems in distribution networks” IEEE

390-399

power & energy magazine,1-5(30), 32-40, 2003

13. Wei,L., Chunwen,L., Changbo,X. “Sliding Mode Control of a Shunt Hybrid Active Power Filter Based on the Inverse System Method”.

Electrical Power and Energy Systems, Vol. 57, 39-48,2014

65.

Authors: C.Nandagopal, G.Shanmugavadivel

Paper Title: Energy-Efficient Big Data Specific Gathering Algorithm for a WSN

Abstract: Big data become as hot topic due to increase in the communication technology. Distributor wireless

sensor networks is major factor in generating big data. We come across various challenges in gathering real time

data. Various routing algorithms are supposed to overcome these challenges. Clustering communication is done by

is done by residual energy available in the sensor nodes. We propose here BDSEG algorithm to have a better live

time for sensor nodes. We verify this algorithm using MATLAB.

Keywords: Big data, gathering, matlab, residual energy.

References: 1. Chamberland J-F, Veeravalli V. Decentralized detection in sensor networks. IEEE Transactions on Signal Processing 2003;51(2):407–16.

Chang R-S, Wang S-H. Self-deployment by density control in sensor networks. IEEE Transactions on Vehicular Technology

2008;57(3):1745–55.

2. Chen A, Kumar S, Lai TH. Designing localized algorithms for barrier coverage. In: Proceedings of the 13th annual ACM international

conference on mobile computing and networking, ser. MobiCom’07. New York, NY, USA: ACM; 2007. p. 63–74.

3. Chen A, Lai TH, Xuan D. Measuring and guaranteeing quality of barrier-coverage in wireless sensor networks. In: Proceedings of the 9th

ACM international symposium on mobile ad hoc networking and computing, ser. MobiHoc’08. New York, NY, USA: ACM; 2008. p.

421–30.

4. Chen B, Jamieson K, Balakrishnan H, Morris R. Span: an energy-efficient coordina- tion algorithm for topology maintenance in ad hoc

wireless networks. Wireless Networks 2002;8:481-94,doi:10.1023/A:1016542229220.

5. Cheng W, Li M, Liu K, Liu Y, Li X, Liao X. Sweep coverage with mobile sensors. In: IEEE international symposium on parallel and

distributed processing, 2008. IPDPS 2008; 2008a. p. 1–9.

6. Cheng X, Du D-Z, Wang L, Xu B. Relay sensor placement in wireless sensor networks. Wireless Networks 2008b;14:347–55,

doi:10.1007/s11276-006- 0724-8.

7. K. Sujatha, C. Nandagopal “ Realization of gateway relocation using admission control algorithm in mobile WIMAX networks”, 4th IEEE

International Conference on Advanced Computing(ICoAC), pp. 1-5, 2012.

8. C. Nandagopal“ A Comparative analysis of coding schemes in low power baseband Transceiver IC for WBAN”, International Conference

on computing, Electronics and Electrical Technologies (ICCEET), pp. 812-817, 2012.

9. S. Sariga, C.Nandagopal “Network on Chip Architectures”, Journal of Engineering and Technology Research, Vol. 4, issue. 5, pp .1-9,

2016.

400-401

66.

Authors: G.Shanmugavadivel, C.Nandagopal

Paper Title: Certain Investigation in Automatic Annexation Detection in a Mobile Multimedia Framework

Abstract: The cellular healthcare enterprise is thriving because of the boom in pc processing power,

improvement of next-era verbal exchange generation, and immoderate garage ability. Portable mixed media

sensors can accumulate social insurance insights, which might be handled to make options on the wellbeing

notoriety of customers. With regards to this, we advocate a cell sight and sound human services system in this

paper, in which a programmed addition location machine is inserted as a case have an investigate. Inside the

proposed framework, electroencephalogram signals from a head-set up set are recorded and prepared the use of

convolution neural systems. A benevolent module decides if or not the signs grandstand extension. Trial results

demonstrate that the proposed framework can advantage extreme phases of precision and affectability.

Keywords: Cell multimedia healthcare, annexation detection, convolution neural community, GVM, EEG alerts.

References: 1. Epilepsy_World Health Organization Fact Sheet. [Online]

2. A. Varsavsky, I. Mareels, and M. Cook, Epileptic Seizures and the EEG:Measurement, Models, Detection and Prediction. Boca Raton,

FL, USA:CRC Press, 2011.

3. M. Sharma and R. B. Pachori, ``A novel approach to detect epileptic seizures using a combination of tunable-Q wavelet transform and

fractal dimension,'' J. Mech. Med. Biol., vol. 17, no. 7, p. 1740003, 2017.

4. J. N. Kutz, X. Fu, and S. L. Brunton, ``Multiresolution dynamic model decomposition,'' SIAM J. Appl. Dyn. Syst., vol.15, no. 2, pp.

713_735, 2016

5. B.W. Brunton, L. A. Johnson, J. G. Ojemann, and J.N. Kutz, ``Extracting spatial_temporal coherent patterns in large-scale neural

recordings using dynamic mode decomposition,'' J. Neurosci. Methods, vol. 258, pp. 1_15, Jan. 2016.

6. S.Palanivel Rajan, “A Significant and Vital Glance on “Stress and Fitness Monitoring Embedded on a Modern Telematics Platform”,

Telemedicine and e-Health Journal, ISSN: 1530- 5627 (Online ISSN: 1556-3669), Vol. No.: 20, Issue No.: 8, pages: 757-758, 2014

7. S.Palanivel Rajan, T.Dinesh, “Statistical Investigation of EEG Based Abnormal Fatigue Detection Using LabVIEW", International

Journal of Applied Engineering Research, ISSN: 0973-4562, Vol. 10, Issue 43, pp.30426-30431, 2015. (SCOPUS).

402-406

67.

Authors: K.Ramash Kumar, S. Balakumar, S. Azath Hussain

Paper Title: Improved Performance of KY Positive Output Boost Converter using Classical PI Controller

Abstract: This paper studies on modeling, simulation with output potential control of KY-POBC using

proportional integral controller (PIC). Due to time varying and switching characteristics of KY-POBC and also its

dynamic performance is complex. Owing to increase the dynamic characteristics with output potential control of

KY-POBC, a PIC is designed. The dynamic equation of the KY-POBC is derived with help of averaging method at

first and then PIC is developed using Zeigler-Nichols Tuning method. The analysis of designed controller is

407-411

verified at different operating conditions via. the transient region, supply voltage variation and the load variation

by making MATLAB/Simulink model. The results are showed designed controller proficiency performance at

various working regions.

Keywords: Boost converter, PIC, and KY converter.

References: 1. F. L. LUO AND H. YE, “Negative output multiple-lift push-pull SC Luo-converters,” IEEE PESC’03, vol. 4, pp. 1571-1576, 2003.

2. FANG LIN LUO AND HONG YE, “Negative output super-lift converters,” IEEE Trans. Power Electron., vol. 18, no. 5, pp. 1113-

1121, 2003.

3. MAHDAVI, J., EMADI, A., TOLIYAT, H.-A., “Application of state space averaging method to sliding mode control for PWM DC/DC

converters,” IEEE Industry Application Society Annual Meeting, New Orieans, Louisianan, 1997, pp. 820-827

4. K. I. HWU, W. C. TU AND Y. H. CHEN “A KY Boost Converter ,” IEEE Trans. Power Electronics, vol. 25, n.11, Nov pp. 2699 – 2703.

5. COMINES, P., MUNRO, N., “PID controllers: recent tuning methods and design to specification,” IEEE Proc. Control Theory

Application, 2002, 149, (1), pp.46-53.

6. R. KALAIVANI, K. RAMASH KUMAR, S. JEEVANANTHAN, “Implementation of VSBSMC plus PDIC for Fundamental Positive

Output Super Lift-Luo Converter,” Journal of Electrical Engineering, Vol. 16, Edition: 4, 2016, pp. 243-258.

7. K.RAMASH KUMAR, S.JEEVANANTHAN, S.RAMAMURTHY, “Improved Performance of the Positive Output Elementary Split

Inductor-Type Boost Converter using Sliding Mode Controller plus Fuzzy Logic Controller,” WSEAS TRANSACTIONS on SYSTEMS

and CONTROL, Vol. 9, 2014, pp. 215-228.

8. K. RAMASH KUMAR, “Implementation of sliding mode controller plus proporotinal double integral controller for neagtive output

elementary boost converter,” Alexandria Engineering Journal, 2016, Vol. 55, No. 2, pp. 1429-1445.

9. RAMASH KUMAR, K., JEEVANANTHAN, S., “Design of sliding mode control for negative output elementary super lift Luo-Converter

operated in continuous conduction mode,” ICCCCT’10, Tamilnadu, India, pp. 138-148.

10. S.SENTAMIL SELVAN, K.RAMASH KUMAR, R.BENSRAJ, “Modeling, Simulation and Design of Variable Structure Based Sliding

Mode Controller for KY-Voltage Boosting Converter,” WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS, Vol. 15, 2016,

pp.143-154.

11. KUPPAN RAMASH KUMAR, SEENITHANGAM JEEVANANTHAN,” Sliding mode control design for current distribution control in

Paralled Positive Output Elementary Super Lift Luo Converters”, Journal of Power Electronics (JPE) Korea, Vol.11, No.5, September

2011, pp. 639-654.

12. K. RAMASH KUMAR, S. JEEVANANTHAN, “A Sliding Mode Control for Positive Output Elementary Luo Converter,” Journal of

Electrical Engineering, Volume 10/4, December 2010, pp. 115-127.

13. K. RAMASH KUMAR, S. JEEVANANTHAN, “Analysis, Design and Implementation Of Hysteresis modulation sliding mode controller

for negative output elementary boost converter”, Journal of Electric Power Components and Systems, Vol.40, No.3, 2012, pp. 292-311.

14. K. RAMASH KUMAR, S. JEEVANANTHAN, “PI Control for Positive Output Elementary Super Lift Luo- Converter,” International

Journal of Electrical and Electronics Engineering, 4:7 2010, pp. 440-446.

15. T. PADMAPRIYA AND V. SAMINADAN, “Improving Throughput for Downlink Multi user MIMO-LTE Advanced Networks using

SINR approximation and Hierarchical CSI feedback”, International Journal of Mobile Design Network and Innovation- Inderscience

Publisher, ISSN : 1744-2850 vol. 6, no.1, pp. 14-23, May 2015.

16. T. PADMAPRIYA AND V. SAMINADAN, “Inter-cell Load Balancing technique for multi-class traffic in MIMO-LTE-A Networks”,

International Journal of Electrical, Electronics and Data Communication (IJEEDC), ISSN: 2320- 2084, vol.3, no.8, pp. 22-26, Aug 2015.

17. S.V.MANIKANTHAN AND V.RAMA“ Optimal Performance Of Key Predistribution Protocol In Wireless Sensor Networks”

International Innovative Research Journal of Engineering and Technology ,ISSN NO: 2456-1983,Vol-2,Issue –Special –March 2017.

18. S.V.MANIKANTHAN AND T.PADMAPRIYA “Recent Trends In M2m Communications In 4g Networks And Evolution Towards

5g”International Journal of Pure and Applied Mathematics, ISSN NO:1314-3395, Vol-115, Issue -8, Sep 2017.

19. RAJESH, M., AND J. M. GNANASEKAR. & quot; GCCover Heterogeneous Wireless Ad hoc Networks .& quot; Journal of Chemical

and Pharmaceutical Sciences (2015): 195-200.

20. RAJESH, M., AND J. M. GNANASEKAR. & quot; An optimized congestion control and error management system for OCCEM. & quot;

International Journal of Advanced Research in IT and Engineering 4.4 (2015): 1-10.

68.

Authors: Priyadharshini M. K, R. Sivakami, M.Janani

Paper Title: Sooty Mould Mango Disease Identification Using Deep Learning

Abstract: In India, half of the population depends on agriculture to lead their life. Our country is the largest

producer of Mangoes. The scientific name of the plant is Mangiferae. Mango plants are affected by the fungus and

pests which reduces the quality and quantity of the product. Already farmers are suffering from lot many problems

and we have to support them to improve their economy. Our project aims to increase the mango fruit productivity

by controlling the plant disease by early identification through deep learning. We have taken a major disease that

affects the mango plant in Tamil Nadu- Sooty Mould In places like Dharmapuri and Triuvallur as the varieties of

Mangoes such as Neelum, Alphonso, Bangalora are mostly affected by this disease and the yield drops out. Plants

infected by Sooty Mould have a velvety coating over the leaves. It is due to the honey dew secretions. The insects

stick to leaf surface and lead to fungal growth. But no direct damage is done by the fungus. The photosynthetic

activity is affected adversely due to the blockage of stomata. We propose a solution for detection and classification

of plant leaf disease in early stage itself. Deep learning constitutes a modern technique for image processing and

data analysis. Deep learning technique has lot of applications in agricultural domain. The Deep Learning

methodology, CNN model is developed to perform plant disease detection from leaves images.

Keywords: Deep Learning, CNN, Machine Learning, Agriculture, Sooty Mould, Mango.

References: 1. Andreas Kamilaris, Francese X. PrenafetaBold “Deep Learning in agriculture:A Survey”. Journal on Computer and Electronics, vol

147,published on Elsevier 2018.

2. Barbaedo, Garcia, “Digital Image Processing Technique for Detecting, Quantifying and Classifying plant diseases” IEEE journal,

published on February 2017

412-415

3. Beyene, Narayan A. “Plant Disease Prediction Using Image Processing and Machine Learning Technique:Survey”. IEEE journal of

computer application. published on February 2018.

4. Chen, Kuanglin Chao, Moon S. Kim,” Machine Vision Technology for Agricultural Applications”, published on 2016 Elsevier.

5. Ghazala yasin, Asit Kumar Das, ”A Hierarchical Strategy for Rice Leaf Disease Detection”. IEEE on Intelligent Computing. Published on

July 2017.

6. Jagadeesh D. Pujari, Rajesh Yakkundimath Abdulmunaf S. Byadgi “ Image Processing Based Detection of Fungal Disease in Plants”.

Conference on Information and Communation Technology. Published on 2015 Elseiver.

7. Jayaprakash, Sethpathy, Veni.S “Opencv Based Disease Identification of Mango Leaves”, IJET 2017.

8. K. Bharathi, D. Srunitha, “Mango leaf unhealthy Region Detection and Classification. Published in Computational vision and Bio Inspired

computing. Published on 2018.

9. Konstantinos P. Ferentinos, “Deep Learning modesl ofr plant disease detection and diagnosis” Elsevier 2018

10. Sukhvir Kaur, Shreelekha Pandey, Shivani Goel, “Plants Disease Identification and Classification through leaf images: A Survey”

Achieves on computation method Springer . Published on January 2018.

11. T. Rump, U. Steiner, “ Early Detection and Classification of plant disease with Support Vector Machine based on hyper spectral

reflectance”, volume 74, issue1,published on October 2010.

69.

Authors: Arun Francis G, V.Mithya, Balaji Venkatraman.S, Dhinesh Raja A.K, Masanadhurai.E

Paper Title: Solution to Environment Disturbances using IoT (Making Alive)

Abstract: The main aim of the project is provide solutions to the earth’s major threats like Deforestation,

Pollution, Population, and Starving and water lack, food lack. The GLOBE with all colours of Peace and happiness

has the right place for life. All creatures in the world have the equal chances of living. HUMAN has the most

dominance of all. Making one’s human life easier has become the prime motto nowadays. Towards creating an

easier life, Humans make environment polluted neither concentrating on other bio-diversities nor on the ambiance.

Having a better life is more important than having easier life. This module has scrapped for making awareness to

humans about their living. Main theme of the module is towards TREES, POLLUTION and Food lack. This

module has taken Coimbatore, Tamil Nadu, India as the study area. The Population of a specific region is selected

also Population count of trees in the same selected region is taken. The demand of oxygen in atmosphere in future

is calculated by comparing the intake of oxygen by human and exhale of oxygen by trees. The comparisons are

done by taking the rate of increase in population and rate of decrease in trees. This module also concentrates on the

water wasted in an area than the water must be consumed. The comparisons are made with the water consumed by

a normal human and with the strategy (by WHO) of water consumed by normal human. This module also

concentrates in the pollution made in the environment. The pollution particles present in normal clean pure air is

taken as base condition. This base condition is frequently Checked for deviation in the environment and analysed.

All these deviations are plotted as graph and provided in a website as Cumulative results. Hoping a change, the

results are manipulated for HUMANS..

Keywords: Food scarcity, water scarcity, Trees welfare, wild life, biodiversity, human population.

References: 1. https://www.univertoday.com/65588/what-percent-of earth-is-water/

2. https://landarchs.com/8-amazing-facts-trees-didnt-know/

3. https://www.universetoday.com/65588/what-percent-of-earth-is-water/

4. https://www.quora.com/How-much-oxygen-does-a-human-breath-in-daily/answer/Suriya-Narayanan-

13?__filter__&__nsrc__=2&__snid3__=1343305334

5. https://landarchs.com/8-amazing-facts-trees-didnt-know/

6. http://indianexpress.com/article/cities/delhi/the-most-polluted-city-in the-world-delhi-suffers-from-a-toxic-blend-study/

7. http://www.conserve-energy-future.com/various-pollution-facts.php

8. http://www.worldometers.info/

9. https://www.youtube.com/watch?v=_MYoZHp4qP8

416-419

70.

Authors: G.Arun Francis, M.Dhinesh, J.Arok Lijo, P.Hariprasad, K.Balasubramanian s

Paper Title: IoT Based Vehicle Emission Monitoring System

Abstract: An increase in automobile vehicle leads to an increase in air pollution since automobiles are the main

source of environmental pollution. The smoke emitted from the vehicle consists of gases like nitrogen oxides

(NOx), carbon monoxide (CO), and hydrocarbon (HC). approximately one-half of the nitrogen oxide gases, carbon

monoxide and one-fourth of hydrocarbon gases in our environment are emitted from automobile vehicles, which

leads to global warming. Due to poor vehicle maintenance and ignition defect. the gases emitted from the exhaust

may increase. In order to reduce environmental pollution and to increase vehicles life, we can use this system.

when the rate of gases emitted from the vehicle exceeds the threshold limit set by the government, our system will

alert to the user through LCD. Using IOT, the emission level is also displayed and stored in the database of a

vehicle owner. When the vehicle owner ignores it, the report will send to the transport office with entire details.

The entire system is controlled by Node MCU microcontroller.

Keywords: Smoke, IoT, gas sensor, LCD, Node MCU.

References: 1. S.P. Bangal1, Gite Pravin E2 IoT Based Vehicle Emissions Monitoring and Inspection System 2017 IJIREEICE

2. Chandra Mohan Reddy S 2015 Development of IoT based Vehicular Pollution Monitoring System

3. Ashita Jagasia1, Sanjana Advani2 IoT based Vehicle Monitoring System using Bluetooth Technology 2017 IJIRSET

420-422

4. 1.Priyadarshini.J.Patil, 2Revathi.M A Survey on Intelligent System for Vehicle Emission Monitoring 2018 IJETT

5. D.Arunkumar, K.Ajaykanth, M.Ajithkannan, Sivasubramanian Smart Air Pollution Detection and Monitoring Using IOT International

Journal of Pure and Applied Mathematics

6. Jagadish Nayak Round the Clock Vehicle Emission Monitoring using Io T for Smart Cities 2018 IJACSA

71.

Authors: Mithya V, Divya Prabha.N, Sisma Samlein S, Madhumitha M

Paper Title: Smart Toilets using Turbidity Sensor

Abstract: In the cutting edge world, the advances are definitely increased, yet at the same time the cleanliness in

our nation is under major risk. The abstract of this paper is to deliver clean and hygiene and disease free toilets. All

the public toilets must be clean and hygiene. In our country, our government has introduced the unique scheme

called “Swachh Bharat” (Clean India). Keeping the toilets uncontaminated is the one of the objective of the Clean

India scheme. This paper can be helpful to encourage the clean India project in majority. In future, it can show the

emerging part in clean India scheme. In an Existing system, they are focused only on identifying the dirt of the

toilets. In our proposed system, we have determined on keeping clean toilets, observing the sweeper’s

working activities and also stoping the use of contaminated toilet. It can dodge many types of syndromes. It may

create the consciousness amongst people about the toilet management in our country. Therefore, our development

is to use safe, disease free and hygienic toilets.

Keywords: Arduino, turbidity sensor, gsm module.

References: 1. Xavier Gibert, Vishal M Patel, and Rama Chellappa, in their IEEE paper titled as “Deep Multi-Task Learning for Railway Track

Inspection” Volume 18, Issue 1, Jan 2017, pp 153 – 167.

2. S Mohamed Ashiq, K Karthikeyan, S Karthikeyan. “Fabrication of Semi- Automated Pressurized Flushing System in Indian Railway

Toilet”, International Journal of Engineering and Advanced Technology (IJEAT), Volume-2, Issue- 3, February 2013.

3. Dr. Manoj Hedaoo, Dr. Suchita Hirde ,Ms. Arshi Khan “Sanitation In Indian Railway Premises: A Great Cause Of Concern”, International

Journal of Advanced Engineering Technology, Mar 2012, Volume 3, Issue 1, pp 50 -55.

4. Dhanajay G Dange, Dattaprakash G Vernekar, Sagar D Kurhade, Prashant D Agwane, “Methodology for Design and Fabrication of

Human Waste Disposal System for Indian Railway”, International Journal of Science Technology & Engineering, Volume 2, Issue 07,

January 2016, pp 14 – 19.

5. Mesch, F., Puente Le´on, F. & Engelberg, T., Train-based location by detecting rail switches. Computers in Railways VII, eds. J. Allen,

R.J. Hill, C.A. Brebbia, G. Sciutto & S. Sone, WIT Press, Southampton, pp. 1251–1260, 2000.

6. K. Osathanunkul, K. Hantarkul, P. Pramokchon, P. Khoenkaw and N. Tantitharanukul, “Design and Implementation of an Automatic

Smart Urinal Flusher”, International Computer Science and Engineering Conference (ICSEC2016), Chiang Mai, Thailand, Dec, 2016, pp

14-17.

7. J. Shah and B. Mishra, “IoT enabled Environmental Monitoring System for Smart Cities”, International Conference on Internet of Things

and Applications (IOTA), Maharashtra Institue of Technology, Pune, India, Volume 3, Issue 2, Jan 2016, pp 383- 388.

8. A. Zanella, S. Member, N. Bui, A. Castellani, L. Vangelista and M. Zorzi, “Internet of Things for Smart Cities,” IEEE Internet of Things,

Vol. 1, no. 1, pp. 22-32, 2014.

9. K. Hantrakul, P. Pramokchon, P. Khoenkaw, N. Tantitharanukul, and K. Osathanunkul, “Automatic Faucet with Changeable Flow based

on MQTT protocol”, International Computer Science and Engineering Conference (ICSEC2016), Chiang Mai, Thailand, 14-17 Dec, 2016.

10. C. H. Tsai, Y. W. Bai, M. B. Lin, R. J. R. Jhang and Y. W. Lin, "Design and implementation of an auto flushing device with ultra-low

standby power," 2013 IEEE International Symposium on Consumer Electronics (ISCE), Hsinchu, 2013, pp. 183-184.

11. Kitisak Osathanunkul, Kittikorn Hantrakul, Part Pramokchon, Paween Khoenkaw and Nasi Tantitharanukul “Configurable Automatic

Smart Urinal Flusher based on MQTT Protocol”,IEEE 2017.

12. A. D. Kadge, A. K. Varute, P. G. Patil, P.R. Belukhi “Automatic Sewage Disposal System for Train”, International Journal of Emerging

Research in Management &Technology (Volume- 5, Issue-5), May 2016.

13. Pandya Chintan, Yadav Jatin, Kareliya Sanket, Darshan Adeshara “AUTOMETIC WORKING BIO-TOILET TANK FOR RAILWAY

COACHES”, International Journal of Advance Engineering and Research Development Volume 2,Issue 10,October - 2015.

14. E.Elakiya, K.Elavarasi, R.P.Kaaviya priya , “Implementation of Smart Toilet (Swachh Shithouse) Using IOT Embedded Sensor Devices”,

International Journal of Technical Innovation in Modern Engineering & Science (IJTIMES), Volume 4, Issue 4, April-2018, pp 65 – 74.

15. K.Dhanalakshmi,P.Hemalatha, ”Development of IOT Enabled Voice Recognition Robotic Guide Dog For Visually Impaired People to

enhance the guiding and interacting experience”, Journal of Advanced Research in Dynamical and Control Systems, Vol 3, Issue 1, pp

262-272.

423-427

72.

Authors: Mithya V, Dharani K V, Nivetha A, Praveen Rajakumari G, Roshel Infan M

Paper Title: Smart Highway Toll Collection System

Abstract: Smart highway toll collection system is used to minimize the time by collecting the toll amount

electronically. In RFID based toll collection systems we face many problems. In order to overcome that this

proposed system is developed with an automated license plate recognition system. In this system, a webcam is

interfaced with a raspberry pi that captures the image of a vehicle that passes through the tollgate. The captured

image will be processed by image processing techniques and it will be sent to the R.T.O database server to identify

the users and the type of their vehicle. This retrieved information will be sent to the system through GSM module

and the respected amount will be deducted from users account and it will be notified to the mobile number which

has been registered before. If the respected amount is deducted correctly the barrier will open and the vehicle is

allowed to leave the tollbooth. If not the barrier will remain closed.

Keywords: RFID, R.T.O, GSM, Tollgate, Raspberry pi.

