PUNJABI UNIVERSITY, PATIALApupdepartments.ac.in/syllabi/Old Syllabi [For Reference and Record... · Web viewoutlines of tests, syllabi and courses of readings. for. m. tech. (computer

PUNJABI UNIVERSITY, PATIALA

OUTLINES OF TESTS,SYLLABI AND COURSES OF READINGS

FOR

M. TECH. (COMPUTER SCIENCE & ENGINEERING) PART-II

IIIrd and IVth SEMESTER

2010-2011, 2011-12 SESSION

DEPARTMENT OF COMPUTER SCIENCE,PUNJABI UNIVERSITY, PATIALA

SYLLABUSOUTLINES OF PAPERS AND TESTS

M. TECH (COMPUTER SCIENCE & ENGINEERING)SECOND YEAR- III & IV SEMESTER FOR

2010-2011, 2011-12 SESSION

CODE NO. TITLE OF PAPER MAXIMUM MARKS

CONTINUOUS ASSESSMENT

UNIVERSITY EXAMINATION

TIME ALLOWED

CS-711 Research Methodology 50 50 100 3 Hrs.

CS-712 Neural Networks & Fuzzy Logic

50 50 100 3 Hrs

CS-713 Software Lab-III 60 40 100 3 Hrs.

CS-714 Digital Image Processing 50 50 100 3Hrs.

CS-715 Project 50 50 100 3 Hrs.

Elective-I 50 50 100 3 Hrs.

Total 310 290 600

Elective-I1. CS-716 E1 Pattern Recognition

2. CS-716 E2 Embedded System

3. CS-716 E3 E-Commerce

4. CS-716 E4 Object Oriented Analysis & Design

5. CS-716 E5 Natural Language Processing

Note: Depending upon the availability of the teachers, the electives will be offered to the students. The decision of the Head of the Department in this respect will be final.

Allocation of Guides to M.Tech (III Semester) students: The Chairman Board of Studies of the Department and the local members of Board of Studies will assign the guides to M.Tech students and their decisions will be final. In case of non-availability of local members, the Chairman Board of Studies of the Department is empowered to appoint the new member from within the faculty for this purpose.

The project will be evaluated by a committee having following members. - HOD/HOD’s Nominee- Internal Supervisor- One/two nominee of D.A.A.- External Examiner

The Quorum will be of any three members.

CONTINUOUS ASSESSMENT (THEORY PAPERS)

1. Two or three tests out of 60% of the marks allotted for Continuous Assessment.which minimum two will be considered for assessment.

Or

2. Seminars/Assignments/Quizes 30% of the marks allotted for Continuous Assessment.

3. Attendance, class participation andbehaviour 10% of the marks allotted for Continuous Assessment.

SYLLABUSOUTLINES OF PAPERS AND TESTS

M. TECH (COMPUTER SCIENCE)SECOND YEAR-FOURTH SEMESTER EXAMINATIONS

CS-801 Dissertation 400 Marks

The break up of marks will be:

Seminar :25% of total marksViva :25% of total marksThesis :50% (External Examiner : 25% (to be awarded separately), Committee : 25%).

Keeping in view the demand of software development industry and foreign clientele, joint software development project may be allowed by the Head of the Department. As such joint project reports will also be recognized and the students should highlight their individual contributions in a joint project report at the time of viva-voce.

Allocation of Guides to M.Tech (IVth Semester) students: (i) The guide assigned to student for project in 3rd semester will continue to be the guide for 4th

semester as well. However, in case of exceptional circumstances the guide may be changed through The Chairman Board of Studies of the Department and the local members of Board of Studies.

(ii) The cases of those M.Tech. students who want to do project work outside the department will also be finalized by the above committee. The committee will approve the external guide in addition to the Internal guide.

The project will be evaluated by a committee having following members. - HOD/HOD’s Nominee- Internal Supervisor- One/two nominee of D.A.A.- External Examiner

The Quorum will be of any three members.

CS-711: Research Methodology L T P C

4 1 0 5Maximum Marks: 50 Maximum Time: 3 Hrs. Minimum Pass Marks: 40% Lectures to be delivered: 45-55

A) Instructions for paper-setterThe question paper will consist of five sections A, B, C, D and E. Sections A, B, C and D will have two questions from the respective sections of the syllabus and will carry 20% marks each. Section E will have 5-10 short answer type questions which will cover the entire syllabus uniformly and will carry 20% marks in all.

