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COURSE HAND-OUT B.TECH. - SEMESTER VIII DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

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Page 1: emester VI, Course Hand-Out

COURSE HAND-OUT

B.TECH. - SEMESTER VIII

DEPARTMENT OF COMPUTER SCIENCE

AND ENGINEERING

Page 2: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 2

RAJAGIRI SCHOOL OF ENGINEERING AND

TECHNOLOGY (RSET)

VISION

TO EVOLVE INTO A PREMIER TECHNOLOGICAL AND RESEARCH INSTITUTION,

MOULDING EMINENT PROFESSIONALS WITH CREATIVE MINDS, INNOVATIVE

IDEAS AND SOUND PRACTICAL SKILL, AND TO SHAPE A FUTURE WHERE

TECHNOLOGY WORKS FOR THE ENRICHMENT OF MANKIND

MISSION

TO IMPART STATE-OF-THE-ART KNOWLEDGE TO INDIVIDUALS IN VARIOUS

TECHNOLOGICAL DISCIPLINES AND TO INCULCATE IN THEM A HIGH DEGREE

OF SOCIAL CONSCIOUSNESS AND HUMAN VALUES, THEREBY ENABLING

THEM TO FACE THE CHALLENGES OF LIFE WITH COURAGE AND CONVICTION

Page 3: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 3

DEPARTMENT OF COMPUTER SCIENCE AND

ENGINEERING (CSE), RSET

VISION

TO BECOME A CENTRE OF EXCELLENCE IN COMPUTER SCIENCE &

ENGINEERING, MOULDING PROFESSIONALS CATERING TO THE RESEARCH

AND PROFESSIONAL NEEDS OF NATIONAL AND INTERNATIONAL

ORGANIZATIONS.

MISSION

TO INSPIRE AND NURTURE STUDENTS, WITH UP-TO-DATE KNOWLEDGE IN

COMPUTER SCIENCE & ENGINEERING, ETHICS, TEAM SPIRIT, LEADERSHIP

ABILITIES, INNOVATION AND CREATIVITY TO COME OUT WITH SOLUTIONS

MEETING THE SOCIETAL NEEDS.

Page 4: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 4

B.TECH PROGRAMME

PROGRAMME EDUCATIONAL OBJECTIVES (PEOs)

1. Graduates shall have up-to-date knowledge in Computer Science & Engineering along

with interdisciplinary and broad knowledge on mathematics, science, management

and allied engineering to become computer professionals, scientists and researchers.

2. Graduates shall excel in analysing, designing and solving engineering problems and

have life-long learning skills, to develop computer applications and systems, resulting

in the betterment of the society.

3. Graduates shall nurture team spirit, ethics, social values, skills on communication and

leadership, enabling them to become leaders, entrepreneurs and social reformers.

PROGRAMME OUTCOMES (POs)

Graduates will be able to achieve

a. An ability to apply mathematical foundations, algorithmic principles, and computer

science theory in the modelling and design of computer-based systems.

b. An ability to identify, analyse, formulate and solve technical problems by applying

principles of computing and mathematics relevant to the problem.

c. An ability to define the computing requirements for a technical problem and to

design, implement and evaluate a computer-based system, process or program to

meet desired needs.

d. An ability to learn current techniques, skills and modern engineering tools necessary

for computing practice.

e. An ability to carry out experiments, analyse results and to make necessary

conclusions.

f. An ability to take up multidisciplinary projects and to carry out it as per industry

standards.

g. An ability to take up research problems and apply computer science principles to

solve them leading to publications.

h. An ability to understand and apply engineering solutions in a global and social

context.

i. An ability to understand and practice professional, ethical, legal, and social

responsibilities as a matured citizen.

j. An ability to communicate effectively, both written and oral, with a range of

audiences.

Page 5: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 5

k. An ability to engage in life-long learning and to engage in continuing professional

development.

l. An ability to cultivate team spirit and to develop leadership skills thereby moulding

future entrepreneurs.

INDEX

SCHEME: B.TECH 8TH SEMESTER 7

CS010 801 High Performance Computing 8

COURSE INFORMATION SHEET 8

COURSE PLAN 11

CS010 802 Artificial Intelligence 15

COURSE INFORMATION SHEET 15

COURSE PLAN 18

CS010 803 Security in Computing 20

COURSE INFORMATION SHEET 20

COURSE PLAN 23

CS010 804L04 Optimization Techniques 25

COURSE INFORMATION SHEET 25

CS010 804L05 Mobile Computing 29

COURSE INFORMATION SHEET 29

COURSE PLAN 36

CS010 804L06 Advanced Networking Trends 39

COURSE INFORMATION SHEET 39

COURSE PLAN 42

CS010 805G02 Neural Networks 44

COURSE INFORMATION SHEET 44

COURSE PLAN 47

CS010 805G05 Advanced Mathematics 49

COURSE INFORMATION SHEET 49

CS010 805G05 Natural Language Processing 55

COURSE INFORMATION SHEET 55

CS010 806 Computer Graphics Lab 59

COURSE INFORMATION SHEET 59

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Department of CSE, RSET 6

COURSE PLAN 62

CS010 807 Project 65

COURSE INFORMATION SHEET 65

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Semester VIII, Course Hand-Out

Department of CSE, RSET 7

SCHEME: B.TECH 8TH SEMESTER

(Computer Science & Engineering)

Mahatma Gandhi University Revised Scheme for B.Tech. Syllabus Revision 2010

Code Subject

Hours/Week Marks End-Sem

duration

– hours

Credits L T P/D

Inter

-nal

End-

Sem

CS010 801 High Performance

Computing 3 2 - 50 100 3 4

CS010 802 Artificial Intelligence 2 2 - 50 100 3 4

CS010 803 Security in Computing 2 2 - 50 100 3 4

CS010

804Lxx

Elective III 2 2 - 50 100 3 4

CS010

805Gxx

Elective IV 2 2 - 50 100 3 4

CS010 806 Computer Graphics Lab - - 3 50 100 3 2

CS010 807 Project - - 6 100 - - 4

CS010 808 Viva Voce - - - - 50 - 2

Total 11 10 9 28

Electives III CS010 804L01 – E-commerce

CS010 804L02 – Grid Computing

CS010 804L03 – Biometrics

CS010 804L04 – Optimization Techniques

CS010 804L05 – Mobile Computing

CS010 804L06 – Advanced Networking Trends

Electives IV CS010 805G01 – Multimedia Techniques

CS010 805G02 – Neural networks

CS010 805G03 – Advanced Mathematics

CS010 805G04 – Software Architecture

CS010 805G05 – Natural Language Processing

CS010 805G06 – Pattern Recognition

Page 8: emester VI, Course Hand-Out

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Department of CSE, RSET 8

CS010 801 High Performance Computing

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH YEAR: JAN 2014 – JUNE 2014

COURSE: HIGH PERFORMANCE COMPUTING SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 801 COURSE TYPE: CORE /ELECTIVE / BREADTH/ S&H

COURSE AREA/DOMAIN: COMPUTER HARDWARE CONTACT HOURS: 3+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

SYLLABUS:

UNIT DETAILS HOURS

I

Introduction to parallel processing - Trends towards parallel processing - Parallelism in

uniprocessor - Parallel computer structures-Architecture classification schemes

,Amdahl’s

law,Indian contribution to parallel processing.

15

II Principles of pipelining and vector processing - Linear pipelining - Classification of

pipeline processors - General pipelines - Instruction and Arithmetic pipelines –Design

of Pipelined instruction unit-Principles of Designing Pipeline Processors- Instruction

prefetch and branch handling- Data Buffering and Busing Structure-Internal

forwarding and register tagging- Hazard detection and Resolution,Dynamic pipelines

and Reconfigurability

15

III Array processors - SIMD array processors - Interconnection networks - Static vs

dynamic

networks - mesh connected networks - Cube interconnection networks - Parallel

algorithms for array processors - SIMD matrix multiplication-Parallel sorting on array

processors - Associative array processing - Memory organization.

15

IV Multiprocessor architectures and Programming - Loosely coupled and Tightly coupled

multiprocessors - Interconnection networks - Language features to exploit parallelism

–Inter process communication mechanism-Process synchronisation mechanisms,

synchronization with semaphores.

15

V Dataflow computers - Data driven computing and Languages, Data flow computers

architectures - Static data flow computer , Dynamic data flow computer ,Data flow

design

alternatives.

15

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

T Computer Architecture & Parallel Processing - Kai Hwang & FayeA.Briggs,Mc Graw Hill R1 Computer architecture A quantitative approach - John L Hennessy and David A.Patterson-

ELSEVIER, Fourth Edition R2 Elements of Parallel computing - V. Rajaraman - PHI

R3 Super Computers - V. Rajaraman - Wiely arstern

R4 Parallel Processing for Super Computers & AI Kai Hwange & Douglas Degneot Mc Graw Hill R5 Highly parallel computing - George S. Almasi,Allan Gottlieb. - Benjamin Cumings Publishers. R6 HIgh Performance Computer Architecture - Harold S. Stone, Addison Wesley. R7 Advanced Computing- Vijay P.Bhatkar, Asok V.Joshi, Arirban Basu, Asok K.Sharma.

