department of computer science & engineering...m.tech – computer science & engg page 1 dr....

Syllabus

M.Tech – Computer Science & Engg

Dr. K. N. Modi University, Newai Rajasthan

(Established by the Government of Rajasthan &

Recognized by UGC under section 2(F) of UGC Act, 1956.)

Department of Computer Science &

Engineering

Syllabus

M.Tech.

(Computer Science & Engineering)

(Session 2017-18)

Syllabus


EVALUATION SYSTEM

Syllabus


Dr. K N Modi University, Newai Student Evaluation System

Continuous Assessment

All courses undertaken by students are evaluated during the semester using internal system of

continuous assessment. The students are evaluated on class /tutorial participation, assignment work, lab

work, class tests, mid-term tests, quizzes and end semester examinations, which contribute to the final

grade awarded for the subject. Students will be notified at the commencement of each courses about the

evaluation methods being used for the courses and weightages given to the different assignments and

evaluated activities.

In order to make the evaluation system as similar and transparent with any of the globally reputed

educational institutions like N.I.Ts, I.I.Ts etc. the Dr. K. N. Modi University Academic Council has

adopted the grading practices. Here marks obtained in the continuous assessment and end semester

examination are added together and a 10-point grading system will be used to award the student with

on overall letter grade for the course (subject).

Distribution of Marks

(i) Courses without Practical Components

10Marks -IITest Midterm(d)

Marks 10 -ITest Midterm(c)

10Marks -subject)each (for each marks 5 of sAssignment Two(b)

Marks 10 - etc.Seminar Projects, Quizzes, Tests, Class ion,participat Class Attendance(a)

40 Marks

End –Term Examination - 60

__________________________________________

Total : 100

(ii)Courses with Practical Components only

Internal Practical Examination and Continuous Progress- 50

End –Term Examination (Practical) - 50

___________________________________________

Total : 100

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Letter Grading system

Final evaluation of course is carried out on a TEN POINT grading system. Performance Grade and

Grade Points are as shown below:

Table 1

Marks Grade Value Grade Description

91 to 100 10 AA Out Standing

81 to 90 9 A+ Excellent

71 to 80 8 A Very Good

61 to 70 7 B+ Good

51 to 60 6 B Above Average

41 to 50 5 C Satisfactory

Less than 41 0 F Exposed

Absent in the University

Final Examination

0 I Incomplete

Note: In order to convert the GPA and CGPA into percentile, multiply the same with the

Conversion factor of 10.

A student who earns a minimum of 5 grade Point (C grade) in a course (subject) is declared to have

successfully completed the course, and is deemed to have earned the credits assigned to that course. A

course successfully completed cannot be repeated.

A student should have appeared for the end semester examination of the prescribed course of study

(mere appearance in the continuous assessment test is not sufficient) to be eligible for the award of the

degree in the course.

If a student is eligible for but-fails to appeared in the end semester examination, he/she will be awarded

an ‘I grade (in complete) on the grade sheet. For all practical purposes an ‘I ‘Grade is treated as an ‘F’.

If a student is not eligible to appear in the end semester examination owing to his/her not fulfilling the

minimum attendance requirements, he may be permitted to re-register for those courses in which he/she

had attendance shortage, at the next available opportunity.

Grade Point Average (GPA) &Cumulative Grade Point Average (CGPA)

Each course grade will be converted into a specific number of points associated with the grade as

mentioned in above Table 1. Here points are weighted with the number of credits assigned to a course.

The Grade Point Average (GPA) is the weighted average of grade points awarded to a student. The

Grade Point Average for each semester will be calculated only for those students who have passed all

the courses of that semester. The weighted average of GPA’s of all semester that the student has

completed at any point of time is the Cumulative Grade Point Average (CGPA) at that point of time.

CGPA up to any semester will be calculated only for those students who have passed all the courses up

to that semester.

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Calculation of GPA and CGPA :

Example:

Table 2

Courses Credits Letter

Grade

Grade

Value

Credit

Value

Grade

Points

Mathematics 3 B+ 7 3x7 21

Chemistry 3 A 8 3x8 24

Physics 3 A+ 9 3x9 27

Language Lab 2 A 8 2x8 16

TOTAL 11 TOTAL 88

In this case GPA = Total Grade Points 88

Credits 11

Suppose the GPAS in two successive semesters are 7.0 and 8.0 with 26 and 24 respective course

credits, then the

CGPA = 7x26+8x24 = 374

26+24 50

After the results are declared, grade cards will be issued to each student which will contain the list of

courses for that semester and the grades obtained by the student, as well as GPA of that semester.

However, a conversion factor of “10”, will be included, enabling students and future employers for

transforming CGPA into percentage of marks at par with the existing practices of I.I.Ts, N.I.Ts and

A.I.C.T.E.

Minimum Eligibility Requirements in Dr. K. N. Modi University for proceeding to the next

academic year of study.

A First year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is

eligible to study in the 3rd Semester of next academic year.

“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the I & II

Semester ( Combined)”

A Second year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is

eligible to study in the Vth Semester of the next academic year.

“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the IIIrd&

IV Semester (Combined)”

A Third year Student of Dr. K. N. Modi University satisfying the below mentioned requirements is

eligible to study in the VIIth Semester of the next academic year.

