MASTER OF TECHNOLOGY IN CSE /COMPUTER ENGINEERING …geetaengineeringcollege.in/wp-content/uploads/2018/10/M.-Tech.-CS… · Part-I 0 0 20 10 -- 100 100 -- 10 Total 120 180 300 16

MASTER OF TECHNOLOGY IN CSE /COMPUTER ENGINEERING SEMESTER-III

S. No.

Course Code

Subject Teaching Schedule

Hours/Week Examination Schedule & Percentage Distribution

Duration of Exam

(Hrs.)

Credit

L T P

Major Test

Minor Test

Total

1 * Program

Elective -V 3 0 0 03

60 40 100 3 3

2 ** Open

Elective 3 0 0 03

60 40 100 3 3

3 MTCE-207A

Dissertation Part-I

0 0 20 10 -- 100 100 -- 10

Total 120 180 300 16

*Program Elective-V

Course No. Subject

MTCE-201A Object Oriented Software System Design

MTCE-203A Big Data Analytics

MTCE-205A Digital Image Processing

**Open Elective

1. MTOE-201A Business Analytics

2. MTOE-203A Industrial Safety

3. MTOE-205A Operations Research

4. MTOE-207A Cost Management of Engineering Projects

5. MTOE-209A Composite Materials

6. MTOE-211A Waste to Energy

MTCE-201A Object Oriented Software System Design

Lecture Tutorial Practical Credit Major Test Minor Test Total Time

3 0 0 3 60 40 100 3 Hrs.

Program

Objective

(PO)

To provide the thorough knowledge to use the concepts and their design attributes for object based system

design and their related paradigms to foster better communication and product quality in order to solve the

real time problems by applying the object oriented pattern and visual modeling throughout the software

development life cycles.

Course Outcomes (CO)

CO1 To learn the basic concepts of object oriented design and methods and also to get exposure of UML for

analyzing and designing quality software systems.

CO2 To explore the details of object-oriented software development methods using use cases, relations,

responsibilities, interface objects, services and system design and object-oriented methodologies for choosing

and designing effective and time critical software systems.

CO3 To realize the nature of design patterns by understanding and identifying design model, components, software

behavior, Methodology for Object-Oriented Design (MOOD), and reusability and Life Cycle issues to create

naturalized object oriented design.

CO4 To evaluate object oriented design processes using software maintenance process, configuration

management and maintenance models to articulate better software system for performing required tasks.

Unit 1: Introduction, Methods and Concepts

Introduction: Object oriented concepts, Object-oriented domain analysis, software reuse, software life cycle models, unified modeling language (UML). Object-oriented methods (OOM): Overview, Goals, Concepts: Object analysis model, Information model. Behavior model, Process model, Requirements definition model, benefits and weaknesses.

Unit 2: Object-Oriented Software Development Methods and Methodologies Object-oriented software development methods: ObjectOry: System development and analysis, use cases, entities, interface objects, services and system design, advantages, Introduction to Object-oriented structured design and application examples. Object-oriented Methodologies: Classification, Rumbaugh methodology, Jacobson methodology, Booch methodology, Responsibility-Driven design, Pun and Winder methodology, Shlaer/Mellor methodology.

Unit 3: Object-Oriented Design, Reusability and Life Cycle Issues Object-Oriented Design: Representation of design model, Identification of components, classes, inheritance and objects, Identification of software behavior, Suitability of Methodology for Object-Oriented Design (MOOD), Context of MOOD, A CASE environment for MOOD, MOOD tools. Reusability and Life Cycle Issues: Reusability during Object-Oriented design, Object-Oriented software life cycle model, Software life cycle issues.