Page 9: emester VI, Course Hand-Out

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Department of CSE, RSET 9

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

CS010

304

COMPUTER ORGANISATION ARCHITECTURE III

COURSE OBJECTIVES:

1 To design a powerful and cost-effective computer system

2 To provide the basic concepts of parallel processing on high performance computers.

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1

Graduates will be able to classify and describe the operation of parallel computer architectures

a

2 Graduates will be able to understand the basic concepts of pipelining and related design issues.

a, b

3 Graduates will be able to learn advanced concepts in multiprocessor architecture and interconnection networks

c, d

4 Graduates will understand the concepts of parallelism especially inter process communication and synchronization

a

5 Graduates will get a thorough knowledge of various design alternatives of dataflow computers c, d

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

PO

MAPPING

1 Study of RISC and CISC architectures Assignment d

2 Case study : IBM Power1( RS6000) Reading

assignment

c,d

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

Sl.No DESCRIPTION PO

MAPPING

1 To study the internal structure of the processing elements in Illiac IV a, d

2 To study operating system requirements for multiprocessors a, d

WEB SOURCE REFERENCES:

1 https://computing.llnl.gov/tutorials/parallel_comp/

2 www.seas.gwu.edu/~narahari/cs211/materials/lectures/simd.pdf

3 csd.ijs.si/courses/dataflow/

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD. ASSIGNMENT WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL EXAMS UNIV. EXAMINATION

STUD. LAB PRACTICES SIMPLE QUESTIONS MINI/MAJOR PROJECTS CERTIFICATIONS

Page 10: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 10

IN TUTORIAL HOUR

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK,

ONCE)

STUDENT FEEDBACK ON FACULTY (TWICE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved by

Ms.Deepa John Mr. Ajith S

(H.O.D)

Page 11: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 11

2014 S8 CS

CS010 801- HIGH PERFORMANCE COMPUTING

COURSE PLAN

Sl.No Module Planned

1 1 Day 1 Introduction to parallel processing

2 1 Day 2 Trends towards parallel processing

3 1 Day 3 Parallelism in Uniprocessor

4 1 Day 4 Parallelism in Uniprocessor

5 1 Day 5 Parallel computer structures

6 1 Day 6 Parallel computer structures

7 1 Day 7 Architecture classification schemes

8 1 Day 8 Architecture classification schemes

9 1 Day 9 Amdahl’s Law

10 2 Day 10 Principles of pipelining and vector processing

11 2 Day 11 Linear pipelining

12 2 Day 12 Classification of pipeline processors

13 2 Day 13 General pipelines

14 2 Day 14 Instruction and Arithmetic pipelines

15 2 Day 15 Design of Pipelined Instruction Unit

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Semester VIII, Course Hand-Out

Department of CSE, RSET 12

16 2 Day 16 Design of Pipelined Instruction Unit

17 2 Day 17 Principles of Designing Pipeline Processors

18 2 Day 18 Instruction Prefetch and Branch Handling

19 2 Day 19 Instruction Prefetch and Branch Handling

20 2 Day 20 Data Buffering and Busing Structure

21 2 Day 21 Data Buffering and Busing Structure

22 2 Day 22 Internal forwarding and register tagging-

23 2 Day 23 Internal forwarding and register tagging-

24 2 Day 24 Hazard detection and Resolution

25 2 Day 25 Hazard detection and Resolution

26 2 Day 26 Dynamic pipelines and Reconfigurability

27 2 Day 27 Dynamic pipelines and Reconfigurability

28 3 Day 28 Array processors - SIMD array processors

29 3 Day 29 Array processors - SIMD array processors

30 3 Day 30 Interconnection networks

31 3 Day 31 Static vs dynamic networks

32 3 Day 32 mesh connected networks

33 3 Day 33 Cube interconnection networks

34 3 Day 34 Parallel algorithms for array processors -

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Department of CSE, RSET 13

35 3 Day 35 SIMD matrix multiplication

36 3 Day 36 SIMD matrix multiplication

37 3 Day 37 Parallel sorting on array processors

38 3 Day 38 Parallel sorting on array processors

39 3 Day 39 Associative array processing

40 3 Day 40 Associative array processing

41 3 Day 41 Memory organization

42 4 Day 42 Multiprocessor architectures and Programming

43 4 Day 43 Loosely Coupled and Tightly Coupled Multiprocessors

44 4 Day 44 Loosely Coupled and Tightly Coupled Multiprocessors

45 4 Day 45 Interconnection networks

46 4 Day 46 Language features to exploit parallelism

47 4 Day 47 Inter Process communication Mechanism

48 4 Day 48 Process synchronisation mechanisms

49 4 Day 49 Process synchronisation mechanisms

50 4 Day 50 synchronization with semaphores.

51 4 Day 51 synchronization with semaphores.

52 5 Day 52 Dataflow computers

53 5 Day 53 Data driven computing and Languages

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Department of CSE, RSET 14

54 5 Day 54 Data flow computers Architectures

55 5 Day 55 Static data flow computer

56 5 Day 56 Static data flow computer

57 5 Day 57 Dynamic data flow computer

58 5 Day 58 Dynamic data flow computer

59 5 Day 59 Data flow design Alternatives.

60 5 Day 60 Data flow design Alternatives.

Page 15: emester VI, Course Hand-Out

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Department of CSE, RSET 15

CS010 802 Artificial Intelligence

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH YEAR: JAN 2014 – JUNE 2014

COURSE: ARTIFICIAL INTELLIGENCE SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 802 REGULATION: 2010

COURSE TYPE: CORE

COURSE AREA/DOMAIN: RECENT TRENDS IN

COMPUTING

CONTACT HOURS: 2+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

SYLLABUS:

UNIT DETAILS HOURS

I

Problems- problem spaces and search, production systems, Problem

characteristics, Searching strategies – Generate and Test, Heuristic Search

Techniques- Hill climbing– issues in hill climbing, General Example Problems.

Python-Introduction to Python- Lists Dictionaries & Tuples in Python- Python

implementation of Hill Climbing

14

II Search Methods- Best First Search- Implementation in Python- OR Graphs,

The A * Algorithm, Problem Reduction- AND-OR Graphs, The AO*

algorithm, Constraint Satisfaction. Games as search problem, MINIMAX

search procedure, Alpha–Beta pruning.

12

III Knowledge representation -Using Predicate logic- representing facts in logic,

functions and predicates, Conversion to clause form, Resolution in

propositional logic, Resolution in predicate logic, Unification, Question

Answering, forward and backward chaining.

12

IV Learning- Rote Learning – Learning by Advice- Learning in Problem Solving

- By Parameter Adjustment with Macro Operators, Chunking, Learning from

Examples- Winston’s Learning Program, Version Spaces- Positive & Negative

Examples – Candidate Elimination- Decision Trees- ID3 Decision Tree

Induction Algorithm.

12

V Fuzzy Sets – Concept of a Fuzzy number- Operations on Fuzzy Sets – Typical

Membership Functions – Discrete Fuzzy Sets.

Expert System –Representing and using Domain Knowledge – Reasoning

with knowledge– Expert System Shells –Support for explanation- examples –

Knowledge acquisition-examples.

10

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

R1 Elaine Rich, Kevin Knight, Shivashankar B Nair

Tata McGraw Hill- Artificial Intelligence, 3rd Edn ,2004.

R2 Stuart Russell – Peter Narang, Pearson Education Asia - Artificial

Page 16: emester VI, Course Hand-Out

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Department of CSE, RSET 16

Intelligence- A modern approach.

R3 George F Luger - Artificial Intelligence, Pearson Education Asia

R4 Allen B. Downey – (Think Python) Python for software design- How to

think like a computer scientist, Cambridge University press, 2009 .

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

CS010 303 Problem Solving & Computer Programming Knowledge of Programming Techniques III

CS010 403 Data Structures and Algorithms knowledge of search and data structures, such as

balanced binary trees. IV

EN010301

B

Engineering Mathematics II Knowledge of mathematical strategies and

graphs

III

COURSE OBJECTIVES:

1 Enabling Knowledge: Ability to apply artificial intelligence techniques, including search heuristics, knowledge

representation, planning and reasoning.

2 Problem Solving: Ability to design and implement appropriate solutions for search problems (such as playing two-person

games) and for planning problems (such as determining a sequence of actions for a robot).

3 Critical Analysis: Ability to analyse problem specifications and derive appropriate solution techniques for them.

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Graduates will be able to assess critically the techniques presented and to apply them to real world

problems

b,c,d

2 Graduates will be able aware of the major challenges facing AI and the complexity of typical problems

within the field

b,e

3 Graduates will get to understand the major areas and challenges of AI c,e

4 Graduates will be able to apply basic AI algorithms to solve problems. a,b,c,d

5 Graduates will be able to get a knowledge of applications in different areas of computing including the

web and human interaction

a,b,e

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

1 Given a planning problem, be able to develop the proper representation

for the problem in a planning language, and then create a plan using an

appropriate planning method

Assignment

2 Given a learning problem, be able to determine which learning techniques

may be applied to this problem, and be able to outline a method to solve the

problem

Assignment

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

SNO TOPICS PO MAPPING

1 Agents and Intelligent agents d

2 Design a problem which uses A* Algorithm c,d

WEB SOURCE REFERENCES:

Page 17: emester VI, Course Hand-Out

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Department of CSE, RSET 17

1 www.nptel.iitm.ac.in/video.php?subjectId=106105077

2 http://code.google.com/p/aima-python/ - Website for search strategy

implementation in python

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD. ASSIGNMENT WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL EXAMS UNIV. EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS CERTIFICATIONS

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK,

ONCE)

STUDENT FEEDBACK ON FACULTY (ONCE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved

by

Ms. Sangeetha Jamal Mr. Ajith S

(H.O.D)