“Pass with Minimum C Grade in Four Theory Papers & Pass in Four Laboratory Papers in the Vth&

VI Semester (Combined)”

= = 8.0

= 7.48

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Proficiencies:

Extra-curricular activities as listed below will be offered to students of all programs. These activities

will run in both semesters and evaluated. Activities will be graded as Outstanding/Excellent/

Very Good/Good/ Above Average/ Satisfactory/Exposedl/Incomplete.

The extracurricular activities are sports, cultural:

1. Tennis 2. Athletics 3. Table Tennis

4. Badminton 5. Gymnastics 6. Chess

7. Throw Ball 8. Gardening 9. Organization & Management

10. Football 11. Electronics 12. Fine Arts & Paintings

13. Cricket 14. Social Service Club 15. Rovers & Rangers

16. Volleyball 17. Music and Dramatics 18. Model and Sculptures

19. Basketball 20. Debate 21. Equestrian Race

22. Kho - Kho 23. Robotics 24. Yoga & Meditation

25. Art & Photography Club

26. Cultural Club 27. Any other activity with prior approval of the President.

Guideline for submission of assignment

A. Assignments (Theory)

Following are the guidelines of assignments, their evaluation.

Assignment means a set of work, tasks and/or numerical problems given to the student, on the basis

of topics recently covered in the class as homework to be solved and submitted, within the time

frame given by the faculty and the examination cell. Each assignment should require 5 – 6 hours work

to be done by the student. The Date of Submission (DOS) duly announced on the Date of Allotment

(DOA) to the student and duly mentioned in the Academic Calendar.

1. In a multiple-section course, the preparation, duplication and distribution is the responsibility of the Course Coordinator.

a. Allotment of an assignment should be made in the academic calendar of the semester. b. The Date of Submission (DOS) of an assignment should be the tutorial in the prescribed

week wherever applicable. Where tutorials are not scheduled, submission should be in the first lecture of the subsequent week.

2. Assignment should NOT have any descriptive questions (that can be directly copied from a book or from the internet). However, in those course(s) where only descriptive problems are feasible, prior approval for the same is to be sought from the President in writing mentioning the justification for the same.

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3. The effective teaching for semester is generally of 14 weeks. The minimum number of assignments to be given throughout the semester is two. No assignment should be due in the last week of the semester.

4. The assignment is to be submitted on or before the Date of Submission (DOS) as announced. 5. The evaluation of numerical assignment will be done through a test based on the assignment.

The test would comprise of one of the questions from the assignment to be solved in the class. The following process may be adopted for the purpose:

a) Ask students to bring the assignment sheets to the class (along with calculators, if required).

b) Take 60 sheets of A4 sheets. On each sheet write the roll number of a student and the question number from the assignment that he/she has to solve. Different question for adjacent students. Make student sit roll-number-wise, so that no two adjacent students are given the same problem.

c) Give student just sufficient time to solve the problem assuming that they have done the assignment at home.

d) Make sure they have submitted the assignment before the start of the test and that they are not copying.

6. Marks to be awarded in these assignment-quizzes only if the assignment is submitted in time. 7. For non-numeric assignments the rest could have questions based on the assignment. Make sure

that there are multiple shuffled sets for these tests to prevent copying. The comments on the assignments are mandatory. The marks are to be allotted to submission and test separately.

8. Minimal time to be given to the students to attempt the said tests because they should not require any thinking for solving these as they have already solved these problems earlier.

9. The evaluated assignments/tests are to be shown to the student (as done in scrutiny of the End Term Examination answer sheets) and are to be retained by the instructor. The evaluated assignments/test should be retained till the next assignment is evaluated. This is to permit checking by designated authority at any instance.

10. The assignment-based tests should be given on the Date of Assignment (DOS). Only the students who have submitted the assignment on time should be allowed to take the test, otherwise, the student should be awarded ZERO marks for the same.

11. This procedure is to be announced and explained to the students in the very first class. The importance of timely submission of assignments should be explained.

12. No deviation from this policy is permitted except with a written prior approval from the president.

B. Laboratory Assessments

Following are the guidelines for the conduct and evaluation of practical in all courses with laboratory

components:

1. A practical is where a student is taken to a laboratory and is asked to perform a set of task on the given computer, equipment or on a setup comprising of devices or components. This includes on-the spot conduct of an activity to derive desired results and to report the findings.

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2. A student will have to maintain record of the experiments performed in the labs in the bound lab notebook.

3. The lab notebook should be maintained in the format of a lab journal, where (in general) the aim of the experiment, the observations, calculations, results ad discussions are reported. These should not have any description like ‘method’ etc, unless the method itself is the aim of the experiment. Error analysis forms an essential part of the lab journal.

4. Each lab work performed is to be verified by the respective teachers in the next class. 5. A student will be evaluated on every experiment/lab performed. The components of practical

assessment are to be re-defined, notified to the student and to be strictly adhered to. 6. The records of the students attendance in the lab is to be maintained. The lab file record is

evaluated for 10 marks and the attendance weightage will be again 10 Marks.

Syllabus


DR. K. N. MODI UNIVERSITY

Syllabus and Evaluation Scheme

M.Tech. (Computer Science & Engg) - I Semester

Effective from session 2017-18

S.

