m.tech i year i semester(computer science & engineering) course structure...

M.Tech I Year I Semester(Computer Science & Engineering)

COURSE STRUCTURE

Sl.No. Code COURSE L P C

1 CSEP1 1401 Data Structures and Algorithms 3+1* - 4

2 CSEP1 1402 Database Management Systems 3+1* - 4

3 CSEP1 1403 Operating Systems 3+1* - 4

4 MEP1 1401 Advanced Optimization Techniques 3+1* - 4

5 Elective – 1 3+1* - 4

CSEP1 1404 Computer Organization & Architecture

3+1*CSEP1 1405 Cryptography and Network Security

CSEP1 1406 Information Retrieval Systems

6 Elective – 2 3+1* - 4

CSEP1 1407 Bio – Informatics

CSEP1 1408 Embedded Systems

CSEP1 1409 Object Oriented Software Engineering -

7 CSEP11210 Data Structures and Algorithms Laboratory - 4 3

8 GMRP10206 Term Paper - - 3

Total Credits 30

M.Tech I Year II Semester(Computer Science & Engineering)

COURSE STRUCTURESl.No. Code COURSE L P C

1 CSEP1 1411 Data Warehousing and Data Mining 3+1* - 4

2 CSEP1 1412 Mobile Computing 3+1* - 4

3 CSEP1 1413 Soft Computing Techniques 3+1* - 4

4 CSEP1 1414 Web Technologies 3+1* - 4

5 Elective – 3 3+1* - 4

CSEP1 1415 Compiler Design

3+1*CSEP1 1416 Distributed Systems

CSEP1 1417 Open Source Software

6 Elective – 4 - 4

CSEP1 1418 Cloud Computing

3+1* -CSEP1 1419 Image Processing & Pattern Recognition

CSEP1 1420 Social Networks and Semantic Web

7 CSEP11221 Web Technologies Lab - 4 3

8 GMRP10202 Comprehensive Viva – voce - - 3

Total Credits 30

M.Tech II Year III & IV Semesters (Computer Science & Engineering)

COURSE STRUCTURESl.No. Code COURSE L P C

1 GMRP20403 Internship and project work - - 4

2 GMRP22005 Project Work - - 20

*Tutorial

M.Tech I Year I Semester(Computer Science & Engineering) A Y 2013-14

Course Title: DATA STRUCTURES AND ALGORITHMS Course Code : CSEP1 1401

L T P C

3 1 0 4

Objectives:

At the end of the course students are expected to:

This course couples work on program design, analysis, and verification with an introduction to the study of data structures. Data structures capture common ways to store and manipulate data, and they are important in the construction of sophisticated computer programs.

It improves the expected performance of a new data structure technique using randomization technique and to impart knowledge to students on Hashing.

It deals with a data structure technique operations applied to elements are based on its priority and also analyzed the methods of external sorting.

It starts with non-linear data structure and it provides knowledge to develop the tree structures

suitable for the representation of a dictionary and also developed the balanced search tree structure to provide better worst-case performance.

Developed more on balanced search tree structure to provide improved performance. Finding all occurrences of a pattern in a text is a problem that arises frequently in text editing programs

like document being edited or searching a particular pattern/word/string given by the user.

Outcomes:

At the end of this course student should be able to write large, reliable programs composed from reusable pieces, students can also develop modular programs on data structures and algorithms that are easy to read, debug, verify, analyze, and modify using C/C++ language.

At the end of this course student should be able to perform basic analysis of algorithms, understand how various data structures and algorithms, be able to implement them in a high-level language, and be able to pick an appropriate data structure or algorithm for a given task.

Unit I:Introduction to data structures, singly linked lists, doubly linked lists, circular list - Algorithms.Stacks and queues: Algorithms implementation using linked list. Algorithms - performance analysis -time complexity and space complexity.Searching-Linear and Binary search methods, Sorting- Bubble sort,Selection sort, Insertion sort, Quick sort and Merge sort.Unit II:Trees - Binary tress, properties, representation and traversals (DFT, BFT) expression trees (infix, prefix, postfix). Graphs - basic concepts, storage structures and traversals.Dictionaries, ADT, The list ADT, Stack ADT, Queue ADT, hash table representation, hash functions collision resolution - separate chaining, open addressing - linear probing, double hashing.

Unit III:Priority Queues - Definition, ADT, Realizing a Priority Queue using Heaps, Definition, insertion, Deletion. External Sorting - Model for external sorting, Multiway merge.Search Trees: Binary Search Trees, Definition, ADT, Implementation, Operations – Searching, Insertion and Deletion.

Unit IV:Search Trees: AVL Trees, Definition, Height of an AVL Tree, Operations – Insertion, Deletion and Searching.Search Trees: Introduction to Red - Black and Splay Trees, B - Trees, height of a B - Tree, insertion, deletion and searching, Comparison of Search Trees.

Text Books:1. Data Structures: A Pseudocode Approach, 2/e, Richard F. GilbergBehrouz A. Forouzan, Cengage.2. Data Structures, Algorithms and Applications in C++, 2/e, SartajSahni, University Press.

Reference Books:1. Data structures and Algorithm Analysis, 2/e, Mark Allen Weiss, Pearson.2. Data structures and Algorithms, 3/e, Adam Drozdek, Cenage.3. C and Data Structures: A Snap Shot Oriented Treatise Using Live Engineering Examples, N.B.

Venkateswarlu, E.V. Prasad, S Chand & Co, 2009.4. Data Structures, Algorithms and OOP, Heileman, TMH.5. Introductions to Algorithms, 2/e, Cormen, PHI, 2001.6. Fundamentals of Computer Algorithms, 2/e, Horowitz Sahni, Rajasekaran, University Press.

7. Design and Analysis, Dave, Dave Pearson,2008.8. Design and Analysis Algorithms, Panneerselvam , PHI, 2007.9. Data Structures, Seymour Lipschutz, Schaum's outlines, TMH.


Course Title: DATABASE MANAGEMENT SYSTEMS Course Code : CSEP1 1402

L T P C

3 1 0 4

OBJECTIVES:

Understand the differences between File system and DBMS, Data Models and database system

structure.

Learn how to use the integrity constraints over the relations and know the expressive power of Algebra

and calculus.

Learn the query language features which are the core of SQL’s DML, Join operations and Triggers.

Students know the concept of the transaction management which is the foundation for concurrent

execution and recovery from the system failure in a DBMS.

Learn the recovery techniques for managing the database effectively and avoid the data loss.

Know how to arrange the records in a file when the file is stored on the external storage.

OUTCOMES:

Apply normalization process on existing database for eliminating redundancy.

Carryout initial database design for large enterprises by learning feature of ER-Models.

Apply the recovery techniques for managing the database effectively and avoid the data loss .

Design database for large enterprises by learning eliminate redundancy by using the features of Normal

Forms.

Develop efficient database management systems.

Unit I:INTRODUCTION - Basics of database systems, Traditional file oriented approach, Motivation fordatabase approach, Evolution of database systems, Database basics, Views of data,Three level architecture of DBMS, Relational database systems, Data models,Database languages, Client-server and multi-tier architectures, Multimedia data,Information integration, Data-definition language commands, Overview of queryprocessing, Storage and buffer management, Transaction processing, The queryprocessor.Use Of SQL, DDL Statements, DML Statements, View Definitions, Constraints andTriggers Keys and Foreign Keys, Constraints on Attributes and Tuples, Modificationof Constraints, Cursors, Dynamic SQL.DATA MODELS - Data Model, Introduction of entity Relationship model, Elements of the E/R Model, Requirement, Relationship, Entity-Relationship Diagrams, Multiplicity of BinaryE/R Relationships, Design Principles, Avoiding Redundancy, Simplicity Counts,Extended ER Models.

RELATIONAL MODEL - The Relational Data Model: Basics of the Relational Model, Relation Instances,Functional Dependencies, Rules about Functional Dependencies, Design ofRelational Database Schemas.Unit II:REPRESENTING DATA ELEMENTS - Data Elements and Fields, Representing Relational Database Elements, Records,Representing Block and Record Addresses, Client-Server Systems, Logical andStructured Addresses, Record Modifications, Index Structures, Indexes onSequential Files, Secondary Indexes, B-Trees, Hash Tables.RELATIONAL ALGEBRA - Relational Algebra: Basics of Relational Algebra, Set Operations on Relations,Extended Operators of Relational Algebra, Constraints on Relations, Modification ofthe Database, Views Relational Calculus, Tuple Relational Calculus, DomainRelational Calculus.NORMALIZATION - Normalization, First Normal form, Second Normal Form, Third Normal Form,BCNF, Multi-valued dependency, Fifth Normal Form.Unit III:QUERY EXECUTION - Introduction to Physical-Query-Plan Operators, One-Pass Algorithms for DatabaseOperations, Nested-Loop Joins, Two-Pass Algorithms Based on Sorting, Two-PassAlgorithms Based on Hashing, Index-Based Algorithms, Buffer Management,Parallel Algorithms for Relational Operations, Using Heuristics in QueryOptimization, Basic Algorithms for Executing Query Operations.CONCURRENCY CONTROL - Serializability, Enforcing Serializability by Locks, Locking Systems With SeveralLock Modes, Architecture for a Locking Scheduler Managing Hierarchies ofDatabase Elements, Concurrency Control by Timestamps, Concurrency Control byValidation.UnitIV:TRANSACTION MANAGEMENT - Introduction of Transaction management, Serializability and Recoverability, ViewSerializability, Resolving Deadlocks, Distributed Databases, Distributed Commit,Distributed Locking.DATABASE SYSTEM ARCHITECTURE - Centralized and Client-Server Architectures, Server System Architectures, Parallel Systems, Distributed Systems, Network Types.DISTRIBUTED DATABASE - Homogeneous And Heterogeneous Database, Distributed Data Storage, DistributedTransaction, Commit Protocols, Concurrency Control In Distributed Databases,Availability, Heterogeneous.Text Books:-1) Raghu Ramakrishnan/Johannes Gehrke,Database Management Systems,Tata McGraw Hill.2) Silber Schatz. Korth,Database System Concepts, Tata McGraw Hill.Reference Books:-1) Introduction to Database Systems, 8/e, C.J.Date, Pearson.2) Database System design, Implementation, and Mangement, 5/e, Rob, Coronel, Thomson.3) ShamKanth B. Navathe, Fundamental of DataBase System, PearsonEducation.

