iv b. tech ii semester (viii semester) - ongoleqiscet.edu.in/docs-pdf/174-2.pdf · code iv b. tech...

Code IV B. Tech II Semester (VIII Semester)

Theory L T P C

A0017

Management Science

2

1

0

3

A0544- A0551

Discipline Elective – III

1

1

0

2

A0552- A0558 Discipline Elective – IV

1

1 0 2

Entrepreneur Development and societal

commitment

2 - - 2

Code Practice L T P C

A0599

Project Work

-

-

-

09

Total 18

DISCIPLINE ELECTIVE-III

IV Year –II SEMESTER L T C 1 1 2

MANAGEMENT SCIENCE (DISCIPLINE ELECTIVE-III)

UNIT - I Introduction to Management: Concepts of Management and organization- nature, importance and Functions of Management, Taylor’s Scientific Management Theory, Fayol’s Principles of Management, Mayo’s Hawthorne Experiments, Maslow’s Theory of Human Needs, Douglas McGregor’s Theory X and Theory Y, Herzberg’s Two-Factor Theory of Motivation, Systems Approach to Management, Leadership Styles, Social responsibilities of Management. UNIT- II Designing Organisational Structures : Basic concepts related to Organisation - Departmentation and Decentralisation, Types of mechanistic and organic structures of organisation (Line organization, Line and staff organization, functional organization, Committee organization, matrix organization, Virtual Organisation, Cellular Organisation, team structure, boundaryless organization, inverted pyramid structure, lean and flat organization structure) and their merits, demerits and suitability. UNIT- III Operations Management : Principles and Types of Plant Layout-Methods of production (Job, batch and Mass Production), Work Study -Basic procedure involved in Method Study and Work Measurement- Statistical Quality Control: chart, R chart, c chart, p chart, (simple Problems), Acceptance Sampling,Deming’s contribution to quality. UNIT-IV a) Materials Management: Objectives, Need for Inventory control, EOQ, ABC Analysis, Purchase Procedure, Stores Management and Stores Records. b) Marketing: Functions of Marketing, Marketing Mix, Marketing Strategies based on Product Life Cycle, Channels of distribution UNIT- V Human Resources Management (HRM) : Concepts of HRM, HRD and Personnel Management and Industrial Relations (PMIR), HRM vs.PMIR, Basic functions of HR Manager: Manpower planning, Recruitment, Selection, Training and Development, Placement, Wage and Salary Administration, Promotion, Transfer, Separation, Performance Appraisal, Grievance Handling and Welfare Administration, Job Evaluation and Merit Rating. Project Management (PERT/CPM) : Network Analysis, Programme Evaluation and Review Technique (PERT), Critical Path Method (CPM), Identifying critical path, Probability of Completing the project within given time, Project Cost Analysis, Project Crashing. (simple problems)

UNIT- VI Strategic Management : Mission, Goals, Objectives, Policy, Strategy, Programmes, Elements of Corporate Planning Process, Environmental Scanning, Value Chain Analysis, SWOT Analysis, Steps in Strategy Formulation and Implementation, Generic Strategy alternatives. Contemporary Management Practices : Basic concepts of MIS, End User Computing, Materials Requirement Planning (MRP), Just-In-Time (JIT) System, Total Quality Management (TQM), Six sigma and Capability Maturity Model (CMM) Levels, Supply Chain Management, Enterprise Resource Planning (ERP), Performance Management, Business Process outsourcing (BPO), Business Process Re-engineering and Bench Marking, Balanced Score Card.

TEXT BOOKS :

1. Aryasri : Management Science, TMH, 2004.

2. Stoner, Freeman, Gilbert, Management, 6th Ed, Pearson Education, New Delhi, 2004.

REFERENCES :

1. Kotler Philip & Keller Kevin Lane: Marketing Mangement 12/e, PHI, 2005

2. Koontz & Weihrich: Essentials of Management, 6/e, TMH, 2005

3. Thomas N.Duening & John M.Ivancevich Management — Principles and Guidelines, Biztantra,2003.

4. Kanishka Bedi, Production and Operations Management, Oxford University Press, 2004.

5. Memoria & S.V.Gauker, Personnel Management, Himalaya, 25/e, 2005

6. Samuel C.Certo: Modern Management, 9/e, PHI, 2005

7. Schermerhorn, Capling, Poole & Wiesner: Management, Wiley, 2002.

8. Parnell: Strategic Management, Biztantra,2003.

9. Lawrence R Jauch, R.Gupta &William F.Glueck:Business Policy and Strategic Management, Frank Bros.2005.

10. L.S.Srinath: PERT/CPM,Affiliated East-West Press, 2005.


INFORMATION THEORY AND CODING TECHNIQUES (DISCIPLINE ELECTIVE-III)