References: 1. Suryatali,V.Dharmadhikari,”Computer Vision Based Vechicle Detection for toll collection system Using Embedded

428-431

Linux”,ICCPCT,2015.

2. A.Wijetungenand D.Ratnaweera,’’Real-Time Recongnition of License Plates of Moving Vechicles in Sri Lanka”,ICIIS,2011,pp. 82-87.

3. Jaya priyaa CT, Y,Beviah Jenilia secured automatic Toll fee collection for private group transportation ,IEEE sponsered 2J/D International

conference on Innovations in Information ,Embedded and communication Systems(ICIIECS)2015.

4. Amol Dhumane Rajesh Prasad ,Jayashree prasad “Routing iaaues in Internet of things: A survey”, Poceedings of the International Multi

conference of Engineers and computer Scientists 2016 VolI, IMECS2016, March 16_18,2016,HongKong.

5. P.S.Hanwate , Narin Meher Ashlesh Mandke, Manoj Nikam Manan Mehta “A Review on Automated Toll Collection Systems

.”IJSTE-International Journal of science Technology & Engineering |Volume 3|Issue 06|December 2016.

6. chang ,E.C.P., Wu,M.F.,Chang,Y.C.:Successful Taiwan freeway electronic collection(ETC) implementation through intelligent transport

system(ITS).In: Bridging the East and West: Theories and practices of Transportation in the Asia Pacific -Selected Papers from the

Proceedings of the 11th Asia Pacific Transportation Development Conference and the 29th ICTPA Annual Conference(2016)

7. Matthews,V.O., et al.: Solar photovoltaic automobile recognition system for smart-green access control using RFID and Lo Ra LPWAN

technologies. J.Eng. Appl.Sci.12(4), 913-919(2017)

73.

Authors: Mithya V, Aishwarya M, Gayathri S, Mahalakshmi L S, Pavithra S

Paper Title: Smart Gardening System

Abstract: The main aim of the project is to develop techniques in agriculture automation to flourish and deliver

its full potential. This system designed by using arduino microcontroller to overcome limitations of agriculture

farming about supplying of water to plants by drip system with the available water tables. In our system we use

Arduino microcontroller, motor pump, soil moisture sensor. The motor pump works according to the soil condition

that is soil wet or dry; if soil is wet motor stops otherwise motor run to give water to plants. The status of smotor

is displayed on LCD. Different sensors are connected to the controller to verify the temperature and CO gas. SMS

will be sent to the owner in case of any critical situation. To keep the strangers away from the field an electric

fence is included with slight shock. The electric fence will be deactivated when a authorized persons presence is

identified near the field through the RFID.

Keywords: Arduino, soilmoisture, temperature, Cosensors, RFID module, electricalfence, GSM, motor pump.

References: 1. A Wireless Sensor Network Solution for Precision Agriculture Based on ZigBee Technology – ManijehKeshtgari

2. An Effective Method for Crop Monitoring Using Wireless Sensor Network - N. Sakthipriya

3. Gwyn A. Beattie. 2006. Plant-Associated Bacteria : survey, molecular phylogeny, genomics and recent advances, Samuel S.

Gnanamanickam editor ,Springer Netherlands pp. 1-5

4. Survey on Bacterial Diseases of crop and Non-crops of Cuddapah District, Andhra Pradesh, India. R.HareKondaiah and A. Sreeramulu

5. Lopez, M. Rosello and A. Palacio-Bielsa .2010. Diagnosis and Detection of the Main Bacterial Pathogens of Stone Fruit and Almond.

Journal of Plant Pathology.92 (1) S1.57-S1.66

6. Principles of electronics by V.K.Mehta

7. A Real Time Irrigation Control System For Precision Agriculture Using WSN In Indian Agricultural Sectors - Prathyusha.K

8. Basic electronics by Boylested

9. www.setvannadatha.com

432-436

74.

Authors: Naveen Raj M, Ajay Ravindran, Bagadesh Kumar R, Gopinath D, Kandasamy A

Paper Title: Smart Mobile Detector for Unapproved Usage of Cell Phones

Abstract: This helpful, take estimate portable finder can identify the nearness of an actuated versatile mobile

phones from a separation of one and a-half meters. Consequently, it can keep the utilization of cell phones in

examination corridors, secret rooms, and practically helpful for identifying the use of cell phones for spying and

unapproved video transmission. The circuit can distinguish the approaching and active calls, SMS and video

transmission regardless of whether the portable is kept in the quiet mode. The minute that the Bug recognizes the

RF transmission motion from an initiated cell phone, it begins sounding a signal alert what's more, the LED squint.

The caution proceeds until the flag transmission ceases. Gather the circuit a broadly useful PCB as minimized as

could be expected under the circumstances and encase in a little box like garbage versatile cases. As referenced

before, capacitor C3 ought to have a lead length of 18mm with lead separating of 8mm.Carefully patch the

capacitor in standing position with equivalent dispersing of the leads.

Keywords: Mobile Phones, Arduino, Switch and Wi-Fi Module.

References: 1. S.D.T. Kelly, N.K. Stradivari and S.C. Mukhopadhyay, “Towards the Implementation of IoT Environmental Condition Monitoring

in Homes”, Sensors Journal, IEEE (Volume: 13, Issue: 10), October 2013.

2. Alimera, C. Floerkemeier and J. Mitsugi, G. Morabito, “The Internet of things”, IEEE Wireless Communications, 2010, Vol.17, Issue.6,

pp-8-9.

3. A. Sehgal, V. Perelman, S. Kuryla and J. Schonwalder, “Management of resource constrained devices in the internet of things”, IEEE

Communications Magazine, 2012, Vol.50, Issue.12, pp.144-149.

4. S. Hong, D. Kim, M. Ha, S. Bae, S. Park, W. Jung and J.E. Kim, “SNAIL: an IP-based wireless sensor network approach to the internet of

things”, IEEE Wireless Communications,2010, Vol. 17, Issue.6, pp.34 –42.

5. A. Iera, C. Floerkemeier, J. Mitsugi, and G. Morabito, “The Internet of things”, IEEE Wireless Communications, 2010, Vol.17, Issue.6,

pp-8-9.

6. A.Gluhak, S. Krco, M. Nati, D. Pfisterer, N. Mitton, and T. Razafindr alambo, “A survey on facilities for experimental internet of things

research”, IEEE Communications Magazine,2011, Vol. 49, Issue.11, pp.58-67.

7. M.Zorzi, A. Gluhak, S. Lange and A. Bassi, “From today's Internet of things to a future Internet of things: a wireless- and mobility-related

view”, IEEE Wireless Communications, 2010, Vol.17, Issue.6, pp.44-51.

437-441

8. A.Sehgal, V. Perelman, S. Kuryla and J. Schonwalder, “Management of resource constrained devices in the internet of things”, IEEE

Communications Magazine, 2012, Vol.50, Issue.12, pp.144-149.

9. S. Helal, W. Mann, H. El-Zabadani, J. King, Y. Kaddoura, and E. Jansen, “The gator tech smart house: A programmable pervasive space”,

IEEE Computer, Vol. 38, Issue.3 ,2005, pp.50-60.

10. D.J. Cook, “Learning Setting-Generalized Activity Models for Smart Spaces”, IEEE Intelligent Systems, Vol. 27, Issue. 1, doi:

10.1109/MIS.2010.112, 2012, pp. 32 – 38.

75.

Authors: Naveen Raj M, Aiswariya Lakshmi A, Edlin Shejila E, Kausalya K, Vinitha R

Paper Title: Lung Image Segmentation using Modified K-Means Algorithm

Abstract: Lung Cancer is also referred as Lung Carcinoma, characterized by unrestrained cell growth in tissues

of lung. It has high mortality rate when compared to other cancers. The main reason of Lung Cancer is smoking

and exposure to secondhand smoke. A fine Lung Cancer detection system must sense the Lung Cancer in its

premature stages. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are the two tools used to

capture the Lung image. The various stages in the Lung Cancer detection include Image Capturing, Image

Enhancement, Image Segmentation and Feature Extraction. In this, various image processing techniques are

utilized for lung cancer detection and performance of each technique is compared.

Keywords: CT, MRI, K-means clustering.

References: 1. Younbum Lee, Takshi Hara, Hiroshi Fujita, Shigeki Itoh, and Takeo Ishigaki, ”Automated Detection of Pulmonary Nodules in Helical

CT Images Based on an Improved Template-Matching Technique,” IEEE Transaction on medical Imaging,Vol.20 page 595604,july 2001

2. Omar S, Al-Kadi, D.Watson, ”Texture Analysis of Aggressive and Nonaggressive Lung Tumor CE CT Images,”

IEEE Trans. Bio-Medi Eng.Vol.55 No.7, page 1822-1830, July 2008.

3. Disha, Gagandeep, ”Identifying Lung Cancer Using Image Processing Techniques,” International conference on computational techniques

and artificial intelligence ICCTAI’2011.

4. Fatma Taher1, Naoufel Werghi1, Hussain Al-Ahmad1, Rachid Sammouda2, “Lung Cancer Detection Using Artificial Neural Network

and Fuzzy Clustering Methods,” American Journal of Biomedical Engineering 2012, 2(3): 136-142

5. A.Amutha, Dr.R.S.D.Wahidabanu, ”Lung Tumor Detection and Diagnosis in CT scan Images,” International conference on

Communication and Signal Processing, April 3-5, IEEE, 2013.

6. Anam Tariq, M.Usman Akram and M.Younus Javed, ”Lung Nodule Detection in CT Images using Neuro Fuzzy Classifier,” IEEE, 2013.

7. Ada, Rajneet Kaur “Early Detection and Prediction of Lung Cancer Survival using Neural Network Classifier”, (IJAIEM)Volume 2, Issue

6, June 2013

8. Dasu Vaman, Ravi Prasad, “Lung cancer detection using image processing techniques”, International journal of latest trends in

engineering and technology.(2013)

9. T. Sowmiya, M. Gopi, M. New Begin L.Thomas Robinson “Optimization of Lung Cancer using Modern data mining techniques.”

International Journal of Engineering Research ISSN:23196890) (online), 23475013 (print)Volume No.3, Issue No.5, pp : 309-3149 (2014)

10. Jinsa Kuruvilla, K.Gunavathi, ”Lung Cancer classification using neural networks for CT images, “computer methods and programs in

Biomedicine113 (2014) 202-209.

11. Sri Krishna Prasath, M. Naveen Raj, Aswin Kumar, R. Vignesh, K. Iniyan “Iot based smart helmet for unsafe event detection for mining

industry”, International Journal of pure and applied mathematics. Volume No.118, Issue No.1311-8080 (15/3/2018).

12. M.Naveen Raj, “Traffic analysis using manet in wireless sensor network”, International journal of pure and applied mathematics.

Volume:118, Issue No:1311-8080 (15/3/2018).

13. M.Naveen Raj, “LPR system for domestic security”, Imperial journal of interdisciplinary research (7/5/2016).

14. M.Naveen Raj, “Detection and implementation of Indian currencies based on computer vision approach”, International journal of Novel

research in electronics and communication (11/4/2016).

15. M.Naveen Raj, “Severity grading for diabetic retinopathy”, International journal of recent trends in engineering and research (11/4/2016).

16. M.Naveen Raj, “Efficient decoding using majority gate”, International journal of engineering research and development (ijerd)

(12/6/2013).

442-444

76.

Authors: T.Maris Murugan, R.Kirubashankar

Paper Title: A Study of Flotation Control

Abstract: The control aspects of pulp level in a flotation column is a difficult task as the complex structure of

cell configuration and the higher interaction as number of cells used in the configuration increases. This paper

analyses about different control approaches for level control in flotation columns. The conventional method of

controller design and other algorithmic and heuristic control are reviewed.

Keywords: Flotation, Deinking.

References: 1. Hamm U (2010) Final disposal of waste from recycled fibre-based papermaking and of non-recycled paper products. In: Höke U

&Schabel S (eds) Recycled fibre and deinking. 2nd edition, Helsinki, Finnish Paper Engineers’ Association: 562–646.

2. Schabel S &Holik H (2010) Unit operations and equipment in recycled fibre processing. In: Höke U &Schabel S (eds) Recycled fibre and

deinking. 2nd edition, Helsinki, Paper Engineers’Association: 122–278

3. Pöyry (1995) Jaakko Pöyry Consulting AB report: Deinking developments. Tummavuorenkirjapaino Oy, Finland.

4. Ajersch M (1997) Mechanisms of pulp loss in flotation deinking. Open Access Dissertations and Theses. Paper 3377. Cited

2012/08/08.URI: http://digitalcommons.mcmaster.ca/opendissertations/3377

5. Jeamsea-Jounela, S.-L., Laurila, H., Karesvuori, J., Timperi, J., 2001. Evaluation of the future automation trends in control and fault

diagnostics––a case study in flotation plant. In: 10th IFAC Symposium on Automation in Mining, Mineral and Metal Processing.

6. Niemi, A., Maijanen, J., Nihtil€a, M., 1974. Singular optimal feed forward control of flotation. In: IFAC/IFORS Symposium on

Optimization Methods––Applied Aspects. Varna, Bulgaria, pp. 277–283.

7. Koivo, H., Cojocariu, R., 1977. An optimal control for a flotation circuit. Automatica 13 (1), 37–45.

8. Andersen, R., Gronli, B., Olsen, T., Kaggernd, I., Ramslo, K., Sandvik, K., 1979. An optimal control system of the rougher flotation at the

445-449

FolldalVerk concentrator, Norway. In: Proceedings of the 13th International Mineral Processing Congress. New York, USA, pp. 1517–

1540.

9. Hammoude, A., Smith, H., 1981. Experiments with self-tuning control of flotation. In: Proceedings of the 3rd IFAC Symposium on

Automation in Mining, Mineral and Metal Processing. Oxford, UK, pp. 213–218.

10. Zargiza, R., Herbst, J.A., 1987. A model based feed forward control scheme for flotation plants. In: 116th AIME annual meeting. Denver,

CO, USA, pp. 23–27.

11. Stenlund, B., Medvedev, A., 2000. Level control of cascade coupled flotation tanks. Future trends in automation in mineral and metal

processing. In: J€ams€a-Jounela, S.-L., Vapaavuori, E. (Eds.), IFAC Workshop 2000, Helsinki, Finland, pp. 194–199.

12. Feely C.D., Landoit C.A., Misczack J. and W.M.Steeburgh, Column Flotation at Inco’s Matte Separation Plant, 89th Annual Meeting of

CIM, Toronto, Canada, (1987).

13. Kosics G.A., Dobby G.S., and P.D. Young, ColumnEx: A Powerful and Affordable Control System for Column Flotation, Proceeding

International Conference on Column Flotation, Sudbury, Canada, 359 (1991).

14. Hirajima T., Takamori T., Tsunekawa M., Mastubara T., Oshima K., Sawaki K. and S. Kubo, The Application of Fuzzy Logic to Control

Concentrate Grade in Column Flotation at Toyoha Mines, Proceeding International Conference on Column Flotation, Sudbury, Canada,

375 (1991).

15. Pu M., Gupta Y.P., and A.M. Al Taweel, Model Predictive Control of Flotation Columns, Proceeding International Conference on

Column Flotation, Sudbury, Canada, 467 (1991).

16. Cutler C.R., and B.L. Ramarker, Dynamic Matrix Control, A Computer Control Algorithm, AIChE 86th Meeting, Paper 51b (1979).

17. Manabe.S., (1998), The Coefficient Diagram Method, 14th IFAC symposium on Automatic control in Aerospace, May 24-28.

18. Hammoude, A. and H. Smith, 1981. Experiments with selftuning control of flotation, Proc. 3rd IFAC Symp. Automation In Mining,

Mineral And Metal Processing. Oxford, UK, pp. 213–218

19. Zargiza, R. and J. A. Herbst, 1988. Model based feedforward control scheme for flotation plants, SME Annual Meeting, Denver,

Colorado, pp. 177–185

20. Carr, D., A. Dixon, and O. Tiili, 2009. Optimizing large flotation cell performance through advanced instrumentation and control, Proc.

10th Mill Operators Conf., Adelaide, Australia, pp. 299–304

21. Wills, B. A. and T. Napier-Munn, 2006. Wills’ Mineral Processing Technology, 7th Edn. Oxford, UK: Butterworth Heinemann, pp. 267–

344

22. Stenlund, B. and A. Medvedev, 2002. Level control of cascade coupled flotation tanks, Control Eng. Prac.,Vol. 10, No. 4, pp. 443–448.

23. Kämpjärvi, P. and S.-L. Jämsä-Jounela, 2003.“Level control strategies for flotation cells,” Minerals Eng., Vol. 16, pp. 1061– 1068

24. Moilanen, J. and A. Remes, 2008. Control of the flotation process,” In: R., Kuyvenhoven, C., Gomez, and A. Casali, (Eds), Procemin

2008, V International Mineral Processing Seminar, Santiago, Chile, pp. 305–313

25. Haibo Li, Tianyou Chai, Jun Fu, and Hong Wang, 2013, Adaptive Decoupling Control of Pulp Levels in Flotation Cells, Asian Journal of

Control. Vol. 15 No. 5 pp 1434 – 1447.

26. B.Meenakshipriya,K.Saravanan, K.Krishnamoorthy &P.Kanthabhabha, 2015. pH control of industrial effluent using CDM based PI

controllers, Indian Journal of Chemical Technology, Vol. 22, pp 141 – 147

27. P.K.Bhabha & S.Somasundaram, 2009. Real time implementation of a new CDM – PI control scheme in a conical tank liquid level

maintaining system, Modern Applied Science, Vol. 3, No. 5, Page no. 38 – 45

28. Erkan IMAL, 2009. CDM based controller design for nonlinear heat exchanger process, Turk J Elec Eng& Comp sci, Vol. 17, No. 2, page

no. 143 – 161

29. K.Senthil Kumar & Dr.D.AngelineVijula, 2015. Implementation of two degree of freedom (2DOF) controller using Coefficient diagram

method techniques for Three tank interacting system, International Journal of Engineering and Technology, Vol. 2, Issue 9, page no. 90 –

96.

30. K.Kanagasabai & N.Jaya, 2014. Design of Multiloop controller for three tank process using CDM Techniques, International Journal on

Soft Computing, Vol. 5, No. 2, page no. 11 - 20

77.

Authors: J. Samson Immanuel, G. Manoj, A. Amir Anton Jone, P. Esther Jebarani

Paper Title: Frequent Itemset Matching for Real Time Applications using Reconfigurable Hardware Architecture

Abstract: Data mining methods remain a quickly developing class of claims that are popular basic usage in

numerous fields. An accumulative quantity of data increases the claim for calculating power. Usually human

being utilizes enormous size of data and understands that the data and information are widely spread at particular

pointer. The algorithms and techniques are known as data mining, remain developed to channel the breach. To

utilize the demand for microprocessor systems and use of graphics processing units (GPU) there are numerous

methods can be obtained. The added method operates on the hardware accelerators termed as Field programmable

gate array (FPGA). Three data mining algorithms nominated for this review: In this apriori algorithm is best to

mine the frequent itemsets from the extensive database, and the frequent itemsets are very useful to get the

association rule for the discovery of knowledge. In this paper apriori algorithm is modified which reduces the large

frequent itemsets and it has implemented in Xilinx Virtex-5 FPGA platform provides up to 5.58 × performance

improvement over an equivalent software implementation. Evaluation and investigation are performed for the three

selected algorithms using FPGA implementations. To precede with conclusion the investigations executed on

common complications, restrictions and resources of various algorithms.

Keywords: Data mining, Algorithms and FPGA.

References:

1. S. Che, J. Li, J. W. Sheaffer, K. Skadron, and J. Lach, "Accelerating compute-intensive applications with GPUs and FPGAs," in Proc.

SASP, 2008, pp. 101-107.

2. M. Estlick, M. Leeser, J. Theiler, and J. J. Szymanski, "Algorithmic transformations in the implementation of k-means clustering on

reconfigurable hardware," in Proc. ACM FPGA, 2001, pp. 103-110.

3. D. Anguita, A. Boni, and S. Ridella, "A digital architecture for support vector machines: theory, algorithm, and FPGA implementation,"

IEEE Tras. Neural Netw., vol. 14, no. 5, Sept.2003.

4. Z. Baker and V. Prasanna. Efficient hardware data mining with the Apriori algorithm on FPGAs[C]. In Proceedings of the Thirteenth

Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM '05),2005.

5. G. A. Covington, C. L. G. Comstock, A. A. Levine, J. W. Lockwood, and Y. H. Cho, "High-speed document clustering in reconfigurable

hardware," in Proc. FPL, 2006, pp. 411-417.

450-454

6. R. Narayanan, D. Honbo, G. Memik, A. Choudhary, and J. Zambreno, “An FPGA implementation of decision tree classification,” in Proc.

DATE, 2007.

7. Karthik Nagarajan & Brian Holland & Alan D. George & K. Clint Slatton & Herman Lam," Accelerating Machine-Learning Algorithms

on FPGAs using Pattern-Based Decomposition" in J Sign Process Syst (2011) 62:43–63 DOI 10.1007/s11265-008-0337-9

8. H. M. Hussain, K. Benkrid, H. Seker, and A. T. Erdogan, “FPGA of K-means algorithm for bioinformatics application: An accelerated

approach to clustering Microarray data,” in Proc. AHS, 2011, pp. 248-255.

9. Hanaa M. Hussain, Khaled Benkrid, Ahmet T. Erdogan, Huseyin Seker,” Highly Parameterized K-means Clustering on FPGAs:

Comparative Results with GPPs and GPUs" in 2011 International Conference on Reconfigurable Computing and FPGAs

10. S. Sun and J. Zambreno. Design and Analysis of a Reconfigurable Platform for Frequent Pattern Mining[J]. IEEE Transactions on Parallel

and Distributed Systems, vol. 22, no. 9, pp. 1497-1505,2011.

11. Grigorios Chrysos, Panagiotis Dagritzikos, Ioannis Papaefstathiou, Apostolos Dollas,” Novel and Highly Efficient Reconfigurable

Implementation of Data Mining Classification Tree" in 2011 21st International Conference on Field Programmable Logic and

Applications.

12. P. Skoda, B. Medved Rogina, V. Sruk,” FPGA implementations of data mining algorithms”, in MIPRO 2012, May 21-25,2012, Opatija,

Croatia.

13. Shaobo Shi, Yue Qi, Qin Wang,” Acceleration Intersection Computation in Frequent Itemset Mining with FPGA" in high-performance

computing and communication & 2013 IEEE international conference on embedded and ubiquitous computing(HPCC_EUC).

14. Han J, Pei J, Yin Y (2000) Mining frequent patterns without candidate generation. ACM SIGMOD Rec 29(2):1–12

15. Meenakshi A (2015) Survey of Frequent Pattern Mining algorithms in horizontal and vertical data layouts. Int J Adv Comput Sci Technol

4(4):48–58

16. Song M, Rajasekaran S (2006) A transaction mapping algorithm for frequent itemsets mining. IEEE Trans Knowl Data Eng 18(4):472–

481

17. M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New Algorithms for Fast Discovery of Association Rules.Proc. 3rd Int. Conf. on

Knowledge Discovery and Data Mining (KDD’97, Newport Beach, CA), 283–296. AAAI Press, Menlo Park, CA, USA 1997.

18. R. Agrawal and R. Srikant. Fast Algorithms for Mining Association Rules.Proc. 20th Int. Conf. on Very Large Databases (VLDB 1994,

Santiago de Chile), 487–499. Morgan Kaufmann, San Mateo, CA, USA 1994

19. C.Borgelt and R.Kruse. Induction of Association Rules: Apriori Implementation. In Proceedings of the 15th Conference on Computational

Statistics, 2002.

20. M.Estlick, M.Leeser, J. Szymanski, and J. Theiler. Algorithmic Transformations in the Implementation of K-means Clustering on

Reconfigurable Hardware. In Proceedings of the Ninth Annual IEEE Symposium on Field-Programmable Custom Computing Machines

2001 (FCCM '01), 2001

78.

Authors: Kaarthik K, Sivaranjani S

Paper Title: A Novel PDA Technique with Flying Capacitor for Buck Boost Converter

Abstract: A Buck Boost Converter is Basic element implemented to process, to Improve the battery life of

Normal device. They Plays an important role in improve the Efficiency, Speed of and executed ripple factor

Output. Inorder to Obtain the Expected Parameters of Accuracy, Speed and response , a Proposed structural

design Hybrid Buck–Boost Feed Forward (HBBFF) technique is Implemented. The Implemented design uses the

Reduced Average Inductor Current (RAIC) Technique and conventional switched capacitor converter, which will

reduce the conduction loss and improves the Efficiency Respectively. The Projected approach uses the converter

named 2D converter is Implemented and Pseudo Current Dynamic Acceleration (PDA) system. The Projected

Implementations will obtain the Fast Transient response to provide the process to convert the Heavy load values to

the Light Load values and to Obtain the switching frequency for 3.3 V is 1 MHz inorder to achieve 2 μs of

Transient response and 90% of expected efficiency.

Keywords: Buck Boost Converter, Capacitor, Power, Speed, Efficiency, Hybrid.

References: 1. N. Kondrath and M. K. Kazimierczuk, “Control current and relative sta-bility of peak current-mode controlled pulse-width modulated

DC–DC converters without slope compensation,” IET Power Electron.,vol.3 (6), Nov. 2010, pp. 936–946,

2. K. Jin X. Ruan "Zero-voltage-switching multiresonant three-level converters" IEEE Trans. Ind. Electron. vol. 54 no. 3 pp. 1705-1715 Jun.

2007.