M.Tech I Year I Semester(Computer Science & Engineering)A Y 2013-14

Course Title: OPERATING SYSTEMS Course Code: CSEP1 1403

L T P C

3 1 0 4

OBJECTIVES:

• Understand functions, objectives services of Operating Systems

• Learn the concepts of the process and threads

• Provides a broad understanding of issues related to concurrency

• Focus on principles of deadlock and related problems of starvation

• Provides an overview of the mechanisms used in memory management

• Understand about design issues related to processor scheduling

• Understand Distributed Operating Systems to some extent

OUTCOMES:

• Analyze the differences between process and threads

• Able to Implement concurrency mechanisms

• Implement Bankers Algorithms to handle deadlocks

• Design and Analyze mechanisms used in memory management

• Develop processor scheduling, Paging technique Algorithms

Unit I:Introduction to Operating Systems - System components ,Evaluation of OS -Simple Batch Processing, Multiprogrammed, Time-shared, Personal computer, Parallel and Distributed Systems, OS Objectives and functions , Virtual machines.Overview - Introduction, design approaches, why advanced operating systems, types of advanced operating systems.Distributed Systems – Hardware and Software concepts, Architectures of Distributed Systems -System Architecture types, issues in distributed operating systems.

Unit II: REAL TIME OPERATING SYSTEM - Task & Task States – Tasks & Data – Semaphores & Shared Data –Operating System Services – Message Queues – Timer Functions – Event Memory Management – Interrupt Routines & RTOS Environment – Basic design Using RTOS.Process description and control - process states, process description, process control , CPU Scheduling - Scheduling criteria, Types of processor scheduling and Scheduling algorithms, Multiple-processor Scheduling , Process and Threads- Multi threading ,ULTS and KLTS.

Unit III: Memory Management and Virtual Memory- Logical Vs Physical address space, Swapping, Contiguous allocation, Paging, Segmentation, Segmentation with paging, Demand paging, Performance of demand paging, Page Replacement algorithms.Process management and Synchronization - The Critical Section problem, Synchronization Hardware, Semaphores and Classical problem of Synchronization, Critical regions, Monitors.message passing ,Readers / Writers problem. Synchronization in Solaris.Unit IV: I/O management and disk scheduling – I/O devices, organization of I/O functions; I/O buffering, disk scheduling, Disk cache, File management – organization, directories, file sharing, record blocking, secondary storage management; case studies-LINUX I/O. SHARED MEMORY AND FILE SYSTEMS Shared memory : Consistency models – Page based distributed shared memory – Shared variables – Object based distributed shared memory; Distributed shared memory: Architecture–algorithms for implementing DSM–memory coherence.

Text Books:1) William Stallings, “Operating Systems – internals and design principles ”, Prentice Hall India, 5thEdition, 2005.

2) Andrew S Tanenbaum , “ Distributed Operating Systems “ , Pearson Education India,

Reference Books:1) Operating Systems Concepts, 5/e, Abraham Silberschatz, Galvin, John Wiley & Sons Inc.2) MukeshSinghal, Niranjan G Shivratri , “ Advanced Concepts in Operating Systems”, McGraw Hill International, 1994.

3) Operating Systems, 2/e, Dhamdhere, TMH

M.Tech I Year I Semester(Computer Science & Engineering)A Y 2013-14

Course Title:ADVANCED OPTIMIZATION TECHNIQUES Course Code:MEP1 1401 L T P C

3 1 0 4

Objectives:

This course is designed for first year M.Tech students. The course is intended to make the students understand

the basic concepts and advanced concepts of optimization techniques.

The main objective of the course is to:

Develop systematic approach to handle problems to design of electrical circuit etc; with a goal of

maximizing the profit and minimizing cost.

Understand the various optimization techniques such as classified optimization,linear programming.

One dimensional minimization methods,unconstrained optimization techniques, constrained

optimization techniques and dynamic programming.

Understand the necessary sufficient conditions for finding the solution of the problems in classical

optimization.

Comprehend the numerical methods for finding approximate solution of complicated problems.

Apply methods like north west corner rule, least count method etc. to solve the transportation problem.

OUTCOMES:

Design of mechanical systems and interdisciplinary engineering applications and business solutions

using suitable optimization technique.

Apply numerical or iterative techniques in power systems for optimal power flow solutions.

Optimize the parameters in control systems for desired steady state or transient response.

Optimize the cost function in deciding economic factors of power systems.

Design of electrical systems optimally using suitable techniques like univariate method,steepest

descent method etc.

UNIT – I:Linear programming-Two-phase simplex method, Big-M method, duality, interpretation,

applications.

Assignment problem- Hungarian’s algorithm, Degeneracy, applications, unbalanced problems, traveling

salesman problem.

UNIT – II:Classical optimization techniques-Single variable optimization with and without constraints, multi – variable

optimization without constraints, multi – variable optimization with constraints – method of Lagrange

multipliers, Kuhn-Tucker conditions.

Numerical methods for optimization-Nelder Mead’s Simplex search method, Gradient of a function,

Steepest descent method, Newton’s method, types of penalty methods for handling constraints.

UNIT –III:Genetic algorithm (GA) -Differences and similarities between conventional and evolutionary algorithms,

working principle, reproduction, crossover, mutation, termination criteria, different reproduction and

crossover operators, GA for constrained optimization, draw backs of GA.

Genetic Programming (GP)-Principles of genetic programming, terminal sets, functional sets, differences

between GA & GP, random population generation, solving differential equations using GP.

UNIT – IV:Multi-Objective GA-Pareto’s analysis, Non-dominated front, multi – objective GA, Nondominated sorted

GA, convergence criterion, applications of multi-objective problems .

Basic Problem solving using Genetic algorithm, Genetic Programming & Multi Objective GA and simple

applications of optimization for engineering systems.

Text Books:1. Optimal design – JasbirArora, McGraw Hill (International) Publishers2. Optimization for Engineering Design – Kalyanmoy Deb, PHI Publishers3. Engineering Optimization – S.S.Rao, New Age Publishers- 18 - Approved by BOS on 25th July 2009References:1.Genetic algorithms in Search, Optimization, and Machine learning , D.E.Goldberg, Addison-Wesley

Publishers

2. Genetic Programming- Koza

3. Multi objective Genetic algorithms - Kalyanmoy Deb, PHI Publishers


Course Title: COMPUTER ORGANIZATION AND ARCHITECTURE (Elective 1) Course Code: CSEP1 1404

L T P C

3 1 0 4

Objectives:This course is designed for first year M.Tech students. The course is intended to make the students understand the basic concepts of number system and computer arithmetic, Analysis and design of sequential circuits using several types of flip flops, Analyze Intel 8086 instruction format and CPU architecture, Input-Output organization.The main objective of the course is to:

Understand the various binary systems representing information in digital system. Analysis and design of combinational and sequential circuits using several types of flip flops

with minimum number of logic gates. Understand the concept of memory structures of shift registers Understand the different arithmetic operations that are involved in different hardware component in

ALU. Acquire knowledge of basic cache memory with basic organizational techniques and performance

tuning and Input-output organization. Understand Intel 8086 CPU architecture, Assembly language Instructions and programming.

Outcomes: Apply knowledge of number systems, codes and Boolean algebra to the analysis and design of digital

logic circuits Use flip-flops in designing sequential logic circuits and counters for digital circuits Design a digital system, components or process to meet desired needs within realistic constraints by

forming multi-disciplinary teams. Evaluate quality of modern computing systems Assess functionality of their components, design of instruction sets and their underlying execution. Analyze the performance of computer systems and know how to improve their efficiency (pipelining,

caches, etc).

Apply cache design to solve performance problems in other aspects of computer design. Design an I/O subsystem supporting processor programmed I/O, direct memory access, interrupt

structures, and industry standards. Understand the full internal workings of a typical simple CPU including the utilization of the various

hardware resources during the execution of instructions. Introduce the design of basic I/O hardware and microprocessor interfacing: memory chip selection,

memory expansion, I/O interfacing, different I/O techniques: interrupts, DMA.

Unit I:Number Systems and Computer Arithmetic-Signed and unsigned numbers Addition & subtraction,

multiplication division, Floating point representation logical operation, Gray code, BCD codes, Error

detecting codes. Boolean algebra ,Simplification of Boolean expressions - Maps.

