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B.E Computer Science & Engineering syllabus - Kumaraguru ...

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KUMARAGURUCOLLEGE OF TECHNOLOGY
(An Autonomous Institution Affiliated to Anna University, Chennai)
COIMBATORE – 641049

REGULATIONS 2014

CURRICULUM AND SYLLABUS






IIIrd- VIIIth Semesters

BE COMPUTER SCIENCE AND ENGINEERING



DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING










DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING


Vision
To evolve as a School of Computer Science with centers of excellence having international reputation to serve the changing needs of Indian industry and society.

Mission
Computer Science and Engineering department is committed to bring out career oriented graduates who are industry ready through innovative practices of teaching-learning process.
To cultivate professional approach, strong ethical values and team spirit along with leadership qualities among the graduates by organizing workshops, seminars and conferences periodically. Association with professional bodies and invitation to external experts should help this.
To contribute towards techno-economic and social development of the nation through quality human resource and encouraging entrepreneurship among the young graduates.



Programme Educational Objectives
Graduates of the programme will be successful in their professional careers, including entrepreneurship using their knowledge in computer science and engineering. (90%)
Graduates of the programme will continue to learn and adopt latest technologies to solve real life problems. (80%)
Graduates of the programme will pursue research and higher education (20%)

















Programme Outcomes
Engineering knowledge -Ability to apply the knowledge of mathematics, physical sciences and computer science and engineering specialization to the solution of complex engineering problems
Problem analysis -Ability to identify, formulate and analyze complex real life problems in order to provide meaningful solutions by applying knowledge acquired in computer science and engineering.
Design/development of solutions -Ability to design cost effective software / hardware solutions to meet desired needs of customers/clients.
Conduct investigations of complex problems –Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions in the field of computer science and engineering.
Modern tool usage -Create, select and apply appropriate techniques, resources and modern computer science and engineering tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
The engineer and society - Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.










KUMARAGURU COLLEGE OF TECHNOLOGY, COIMBATORE – 641 049
REGULATIONS 2014 (REVISED 2015)
BE COMPUTER SCIENCE AND ENGINEERING
CURRICULUM
SEMESTER I
Code No.Course TitleLTPCTheory U14ENT101Technical English 2103U14MAT101Engineering Mathematics – I3104U14PHT101Engineering Physics 3003U14CHT101Engineering Chemistry 3003U14CST101Structured Programming Using C3104U14ITT101Foundations of Information Technology3003PracticalU14PHP101Physics Laboratory0031U14CSP101Structured Programming Laboratory using C0031U14CSP102Computer Hardware Laboratory0031U14GHP101Human Excellence: Personal Values 1011 Total Credits:24
SEMESTER II
Code No.Course TitleLTPCTheory U14ENT201Professional English1022U14MAT201Engineering Mathematics - II 3104U14PHT203Materials Science 3003U14EET212Electrical and Electronic Circuits3104U14MET201Engineering Graphics2033U14CST201Digital Systems and Design3104Practical U14EEP212Electrical and Electronic Circuits Laboratory0021U14MEP201Engineering Practices Laboratory0021U14CSP201 Digital Systems and Design Laboratory0021U14GHP201Human Excellence: Family and Professional values1011 Total Credits:24


SEMESTER III
Code No.Course TitleLTPCTheory U14MAT301Numerical Methods 3104U14CST301Data Structures and Algorithms3003U14CST302Computer Architecture 3104U14CST303Computer Graphics3024U14CST304Object Oriented Programming with C++ 3003U14GST001Environmental Science and Engineering3 003Practical U14CSP301Data Structures and Algorithms Laboratory0021U14CSP302Object Oriented Programming Laboratory 0021U14ENP301Communication Skills Laboratory0021U14GHP301Human Excellence: Social Values1011 Total Credits:25SEMESTER IV
Code No.Course TitleLTPCTheory U14MAT402Signals and Systems3024U14CST401Design and Analysis of Algorithms3024U14CST402Operating Systems3 003U14CST403Microprocessors 3104U14CST404Database Management Systems3024U14CST405Theory of Computation3104Practical U14CSP401Java Programming Laboratory 0021U14CSP402Microprocessors Laboratory 0021U14CSP403Operating Systems Laboratory0021U14GHP401Human Excellence: National and Global Values1011 Total Credits:27





Code No.Course TitleLTPCTheory U14MAT506Probability and Queuing Theory3104U14CST501Principles of Compiler Design3104U14CST502Computer Networks3003U14CST503XML and Web Services 3003U14ECT511Digital Signal Processing3104E1Elective I3003Practical U14CSP501Computer Networks Laboratory0021U14CSP502XML and Web Services Laboratory 0021U14CSP503Database Management Systems Laboratory0021 Total Credits:24SEMESTER V


SEMESTER VI
Code No.Course TitleLTPCTheory U14CST601Artificial Intelligence3104U14CST602Cryptography and Network Security3024U14CST603Software Engineering3003U14GST007Professional Ethics3003E2Elective II 3003E3Elective III3003EINElective – One credit course1001Practical U14CSP601Software Engineering Laboratory0021U14CSP604Mini Project using Open Source Software0021E3PElective III Laboratory0021 Total Credits:24






SEMESTER VII
Code No.Course TitleLTPCTheory U14CST701Mobile and Pervasive Computing3003U14CST702Data Warehousing and Data Mining3003U14CST703Cloud Computing3024U14GST003 Principles of Management 3003E4Elective IV – Engineering Science3104E5Elective V3104Practical U14CSP701Mobile and Wireless Networks Laboratory0021U14CSP702Data Warehousing and Data mining Laboratory0021U14CSP703Project Work – Phase I0042 Total Credits:25

SEMESTER VIII
Code No.Course TitleLTPCTheory E6Elective VI3003E7Elective VII3003E8Elective VIII3003Practical U14CSP801Project Work – Phase II00126 Total Credits:15Overall Credits(1-8 semesters):187 
ELECTIVES FOR FIFTH SEMESTER
Code No.Course TitleLTPCTheory (Elective I)U14CSTE11Advanced Computer Architecture3003U14CSTE12Knowledge Based Decision Support Systems3003U14CSTE13Building Enterprise Applications3003





ELECTIVES FOR SIXTH SEMESTER

Code No.Course TitleLTPCTheory (Elective II)U14GST005Engineering Economics and Financial Management3003U14GST008Foundation Skills in Integrated Product Development3003U14CSTE21Content Management using Joomla2023U14CSTE22Web Programming with XML 2023U14CSTE23Fundamentals of Database Management Systems2023U14CSTE24Functional Programming2023U14CSTE25PERL Programming2023Theory (Elective III)U14CSTE31Open Source Technologies300 3U14CSTE32Digital Image Processing3003U14CSTE33Multimedia Systems3003Practical (Elective III)U14CSPE31Open Source Technologies Laboratory0031U14CSPE32Digital Image Processing Laboratory0031U14CSPE33Multimedia Systems Laboratory0031
ELECTIVES FOR SEVENTH SEMESTER

Code No.Course TitleLTPCTheory (Elective IV -Engineering Science )U14CSTE41 Natural Language Processing 3104U14CSTE42Mobile Application Development using Android3024U14CSTE43Internet of Things3024Theory (Elective V )U14CSTE51Real Time Systems3104U14CSTE52High Speed Networks3104U14CSTE53Pattern Recognition3104U14CSTE54Machine Learning Techniques3104







ELECTIVES FOR EIGHTH SEMESTER

Theory (Elective VI)U14GST004Operations Research3003U14ECTE81Analog and Digital Communication3003U14CSTE61Cyber Forensics3003U14CSTE62Advanced Database Technologies3003U14CSTE63TCP/IP Socket Programming3003Theory (Elective VII)U14CSTE71Service Oriented Architecture3003U14CSTE72Computer Vision3003U14CSTE73Adhoc and Sensor Networks3003U14CSTE74Business Intelligence and its Applications3003U14CSTE75Big Data and Analytics3003Theory (Elective VIII)U14CSTE81Distributed Systems3003U14CSTE82Ontology and Semantic Web3003U14CSTE83Software Quality Assurance and Testing3003U14CSTE84Information Retrieval3003U14CSTE85Computational Intelligence3003

ONE CREDIT COURSES
Sl. No.Course CodeCourse TitleIndustry offering the course1U14CSIN01Computer Crimes, Security and Cyber LawsHCL Technologies, Coimbatore2U14CSIN02Business AnalyticsHCL Technologies, Coimbatore3U14CSIN03Ethical HackingHCL Technologies, Coimbatore4U14CSIN04Linux System AdministrationHCL Technologies, Coimbatore












SEMESTER III




































LTPC3104U14MAT301 NUMERICAL METHODS
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Solve a set of algebraic equations representing steady state models formed in engineering problems
CO2: Fit smooth curves for the discrete data connected to each other or to use interpolation
methods over these data tables.
CO3: Find the trend information from discrete data set through numerical differentiation and
summary information through numerical integration.
CO4: Predict the system dynamic behavior through solution of ODEs modeling the system.
CO5: Solve PDE models representing spatial and temporal variations in physical systems
through numerical methods.
CO6: Have the necessary proficiency of using MATLAB for obtaining the above solutions.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMSSCO2SSSSCO3MSSMCO4SMSCO5MSSSCO6SCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam
5. Lab ExerciseCourse End Survey

INTRODUCTION 3 Hrs
Simple mathematical modeling and engineering problem solving – Algorithm Design – Flow charting and pseudocode - Accuracy and precision – round off errors.
NUMERICAL SOLUTION OF ALGEBRAIC EQUATIONS 7+3HrsSolution of nonlinear equations: False position method – Fixed point iteration – Newton Raphson method for a single equation and a set of non- linear equations
Solution of linear system of equations by Gaussian elimination method - Gauss Jordan method - Gauss Seidel method.
CURVE FITTING AND INTERPOLATION 7+3HrsCurve fitting – Method of least squares – Regression – Interpolation: Newton’s forward and backward difference formulae – Divided differences – Newton’s divided difference formula - Lagrange’s interpolation – Inverse interpolation.
NUMERICAL DIFFERENTIATION AND INTEGRATION 7+3HrsNumerical differentiation by using Newton’s forward, backward and divided differences – Numerical integration by Trapezoidal and Simpson’s 1/3rd and 3/8 th rules – Numerical double integration.
NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS 10+3HrsInitial value problems - Single step methods: Taylor’s series method – Truncation error – Euler and Improved Euler methods – Fourth order Runge - Kutta method – Multistep method: Milne’s predictor - corrector method.
NUMERICAL SOLUTION OF PARTIAL DIFFERENTIAL EQUATIONS (PDEs) 11+3HrsPDEs and Engineering Practice – Laplace Equation derivation for steady heat conduction – Numerical solution of the above problem by finite difference schemes – Parabolic Equations from Fourier`s Law of Transient Heat Conduction and their solution through implicit schemes – Method of Lines – Wave propagation through hyperbolic equations and solution by explicit method.
Use of MATLAB Programs to workout solutions for all the problems of interest in the above topics. 
Theory:45 Hrs Tutorial: 15 Hrs Total Hours: 60 References:
1. Steven C.Chapra and Raymond P. Canale, “ Numerical Methods for Engineers with
Programming and Software Applications”, Sixth Edition, WCB/McGraw-Hill, 1998.
2. John H. Mathews and Kurtis D. Fink, “Numerical Methods using Matlab”, Fourth
Edition, Prentice Hall of India, 2004.
3. Gerald C. F. and Wheatley P.O, “Applied Numerical Analysis”, Sixth Edition, Pearson
Education Asia, New Delhi, 2002.
4. Sastry S.S, “Introductory Methods of Numerical Analysis”, Third Edition, Prentice –
Hall of India Pvt Ltd, New Delhi, 2003.
5. Kandasamy P., Thilagavathy K. and Gunavathy K., “Numerical Methods”, S.Chand Co.
Ltd., New Delhi, 2007.



LTPC3003U14CST301 DATA STRUCTURES AND ALGORITHMS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the basic data structures and its operations.
CO2: Explain the concept of time complexity and space complexity.
CO3: Identify an appropriate data structure for a problem.
CO4: Make use of basic data structures to solve problems.
CO5: Summarize various searching and sorting algorithms.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3MMCO4MMCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam Course End SurveyLISTS, STACKS AND QUEUES 9 HrsAbstract Data Type (ADT) – The List ADT and its applications – The Stack ADT and its applications – The Queue ADT and its applicationsTREES 9 HrsPreliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees-Threaded Binary trees – Tree Traversals - Priority Queues (Heaps) – Model – Simple implementations – Binary Heap

SEARCH STRUCTURES AND HASHING 9 HrsAVL Trees – Splay Trees – B-Trees -Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing – Linear Probing GRAPHS 9 HrsDefinitions – Topological Sort – Shortest-Path Algorithms – Unweighted Shortest Paths – Dijkstra’s Algorithm – Minimum Spanning Tree – Prim’s Algorithm – Kruskal’s Algorithm - Applications of Depth-First Search – Undirected Graphs – Biconnectivity.SORTING AND SEARCHING 9 Hrs Sorting-Preliminaries – Insertion Sort – Shell sort – Heap sort – Merge sort – Quick sort – External Sorting –Searching –Linear Search-Binary Search.Theory: 45 Hrs Total Hours: 45 
References:
M.A.Weiss, “Data Structures and Algorithm Analysis in C”, Second Edition, Pearson Education Asia, 2007.
Y. Langsam, M. J. Augenstein and A. M. Tenenbaum, “Data Structures using C and C++”, Second Edition, Prentice-Hall of India, 2009.
Alfred V. Aho, John E. Hopcroft and Jeffry D. Ullman, “Data Structures & Algorithms”, Pearson Education, New Delhi, 2009.

Other References:
http://www.pearsonhighered.com/educator/product/Data-Structures-and-Algorithm-Analysis-in-C
HYPERLINK "http://users.cis.fiu.edu/~weiss/"http://users.cis.fiu.edu/~weiss/
http://catalogue.pearsoned.co.uk/educator/product/Solutions-Manual-for-Data-Structures-and-Algorithm-Analysis-in-C-International-Editions-4E










LTPC3104U14CST302 COMPUTER ARCHITECTURE

Course Outcomes:After successful completion of this course, the students should be able to
CO1: Explain the organization and working principle of computer hardware components.
CO2: Explain the hierarchical memory system and data transfer with in a digital computer.
CO3: Outline the operation of arithmetic unit
CO4: Summarize the execution sequence of an instruction through the processor
CO5: Explain the ways of communication between a processor and I/O devices.
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SCO3MCO4MMCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey

BASIC STRUCTURE OF COMPUTERS  7+3 HrsFunctional Units - Basic Operational Concepts - Bus Structures - Software Performance - Memory Locations and Addresses - Memory Operations - Instruction and Instruction Sequencing - Addressing Modes - Assembly Language - Basic I/O Operations - Stacks and Queues.MEMORY SYSTEM  8+3 HrsBasic Concepts - Semiconductor RAM- ROM- Speed, Size and Cost - Cache Memories - Performance Considerations - Virtual Memory- Memory Management Requirements.ARITHMETIC AND LOGIC UNIT 11+3 HrsAddition and Subtraction of Signed Numbers - Design of Fast Adders - Multiplication of Positive Numbers - Signed Operand Multiplication and Fast Multiplication - Integer Division - Floating Point Numbers and Operations.BASIC PROCESSING UNIT AND PIPELINING  12+3 HrsFundamental Concepts - Execution of a Complete Instruction - Multiple Bus Organization - Hardwired Control - Microprogrammed Control - Pipelining - Basic Concepts - Data Hazards - Instruction Hazards - Influence on Instruction Sets- Data path and control considerations- Superscalar operation.PERIPHERALS AND I/O ORGANIZATION  7+3 HrsInput and output devices- Serial communication links - Accessing I/O Devices - Interrupts - Direct Memory Access - Buses - Standard I/O Interfaces (PCI, SCSI, USB).Theory: 45 Hrs Tutorial: 15 Hrs Total Hours: 60 
References:
Carl Hamacher, Zvonko Vranesic and Safwat Zaky, “Computer Organization”, Fifth Edition, McGraw-Hill, 2002.
William Stallings, “Computer Organization and Architecture - Designing for Performance”, Ninth Edition, Prentice Hall, 2012.
David A.Patterson and John L.Hennessy, “Computer Organization and Design: The hardware / software interface”, Fourth Edition, Morgan Kaufmann, 2008.
John P.Hayes, “Computer Architecture and Organization”, Third Edition, McGraw Hill, 2002.




LTPC3024
U14CST303 COMPUTER GRAPHICS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the working of Input and Output devices for graphics.
CO2: Explain about graphics primitives and work with coordinate spaces, coordinate
conversion, and transformations of graphics objects.
CO3: Demonstrate 2D & 3D geometrical transformations using modern tools.
CO4: Explain various 3D projections and current models for surfaces.
CO5: Make use of the color and transformation techniques for various applications.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2SMCO3SMCO4MCO5MW
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Mini Project
4. End Semester ExamCourse End Survey


2D PRIMITIVES 9+3 Hrs
Computer Graphics hardware–software–Introduction to OpenGL–Basic OpenGL programming– graphics Output primitives–Attributes of graphics primitives–Implementation algorithms for graphics primitives and attributes-Line, Circle and Ellipse drawing algorithms





2D GEOMETRIC TRANSFORMATIONS AND VIEWING  9+3 Hrs
Basic 2D Geometric Transformations – Matrix Representations – Composite Transformations – Reflection and Shearing Transformations- 2D Viewing-The Viewing pipeline – Viewing Coordinate Reference Frame – Window to View port Coordinate Transformation – Two Dimensional Viewing Functions- Clipping Operations –Point Clipping –Cohen-Sutherland Line Clipping – Sutherland-Hodgman Polygon Clipping
3D GEOMETRIC TRANSFORMATIONS 9+3 Hrs
3D Transformations-Translation–Rotation–Scaling–Reflection and Shear- Composite transformations –Transformations between 3D coordinate systems-Affine Transformations - -3D clipping algorithms – Clipping in Three-Dimensional Homogeneous Coordinates- Three-Dimensional Region Codes- Three-Dimensional Point and Line clipping - Three-Dimensional Polygon Clipping
3D OBJECT VIEWING AND REPRESENTATIONS 9+3 Hrs
3D viewing pipeline-viewing coordinate parameters- Transformation from World to Viewing coordinates – Projection Transformations-Viewport Transformation and 3D screen coordinates-Parallel Projection-Perspective Projection – Curved surfaces – Quadric surfaces–Interpolation and Approximation Splines- Bezier Spline curves
COLOR MODELS AND COMPUTER ANIMATION 9+3 Hrs
Color Models – Standard Primaries and the Chromaticity Diagrams –The RGB Color Model – YIQ and related Color Models – CMY and CMYK Color Models – HSV and HLS Color Models– Computer Animation: Design of Animation Sequences – General Computer Animation Functions – Raster Animations – Computer Animation Languages – Key Frame Systems – Motion Specifications
Theory: 45 Hrs Practical: 15 Hrs Total Hours: 60 
References:
Donald D. Hearn, M. Pauline Baker and Warren Carithers, “Computer Graphics with OpenGL”, Fourth Edition, Pearson Education, 2014.
John F. Hughes, Andries Van Dam, Morgan Mc Guire ,David F. Sklar , James D. Foley, Steven K. Feiner and Kurt Akeley ,”Computer Graphics: Principles and Practice”, Third Edition, AddisonWesley Professional, 2013.
F. S. Hill and Stephen M.Kelley, “Computer Graphics using OPENGL”, Third Edition, Pearson Education, 2014.





Other References:
http://nptel.ac.in/
http://ocw.mit.edu/courses/electrical-engineering-and-computerscience/6-837-computer-graphics-fall-2003/
http://www.moshplant.com/direct-or/bezier/
http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/spline/B -spline/bspline-curve-prop.html





LTPC3003U14CST304 OBJECT ORIENTED PROGRAMMING WITH C++
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Define principles of Object Oriented programming.
CO2: Outline the differences between object oriented programming and procedure oriented programming.
CO3: Develop solutions for problems using class and object concepts.
CO4: Make use of overloading and inheritance concepts to solve problems.
CO5: Develop programs for file and template related concepts.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1WCO2WCO3SMC04SCO5MMCourse Assessment methods:
DirectIndirectInternal Tests
End Semester Exam
3. Assignments
4. SeminarCourse End Survey
INTRODUCTION  9 HrsObject-Oriented Paradigm - Elements of Object Oriented Programming – Merits and Demerits of OO Methodology – C++ fundamentals – Data types, Operators and Expressions, Control flow, Arrays, Structure and Functions. CLASSES AND OBJECTS  9 HrsClasses and Objects – Passing objects as arguments – returning objects –– Static data and member functions – Constructors- Parameterized constructor - Destructor- Copy Constructors - Array of Objects – pointer to object members.
POLYMORPHISM AND INHERITANCE  9 HrsPolymorphism – Function overloading – Unary operator overloading – binary operator overloading – Data Conversion- Overloading with Friend Functions. Inheritance –Derived class – Abstract Classes - Types of Inheritance.VIRTUAL FUNCTIONS AND TEMPLATES  9 HrsVirtual functions – Need- Definition - Pure Virtual Functions – Virtual Destructors Template – Class template, Function Template. FILES AND EXCEPTION HANDLING 9 HrsC++ streams – console streams – console stream classes - formatted and unformatted console I/O operations – Manipulators - File stream classes - File modes - File pointers and Manipulations - File I/O – Exception handling. Theory: 45 Hrs Total Hours: 45 References:
K.R.Venugopal, Rajkumar Buyya, "Mastering C++", TMH, 2013.
Bjarne Stroustrup, “The C++ programming language”, Addison Wesley, Fourth Edition, 2013.
E.Balagurusamy, “Object Oriented Programming with C++”, Fifth Edition, TMH Second Edition, 2011.
Ira Pohl, “Object oriented programming using C++”, Pearson Education Asia, 2004.











LTPC3003U14GST001 ENVIRONMENTAL SCIENCE AND
ENGINEERING

Course Outcomes:
After successful completion of this course, the students should be able to

CO1: Play an important role in transferring a healthy environment for future generations
CO2: Analyse the impact of engineering solutions in a global and societal context
CO3: Discuss contemporary issues that results in environmental degradation and would attempt
to provide solutions to overcome those problems
CO4: Ability to consider issues of environment and sustainable development in his personal and
professional undertakings
CO5: Highlight the importance of ecosystem and biodiversity
CO6: Paraphrase the importance of conservation of resources

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSCO2SSCO3MCO4WMWCO5MMCO6MWCourse Assessment methods:
DirectIndirectInternal tests
End Semester Exam
Assignments Course End Survey












INTRODUCTION TO ENVIRONMENTAL STUDIES AND NATURAL RESOURCES











10 HrsDefinition, scope and importance – Need for public awareness – Forest resources: Use and over-exploitation, deforestation, case studies. Timber extraction, mining, dams and their effects on forests and tribal people – Water resources: Use and overutilization of surface and ground water, floods, drought, conflicts over water, dams benefits and problems – Mineral resources: Use and exploitation, environmental effects of extracting and using mineral resources, case studies – Food resources: World food problems, changes caused by agriculture and overgrazing, effects of modern agriculture, fertilizer-pesticide problems, water logging, salinity, case studies – Energy resources: Growing energy needs, renewable and non renewable energy sources, use of alternate energy sources. Case studies – Land resources: Land as a resource, land degradation, man induced landslides, soil erosion and desertification – Role of an individual in conservation of natural resources – Equitable use of resources for sustainable lifestyles.ECOSYSTEMS AND BIODIVERSITY 14 HrsECOSYSTEM : Concept of an ecosystem – Structure and function of an ecosystem: Producers, consumers and decomposers, Energy flow in the ecosystem, Food chains, food webs and ecological pyramids - Ecological succession – Introduction, types, characteristic features, structure and function of the (a) Forest ecosystem (b) Grassland ecosystem (c) Desert ecosystem (d) Aquatic ecosystems (ponds, streams, lakes, rivers, oceans, estuaries) –
BIODIVERSITY : Introduction to Biodiversity – Definition: genetic, species and ecosystem diversity – Biogeographical classification of India – Value of biodiversity: consumptive use, productive use, social, ethical, aesthetic and option values – Biodiversity at global, National and local levels – India as a mega-diversity nation – Hot-spots of biodiversity – Threats to biodiversity: habitat loss, poaching of wildlife, man-wildlife conflicts – Endangered and endemic species of India – Conservation of biodiversity: In-situ and Ex-situ conservation of biodiversity.
ENVIRONMENTAL POLLUTION 8 HrsDefinition – Causes, effects and control measures of: (a) Air pollution (b) Water pollution (c) Soil pollution (d) Marine pollution (e) Noise pollution (f) Thermal pollution (g) Nuclear hazards – Solid waste Management: Causes, effects and control measures of urban and industrial wastes – Role of an individual in prevention of pollution – Pollution case studies – Disaster management: floods, earthquake, cyclone and landslides.
SOCIAL ISSUES AND THE ENVIRONMENT 7HrsFrom Unsustainable to Sustainable development – Urban problems related to energy – Water conservation, rain water harvesting, watershed management – Resettlement and rehabilitation of people; its problems and concerns, case studies – Environmental ethics: Issues and possible solutions – Climate change, global warming, acid rain, ozone layer depletion, nuclear accidents and holocaust, case studies. – Wasteland reclamation – Consumerism and waste products – Environment Production Act – Air (Prevention and Control of Pollution) Act – Water (Prevention and control of Pollution) Act – Wildlife Protection Act – Forest Conservation Act – Issues involved in enforcement of environmental legislation – Public awareness.

HUMAN POPULATION AND THE ENVIRONMENT  6 Hrs
Population growth, variation among nations – Population explosion – Family Welfare Programme – Environment and human health – Human Rights – Value Education – HIV / AIDS – Women and Child Welfare – Role of Information Technology in Environment and human health – Case studies.
Field Work
Visit to local area to document environmental assets- river / grassland / hill / mountain, visit to local polluted site- urban / rural / industrial / agricultural, study of common plants, insects, birds, study of simple ecosystems-pond, river, hill slopes etc.,
 Theory: 45 Hrs Total Hours: 45 
References:
Miller T.G. Jr., “Environmental Science”, Wadsworth Publishing Co., 2013.
Masters G.M., and Ela W.P., “Introduction to Environmental Engineering and Science”, Pearson Education Pvt., Ltd., Second Edition.
Bharucha Erach, “The Biodiversity of India”, Mapin Publishing Pvt. Ltd., Ahmedabad India., 2002.
Trivedi R.K and Goel P.K., “Introduction to Air pollution”, Techno-science Pubications. 2003
Trivedi R.K., “Handbook of Environmental Laws, Rules, Guidelines, Compliances and Standards”, Vol. I and II, Enviro Media. 1996
Cunningham, W.P., Cooper, T.H.., & Gorhani E., “Environmental Encyclopedia”, Jaico Publ., House, Mumbai, 2001.
Wager K.D., “Environmental Management”, W.B. Saunders Co., Philadelphia, USA, 1998.
Townsend C., Harper J and Michael Begon, “Essentials of Ecology”, Blackwell science Publishing Co., 2003.
Syed Shabudeen, P.S. “Environmental chemistry”, Inder Publishers, Coimbatore. 2013.


