Syllabus Master in Computer Applications (MCA) Assam Science … SYLLABUS-ASTU... · 2018. 12. 1. · Syllabus Master in Computer Applications (MCA) Assam Science and Technology University

Syllabus Master in Computer Applications (MCA)

Assam Science and Technology University (ASTU)

MCA SYLLABUS STRUCTURE

1st Semester subjects

Paper Subject Name L T P Credits

Theory Subjects

CA132101 Introductory Programming (IP) 3 2 0 4

CA132102 Digital Systems (DS) 3 2 0 4

CA132103 Theory of Computer Science(TCS)

3 2 0 4

CA132104 Accounting and financial management (AFM)

3 2 0 4

CA132105 Computer oriented numerical methods(CONM)

3 2 0 4

Practical Subjects

CA132116 Laboratory-I (LAB-1) 0 0 10 5

Total Contact Hrs : 35 ; Total Credits : 25 ;

2nd Semester subjects


Theory Subjects

CA132201 Data and File Structure (DFS) 3 2 0 4

CA132202 Computer Architecture and Organization (CAO)

3 2 0 4

CA132203 Computer based optimization techniques (CBOT)

3 2 0 4

CA132204 Graph Theory (GT) 3 2 0 4

CA132205 Probability and Statistics (PS) 3 2 0 4

Practical Subjects

CA132216 Laboratory-II (LAB-2) 0 0 10 5


3rd Semester subjects


Theory Subjects

CA132301 System Software (SS) 3 2 0 4

CA132302 Database Management Systems -I(DBMS)

3 2 0 4

CA132303 Management Information System(MIS)

3 2 0 4

CA132304 Object Oriented Programming and Design (OOPD)

3 2 0 4

CA132305 Computer Graphics & Multimedia(CGM)

3 2 0 4

Practical Subjects

CA132316 Laboratory-III (LAB-3) 0 0 10 5


4th Semester subjects


Theory Subjects

CA132401 Operating Systems (OS) 3 2 0 4

CA132402 Software Engineering(SE) 3 2 0 4

CA132403 Database Management Systems -II(DBMS)

3 2 0 4

CA132404 Computer Network (CN) 3 2 0 4

CA132405 Design and Analysis of Algorithms (DAA)

3 2 0 4

Practical Subjects

CA132416 Laboratory-IV (LAB-4) 0 0 10 5




Theory Subjects

CA132501 Data Warehousing and Data Mining(DWDM)

3 2 0 4

CA132502 Web Technology (WT) 3 2 0 4

CA132503 Artificial Intelligence(AI) 3 2 0 4

CA132504 Elective-I 3 2 0 4



CA132505 Elective-II 3 2 0 4

Practical Subjects

CA132526 Minor Project 0 0 10 5



Paper Subject Name Total Project duration and work hours

Credits

Subjects

CA132621 System Development Project (Internal Evaluation)

15 Weeks to be devoted for the project work

10

CA132622 System Development Project (External Evaluation)

15


ELECTIVE SUBJECTS:

Elective –I (CA132504) Elective-II (CA132505)

a) Microprocessor and Embedded Design(MED)

b) Distributed Systems(DS) c) Expert Systems(ES) d) Image Processing(IP) e) Biologically Implied Computing(BIC) f) Programming Language and

Paradigms(PLP)

a) Cryptography and Network Security (CNS) b) Information Storage and Retrieval (ISR) c) Multimedia Systems(MS) d) Simulation and Modeling(SM) e) Remote Sensing and GIS(RSG) f) Mobile Computing(MC)

MCA 1ST SEMESTER SYLLABUS

Paper : CA132101 Subject Name : INTRODUCTORY PROGRAMMING Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre–requisite : NIL This course aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The course uses the C programming language. This course aims to provide students with an understanding of the role computation can play in solving problems. It also aims to help students, regardless of their major, to feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The course uses the C programming language. Course Outcome:

1. Understand the methodology of problem solving using algorithms. 2. Write Programs using C language and thus debug and run the programs using C Compilers. 3. Understand and implement basic data structures and their representations using arrays,

pointers, structures and defined types. 4. Write programs that read text data from files and write data from memory to text files. 5. Solve scientific and numerical problems using C language.

Course Content:

UNIT PARA Content Weeks

1 (i) Introduction to Programming ,Programming methodology, Types of Programming Languages , Assembler, Compiler and Interpreter, Programming development steps and tools ,Structure of a C program, The C keywords, Identifiers, Constants, Variables, C Data types, dynamic initialization, type modifiers, type conversions, constant and volatile variables

2

(ii) Properties of Operators, Operator Priority, conditional operators, arithmetic, relational, assignment operators and expressions, logical, bitwise operators. Input and output in c: Formatted and Unformatted functions, Library functions.

1

(iii) Control statement: if statement, if-else, nested if else, if-else-if ladder, break, continue, got, Switch statement. Loop control statement.

1

2 (i) Arrays: Array initialization, array terminology, characteristics of an array, 1-D array and its operations, Multi -dimensional arrays. Strings: string standard functions.

2

(ii) Pointers, void pointers, arithmetic operations with pointers, pointers and arrays, array of pointers, pointers to pointers, pointers and strings. Dynamic memory allocation, memory allocation functions.

2



3 (i) Function, call by value, call by reference, and function as an argument, Functions with arrays and Pointers, Recursion-Types of Recursion, Recursion versus Iterations, Advantages and Disadvantages of Recursion, Efficiency of Recursion.

2

4 (i) Preprocessor Statement and macros:#define, #include , #line, #finder , #error , #line , #pragma Directive.

1

(ii) User Define Datatypes:Structure, Enumerated Data Type, Union,Typedef. 1

5 (i) File Handling in C: Storing, creating, retrieving, updating Sequential, relative, indexed and random access mode, Files with binary mode (Low level), performance of Sequential Files. File operation: creation, copy, delete, update, text file, binary file.

2

Books: 1. Dromey, G.: How to solve it by computer, PHI(EEE), 1985

2. Kanetkar, Let us C, BPB

3. Jeri, Elliot: Problem Solving and Programming Design in C, Pearson

4. Balaguruswamy: Programming in ANSI C, TMGH

5 Balagurusamy : Fundamentals Of Computers,TMH

6 Venugopal : Mastering C, TMH

Paper : CA132102 Subject Name : DIGITAL SYSTEMS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60)

Pre – requisite : NIL This course covers the fundamentals of the electronic circuits that are used to build computers, and outlines the software components that support their use. From the functions of individual transistors, it constructs a complete implementation of a simple processor, explaining in a structured way how complex behaviors are built up from simpler parts. This is followed by an overview of the software components of a complete computer system. Students will gain an understanding of the factors that affect the performance of hardware, and how these factors change with changes of scale, for example in the size of the data that a computer system handles. They will also gain experience in the important technique of hierarchical specification, implementation and proof of correctness using logic and data representation. Impel design of combinational and sequential circuits; standard design elements. Computer arithmetic for integers and floating-point numbers; basic error analysis. Register transfer level design of a simple microprocessor. Simple programming in assembly language. Role of assemblers, compilers and linkers. Memory hierarchy. Course Outcome:

1. Represent the number in any number system and thus have clean idea about computer

arithmetic’s. 2. Design optimized Combinational Circuits with logic gates. 3. Design optimized sequential circuits with logic gates. 4. Have an idea about inner functioning of electronics devices and simple computers.

Course Content:


1 Representation of Information: Number System: Binary, octal, hexadecimal; Positive and negative numbers; fixed point and floating point quantities. Arithmetic operations: Addition, subtraction. Character codes: ASCII and EBCDIC, Redundant coding for error detection and correction: Concept of parity codes, Hamming Codes (SEC-DEC)0 and distance.

3

2 2.1 Logic Design: Boolean algebra, Boolean variables and functions- canonical and standard forms, truth table, minimization of Boolean functions- Karnaugh map, tabulation methods..

2

2.2 Combinational logic circuits: AND, OR, NAND, NOR and NOT gates and tri-state

buffer; Implementation of Boolean functions using logic gates; Multiplexers, decoders, encoders, simple arithmetic and logic circuits.

4

3 Sequential circuits: flip-flops, shift registers and counters- synchronous and asynchronous. Concept of bus and register transfer language, state table, state diagram and state equations.

3

4 Memory Devices: Semiconductor memory - RAM, ROM; Magnetic core and surface memory- disk, drum, tape; Access time and cost considerations: Concepts of volatility, random access, serial access, direct access, online and backup storage.

2

5 Basic CPU organization: Simplified functional block diagram of a CPU; Instruction execution process.

1



Books: 1. Mano, M.M.: Digital Logic and Computer Design, Pearson

2. Rajaraman V, Radhakrishnan : An introduction to Digital Computer Design. PHI

3. Mano, M.M.; Computer System Architecture, Pearson

4. Hamacher, Vranesic, Zaky: Computer organization, McGraw Hill.

5 Uyemura . J.P.: Digital Systems Design an integrated approach, Cengage

6 Leach : Digital Principles & Applications,7/e, TMH

Paper : CA132103 Subject Name : THEORY OF COMPUTER SCIENCE Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : NIL Theoretical computer science is a division or subset of general computer science and mathematics which focuses on more abstract or mathematical aspects of computing and includes the theory of computation This module introduces the theory of computation through a set of abstract machines that serve as models for computation - finite automata, pushdown automata, and Turing machines – and examines the relationship between these automata and formal languages. Additional topics beyond the automata classes themselves include deterministic and nondeterministic machines, regular expressions, context free grammars, undesirability, and the P = NP question. Course Outcome:

1. Students will be able to understand the working principle of a finite automaton 2. Students will be able to differentiate between DFA and NDFA 3. Students will be able to understand the grammar used in Finite automata and to define the

language generated by the grammar 4. Students will be able to classify the different languages 5. An ability to define and use abstract models of computation such as finite and push-down

automata, and analyze their relative expressive power. 6. An ability to define, use, and convert between abstract machine models and formal languages.

Course Content:


1 Introductory Concept on Formal logic, revision of propositional and first orders predicate logic, conjunctive normal form, clausal form, Logic programming.

2

2 Functions and relation: Binary relation, types of relation , equivalence relation and equivalence class, closure of relation, function, different types of functions.

2

3 Logic: truth tables, algebra of propositions, logical arguments, predicate calculus 3

4 Concepts of Automata Theory: Automata, Computability and Complexity, Alphabets, Strings, Languages, Grammars.

1

5 Automata and Languages:

5.1

Finite Automata: Deterministic and non deterministic finite Automata, Equivalence of DFA & NFA, Finite Automata with Epsilon- Transitions.

2

5.2

Regular Expression (RE) and Languages: Building RE, operators of RE, Conversion of RE to Automata and Automata to RE. Application of RE and its algebraic laws.

2

5.3 Non Regular Languages: Pumping Lemma and its application. 1

6 Context Free Grammars and Languages:

6.1 Context-free Grammars: Definition and Derivation of languages. Ambiguity in Grammars and languages. CHOMSKY NORMAL FORM (CNF).

2

6.2 Pushdown – Automata: Definition, The language of a PDA, Equivalence of PDA and CFG’s.

2

6.3 Non-Context-free Languages: Application of Pumping Lemma for non- Context free languages.

1

7 Computability Theory:

7.1 Turing Machines: Notations, ID for Turing Machine, i.e., recursively enumerable languages, Acceptability and Halting, Multi Traces Turing Machine. The Church- Turing Thesis.

7.2 Variants of Turing Machines: Multitape Turing Machine, Non-Deterministic Turing Machine, Enumerator, Equivalence of one tape and multitape Turing Machine.

