UTTAR PRADESH TECHNICAL UNIVERSITYLUCKNOW

Syllabus

for

B.TECH. INFORMATION TECHNOLOGYof

Second Year

(Effective from the Session: 2014-15)

B.TECH INFORMATION TECHNOLOGYSTUDY & EVALUATION SCHEME

2nd Year SEMESTER III

S.No.

Course Code SubjectPeriods Evaluation Scheme

SubjectTotal

CreditL T P Sessional Exam ESECT TA Total

THEORY SUBJECT1 NAS-301/

NOE-031 toNOE-039

Mathematics III/ScienceBased Open Elective

3 1 0 30 20 50 100 150 4

2 NEC-309 Digital Logic Design 3 1 0 30 20 50 100 150 43 NCS-301 Data Structures Using C 3 1 0 30 20 50 100 150 44 NCS-302 Discrete Structures And

Graph Theory3 1 0 30 20 50 100 150 4

5 NHU-301/NHU-302

Industrial Psychology/Industrial Sociology

2 0 0 15 10 25 50 75 2

6 NCS-303 Computer Based NumericalAnd Statistical Techniques

2 1 0 15 10 25 50 75 3

AUC-001/AUC-002

Human Values & ProfessionalEthics/ Cyber Security

2 0 0 15 10 25 50 75*

PRACTICAL/DESIGN/DRAWING7 NEC 359 Digital Logic Design Lab 0 0 3 10 10 20 30 50 18 NCS 351 Data Structures Using C Lab 0 0 3 10 10 20 30 50 19 NCS 353 Numerical Techniques Lab 0 0 2 10 10 20 30 50 110 NCS 355 Advance Programming Lab 0 0 2 10 10 20 30 50 111 NGP 301 GP 50 50

TOTAL 18 5 10 1000 25

Science Based Open Elective:NOE031 Introduction to Soft Computing (Neural Network, Fuzzy Logic and Genetic

AlgorithmNOE032 Nano SciencesNOE033 Laser Systems and ApplicationsNOE034 Space SciencesNOE035 Polymer Science & TechnologyNOE036 Nuclear ScienceNOE037 Material ScienceNOE038 Discrete MathematicsNOE039 Applied Linear Algebra

*Human values & Professional Ethics /Cyber Security will be offered as a compulsory audit course for which passing marks are 30% in EndSemester Examination and 40% in aggregate.

B.TECH INFORMATION TECHNOLOGYSTUDY & EVALUATION SCHEME

2nd Year SEMESTER IV

S.No.

Course Code SubjectPeriods Evaluation Scheme

SubjectTotal

CreditL T P Sessional Exam ESECT TA Total

THEORY SUBJECT1 NOE-041 to

NOE-049/NAS-401

Science Based Open Elective/Mathematics III

3 1 0 30 20 50 100 150 4

2 EHU-401/EHU -402

Industrial Sociology/ IndustrialPsychology

2 0 0 15 10 25 50 75 2

3 NEC-408 Information Theory and Coding 3 1 0 30 20 50 100 150 44 NCS- 401 Operating System 3 1 0 30 20 50 100 150 45 NCS- 402 Theory Of Automata and Formal

Launguage3 1 0 30 20 50 100 150 4

6 NIT-401 Multimedia and Animation 2 1 0 15 10 25 50 75 37 AUC-002/

AUC-001Cyber Security /Human Values & Professional Ethics

2 0 0 15 10 25 50 75*

PRACTICAL/DESIGN/DRAWING7 NCS-451 Operating System Lab 0 0 3 10 10 20 30 50 1

8 NIT-451 Multimedia and Animation Lab 0 0 3 10 10 20 30 50 19 NCS-455 Functional and Logic

Programming Lab0 0 3 10 10 20 30 50 1

10 NIT-456 Colloquium 0 0 3 10 10 20 30 50 111 NGP-401 GP 50 50

TOTAL 18 5 10 1000 25Science Based Open Elective:NOE-041 Introduction to Soft Computing (Neural Network, Fuzzy Logic and Genetic AlgorithmNOE-042 Nano SciencesNOE-043 Laser Systems and ApplicationsNoE-044 Space SciencesNOE-045 Polymer Science & TechnologyNOE-046 Nuclear ScienceNOE-047 Material ScienceNOE-048 Discrete MathematicsNOE-049 Applied Linear Algebra*Human values & Professional Ethics /Cyber Security will be offered as a compulsory audit course for which passing marks are 30% in EndSemester Examination and 40% in aggregate.

NEC-309: DIGITAL LOGIC DESIGNUnit-IDigital Design and Binary Numbers:Binary Arithmetic, Negative Numbers and their Arithmetic, Floating point representation, Binary Codes, CyclicCodes, Error Detecting and Correcting Codes, Hamming Codes.Minterm and Maxterm Realization of Boolean Functions, Gate-level minimization: The map method up to fourvariable, don’t care conditions, SOP and POS simplification, NAND and NOR implementation, Quine Mc-Cluskey Method (Tabular method).Unit-IICombinational Logic:Combinational Circuits, Analysis Procedure, Design Procedure, Binary Adder-Subtractor, Code Converters,Parity Generators and Checkers, Decimal Adder, Binary Multiplier, Magnitude Comparator, Decoders,Encoders, Multiplexers, Hazards and Threshold LogicUnit-IIIMemory and Programmable Logic Devices:Semiconductor Memories, RAM, ROM, PLA, PAL, Memory System design.Unit-IVSynchronous Sequential Logic:Sequential Circuits, Storage Elements: Latches, Flip Flops, Analysis of Clocked Sequential circuits, statereduction and assignments, design procedure.Registers and Counters: Shift Registers, Ripple Counter, Synchronous Counter, Other Counters.Unit-VAsynchronous Sequential Logic: Analysis procedure, circuit with latches, design procedure, reduction of stateand flow table, race free state assignment, hazards.

References:1. M. Morris Mano and M. D. Ciletti, “Digital Design”, Pearson Education.2.A.K .Singh, “Foundation of Digital Electronics and Logic design”,New Age international.3.M. Rafiquzzaman, “Fundamentals of Digital Logic and Microcomputer Design”, Wiley Dreantech Publication.4.ZVI Kohavi, “Switching and Finite Automata theory” ,Tata McGraw-Hill.5.C.H Roth,Jr., “Fundamentals of Logic Design”, ,Jaico Publishing.6. Rajaraman & Radhakrishnan, “Digital Logic and Computer Organization”,PHI Learning Private Limited,Delhi India.7. Donald D. Givone, “Digital Principles and Design”, Tata MCGraw Hill.8. Marcovitz:Introduction to logic Design ,Tata Mcgraw-hill Education (India) Pvt. Ltd.

NCS-301: DATA STRUCTURES USING – CUnit - IIntroduction: Basic Terminology, Elementary Data Organization, Algorithm, Efficiency of an Algorithm, Timeand Space Complexity, Asymptotic notations: Big-Oh, Time-Space trade-off.Abstract Data Types (ADT)Arrays: Definition, Single and Multidimensional Arrays, Representation of Arrays: Row Major Order, andColumn Major Order, Application of arrays, Sparse Matrices and their representations.Linked lists: Array Implementation and Dynamic Implementation of Singly Linked Lists, Doubly Linked List,Circularly Linked List, Operations on a Linked List. Insertion, Deletion, Traversal, Polynomial Representationand Addition,Generalized Linked List .Unit – IIStacks: Abstract Data Type, Primitive Stack operations: Push & Pop, Array and Linked Implementation of Stackin C, Application of stack: Prefix and Postfix Expressions, Evaluation of postfix expression, Recursion, Towerof Hanoi Problem, Simulating Recursion, Principles of recursion,Tail recursion, Removal of recursion Queues,Operations on Queue: Create, Add, Delete, Full and Empty, Circular queues, Array and linked implementationof queues in C, Dequeue and Priority Queue.Unit – IIITrees: Basic terminology, Binary Trees, Binary Tree Representation: Array Representation and DynamicRepresentation, CompleteBinary Tree, Algebraic Expressions, Extended Binary Trees, Array and LinkedRepresentation of Binary trees, Tree Traversal algorithms: Inorder, Preorder and Postorder, Threaded Binarytrees, Traversing Threaded Binary trees, Huffman algorithm.Unit – IVGraphs: Terminology, Sequential and linked Representations of Graphs: Adjacency Matrices, Adjacency List,Adjacency Multi list, Graph Traversal : Depth First Search and Breadth First Search, Connected Component,

Spanning Trees, Minimum Cost Spanning Trees: Prims and Kruskal algorithm. Transistive Closure and ShortestPath algorithm: Warshal Algorithm and Dijikstra Algorithm, Introduction to Activity NetworksUnit – VSearching : Sequential search, Binary Search, Comparison and Analysis Internal Sorting: Insertion Sort,Selection, Bubble Sort, Quick Sort, Two Way Merge Sort, Heap Sort, Radix Sort, Practical consideration forInternal Sorting.Search Trees: Binary Search Trees(BST), Insertion and Deletion in BST, Complexity of Search Algorithm,AVL trees, Introduction to m-way Search Trees, B Trees & B+ Trees .Hashing: Hash Function, Collision Resolution StrategiesStorage Management: Garbage Collection and Compaction.

References :1. Aaron M. Tenenbaum,YedidyahLangsam and Moshe J. Augenstein “Data Structures Using C and C++”, PHILearning Private Limited, Delhi India2. Horowitz and Sahani, “Fundamentals of Data Structures”, Galgotia Publications Pvt Ltd Delhi India.3. A.K. Sharma ,Data Structure Using C, Pearson Education India.4. Rajesh K. Shukla, “Data Structure Using C and C++” Wiley Dreamtech Publication.5. Lipschutz, “Data Structures” Schaum’s Outline Series, Tata Mcgraw-hill Education (India) Pvt. Ltd .

6. Michael T. Goodrich, Roberto Tamassia, David M. Mount “Data Structures and Algorithms in C++”, WileyIndia.7. P.S. Deshpandey, “C and Datastructure”, Wiley Dreamtech Publication.8. R. Kruse etal, “Data Structures and Program Design in C”, Pearson Education9. Berztiss, A.T.: Data structures, Theory and Practice :, Academic Press.10. Jean Paul Trembley and Paul G. Sorenson, “An Introduction to Data Structures with applications”, McGrawHill.

NCS-302: DISCRETE STRUCTURES AND GRAPH THEORYUnit-ISet Theory: Introduction, Combination of sets, Multisets, Ordered pairs, Set Identities.Relations: Definition, Operations on relations, Properties of relations, Composite Relations,Equality of relations, Order of relations.Functions: Definition, Classification of functions, Operations on functions, Recursively definedfunctions.Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction withNonzero Base cases.Unit-IIAlgebraic Structures: Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange's theorem,Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms , Definition and elementaryproperties of Rings and Fields, Integers Modulo n.Unit-IIIPartial order sets: Definition, Partial order sets, Combination of partial order sets, Hasse diagram.Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and CompleteLattice,Morphisms of lattices.Boolean Algebra: Introduction, Axioms and Theorems of Boolean algebra, Algebraic manipulation of Booleanexpressions. Simplification of Boolean Functions, Karnaugh maps, Logic gates, Digital circuits and Booleanalgebra. Combinational and sequential CircuitsUnit-IVPropositional Logic: Proposition, well formed formula, Truth tables, Tautology, Satisfiability,Contradiction, Algebra of proposition, Theory of Inference ,Natural Deduction.Predicate Logic: First order predicate, well formed formula of predicate, quantifiers, Inferencetheory of predicate logic.Unit-VTrees : Definition, Binary tree, Binary tree traversal, Binary search tree.Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs,Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths, Graph coloring .Recurrence Relation & Generating function: Recursive definition of functions, Recursivealgorithms, Method of solving recurrences.Combinatorics: Introduction, Counting Techniques, Pigeonhole PrincipleReferences :1. Liu and Mohapatra, “Elements of Distcrete Mathematics”, McGraw Hill2. Jean Paul Trembley, R Manohar, Discrete Mathematical Structures with Application to

Computer Science, McGraw-Hill3. Y. N. Singh, “Discrete Mathematical Structures”, Wiley India, New Delhi, First Edition, August 2010.4. R.P. Grimaldi, Discrete and Combinatorial Mathematics, Addison Wesley,5. B. Kolman, R.C. Busby, and S.C. Ross, Discrete Mathematical Structures, PHI Learning Private Limited,Delhi India.6. Biswal ,“Discrete Mathematics and Graph Theory, PHI Learning Private Limited, Delhi India.7. Goodaire and Parmenter,“ Discrete Mathematics with Graph Theory”, PHI Learning Private Limited, DelhiIndia.8. Lipschutz “Discrete Mathematics” Mc Graw Hill9. Deo N., “Graph Theory with Applications to Engineering and Computer Science”, PHI Learning PrivateLimited, Delhi India.

NCS-303: Computer Based Numerical and Statistical Techniques

Unit –I :Computer Arithmetic and Errors: Floating Point Arithmetic, Machine epsilon, Round off Error,Chopping Error, Truncation Error, Associative and Distributive Law in Floating Point arithmetic, InherentError, Error propagation, Numerical InstabilityRoots of Equation: Secant Method, Newton Raphson Method and Fixed point Iteration Methods forSimple roots and derivation of their rate of convergence, Aitken Acceleration of Convergence, ModifiedNewton Raphson Method for Multiple roots, Birge-Vieta Method for Polynomials, Bairstrow Method forquadratic factors, Computer Algorithms of these methods.

Unit –IIInterpolation: Algorithms and Error Analysis of Lagrange and Newton divided difference interpolations,Relationship in various difference operators, Piecewise Linear Interpolation, Cubic Spline Interpolation,Natural Spline, Chebshev Polynomial Approximations, Lanczos Economization of Power SeriesCurve fitting: Linear and Non Linear Least Squares Approximation, ill Conditioning in Least SquaresMethods, Gram-Schmidt Process of Orthogonalization. Computer Algorithms of Least Square Curve Fitting

Unit – IIIDifferentiation: Methods based on Interpolation and Finite Differences, Richrdson ExtrapolationIntegration: Error Analysis of Trepezoidal and Simpson Methods, Newton Cotes Integration Methods,Guassian Integration Methods: Guass Legendre Method, Lobatto Integration Method and Radau IntegrationMethod, Error Terms in Integration Methods

Unit – IVSolution of Simultaneous Linear Algebraic Equations: Guass Elimination Method, ill ConditionedSystems, Condition Number, Successive Over Relaxation Method, Rate of ConvergenceSolution of Ordinary Differential equations: Single Step Methods-Runge-Kutta Second Order, ThirdOrder and Fourth Order Methods, Multi Step Method-Predictor- Corrector MethodStatistical Techniques: Statistical Hypotheses, Test of Hypotheses, Type-I and Type-II Errors, Level ofSignificance, Test involving Normal Distribution

Recommended Books:o Numerical Methods: M.K. Jain, S.R.K. Iyenger and R.K. Jaino Applied Numerical Analysis: Curtis F. Gerald and Patrick O. Wheatleyo Schaum's Outline of Theory and Problems of Statistics: Murray R. Spiegel

NEC-359: LOGIC DESIGN LAB

Objective: To understand the digital logic and create various systems by using these logics.1. Introduction to digital electronics lab- nomenclature of digital ICs, specifications, study of thedata sheet, concept of Vcc and ground, verification of the truth tables of logic gates using TTLICs.2. Implementation of the given Boolean function using logic gates in both SOP and POS forms.3. Verification of state tables of RS, JK, T and D flip-flops using NAND & NOR gates.4. Implementation and verification of Decoder/De-multiplexer and Encoder using logic gates.

5. Implementation of 4x1 multiplexer using logic gates.6. Implementation of 4-bit parallel adder using 7483 IC.7. Design, and verify the 4-bit synchronous counter.8. Design, and verify the 4-bit asynchronous counter.

Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.

