Lecture Notes in Electrical Engineering 511

Vijay Nath · Jyotsna Kumar MandalEditors

Nanoelectronics, Circuits and Communication Systems Proceeding of NCCS 2017

Lecture Notes in Electrical Engineering

Volume 511

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Vijay Nath • Jyotsna Kumar MandalEditors

Nanoelectronics, Circuitsand Communication SystemsProceeding of NCCS 2017

123

EditorsVijay NathDepartment of Electronics andCommunication Engineering

Birla Institute of Technology, MesraRanchi, JharkhandIndia

Jyotsna Kumar MandalDepartment of Computer Scienceand Engineering

University of KalyaniKalyaniIndia

ISSN 1876-1100 ISSN 1876-1119 (electronic)Lecture Notes in Electrical EngineeringISBN 978-981-13-0775-1 ISBN 978-981-13-0776-8 (eBook)https://doi.org/10.1007/978-981-13-0776-8

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Preface

Nowadays the development of electronic goods provides major benefits to theworld market in terms of high-level digital portability, connectivity, safety, andsecurity. Designs of complex integrated circuits (ICs) are possible due to ElectronicDesign Automation (EDA) software such as Cadence, Mentor Graphics, Synopsis,Xilinx, and Active HDL. Presently, three types of advanced techniques play a majorrole in IC design and manufacture, such as the design of full custom ICs, semi-custom ICs, and Application Specific Integrated Circuit (ASIC). Up to 2015, morethan 1 billion transistors existed in desktop computers. For their complete designthey require more than 500 rules which are statistical in nature. To meet the demandof the market for sophisticated systems, both designers and engineers are devel-oping automated EDA software tools for efficient, bulk design. These tools considerthe length of transistors in the nanometer range. These range-designed ICs requiregood support in terms of nano-materials and their related chemicals. Testing of ICsis also a major issue in sophisticated systems. Testing should occur at each step ofdesign, from the Simulation Program of Integrated Circuit Emphasis (SPICE) level,through the schematics and layout levels, to fabrication. As levels of designincrease, so does the testing cost of ICs. Without efficient software support, testingof ICs is difficult.

System on Chip (SoC) provides an excellent platform where analog and digitalIC layouts can come together and be fabricated on a single wafer. Because of this,the cost of fabrication per IC and chip, accommodated on a single wafer, decreasesand the product quality increases. Nanotechnology has allowed the integration ofelectronic devices, chips, circuits, and systems. The nanoscale dimensions ofnano-electronics components of systems having giga-scale complexity can bemeasured on a chip. Nanotechnology improves the capability of electronic com-ponents by reducing the size of the transistors in ICs, increasing the density ofmemory chips, reducing power consumption, and improving display screens, e.g.,their thickness. Today, in global automation, control, and functional environments,the Internet of Things (IoT) plays a major role. Nowadays peoples are leadingtoward a cashless world. The computing systems driving the cashless world arereliable, robust, correct, and highly accurate. IoT system may be adopted for smart

v

education systems to make a global education hub. It is also adopted in globalfactory operation, control, and monitoring, for perfect and optimized products.NCCS–2017 provides an excellent forum for young researchers, engineers, andprofessors to work together and share knowledge. It also generates ideas about howto work in electronic media both safely and securely. Manufacturingcompanies/industries and universities make significant contributions to the devel-opment of their countries. However, they are facing several challenges such as rapidproduct development, flexibility, Low to medium volume, transportation, low cost,etc. Many advanced and unconventional technologies, tools, and software programsare being developed worldwide to face up to these challenges. Among thesetechnologies, IC design, manufacturing, and the IoT have become more popular dueto their ability in terms of precision. For research, development, sharing knowledge,and exchanging ideas in current trends, the Third International Conference onNanoelectronics, Circuits and Communication Systems (NCCS-2017) was orga-nized by the Indian Society of Very Large Scale Integration (VLSI) Education(ISVE) in Ranchi and the Institution of Electronics and TelecommunicationEngineers (IETE), also in Ranchi, at the Advanced Regional Telecom TrainingCentre (ARTTC) Bharat Sanchar Nigam Limited (BSNL) near the Jumar River,Hazaribag Road, Ranchi, from 11–12 November 2017. This conference coveredadvancement in Micro Electro Mechanical System (MEMS) and nanoelectronics,wireless communication, optical communication, instrumentation, signal process-ing, the IoT, image processing, bioengineering, green energy, hybrid vehicles,environmental science, weather forecasting, cloud computing, renewable energy,Radio Frequency ID (RFID), CMOS sensors, actuators, transducers, telemetrysystems, embedded systems, sensor network applications in mines, etc.Additionally, there is a demand for manpower to drive electronic system design andmanufacturing. Because populations are increasing, society has a duty to provide alltypes of facilities to new users in order that they can live their lives efficiently. Thisis only possible with the help of research and development. As people move intothe digital era, knowledge of safety and security is very important, something whichis driven in part by technical meetings, conferences, workshops, and seminars oncurrent trends in technology. NCCS-2017 represents a forum for young researchesto develop their knowledge in current trends and provide solutions for futuretechnologies demanded by the world market.

At this conference around 300 papers were received, of which 58 were peerblind reviewed and registered. Presented papers were accepted for publication in theconference proceedings of the Springer Scopus book series, Lecture Notes inElectrical Engineering (LNEE). In addition, 11 outstanding papers were selected forSCI Journals like Microsystem Technologies and IETE Technical Review; IETETechnical Research, etc. Expert evaluators also guided to authors for extendedversion of the research articles. They suggest continue on same track and updatetheir articles 70–80% with new titles, contents and results and submit to listedScience Citation Index (SCI) and Scopus journals for publications. All these articleswere blindly peer reviewed by at least three reviewers with their detailed commentsbeing passed to the authors for final decisions. During presentation of authors, six

vi Preface

expert committee members evaluated their work. They also guided to authors forIPR/patents and new innovative project for funding in their area of research.NCCS–2017 organized by the ISVE and IETE in Ranchi at ARTTC BSNL pro-vided a unique platform to young researchers, scientists, engineers, and professorsto present their work worldwide. An expert committee guided authors to improvetheir articles, and provided advice about how to get work published in high-impactjournals and book series. This conference was totally different to other conferencesand symposia. This conference provided very good support to young researchers interms of learning (by expert lectures, suggestions & comments) and updating theirknowledge. This forum provided outcome-based learning and research strategies.