Books:

1. Hopcroft, Motwani & Ullman: Introduction to Automata Theory, Languages and Computation. 3rd Edn. LPE.

2. Theory of Computation: Michael Sipser CENCAGE Learning

3 Martin : Introduction To Languages & Theory Of Computation, TMH

4. Liu and Mahapatra, Discrete Mathematics, TMH

http://en.wikipedia.org/wiki/Computer_science

http://en.wikipedia.org/wiki/Computer_science

http://en.wikipedia.org/wiki/Mathematics

http://en.wikipedia.org/wiki/Theory_of_computation



Paper : CA132104 Subject Name : ACCOUNTING AND FINANCIAL MANAGEMENT Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : NIL Accountants record, classify, summaries, interpret and communicate the financial information about a business. However they do more than just prepare financial reports on the activities of an organization. Experienced accountants work strategically with the executive and management teams by providing expert financial advice on the impacts of management decisions, compliance and governance and the deployment of systems, resources and processes throughout the company. Through this course Students learn to apply accounting skills to a range of different managerial, business and problem-solving situations. Course Outcome: 1. Recognize, read and use any of the common management accounting reports 2. Prepare, or provide the necessary information for the preparation of budgets

3. Cost current or proposed products, and know the contentious issues that will need to be addressed. Course Content:


1 1.1 Accounting concepts and principles, Accounting conventions, principles of Double-entry system of accounting, objectives and advantages of accounting;

2

1.2 Classification of Debit and Credit, cardinal Rules for Debit and credit, Journalising, Ledger postings, closing and balancing of Ledger Accounts, Subsidiary Books, types of cash Book;

3

2 3.1 Trial balance, Preparation of trading Account, Manufacturing Account, Profit and loss Account and Balance Sheet for Proprietary concerns,

3

3.2 Capital Expenditures and revenue Expenditures, Depreciation of Fixed Assets, Simple adjustments;

2

4 4.1 Financial management- Concept and importance, its increasing role in modern times, cost accounting and its importance, standard costing and marginal costing, Break-even Analysis, ratio analyses, type of ratios & usefulness, fund flow and cash flow, working capital cycle.

3

5 5.1 Introduction to computerised accounting system, coding logic, master and transaction files, documents used for data collection, processing of different files and outputs obtained, automatic generation of profit and loss account and balance sheet.

2

Books: 1. Chandra: Financial Management. TMH

2. Shukla &Grewal, Cost Accounting

3. Chawla,Juneza& Saxena Double Entry Book Keeping and Accounts

4. Anole: Financial Accounting, prentice-Hall.

5. Horngren and Sundem: Introduction to Financial Accounting, PH Int.

6. Murthy,U.S.; Management Finance, 2nd Edn., Vakils Fefers & Simons Ltd.

7. Van Home, James,C.: Financial Management and policy, PH Inc.

8. Pandey, I.M.: Financial management, Vikas publications, 1979

9 Levy and Sarnat: Principles of Financial management, Prentice- Hall.

Paper : CA132105 Subject Name : COMPUTER ORIENTED NUMERICAL METHODS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : MCA 1.1 and MCA 1.3 Computer oriented methods for solving numerical problems in science and engineering; numerical solutions to systems of simultaneous linear equations, nonlinear algebraic equations (root solving), differentiation and integration, ordinary differential equations, interpolation, and curve fitting. Course Outcome:

1. Be familiar with numerical interpolation and approximation of functions. 2. Be familiar with numerical integration and differentiation 3. Be familiar with numerical solution of ordinary differential equations. 4. Be familiar with numerical solutions of nonlinear equations in a single variable. 5. Be aware of the use of programming languages for the solution of numerical problems.

Course Content:




1 Interpolation-Polynomial Interpolation, difference tables and calculations of difference.

2

2 2.1 Numerical differentiation- Newton’s Interpolation, Lagrange’s interpolation and Newton’s divided difference formulae.

1 ½

2.2 Numerical integration- Trapezoidal rule,Simpson’s (1/3 and 3/8)rules, Gaussian Quadrature formula , Romberg integration

1 ½

3 Simultaneous linear equations- Direct methods: Gauss elimination , Jacobi’s. Iterative methods: Gauss-Jordan , Gauss- Seidal

3

4 Solution of non linear equations of one variable- Iterative methods: Zeros of transcendental equation and zeros of polynomials using Bisection, Iterative, False-Position, Secant and Newton Raphson methods. Convergence of these methods

3

5 Ordinary differential equations of one and two variables- Euler’s method, Modified Eular’s method , Runga Kutta (2nd and 4th ) methods, Milne’s methods. Predictor – corrector methods.

4

Books: 1. Gerald and Wheatley : Applied Numerical Analysis ,Pearson

2. Niyogi : Numerical Analysis and algorithm ,TMGH

3. Schilling and Harris : Applied numerical methods for Engineering, Cengage

4. Scheld: Numerical Analysis, TMGH

5 Chapra : Numerical Methods For Engineers, TMH

Paper : CA132116 Subject Name : PROGRAMMING LABORATORY-I Marks : CE-20(WT 20), ST-50(WT 20), ESE-100(WT 60) Course Outcome:

1. Apply and practice logical ability to solve the problems. 2. Understand C programming development environment, compiling, debugging, linking and

executing a program using the development environment 3. Analyzing the complexity of problems, Modularize the problems into small modules and then

convert them into programs 4. Understand and apply the in-built functions and customized functions for solving the problems. 5. Understand and apply the pointers, memory allocation techniques and use of files for dealing

with variety of problems. 6. Document and present the algorithms, flowcharts and programs in form of user-manuals

Course Content :

LAB PART PARA Laboratory Content Total Weeks

1 (75%) 1.1 Understand the fundamentals of C programming. 2

1.2 Choose the loops and decision making statements to solve the problem. 3

1.3 Implement different Operations on arrays. 3

1.4 Use functions to solve the given problem. 2

1.5 Understand pointers, structures and unions. 2

1.6 Implement file Operations in C programming for a given application. 2

Books: As given CA132101



MCA 2ND SEMESTER SYLLABUS Paper : CA132201 Subject Name : DATA AND FILE STRUCTURE Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101 Course Outcome:

1. The student will learn a variety of algorithm design techniques and the factors on which the efficiency of an algorithm depends.

2. Student will learn to analyze the best case, worst case and average case analysis of an algorithm. 3. Students will be able to select an appropriate data structure for the successful implementation of

a given problem. 4. Students will be able to differentiate between linear and non linear data structure. 5. Students will be able to learn about the operations that can be performed on different data

structure and their real life applications. 6. Students will be able to learn various methods of organizing and retrieving data.


1 Fundamental Notions : Primitive and composite data types ; Time and Space

Complexity of algorithms, Concept of Big-O, small-o & Big-.

1

2 Data Structures : Linear List: Stacks, Queues, Arrays, Linked Lists, Circular & .Doubly Linked Lists.

2

3 Trees and Graphs : Introduction to Graph & Trees. Tree: Properties of trees; Pedant vertices in a tree; center of a tree; Rooted binary trees.Concepts of trees; Extended Binary trees; Complete Binary trees; General Trees. Binary Search Trees; Weight balanced and Height balanced trees; AVL Tree; Balanced Multi-Way Trees; Threaded Binary Trees.

3

4 Graph: Concept of graph, vertex set, edge set, connected graph,etc., Adjacency matrix, Path matrix, Warshall’s algorithm, Modified Warshall’s algorithm,

Adjacency list, Node list, Edge list. Spanning trees – Spanning tree algorithms; Fundamental circuits spanning trees of weighted graph

2

5 File Structures : Concepts of Fields, Records and Files; Concepts of Blocks, Clusters, Sectors. Sequential File Organization, Variable length Records and Text Files; Indexing Structures like B-trees; ISAM; Hashing Techniques for Direct Files; Inverted lists; Multilists

2

6 Sorting and Searching: Selection_sort, Insertion-sort, Bubble-sort, Quick-sort, Heap-sort, Merge-sort. Searching Techniques; Binary search, Linear search,

2

Books :

1 Abo,Hopcroft and Ullman , Data Structures and Algorithms,Addson Wesley Publishing Co.

2 Horowitz and Sahni , Fundamentals of Algorithms, Narosa Publishing House .

3 Cormen , Leiserson , Rivest, Introduction to Algorithms, Mil Press & MeGraw - Hill Books Company.

4 Kunth.D., The Art of Computer Programming,Vol - 1 & 11 , Addison Wesely.

5 Rauthan & Patel, Expert Data Structures, Khanna Publication Co(Ltd ).

6 Weiss, Data Structures and Algorithm Analysis in C++, Pearson Education

Paper : CA132202 Subject Name : COMPUTER ARCHITECTURE AND ORGANISATION (CAO) Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132102 Computer architecture is concerned with all aspects of the design and organization of the central processing unit and the integration of the CPU into the computer system itself. Architecture extends upward into computer software because a processor’s architecture must cooperate with the operating system and system software. It is impossible to design an operating system well without a knowledge of the underlying architecture. Moreover, the computer designer has to have an intimate understanding of software in order to implement the optimum architecture. Moreover, there is a tighter relationship between the computer architect and the compiler writer than at any time in the past. Course Outcome:

1. Understand the basic structure of a Computer system describing its units. 2. Understand the basic computer arithmetic including floating point representations. 3. Understand the basic concepts of memory and its addressing.



4. Know the instruction format and instruction set used for a CPU and thus capable of writing the assembly language programs.

5. Associative memory, Virtual memory and its working principles.

Course Content:


1 Overview: Simplified block diagram of a computer system, Instruction execution Model.

1

2 2.1 Processor Organization: Instruction set, types, formats, addressing modes; Register set; Assembly and machine language programming.

2

2.2 Computer arithmetic: Review of addition and subtraction; Multiplication- basic, Booth's, array; Division- basic, restoring, non-restoring; Floating point arithmetic.

2

3 Data path organization, concept of a bus. Control structure: Hardware, Microprogramming.

3

4 4.1 Memory Organization: Interfacing of memory with a processor; Cache memory; Introduction to virtual memory.

2

4.2 Input output organization: Synchronization of data transfer: strobes and handshaking, I/O mapping and control: Program controlled, Interrupt, driven, DMA, Interrupt and DMA mechanisms.

3

5 Microprocessors: Introduction to Intel 8085 microprocessor and its peripheral chips, addressing modes and simple programming examples, A RISC processor (e.g. Motorola 88000) to introduce the basic concepts of RISC architecture,SISD,SIMD,MISD,MIMD,,.

2

Books: 1. Hamacher, Vranesic and Zaky: Computer Organization, TMGH

2. Mano M.M: Computer system Architecture, PHI (EEE)

3. William Stallings, Computer Organisation and architecture, Pearson

4 Hennessey : Computer Architecture, Elsevier

5 Stallings : Computer Organization & Architecture, PE

6 Hayes : Computer Architecture & Organization,MGH

Paper : CA132203 Subject Name : COMPUTER BASED OPTIMISATION TECHNIQUES Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101 and CA132105 Solution of the global optimization problems based on a given fitness function. The optimization technique exploits genetic algorithms and is widely applicable to industrial and scientific tasks which include the effective use of neural network applications and complex computational packages in the distributed computer environment. Design and security of computer networks; pattern recognition; optimization of the oil and gas infrastructure; manufacturing electronic devices. Course Outcome:

1. Understand the operation research techniques and classify different ranges of problems of operation research.

2. The student will be able to formulate problems as abstract models which can be solved by generic algorithms.

3. The student will be able to use knowledge of operations research to solve transportation problems, assignment problem, dynamic programming.

Course Content:


1 1.1 Linear Programming: Mathematical model, assumptions of linear programming, Principles of simplex method, Revised simplex method, Applications, Duality, Dual Simplex method, sensitivity analysis

3

1.2 Special type of linear programming problems: Transportation and assignment problems.

3

2 Integer programming: introduction, Branch and bound techniques, Assignment and travelling salesman problems with algorithmic approach.

4

3 Dynamic programming: deterministic and probabilistic dynamic programming 3

4 Queueing model: Specification and measure of queueing systems, Structures of basic queueing system- Definition and classification of stochastic processes, Characteristics of a Queing system, Interpretation of a model, Single Channel waiting line- (M/M/1) (∞: FIFO), Single channel finite population queue (M/M/1): (C/FIFO), Multichannel Queing problem (Infinite population) (M/M/C): (∞: FIFO), Earlang Distribution (M/Ek/1): (∞: FIFO).

