Syllabus Part2

8/3/2019 Syllabus Part2

1/28

www.missionmca.com 1

Syllabus M Sc Information Technology Year 2

M Sc Information Technology Year II, Paper I, Term ISUBJECT: SOFTWARE TESTING

ObjectivesTo improve your understanding of software testing - its purpose and nature -a n d r a i s e y o u r a w a r e n e s s o f i s s u e s a n d c o n s t r a i n t s a r o u nd t e s t i n g . T o p r o v i d e a professional qualification widely recognized byemployers, customers and peers. Tolearnstandard terminology. Discover good sources of information. To provide a completep i c t u r e o f t h e t e s t a c t i v i t i e s a n d p r o c e s s e s f r o m r e q u i r e m e n t s r e v i e w t o s y s t e m implementation.

Pre-requisites:Software Engineering, OOAD

DETAILED SYLLABUS1.Introduction:Defect, Defect Vs failures, Process problems and defect rates,Thebusiness perspective for testing

2.Building a Software Testing Strategy:Computer system strategic risk, Economicsof test ing, Commo n computerproblems, Economics of SDLC testing, Testing- anorganizational issue,

Establishing a testing policy, Structured approach to testing, Teststrategy, Testingmethodology

3.Establishing a Software Testing Methodology:Introduction, Verification andval idation, Functional and stru ctural tes ting,Workbench concept, Considerations indeveloping testing methodologies

4.Determining Software Testing Techniques:Testing techniques/tool selectionprocess, Selecting techniques/tools,Structural system testing techniques, Functionalsystem testing techniques, Unittesting techniques, Functional testing and analysis

5.Selecting and Installing Software Testing Tools:Testing tools-Hammers of testing,Selecting and using the test tools, Appointingmanagers for testing tools

6.Software Testing Process:Cost of computer testing, Life cycle testingconcept,Verification and validation in the software development process, Software testingprocess, Workbench skills

7.Software Testing Process:


2/28


3/28


1.Introduction:Security, Attacks, Computer criminals, Method of defense2. Program Security:

Secure programs, Non-malicious program errors, Viruses andother maliciouscode, Targeted malicious code, Controls against program threats

3.Operating System Security:Protected objects and methods of protection, Memoryaddress protection, Controlof access to general objects, File protection mechanism,Authentication:Authentication basics, Password, Challenge-response, Biometrics.

4.Database Security:Security requirements, Reliability and integrity, Sensitive data,Interface,Multilevel database, Proposals for multilevel security

5.Security in Networks:Threats in networks, Network security control, Firewalls,Intrusion detectionsystems, Secure e-mail, Networks and cryptography, Exampleprotocols: PEM, SSL, IPsec

6.Administrating Security:Security planning, Risk analysis, Organizational securitypolicies, Physical security.

7. Legal, Privacy, and Ethical Issues in Computer Security: Protecting programsand data, Information and law, Rights of employees

and employers, Software failures,Computer crime, Privacy, Ethical issuesin computer society, Case studies of ethics

Books

Text Books:1. C. P. Pfleeger, and S. L. Pfleeger,

Security in Computing, Pearson Education.2. Matt Bishop, Computer Security: Art and Science, Pearson Education.

References :1. Stallings, Cryptography And Network Security: Principles and practice2. Kaufman, Perlman, Speciner, Network Security3. Eric Maiwald, Network Security : A Beginners Guide, TMH4. Macro Pistoia, Java Network Security


4/28


, Pearson Education5. Whitman, Mattord, Principles of information security,Thomson

Assignments:10 assignments covering the syllabus has tobe submitted

M Sc Information Technology Year II, Paper II, TermISUBJECT: Artificial Intelligence

1 AI and Internal RepresentationArtificial Intelligence and the World, Representation in AI, Properties of InternalRepresentation,The Predicate Calculus, Predicates and Arguments, Connectives

Variables and Quantification,How to Use the Predicate Calculus, Other Kinds ofInference Indexing, Pointers and AlternativeNotations, Indexing, The IsaHierarchy, Slot-Assertion Notation, Frame Notation

2 LispsLisps, Typing at Lisp, Defining Programs, Basic Flow of Control in Lisp, LispStyle, Atoms andLists, Basic Debugging, Building Up List Structure, More onPredicates, Properties, Pointers,Cell Notation and the Internals (Almost) of Lisp,Destructive Modification of Lists, The for Function ,Recursion, Scope ofVariables, Input/Output, Macros

3. Neural Networks and Fuzzy systems

Neural and fuzzy machine Intelligence, Fuzziness as Multivalence, TheDynamical Systemsapproach to Machine Intelligence, The brain as a dynamicalsystem, Neural and fuzzy systemsas function Estimators, Neural Networks astrainable Dynamical system, Fuzzy systems andapplications, Intelligent Behavioras Adaptive Model free Estimation, Generalization andcreativity, Learning aschange, Symbol vs Numbers, Rules vs Principles, Expert systemKnowledge asrule trees, Symbolic vs Numeric Processing, Fuzzy systems asStructuredNumerical estimators, Generating Fuzzy rules with product spaceClustering, Fuzzy Systems asParallel associators, Fuzzy systems as Principle

based Systems

1. Neural Network TheoryNeuronal Dynamics: Activations and signals

,Neurons as functions, signal monotonicity,Biological Activations andsignals, Neuron Fields, Neuron Dynamical Systems, Commonsignalfunctions, Pulse-Coded Signal functions

