Syllabus forstc.ac.in/syllabus/2015-2016/M.Sc_Computer_Science.pdfSyllabus for M.Sc ( COMPUTER SCIENCE ) 2015 – 2016 Batch Knowledge Wisdom Compassion SREE SARASWATHI THYAGARAJA

Syllabus for

M.Sc ( COMPUTER SCIENCE )

2015 – 2016 Batch

Knowledge Wisdom Compassion

SREE SARASWATHI THYAGARAJA COLLEGE

An Autonomous, NAAC Re-Accredited with 'A' Grade, ISO – 9001:2008 Certified Institution, Affiliated to Bharathiar University, Coimbatore, Approved by AICTE for MBA/MCA and by UGC for 2(f) & 12(B) status, Thippampatti, Palani Road, Pollachi - 642 107, Coimbatore Dt., Tamil Nadu,

Tel.: 04259-266008, 266550, Tele Fax: 04259-266009, Email: [email protected], Website: www.stc.ac.in

PERSONAL MEMORANDA 1. Register Number :

2. Name :

3. Class :

4. Father’s Name and Occupation :

5. Permanent Residential Address : …………………………………………..

…………………………………………..

…………………………………………..

PIN …………………………………………..

6. Residential Phone No : STD Code …………………………………………..

: Phone No …………………………….................

: Mobile No …………………………………………..

7. Temporary Address : …………………………………………..

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8. Temporary Phone No : STD Code ………………………………………….

: Phone No ……………………………................

: Mobile No ………………………………………….

9. Day Scholar / Hosteller :

10. Blood Group :

INDEX

Page No.

1. Scheme of Examinations & Syllabus

a. Scheme of Examinations I-III

b. Semester-wise Syllabus 01-42

2. Autonomous Examination System and Regulations

a. Examination Regulations 43-52

b. Grievance Form 53

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1. Scheme of Examination and Syllabus

I

SREE SARASWATHI THYAGARAJA COLLEGE [AUTONOMOUS], POLLACHI

Scheme of Examinations and Syllabi for M.Sc Computer Science (CBCS)

with effect from 2015-16 Batch

Batch Code: N5 Medium of Instruction: English

Programme Code: MCS

S.No Spl Code Part Sem Course Hours Credits Int Ext Total 1 Z N5MCS1T11 III I Core1: Advanced Software Engineering 5 4 25 75 100

2 Z N5MCS1T52 III I Core2: Advanced Java Programming 5 4 25 75 100 3 Z N5MCS1T43 III I Core3: Advanced Microprocessor and Microcontroller 5 4 25 75 100 5 Z N5MCS1T54 III I Core4: Distributed Operating System 5 4 25 75 100 6 A N5MCS1T45 III I Elective I 4 4 25 75 100 7 Z N5MCS1P56 III I Core 5:Practical: Advanced Java Programming Lab 4 4 40 60 100 Library 2 Extra Hours & Credits 8 Z N5MCS1T57 IV I Yoga for the Modern Age** 3 1 50 - 50

9 Z N5MCS2T51 III II Core6: Web Technology 4 4 25 75 100 10

Z N5MCS2T42 III

II Core7: Computer

Architecture and Parallel Processing 4 4 25 75 100

11 Z N5MCS2T53 III II Core8: Software Testing 4 4 25 75 100 12 A N5MCS2T54 III II Elective II 4 4 25 75 100

13 Z N5MCS2P55 III II Core 9:Practical: Web Technology Lab 4 4 40 60 100

14 Z N5MCS2P46 III II Core10: Practical: Linux Lab 4 3 40 60 100

15 Z N5MCS2P57 III II Core11: Practical: Software Testing Lab 4 4 40 60 100

Library 2 Extra Hours & Credits

16 Z N5MCS2T18 IV II Communication for executives** 4 2 25 75 100

17 Z N5MCS3T51 III III Core 12: Software Quality Assurance 4 4 25 75 100 18 Z N5MCS3T42 III III Core 13: Information Security 4 4 25 75 100

II

19 Z N5MCS3T53 III III Core 14: Data Mining and Warehousing 4 4 25 75 100 20 A N5MCS3T44 III III Elective III 4 4 25 75 100 21 A N5MCS3T55 III III Elective IV 4 4 25 75 100 22 Z N5MCS3P56 III III Core 15: Practical: Software Quality Assurance Lab 4 4 40 60 100 23 Z N5MCS3P57 III III Core 16:Practical: Data Mining Lab 4 3 40 60 100 Library 2

Extra Hours & Credits 24 Z N5MCS3T58 IV III Quantitative Aptitude & Verbal Reasoning** 5 2 100 - 100 25 Z N5MCS3R49 IV III Internship

# - 2 50 50

26 A N5MCS4T41 III IV Elective V 4 4 25 75 100 27 Z N5MCS4R22 III IV Core 17: Project Work* - 8 40 60 100 Extra Hours & Credits

28 Z N5MCS4T23 IV IV Professional Ethics** 3 1 50 - 50

90 + 8

(Extra) 2200+350

** These are the courses which are conducted during the special hours with extra credits. Extra Credits were not included for classification.

# Internship, an extra credit course carries 50 Marks 80% for evaluation and 20% for viva evaluation jointly done by both internal and external.

* Project carries 100 marks. (40 marks for internal (based on I , II and Final Review) and 60 marks for External evaluation jointly done by both

internal and external.

List of Electives

Elective I Elective II Elective III

Mobile Computing Cloud Computing Digital Image Processing

Embedded System Advanced Network Concepts Genetic Algorithm

Distributed Database System AI and Expert System Artificial Neural Networks

III

Elective IV Elective V

______ Cybercrime and Cyber Law Pattern Recognition

Multimedia Bioinformatics

Big Data Analytics Robot Technology

CLASSIFICATION OF TOTAL CREDITS:90

SL.NO NUMBER OF COURSES TOTAL CREDITS

1 CORE 17 70

2 ELECTIVE 5 20

3 EXTRA CREDITS 5 8

Expansion of the titles

Spl : Z for compulsory one and A to X for alternatives (shall be indicated along with code connected by a hyphen mark)

Code : Code number for each of the course

Part : I to V for the UG programs and blank space for PG programs

Sem : I to X for first semester to last semester (six for UG programs and four/six/ten for PG program)

Course : Title of the paper

Hours : Contact allocated for each course

Credits : Credit weightage allocated for each course and total for each program

Int : Maximum internal marks allocated for each course

Ext : Maximum external marks allocated for each course

Total : Maximum total marks allocated for each course

1

SEMESTER-I

ADVANCED SOFTWARE ENGINEERING

Credits:4 Course Code : N5MCS1T11

Total Instructional Hours:60

Course objectives: This course presents the introduction to software engineering, applying web engineering,

Project management and specifications.

Skill sets to be acquired: On successful completion of the course the students would have the knowledge about

software engineering, web engineering and component based development.

Unit I 12 Hrs Introduction to software engineering: The evolving role of software – the changing nature of

software – software myths – a process frame work – process technology – process model –

agile process model.

Self-study: Software Myths

Unit II 12 Hrs Applying web engineering: Attributes of web based systems and applications – webapp

engineering layers – process – practices – web based systems – planning web engineering

projects – team issues – requirement analysis for webapp – models – architecture design –

object oriented hyper media design method – testing.

Self-study: Team Issues

Unit III 12 Hrs Project management : The management spectrum – estimation – resources – decomposition

techniques – empirical estimation models – project scheduling – defining the tasks – risk

management – quality management – concepts – assurance – reviews – change management

– software configuration management – the SCM process.

Self-study: Change Management

Unit IV 12 Hrs Advanced topic in software engineering: formal methods – basic concepts – mathematical

preliminaries – mathematical notations – formal specification languages – object constraint

languages – the z specifications – the ten commandments of formal methods – the clean

room approach – functional specification – clean room design – clean room testing.

Self-study: Clean Room Testing

Unit V 12 Hrs Component based development: engineering of component based systems – the CBSE

process – domain engineering – component based development – classifying and retrieving

Components – economics of cbse – re-engineering: business process re-engineering –

software re-engineering – reverse engineering – restructuring – forward engineering – the

Economics of re-engineering.

Self-study: Economics of Re-Engineering

2

TEXT BOOK 1. Roger S. Pressman, “Software Engineering – A Practitioner’s Approach”, 6

th edition,

McGraw Hill International Edition, 2005.

REFERENCE BOOKS: 1.Watts S Humphrey, “A Discipline for Software Engineering”, Pearson Education

Publishers, 2001.

2. Ian Somerville, “Software Engineering”, Pearson Education Publication,6th

Edition,2001

SEMESTER-I

ADVANCED JAVA PROGRAMMING

Credits:4 Course Code: N5MCS1T52

Total Instructional Hours: 60

Course objectives: To enable the students to learn the features of java programming.

Skill sets to be acquired: On successful completion of the course the students should have the ability to develop a

program in advanced java. Concepts like RMI, servlets.

Unit-I 12Hrs Data types, variables and arrays-operators-control statements-inheritance-packages and

interfaces-exception handling -multithreaded programming- Self-study: Variables

Unit-II 12Hrs Applet class: Applet basics-applet architecture-applet display methods. Event handling:

mechanisms-model-event classes-event interfaces.

Self-study: Applet Display Methods

Unit-III 12Hrs AWT: AWT classes-window fundamentals-frame windows-work with graphics-working

with color, font, controls, layout managers and menus

Self-study: Working With Color

Unit-IV 12Hrs Swing: introduction applet-icons and labels-text fields-buttons-combo boxes-tabbed panes-

scroll panes- Introduction to JDBC- Java Enterprise Bean: Enterprise Bean Technology-EJB

middleware services- Roles in the EJB application life cycle –Service oriented architecture

and enterprise java beans-Apache Tomcat.

Self-study: Icons and Labels

Unit-V 12Hrs Servlet: Introduction-life cycle of servlet-servlet package - servlet parameters-handling http

request and responses. Java remote method invocation-SOAP- Javadoc and eclipse.

Self-study: Introduction to Remote Methods

3

TEXT BOOKS: 1. Herbert Sduldt, “Complete Reference Java 2”, Tata McGraw Hall, Fifth Edition.

(Unit –I, II, III, IV, V)

2. Rima Patel sriganesh, Gerald Brose, Micah Silverman “Mastering Enterprise Java Bean”,

Wiley India (p) Ltd, New Delhi [Page Nos.10 -27]

3. Java server programming java EE5” Black Book, Beginners Edition,” (Unit – IV)

4. Vivek chopra, Sing Li, Jeff Genender”Professional Apache Tomcat 6” Wiley India

Edition (Page Nos: 1- 10) Unit - IV

5. Jim Keogh, “Complete Reference J2EE”, Tata McGraw Hall (Unit-V)

6. http://www.cs.laurentian.ca/aaron/cosc1047/eclipse-tutorials/javadoc-tutorial.html(unit-5)

REFERENCE BOOKS: 1. PatrickNaughton- “Java Hand Book”, McGraw-Hill Osborne Media publishers, New

Delhi, First Edition, 2002.

2. Bryan Basham, Kathy Sierra and Bert Bates, “Head First Servlets and JSP”, O’reilly

Publishers, Second edition, 2009.

SEMESTER-I

ADVANCED MICROPROCESSORS AND MICRO CONTROLLERS



Course objectives: To enable the students to learn the concepts of the architecture of Microprocessor and

Microcontroller, importance of interfacing devices and explaining the way to program the

Microprocessor.

Skill sets to be acquired: On successful completion of the course the students should have the Knowledge about Low

Level Programming and Functions of Microprocessor and interfacing Devices.