2



Books 1 Natarajan, Balasubramani, Tamilasari : Operations Research , Pearson

2 Gillett, B.G.: Introduction to operations research - A Computer oriented Algorithmic approach, McGraw-Hill.

3 Srinath, L.S: Linear programming, East-west, New Delhi.

4 Hiller, F.S. and Liberman, G.J.: Introduction to Operations Research, Holden Day In

5 Taha: Operations Research , Pearson

Paper : CA132204 Subject Name : GRAPH THEORY Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101and MCA CA132103 This Course includes various topics in Graph Theory including a selection from graph algorithms, connectivity, networks, planarity, graph colouring, graph symmetries. An introduction to Design Theory including a selection of topics from Latin squares, Steiner triple systems, balanced incomplete block designs, graph decompositions, projective and affine designs. This course serves as an introduction to major topics of modern enumerative and algebraic combinatory with emphasis on partition identities, young tableaux bijections, spanning trees in graphs, and random generation of combinatorial objects. There is some discussion of various applications and connections to other fields. Course Outcome:

1. Understand the concept of a graph and its use in scientific and engineering problems. 2. Identify different kinds of special graphs and its basic properties. 3. Represent the graph as a data structure and store the graph the same in computer. 4. Understand the basic principles of important graph algorithms such as finding shortest path,

directed or undirected cycle, minimum spanning tree, maximum flow and minimum cut, etc. 5. Understanding of the basic techniques and strategies of applying graph theory to solve advanced

data structures and other real world problems. Course Content:


1 Graph: Incidence and degree; Handshaking Lemma; Isomorphism; Sub graphs and Union of graphs; Connectedness; Walks, Paths and Circuits;

Components and Connectedness; Walks, Paths and Circuits; Components and Connectedness algorithms; Shortest Path Algorithms, Eulerian graph, Fleury's algorithm and Chinese postman problem; Hamiltonian graph - necessary and sufficient conditions; Travelling salesman; Bipartite graph.

3

2 Tree: Properties of trees; Pedant vertices in a tree; Centre of a tree; Rooted binary trees; Spanning trees - Spanning tree algorithms; Fundamental circuits; Spanning trees of a weighted graph; cut-sets and cut-vertices; Fundamental cut-sets; Connectivity and separativity; network flow; max-flow min-cut theorem.

2

3 3.1 Planner graph: Combinatorial and geometric duals; Kuratowski's graph; detection of planarity; Thickness and crossings

2

3.2 Matrix representations of graph: Incidence; Adjacency; matrices and their properties

2

4 Colourings: Chromatic number: Chromatic polynomial; The six and five colour theorems; The four colour problem.

1

5 5.1 Directed graphs: Binary relations; Directed graphs and connectedness; directed trees; Aborecence; Polish method; Touranaments.

2

5.2 Counting of labelled trees: Cayley's theorem; Counting methods; Polya theory. 2

6 Switching and coding theory and VLSI design 1

Books 1. Deo, N.: Graph Theory with Applications to Engineering and Computer Science

2 Agnarsson: Graph Theory ,Pearson

3 Harary : Graph Theory, PHI(EEE).

4 : West : Graph Theory, PHI

5 Chartran : Introduction To Graph Theory, TMH

Paper : CA132205 Subject Name : PROBABILITY AND STATISTICS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : NIL This course provides an elementary introduction to probability and statistics with applications. Topics include; basic probability models; combinatory; random variables; discrete and continuous probability



distributions; statistical estimation and testing. This course also provides an introduction to probability theory, one- and two-dimensional random variables and statistical inference, and shows how these concepts are applied in decision-making processes. The topics covered in this course include moment estimates of random variables, properties of sums of random variables, confidence intervals, hypothesis testing and linear regression. Course Outcome:

1. Ability to use the distributions. 2. Ability to test the hypothesis using suitable statistical test. 3. Ability to apply these tests in their projects and research work 4. Ability to calculate coefficient of correlation and regression lines 5. Ability to apply queuing theory in real life situations

Course Content:


1 Probability: Probability Theory: sample spaces; Events and probability; Discrete Probability; Union, intersection and compliment of events; conditional probability; Bay's Theorem; Random variables and Distribution: random variables, Discrete Probability Distribution - Binomial, Poisson, Geometric and Hyper geometric distributions; Density functions; Continuous probability distribution - Uniform, Exponential, Normal, Student’s t,Ӽ2, Beta and F - static. Expectations; Characteristics Functions.

7

2

Statistics: Basic statistics: Measures of central tendencies- Mean, Median, Mode; Measures of dispersion:-Range, Variance and Standard deviation: Frequency distributions and cumulative frequency distributions and cumulative frequency

3

3

Moments and Moment generating functions: Linear correlation coefficient: Linear and Non-linear regression; Multiple correlation and multi-regression;

3

4

Sampling: Theory of sampling: Population and sample; sampling survey methods and estimation. Statistical inference; testing of hypothesis and inference. Central limit theorem.

2

Books 1 Hogg,Tanis and Rao: Probability and Statistical Inference , Pearson

2 Mendenhall,Beaver, Beaver , Probability and Statistics, Cengage.

3 Yule, U.G., Kendall, M.G: An Introduction to the Theory of statistics, Chalies Griffin and Co.Ltd.

4 Milton : Introduction To Probability & Statistics, TMH

5 Das : Statistical Methods, combined edition, TMH

6 Leon & Garcia : Probability & Statistics, PE

Paper : CA132216 Subject Name : PROGRAMMING LABORATORY-II Marks : CE-20(WT 20), ST-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132201and CA132205 Course Outcome:

1. Write , compile and execute programs related to data structures. 2. Have a Clear idea about linear data structures such as stacks, queues and linked lists and their

manipulation using C/ C++ programs. 3. Have a Clear idea about non linear data structures trees and Graphs, and implement their

operations. 4. Implement different searching and sorting techniques. Compare different searching and sorting

techniques.

LAB PART PARA Laboratory Content Total Weeks

1(75%) 1.1 Concept of Object oriented programming in C++ 1

1.2 Simple link list, Stack, queues, 2

1.3 Single, double, circular Link lists, queues 2

1.4 graphs and trees, Several searching and sorting techniques, using Graphs and trees

3

1.5 B Tree, B+ Trees: Insertion deletion techniques 3

2(25%) Simple programming on Numerical Methods 4

Books As on CA132201and CA132205



MCA 3RD SEMESTER SYLLABUS

Paper : CA132301 Subject Name : SYSTEM SOFTWARE Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101, CA132102, CA132102 This course is an introduction to the design and implementation of system software. System software consists of a variety of programs that support the operation of a computer. System software was mainly (initially) written in assembly language. So the course will discuss assembly language, its programming and some most typical systems software including assembler (and linker, loader, macro processors) and compiler. The structure of a simple and a typical computer will be introduced and different operations/functions based on the structure will be discussed. This course covers the design and implementation of compiler and runtime systems for high-level languages, and examines the interaction between language design, compiler design, and runtime organization. Topics covered include lexical and syntactic analysis, handling of user-defined types and type-checking, context analysis, code generation and optimization, and memory management and runtime organization.

Course Outcome: 1. Acquire and Demonstrate knowledge in different phases and passes of Compiler, and

specifying different types of tokens by lexical analyzer, and also able to use the compiler tools like LEX, YACC, etc.

2. Construct the LL, SLR, CLR and LALR parse table. 3. Have the clear idea about assembler, linker, loader.

Course Content:


1 Overview: Definition and classification of system software. 1

2 Assemblers: Assembly language, Assembly process, Data structures, Macros and macroprocessors.

3

3 Linkers and loaders: Basic concepts, Static and dynamic linking, shared libraries, loaders, overlays. Case study of the Unix linking system, Windows DLLs, OLEs.

4

4 Compilers: Introduction: Phases of a compiler, Languages and grammer, Chomshy hierarchy. Lexical analysis: Finite automata, Lexical analyzer, Lexical analyzer generator (LEX). Parsing: Top-down and Bottom-up parsers, shift-reduce parser, recursive descent (operator precedence ) parser, LL(1), LR parsers, Parser generator (YACC).

5

5 System Software Tools: Text Editor- Overview of editing process, user interface, editor structure, interactive debugging system, debugging functions and capabilities, relationship with other parts of the system, user interface criteria. Eg: LaTeX

2

Books: 1. Aho,A.V., Sethi, and Ullman J.d: complier design.

2. Dhandhere, System programming and operating systems, Tata McGrawHill.

3. Leland.L.Beck, System software, An introduction to System Programming, Pearson Education

3. Louden, Compiler construction, Cengage

Paper : CA132302 Subject Name : DATABASE MANAGEMENT SYSTEM-I Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA 132201 To give the students the main concepts of database, design of the database, database models, ERD and normalization techniques, Physical Database design, query languages SQL. Distributed Database. Further the students have to practice and write some applications regarding the database. Course Outcome:

1. Know about the basic database concepts with its importance. 2. Know about the data models including Conceptual, representational data models. 3. Design databases pertained to a practical problems in organizational data management. 4. Design optimized databases using normalization. 5. Have an idea about transaction processing , concurrency control mechanisms. 6. Understand types of Data Base failures and Recovery techniques. 7. Have the knowledge about the SQL/PL-SQL to manipulate and retrieve data from a relational

database.

Course Content:




1 Introduction : What is DBMS , advantage of using DBMS ,data models (object based logical models , record based logical models ) , DBMS users , overall system structure

1

2 Entity Relationship models: ER diagrams , generalization , specialization ,

aggregation . Database models - Network model , Hierarchical model , and Relational model.

2

3 Relational Database : Underlying concepts , structure , study of relational languages (relational algebra , tuple relational calculus , domain relational calculus , SQL , QBE ) , storage and file structure , file organization . Indexing : Primary and secondary , B+ tree indexed files , B - tree indexed files , static and dynamic hashing , multiple key access , grid files , partitioned hashing .

3

4 Relational Data Base Design : Integrity constraints ( domain constraints , referential , assertions , triggers , functional dependencies ) , Normalization (using FDs , multivalued dependencies , join dependencies ) , Domain -key normal form.

2

5 Transactions : Concept , state , ACID properties , serializability and recoverability , testing for serializability . Concurrency Control : Lock - based , protocols , timestamp based protocols , validation based protocols , multiversion schemes , deadlock handling .

2

6 Recovery System : Log based recovery (deferred and immediate database modification ), checkpoints , shadow paging , recovery with concurrent with transactions , buffer managements in recovery , recovery from loss of non - volatile storage , logical undo logging , transaction rollback , restart recovery , fuzzy checkpointing.

3

Books: 1 Elmarsi and Navathe, fundamentals of Database Systems , Norsa publishing Company,1989

2 J.D . Ullman , Principles of Database Systems , Galgotia Publishing Private Limited

3 Silberschatz, Korth and Sudersan , Principles of Database Systems Mc GrawHill Publication

4 C.J .Date An Introduction to Database systems , Vol - I And Vol II Addison - Wesley Publishing Company.

Paper : CA132303 Subject : MANAGEMENT INFORMATION SYSTEM Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : NIL This course examines the role of information technology, and its management, in supporting an organization’s (internally- and externally-focused) operations and strategies. Particular attention is given to issues associated with the funding and building of business and technology architectures to enable efficient, effective, and adaptable operational, tactical and strategic actions. Course Outcome:

1. Describe the major technological, organizational, behavioral, and ethical issues facing today’s information systems professional.

2. Describe IT strategy formulation and explain its alignment with organizational strategy. 3. Conduct research on and describe, several current and emerging technologies and explain their

impact on corporate performance. 4. Explain the difference between supporting a business with technology and driving a business

with technology. 5. Describe ways in which technology can provide an organization with competitive advantages. 6. Describe how technology facilitates and enhances both operational and strategic decision

making in an organization.