Unit 4: Software Maintenance Concepts and Object-Oriented Programming Languages Software Maintenance Concepts: Software maintenance process, Reverse engineering environment, Documentation for Software maintenance, Software configuration management and Software maintenance models. Object-Oriented Programming Languages: Simula, SmallTalk, Ada95, Object COBOL. Text Books: 1. Jag Sodhi, Prince Sodhi, Object-Oriented Methods for Software Development, McGraw-Hill. 2. Luiz Fernando Capretz, Miriam A M Captrez, Object-Oriented Software: Design and Maintenance, World Scientific. 3. Luiz Fernando Capretz, Object-Oriented Design Methodologies for Software Systems, Ph.D. Thesis, University of

Newcastle upon Tyne, United Kingdom, November 1991. Available Online at: https://theses.ncl.ac.uk/dspace/bitstream/10443/1967/1/Capretz,%20L.F.%201991.pdf

4. Ali Bahrami, Object Oriented Systems Development: McGraw Hill, 1999. 5. Rumbaughet al.,Object Oriented Modeling and Design, PHI, 1997 . 6. Wendy Boggs, Michael Boggs, Mastering UML with Rational Rose, Sybex BPB Publications, 2007. Reference Books: 1 Object-Oriented Analysis and Design with Applications (3rd Edition) 3rd Edition, Grady Booch, Robert A. Maksimchuk,

Michael W. Engle, Bobbi J. Young, Jim Conallen, Kelli A. Houston, Addison-Wesley, 2007 2. Design Patterns: Elements of Reusable Object-Oriented Software, Erich Gamma, Richard Helm, Ralph Johnson, John

Vlissides, 1st Edition, , Addison-Wesley, 2007

3. Refactoring: Improving the Design of Existing Code (Addison-Wesley Object Technology Series), Martin Fowler, Kent Beck, John Brant, William Opdyke, Don Roberts, Erich Gamma, Addison-Wesley, 2007

4. Object Oriented Analysis and Design: Understanding System Development with UML 2.0, Mike O’ Docherty, Wiley India, 2010.

MTCE-203A Big Data Analytics

Lecture Tutorial Practical Credit Major Test Minor Test Practical Total Time

4 0 0 4 60 40 -- 100 3 Hrs.

Program Objective (PO)

Understand big data for business intelligence. Learn business case studies for big data analytics. Understand NoSQL big data management. Perform map-reduce analytics using Hadoop and related tools


CO1 Understand the basics of big data

CO2 Understand the detailed explanation of NoSQL

CO3 Analysing the data with Hadoop and learn the MapReduce

CO4 Description on Hbase, Pig and Hive

Unit 1

What is big data, why big data, convergence of key trends, unstructured data, industry examples of big data, web analytics, big data and marketing, fraud and big data, risk and big data, credit risk management, big data and algorithmic trading, big data and healthcare, big data in medicine, advertising and big data, big data technologies, introduction to Hadoop, open source technologies, cloud and big data, mobile business intelligence, Crowd sourcing analytics, inter and trans firewall analytics.

Unit 2

Introduction to NoSQL, aggregate data models, aggregates, key-value and document data models, relationships, graph databases, schema less databases, materialized views, distribution models, sharding, master-slave replication, peer replication, sharding and replication, consistency, relaxing consistency, version stamps, map-reduce, partitioning and combining, composing map-reduce calculations.

Unit 3

Data format, analyzing data with Hadoop, scaling out, Hadoop streaming, Hadoop pipes, design of Hadoop distributed file system (HDFS), HDFS concepts, Java interface, data flow, Hadoop I/O, data integrity, compression, serialization, Avro, file-based data structures MapReduce workflows, unit tests with MRUnit, test data and local tests, anatomy of MapReduce job run, classic Map-reduce, YARN, failures in classic Map-reduce and YARN, job scheduling, shuffle and sort, task execution, MapReduce types, input formats, output formats

Unit 4

Hbase, data model and implementations, Hbase clients, Hbase examples, praxis.Cassandra, Cassandra data model, Cassandra examples, Cassandra clients, Hadoop integration. Pig, Grunt, pig data model, Pig Latin, developing and testing Pig Latin scripts. Hive, data types and file formats, HiveQL data definition, HiveQL data manipulation, HiveQL queries.