3. X. Ruan B. Li Q. Chen "Three-level convertersA new approach in high voltage dc-to-dc conversion" Proc. IEEE PESC pp. 663-668 2002.

4. F. Forest T. A. Meynard S. Faucher F. Richardeau J.-J. Huselstein C. Joubert "Using the multilevel imbricated cells topologies in the

design of low-power power-factor-corrector converters" IEEE Trans. Ind. Electron. vol. 52 no. 1 pp. 151-161 Feb. 2005.

5. R. Stala S. Pirog M. Baszynski A. Mondzik A. Penczek J. Czekonski S. Gasiorek "Results of investigation of multicell converters with

balancing circuitPart I" IEEE Trans. Ind. Electron. vol. 56 no. 7 pp. 2610-2619 Jul. 2009.

6. R. Stala S. Pirog A. Mondzik M. Baszynski A. Penczek J. Czekonski S. Gasiorek "Results of investigation of multicell converters with

balancing circuitPart II" IEEE Trans. Ind. Electron. vol. 56 no. 7 pp. 2620-2628 Jul. 2009.

7. V.Kavitha and S. Mohanraj, “High performance Viterbi decoder design”, Springer – Cluster Computing, Online ISSN: 1573-7543,

Pages 1-6, 2018.

8. X. Ruan B. Li Q. Chen S.-C. Tan C. K. Tse "Fundamental considerations of three-level DC-DC converters: Topologies analyses and

control" IEEE Trans. Circuits Syst. I Reg. Papers vol. 5 no. 11 pp. 3733-3743 Dec. 2003.

9. C.Vivek, S.Palanivel Rajan, "Z-TCAM : An Efficient Memory Architecture Based TCAM", Asian Journal of Information Technology,

ISSN No.: 1682-3915, Vol: 15, Issue : 3, pp. 448-454, 2016.

10. X. Ruan J. Wei Y. Xue "Three-level converters with the input and output sharing the ground" Proc. 34th Annu. IEEE PESC vol. 4 pp.

1919-1923 2003-Jun.-1519.

11. K. Kaarthik, S. Pradeep, S. Selvi, "An Efficient Architecture Implemented to Reduce Area in VLSI Adders", Imperial Journal of

Interdisciplinary Research, Vol.3, Issue 2, pp. 326-330, 2017.

12. C.Vivek, S.Palanivel Rajan, “Design of Data Aware Low Power Area Efficient Data paths for Processing Elements in a Reconfigurable

System”, International Journal of Computer Science and Information Security, ISSN : 1947-5500, Vol.14, Issue 9, pp. 1100-1113, 2016.

13. K Kaarthik, C Vivek, "Hybrid Han Carlson Adder Architecture for Reducing Power and Delay", Middle-East Journal of Scientific

Research, Vol. 24, Special Issue, pp. 308-313, 2016.

14. T. A. Meynard H. Foch P. Thomas J. Courault R. Jakob M. Nahrstaedt "Multicell converters: Basics concepts and industry applications"

IEEE Trans. Ind. Electron. vol. 49 no. 5 pp. 955-964 Oct. 2002.

15. P.Sakthi and P.Yuvarani,” Multipliers based on Urdhva Tiryagbhyam Algorithm: A Survey”,Advances in Natural and Applied Sciences,

455-461

ISSN:1995-0772, 8(19) Special 2014, Pages: 100-106.

16. T. A. Meynard H. Foch F. Forest C. Turpin F. Richardeau L. Delmas G. Gateau T. A. Lefeuvre "Multicell converters: Derived topologies"

IEEE Trans. Ind. Electron. vol. 49 no. 5 pp. 978-987 Oct. 2002.

17. Kaarthik K, T. Jayanthi, N. Kanimozhi, L. Kanmani, R. Karthika, “A COMPREHENSIVE SURVEY ON VARIOUS ADDERS AND ITS

COMPACTION RESULT”, International Journal of Pure and Applied Mathematics, Online ISSN No.: 1314-3395, Print ISSN No.: 1311-

8080, Vol. No.: 118, Issue No.: 22, pp. 1021-1029, 2018.

18. S. Pirog R. Stala "Selection of parameters for a balancing circuit of DC-DC and AC-AC multicell converters" Proc. 11th EPE pp. 910

2005-Sep.-1114.

19. R. H. Wilkinson T. A. Meynard H. du Toit Mouton "Natural balance of multicell converters: The two-cell case" IEEE Trans. Power

Electron. vol. 21 no. 6 pp. 1649-1657 Nov. 2006.

20. K. Kaarthik, P. Yuvarani, “Implementation of Distributed Operating System for industrial process automation using embedded

technology", Journal of Chemical and Pharmaceutical Sciences, Online ISSN No.: 2349 - 8552, Print ISSN No.: 0974-2115, Special Issue

8, pp. 14 – 17, December 2016.

21. H. du Toit Mouton "Natural balancing of three-level neutral-point-clamped PWM inverters" IEEE Trans. Ind. Electron. vol. 49 no. 5 pp.

1017-1025 Oct. 2002.

22. D. Krug S. Bernet S. Saeed Fazel K. Jalili M. Malinowski "Comparison of 2.3-kV medium-voltage multilevel converters for industrial

medium-voltage drives" IEEE Trans. Ind. Electron. vol. 54 no. 6 pp. 2979-2992 Dec. 2007.

23. N.Mahendran, S.Vishwaja, “Enhancing the Performance of Wireless Sensor Networks Using Low Power Design”, International Journal of

Electrical, Computer, Energetic, Electronic and Communication Engineering, World Academy of Science, Engineering and Technology,

Volume: 10, No: 4, 2016, PP: 564-569.

24. Dhamodaran M, Jegadeesan S, et al., ‘On-chip spiral inductors and on-chip spiral transistors for accurate numerical modeling, Journal of

Magnetics, pp.50-54, 2018.

25. P.Sakthi,S.Maheswari and P.Yuvarani, High Performance Vedic Multiplier using Compressors, International Journal of Applied

Engineering Research, ISSN 0973-4562 Vol. 10 No.20 (2015),pages 16882-16886.

26. B. P. McGrath D. G. Holmes "Analytical modeling of voltage balance dynamics for a flying capacitor multilevel converter" IEEE Trans.

Power Electron. vol. 23 no. 2 pp. 543-550 Mar. 2008.

79.

Authors: K.GerardJoe Nigel, D.Pamela

Paper Title: A Novel Approach for Maximum Power Point Tracking in Photovoltaic System

Abstract: The output power from the solar panel varies with solar irradiance level, temperature and load. In

order to increase the efficiency of power extracted from the solar panel, it is necessary to operate the photovoltaic

(PV) system near the maximum power point (MPP). There are different types of maximum power point tracking

(MPPT) methods. This paper proposes a novel approach for tracking MPP. In this approach it tracks the MPP

using normal perturb and observation method, the current-voltage curve corresponding to each MPP is obtained

and stored. Whenever a new single data value is read, the algorithm finds which curve has maximum points nearest

to the new value and assigns the voltage corresponding to the curve’s MPP.

Keywords: MPPT, PV, MPP, Boost-converter, Lab VIEW.

References: 1. L.MacIssac, A.Knox, “Improved Maximum Power Point Tracking Algorithm for Photovoltaic Systems” International Conference on

Renewable Energies and Power Quality(ICREPQ’10), Granada (Spain),23rd to 25th March 2010.

2. A. Yafaoui., B. Wu and R. Cheung, “Implementation of maximum power point tracking algorithm for residential photovoltaic

systems”, 2nd Canadian Solar Buildings Conference Calgary, June 10 – 14, 2007.

3. Joe-Air Jiang, Tsong-Liang Huang, Ying-Tung Hesiao and Chia-Hong Chen, “Maximum Power Tracking for Photovoltaic Power

Systems”, Tamkang Journal of Science and Engineering, Vol. 8, No 2,pp. 147153 (2005).

4. J. Kouta, A. El-Ali, N. Moubayed and R. Outbib, “Improving the incremental conductance control method of a solar energy conversion

system”.

5. S. Armstrong, W.G. Hurley, “Self-regulating Maximum Power Point Tracklng for Solar Energy Systems” IEEE.

6. Tun-Ping Teng, Hwa-Ming Nieh, Jiann-Jyh Chen, Yu-Cheng Lu, “Research and development of maximum power transfer tracking

system for solar cell unit by matching impedance”, Renewable Energy (2009), doi: 10.1016/j.renene.2009.09.001,ww.elsevier.com/locate/

renene.

7. Pallab Midya, Philip T Krein, Robert J Turnbull, Robert Reppa, Jonathan Kimball, “Dynamic Maximum Power Point Tracker for

Photovoltaic Applications”, 1996 IEEE.

8. A. Chouder, F. Guijoan and S. Silvestre“Simulation of fuzzy-based MPP tracker and performance comparison with perturb & observe

method”, Revue des Energies Renouvelables Vol. 11 N°4 (2008) 577 – 586.

462-465

80.

Authors: C.R.Balamurugan, M.Balaji, Bibin K Thomas, M.Suriya Mohan, R.Vasantha Kumar

Paper Title: Design and Analysis of Fully Automated Smart Pump System

Abstract: This paper study’s an analysis and design of smart pumping system for domestic application. the

analysis is based on pump from overheating, low level water, single phasing, rubbish water and unbalanced

voltages. This proposed work continuously monitoring all the phase voltages of the motor to avoid single phasing

and unbalanced voltages and there by saves the motor coil from failure. The Heat sensor attached to the motor

continuously monitors overheating of motor. PH module senses the water level as well as the quality of the water

so as to avoid damage of the motor. In order to monitoring the different analysis of parameters by using Arduino

board. The GSM module attached to the Arduino automatically controls the motor ON/OFF.

Keywords: Arduino, GSM module, PH module, Temperature sensor.

References: 1. Ch.Sowmys,C.D.Naidu,Rajendra Prasad,Ramesh Reddy “implemention of wireless sensor network for real time overhead tank water

quality monitoring”, IEE 2017 7th international advance computing conference.

2. Dipali Sarode,Arti Wadhekar, Rajes Autee “Voltage Source inverter with three phase preventer and selector for industrial application”

466-469

2015 international conference on pervasive computing.

3. Tigor Hamonangan Nasution ,Muhammad Anggia Muchtar, Ikhsan Siregar, Ulfi Andayani, Esra Christian .”Electrical Appliances control

prototype by using GSM Module and Arduino” 2017 4th international cnference on industrial engineering and applications.

4. https://en.wikipedia.org/wiki/GSM

5. https://arduinomodules.info/ky-013-analog-temperature-sensor-module/

6. M.J. Melfi, R.T. Hart, "Considerations for the use of AC Induction Motors on Variable Frequency Controllers in High Performance

Applications", IEEE Textile Film & Fiber Conference, May 1992.

7. H.-Z. Tan, N. Sepehri, "On condition monitoring of pump pressure in a hydraulic servo-drive system", The American Control Conference,

pp. 4478-4483, 2001.

8. R. O'Neill, M. Cain, D. Mead, D. Bandera, D. Withnell, Z. Salihi, and D. Sharma, " Principles for Efficient and Reliable Reactive Power

Supply and Consumption," Federal Energy Regulatory Commission, Tech. Rep., 2005.

9. Oleg Roizman, Valery Davydov, "Temperature Rise Tests: Centre for Power Transformer Monitoring Diagnostics and Life Management

(transformerLIFE)", IEEE Transformers Committee Meeting Miami FL, 21 April 2009.

10. E. K. Hansen, G. G. Olesen, "The window—A poetic device and technical tool to improve life in energy positive homes: A case study of

an active house", Proc. World Sustainable Building Conf., vol. 1, 2011.

11. Y. Riffonneau, S. Bacha, S. Barruel and S. Ploix, "Optimal power management for grid connected PV systems with batteries", IEEE

Transaction on Sustainable Energy, vol. 2, no. 3, pp. 309-320, July 2011.

12. P.C. Loh, L. Zhang and F. Gao, "Compact integrated energy systems for distributed generations", IEEE Transactions on Industry

Electronics, Vol. 5, May 2012.

81.

Authors: Pamela D, Gerard Joe Nigel, Sanjeevi Gandhi A

Paper Title: Design of Model Based Controller for Air Temperature Control in Tea Leaf Withering Process

Abstract: Good tea manufacturing process actually starts with proper plucking of shoot, handling of leaf,

Withering, Fermenting and Blending. Withering of tea leaves is the first and foremost step in the process of tea

manufacturing after plucking the leaves. After plucking it is necessary to separate the shoots and hence the leaves

in the trough needs to be broken up to separate every shoot from each other as this is must for even withers. The

tea leaves are dried to arrest enzymic reaction as well as oxidation and also to remove moisture from the leaf and

to produce a stable product with good keeping quality. Application of hot air during withering reduces the moisture

content in the leaf. This process of drying tea leaves to reduce moisture content is done by blowing hot air of

temperature 60 oC to 80 oC for 6 hours to 10 hours and the moisture content is reduced to 65% initially. Then

further processing like fermentation and drying of leaves to ultimate 3% moisture level is done in successive stages

to obtain the end product. Maintaining the temperature of the air blown in the troughs is critical and monitoring the

temperature continuously is challenging. Hence this paper proposes a remote monitoring and control system for air

temperature via Ethernet.

Keywords: Tea leaf withering, MRAC, Modified MRAC, Ethernet

References: 1. Chien-Liang Lai and Pau-Lo Hsu (FEBRUARY 2010) “Design the remote control system with the Time-Delay estimator and the

Adaptive Smith Predictor” IEEE Transaction on Industrial Informatics, vol.6,No.1.

2. Juliano S. A. Carneiro and Luca Ferrarini,( NOVEMBER 2010) “Preventing thermal overloads in Transmission Circuits via Model

Predictive Control” IEEE Transactions On Control Systems Technology, Vol. 18, No. 6.

3. V.Balaji, Dr. L.Rajaji,( November 2013) “Comparative Study of PID and MPC Controller Using Lab View” International Journal of

Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 11.

4. Arvapalli Rajesh, Y.V., Pavan Kumar, Sadhu Yugandhar and Viswaraju Srikanth (2012), “Cascaded PID Controller Design for Heating

Furnace Temperature Control”, IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Vol.2, No.2, pp.217-229.

5. Asan Mohideen K (2014). “Differential Evolution Algorithm for System Identification and Tuning of Fuzzy Modified Model Reference

Adaptive Controller for a Coupled Tank Level Process”. IJET, vol.6, No.3, pp. 1530-1547.

6. M. A. Zermani, Elyes Feki, Abdelkader Mami,( OCTOBER 2014) “Temperature Acquisition and Control System based on the Arduino”

International Journal of Emerging Science and Engineering (IJESE) ISSN: 2319–6378, Volume-2 Issue-12.

7. Pamela D. and Jebarajan T. ( December 2012), “Design of Intelligent Controller for Temperature Process FGCN/DCA 2012, CCIS 350”,

Springer-Verlag Berlin Heidelberg, 16th to 19th December 2012, 278-284, ISSN 1865-0929, ISBN 978-3-642-35593

8. Donald R. Coughanowr and Steven E. LeBlanc, “Process Systems Analysis And Control,” Third Edition, Published by McGraw-Hil.

Version 2 EE IIT, Kharagpur, Process Control.

9. Aytekinbagis (2007), “Determination of the PID controller parameters by modified genetic algorithm for improved performance”, Journal

of Information Science and Engineering.

10. Balaji V. and Rajaji L. (2013), “Comparative Study of PID and MPC Controller Using LabView”, International Journal of Advanced

Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, No.11, pp. 97-108.

11. Barber, R., Crespo J. and Horra M. (2012), “Control Practices using Simulink with Arduino as Low Cost Hardware”, Book, University

Carlos III of Madrid.s

470-475

82.

Authors: Chinnapettai Ramalingam Balamurugan, P.Abinaya, S.Aravind, K.Gowsith, D.M.Tamilselvan

Paper Title: Comprehensive Analysis and Response of Closed Loop CBBCTPNLI System with PI and FLC

Abstract: The industrial drive is normally using three-phase induction motor, since they need high speed –

torque performance operations. The speed control is normally in open loop. However, these open loop drives are

not giving good performance. The closed controller is playing a role in the design of any closed loop system. PI

controller is the best conventional controller. The fuzzy and neural based controller is better than PI controller for

many applications. Hence, in this chapter, a fuzzy logic based closed loop speed control of motor is investigated.

In addition to speed control, the current controls are pre-requisite for providing the smooth speed-torque

characteristics. In this paper a 3Ф five-level DC to DC converter five-level CHB-MLI fed variable speed motor

with proportional integral and fuzzy logic controller are modeled and investigated using MATLAB/Simulink. The

analysis is made with various modes of operation of motor drive. The FPGA SPARTAN-3 controller based

476-486

experimental setup is realized and tested for the proposed HCC and FLC speed controller. The experimental results

are conforming simulation results and prove the FLC performance against speed and HCC.

Keywords: MLI; PI; FLC; CHB; FPGS; HCC.

References: 1. Lin, F.J., Lin, C.H., and Shen, P.H.,Jul. (2004) ‘Variable-structure control for a linear synchronous motor using a recurrent fuzzy neural

network’, IEE Proceedings - Control Theory and Applications, vol. 151, no. 4, pp. 395–406.

2. Jung,J.W., Kim,T.H., and Choi, H.H., (2010) ‘Speed control of a permanent magnet synchronous motor with a torque observer: a fuzzy

approach’, IET Control Theory & Applications, vol. 4, no. 12, pp. 2971–2981.

3. Duranay Z.B., and Guldemir, H.,Mar. (2018) ‘Selective harmonic eliminated V/f speed control of single-phase induction motor’, IET

Power Electronics, vol. 11, no. 3, pp. 477–483.

4. Devanshu, A., Singh,M., and Kumar, N., (2018) ‘Sliding Mode Control of Induction Motor Drive Based on Feedback Linearization’,

IETE Journal of Research, pp. 1–14.

5. Lu, C.-H. T. H.-C., (2000) ‘Observer-Based Speed Estimation Method for Sensorless Vector Control Using Artificial Neural Network’,

Electric Machines & Power Systems, vol. 28, no. 9, pp. 861–873.

6. Schild, A., Lunze, J., Krupar,J., and Schwarz,W., (2009) ‘Design of Generalized Hysteresis Controllers for DC–DC Switching Power

Converters’, IEEE Transactions on Power Electronics, vol. 24, no. 1, pp. 138–146.

7. Abderrezek.H.,and Harmas, M.N., (2014) ‘PSO Based Adaptive Terminal Sliding Mode Controllers for a DC-DC Converter’,

International Journal of Computer Theory and Engineering, vol. 6, no. 4, pp. 302–306.

8. Venkatramanan,R., Sabanovic, A.,and Cuk, S., (1985) ‘Sliding mode control of DC-to-DC converters’, in Proc. IEEE Conf. IECON, pp.

251-258.

9. Huang, S.P., Xu, H.Q., and Liu.Y.F., (1989) ‘Sliding mode controlled Cuk switching regulator with fast response and first-order dynamic

characteristics’, in Proc. IEEE PESC Rec., pp. 124-129.

10. FossasE., Martinez, L.,and Ordinas,J., (1992) ‘Sliding-mode control reduces audio susceptibility and load perturbation in the Cuk

converter’, IEEE Trans. Circuits Syst. I. Fundam. Theory Appl., vol. 39, no. 10, pp. 847-849.

11. Shtessel,Y.B., Zinober, A.S.I and Shkolnikov, I.A., (2002) ‘Boost and buck-boost power converters control via sliding modes using

method of stable system centre’, in Proc. 41st IEEE Conf. Decision Control, vol. 1, pp. 346-347.

12. Tan,S.C., Lai, Y.M., Tse,C.K., (2008) ‘General design issues of sliding-mode controllers in dc-dc converters’, IEEE Trans. Industrial

Electronics., vol. 55, no. 3, pp. 1160–1174.

13. Tan, S.C., Lai, Y.M., Cheung, M.K.H., and Tse, C.K., (2005) ‘On the practical design of a sliding mode voltage controlled buck

converter’, IEEE Trans. Power Electron., vol. 20, no. 2, pp. 425–437.

14. Raviraj, V.S.C.,and Sen,P.C., Mar./Apr. (1997) ‘Comparative study of proportional integral, sliding mode, and fuzzy logic controllers for

power converters’, IEEE Trans. Ind. Appl., vol. 33, no. 2, pp. 518–524.

15. Perry,A.G., Guang,F., Liu, Y.F., and Sen, P.C., (2004) ‘A new sliding mode like control method for buck converter’, in Proc. IEEE

PESC Rec., vol. 5, pp. 3688–3693.

16. Nguyen., V.M., and Lee, C.Q., (1995) ‘Tracking control of buck converter using sliding-mode with adaptive hysteresis’, in Proc. IEEE

PESC Rec., vol. 2, pp. 1086–1093.

17. Tan,S.C., Lai, Y.M., Tse,C.K., and Cheung, M.K.H., (2006) ‘Adaptive feed forward and feedback control schemes for sliding mode

controlled power converters’, IEEE Trans. Power Electron., vol. 21, no. 1, pp. 182–192.

18. Sukumar, D.,Ranjan, V., and J., Rabi, (2010) ‘FLC based adjustable speed drives for power quality enhancement’, Serbian Journal of

Electrical Engineering, vol. 7, no. 2, pp. 217–229.

19. Chaturvedula,U.P.K., (2017) ‘Integrated Three Phase Hybrid Cascaded MLI Fed Induction Motor Drive for Energy Management in

Electric Vehicles’, International Journal for Research in Applied Science and Engineering Technology, vol. 36, no. 12, pp. 1359–1366.

20. Hayim,A., Knieser, M., and Rizkalla,M., (2010) ‘DSPs/FPGAs Comparative Study for Power Consumption, Noise Cancellation, and Real

Time High Speed Applications’, Journal of Software Engineering and Applications, vol. 03, no. 04, pp. 391–403.

21. Prasad, J.S., Obulesh, Y.P., and Babu, C.S., (2016) ‘FPGA (Field Programmable Gate Array) controlled solar based zero voltage and zero

current switching DC–DC converter for battery storage applications’, Energy, vol. 106, pp. 728–742.

22. Chen,Y., Chang, C.Y., and Yan,Y., (2013) ‘FPGA-Based Expert PID Controller for Buck DC-DC Converter’, Applied Mechanics and

Materials, vol. 431, pp. 215–220.

23. Rajkumar,M.V., Prakasam, P., and Manoharan, P.S., (2016) ‘Investigational Validation of PV Based DCD-MLI Using Simplified SVM

Algorithm Utilizing FPGA Tied with Independent Sources’, Circuits and Systems, vol. 07, no. 11, pp. 3831–3848.

83.

Authors: Chinnapettai Ramalingam Balamurugan, R.Kalai Surya, N.Kayalvizhi, M.Raouf Khan, P.Santhosh

Paper Title: Performance Analysis of Extended Boost Switched Capacitor Impedance Type DC-AC Converter

Abstract: The improvement in impedance type DC-AC converter with step up voltage is achieved by the

inclusion of new type of On/OFF capacitor. Impedance source inverter is used to step up and step down the input

voltage. Impedance source DC-AC converter is used to decrease the effect of wide change in electrostatic effects

for the capacitor used. To have better step up voltage without change in switches initially impedance source

inverter is proposed. The proposed circuit overcomes the disadvantages of traditional impedance source inverter.

Keywords: THD; boost; shoot through; non shoot through.

References: 1. Peng, F.Z. (2003) ‘Z-Source Inverter’, IEEE Transactions on Industrial Application, Vol. 39, No. 2, pp. 504–510.

2. Peng, F. Z., Shen, M. and Qian Z.(2005) ‘Maximum Boost Control of the Z-Source Inverter’, IEEE Transactions on Power Electronics,

Vol. 20, No. 4, pp. 833-838.

3. Loh, P. C., Vilathgamuwa, M., Lai, Y. S., Chua, G. T. and Li Y. W. (2005) ‘Pulse Width Modulation of Z Source Inverters’, IEEE

Transactions on Power Electronics, Vol. 20, No. 6, pp. 1346-1355.

4. Shen, M., Wang, J., Joseph, A. and Peng, F. Z. (2006) ‘Constant Boost Control of the Z-Source Inverter to Minimize Current Ripple and

Voltage Stress’, IEEE Transactions on Industry Applications, Vol. 42, No. 3, pp. 770-778.

5. Huang, Y., Shen, M., Peng, F.Z. and Wang, J. (2006) ‘Z-source inverter for residential photo voltaic systems’, IEEE Transactions on

Power Electronics, Vol.21, No. 6, pp. 1776–1782.

6. Thangaprakash, S. and Krishnan, A. (2010) ‘Implementation and Critical Investigation on Modulation Schemes of Three Phase

Impedance Source Inverter’, Iranian Journal of Electrical & Electronic Engineering, Vol. 6, No. 2, pp. 84-92.

487-492

7. Zhu., M. (2010) ‘Switched Inductor Z-Source Inverter’, IEEE Transactions on Power Electronics, Vol. 25, No. 8, pp. 2150-2158.

8. Nguyen, M.K., Lim, Y.C., Choi, J.H. (2012) 'Two Switched Inductor Quasi Z-Source Inverters', IET Power Electronics, Vol. 5, No. 7, pp.

1017-1025

9. Subramanian, D., Rasheed, R. (2013) 'Five Level cascaded H-Bridge Multilevel Inverter Using Multicarrier Pulse Width Modulation

Technique', International Journal of Engineering and Innovative Technology, Vol. 3, No.1, pp. 438-441.