Page 18: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 18

COURSE PLAN

SL

NO TOPICS MODULE

DAY 1 problem spaces and search MODULE 1

DAY 2 production systems MODULE 1

DAY 3 Problem characteristics MODULE 1

DAY 4 Searching Strategies MODULE 1

DAY 5 Generate and Test MODULE 1

DAY 6 Heuristic Search Techniques MODULE 1

DAY 7 Hill climbing MODULE 1

DAY 8 issues in hill climbing MODULE 1

DAY 9 Introduction to Python- Lists Dictionaries & Tuples in Python MODULE 1

DAY

10 Python implementation of Hill Climbing MODULE 1

DAY

11 Best First Search MODULE 2

DAY

12 Implementation in Python OR Graphs MODULE 2

DAY

13 The A * Algorithm MODULE 2

DAY

14 Problem Reduction MODULE 2

DAY

15 AND-OR Graphs, The AO* algorithm MODULE 2

DAY

16 Constraint Satisfaction MODULE 2

DAY

17 Games as search problem MODULE 2

DAY

18 MINIMAX search procedure MODULE 2

DAY

19 Alpha–Beta pruning MODULE 2

DAY

20 Using Predicate logic MODULE 3

DAY

21 representing facts in logic MODULE 3

DAY

22 functions and predicates MODULE 3

DAY

23 Conversion to clause form MODULE 3

DAY

24 Resolution in propositional logic MODULE 3

DAY

25 Resolution in predicate logic MODULE 3

DAY Unification, Question Answering MODULE 3

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Department of CSE, RSET 19

26

DAY

27 forward and backward chaining MODULE 3

DAY

28 Rote Learning MODULE 4

DAY

29 Learning by Advice MODULE 4

DAY

30 Learning in Problem Solving MODULE 4

DAY

31 By Parameter Adjustment with Macro Operators, Chunking, MODULE 4

DAY

32 Learning from Examples MODULE 4

DAY

33 Winston’s Learning Program, Version Spaces MODULE 4

DAY

34 Positive & Negative Examples MODULE 4

DAY

35 Candidate Elimination MODULE 4

DAY

36 Decision Trees MODULE 4

DAY

37 ID3 Decision Tree Induction Algorithm MODULE 4

DAY

38 Concept of a Fuzzy number MODULE 5

DAY

39 Operations on Fuzzy Sets MODULE 5

DAY

40 Typical Membership Functions MODULE 5

DAY

41 Discrete Fuzzy Sets MODULE 5

DAY

42 Representing and using Domain Knowledge MODULE 5

DAY

43 Reasoning with knowledge MODULE 5

DAY

44 Expert System Shells MODULE 5

DAY

45 Support for explanation- examples MODULE 5

DAY

46 Knowledge acquisition-examples MODULE 5

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Department of CSE, RSET 20

CS010 803 Security in Computing

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE &

ENGINEERING

DEGREE: BTECH YEAR: JAN 2013 – JUNE 2013

COURSE: SECURITY IN COMPUTING SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 803 COURSE TYPE: CORE /ELECTIVE / BREADTH/ S&H

COURSE AREA/DOMAIN: RECENT TRENDS IN

COMPUTING

CONTACT HOURS: 3+1 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): NIL LAB COURSE NAME: NIL

SYLLABUS:

UNIT DETAILS HOURS

I Introduction: Security basics – Aspects of network security – Attacks

Different types –Security attacks -Security services and mechanisms.

Cryptography: Basic Encryption & Decryption – Classical encryption

techniques – symmetric encryption, substitution ciphers – Caesar

cipher – Monoalphabetic Cipher, Playfair Cipher, Polyalphabetic cipher -

Vigenère – Cipher, Transposition ciphers - Rail Fence cipher, Row

Transposition Ciphers.

12

II Modern Block Ciphers - Fiestel Networks , DES Algorithm –

Avalanche Effect.

Introduction to Number Theory - Prime Factorisation, Fermat's

Theorem, Euler's Theorem, Primitive Roots, Discrete Logarithms.

Public key Cryptography:- Principles of Public key Cryptography

Systems, RSA algorithms- Key Management – Diffie-Hellman Key

Exchange, Elliptic curve cryptography.

12

III Message Authentication-Requirements- Authentication functions-

Message authentication codes-Hash functions- Secure Hash Algorithm,

MD5, Digital signatures- protocols- Digital signature standards, Digital

Certificates.

Application Level Authentications- Kerberos, X.509 Authentication

Service, X.509 certificates.

12

IV Network Security: Electronic Mail Security, Pretty Good Privacy,

S/MIME, IP Security Overview, IP Security Architecture, Authentication

Header, Encapsulating Security Payload.

Web Security: Web Security considerations- Secure Socket Layer -

Transport layer Security- Secure electronic transaction. Firewalls-

Packet filters- Application Level Gateway- Circuit Level Gateway.

12

V Operating System Security: Memory and Address Protection, Control

of Access to General Objects, File Protection Mechanisms, Models of

Security – Bell-La Padula Confidentiality Model and Biba Integrity

Model.

System Security: Intruders, Intrusion Detection, Password

Management, Viruses and Related Threats, Virus Countermeasure.

12

TOTAL HOURS 60

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Department of CSE, RSET 21

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

1 William Stallings, “Cryptography and Network Security – Principles and Practices”, Pearson Education, Fourth Edition, 2006.

2 Charles P. Pfleeger, “Security in Computing”, Pearson Education, Third Edition, 2005.

3 Behrouz A. Forouzan, Dedeep Mukhopadhyay “Cryptography & Network Security”, Second Edition,Tata McGraw Hill, New Delhi, 2010.

4 Andrew S. Tanenbaum, “Modern Operating Systems”, Pearson Education, Second Edition, 2002.

5 Atul Kahate, “Cryptography and Network Security”, Second Edition, Tata McGraw Hill

6 Wenbo Mao, “ Modern Cryptography- Theory & Practice”, Pearson Education, 2006.

7 Bruce Schneier, “Applied Cryptography”, John Wiley and Sons Inc, 2001.

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

EN010

103,301 Engineering mathematics I & II Mathematical Skills I,II

&

III

CS010-

303 PSCP Problem Solving Skills III

CS010-

505 Operating Systems System Architecture V

CS010-

604 Computer Networks Networking VI

CS010-

701 Web Technologies Programming Skills VII

COURSE OBJECTIVES:

1 To impart an essential study of computer security issues

2 To develop basic knowledge on cryptography

3 To impart an essential study of various security mechanisms

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Students will have the basic knowledge of different types of

Security attacks

a,b

2 Students will be able to analyze and compare different security

mechanisms and services.

a,b,c

3 Students will be able to analyze different modern encryption

algorithms.

a.b.c.h

4 Students will have the basic knowledge of different Authentication

mechanisms

a,b

5 Students will have the knowledge on latest techniques used in

different Security aspects (e.g. network security, web security

etc.)

a,b,c,h

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

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Department of CSE, RSET 22

SNO DESCRIPTION PROPOSED

ACTIONS

PO

MAPPING

1

2

3

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

SNO DESCRIPTION PO

MAPPING

1

WEB SOURCE REFERENCES:

1

2

10

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD.

ASSIGNMENT

WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL

EXAMS

UNIV.

EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS CERTIFICATIONS

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK, ONCE) STUDENT FEEDBACK ON FACULTY (TWICE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved

by

Mr. Mintu Philip Mr. Ajith S

(H.O.D)

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Department of CSE, RSET 23

COURSE PLAN

SL NO TOPIC

1 Introduction: Security basics

2 Aspects of network security

3 Attacks Different types

4 Security attacks

5 Security services and mechanisms

6 Basic Encryption & Decryption

7 Classical encryption techniques

8 symmetric encryption, substitution ciphers

9 Caesar cipher

10 Monoalphabetic Cipher, Playfair Cipher

11 Polyalphabetic cipher - Vigenère – Cipher

12 Transposition ciphers - Rail Fence cipher, Row Transposition Ciphers

13 Modern Block Ciphers - Fiestel Networks

14 DES Algorithm

15 Avalanche Effect

16 Introduction to Number Theory - Prime Factorisation

17 Fermat's Theorem

18 Euler's Theorem

19 Primitive Roots

20 Discrete Logarithms

21 Public key Cryptography:- Principles of Public key Cryptography Systems

22 RSA algorithms

23 Key Management

24 Diffie-Hellman Key Exchange

25 Elliptic curve cryptography

26 Message Authentication-Requirements

27 Authentication functions

28 Message authentication codes

29 Hash function

30 Secure Hash Algorithm

31 MD5

32 Digital signatures- protocols

33 Digital signature standards

34 Digital Certificates

35 Application Level Authentications- Kerberos

36 X.509 Authentication Service

37 X.509 certificates

38 Network Security: Electronic Mail Security

39 Pretty Good Privacy

40 S/MIME

41 IP SecurityOverview

42 IP Security Architecture

43 Authentication Header

44 Encapsulating Security Payload

45 Web Security: Web Security considerations

46 Secure Socket Layer

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47 Transport layer Security-

48 Secure electronic transaction

49 Firewalls

50 Packet filters

51 Application Level Gateway

52 Circuit Level Gateway

55 Operating System Security: 56 Memory and Address Protection

57 Control of Access to General Objects

58 File Protection Mechanisms

59 Models of Security – Bell-La Padula Confidentiality Model

60 Biba Integrity Model

61 System Security: Intruders

62 Intrusion Detection

63 Password Management

64 Viruses and Related Threats

65 Virus Countermeasure.

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Department of CSE, RSET 25

CS010 804L04 Optimization Techniques

COURSE INFORMATION SHEET PROGRAMME: DEGREE: BTECH

COURSE: ELECTIVE –II : OPTIMIZATION

TECHNIQUES

SEMESTER: S8 CREDITS: 4

COURSE CODE: CS010 804L04 REGULATION:

COURSE TYPE: CORE /ELECTIVE / BREADTH/ S&H:

ELECTIVE

COURSE AREA/DOMAIN: CONTACT HOURS: 3+1 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

UNIT DETAILS HOURS

I MODULE 1

Classical optimization techniques ( 12 hrs)

One dimensional unconstrained minimization techniques.

Single variable minimization

Unimodality.

Bracketing the minimum

Necessary and sufficient condition for optimality

Convexity

Steepest decent method.

II MODULE 2

Linear programming problem ( 12 hrs)

Linear programming problem introduction.

Introduction.

Linear programming problem with constraints.

Simplex method

Big M method.

12

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Department of CSE, RSET 26

III MODULE 3

Transportation and Assignment problems. (12 hrs)

Transportation models, definition

Transportation algorithm,

North West corner method,

Vogel’s approximation method,

Assignment model,

Hungarian method.

12

IV MODULE 4

Forecasting & Game problems. ( 12 hrs)

Moving average techniques

Regression method

Exponential smoothing.

Game Theory, two person zero sum games

Mixed strategy problems, graphical method.

12

V MODULE 5 Queuing Theory ( 12 hrs) Queuing models, Elements of queuing model, pure birth and death model, Specialized Poisson queues, single server models, Multiple server models, Self service model.