Unit I 12 Hrs Introduction to Advanced Microprocessors: Advanced Microprocessor – architecture of 8086

microprocessor – pin description of 8086 microprocessor – working principle of 8086

microprocessor – the segment registers. Hardware Features Of 8086/8088: Functional pin

diagram of 8086/8088 – memory addressing in 8086

Self-study: the segment registers

Unit II 12 Hrs Memory Interfacing: Introduction – operation & terminology of memory – memory devices –

read only memory – static ram devices – read & write memory cycles – memory interfacing

concepts – 8/16 bit memory interfacing – addressing modes & Instruction Set of 8086: levels

of programming – assembler directives – addressing modes of 8086 – instruction set of 8086

Self-study: assembler directives

4

Unit III 12 Hrs Assembly Language Programming: Introduction – structure – sample ALPs – 8086 interrupts

and P/C: The interrupts – operation of real & protected mode interrupts – 8259a

programmable interrupt controller – programming 8259a – Basic I/O Interfacing:

Introduction – I/O Instructions – address decoding

Self-study: I/O Instructions

Unit IV 12 Hrs Introduction to Microcontrollers: Introduction – Microprocessor V/S Microcontroller –

history – applications – commercial microcontrollers – architecture of Intel 8051

microcontroller – Intel 8748 microcontroller- Types Of Microcontrollers: Introduction –

processor architectures – CISC V/S RISC architectures – memory types – features – 8051

Architecture: Introduction – features – architecture

Self-study: commercial microcontrollers

Unit V 12 Hrs 8051 Memory Organization – addressing modes –Boolean processor – memory organization

& external addressing – interrupts – 8051 instruction execution – 8051 Instruction Set:

Introduction – functional overview – 8051 instruction set – instruction dictionary of 8051 –

sample programs

Self-study: sample programs

Text book: 1. S. K. Venkataram ,“Advanced Microprocessor and Controllers”, Laxmi publications, 2002

Reference Books: 1. Tim Wilmshurst, “An Introduction to the Design Of Small Scale Embedded Systems”,

Palgrave publishers, 2004.

2. Muhammad Ali Mazidi et al , “The 8051 Microcontroller and Embedded systems”,

Pearson Education ,2nd

Edition, 2006.

SEMESTER I

DISTRIBUTED OPERATING SYSTEM



Course objectives: To enable the students to learn the features of distributed operating system.

Skill sets to be acquired: On successful completion of the course the students should have the knowledge about

Distributed computing systems, RPC, Distributed Shared Memory, Synchronization, and

Process Management, Resource management, Distributed File System, Linux and shell

scripts.

Unit – I 12 Hrs Operating Systems: Types of Operating Systems-Distributed Computing Systems:

Definition, evolution, models, and popularity of distributed computing systems. Distributed

operating systems: Definition, design issues, introduction to distributed computing

5

environment. Message Passing: Introduction , desirable features if a good message passing

system, issues in IPC, synchronization, buffering, multi datagram messages, encoding and

decoding of message data, process addressing, failure handling, group communication.

Self-study: buffering.

Unit – II 12 Hrs RPC: Introduction , model, transparency of RPC, implementation, stub generation, RPC

messages, marshaling arguments and result, server management, semantics, protocols, client

server binding, special types of RPC, lightweight RPC. Distributed Shared Memory:

architecture of DSM systems, design and implementation issues, granularity, structure of

shared memory space, consistency models, replacement strategy, thrashing, advantages.

Self-study: consistency models

Unit-III 12 Hrs Synchronization: Introduction, clock synchronization, event ordering, mutual exclusion,

deadlock, election algorithms. Resource Management: Features of global scheduling

algorithm, task assignment approach, load sharing approach.

Self-study: deadlock

Unit-IV 12 Hrs Process Management: Process Migration: Features Of Process Migration, Process Migration

Mechanisms, Threads. Distributed File System: Features, File Models, Accessing Models,

File Sharing Semantics, File Caching Schemes, Replication, Atomic Transactions, and

Design Principles.

Self-study: Atomic Transactions

Unit-V 12 Hrs Linux: Introduction to Linux Operating System: the Linux Operating System. Managing files

and directories: the Linux file system – directory commands in Linux – file commands in

Linux. Using Conditional Execution In Shell Scripts: Conditional execution – the case…esac

construct. Managing repetitive tasks using shell scripts: Using iteration in shell scripts –

parameter handling in shell scripts – the shift command.

Self-study: The Linux Operating System.

Text books: 1. Pradeep K. Sinha, “Distributed operating system concepts and design”, PHI Private ltd,

1st edition,2006.

2. NIIT , “Operating System Linux”, Prentice hall of India private limited, 1st edition,2003.

3.Ida M.Flynn &Ann.Mclver McHoes, “Operating Systems”, published by cengage learning,

Indian Edition, 2006.

Reference book: 1. Andrew S.Tanenbaum, “Distributed Operating Systems”, Pearson Education,1

st

edition,2004.

6

SEMESTER-I

ADVANCED JAVA PROGRAMMING LAB

Credits: 4 Course Code: N5MCS1P56


Course objectives: To enable the students to learn the features of internet and java programming concepts in lab.

Skill sets to be acquired: On successful completion of the course the students would have the knowledge about the

facilities of internet and the capacity of developing a program in internet and java.

LIST OF PROGRAMMS

1. Write a java program for Employee details

2. Write a java program for Polymorphism

3. Write a java program for Random image using applet

4. Write a java program for Mouse event handling using applet

5. Write a java program for Calculator using AWT method

6. Write a java program for student information using JDBC

7. Write a java program for Tree Viewer using java swing.

8. Write a java program for Server Socket

9. Write a simple message display program using JSP

10. Write a java program for Advertisement using java swing

7

SEMESTER - I

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BOOKS REFERENCES:

1.Unified force -ThathuvagnaniVethathiri Maharishi

2.The History of universe and living beings- ThathuvagnaniVethathiri Maharishi

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11. Advanced Educational Psychology- G.K.Mangal.

12. Effective Study Material-Reddy.

13. Psychology-Robert A. Baron.

SEMESTER – I

PG SYLLABUS

YOGA FOR THE MODERN AGE

COURSE CODE: N5MCS1T57

Credits: 1 Instructional

Hours:35

OBJECTIVES:

Understanding the Law of Nature – Learning about Management Techniques

and Exam Preparation.

UNIT: 1 Simplified Physical Exercises of SKY System - (7 Hrs)

Simplified Physical Exercises Kayakalpa – Managing infatuation – Practice.

UNIT: 2 Meditation - (7 Hrs) Definition of Meditation – Mental

Frequency – Types – General and Special meditations in SKY – Importance –

9

brow centre meditation – Genetic centre meditation – Clearence – Crown centre

meditation.

UNIT: 3 Management of life - (7 Hrs) Concepts of Life – Problems faced by

Individual – Difference between Ego and Personality – Impact of Ego –Factors

influencing Personality – Women empowerment - Individual difference – Role of

Hereditary, Environment.

UNIT: 4 Law of Nature - (7 Hrs) Cause and effect - Unity in diversity –

Consciousness and living – Relation between body and consciousness –

Conciousness and Society – Concept of Action-Karmayoga – Role of karma yoga

for self management – Impact of Qualities – Supremacy of love and compassion.

UNIT: 5 Management Techniques - (7 Hrs) Stress Management – Emotional

Management - Self Management – Conflict Management – Peer Pressure

Management – Self identity – Self Monitering – Self Evaluation – Self

Reinfocement – Group dynamics – Team Management.

Reference Books:

1. Simplified Physical Exercises – Thathuvagnani Vethathiri Maharishi

2. Karma yoga - Thathuvagnani Vethathiri Maharishi

3. Journey of Conciousness – Thathuvagnani Vethathiri Maharishi

4. Yoga for modern age – Thathuvagnani Vethathiri Maharishi

5. Unified force – Thathuvagnani Vethathiri Maharishi

6. The History of universe and living beings – Thathuvagnani Vethathiri

Maharishi

7. Genetic centre – Thathuvagnani Vethathiri Maharishi

8. Psychology - Robrt A. Baron

SEMESTER – II

WEB TECHNOLOGY



Course objectives: To enable the students to learn the concepts of web technologies.

Skill sets to be acquired: On successful completion of this course, students would develop the projects related to web

and they may become the web designer.

10

Unit I 10 Hrs Basics Of Web Technology: Getting set up-what is ASP.NET-setting up for ASP.NET- The

development environment-ASP And ASP.NET: An overview-Programming Basic: Basic of

programming-how dynamic website applications work. XML Basic: Getting a global

perspective-reviewing XML validating and non-validating parsers-saying “hello world” in

XML- HTML Basic: Getting started –basic page structure.

Self-study: Basic of programming

Unit II 10 Hrs Introducing PHP: History-unique features-basic development-creating your first PHP script-

escaping special characters-sample applications. Using variables and operators-controlling

program flow.

Self-study: sample applications

Unit III 10 Hrs Working with arrays - using functions and classes- working with files and directives-working

with cookies, sessions, and headers.

Self-study: Cookies

Unit IV 10 Hrs Working databases and SQL-securing PHP- Extending PHP-Introducing JQuery: Bring

pages to life with JQuery-Introduction to Ajax, Pre-Ajax java script communications

techniques: One way Communication-Two way Communication.

Unit V 10 Hrs Data formats: Ajax and Character sets-Data format Decisions-Standard Encoding-

developing an Ajax library-Security Concerns: The web attack surfaces –Ajax security

differences-java script security-Ajax and authentication-cross site scripting-User Interface

Design For Ajax: Communicating network activity-drag and drop-The Real Power: Data on

demand.

Text books:

1. Dave mercer, “ASP.NET A Beginner’s Guide”, Tata McGraw Hill Edition, 2008

(Unit I)

2. Heather Williamson, “The Complete Reference XML”, Tata McGraw Hill

Edition, 2006(Unit I)

3. Wendy Willard, “HTML: A Beginner’s Guide”, Tata McGraw Hill Edition Fourth

Edition.

4. Vikram Vaswani, “PHP - A Beginner’s Guide”, Tata McGraw Hill Edition,2009

(Unit II, III, IV).

5. Thomas A. Powell, “The Complete Reference Ajax”, Tata McGraw Hill

Edition,2008.(Unit- V)

6. Bear Bibeault, Yehuda Katz, “ JQuery In Action”, Second Edition,2010.

11

Reference books:

1. A. A. Puntambekar, “Web Technologies”, Technical Publications First Edition,

2011.

2. Steven Holzner, “The Complete Reference PHP” McGraw-Hill Education Pvt

Limited, 2007.

SEMESTER-II

COMPUTER ARCHITECTURE AND PARALLEL PROCESSING



Course Objective: To enable the students to learn the parallel processing and SIMD arrays.

Skill set to be Acquired: On successful completion of the course the students should have understood the trends and

principles of parallel processing in computers

Unit I 10 Hrs Introduction to parallel processing – trends towards parallel processing – parallelism in

Uniprocessor systems – parallel computer structures – architectural classification schemes –

parallel processing Applications

Self-study: parallel processing Applications

Unit II 10 Hrs Principles of linear pipelining – classification of pipeline processors – general pipeline and

reservation tables – arithmetic pipeline design examples – data buffering and busing

structure – internal forwarding and register tagging – hazard detection and resolution – job

Sequencing and collision prevention – vector processing requirements – characteristics –

Pipelined vector processing methods

Self-study: classification of pipeline processors

Unit III 10 Hrs SIMD array processors – organization – masking and data routing – inter PE

Communications – SIMD interconnection networks – static vs dynamic – mesh connected

Illiac – cube interconnection network – shuffle-exchange and omega networks -

Multiprocessor architecture and programming functional structures : Interconnection

Networks

Self-study: Interconnection Networks

Unit IV 10 Hrs Multiprocessing control and algorithms: Interprocess Communication Mechanisms- System

deadlocks and protection, Multiprocessor scheduling strategies: dimensions of multiple

processor management-Deterministic scheduling models. Parallel algorithms for

multiprocessors: Classification of parallel algorithms-synchronize parallel algorithms-

Asynchronized parallel algorithms

Self-study: Interprocess Communication Mechanisms

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=A.+A.+PUNTAMBEKAR&search-alias=stripbooks

12

Unit V 10 Hrs Data flow Computers and VLSI Computations: Data Driven Computing and Languages-

Data Flow Computer Architectures. VLSI Computing Structures: The Systolic Array

Architecture- Reconfigurable Processor Array-VLSI Architectural Modules-Partitioned

Matrix Algorithms- Matrix Arithmetic pipelines

Self-study: Matrix Arithmetic pipelines

Text book 1. Kai Hwang, Faye A. Briggs, “Computer Architecture And Parallel Processing” McGraw

Hill book company, 1985.