Course Content:


1. MANAGEMENT INFORMATION SYSTEM (MIS) (20% credit): Organization and Information Systems, Changing Environment and its impact on Business - The IT/IS and its influence. The Organization: Structure, Managers and activities - Data, information and its attributes - The level of people and their information needs - Types of Decisions and information - Information System, categorization of information on the basis of nature and characteristics.

2



2 KINDS OF INFORMATION SYSTEMS (20% credit): Transaction Processing System (TPS) - Office Automation System (OAS) - Management Information System (MIS) - Decision Support System (DSS) and Group Decision Support System (GDSS) - Expert System (ES) - Executive Support System (EIS or ESS).

2

3 COMPUTER IN TELECOMMUNICATION AND NETWORKS (20% credit): Communication, Media, Modems & Channels - LAN, MAN & WAN - Network Topologies, Internet, Intranet and Extranet. Wireless technologies like Wi-Fi, Bluetooth and Wi-Max.

3

4 MANUFACTURING AND SERVICE SYSTEMS (10% credit): Information systems for Accounting, Finance, Production and Manufacturing, Marketing and HRM functions - IS in hospital, hotel, bank.

2

5 ENTERPRISE SYSTEM (10% credit): Enterprise Resources Planning (ERP): Features, selection criteria, merits, issues and challenges in Implementation - Supply Chain Management (SCM): Features, Modules in SCM - Customer Relationship Management (CRM): Phases. Knowledge Management and e-governance.

2

6 CHOICE OF IT (10% credit): Nature of IT decision - Strategic decision - Configuration design and evaluation Information technology implementation plan.

2

7 SECURITY AND ETHICAL CHALLENGES (10% credit): Ethical responsibilities of Business Professionals – Business, technology. Computer crime – Hacking, cyber theft, unauthorized use at work. Piracy – software and intellectual property. Privacy Issues and the Internet Privacy. Challenges – working condition, individuals. Health and Social Issues, Ergonomics and cyber terrorism.

2

Books 1. “Management Information Systems”, Kenneth J Laudon, Jane P. Laudon, Pearson/PHI,10/e, 2007

2. “Management Information Systems”, W. S. Jawadekar, Tata McGraw Hill Edition, 3/e, 2004

3. MIS by Ralph Stair

Ref. 1. “Introduction to Information System”, James A. O’ Brien, Tata McGraw Hill, 12th Edtion. 2. “Management Information Systems”, S.Sadagopan, PHI, 1/e, 2005 3. “Management Information Systems”, Effy Oz, Thomson Course Technology, 3/e, 2003 4. Corporate Information Strategy and Management”, Lynda M AppleGate, Robert D Austin et al, Tata McGraw Hill, 7th Edition.

Paper : CA132304 Subject Name : OBJECT ORIENTED PROGRAMMING AND DESIGN Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101 This course provides an introduction to software construction using an object-oriented approach.Acquire programming skills in connection with engineering science or technology. Object-oriented programming (OOP) is a programming paradigm that uses "objects" and their interactions to design applications and computer programs. It is based on several techniques, including inheritance, modularity, polymorphism, and encapsulation. Many modern programming languages now support OOP. From this module, we will learn the art of the object-oriented programming using JAVA Programming Language after having a background in the procedural paradigm that was introduced in the module “Programming Fundamentals". Course Outcome:

1. An understanding of the principles and practice of object oriented analysis and design in the construction of robust, maintainable programs which satisfy their requirements

2. Will be able to explain the object- oriented software development process, including object-oriented methodologies and work flows

3. To be able to design UML-diagrams viz. use case diagram, class diagram, object diagram, activity diagram, sequence diagram, state flow diagram

Course Content:


1 Part - I : Object Oriented Programming Object, Class. State and Behavior of an object, Attributes and Operations of a class. Encapsulation and Data Hiding: Interface, Implementation, Access modifiers. Inheritance: Reusing, Is_a relationship, Generalization, Specialization, superclass and subclass, Abstraction. Composition: Has_a relationship, Aggregation, Association, Composition. Multiplicity and cardinality. Polymorphism, getter & setter, Operator overloading. Local attributes, Object attributes, Class attributes. Constructor: Default

6



Constructor, Multiple Constructor, Constructor overloading. Error Handling.

2 2.1 2.2 2.3

Part – II : Object Oriented Design Class Model: Class and Object, Link and Association, Generalization and Inheritance, OCL. Enumeration, Multiplicity, Scope, Visibility, Association End Name, Ordering, Bags and Sequences, aggregation, Constraints on Objects, Generalization Sets and Links. State Model: Signal Events and Change Events; States, Transitions and Conditions. State Diagrams: Basic notations, One-shot State Diagrams, Activity Effects, Do-Activities, Entry and Exit Activities, Completion Transition, Sending Signals, Nested States, Concurrency and Synchronization of Concurrent

Activities. Interaction Model: Use Case Models with Include, Extend, Generalization, Sequence Models. Activity Models, sending & receiving signals, swimlanes, Object flows.

4

3 Part-III : Development Stages and Life Cycles System conception, Analysis, System design, Class design, Implementation, Testing, Training, Deployment and Maintenance.

5

Books 1. Matt Weisfeld: The Object Oriented Thought Process, Addison-Wesley.

2. Rambaugh et al.: Object Oriented Modeling and Design, PHI (EEE).

3. Rambaugh Booch, Jackobson : Unified Modelling Language Referance Mannual.

4. Barclay, Savage : Object-Oriented Design with UML and Java, Elsevier Butterworth- Heinemann

Paper : CA132305 Subject Name : COMPUTER GRAPHICS & MULTIMEDIA(CGM) Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre-requisite : CA132201 The basic principles and practices of interactive computer graphics and multimedia systems are covered in this introductory course. The design and implementation of state-of-the-art computer graphic rendering and visual multimedia systems are the main part of the course. The sub-topics of the course deal with specific input/output hardware devices and their technology, software and hardware standards, programming methods for implementing 3-dimensional graphical applications and interactive multimedia applications, and a study and evaluation of the effectiveness of graphic/multimedia communications. A large component of the class is the building of a large-scale application.

Course Outcome: 1. Students will demonstrate an understanding of contemporary graphics hardware. 2. To provide students with an understanding of the algorithms and theories that form the basis of

computer graphics and modeling(draw lines, circles and polygons) 3. To provide students with an understanding the application of transformation techniques to

scale, rotate and translate the object. 4. A competence to the Line clipping and Polygon Clipping techniques 5. To provide knowledge of different methods of enlarging visible portion of drawing 6. To give students skills necessary in the production of 3D models, lighting, and rendering. 7. Analyze and explain various technologies involved to support multimedia application

development. Course Content:


1 Display Devices: Line and point plotting Systems; Raster, vector, pixel and point plotters, Continual refresh and storage displays, Digital frame buffer , Plasma panel displays, Very high resolution devices , High - speed drawing , Display processors , Character generators , Color-display techniques ( Shadow mask and penetration CRT, color look - up tables , analog false colours , hard copy color printers ) .

2

2 Display Description : Screen co - ordinates , user co - ordinates ; Graphical data structures ( compressed incremental list, vector list, use of homogeneous co-ordinates ) ; Display code generation ; Graphical functions ; The view algorithms; Two - dimensional transformation .

3

3 Interactive Graphics : Pointing and positioning devices (cursor,light pen, digitizing tablet, the mouse , track balls) , Interactive graphical techniques. Positioning , Elastic lines , Inking , zooming , panning , clipping , scissoring,windowing,censoring .

2

4 Graphic Language Primitives constants , actions , operators 2

5 3 -D Graphics: Wire - frame perspective display, Perspective depth, Projective transformations, Hidden line and surface elimination, Transparent solids Shadowing . (GKS is to be used as the standard teaching tool).

2



6 Concept of Image Processing : Techniques and applications. Multimedia : Introduction to multimedia, Concept of hypertext and hypermedia, Multimedia applications, Basics of Animation, Music and sounds, Audio basic Concepts, Digital and Analog basic concepts. MIDI hardware, MIDI messages, MIDI files, Video: Basic Concepts, Analog and digital video. Imaging and graphics, Image formats, Graphic formats, File format, Image quality and Graphic systems, Compression, Image Compression, Sound Compression, Video Compression.

3

Books: 1 Computer Graphics : Hearn ID.and Baker.P.M. PHI

2 Principles of Interactive computer graghics : Newman W.Sproule, R.F. Mcgraw Hill

Paper : CA132316 Subject Name : PROGRAMMING LABORATORY-III Marks : CE-20(WT 20),ST-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132216 The module introduces the object-oriented approach and emphasizes on the concepts of classes, templates, friend classes, inheritance, and virtual functions. Program design will be addressed by the use of a number of Lab work and assignments in which complete programs will be developed from informal requirements expressed in English and this development will include the process of identifying objects, classes, and methods. Course Outcome: Java Programming :

1. Write, compile, and execute Java programs that may include basic data types and control flow constructs.

2. Write, compile and execute Java programs using object oriented features and exception handling and introduction to Applet Programming.

Course Content:

UNIT PARA Laboratory Content Total Weeks

1 (75%) 1.1 Concept of Object oriented programming in Java 2.6 2

1.2 Example of Inheritance, Multiple inheritance, Polymorphism related programs

5

1.3 Designing of DFD, Class Diagram with UML/SE Tools 4

2(25%) Programs related to Computer graphics 4

Books: As given in MCA 3.4 and MCA 3.5



MCA 4TH SEMESTER SYLLABUS Paper : CA132401 Subject Name : OPERATING SYSTEMS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132202 This course is an introduction to the theory and practice behind modern computer operating systems. Topics will include what an operating system does (and doesn't) do, system calls and interfaces, processes, concurrent programming, resource scheduling and management (of the CPU, memory, etc.), virtual memory, deadlocks, distributed systems and algorithms, networked computing and programming, and security. We will approach the subject from both a theoretical perspective (what are the abstractions and algorithms?) as well as a practical one (what are the mechanisms and how are they built?). Course Outcome:

1. Students should know the importance of the study Operating Systems and they must aware about the Popular Operating systems used in PC's, Mobiles and Servers.

2. Should know how To Protect and safegurd operating system from Virus,attacks and hacking.

3. Students should Know Programming for tuning and increasing perormance of the Operating systems. Batch Programming , Registry Edit, Performance monitoring and tuning)

4. Students must aquire a good idea about the design of an operating system, its use with different applications.

5. Students Should know the installations and tuning of Popular Operating Systems. 6. Latest Windows version , Service Pack utilities, Basic tools like Multimedia, latest Linux /

Fedora , Winows Server-2008, latest software packages and their tuning including DBMS software

Course Content:


1 Overview: Evolution, current status and future trends. Structural overview. 1

2 Process concepts: Process states, process control block, process scheduling algorithms. Support for concurrent processes: Mutual exclusion, shared data, critical sections, busy form of waiting, lock and unlock primitives, synchronization, block and wakeup. Inter process communication issues, primitives.

5

3 System Deadlock: Prevention, detection and avoidance. 2

4 Memory management: Contiguous and non-contiguous allocation, virtual memory, segmentation, paging, page scheduling and replacement algorithms.

4

5 File Systems: Management, protection mechanisms. I/O management, disk scheduling. Design of UNIX, LINUX- a case study. An overview of network and distributed operating systems.

3

Books: 1. Silberschatz A, Galvin P: Operating system concepts, 4th ed. AWP.