12

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

Reference

1. S.S. Rao, Optimization theory and application. 2. H.A. Taha, Operation Research an introduction. 3. R. Panneerselvam, Operations Research. 4. G.S.S. Bhishma Rao, Optimization techniques.

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

1 Calculus and Operation Research.

2 Engineering Mathematics IV

Page 27: emester VI, Course Hand-Out

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Department of CSE, RSET 27

COURSE OBJECTIVES:

Upon successful completion of this course, students should be able to understand various

optimization techniques that help them to design and produce products both economically and

efficiently.

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Graduates will develop a thorough knowledge of various optimization techniques

2 Graduates will be able to solve application problems using Numerical methods.

3 Graduates will be able to use various queuing theory problems.

4

5

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

1 Non linear programming Lectures

2 Optimality testing for two variable functions. Assignments

3 Network algorithms Assignments

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

1 Module I

Finding the application of classical optimization techniques in different branches of engineering.

2 Module II

Finding the application of linear programming methods in different branches of engineering.

3 ModuleIII

Importance of Assignment and TP in real world problems.

4 Module IV

Application of Game theory in various branches of engineering.

5 Module V

Applications of queuing theory in real time problems.

WEB SOURCE REFERENCES:

1 en.wikipedia.org/wiki/Mathematical_optimization

2 en.wikipedia.org/wiki/Program_optimization

3 www.optimization-online.org/

4 www.thefreedictionary.com/optimization

5 www.nptel.iitm.ac.in/.../OPTIMIZATION%20METHODS/.../M1L4slides

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

☐ CHALK & TALK ☐ STUD. ASSIGNMENT ☐ WEB RESOURCES

☐ LCD/SMART BOARDS ☐ STUD. SEMINARS ☐ ADD-ON COURSES

Page 28: emester VI, Course Hand-Out

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ASSESSMENT METHODOLOGIES-DIRECT

☐ ASSIGNMENTS ☐ STUD. SEMINARS ☐ TESTS/MODEL EXAMS ☐ UNIV. EXAMINATION

☐ STUD. LAB PRACTICES ☐ STUD. VIVA ☐ MINI/MAJOR PROJECTS ☐ CERTIFICATIONS

☐ ADD-ON COURSES ☐ OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

☐ ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK,

ONCE)

☐ STUDENT FEEDBACK ON FACULTY (TWICE)

☐ ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS ☐ OTHERS

Prepared by

Yogesh Prasad Approved by

(Faculty) (HOD)

Page 29: emester VI, Course Hand-Out

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Department of CSE, RSET 29

CS010 804L05 Mobile Computing

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE &

ENGINEERING

DEGREE: BTECH YEAR: JAN 2014 – JUNE

2014

COURSE NAME: MOBILE COMPUTING SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 804 L05

REGULATION: 2010

COURSE TYPE: ELECTIVE

COURSE AREA/DOMAIN: NETWORKING AND

COMMUNICATION

CONTACT HOURS: 2+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY):

NIL

LAB COURSE NAME: NA

SYLLABUS:

UNIT DETAILS HOURS

I Introduction to wireless communication system:- 2G cellular network,2G TDMA

Standards,3G wireless networks, wireless local loop and LMDS, Broadcast

Systems-Broadcast transmission, Digital Audio Broadcasting-Multimedia Object

Transfer Protocol. Digital Video Broadcasting.

Cellular concepts-channel assignment strategy-hand off strategy-interface and

system

Capacity-trunking –improving coverage and capacity in cellular system.

10

II Wireless Communication Systems:-Telecommunication Systems-GSM-GSM

services &

features,architecture,channel type, frame structure, signal processing in GSM &

DECT features & characteristics,architecture,functional concepts & radio link,

personal access

communication system(PACS)-system architecture-radio interface,

Protocols. Satellite Systems-GEO, LEO, MEO.

12

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III Wireless LAN and ATM:- Infra red and Radio Transmission, Infrastructure and ad

hoc

networks ,802.11- Bluetooth- Architecture, Applications and Protocol, Layers,

Frame

structure. comparison between 802.11 and 802.16.

Wireless ATM- Services, Reference Model, Functions, Radio Access Layer.

Handover-

Reference Model, Requirements, Types, handover scenarios.

Location Management, Addressing, Access Point Control Protocol (APCP).

11

IV TreesBary

Mobile Network and Transport Layers:- Mobile IP- Goals, Requirements, IP

packet

delivery, Advertisement and discovery. Registration, Tunneling and

Encapsulation,

Optimization, Reverse Tunneling, IPv6, Dynamic Host configuring protocol, Ad hoc

networks – Routing, DSDV, Dynamic source routing. Hierarchical Algorithms.

Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Transmission.

14

V Wireless Application Protocol & World Wide Web

WAP- Architecture, Protocols-Datagram, Transaction, Session.-Wireless

Application

Environment-WML- Features, Script- Wireless Telephony Application.

WWW- HTTP, Usage of HTML, WWW system architecture.

13

TOTAL HOURS 60

Page 31: emester VI, Course Hand-Out

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Department of CSE, RSET 31

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

1 Jochen Schiller “Mobile Communications “ , Preason Education Asia

2 Wireless communications Principles and practice-second edition-Theodore

S.Rappaport,PHI,Second Edition ,New Delhi, 2004

3 Computer Networks – Andrew S. Tanenbaum , PHI

4 Communication Networks -Fundamental Concepts and Key Architectures

Leon-Garcia & Indra Widjaja, Tata McGraw Hill

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

CS010

604

COMPUTER NETWORKS NETWORKING FUNDAMENTALS VI

COURSE OBJECTIVES:

1 To learn about the concepts and principles of mobile computing.

2 To learn about the key components and technologies involved in building mobile applications.

Page 32: emester VI, Course Hand-Out

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Department of CSE, RSET 32

3 To learn about Wireless networks such as 2G/3G networks and protocols , Mobile Ad-hoc

networks and mobility management strategies that are needed to support mobile computing.

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Students should be able to describe the basic concepts and principles in

wireless communication systems and satellite communication systems.

a, d

2 Students should understand the concept of wireless LANs, wireless ATM,

Mobile and ad-hoc networks.

a, b, c, d

3 Students should be able to explain the structure and components of Mobile IP

,adhoc routing protocols and mobility management.

b

4 Students should be able to understand positioning techniques and location based

services and applications.

b, c, d

5 Students should have a good understanding of how the underlying wireless and

mobile communication networks work, their technical features and what kind of

applications they support.

a,c,h

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PO

Mapping

PROPOSED

ACTIONS

1 Wireless Personal Area Networks-Comparative study c, h Reading

Assignment

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST

LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

1 Evolution of wireless communication systems a, b

WEB SOURCE REFERENCES:

1 http://wsl.stanford.edu/~andrea/Wireless/SampleChapters.pdf

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Department of CSE, RSET 33

2 http://www.iject.org/pdf/amit.pdf

3 http://web.ee.ccu.edu.tw/~wl/wireless_class/Introduction%20to%20Wireless%20Communicati

on%20Systems.pdf

4 http://johnkooker.com/blog/wp-content/uploads/2009/05/jkooker_BTZigBeeWibree.pdf

5

6

7

8

9

1

0

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD.

ASSIGNMENT

WEB RESOURCES

LCD/SMART

BOARDS

STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL

EXAMS

UNIV.

EXAMINATION

STUD. LAB

PRACTICES

STUD. VIVA MINI/MAJOR

PROJECTS

CERTIFICATIONS

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY

FEEDBACK, ONCE)

STUDENT FEEDBACK ON FACULTY

(TWICE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT.

EXPERTS

OTHERS

Page 34: emester VI, Course Hand-Out

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Department of CSE, RSET 34

Prepared by Approved

by

Ms. Tripti. C Mr. Ajith S

(H.O.D)

Page 35: emester VI, Course Hand-Out

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Department of CSE, RSET 35

Page 36: emester VI, Course Hand-Out

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Department of CSE, RSET 36

2014S8CS CS010 804L05

COURSE PLAN

Sl.No Module Planned

1 1 Introduction

2 1 2G cellular network,2G TDMA Standards,3G wireless networks

3 1 2G cellular network,2G TDMA Standards,3G wireless networks

4 1 wireless local loop and LMDS

5 1 wireless local loop and LMDS

6 1 Broadcast Systems-Broadcast transmission

7 1

Digital Audio Broadcasting-Multimedia Object Transfer Protocol. Digital Video Broadcasting.

8 1

Digital Audio Broadcasting-Multimedia Object Transfer Protocol. Digital Video Broadcasting.

9 1 Cellular concepts-channel assignment strategy

10 1 hand off strategy-interface and system Capacity

11 1 trunking –improving coverage and capacity in cellular system

12 1 Tutorial

13 2 Telecommunication Systems-GSM

14 1 GSM services & features,architecture

15 2 GSM services & features,architecture

16 2 channel type, frame structure

17 2 signal processing in GSM & DECT features & characteristics

18 2 architecture,functional concepts & radio link

19 2 architecture,functional concepts & radio link

20 2 personal access communication system(PACS)-system architecture

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Department of CSE, RSET 37

21 2 personal access communication system(PACS)-system architecture

22 2 radio interface Protocols

23 2 radio interface Protocols

24 2 Tutorial

25 2 Satellite Systems-GEO, LEO, MEO

26 3 Infra red and Radio Transmission, Infrastructure and ad hoc networks

27 3 802.11

28 3 Bluetooth- Architecture, Applications and Protocol, Layers, Frame structure

29 3 comparison between 802.11 and 802.16

30 3 Wireless ATM- Services, Reference Model, Functions, Radio Access Layer

31 3 Wireless ATM- Services, Reference Model, Functions, Radio Access Layer

32 3

Handover- Reference Model, Requirements, Types, handover scenarios.

33 3

Handover- Reference Model, Requirements, Types, handover scenarios.

34 3 Location Management, Addressing, Access Point Control Protocol (APCP).

35 3 Tutorial

36 4

Mobile IP- Goals, Requirements, IP packet delivery, Advertisement and discovery

37 4 Registration, Tunneling and Encapsulation, Optimization

38 4 Reverse Tunneling, IPv6, Dynamic Host configuring protocol

39 4

Ad hoc networks – Routing, DSDV, Dynamic source routing. Hierarchical Algorithms.

