Babu Banarasi Das University, Lucknow - Best University in ......Babu Banarasi Das University, Lucknow School of Engineering (School Code: 04) Department of CE/CSE/EE/ECE/ME/IT (University

Babu Banarasi Das University, Lucknow School of Engineering

(School Code: 04)

Department of CE/CSE/EE/ECE/ME/IT(University Branch Code: 31/32/33/34/35/36)

Bachelor of Technology

Evaluation Scheme

Semester I

Contact Evaluation Scheme

Course Course Hours

Category Code Code Title

Course Credits

L T p CIA ESE Total

C BAS3101 Matrices and Calculus 3 1 0 40 60 100 4

C BAS3102 Physics-I 2 1 0 40 60 100 3

Students need to select either

GROUP 'A' or GROUP 'B'

GP3101 General Proficiency 0 0 0 100 0 100 1

Total 5 2 0 180 120 300 8

GROUP 'A'


Course Course Hours


Course Credits

L T p CIA ESE Total

F BME3101 Engineering

3 1 0 40 60 100 4 Mechanics

Foundation of F BCS3101 Information 3 1 0 40 60 100 4

Technology

F BEC3101 Basic Electronics

3 1 0 40 60 100 4 Engineering

C BAS3104 Environmental Studies 2 0 0 40 60 100 2


0 0 2 40 60 100 1 Mechanics Lab


Technolo!!v Lab

F BME3152 Workshop Practice 0 1 2 40 60 100 2

C BAS3152 Physics-I Lab 0 0 2 40 60 100 1

Total 11 4 8 320 480 800 19

GROUP'B'


Course Course Hours


Course Credits

L T p CIA ESE Total

F BEE3101 Basic Electrical

3 1 0 40 60 100 4 Engineering

F BME3102 Basic Mechanical

3 1 0 40 60 100 4 Engineering

C BAS3103 Chemistry 3 1 0 40 60 100 4

C BHS3101 Technical

3 1 0 40 60 100 4 Communication

F BEE3151 Basic Electrical

0 0 2 40 60 100 1 Engineering Lab

F BME3153 Engineering Graphics

0 1 2 40 60 100 2 Lab

C BAS3153 Chemistry Lab 0 0 2 40 60 100 1

Total 12 5 6 280 420 700 20

Semester II


Course Course Hours


Course Credits

L T p CIA ESE Total

C BAS3201 Differential Equations

3 1 0 40 60 100 4 and Fourier Analysis

C BAS3202 Physics-II 2 1 0 40 60 100 3

Students need to select either

GROUP 'A' or GROUP 'B'

GP3201 General Proficiency 0 0 0 100 0 100 1

Total 5 2 0 180 120 300 8

Note: Students who have selected GROUP 'A' in the first semester will select GROUP 'B' in the second semester and Vice-Versa.

GROUP 'A'


Course Course Hours


Course Credits

L T p CIA ESE Total


3 1 0 40 60 100 4 Mechanics Foundation of

F BCS3201 Information 3 1 0 40 60 100 4

TechnoloJ;?;y

F BEC3201 Basic Electronics

3 1 0 40 60 100 4 Engineering

C BAS3204 Environmental

2 0 0 40 60 100 2 Studies


0 0 2 40 60 100 1 Mechanics Lab


Technology Lab

F BME3252 Workshop Practice 0 1 2 40 60 100 2

C BAS3252 Physics-I Lab 0 0 2 40 60 100 1

Total 11 4 8 320 480 800 19

GROUP'B'

Contact

Course Course Hours


L T p

F BEE3201 3 1 0

F BME3202 3 1 0

C BAS3203 3 1 0

C BHS3201 3 1 0

F BEE3251 0 0 2

F BME3253 0 1 2

C BAS3253

Basic Electrical En2ineerin2 Basic Mechanical Engineering

Chemistry

Technical

Communication

Basic Electrical

En2ineerin2 Lab

Engineering

Graphics Lab

Chemistrv Lab 0 0 2

Total 12 5 6

Legends:

L

T

p

CIA

ESE

Number of Lecture Hours per week

Number of Tutorial Hours per week

Number of Practical Hours per week

Continuous Internal Assessment

End Semester Examination

Category of Courses:

F Foundation Course

C Core Course

GE

OE

Generic Elective

Open Elective

Evaluation Scheme

Course Credits

CIA ESE Total

40 60 100 4

40 60 100 4

40 60 100 4

40 60 100 4

40 60 100 1

40 60 100 2

40 60 100 1

280 420 700 20

BAS 3101 Matrices and Calculus Credits: 4

Course Objective:

Tfie general objective of the course is to introduce

I. the concepts of matrix algebra, methods of solving system of linear equations and determineeigen values and eigen vectors of a matrix:

2. the concepts of the eigen values and eigen vectors of Hermitian. Unitary and Normal matricesdiffer from those of general matrices;

3. · the concepts of derivatives of functions (one and several variables) and their applications;4. the concepts of multiple integration, Beta. Gamma functions and their applications;5. the concepts of vector cal cul us to expose students to mathematical appl ica�ions.

Learning Outcomes:

Upon successful completion of the course, students will be able to

I. demonstrate ability to manipulate matrices, to find rank and to solve the system of linearequations;

2. find eigen values and eigenvectors and use them in diagonalization problems and otherapplications;

3. find nth derivative by using Leibnitz theorem:4. apply partial derivatives to study extrema & expansion of functions of two variables;5. evaluate double integrals by changing variables . changing order and triple integration to find

the area and volume of given region;6. calculate line integrals along piecewise smooth paths, interpret such quantities as work done

by a force;

7. ·· solve double and triple integrations and apply it to calculate line, surface and volume integrals;8. apply Green's theorem to" evaluate line integi·als ijlong simple closed contours on the plane,

Stoke's theorem to give physical interpretation of the curl of a vector field and Divergencetheorem to give physical interpretation of the divergence of a vector field.

Course Contents:

Module Course Topics Total Hours I Credits

Matrices Type of Matrices, Elementary row and column

transformation, Rank of matrix, Linear dependence, I Consistency of linear system of equations and their 30 I

solution, Characteristi'c eq1;1ation, Caley-Hamiltion theorem, Eigen values and eigen vectors, Application of matrices to engineering problems. Differential Calculus Leibnitz theorem. Partial differentiation, Euler's

II theorem, Expansion of function of several variables. I Jacobian, Extrema of functions of several variables. I 30 1

Lagranges method of multipliers (Simple ! I aoolicatioilsJ.

(

SYLLABUS

BAS-3102 ENGINEERING PHYSICS I

Course Objective:

The main objectives of the course are l. To provide knowledge and develop an understanding of principles and processes of wave optics,

optical communication and fundamentals of special theory of relativity.2. To develop the basic skills to apply knowledge by the topics covered in the course to engineering

problems. !

Learning Outcome:

At the end of the course students shall be able1. To apply knowledge of wave optics.2. To design and conduct experiments.3. To identify and solve the problems in different field of engineering & technology.

Course Contents:

Module

I

II

Course Topics

Wave Optics:

Interference: Interference of light, Biprism experiment, ..

Displacement of fringes, Interference in thin film, Wedge shaped film, Newton's rings. Diffraction: Single slit and N-slit, Diffraction grating,· Grating spectra, Dispersive power of grating, Rayleigh criterion and resolving power-of grating. Polarisation: Double refraction, Nicolprism, Production and detection of plane, circularly and elliptically polarised light, Optical activity and Fresnel's theory of optical activity, Specific rotation and Polarimeter.

Laser and Fibre Optics:

Laser: Spontaneous and stimulated emission of radiation, Einstein coefficient,. P.opulation invers�on & pumping,

Total Hours

30

Construction and working oJ ruby & He-Ne Laser, 30 Applications of Laser, Holography. Fundamental idea about optical fibre, Propagation mechanism & communication in optical fibre, Types of optical fibre, Acceptance angle and acceptance cone, Numerical aperture

Credits

1

(

I and . V -number, Attenuation ,Signal loss 1 Dispersion in optical fibre.

in optical fibre,

Special theory of Relativity:

Inertial & non inertial frames, Concept of ether, Michelson J and Morley Experiment, Einstein's basic postulate of

I III special theory of relativity, Lorentz transformation

equations, length contraction, Time dilation, variation, relativistic velocity addition theorem, energy Equivalence relation.

References:

1. Concepts of Modern Physics, Aurther 'Beiser , Mc-Graw Hill

Mass Mass-

2. Introduction of Special theory of relativity, Robert Resnick, Wiely3. Optics, Ajay Gha,tak, TataMc-Graw Hill4. Optical fibre and Laser, Anuradha De, New Age5. Fundamental of Physics, Resnick, Halliday & Walker, Wiely6. Optics, Jenkin and White, Tata Mc-Graw Hill

30

�� (Dr. Karunesh Tiwari Convener

(Prof. Rajeev Manohar) External Expert

��1/ (Dr. N£n Jain) (Dr.Nee

4C,

- Nominee Member

1

II

III

IV

Beam:

>s lurncnt, I lnlroJut.:tion, Shear force anJ D�1h.l i ng Differential equations for shear force & bending moment, Shear force and Bending Moment Diagrams for Statically Determinate Beams. Trusses:

Introduction, Simple Truss and Solution of Simple Truss, Method of Sections; Method of Joints; How to determine if a member is in tension or compression; Simple Trusses; Zero force members

Centroid and Moment of Inertia:

Introduction, Centroid of plane, curve, area, volume and composite bodies, Moment of inertia of plane area,Parallel Axes Theorem & Perpendicular axes theorem, Moment of inertia of composite bodies. Kinematics and Kinetics:

Linear motion, Instantaneous center, D' Alembert principle, Rotation of rigid bodies, Impulse and momentum principle, Work and energy principle. Simple Stress and Strain:

Definition of stress,· stress tensor, normal and shear stresses m axially loaded members, Stress-strain

relationship, Stress-strain diagram for uniaxial loading of ductile and brittle materials, Hooke's law, Poisson's ratio, shear stress, shear strain, modulus of rigidity, Relationship between ela�tic constants. On.e Dimensional Loading ofmembers of varying cross-sections, Temperature Stresses,Strain energy.

Reference Books:

1. Engineering Mechanics by Irving H. Shames. Prentice-Hall.

I

30 1

30 I

30 1

2. Engineering Mechanics: Principles of Statics and Dynamics by R. C. Hibbler.Pearson Press.

3. Engineering Mechanics: by Shanes and Rao. Pearson Education.

4. Engineering Mechanics by S.S. Bhavikatti, K.G. Rajashekarappa, New AgePublications.

5. A textbook of Engineering Mechanics by Dr. R.K. Bansal, Laxmi Publications.

6. Mechanics of Solids by Abdul Mubeen, Pearson Education Asia.

7. Mechanics of Materials by E.P. Popov, Prentice Hall of India Private Limited.

)

)

Babu Banarasi Das University, Lucknow Depnrrrnent ol'CSE

SYLLABUS

BCS3101/ J3CS3201 Foundation ofl 11t'or111atio1: Tcchno'..: . .:..' Course Objective:

l. Introduce the fundamentals of computing devices aml rci11lt11\.:c c,lmputcrvocabulary, particularly with respect to personal use of hardware ,1ml software. the internet, network and mobile computing.