LTPC0031 U14CSP301 DATA STRUCTURES AND ALGORITHMS
LABORATORY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Implement various basic data structures and its operations.
CO2: Implement various sorting and searching algorithms.
CO3: Implement various tree operations.
CO4: Implement various graphs algorithms.
CO5: Develop simple applications using various data structures.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2SMCO3MCO4MCO5MM
Course Assessment methods:
DirectIndirect1.Model Exams
2. End Semester Exam
3.Viva VoceCourse End Survey

List of Experiments
Array based implementation of stack and queue.
Linked list implementations and problems related to linked list such as inverting list, concatenation, etc.
Linked list based implementation of stack and queue.
Problems related to applications of stack.
Search Tree ADT - Binary Search Tree and traversal.
AVL tree implementation.
Implementation of Hash Tables.
Implementation of graph traversal.
Implementation of Dijkstra’s algorithm.
Implementation of minimum spanning tree algorithm.
Sorting – Heap sort, Quick sort, Merge sort.
Searching – Linear search, Binary search.

Experiments beyond the syllabus should be conducted.

Total Hours: 24



























LTPC0031U14CSP302 OBJECT ORIENTED PROGRAMMING
LABORATORY
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Demonstrate class object concepts by using C++.
CO2: Develop programs using inheritance and polymorphism.
CO3: Demonstrate the significance of constructors and destructor.
CO4: Implement function and operator overloading using C++.
CO5: Construct generic classes using template concepts.
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3WCO4MCO5M
Course Assessment methods:
DirectIndirect1.Model Exams
2. End Semester Exam
3.Viva VoceCourse End Survey

List of Experiments
Simple class, objects and array of objects.
Function Overloading
Constructor, Destructor, Constructor Overloading
Unary and binary operator overloading
Inheritance, Data conversions
Static data and Static function
Virtual function and virtual base class
Class Templates, Function Templates
Exception handling
File operations
Experiments beyond the syllabus should be conducted.
Total Hours: 24





LTPC0031U14ENP301 COMMUNICATION SKILLS LABORATORY
(Common to all branches of Engineering and Technology)
Course Outcomes (COs)
After successful completion of this course, the students should be able to
CO1: Imparting the role of communicative ability as one of the soft skills needed for placement
CO2: Developing communicative ability and soft skills needed for placement
CO3: Making students Industry-Ready through inculcating team-playing capacity

Pre-requisites:
1. U14ENT101 - Functional English I
2. U14ENT201 - Functional English II

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2WMSCO3SWS
Course Assessment methods:
DirectIndirectPresentation, Role Play, Mock interview, GD etc.

GRAMMAR IN COMMUNICATION 9 periods
Grammar and Usage – Building Blocks, Homonyms, Subject and Verb Agreement, Error Correction - Grammar Application, Framing Questions – Question words, Verbal Questions, Tags, Giving Replies –Types of Sentences, Listening Comprehension –Listening and Ear training.
ASSERTIVE COMMUNICATION 9 periods
Listening Comprehension in Cross–Cultural Ambience, Telephonic Conversations/Etiquette, Role Play Activities, Dramatizing Situations- Extempore – Idioms and Phrases.
CORPORATE COMMUNICATION 9 periods
Video Sensitizing, Communicative Courtesy – Interactions – Situational Conversations, Time Management, Stress Management Techniques, Verbal Reasoning, Current Affairs – E Mail Communication / Etiquette.


PUBLIC SPEAKING 9 periods
Giving Seminars and Presentations, Nuances of Addressing a Gathering - one to one/ one to a few/ one to many, Communication Process, Visual Aids & their Preparation, Accent Neutralization, Analyzing the Audience, Nonverbal Communication.

INTERVIEW & GD TECHNIQUES 9 periods
Importance of Body Language –Gestures & Postures and Proxemics, Extempore, Facing the Interview Panel, Interview FAQs, Psychometric Tests and Stress Interviews, Introduction to GD, Mock GD Practices.
Total: 45 Periods
References:
Bhatnagar R.P. & Rahul Bhargava, “English for Competitive Examinations”, Macmillian Publishers, India, 1989, ISBN: 9780333925591
Devadoss K. & Malathy P., “Career Skills for Engineers”, National Book Publishers, Chennai, 2013.
Aggarwal R.S., “A Modern Approach to Verbal & Non–Verbal Reasoning”, S.Chand Publishers, India, 2012, ISBN : 8121905516










LTPC1011U14GHP301 HUMAN EXCELLENCE: SOCIAL VALUES
(Common to all branches of Engineering and Technology)

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Adopt and practice social values as his regular duties.
CO2: Take over the social responsibilities.
CO3: Give solutions and to manage the challenging social issues.
CO4: Voluntarily participate and organize social welfare programmes.
CO5: Explore his ideology of techno social issues and provide the best solution.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1WWMSCO2SMCO3WMWCO4WSMWCO5MWWCourse Assessment methods:
DirectIndirect1.Continuous assessment
2.End Semester Exam1.Attitude
2.Behavior
ORGIN OF SOCIETY 5 Hrs
Evolution of universe: Creation theory,Big bang theory, Evolution theory, Permanence theory - Mithya, Maya – Evolution of living being - Evolution of Man – Formation of society and social values.
Practical: Group Discussion on Evolution of Man and formation of society, Panel discussion on Social values - Pancha Bhoodha Navagraha Meditation.

SELF AND SOCIETY 2 Hrs
Duty to self, family, society and world –Realization of Duties and Responsibilitiesof individuals in the society (Five fold cultures) – impact of social media on present day youth and correction measures.
Practical: Case study – interaction with different professionals.



EDUCATION& SOCIETY 3 Hrs
Education: Ancient and Modern Models.
Practical: Making Short film on impact of education in social transformation.

DISPARITY AMONG HUMAN BEINGS 3 Hrs
Wealth’s for humans, Factors leading to disparity in human beings and Remedies.
Practical: Debate on disparity and social values.

CONTRIBUTION OF SELF TO SOCIAL WELFARE 3 Hrs
Participation in Social welfare – Related programmes– Recognized association – Activities for social awareness – Programme by Government and NGOs – Benefits of social service – Balancing the family and social life.
Practical: In campus, off campus projects.
GENERAL PRACTICAL 14 Hrs
Ashtanga Yoga: Pathanjali maharishi & Yoga – Involvement – Rules of Asanas -Suryanamaskara (12 Steps)- Meditation.
Standing : Pada Hastasana, Ardha Cakrasana, Trikonasana, Virukchsana (Eka Padaasana)
Sitting : Padmasana, Vakrasana, Ustrasana, Paschimatanasana.
Prone : Uthanapathasana, Sarvangasana, Halasana, Cakrasana,
Supine : Salabhasana, Bhujangasana, Dhanurasana, Navukasana.
Theory: 16 Hrs Practical: 14 Hrs Total Hours: 30
References:
HYPERLINK "http://www.flipkart.com/author/steven"Steven , HYPERLINK "http://www.flipkart.com/author/weinberg"Weinberg, “The First Three Minutes”, A Modern View of the Origin of the Universe (English), Perseus books group, 1977.
Vethathiri’s Maharishi’s, “Vethathirian Principles of Life”, The World Community Service Centre, Vethathiri Publications, 2003.
Vethathiri’s Maharishi’s, “Karma Yoga: The Holistic Unity”, The World Community Service Centre, Vethathiri Publications, 1994.
Vethathiri’s Maharishi’s, “Prosperity of India”, The World Community Service Centre, Vethathiri Publications, 1983.
Swami Vivekananda, “The Cultural Heritage of India”, First Edition, Ramakirshna Mission Institute of Culture, 1937.
Vivekananda Kendra Prakashan Trust, “YOGA”, Vivekanandha Kendra PrakashanTrust, Chennai, 1977.










SEMESTER IV




















LTPC3024 U14MAT402 SIGNALS AND SYSTEMS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Apply laws of Physics to model simple real life systems to predict its dynamic
behavior.
CO2: Use Fourier analysis to identify the frequency characteristics of signals of interest.
CO3: Use time domain and frequency domain methods to understand the inherent behavior of
LTI systems.
CO4: Take up advanced courses on system dynamics, digital signal processing and design of
feedback control systems.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSSCO2MMCO3SMMCO4SSMS
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. Lab Exercise
5.End Semester ExamCourse End Survey 

REPRESENTATION OF SIGNALS AND SYSTEMS  9HrsIntroduction to systems, signals and their interaction.
Continuous time and discrete time signals, periodic and aperiodic signals, energy and power signals.
Representation of simple systems with examples. Linear and nonlinear systems, Systems with and without memory, Time varying and time- invariant systems.
DYNAMIC SYSTEM MODELING & SIMULATION 
9 HrsLumped element modeling - Laws of Physics applied to Simple Mechanical Systems and RLC Electrical circuits.
System State - State variables and forms of state equations. Matrix representation of state equations for linear dynamic systems – Free response and forced response.
Time response from general system models through numerical integration. Use of Continuous System Simulation Tools (MATLAB).PERIODIC SIGNALS AND FOURIER SERIES  9 HrsObtaining trigonometric Fourier series – Exponential Fourier Series –Fourier Spectra – Parseval’s Theorem- Linearity and time-shifting properties of Fourier Series.
FOURIER TRANSFORMS FOR APERIODIC SIGNALS 9 HrsFourier Transform(FT) pair and equations relating them – Magnitude and phase spectra from Fourier Transforms – Linearity, time scaling , time shifting, time differentiation and integration properties of FTs - Parseval’s Energy Theorem – Existence condition for FT.
ANALYSIS OF LINEAR TIME INVARIANT (LTI) SYSTEMS USING TRANSFORMS  9 HrsImpulse Response of LTI system- Convolution integral – FT for convolved time signals - Transfer function of LTI system using Fourier Transform – System gain and phase responses in sinusoidal steady state – Bode plots – Stability of Linear Systems - Applications in Communication and Control – Analog filtersTheory: 45 Hrs Practical: 15 Hrs Total Hours: 60 
References:

Mrinal Mandal and Amrit Asif, “Continuous and Discrete Time Signals and Systems”, Cambridge University Press, 2007.
P.D. Cha, J.J. Rosenberg & C.L. Dym, “Fundamentals of Modeling and Analyzing Engineering Systems”, Cambridge University Press, 2000.
W.Y. Yang et. al., “Signals and Systems with MATLAB”, Springer, 2009.
A.V. Oppenheim & A.S. Willsky, “Signals & Systems”, PHI Learning Pvt.Ltd.,2011.
V. Krishnaveni & A. Rajeshwari, “Signals & Systems”,Wiley – India, 2012.















LTPC3024U14CST401 DESIGN AND ANALYSIS OF ALGORITHMS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the fundamentals of analysis of algorithm.
CO2: Explain mathematical analysis for recursive and non-recursive algorithms.
CO3: Comparing algorithms through estimating their best-case, worst-case and average-case
behavior.
CO4: Explain various algorithms design techniques.
CO5: Develop algorithms for problems using different design techniques.

Pre-requisites:
1. U14CST301- Data Structures and Algorithms
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3MCO4MCO5MCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey

INTRODUCTION  8+3 HrsNotion of Algorithm - Fundamentals of Algorithmic Problem Solving - Important Problem Types – Fundamentals of the Analysis of Algorithm Efficiency: Analysis Framework - Asymptotic Notations and Basic Efficiency Classes.
ALGORITHM ANALYSIS 
9+3 HrsMathematical Analysis of Non-recursive Algorithms - Mathematical Analysis of Recursive Algorithms - Fibonacci Numbers- Empirical Analysis of Algorithms - Algorithm Visualization. BRUTE FORCE, DIVIDE AND CONQUER TECHNIQUES 10+3 HrsBrute Force Method: Selection Sort and Bubble Sort - Sequential Search and Brute-Force string matching-closest pair problem-Exhaustive search.
Divide and Conquer Method: Merge Sort - Multiplication of large integers-Strassen’s Matrix Multiplication- closest pair problem and Convex Hull Problem
Decrease and Conquer Method: Josephus Problem.
Transform and Conquer Method: Presorting DYNAMIC PROGRAMMING AND GREEDY TECHNIQUES 10+3 HrsDynamic Programming: Warshall’s and Floyd’s Algorithm - Optimal Binary Search Trees- 0/1 knapsack using dynamic programming – Travelling salesperson problem
Greedy Technique: General Method – Knapsack problem – Job sequencing with deadlines -Optimal storage on tapes –Huffman trees.BACKTRACKING, BRANCH AND BOUND TECHNIQUES 8+3 HrsBacktracking: N-Queen’s Problem - Hamiltonian Circuit Problem - Subset-Sum Problem-Graph Colouring.
Branch and Bound: Assignment Problem - Knapsack Problem - Traveling Salesman Problem.Theory: 45 Hrs Practical: 15 Hrs Total Hours: 60 
References:Anany Levitin, “Introduction to the Design and Analysis of Algorithms”, Third Edition, Pearson Education Asia, 2008.
Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, “Fundamentals of Computer Algorithms”, Second Edition, Universities Press, Hyderabad, 2008.
Thomas H Cormen, Charles E Leiserson, Ronald L Rivest and Clifford Stein, “Introduction to Algorithms”, Second Edition, Prentice Hall of India,New Delhi, 2007.
Sara Baase and Allen Van Gelder, “Computer Algorithms - Introduction to Design and Analysis”, Pearson Education Asia, 2003.
A.V.Aho, J.E. Hopcroft and J.D.Ullman, “The Design and Analysis of Computer Algorithms”, Pearson Education Asia, 2003.

Other References:
HYPERLINK "http://www.oopweb.com/Algorithms/Files/Algorithms.html"http://www.oopweb.com/Algorithms/Files/Algorithms.html
HYPERLINK "http://www.learnalgorithms.in/"http://www.learnalgorithms.in/
HYPERLINK "http://freevideolectures.com/Course/2279/Data-Structures-And-Algorithms"http://freevideolectures.com/Course/2279/Data-Structures-And-Algorithms
http://ocw.mit.edu/courses






LTPC3003U14CST402 OPERATING SYSTEMS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Illustrate the operating system concepts and its functionalities.
CO2: Apply various CPU scheduling algorithms for problems.
CO3: Outline the needs and applications of process synchronization.
CO4: Identify the issues in deadlock and memory management.
CO5: Illustrate various file and disk management strategies.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2SSSCO3SCO4MMCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey INTRODUCTION AND PROCESS CONCEPT  9 HrsOperating System Structure – Operating System Operations – Process Management – Memory Management – Storage Management – Protection and Security – Distributed Systems – Computing Environments – System Structures: Operating System Services – User Operating System Interface – System Calls – Types of System Calls – System Programs. Process Scheduling – Operations on Processes – Inter-process Communication.

MULTITHREADED PROGRAMMING AND PROCESS SCHEDULING 9 HrsOverview – Multithreading Models – Threading Issues
Basic Concepts of process scheduling – Scheduling Criteria – Scheduling Algorithms – Multiple-Processor Scheduling – Synchronization – The Critical-Section Problem – Peterson’s Solution – Synchronization Hardware – Semaphores – Classic problems of Synchronization – Monitors. DEADLOCK AND MEMORY MANAGEMENT STRATEGIES  9 HrsSystem Model – Deadlock Characterization – Methods for Handling Deadlock – Deadlock Prevention – Deadlock Avoidance – Deadlock Detection – Recovery from Deadlock.
Swapping – Contiguous Memory Allocation – Paging – Structure of the Page Table – Segmentation.
VIRTUAL MEMORY MANAGEMENT AND FILE SYSTEM  9 Hrs
Demand Paging – Copy on Write – Page Replacement – Allocation of Frames – Thrashing
File Concept – Access Methods – Directory Structure – File Sharing – Protection.
IMPLEMENTING FILE SYSTEMS AND SECONDARY STORAGE STRUCTURE 9 HrsFile System Structure – File System Implementation – Directory Implementation – Allocation Methods – Free-space Management.
Disk Structure – Disk Scheduling – Disk Management – Swap-Space Management.
Case Study: Linux OS, Android OS.Theory:45 Hrs Total Hours: 45 References:
Abraham Silberschatz, Peter Baer Galvin and Greg Gagne, “Operating System Principles”, John Wiley & Sons (Asia) Pvt. Ltd, Ninth Edition, 2013.
Andrew S. Tanenbaum, “Modern Operating Systems”, Third Edition Prentice Hall of India Pvt. Ltd, 2010 (Case Study Topic).
Harvey M. Deitel, “Operating Systems”, Pearson Education Pvt. Ltd, Second Edition, 2002.
William Stallings, “Operating System”, Pearson Education, Sixth Edition, 2012.
Christopher Negus, Christine Bresnahan, “Linux Bible”, Wiley Pvt Ltd, Eighth Edition , 2013.
Other References:
1. HYPERLINK "http://nptel.ac.in/courses/Webcourse-contents/IISc"http://nptel.ac.in/courses/Webcourse-contents/IIScBANG/Operating%20Systems/New_index1.html
2. www.thenewboston.com (for Android Application development)











LTPC3104 U14CST403 MICROPROCESSORS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Identify the basic functions of a microprocessor and explain the instruction sets of 8085
and 8086 microprocessors.
CO2: Make use of the instruction set of 8085 microprocessor and develop assembly code to
solve problems.
CO3: Illustrate the use of various general purpose interfacing devices.
CO4: Develop skills to write programs using 8086 processor development tools.
CO5: Compare the architecture of 8085, 8086 and 8051 microcontroller.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SMMCO3SMCO4SMCO5S
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey


THE 8085 MICROPROCESSOR 
9+3 HrsIntroduction to 8085 - Microprocessor architecture and its operations –8085 MPU - Example of a 8085 based Microcomputer - Instruction set- Addressing modes- Timing diagram of 8085 (Opcode fetch, Memory Read/Write, I/O Read/Write).PROGRAMMING THE 8085 9+3 HrsProgramming techniques –Counters – Time Delays – Stack and Subroutines – Code conversion – BCD Arithmetic - Interrupts- Memory mapped I/O and I/O mapped I/O for 8085. GENERAL PURPOSE INTERFACING DEVICES  9+3 Hrs8255A Programmable Peripheral Interface - IC 8251A Serial Communication Interface – 8253 Programmable Interval Timer IC - IC 8279 Programmable Keyboard /Display Interface – 8259A Programmable Interrupt Controller.8086 MICROPROCESSOR  9+3 HrsIntel 8086 microprocessor - Architecture - Instruction set - Addressing modes – Assembly language programming – Procedures - Interrupts and interrupt service routines- Basic 8086/8088 Configurations: Minimum Mode and Maximum Mode. 8051 MICROCONTROLLER  9+3 HrsArchitecture of 8051 Microcontroller – signals – I/O ports – memory – counters and timers – serial data I/O – interrupts – Applications.
Theory: 45 Hrs Tutorial: 15 Hrs Total Hours: 60 
References:
Ramesh S.Gaonkar, “Microprocessor - Architecture, Programming and Applications with the 8085”, Penram International Publishing Private Limited, Sixth Edition, 2014.
Yn-cheng Liu,Glenn A.Gibson, “Microcomputer systems: The 8086 / 8088 Family architecture, Programming and Design”, Second Edition, Prentice Hall of India , 2006.
Kenneth J.Ayala, “The 8051 microcontroller Architecture, Programming and
Applications”, Third Edition, Penram international 2004.
Douglas V.Hall, “Microprocessors and Interfacing: Programming and Hardware”, TMH, Revised Second Edition, 2006.
Krishna Kant, “Microprocessors and Microcontrollers: Architecture, Programming and System Design 8085, 8086, 8051, 8096”, Prentice Hall of India Pvt. Ltd., 2012.





















LTPC3024U14CST404 DATABASE MANAGEMENT SYSTEMS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Define the fundamental elements of database management systems.
CO2: Explain the basic concepts of relational data model and entity-relationship model.
CO3: Outline relational database design, relational algebra and database language SQL.
CO4: Explain the basic concepts of query processing, transaction management and file storage.
CO5: Develop a database for a given problem.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3MSCO4MCO5S
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam
5. Mini ProjectCourse End Survey
DATABASE SYSTEM ARCHITECTURE 10+3 HrsPurpose of Database Systems-Views of Data- Database Languages-Data Storage and Querying-Transaction Management-Database Architecture-Database Users and Administrators
Relational Databases: Structure of Relational Databases-Database Schema-Keys-Schema Diagram
Formal Relational Query Languages: Relational Algebra –Tuple and Domain Relational Calculus.

DATABASE DESIGN AND E-R MODEL

10+3 HrsOverview-Entity Relationship Model-Constraints-Removing Redundant Attributes in Entity Sets-E-R Diagrams.
Introduction to SQL: Overview of SQL Query Languages-SQL Data Definition-Basic Structure Of SQL Queries- Additional Basic Operations-Set Operations-Aggregate Functions-Nested Sub Queries-Join Expressions-Views-Transactions-Integrity Constraints-SQL Data Types and Schemes-Authorization.
Advanced SQL: Accessing SQL from a Programming Languages-Functions and Procedures-Triggers.RELATIONAL DATABASE DESIGN 8+3 Hrs Features of Good Relational Database Design –Informal Guidelines for Relational Schemas- Decomposition using Functional Dependencies-Functional Dependency Theory-First, Second, Third and Boyce-Codd Normal Forms.
Data Storage: Overview of Physical Storage Media-RAID-File Organization-Organization of Records in Files-Data Dictionary Storage. DATA INDEXING AND HASHING 8+3 HrsBasic Concepts-Ordered Indices-B+ Tree Index Files-Multiple Key Access-Static and Dynamic Hashing.
Query Processing: Overview-Measures of Query Cost-Selection, Sorting and Join Operations-Other Operations-Evaluations of Expressions. TRANSACTION MANAGEMENT 9+3 HrsTransaction concept- Transaction model- Transaction Atomicity, Durability and Isolation-Serializability.
Concurrency Control: Lock based protocols-Time stamped based protocols-Deadlock handling.
Recovery System: Failure classification-Storage- Log based recovery-Shadow paging.Theory: 45 Hrs Practical: 15 Hrs Total Hours: 60 










References:

Abraham Silberschatz, Henry Korth, and S. Sudarshan, “Database System Concepts”, Sixth Edition, McGraw-Hill.2011.
R. Elmasri and S. Navathe, “Fundamentals of Database Systems”, Sixth Edition, Pearson Education, 2011.
Thomas M. Connolly and Carolyn E. Begg, “Database Systems - A Practical Approach to Design, Implementation and Management”, Fifth edition, Pearson Education, 2010.
C.J.Date, A.Kannan and S.Swamynathan, “An Introduction to Database Systems”, Eighth Edition, Pearson Education, 2006.

Other References:
http://ocw.mit.edu/courses
http://www.db-book.com

































LTPC3104U14CST405 THEORY OF COMPUTATION

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain automata theory as the basis of all computer science languages design.
CO2: Classify different types of grammars.
CO3: Build grammars for a given language and vice versa.
CO4: Develop Finite Automata, Push Down Automata and Turing machines.
CO5: Classify decidable and undecidable problems, solvable and unsolvable problems.

Pre-requisites:
U14CST301 – Data Structures and Algorithms

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3SCO4SMCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey

AUTOMATA  8+3 HrsBasic Machines Finite Automata (FA) - Deterministic Finite Automata (DFA) - Non-deterministic Finite Automata (NFA) - Finite Automata with Epsilon transitions.REGULAR EXPRESSIONS AND LANGUAGES  9+3 HrsFinite State Automata and Regular Expressions – Converting regular expression to Finite Automata – Subset construction – Epsilon Closure – NFA to DFA - Applications of finite automata - Proving languages not to be regular -Equivalence and minimization of Automata -Decision algorithms.
CONTEXT-FREE GRAMMAR AND LANGUAGES  10+3 HrsContext-Free Grammar (CFG) - Parse Trees - Ambiguity in grammars and languages - Definition of the Pushdown automata - Languages of a Pushdown Automata - Equivalence of Pushdown automata and CFG, Deterministic Pushdown Automata. Properties of context free languages - Normal forms for CFG – Chomsky Normal Form (CNF) – Greibach Normal Form (GNF)- Pumping Lemma for Context Free Language (CFL) - Closure Properties of CFL. TURING MACHINES  9+3 HrsDefinitions of Turing machines – Models – Computable languages and functions –Techniques for Turing machine construction – Multi head and Multi tape Turing Machines - The Halting problem – Partial Solvability – Problems about Turing machine- Chomsky hierarchy of languages.UNSOLVABLE PROBLEMS AND COMPUTABLE FUNCTIONS 9+3 HrsUnsolvable Problems and Computable Functions – Primitive recursive functions – Recursive and recursively enumerable languages – Universal Turing machine.
Measuring and classifying complexity: Tractable and Intractable problems- Tractable and possibly intractable problems- P and NP completeness - Polynomial time reductions. Theory: 45 Hrs Tutorial: 15 Hrs Total Hours: 60 
References:
J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Third Edition, Pearson Education, 2011.
John C.Martin, “Introduction to Languages and the Theory of Computation”, Third Edition, Tata McGraw Hill, 2007.
H.R.Lewis and C.H.Papadimitriou, “Elements of The theory of Computation”, Second Edition, Pearson Education/PHI, 2003.
Micheal Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 1997.
Kavi Mahesh, “Theory of Computation, A Problem-solving Approach” Wiley India Pvt, Ltd, 2012.














LTPC0031U14CSP401 JAVA PROGRAMMING LABORATORY

Course Outcomes:

After successful completion of this course, the students should be able to
CO1: Identify classes, objects, members of a class and the relationships among them for a
specific problem.
CO2: Develop programs using appropriate packages for Inter –thread Communication and
Synchronization.
CO3: Develop GUI applications to handle events.
CO4: Develop client server based applications.
CO5: Design, develop, test and debug Java programs using object-oriented principles in
conjunction with development tools including integrated development environments.

U14CSP302 Object Oriented Programming Laboratory
Pre-requisites:


CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMWCO2MMCO3MMWCO4MMCO5MMMM
Course Assessment methods:
DirectIndirect1. Model Exams
2. End Semester Exam
3.Viva Voce
Course End Survey











List of experimentsSimple Programs in java using classes and methods
Programs for Method Overloading and Method Overriding
Use the concept of Packages and Interfaces
Program for User Defined Exception Handling
Program using inbuilt methods of String class.
Thread Creation( 2 experiments)
Using Thread Class and Runnable Interface
Inter Thread Communication
Program using Input streams and Output streams
Programs using JDBC for developing real time applications (2 experiments)
Event handling in Swing ( 2 experiments)
Usage of at least four different components in swing and different layouts
Experiments beyond the syllabus should be conducted.

Total Hours: 24































LTPC0031U14CSP402 MICROPROCESSORS LAB

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Make use of the microprocessor trainer kit to execute 8085 programs.
CO2: Develop assembly language program for 8085to solve simple programs.
CO3: Make use of interfacing devices for a specified application.
CO4: Develop simple assembly language program for 8086.
CO5: Develop assembly language program for 8086 using BIOS/DOS Calls.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SMCO3SMWCO4SMCO5SS
Course Assessment methods:
DirectIndirect1. Model Exams
2. End Semester Exam
3.Viva VoceCourse End Survey

List of experiments

Programming with 8085
Programs using loops.
Programs using counting.
Arranging the set of numbers in ascending order.
Code conversion - Binary to BCD and BCD to Binary.
Interfacing 8255.
Interfacing 8279.
Stepper Motor Controller.
Mini Project


Programming with 8086

Programs for String Processing.
Keyboard and Screen Processing using BIOS/DOS Calls.

References:
8086 Technical manual
HYPERLINK "http://8085projects.info/"http://8085projects.info/
HYPERLINK "http://www.hobbyprojects.com"www.hobbyprojects.com

Experiments beyond the syllabus should be conducted.