NCS-351: DATA STRUCTURE USING C LAB

Program in C or C++ for following:1. To implement addition and multiplication of two 2D arrays.2. To transpose a 2D array.3. To implement stack using array.4. To implement queue using array.5. To implement circular queue using array.6. To implement stack using linked list.7. To implement queue using linked list.8. To implement circular queue using linked list.9. To implement binary tree using linked list.10. To implement binary search tree using linked list.11. To implement tree traversals using linked list.12. To implement BFS using linked list.13. To implement DFS using linked list.14. To implement Linear Search.15. To implement Binary Search.16. To implement Bubble Sorting.17. To implement Selection Sorting.18. To implement Insertion Sorting.19. To implement Merge Sorting.20. To implement Heap Sorting.

Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.

NCS-353: NUMERICAL TECHNIQUES LAB

Write Programs in ‘C’ Language:1. To deduce error involved in polynomial equation.2. To Find out the root of the Algebraic and Transcendental equations using Bisection,Regula-falsi , Newton Raphson and Iterative Methods. Also give the rate of convergence of roots in tabular formfor each of these methods.3. To implement Newton’s Forward and Backward Interpolation formula.4. To implement Gauss Forward and Backward, Bessel’s, Sterling’s and Evertt’s Interpolation formula5. To implement Newton’s Divided Difference and Langranges Interpolation formula.6. To implement Numerical Differentiations.7. To implement Numerical Integration using Trapezoidal, Simpson 1/3 and Simpson 3/8 rule.8. To implement Least Square Method for curve fitting.9. To draw frequency chart like histogram, frequency curve and pie-chart etc.10. To estimate regression equation from sampled data and evaluate values of standard deviation, t-statistics,regression coefficient, value of R2 for atleast two independent variables.

Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.

NCS-355: ADVANCE PROGRAMMING LAB

LIST OF EXPERIMENTS:1. Programs using Functions and Pointers in C2. Programs using Files in C3. Programs using Classes and Objects

4. Programs using Operator Overloading5. Programs using Inheritance, Polymorphism and its types6. Programs using Arrays and Pointers7. Programs using Dynamic memory allocation8. Programs using Templates and Exceptions9. Programs using Sequential and Random access files

Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.

NEC-408: INFORMATION THEORY AND CODING

Unit IReview of probability theory, Definition of Information Measure and Entropy: Measure of information, Averageinformation content of symbols in long independent sequences, Average information content of symbols in longdependent sequences. Mark-off statistical model for information source, Entropy and information rate of mark-off source, Mutual information. Asymptotic Properties of Entropy and Problem Solving in EntropyUnit – IIBlock Code and its Properties, Data compression, Kraft-Mcmillan Equality and Compact Codes, Encoding ofthe source output, Shannon’s encoding algorithm, Coding Strategies, Huffman Coding, Shannon-Fano-EliasCoding and Introduction to Arithmetic Coding.Unit – IIIIntroduction to Information Channels, Communication Channels, Discrete communication channels, Continuouschannels. Discrete memory less Channels, Mutual information, Channel Capacity, Channel coding theorem,Differential entropy and mutual information for continuous ensembles, Channel capacity Theorem.Unit – IVIntroduction to Error Control Coding: Introduction, Types of errors, examples, Types of codes Linear BlockCodes: Matrix description, Error detection and correction, Standard arrays and table look up for decodingUnit – VBinary Cycle Codes, Algebraic structures of cyclic codes, Encoding using an (n-k) bit shift register, Syndromecalculation. BCH codes. RS codes, Golay codes, Shortened cyclic codes, Burst error correcting codes. Burst andRandom Error correcting codes. Convolution Codes, Time domain approach. Transform domain approach.Reference:1.K. Sam Shanmugam, “Digital and analog communication systems”, John Wiley.2.Simon Haykin, “Digital communication”, John Wiley.3.Ranjan Bose, “ITC and Cryptography” ,Tata McGraw-Hill.4. Thomas M. Cover, Joy A. Thomas ,” Elements of Information Theory, 2nd Edition”, Wiley Publication.5. Roberto Togneri, Christopher J.S deSilva “Fundamentals of Information Theory and Coding Design”, CRCPress.6. Steven Roman,” Introduction to Coding and Information Theory”, Springer New York.7. Glover and Grant, “Digital Communications”, Pearson Education.

NCS-401: OPERATING SYSTEMUnit – IIntroduction : Operating system and functions, Classification of Operating systems- Batch, Interactive, Timesharing, Real Time System, Multiprocessor Systems, Multiuser Systems, Multiprocess Systems, MultithreadedSystems, Operating System Structure- Layered structure, System Components, Operating System services,Reentrant Kernels, Monolithic and MicrokernelSystems.Unit – IIConcurrent Processes: Process Concept, Principle ofConcurrency, Producer / Consumer Problem, MutualExclusion, Critical Section Problem, Dekker’s solution, Peterson’s solution, Semaphores, Test and Setoperation; Classical Problem in Concurrency- Dining Philosopher Problem, Sleeping Barber Problem; InterProcess Communication models and Schemes, Processgeneration.Unit – IIICPU Scheduling: Scheduling Concepts, Performance Criteria, Process States, Process TransitionDiagram, Schedulers, Process Control Block (PCB), Process address space, Process identification information,Threads and their management, Scheduling Algorithms, Multiprocessor Scheduling. Deadlock: System model,Deadlock characterization, Prevention, Avoidance and detection, Recovery from deadlock.Unit – IVMemory Management: Basic bare machine, Resident monitor, Multiprogramming with fixed partitions,Multiprogramming with variable partitions, Protection schemes, Paging, Segmentation, Paged segmentation,

Virtual memory concepts, Demand paging, Performance of demand paging, Page replacement algorithms,Thrashing, Cache memory organization, Localityof reference.Unit – VI/O Management and Disk Scheduling: I/O devices, and I/O subsystems, I/O buffering, Disk storage and diskscheduling, RAID. File System: File concept, File organization and access mechanism, File directories, and Filesharing, File system implementation issues, File system protection and security.

References :1. Silberschatz, Galvin and Gagne, “Operating Systems Concepts”, Wiley2. SibsankarHalder and Alex A Aravind, “Operating Systems”, Pearson Education3. Harvey M Dietel, “ An Introduction to Operating System”, Pearson Education4. D M Dhamdhere, “Operating Systems : A Concept basedApproach”, McGraw Hill.5. Charles Crowley, “Operating Systems: A Design-Oriented Approach”, Tata McGraw HillEducation”.1. Stuart E. Madnick & John J. Donovan, “ Operating Systems”, Tata McGraw Hill.

NCS-402: THEORY OF AUTOMATA AND FORMAL LANGUAGESUnit – IIntroduction; Alphabets, Strings and Languages; Automata and Grammars, Deterministic finiteAutomata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition table, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transi ion,Language of NFA, Equi valence of NFA and DFA, Minimization of Finite Automata, Distinguishing one string from other, Myhill-Nerode TheoremUnit – IIRegular expression (RE) , Definition, Operators of regular expression and their precedence,Algebraic laws for Regular expressions, Kleen’s Theorem, Regular expression to FA, DFA toRegular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regularLanguages . Application of Pumping Lemma, Closure properties of Regular Languages, Decision properties ofRegular Languages, FA with output: Moore and Mealy machine,Equivalence of Moore and Mealy Machine, Applications and Limitation of FA.Unit – IIIContext free grammar (CFG) and Context Free Languages (CFL): Definition, Examples, Derivation , Derivationtrees, Ambiguity in Grammer, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless symbols,Simplification of CFGs, Normal forms for CFGs: CNFand GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness andMemership, Pumping lemma for CFLs.Unit – IVPush Down Automata (PDA): Description and definition, Instantaneous Description, Language of PDA,Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFGto PDA and PDA to CFG, Two stack PDAUnit – VTuring machines (TM): Basic model, definition and representation, Instantaneous Description,Language acceptance by TM, Variants of Turing Machine, TM as Computerof Integer functions, Universal TM,Church’s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction toUndecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP,Introduction to recursive function theory .

References :1. Hopcroft, Ullman, “Introduction to Automata Theory,Languages and Computation”,Pearson Education .2. K.L.P. Mishra and N.Chandrasekaran, “Theory of Computer Science : Automata,Languages and Computation”, PHI Learning Private Limited, Delhi India.

3.Peter Linz, "An Introduction to Formal Language and Automata", Narosa Publishing house.4. Y.N.Singh “Mathematical Foundation of Computer Science”, New Age International.5. Papadimitrou, C. and Lewis, C.L., “Elements of the Theory of Computation”, PHI Learning Private Limited,Delhi India.6. K.Krithivasan and R.Rama; Introduction to Formal Languages, Automata Theory and Computation; PearsonEducation.7. Harry R. Lewis and Christos H. Papadimitriou, Elements of the theory of Computation,

Second Edition, Prentice-Hall of India Pvt. Ltd.8. Micheal Sipser, “Introduction of the Theory and Computation”, Thomson Learning.

NIT-401: MULTIMEDIA AND ANIMATION

Unit I – Introduction:Introduction to Multimedia and animation, Multimedia Systems, Design Fundamentals, Elements of multimediaand animation and their use, Back ground of Art, Color theory overview, Sketching & illustration,Storyboarding, different tools for animation .Unit- 2 – Multimedia Projects:Multimedia Skills, Hardware, Use of Graphics in Multimedia, Overview of Vector and Raster Graphics, Basicsoftware tools, Multimedia Authoring Tools, Planning and Costing, Designing and Producing, Contents andtalent, Delivering, Enhancing and Testing Multimedia Projects.Unit-3 – Tools of Multimedia:Paint and Draw Applications, Graphic effects and techniques, Image File Format, Anti-aliasing, Morphing,Multimedia Authoring tools, professional development tools.Unit-4 - Animation:Introduction and Principles of Animations, Power of Motion, Animation Techniques, Animation File Format,Making animation for Rolling Ball, making animation for a Bouncing Ball, Animation for the web, GIF, Plug-ins and Players, Animation tools for World Wide Web.

References:1. Tay Vaughan, “Multimedia, Making IT Work”,Tata McGraw Hill.2. Buford, “Multimedia Systems”, Addison Wesley.3. Sleinreitz, “Multimedia System”, Addison Wesley.4. Ze-Nian Li and Mark S.Drew, “Fundamentals of Multimedia”, PearsonEducation.5.Prabhat K Andleigh, Kiran Thakrar, “Multimedia systems design”, PHI Learning Private Limited, Delhi India.6.Elsom Cook – “Principles of Interactive Multimedia” ,Tata McGraw Hill.

NCS-451: OPERATING SYSTEM LAB

1. To implement CPU Scheduling Algorithms FCFS SJF SRTF PRIORITY ROUND ROBIN

2. Simulate all Page Replacement Algorithms FIFO LRU

3. Simulate Paging Technique of Memory Management

Note: The Instructor may add/delete/modify/tune experiments, wherever he/shefeels in a justified manner.

NIT-451: MULTIMEDIA AND ANIMATION LAB

1. Procedure to create an animation to represent the growing moon.2. Procedure to create an animation to indicate a ball bouncing on steps.3. Procedure to simulate movement of a cloud.4. Procedure to draw the fan blades and to give proper animation.5. Procedure to display the background given (filename: tulip.jpg) through your name.6. Procedure to display the background given (filename: garden.jpg) through your name using mask.

7. Procedure to create an animation with the following features.WELCOME (Letters should appear one by one .The fill color of the text should change to a differentcolour after the display of the full word.)

8. Procedure to simulate a ball hitting another ball.9. Procedure to design a visiting card containing at least one graphic and text information.10. Procedure to take a photographic image. Give a title for the image. Put the border. Write your

names. Write the name of institution and place.11. Procedure to prepare a cover page for the book in your subject area. Plan your own design.12. Procedure to extract the flower only from given photographic image and organize it on a

background. Selecting your own background for organization.13. Procedure to change a circle into a square using flash.14. Procedure to display the background given (FILENAME: GARDEN.JPG) through your name using

mask.

Note: The Instructor may add/delete/modify/tune experiments, wherever he/she feels in a justified manner.

NCS-455: FUNCTIONAL AND LOGIC PROGRAMMING LAB

Program in SML- NJ or CAML or F# for following:1. To implement Linear Search.2. To implement Binary Search.3. To implement Bubble Sorting.4. To implement Selection Sorting.5. To implement Insertion Sorting.

Implement using LISP6. Write a function that compute the factorial of a number.(factorial of 0 is 1, and

factorial of n is n*(n-1)*...1.Factorial is defined only for integers greater than orequal to 0.)7. Write a function that evaluate a fully parenthesized infix arithmetic expression .For examples, (infix (1+(2*3))) should return 7.8. Write a function that perform a depth first traversal of binary tree. The functionshould return a list containing the tree nodes in the order they were visited.9. Write a LISP program for water jug problem.10. Write a LISP program that determines whether an integer is prime.11. Write a PROLOG program that answers questions about family members and

relationships includes predicates and rules which definesister,brother,father,mother,grandchild,grandfather and uncle. The programshould be able to answer queries such as the following :

o father(x,Amit)o grandson(x,y)o uncle(sumit,puneet)o mother(anita,x)o

Note: The Instructor may add/delete/modify/tune experiments, wherever he/shefeels in a justified manner.

UTTAR PRADESH TECHNICAL UNIVERSITY

LUCKNOW

SYLLABUS

Bachelor of Information Technology

3rd Year (V & VI Semester)

(Effective from Session 2015-2016)

U.P. TECHNICAL UNIVERSITY, LUCKNOW

STUDY EVALUATION SCHEME B. TECH. INFORMATION TECHNOLOGY

YEAR THIRD, SEMESTER –V (Effective from the session : 2015-16)

S. No.

Course Code

Subject Periods Evaluation Scheme Subject Total

Credit

L T P Sessional Exam ESE CT TA Total

THEORY SUBJECT 1 NCS

501 Design and Analysis of Algorithm

3 1 0 30 20 50 100 150 4

2 NCS 502

Database Management System

3 1 0 30 20 50 100 150 4

3 NCS 503

Principle of Programming Language

3 1 0 30 20 50 100 150 4

4 NCS 504

Web Technology 3 1 0 30 20 50 100 150 4

5 NIT 501

Management Information System

2 1 0 15 10 25 50 75 3

6 NHU 501

Engineering Economics 2 0 0 15 10 25 50 75 2

PRACTICAL/DESIGN/DRAWING 7 NCS

551 Design and Analysis of Algorithm Lab

0 0 3 10 10 20 30 50 1

8 NCS 552

DBMS Lab 0 0 3 10 10 20 30 50 1

9 NCS 553

Principle of Programming Language Lab

0 0 2 10 10 20 30 50 1

10 NCS 554

Web Technology Lab 0 0 2 10 10 20 30 50 1

11 NGP 501

GP 50 50

TOTAL 16 5 10 1000 25

U.P. TECHNICAL UNIVERSITY, LUCKNOW STUDY EVALUATION SCHEME

B. TECH. INFORMATION TECHNOLOGY YEAR THIRD, SEMESTER –VI

(Effective from the session : 2015-16)

S. No.

Course Code

Subject Periods Evaluation Scheme Subject Total

Credit

L T P Sessional Exam ESE CT TA Total

THEORY SUBJECT 1 NCS

601 Computer Networks 3 1 0 30 20 50 100 150 4

2 NCS 602

Software Engineering 3 1 0 30 20 50 100 150 4

3 NCS 603

Compiler Design 3 1 0 30 20 50 100 150 4

4 Departmental Elective-I 3 1 0 30 20 50 100 150 4 5 Departmental Elective-II 2 1 0 15 10 25 50 75 3 6 NHU

601 Industrial Management 2 0 0 15 10 25 50 75 2

PRACTICAL/DESIGN/DRAWING 7 NCS

651 Computer Networks Lab 0 0 3 10 10 20 30 50 1

8 NCS 652

Software Engineering Lab

0 0 3 10 10 20 30 50 1

9 NCS 653

Compiler Design Lab 0 0 2 10 10 20 30 50 1

10 NIT 654

SEMINAR 0 0 2 50 50 50 1

11 NGP 601

GP 50 50

TOTAL 16 5 10 1000 25

Departmental Elective-I

1. Information Retrieval and Management 2. Modeling & Simulation 3. Bioinformatics 4. Knowledge based & decision Support System 5. Geographic Information System

Departmental Elective-II

1. Data Warehousing & Data Mining 2. Human Computer Interface 3. E-Business Strategies 4. Distributed DBMS 5. Big Data

NCS- 501 Design and Analysis of Algorithms 3 1 0 Unit Topic

Proposed Lectures

I. Introduction : Algorithms, Analyzing algorithms, Complexity of algorithms, Growth of functions, Performance measurements, Sorting and order Statistics - Shell sort, Quick sort, Merge sort, Heap sort, Comparison of sorting algorithms, Sorting in linear time.