UNIT I: INFORMATION THEORY Information – Entropy, Information rate, classification of codes, Kraft McMillan inequality, Source coding theorem, Shannon-Fano coding, Huffman coding, Extended Huffman coding - Joint and conditional entropies, Mutual information - Discrete memoryless channels – BSC, BEC – Channel capacity, Shannon limit. UNIT II: SOURCE CODING: TEXT, AUDIO AND SPEECH Text: Adaptive Huffman Coding, Arithmetic Coding, LZW algorithm – Audio: Perceptual coding, Masking techniques, Psychoacoustic model, MEG Audio layers I,II,III, Dolby AC3 - Speech: Channel Vocoder, Linear Predictive Coding UNIT III: SOURCE CODING: IMAGE AND VIDEO Image and Video Formats – GIF, TIFF, SIF, CIF, QCIF – Image compression: READ, JPEG – Video Compression: Principles-I,B,P frames, Motion estimation, Motion compensation, H.261, MPEG standard UNIT IV: ERROR CONTROL CODING: BLOCK CODES Definitions and Principles: Hamming weight, Hamming distance, Minimum distance decoding - Single parity codes, Hamming codes, Repetition codes - Linear block codes, Cyclic codes - Syndrome calculation, Encoder and decoder - CRC UNIT V: ERROR CONTROL CODING: CONVOLUTIONAL CODES Convolutional codes – code tree, trellis, state diagram - Encoding – Decoding: Sequential search and Viterbi algorithm – Principle of Turbo coding

UNIT-VI: CODING FOR SECURE COMMUNICATIONS Introduction to Cryptography, An overview of Encryption techniques, Symmetric cryptography, DES, IDEA, RSA, PGP. Text Books:

1.R Bose, “Information Theory, Coding and Cryptography”, TMH 2007

2.Fred Halsall, “Multidedia Communications: Applications, Networks, Protocols and Standards”, Perason Education Asia, 2002

References: 1. K Sayood, “Introduction to Data Compression” 3/e, Elsevier 2006. 2. S Gravano, “Introduction to Error Control Codes”, Oxford University Press 2007 3. Amitabha Bhattacharya, “Digital Communication”, TMH 2006


MACHINE LEARNING (DISCIPLINE ELECTIVE-III)

UNIT-1 INTRODUCTION -Well-posed learning problems, Designing a learning system, Perspectives and issues in machine learning Concept learning and general to specific ordering –Introduction, A concept learning task, Concept learning as search, Find-S: finding a maximally specific hypothesis, Version spaces and the candidate elimination algorithm, Remarks on version spaces and candidate elimination, Inductive bias UNIT-2 Decision Tree learning –Introduction, Decision tree representation, Appropriate problems for decision tree learning, The basic decision tree learning algorithm, Hypothesis space search in decision tree learning, Inductive bias in decision tree learning, Issues in decision tree learning UNIT-3 Bayesian learning Introduction, Bayes theorem, Bayes theorem and concept learning, Maximum likelihood and least squared error hypotheses, Maximum likelihood hypotheses for predicting probabilities, Minimum description length principle, Bayes optimal classifier, Gibs algorithm, Naïve Bayes classifier. UNIT-4 Computational learning theory –Introduction, Probability learning an approximately correct hypothesis, Sample complexity for Finite Hypothesis Space, Sample Complexity for infinite Hypothesis Spaces, The mistake bound model of learning -Instance-Based Learning- Locally Weighted Regression, Radial Basis Functions, Case-Based Reasoning, UNIT-5 Genetic Algorithms–Genetic Algorithms, Hypothesis Space Search, Genetic Programming, Models of Evolution and Learning, Parallelizing Genetic Algorithms Combining Inductive and Analytical Learning–Motivation, Inductive-Analytical Approaches to Learning, Using Prior Knowledge to Initialize the Hypothesis, Using Prior Knowledge to Alter the Search Objective, Using Prior Knowledge to Augment Search Operators, UNIT-6 Reinforcement Learning–Introduction, The Learning Task, Q Learning, Non-Deterministic, Rewards and Actions, Temporal Difference Learning, Generalizing from Examples, Relationship to Dynamic Programming

TEXT BOOKS: 1.Machine Learning –Tom M. Mitchell, -MGH 2.Machine Learning: An Algorithmic Perspective, Stephen Marsland, Taylor & Francis (CRC) REFERENCE BOOKS:

1. Machine Learning Methods in the Environmental Sciences, Neural Networks, William W Hsieh, Cambridge Univ Press. 2. Richard o. Duda, Peter E. Hart and David G. Stork, pattern classification, John Wiley & Sons Inc., 2001 3. Chris Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995


HUMAN COMPUTER INTERACTION (DISCIPLINE ELECTIVE-III)

UNIT-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: Graphical system, Characteristics, Web user –interface popularity, characteristics. UNIT-II: Design process: Human interaction with computers, importance of human characteristics human consideration, Human interaction speeds, understanding business junctions. UNIT-III: Screen Designing : Visually pleasing composition, focus and emphasis, presentation information simply and meaningfully, information retrieval on web, statistical graphics, Technological consideration in interface design. UNIT-IV: Windows & Components: selection of devices based and screen based controls, Components text and messages, Icons and increases, Multimedia, colors, uses problems, choosing colors. UNIT-V: Software tools: Specification methods, interface, Building Tools. UNIT-VI: Interaction Devices: Keyboard and function keys, pointing devices, speech recognition digitization and generation, image and video displays, drivers. TEXT BOOKS: 1. Human Computer Interaction. 3/e, Alan Dix, Janet Finlay, Goryd, Abowd, Russell Beal, PEA,2004.