Total Hours: 24































LTPC0031U14CSP403 OPERATING SYSTEMS LABORATORY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Demonstrate Linux commands.
CO2: Implement various commands using shell programming.
CO3: Implement various CPU scheduling algorithms.
CO4: Implement various disk scheduling algorithms.
CO5: Implement memory management techniques.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2MMCO3MMCO4MMCO5WW
Course Assessment methods:
DirectIndirect1. Model Exams
2. End Semester Exam
3.Viva VoceCourse End SurveyList of Experiments

Working with UNIX commands.
Shell script programs.
Implement the following CPU scheduling algorithms.
FCFS b) Non-Preemptive SJF c) Round Robin
Parent-Child simulation program.
Implement Bankers Algorithm for Dead Lock Avoidance.
Implementation of First bit, Best fit, Worst fit memory allocation methods
Implement Paging Technique.
Implementation of First in First out and Least Recently Used page replacement algorithms.
Implement indexed file allocation strategy.
Implement Disk scheduling algorithms.
11. Study of Linux OS, Android OS.
Experiments beyond the syllabus should be conducted.
Total Hours: 24


LTPC1011U14GHP401 NATIONAL AND GLOBAL VALUES

Course Outcomes:
CO1: Act as a good and responsible citizen.
CO2: Conserve and protect eco cycle.
CO3: Voluntarily work with global welfare organization and provide solution for global peace.
CO4: Invent his Technical design by considering humanity and nature

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSMCO2SCO3WMMMCO4SSS
Course Assessment methods:
DirectIndirectContinuous assessment
End Semester Exam1.Attitude
2.Behavior

ROLE OF A RESPONSIBLE CITIZEN 4 Hrs
Citizen - its significance–National and Global perspectives.
Practical: Group discussion on National and Global values.

GREATNESS OF INDIAN CULTURE 2 Hrs
Emerging India – past and present, about Culture, Morality and spirituality– Beauty of Unity in diversity - Impact of western culture in India and Indian culture over other countries.
Practical: Demonstration and impact measurements of simple and good actions.

GLOBAL WELFARE ORGANISATIONS 2 Hrs
Education – Health – Nature – Peace
Practical: Organizing an event linking with one of the Organizations In campus /off campus.

PRESERVING NATURE 2 Hrs
Appreciating the flora and fauna on Earth - Importance ofEcological balance – Conservation.
Practical: Trekking, field visit.

GLOBAL PEACE 4 Hrs
One World and One Humanity - Global Peace.
Global personalities: Thiruvalluvar, Vallalar, Vivekanadar, Mahatma Gandhi,Vethathiri Maharishi – Plans for world peace.
Practical: Group discussion on individual plans for world peace.

GENERAL PRACTICAL 16 Hrs
Simplified physical Exercise – Kayakalpa practice (Follow up practice) – Meditatyion -
Theory & Practice
Pranayama : Bhastrika, Kapala Bhati, Nadi suddhi, Sikari, Sitali.
Mudhra : Chin Mudhra, Vayu Mudhra, Shunya Mudhra, Prithvi Mudhra, Surya Mudhra, Varuna Mudhra, Prana Mudhra, Apana Mudhra, Apana Vayu Mudhra, Linga Mudhra, Adhi Mudhra, Aswini Mudhra.

Theory: 14 Hrs Practical: 16 Hrs Total Hours: 30

References:
HYPERLINK "http://www.amazon.com/Drunvalo-Melchizedek/e/B001JRZJ6S/ref=dp_byline_cont_book_1"Drunvalo Melchizedek, “The Ancient Secret of the Flower of Life”, Vol. 1, Light Technology Publishing; First Edition, 1999. 
Dr.M. B. Gurusamy, “Globalisation – Gandhian Approach” Kumarappa Research Institution, 2001.
Vethathiri’s Maharishi’s, “Karma Yoga: The Holistic Unity” The World Community Service Centre, Vethathiri Publications, 1994.
Vethathiri’s Maharishi’s, “World peace” The World Community Service Centre, Vethathiri Publications, 1957.
Vethathiri’s Maharishi’s, “Atomic Poison” The World Community Service Centre, Vethathiri Publications, 1983.
Vethathiri’s Maharishi’s, “The World Order of Holistic Unity”, The World Community Service Centre, Vethathiri Publications, 2003.
Swami Vivekananda, “What Religion is” 41th edition, The Ramakirshna Mission Institute of Culture, 2009.













SEMESTER V


















LTPC3104
U14MAT506 PROBABILITY AND QUEUEING THEORY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Analyze random or unpredictable experiments and investigate important features of
random experiments
CO2: Construct probabilistic models for observed phenomena through distributions which
play an important role in many engineering applications
CO3: Associate random variables by designing joint distributions and correlate the random
variables.
CO4: Know about random processes, in particular about Markov chains which have
applications in engineering.
CO5: Identify the queueing model in the given system, find the performance measures and
analyse the result

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSSSCO2SMMCO3SSSCO4SSMSCO5SSSCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. Lab Exercise
5. End Semester ExamCourse End Survey 

PROBABILITY  9+3 HrsProbability – Axioms of Probability – Addition Theorem – Conditional Probability - Multiplication Theorem – Posterior Probability – Baye’s TheoremRANDOM VARIABLES & JOINT DISTRIBUTIONS 9+3 HrsDiscrete and continuous random variables – Moments – Moment generating functions and their properties – Binomial – Poisson – Exponential and Normal distributions.
Marginal and conditional distributions – Correlation and Regression
RANDOM PROCESSES AND MARKOV CHAINS  9+3 HrsClassification – Stationary process – Markov process – Markov chains – Transition probabilities – Limiting distributions – Poisson process.






MARKOVIAN QUEUES 9+3 HrsMarkovian models – Birth and death queueing models – Steady state results – Single and Multiple server Queueing models – Queues with finite waiting rooms – Finite source models – Little’s formula. (Derivations excluded)
NON–MARKOVIAN QUEUES AND QUEUEING NETWORKS 9+3 HrsM/G/1 Queue – Pollaczek – Khintchine formula (Derivation excluded) – Series queues – Open and Closed NetworksTheory: 45 Hrs Tutorial: 15 Hrs Total Hours: 60 
References:
O.C. Ibe, “Fundamentals of Applied Probability and Random Processes”, Elsevier, First Indian Reprint, 2009.
D. Gross and C.M. Harris, “Fundamentals of Queueing Theory”, Wiley Student Edition, 2004.
A.O. Allen, “Probability, Statistics and Queueing Theory with Computer Applications”, Elsevier, Second Edition, 2005.
H.A. Taha, “Operations Research”, Pearson Education, Asia, Eighth Edition, 2007.
K.S. Trivedi, “Probability and Statistics with Reliability, Queueing and Computer Science Applications”, John Wiley and Sons, Second Edition, 2002.














LTPC3104U14CST501 PRINCIPLES OF COMPILER DESIGN

Course Outcomes:
After successful completion of this course, the students should be able toCO1: Explain various phases of a compiler.
CO2: Design token recognizer using modern tools.
CO3: Design Top-down and Bottom-up parsing Techniques.
CO4: Translate given input to intermediate code.
CO5: Identify various types of optimizations on intermediate code and generate assembly code.
Pre-requisites:
U14CST405- Theory of Computation
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SMCO3SMCO4SCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey
INTRODUCTION AND LEXICAL ANALYSIS 9 + 3 HrsLanguage Processors – The Structure of a Compiler – Applications of Compiler Technology – Programming Language Basics - Lexical Analysis – The Role of the Lexical Analyzer – Input Buffering – Specification of Tokens – Recognition of Tokens – The Lexical-Analyzer Generator - LEX– Finite Automata – From Regular Expression to Automata – Design of a Lexical-Analyzer Generator – Optimization of DFA-Based Pattern Matchers.SYNTAX ANALYSIS  9 + 3 HrsIntroduction – Context-Free Grammars – Writing a Grammar – Top-Down Parsing – Recursive-Descent Parsing and Predictive Parsers - Bottom-up Parsing – Shift-Reduce Parsing and Operator Precedence Parsing - Introduction to LR Parsing: Simple LR – More Powerful LR Parsers – Canonical LR and LALR Parsers.INTERMEDIATE CODE GENERATION  9 + 3 HrsVariants of Syntax Trees – Three-Address Code – Types and Declarations – Translation of Expressions – Type Checking – Control Flow – Backpatching – Switch-Statements – Intermediate Code for Procedures.CODE GENERATION 9 + 3 HrsIssues in the Design of a Code Generator – The Target Language – Addresses in the Target Code – Basic Blocks and Flow Graphs – Optimization of Basic Blocks – A Simple Code Generator – Peephole Optimization.CODE OPTIMIZATION AND RUN TIME ENVIRONMENT 9 + 3 HrsThe Principal Sources of Optimization – Introduction of Data-Flow Analysis – Loops in Flow Graphs – Run time Environments – Storage Organization – Stack Allocation of Space – Heap Management.Theory: 45 Hrs Tutorial: 15 Hrs Total Hours: 60 
References:
Alfred V. Aho et al “Compilers Principles, Techniques and Tools”, Second Edition , Pearson Education, 2007.
Allen I. Holub, “Compiler Design in C”, Prentice Hall of India, 2003.
Fischer C.N. and LeBlanc R.J. “Crafting a Compiler with C”, Benjamin Cummings, 2003.
Bennet J.P. “Introduction to Compiler Techniques”, Second Edition, Tata McGraw-Hill, 2003.
HenkAlblas and Albert Nymeyer, “Practice and Principles of Compiler Building with C”, PHI, 2001.
Kenneth C. Louden, “Compiler Construction: Principles and Practice”, Thompson Learning, 2003.



















LTPC3003
U14CST502 COMPUTER NETWORKS

Course Outcomes:

After successful completion of this course, the students should be able toCO1: Explain data communication system, components and the purpose of layered architecture.
CO2: Illustrate the functionality of each layer of OSI and TCP/IP reference model.
CO3: Explain the data link layer and network layer protocols.
CO4: Outline the functions of transport layer protocols.
CO5: Summarize application layer protocols. Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2S
CO3MWWCO4MWWCO5MWW
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey



DATA COMMUNICATIONS  6 HrsData Communication- Networks-The OSI Model- Layers in the OSI Model – TCP/IP Protocol Suite – Addressing – Transmission Media.DATA LINK LAYER  9 HrsLink and Medium Access protocols – Framing – Error Detection – Reliable Transmission – IEEE 802 Standards – Ethernet – Token Rings – Wireless LANs.NETWORK LAYER  10 HrsCircuit Switching – Packet Switching – Switching and Forwarding – Bridges and LAN Switches – Cell Switching – Internetworking – Routing Techniques: Distance vector (RIP) – Link state (OSPF) – Subnetting – CIDR- BGP - IPv6.TRANSPORT LAYER  10 HrsUDP – TCP – Congestion Control and Resource Allocation –TCP Congestion Control – Congestion Avoidance Mechanisms – Quality of Service- Integrated Services – Differentiated Services.APPLICATION LAYER  10 HrsDomain Name System – Electronic Mail – File Transfer- WWW and HTTP-Network Management System – Simple Network Management Protocol.Theory: 45 Hrs Total Hours: 45
References:
Larry L. Peterson, Bruce S. Davie, “Computer Networks: A Systems Approach”, Fifth Edition, Morgan Kaufmann Publishers Inc., 2011.
William Stallings, “Data and Computer Communications”, Eighth Edition, Pearson Education, 2011.
James F. Kurose, Keith W. Ross, “Computer Networking, A Top-Down Approach Featuring the Internet”, Third Edition, Pearson Education, 2006.
Nader F. Mir, “Computer and Communication Networks”, First Edition, Pearson Education, 2007.
Ying-Dar Lin, Ren-Hung Hwang and Fred Baker, “Computer Networks: An Open Source Approach “, McGraw Hill Publisher, 2011.
Behrouz A. Forouzan, “Data communication and Networking”, Tata McGraw-Hill, 2004.

Other Reference:
HYPERLINK "http://nptel.ac.in/courses/106105081/"http://nptel.ac.in/courses/106105081
















LTPC3003U14CST503 XML AND WEB SERVICES

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the concept of service oriented architecture
CO2: Develop a simple XML application.
CO3: Explain the design principles and application of SOAP based Web Services.
CO4: Explain the key technologies in web services.
CO5: Explain the security issues in XML.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MMMCO3MMMCO4MCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam
5. Mini ProjectCourse End Survey

INTRODUCTION  9 HrsRole of XML – XML and the Web – XML Language Basics – SOAP – Web Services – Revolutions of XML – Service Oriented Architecture (SOA).
XML TECHNOLOGY
9 HrsXML – Name Spaces – Structuring with Schemas and DTD – Presentation Techniques – Transformation. SOAP 9 HrsOverview of SOAP – HTTP – XML - RPC – SOAP: Protocol – Message Structure – Intermediaries – Actors – Design Patterns and Faults – SOAP with Attachments.WEB SERVICES 9 HrsOverview – Architecture – Key Technologies - UDDI – WSDL – ebXML – SOAP and Web Services in E-Com – Overview of .NET and J2EE.XML Security 9 Hrs Security Overview – Canonicalization – XML Security Framework – XML Encryption – XML Digital Signature – XKMS Structure – Guidelines for Signing XML Documents – XML in Practice.Theory: 45 Hrs Total Hours: 45 References:
Frank. P. Coyle, “XML, Web Services and the Data Revolution”, Pearson Education, 2002.
HYPERLINK "https://www.google.co.in/search?sa=X&hl=en&biw=1366&bih=608&tbm=bks&q=inauthor:%22David+Hunter%22&ei=ekgrVY_gIsWouwSBmYGoCg&ved=0CC0Q9AgwAQ"David Hunter,  HYPERLINK "https://www.google.co.in/search?sa=X&hl=en&biw=1366&bih=608&tbm=bks&tbm=bks&q=inauthor:%22Jeff+Rafter%22&ei=ekgrVY_gIsWouwSBmYGoCg&ved=0CC4Q9AgwAQ"Jeff Rafter, Joe Fawcett, Eric Van der Vlist, Danny Ayers, Jon Duckett, Andrew Watt, Linda McKinnon, ”Begining XML” , Fourth Edition, Wrox publication.

Other References:
HYPERLINK "http://www.w3schools.com/xml/"http://www.w3schools.com


























LTPC3104U14ECT511 DIGITAL SIGNAL PROCESSING

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Outline the characteristics of discrete-time signals and discrete systems CO2: Analyze signal / system properties using mathematical tools CO3: Apply and develop algorithms for digital systems CO4: Illustrate efficient computation of DFT CO5: Explain the advanced features and architecture of generic P-DSP Pre-requisites:
U14MAT402 – Signals and Systems

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2MMWCO3SMMWCO4SWCO5W
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey
DISCRETE TIME SIGNALS AND SYSTEMS 12HoursRepresentation of a CT signal by samples – Sampling theorem – Reconstruction of a signal from its samples – Aliasing – DT Signals – Impulse, Step, Pulse, Sine, Exponential – Properties of DT signals - Transformation of independent variable – Shifting, scaling, folding - Discrete Time LTI systems – Properties – Impulse response – Convolution sum – Properties of ConvolutionZ-TRANSFORM AND SYSTEM ANALYSIS12HoursDTFT – Properties - Z transform – Forward Transform - Inverse Transform using Partial Fractions - Properties – Pole-Zero plot – Difference Equations - Transfer function - Analysis of Discrete Time systems using DTFT and Z Transform.



DISCRETE FOURIER TRANSFORM



12HoursIntroduction to DFT– Properties of DFT – Efficient computation of DFT – FFT algorithms – Introduction to Radix-n algorithms - Radix-2 FFT – Decimation-in-Time and Decimation–in-Frequency algorithms – Butterfly diagram.
DESIGN OF DIGITAL FILTERS
12HoursFIR filter design: Linear phase characteristics - Windowing Technique –Rectangular, Hamming, Hanning, Blackmann windows – IIR filter design: Analog filter design - Butterworth and Chebyshev approximations – Impulse invariance and Bilinear transformations - FIR and IIR filter structures – Direct form I and II - cascade and parallel forms – Finite Precision effects.
ADVANCED TOPICS AND PROGRAMMABLE DSP CHIPS 
12HoursConcepts of multi-rate signal processing – Decimation and interpolation by integer factor – Sampling rate conversion – Introduction to DSP architecture - Von Neumann, Harvard, Modified Harvard architectures - MAC unit – Multiple ALUs Modified Bus structures and memory access schemes in P-DSP – Multiple access memory – Multi-ported memory – VLIW architecture - Pipelining – Special addressing modes.Theory: 45Hrs Tutorial: 15Hr Total Hours: 60 Hrs References:
Mrinal Mandel and Amir Asif, “Continuous and Discrete Time Signals and Systems”, Cambridge International Student Edition, Cambridge University Press, 2007.
John G.Proakis and Dimitris G.Manolakis, “Digital Signal Processing, Principles, Algorithms and Applications”, PHI, Third Edition. 2000.
B. Venkataramani, M. Bhaskar, “Digital Signal Processors, Architecture, Programming and Applications”, Tata McGraw Hill, New Delhi, 2003. (Unit V)
Johny R.Johnson, “Introduction to Digital Signal Processing”, PHI, 2009.
Won Y. Yang et. Al., “Signals and Systems with MATLAB”, Springer International Edition, 2009
Steven W. Smith, “The Scientists and Engineer’s Guide to Digital Signal Processing”, California Technical Publishing, 1997.
James H. McClellan, Ronald W. Schafer, Mark A. Yoder, “Signal Processing First”, Second Edition.







\





U14CSP501 COMPUTER NETWORKS LABORATORY
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Develop knowledge to implement client server applications.
CO2: Develop skills in UNIX socket programming.
LTPC0031CO3: Develop skills to use simulation tools.
CO4: Analyze the performance of network protocols.
CO5: Analyze the network traffic.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMMCO2SMCO3SMCO4MMCO5MM
Course Assessment methods:
DirectIndirectModel Exams
End Semester Exam
Viva Voce Course End Survey

List of Experiments:
Demonstrate various network commands.
Develop client server based TCP applications using UNIX socket programming functions.
Develop client server based UDP applications using UNIX socket programming functions.
Implementation of HTTP/DNS/ARP/RARP protocols.
Implementation of sliding window and CRC protocols.
Implementation of Distance Vector and Link state routing protocols.
Study of network simulation tool - NS2.
Performance analysis of TCP/UDP protocol using simulation tool
Performance analysis of routing protocols using simulation tool.
Analyze the network traffic using Wireshark tool.
Experiments beyond the syllabus should be conducted.
Total Hours: 24







L TPC0031U14CSP502 XML AND WEB SERVICES LABORATORY
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Develop a XML document to store user data.
CO2: Develop a DTD and Schema for a XML document.
CO3: Demonstrate the use of XML document for various web services.
CO4: Develop a web service using SOA concepts.
CO5: Build XML document for various web services.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3MCO4MMCO5M
Course Assessment methods:
DirectIndirect1.Model Lab Exams
2.End semester practical exam
3.Viva Voce Course End Survey








List of experiments (using JAVA)Create an XML document to store an address book.
Create an XML document to store information about books and create the DTD files.
Create an XML schema for the book’s XML document from exercise 2.
Create an XML document to store resumes for a job web site and create the DTD file
Present the book’s XML document using cascading style sheets (CSS).
Write an XSLT program to extract book titles, authors, publications, book rating from the book’s XML document and use formatting.
Use Microsoft DOM to navigate and extract information from the book’s XML document.
Use Microsoft DSO to connect HTML form or VB form to the book’s XML document and display the information.
Create a web service for temperature conversion with appropriate client program.
Create a web service for currency conversion (at five currencies) with appropriate client program.
Experiments beyond the syllabus should be conducted.
Total Hours: 24


















LTPC0031U14CSP503 DATABASE MANAGEMENT SYSTEMS
LABORATORY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Develop database modeling for a problem.
CO2: Design a database using normalization.
CO3: Implement a data base query language.
CO4: Develop GUI using front end tool.
CO5: Develop a connection between front end and database.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2SSMCO3SMCO4MCO5MCourse Assessment methods:
DirectIndirect1. Model Exam
2. Viva voce
3. Mini Project
4. End semester practical examCourse End Survey











List of experiments:

Design and develop a mini project using following concepts.
Database modelling.
Database Design using normalization.
Database implementation using query language.
Triggers in SQL.
Graphical user interface design using front end tool.
Database connectivity.
Sample list of projects:

Hospital management
Railway ticket reservation
Student Mark list processing
Employee pay roll processing
Inventory control

Experiments beyond the syllabus should be conducted.

Total Hours: 24







































SEMESTER VI































LTPC3104U14CST601 ARTIFICIAL INTELLIGENCE

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Describe the modern view of AI as the study of agents that receive percepts from the
environment and perform actions.
CO2: Demonstrate awareness of informed search and exploration methods.
CO3: Explain about AI techniques for knowledge representation, planning and uncertainty
Management.
CO4: Develop knowledge of decision making and learning methods.
CO5: Describe the use of AI to solve English Communication problems.
Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak

COs
Programme Outcomes(POs)


PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12

CO1
S












CO2

S











CO3
S
M











CO4

M











CO5
S
M












Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam
5. Mini ProjectCourse End Survey






INTELLIGENT AGENTS AND SEARCHING METHODS 9+3 HrsDefinitions of AI - Intelligent Agents: Agents and environments - Good behavior – The nature of environments – structure of agents.
Problem solving agents: Formulating problems – searching for solutions – Uninformed search strategies.
Informed search and exploration: Informed search strategies – heuristic functions – local search algorithms.LOGIC 9+3 HrsLogical agents: Knowledge-based agents – The Wumpus world. Logic – Propositional logic: A very simple logic.
First order logic: Representation revisited – Syntax and semantics for first order logic – Using first order logic – Knowledge engineering in first order logic.
Inference in First order logic: propositional versus first order logic – unification and lifting – forward chaining – backward chaining – Resolution.PLANNING AND UNCERTAINTY9+3 HrsPlanning: The planning problem- planning with state-space search-partial order planning- graphs.
Uncertainty: Overview of probability concepts, Representing knowledge in an Uncertain Domain, Semantics of Bayesian Networks, Exact Inference in Bayesian Networks.DECISION MAKING AND LEARNING9+3 HrsMaking Simple Decisions: The basis of Utility theory – Utility and multi-attribute utility functions – decision networks – The value of information – Decision theoretic expert systems.
Learning from Observations: Forms of learning - Inductive learning - Learning decision trees. Knowledge in Learning – Logical formulation of learning – Explanation based learning – Learning using relevant information – Inductive logic programming.
LEARNING AND COMMUNICATION9+3 HrsStatistical Learning Methods: Introduction to neural networks, Perceptrons, Multi-layer feed forward network, Application of ANN.
Reinforcement Learning: Passive reinforcement learning - Active reinforcement learning - Generalization in reinforcement learning.
Communication: Communication as action – Formal grammar for a fragment of English – Syntactic analysis – Augmented grammars – Semantic interpretation – Ambiguity and disambiguation.
Theory: 45 Hrs Tutorial: 15 Hrs Total Hours:60






References:
Stuart Russell, Peter Norvig, “Artificial Intelligence – A Modern Approach”, Third Edition, Pearson Education / Prentice Hall of India, 2009.
Elaine Rich, Kevin Knight, Shivashankar.B.Nair, “Artificial Intelligence”, Tata Mc Graw Hill Publishing Company Limited. Third Edition, 2009.
Nils J. Nilsson, “Artificial Intelligence: A new Synthesis”, Harcourt Asia Pvt. Ltd., 2000.
George F. Luger, “Artificial Intelligence-Structures and Strategies for Complex Problem Solving”, Pearson Education / PHI, 2002.






































LTPC3024 U14CST602 CRYPTOGRAPHY AND NETWORK SECURITY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain security issues and objectives in computer systems and networks.
CO2: Explain the workings of fundamental cryptographic, authentication, network security and
system security algorithms.
CO3: Identify the appropriate cryptography scheme & security mechanism for different
computing environment and information systems.
CO4: Develop security protocols and methods to solve societal security problems.
CO5: Analyze security of network protocols and systems.

Pre-requisites:
U14CST502- Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SWCO2MCO3MMCO4MMMCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey
INTRODUCTION  9+3 HrsComputer Security Concepts- OSI Security Architecture – Security Attacks– Security Services- Security Mechanisms-A model for Network Security – Classical Encryption Techniques –Block Cipher Principles – DES– Strength of DES – Block Cipher Operation – AES – Triple DES.
PUBLIC KEY CRYPTOGRAPHY 
10+3 HrsPseudorandom Number Generators – Introduction to Number Theory – Public Key Cryptography and RSA – Diffie-Hellman Key Exchange – Elliptic Curve Arithmetic and Cryptography - Key Management and Distribution–Symmetric key distribution using symmetric encryption – Symmetric key distribution using asymmetric encryption- Distribution of public keys.AUTHENTICATION AND HASH FUNCTION  9+3 HrsAuthentication Requirements – Authentication Functions – Message Authentication Codes –Hash Functions – Security of Hash Functions and MACs – Secure Hash Algorithm – HMAC Digital Signatures – Digital Signature Standard.NETWORK SECURITY 8+3 HrsAuthentication Applications – Kerberos Version 4 – Electronic Mail Security – PGP – IP Security Overview – VPNs – Intrusion - Detection – Firewall- Design Principles.WIRELESS NETWORK SECURITY 9+3 HrsWireless Local Area Network (WLAN) – Securing WLANs – Countermeasures – The Infamous WEP – Physical Security – Wireless Application Protocol (WAP) – Comparison of the TCP/IP,OSI, and WAP models – WAP Security Architecture – Marginal Security – Wireless Transport Layer Security (WTLS) –Secure Socket Layer – WTLS and WAP.Theory: 45 Hrs Practical: 15 Hrs Total Hours: 60
References:
William Stallings, “Cryptography and Network Security : Principles and Practices”, Fifth Edition, Prentice Hall, 2011.
AtulKahate, “Cryptography and Network Security”, Third Edition, Tata McGraw Hill, 2013.
Randall K.Nichols, PanosC.Lekkas, “Wireless Security- Models, Threats, and Solutions”, McGraw Hill, 2006. (Unit V)
Charles B. Pfleeger and Shari Lawrence Pfleeger, “Security in Computing”, Fourth Edition, Pearson Education, 2011.


