N

O.

Sub Code Subject Name Period Evaluation Scheme Credit

Continuous

Assessment

Final

Exam

Total

L T P

1 01MTCS101 Advanced

computer

architecture

3 1 0 40 60 100 4

2 01MTCS102 Object oriented

software

engineering

3 1 0 40 60 100 4

3 01MTCS103 Data mining &

ware housing

3 1 0 40 60 100 4

4 01MTCS104 High performance

networks

3 1 0 40 60 100 4

LAB

1 01MPCS101 Computer

Network lab

0 0 2 50 50 100 1

2 01MPCS102 Unified

Modelling

Language Lab

0 0 2 50 50 100 1

3 01MP1010 Seamless

Learning

0 0 4 100 100 1

4 01MP1011 Co-Curricular

Activities

0 0 4 100 100 1

Total 12 4 12 460 340 800 20

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M.Tech. (Computer Science & Engg) - II Semester


S.

NO.


Continuous

Assessment

Final

Exam

Total

L T P

1 01MTCS201 Advance Java 3 1 0 40 60 100 4

2 01MTCS202 Digital Image

Processing 3

1 0 40 60 100 4

3 01MTCS203 Neural Network &

Fuzzy Logic

3 1 0 40 60 100 4

4 01MTCS204 Information Security 3 1 0 40 60 100 4

LAB

1 01MPCS201 Advance java 0 0 2 50 50 100 1

3 01MP2010 Seamless Learning 0 0 4 100 100 1


Activities

0 0 4 100 100 1

Total 12 4 10 410 290 700 19

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M.Tech. (Computer Science & Engg) - III Semester


S.

NO.


Continuous

Assessment

Final

Exam

Total

L T P

1 02MTCS301 Mobile Computing 3 1 0 40 60 100 4

2 02MTCS302 Software Testing &

Quality Management 3

1 0 40 60 100 4

LAB

1 02MPCS301 Software Testing Lab 0 0 2 50 50 100 1

2 02MPCS302 Seminar & Minor

Project

0 0 12 50 50 100 6



Activities

0 0 4 100 100 1

Total 9 3 12 380 220 600 17

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M.Tech. (Computer Science & Engg) - IV Semester


S.

NO.


Continuous

Assessment

Final

Exam

Total

L T P

1 02MPCS401 Dissertation 0 0 10 200 100 300 15


3 02MP4011 Discipline & Co-

Curricular Activities 0 0 4 100 100 1

Total 400 100 500 17

Syllabus


ADVANCED COMPUTER ARCHITECTURE

CODE: 01MTCS101

Course Objective:

The course is intended to understand the architecture of the computer, how the data is flowed in

the different parts of the computer and how it is processed by the computer. To understand the

different memory architectures used in the computer.

Unit – 1 : Review of Basic Organization and Architectural Techniques

RISC processors, Characteristics of RISC processors, RISC Vs CISC, Classification of

Instruction Set Architectures, Review of performance measurements, Basic parallel processing

techniques: instruction level, thread level and process level.

Unit – 2 : Parallelism

Classification of parallel architectures, Trends towards parallel processing, parallelism in Uni

processor systems, , parallel processing applications.

Bus structures and standards, Synchronous and asynchronous buses, Types and uses of storage

devices, Interfacing I/O to the rest of the system, Reliability and availability, I/O system design,

Platform architecture

Unit – 3 : Instruction Level Parallelism

Basic concepts of pipelining, Arithmetic pipelines, Instruction pipelines, Hazards in a pipeline:

structural, data, and control hazards, Overview of hazard resolution techniques, Dynamic

instruction scheduling, Classification of pipeline processors, nonlinear pipeline and reservation

table, Branch prediction techniques, Instruction-level parallelism using software approaches,

Superscalar techniques, Speculative execution

Unit – 4 : Processors & Memory Hierarchies

Pentium Processor: IA 32 and P6 micro architectures, ARM Processor, vector processing.

Basic concept of hierarchical memory organization, , memory hierarchy in parallel processing

systems, Main memories, Cache memory design and implementation, Virtual memory design

and implementation, Secondary memory technology, RAID

Reference Books:

1. Advanced Computer Architecture Book by Kai Hwang

2. Mano, M “Computer System and Architecture”, PHI.

3. Malvino “Digital Computer Electronics: An Introduction to Microcomputers, 3/e”,

McGraw Hill.

4. Pal Chaudhuri, P. “Computer Organization & Design”, PHI.

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OBJECT ORIENTED SOFTWARE ENGINEERING

CODE: 01MTCS102

Course Objective:

To understand the software development requirements, life cycles, risks, testing and the

maintenance of the software. Software development is contain many phases with the UML

building blocks.

Unit I:

Software Engineering Development, Software processes and characteristics, Software Life Cycle

Models, Standards for developing life cycle models like ISO 9001, Introduction to Object

Oriented Methodology. Size estimation (line of code), cost estimation models.

Unit II:

Model Architecture, Requirements Model, Requirement Engineering Analysis Model, Design

Model, Implementation Model, Test Model, Requirement documentation, nature of SRS,

Characteristic and organization of SRS. Cohesion and Coupling

Unit III:

Object oriented design, Basic Building Blocks of UML, Use case approach, requirement using

DFD, A Conceptual Model of UML, Basic Structural Modelling, UML Diagrams

Unit IV:

Risk Management, Testing process, Design of test cases ,unit testing , Integration testing and

system testing, functional testing , structural testing, Regression testing ,testing tools and

standards.