10. Dinakaran, C., Panthee, A.B., Eswaramma, K. (2014) 'Modelling and Control of Quasi Z-Source Inverter for Advanced Power

Conditioning of Renewable Energy Systems', International Journal of Advanced Research in Electrical, Electronics, and Instrumentation

Engineering, Vol. 3, No.2, pp.136-141.

11. Khosravi, F., Azli, N.A., Kaykhosravi1, A. (2014) 'Design of Reduced Component Count Single Phase-Three Phase quasi Z-Source

Converter', IET Power Electronics, Vol.7, No.3, pp. 489-495

12. Kohila, J., Munia Raj, R., Kannan, S. (2014) 'Z Source Multilevel Inverter for Photovoltaic Application', International Journal of

Innovative Research in Science, Engineering and Technology, Vol. 3, No. 3, pp. 492-297

13. Chougule. G., Gaikwad, A. (2015) 'Simulation Study of Quasi Z-Source Inverter for Resistive and Inductive Load', International Journal

of Innovations in Engineering Research and Technology, 2015, Vol. 2, No. 6, pp.2-13

14. Elakya, V.C., Aarthi., Teresa, V.V. (2015) 'High Performance Extended Switched Inductor Quasi Z-Source Inverter for Three Phase

Loads', International Journal of Innovative Research in Science, Engineering and Technology, Vol. 4, No. 4, pp. 76-81

15. Yang, L., Qiu, L., Zhang, B. (2015) 'High-Performance Quasi Z-Source Inverter with Low Capacitor Voltage Stress and Small Inductance

', IET Power Electronics, Vol.8, No.6, pp. 1061-1067

16. Jackson, E.S. (2016) 'Implementation of Switched Inductor Quasi Z-Source Inverter', International Journal of Pharmacy and Technology,

Vol.8, No.4, pp.23769-23779

17. Bhujangaro, Y., Bhavani, T. (2016) 'Implementation of Cascaded H-bridge Multilevel Inverter for Sinusoidal PWM Controller Fed

Induction Drive', International Journal of Advanced Technology and Innovative Research, Vol.8, No.9, pp.1870-1876

18. Shehu, G.S., Kunya, A.B., Shanono, I.H. (2016) 'A Review of Multilevel Inverter Topology and Control Techniques', Journal of

Automation and Control Engineering, Vol.4, No.3, pp.233-241.

19. Himanshu., Khanna, R., Jain, N., (2016) 'A Survey on Various Topologies of Z-Source Inverters', International Journal of Electrical and

Electronics Engineering, Vol.3, No.7, pp.5-9.

20. Nishamol, P.T., Jassia, M.A. (2016) 'Single Phase Switched- Capacitor/ Switched Inductor Quasi –Source Inverter', International Journal

of Innovative Research in Science, Engineering and Technology, Vol.5, No.8, pp. 14935-14943.

21. Yuyao, He., Hailong, Liu., Wei, F., (2016) 'Novel Cascaded Z-Source Neutral Point Clamped Inverter', Chinese Journal of Electronics,

Vol.25, No.5, pp. 965-973.

22. Mubeen, M. (2016) 'Design of Z-Source Inverter for Voltage Boost Applications', International Journal of Innovative Research in

Electrical, Electronics, Instrumentation and Control Engineering, Vol.4, No.2, pp. 136-140.

23. Vijayalakshmi, K., Balamurugan, C.R. (2017) ‘Z Source Multilevel Inverter Based on Embedded Controller’, TELKOMIKA Indonesian

Journal of Electrical Engineering and Computer Science, Vol.6, No.1, pp.1-8.

84.

Authors: B.K.S.Rajaram, Krishna Prakash N

Paper Title: Secure MQTT using AES for Smart Homes in IoT Network

Abstract: The privacy and security have been becoming the most exigent tasks in the Internet of Things (IoT)

network. The worst enemy could be the IoT without the security and privacy policies. MQTT depends on TCP as

per the transport protocol, and by default the encrypted communication is not being utilized by the connection.

This paper investigates the approach of applying Advanced Encryption Standard (AES) for smart home

communication in MQTT based IoT network. A prototype of network of smart homes is implemented and the data

transmission reception is done using MQTT protocol. AES payload encryption with MQTT is done and the

network is analysed for privacy and efficiency. Brute force attack is considered for testing the confidentiality and

integrity of the data. The hardware setup of the network is implemented using Raspberry pi.

Keywords: Internet of Things, Message Authentication Codes, Cyclic Redundancy Check, Advanced

Encryption Standards, MQTT protocol, Security, cipher text, plain text.

References: 1. T. Song, R. Li, B. Mei, J. Yu, X. Xing and X. Cheng, "A Privacy Preserving Communication Protocol for IoT Applications in Smart

Homes," in IEEE Internet of Things Journal, vol. 4, no. 6, pp. 1844-1852, Dec. 2017.

2. I. Andrea, C. Chrysostom and G. Hadjichristofi, "Internet of Things: Security vulnerabilities and challenges," 2015 IEEE Symposium on

Computers and Communication (ISCC), Larnaca, 2015, pp. 180-187.

3. R. K. Kodali, V. Jain, S. Bose and L. Boppana, "IoT based smart security and home automation system," 2016 International Conference

on Computing, Communication and Automation (ICCCA), Noida, 2016, pp. 1286-1289.

4. A. Mosenia and N. K. Jha, "A Comprehensive Study of Security of Internet-of-Things," in IEEE Transactions on Emerging Topics in

Computing, vol. 5, no. 4, pp. 586-602, Oct.-Dec. 1 2017.

5. A. Syed and R. M. Lourde, "Hardware Security Threats to DSP Applications in an IoT Network," 2016 IEEE International Symposium

on Nanoelectronic and Information Systems (iNIS), Gwalior, 2016, pp. 62-66.

6. Muneer Bani Yassein, Yaser Khamayseh and Maryan Yatim, “NISHA: Novel Interface for Smart Home Applications for Arabic Region

subtitle as needed” International Journal of Advanced Computer Science and Applications (ijacsa), 7(5), 2016.

7. D. M. Alghazzawi, S. H. Hasan and M. S. Trigui, "Advanced Encryption Standard - Cryptanalysis research," 2014 International

Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, 2014, pp. 660-667.

8. S. Kulkarni, S. Durg and N. Iyer, "Internet of Things (IoT) security," 2016 3rd International Conference on Computing for Sustainable

Global Development (INDIACom), New Delhi, 2016, pp. 821-824.

9. R. Román-Castro, J. López and S. Gritzalis, "Evolution and Trends in IoT Security," in Computer, vol. 51, no. 7, pp. 16-25, July 2018.

10. D.Yogavani, N.Krishna Prakash, "Implementation of wireless sensor network based multi-core embedded system for smart city",

International Journal of Control Theory and Applications, 2017, 10 (2), 119-123.

11. M. V. Ramesh et al., "Water quality monitoring and waste management using IoT," 2017 IEEE Global Humanitarian Technology

Conference (GHTC), San Jose, CA, 2017, pp. 1-7.

12. Polamarasetty Anudeep, N. Krishna Prakash, Intelligent Passenger Information System Using IoT for Smart Cities, Advances in

Intelligent Systems and Computing, Springer, Vol.851, pp.67-76, 2019.

13. F. J. D'souza and D. Panchal, "Advanced encryption standard (AES) security enhancement using hybrid approach," 2017 International

Conference on Computing, Communication and Automation (ICCCA), Greater Noida, 2017, pp. 647-652.

14. S. C. V. Bhaskar and V. R. Rani, "Performance analysis of efficient routing protocols to improve quality of service in Wireless Sensor

493-495

networks," 2017 International Conference on Communication and Signal Processing (ICCSP), Chennai, 2017, pp. 0006-0009.

15. Wong Seng Yue, “Application of Energy Conservation Techniques in Industries and Institution”, International Innovative Research

Journal of Engineering and Technology, Vol: 4, No: 2, p. 7-16, Dec 2018.

85.

Authors: Gopikrishnan S, Priakanth P, Jothiprakash V

Paper Title: Surveillance in Nuclear Power Plant using Internet of Things

Abstract: A nuclear power plant is kind of power station that generates the electricity by nuclear reactor. As

like thermal power plants, in these nuclear power plants heat energy is used to generate the steam to drive the

turbine which is connected to power generator to produce energy. But the heat energy has been produced by the

nuclear reactor. On routine process of this type of nuclear power plant operations, the discharge of radioactive

effluents from nuclear reactor causes hazardous impacts on its environment and affects the normal life of human

beings, animals and plants. Hence it is essential to monitor the nuclear power plant and control the valves and

devices to ensure the safety of the environment. Even many safety measures has already implemented at the power

plant, the facility of monitoring and controlling from the remote location is better because the operator can be

isolated from the environment. This requirement leads to the use of Internet of Things technology in monitoring

and controlling the entire plant from remote location through internet. This research proposed a IoT based nuclear

power plant monitoring system with security features to enhance the safety of nuclear power plants.

Keywords: Internet of Things, Monitoring, Controlling, Nuclear Power Plant, Remote Location.

References: 1. Gubbi, J., Buyya, R., Marusic, S. and Palaniswami, M., 2013. Internet of Things (IoT): A vision, architectural elements, and future

directions. Future generation computer systems, 29(7), pp.1645-1660.

2. Hu, L., Zhang, Z., Wang, F. and Zhao, K., 2013. Optimization of the deployment of temperature nodes based on linear programing in the

internet of things. Tsinghua Science and Technology, 18(3), pp.250-258.

3. Jara, A.J., Zamora-Izquierdo, M.A. and Skarmeta, A.F., 2013. Interconnection framework for mHealth and remote monitoring based on

the internet of things. IEEE Journal on Selected Areas in Communications, 31(9), pp.47-65.

4. Li, F. and Xiong, P., 2013. Practical secure communication for integrating wireless sensor networks into the internet of things. IEEE

Sensors Journal, 13(10), pp.3677-3684.

5. Bello, O. and Zeadally, S., 2016. Intelligent device-to-device communication in the internet of things. IEEE Systems Journal, 10(3),

pp.1172-1182.

6. Atzori, L., Iera, A. and Morabito, G., 2014. From" smart objects" to" social objects": The next evolutionary step of the internet of things.

IEEE Communications Magazine, 52(1), pp.97-105.

7. Zanella, A., Bui, N., Castellani, A., Vangelista, L. and Zorzi, M., 2014. Internet of things for smart cities. IEEE Internet of Things journal,

1(1), pp.22-32.

8. Bi, Z., Da Xu, L. and Wang, C., 2014. Internet of things for enterprise systems of modern manufacturing. IEEE Transactions on industrial

informatics, 10(2), pp.1537-1546.

9. Chen, S., Xu, H., Liu, D., Hu, B. and Wang, H., 2014. A vision of IoT: Applications, challenges, and opportunities with china perspective.

IEEE Internet of Things journal, 1(4), pp.349-359.

10. Kantarci, B. and Mouftah, H.T., 2014. Trustworthy sensing for public safety in cloud-centric internet of things. IEEE Internet of Things

Journal, 1(4), pp.360-368.

11. Jin, J., Gubbi, J., Marusic, S. and Palaniswami, M., 2014. An information framework for creating a smart city through internet of things.

IEEE Internet of Things Journal, 1(2), pp.112-121.

496-500

86.

Authors: N. Malathi, N. Devarajan

Paper Title: An Algebraic Procedure for the Design of Linear Time Invariant Discrete and Continuous Systems

Employing Lower Order Model

Abstract: A simple algebraic procedure for model reduction of Linear Time Invariant Discrete Systems

(LTIDS) is formulated. For the given original higher order system, a second order reduced model is assumed with

unknown parameters. These parameters are determined by matching the selected amplitudes (including the steady

state and dominant dynamics) from the plot of original system response with the Laurent series terms of reduced

second order unit step response, which are the expressions in terms of unknown parameters. The responses of

original and the determined second order systems are compared. The proposed reduced order system can retain the

stability, steady state and the peak amplitudes of the original higher order system response. However, if the

dynamics of resultant reduced order system response diverge, then the sample time is tuned to an appropriate value

to attain the time match. The proposed model reduction method is extended for Linear Time Invariant Continuous

Systems (LTICS). By employing the proposed second order reduced order model, the Proportional Integral

Derivative (PID) controller is designed and then attached to the original higher order system for stabilization of the

output response. The results for LTIDS and LTICS are shown with few examples.

Keywords: Model order reduction, identification, step response, Laurent series, amplitude matching, sample

time, LTIDS, LTICS, PID.

References: 1. Devarajan N and Sivanandam S.N., “An Amplitude Matching Procedure for Constructing a Second Order Model of Linear Higher Order

Discrete Systems”, National System Conference NSC-98 proceedings, REC, Calicut, pp 99-104, December 1998.

2. Lei Chen, Junhong Li, Ruifeng Ding, “Identification for the second order systems based on the step response”, Mathematical and

Computer Modelling, pp 1074-1083, 2011.

3. Giordana Scarciotti, Alessandro Astolfi, “Data-driven model reduction by moment matching for linear and nonlinear systems”,

Automatica 79, pp 340-251, 2017.

4. S.Mukherjee, Satakshi, R.C.Mittal, “Discrete system order reduction using multipoint step response matching”, Journal of Computation

501-506

and Applied Mathematics 170, pp 461-466, 2004.

5. S.Mukherjee, Satakshi, R.C.Mittal, “Model OrderReduction using Response-Matching Technique”, Journal of the Franklin Institute 342,

pp 503-519, 2005.

6. S.Mukherjee, V.Kumar, R.Mitra, “ Order reduction of Discrete Systems using Step Response Matching”, International Journal of

Modelling and simulation, Volume 27, Issue 2, March 2007.

7. T.N.Lucas, “ Optimal discrete model reduction by multipoint Pade approximation”, Journal of the Franklin Institute 330(5), pp 855-867,

September 1993.

8. Alexander Horch, Alf J.Isaksson, “Assessment of the Sampling Rate in Control System”, Control Engineering Practice 9, pp 533-544,

2001.

9. Shamash Y, Feinmesser D, “Reduction of Discrete Time Systems using a Modified Routh Array”, Int.J. of Sys.Sci., Vol. 9, pp 53-64, 1978.

10. Prasad R, “Order Reduction of Discrete Time using Stability Equation Method and Weighted Time Moments”, Journal of I.E(India), Vol.

74, pp 94-99, November 1993.

11. Sastry G and Srinivasa Reddy G 1995, ‘New Routh Approximations for Order Reduction of Discrete Time Large Scale Systems’, NSC-

95, Coimbatore,India, pp. 210-214.

12. Gutman P.O., Mannerfelt C.F and Molander P, “Contribution to Model Reduction Problem”, IEEE Transaction Automatic Control, Vol

27, pp 454-455, 1982.

13. Bhagat S, Tewari J and Srinivasan,T 2004, ‘Some Mixed Methods for the Simplification of Higher Order Single Input Single Output

Systems’, IE(I), pp. 120-123.

14. ManigandanT., DevarajanN. and Sivanandam S.N., “A Novel Method for Linear System Model Reduction”, ACCST Research Journal,

Vol.IV, No.2, 2006.

15. Wong Seng Yue, “Application of Energy Conservation Techniques in Industries and Institution”, International Innovative Research

Journal of Engineering and Technology, Vol: 4, No: 2, p. 7-16, Dec 2018.

87.

Authors: M. Deepak, A. Gopalan, R. Akshay Raj, S.Shanmugi, P.Usha

Paper Title: Modeling of Concrete Slump and Compressive Strength using ANN

Abstract: Artificial Neural Network (ANN) is a subdivision of Artificial Intelligence are extensively used to

answer a complex civil engineering concerns. The following paper would predict the compressive strength and

slump, having several mixtures with 28 days. ANN model with 7 different parameters that comprises: Slag (SL),

Fly Ash (FL), Fine Aggregate (FA), Coarse Aggregate (CA), Super Plasticizers (SP), Cement (C), Water (W)

respectively as input while concrete slump and while compressive strength as output. The same inputs are provided

and are developed as another model. The slump and compressive strength of concrete are determined by ANN

through its machine learning which is identified by validation, testing and training results. This kind of strength

conjecture will help the concrete factories that manufactures the concrete, which when used in concrete will result

in definite strength.

Keywords: Back propagation algorithm, Slump, Compressive strength, Artificial Neural Network.

References: 1. I.-C. Yeh, “Modeling slump flow of concrete using second-order regressions and artificial neural networks,” Cement and Concrete

Composites, vol. 29, no. 6, pp. 474–480, 2007

2. Mansour M Y, Eng Struct, 26 (2004) 781-799.

3. P.K. Mehta and P.J.M. Monteiro, Concrete: Structure, Properties and Materials. 3rd ed. New York: McGraw Hill, 2006.

4. A. Jain, S. K. Jha,, and S. Misra, “Modeling the compressive strength of concrete using Artificial Neural Networks,” Indian Concr. J., pp.

17-22, Oct. 2006.

5. H. G. Ni, and J. Z. Wang, “Prediction of Compressive Strength of Concrete by Neural Networks,” Cem. Concr. Res., vol. 30, no. 8, pp.

1245-1250, 2000.

6. T. Ji, T. Lin, and X. Lin, “A Concrete Mix Proportion Design Algorithm based on Artificial Neural Networks,” Cem. Conc. Res., vol. 36,

no. 7, pp. 1399-1408, 2006.

7. D. Svozil, V. Kvasnicka, J. Pospichal, “Introduction to multi– layer Feed – Forward Neural Networks”, Chemometrics and Intelligent

Laboratory System, Vol. – 39, pp. - 43 – 62 1997

8. M. Sazli, “A Brief Review of Feed- Forward Neural Networks” Commun.Fac.Sci.Univ.Ank.Series A2-A3, Vol.50, No.-1, pp.-11-17, 2006

9. Ji T, Lin T & Lin X, Cement Concrete Res, 36 (2006) 1399-1408.

10. Yeh I C, Chen I C, Ko T Z, Peng C C, Gan C C & Chen J W, J Technol, 17(4) (2002) 583

11. Schalkoff, R. J. (1995). “Artificial Neural Networks.” McGraw Hill, Singapore.

12. S. Tamura and M. Tateishi, “Capabilities of four layered feedforward neural network: four layer versus three,” IEEE Trasactions on Neural

Networks, vol. 8, no. 2, pp. 251-255, 1997.

13. D. Hunter, Y. Hao, M.S. Pukish, J. Kolbusz and B.M Wilamowski, “Selection of proper Neural Network sizes and architectures-A

comparative study,” IEEE Transaction on Industrial Informatics, vol. 8, no. 2, pp. 228-240, 2012.

14. P.C. Pendharkar and J.A.Rodger, “Technical efficiency based selection of learning cases to improve the forecasting efficiency of neural

networks under monotonicity assumption,”, Decision Support Systems, vol. 36, no. 1, pp. 117-136, 2003.

15. K. Jinchuan and L. Xinzhe, “Empirical analysis of optimal hidden layer neurons in neural network modeling for stock prediction,” in

Proceedings of Pacific-Asia Workshop on Computational Intelligence and Industrial Applications, vol. 2, pp. 828-832, Dec. 2008

16. M. Deepak , K. Ramakrishnan, "ANN Modelling for Prediction of Compressive Strength of Concrete Having Silica Fume and

Metakaolin”, International Journal of ChemTech Research, Vol.8, No.1, pp 184-189, 2015.

507-513

88.

Authors: Sukanya.M, Madhuvannthan. S, Thaarani. T, Nathiya. P, Nirmal. S

Paper Title: An Experimental Study on Mechanical Properties of Concrete using Sludge Ash

Abstract: The aim of this project is to give a simple method of using the sludge ash in partial replacement with

cement. The disposal of sewage sludge affects the environment as it may contain harmful pathogens, heavy metals

and excess phosphorous and nitrogen. The sludge produced from waste water treatment plant is incinerated. The

sludge ash retained is partly replaced with cement in concrete at different proportions (5%, 10%, and 13%) and the

behaviour of the concrete is studied. The casted specimens are tested for 7 days and 28 days of curing strength as

per Bureau of Indian Standards (BIS) specification codes. Mechanical properties such as compressive strength,

514-517

tensile strength and flexural strength of the sludge concrete are determined. The strength obtained from the above

process is compared with the nominal concrete and the difference in the strength, flexure and tension is studied.

Keywords: Sludge ash, casting, curing, compression test.

References: 1. D. Vouk, D. Nakic, N. Stirmer and C. R. Cheeseman (2016). Use of sewage sludge ash in cementitious materials.

2. R. Baskar, K.M. Meera Sheriffa Begum, S.Sundaram (2006). Characterization and reuse of textile effluent treatment plant water sludge in

clay bricks.

3. S.Arulkesavan, V.Jayabal, S.Purusothaman, J.Uma Maheshwaran & P.Vignesh (2017). Experimental study on effect of concrete made

with textile effluent treatment effluent water.

4. Maha Alqam , Ahmad Jamrah and Haya Daghlas (2011). Utilization of cement incorporated with water treatment sludge.

5. RaghunathanT, GopalsamyP, Elangovan.R (2010). Study on strength of concrete with ETP sludge from dyeing industry.

6. Doh Shu Ing, Siew Choo Chin, Tan Kim Guan and Adilen Suil (2016). The use of sewage sludge ash as partial replacement of cement in

concrete.

7. Rafiu O. Yusuf and Zainura Zainon Noor, Moh’d Fadhil Moh’d Din, Ahmad H. Abba (2012). Use of sewage sludge ash in the production

of cement and concrete.

8. Srinivasan. K, Vazhviniyan. R, MohanKumar. L2, Palpandi. K (2016). Replacement of fine aggregate using sludge in concrete.

9. Thevaneyan Krishta David and Sivasan Karan Nair (2009). Compressive strength of concrete with sewage sludge ash.

10. Ghada Mourtada Rabie, Egypt (2016). Using of wastewater dry and wet sludge in concrete mix.

11. Sreedevi Lekshmi, Sheeba Sasidharan (2015). Experimental study on the use of textile sludge in concrete.

12. Sandhesh N U, Varun K, Prashanth V P (2014). A study on engineering properties of textile ETP sludge based cement concrete.

13. J.Balasubramanian, P.C.Sabumon, John U. Lazar, R.Illangovan (2005). Reuse of textile effluent treatment plant sludge in building

materials.

14. Mr.G.J.Kulkarni, Prrof.A.K.Dwivedi & Prof.S.S.Jahgerdar (2012). Textile mill sludge a fine aggregate in concrete.

15. IS – 10262: 2009, Bureau of Indian Standards, New Delhi. Indian Standard Code for concrete mix proportioning guidelines (First

Revision), July 2009.

16. IS - 456:2000, Bureau of Indian Standards, New Delhi. Indian Standard Code for plain and Reinforcement Concrete (Fourth Revision),

July 2000.

17. “Concrete Technology Book” M.S.Shetty.

89.

Authors: M.Manimegalai, K.Sebasthirani

Paper Title: A Novel ANN based Harmonics Mitigation and Monitoring Approach of Shunt Active Power Filter

Abstract: A new approach to monitor the power quality terms like harmonics, voltage sag or swell, flicker etc.,

in the distributed power system using shunt active power filter (SAPF) and controlling the filter using Artificial

Neural Network (ANN) has been proposed in this paper. Harmonics are identified and mitigated using MOSFET

based SAPF and controlled by ANN. Power quality has been monitored in the online for the domestic electronic

applications. Comparing to PI controller ANN has better performance. Performance of the proposed technique has

been shown in the Simulation results based on the parameter Total Harmonic Distortion (THD). Simulation has

been done in MATLAB simulink. Online Monitoring has been carried out using PHP and SQL server.

Keywords: Shunt Active Power Filter (SAPF), Artificial Neural Network (ANN), Total Harmonic Distortion

(THD), Hypertext Preprocessor (PHP), Structured Query Language (SQL).

References: 1. W.M.Grady,M.J.Samotyj, and A. H. Noyola, “Survey of active power line conditioning methodologies,” IEEE Transactions on Power

Delivery, vol. 5, no. 3, Jul. 1990, pp. 1536–1542.

2. H.Akagi,Y.Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage

components,” IEEE Transactions on Industry Applications, vol. IA-20, no. 3, May/Jun. 1984, pp. 625–630.

3. S. Jain, P. Agarwal, and H. O. Gupta, “Design simulation and experimental investigations on a shunt active power filter for harmonics and

reactive power compensation,” Electrical Power Components and Systems, vol. 32, no. 7, Jul. 2003, pp. 671–692.

4. F. Z. Peng, H. Akagi, and A. Nabae, “Study of active power filters using quad series voltage source PWM converters for harmonic

compensation,” IEEE Transactions on Power Electronics, vol. 5, no. 1, Jan. 1990, pp. 9–15.

5. H.Akagi, “Trends in active power line conditioners,” IEEE Transactions on power Electronics, vol 9, no 3, 1994, pp 263-268.

6. S. K. Jain, P. Agrawal, and H. O. Gupta, “Fuzzy logic controlled shunt active power filter for power quality improvement,” Proceedings

of Institute of Electrical Engineers, Electrical Power Applications, vol. 149, no. 5, 2002.

7. Ambrish Chandra, Bhimsingh B.N.Singh and kamal A1-Haddad. 2000. “An improved control algorithm of shunt active filter for voltage

regulation, Harmonic elimination Power factor correction, and balancing of non-linear loads” IEEE Transactions on Power electronics Vol

15, pp-495-507.

8. C.L.Trujillo D, Velasco, G.Gacera, E.Figueres, O.Carranza, “Analysis of Active Islanding methods for single phase inverters”

International conference on renewable energies and power quality, Granada(Spain) 23rd to 25th March 2010.