Consent for the conference was received from the Honorable Governor ofJharkhand, Smt. Draupadi Murmu, and President of the IETE, New Delhi, Dr. K. T.V. Reddy. Their message was published in the conference souvenir booklet alongwith other messages from dignitaries, wishing success for the two-day event. In theinaugural session of the conference on dais present as the Chief Guest Dr. GopalPathak, Vice-chancellor of Jharkhand Technical University, Ranchi; Guest ofHonor Dr. K. K. Thakur, CGMT BSNL, Ranchi; Guest of Honor Dr. A. A. Khan,Former Vice-chancellor of Ranchi University, Ranchi; Guest of Honor, Dr. R. K.Singh, Former Chairman of the IETE, Ranchi; Guest of Honor Sh. Sanjay KumarJha, Past Chairman of the IETE, Ranchi, and Chief Executive Engineer of theGovernment of Jharkhand; Guest of Honor Dr. P. R. Thakura, Professor at the BITMesra and Executive Member of the ISVE and IETE, Ranchi; Guest of Honor, Sh.Ajay Kumar, Chairman of the IETE, Ranchi, and AGM (Admin) ARTTC BSNL,Ranchi; Dr. Anand Kumar Thakur, Faculty at SSMC RU and Organizing Secretaryof NCCS-2017; Dr. Raj Kumar Singh, Faculty at RLSY RU and Convenor ofNCCS-2017, Ranchi; Dr. Vijay Nath, Faculty at BIT, Mesra, and General Chair ofNCCS-2017; and Keynote Speaker Dr. S. Jit, Professor at the Indian Institute ofTechnology, BHU (Uttar Pradesh). The conference began with a welcome addressby Sh. Ajay Kumar, Chairman of the IETE Ranchi Centre with technical detailsabout the conference being delivered by Dr. Vijay Nath, General Chair of theconference. A keynote address was given by Dr. S. Jit, Professor at the IndianInstitute of Technology, BHU (Uttar Pradesh), entitled “Nanoelectronics and itsfuture prospective.” The chief guest at this function, Dr. Gopal Pathak, demon-strated the impact of research in new technology and its applications in society. Healso shared his research and development views. He explained that without qualityof research, technical education cannot grow, because day by day new technologiesare emerging. He also demonstrated that through this conference in nearby IndianInstitute of Technology (IITs), National Institute of Technology (NITs), BirlaInstitute of Technology (BITs), and other parallel technical universities, researcherswere following trend by publishing their articles in high-quality journals. All of theother dignitaries also gave views about the growth of society, quality of publica-tions, research innovations, and challenges.

The first technical session started with an enlightening lecture by Dr. S. Jit on thetopic of “Nanotechnology and its future perspective.”After his lecture he took chargeas the chairman of the first technical session. M. Selvi et al. presented their ideas on

Preface vii

the Chapter “Classification of Medical Dataset Along with Topic Modeling UsingLDA.” Manish Mohan Baral and Amitabh Verma demonstrated Chapter “Cloud-Based Intelligent System for Supply Chain Management: A Future Roadmap forSCM Technologies.” Shipra and Mahesh Chandra explained the Chapter “Effect ofProcessing Combined MFCC and DSCC Features with QCN for Hindi VowelClassification in Noisy Environments.” Sanjiv Kumar Srivastava et al. demonstratedChapter “The Impact of Knowledge Management and Data Mining on CRM in theService Industry.”R. S. Nancy Noella and J. Priyadarshini defined Chapter “EfficientComputer-Aided Diagnosis of Alzheimer’s Disease and Parkinson’s Disease—ASurvey.” Brij Mohan Prasad and P. R. Thakura explained the Chapter “Designand Analysis of Dedicated Power Converter for Hybrid Electric Vehicles.” KeshavSinha and Partha Paul demonstrated Chapter “An Underground Mine Safety ofPersonnel’s Using IoT.” Ravi Prakash et al. demonstrated the Chapter“Implementation of Trapdoor Functionality to Two-Layer Encryption andDecryption by Using RSA-AES Cryptography Algorithms.” Bathula Siva KumarReddy explained the Chapter “Experimental Validation of Spectrum SensingTechniques Using Software-Defined Radio.” Shaik Qadeer et al. demonstratedChapter “Smart Switch for Power Saving.” Debdatta Kandar and Babu Sena Pauldefined Chapter “SDN-Based Programmable RSU Selection Method inHeterogeneous Networks.” K. Damayanti et al. demonstrated the Chapter “Designand Implementation of an Energy-Efficient, Low-Cost Robotic Solar Tracker.”Arindam Banerjee et al. explained the Chapter “Fast Squaring Technique for RadixVicinity Numbers for Radix 2n ± M with Reduced Computational Complexity.”Annu Priya and Sudip Kumar Sahana presented Chapter “A Survey onMultiprocessor Scheduling Using Evolutionary Technique.” Minal Padlia andJankiballabh Sharma defined Chapter “Fractional Sobel Filter Based Brain TumorDetection and Segmentation Using Statistical Features and SVM.” Anupam Kumarand Manoj Kumar demonstrated Chapter “Cladding Mode Analysis of PhotonicCrystal Fiber Using Scalar Effective Index Model.” M. J. Abinash andV. Vasudevan defined Chapter “A Hybrid Forward Selection Based LASSOTechnique for Liver Cancer Classification.” Smita Pallavi et al. explained theChapter “Feature Subset Selection Using IULDA Model for Prediction.” Md Sajidet al. defined the Chapter “Effect of RC Surge Suppressor in Reduction of OverVoltages at Motor Terminal Caused by PWM-Based Inverter.” Nalini Singh andSatchidananda Dehuri explained the Chapter “Usage of Deep Learning in EpilepticSeizure Detection Through EEG Signal.” Annapurna Mishra and SatchidanandaDehuri defined Chapter “An Experimental Study of Filter Bank Approach andBiogeography-Based Optimized ANN in Fingerprint Classification.” SandeepDabhade et al. demonstrated Chapter “Performance and Capacity Testing of Mediumand Large Managed Plane and Control Plane Optical Networks.” Prabhat KumarRanjan and P. R. Thakura demonstrated Chapter “Analysis of Single-StageThree-Phase DC–AC Boost Inverter for Distributed Generation System.” AvanishKumar and P. R. Thakura defined a Chapter “Close Loop Speed Controller forBrushless DC Motor for Hybrid Electric Vehicles.” Ankita and Sudip Kumar Sahanadefined Chapter “A Survey on Grid Schedulers.” M. K. Mandal and A. K. Das