Combinational and Sequential Circuits- Decoders, Encoders, Multiplexers, Half and Full adders ,shift

registers, flip-flops, binary counters, memory Unit.

Unit II:Memory Organization-Memory hierarchy , Main memory, Auxiliary Memory, Associative Memory, Cache

Memory, Virtual Memory Concept.

Intel 8086 CPU Architecture- Diagram, code and segment registers, internal operations , machine language

instructions (addressing modes, instruction formats), Instruction execution timing.

Unit III:Intel 8086 Assembly Language Instructions- Data transfer instructions - input output instructions, address

transfer Flags, arithmetic, logical shift and rotate instructions.

Intel 8086 Assembly Language Programming-Conditional and unconditional transfer, iteration control,

interrupts and process control instructions assembler directives Programming with assembly language

instructions.

Unit IV:

ALU Design- Addition and subtraction sign and unsigned numbers, multiplication and division algorithms,

BCD Adders.

Input-Output Organization- Peripheral devices, input-output interface, Asynchronous data transfer, Modes

of transfer , priority interrupts, DMA, Input output processor, Serial communication.

Text Books:1. Computer System Architecture, 3/e, Moris Mono, Pearson / PHI.2. Microprocessor and interfacing ,2/e, Douglas V. Hall, TMH.

Reference Books:1. Digital Logic and computer organization, Rajaraman, Radha Krishnan, PHI.2. Microcomputer systems: 8086/8088 family, 2/e, Liu, Gibson, PHI3. Computer Organization and Architecture, 7/e, stallings, pearson4. Computer Organization, 5/e, Hamacher, Vranesic, TMH5. Computer systems organization and architecture, carpinellipearson6. Computer organization and Design, pal chowdary, PHI7. Computer system organization, jotwani, TMH

M.Tech I Year I Semester(Computer Science & Engineering)

A Y 2013-14 Course Code:CSEP1 1405

Coursr Title: CRYPTOGRAPHY AND NETWORK SECURITY (Elective – 1 ) L T P C

3 1 0 4

Objectives:

Understand about various Conventional Encryption Principles designed for providing security.

Learn public key cryptography, key management principles and Learn Pretty Good Privacy (PGP) which is a computer program that provides cryptographic privacy and authentication.

Learn IP Security fundamentals, architecture and identifying the key features IP security system.

Describes how to achieve data confidentiality, data integrity, data authentication and authentication for participants during data transit

Identify and evaluate current and emerging technologies in security and assess their applicability to address the users’ needs and recognize the need for continued learning throughout their career.

Outcomes:

Know the information security priorities and information assets Design information security strategy and the architecture. Identify and prioritize threats to information assets. Understand of professional, ethical, legal, security and social issues and responsibilities. Apply current techniques, skills, and tools necessary for providing data and network security.

UNIT I:Introduction -Attacks, Services and Mechanisms, Security attacks, Security services, A Model for Inter-network security, Session Hijacking and Spoofing, Buffer overflow.Cryptography - Symmetric Cipher Model, Substitution Techniques, Confusion, Diffusion Steganography, Water mark security, Classical Encryption Techniques.Secret Key Cryptography -Simplified DES, Block Cipher principles, Data Encryption standard, Strength of DES, Differential and Linear Cryptanalysis, Block Cipher Design, Principles and Modes of operation, Algorithms: Triples DES, International Data Encryption algorithm, Blowfish, RC5, CAST-128, Characteristics of Advanced Symmetric block ciphers.

UNIT II:Number Theory-Prime and Relatively prime numbers, Modular arithmetic, Fermat’s and Euler’s Theorems, Testing for primarily, Euclid’s Algorithm, the Chinese remainder theorem, Discrete logarithms.Public Key Cryptography-Principles, RSA Algorithm, Key Management, Diffie-Hellman Key exchange, Elliptic Curve Cryptography.Message Authentication and Hash Functions- Authentication requirements and functions, Message Authentication, Hash functions, Security of Hash functions and MACs.Hash and MAC algorithms-MD file, Message digests Algorithm, Secure Hash Algorithm, RIPEMD-160, HMAC.UNIT III:Digital Signatures and Authentication Protocols- Digital signatures, Authentication protocols, Digital signature Standards, Digital signature through Elliptic curve cryptosystem.Authentication Applications -Kerberos, X.509 directory Authentication Service.Electronic Mail Security: Pretty Good Privacy, S/MIME.UNIT IV:IP Security -Overview, Architecture, Authentication, Encapsulating Security Payload, Combining security Associations, Key Management.Web Security: Web Security requirements, Secure sockets layer and Transport layer security, Secure Electronic Transaction.Intruders, Viruses and Worms-Intruders, Viruses, Worms, Bacterias.Fire Walls: Fire wall Design Principles, Trusted systems.TEXT BOOKS1. William Stallings,Cryptography and Network Security: Principles and Practice, 5th Edition, William

Stallings, Pearson Education, 2011.2. Cryptography and Network Security, Behrouz A. Forouzan and DebdeepMukhopadhay, Tata

McGraw-Hill, 2010.REFERENCE BOOKS1. Eric Maiwald ,Fundamentals of Network Security (Dreamtech press)2. Charlie Kaufman, Radia Perlman and Mike Speciner,Network Security – Private Communication in a

Public World, Pearson/PHI.3. Whitman, Principles of Information Security, Thomson.4. Robert Bragg,Network Security The Complete reference, Mark Rhodes, TMHBuchmann,Introduction

to Cryptography, Springer.5. Applied Cryptography, 2nd edition, Bruce Schneier.

M.Tech I Year I Semester(Computer Science & Engineering) A Y 2013-14 Course Code:CSEP1 1406

Course Title: INFORMATION RETRIEVAL SYSTEMS (Elective 1) L T P C

3 1 0 4

Objectives:This course is concerned with the extraction of relevant information from large collections of documents. It has applications to proprietary retrieval systems. This course will aim to provide students with an overview of the main principles and methods underlying the domain of Information Retrieval.

Introduce the information system capabilities, Cataloging and indexing.

This course also provides to learn document and term clustering.

It deals with various information system evolution and multimedia information retrieval.

Outcomes: Students are able to understand overview of the main principles and methods underlying the domain of

information retrieval.

Students are able to know cluster the documents of the real world data.

Understand more recent developments in IR such as collaborative filtering and Latent Semantic Indexing.

After complete this course students are able to make construction of information retrieval will furthermore acquire practical experience in the construction of IR systems by a series of projects.

UNIT I:Introduction-Definition, Objectives, Functional Overview, Relationship to DBMS, Digital libraries and Data Warehouses.Information Retrieval System Capabilities - Search, Browse, Miscellaneous.Cataloging and Indexing: Objectives, Indexing Process, Automatic Indexing, Information Extraction.UNIT II:Data Structures- Introduction, Stemming Algorithms, Inverted file structures, N-gram data structure, PAT data structure, Signature file structure, Hypertext data structure.Automatic Indexing- Classes of automatic indexing, Statistical indexing, Natural language, Concept indexing, Hypertext linkages.UNIT III:Document and Term Clustering- Introduction, Thesaurus generation, Item clustering, Hierarchy of clusters .User Search Techniques- Search statements and binding, Similarity measures and ranking, Relevance feedback, Selective dissemination of information search, Weighted searches of Boolean systems, Searching the Internet and hypertext.UNIT-IV:Information Visualization- Introduction, Cognition and perception, Information visualization technologies.Text Search Algorithms- Introduction, Software text search algorithms, Hardware text search systems.Information System Evaluation- Introduction, Measures used in system evaluation, Measurement example –TREC results.Multimedia Information Retrieval – Models and Languages – Data Modeling, Query Languages, Indexing and Searching - Libraries and Bibliographical Systems – Online IR Systems, OPACs, Digital Libraries.

TEXT BOOKS:1. Information Storage and Retrieval Systems: Theory and Implementation By Kowalski, Gerald, Mark T

Maybury Kluwer Academic Press, 2000.2. Modern Information RetrievalBy Ricardo Baeza-Yates, Pearson Education, 2007.3. Information Retrieval: Algorithms and Heuristics By David A Grossman and OphirFrieder, 2nd Edition,

Springer International Edition, 2004.

