cse 5th-6th finalaized version

Rashtreeya Sikshana Samithi TrustR. V. COLLEGE OF ENGINEERING

(Autonomous Institution Affiliated to VTU, Belgaum)R.V Vidyaniketan Post, Mysore Road

Bangalore-560 059

Scheme & SyllabusV & VI Semester B.E

Computer Science and Engineering

(2012 Scheme)

Department of Computer Science and EngineeringR V College of Engineering, Bangalore

Vision and Mission of the Department of Computer Science and Engineering:

Vision

Empower every student to be creative and productive in the area of Computer Science /

Information Technology by imparting quality education and inculcating human values.

Mission

To evolve continually as a centre of excellence in quality education

To promote collaboration with Industry to achieve constructive interaction for better

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integration of theory with application.

To build and update infrastructure and create environments to facilitate research and

skill enhancement.

To collaborate with institutions at national & international level to offer high-end

Information Technology education and training.

Program Educational Objectives(PEO’s):

I. To facilitate graduates to apply the principles of computer science & engineering,

mathematics and science to solve real-world problems.

II. To develop the ability among students to analyze, understand and apply current

pedagogical techniques, industry accepted computing practice and state-of-art

technology.

III. To provide opportunities to students to broaden their educational experiences

through independent studies with innovative ideas, internship and career

exploration experiences to inculcate practical work managements, customer-

relationship management & business domain knowledge.

IV. To develop graduates who will exhibit cultural awareness, teamwork with

professional ethics, effective communication skills and appropriately apply

knowledge of societal impacts of computing technology.

V. To prepare graduates to be successfully employed in the right role and achieve

career succession in industry/R & D organization, to take up higher education

programs and to pursuit lifelong learning.

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Program Outcomes:

a. Graduates get an ability to analyze and apply fundamental principles of computing and

mathematics as appropriate to the discipline of computer science and engineering.

b. Graduates will demonstrate the proficiency in understanding of various computer

programming languages and knowledge of various technologies in computer system

c. Graduates will demonstrate an ability to apply mathematical foundation, algorithmic

principles and computer science theory, in the modeling and design of computer based

system.

d. Graduates will demonstrate an ability to use techniques, skills to analyze and investigate

complex problems through research and effectively utilize appropriate modern

engineering tools to solve it.

e. Graduates will possess sustainable, inclusive technology for societal and environmental

contexts.

f. Graduates will be able to communicate effectively and develop confidence in self and

life-long learning.

g. Graduates will possess leadership, project management and financial skills with

professional ethics.

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Department of Computer Science and Engineering R.V.College of Engineering, Bangalore – 560059.

(Autonomous Institution Affiliated to VTU, Belgaum)

FIFTH SEMESTERSl. No.

Course Code

Course Title BoSCredit Allocation

Total CreditsLecture Tutorial Practical Self -Study

1. 12HSI51Intellectual Property Rights & Entrepreneurship

HSS 3 0 0 0 3

2. 12CS52 Computer Networks-I CSE 3 1 0 1 5

3. 12CS53 Microprocessor & Microcontroller CSE 3 0 1 1 5

4. 12CS54 Database Management System CSE 3 0 1 1 5

5. 12CS5AX Elective A CSE 3 0 0 1 4

6. 12CS5BX Elective B CSE 3 1 0 0 4Credit Total 18 02 02 4 26No. of Hrs. 18 04 04 16 42

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Subject Code Professional Elective12CS5AX - Group A

Subject Code Professional Elective12CS5BX

12CS5A1 System Simulation & Modeling 12CS5B1 Java & JEE12CS5A2 Probability & Statistics 12CS5B2 Introduction to mainframes12CS5A3 OOAD 12CS5B3 Middleware Technologies12CS5A4 Introduction to machine Learning 12CS5B4 Advanced Algorithms12CS5A5 Distributed Operating System 12CS5B5 Fundamentals of Computer Vision12CS5A6 Artificial Intelligence 12CS5B6 Multimedia Computing12CS5A7 Graph Theory and Applications 12CS5B7 Distributed Systems

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SIXTH SEMESTERSl. No.

Course Code Course Title BoSCredit Allocation

Total CreditsLecture Tutorial Practical Self-Study

1. 12HSM61 Management & Organizational Behaviour HSS 3 0 0 0 3

2. 12CS62 Software Engineering ISE 3 0 0 1 4

3. 12CS63 Computer Networks-II CSE 3 0 1 1 5

4. 12CS64 System Software & Compiler Design CSE 3 0 1 1 5

5. 12CS65Emerging Technology in Computational Sciences

CSE 2 0 0 0 2

6. 12CS6CX Elective C CSE 3 1 0 0 4

7. 12CS6DX Elective D CSE 3 0 0 0 3Credit Total 20 1 2 3 26No. of Hrs. 20 02 04 12 38

Subject code Professional Elective12CS6CX

Subject Code Professional Elective12CS6DX

12CS6C1 Embedded System 12CS6D1 Linux Internal12CS6C2 Grid Computing 12CS6D2 Mobile Application

Development12CS6C3 Natural Language Processing 12CS6D3 Network Programming12CS6C4 Artificial Neural Networks 12CS6D4 Fuzzy Logic12CS6C5 Data warehousing and mining 12CS6D5 Software Architecture &

Testing12CS6C6 Game Theory 12CS6D6 Genetic Algorithm12CS6C7 Unix System Programming

INTELLECTUAL PROPERTY RIGHTS AND ENTREPRENEURSHIP

Course Code: 12HSI51 CIE Marks :50

L:T:P:S: 3-0-0-0 SEE Marks: 100

Credits: 03 SEE Duration:2 Hrs

COURSE LEARNING OBJECTIVESStudents will be able to:

Identify and analyse the legal regulation of the way in which ideas, innovation and artistic endeavour are protected and commercially exploited.

Understand the law relating to patents, trademarks, passing off, copyright, registered designs, plant varieties, trade secrets and confidential information.

Appraise and evaluate the social and economic justifications for such rights. To explores the challenges to IP law in the digital age and examines specific electronic

commerce practices that raise complex Trademark, Patent And Copyright policy questions.

To provide practical, useful and easy to understand information on IP law as it relates to commercial activities on the Internet

To find sophisticated problem related solutions of different forms of IPR. To act as an interface between industry / government and multilateral institution in

various aspects relating to Intellectual Property

Unit – I

Introduction: Types of Intellectual Property, International Scenario in IPR: WIPO,

WTO, TRIPS.

Patents: Introduction, Object of patent; Scope and salient features of patent;

patentable inventions, inventions are not patentable, Patent Procedure- Overview,

Rights and obligations of patentee; Transfer of Patent Rights; Government use of

inventions; Biotechnology patents, protection of traditional knowledge, Infringement

of patents and remedy, Case study

Trade Secrets: Definition, Significance, Tools to protect Trade secrets in India.

08Hrs

Unit – II

Trade Marks:Introduction and overview of trade mark; Evolution of trade mark law;

Object of trade mark; Features of good trade mark; Different forms of trade mark;

Trade mark registry and register of trademarks; Registrable and non- registrable

5Hrs

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marks; Basic principles of registration of trade mark; Deceptive similarity;

Assignment and transmission; Trade mark and ECO Label, Infringement of trade

mark; Passing off; Offences and penalties, Case study

Unit – III

Industrial Design: Introduction, Need for Protection of Industrial Designs, Subject

Matter of Protection and Requirements, Procedure for obtaining Design Protection,

Revocation, Infringement and Remedies , Case study

Copy Right: Introduction, Nature and scope, Subject matter, the works in which copy

right subsists, Rights conferred by copy right, Copy right protection in India, transfer

of copy rights, right of broad casting organisations and of performer and Case Studies.

Intellectual property and cyberspace; Emergence of cyber-crime ; Grant in software

patent and Copyright in software; Software piracy; Trademarks issues related to

Internet (Domain name); Data protection in cyberspace;; Salient features of

Information Technology Act; IPR provisions in IT Act; Internet policy of Government

8Hrs

Unit – IV

Entrepreneur and Entrepreneurship: Evolution of the concept of Entrepreneur,

Characteristics of an Entrepreneur, Distinction between an entrepreneur and a

manager, Functions of an entrepreneur, types of entrepreneur, Intrapreneur, Concept of

Entrepreneurship ,Growth of entrepreneurship in India, Role of Entrepreneurship in

economic development, overview on entrepreneurial development models, Case

discussions on a couple of successful entrepreneurs.

7Hrs

Unit – V

Micro Small & Medium Enterprises (MSME): Definition, Characteristics, Need

and rationale, Objectives, Scope, role of MSME in Economic Development,

Advantages of MSME, Steps to start an MSME – Government policy towards MSME,

Impact of Liberalization, Privatisation & Globalization on MSME, Effect of WTO /

GATT. Sustainability and MSME.

Institutional Support to entrepreneurs: Over view on National and State Agencies.

Identification of Business Opportunities: Market Feasibility studies; Technical

Feasibility Studies; Financial Feasibility Studies and Social Feasibility studies.

7Hrs

7

Reference Books:

1. Dr G.B Reddy, “Intellectual Property Rights and the Law’ Gogia Law Agency, 7th

Edn.,2008

2. Prabuddha Ganguly, “Intellectual Property Rights: Unleashing Knowledge Economy”,

Tata McGraw Hill Publishing Company Ltd., New Delhi, 1st Edition, 2001. ISBN:

0074638602.

3. Rodney Ryder – Intellectual Property and the Internet. ISBN: 8180380025; LexisNexis

Butterworth ,New Delhi , 2002;

4. Rahul Matthan – The law relating to Computers and the Internet. ISBN 10:

8187162139 / ISBN 13: 9788187162131 Oscar Publications (Delhi, DEL, India)

5. S.R Myneni, “Law of Intellectual Property”, Asia Law House, Hyderabad, 2001, SKU –

664773841.

6. SS Khanka ,Entrepreneurial Development , S Chand & Co, 2008,ISBN:81-219-1801-4

7. Entrepreneurship Development & Small Business Enterprises – Poornima M

Charantimath , Pearson Education ,2007 ,ISBN: 81-7758-260-7

COURSE OUTCOMES

To have an understanding of the fundamental legal principles relating to Confidential Information, Copyright, Patents, Designs, Trademarks and Unfair Competition;

Able to identify, apply and assess principles of law relating to each of these areas of

intellectual property;

Understand the legal and practical steps needed to ensure that intellectual property rights

remain valid and enforceable;

Able to demonstrate a capacity to identify, apply and assess ownership rights and

marketing protection under intellectual property law as applicable to information, ideas,

new products and product marketing

Understand current and emerging issues relating to the intellectual property protection,

including those relating to indigenous knowledge or culture, information technology

especially the distribution of material on the internet, biotechnology and international

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trade; and

To anticipate and subject to critical analysis arguments relating to the development and

reform of intellectual property right institutions and their likely impact on creativity and

innovation.

Continuous internal evaluation Scheme

CIE consists of two Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best of one will be considered. The test component will have a weightage of 45 marks in CIE. In addition there will be one seminar on new topics / model presentation etc. for 05 marks.

Scheme of Semester End Examination:

The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions carrying 16 marks each. All five questions from Part B will have internal choice and one of the two have to be answered compulsorily.

R. V COLLEGE OF ENGINEERING, Bangalore – 560059.(Autonomous Institution under VTU, Belgaum)

COMPUTER NETWORKS - I

Sub Code: 12CS52L:T:P:S 3:1:0:1Credits: 5

CIE Marks: 100 SEE marks: 100

Exam Hrs: 03

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Prerequisite:The student should have undergone the following courses :(a) Basic Electronics Engineering (Code: 12EC14/24).(b) Digital Logic Design using HDL (Code: 12CS34).

Course Learning Objectives:

1. To develop a fundamental understanding on the network elements.2. To develop a clear picture on working of the network.3. To understand and visualize the roles of various protocols.4. To develop a clear understanding on the OSI Reference model and TCP/IP Suite.5. To present protocols relevant for various types of channels used in computer networks.6. To illustrate the operation and formats of IEEE standard protocols used in LAN.

Syllabus Content

UNIT – I

Chapter 1 : Introduction

Introduction to Data Communications, components, data representation, data flow, Essential elements of network architecture, Message switching, circuit switching and packet switching, Introduction to Networks, topologies, categories, Internet.

Chapter 2 : Data and Signals

Analog and digital, Periodic analog signals, Digital signals, Transmission impairments, Data rate limits, Performance.

UNIT – II

Chapter 3 : Physical Layer : Digital Transmission and Media

Digital - to -digital conversion, Analog - to - digital conversion, Transmission

modes.TransmissionMedia : Guided media, Unguided media - wireless.

Chapter 4 : Physical Layer : Bandwidth Utilization

Multiplexing : FDM, WDM, Synchronous TDM, Statistical TDM. Spreading : Frequency Hopping Spread Spectrum (FHSS), Direct Sequence Spread Spectrum.

Hrs

3 Hrs

6Hrs

6Hrs

3Hrs

10

UNIT – III

Chapter 5 : Network Models and Layered Architecture

Layered tasks, The OSI model, Layers in the OSI model, TCP / IP protocol suite, Addressing. Design Issues for the Layers, Connection-Oriented and Connectionless Services, Service Primitives.

Chapter 6 : Data Link Layer : Error Detection and Correction

Introduction, Block coding, Cyclic codes, Checksum

5 Hrs

4Hrs

UNIT – IV

Chapter 7 : Data Link Layer : Data Link Control

Framing, Flow and Error control, Protocols, Noiseless channels, Noisy channels, HDLC, Point-to-point Protocol - framing, transition phases.

9 Hrs

UNIT – V

Chapter 8 : Data Link Layer : Medium Access Control

Random access - CSMA, CSMA / CD, CSMA / CA, Controlled access - reservation, polling, token passing, Channelization - FDMA, TDMA, CDMA.

Chapter 9 : Local Area Networks

Ethernet (802.3) MAC sub layer protocol, Binary exponential back off algorithm, Switched Ethernet, Fast Ethernet, Gigabit Ethernet, IEEE 802.2 LLC, Wireless LANs,802.11 stack, 802.11 Physical layer, 802.11 MAC sub layer protocol, 802.11 frame structure.

4 Hrs

4 Hrs

REFERENCE BOOKS:1.Behrouz A Forouzan; Data Communications and Networking; Tata McGraw-Hill; 4th Edition; 2006.2. Alberto Leon-Garcia and IndraWidjaja; Communication Networks; Tata McGraw-Hill, 2nd

Edition; 2011.3. Andrew S Tanenbaum; Computer Networks; Pearson Education; 4th Edition; 2008.4. William Stallings; Data and Computer Communications; Pearson Education; 8th Edition; 2009.

Course Outcomes:CO1: Describe the basic concepts related to techniques used in the network support layers.

CO2: Analyze and explain the differences between various types of transmissions through physical

media and associated error handling mechanisms.

CO3: Apply the concepts and solve problems relevant to performance of communication links.

CO4: Assess the applicability of different line coding methods and protocols used in the network support layers.

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Self-Learning (1 Credit – 4 Hrs/Week):Self-learning will be on emerging fields of the computing technology. It is an extension of

content of tutorial sessions. Students demonstrate realization of the real-life applications achieved independently. This exercise is to assess understanding of the fundamentals by student and their aptitude to apply the same to real world problems.

Scheme for Self Learning Evaluation:The self-learning must be presented in front of evaluation committee; the members of this committee will be Faculties handling the subject along with an observer appointed by Head of the Department. Students are required to present their work either in form of technical presentation or in form of live demonstration. At the end of the presentation the students are required to submit the report as per the format recommended by the Dept. or Dean Academics. The format of evaluation for 20 marks is completely under the prerogative of the committee members or as suggested by HOD.

Scheme for Continuous Internal Evaluation (CIE):

CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment component.

Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Max Assignment marks : 10

Scheme of Semester End Examination (100)

Scheme of Evaluation for Theory (100)The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions (descriptive, analytical, problems or/and design) carrying 16 marks each. All five from Part B will have internal choice and one of the two have to be answered compulsorily.


MICROPROCESSOR & MICROCONTROLLER

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CIE Marks: 100+50 SEE marks: 100+50

Exam Hrs: 03

Prerequisite:The student should have undergone the following courses , 1. Digital Electronics , 2. Introduction to Computer Programming


1. Analyze draw and explain 8086 Microprocessor & 8051 Microcontroller architecture/block diagram and & describe their Pins/signals

2. Analyze and code programs with different addressing modes, instructions , assembler directives of 8086

3. Design and develop flow chart & algorithms to solve problems and write assembly language programs for 8086

4. Develop embedded C programs for 8051 microcontroller and run on the simulator and target board

5. Differentiate between Microprocessor & Microcontroller based systems and based on the problem statement, able to decide whether to go for microprocessor or microcontroller for solving the problem/industry requirement

6. Analyze the given problem and partition into different subroutines and develop multi segment and multi text file based assembly programs using Stack structure , Macros, Procedures, Interrupts and ISRs

7. Understand and use DOS and BIOS services while writing assembly language programs

8. Demonstrate Interfacing and Programming of 8086 with I/O ports using 8255, and interface Keys, LEDs, Seven Segment Displays

9. Develop and code embedded C programs for interfacing 8051 with ADC, DAC, Sensors, stepper motor, dc motor and with serial port of PC

10. Executing Mini course Project in a group, involving

gathering societal and industry requirements and trends,

study of current developments in the field of microprocessors & microcontrollers

gaining hands on practical’s in building the project,

effective communication among group members – respecting and receiving ideas, sharing work responsibilities

Syllabus Content Hrs

Unit 1. Microprocessors - Intel 8086 Processor

Introduction , Architecture , Signal Descriptions, Physical Memory Organization, Minimum

6hrs

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mode of operation, Maximum mode of operation , Brief overview of Intel Advanced

Microprocessors

Unit 2. 8086 Instruction set & Assembler Directives

Addressing modes , Instruction set, Assembler directives ,Assembly Language

Programming.

7hrs

Unit 3.Special Architectural Features, Interfacing I/O Ports & Related Programming

8086: Procedures , Macros, Stack Structure & Programming for Stack, Interrupts - structure of IVT and Interrupt programming, Interfacing Memory(static RAM), Interfacing I/O Ports, 8255(Mode0 only), Interfacing & Programming with LEDs, Switches and Seven segment displays

7hrs

Unit 4 . Microcontrollers - Intel 8051 Microcontroller & Programming

Introduction, Block Diagram, Memory Organization , Interrupts, Introduction to Embedded C Programming, Working of I/O Ports, Counters & Timers, Programming( embedded C) of I/O Ports, Counters & Timers(Mode1 only). Writing Delay programs using Timers.

6hrs

Unit 5 - 8051 Interfacing & Applications

Interfacing & Programming (using embedded C) of : Matrix Keypad, Parallel ADC (ADC0804) , DAC (DAC0800), Stepper motor, DC Motor, High power devices using Relays, Industrial sensors using optoisolators. Programming serial port of 8051, Communication of 8051 with the PC using serial port, Brief overview of ARM Microcontrollers.

Laboratory Experiments

Write an 8086 ALP to search an element in a list of ‘n’ 16-bit numbers using the Binary Search algorithm. [Use Codeview to demonstrate the result]

1b. Write an ALP to implement decimal UP/decimal Down/Ring counter using Interface module

2a. Write an 8086 ALP to sort a given set of ‘n’ numbers in ascending or descending orders using Bubble sort algorithm. [Use Codeview to demonstrate the result]

2b. Write an ALP to read the status of 8 inputs bits from 8bit switch and display ‘FF’ if it is even parity otherwise display 00. Also display number of 1’s in the input data on the LED outputs, using interface module.