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II. Advanced Data Structures: Red-Black trees, B – trees, Binomial Heaps, Fibonacci Heaps.

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III. Divide and Conquer with examples such as Sorting, Matrix Multiplication, Convex hull and Searching. Greedy methods with examples such as Optimal Reliability Allocation, Knapsack, Minimum Spanning trees – Prim’s and Kruskal’s algorithms, Single source shortest paths - Dijkstra’s and Bellman Ford algorithms.

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IV. Dynamic programming with examples such as Knapsack. All pair shortest paths – Warshal’s and Floyd’s algorithms, Resource allocation problem. Backtracking, Branch and Bound with examples such as Travelling Salesman Problem, Graph Coloring, n-Queen Problem, Hamiltonian Cycles and Sum of subsets.

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V. Selected Topics: Algebraic Computation, Fast Fourier Transform, String Matching, Theory of NP-completeness, Approximation algorithms and Randomized algorithms.

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Text books: 1. Thomas H. Coreman, Charles E. Leiserson and Ronald L. Rivest, “Introduction to Algorithms”,

Printice Hall of India. 2. E. Horowitz & S Sahni, "Fundamentals of Computer Algorithms", 3. Aho, Hopcraft, Ullman, “The Design and Analysis of Computer Algorithms” Pearson Education,

2008. References:

1. Jon Kleinberg and Éva Tardos, Algorithm Design, Pearson, 2005. 2. Michael T Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis, and Internet

Examples, Second Edition, Wiley, 2006. 3. Harry R. Lewis and Larry Denenberg, Data Structures and Their Algorithms, Harper Collins, 1997 4. Robert Sedgewick and Kevin Wayne, Algorithms, fourth edition, Addison Wesley, 2011. 5. Harsh Bhasin,”Algorithm Design and Analysis”,First Edition,Oxford University Press. 6. Gilles Brassard and Paul Bratley,Algorithmics:Theory and Practice,Prentice Hall,1995.

NCS-502 Database Management System 3 1 0

Unit Topic

Proposed Lectures

I. Introduction: An overview of database management system, database system Vs file system, Database system concept and architecture, data model schema and instances, data independence and database language and interfaces, data definitions language, DML, Overall Database Structure. Data Modeling using the Entity Relationship Model: ER model concepts, notation for ER diagram, mapping constraints, keys, Concepts of Super Key, candidate key, primary key, Generalization, aggregation, reduction of an ER diagrams to tables, extended ER model, relationship of higher degree.

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II. Relational data Model and Language: Relational data model concepts, integrity constraints, entity integrity, referential integrity, Keys constraints, Domain constraints, relational algebra, relational calculus, tuple and domain calculus. Introduction on SQL: Characteristics of SQL, advantage of SQL. SQl data type and literals. Types of SQL commands. SQL operators and their procedure. Tables, views and indexes. Queries and sub queries. Aggregate functions. Insert, update and delete operations, Joins, Unions, Intersection, Minus, Cursors, Triggers, Procedures in SQL/PL SQL

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III. Data Base Design & Normalization: Functional dependencies, normal forms, first, second, third normal forms, BCNF, inclusion dependence, loss less join decompositions, normalization using FD, MVD, and JDs, alternative approaches to database design.

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IV. Transaction Processing Concept: Transaction system, Testing of serializability, serializability of schedules, conflict & view serializable schedule, recoverability, Recovery from transaction failures, log based recovery, checkpoints, deadlock handling. Distributed Database: distributed data storage, concurrency control, directory system.

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V. Concurrency Control Techniques: Concurrency control, Locking Techniques for concurrency control, Time stamping protocols for concurrency control, validation based protocol, multiple granularity, Multi version schemes, Recovery with concurrent transaction, case study of Oracle.

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Text books: 1.Korth, Silbertz, Sudarshan,” Database Concepts”, McGraw Hill 2.Date C J, “ An Introduction to Database Systems”, Addision Wesley 3. Elmasri, Navathe, “ Fudamentals of Database Systems”, Addision Wesley 4. O’Neil, Databases, Elsevier Pub.

References:

1.Leon & Leon,”Database Management Systems”, Vikas Publishing House 2.Bipin C. Desai, “ An Introduction to Database Systems”, Gagotia Publications 3. Majumdar & Bhattacharya, “Database Management System”, TMH

NCS- 503 Principle of Programming Language 3 1 0 Unit Topic

Proposed Lectures

I.

Introduction The Role of Programming Languages: Why Study Programming Languages, Towards Higher-Level languages, Programming paradigms, Programming environments Language Description: Syntactic structure, language Translation Issues: Programming language Syntax, Stages in translation, Formal translation Models

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II.

Language Properties Modeling Language Properties, Elementary Data Types, Encapsulation, Inheritance, Sequence Control, Subprogram Control

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III.

Programming Paradigms Imperative Programming: Statements, Types, Procedure Activations Object-Oriented Programming: Grouping Of Data and Operations, object oriented programming Functional Programming: Elements, Programming in a Typed language, Programming with lists

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IV. Other Programming Paradigms Logic Programming, Concurrent Programming, Network Programming , Language Description: Semantic Methods

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V. Lambda Calculus Introduction to Lambda Calculus, Simple types, Subtyping

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Text books: 1. “Programming Languages: Design and Implementations” , Terrance W.Pratt, Marvin V. Zelkowitz,

T.V.Gopal,Fourth ed.,Prentice Hall 2. “Programming Language Design Concept”, David A. Watt, Willey India 3. “Programming languages: Concepts and Constucts”, Ravi Sethi, Second Ed.,Pearson. 4. “Types and programming Languages”, Benjamin C. Pierce. The MIT Press Cambridge, Massachusetts

London, England

References: 1. Concepts of Programming Languages, Robert W. Sebesta, 10th Ed.,Pearson

NCS- 504 Web Technology 3 1 0

Unit Topic

Proposed Lectures

I.

Introduction: Introduction and Web Development Strategies, History of Web and Internet, Protocols governing Web, Writing Web Projects, Connecting to Internet, Introduction to Internet services and tools, Introduction to client-server computing. Core Java: Introduction, Operator, Data type, Variable, Arrays, Methods & Classes, Inheritance, Package and Interface, Exception Handling, Multithread programming, I/O, Java Applet, String handling, Event handling, Introduction to AWT, AWT controls, Layout managers.

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II. Web Page Designing: HTML: list, table, images, frames, forms, CSS, Document type definition, XML: DTD, XML schemes, Object Models, presenting and using XML, Using XML Processors: DOM and SAX, Dynamic HTML.

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III. Scripting: Java script: Introduction, documents, forms, statements, functions, objects; introduction to AJAX, VB Script, Introduction to Java Beans, Advantage, Properties, BDK, Introduction to EJB, Java Beans API.

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IV. Server Site Programming: Introduction to active server pages (ASP), Introduction to Java Server Page (JSP), JSP Application Design, JSP objects, Conditional Processing, Declaring variables and methods, Sharing data between JSP pages, Sharing Session and Application Data, Database Programming using JDBC, development of java beans in JSP, Introduction to Servelets, Lifecycle, JSDK, Servlet API, Servlet Packages, Introduction to COM/DCOM/CORBA.

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V. PHP (Hypertext Preprocessor): Introduction, syntax, variables, strings, operators, if-else, loop, switch, array, function, form, mail, file upload, session, error, exception, filter, PHP-ODBC,

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Text books: 1. Burdman, Jessica, “Collaborative Web Development” Addison Wesley 2. Xavier, C, “ Web Technology and Design” , New Age International 3. Ivan Bayross,” HTML, DHTML, Java Script, Perl & CGI”, BPB Publication 4. Bhave, “Programming with Java”, Pearson Education 5. Herbert Schieldt, “The Complete Reference:Java”, TMH. 6. Hans Bergsten, “Java Server Pages”,

SPD O’Reilly 6. Ullman, “PHP for the Web: Visual QuickStart Guide”, Pearson Education 7. Margaret Levine Young, “The Complete Reference Internet”, TMH 8. Naughton, Schildt, “The Complete Reference JAVA2”, TMH 9. Balagurusamy E, “Programming in JAVA”, TMH

References:

1. Ramesh Bangia, “Internet and Web Design” , New Age International 2. Ivan Bayross,” HTML, DHTML, Java Script, Perl & CGI”, BPB Publication 3. Deitel, “Java for programmers”, Pearson Education 4. Chris Bates, “Web Programing Building Internet Applications”, 2nd Edition, WILEY, Dreamtech 5. Joel Sklar , “Principal of web Design” Vikash and Thomas Learning 6. Horstmann, “CoreJava”, Addison Wesley

NIT 501 MANAGEMENT INFORMATION SYSTEMS 2 1 0 Unit Topic

Proposed Lectures

I Foundation of Information Systems: Introduction to information system in business, fundamentals of information systems, Solving business problems with information systems, Types of information systems, Effectiveness and efficiency criteria in information system.

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II An overview of Management Information Systems: Definition of a management information system, MIS versus Data processing, MIS & Decision Support Systems, MIS & Information Resources Management, End user computing, Concept of an MIS,Structure of a Management information system.

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III Concepts of planning: Concept of organizational planning, The Planning Process, Computational support for planning. Business applications of information technology: Internet & electronic commerce and its applications Enterprise Solutions, Information System for Business Operations(SDLC),Information System for Strategic Advantage,Decision Support Systems and its benefits and characterstics.

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IV Managing Information Technology: Enterprise & global management, Security & Ethical challenges, Planning & Implementing changes. Advanced Concepts in Information Systems: Enterprise Resource Planning, Supply Chain Management, Customer Relationship Management, and Procurement Management.

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TEXT BOOK: 1. O Brian, “Management Information System”, TMH 2. Gordon B. Davis & Margrethe H. Olson, “Management Information System”, TMH 3. Ravi Kalakota, Andrew Winston, “Frontiers of Electronic Commerce”, Addison Wesley. REFRENCE BOOKS:- 1. O Brian, “Introduction to Information System”, MCGRAW HILL. 2. Murdick, “Information System for Modern Management”, PHI. 3. Jawadekar, “ Management Information System”, TMH. 4. Jain Sarika, “Information System”, PPM 5. Davis, “Information System”, Palgrave Macmillan

NCS 551 Design and analysis of algorithms Lab Objective :- 1. Program for Recursive Binary & Linear Search. 2. Program for Heap Sort. 3. Program for Merge Sort. 4. Program for Selection Sort. 5. Program for Insertion Sort. 6. Program for Quick Sort. 7.Study of NP-Complete theory. 8.Study of Cook’s theorem. 9.Study of Sorting network. NCS 552 DBMS Lab Objectives:- 1. Installing oracle. 2. Creating Entity-Relationship Diagram using case tools. 3. Writing SQL statements Using ORACLE /MYSQL:

a)Writing basic SQL SELECT statements. b)Restricting and sorting data.

c)Displaying data from multiple tables. d)Aggregating data using group function. e)Manipulating data. e)Creating and managing tables. 4. Normalization in ORACLE. 5. Creating cursor in oracle. 6. Creating procedure and functions in oracle. 7. Creating packages and triggers in oracle. NCS 553 Principles of programming languages 1. Define a LISP function to compute sum of squares. 2. Define a LISP function to compute difference of squares. (if x > y return x2 -y 2 , otherwise y2 - x2 ) 3. Define a Recursive LISP function to solve Ackermann’s Function. 4. Define a Recursive LISP function to compute factorial of a given number. 5. Define a Recursive LISP function which takes one argument as a list and returns last element of the list. (do not use last predicate) 6. Define a Recursive LISP function which takes one argument as a list and returns a list except last element of the list. (do not use but last predicate) 7. Define a Recursive LISP function which takes one argument as a list and returns reverse of the list. (do not use reverse predicate) 8. Define a Recursive LISP function which takes two arguments first, an atom, second, a list, returns a list after removing first occurrence of that atom within the list.

NCS 554 Web Technology Lab Objectives:-

1. Write HTML/Java scripts to display your CV in navigator, your Institute website, Department Website and Tutorial website for specific subject

2. Design HTML form for keeping student record and validate it using Java script. 3. Write an HTML program to design an entry form of student details and send it to store at database

server like SQL, Oracle or MS Access. 4. Write programs using Java script for Web Page to display browsers information. 5. Write a Java applet to display the Application Program screen i.e. calculator and other. 6. Writing program in XML for creation of DTD, which specifies set of rules. Create a style sheet in CSS/

XSL & display the document in internet explorer. 7. Using ASP for server side programming, ASP for user name and password and to retrieve & match the

value. It display success and failure messages. ASP for creating text file local drive, ASP for keeping the student record in database.

8. Program to illustrate JDBC connectivity. Program for maintaining database by sending queries. Design and implement a simple servlet book query with the help of JDBC & SQL. Create MS Access Database, Create on ODBC link, Compile & execute JAVA JDVC Socket.

9. Design and implement a simple shopping cart example with session tracking API.

NCS-601 Computer Networks 3 1 0 Unit Topic

Proposed Lectures

I Introduction Concepts: Goals and Applications of Networks, Network structure and architecture, The OSI reference model, services, Network Topology Design - Delay Analysis, Back Bone Design, Local Access Network Design, Physical Layer Transmission Media, Switching methods, ISDN, Terminal Handling.

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II Medium Access sub layer: Medium Access sub layer - Channel Allocations, LAN protocols - ALOHA protocols - Overview of IEEE standards - FDDI. Data Link Layer - Elementary Data Link Protocols, Sliding Window protocols, Error Handling.

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III Network Layer: Network Layer - Point - to Pont Networks, routing, Congestion control Internetworking -TCP / IP, IP packet, IP address, IPv6.

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IV Transport Layer: Transport Layer - Design issues, connection management, session Layer-Design issues, remote procedure call. Presentation Layer-Design issues, Data compression techniques, cryptography - TCP - Window Management.

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V Application Layer: Application Layer: File Transfer, Access and Management, Electronic mail, Virtual Terminals, Other application. Example Networks - Internet and Public Networks.

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TEXTBOOKS: 1. Forouzen, "Data Communication and Networking", TMH 2. A.S. Tanenbaum, Computer Networks, Pearson Education 3. W. Stallings, Data and Computer Communication, Macmillan Press

REFRENCES: 1. Anuranjan Misra, “Computer Networks”, Acme Learning 2. G. Shanmugarathinam, ”Essential of TCP/ IP”, Firewall Media

NCS- 602 Software Engineering 3 1 0 Unit Topic

Proposed Lectures

I Introduction:Introduction to Software Engineering, Software Components, Software Characteristics, Software Crisis, Software Engineering Processes, Similarity and Differences from Conventional Engineering Processes, Software Quality Attributes. Software Development Life Cycle (SDLC) Models: Water Fall Model, Prototype Model, Spiral Model, Evolutionary Development Models, Iterative Enhancement Models.