viii Preface

demonstrated Chapter “Chaos-Based Colour Image Encryption Using Microcon-troller ATMEGA 32.” Rahul Priyadarshi et al. defined Chapter “An Enhanced GEARProtocol for Wireless Sensor Networks.” C. Kavitha and M. Ganesh Madhandemonstrated Chapter “A Novel Equivalent Circuit Approach for Modal Analysis ofMEMS Cantilever Beam.”M. Karuppasamy and S. P. Balakannan explained Chapter“Energy-Efficient Data Delivery in Green Cloud Networks.” Shalini Mahato andSanchita Paul defined Chapter “Electroencephalogram (EEG) Signal Analysis forDiagnosis of Major Depressive Disorder (MDD): A Review.” K. Murali Krishna andM. Ganesh Madhan defined the Chapter “Numerical Simulation of High-TemperatureVCSEL Operation and Its Impact on Digital Optical Link Performance.” JatindeepSingh et al. illustrated a Chapter “Smart Activity Sequence Generator inWearable IoT.” Shamama Anwar et al. defined Chapter “Hand Gesture Recognition: A Survey.”Qaiser Razi and Vijay Nath demonstrated the Chapter “Design of Smart EmbeddedSystem for Agricultural Update Using Internet of Things.” Sabiha Fatma and VijayNath defined the Chapter “Study and Design of Smart Embedded System for TrainTrackMonitoring Using IoTs.”Abhinav Kumar and Vijay Nath explained the Chapter“Study and Design of Smart Embedded System for Smart City Using Internet ofThings.” Satvika Anand and Vijay Nath demonstrated the Chapter “Study and Designof Smart Embedded System for Remote Health Monitoring Using Internet of Things.”Chandan Kumar and Vijay Nath illustrated the Chapter “Design of Smart EmbeddedSystem for Auto Toll Billing System Using IoTs.” Pratik Mondal and Susanta KumarParui explained the Chapter “Two Step Coupled Gap Resonator and Its Application asBandpass Filter.” Ashwani Sharma et al. defined the Chapter “PerformanceComparison of DCF and FBG as Dispersion Compensation Techniques at 100 GbpsOver 120 km Using SMF.” Neha Nidhi et al. explained Chapter “Different Aspects ofSmart Grid: An overview.” Sumit Srivastava et al. defined Chapter “Robust VoiceprintBased Audio Watermarking Using Wavelet Transform.” Neha Nidhi et al. demon-strated Chapter “A High-Performance Energy-Efficient 75.17 dB Two-StageOperational Amplifier.” Utkarsh Raj et al. explained the Chapter “Automated TollPlaza Using Barcode-Laser Scanning Technology.” Trisha Ghosh et al. defined theChapter “MIMO Wideband Antenna Technique in DGS for Enhanced WirelessCommunication.” Jyoti et al. explained the Chapter “Designing of FIR Filter UsingFPGA: A Review.” Shantanu Chaudhary et al. defined the Chapter “Design ofAll-Terrain Rover Quadcopter for Military Engineering Services.” Dipti Kumari andKumar Rajnish explained Chapter “A Systematic Approach Towards Development ofUniversal Software Fault Prediction Model Using Object-Oriented DesignMeasurement.” Priyanka Parihar et al. defined the Chapter “6T SRAM Cell Designand Investigation for Ultra-Low-Power Application.” Rohit Mohan et al. defined theChapter “Design of Robot Monitoring System for Aviation.” E. V. V. Hari Charan etal. demonstrated the Chapter “Electronic Toll Collection System Using BarcodeTechnology.” Vidushi Goel et al. explained the Chapter “Design of SmartphoneControlled Robot Using Bluetooth.” Paritosh Kumar Sinha et al. defined the Chapter“Design of Earthquake Indicator System Using ATmega328p and ADXL335 forDisaster Management.” Deril Raju et al. defined the Chapter “Study and Design ofSmart Embedded System for Aviation System: A Review.” Deepak Prasad et al.

Preface ix

explained the Chapter “Study and Design of Smart Industry: A Review.” S. SanjayKumar et al. explained the Chapter “Design of Smart Security Systems for HomeAutomation.” Vidushi Goel et al. defined the Chapter “Auto-Train Track FaultDetection System.” Sonali B. Wankhede demonstrated the “Study of Network-BasedDoS Attacks.”

At this conference authors were invited to submit original papers with selected,quality papers being presented. Authors described their articles very well. Authorsand editors took the utmost care in presenting information and acknowledgingoriginal sources whenever necessary. The editors would like to express theirgratitude toward the authors, organizers of the IC-NCCS-2017, and staff of Springer(India) for publishing these conference proceedings. Readers are requested toprovide their valuable feedback on the quality of presentation and inadvertent errorsor omission of information. We expect that the book will be welcomed by studentsas well as practicing engineers, researchers, and professors.

Ranchi, India Vijay Nath

x Preface

Editorial Acknowledgements

We extend our thanks to all the authors for contributing to this book/proceedings bysharing their valuable research findings. We would especially like to thank a numberof reviewers for promptly reviewing the papers submitted to the conference. We aregrateful to the volunteers, invited speakers, session chairs, sponsors, sub-committeemembers, members of the international advisory committee and the national advisorycommittee, members of the technical program committee, members of the jointsecretary, and members of scientific advisory committee, for the part they all playedin making the conference a success. The editors express their heartfelt gratitudetoward Dr. K. T. V. Reddy, President of the IETENewDelhi; Dr. A. K. S. Chandelle,Immediate Past President of the IETE New Delhi; Smt. Srimati Dagur, FormerPresident of the IETE New Delhi; Sh. Sanjay Kumar Jha, Immediate Past Chairmanof the IETE Ranchi and Executive Engineer Government of Jharkhand; Prof. BerndMichel, Micro Materials Centre (MMC) Berlin Germany; Prof. Bharath Bhushan,Ohio Eminent Scholar and The Horward D. Winbigler Professor and Director of theNBLL at Ohio State University Columbus Ohio U.S.A.; Prof. P. S. Neelakanta(C. Engg.), Fellow at the IEE Florida Atlantic University (FAU) U.S.A.; Sh. PrasadVijay Bhushan Pandey, DTO Term Cell1 BSNL Ranchi and Chairman of the ISVERanchi; Prof. A. A. Khan, former Vice-chancellor of Ranchi University; Prof. M. K.Mishra, Vice-chancellor of BIT Mesra; Prof. Gopal Pathak, Vice-chancellor ofJharkhand Technical University Ranchi; Dr. K. K. Thakur, CGMT BSNL Ranchi;Prof. R. K. Pandey, Vice-chancellor of Ranchi University; Prof. P. K. Barhai, formerVice-chancellor of BIT Mesra; Sh. R. Mishra, former CMD-HEC Ranchi; Dr.M. Chakraborty, Professor at IIT Kharagpur; Dr. Ramgopal Rao, Professor at IITBombay, and Director at IIT Delhi; Dr. P. Chakraborty, Professor at IIT BHU;Dr. S. Jit, Professor at IIT BHU; Dr. J. K. Mandal, Professor at Kalyani University;Dr. Abhijit Biswas, Professor at Kolkata University; Dr. Subir Kumar Sarkar,Professor at Jadavpur University; Dr. Gaurav Trivedi, Associate Professor at IITGuwahati; Dr. Y. S. Chauhan, Associate Professor at IIT Kanpur; Dr. B. K. Kaushik,Professor at IIT Roorkee; Dr. Shree Prakash Tiwari, Faculty at IIT Jodhpur;Dr. P. Kumar, Associate Professor at IIT Patna; Dr. M. Bhaskar, Professor at NIT