References: 1. Michael Minelli, Michelle Chambers, and AmbigaDhiraj, "Big Data, Big Analytics: Emerging 2. Business Intelligence and Analytic Trends for Today's Businesses", Wiley, 2013. 3. P. J. Sadalage and M. Fowler, "NoSQL Distilled: A Brief Guide to the Emerging World of 4. Polyglot Persistence", Addison-Wesley Professional, 2012. 5. Tom White, "Hadoop: The Definitive Guide", Third Edition, O'Reilley, 2012. 6. Eric Sammer, "Hadoop Operations", O'Reilley, 2012. 7. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012. 8. Lars George, "HBase: The Definitive Guide", O'Reilley, 2011. 9. Eben Hewitt, "Cassandra: The Definitive Guide", O'Reilley, 2010. 10. Alan Gates, "Programming Pig", O'Reilley, 2011.

MTCE-205A Digital Image Processing


4 0 0 4 60 40 100 3Hrs.

Program Objective

(PO)

Introduces the working knowledge of how digital image processing is implemented by using various algorithms and also the various techniques of transformation, enhancement, restoration, compression, segmentation and image morphology.


CO1 Knowledge in the science of images and image processing.

CO2 To apply knowledge of mathematics, science and engineering in the area of computer vision.

CO3 knowledge in the techniques of Digital Image Processing, including Image Enhancement in the Spatial and Frequency Domain, Compression, Morphology and Segmentation.

CO4 Learn and apply knowledge in analyzing image segmentation, representation, description, and recognition techniques.

CO5 Design and implement computer vision systems to detect, localize and recognize objects within images.

Unit 1

Introduction And Digital Image Fundamentals: The origins of Digital Image Processing, Examples of Fields that Use Digital Image Processing, Fundamentals Steps in Image Processing, Elements of Digital Image Processing Systems, Image Sampling and Quantization, Some basic relationships like Neighbours, Connectivity, Distance Measures between pixels, Linear and Non Linear Operations.

Unit 2

Image Enhancement in the Spatial Domain: Some basic Gray Level Transformations, Histogram Processing, Enhancement Using Arithmetic and Logic operations, Basics of Spatial Filters, Smoothening and Sharpening Spatial Filters, Combining Spatial Enhancement Methods. Image Enhancement in the Frequency Domain: Introduction to Fourier Transform and the frequency Domain, Smoothing and Sharpening Frequency Domain Filters, Homomorphic Filtering.

Unit 3

Image Restoration:A model of The Image Degradation / Restoration Process, Noise Models, Restoration in the presence of Noise Only Spatial Filtering, Pereodic Noise Reduction by Frequency Domain Filtering, Linear Position-InvarientDedradations, Estimation of Degradation Function, Inverse filtering, Wiener filtering, Constrained Least Square Filtering, Geometric Mean Filter, Geometric Transformations. Image Compression: Coding, Interpixel and Psychovisual Redundancy, Image Compression models, Elements of Information Theory, Error free comparison, Lossy compression, Image compression standards.

Unit 4

Image Segmentation:Detection of Discontinuities, Edge linking and boundary detection, Thresholding, Region Oriented Segmentation, Motion based segmentation. Representation and Description: Representation, Boundary Descriptors, Regional Descriptors, Use of Principal Components for Description, Introduction to Morphology, Some basic Morphological Algorithms. Object Recoginition: Patterns and Pattern Classes, Decision-Theoretic Methods, Structural Methods. Text Books: 1 Rafael C. Gonzalez & Richard E. Woods, “Digital Image Processing”, 2nd edition, Pearson Education, 2004. 2 A.K. Jain, “Fundamental of Digital Image Processing”, PHI, 2003. Reference Books: 1 RosefieldKak, “Digital Picture Processing”, 1999.

1. W.K. Pratt, “Digital Image Processing”, 2000.

MTOE-201A Business Analytics


3 0 0 3 60 40 100 3 Hrs.


The main objective of this course is to give the student a comprehensive understanding of business analytics methods.


CO1 Able to have knowledge of various business analysis techniques.

CO2 Learn the requirement specification and transforming the requirement into different models.

CO3 Learn the requirement representation and managing requirement assests.