3a. Write the macros using 8086 ALP to perform the following tasks using DOS/BIOS interrupts,i) To read a character from the keyboardii) To display a characteriii) To clear the screeniii) To exit to DOS operating system.

Write these macros in separate file “macros.asm”, Using these macros write a program(in a different file) to read a string terminated by carriage return from keyboard and print the same on the Monitor after clearing the screen and setting

7hrs

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the cursor to the center of the screen.3b. Write an ALP to read the status of two 8-bit inputs (X and Y) and display the result

X*Y using the interface module4a. Write an 8086 ALP to read two strings, store them in locations str1, str2, check

whether they are equal or not and display appropriate messages. Also display the length of the stored strings

4b. Write an ALP program to display messages “FIRE” & “HELP” on 4 digit seven segment display alternately with a suitable delay, [the exact delay value not specified]

5a. Write an 8086 ALP to read password and validate the user and display appropriate message, also display the count of characters in the password.

5b. Write an Embedded C Program to Interface LCD for displaying a string on single line / two line

6a. Write 8086 ALP Procedures to perform the following functions,i) “read_8” – read 2 digit hex number from keyboard, AL should return the valii) “disp_16” - display decimal equivalent of 4 digit hex number/16 bit binary

number, AX contains the numberUsing the above procedures write an ALP to read 8bit number and compute its factorial and display the result. Store the procedures in different file and link it with the main program.

6b. Write an Embedded C program to rotate stepper motor in clock wise direction for “N” steps

7a. Write an 8086 ALP to read the 4 digit hex number and convert 4digit Hex number to decimal number, and display the decimal number.

7b. Write an Embedded C program to rotate stepper motor in anti-clock wise direction for “N” steps

8a. Write an 8086 ALP to implement Stack Data Structure, with all the operations8b. Write an Embedded C program to rotate stepper motor in clock-wise & in anti-

clock wise direction for “N” steps9a. Write an 8086 ALP to compute GCD of two 16 bit Positive Integer numbers9b. Write an Embedded C program to generate sine waveform using DAC module10a. Write an 8086 ALP to compute LCM of two 16 bit Positive Integer numbers10b. Write an Embedded C program to generate full rectified sine waveform using

DAC module11a. Write an 8086 ALP to compute nCr using recursive procedure. Assume that ‘n’ and

‘r’ are non-negative integers.11b. Write an Embedded C program to generate half rectified sine waveform using

DAC module12a. Write an 8086 ALP to generate the first ‘n’ Fibonacci numbers. Input the value of n

and display the Fibonacci numbers.12b. Write an Embedded C program to interface 4 X 4 matrix keyboard using lookup

table and display the key pressed on the Monitor

REFERENCE BOOKS:1. A K Ray & K M Bhurchandi, Advanced Microprocessors and Peripherals : Architecture, Programming and Interfacing, 2nd Edition, Tata McGraw-Hill Pub.

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[ISBN-13: 978-0-07-014062-2]2. RamaniKalpathi& Ganesh Raja, Microcontrollers & Applications, Revised Edition, Sanguine Technical Publishers [ Pearson ]3. Muhammad Ali Mazidi, Janice GillispieMazidi , Rolin D. McKinlay, The 8051 Microcontroller &Embedded Systems (Using Assembly & C), Second Edition, Prentice Hall (Pearson)4. Barry B Brey, The Intel Microprocessors 8086/8088, 0186/80188,80286,80386,80486 Pentium and Pentium processor,6th Edition, Pearson Education.5 . Douglas V.Hall, Microprocessors and Interfacing, Revised 2nd Edition, TMH[ISBN-13:978-0-07-060167-3]

6. LylaB.Das, Microprocessors & Microcontrollers , First Edition, Pearson

[ISBN 978-81-317-6906-5]

Course Outcomes:

1. To identify the required architecture for an application

2. Design and develop efficient software in Assembly level language & Embedded C.

3. Design system configuration for a given application.

4. Integrate, implement and test the design in applications.



Scheme for Self Learning Evaluation:The self-learning must be presented in front of evaluation committee; the members of this

committee will be Faculties handling the subject along with an observer appointed by Head of the Department. Students are required to present their work either in form of technical presentation or in form of live demonstration. At the end of the presentation the students are required to submit the report as per the format recommended by the Dept. or Dean Academics. The format of evaluation for 20 marks is completely under the prerogative of the committee members or as suggested by HOD.


CIE consists of Three Tests each for 40 marks (15 marks for Quiz + 25 marks for descriptive) out of which best two will be considered. In addition 20 marks has to be earned through self-learning component on emerging topics in computer architecture, computing infrastructure and programming.

Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 25) Max Self Study marks : 20

Scheme of Evaluation for Practical’s (50)The students have to execute all the programs listed, in the lab and a record duly signed by the faculty should be maintained. Each program is evaluated independently for 10 marks. Finally, total marks are

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reduced to 30. A lab test will be conducted at the end of the semester for the remaining 20 marks, the questions for the lab test will programs from the given list will be evaluated for 55% of the marks and 35% will be execution of program of the faculty’s choice. The remaining 10% will be viva voce.

Final CIE = Internal Assessment + Self Study valuation + Practical’s (CCE+Test) = 40 x2 (Best Two Scores) + 20 (Self Study valuation) + 30 (CCE) + 20 (Test)

= 150



Scheme of Evaluation for Practical’s (50)In the examination questions must be given from lots. The questions for the lab exam will programs from the given list evaluated for 55% of the marks and 35% will be execution of program of the examiner’s choice. The remaining 10% will be viva voce.

Minimum of 35% should be obtained in both theory & laboratory, with cumulative of marks obtained in theory and laboratory should be minimum 40%.

Policy for Practical Examination/ Test:

Following things are prohibited during the course of the practical session or examination:

No External Devices like – Laptop, Mobile, Pen drives, ipads etc.,Internet must not be accessed during the sessions.

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DATA BASE MANAGEMENT SYSTEMS



Exam Hrs: 03

Prerequisite:Programming Fundamentals , Discrete Mathematical Structures, Probability & Statistics.


1. Analyze the basic concepts and architecture associated with DBMS2. Apply normalization steps in database design and removal of data anomalies3. Describe the characteristics of database transactions and how they affect database integrityand consistency.4. Create, maintain and manipulate a relational database using SQL.5. Employ the conceptual and relational models to design large database6. Finally design databases with reduced redundancy; support for multiuser environment; suggest concurrency and recovery strategies and support from security features


Unit-IIntroduction to Database SystemsDatabases and Database users: Introduction, An example, Characteristics of Database Approach, Actors on the scene, Workers behind the scene, Advantages of using the DBMS Approach, A brief history of Database applications, When not to use a DBMS. Database System—Concepts and Architecture: Data Models, Schemas and Instances, Three-schema Architecture and Data Independence, Database Languages and Interfaces, The Database System Environment, Centralized and Client/Server Architectures for DBMSs, Classification of Database Management Systems.

Entity-Relationship ModelUsing High-Level Conceptual Data Models for Database Design; An Example Database Application; Entity Types, Entity Sets, Attributes and Keys; Relationship types, Relationship Sets, Roles and Structural Constraints; Weak Entity Types; Refining the ER Design for the COMPANY Database; ER Diagrams, Naming Conventions and Design Issues.

8hrs

Unit-IIRelational Model and Relational AlgebraRelational Model Concepts; Relational Model Constraints and Relational Database Schemas;

Update Operations and Dealing with Constraint Violations; Unary Relational Operations:

SELECT and PROJECT; Relational Algebra Operations from Set Theory; Binary Relational

7hrs

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Operations: JOIN and DIVISION ;Additional Relational Operations; Examples of Queries in

Relational Algebra; Relational Database Design Using ER- to-Relational Mapping.

Sql-99: Schema Definition, Basic Constraints and QueriesSQL Data Definition, Specifying Basic Constraints in SQL, Schema Change Statements in

SQL; Basic Queries in SQL; More Complex SQL Queries; Insert, Delete and Update

Statements in SQL

Unit-III

Introduction to SQL programming TechniquesData base programming: Issues and Techniques, Embedded SQL, Dynamic SQL and SQLJ.

Relational Database Design Informal Design Guidelines for Relation Schemas; Functional Dependencies; Normal Forms Based on Primary Keys; General Definitions of Second and Third Normal Forms; Boyce-Codd Normal Form; Properties of Relational Decompositions; Algorithms for Relational Database Schema Design; Multivalued Dependencies and Fourth Normal Form; Join Dependencies and Fifth Normal Form

7hrs

Unit-IVTransaction Processing Concepts

The ACID property, Transaction and schedules, Concurrent Execution of Transactions, Lock based Concurrency control, performance of locking, Transaction support in SQL, Introduction to crash recovery

Concurrency Control2PL, Serializability, recoverability, Introduction to Lock management , Lock conversions, Dealing with Deadlocks, Specialized Locking Techniques, Concurrency control without Locking

7hrs

Unit-VCrash Recovery

Introduction to ARIES, the LOG, Other recovery related structures, The Write Ahead Log protocol, checkpointing, Recovery from a system Crash, media recovery,

Database Security and AuthorizationIntroduction to Database Security Issues, Discretionary Access Control based on Granting and Revoking Privileges, Mandatory Access Control and Role-Based Access Control for Multilevel Security

7hrs

Database Management System LAB

A Mini Project should be implemented and shall be carried out in a batch of two students. The students will finalize a topic in consultation with the faculty. The mini project must be carried out in the college only.The Mini Project tasks would involve

Understand the complete domain knowledge of application and derive the complete

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data requirement specification of the Mini Project

Design of the project

Normalization of the Relational design up to 3NF (Desirable 5NF).

Appreciate the importance of security for database systems.

Documentation and submission of report.

General Guidelines :

Database for the project- MySQL, DB2, Oracle, SQL Server etc

Front End for the project – Visual Basic, C++, C#, Web Interface (HTML, PhP)

Typical Mini Projects

Placement management system.

Result management & analysis system.

RVCE Blog management system.

Student Feedback system

Library management

REFERENCE BOOKS:

1. Elmasri, Navathe; Fundamentals of Database Systems; Pearson Education; 5th Edition; 2006. ISBN – 978-81-317-1625-0

2. Raghu Ramakrishnan and Johannes Gehrke; Database Management Systems; Tata McGraw-Hill;3rd Edition, 2003. ISBN – 0-07-123151-X

3. Silberschatz, Korth and Sudharshan; Data base System Concepts; Tata Mc-GrawHill; 5th Edition; 2002. ISBN – 007-124476-X

Course Outcomes:

1. Understand the fundamentals of database and its operation, different architectures, Query language, transaction, security and recovery issues.

2. Analyze different relational model concepts and normalize relations.3. Design relational models using schema definition and constraints.4. Implement the relational model for transaction using SQL.




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Scheme of Evaluation for Practical’s (50)The students have to execute all the programs listed, in the lab and a record duly signed by the faculty should be maintained. Each program is evaluated independently for 10 marks. Finally, total marks are reduced to 30. A lab test will be conducted at the end of the semester for the remaining 20 marks, the questions for the lab test will programs from the given list will be evaluated for 55% of the marks and 35% will be execution of program of the faculty’s choice. The remaining 10% will be viva voce.


= 150






21



22


SYSTEM SIMULATION & MODELING

Sub Code: 12CS5A1L:T:P:S 3:0:0:1Credits: 4


Exam Hrs: 03

Prerequisite:Students require preliminary knowledge of Probability and Statistics.


System Simulation and Modelling provides the basic understanding of Simulation and its importance in real world. This course lays down the following objectives :

1. Students understand the relevance of simulation in real-world applications.2. Provides an introduction to system modeling using both computer simulation and mathematical

techniques. A wide range of case studies are examined using discrete-event simulation.3. Students understand the relevance of Random numbers and variates to model the stochastic

behavior of real-world system.4. The student will obtain the knowledge and skills to conduct small simulation projects,

consisting of input data analysis, model building, verification and validation, and finally interpretation of output data.

Syllabus Content: Hrs

UNIT – I

1. Introduction:When simulation is the appropriate tool and when it is not appropriate; Advantages and disadvantages of Simulation; Areas of application; Systems and System environment; Components of a system; Discrete and continuous systems; Model of a system; Types of Models; Discrete-Event System Simulation; Steps in a Simulation Study.

2. Simulation Examples:Simulation of Queuing Systems: Waiting Line Models, Simulating a Single-Server queue, Simulating a queue with two servers; Simulation of Inventory Systems: Simulating the News Dealer’s problem, Simulating an (M,N) inventory Policy; Other examples of Simulation: Reliability Problem, Hitting a Target, Estimating the Distribution of Lead-Time Demand, Simulating an Activity Network.

3Hrs

7 Hrs

UNIT – II

3. General Principles:Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance Algorithm, World Views, Manual simulation using Event Scheduling.

4Hrs

23

4. Statistical Models in Simulation, Queuing Models:Review of terminology and concepts; Useful statistical models; Discrete distributions; Continuous distributions: Uniform, Exponential, Normal; Poisson process; Empirical distributions.

Queueing Models: Characteristics of queueing systems; Queueing notation.

5Hrs

UNIT – III

5. Random-Number Generation:Properties of random numbers; Generation of pseudo-random numbers; Techniques for generating random numbers; Tests for Random Numbers: Frequency tests, Test for Autocorrelation.

6. Random-Variate Generation: Inverse transform technique: Exponential Distribution, Uniform Distribution and Discrete Distributions; Acceptance-Rejection technique: Poisson Distribution; SpecialProperties.

5Hrs

4Hrs

UNIT – IV

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

8. Verification and Validation of Simulation Models:Model building, verification and validation; Verification of simulation models; Calibration and validation of models.

5 Hrs

4Hrs

UNIT – V

9. Estimation of Absolute PerformanceTypes of simulations with respect to Output Analysis; Stochastic Nature of Output data; Absolute measures of performance and their estimation;

10. Simulation of Networked Computer SystemsIntroduction; Simulation Tools; Mobility Models in Wireless Systems; The OSI Stack Model; Physical Layer in Wireless Systems; Media Access Control; Data link Layer; TCP;

3Hrs

6Hrs

REFERENCE BOOKS:1. Jerry Banks, John S. Carson II, Barry L. Nelson, David M. Nicol: Discrete-Event System

Simulation, 5th Edition, Pearson Education, 2013, ISBN: 978-81-317-9699-3 (All Units are covered)

2. Lawrence M. Leemis, Stephen K. Park: Discrete – Event Simulation: A First Course, Pearson Education, 2006, ISBN: 9780131429178, Unit I and Unit V

3. Averill M. Law: Simulation Modeling and Analysis, 4th Edition, Tata McGraw-Hill, 2007, ISBN : 9780070667334, Unit I , Unit III and Unit V

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Course Outcomes:

1. Understand the basic concepts of Discrete Event System Simulation & Modeling, and explore the different steps towards simulation of the real-world system or process

2. Analyze whether simulating a given system is appropriate and design a model for the same to address the stochastic nature of input using Random Numbers & Random variates.

3. To formulate and solve real-world problems through the competent use of Computer Simulation methods and Mathematical Modeling techniques.

4. Simulate a given problem and implementation on to real-world system or process








Scheme of Evaluation for Theory (100)-SEEThe question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions (descriptive, analytical, problems or/and design) carrying 16 marks each. All five from Part B will have internal choice and one of the two have to be answered compulsorily.


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PROBABILITY, STATISTICS and QUEUING



Exam Hrs: 03

Prerequisite:

Student will have to undergo the elementary engineering mathematics of all the four semester.


After completing the course the student should be able to work with the basic problems in conditional probability, conditional expectation, Sampling Theory, inferences concerning means, inferences concerning variances, hypothesis testing,Markovchain,Poisson process, and queuing theory. An engineering student should have mastered the following quantitative skills after completing this course:

1. Compute the probabilities of composite events using the basic rules of probability.2. Exhibit the significance of the connection between logic, sets, probability, statistics, queuing theory and theirapplicability to the real world.3. Explain the concept of approximation, estimation, error, hypothesis testing, and accuracy in interpreting the resultsof such measurements.4. Demonstrate several approaches to basic problem solving and implement those strategies.5. Acquire, organize, and synthesize information and creatively use of that information.


UNIT – I

Conditional probability, Conditional expectation and Sampling theoryConditional probability, Bayes Theorem, Joint distributions-discrete and continuous, covariance, Conditional expectation, computing expectations by conditioning, computing variances by conditioning, central limit theorem, sampling distribution of the mean (known and unknown), sampling distribution of difference of means, sampling distribution of the variance.

7 Hrs

UNIT – II

Estimation and Tests of HypothesisInterval estimation of mean(sigma known and sigma unknown),Estimation of difference between two means, interval estimation of variance, Tests of Hypotheses, Type-I error, Type II error, Hypotheses concerning Mean, The relation between test and confidence intervals. Hypothesis concerning two Means, Hypothesis concerning variance, Hypothesis concerning two variances.

7 Hrs

26

UNIT – III

Probability bounds,Approximations, Computations and Poisson processesTail probability in equalities-Markov’s inequality, Chern off bounds, Jensen’s inequality,The second moment and the conditional expectation inequality, Poisson random variables, The exponential distribution and its properties, Counting processes, Definition of Poisson process, Inter arrival and waiting time distributions, Further properties of Poisson process,Conditional distribution of the arrival times,

7 Hrs

UNIT – IV

Introduction to queuing TheoryIntroduction, Preliminaries, Exponential models,Birth-and-Death process models,M/M/1 queuing system, M/M/1/c queuing system, M/M/c queuing system, M/M/c/c,other queuing systems.

7 Hrs

UNIT – V

Markov ChainsChapman-Kolmogorov equations, Transition matrix of Markov process, Classification of states, Limiting probabilities, mean time spent in transient states, branching processes, time reversible Markovchain, Markov chain Monte-Carlo methods and Markov decision processes.

7 Hrs

REFERENCE BOOKS:

1. MillerandFreund’s(Richard.A.Johnson,C.B.Gupta), Probability and statistics for Engineers, PearsonEducation, Second impression 2007. ISBN- 978-0-12-051051-1, Unit I,II,III,V

2. Sheldon M. Ross, Introduction to Probability and Statistics for Engineers and Scientists Academic Press-An imprint of Elsevier, 4thEdition, First reprinted in India 2011. ISBN-9780123705280, Unit I,II,III

3. Sheldon M. Ross, Introduction to Probability Models, Academic Press-An imprint of Elsevier, 9thEdition, 2009. ISBN-9780080920177, Unit I,II,III

4. R.E.Walpole, S.L.Myersand Keying Ye, Probability and Statistics for Engineers and Scientists, Pearson Education, Eight Edition,2007.ISBN81-7808-613-1 Unit I,II,III,V

5. Arnold,O.AllenIntoductiontoProbability and Statistics and Queuing with ComputerScience Applications, An imprint of ELSEVIER,AP, Second Edition, 2011, Unit IV

27

Course Outcomes:1. Understand many basic skills of probability, statistics ,markov chains and queuing.2. analyze the significance of the connection between logic , sets, probability, estimation, testing,

classification of states, birth and death process3. Demonstrate the concept of sampling, relation between real world confidence intervals,

hypothesis concerning parameters, counting and poison processing, queuing models and accuracy in interpreting the results of such measurements.