Unit V:

Management of maintenance, maintenance process, maintenance models, reverse engineering,

software re-engineering documentation.

Reference Books:

1. Stephen R. Scach, “Classical & Object Oriented Software Engineering with UML and

Java”, McGraw Hill, 1999.

2. R.Fairley , ”Software Engineering Concepts”, Tata McGraw Hill,1977.

3. P.Jalote, “An Integrated approach to Software Engineering “ , Narosa,1991.

4. James Peter ,W.Pedrycz,:”software Engineering “,John Wiley & sons.

DATA MINING & DATA WAREHOUSING

CODE: 01MTCS103

Course Objective: The course is concerned to analysis of database used for reporting and

finding out the useful data and result from that database. The data stored in the warehouse

is uploaded from the operational systems. Data Mining is the analysis step of the Knowledge

Discovery in Databases process.

Unit I: Data Mining

Basics of data mining, Data mining techniques, KDD (Knowledge Discovery in Database

Process), Application and Challenges of Data Mining, Data Preprocessing, Data Integration and

http://en.wikipedia.org/wiki/Database

http://en.wikipedia.org/wiki/Reporting

http://en.wikipedia.org/wiki/Uploading_and_downloading

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Transformation, Data Reduction, Discretization and Concept Hierarchy Generation, Introduction

of Web Structure Mining, Web Usage Mining, Spatial Mining, Text Mining, Security Issue,

Privacy Issue, Ethical Issue.

Unit II: Mining Association Rules in Large Databases

Association Rule Mining, Single-Dimensional Boolean Association Rules, Multi-Level

Association Rule, Apriori Algorithm, Time series mining association rules, latest trends in

association rules mining, Constraint based association rule mining.

Unit III: Classification and Prediction

Classification, Supervised & Unsupervised approaches, Measuring central tendency, Clustering

Distance Measures, Types of Clustering, K-Means Algorithm, Decision Tree Induction,

Bayesian Classification, Association Rule Based, Other Classification Methods, Prediction,

Classifier Accuracy, Categorization of methods, Partitioning methods, Cluster Analysis: Data

types in cluster analysis, Categories of clustering methods, Partitioning methods, Parallel

approaches to clustering and outlier analysis, Hierarchical Clustering- CURE and Chameleon,

Density Based Methods-DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model

Based Method –Statistical Approach, Neural Network approach.

Unit IV: Data Warehousing

Concept and Introduction, Need for data warehousing, Basic elements of data warehousing, Data

Mart, Data Warehouse Architecture, extract and load Process, Clean and Transform data, Star

,Snowflake and Galaxy Schemas for Multidimensional databases, Fact constellation and

dimension data, Partitioning Strategy-Horizontal and Vertical Partitioning.

Unit V: OLAP

Data Warehouse and OLAP, Multidimensional data models and different OLAP Operations,

OLAP Server: ROLAP, MOLAP, Data Warehouse implementation, Data Cubes constructions,

Efficient Computation of Data Cubes, Processing of OLAP queries, Indexing Data, Data Cube

Computation and Data Generalization.

Reference Books:

1. M.H.Dunham,”Data Mining: Introductory and Advanced Topics” Pearson Education

2. Jiawei Han, Micheline Kamber,”Data Mining Concepts & Techniques” Elsevier

3. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World: A Practical Guide

for Building Decision Support Systems, Pearson Education

4. Mallach,”Data Warehousing System”, McGraw –Hill

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HIGH PERFORMANCE NETWORKS

CODE: 01MTCS104

Course Objective:

This course provides knowledge about various types of Network, Network Topologies, and

protocols.

UNIT – I : Introduction The Motivation for Internetworking; Need for Speed and Quality of Service; History of

Networking and Internet; Advanced TCP/IP and ATM Networks; Internet Services; Internet

Architecture; Interconnection through IP Routers; Standards; TCP Services; TCP format and

connection management; Encapsulation in IP; UDP Services, Format and Encapsulation in IP; IP

Services; Header format and addressing; Fragmentation and reassembly; classless and subnet

address extensions; sub netting and super netting; CIDR; IPV4 & IPv6.

UNIT –II : Error & Control Messages

ICMP; Error reporting vs Error Correction; ICMP message format and Delivery; Types of

messages; Address Resolution (ARP); BOOTP; DHCP; Remote Logging; File Transfer and

Access; Network Management and SNMP; Comparison of SMTP and HTTP; Proxy Server; The

Socket Interface.

UNIT – III : High Speed Networks Packet Switching Networks; Frame Relay Networks; Asynchronous Transfer Mode (ATM);

ATM protocol Architecture; ATM logical connections; ATM cells; ATM Service categories;

ATM Adaptation Layer; Optical Networks: SONET networks; SONET architecture; High-Speed

LANs: The Emergence of High-Speed LANs; Bridged and Switched Ethernet; Fast Ethernet;

Gigabit Ethernet; Wireless LANs: IEEE 802.11, Bluetooth; Connecting LANs: Devices,

Backbone networks, Virtual LANs.