2. The Essential guide to user interface design,2/e, Wilbert O Galitz, Wiley DreamaTech. REFERENCE BOOKS: 1. Human Computer, Interaction Dan R.Olsan, Cengage ,2010.

2. Designing the user interface. 4/e, Ben Shneidermann , PEA.

3. User Interface Design, Soren Lauesen , PEA.

4. Interaction Design PRECE, ROGERS, SHARPS, Wiley.


BUSINESS INTELLIGENCE

(DISCIPLINE ELECTIVE-III)

Course Outcomes:

Be exposed with the basic rudiments of business intelligence system

understand the modeling aspects behind Business Intelligence

understand of the business intelligence life cycle and the techniques used in it

Be exposed with different data analysis tools and techniques

Course Outcomes:

At the end of the course the students will be able to

Explain the fundamentals of business intelligence.

Link data mining with business intelligence.

Apply various modeling techniques.

Explain the data analysis and knowledge delivery stages.

Apply business intelligence methods to various situations.

Decide on appropriate technique.

UNIT I : BUSINESS INTELLIGENCE Effective and timely decisions – Data, information and knowledge – Role of mathematical models – Business intelligence architectures: Cycle of a business intelligence analysis – Enabling factors in business intelligence projects – Development of a business intelligence system – Ethics and business intelligence. UNIT II : KNOWLEDGE DELIVERY The business intelligence user types, Standard reports, Interactive Analysis and Ad Hoc Querying, Parameterized Reports and Self-Service Reporting, dimensional analysis, Alerts/Notifications, UNIT-III : VISUALIZATION Visualization: Charts, Graphs, Widgets, Scorecards and Dashboards, Geographic Visualization, Integrated Analytics, Considerations: Optimizing the Presentation for the Right Message.

UNIT IV:

EFFICIENCY Efficiency measures – The CCR model: Definition of target objectives- Peer groups – Identification of good operating practices; cross efficiency analysis – virtual inputs and outputs – Other models. Pattern matching – cluster analysis, outlier analysis UNIT V: BUSINESS INTELLIGENCE APPLICATIONS Marketing models – Logistic and Production models – Case studies. UNIT VI: FUTURE OF BUSINESS INTELLIGENCE

Future of business intelligence – Emerging Technologies, Machine Learning, Predicting the Future, BI Search & Text Analytics – Advanced Visualization – Rich Report, Future beyond Technology. TEXT BOOK:

1.E. fraim Turban, Ramesh Sharda, Dursun Delen, “Decision Support and Business

Intelligence Systems”, 9th Edition, Pearson 2013.

REFERENCES:

1. Larissa T. Moss, S. Atre, “Business Intelligence Roadmap: The Complete Project Lifecycle of Decision Making”, Addison Wesley, 2003.

2. Carlo Vercellis, “Business Intelligence: Data Mining and Optimization for Decision Making”, Wiley Publications, 2009.

3. David Loshin Morgan, Kaufman, “Business Intelligence: The Savvy Manager‟s Guide”, Second Edition, 2012.

4. Cindi Howson, “Successful Business Intelligence: Secrets to Making BI a Killer App”, McGraw- Hill, 2007.

5. Ralph Kimball , Margy Ross , Warren Thornthwaite, Joy Mundy, Bob Becker, “The Data

Warehouse Lifecycle Toolkit”, Wiley Publication Inc.,2007.


SIMULATION AND MODELLING


UNIT I: System models: Concepts, continuous and discrete systems, System modeling, types of models, subsystems, corporate model, and system study. System Simulation: Techniques, comparison of simulation and analytical methods, types of simulation UNIT II: Continuous system Simulation: Numerical solution of differential equations, Analog Computers, Hybrid Computers, continuous system simulation languages CSMP, system dynamic growth models, logistic curves. UNIT III: Probability concepts in simulation: Monte Carlo techniques, stochastic variables, probability functions, Random Number generation algorithms. UNIT IV: Queuing Theory: Arrival pattern distributions, servicing times, queuing disciplines, measure of queues, mathematical solutions to queuing problems.Discrete System Simulation: Events, generation of arrival patterns, simulation programming tasks, analysis of simulation output. UNIT V: GPSS & SIMSCRIPT: general description of GPSS and SIMSCRIPT, programming in GPSS. UNIT VI: Simulation Programming Techniques: Data structures, Implementation of activities, events and queues, Event scanning, simulation algorithms in GPSS and SIMSCRIPT. Text Book: Geoffrey Gordon: System Simulation, PHI .