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II Software Requirement Specifications (SRS):Requirement Engineering Process: Elicitation, Analysis, Documentation, Review and Management of User Needs, Feasibility Study, Information Modeling, Data Flow Diagrams, Entity Relationship Diagrams, Decision Tables, SRS Document, IEEE Standards for SRS.Software Quality Assurance (SQA): Verification and Validation, SQA Plans, Software Quality Frameworks, ISO 9000 Models, SEI-CMM Model.

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III Software Design:Basic Concept of Software Design, Architectural Design, Low Level Design: Modularization, Design Structure Charts, Pseudo Codes, Flow Charts, Coupling and Cohesion Measures, Design Strategies: Function Oriented Design, Object Oriented Design, Top-Down and Bottom-Up Design. Software Measurement and Metrics: Various Size Oriented Measures: Halestead’s Software Science, Function Point (FP) Based Measures, Cyclomatic Complexity Measures: Control Flow Graphs.

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IV Software Testing:Testing Objectives, Unit Testing, Integration Testing, Acceptance Testing, Regression Testing, Testing for Functionality and Testing for Performance, Top-Down and Bottom-Up Testing Strategies: Test Drivers and Test Stubs, Structural Testing (White Box Testing), Functional Testing (Black Box Testing), Test Data Suit Preparation, Alpha and Beta Testing of Products.Static Testing Strategies: Formal Technical Reviews (Peer Reviews), Walk Through, Code Inspection, Compliance with Design and Coding Standards.

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V Software Maintenance and Software Project Management:Software as an Evolutionary Entity, Need for Maintenance, Categories of Maintenance: Preventive, Corrective and Perfective Maintenance, Cost of Maintenance, Software Re-Engineering, Reverse Engineering. Software Configuration Management Activities, Change Control Process, Software Version Control, An Overview of CASE Tools. Estimation of Various Parameters such as Cost, Efforts, Schedule/Duration, Constructive Cost Models (COCOMO), Resource Allocation Models, Software Risk Analysis and Management.

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Textbooks: 1. R. S. Pressman, Software Engineering: A Practitioners Approach,

McGraw Hill. 2. Rajib Mall, Fundamentals of Software Engineering, PHI Publication. 3. K. K. Aggarwal and Yogesh Singh, Software Engineering, New Age

International Publishers. 4. Pankaj Jalote, Software Engineering, Wiley

5.Deepak Jain,”Software Engineering:Principles and Practices”,Oxford University Press.

NCS-603 Compiler Design 3 1 0 Unit Topic

Proposed Lectures

I Introduction to Compiler, Phases and passes, Bootstrapping, Finite state machines and regular expressions and their applications to lexical analysis, Optimization of DFA-Based Pattern Matchers implementation of lexical analyzers, lexical-analyzer generator, LEX-compiler, Formal grammars and their application to syntax analysis, BNF notation, ambiguity, YACC. The syntactic specification of programming languages: Context free grammars, derivation and parse trees, capabilities of CFG.

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II Basic Parsing Techniques: Parsers, Shift reduce parsing, operator precedence parsing, top down parsing, predictive parsers Automatic Construction of efficient Parsers: LR parsers, the canonical Collection of LR(0) items, constructing SLR parsing tables, constructing Canonical LR parsing tables, Constructing LALR parsing tables, using ambiguous grammars, an automatic parser generator, implementation of LR parsing tables.

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III Syntax-directed Translation: Syntax-directed Translation schemes, Implementation of Syntax-directed Translators, Intermediate code, postfix notation, Parse trees & syntax trees, three address code, quadruple & triples, translation of assignment statements, Boolean expressions, statements that alter the flow of control, postfix translation, translation with a top down parser. More about translation: Array references in arithmetic expressions, procedures call, declarations and case statements.

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IV Symbol Tables: Data structure for symbols tables, representing scope information. Run-Time Administration: Implementation of simple stack allocation scheme, storage allocation in block structured language. Error Detection & Recovery: Lexical Phase errors, syntactic phase errors semantic errors.

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V Code Generation: Design Issues, the Target Language. Addresses in the Target Code, Basic Blocks and Flow Graphs, Optimization of Basic Blocks, Code Generator. Code optimization: Machine-Independent Optimizations, Loop optimization, DAG representation of basic blocks, value numbers and algebraic laws, Global Data-Flow analysis.

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Textbooks: 1. Aho, Sethi & Ullman, "Compilers: Principles, Techniques and Tools”, Pearson

Education 2. V Raghvan, “ Principles of Compiler Design”, TMH 3. Kenneth Louden,” Compiler Construction”, Cengage Learning. 4. Charles Fischer and Ricard LeBlanc,” Crafting a Compiler with C”, Pearson

Education Refrences:

1.K. Muneeswaran,Compiler Design,First Edition,Oxford University Press. 2.J.P. Bennet, “Introduction to Compiler Techniques”, Second Edition, Tata McGraw-Hill, 2003. 3.Henk Alblas and Albert Nymeyer,“Practice and Principles of Compiler Building with C”, PHI, 2001.

DEPARTMENTAL ELECTIVE-I

NIT-061 Information Retrieval and Management 3 1 0 Unit Topic

Proposed Lectures

I Basic Concepts of IR, Data Retrieval & Information Retrieval, IR system block diagram. Automatic Text Analysis, Luhn's ideas, Conflation Algorithm, Indexing and Index Term Weighing, Probabilistic Indexing, Automatic Classification. Measures of Association, Different Matching Coefficient, Classification Methods, Cluster Hypothesis. Clustering Algorithms, Single Pass Algorithm, Single Link Algorithm, Rochhio's Algorithm and Dendograms

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II File Structures, Inverted file, Suffix trees & suffix arrays, Signature files, Ring Structure, IR Models, Basic concepts, Boolean Model, Vector Model, and Fuzzy Set Model. Search Strategies, Boolean search, serial search, and clusterbased retrieval, Matching Function. Performance Evaluation- Precision and recall, alternative measures reference collection (TREC Collection), Libraries & Bibliographical system- Online IR system, OPACs, Digital libraries - Architecture issues, document models, representation & access, Prototypes, projects & interfaces, standards

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III Taxonomy and Ontology: Creating domain specific ontology, Ontology life cycle Distributed and Parallel IR: Relationships between documents, Identify appropriate networked collections, Multiple distributed collections simultaneously, Parallel IR - MIMD Architectures, Distributed IR – Collection Partitioning, Source Selection, Query Processing

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IV Multimedia IR models & languages- data modeling, Techniques to represent audio and visual document, query languages Indexing & searching- generic multimedia indexing approach, Query databases of multimedia documents, Display the results of multimedia searches, one dimensional time series, two dimensional color images, automatic feature extraction.

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V Searching the Web, Challenges, Characterizing the Web, Search Engines, Browsing, Mata searchers, Web crawlers, robot exclusion, Web data mining, Metacrawler, Collaborative filtering, Web agents (web shopping, bargain finder), Economic, ethical, legal and political issues..

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Text Books : 1. Yates & Neto, "Modern Information Retrieval", Pearson Education, ISBN 81-297-0274-6 2. I. Witten, A. Moffat, and T. Bell, “Managing Gigabytes” 4. D. Grossman and O. Frieder “Information Retrieval: Algorithms and Heuristics” Reference Books : 1. Mark leven, “Introduction to search engines and web navigation”, John Wiley and sons Inc., ISBN 9780-170-52684-2. 2. V. S. Subrahamanian, Satish K. Tripathi “Multimedia information System”, Kulwer Academic Publisher 3. Chabane Djeraba, ”Multimedia mining A highway to intelligent multimedia documents”, Kulwer Academic Publisher, ISBN 1-4020-7247-3

NIT-062 Modelling and Simulation 3 1 0 Unit Topic

Proposed Lectures

I System definition and components, stochastic activities, continuous and discrete systems, System modeling, Types of models, static and dynamic physical models, static and dynamic mathematical models, full corporate model, types of system study.

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II System simulation, Need of simulation, Basic nature of simulation, techniques of simulation, comparison of simulation and analytical methods, types of system Simulation, real time simulation, hybrid simulation, simulation of pursuit problem, single-server queuing system and an inventory problem, Monte-Carlo simulation, Distributed Lag model, Cobweb model.

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III Simulation of continuous Systems, analog vs digital simulation, simulation of water reservoir system, simulation of a servo system, simulation of an auto-pilot. Discrete system simulation, fixed time-step vs event-to-event model, generation of random numbers, test of randomness, Monte-Carlo computation vs stochastic simulation.

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IV System dynamics ,exponential growth models, exponential decay models, logistic curves, system dynamics diagrams, world model.

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V Simulation of PERT networks, critical path computation, uncertaintities in activityduration, resource allocation and consideration, Simulation languages, object oriented simulation.

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Textbooks: 1) Geoftrey Gordon, “System Simulation”, PHI 2) Narsingh Deo, “System Simulation with digital computer”, PHI. 3) Averill M. Law, W. David Kelton, “Simulation Modelling and Analysis”,TMH.

NIT-063 Bioinformatics 3 1 0 Unit Topic

Proposed Lectures

I Bioinformatics objectives and overviews, Interdisciplinary nature of Bioinformatics, Data integration, Data analysis, Major Bioinformatics databases and tools. Metadata: Summary & reference systems, finding new type of data online. Molecular Biology and Bioinformatics: Systems approach in biology, Central dogma of molecular biology, problems in molecular approach and the bioinformatics approach, oerview of the bioinformatics applications.

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II Basic chemistry of nucleic acids, Structure of DNA, Structure of RNA, DNA Replication, Transcription-Translation, Genes- the functional elements in DNA, Analyzing DNA,DNA sequencing. Proteins: Amino acids, Protein structure, Secondary, Tertiary and Quaternary structure, Protein folding and function, Nucleic acid-Protein interaction.

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III Perl Basics, Perl applications for bioinformatics- Bioperl, Linux Operating System, mounting/unmounting files, tar, gzip / gunzip, telnet, ftp, developing applications on Linux OS, Understanding and Using Biological Databases, Overview of Java, CORBA, XML, Web deployment concepts.

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IV Genome, Genomic sequencing, expressed sequence tags, gene expression, transcription factor binding sites and single nucleotide polymorphism. Computational representations of molecular biological data storage techniques: databases (flat, relational and object oriented), and controlled vocabularies, general data retrieval techniques: indices, Boolean search, fuzzy search and neighboring, application to biological data warehouses.

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V Macromolecular structures, chemical compounds, generic variability and its connection to clinical data. Representation of patterns and relationships: sequence alignment algorithms, regular expressions, hierarchies and graphical models, Phylogenetics. BLAST.

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Textbooks : 1. D E Krane & M L Raymer, ” Fundamental concepts of Bioinformatics”, Perason

Education. 2. Rastogi, Mendiratta, Rastogi, “Bioinformatics Methods & applications, Genomics,

Proteomics & Drug Discovery” PHI, New Delhi 3. Shubha Gopal et.al. “ Bioinformatics: with fundamentals of genomics and proteomics”,

Mc Graw Hill. 4. O’Reilly, “ Developing Bio informatics computer skills”, CBS 5. Forsdyke, “Evolutionary Bioinformatics”, Springer

NIT-064 Knowledge based decision Support System 3 1 0 Unit Topic

Proposed Lectures

I DECISION MAKING AND COMPUTERIZED SUPPORT : Management Support Systems: An Overview - Decision Making, Systems, Modeling , and Support.

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II DECISION SUPPORT SYSTEMS: Decision Support Systems: An Overview - Modeling and Analysis - Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business Analysis, and Visualization - Decision Support System Development.

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III COLLABORATION, COMMUNICATION, ENTERPRISE DECISION SUPPORT SYSTEMS, AND KNOWLEDGE MANAGEMENT: Collaborative Computing Technologies: Group Support Systems -Enterprise Information Systems - knowledge Management.

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IV INTELLIGENT DECISION SUPPORT SYSTEMS: Artificial Intelligence and Expert Systems: Knowledge-Based System - Knowledge Acquisition, Representation, and Reasoning - Advanced Intelligent Systems - Intelligent Systems over the Internet.

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V IMPLEMENTING IN THE E-BUSINESS ERA : Electronic Commerce - Integration, Impacts, and the Future of the Management Support Systems.

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Text Book: 1. Efraim Turban, Jay Aronson E., Ting-Peng Liang, "Decision Support Systems and Intelligent Systems", 7th Edition, Pearson Education, 2006. References: 1. George M .Marakas , "Decision Support Systems in the 21st century",2nd Edition, PHI, 2009. 2. Janakiraman V.S., Sarukesi K., “ Decision Support Systems”, PHI, 2009.

NIT-065 Geographic Information System 3 1 0

Unit Topic

Proposed Lectures

I FUNDAMENTALS OF GIS,What is GIS – Introduction Defining GIS – Components of a GIS – Spatial data – Introduction - Maps and their influence on the character of spatial data – Other sources of spatial data

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II SPATIAL DATA MODELING :Introduction – Entity definition – Spatial data models – Spatial data structures – Modeling surfaces – Modeling networks – Building computer networks – Modeling the third dimension –modeling the fourth dimension - Attribute data management - Introduction – Why choose a databaseapproach? - Database data models – Creating a database – GIS database applications – Developments in databases

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III DATA INPUT AND EDITING :Introduction – Methods of data input –Data editing – Towards an integrated database - Data analysis: Introduction – Measurements in GIS – lengths, perimeters and areas – Queries – Reclassification – Buffering and neighborhood functions – Integrating data –map overlay – Spatial interpolation – Network analysis.

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IV ANALYTICAL MODELING IN GIS : Introduction – process models – Modeling physical and environmental processes – Modeling human Processes –Modeling the decision – making process – Problems with using GIS to model spatial processes - Output: from new maps to enhanced decisions: Introduction – Maps as output – Non-cartographic output – Spatial multimedia – Mechanisms of delivery – GIS and spatial decision support

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V ISSUES IN GIS - The development of computer methods for handling spatial data – Introduction – Handling spatial data manually – The development of computer methods for handling spatial data – The development of GIS - Data quality issues – Introduction –Describing data quality and errors sources of errors in GIS

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Text Books: 1. Ian Heywood, Sarah Cornelius and Steve carver, “Introduction to geographical information systems”, Pearson Education, 4th Edition, 2012. Refrences: 1. DeMers, M.N., “Fundamentals of Geographic Information Systems”, 3 rdEdition, Wiley Press, 2009. 2. Lo C.P. and Yeung, A.K.W.,“Concepts and Techniques of Geographic Information Systems”, Prentice Hall, 2002. 3. Burrough, P.A. and R.A. McDonald, “Principles of Geographical Information Systems”, Oxford University Press, 1998.

DEPARTMENTAL ELECTIVE-II

NCS-066 Data warehousing & Data Mining 3 1 0 Unit

Topic

Proposed Lectures

I Data Warehousing: Overview, Definition, Data Warehousing Components, Building a Data Warehouse, Warehouse Database, Mapping the Data Warehouse to a Multiprocessor Architecture, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting.

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II Data Warehouse Process and Technology: Warehousing Strategy, Warehouse /management and Support Processes, Warehouse Planning and Implementation, Hardware and Operating Systems for Data Warehousing, Client/Server Computing Model & Data Warehousing. Parallel Processors & Cluster Systems, Distributed DBMS implementations, Warehousing Software, Warehouse Schema Design, Data Extraction, Cleanup & Transformation Tools, Warehouse Metadata

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III Data Mining: Overview, Motivation, Definition & Functionalities, Data Processing, Form of Data Preprocessing, Data Cleaning: Missing Values, Noisy Data,(Binning, Clustering, Regression, Computer and Human inspection),Inconsistent Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data Compression, Numerosity Reduction, Discretization and Concept hierarchy generation, Decision Tree.