Reference Books: 1. V. Rajaraman, c. Sivaram Murthy, “Parallel Computers Architectures and Programming”,

PHI, 2003.

2. Michael J. Quinn, “Parallel Computing Theory and Practice”, TMH, Second Edition,

2002.

3. Barry Wilkinson, Micheal Allen, “Parallel programming: Techniques and Applications”,

Prentice Hall, 1999.

SOFTWARE TESTING



Course Objective: To enable the students to learn the parallel processing and SIMD arrays.

Skill set to be Acquired: On successful completion of the course the students should have understood the trends and

principles of Software Testing.

Unit I 10 Hrs

Introduction to Quality: Introduction-Historical Perspective of Quality-Definitions of

Quality-Core Components of Quality-Quality View-Customer, Suppliers and Processes-Total

Quality Management (TQM)-Continual (Continuous) Improvement Cycle. Basic Concepts of

Software Testing: Introduction-Definition of Testing-Basic Principles of Testing-Testing

During Development Life Cycle-Work Bench-Test Policy-Test Strategy-Developing Test

Strategy-Test Methodologies.

Unit II 10 Hrs

Configuration Management: Introduction- Configuration Management- Cycle of

Configuration Management-Using Automated Configuration Tools Configuration

Management Planning. Risk Analysis: Introduction-Advantages and Disadvantages of

Automated System-Risk-Constraints-Project Risk-Product Risk Software Implementation

Risk-Identification of Risk-Types Software Risk-Handling of Risk in Testing-Risk and

Testing-Assumption in Testing-Testing as a Reduction Program-Risk of Testing.

13

Unit III 10 Hrs

Software Verification And Validation: Introduction- Verification- Verification Work Bench-

Methods Of Verification-Types Of Review On The Basis Of Stage/Phase-Coverage In

Verification-Concerns Of Verification- Validation-Work Bench-Levels-Coverage In

Validation-Acceptance Testing-Software Development Verification And Validation

Activities. V-Test Model.

Unit IV 10 Hrs

Testing Techniques and Tools: Levels Of Testing-Acceptance Testing: Introduction-

Acceptance Criteria-Importance of Acceptance Criteria-Alpha Testing-Beta Testing-Gamma

Testing-Acceptance Testing During Each Phase of Software Development-Factors Affecting

Criticality of the Requirements-Developing Acceptance Plan. Special Test (Part I).

Unit V 10 Hrs Testing Tools-Test Planning-Test Metrics And Test Reports-Qualitative And Quantitative

Analysis.

Text Book:

1. M G Limaye, “Software Testing Principles, Techniques And Tools”, Tata Mcgraw Hill

Companies.

Reference Books:

1. Myers And Glenford.J. ”The Art of Software Testing”, John-Wiley & Sons, 1979.

2. Roger.S.Pressman, ”Software Engineering-A Practitioner’s Approach”,Mc-Graw Hill,

5th

Edition,2001.

3. Marnie.L.Hutcheson.”Software Testing Fundamentals”, Wily-India, 2007

4 Boris Beizer, “Software Testing Techniques”, Dream Tech Press, Second Edition – 2003.

SEMESTER-II

WEB TECHNOLOGY LAB

Credits:4 Course Code: N5MCS2P55


Course objectives: To enable the students to learn the concepts of designing the websites using XML, PHP.

Skill sets to be acquired: On successful completion of the lab, the students will acquire the knowledge to develop the

web based projects

List of Programs 1. Working with numbers, strings, dates and times.

2. Build complex data structures using PHP’s array manipulation API

3. Use functions and classes to build modular, reusable code

4. Obtain and process user input submitted via online forms

5. Write a program to Debug PHP script.

6. Authenticate and track users with sessions and cookies

7. File handling in PHP.

8. Traverse, validate, and transform XML documents

9. Store and retrieve and modify data from MYSQL databases

10. Perform efficient exception handling and error processing.

11. Create a Login Form Using Ajax.

14

SEMESTER-II

LINUX LAB



Course objectives: To enable the students learn to develop the program in Linux OS

Skill sets to be acquired: On successful completion of the lab, the students will gain the knowledge of the way to

program in Linux Platform

Complete all the programs 1. Write a menu driven shell script to (a) find sum of digits and (b) sum up to that number.

2. Write a shell script to accept two file names as arguments. Check whether the file

contents are same or not.

3. Write a shell script to accept two file names and check it both exists. If the second file

name exists then the contents of the first file name should be appended to it. If the second

file name does not exist then create a new file with contents of the first file name.

4. Write a menu driven shell script to check if the given string and the number are

palindromes.

5. Write a shell script to search a file from the current directory in any of the subdirectories

and report the path.

6. Write a shell script to prepare payslip. 7. Create a file called test.dat which contains sample data as follows:

A00001 shanthi 80

A00007 arun 70

S00005 karthi 50

Answer the following questions based on the above data:

A. Display the contents of the file sorted according to the marks in descending

order.

B. Display the names of the students in alphabetical order ignoring the cases.

C. Display the list of students who have scored marks between 60 and 80.

D. Display the list of students and their register numbers.

8. Write a menu driven shell script for file manipulation which includes

1) Creating a file 2) editing a file 3) removing a file/directory 4) copying a file

5) appending contents of files 6) displaying content of a file 7) translating contents

of a file either lowercase or uppercase

9. Write a menu driven shell script for computing factorial value of a given number &

generating Fibonacci series using recursive function.

10.Write a shell script to display all perfect numbers between 1 and the given limit.

11.Write a shell script to sort n numbers and print the biggest and smallest numbers and

their corresponding positions.

15

SEMESTER-II

Software Testing Lab



Course Objective: To enable the students to learn the principles of software testing in lab.

Skill Sets To Be Acquired: On successful completion of the course the students would have the knowledge about the

strategies of software testing.

1. Write a program for hospital management system.

2. Write a program for electricity bill system.

3. Write a program for payroll processing system.

4. Write a program for matrix list maintenance.

5. Write a program for hotel management system.

6. Write a program for inventory control system.

7. Write a program for medical shop management system.

SEMESTER-II

COMMUNICATION FOR EXECUTIVES



Course objective To expose students in advance level courses in communicative skills.

Skill set to be acquired On successful completion of the course, the students should have acquired proficiency in

communicative skills

Unit I 10 Hrs Communication: basic concepts – process – kinds – importance – barriers

Unit II 10 Hrs Fundamentals of speech, basics of grammar, punctuation and capitalization

Unit III 10 Hrs Letter writing, report writing, drafting e-mail, description of datum, resume writing

Unit IV 10 Hrs Body language, audio visual aids for communication, mock interview reviews of articles,

editorials, films, stories, novels, products

Unit V 10 Hrs Advertising and job description, research papers and articles Reading comprehension, group

discussion

16

Text book: 1. Krishna Mohan &Meera Baneerji ,“Developing Communication Skills” Macmillan India

Limited.

SEMESTER-III

SOFTWARE QUALITY ASSURANCE Credits: 4 Course Code: N5MCS3T51


Course objective: To enable the students learn the quality software for an applications & describing the factors

to be considered for developing software.

Skills set to be acquired: On successful completion of the course the students would have the knowledge about, the

factors to be considered for quality software. Learn the way of preparing quality software

with zero error.

Unit I 10 Hrs

Introduction - quality and the quality system - standards aid procedures – technical activities.

Software tasks - management responsibility - quality system - contract review – design

control -document control - purchasing - product identification and trace ability.

Unit II 10 Hrs

Process control - and checking - identification of testing tolls - control of non-informing

product - corrective action.

Unit III 10 Hrs

Handling. Storage, Packaging And Delivery -Quality Records - Internal Quality Audits -

Training -Servicing - Statistical Techniques.

Unit IV 10 Hrs

QA And New Technologies - QA And Human - Computer Interface - Process Modeling -

Standards And Procedures.

Unit V 10 Hrs

ISO 9001 - Elements Of ISO 9001 - Improving Quality System - Case Study.

Text Book:

1. Darrel Ince, “An Introduction To S/W Quality Assurance Its Implementation”, Mcgraw

Hill Book Company Ltd. 1994.

Reference Book:

1. Darrel Ince,. “ISO 9001 And S/W Quality Assurance” , Mcgraw- Hill Book Company

Ltd,1994.

17

SEMESTER-III

INFORMATION SECURITY



Course objectives: To enable the students to learn different kinds of security .

Skill sets to be acquired: On successful completion of the course, the students can empower themselves in developing

the system which follows different security measures.

Unit I 10 Hrs Cryptography - access control – protocols – software - a taxonomy of cryptography -block

ciphers – knapsack – RSA - Diffie-Hellman - elliptic curve cryptography - public key

notation - uses for public key crypto - public key infrastructure.

Self Study: public key notation

Unit II 10 Hrs What is a hash function? - uses of hash functions - other crypto related topics - authentication

- introduction - authentication methods - biometrics - two factor authentication.

Self Study: uses of hash functions

Unit III 10 Hrs Authorization-Introduction - Access Control Matrix - Multilevel Security Models-

Multilateral Security - Convert Channel – Firewalls - Intrusion Detection.

Self Study: Intrusion Detection.

Unit IV 10 Hrs Simple Authentication Protocols: Introduction-simple security protocols – authentication

protocols – authentication and TCP. Real world security protocols: Introduction - secure

socket layer – IPSec - IKE phase1: digital signature - symmetric key - public key encryption

- IPSec cookies – Kerberos - GSM.

Self Study: digital signature

Unit V 10 Hrs Software Flaws And Malware: Introduction – software flaws – malware – insecurity in

software – introduction – software reverse engineering – digital rights management – what is

DRM? – a real world DRM system – DRM failures – software development – open versus

closed source software- Operating systems and security.

Self Study: software reverse engineering

Text book: 1. Mark Stamp ,“Information Security Principles and Practices”, John Wiley & Sons, Inc

publishers, 2006 edition.

Reference Books: 1. Charles P Pfleeger And Shai Lawrence Pflegeer,”Security In Computing”, Prentice Hall

2007, fourth edition.

2. Ross J.Anderson And Ross Anderson,” Security Engineering: A Guide To Building

dependable Distributed Systems”, wiley publications ,2001 edition

18

3. Debby Russell And Sr.G.T.Gangemi,”Computer Security Basics(paperback)”, O’reilly

media 2nd

edition ,2006

4. Thomas.R.Peltier, Justin Peltier And John Blackley,”Information Security fundamentals”,

prentice hall Publications,2nd

edition,

SEMESTER-III

DATA MINING AND WAREHOUSING



Course Objectives: To enable the students to learn the concepts of mining tasks, classification, clustering ,data

warehousing and basic concepts of big data analytics.

Skill sets to be acquired: On successful completion of the course the students would have the knowledge about

association rules, clustering techniques and data warehousing and basic concepts of big data

analytics.

.

Unit I 10 Hrs Data warehousing: Introduction - characteristics of a data warehouse – data marts – other

aspects of data mart. Online Analytical Processing: Introduction - OLTP & OLAP systems –

Data Modeling: Star schema for multidimensional view –multi fact star schema or snow

flake schema – OLAP tools – state of the market – OLAP tools and the internet.