CO4 Learn the Recent Trends in Embedded and collaborative business

Unit 1

Business Analysis: Overview of Business Analysis, Overview of Requirements, Role of the Business

Analyst. Stakeholders: the project team, management, and the front line, Handling, Stakeholder Conflicts.

Life Cycles: Systems Development Life Cycles, Project Life Cycles, Product Life Cycles, Requirement Life Cycles.

Unit 2

Forming Requirements: Overview of Requirements Attributes of Good Requirements, Types of Requirements, Requirement Sources, Gathering Requirements from Stakeholders, Common Requirements Documents.

Transforming Requirements: Stakeholder Needs Analysis, Decomposition Analysis, Additive/Subtractive Analysis, Gap Analysis, Notations (UML & BPMN), Flowcharts, Swim Lane Flowcharts, Entity-Relationship Diagrams, State-Transition Diagrams, Data Flow Diagrams, Use Case Modeling, Business Process Modeling

Unit 3

Finalizing Requirements: Presenting Requirements, Socializing Requirements and Gaining Acceptance, Prioritizing Requirements.

Managing Requirements Assets: Change Control, Requirements Tools

Unit 4

Recent Trends in: Embedded and collaborative business intelligence, Visual data recovery, Data Storytelling and Data Journalism.

References:

1. Business Analysis by James Cadle et al.

2. Project Management: The Managerial Process by Erik Larson and, Clifford Gray

MTOE-203A Industrial Safety


3 0 0 3 60 40 100 3 Hrs.


To enable students to aware about the industrial safety.


CO1 Understand the industrial safety.

CO2 Analyze fundamental of maintenance engineering.

CO3 Understand the wear and corrosion and fault tracing.

CO4 Understanding that when to do periodic inceptions and apply the preventing maintenance.

Unit-1

Industrial safety: Accident, causes, types, results and control, mechanical and electrical hazards, types, causes and preventive steps/procedure, describe salient points of factories act 1948 for health and safety, washrooms, drinking water layouts, light, cleanliness, fire, guarding, pressure vessels, etc, Safety color codes. Fire prevention and firefighting, equipment and methods.

Fundamentals of maintenance engineering: Definition and aim of maintenance engineering, Primary and secondary functions and responsibility of maintenance department, Types of maintenance, Types and applications of tools used for maintenance, Maintenance cost & its relation with replacement economy, Service life of equipment.

Unit-2

Wear and Corrosion and their prevention: Wear- types, causes, effects, wear reduction methods, lubricants-types and applications, Lubrication methods, general sketch, working and applications, i. Screw down grease cup, ii. Pressure grease gun, iii. Splash lubrication, iv. Gravity lubrication, v. Wick feed lubrication vi. Side feed lubrication, vii. Ring lubrication, Definition, principle and factors affecting the corrosion. Types of corrosion, corrosion prevention methods.

Unit-3

Fault tracing: Fault tracing-concept and importance, decision treeconcept, need and applications, sequence of fault finding activities, show as decision tree, draw decision tree for problems in machine tools, hydraulic, pneumatic,automotive, thermal and electrical equipment’s like, I. Any one machine tool, ii. Pump iii. Air compressor, iv. Internal combustion engine, v. Boiler, vi. Electrical motors, Types of faults in machine tools and their general causes.

Unit-4

Periodic and preventive maintenance: Periodic inspection-concept and need, degreasing, cleaning and repairing schemes, overhauling of mechanical components, overhauling of electrical motor, common troubles and remedies of electric motor, repair complexities and its use, definition, need, steps and advantages of preventive maintenance. Steps/procedure for periodic and preventive maintenance of: I. Machine tools, ii. Pumps, iii. Air compressors, iv. Diesel generating (DG) sets Program and schedule of

preventive maintenance of mechanical and electrical equipment, advantages of preventive maintenance. Repair cycle concept and importance

Reference: 1. Maintenance Engineering Handbook, Higgins & Morrow, Da Information Services. 2. Maintenance Engineering, H. P. Garg, S. Chand and Company. 3. Pump-hydraulic Compressors, Audels, Mcgrew Hill Publication. 4. Foundation Engineering Handbook, Winterkorn, Hans, Chapman & Hall London.