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Tirchy; Dr. Adesh Kumar, Faculty at UPES University, Dehradun; Dr. ManishKumar Associate Professor at MMMUT Gorakhpur; Dr. Manish ishra, AssociateProfessor at DDU University Gorakhpur; Dr. Umesh Yadav, Professor at DDUUniversity Gorakhpur; Dr. J. K. Mandal, Professor at Kalyani University; Prof.D. Acharjee, President at ISTM Kolkata; Dr. N. Gupta, Professor at BIT Mesra,Ranchi; Dr. Vibha Rani Gupta, Professor at BIT Mesra; Dr. S. Pal, Professor at BITMesra, Dr. B. K. Mishra, Principal Jumeritelaya Government of Jharkhand; Dr. V. K.Jha, BITMesra; Sh. Ajay Kumar, AGM (administration) ARTTC BSNL Ranchi, andChairman of IETE Ranchi; Dr. P. R. Thakura, Executive Member of IETE and ISVE,Ranchi and Professor at BIT Mesra Ranchi; Dr. M. Chandra, Dr. M. Chandra,Executive Member of IETE Ranchi, and Professor at BIT Mesra Ranchi; Dr. S. K.Ghorai, Executive Member of IETE Ranchi and Professor at BIT Mesra Ranchi;Dr. B. Chakraborty, Executive Member of IETE Ranchi, and Executive Engineer atMecon Ranchi; Dr. S. Chakraborty, Executive Member of IETE Ranchi andProfessor at BITMesra Ranchi; Dr. S. S. Solanki, Professor at BITMesra Ranchi; Dr.S. Pal, Professor at BIT Mesra Ranchi; Dr. S. Kumar, Executive Member of IETERanchi and Associate Professor at BIT Mesra Ranchi; Dr. B. K. Bhattacharya,Professor at NIT Agartala; Dr. Anand Kumar Thakur, Treasurer of IETE Ranchi &Faculty SSMC and Director FM Ranchi University; Dr. Raj Kumar Singh, ExecutiveMember of IETE Ranchi and Faculty at RLSYC Ranchi University and Coordinatorof UGC Refresher Course Ranchi University; Dr. R. K. Lal, Associate Professor atBIT Mesra Ranchi; Dr. Sudip Sahana ; Dr. P. Pal; Dr. Amritanjali; Dr. Rishi Sharma;Dr. K. K. Senapati; Dr. S. S. Sahu; Dr. M. K. Mukul; Dr. K. Bose, BIT Mesra; Smt.Saroj, Treasurer of ISVE Ranchi; Prof. Jyoti Singh Joint Secretary of ISVE Ranchi;Prof. A. K. Pandey, Secretary of ISVE Ranchi; Sh. Suraj Kumar Saw; Sh. SubroChakraborty; Sh. Dipayan Ghosh; Sh. Ramkrishna Kundu, Executive Member ofISVE Ranchi; Sh. Deepak Prasad; Sh. Sumit Singh; Sh. H. Kar; Sh. Rajanish Yadav;and Sh. Anup Tirkey member of ISVE Ranchi for their endless support, encour-agement, and motivation to organize such a prestigious event which paved the wayfor publishing the Proceedings of the Third International Nanoelectronics, Circuitsand Communication Systems (NCCS-2017) conference. At last we express oursincere gratitude toward the staff members at Springer (India) who helped publishthis book.

xii Editorial Acknowledgements

Contents

Classification of Medical Dataset Along with Topic ModelingUsing LDA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1M. Selvi, K. Thangaramya, M. S. Saranya, K. Kulothungan, S. Ganapathyand A. Kannan

Cloud-Based Intelligent System for Supply Chain Management:A Future Roadmap for SCM Technologies . . . . . . . . . . . . . . . . . . . . . . 13Manish Mohan Baral and Amitabh Verma

Effect of Processing Combined MFCC and DSCC Features with QCNfor Hindi Vowel Classification in Noisy Environments . . . . . . . . . . . . . . 25Shipra and Mahesh Chandra

The Impact of Knowledge Management and Data Mining on CRMin the Service Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Sanjiv Kumar Srivastava, Bibhas Chandra and Praveen Srivastava

Efficient Computer-Aided Diagnosis of Alzheimer’s Diseaseand Parkinson’s Disease—A Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53R. S. Nancy Noella and J. Priyadarshini

Design and Analysis of Dedicated Power Converter for HybridElectric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65Brij Mohan Prasad and P. R. Thakura

An Underground Mine Safety of Personnel’s Using IoT . . . . . . . . . . . . 77Keshav Sinha and Partha Paul

Implementation of Trapdoor Functionality to Two-Layer Encryptionand Decryption by Using RSA-AES Cryptography Algorithms . . . . . . . 89Ravi Prakash, Premkumar Chithaluru, Deepak Sharma and P. Srikanth

Experimental Validation of Spectrum Sensing TechniquesUsing Software-Defined Radio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97Bathula Siva Kumar Reddy

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Smart Switch for Power Saving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105Shaik Qadeer, Ajaz Fatima, Asfia Aleem and Amreen Begum

SDN-Based Programmable RSU Selection Method in HeterogeneousNetworks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115Debdatta Kandar and Babu Sena Paul

Design and Implementation of an Energy-Efficient, Low-CostRobotic Solar Tracker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127K. Damayanti, T. Sunil Reddy, B. M. Reddy, Avireni Srinivasuluand SM-IEEE

Fast Squaring Technique for Radix Vicinity Numbersfor Radix 2n – M with Reduced Computational Complexity . . . . . . . . . 139Arindam Banerjee, Arpan Deyasi, Swapan Bhattacharyyaand Angsuman Sarkar

A Survey on Multiprocessor Scheduling Using EvolutionaryTechnique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149Annu Priya and Sudip Kumar Sahana

Fractional Sobel Filter Based Brain Tumor Detectionand Segmentation Using Statistical Features and SVM . . . . . . . . . . . . . 161Minal Padlia and Jankiballabh Sharma