Self Study: Applications Of Data Warehousing And Data Mining In Government:

Introduction -national data warehouses – other areas for data warehousing and data mining

Unit I I 10 Hrs Introduction-basic data mining tasks-data mining versus knowledge discovery in databases-

data mining metrics-social implications of data mining-data mining from a database

perspective- data mining techniques.

Self Study: data mining metrics

Unit III 10 Hrs Classification: Introduction-statistical based algorithms- distance based algorithms-decision

tree based algorithms-neural network based algorithms- rule based algorithms – combining

techniques. Clustering: Introduction – similarity and distance measures-outliers- hierarchical

algorithms-partitioned algorithms- clustering large databases.

Self Study: Clustering Large Databases

Unit IV 10 Hrs Association rules: Introduction - large item sets - basic algorithms – parallel & distributed

algorithms – comparing approaches- incremental rules – advanced association rule

techniques-measuring the quality of rules. Web mining: Introduction-web content mining -

web usage mining.

Self Study: web content mining

19

Unit V 10 Hrs The feedback economy: data-obese, digital-fast – the big data supply chain – replacing

everything with data – how new data analytics systems will impact storage,a feedback

economy, what is big data: what does big data look like? – in practice, Apache hadoop: core

of hadoop, hadoop’s lower levels, improving programmability, improving data access, co-

ordination & workflow, management & deployment, machine learning mahout, using

hadoop.

Self Study: machine learning mahout, using hadoop

Text books: 1. Margaret H. Dunham, “Data Mining Introductory And Advanced Topics”, Pearson

Education, Edition, 2003 (Unit I ,II AND III).

2. C.S.R. Prabhu, “Data Warehousing Concepts, Techniques, Products And Applications”,

PHI Publications , Second Edition 2002. (Unit IV)

3. O’Reilly, “Planning for Big data”, O’Reilly Media, Inc., 2012

Reference books: 1. Berry M. J. A. and Linoff G. S. “Mastering Data Mining”, New York: John Wiley

&Sons, 2004.

2. Sushmitha Mitra , “Data Mining”, New York: John Wiley Sons Publications, 1st

Edition, 2004.

Reference web portal: 1.https://www.eiseverywhere.com/file_uploads/293c903560bc03d67acefe4b239446a6_Webs

ter_Tuesday_1045_SNWS11.pdf

SEMESTER – III

SOFTWARE QUALITY ASSURANCE LAB



Course objective: To enable the students learn the concepts of the SQA

Skill sets to be acquired: On successful completion of the course the students should have the knowledge about the

applications of SQA.

1. Write a VB program for electricity bill system and check the various quality factors.

2. Write a VB program for medical shop management system and check the various quality

factors.

3. Write a VB program for hotel room booking system and check the various quality factors.

4. Write a VB program for mark maintenance system and check the various quality factors.

5. Write a VB program for inventory management and check the various quality factors.

6. Write a VB program for hospital management system and check the various quality

factors.

7. Write a VB program for payroll processing system and check the various quality factors.

20

SEMESTER – III

DATA MINING LAB



LIST OF PRACTICALS

1.Implement data pre processing using weka .

2.Implement classification-zero algorithm using weka.

3.Implement classification-J48 algorithm using weka .

4.Implement clustering-hierarchical algorithm using weka.

5.Implement clustering-simple k-means algorithm using weka .

6.Implement association rule using weka.

7.Implement attribute selection-I using weka.

8.Implement attribute selection-II using weka.

SEMESTER II

QUANTITATIVE APTITUDE AND VERBAL REASONING

(Common for MBA / MCA / MSW/ M.Com/ MIB/ M.Sc (CS) Students admitted from

2015 onwards)


Hours per week: 5 Total instructional Hours: 60

Course Objectives: To inculcate the managerial and problem solving skills among the

students.

Skill sets to be acquired: After the completion of the course the student will be able to

develop reasoning skills and face any competitive examinations with confidence.

UNIT I (12 Hours)

Averages

Problem on Numbers

Problems on Ages

Simple Interest

Compound Interest

UNIT II (12 Hours)

Profit and loss

Time and work

Time and Distance

Problems on trains

Data interpretation

21

UNIT III (12 Hours)

Analogy

Coding and Decoding

Blood Relations

UNIT IV (12 Hours)

Direction sense Test

Logical Venn diagram

Number of ranking and Time Sequence test

UNIT V (12 Hours)

Insert the missing character

Data sufficiency

Situation reaction Test

Series completion

TEXT BOOK:

“Quantitative Aptitude for Competitive Examinations”, Department of Mathematics, Sree

Saraswathi Thyagaraja College, Pollachi, 2015.

REFERENCE BOOKS:

1. Dr. R.S. Agarwal, Quantitative Aptitude for Competitive Exams-S.Chand and Company,

2012 Edition, New Delhi (for units I & II only).

2. Dr.R.S. Aggarwal, A Modern Approach to Verbal and Non-Verbal Reasoning-S.chand

and Company, 2011 Edition, New Delhi (For units III, IV, V).

3. Abijit Guha, Quantitative Aptitude for Competitive Exams -Tata McGrawHill 3rd

Edition.

4. B.S. Sijwali, Reasoning Verbal and Non Verbal, Arihant Publications, 2007.

SEMESTER-III

Credits:2 Course Code: N5MCS3R49

Guidelines for the internship programme

For M.Sc(Computer Science)

Objective: to give optimum exposure on the practical side of commerce and industry.

1. Duration of the internship training is 30 days during the summer vacation which falls

at the end of the 2nd

semester.

2. The departments concerned will prepare on exhaustive panel of institutions, industries

and practitioners.

22

3. The individual student has to identify the institution / industry / practitioners of their

choice and inform the same to the HOD / staff-in-charge.

4. The students hereafter will be called as trainees should maintain a work diary in

which the daily work done should be entered and the same should be attested by the

section in-charge.

5. The departments should prepare an outline of the job to be done, sections in which

they have to be attached both in the office as well as in the field.

6. The trainees should strictly adhere to the rules and regulations and office timings of

the institutions to which they are attached.

7. The trainees have to obtain a certificate on successful completion of the internship

from the chief executive of the organization.

8. Monitoring and inspection by staff on a regular basis.

9. Report writing manual and format should be prepared by the respective departments.

10. All model forms are to be attached wherever it is necessary.

11. Report evaluation: Internal viva-voce examination will be conducted and the

maximum mark awarded is 50.

12. Report should be submitted in the 3rd

semester on or before 15th

september.

SEMESTER-IV

PROJECT & VIVA-VOCE – I

CREDITS: 8 COURSE CODE: N5MCS4R22

Project Report Format

Title of The Project

Project Report –I

Submitted By

Name of The Student

(Reg.No)

Under The Guidance of

Guide Name (Designation)

In partial fulfillment of the requirements for the award of the degree of

Master of Science (Computer Science)

23

PG Department Of Computer Science

Sree Saraswathi Thyagaraja College

(autonomous)

An ISO 9001:2008 certified and NAAC Re-accredited Institution with ‘A’ Grade

(Affiliated To Bharathiar University, Coimbatore & Approved By UGC & AICTE ,

New Delhi)

Pollachi-642 107

Month & year

Guidelines to prepare documentation:

The cover should be in the silver gray colour and hard binding

Font type : Times New Roman

Font size : 12

Sub heading size :14

Heading size :16

Margin : top,bottom,right-2.5 cm, left -3 cm

Line spacing between two lines - 1.5

Every paragraph should start with one tab space.

Report should be in the following sequence…

Bonafide certificate

Certificate from the company/organization

Declaration

CONTENTS Page No

ACKNOWLEDGEMENT

SYNOPSIS (abstract of the project)

1. INTRODUCTION

1.1. About the project

1.2. Organization profile

2. SYSTEM ANALYSIS

2.1. Existing system

2.2. Proposed system

2.2.1. System Study

2.3. System specification

2.3.1. Hardware specification

2.3.2. Software specification

2.3.3. About the software.

24

3.SYSTEM DESIGN

3.1 Design Notations

3.1.1 Data flow diagram

3.1.2 System flow diagram

3.1.3 ER Diagram

3.2 Design Process

3.2.1 Input design

3.2.2 Database design

3.2.3 Output design

4. SYSTEM TESTING AND IMPLEMENTATION

4.1.Testing methodologies

4.2 System implementation

5. CONCLUSION & FUTURE ENHANCEMENTS

Bibliography

Appendix

Sample Screens

Reports

Declaration

I( Student Name , Reg.No ) do hereby declare that the project entitled ( Title Of The

Project) submitted to the Bharathiar University, Coimbatore, in partial fulfillment of the

requirements for the award of the degree of M.Sc Computer Science, is a record of original

work done by me during the period of the study at Sree Saraswathi Thyagaraja College,

pollachi, under the guidance of (Name Of The Guide)

Place:

Signature Of Candidate

SEMESTER IV

PROFESSIONAL ETHICS

Credits:1 Course Code:

N5MCS4T23

Total instruction hours: 35

Course objectives: 1. To provide students with an introduction to the philosophical foundation of ethics and

values based decision making and behavior

2. To aid the students in relating professional code of ethics and how to apply them in

their own work place.

3. To provide the students with resources that may assist them in appreciating universal

human values

Unit I: Nature And Scope Of Business Ethics 7 Hrs

Introduction – Scope Of Business Ethics- Religion And Ethics- Types Of Ethics – Sources Of

Business Ethics- Factors Influencing Business Ethics –Importance Of Business Ethics

25

Unit II: Professional Ethics 7 Hrs Introduction –professional ethics – ethical problems faced by managers – new skill required

for managers – managing ethical conduct in modern times

Unit III: Corporate Governance And CSR 7 Hrs

Principles of corporate governance – issues involved in corporate governance- theories of

corporate governance –CSR – introduction – various dimensions – argument for and against

CSR

Unit IV: Ethics in India 7 Hrs Religious foundations of ethics-Hinduism-Buddhism-Jainism-Ethical Values Of Gandhi,

Vivekananda, Aurobindo and Tagore.

Unit V: Dimensions Of Ethics 7 Hrs Personal ethics-marketing ethics –technology ethics –environmental ethics.

Text books 1. R.Nandagopal,Ajithsankar.R.N,”Indian Ethos and Values in Management”,Tata McGraw

Hill education Private Ltd, New Delhi ,2010.

2. S.Prabakaran,” Business ethics and corporate governance”, Excel books (2010), First

Edition.

SEMESTER-I

Elective - I 1. MOBILE COMPUTING



Course Objectives: To enable the students to learn about the basics for various techniques in mobile

communications and mobile content services.

Skill sets to be acquired: On successful completion of the course the student should

Learn the basics of wireless voice and data communications technologies.

Build working knowledge on various telephone and satellite networks.

Study the working principles of wireless LAN and its standards.

Build knowledge on various mobile computing algorithms.

Unit I 10 Hrs Introduction: Introduction to Mobile Computing-Mobile Computing Architecture-Mobile

Devices-Mobile System Networks-Data Dissemination-Mobility Management-Mobile

Operating Systems-Telecommunication Systems - Wireless Transmission – Multiplexing –

Digital Cellular Systems – Medium Access Control.

Self Study: Mobile Devices

Unit II 10Hrs GSM and similar Architecture – Sessions – Protocols and the TCP/IP Suite – Hand over and

Security – Satellite System –Broadcast Systems-Mobile IP Network and Transport Layer.

Self Study: Satellite System

26

Unit III 10 Hrs Wireless LAN: IEEE S02.11 – Hiper LAN – Bluetooth – MAC Layer – Security and Link

Management-Data Synchronization in Mobile Computing Systems-Mobile Ad-hoc and

Sensor Networks.