MTOE-205A Operations Research


3 0 0 3 60 40 100 3 Hrs.


To enable students to aware about the dynamic programming to solve problems of discreet and continuous variables and model the real world problem and simulate it.


CO1 Students should able to apply the dynamic programming to solve problems of discreet and continuous variables.

CO2 Students should able to apply the concept of non-linear programming

CO3 Students should able to carry out sensitivity analysis

CO4 Student should able to model the real world problem and simulate it.

Unit -1

Optimization Techniques, Model Formulation, models, General L.R Formulation, Simplex Techniques, Sensitivity Analysis, Inventory Control Models

Unit -2

Formulation of a LPP - Graphical solution revised simplex method - duality theory - dual simplex method - sensitivity analysis - parametric programming

Nonlinear programming problem - Kuhn-Tucker conditions min cost flow problem - max flow problem - CPM/PERT

Unit- 3

Scheduling and sequencing - single server and multiple server models - deterministic inventory models - Probabilistic inventory control models - Geometric Programming.

Unit -4

Competitive Models, Single and Multi-channel Problems, Sequencing Models, Dynamic Programming, Flow in Networks, Elementary Graph Theory, Game Theory Simulation

References:

1. H.A. Taha, Operations Research, An Introduction, PHI, 2008 2. H.M. Wagner, Principles of Operations Research, PHI, Delhi, 1982. 3. J.C. Pant, Introduction to Optimisation: Operations Research, Jain Brothers, Delhi, 2008 4. Hitler Libermann Operations Research: McGraw Hill Pub. 2009 5. Pannerselvam, Operations Research: Prentice Hall of India 2010 6. Harvey M Wagner, Principles of Operations Research: Prentice Hall of India 2010

MTOE-207A Cost Management of Engineering Projects


3 0 0 3 60 40 100 3 Hrs.


To enable students to make aware about the cost management for the engineering project and apply cost models the real world projects.


CO1 Students should able to learn the strategic cost management process.

CO2 Students should able to types of project and project team types

CO3 Students should able to carry out Cost Behavior and Profit Planning analysis.

CO4 Student should able to learn the quantitative techniques for cost management.

Unit-1

Introduction and Overview of the Strategic Cost Management Process Cost concepts in decision-making; relevant cost, Differential cost, Incremental cost and Opportunity cost.Objectives of a Costing System; Inventory valuation; Creation of a Database for operational control; Provision of data for Decision-Making.

Unit-2

Project: meaning, Different types, why to manage, cost overruns centres, various stages of project execution: conception to commissioning. Project execution as conglomeration of technical and nontechnical activities.Detailed Engineering activities. Pre project execution main clearances and documents Project team: Role of each member. Importance Project site: Data required with significance. Project contracts.Types and contents. Project execution Project cost control. Bar charts and Network diagram. Project commissioning: mechanical and process

Unit-3

Cost Behavior and Profit Planning Marginal Costing; Distinction between Marginal Costing and Absorption Costing; Break-even Analysis, Cost-Volume-Profit Analysis. Various decision-making problems.Standard Costing and Variance Analysis. Pricing strategies: Pareto Analysis. Target costing, Life Cycle Costing. Costing of service sector.Just-in-time approach, Material Requirement Planning, Enterprise Resource Planning, Total Quality Management and Theory of constraints.Activity-Based Cost Management, Bench Marking; Balanced Score Card and Value-Chain Analysis.Budgetary Control; Flexible Budgets; Performance budgets; Zero-based budgets.Measurement of Divisional profitability pricing decisions including transfer pricing.

Unit-4

Quantitative techniques for cost management, Linear Programming, PERT/CPM, Transportation problems, Assignment problems, Simulation, Learning Curve Theory.

References:

1. Cost Accounting A Managerial Emphasis, Prentice Hall of India, New Delhi 2. Charles T. Horngren and George Foster, Advanced Management Accounting 3. Robert S Kaplan Anthony A. Alkinson, Management & Cost Accounting 4. Ashish K. Bhattacharya, Principles & Practices of Cost Accounting A. H. Wheeler publisher 5. N.D. Vohra, Quantitative Techniques in Management, Tata McGraw Hill Book Co. Ltd.