REFERENCE BOOKS:1. Information Retrieval Data Structures and Algorithms By William B Frakes, Ricardo Baeza-Yates, Pearson

Education, 1992.2. Information Storage &RetievalBy Robert Korfhage – John Wiley & Sons.3. Introduction to Information Retrieval By Christopher D. Manning and PrabhakarRaghavan, Cambridge

University Press, 2008


Course Code: CSEP1 1407

Course Title: BIO-INFORMATICS (Elective 2) L T P C

3 1 0 4

Objectives:• Understand the functions, objectives of Molecular Biology and Bio-Informatics• Learn the concepts of the structure of Genes & DNA and their Visualization• Understand the structural prediction, comparison and classification of proteins• Focus on principles of Searching from Databases• Utilize and understand statistical methods for the analysis of large datasets where appropriate• Understand about the Pattern Matching Concepts• Understand the various mathematical and statistical models of gene regulatory network• Understand the simulation and Modeling of Drug Design using various Algorithms

Outcomes:• Understand electronic storage and sharing of biological information• Able to Implement Search strategies from Biological Databases• Get knowledge of laboratory technologies used in biology to generate large datasets• Design effective data representations for the storage and manipulation of large datasets where needed• Able to generate virtual gene expression data with statistical and biological plausibility

UNIT I:Introduction - The Central Dogma, The Killer Application, Parallel Universes,Watson’s Definition, Top-Down Versus Bottom-up, Information Flow, Convergence Databases, Data Management,Data Life cycle,DatabaseTechnology,Interfaces, Implementation.Molecular Biology Primer - Genes, Molecules, Structure of DNA, Proteins Analysis.UNIT II:Searching Biological Data From databases - Finding the information stored and its retrieval methods at NCBI, EMBL and DDBJ, Protein Data Bank(PDB), NDB, CCSD, PIR, Swiss Prot, EMBL, Pfam, EST, SNP, Metabolic pathways databases, EMP, KEGG, MetaCyc, structural databases: SCOP, CATH ,Retrieving microbial and viral genome informationData Visualization - Data Visualization , sequence visualization, structure visualization, user Interface, Animation Versus simulation, General Purpose Technologies.UNIT III:Statistics - Statistical concepts, Microarrays, Imperfect Data, Randomness, Variability, Approximation, Interface Noise, Assumptions, Sampling and Distributions, Hypothesis Testing, Quantifying Randomness, Data Analysis, Tool selection statistics of AlignmentData Mining - Clustering and Classification, Data Mining, Methods, Selection and Sampling, Preprocessing and Cleaning, Transformation and Reduction, Data Mining Methods, Evaluation, Visualization, Designing new queries, Pattern Recognition and Discovery, Machine Learning, Text Mining, Tools.UNIT IV:Pattern Matching - Pairwise sequence alignment, Local versus global alignment, Multiple sequence alignment, Computational methods, Dot Matrix analysis, Substitution matrices, Dynamic Programming, Word methods, Bayesian methods, Multiple sequence alignment, Dynamic Programming, Progressive strategies, Iterative strategies, Tools, Nucleotide Pattern Matching, Polypeptide pattern matching, Utilities, Sequence Databases. Modeling and Simulation - Drug Discovery, components, process, Perspectives, Numeric considerations, Algorithms, Hardware, Issues, Protein structure, AbInitio Methods, Heuristic methods, Systems Biology, Tools, Collaboration and Communications, standards, Issues, Security, Intellectual property. TEXT BOOKS 1. Bio Informatics Computing, Bryan Bergeron, PHI, 2003. 2. Bio Informatics - Managing Scientific Data, Lacroix, Terence Critchlow, Elsevier.

REFERENCE BOOKS 1. Introduction to Bio Informatics, Attwood, Smith, Longman, 1999. 2. Bio-Informatics, D Srinivasa Rao, Biotech. 3. Bio-Informatics- Methods and Applications, Rastogi, Mendiratta, Rastogi, PHI4. Baxevanis AS and Ouellette BF, Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins,

Wiley International Science


Course Code:CSEP1 1408

Course Title :EMBEDDED SYSTEMS (Elective-2) L T P C

3 1 0 4

Objectives: Students will understand about embedded computing and study the internal architecture of 8051 micro

controller. To learn programming on 8051 micro controller using various tools. Understand how to interface i/o devices ,A/D and D/A conversions. Introduction about real time

operating system. Learn various design concepts of real time operating system like semaphores, queues ,scheduling..etc.

Outcomes: An understanding of embedded computing and internal architecture of 8081 micro controller. Students able to do programming in 8051 using tools. Demonstrate the interfacing of various i/o ,A/d and D/A devices with 8051 micro controller. Develop various algorithms for real time operating system scheduling , semaphores..etc.

Unit I:

Embedded Computing - Introduction, Complex Systems and Microprocessor, The Embedded System Design Process, Formalisms for System Design, Design Examples. The 8051 Architecture - Introduction, 8051 Micro controller Hardware, Input/Output Ports and Circuits, External Memory, Counter and Timers, Serial data Input/Output, Interrupts.

Unit II:Basic Assembly Language Programming Concepts - The Assembly Language Programming Process, Programming Tools and Techniques, Programming the 8051. Data Transfer and Logical Instructions.Arithmetic Operations, Decimal Arithmetic.Jump and Call Instructions, Further Details on Interrupts. Unit III :Applications -Interfacing with Keyboards, Displays, D/A and A/D Conversions, Multiple Interrupts, Serial Data Communication.Introduction to Real – Time Operating Systems - Tasks and Task States, Tasks and Data, Semaphores, and Shared Data; Message Queues, Mailboxes and Pipes, Timer Functions, Events, Memory Management,Interrupt Routines in an RTOS Environment.Unit IV:Basic Design Using a Real-Time Operating System - Principles, Semaphores and Queues, Hard Real-Time Scheduling Considerations, Saving Memory and Power, An example RTOS like uC-OS (Open Source); Embedded Software Development Tools: Host and Target machines, Linker/Locators for Embedded Software, Getting Embedded Software into the Target System; Debugging Techniques: Testing on Host Machine, Using Laboratory Tools, An Example System. Introduction to advanced architectures - ARM and SHARC, Processor and memory organization and Instruction level parallelism; Networked embedded systems: Bus protocols, I2C bus and CAN bus; Internet-Enabled Systems, Design Example-Elevator Controller.

TEXT BOOKS :1. Computers as Components-principles of Embedded computer system design, Wayne Wolf, Elseveir.2. The 8051 Microcontroller, Third Edition, Kenneth J.Ayala, Thomson.

REFERENCES :1. Embedding system building blocks, Labrosse, via CMP publishers.2. Embedded Systems, Raj Kamal, TMH.3. Micro Controllers, Ajay V Deshmukhi, TMH.4. Embedded System Design, Frank Vahid, Tony Givargis, John Wiley.5. Microcontrollers, Raj kamal, Pearson Education.6. An Embedded Software Primer, David E. Simon, Pearson Education.



Course Title:OBJECT ORIENTED SOFTWARE ENGINEERING (Elective 2) L T P C

3 1 0 4

Objectives: Understand about process models and learn to know how to specify software requirements.

Learn how to perform feasibility study of the projects under the requirement engineering process and

system models.

Students can learn design and implementation of software and the management of the software project

development.

Deriving the use cases from requirements.

Outcomes: An understanding of the object oriented methodology and how it is applicable in the design and

implementation of software and the management of the software project.

He is able to use UML, an object oriented design tool, in the realization of a given software

engineering project.

Design real world projects to make success of the project.

Develop sketch out an idea on a blackboard or a scrap of paper in order to visualize a part of a system.

Design and develop real-time software projects with effective cost estimation and plan

Unit I:Introduction to Classical software Engineering - Historical, Economic and Maintenance aspects.

introduction to Object Oriented Paradigm.Different phases in structured paradigm and Objective Oriented

Paradigm. Software Process and different life cycle models and corresponding strengths and weaknesses.

Planning and Estimation -Estimation of Duration and Cost , COCOMO components of software. Project

Management plan, one case Study.

Unit II :Tools for step wise refinement - Cost - Benefit analysis, Introduction to software metrics and CASE

tools.Taxonomy and scope of CASE tools.Introduction to testing, with focus on Utility, Reliability,

Robustness, Performance, Correctness.

Modules to objects -Cohesion and Coupling, Data Encapsulation and Information hiding aspects of Objects.

Inheritance, polymorphism and Dynamic Binding aspects.Cohesion and coupling of objects.Reusability,

Portability and Interoperability aspects.

Unit III:Requirement phase - Rapid Prototyping method, Specification phase , Specification Document, Formal

methods of developing specification document, Examples of other semi - formal methods of using Finite-

State- Machines, Petri nets.

Analysis phase -Use case Modeling, Class Modeling, Dynamic Modeling.

Unit IV:Design phase -Data oriented design, Object Oriented design, Formal techniques for detailed design. One case study.IIM Phases - Implementation, Integration and maintenance phases.

TEXT BOOKS1. Object oriented and Classical Software Engineering, 7/e, Stephen R. Schach, TMH 2. Object oriented and classical software Engineering, Timothy Lethbridge, Robert Laganiere, TMH

REFERENCEBOOKS 1.Component-based softwareengineering:7thinternational symposium, CBSE 2004, IvicaCrnkovic, Springer



CourserTitle:DATA STRUCTURES AND ALGORITHMSLABORATORY T P C

0 3 2

Objectives:At the end of the course students are expected to:

The main objective of this course is to enable the student to implement programs of DS using the concepts of C language. To implement various data structures that applied to solve the problems of real world in an efficient manner.

The learning objectives of the course are given as follows:

To be able to implement the fundamental concepts of DS like stack, queue, linked list etc. To implement the concepts of avl trees, b+ trees. To implement concepts of hashing techniques. To apply the concepts of searching and sortingOutcomes: At the end of this course, the students will demonstrate the knowledge of various concepts in DS Programming. They are capable of developing programs of for various applications. They also will have the sound knowledge of data structures and their application in the real world. They will be able to apply this knowledge in solving any problem by developing programs of better efficiency in terms of time complexity and length. Learning outcomes can be assessed through their performance in mid-term examinations and end-semester examinations. Also assignments can be given at the end of each unit from the important questions appearing in university question papers.