9. Bimal K.Bose, “An Adaptive Hysteresis band current control technique of a voltage fed PWM inverter machine drives system”, IEEE

Transactions on Industrial electronics, Vol. 37, No.5, October 1990.

10. S.R.Bowes, S.Grewah,D.Holliday, A Novel adaptive hysteresis band modulation strategy for three phase inverters” IEEE Proceedings on

Power applications ,Vol.148,No.1 , Jan 2001

11. K.Murat, O.Engin, “An Aaptive hysteresis band current controller for Shunt Active Power Filter”, Elsevier Electric Power systems

Research 73(2005) pp-113-119.

12. Fang Zheng Peng & Jih-Sheng Lai, “Generalized Instantaneous reactive power theory for three phase power systems”, IEEE Transactions

on Instrument and measurement 1996.

13. Joao Afonso, carlos Couto, Julio Martins, “Active filters with control Based on p-q theory”,IEEE Industrial Electronics Society letter.

14. Leszek S.Czarnecki, “Instantaneous Reactive power p-q theory and Power properties of Three-Phase systems” IEEE Transactions on

Power electronics Vol 21. No 1.pp 362-367, 2006.

15. J. Mu Longhua, ―Application of adaptive filtering in harmonic analysis and detection,‖ in Proc. IEEE/PES Transm. Distrib. Conf.

Exhibition:Asia Pacific, Dalian, China, 2005, pp. 1–4.

518-524

90.

Authors: M. Senthamil Selvi, P. V. Kavitha, J. Angel Ida Chellam

Paper Title: Extracting Top Competitors from Unorganized Data

Abstract: In a competitive business, success factor is based on the ability to make an item more interesting to

customers than competition. An E-Commerce application allows the user to view the items and their features along

with the option of commenting about the item and can also view comments of other customer. From the large

reviews, it is difficult for a customer to make a decision. With the set of items in existing market, competitiveness

should be evaluated using the reviews so that manufacturing item is not dominated by other existing items. The

proposed novel approach defines the competitiveness between two items based on market segments. A “CMiner”

algorithm is used to find the top competitors of a given item using the result of Item dominance. This method

improves the quality of the result when compared to previous competitor ranking models based on probability

value.

Keywords: Customer reviews, Competitor mining, Data mining, Firm analysis, Information Search and

Retrieval, Item Dominance.

References: 1. George Valkanas, Theodoros Lappas, and Dimitrios Gunopulos,” Mining Competitors from Large Unstructured Datasets”, IEEE

Transactions on Knowledge and Data Engineering, 1041-4347 (c) 2016.

2. M. Bergen and M. A. Peteraf, “Competitor identification and competitor analysis: a broad-based managerial approach,” Managerial and

Decision Economics, 2002.

3. R. Li, S. Bao, J. Wang, Y. Yu, and Y. Cao, “Cominer: An effective algorithm for mining competitors from the web,” in ICDM, 2006.

4. Kunpeng Zhang, Ramanathan Narayanan,” Voice of the Customer: Mining Online Customer Reviews for Product-Feature Based

Ranking”.

5. Kunpeng, Zhang, Yu, Cheng, Wei-Kang, Liao, Alok, Choudhary, ”Mining Millions of Reviews : A Technique to Rank Products Based on

Importance of Reviews”.

6. E. Marrese-Taylor, J. D. Vel´asquez, F. Bravo-Marquez, and Y. Matsuo,“Identifying customer preferences about tourism products using

an aspect-based opinion mining approach,” Procedia Computer Science, vol. 22, pp. 182–191, 2013.

7. T.-N. Doan, F. C. T. Chua, and E.-P. Lim, “Mining business competitiveness from user visitation data,” in International Conference on

Social Computing, Behavioral-Cultural Modeling, and Prediction. Springer, 2015, pp. 283–289.

8. Bushra Anjum, Chaman Lal Sabhaewal,” An Entropy Based Product Ranking Algorithm using reviews and Q&A data”.

525-529

91.

Authors: M.R.Vanithamani, Dinesh Babu. N

Paper Title: Impact of Personal Traits and Professional Competencies on Entrepreneurial Competencies of Women

Entrepreneurs

Abstract: Women as the better hsalf of men constitute approximately half of the global population. Therefore

they are, regarded as the better half of the society. Evidences across the globe buttress that, women are performing

in a great manner in all major discipline of life like, research & academia, entrepreneurship, medicine,

constrictions, technical fields, in politics, as business administrators and in social work too. Today, they have

started proving their competency in industry also and running their business enterprises successfully. Regardless of

the variety of explanations for the self-help phenomenon, the consensus is that there is a need for a new business

model to anchor and encourage professional services. Self-help groups are growing at an extraordinary speed

globally. Keeping this as a research gap the author has done an in-depth analysis about the impact of personal traits

and professional competencies on the entrepreneurial competency of women entrepreneurs, so as to frame a

suitable model which encompasses all those factors that leads to their entrepreneurial success.

Keywords: Women Entrepreneurs, Professional Competencies, Entrepreneurial Competencies, Personal Traits.

References:

1. Gupta C.B, Khanka S.S..(2003) Entrepreneurship and Small Business Management, Sultan Chand & Sons, New Delhi, 4th Edition..

2. Ivy Jeno.S, (2007)“Empowerment of Women /through SHGs”, India: Economic Empowerment of women , New Century Publications,

New Delhi, P. 158-163.

3. Janaki Radha Krishnan,(2007), “Women empowerment through Self- Help Groups”, India : Economic Empowerment of women, New

Century Publications, New Delhi, p 238-241.

4. Kavitha.K.S, and Vasudevan.V.P, (2007) SHGs for the Success of Women Entrepreneurs, India: Economic Empowerment of women,

New Century Publications, New Delhi, P. 129-134.

5. Krishnamurthi.N.A & Suresh.K.M,(2007)“Role of SHGs in Women empowerment”, India: Economic Empowerment of women , New

Century Publications, New Delhi, P. 48-54.

6. Kiggundu, M.N. Entrepreneurs and Entrepreneurship in Africa: what is known and what needs to be done, Journal of Development

Entrepreneurship, 7(3), 2002, 239-258.

7. Manimala .M.J(2005),” Entrepreneurial Heuristics’ in Entrepreneurship Theory at the Cross- roads: Paradigms and Praxis Second Edition

, Biztantra Publishing, New Delhi..

8. Panandikar and S.Patel .V.G.; Women Entrepreneurship Development, Keynote Address at the fifth National convention of Women

Entrepreneurs, under the aegis of women’s wing of NAYE, Gujarat Chapter, Ahmedabad, February 6-8, 1986.

9. Ramasamy. H.(1995) Productivity in the Age of Competitiveness: Focus on Manufacturing in Singapore. In Productivity in the Age of

Competitiveness. APO Monograph Series 16, Asian Productivity Organization.

10. Singh, K.P.; Women Entrepreneurs; Their Profile and Motivation, The Journal of Entrepreneurship, Vol.2, No.1 ,1993.

11. Thompson, J. E., Stuart, R. and Lindsay, P. R,(1996) The Competence of Top Team Members: A Framework for Successful Performance,

Journal of Managerial Psychology, 113, p: 48-66.

12. Vanithamani.M.R., “A Comparative Study of Urban and Rural Woman entrepreneurs in Unorganized Business Sector” JM International

Journal Of Management Research, ISSN 2229-4562, Vol. 1,Issue:3 March 2011 Issue, Pg: 218-230

530-536

13. Vanithamani.M.R., “Impact of Business Types on the Problems Faced by SHG Women Entrepreneurs” , International Journal of Research

in Commerce & Management, ISSN 0976-2183, Vol. 1, Issue7, Dec-2011, Pg: 41-45

14. Vanithamani.M.R., “Enhancing Entrepreneurial Success Of Self Help Group Women Entrepreneurs through Effective Training” Excel

International Journal of Multidisciplinary Management Studies, ISSN2249-8834, Jan-2012 Issue, Pg: 60-72.

15. Vanithamani.M.R., “Microfinance Management in Self Help Groups” is published in International Journal of Social Science &

Interdisciplinary Research, ISSN 2277-3630, Vol-1 No.4, April 2012 Issue, Pg: 24-30

16. Vanithamani.M.R., “Entrepreneurial Competency Components of SHG Women Entrepreneurs- Factor Analysis”, International journal of

Information Technology & Computer Science Prospective , Vol. 1, No:1, Oct – Dec -2012-ISSN: 2219-9016, Pg. No: 229-236.

92.

Authors: R.M. Sekar, S.Muthukumaran, B.Pushpavanam, K. Sanjula

Paper Title: Synchronously Operating Buck-Boost Converter with Continuous Current

Abstract: This paper reports a modernized synchronously Operating buck-boost converter with persistent

current will be proposed. Contrasted and the conventional buck-boost converter, the suggest converter can get a

dynamically wide degree of the voltage transformation proportion with the similar obligation cycle. In addition,

the suggest converter can work with persistent current contrasted to the existing counterparts with an inherently

discontinuous current. The operational guideline and enduring-state execution of the suggest converter under

persistent inductor current mode is investigated personally. At that point, the examination among the suggest

converter and thus the current quadratic buck-boost converters has been directed to exhibit the unmistakable

highlights of the suggest one. To check the operation of the proposed converter, a simulation model will need to

develop by using MATLAB Simulink. The developed simulation model needs to be analyzing for various stacking

conditions.

Keywords: DC-DC power conversion, a buck-boost converter, CCM.

References: 1. D .Zhou, “Synthesis of PWM Dc-to-Dc Power Converters,” Ph.D. thesis, California Institute of Technology, October 1995.

2. P. Lee, Y. Lee, D. Cheng, and X. Liu,”Steady-State Analysis of an Interleaved Boost Converter with Coupled Inductors”, IEEE Trans. On

Industrial Electronics, Vol. 47, No.4, August 2000, pp787-795.

3. B. Lin and H. Lu,”A Novel PWM Scheme for Single-Phase Three Level Power-Factor-Correction Circuit”, IEEE Trans.On Industrial

Electronics, Vol. 47, No. 2, April 2000

4. D. Maksimovic and R. Erickson,” Universal-Input, High-Power-Factor, Boost Doublers Rectifier”, Proc.IEEE APEC, 1995 Record, pp.

459-465.

5. D. Wolaver,”Fundamental Study of Dc to Dc Conversion System,”Ph.D. thesis, Massachusetts Institute of Technology, January 1969.

6. D. Maksimovic and S. Cuk,”General Properties and Synthesis of PWM Dc-to-Dc converters”, in IEEE Power Electronics Specialists

Conference, pp.515-525, 1989.

7. D. Maksimovic and S. Cuk, “Switching Converters with wide Dc conversion range” ,IEEE Transaction on Power Electronics, Vol. 6, No.

1, pp.151-157, Jan.,1991

8. G. Moschopoulos, “Quadratic Power Conversion for industrial application”, APEC, pp. 1320-1327, 2010.

9. X. L. Wei, K. M. Tsang and W. L. Chan, “Non-linear PWM control of single-switch quadratic buck converters using internal model”, IET

Power Electronics, Vol. 2, No. 5, pp.475-483, 2009.

10. J. A. M. saldana, J. L. Ramson, E. E. C. Gutierrez and M. G. O. Lopez, “Average current-mode control scheme for a quadratic buck

converter with a single switch” , IEEE Transaction on Power Electronics, Vol. 23, No.1, pp. 485-490, Jan.,2008.

537-541

93.

Authors: I. Gerald Christopher Raj, P. Soundar Rajan, G. Praveen Raj, J. Anjel

Paper Title: A Study and Hardware Implementation of Enhanced Isolated Boost DC-DC Converter with the

Reduced Number of Switches

Abstract: For voltage gain utilization, the originators are foremost half lean towards the DC-DC boost

converter. In any case, it needs the restriction in Vout by the additional transferral proportion, diminished

efficiency and its necessity of voltage and current for response signals, that makes composite control system by

means of expanded by and large expense. Besides, the Vout and efficiency are diminished because of the self-

parasitic nature of power circuit parts. To overcome these disadvantages, this paper gives the theoretical

enhancement and hardware execution of the DC-DC boost converter with the reduced number of switches circuit

for acquiring high Vout and high enactment. The proposed circuit munificently will increase the high Vout by

VDR with a closed loop proportional-integral controller. The converter circuit together with a closed-loop PID

controller is created within the hardware prototype model. A point by point execution examination was completed

under resistive loading conditions. Numerical verification results gave during this paper demonstrate the incredible

course of action in the circuit with a theoretic circumstantial.

Keywords: DC to DC power conversion, voltage fed full-bridge (VFFB) converter, galvanic isolation, high-

frequency step-up transformer, voltage doubler rectifier (VDR).

References: 1. D. S. Gautam, F. Musavi, W. Eberle, and W. G. Dunford, “A zero-voltage switching full-bridge dc–dc converter with capacitive output

filter for plug-in hybrid electric vehicle battery charging,” IEEETrans. Power Electron. vol. 28, no. 12, pp. 5728–5735, Dec. 2013.

2. Y. Xie, R. Ghaemi, J. Sun, and J. S. Freudenberg, “Implicit model predictive control of a full bridge dc–dc converter,” IEEE Trans.

PowerElectron., vol. 24, no. 12, pp. 2704–2713, Dec. 2009.

3. R. W. De Doneker, D. M. Divan, and M. H. Kheraluwala, “A three-phase soft-switched high-power-density dc/dc converter for high-

power applications,”IEEE Trans. Ind. Appl., vol. 27, no. 1, pp. 797–806, Jan./Feb 1991.

4. M. H. Kheraluwala, R. W. Gascoigne, D. M. Divan, and E. D. Baumann,“Performance characterization of a high-power dual active bridge

dc-to dc converter,” IEEE Trans. Ind. Appl., vol. 28, no. 6, pp. 1294–1301,Nov./Dec. 1992.

5. R. Ayyanar and N. Mohan, “Novel soft-switching DC–DC converter with full ZVS-range and reduced filter requirement—Part II:

542-545

Constant-input variable-output applications,” IEEE Trans. Power Electron., vol. 16, no. 2, pp. 193–200, Mar. 2001.

6. M. Borage, S. Tiwari, S. Bhardwaj, and S.Kotaiah, “A full-bridge DC–DC converter with zero-voltage-switching over the entire

conversion range,”IEEE Trans. Power Electron., vol. 23, no. 4, pp. 1743–1750, Jul. 2008.

7. H. Bai and C. C. Mi, “Comparison and evaluation of different DC/DC topologies for plug-in hybrid electric vehicle chargers,” Int. J.

Power Electron., vol. 4, no. 2, pp. 119–133, 2012.

8. P. G. Barbosa, H. A. C. Braga, M. C. B. Rodrigues, and E. C. Teixeira,“Boost current multilevel inverter and its application on single-

phase grid connected photovoltaic systems,” IEEE Trans. Power Electron., vol. 21,no. 4, pp. 1116–1124, Jul. 2006.

9. J. Chen, D.Maksimovic, and R.W. Erickson, “Buck–boost PWM converters having two independently controlled switches,” in Proc. IEEE

PESC, 2001, pp. 736–741.

10. M. H. Kheraluwala, R. W. Gascoigne, D. M. Divan, and E. D. Baumann,“Performance characterization of a high-power dual active bridge

dc-to dc converter,” IEEE Trans. Ind. Appl., vol. 28, no. 6, pp. 1294–1301,Nov./Dec. 1992.

94.

Authors: M.Arul prasanna, D.Arun Prasad, R.Baladhandapani, K.Shanmuga priya

Paper Title: Switched Capacitor based High Gain DC-DC Boost Converter

Abstract: A switched-capacitor (SC) - based High gain DC to DC boost converter is suggest in this work. This

work uses switched capacitor based double switch converter for attaining the huge Voltage gain with minimum

duty cycle. Hence in turn it reduces the Voltage stress and the on state losses on the influence electronic switches.

Here the working principles and the design parameters are presented for the converter in both Conduction modes.

Also the developed topology is going to be validated towards the conventional non-isolated converters both in

simulation and in hardware prototype. Also the simulated DC-DC Boost Converter a research center model is

structured and the outcomes are approved for its functionality.

Keywords: Switched capacitor, High Gain, Full Bridge Converter, Voltage Multiplier.

References: 1. Chen S.M , T. Liang T.J, Yang L.S, and Chen J.F. (2013) , “A boost converter with capacitor multiplier and coupled inductor for ac

module applications,” IEEE Trans. Ind. Electron., vol. 60, no. 4, pp. 1503–1511.

2. Hsieh Y.P , Chen J.F , Yang L.S, Wu C.Y, and Liu W.S. (2014) , “High-conversion-ratio bidirectional DC/DC converter with couple

inductor,” IEEE Trans. Ind. Electron., vol. 61, no. 3, pp. 1311-1319.

3. Hu X.F, and Gong C.Y (2015) , “A high gain input-parallel output-series DC/DC converter with dual coupled inductors”, IEEE Trans.

Power Electron., vol. 30, no. 3, pp. 1306-1317.

4. Li W, and He X. (2011) “Review of non isolated high-step-up dc/dc converters in photovoltaic grid-connected applications,” IEEE Trans.

Ind. Electron., vol. 58, no. 4, pp. 1239–1250.

5. Liu H, Hu H, Wu H, Xing Y, and Batarseh I. (2016) , “Overview of high-step-up coupled-inductor boost converters,” IEEE J. Emerg. Sel.

Topics Power Electron., vol. 4, no. 2, pp. 689–704.

6. Nymand M and Andersen M.A.E . (2010) , “High-efficiency isolated boost dc–dc converter for high-power low-voltage fuel-cell

applications,” IEEE Trans. Ind. Electron., vol. 57, no. 2, pp. 505-514.

7. Rosas-Caro J.C , Ramirez J.M , Peng F.Z and Valderrabano A. (2010) “A dc–dc multilevel boost converter,” IET Power Electron., vol. 3,

no. 11, pp. 129–137.

8. Tofoli F.L , Pereira D.C , Paula W.J and Junior D.S.O .(2015). “Survey on non-isolated high-voltage step-up dc–dc topologies based on

the boost converter,” IET Power Electron., vol. 8, no. 10, pp. 2044–2057.

9. Yao C, Ruan X and Wang X. (2015), “Automatic mode-shifting control strategy with input voltage feed-forward for full-bridge-boost dc–

dc converter suitable for wide input voltage range,” IEEE Trans. Power Electron., vol. 30, no. 3, pp. 1668–1682.

10. Zhu M and Luo F.L . (2010), “Enhanced self-lift Cuk converter for negative-to-positive voltage conversion,” IEEE Trans. Power

Electron., vol. 25, no. 9, pp. 2227-2233.

546-549

95.

Authors: Ravi Kumar Kandagatla, Potluri Venkata Subbaiah

Paper Title: Posteriori Regularization based Non-Negative Matrix Factorization approach for Speech Enhancement

Abstract: The paper proposes, a speech enhancement method for reducing additive Gaussian noise using

iterative posterior regularized Non-negative matrix factorization (NMF). Here, regularization for NMF criterion is

obtained by assuming the prior distribution of the Discrete Fourier Transform (DFT) spectral magnitudes of speech

follows Nakagami, Weibull distribution and DFT spectral magnitudes of coefficients follows as Rayleigh

distribution. In this paper, different prior distributions, Nakagami, Weibull and Rayleigh are used and the

estimates of distribution statistics are changed adaptively to provide regularization. The results for different priors

are compared using different objective performance measures Perceptual Evaluation of Speech Quality (PESQ)

and Signal to Distortion Ratio (SDR).

Keywords: Speech enhancement, Noise reduction, Non-negative Matrix Factorization, Weibull distribution,

Iterative Posterior regularization.

References: 1. C. Fevotte, N. Bertin, J-L. Durrieu, “ Nonnegative matrix factorization : with the itakura-saito divergence with application to music

analysis,” Neural computation., Vol. 21, no. 3, pp. 793 – 830, Mar. 2009.

2. D. D. Lee, H. S. Seung, “ Algorithms for non-negative matrix factorization, ” in Proc..Advances in neural information processing systems

(NIPS)., pp. 556 – 562, 2001.

3. Ivan Tashev, Alex Acero, “ Statistical Modeling of the speech signal, ” in International Workshop on Acoustic, Echo, and Noise Control

(IWAENC)., 2010

4. M. W. Berry, M. Browne, A. N. Langville, V. P. Pauca, R. J. Plemmons, “Algorithms and applications for approximate nonnegative

matrix factorization,” at Computational statistics & data analysis., Vol. 52, no. 1, pp. 155 - 173. 2006

5. N. J. Bryan, G. J. Mysore, “ An efficient posterior regularized latent variable model for interactive sound source separation, ” in

International Conference of Machine Learning (ICML)., pp.208 – 216, June 2013

6. N. Mohammadiha, P. Smaragdis, A. Leijon, “ Supervised and unsupervised speech enhancement using nonnegative matrix factorization, ”

550-555

IEEE Transactions on Audio, Speech and Language Processing., Vol. 21, no. 1, pp. 2140- 2151. Oct. 2013

7. K. Y. Chan, S. Nordholm, K. F. C. Yiu, R. Togneri, “ Speech enhancement strategy for speech recognition microcontroller under noisy

environments,” in Neuro computing., Vol 118, pp. 279-288, March. 2013

8. NOIZEUS Database.

9. Y. Hu, P. C. Loizou, “ Evaluation of objective quality measures for speech enhancement, ” in IEEE Transactions on Audio, Speech, and

language processing., Vol.16 , no. 1, pp.229-238, Jan. 2008

10. E. Vincent, R. Gribonval and C. Fevotte, " Performance measurement in blind audio source separation," in IEEE Transactions on Audio,

Speech, and Language Processing., vol. 14, no. 4, pp. 1462-1469, July 2006.

11. K.Ravi Kumar, P.V.Subbaiah, “Speech Enhancement using MMSE Estimation under phase Uncertainty”, in International Journal of

Speech Technology, Volume 20, pp 373–385, June 2017.

12. Ravi Kumar Kandagatla, P.V. Subbaiah, “Speech enhancement using MMSE estimation of amplitude and complex speech spectral

coefficients under phase-uncertainty” , Speech Communication, Volume 96, pp 10-27, February 2018

96.

Authors: Veena Dinesh, H.K Shivanada, Arasu Kumar, Srinivasa Chari V

Paper Title: Preparation of Hybrid Polymer Composite Materials

Abstract: In this project we endured through the natural fibers. As we know the extensive use of fibres in all the

fields, so we can’t directly use the fibers it needs to-do reinforcement of the composites. We are introducing the

new hybrid polymer with light weight and economical composites.

Keywords: Metal matrix, composites, fibers and reinforcement.

References: 1. A Review on Sisal Fiber reinforced Polymer Composites. Kuruvilla Joseph1, Romildo Dias Tolêdo Filho2, Beena James3, Sabu Thomas4

& Laura Hecker de Carvalho5 RevistaBrasileira de EngenhariaAgrícola e Ambiental, v.3, n.3, p.367-379, 1999 Campina Grande, PB,

DEAg/UFPB

2. Properties of SBS and Sisal Fiber Composites: Ecological Material for Shoe Manufacturing José Carlos Krause de Verney*, Martha

Fogliato Santos Lima, Denise Maria Lenz

3. Tensile Properties and SEM Analysis of Bamboo and Glass Fiber Reinforced Epoxy Hybrid Composite sH.RaghavendraRao*1, A. Varada

Rajulu2, G. Ramachandra Reddy3and K. Hemachandra Reddy4

4. Biodegradable Polymers: Past, Present, and Future M. Kolybaba1, L.G. Tabil 1, S. Panigrahi1, W.J. Crerar1, T. Powell1, Wang1

5. Yan Li, Yiu-Wing Mai, Lin Ye, ‘Sisal fiber and its composites: a review of recent developments’. Composites Science and Technology,

volume 60, (2000), 2037-2055.

6. K. Murali Mohan Rao, K. MohanaRao ‘Extraction and tensile properties of natural fibers: Vakka, date and bamboo’. Composite

Structures volume 77,(2007), 288–29.

7. A.Alavudeen,M. Thiruchitrambalam, N.Venkateshwaran and A.Athijayamani “Review of natural fiber reinforced Woven composite”

Advances in Material science, volume -27: 2011.

8. H.M.M.A. Rashed, M. A. Islam and F. B. Rizvi, “Effects Of Process Parameters On Tensile Strength Of Jute Fiber Reinforced

Thermoplastic Composites”, Journal of Naval Architecture and Marine Engineering, June, 2006.

9. A.V.Ratna Prasad K.Murali Mohan Rao and G.Nagasrinivasulu “Mechanical properties of banana empty fruit bunch fiber reinforced

polyester composites” Indian journal of fiber and textile reasearch,Vol-34:2009.

10. JORG MUSSIG “Industrial Applications of Natural Fibers” Department of Biomimetics, Hochschule Bremen – University of Applied

Sciences,Bremen, Germany.

11. Lina Herrera, SelvumPillay and UdayVaidya “Banana fiber composites for automotive and transport applications” Department of Matrial

Science & Engineering, University of Alabama at Birmingham, Birmingham, AL 35294.

556-561

97.