2. Genetic Algorithms


5/28


A simple genetic algorithm, A simulation by hands, similaritytemplates(Schemata),Mathematical foundations, Schema Processing atwork, The two- armed and k-armed BanditProblem, The building block

hypothesis, The minimal Deceptive Problem

Computer implementation of Genetic algorithm, Data Structures,Reproduction , Cross over andMutation, Time to reproduce and time toCross Mapping objective function to fitness form,FitnessscalingApplications of genetic algorithm, De Jong and FunctionOptimization, Improvement in basictechniques, Introduction to Geneticsbased machine learning, applications of genetic basedmachine leaning

3. Data MiningIntroduction to Data Mining, Computer systems that can learn, Machine

learning andmethodology of science, Concept learning, Data ware house,designing decision supportsystems, Client server and data warehousing,Knowledge Discovery Process, VisualizationTechniques, K- nearestneighbor, Decision trees, OLAP tools, Neural networks, Geneticalgorithm,Setting up a KDD environment, Real life applications, Customerprofiling,Discovering foreign key relationships

Assignments

10 assignments covering the syllabus has to be submitted

Text bookIntroduction to Artificial Intelligence By Eugene Charniak, Drew McDermott-AddisonWesley

Neural Networks and fuzzy systems A dynamical systems approach tomachineIntelligence by Bart Kosko- PHI

Genetic Algorithms in search, Optimization & Machine Learning by David EGoldberg-Addison Wesley

Data Mining by Pieter Adriaans and Dolf Zantinge Pearson Education Asia

Data Warehousing in the Real World by Sam Anahory and Dennis Murray,Addison-Wesley

M Sc Information Technology Year II, Paper II, TermII

SUBJECT: ROBOTICS

Objective:


6/28


The goal of the course is to familiarize the students with the conceptsandtechniques in robot manipulator control, enough to evaluate, chose, andincorporate robotsin engineering systems.

Pre-requisite:Exposure to linear algebra and matrix operations. Exposure to programmingin ahigh level language

DETAILED SYLLABUS

1. Robotic Manipulation: Automation and Robots, Classification, Application,Specification, Notations.

2.Direct Kinematics: Dot and cross products, Co-ordinate frames, Rotations,Homogeneous, Co-

ordinates, Link co-ordination arm equation, (Five-axis robot, Fouraxis robot, Sixaxis robot).

3.Inverse Kinematics: General properties of solutions tool configuration Five axisrobots, Three-Fouraxis, Six axis robot (Inverse kinematics).

4. Workspace analysis and trajectory planning work envelop and examples,workspacefixtures, Pick and place operations, Continuous path motion,Interpolated motion,

5. Robot Vision:Image representation, Template matching, Polyhedral objects, Shaneanalysis,Segmentation (Thresholding, region labeling, Shrink operators, Swelloperators,Euler numbers, Perspective transformation, Structured Illumination,Cameracalibration).

6. Task Planning:Task level programming, Uncertainty, Configuration, Space, Grossmotion,Planning, Grasp planning, Fine-motion Planning, Simulation of Planermotion,Source and goal scenes, Task planner simulation.

7. Moments of Inertia.8. Principles of NC and CNC Machines.

BOOKS

Text Books:1. Robert Shilling, Fundamentals of Robotics-Analysis and control,PHI.2. Fu, Gonzales and Lee, Robotics,McGraw Hill3. J.J, Craig, Introduction to Robotics


7/28


, Pearson Education

References:

1. Staughard, Robotics and AI,PHI.2. Grover, Wiess, Nagel, Oderey, Industrial Robotics, McGraw Hill3. Walfram Stdder, Robotics and Mecatronics , TMH.

4. Niku, Introduction to Robotics, Pearson Education

5. Klafter, Chmielewski, Negin, Robot Engineering , PHI

6. Mittal, Nagrath, Robotics and Control , TMH

Assignments:

10 assignments covering the syllabus has tobe submitted

M Sc Information Technology Year II, Elective I, TermISUBJECT: PARALLEL PROCESSING

Objective:Upon completion of this course students will be able to understand andemploythe fundamental concepts and mechanisms which form the basis of the design of

parallel computation models and algorithms, recognize problems and limitationstoparallel systems, as well as possible solutions

Pre-requisite:Computer architecture, Data structures

DETAILED SYLLABUS

1.Introduction:Parallel Processing Architectures: Parallelism in sequential machines,Abstractmodel of parallel computer, Multiprocessor architecture, Pipelining,

Arrayprocessors.