MTOE-209A Composite Materials


3 0 0 3 60 40 100 3 Hrs.


To enable students to aware about the composite materials and their properties.


CO1 Students should able to learn the Classification and characteristics of Composite materials.

CO2 Students should able reinforcements Composite materials.

CO3 Students should able to carry out the preparation of compounds.

CO4 Student should able to do the analysis of the composite materials.

UNIT–1:

INTRODUCTION: Definition – Classification and characteristics of Composite materials. Advantages and application of composites.Functional requirements of reinforcement and matrix.Effect of reinforcement (size, shape, distribution, volume fraction) on overall composite performance.

REINFORCEMENTS: Preparation-layup, curing, properties and applications of glass fibers, carbon fibers, Kevlar fibers and Boron fibers. Properties and applications of whiskers, particle reinforcements. Mechanical Behavior of composites: Rule of mixtures, Inverse rule of mixtures. Iso-strain and Iso-stress conditions.

UNIT – 2

Manufacturing of Metal Matrix Composites: Casting – Solid State diffusion technique, Cladding – Hot isostaticpressing.Properties and applications. Manufacturing of Ceramic Matrix Composites: Liquid Metal Infiltration – Liquid phase sintering. Manufacturing of Carbon – Carbon composites: Knitting, Braiding, Weaving. Properties and applications.

UNIT–3

Manufacturing of Polymer Matrix Composites: Preparation of Moulding compounds and prepregs – hand layup method – Autoclave method – Filament winding method – Compression moulding – Reaction injection moulding. Properties and applications.

UNIT – 4

Strength: Laminar Failure Criteria-strength ratio, maximum stress criteria, maximum strain criteria, interacting failure criteria, hygrothermal failure. Laminate first play failure-insight strength; Laminate strength-ply discount truncated maximum strain criterion; strength design using caplet plots; stress concentrations.

TEXT BOOKS:

1. Material Science and Technology – Vol 13 – Composites by R.W.Cahn – VCH, West Germany. 2. Materials Science and Engineering, An introduction. WD Callister, Jr., Adapted by R. 3. Balasubramaniam, John Wiley & Sons, NY, Indian edition, 2007.

References:

1. Hand Book of Composite Materials-ed-Lubin. 2. Composite Materials – K.K.Chawla. 3. Composite Materials Science and Applications – Deborah D.L. Chung. 4. Composite Materials Design and Applications – Danial Gay, Suong V. Hoa, and Stephen W. Tasi.

MTOE-211A Waste to Energy


3 0 0 3 60 40 100 3 Hrs.


To enable students to aware about the generation of energy from the waste.


CO1 Students should able to learn the Classification of waste as a fuel.

CO2 Students should able to learn the Manufacture of charcoal.

CO3 Students should able to carry out the designing of gasifiers and biomass stoves.

CO4 Student should able to learn the Biogas plant technology.

Unit-1

Introduction to Energy from Waste: Classification of waste as fuel – Agro based, Forest residue, Industrial waste - MSW – Conversion devices – Incinerators, gasifiers, digestors

Biomass Pyrolysis: Pyrolysis – Types, slow fast – Manufacture of charcoal – Methods - Yields and application – Manufacture of pyrolytic oils and gases, yields and applications.

Unit-2

Biomass Gasification: Gasifiers – Fixed bed system – Downdraft and updraft gasifiers – Fluidized bed gasifiers – Design, construction and operation – Gasifier burner arrangement for thermal heating – Gasifier engine arrangement and electrical power – Equilibrium and kinetic consideration in gasifier operation.

Unit-3

Biomass Combustion: Biomass stoves – Improved chullahs, types, some exotic designs, Fixed bed combustors, Types, inclined grate combustors, Fluidized bed combustors, Design, construction and operation - Operation of all the above biomass combustors.