Cladding Mode Analysis of Photonic Crystal Fiber Using ScalarEffective Index Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177Anupam Kumar and Manoj Kumar

A Hybrid Forward Selection Based LASSO Techniquefor Liver Cancer Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185M. J. Abinash and V. Vasudevan

Feature Subset Selection Using IULDA Model for Prediction . . . . . . . . 195Smita Pallavi, Akshay Kumar and Utkarsh Mohan

Effect of RC Surge Suppressor in Reduction of Over Voltagesat Motor Terminal Caused by PWM-Based Inverter . . . . . . . . . . . . . . . 209Md Sajid, Amer Ali Khan, M. Suryakalavathi and B. P. Singh

Usage of Deep Learning in Epileptic Seizure Detection ThroughEEG Signal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219Nalini Singh and Satchidananda Dehuri

An Experimental Study of Filter Bank Approach andBiogeography-Based Optimized ANN in FingerprintClassification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229Annapurna Mishra and Satchidananda Dehuri

xiv Contents

Performance and Capacity Testing of Medium and Large ManagedPlane and Control Plane Optical Networks . . . . . . . . . . . . . . . . . . . . . . 239Sandeep Dabhade, Sumit Kumar, Shishir Kumarand K. B. Sivasubramanian

Analysis of Single-Stage Three-Phase DC–AC Boost Inverterfor Distributed Generation System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245Prabhat Kumar Ranjan and P. R. Thakura

Close Loop Speed Controller for Brushless DC Motorfor Hybrid Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255Avanish Kumar and P. R. Thakura

A Survey on Grid Schedulers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269Ankita and Sudip Kumar Sahana

Chaos-Based Colour Image Encryption Using MicrocontrollerATMEGA 32 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281M. K. Mandal and A. K. Das

An Enhanced GEAR Protocol for Wireless Sensor Networks . . . . . . . . 289Rahul Priyadarshi, Surender Kumar Soni and Prashant Sharma

A Novel Equivalent Circuit Approach for Modal Analysisof MEMS Cantilever Beam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299C. Kavitha and M. Ganesh Madhan

Energy-Efficient Data Delivery in Green Cloud Networks . . . . . . . . . . . 313M. Karuppasamy and S. P. Balakannan

Electroencephalogram (EEG) Signal Analysis for Diagnosisof Major Depressive Disorder (MDD): A Review . . . . . . . . . . . . . . . . . . 323Shalini Mahato and Sanchita Paul

Numerical Simulation of High-Temperature VCSEL Operationand Its Impact on Digital Optical Link Performance . . . . . . . . . . . . . . . 337K. Murali Krishna and M. Ganesh Madhan

Smart Activity Sequence Generator in Wearable IoT . . . . . . . . . . . . . . 353Jatindeep Singh, Punit Mishra, Satyajit Mohapatra, Hari Shanker Guptaand Nihar Mohapatra

Hand Gesture Recognition: A Survey . . . . . . . . . . . . . . . . . . . . . . . . . . 365Shamama Anwar, Subham Kumar Sinha, Snehanshu Vivekand Vishal Ashank

Design of Smart Embedded System for Agricultural UpdateUsing Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373Qaiser Razi and Vijay Nath

Contents xv

Study and Design of Smart Embedded System for Train TrackMonitoring Using IoTs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383Sabiha Fatma and Vijay Nath

Study and Design of Smart Embedded System for Smart CityUsing Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397Abhinav Kumar and Vijay Nath

Study and Design of Smart Embedded System for Remote HealthMonitoring Using Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . 409Satvika Anand and Vijay Nath

Design of Smart Embedded System for Auto Toll Billing SystemUsing IoTs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415Chandan Kumar and Vijay Nath

Two Step Coupled Gap Resonator and Its Applicationas Bandpass Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425Pratik Mondal and Susanta Kumar Parui

Performance Comparison of DCF and FBG as DispersionCompensation Techniques at 100 Gbps Over 120 km Using SMF . . . . . 435Ashwani Sharma, Inder Singh, Suman Bhattacharya and Shalini Sharma

Different Aspects of Smart Grid: An Overview . . . . . . . . . . . . . . . . . . . 451Neha Nidhi, Deepak Prasad and Vijay Nath

Robust Voiceprint Based Audio Watermarking UsingWavelet Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457Sumit Srivastava, Mahesh Chandra and G. Sahoo

A High-Performance Energy-Efficient 75.17 dB Two-StageOperational Amplifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469Neha Nidhi, Deepak Prasad and Vijay Nath

Automated Toll Plaza Using Barcode-Laser Scanning Technology . . . . . 475Utkarsh Raj, Neha Nidhi and Vijay Nath

MIMO Wideband Antenna Technique in DGS for EnhancedWireless Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 483Trisha Ghosh, Sneha Tiwari and J. Sahay

Designing of FIR Filter Using FPGA: A Review . . . . . . . . . . . . . . . . . . 493Jyoti, Adesh Kumar and Anil Sangwan

Design of All-Terrain Rover Quadcopter for Military EngineeringServices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 507Shantanu Chaudhary, Arka Prava, Neha Nidhi and Vijay Nath

xvi Contents

A Systematic Approach Towards Development of UniversalSoftware Fault Prediction Model Using Object-OrientedDesign Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515Dipti Kumari and Kumar Rajnish

6T SRAM Cell Design and Investigation for Ultra-Low-PowerApplication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527Priyanka Parihar, Neha Gupta, Vaibhav Neema and Praveen Singh

Design of Robot Monitoring System for Aviation . . . . . . . . . . . . . . . . . . 535Rohit Mohan, Akash Keneth Suraj, Sakshi Agarawal, Sananaya Majumdarand Vijay Nath

Electronic Toll Collection System Using BarcodeTechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549E. V. V. Hari Charan, Indrajit Pal, Akash Sinha, Raj Kamal Roye Baroand Vijay Nath

Design of Smartphone Controlled Robot Using Bluetooth . . . . . . . . . . . 557Vidushi Goel, Riya, Pinki Kumari, Prachi Shikha, Tanushree,Deepak Prasad and Vijay Nath

Design of Earthquake Indicator System Using ATmega328pand ADXL335 for Disaster Management . . . . . . . . . . . . . . . . . . . . . . . . 565Paritosh Kumar Sinha, Satyam Saraiyan, Momojit Ghosh and Vijay Nath

Study and Design of Smart Embedded System for Aviation System:A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573Deril Raju, Lalitha Eleswarapu, Rohith Saiv and Vijay Nath

Study and Design of Smart Industry: A Review . . . . . . . . . . . . . . . . . . . 591Divyesh Kumar Maurya, Ankush Kumar, Suraj Kaunoujiya,Deepak Prasad and Vijay Nath