ADVANCED C++


UNIT I: INTRODUCTION: Rationale for a New Programming Language, The Language of Object-Orientation, A Typical C++ Class, Issues Regarding Member Functions vs. Non-Member Functions, Relationships, Initialization Lists, Access Levels, Simple C++ I/O, The Many Uses of const. UNIT II: EXCEPTION HANDLING : Introduction, Principles Of Exception Handling, The Keywords Try, Throw And Catch , Exception Handling Mechanism, Multiple Catch Statements, Catching Multiple Exceptions, Re- Throwing Exception, Specifying Exception, Exceptions In Constructor And Destructors, Controlling Uncaught Exceptions, Class Template With Exception Handling. UNIT III: APPLICATIONS WITH FILES: Introduction, File Stream Classes, File Opening Modes, File Pointers And Manipulators, Manipulators With Arguments, Sequential Access Files, Binary And ASCII Files random Access Operation. UNIT IV: Introduction, A Simple List, Layering Type-safe Classes Upon List, A Template List Class, Iterators, A Template Iterator Stack and Queue Classes, Templates and Inheritance. UNIT V: Why Have Function Pointers? Passing Functions as Arguments, Registering Functions, Function Pointers in C++, Callback Functions, A Class with a Callback Object, Registration of Exception Handlers. UNIT VI: The C++ Standard Template Library Introduction, The Standard Template Library, Design Goals, STL Components, Iterators: vector, list, set map, find, merge, accumulate, Adaptors. TEXT BOOKS : 1. Programming In C++ , Ashok N Kamthane. Pearson 2nd Edition. 2. Object Oriented Programming C++ , Joyce Farrell, Cengage 3. Mastering C ++, Venugopal, Rajkumar, Ravi kumar TMH 4. Object Oriented Programming with C++, 2nd ed, Sourav Sahay, OXFORD

REFERENCE BOOKS:

1. The Complete Reference, C++, 4ed, Herbert Schildt, TMH 2. http://www.tutorialspoint.com/cplusplus/cpp_stl_tutorial.htm.


RUBY


UNIT I: Fundamentals What is Ruby; Ruby download and installation; irb and SciTE; Free format; Case sensitive; Comments; Statement delimiters; Documentation; Operators (with precedence and associatively rules); Ruby editors; .rb file; Concept of an object and that everything is an object in Ruby; Object class and its methods; Usage of puts, gets methods; Ruby conventions; Garbage collection UNIT II: Variables and Constants Name characters; Variables – local, instance, class, global; Constants naming, rules and concept of scope operator::; Naming conventions; Dynamically typed; Usage of method type Numbers: Concept and usage with Class Numeric, Float, Integer, Fixnum and Bignum Strings: String literals using single- and double-quotes and their differences; Usage of #{expression}; Conversions using .to_i, .to_f, .to_s; Usage of <<; Concept of symbols; Class String methods like chomp, reverse, length, upcase, downcase, swapcase, capitalize, strip, length, index, slice, upcase!, downcase!, swapcase! and capitalize!. Random Numbers: rand method UNIT III: Arrays: Concept; Class Array methods like delete, sort, length and each using do end Concept of Ranges and Hashes Constructs: if else end elsif; while end; case when end Regular Expressions: Simple examples UNIT IV: Methods: Writing own methods using def end; class and instance methods (with getter and setter);return and concept of value returned by last statement in a method; variable number of parameters using * Code Blocks: Using do end and { }; Usage of yield method; Concept of Procand its method call; lambda30 UNIT V: File I/O: File class and its method open Writing a class: Standard class Class; initialize; new methods; Access modifiers privateand protected; Usage of attr_reader, attr_writer, attr_accessor; Concept of inheritance and using <; Using super Concept of Duck Typing Modules: Examples of writing a module; Usage of require and include; Concept of mix-ins UNIT VI: Exception handling Exception class and its hierarchy; begin rescue ensure end; Concept of Unit Testing Standard Classes and Modules: Usage of Dir, Time, Thread, Range, IO, Module, GC, Kernel, Math - usage Books:

Programming Ruby by Dave Thomas

Learn to Program by Chris Pine

Ruby For Rails by David Black

Beginning Ruby by Peter Cooper


PHP & MySQL


Course Description: Use PHP and MySQL to develop dynamic web sites for user on the Internet. Develop web sites ranging from simple online information forms to complex e-commerce sites. MySQL database, building, connectivity, and maintenance. Course Objectives:

To understand the general concepts of PHP scripting language for the development of Internet websites.

To understand the basic functions of MySQL database program.

To learn the relationship between the client side and the server side scripts.

To develop a final project using the learned techniques. Outcomes: Upon successful completion of this course, a student should be able to:

Use a PHP editing program. Develop functional PHP script. Develop a MySQL database. Understand the use of PHP with HTML. Understand the ability to post and publish a PHP website. Develop Database connectivity using MySQL. Debug script. Develop Web Applications.