B) Instructions for candidates1. Candidates are required to attempt one question each from sections A, B, C and D of the question paper and

the entire section E.

2. Use of non-programmable scientific calculator is allowed.

SECTION-A

Scientific Research: Nature and Objectives of research; Methods of research: historical, descriptive and experimental. Study and formulation of research problem.

Scope of research and formulation of hypothesis; Feasibility, preparation and presentation of research proposal. Statistical Analysis: Introduction to statistical analysis: Measures of central tendency and dispersion; mean, median, mode, range, mean deviation and standard deviation.

SECTION-B

Regression and Correlation Analysis.

Random Variables and Probability Distribution: Probability and probability distributions; Binomial, Poisson, Geometric, Negative binomial, Uniform, Exponential, Normal and Log-normal distribution.

SECTION-C

Test of Hypothesis: Basic ideas of testing of hypothesis; Tests of significance based on normal, t and Chi-square distributions. Analysis of variance technique.

SECTION-D

Design of Experiments: basic principles, study of completely randomized and randomized block designs. Introduction to Thesis report writingPresentation: Edition and tabulation of results, presentation of results using figures, tables and text, quoting of references and preparing bibliography.

Softwares : Use of common softwares like SPSS, Mini Tab and/or Mat Lab. Fro statistical analysis .

Text Book :

1. Borth, Wayne C, et. Al. The Craft of Research Chicago Guides to Writing Edition and Publishing.

2. Johnson, R.A., Probability and Statistics, PHI, New Delhi, 1994. 3. Meyer, P. L. : Introduction to Probability & Statistical Applications : Oxford, IBH, 1986.

References :

1. Hogg, R.V. & Craig, A. T : Introduction to Mathematical Statistics: MacMillan, 1965. 2. Goon, A. M., Gupta, M. K. & Dasgupta : Fundamentals of Statistics, Vol. I : World Press, 1975. 3. Gupta, S.C. & Kapoor, V. K. : Fundamentals of Mathematical Statistics, Sultan Chand & Sons,

1994.

L T P C 4 1 0 5

CS-712 NEURAL NETWOKS AND FUZZY LOGIC

Maximum marks: 50 Maximum Time :3 Hrs.Minimum pass marks: 40% Lectures to be taken :45-55

A) Instructions for paper-settersThe question paper will consist of five sections A, B, C, D and E. Sections A, B, C and D will have two questions from the respective sections of the syllabus and will carry 20% marks each. Section E will have 5-10 short answer type questions which will cover the entire syllabus uniformly and will carry 20% marks in all.

B) Instructions for candidates1. Candidates are required to attempt one question each from sections A, B, C and D of the question paper

and the entire section E.

2. Use of non programmable scientific calculator is allowed.

SECTION A

Introduction of Neural Networks: Concepts of neural networks, Network Properties, Systems Dynamics. Inference & Learning : Neural Networks, Learning Algorithm, Data representation, Functional Classification, Neuron Concept, terminology, Notation & representation of Neural Networks. Perception: Single layer perceptrons, Multilayer Perceptrons, perceptron learning & training.

SECTION B

Back propagation: Concept, Back Propagation, Learning Algorithm. A derivation of Back propagation, Kohonen Network, Gross berg networks. Counter Propagation Networks: Counter propagation Algorithm & its Applications. Hopfield nets: Concept, Hopfield net Algorithm for Auto-association, Capacity of Hopfield Nets. Hopfield net Algorithm for optimization, stability of Hopfield nets.

SECTION C Fuzzy Set : Introduction, uncertainty, Newtonian mechanics, Probability Theory, organized simplicity, disorganized complexity, trans computational problems. Crisp Sets : An overview, fuzzy sets : Basic types, basic concepts. Fuzzy sets versus crisp sets, additional properties of alpha-cuts, representations of fuzzy sets. Operations on Fuzzy sets : Types of operations, fuzzy complements, Fuzzy instructions : t-Norms. Fuzzy Unicons : t-co norms, combination of operations, aggregation operations.

SECTION D

Fuzzy Logic : Classical logic, logic, reasoning, propositional logic, logic operation's logic formulas, tautology, inference rules, Boolean algebra, properties of Boolean algebra, quantification, predicate logic, multi-valued logic, fuzzy propositions, fuzzy quantifiers, linguistic hedges, Inference from conditional Fuzzy propositions,Inference from conditional and quantified propositions. Mamdani fuzzy models, Sugeno Fuzzy Models, Tsukamoto Fuzzy Model, Input space partitioning, Fuzzy modeling.