2.Programmability Issues:An overview, Operating system support, Types of operating systems, Parallelprogramming models, Software tools

3.Data Dependency Analysis:Types of dependencies loop and array dependences,Loop dependence analysis,Solving diophantine equations, Program transformations

4.Shared Memory Programming:


8/28


General model of shared memory programming,Process model under UNIX

5.Algorithms for Parallel Machines:

Speedup, Complexity and cost, Histogramcomputation, Parallel reduction,Quadrature problem, Matrix multiplication, Parallelsorting algorithms, Solvinglinear systems, Probabilistic algorithms

6.Message Passing Programming:Introduction, Model, Interface, Circuitsatisfiability, Introducing collective,Benchmarking parallel performance

7.Parallel Programming languages:Fortran90, nCUBE C, Occam, C-Linda

8.Debugging Parallel Programs:Debugging techniques, Debugging message passingparallel programs, Debuggingshared memory parallel programs

9.Memory and I/O Subsystems:Hierarchical memory structure, Virtual memorysystem, Memory allocation andmanagement, Cache allocation and management,Cache memories andmanagement, Input output subsystems

10.Other Parallelism Paradigms:Data flow computing, Systolic architectures,Functional and logic paradigms,

Distributed shared memory

11.Performance of Parallel Processors:Speedup and efficiency, Amdahls law,Gustafson-Barsiss law, Karf-Flatt metric,Isoefficiency metric

BOOKS

Text Books:1. Hawang Kai and Briggs F. A., Computer Architecture and Parallel Processing,McGraw Hill

2. Jorden H. F. and Alaghaband G., Fundamentals of Parallel Processing 3. M.J.Quinn, 3. Parallel Programming , TMH

References:

1. Shasikumar M., Introduction to Parallel Processing , PHI

2. Wilson G.V., Practical Parallel Programming , PHI


9/28


3. D. E. Culler, J.P. Singh, A. Gupta, Parallel Computer Architecture,MorganKaufman

TERM WORK8. Term work should consist of at least 10 practical experiments and twoassignmentscovering the topics of the syllabus.

ORAL EXAMINATIONAn oral examination is to be conducted based on the above syllabus.


10/28


M Sc Information Technology Year II, Elective I, TermII

SUBJECT: DISTRIBUTED COMPUTING

Objective:This course aims to build concepts regarding the fundamental principlesof distributed systems. The design issues and distributed operating systemconcepts arecovered.Pre-requisites:

Operating Systems and Computer NetworksDETAILED SYLLABUS

1.Introduction to Distributed System:Goals, Hardware concepts, Softwareconcepts, and Client-Server model. Examplesof distributed systems.

2. Communication:Layered protocols, Remote procedures call, Remote objectinvocation, Message-oriented communication, Stream-oriented communication.

3. Processes:Threads, Clients, Servers, Code Migration, Software agent.

4. Naming:Naming entities, Locating mobile entities, Removing un-referencedentities.

5. Synchronization:Clock synchronization, Logical clocks, Global state, Electionalgorithms, Mutualexclusion, Distributed transactions.

6. Consistency and Replication:Introduction, Data centric consistency models,

Client centric consistency models, Distribution protocols, Consistency protocols.7. Fault Tolerance:

Introduction, Process resilience, Reliable client servercommunication, Reliablegroup communication. Distributed commit, Recovery.

8.Security:Introduction, Secure channels, Access control, Security management.

9. Distributed File System:Sun network file system, CODA files system.


11/28


10.Case Study:CORBA, Distributed COM, Globe, Comparison of CORBA, DCOM,and Globe.

BOOKS

Text Books:1. A. Taunenbaum, Distributed Systems: Principles and Paradigms2. G. Coulouris, J. Dollimore, and T. Kindberg, Distributed Systems: Concepts and Design, Pearson Education

References:1. M. Singhal, N. Shivaratri,

Advanced Concepts in Operating Systems, TMH

TERM WORK9. Term work should consist of at least 10practical experiments and two assignmentscovering the topics of the syllabus.


M Sc Information Technology Year II, Elective I, TermISUBJECT: INTELLIGENT SYSTEMS

Objectives:

To understand and apply principles, methodologies and techniques in designandimplementation of intelligent system.Prerequisite:Data Structures, Programming Languages, and Algorithms

DETAILED SYLLABUS

1.Artificial Intelligence

: An overview, Intelligent Systems: Evolution of the concept.