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Department of CSE, RSET 38

40 4

Ad hoc networks – Routing, DSDV, Dynamic source routing. Hierarchical Algorithms.

41 4 Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Transmission.

42 4 Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Transmission.

43 4 Tutorial

44 5 Wireless Application Protocol & World Wide Web WAP- Architecture

45 5 Wireless Application Protocol & World Wide Web WAP- Architecture

46 5 Protocols-Datagram, Transaction, Session

47 5 Wireless Application Environment-WML- Features, Script

48 5 Wireless Application Environment-WML- Features, Script

49 5 Wireless Telephony Application

50 5 WWW- HTTP, Usage of HTML

51 5 WWW system architecture

52 5 Tutorial

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Department of CSE, RSET 39

CS010 804L06 Advanced Networking Trends

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH YEAR: JAN 2013 – JUNE 2013

COURSE: Advanced Networking Trends SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 804L06 COURSE TYPE: Elective

COURSE AREA/DOMAIN: Networking & Communication CONTACT HOURS: 2(lecture)+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): NIL LAB COURSE NAME: NIL

SYLLABUS:

UNIT DETAILS HOURS

I Ethernet Technology – Frame format – Interface Gap – CSMA/CD – 10 mbps

Ethernet, Fast Ethernet, Gigabit Ethernet, Wireless Ethernet.

ISDN - Definition - Protocol architecture - System architecture - Transmission

channels - ISDN interface, B-ISDN.

12

II ATM – ATM Principles – BISDN reference model – ATM layers – ATM adaption

Layer – AAL1, AAL2, AAL3/4, AAL5 – ATM addressing – UNI Signalling – PNNI

Signalling

12

III Wireless LAN – Infrared Vs Radio transmission – Infrastructure & ad hoc n/w –

IEEE 802.11 – Physical Layer – MAC layer.

Bluetooth – Physical Layer – MAC layer – Networking – Security

12

IV Mesh Networks- Necessity for Mesh Networks – MAC enhancements – IEEE

802.11s Architecture –Opportunistic Routing – Self Configuration and Auto

Configuration - Capacity Models –Fairness – Heterogeneous Mesh Networks –

Vehicular Mesh Networks

12

V Sensor Networks- Introduction – Sensor Network architecture – Data Dissemination –

Data Gathering –MAC Protocols for sensor Networks – Location discovery – Quality

of Sensor Networks– Evolving Standards – Other Issues – Recent trends in

Infrastructure less Networks

12

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

T1 An introduction to Computer Networking - Kenneth C Mansfield, Jr., James L. Antonakos, PHI.

T2 Communication Networks Fundamental Concepts & Key Architecture - Leon-Garcia –

Widjaja, Tata McGraw Hill.

R1 Mobile Communication - Jochen Schiller, Pearson Education Asia.

R2 C. Siva Ram Murthy and B.S.Manoj, “Ad hoc Wireless Networks – Architectures and

Protocols’, Pearson Education, 2004.

R3 C.K.Toh, “Adhoc Mobile Wireless Networks”, Pearson Education, 2002.

COURSE PRE-REQUISITES:

Page 40: emester VI, Course Hand-Out

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Department of CSE, RSET 40

C.CODE COURSE NAME DESCRIPTION SEM

CS010 604 Computer Networks Basic knowledge of different types of computer

networks

VI

COURSE OBJECTIVES:

1 To acquaint the students with the application of networking.

2 To understand the various TCP/IP protocols and the working of ATM and its

performance, Network security and authentication, and various algorithms related to

it has been dealt, to get a practical approach ,advanced topics in the design of

computer networks and network protocols

COURSE OUTCOMES:

Sno Description PO

Mapping

1 Graduates have a detailed knowledge about ethernet services, functions and ISDN a,b

2 Graduates will get a better idea about ATM principles a,b

3 Graduates are acquainted with thorough knowledge of wireless LAN applications and their

requirements

a,b,d

4 Graduates have awareness on mesh networks a,b

5 Graduates will be familiar with architectures, functions and performance of wireless sensor

networks systems and platforms.

a,b,c

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

PO Mapping

1 Android based mobile applications Conducting workshops, main

projects.

a,c,d

2 Study of the Ethernet Network at college Assignment a, c, d

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

Sno Topics PO

Mapping

1 Study of various Cyber Security issues e,h

2 Study of Broadband Wireless Communications a,c

WEB SOURCE REFERENCES:

1 en.wikipedia.org/wiki/

2 http://www.infotoday.com/online

3 http://www.scribd.com/doc

4 http://compnetworking.about.com/cs/

5 http://www.ask.com/question

6 http://www.sciencedirect.com

7 http://www.slideshare.net

8 http://www.britannica.com

9 http://mobileoffice.about.com

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Department of CSE, RSET 41

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD. ASSIGNMENT WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS

STUD. SEMINARS

TESTS/MODEL EXAMS UNIV. EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS CERTIFICATIONS

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK, ONCE) STUDENT FEEDBACK ON FACULTY (ONCE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved by

Mr. Biju Abraham N. Mr. Ajith S

(H.O.D)

Page 42: emester VI, Course Hand-Out

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Department of CSE, RSET 42

ADVANCED NETWORKING TRENDS (CS010 804L06)

COURSE PLAN

Sl.No Module Planned

1 1 Introduction

2 1 Ethernet Technology, Frame Format

3 1 Interface Gap

4 1 CSMA/CD

5 1 10 Mbps Ethernet, Fast Ethernet, Gigabit Ethernet

6 1 Wireless Ethernet

7 1 ISDN, Definition

8 1 Protocol Architecture

9 1 System Architecture

10 1 Transmission Channels

11 1 ISDN Interface

12 1 B-ISDN

13 2 ATM, ATM Principles

14 2 BISDN Reference Model

15 2 ATM Layers

16 2 ATM Adaptation Layer - AAL1, AAL2

17 2 ATM Adaptation Layer - AAL3/4, AAL5

18 2 ATM Addressing

19 2 UNI Signalling

20 2 PNNI Signalling

21 3 Wireless LAN

22 3 Infrared Vs Radio Transmission

23 3 Infrastrure & Adhoc N/W

24 3 IEEE 802.11

25 3 Physical Layer

26 3 MAC Layer

27 3 Bluetooth

28 3 Bluetooth Physical Layer

29 3 Bluetooth MAC Layer

30 3 Networking

31 3 Security

32 4 Mesh Networks

33 4 Necessity for Mesh Networks

34 4 MAC enhancements

35 4 IEEE 802.11s Architecture

36 4 Opportunistic Routing

37 4 Self Configuration and Auto Configuration

38 4 Capacity Models

39 4 Fairness

40 4 Heterogeneous Mesh Networks

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Department of CSE, RSET 43

41 4 Vehicular Mesh Networks

42 5 Sensor Networks - Introduction

43 5 Sensor Network Architecture

44 5 Data Dissemination, Data Gathering

45 5 MAC Protocols for sensor networks

46 5 Location Discovery

47 5 Quality of Sensor Networks

48 5 Evolving Standards

49 5 Other issues

50 5 Recent Trends in Infrastructureless Networks

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Department of CSE, RSET 44

CS010 805G02 Neural Networks

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH

COURSE: NEURAL NETWORKS SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 805G02 REGULATION: 2010 COURSE TYPE: ELECTIVE

COURSE AREA/DOMAIN: RECENT TRENDS IN

COMPUTING

CONTACT HOURS: 2+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): NIL LAB COURSE NAME: NIL

SYLLABUS:

UNIT DETAILS HOURS

I Biological Neurons and Neural Networks, Basic Structures and Properties of Artificial

Neural Networks, Basic Neuron Models-McCulloch-Pitts -Nearest Neighbour- Radial Basis

Function, Activation Functions ,Singe Layer Perceptrons-Linear Seperability, Learning and

Generalization in Single Layer Perceptron-Hebbian Learning-Gradient Descent Learning-

Widrow-Hoff Learning-The Generalized Delta rule, Practical Considerations

14

II Multi Layer Perceptron Learning,Back Propogation Algorithim -Applications –

Limitations–Network Paralysis – Local Minima – Temporal Instability, Pattern Analysis

Tasks- Classification-Regression- Clustering, Pattern Classification and Regression using

Multilayer Perceptron.

12

III Radial Basis Function Networks: Fundamentals, Algorithms and Applications, Learning

with Momentum, Conjugate Gradient Learning, Bias and Variance. Under-Fitting and Over-

Fitting,Stochastic neural networks, Boltzmann machine.

10

IV Network based on competition:- Fixed weight competitive Network-Maxnet, Mexican Hat

and Hamming Net, Counter Propagation Networks- Kohonen’s self-organizing map –

Training the Kohonen layer – Training the Grossberg layer – Full counter propagation

network – Application, Adaptive resonance theory – classification- Architecture – Learning

and generalization.

12

V Pattern Association: - training algorithm for pattern association - Hetro Associative

Network, Auto Associative Network, Architecture of Hopfield nets – stability analysis

,General Concepts of Associative Memory, Bidirectional Associative Memory (BAM)

Architecture, BAM training algorithms.

12

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

R1. B. Yegnanarayana, "Artificial Neural Networks", PHI.

R2. Simon Haykin, Neural Networks, 2/e, Prentice Hall

R3. Neural Computing & Practice – Philip D. Wass

R4. Neural Networks in Computer Intelligence-Limin Fu,Tata Mc.Hill Edition

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

EN010301 B Engineering Mathematics II Graph Theory III

CS010 601 Design And Analysis Of Algorithms

To develop an understanding about how to develop an

algorithm, how to do pseudo code conversion and to

analysis time and space complexity.

VI

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Department of CSE, RSET 45

CS010 802 ARTIFICIAL INTELLIGENCE

Introduction to the basic knowledge representation,

problem solving, and learning methods of Artificial

Intelligence.