2. Milenkovic M.: Operating System- Concepts and Design, MGH Tanenbaum

3. Operating System- Design and Implementation, PHI (EEE).

4. Bach, M.: Design of the UNIX operating system, PHI (EEE).

5. Deitel, Deitel, choffnes, Operating systems, Pearson

Paper : CA132402 Subject name : SOFTWARE ENGINEERING. Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre-requisite : NIL To introduce the various stages of system level development and design, and the models used come up with real system SW creation. Development with reuse. Verification and validation: Test process. test planning. Testing strategies. Defect testing. Static verification. Engineering Design: Process. design strategies. Design quality. Architectural design: System structuring. Control models. Modular decomposition. Domain-specific architectures. Object oriented design. Function-oriented design. Real - time system design. User interface design. Course Outcome:

1. Apply software engineering principles and techniques to the software development life cycles. 2. Manage the development of software systems 3. Produce efficient, reliable, robust and cost-effective software solutions

4. Analyze, design, verify, validate, implement, apply, and maintain software systems 5. Work as an effective member or leader of software engineering teams



Course Content:

UNIT PARA CONTENT Weeks

1 Overview of system analysis and design(credit): Information systems concepts, system environment, elements of a system, characteristics and types, system development life cycle.

2

2 Introduction to software engineering : (credit) Basic concepts of SE, different phases of a software development life cycle, life cycle models, planning software project.

2

3 Software requirements engineering process(credit): Functional and non functional requirements, user requirements, system requirements, the SRS document,requirements elicitation and analysis, system modelling, system modelling tools, DFD,DD,UML etc.

2

4 Software design (credit): Concenpt of fundamental design approaches top down and bottom up, structured, object based and object oriented design, modular degign, architectural design, user interface design.

3

5 Software testing and maintenance (credit): Concepts of software testing, type of testing, testing strategies, post implementation review and software maintenance.

2

6 Software project and quality management (credit): Measures and measurements, cost estimation, cocomo model, scheduling, quality concepts, software reliability and quality standards.

1

7 Software risk management (credit):Software risks, risk strategies risk identification, risk projection, risk refinement.

2

Books 1.Awad.E.H..System analysis and design 2.Pressman. R.S..Software Engineering: A practitioner’s Approach. Mc Graw-Hill

3.Sommerville, Software Engineering, Pearson education

4. Rajib Mall; Software Engineering,.

Paper : CA132403 Subject name : DATABASE MANAGEMENT SYSTEM-II Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre-requisite : CA132302 This course covers advanced database management system design principles and techniques. The course materials will be drawn from both classic and recent research literature. Possible topics include access methods, query processing and optimization, transaction processing, distributed databases, object-oriented and object-relational databases. Course Outcome:

1. Know about storage structure of databases and different access paths to retrieve data from database.

2. Know about the optimization of query thus use it in program design. 3. Know about the data representation and manipulation in parallel and distributed databases. 4. Have an idea about object oriented databases and using OO and relational concept as Object

relational databases. 5. Understand the basic concepts of data security and integrity and practically apply the same in

real life situations. Course Content:


1 Query Processing : Study of algorithms for selection operations , sorting , join operations , projection , set operations , aggregation ; measurement of cost , evaluation of expressions, transformation of relational expressions , optimization techniques.

3

2 Parallel Databases : Introductory concepts ,partitioning techniques , interoperation parallelism - parallel sort (range partitioning sort, parallel external sort-merge ), parallel join ( partitioned join, fragment-and-replicate join, parallel hash join ), interoperation parallelism ( pipelined, independent ).

3

3 Distributed Databases : Replication and fragmentation, network transparency, join processing, distributed transaction processing, two-phase and three-phase commit protocols, handling failure, coordinator selection, concurrency control ( locking, timestamping ), deadlock handling ( centralized, fully distributed ), multidatabase systems.

3

4 Object Oriented Databases : Object classes, inheritance, DAG representation, 2



object identity and persistence ( brief introduction to ODMG C++ ), storage structure for object oriented databases.Security and Integrity : Violations, authorization, views, privileges, granting privileges, security specification in SQL.

5 Introductory concepts on following topics : Data mining and data warehousing, multimedia databases, distributed information systems, information retrieval systems, spatial and graphical databases, transactions processing monitors, transactional workflows, active and main memory databases. ( Example and case studies from ORACLE to be discuss in the course )

3

Books 1 Elmasari and Navathe, Fundamentals Of Database System, Narosa Publishing Company, 1989.

2 J.D. Ullman, principles of Database Systems, Galgotia Publishing Private Limited.

3 Silberschats, Kroth and Sudershan, Principles of Database Systems, McGraw Hill Publication.

4 C.J. Date, An Introduction to Database Systems, Vol-I and Vol-II, Addison-Wesley Publishing Company.

Paper : CA132404 Subject Name : COMPUTER NETWORKS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132102 Basic concepts in networking, the OSI model, error detection codes, flow control.Data communications, network architectures, communication protocols, data link control, medium access control; introduction to local area networks metropolitan area networks and wide area networks; introduction to Internet and TCP/IP. Course Outcome:

1. Able to explain the importance of data communications and the Internet in supporting business

communications and daily activities.

2. Able to explain how communication works in data networks and the Internet.

3. Recognize the different internetworking devices and their functions.

4. Explain the role of protocols in networking.

5. Analyze the services and features of the various layers of data networks.

6. Design, calculate, and apply subnet masks and addresses to fulfil networking requirements.

7. Analyze the features and operations of various application layer protocols such as Http, DNS, and SMTP.

Course Content:


1 Overview: Goals of networking, types, application, topologies, Switching techniques, Standards, performance issues. Network Architecture: ISO-OSI reference model, design philosophy, layer, protocol, interface, and service concepts. Layer-wise functionality

3

3 Physical Layer: Concepts of data transmission, modulation and multiplexing methods, modem, encoding methods, communication media, standard protocols. Medium Access Control sublayer – channel allocation, ALOHA, CSMA, CSMA/CD, token ring, token bus, Standard LAN/WAN, MAC Protocols. Protocols (IEEE 802.X), satellite networks.

3

4

Data link layer: Framing, error control techniques, data link protocols and their performance. Sliding window protocols, examples of DLL protocols.

3

5 Introduction to Network layer Overview of physical layer,data link layer & MAC. Network Layer: Routing, Congestion and deadlock control algorithms. Internetworking issues and devices, gateways, bridges and routers, IP v4/v6 & X. 25 protocols. Transport layer: Connection management, ICP, X.25. Sessionand presentation layer: Remote procedure call. Data Compression method. Data encryption and decryption. Application layer: Email, Remote login, File transfer, Network file system. Network security-issues, threats, attacks to networks, design of security system, recent trends in network security. Advance concepts in computer networking wireless network, ad hock networks etc.

4

Books:

1. Tanenbaum A.S., Computer Network, PHI (EEE).



2. Stalling, Data and Computer Communication, PHI (EEE).

3. Stevens, UNIX Network Programming, PHI (EEE)

4. Forouzan, Data communication and networking, 4th Edn, TMGH

Paper : CA132405 Subject Name : DESIGN AND ANALYSIS OF ALGORITHMS Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132101, CA132201 Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms and recurrences; greedy algorithms; data structures; dynamic programming; graph algorithms; and randomized algorithms. Course Outcome:

1. Able to learn about the basic properties of an algorithm and what are the important points one has to consider while designing an efficient and correct algorithm.

2. Able to analyze the running time of an algorithm for all possible input. 3. Able to learn how the running time of an algorithm increases with the increase in size of input

and how this running time can be described with the help of asymptotic notation. 4. Able to learn various methods of solving a recurrence of a divide and conquer algorithm 5. Able to learn and analyze a variety of algorithm design techniques such as dynamic

programming, greedy methods divide and conquer strategy. 6. Able learn about various classes of problems and will be able to differentiate between decision

problem and optimization problem

Course Content:


1 Algorithms: Models of Computation, Space and Time Complexity, Growth of functions, Upper and Lower bounds, Recurrences.

3

2 Paradigms: Divide -and -Conquer, Branch and Bound, Backtracking, Dynamic Programming, Greedy Method.

2

3 Analysis of sorting, Graph & Data Structures based Algorithms: 3

3.1 Sorting algorithms: Insertion sort, Merge sort, Heap sort, Quick sort, Linear Time sorting algorithms(Count sort, Radix sort, Bucket sort)

3.2 Graph Algorithms: BFS, DFS, Topological sort, Spanning trees 2

3.3 Data Structure based Algorithms : Hashing algorithms, BST, B-Trees 3

4 Introduction to NP-Completeness: The class P, The class NP, Polynomial reducibility NP- Completeness, NP-Completeness proofs. Examples of NP-Complete problems.

2

Books: 1. Cormen, Leiserson, Rivest, Stein: Introduction to algorithms, PHI

2. Manber, Udi: Introduction to Algorithms. 2/e Addison-Wesley,1994

3 Aho, Hopcroft and Ullman: The Design and Analysis of Computer Algorithms, PE

4 G. Brassard and P. Bratley: Fundamentals of Algorithms. Prentice Hall, 1995.

5 Dasgupta : Algorithms, TMH

Paper : CA132416 Subject Name : PROGRAMMING LABORATORY-IV Marks : CE-20(WT 20), ST-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132206 Course Outcome: Oracle PL/SQL:

1. Understand the basic concepts of relational databases 2. Will be able to write and execute DDL statements and DML statements which includes

constraints, using aggregate functions & joins 3. Will be able to write and execute Store Procedure , Cursor and Trigger. 4. Build dynamic web pages with embedded SQL. 5. Basic UNIX command and shell programming.

UNIT PARA Laboratory Content Total Weeks

1 (75%) Design of relational databases in SQL Server, Oracle Server, Extensive use of SQL and PL/SQL statements

11

2(25%) Unix/Linux shell programming. 4



MCA 5TH SEMESTER SYLLABUS Paper : CA132501 Subject Name : DATA WAREHOUSING & DATA MINING Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Data Mining studies algorithms and computational paradigms that allow computers to find patterns and regularities in databases, perform prediction and forecasting, and generally improve their performance through interaction with data. It is currently regarded as the key element of a more general process called Knowledge Discovery that deals with extracting useful knowledge from raw data. The knowledge discovery process includes data selection, cleaning, coding, using different statistical, pattern recognition and machine learning techniques, and reporting and visualization of the generated structures. The course will cover all these issues and will illustrate the whole process by examples of practical applications. The students will use recent Data Mining software Course Outcome:

1. The students will be able to develop practical work of Data Mining(DM) techniques and design hypotheses based on the analysis to conceptualize a DM solution to a practical problem.

2. The students will be able to discuss the role of data warehousing and enterprise intelligence in

industry and government. 3. The students can be able to evaluate and select appropriate data-mining algorithms and apply,

and interpret and report the output appropriately. 4. The students will be able to explore OLAP, and devise efficient & cost effective methods for

maintaining Data Warehouses Course Content:


1 Introduction to Data Warehousing: Basic Concepts: Characteristics of Data Warehouse, DSS, Differences between Data Warehouse and Database Systems, Data Warehouse architecture and its components, Metadata, Data mart, Warehouse versus Data Mining (OLTP & OLAP), OLAP tools, Data Cubes, Multidimensional Data.