2. Study the basic concepts and functions of hardware ,111d sul't" a1-c.3. Study the basic concepts and functions of uperating S: stem.4. Study the basic concepts and functions ol' computer nctw,>1-k.5. Study the basic concepts and functions of I nfor111ation Tecllnuiug:-.6. Study the ba�ic concepts of C programming language.7. Provide foundational or "Computer literacy" curriculum that prepan�s students

for life-long learning of computer concept and skills. Learning Outcome: At the end of the course, the student should be able to:

I. Understanding organization of computer system and net,Norking.2. An ability to understand the basics of computer hardware and soil wan:.3. Awareness of basic information security issues.4. To understand the use of In format ion Technology in busi 1h.:'i�.

5. To analyse and understand variouSi type� 01· so�t,1-are :-_vsll'111.

6. An ability to understand operating system :ind its fu11..:ti,)11:,. 7. Ability to apply knowledge and practice on oi'li1.:e tvuls tu <k\clup I. Iapplication.

8. To analyse various co111puter network�.Course Contents:

Module Course Topics ..... _-_-_-_-

_--- --f ;:,�:.':'. ; C,c,J;t,:

�=;dct;:,;� ;��!:�;:v: ::orniatioO tec�no Io gy, Types 1 · - --: - - - i

I

of computer: Mainframe computer, network I I 1

computer, personal computer, laptop. personal digital i assistant (PDA); Personal computer: Central , processing unit (CPU), hard disk, common input or i output devices, types of me111ory viz. RAM. ROM. 1

peripheral device, computer perform:rnce. !Input Devices: Mouse. keyboard. trackball, sc:11111er. ' touchpad, light pen, joystick. digital camera .ind .HJ I luur, microphone. Output Devices: Monitors. sc1-..:1.·ns. ' printers, plotters, speakers. Input/output Dcvit·cs: : Modems, Touch Screens. Storage Devices: Diskdte. : Zip disk, data cartridges, CD-ROM. internal, external 1

1 hard disk: Disk formatting Software: Types Of Software: Opl!1·ating S) ,t1.·111s · software and application solhvare. Stll.tware ve1·::sitlllS. Operating System: Functions and rypes. Grapll1cal Usei· Interface (GUI), SDLC and its pluses. -----

21

)

BEC3101/BEC3201 BASIC ELECTRONICS ENGINEERING

Course Objective:

This course provides I. Comprehensive idea about basic electronics devices like Diodes. BJT, JFET.

MOSFET, Operational Amplifier.2. Fundamental principles of Electronic instruments like CRO and digital multi

meter.3. Fundamental principle of communication.

Learning Outcome:

At the end of the course students will be able to gain knowledge about the l . Fundamentals of electronic devices like Diodes, BJT. JFET, MOSFET,

Operational Amplifier and Electronic instruments like CRO and digital multimeter.

2. Number system, Boolean algebra, logic gates, Kaurnaugh map3. Basics of communication systems.

Course Contents: ---�-------------·-·-·---·--·-·--�--·-·-·- .. -----·-·-·- --·--,

Module Course Topics Hours 1-----------------------·---··----·--

Total Credits I··-·--·

I

DIODES: Energy band theory. Semiconductor n:iaterial. Mass action law, PN junction: Forward and Reverse Bias characteristics, Diode as Rectifier: Half wave and Full wave Rectifiers, Breakdowp Mechanism: Zener &

30 Hours

Avalanche breakdown, Zener Diode and its application, LED, LCD, and Solar Cell.

------�--'----------------------1-----.. --+------1

II

III

TRANSISTORS Construction of Bipolar Junction Transistor: PNP and NPN, Working of Transistor, BJT configurations: CE, CB and CC, Input & Output characteristics of CB & CE configuration, Biasing: Fixed bias, Emitter bias, Potential divider bias, Comparison of biasing circuits. JO

JFET: Basic construction and characteristics. Concept of Hours

pinch ofl� maximum drain saturation current. Input and transfer characteristics, Biasing: Self bias and tixed bias. MOSFET- Depletion and Enhancement type MOSFET-construction, operation and characteristics.

iDIGITAL ELECTRONICS -· AND ---·-

��!:�::t;!,1��=P�:,�!�Boolean Algebra Basic -�-�-�

)

IV

I Theorems and De Morgan Theorems. Standard logic gates, Universal Logic Gates, lmplemenLaLion ur

Boolean function using Basic gates and Universal gates. Reduction of Boolean function usmg K-Map upto4 variables. Block Diagram of Communication System, Electromagnetic spectrum, Need for Modulation, Basic Definitions AM,FM,PM OPERATIONAL AMPLIFIER AND

APPLICATIONS: Introduction to OP-AMP, Characteristics of ideal OP-AMP. Basics of ideal and practical OP-AMP. Configurations: Open loop and closed loop, Applications of OP-AMP, Inverting 30 amplifier, Non-inverting amplifier, Voltage follower, Hours summing amplifier, Difference Amplifier, Integrator and Differentiator. Principle of oscillation and Barkhausen criterion .

....._ __ ___,_ ______________________ ....._ ___ .___ __

Text Books:

1. Robert L. Boylestad and Louis Nashelsky Electronic Devices and Circuit Theory,Pearson India.

2. Kennedy. Electronic Communication System. TM!-!3. Kalsi H.S. Electronic Instrumentation. TM H4. M. Morris Mano, Digital Logic and Computer Design, PHI

·· Reference Books:

1. Jacob Millman, Christos C. Halkias, Integrated Electronics: Analog and DigitalCircuits and Systems (McGraw-Hill electrical and electronic engineering series).

2. William D. Cooper, Albert D.Hefrick, Modern Electronic instrumentation andmeasurement technique 5th edition Prentice Hall Of India, New Delhi 1997.

3. Ramakant Gaikwad .Op -Amp's & linear Integrated Circuits, 4th edition. PrenticeHall of India, New Delhi 2002.

4. Albert Paul Malvina. Donald P Leach . Digital Principle & Application 4thedition, Tata McGraw -Hill Edition. New Delhi -1991.

BAS 3104/BAS3204: ENVIRONMENTAL STUDIES

Course Ob_jectives: The main objectives of the course are:

l. To create awareness and improve knowledge about environment.2. To conserve natural resources through sustainable use.3. To prevent, control of pollution and protect environment.4. To developed skill and participation in environment protection activities.

Learning outcome: After the completion of the course, students are expected to better understanding of:

• Environments and related issues.• Develop skill to solve many inter related problems of socio-economic nature and

ecology.• Able to conserve natural resources and sustainable use.• Able to protect environment.

Course Contents:

Modules Course Topics Total Cre Lecture/

1.

Hours dit

Environment 30

Environment: Definition, Principles and Scope of Environmental

Studies, Structure and composition of atmosphere, hydrosphere,

lithosphere and biosphere, Ecosystems, structure and function of

ecosystem, Types of ecosystem, energy flow in an ecosystem,

Food chain and food web, ecological pyramids, Prey-Predator

interaction. Population dynamics of Prey and Predator.

Material cycle: Definition and importance, Nitrogen and carbon

cycle

Environmental Impact Assessment (EIA): Definition and Concept, Elements of EIA, Prediction of impacts and its

methodology, Sustainable Development.

Natural resource and its conservation

Natural resources: Renewable & non-renewable natural

resources, drinking water quality, water borne and water induced

diseases, arsenic and fluoriae problem m drinking water,

deforestation. impact of overexploitation mineral resources.

Energy resources: Conventional and non-conventional energy

sources. solar energy, hydro-power energy, Hydrogen-energy,

wind energy, geothermal energy, biomass energy, nuclear energy, fossil fuels.

. '_,'\XI -�---

1

week

L T P

2 0 0

,- )

)

1.

2.

3.

4.

5.

6.

7.

8.

ENGINEERING M�CHANICS LAB (BME3151/BME3251)

To conduct the tensile test and determine the ultimate tensile strength, percentage

elongation for a steel specimen.

To determine the compression test and determine the ultimate compressive strength

for a Specimen.

To conduct the Impact-tests (lzod/Charpy) on Impact-testing machine to find the

toughness.

To determine the hardness of the given specimen using Vickers/Brinell/Rockwell

hardness testing machine.

Friction experiment(s) on inclined plane and/or on screw�ack.

Worm & worm-wheel experiment for load lifting.

Belt-Pulley experiment.

Bending of simply-supported and cantilever beams for theoretical & experimental

deflection.

9. Torsion of rod/wire experiment.

10. Experiment on Trusses.

11. Statics experiment on equilibrium.

12. Experiment on Moment of Inertia.

Note:

1. At least ten experiments are to be performed in the semester.

2. At least eight experiments should be performed from the above list.

Remaining two experiments may either be performed from the above list or designed &

set by the concern faculty as per the scope of the syllabus.

BCS3151/BCS 3251 Foundation of Information Technology Lab

1) Run basic DOS commands.

2) Learn the use of Word Processor.

3) Learn the use of Excel.

4) Prepare presentation on any topic of your choice.

5) Write a C program to find sum of two numbers.

6) Write a C program to learn the function of FOR loop.

7) Write a C program to learn the function of WHILE/ DO WHILE loop.

8) Write a C program for pattern printing

9) Write a C program to print Fibonacci series.

10) Write a C program to find factorial and reverse of a number.

WORKSHOP PRACTICE (BME3152/BME3252)

1. Carpentry Shop: Study of tools & operations and carpentry joints, Simple exercise

using jack plane, to prepare half-lap corner joint, mortise & tennon joints. Simpleexercise on wood working lathe.

2. Fitting Bench Working Shop: Study of tools & operations, Simple exercises

involving fitting work, make perfect male-female joint, Use of drills/taps idea.

3. Black Smithy Shop: Study of tools & operations, Simple exercises base on black

smithy operations such as upsetting, drawing down, punching, bending, fullering &

swaging.

4. Welding Shop: Study of tools & operations of Gas welding & Arc welding, Simple

butt and Lap welded joints, Oxy-acetylene flame cutting.

5. Sheet-metal Shop: Study of equipment & operations, Making Funnel complete with

'soldering', Fabrication of tool-box, tray, electric panel box etc.

6. Machine Shop: Study of machine tools and operations, Plane turning, Step turning.

Taper turning, Threading, grinding of turning equipment.

7. Foundry Shop: Study of tools & operations, Pattern making, Mould making with the

use of a core, Method of material pouring and Casting.

Note:



Remaining two experi111ents may either be pe:formed from the above list or designed &

set by the concern faculty as per the scope of the syllabus

.....,..

BAS-3151*BAS-3252 PHYSICS PRACTICALS**

Course Objective:

The main objectives of the course are 1. To learn some basic principle� of physics that help stude�ts to understand how theworld around them works.2. To realize fundamental concepts of physics and how it can be applied to other field i.e.engmeenng.3. To apply scientific knowledge systematically.

Learning Outcome:

At the end·of the end of the course students be able to 1. Tack.le experimental problems in physics.2. Use mathematics to describe the physical world.3 Plan, execute, analyse and report experiments.4. Compare results critically with prediction from theory .

The student shall perform ten experiments in the laboratory by choosing at least four

experiments from each group

GROUP-A

Practical Topics Total

Hours

I. To determine the wavelength of monochromatic light by Newton's rings.

2. To determine the wavelength of monochromatic light with the help of Fresnel's bi prism .

3. To determine the focal length of two lenses by nodal slide and locate the position of cardinal points.

4. To determine the specific rotation of cane sugar solution using Bi-quartz 30

polarimeter.

5. · To . determine the wavelength of various spectral lines usmg planetransmission grating

6. To study the polarization ofl_ight by simple reflection using laser ..

7. Measurement of wavelength of a laser (He-Ne) light using single slit diffraction.

Credits

*BAS3152

**PHYSICS-I LABAs per Evaluation Scheme, SOE

GROUP-B

I Practical Topics

I

8

10

11 12

13

14 15

16

17

18

19

20.