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IV Classification: Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisons, Statistical measures in large Databases, Statistical-Based Algorithms, Distance-Based Algorithms, Decision Tree-Based Algorithms. Clustering: Introduction, Similarity and Distance Measures, Hierarchical and Partitional Algorithms. Hierarchical Clustering- CURE and Chameleon. Density Based Methods-DBSCAN, OPTICS. Grid Based Methods- STING, CLIQUE. Model Based Method –Statistical Approach, Association rules: Introduction, Large Itemsets, Basic Algorithms, Parallel and Distributed Algorithms, Neural Network approach.

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VData Visualization and Overall Perspective: Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security, Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse. Warehousing applications and Recent Trends: Types of Warehousing Applications, Web Mining, Spatial Mining and Temporal Mining.

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TEXTBOOKS: 1. Alex Berson, Stephen J. Smith “Data Warehousing, Data-Mining & OLAP”, TMH 2. Mark Humphries, Michael W. Hawkins, Michelle C. Dy, “ Data Warehousing: Architecture

and Implementation”, Pearson 3. Margaret H. Dunham, S. Sridhar,”Data Mining:Introductory and Advanced Topics” Pearson

Education 4. Arun K. Pujari, “Data Mining Techniques” Universities Press 5. Pieter Adriaans, Dolf Zantinge, “Data-Mining”, Pearson Education

NCS-070 Human Computer Interaction 3 1 0 Unit Topic

Proposed Lectures

I Introduction : Importance of user Interface – definition, importance of good design. Benefits of good design. A brief history of Screen design. The graphical user interface – popularity of graphics, the concept of direct manipulation, graphical system, Characteristics, Web user – Interface popularity, characteristics- Principles of user interface.

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II Design process – Human interaction with computers, importance of human characteristics human consideration, Human interaction speeds, understanding business junctions.

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III Screen Designing : Design goals – Screen planning and purpose, organizing screen elements, ordering of screen data and content – screen navigation and flow – Visually pleasing composition – amount of information – focus and emphasis – presentation information simply and meaningfully – information retrieval on web – statistical graphics – Technological consideration in interface design.

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IV Windows – New and Navigation schemes selection of window, selection of devices based and screen based controls. Components – text and messages, Icons and increases – Multimedia, colors, uses problems, choosing colors.

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V Software tools – Specification methods, interface – Building Tools. Interaction Devices – Keyboard and function keys – pointing devices – speech recognition digitization and generation – image and video displays – drivers.

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TEXT BOOKS: 1. Alan Dix, Janet Finlay, Gregory Abowd, Russell Beale Human Computer Interaction, 3rd Edition Prentice Hall, 2004. 2. Jonathan Lazar Jinjuan Heidi Feng, Harry Hochheiser, Research Methods in HumanComputer Interaction, Wiley, 2010. REFERENCE: 1. Ben Shneiderman and Catherine Plaisant Designing the User Interface: Strategies for Effective Human-Computer Interaction (5th Edition, pp. 672, ISBN 0-321-53735-1, March 2009), Reading, MA: Addison-Wesley Publishing Co.

NIT 066 E-Business Strategies 3 1 0 Unit Topic

Proposed Lectures

I Electronic Commerce Environment and Opportunities: Background – The Electronic Commerce Environment – Electronic Marketplace Technologies – Modes of Electronic Commerce: Overview – Electronic Data Interchange – Migration to Open EDI – Electronic Commerce with WWW/Internet – Commerce Net Advocacy – Web Commerce going forward.

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II Approaches to Safe Electronic Commerce: Overview – Secure Transport Protocols – Secure Transactions – Secure Electronic Payment Protocol(SEPP) – Secure Electronic Transaction (SET)- Certificates for Authentication – Security on Web Servers and Enterprise Networks – Electronic cash and Electronic payment schemes: Internet Monetary payment and security requirements – payment and purchase order process - Online Electronic cash.

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III Internet/Intranet Security Issues and Solutions: The need for Computer Security – Specific Intruder Approaches – Security strategies – Security tools – Encryption – Enterprise Networking and Access to the Internet – Antivirus programs – Security Teams.

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IV MasterCard/Visa Secure Electronic Transaction: Introduction – Business Requirements – Concepts – Payment processing – E-mail and secure e-mail technologies for electronic commerce. Introduction – The Mean of Distribution – A model for message handling – Working of Email - MIME: Multipurpose Internet Mail Extensions – S/MIME: Secure Multipurpose Internet Mail Extensions – MOSS: Message Object Security Services.

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V Internet and Website Establishment: Introduction – Technologies for web servers – Internet tools relevant to Commerce – Internet Applications for Commerce – Internet charges – Internet Access and Architecture – Searching the Internet- Case study.

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TEXT BOOK 1. Daniel Minoli and Emma Minoli, “Web Commerce Technology Handbook”, Tata McGraw-Hill, 2005. REFERENCES 1. Andrew B. Whinston, Ravi Kalakota, K. Bajaj and D. Nag, “Frontiers of Electronic Commerce”, Tata McGraw-Hill, 2004. 2. Bruce C. Brown, “How to Use the Internet to Advertise, Promote and Market Your Business or Website with Little or No Money”, Atlantic Publishing Company, 2006.

NCS-067 Distributed Database 3 1 0 Unit Topic

Proposed Lectures

I Transaction and schedules, Concurrent Execution of transaction, Conflict and View Serializability, Testing for Serializability, Concepts in Recoverable and Cascadeless schedules.

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II Lock based protocols, time stamp based protocols, Multiple Granularity and Multiversion Techniques, Enforcing serializablity by Locks, Locking system with multiple lock modes, architecture for Locking scheduler.

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III Distributed Transactions Management, Data Distribution, Fragmentation and Replication Techniques, Distributed Commit, Distributed Locking schemes, Long duration transactions, Moss Concurrency protocol.

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IV Issues of Recovery and atomicity in Distributed Databases, Traditional recovery techniques, Log based recovery, Recovery with Concurrent Transactions, Recovery in Message passing systems, Checkpoints, Algorithms for recovery line, Concepts in Orphan and Inconsistent Messages.

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V Distributed Query Processing, Multiway Joins, Semi joins, Cost based query optimization for distributed database, Updating replicated data, protocols for Distributed Deadlock Detection, Eager and Lazy Replication Techniques.

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References 1. Silberschatz,korth and Sudershan, Database System Concept’, Mc Graw Hill 2. Ramakrishna and Gehrke,’ Database Management System, Mc Graw Hill 3. Garcia-Molina, Ullman,Widom,’ Database System Implementation’ Pearson

Education 4. Ceei and Pelagatti,’Distributed Database’, TMH 5. Singhal and Shivratri, ’Advance Concepts in Operating Systems’ MC Graw Hill

NIT 067- BIG DATA 3 1 0 Unit Topic

Proposed Lectures

I UNDERSTANDING BIG DATA What is big data,why big data,convergence of key trends, unstructured data, industry examples of big data, web analytics,big data and marketing,fraud and big data,risk and big data ,credit risk management, big data and algorithmic trading,big data and healthcare,big data in medicine,advertising and big data,big data technologies, introduction to Hadoop,open source technologies,cloud and big data mobile business intelligence,Crowd sourcing analytics ,inter and trans firewall analytics

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II NOSQL DATA MANAGEMENT Introduction to NoSQL , aggregate data models ,aggregates ,key-value and document data models, relationships, graph databases, schema less databases ,materialized views,distribution models ,sharding , master-slave replication , peer-peer replication , sharding and replication , consistency , relaxing consistency , version stamps , map-reduce , partitioning and combining , composing map-reduce calculations

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III BASICS OF HADOOP Data format , analyzing data with Hadoop , scaling out , Hadoop streaming , Hadoop pipes , design of Hadoop distributed file system (HDFS) , HDFS concepts , Java interface , data flow ,Hadoop I/O , data integrity , compression , serialization , Avro file-based data structures

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IV MAP REDUCE APPLICATIONS Map Reduce workflows , unit tests with MRUnit , test data and local tests – anatomy of Map Reduce job run , classic Map-reduce , YARN , failures in classic Map-reduce and YARN , job scheduling , shuffle and sort , task execution , MapReduce types , input formats , output formats .

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V HADOOP RELATED TOOLS Hbase,data model and implementations, Hbase clients ,Hbase examples – praxis.Cassandra ,cassandra data model , cassandra examples , cassandra clients , Hadoop integration. Pig , Grunt , pig data model , Pig Latin , developing and testing Pig Latin scripts. Hive , data types and file formats , HiveQL data definition , HiveQL data manipulation – HiveQL queries

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Text Books: 1. Michael Minelli, Michelle Chambers, and Ambiga Dhiraj, "Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses", Wiley, 2013. 2. Big-Data Black Book, DT Editorial Services, Wily India 3. P. J. Sadalage and M. Fowler, "NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence", Addison-Wesley Professional, 2012. 4. Tom White, "Hadoop: The Definitive Guide", Third Edition, O'Reilley, 2012. 5. Eric Sammer, "Hadoop Operations", O'Reilley, 2012. 6. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012. 7. Lars George, "HBase: The Definitive Guide", O'Reilley, 2011. 8. Eben Hewitt, "Cassandra: The Definitive Guide", O'Reilley, 2010. 9. Alan Gates, "Programming Pig", O'Reilley, 2011.

NCS 651 Computer Networks Lab

1. Programs using TCP Sockets (like date and time server & client, echo server & client, etc.) 2. Programs using UDP Sockets (like simple DNS) 3. Programs using Raw sockets (like packet capturing and filtering) 4. Programs using RPC 5. Simulation of sliding window protocols

NCS 652 Software Engineering Lab

For any given case/ problem statement do the following;

1. Prepare a SRS document in line with the IEEE recommended standards. 2. Draw the use case diagram and specify the role of each of the actors. Also state the

precondition, post condition and function of each use case. 3. Draw the activity diagram. 4. Identify the classes. Classify them as weak and strong classes and draw the class

diagram. 5. Draw the sequence diagram for any two scenarios. 6. Draw the collaboration diagram. 7. Draw the state chart diagram. 8. Draw the component diagram. 9. Perform forward engineering in java.(Model to code conversion) 10. Perform reverse engineering in java.(Code to Model conversion) 11. Draw the deployment diagram.

NCS 653 Compiler Design Lab

1. Implementation of LEXICAL ANALYZER for IF STATEMENT 2. Implementation of LEXICAL ANALYZER for ARITHMETIC EXPRESSION 3. Construction of NFA from REGULAR EXPRESSION 4. Construction of DFA from NFA 5. Implementation of SHIFT REDUCE PARSING ALGORITHM 6. Implementation of OPERATOR PRECEDENCE PARSER 7. Implementation of RECURSIVE DESCENT PARSER 8. Implementation of CODE OPTIMIZATION TECHNIQUES 9. Implementation of CODE GENERATOR

G. B. Technical University, Lucknow

SYLLABUS B.Tech 4th Year (7th and 8th Sem)

Information Technology

Effective from session 2011-12

ECS-701 DISTRIBUTED SYSTEMS Unit–I Characterization of Distributed Systems: Introduction, Examples of distributed Systems, Resource sharing and the Web Challenges. Architectural models, Fundamental Models. Theoretical Foundation for Distributed System: Limitation of Distributed system, absence of global clock, shared memory, Logical clocks, Lamport’s & vectors logical clocks. Concepts in Message Passing Systems: causal order, total order, total causal order, Techniques for Message Ordering, Causal ordering of messages, global state, and termination detection. Unit-II Distributed Mutual Exclusion: Classification of distributed mutual exclusion, requirement of mutual exclusion theorem, Token based and non token based algorithms, performance metric for distributed mutual exclusion algorithms. Distributed Deadlock Detection: system model, resource Vs communication deadlocks, deadlock prevention, avoidance, detection & resolution, centralized dead lock detection, distributed dead lock detection, path pushing algorithms, edge chasing algorithms. Unit–III Agreement Protocols: Introduction, System models, classification of Agreement Problem, Byzantine agreement problem, Consensus problem, Interactive consistency Problem, Solution to Byzantine Agreement problem, Application of Agreement problem, Atomic Commit in Distributed Database system. Distributed Resource Management: Issues in distributed File Systems, Mechanism for building distributed file systems, Design issues in Distributed Shared Memory, Algorithm for Implementation of Distributed Shared Memory. Unit–IV Failure Recovery in Distributed Systems: Concepts in Backward and Forward recovery, Recovery in Concurrent systems, Obtaining consistent Checkpoints, Recovery in Distributed Database Systems. Fault Tolerance: Issues in Fault Tolerance, Commit Protocols, Voting protocols, Dynamic voting protocols. Unit –V Transactions and Concurrency Control: Transactions, Nested transactions, Locks, Optimistic Concurrency control, Timestamp ordering, Comparison of methods for concurrency control. Distributed Transactions: Flat and nested distributed transactions, Atomic Commit protocols, Concurrency control in distributed transactions, Distributed

deadlocks, Transaction recovery. Replication: System model and group communication, Fault - tolerant services, highly available services, Transactions with replicated data. References:

1. Singhal & Shivaratri, "Advanced Concept in Operating Systems", McGraw Hill

2. Ramakrishna,Gehrke,” Database Management Systems”, Mc Grawhill 3. Coulouris, Dollimore, Kindberg, "Distributed System: Concepts and

Design”, Pearson Education 4. Tenanuanbaum, Steen,” Distributed Systems”, PHI 5. Gerald Tel, "Distributed Algorithms", Cambridge University Press

ECS-702 DIGITAL IMAGE PROCESSING UNIT-I Introduction and Fundamentals Motivation and Perspective, Applications, Components of Image Processing System, Element of Visual Perception, A Simple Image Model, Sampling and Quantization. Image Enhancement in Frequency Domain Fourier Transform and the Frequency Domain, Basis of Filtering in Frequency Domain, Filters – Low-pass, High-pass; Correspondence Between Filtering in Spatial and Frequency Domain; Smoothing Frequency Domain Filters – Gaussian Lowpass Filters; Sharpening Frequency Domain Filters – Gaussian Highpass Filters; Homomorphic Filtering. UNIT-II Image Enhancement in Spatial Domain Introduction; Basic Gray Level Functions – Piecewise-Linear Transformation Functions: Contrast Stretching; Histogram Specification; Histogram Equalization; Local Enhancement; Enhancement using Arithmetic/Logic Operations – Image Subtraction, Image Averaging; Basics of Spatial Filtering; Smoothing - Mean filter, Ordered Statistic Filter; Sharpening – The Laplacian. UNIT-III Image Restoration A Model of Restoration Process, Noise Models, Restoration in the presence of Noise only-Spatial Filtering – Mean Filters: Arithmetic Mean filter, Geometric Mean Filter, Order Statistic Filters – Median Filter, Max and Min filters; Periodic Noise Reduction by Frequency Domain Filtering – Bandpass Filters; Minimum Mean-square Error Restoration.