Books :

1. Li Min Fu," Neural Networks in Computer Intelligence", McGraw-Hill, Inc.2. George J Klir/Bo Yuan, "Fuzzy sets & Fuzzy Logic, Theory & Applications", PHI.3. "Neuro Fuzzy & Soft Computing : A Computational approach to learning & Machine Intelligence", J.S.R.

Jang, C.T. Sun, E. Mizutani. Pearson Education. 4. Ian Cloete & Jack M. Zurada, "Knowledge based Neuro Computing", University Press.

L T P C 0 0 6 6

CS-713 : SOFTWARE LAB-III

Maximum Marks: * Maximum Time :3 Hrs.Minimum Pass Marks: 40% Practicals Sessions to be Conducted : 45-55

The Laboratory assignments for this lab will include the assignments mainly from the papers CS-714: Digital Image Processing

*Maximum Marks for Continuous Assessment : 60Maximum Marks for University Examination : 40

L T P C4 1 0 5

CS-714 DIGITAL IMAGE PROCESSING






SECTION A

Digital Image Processing: Definition, Examples of Fields that use Digital Image Processing, Fundamental Steps in Digital Image Processing, Components of an Image Processing System.

Digital Image Fundamentals: Image Sensing, and Acquisition, Image Sampling and Quantization, Basic Relationship between Pixels, Distance Measures, Linear and Non-linear Operations.

Image Enhancement in Spatial Domain: Basic Gray Level Transformations, Histogram Processing, Enhancements using Arithmetic/Logic Operations, Basics of Spatial Filtering, Smoothing, Spatial Filters, Sharpening Spatial Filters, Combining Spatial Enhancement Methods.

SECTION B

Fourier Series, Impulses and their sifting Property, Discrete Fourier Transform (DFT) of one variable and Its Inverse, 2-D Discrete Fourier Transform and Its inverse, Properties of 2-D DFT, Image Smoothing using Frequency Domain Filters, Image Sharpening Using Frequency Domain Filters, Laplacian in Frequency Domain, Homomorphic Filtering, Bandreject and Bandpass Filters, Notch Filters, The Fast Fourier Transform in 1-D Image Restoration : Noise Models, Restoration in the Presence of Noise Only-Spatial Filtering, Periodic Noise Reduction by Frequency Domain Filtering, Linear, Position-Invariant Degradations, Estimating the Degradation Function, Inverse Filtering, Minimum Mean Square Error (Wiener) Filtering, Constrained Least Squares Filtering, Geometric Mean Filter, Geometric Transformations.

SECTION C

Colour Image Processing: Colour Models, Pseudocolour Image Processing, Basics of Full Colour Image Processing. Colour Transformations, Smoothing and Sharpening. Colour Segmentation. Wavelets and Multi Resolution Processing: Image pyramids, subband coding, The Haar Transform, series expansion, scaling functions, wavelet functions, wavelet transform in 1-D, Inverse Discrete wavelet Transform in 1-D, Fast wavelet Transform in 1-D, Discrete wavelet Transform in 2-D, wavelet Packets

SECTION D

Image Compression: Image Compression Models, Huffman coding, Golomb Coding, Arithmetic coding, LZW coding, Run Length coding, Bit-Plane coding, Block Transform coding, wavelet coding.Point Detection, Line Detection and Edge Detection, Edge Linking and Boundary Detection.Text Book:

1. R. C. Gonzalez, R. E. Woods, “Digital Image Processing”, Pearson Education-2002

References:

1. A. K. Jain, “Fundamentals of Digital Image Processing”, PHI, 2002

L T P C 0 1 0 0

CS-715: PROJECT

Maximum Marks: * Minimum Pass Marks: 40%

In this paper, the students will be doing analysis/implementation of a research problem to be

assigned by internal guide. The student is expected to carry out detailed literature survey of the

research problem. At the end of the semester the student will submit a report of the work carried

out.

*Maximum Marks for Continuous Assessment: 50Maximum Marks for University Examination: 50

L T P C4 1 0 5

CS-716 E1 PATTERN RECOGNITION (Elective)






SECTION-A

Introduction to Pattern Recognition: What is Pattern Recognition, Pattern Recognition Approaches, Examples of Pattern Recognition Applications. Features, Feature Vectors and Classifiers.