To determine the specific resistance of the material of given wire usingCarey Foster's bridge To determine the variation .of magnetic field along the axis of a currentcarrying coil and then to estimate-the radius of the coil.

To verify Stefan's Law by electrical method .

To calibrate the given ammeter and voltmeter

To study the Hall Effect and determine Hall coefficient, carrier densityand mobility of a given semiconductor material using Hall-effect set up.

To determine energy band gap of a given semiconductor material.

To study the characteristics of zener diode

To determine electrochemical equivalent of copper using Tangent orHelmholtz galvanometer To draw hysteresis curve of a given sample of ferromagnetic material andfrom this to determine magnetic susceptibility· and permeability of thegiven specimen. �· .

To determine the ballistic constant of a ballistic galvanometer

To determine the �alu� of a planck's constant. by a photocell. .

To determine the coefficient of viscosity of a liquid.

Measurement of fiber attenuation and aperture of fiber

(Dr. Karunesh Tiwari Convener

.

t\}t>

(Dr.Zin) Nominee

(Prof. Rajeev Manohar) External Expert

r (Dr.� Yael.av)

Member

Total

Hours Credits

30 1

BABU BANARASI DAS UNIVERSITY, LUCKNOW

School of Engineering

Department of Electrical Engineering


SEMESTER - I / II

BEE3101/BEE3201 BASIC ELECTRICAL ENGINEERING

Course Objective:

1. This course provides comprehensive idea about circuit analysis.

2. The subject gives the knowledge about combinational circuits.

3. Subject gives the knowledge about the analysis and design of new electricalcircuits.

4. Other logical working principles of machines and common Measuringinstruments.

Learning Outcome:

At the end of the course students will be able.

1. To understand basic theorem of electrical engineering.

2. To understand basic electrical engineering.

3. To understand the basic concepts of magnetic, AC & DC circuits.

4. To explain the working principle, construction, applications of DC & ACmachines & measuring instruments.

5. To gain knowledge about the fundamentals of electric components, devices.

Course Contents:

Module Course Topics Total

Credits Hours

Electric Circuit: Introduction to linear and nonlinear circuits, circuit elements, various sources and source transformation, Star delta transformation, solution of D.C. circuits using Kirchhoff's laws- Mesh Analysis

30 I and Nodal Analysis, Signal wave forms, Passive

elements specifications. Hours

Basic theorems: Thevenin, Norton, Maximum Power, Superposition, Millman's Theorem, Tellegen's Theorem applied to DC networks.

II A. C. Circuits: A.C. voltage and currents, average and 30

r.m.s. values, Form factor and peak factor, Phasor Hours

/

III

IV

representation of sinusoidal quantities, phasor in polar, rectangular and exponential forms.

Analysis of single phase series, parallel and seriesparallel circuits, Active & reactive and apparent power, p.f., Volt-amperes, frequency response and Q-factor.Analysis of balanced three phase a.c. circuits,Introductory concept, voltage, current and power inthree phase balanced circuits. Star-delta connections.Measurement of three phase power by WattmeterMethod.

Measuring Instruments & Electromagnetic and Transformer: Types of instruments, construction, working principles & applications, PMMC, MI, Single phase dynamometer, Ammeter, Voltmeter, Wattmeter, Induction type Energy meter, Use of shunt and multiplier.

Magnetic circuit concept, B-H curves characteristics of magnetic materials, Practical magnetic circuits. 30 Magnetic circuits with D.C. and A.C. excitation, Hours Hysteresis and eddy current losses, Magnetic force.

Self and mutual inductances, Faraday's laws, Lenz's Law, Statically and dynamically induced emfs, Energy stored in magnetic fields.

Principle of Transformer operation, emf equation, Equivalent circuit of transformer, Losses and efficiency, Introduction of Auto Transformer and its applications.

Electrical Macl\ines: Basic concepts of rotating electric machines, DC machines (motor aud g�nerator), working principle, types, EMF and torque equations characteristics and application of DC motor. Three phase induction motors, types, principle of operation, 30 applications. Hours Single phase induction motors, principle of operation, starting methods, applications. Synchronous machines (motor and generator), principle of operation and applications.

Text &Reference books:

1

· 1. 'Fundamental of Electric Circuits' by Cl_iarles K Alexander and Matthew N.O.

Sadiku, Tata McGraw Hill Publication.

2. 'Electrical Engineering Fundamentals' by Vincent Del Toro, PHI Publication.

3. 'Electric Technology, by H.Cotton, CBS Publishers and Distributors.

4. 'Basic Electrical Technology' by A.E.Fitzgerald, McGraw Hill Publication.

5. 'Basic Electrical Technology' by Kothari and l.J. Nagrath, Tata McGraw Hill.

6. 'Basic Electrical Technology' by S.N.Singh, PHI Publication.

"

III

IC engines:

Classification of IC engines, engine terminology, Compression

Ignition engines and Spark Ignition engines, Construction and

working of two stroke and four stroke engines, Difference

between SI and CI engines, difference between 2-stroke and 4-

stroke engine, Efficiency of Otto cycle and diesel cycle. Boilers

& Condensers

Boilers:

Steam generators-classifications, Working of fire-tube and

water-tube boilers, Boiler mountings & accessories.

Condensers:

Classification of condenser, Air leakage, condenser

performance parameters.

Reference Books:

30 1

1. P.K. Nag, Basic and Applied Thermodynamics, Tata McGraw-Hill Publishing

Company Ltd.

2. Yunus A. Cengel and M.A. Boles, Thermodynamics: An Engineering Approach.

Tata McGraw- Hill Publishing Company Ltd.

3. C.P. Arora,Thermodynamics, Tata McGraw- Hill Publishing Company Ltd.

SYLLABUS

(BAS 3103/BAS 3203) CHEMISTRY

Course Objective: The main objectives of course are:

I. To provide basic building blocks of engineering chemistry.

2. To provide spatial learning style using images, pictures, colors and models.

3. l-:1 pro\ idc the basic mathematical probkms of polymer chemistry.

Learning Outcome: At the end of the course, the student l-ViU be able to:

I. understand the rok of chemistry in field or engineering.2. understand the structure of atoms and apply the periodic laws to predict chemical and

physical properties of the elements.) . de, cl<.lp analytical capabi I ities and techniques of interpretation. 4. arply tht knowledge in solving problems in their respective field of study.5. �'111ploy critical thinking and efficient problem-solving skills in the lour basic areas of

chc111istry (analytical, inorganic. organic. and physical).

Course Contents: ·----- ·--------------------------.....-·---,.-----,

Module Course contents Total Hours

Credits --1-------------------------+----+-------i

I

Introduction to General Chemistry Atomic structure, Chemical bonding: Significance of Quantum numbers, Shapes of s, p, d, and f atomic orbitals. Rules for

·filling electrons in various orbitals. Electronic configuration ofatoms, Molecular Orbital Theory arid it.s Applications mHomonuclear and Heteronuclear diatomic molecules.Reactions kinetics: Rate equation, Order and molecularity ofreaction. Theories of reaction rates, Integrated rate equations. 30 Electrochemistry: Nernst equation and its importance.Nanomaterials: Types of nanomaterial, Creation and use ofFullerenes. Carbon nanotube and its application. States ofmatter: Space lattice, Types of unit cell (cube), Density of unitcell, Defects in crystal.Liquid crystal and its application.

1

SYLLABUS

Course Title: Technical Communication Course Code: BHS3101/3201

Course Objectives:

• To make the students aware of the fundamentals of communication and its types and variouslevels�

• To train them techniques and methods of vocabulary building and paragraphs writing andmake com111unicat1on effective and impressive;

• To groom them expert in oral as well as written communication with the knowledge ofvarious forms and formats;

• To make them understand the role of Nonverbal (Kinesics) in Communication• To enhance their capacity for comprehension, creative and critical thinking;

Learning Outcome: The successful completion of the course students will be able to:• Understand the meaning of communication and its various applications;• Form and apply suitable vocabulary, phrases and sentences in communicating variety of

situations;• Able to use variety of forms/formats and techniques required in different levels of

communication;• Maintain congruity between verbal and nonverbal communication;• Able to comprehend and clarify the intricacies of art of communication.

Course Contents:

Module Course Topics Total

. Hours Credits

. - ·--· ·-·····--------------------+-----,-----

Fundamentals of Communication: Communication: Definition, Nature, Origin, Scope, Featuresand Process o1 communication;Types ofC'ornmunication: Verbal and Non-Verbal, Formal andlnfonnal. Oral & Written Communication and technical andgeneral Communication;Level5 of C'ommunication: Extra-personal, Intra-personal,Interpersonal. organisational, Grapevine, Group and MassCommunication; Language as a Tool of Communication;The Flo"' of Communication: Vertical (Upward and 30Downward). Lateral or Horizontal;Technical Communication: Definition, Distinction betweenTechnical & General Communication, Importance ofTechnical Communication for Technocrats & Professionals;Barriers to Communication: definition; types: Physical,Semantic. Psychological barriers or Extra-personal, Intrapersonal. Interpersonal, and Organizational barriers, How toOvercome these Barriers;

J...------- �-- ·-- -·-----------------+-----+----1

II Creativities in�ommunication 30 IWo1��7'

a"tion: Affixation. Compounding, Blending,

�J��\ C\ �j, __ js,'"° ,\,} � - ��10i

BEE3151/BEE3251 BASIC ELECTRICAL ENGINEERING LAB

(Any 10 experiments)

1. Verification of KCL & KVL.

2. Verification of Thevenin' s theorem.

3. Verification of Norton's theorem.

4. Verification of Superposition theorem.

5. Measurement of active and reactive power m 1-phase and Power Factor

Improvement.

6. Measurement of active power in 3 -phase circuit using TWO wattmeter methods.

7. Study of transfonner through assembling and polarity check.

8. Detennination of equivalent circuit parameters of a single phase transfonner by

O.C. and S.C. tests and estimation of voltage regulation and efficiency at various

loading conditions and verification by load test.

9. Study of de shunt motor speed control using (1) Armature control (2) Field

Control.

10. Determination of efficiency of DC shunts motor by load test.

11. Study of Electrical Equipment used in daily life.

12. Study of DC Machine.

13. Full wave rectifier circuit using diodes.

14. Transistor input-output characteristics.

ENGINEERING GRAPHICS LAB (BME3153/BME3253)

1. Scales: Representative factor, plain scales, diagonal scales, scales of chords.

2. Projection: Types of projection, orthographic projection, first and third angle projection.

3. Projection of points: The principle of orthographic projections of a point on HP and VP,Conventional representation, Projection of a point in all the quadrants.

4. Projection of Lines: Line inclined to one plane, inclined with both the plane, True Lengthand True Inclination, Traces of straight lines.

5. Projection of planes and solids: Projection of Planes like circle and polygons in differentpositions; Projection of polyhedrons like prisms, pyramids and solids of revolutions likecylinder, cones in different positions.

6. Section of Solids: Section of right solids by normal and inclined planes; Intersection ofcylinders.

7. Isometric Projections: Isometric scale, Isometric axes, Isometric Projection fromorthographic drawing.

8. Perspective Projection: Nomenclature of Perspective Projection, Method of drawingperspective views, Visual Ray Method, using Top and Front, Top and Side views.

9. Computer Aided Drafting (CAD)-I: Introduction, benefit, software’s basic commands ofdrafting entities like line, circle, polygon, polyhedron, cylinders.

10. Computer Aided Drafting (CAD)-II: Transformations and editing commands like move,rotate, mirror, array; solution of projection problems on CAD.