Authors: Abdul Ghani Abdul Samad, Rayed Haider, Khairul Amiza Md Hairudin

Paper Title: Human Factors Affecting Avionics Workshop in MRO 145

Abstract: The study set out to find the human factors influencing aviation safety in Maintenance, Repair and

Overhaul 145. The research objectives were to establish the extent to which personal professional qualifications,

aviation infrastructure and technical guidance material influence human factors in Maintenance, Repair and

Overhaul 145. The target population of the study was 30 employees of Maintenance, Repair and Overhaul 145. A

census approach was used as the researcher was interested in collecting data from every member of the target

population. The questionnaire was constructed using structured and unstructured questions. Both descriptive and

inferential statistics were used as a tool of evaluation in the data analysis. A set of 27 questions consisted of 3

subsets (Personnel Qualified and Aviation Safety, Infrastructure on Aviation Safety and Technical Guidance

Material (TGM) on Aviation Safety) of variables have been used to meet the research objectives respectively. The

study concludes that personnel professional qualifications are a major contributor to aviation safety because the

aviation industry is technical based with rapidly changing technologies, applications and emerging issues.

Recruitment and retention policies need to be prioritized in order to attract the appropriate personnel based on the

organization needs. The overall infrastructure Maintenance, Repair and Overhaul 145 is wanting and hence has a

great effect on aviation safety. The study concludes that the relevance of the existing TGMs is in line with the

current practices in the aviation industry. However, recommended revisions should be implemented as soon as

possible.

Keywords: Technical Guidance Material (TGM), Aviation Safety, MRO 145, Human Factors.

References: 1. Christopher D., John D., Yili L., &Gordon-Becker S. Introduction to Human Factors Engineering, 2ndEdition, Pearson; 2003

2. WiegmannD. &Shappell S. Human Error Approach to Aviation Accident Analysis: The Human Factors Analysis and Classification

System, Routledge; 2016

3. Hawkins F. Human Factors in Flight, 2nd Edition, Ashgate;1987

562-564

4. ICAO Doc 9734 – Safety Oversight Manual. Available on https://www.icao.int/WACAF/AFIRAN08_Doc/9734_parta_cons_en.pdf

accessed on 25/10/2018.

5. ICAO Doc 9735 – Universal Safety Oversight Audit Programme Continuous Monitoring Manual. Available on

https://www.icao.int/SAM/Documents/2011/CMA/9735_USOAP_CMA_Manual_3rd_Edition.pdf accessed on 25/10/2018.

6. Salas E.& Maurino E. Human Factors in Aviation, 2nd Edition, Academic Press; 2010

7. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

8. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

9. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

10. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

11. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

12. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

13. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

14. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

15. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

16. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

17. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

18. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

19. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

20. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

21. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

22. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

23. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

24. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

25. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

98.

Authors: AfiqFaizalAzman, Ahmad AmirulIqhmal Abdul Rahman

Paper Title: Potential and challenges of drop-in biojet fuel in Malaysia

Abstract: “Drop-in” biojet fuel is the term used for the renewable alternative jet fuel which requires no

modification on the current aircraft engine and the existing infrastructures. Technically, biojet fuel is ready to be

used as either mixed with petroleum-based jet fuel or potentially become a 100% replacement for conventional jet

fuel. Although there have been some airline companies utilizing biojet fuel for their fleets, Malaysian airline

companies have yet to implement it. Thus, the main objectives of this research are to investigate the potential of

drop-in biojet fuel, to identify the challenges in implementing drop-in biojet fuel and to measure the potential and

the challenges of drop-in biojet fuel to ensure a smooth transition in using the alternative jet fuel; all within

Malaysia Airline Berhad (MAB) contexts and parameters. The quantitative data result shows that most of MAB’s

personnel in engineering and management department are aware and knowledgeable in biojet fuel. Most of them

acknowledge the potential and challenges of drop-in biojet fuel. From the response from respondent, it is highly

potential in Malaysia for the drop-in biojet fuel to be implemented. However, there are still challenges that need to

be tacked to ensure the transition process from conventional to biojet fuel is smooth.

Keywords: Biojet fuel, Greenhouse Gas (GHG), Malaysia Airline Berhad (MAB).

References: 1. The Flight Path for Biojet Fuel. Available on https://www.eia.gov/workingpapers/pdf/flightpaths_biojetffuel.pdf accessed on 25/10/2018.

2. The Potential and Challenges of Drop-in Biofuels. Available on http://task39.sites.olt.ubc.ca/files/2014/01/Task-39-Drop-in-Biofuels-

Report-FINAL-2-Oct-2014-ecopy.pdf accessed on 25/10/2018.

3. ICAO Environmental Report 2010. Available on https://www.icao.int/environmental-

protection/Documents/Publications/ENV_Report_2010.pdfaccessed on 25/10/2018.

4. Noh H, Rodriges G, & Abdul Rahman N.Green Renewable Energy Risk need to be Tackled in Going Green for Air Transportation.

Applied Mech. And Mater. 2015;747:325-328

5. Brasseur G, Gupta M, Anderson B, Balasubramaniam S, Barrett S, Duda D, & Zhou C. Impact on climate: FAA’s Aviation Climate

Change Research Initiative (ACCRI) phase II. Bul. of the. Amer. Meteor. Soc.;97(4):561-583

6. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

7. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

565-572

8. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

9. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

10. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

11. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

12. Johari M, Jalil M, &MohdShariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

13. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

14. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

15. Ya'acob A, MohdRazali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, MohdAris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

16. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

17. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

18. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

19. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

20. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

21. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

22. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

23. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

24. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, MohdAris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

99.

Authors: Muhammad IqmalMohd Ali, Nurul Asmia’tulAsii’mah Ahmad Khairul Azman

Paper Title: Automated Deployable Protection Unit for Drones

Abstract: This drone protection unit is designed to protect from possible accidents on the ground or water.

Accidents may cause technical failure, signal losses, motor malfunction, weather condition, collision etc. The

objective is to develop a prototype to protect the components or any such packaging attached to the drone for safe

landing. Similar to an airbag concept, it deploys two inflators once the sensor detects any unwanted movement

experienced by the drone. A total of six tests were done for this experiment. The first three tests were the

Ultrasonic, Arduino and reliability tests; to indicate any environmental variables that can have an impact to the

drone and for the speed sensor. Among these three, ultrasonic test gave the best sensing ability compared to the

others. The reliability test was conducted by placing the sensor in front of a fan to observe the effect on the sensor;

whether it would be affected by windy conditions. The functional test involved the drone to be equipped with six

sensors to determine the result for any changes in movement of any object from the sensor. The final test was

observing the whole system by dropping the decoy drone from a height of 12m. Overall results showed that the

time taken for the airbag to fully be inflated was 32ms while the drone protection applied for this project was

1.293s.

Keywords: Drone Protection System, Ultrasonic Sensor, Arduino Infrared Sensor.

References: 1. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

2. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

3. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

4. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

5. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

6. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

7. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

8. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

9. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

10. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

11. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

573-583

12. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

13. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

14. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

15. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

16. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

17. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

18. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

19. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

20. FAA Drone Sighting Reports. Available on https://www.faa.gov/news/updates/?newsId=87565 accessed on 25/10/2018.

100.

Authors: Muhammad Iqmal Mohd Ali, Mohd Husaini Husni

Paper Title: Efficiency of Solar Cells for UAV

Abstract: This study analyzed the C60 solar cell compared to conventional solar cell in terms of efficiency of

the solar cell in the application of running brushless motor load. The efficiency of both solar cell output produced

will determine if it can support the brushless motor load or not throughout the day, from afternoon at 12pm till the

battery drop at 14.8V which is the lowest point of battery can go without damaging it. A detailed analysis has been

performed in order to compare the efficiency of both solar cell by measuring both of its output throughout the day

from 9am till 3pm by setting up two multimeter to measure current and voltage respectively for both solar cells. A

flat cardboard surface is used as platform. Ground Battery endurance test is conducted to get the data of power

consumption at different brushless motor load and solar radiance, rate of charge and full battery endurance test

with and without solar cell power support from both C60 and conventional solar panel. From the analysis, it was

found that C60 solar panel performed better than conventional solar panel on the test conducted. This is due to

difference of conversion efficiency between Sunpower C60 and conventional solar panel which were 22.5% and

17.6% respectively. These findings have significant implications for commercial applications when using solar

cell. It appears Sunpower C60 solar panel would provide more power than Conventional solar panel during their

usage cycle.

Keywords: Solar Cells, UAV, Battery Endurance, solar power, Endurance flight project.

References: 1. Siddiqui R & Bajpai U.Deviation in the performance of solar module under climatic parameter as ambient temperature and wind velocity

in composite climate. Int. Jour. of Renew. Ener. Reser. 2012;2(3):486-490

2. Schwingshackl C, Petitta M, Wagner J, Belluardo G, Moser D, Castelli M, Zebisch M, &Tetzlaff A.Wind effect on PV module

temperature: Analysis of different techniques for an accurate estimation. Ener. Procedia2013;40:77-86

3. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

4. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

5. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

6. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

7. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

8. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

9. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

10. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

11. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

12. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

13. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

14. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

15. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

16. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

17. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

18. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

584-586

19. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

20. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

21. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

101.

Authors: Baha Rudin Abd Latif, Muhammad Irfan Abdul Satar

Paper Title: Developing a Dual-Axis Solar Tracker System with Arduino

Abstract: Solar panels have been used increasingly in recent years to convert solar energy to electrical energy.

The solar panel can be used either as a standalone system or as a large solar system that is connected to the

electricity grids. The problem that we can see now is most of the solar panel that had been used by a user is only in

a static direction. This project is focusing on consuming more energy from the sun using solar tracker. The

developed dual-axis solar tracker uses a Light Dependence Resistor (LDR) to sense the intensity of light while

servo motor will rotate the solar panel based on the highest intensity of light.

Keywords: Solar Tracker System, Light Dependence Resistor (LDR), fixed and single axis.

References: 1. Guo L, Curtis P, Barendregt A, &Surillo A.Sun-tracking Solar Power System. Amer. Soc. for Eng. Edu.2009;354:14.122.1-14.122.11

2. Dhanabal R, Bharati V, Ranjitha R, Ponni A, Deepthi S, &Mageshkannan P.Comparison of Efficiencies of Solar Tracker systems with

static panel Single Axis Tracking System and Dual-Axis Tracking System with Fixed Mount. Int. Jour. of Eng. & Tech. 2013;5(2):1925-

1933

3. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

4. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

5. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

6. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

7. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

8. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

9. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

10. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

11. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

12. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

13. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

14. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

15. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

16. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

17. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

18. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

19. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

20. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

21. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

587-590

102.

Authors: Abdul Ghani Abdul Samad, Hani HafieraKhahar

Paper Title: Human Factor Issue – Glare Effects towards Airline Personnel

Abstract: The main objectives of this research are to identify the factors and effects of glare that could grave

consequences towards the airline personnel and discuss effective, economical preventive measures; especially

pilots and technicians. This research focuses on 102 airline personnel; consisting of pilots, ground handling

services staffs, and line maintenance workers of a major airline in Malaysia who were stationed at Kuala Lumpur

International Airport (KLIA) and Penang International Airport (PIA). A quantitative approach has been utilized to

measure not just the awareness levels of glare effects, but also possible innovative ways to avoid glare effects. A

validated, customized questionnaire involving Likert-scale and open-ended questions was successfully distributed

and returned. Overall, the results showed that glare effects have been critically affecting their work during the day

591-593

and night. In addition, several staffs have revealed several cases of eye hazards caused by prolonged glare effects.

This has imposed the airline company to implement precautionary steps extensively, e.g. always impose the ruling

of wearing shades, apply safety tints on glasses and windows around the working sites, and usage of special paints

which do not reflect sunlight. It is hoped that more researchers and aviation companies can collaborate with safety

equipment industries to innovate not just effective, but also economical solutions for preventing glare effects.

Keywords: Penang International Airports (PIA), Malaysia Airline Berhad (MAB), Factor and Effect of Glare.

References: 1. Evaluation of Glare as a hazard for general Aviation Pilots on Final Approach. Available on

https://www.faa.gov/data_research/research/med_humanfacs/oamtechreports/2010s/media/201512.pdfaccessed on 13/09/2018.

2. Nakawara V, Montgomery R, & Wood K.Aircraft accidents and incidents associated with visual effects from bright light exposures during

low-light flight operations. Optometry. 2007;78(8):415-420

3. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

4. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

5. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

6. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

7. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

8. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

9. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

10. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

11. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

12. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

13. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

14. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

15. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

16. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

17. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

18. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

19. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

20. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

21. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738.

103.

Authors: Abdul Ghani Abdul Samad, Nur AinaaHusna Omar

Paper Title: Shift and Schedule Affecting Line Maintenance Performance

Abstract: The main objective of this research is to identify the impact of shift and schedule related to stress that

are reflected in line maintenance performance. It is also intended to emphasize more on the consequences towards

the line maintenance personnel so they would be aware and take precaution steps. With the utilization of

quantitative methods, 100 Malaysian Aircraft Maintenance Technicians (AMTs) from a major low-cost airline

company were given a specifically-tailored questionnaire which investigates the impact of shift and schedule in

their Line Maintenance Department. Based in Selangor, these maintenance personnel were from the 23-46 years of

age and had a variety of weekly work schedule. The data has concluded that among them, several different health

issues have been recorded because of irregular and/or extensive working hours. Other contributing factors included

tough deadlines, low wages, work environment, and mismatch between personnel’s capabilities and organizational

demands.

Keywords: Maintenance performance, questionnaire, Shift and Schedule.

References: 1. Work-related factors and ill health: the Whitehall II study. Available on

https://www.centredoc.cnesst.gouv.qc.ca/in/fr/;jsessionid=D7613C99D117DB0A7B797C4B58CF285Faccessed on 15/07/2018.

2. Pettersen K & Aase K. Explaining safe work practices in aviation line maintenance. Safety Science. 2008;46(3):510-519

3. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

594-598

4. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

5. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

6. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

7. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

8. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

9. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

10. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

11. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

12. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

13. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

14. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

15. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

16. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

17. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

18. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

19. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

20. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

21. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738.

104.

Authors: Muhd Zulfadhli Muhd Zaimi, Muhammad SyahmiNazran, RoslanBasit

Paper Title: Design and Testing UniKL MIAT CF 700 AFT Fan Turbofan Fuel Tank with Indicator

Abstract: This project is to describe designing and testing UniKL MIAT CF 700 Aft turbo fan fuel tank with

indicator system. The original fuel tank engine tends to run out fuel in a short time of period when engine ground

run is conducted. As an alternative to this problem, a new bigger design of the fuel tank will be design and will be

tested with simulation to overcome this problem. The main objective is to design new bigger fuel tank with

indicator and to test the design with the hydrostatic test in simulation program.

Keywords: Fuel tank, hydrostatic pressure, Engine, Design and Testing.

References: 1. CF 700 Engine by General Electric. Available on https://www.geaviation.com/bga/engines/cf700-engineaccessed on 01/02/2018.

2. Pettersen K & Aase K. Explaining safe work practices in aviation line maintenance.Safety Science. 2008;46(3):510-519

3. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

4. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

5. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

6. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

7. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

8. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

9. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

10. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

11. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

12. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

13. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

14. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

15. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

16. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

599-604

17. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

18. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

19. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

20. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Superhydrophobic SAM Modified Electrodes for

Enhanced Current Limiting Properties in Intrinsic Conducting Polymer Surge Protection Devices. Langmuir. 2015;31(22):6253-6264

21. Othman R, Hossain M, &Jabarullah N. Synthesis and characterization of iron‐and nitrogen‐functionalized graphene catalysts for oxygen

reduction reaction. Applied Organo. Chem. 2017;31(10):e3738

22. Gas Engine Turbine Section. Wijerathne C. Available on http://okigihan.blogspot.my/p/compressor-section-compressor-section.html

accessed on 01/02/2018

105.

Authors: Abdul Ghani Abdul Samad, Adi Harith Mohd Tahir

Paper Title: Bird Strikes and Preventive Methods used at Malaysian Airport

Abstract: The main objective of this project is to determine the cause and effect of bird attack and the most

effective way to prevent this bird attack. In general, birds are very dangerous to the aircraft because when birds

attack the parts of the aircraft, especially the engine parts of the aircraft, it will damage the aircraft system in small

or large. According to the International Civil Aviation Organization (ICAO) report, the number of bird attack

accidents increased from 2010 to 2017. The project is to track and identify the best way to prevent and reduce the

number of bird attacks. These projects are primarily to implement theory over the Bachelor's time and are based on

reports of flight safety authorities. Among the relevant subjects are human factors, aircraft structure maintenance,

piston engines and aviation law are among the subjects we use in conducting this project. Collecting reports from

flight authorities and data from aviation industry workers will be implemented in this project. The end result is to

find ways to effectively prevent and reduce the number of bird attacks.

Keywords: Bird strike, Malaysian Airport, Preventive methods.

References: 1. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

2. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

3. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

4. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

5. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

6. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

7. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

8. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

9. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

10. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

11. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

12. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

13. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

14. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

15. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

16. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

17. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030.

605-608

106.

Authors: Muhd Zulfadhli Muhd Zaimi, Muhammad Asyraaf Zulkifli

Paper Title: Analysis on the Aerodynamic Efficiency of Modified Blended Wingtip

Abstract: As aircrafts fly, a lot of lift needed to ensure maximum thrust can be generated. However, as lift

increase, induced drag also will increase. One of the problems due to drag usually happen at the wingtip. Vortices

will be formed at the wingtip and create pressure above the wing. Therefore, reduce lift. In order to overcome this

problem, various wingtip shapes are being applied at the wingtip. The purpose of this analysis is to analyse the

aerodynamic efficiency of modified blended wingtip. This analysis consists of blended wingtip and modification

of the wingtip itself based on different speed and angle of attack. From this analysis, the lift and drag ratio from the

609-612

coefficient of lift and drag obtained for the blended wingtip and all the design will be compared and therefore,

analyse the efficiency of the applied modification. The analysis involving wing of NACA 4415 with four different

types of wingtip; the original blended wingtip, modification 1 with 15° plane added, modification 2 with 30° plane

added and modification 3 with 45° plane added, four different speed and so do four different angle of attack

(AOA). All of these designs will be analysed by using Computational Fluid Dynamic (CFD) software. From the

analysis, the efficiency can be determined by comparing the lift and drag ratio. The result from the analysis has

been proved that modification of blended wingtip with 45° plane added has the highest lift and drag coefficient that

is 2.16 X 10-1 at highest angle of attack at 30 m/s compared to blended wingtip and design modification of

blended wingtip with 15° and 30° added plane.

Keywords: Blended Wingtip, aircraft, Lift and drag ratio.

References: 1. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

2. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

3. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

4. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

5. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

6. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

7. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

8. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

Appli. Journ. 2014;3(3):163-168

9. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

10. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

11. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

12. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

13. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

14. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

15. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

16. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

17. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

107.

Authors: Muhd Zulfadhli Muhd Zaimi, Imran AsyrafRosdi, YusriDahdi

Paper Title: Tensile Test on Sisal/Fibre Glass Reinforced Epoxy-based Hybrid Composites

Abstract: The progress of usual fiber underpinned composite produces to substitute engineering resources is

coil out to be a movement in engineering application. The target of this study is to examine whether sisal fibers can

be crafted into composite physical that next can be substitute synthetic fibers support composites that are

expensive. In this discover, sisal fiber will be made into composite panels by employing the hand lay-up technique.

The composite panels are next assessed for their mechanical properties.

Keywords: Tensile Test, sisal fiberglass panel, reinforced composites.

References: 1. Bardai A., Er A, Johari M, &Mohd Noor A. A review of Kuala Lumpur International Airport (KLIA) as a competitive South-East Asia

hub. Proceedings of an international conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012039

2. Omar S, Johari M, & Abdul Samad A.Assessment on risk management of helicopter services for offshore installations. Int. Jour. of

Engine. & Tech. 2018;7(4.13):229-231

3. Jabarullah N, Verrelli E, Mauldin C, Navarro L, Golden J, Madianos L & Kemp N. Novel conducting polymer current limiting devices for

low cost surge protection applications. Jour of Applied Phys. 2014;116(16):164501

4. Johari M, Jalil M, &Mohd Shariff M.Comparison of horizontal axis wind turbine (HAWT) and vertical axis wind turbine (VAWT). Int.

Jour. of Engine. & Tech. 2018;7(4.13):74-80

5. Zainal Ariffin M, JohariM, & Ibrahim H.The needs of aircraft avionics' radio line replaceable unit repair center at UniKL MIAT. Int. Jour.

of Engine. & Tech. 2018;7(4.13):86-88

6. Ishak F, Johari M, &Dolah R.A case study of LEAN application for shortest lead time in composite repair shop. Int. Jour. of Engine. &

Tech. 2018;7(4.13):112-119

7. Ya'acob A, Mohd Razali M, Anwar U, Mohd Radhi M, Ishak M, Minhat M, Mohd Aris K, Johari M,Teh C.Investigation of closed

compartment moulding for pull-winding process. Int. Jour. of Engine. & Tech. 2018;7(4.13):107-111.

8. Amzar M, Fard M, & Azari M. Characterization of the effects of vibration on seated driver alertness. Nonlinear Engine. - Model. and

613-616

Appli. Journ. 2014;3(3):163-168

9. Jabarullah N, Mauldin C, Navarro L, Golden J, Madianos L, & Kemp N. Modelling and Simulation Analysis for the Prediction of the

Performance of Intrinsic Conducting Polymer Current Limiting Device. Adv. Sci. Letters. 2017;23(6):5117-5120

10. Abdul Samad A, Johari M, &Omar S. Preventing human error at an approved training organization using Dirty Dozen. Int. Jour. of

Engine. & Tech. 2018;7(4.13):71-73

11. Johari M, & Jamil N.Personal problems and English teachers: Are they always bad?. Int. Jour. of Applied Ling. And English Lit.

2014;3(1):163-169

12. Jabarullah N, Verrelli E, Gee A, Mauldin C, Navarro L, Golden J, & Kemp N. Large dopant dependence of the current limiting properties

of intrinsic conducting polymer surge protection devices. RSC Advances. 2016;89:85710-85717

13. Amzar M, Fard M, Azari M, Benediktsdttir B, Arnardttir E, Jazar R, & Maeda S. Influence of vibration on seated occupant drowsiness.

Indust. Health Jour. 2016;54(4) :296-307

14. Amzar M, Fard M, Azari M, &Jazar R. Influence of vibration on seated occupant drowsiness measured in simulated driving. Appl. Ergo.

Jour. 2017;60:348-355

15. Amzar M &Padil H. Lane keeping performances subjected to whole-body vibrations. Int. Jour. of Engine. & Tech. 2018;7(4.13):1-4

16. Khairuddin M, Yahya M, & Johari M. Critical needs for piston engine overhaul centre in Malaysia. Proceedings of an international

conference. Putrajaya, 12 December 2017. IOP Publ. Ltd. 2017;270:012013

17. Ya'acob, A, Razali D, Anwar U, Radhi A, Ishak A, Minhat M, Mohd Aris K, Johari M, &Teh C. Preliminary Study on GF/Carbon/Epoxy

Composite Permeability in Designing Close Compartment Processing. Proceedings of an international conference. Pulau Pinang, 21-22

November 2017. IOP Publ. Ltd. 2017;370:012030

108.

Authors: Ranjithkumar S, R Mahesh

Paper Title: A Pragmatic Esplanade to Potential Investor

Abstract: Supply and demand statistics determine the usage and value of investment. Crypto currency, the

recent techno-inclusion into financial industry, provides the best means of exchange in the form of money card in

order to carry large amount of transactions with easy and affordable cost. We find the possibilities of investment to

determine the higher return which attracts potential investors prefer to include the crypto currency in the portfolio.

A relationship between crypto currency and equity is measured by using canonical correlation with the help of

cutting score and group centroids.

Keywords: Crypto currency, Gross Domestic Product, Investment, Potential investor.

References: 1. Richard E. Smith (1997). Internet Cryptography. US Boston: Addison - Wesley Pub Co ISBN: 0201924803.

2. William R. Cheswick, Steven M. Bellovin, and Aviel D. Rubin (2003).Firewalls and Internet Security: Repelling the Wily Hacker. US

Boston: Addison-Wesley Pub Co; ISBN: 0201633574.

3. Bruce Schneier(1996). Applied Cryptography, Second Edition: Protocols, Algorthms, and Source Code in C (cloth). United States: John

Wiley & Sons. ISBN: 0471128457

4. S.P.Gupta (Eds) (2010). Statistical Methods. New Delhi: Sultan Chand & Sons. ISBN 978-81-8054-739-3

5. Alfred J. Menezes, Paul C. van Oorschot and Scott A. Vanstone (Eds), (2001). Handbook of Applied Cryptography.United States: CRC

Press. ISBN: 0849385237.

6. Rainer Bhome and Nicolas Christen (2015). Bitcoin: Economics, Technology and Governance. Journal of Economic Perspectives Volume

29, Number 2 spring 2015Pages 213–238.

7. Kim YB, Kim JG, Kim W, Im JH, Kim TH, Kang SJ, et al. (2016). Predicting Fluctuations in Cryptocurrency Transactions Based on

User Comments and Replies. PLoS ONE 11(8): e0161197. doi.org/10.1371/journal.pone.0161197

8. Polasik, Michal and Piotrowska, Anna and Wisniewski, Tomasz Piotr, et al. Price Fluctuations and the Use of Bitcoin: An Empirical

Inquiry (October 30, 2014). International Journal of Electronic Commerce 20(1), pp. 9-49, 2015.