LTPC3003U14CST603 SOFTWARE ENGINEERING

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Outline the features of different lifecycle models.
CO2: Explain the principles involved in gathering and validating software requirements
CO3: Make use of suitable models through analysis of requirements and arrive at an appropriate software design
CO4: Appreciate the quality assurance procedures during software development
CO5: Explain software project management and software maintenance practices

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak

COs
Programme Outcomes(POs)


PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12

CO1
M
M











CO2

S











CO3
M

M










CO4
M












CO5
M
S











Course Assessment methods:Direct
Indirect

1. Internal Tests
2. Assignments
3. Seminar
4. End Semester Exam
Course End Survey



INTRODUCTION TO SOFTWARE ENGINEERING 9 HrsExpanding roles for computers - the place of Software - Software Engineering Discipline - Computer Based Systems - Increasing size and scope of software - Generic vs. Custom-made software products-distinctive characteristics of software products.
Software Development Models: Life cycle - Development process - Life cycle models-Linear Sequential - Evolutionary - Unified models - Agile development approach.
REQUIREMENTS ENGINEERING 9 HrsClassification of Requirements-System Requirements and Software Requirements - Functional and Non-Functional requirements - Priority Categories of Requirements. Requirement Engineering Tasks - Elicitation - Analysis - Specification - Validation and Management.
System Models: Domain Analysis and Modeling - Data Models - Functional Models-structured Analysis Model - Object Oriented Models- Class - State - Use Case Models - Sequence and activity diagrams - Relationship among the Object Oriented Models - Building Object Oriented Analysis Models
SOFTWARE DESIGN AND IMPLEMENTATION 9 HrsArchitectural Design-Decomposition strategy - Partitions and Layers - Structured System Design-Use of Heuristics for Design Refinements - Object-Oriented Design-Handling Concurrency - Management of Global Resources
Detailed Design - User Interface Design-Human Factors - Evolution in HCI styles - HCI Design Issues - User Interface Standards and Guidelines - Evolution of User Interface Design through Prototypes. Reusable Components - Patterns - Frame works - Coding – Choice of Programming Language - Coding Standards
SOFTWARE TESTING 9 HrsConventional Testing and SDLC Testing - Organization for Testing - Non-Execution-Based Testing-Formal Technical Reviews - Walkthroughs - Inspections - Use of Static Analyzers. Execution-Based Testing- Black-Box vs. Glass-Box Testing - Testing during Code Integration - Product Testing System Testing - Testing Distributed Implementation - Testing of Real-Time systems - Acceptance Testing. Software Quality Management: Quality Dimensions - Process Quality and Product Quality - Quality Assurance Planning - Quality Measurements - Software Configuration Management-Version management - Software Process Improvement-Capability Maturity Model - Other SPI models.SOFTWARE PROJECT MANAGEMENT 9 HrsSoftware Projects - Project Feasibility Study - Project Planning - Project Organization - Estimation of Project Effort-Measuring Software Attributes and Productivity - COCOMO for Effort Estimation. Risk Management-Risk Identification - Risk Monitoring and Mitigation. Project Scheduling - Project Monitoring and Control-Assessment of Project Progress - Measurement during Software Projects.
Software Maintenance: Planning for Maintenance - maintenance Activities - Reengineering.
Theory: 45 Hrs Total Hours: 45 References:S. Thangasamy, “Essentials of Software Engineering”, Wiley India, First Edition, 2012.
R.S. Pressman, “Software Engineering – A Practitioner’s Approach”, Seventh Edition, McGraw Hill International Edition, 2010.
M. Blaha and J. Rumbaugh, “Object Oriented Modeling and Design with UML”, Second Edition, Prentice-Hall India, 2007.
Stephen Schach, “Software Engineering”, Seventh Edition, TMH, New Delhi, 2007.
Pankaj Jalote, “An Integrated Approach to Software Engineering”, Third Edition, Narosa Publishing House, Reprint 2014.
I. Sommerville, “Software Engineering”, Ninth Edition, Pearson Education, 2010.


LTPC3003
U14GST007 PROFESSIONAL ETHICS

Course outcomes:After successful completion of this course, the students will be able toCO1: Understand the ethical theories and concepts
CO2: Understanding an engineer’s work in the context of its impact on society
CO3: Understand and analyze the concepts of safety and risk
CO4: Understand the professional responsibilities and rights of Engineers
CO5: Understand the concepts of ethics in the global context
Pre-requisites: NilCO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak

COs
Programme Outcomes(POs)


PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12

CO1





M
M
S
M




CO2





M
M
S
M




CO3





M
M
S
M




CO4





M
M
S
M




CO5





M
M
S
M




Course assessment methods:
Direct
Indirect

Internal tests
Assignments
End Semester Exam
Course End Survey



ENGINEERING ETHICS AND THEORIES 9 Hrs
Definition, Moral issues, Types of inquiry, Morality and issues of morality, Kohlberg and Gilligan’s theories, consensus and controversy, Professional and professionalism, moral reasoning and ethical theories, virtues, professional responsibility, integrity, self respect, duty ethics, ethical rights, self interest, egos, moral obligations.

SOCIAL ETHICS AND ENGINEERING AS SOCIAL EXPERIMENTATION 9 Hrs

Engineering as social experimentation, codes of ethics, Legal aspects of social ethics, the challenger case study, Engineers duty to society and environment.

SAFETY 9 Hrs
Safety and risk – assessment of safety and risk – risk benefit analysis and reducing risk – the Three Mile Island and Chernobyl case studies. Bhopal gas tragedy.

RESPONSIBILITIES AND RIGHTS OF ENGINEERS 9 Hrs
Collegiality and loyalty – respect for authority – collective bargaining – confidentiality – conflicts of interest – occupational crime – professional rights – employee rights – Intellectual Property Rights (IPR) – discrimination.

GLOBAL ISSUES AND ENGINEERS AS MANAGERS, CONSULTANTS AND LEADERS 9 Hrs
Multinational Corporations – Environmental ethics – computer ethics – weapons development – engineers as managers – consulting engineers – engineers as expert witnesses and advisors – moral leadership – Engineers as trend setters for global values.

Theory: 45 Hrs Total Hours: 45

References:
Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGraw-Hill, New York, 2005.
John R. Boatright, “Ethics and the Conduct of Business”, Pearson Education, New Delhi, 2003.
Bhaskar S. “Professional Ethics and Human Values”, Anuradha Agencies, Chennai, 2005.
Charles D. Fleddermann, “Engineering Ethics”, (Indian Reprint) Pearson Education / Prentice Hall, New Jersey, 2004.
Charles E. Harris, Michael S. Protchard and Michael J Rabins, “Engineering Ethics – Concepts and cases”, (Indian Reprint now available) Wadsworth Thompson Learning, United States, 2000.



















LTPC0031U14CSP601 SOFTWARE ENGINEERING LABORATORY

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Analyze the problem and do project planning.
CO2: Identify project scope, objectives, and perform data modeling.
CO3: Identify the deliverables in various phases of SDLC.
CO4: Implement solutions using modern tools.
CO5: Explain test plan, perform validation testing, coverage analysis.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSCO2SMCO3SCO4MCO5M
Course Assessment methods:
DirectIndirect1. Model Lab Exams
2. End semester practical exam
3. Viva VoceCourse End Survey

List of experiments:

College Information System
Super Market Automation System
Restaurant Automation System
Judiciary Information System
Student Academic Record Management System
Medicine Shop Automation
Automobile Parts Shop Automation
Quiz System
ATM Systems
Development of Computer Games
Railway Ticket Reservation System
Payroll Processing System
Inventory System



Library Management System
Book Shop Automation System
Text Editor

Experiments beyond the syllabus should be conducted.

Total Hours: 24






































LTPC0031U14CSP604 MINI PROJECT USING OPEN SOURCE SOFTWARE
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Identify the problem which needs to be provided a solution.
CO2: Define the problem statement and carryout design for it.
CO3: Show an attitude of team work and independent working on problems.
CO4: Analyze, Design, Implement and process the experimental information using open
source software.
CO5: Create a mini project report.

Pre-requisites:
1. U14CST603-Software Engineering
2. U14CSP601- Software Engineering laboratory

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMMCO2SMMCO3MCO4MMCO5M
Course Assessment methods:
DirectIndirectProject ReviewsCourse End Survey

Total Hours: 24









SEMESTER VII













LTPC3003U14CST701 MOBILE AND PERVASIVE COMPUTING

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the concepts and features of mobile networks.
CO2: Explain the working of wireless communication protocols.
CO3: Compare the routing protocols of mobile networks.
CO4: Explain the transport and application layer protocols of mobile networks.
CO5: Outline the basics of pervasive computing.

Pre-requisite course:
U14CST502 - Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2M CO3MMMCO4MMCO5M 
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey


MOBILE NETWORKS  9 HrsCellular Wireless Networks – GSM – Architecture – Protocols – Connection Establishment – Frequency Allocation – Routing – Mobility Management – Security – GPRS.
WIRELESS NETWORKS  9 HrsWireless LANs and PANs – IEEE 802.11 Standard – Architecture – Services –Network – HiperLAN – Bluetooth- Wi-Fi – WiMAX.
ROUTING  9 HrsMobile IP – DHCP – AdHoc– Proactive and Reactive Routing Protocols – Multicast Routing.
TRANSPORT AND APPLICATION LAYERS  9 HrsMobile TCP– WAP – Architecture – WWW Programming Model– WDP – WTLS – WTP – WSP – WAE – WTA Architecture – WML – WML Scripts.
 PERVASIVE COMPUTING 9 HrsPervasive computing infrastructure-applications- Device Technology - Hardware, Human-machine Interfaces, Biometrics, and Operating systems– Device Connectivity – Protocols, Security, and Device Management- Pervasive Web Application architecture- Access from PCs and PDAs - Access via WAP.Theory: 45 Hrs Total Hours: 45 References:Jochen Schiller, “Mobile Communications”, PHI, Second Edition, 2008.
Jochen Burkhardt, “Pervasive Computing: Technology and Architecture of Mobile Internet Applications”, Addison-Wesley Professional; Third Edition, 2007
Frank Adelstein, Sandeep KS Gupta, Golden Richard, “Fundamentals of Mobile and Pervasive Computing”, McGraw-Hill, 2005.
Debashis Saha, “Networking Infrastructure for Pervasive Computing: Enabling Technologies”, Kluwer Academic Publisher, Springer; First Edition, 2011.
Agrawal and Zeng “Introduction to Wireless and Mobile Systems”, Brooks / Cole (Thomson Learning), First Edition, 2006.
Uwe Hansmann, Lothar Merk, Martin S. Nicklons and Thomas Stober, “Principles of Mobile Computing”, Springer, New York, 2006.

Other References:
HYPERLINK "http://nptel.ac.in/courses/108102045/37"http://nptel.ac.in/courses/108102045/37
HYPERLINK "http://nptel.ac.in/video.php?subjectId=117102062"http://nptel.ac.in/video.php?subjectId=117102062




















LTPC3003U14CST702 DATA WAREHOUSING AND DATA MINING
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain about the necessity of preprocessing and its procedure.
CO2: Apply the association rules for mining applications.
CO3: Identify an appropriate Classification techniques for various problems with
high dimensional data.
CO4: Identify an appropriate Clustering techniques for various problems with
high dimensional data
CO5: Outline various mining techniques on complex data objects.

Pre-requisites:
U14CST404 -Database Management Systems

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2SMCO3MC04MSCO5MCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey















DATA WAREHOUSING AND BUSINESS ANALYSIS 9 HrsData warehousing Components –Building a Data warehouse – Mapping the Data Warehouse to a Multiprocessor Architecture – DBMS Schemas for Decision Support – Data Extraction, Cleanup, and Transformation Tools –Metadata – reporting – Query tools and Applications – Online Analytical Processing (OLAP) – OLAP and Multidimensional Data Analysis. DATA MINING PRIMITIVES AND CONCEPT DESCRIPTION 9 HrsData mining primitives – Data mining query language - concept description – Data generalization and characterization – Analytical characterization – Mining Descriptive statistical measures in large databases.
CLASSIFICATION AND PREDICTION  9 HrsIntroduction – Decision Tree Induction – Bayesian Classification – Back propagation – Lazy Learners – Other classification methods – Prediction – Evaluating the accuracy CLUSTERING AND ASSOCIATION  9 HrsSimilarity and Distance Measures – Hierarchical Algorithms – Partitional Algorithms – Outlier Analysis – Mining Frequent Patterns, Associations, and Correlations ADVANCED TOPICS  9 HrsWeb Mining – Web Content Mining – Structure and Usage Mining – Spatial Mining – Time Series and Sequence Mining – Graph Mining.Theory: 45 Hrs Total Hours: 45 References:
HYPERLINK "http://www.goodreads.com/author/show/342574.Vipin_Kumar"Vipin Kumar, HYPERLINK "http://www.goodreads.com/author/show/597027.Michael_Steinbach"Michael Steinbach,” Introduction to Data Mining”, Second Edition, Addison Wesley, 2005.
Jiawei. Han, Micheline Kamber, “Data Mining: Concepts and Techniques”, Second Edition, Elsevier, New Delhi, 2008.
Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata McGraw– Hill Edition, Tenth Reprint 2007.
Other References:
HYPERLINK "http://www.information-management-architect.com/process-architecture.html"http://www.information-management-architect.com/process-architecture.html
HYPERLINK "http://www.cs.ccsu.edu/~markov/ccsu_courses/DataMining-1.html"http://www.cs.ccsu.edu/~markov/ccsu_courses/DataMining-1.html
HYPERLINK "http://www.tutorialspoint.com/data_mining/dm_cluster_analysis.htm"http://www.tutorialspoint.com/data_mining/dm_cluster_analysis.htm
HYPERLINK "http://study.com/academy/lesson/data-warehousing-and-data-mining-information-for-business-intelligence.html"http://study.com/academy/lesson/data-warehousing-and-data-mining-information-for-business-intelligence.html





LTPC3024U14CST703 CLOUD COMPUTING

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the cloud computing paradigm and its various forms of services
CO2: Identify the architecture, infrastructure and delivery models of cloud computing
CO3: Apply suitable virtualization concepts.
CO4: Illustrate different Programming Models and approaches.
CO5: Apply cloud Toolkits to solve the problems

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3SCO4MCO5WM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey

INTRODUCTION  9+3 HrsOverview – Cloud Components – Infrastructure – Services- Applications – Benefits –Limitations – Security Concerns – Regularity Issues. Hardware and Infrastructure – Clients –Security–Network –Services.



CLOUD ARCHITECTURE AND MODEL 9+3 HrsTechnologies for Network-Based System – System Models for Distributed and Cloud Computing – NIST Cloud Computing Reference Architecture. Cloud deployment model: Public clouds – Private clouds – Community clouds- Hybrid clouds – Commoditization in cloud computing and Advantages of Cloud computing
CLOUD SERVICES9+3 HrsWeb-Based Application – Pros and Cons of Cloud Service Development – Types of Cloud Service Development – Software as a Service – Platform as a Service – Web Services – On-Demand Computing – Discovering Cloud Services Development Services and Tools – Amazon Ec2 – Google App Engine – IBM Clouds.
VIRTUALIZATION9+3 HrsVirtualization and cloud computing – Virtualization benefits- Server virtualization –VM, Hardware virtualization – OS virtualization - Storage virtualization –Network attached storage -Cloud Server virtualization – Networking essential to cloud.
PROGRAMMING MODEL 9+3 HrsParallel and distributed programming paradigms – MapReduce , Twister and iterative MapReduce – Hadoop library from Apache – Mapping applications - Programming support- Google App Engine, Amazon AWS-Case study: OpenStack.
Theory: 45 Hrs Practical: 15 Hrs Total Hours: 60References:
Anthony T.Velte, Toby J. Velte Robert Elsenpeter, “Cloud Computing - A practical approach”, Tata McGraw- Hill , New Delhi, 2010.
Kai Hwang, Geoffrey C Fox, Jack G Dongarra, “Distributed and Cloud Computing, From Parallel Processing to the Internet of Things”, Morgan Kaufmann Publishers, 2012.
Michael Miller, “Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online”, Que Publishing, August 2008.
Rittinghouse John W, Ransome James F, “Cloud Computing-Implementation, Management and Security”, CRC Press, Taylor and Francis Group, 2012.
RajkumarBuyya, Christian Vecchiola, S.TamaraiSelvi, “Mastering Cloud Computing”, TMGH, 2013.
Other References:
1. http://www.buyya.com/papers/CloudSim2010.pdf
2. http://thecloudtutorial.com/
3. http://www.top-windows-tutorials.com/cloud






LTPC3003U14GST003 PRINCIPLES OF MANAGEMENT
Course Outcomes:
CO1: Understand the concepts of management, administration and the evolution of management thoughts.
CO2: Understand and apply the planning concepts.
CO3: Analyze the different organizational structures and understand the staffing process.
CO4:Analyze the various motivational and leadership theories and understand the communication and controlling processes.
CO5: Understand the various international approaches to management

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSSWCO2MSMMCO3MMMWCO4MMMMCO5SM
Course Assessment methods:
DirectIndirectInternal Tests
Assignments
End Semester ExamCourse End Survey

MANAGEMENT CONTEXT 9 Hrs
Management – Definition – Importance – Functions – Skills required for managers - Roles and functions of managers – Science and Art of Management –Management and Administration.
Evolution of Classical, Behavioral and Contemporary management thoughts.

PLANNING 9 Hrs
Nature & Purpose – Steps involved in Planning – Forms of Planning – Types of plans – Plans at Individual, Department and Organization level - Managing by Objectives. Forecasting – Purpose – Steps and techniques. Decision-making – Steps in decision making.

ORGANISING 9 Hrs
Nature and Purpose of Organizing - Types of Business Organization - Formal and informal organization – Organization Chart – Structure and Process – Strategies of Departmentation– Line and Staff authority – Benefits and Limitations. Centralization Vs De-Centralization and Delegation of Authority. Staffing – Manpower Planning – Recruitment – Selection – Placement – Induction.


DIRECTING & CONTROLLING 9 Hrs
Nature & Purpose – Manager Vs. Leader - Motivation - Theories and Techniques of Motivation.
Leadership – Styles and theories of Leadership.
Communication – Process – Types – Barriers – Improving effectiveness in Communication.
Controlling – Nature – Significance – Tools and Techniques.

CONTEMPORARY ISSUES IN MANAGEMENT 9 Hrs
Corporate Governance Social responsibilities – Ethics in business – Recent issues. American approach to Management, Japanese approach to Management, Chinese approach to Management and Indian approach to Management.

Theory: 45 Hrs Total Hours: 45
References:
Tripathy PC And Reddy PN, “Principles of Management”, Tata McGraw-Hill, Fourth Edition, 2008.
Dinkar Pagare, “Principles of Management”, Sultan Chand & Sons, 2000.
Kanagasapapathi. P, “Indian Models of Economy, Business and Management”, Prentice Hall of India, New Delhi, 2008, ISBN: 978-81-203-3423-6.
G.K.Vijayaraghavan and M.Sivakumar, “Principles of Management”, Lakshmi Publications, Fifth Edition, 2009.
Harold Koontz & Heinz Weihrich, “Essentials of Management – An International perspective”, Eighth Edition, Tata McGraw-Hill, 2009.
Charles W.L. Hill and Steven L McShane, “Principles of Management” , Tata Mc Graw-Hill, 2009.












LTPC0031U14CSP701 MOBILE AND WIRELESS NETWORKS
LABORATORY

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Demonstrate knowledge in use of simulation tool.
CO2: Develop skills to install and configure wireless devices.
CO3: Analyse the behavior of wireless network in infrastructure and ad hoc mode.
CO4: Evaluate the performance of wireless routing protocols.
CO5: Examine the effect of MAC layer characteristics of a wireless network.

Pre-requisites:
1. U14CST502- Computer Networks
2. U14CSP501- Computer Networks Laboratory

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSCO2WMCO3SCO4WMWCO5W
Course Assessment methods:
DirectIndirect1. Model Lab Exams
2. End semester practical exam
3.Viva VoceCourse End Survey

List of experimentsInstall a WLAN adapter card in a desktop and laptop
Configuring an Access Point
Write a mobile application that turns on Bluetooth and communicate with another phone and transfer a picture file from one phone to other.
Write a mobile application to enable a continuous chat between the two phones.
Simulate the behavior of wireless network in infrastructure and ad hoc mode.
Evaluate the performance of unicast routing protocol in ad hoc networks.
Analyse the performance of multicast routing protocols in ad hoc networks.
Investigate the performance of broadcasting in ad hoc networks.
Analyse the performance of various queuing disciplines in ad hoc networks.
Study the effect of physical and MAC layer characteristics of wireless links using signal strength, data rate, retransmission and delay measurement

Experiments beyond the syllabus should be conducted.


Total Hours: 24
























LTPC0031U14CSP702 DATA WAREHOUSING AND DATA MINING
LABORATORY
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Demonstrate the importance of preprocessing the given datasets.
CO2: Design and implement classification algorithm to classify given problems using modern tools.
CO3: Design and implement clustering algorithm to group the given attributes in a dataset using modern tools.
CO4: Demonstrate to find association rules for the given datasets using modern tools.
CO5: Develop skills to design data warehouse for an enterprise.
Pre-requisites:
U14CST404 -Database Management Systems
U14CSP503-Database Management Systems Laboratory
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1 SCO2MMCO3MMC04SMCO5WCourse Assessment methods:
DirectIndirect1. Model Exams
2. End Semester Practical Exam
3. Viva VoceCourse End Survey
List of experiments   1.   Exercises on Data warehouse Design for an enterprise.
2. Exercises on Classification Algorithms.
3. Exercises on Clustering Algorithms.
4.   Exercises on Discovering Association Rules.
5.   Exercises on Data mining tools.
Experiments beyond the syllabus should be conducted.




 Total Hours: 24






LTPC0063U14CSP703 PROJECT WORK - PHASE I

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Prepare a literature survey in a specific domain as a team / individual to motivate lifelong learning.
CO2: Identify the problem which needs to be provided a sustainable solution using modern tools.
CO3: Analyze the problem definition and its impact on the society and environment.
CO4: Analyze the design information to provide environment friendly solutions
CO5: Document the literature and findings.

Pre-requisites:
1. U14CST603-Software Engineering
2. U14CSP601- Software Engineering laboratory

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSMMSMCO2MSMMMMSMCO3SSSMWSSCO4SSSMSCO5S
Course Assessment methods:
DirectIndirectProject ReviewsCourse End Survey













SEMESTER VIII
















LTPC00126U14CSP801 PROJECT WORK-PHASE II


Course Outcomes:
After successful completion of this course, students should be able to
CO1: Analyze the literature survey in a specific domain as a team / individual in a ethical way.
CO2: Plan an experimental design to solve engineering / societal problems using modern tools
CO3: Develop lifelong learning to keep abreast of latest technologies.
CO4: Analyze and implement the design to provide sustainable solutions
CO5: Evaluate and interpret the experimental results and analyze the impact on society and environment

Pre-requisites:
1. U14CST603-Software Engineering
2. U14CSP601- Software Engineering laboratory
3. U14CSP703 - Project Work – Phase I

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSMMSMMCO2SSSMSMCO3MSMMCO4MMMSMSCO5SMSSMMSMMMM

Course Assessment methods:
DirectIndirectProject Reviews
End Semester ExamCourse End Survey




















ELECTIVE I

















LTPC3003U14CSTE11 ADVANCED COMPUTER ARCHITECTURE

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the need to switch from Uniprocessor to Multiprocessor
CO2: Explain the basics of pipelining and the influence of hazards on its performance.
CO3: Summarize the performance of cache memories.
CO4: Explain the storage and i/o requirements for processors.
CO5: Explain about shared memory architecture

Pre-requisites:
l. U14CST302 Computer Architecture

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2SMCO3SMMCO4SCO5SCourse Assessment methods:

DirectIndirectInternal Tests
Assignment
Seminar
End Semester ExamCourse End Survey

COMPUTER ABSTRACTION AND TECHNOLOGY 8 Hrs
Introduction- Performance- Power Wall- The Switch from Uniprocessors to Multiprocessors-Real Stuff: Manufacturing and Benchmarking the AMD Opteron X4- Fallacies and Pitfalls.







PROCESSOR 10 Hrs
Introduction- Logic Design Conventions- Building a Data Path-A Simple Implementation Scheme-An Overview of Pipelining- Pipelined Data Path and Control-Data Hazards: Forwarding versus Stalling- Control Hazards-Exceptions-Parallelism and Advanced Instruction-Level Parallelism.

EXPLOITING MEMORY 11 Hrs
Introduction-The Basics of Caches-Measuring and Improving Cache Performance-Virtual Memory-A Common Framework for Memory Hierarchies-Virtual Machines-Using a Finite-State Machine to Control a Simple Cache- Parallelism and Memory Hierarchies: Cache Coherences.

STORAGE AND I/O 7 Hrs
Introduction-Dependability, Reliability and Availability-Disk Storage-Flash Storage-Connecting Processors, Memory and I/O Devices- Interfacing I/O Devices to the Processor, Memory and Operating System- I/O Performance Measures: Examples from Disk and File Systems- Designing an I/O System- Parallelism and I/O: Redundant Arrays of Inexpensive Disks.

MULTICORES, MULTIPROCESSORS AND CLUSTERS 9 Hrs
Introduction- The Difficulty of Creating Parallel Processing Programs- Shared Memory Multiprocessors- Clusters and other Message-Passing Multiprocessors- Hardware Multithreading- SISD, MIMD, SIMD, SPMD and Vector- Introduction to Graphics Processing Units- Multiprocessor Network Topologies- Multiprocessor Benchmarks- Roofline: A Simple Performance Model.

Theory: 45 Hrs Total Hours: 45

References:
David A. Patterson and John L. Hennessy, “Computer Organization and Design”, The Hardware/Software Interface.Revised, Morgan Kaufmann, Fifth Edition, 2013.
Vincent P.Heuring and Harry F.Jordan, “Computer System Design and Architecture”, Addison Wesley, Second Edition, 2004.
John P.Hayes, “Computer Architecture and Organization”, McGraw Hill, Third Edition, 2002.
Carl Hamacher, ZvonkoVranesic and SafwatZaky, “Computer Organization”, McGraw-Hill, Sixth Edition, 2011.












LTPC3003U14CSTE12 KNOWLEDGE BASED DECISION SUPPORT
SYSTEMS
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the basic concepts of Decision Support System and Business Intelligence.
CO2: Explain about the Decision Support System technologies and modeling methods.
CO3: Summarize the usage of data mining for Business Intelligence.
CO4: Outline the features of Collaborative Computer-Supported Technologies and Group Support systems
CO5: Demonstrate awareness of Artificial Intelligence, Expert Systems and emerging trends in Management Support System

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3
MCO4MCO5MMM
Course Assessment methods:

DirectIndirectInternal Tests
Assignments
Seminar
End Semester ExamCourse End Survey

DECISION SUPPORT SYSTEMS (DSS) AND BUSINESS INTELLIGENCE 9 HrsChanging Business Environments and computerized decision support-Managerial Decision Making-Computerized Support for Decision Making-Frameworks for Decision Support Systems, Framework for BI-Work System View -Major Tools and Techniques of Managerial Decision Support.
Decision Making, Modeling And Support: Decision making introduction and Definitions-Models-Phases of Decision Making Process-How decisions are supported.