UNIT I: Fundamental of PHP

Concept of PHP, Constants, variables declaration, Comments, Data types, Operators, Command line arguments

UNIT II: Branching and Looping statements

Conditional statements

2.1.1 If-else

2.1.2 Switch

2.1.3 Ternary operators

Looping statements

2.2.1 For loop

2.2.2 While loop 2.2.3 Do-while loop UNIT III:

Creating arrays, Inserting elements in arrays, Retrieving elements from array, Displaying arrays, Sorting array elements

UNIT IV: Introduction to MYSQL

What is Database, Understanding an RDBMS, Understanding Tables, Record & Fields SQL Language,

UNIT V:

Working with MYSQL Admin

Working with PHP My Admin, Types Data Type, Creating Database & Tables, Dropping Database & Tables, Adding Fields, Selecting Table, Alerting Fields Properties

UNIT IV: Developing Applications in PHP using MySQL

Introduction to Databases

Creating database, creating tables, Inserting values in table, Displaying, changing, searching, deleting records from the table

Developing applications in PHP

Arithmetic operators through GUI, Web calculator, SQL queries- insert, select, delete, and update, where, order by.

Reference Books:

1. PHP and MySQL By Dreamtech Publications 2. PHP 5.1 for Beginners – By Ivan Bayross and Sharanam Shah(Shroff Publishers &

Distributors) 3. Beginning PHP 6, Apache, MySQL Web Development- By Timothy Boronczyk, Elizabeth

Naramore, Jason Gerner, Yann Le Scouarnec, Zeremy Stolz, Michael K. Glass

4. PHP and MySQL by Rajendra Salokhe (Aruta Publication

DISCIPLINE ELECTIVE-IV IV Year –II SEMESTER L T C 1 1 2

MOBILE ADHOC AND ENSOR NETWORKS (DISCIPLINE ELECTIVE-IV)

UNIT I

ROUTING Cellular and Ad hoc wireless networks – Issues of MAC layer and Routing – Proactive, Reactive and Hybrid Routing protocols – Multicast Routing – Tree based and Mesh based protocols – Multicast with Quality of Service Provision. UNIT II QUALITY OF SERVICE Real-time traffic support – Issues and challenges in providing QoS – Classification of QoS Solutions – MAC layer classifications – QoS Aware Routing Protocols – Ticket based and Predictive location based Qos Routing Protocols UNIT III ENERGY MANAGEMENT AD HOC NETWORKS Need for Energy Management – Classification of Energy Management Schemes – Battery Management and Transmission Power Management Schemes – Network Layer and Data Link Layer Solutions – System power Management schemes UNIT IV MESH NETWORKS Necessity for Mesh Networks – MAC enhancements – IEEE 802.11s Architecture – Opportunistic Routing – Self Configuration and Auto Configuration - Capacity Models – Fairness – Heterogeneous Mesh Networks – Vehicular Mesh Networks UNIT V SENSOR NETWORKS Introduction – Sensor Network architecture – Data Dissemination – Data Gathering – MAC Protocols for sensor Networks – Location discovery – Quality of Sensor Networks – Evolving Standards – Other Issues – Recent trends in Infrastructure less Networks UNIT VI : Security: Security in ad hoc networks, Key management, Secure routing, Cooperation in MANETs, and Intrusion detection systems. Sensor Network Platforms and Tools: Sensor Network Hardware, Berkeley motes, Sensor Network Programming Challenges, Node-Level Software Platforms, TinyOS, NS-2 and TOSSIM. TEXT BOOK: 1. C. Siva Ram Murthy and B.S.Manoj, “Ad hoc Wireless Networks – Architectures and Protocols’, Pearson Education, 2004 REFERENCES 1. Feng Zhao and Leonidas Guibas, “Wireless Sensor Networks”, Morgan Kaufman Publishers, 2004.

2. C.K.Toh, “Adhoc Mobile Wireless Networks”, Pearson Education, 2002. 3. Thomas Krag and Sebastin Buettrich, ‘Wireless Mesh Networking’, O’Reilly Publishers, 2007. IV Year –II SEMESTER L T C 1 1 2

CYBER FORENSICS (DISCIPLINE ELECTIVE-IV)