Note:



Remaining two experiments may either be performed from the above list or designed & set by the concern faculty as per the scope of the syllabus

Reference Books:

1. Computer Aided Engineering Drawing by S.Trymbaka Murthy, I.K. International PublishingHouse Pvt. Ltd., New Delhi, 3rd revised edition-2006.

2. Engineering Graphics by K.R.Gopalakrishna, 32nd edition, 2005, Subash PublishersBangalore.

BAS 3153/BAS3253 CHEMISTRY LAB

Course Objective: The main objectives of course are:

1. To Purify and identify organic compounds.2. To calculate reaction yield for relevant lab experiments .

. Learning objective: Upon successful completion of this course, students will be able to:

1. identify the difference between scholarly/peer-reviewed research and practical

information related to agriculture as well as information that is authoritative, unbiased,

and timely.

2. apply the principles of teaching and learning in relation to practical chemistrylaboratories and associated chemistry concepts.

Course Contents:

Module List of Experiments Total Credit hours

1.

2.

.) .

4.

5.

6:

Determination of constituents and amount of alkalinity of supplied water sample.

Determination of total hardness of water by complexometric titration method.

Determination of chloride content in a given sample of bleaching powder

Determination .of chloride content io supplied water sample using 60 mohes method. ·

Determination of iron content in the given water sample by using external indicator

Determination of pH of a solution using a pH meter and titration of such a solution phmetrically.

Suggested Readings: I. Textbook of practical chemistry, ·A.I. Vogel, Prentice Hall, 5 th edition.2. Vogels quantitative chemical analysis, A.I, Vogel, Prentice hall, 6th edition.'3. Practical organic chemistry, F.G. Mann & B.C. Saunders, orient longman,1960.

* .

'

-'-

2

BAS 3201 Differential Equations and Fourier Analysis

Course Objective:

The general objective of the course is to introduce

I. the formulation and solution of ordinary differential equations;

Credits: 4

2. the concepts of series solution of differential equation and solution of Bessel ·s. Legendre'sequations ahd their properties;

3. the concept of Fourier series expansion of functions and harmonic analysis;4. the formulation and solution of partial differential equations arising in a number of practical

problems;5. the applications of partial differential equation in wave equations. heat flow and line

transmission.

Learning Outcomes:

Upon successful completion of the course, students will be able to

I. identify an ordinary differential equation and its order and degree;2. compute the general solution of 2nd order ordinary differential equations and apply them to solve

the L-C-R circuits:3. determine the general solution of higher order linear equations with constant coefficients:4. determine whether a system of functions is linearly independent using the Wronksian;5. use the method of reduction of order and undetermined coefficients to· find a second linearly

independent solution of a second order linear homogeneous equation when one solution is given;6. use the method cf variation of parameters to find particular solutions of second order, linear

homogeneous equations;7.. use power series and Frobenius series method to solve differential equations; 8. expand periodic functions into Fourier series the knowledge of which is useful in signal

processing;9. determine the Fourier sine and cosine series for functions defined on an interval;

• I 0. use the method of separation of variables to reduce some partial differential equations to ordinarydifferential equations;

11. solve quasilinear first-order partial differential equations using the method of characteristics andft rst integrals;

12. solve second-order hyperbolic partial differential equations by the travelling wave approach(D'Alembert's method of solution);

13'. provide an application oriented computation for solving wave equation. heat equation and steady state two dimensional heat flow.

Course Contents:

'Module Course Topics

Differential Equations Linear differential equations of nth order with constant coefficients, Complementary functions and particular integrals, Simultaneous linear differential e uations, Solution of secon o er differential

Total Hours Credits

30

(

SYLLABUS

BAS-3202 ENGINEERING PHYSICS II

Course Objective:

The main objectives of the course are 1. To provide knowledge and to develop an understanding of Modem Physics.2. To develop a scientific attitude at mic�o and nano scales of materials.

Learning Outcome:At the end of the course students shall be able

1. To apply knowledge in developing advanced materials and devices.2. To apply fundamental laws of electricity and magnetism in engineering.3. To identify and solve applied physics problems.

Course Contents:

Module

I

Course Topics

Fundamental of quantum Mechanics:

Wave particle duality, de-Broglie matte� wave,.

Davission Germer experiment, Phas� velocity and group velocity, Uncertainty principle and its applications, Wave function and its significance, Expectationvalue, Schrodinger wave equation and its significance, Particle in one dimensional· box, Linear harmonic oscillator.

Crystal Structure, X ray Diffraction & Electromagnetism:

Space lattice, basis, Unit cell, Lattice parameter, Seven crystal systems and Fourteen Bravais lattices, CrystalSystem Structure, Packing factor (cubic, body and face), Crystal structure of NaCl and diamond, Lattice planes and Miller Indices, Reciprocal Lattice, Diffraction of X-rays by

Total Hours

30

II crystal, Laue's experiment, Bragg's· Law, Bragg's 30 spectrometer. � Displacement current, Equation of continuity, Maxwell's equations (Integral ·and Differential forms), Poynting .. theorem and poynting vectors, EM-wave equation and its propagation characteristics in free space, non-conducting and in conducting media, Skin depth.

Credits

V/trJI· /Y ,

(l

-·

III

References:

Superconductivity and Nanotechnology:

I Superconductors: Temperature dependence of resistivity insuperconducting materials, Effect of magnetic field

I (Meissner effect), Temperature dependence of critical field, Type I and Type II superconductors, BCS theory (Qualitative), High temperature superconductors andapplications of super-conductors. Nano-Materials: Basic principle of nanosc1ence andtechnology, Structure; properties and uses of fullerene andcarbon nanotubes, Synthesis ··of nanomaterials-chemicalvapour deposition teclmique, pulse laser depositiontechnique, characterization techniques (XRD, SEM,AFM),. · Applications of nanotechnology,

1. Concept of modern physics, Auther Bieser, Tata Mc-Graw Hill2. Solid state Physics, S.O. Pillai, New Age International3. Solid State Physics, CharleKittal Seventh Ed. Wiley Eastren4. Nanotechnolgy, Reached Booker& Earl Boisen, Welly PL5. Introduction to Electrodynamics, David J. Griffith, PHI

30

�::-\, -----�� (Dr. Karunesh Tiwari (Prof. Rajeev Manohar)

Convener

�,�y (Dr. Nffin Jain)

Nominee

External Expert

1

Babu Banarasi Das University, LucknowDepartment of Computer Science & Engineering

School of Engineering


Credit Summary Chart:

Credit Summary Chart

Course CategorySemester Total

Credits%age

I II III IV V VI VII VIIIF 16/11 11/16 0 0 0 0 0 0 27/27 12.92C 10/16 16/10 25 25 21 21 12 16 146/146 69.85

GE 0 0 0 0 4 4 8 4 20 9.57OE 0 0 0 0 0 0 4 4 8 3.83GP 1 1 1 1 1 1 1 1 8 3.83

Total 27/28 28/27 26 26 26 26 25 25 209 100Discipline wise Credit Summary Chart

Course CategorySemester Total

Credits %ageI II III IV V VI VII VIII

Basic Sciences 10/12 12/10 4 3 22 10.52Humanities andSocials Sciences 0/4 4/0 2 2 3 3 21 10.05

Engg. Sciences 16/11 11/16 27 12.92ProfessionalSubject Core 19 20 18 17 10 8 92 44.02

ProfessionalSubject -General

Elective4 4 8 4 20 9.57

ProfessionalSubject -Open

Elective4 4 8 3.83

GP + ProjectWork, Seminar

and / orInternship inIndustry orelsewhere.

1 1 1 1 1 2 3 9 19 9.09

Total 27/28 28/27 26 26 26 26 25 25 209 100

2

SEMESTER III

Cou

rse

Cat

egor

y

CourseCode Code Title

ContactHours

Evaluation Scheme

Cre

dits

L T P CIA ESECourseTotal

CBHS3301/BHS3302

Industrial Psychology /Industrial Sociology

2 0 0 40 60 100 2

C BAS3301Complex Analysis andIntegral Transforms

3 1 0 40 60 100 4

C BCS3301 Discrete Mathematics 3 1 0 40 60 100 4

C BCS3302Object OrientedAnalysis and Design(Using UML)

2 1 0 40 60 100 3

C BCS3303 Digital Logic Design 3 1 0 40 60 100 4

CBCS3305/BCS3405

Computer Concepts &Programming in ‘C’ 3 1 0 40 60 100 4

C BCS3351UNIX & ShellProgramming

0 0 2 40 60 100 1

C BCS3352Object OrientedProgramming Lab

0 0 2 40 60 100 1

C BCS3353Digital Logic DesignLab

0 0 2 40 60 100 1

CBCS3355/BCS3455

‘C’ Programming Lab 0 0 2 40 60 100 1

GP3301 General Proficiency - - - 100 - 100 1Total 16 5 8 500 600 1100 26

3

SEMESTER IV

Cou

rse

Cat

egor

y


ContactHours

Evaluation Scheme

Cre

dits


CBHS3402/BHS3401

Industrial Sociology/Industrial Psychology

2 0 0 40 60 100 2

C BAS3401Statistical andNumerical Techniques

2 1 0 40 60 100 3

C BCS3401Database ManagementSystems

3 1 0 40 60 100 4

C BCS3402 Operating System 3 1 0 40 60 100 4

C BCS3403Data Structure Using'C'

3 1 0 40 60 100 4

C BCS3404Computer Organization& Architecture

3 1 0 40 60 100 4

C BCS3451Database ManagementSystem Lab

0 0 2 40 60 100 1

C BCS3452 Operating System Lab 0 0 2 40 60 100 1C BCS3453 Data Structure Lab 0 0 2 40 60 100 1

C BCS3454Numerical TechniquesLab

0 0 2 40 60 100 1


SEMESTER V

Cou

rse

Cat

egor

y

CourseCode

Code Title

ContactHours Evaluation Scheme

Cre

dits

L T P CIA ESE CourseTotal

C BHS3501Engineering &Managerial Economics

3 0 0 40 60 100 3

C BCS3501 Software Engineering 3 1 0 40 60 100 4

C BCS3502Microprocessor andInterfacing

3 1 0 40 60 100 4

C BCS3503 Computer Networks 3 1 0 40 60 100 4

C BCS3504Automata Theory andFormal Languages

3 1 0 40 60 100 4

C BCS3505 Computer Graphics 2 1 0 40 60 100 3

C BCS3552Microprocessor andInterfacing Lab

0 0 2 40 60 100 1

C BCS3553Computer NetworksLab

0 0 2 40 60 100 1

C BCS3555Computer GraphicsLab

0 0 2 40 60 100 1


4

SEMESTER VI

Cou

rse

Cat

egor

y

CourseCode

Code Title

ContactHours

Evaluation Scheme

Cre

dits


C BHS3601 Industrial Management 3 0 0 40 60 100 3

C BCS3601Core and AdvanceJAVA

3 1 0 40 60 100 4

C BCS3602Design & Analysis ofAlgorithms 3 1 0

40 60 100 4

C BCS3603Advanced ComputerArchitecture 2 1 0

40 60 100 3

C BCS3604 Compiler Design 3 1 0 40 60 100 4GE Generic Elective I 3 1 0 40 60 100 4C BCS3651 JAVA Lab 0 0 2 40 60 100 1

C BCS3652 Algorithms Lab 0 0 2 40 60 100 1

C BCS3658 Seminar 0 0 2 100 0 100 1GP3601 General Proficiency - - - 100 - 100 1

Total 18 4 6 520 480 1000 26Note: The students need to undergo a 4 to 6 weeks of industrial training that will beevaluated in the VII Semester.