2.Intelligent Agents: How agent should act, Structure of intelligent agents,Environments

3. Problem Solving:Solving problems by searching, Informed search methods, Gameplaying

4. Knowledge and Reasoning:


12/28


A knowledge based agent, The wumpus worldenvironment, Representation,Reasoning, Logic, Proportional logic, First order logic:Syntax and Semantics,Extensions and Notational variation, Using first order logic

5. Building a Knowledge Base:Properties of good and bad knowledge base,Knowledge engineering, General ontology

6. Interfacing First Order Logic:Interface rules involving quantifiers, An exampleproof, Forward and backwardchaining, Completeness

7. Acting Logically:Planning, Practical planning: Practical planners, Hierarchicaldecomposition,

Conditional planning

8. Uncertain Knowledge and Reasoning:Uncertainty, Representing knowledge in anuncertain domain, The semantics ofbelief networks, Inference in belief networks

9. Learning:Learning from observations: General model of learning agents,Inductivelearning, learning decision trees, Learning in neural and beliefnetworks:Introduction to neural networks, Perceptrons, Multilayer feed-forwardnetwork,Application of ANN, Reinforcement learning: Passive learning in a

knownenvironment, Generalization in reinforcement learning, Geneticalgorithms

10. Agents that Communicate:Communication as action, Types of communicatingagents, A formal grammar fora subset of English

11. Expert system:Introduction to expert system, Representing and using domainknowledge, Expertsystem shells, Explanation, Knowledge acquisition

12. Applications:Natural language processing, Perception, Robotics

BOOKS

Text Books:1. Struart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach2. George F.Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Pearson Education


13/28


References:

1. Nils J. Nillson,

Artificial Intelligence: A New Synthesis, Harcourt Asia 2. Elaine Rich and Kevin Knight, Artificial Intelligence, TMH3. Patrick Winston, Artificial Intelligence, Pearson Education4. Ivan Brakto, Prolog Programming for Artificial Intelligence, Pearson Education5. Efraim Turban Jay E.Aronson, Decision Support Systems and Intelligent Systems6. Ed. M. Sasikumar and Others, Artificial Intelligence : Theory and Practice

Proceedings of the International Conference KBCS-2002, Vikas PublishingHouse

TERM WORK

10. Term work should consist of at least 10 practical experiments and twoassignmentscovering the topics of the syllabus.


M Sc Information Technology Year II, Elective I, Term IISUBJECT: NEURAL NETWORKS & FUZZYSYSTEMS

Objective:This course covers basic concepts of artificial neural networks, fuzzy logicsystemsand their applications. Its focus will be on the introduction of basictheory,algorithm formulation and ways to apply these techniques to solve realworld problems.

Pre-requisite:

Knowledge of calculus, and basic probability and statistics arerequired.Background in the following subjects desirable: numerical analysis(includingoptimization). Programming skills in one of the following would bedesirable: Matlab,MathCad, C, Java, C++

DETAILED SYLLABUS

1.Introduction:Biological neurons, McCulloch and Pitts models of neuron, Types of activationfunction, Network architectures, Knowledge representation. Learningprocess:


14/28


Error-correction learning, Supervised learning, Unsupervised learning,LearningRules.

2.Single Layer Perceptron:Perceptron convergence theorem, Method of steepestdescent - least mean squarealgorithms

.3.Multilayer Perceptron: Derivation of the back-propagation algorithm, LearningFactors.

4.Radial Basis and Recurrent Neural Networks:RBF network structure, theoremand the reparability of patterns, RBF learningstrategies, K-means and LMS algorithms, comparison of RBF and MLP networks,Hopfield networks: energyfunction, spurious states, error performance

5.Simulated Annealing: The Boltzmann machine, Boltzmann learning rule,Bidirectional AssociativeMemory.

6.Fuzzy logic:Fuzzy sets, Properties, Operations on fuzzy sets, Fuzzy relations,Operations onfuzzy relations, The extension principle, Fuzzy measures, Membershipfunctions,Fuzzification and defuzzification methods, Fuzzy controllers.

BOOKS

Text Books:

1. Simon Haykin, Neural Network a - Comprehensive Foundation, PearsonEducation2. Zurada J.M., Introduction to Artificial Neural Systems,Jaico publishers3. Thimothy J. Ross, Fuzzy Logic with Engineering Applications, McGraw Hill4. Ahmad Ibrahim, Introduction to Applied Fuzzy Electronics

, PHI

References:

1. Yegnanarayana B., Artificial Neural Networks, PHI2. Driankov D., Hellendoorn H. & Reinfrank M., An Introduction to Fuzzy Control,Norosa Publishing House3. Berkan R.C., and Trubatch S.L., Fuzzy Systems Design Principles, IEEE Press


15/28


TERM WORK11. Term work should consist of at least 10 practical experiments and two

assignmentscovering the topics of the syllabus.ORAL EXAMINATIONAn oral examination is to be conducted based on the above syllabus

M Sc Information Technology Year II, Elective I, Term ISUBJECT: DIGITAL SIGNAL PROCESSING

Objective:Digital Signal Processing continues to play an increasingly important role inthefields that range literally from A (astronomy) to Z (zeugmatography, ormagneticresonance imaging) and encompass applications such as Compact Discplayer, SpeechRecognition, echo cancellations in communication systems, imageEnhancement,geophysical exploration, and noninvasive medical imaging. Thiscourse aims to buildconcepts regarding the fundamental principles andapplications of Signals, SystemTransforms and Filters.