Self Study: Bluetooth

Unit IV 10 Hrs Wireless Application Protocol: Wireless Application Protocol (WAP) – Architecture –

Mobile Application Languages XML – WML Script-JAVA, J2ME and Java Card.

Self Study: Applications

Unit V 10 Hrs Android –Introduction to Android OS-Configuration of Android-Create the first Android

Application-Designing user interface with view-Activity-Multimedia.

Self Study: Multimedia.

Text Book(s) 1.Jochen Schiller, “Mobile Communication”, Pearson Education, Delhi, 2000.

2.Renuka T.Ambiger ”Mobile Computing” ,Eastern Book Publishers, First Edition 2007.

3.V.Jayasri Arokiamary “Mobile Computing” ,Technical Publications First Edition 2007.

4.Rajkamal “Mobile Computing” ,Oxford University press,2009.

5.Prasanna kumar DIXIT, “Android”, Vikas Publications,I st Edition,2014.

Reference Book 1. Sandeep Singhal et al “The Wireless Application Protocol: Writing Applications For The

Mobile Internet”. Addison-Wesley, 2001.

SEMESTER-I

Elective - I 2.EMBEDDED SYSTEM



Course Objective: To enable the students to learn the concepts of Architecture, designing of Embedded Systems

Skill set to be acquired: On successful completion of the course the students would gain the basic knowledge of

Embedded System

Unit –I 10 Hrs Introduction to embedded systems: Embedded systems-processor embedded into a system-

embedded hardware units and devices in a system-embedded software in a system-examples

of embedded systems-SOC&VLSI.-8051 architecture –Introduction to advanced

architectures-processor and memory organization

Self Study: processor and memory organization

27

Unit-II 10 Hrs Devices and communication buses for devices network: IO types and examples-serial

communication devices-parallel devices ports-timer and counting devices-programming

concepts and embedded programming in C,C++,And Java:Software programming in

assembly language(ALP)and in high level language ‘C’-C Program Elements-Program

Elements:Macro and functions-embedded programming in java.

Self Study:macro and functions

Unit-III 10 Hrs Program modeling concepts: Program models-DFG models-state machine programming

models for event controlled program flow-modeling of multiprocessor systems-UML

modeling.-multi processors in an application-multiple treads in an application-single

function-semaphore function-message queue function-mailbox function-pipe function.

Self Study: semaphore function

Unit-IV 10 Hrs Real time operating systems:os service-process management-timer function-event function-

memory management. -real –time operating system programming-i:basic function ant types

of RTOSes-RTOS MTOS MC/OS-II.

Self Study: basic functions of RTOS

Unit-V 10 Hrs Embedded software development process and tools: introduction to embedded software

development process and tools-host and target machines-linking and locating software-

getting embedded software into the target system-issues in hardware-software design and co-

design-testing on host machine-simulators-laboratory tools

Self Study: linking and locating the software

Text book: 1. Rajkamal,”Embedded System Architecture, Programming And Design”, Second Edition,

Reprint TMH 2009.

Reference books: 1. Oliver H.Bailey “Embedded Systems Desktop Integration” , First Indian Ed BPB,

Publication, 2007.

2. Arnolo S.Berger “Embedded System Design” First South Asian Edition, Viva CMP Books 2005.

SEMESTER-I

Elective –I 3.DISTRIBUTED DATABASE



Course Objectives: To learn the concepts of Relational databases, transactions, recovery

system and distributed databases, object based databases and XML documents.

28

UNIT I 10 Hrs Database System Applications - Database Systems versus File Systems - Views of Data -

Data Models-Database Languages - Database Users and Administrators. ER Model: Basic

Concepts - Constraints-Keys - ER Diagram - Weak Entity Sets. Relational Model: Relational

Algebra.

Self Study: Data models

UNIT II 10 Hrs Database Design - Pitfalls in Relational Database Design. Functional Dependencies -Basic

definitions - Trivial and nontrivial dependencies - Closure of a set of dependencies - Nonloss

decomposition - First, Second and Third Normal Forms - Boyce/Codd normal form -

Multivalued dependencies and Fourth normal form - Join Dependencies.

Self Study: Trivial and nontrivial dependencies

UNIT III 10 Hrs Object-Based Databases: Object-oriented Data Model. Object - Relational Databases: Nested

Relations- Inheritance – Reference Types. XML: Structure of XML data – XML Documents

Schema – Querying and Transformation – The Application Program Interface – Storage of

XML Data – XML Applications.

Self Study: XML Applications

UNIT IV 10 Hrs Transactions: Concepts – State – Concurrent Executions - Serializability- Testing for

Serializability. Concurrency Control: Lock-Based Protocols - Timestamp Based Protocols -

Validation Based Protocols. Recovery System: Failure Classification-Storage Structure -

Recovery and Atomicity - Log Based Recovery.

Self Study: Failure Classification ,Storage Structure

UNIT V 10 Hrs Database System Architectures: Centralized and C/S Architectures-Server System

Architectures - Distributed Systems. Distributed Database: Homogeneous and Heterogeneous

Database - Distributed Data Storage - Distributed Transactions – Commit Protocols -

Heterogeneous Distributed System.

Self Study: Distributed Data Storage

Text Books 1. Abraham Silberschatz, Henry F. Korth, S.Sudarshan,” Database System Concepts”,McGraw Hill,

Fourth Edition, 2002. (For Units I, III, IV & V)

2. C.J. Date, “An Introduction to Database Systems”, Pearson Education, Seventh Edition, 2002.

(For Unit II only)

Reference Books 1. Connolly, Begg, “Database Systems”, Pearson Education, Third Edition 2005. 2. Elmasri, Navathe, Somayajulie, Gupta, “Fundamentals of Database Systems”, Pearson

Education, Fifth Edition, 2007.

29

SEMESTER-II

Elective II.1 CLOUD COMPUTING



Course Objective: To enable the students to learn the concepts of cloud computing.

Skill sets to be acquired: On successful completion of the course the students would acquire the knowledge about the

importance of cloud

Unit – I 10 Hrs Defining cloud computing: defining cloud computing-cloud types-examining the

characteristics of cloud computing- understanding cloud architecture: exploring the cloud

computing stack- connecting to the cloud.

Self Study: cloud types

Unit –II 10 Hrs Understanding services and applications by type: defining infrastructure as a service (IaaS)-

defining platform as a service (PaaS) -defining software as a service (SaaS)- defining identity

as a service (IDaaS)- defining compliance as a service (CaaS).

Self Study: infrastructure as a service (IaaS)-

Unit – III 10 Hrs Using platforms: understanding abstraction and virtualization using virtualization

technologies- load balancing and virtualization - understanding hypervisors- understanding

machine imaging - porting applications.

Self Study: porting applications.

Unit – IV 10 Hrs Exploring cloud infrastructures: managing the cloud: administrating the clouds-Management

responsibilities-lifecycle management-cloud management products-emerging cloud

management standards: DMTF cloud management standards-cloud commons and SMI

Self Study: lifecycle management

Unit –V 10 Hrs Understanding cloud security: securing the cloud-the security boundary-security service

boundary-security mapping-securing data-brokered cloud storage access-storage location and

tenancy-encryption-auditing and compliance-establishing identity and presence-identity

protocol standards-windows azure identity standards

Self Study: securing the cloud

Text Book: 1. Barrie Sosinsky , “Cloud Computing Bible” John Wiley & Sons Publications, First

Edition,2011.

Reference book: 1.Cloud Computing :Concepts,Technology & Architecture by Thomas ERL Published May

2013

30

SEMESTER II

ELECTIVE II.2 ADVANCED NETWORKING CONCEPT



Course objectives: This course presents the introduction to data communication principles and networking

Skills sets to be acquired: On successful completion of the course the students should have understood the trends and

principles of data communication & network protocols.

Unit I: 10 Hrs Overview of data communications and networking - network model, layered tasks, Internet

model, OSI model,CISCO Model.

Self Study: OSI model

Unit II: 10 Hrs Physical layer-data and signals – digital transmission, multiplexing, transmission media.

Self Study: multiplexing

Unit III: 10 Hrs Switching: circuit switched networks-virtual circuit networks- structure of a switch.

Telephone network: major components--DSL-cable TV networks-cable TV for data transfer.

Data link layer error detection and correction – types of errors, detection, error correction,

data link control and protocols – flow and error control, stop and wait ARQ, go –back –

NARQ, selective repeat ARQ, HDLC, PPP.

Self Study: Data link layer error detection and correction

Unit IV: 10 Hrs LAN traditional Ethernet, fast Ethernet, gigabit Ethernet, wireless LANs – IEEE 802.11–

Bluetooth connecting LANS, backbone networks and virtual LANS – connecting devices

backbone networks, Virtual LANS. Cellular telephone and satellite networks. Sonnet layers.

Self Study: Virtual LANS

Unit V: 10 Hrs Frame relay-ATM-ATM LANs, architecture-Network Address Translation (NAT)-ICMP-

IGMP –icmpv6.cryptography: Introduction-symmetric and asymmetric-key cryptography-

security services.

Self Study: Network Address Translation

Text book: 1. Behrouz A. Forouzan Sophia Chung Fegan, “Data Communication And Networking”,

4th

Edition, Tata Mcgraw-Hill Publishing Company Limited New Delhi, 6th

Reprint 2007.

Reference book: 1. Andrew S.Tannenbaum, “Computer Networks”,Pearson Education, 3

rd Edition,

New Delhi , 2003.

31

Website Reference:

WWW.Omnisecu.Com/Cisco-Certified-Network-Associate-CCNA/Three-TIER

Hierarchical-Network-Model.PHP

SEMESTER-II

Elective II.3 ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS



Course objective: To enable the students to learn the concepts of Artificial Intelligence.

Skill sets to be acquired: On successful completion of the course the students would get the problem and could solve

the problems.

Unit I 10 Hrs Introduction to artificial intelligences-semantic nets and description matching: semantic nets:

good representation are the key to good problem solving-good representation support

explicit, exposing description-a representation has four fundamental parts-the describe and

match methods and analogy problem-the describe-and-match method and recognition of

abstractions

Self Study: semantic nets

Unit II 10 Hrs Generate and test, means-ends analysis, and problem reduction: the generate-and-test

method-the means-ends analysis method-the problem-reduction method.

Self Study: the problem-reduction method

Unit III 10 Hrs Blind methods: net search is really tree search-search tress explode exponentially-depth-first

search dives into the search tree-breadth-first search pushes uniformly into the search tree-the

right search depends on the tree-nondeterministic search moves randomly into the search

tree-heuristically informed methods: quality measurements turn depth-first search into hill

climbing-foothills, plateaus, and ridges make hill hard to climb-beam search expands several

partial paths and purges the rest-best-first search expands the best partial path-search may

lead to discovery-search alternatives form a procedure family-nets and optimal search: the

best path-redundant paths

Self Study: the rest-best-first search expands the best partial path

Unit IV 10 Hrs Trees and adversarial search: algorithmic methods-heuristic method-rules and rule chaining:

rule-based deducting system-procedures for forward and backward chaining-rules, substrates,

and cognitive modeling: rule-based system viewed as substrate-rule-based system viewed as

models for human problem solving

Self Study: heuristic method

32

Unit V 10 Hrs Frames and inheritance: frames, individuals, and inheritance-demon procedures-frames,

events and inheritance

Self Study: demon procedures

Text book: 1. Patrick Henry Winston, “Artificial Intelligence”, Addision Wesley Publishing Company,

Third Edition.

Reference books: 1.Nils J.Wilson “Artificial Intelligence” ,Morgan Kauf Mann Publishers ,Reprinted 2009.

2.Elaine Rich ,Kevinknight, Sivasangaran B Nair ”Artificial Intelligence” ,Tata Mc Graw

Hill Third Edition, Fourth Reprint 2010 .