UNIT-IV Morphological Image Processing Introduction, Logic Operations involving Binary Images, Dilation and Erosion, Opening and Closing, Morphological Algorithms – Boundary Extraction, Region Filling, Extraction of Connected Components, Convex Hull, Thinning, Thickening UNIT-V Registration Introduction, Geometric Transformation – Plane to Plane transformation, Mapping, Stereo Imaging – Algorithms to Establish Correspondence, Algorithms to Recover Depth Segmentation Introduction, Region Extraction, Pixel-Based Approach, Multi-level Thresholding, Local Thresholding, Region-based Approach, Edge and Line Detection: Edge Detection, Edge Operators, Pattern Fitting Approach, Edge Linking and Edge Following, Edge Elements Extraction by Thresholding, Edge Detector Performance, Line Detection, Corner Detection. References:

1. Digital Image Processing 2nd Edition, Rafael C. Gonzalvez and Richard E. Woods. Published by: Pearson Education.

2. Digital Image Processing and Computer Vision, R.J. Schalkoff. Published by: John Wiley and Sons, NY.

3. Fundamentals of Digital Image Processing, A.K. Jain. Published by Prentice Hall, Upper Saddle River, NJ.

EIT-701 Cryptography & Network Security Unit-I Introduction to security attacks, services and mechanism, Classical encryption techniques-substitution ciphers and transposition ciphers, cryptanalysis, steganography, Stream and block ciphers. Modern Block Ciphers: Block ciphers principles, Shannon’s theory of confusion and diffusion, fiestal structure, Data encryption standard(DES), Strength of DES, Idea of differential cryptanalysis, block cipher modes of operations, Triple DES Unit-II Introduction to group, field, finite field of the form GF(p), modular arithmetic, prime and relative prime numbers, Extended Euclidean Algorithm, Advanced Encryption Standard (AES) encryption and decryption Fermat’s and Euler’s theorem, Primality testing, Chinese Remainder theorem, Discrete Logarithmic Problem, Principals of public key crypto systems, RSA algorithm, security of RSA Unit-III

Message Authentication Codes: Authentication requirements, authentication functions, message authentication code, hash functions, birthday attacks, security of hash functions, Secure hash algorithm (SHA) Digital Signatures: Digital Signatures, Elgamal Digital Signature Techniques, Digital signature standards (DSS), proof of digital signature algorithm, Unit-IV Key Management and distribution: Symmetric key distribution, Diffie-Hellman Key Exchange, Public key distribution, X.509 Certificates, Public key Infrastructure. Authentication Applications: Kerberos Electronic mail security: pretty good privacy (PGP), S/MIME. Unit-V IP Security: Architecture, Authentication header, Encapsulating security payloads, combining security associations, key management. Introduction to Secure Socket Layer, Secure electronic, transaction (SET) .System Security: Introductory idea of Intrusion, Intrusion detection, Viruses and related threats, firewalls References:

1. William Stallings, “Cryptography and Network Security: Principals and Practice”,

Pearson Education. 2. Behrouz A. Frouzan: Cryptography and Network Security, TMH 3. Bruce Schiener, “Applied Cryptography”. John Wiley & Sons 4. Bernard Menezes,” Network Security and Cryptography”, Cengage

Learning. 5. Atul Kahate, “Cryptography and Network Security”, TMH

ECS-801: Artificial Intelligence Unit-I Introduction: Introduction to Artificial Intelligence, Foundations and History of Artificial Intelligence, Applications of Artificial Intelligence, Intelligent Agents, Structure of Intelligent Agents. Computer vision, Natural Language Possessing. Unit-II Introduction to Search : Searching for solutions, Uniformed search strategies, Informed search strategies, Local search algorithms and optimistic problems, Adversarial Search, Search for games, Alpha - Beta pruning.

Unit-III Knowledge Representation & Reasoning: Propositional logic, Theory of first order logic, Inference in First order logic, Forward & Backward chaining, Resolution, Probabilistic reasoning, Utility theory, Hidden Markov Models (HMM), Bayesian Networks. Unit-IV Machine Learning : Supervised and unsupervised learning, Decision trees, Statistical learning models, Learning with complete data - Naive Bayes models, Learning with hidden data - EM algorithm, Reinforcement learning, Unit-V Pattern Recognition : Introduction, Design principles of pattern recognition system, Statistical Pattern recognition, Parameter estimation methods - Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA), Classification Techniques – Nearest Neighbor (NN) Rule, Bayes Classifier, Support Vector Machine (SVM), K – means clustering. References:

1. Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”, Pearson Education

2. Elaine Rich and Kevin Knight, “Artificial Intelligence”, McGraw-Hill 3. E Charniak and D McDermott, “Introduction to Artificial Intelligence”,

Pearson Education 4. Dan W. Patterson, “Artificial Intelligence and Expert Systems”, Prentice

Hall of India,

Syllabus of Elective Subjects

EIT-061 Software Quality Engineering

UNIT-I: Introduction Defining Software Quality, Software Quality Attributes and Specification, Cost of Quality, Defects, Faults, Failures, Defect Rate and Reliability, Defect Prevention, Reduction, and Containment, Overview of Different Types of Software Review, Introduction to Measurement and Inspection Process, Documents and Metrics. UNIT-II: Software Quality Metrics Product Quality Metrics: Defect Density, Customer Problems Metric, Customer Satisfaction Metrics, Function Points, In-Process Quality Metrics: Defect Arrival Pattern, Phase-Based Defect Removal Pattern, Defect Removal Effectiveness, Metrics for Software Maintenance: Backlog Management Index, Fix Response Time, Fix Quality, Software Quality Indicators.

UNIT-III: Software Quality Management and Models Modeling Process, Software Reliability Models: The Rayleigh Model, Exponential Distribution and Software Reliability Growth Models, Software Reliability Allocation Models, Criteria for Model Evaluation, Software Quality Assessment Models: Hierarchical Model of Software Quality Assessment. UNIT-IV: Software Quality Assurance Quality Planning and Control, Quality Improvement Process, Evolution of Software Quality Assurance (SQA), Major SQA Activities, Major SQA Issues, Zero Defect Software, SQA Techniques, Statistical Quality Assurance, Total Quality Management, Quality Standards and Processes. UNIT-V: Software Verification, Validation & Testing: Verification and Validation, Evolutionary Nature of Verification and Validation, Impracticality of Testing all Data and Paths, Proof of Correctness, Software Testing, Functional, Structural and Error-Oriented Analysis & Testing, Static and Dynamic Testing Tools, Characteristics of Modern Testing Tools. References:

1. Jeff Tian, Software Quality Engineering (SQE), Wiley 2. Stephen H. Kan, Metrics and Models in Software Quality Engineering,

Addison-Wesley

EIT-062 Software Testing Unit-I: Introduction Faults, Errors, and Failures, Basics of software testing, Testing objectives, Principles of testing, Requirements, behavior and correctness, Testing and debugging, Test metrics and measurements, Verification, Validation and Testing, Types of testing, Software Quality and Reliability, Software defect tracking. Unit-II: White Box and Black Box Testing White box testing, static testing, static analysis tools, Structural testing: Unit/Code functional testing, Code coverage testing, Code complexity testing, Black Box testing, Requirements based testing, Boundary value analysis, Equivalence partitioning, state/graph based testing, Model based testing and model checking, Differences between white box and Black box testing. Unit-III: Integration, System, and Acceptance Testing Top down and Bottom up integration, Bi-directional integration, System integration, Scenario Testing, Defect Bash, Functional versus Non-functional testing, Design/Architecture verification, Deployment testing, Beta testing,

Scalability testing, Reliability testing, Stress testing, Acceptance testing: Acceptance criteria, test cases selection and execution, Unit-IV: Test Selection & Minimization for Regression Testing Regression testing, Regression test process, Initial Smoke or Sanity test, Selection of regression tests, Execution Trace, Dynamic Slicing, Test Minimization, Tools for regression testing, Ad hoc Testing: Pair testing, Exploratory testing, Iterative testing, Defect seeding. Unit-V: Test Management and Automation Test Planning, Management, Execution and Reporting, Software Test Automation: Scope of automation, Design & Architecture for automation, Generic requirements for test tool framework, Test tool selection, Testing in Object Oriented Systems. References:

1. S. Desikan and G. Ramesh, “Software Testing: Principles and Practices”, Pearson Education.

2. Aditya P. Mathur, “Fundamentals of Software Testing”, Pearson Education.

3. Naik and Tripathy, “Software Testing and Quality Assurance”, Wiley 4. K. K. Aggarwal and Yogesh Singh, “Software Engineering”, New Age

International Publication.

EIT-063 Software Reliability UNIT-I: Introduction Defining Software Reliability, Software Reliability Attributes and Specification, Concept of Defects, Faults, Failures, Defect Rate and Reliability, Defect Prevention, Reduction, and Containment, Overview of Different Types of Software Review, Introduction to Measurement and Inspection Process, Documents and Metrics. UNIT-II: Software Reliability Metrics Collection of fault and failure data, Measurement of internal and external product attributes, Customer Problems Metric, Customer Satisfaction Metrics, In-Process Quality Metrics: Defect Arrival Pattern, Phase-Based Defect Removal Pattern, Defect Removal Effectiveness, Metrics for Software Maintenance, Software Reliability indicators, Software Reliability Metrics, Static Code Metrics, Dynamic Metrics. UNIT-III: Software Reliability Assessment Models Basics of Reliability Theory, Software Reliability Problem, Modeling Process,

Software Reliability Models, Parametric Reliability Growth Models, The Rayleigh Model, Exponential Distribution and Software Reliability Growth Models, Software Quality Assessment Models: Hierarchical Model of Software Quality Assessment. UNIT-IV: Software Reliability Allocation Models Software Reliability Allocation Models, Criteria for Model Evaluation, Optimal Reliability Allocation, Quality Planning and Control, Quality Improvement Process, Evolution of Software Quality Assurance (SQA), Major SQA Activities, Major SQA Issues, Zero Defect Software. UNIT-V: Software Reliability Techniques Reliability Techniques: Trending Reliability Techniques, Predicting Reliability Techniques, Error Seeding, Failure Rate, Curve Fitting, Reliability Growth, Models and Tools: Study of tools like CASRE, SARA, SMERFS. References:

1. John Musa, “Software Reliability Engineering”, McGraw-Hill 2. Fenton, and Pfleeger, “Software Metrics: A Rigorous and Practical

Approach”, International Thomson Computer Press 3. Jeff Tian, Software Quality Engineering (SQE), Wiley 4. Stephen H. Kan, Metrics and Models in Software Quality Engineering,

Addison-Wesley

ECS-071 COMPUTATIONAL GEOMETRY UNIT-I Convex hulls: construction in 2d and 3d, lower bounds; Triangulations: polygon triangulations, representations, point-set triangulations, planar graphs UNIT-II Voronoi diagrams: construction and applicat ions, variants; Delayney triangulations: divide-and-conquer, flip and incremental algorithms, duality of Voronoi diagrams, min-max angle properties UNIT-III Geometric searching: point-location, fractional cascading, linear programming with prune and search, finger trees, concatenable queues, segment trees, interval trees; Visibility: algorithms for weak and strong visibility, visibility with reflections, art-gallery problems UNIT-IV Arrangements of lines: arrangements of hyper planes, zone theorems, many-faces complexity and algorithms; Combinatorial geometry: Ham-sandwich cuts.

UNIT-V Sweep techniques: plane sweep for segment intersections, Fortune's sweep for Voronoi diagrams, topological sweep for line arrangements; Randomization in computational geometry: algorithms, techniques for counting; Robust geometric computing, Applications of computational geometry; References:

1. Computational Geometry: An Introduction by Franco P. Preparata and Michael Ian Shamos; Springer Verlag

2. Mark de Berg , Marc van Kreveld , Mark Overmars , and Otfried Schwarzkopf, Computational Geometry, Algorithms and Applications , Springer-Verlag,

3. Ketan Mulmuley, Computational Geometry: An Introduction Through Randomized Algorithms, Prentice-Hall

4. Joseph O'Rourke, Computational Geometry in C, Cambridge University Press

.

ECS-072 COMPUTATIONAL COMPLEXITY UNIT-I Models of Computation, resources (time and space), algorithms, computability, complexity. UNIT-II Complexity classes, P/NP/PSPACE, reduction s, hardness, completeness, hierarchy, relationships between complexity classes. UNIT-III Randomized computation and complexity; Logical characterizations, incompleteness; Approximability. UNIT-IV Circuit complexity, lower bounds; Parallel computation and complexity; Counting problems; Interactive proofs. UNIT-V Probabilistically checkable proofs; Communication complexity; Quantum computation References:

1. Christos H. Papadimitriou., Combinatorial Optimization: Algorithms and Complexity , Prentice-Hall

2. Sanjeev Arora and Boaz Barak , Complexity Theory: A Modern Approach, Cambridge University Press

3. Steven Homer , Alan L. Selman , Computability and Complexity Theory , Springer

ECS-073 PARALLEL ALGORITHMS Unit-I:

Sequential model, need of alternative model, parallel computational models such as PRAM, LMCC, Hypercube, Cube Connected Cycle, Butterfly, Perfect Shuffle Computers, Tree model, Pyramid model, Fully Connected model, PRAM-CREW, EREW models, simulation of one model from another one. Unit-II: Performance Measures of Parallel Algorithms, speed-up and efficiency of PA, Cost- optimality, An example of illustrate Cost- optimal algorithms- such as summation, Min/Max on various models. Unit-III: Parallel Sorting Networks, Parallel Merging Algorithms on CREW/EREW/MCC, Parallel Sorting Networks on CREW/EREW/MCC/, linear array Unit-IV: Parallel Searching Algorithm, Kth element, Kth element in X+Y on PRAM, Parallel Matrix Transportation and Multiplication Algorithm on PRAM, MCC, Vector-Matrix Multiplication, Solution of Linear Equation, Root finding. Unit-V: Graph Algorithms - Connected Graphs, search and traversal, Combinatorial Algorithms-Permutation, Combinations, Derrangements. References:

1. M.J. Quinn, “Designing Efficient Algorithms for Parallel Computer”, McGrawHill.

2. S.G. Akl, “Design and Analysis of Parallel Algorithms” 3. S.G. Akl, ”Parallel Sorting Algorithm” by Academic Press

ECS-074 Pattern Recognition Unit-I Introduction: Basics of pattern recognition, Design principles of pattern recognition system, Learning and adaptation, Pattern recognition approaches, Mathematical foundations – Linear algebra, Probability Theory, Expectation, mean and covariance, Normal distribution, multivariate normal densities, Chi squared test. Unit-II Statistical Patten Recognition: Bayesian Decision Theory, Classifiers, Normal density and discriminant functions, Unit – III Parameter estimation methods: Maximum-Likelihood estimation, Bayesian Parameter estimation, Dimension reduction methods - Principal Component Analysis (PCA), Fisher Linear discriminant analysis, Expectation-maximization (EM), Hidden Markov Models (HMM), Gaussian mixture models. Unit - IV Nonparametric Techniques: Density Estimation, Parzen Windows, K-Nearest Neighbor Estimation, Nearest Neighbor Rule, Fuzzy classification. Unit - V Unsupervised Learning & Clustering: Criterion functions for clustering, Clustering Techniques: Iterative square - error partitional clustering – K means, agglomerative hierarchical clustering, Cluster validation. References:

1. Richard O. Duda, Peter E. Hart and David G. Stork, “Pattern Classification”, 2nd Edition, John Wiley, 2006.

2. C. M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2009.

3. S. Theodoridis and K. Koutroumbas, “Pattern Recognition”, 4th Edition, Academic Press, 2009.

ECS-075 Data Mining & Data Warehousing Unit-I Overview, Motivation(for Data Mining),Data Mining-Definition & Functionalities, Data Processing, Form of Data Preprocessing, Data Cleaning: Missing Values, Noisy Data,(Binning, Clustering, Regression, Computer and Human inspection),Inconsistent Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data Compression, Numerosity Reduction, Clustering, Discretization and Concept hierarchy generation Unit-II Concept Description:- Definition, Data Generalization, Analytical Characterization, Analysis of attribute relevance, Mining Class comparisions, Statistical measures in large Databases. Measuring Central Tendency, Measuring Dispersion of Data, Graph Displays of Basic Statistical class Description, Mining Association Rules in Large Databases, Association rule mining, mining Single-Dimensional Boolean Association rules from Transactional Databases– Apriori Algorithm, Mining Multilevel Association rules from Transaction Databases and Mining Multi-Dimensional Association rules from Relational Databases Unit-III Classification and Predictions: What is Classification & Prediction, Issues regarding Classification and prediction, Decision tree, Bayesian Classification, Classification by Back propagation, Multilayer feed-forward Neural Network, Back propagation Algorithm, Classification methods K-nearest neighbor classifiers, Genetic Algorithm. Cluster Analysis: Data types in cluster analysis, Categories of clustering methods, Partitioning methods. Hierarchical Clustering- CURE and Chameleon, Density Based Methods-DBSCAN, OPTICS, Grid Based Methods- STING, CLIQUE, Model Based Method –Statistical Approach, Neural Network approach, Outlier Analysis Unit-IV Data Warehousing: Overview, Definition, Delivery Process, Difference between Database System and Data Warehouse, Multi Dimensional Data Model, Data Cubes, Stars, Snow Flakes, Fact Constellations, Concept hierarchy, Process Architecture, 3 Tier Architecture, Data Marting. Unit-V Aggregation, Historical information, Query Facility, OLAP function and Tools. OLAP Servers, ROLAP, MOLAP, HOLAP, Data Mining interface, Security,