SEMESTER VII

Cou

rse

Cat

egor

y


ContactHours

Evaluation Scheme

Cre

dits


C BCS3701 Artificial Intelligence 3 1 0 40 60 100 4

C BCS3702Network Security andCryptography

3 0 0 40 60 100 3

GE Generic Elective II 3 1 0 40 60 100 4GE Generic Elective III 3 1 0 40 60 100 4OE Open Elective I* - - - 40 60 100 4

C BCS3751Artificial IntelligenceLab

0 0 2 40 60 100 1

C BCS3752 Network Security Lab 0 0 2 40 60 100 1

C BCS3759 Project I# 0 0 4 100 0 100 2

C BCS3758Industrial TrainingEvaluation

0 0 2 100 0 100 1


*Students will opt any one of the open elective from the list of open electivesprovided by the university.

5

#Students need to submit an abstract for the project, select a guide and will completethe literature review related to the project.

SEMESTER VIII

Cou

rse

Cat

egor

yCourseCode

Code Title

ContactHours Evaluation Scheme

Cre

dits


C BCS3801Digital ImageProcessing 3 0 0 40 60 100 3

GE Generic Elective IV 3 1 0 40 60 100 4GE Generic Elective V 3 1 0 40 60 100 4OE Open Elective II** - - - 40 60 100 4

C BCS3851Digital ImageProcessing Lab 0 0 2 40 60 100 1

C BCS3859 Project II## 0 0 16 160 240 400 8GP3801 General Proficiency - - - 100 - 100 1

Total 9 2 18 460 540 1000 25**The opted subject should be different from the one selected in VII Semester.

##This is in continuation with the project work started in Semester VII. In thissemester the students will formulate the methodology do experimentation and showthe results. Finally all project work will be presented in a report i.e. Project Report.

Legends:L Number of Lecture Hours per weekT Number of Tutorial Hours per weekP Number of Practical Hours per weekCIA Continuous Internal AssessmentESE End Semester Examination

Category of Courses:F Foundation CourseC Core CourseGE Generic ElectiveOE Open Elective

List of Open ElectivesOffered by Department of Computer Science and Engineering

S.N. Course Code Open Elective

1 OE33211 E-Commerce2 OE33221 Human Computer Interaction

6

List of Generic Electives

CourseCode Generic Elective I

GE33211 Multimedia Systems

GE33212 Soft Computing

GE33213 Evolutionary Algorithms

GE33214 Distributed Database Systems

GE33215 Internet of Things

CourseCode

Generic Elective II

GE33221 System Programming & System AdministrationGE33222 System Modeling & Simulation

GE33223 Web Technology

GE33224 Embedded System Design

GE33225 Big Data

CourseCode Generic Elective III

GE33231 Cyber law and SecurityGE33232 Real Time Operating SystemGE33233 RoboticsGE33234 Computer Vision

GE33235 Cloud Computing

CourseCode Generic Elective IV

GE33241 Data Mining and Ware HousingGE33242 Artificial Neural Network (ANN) and Fuzzy LogicGE33243 Mobile ComputingGE33244 Natural Language Processing

GE33245 Augmented & Virtual Reality

CourseCode

Generic Elective V

GE33251 Data CompressionGE33252 Distributed SystemGE33253 BioinformaticsGE33254 Pattern Recognition

GE33255 Deep Learning

Babu Banarasi Das University, Lucknow Department of CSE

1 | 9 1

SYLLABUS

BCS3101/ BCS3201 Foundation of Information Technology

Course Objective:

1. Introduce the fundamentals of computing devices and reinforce computervocabulary, particularly with respect to personal use of hardware and software,the internet, network and mobile computing.

2. Study the basic concepts and functions of hardware and software.3. Study the basic concepts and functions of operating system.4. Study the basic concepts and functions of computer network.5. Study the basic concepts and functions of Information Technology.6. Study the basic concepts of C programming language.7. Provide foundational or “Computer literacy” curriculum that prepares students

for life-long learning of computer concept and skills.

Learning Outcome:

At the end of the course, the student should be able to:

1. Understanding organization of computer system and networking.2. An ability to understand the basics of computer hardware and software.3. Awareness of basic information security issues.4. To understand the use of Information Technology in business.5. To analyse and understand various types of software system.6. An ability to understand operating system and its functions.7. Ability to apply knowledge and practice on office tools to develop I.T

application.8. To analyse various computer networks.

Course Contents:

Module Course Topics TotalHours

Credits

I

Hardware and SoftwareHardware, Software, Information technology, Typesof computer: Mainframe computer, networkcomputer, personal computer, laptop, personal digitalassistant (PDA); Personal computer: Centralprocessing unit (CPU), hard disk, common input oroutput devices, types of memory viz. RAM, ROM,peripheral device, computer performance.Input Devices: Mouse, keyboard, trackball, scanner,touchpad, light pen, joystick, digital camera andmicrophone. Output Devices: Monitors, screens,printers, plotters, speakers. Input/output Devices:Modems, Touch Screens. Storage Devices: Diskette,Zip disk, data cartridges, CD-ROM, internal, externalhard disk: Disk formattingSoftware: Types Of Software: Operating systemssoftware and application software, Software versions,Operating System: Functions and Types. GraphicalUser Interface (GUI), SDLC and its phases.

30 Hours 1


2 | 9 1

II

Computer NetworkNetworks: LAN, WAN, client/server, sharingprinters, applications, and files across a network.Intranet, Extranet, Internet and its uses, World WideWeb (WWW)The Telephone Network In Computing: PublicSwitched Telephone Network (PSTN), IntegratedServices Digital Network (ISDN), AsymmetricDigital Subscriber Line (ADSL), Analog and digitalmodem and transfer rate.

30 Hours 1

III

Information Technology (IT)Applications of IT: Applications in business such as:business administration systems, airline bookingsystems, insurance claims processing, online banking.Uses of large-scale computer applications ingovernment such as: public records systems (census,vehicle registration), revenue collection, electronicvoting. Applications in education such as: studentregistration and timetabling systems, computer-basedtraining (CBT), distance learning, homework usingthe Internet. Electronic World: electronic mail, E-Commerce, concept of purchasing goods and servicesonline, payment methods, advantages anddisadvantages of purchasing goods and servicesonlineHealth, safety and environment: Ergonomics, healthissues, precautions, recycling printed outputs,recycling printer toner cartridges, using efficientmonitor

30 Hours 1

IV

Introduction to the C LanguageIntroduction to the C Language and its Advantages, CProgram: Structure, Writing, Building an ExecutableVersion, Debugging, and Running.Data Types and Variables, Operands, Operators, andArithmetic Expressions, Control statements, use ofwhile, for and do while loops, nesting loops andbreak, continue statement.

30 Hours 1

Text/Reference Books:

1. D. S. Yadav, “Foundations of Information Technology”, New AgeInternational Pvt. Ltd.

2. Silberschatz, Galvin and Gagne, “Operating Systems Concepts”, WileyPublication

3. D M Dhamdhere, “Operating Systems: A Concept based Approach”, TMH4. Yashavant P. Kanetkar, “Let us C”, BPB


3 | 9 1

BCS3301 Discrete Mathematics

Course Objective:

1. To introduce a number of Discrete Mathematical Structures (DMS) found tobe serving as tools even today in the development of theoretical computerscience.

2. Course focuses on of how Discrete Structures actually helped computerengineers to solve problems occurred in the development of programminglanguages.

3. Also, course highlights the importance of discrete structures towardssimulation of a problem in computer science and engineering.

4. Introduction of a number of case studies involving problems of ComputerTechnology.

5. List the terms in a sequence, write a sequence in closed from computer thesum of a finite sequence, compute the product of a finite sequence and expresssequence in term recursive or non-recursive forms.

6. Simplify and evaluate basic logic statement including compound statementimplications, inverse, converse and contra positive using truth table andproperties of logic. Determine if a graph has Euler or Hamilton path or circuit.

Learning Outcome:

At the end of the course, the student should be able to:1. Have a complete knowledge on various discrete structures available in

literature.2. Have realization of some satisfaction of having learnt that discrete structures

are indeed useful in computer science and engineering and thereby concludingthat no mistake has been done in studying this course.

3. Gain some confidence on how to deal with problems which may arrive incomputer science and engineering in near future.

4. To appreciate the basic principles of Boolean algebra, Logic, Set theory.5. Be able to construct simple mathematical proofs.6. Be able to understand logical argument and logical constructs have a better

understanding of sets, functions and relations.

Course Contents:


Credits

I

Set Theory, Relations, Functions & NaturalNumbersSet Theory: Introduction, Combination of sets,Multisets, Ordered pairs, Proofs of some generalidentities on sets.Relations: Definition, Operations on relations,Properties of relations, Composite Relations, Equalityof relations, Recursive definition of relation, Order ofrelations.Functions: Definition, Classification of functions,Operations on functions, Recursively definedfunctions, Growth of Functions. Natural Numbers:Introduction, Mathematical Induction, Induction with

30Hours

1


4 | 9 1

Nonzero Base cases, Proof Methods, Proof by counter– example, Proof by contradiction.

II

Groups, Rings, Fields & LatticeAlgebraic Structures: Definition, Groups, Subgroupsand order, Cyclic Groups, Cosets, Lagrange'stheorem, Normal Subgroups, Definition andelementary properties of Rings and Fields, IntegersModulo n; Partial order sets: Definition, Partial ordersets, Combination of partial order sets, Hassediagram.Lattices: Definition, Properties of lattices ,Bounded,Complemented, Modular, Complete lattice;

30Hours

1

III

Boolean Algebra & Proposition LogicBoolean Algebra: Introduction, Axioms andTheorems of Boolean algebra, Algebraic manipulationof Boolean expressions, Simplification of BooleanFunctions, Karnaugh maps, Logic gates, Digitalcircuits and Boolean algebra.Propositional Logic: Proposition, well-formedformula, Truth tables, Tautology, Satisfiability;Contradiction; Algebra of proposition; Theory ofInference; Predicate Logic: First order predicate-well-formed formula of predicate, quantifiers, Inferencetheory of predicate logic.

30Hours

1

IV

Trees, Graph, Recurrence Relation &CombinatoricsTrees: Definition: Binary tree, Binary tree traversal,Binary search tree; Graphs: Definition andterminology: Representation of graphs, Multigraphs,Bipartite graphs, Planar graphs, Isomorphism andHomeomorphism of graphs, Euler and Hamiltonianpaths, Graph Coloring.Recurrence Relation & Generating function:Recursive definition of functions, Recursivealgorithms, Method of solving recurrences.Combinatorics: Introduction; Counting Techniques:Pigeonhole Principle.

30Hours

1


1. Koshy, “Discrete Structures”, Elsevier Publication.2. Kenneth H. Rosen, “Discrete Mathematics and Its Applications”, McGraw-

Hill.3. B. Kolman, R.C. Busby, and S.C. Ross, “Discrete Mathematical Structures”,

Prentice Hall.4. R.P. Grimaldi, “Discrete and Combinatorial Mathematics”, Addison Wesley.5. Jean Paul Trembley, R Manohar, “Discrete Mathematical Structures with

Application to Computer Science,” McGraw-Hill.


5 | 9 1

BCS3302 Object Oriented Analysis and Design (Using UML)

Course Objective:

1. Analysing and designing problem using OOAD techniques.2. Analysing and designing problems using UML.3. Understanding from example with UML.4. Understanding of modelling, architecture and SDLC.5. Study the basic concepts and functions of UML.6. Learn about Modelling, Architecture and SDLC.7. Learn various Diagrams like Class and Object diagram.8. Understand the Modelling Techniques.9. Learn various Architectural modelling likes activity and component diagrams.