SEMESTER-III

ELECTIVE III.1 DIGITAL IMAGE PROCESSING



Course objectives: To enable the students to learn the introduction to digital image processing, fundamentals,

image enhancement and image restoration techniques.

Skill sets to be acquired: On successful completion of the course students would have the knowledge about the

fundamentals of digital image processing, image compression and segmentation.

Unit I 10 hrs Introduction: what is digital image processing – the origin of dip – examples of fields that use

dip – fundamentals steps in dip – components of an image processing system. Digital image

fundamentals: elements of visual perception – light and the electromagnetic spectrum –

image sensing and acquisition – image sampling and quantization – some basic relationship

between pixels – linear & nonlinear operations.

Self-study: some basic relationship between pixels

Unit II 10 hrs Image enhancement in the spatial domain: - background – some basic gray level

transformations – histogram processing – enhancement using arithmetic / logic operations –

basics of spatial filtering – smoothing spatial filters – sharpening spatial filters – combining

spatial enhancement methods.

Self-study: combining spatial enhancement methods.

Unit III 10 hrs Image restoration: a model of the image degradation restoration process – noise models –

restoration is the process of noise only – spatial filtering-estimating the degradation function

33

– inverse filtering – minimum mean square error filtering – constrained least squares filtering

– geometric mean filter – geometric transformations.

Self-study: geometric transformations.

Unit IV 10 hrs Image compression: fundamentals – image compression models – elements of information

theory – error free compression – loss compression – image compression standards.

Self-study: image compression standards.

Unit V 10 hrs Image segmentation: detection and discontinuities – edge linking and boundary deduction –

threshold – region-based segmentation

Self-study: region-based segmentation

Text book: 1. Rafael C.Gonazalez, Richard E. Woods, “Digital Image Processing”, Pearson Education,

Second Edition, 2002.

Reference books: 1. B.Chanda, D.Dutta Majumder, “Digital Image Processing And Analysis”,PHI, 2003.

2. Nick Efford, “Digital Image Processing A Practical Introducing Using Java” ,Pearson

Education,2004.

SEMESTER-III

ELECTIVE III.2 GENETIC ALGORITHM



Course objectives: To enable the students to learn the introduction to digital image processing, fundamentals,

image enhancement and image restoration techniques.


fundamentals of digital image processing, image compression and segmentation.

Unit-I 10 Hrs Introduction: genetic algorithms (GA)-traditional optimization and search methods-GA vs

traditional methods-simple GA-schemata-learning the lingo-GA mathematical foundation:

schema processing-two armed and k-armed bandit problem-building block hypothesis-

minimal deceptive problem. Data structure-ga operations-mapping objectives functions to

fitness values. Fitness scaling-coding-multi parameter representation discrimination-

constraints.

Self-study: GA vs traditional methods

Unit-II 10 Hrs Application of GA:the rise of GA-bagley and adaptive GAme playing program,tosenberg and

biological cell simulation-pattern recognition-metalevel GAs-hollstien and function

34

optimization techniques, programming.function optimization-improvements in basic

techniques-current applications –pipeline systes-structural optimization-medical registration

Self-study: Current applications

Unit-III 10 Hrs Dominence-diploidy and abeyance and reordering operations-other micro operators:

segregation, translocation ,multiple chromosome structure-duplication and deletion. Sexual

determination and differentiation-niche and specification.multi objective optimization-

knowledge based techniques-GA and parallel processors.

Self-study:Knowledge Based Techniques

Unit-IV 10 Hrs Genetic based machine: classifier system-rule and message system-the bucket brigade GA-

implementation issues.

Self-study: Implementation Issues

Unit-V 10 Hrs Genetic based learning (GBL)-development of CSL-smith ‘s poker player-ls 1-performance-

GBL efforts-animate classifier system, pipeline operation classifier system.

Self-study: Animate Classifier system

Text book 1.D.E.Goldberg,”Genetic Algorithms, Optimization And Machine Learning”, Addison

Wesley,2nd

Edition, 2009.

SEMESTER-III

ELECTIVE III.3 ARTIFICIAL NEURAL NETWORKS



Course objectives: To enable the students to learn the introduction to Artificial Neural Network and would have

knowledge about functional units of ANN.


Networks, Neural Systems and Neural Algorithms.

Unit I 10 Hrs

Basics of artificial neural networks : characteristics of neural networks – historical

development of neural network principles – artificial neural networks: terminology – models

of neuron – topology – basic learning laws.

Self-Study: models of neuron

Unit II 10 Hrs

Activation and synaptic dynamics : introduction – activation dynamic models –

synaptic dynamic model – learning models – learning methods.

Self-Study: Learning models

35

Unit III 10 Hrs

Functional units of Ann for pattern recognition tasks : pattern recognition

problem – basic functional units – pattern recognition tasks by the functional units – feed

forward neural networks: introduction – analysis of pattern association networks – analysis of

pattern classification networks – analysis of pattern mapping networks.

Self-Study: pattern recognition tasks by the functional units

Unit IV 10 Hrs

Feedback neural networks : introduction – analysis of linear auto associative

networks – analysis of pattern storage networks. Competitive learning neural networks :

introduction – components of a competitive 29 learning network – analysis of feedback layer

for different output functions – analysis of pattern clustering networks – analysis of feed

mapping network.

Self-Study: analysis of feed mapping network

Unit V 10 Hrs

Applications of neural systems : applications of neural algorithms and systems

character recognition – expert systems applications – neural network control applications,

spatial – temporal pattern recognition – neocognitron and other applications.

Self-Study: temporal pattern recognition

Text books: 1.B.Yegnanarayanan, “Artificial Neural Networks”, Eastern Economy Edition ,– chapter 1,

(Units I to IV)

2. Jacek M.Zurada, “Introduction To Artificial Neural Systems”– Jaico Publishing, 2007.

(Unit V)

SEMESTER-III

ELECTIVE IV.1- CYBER CRIME AND CYBER LAW



Course objectives: To enable the students to learn about the cyber crimes and the way to protect the users from

it.

Skill sets to be acquired: On successful completion of the course students would have the knowledge about digital

footprints, cyber law.

Unit I 10 Hrs Cyber Crime in the information age – investigation of cyber crime-hacking tools:burp suite-

metasploit.

Self study: hacking tools

Unit II 10 Hrs Intellectual Property Rights And Cyber Law – trade mark and cyber domain name right

dispute – cyber and e-commerce – electronic money and the challenge to national monetary

sovereignty.

Self study: cyber and ecommerce

36

Unit III 10 Hrs Digital Footprints: accessing computer evidence – right of privacy: media law on the internet

– indian penal code and cyber law.

Self study: Cyber Law

Unit IV 10 Hrs Protection of cyber consumers in India – employment rights in an information society –

cyber terrorism and its network – legislative and regularity norms in cyberspace – the global

medium in a territorial world – jurisdiction and the internet.

Self study: employment rights in an information society

Unit V 10 Hrs Torts Liability – new horizon in field of information technology by year 2020 – fundamental

of computer contracts – defective hardware or software – proposed amendment to the

information technology act by bill 2005 – electronic filing of cases.

Self study: electronic filing

Text Book: 1. Dr.Gupta & Agrawal ,“Cyber Laws”, Premier Publishing Company, 2009, 1

st Edition.

Reference Book: 1. Yatindra Singh ,“Cyber Laws”, Universal Law Publishing, 5

th Edition, 2013.

Website Reference:

1.https://www.concise-courses.com/hacking-tools/top-ten/(Hacking tools)

SEMESTER-III

Elective IV.2- MULTIMEDIA



Course objectives: To enable the students to learn about the basics for various techniques in multimedia and its

application.

Skill Set To Be Acquired: On successful completion of the course the students would develop the multimedia

applications.

Unit-I 10 Hrs Application: document imaging-image processing and image recognition-full-motion digital

video application-electronic messaging-a universal multimedia application-system

architecture: high resolution graphics display-the IMA architecture framework-network

architecture for multimedia system-network standard-evolving technologies for multimedia

system: hypermedia document-HDTV and UDTV-3-d technologies and holography-fuzzy

logic-digital signal processing(DSP)

Self Study: Digital Signal Processing

https://www.concise-courses.com/hacking-tools/top-ten/

37

Unit-II 10 Hrs Multimedia data interface standards: file formats for multimedia system-video processing

standards-Microsoft’s AVI-the need of data compression: compression standards-non-lossy

compression for images-lossy compression for photographs and video-hardware versus

software compression-multimedia database: multimedia storage and retrieval-database

management system for multimedia system-database organization for multimedia

application-transaction management for multimedia system

Self Study: Compression standards

Unit-III 10 Hrs Compression and decompression:types of compression:lossless compression-loossy

compression-binary image compression schemes:packbits encoding(run-lenth encoding)-ccitt

group 3 1-d compression- ccitt group 3 2-d compression- ccitt group 4 2-d compression-

color,gray,scale,and still-video image compression:b/w tv and color image compression-joint

photographic experts group compression-definition in the jpeg standard-overview of jpeg

compression-jpeg methodology-the discrete cosine transform(DCT):quantization-zigzag

sequence-entropy encoding

Self Study:Quantization

Unit-IV 10 Hrs Audio compression: adaptive differential pulse code modulation-data and file format

standards: rich-text format-TIFF file format: TIFF specification-TIFF structure-TIFF tags-

TIFF implementation issues-TIFF classes-midi file format: MIDI communication protocol-

channel messages-system message-jpeg dib file format for still and motion image: jpeg still

image-jpeg motion image-jpeg AVI file format with jpeg dibs-AVI video file format-mpeg

standards .Twain: twain specification objectives-twain architecture-new wave RIFF file

format-setting up new wave type: Microsoft up new wave type.

Self Study: TIFF structure

Unit-V 10 Hrs Architecture and telecommunication consideration: specialization computational processors:

custom processing chips-digital signal processing-DSPs vs. traditional architectures-memory

system: memory types/speed-memory organization-multimedia board solution: dedicated

function board-multi function boards-virtual reality design: human factors-multimedia inputs

and outputs-virtual reality modeling-virtual reality design consideration-hypermedia

messaging: hypermedia message components: text message-rich-text message-voice

message-full-motion video management-hypermedia linking and embedding: linking in

hypertext document-linking and embedding: definition- multiserver network topologies:

traditional LANs-extended LANs-high-speed LANs-WANs-network performance issues

Self Study: multimedia inputs and outputs

Text book: 1. Prabhat K.Andleigh,Kiran Thakrar, “Multimedia Systems Design”, PHI Learning Private

Limited,New Delhi,2009.

Reference Books: 1 Rajanparekh “Principles of Multimedia”,Fourth Reprint , Tata Mcgraw-Hill, 2008.

2.Ralf Stein Metz And Klara Nahrstedt “Multimedia:Computing,Communication &

Application” Fourth Impression,Pearson, Edcation,2008.

38

SEMESTER-III

ELECTIVE IV.3- BIG DATA ANALYTICS



Course objectives: To enable the students to learn about:

Be exposed to big data

Learn the different ways of Data Analysis

Be familiar with data streams

Learn the mining and clustering

Be familiar with the visualization

Skill Set To Be Acquired: On successful completion of the course the students would

Apply the statistical analysis methods.

Compare and contrast various soft computing frameworks.

Design distributed file systems.

Apply Stream data model.

Use Visualisation techniques

Unit I 10 Hrs

Introduction to big data: Introduction to big data platform – challenges of conventional

systems - web data – evolution of analytic scalability, analytic processes and tools, analysis

Vs reporting - modern data analytic tools, statistical concepts: sampling distributions,

resampling, statistical inference, prediction error.