UNIT – IV: Congestion Control and Quality of Service Congestion Control : Data traffic; Network performance; Effects of Congestion; Congestion

Control; Congestion control in TCP and Frame Relay; Link-Level Flow and Error Control; TCP

flow control.

Quality of Service: Flow Characteristics, Flow Classes; Techniques to improve QoS; Traffic

Engineering; Integrated Services; Differentiated Services; QoS in Frame Relay and

ATM;Protocols for QoS Support: Resource Reservation-RSVP; Multiprotocol Label Switching;

Real-Time Transport Protocol

UNIT – V : Wireless Telephony & Routing

Cellular Telephony; Generations; Cellular Technologies in different generations; Satellite

Networks.

Reference Books:

1. William Stallings, “High-Speed Networks and Internets, Performance and Quality of

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Service”, Pearson Education;

2. B. Muthukumaran, “Introduction to High Performance Networks”, Vijay Nicole Imprints.

3. James F. Kurose, Keith W. Ross, “Computer Networking, A Top-Down Approach Featuring

the Internet”, Pearson Education.

4. Andrew S. Tanenbaum, “Computer Networks”, Pearson Education.

5. Behrouz A. Forouzan, “Data Communications and Networking”, Fourth Edition, McGraw

Hill.

6. Mahbub Hassan, Raj Jain, “High Performance TCP/IP Networking, Concepts, Issues, and

Solutions”, Pearson Education.

Network lab

CODE: 01MPCS101

1. Implementation of network between two or more computer using star topology

2. Implementation of the Data Link Layer framing method such as character stuffing and bit

stuffing in C.

3. Write a program for bit staffing.

4. Implementation of CRC algorithm in C.

5. Write a program for substitution method.

6. Write a program for transposition method.

7. Write a program for find out the self IP address.

8. Write program for find out the IP address of server.

9. Implementation of a Hamming code. We have to code the 4 bit data in to 7 bit data by adding

10. Parity bits. Implementation will be in C.

11. Write a socket program in C to implement a listener and a talker.

Syllabus


UML Lab

CODE: 01MPCS102

Students are required to prepare various UML diagrams for any case study.

Following diagrams should be prepared:

Use case static structure diagram

Object and Class diagram

Sequence Diagram

Collaboration Diagram

State Chart Diagram

Activity Diagram

Component Diagram

Deployment Diagram

Reference Books:

1. Object Oriented Analysis and Design using UML, Mahesh P. Matha, PHI, New Delhi

Syllabus


SECOND SEMESTER

ADVANCE JAVA CODE: 01MTCS201

Course Objective:

Understand the concepts of applet swing jdbc connectivity Serve let jsp.Write client-side Java

applications using Swing jsp servlet Work with Java Web Services.

UNIT – I : Introduction to GUI

AWT: Working with Windows, Graphics, and Text, Using AWT Controls, Layout Managers

and Menus

Swing : Frames, Panels and layouts, Swing Applets

Event Handling : Event Classes, Sources of Events, Event Listeners and Handlers, Handling

Mouse Events, Handling Keyboard events

UNIT – II : Java Database Connectivity and HTML

JDBC : Fundamentals, Establishing Connectivity and working with connection interface,

working with statements, Creating and Executing SQL statements, working with Result Set

Object & Result Set Meta Data, Merging Data from Multiple Tables: Joining, Manipulating

Databases with JDBC, Prepared Statements, Transaction Processing

HTML : Introduction to HTML, HTML Tags, Creating Forms, Creating tables, Managing home

page

UNIT – III : Servlets Introduction to Servlets, Life cycle of servlets, Java Servlets Development Kit, Creating,

Compiling and running servlet, Servlet API, Reading the servlet Parameters, Reading

Initialization parameter, Request Dispatcher, HTTP Request and Response, GET and POST

methods, Using Cookies, Session Tracking, URL Rewriting, Servlet Collaboration, Deployment

Descriptor, Servlet Input Stream and Servlet Output Stream

UNIT – IV : Java Server Pages

JSP, Advantage of JSP technology, JSP Architecture, JSP Access Model, JSP Syntax Basic,

Scripting Elements, Implicit Objects, Directive Elements, Action Elements, Custom tags,

Project Development in JSP, Java Beans, Use Bean in JSP.

UNIT – V : MVC Architecture and Struts

Introduction to MVC architecture, Struts architecture, Struts Components, Controller, Actions,

Interceptors, Result and View Components, Understanding Action Context and Action

Invocation.

Reference Books:

1. Head First Servlets and JSP By Bert Bates, Kathy Sierra, Bryan Basham, O Reilly

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2. Java Programming Advanced Topics, Joe Wigglesworth ‘And Paula Lumby,

Course Technology (Thomson Learning), (2000).

3. The Complete Reference 3/e, Patrick Naughton and Herbert Schildt, TMH).

4. Beginning Java EE 5 From Novice to Professional by Kevin Mukhar and Chris

Zelenak with James L. Weaver and Jim Crume

5. Programming Jakarta Struts by Chuck Cavaness, Publisher: O'Reilly Media

DIGITAL IMAGE PROCESSING

CODE: 01MTCS202 Course Objective:

To understand the concepts of the digital image, image transformation, compression of a image

without affecting the image quality and representation and decryption of the digital image.