Backup and Recovery, Tuning Data Warehouse, Testing Data Warehouse. References:

1. M.H.Dunham,”Data Mining:Introductory and Advanced Topics” Pearson

Education 2. Jiawei Han, Micheline Kamber, ”Data Mining Concepts & Techniques”

Elsevier 3. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World : A

Practical Guide for Building Decision Support Systems, Pearson Education 4. Mallach,”Data Warehousing System”,McGraw –Hill

ECS-076 Distributed Database UNIT-I Transaction and schedules, Concurrent Execution of transaction, Conflict and View Serializability, Testing for Serializability, Concepts in Recoverable and Cascadeless schedules. UNIT –II Lock based protocols, time stamp based protocols, Multiple Granularity and Multiversion Techniques, Enforcing serializablity by Locks, Locking system with multiple lock modes, architecture for Locking scheduler UNIT III Distributed Transactions Management, Data Distribution, Fragmentation and Replication Techniques, Distributed Commit, Distributed Locking schemes, Long duration transactions, Moss Concurrency protocol. UNIT –IV Issues of Recovery and atomicity in Distributed Databases, Traditional recovery techniques, Log based recovery, Recovery with Concurrent Transactions, Recovery in Message passing systems, Checkpoints, Algorithms for recovery line, Concepts in Orphan and Inconsistent Messages. UNIT V Distributed Query Processing, Multiway Joins, Semi joins, Cost based query optimization for distributed database, Updating replicated data, protocols for Distributed Deadlock Detection, Eager and Lazy Replication Techniques References

1. Silberschatz, orth and Sudershan, Database System Concept’, Mc Graw Hill

2. Ramakrishna and Gehrke,’ Database Management System, Mc Graw Hill 3. Garcia-Molina, Ullman,Widom,’ Database System Implementation’

Pearson Education 4. Ceei and Pelagatti,’Distributed Database’, TMH 5. Singhal and Shivratri, ’Advance Concepts in Operating Systems’ MC Graw

Hill

ECS-077 Data Compression Unit - I: Compression Techniques: Loss less compression, Lossy Compression, Measures of prefonnance, Modeling and coding, Mathematical Preliminaries for Lossless compression: A brief introduction to information theory, Models: Physical models, Probability models, Markov models, composite source model, Coding: uniquely decodable codes, Prefix codes. Unit – II: The Huffman coding algorithm: Minimum variance Huffman codes, Adaptive Huffman coding: Update procedure, Encoding procedure, Decoding procedure. Golomb codes, Rice codes, Tunstall codes, Applications of Hoffman coding: Loss less image compression, Text compression, Audio Compression. Unit-III: Coding a sequence, Generating a binary code, Comparison of Binary and Huffman cding, Applications: Bi-level image compression-The JBIG standard, JBIG2, Image compression. Dictionary Techniques: Introduction, Static Dictionary: Diagram Coding, Adaptive Dictionary. The LZ77 Approach, The LZ78 Approach, Applications: File Compression-UNIX compress, Image Compression: The Graphics Interchange Format (GIF), Compression over Modems: V.42 bits, Predictive Coding: Prediction with Partial match (ppm): The basic algorithm, The ESCAPE SYMBOL, length of context, The Exclusion Principle, The Burrows-Wheeler Transform: Move-to-front coding, CALIC, JPEG-LS, Multi-resolution Approaches, Facsimile Encoding, Dynamic Markoy Compression. Unit – IV: Distortion criteria, Models, Scalar Ouantization: The Quantization problem, Uniform Quantizer, Adaptive Quantization, Non uniform Quantization. Unit-V: Advantages of Vector Quantization over Scalar Quantization, The Linde-Buzo-Gray Algorithm, Tree structured Vector Quantizers. Structured Vector Quantizers.

References: 1. Khalid Sayood, Introduction to Data Compression, Morgan Kaufmann Publishers

EIT-071 Discrete Structures Unit-I Set Theory: Introduction, Combination of sets, Multisets, Ordered pairs. Proofs of some general identities on sets. Relations: Definition, Operations on relations, Properties of relations, Composite Relations, Equality of relations, Recursive definition of relation, Order of relations. Functions: Definition, Classification of functions, Operations on functions, Recursively defined functions. Growth of Functions. Natural Numbers: Introduction, Mathematical Induction, Variants of Induction, Induction with Nonzero Base cases. Proof Methods, Proof by counter – example, Proof by contradiction. Unit-II Algebraic Structures: Definition, Groups, Subgroups and order, Cyclic Groups, Cosets, Lagrange's theorem, Normal Subgroups, Permutation and Symmetric groups, Group Homomorphisms, Definition and elementary properties of Rings and Fields, Integers Modulo n. Unit-III Partial order sets: Definition, Partial order sets, Combination of partial order sets, Hasse diagram. Lattices: Definition, Properties of lattices – Bounded, Complemented, Modular and Complete lattice. Boolean Algebra: Introduction, Axioms and Theorems of Boolean algebra, Algebraic manipulation of Boolean expressions. Simplification of Boolean Functions, Karnaugh maps, Logic gates, Digital circuits and Boolean algebra. Unit-IV Propositional Logic: Proposition, well formed formula, Truth tables, Tautology, Satisfiability, Contradiction, Algebra of proposition, Theory of Inference Predicate Logic: First order predicate, well formed formula of predicate, quantifiers, Inference theory of predicate logic. Unit-V Trees : Definition, Binary tree, Binary tree traversal, Binary search tree. Graphs: Definition and terminology, Representation of graphs, Multigraphs, Bipartite graphs, Planar graphs, Isomorphism and Homeomorphism of graphs, Euler and Hamiltonian paths,

Graph coloring Recurrence Relation & Generating function: Recursive definition of functions, Recursive algorithms, Method of solving recurrences. Combinatorics: Introduction, Counting Techniques, Pigeonhole Principle References:

1. Liu and Mohapatra, “Elements of Distcrete Mathematics”, McGraw Hill 2. Jean Paul Trembley, R Manohar, Discrete Mathematical Structures with

Application to Computer Science, McGraw-Hill 3. R.P. Grimaldi, Discrete and Combinatorial Mathematics, Addison Wesley, 4. Kenneth H. Rosen, Discrete Mathematics and Its Applications, McGraw-

Hill, 5. B. Kolman, R.C. Busby, and S.C. Ross, Discrete Mathematical Structures,

PHI

EIT-072 THEORY OF AUTOMATA AND FORMAL LANGUAGES

Unit – I Introduction; Alphabets, Strings and Languages; Automata and Grammars, Deterministic finite Automata (DFA)-Formal Definition, Simplified notation: State transition graph, Transition tabl e, Language of DFA, Nondeterministic finite Automata (NFA), NFA with epsilon transit ion, Language of NFA, Equi valence of NFA and DFA, Minimization of Finite Automata, Distinguis hing one string from other, Myhill-Nerode Theorem Unit – II Regular expression (RE) , Definition, Operators of regular expression and their precedence, Algebraic laws for Regular expressions, Kleen’s Theorem, Regular expression to FA, DFA to Regular expression, Arden Theorem, Non Regular Languages, Pumping Lemma for regular Languages . Application of Pumping Lemma, Closure properties of Regu lar Languages, Decision properti es of Regular Languages, FA with output: Moore and Mealy machine, Equivalence of Moore and Mealy Machine, Applications and Limitation of FA. Unit – III Context free grammar (CFG) and Contex t Freee Languages (CFL): Definition, Examples, Derivation , Derivation trees, Am biguity in Grammer, Inherent ambiguity, Ambiguous to Unambiguous CFG, Useless sym bols, Simplification of CFGs, Normal forms for CFGs: CNF and GNF, Closure proper ties of CFLs, Decision Properties of CFLs: Emptiness, Finiteness and Memership, Pumping lemma for CFLs,

Unit – IV Push Down Automata (PDA): Description and definition, Instantaneous Description, Language of PDA, Acceptance by Final state, Acceptance by empty stack, Deterministic PDA, Equivalence of PDA and CFG, CFG to PDA and PDA to CFG, Two stack PDA Unit – V Turing machines (TM): Basic model, definit ion and representatio n, Instantaneous Description, Language acceptance by TM, Variants of Turing Machine, TM as Computer of Integer functions, Universal TM, Chur ch’s Thesis, Recursive and recursively enumerable languages, Halting problem, Introduction to Undecidability, Undecidable problems about TMs. Post correspondence problem (PCP), Modified PCP, Introduction to recursive function theory References:

1. Hopcroft, Ullman, “Introduction to Automata Theory, Languages and Computation”, Pearson Education

2. K.L.P. Mishra and N.Chandrasekaran, “Theory of Computer Science : Automata, Languages and Computation”, PHI

3. Martin J. C., “Introduction to Languages and Theory of Computations”, TMH

4. Papadimitrou, C. and Lewis, C.L., “Elements of the Theory of Computation”, PHI

EIT-073 Bioinformatics Unit I: Bioinformatics objectives and overviews, Interdisciplinary nature of Bioinformatics, Data integration, Data analysis, Major Bioinformatics databases and tools. Metadata: Summary & reference systems, finding new type of data online. Molecular Biology and Bioinformatics: Systems approach in biology, Central dogma of molecular biology, problems in molecular approach and the bioinformatics approach, oerview of the bioinformatics applications. Unit II: Basic chemistry of nucleic acids, Structure of DNA, Structure of RNA, DNA Replication, -Transcription, -Translation, Genes- the functional elements in DNA, Analyzing DNA,DNA sequencing. Proteins: Amino acids, Protein structure, Secondary, Tertiary and Quaternary structure, Protein folding and function, Nucleic acid-Protein interaction.

Unit III: Perl Basics, Perl applications for bioinformatics- Bioperl, Linux Operating System, mounting/unmounting files, tar, gzip / gunzip, telnet, ftp, developing applications on Linux OS, Understanding and Using Biological Databases, Overview of Java, CORBA, XML, Web deployment concepts. Unit IV: Genome, Genomic sequencing, expressed sequence tags, gene expression, transcription factor binding sites and single nucleotide polymorphism. Computational representations of molecular biological data storage techniques: databases (flat, relational and object oriented), and controlled vocabularies, general data retrieval techniques: indices, Boolean search, fuzzy search and neighboring, application to biological data warehouses. Unit V: Macromolecular structures, chemical compounds, generic variability and its connection to clinical data. Representation of patterns and relationships: sequence alignment algorithms, regular expressions, hierarchies and graphical models, Phylogenetics. BLAST. References 1. D E Krane & M L Raymer, ” Fundamental concepts of Bioinformatics”,

Perason Education. 2. Rastogi, Mendiratta, Rastogi, “Bioinformatics Methods & applications,

Genomics, Proteomics & Drug Discovery” PHI, New Delhi 3. Shubha Gopal et.al. “ Bioinformatics: with fundamentals of genomics and

proteomics”, Mc Graw Hill. 4. O’Reilly, “ Developing Bio informatics computer skills”, CBS 5. Forsdyke, “Evolutionary Bioinformatics”, Springer

EIT -074 IT in Forensic Science UNIT I Overview of Biometrics, Biometric Identification, Biometric Verification, Biometric Enrollment, Biometric System Security. Authentication and Biometrics: Secure Authentication Protocols, Access Control Security Services, Matching Biometric Samples, Verification by humans. Common biometrics: Finger Print Recognition, Face Recognition, Speaker Recognition, Iris Recognition, Hand Geometry, Signature Verification UNIT II Introduction to Information Hiding: Technical Steganography, Linguistic Steganography, Copy Right Enforcement, Wisdom from Cryptography Principles of Steganography: Framework for Secret Communication, Security of Steganography System, Information Hiding in Noisy Data , Adaptive versus non-Adaptive Algorithms, Active and Malicious Attackers, Information hiding in Written Text. UNIT III A Survey of Steganographic Techniques: Substitution systems and Bit Plane Tools, Transform Domain Techniques: - Spread Spectrum and Information hiding, Statistical Steganography, Distortion Techniques, Cover Generation Techniques. Steganalysis: Looking for Signatures: - Extracting hidden Information, Disabling Hidden Information. UNIT IV Watermarking and Copyright Protection: Basic Watermarking, Watermarking Applications, Requirements and Algorithmic Design Issues, Evaluation and Benchmarking of Watermarking system. Transform Methods: Fourier Transformation, Fast Fourier Transformation, Discrete Cosine Transformation, Mellin-Fourier Transformation, Wavelets, Split Images in Perceptual Bands. Applications of Transformation in Steganography. UNIT V Computer Forensics, Rules of evidence, Evidence dynamics, Evidence collection, Data recovery, Preservation of digital evidence, surveillance tools for future warfare,

References: 1. Katzendbisser, Petitcolas, " Information Hiding Techniques for Steganography

and Digital Watermarking", Artech House. 2. Peter Wayner, "Disappearing Cryptography: Information Hiding,

Steganography and Watermarking 2/e", Elsevier 3. Bolle, Connell et. al., "Guide to Biometrics", Springer 4. John Vecca, “Computer Forensics: Crime scene Investigation”, Firewall

Media 5. Christopher L.T. Brown, “Computer Evidence: Collection and Preservation”,

Firewall Media

ECS-081 Real Time System UNIT-I: Introduction

Definition, Typical Real Time Applications: Digital Control, High Level Controls, Signal Processing etc., Release Times, Deadlines, and Timing Constraints, Hard Real Time Systems and Soft Real Time Systems, Reference Models for Real Time Systems: Processors and Resources, Temporal Parameters of Real Time Workload, Periodic Task Model, Precedence Constraints and Data Dependency. UNIT-II: Real Time Scheduling

Common Approaches to Real Time Scheduling: Clock Driven Approach, Weighted Round Robin Approach, Priority Driven Approach, Dynamic Versus Static Systems, Optimality of Effective-Deadline-First (EDF) and Least-Slack-Time-First (LST) Algorithms, Rate Monotonic Algorithm, Offline Versus Online Scheduling, Scheduling Aperiodic and Sporadic jobs in Priority Driven and Clock Driven Systems. UNIT-III: Resources Sharing

Effect of Resource Contention and Resource Access Control (RAC), Non-preemptive Critical Sections, Basic Priority-Inheritance and Priority-Ceiling Protocols, Stack Based Priority-Ceiling Protocol, Use of Priority-Ceiling Protocol in Dynamic Priority Systems, Preemption Ceiling Protocol, Access Control in Multiple-Unit Resources, Controlling Concurrent Accesses to Data Objects. UNIT-IV: Real Time Communication Basic Concepts in Real time Communication, Soft and Hard RT Communication systems, Model of Real Time Communication, Priority-Based Service and Weighted Round-Robin Service Disciplines for Switched Networks, Medium

Access Control Protocols for Broadcast Networks, Internet and Resource Reservation Protocols UNIT-V: Real Time Operating Systems and Databases Features of RTOS, Time Services, UNIX as RTOS, POSIX Issues, Charecteristic of Temporal data, Temporal Consistencey, Concurrency Control, Overview of Commercial Real Time databases References:

1. Real Time Systems by Jane W. S. Liu, Pearson Education Publication. 2. Mall Rajib, “Real Time Systems”, Pearson Education 3. Albert M. K. Cheng , “Real-Time Systems: Scheduling, Analysis, and

Verification”, Wiley.