Unit II 10 Hrs

Data Analysis: Regression modeling, multivariate analysis, bayesian modeling, inference

and bayesian networks, support vector and kernel methods, analysis of time series: linear

systems analysis, nonlinear dynamics - rule induction - neural networks: learning and

generalization, competitive learning, principal component analysis and neural networks;

fuzzy logic: extracting fuzzy models from data, fuzzy decision trees, stochastic search

methods.

Unit III 10 Hrs

Mining data streams: Introduction to streams concepts – stream data model and architecture - stream computing,

sampling data in a stream – filtering streams – counting distinct elements in a stream –

estimating moments – counting oneness in a window – decaying window - realtime analytics

platform(rtap) applications - case studies - real time sentiment analysis, stock market

predictions.

Unit IV 10 Hrs

Frequent itemsets and clustering:Mining frequent itemsets - market based model –

apriori algorithm – handling large data sets in main memory – limited pass algorithm –

counting frequent itemsets in a stream – clustering techniques – hierarchical – k- means –

39

clustering high dimensional data – clique and proclus – frequent pattern based clustering

methods – clustering in non-euclidean space – clustering for streams and parallelism.

Unit V 10 Hrs

Frameworks and visualization:Mapreduce – hadoop, hive, mapr – sharding – nosql

databases - s3 - hadoop distributed file systems – visualizations - visual data analysis

techniques, interaction techniques; systems and applications: , big data analytics using open

source data mining tools: weka and rapid miner

Text Books: 1. Michael Berthold, David J. Hand, Intelligent Data Analysis, Springer, 2007.

2. Anand Rajaraman And Jeffrey David Ullman, Mining Of Massive Datasets, Cambridge

University Press, 2012.

3. Jason Bell, Machine Learning, Wiley Publications, 2015.

References: 1. Bill Franks, Taming The Big Data Tidal Wave: Finding Opportunities In Huge Data

Streams With Advanced Analystics, John Wiley & Sons, 2012.

2. Glenn J. Myatt, Making Sense Of Data, John Wiley & Sons, 2007 Pete Warden, Big Data

Glossary, O Reilly, 2011.

3. Jiawei Han, Micheline Kamber “Data Mining Concepts And Techniques”, Second Edition,

Elsevier, Reprinted 2008.

Elective V.1- PATTERN RECOGNITION



Course objectives: To enable the students to learn about the basics for various techniques in pattern recognition

Skill Set To Be Acquired:

On successful completion of the course the students have knowledge about various theories,

Nonparametric techniques and Neural networks.

UNIT-I 10 Hrs Probability: Introduction-probabilities of events-random variables-joint distributions and

densities-moments of random variables-estimation of parameters from samples-minimum

risk estimators-problems. Statistical Decision Making: Introduction- bayes theorem-multiple

features-conditionally independent features-decision boundaries-unequal costs of error-

estimation of error rates-the leaving one out technique-characteristic curves-estimating the

composition of populations-problems.

Self Study: estimating the composition of populations

UNIT-II 10 Hrs Non Parametric Decision Making: Introduction-histograms-kernel neighbor classification

techniques-adaptive decision boundaries-adative discriminant functions-minimum squared

error discriminate function-choosing a decision making technique-problems. Clustering:

Introduction-hierarchical clustering-partitioned clustering-problems.

Self Study: Histograms

40

UNIT-III 10 Hrs Artificial neural networks: Introduction-nets without hidden layers-nets with hidden layers-

the back propagation algorithm-Hopfield nets-an application: classifying sex from facial

images-problems.

Self Study: Problems

UNIT-IV 10 Hrs Processing Of Waveforms And Images: Introduction-gray level scaling transformations-

equalization-geometric image scaling and interpolation-smoothing transformations-edge

detection-laplacian and sharpening operators-line detection and template matching-

logarithmic gray level scaling-the statistical significance of image features-problems.

Self Study: Smoothing Transformation

UNIT-V 10 Hrs Image Analysis: Introduction-scene segmentation and labeling-counting objects-perimeter

measurement-following and representing boundaries-projections-Hough transforms-least

squares and eigenvector line fitting-shapes of regions- morphological operations-texture-

Fourier transforms-color-system design-the classification of white blood cells-image

sequences-cardiac blood-pool image sequence analysis-computer vision-image compression-

problems.

Self Study: image compression

TEXT BOOK:

1. Earl Gose, Richard Johnsonbaugh and Steve Jost, “Pattern Recognition And Image

Processing”, Prentice Hall India,2002.

SEMESTER-IV

Elective V.2- BIOINFORMATICS


Total Instructional Hours:50 Course objectives:

To enable the students to learn about the concepts of both Biology and Information

Technology

Skill Set To Be Acquired:

On successful completion of the course the students would acquire knowledge in biological

term used in IT.

Unit I : 10 Hrs Molecular Biology, Gene Structure and Information Content, Molecular Biology Tools,

Genomic Information Content, Data Searches and Pairwise Alignments, Gaps, Scoring

Matrices, Needleman and Wunsch Algorithm, Global and Local Alignments, Database

Searches.

Self Study: Scoring Matrices

Unit II : 10 Hrs Patterns of Substitution Within Genes, Estimating Substitution Numbers, Molecular Clocks,

Molecular Phylogenetics, Phylogenetic Trees, Distance Matrix Methods.

Self Study: Distance Matrix Methods

41

Unit III: 10 Hrs

Character-Based Methods Of Phylogenetics, Parsimony, Ancestral Sequences, Searches,

Consensus Trees, Tree Confidence, Genomics, Prokaryotic Gene Structure, Gene Density,

Eukariotic Genomes, Gene Expression.

Self Study: Gene Expression.

Unit IV : 10 Hrs Protein and RNA Structure Prediction, Polypeptic Composition, Secondary and Tertiary

Structure, Algorithms For Modeling Protein Folding, Structure Prediction

Self Study: Structure Prediction.

Unit V : 10 Hrs Proteomics, Protein Classification, Experimental Techniques, Ligand Screening, Post-

Translational Modification Prediction.

Self Study: Protein Classification.

Text Book: 1. D. E. Krane and M. L. Raymer ,"Fundamental Concepts of Bioinformatics" , Pearson

Education , 2003.

References Books:

1. T. K. Attwood and D. J. Parry-Smith ,"Introduction to Bioinformatics",Pearson Education,

2007.

2. J. H. Zar ,“Biostatistical Analysis” , Pearson Education , Fifth Edition 2010.

SEMESTER- V

Elective V.3 ROBOT TECHNOLOGY



Course objective: To enable the students to learn the concepts of robot technology.

Skill sets to be acquired: On successful completion of the course the students would develop few kinds of robots.

Unit-I 10 Hrs Introduction: Objectives-automation and robots- brief history-the technology of robots-

economic and social issues-present and future applications. Robot Technology: Objectives-

fundamentals-general characteristics-basic components-robot anatomy-robot generations-

robot selection.robot classification: objectives-classification-arm geometry-degrees of

freedom-power sources-type of motion-path control-intelligence level

Self Study: Robot Generations.

42

Unit-II 10 Hrs Robot system analysis: Objectives-robot operation-hierarchical control structures-control

structure-line tracking-dynamic properties of robots-modular robot components. Robot End

Effectors: objectives-types of end effectors-mechanical grippers-gripper forces analysis-

other types of grippers-special-purpose grippers-grippers selection and design-process

tooling-compliance.

Self Study: Modular Robot Components.

Unit-III 10 Hrs Sensors: objectives-robot sensors-sensor classification-micro switches-solid-state switches-

proximity sensors-photoelectric sensors-rotary positions-usage and selection of sensors-

signal processing-sensors and control integration. Vision: objectives-visual sensing-machine

vision-machine vision applications-other optical methods

Self Study: Sensor Classification.

Unit-IV 10 Hrs Control systems: objectives-control systems correlation-control system requirements-

programmable logic controller-PLC programming terminals-proportional-integral-derivative-

computer numerical control-microprocessor unit- universal robot controller-interfacing-work

cell control. Programming: objectives-robot programming-programming methods-

programming languages-levels of robot programming-space position programming-motion

interpolation-program statements-sample programs

Self Study: Microprocessor Unit.

Unit-V 10 Hrs Safety: Objectives-robot safety-safety standards-system reliability-human factor issues-

safety sensors and monitoring-safeguarding-training-safety guidelines-definitions. Industrial

Applications: objectives-automation in manufacturing-robot applications-material-handling

applications-processing operations –assembly operations-inspection operation-evaluating the

potential of a robot application-future applications-challenge for the future-innovations-case

studies

Self Study: Human Factor Issues.

Text book: 1. James G.Keramas “Robot Technology Fundamentals”, Thomson Delmar Publications,

1998.

Reference Book: 1."Fundamentals of Robotics, analysis & Control" Robert J. Schilling, Prentice Hall of India

P.Ltd., 2002.

43

EXAMINATION SYSTEM UNDER AUTONOMY

1. Pattern of Examinations:

The college follows semester pattern. Each academic year consists of two semesters and each semester ends with the End Semester Examination. A student should have a minimum of 75% attendance out of 90 working days to

become eligible to sit for the examinations.

2. Internal Examinations: The questions for every examination shall have equal representation from the

units of syllabus covered. The question paper pattern and coverage of syllabus for each of the internal (CIA) tests for PG programs other than MBA

and MCA are as follows. i) First Internal Assessment Test

Syllabus : First Two Units Working Days : On completion of 30 working days, approximately

Duration : Two Hours Max. Marks : 50

For the First internal assessment test, the question paper pattern shall

be as given below.

Question Paper Pattern

Section A

Attempt all questions (three each from both units) 06 questions – each carrying one mark 06 X 01 = 06 No Choice

Section B

Attempt all questions (two each from both units) 04 questions – each carrying five marks 04 X 05 = 20 Inbuilt Choice [Either / Or]

Section C Attempt all questions (Minimum one question shall be asked from each unit)

03 questions - each carrying eight marks 03 X 08 = 24 Inbuilt Choice [Either / Or]

Reduce these marks to a maximum of 05 i.e.,(Marks obtained/50) X 5== A

44

ii) Second Internal Assessment Test

Syllabus : Third and Fourth Units Working Days : On completion of 65 working days approximately,

Duration : Two Hours Max. Marks : 50

For the Second internal assessment test, the question paper pattern

shall be as given below.


Section A

Attempt all questions

06 questions – each carrying one mark 06 X 01 = 06 No Choice

Section B

Attempt all questions (two each from both units) 04 questions – each carrying five marks 04 X 05 = 20 Inbuilt Choice [Either / Or]

Section C

Attempt all questions (Minimum one question shall be asked from each unit)

03 questions - each carrying eight marks 03 X 08 = 24 Inbuilt Choice [Either / Or]

Reduce these marks to a maximum of 05 i.e., (Marks obtained/50) X 5 == B

iii) Model Examinations

Syllabus : All Five Units

Working Days : On completion of 85 working days approximately, Examination : Commences any day from 86th working day to 90th working day.

Duration : Three Hours Max. Marks : 75

For the model examinations, the question paper pattern shall be the

same for all UG and PG programs, as given below.

45


Section A

Attempt all questions 10 questions – each carrying one mark 10 X 01 = 10

No Choice Section B


05 questions – each carrying five marks 05 X 05 = 25

Inbuilt Choice [Either / Or]

Section C

Attempt all questions 05 questions – each carrying eight marks 05 X 08 = 40 Inbuilt Choice [Either / Or]

Reduce these marks to a maximum of 10 i.e.,(Marks obtained / 75) X 10 C

The following is the Question Paper Pattern for the courses ‘Yoga for the modern age’ & ‘Professional Ethics’

Syllabus : All Five Units

Duration : Three Hours

Max. Marks : 50


Section A (5 x 10 = 50 marks)

Five Questions of “either / or” type. Each question carries 10 marks.