VII

COURSE OBJECTIVES:

1 To understand the fundamental building blocks of Neural networks

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Graduates will be able to differentiate biological neural network and artificial neural network and will

also understand the basic structures, models and properties of neural network

a,b,c,e

2 Graduate will gain knowledge on pattern analysis task, applications of neural network using back

propagation algorithm and its limitations.

a,b,c

3 Graduate will be able to learn fundamentals, algorithm and applications of radial basis function

network

a,b,c

4. Graduate will have an insight into different neural network based on competition

a,b,c

5 Graduate will be able to learn pattern association and Associative Neural-networks a,b,c

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

PO

MAPPING

1 Implementation of neural network application

like handwritten detection, cancer detection

Project work on neural network

applications and guest lectures on

neural network applications

b,c,e,f

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

SNO TOPICS PO MAPPING

1 Implementation of handwritten detection using neural network b,c,d,e

2 Realization of logical gates using neural networks c,d

WEB SOURCE REFERENCES:

1 http://www-cs-faculty.stanford.edu/~eroberts/courses/soco/projects/neural-networks/Neuron/index.html

2 http://www.codeproject.com/Articles/24361/A-Neural-Network-on-GPU

3 http://www.sourcecodeonline.com/ (To get sample project on neural network)

4 http://www.codeproject.com/Articles/14188/Brainnet-1-A-Neural-Netwok-Project-With-

Illustrati#1.1%20Introduction%20To%20This%20Article%20Series

Page 46: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 46

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD.

ASSIGNMENT

WEB RESOURCES

LCD/SMART

BOARDS

☐ STUD. SEMINARS ☐ ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL

EXAMS

UNIV.

EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS ☐ CERTIFICATIONS

☐ ADD-ON COURSES ☐ OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY

FEEDBACK, ONCE)

☐ STUDENT FEEDBACK ON FACULTY (ONCE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS ☐ OTHERS

Prepared by Approved

by

Amitha Mathew (HOD)

Page 47: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 47

CS010 805G02 :Neural networks(Elective IV)

COURSE PLAN

Sl No

Day Module TOPIC

1 1

1

Introduction,Biological Neurons and Neural Networks

2 2 Basic Structures and Properties of Artificial Neural Networks

3 3 Basic Neuron Models

4 4 McCulloch-Pitts

5 5 Nearest Neighbour

6 6 Radial Basis Function

7 7 Activation Functions

8 8 Single Layer Perceptrons

9 9 Linear Seperability

10 10 Learning and Generalization in Single Layer Perceptron

11 11 Hebbian Learning-Gradient Descent Learning

12 12 Widrow-Hoff Learning

13 13 The Generalized Delta rule

14 14 Practical Considerations

15 15

2

Multi Layer Perceptron Learning

16 16 Back Propogation Algorithim

17 17 Applications

18 18 Limitations

19 19 Network Paralysis

20 20 Local Minima

21 21 Temporal Instability

22 22 Pattern Analysis Tasks

23 23 Classification

24 24 Regression

25 25 Clustering

26 26 Pattern Classification and Regression using Multilayer Perceptron

27 27

3

Radial Basis Function Networks: Fundamentals

28 28 Algorithms

29 29 Applications

30 30 Learning with Momentum

31 31 Conjugate Gradient Learning

32 32 Bias and Variance

33 33 Under-Fitting and Over-Fitting

34 34 Stochastic neural networks

35 35 Boltzmann machine

36 36

4

Network based on competition:- Fixed weight competitive Network

37 37 Maxnet, Mexican Hat and Hamming Net

38 38 Counter Propagation Networks

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Department of CSE, RSET 48

39 39 Kohonen’s self-organizing map

40 40 Training the Kohonen layer

41 41 Training the Grossberg layer

42 42 Full counter propagation network

43 43 Application

44 44 Adaptive resonance theory – classification

45 45 Architecture

46 46 Learning and generalization

47 47

5

Pattern Association: - training algorithm for pattern association

48 48 Hetro Associative Network

49 49 Auto Associative Network

50 50 Architecture of Hopfield nets

51 51 stability analysis

52 52 General Concepts of Associative Memory

53 53 Bidirectional Associative Memory (BAM) Architecture

54 54 BAM training algorithms

55 55 University Question Paper Discussion

56 56 Revision

Page 49: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 49

CS010 805G05 Advanced Mathematics

COURSE INFORMATION SHEET PROGRAMME: DEGREE: BTECH

COURSE: ELECTIVE –IV: ADVANCED

MATHEMATICS

SEMESTER: S8 CREDITS: 4

COURSE CODE: EE/CS 010 805 G03 REGULATION: UG

COURSE TYPE: CORE /ELECTIVE / BREADTH/ S&H:

ELECTIVE

COURSE AREA/DOMAIN: CONTACT HOURS: 3+1 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

SYLLABUS:

Topic

Module 1 Green’s Function ( 8 hrs)

Heavisides, unit step function (1hr)

Derivative of unit step function ( 1 hr)

Dirac delta function- properties of delta function ( 1hr)

Derivatices of delta function ( 1 hr)

Testing functions- symbolic function- symbolic derivatives ( 1hr)

Inverse of differential operator (1 hr)

Green’s function-initial function(1 hr)

Initial value problems- boundary value problems-simple cases only ( 1 hr)

Module 2 Integral Equations ( 8 hrs)

Definition of Volterra and Fredhlom Integral equations ( 1 hr)

Conversion of a linear differential equation into an integral equation ( 1 hr)

Conversion of boundary value problem in to an integral equation using Green’s function(2 hrs)

Solution of Fredhlom integral equation with separable kernels (2 hrs)

Integral equations of convolution type (1 hr)

Neumann series solution ( 1 hr)

Page 50: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 50

Module 3 Gamma , Beta functions ( 7 hrs)

Gamma function, Beta function ( 1hr)

Relation between them- their transformations ( 2 hrs)

Use of them in the evaluation certain integrals ( 1 hr)

Dirichlet’s integral – Liouville’s extension of Dirichlet’s theorem ( 2 hr)

Elliptic integral - Error function ( 1 hr)

Module 4 Power series solution of differential equation ( 10 hrs)

The power series method ( 2 hrs )

Legendre’s equation - Legendre’s polynomial ( 2 hrs)

Rodrigues formula - Generating function ( 2 hrs)

Bessel’s equation- Bessel’s function of the first kind ( 2 hrs)

Orthogonality of Legendre’s polynomials and Bessel’s functions ( 2 hrs)

Module 5 Numerical solution of partial differential equations

( 7 hrs)

Classification of second order equations (1 hr)

Finite difference approximations to partial derivatives (2 hrs)

Solution of Laplace and Poison’s equations by finite difference method ( 2 hrs)

Solution of one dimensional heat equation by Crank – Nicolson method ( 1 hr)

Solution one dimensional wave equation ( 1 hr)

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

Reference

1. Ram P.Kanwal : Linear Integral Equation 2. Allen C. Pipkin : A course on Integral Eqautions 3. H.K. Dass : Advanced Engineering Mathematics 4. Michael D. Greenberg : Advanced Engineering Mathematics.

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

Page 51: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 51

EN 010

101 Calculus Basic knowledge to understand the concepts 1

&IV

EN010401

Linear algebra Matrix theory 1

COURSE OBJECTIVES:

Upon successful completion of this course, students should be able to understand basic concepts of

various integration techniques.

COURSE OUTCOMES:

SI No Course Outcome

CO1 Students will study the fundamentals of Green's Function.

CO2 Students will get an ides of solving integral equations in various fields.

CO3 Students will understand the applications of beta and gamma function in

solving various complex integration.

CO4 Students will gain knowledge of solving an differential equations using a

series method, which can be used in approximation methods.

CO5 Students will be able to solve any ordinary or partial differential equation

using computer programming.

CO6 Students will learn various methods to tackle the complex mathematical

equation using simple or basic methods and computing.

CO mapping with PO, PSO

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO1 2 1

CO2 2 3 1 1

CO3 3 1 2

CO4 3 2 2 1 1

CO5 3 2 1 3 2 1 1 1 1

CO6 3 2 3 2 2 1 1

CS010805G03 2.8 2 1.7 1.7 1.7 1 1

1

1

Justification for the correlation level assigned in each cell of the table above.

PO1 PO2 PO3 PO4 PO5 PO6 PO7

P

O

8

PO9 PO

10

PO

11

PO

12

Page 52: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 52

C

O

1

This is

mainly

used in

theoreti

cal

level

where

differen

tial

operato

rs are

mainly

used

This

proble

ms can

be

faced

only in

researc

h levels

and

particul

ar

areas.

C

O

2

This is

just to

get an

idea of

integral

equatio

ns in

mathe

matics.

They

are

mainly

used

for the

formula

tion of

certain

proble

ms

which

need to

be

solved

using

IE

They

rarely

used in

designi

ng

comple

x

enginee

ring

proble

m.

They

are

used in

researc

h based

proble

ms like

in CFD

C

O

3

Its idea

can be

used to

solve

some

of the

comple

x

proble

ms in

definite

integral

s.

This is

mainly

used

for the

comple

x

integrat

ion

which

can be

faced

integral

s

can be

applied

in

various

researc

h

proble

ms

Page 53: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 53

C

O

4

These

ideas

can be

used to

approxi

mate

solutio

ns.

These

can be

used in

those

proble

ms

which

can be

fitted

through

polynol

mials.

Where

ver

polyni

mial

approxi

mtion

needed.

Arroxi

mation

method

s can

be used

in

reasear

ch

proble

ms

Certain

tools

need

polyno

mial

approxi

mation

C

O

5

Used in

FEM

PDE's

related

proble

ms can

be

solved

CFD

need

mainly

these

type of

numeri

cal

method

s

Can be

used in

CFDs

It is

used in

mainly

applicat

ions

related

too pde.

They are

mainly

applied

in

thermody

namics

and Fluid

mech etc.