Pre-requisites: Nil

DETAILED SYLLABUS

1.Discrete Time Signals & System:Discretetime signals, Discretetime systems,Analysis of discrete-time LTIsystems, Discrete-time systems described by differentialequations,Implementation of discrete-time systems, Correlation of discrete-timesystems

2.Z-Transform:Definition and Properties of Z-transform, Rational Z-transforms,Inverse Z-transform, one-sided Z-transform, Analysis of LTI systems in Z-domain

3.Frequency Analysis of Signals and Systems:Frequency analysis: Continuous timesignals and Discrete-time signals, Properties

of the Fourier transform for discrete-timesignals, Frequency domaincharacteristics of LTI systems, LTI system as a frequencyselective filter, Inversesystems and deconvolution

4.Discrete Fourier Transform:Frequency domain sampling, Properties of DFT,Linear filtering method based onDFT, Frequency analysis of signals using DFT, FFTalgorithm, Applications of FFT, Goertzel algorithm, Quantisation effects inthecomputation of DFT

5.Implementation of Discrete Time Systems:


16/28


Structure of FIR systems, Structure of IIR systems, quantization of filtercoefficients, round-off effects in digital filters

6.Design of Digital Filters:Design of FIR filters, Design of IIR filters from analogfilters, frequencytransformations, Design of digital filters based on least-squaresmethod digitalfilters from analogue filters, Properties of FIR digital filters, Design of FIR filtersusing windows, Comparison of IIR and FIR filters, and Linear phase filters.

7.Introduction to DSP co-processors: TMS 320C40/50, Analog Devices

.8.Applications :Image processing, Control, Speech, Audio, Telecommunication

BOOKS

Text Books:

1. J.G. Proakis, Introduction to Digital Signal Processing, PHI2. Oppenhiem and Schaffer, Discrete Time Signal ProcessingReferences:

1. S.K. Mitra, Digital Signal Processing, TMH.2. T.J. Cavicchi, Digital Signal Processing, John Wiley.3. L.C. Ludeman,Fundamentals Of Digital Signal Processing, John Wiley.4. E.C. Ifeachor, B.W. Jervis, Digital Signal Processing, Pearson Education.5. S Sallivahanan, Digital Signal Processing

, TMH.6. Ashok Ambardar, Analog and Digital Signal Processing, Thompson Learning.

TERM WORK12. Term work should consist of at least 10 practical experiments and twoassignments



17/28


M Sc Information Technology Year II, Elective I, Term ISUBJECT: Enterprise Networking

IntroductionGrowth of Computer Networking, Complexity in Network Systems, Mastering theComplexity,Resource Sharing, Growth of the Internet, Probing the Internet,Interpreting A Ping Response

PART I DATA TRANSMISSION

Transmission MediaCopper Wires, Glass Fibers, Radio, Satellites, Geosynchronous Satellites, LowEarth OrbitSatellites, Low Earth Orbit Satellite Arrays, Microwave, Infrared,Light Form a Laser

Local Asynchronous CommunicationThe Need for Asynchronous Communication, Using Electric Current to Send Bits,Standards for Communication, Baud Rate, Framing, and Errors, Full DuplexAsynchronous Communication,Limitations of Real Hardware, HardwareBandwidth and the Transmission of Bits, The Effect of Noise On Communication,Significance for Data Networking

Long-Distance Communication (Carriers, Modulation and Modems)Sending Signals across Long Distances, Modem Hardware Used for ModulationandDemodulation, Leased Analog Data Circuits, Optical, Radio Frequency, And

Dialup Modems,Carrier Frequencies and Multiplexing, Base band AndBroadband TechnologiesWave Division Multiplexing, Spread Spectrum, TimeDivision Multiplexing

PART II PACKET TRANSMISSION

Packets, Frames and Error DetectionThe Concept of Packets, Packets and Time-Division Multiplexing, Packets andHardware Frames, Byte Stuffing, Transmission Errors, Parity Bits and ParityChecking, Probability,Mathematics And Error Detection, Detecting Errors WithChecksums, Detecting Errors WithCyclic Redundancy Checks, Combining

Building Blocks, Burst Errors, Frame format And Error Detection Mechanisms

LAN Technologies and Network TopologyDirect Point-To-Point Communication, Shared Communication Channels,Significance of LANsand Locality of Reference, LAN Topologies, Bus Network:Ethernet Carrier Sense on Multi-Access Networks (CSMA), Collision Detectionand Back off With CSMA/CD, Wireless LANsAnd CSMA/CA, Bus Network: LocalTalk

Hardware Addressing and Frame Type Identification


18/28


Specifying a Recipient, How LAN Hardware Uses Addresses to Filter PacketsFormat of aPhysical Address, Broadcasting, Multicasting, Multicast Addressing,Identifying PacketContents, Frame Headers And Frame Format, Using Networks

That Do Not Have Self-Identifying Frames, Network Analyzers

LAN Wiring, Physical Topology, and Interface HardwareSpeeds of LANs and Computers, Network Interface Hardware, the Connectionbetween A NICand A Network, Original Thick Ethernet Wiring, ConnectionMultiplexing, Thin Ethernet WiringTwisted Pair Ethernet, the Topology Paradox,Network Interface Cards and Wiring Schemes,