9. ElBahrawy A, Alessandretti L, Kandler A, Pastor-Satorras R, Baronchelli A (2017). Evolutionary dynamics of the cryptocurrency

market. R. Soc. open sci. 4: 170623. doi.org/10.1098/rsos.170623

10. Hileman, Garrick and Rauchs, Michel, (2017) Global Blockchain Benchmarking Study (September 22, 2017).

SSRN. doi.org/10.2139/ssrn.3040224

11. KuoChuen, David Lee and Guo, Li and Wang, Yu,(2017). Cryptocurrency: A New Investment Opportunity?

SSRN. doi.org/10.2139/ssrn.2994097

12. Zhengyao Jiang and Jinjun Liang (2017). Cryptocurrency Portfolio management with Deep Reinforcement Learning. ResearchGate

Conference Paper September 2017 DOI: 10.1109/IntelliSys.2017.8324237

13. Chohan, Usman (2017). The Cryptocurrency Tumblers: Risks, Legality and Oversight. Discussion Paper Series: Notes on the 21st

Century. SSRN. doi.org/10.2139/ssrn.3080361

14. Ravi kumar (2018). Stand up India programme – an address to financial problems of micro and small scale manufacturing and production

units. International Journal of Mechanical and Production Engineering Research and Development ISSN (P): 2249-6890; ISSN (E):

2249-8001 Vol. 8, Issue 1, Feb 2018, 1271-1278

15. Lee, J. (2009, April 30). Aristotle and the Definition of Money. The Market Oracle. Retrieved from

http://www.marketoracle.co.uk/Article10370.html

16. https://coin.dance/volume/localbitcoins

17. https://coinmap.org

18. https:// bitnodes.21.co

617-621

109.

Authors: R.Subhashini, J.K.Jeevitha, B. Keerthi Samhitha

Paper Title: A Pragmatic Esplanade to Potential Investor

Abstract: Water is one of the most used natural resources. Increase in content of harmful chemicals is one of

the main reasons which will affect quality of water. Continuous monitoring and early forecasting can help us in

maintaining quality of water. Data mining is one of the most efficient techniques that can effectively perform this

operation. It is the process to discover interesting information from even large amounts of data. In this paper we

are going to make use of R tool to perform data mining for water samples.

Keywords: Multiple linear regression; Randomforest; RegressionTree; Model evaluation.

622-626

References: 1. Brian ALAN Whitton, Martyn Kelly (1995) Use of algae and other plants for monitoring rivers.

2. Tochukwu K. Anyachebelu, Marc Conrad, TahminaAjmal (2014)Modelling and prediction of Surface Water Contamination using On-line

Sensor Data.

3. Package ‘DMwR’ –CRAN

4. Beach Water Quality – Automated Sensors (2015) http://catalog.data.gov/dataset/beach-water-quality-automated-sensors-66a4b

5. Vipin KumarData Mining with R Learing with Case Studies

110.

Authors: R.Sethuraman, T.Sasipraba

Paper Title: Cloud Based Predictive Data Analysis Framework for Wearable Device Health Alert System using

Semantic Web Services

Abstract: Rapid Innovation in Digital Technology achieved its frontier with fitness wearable technological

devices. The ubiquitous tracking devices currently available in the market only monitor the amount of calories

burnt by the user. They do not predict nor encourage users. This paper intends to provide prediction of calories

burn based on users' physical activities, and encourage them to achieve more of their fitness goals, with the help of

machine learning algorithms and ontology. The proposed framework has two different ontologies used for

semantic synchronization. Fitness activities ontology deals with the predicted calories burn value and cloud

Telephony ontology provides multi-channel alert services to the end user. FitBit Wearable fitness devices user data

are analyzed from the cloud storage via cloud API, is proposed to interact with the user continuously with calories

burn value for the improvement of their physical Activities like walking, jogging and step count. A custom model

is constructed for predicting the calories burn value using Linear Regression Analysis through Machine Learning

Algorithm. The proposed novel framework interacts with semantic web service registry through OWL API with

the obtained predicted calories burn value from the prediction models. When compared to the existing system, the

proposed framework produces enhanced insights on amount of calories burn to the user based on their activities

through cloud telephony alerts like SMS, IVR, Mobile App and Email. The end user improves their activities from

the obtained predicted value insights.

Keywords: wearable technological device, ontology, fitness activity, ondemand cloud telephony, web service

registry, OWL API.

References: 1. Judit Takacs, Courtney L. Pollock, Jerrad R. Guenther, Mohammadreza Bahar, Christopher Napier, Michael A. Hunt “Validation of the

Fitbit One activity monitor device during treadmill walking.” J Sci Med Sp.DOI:http://dx.doi.org/10.1016/j.jsams.2013.10.241

2. Keith M. Diaz,1 David J. Krupka,1 Melinda J Chang,1 James Peacock,1 Yao Ma,2 Jeff Goldsmith,2 Joseph E. Schwartz, and Karina W.

Davidson An accurate and reliable device for wireless physical activity tracking. Int J Cardiol. DOI : 10.1016/j.ijcard.2015.03.038

3. Lisa A. Cadmus-Bertram, Bess H. Marcus, Ruth E. Patterson, Barbara A. Parker, Brittany L. Morey Randomized Trial of a Fitbit-Based

Physical Activity Intervention for Women Am J Prev Med DOI: 10.1016/j.amepre.2015.01.020

4. Jeffer Eidi Sasaki , Amanda Hickey , Marianna Mavilia , Jacquelynne Tedesco , Dinesh John, Sarah Kozey Keadle , Patty S. Freedson

Validation of the Fitbit Wireless Activity Tracker for Prediction of Energy Expenditure J phys. Activity Health DOI:

http://dx.doi.org/10.1123/jpah.2012-0495

5. Slootmaker SM, Schuit AJ, Chinapaw MJ, Seidell JC, van Mechelen W. Disagreement in physical activity assessed by accelerometer and

selfreport in subgroups of age, gender, education and weight status. Int J Behav Nutr Phys Act. DOI: 10.1186/1479-5868-6-17

6. Comparison of FitBit® Ultra to ActiGraph™ GT1M for Assessment of Physical Activity in Young Adults During Treadmill Walking

R.J. Gusmer, T.A. Bosch, A.N. Watkins, J.D. Ostrem, D.R. Dengel Open Sp. Med. J DOI: 10.2174/1874387001408010011

7. M. Shamim Hossain and Ghulam Muhammad Cloud-Based Collaborative Media Service Framework for HealthCare Int. J Distrib. Sens.

Netw. DOI: http://dx.doi.org/10.1155/2014/858712

8. Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining (2015 5th Edition) Introduction to Linear Regression Analysis.

9. Vinh Bui, Weiping Zhu, Antonio Pescape Long Horizon End-to-End Delay Forecasts: A Multi-Step-Ahead Hybrid Approach. 2007 12th

IEEE Symposium on Computers and Communications.DOI: 10.1109/ISCC.2007.4381513

10. K. Salamatian and S. Vat On. Hidden markov modeling for network communication channels. In Proc. ACM SIGMETRICS 2001, pages

92-101, USA

11. Kanitthika Kaewkannate and Soochan KimEmail A comparison of wearable fitness devices BMC Public HealthBMC series – open,

inclusive and trusted201616:433.https://doi.org/10.1186/s12889-016-3059-0

12. Harish, P., Subhashini, R., Priya, K Intruder detection by extracting semantic content from surveillance videos 2014 Proceeding of the

IEEE International Conference on Green Computing, Communication and Electrical Engineering, ICGCCEE 2014

13. Fitbit Fitness Wearable Device Experimental Dataset from zenedo.org https://zenodo.org/record/14996#.WfxTJFuCzZ4.

627-631

111.

Authors: B. Suhasini, Santhosh Kumar N

Paper Title: A Study on Factors influencing International Students Online Compulsive Behaviour

Abstract: In the international market of Higher education India has its paved a way for many students to access

higher education due to various factors such as; cost of living is very less comparing to European countries, safe

and secured environment. The present study examines the stress driven compulsive online spending among the

inbound international students. In online shopping compulsive buyers have high levels of both positive and

negative impacts. The existing research in the area of compulsive spending shows that most of the time it affects

the buyers that may lead to serious problems that includes of health issues.

Keywords: Higher Education, Compulsive Online Spending.

References: 1. Black, D. W. (2007). A review of compulsive buying disorder. World Psychiatry, 6(1), 14–18.

632-638

2. Qamar, F. & Bhalla, V. (2017). Internationalization of Higher Education in India. Annual Survey Of International Students In India.

http://www.aiu.ac.in/International/AIU_International_Students_2017%20(2).pdf

3. Deloitte CII. (2014). Annual Status of Higher Education of States and UTs in India, 2014. New Delhi: Deloitte CII

4. Roberts, J. A., & Jones, E. (2001). Money attitudes, credit card use, and compulsive buying among American college students. Journal of

Consumer Affairs, 35(2), 213–240. http://dx.doi.org/10.1111/j.1745-6606.2001.tb00111.x

5. Ministry of HRD. (2015). All India Survey on Higher Education (2014-15). New Delhi: Govt.of India.

6. Ministry of HRD. (2016). All India Survey on Higher Education (2015-16). New Delhi: Govt. of India.

Mohanraj, P. (2017). Consumers’ Compulsive Buying Behaviour – An Empirical Study. Great Lakes Herald, Volume 11 Issue No 1.

https://www.greatlakes.edu.in/herald/pdfs/march-2017/article-1.pdf

7. Vaidya, A. (2017). Online shopping trends among college students. https://www.researchgate.net/publication/320056505

8. Vesterby, T., & Chabert, M. (2001). E-Marketing. Viby J, Jyllands - Posten Erhvervsbogklubb.

9. Vrechopoulos, A.P. Siomkos, G.f and Doukindis, G.I. (2001) ‘Internet shopping adoption by Greek consumers’, European Journal of

Innovation Management, Vol. 4, No. 3, pp.142-152.

10. McElroy, S, Phillips, K, Keck, P., 1994. Obsessive Compulsive Spectrum Disorder, Journal of Clinical Psychiatry, 55, 33-53.

11. Yüksel, C. A., & Eroğlu, F. (2015). The effects of personal factors and attitudes towards advertising on compulsive buying tendency.

Pazarlama ve Pazarlama Araştırmaları Dergisi, 16, 43–70

12. Millan E. S., Howard E. (2007). Shopping for pleasure? Shopping experiences of Hungarian consumers. International Journal of Retail &

Distribution Management. 35(6):474–487.

112.

Authors: K.Sakthivel, V.Jayalakshmi

Paper Title: Hybrid Renewable Power Generation Scheme for Grid Integration

Abstract: In this research work, a novel grid reconciliation scheme for a hybrid electric power generation plot

utilizing PV power generation and Synchronous generator based breeze (wind) power generation is proposed here.

In this proposed work, MPPT is obtained and tracked with the help of Fuzzy Logic Controller for Wind turbine

and P&O methodology for photovoltaic systems. The wind power and the photo voltaic source are conveyed to a

CUK DC converter connect and a DC to AC three stage Multilevel inverter (13 Level) is utilized to transfer

control into the framework(grid) and a novel control scheme is taken for sinusoidal current infusion at the grid

integration.

Keywords: Power Generation, DC-DC converter, multilevel inverter.

References: 1. S. Prakash&S.P.Vijayaragavan, “Design and Optimization of High Efficient Charge Controller for a Solar Photovoltaic System Power

Generation”, International Journal of Pure and Applied Mathematics, Volume 119 No. 12 2018, 4057-4065.

2. S. Prakash &V.Jayalakshmi, “Hybrid Solar-Wind Energy System with Mppt Using Cuk- Sepic Fused Converter”, International Journal of

Pure and Applied Mathematics, Volume 119 No. 12 2018, 6851-6859.

3. S. Prakash &K.Sakthivel, “APWM Based Multiple Output ZVS DC/DC Converter”, International Journal of Pure and Applied

Mathematics, Volume 119 No. 12 2018, 7665-7671.

4. S. Prakash &K.Sakthivel, “Battery Energy Storage System for A Stand Alone Windmill -Based On State Of-Charge (SOC) Balancing

Control”, International Journal of Pure and Applied Mathematics, Volume 119 No. 12 2018, 7691-7700.

5. S. Prakash & K.Sakthivel, “Efficient Transformer less Mosfet Inverter For Grid-Tied Photovoltaic System”, International Journal of

Pure and Applied Mathematics, Volume 119 No. 12 2018, 7787-7796.

639-643

113.

Authors: G.Santhana Lakshmi, D.Senthil

Paper Title: Drivers Behavior and Performance of State Transport Corporation in Villupuram Division at

Tamilnadu

Abstract: Purpose: The paper attempts to elaborate the drivers behavior and performance of state transport

corporation in villupuram division at Tamilnadu, India. Method: Descriptive research method is suited to explore

questions regarding the drivers behavior and performance. There are 11 depots in the Villupuram division. In these

depots, there are 1758 drivers are working at presently. The researcher has applied random sample method to

collect the questionnaire. The researcher has completed 368 sample respondents based on the formula. Further,

descriptive statistics, Pearson correlation and multiple regression tools are applied. Finding: It is found that the

electronic devise and any odds ratio use of distraction activities are positively influenced on drivers behaviour. In

other hand, it is found that the performance deficits and aggressive behavior are positively influenced the job

performance. But, caution behavior is negatively impact on job performance. Conclusion: In Indian Drivers are

working more than 8 hours per day. Hence, the drivers holding regular meetings will maintain the safety and also

preserving their relative autonomy. Implication: From the study 70 percentage of collision are occurred based on

vehicles repair and lack of working condition. Hence, the depot management should be maintain the vehicles and

solve drivers grievance.

Keywords: Drivers Behaviour, Distraction, Job Performance and Villupuram Division.

References: 1. Adriana Faria, Ana Rita Matos, Vânia Rocha,Lucinda Rodrigues, Ana Araújo, Patrícia Magalhães, Davide Barroso, Catarina Samorinha,

José Precioso (2017) Traffic risk behaviour: an observational study of drivers’ behaviour in Braga (Portugal). Journal of Gac Sanit.

https://doi.org/10.1016/j.gaceta.2017.10.012

2. Amanda N. Stephens and Keis Ohtsuka (2014) Cognitive biases in aggressive drivers: Does illusion of control drive us off the road?

Personality and Individual Differences 68: 124–129

3. Ashish Vermaa, Neelima Chakrabarty, Velmuruganc, Prithvi Bhat Bd, Dinesh Kumar (2017) Sensation Seeking Behavior and Crash

Involvement of Indian Bus Drivers. Transportation Research Procedia 25: 4750–4762

4. Benekohal, R. F., Micheals, M.R., Resende, V.T.P., Shim, E., (1994) Highway Design and Traffic Operation Needs of Older Drivers,

presented at the 73rd Annual Meeting of Transportation Research Board, Washington, D. C., January 9-13.

644-650

5. Bifulco G.N, Galante, F, Pariota L, Russo Spena M, Del Gais, (2014) Data Collection for Traffic and Drivers’ Behaviour Studies: a large-

scale survey. Procedia - Social and Behavioral Sciences 111: 721 – 730

6. Bishu, R., Tarawneh, M., McCoy, T.P., and Foster, B., A (1992) Predictive Model for Elderly Drivers, presented at the 71st Annual

Meeting of Transportation Research Board, Washington, D. C., January 12-16.

7. Charlton, 2009 driving while conversing: cell phones that distract and passengers who react. Accident analysis and prevention 38: 496-

506.

8. Chen, baker, braver and Li (2000) carrying passengers as risk factors for crashes fatal to 16 to 17 years old drivers. JAMA 283: 1578-

1582.

9. Doherty Andey and mac Gregor (1998) The situational risk od young drivers the influence of passengers, time of Dy and day of week on

accident rate. Accident analysis and prevention 30 (1): 45-52.

10. Drews, F.A., Yazdani, H., Godfrey, C.N., Cooper, J.M. & Strayer, D.L. (2009) Text messaging during simulated driving, Human Factors,

51, 762–70.

11. Emma Tivesten and Marco Dozza (2015) Driving context influences drivers' decision to engage in visual–manual phone tasks: Evidence

from a naturalistic driving study. Journal of Safety Research 53: 87–96

12. Faria Adriana, Ana Rita Matos, Vânia Rocha,Lucinda Rodrigues, Ana Araújo, Patrícia Magalhães,Davide Barroso, Catarina Samorinha,

José Precioso (2017) Traffic risk behaviour: an observational study of drivers’ behaviour in Braga (Portugal). Journal of Gac Sanit..

https://doi.org/10.1016/j.gaceta.2017.10.012

13. Fildes, G. Rumbold and A. Leening 1991 Speed Behaviour and Drivers’ Attitude to Speeding. Report by Accident Research Centre

14. Francesco Bella (2014) Effects of combined curves on driver’s speed behavior: driving simulator study Transportation Research Procedia

3: 100 – 108

15. Gregersen and bjurulf (1996) young novice drivers: towards a model of their accident involvement. Acid anal prev 28 (2): 229-41.

16. Haigney, D.E., Taylor, R.G., & Westerman, S.J. (2000). Concurrent mobile (cellular) phone use and driving performance: task demand

characteristics and compensatory processes. Transportation Research, Part F (3): 113-121.

17. Hakamies-Blomqvist (1996) Research on Older Drivers: A Review. “IATSS Research 20 (1): 91-101.

18. Harrison (2011) College student orevalence and perception of text messaging while driving. Accident analysis and prevention 43: 1516-

1520.

19. Hashimoto, S. Kato, S. Tsugawa (2009) A Cooperative Assistance System Between Vehicles For Elderly Drivers. Iatss Research 33 (1).

20. Jafarpour and Rahimi-Movaghar (2014) Determinants of risky driving behaviour: a narrative review. Med J Islam Repub Iran. 28 142.

21. Jonck, J., 2010, ‘What are the effects of fatigue on driving?’, Arrive Alive Road Safety Blog, viewed 19 February 2013,

from http://roadsafety.co.za/2010-10/what-are-the-effects-of-fatigue-on-driving/

22. Joshua D. Clappa, Shira A. Olsenb, J. Gayle Beckb, Sarah A. Palyoa, DeMond M. Granta, Berglind Gudmundsdottira,and Luana Marques

(2011) Driving Behavior Survey: Scale construction and validation. Journal of Anxiety Disorders 25: 96–105

23. Kircher, A., Vogel, K., Törnros, J., Bolling, A., Nilsson, L., Patten, C., Malmström, T. & Ceco, C. (2004) Mobile telephone simulator

study, report no. 969A, Swedish National Road and Transport Research Institute, Linköping, Sweden.

24. Marta V. Faria, Patrícia C. Baptista and Tiago L. Farias (2017) Identifying driving behavior patterns and their impacts on fuel use.

Transportation Research Procedia 27. 953–960

25. Matthews, R., Legg, S., & Charlton, S. (2003). The effect of cell phone type on drivers’ subjective workload during concurrent driving

and conversing. Accident Analysis and Prevention 35: 441-450.

26. Matúš Šucha and Dana cernochova (2016) Driver personality as a valid predictor of risky driving. Transportation Research Procedia 14:

4286 – 4295

27. Mayou Bryant (2002) outcome 3 years after a road traffic accident. Psychological medicine, 32: 671-675.

28. McCoy, T.P. (1991) Strategies for Improving the Safety of Elderly Drivers, ITE 1991 Compendium of Technical Papers.

29. McEvoy, S., Stevenson, M., McCartt, A., Woodward, M., Haworth, C., Palamara, P., & Cercarelli, R. (2005) Role of mobile phone in

motor vehicle crashes resulting in hospital attendance: a case-crossover study, British Medical Journal, 331, 428–430.

30. McKnight, A., & McKnight, A. (2003) Young novice drivers: careless or clueless? Accident Analysis & Prevention, 35, 921–925.

31. McShane, W. R. and Roess, R. P., (1991) Traffic Engineering, Prentice-Hall Inc., Polytechnic Series in Transportation, Englewood Cliffs,

New Jersey, (1991).

32. Michalik, C., (1996) Development and Evaluation of Measures to Reduce the Accident Risk of Elderly Road Users, “IATSS Research”,

Vol. 20, No. 1, pp. 83-90.

33. Mullapudi, S. and Lu, J. J., (1998) Capacity Reductions due to Older Drivers at Intersections, Research Report, Department of Civil and

Environmental Engineering, University of South Florida, Tampa, Florida.

34. Neale, et al., (2005) an overview of the 100-car naturalistic study and finding. Proceedings of the 19th international technic conference on

enhanced safety of vehicles ESV. 6-9 june 2005. Washington D C.

35. Neelima Chakrabarty, Kamini Gupta & Ankit Bhatnagar (2013) A Survey on Awareness of Traffic Safety among Drivers in Delhi, India.

The SIJ Transactions on Industrial, Financial & Business Management (IFBM), Vol. 1, No. 2, May-June 2013

36. Nick Owena,b,, Horace Kinga, Matthew Lamb (2015) Literature review of race driver fatigue measurement in endurance Motorsport.

Procedia Engineering 112 ( 2015 ) 344 – 348

37. Redelmeier, D.A., & Tibshirani, R.J. (1997). Association between Cellular Telephone Calls and Motor Vehicle Collisions. The New

England Journal of Medicine, 336(7), 453-458

38. Regan, Hallett and Gordon (2011) drivers distraction and driver inattention: definition, relationship and taxonomy, accident analysis and

prevention 43 1771-1781

39. Robert D. Foss, and Arthur H. Goodwin (2014) Distracted Driver Behaviors and Distracting Conditions among Adolescent Drivers:

Findings from a Naturalistic Driving Study. Journal of Adolescent Health 54, 50 to 60

40. Rosenblooma Yuval Hadasa, Avi Tillmana,Tova, Riccardo Rossi and Massimiliano Gastaldi (2016) Drivers' Attitude Towards Caffeine

Chewing Gum As Countermeasure To Driver Task-Related Fatigue. Transportation Research Procedia 00 (2016) 000–000

41. Satoshi Hyodo, Tohio Yoshii, Matstushita Satoshi and Shirayanagi Hirotoshi ( 2016 ) An analysis of the impact of driving time on the

driver’s behavior using probe car data Transportation Research Procedia 21.

42. Shinar, D. (1998). Aggressive driving: The contribution of the drivers and the situation. Transportation Research Part F, 1, 137-160.

43. Strayer, D.L., & Johnston, W.A. (2001). Driven to distraction: Dual-task studies of simulated driving and conversing on a cellular

telephone. Psychological Science, 12, 462-466.

44. Strickland, G.S. and Nowakowski J.V (1989) The Older Driver: A Growing Concern in Roadway Design and Operations, ITE 1989

Compendium of Technical Papers.

45. Suk, C.J., 2012, Consequences of failing to use turn signals, viewed 26 February 2013,

from http://rochester.legalexaminer.com/automobile-accidents/consequences-of-failing-to-use-turn-signals.aspx?googleid=300618

46. Susanne Kaiser and Gerald Furiana, Christopher Schlembacha (2016) Aggressive behaviour in road traffic – findings from Austria.

Transportation Research Procedia 14 (2016) 4384 – 4392

47. Troup, (1978) drivers back pain and its prevention: a review of the postural, vibratory and muscular factors, together with the problem of

transmitted road-shock. Applied ergonomics 9 (4): 207-214.

48. Tyre Savings, 2013, Tyre wear, viewed 23 February 2013, from http://www.tyresavings.com/articles/safe-driving/looking-after-your-

tyres/tyre-wear

49. Violanti and Marshall, (1996) Cellular phones and traffic accident: an epidemiological approach. Accident Analysis and Prevention 28,

265-270.

50. Violanti. J. (1998) Cellular phones and fatal traffic collisions. Accident Analysis and Prevention 30, 519-524

51. Weinard, M., (1996) Safety Measures for Elderly Drivers: the Situation in Germany, “IATSS Research”, Vol. 20, No. 1. pp. 67-74.

52. West, elander and French (1992) decision making, personality and driving style as correlates of individual accident risk. Transport

research laboratory report number CR 390, crowthorne: Transport research laboratory.

53. Williams (2003) teenage drivers: pattern of risk. Journal of sat. research 34 5-15.

54. Wundersitz, L. (2012). An analysis of young drivers involved in crashes using in-depth crash investigation data. Report No. CASR101).

Centre for Automotive Safety Research, Adelaide, Australia.

55. Ying CHEN (2013) Stress State of Driver: Mobile Phone Use While Driving. Procedia - Social and Behavioral Sciences 96; 12 – 16.

56. Zhao Jianyou et al. (2013) Procedia - Social and Behavioral Sciences 96: 2173 – 2178 2177.

114.

Authors: Harish R, Karthick R

Paper Title: Optimized Design and Control of a Stand-Alone Hybrid Power System using Modified Cuckoo Search

Algorithm

Abstract: This paper presents the optimized design and control of a stand-the only hybrid power system with

power management function using a modified search algorithm for cuckoo. The hybrid system comprising PV,

Wind, Battery and Fuel Cell is connected to a common DC bus from which the load is supplied with a DC-AC

converter. The two main sources namely wind and PV are embedded with MPPT controller to obtain optimum

output. The battery which supplies the load during reduced PV output and fuel cell with electrolyzer is considered

as an additional support of power to the DC bus. In addition, for power management in the hybrid system, the

modified cuckoo search algorithm is proposed to improve the DC bus voltage and supervise the power sharing

between loads and different sources. The results obtained are compared to the conventional controller to

demonstrate the efficiency of the soft computing approach proposed. The whole system is constructed using the

MATLAB Simulink environment and the results of the simulation are presented to validate the proposed method.

Keywords: Hybrid Power system (HPS), Modified Cuckoo search Algorithm, Maximum Power Point

Tracking (MPPT), Wind Turbine (WT), Fuel Cell, Electrolyzer.