Design of Smart Security Systems for Home Automation . . . . . . . . . . . . 599S. Sanjay Kumar, Ayushman Khalkho, Sparsh Agarwal, Suraj Prakash,Deepak Prasad and Vijay Nath

Auto-Train Track Fault Detection System . . . . . . . . . . . . . . . . . . . . . . . 605Vidushi Goel, Shubham Kumar, Aditya Muralidharan, Naveen Markham,Deepak Prasad and Vijay Nath

Study of Network-Based DoS Attacks . . . . . . . . . . . . . . . . . . . . . . . . . . 611Sonali B. Wankhede

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617

Contents xvii

About the Editors

Vijay Nath received his bachelor’s degree in Physics and master’s degree inElectronics from DDU Gorakhpur University, India, in 1998 and 2001, respec-tively. He received PGDCN from MMM Engineering College Gorakhpur (GM) in1999 and Ph.D. in VLSI Design & Technology from Dr. RML Avadh University,Faizabad, in association with CEERI, Pilani, in 2008. He served as faculty in theDepartment of Electronics, DDU Gorakhpur University, Gorakhpur (2002–2006).In 2006, he joined as faculty in the Department of Electronics and CommunicationEngineering, Birla Institute of Technology, Mesra, Ranchi. Currently, he isProfessor In-charge of Embedded System Design Lab of the Department of ECE,Member of BIT Brand Management, Assistant Examination Controller of BIT,Mesra, Ranchi. His research interests include microelectronics, low power VLSIdesign, temperature sensors, ASICs design, SoC, FPGA-based wireless systemdesign, signal conditioning, real embedded systems designs, smart cardiac pace-makers, etc. He has completed three projects funded by DRDO, MHRD, ISRO,Government of India. He has 16 years of teaching and research experience, guidedtwo Ph.D. scholars, developed pedagogy course on VLSI design, edited four booksas volume editor of Springer, published 120 research articles in internationaljournals and conferences, and is a member of several respected professional andacademic bodies including IETE, ISVE, and IEEE.

Jyotsna Kumar Mandal received his M.Tech. from the Department of ComputerScience, University of Calcutta, India, and Ph.D. in the field of Data Compressionand Error Correction Techniques from Jadavpur University. He is Professor ofComputer Science and Engineering, Director of IQAC, and Former Dean of FETM,University of Kalyani. He has 29 years of teaching and research experience and iscurrently working in the fields of network security, steganography, image pro-cessing, and wireless and sensor networks. He has guided 21 Ph.D. scholars,published six books and more than 380 papers, including 154 publications invarious international journals, and edited 27 volumes as volume editor forScienceDirect, Springer, CSI, etc.

xix

Classification of Medical Dataset Alongwith Topic Modeling Using LDA

M. Selvi, K. Thangaramya, M. S. Saranya, K. Kulothungan,S. Ganapathy and A. Kannan

Abstract Nowadays, medical applications need a lot of storage for storing andproviding access to the medical information seekers. Moreover in medical appli-cations, information grows tremendously and hence they must be stored using asuitable storage structure so that it is possible to retrieve them faster from the textcorpus in which the medical information is stored. The existing methods for storageand retrieval do not focus on classified organization. However, classified datastorage will facilitate fast retrieval. Therefore, a new Latent Dirichlet Allocation(LDA) based topic modeling approach is proposed in this paper which uses tem-poral rules for effective manipulation of stored data. Therefore, a temporal rulebased classification algorithm is proposed in this work by combining Naïve BayesClassifier with LDA and temporal rules to store the data more efficiently and ithelps to retrieve the documents faster. From the experiments conducted in this workby storing and retrieving medical data in a corpus, it is proved that the proposedmodel is more efficient with respect to classification accuracy leading to organizedstorage and fast retrieval.

Keywords Topic modeling � Latent Dirichlet Allocation (LDA)Word cloud � Topic of words � Naive Bayes classification

M. Selvi (&) � K. Thangaramya � M. S. Saranya � K. Kulothungan � A. KannanDepartment of IST, Anna University, CEG Campus, Chennai, Indiae-mail: arpudhaselvi123@gmail.com

K. Thangaramyae-mail: thangaramya112@gmail.com

M. S. Saranyae-mail: saranyasivaraman5@gmail.com

K. Kulothungane-mail: kulo@auist.net

A. Kannane-mail: kannan@annauniv.edu

S. GanapathySchool of CSE, VIT University, Chennai Campus, Chennai, Indiae-mail: sganapathy@vit.ac.in

© Springer Nature Singapore Pte Ltd. 2019V. Nath and J. K. Mandal (eds.), Nanoelectronics, Circuits and CommunicationSystems, Lecture Notes in Electrical Engineering 511,https://doi.org/10.1007/978-981-13-0776-8_1

1

1 Introduction

In this work, an intelligent medical data mining system has been developed foreffective storage and retrieval of medical data with relevancy. For this purpose,classification algorithms from machine learning are used to perform effectivedecisions. From University of California, Irvine (UCI) repository breast and liverdatasets are collected. Data preprocessing is done on the real benchmark life sci-ences dataset to remove missing values. The preprocessed data is given as a input tovarious classification algorithms namely Navie Bayes (NB), Support VectorMachine (SVM), Differential Topic Modeling (DTM) [1] which uses LatentDirichlet Allocation (LDA) with SVM classification algorithm and finally with acombination of Naïve Bayes and temporal constraints with LDA (NBTC) which isthe newly designed technique which is proposed in this paper to mine medical datastorage system. To provide a system with user-friendly environment, a user inter-face with a facility to output clearly is provided in this system which displays themined results to the user with graphical output.

Topic modeling is considered in this work for organizing, analyzing, under-standing, and summarizing the textual documents related to medical applications.For this purpose, the topic modeling technique namely Latent Dirichlet Allocation(LDA) algorithm is used in this work for providing relevant list of topics by mainlyfocusing the retrieval of textual documents. In this model, each textual document isviewed as a mixture of topics. Moreover, LDA algorithm assigns topics of wordswith certain probabilities. In topic modeling, distribution of topics is combined toform documents and distribution of words is viewed as topics. R tool has beenemployed in this work for implementation of the proposed NBTC classifier whichgenerates word cloud with weight of the words. This word cloud is composed ofimages which contain words occurred in particular documents. Word cloud is usedto find the most occurred words in given corpus. High-frequency words are high-lighted in bold and bigger using word cloud. Using this, the relevant topics areretrieved from the text corpus and are given to the user. From the experimentconducted in this work, it is proved that the proposed model provides most relevantinformation to medical information seekers.