1. Perform various operations by using singly linked list, doubly linked list and circular linked list.2. Implement Bubble sort, selection sort, Insertion sort, Quick sort, and merge sort.3. Create a binary tree, perform insertion and deletion operations.4. Perform Infix and postfix operations by using binary search tree.5. To implement operations on graphs

a) vertex insertion

b) Vertex deletion

c) finding vertex

d)Edge addition and deletion

6. Implement Depth First Search(DFS) for a graph nonrecursively. 7. Implement Breadth First Search(BFS) for a graph non recursively.8. Implement functions of Dictionary using Hashing .9. Perform various operations i.e., insertions and deletions on AVL trees.10. Perform various operations i.e., insertions and deletions on B-Tree.



Course Title:DATA WAREHOUSING AND DATA MINING L T P C

3 1 0 4

Objectives:

Understand the role of data warehouse as information repository.

Learn different kind of information and statistics of the data by using various operations such as roll-

up, roll-down, drill-up, drill-down, etc.

Learn how to extract the hidden knowledge from the data warehouse or repository for decision making

by

using one or more of the data mining tasks such as Data characterization, Association rule mining,

Classification and Clustering.

Study the characterization and describing data by generalization, summarization and comparison of

thegiven data.

Establish association between different data groups by discovering frequent patterns.

Design a classifier model, first to learn from the given dataset and then to classify the given data into

one of the specified classes.

Use one of the many clustering algorithms that the students learn to classify/group the data into

unspecified number of classes and also to detect outliers for the applications such as fraud detection,

etc.

Scale the existing data mining algorithms or to design new algorithms for mining of large and ever

growing databases.

Outcomes:

Demonstrate the knowledge of warehouse and information repository.

Develop various extraction of knowledge form the data repository.

Develop market basket analysis methods for market analysis

Implement projects using data mining tools to consult corporate industries

UNIT I :Data Warehouse and OLAP - Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture, Data Warehouse Implementation, Further Development of Data Cube Technology, From Data Warehousing to Data Mining. Fundamentals of Data Mining, Data Mining Functionalities - Classification of Data Mining systems, Major issues in Data Mining.Data Preprocessing: Needs Preprocessing the Data, Data Cleaning, Data Integration and Transformation, Data Reduction, Discretization and Concept Hierarchy Generation.

UNIT II: Measures of similarity and dissimilarity - Basics, Similarity and Dissimilarity between Simple Attributes, Dissimilarities between Data objects, Similarities between Data objects, Examples of proximity measures, Issues in proximity Calculations, selection the right proximity Measure.

Concepts Description , Characterization and Comparison - Data Generalization and Summarization- Based Characterization, Analytical Characterization: Analysis of Attribute Relevance, Mining Class Comparisons: Discriminating between Different Classes, Mining Descriptive Statistical Measures in Large Databases.

UNIT III :Mining Association Rules in Large Databases - Association Rule Mining, Mining Single-Dimensional Boolean Association Rules from Transactional Databases, Mining Multilevel Association Rules from Transaction Databases, Mining Multidimensional Association Rules from Relational Databases and Data Warehouses, From Association Mining to Correlation Analysis, Constraint-Based Association Mining. Classification - Preliminaries, General approach to solving a classification problem, Decision tree induction, Rule-based classifier, Nearest-Neighbor classifiers, Bayesian classifiers,Artificial Neural Network.

UNIT IV: Cluster Analysis - Overview, K-means, Agglomerative Hierarchical Clustering, DBSCAN, Prototype-based clustering, Cluster Evaluation. Mining Complex Types of Data - Multidimensional Analysis and Descriptive Mining of Complex, Data Objects, Mining Spatial Databases, Mining Multimedia Databases, Mining Time-Series and Sequence Data, Mining Text Databases, Mining the World Wide Web.

TEXT BOOKS :1. Data Mining,Concepts and Techniques , Jiawei Han &MichelineKamber Harcourt India.2. Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson Education.

REFERENCE BOOKS :1. Data Mining Introductory and advanced topics, Margaret H Dunham, Pearson Education.2. Data Mining Techniques, Arun K Pujari, University Press.


Course Code:CSEP1 1412 Course Title: MOBILE COMPUTING L T P C

3 1 0 4

OBJECTIVES

Understand various technologies & applications in wireless and mobile environments and to learn in

detail about GSM.

Learn various medium access schemes (MAC) viz. SDMA, FDMA, TDMA and CDMA.

Get knowledge about Mobile IP and IP packet delivery from a fixed node to a mobile node and vice-

versa.

Understand in detail about Mobile Adhoc Networks (MANETs) and various routing algorithms used.

Learn the concepts of various data delivery mechanisms and selective tuning techniques.

Know about latest protocols and tools used in mobile environments like WAP, Bluetooth and J2ME

OUTCOMES

Demonstrate the knowledge of protocols used in mobile computing.

Gain the knowledge about the technologies in modern world like GSM, CDMA, MANETs, WAP,

Bluetooth and J2ME

Develop projects in mobile computing and also able to deliver a seminar on mobile computing

working functionality

Demonstrate various data delivery techniques through various protocols.

Demonstrate how the data is transferring through various layers of the network

Unit I:Introduction to Mobile Communications and Computing - Mobile Computing (MC): Introduction to

MC, novel applications, limitations, and architecture GSM: Mobile services, System architecture, Radio

interface, Protocols, Localization and calling, Handover, Security, and New data services.

(Wireless) Medium Access Control - Motivation for a specialized MAC (Hidden and exposed terminals,

Near and far terminals), SDMA, FDMA, TDMA, CDMA.

Unit II:Mobile Network Layer - Mobile IP (Goals, assumptions, entities and terminology, IP packet delivery, agent

advertisement and discovery, registration, tunneling and encapsulation, optimizations), Dynamic Host

Configuration Protocol (DHCP).

Mobile Transport Layer - Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Fast retransmit/fast

recovery, Transmission /time-out freezing, Selective retransmission, Transaction oriented TCP.

Unit III:Database Issues -Hoarding techniques, caching invalidation mechanisms, client server computing with

adaptation, power-aware and context-aware computing, transactional models, query processing, recovery, and

quality of service issues.

Data Dissemination - Communications asymmetry, classification of new data delivery mechanisms,

push-based mechanisms, pull-based mechanisms, hybrid mechanisms, selective tuning (indexing) techniques.

Unit IV:Mobile Ad hoc Networks (MANETs) - Overview, Properties of a MANET, spectrum of MANET

applications, routing and various routing algorithms, security in MANETs.

Protocols and Tools - Wireless Application Protocol-WAP. (Introduction, protocol architecture, and

treatment of protocols of all layers), Bluetooth (User scenarios, physical layer, MAC layer, networking,

security, link management) and J2ME.

TEXT BOOKS:

1. Mobile Communications, 2/e, Jochen Schiller, 2004, Addison-Wesley.

2. Handbook of Wireless Networks and Mobile Computing, Stojmenovic ,Cacute, Wiley, 2002.3. Adhoc Wireless Networks, 2/e, Sivarammurthy, Manoj, Pearson, 2009.REFERENCE BOOKS:1. Mobile Computing Principles: Designing and Developing Mobile Applications with UML and XML,

Reza Behravanfar, Cambridge, University Press, 2004. 2. Fundamentals of Mobile and Pervasive Computing, Adelstein, Frank, Gupta, SandeepKS. Richard

III, Golden , Schwiebert, Loren, TMH , 2005. 3. Principles of Mobile Computing, 2/e, Hansmann, Merk, Nicklous, Stober, Springer, 2003. 4. Mobile and Wireless Design Essentials, MartynMallick, Wiley DreamTech, 2003.5. Mobile Computing, Rajkamal, Oxford, 2008 .6. Adhoc Wireless Networks, 2/e, Sivarammurthy, manoj, Pearson, 2009.



Course Title:SOFT COMPUTING TECHNIQUES L T P C

3 1 0 4

Objectives:

This course is designed for first year M.Tech students. The course is intended to make the students understand

concepts about Soft Computing and its application in various field.

The main objective of the course is to:

• knowSoft Computing basics and its branches

• understand the basic implementation details onArtificial Neural Networks

• understandfuzzy logic and it application in ANN.

• introduction of Support vector machine and its application

• elaborate discussion on applications of Soft Computing

OUTCOMES:

• differentiate between Soft Computing and Hard computing.

• understand its branches Artificial Neural Networks, Fuzzy Logic, and Support Vector machine

• understandvarious applications of soft computing.

• judge less complexity by using various soft computing methods

UNIT I:Basic elements of soft Computing – Introduction to soft computing, Fuzzy logic, Neural Networks and

Evolutionary Computing, Approximations of Multivariate functions, Non – linear Error surface and

optimization.

Artificial Neural Networks- Introduction, Basic models of ANN, important terminologies, Basic Learning

Laws, Supervised Learning Networks, Perceptron Networks, Adaptive Linear Neuron,

BackpropagationNetwork.Radial basis function network and Hopfield Networks.

UNIT II :Unsupervised Learning Network- Introduction, Fixed Weight Competitive Nets, Maxnet, Hamming

Network, Kohonen Self-Organizing Feature Maps, Learning Vector Quantization, Counter Propagation

Networks, Adaptive Resonance Theory Networks. Special Networks-Introduction to various networks.