DSS CONCEPTS, METHODOLOGIES, TECHNOLOGIES AND MODELING 9 Hrs
Decision Support Systems: Concepts-Decision Support Systems Description-Characteristics and Capabilities-Classifications and components of Decision Support System-Data, model Management Subsystems-User Interface Subsystem-Knowledge Based Management Subsystem-DSS user.
Modeling and analysis: Management Support Systems Modeling-Structure of Mathematical Models – Certainty, Uncertainty, Risk-Management Support Systems Modeling with Spreadsheets-Mathematical Programming Optimization-Multiple Goals, Sensitivity Analysis, What-if Analysis and Goal Seeking-Decision Analysis with Decision Tables and Decision Trees-Multi-criteria Decision Making with Pair wise Comparisons-Problem Solving Search Methods-Simulation-Visual Interactive Simulation-Quantitative Software Packages and Model Base Management.
DATA MINING AND DATA WAREHOUSING9 HrsData Mining(DM): Concepts and applications-DM process- methods-Software tools
Data warehousing: Data Warehousing Definitions and Concepts -Data warehousing Process Overview - Architectures-Data Integration and the Extraction Transformation and Load Processes.
COLLABORATION, BUSINESS PERFORMANCE AND KNOWLEDGE MANAGEMENT
9 HrsBusiness Performance Management (BPM): Overview – Performance Measurement – BPM Methodologies – BPM Technologies and Applications.
Collaborative computer supported technologies: Making Decisions in Group Characteristics, Process, Benefits and Dysfunctions-Supporting Group Work and Computerized Systems-Tools for Indirect Support of Decision Making-Integrated Groupware Suites-Direct Computerized Support for Decision Making-Products and Tools for GDSS/GSS and Successful implementation-Emerging Collaboration Tools: From VoIP to Wikis-Collaborative Efforts in Design, Planning and Project Management-Creativity, idea Generation and Computerized Support.
Knowledge management: Introduction-Organizational Learning and Transformation-Knowledge Management Activities- Approaches to Knowledge Management-Information Technology (IT) in Knowledge Management- Knowledge Management Systems Implementation-Roles of people in knowledge Management-Ensuring the Success of Knowledge Management Efforts. ARTIFICIAL INTELLIGENCE(AI), EXPERT SYSTEMS AND MANAGEMENT SUPPORT SYSTEMS
9 HrsArtificial Intelligence and Expert Systems: Concepts and definitions-The Artificial Intelligence Field-Basic Concepts of Expert Systems-Applications of Expert Systems-Structure of Expert Systems-Knowledge Engineering-Problem Areas Suitable for Expert Systems-Development of Expert Systems-Benefits , Limitations and Critical Success Factors of Expert Systems- Expert Systems on the Web.
Management Support Systems(MSS): Emerging trends and Impacts: RFID and New BI Application Opportunities-Reality Mining-Virtual Methods- The Web 2.0 Revolution- Virtual Communities-Online Social Networking :Basics and Examples-Cloud Computing and BI-The Impacts of Management Support Systems: An Overview-Management Support Systems Impacts on Organizations- Management Support Systems Impacts on Individuals-Automating Decision Making and the Manager’s job-Issues of Legality, Privacy, and Ethics.Theory:45 Hrs Total Hours:45References:Efraim Turban, Ramesh Sharda, Dursun Delen, “Decision Support and Business Intelligence Systems”, Ninth Edition, Pearson Education, 2011.
V.S.Janakiraman and K.Sarukesi, “Decision Support Systems”, Prentice Hall of India, 2004.
Efrem G Mallach,”Decision Support Systems and Data Warehouse Systems”, Mc Graw Hill, 2000.
George M Marakas,”Decision Support Systems”, II edition, - Pearson/Prentice Hall, 2002.






























LTPC3003U14CSTE13 BUILDING ENTERPRISE APPLICATIONS
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the concept of Enterprise Analysis and Business Modeling.
CO2: Explain requirements validation, planning and estimation.
CO3: Demonstrate a simple application design in a framework.
CO4: Explain the construction and development of different solution layers.
CO5: Explain different testing levels and rolling out an enterprise application.
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MWCO2MWCO3MMCO4MMCO5MCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Seminar
3. Assignments
4. End Semester Exam Course End Survey

INTRODUCTION TO BUILDING ENTERPRISE APPLICATION  9 HrsOverview of ERP and its Benefits- ERP and Related Technologies- Business Process Reengineering (BPR).Introduction to enterprise applications and their types- software engineering methodologies- life cycle of raising an enterprise application- introduction to skills required to build an enterprise application- key determinants of successful enterprise applications- and measuring the success of enterprise applications.
INCEPTING ENTERPRISE APPLICATIONS  8 HrsInception of enterprise applications, enterprise analysis, business modeling, requirements elicitation, use case modelling, prototyping, non functional requirements, requirements validation, planning and estimation

ARCHITECTING AND DESIGNING ENTERPRISE APPLICATIONS 10 HrsConcept of architecture, views and viewpoints, enterprise architecture, logical architecture, technical architecture- design, different technical layers, best practices, data architecture and design – relational, XML, and other structured data representations, Infrastructure architecture and design elements - Networking, Internetworking, and Communication Protocols, IT Hardware and Software, Middleware, Policies for Infrastructure Management, Deployment Strategy, Documentation of application architecture and design.
CONSTRUCTING ENTERPRISE APPLICATIONS  10 HrsConstruction readiness of enterprise applications - defining a construction plan, defining a package structure, setting up a configuration management plan, setting up a development environment, introduction to the concept of Software Construction Maps, construction of technical solutions layers, methodologies of code review, static code analysis, build and testing, dynamic code analysis – code profiling and code coverage.
TESTING AND ROLLING OUT ENTERPRISE APPLICATIONS 8 HrsTypes and methods of testing an enterprise application, testing levels and approaches, testing environments, integration testing, performance testing, penetration testing, usability testing, globalization testing and interface testing, user acceptance testing, rolling out an enterprise application.Theory: 45 Hrs Total Hours: 45References:
Anubhav Pradhan, Satheesha B. Nanjappa, Senthil K. Nallasamy, Veerakumar Esakimuthu “Raising Enterprise Applications”, Wiley India Pvt Ltd, April 2010
Brett McLaughlin, “Building Java Enterprise Applications”,O’Reilly Media,March 2002
Soren Lauesen, “Software Requirements: Styles & Techniques”, Addison-Wesley Professional, 2002.
Arnold Rdorfer, “Software and Systems Requirements Engineering: In Practice”, McGraw-Hill/Osborne Media, 2009.
Dean Leffingwell, Don Widrig, “Managing Software Requirements: A Unified Approach”, Pearson Education, 2002.
Len Bass, Paul Clements, Rick Kazman, “Software Architecture in Practice”, second edition, Pearson Education, 2002.
Inderjeet Singh, Mark Johnson, Beth Stearns, “Designing Enterprise Applications with the J2EE Platform”, second edition, Pearson Education, 2002.
Ron Patton, “Software Testing”, second edition, Pearson Education, 2005.
Naresh Chauhan, “Software Testing –Principles and Practices”, Oxford University Press, 2011.
Other References:
 HYPERLINK "http://www.campusconnect.infosys.com" www.campusconnect.infosys.com










ELECTIVE II
















LTPC3003U14GST005 ENGINEERING ECONOMICS AND FINANCIAL
MANAGEMENT
Course outcomes:After successful completion of this course, the students will be able toCO1: Evaluate the economic theories, cost concepts and pricing policies
CO2: Understand the market structures and integration concepts
CO3: Understand the measures of national income, the functions of banks and concepts of globalization
CO4: Apply the concepts of financial management for project appraisal
CO5: Understand accounting systems and analyze financial statements using ratio analysis
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak

COs
Programme Outcomes(POs)


PO1
PO2
PO3
PO4
PO5
PO6
PO7
PO8
PO9
PO10
PO11
PO12

CO1





W


W

S
W

CO2





W


W

S
W

CO3





W


W

S
W

CO4





W


W

S
W

CO5





W


W

S
W

Course assessment methods:
Direct
Indirect

Internal tests
Assignments
Seminars
End Semester Exam
Course End Survey


ECONOMICS, COST AND PRICING CONCEPTS 9 Hrs
Economic theories – Demand analysis – Determinants of demand – Demand forecasting – Supply – Actual cost and opportunity cost – Incremental cost and sunk cost – Fixed and variable cost – Marginal costing – Total cost – Elements of cost – Cost curves – Breakeven point and breakeven chart – Limitations of break even chart – Interpretation of break even chart – Contribution – P/V-ratio, profit-volume ratio or relationship – Price fixation – Pricing policies – Pricing methods

CONCEPTS ON FIRMS AND MANUFACTURING PRACTICES 9 Hrs
Firm – Industry – Market – Market structure – Diversification – Vertical integration – Merger – Horizontal integration

NATIONAL INCOME, MONEY AND BANKING, ECONOMIC ENVIRONMENT 9 Hrs
National income concepts – GNP – NNP – Methods of measuring national income – Inflation – Deflation – Kinds of money – Value of money – Functions of bank – Types of bank – Economic liberalization – Privatization – Globalization

CONCEPTS OF FINANCIAL MANAGEMENT 9 Hrs
Financial management – Scope – Objectives – Time value of money – Methods of appraising project profitability – Sources of finance – Working capital and management of working capital

ACCOUNTING SYSTEM, STATEMENT AND FINANCIAL ANALYSIS 9 Hrs
Accounting system – Systems of book-keeping – Journal – Ledger – Trail balance – Financial statements – Ratio analysis – Types of ratios – Significance – Limitations

Theory: 45 Hrs Total Hours: 45
References:
Prasanna Chandra, “ Financial Management (Theory & Practice)”, TMH
Weston & Brigham, “ Essentials of Managerial Finance”
Pandey, I. M., “Financial Management”
Fundamentals of Financial Management- James C. Van Horne.
Financial Management & Policy -James C. Van Horne
Management Accounting & Financial Management- M. Y. Khan & P. K. Jain
Management Accounting Principles & Practice -P. Saravanavel























LTPC3003U14GST008 FOUNDATION SKILLS IN INTEGRATED
PRODUCT DEVELOPMENT
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Analyze various global trends and decide on the scope of a new product.
CO2: Outline the product development methodologies and management.
CO3: Develop product management plan for a new product based on the type of the new product
and development methodology.
CO4: Summarize requirement engineering and know how to collect, analyze and arrive at
requirements for new product development and convert them in to design
specification.
CO5: Conceptualize new product integrating the hardware, software, controls, electronics and
mechanical systems.
CO6: Develop test specifications and coordinate the respective activities with testing group,
validate the product and confirm its performance as per design specification.
CO7: Develop product documentation as required.

Pre-requisites:
1. U14CST603-Software Engineering
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3MCO4MCO5MCO6MMMCO7M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.Mini Project
5.End Semester ExamCourse End Survey



FUNDAMENTALS OF PRODUCT DEVELOPMENT  9 HrsGlobal Trends Analysis and Product decision: Types of various trends affecting product decision - Social Trends (Demographic, Behavioral, Psychographic), Technical Trends (Technology, Applications, Tools, Methods), Economical Trends (Market, Economy, GDP, Income Levels, Spending Pattern, target cost, TCO), Environmental Trends (Environmental Regulations and Compliance), Political/Policy Trends (Regulations, Political Scenario, IP Trends and Company Policies); PESTLE Analysis.
Introduction to Product Development Methodologies and Management: Overview of Products and Services (Consumer product, Industrial product, Specialty products etc); Types of Product Development (NPD/ Re-Engineering (Enhancements, Cost Improvements)/ Reverse Engineering/ Design Porting & Homologation); Overview of Product Development methodologies (Over the Wall/ Waterfall/ V-Model/ Stage-Gate Process/ Spiral/Systems Engineering/ Agile); Product Life Cycle (S- Curve, Reverse Bathtub Curve); Product Development Planning and Management (Budgeting, Risk, Resources and Design Collaboration, Scheduling, Change Management, Product Cost Management).
REQUIREMENTS AND SYSTEM DESIGN  9 HrsRequirement Engineering: Types of Requirements (Functional, Performance, Physical, Regulatory, Economical, Behavioral, Technical, Stakeholder, Environmental, Industry specific, Internal-Company Specific); Requirement Engineering (Gathering (VOC), Analysis (QFD), Design Specification); Traceability Matrix and Analysis; Requirement Management.
System Design & Modeling: Introduction to System Modeling; System Optimization; System Specification; Sub-System Design; Interface Design.
DESIGN AND TESTING  9 HrsConceptualization: Industrial Design and User Interface Design; Introduction to Concept generation Techniques; Concept Screening & Evaluation - Concept Design, S/W Architecture, Hardware Schematics and simulation.
Detailed Design: Component Design and Verification; High Level Design/Low Level Design of S/W Programs, S/W Testing; Hardware Schematic, Component design, Layout and Hardware Testing.
Prototyping: Types of Prototypes (Mockups, Engineering Assessment Prototype, Alpha, Beta, Gama); Introduction to Rapid Prototyping and Rapid Manufacturing. System Integration, Testing, Certification and Documentation: Manufacturing/Purchase and Assembly of Systems; Integration of Mechanical, Embedded and S/W systems; Introduction to Product verification processes and stages – Industry specific (DFMEA, FEA, CFD); Introduction to Product validation processes and stages - Industry specific (Sub-system Testing/ Integration Testing/ Functional Testing/ Performance Testing / Compliance Testing); Product Testing standards and Certification – Industry specific; Product Documentation (Compliance Documentation, Catalogue, Brochures, user manual, maintenance Manual, Spares Parts List, Warranty, Disposal Guide, IETMS, Web Tools).SUSTENANCE ENGINEERING AND END-OF-LIFE (EOL) SUPPORT 6 HrsSustenance: Maintenance and Repair; Enhancements. Product EoL: Obsolescence Management; Configuration Management; EoL Disposal.



BUSINESS DYNAMICS – ENGINEERING SERVICES INDUSTRY


6 HrsThe Industry: Engineering Services Industry – Overview; Product development in Industry versus Academia.
The IPD Essentials: Introduction to vertical specific product development processes; Product development Trade-offs; Intellectual Property Rights and Confidentiality; Security and Configuration management.
SUSTENANCE ENGINEERING AND END-OF-LIFE (EOL) SUPPORT 6 HrsSustenance: Maintenance and Repair; Enhancements.
Product EoL: Obsolescence Management; Configuration Management; EoL Disposal.
Theory:45 Hrs Total Hours: 45 
References:
“Foundation Skills in Integrated Product Development (FSIPD)”, NASSCOM, First Edition, 2013.
Ulrich, Karl T. and Eppinger, Steven D, “Product Design and Development”, McGraw-Hill, Fifth Edition, 2012.
Kevin N. Otto, “Product design – Techniques in Reverse Engineering and New Product Development”, Pearson, New Delhi, 2011.
























LTPC2023U14CSTE21 CONTENT MANAGEMENT USING JOOMLA
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the use of web development framework.
CO2: Build the Joomla web development platform.
CO3: Make use of plug-in in web development.
CO4: Develop web application using Joomla modules.
CO5: Make use of database in web development.

Pre-requisites:
U14CST503-XML and Web Services
U14CST404-Database Management Systems

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2SCO3SCO4MMCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey
JOOMLA DEVELOPMENT6+3 Hours Joomla technical environment-Extension-Plugins-Modules-Component-Languages-Template. Getting Your Workstation Ready for Joomla Development: Requirements to run Joomla-Tools of the trade-Other tools. How Joomla works: Tours of Joomla folder-Joomla Platform-Anatomy of a Joomla Execution cycle.EXTENDING JOOMLA WITH LAYOUT OVERRIDES6+3 HoursTemplate basics-Copy template-Change the Look of Component-Non-layout Overrides. Extending Joomla with Plugins: What is plugin-Plugin types-Tour of Selected Core Plugins-User Registration Plugin-Improved user registration Plugin.


EXTENDING JOOMLA WITH MODULES6+3 HoursModule-Tour of a core module- Show Articles by the Current Author.Components part-1: controllers and Modules- Components Part II: Views, JForm, and Front End Views and the display () Method.
COMPONENTS 6+3 HoursComponent Back End- Component Functional Overview- Subscriptions Manager: Subscriptions Screen- Subscriptions Manager: Add and Edit- Language Files -Installation and Configuration. Components Part IV: Files Overview- Subscription- Category View- Subscription View- Packaging the Component.
WORKING WITH DATABASE6+3 Hours Database Overview- Tables with DDL Commands- Using phpMyAdmin- Using SQL Data with DML Commands- Designing the Table Structure- Working with the Database Inside Joomla. JavaScript and MooTools in Joomla: How Does JavaScript Work- Built- In JavaScript Features.Theory: 30 Hrs Tutorial: 15 Hrs Total Hours: 45 
References:
Mark Dexter, Louis Landry,” Joomla Programming”, Pearson Education, 2012.
Ric Shreves,” Joomla Bible”,Second edition,Willey publication,2013.

Other References:
HYPERLINK "https://www.siteground.com/tutorials/joomla/"https://www.siteground.com/tutorials/joomla/
HYPERLINK "https://docs.joomla.org/Tutorials:Beginners"https://docs.joomla.org/Tutorials:Beginners
HYPERLINK "https://www.joomlatutorials.com/"https://www.joomlatutorials.com/






















LTPC2023U14CSTE22 WEB PROGRAMMING WITH XML
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the use of XML in web development
CO2: Develop an XML document for simple web application
CO3: Explain the use of XML technologies in web development
CO4: Explain the process of XML document transformation
CO5: Explain the use of XML in database

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MCO4MCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey

XML INTRODUCTION6+3 HrsWhat is XML-Well-Formed XML-XML Namespace-Document type definition.
XML SCHEMAS
6+3 Hrs Benefits of XML Schemas- Need of DTDs- Creating a Schema from Multiple Documents- Documenting XML Schemas. RELAX NG: XML and Compact Syntaxes- RELAX NG Patterns- Combining and Reusing Patterns and Grammars- Additional RELAX NG Features.




XPATH



6+3 HrsAbbreviated and Unabbreviated Syntax XPath 1.0 Axes- XPath 1.0 Functions- Predicates Structure of XPath Expressions- XSLT: How an XSLT Processor Works- Procedural versus Declarative Programming- Foundational XSLT Elements- Getting Information from the Source Tree- XSLT Modes- XSLT Variables and Parameters.
X QUERY
6+3 HrsXQuery- XQuery Tools- XQuery Examples- The XQuery Data Model- XQuery Expressions- XQuery Functions- Using Parameters with XQuery.
XML and Databases6+3 HrsThe Need for Efficient XML Data Stores- Approaches to Storing XML- Using Native XML Databases- XML in Commercial RDBMSs- XML in Open Source RDBMS- Choosing a Database to Store XML.Theory: 30 Hrs Practical: 15 Hrs Total Hours: 45 

References:
HYPERLINK "https://www.google.co.in/search?sa=X&hl=en&biw=1366&bih=608&tbm=bks&q=inauthor:%22David+Hunter%22&ei=ekgrVY_gIsWouwSBmYGoCg&ved=0CC0Q9AgwAQ"David Hunter,  HYPERLINK "https://www.google.co.in/search?sa=X&hl=en&biw=1366&bih=608&tbm=bks&tbm=bks&q=inauthor:%22Jeff+Rafter%22&ei=ekgrVY_gIsWouwSBmYGoCg&ved=0CC4Q9AgwAQ"Jeff Rafter, Joe Fawcett, Eric Van der Vlist, Danny Ayers, Jon Duckett, Andrew Watt, Linda McKinnon, ”Begining XML” , Fourth Edition, Wrox publication.
Erik T.Ray “Learning XML”, Second edition, O’Reilly publication, 2003.

Other References:
HYPERLINK "http://www.w3schools.com/xml/default.asp"http://www.w3schools.com/xml/default.asp
HYPERLINK "http://www.xmlfiles.com/"http://www.xmlfiles.com/






















LTPC2023U14CSTE23 FUNDAMENTALS OF DATABASE MANAGEMENT
SYSTEMS
Course Outcomes:
After successful completion of this course, the students should be able to

CO1: Define the fundamental elements of a database management system.
CO2: Explain the basic concepts of relational data model, entity-relationship model.
CO3: Outline relational algebra and database query language (SQL).
CO4: Explain relational database design.
CO5: Construct a database for a given problem using E-R model, normalization and SQL.

Pre-requisites: NIL

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3MSCO4MCO5S
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey
INTRODUCTION 6+3 Hrs
Database System Architecture: Purpose of Database Systems-Views of Data- Database Languages-Data Storage and Querying-Transaction Management-Database Architecture-Database Users and Administrators.
Relational Databases: Structure of Relational Databases-Database Schema-Keys-Schema Diagram.



QUERY LANGUAGES AND E-R MODEL 6+3 Hrs
Formal Relational Query Languages: Relational Algebra –Tuple and Domain Relational Calculus.
Database Design and E-R Model: Overview-Entity Relationship Model-Constraints-Removing Redundant Attributes in Entity Sets-E-R Diagrams
STRUCTURE QUERY LANGUAGE (SQL) 7+3 Hrs
Introduction to SQL: Overview of SQL Query Languages-SQL Data Definition-Basic Structure Of SQL Queries- Additional Basic Operations-Set Operations-Aggregate Functions-Nested Sub Queries-Join Expressions-Views-Transactions-Integrity Constraints-SQL Data Types and Schemes-Authorization.

ADVANCED SQL 4+3 Hrs
Accessing SQL from a Programming Languages-Functions and Procedures-Triggers

RELATIONAL DATABASE DESIGN 7+3 Hrs
Features of Good Relational Database Design –Informal Guide Lines For Relational Schemas- Decomposition Using Functional Dependencies-Functional Dependency Theory-First, Second, Third and Boyce Codd Normal Forms.

Theory: 30 Hrs Practical: 15 Hrs Total Hours: 45

References:
Abraham Silberschatz, Henry Korth, and S. Sudarshan, “Database System Concepts”, Sixth Edition, McGraw-Hill, 2011.
R. Elmasri and S. Navathe, “Fundamentals of Database Systems”, Pearson Education, Sixth Edition, 2011.
Thomas M. Connolly and Carolyn E. Begg, “Database Systems - A Practical Approach to Design, Implementation, and Management”, Pearson Education, Fifth edition, 2010.
C.J.Date, A.Kannan and S.Swamynathan, “An Introduction to Database Systems”, Pearson Education, Eighth Edition, 2006.
Other References:
http://ocw.mit.edu/courses
HYPERLINK "http://docs.mongodb.org/manual/" \hhttp://docs.mongodb.org/manual/














LTPC2023U14CSTE24 FUNCTIONAL PROGRAMMING

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Classify and make use of python programming elements to solve and debug simple logical problems.
CO2: Interpret the problem and able to identify checkpoints to create ordered programs.
CO3: Apply the concept of data structures to solve simple non deterministic problems.
CO4: Make use of object oriented concepts to build real time applications.
CO5: Use various functions to manipulate hold set of values.
CO6: Solve complex problems using loop functions.
CO7: Perform arithmetic operations and able to print output.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SSCO2SCO3SCO4SCO5SCO6SCO7S
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey


INTRODUCTION TO FUNCTIONAL PROGRAMMING: PYTHON 3 HrsWhy Python is popular? - The Python Programming Language - What Is a Program? - What Is Debugging? – Errors: Syntax Errors, Runtime Errors and Semantic Errors - The first program- Essentials for programming: Values and Types, Variables, Variable Names, Keywords, Operators, Operands, Expressions, Statements- Mode of programming: Interactive Mode and Script Mode- Operations: Order of Operations and String Operations – Comments



FUNCTIONS, CONDITIONALS AND RECURSION6 HrsFunction Calls - Type Conversion Functions - Math Functions – Composition - Adding New Functions - Definitions and Uses - Flow of Execution - Parameters and Arguments - Variables and Parameters Are Local- Stack Diagrams - Fruitful Functions and Void Functions - Why Functions?- Importing with from. Modulus Operator - Boolean Expressions - Logical Operators - Conditional Execution - Alternative Execution - Chained Conditionals - Nested Conditionals  - Stack Diagrams for Recursive Functions - Infinite Recursion - Keyboard Input.
FRUITFUL FUNCTIONS AND ITERATIONS 4 HrsSignificant functions : Return Values , Incremental Development, Composition, Boolean Functions, More Recursion, Leap of Faith and checking types - Iterations: Multiple Assignment, Updating Variables, The while Statement, break, Square Roots and Algorithms. STRINGS, LISTS AND DICTIONARIES 8 HrsStrings: A String Is a Sequence , len, Traversal with a for Loop, String Slices, Strings Are Immutable, Searching, Looping and Counting- String Methods, The in Operator and String Comparison – Lists: A List Is a Sequence, Lists Are Mutable, Traversing a List- List Operations - List Slices - List Methods - Map, Filter, and Reduce - Deleting Elements - Lists and Strings - Objects and Values – Aliasing - List Arguments- Dictionaries: Dictionary as a Set of Counters, Looping and Dictionaries, Reverse Lookup, Dictionaries and Lists, Memos, Global Variables, Long Integers.
TUPLES AND FILES 6 HrsTuples: Tuples Are Immutable, Tuple Assignment, Tuples as Return Values, Variable-Length Argument Tuples, Lists and Tuples- Dictionaries and Tuples -Comparing Tuples- Sequences of Sequences- Files: Persistence, Reading and Writing, Format Operator, Filenames and Paths, Catching Exceptions, Databases, Pickling and Pipes.
 INTRODUCTION TO CLASSES AND OBJECTS3 HrsClasses and Objects: User defined types, Attributes, rectangles and copying- Classes and Functions: Time, Pure functions and modifiers- Classes and Methods: object oriented features, polymorphism and type based dispatch- Inheritance: Card Objects, Class Attributes, Comparing Cards, Inheritance Class Diagrams and Data Encapsulation.





LIST OF EXPERIMENTS 15 Hrs
Use tuples and lists to assign and hold multiple values
Use lists to manipulate sets of values.
Use slices to obtain parts of lists and to manipulate lists.
Use range () to generate lists containing sequences of integers.
Use for loops to iterate through predefined lists of objects.
Use while loops to iterate until satisfactory exit conditions are obtained
Use break to program more flexible loop exit conditions.
Read lines of input from the user, without giving a prompt. When the input line is quit, stop accepting input. As output, print the input lines in reverse order, one on each output line. The line quit should not be included in the output.
Write a program to Convert a Decimal number to Binary number
Write a function roots that computes the roots of a quadratic equation. Check for complex roots and print an error message saying that the roots are complex.Theory: 30Hrs Practical: 15 Hrs Total Hours: 45 References:
Allen B. Downey, “Think Python”, O’Reilly Media, Inc, 2012.
HYPERLINK "https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Mark+Lutz%22"Mark Lutz, “Learning Python”, "O'Reilly Media, Inc., Fifth Edition, 2013.
HYPERLINK "https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Alex+Martelli%22"Alex Martelli, “Python in a Nutshell”, "O'Reilly Media, Inc., Second Edition, 2006.
HYPERLINK "https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Steven+Bird%22"Steven Bird, HYPERLINK "https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Ewan+Klein%22"Ewan Klein and HYPERLINK "https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Edward+Loper%22"Edward Loper, “Natural Language Processing with Python”, "O'Reilly Media, Inc, 2009.























LTPC2023U14CSTE25 PERL PROGRAMMING

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Demonstrate the proper use of Perl syntax, including control structures and expressions.
CO2: Apply the concept of list, arrays and hashes.
CO3: Explain the concept of file handling and references.
CO4: Develop Perl modules using built-in Perl functions as a team.
CO5: Explain the proper usage of Perl regular expressions.
.
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MWCO3MCO4MMWMCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. End Semester Exam
3. Assignments
4. SeminarCourse End Survey

INTRODUCTION TO PERL PROGRAMMING 7+3 HrsAn overview of Perl: Getting started, Scalar data – Numbers – Strings – built-in warnings - Operators – Variables - Output with print – Control structures – Getting user input – More control structures.
LISTS, ARRAYS AND HASHES6+3 HrsIntroduction to lists, simple lists, complex lists, accessing list values, list slices, ranges, combining ranges and slices. Arrays - Accessing single and multiple elements from an array - Interpolating Arrays into Strings - foreach Control Structure - array functions (pop, push, shift, unshift, and sort) – array manipulations; Introduction to Hashes – hash element access – hash functions – typical use of hash.
INPUT, OUTPUT AND FILE HANDLES6+3 HrsInput from standard input – Diamond operator – Invocation Arguments – Standard Output – Formatted Output using printf – Filehandles – Opening a file handle – Fatal errors – using filehandle – reopening a standard filehandle – output with say – Filehandles in a scalar.SUBROUTINES AND MODULES 6+3 HrsIntroduction to subroutines – Defining – Invoking – Return Values – Arguments – private variables – variable length parameter list – lexical variables – use strict pragma - return operator – non-scalar return values – Perl Modules – Finding and Installing Modules – using simple Modules.REGULAR EXPRESSION 5+3HrsIntroduction to regular expressions- simple patterns – character classes – Matching with regular expression - Processing text with regular expression – Substitutions – split operator – join function.Theory: 30 Hrs Practical: 15 Hrs Total Hours: 45

References:
HYPERLINK "http://shop.oreilly.com/product/9780596004927.do" \l "tab_04_2"Tom Christiansen, Brian D Foy, Larry Wall, Jon Orwant, “Programming Perl”, O'Reilly Media, Fourth Edition, 2012.
HYPERLINK "http://shop.oreilly.com/product/0636920018452.do" \l "tab_04_2"Randal L. Schwartz, Brian D Foy, Tom Phoenix, “Learning Perl”, O'Reilly Media, Sixth Edition, 2011.
Ellie Quigley, “Perl by Example”, Prentice Hall, Fifth Edition, 2014.
Simon Cozens, Peter Wain Wrigth, “Beginning Perl”, Wrox press, First Edition, 2000.