Unit I Introduction and Fundamentals

Motivation and Perspective, Applications, Components of Image Processing System, Element of

Visual Perception, A Simple Image Model, Sampling and Quantization. Image Enhancement in

Frequency Domain Fourier Transform and the Frequency Domain, Basis of Filtering in

Frequency Domain, Filters – Lowpass, High-pass; Correspondence Between Filtering in Spatial

and Frequency Domain; Smoothing Frequency Domain Filters – Gaussian Lowpass Filters;

Sharpening Frequency Domain Filters – Gaussian Highpass Filters; Homomorphic Filtering.

Unit II

Image Enhancement in Spatial Domain Introduction; Basic Gray Level Functions – Piecewise-

Linear Transformation Functions: Contrast Stretching; Histogram Specification; Histogram

Equalization; Local Enhancement; Enhancement using Arithmetic/Logic Operations – Image

Subtraction, Image Averaging; Basics of Spatial Filtering; Smoothing - Mean filter, Ordered

Statistic Filter; Sharpening – The Laplacian.

Unit III Image Restoration

A Model of Restoration Process, Noise Models, Restoration in the presence of Noise only-

Spatial Filtering – Mean Filters: Arithmetic Mean filter, Geometric Mean Filter, Order Statistic

Filters – Median Filter, Max and Min filters; Periodic Noise Reduction by Frequency Domain

Filtering – Bandpass Filters; Minimum Mean-square Error Restoration.

Unit IV

http://shop.oreilly.com/product/9780596003289.do#tab_04_2

Syllabus


Morphological Image Processing Introduction, Logic Operations involving Binary Images,

Dilation and Erosion, Opening and Closing, Morphological Algorithms – Boundary Extraction,

Region Filling, Extraction of Connected Components, Convex Hull, Thinning, Thickening

Unit V Registration

Introduction, Geometric Transformation – Plane to Plane transformation, Mapping, Stereo

Imaging – Algorithms to Establish Correspondence, Algorithms to Recover Depth Segmentation

Introduction, Region Extraction, Pixel-Based Approach, Multi-level Thresholding, Local

Thresholding, Region-based Approach, Edge and Line Detection: Edge Detection, Edge

Operators, Pattern Fitting Approach, Edge Linking and Edge Following, Edge Elements

Extraction by Thresholding, Edge Detector Performance, Line Detection, Corner Detection.

References:

1. Digital Image Processing 2nd Edition, Rafael C. Gonzalvez and Richard E. Woods.

Published by: Pearson Education.

2. Digital Image Processing and Computer Vision, R.J. Schalkoff. Published by: John Wiley

and Sons, NY.

3. Fundamentals of Digital Image Processing, A.K. Jain. Published by Prentice Hall, Upper

Saddle River, NJ.

4. Sonka, Digital Image Processing and Computer Vision, Cengage Learning

5. Gonzalez and Woods, Digital Image Processing, Addison Wesley.

NEURAL NETWORKS AND FUZZY LOGIC

CODE: 01MTCS203

Course Objective:

To understand the networking concept and the parts and working of the each used in the

network. Understanding the fuzzy logics ,how it is used in the computer. and to understand the

probability theory.

UNIT – I : Introduction

Fundamentals of ANN, Biological prototype, Neural Network Concepts, Definitions Activation,

Functions, single layer and multilayer networks, Training ANNs, perceptrons, Exclusive OR

problem, Linear seperability, storage efficiency, perceptron learning - perceptron training

algorithms, Hebbian learning rule - Delta rule, Kohonen learning law, problem with the

perceptron training algorithm.Back propagation neural network, Training algorithm, network

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configurations, Back propagation error surfaces, Back propagation learning laws, Network

paralysis - Local minima, and temporal instability

UNIT – II : Networks Counter propagation Networks, Kohonen layer, Training the Kohonen layer, preprocessing the

input vectors, initializing the weight vectors.

Statistical properties, Training the Grossberg layer- Feed forward counter propagation Neural

Networks, Applications. Statistical methods simulated annealing, Bloltzman Training, Cauchy

training - artificial specific heat methods, Application to general non-linear optimization

problems, back propagation and cauchy training. Hopfield network

UNIT – III : Fuzzy Logic Classical and Fuzzy Sets, Overview of Classical Sets, Membership Function, a-cuts, Properties

of a-cuts, Decomposition Theorems, Extension Principle, fuzzy operations, fuzziness in neural

networks, neural trained fuzzy system, Bidirectional Associative Memory (BAM), Fuzzy

Associative Memory (FAM), Operations on Fuzzy Sets: Complement, Intersections, Unions,

Combinations of Operations, Aggregation Operations, Fuzzy Arithmetic: Fuzzy Numbers,

Linguistic Variables, Arithmetic Operations on intervals & Numbers, Lattice of Fuzzy Numbers,

Fuzzy Equations.

UNIT – IV : Fuzzy Relations

Crisp & Fuzzy Relations, Projections & Cylindric Extensions, Binary Fuzzy Relations, Binary

Relations on single set, Equivalence, Compatibility & Ordering Relations, Morphisms, Fuzzy

Relation Equations.