Introduction to Classical Sets and Fuzzy Sets- Crisp Sets and Fuzzy Sets- operations. Classical Relations

and Fuzzy Relations- Cardinality, Properties and composition. Tolerance and equivalence relations.

Membership functions- Features, Fuzzification, membership value assignments, Defuzzification.

UNIT-III :Fuzzy Logic-Classical& Fuzzy logic, Operations, Boolean Logic, Multivalued Logics, Fuzzy Rule Base and

Approximate Reasoning ,Fuzzy Decision making ,Fuzzy Logic Control Systems.

Genetic Algorithm- Introduction, Traditional Optimization and search techniques, Search space, Operators:

Encoding, Selection, Crossover and Mutation. Stopping Condition of GA.

UNIT IV:Support Vector Machine -Introduction, optimal hyper plane for linearly separable pattern, linear classifier,

nonlinear classifier problem, optimal plane for non-separable pattern, example XOR problem, support vector

machine for non-linear regression., summary and discussion.

Applications of Soft Computing - A fusion Approach of Multispectral Images with SAR Image for flood

area analysis, Optimization of TSP using GA Approach and GA-Fuzzy system for Control of flexible Robots.

TEXT BOOKS1. Principles of Soft Computing- S N Sivanandam, S N Deepa, Wiley India, 20112. V. Kecman, “Learning and Soft computing”, Pearson Education, India

REFERENCE BOOKS:1.Soft Computing and Intelligent System Design -Fakhreddine O Karray, Clarence D Silva,. Pearson Edition, 2004.2.Introduction to Fuzzy Systems, Guanrong Chen, Trung Tat Pham, Chapman & Hall/CRC, 2009.

3 .S. Haykins,“Neural networks: a comprehensive foundation”. Pearson Education, India..



Course Title: WEB TECHNOLOGIES L T P C

3 1 0 4

Objectives • Understand markup languages

• Understand how to integrate with PHP

• To Understand the basic web application development

• To understand how to design web applications using MVC

• Various ways to collaborate web services

Outcomes • Develop markup language and scripting language programs for web applications

• Develop advanced Java programs

• Design web applications using PHP

• Implement various challenges associated with web development

• Demonstrate different architectures and web services

UNITI:HTML - Common tags, linking, Lists, Tables, images, forms, Frames, Cascading Style sheets.Java Script - Introduction to Java Scripts, control structures, functions, objects, event handling, Dynamic HTML.UNITII:XML - Introduction, importance, Document type definition, XML Schemas, XML parsers: DOM and SAX, namespaces, Style sheets: XSL and CSS.Java Beans - Introduction to Java Beans, Advantages of Java Beans, BDK, Introspection, jar file, Bound properties, Constrained properties, Persistence, Customizer, Bean Info Interface, Java Beans API, Introduction to EJB’s.UNIT III:Web Servers and Servlets -Tomcat web server, installing Tomcat Server & Testing Tomcat, Introduction to Servlets, Lifecycle of a Servlet, The Servlet API, The javax.servlet Package, Reading Servlet parameters, Reading Initialization parameters. The javax.servlet.http package, Handling http Request & Responses, Using Cookies, Session Tracking, Security Issues.Introduction to JSP - The Problem with Servlet. The Anatomy of a JSP Page, JSP Processing. JSP Application Design with MVC, JSP elements, Directives, Using scripting elements, Implicit JSP objects.JSP Application Development: Generating Dynamic Content, The JSP 2.0 API, Action elements- standard actions and custom actions, using JSTL and custom tag libraries, EL Expressions, sharing data between JSP pages, requests and users, passing control and data between pages, Deploying JAVA Beans in a JSP Page, Error handling and debuggingUNIT IV:Database Connectivity -Introduction to JDBC, drivers, Database Programming ,java.sql and javax.sqlpackages, Accessing a Database from a JSP Page, Introduction to struts framework.PHP -Creating PHP script, running PHP script, working with variables and constants, datatypes, operators, conditional statements, arrays, functions, working with forms, database connectivity

TEXT BOOKS:1.Internet and World Wide Web – How to program, Dietel and Dietel, Pearson Education. 2. The complete Reference Java 2, Fifth Edition, Herbert Schildt, TMH.

REFERENCE BOOKS:1. Web Programming, building internet applications, Chris Bates, second edition, Wiley Dreamtech.2. Programming world wide web, Sebesta, Pearson education.3. Java – How to program, Dietel&Dietel, Pearson education.4. Java Server Pages, Hans Bergsten, SPD O’Reilly.



Course Title:COMPILER DESIGN( Elective – 3) L T P C

3 1 0 4

Objectives:

To learn basic structure of compilers, basic concepts and terminology in programming language. To learn context free grammars, recursive descent parsing, predictive parsers on top-down parsing. To learn SLR,CLR, LALR parsers on bottom-up parsing. To learn intermediate code forms and syntax directed translation. To learn symbol table format, hashing and storage allocations To learn different types of optimization of code. To learn flow gaphs, live variables and global optimization. To learn different object code generation techniques.

Outcomes:

Understand the lexical analysis, parsing and code generation and optimization phases of compilation, and design a compiler for a concise programming language.

Design and implementation of the following four stages of compilation for a subset of a modern imperative programming language: lexical analysis, parsing, code generation and code optimization.

The learning outcomes are assessed through assignments, mid-semester and final exam.. Assesment of students understanding of the subject may be done through the quality of the programs

that they write in conducted laboratory.

UNIT I:Overview of language processing - preprocessors, compiler, assembler, interpreters, linkers & loaders, Overview of Compilation: Phases of Compilation, pass and Phases of translation, bootstrapping.Lexical Analysis, Role of Lexical Analysis - Lexical Analysis Vs. Parsing, Token, patterns and Lexemes, Lexical Errors, Regular Grammar and regular expression for common programming language features,Transition diagram for recognition of tokens, Reserved words and identifiers, Examples. , LEX-lexical analyzer generator. UNIT II:Syntax analysis -Context free grammars, Role of a parser, Top down parsing, Backtracking, LL (1), recursive descent parsing, Predictive parsing, Preprocessing steps required for predictive parsing. Bottom up parsing - Shift Reduce parsing, Simple LR parsers, Why LR parsers, Construction of CLR, LALR parsing, Error recovery in parsing.Semantic analysis -Intermediate code , three address code, quadruples, triples Intermediate forms of source Programs , Syntax directed translation, Attributed grammars, abstract syntax tree, evolution and flow of attribute in syntax tree, Conversion of popular Programming languages language Constructs into Intermediate code forms.UNIT III:Symbol Tables -Symbol table format, use of symbol tables, Symbol attribute and management , Run-time environment: Procedure activation, parameter passing, value return, memory allocation, and scope. Code optimization - Consideration for Optimization, Machine independent code optimization- Common sub expression elimination, constant folding, copy propagation, dead code elimination, strength reduction, loop optimization, procedure inclining.Machine dependent code optimization: Peephole optimization, register allocationUNIT IV:Data flow analysis - Dataflow Analysis, Intermediate representation for flow analysis , Various dataflow analyses, Loop Optimizations: Dominators, Loop-invariant computations, Array bounds checks, Loop unrolling.Code Generation - Processing the intermediate Code- Interpretation, Code generation, Simple code generation, code generation for basic blocks, BURS Code generation and dynamic programming, Register allocation by graph coloring, Evaluation of code generation techniques Preprocessing the intermediate code, post processing the target code, machine code generation.TEXT BOOKS :1.Principles of compiler design , A.V. Aho . J.D.Ullman; Pearson Education 2.Modern Compiler Design- Dick Grune, Henry E. Bal, Cariel T. H.Jacobs, Wileyndreamtech. REFERENCE BOOKS :1.Advanced Compiler Design Implementation, S.S.Muchnick,Elsevier. 2. Compilers principles,techniques and tools A.V.Aho,RaviSethi& J.D. Ullman; Pearson ed., 3.lex&yacc,John R. Levine, Tony Mason, Doug Brown, O’reilly

M.Tech I Year I Semester(Computer Science & Engineering) A Y 2013-14 Course Code:CSEP1 1416

Course Title:DISTRIBUTED SYSTEMS ( Elective – 3) L T P C

3 1 0 4

Objectives:

This course is designed for first year M.Tech students. The course is intended to make the students to

understand the basic concepts of distributed system with various system models and Interprocess

Communication andCommunication between Distributed Objectswith their operating system support, support

of distributed File and variousTransactions & Replications.

Understand the distributed systems with examples

Understand Architectural models and other Fundamental models and Internet Protocols and IPC and

various types of communications.

Acquire knowledge of Communication between Distributed Objects and RMI implementation

Acquire knowledge of Operating System Layer, Processes and Threads and Distributed File Systems.

Understand distributed Mutual Exclusion and elections and distributed Dead Locks.

Understand Transaction Recovery and Replication

Course Outcomes:

Gain the knowledge about the technologies in distributed environment.

Develop applications in the area of distributed system.

Demonstrate various data delivery models (peer to peer system, Napster)

Demonstrate how Mutual Exclusion and elections and distributed Dead Locks are used.

UNIT I:Characterization of Distributed Systems - Introduction, Examples of Distributed Systems, Resource

Sharing and the Web, Challenges.