4. Apply the concepts to the real world.









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OBJECT ORIENTED ANALYSIS AND DESIGN


CIE Marks: 100 Exam Hrs: 3 Hrs

SEE marks: 100

Prerequisite:

Student should have working knowledge of object oriented programming language.


1. Strengthen and solidify understanding of Object Oriented Analysis and Design concepts and apply them to solve problems using Unified Modeling Language

2. Gather and apply system’s requirements with use cases and understanding requirements, analysis and design workflow.

3. Specify object interaction in UML and to identify association and inheritance between classes.

4. Analyze, design and develop key mechanisms.

Syllabus Content

UNIT I 8 Hrs

Introduction.

An overview of object oriented systems development, why an object orientation?,

overview of the United Approach. Object basics-Introduction, an object-oriented

philosophy. Objects, classes, attributes- object behavior and methods. Encapsulation

and information hiding, class hierarchy, polymorphism, object relationships and

associations, aggregations and object containment. Case study- payroll program,

advanced topics. Object-oriented systems development life cycle- Introduction, the

software development process, building high-quality software, object oriented

systems development - a use-case driven approach, reusability.

UNIT II 6 Hrs

Modeling and UML.

The unified approach, Unified Modeling Language (UML) - Introduction, static and

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dynamic models, why modeling?, introduction to the unified modeling language,

UML diagrams, UML class diagram, use-case diagram. UML dynamic modeling,

model management - Packages and model organizations, UML extensibility, UML

meta-model.

UNIT III 8 Hrs

Object Oriented Analysis - Identifying Use Cases Introduction, why analysis is a difficult activity?, Business object analysis,

use case driven object oriented analysis, Business process modeling, use-case

model, developing effective documentation.

Object Oriented Analysis - ClassificationIntroduction, classification theory, approaches for identifying classes-Noun phrase

approach, Common Class Pattern approach, Use case driven approach, Classes

Responsibilities, and Collaborators (CRC) , naming classes, identifying object

relationships, attributes and methods - introduction, associations, super-sub class

relationships, A-part-of relationships-aggregation.

Case study: Analyzing the ViaNet Bank ATM- the use case driven process, the

ViaNet bank ATM system-Identifying classes by using noun phrase approach,

identifying classes using common class patterns approach, use-case driven approach-

identifying classes and their behaviors through sequence/collaboration modeling,

Classes, Responsibilities and Collaborators (CRC), relationship analysis for the

ViaNet bank ATM system, class responsibility-Identifying attributes and methods,

class responsibility - defining attributes by analyzing use cases and other UML

diagrams, defining attributes for ViaNet bank objects, object responsibility -methods

and messages, defining methods for ViaNet bank objects.

UNIT IV

Object-Oriented Design

The object-oriented design process and design axioms: Introduction, The object-oriented

design process and design axioms, corollaries, design patterns. Designing classes-

Introduction, the object-oriented design philosophy, UML object constraint language.

Designing classes - the process, class visibility - designing well-defined public,

private and protected protocols. Designing classes- refining attributes, designing

6 Hrs

30

methods and protocols.

Case Study: refining attributes for the ViaNet bank objects, designing methods for the

ViaNet bank objects, packages and managing classes.

UNIT V 7 Hrs

Patterns

Patterns- what is a pattern?, what makes a pattern?, pattern categories, relationship

between patterns, pattern description, patterns and software architecture. Design

Pattern- Master Slave Pattern, Whole Part Pattern.

Reference Books:

1. Ali Bahrami: Object oriented systems development, McGraw-Hill, 2nd Edition, 1999.

2. David J. Barnes & Michael Kölling, Objects First with Java, A Practical Introduction using BlueJ, Fifth edition, Prentice Hall / Pearson Education, 2012, ISBN 978-013-249266-9, Prentice-Hall India, 2nd Edition, 1990.

3. Sandi Metz, Practical Object-Oriented Design in Ruby: An Agile Primer, Addison Wesley Professional, 1st Edition, ISBN-10: 0-321-72133-0.

4. Gamma. E: Design patterns: Elements of reusable Object oriented software, Addison-Wesley, 2nd Edition, 1995.

Course Outcomes:

1. Understand object-oriented approaches and perspectives of systems development and to demonstrate the difference between object-oriented approaches and traditional approach.

2. Analyze the real world problems and construct UML model using the appropriate notation.3. Design the system from the requirements model using UML notations.4. Evaluate the design for applicability to produce high quality software that meets the requirements.





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32

INTRODUCTION TO MACHINE LEARNING



Exam Hrs: 03

Prerequisite:Students are expected to have the following background:

1. Knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program.

2. Familiarity with the basic probability theory.3. Familiarity with the basic linear algebra


1. Have basic knowledge about the key algorithms and theory that form the foundation of machine learning and computational intelligence

2. Have a practical knowledge of machine learning algorithms and methods so that they will be able to understand the principles, advantages, limitations and possible applications of machine learning

3. Understand the principles, advantages, limitations and possible applications of machine learning

4. To identify and apply the appropriate machine learning technique to classification, pattern recognition, optimization and decision problems.

5. Leverage interpersonal dynamics and leadership.


UNIT – I

Introduction to ML:Probability Theory, Probability densities, Expectations and covariances, Bayesian

probabilities, The Gaussian distribution, Bayesian curve fitting, Model Selection, The Curse of Dimensionality, Decision Theory, Minimizing the misclassification rate, Minimizing the expected loss, The reject option, Inference and decision, Loss functions for regression, Information Theory, Relative entropy and mutual information.

7Hrs

UNIT – II

Bayesian Decision Theory:Bayesian Decision Theory-Continuous Feature, Minimum – Error – Rate Classification, Classifiers, Discriminant Functions, and Decision Surfaces, The Normal Density, Discriminant Functions for the Normal Density.Multilayer Neural Networks:

4Hrs

33

Introduction, Feed Forward Operation and Classification, Back Propagation Algorithm

3Hrs

UNIT – III

Non Parametric Techniques:Density Estimation, Parzen Window, K-n-Nearest- neighbor Estimation, the nearest neighbor Rule, Metrics and Nearest Neighbor Classification, Fuzzy Classification

Linear Discriminant functions:Linear Discriminant functions and decision surfaces, Generalized Linear Discriminant functions, The two category linear separable case, Relaxation Procedures

4Hrs

3Hrs

UNIT – IV

Unsupervised Learning and Clustering:Mixture Densities and Identifiability, Maximum Likelihood Estimates, Applications to Normal Mixtures, Data Discription and Clustering, Criterion Functions for Clustering, Iterative Optimization, Hierarchical Clustering, The Problem of Validity, Online Clustering, Graph Theoretic Methods.

7Hrs

UNIT – V

Case studies: Collaborative filtering :Predict the rating from user to movie, Document Retrieval: Finding similar documents, Clustering documents, Estimating Click Probabilities : Predicting click probabilities, Classification:Spam detection

Recent trends : Topics to be selected by the faculty handling the Course Code and given as assignments to the students (Assignment for 10 marks).

7Hrs

REFERENCE BOOKS:1. "Pattern Recognition and Machine Learning" by Christopher M. Bishop, Springer, ; 1st ed.

2006. Corr. 2nd printing 2011 edition, ISBN-13: 978-0387310732

2. "Pattern Classification" by Richard O. Duda, Peter E. Hart and David G. Stork, 2nd edition; 2001, Wiley-Interscience, ISBN-13: 978-0471056690

3. "Artificial Intelligence A Modern Approach", by Stuart J. Russell and Peter Norvig3 edition 2009, , Prentice Hall; ISBN-13: 978-0136042594

4. Machine Learning by Tom Mitchell, 1st edition; 1997, TATA McGraw-Hill ISBN-13: 978-0070428072

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Course Outcomes:

1. Understand the fundamentals and theory of machine learning techniques.2. Apply and use different mathematical techniques to construct algorithms.3. Analyze the strength and weakness of different machine learning models to solve real world

problems.

4. Implement and apply different machine learning algorithms using supervised and unsupervised techniques.









35


DISTRIBUTED OPERATING SYSTEM



Exam Hrs: 03

Prerequisite:

Student should have knowledge of operating systems.


1. To understand andexamine the fundamental principles of distributed systems.2. Present the principles underlying the functioning of distributed systems.3. Create an awareness of the major technical challenges in distributed systems design and

implementation4. To study distributed systems in a broader sense. Emphasis will be placed on Message passing,

Remote procedure calls, Distributed shared memory, Process migration and Synchronization.5. To study various Distributed Deadlock, Scheduling and Load balancing Algorithms.6. Expose students to past and current issues in the field of distributed systems.


Unit –I

1. FundamentalsWhat is Distributed Computing Systems? Distributed Computing System Models, What is Distributed Operating System?, Issues in Designing a Distributed Operating System.

Message PassingDesirable Issues of Good Message Passing, Issues in IPC by Message Passing, Synchronization, Buffering, Multi datagram Messages, Encoding and Decoding of Message Data, Process Addressing, Failure Handling, Group Communication

4 Hrs

6 Hrs

UNIT – II

Remote Procedure CallsThe RPC Model, Transparency of RPC, Implementing RPC Mechanism, Stub Generation, RPC Messages, Marshaling Arguments and Results, Server Management, Parameter - Passing Semantics, Call semantics, Communication Protocols for RPCs.

7Hrs

UNIT – III

Distributed Shared MemoryGeneral Architecture of DSM Systems, Design and Implementation Issues of DSM,

5Hrs

36

Granularity, Structure of Shared Memory Space, Consistency Models, Replacement Strategy, Thrashing.

UNIT – IV

SynchronizationClock Synchronization , logical clocks , physical clock, clock synchronization algorithms, Mutual exclusion: a centralized algorithm , a distributed algorithm ,a token ring algorithm, Election algorithms , The Bully algorithm, Dead locks in distributed systems , Distributed deadlock detection , distributed deadlock prevention.

7hrs

UNIT – V

Resource ManagementDesirable Features of a Good Global Scheduling Algorithm, Task Assignment Approach, Load – Balancing Approach, Load – Sharing Approach.

Process ManagementProcess Migration, Threads , usage, design issues for thread packages.

3hrs

3Hrs

REFERENCE BOOKS:

1. Pradeep. K. Sinha; Distributed Operating System: Concepts and Design; Prentice-Hall of India Pvt.Ltd; 1st Edition, 2009. ISBN – 9788-120313804

2. Andrew S. Tanenbaum; Distributed Operating System; Pearson Education, 6 th Edition, 2009. ISBN – 978-0132199087

3. G. Coulouris, J.Dollimore& T. Kindberg; Distributed Systems Concepts and Design, Pearson Education; 5th Edition; 2011. ISBN – 978-0132143011

4. Andrew S. Tanenbaum; Maarten Van Steen; Distributed Systems Principles and Paradigms; Pearson Education;2nd Edition; 2007. ISBN – 9780132392273

Course Outcomes:

1. Understand fundamentals of Distributed Operating System, computing system, remote procedure call, shared memory, synchronization and resource management.

2. Design computing model, message passing, RPC, shared memory, resource and process management.

3. Implementation of message passing algorithms, encoding, decoding, PRC, synchronization algorithms, resource and process management.

4. Apply above algorithm to check functionality of group communication, RPC, deadlock detection, prevention, thread packages, memory replacement softwares.


content of tutorial sessions. Students demonstrate realization of the real-life applications achieved independently. This exercise is to assess understanding of the fundamentals by student and their

37

aptitude to apply the same to real world problems.







38


ARTIFICIAL INTELLIGENCE



Exam Hrs: 03

Prerequisite:This Course requires a background in computer programming, algorithms and data structures, and basic discrete mathematics and probability theory.


1. Understand fundamental AI concepts and current issues.2. Understand and apply a range of AI techniques including search, logic-based reasoning, neural

networks and reasoning with uncertain information.3. Recognize computational problems suited to an AI solution.4. To have an understanding of the basic issues of knowledge representation, blind and heuristic

search.5. Understand the design issues inherent in different AI approaches.


Unit –I

1.Introduction and Review of AI: What is AI? The foundations of AI, The history of AI. Introduction Concepts and definition of AI, AI Problems, The Underlying assumption, What is an AI technique?, AI characteristics, AI versus Natural Intelligence, Applications of AI, etc. AI as Representation and Search – The Predicate Calculus- Inference rules.

7hrs

Unit –II2.Heuristic SearchHeuristic Search – An algorithm for heuristic search, Admissibility, Monotonicity and informedness, Heuristic in games, complexity issues. Control and implementation of state space search- Recursion based search, pattern directed search, production systems, Predicate calculus and planning. The black board architecture for Problem solving.

8Hrs

Unit –III3. Knowledge based systemsUncertainty: Acting under uncertainty; Inference using full joint distributions; Independence; Bayes’ rule and its use; The Wumpus world revisted.Probabilistic Reasoning: Representing knowledge in an uncertain domain; The semantics of Bayesian networks; Efficient representation of conditional distributions; Exact inference in

8hrs

39

Bayesian networks; Approximate inference in Bayesian Networks; Extending probability to first-order representations.

Unit –IV4. Learning MethodsKnowledge in Learning:A logical formulation of learning; Knowledge in learning; Explanation-based learning; Learning using relevance information; Inductive logic programmingStatistical learning; Learning with complete data; Learning with hidden variables; Instance-based learning.

8hrs

Unit-V5. Philosophical Foundations: Weak AI and Strong AI; The ethics and risks of developing AI. AI: Present and Future:Agent components; Agent architectures; Are we going in the right direction? What if AI does succeed?

5hrs

REFERENCE BOOKS:1. Stuart Russel, Peter Norvig: “Artificial Intelligence A Modern Approach”, 2nd Edition,

Pearson Education, 2003.2. G. F lunger and W. A Stubblefield, Artificial Intelligence – Structures and Strategies for

complex problem solving, 4thEdition,addsison –Wesley, 1998.3. Elaine Rich, Kevin Knight: “Artificial Intelligence”, 3rd Edition, Tata McGraw Hill, 2009.4. P.H Winston, Artificial Intelligence, Third Edition, Addison-Wesley, 1992.5. Nils J. Nilsson: “Principles of Artificial Intelligence”, Elsevier, 1980.

Course Outcomes:

1. Understand the basic concepts and challenges of Artificial Intelligence.2. Apply basic Artificial Intelligence algorithms to solve problems.3. Connect the ethical issues in Artificial Intelligenceand combine various logic-based techniques

in research applications.4. Assess the strong association by comparing different Artificial Intelligence techniques.





40





41


GRAPH THEORY AND APPLICATIONS



Exam Hrs: 03

Prerequisite:

Student should have the knowledge of the Discrete Mathematics and Data structures.


1. Representing the real world problems using graphs makes the problem easy to understand.2. Solving Real world problems

3. Application of the graph theory


Unit –I

1. Introduction to graph theoryIntroduction, why study graphs?, mathematical preliminaries, definitions and examples of graphs, degrees and regular graphs, sub graphs, directed graphs, in degrees and out degrees in digraphs.

2. Basic concepts in graph theoryPaths and cycles, connectivity, homomorphism and isomorphism of graphs, connectivity in digraphs.

8hrs

Unit –II3. Graph representations, Trees, Forests

Adjacency matrix of a graph, Incidence matrix of a graph, Adjacency lists, Trees and properties of trees, Characterization of trees, Centers of trees, Rooted trees, Binary threes, Spanning trees and forests, Spanning trees of complete graphs, An application to electrical networks, Minimum cost spanning trees.

4. Fundamental properties of graphs and digraphsBipartite graphs, Eulerian graphs, Hamiltonian graphs, Hamiltonian cycles in weighted graphs, Eulerian digraphs, Tournament in digraphs, Acyclic digraphs.

8Hrs

Unit –III5. Planar graphs, Connectivity and Flows

8hrs

42

Embedding in surfaces, Euler’s formula, Characterization of planar graphs, Kuratowski’s theorem, Dual of a planar graphs, Edge cuts, Edge connectivity, Blocks in separable graphs, Flows in networks, Menger’s theorem.

6. Matchings and FactorsMaximum matching, Hall’s matching condition, Min-Max theorem, Independent sets and covers, Dominating sets, maximum bipartite matching, weighted bipartite matching, stable matching.

Unit –IV7. Coloring of graphs

The chromatic number of a graph, Multipartite graphs, Results for general graphs, The chromatic polynomial of a graph, Basic properties of chromatic polynomial, chordal graphs, powers of graphs, Edge coloring of graphs, Tait’s theorem.

6hrs

Unit-V8. Graph algorithms

Graph connectivity algorithms, Algorithm of Warshall, Breadth first search and Depth first search, Shortest path algorithms, Dijikstra’s shortest path algorithm, Bellman-Ford algorithm, Minimum cost spanning tree algorithms, Algorithm of Kruskal’s and Prim’s. Ford-Fulkerson algorithm to find max flow in a network.

8hrs

REFERENCE BOOKS:1. Douglas B. West, “Introduction to graph theory”, 2nd Edition, PHI.

2. GeirAgnarsson, Raymond Greenlaw, “Graph Theory, modeling, Applications and Algorithms”, Pearson Education.

3. Cormen, Leiserson, Rivest, Stein, An Introduction to Algorithms, 3rd Edition, PHI publication.

Course Outcomes:1. Understand the basics of graph theory2. Analyse the significance of graph theory in different areas of computer science3. Demonstrate algorithms used in various fields of computer science.4. Synthesize any real world applications using graph theory.




committee will be Faculties handling the subject along with an observer appointed by Head of the

43

Department. Students are required to present their work either in form of technical presentation or in form of live demonstration. At the end of the presentation the students are required to submit the report as per the format recommended by the Dept. or Dean Academics. The format of evaluation for 20 marks is completely under the prerogative of the committee members or as suggested by HOD.





44


JAVA & JEE

Sub Code: 12CS5B1L:T:P:S 3:1:0:0Credits: 4


Exam Hrs: 03

Prerequisite:Student should have undergone programming in C and object oriented programming in C++


1. To map the concept learnt under object orientation by considering suitable use-cases and implement same using the programming constructs specified in Java.

2. To build awareness of basic programming constructs and methods in Java and implement simple programs on it.

3. To introduce utilities and advanced programming concepts in Java to cater the demand of full-fledged application.

4. To present an industry relevant technology and highlight its roles in an Enterprise application.5. To develop a project that will apply concepts in to workable code.


Unit –I

1. Java Programming Fundamentals: Features, Data Types, Variables and Arrays , Operators , Control Statements ,Introduction to Classes : Class Fundamentals , Declaring Objects , Assigning Object Reference Variables , Introducing Methods , Constructors ,Static fields and Methods, Super and this keyword, Inheritance ,Interface ,Inner-classes, Package.Example of Class template in Java Programming – Exceptions, Threads, Java Collections.

7Hrs

Unit –II2. Exception Handling : Exception-Handling Fundamentals – Exception Classes , Exception Types, Uncaught Exceptions, Using try and catch, Multiple catch Clauses, Nested try Statements, throw,throws,finally,Java’s Built-in Exceptions, Creating Your Own Exception Subclasses Chained Exceptions .Multithreaded Programming : Java Thread Classes, The Java Thread Model , The Main Thread , Creating a Thread, Creating Multiple Threads, Using isAlive( ) and join( ) , Thread Priorities , Synchronization , Suspending, Resuming and Stopping Threads ,Selfish thread.

7Hrs

Unit –III3. Collections :The Collection Interfaces , The Collection Classes , Accessing a Collection via an Iterator , Storing User-Defined Classes in Collections, The RandomAccess Interface.