SECTION-B

Statistical pattern Recognition: Supervised Learning (training) using parametric and non parametric approaches, linear discriminant functions and discrete and binary feature cases, unsupervised learning and clustering.

SECTION-C

Syntatic Pattern Recognition: Syntatic Pattern Recognition via parsing and other grammars, graphical approaches to syntactic Pattern Recognition, learning via grammatical inference.

SECTION-D

Neural pattern Recognition: Introduction to Neural Networks, Introduction to Neural pattern associators and matrix approaches, Feedforward Networks and training by back propagation, Content Addressable Memory approaches and unsupervised learning in Neural Pattern Recognition.

Text Books:

1. Robert J. Schalkoff, “Pattern Recognition: Statistical, Syntactic and Neural Approaches”, John Wiley and Sons, NY, 1992.

2. “Pattern Recognition”, Second Edition, Academic Press.

L T P C4 1 0 5

CS-716 E2 EMBEDDED SYSTEM (Elective)






SECTION A

Embedded Systems: Typical Hardware.Hardware: Gates, Timing Diagrams, Microprocessors, Buses, Direct Memory Access, Interrupts, Built-Ins on the Microprocessor, Conventions Used on Schematics

Interrupts: Microprocessor Architecture, Interrupts Basics, Shared Data Problem, Interrupt Latency.

SECTION B

Software Architecture: Round Robin, Round Robin with Interrupts, Function Queue Scheduling Architecture, Real Time Operating system Architecture, Selecting an Architecture.

Real Time Operating Systems: Tasks and Task States, Tasks and Data, Semaphores and Shared Data.

SECTION C

Operating System Services: Message Queues, Mailboxes and Pipes, Timer Functions, Events, Memory Management.

Design using Real Time Operating System: Encapsulating Semaphores and Queues, Hard Real Time Scheduling Considerations, Saving Memory Space, Saving Power.

SECTION D

Embedded Software Development Tools: Host and Target Machines, Linker/Loader for Embedded Software, Getting Embedded Software into the Target System.

Debugging Techniques: Testing on Host Machine, Instruction Set Simulator, Assert Macro, Using Laboratory Tools.

Text Book:

1. D. E. Simon, “An Embedded Software Primer”, Pearson Education.

References:

1. D. W. Lewis, “Fundamentals of Embedded Software”, Pearson Education2. M. A Mazidi, “The 8085 Microcontroller and Embedded System”, Pearson Education

L T P C4 1 0 5

CS-716 E3 E-COMMERCE (Elective)






SECTION A

E-Commerce : Meaning, advantages & disadvantages. Electronic Commerce Framework, Electronic Commerce and media Convergence, The Anatomy of E-commerce Applications, Types of E-Commerce.Architectural Framework for Electronic Commerce, World Wide Web as the Architecture, Web Background : Hypertext publishing, Security and the Web.

SECTION B

Client-Server Network Security, Emerging Client-Server Security Threats, Firewalls and Network Security, Data and Message Security, Digital signatures, Encrypted Documents and Electronic Mail : PGP and PEM.

Legal, Ethical and other public policy issues related to Electronic Commerce : Protecting privacy, protecting Intellectual property, Copyright, trademarks and patents, Taxation and encryption policies.

SECTION C

Consumer oriented Electronic commerce : Consumer oriented applications, Mercantile models from the Consumer’s perspective-Mercantile models from the Merchant perspective.

SECTION D

Types of Electronic Payment Systems, Digital Token- Based Electronic Payment Systems, Smart cards and Electronic payment Systems, Credit Card-Based Electronic Payment Systems, Risk and Electronic payment Systems, Designing Electronic Payment Systems.

Electronic Data Interchange, EDI Applications in Business, EDI : Legal, Security and Privacy Issue, EDI and Electronic Commerce.

Text Book :

1. Ravi Kalakota Andrew B. Whinston : Frontiers of Electronic Commerce, Addison Wesley.

References:1 Efraim Turbon, Jae Lee, David King, Chung : Electronic Commerce- A managerial perspective,

Prentice-Hall International.2 Greenstein, Feinnman : Electronic Commerce, Tata McGraw-Hill.3 Jeffrey F. Rayport, Bernard J. Jaworski : e-Commerce, Tata McGraw Hill..4 David Whiteley : e-Commerce, Tata McGraw Hill.5 Pete Loshin, Paul A. Murphy : Electronic Commerce, Jaico Publishing House.