Learning Outcome:

At the end of the course, the student should be able to:1. Specify, analyse and design the use case drive requirements for a particular

system.2. Model the event driven state of object and transform them into implementation

specific layouts.3. Identify analyse the subsystem, various components and collaborate them

interchangeably4. Draw the various Classes and Objects.5. Apply the Modelling Techniques.6. Use various Relationships.7. Compare various interaction Diagrams.8. Design and implement activity, component and deployment diagram.

Course Contents:


Credits

I

Introduction to UMLIntroduction to UML Model, Importance of Model,Principles of Modelling, and Object orientedModelling, Conceptual Model of UML, Architecture,and Software Development Life Cycle.

30 Hours 1

II

Basic and Advanced Structural ModelingClasses and Advanced Classes, Relationship andAdvanced Relationship – Dependency,Generalisation and Realization, Association andAggregation- Association Class, Interfaces, Packages.Class and Object Diagrams-Terms and Concepts andModelling Techniques.Basic Behavioral Modeling-IInteractions- Terms and Concepts, Interactiondiagrams and its Type - Sequential diagram andCollaboration diagram, Modeling Techniques.

30 Hours 1

III

Basic Behavioral Modeling-IIUse cases- Terms and Concepts, Use case diagrams-Use case and Collaboration and ModelingTechniques, Activity diagrams-Forking and Joining,

30 Hours 1


6 | 9 1

Swimlanes, Object flow.Architectural ModelingEvents and signals, Processes and Threads, StateMachines, State Chart diagrams, Component andComponent diagrams- Terms and Concepts andModeling Techniques.Deployment and Deployment diagrams- Terms andConcepts and Modeling Techniques.


1. Grady Booch, James Rumbaugh, Ivar Jacobson: “The Unified ModelingLanguage User Guide”, Pearson Education.

2. Hans-Erik Eriksson, Magnus Penker, Brian Lyons, David Fado: “UML 2Toolkit”, WILEY -Dreamtech India Pvt. Ltd.

3. Meilir Page-Jones: “Fundamentals of Object Oriented Design in UML”,Pearson Education.

4. Pascal Roques, “Modeling Software Systems Using UML2”, WILEY-Dreamtech India Pvt. Ltd.

5. Atul Kahate, “Object Oriented Analysis & Design”, McGraw-Hill.6. Mark Priestley, “Practical Object-Oriented Design with UML”, McGraw Hill

BCS3303 Digital Logic Design

Course Objective:

1. To impart an understanding of basic concepts of Boolean algebra and digitalSystem.

2. To impart familiarity with the design and implementation of different types ofpractically used sequential circuits.

3. To provide an introduction to use hardware description circuits4. Introduce the concept of digital and binary systems5. Be able to design and analyse combinational logic circuits.6. Be able to design and analyse sequential logic circuits.7. Reinforce theory and techniques taught in the classroom through experiments

and projects in the laboratory.

Learning Outcome:

At the end of the course, the student should be able to:1. Apply the basic concepts of Boolean algebra for the simplification and

implementation of logic functions using suitable gates namely NAND, NORetc.

2. Design simple combinational circuits.3. Define different number systems, binary addition and subtraction, 2’s

complement representation and operations with this representation.4. Understand the basic knowledge of flip-flops5. Understand the different switching algebra theorems and apply them for logic

functions.6. Define the Karnaugh map for a few variables and perform an algorithmic

reduction of logic functions.


7 | 9 1

7. Define the following combinational circuits: buses, encoders/decoders,(de)multiplexers, exclusive-ORs, comparators, Arithmetic-logic; and to beable to build simple applications.

Course Contents:

Module Course TopicsTotalHours Credits

I

Binary Numbers and Gate level MinimizationDigital system and binary numbers: Signed binarynumbers, Binary codes, Cyclic codes, Error detectingand correcting codes, Hamming codes, Floating pointrepresentation.Gate-level minimization: The map method up to fivevariable, Don’t care conditions, Karnaugh maps, POSsimplification, NAND and NOR implementation,Quine McClusky method (Tabular method).

30Hours

1

II

Combinational LogicCombinational circuits: analysis procedure, designprocedure;Binary adder-subtractor; decimal adder; binarymultiplier; magnitude comparator; decoders;encoders; multiplexers.

30Hours

1

III

Synchronous Sequential LogicSequential circuits: Binary cell, Latches, Flip-flops-RS, JK, Master-Slave JK, D F/F,T flip flops;Synchronous Sequential Circuit Design:Fundamentals of Synchronous sequential circuits;Classification of synchronous machines; Analysis ofSynchronous Sequential circuits; Design ofSynchronous and Asynchronous Counters-Shiftregisters, Ring counters; Analysis and design of FiniteState Machines; Timing issues in synchronouscircuits.

30Hours

1

IV

Asynchronous Sequential LogicFundamentals of Asynchronous Sequential circuits:Analysis and design of Asynchronous Sequentialcircuits; Pulse mode and Fundamental-mode Circuits;Cycles; Races; Hazards in asynchronous circuits;Programmable Logic Devices: PLAs, PALs, CPLD;FPGA Architecture; Finite state machines: Mealy,Moore design.

30Hours

1


1. Raj Kamal, “Digital Systems Principle and Design”, Pearson Education.2. Balbaniam, Carison, “Digital Logic Design Principles”, Wiley Publications.3. Morris Mano, “Digital Design”, Pearson Education.4. R.P. Jain, “Modern Digital Electronics”, McGraw Hill.5. D.P. Leach, A .P. Malvino, “Digital Principles and Applications”, TMH.6. Tocci, Digital systems, “Principles and applications”, Pearson.


8 | 9 1

7. Sudhakar Yalamachili, John M. Yarbrough, “Introductory VHDL”, PearsonEducation.

BCS3305/BCS3405 Computer Concepts & Programming in ‘C’Course Objective:

1. The course aims to provide exposure to problem solving throughprogramming.

2. It aims to train the student to the logic concepts of c- programming language.3. To learn C programs and to apply your skills in writing real application

programs using C.4. Explains all the concepts of C programming language clearly with simple

programs.5. To learn the basics of all other programming languages such as C++, Java,

Learning Outcome:


1. Identify situation where computational methods and computers would beuseful.

2. Write, compile and debug programs in C language.3. Chose the right data representation formats based on the requirements of the

problem.4. Design programs involving decision structures, loops and functions.5. Explain the difference between call by value and call by reference6. Understand the dynamics of memory by the use of pointers.7. Use different data structures and create/update basic data files.

Course Contents:


Credits

I

IntroductionProgramming Environment, Concept of algorithm,Strategy for designing Algorithms, Top-downdevelopment, Stepwise refinement, Flowchart,Programming Languages, Assembler, Compiler,Interpreter, Systematic Development of Programs,Program Writing and execution, Introduction to thedesign and implementation of correct efficient andmaintainable programs, Structured ProgrammingConcept, Number System and Conversion Methods,Introduction to C language, Identifiers, Keywords,Constants and Variables in C, Storage classes,Fundamental Data types in C, Integer types, short,long. Unsigned Character types, single and doubleprecision floating point.

30Hours

1

II

Storage Classes, Operators and ControlStatementsStorage Classes in C: Automatic, register, static,extern, Operators and Expressions in C: Arithmetic,

30Hours

1


9 | 9 1

Relational, Logical, Assignment, Bitwise,Conditional, Increment and Decrement, SpecialOperators such as comma, sizeof etc. TypeConversion in C, Operator Precedence andAssociativity, Mixed mode operations, StandardInput/output functions: printf(), scanf(), getch(),getchar(), getche() etc. Conditional and ControlStatements: if statement, if-else statement, nested if-else statement, else if ladder, switch statements,restrictions on switch values, Use of break and defaultstatement with switch. Looping or Iteration: Uses ofwhile, for and do-while loops, nesting of loops, use ofbreak and continue statements.

III

Arrays, Structures and FunctionsArray, notation and representation, using onedimensional, two dimensional and multi-dimensionalarrays, Arrays of unknown and varying size,Searching and sorting in arrays. Strings: Stringdeclaration and initialization, String manipulation.Structures: Purpose and use of structures, declaringand assigning of structures, accessing structureelements, Array of structures, Arrays withinstructures. Union: Utility of unions, Union ofstructures. Function Declaration, function Definition,function call, Passing values between functions,Global and local variables and their scope, Call byvalue and call by reference

30Hours

1

IV

Pointers, Preprocessors and File HandlingPointers: Understanding Pointers, Declaration andinitialization of pointer variables, Accessing theaddress of the variable, Pointer arithmetic, Pointersand arrays. Dynamic Memory Allocation, Stack,Linked list, Recursion, Pointers to functions,Declaration of a pointer to a function, Initialization offunction pointers, Calling a function using a functionpointer, Passing a function to another function, Howto return a function pointer. Standard C libraryfunctions: Math functions, String handling functions,The C preprocessor: preprocessor directives, definingand calling macros, conditional compilation, passingvalues to the compiler. File Handling in C: Types offiles, Defining, opening and closing of a file,Input/output operations on files, Multiple filehandling in C.

30Hours

1


1. Yashavant P. Kanetkar, “Let Us ‘C’”, BPB Publications2. Jeri R. Hanly, Elliot B. Koffman, “Problem Solving and Program Design in

C”, Pearson Addison-Wesley.


10 | 9 1

3. Behrouz A., “Computer Science- A Structured Programming Approach UsingC”.

4. E Balaguruswamy, “Computer Concepts and Programming in C”, TataMcGraw Hill Publications

BCS3351 UNIX & Shell Programming

Introduction to basic UNIX commands and scripts.

1. To Study Basic UNIX / Linux Commands.2. Study & use of commands for performing arithmetic operations with UNIX/Linux.3. Performing input output redirection.4. Practicing Disk related utilities.5. Implementing the file security using chmod, umask and sticky bit.6. Understanding filters & pipes to perform complex taskspr, head,7. tail, cut, paste, sort, uniq, nl, tr, grep etc.8. Using Regular Expressions (including basic awk programming)Shell Programming1. Learning vi editor2. Writing and executing Shell script for UNIX environment3. Implementing positional parameters, shell Meta characters,argument validation inShell scripts.4. Shell programming- writing simple functions, basic tests, loops, patterns,

expansions, substitutions5. Writing, compiling and running a C program on UNIX / Linux.6. Implementation of eval command to handle input and output

BCS3352 Object Oriented Programming Lab

Tools used: Violet UML Editor/Agro-UML / MS Visio / Rational Rose

Language used: UML 2.0

1. Develop a UML Class diagram For Online railway reservation system.2. Develop a UML Class diagram for Library Management system.3. Develop a Use-Case Model for Student Admission System in a University,

make necessary assumptions.4. Develop Use-Case diagram for a library, where a member can perform two

operations issue book and return it. A book is issued to a member only afterverifying his credentials

5. Develop Use-Case diagram for a travel agent.To book a flight ticket the travel agent need to know the details about journeydate and user address. The user can pay either by cash or by card. User canalso cancel a booked ticket later Travel agent also allows to book a hotelalong with flight ticket, so while cancelling a flight ticket the agent also cancelhotel booking. Appropriate refund as per policy is made in case ofcancellation.

6. Develop a UML class diagram & sequence diagram for a web browserconsisting of different sub-components, which can be primarily categorized


11 | 9 1

into browser rendering engine and browser control. The web browser control,too, consists of several sub-components including navigation, window control,event handlers, page display etc.

7. Develop a UML Sequence diagram for an information system for online bookstore.

8. Develop a UML Class diagram & Sequence diagram for car manufacturingprocess.

9. Develop State-Transition diagram for online air reservation system10. Develop Deployment diagram for different scenarios of Railway Reservation

System.