Answer all questions

Q.1 (a) ___________________ or (b) ___________________

Q.2 (a) ___________________ or (b) ___________________

Q.3 (a) ___________________ or

(b) ___________________

Q.4 (a) ___________________ or

(b) ___________________

Q.5 (a) ___________________ or

(b) ___________________

46

iv) Assignments

Each student is expected to submit at least two assignments per

course. The assignment topics will be allocated by the course teacher. The students are expected to submit the first assignment before the commencement of first Internal Assessment Test and the second assignment

before the commencement of second Internal Assessment Test. Typed/computer print outs and photo copies will not be accepted for

submission. Scoring pattern for Assignments

Punctual Submission : 2 Marks

Contents : 4 Marks Originality/Presentation skill : 4 Marks

Maximum : 10 Marks x 2 Assignments = 20 marks

Reduce these marks to a maximum of 5 i.e., (Marks obtained / 20)X 5 ==D

v) Seminars

Each PG student is expected to present the two assignments as

seminar in the class. Scoring pattern for Seminars

Logical and clear presentation : 3

Illustration : 3 Originality / Presentation skill : 4

Maximum : 10 Marks x 2seminars = 20marks

Reduce these marks to a maximum of 5 i.e.,(Marks obtained / 20)X 5===F

Calculation of Internal Marks for all PG and Parallel programs: 1. Internal Assessment Test : Average of the two tests.

Reduced to a Maximum of 05 Marks (A+B)/2

2. Model Examination : Reduced to a Maximum of 10 Marks (C) 3. Assignment : Reduced to a Maximum of 05 Marks (D)

4. Seminars : Reduced to a Maximum of 05 Marks (F)

Internal Marks Scored = ((A + B)/2) + C + D + F

47

Calculation of Exclusive Internal Marks For “Quantitative Aptitude And

Verbal Reasoning” For All PG Programmes

a) Average of two cycle tests – For a maximum of 25 marks

b) Model Examinations – For a maximum of 50 marks c) Assignment marks – For a maximum of 05 marks d) Seminar marks – For a maximum of 10 marks

e) Unannounced Quiz – For a maximum of 10 marks Total marks – 100 marks

vii) Calculation of Internal Marks for Yoga and Professional Ethics all PG

1. I Cycle Test : 50 marks test is reduced to the maximum to 15 Marks

2. II Cycle Test : 50 marks test is reduced to the maximum to 15 Marks

3. Model : 50 marks test is reduced

to the maximum to 20 Marks --------------------

50 Marks

------------------- viii) Practical Examination

The Internal Assessment marks for practical examinations are

based on the following criteria. The assessment is for 40 % marks of each

practical course. I Cycle Test - 5

II Cycle Test - 5 Model - 10 Lab Performance - 12

Record - 8 -------- Total 40

-------- ix) Project and Viva Voce

The Project assessment will be done for 100 marks for each Project /

Research work. 40 marks for internal assessment mark and 60 marks for

External assessment mark.

The Internal Assessment mark for project evaluation is based on the

following criteria.

a. I Review 10

b. Pre Final Review 15

c. Final Review 15

----------------- Total 40

-----------------

48

I Review Title

Synopsis Introduction Module description

Existing and proposed system Pre Final Review Data Flow Diagram

System Flow Diagram Entity Relationship Diagram

Database Design Final Review Testing

Implementation

Form Design

3. External Examinations:

The external examinations for theory courses will be conducted for 75 %

marks, for all UG and PG degree programs. The external theory examinations

will be conducted only after the completion of 90 working days in each

semester.

Normally, the external practical examinations will be conducted before

the commencement of theory examinations. Under exceptional conditions

these examinations may be conducted after theory examinations are over. The

external evaluation will be for 60 % marks of each practical course.

The External Assessment marks for practical examinations are

based on the following criteria. The assessment is for 60 % marks of each

practical course.

Programmes(2*24)48 (Algoritham 12 marks

Key and execution 12 marks)

Record 12

-------- Total 60

-------

The external viva voce examinations Research / project works also will

be conducted after the completion of theory examinations. The external

assessment is for 60 % marks of the project / research work / Dissertation.

The External Assessment mark for project evaluation is based on

the following criteria.

a) Assessment (80%) 48

b) Viva (20%) 12 ------------------ Total 60

49

a. Methodology 10

b. Application Skill / Tools & Techniques / Analysis 18

c. Logical Presentation & result / Future enhancement

/ Suggestion 10

d. Regularity with Punctuality 10

------------------- Total 48

End Semester Examination Question Paper Pattern

Syllabus : All Five Units Working Days : On completion of a minimum of 90 working days. Duration : Three Hours

Max. Marks : 75


For the End semester external theory examinations, the question paper

pattern shall be the same for all UG and PG programs, as given below, except in the case of Part – II English.

Section A

Attempt all questions 10 questions – each carrying one mark 10 X 01 = 10

No Choice Section B


05 questions – each carrying five marks 05 X 05 = 25 Inbuilt Choice [Either / Or]

Section C

Attempt all questions 05 questions – each carrying eight marks 05 X 08 = 40

Inbuilt Choice [Either / Or]

4. Essential conditions for the Award of Degree / Diploma / Certificates:

1. Pass in all components of the degree, i.e., Part–I, Part–II, Part–III, Part

– IV and Part–V individually is essential for the award of degree.

2. First class with Distinction and above will be awarded for part III only.

Ranking will be based on marks obtained in Part – III only. GPA (Grade Point Average) will be calculated every semester separately. If a

candidate has arrears in a course, then GPA for that particular course will not be calculated. The CGPA will be calculated

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1. for those candidates who have no arrears at all. The ranking also will

be done for those candidates without arrears only.

2. The improvement marks will not be taken for calculating the rank. In

the case of courses which lead to extra credits also, they will neither be considered essential for passing the degree nor will be included for computing ranking, GPA, CGPA etc.

3. The grading will be awarded for the total marks of each course.

4. Fees shall be paid for all arrears courses compulsorily.

5. There is provision for re-totaling and revaluation for UG and PG programmes on payment of prescribed fees.

5. Classification of Successful Candidates [Course-wise]

RANGE OF MARKS (In percent)

GRADE POINTS GRADE DESCRIPTION

90 - 100 9.0 - 10.0 O OUTSTANDING

80 - 89 8.0 - 8.9 D+ EXCELLENT

75 - 79 7.5 - 7.9 D DISTINCTION

70 – 74 7.0 - 7.4 A+ VERY GOOD

60 – 69 6.0 - 6.9 A GOOD

50 – 59 5.0 - 5.9 B AVERAGE

40 – 49 # 4.0 - 4.9 C SATISFACTORY

00 – 39 0.0 U RE-APPEAR

ABSENT 0.0 U ABSENT

Reappearance is necessary for those who score below 50% Marks in PG **; those who score below 40% Marks in UG*; # only applicable for UG programs

Individual Courses

Ci = Credits earned for course “i” in any semester

Gi = Grade Point obtained for course “I” in any semester

'n' refers to the semester in which such courses were credited.

GRADE POINT AVERAGE [GPA] = ΣCi G i

ΣCi

Sum of the multiplication of grade points by the credits of the courses

GPA = --------------------------------------------------------------------------------- Sum of the credits of the courses in a semester

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Classification of Successful Candidates:

CGPA GRADE CLASSIFICATION OF FINAL RESULT

9.5 to 10.0 O+ First Class - Exemplary *

9.0 and above but below 9.5 O

8.5 and above but below 9.0 D++

First Class with Distinction * 8.0 and above but below 8.5 D+

7.5 and above but below 8.0 D

7.0 and above but below 7.5 A++

First Class 6.5 and above but below 7.0 A+

6.0 and above but below 6.5 A

5.5 and above but below 6.0 B+ Second Class

5.0 and above but below 5.5 B

4.5 and above but below 5.0 C+ # Third Class

4.0 and above but below 4.5 C #

0.0 and above but below 4.0 U Re-appear

“*” The candidates who have passed in the first appearance and within the

prescribed semester of the Programme (Major, Allied and Elective Course

alone) are eligible.

“#” Only applicable to U.G. Programme

Σn Σi Cni Gni CUMULATIVE GRADE POINT AVERAGE [CGPA] = ------------------

Σn Σi Cn i

Sum of the multiplication of grade points by the credits of entire program

CGPA= ---------------------------------------------------------------------------------- Sum of the Courses of entire Program

In order to get through the examination, each student has to earn the minimum marks prescribed in the internal (wherever applicable) and

external examinations in each of the theory course, practical course and project viva.

Normally, the ratio between internal and external marks is 25:75. There is no passing minimum for internal component. The following are the

minimum percentage and marks for passing of each course, at UG and PG levels for external and aggregate is as follows:

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S.No Program

Passing Minimum in Percent

External (75) Aggregate

(100)

1 UG Degree 40% (30) 40% (40)

2 PG Degree 50% (38) 50% (50)

However, the passing minimum marks may vary depending up on the

maximum marks of each course. The passing minimum at different levels of marks is given in the following table:

S.N

o

UG & PG

Maximum Marks

Passing minimum for

UG

Passing minimum

for PG

Int. Ext. Total Int. Ext. Agg. 40%

Int. Ext. Agg. 50%

1 25 75 100 - 30 40 - 38 50

2 50 150 200 - 60 80 - 75 100

3 40 60 100 - 24 40 - 30 50

4 80 120 200 - 48 80 - 60 100

5 80 20 100 - 8 40 - 10 50

6 160 40 200 - 16 80 - 20 100

7 15 60 75 - 24 30 - 30 38

8 50 - 50 20 - 20 25 - 25

9 - 50 50 - 20 20 - 25 25

10 - - 100 - - - - 50 50

11 20 30 50 - - - - 15 25

12 - - 200 - - - - 100 100

13 10 40 50 - - - - 20 25

Reappearance The students having arrears shall appear in the subsequent semester

(external) examinations compulsorily. The candidates may be allowed to write

the examination in the same syllabus for 3 years only. Thereafter, the candidates shall be permitted to write the examination in the revised / current syllabus depending on various administrative factors. There is no re-

examination for internals. Criteria for Ranking of Students:

1. Marks secured in core and elective courses (Part-III) will be considered for PG Programs and marks secured in core and allied courses (Part-III) will be considered for UG programs, for ranking of students.

2. Candidate must have passed all courses prescribed chosen / opted in the first attempt itself.

3. Improvement marks will not be considered for ranking but will be considered for classification.

External Examination Grievances Committee:

Those students who have grievances in connection with examinations may represent their grievances, in writing, to the chairman of examination grievance committee in the prescribed proforma. The Principal will be

chairman of this committee.

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SREE SARASWATHI THYAGARAJA COLLEGE (AUTONOMOUS) THIPPAMPATTI, POLLACHI - 642 107

Student Grievance Form

(Forms Available at Utility Stores) Date: Place:

From Register No : ………………………………………........,

Name : ………………………………………........, Class : ………………………………………….....,

Sree Saraswathi Thyagaraja College,

Pollachi – 642 107 To

The Principal / Examination-in-charge, Sree Saraswathi Thyagaraja College, Pollachi – 642 107

Through: 1. Head of the Department, Department of ……………….……….,

Sree Saraswathi Thyagaraja College,

Pollachi – 642 107 2. Dean of the Department

Faculty of ………………………………., Sree Saraswathi Thyagaraja College, Pollachi – 642 107

Respected Sir / Madam,

Sub: ………………………………………………………… ……………... - reg. NATURE OF

GRIEVANCE:………………………………………………………………...………………

……………………………………………………………………………………………………

……………………………………………………………………………………………………

Thanking you,

Yours Truly,

Signature

Forwarded by:

1. HOD with comments / recommendation

………………………………………………………………………………………...............

2. Dean with comments / recommendation

………………………………………………………………………………………...............

3. Signature and Directions of the Principal

………………………………………………………………………………………...............

4. Controller of Examinations:

………………………………………………………………………………………...............

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