2

2 Introduction to Data Mining: Basic Concepts: Data Mining, Kinds of data that can be mined, Data Mining versus Database Systems, KDD, Data Preparation, Cleaning and Visualization. Data Mining Techniques: Association Rule: What is an association rule? Mining association rules, Frequent sets and Border sets, Algorithms for mining association rules- Apriori Algorithm, Pincer-Search Algorithm, Border Algorithm, FP-Tree Growth Algorithm, generalized association rule, association rule with item constraints

3

3 Clustering: Hierarchical versus Partitional clustering, Types of data in clustering, Partitional Algorithms- K-means, K-medoids, PAM, CLARA, CLARANS. Density based clustering algorithm- DBSCAN. Hierarchical Algorithms- BIRCH, CURE. Categorical clustering Algorithms- ROCK, CACTUS

3

4 Decision Trees: Introduction, Tree construction principle, Decision tree generation algorithm- CART, ID3, C4.5

1

5 Other Techniques for Data Mining: Concepts of Genetic Algorithms, Artificial Neural Network, Rough Sets and their application in the domain of Data Mining. Introduction to Web Mining, Text Mining and Temporal Data Mining

2

6 Issues and challenges in Data mining, Data mining application areas (example with practical case studies)

1

Books :

1 Data Mining Techniques, By Arun K. Pujari (University Press)

2 Data Mining Concepts and Techniques, By Han and Kamber (Morgan Kaufmann and Harcourt India)

3 Data Mining, By Peter Adriaans, Dolf Zantinge (Pearson Education Asia)

4 Algorithms for Clustering Data, By K. Jain and R. C. Dukes (Prentice Hall)

5 Data Warehouse, from Architecture to Implementation.- by Barry Devlin ( Addison Wesley language )

6 Data Warehousing in the Real World. By Sam Anahory, Dennis Murray (Pearson Education Asia)

Paper : CA132502 Subject Name : WEB TECHNOLOGY Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Pre – requisite : CA132403



Quick review of the Internet and Internet programming concepts, Web Servers and Web Application Servers, Design Methodologies with concentration on Object-Oriented concepts, Client-Side Programming, Server-Side Programming, Active Server Pages, Database Connectivity to web applications, Adding Dynamic content to web applications, Programming Common Gateway Interfaces, Programming the User Interface for the web applications. Understand, analyze and apply the role of languages like HTML, DHTML, CSS, XML, Javascript, VBScript, ASP, PHP and protocols in the workings of the web and web applications. Course Outcome:

1. Differentiate between client side web technologies and server side web technologies 2. Understand, analyze and apply the role of languages like HTML, DHTML, CSS, XML, JavaScript,

VBScript, ASP, PHP, JSP, Servlet and protocols in the workings of the web and web applications 3. Analyze a web project and identify its elements and attributes in comparison to traditional

projects. 4. Understand, analyze and build customize web sites and web applications Course Content:


1 Introduction to Internet Technology: Overview of Networking protocols and OSI Model. Internetworking concepts

2

2 Internet Protocols and Architecture and Background work: TCP/IP, IP, IP Addressing & Datagrams, IPv6, ARP, RARP, BOOTP, DHCP, ICMP. TCP, UDP, Ports & Sockets, TCP Connection & properties, TCP Segment format, Active & Passive Open Connections. DNS, DNS Server, Email Architecture, SMTP, POP & IMAP, FTP, TFTP. WWW, web server & web browser, HTTP commands & interaction, Architecture of Web browser, CGI, TELNET.

4

3 Web Development Technologies: Client Side Programming: Different client-side scripting: JavaScript, VBScript etc. HTML; CSS, XML, DTD; Server Side Programming: Servlets, JSP, Java beans, EJB, Struts, JSF, ASP.NET; Web Servers: IIS, Apache; RIA, Ajax; Types of web pages, ActiveX Controls, Java Applets, Tiers in web applications; Database connectivity: ODBC, JDBC.

4

4 Web Security: Confidentiality, authentication, Integrity, Non-repudiation, Access Control, and Availability. Sniffing, spoofing, phishing, pharming. Web Security: Cryptography, Cipher Text, Digital Signature, Digital Certificates. Network Security: SSL, Firewalls, IP Security, VPN.

2

5 Web Services & Middleware: Concept, RPC, CTM, Message Queuing. DCOM & CORBA: basic interface, Architecture; ORB, IDL, IIOP, RMI. Web Services.

2

6 Wireless Internet: Mobile IP, addressing and its work. WAP: Architecture, Gateway.

1

Books

1 Achyut S Godbole, Atul Kahate: Wed Technologies – TCP/IP to Internet Architectures, Tata McGraw Hill.

2 Deitel & Deitel: Web Technology, Pearson Education

3 Raj Kamal: Internet and Web Technologies, Tata McGraw Hill

Paper : CA132503 Subject Name : ARTIFICIAL INTELLIGENCE Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60)

This course will introduce the basic principles in artificial intelligence research. It will cover simple representation schemes, problem solving paradigms, constraint propagation, and search strategies. Areas of application such as knowledge representation, natural language processing, expert systems, vision and robotics will be explored. The LISP programming language will also be introduced.

Course Outcome:

1. Demonstrate an understanding of agent-based AI architectures. 2. Demonstrate an understanding of various searching algorithms commonly used in artificial

intelligence software. 3. Demonstrate an understanding of adversarial search and game-playing agents. 4. Demonstrate an understanding of logic-based agents. 5. Demonstrate an understanding of machine learning.

Course Content:


1 Introduction to the object and goal of artificial intelligence: Aim and scope of the artificial intelligence, problem space and problem characteristics, state space representation.

1

2 Problem solving techniques: Generate and test, hill climbing , search problem reduction techniques, constraint propagation, means-end-analysis, heuristics

2



search techniques and heuristic problem solving .

3 Game playing: And or graph search, game trees and associated techniques, minimax and alpha beta pruning. Some case studies.

1

4 Knowledge representation and inferencing : Procedural and deductive approaches production system formalism, predicate logic (first order and second order), Rule based system, schematics net, conceptual dependencies, conceptual path, frames,

scripts associated inferencing mechanism. Resolution in predicate logic, unification , natural deduction theorem proving, forward and backward deduction.

2

5 Different techniques for reasoning under uncertainty, monotics and non monotic reasoning. Constraint satisfaction problem

2

6 Rule based system and expert system: Domain exploration, meta language ,expertise, transfer self explaining system case studies(dendral, mycin)

2

7 Introduction to neural network: Defination and representation of artificial neuron and its analogy with biological neuron, basic concepts of three layer neural-net and learning by back propagation.

2

8 Basic syntax and semantics of lips and prolog. Programming exercise from ai in lips.

2

Books: 1 Artficial Intelligence By Patrick,Henry,Winston , Pearson Education

2 Introduction to Artificial Intelligence By Charniak, Mc Dermott, Pearson Education.

3 Artificial Intelligence By Nilson

4 Artificial Intelligence By Rich and Night

Paper : CA132504 Subject : ELECTIVE-I ( Any one subject from the list ) Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Elective subjects :

a) Microprocessor and Embedded Design(MED)

b) Distributed Systems(DS)

c) Image Processing(IP) d) Expert Systems(ES) e) Biologically Implied Computing(BIC)

(a) MICROPROCESSOR AND EMBEDDED DESIGN(MED)

Course Outcome:

1. Students should be able to solve basic binary math operations using the microprocessor.

2. Students should be able to demonstrate programming proficiency using the various addressing modes and data

transfer instructions of the target microprocessor.

3. Students should be able to program using the capabilities of the stack, the program counter, and the status register

and show how these are used to execute a machine code program.

4. Students should be able to apply knowledge of the microprocessor’s internal registers and operations by use of a

PC based microprocessor simulator.

5. Students should be able to design electrical circuitry to the Microprocessor I/O ports in order to interface the

processor to external devices.

6. Students should be able to write assembly language programs and download the machine code that will provide solutions real-world control problems such as fluid level control, temperature control, and batch processes.


1 Introduction(5%) : Introduction to microprocessors, its evolution, use and application.

2 Microprocessor Architecture(25%) : 8088 MPU, Signal description, memory organization, Instruction processing in 8085/8088 MPU, 80486-SX/DX 32 bit processors architecture, addressing modes of 80386, 80486-SX/DX 32 bit processors, data types, paging and segmentation. Introduction to Pentium Processors, its difference with 80486/80386.

3 Advanced Programming(10%) : Stack and subroutines, Data conversion, BCD arithmetic, Interrupt and Interrupt service routine, Interrupt codes of 8085/8088

4 Peripheral and Interfacing(20%) : Basic peripherals and their interfacing with 8085/8088, Dynamic RAM interfacing, Interfacing I/O Ports, PIUO 8255 and its operation modes, Interfacing with D/A and A/D Convertors.

5 Embedded Design(40%) : Case study - I : Introduction to Microprocessor based concept, Design of a Aluminium Smelter shell: General process Description, Normal Control electrolysis cell,Cell abnormalities in an aluminium shelter, Brief description of the control laws, salient issues in Design, Result and



(b) DISTRIBUTED SYSTEMS(DS) Course Outcome:

1. Differentiate between distributed systems and computer network 2. Learn the advantage of designing a distributed system and what the desired properties of such

systems. 3. Learn the concept of physical and logical clock and the problem of synchronization. 4. Learn the various techniques of clock synchronization and various algorithms to find coordinator

of a system. 5. Learn the role of middleware in distributed systems 6. Learn how we can make a fault tolerant distributed system

Course Content:

UNIT

PARA Content Weeks

1. INTRODUCTION : Introduction to Distributed systems-examples of distributed systems, challenges-architectural models- fundamental models - Introduction to interprocess communications-external data representation and marshalling- client server communication-group communication – Case study: IPC in UNIX

3

2. DISTRIBUTED OBJECT AND FILE SYSTEM : Introduction - Communication between distributed objects - Remote procedure call - Events and notifications - Java RMI case Study - Introduction to DFS - File service architecture - Sun network file system - Introduction to Name Services- Name services and DNS - Directory and directory services

3

3 DISTRIBUTED OPERATING SYSTEM SUPPORT: The operating system layer – Protection - Process and threads - Communication and invocation - Operating system architecture - Introduction to time and global states - Clocks, Events and Process states - Synchronizing physical clocks - Logical time and logical clocks - Global states - Distributed debugging – Distributed mutual exclusion.

3

4 TRANSACTION AND CONCURRENCY CONTROL – DISTRIBUTED TRANSACTIONS : Transactions – Nested transaction – Locks - Optimistic concurrency control - Timestamp ordering - Comparison of methods for concurrency control - Introduction to distributed transactions - Flat and nested distributed transactions - Atomic commit protocols - Concurrency control in distributed transactions - Distributed deadlocks - Transaction recovery

3

5. SECURITY AND REPLICATION : Overview of security techniques - Cryptographic algorithms – Digital signatures - Cryptography pragmatics – Replication - System model and group communications – Fault tolerant services – Highly available services – Transactions with replicated data

3

Books

1. . George Coulouris, Jean Dollimore, Tim Kindberg “Distributed Systems Concepts and Design” Third Edition – 2002- Pearson Education Asia.

2 Principle and paradigms,Distributed System by Tanenbaum,PHI

(c) IMAGE PROCESSING

Course Outcomes: 1. Understand image formation and the role human visual system plays in perception of gray and

color image data. 2. Get broad exposure to and understanding of various applications of image processing in

industry, medicine, and defense. 3. Learn the signal processing algorithms and techniques in image enhancement and image

restoration. 4. Acquire an appreciation for the image processing issues and techniques and be able to apply

these techniques to real world problems.

discussion.

6 Introduction to Micro controllers : Intel family 8 bit Micro controllers, Architecture of 8051, Signal description of 8051, Register set of 8051, memory and I/O addressing, interrupts, Design of 8051 micro controller based length measurement system for continuity rolling cloth paper.

BOOKS:

1 Gaonkar : Microprocessor Architecture, Programming and applications with the 8085/8080A : Latest Edition, WILEY EASTERN LIMITED

2 Todd D.Morton : Embedded Microcontrollers, PEARSON EDUCATION.

3 Mazidi Mazidi : The 8051 Microcontroller & Embedded Systems,PEARSON EDUCATION



5. Be able to conduct independent study and analysis of image processing problems and techniques.


1 Image digital representation. Elements of visual perception. Sampling and quantisation. Image processing system elements.

3

2 Fourier transforms. Extension to 2· D, OCR, Walsh, Hadamard transforms 3

3 Enhancement and segmentation: Histogram modification. Smoothing, sharpening. Thresholding. Edge detection. Segmentation. Point and region dependent techniques.

3

4 Image encoding: Fidelity criteria. Transform compression. KL, Fourier, DCT. Spatial compression, Run length coding. Huffman and contour coding.

3

5 Restoration: Models. Inverse filtering. Least squares filtering. Recursive filtering. 3

Books: 1. Gonslaez, et.a1, "Digital Image Processing", Addison Wesley, Reading, M.A., 1990.