UNIT-I

Introduction to Cyber forensics: Information Security Investigations, Corporate Cyber Forensics,Scientific method in forensic analysis, investigating large scale Data breach cases. Analyzingmalicioussoftware. UNIT-II Types of Computer Forensics Technology, Types of Military Computer Forensic Technology, Types ofLaw Enforcement: Computer Forensic Technology, Types of Business Computer Forensic Technology,Specialized Forensics Techniques, Hidden Data and How to Find It, Spyware and Adware, EncryptionMethods and Vulnerabilities, Protecting Data from Being Compromised Internet Tracing Methods,Security and Wireless Technologies, Avoiding Pitfalls with Firewalls Biometric Security Systems UNIT-III Types of Computer Forensics Systems: Internet Security Systems, Intrusion Detection Systems,Firewall Security Systems, Storage Area Network Security Systems, Network Disaster RecoverySystems, Public Key Infrastructure Systems, Wireless Network Security Systems, Satellite Encryption, Security Systems, Instant Messaging (IM) Security Systems, Net Privacy Systems, IdentityManagement Security Systems, Identity Theft, Biometric Security Systems UNIT-IV Ethical Hacking: Essential Terminology, Windows Hacking, Malware, Scanning, Cracking. DigitalEvidence in Criminal Investigations: The Analog and Digital World, Training and Education in digitalevidence, Evidence Collection and Data Seizure: Why Collect Evidence, Collection Options Obstacles, UNIT-V Types of Evidence, The Rules of Evidence, Volatile Evidence, General Procedure, Collection andArchiving, Methods of Collection, Artifacts, Collection Steps, Controlling Contamination: The Chainof Custody, Reconstructing the Attack, The digital crime scene, Investigating Cybercrime, DutiesSupport Functions and Competencies. UNIT-VI Identification of Data: Timekeeping, Forensic Identification and Analysis of Technical SurveillanceDevices, Reconstructing Past Events: How to Become a Digital Detective, Useable File Formats,Unusable File Formats, Converting Files, Investigating Network Intrusions and Cyber Crime,Network Forensics and Investigating logs, Investigating network Traffic, Investigating Web attacks,Router Forensics. Cyber forensics tools and case studies. References: 1. John R. Vacca, Computer Forensics: Computer Crime Scene Investigation, 2nd Edition,

CharlesRiver Media, 2005 2. ChristofPaar, Jan Pelzl, Understanding Cryptography: A Textbook for Students and

Practitioners,2nd Edition, Springer’s, 2010

3. Ali Jahangiri, Live Hacking: The Ultimate Guide to Hacking Techniques & Countermeasures forEthical Hackers & IT Security Experts, Ali Jahangiri, 2009

4. Computer Forensics: Investigating Network Intrusions and Cyber Crime (Ec-Council Press Series:Computer Forensics), 2010


PATTERN RECOGNITION (DISCIPLINE ELECTIVE-IV)

UNIT-I: Introduction: Is Pattern Recognition Important; features, feature vectors, and classifiers; supervised, unsupervised and semi supervised learning; Matlab programs. UNIT-II: Classifiers based on Bayes Decision Theory: Introduction, Bayes Decision Theory; discriminant functions and decision surfaces; Bayesian classification for normal distributions- the Gaussian probability density function, the Bayesian classifier for normally distributed classes; UNIT-III: Linear & Non linear Classifiers: Introduction; linear discriminant functions and decision hyper planes, the perceptron algorithm, Nonlinear Classifiers: introduction, the xor problem, the two -layer perception-classification capabilities of the two-layer perceptron; three-layer perception. Feature Selection: Introduction, Preprocessing-outlier removal, data normalization, missing data; the peaking phenomenon; class separability measures-divergence, chernoff bound and Bhattacharya distance, scatter matrices. UNIT-IV: Supervised Learning: introduction, error-counting approach, exploiting the finite size of the data set; a case study from medical imaging; semi supervised learning-generative models, graph-based methods, transductive support vector machines. Unit-V: Skin based Pattern Extraction And Recognition-Introduction, Neural color Constancy based skin detection, Image segmentation, Local region graph Pattern, Skin region Synthesis pattern, Matching multiple regions with Local Global Graph Method. UNIT-VI: Spatio Temporal Patterns-Measuring similarity patterns-Introduction-Spatio-temporal data collection, representation,. data summarization, Querying Indexing and Clustering of moving object Patterns and trajectories, group patterns mining, mobile patterns, Predicting, similarity measures, l data generation, Trajectory representation, Defining a new similarity measure, Clustering trajectories with K-means algorithm, Incremental approach for clustering. Graph-based methods Introduction, Hyper graph matching and Algorithms, Parquet graphs- similarity function, Local Feature Detectors. TEXT BOOKS: 1. Sergios Theodoridis, Konstantinos Koutroumbas, “Pattern Recognition” Fourth Edition, (Unit I –V) Elsevier 2. Horst Bunke, Abrahmkadel, MarksLast, “Applied Pattern Recognition” 2008 Springer –

Verlag Berlin Heidelberg.(Unit VI-VIII) REFERENCE BOOKS: 1. “Pattern Recognition”, Devi & Murthy, Universities Press 2. “Pattern Recognition and Image Analysis”, Gose, Johnsonbaugh, Jost, PHI 3. Rajjan Shinghal, “Pattern Recognition Techniques and Applications” Oxford University Press. 4. Pattern Classification, 2nd ed, Richard O Duda 5. Applied Pattern recognition, Horst Bunku, Abraham Kandel IV Year –II SEMESTER L T C 1 1 2

GRAPH THEORY AND APPLICATIONS (DISCIPLINE ELECTIVE-IV)