UNIT – V : Possibility Theory

Fuzzy Measures, Evidence & Possibility Theory, Possibility versus Probability Theory. Fuzzy

Logic: Classical Logic, Multivalued Logics, Fuzzy Propositions, Fuzzy Qualifiers, Linguistic

Hedges. Uncertainty based Information: Information & Uncertainty, Non-specificity of Fuzzy &

Crisp sets, Fuzziness of Fuzzy Sets.

Reference Books:

1. James A. Freeman and David M. Skapura, Neural Network Algorithms, Application and

Programming Techniques, Addison – Wesley publishing company.

2. Freeman A. James, Skapura M. David, Neural networks algorithms, applications and

programming Techniques, Pearson Education.

3. Philip D. Wasserman, Neural Computing – Theory and Practice, Van Nostrand and Reinhold,

Syllabus


INFORMATION SECURITY

CODE: 01MTCS204

Course Objective:

The course is intended to practice and study of techniques for securing the communication from

unauthorized users. And the policies adopted by the network administrator to prevent and

monitor unauthorized access, misuse, modification, or denial of the computer network and

network-accessible resources.

Unit I : Introduction and Objectives

Basic objectives of cryptography, secret-key and public-key cryptography, one-way and trapdoor

one-way functions, cryptanalysis, attack models, Block ciphers: Modes of operation, DES and its

variants, AES, linear and differential cryptanalysis. Stream ciphers: Stream ciphers based on

linear feedback shift registers.

Unit II : Message Digest

Properties of hash functions, attacks on hash functions. Public-key parameters: Modular

arithmetic, gcd, primality testing, Chinese remainder theorem, modular square roots, finite fields.

Unit III : Intractable problems

RSA problem, modular square root problem, Diffie-Hellman problem, known algorithms for

solving the intractable problems.

Unit IV : Public-key encryption

RSA, side channel attacks. Key exchange: Diffie-Hellman and Digital signatures: RSA, signature

schemes, blind and undeniable signatures. Entity authentication: Passwords, challenge-response

algorithms, zero-knowledge protocols. Standards: IEEE, RSA and ISO standards

Unit V : Network issues

Certification, public-key infrastructure (PKI), secured socket layer (SSL), Kerberos. Advanced

topics: Elliptic and hyper-elliptic curve cryptography, number field sieve, lattices and their

applications in cryptography, hidden monomial cryptosystems, cryptographically secure random

number generators.

Reference Books:

1. William Stallings, Cryptography and Network Security, PHI

2. Atul Kahate, “Cryptography and Network Security”, TMH

3. Calabrese, Info security intelligence-cryptography principles appl., Cengage Learn

4. Krawetz, Intro to network security, Cengage Learning.

http://en.wikipedia.org/wiki/Policies

http://en.wikipedia.org/wiki/Network_administrator

http://en.wikipedia.org/wiki/Unauthorized

http://en.wikipedia.org/wiki/Computer_network

Syllabus


ADVANCED JAVA LAB

CODE: 01MPCS201

Write programs to carry out:

1. Write an Application program /Applet to make connectivity with Database using JDBC

API

2. Write an Application program/Applet to send queries through JDBC Bridge& handle

result.

3. Write a program to design a form using basic swing components.

4. Write a program to demonstrate the use of scroll panes in Swing.

5. Write a servlet for demonstrating the generic servlet class.

6. Write a servlet for demonstrating the generic servlet class.

7. Write a servlet to demonstrate the Http Servlet class using do Get ().

8. Write a servlet to demonstrate the Http Servlet class using do Post ().

9. Write a servlet to demonstrate the cookie

10. Write a servlet for demonstrating the generic jsp class.

Syllabus


THIRD SEMESTER

MOBILE COMPUTING

CODE: 02MTCS301

Course Objective:

This course is intended to understand cellular network concepts, multiple access techniques,

GSM and CDMA architectures, wireless networks, and mobile Ad-hoc network.

UNIT – I : Introduction Overview of Mobile Computing and its applications; Radio Communication; Mobile Computing

Architecture; Mobile System Networks; Data Dissemination; Mobility Management;

Introduction to Cellular network: components, Architecture, Call set-up, Frequency Reuse and

Co-channel cell, Cell Design, Interference, Channel assignment, Hand Off;

UNIT – II : Cellular Networks and Techniques Cellular Network Standards; Digital cellular communication; Multiple Access Techniques:

FDMA, TDMA, CDMA;

GSM: System Architecture, Mobile services & features, Protocols, Radio interface, Handover,

GSM Channels, Localization and calling, User validation; General Packet Radio Service;

Introduction to CDMA based systems; Spread spectrum in CDMA systems; coding methods in

CDMA; IS-95

UNIT – III : Wireless and Bluetooth Wireless LAN, Wireless LAN (Wi-Fi) Architecture and protocol layers, WAP Architecture,

Bluetooth Architecture, Layers, Security in Bluetooth.

UNIT – IV : Mobile Ad-hoc and Sensor Networks Introduction, MANET, Routing in MANET’s Wireless Sensor Networks, Applications; Mobile

Devices: Mobile Agent, Application Server, Gateways, Portals, Service Discovery, Device

Management,

Unit –V : Network System and Protocols

Mobile File Systems; Mobile IP: Architecture, Packet delivery and Hand over Management,

Location Management, Registration, Tunneling and Encapsulation, Route optimization, DHCP.