1. Use Case Driven Object Modelling with UML: Theory and Practice, Apress,2007

2. UML 2 Certification Guide: Fundamental & Intermediate Exams (TheMK/OMG Press), Morgan Kaufmann, 2006

3. UML Distilled: A Brief Guide to the Standard Object Modelling Language,Addison Wesley

BCS3353 Digital Logic Design Lab

Note: Minimum 10 experiments to be performed by students

List of Experiments:

1. Simplification, Realization of Boolean Expressions using Logicgates/Universal gates.

2. Realization of Half/Full adder and Half/Full Subtractors using logic gates.3. Realization of parallel adder/Subtractors using 7483 chip.4. BCD to Excess-3 code conversion and vice versa.5. Realization of Binary to Gray code conversion and vice versa.6. MUX/DEMUX–use of 74153, 74139 for arithmetic circuits and code

converter.7. Realization of One/Two bit comparator and study of 7485 magnitude

comparator.8. Use of a Decoder chip to drive LED display and Priority encoder.9. Truth table verification of Flip-Flops:

a. JK Master slave (ii) T type (iii) D type.10. Realization of 3 bit counters as a sequential circuit and MOD–N counter

design (7476, 7490, 74192, 74193).11. Perform Shift left; Shift right, SIPO, SISO, PISO, PIPO operations using

74S95.12. Wiring and testing of Ring counter/Johnson counter.13. Wiring and testing of Sequence generator.

BCS3355/ BCS3455 ‘C’ Programming Lab

Note: Minimum 10 experiments to be performed by students.

List of Experiments: Using Turbo C / Visual Studio 6.0 C++ environment

Part I:


12 | 9 1

1. Creating and editing simple C program, debugging, compilation, execution.2. ‘C’ programming on variables and expression assignment, simple arithmetic

Loops, If-else, Case statements, break, continue, goto.3. Implementing different operations on Single & Multidimensional arrays.4. Implementing different String handling inbuilt and user defined functions.5. Functions, recursion, file handling in ‘C’.6. Pointers, address operator, declaring pointers and operations on pointers.7. Address of an array, structures, pointer to structure, dynamic memory

allocation.8. 2’s complement of a numbers.

BCS3401 Database Management Systems

Course Objective:

1. The course DBMS provides an introduction to the management of system.2. The course emphasizes the understanding of the fundamental of relational

system includes data mode, data architecture and data manipulations.3. The course also provides an understanding of new development such as

internet Database environment and data warehousing.4. The course uses a problem based approach to learning.5. To develop the concepts of Transaction Processing System, Concurrency

control, and Recovery procedures in database.

Learning Outcome:


1. Understand terms related to database design and management.2. Understand the objectives of data and information management.3. Understanding of data development problems.4. Relation model and RDBMS understanding.5. Construct conceptual data model.6. Understand data base performance issues.7. Understand the basic of data management and administration.

Course Contents:


Credits

I

Database System Concepts, Database Users, andArchitectureIntroduction to Database System with example,Characteristics of the Database Approach, Users ofDatabase System, Advantages and disadvantages ofUsing a DBMS, Implications of the DatabaseApproach, Data Models, Schemas, and Instances,DBMS Architecture and Data Independence,Database Languages and Interfaces, The Componentsof Database System, Classification of DatabaseManagement Systems

30 Hours 1

IIData Modelling & Relational DatabaseManagement System

30 Hours 1


13 | 9 1

Data Modelling Using the Entity-Relationship Model,concepts, notation for ER diagram, mappingconstraints, keys, Concepts of Super Key, candidatekey, primary key, Entity Types, Entity Sets, andAttributes, Relationships, Relationship Types, Roles,and Structural Constraints, Strong vs. Weak EntityTypes, ER Diagrams, Naming Conventions, andDesign Issues, Enhanced Entity-RelationshipModelling, Subclasses, Super classes, andInheritance, Specialization and Generalization,Constraints and Characteristics of Specialization andGeneralization, Modelling of UNION Types UsingCategories, The Relational Data Model, RelationalConstraints, and the Relational Algebra, RelationalModel Concepts, Relational Constraints andRelational Database Schemas, Update Operations andDealing with Constraint Violations, Basic RelationalAlgebra Operations, Additional RelationalOperations, Examples of Queries in RelationalAlgebra

III

SQL and Database Design Theory andMethodologyStructured Query Language- The Relational DatabaseStandard, Data Definition, Constraints, and SchemaChanges in SQL, Types of SQL Commands, SQLOperators and their Procedure, Insert, Delete, andUpdate Statements in SQL, Queries and Sub Queries,Aggregate Functions, Joins, Unions, Intersection,Minus, Views (Virtual Tables) in SQL, Cursors,Triggers and PL/SQL, Functional Dependencies andNormalization for Relational Databases, InformalDesign Guidelines for Relation Schemas, FunctionalDependencies, Normal Forms Based on PrimaryKeys, General Definitions of Second and ThirdNormal Forms, Boyce-Codd Normal Form,Multivalued Dependencies and Fourth Normal Form,Join Dependencies and Fifth Normal Form

30 Hours 1

IV

Transaction Processing, Concurrency Control andDatabase RecoveryTransaction Processing Concepts, Introduction toTransaction Processing, Transaction states and StateDiagram, Transaction and System Concepts,Desirable Properties of Transactions, Schedules andRecoverability, Serializability of Schedules,Concurrency Control Techniques, LockingTechniques for Concurrency Control, ConcurrencyControl Based on Timestamp Ordering, Multi versionConcurrency Control Techniques, Validation(Optimistic) Concurrency Control Techniques,Granularity of Data Items and Multiple Granularity

30Hours 1


14 | 9 1

Locking, Database Recovery Techniques, RecoveryConcepts, Recovery Techniques Based on DeferredUpdate, Recovery Techniques Based on ImmediateUpdate, Shadow Paging, The ARIES RecoveryAlgorithm, Database Backup and Recovery fromCatastrophic Failures, Client Server DatabaseEnvironment, Internet Database Environment, DataWarehousing Introduction.


1. Korth, Silbertz, Sudarshan, “Data Base Concepts”, McGraw-Hill.2. Ivan Bayross, “SQL, PL/SQL: The Programming Language Of Oracle”3. Date C. J., “An Introduction to Data Base System”, Addision Wesley.4. Elmasri, Navathe, “Fundamentals of Data Base Systems”, Addision Wesley.5. Bipin C. Desai, “An introduction to Data Base Systems”, Galgotia Publication.6. Ramakrishnan, Gehrke, ‘Data Base Management System”, McGraw-Hill.7. Connolly &Begg, “Database Systems: A Practical Approach to Design,

Implementation and Management”, Pearson Education.8. R. S. Despandey, “SQL/PL SQL for Oracle’.

BCS3402 Operating system

Course Objective:

1. Study the basic concepts and functions of operating systems.2. Understand the structure and functions of OS.3. To gain insight on the distributed resource management components.4. Learn about Processes, Threads and Scheduling algorithms.5. To gain knowledge on O.S concepts that includes architecture mutual

exclusion algorithms, deadlock detection algorithms and agreement.6. Understand the principles of concurrency and Deadlocks.7. Learn various memory management schemes.8. Study I/O management and File systems.

Learning Outcome:

At the end of the course, the student should be able to:1. Understanding of the concepts, structure and design of O.S.2. Design various Scheduling algorithms.3. Apply the principles of concurrency.4. Design deadlock, prevention and avoidance algorithms.5. Compare and contrast various memory management schemes.6. Design and Implement a prototype file systems.7. Demonstrate understanding of O.S design and its impact on application system

design and performance.

Course Contents:


IIntroduction to Operating System and ProcessConceptOperating system and functions, Classification of

30Hours

1


15 | 9 1

Operating systems, Operating System Structure,Operating System Services, System call and Systemprogram, Process concept, Process state, Processcontrol block, Context switching, Operation onprocess, Threads and their management, Benefits ofmultithreading, Types of threads, Threading issues,CPU-scheduling, Scheduling criteria, SchedulingAlgorithms, Concurrent Processes, Inter ProcessCommunication models and Schemes

II

Process Synchronization and DeadlockProcess synchronization, Producer/ConsumerProblem, Critical Section Problem, Peterson’ssolution, Synchronization of hardware, Semaphore,Classical-problem of synchronization, Deadlock,Deadlock characterization, Deadlock Prevention,Deadlock Avoidance, Resource allocation graphalgorithm, Banker’s algorithm, Deadlock detection,Recovery from deadlock

30Hours

1

III

Memory ManagementMemory Management, Basic bare machine, Residentmonitor, Multiprogramming with fixed partitions,Multiprogramming with variable partitions, Paging,Segmentation, Paged segmentation, Virtual memoryconcepts, Demand paging, Performance of demandpaging, Page replacement algorithms, Thrashing

30Hours

1

IV

I/O Management And File SystemFile System Structure, File System Implementation,Directory Implementation and Allocation Methods,Free space Management, Kernel I/O Subsystems,Disk Structure, Disk Scheduling, Disk Management,Swap-Space Management

30Hours

1


1. Silberschatz, Galvin and Gagne, “Operating Systems Concepts”, Wiley Publication2. Sibsankar Halder and Alex A Aravind, “Operating Systems”, Pearson Education3. Harvey M Dietel, “An Introduction to Operating System”, Pearson Education4. D M Dhamdhere, “Operating Systems: A Concept based Approach”, TMH5. William Stallings, “Operating Systems: Internals and Design Principles”, Pearson

Education

BCS3403 Data Structure using ‘C’Course Objective:

1. Master analysing problem writing program solutions to problems using theabove techniques. Demonstrate familiarity with major algorithms and datastructures.

2. Demonstrate familiarity with major algorithms and data structures.3. Master the implementation of linked data structures such as link list and binary

trees.


16 | 9 1

4. Analyse performance of algorithms.5. Be familiar with several sub quadratic solving algorithms including quick

short, heap sort and merge short.6. Choose the appropriate data structure and algorithm design method for a

specified application.7. Determine which algorithm or data structure to use in different scenarios.8. Be familiar with writing recursive methods.9. Demonstrate understanding of the abstract properties of various data structures

such as stacks, queues, lists, trees and graphs.10. Use various data structures effectively in application programs.11. Demonstrate understanding of various sorting algorithms, including bubble

sort, insertion sort, selection sort, heap sort and quick sort.12. Understand and apply fundamental algorithmic problems including Tree

traversals, Graph traversals, and shortest paths.13. Demonstrate understanding of various searching algorithms.

Learning Outcome:


1. Student develop knowledge of applications of data structures including theability to implement algorithms for the creation, insertion, deletion, searchingand sorting of each data structures.

2. Demonstrate knowledge of underlying data structures needed for solvingproblems and programming.

3. Develop knowledge of applications of data structures for storage and retrievalof ordered and unordered data.

4. Learn to analyse and compare algorithms for efficiency using Big-O notation.5. Implement/ utilize various data structures using a programming language such

as C.6. Analyse algorithms in connection with data structures.7. Demonstrate knowledge of various searching and sorting techniques.8. Apply dynamic memory allocation in creation of linked lists.

