COURSE HAND-OUT
B.TECH. - SEMESTER VIII
DEPARTMENT OF COMPUTER SCIENCE
AND ENGINEERING
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
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.
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.
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
Semester VIII, Course Hand-Out
Department of CSE, RSET 6
COURSE PLAN 62
CS010 807 Project 65
COURSE INFORMATION SHEET 65
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
Semester VIII, Course Hand-Out
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.
Semester VIII, Course Hand-Out
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
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)
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
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 -
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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.
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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:
Semester VIII, Course Hand-Out
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)
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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:
Semester VIII, Course Hand-Out
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)
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
Department of CSE, RSET 24
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.
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
Department of CSE, RSET 28
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)
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
Department of CSE, RSET 30
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
Semester VIII, Course Hand-Out
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.
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
Department of CSE, RSET 34
Prepared by Approved
by
Ms. Tripti. C Mr. Ajith S
(H.O.D)
Semester VIII, Course Hand-Out
Department of CSE, RSET 35
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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.
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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:
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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)
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
Semester VIII, Course Hand-Out
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
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)
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
Semester VIII, Course Hand-Out
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
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)
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
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
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
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
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)
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
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
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)
Semester VIII, Course Hand-Out
Department of CSE, RSET 58
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
Semester VIII, Course Hand-Out
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
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
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.
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
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
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
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
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)
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)