J2EE Database Concepts : JBDC Driver types , JDBC Packages , JDBC Process,

8Hrs

45

Database Connection , Connection pool ,Statement Objects , Result Sets , Transaction processing ,Exceptions.

Unit –IV4. MVC: An overview of application architecture, multi-tier architecture, Applying Software architecture pattern - MVC Architecture,Servlets: The Life Cycle of a Servlet, Using Tomcat for Servlet Development A simple Servlet, The Servlet API, The Javax.servlet Package, Reading Servlet Parameter, The Javax.servlet.http package, Handling HTTP Requests and Responses, Using Cookies, Session Tracking;

Java Server Pages (JSP): JSP Tags, Tomcat, Request String, User Sessions, Cookies, Session Objects.

7Hrs

Unit-V5. Native methods : Calling a C function from Java programming Language , Numeric parameters and return Values, String Parameter ,Accessing Fields ,Encoding Signatures , Calling Java methods ,Accessing array elements ,Handling Errors.

7Hrs

REFERENCE BOOKS:1. Herbert Schildt ,"The Complete Reference - Java " 7th Edition ,TMH Publications.2. Jim Keogh ,"The Complete Reference -J2EE ",Tata McGRAW Hill publications.3. Cay S.Horstmann ,"Core Java 2 Vol II "7th Edition ,Pearson ,2005.

Course outcomes:1. Understand the fundamentals of JAVA , Exception ,String handling ,JDBC ,JNI ,JSP.2. Design application using Java allied technologies.3. Develop an application using Collection framework , JDBC ,JNI and Servlets.4. Implement web based application using Java and advance J2EE technologies.





46


INTRODUCTION TO MAINFRAMES



Exam Hrs: 03

Prerequisite:

Students should have basic knowledge in operating systems and programming languages.


1.Demonstrate an understanding of the mainframe operating system2. Able to create JCL to execute mainframe jobs.


Unit –I

1. Introduction to New Mainframe The new mainframe, An evolving architecture, what is a mainframe, who uses mainframe computers, Factors contributing to mainframe use, Typical mainframe workloads, Rolesin the mainframe world, z/OS and other mainframe operating systemsMainframe Hardware Systems and High Availability

Introduction to mainframe hardware systems, Early system design, Current design, Processing units, Multiprocessors, Disk devices, Clustering, Basic shared DASD, What is

a sysplex, Intelligent Resource Director, Platform Performance Management withzEnterprise, Typical mainframe system growth, Continuous availability of mainframes.

8Hrs

Unit –II2. Mainframe Hardware Systems and High Availability

Introduction to mainframe hardware systems, Early system design, Current design, Processing units, Multiprocessors, Disk devices, Clustering, Basic shared DASD, What is

a sysplex, Intelligent Resource Director, Platform Performance Management withzEnterprise, Typical mainframe system growth, Continuous availability of mainframes.

7Hrs

Unit –III3. TSO/E, ISPF, and UNIX: Interactive facilities of z/OS

How do we interact with z/OS, Time Sharing Option/Extensions overview, ISPF overview, z/OS UNIX interactive interfaces.

Using Job Control Language and System Display and Search FacilityWhat is Job Control Language (JCL), JOB, EXEC, and DD parameters, Data set

7Hrs

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disposition and the DISP parameter, Continuation and concatenation, Why z/OS uses symbolic file names, Reserved DDNAMES, JCL procedures (PROCs), Understanding SDSF, Utilities, System libraries.

Unit –IV4. Designing and developing applications for z/OSApplication designers and programmers, Designing an application for z/OS, Application

development life cycle: An overview, Developing an application on the mainframe, Going into production on the mainframe .

Using programming languages on z/OSOverview of programming languages, Choosing a programming language for z/OS, Using Assembler language on z/OS, Using COBOL on z/OS, HLL relationship between JCL and program files, Using PL/I on z/OS, Using C/C++ on z/OS, Using Java on z/OS, Using CLIST language on z/OS, Using REXX on z/OS, Compiled versus interpreted language, What is z/OS Language Environment.

8Hrs

Unit-VOverview of system programming

The role of the system programmer, separation of duties, customizing the system, Managing system performance, Configuring I/O devices, following a process of change control, Configuring consoles, initializing the system.

Security on z/OSWhy security is important, Security facilities of z/OS, Security roles, The IBM Security Server, Security administration, Operator console security, Integrity.

6Hrs

REFERENCE BOOKS:IBM Redbook ‘Introduction to the New Mainframe - z/OS Basics’ and provided slides.(On the course site in ‘References’ folder as: zOSIntro.pdf)

Course Outcomes:1. Understand the fundamental concepts of mainframe operating system and its architecture2. Analyze the mainframe workloads3. Integrate the middlewaretools for main frame applications.4. Design, develop, test and maintain mainframe applications.




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49


MIDDLEWARE TECHNOLOGIES



Exam Hrs: 03

Prerequisite:

Students should have knowledge of Operating System, Computer Networks and Application Architectures.


1. Understand the essence of client-server architecture and its impact on all walks of the network-based computing. Understand the evolution of middleware Technologies.

2. Identify a working knowledge of the role of middleware in distributed information systems, the types of middleware in common use in enterprise information systems, and their operation.

3. Analyze and make competent judgements about the appropriate choices of middleware for solving practical distributed information system problems.

4. Apply the design and build a distributed information system by creating and integrating services using several different types of middleware.


Unit –I

1. Client/Server Concepts: Client-Server, File Server, Database server, Group server, Object Server, Web server, Middleware – General middleware –Service specific middleware. Client/Server Building blocks – RPC – Messaging – Peer- to- Peer. Web Services - SOAP, WSDL.

10Hrs

Unit –II2. EJB Architecture: EJB –EJB Architecture – Overview of EJB software architecture – View of EJB – Conversion – Building and Deploying EJBs – Role in EJB.

6Hrs

Unit –III3. EJB Applications: EJB Session Beans – EJB entity beans – EJB Clients – EJB Deployment Building an application with EJB.

10Hrs

Unit –IV4. Architecture overview – CORBA, COM: Distributed object fundamentals, COM and CORBA on the server side-strategic directions of COM and CORBA, Introduction to .NET –

10Hrs

50

Overview of .NET architecture – Marshalling – Remoting.Unit-V5. Object- Oriented Programming with C#: Forms defining of the C# Class, Definition the “Default Public Interface” of a Type, Recapping the Pillars of OOP, The First Pillars: C#’s Encapsulation Services, Pseudo- Encapsulation: Creating Read-Only Fields, The Second Pillar: C#’s Inheritance Supports, keeping Family Secrets: The “Protected” Keyword, Nested Type Definitions, The Third Pillar: C #’s Polymorphic Support, Casting Between. Client server with distributed objects: distributed objects and components

12Hrs

REFERENCE BOOKS:1. Robert Orfali, Dan Harkey and Jeri Edwards, The Essential Client / Server Survival Guide,

Galgotia Publications Pvt.Ltd, 2002 (Unit 1&5).2. Tom Valesky, Enterprise Java Beans, Pearson Education, 2002 (Unit 2 & 3).3. Jason Pritchard, COM and CORBA side by side, Addison Wesley, 2000 (Unit 44. Jesse Liberty, Programming C#, 2ndEdition , O’ Reilly Press , 2002 (Unit4).5. Andrew Troelsen: Programming C# with .NET 3.0, 4th Edition, Wiley India, 2009.(Unit5)6. E. Balagurusamy: Programming in C#, 2nd Edition, Tata McGraw Hill, 2008. (Unit5)

Course outcomes:CO1: Understand the essence of client-server architecture and the evolution of middleware Technologies.CO2: Analyzethe appropriate choices of middleware for solving practical distributed information system problems.CO3: Design the role of middleware in distributed information systems and different middlewareTechnologies .CO4: Develop distributed information system applications by creating and integrating services using different middleware technologies.





51


ADVANCED ALGORITHMS



Exam Hrs: 03

Prerequisite:

1. Knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program.

2. Familiarity with the basic Data structure concepts.

3. Must have done Analysis and Design of algorithms course.


1. Design and implement `new' algorithms in the real world.2. Map practical problems to algorithmic problems.3. Read and understand algorithms published in journals.4. Develop writing skills to present own algorithms5. Collaborate and work together in group to design new algorithms.


Unit –I

1. Analysis techniques:Growth of functions: Asymptotic notation, Standard notations and common functions, Substitution method for solving recurrences, Recursion tree method for solving recurrences, Master theorem, Amortized analysis, Aggregate, Accounting, and Potential methods

7Hrs

Unit –II2. String Matching Algorithms:Naïve algorithm, Rabin-Karp algorithm, String matching with finite automata, Knuth-Morris-Pratt algorithmGraph AlgorithmsBellman-Ford Algorithm, Shortest paths in a DAG, Johnson’s Algorithm for sparse graphs.

7Hrs

Unit –III3. Advanced Data structures

Red-Black tree, Fibonacci heaps, Splay trees, Binomial Queues, skip lists.

Maximum Flow:Flow networks, Ford Fulkerson method and Maximum Bipartite Matching

7Hrs

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Unit –IV4. Number Theoretic Algorithms:

Elementary notions, GCD, Modular arithmetic, solving modular linear equations, The Chinese remainder theorem, powers of an element, RSA cryptosystem, primality testing, Integer factorization

7Hrs

Unit-V5 Polynomials and the FFT

Representation of polynomials; The DFT and FFT; Efficient implementation of FFT.

Recent trends : Topics to be selected by the faculty handling the Course Code and given as assignments to the students (Assignment for 10 marks).

7Hrs

REFERENCE BOOKS:

1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein; Introduction to Algorithms; Columbia University, 3rd Edition; 2009, ISBN-13: 978-0262033848.

2. Mark Allen Weiss; Data Structures and Algorithm Analysis in C++; Addison-Wesley; 4th Revised edition; 2013, ISBN-13: 9780132847377.

Course Outcomes:1. Understand the fundamentals of Asymptotic notation, Standard notations and common

functions , Naïve string matching algorithm, Flow networks, Elementary notions, GCD, Representation of polynomials.

2. Analyze and solve practical problems using different algorithmic techniques.3. Design robust algorithms using mathematical techniques.4. Implement advanced techniques for a given problem.





53


FUNDAMENTALS OF COMPUTER VISION



Exam Hrs: 03

Prerequisite:Most of the knowledge required should be part of the standard background in Computer Science and basics of Mathematics. It is a prerequisite that students have knowledge in fundamental of computer science and programming techniques. This course builds on some fundamental image processing methodology and Computer vision concepts.


1. This course will present a broad, introductory survey intended to develop familiarity with the approaches to modelling and solving problems in computer vision. Analyze basic concepts and methodologies of Digital Image processing.

2. Apply and Analyze image enhancement using filters.3. Construct image features, segmentation and texture from an image.4. The students learn to choose appropriate features to recognize patterns.5. Clear understanding of different algorithms for pattern recognition.

Student can apply the algorithms for real time applications.

Goal and ObjectivesTo introduce the fundamental problems in computer vision.To introduce the main concepts and techniques used to solve those.To enable participants to implement solutions for reasonably complex problems.To enable participants to understand basic methodology that is discussed in the computer visionLiterature

This course covers fundamental topics in image processing and topics in computer vision with a focus on image statistics, machine learning techniques, and applied vision. Topics include image representations, frequency analysis, filtering techniques, segmentation, Bayesian inference, object recognition and scene understanding.


Unit –I

1. Introduction to Digital Image FundamentalsWhat is Digital Image Processing? The origin of Digital Image processing, Fundamental Steps in Digital Image Processing, Components of an Image Processing System, Image Sampling and Quantization, Some Basic Relationships between Pixels.

7Hrs

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2. Introduction: What is computer vision?, A brief history;

Unit –II3. Image Processing-I

Point operators: Pixel transforms Color transforms, Compositing and matting, Histogram equalization, Locally adaptive histogram equalization.Linear filtering: Separable filtering, Examples of linear filtering, Band-pass , steerable filters;More neighborhood operators: Non-linear filtering.Fourier transforms: Fourier transform pairs, Two-dimensional Fourier transforms, Wiener filtering.

9Hrs

Unit –III4. Image SegmentationThresholding : Foundation, Basic global thresholding , Optimum global thresolding using Otsu’s method, using image smoothing to improve Global thresholding , Using edge to improve Global thresholding.

9Hrs

Unit –IV5. SegmentationSplit and merge: Watershed, Region splitting (divisive clustering), Region merging (agglomerative clustering), Graph-based segmentation, Probabilistic aggregation.Mean shift and mode finding: K-means and mixtures of Gaussians, Mean shift.

4Hrs

Unit-V6. Recognition-IObject detection; Face detection, Face recognition; Eigen faces , Active appearance and 3D shape models, Application: Personal photo collections,Category recognition; Bag of words, Part-based models, Recognition with segmentation.

5Hrs

REFERENCE BOOKS:1. Richard Szeliski, “Computer Vision: Algorithms and Applications" , Springer Verlag :

http://szeliski.org/Book/2. Rafael C. Gonzalez, Richard E. Woods; ”Digital Image Processing”; Pearson Education; 3rd

Edition; 2012;3. David Forsyth and Jean Ponce, "Computer Vision: A Modern Approach" .4. Milan Sonka, Vaclav Hlavac, Roger Boyle, “Image Processing , Analysis and Machine

Vision”.

Course Outcomes:[1-4]

After the course students will be able to:

After going through this course the student will acquire:1. The basic concepts of the processes and hardware of image acquisition, pre-processing

operations in image enhancement. Color transforms, Histogram equalization, Segmentation and

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feature extraction operations, Recognition.2. Ability to analyze inherent difficulties of the pattern recognition problems, classification

techniques, Feature detection, Histogram equalization process and design.3. Formulating and solving using mathematical expressions using Non-linear and linear filters,

Bayesian, maximum-likelihood, Mean shift and mode finding, Compression4. Exploring perception on scene understanding , real time application clearly and concisely using

pattern recognition terminology, Edge and feature detection concepts, point processing, Applications like Sharpening, blur, noise removal, Tonal adjustment, scene understanding.





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MULTIMEDIA COMPUTING



Exam Hrs: 03

Prerequisite:

Student should have undergone the Data structures and must be aware of programming concepts.


1. To provide the foundation knowledge of multimedia computing, e.g. media characteristics, compression standards, multimedia representation, data formats, multimedia technology development.

2. To provide programming training in multimedia computing, multimedia system design and implementations.

3. To provide a fundamental knowledge on image and video Compression.


Unit –I

1. Introduction to Multimedia : What is Multimedia, Multimedia and Hypermedia, World Wide Web, Overview of Multimedia Software Tools.

2. Graphics and Image Data Representations : Graphics/Image Data Types, Popular File Formats

7Hrs

Unit –II3. Color in Image and Video : Color Science, Color Models in Images, Color Models in

Video.4. Fundamental Concepts in Video: Types of Video Signals, Analog Video, Digital

Video.5. Basics of Digital Audio : Digitization of Sound, MIDI: Musical Instrument Digital

Interface, Quantization and Transmission of Audio.

7Hrs

Unit –III6. Lossless Compression Algorithms : Introduction, Basics of Information Theory, Run-Length Coding, Variable-Length Coding, Dictionary-Based Coding , Arithmetic Coding,7. Lossy Compression Algorithms: Distortion Measures, The Rate-Distortion Theory, Quantization, Transform Coding, Wavelet-Based Coding, Wavelet Packets.

8Hrs

Unit –IV2. Image Compression Standards : The JPEG Standard, The JPEG2000 Standard, The

JPEG-LS Standard, Bilevel Image Compression Standards.

7Hrs

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3. Video Compression Techniques : Introduction to Video Compression, Video Compression Based on Motion Compensation, Search for Motion Vectors, H.261, H.263

Unit-V4. Computer and Multimedia Networks: Basics of Computer and Multimedia Networks,

Multiplexing Technologies, LAN and WAN, Access Networks.

5. Multimedia Network Communications and Applications : Quality of Multimedia Data Transmission, Multimedia over IP, Multimedia over ATM Networks, Transport of MPEG-4, Media-on-Demand (MOD).

7Hrs

REFERENCE BOOKS:1. Z.N. Li and M.S. Drew, Fundamentals of Multimedia. Prentice Hall, 2003.2. K. Jeffay and H. Zhang, Readings in Multimedia Computing and Networking. Morgan Kaufmann,

2002.

Course outcomes:1. Understand the characteristics of different media; and types.2. Analyzes the different typescompression algorithm and JPEG standards.3. Design issues and solutions with computing and information technologies for given problem.4. Implement various media applications and multimedia network communication application.





R. V COLLEGE OF ENGINEERING, Bangalore – 560059.

58

(Autonomous Institution under VTU, Belgaum)

DISTRIBUTED SYSTEMS



Exam Hrs: 03

Prerequisite:

Students must have undergone operating systems.


1. Provide understanding of distributed systems and their characteristics,and the developments in distributed systems.

2. Investigating problems of timing and event ordering, naming of objects and distribution of objects.

3. Gaining knowledge of inter-process communication in a distributed environment.4.Understand how fault-tolerance can be enhanced with concurrency control mechanisms and

replication of services.5.Develop a familiarity with distributed file systems.


Unit –I

1. Characterization Of Distributed System

Introduction,Examples of distributed systems,Resource sharing and the web, ChallengesSYSTEM MODELSIntroduction,Architecturalmodels,Fundamental models

7Hrs

Unit –II2. Interprocess Communication

Introduction,The API for the Internet protocols,External data representation and marshalling, Client-Server communication,Groupcommunication,Casestudy:Interprocess communication in UNIX

Distributed Objects And Remote Invocation

Introduction,Communication between distributed objects,Remote procedure call, Events and notifications,Casestudy:Java RMI

8Hrs

Unit –III3. Operating System Support

7Hrs

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Introduction, the operating system layer,Protection,Process and threads,Communication and invocation ,Operating system architecture

Distributed File Systems

Introduction,File service architecture,Casestudy:Sun Network File System,Case study: The Andrew File System,Enhancement and further developments

Unit –IV4. Coordination And Agreement

Introduction,Distributed mutual exclusion,Elections,Multicastcommunication,Consensus and related problems

Transaction And Concurrency Control

Introduction,Transactions,Nestedtransactions,Locks,Optimistic concurrency control,Timestampordering,Comparison of methods for concurrency control

7Hrs

Unit-V5. Mobile And Ubiquitous Computing

Introduction,Association,Interoperation,Sensing and context-awareness,Security and privacy,Adaptation,Case study of Cooltown

CORBA CASE STUDYIntroduction,CORBA RMI,CORBA services

7Hrs

REFERENCE BOOKS:1. DISTRIBUTED System Concepts and Design-fourth edition by George Coulouris,JeanDollimore,TimKindberg.2. A.S Tanenbaum and M.vanstreen,DistributedSystems:Principles and paradigms,Prentice-hall,2002.Other references:3. M.L.Liu,distributed Computing-Principles and applications,Addison-Wesley,2004.4. J.Kurose and K.Ross,ComputerNetworking:A Top-Down Approach Featuring the Internet,Addision-Wesley,2001.

Course Outcomes:1. Understand the important characteristics of distributed systems and the salient architectural

features of such systems.2. Analyze the features and applications of important standard protocols which are used in

distributed systems.3. Design the different implementation paradigms for distributed systems and explain the working

of a distributed file systems.4. Implement and Perform simple proofs of system properties,given a formalized description of a

system and develop an implementation of a distributed system from a formal or informal description of its function and purpose.