Extending LANs: Fiber Modems, Repeaters, Bridges and SwitchesDistance Limitation and LAN Design, Fiber Optic Extensions, Repeaters, Bridges,FrameFilteringStartup and Steady State Behavior of Bridged Networks, Planning

a Bridged Network, BridgingBetween Buildings, Bridging Across LongerDistances, A Cycle Of Bridges, DistributedSpanning Tree, Switching, CombiningSwitches And Hubs, Bridging And Switching With Other Technologies

Long-Distance Digital Connection TechnologiesDigital Telephony, Synchronous Communication, Digital Circuits and DSU,TelephoneStandardsDS Terminology and Data Rates, Lower Capacity Circuits,Intermediate Capacity Digital CircuitsHighest Capacity Circuits, Optical CarrierStandards, the C Suffix, Synchronous OpticalNetwork (SONET), the LocalSubscriber Loop, ISDN, Asymmetric Digital Subscriber LineTechnologyOtherDSL Technologies, Cable Modem Technology, Upstream Communication, Hybrid

Fiber Coax

Wan Technologies and RoutingLarge Networks and Wide Areas, Packet Switches, Forming A WAN, Store andForwardPhysical Addressing In A WAN, Next-Hop Forwarding, SourceIndependence, Relationship of Hierarchical Addresses to Routing, Routing In A

WAN, Use of Defaults Routes, Routing TableComputation, Shortest PathComputation in a Graph, Distributed Route Computation, DistanceVectorRouting

Network Ownership, Service Paradigm, and Performance

Network Ownership, Virtual Private Networks, Service Paradigm, ConnectionDuration andPersistence, Examples of Service Paradigms, Addresses andConnection Identifiers, NetworkPerformance Characteristics

Protocols and LayeringThe Need for Protocols, Protocol Suites, A Plan for Protocol Design, the SevenLayers, Stacks:Layered Software, How Layered Software Works, Multiple, NestedHeaders, the Scientific Basisfor Layering,

TERM WORK


19/28


Term work should consist of at least 10 assignments from the aforementionedtopics. A Seminar to be presented by each student as part of term works carrying15 marks.

REFERENCEComputer Network, Tuekeun, PHINetworking Technology, Jaiswal, Galgotia.Data Networking, Bertsekas, PHIComputer Networks and Internets, Douglas E. Comer Pearson Education Asia

M Sc Information Technology Year II, Elective II, TermISUBJECT: PATTERN RECOGNITION

Objective:

This course teaches the fundamentals of techniques for classifying multi-dimensional data, to be utilized for problem-solving in a wide variety ofapplications,such as engineering system design, manufacturing, technical andmedical diagnostics,image processing, economics, psychology.

Pre-requisite:Linear Algebra, Probability and Statistics

DETAILED SYLLABUS

1.Introduction:Machine perception, Pattern recognition systems, Design cycle,Learning andAdaptation

2.Bayesian Decision Theory:Bayesian decision theory: Continuous features,Minimum-error rate classification,classification, Classifiers, Discriminant functionsand Decision surfaces, Normaldensity, Discriminant functions for normal density,Bayes Decision theory:discrete features

3.Maximum-Likelihood and Bayesian Parameter Estimation:

Maximum likelihoodestimation, Bayesian estimation, Bayesian parameterestimation: Gaussian caseandGeneral theory, Prolems of dimentionality, HiddenMarkov Model

4.Nonparametric Techniques:Density estimation, Parzen windows,k n-Nearest- Neighbor estimation, Nearest-Neighbor rule, Matrics and Nearest-Neighborclassification

5.Linear Discriminants Functions:


20/28


Linear discriminant functions and decisionsurfaces, Generalised lineardiscriminant functions, 2-Category linearly separable case,Minimising thePerceptron criterion function, Relaxation procedure, Non-separablebehavior,

Minimum squared error procedure, Ho-Kashyap procedures,Multicategorygeneralizations

6.Nonmetric Methods:Decision tree, CART, ID3, C4.5, Gramatical methods,Gramatical interfaces

7. Algorithm Independent Machine Learning: Lack of inherent superiority ofanyclassifier, Bias and Variance, Resampling for estimating statistic, Resamplingforclassifier design, Estimating and comparing classifiers, Combining classifiers

8. Unsupervised Learning and Clustering:

Mixture densities and Identifiability,Maximum-Likelihood estimations,Application to normal mixtures, UnsupervisedBayesian learning, Datadescription and clustering criterion function for clustering,Hierarchicalclustering

9. Applications of Pattern Recognition

BOOKS

Text Books:

1. Duda, Hart, and Stock, Pattern Classification, John Wiley and Sons.2. Gose, Johnsonbaugh and Jost, Pattern Recognition and Image analysis, PHI

TERM WORK

Term work should consist of at least 10 practical experiments and twoassignmentscovering the topics of the syllabus.


M Sc Information Technology Year II, Elective II, Term IISUBJECT: COMPUTER VISION

Objective:To introduce the student to computer vision algorithms, methods andconceptswhich will enable the student to implement computer vision systemswith emphasis onapplications and problem solving


21/28


Pre-requisite:Introduction to Image Processing.