The rest of the paper is organized as follows: Sect. 2 deals with the LiteratureSurvey, Sect. 3 explains about the proposed Methodology, Sect. 4 describes thedetails of the proposed work, Sect. 5 explains about the results and discussions andSect. 6 provides conclusions on this work and suggests some suitable future works.

2 Literature Survey

There are many works on topic modeling, classification [2–4], and informationretrieval which are available in the literature [5–7]. Among them, Saranya et al. [5]proposed a new approach for effective storage and retrieval of medical data by

2 M. Selvi et al.

using intelligent techniques. Farid et al. [8] proposed an adaptive rule based clas-sifier for mining and extracting the relevant knowledge from biological datasets forproviding efficient diagnosis for health seekers. Nahato et al. [9] proposed aneffective classification model for classifying clinical datasets. This model enablesclassifier to predict presence or absence of a disorder from the clinical datasets.Back Propagation Neural Network (BPNN) is used in the classification model.Farid et al. [10] used Naive Bayesian is one of the popular algorithms in datamining and its main advantage is that the algorithm needs only one scan for trainingdata and also handles missing values. Lawrence et al. [11] compared traditionalClassification Tree Analysis (CTA) results to Stochastic Gradient Boosting(SGB) for remote sensing based datasets. Farid and Rahman [12] proposed amethod for weights assigned to each training instance in the training data thatimproves classification accuracy of the decision tree.

Liu and Yu [13] proposed a feature selection algorithm for classification andclustering. Feature selection algorithm is integrated with meta data to providedetailed description about classification system. Alghamdi and Alfalqi [14]explained four methods for analyzing the huge volume of unclassified text.Methodology includes Latent Semantic Analysis (LSA), Probabilistic LatentSemantic Analysis (PLSA), and Latent Dirichlet Allocation (LDA). Zeng et al. [15]used Belief Propagations (BP) in Latent Dirichlet allocation (LDA) for achievingbetter speed and accuracy in classifying large-scale document datasets.Author-Topic Models (ATM) using belief propagations (BP). Chen et al. [1] pro-posed a transformed Pitman-Yor Process (TPYP) to compare vocabulary similari-ties and dissimilarities between topics of two different document collections byusing differential topic model. Cheng et al. [16] proposed a Biterm Topic Model(BTM) for finding biterms that occur in the entire corpus. This will make the topicmodeling effectively.

3 Methodology

Figure 1 shows the overall view of the machine learning based probabilistic clas-sification approach for effective storage of medical records. From University ofCalifornia, Irvine (UCI) repository breast and liver datasets are collected. Datasetpreprocessing is done on the real benchmark life sciences dataset to remove missingvalues. Preprocessed data can be feed into Naive Bayes algorithm. Classified resultsare obtained using Naive Bayes algorithm. Knowledge discovery will be intimatedwhether it is true positive, true negative, false positive, and false negative valuesbased on the confusion matrix which allows visualizing the algorithm. Then theformula will be executed and will be displayed in graph mode.

In this work, LDA is used for topic modeling. The main focus of the LDA model[6, 7] is the distribution of words representing topics. In this model, mixture oftopics is viewed as documents and Bag of Words concept is also used in themodeling.

Classification of Medical Dataset Along with Topic … 3

4 Proposed Work

The proposed scheme consists of medical related topics which are collected andstored in medical database. Using Latent Dirichlet Allocation (LDA) based topicmodeling used to provide quick access to humans to visualize the topics which aremainly discussed in documents.

4.1 Document Topic Modeling

The most common and popular method for topic modeling is Latent DirichletAllocation (LDA). LDA is an algorithm which is used to generate topics withrelated keywords from the entire document. LDA discovers the topical patternsfrom the documents. From a collection of documents, we represent the frequentkeywords and assign those keywords to a particular topic. The topic modelingprocess developed in this work is shown in Fig. 2.

Topic modeling is efficiently used in this work to analyze large volumes of text.In this topic-based probabilistic generative model, words are distributed over topicsand topics are distributed over documents. In Natural Language Processing,

Fig. 1 Probabilistic basedclassification system

4 M. Selvi et al.

LDA plays an important role. Topic model is an unsupervised learning techniquewhich extracts the content from the raw and unlabeled data. Topics are generatedalong with the most likely and frequently occurring words. In this work, featureextraction is performed using LDA with temporal rules and the topics are classifiedusing the existing classification algorithms namely SVM, SVM with LDA, NB andthe proposed NBTC classifier which uses NB with LDA and temporal constraints. Itis proved through experiments that the proposed NBTC provides better classifi-cation accuracy when it is compared with the existing classification algorithmsdiscussed in this paper.

4.2 Word Cloud Generation

A word cloud is a text mining method that allows us to highlight the most fre-quently used keywords in a paragraph of texts. It is also referred to as a text cloud ortag cloud. The procedure of creating word cloud is very simple in R software if youknow the different steps to execute. A text mining package (tm) and word cloudgenerator package (word cloud) are available in R for helping us to analyze textsand to quickly visualize the keywords as a word cloud. Table 1 shows the distri-bution of data in University of California, Irvine (UCI) Repository.

Fig. 2 Topic modeling

Classification of Medical Dataset Along with Topic … 5

Table 2 shows the confusion matrix for the use of evaluation of the proposedmodel using the UCI repository.

5 Results and Discussions

From University of California, Irvine (UCI) repository breast and liver datasets arecollected for classification. Datasets consist of breast cancer and liver cancer textfile for experimenting topic modeling and word cloud generation. Figure 3 shows asample word cloud generation for breast cancer dataset.

This word cloud has been generated by running the entire corpus of preprocessedbreast cancer corpus. Moreover, the word cloud indicates the weights and fre-quently occurred words in the document. In this model, breast is the most frequentlyoccurring word as shown in Fig. 4.

Frequently occurring words have been plotted by using Word Plot in R tool. Itcan be performed by setting the minimum frequency limit as 100 so the wordswhich are repeated more than 100 times are listed. Breast is the medical term thatoccurs frequently in the entire corpus.

Figure 5 shows the list of topic generated from the breast cancer dataset. Thisdataset consists of breast cancer text file. Preprocessing involves removing stop

Table 1 Dataset collection from UCI repository

No. Dataset Instance No. of Attributes Attribute type Classes

1. Breast cancer 286 9 Nominal 2

2. Liver disorders 345 7 Numeric 2

Table 2 Confusion Matrix

Current = Predicted class True class False class

True class True positive (TP) False positive (FP)

False class True negative (TN) False negative (TN)

Fig. 3 Word cloudgeneration for breast cancerdataset

6 M. Selvi et al.

words from the documents. The topic of words with their probabilities value hasbeen generated.