CIE consists of Three Tests each for 40 marks (15 marks for Quiz + 25 marks for descriptive) out of

60

which best two will be considered. In addition 20 marks has to be earned through self-learning component on emerging topics in computer architecture, computing infrastructure and programming.



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62

MANAGEMENT& ORGANIZATIONAL BEHAVIOR

CourseCode : 12HSM61 CIE Marks : 100

L:T:P:S : 3+0+0+0 SEE Marks : 100

Credits : 03 Exam Hours : 3 Hrs

UNIT - I

Introduction to Management:Management Functions, Roles & Skills, Management History – Classical Approach: Scientific Management & Administrative Theory, Quantitative Approach: Operations Research, Behavioral Approach: Hawthorne Studies, Contemporary Approach: Systems Theory, Overview of Social Responsibility & Managerial Ethics, Case Study.

6 Hrs

UNIT - II

Foundations of Planning:Types of Goals &Plans, Approaches to Setting Goals & Plans, Strategic Management Process, Corporate & Competitive Strategies, Decision Making Process, Types of Decisions& Decision Making Conditions, Case Study.

4 Hrs

Organizational Structure & Design: Designing Organizational Structure: Work Specialization, Departmentalization, Chain of Command, Span of Control, Centralization & Decentralization, Mechanistic &Organic Structures, Organizational Design: Traditional & Contemporary, Case Study.

4 Hrs

UNIT - III

Understanding Organizational Behavior:Attitudes, Job Satisfaction& Organizational Commitment, Cognitive Dissonance Theory, Personality: MBTI & Big Five Model, Emotional Intelligence, Perception & Factors Influencing Perception, Attribution Theory, Learning: Classical & Operant Conditioning, Social Learning & Shaping Behavior, Case Study.

6 Hrs

UNIT - IV

Managing Teams: Groups & Stages of Group Development, Group Structure,Processes & Tasks,Work Team & Types of Work Teams, Case Study.

2 Hrs

Motivating Employees: Early Theories of Motivation: Maslow’s Hierarchy of Needs Theory, McGregor’s Theory X& Theory Y, Herzberg’s Two Factor Theory& McClelland’s Three Needs Theory, Contemporary Theories of Motivation: Adam’s Equity Theory & Vroom’s Expectancy Theory, Case Study.

4 Hrs

UNIT - V

Managers as Leaders: Early Leadership Theories: Trait Theories,Behavioral Theories: Ohio State Studies, University of Michigan Studies, Blake & Mouton’s Managerial Grid, Contingency Theories of Leadership: The Fiedler Model, Hersey & Blanchard’s Situational Leadership, Contemporary Views of Leadership: Transactional & Transformational Leadership, Case Study.

4 Hrs

Introduction to Controlling: The Control Process, Controlling for Organizational Performance & Tools for Measuring Organizational Performance, Case Study.

2 Hrs


SOFTWARE ENGINEERING

Sub Code: 12CS62L: T: P: S 3:0:0:1Credits: 04


Exam Hrs: 03

Prerequisite:

Any programming language.


1. Understand software process, process models, activities involved in software engineering process, stages of software engineering process.

2. Understand requirements engineering process and write the functional and non-function requirements using data flow diagrams, Use case diagrams as part of SRS document.

3. Express the Critical / Non Critical Software design using Structured, Object Oriented, Agile and Software Reuse Methodology based models and diagrams.

4. Learn the use of appropriate CASE tool for software development5. Estimate the software development cost and prepare software project plan6. Carry out software testing and formal verification and validation of software.


Unit –I

Overview: Introduction: FAQ's about software engineering, Professional and ethical responsibility. Socio-Technical systems: Emergent system properties. Systems engineering. Organizations, people and computer systems. Legacy systems. Software Evolution: Program evolution dynamics. Software maintenance. Evolution processes. Legacy system evolution. Software Processes: Models, process iteration, Process activities. The Rational Unified Process. Computer Aided Software Engineering.

9Hrs

Unit –IIRequirements: Software Requirements: Functional and Non-functional requirements. User requirements. System requirements. Interface specification. The software requirements document. Requirements Engineering Processes: Feasibility studies. Requirements elicitation and analysis. Requirements validation. Requirements management. Critical Systems: A simple safety-critical system. System dependability. Availability and reliability.

9Hrs

63

Unit –IIIDevelopment: Rapid Software Development: Agile methods. Extreme programming. Rapid application development. System Models: Context models. Behavioral models. Data models. Object models. Structured methods. Software Design: Architectural Design: Architectural design decisions. System organization. Modular decomposition styles. Control styles. Object-Oriented design: Objects and Object Classes. An Object-Oriented design process. Design evolution.

9Hrs

Unit-IVVerification and Validation: Verification and Validation: Planning. Software inspections. Automated static analysis. Verification and formal methods. Software testing: System testing. Component testing. Test case design. Test automation.

9Hrs

Unit-VProject Management: Management activities. Project planning. Project scheduling. Risk management. Managing People: Selecting staff. Motivating people. Managing people. The People Capability Maturity Model. Software Cost Estimation: Productivity. Estimation techniques. Algorithmic cost modeling, Project duration and staffing.

9Hrs

References Books1 Ian Sommerville,“ Software Engineering”, 9th Edition, Pearson Education, 2013, ISBN: 97881317621652 Roger.S.Pressman,“ Software Engineering-A Practitioners Approach”, 7th Edition, Tata McGraw Hill, 2007, ISBN: 97800712678233 Pankaj Jalote,“ An Integrated Approach to Software Engineering”, 3rd Edition, Narosa Publishing House, 2013, ISBN: 97881731970244 Rajib Mall, Fundamentals of Software Engineering, 3rd Edition, Prentice-hall Of India Pvt Ltd., 2012, ISBN: 9788120348981.

Course Outcome1 Comprehend various software life cycle models and steps of software development process.2 Apply concepts of Software Project Planning and software Design techniques.3 Analyze capabilities of various tools to assist in the software development activities.4 Develop correct and robust software design and software project plan from requirement gathering to implementation.



Scheme for Self Learning Evaluation:

The self-learning must be presented in front of evaluation committee; the members of this committee will be Faculties handling the subject along with an observer appointed by Head of the Department. Students are required to present their work either in form of technical presentation or in form of live

64

demonstration. At the end of the presentation the students are required to submit the report as per the format recommended by the Dept. or Dean Academics. The format of evaluation for 20 marks is completely under the prerogative of the committee members or as suggested by HOD.

Scheme of Continuous Internal Evaluation:

CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best of two will be considered. In addition, there will be one seminar on new topics/model presentation etc. for 10 marks..


The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions carrying 16 marks each. All five questions from Part B will have internal choice and one of the two have to be answered compulsorily.

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COMPUTER NETWORKS- II

Sub Code: 12CS63L:T:P :S 3:0:1:1Credits: 05


Exam Hrs: 3Hrs

Prerequisite:The student should have undergone basic course on connectivity like Data Communication/Computer Networks-I


The course on Computer Networks seamlessly provides a continuation from the course on ‘Computer Networks - I’ which concluded with an exposure to the bottom two layers of the network architecture. The objective of the course is to provide exposure to the following topics related to Layer 3 and the upper layers:1. Functions of network layer, Routing algorithms, Congestion Control and Quality of Service.2. Internetworking technology, IPv4 and IPv6 protocols.3. Transport Layer functions and protocols.4. Application Layer protocols viz. DNS, Telnet, E-mail protocols, FTP, HTTP and SNMP.


Unit – INetwork layer - 1Network layer design issues,Store and Forward packet Switching, Services Provided to the Transport Layer,Implementation of Connectionless Service, Implementation of Connection-Oriented Service, Comparison of Virtual Circuit and Datagram Subnets;Routing algorithms: Shortest Path Routing, Flooding, Distance Vector Routing, Link state Routing, Hierarchical Routing, Broadcast Routing, Multicast Routing;Congestion Control Algorithms,General Principles of Congestion Control, Congestion Prevention Policies, Congestion Control in Virtual-Circuit Subnets, Congestion Control in Datagram Subnets, Load Shedding, Jitter Control;Quality Of Service: Requirements, Techniques for Achieving Good Quality of Service; Integrated Services, DifferentiatedServices, RSVP, MPLS

07 Hrs

Unit – IINetwork layer - 2Internetworking: How networks differ, How networks can be connected, Connectionless Internetworking, Tunneling, Internetwork Routing, Fragmentation,The Network Layer in the Internet : The IP Protocol, IP Addresses, Internet Control Protocols, IPv6.

07 Hrs

Unit – III

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Transport LayerThe Transport Service: Services provided to the Upper Layers, Transport Service Primitives;Elements of Transport Protocols: Addressing, Connection Establishment, Connection Release, Flow Control and Buffering;The Internet Transport Protocols(UDP): Introduction to UDP,Remote Procedure Call, The Real-Time Transport Protocol ; The Internet Transport Protocols(TCP): Introduction to TCP, The TCP Service Model, The TCP Protocol, The TCP Segment Header, TCP Connection Establishment, TCP Connection Release, TCP Transmission Policy, TCP Congestion Control, TCP Timer Management, Wireless TCP and UDP.

07 Hrs

Unit – IVApplication Layer - 1Domain Name system (DNS) : Name space, Domain name space, Distribution of Name space, DNS in the Internet, Resolution, DNS messages, Type of records, Registrars.Remote Logging : Telnet. Electronic Mail : Architecture, User agent, Message transfer agent (SMTP),S/MIME, Message access agents (POP and IMAP), Web-based mail; File transfer : File transfer protocol (FTP).

06 Hrs

Unit – VApplication Layer - 2WWW and HTTP : Architecture - browser, server, URL, cookies;Web documents- static, dynamic, active; HTTP - transaction, persistent vs. non-persistent connection, proxy server.Network Management : Network Management System; Simple Network Management Protocol (SNMP) - concept, management components, SMI, MIB, SNMP messages, features of SNMPv3.

LABORATORY : SYLLABUSPART - I : EXPERIMENTS

1. Implement file transfer between a client and server using pipe as IPC.2. Implement file transfer between a client and server using FIFO as IPC.3. Implement file transfer between a client and server using message queue.4. Implement file transfer between a client and server using sockets.5. Implement distance vector routing protocol for a simple topology of routers.6. Write a C program to implement link state routing protocol.7. Implement CRC error detection program. Generator is CCITT-16.8. Write a program to demonstrate the internet checksum algorithm for operation on

8bit, 12 bit and 16bit.9. Write a program to illustrate the hamming code concept.10. Implement leaky bucket congestion control algorithm.11. Implement a simple multicast routing mechanism.

Note : The above experiments shall be conducted using C / C++ on Linux Operating System.

PART – III: CASE STUDY

06 Hrs

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1.Cisco Packet tracer to experiment with network behavior. Create a topology of few nodes and run suitable application protocol and study the behavior of protocol.2. Monosek hardware to capture packets in a network

REFERENCE BOOKS:1. Andrew S Tanenbaum; Computer Networks; Pearson Education; 4th Edition; 2008, ISBN –

978-81-7758-165-22. Behrouz A Forouzan; Data Communications and Networking; Tata McGraw-Hill; 4th Edition;

2006, ISBN – 978-00732503283. Alberto Leon-Garcia and IndraWidjaja; Communication Networks; Tata McGraw-Hill, 2nd

Edition; 2011, ISBN – 97881203205814. Larry L Peterson and Bruce S Davie; Computer Networks - A Systems Approach; Elsevier; 5th

Edition; 2011, ISBN – 978-0123850591

Course Outcomes:1. Interpret the functionalities and services provided by each layer2. Analyse different protocols used in each layer of protocol stack3. Design various protocols and implement algorithms indifferent layers4. Solve the challenges in interfacing various protocols in real world.








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Scheme of Evaluation for Practical’s (50)The students have to execute all the programs listed, in the lab and a record duly signed by the faculty should be maintained. Each program is evaluated independently for 10 marks. Finally, total marks are reduced to 30. A lab test will be conducted at the end of the semester for the remaining 20 marks, the questions for the lab test will programs from the given list will be evaluated for 55% of the marks and 35% will be execution of program of the faculty’s choice. The remaining 10% will be viva voce.


= 150








69


System Software & Compiler Design


CIE Marks: 100+50 SEE marks: 100 +50 Exam Hrs: 3

Prerequisite:The students should have the knowledge of Theory of Computation.


1. The objective is to get exposed to the fundamental concepts of different system software2. To know the architecture of SIC, SIC/XE machines3. To analyze the function of one pass and two pass assemblers, Loaders and linkers, Macro-

Processor & algorithm.4. Students will be able to understand the logic and fundamental concepts using different data

structures and techniques5. Students will be able to apply rules for designing and generating code6. Students will be able to apply different optimization methods on intermediate code to generate

optimized code7. Students will be able to implement and demonstrate in-depth knowledge of various

technologies related to principles, techniques and tools of compiler design.


Unit – I

Machine Architecture: Introduction, System software and machine architecture, Simplified instructional Computer (SIC) Machine Architecture, SIC/XE Machine Architecture, SIC programming and SIC/XE programming examples.Assembler: Basic Assembler Function - A Simple SIC Assembler, Assembler Algorithm and Data Structures, Machine Dependent Assembler Features - Instruction Formats & Addressing Modes, Program Relocation. Machine Independent Assembler Features – Literals, Symbol-Definition Statements, Expression, Program Blocks, Control Sections and Programming Linking, Assembler Design Operations - One-Pass Assembler, Multi-Pass Assembler.

6Hrs

Unit – II

Loaders And Linker: Basic Loader Functions - Design of an Absolute Loader, A Simple Bootstrap Loader, Machine-Dependent Loader Features – Relocation, Program Linking, Algorithm and Data Structures for a Linking Loader, Machine-Independent Loader Features - Automatic Library Search, Loader Options, Loader Design Options - Linkage Editor,

7Hrs

70

Dynamic Linkage.Macro Processor: Basic Macro Processor Functions - Macro Definitions and Expansion, Macro Processor Algorithm and Data Structures, Machine-Independent Macro Processor Features - Concatenation of Macro Parameters, Generation of Unique Labels, Conditional Macro Expansion, Keyword Macro Parameters,

Unit – III

Introduction to Compiling and Lexical AnalysisIntroduction, Language Processors, The structure of Compiler, Lexical Analysis- The Role of Lexical Analyzer, Input Buffering, Syntax Analysis- Introduction, Context-free Grammars, Writing a Grammar, Top-down Parsing

8Hrs

Unit – IV

Syntax Analysis Bottom-up Parsing, and Introduction to LR Parsing: Simple LR, Most powerful LR parsers (Excluding efficient construction and compaction of parsing tables), Using ambiguous grammars.Syntax-Directed TranslationSyntax-Directed Definitions, Evaluation orders for SDD, Application of Syntax DirectedTranslation,

8Hrs

Unit – V

Intermediate Code Generation-Variants of Syntax trees, Three address code, Control flow, Back patching Code Generation- Issues in the design of Code Generator, Basic Blocks and Flow graphs, Principal Sources of Optimization, Optimization of Basic blocks, Peephole Optimization.

Recent trends: Topics to be selected by the faculty handling the Course Code and given as assignments to the students (Assignment for 10 marks).

7Hrs

System Software & Compiler Design Laboratory

UNIT – I

1) a) Write a LEX program to count the number of vowels and consonants in a given string.b) Write a YACC program to evaluate an arithmetic expression involving operators +, -, * and /.

2) a) Write a LEX program to count number of words, lines, and characters.b) Write a YACC program to recognize strings of the form anbn+m cm, n,m>=0.

3) a) Write a LEX program to count number of Positive & negative integers and Positive & negative fractions

b) Write a YACC program to recognize strings of the form an bn , n>=0.

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4) a) Write a LEX program to count the number of comment lines in a given C program. Also eliminate them and copy that program into a separate file.

b) Write a YACC program to test the validity of a simple expression involving operators +, -, * and /

5) a) Write a LEX program to count the number of ‘scanf’ and ‘printf’ statements in a C program. Replace them with ‘readf’ and ‘writef’ statements respectively.

b) Write a YACC program to recognize a nested FOR loop statement for C language.

6) a) Write a LEX program to recognize and count the number of identifiers in a given input file.b) Write a YACC program to recognize nested IF control statements(C language) and display the

number of levels of nesting.

7) a) Write a LEX program to implement Find and Replace command that replaces all the occurrences of one given word by the other.

b) Write a YACC program to identify the number of variables, which starts with a letter or underscore, followed by any number of letters or digits or underscores.

UNIT - II

A group of TWO students can do one of the below mentioned mini Projects in C/C++.1. Implement a 2-pass assembler for 8086

2. Implement a 2-pass assembler for SIC/XE

3. Implement a single pass assembler for 8086

4. Implement a single pass assembler for SIC/XE

5. Implement a single pass macro processor for 8086

6. Implement a single pass macro processor for SIC/XE

7. Implement a 2- pass macro processor for 8086

8. Implement a 2-pass macro processor for SIC/XE

9. Implement a 2- pass loader for SIC/XE

10. Implement a macro processor within language translator for SIC

11. Implement a macro processor within language translator for SIC/XE

12. Implement a simple parser for C++.

13. Implement a simple parser for C.

Note:a) A report of about 25 – 30 pages on the package developed in Part B, duly certified by the

department must be submitted during examination.b) Students must give complete code in their report

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REFERENCE BOOKS:1. Leland. L. Beck; System Software; Addison-Wesley; 3rd Edition, , 1997.

2. Alfred W Aho, Monica S Lam, Ravi Sethi, Jeffrey D Ullman, Compilers- Principles, Techniques and Tools, Person Education, 2008

3. John.R.Levine, Tony Mason and Doug Brown,;Lex and Yacc; O'Reilly, 2nd Edition, 1995.

4. Kenneth C Louden , Compiler Construction Principles & Practice, Thomson Education, 1997.

Course Outcomes:

1. To understand the relationship between different system softwares and machine architecture.

2. To analyze the implementation of assemblers, loaders, macro processors and parsers.

3. To design an assembler, loader, macro processor and parsers.

4. To implement and demonstrate in-depth knowledge of various technologies related to software tools and their construction.








Scheme of Evaluation for Practical’s (50)The students have to execute all the programs listed, in the lab and a record duly signed by the faculty should be maintained. Each program is evaluated independently for 10 marks. Finally, total marks are reduced to 30. A lab test will be conducted at the end of the semester for the remaining 20 marks, the

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questions for the lab test will programs from the given list will be evaluated for 55% of the marks and 35% will be execution of program of the faculty’s choice. The remaining 10% will be viva voce.


= 150









EMERGING TECHNOLOGIES(COMPUTER VISION, CLOUD COMPUTING, HETEROGENEOUS COMPUTING, Smarter SCADA & The Internet of

Things)


CIE Marks: 50 SEE marks: --

Exam Hrs: --

Prerequisite:

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The student should have undergone the following courses :Basic read Computer Science subjects like Data Structures, algorithms, computer organization etc.,


1. To develop a fundamental understanding on recent technology.2. To understand and visualize the components of the methodology.3. To analyze the contemporary advances and innovation in various fields of technology.4. To study and implement converging technologies that is emerging in the domain.5. Add to the research component in view of the future enhancements.6. To add to the technical innovations aligning to the center of excellence of the institution

SYLLABUS DESCRIPTION

Emerging technologies] are contemporary advances and innovation in various fields of technology. Various converging technologies have emerged into different systems evolving towards similar goals. Convergence can refer to previously separate technologies such as voice (and telephony features), data (and productivity applications) and video that now share resources and interact with each other, creating new efficiencies.

