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 : …………………………………………..
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PIN …………………………………………..
6. Residential Phone No : STD Code …………………………………………..
: Phone No …………………………….................
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7. Temporary Address : …………………………………………..
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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
Credits:4 Course Code: N5MCS1T43
Total Instructional Hours:60
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
Credits:4 Course Code: N5MCS1T54
Total Instructional Hours:60
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
Total Instructional Hours: 50
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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Credits:1 Instructional Hours:35
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8
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
Credits:4 Course Code: N5MCS2T51
Total Instructional Hours: 50
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
Credits:4 Course Code: N5MCS2T42
Total Instructional Hours:50
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
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
Credits:4 Course Code: N5MCS2T53
Total Instructional Hours:50
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
Total Instructional Hours:50
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.
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SEMESTER-II
LINUX LAB
Credits:3 Course Code: N5MCS2P46
Total Instructional Hours:40
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
Credits: 4 Course Code: N5MCS2P57
Total Instructional Hours: 40
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
Credits:1 Course Code: N5MCS2T18
Total Instructional Hours:50
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
Total Instructional Hours: 50
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
Credits:4 Course Code: N5MCS3T42
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS3T53
Total Instructional Hours:50
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
Credits: 4 Course Code: N5MCS3P56
Total Instructional Hours: 50
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
Credits:3 Course Code: N5MCS3P57
Total Instructional Hours:50
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)
Credits:2 Course Code: N5MCS3T58
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
Credits:4 Course Code: N5MCS1T45
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS1T45
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS1T45
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS2T54
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS2T54
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS2T54
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS3T44
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS3T44
Total Instructional Hours:50
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: 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
Credits:4 Course Code: N5MCS3T44
Total Instructional Hours:50
Course objectives: To enable the students to learn the introduction to Artificial Neural Network and would have
knowledge about functional units of ANN.
Skill sets to be acquired: On successful completion of the course students would have the knowledge about the
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
Credits:4 Course Code: N5MCS3T55
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS3T55
Total Instructional Hours:50
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
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
Credits:4 Course Code: N5MCS3T55
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS4T41
Total Instructional Hours:50
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
Credits:4 Course Code: N5MCS4T41
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
Credits:4 Course Code: N5MCS4T41
Total Instructional Hours:50
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.
Question Paper Pattern
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
Question Paper Pattern
Section A
Attempt all questions 10 questions – each carrying one mark 10 X 01 = 10
No Choice Section B
Attempt all questions
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
Question Paper Pattern
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
-----------------
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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
Question Paper Pattern
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
Attempt all questions
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:
52
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:
………………………………………………………………………………………...............
54