ECS-082 Software Project Management UNIT-I: Introduction and Software Project Planning Fundamentals of Software Project Management (SPM), Need Identification, Vision and Scope document, Project Management Cycle, SPM Objectives, Management Spectrum, SPM Framework, Software Project Planning, Planning Objectives, Project Plan, Types of project plan, Structure of a Software Project Management Plan, Software project estimation, Estimation methods, Estimation models, Decision process. UNIT-II: Project Organization and Scheduling Project Elements, Work Breakdown Structure (WBS), Types of WBS, Functions, Activities and Tasks, Project Life Cycle and Product Life Cycle, Ways to Organize Personnel, Project schedule, Scheduling Objectives, Building the project schedule, Scheduling terminology and techniques, Network Diagrams: PERT, CPM, Bar Charts: Milestone Charts, Gantt Charts. UNIT-III: Project Monitoring and Control Dimensions of Project Monitoring & Control, Earned Value Analysis, Earned Value Indicators: Budgeted Cost for Work Scheduled (BCWS), Cost Variance (CV), Schedule Variance (SV), Cost Performance Index (CPI), Schedule Performance Index (SPI), Interpretation of Earned Value Indicators, Error Tracking, Software Reviews, Types of Review: Inspections, Deskchecks, Walkthroughs, Code Reviews, Pair Programming. UNIT-IV: Software Quality Assurance and Testing Testing Objectives, Testing Principles, Test Plans, Test Cases, Types of Testing, Levels of Testing, Test Strategies, Program Correctness, Program Verification &

validation, Testing Automation & Testing Tools, Concept of Software Quality, Software Quality Attributes, Software Quality Metrics and Indicators, The SEI Capability Maturity Model CMM), SQA Activities, Formal SQA Approaches: Proof of correctness, Statistical quality assurance, Cleanroom process. UNIT-V: Project Management and Project Management Tools Software Configuration Management: Software Configuration Items and tasks, Baselines, Plan for Change, Change Control, Change Requests Management, Version Control, Risk Management: Risks and risk types, Risk Breakdown Structure (RBS), Risk Management Process: Risk identification, Risk analysis, Risk planning, Risk monitoring, Cost Benefit Analysis, Software Project Management Tools: CASE Tools, Planning and Scheduling Tools, MS-Project. References:

1. M. Cotterell, Software Project Management, Tata McGraw-Hill Publication. 2. Royce, Software Project Management, Pearson Education 4. Kieron Conway, Software Project Management, Dreamtech Press 5. S. A. Kelkar, Software Project Management, PHI Publication.

ECS-083 Embedded Systems Unit-I Introduction to embedded systems: Classification, Characteristics and requirements, Applications Unit-II Timing and clocks in Embedded systems, Task Modeling and management, Real time operating system issues. Unit-III Signals, frequency spectrum and sampling, digitization (ADC, DAC), Signal Conditioning and Processing. Modeling and Characterization of Embedded Computation System. Unit-IV Embedded Control and Control Hierarchy, Communication strategies for embedded systems: Encoding and Flow control. Unit-V Fault-Tolerance, Formal Verification. Trends in Embedded Processor, OS, Development Language References:

1. H.Kopetz, “Real-Time Systems”, Kluwer 2. R.Gupta, “Co-synthesis of Hardware and Software for Embedded

Systems”, Kluwer 3. Shibu K.V., “Introduction to Embedded Systems”, TMH 4. Marwedel, “Embedded System Design”, Springer

ECS-084 Cryptography & Network Security Unit-I Introduction to security attacks, services and mechanism, Classical encryption techniques-substitution ciphers and transposition ciphers, cryptanalysis, steganography, Stream and block ciphers. Modern Block Ciphers: Block ciphers principles, Shannon’s theory of confusion and diffusion, fiestal structure, Data encryption standard(DES), Strength of DES, Idea of differential cryptanalysis, block cipher modes of operations, Triple DES Unit-II Introduction to group, field, finite field of the form GF(p), modular arithmetic, prime and relative prime numbers, Extended Euclidean Algorithm, Advanced Encryption Standard (AES) encryption and decryption Fermat’s and Euler’s theorem, Primality testing, Chinese Remainder theorem, Discrete Logarithmic Problem, Principals of public key crypto systems, RSA algorithm, security of RSA Unit-III Message Authentication Codes: Authentication requirements, authentication functions, message authentication code, hash functions, birthday attacks, security of hash functions, Secure hash algorithm (SHA) Digital Signatures: Digital Signatures, Elgamal Digital Signature Techniques, Digital signature standards (DSS), proof of digital signature algorithm, Unit-IV Key Management and distribution: Symmetric key distribution, Diffie-Hellman Key Exchange, Public key distribution, X.509 Certificates, Public key Infrastructure. Authentication Applications: Kerberos Electronic mail security: pretty good privacy (PGP), S/MIME. Unit-V IP Security: Architecture, Authentication header, Encapsulating security payloads, combining security associations, key management. Introduction to Secure Socket Layer, Secure electronic, transaction (SET) System Security: Introductory idea of Intrusion, Intrusion detection, Viruses and related threats, firewalls References:

1. William Stallings, “Cryptography and Network Security: Principals and

Practice”, Pearson Education. 2. Behrouz A. Frouzan: Cryptography and Network Security, Tata McGraw

Hill 3. Bruce Schiener, “Applied Cryptography”. John Wiley & Sons 4. Bernard Menezes,” Network Security and Cryptography”, Cengage

Learning. 5. Atul Kahate, “Cryptography and Network Security”, Tata McGraw Hill

ECS-085 Neural Networks Unit-I: Neurocomputing and Neuroscience Historical notes, human Brain, neuron Mode l, Knowledge representation, Al and NN. Learning process: Supervised and unsuperv ised learning, Error correction learning,competitive learning, adaptation, statistical nature of the learning process. Unit-II: Data processing Scaling, normalization, Transformation (FT/FFT), principal component analysis, regression, co-variance matrix, eigen values & eigen vectors. Basic Models of Artificial neurons, activation Functions, aggregation function, single neuron computation, multilayer perceptron, least mean square algorithm, gradient descent rule, nonlinearly separable problems and bench mark problems in NN. Unit-III Multilayered network architecture, back propagation algorithm, heuristics for making BP-algorithm performs better. Accelerated learning BP (like recursive least square, quick prop, RPROP algorithm), approximation properties of RBF networks and comparison with multilayer perceptran. Unit-IV Recurrent network and temporal feed-forward network, implementation with BP, self organizing map and SOM algorithm, properties of feature map and computer simulation. Principal component and Independent component analysis, application to image and signal processing. Unit-V Complex valued NN and complex valued BP, analyticity of activation function, application in 2D information processing. Complexity analysis of network models. Soft computing. Neuro-Fuzzy-genetic algorithm Integration.

References:

1. J.A. Anderson, An Intoduction to Neural Networks, MIT 2. Hagen Demuth Beale, Neural Network Design, Cengage Learning 3. R.L. Harvey, Neural Network Principles, PHI 4. Kosko, Neural Network and Fuzzy Sets, PHI

ECS-086 Natural Language Processing Unit-I Introduction to Natural Language Understanding: The study of Language, Applications of NLP, Evaluating Language Understanding Systems, Different levels of Language Analysis, Representations and Understanding, Organization of Natural language Understanding Systems, Linguistic Background: An outline of English syntax. Unit-II Introduction to semantics and knowledge representation, Some applications like machine translation, database interface. Unit-III Grammars and Parsing: Grammars and sentence Structure, Top-Down and Bottom-Up Parsers, Transition Network Grammars, Top- Down Chart Parsing. Feature Systems and Augmented Grammars: Basic Feature system for English, Morphological Analysis and the Lexicon, Parsing with Features, Augmented Transition Networks. Unit-IV Grammars for Natural Language: Auxiliary Verbs and Verb Phrases, Movement Phenomenon in Language, Handling questions in Context-Free Grammars. Human preferences in Parsing, Encoding uncertainty, Deterministic Parser. Unit-V Ambiguity Resolution: Statistical Methods, Probabilistic Language Processing, Estimating Probabilities, Part-of-Speech tagging, Obtaining Lexical Probabilities, Probabilistic Context-Free Grammars, Best First Parsing. Semantics and Logical Form, Word senses and Ambiguity, Encoding Ambiguity in Logical Form. References:

1. Akshar Bharti, Vineet Chaitanya and Rajeev Sangal, NLP: A Paninian Perspective, Prentice Hall, New Delhi

2. James Allen, Natural Language Understanding, Pearson Education 3. D. Jurafsky, J. H. Martin, Speech and Language Processing, Pearson

Education

4. L.M. Ivansca, S. C. Shapiro, Natural Language Processing and Language Representation

5. T. Winograd, Language as a Cognitive Process, Addison-Wesley

ECS-087 Mobile Computing Unit – I Introduction, issues in mobile computing, overview of wireless telephony: cellular concept, GSM: air-interface, channel structure, location management: HLR-VLR, hierarchical, handoffs, channel allocation in cellular systems, CDMA, GPRS. Unit - II Wireless Networking, Wireless LAN Overview: MAC issues, IEEE 802.11, Blue Tooth, Wireless multiple access protocols, TCP over wireless, Wireless applications, data broadcasting, Mobile IP, WAP: Architecture, protocol stack, application environment, applications. Unit – III Data management issues, data replication for mobile computers, adaptive clustering for mobile wireless networks, File system, Disconnected operations. Unit - IV Mobile Agents computing, security and fault tolerance, transaction processing in mobile computing environment. Unit – V Adhoc networks, localization, MAC issues, Routing protocols, global state routing (GSR), Destination sequenced distance vector routing (DSDV), Dynamic source routing (DSR), Ad Hoc on demand distance vector routing (AODV), Temporary ordered routing algorithm (TORA), QoS in Ad Hoc Networks, applications. References:

1. J. Schiller, Mobile Communications, Addison Wesley. 2. Charles Perkins, Mobile IP, Addison Wesley. 3. Charles Perkins, Ad hoc Networks, Addison Wesley. 4. Upadhyaya, “Mobile Computing”, Springer

ECS-088 Soft Computing Unit-I: ARTIFICIAL NEURAL NETWORKS Basic concepts - Single layer perception - Multilayer Perception - Supervised and Unsupervised learning – Back propagation networks - Kohnen's self organizing networks - Hopfield network. Unit-II: FUZZY SYSTEMS Fuzzy sets, Fuzzy Relations and Fuzzy reasoning, Fuzzy functions - Decomposition - Fuzzy automata and languages - Fuzzy control methods - Fuzzy decision making. Unit-III: NEURO - FUZZY MODELING Adaptive networks based Fuzzy interface systems - Classification and Regression Trees - Data clustering algorithms - Rule based structure identification - Neuro-Fuzzy controls - Simulated annealing – Evolutionary computation. Unit-IV: GENETIC ALGORITHMS Survival of the Fittest - Fitness Computations - Cross over - Mutation - Reproduction - Rank method - Rank space method. Unit-V: APPLICATION OF SOFT COMPUTING Optimiation of traveling salesman problem using Genetic Algorithm, Genetic algorithm based Internet Search Techniques, Soft computing based hybrid fuzzy controller, Intoduction to MATLAB Environment for Soft computing Techniques. References:

1.Sivanandam, Deepa, “ Principles of Soft Computing”, Wiley

2.Jang J.S.R, Sun C.T. and Mizutani E, "Neuro-Fuzzy and Soft

computing", Prentice

Hall 3. Timothy J. Ross, "Fuzzy Logic with Engineering Applications", McGraw Hill 4. Laurene Fausett, "Fundamentals of Neural Networks", Prentice Hall 5. D.E. Goldberg, "Genetic Algorithms: Search, Optimization and Machine

Learning", Addison Wesley 6. Wang, “Fuzzy Logic”, Springer

EIT-081 Digital Image Processing UNIT-I Introduction and Fundamentals Motivation and Perspective, Applications, Components of Image Processing System, Element of Visual Perception, A Simple Image Model, Sampling and Quantization. Image Enhancement in Frequency Domain Fourier Transform and the Frequency Domain, Basis of Filtering in Frequency Domain, Filters – Low-pass, High-pass; Correspondence Between Filtering in Spatial and Frequency Domain; Smoothing Frequency Domain Filters – Gaussian Lowpass Filters; Sharpening Frequency Domain Filters – Gaussian Highpass Filters; Homomorphic Filtering. UNIT-II Image Enhancement in Spatial Domain Introduction; Basic Gray Level Functions – Piecewise-Linear Transformation Functions: Contrast Stretching; Histogram Specification; Histogram Equalization; Local Enhancement; Enhancement using Arithmetic/Logic Operations – Image Subtraction, Image Averaging; Basics of Spatial Filtering; Smoothing - Mean filter, Ordered Statistic Filter; Sharpening – The Laplacian. UNIT-III Image Restoration A Model of Restoration Process, Noise Models, Restoration in the presence of Noise only-Spatial Filtering – Mean Filters: Arithmetic Mean filter, Geometric Mean Filter, Order Statistic Filters – Median Filter, Max and Min filters; Periodic Noise Reduction by Frequency Domain Filtering – Bandpass Filters; Minimum Mean-square Error Restoration. UNIT-IV Morphological Image Processing Introduction, Logic Operations involving Binary Images, Dilation and Erosion, Opening and Closing, Morphological Algorithms – Boundary Extraction, Region Filling, Extraction of Connected Components, Convex Hull, Thinning, Thickening UNIT-V Registration Introduction, Geometric Transformation – Plane to Plane transformation, Mapping, Stereo Imaging – Algorithms to Establish Correspondence, Algorithms to Recover Depth Segmentation Introduction, Region Extraction, Pixel-Based Approach, Multi-level Thresholding,

Local Thresholding, Region-based Approach, Edge and Line Detection: Edge Detection, Edge Operators, Pattern Fitting Approach, Edge Linking and Edge Following, Edge Elements Extraction by Thresholding, Edge Detector Performance, Line Detection, Corner Detection. References:

1. Digital Image Processing 2nd Edition, Rafael C. Gonzalvez and Richard E. Woods. Published by: Pearson Education.

2. Digital Image Processing and Computer Vision, R.J. Schalkoff. Published by: John Wiley and Sons, NY.

3. Fundamentals of Digital Image Processing, A.K. Jain. Published by Prentice Hall, Upper Saddle River, NJ.

EIT-082 Multimedia Systems Unit-I: Introduction Introduction to Multimedia, Multimedia Information, Multimedia Objects, Multimedia in business and work. Convergence of Computer, Communication and Entertainment products Stages of Multimedia Projects Multimedia hardware, Memory & storage devices, Communication devices, Multimedia software's, presentation tools, tools for object generations, video, sound, image capturing, authoring tools, card and page based authoring tools. Unit-II: Multimedia Building Blocks Text, Sound MIDI, Digital Audio, audio file formats, MIDI under windows environment Audio & Video Capture. Unit-III: Data Compression Huffman Coding, Shannon Fano Algorithm, Huffman Algorithms, Adaptive Coding, Arithmetic Coding Higher Order Modelling. Finite Context Modelling, Dictionary based Compression, Sliding Window Compression, LZ77, LZW compression, Compression, Compression ratio loss less & lossy compression. Unit-IV: Speech Compression & Synthesis Digital Audio concepts, Sampling Variables, Loss less compression of sound, loss compression & silence compression. Unit-V: Images Multiple monitors, bitmaps, Vector drawing, lossy graphic compression, image file formatic animations Images standards, JPEG Compression, Zig Zag Coding, Multimedia Database.Content based retrieval for text and images,Video:Video

representation, Colors, Video Compression, MPEG standards, MHEG Standard Video Streaming on net, Video Conferencing, Multimedia Broadcast Services, Indexing and retrieval of Video Database, recent development in Multimedia. References:

1. Tay Vaughan, “Multimedia, Making IT Work”, McGraw Hill. 2. Buford, “Multimedia Systems”, Addison Wesley. 3. Mark Nelson, “Data Compression Hand Book”, BPB. 4. Sleinreitz, “Multimedia System”, Addison Wesley.