Emerging technologies are those technical innovations which represent progressive developments within a field for competitive advantage; converging technologies represent previously distinct fields which are in some way moving towards stronger inter-connection and similar goals.

Senior Faculty of the department would identify some of the most prominent ongoing developments, advances, and innovations in various fields of modern technology like

Computer Vision, Cloud Computing, Heterogeneous Computing, SCADA systems.

Each student would be assigned a mentor to guide through the process of evaluation. The faculty would spend a minimum of 10 to 12 hours in the knowledge transfer required to understand the topic assigned and guide him to carry over the self study.

SYLLABUS CONTENTS

COMPUTER VISION

Prerequisite:A basic knowledge of Computer Science and undergraduate/graduate Mathematics is required. It is a prerequisite that students have known any programming techniques or language. This course builds on fundamental of Computer vision concepts and new technology involved in robotics.

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1. This course will present a broad, introductory survey intended to develop familiarity with the approaches to modeling and solving problems in computer vision.

2. Apply and Analyze computer perception.3. The students learn to choose appropriate features to recognize features.4. Clear understanding of different algorithms and its applications for real time.

Goal and ObjectivesTo introduce the fundamental problems of 3D computer vision.To introduce the main concepts and techniques used to solve those.To enable participants to understand basic methodology that is discussed in the computer vision

Unit –I

FUNDAMENTALS IN COMPUTER VISION, CAMERA CALIBRATION, Introduction, Notation and Problem Statement, Camera Calibration with 3D Objects , Camera Calibration with 2D Objects: Plane Based Technique, Robust Regression.APPLICATIONS IN COMPUTER VISION , IMAGE BASED LIGHTING, Basic Image Based Lighting, Basic Image Based Lighting, Advanced Image Based Lighting , Image Based Relighting.

12Hrs

Unit –IICOMPUTER VISION IN VISUAL EFFECTS, Introduction, Computer Vision Problems Unique to Film, Feature Tracking, Optical Flow , Camera Tracking and Structure from Motion, The Future.FACE DETECTION, ALIGNMENT AND RECOGNITION, Introduction, Face Detection, Face Alignment, PERCEPTUAL INTERFACES, Perceptual Interfaces and HCI, Multimodal Interfaces, Vision Based Interfaces

12Hrs

REFERENCE BOOKS:

1. Gerard Medioni and Sing Bing Kang, “Emerging Topics in Computer Vision" , Springer Verlag : http://szeliski.org/Book/

2. David Forsyth and Jean Ponce, "Computer Vision: A Modern Approach" .

CLOUD COMPUTING


1. Analyze the components of cloud computing showing how business agility in an organization can be created.

2. Compare and contrast the economic benefits delivered by various cloud models based on

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application requirements, economic constraints and business requirements.

3. Analyze a real world problem and develop a cloud based software solution.

4. Manage and deploy a cloud based application.

5. Evaluate the security issues related to the development of cloud applications.

Unit I 12 Hrs

IntroductionCloud Fundamentals: Cloud building blocks, Understanding private & public cloud environments,How to build private cloud using open source tools: Eucalyptus , Nimbus and Nebula Understanding various cloud plugins, setting up our own cloud environment: Auto provisioning, Custom images and Integrating tools like Nagios, Deploying multinode clusters on cloud environment.Cloud Applications and Security issues Overview of Cloud Storage, Building search engine on a cloud computing infrastructure, Usage of cloud computing platform as a possible solution for analyzing large amount of social network data,Analysis of different privacy mechanisms for applications in Cloud Computing, Cloud Securitychallenges.Use Case 1: Building an Application using the LAMP stack: Setting up a LAMP development environment. Building a simple Web app demonstrating an understanding of the presentation layer and connectivity with persistance.

Unit II 12HrsIntroduction to OpenStack and OpenStack SecurityIntroduction to OpenStack: Architecture, Components and different versions. Deploying IaaS platform using OpenStack, Service Assurance over OpenStack cloud platform.Open Stack Security: REST based APIs for accessing cloud services, Role based access control for controlled access to VM’s over cloud, Intrusion detection systems in cloud.Cloud Computing - Big Data, Software Defined Networking(SDN), Forensic AnalysisBig data processing in cloud environments, Cloud computing-based forensic analysis for collaborative network security management systems, SDN: The key to computing in cloud

Reference Books:1. Anthony T. Velte, Toby J. Velte, Robert Elsenpeter: Cloud Computing, A Practical Approach, McGraw Fill, 2010.Research papers on Big data and Cloud computing Infrastructure

6. Gautam Shroff, Enterprise Cloud Computing Technology Architecture Applications [ISBN: 978-0521137355]

7. 2. Toby Velte, Anthony Velte, Robert Elsenpeter, Cloud Computing, A Practical Approach [ISBN: 0071626948]

8. Volker Herminghaus, Albrecht Scriba,, Storage Management in Data Centers [ISBN: 978-3540850229]

9. Tim Mather, SubraKumaraswamy, ShahedLatif, Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance [ISBN: 0596802765]

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HETEROGENEOUS COMPUTING

UNIT-I 12HrsThinking in Parallel: Parallelism Vs. Concurrency, Types and levels of parallelism, Different grains of parallelism, Flynn’s classification of multi-processors, Introduction to parallelization and vectorization: Data dependencies, Bernstein conditions for Detection of Parallelism, Motivation for Heterogeneous Computing.Thinking in Parallel:Definition of thread and process, Parallel programming models, Parallel Programming constructs: Synchronization, Deadlocks, Critical sections, Data sharing etc.GPU Architecture: Introduction to heterogeneous architectures- GPU. Introduction to GPU computing, evolution of GPU pipeline and general purpose computation on GPU, GPU architecture case studies: NVIDIA G80, GT200, Fermi, Kepler etc.

UNIT-II 12Hrs

Compute Unified Device Architecture (CUDA): CUDA Architecture, CUDA programming model, execution model, thread organization: Concept of grid, block and thread, thread index generation, warp;GPU primitives, algorithms and applications: GPU primitives: scan (exclusive or inclusive), scatter, gather, reduce, memory model: Introduction to global, shared, local memories, usage of cache, texture cache, constant memory. CUDA structure, API and library (CUDPP, CUBLAS, FFT etc.) details.CUDA Programming: CUDA example programs (Vector dot product, Matrix multiplication (with the usage of tiling and shared memory) etc.). Graph algorithms, molecular dynamics, n-body simulations, dense linear algebra etc. using GPU.

Reference Books:

1. CUDA: Programming Massively Parallel Processors: A Hands-On Approach. Authors: David Kirk, Wen-mei Hwu © ELSEVIER Inc.

2. CUDA by Example: An Introduction to General-Purpose GPU Programming by Jason Sanders and Edward Kandrot

3. Parallel Programming in C with MPI and OpenMP by Michael J. Quinn, Tata McGraw-Hill Edition

Smarter SCADA & The Internet of Things


1. Be conversant in SCADA, IoT nomenclature2. Understand the typical architecture of a SCADA system and IoT3. Demonstrate knowledge of the basic technology of each of SCADA’s major

building blocks4. Determine when a SCADA system would be useful to your operation5. Design Smarter SCADA system for IoT

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UNIT - I 12Hrs

Fundamentals of SCADA Systems: Introduction, SCADA – A Practical View, SCADA architecture : Hardware Architecture, Software Architecture, System Components , Introduction to PLC: Basics of PLCs, Programming of PLC using IEC 1131-3 Languages (LD, FBD etc.), Next Generation SCADA Systems.

SCADA Systems Operation and Integration: SCADA Protocols (IEC 61850, IEC 62056, IEC 870-5-101 , ICCP), Reports generation, SCADA Remote Terminal Unit (RTU), Features of RTU, Human Machine Interface (HMI), Visualization tools, Data Representation formats, Error detection and control systems, Tools and applications (CDAC-COPS), Alarms and events.

UNIT - II 12Hrs

Introduction to The Internet Of Things: Architectures and design patterns, Concepts behind the Internet of Things,The IoT paradigm, Smart objects, Bits and atoms, Goal orientation, Convergence of technologies

Prototyping Connected Objects: Open-source prototyping platforms, Integrating Internet Services, HTTP APIs for accessing popular Internet services (Facebook, Twitter, and others)

Security for SCADA Systems: Risk Components and Mitigation, Threats and Attack Routes, Security Mechanisms,Intrusion Detection Systems, IEC 62351-5 standard -application layer security for protocols IEC 60870-5-101, IEC 60870-5-104.

Reference Books:

1. “Practical SCADA for Industry by David Bailey and MIPENZ, IDC Technologies, Perth , Australia

2. SCADA: Supervisory Control And Data Acquisition by Stuart A. Boyer

Practical Modern SCADA Protocols: DNP3, 60870.5 and Related Systems IEC 60870-5-101/104 , IEC 61850 , ICCP and MMS standards

3. Modern SCADA Protocols”, Gorden Clarke, Deon, Elsevier, Publications 2005

4. Smart Things: Ubiquitous Computing User Experience Design. Mike Kuniavsky. Morgan Kaufmann Publishers. 2010.

5. Meta Products: Building the Internet of Things. Sara Cordoba, Wimer Hazenberg, Menno Huisman. BIS Publishers. 2011

Course Outcomes:CO1: Select the appropriate SCADA technologies for particular IoT applications.

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CO2: Configure the successful application of IEEE 802.3 standards, determine cabling, fiber optics, connectors,

and hardware that meet the electrical noise, vibration, temperature, and durability requirements of industrial equipment

CO3: Implement Smart Device & Services Opportunities

CO4: Evaluate network protocols that provide interoperability and time-critical control of smart devices and machines.

Scheme of Continuous Internal Evaluation (CIE)

CIE consists of 2 phases

Phase 1 : Test + Assignment = 20 + 5 =25

Phase 2 : Test + Assignment = 20 + 5 + 25

Total = 25+25 = 50 Marks.

Note: There is No SEE for this course.


EMBEDDED SYSTEMS

Sub Code: 12CS6C1L: T: P: S 3:1:0:0Credits: 04


Exam Hrs: 03

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Prerequisite:1. Microprocessor & Microcontroller2. Operating Systems


1. Identify & understand the different Hardware & Software components,variety of buses & protocols which constitute the embedded systems, and Understand the design issues for embedded computer

2. Design & program ARM processor based embedded systems3. Study of RTOS services & designing basic RTOS based embedded system4. Adopting µC/OS-II RTOS for implementing embedded system applications


Unit –I1. Introduction to Embedded SystemsEmbedded Systems , Processor Embedded into a System, Embedded hardware units and devices in a system, Embedded software in a system, Examples of embedded systems, Complex systems design and processors, Design process in embedded system, Design process and design examples, Classification of Embedded Systems

Unit – II2. ARM Processor/Controller– Architecture and Peripheral Programming using embedded CHistory of the ARM Processor, ARM Architecture, Interrupt vector table, The internal architecture of LPC 2148 ( a typical and popular ARM7 MCU) – Features of the LPC 214X Family, Peripherals and Programming : GPIO, Timers, PWM , UART, SSP units, Case study of a project built using MCB 2140 compatible board

Unit – IIIBuses & Protocols

Defining Buses and Protocols, On-board Buses for Embedded Systems- I2C , SPI ; External Buses – USB, Firewire, RS-232, RS-422/485, Ethernet; Automotive Buses-CAN , Wireless communication protocols – WLAN, Zigbee, Bluetooth

Unit – IVReal-Time Operating Systems

OS Services, Process Management, Timer functions, Event functions, Memory management, Device-File-I/O subsystems management, Interrupt Routines in RTOS environment, Real-time Operating systems, Basic design using an RTOS – Principles, Encapsulation using the Semaphores & Queues, Hard real-time considerations

Unit – VReal-Time Operating System Programming using MicroC/OS-IIBasic functions and types of RTOSes, RTOS µC/OS-II, Source files, System-Level functions, Task Service and Time functions and their exemplary uses, Time delay functions, Memory

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related functions, Semaphore related functions, Mail box related functions, Queue-Related functions, Case Study of embedded system design and coding using µC/OS-II

REFERENCE BOOKS:

1. David.E.Simon, “An Embedded Software Primer”, Pearson Education, Reprint 2013, ISBN-978-81-

7758-154-6

2. Raj Kamal, “Embedded Systems, Architecture, Programming and Design”, Tata McGraw-Hill,Second

Edition-Reprint 2011,ISBN-978-0-07-066764-8

3. Lyla B. Das, “Embedded Systems – An integrated approach”, Pearson Education, First Impression

2013, ISBN- 978-81-317-8766-3

4. Michael J.Pont, “Embedded C”, Pearson Education, Reprint 2013, ISBN-978-81-317-1589-5

Course Outcomes:1. Understand the architectures of embedded system tools such as processors, controllers and their

associated devices & components2. Develop embedded applications using ARM processor based systems3. Design and deploy RTOS based embedded systems.4. Analyze real time embedded problems and choose suitable embedded solutions.


CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best of two will be considered. In addition there will be one seminar on new topics / model presentation etc. for 10 marks.


The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions (descriptive, analytical, problems or/and design) carrying 16 marks each. All five from Part B will have internal choice and one of the two have to be answered compulsorily.


GRID COMPUTING



Exam Hrs: 03

Prerequisite:Students should have knowledge of

1. Object oriented programming language2. Networking

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3. Operating systems


1. To provide in depth Knowledge about Grid Computing.2. To cover theoretical and practical aspects of Grid Computing –Architecture and Middlware3. To design and implement Grid computing applications using Grid computing toolkits4. To enhance the student skills in the area of grid portal set up and working in grid environment


Unit –I

Grid Computing Organizations and their Roles

Early Grid Activities, Current Grid Activities, An Overview of Grid Business Areas, Grid Applications, Grid Infrastructure. Organizations Developing Grid Standards and Best Practice Guidelines, Organizations Developing Grid Computing Toolkits and the Framework, Organizations Building and Using Grid-Based Solutions to Solve Computing, Data and Network Requirements, Commercial Organizations Building and Using Grid-Based Solutions

8Hrs

Unit –IIThe Grid Computing AnatomyThe Grid Problem. Anatomy Computing, Business on Demand and InfrastructureVirtualization, Service-Oriented Architecture and Grid, Semantic Grids, Architectures – I: Introduction to Service – Oriented Architecture, Web Services Architecture.

07 Hrs

Unit –IIIArchitectures – IService – Oriented Architecture, Web Services Architecture, XML, Related Technologiesand Their Relevance to Web Services, XML Messages and Enveloping, Service MessageDescription Mechanisms.Architectures – IIRelationship between Web Service and Grid Service, Web Service Interoperability and theRole of the WS-I 100 Organization, OGSA Architecture and Goals, Commercial Data Center(CDC), National Fusion Collaborator (NFS), Online Media and Entertainment.

5Hrs

7Hrs

Unit –IVThe OGSA Platform Components, OGSI – INative Platform Services and Transport Mechanisms, OGSA Hosting Environment, CoreNetworking Services Transport and Security, OGSA Infrastructure, OGSA Basic Services.Grid Services, A High-Level Introduction to OGSI (Open Grid Services Infrastructure).OGSI – IITechnical Details of OGSI Specification, Introduction to Service Data Concepts, GridService: Naming and Change Management Recommendations.

7Hrs

3Hrs

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Unit-VOGSA Basic Services – ICommon Management Model (CMM), Service Domains, Policy Architecture, Security Architecture, Metering and Accounting.OGSA Basic Services –II, ToolkitCommon Distributed Logging, Distributed Data Access and Replication. GLOBUS GT3 Toolkit Architecture.

5Hrs

4Hrs

REFERENCE BOOKS:1.Craig FellensteinandJoshy Joseph ;Grid Computing; IBM Press; 20072. Prabhu ;Grid and Cluster Computing; Prentice Hall of India; 2007.3. Fran Berman, Geoffrey Fox and Anthony J.G. Hey ;Grid Computing- Making The Global Infrastructure a Reality;John Wiley & Sons; 2009.4. Lizhe Wang, Wei Jie and Jinjun Chen ;Grid Computing: Infrastructure, Service, and Applications; 2009.

Course outcomes:1. Understand basic fundamental components of Grid environments2. Design Grid computing applications using toolkits3. Analyze diverse architectures as a basis for building different kinds of Grid systems4. Demonstrate the interoperability of different grid services with the awareness of Grid computing

anatomy.

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Scheme of Semester End Examination:The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions (descriptive, analytical, problems or/and design) carrying 16 marks each. All five from Part B will have internal choice and one of the two have to be answered compulsorily.


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NATURAL LANGUAGE PROCESSING



Exam Hrs: 03

Prerequisite:

The student should have undergone course on Mathematics( Statistics and Probability), knowledge of Theory of Computing.


1. Develop the algorithmic description of the main language levels: morphology, syntax, semantics and pragmatics, as well as the resources of natural language data – corpora.

2. Grasp basics of knowledge representation, inference, and relations to artificial intelligence.3. Explore linguistic phenomena and linguistic features relevant to each NLP task.4. Apply the methods to new NLP problems and to problems outside NLP.5. Implement probabilistic models in code, estimate parameters for such models, and run

meaningful experiments to validate such models.


Unit –I

Introduction to Natural Language Processing

The Study of Language, applications of natural language understanding, evaluating language understanding, different levels of language analysis,representations and understanding, organization of natural language understanding systems

Features and Augmented GrammarsFeature systems and augmented grammars, some basic feature systems for English, morphological analysis and the lexicon, simple grammar using features, parsing with features, augmented transition networks, definite clause grammars, generalized feature systems and unification grammars

Grammars for Natural LanguageAuxiliary verbs and phrases, movement phenomena in Language, handling questions in Context-Free Grammars, relative clauses, The Hold Mechanism in ATNs, Gap Threading.

02Hrs

04 Hrs

04 Hrs

Unit –IIMarkov Models

Hidden Markov Models, The three fundamental questions for HMMs, HMMs: Implementation, Properties and Variants

3Hrs

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Part-of-Speech TaggingThe Information Sources in Tagging, Markov Model Taggers, Hidden Markov Model Taggers, Transformation-Based Learning of Tags, Tagging Accuracy and Uses of Taggers,Probabilistic Context Free GrammarsSome Features of PCFGs, Questions for PCFGs, The Probability of a String, Problems with the Inside-Outside Algorithm.

3Hrs

3Hrs

UNIT IIISemantics and Logical FormSemantics and Logical Form, word senses and ambiguity, basic logical form language, Encoding ambiguity in the logical form, Verbs and states in logical form, Thematic Roles, Speech Acts and embedded sentences, Defining semantic structure: Model Theory.

Linking Syntax and SemanticsSemantic interpretation and compositionality, simple grammar and lexicon with Semantic Interpretation, prepositional phrases and verb phrases, Lexicalized semantic interpretation and semantic roles,handling simple questions,semantic interpretation using feature unification, generating sentences from logical form.

4Hrs

5Hrs

UNIT IVAmbiguity ResolutionSelectional restrictions, semantic filtering using selectional restrictions, semantic networks, statistical word sense disambiguation, statistical semantic preferences, combining approaches to disambiguation.

Other Strategies for Semantic InterpretationGrammatical relations, Semantic grammars,Template matching, Semantically driven parsing techniques.

