Department of Computer Science and Engineering

Theory (14 Hours)

State Space Search, Two-agent Games, Logic, Machine Learning

Practical (42 Hours)

State Space Search – Water Jug Problem, Missionaries and cannibals, Tower of HANOI, Eight puzzle, Implementation of these problems using both uninformed and informed search. – BFS, DFS, Best First Search, A*

Two-agent Games – Tic-Tac-Toe using Min-Max search and Alpha-Beta pruning, Constraint Satisfaction Problems – N-Queens using Heuristic repair and constraint propagation

Logic-Unification, Resolution,Answer Extraction Using Resolution

Machine Learning – Decision Tree, Candidate Elimination, Clustering (K-means), Neural net learning (Perceptron), Genetic algorithms (2SAT), Expert Systems, Natural Language Processing

References:

1. George F Luger, Artificial Intelligence- Structures and Strategies for Complex Problem Solving, 4/e, Pearson Education, 2002.

2. E. Rich, K.Knight, Artificial Intelligence, 2/e, Tata McGraw Hill, 2000.

3. S Russel, P Norvig, Artificial Intelligence- A Modern Approach, 2/e, Pearson Education, 2002.

3. Winston. P. H, LISP, Addison Wesley, 1996.

4. Ivan Bratko, Prolog Programming for Artificial Intelligence, 3/e, Addison Wesley, 2000.

CS3097 WEB PROGRAMMING LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)

Review of basic technologies and concepts in Web Programming

Practical (42 Hours)

• 
  Basic web client: Client programming, processing and parsing data when reading from a network socket - basics of the HTTP protocol.
  
• 
  Basic web server: Client-server programming - Implement a protocol. 1.0 specification of HTTP - conditional get and cookies.
  
• 
  Concurrent web server: Modifying web server for pool of threads - semaphores to synchronize access to shared memory.
  
• 
  Performance evaluation: Workload generation, and performance evaluation. performance improvement gained by using threads - optimization.
  
• 
  Peer-to-peer web browser: Peer-to-peer programming – building a distributed system. Peer to peer file sharing – synchronization similar to BitTorrent tracker. Quantifying scalability.
  
• 
  Complete web application: Developing a database-driven complete web application following SDLC. Database backend (say MySQL) – application in PHP / Rails.
  

References:

1. 
   Sam Ruby, Dave Thomas and David Heinemeier Hansson. Agile Web Development with Rails, 3/e, Pragmatic Programmers, 2009.
   
2. 
   Hugh E. Williams and David Lane. Web Database Applications with PHP and MySQL, 2/e, O'Reilly & Associates, May 2004.
   

CS4091 BIOCOMPUTING LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56Hrs  
Module 1 (3 (T) + 10 (P) Hours)

Familiarization with Bioinformatics Resources: Understanding of biological databases [GenBank, EMBL, DDBJ, PDB, PIR, SwissProt], Retrieving and analyzing various types of data from these databases, Study of sequence alignment tools (both standalone and online versions) [DotPlot, Clustal, BLAST, FASTA], Study of PHYLIP.

Module 2 (3 (T) + 10 (P) Hours)

Introduction to Bio-programming languages: BioPerl, BioPython, BioJava.

Module 3 (3 (T) + 10 (P) Hours)

Study of Genomics and Proteomics Tools: Working with Genscan, Study of molecular visualization tools [Rasmol, Deep View], Study of Protein structure prediction tools [SCOP, MODELLER, I-TASSER]

Module 4 (5 (T) + 12 (P) Hours)

Implementation of algorithms in Bioinformatics: Sequence analysis and alignment, Motif finding, Protein structure prediction, Construction of Phylogenetic trees.

References:

1. 
   Neil C Jones and Pavel A Pevzner, An Introduction To Bioinformatics Algorithms, MIT Press, 2004.
   
2. 
   Richard Ernest Bellman, Dynamic Programming, Princeton University Press, 2003.
   
3. 
   Dan Gusfield, Algorithms On Strings, Trees, And Sequences, Cambridge University Press, 1997.
   
4. 
   Gary Benson and Roderic Page, Algorithms In Bioinformatics, Springer, Vol 2812, 2003.
   

CS4092 DATA MINING LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours) + Practical (42 Hours)

Introduction to Scilab Matrix operations, Plotting functions, contours (2(T)+6(P)Hours)

Classification Bayesian classifier, Perceptron , Support Vector Machine(3(T)+12(P) Hours)

Clustering K-means and EM Clustering (3(T)+6(P) Hours) Association rule mining (2(T)+6(P) Hours)

Feature selection (2(T)+6(P) Hours) Introduction to Weka (2(T)+6(P) Hours)

References:

1. 
   Pang-Ning Tan,Michael Steinbach and Vipin Kumar Introduction to Data Mining, Pearson Education 2006.
   
2. 
   Han and Kamber, Data Mining: Concepts and Techniques, 2/e, Morgan Kaufmann.
   

CS4093 IMAGE PROCESSING LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)

An introduction to digital images- sampling, quantization. Basic image processing, arithmetic processing. Image enhancement and point operation. Image enhancement and spatial operation. Color images and models models. Frequency domain operations.