Applie

d in

fluid

and

meteria

l

interact

ions

It

really

neede

d

theor

etical

and

applie

d

senari

o. Its

not

just a

indivi

dual

work

The

se

idea

s

can

be

use

d in

vari

ous

fiel

d

whi

ch

nee

d

PD

E

C

O

6

Variou

s ideas

can be

applied

to

proble

ms like

CFD

and

signal

process

ing

They

would

get an

idea of

folmula

tion of

certain

proble

ms

They

can

solve

comple

x

proble

ms

easily

they

have

many

applicat

ions in

researc

h.

They

get idea

of tools

making

like

CFD

and lile

that.

They are

used in

making

certain

structures

they

are

mainly

used in

mathe

matical

realted

proble

ms.

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

1 Application of Integral equation Seminar

2 Theory related application numerical solutions of partial differential equations Lecturing

3 Greens function application

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

Page 54: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 54

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

1 Integral equations and applications

2 Applications of series solution of integral equations

3 Applications of gamma and beta functions

4 Applications of differential equations and series solutions

5 Applications of partial differential equations and numerical solutions

WEB SOURCE REFERENCES:

1 en.wikipedia.org/wiki/Heaviside_step_function

2 en.wikipedia.org/wiki/Beta_function

3 rmmc.asu.edu/jie/jie.html

4 gwu.geverstine.com/pdenum.pdf

5 en.wikipedia.org/wiki/Power_series_solution_of_differential_equations

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

☐ CHALK & TALK ☐ STUD. ASSIGNMENT ☐ WEB RESOURCES

☐ LCD/SMART BOARDS ☐ STUD. SEMINARS ☐ ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

☐ ASSIGNMENTS ☐ STUD. SEMINARS ☐ TESTS/MODEL EXAMS ☐ UNIV. EXAMINATION

☐ STUD. LAB PRACTICES ☐ STUD. VIVA ☐ MINI/MAJOR PROJECTS ☐ CERTIFICATIONS

☐ ADD-ON COURSES ☐ OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

☐ ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK,

ONCE)

☐ STUDENT FEEDBACK ON FACULTY (TWICE)

☐ ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS ☐ OTHERS

Prepared by

Mr. Shyam Sunder Iyer Approved by

(Faculty) (HOD)

Page 55: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 55

CS010 805G05 Natural Language Processing

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH YEAR: JUNE 2013 – DEC 2013

COURSE: NATURAL LANGUAGE PROCESSING SEMESTER: VIII CREDITS: 4

COURSE CODE: CS010 805G05 COURSE TYPE: ELECTIVE

COURSE AREA/DOMAIN: PROGRAMMING LANGUAGE CONTACT HOURS: 2+2 (Tutorial) hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

SYLLABUS:

UNIT DETAILS HOURS

I INTRODUCTION:Introduction: Knowledge in speech and language processing – Ambiguity –Models

and Algorithms – Language, Thought and Understanding. Regular Expressions and automata: Regular

expressions – Finite-State automata. Morphology and Finite-State Transducers: Survey of English

morphology – Finite-State Morphological parsing –Combining FST lexicon and rules – Lexicon-Free

FSTs: The porter stammer – Human morphological processing

12

II

SYNTAX:Word classes and part-of-speech tagging: English word classes – Tagsets for English – Part-

of-speech tagging – Rule-based part-of-speech tagging – Stochastic part-of speech tagging –

Transformation-based tagging – Other issues. Context-Free Grammars for English: Constituency –

Context-Free rules and trees – Sentence-level constructions – The noun phrase – Coordination –

Agreement – The verb phase and sub categorization – Auxiliaries – Spoken language syntax – Grammars

equivalence and normal form – Finite-State and Context-Free grammars – Grammars and human

processing. Parsing with Context-Free Grammars: Parsing as search – A Basic Top-Down parser –

Problems with the basic Top- Down parser – The early algorithm – Finite-State parsing methods.

12

III ADVANCED FEATURES AND SYNTAX :Features and Unification: Feature structures –

Unification of feature structures – Features structures in the grammar – Implementing unification –

Parsing with unification constraints – Types and Inheritance. Lexicalized and Probabilistic Parsing:

Probabilistic context-free grammar – problems with PCFGs – Probabilistic lexicalized CFGs –

Dependency Grammars – Human parsing.

12

IV SEMANTIC:Representing Meaning: Computational desiderata for representations – Meaning

structure of language – First order predicate calculus – Some linguistically relevant concepts –

Related representational approaches – Alternative approaches to meaning. Semantic Analysis:

Syntax-Driven semantic analysis – Attachments for a fragment of English – Integrating semantic analysis

into the early parser – Idioms and compositionality – Robust semantic analysis. Lexical semantics:

relational among lexemes and their senses – WordNet: A database of lexical relations – The Internal

structure of words – Creativity and the lexicon.

12

V APPLICATIONS:Word Sense Disambiguation and Information Retrieval: Selectional restriction-based

disambiguation – Robust word sense disambiguation – Information retrieval –other information retrieval

tasks. Natural Language Generation: Introduction to language generation – Architecture for generation –

Surface realization – Discourse planning – Other issues. Machine Translation: Language similarities and

differences – The transfer metaphor –The interlingua idea: Using meaning – Direct translation – Using

statistical techniques – Usability and system development.

12

TOTAL HOURS 60

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

1 Daniel Jurafsky & James H.Martin, “ Speech and Language Processing”, Pearson

Education(Singapore)Pte.Ltd.,2002. 2 James Allen, “Natural Language Understanding”, Pearson Education, 2003

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

CS010

702,CSOIO406

COMPILER CONSTRUCTION,THEORY OF

COMPUTATION

Compiler consepts,parsing,automata langauges VI,IV

COURSE OBJECTIVES:

1 To acquire a general introduction including the use of state automata for

Page 56: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 56

language processing

2 To understand the fundamentals of syntax including a basic parse

3 To explain advanced feature like feature structures and realistic parsing

Methodologies

4 To explain basic concepts of remotes processing

5 To give details about a typical natural language processing applications

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Graduates will have knowledge in Morphological features of English language a,b

2 Graduates will have the ability to design a parser for English language a,b,c,d

3 Graduates will be able to design a good Syntax representation a language b,c

4 Graduates will be able represent syntax and semantics of a language b

5 Graduates will able to do projects in Translation,Disambiguation,Discourse analysis etc. f,g,h

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SN

O

DESCRIPTION PROPOSED

ACTIONS

PO

MAPPING

1 Morphology of Malayalam or other Indian

languages

Assignment c

2 Parsing Indian languages Assignment c

3 Translating Indian languages Lab Session/projects c PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

SNO Topic PO MAPPINGS

1 Text Segmentation b,c,g

2 Text Clustering b,c,g

3 Text Summarization b,c,g

4 Implementation of Support vector machines b,c,g

5 Use of Neural networks,Genetic algorithms

Fuzzy logic for Text processing

b,c,f,g

WEB SOURCE REFERENCES:

1 http://www.cs.toronto.edu/~kazemian/textsegsum.pdf

2 www.unal.edu.co/diracad/einternacional/Weka.pdf

3 http://link.springer.com/chapter/10.1007%2F978-1-4614-3223-4_3#page-1

4 www.joachims.org/publications/joachims_98a.pdf

5 http://www.statsoft.com/textbook/support-vector-machines/

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD. ASSIGNMENT WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

m. ASSIGNMENTS STUD. SEMINARS TESTS/MODEL EXAMS UNIV.

EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS CERTIFICATIONS

Page 57: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 57

ADD-ON COURSES OTHERS

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK, ONCE) STUDENT FEEDBACK ON FACULTY (ONCE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved by

Dhanya P.M Mr. Ajith S

(H.O.D)

Page 58: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 58

Page 59: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 59

CS010 806 Computer Graphics Lab

COURSE INFORMATION SHEET PROGRAMME: COMPUTER SCIENCE & ENGINEERING DEGREE: BTECH JAN-JUN 2014

COURSE: COMPUTER GRAPHICS LAB SEMESTER: EIGHTH CREDITS: 2

COURSE CODE: CS010 806

REGULATION: 2010

COURSE TYPE: CORE

COURSE AREA/DOMAIN: RECENT TRENDS IN

COMPUTING

CONTACT HOURS: 3 hours/Week.

CORRESPONDING LAB COURSE CODE (IF ANY): LAB COURSE NAME:

SYLLABUS:

UNIT DETAILS HOURS

I Experiments to implement the following

1 DDA Algorithm

2. Bresenham's Line drawing Algorithm for any slope.

3. Mid-point Circle Algorithm.

4. 2D Transformations

9

II Experiments to implement the following

1. 3D Rotations on a cube (about any axis, any general line) controlled by keyboard

navigation keys.

2. 3D Rotations on a cube with hidden surface elimination.(keyboard controlled)

3. Composite transformations

4. Bezier cubic splines like screen saver

5. Any Fractal Construction (Koch curve )

6. Animations using the above experiments.(eg.moving along curved path)

33

TOTAL HOURS 42

Lab Cycle

1. Implement DDA line Algorithm.

2. Implement Bresenham’s line Algorithm.

3. Implement Bresenham's circle Algorithm.

4. Implement Midpoint Circle Algorithm

9

5. Menu driven program to do the following transformations on an asymmetric

quadrilateral. a)Translation. b) Scaling. c) Rotation. d) Reflection.

6. Write a program to implement Bezier and B-Spline curves

6

7. Write a program to implement Cohen-Sutherland line clipping algorithm.

8. Implement polygon clipping using Sutherland-Hodgeman polygon clipping algorithm.

6

9. Write a program to implement Composite transformations

10. Menu driven program to do the following 3d transformations on a cube

a) Translation. c) Rotation. d) hidden surface elimination

6

11. Simulate a scene in which a man with an umbrella rowing a boat is subjected to three

different climatic conditions like hot sun, heavy rain and strong wind.

12. Simulate a moving conveyor belt with a ball placed on it. The spokes of the wheel

should rotate.

13. Simulate the motion of a cyclist on a slope. The cycle should ascend the hill, descend

the hill and move through the plain.

14. Simulate a burning candle (height should reduce gradually).Show how the flame

waves in the wind

9

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Department of CSE, RSET 60

15. Write a program to implement a fern (fractal) 3

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

R1 Computer Graphics (C version) - Donald Hearn & Pauline Baker (Pearson Education

Asia)

R2 Procedural Elements for Computer Graphics –David F. Rogers, TATA McGraw Hill

edition-second edition.