UNIT-I Introduction: Graphs, Sub-graphs, Regular graph, Adjacency and incidence matrices, Finite and infinite graph, Incidence and degree, Isolated vertex, Pendent vertex and null graph, Turan’s theorem. Paths and Circuits: Isomorphism, Walk, Cycle, Paths and circuits, Simple and proper circuit, Connected and disconnected graph, Euler graphs, Operations on graphs, Hamiltonian paths and circuits, Bipartite graph, Berge theorem, Hall’s theorem, Edge connectivity, Blocks, Menger’s theorem. UNIT-II Trees and Fundamental Circuits: Trees, Properties of tree, Pendant vertices in a tree, Distance and centers in a tree, Spanning tree, Cayley’s Formula, Minimal spanning tree, Prim and Kruskal’s algorithm, Matrix Tree theorem, Dijkstra's Shortest Path Algorithm, Floyd-Warshall algorithm, Huffman's Coding Algorithm, Depth-first and breath first algorithm. UNIT-III Cuts sets and cut-vertices: Cut sets, Properties of cutset, all cut sets in a graph, 1-isomorphism, 2-isomorphism. Planar graph and dual graphs: Planar graphs, Homoeomorphic graph, Kuratowski’s Two Graphs, Different representation of a planar graph, Tutte’s f-factor theorem, Detection of planarity, Geometric dual, Combinatorial dual. UNIT-IV Coloring, Covering and Partitioning: Chromatic number, Chromatic Partitioning, Chromatic Polynomial, Covering, Four colour conjecture, Five-colour theorem, Dirac Theorem, Brooks theorem, Vizing theorem. UNIT-V Directed Graphs: Directed graph, Diagraph and binary relations, Directed Paths, Euler diagraphs, Acyclic digraphs, Topological sorting, Warshall’s algorithm, Bellman-Ford algorithm, Ramsey theorems. UNIT-VI Application of Graphs: Study of Konigsberg bridge problem, Travelling-salesman problem, Utilities problem, Electrical network problem, Seating problem, Use of graph in sequential switching networks, Graphs in coding theory, Graphs in computer programming, Flow graph notation, Test case generation using graphs, Job sequencing problem, Graph coloring in scheduling of examinations. Recommended Books: 1. DeoNarsingh, Graph Theory with applications to Engineering and Computer Science, Prentice-Hall of India (2007). 2. Parmenter Michael M., Goodaire Edgar G., Discrete Mathematics with Graph Theory, Prentice-Hall of India (2007).

3. Rosen, Kenneth H. Discrete Mathematics and its Applications, Tata Mcgraw-Hill (2003). 4. Bondy, J.A. Murty U.S.R., Graph theory and Applications, North Holland Publications (1995). IV Year –II SEMESTER L T C 1 1 2

E- COMMERCE (DISCIPLINE ELECTIVE-IV)

UNIT-I Electronic Commerce - Frame work, anatomy of E-Commerce applications, E-Commerce Consumer applications, E-Commerce organization applications. UNIT-II Consumer Oriented Electronic commerce –Consumer Oriented Applications, Mercantile Process models UNIT-III Electronic payment systems (EPS) –Types of EPS, Digital Token-Based, Smart Cards, and Credit Card based EPSs, Risks in Electronic Payment systems. UNIT-IV Inter Organizational Commerce - EDI, EDI Implementation, Value added networks, Legal, Security and Privacy Issues. UNIT-V Corporate Digital Library - Document Library, Types of Digital documents, corporate Data Warehouses. Advertising and Marketing - Information based marketing, Advertising on Internet, on-line marketing process, market research. UNIT-VI Multimedia - key multimedia concepts, Digital Video and electronic Commerce, Desktop video processing, Desktop video conferencing. TEXT BOOKS:

1. Frontiers of Electronic Commerce – Ravi Kalakata, and Andrew B. Whinston, Pearson Education.

REFERENCE BOOKS:

1. E-Commerce fundamentals and applications Hendry Chan, Raymond Lee, Tharam Dillon, Ellizabeth Chang, John Wiley. 2. E-Commerce, S.Jaiswal – Galgotia. 3. E-Commerce, Efrain Turbon, Jae Lee, David King, H.Michael Chang. 4. Electronic Commerce – Gary P.Schneider – Thomson. 5. E-Commerce – Business, Technology, Society, Kenneth C.Taudon, Carol

Guyerico Traver IV Year –II SEMESTER L T C 1 1 2

COMPUTER VISION (DISCIPLINE ELECTIVE-IV)