3Hrs

4Hrs

UNIT VStatistical Alignment and Machine TranslationText Alignment, Word Alignment, Statistical Machine Translation

Clustering Hierarchical Clustering, Non-Hierarchical Clustering

Text CategorizationDecision Trees, Maximum Entropy Modeling, Perceptrons, k Nearest Neighbor Classification

3Hrs

3Hrs

3Hrs

REFERENCE BOOKS:1. James Allen – Natural Language Understanding, Pearson Education,2ndEdition.ISBN: 0-8053-

0334-02. Christopher D. Manning - Foundations of Statistical Natural Language Processing, The MIT Press; 1st

edition.ISBN:0262133601, 9780262133609.

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Course Outcomes:1. Understand the basics of in any language representation in machine learning format.2. Apply machine learning algorithms for Natural Language applications.3. Analyse the linguistic phenomena and linguistic features to each NLP task.4. Demonstrate the use of modern NLP techniques for processing of texts.

Scheme of Continuous Internal Evaluation:CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment / seminar component on emerging topics in android platform and programming. Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Seminar/Assignment : 10 Final CIE = (Best two quiz and Internal test) + Seminar/Assignment = 45 x2 (Best Two Scores) + Seminar/Assignment(10) = 100


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ARTIFICIAL NEURAL NETWORKS



Exam Hrs: 03

Prerequisite:The student should have undergone a course on Data Structures and any programming language.


1. Explain the importance of artificial neural networks and its applications to various real worldproblems

2. Explain the function of Error-correction learning, Memory-based learning, Hebbian learning,Competitive learning and Boltzamann learning

3. differentiate between supervised and unsupervised learning4. describe the assumptions behind, and the derivations of the ANN algorithms dealt with in the

course5. give example of design and implementation for small problems6. implement ANN algorithms to achieve optimization, classification and pattern recoginition7. achieve an understanding of the technical potential and the advantages and limitations of neural

networks.8. apply the methods and produce applications in their working life


Unit –I1.Introduction: What is a Neural Network?, Human Brain, Models of Neuron, Neural Networks viewed as directed graphs, Feedback, Network Architectures, Knowledge representation, Artificial Intelligence and Neural Networks.

8Hrs

Unit – II2. Learning Processes – 1 : Introduction, Error-correction learning, Memory-based learning, Hebbian learning, Competitive learning, Boltzamann learning, Credit Assignment problem, Learning with a Teacher, Learning without a Teacher, Learning tasks, Memory, Adaptation.

9Hr

Unit – IIILearning Processes – 2Statistical nature of the learning process, Statistical learning theory, Approximately correct model of learning. Single Layer Perceptrons: Introduction, Adaptive filtering problem, Unconstrained optimization techniques, Linear least-squares filters, Least-mean square algorithm, Learning curves, Learning rate annealing techniques, Perceptron, Perceptron

9Hrs

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convergence theorem, Relation between the Perceptron and Bayes classifier for a Gaussian environment.

Unit – IVMultilayer Perceptrons – 1Introduction, Some preliminaries, Back-propagation Algorithm, Summary of back-propagation algorithm, XOR problem, Heuristics for making the back-propagation algorithm perform better, Output representation and decision rule, Computer experiment, Feature detection, Back-propagation and differentiation.

8Hrs

Unit – VMultilayer Perceptrons – 2Hessian matrix, Generalization, approximation of functions, Cross validation, Network pruning techniques, virtues and limitations of back- propagation learning, Accelerated convergence of back propagation learning, Supervised learning viewed as an optimization problem, Convolution networks.Support Vector MachinesIntroduction, Optimal Hyperplane, Margin of separation, constrained optimization, Soft margin of separation, SVM for pattern recognition, Mercer’s theorem, SVM models.

10Hrs

REFERENCE BOOKS:1. Simon Haykin; Neural Networks- A Comprehensive Foundation; Pearson Education; 2nd Edition; 1999.

2. Zurada, Jacek M; Introduction to Artificial Neural Systems; West Publishing Company; 1992.3. KishanMehrotra, Chilkuri K. Mohan, Sanjay Ranka; Artificial Neural Networks; Penram International Publishing; 1997.

4. B.Yegnanarayana; Artificial Neural Networks; PHI; 2001.

Course Outcomes:1. Understand fundamentals of Neural Networks, Memory base learning, single layer and

multilayer Perceptron, and Support vector machine.2. Analyze different Network Architectures, Knowledge representations for various learning

tasks.3. Design ANN algorithms to achieve signal processing, optimisation, classification and

process modelling.4. Implement the ANN algorithms and produce applications in working life





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DATA WAREHOUSING AND MINING



Exam Hrs: 3

Prerequisite:The students should have undergone course on Database Management Systems, and Course.


1. To provide comprehensive analysis of the organization, related to business, its requirements and any trends which requires access of historical data.

2. To involve an in-depth study of various concepts needed to design and develop a data warehouse.3. To find the hidden interesting patterns in data.4. It enables the students to understand and implementclassicalalgorithms in data mining.5. To learn how to analyze the historical data, identify the problems, and choose the relevant

algorithms to apply.


UNIT IIntroduction to Data WarehouseData Warehouse and DBMS, Data marts, Metadata, Multidimensional data model, OLTP, OLAP, Data warehouse architecture

Data warehouse designAccessing the data warehouse.

5Hrs

2Hrs

UNIT IIIntroduction to Data MiningWhat is Data Mining?, Motivating Challenges; The origins of data mining; Data Mining Tasks. Types of Data; Data Quality.

DataData Preprocessing; Measures of Similarity and Dissimilarity.

4Hrs

3Hrs

UNIT IIIClassification

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Decision Tree Induction-Bayesian Classification – Rule Based Classification – ClassificationbyBackpropagation–Support Vector Machines –Associative Classification – Lazy Learners – Other Classification Methods.ClusteringClustering techniques – Partitioning methods:k-means- Hierarchical Methods:distance-Basedagglomerativeanddivisibleclustering-Density-BasedMethods: DBSCAN–GridBasedMethods:STING–Model-BasedClusteringMethods:Expectation-Maximization– Clustering High-Dimensional Data:CLIQUE-Constraint-BasedClusterAnalysis:Clustering with Obstacle Objects– OutlierAnalysis:Statistical Distribution-Based Outlier Detection.

5Hrs

5Hrs

UNIT IV

Association Analysis - 1Problem Definition; Frequent Itemset generation; Rule Generation; Compact representation of frequent itemsets; Alternative methods for generating frequent item sets.

Association Analysis - 2FP-Growth algorithm, Evaluation of association patterns; Effect of skewed supportdistribution; Sequential patterns.

5Hrs

4Hrs

UNIT VFurther Topics in Data MiningMultidimensional analysis and descriptive mining of complex data objects; Spatial

datamining; Multimedia data mining

ApplicationsText Mining –Graph mining-web mining-Application and trends in data mining

5Hrs

4Hrs

REFERENCE BOOKS:1. Kimball R, “The Data Warehouse Toolkit”, John Wiley, 2nd Ed., 2002, ISBN: 978-0-471-20024-62. Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining, Pearson

Education, 2007, ISBN 97881317147203. Jiawei Han and MichelineKamber: Data Mining – Concepts and Techniques, 2nd Edition, Morgan

Kaufmann, 2006, ISBN 1-55860-901-64. Insight into Data Mining, Theory & Practice by K. P. Soman, ShyamDiwakar, V. Ajay, PHI –

2006, ISBN: 978-81-203-2897-6

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Course Outcomes:

1. Understand the Data Warehousing and Data Mining principles and techniques.2. Apply machine learning and data mining algorithms for large set of data.3. Analyze large set of data using data warehousing and mining techniques to gain useful business

understanding.4. Develop software tools using warehousing and mining techniques.

Scheme of Continuous Internal Evaluation:CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment / seminar component on emerging topics in android platform and programming.

Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Self-study : 10 Final CIE = (Best two quiz and Internal test) + Seminar/Assignment = 45 x2 (Best Two Scores) + Seminar/Assignment(10) = 100




93

GAME THEORY



Exam Hrs: 3


To comprehend the basics of strategic gaming and mixed strategic equilibrium To enable students to develop skills on extensive gaming strategies design Graphics Pipelines and

program on real-time graphics. To analyze and discuss various gaming models like Prisoner’s and Stackelberg’s.


UNIT IIntroduction, Strategic Games:What is game theory?, The theory of rational choice,Interacting decision makers, Strategic games; Examples: The prisoner’s dilemma, Bach or Stravinsky, Matching pennies; Nash equilibrium; Examples of Nash equilibrium; Bestresponse functions; Dominated actions; Equilibrium in a single population: symmetric games and symmetric equilibria.

8Hrs

UNIT IIMixed Strategy Equilibrium:Introduction; Strategic games in which players may randomize; Mixed strategy Nash equilibrium; Dominated actions;Pureequilibria when randomization is allowed, Illustration: Expert Diagnosis; Equilibrium in a single population, Illustration: Reporting a crime; The formation of players’ beliefs; Extensions; Representing preferences by expected payoffs.

9Hrs

UNIT IIIExtensive Games:Extensive games with perfect information; Strategies and outcomes; Nash equilibrium; Subgame perfect equilibrium;Findingsubgame perfect equilibria of finite horizon games: Backward induction. Illustrations:The ultimatum game, Stackelberg’s model of duopoly, Buying votes.

8Hrs

UNIT IV

Bayesian Games, Extensive Games with Imperfect Information:Motivational examples; General definitions; Two examples concerning information; Illustrations: Cournot’s duopoly game with imperfect information, Providing a public good Auctions;Auctions with an arbitrary distribution of valuations,. Extensive games with imperfect information; Strategies, Strictly Competitive Games, Evolutionary Equilibrium: Strictly competitive games and maximization; Case Study.

10Hrs

UNIT V

94

Iterated Games:Repeated games: The main idea; Preferences; Repeated games; Finitely and infinitelyrepeated Prisoner’s dilemma; Strategies in an infinitely repeated Prisoner’s dilemma; SomeNash equilibria of an infinitely repeated Prisoner’s dilemma, Nash equilibrium payoffs of aninfinitely repeated Prisoner’s dilemma. Coalitional Games and Bargaining: Coalitionalgames, Case Study.

9Hrs

REFERENCE BOOKS:1. Martin Osborne; An Introduction to Game Theory; Oxford University Press, Indian Edition, 2009,

ISBN – 01951289582. Roger B. Myerson; Game Theory: Analysis of Conflict; Harvard University Press, 2008, ISBN –

978-06743411663. Frederick S. Hillier and Gerald J. Lieberman: Introduction to Operations Research: Concepts and

Cases; Tata McGraw Hill ; 9th Edition; 2010, ISBN – 00733762994. Joel Watson; Strategy: An Introduction to Game Theory; W.W. Norton

& Company ; 2nd Edition, 2007, ISBN – 9780393929348

Course Outcomes:

1. Interpret the basics of strategic gaming and mixed strategic equilibrium.2. Analyse gaming strategies design, Graphics Pipelines & program on real-time graphics.3. Design Bayesian, Stackelberg’s , Prisoner’s and many other models of gaming

4. Implement gaming strategy in corporate world

Scheme of Continuous Internal Evaluation:CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment / seminar component on emerging topics in android platform and programming.

Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Self-study : 10 Final CIE = (Best two quiz and Internal test) + Seminar/Assignment = 45 x2 (Best Two Scores) + Seminar/Assignment(10) = 100



95


UNIX SYSTEM PROGRAMMING



Exam Hrs: 03

Prerequisite:The students should know the concepts of Operating Systems(12CS44) and C++ Programming language(12CS46).


1. Know the operating system standards like POSIX standards.2. Comprehend UNIX internal-kernel structures.3. Design & develop UNIX commands & applications using UNIX system API’s.4. Understand the UNIX process control mechanism.5. Analyze the problem & apply the relevant IPC techniques in UNIX system programming.

Adopting signals as IPC for efficient low level and high level application development on Unix systems


Unit-IIntroduction

UNIX and ANSI Standards: The POSIX Standards, UNIX and POSIX APIs: The POSIX APIs, The UNIX and POSIX Development Environment, API Common Characteristics.UNIX Files and General file API’s : File Types, The UNIX and POSIX File System, The UNIX and POSIX File Attributes, Inodes in UNIX System V, Application Program Interface to Files, UNIX Kernel Support for Files, Directory Files, Hard and Symbolic Links. General file API’s : File and Record Locking, Directory File APIs, Device File APIs, FIFO File APIs, Symbolic Link File APIs.

8Hrs

Unit – IIUNIXprocesses

UNIX Kernel Support for Processes. The Environment of a UNIX Process: Introduction, main function, Process Termination, Command-Line arguments, Environment List, Memory Layout of a C Program, Shared Libraries, setjmp and longjmp Functions, getrlimit, setrlimit functions.

5Hrs

96

Unit – IIIProcess ControlIntroduction, Process Identifiers, fork, vfork, exit, wait, waitpid, Race Conditions, exec Functions, Changing User IDs and Group IDs, system Function, Process Accounting, User Identification, Process Times.

8Hrs

Unit – IVProcess Relationships and SignalsProcess Relationships : Introduction, Terminal Logins, Network Logins, Process Groups, Sessions, Controlling Terminal, tcgetpgrp and tcsetpgrp Functions, Job Control.Signals: Introduction, The UNIX Kernel Support for Signals, signal, Signal Mask, sigaction, The SIGCHLD Signal and the waitpid Function, The sigsetjmp and siglongjmp Functions, kill, alarm, Interval Timers.

9Hrs

Unit – V

Daemon Processes and Inter-process CommunicationDaemon Processes: Introduction, Daemon Characteristics, Coding Rules.Interprocess communication: Overview of IPC Methods, Pipes, popen and pclose functions, FIFOs, Message Queues.

6Hrs

REFERENCE BOOKS:1. Terrence Chan; UNIX System Programming Using C++; Prentice Hall India, 1999,ISBN-

81-203-1468-9.2. W. Richard Stevens; Advanced Programming in the UNIX Environment; Pearson

Education; 2nd Edition; 2005, ISBN 81-317-0005-4.3. Marc J. Rochkind: Advanced UNIX Programming; Pearson Education; 2nd Edition; 2005,

ISBN 8129710951, 9788129710956.4. Maurice J Bach: The Design of the UNIX Operating System, Pearson Education, 1987,

ISBN 0132017997, 9780132017992.

Course Outcomes:5. Understand the fundamentals of UNIX operating system such as the POSIX standards, UNIX processes, UNIX filesystemand Signals.6. Analyze UNIX kernel level support for UNIX processes, UNIX filesystem and Signals.7. Demonstrate advanced UNIX features such as signals, Job Control, daemon processes and inter process communication.8. Develop UNIX commands, utilities and applications utilizing UNIX Systemcalls.

Scheme for Continuous Internal Evaluation (CIE):CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment component.

Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Max Assignment Marks : 10

97



98

LINUX INTERNAL

Sub Code: 12CS6D1L: T: P: S 3:0:0:0Credits: 03


Exam Hrs: 03

Prerequisite:Students require knowledge of some basic Unix Architectureand the basic operating system concepts.


Elements of Kernel level features of the Linux operating system, Linux communication stacks and the file systems are increasingly finding practical applications in areas such as Linux kernel development, Linux kernel programming and Linux programming Interface. This course will develop students’ understanding of fundamental concepts and key architectures of advanced Linux operating system concepts and their applications. This course aims1. To reinforce the kernel level features of Linux operating system.2. To develop and implement the system calls.3. To gain knowledge about the memory management of the OS.4. To present an adequate programming and debugging environment in linux OS.


UNIT I1. Introduction to Linux:Introduction to Linux, Overview of Operating systems and kernels. Linux Vs Classic Unix Kernels, Linux Kernel Versions.

2. Getting Started with the Kernel:Obtaining the Kernel source, installing the Kernel source, Using Patches, The Kernel SourceTree, Building the Kernel, Minimizing the build noise, Spawning Multiple Build Jobs,Installing the Kernel, Synchronization and Concurrency.3. DebuggingWhat one needs to start a Kernel, Bugs in the kernel, printk(), The Robustness of printk(),Loglevels, The Log Buffer, syslogd and klogd, A note about printk() and Kernel Hacking,Oops, ksymoops, kallsyms, Kernel debugging options, Atomicity debugging, Asserting Bugsand dumping Information, Magic SysRq Key, The saga of a Kernel Debugger, gdb, kgdb.

03 Hrs

03 Hrs

04 Hrs

UNIT II4. Process ManagementProcess Descriptor and the Task Structure, Allocating the process Descriptor, Storing the process Descriptor, Process State, Manipulating the current process state, process context,

3Hrs

99

the Process family tree, process creation, copy on write, fork(), vfork(), The Linux Implementation of Threads, Kernel Threads, Process termination, Removal of the Process Descriptor, The Dilemma of the Parentless Task, Process Wrap Up.5. Memory ManagementPages, Zone, Getting pages, Getting zeroed Pages, Freeing pages, kmalloc(), gfp_mask flags, kfree,vmalloc(),slab layer, design of the slab layer, slab allocator Interface, Statically Allocating on the stack, Playing Fair on the stack, High Memory mappings, Temporary Mappings.

3Hrs

UNIT III6. Process SchedulingPolicy, I/O- Bound Versus processor-bound Processes, Process Priority, Time slice, Process preemption, the scheduling Policy in Action, the Linux Scheduling algorithm, Run queues, The Priority arrays, Recalculating time slices, schedule(), Calculating priority and Time slice, Sleeping and Waking up, The Load Balancer, Preemption and Context switching, User Preemption, Kernel Preemption, Real-Time, scheduler- Related system calls, Scheduling Policy and Priority- Related System calls.

7. The Virtual File SystemCommon File system Interface, File system Abstraction Layer, Unix Filesystems, VFS objects and Their data structures, other VFS objects, The superblock object, superblock operations, The Inode object, Inode operations, The Dentry object, Dentry state, The Dentry cache, Dentry operations, The File object, Flie operations, Data structures associated with file systems, Data structures Associated with a Process, File systems in Linux.

4Hrs

3Hrs

UNIT IV

8. Kernel Synchronization Introduction and MethodsCritical Regions and Race conditions. Locking and Deadlocks, Contention and Scalability, Locking and your code. Atomic integer operations, Atomic bitwise operations, Spin Locks, Other Spin Lock Methods, spin Locks and Bottom Halves, Reader writer Spin locks, Semaphores, Creating and Initializing Semaphores, Using semaphores, Reader-writer semaphores, Spin Locks Versus Semaphores, Completion variables, BKL; The Big Kernel Lock, seq Locks.

9. Modules Hello, world! Building Modules, At Home in the Source Tree, Living Externally, Installing modules, Generating Module Dependencies, Loading modules, Managing configuration options, Module Parameters, Exported symbols, Wrapping up Modules.

3Hrs

4Hrs

UNIT V

10. Interrupt and Interrupt HandlersInterrupts, Interrupt Handlers, Top Halves Versus Bottom Halves, Registering an Interrupt

6Hrs

100

Handler, Freeing an Interrupt handler, writing an interrupt handler, Interrupt context, Implementation of Interrupt handling, /proc/ interrupt, Interrupt control, Disabling and Enabling Interrupts, Disabling a Specific interrupt, Line status of the Interrupt system.

REFERENCE BOOKS:

1. Robert Love; Linux Kernel Development; Pearson Education ; 2nd Edition; 2010. ISBN-8131758182.

2. M. Beck et.al ; Linux Kernel Programming; Pearson Education; 3 rd Edition; 2002. ISBN-110-201-71975-4

3. Michael kerrish; Linux Programming Interface; 1st Edition, 2010. ISBN-10159327220.

4. Daniel P. Bovet MarcoCesati; Understanding the Linux Kernel , 3rd Edition ,OReilly.

Course Outcomes:1) Understand the fundamental concepts of Unix, high-level structure and development

environments.2) Illustrate the use of data structures and system calls within the Linux kernel.3) Integrate the operating system concepts with relevant design issues associated with Linux

kernel.4) Develop applications using Linux Processes and Interrupt handling techniques.