Mobile Transport Layer: Conventional TCP/IP transport protocols, Indirect TCP, Snooping TCP,

Mobile TCP

Reference Books:

1. Jochen Schiller, “Mobile Communications”, Second Edition, Pearson Education, 2004.

2. Raj Kamal, “Mobile Computing”, Oxford Higher Education, 2008.

3. Sipra DasBit, Biplab K. Sikdar, “Mobile Computing”, PHI, 2009.

4. William C.Y.Lee, “Mobile Cellular Telecommunications”, Second Edition, (Tata

McGraw-Hill), 2006.

Syllabus


SOFTWARE TESTING & QUALITY MANAGEMENT

Code: 02MTCS302

Course Objective:

This course is intended to understand the concepts of software testing, automation, software

quality, quality assurance, errors occurred in the software their quality and actions to be taken

for removing the errors.

Unit – 1 : Introduction

Software, Software Development Life Cycle, V-Model, Error, Fault, Failure, Software Testing

Life cycle, Limitations of the testing, Need of the software testing, Types of testing, Test

Documentation, Test Environment Set Up, Test Data, Test Cases, Entire Flow/Test Execution,

Test Reporting – Metrices.

Unit – 2 : Levels of Testing

Functional Testing, Boundary Value Analysis, Equivalence Class Testing, Decision Table Based

Testing, Cause Effect Graphing Technique.

Structural Testing, Path testing, DD-Paths, Cyclomatic Complexity, Graph Metrics, Data Flow

Testing, Mutation testing, Risk Analysis, Regression Testing, Slice based testing, Integration

Testing, System Testing, Debugging, Domain Testing.

Unit – 3 : Object Oriented Testing Issues and Automation

Object Oriented Testing, Testing issues, Class Testing, GUI Testing, Object Oriented Integration

and System Testing, Manual & Automation Teting, Testing Stand Alone Applications, Project

based Automation, Product based Automation Testing Tools, Static Testing Tools, Dynamic

Testing Tools, Characteristics of Modern Tools.

Unit – 4 : Software Quality and SQA

Software Quality: Concepts of software quality, quality attributes, software quality control,

Hierarchical models of Boehm and McCall, Quality measurement – Metrics measurement and

analysis.

Software Quality Assurance: Quality tasks, SQA plan, Teams, Characteristics,

Implementation, Documentation, Reviews and Audits

Unit – 5 : Quality Control and Management System

Tools for Quality, CASE tools, Reliability growth models for quality assessment

Elements of Quality Management System, Rayleigh model framework, Reliability Growth

models for QMS, Complexity metrics and models, Customer satisfaction analysis.

Quality Standards, Need for standards, ISO 9000 Series, ISO 9000-3 for software development,

CMM and CMMI, Six Sigma concepts.

Syllabus


Reference Books:

1. Boris Beizer, “Software Testing Techniques”, Second Volume, Second Edition,Van

Nostrand Reinhold, New York, 1990.

2. Louise Tamres, “Software Testing”, Pearson Education Asia, 2002.

3. Roger S. Pressman, “Software Engineering – A Practitioner’s Approach”, Fifth Edition,

McGraw-Hill International Edition, New Delhi, 2001.

4. Robert Dunn,”Software Quality Concepts and Plans”, Prentice-Hall,1990.

5. Alan Gillies,”Software Quality, Theory and management”, Chapman and Hall,1992.

6. Michael Dyer, “The Cleanroom approch to Quality Software Engineering “,Wiley &

Sons.1992.

7. Tom Gilb, ” Prnciples of Software Engineering Management”, Addison-Wesley,1988.

SOFTWARE TESTING LAB

CODE : 02MPCS301

1. Hands on Software Engineering principles Infrastructure.

2. Usage of Front-end and Back-end technologies and packages

3. Prepare the following documents for three of the experiments listed below Using

software engineering methodology.

a. Program Analysis and Project Planning.

b. Thorough study of the problem – Identify project scope, Objectives,

c. Software requirement Analysis

4. Describe the individual Phases / Modules of the project, Identify deliverables

5. Software Design

a. Use work products – Data dictionary, Use case diagrams and activity diagrams,

Build and test class diagrams,

b. Sequence diagrams and add interface to class diagrams, DFD, ER diagrams

c. Software Development and Debugging using any Front end and Back end tool

d. Software Verification and Validation procedures

SEMINAR AND MINOR PROJECT

CODE : 02MPCS302

Students have to select one topic given by the department .He \She has to first submit the

synopsis, and then carry out detailed study on the subject. He has to submit his progress to the

guide assigned. He has to give presentation of near about 15 minutes duration on the topic

assigned.

A team consisting of Dean, HOD and External examiner appointed by University shall carry out

the evaluation of the student for his/her major project and evaluation for his/her professional

branch

Syllabus


FOURTH SEMESTER

DISSERTATION

CODE: 02MPCS401

The students have to submit a synopsis in a specified format at the beginning of the semester for

the approval by the university project committee. The students have to present the progress

report of the work through seminars and progress reports. A report must be submitted to the

university for the evaluation purpose at the end of the semester in a specific format.

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