R3 Computer Graphics - Zhigang Xiang & Roy A Plastack, Schaum’s Series McGraw

Hill edition.

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

EN010101 Engineering Mathematic I Basic familiarity with calculus and linear

algebra

1

CS010307 Programming Lab Programming skills 3

CS010703 COMPUTER GRAPHICS Theoretical background 7

COURSE OBJECTIVES:

1 To acquaint the students with the implementation of fundamental algorithms in Computer Graphics.

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Students will develop programs for lines and circle drawing. A,b,c

2 Students will program the hidden surface elimination technique and demonstrate the

rotation of the 3d object.

A,b,c

3 Students will write program functions to implement the different transformations that

includes rotation, translation, scaling of 2d objects

A,b,c,e

4 Students will be able to construct curves and irregular patterns

A,b,c

5 Students will write programs that demonstrate computer graphics animations

A,c,b

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

1

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY VISIT/GUEST

LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

SNO DESCRIPTION PO

MAPPING

1 Conics drawing algorithm A,b

Page 61: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 61

WEB SOURCE REFERENCES:

1 http://www.sersc.org/journals/IJCG/vol3_no2/1.pdf

2 http://winnyefanho.net/research/MEA.pdf

3 http://users.iit.demokritos.gr/~agalex/publications/CAG98.pdf

4 http://www.hhhprogram.com/2013/05/draw-elipse-midpoint-elipse-algorithm.html

5 http://comjnl.oxfordjournals.org/content/10/3/282.full.pdf

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK STUD. ASSIGNMENT WEB RESOURCES

LCD/SMART BOARDS STUD. SEMINARS ADD-ON COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMENTS STUD. SEMINARS TESTS/MODEL EXAMS UNIV. EXAMINATION

STUD. LAB PRACTICES STUD. VIVA MINI/MAJOR PROJECTS CERTIFICATIONS

ADD-ON COURSES OTHERS RECORD

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES (BY FEEDBACK,

ONCE)

STUDENT FEEDBACK ON FACULTY (ONCE)

ASSESSMENT OF MINI/MAJOR PROJECTS BY EXT. EXPERTS OTHERS

Prepared by Approved

by

Ajith S

Elizabeth Isaac

Page 62: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 62

COURSE PLAN

CS010 806 Computer Graphics Lab

LAB SCHEDULE-S8CS A & B

Cycle 1: Implementation of Graphics Algorithm

Day-1

1. Implement DDA Line Drawing Algorithm.

2. Implement Bresenham’s line Algorithm.

Viva: Module 1

Day-2

3. Implement Bresenham’s circle Algorithm.

4. Implement Midpoint circle Algorithm.

Viva: Module 1

Day-3

5. Menu driven program to do the following transformations on an asymmetric

quadrilateral.

a. Translation.

b. Scaling.

c. Rotation.

d. Reflection.

6. Write a menu driven program to implement composite 2d transformation.

Viva: Module 2 , Fair Record submission of Experiment 1,2,3,4.

Day-4

7. Menu driven program to do the following 3d transformations on a cube

a) Translation. c) Rotation. d) hidden surface elimination

8. Write a program to Implement Sierpinski Gasket using fractals

Viva: Module 2

Day-5

9. Write a program to implement Bezier cubic splines like screen saver.

10. Write a program to implement Bezier Curves and B-Spline Curves.

Viva: Module 3

Day-6

11. Implement polygon clipping using Sutherland-Hodgeman polygon clipping

algorithm.

12. Write a program to implement Cohen-Sutherland line clipping algorithm.

Viva: Module 3, Fair Record submission of Experiment 5,6,7,8.

Day-7

Mid term Lab Exam Viva: Module 1,2,3. , Fair Record submission of Experiments 1-

12.

Page 63: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 63

Cycle 2: Animation

Day-8

13. To write a program in c to simulate working of a table fan, display the

regulator and change rotation speed using mouse clicks.

14. To write a program in c to simulate aeroplane with the following functions

1.take off

2.landing

3.turning left

4.turning right

Use arrow keys for different functions.

Viva: Module 4 and 5

Day-9

15. Simulate the motion of a cyclist on a slope. The cycle should ascend the hill,

descend the hill and move through a plain.

16. Simulate a burning candle (height should reduce gradually).Show how the

flame waves in the wind.

Viva: Module 4 and 5

Day-10

Final lab exam & Viva , Final record submission.

SI NO

Heading

R1 DDA LINE DRAWING ALGORITHM

R2 BRESENHAM’S LINE DRAWING ALGORITHM

R3 BRESENHAM’S CIRCLE DRAWING ALGORITHM

R4 MIDPOINT CIRCLE DRAWING ALGORITHM

R5 2D TRANSFORMATION

R6 2D COMPOSITE TRANSFORMATION

R7 3D TRANSFORMATION

Page 64: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 64

R8 COHEN-SURTHERLAND LINE CLIPPING ALGORITHM

R9 SIERPINSKI GASKET

R10 BEZIER CURES AND B-SPLINES CURVES

R11 BEZIER CUBIC SPLINES

R12 SUTHERLAND-HODGEMAN POLYGON CLIPPING

R13 TABLE FAN

R14 AEROPLANE MOVEMENTS

R15 MAN RIDING A BYCYCLE

R16 BURNING CANDLE

Page 65: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 65

CS010 807 Project

COURSE INFORMATION SHEET

PROGRAMME: COMPUTER SCIENCE

& ENGINEERING

DEGREE: BTECH

COURSE: PROJECT WORK

SEMESTER: VII CREDITS: 4

COURSE CODE : CS010 807

REGULATION: 2010

COURSE TYPE: CORE

COURSE AREA/DOMAIN: CONTACT HOURS: 6 hours/Week.

CORRESPONDING LAB COURSE CODE (IF

ANY):

LAB COURSE NAME:

SYLLABUS:

UNIT DETAILS HOURS

The progress in the project work is to be presented by the middle of eighth semester before the evaluation committee. By this time, the students will be in a position to publish a paper in international/ national journals/conferences. The EC can accept, accept with modification, and request a resubmission. The progress of project work is found unsatisfactory by the EC during the middle of the eighth semester presentation, such students has to present again to the EC at the end of the semester and if it is also found unsatisfactory an extension of the project work can be given to the students. Project report: To be prepared in proper format decided by the concerned department. The report shall record all aspects of the work, highlighting all the problems faced and the approach/method employed to solve such problems. Members of a project group shall prepare and submit separate reports. Report of each member shall give details of the work carried out by him/her, and only summarize other members’ work. The student’s sessional marks for project will be out of 100, in which 60 marks will be based on day to day performance assessed by the guide. Balance 40 marks will be awarded based on the presentation of the project by the students before an evaluation committee.

TOTAL HOURS 6

TEXT/REFERENCE BOOKS:

T/R BOOK TITLE/AUTHORS/PUBLICATION

Seven latest international journal papers having high impact factor

COURSE PRE-REQUISITES:

C.CODE COURSE NAME DESCRIPTION SEM

CS010 304 Computer Organization 3

Page 66: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 66

CS010 305 Switching Theory and Logic

Design

3

CS010 403 Data Structures and

Algorithms

4

CS010 405 Microprocessor Systems 4

CS010 406 Theory of Computation 4

CS010503 Database Management

Systems

5

CS010505 Operating Systems 5

CS010602 Internet Computing 6

CS010604 Computer Networks 6

CS010710 Project Work 7

COURSE OBJECTIVES:

1 To help student demonstrate practical concepts, command and knowledge gained so

far into realistic project

2 Provide exposure to prominent cutting edge technologies, sufficient training and

opportunistic to work as teams on multidisciplinary projects with effective writing

and communication skills

COURSE OUTCOMES:

SNO DESCRIPTION PO

MAPPING

1 Graduates will be able to make contributions in design,

implementations and execution of Computer science related projects.

a,c

2 Graduates will be able to develop practical skills needed to

understand and modify problems related to programming and

designing

a,c

3 Graduates will get an exposure to current technologies d

4 Graduates will get opportunities to work as teams on

multidisciplinary projects with effective writing and communication

skills

f,g

GAPS IN THE SYLLABUS - TO MEET INDUSTRY/PROFESSION REQUIREMENTS:

SNO DESCRIPTION PROPOSED

ACTIONS

Page 67: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 67

1

2

3

4

5

PROPOSED ACTIONS: TOPICS BEYOND SYLLABUS/ASSIGNMENT/INDUSTRY

VISIT/GUEST LECTURER/NPTEL ETC

TOPICS BEYOND SYLLABUS/ADVANCED TOPICS/DESIGN:

1

2

3

4

5

WEB SOURCE REFERENCES:

1 ieee.org

2 dl.acm.org

DELIVERY/INSTRUCTIONAL METHODOLOGIES:

CHALK & TALK ☐ STUD.

ASSIGNMENT

WEB

RESOURCES

LCD/SMART

BOARDS

STUD.

SEMINARS

☐ ADD-ON

COURSES

ASSESSMENT METHODOLOGIES-DIRECT

ASSIGNMEN

TS

STUD.

SEMINA

RS

☐TESTS/MOD

EL EXAMS

☐ UNIV.

EXAMINATION

☐ STUD.

LAB

PRACTICES

STUD.

VIVA

MINI/MAJOR

PROJECTS

CERTIFICATIO

NS

☐ ADD-ON

COURSES

OTHER

S

ASSESSMENT METHODOLOGIES-INDIRECT

ASSESSMENT OF COURSE OUTCOMES

(BY FEEDBACK, ONCE)

☐ STUDENT FEEDBACK ON

FACULTY (TWICE)

Page 68: emester VI, Course Hand-Out

Semester VIII, Course Hand-Out

Department of CSE, RSET 68

☐ ASSESSMENT OF MINI/MAJOR

PROJECTS BY EXT. EXPERTS

☐ OTHERS

Prepared by Approved

by

Mintu Philip (HOD)