System Models – Introduction, Architectural Models- Software Layers, system Architecture, Variation,

Interface and Objects, design Requirements for Distributed architectures, Fundamental models – Interaction

Model, Failure Model, Security Model.

UNIT II:Interprocess Communication – Introduction, The API for the Internet Protocols – The Characteristics of

Interprocess communication, Sockets, UDP datagram Communication, TCP stream Communication; External

Data Representation and Marshalling; Client Server Communication; Group Communication – IP Multicast –

an implementation of group communication, Reliability and Ordering of Multicast.

Distributed Objects and Remote Invocation – Introduction, Communication between Distributed Objects –

Object Model, Distributed Object Modal, Design Issues for RMI, Implementation of RMI, Distributed

Garbage Collection; Remote Procedure Call, Events and Notifications, Case Study: JAVARMI

UNIT III:Operating System Support – Introduction, The Operating System Layer, Protection, Processes and Threads –

address Space, Creation of a New Process, Threads.

Distributed File Systems – Introduction, file Service architecture; Peer – to – peer Systems: Introduction,

Napster and its Legacy, Peer – to – Peer Middleware, Routing Overlays.

UNIT IV:Coordination and Agreement – Introduction, distributed Mutual Exclusion, Election, Multicast Communication.Transactions & Replications – Introduction, system Model and Group Communication, Concurrency Control in distributed Transactions, distributed Dead Locks, Transaction Recovery; Replication –Introduction, Passive (Primary) Replication, active Replication.TEXT BOOKS: 1. Ajay D Kshemkalyani, MukeshSighal, “Distributed Computing, Principles, algorithms and Systems”,

Cambridge.2. George Coulouris, Jean Dollimore, Tim Kindberg, “ Distributed Systems – Concepts and Design”, fourth

Edition, Pearson Publication.REFERENCES:

1. Distributed Operating Systems,PradeepK.Sinha,PHI.2. Distributed Systems,S.Ghosh,Chapman&Hall/CRC,Taylor&Francis Group,2010.3. Distributed Systems – Principles and Paradigms, A.S. Tanenbaum and M.V. Steen,PearsonEducation.

M.Tech I Year I Semester(Computer Science & Engineering) A Y 2013-14 Course Code: CSEP1 1417

Course Title:OPEN SOURCE SOFTWARE ( Elective-3) L T P C

3 1 0 4

Objectives: The main objective of this course is : To understand open sources and Application of open sources

Learn open source operating system LINUX and its environment and development

Learn open source database i.e MYSQL record selection technology, sorting query results, generating summary, generating metadata.

Study the open source programming languages i.e PHP programming environment, File handling and data storage and database connectivity to MYSQL

Study the open source programming language PYTHON’s syntax and style, objects, Lists and tuples, dictionaries, conditionals and loops, File handling

Study the open source programming language PERL’s parsing rules, statements and control structures, packages and modules, files and Data manipulation

Outcomes:At the end of the course students are able to :

Involve open source software groups and develop new features for existing software’s

Design a Dynamic WEB application using open sources with database Connectivity

Develop real time projects using PHP and database interfacing

Develop real time projects using PYTHON and PERL database interfacing

UNIT I:INTRODUCTION-Introduction to open sources-Need of Open Sources –Advantages of Open Sources-

Application of Open Sources. Open Sources Operating systems :LINUX Introduction-General Overview-

Kernel Mode and user mode.

LINUX-Process-AdvancedConcepts-Scheduling-Personalities-Cloning-Signals-Developmentwith Linux.

UNIT II:

OPEN SOURCE DATABASE - MySQL: Introduction-Setting up account-Starting, termination and writing

your own SQL programs-Record selection Technology-Working with strings-Date and Time –Sorting Query

Results-Generating Summary-Working with metadata-Using equences - MySQL and Web.

OPE N SOURCE PROGRAMMING LANGUAGES-PHP: Introduction - Programming in web

environment -variables-constants- data types - operators-Statements -Functions -Arrays -OPP - String

Manipulation and regular expression - File handling and data storage

UNIT III:PHP and SQL database-PHP and LDAP-PHP Connectivity-Sending and receiving E-mails-Debugging and

error handling-Security-Templates.

PYTHON - Syntax and Style-Python Objects-Numbers-Sequences-Strings-Lists and Tuples-Dictionaries-

C0nditionals and Loops.

UNIT-IV:Files-Input and output-Errors and Exceptions-Functions-Modules-Classes and OOP-Execution Environment.

PERL - Perl backgrounder-Perl overview-Perl parsi8ng rules-Variables and Data-0 Statements and Control

structures-Subroutines, Packages, and Modules-Working with Files-Data Manipulation.

TEXT BOOKS:1. Remy Card, Eric Dumas and frank Mevel, “The Linux Kernel Book”, Wiley Publications, 2003.2. Steve Suchring, ”MySQL Bible”, John Wiley, 2002.REFERENCE BOOKS:1. RasmusLerdorf and Levin Tatroe,”Programming PHP”, O’Reilly,2002.2. Wesley J.Chun, “Core Phython Programming”, Prentice Hall, 2001.3. Marin C.Brown, “Perl: The Complete Reference”,2nd Edition, Tata McGraw-Hill Publishing Company

Limited, Indian Reprint 2009.4.StevenHolzner,’PHP: The Complete Reference”,2nd Edition, Tata McGraw-Hill Publishing Company

Limited, Indian Reprint 2009.5.VikramVaswani,”MYSQL: The Complete Reference”, 2nd Edition, Tata McGraw-hill Publishing Company

Limited, Indian Reprint 2009.



Course Title:CLOUD COMPUTING (Elective - 4) L T P C

3 1 0 4

Objective:

• Understand cloud computing basics

• To Understand the basic implementation details about cloud services on web

• To understand how cloud computing can be applied to family and to corporations

• Various ways to collaborate cloud services online

• Cloud computing software security fundamentals and its secured architecture.

OUTCOMES:

• Understand the use of cloud computing and its services at individual level, family level and at

corporate level

• able to understand how to collaborate various cloud services online

• Understand cloud computing software security fundamentals

• Understand various risks, threats and challenges associated with cloud computing for an organization

• Able to understand the influence of cloud computing architecture on its security.

UNIT I: Understanding Cloud Computing-Cloud Computing, History of Cloud Computing, Cloud Architecture, Cloud Storage, Why Cloud Computing Matters, Advantages of Cloud Computing, Disadvantages of Cloud Computing, Companies in the Cloud Today, Cloud Services.Developing Cloud Services -Web-Based Application, Pros and Cons of Cloud Service Development, Types of Cloud Service Development, Software as a Service, Platform as a Service , Web Services, On-Demand Computing, Discovering Cloud Services Development Services and Tools, Amazon Ec2, Google App Engine, IBM Clouds.UNIT II:Cloud Computing for Everyone -Centralizing Email Communications, Collaborating on Schedules, Collaborating on To-Do Lists, Collaborating Contact Lists, Cloud Computing for the Community, Collaborating on Group Projects and Events, Cloud Computing for the Corporation.Using Cloud Services -Collaborating on Calendars, Schedules and Task Management, Exploring Online Scheduling Applications, Exploring Online Planning and Task Management, Collaborating on Event Management , Collaborating on Contact Management, Collaborating on Project Management, Collaborating on Word Processing, Collaborating on Databases, Storing and Sharing Files.UNIT III:Other Ways to Collaborate Online-Collaborating via Web-Based Communication Tools, Evaluating Web Mail Services, Evaluating Web Conference Tools, Collaborating via Social Networks and Groupware,Collaborating via Blogs and Wikis.Cloud Computing Software Security Fundamentals -Cloud information Security Objectives, Cloud Security Services, Relevant Cloud Security Design Principles, Secure Cloud Software Requirements, Approaches to Cloud Software Requirements Engineering, Cloud Security Policy Implementation, Secure Cloud Software Testing, Cloud Penetration Testing, Cloud Computing and Business Continuity Planning/Disaster Recovery, Summary.UNIT IV:Cloud Computing Risk Issues / Cloud Computing Security Challenges -The CIA Triad, Privacy and Compliance Risks, Threats to Infrastructure Data and Access Control, Cloud Access Control Issues, Cloud Service Provider Risks, Summary, Security Policy Implementation, Computer Security Incident Response Team (CSIRT), Virtualization Security Management, VM Security Recommendations, VM-Specific Security Techniques, Summary.Cloud Computing Security Architecture -Architectural Considerations, General Issues, Trusted Cloud Computing, Secure Execution Environments and Communications, Micro architectures,, Identity Management and Access Control.

TEXT BOOKS :1. Cloud Security,Ronald L. Krutz and Russell Dean Vines.

REFERENCES1. Michael Miller, Cloud Computing: Web-Based Applications That Change the Way You Work and

Collaborate Online, Que Publishing, August 2008.2. Haley Beard, Cloud Computing Best Practices for Managing and Measuring Processes for On-demand

Computing, Applications and Data Centers in the Cloud with SLAs, Emereo Pty Limited, July 2008.