Other References
 HYPERLINK "http://www.perl.org/books/beginning-perl/" http://www.perl.org/books/beginning-perl/















ELECTIVE III

















LTPC3003
U14CSTE31 OPEN SOURCE TECHNOLOGIES

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the use of various open source software available in the industry.
CO2: Summarize the differences between open source and proprietary software.
CO3: Compare the technical differences between PHP, Python and Perl.
CO4: Build an open source platform to develop a project/application for solving real world problem. .
CO5: Demonstrate the interoperability among various open source tools and it s applications.
Pre-requisites:
U14CST304- Object Oriented Programming with C++
U14CST404-Database Management Systems

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MMCO4SCO5SCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Seminar
3. Assignments
4. End Semester Exam
5. Mini ProjectCourse End Survey

Introduction9 HrsIntroduction to Open Sources – Need of Open Sources – Advantages of Open Sources– Application of Open Sources - Open Source Operating Systems: LINUX: Introduction – General Overview – Kernel Mode and User Mode- Development with Linux.MySQL9 HrsIntroduction – Setting up Account –Record Selection Technology – Working with Strings – Date and Time– Sorting Query Results – Generating Summary – Working with Metadata – Using Sequences. PHP9 HrsIntroduction – Programming in Web Environment – Variables – Constants –Data; Types – Operators – Statements – Functions – Arrays – OOP – String Manipulation and Regular Expression – File Handling and Data Storage – PHP and SQL Database – PHP and LDAP – PHP Connectivity – Sending and Receiving E-mails.Python9 HrsSyntax and Style – Python Objects – Numbers – Sequences – Strings – Lists and Tuples – Dictionaries – Conditionals and Loops – Files – Input and Output – Errors and Exceptions – Functions – Modules – Classes and OOP – Execution Environment.PERL9 HrsPerl Backgrounder – Perl Overview – Perl Parsing Rules – Variables and Data – Statements and Control Structures – Subroutines - Packages and Modules - Working with Files – Data Manipulation.Theory:45Hrs Total Hours:45References:
Remy Card, Eric Dumas and Frank Mevel, “The Linux Kernel Book”, Wiley Publications, 2003
Steve Suchring, “MySQL Bible”, John Wiley, 2002
Rasmus Lerdorf and Levin Tatroe, “Programming PHP”, O’Reilly, 2002
Wesley J. Chun, “Core Phython Programming”, Prentice Hall, 2001
Martin C. Brown, “Perl: The Complete Reference”, Second edition, Tata McGraw-Hill, Indian Reprint, 2009.
Steven Holzner, “PHP: The Complete Reference”, Second edition, Tata McGraw-Hill, Indian Reprint, 2009.
Vikram Vaswani, “MYSQL: The Complete Reference”, Second edition, Tata McGraw-Hill, Indian Reprint, 2009.
Other References:
HYPERLINK "http://dev.mysql.com/doc/"http://dev.mysql.com/doc/
HYPERLINK "http://www.php.net/manual/en/"http://www.php.net/manual/en/
HYPERLINK "http://www.linux.com/learn/docs"http://www.linux.com/learn/docs
HYPERLINK "http://www.learnpython.org/"http://www.learnpython.org/
HYPERLINK "https://docs.python.org/2/tutorial/"https://docs.python.org/2/tutorial/
HYPERLINK "https://www.perl.org/books/beginning-perl/"https://www.perl.org/books/beginning-perl/










LTPC3003U14CSTE32 DIGITAL IMAGE PROCESSING

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Apply histogram equalization to images.
CO2: Outline the basics of filtering in the frequency domain.
CO3: Summarize the procedure for restoring degraded images.
CO4: Explain the basics of color image processing.
CO5: Demonstrate image segmentation for better perception of images.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes (POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSMCO2MCO3MCO4MCO5MMSCourse Assessment Methods

DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester Exam Course End Survey

INTENSITY TRANSFORMATIONS AND SPATIAL FILTERING 9 Hrs
Basic Relationship between Pixels - Intensity Transformation Functions - Histogram Processing - Fundamentals of Spatial Filtering - Smoothing Spatial Filters - Sharpening Spatial Filters
FILTERING IN FREQUENCY DOMAIN 9 Hrs
Basics of Filtering in the Frequency Domain - Image Smoothing using Frequency Domain Filters - Image Sharpening using Frequency Domain Filters - Selective Filtering
IMAGE RESTORATION 9 Hrs
Model of the Image Degradation/Restoration Process - Noise Models - Restoration using Spatial Filtering - Noise Reduction by Frequency Domain Filtering – Inverse Filtering - Wiener Filtering – Constrained Least Mean Square Filtering - Geometric Mean Filter
COLOR IMAGE PROCESSING 9 Hrs
Pseudo Color Image Processing – Basics of Full-Color Image Processing – Color Transformations – Smoothing and Sharpening – Image Segmentation based on Color – Noise in Color Images.
IMAGE SEGMENTATION 9 Hrs
Fundamentals - Point, Line, and Edge Detection - Thresholding - Region-Based Segmentation
Theory: 45 Hrs Total Hours: 45

References:
R.C. Gonzalez and R.E. Woods, “Digital Image Processing”, Third edition, Prentice Hall, 2009.
William K Pratt, “Digital Image Processing”, John Willey, 2001.
A.K. Jain, “Fundamentals of Digital Image Processing”, PHI, New Delhi, 2003.
R.C. Gonzalez, R.E. Woods and S.Eddins, “Digital Image Processing using MATLAB”, Pearson Education, 2004.
Sid Ahmed, M.A., “Image Processing Theory, Algorithms and Architectures”, McGraw Hill, 1995.













LTPC3003U14CSTE33 MULTIMEDIA SYSTEMS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain security issues and infrastructure of multimedia computing.
CO2: Explain the workings of architectures and issues for distributed multimedia systems.
CO3: Apply various compression techniques for both audio and video.
CO4: Identify the appropriate network protocol mechanism for different multimedia communication systems.
CO5: Analyze the anatomy of multimedia information system.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MWCO2MCO3SMCO4MCO5MM
Course Assessment methods:

DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester Exam
5. Mini Project Course End Survey













INTRODUCTION TO MULTIMEDIA SYSTEM 9 HrsArchitecture and components, Multimedia distributed processing model, Synchronization, Orchestration and Quality of Service (QOS) architecture. Audio and Speech: Data acquisition, Sampling and Quantization, Human Speech production mechanism, Digital model of speech production, Analysis and synthesis, Psycho-acoustics, low bit rate speech compression, MPEG audio compression.IMAGES AND VIDEO9 HrsImage acquisition and representation, Composite video signal NTSC, PAL and SECAM video standards, Bilevel image compression standards: ITU (formerly CCITT) Group III and IV standards, JPEG image compression standards, MPEG video compression standards. MULTIMEDIA COMMUNICATION9 HrsFundamentals of data communication and networking, Bandwidth requirements of different media, Real time constraints: Audio latency, Video data rate, multimedia over LAN and WAN, Multimedia conferencingHYPERMEDIA PRESENTATION9 HrsAuthoring and Publishing, Linear and non-linear presentation, Structuring Information, Different approaches of authoring hypermedia documents, Hyper-media data models and standardsMULTIMEDIA INFORMATION SYSTEMS9 HrsOperating system support for continuous media applications: limitations is usual OS, New OS support, Media stream protocol, file system support for continuous media, data models for multimedia and hypermedia information, content based retrieval of unstructured data.Theory:45Hrs Total Hours: 45References:
Ralf Steinmetz and Klara Nahrstedt, “Multimedia Systems”, Springer Berlin Heidelberg, 2010.
Andleigh Prabhat K, Thakrar Kiran , “Multimedia Systems Design”, PHI Learning, 2009.








LTPC0031U14CSPE31 OPEN SOURCE TECHNOLOGIES LABORATORY
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Demonstrate the Linux OS installation.
CO2: Build the LAMP platform in Linux OS to develop various applications.
CO3: Demonstrate the user account creation in MySQL.
CO4: Develop simple applications using Python.
CO5: Develop simple applications using Perl.

Pre-requisites:
U14CST304 - Object Oriented Programming with C++

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3MSCO4MSCO5M
Course Assessment methods:
DirectIndirect1.Model Lab Exams
2.End semester practical exam
3.Viva VoceCourse End Survey
List of experimentsObtain ISO installation disc form Ubuntu official website and installation of Ubuntu Linux.
Install and check the working of default LAMP stack in Ubuntu Linux.
Create user account in MySQL and grant different user permissions.
Use essential MySQL record selection query to extract records in a MySQL database (minimum 10 selection query).
Write a PHP program to implement the following,
Variables – Constants –Data Types – Operators – Statements – Functions – Arrays
Write a PHP program to implement object oriented concepts.
Write a PHP program to connect MySQL database and retrieve a record in HTML table.
Write a Python program to implement the following, Python Objects – Numbers – Sequences – Strings – Lists and Tuples – Dictionaries – Conditionals and Loops.
Write a Python program to implement the following,
Files – Input and Output –Functions – Modules.
Write a PERL program to implement the following,
Variables and Data – Statements and Control Structures
Write a PERL program to implement the following,
Subroutines - Packages and Modules.

Experiments beyond the syllabus should be conducted.

Total Hours: 24



































LTPC0031
U14CSPE32 DIGITAL IMAGE PROCESSING LABORATORY
Course Outcomes:
On successful completion of this course, students should be able to
CO1: Apply different Point processing operations on images and show the output.
CO2: Develop a set of filtering methods for removing noise present in images.
CO3: Demonstrate different Arithmetic operations on images and visualize the effects.
CO4: Show how histogram equalization improves images.
CO5: Illustrate the segmentation process over an image.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MSCO2SMCO3MCO4MCO5SM
Course Assessment methods
DirectIndirect1. Model Lab Exams
2. End semester practical exam
3. Viva Voce Course End Survey

List of experiments:
Point processing operations - Image negation and contrast stretching to be carried out on images.
Point processing operations - Dynamic range compression, thresholding and gray level slicing
Logic operations – Perform AND, OR, NOT, XOR operations on the given input images.
Arithmetic operations – Perform addition, subtraction, multiplication and division of two different images and display the resultant images.
Histogram equalization – Obtain the histogram of the given image and enhance the input image by equalizing its histogram.
Image enhancement using spatial filtering – Perform HPF, LPF, median filtering and high-boost filtering over the given noisy images.
Image enhancement using frequency domain filtering – Perform HPF and LPF over the given noisy images.
Image enhancement using frequency domain filtering – Perform homomorphic filter over the given noisy images.
Image segmentation – Perform point, line and edge detection of the given image.
Perform bit plane slicing and bit removal operations on the given image.

Experiments beyond the syllabus should be conducted.

References:
robotix.in/rbtx13/tutorials/category/image processing/ip_matlab
www.bogotobogo.com/Matlab/Matlab_Tutorial_Digital_Image_Processing_I.php
www.cs.otago.ac.nz/cosc451/Resources/matlab_ipt_tutorial.pdf
Total Hours: 24





















LTPC0031U14CSTE33 MULTIMEDIA SYSTEMS LABORATORY
Course Outcomes:
On successful completion of this course, students should be able to
CO1: Demonstrate simple 2D animations using animation software.
CO2: Prepare simple scenes using image editing software.
CO3: Explain the linking between web and multimedia.
CO4: Model a simple multimedia application.
CO5: Demonstrate team work towards the development of multimedia applications.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MSCO3MSCO4SCO5SMM
Course Assessment methods
DirectIndirect1.Model Lab Exams
2. End Semester Practical Exam
3. Viva VoceCourse End Survey
List of experiments:
Animate - Shooting a bullet towards a target.
Animate an Analog Clock.
Animate - Bird on a Journey.
Animate the designs as seen in a Kaleidoscope on rotation
Using spotlight effect, display your name.
Animate a Car Race.
Animate 3 different colored balls bouncing. (Random motion of balls)
Prepare a HTML program making a call to a flash program.
Create a landscape scene using Adobe Photoshop.
Use images of individuals to create a group photo and separate individual images from group photo
Create a mirror image of a scene containing a person and a few objects in the background.
Construct a flower vase using photographic images of a jar and individual flowers.

Experiments beyond the syllabus should be conducted.
Total Hours: 24






ELECTIVE IV


















LTPC3104U14CSTE41 NATURAL LANGUAGE PROCESSING

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Outline Natural Language Processing tasks in syntax, semantics, and pragmatics.
CO2: Explain Morphology and Part of Speech Tagging.
CO3: Show how syntax parsing techniques can be used.
CO4: Explain the use of semantic analysis methods.
CO5: Relate a few applications of NLP.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MMCO4SMCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey

INTRODUCTION9+3HrsNatural Language Processing tasks in syntax, semantics, and pragmatics – Issues - Applications - The role of machine learning - Probability Basics –Information theory – Collocations -N-gram Language Models - Estimating parameters and smoothing - Evaluating language models.MORPHOLOGY AND PART OF SPEECH TAGGING9+3HrsLinguistic essentials - Lexical syntax- Morphology and Finite State Transducers - Part of speech Tagging - Rule-Based Part of Speech Tagging - Markov Models - Hidden Markov Models – Transformation based Models - Maximum Entropy Models - Conditional Random Fields
SYNTAX PARSING9+3HrsSyntax Parsing - Grammar formalisms and tree banks - Parsing with Context Free Grammars - Features and Unification -Statistical parsing and probabilistic CFGs (PCFGs)-Lexicalized PCFGs.SEMANTIC ANALYSIS9+3HrsRepresenting Meaning – Semantic Analysis -Lexical semantics –Word-sense disambiguation - Supervised – Dictionary based and Unsupervised Approaches - Compositional semantics-Semantic Role Labeling and Semantic Parsing– Discourse Analysis. APPLICATIONS  9+3 HrsNamed entity recognition and relation extraction- IE using sequence labeling- Machine Translation (MT) - Basic issues in MT - Statistical translation - word alignment-phrase - based translation – Question AnsweringTheory:45Hrs Tutorial: 15 Hrs Total Hours:60References:
Daniel Jurafsky and James H. Martin, “Speech and Language Processing”, Second Edition, Prentice Hall, 2008.
Steven Bird, Ewan Klein and Edward Loper, “Natural Language Processing with Python”, O'Reilly Media, First Edition, 2009.
Roland R. Hausser, “Foundations of Computational Linguistics: Human- Computer Communication in Natural Language”, Paperback, MIT Press, 2011.
Pierre M. Nugues, “An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies)”, Soft cover reprint, 2010.

Other References:
NLTK – Natural Language Tool Kit - HYPERLINK "http://www.nltk.org/"http://www.nltk.org/














LTPC3024U14CSTE42 MOBILE APPLICATION DEVELOPMENT USING ANDROID
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the mobility landscape.
CO2: Explain the mobile apps development aspects.
CO3: Design and develop mobile apps, using Android as development platform, with key focus on user experience design, native data handling and background tasks and notifications.
CO4: Identify difference of native hardware play, location awareness, graphics, and multimedia.
CO5: Demonstrate testing, signing, packaging and distribution of mobile applications.

Pre-requisites:
U14CSP401 – Java Programming Laboratory

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MMCO4MCO5MM
Course Assessment methods:
DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.Mini Project
5.End Semester ExamCourse End Survey

 `

GETTING STARTED WITH MOBILITY8+3 HrsMobility landscape-Mobile platforms-Mobile apps development-Overview of Android platform- setting up the mobile app development environment along with an emulator- a case study on Mobile app developmentnd Business rsity of Pune.
BUILDING BLOCKS OF MOBILE APPS15+5 HrsApp user interface designing – mobile UI resources (Layout, UI elements, Draw-able, Menu), Activity- states and life cycle, interaction amongst activities.
App functionality beyond user interface - Threads, Async task, Services – states and lifecycle, Notifications, Broadcast receivers, Telephony and SMS APIs
Native data handling – on-device file I/O, shared preferences, mobile databases such as SQLite, and enterprise data access (via Internet/Intranet).
SPRUCING UP MOBILE APPS10+4 HrsGraphics and animation – custom views, canvas, animation APIs, multimedia – audio/video playback and record, location awareness, and native hardware access (sensors such as accelerometer and gyroscope).TESTING MOBILE APPS8+2 HrsDebugging mobile apps-White box testing, Black box testing- and test automation of mobile apps- JUnit for Android- Robotium- MonkeyTalk.TAKING APPS TO MARKET  4+1 HrsVersioning-signing and packaging mobile apps- distributing apps on mobile market place.
Theory: 45 Hrs Practical: 15 Hrs Total Hours:60References:
Anubhav Pradhan, Anil V. Deshpande, “Composing Mobile Apps: Learn. Explore. Apply. Using Android”, Wiley publication, 2014.
Barry Burd, “Android Application Development All in one for Dummies”, John Wiley & Sons publication,2011.
“Teach Yourself Android Application Development in 24 Hours”, Third edition, SAMS publication, 2013.










LTPC3024U14CSTE43 INTERNET OF THINGS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Identify and design the new models for market strategic interaction.
CO2: Develop business intelligence and information security for IoT.
CO3: Compare various protocols for IoT.
CO4: Develop a middleware for IoT.
CO5: Develop different models for network dynamics.

Pre-requisites:
U14CST502 Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2MMCO3MMCO4MMMCO5MMM
Course Assessment methods:
DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester ExamCourse End Survey


INTRODUCTION 10 +3 HrsDefinitions and Functional Requirements –Motivation – Architecture - Web 3.0 View of IoT– Ubiquitous IoT Applications – Four Pillars of IoT – DNA of IoT - The Toolkit Approach for End-user Participation in the Internet of Things. Middleware for IoT: Overview – Communication middleware for IoT –IoT Information Security.

IOT PROTOCOLS8 +3HrsProtocol Standardization for IoT – Efforts – M2M and WSN Protocols – SCADA and RFID Protocols –Issues with IoT Standardization – Unified Data Standards – Protocols – IEEE 802.15.4 – BACNet Protocol – Modbus – KNX – Zigbee Architecture – Network layer – APS layer – Security
WEB OF THINGS 10+4 HrsWeb of Things versus Internet of Things – Two Pillars of the Web – Architecture standardization for WoT– Platform Middleware for WoT – Unified Multitier WoT Architecture – WoT Portals and Business Intelligence. Cloud of Things: Grid/SOA and Cloud Computing–Cloud Middleware – Cloud Standards – Cloud Providers and Systems – Mobile Cloud Computing – The Cloud of Things Architecture
.INTEGRATED 9+3 HrsIntegrated Billing Solutions in the Internet of Things Business Models for the Internet of Things - Network Dynamics: Population Models – Information Cascades - Network Effects – Network Dynamics: Structural Models - Cascading Behavior in Networks - The Small-World Phenomenon.
APPLICATIONS 8+2 HrsThe Role of the Internet of Things for Increased Autonomy and Agility in Collaborative Production Environments - Resource Management in the Internet of Things: Clustering, Synchronisation and Software Agents. Applications - Smart Grid – Electrical Vehicle Charging.Theory:45 Hrs Practical: 15 Hrs Total Hours:60
References:Honbo Zhou, “The Internet of Things in the Cloud: A Middleware Perspective”, CRC Press, 2012.
Dieter Uckelmann, Mark Harrison, Florian Michahelles, “Architecting the Internet of Things”, Springer, 2011.
David Easley and Jon Kleinberg, “Networks, Crowds, and Markets: Reasoning About a Highly Connected World”, Cambridge University Press, 2010.
Olivier Hersent, Omar Elloumi and David Boswarthick, “The Internet of Things: Applications to the Smart Grid and Building Automation”, Wiley, 2012.
Olivier Hersent, David Boswarthick, Omar Elloumi, “The Internet of Things – Key applications and Protocols”, Wiley, 2012.Other Reference:
1.HYPERLINK "http://nptel.ac.in/courses/106105081/"http://nptel.ac.in/courses/106105081/














ELECTIVE V

















LTPC3104U14CSTE51 REAL TIME SYSTEMS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain about typical real-time applications, hard versus soft real-time systems
CO2: Explain about commonly used approaches to real-time scheduling
CO3: Summarize about clock-driven scheduling
CO4: Outline the knowledge about priority-driven scheduling of periodic tasks
CO5: Express about resources and resource access control

Pre-requisites:
U14CST402 - Operating Systems
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMMCO2MM CO3MWCO4MMCO5MMCourse Assessment methods:
DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester ExamCourse End Survey
TYPICAL REAL-TIME APPLICATIONS, HARD VERSUS SOFT REAL-TIME SYSTEMS  9+3 HrsJobs and Processors, Release Times, Deadlines and Timing Constraints, Hard and Soft Timing Constraints, Hard Real-time systems, Soft Real-time systems. A Reference Model of Real-time system: Processors and Resources, Temporal Parameters of Real-time Workload, Periodic Task Model, Precedence Constraints and Data Dependency, Other types of Dependencies, Functional Parameters, Resource Parameters of Jobs and Parameters of Resources, Scheduling Hierarchy.





COMMONLY USED APPROACHES TO REAL-TIME SCHEDULING 9+3 HrsClock driven Approach, Weighted Round-Robin Approach, Priority Driven Approach, Dynamic versus Static Systems, Effective Release Times and Deadlines, Optimality of the EDF and LST Algorithms, Non optimality of the EDF and LST Algorithms, Challenging in Validating Timing Constraints in Priority-Driven Systems, Off-Line versus On-Line Scheduling.CLOCK-DRIVEN SCHEDULING9 +3 HrsNotation and Assumptions, Static, Timer Driven Scheduler, General Structure of Cyclic Schedules, Cyclic Executives, Improving the Average Response Time of Aperiodic Jobs, Scheduling Sporadic Jobs, Practical Consideration and Generalizations, Algorithms for Constructing Static Schedules, Pros and Cons of Clock-Driven Scheduling.PRIORITY-DRIVEN SCHEDULING OF PERIODIC TASKS9+3 HrsStatic Assumption, Fixed-Priority versus Dynamic-Priority Algorithms, Maximum Schedulable Utilization, Optimality of the RM and DM Algorithms, A Schedulability Test for Fixed-Priority Tasks with Short Response Times, Schedulability Test for Fixed-Priority Tasks with Arbitrary Response Times, Sufficient Schedulability Conditions for the RM and DM Algorithms. Scheduling Aperiodic and Sporadic Jobs in Priority-Driven Systems Assumption and Approaches, Deferrable Servers, Sporadic Servers, Constant Utilization, Total Bandwidth, and Weighted Fair Queuing Servers, Scheduling of Sporadic Jobs, Real-time Performance for Jobs with Soft Timing Constraints.RESOURCES AND RESOURCE ACCESS CONTROL 9+3 HrsEffects of Resource Contention and Resource Access Control, Non-preemptive Critical Sections, Basic Priority-Inheritance Protocol, Basic Priority-Ceiling Protocol, Stack-Based Priority-Ceiling (Ceiling-Priority) Protocol, Use of Priority-Ceiling Protocol in Dynamic-Priority Systems, Preemption-Ceiling Protocol, Controlling Accesses to Multiple-Unit ResourcesTheory: 45Hrs Tutorial: 15 Hrs Total Hours: 60References:
1. Thomas Connolly and Carlolyn Begg, “Database Systems, A Practical Approach to Design, Implementation and Management”, Sixth Edition, Pearson Education, 2015.
2. R. Elmasri, S.B. Navathe, “Fundamentals of Database Systems”, Sixth Edition, Pearson Education, 2011.
3. Abraham Silberschatz, Henry F. Korth, S. Sudharshan, “Database System Concepts”, Sixth Edition, Tata McGraw Hill, 2011.
4. C.J.Date, A.Kannan, S.Swamynathan, “An Introduction to Database Systems”, Eighth Edition, Pearson Education, 2009.

LTPC3104

U14CSTE52 HIGH SPEED NETWORKS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Summarize the mechanisms to provide high speed networking through case studies of ATM and frame relay networks.
CO2: Construct queuing system with different arrival and service rates.
CO3: Analyze the performance of various congestion control and admission control mechanisms.
CO4: Analyze various QoS parameters needed for real time traffic.
CO5: Explain the protocols needed for QoS support.

Pre-requisites:
U14CST502- Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MWWCO3MWCO4MWCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2.Seminar
3.Assignments
4.End Semester Exam
5.Mini ProjectCourse End Survey

HIGH PERFORMANCE NETWORKS 9+3 HrsFrame Relay Networks – Asynchronous Transfer Mode – Asynchronous Transfer Mode (ATM) Protocol Architecture - ATM Logical Connection - ATM Cell – ATM Service Categories – ATM Adaptation Layer (AAL) - High Speed LANs: Fast Ethernet - Gigabit Ethernet - Fibre Channel.QUEUING MODELS AND CONGESTION MANAGEMENT8 +3 HrsQueuing Analysis- Queuing Models – Single Server Queues – Effects of Congestion – Congestion Control – Traffic Management – Congestion Control in Packet Switching Networks.ATM CONGESTION CONTROL 12 +3 HrsPerformance of TCP over ATM - Traffic and Congestion control in ATM – Requirements – Attributes – Traffic Management Frame Work - Traffic Control – Available Bit Rate (ABR) Traffic Management – ABR Rate Control - Resource Management (RM) Cell Formats - ABR Capacity Allocations.INTEGRATED AND DIFFERENTIATED SERVICES8+3 HrsIntegrated Services Architecture – Approach - Components - Services - Queuing Discipline - Fair Admission Control - Traffic Shaping - Resource Reservation Queuing (FQ) - Processor Sharing (PS) - Bit-Round Fair Queuing (BRFQ) - Generalized Processor Sharing (GPS) - Weighted Fair Queuing (WFQ) – Random Early Detection - Differentiated Services DS code points – Per Hop Behavior.PROTOCOLS FOR QOS SUPPORT 8+3 HrsResource Reservation (RSVP) – Goals & Characteristics - Data Flow - RSVP operations - Protocol Mechanisms – Multiprotocol Label Switching – Operations - Label Stacking - Protocol details – Real Time Protocol (RTP) – Protocol Architecture - Data Transfer Protocol - Real Time Control Protocol (RTCP).Theory:45 Hrs Tutorial:15 Hrs Total Hours:60 References:
William Stallings, “High Speed Networks and Internet”, Pearson Education, Second Edition, 2002.
Warland & PravinVaraiya, “High Performance Communication Networks”, Jean Harcourt Asia Pvt. Ltd., Second edition, 2001.
IrvanPepelnjk, Jim Guichard and Jeff Apcar, “MPLS and VPN architecture”, Cisco Press, Volume 1 and 2, 2003.