UNIT-1 CAMERAS: Pinhole Cameras, Camera with Lenses, the Human Eye, Sensing. RADIOMETRY-MEASURING LIGHT: Light in Space, Light at Surfaces, Important Special Cases. UNIT-2 SOURCES, SHADOWS, AND SHADING: Qualitative Radiometry, Sources and Their Effects, Local Shading Models, Application: Photometric Stereo, Inter reflections: Global Shading Models. UNIT-3 LINEAR FILTERS: Linear Filters and Convolution, Shift Invariant Linear Systems, Spatial Frequency and Fourier Transforms, Sampling and Aliasing, Filters as Templates, Technique: Normalized Correlation and Finding Patterns, Technique: Scale and Image Pyramids. UNIT-4 SEGMENTATION BY CLUSTERING: What is Segmentation, Human Vision: Grouping and Gestalt, Applications: Shot Boundary Detection and Background Subtraction, Image Segmentation by Clustering Pixels, Segmentation by Graph-Theoretic Clustering. UNIT-5 SEGMENTATION BY FITTING A MODEL: The Hough Transform, Fitting Lines, Fitting Curves, Fitting as Probabilistic Inference Problem, Robustness, Example: Using RANSAC to Fit Fundamental Matrices, Missing Data Problems, the EM Algorithm. UNIT-6 FINDING TEMPLATES USING CLASSIFIERS: Method for Building Classifiers, Building Classifiers from Class Histograms, Feature Selection, Neural Networks, the Support Vector Machine. TEXT BOOK: 1. David A.Forsyth, Jean Ponce, Computer Vision-A Modern Approach, PHI, 2003. REFERENCE BOOKS: 1. Geometric Computing With Clifford Algebras: Theoretical Foundations and Applications in

Computer Vision and Robotics , Springer; 1 edition,2001 by Sommer. 2. Digital Image Processing and Computer Vision, 1/e, by Sonka. 3. Computer Vision and Applications: Concise Edition(With CD) by Jack, Academy Press, 2000.


GRID & CLOUD COMPUTING (DISCIPLINE ELECTIVE-IV)

OBJECTIVES: The student should be made to:

Understand how Grid computing helps in solving large scale scientific problems.

Gain knowledge on the concept of virtualization that is fundamental to cloud computing.

Learn how to program the grid and the cloud.

Understand the security issues in the grid and the cloud environment. UNIT I INTRODUCTION Evolution of Distributed computing: Scalable computing over the Internet – Technologies for network based systems – clusters of cooperative computers - Grid computing Infrastructures – cloud computing - service oriented architecture – Introduction to Grid Architecture and standards – Elements of Grid – Overview of Grid Architecture. UNIT II GRID SERVICES Introduction to Open Grid Services Architecture (OGSA) – Motivation – Functionality Requirements – Practical & Detailed view of OGSA/OGSI – Data intensive grid service models – OGSA services. UNIT III VIRTUALIZATION Cloud deployment models: public, private, hybrid, community – Categories of cloud computing: Everything as a service: Infrastructure, platform, software - Pros and Cons of cloud computing – Implementation levels of virtualization – virtualization structure – virtualization of CPU, Memory and I/O devices – virtual clusters and Resource Management – Virtualization for data center automation. UNIT IV PROGRAMMING MODEL Open source grid middleware packages – Globus Toolkit (GT4) Architecture, Configuration –

Usage of Globus – Main components and Programming model. UNIT V HADOOP FRAME WORK: Introduction to Hadoop Framework - Mapreduce, Input splitting, map and reduce functions, specifying input and output parameters, configuring and running a job – Design of Hadoop file system, HDFS concepts, command line and java interface, dataflow of File read & File write. UNIT VI SECURITY Trust models for Grid security environment – Authentication and Authorization methods - Grid security infrastructure – Cloud Infrastructure security: network, host and application level – aspects of data security, provider data and its security, Identity and access management architecture, IAM practices in the cloud, SaaS, PaaS, IaaS availability in the cloud, Key privacy issues in the cloud. OUTCOMES: At the end of the course, the student should be able to:

Apply grid computing techniques to solve large scale scientific problems.

Apply the concept of virtualization.

Use the grid and cloud tool kits.

Apply the security models in the grid and the cloud environment. TEXT BOOK: 1. Kai Hwang, Geoffery C. Fox and Jack J. Dongarra, “Distributed and Cloud Computing:

Clusters, Grids, Clouds and the Future of Internet”, First Edition, Morgan Kaufman Publisher, an Imprint of Elsevier, 2012.

REFERENCES: 1. Jason Venner, “Pro Hadoop- Build Scalable, Distributed Applications in the Cloud”, A Press,

2009 2. Tom White, “Hadoop The Definitive Guide”, First Edition. O’Reilly, 2009. 3. Bart Jacob (Editor), “Introduction to Grid Computing”, IBM Red Books, Vervante, 2005 4. Ian Foster, Carl Kesselman, “The Grid: Blueprint for a New Computing Infrastructure”,

2nd Edition, Morgan Kaufmann. 5. Frederic Magoules and Jie Pan, “Introduction to Grid Computing” CRC Press, 2009. 6. Daniel Minoli, “A Networking Approach to Grid Computing”, John Wiley Publication, 2005. 7. Barry Wilkinson, “Grid Computing: Techniques and Applications”, Chapman and Hall, CRC,

Taylor and Francis Group, 2010.


PROJECT WORK

iv b. tech ii semester (viii semester) - ongoleqiscet.edu.in/docs-pdf/174-2.pdf · code iv b. tech...

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