Course Title:IMAGE PROCESSING AND PATTERN RECOGNITION (Elective-4) L T P C

3 1 0 4

Objective: Students undergoing this course are expected to:

learn the fundamentals of digital image processing (transforming and filtering) Understand statistical and spatial image compression techniques. Know about edge detection and segmentation techniques used for analyzing the images. Understand and analyze methods for pattern classification and clustering methodologies. Learn common feature extraction methods for pattern recognition

Outcomes:At the end of the course students are expected to:

Apply image processing techniques in both the spatial and frequency (Fourier) domains Able to implement image processing programs using C++, MATLAB and java languages Design systems and algorithms for pattern recognition Implement typical pattern recognition algorithms in MATLAB Apply well‐known algorithms to pilot problems

UNIT I:

Introduction - Origins of digital image processing, Applications of digital image processing, Fundamental steps of image processing, components of an image processing of system. The image model and image acquisition, sampling and quantization, relationship between pixels, distance functions, scanner.Transformation and Filtering - Statistical and spatial operations, Intensity functions transformations, histogram processing, smoothing &sharpening, spatial filters Frequency domain filters, homomorphic filtering, image filtering & restoration. Inverse and weiner filtering, FIR weiner filter, Filtering using image transforms, smoothing splines and interpolation. UNIT II:Image compression- Types and requirements, statistical compression, spatial compression, contour coding, quantizing compression, image data compression-predictive technique, pixel coding, transfer coding theory, lossy and lossless predictive type coding, Digital Image Water marking.Morphology - Morphological and other area operations, basic morphological operations, opening and closing operations, dilation erosion, Hit or Miss transform, morphological algorithms, extension to grey scale images. UNIT III:Segmentation and Edge Detection - Detection of discontinuities, edge linking and boundary detection, thresholding, region based segmentation, segmentation by morphological watersheds., use of motion in segmentation.Representation and Description - Chain codes, Ploygonal approximation, Signature Boundary Segments, Skeltons, Boundary Descriptors, Regional Descriptors, Relational Descriptors, Principal components for Description, Relational Descriptors UNIT IV:Pattern Recognition Fundamentals- Basic Concepts of pattern recognition, Fundamental problems in

pattern recognition system, design concepts and methodologies, example of automatic pattern recognition systems, a simple automatic pattern recognition model .Pattern classification- Pattern classification by distance function: Measures of similarity, Clustering criteria, K-means algorithm, Pattern classification by likelihood function: Pattern classification as a Statistical decision problem, Bayes classifier for normal patterns. TEXT BOOKS :1. Digital Image Processing, 3/e,,Rafael C. Gonzalez, Richard E. Woods, PEA.2. Pattern recognition Principles, Julus T. Tou, and Rafel C. Gonzalez, Addision-Wesly.REFERENCE BOOKS :1. Image Processing, Analysis and Machine Vision, Second Edition, Milan Sonka, Vaclav Hlavac and Roger

Boyle.Thomson learning.2. Digital Image Processing,Williamk. Pratl, John wiley edition.3. Fundamentals of digital image processing, A.K. Jain. PH.4. Pattern classification, Richard Duda, Hart and David strok John Weily publishers. 5. Digital Image Processing,S.Jayaraman,S.Esakkirajan,T.Veerakumar,TMH. 6. Pattern Recognition,R.Shinghal,Oxford University Press.



Course Title:SOCIAL NETWORKS AND SEMANTIC WEB (Elective - 4) L T P C

3 1 0 4

Objectives:

To understand the Today’s world wide web i.e. www and The Next Generation Web, Development of semantic web, Semantic Web Road Map, Logic on the semantic Web.

To learn Electronic Sources for Network Analysis,Knowledge Representation for the Semantic Web To learn Ontological representation of social individuals ,social relationships, Aggregating and

reasoning with social network data To Study Evaluationof web-based social network extraction i.e. optimizing goodness of fit,

comparison across methods and networks, predicting the goodness of fit, evaluation through analysis. To learnSemantic-based Social Network Analysis in the sciences Methodology

OUTCOMES:

At the end of the course students are able to :

Involve developing and managing social networks.

Apply the semantic web techniques for managing the data effectively.

Develop tools using ontology Engineering

UNIT I:Introduction -The World Wide Web ,Limitations of Today’s Web, The Next Generation Web, Development of semantic web, Semantic Web Road Map, Logic on the semantic Web .Social Network Analysis- What is networks analysis?, Development of Social Networks Analysis, Key concepts and measures in network analysis.

UNIT II:Electronic Sources for Network Analysis- Electronic Discussion networks, Blogs and Online Communities, Web-based networks. Modeling and aggregating social network data.Knowledge Representation for the Semantic Web- Ontology’s and their role in the semantic web, Ontology’s Languages for the Semantic Web –Resource Description Framework(RDF) / RDF Schema, Ontology Web Language(OWL),UML,XML/XML Schema.

UNIT III:Modeling and aggregating social network data-State-of-art in network data representation, Ontological representation of social individuals, Ontological representation of social relationships, Aggregating and reasoning with social network data.Developing social-semantic applications- Building Semantic Web Applications with social network features, Flink: the social networks of the Semantic Web community, Open academia: distributed. Semantic based publication management

UNIT IV:Evaluation of web-based social network extraction- Differences between survey methods and electronics data extraction , context of the empirical study, data collection, preparing the data, optimizing goodness of fit, comparison across methods and networks, Predicting the goodness of fit, evaluation through analysis.Semantic-based Social Network Analysis in the sciences Methodology - Data acquisition, Representation, storage and reasoning, Visualization and Analysis, Results – Descriptive analysis, Structural and cognitive effects on scientific performance.TEXT BOOK1.Social Networks and the Semantic Web ,Peter Mika,Springer,2007.2.Thinking on the Web - Berners Lee,Godel and Turing,Wiley interscience,2008.

REFERENCES:1.Semantic Web Technologies ,Trends and Research in Ontology Based

Systems,J.Davies,RudiStuder,PaulWarren,JohnWiley&Sons.2. Semantic Web and Semantic Web Services -LiyangLuChapman and Hall/CRC Publishers,(Taylor &

Francis Group).3. Information Sharing on the semantic Web - HeinerStuckenschmidt;Frank Van Harmelen, Springer

Publications.4. Programming the Semantic Web,T.Segaran,C.Evans,J.Taylor,O’Reilly,SPD.

M.Tech I Year I Semester(Computer Science & Engineering) A Y 2013-14 Course Code: CSEP1 1221

Course Title: WEB TECHNOLOGIES LAB T P C 0 3 2Objectives:

• Understand html tags

• Understand how to integrate with PHP& PHP databases

• To Understand the basic web application development with J2EE technology

• To understand how to design web applications using MVC

• Various ways to collaborate web services

Outcomes:• Develop html programs for web applications

• Develop advanced Java programs like javabean,servelet and jsp

• Design web applications using PHP and connects to database

• Implement web pages design with javascript language

• Implement web applications with tomcat server

1 Design the following static web pages required for an online book store web site.a) Home Page b) Login Page c) Catalogue page

2 Design the following static web pages required for an online book store web site.d) Cart Page e) Registration Page

3 VALIDATION: Write JavaScript to validate the various fields of the above registration page.

4 Design a web page using CSS (Cascading Style Sheets) which includes the following:

a) use different font styles b) set background imagesc) control the repetition of imagesd) define styles for linkse) work with layersf) add customized cursor

5 Write an XML file which will display the Book information which includes the following:

1) Title of the book 2) Author Name 3) ISBN number4) Publisher name 5) Edition 6) Price

6 VISUAL BEANS:Create a simple visual bean with a area filled with a color.

7 1) Install TOMCAT web server and APACHE.2)Access the above developed static web pages for books web site, using these servers by putting the web pages developed in week-1 and week-2 in the document root.

8 User Authentication : Assume four users user1,user2,user3 and user4 having the passwords pwd1,pwd2,pwd3 and pwd4 respectively. Write a servelet for doing the following.1. Create a Cookie and add these four user id’s and passwords to this Cookie.2. Read the user id and passwords entered in the Login form (week1) and authenticate with the values (user id and passwords ) available in the cookies.

9 Install a database(Mysql or Oracle). Create a table which should contain at least the following fields: name, password, email-id, phone number(these should hold the data from the registration form). Practice 'JDBC' connectivity. Write a java program/servlet/JSP to connect to that database and extract data from the tables and display them. Experiment with various SQL queries.Insert the details of the users who register with the web site, whenever a new user clicks the submit button in the registration page (week2).

10 Write a JSP which does the following job: Insert the details of the 3 or 4 users who register with the web site (week9) by using registration form. Authenticate the user when he submits the login form using the user name and password from the database ( similar to week8 instead of cookies).

11 Create tables in the database which contain the details of items (books in our case like Book name , Price, Quantity, Amount )) of each category. Modify your catalogue page (week 2)in such a way that you should connect to the database and extract data from the tables and display them in the catalogue page using JDBC.

12 HTTP is a stateless protocol. Session is required to maintain the state. The user may add some items to cart from the catalog page. He can check the cart page for the selected items. He may visit the catalogue again and select some more items. Here our interest is the selected items should be added to the old cart rather than a new cart. Multiple users can do the same thing at a time(i.e., from different systems in the LAN using the ip-address instead of localhost). This can be achieved through the use of sessions. Every user will have his own session which will be created after his successful login to the website. When the user logs out his session should get invalidated (by using the method session.invalidate() ).

Modify your catalogue and cart JSP pages to achieve the above mentioned functionality using sessions.

m.tech i year i semester(computer science & engineering) course structure...

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