DETAILED SYLLABUS

Recognition Methodology:Conditioning, Labeling, Grouping, Extracting,Matching. Edge detection, Gradientbased operators, Morphological operators, Spatialoperators for edge detection.Thinning, Region growing, region shrinking, Labeling of connected components.

Binary Machine Vision:Thresholding, Segmentation, Connected componentlabeling, Hierarchalsegmentation, Spatial clustering, Split & merge, Rule-basedSegmentation,

Motion-based segmentation.

Area Extraction:Concepts, Data-structures, Edge, Line-Linking, Hough transform,Line fitting,Curve fitting (Least-square fitting).12.

Region Analysis:Region properties, External points, Spatial moments, Mixed spatialgray-levelmoments, Boundary analysis: Signature properties, Shape numbers.

Facet Model Recognition:Labeling lines, Understanding line drawings,Classification of shapes by labelingof edges, Recognition of shapes, Consisting labeling problem, Back-tracking,Perspective Projective geometry, Inverse perspectiveProjection, Photogrammetry from 2D to 3D, Image matching : Intensity matching of ID signals, Matching of2D image, Hierarchical

image matching.Object Models And Matching:2D representation, Global vs. Local features.

General Frame Works For Matching:Distance relational approach, Ordered-structural matching, View class matching,Models database organization.

General Frame Works:Distance relational approach, Ordered Structuralmatching, View classmatching, Models database organization.

Knowledge Based Vision:Knowledge representation, Control-strategies,Information integration.


22/28


BOOKS

Text Books:

1. David A. Forsyth, Jean Ponce, Computer Vision: A Modern Approach2. R. Jain, R. Kasturi, and B. G. Schunk, Machine Vision, McGraw-Hill.

References:1. Milan Sonka,Vaclav Hlavac, Roger Boyle, Image Processing, Analysis, andMachine Vision Thomson Learning

2. Robert Haralick and Linda Shapiro, Computer and Robot Vision , Vol I,II,Addison-Wesley, 1993.

TERM WORK

Term work should consist of at least 10 practical experiments and twoassignments covering the topics of the syllabus.

ORAL EXAMINATION

An oral examination is to be conducted based on the above syllabus.

M Sc Information Technology Year II, Elective II, Term ISUBJECT: SYSTEM SECURITY

Objectives of the course:

Learn about the threats in computer security. Understand whatputs you at a riskand how to control it. Controlling a risk is not eliminating the risk but tobring itto a tolerable level.

Pre-requisites:Computer Networks, Operating system.

DETAILED SYLLABUS8.Introduction:Security, Attacks, Computer criminals, Method of defense

9. Cryptography:Basic Cryptography: Classical Cryptosystems, Public keyCryptography,Cryptographic checksum, Key Management: Key exchange, Keygeneration,Cryptographic key infrastructure, Storing and revoking keys, Hashalgorithm,


23/28


24/28


TERM WORK

Term work should consist of at least 10 practical experiments and twoassignments covering the topics of the syllabus.


M Sc Information Technology Year II, Elective II, Term IISubject: Virtual Reality and Virtual Environment

Real time computer graphics, Flight simulation, virtual environment, Benefits ofvirtual reality,Evolution of Virtual Reality, Historical perspective, scientific landmarks3D Computer graphicsThe virtual world space, positioning the virtual observer, the perspectiveprojection, Human vision,Stereo perspective projection, 3D clipping, colourtheory, simple 3D modelling, illumination models,shading algorithms, radiosity,hiddensurface removal, realism, stereographic images

Geometric modellingFrom 2D to 3D, 3D space curves, 3D boundary representation,

Geometrical Transformations

Frames of reference, Modelling transformations, instances, picking flying,Scaling the VE, Collisiondetection

A generic VR SystemsThe virtual Environment, The computer environment, VR Technology, Modes of

Interaction, VR systemsAnimating the Virtual EnvironmentDynamics of numbers, the animation of objects, shape and object inbetweening,free-formdeformation, particle systems

Physical SimulationObjects falling in a gravitational field, rotating wheels, Elastic collisions,Projectiles, simplependulums, springs, flight dynamics of an aircraft

Human factorsThe eye, The ear, the somatic senses, Equilibrium

Virtual Reality HardwareSensor hardware, Head-coupled displays, Acoustic hardware, Integrated VRSystems


25/28


Virtual Reality Software

Modelling Virtual worlds, Physical simulation, VR tool kits

Virtual Reality ApplicationsEngineering, Entertainment, science, Education, trainingFutureVirtualEnvironment, Modes of Interaction

Text BooksVirtual Reality Systems John Vince- Pearson Education Asia

M Sc Information Technology Year II, Elective III, Term I

Subject: Multimedia systems and convergence of technologies

Multimedia systems and convergence of technologiesDefining the scope of multimedia, Hypertext and Collaborative research,Multimedia and personalisedcomputing, Multimedia on the map, Emergingapplications, The challengesThe convergence of computers, Communications, and entertainment productsThe technology trends, Multimedia appliances, Hybrid Devices, Designersperspective, industryperspective of the future, Key challenges ahead, Technical,

regulatory, SocialArchitectures and issues for Distributed Multimedia systems

Distributed Multimedia systems, Synchronization, and QOS Architecture, Therole of Standards, Aframe work for Multimedia systems