References: 1. Bouthaina Madaci , Rachid Chenni , Erol Kurt , Kamel Eddine Hemsas , “Design And Control of a Stand-alone Hybrid Power System,”

International Journal of Hydrogen Energy, vol.41, No.29, pp.12485-12496, 2016.

2. R.Karthick, S.Manoharan. “Fuzzy based optimised energy management strategy of renewable energy sources for stand – alone

applications”, Journal of Electrical Engineering, Vol.17, No.1, pp.418-426, 2017.

3. Valenciaga F, Evangelista CA., “Control design for an autonomous wind-based hydrogen production system”, Int Journal of Hydrogen

Energy, vol.35, no.11, pp.5799-5807, 2010

4. Malla SG, Bhende CN. “Voltage control of stand-alone wind and solar energy system”, Int J Electr Power Energy Systems, Vol.56,

pp.361-393, 2014.

5. M. H. Nehrir, C. Wang, K. Strunz, H. Aki, R. Ramakumar, J. Bing, Z. Miao, and Z. Salameh.: A Review of Hybrid

Renewable/Alternative Energy Systems for Electric Power Generation: Configurations, Control, and Applications. In: IEEE transactions

on sustainable energy, vol. 2(2011), no. 4, October 2011, p.392-403.

6. T. Logeswaran,A. Senthilkumar, P. Karuppusamy, “Adaptive Neuro-Fuzzy Model for Grid-Connected Photovoltaic System,”

International Journal of Fuzzy Systems, Vol.17, No.4, pp.585-594, 2015.

7. Villavla MG, Gazoli JR, Filho ER. “Comprehensive approach to modeling and simulation of photovoltaic arrays”. IEEE Tran Power

Electron, vol.24, no.5, pp.1198-1208, 2009.

8. S. Ozdemir, N. Altin, I. Sefa, G. Bal “PV Supplied Single Stage MPPT Inverter for Induction Motor Actuated Ventilation Systems,”

Elektronika ir elektrotechnika, vol. 20, no. 5, pp.1392-1215, 2014.

9. Arteaga Orozco MI, V_azquez JR, Salmer_on P, P_erez A., “A sliding maximum power point tracker for a photovoltaic system”, 11th

Spanish Portuguese Congress on Electrical Engineering, July 2009.

10. Y. Uzun, S. Demirbas, E. Kurt, “Implementation of a New Contactless Piezoelectric Wind Energy Harvester to a Wireless Weather

Station”, Elektronika ir elektrotechnika, vol. 20, no. 10, pp.1392-1215, 2014.

11. Datta A, Bhattacharya G, Mukherjee D, Saha H, “An efficient technique for controlling power flow in a single stage grid connected

photovoltaic system”, International Journal of Science and Technology, vol.21, no.3, pp.885-897, 2014.

12. Bendib B, Krim F, Belmili H, Almi MF, Boulouma S. Advanced fuzzy MPPT controller for a stand-alone PV system, Energy Procedia,

Vol.50, pp.383-392, 2014.

13. Zainuri MAAM, Radzi MAM, Soh AC, Rahim NA, “Development of adaptive perturb and observe-fuzzy control maximum power point

tracking for photovoltaic boost dc-dc converter”, IET Renew Power Generation, Vol.8, No.2, pp.183-194, 2014.

14. Hiroshi N, Tatsuya N, Hiroshi M, Takenobu K. “Development of 100-W high-efficiency MPPT power conditioner and evaluation of TEG

system with battery load. Journal of Electronic Materials, vol.40, no.5, pp.657-661, 2011.

15. Nordin AHM, Omar AM., “Modeling and simulation of photovoltaic (PV) array and maximum power point tracker (MPPT) for grid-

connected PV system”. In: 3rd Int. Symp. Exhibition in Sustainable Energy & Environment, Melaka, Malaysia, June 2011.

16. Ishita Biswas, Vaishalee Dash, Prabodh Bajpai, “Sizing Optimization of PV-FC-Battery System with Hybrid PSO-EO Algorithm”,

Annual IEEE India Conference, 2012.

17. Yun Wanga, Ken S.Chen Jeffrey Mishler, Sung Chan Cho, Xavier Cordobes Adroher, “A Review of Polymer Electrolyte Membrane Fuel

Cells Technology, Applications and needs on Fundamental Research. In: Applied Energy, vol. 88, no.4, pp.981–1007, 2011.

18. Khazaee I, Ghazikhani M, Mohammadiunc M. “Experimental and thermodynamic investigation of a triangular channel geometry PEM

fuel cell at different operating conditions”, Scientia Iranica, vol.19, no.3, pp.585-593, 2012.

19. Rong-Jong Wai, Shih-Jie Jhung, Jun-Jie Liaw and Yung- Ruei Chan.: Intelligent Optimal Energy Management System for Hybrid Power

Sources Including Fuel Cell and Battery. In: IEEE transactions on power electronics, vol.28(2013), no. 7, July 2013, p.3231-3244.

20. Erkan Dursun and Osman Kilic, “Comparative evaluation of different power management strategies of a stand-alone PV/ Wind / PEMFC

hybrid power system”, Electrical Power and Energy Systems, Vol. 34, No.1, pp. 81-89, 2012.

21. Dimitris Ipsakisa, Spyros Voutetakisa, Panos Seferlisa, Fotis Stergiopoulosa and Costas Elmasidesb, “Power management strategies for a

stand-alone power system using renewable energy sources and hydrogen storage”, International Journal of Hydrogen Energy, Vol. 34,

No.16, pp. 7081-7095, 2009.

651-660

Authors: S.Rajasekaran, R.Anand, P.Muthukumar

115.

Paper Title: Digital Controller based Multi motor drive using SPWM

Abstract: Controlling the speed of an induction motor through stator side is vital in industries. Multi motor

speed control (MMD) is one of the inevitable needs in electrical companies like mills, crane etc. Individual

converter is triggered by Field Programmable Gate Array (FPGA) with single digital controller is used to control

the multi motor in this work. Due to this controller price and manual work have been reduced. Now a days, many

controllers in need of digital execution. Electrical machines requires Sinusoidal Pulse Width Modulated (SPWM)

converters for vary the speed. The generation of SPWM is done by using FPGA in this work.

Keywords: Multi motor drive, FPGA, SPWM.

References: 1. S.Rajasekaran, V.Gopalakrishnan, 2016‘A FPGA Based Multi Motor variable Speed drive’ Asian Journal of Information Technology,

vol. 15, no. 13, pp. 2186-2190

2. R Anand, P Melbamary, “Firefly Optimization Algorithm Tuned Fuzzy Sliding Mode Controller based Phase Shift Series Resonant DC to

DC Converter” Asian Journal of Research in Social Sciences and Humanities 6 (8), 2016, pp.764-778

3. S.Rajasekaran ,Dr.V.Gopalakrishnan 2015‘Multi Motor Speed control using FPGA’ International Journal of Applied Engineering

Research,ISSN :0973-4562,vol.10, no. 64,pp. 149-156.

4. S.Rajasekaran, V.Gopalakrishnan, Amal Dev V.R, “FPGA Implementation of a PWM for a three phase multimotor drive”, International

Journal of Applied Engineering Research, pp.7-12, Vol. 10(64), 2015.

5. S.Rajasekaran, V.Gopalakrishnan, Sarath.C “FPGA Implementation of Flux and Torque Controller for A Three Phase Induction Motor”

International Journal of Applied Engineering Research, pp167-173, Vol. 10(64), 2015.

6. Das, B, Fancon, M, Kasari, PR &Chakrabarti, A 2015, 'Comparison of different PWM-VSI fed 3 phase IM based on modulation index and

switching frequency', International Conference on Electrical, Electronics, Signals, Communication and Optimization, EESCO 2015.

7. Chen, B, Yao, W, Lu, Z & Lee, K 2014, 'A novel stator flux oriented V/f control method in sensorless induction motor drives for accuracy

improvement and oscillation suppression', 2014 IEEE Energy Conversion Congress and Exposition, ECCE 2014, pp. 5092-5099.

8. Lakka, M, Koutroulis, E &Dollas, A 2014, 'Development of an FPGA-based SPWM generator for high switching frequency DC/AC

inverters', IEEE Transactions on Power Electronics, vol. 29, no. 1, pp. 356-365.

9. Boudjit, K &Larbes, C, 'A New Approach for Synchronisation Multiple Motors using DSP',International Conference on Systems, Signal

Processing and Electronics Engineering (ICSSEE'2012) pp. 216-220.

10. De Castro, R, Araújo, RE & Oliveira, H 2009, 'Control in multi-motor electric vehicle with a FPGA platform', Proceedings - 2009 IEEE

International Symposium on Industrial Embedded Systems, SIES 2009, pp. 219-227.

11. Iyer, J, Tabarraee, K, Chiniforoosh, S &Jatskevich, J 2011 'An improved V/F control scheme for symmetric load sharing of multi-machine

induction motor drives', in pp. 1487-1490.

12. Jeftenic, B, Bebic, M &Statkic, S 2006, 'Controlled multi-motor drives', in International Symposium on Power Electronics, Electrical

Drives, Automation and Motion, 2006. SPEEDAM, pp. 1392-1398.

13. Ricci, F & Le-Huy, H 2002, 'An FPGA-based rapid prototyping platform for variable-speed drives', IECON Proceedings (Industrial

Electronics Conference), vol. 2, pp. 1156-1161.

661-664

116.

Authors: J.Arulvadivu, P.Palpandian, S.Manoharan

Paper Title: Efficiency Enhancement of Induction Motor Using Soft Computing Technique

Abstract: Induction motor is predominently used as driver for industrial and commertial applications.Although

induction motor has many significance it offers poor efficiency when the applied load on a motor is low. This

factor limits the application of induction motor for lighter torque conditions. So its become mandatory enhance the

efficiency of motor when the applied load is lesser. It is possibleto improve the performance of a motor by means

of mathematical modelling. In this the first principle model of an motor is developed. The efficiency of a motor for

various load condition is calculated from the data obtained from mathematical model by considering all the losses

associated with motor. The performance of model is evaluated for different control algorithms like fuzzy logic and

Particle swarm optimization.

Keywords: Induction Motor, Mathematical Model, Fuzzy logic, Particle swarm optimization.

References: 1. Murat Barut, Seta Bogosyan, Metin Gokasan “Speed-sensorless Estimation for Induction motor using Extended kalman filters ” IEEE

Transactions on industrial electronics, Vol. 54, No. 1,Feb 2007.

2. Vilas N.Ghate, Sanjay V.Dudul and G.M.Dhole “Generalized model of three phase induction motor for fault analysis” IEEE Region 8

Sibircon 2008.

3. M.R.Baqheetha Fathima, P.Magdelin Jennifer Princy, S. RamPrasath " Mathematical Modeling of SVPWM inverter fed 3 phase Induction

Motor Vector control in MATLAB/Simulink Environment " IEEE International Conference on circuits Power and Computing

Technologies,2017.

4. Cui shumei, Liang chen, Song liwei “ Study on efficiency calculation model of induction motor for electrical vehicles” IEEE Vehicle

Power and Propulsion Conference (VPPC), September 3-5, 2008.

5. P.Palpandian , E.Arunkumar, K.Syril Jennifer Paul "Efficiency Improvement of 3 Phase Induction Motor "International Journal of

Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol.1,No.3, pp-212-222

6. G. K. Singh and S. A. S. Al Kazzaz, “Induction machine drive condition monitoring and diagnostic research – a survey,” Electric Power

Systems Research, vol. 64, no. 2, pp. 145–158, 2003.

7. J. Arulvadivu, N. Divya, S. Manoharan " Integrated PID Based Intelligent Control For Three Tank System" ARPN Journal of Engineering

and Applied Sciences, vol.10, No.9, pp 4013-4017.

8. S. Tharani , P. Palpandian , N. Gowthaman, "Speed control of a Separately Excited DC Motor Using Optimization techniques

"International Journal of Innovative Research in Computer and Communication Engineering,vol.2,No.3,pp-3924-3934

665-671

Authors: D.Saveetha, M.B. Mukesh Krishnan, A.Arokiaraj Jovith, P.Rajasekar

Paper Title: Smart Vehicle Automation

117.

Abstract: This paper investigates the improvements and patterns in mechanization of vehicles which can

control crash of vehicles. It is an endeavor to give a nitty gritty research here. Drivers comfort, expanded wellbeing

is among the most essential variables of robotization. With reference to the expository study of the distributed

research, this paper will attempt to give an all the more clear comprehension of effect of robotization framework

on every one of the previously mentioned components. While improvements in accident control has prompted

vehicle plans (auto) that are significantly more secure in case of impact, they can't decrease the odds of a crash.

Vehicle mishaps still happen each day, the minor ones reason prudent misfortunes to the general public and

genuine ones causes wounds or loss of lives. Numerous mischance’s can be maintained a strategic distance from if

the human driver breaking points can be overwhelmed via robotizing a few sections of the driving errands with

security activities. This activity has energized broad research in crash cautioning and impact shirking framework.

Factual mischance information demonstrates that an impressive segment of mishaps is caused by drivers delay in

perceiving or making a decision about the risky circumstance. Hence, it is trusted that giving a type of proper

cautioning to the driver can help decrease the likelihood and seriousness of vehicle mischance’s. Auto

organizations are associated with real research intends to actualize Collision Warning System, which can build

security. Not just on account of crash, Smart Vehicle Automation (SVA) additionally identifies different elements

like temperature, stickiness and smoke utilizing certain sensors. Likewise Ultrasonic sensor is utilized to avoid

crash. So we have created Smart Vehicle Automation to decrease the danger of mishaps and maintaining a

strategic distance from life and Economical misfortune.

Keywords: Internet of things, vehicle mechanization, Raspberry pi, Raspbian OS, Collision discovery, Collision

shirking.

References: 1. Kuang, X.; Zhao, F.; Hao, H.; Liu, Z. Intelligent connected vehicles: The industrial practices and impacts on automotive value-chains in

China. Asia Pac. Bus. Rev. 2018, 24, 1–21.

2. Lee, D. CES 2018: Byton Unveils Futuristic ‘Truly Smart’ Car—BBC News. Available online: http://www. bbc.com/news/technology-

42599345

3. Harmeling, C.M.; Moffett, J.W.; Arnold, M.J.; Carlson, B.D. Toward a theory of customer engagement marketing. J. Acad. Mark. Sci.

2017, 45, 312–335.

4. Fagnant, D.J.; Kockelman, K. Preparing a nation for autonomous vehicles: Opportunities, barriers and policy recommendations. Trans.

Res. Part A Policy Pract. 2015, 77, 167–181.

5. Z. Yihua, “Vip customer segmentation based on data mining in mobile-communications industry,” in Computer Science and Education

(ICCSE), 2010 5th International Conference on. IEEE, 2010, pp. 156–159.

6. Helu, M., D. Libes, J. Lunell, K. Lyons, and K. C. Moris. 2016. “Enabling Smart Manufacturing Technologies for Decision-Making

Support.” Proceedings of the ASME 2016 International Design Engineering Technical Conferences & Computers and Information in

Engineering Conference IDETC/CIE, Charlotte, NC. 1–10. August 21–24.

7. Lu, Y., K. C. Morris, and S. Frechette. 2016. “Current Standards Landscape for Smart Manufacturing Systems, National Institute of

Standards and Technology.” Report No. NISTIR 8107. doi:10.6028/NIST.IR.8107 8. X. Hu, N. Murgovski, L. M. Johannesson, and B. Egardt, "Optimal dimensioning and power management of a fuel cell/battery hybrid bus

via convex programming," Mechatronics, IEEE/ASME Transactions, 20(1), pp.457-468, 2015.

672-674

118.

Authors: Sreejith Damodaran, S. Bhavani, K.Muthukumar

Paper Title: Power Consumption in Automated Service-Oriented Buildings using Fuzzy KNX Protocol

Abstract: Automating a building is considered to be a complex task with the availability of a large number of

devices like home appliances, sensors etc. In addition to this, continuous monitoring of these devices requires

extensive computing devices that route the devices with a needed protocol. Proper selection of a particular device

that consumes more energy during an ideal time is an intelligent task. To efficiently conserve the energy in a

building and to effectively monitor the activity of the device constantly, a novel architecture is proposed at

network layer. This architecture makes use of KNX protocol that helps in routing the devices effectively from a

monitoring station. In addition to this, to improve the monitoring and controlling activity from a main server fuzzy

devices have been added with KNX protocol. Fuzzy KNX protocol is applied over both non-residential and

residential buildings through this automated communication protocol. The devices are connected and interlinked

with each other through two way bus or a full duplex channel that allows both controlling and monitoring at the

same time. The feedback signals from the surrounding sensors for a particular appliance in a room environment is

fed into fuzzy that helps in controlling the appliance through the control devices. This behavior has been divided

into two modules: the first module has the control over each rooms and the second module controls each floor.

Using this proposed model, reducing the consumption of electrical energy from unusual electrical appliances that

are kept ON ideally is tried. The system is tested in building automation software that helps suitably in

implementing the proposed model. Also from the results obtained it could be found that the Fuzzy KNX model

works well in automating a building using a full duplex channel. Finally, this system helps in reducing the energy

consumption in buildings derived from the simulated prototype.

Keywords: Energy consumption, Fuzzy KNX automation, full duplex system, Monitoring and Controlling.

References: 1. Dietrich, Dietmar, et al. "Communication and computation in buildings: A short introduction and overview." Industrial Electronics, IEEE

Transactions on 57.11 (2010): 3577-3584.

2. R.Maheswari, S.Sheeba Rani, V.Gomathy and P.Sharmila,“Real Time Environment Simulation through Virtual Reality” in International

675-683

Journal of Engineering and Technology(IJET) , Volume.7, No.7, pp 404-406, April 2018

3. Teich, Tobias, et al. "Concept for a Service-oriented Architecture in Building Automation Systems." Procedia Engineering 69 (2014):

597-602.

4. Ghadi, Yazeed Yasin, M. M. G. Rasul, and M. K. K. Khan. "Recent Developments of Advanced Fuzzy Logic Controllers Used in Smart

Buildings in Subtropical Climate." Energy Procedia 61 (2014): 1021-1024.

5. Ghadi, Yazeed Yasin, M. G. Rasul, and Mohammad Masud Kamal Khan. "Potential of Saving Energy Using Advanced Fuzzy Logic

Controllers in Smart Buildings in Subtropical Climates in Australia." Energy Procedia 61 (2014): 290-293.

6. S.Sheeba Rani, V.Gomathy and R.Geethamani, “Embedded design in synchronisation of alternator automation” in International Journal of

Engineering and Technology(IJET) , Volume No.7, pp 460-463, April 2018

7. Kastner, Wolfgang, and Stefan Szucsich. "Accessing knx networks via bacnet/ws." Industrial Electronics (ISIE), 2011 IEEE International

Symposium on. IEEE, 2011.

8. Sita, Ioan-Valentin, and Petru Dobra. "KNX building automations interaction with City Resources Management System." Procedia

Technology 12 (2014): 212-219.

9. Bovet, Gérôme, and Jean Hennebert. "A web-of-things gateway for knx networks." Smart Objects, Systems and Technologies

(SmartSysTech), Proceedings of 2013 European Conference on. VDE, 2013.

10. Rezeka, Sohair F., Abdel-Hamid Attia, and Ahmed M. Saleh. "Management of air-conditioning systems in residential buildings by using

fuzzy logic." Alexandria Engineering Journal 54.2 (2015): 91-98.

11. Deb, Chirag, et al. "Forecasting Energy Consumption of Institutional Buildings in Singapore." Procedia Engineering 121 (2015): 1734-

1740.

12. Reena, K. E., Abmtam T. Mathew, and Lillykutty Jacob. "Decentralized controllers for wireless networked building automation system."

Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015 IEEE International Conference on. IEEE, 2015.

13. Muthukumar.k., S. Poorani., S. Gobhinath., “Extraction of Hand Gesture Features for Indian Sign languages using Combined DWT-DCT

and Local Binary Pattern”, International Journal of Engineering and Technology, 2018.

14. Muthukumar.k., S. Poorani., S. Gobhinath., Turbulence Mitigation Using Vibration Sensor And Imaging Processing Techniques,

International Journal of Pure and Applied Mathematics, Volume 119, No. 12 (2018).

15. Cao, Xianghui, et al. "Building-environment control with wireless sensor and actuator networks: Centralized versus distributed." Industrial

Electronics, IEEE Transactions on 57.11 (2010): 3596-3605.

119.

Authors: Y. Maheswar, B.L. Raju, K. Soundara Rajan

Paper Title: 256K Memory Bank Design with 9T SRAM Bit Cell and 22nm CNTFET Optimizing for Low Power

and Area

Abstract: In this paper, 9T bit cell is designed along with its periphery circuits to enhance the operating speed

of 256 Kb memories. 9T SRAM bit cell is designed with 22nm FINFET technology to obtain optimum bit cell

transistor geometry. For variations in transistor geometries, VDD and temperature, the leakage current for the

designed bit cell is estimated. The peripheral circuitry transistor geometries are designed for applications with low

power and high speed. 9T bit cell integrated with its periphery is designed to form 256 Kb memory with two 128

Kb memory banks.

Keywords: Sub threshold SRAM, current sense amplifier, high speed, cross coupled inverter, 9T bit cell,

CNTFET.

References: 1. Shimadzu Corporation, “Carbon Nanotube: Mapping of CNT FET,” http://www.shimadzu.com/an/industry/../cnt 0105005.htm, Last

visited 15/09/2013.

2. K. Kureshi, and Mohd. Hasan, “Performance comparison of CNFETand CMOS-based 6T SRAM cell in deep submicron,”

Microelectronics Journal, vol. 40, no. 6, pp. 979–982, Jun. 2009.

3. Z. Zhang, and J. G. Delgado-Frias, “Carbon Nanotube SRAM Design With Metallic CNT or Removed Metallic CNT Tolerant

Approaches,” IEEE Trans. on Nanotechnology, vol 11, no. 4, pp. 788-798, Jul. 2012.

4. Luo Sun, Jimson Mathew, Rishad A. Shafik, Dhiraj K. Pradhan and Zhen Li, A Low Power and Robust Carbon Nanotube 6T SRAM

Design with Metallic Tolerance, 978-3-9815370-2-4/DATE14/c 2014 EDAA.

5. Pushkarna, S. Raghavan, and H. Mahmoodi, “Comparison of performance parameters of SRAM designs in 16nm CMOS and CNTFET

technologies,” in Proc. IEEE International SOC Conference, Sept. 2010, pp. 27-29.

6. S. Lin, Y. B. Kim, F. Lombardi, and Y. J. Lee, “A new SRAM cell design using CNTFETs ,” in Proc. IEEE International SOC Design

Conference, Nov. 2008, pp. 168-171.

7. S. Lin, Y. B. Kim, and F. Lombardi, “Design of a CNTFET-based SRAMcell by dual-chirality selection,” IEEE Transactions on

Nanotechnology, vol. 9, no. 1, pp. 30-37, Jan. 2010

8. M. E. Sinangil, N. Verma, and A. P. Chandrakasan, “A 45nm 0.5V 8T column-interleaved SRAM with on-chip reference selection loop

for sense-amplifier,” in Proc. IEEE Asian Solid-State Circuits Conf., Nov. 2009, pp. 225–228.

9. I.J. Chang, J.-J. Kim, S. P. Park, and K. Roy, “A 32 kb 10T sub-threshold SRAM array with bit-interleaving and differential read scheme

in 90 nm CMOS,” IEEE J. Solid-State Circuits, vol. 44, no. 2, pp. 650–658, Feb. 2009.

10. Zhiyu Liu and Volkan Kursun, “Characterization of a Novel Nine-Transistor SRAM Cell”, IEEE Transactions on Very Large Scale

Integration (VLSI) Systems, vol. 16, no. 4, pp. 488-492, April 2008

11. Rajiv V. Joshi, Yue Tan and Robert C. Wong , “SRAM Cell Design to Improve Stability” United States Patent No.: US 7355906 B2, 8

April 2008

12. Clement Wann, Robert Wong, David J. Frank, Randy Mann, Shang-Bin Ko, Peter Croce, Dallas Lea, Dennis Hoyniak, Yoo-Mi Lee,

James Toomey, Mary Weybright and John Sudijono, “SRAM Cell Design for Stability Methodology”, IEEE International SOC Conference

2006, pp. 115-116, September 2006

13. Ming-Hung Chang, Yi-Te Chiu, and Wei Hwang, Design and Iso-Area Vmin Analysis of 9T Subthreshold SRAM With Bit-Interleaving

Scheme in 65-nm CMOS, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—II: EXPRESS BRIEFS, VOL. 59, NO. 7, JULY

2012, pp. 429-433

14. Bo Wang, Truc Quynh Nguyen, Anh Tuan Do, Jun Zhou, Minkyu Je and Tony T. Kim, A 0.2V 16Kb 9T SRAM with Bitline Leakage

Equalization and CAM-assisted Write Performance Boosting for Improving Energy Efficiency, IEEE Asian Solid-State Circuits

Conference, November 12-14, 2012/Kobe, Japan, pp. 73-76

15. N. Verma and A. Chandrakasan, “A 65nm 8T Sub-Vt SRAM Employing Sense-Amplifier Redundancy”, IEEE International Solid-State

Circuits Conference, pp. 328-329, Feb. 2007.

16. T.-H. Kim, J. Liu, and C. H. Kim, “A voltage scalable 0.26V, 64 kb 8T SRAM with Vmin lowering techniques and deep sleep mode,”

IEEE J. Solid-State Circuits, vol. 44, no. 6, pp. 1785–1795, Jun. 2009.

684-690