LTPC3104U14CSTE53 PATTERN RECOGNITION

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Summarize on supervised and unsupervised classification methods for various pattern recognition problems.
CO2: Identify appropriate clustering techniques for various problems with high dimensional data.
CO3: Explain about various structural pattern recognition models.
CO4: Outline feature extraction and subset selection methods for various applications.
CO5: Explain about the neural networks for pattern recognition problems and Fuzzy Pattern Classifiers.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2MWCO3MMCO4MMCO5M
Course Assessment methods:
DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester ExamCourse End Survey


PATTERN CLASSIFIER  10+3 HrsOverview of pattern recognition – Discriminant functions – Supervised learning – Parametric estimation – Maximum likelihood estimation – Bayesian parameter estimation – Perceptron algorithm – LMSE algorithm – Problems with Bayes approach – Pattern classification by distance functions – Minimum distance pattern classifier.UNSUPERVISED CLASSIFICATION  8+3 HrsClustering for unsupervised learning and classification – Clustering concept – C-means algorithm – Hierarchical clustering procedures – Graph theoretic approach to pattern clustering – Validity of clustering solutions.STRUCTURAL PATTERN RECOGNITION  8 +3 HrsElements of formal grammars – String generation as pattern description – Recognition of syntactic description – Parsing – Stochastic grammars and applications – Graph based structural representationFEATURE EXTRACTION AND SELECTION  9 +3HrsEntropy minimization – Karhunen – Loeve transformation – Feature selection through functional approximation – Binary feature selection.RECENT ADVANCES  10 +3HrsNeural network structures for Pattern Recognition – Neural network based Pattern associators – Unsupervised learning in neural Pattern Recognition – Self-organizing networks – Fuzzy logic – Fuzzy pattern classifiers – Pattern classification using Genetic Algorithms.Theory:45Hrs Tutorial:15 Hrs Total Hrs: 60 HrsReferences:
Robert J.Schalkoff, “Pattern Recognition Statistical, Structural and Neural Approaches”, Wiley, India, 2009.
M. Narasimha Murthy and V. Susheela Devi, “Pattern Recognition”, Springer 2011.
HYPERLINK "http://library.alibris.com/search/books/author/Konstantinos-Koutroumbas-Sergios-Theodoridis"Sergios Theodoridis, Konstantinos Koutroumbas, “HYPERLINK "http://library.alibris.com/booksearch.detail?invid=11391159340&qcond=6&browse=1&qwork=7659098&mtype=B&qsort=&page=1"Pattern Recognition & Matlab Introduction”, Fourth edition, Acadamic press, 2010
HYPERLINK "http://as.wiley.com/WileyCDA/Section/id-302477.html?query=Andrew+R.+Webb"Andrew R. Webb, HYPERLINK "http://as.wiley.com/WileyCDA/Section/id-302477.html?query=Keith+D.+Copsey"Keith D. Copsey, “Statistical Pattern Recognition”, Third Edition, Wiley, 2011.
Duda R.O., Har P.E.,and David G Stork, “Pattern Classification”, Second edition, John Wiley & Sons, NewYork, 2012.
 HYPERLINK "http://www.amazon.in/S.N.-Deepa/e/B00J70LKLC/ref=dp_byline_cont_book_1"S.N. Deepa , HYPERLINK "http://www.amazon.in/S.N.-Sivanandam/e/B00J70LMJC/ref=dp_byline_cont_book_2"S.N. Sivanandam, “Principles of Soft Computing”, Second Edition, Wiley, 2012.
Tou and Gonzales, “Pattern Recognition Principles”, Wesley Publication Company, London, 1974.









LTPC3014U14CSTE54 MACHINE LEARNING TECHNIQUES
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Describe the basic concepts of Machine Learning theory.
CO2: Outline the needs and application of various types of learning.
CO3: Identify suitable Supervised or Unsupervised learning methods for an application.
CO4: Apply machine learning techniques in neural networks to solve real world problems.
CO5: Identify applications suitable for different types of machine learning models.

Pre-requisites:
U14CST601 - Artificial Intelligence
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MWCO3SCO4MMWWCO5SWCourse Assessment methods:
DirectIndirect1.Internal Tests
2.Seminar
3.Assignments
4.End Semester ExamCourse End Survey

INTRODUCTION AND SUPERVISED LEARNING 9 +3 Hrs
Introduction to Machine Learning – basic concepts in machine learning - Examples of machine learning applications -Supervised Learning: Learning a Class from Examples–VC Dimension – PAC Learning -–Noise–Learning Multiple Classes–Regression–Model Selection and Generalization – Dimensions of a supervised machine learning algorithm. Bayesian Decision Theory: Classification–Losses and Risks– Discriminant Functions– Utility Theory - Association rules.
PARAMETRIC AND SEMI-PARAMETRIC METHODS9+3 Hrs Parametric Methods: Maximum Likelihood Estimation–Evaluating an Estimator–Bayes’ Estimator–Parametric Classification–Regression–Tuning Model Complexity–Model Selection Procedures. Multivariate Methods: Data–Parameter Estimation–Estimation of Missing Values–Multivariate Normal Distribution–Multivariate Classification and Regression. Semi parametric method: Clustering k–Means Clustering–Expectation–Maximization Algorithm–Latent Variable Models–Hierarchical Clustering.
NONPARAMETRIC METHODS AND LINEAR MODEL9 +3HrsNonparametric Methods: Nonparametric Density Estimation and Classification-Generalization to Multivariate Data–Condensed Nearest Neighbor–Smoothing Models. Decision Trees: Univariate Trees–Pruning–Rule Extraction–Learning Rules–Multivariate Trees. Linear Model:Linear classification – univariate linear regression – multivariate linear regression – regularized regression – Logistic regression.
MULTILAYER PERCEPTRONS AND LOCAL MODEL9+3 HrsMultilayer perceptrons: Perceptron - Training a Perceptron– Learning Boolean Functions – multilayer perceptron – MLP as a universal Approximator – back propogation algorithm - Training Procedures- Tuning the Network Size – Bayesian View of Learning – Learning Time - Local Models: Competitive Learning – Radial Basis Functions – Rule Based Knowledge –Normalized and Competitive Basis Functions– Learning Vector Quantization – Mixture of Experts.
GRAPHICAL MODEL, MULTIPLE LEARNERS AND REINFORCEMENT LEARNING 9+3 HrsGraphical Model- canonical cases for conditional Independence – example graphical models –Belief propagation - undirected graph – learning the structure of graphical model. Combining Multiple Learners: Voting–Error–Correcting Output Codes–Bagging–Boosting–Stacked Generalization–Cascading–Reinforcement Learning: Single State Case–Elements of Reinforcement Learning–Model–Based Learning–Temporal Difference Learning–Generalization.Theory: 45 Hrs Tutorial: 15 Hrs Total Hours:60
References:
Ethem Alpaydin, “Introduction to Machine Learning”, Second Edition, MIT Press, 2013
Y. S. Abu-Mostafa, M. Magdon-Ismail, and H.-T. Lin, “Learning from Data”, AML Book Publishers, 2012.
K. P. Murphy, “Machine Learning: A probabilistic perspective”, MIT Press, 2012.
M. Mohri, A. Rostamizadeh, and A. Talwalkar, “Foundations of Machine Learning”, MIT Press, 2012.














ELECTIVE VI















LTPC3003U14GST004 OPERATIONS RESEARCH

Course Outcomes:
After successful completion of this course, students should be able to
Apply linear programming model and assignment model to domain specific situations
Analyze the various methods under transportation model and apply the model for testing the closeness of their results to optimal results
Apply the concepts of PERT and CPM for decision making and optimally managing
projects
Analyze the various replacement and sequencing models and apply them for arriving at optimal decisions
Analyze the inventory and queuing theories and apply them in domain specific situations.
Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SCO3MMMCO4SCO5MS
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3.Seminar
4. End Semester ExamCourse End Survey

LINEAR MODEL 9 Hrs
The phases of OR study – formation of an L.P model – graphical solution – simplex algorithm – artificial variables technique (Big M method, two phase method), duality in simplex.

TRANSPORTATION AND ASSIGNMENT MODELS 9 Hrs
Transportation model – Initial solution by North West corner method – least cost method – VAM. Optimality test – MODI method and stepping stone method.
Assignment model – formulation – balanced and unbalanced assignment problems.





PROJECT MANAGEMENT BY PERT & CPM 9 Hrs
Basic terminologies – Constructing a project network – Scheduling computations – PERT - CPM – Resource smoothening, Resource leveling, PERT cost.

REPLACEMENT AND SEQUENCING MODELS 9 Hrs
Replacement policies - Replacement of items that deteriorate with time (value of money not changing with time) – Replacement of items that deteriorate with time (Value of money changing with time) – Replacement of items that fail suddenly (individual and group replacement policies).
Sequencing models- n job on 2 machines – n jobs on 3 machines – n jobs on m machines, Traveling salesman problem.

INVENTORY AND QUEUING THEORY 9 Hrs
Variables in inventory problems, EOQ, deterministic inventory models, order quantity with price break, techniques in inventory management.
Queuing system and its structure  Kendall s notation  Common queuing models - M/M/1: FCFS/"/" - M/M/1: FCFS/n/" - M/M/C: FCFS/"/" - M/M/1: FCFS/n/m

Theory: 45 Hrs Total Hours: 45
References:
Taha H.A., “Operation Research”, Pearson Education
Hira and Gupta “Introduction to Operations Research”, S.Chand and Co.2002
Hira and Gupta “Problems in Operations Research”, S.Chand and Co.2008
Wagner, “Operations Research”, Prentice Hall of India, 2000
S.Bhaskar, “Operations Research”, Anuradha Agencies, Second Edition, 2004












LTPC3003U14ECTE81 ANALOG AND DIGITAL COMMUNICATION

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Describe various Analog modulation techniques.
CO2: Describe various Digital modulation techniques.
CO3: Differentiate various Pulse modulation schemes.
CO4: Relate Data communication standards.
CO5: Discuss spread spectrum and multiple access techniques.

Pre-requisites: Nil
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme outcomesPO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SMCO2 SMCO3 SWCO4 M       CO5 MW       
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey

FUNDAMENTALS OF ANALOG COMMUNICATION 9 Hrs
Principles of Amplitude Modulation - AM Envelope - Frequency Spectrum and Bandwidth - Modulation Index and Percent Modulation - AM Voltage Distribution - AM Power Distribution – Angle Modulation - FM and PM Waveforms - Phase Deviation and Modulation Index - Frequency Deviation and Percent Modulation - Frequency Analysis of Angle Modulated Waves. Bandwidth Requirements for Angle Modulated Waves - Average Power of An Angle Modulated Waves.

DIGITAL COMMUNICATION 9 Hrs
Introduction - Shannon Limit for Information Capacity - Digital Amplitude Modulation - Frequency Shift Keying - FSK Bit Rate and Baud - FSK Transmitter - BW Consideration of FSK - FSK Receiver - Phase Shift Keying – Binary Phase Shift Keying – QPSK - Quadrature Amplitude Modulation - Bandwidth Efficiency - Carrier Recovery – Squaring Loop - Costas Loop – DPSK.

DIGITAL TRANSMISSION 9 Hrs
Introduction - Pulse Modulation - PCM – PCM Sampling - Sampling Rate - Signal To Quantization Noise Rate - Companding – Analog and Digital – Percentage Error - Delta Modulation - Adaptive Delta Modulation - Differential Pulse Code Modulation - Pulse Transmission – Intersymbol Interference - Eye Patterns.

DATA COMMUNICATIONS 9 Hrs
Introduction - History of Data Communications - Standards Organizations for Data Communication - Data Communication Circuits - Data Communication Codes - Error Control - Error Detection - Error Correction - Data Communication Hardware - Serial and Parallel Interfaces - Data Modems - Asynchronous Modem - Synchronous Modem - Low-Speed Modem - Medium and High Speed Modem - Modem Control.

SPREAD SPECTRUM AND MULTIPLE ACCESS TECHNIQUES 9 Hrs
Introduction - Pseudo-Noise Sequence - DS Spread Spectrum With Coherent Binary PSK - Processing Gain - FH Spread Spectrum - Multiple Access Techniques – Wireless Communication - TDMA and CDMA in Wireless Communication Systems

Theory: 45 Hrs Total Hours: 45

References:
Wayne Tomasi, ‘Electronic Communication Systems’, Pearson Education, Third Edition, 2001.
Simon Haykin, “Communication Systems”, John Wiley & Sons, Fourth Edition, 2001.
Taub, D L Schilling and G Saha, ”Principles of Communication”, Third Edition, 2007.
B.P.Lathi, ”Modern Analog and Digital Communication Systems”, Oxford University Press, Third Edition, 2007.
Blake, “Electronic Communication Systems”, Thomson Delmar Publications, 2002.
Martin S.Roden, “Analog and Digital Communication System”, Prentice Hall of India, Third Edition, 2002.
B.Sklar,”Digital Communication Fundamentals and Applications”, Pearson Education, Second Edition, 2007.












LTPC3003U14CSTE61 CYBER FORENSICS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the role of forensics in preventing various forms of fraud.
CO2: Develop skills in distinguishing various types of computer crimes and identify the digital fingerprints associated with criminal activities.
CO3: Illustrate how to apply different forensic analysis tools to recover important evidence for identifying computer crimes.
CO4: Explain about threats and compare various threats.
CO5: Summarize the need for surveillance and list the tools used.

Pre-requisites:
Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes (POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2MCO3MSCO4MMCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey
TYPES OF COMPUTER FORENSICS 9 Hrs
Computer Forensics Fundamentals – Types of Computer Forensics Technology –Types of Vendor and Computer Forensics Services

DATA RECOVERY 9 Hrs
Data Recovery – Evidence Collection and Data Seizure – Duplication and Preservation
of Digital Evidence – Computer Image Verification and Authentication

ELECTRONIC EVIDENCE 9Hrs
Discover of Electronic Evidence – Identification of Data – Reconstructing Past Events –Networks.

THREATS 9 Hrs
Fighting against Macro Threats – Information Warfare Arsenal – Tactics of the Military – Tactics of Terrorist and Rogues – Tactics of Private Companies.
SURVEILLANCE 9 Hrs
The Future – Arsenal – Surveillance Tools – Victims and Refugees – Advanced Computer Forensics.
Theory: 45 Hrs Total Hours: 45
References:
John R. Vacca, “Computer Forensics”, Charles River Media, 2005.
Chad Steel, “Windows Forensics”, Wiley India, 2006.
Majid Yar, “Cybercrime and Society”, Sage Publications, 2006
Robert M Slade, “Software Forensics”, Tata McGraw Hill, 2004

Other References:
1. cdac.in › Cyber Security and Forensics
2. searchsecurity.techtarget.com/definition/computer-forensics
3. forensiccontrol.com › Resources



















LTPC3003U14CSTE62 ADVANCED DATABASE TECHNOLOGIES
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the fundamentals of distributed database.
CO2: Outline the importance of backup and recovery techniques in distributed database systems.
CO3: Apply the object oriented concepts in relational databases.
CO4: Summarize the concepts of various enhanced data models.
CO5: Explain the concepts of different emerging database technologies.
Pre-requisites:
1. U14CST404-Data Base Management Systems

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3MSMCO4MSCO5MWM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Model Exam
3. Assignment
4. Seminar
5.End Semester Exam1. Course End Survey
DISTRIBUTED DBMS - CONCEPTS AND DESIGN 9 HrsIntroduction- Functions and architecture of DDBMS - Distributed Relational Database design – Transparency in DDBMS – Date’s Twelve Rules for a DDBMS.






DISTRIBUTED DBMS - ADVANCED CONCEPTS 
9 HrsDistributed Transaction Management – Concurrency control – Deadlock Management – Database Recovery – The X/Open Distributed Transaction Processing Model –Replication Servers – Distribution and Replication in Oracle.OBJECT ORIENTED AND RELATIONAL DATABASE 9 HrsConcepts for object databases: Object identity –Object structure –Type constructors –Encapsulation of operations –Methods –Persistence –Type and class hierarchies –Inheritance –Complex objects–Object database standards, languages and design: ODMG model –ODL –OQL –Object relational and extended –Relational systems: Object relational features in SQL / Oracle.
ENHANCED DATA MODELS9 HrsActive database concepts and triggers–Temporal databases–Spatial databases–Multimedia databases–Deductive databases –XML databases: XML data model –DTD-XML schema-XML querying -Geographic information systems-Genome data management.EMERGING TECHNOLOGIES9 HrsMobile Databases: Location and handoff management-Effect of mobility on data management –Location dependent data distribution -Mobile transaction models -Concurrency control -Transaction commit protocols. Case study: Information retrieval-Web databases.
Theory:45 Hrs Total Hours: 45
References:
Thomas Cannolly and Carolyn Begg, “Database Systems, A Practical Approach to Design,Implementation and Management”, Sixth Edition, Pearson Education, 2014.
Ramez Elmasri and Shamkant B.Navathe, “Fundamentals of Database Systems”, Eighth edition, Pearson Education, 2011.
M.Tamer Ozsu and Patrick Ualduriel, “Principles of Distributed Database Systems”,
Second edition, Pearson Education, 2008.
C.S.R Prabhu, “Object-Oriented Database Systems”, Prentice Hall Of India, Third
Edition, 2011.
Peter Rob and Corlos Coronel, “Database Systems – Design, Implementation and Management”, Thompson Learning, Course Technology, Fifth edition, 2010.Other References:
1. HYPERLINK "http://cs.uwindsor.ca/~cezeife/courses/60-415/notes/415notes.pdf"http://cs.uwindsor.ca/~cezeife/courses/60-415/notes/415notes.pdf
2. HYPERLINK "http://nptel.iitm.ac.in/video.php?subjectId=106106093"http://nptel.iitm.ac.in/video.php?subjectId=106106093
3. http://personalpages.manchester.ac.uk/staff/GNenadic/CN3023/






LTPC3003U14CSTE63 TCP/IP AND SOCKET PROGRAMMING
Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Explain the principles of internetworking protocols.
CO2: Summarize the functions of transport protocols.
CO3: Explain the concepts of routing, subnetting and supernetting.
CO4: Explain the concepts of elementary socket programming.
CO5: Demonstrate client server applications using socket programming.

Pre-requisites:
U!4CST502- Computer Networks
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SWCO3SWCO4MCO5MW
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey

ELEMENTARY TCP SOCKETS9 HrsIntroduction to Sockets – Socket Address Structures – Byte Ordering Functions – Byte Manipulation Functions – Elementary TCP Sockets – Socket, Connect, Bind, Listen, Accept, Read, Write, Close Functions – Iterative Server – Concurrent Server.APPLICATION DEVELOPMENT9 HrsTCP Echo Server – TCP Echo Client – UDP Echo Server – UDP Echo Client – Server with Multiple Clients – Boundary Conditions: Server Process Crashes - Server Host Crashes - Server Crashes and Reboots - Server Shutdown – I/O multiplexing – I/O Models – Select Function – Shutdown Function – Poll Function.






SOCKET OPTIONS, ELEMENTARY NAME & ADDRESS CONVERSIONS9 HrsSocket Options – getsocket and setsocket Functions – Generic Socket Options – IP Socket Options – ICMP Socket Options – TCP Socket Options – Elementary UDP Sockets –Domain Name System – gethostbyname Function – gethostbyaddr Function – getservbyname and getservbyport Functions. INTERNET PROTOCOLS – I9 HrsInternetworking Concept and Architectural Model – Classful Internet Addresses -Mapping Internet Addresses to Physical Addresses (ARP) - Determining an Internet Address at Startup (RARP) - Internet Protocol: Connectionless Datagram Delivery - Internet Protocol: Routing IP Datagrams - Internet Protocol: Error and Control messages (ICMP) – Classless Inter Domain Routing (CIDR) – Classless Addressing (Supernetting) – The Effect of Supernetting on Routing – CIDR Address Blocks and Bit Masks – Address Blocks and CIDR Notation.INTERNET PROTOCOLS – II9 HrsReliable Stream Transport Service (TCP) – Timeout and Retransmission – Accurate Measurement of Round Trip Samples - Karn’s Algorithm and Timer Backoff – Establishing a TCP Connection – Closing a TCP Connection – TCP Connection Reset – TCP State Machine – Silly Window Syndrome and Small Packets – Avoiding Silly Window Syndrome - Internet Multicasting -Internet Group Management Protocol (IGMP) - IGMP Implementation - Group Membership State Transitions -IGMP Message Format - Auto configuration (DHCP) - IPv6 : Features of IPv6- General form of an IPv6 Datagram - IPv6 Base Header Format - IPv6 Extension Headers - Parsing an IPv6 Datagram - IPv6 Fragmentation and Reassembly -The Consequence of End to End Fragmentation - IPv6 Source Routing - IPv6 options.Theory:45Hr Total Hours:45References:Richard Stevens, "UNIX Network Programming, the sockets Networking API", Volume 1, Pearson education Asia, Third edition, 2010
Douglas E. Comer, “Internetworking with TCP/IP Volume – I”, Fifth Edition, Prentice Hall, 2010.
Comer D.E., Stevens D.L., “Internetworking with TCP/IP Volume II: Design, Implementation, and Internals”, Third edition, PHI, 2009.
Comer D.E., “Internetworking with TCP/IP Volume- III”, (BSD Sockets Version), Second edition, PHI, 2006.
Behrouz A. Forouzan, “TCP / IP Protocol Suite”, Fifth edition, Tata McGraw Hill, 2013.
Other References:
HYPERLINK "http://nptel.ac.in/courses/106105082/35"http://nptel.ac.in/courses/106105082/35
HYPERLINK "http://nptel.ac.in/courses/106105081/"http://nptel.ac.in/courses/106105081/













ELECTIVE VII








LTPC3003U14CSTE71 SERVICE ORIENTED ARCHITECTURE

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the fundamental principles of SOA.
CO2: Organise the services to perform the service composition.
CO3: Model and design a service-oriented system using architectural principles, development
methods with SOA and related technologies to solve the real life problem.
CO4: Outline the technologies used for SOA implementation.
CO5: Demonstrate software development using SOA as a team.
Pre-requisites:
1. U14CST503 - XML and Web Services
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1WCO2SCO3SSCO4MCO5SSSCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. Mini Project
5.End Semester Exam Course End Survey

INTRODUCTION9 HrsThe Evolution of SOA –Characteristics of SOA – Introducing SOA.WEB SERVICES AND SOA9 HrsWeb services – Service descriptions – Messaging with SOAP –Message exchange Patterns – Coordination –Atomic Transactions – Business activities – Orchestration – Choreography - Service layer abstraction – Application Service Layer – Business Service Layer – Orchestration Service Layer.


SERVICE ORIENTATION9 HrsService oriented analysis – Business-centric SOA – Deriving business services- service modeling - Service Oriented Design – WSDL basics – SOAP basics – SOA composition guidelines – Entity-centric business service design – Application service design – Task centric business service design.SOA PLATFORMS9 Hrs SOA platform basics – SOA support in J2EE – Java API for XML-based web services (JAX-WS) - Java architecture for XML binding (JAXB) – Java API for XML Registries (JAXR) - Java API for XML based RPC (JAX-RPC) - Web Services Interoperability Technologies (WSIT) - SOA support in .NET – Common Language Runtime - ASP.NET web forms – ASP.NET web services – Web Services Enhancements (WSE).BUILDING SOA9 HrsWS-BPEL basics – WS-Coordination overview - WS-Policy- WS-Security.Theory: 45 Hrs Total Hours:45 References:
Thomas Erl, “Service-Oriented Architecture: Concepts, Technology, and Design”, Pearson Education, 2010.
Thomas Erl, “SOA Principles of Service Design “(The Prentice Hall Service-Oriented Computing Series from Thomas Erl), 2007.
Newcomer, Lomow, “Understanding SOA with Web Services”, Pearson Education, 2005.
Sandeep Chatterjee, James Webber, “Developing Enterprise Web Services, An Architect’s Guide”, Pearson Education, 2005.
Dan Woods and Thomas Mattern, “Enterprise SOA Designing IT for Business Innovation” O’REILLY, First Edition, 2006.
Other References:
HYPERLINK "http://www.youtube.com/watch?v=Suf5FbTT7T8"www.youtube.com/watch?v=Suf5FbTT7T8
HYPERLINK "http://www.oracle.com/technetwork/systems/soa2-137288.html"www.oracle.com/technetwork/systems/soa2-137288.html
HYPERLINK "https://www.opengroup.org/soa/source-book/soa_refarch/concepts.html"https://www.opengroup.org/soa/source-book/soa_refarch/concepts.html















LTPC3003U14CSTE72 COMPUTER VISION

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain about shift invariant linear systems.
CO2: Summarize filling of holes in images.
CO3: Explain the performance of image denoising system.
CO4: Explain the different tracking methods.
CO5: Demonstrate the process of segmenting images.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3MMCO4MCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey


GEOMETRIC CAMERA MODELS 9 HrsImage Formation - Intrinsic and Extrinsic Parameters - Geometric Camera Calibration LINEAR FILTERS 9 HrsLinear Filters and Convolution - Shift Invariant Linear Systems - Spatial Frequency and Fourier Transforms - Sampling and Aliasing - Filters as Templates – Normalized Correlation and Finding Patterns-Scale and Image Pyramids.

IMAGE FEATURES AND TEXTURE9 HrsComputing the Image Gradient - Representing the Image Gradient - Finding Corners and Building Neighborhoods - Describing Neighborhoods with SIFT and HOG Features - Local Texture Representations Using Filters - Pooled Texture Representations by Discovering Textons - Synthesizing Textures and Filling Holes in Images - Image Denoising - Shape from Texture.  SEGMENTATION9 HrsWhat is segmentation? - Human vision: Grouping and Gestalt - Applications: Shot boundary detection and Background subtraction - Image segmentation by Clustering pixels - Segmentation by Graph-theoretic clustering - Hough Transform - Fitting Lines - Fitting Curves - Fitting as a Probabilistic Inference problem - Robustness.TRACKING9 HrsSimple Tracking Strategies - Tracking Using Matching - Tracking Linear Dynamical Models with Kalman Filters - The Kalman Filter - Data Association - Particle Filtering.Theory: 45 Hrs Total Hours:45References:
David A.Forsyth and Jean Ponce, “Computer Vision- A Modern Approach”, PHI, Second Edition, 2009.
Ballard.D.H and Brown.C.M, “Computer vision”, PHI, Englewood Cliffs, 1982.
M.Shah, “Fundamentals of computer vision”, 1997. (available on-line)
Richard Szeliski, “Computer Vision: Algorithms and Applications”, Springer, New York, 2010.











LTPC3003U14CSTE73 ADHOC AND SENSOR NETWORKS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the fundamentals of adhoc and sensor networks.
CO2: Compare the routing protocols of adhoc networks.
CO3: Illustrate the security issues in adhoc networks and explain solutions for it.
CO4: Explain the principles of energy management in adhoc networks.
CO5: Summarize the methods for data dissemination and gathering.

Pre-requisites:
U14CST502- Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3SCO4SMCO5M
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey

INTRODUCTION  7 Hrs Characteristics of wireless channel - Wireless local loop - IEEE 802.16 standard – HIPERACCESS -Ad hoc Wireless Networks: Introduction and Issues - MAC Protocols: Design issues - Goals and classification -MACAW: A Media Access Protocol for Wireless LANs- Distributed Packet Reservation Multiple Access Protocol-Distributed Priority Scheduling and Medium Access in Ad Hoc Networks- MAC Protocol using Directional Antennas.