Digital Audio Representation and processingUses of Audio in Computer Applications, Psychoacoustics, Digital representationof sound,transmission of digital sound, Digital Audio signal processing, Digitalmusic making, Speechrecognition and generation, digital audio and thecomputersVideo TechnologyRaster Scanning Principles, Sensors for TV Cameras,

Colour Fundamentals, Colour Video, Videoperformance Measurements, Analogvideo Artifacts, video equipments, World wide televisionstandards

Digital Video and Image CompressionVideo compression techniques, standardization of Algorithm, The JPEG ImageCompression Standard,ITU-T Recommendations, The EPEG Motion VideoCompression Standard, DVI Technology

Operating System Support for Continuous Media ApplicationsLimitation of Work station Operating system, New OS support, ExperimentsUsing Real Time Mach


26/28


Middleware System Services ArchitectureGoals of Multimedia System services, Multimedia system services Architecture,

Media stream protocol

Multimedia Devices, Presentation Services, and the User InterfaceClient control of continuous multimedia, Device control, Temporal coordinationand composition,toolkits, hyperapplicationsMultimedia File systems and Information ModelsThe case for multimedia information systems, The file system support forcontinuous Media, Datamodels for multimedia and Hypermedia information,Content- based

Retrieval of Unstructured Data

Multimedia presentation and AuthoringDesign paradigms and User interface, barriers to wide spread use, researchtrendsMultimedia Services over the Public NetworksRequirements, Architecture, and protocols, Net work services, applicationsMultimedia InterchangeQuick time Movie File Format, QMFI, MHEG (Multimedia and HypermediaInformation EncodingExpert Group), Format Function and representation, Trackmodel and Object model, Real TimeInterchange

Multimedia conferencing

Teleconferencing Systems, Requirements of Multimedia Communications,Shared ApplicationArchitecture and embedded Distributed objects, MultimediaConferencing Architecture

Multimedia GroupwareComputer and Video fusion approach to open shared wok place, High DefinitionTelevision anddesktop computing, HDTV standards, Knowledge basedMultimedia systems, Anatomy of anIntelligent Multimedia system

Text BookMultimedia Systems by John F. Koegel Buford- Pearson Education

M Sc Information Technology Year II, Elective II, Term ISUBJECT: Java Technology

Java ProgrammingObject oriented programming revisited, JDK, Java Virtual machine-Platformindependent-portability-scalability Operators and expressions-decision making,branching, looping, Classes,Objects and methods, Arrays Strings and Vectors,Interfaces, Packages, Multi-Threading,managing errors and exceptions, Appletprogramming, Managing files and streams


27/28


Java Technology for Active Web DocumentsAn Early Form of Continuous Update, Active Documents and Server Overhead,

ActiveDocument Representation and Translation, Java Technology, the JavaRun-Time Environment,The Java LibraryA Graphics Toolkit, Using JavaGraphics on a Particular Computer, Java Interpreters andBrowsers

Compiling a Java Program, Invoking an Applet, Example of Interaction with aBrowser

RPC and MiddlewareProgramming Clients and Servers, Remote Procedure Call Paradigm, RPCParadigm,Communication Stubs, External Data Representation, Middleware andObject-OrientedMiddleware

Network Management (SNMP)Managing an Internet, The Danger of Hidden Features, Network ManagementSoftware,Clients, Servers, Managers and Agents, Simple Network ManagementProtocol, Fetch-StoreParadigm, The MIP and Object Names, The Variety of MIBVariables, MIB variables that

Java technologiesGraphics, JFC-JAVA foundation classes, swing, images, java 2d graphics,internationalization,Communication and Networking, TCP Sockets, UDPSockets,

java.net,java security, Objectserialization, Remote method serialization, JDBC: Java DataBase Connectivity, Java beans,Java interface to CORBA, JAVA- COM Integration,Java Media Framework, commerce and javawallet, Data structures and javautilities, JavaScript, ServeletsTERM WORKTerm work should consist of at least 06 assignments including debugged javasource code for the applications from the aforementioned topics. A Seminar to bepresented by each student aspart of term work carrying 15 marks.

REFERENCE

Using JAVA 2, Joseph L weber, PHIJAVA 2 complete, Sybex, BPBJava2 The complete Reference, Patrick Naughton, T M HComputing concepts With JAVA2, Cay Horstmann, WILEYJSP Java Server Pages, Barry Burd, IDG Books India(p) LtdJava2 Programming Bible, Aaron Walsh, IDG Books India(p) LtdJava2, swing, servlets, JDBC & JAVA Beans Programming Black Book StevenHolzner dreamtech press


28/28


Visit for more notes and updated information

www.missionmca.com