Figure 6 shows the list of topics generated for liver dataset. This dataset consistsof liver cancer text file. Preprocessing involves removing stop words from thedocuments. The topic of words with their probabilities value has been generated.

Fig. 4 Plotting wordfrequencies for breast cancerdataset

Topic0: Treatment(0.044103) Breast(0.044103) treatment(0.044103) radiation(0.044103) patient(0.044103) Women(0.044103) increased(0.044103) different(0.029451) surgery(0.029451) cells(0.029451) breast(0.029451) tumors(0.029451)Topic1: factors(0.090679) cancer(0.05448) care(0.05448) oncology(0.05448) plan(0.03638) types(0.03638) grow(0.03638) causes(0.03638) women(0.018281) specializing(0.018281) medical(0.018281) treatments(0.018281) multidisciplinary(0.018281)Topic2: status(0.069595) health(0.046474) therapy(0.046474) hormone(0.046474) Cancer(0.023353) variety(0.023353) professionals(0.023353) nurses(0.023353) social(0.023353) workers(0.023353) pharmacists(0.023353) postmenopausal hormone(0.023353)Topic3: age(0.068718) breast cancer(0.068718) Chemotherapy(0.03453) radiationdestroy breast(0.03453) treatments(0.03453) healthy(0.03453) feel(0.03453) modified(0.03453) influenced(0.03453) capability(0.03453) spreading(0.03453) Topic4: change(0.066446) nipple(0.066446) disease(0.066446) counselors(0.033388) sore(0.033388) Mouth sores(0.033388) size(0.033388) shape(0.033388) Weight gain(0.033388) Family(0.033388) history(0.033388) relatives(0.033388)Topic5: breast(0.260042) cancer(0.176184) risk(0.151027) cancer(0.06717) increases(0.033627) diagnosed(0.025241) higher(0.025241) texture(0.00847) dimpling(0.00847) chances(0.00847) increase(0.00847) physical(0.00847)Topic6: risk(0.124472) alcohol(0.124472) use(0.124472) women(0.099627) armpit(0.049938) cancer cell(0.025093) cause(0.025093) breast cancer(0.025093) factors (0.025093) develops breast(0.025093) lump(0.025093) affects(0.025093)

Fig. 5 List of topicsgenerated for breast cancerdataset

Classification of Medical Dataset Along with Topic … 7

Figure 7 shows the word cloud which is generated by running the entire corpusof preprocessed liver corpus. Word cloud indicates the weights and frequentlyoccurred words in the document. Liver is the word most frequently occurred.

Frequently occurring words have been plotted in Fig. 8 by using Word Plot in Rtool. It was performed by setting the minimum frequency limit as 100 so the wordswhich are repeated more than 100 times are listed. Liver is the medical terms occurfrequently in the entire corpus.

Topic0: liver(0.20934) body(0.069935) hepatic(0.046701) blood(0.046701) human(0.046701) organ(0.023467) section(0.023467) recover(0.023467) Diabetes(0.023467) Topic1: pain(0.172521) discomfort(0.10365) clinical(0.069215) pain.(0.03478) swollen(0.03478) stage(0.03478) trials(0.03478) left(0.03478) Fatigue(0.03478)Topic2: tumor(0.063988) right(0.063988) cancers(0.04273) lung(0.04273) Cancer(0.021471) Symptoms(0.021471) Lasers(0.021471) Family(0.021471)Topic3: injected(0.051486) alcohol(0.051486) males(0.051486) females(0.051486) smoke(0.051486) Jaundice (0.025871) skin(0.025871) tongue(0.025871)Topic4: cancer(0.147099) liver(0.147099) risk(0.107899) hepatitis(0.039298) people(0.039298) higher(0.039298) developing(0.039298) individuals(0.029498) Liver(0.019698) Topic5: Side(0.062734) effects(0.062734) vomiting(0.062734) Liver(0.031523) Treatment(0.031523) Causes(0.031523) cancer(0.031523) treatment(0.031523)Topic6: liver(0.212798) cancer(0.191539) cells(0.04273) L-carnitine(0.04273) deficiency(0.04273) acetaminophen(0.04273) medication(0.021471) damaged(0.021471)

Fig. 6 List of topicsgenerated for liver dataset

Fig. 7 Generation of wordcloud for liver dataset

Fig. 8 Plotting wordfrequencies for liver dataset

8 M. Selvi et al.

Evaluation Metrics like Precision, Recall, Accuracy, F Measure, Specificity, andF1Score that are calculated for breast cancer class label 2 results are recorded inFig. 9.

EvaluationMetrics like Precision, Recall, Accuracy, FMeasure, Specificity, and F1Score that are calculated for breast cancer class label 4 results are recorded in Fig. 10.

Evaluation Metrics like Precision, Recall, Accuracy, F Measure, Specificity, andF1 Score that are calculated for liver disorders class label selector 1 results arerecorded in Fig. 11.

Fig. 9 Naive Bayes breastcancer class2 results

Fig. 10 Naive Bayes breastcancer class4 results

Fig. 11 Naive Bayes liverdisorders selector 1 results

Classification of Medical Dataset Along with Topic … 9

Evaluation Metrics like Precision, Recall, Accuracy, F Measure, Specificity, andF1 Score that are calculated for liver disorders class label selector 2 results arerecorded in Fig. 12.

Figure 13 shows the accuracy analysis based on the comparison of the proposedNBTC with the existing classification techniques namely SVM, SVM with LDA,and Naïve Bayes classifier.

From Fig. 13, it can be observed that the proposed NBTC algorithm providesbetter classification accuracy due to the use of LDA and temporal constraints withNaïve Bayes classifier.

6 Conclusion

In this paper, a machine learning approach to classify medical dataset has beenproposed for effective analysis by combining Naïve Bayes classifier with LDA andtemporal constraints. In addition, this model uses topic modeling techniques todisplay the list of topics from the textual documents stored in corpus. Moreover,patterns of words are measured by considering them as latent topics which areretrieved from large collection of documents that are designed to automaticallyorganize using LDA technique. Word cloud has been generated for textual docu-ments in order to provide effective storage. The data set has been analyzed using

Fig. 12 Naive Bayes liverdisorders selector 2 results

020406080

100

E1 E2 E3 E4 E5

Cla

ssif

icat

ion

Acc

urac

y (%

)

Experiment Number

Classification Accuracy Analysis

SVM

DTM(SVM+LDA)

NB

NBTC

Fig. 13 Classificationaccuracy comparison analysis

10 M. Selvi et al.

classification algorithms and proved that the proposed model performs betterdecision-making when it is compared with the existing systems.

References

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