Scheme of Continuous Internal Evaluation:CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment / seminar component on emerging topics in android platform and programming. Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Self-study : 10 Final CIE = (Best two quiz and Internal test) + Seminar/Assignment = 45 x2 (Best Two Scores) + Seminar/Assignment(10) = 100



101


Mobile Application Development



Exam Hrs: 03

Prerequisite:

102

Student should have gone a course on operating systems and networks.


1. To understand the working of the Mobile Architecture.2. To write a simple and complex program for android OS and Windows programming.3. To present different Google Map API.4. To perform behavioral analysis of system under test and understand the Network.5. To introduce the Concept of sharing the data across network.


UNIT I

An Overview of Android: Introducing Android , The Open Handset Alliance, Android Platform differences, Android Platform.Configuring Your Development environment, Exploring Android software development Kit, Writing first android application.

Understand the Anatomy of an android application :The life Cycle of android application ,manifest file , Defining android application using the manifest file ,Creating First android application ,Type of Android application.

9Hrs

UNIT-II

Managing Application Resources :Resources ,Working with resources. Refercing the system resources, Managing multiple Application Configuration, Configurations.

Exploring User Interface Screen Elements : Introducing Android view ,Widgets and Layouts, Displaying Text to user, Getting the text from the user, Using Buttons, checkbox and Radio groups, Getting Dates and times user, Indicating the information to the user.

9Hrs

UNIT III

Working in the Background :Introducing Services,Creating and Controlling Services,Using background thread,introducingloaders,Manual thread creation and thread synchronization.

Using Android Data and Storage API: Working with application Prefernces, Working with files and Directories, Storing the Structured data using SQLlite Databases, Implementing query(),insert(),update() and getType (), Updating the Manifest file, Working with Live Folder,maps.

9Hrs

UNIT IV

Windows Mobile Programming : Introducing the Microsoft .NET Framework,,Introducing the .NET Compact Framework ,.NET Compact Framework Type System.

Smartphone Application Development :Developing Your First Smartphone Application ,UI Design with Forms and Controls ,Smartphone UI Design,Keyboard Input and Input Mode.

9Hrs

UNIT V

Data Access with SQL Server Mobile : Microsoft SQL Server 2005 Mobile Edition

8Hrs

103

,Writing SQL Server Mobile Applications,Setting Up the SQL Server Mobile Server Environment .

Networking: Web Access,TCP Servers and Clients,NetworkSockets,Creating E-mail Applications with Managed APIs ,Accessing PIM Data,Using SMS

REFERENCE BOOKS:2. Reto Meier , Professional Android 4 Application Development ,Wrox Publication,2012,ISBN :

978-1-1181-0227-5.3. Baijian Yang, Pei Zheng, Lionel M. Ni ,Professional Microsoft Smartphone

Programming ,Wrox Publication,2007,ISBN : 978-0-471-76293-5.4. Shane Conder , Lauren Darcey, Android Wireless Application Development,3rd Edition,

Addison Wesley,2009,ISBN-13: 978-0-321-61966-2.5. ZigurdMednieks, Laird Dornin, G. Blake Meike, Masumi Nakamura , Programming

Android,2nd Edition ,O'Reilly Publication ,2012,ISBN:978-1-4493-1664-8.6. SatyaKomatineni , Dave MacLean , SayedHashimi , Pro Android 3, Apress

publication ,2011,ISBN13: 978-1-4302-3222-3

Course Outcomes:1. Understand the fundamentals of mobile architecture.2. Design the map application framework using the available Map API’s for given OS platform.3. Develop the application based on the communication API’s.4. Implement the software issue access the network through mobile.

Scheme of Continuous Internal Evaluation:CIE consists of Three Tests each for 45 marks (15 marks for Quiz + 30 marks for descriptive) out of which best two will be considered. In addition 10 marks has to be earned through assignment / seminar component on emerging topics in android platform and programming. Each quiz Max marks : 15 Each Internal Test Marks : 50 (Reduced to 30) Seminar/Assignment : 10Final CIE = (Best two quiz and Internal test) + Seminar/Assignment = 45 x2 (Best Two Scores) + Seminar/Assignment(10) = 100


104

http://www.apress.com/author/author/view/id/1749



http://shop.oreilly.com/product/0636920023005.do?code=HDMBDT&intcmp=ba-code-ebooks-int-search-hd-mobile-dev-ct#tab_04

http://www.informit.com/authors/bio.aspx?a=d96d26ef-d85c-4eac-8f85-77c6db59cde9

http://www.informit.com/authors/bio.aspx?a=d184e3e6-5e86-4f76-b44c-0b83ce9ac51f

http://it-ebooks.info/author/1158/


NETWORK PROGRAMMING



Exam Hrs: 03

105

Prerequisite:

The student should have undergone course on computer networks(CN-I)


1. To introduce students to programming fundamentals and TCP/IP socket programming.2. The students will be able to develop simple client/server applications using TCP and UDP

sockets.3. The basic knowledge of DNS and daemon process are provided to utilize and develop

applications.4. The knowledge of IPV4 & IPV6 interoperability with respect to network applications.5. Broadcasting, Unix domain protocols are introduced to the students.6. Thread concepts with echo server/client example with introduction to synchronization of

threads.


Unit – IThe Transport Layerand introduction to socketsIntroduction to TCP, UDP and SCTP, The big picture, Difference between UDP, TCP,SCTP, TCP connection establishment and termination, TIME_WAIT state, TCP portnumbers and concurrent servers, Buffer sizes and limitation.Socket address structure, valueresult arguments, byte ordering functions, byte manipulation functions, inet_aton, inet_addrand inet_ntoa functions, inet_pton and inet_ntop functions,

6Hrs

Unit – IITCP client/serversocket function, connect function, bind, listen, accept, fork, exec functions, concurrent servers, close function, getsockname and getpeername functions, TCP Echo server – main – str_echo ,TCP Echo client - main – str_echo, Normal startup, normal termination.

8Hrs

Unit – IIIUDP client/server and Name serversocket options introduction, getsockopt and setsockopt functions.recvfrom and sendto functions, UDP Echo server & UDP Echo client, lost datagrams.DNS, Gethostbyname function, gethostbyaddr function, getservbyname and getservbyport functions, getaddrinfo function, gai_strerror function, freeaddrinfo function, getaddrinfo function: example, host_serv function.

6Hrs

Unit – IV

106

8HrsIPV4 and IPV6 Interoperability, Daemon process and UNIX Domain SocketsIntroduction to IPv4 and IPv6, IPv4 client- IPv6 server, IPv6 client - IPv4 server, IPv6 address – Testing Macros, Source code portability.Introduction to daemon processes, syslogdDeamon, syslog function,daemon_init function, inetd Daemon, daemon_inetd function.Domain protocols, Unix domain socket address structure, socketpair function, Socket functions,Unix domain stream client/server, Unix domain Datagram client/server.Unit – VBroadcasting and multicastingIntroduction to Broadcasting, Broadcast address, Unicast Vs Broadcast, dg_client function using broadcasting. Multicast addresses, Multicasting versus broadcasting on a LAN, Multicasting on a WAN, Source-specific multicast.

6Hrs

REFERENCE BOOKS:1. W.Richard Stevens, Bill Fenner, Andrew M. Rudoff; UNIX Network Programming – The sockets networking API Vol.I , PHI, 3rd Edition; 2004. ISBN – 978-81-203-2823-52. Stephen A. Rago; Unix System V Network Programming; AWL; 1993. ISBN – 978-80-201-5631-843. Douglas comer, E. stevens David L; Internetworking with TCP/IP : Client – Server Programming and application ; 2nd edition, Vol III, PHI, 2001, ISBN – 978-81-203-2553-1

Course Outcomes:1. Understand the OSI reference model and a variety of network concepts and protocols.2. Analyze Protocol interoperability and application.3. Design and demonstrate client/server programs on Unix platforms to create robust real-world

sockets-based applications.4. Implement specific network programming modules using specific APIs and structures.




The question paper consists of Part A and Part B. Part A will be for 20 marks covering the complete syllabus and is compulsory. Part B will be for 80 marks and shall consist of five questions (descriptive, analytical, problems or/and design) carrying 16 marks each. All five from Part B will have internal choice and one of the two have to be answered compulsorily

107


FUZZY LOGIC



Exam Hrs: 03

Prerequisite:Discrete Mathematical Structures


1. This course is designed to provide an engineering student an intense foundational introduction to the fundamental concepts in Fuzzy Logic.

2. Many technical disciplines involve environments where all necessary information is not available or is ambiguous. This course will propose fuzzy sets and fuzzy logic as appropriate

108

mathematical models of this incompleteness and ambiguity.3. The course will focus on example problems in various engineering, mathematics, and science

disciplines with an emphasis on environmental issues and processes impacting the environment.

4. After completing the course the student will use fundamental principles and models in fuzzy logic and fuzzy logic based techniques and their applications in information systems.


Unit IIntroductionThe case for Imprecision, The Utility and Limitations of Fuzzy Systems, Fuzzy sets and membership, Chance verses fuzziness, Sets as points in hyper cubes. Fuzzy Sets - Fuzzy set operations, Properties of Fuzzy Sets, Non-interactive fuzzy sets, Alternative fuzzy set operations, Intuitionistic fuzzy sets, Intuitionistic fuzzy set operations, Properties of Intuitionistic fuzzy sets.

7Hrs

Unit II

Fuzzy /intuitionistic fuzzy RelationsFuzzy Relations, Cardinality of Fuzzy Relations, Operations on Fuzzy Relations, Propertiesof Fuzzy Relations, Fuzzy Cartesian product and Composition, Fuzzy Tolerance andequivalence relations. Value assignments - Cosine amplitude, Max-min method, othersimilarity methods, Intuitionistic fuzzy relations, operations on Intuitionistic fuzzy relations,properties of Intuitionistic fuzzy relations.

7Hrs

Unit III

Properties of membership Functions, Fuzzification, and DefuzzificationFeatures of the Membership Function, Various Forms-Interval valued fuzzy sets, Type-2 fuzzy sets, fuzzification, defuzzification to crisp sets, Lambda-cuts for fuzzy relations, Defuzzification to Scalars.

Logic and Fuzzy SystemsClassical Logic – Tautologies, Contradictions, Equivalence, Exclusive or and Exclusive Nor,Logical Proofs, Deductive Inferences. Fuzzy Logic, approximate reasoning, other forms ofthe Implication Operation, Fuzzy Systems: Natural Languages, Fuzzy (Rule -Based) systems.

4Hrs

3Hrs

Unit IV

Development of Membership FunctionsMembership value Assignments, Intuition, Inference, Rank Ordering, Neural Networks, Genetic Algorithms.Fuzzy Arithmatic and Extention Principle

5Hrs

109

Extention principle, Crisp Function, Mapping and Relations, Function of fuzzy sets- Extention principle, fuzzy transform, practical considerations, fuzzy arithmetic, interval analysis in arithmetic, Approximate methods of extension.

3Hrs

Unit V

Fuzzy Classification and Pattern RecognitionClassification by equivalence relations- Crisp relations and Fuzzy relations, Cluster analysis, Cluster validity, c-means clustering, Hard c-means, Fuzzy c-means algorithm, Classification metric, Feature analysis, Partition of the feature space, Single-sample identification, Multifeature pattern recognition.

7Hrs

REFERENCE BOOKS:1. Timothy J. Ross; Fuzzy logic with engineering applications, John Wiley- 2nd Edition, 2007,

ISBN:13 978-81-265-1337-6.2. George J. Klir, Bo Yuan; Fuzzy sets and Fuzzy logic-Theory and applications, Prentice Hall; 1 st

Edition, 2008, ISBN: 81-203-0695-3.3. John Yen, Reza Langari , Fuzzy Logic Intelligence, Control and Information , 1st edition, 9th

Impression, 2012, Pearson, ISBN:978-81-317-0534-6.4. Research papers on Intuitionistic sets and Intuitionistic relations.

Course outcomes:

1. The students will have in depth knowledge on basics of fuzzy sets / Intuitionistic fuzzy sets concepts.

2. They willanalyze tools of fuzzy sets/ Intuitionistic fuzzy sets to different areas, where uncertainty and imprecision are involved.

3. The students will design the appropriate skill of this modern tool necessary for getting better results in their field of interest.

4. The students will apply the fuzzy logic skills in situations involving highly complex systems whose behaviors are not well understood and in situations, where an approximate, but fast, solution is warranted.





110


Software Architecture and Testing



Exam Hrs: 03

Prerequisite:The needs to complete a course on software engineering.


1. The objective of the course is to provide a sound technical exposure to the concepts, principles, methods and best practices in Software Architecture and Design.

2. The vision of the course is to produce Software Architects with sound knowledge and superior competence in building Robust, Scalable and Reliable software intensive systems in an effective way.

3. Work from stakeholder requirements to create system interfaces that support partitioning.

4. Use different viewpoints to organize partitioning to support deployment, maintenance and functional extension.

5. Apply architectural patterns to quickly generate architectural alternatives and choose between them

6. Identify any failure modes that may emerge when the system is integrated on-site

111

through site integration testing

7. Identify any noncompliances with customer's requirements prior to placing the system in common use through acceptance testing

8. Identify any faults induced by maintenance activities through comprehensive regression testing of all changes


UNIT I1. IntroductionThe Architecture Business Cycle: Where do architectures come from? Software processes and the architecture business cycle; What makes a “good” architecture? ; What software architecture is and what it is not? ; Other points of view; Architectural patterns, reference models and reference architectures; Importance of software architecture; Architectural structures and views

5Hrs

UNIT II2. Architectural Styles and Case StudiesArchitectural styles; Pipes and filters; Data abstraction and object-oriented organization; Event-based, implicit invocation; Layered systems; Repositories; Interpreters; Process control; Other familiar architectures; Heterogeneous architectures.Case Studies: Keyword in Context; Instrumentation software; Mobile robotics; Cruise control; Three vignettes in mixed style.

7Hrs

UNIT III

3. QualityFunctionality and architecture; Architecture and quality attributes; System quality attributes; Quality attribute scenarios in practice; Other system quality attributes; Business qualities; Architecture qualities.Achieving Quality: Introducing tactics; Availability tactics; Modifiability tactics; Performance tactics; Security tactics; Testability tactics; Usability tactics; Relationship of tactics to architectural patterns; Architectural patterns and styles.

7Hrs

UNIT IV

4. Testing Concepts, Issues and Planning:

Purpose, Activities, Processes and Context Questions about Testing, Functional vs Structural Testing: Coverage –based vs Usage –based Testing: When to Stop Testing? – Test Planning and Preparation: Goals, Strategies and techniques, Testing models and test cases. Test suite preparation and management for Preparation of Test procedure, Test Execution, Result Checking and Measurement, Analysis and Follow-up, Activates, People, and Management, Test Automation

6Hrs

UNIT V 8Hrs

112

5. Control Flow, Data Dependency, and Integration Testing:

Basic Control Flow Testing, Model construction path selection & sensitization, Loop Testing, CFT Usage, and Other Issues, Different types of loops and corresponding CFGs, Loop testing: Difficulties and a heuristic strategy, CFT Usage and other Issues, Data Dependency and Data flow Testing: Basic concepts: Operations on data and data dependencies, DFT and DDG elements and characteristics DFT: Coverage and Applications, Achieving slice and other coverage

Testing Techniques: Adaptation, Specialization and Integration:

Testing Sub-Phases and Applicable Testing Techniques, Specialized Test Tasks and Techniques, Test Integration case Study: Hierarchical Web Testing

REFERENCE BOOKS:1. Len Bass, Paul Clements, Rick Kazman; Software Architecture in Practice; Pearson Education; 2nd

Edition; 2003. (Chapter 1: 1.1-1.3, Chapter 2 : 2.1-2.5).2. Frank Buschmann, RegineMeunier, Hans Rohnert, Peter Sommerlad, Michael Stal; Pattern -

Oriented Software Architecture, A System of Patterns; John Wiley; Volume 1; 2006. (Chapter 2 : 2.1-2.5, Chapter 3 : 3.1-3.4).

3. Mary Shaw, David Garlan; Software Architecture - Perspectives on an Emerging Discipline; Prentice Hall; 2007. (Chapter 2 , Chapter 3).

4. Jeff Tian, “Software Quality Engineering: Testing, Quality Assurance, and Quantifiable

Improvement”, - John Wiley and Sons Inc., and IEEE Computer Society Press, February

2005

5. Edwar.Dkit. “Software testing in the Real World”, Pearson Education 2003.

113

Course Outcomes:

1. Understand the fundamentals of Architecture Business Cycle: Architectural patterns, reference models and reference architectures.

2. Analyze the roll of abstractions, modelling, architecture and design patterns in the development of a software product.

3. Design optimal architectural choices and employ the most relevant methods, best practices and technologies for architecture.

4. Implement a software product regardless of its complexity and scale and make the comparison of various testing strategies.





114


Genetic Algorithms



Exam Hrs: 03

Prerequisite:Students must be aware of data structures and algorithms.


1.To understand search algorithms based on the mechanics of the natural selection process2. To create an initial population of feasible solutions,3. To apply basic operations of GA .4. To deduce feasible solutions to encode the solution chromosomes.5. To formulate the fitness criteria for various range of real world problems.


UNIT I

1. Introduction to Genetic Algorithms:A Gentle Introduction to Genetic Algorithms; Genetic Algorithms revisited-Mathematical Foundations: The Fundamental Theorem, Schema Processing at work, Two-armed and k-armed Bandit problem, The Building block hypothesis.

8Hrs

UNIT II

2. Computer Implementation of a Genetic Algorithm:Reproduction, crossover and Mutation, Fitness Scaling, Codings, Discretization. Some applications of genetic algorithms.

7Hrs

UNIT III

3. AdvancedOperators and Techniques in Genetic Search:Dominance, Diploidy and Abeyance. Inversion and other reordering operators, Niche and speciation, Knowledge based Techniques, Genetic Algorithms and parallel processors.

6Hrs

UNIT IV 6Hrs

115

4. Introduction to Genetics-based Machine Learning:Classifier system, Rule and Message system, Apportionment of credit, A Classifier system in pascal.

UNIT V

5. Applications of Genetics-based Machine Learning:The Rise of GBML, Development of CS-1, Smith's Poker player, other Early GBML efforts.

6Hrs

REFERENCE BOOKS:1. David E.Goldberg, "Genetic Algorithms in search, Optimization & Machine Learning" Pearson

Education, ISBN-13:978-0201157673.2. William B. Langdon, Riccardo Poli,"Foundations of Genetic Programming" P. J. Fleming, A.M.S.

Zalzala, "Genetic Algorithms in Engineering Systems”, ISBN: 0852969023.3. David A. Coley, "An Introduction to Genetic Algorithms for Scientists and Engineers".

ISBN:9810236026.

Course Outcomes:1. Understand probabilistic rules to evolve a population from one generation to the next2. Analyze parallel processing with the help of Genetic Algorithm.3. Design parallel processing codes for Genetic Applications.4. Implement optimized solutions and create platform for Machine learning techniques in the

process of development of Genetic Algorithms.





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cse 5th-6th finalaized version

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