D) EXPERT SYSTEM Course Outcomes:

Unit PARA Course Content Week

01

Introduction to Expert System: What are Expert Systems, Features of Expert System, features of good Expert System, Role of human in Expert System, Expert System organization, Difference between expert system and conventional program, Basic activities of expert system and the areas in which they solve problems, Prospector systems-features, working principle.

1

02 Expert System Tools : Knowledge representation in expert systems-using rules semantic nets, frames, Types of tools available for expert system building and how they are used, Stages in the development of expert system tools, Examples of knowledge engineering

2

03 Building an Expert Systems: Necessary requirements for expert systems development, Justification for expert system development, Task in building expert systems, Stages of expert system development, Choosing a tool for building expert system, Acquiring knowledge from the experts, Examples of the expert system building process,examples of expert system used in different areas.

2

04 Difficulties in developing an expert system : Common pitfalls in-planning an expert system, Scaling with the domain expert during development process.

2

05 Neural Network Introduction: Biological neural networks-neuron physiology, eye’s neural network, Artificial neuron models, Neural net architecture (Topologies), Learning in ANN, Characteristics of ANN

1

06 Supervised Learning: Single layer networks-perceptrons, Linear separability, Perceptron training algorithm, Modifications multi-layer network-multi-layer discrimination, back propagation algorithm, Classification using back propagation algorithm, Application of back propagation algorithm, Adaptive multiplier networks-algorithm, boosting, prediction network, radial basis functions

2

07 Unsupervised Learning: Winner-take all networks, Learning vector quantiser, Co-inter propagation networks, Adaptive response theory

1

08 Associative Networks: Non-interactive procedures for association, Hopfield networks, Optimization using Hopfield networks, Brain state in a box network, Boltzmann machines, Hetero associates

2

09 Fuzzy Logic : Propositional logic, Membership functions, Fuzzy logic, Fuzzy rule generation, De-fuzzification, Time dependent fuzzy logic, Temporal fuzzy logics, Case study-to use fuzzy logic for processes control problem

2

Text Book : 1. Stamatios V. Kartalopolous, .Understanding Neural Network and Fuzzy Logic., PHI Pvt Ltd. 2. Kishan Mehrotra, .Elements of ANN., 2nd Editon, Penram International Publishing (I) Pvt. Ltd. Reference Books: Donald A. Waterman, .A Guide to Expert Systems., Addison-Wesley Publishing Company.

f) BIOLOGICALLY IMPLIED COMPUTING (BIC)

Course Outcomes:


01 Introduction: Sequencing, Molecular Biology and Bioinformatics, Biological

sequence/structure, Genomoe Projects, Pattern Recognition and prediction, Folding problem, Sequence Analysis, Homology and Analogy, Bioinformatics Applications,

2



Central Dogma of Molecular Biology

02 Information Resources: Biological databases, Primary Sequence databases, Protein sequence databases, Secondary databases, Protein pattern databases, and Structure classification databases DNA sequence databases, specialized genomic resources

2

03 DNA Sequence Analysis: Importance of DNA analysis, Gene Structure and DNA sequences, Features of DNA sequence analysis, EST (Expressed Sequence Tag) searches, Gene Hunting, Profile of a cell, EST analysis, Effects of EST data on DNA databases, The Human Genome Project

2

04 Pair Wise Alignment Techniques: Database Searching, Alphabets and complexity, algorithm and programs, comparing two sequences, sub-sequences, Identity and similarity, The Dot plot, Local and Global similarity, Different alignment techniques, Scoring Matrices, Dynamic Programming, Pair wise database searching

2

05 5.1 Multiple sequence alignment: Definition and goal, The consensus, Computational complexity, Manual methods, Simultaneous methods, Progressive methods, Databases of Multiple alignments, and searching, Applications of Multiple Sequence alignment

2

5.2 Phylogenetic Analysis: Methods of Phylogenetic Analysis, Tree Evaluation, Problems in Phylogenetic analysis, Tools for Phylogenetic Analysis

2

06 Secondary database Searching: Importance and need of secondary database searches, secondary database structure and building a sequence search protocol

1

07

Gene Expression and Microarrays : Introduction, DNA Microarrays, Clustering Gene Expression Profiles, Data Sources and tools, Applications

1

08 Analysis Packages: Analysis Package structure, commercial databases, commercial software, comprehensive packages, packages specializing in DNA analysis, Intranet Packages, Internet Packages.

1

Text Books: 1. Introduction to Bioinformatics,T K Attwood & D J Parry-Smith, Essex: Addison WesleyLongman, 1999. Reference Books: 1. Bioinformatics For Dummies Jean-Michel Claveriw, Cerdric Notredame, WILEY DreamTech India Pvt. Ltd, 2/e 2006. 2. Sequence Analysis in A Nutshell, Scott Markel &Darryl Leon, O’REILLY, 1/e, 2003.

Paper : CA132505 Subject : ELECTIVE-II (Any one subject from the list) Marks : CE-20(WT 20), MSE-50(WT 20), ESE-100(WT 60) Elective subjects:

a) Cryptography and Network Security (CNS) b) Information Storage and Retrieval (ISR) c) Software Project Development (SPD) d) Mobile Computing e) Multimedia Systems(MS)

f) Simulation and Modeling(SM) g) Remote Sensing and GIS(RSG) h) Programming Language and

Paradigms(PLP)

(a) CRYPTOGRAPHY AND NETWORK SECURITY (CNS)

Course Outcomes: 1. To be able to identify common network security vulnerabilities/attacks; explain the foundations

of Cryptography and network security. 2. To be able to evaluate the risks and threats to networked computers. 3. To be able to demonstrate detailed knowledge of the role of encryption to protect data. 4. To be able to analyze security issues arising from the use of certain types of technologies.


1. Course Introduction and terminology 1

2. Conventional Cryptography : Definitions, Classical Cryptography, Galois Field, Unicity Distance, Entropy, Perfect Secrecy DES, AES and others symmetric cryptography.

3

3 Asymmetric Cryptography: Number Theory, public key cryptography, RSA and Elliptic Curve Cryptography, Key management using symmetric and asymmetric key.

3

4 Authentication: Message authentications and hash functions, hash algorithms, Digital Signatures and Authentication Protocols.

3

5. Operating System security : Computer systems overview, Buffer overflow, Securing UNIX

2

6 Network and System Security: Vulnerability, Monitoring/Sniffing, Spoofing b.



Firewalls, Intrusion Detection PGP, Kerberos ,IPSec, SSL 3

Books

W Stallings, “Cryptography and Network Security: Principles and Practice, 4/e”, Prentice Hall, 2006.

1 B. Schneier, Applied Cryptography, 2nd Ed, John Wiley & Sons, Inc., 1996.

2 A. Menezes, P. van Oorshot and S. Vanstone, Handbook of Applied Cryptogrphy, CRC Press, 1997.

3 C. Kauffman, R. Perham and M. Speciner, Network Security: Private Communication in a Public World, Prentice-Hall, 1994.

4 H. C. A. van Tilborg, Fundamentals of Cryptology, Kluwer Academic Publishers, 2000.

(b) INFORMATION STORAGE AND RETRIEVAL (ISR) Course Outcome:

1. Acquire and demonstrate knowledge the techniques of preparing data and information for storage.

2. The student will learn learn to store data and information in appropriate formats and in suitable media

3. Student acquires skills in retrieving data and information from an information system.


1. Introduction: Definition, Objectives, Functional Overview, Relationship to DBMS, Digital libraries and Data Warehouses.

2

2. Information Retrieval System Capabilities: Search, Browse, Miscellaneous. Cataloguing and Indexing: Objectives, Indexing Process, Automatic Indexing, information Extraction.

3

3 Data Structures: Introduction, Stemming Algorithms, Inverted file structures, N-gram data structure, PAT data structure, Signature file structure, Hypertext data

structure.

3

4 Automatic Indexing: Classes of automatic indexing, Statistical indexing, Natural language, Concept indexing, Hypertext linkages

2

5. 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. Information Visualization: Introduction, Cognition and perception, Information visualization technologies.

3

6. 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.

2

Books 1. Kowalski, Gerald, Mark T Maybury: Information Retrieval Systems: Theory and Implementation, Kluwer Academic Press, 1997.

(c) SOFTWARE PROJECT MANAGEMENT Course Outcome:

1. Evaluate and select the most desirable projects. 2. Apply appropriate approaches to plan a new project. 3. Apply appropriate methodologies to develop a project schedule. 4. Develop a suitable budget for a new project. 5. Identify important risks facing and quality of project a new project.


1 FUNDAMENTALS :Conventional Software Management – Evolution of Software Economics – Improving Software Economics – Conventional versus Modern Software Project Management.

3

2 SOFTWARE MANAGEMENT PROCESS FRAMEWORK : Lifecycle Phases – Artifacts of the Process – Model Based Software Architectures – Workflows of the Process – Checkpoints of the Process

3

3 SOFTWARE MANAGEMENT DISCIPLINES : Iterative Process Planning – Organization and Responsibilities – Process Automation – Process Control and Process Instrumentation – Tailoring the Process.

3

4 MANAGED AND OPTIMIZED PROCESS Data Gathering and Analysis – Principles of Data Gathering – Data Gathering Process – Software Measures – Data Analysis – Managing Software Quality – Defect Prevention.

3

5 CASE STUDIES : COCOMO Cost Estimation Model – Change Metrics – CCPDS–R.. 3



Books:

1. Walker Royce “Software Project Management A Unified Framework”, Pearson Education,2004

2 Humphrey Watts, “Managing the software process”, Addison Wesley, 1989. (Unit IV)

3 Ramesh Gopalaswamy, “Managing Global Projects”, Tata McGraw Hill, 2001.

4 Bob Hughes, Mikecotterell, “Software Project Management”, 3rd Edition, Tata McGraw

d) MOBILE COMPUTING Course Outcomes:

1. Introduction of an advanced element of learning in the field of wireless communication. 2. The students to the concepts of wireless devices and mobile computing. 3. To introduce wireless communication and networking principles, that support connectivity to

cellular networks, wireless internet and sensor devices. 4. To understand the use of transaction and e-commerce principles over such devices to support

mobile business concepts 5. To appreciate the social and ethical issues of mobile computing, including privacy.

Unit PARA Content Week

01 1.1 Cellular concepts: Cell structure, frequency reuse, cell splitting, channel assignment, handoff, interference, capacity, power control;

1

1.2 Wireless Standards: Overview of 2G and 3G cellular standards. Wireless Standards: Overview of 2G and 3G cellular standards.

1

02 Signal propagation: Propagation mechanism- reflection, refraction, diffraction and scattering, large scale signal propagation and lognormal shadowing.

2

03 Fading channels : Multipath and small scale fading- Doppler shift, statistical multipath channel models, narrowband and wideband fading models, power delay profile, average and rms delay spread, coherence bandwidth and coherence time, flat and frequency selective fading, slow and fast fading, average fade duration and level crossing rate. Capacity of flat and frequency selective channels.

3

04 Antennas for mobile terminal: monopole antennas, PIFA, base station antennas and arrays.

1

05 Multiple access schemes: FDMA, TDMA, CDMA and SDMA. 1

06 Modulation schemes: BPSK, QPSK and variants, QAM, MSK and GMSK, multicarrier modulation, OFDM.

1

07 Receiver and Transmitter structure: Receiver structure: diversity receivers- selection and MRC receivers, RAKE receiver, equalization: linear-ZFE and adaptive, DFE. Transmit diversity-Alamouti scheme.