L T P C4 1 0 5

CS-716 E4 OBJECT ORIENTED ANALYSIS & DESIGN (Elective)






SECTION A

Introduction to Object: Object Orientation, Development, Modeling, Object Modeling technique. Object modeling: Objects and classes, Links and Association, Generalization and inheritance, Grouping constructs, Aggregation, Abstract Classes, Generalization as extension and restriction, Multiple inheritance, Meta data, Candidate keys, Constraints.Dynamic modeling: Events and states, Nesting, Concurrency, Advanced Dynamic Modeling conceptsFunctional modeling: Functional Models, Data flow diagrams, Specifying operations, Constraints, Relation of Functional model to Object and Dynamic Models.

SECTION B

Design Methodology, Analysis: Object modeling, Dynamic modeling, Functional modeling, Adding operations, Iterating Analysis.System design: Subsystems Concurrency, Allocation to processor and tasks, Management of data stores, Handling Global Resources, Handling boundary Conditions, Setting Trade-off priorities.Object Design: Overview, Combining the three models, Designing Algorithms, Design Optimization, Implementation of Control, Adjustment of Inheritance, Design of Associations, Object Representation, Physical Packaging, Document Design Decision.

Comparison of methodologies: Structured Analysis/Structured Design, Jackson Structured Development.Implementation: Using Programming Language, Database System, outside Computer.Programming Style: Object Oriented Style, Reusability, Extensibility, Robustness, Programming-in-the-large.

SECTION C

UML: Basics, Emergence of UML, Types of Diagrams.Use Case: Actors, Use Case Diagram, Relationships between Use Cases.Classes: Class Diagram, Classes, Objects, Attributes, Operations, Methods, Interfaces, Constraints, Generalization, Specialization, Association, Aggregation.

SECTION DBehavioral Diagrams: Activity Diagram, Collaboration Diagram, Sequence Diagram, Statechart Diagram.Implementation Diagrams: Component Diagram, Deployment Diagram

Text Books:

1. Rambough, “Object Oriented Modeling and Design”, Pearson Education, 20022. Bernd Oestereich, “Developing Software With UML”, Pearson Education.

References:

1. BOOCH, “Object Oriented Analysis and Design”, Addison Wesley2. Pierre-Alain Muller, “Instant UML”, Shroff Publishers, 20003. Booch, Rumbaugh, Jacobson, “The Unified Modeling Language User Guide”, Addison Wesley, 19994. Booch, Rumbaugh, Jacobson, “The Unified Modeling Language Reference Manual”, Addison Wesley,

19995. Rebecca Wirfs-Brock, “Design Object Oriented Software”, PHI

CS-716 E5 Natural Language ProcessingMaximum marks: 50 Maximum Time :3 Hrs.Minimum pass marks: 40% Lectures to be taken :45-55





Section A:

Introduction to NLP: Definition, History, Applications, Goals.Regular expressions and Automata, Morphology and Finite State Transducers, N-grams, HMMs

Section B:

Syntax: Word Classes and Part-of Speech Tagging, Context Free Grammars for English, Parsing with Context-Free Grammars.

Section C:

Word Sense Disambiguation: Selection Restriction Based Disambiguation, Robust WSD: Machine Learning, Supervised Learning Approaches, Bootstrapping Approaches, Unsupervised Methods, Dictionary Based Approaches.

Section D:

Machine Translation: Introduction, Language Similarities and Differences, Approaches, Steps involved in machine translation system design, Study of a case study of machine translation for a language pair.Text Books:

1. Jurafsky, D. & J. Martin, "Speech and Language Processing: An Introduction to Natural Language Processing Computational Linguistics, and Speech Recognition" Prentice Hall, 2000.

References:

1. Grosz, B.J., Sparck Jones, K. & Webber, B.L. (eds) "Readings in natural language processing", Los Altos, CA. Morgan Kaufmann, 1986.

2. Allen, J., "Natural Language Understanding", Redwood City, CA: 1994. Benjamin/Cummings.3. Bharti, Akshar,Chaitanya Vineet, Sangal Rajeev, "Natural Language Processing", Prentice Hall.