Practical (42 Hours)

Lab1: An introduction to digital images- sampling, quantization, Image re-sampling, Image properties: bit-depth

Lab2: Basic image processing, arithmetic processing
Lab3: Image enhancement and point operation- Linear point operation, clipping, thresholding, negation, non-linear mapping, intensity slicing, image histogram, histogram equalization.
Lab4: Image enhancement and spatial operation- Convolution, correlation, linear filtering, edge detection.

Lab5: Color images- color models, color enhancement, color thresholding.

Lab6: Frequency domain operations- fourier transform, freq domain filtering
References:

1. Rafael C., Gonzalez & Woods R.E., Digital Image Processing, Addison Wesley, 2007.

2. Jain A.K, Fundamentals of Digital Image Processing, Prentice Hall, Englewood Cliffs, 2002.

3. Schalkoff R. J., Digital Image Processing and Computer Vision, John Wiley, 2004.

CS4094 COMPUTER VISION LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)
Edge operations: Various edge operators.

Segmentation and clustering techniques and applications.

Colouring and color image processing. Object detection and classification.

Computation of 3D scene from 2D.

Practical (42 Hours)

MatLab implementation for the following:

1. 
   Edge operations:
   
2. 
   Segmentation: by clustering, segmentation by fitting models-Vision applications.
   
3. 
   Colouring techniq ues, Pseudo-colouring,
   
4. 
   Colour image analysis.
   
5. 
   Object detection and classifications
   
6. 
   Computation of 3D scene from 2D.
   

References:

1. 
   David A Forsynth and Jean Ponce (2003), Computer Vision- A modern approach, Pearson education series, 2003.
   
2. 
   Milan Sonka, Vaclav Hlavac and Roger Boyle (2008), Digital image processing and computer vision, Cengage learning, 2008.
   
3. 
   Schalkoff R. J., Digital Image Processing and Computer Vision, John Wiley, 2004.
   

CS4095 COMPUTER GRAPHICS LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)

OpenGL programming - constructs and standards.

Practical (42 Hours)

Drawing Geometric Primitives - case studies.

Create simple models.

Interactive Transformations and Projections

Parsing simple mesh file formats

Rendering meshes.

Case Study: Model a scene, Place lights on the scene, render shadows and texture models.
References:

1. 
   D. Shreiner, M. Woo, J. Neider and T. Davis, OpenGL Programming Guide, Addison Wesley, 2005.
   

CS4096 SOFTWARE ENGINEERING LABORATORY

Pre-requisite: CS3004 Software Engineering

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)

Introductory Lectures on the use of appropriate tools is to be given.

Peer review discussions of deliverables will also be done in theory sessions.
Practical (42 Hours)

Objective is to develop a significant software product using sound software engineering principles by small student groups. Choice of appropriate methodology and standard tools are also expected. The lab will have deliverables at each milestone of development.

1. 
   Problem Statement / Product Specification
   
2. 
   Project Plan – Project Management Tool to be identified and Estimation and Costing to be done.
   
3. 
   Requirements Document – Specification Tool choice to be justified - In class Review
   
4. 
   Design Document – Choice of Methodology to be justified - In class Review
   
5. 
   Code and Test Report – Peer review documents of standards adherence to be provided
   
6. 
   Demo – Integrated Product or Solution to the problem
   
7. 
   Review of the process and analysis of variation from initial plan and estimation.
   

References:

1. 
   Roger S Pressman, Software Engineering: A Practitioner’s Approach, 6/e, Mc Graw Hill, 2008.
   

CS4097 OBJECT ORIENTED PROGRAMMING LABORATORY

Pre-requisite: Nil

L	T	P	C
1	0	3	3

Total Hours: 56 Hrs  
Theory (14 Hours)

Procedural vs. Objected oriented approaches – Concept of Abstraction - Design and analysis using OO methodologies. Introduction to UML.

Practical (42 Hours)

The implementation has to be done using languages like C++/Java/C#.

Programs to study

Functions – Control structures – String handling – File handling

Error and Exception handling

Class – Objects –Instantiation

Principles of Inheritance, Encapsulation, Polymorphism – Overloading, Virtual functions

OO Design with stress on interface specification. Automated code generation and component reuse - UML

References:

1. 
   B Stroustrup, The C++ Programming Language, 3/e, Addison Wesley, 1997.
   
2. 
   Steve Oualline, Practical C++ Programming, 2/e, O'Reilly & Associates, 2002.
   
3. 
   J Nino and F A Hosch, An introduction to programming and object oriented design using Java, Wiley India, 2010.