2

08 Time Signal Processing: MIMO and space time signal processing, spatial multiplexing, diversity/multiplexing tradeoff.

1

09 Performance measures: Outage, average snr, average symbol/bit error rate. 1

10 System examples: GSM, EDGE, GPRS, IS-95, CDMA 2000 and WCDMA. 1

Books : 1. J. Schiller, Mobile Communications, Addison Wesley. 2. A. Mehrotra , GSM System Engineering. 3. M. V. D. Heijden, M. Taylor, Understanding WAP, Artech House. 4. Charles Perkins, Mobile IP, Addison Wesley.

g) MULTIMEDIA SYSTEMS Course Outcomes:

1. Understand the characteristics of different media; understand the representations of different multimedia data; understand different data formats; be able to take into considerations in

multimedia system designs; 2. Understand the characteristics of human’s visual system; understand the characteristics of

human’s audio system; be able to take into considerations in multimedia techniques design and implementation;

3. Understand different compression principles; understand different compression techniques; understand different multimedia compression standards; be able to design and develop multimedia systems according to the requirements of multimedia applications.

4. Program multimedia data and be able to design and implement media applications;


01 Introduction to Multimedia System: Architecture and components, Multimedia distributed processing model, Synchronization, Orchestration and Quality of Service (QOS) architecture.

2

02 Audio and Speech: Data acquisition, Sampling and Quantization, Human Speech production mechanism, Digital model of speech production, Analysis and synthesis,

3



Psycho-acoustics, low bit rate speech compression, MPEG audio compression.

03 Images and Video: Image acquisition and representation, Composite video signal NTSC, PAL and SECAM video standards, Bilevel image compression standards: ITU (formerly CCITT) Group III and IV standards, JPEG image compression standards, MPEG video compression standards.

3

04 Multimedia Communication: Fundamentals of data communication and networking,

Bandwidth requirements of different media, Real time constraints: Audio latency, Video data rate, multimedia over LAN and WAN, Multimedia conferencing.

2

05 Hypermedia presentation: Authoring and Publishing, Linear and non-linear presentation, Structuring Information, Different approaches of authoring hypermedia documents, Hyper-media data models and standards.

2

06 Multimedia Information Systems: Operating system support for continuous media applications: limitations is usual OS, New OS support, Media stream protocol, file system support for continuous media, data models for multimedia and hypermedia information, content based retrieval of unstructured data.

3

Books: 1. Ralf Steinmetz and Klara Nahrstedt, Multimedia Systems, Springer. 2. J. D. Gibson, Multimedia Communications: Directions and Innovations, Springer.

Reference: 1. K. Sayood, Introduction to Data Compression, Morgan-Kaufmann. 2. Puri and T. Chen, Multimedia Systems, Standards, and Networks, Marcel Dekker. 3. Iain E.G. Richardson, H.264 and MPEG-4 Video Compression, John Wiley. 4. Borivoje Furht, Handbook of Multimedia Computing, CRC Press.

f) SIMULATION AND MODELING:


01 1.1 Introduction to Simulation: When simulation is the appropriate tool and when it is not appropriate; Advantages and disadvantages of Simulation; Areas of application; Systems and system environment.

1

1.2 Components of a system: Discrete and continuous systems; Model of a system; Types of Models; Discrete-Event System Simulation; Steps in a Simulation Study. Simulation examples: Simulation of queuing systems; Simulation of inventory systems; Other examples of simulation.

2

02 General principles, simulation software: Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance Algorithm, World Views, Manual simulation Using Event Scheduling; List processing. Simulation in Java; Simulation in GPSS.

2

03 Statistical models in simulation: Review of terminology and concepts; Useful statistical models; Discrete distributions; Continuous distributions; Poisson process; Empirical.

1

04 Queuing models: Characteristics of queuing systems; Queuing notation; Long-run measures of performance of queuing systems; Steady-state behavior of M/G/1 queue; Networks of queues.

2

05 Random-number generation, random-variant generation: Properties of random numbers; Generation of pseudo-random numbers; Techniques for generating random numbers; Tests for Random Numbers. Random-Variate Generation: Inverse transform technique; Acceptance-Rejection technique; Special properties.

2

06 Input modeling: Data Collection; Identifying the distribution with data; Parameter estimation; Goodness of Fit Tests; Fitting a non-stationary Poisson process; Selecting input models without data; Multivariate and Time-Series input models

2

07 Output analysis for a single model: Types of simulations with respect to output analysis; Stochastic nature of output data; Measures of performance and their estimation; Output analysis for terminating simulations; Output analysis for steady-state simulations.

2

08 Model Building : Model building, verification and validation; Verification of simulation models; Calibration and validation of models. Optimization via Simulation.

1

Text Book : 1. Discrete-Event System Simulation – Jerry Banks, John S. Carson II, Barry L. Nelson,

David M. Nicol, 4 th Edition, Pearson Education,. 2. Jerry Banks, John Carson, Barry Nelson, David Nicol, .Discrete Event System Simulation. 3. Averill Law, W. David Kelton, .Simulation Modeling and Analysis., McGRAWHILL

References: 1. Geffery Gordon, .System Simulation., PHI 2. Bernard Zeigler, Herbert Praehofer, Tag Gon Kim, .Theory of Modeling and 3. Simulation., Academic Press



4. Narsing Deo, .System Simulation with Digital Computer., PHI 5. Donald W. Body, .System Analysis and Modeling., Academic Press Harcourt India

g) REMOTE SENSING AND GIS

Course Outcomes:


01 Introduction of Remote Sensing - Electro Magnetic Spectrum, Physics of Remote Sensing- Effects of Atmosphere- Scattering, Different types of Absorption-Atmospheric window, Energy interaction with surface features of Spectral reflectance of vegetation, soil ,and water –atmospheric influence on spectral response patterns- multi concept in Remote sensing.

2

02 Data Acquisition : Types of Platforms – different types of aircrafts-Manned and Unmanned spacecrafts – sun synchronous and geo synchronous satellites – Types and characteristics of different platforms LANDSAT, SPOT, IRS,INSAT,IKONOS,QUICKBIRD etc - Photographic products, B/W, colour, colour IR film and their characteristics – resolving power of lens and film- Opto mechanical electro optical sensors – across track and along track scanners – multi spectral scanners and thermal scanners – geometric characteristics of scanner imagery - calibration of thermal scanners.

2

03 Microwave scatterometry – types of RADAR – SLAR – resolution - range and azimuth – real aperture and synthetic aperture RADAR. Characteristics of Microwave images topographic effect - different types of Remote Sensing platforms –airborne and space borne sensors – ERS, JERS, RADARSAT, RISAT - Scatterometer, Altimeter- LiDAR remote sensing, principles, applications.

2

04 Data Analysis : Resolution – Spatial, Spectral, Radiometric and temporal resolution- signal to noise ratio- data products and their characteristics - visual and digital interpretation –Basic principles of data processing –Radiometric correction –Image enhancement – Image classification – Principles of LiDAR, Aerial Laser Terrain Mapping.

2

05 Introduction to GIS – definitions, concept and history of developments in the field of information systems,Computer fundamentals for GIS, Hardware and software requirements for GIS, Coordinate System and Projections in GIS – Conic, cylindrical and planner

2

06 6.1 GIS Data Structure: Data structure and formats, Spatial data models – Raster and Vector, Data inputting in GIS, Data base design - editing and topology creation in GIS, Linkage between spatial and non spatial data.

1

6.2 Spatial data analysis – significance and type, Attribute Query, spatial query, Vector based spatial data analysis, Raster based spatial data analysis, Buffer analysis, Data quality and sources of errors, Integration of RS and GIS data, Digital Elevation Model, Network Analysis in GIS

1

07 Data analysis and modeling in GIS : Data analysis and modeling in GIS– types of GIS modeling,Decision support systems,Overview of image processing & GIS Packages – ARC GIS, ERDAS, MAP INFO, ILWIS, GEOMEDIA, IDRISI

2

08

Recent Trends in GIS : AM/FM, Virtual 3D GIS, OLAP, Internet GIS, Open GIS 1

Text Books: 1. Paul Curran P.J. Principles of Remote Sensing, ELBS; 1995. 2. Lillesand T.M., and Kiefer,R.W. Remote Sensing and Image interpretation, VI edition of John Wiley &

Sons-2000.

3. Anji Reddy, M. 2004 : Geoinformatics for environmental management.B.S. Publications 4. Chang.T.K. 2002 : Geographic Information Systems. Tata McGrawHill

Reference Books: 1. Charles Elachi and Jakob J. van Zyl , Introduction To The Physics and Techniques of Remote Sensing

, Wiley Series in Remote Sensing and Image Processing, 2006. 2. Ram Mohan Rao. 2002: Geographical Information Systems. Rawat Publication.

h) PROGRAMMING LANGUAGE AND PARADIGMS Course Outcomes:

1. Explain the paradigm of programming languages. 2. Analyze the different programming language scenario. Develop and design a software, satisfying

all principles of programming language. 3. Ability to program in different language paradigms and evaluate their relative benefits 4. Knowledge of, and ability to use, language features in current programming languages




01 Introduction: Overview of different programming paradigms e.g. imperative, object oriented, functional, logic and concurrent programming.

2

02 Syntax and semantics of programming languages: A quick overview of syntax specification and semiformal semantic specification using attribute grammar.

2

03 Imperative and OO Languages: Names, their scope, life and binding. Control-flow, control abstraction; in subprogram and exception handling. Primitive and

constructed data types, data abstraction, inheritance, type checking and polymorphism.

2

04 Functional Languages: Typed-calculus, higher order functions and types, evaluation strategies, type checking, implementation, case study.

2

05 Logic Programming Languages: Computing with relation, first-order logic, SLD-resolution, unification, sequencing of control, negation, implementation, case study.

2

06 Concurrency: Communication and synchronization, shared memory and message passing, safety and liveness properties, multithreaded program.

2

07 Formal Semantics: :Operational, denotational and axiomatic semantics of toy languages, languages with higher order constructs and types, recursive type, subtype, semantics of nondeterminism and concurrency.

3

Text Books : 1. Ravi Sethi, Programming Languages: Concepts and Constructs, Addison-Wesley. 2. T.W. Pratt and M. V. Zelkowitz: Programming Languages: Design and Implementation; PHI.

Reference Books: 1. W. Lloyd, Foundations of Logic Programming, Springer 1984. 2. Carlo Ghezzi, Mehdi Jazayeri, Programming Language Concepts, J. Wiley & sons. 3. E. Horowitz : Fundamentals of Programming Languages; Galgotia Publications Pvt Ltd. 4. K. C. Louden; Programming Languages-Principles and Practice; Thompson (2 nd Indian Edition);

Paper : CA132526 Subject Name : MINOR PROJECT Marks : Internal Evaluation( as per regulation) : 100; External Evaluation : 100 Course Outcome:

1. Take a real-world problem through the project definition, planning, design, implementation, and documentation phases of the software development cycle.

2. Apply principles of software engineering 3. Design and conduct experiments and analyze data to ensure conformance to technical specifications and

user requirements. 4. Demonstrate the ability to present and communicate technical material through a formal report

presentation and project demonstration.


1. 1. System development Project (based on data processing requirements in an organisation)

15

2. 2. Seminar on recent state of art of technology on Computer Science

Books

1. E M Awad, System Analysis and Design, PHI

MCA 6TH SEMESTER SYLLABUS

6th Semester subject Paper : CA132621 Subject Name : SYSTEM DEVELOPMENT PROJECT Marks : Internal Evaluation (as per regulation): 250; External Evaluation: 250 Course Outcome:

1. Analyze the real world problem for project development to fulfill the need of society. 2. Design a overview of their project for future development of final project and to develop research

attitude for implementing innovative project 3. Explain the role of software project in development of society 4. Use the existing technologies to find the scope of advancement for future research, optimizing

the issues of software engineering in project

Paper Subject Name Total Project duration and work hours

Credits



Subjects

CA132621 System Development Project (Internal Evaluation)

15 Weeks to be devoted for the project work

10

CA132622 System Development Project (External Evaluation)

15


Syllabus Master in Computer Applications (MCA) Assam Science … SYLLABUS-ASTU... · 2018. 12. 1. · Syllabus Master in Computer Applications (MCA) Assam Science and Technology University

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