Unit-4

Biogas: Properties of biogas (Calorific value and composition) - Biogas plant technology and status - Bio energy system - Design and constructional features - Biomass resources and their classification - Biomass conversion processes - Thermo chemical conversion - Direct combustion - biomass gasification - pyrolysis and liquefaction - biochemical conversion - anaerobic digestion - Types of biogas Plants – Applications - Alcohol production from biomass - Bio diesel production - Urban waste to energy conversion - Biomass energy programme in India.

References:

1. Non Conventional Energy, Desai, Ashok V., Wiley Eastern Ltd., 1990. 2. Biogas Technology - A Practical Hand Book - Khandelwal, K. C. and Mahdi, S. S., Vol. I & II, Tata

McGraw Hill Publishing Co. Ltd., 1983. 3. Food, Feed and Fuel from Biomass, Challal, D. S., IBH Publishing Co. Pvt. Ltd., 1991.

4. Biomass Conversion and Technology, C. Y. WereKo-Brobby and E. B. Hagan, John Wiley & Sons, 1996. 5.

6.

7.

Dissertation Part-I (MTCE-207A) and Dissertation Part-II (MTCE-202A)


CO1 Ability to synthesize knowledge and skills previously gained and applied to an in depth study and execution of new technical problem.

CO2 Capable to select from different methodologies, methods and forms of analysis to produce a suitable research design, and justify their design.

CO3 Ability to present the findings of their technical solution in a written report. CO4 Presenting the work in International/ National conference or reputed journals.

8. 9. Syllabus Contents: 10. The dissertation / project topic should be selected / chosen to ensure the satisfaction of the urgent need to establish a direct link between education, national development and productivity and thus reduce the gap between the world of work and the world of study. The dissertation should have the following: 11. Relevance to social needs of society 12. Relevance to value addition to existing facilities in the institute 13. Relevance to industry need 14. Problems of national importance 15. Research and development in various domain. 16. 17. The student should complete the following: 18. Literature survey Problem Definition 19. Motivation for study and Objectives 20. Preliminary design / feasibility / modular approaches 21. Implementation and Verification 22. Report and presentation 23. The dissertation part- II is based on a report prepared by the students on dissertation allotted to them. It may be based on: 24. Experimental verification / Proof of concept. 25. The viva-voce examination will be based on the above report and work. 26. 27. Guidelines for Dissertation Part – I and II 28. As per the AICTE directives, the dissertation is an yearlong activity, to be carried out and evaluated in two parts i.e. Part– I: July to December and Part– II: January to June. 29. The dissertation may be carried out preferably in-house i.e. department’s laboratories and centers OR in industry allotted through department’s T & P coordinator. 30. After multiple interactions with guide and based on comprehensive literature survey, the student shall identify the domain and define dissertation objectives. 31. The referred literature should preferably include IEEE/IET/IETE/Springer/Science Direct/ACM journals in the areas of Computing Engineering and any other related domain. In case of Industry sponsored projects, the relevant application notes, white papers, product catalogues should be referred and reported. 32. Student is expected to detail out specifications, methodology, resources required, critical issues involved in design and implementation and phase wise work distribution, and submit the proposal within a month from the date of registration.

33. Part–I deliverables: A document report comprising of summary of literature survey, detailed objectives, project specifications, paper, proof of concept/functionality, part results, and record of continuous progress. 34. Part–I evaluation: A committee comprising of guides of respective specialization shall assess the progress/performance of the student based on report, presentation and Q & A. In case of unsatisfactory performance, committee may recommend repeating the Part-I work. 35. During Part– II, student is expected to exert on design, development and testing of the proposed work as per the schedule. Accomplished results/contributions/innovations should be published in terms of research papers in reputed journals and reviewed focused conferences OR IP/Patents. 36. Part–II deliverables: A dissertation report as per the specified format, developed system in the form of hardware and/or software, and record of continuous progress. 37. Part-II evaluation: Guide along with appointed external examiner shall assess the progress/performance of the student based on report, presentation and Q & A. In case of unsatisfactory performance, committee may recommend for extension or repeating the Part-I work. 38.

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