ROUTING PROTOCOLS  11 HrsDesign Issues – Classification – DSDV – WRP - Location Aided Routing - Zone Routing Protocol - Hierarchical State Routing Protocol - Power Aware Routing Protocol - Associativity based Multicast Routing Protocol - Multicast AODV - On demand Multicast Routing Protocol. SECURITY IN ADHOC NETWORKS 9 HrsSecurity in Adhoc Wireless Networks – Network Security Requirements - Issues and Challenges in Security Provisioning – Network Security Attacks – Key Management – Secure Routing in Adhoc Networks. ENERGY MANAGEMENT  9 HrsNeed - Classification of Battery Management Schemes - Transmission Power Management Schemes - System Power Management Schemes.WIRELESS SENSOR NETWORKS  9 HrsArchitecture - Data Dissemination - Date Gathering - MAC Protocols - Location Discovery - Quality of Sensor NetworksTheory: 45 Hrs Total Hours:45References:C.Siva Ram Murthy and B.S.Manoj, “Adhoc Wireless Networks: Architectures and Protocols”, Prentice Hall PTR, 2004.
C.-K.Toh, “Adhoc Mobile Wireless Networks: Protocols And Systems”, Prentice Hall PTR, 2001
Mohammad Ilyas, “The Handbook Of Adhoc Wireless Networks”, CRC press, 2002
Charles E. Perkins, “Adhoc Networking”, Addison –Wesley, 2000
Stefano Basagni , Marco Conti, et al, “Mobile Adhoc Networking”, Wiley –IEEE press, 2004
Zhao and Guibas, ”Wireless Sensor Networks”, Morgan Kaufmann Publications, 2004

LTPC3003U14CSTE74 BUSINESS INTELLIGENCE AND ITS
APPLICATION

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain about business intelligence architectures.
CO2: Summarize various knowledge delivery methods.
CO3: Summarize efficiency measures used in business intelligence.
CO4: Explain about business intelligence applications.
CO5: Apply business intelligence concepts in a problem.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SWCO2MCO3SCO4MCO5MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey

BUSINESS INTELLIGENCE                                                         9 HrsEffective 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.
KNOWLEDGE DELIVERY 9 HrsThe business intelligence user types, Standard reports, Interactive Analysis and Ad Hoc Querying, Parameterized Reports and Self-Service Reporting, dimensional analysis, Alerts/Notifications, Visualization: Charts, Graphs, Widgets, Scorecards and Dashboards, Geographic Visualization, Integrated Analytics, Considerations: Optimizing the Presentation for the Right Message.


EFFICIENCY  9 HrsEfficiency 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 analysisBUSINESS INTELLIGENCE APPLICATIONS 9 HrsMarketing models – Logistic and Production models – Case studies.
FUTURE OF BUSINESS INTELLIGENCE 9 HrsFuture of business intelligence – Emerging Technologies, Machine Learning, Predicting the Future, BI Search & Text Analytics – Advanced Visualization – Rich Report, Future beyond Technology.
Theory: 45 Hrs Total Hours:45 
References:
Efraim Turban, Ramesh Sharda, Dursun Delen, “Decision Support and Business Intelligence Systems”, Ninth Edition, Pearson 2013.
Larissa T. Moss, S. Atre, “Business Intelligence Roadmap: The Complete Project Lifecycle of Decision Making”, Addison Wesley, 2003.
Carlo Vercellis, “Business Intelligence: Data Mining and Optimization for Decision Making”, Wiley Publications, 2009.
David Loshin Morgan, Kaufman, “Business Intelligence: The Savvy Manager s Guide , Second Edition, 2012.
Cindi Howson,  Successful Business Intelligence: Secrets to Making BI a Killer App , McGraw-Hill, 2007.
Ralph Kimball , Margy Ross , Warren Thornthwaite, Joy Mundy, Bob Becker,  The Data Warehouse Lifecycle Toolkit , Wiley Publication Inc.,2007.












U14CSTE75 BIG DATA AND ANALYTICS

LTPC3003Course Outcomes:
After successful completion of this course, students should be able to
CO1: Identify the difference between structured, semi-structured and unstructured data.
CO2: summarize the challenges of big data and how to deal with the same.
CO3: Explain the significance of NoSQL databases.
CO4: Explain about Hadoop Ecosystem.
CO5: Identify the difference between Pig and Hive.

Pre-requisites:
1. U14CST404 - Database Management Systems
2. U14CSP503 - Database Management Systems Laboratory

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MCO4SCO5MS
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. Mini Project
5.End Semester ExamCourse End Survey
TYPES OF DIGITAL DATA AND BIG DATA ANALYTICS9 HrsTypes of digital data: Structured: Sources of structured data and Ease with Structured data Semi-Structured: sources of semi-structured data Unstructured: sources of unstructured data: Issues with terminology, Dealing with unstructured data.
Big data analytics-1: Characteristics of data-Definition of big data-Challenges of big data-Traditional BI vs. Big data-A typical BI environment-A big data environment-Big data stack.
Big data analytics-2: Classification of analytics-Top challenges facing big data-Data science-Data Scientist.
Terminologies used in big data environment: In memory analytics-In database processing-Massively parallel processing-Parallel vs distributed systems-Shared Memory architecture-CAP (Consistency, Availability, Partition Tolerance) theorem explained- BASE (Basically Available Soft State Eventual Consistency)-Few top Analytics tools.
THE BIG DATA TECHNOLOGY LANDSCAPE AND HADOOP7 HrsThe big data technology landscape: NoSQL-Types of NoSQL databases-Why NoSQL-Advantages of NoSQL- What we miss with NoSQL?- NoSQL Vendors SQL Vs. NoSQL- NewSQL - Comparison of SQL, NoSQL and NewSQL.
Hadoop: Features of Hadoop- Key advantages of Hadoop- Versions of Hadoop-Hadoop 1.0
Hadoop 2.0- Overview of Hadoop Ecosystems- Hadoop Vs. SQL- Integrated Hadoop systems offered by leading market vendors-Cloud based Hadoop solutions.
Introducing Hadoop: Why not RDBMS-Distributed Computing Challenges.
Hadoop Overview: Hadoop Components-High Level Architecture of Hadoop.
Hadoop Distributed File System: HDFS Architecture-Daemons Related to HDFS- Working with HDFS Command-Special Features of Hadoop.
Processing Data With Hadoop: Introduction-How Map Reduce Works-Map Reduce Example- Word Count Example using Java.
Managing Resources and Applications with YARN: Introduction-Limitation of Hadoop 1.0- Hadoop 2: HDFS-Hadoop 2: YARN-Business Intelligence on Hadoop.
NOSQL – MONGODB AND NOSQL - CASSANDRA10 HrsNoSQL – MongoDB: What is MongoDB?- Using JSON-Creating or generating a unique key- Support for dynamic queries- Storing binary data-Replication-Sharding-Updating information in-place.Terms used in RDBMS and MongoDB-Data types in Mongodb-MongoDB - CRUD (Insert(), Update(), Save(), Remove(), find())-MongoDB- Arrays, Java Scripts, Cursors, Map Reduce Programming, Aggregations.
NoSQL – Cassandra: What is Cassandra?-Why Cassandra?- Peer to peer network-Gossip and Failure detection- Anti-Entropy & Read Repair- Writes in Cassandra- Hinted handoffs- Tunable consistency.Cassandra- CQLSH - CRUD, Counter, List, Set, Map, Tracing.
HADOOP HIVE 9 HrsIntroduction to Hive - The Problem-
Solution: Hive Use Case- Data Growth- Schema Flexibility and Evolution- Extensibility.
What is Hive: History of Hive and Recent Releases of Hive-Hive Features-Hive Integration and Work Flow- Hive Data Units.
Hive Architecture-Hive Primitive Data Types and Collection Types-Hive File Formats-Hive Query Language Statements:DDL-DML.Hive Partitions-Bucketing-Views-Sub Query-Joins-Hive User Defined Function-Aggregations in Hive-Group by and Having-Serialization and Deserialization-Hive Analytic Functions.HADOOP – PIG10 HrsHadoop – Pig: Introducing Pig:History and Anatomy of Pig-Pig on Hadoop-Pig Features-Pig Philosophy-Word count example using Pig-Use Case for Pig-Pig Primitive Data Types , Colletion Types and NULL.
Pig Latin Overview: Pig Latin Grammar - Comments, Keywords, Identifiers-Case sensitivity in Pig-Common Operators in Pig.
Pig Statements: LOAD-STORE-DUMP-Interactive Shell – GRUNT: FILTER- SORT- GROUP BY-ORDER BY-JOIN-LIMIT.
Pig Latin Script: Local Mode-Map Reduce Mode-Running Pig Script. Working with: Field-Tuple-Bag. User Defined Function-Parameters in Pig.
Jasper Report using Jasper soft studio: Introduction to Jasper Report using Jasper Soft Studio-Reporting using MongoDB-Reporting using Cassandra.Theory: 45 Hrs Total Hours: 45
References:
Mark Dexter, Louis Landry, “Joomla Programming”, 2012 Pearson Education.
Seema Acharya and Subhashini C, “Big Data and Analytics”, Wiley Publication, 2015
Judith Hurwitz, Alan Nugent, Fern Halper, Marcia Kaufman, “Big data for dummies”, Wiley Publication, 2013.
Tom White, “Hadoop: The Definitive Guide”, O’Rilly Publication, 2015.
HYPERLINK "http://www.flipkart.com/author/chuck-lam"Chuck Lam, “Hadoop in action”, Dreamtech Press, 2011.
Dirk Deroos, Paul C. Zikopoulos, Roman B. Melnyk, Bruce Brown, “Hadoop for dummies”, Wiley publication, 2015.

Other References:
https://www.mongodb.org
http://cassandra.apache.org
http://apache.bytenet.in/hadoop/common/hadoop-2.6.0/
http://apache.bytenet.in/hive/
http://apache.bytenet.in/pig/
https://community.jaspersoft.com





















ELECTIVE VIII












LTPC3003U14CSTE81 DISTRIBUTED SYSTEMS

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain the distributed environment.
CO2: Explain the functionalities of file management system.
CO3: Organize processes in a distributed systems.
CO4: Demonstrate the access of remote objects for the service.
CO5: Apply security methods.
Pre-requisites:
U14CST402- Operating Systems
U14CST502- Computer Networks

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SWCO3MMWCO4SCO5MW
Course Assessment methods:
DirectIndirect1. Internal tests
2. End Semester Exam
3. Assignments
4. SeminarCourse End Survey

INTRODUCTION  9 HrsIntroduction to Distributed systems-examples of distributed systems- resource sharing and the web- challenges-architectural models- fundamental models - Introduction to inter-process communications-external data representation and marshalling- client server communication-group communication.DISTRIBUTED OBJECTS AND FILE SYSTEM  9 HrsIntroduction - Communication between distributed objects - Remote procedure call - Events and notifications - Java RMI case Study - Introduction to Distributed File System - File service architecture - Sun network file system - Introduction to Name Services- Name services and DNS - Directory and directory servicesDISTRIBUTED OPERATING SYSTEM SUPPORT  10 HrsThe operating system layer – Protection - Process and threads - Communication and invocation - Operating system architecture - Introduction to time and global states - Clocks, Events and Process states - Synchronizing physical clocks - Logical time and logical clocks - Distributed debugging – Distributed mutual exclusion.TRANSACTION AND CONCURRENCY CONTROL – DISTRIBUTED TRANSACTIONS  9 HrsTransactions – Nested transaction – Locks - Optimistic concurrency control - Timestamp ordering - Comparison of methods for concurrency control - Introduction to distributed transactions - Flat and nested distributed transactions - Concurrency control in distributed transactions - Distributed deadlocks - Transaction recoverySECURITY AND REPLICATION  8 HrsOverview of security techniques - Cryptographic algorithms – Digital signatures - Cryptography pragmatics – Replication Introduction to Distributed Multimedia systems.Theory:45Hrs Total Hours:45 
References:
George Coulouris, Jean Dollimore, Tim Kindberg, "Distributed Systems: Concepts and Design", Fifth Edition, Addison-Wesley, 2011.
A.t S. Tanenbaum and M. V. Steen, "Distributed Systems: Principles and Paradigms", Second Edition, PHI, 2012.
Mukesh Singhal and N. G. Shivaratri, “Advanced Concepts in Operating Systems”, Tata Mcgraw - Hill Education, 2011.




















LTPC3003U14CSTE82 Ontology ANd SEMANTIC WEB

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain semantic web layers and semantics in semantic web.
CO2: Develop domain specific ontologies using ontology languages.
CO3: Make use of tools for building and storing ontologies.
CO4: Develop ontologies with intelligence by incorporating logic and inference rules.
CO5: Outline the applications of semantic web technologies.

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3SSSCO4MCO5SS
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey
INTRODUCTION TO SEMANTIC WEB 8 Hrs The world wide web, Limitations of Today‘s Web – The Next Generation Web – Semantic Web Layers –Semantic Web technologies – Semantics in Semantic Web – XML: Structuring – Namespaces – Addressing – Querying – Processing.
SEMANTIC WEB LANGUAGES 10 HrsResource Description Framework: RDF Basic Ideas - RDF Specification – RDF Syntax: XML and Non- XML – RDF elements – RDF relationship: Reification, Container, and collaboration – RDF Schema – Editing, Parsing, and Browsing RDF/XML – Discovering Information – Querying (RQL, SPARQL) – OWL – OWL Specification - OWL Elements – OWL constructs: Simple and Complex.



INTRODUCTION TO ONTOLOGY 9 Hrs Ontology- Why Ontology – Ontology movement – Ontology Engineering : Introduction – Constructing ontologies – Tools used in building and storing ontologies (Sesame, Jena, Protégé, NeOn toolkit) – Reusing ontologies – ontology reasoning (RACER).
ONTOLOGY LOGIC 9 HrsLogic and Inference: Logic – Description Logics - Rules – Monotonic Rules: Syntax, Semantics and examples – Non-Monotonic Rules – Motivation, Syntax, and Examples – Rule Markup in XML: Monotonic Rules, and Non-Monotonic Rules.
APPLICATIONS9 HrsApplications of Semantic Web Technologies
RDF Uses: Commercial and Non-Commercial use – Sample Ontology – e-Learning – Web Services – Web mining – Horizontal information – Data Integration – Future of Semantic WebTheory: 45Hrs Total Hours:45
References:
Paul Groth, Frank van Harmelen, Rinke Hoekstra, “A Semantic Web Primer”, Third Edition, MIT press, 2012.
Gómez-Pérez, A. Fernández-López, M. Corcho, “Ontological Engineering”, Springer Verlag 2003.
Michael C. Daconta, Leo J. Obrst, Kevin T. Smith, “The Semantic Web: A Guide to the Future of XML, Web Services, and Knowledge Management”, Fourth Edition, Willey Publishing, 2003.
John Davies, Rudi Studer, Paul Warren, “Semantic web technologies: Trends and Research in ontology-based systems”, Wiley & Sons, 2006.
Jiawei Han, Micheline Kamber, Jian Pei, “Data Mining: Concepts and Techniques”,Third Edition, Elsevier Inc, 2011.
Other References:
www.mitpress-ebooks.mit.edu/product/semantic-web-primer
 HYPERLINK "http://www.ebook3000.com/Programming/General/Semantic-Web-Programming_114984.html" http://www.ebook3000.com/Programming/General/Semantic-Web-Programming_114984.html
HYPERLINK "http://videolectures.net/iswc08_hendler_ittsw/"http://videolectures.net/iswc08_hendler_ittsw/











LTPC3003U14CSTE83 SOFTWARE QUALITY ASSURANCE AND
TESTING
Course Outcomes:
After successful completion of this course, students should be able to
CO1: Outline software testing methods
CO2: Summarize risk in software project development.
CO3: Develop knowledge in understanding the importance of Software Quality Assurance.
CO4: Utilize the appropriate testing techniques for information systems development.
CO5: Apply the metrics involved in software development.
Pre-requisites:
U14CST603- Software Engineering

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2SCO3SCO4SCO5S
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4. End Semester ExamCourse End Survey
FUNDAMENTALS OF SOFTWARE TESTING 9 HrsIntroduction- Approaches to Testing - Testing during Development Life cycle - Requirement Traceability Matrix - Salient Features of Good Testing -Test Policy - Test Strategy - Test Planning –Testing Process & Number of Defects found in Testing - Test Team Efficiency - Mutation Testing -Challenges in Testing - Test Team Approach - Process Problems faced in Testing – Defect - Error/Mistake and Failures in Software - People Challenges in Software Testing.RISK ANALYSIS9 HrsIntroduction - Advantage & Disadvantages of Automated Development System – Risk – Constraints - Project & Product Risks - Risks faced due to Software Development Systems - Software Implementation Risks - Risk Assessment - Handling of Risks - V Test Model - Defect Management.SOFTWARE QUALITY9 HrsQuality: Popular Views - Professional Views – Software Quality – Total Quality Management – Software Quality Metrics – In-process Quality Metrics – Metrics for Software Maintenance – Applying the Seven Basic Quality Tools in Software Development.MODELS FOR SOFTWARE QUALITY9 HrsDefect Removal Effectiveness – Rayleigh Model – Exponential Distribution and Reliability Models – Quality Management Models.METRICS9 HrsAvailability metrics – Measuring and Analyzing customer satisfaction – Conducting In- process Quality Assessments – Audit and Assessment – Software Process Maturity Assessment – Software Project Assessment – Do’s and Don’ts of Software Process ImprovementTheory:45Hrs Total Hours:45References:
M.G. Limaye, “Software Testing – Principles, Techniques and Tools”, Tata McGraw Hill, 2011.
Stephen H. Khan, “Metrics and Models in Software Quality Engineering”, Pearson Education, Second Edition, 2004.
Watts S. Humphrey, “Managing The Software Process”, Addison Wesley, 1989.
William E. Perry, “Effective Methods for Software Testing”, John Wiley, Fourth Edition, 2007.




















LTPC3003
U14CSTE84 INFORMATION RETRIEVAL

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain Information retrieval system strategies.
CO2: Compare various types of retrieval utilities.
CO3: Explain cross-language information retrieval strategies.
CO4: Summarize various steps involved in information retrieval techniques.
CO5: Identify various web based information retrieval techniques using modern tools.

Pre-requisites:
U14CST702 - Data Warehousing and Data Mining
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MCO3SMCO4MCO5SM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignments
3. Seminar
4.End Semester ExamCourse End Survey

RETRIEVAL STRATEGIES 9 HrsVector Space Model – Probabilistic Retrieval Strategies – Language Models – Inference Networks – Extended Boolean Retrieval – Latent Semantic Indexing – Neural Networks – Genetic Algorithms – Fuzzy Set Retrieval.RETRIEVAL UTILITIES9 HrsRelevance Feedback – Clustering – Passage-based Retrieval – N-grams – Regression Analysis – Thesauri – Semantic Networks – Parsing.CROSS-LANGUAGE INFORMATION RETRIEVAL9 HrsIntroduction – Crossing the Language Barrier – Cross-Language Retrieval strategies – Cross Language Utilities – Efficiency - Inverted Index – Query Processing – Signature Files – Duplicate Document Detection.
Integrating Structured Data and Text: Relational Model – Historical Progression –Relational Application – Semi-Structured Search – Multi-dimensional Data Model – Mediators.
PARALLEL AND DISTRIBUTED INFORMATION RETRIEVAL9 HrsParallel Information Retrieval: Parallel Text Scanning – Parallel Indexing – Clustering and Classification – Parallel Systems
Distributed Information Retrieval: Theoretical Model – Web Search – Result Fusion – Peer-to-Peer Information Systems – Architectures.
WEB BASED RETRIEVAL9 HrsWeb Search Basics – Indexing – Query Processing– Crawling– Ranking– Link Analysis: Page rank, Hubs and Authorities (HITS).
Theory: 45Hrs Total Hours:45References:
David A. Grossman, Ophir Frieder, “Information Retrieval: Algorithms, and Heuristics”, Academic Press, Second Edition, 2008.
Christopher D. Manning, Prabhakar Raghavan, Hinrich SchützeAn ,”Introduction to Information Retrieval” ,Cambridge University Press, Cambridge, England, 2009.
Ricardo Baeza-Yate, Berthier Ribeiro-Neto, “Modern Information Retrieval”, Pearson Education Asia, 2012.
G.G. Chowdhury, “Introduction to Modern Information Retrieval”, Neal- Schuman Publishers, Third Edition, 2010.
Daniel Jurafsky and James H. Martin, “Speech and Language Processing”, Second Edition, Pearson Education, 2009.
Charles T. Meadow, Bert R. Boyce, Donald H. Kraft, “Text Information Retrieval Systems”, Academic Press, Third Edition, 2007.

Other References:
HYPERLINK "http://www.csee.umbc.edu/csee/research/ngram/"http://www.csee.umbc.edu/csee/research/ngram/
HYPERLINK "http://searchengineshowdown.com/"http://searchengineshowdown.com/
















LTPC3003U14CSTE85 COMPUTATIONAL INTELLIGENCE

Course Outcomes:
After successful completion of this course, students should be able to
CO1: Explain about the basics of Neural networks.
CO2: Develop appropriate classification algorithm for various problems.
CO3: Build appropriate clustering techniques for various problems with high dimensional data.
CO4: Explain inductive generalization from examples and other traditional learning paradigms. CO5: Experiment with tools used to study complexity, including evolutionary computing and Fuzzy logic.

Pre-requisites:
U14CST601 - Artificial Intelligence

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1SCO2MMCO3MMCO4WCO5 MMM
Course Assessment methods:
DirectIndirect1.Internal Tests
2. Assignments
3. Seminar
4. Mini Project
5. End Semester ExamCourse End Survey


BIOLOGICAL BASIS FOR NEURAL NETWORKS 9 HrsBiological Basis for Neural Networks - Evolutionary Computation – Behavioral Motivations for Fuzzy Logic – Application Areas – Computational Intelligence DevelopmentNEURAL NETWORK THEORY 10 HrsComponents and Terminology – Topologies – Learning – Recall – Taxonomy - Preprocessing & Post Processing – Implementation of Neural Network – Back Propagation – Learning Vector Quantizer – Radial Basis Function Networks – Kohonen Self Organizing Maps.EVOLUTIONARY COMPUTATION THEORY 10 HrsOverview - Genetic Algorithm – Simple Example Problem – Programming – Strategies – Genetic Programming – Implementation of Genetic Algorithm and Particle Swarm Optimizer.FUZZY SYSTEM THEORY 10 HrsFuzzy Sets and Fuzzy Logic – Approximate Reasoning – Issues – Fuzzy Systems Implementation
COMPUTATION INTELLIGENCE THEORY 6 HrsDefinitions – Relationships among Components of Intelligent Systems Implementations – Metrics
Theory: 45 Hrs Total Hours:45
References:
Andries P. Engelbrecht, “Computational Intelligence: An Introduction”, Wiley India (P) Ltd, Second edition, 2007.
S.Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2011.
S.N.Sivanandam and S.N.Deepa, “Principles of Soft Computing”, Wiley India (P) Ltd, Second Edition, 2011.
Amit Konar, “Computational Intelligence-Principles, Techniques and Applications”, Springer International Edition, 2005.
Timothy J.Ross, “Fuzzy Logic with Engineering Application”, Wiley India (P) Ltd, 2010.














U14CSIN01 COMPUTER CRIMES, SECURITY AND CYBER LAWS
Course Outcomes:
After successful completion of this course, the students should be able to

CO1: Explain different crimes in internet.
CO2: Explain the issues those are specific to amendment rights.
CO3: Explain knowledge on copy right issues of software’s.

Pre-requisites:

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2MMCO3MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. End Semester Exam Course End Survey















COMPUTER CRIME INTRODUCTION 5 HrsIntroduction to Computer Misuse -The Meaning of “Authorization”: Code and Contract-based Approaches - Computer Damage Statutes and Review- Online Threats and Harassment and Invasion of Privacy Crimes- Sentencing Computer Crimes-Computer crime statistics. Types of Computer and Internet Crime: Types of crimes involving computers-Computer crimes-Network crimes- Criminals, hackers, and crackers.
INFORMATION SECURITY5 HrsOverview of computer Security-managing firewalls and VPNs-Classes of attackers, Kids/ hackers/ sophisticated groups, automated: Drones, Worms and Viruses-Security considerations for the mobile work force, Network security perspectives, networking and digital communications, security of wireless networks.
CYBER LAWS5 HrsIntroduction-Cyber Security and its problem-Regulation and Jurisdiction for global Cyber security-Copy Right-source of risks, Pirates, Internet Infringement, Fair Use, postings, criminal liability, First Amendments, Data Loss-Trademarks, Defamation, Privacy-Common Law Privacy, Constitutional law, Federal Statutes, Anonymity, Technology expanding privacy rights-Criminal Liability-Procedural issues-Digital Signatures, Misappropriation of information, Civil Rights, Tax-security in Society, Security in cyber laws case.
Theory: 15 Hrs Total Hours: 15

References:
orin kerr, “ Computer Crime law(American casebook series)”, 2012.
Nina S. Godbole, “Information Systems Security Management”, Wiley India Pvt.Ltd., 2013.
W. Stallings, “Network Security Essentials: Applications and Standards”, Pearson Education, 2003
Jonathan Rosenoer,“Cyber Law: The law of the Internet”, Springer-Verlag,1997.
Mark F Grady, Fransesco Parisi, “The Law and Economics of Cyber Security”, Cambridge University Press, 2006.

Other References:
http://paulohm.com/classes/cc11
https:// www.cyberlaw.com/















U14CSIN02 BUSINESS ANALYTICS

Course Outcomes:
After successful completion of this course, the students should be able to
CO1: Describe and interpret the basic concepts of Business Analytics (BA).
CO2: Describe basic principles of data mining as a basic tool for Business Analytics.
CO3: Understand business problems and determine suitable analytical methods
CO4: Compare and contrast different BA techniques

Pre-requisites: Nil

CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-WeakCOsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MCO2MCO3MCO4MCourse Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. End Semester Exam Course End Survey
OVERVIEW OF BUSINESS ANALYTICS  3 HrsBusiness Analytics: Definition-Evolution-Architecture-Benefits-Future- Business Analytics as Solution for Business ChallengesDATA MINING AND DATA ANALYTICS 4 HrsWhat is Data Mining- Applications and Methods -Effective Predictive Analytics-Integrating Analytics in Business Processes Unstructured Data AnalyticsDATA MODELING 4 HrsData Modeling Concepts-Data Modeling Types and Techniques- Multidimensional modelingDATA INTEGRATION AND DATA WAREHOUSING 4 HrsBasics of Data Integration- Data Warehouse: Architecture- Development and Implementation issues- Introduction to OLTP and OLAP.Theory: 15 Hrs Total Hours: 15 
References:RN Prasad and Seema Acharya ,“Fundaments of Business Analytics” ,Wiley India Publication,2011
Jean Paul Isson and Jesse S. Harroitt,” Win With Advanced Business Analytics”, Wiley Publication, 2013
Cindi Howson,” Successful Business Intelligence: Secrets to Making BI a Killer App” Tata McGraw Hill Edition 2012..
Efraim Turban, Ramesh Sharda, Dursun Delen and Daid King,” Business Intelligence: A Managerial Approach”, Pearson Publication, 2012.







































U14CSIN03 ETHICAL HACKING

Course Outcomes (COs):
On successful completion of this course, the students should be able to
CO1: Explain testing and issues in creating test plans
CO2: Explain social engineering and host reconnaissance.
CO3: Explain about hacking and various attacks

Pre-requisites: P15CST203-Network Engineering and Management
CO/PO Mapping
(S/M/W indicates strength of correlation) S-Strong, M-Medium, W-Weak
COsProgramme Outcomes(POs)PO1PO2PO3PO4PO5PO6PO7PO8PO9PO10PO11PO12CO1MMCO2MMCO3MM
Course Assessment methods:
DirectIndirect1. Internal Tests
2. Assignment
3. Seminar
4. End Semester Exam
Course End Survey
Introduction to Penetration Testing .NET Framework2 HrsLegal and Ethical Considerations Creating and Implementing a Test Plan3 HrsSocial Engineering3 HrsHost Reconnaissance3 HrsHacking & Attacks: Session Hijacking, Web server Attacks, Database Attacks, Password Cracking, Network Devices & Attacks, Wireless Network Attacks 4 HrsTheory: 15 Hrs Total Hours: 15




U14CSIN04 LINUX SYSTEM ADMINISTRATION
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