Course Contents:


Credits

I

IntroductionIntroduction: Basic Terminology, Data types and itsclassification, Algorithm complexity notations like bigOh, Time-Space trade- off. Abstract DataTypes (ADT). Array: Array Definition, Representationand Analysis of Arrays, Single and MultidimensionalArrays, Address calculation, Array as Parameters, SparseMatrices, Recursion- definition and processes,simulating recursion, Backtracking, Recursivealgorithms, Tail recursion, Removal of recursion, Towerof Hanoi

30Hours

1

II

Stack and Linked ListStack, Array Implementation of stack, LinkedRepresentation of Stack, Application of stack:Conversion of Infix to Prefix and Postfix Expressions

30Hours

1


17 | 9 1

and Expression evaluation, Queue, Array and linkedimplementation of queues, Circular queues, D-queuesand Priority Queues. Linked list, Implementation ofSingly Linked List, Two-way Header List, Doubly linkedlist, Linked List in Array. Generalized linked list,Application: Garbage collection and compaction,Polynomial Arithmetic

III

Tree, Searching, Sorting and HashingTrees: Basic terminology, Binary Trees,, algebraicExpressions, Complete Binary Tree, Extended BinaryTrees, Array and Linked Representation of Binary trees,Traversing Binary trees, Threaded Binary trees, BinarySearch Tree(BST), AVL Trees, B-trees.Application: Algebraic Expression, Huffman codingAlgorithm. Internal and External sorting, Insertion Sort,Bubble Sort, selection sort, Quick Sort, Merge Sort,Heap Sort, Radix sort, Searching &Hashing: Sequentialsearch, binary search, Hash Table, Hash Functions,Collision Resolution Strategies, Hash TableImplementation. Symbol Table, Static tree table,Dynamic Tree table.

30Hours

1

IV

GraphsGraphs: Terminology, Sequential and linkedRepresentations of Graphs: Adjacency Matrices,Adjacency List, Adjacency Multi-list, Graph Traversal:Depth First Search and Breadth First Search, ConnectedComponent, Spanning Trees, Minimum Cost SpanningTrees: Prims and Kruskal algorithm. Transitive Closureand Shortest Path algorithm: Warshal Algorithm andDijikstra Algorithm.

30Hours

1


1. Aaron M. Tenenbaum, Yedidyah Langsam and Moshe J. Augenstein, “DataStructures Using C and C++”, PHI.

2. Horowitz and Sahani, “Fundamentals of Data Structures”, GalgotiaPublication.

3. Jean Paul Trembley and Paul G. Sorenson, “An Introduction to DataStructures with applications”, McGraw Hill.

4. R. Kruseetal, “Data Structures and Program Design in C”, Pearson Education5. Lipschutz, “Data Structures”, Schaum’s Outline Series, TMH.6. GAV Pai, “Data Structures and Algorithms”, TMH.

BCS3404 Computer Organization & Architecture

Course Objective:

1. To understand how computer are constructed out of a set of functional units.2. To understand how these functional units operate, interact and communicate.3. To understand how to computations are actually performed at the machine

level.


18 | 9 1

4. To understand the factors and trade-offs that affect computer performance.5. To understand how problems expressed by humans are expressed as binary

string in a machine.

Learning Outcome:


1. Identify the basic structure and function unit of a digital computer.2. Analyse the effect of addressing modes on the execution time of a program.3. Design processing unit using the concepts of ALU and control logic unit.4. Select appropriate instruction standards for I/O devices.

Course Contents:


I

Computer Evolution & ArithmeticA Brief History of computers: Von NeumannArchitecture, Hardware architecture, ComputerComponents, Interconnection Structures, BusInterconnection, Register Transfer Language, Bus andMemory Transfers, Bus Architecture, Bus ArbitrationTechniques, Arithmetic Logic, Shift Micro operation,Arithmetic Logic Shift Unit, Arithmetic Algorithms(addition, subtraction, Booth Multiplication, Division)

30Hours

1

II

Control UnitControl Design: Hardwired & Micro Programmed ,Performing of arithmetic or logical operations,Multiple-Bus organization, Hardwired Control, Microprogrammed control, Microinstruction, Microprogram sequencing, Wide-Branch addressing,Microinstruction with Next-address field, Prefetching,Microinstruction, Pipeline control: Instructionpipelines, Pipeline performance

30Hours

1

III

Processor Organization and Input-OutputOrganizationProcessor Design: General register organization,Stack organization, Addressing mode, Instructionformat, Data transfer & manipulations, ProgramControl, Reduced Instruction Set Computer, Input-Output Organization: Peripheral devices, I/O interfaceI/O ports.Interrupts: Interrupt hardware, Types of interrupts andexceptions, Modes of Data Transfer: ProgrammedI/O, Interrupt initiated I/O, Direct Memory Access:I/O channels and processors, Serial Communication:Synchronous & asynchronous communication,Standard communication interfaces

30Hours

1

Memory Organization: Basic concept and hierarchy,semiconductor RAM memories,2D & 2 1/2D memoryorganization, ROM memories, Cache memories,Concept and design issues 9 performance, Address

30Hours 1


19 | 9 1

IV mapping and replacement, Auxiliary memories:Magnetic disk, Magnetic tape and optical disks,Virtual memory, Concept implementation


1. Patterson, ”Computer Organisation and Design”, Elsevier Publication2. William Stalling, “Computer Organization”, PHI.3. Vravice, Hamacher & Zaky, “Computer Organization”, TMH.4. Moris Mano, ” Computer System Architecture”, PHI5. John P Hays, “ Computer Organization”, McGraw Hill6. Tannenbaum,” Structured Computer Organization”, PHI7. P Pal Chaudhry, ” Computer Organization & Design”, PHI

BCS3451 Database Management System Lab



1. Write the queries for Data Definition and Data Manipulation Language.2. Write SQL queries using logical operations (=, <,>, etc)3. Write SQL queries using SQL operators.4. Write SQL query using character, number, date and group functions.5. Write SQL queries for relational algebra.6. Write SQL queries for extracting data from more than one table.7. Write SQL queries for sub queries, nested queries.8. Write programme by the use of PL/SQL.9. Concepts for ROLL BACK, COMMIT & CHECK POINTS.10. Create VIEWS, CURSORS and TRGGERS & write ASSERTIONS.11. Create FORMS and REPORTS.12. Create table command.13. Alter table command.14. Drop table command.15. Update table command.

BCS3452 Operating Systems Lab



Implement the following on LINUX or other UNIX like platform. Use C for highlevel language implementation

1. Write programs using the following system calls of UNIX operating system:fork, exec, getpid, exit, wait, close, stat, open dir, read dir

2. Write programs using the I/O system calls of UNIX operating system (open,read, write, etc)

3. Write C programs to simulate UNIX commands like ls, grep, etc.4. Given the list of processes, their CPU burst times and arrival times,

display/print the Gantt chart for FCFS and SJF. For each of the schedulingpolicies, compute and print the average waiting time and average turnaroundtime.


20 | 9 1

5. Given the list of processes, their CPU burst times and arrival times,display/print the Gantt chart for Priority and Round robin. For each of thescheduling policies, compute and print the average waiting time and averageturnaround time.

6. Developing Application using Inter Process communication (using sharedmemory, pipes or message queues).

7. Implement the Producer – Consumer problem using semaphores (using UNIXsystem calls).

8. Implement memory management scheme: Free space is maintained as a linkedlist of nodes with each node having the starting byte address and the endingbyte address of a free block. Each memory request consists of the process-idand the amount of storage space required in bytes. Allocated memory space isagain maintained as a linked list of nodes with each node having the process-id, starting byte address and the ending byte address of the allocated space.

9. Implement any file allocation technique (Linked, Indexed or Contiguous).

BCS3453 Data Structure Lab


Write Programs in C or C++ for following.

1. Array implementation of Stack.2. Array implementation of Queue.3. Array implementation of Circular Queue.4. Array implementation of List5. Implementation of Stack,6. Implementation of Circular Queue,7. Implementation of List using Dynamic memory Allocation.8. Implementation of Queue.9. Implementation of Tree Structures,10. Implementation of Binary Tree.11. Implementation of Tree Traversal.12. Implementation of Binary Search Tree.13. Implementation of Insertion in BST.14. Implementation of Deletion in BST.15. Implementation of Searching and Sorting Algorithms.16. Graph Implementation, BFS.17. Graph Implementation, DFS.18. Graph Implementation, Minimum cost spanning tree.19. Graph Implementation, shortest path algorithm.

BCS3454 Numerical Techniques Lab

Write Programs in ‘C’ Language:

1. To deduce error evolved in polynomial equation.2. To find out the root of the Algebraic and Transcendental equations using

Bisection, Regula-falsi, Newton Raphson and Iterative Methods. Also give therate of convergence of roots in tabular form for each of these methods.

3. To implement Newton’s forward and Backward Interpolation formula.


21 | 9 1

4. To implement Gauss Forward and Backward, Bessel’s, Sterling’s and Evertt’sInterpolation formula

5. To implement Newton’s Divided Difference and Langranges Interpolationformula.

6. To implement Numerical Differentiations.7. To implement Numerical Integration using Trapezoidal, Simpson 1/3 and

Simpson 3/8 rule.

BCS3501 Software Engineering

Course Objective:

1. Study the basic concepts and functions of Software Engineering.2. To understand the phases in a software project.3. To understand the fundamental concepts of requirement engineering and

Analysis Modelling.4. Learn various Designing and Testing techniques.5. Understand the Techniques of Debugging.6. Learn various Software project planning activities7. Study Software Quality & Maintenance.

Learning Outcome:


1. Selection and implementation of different software development processmodels.

2. Extracting and analyzing software requirements specifications for differentprojects.

3. The ability to design & experiment with software prototypes and to select, usesoftware metrics.

4. Defining the basic concepts and importance of Software project managementconcepts like cost estimation, scheduling and reviewing the progress.

5. Effective communication skills trough oral and written reports and softwaredocumentation evaluated by both peer and faculty.

6. Applying different testing and debugging techniques and analyzing theireffectiveness.

7. Analyzing software risks and risk management strategies.8. Defining the concepts of software quality and reliability on the basis of

International quality standards.

Course Contents:

Module Course TopicsTotalHours

Credits

I

Introduction to Software Engineering, SoftwareEngineering Approaches, Defining the Problem,Developing a solution strategy, Planning anddevelopment process, Software Life Cycle Models,Visual Modeling, Software Development Methods,Software Cost Estimation, Staffing Level Estimation,Estimating Software Maintenance Cost

30Hours

1


22 | 9 1

II

Software Requirement Specification, FormalRequirement Speciation, Formal RequirementVerification, Axiomatic Specification, AlgebraicSpecification

30Hours

1

III

Software Design Paradigms, Function OrientedSoftware Design, Object Oriented Design, UML,Design Patterns, User Design Interface Pattern,Coding, Software Testing, Unit Testing, Integrationand System Testing, Debugging Techniques

30Hours

1

IV

Software Quality & Maintenance, Software qualitystandards, SEI CMM and ISO-9001, Softwarereliability and fault-tolerance, Software ProjectManagement, Software project planning, Softwaremonitoring and control, Software maintenance,Computer-aided software engineering (CASE),Software reuse, Component-based softwaredevelopment, Extreme programming

30Hours

1


1. Rajib Mall, “Fundamentals of Software Engineering”, Prentice Hall India.2. Pankaj Jalote, “An integrated approach to Software Engineering”, Springer/Narosa.3. Roger S. Pressman, “Software Engineering: A practitioner's approach”, McGrawHill.4. Ian Sommerville, “Software Engineering”, Addison-Wesley.

BCS3502 Microprocessor & Interfacing

Course Objective:

1. To understand basic architecture of 16 bit and 32 bit microprocessor.2. To implement interfacing from microprocessors based system to peripheral

devices.3. To learn how the hardware and software components of a microprocessor-

based system work together to implement system-level features;4. To understand techniques for faster execution of instructions and improve

speed of operation and performance of microprocessor.5. To learn the operating principles of, and gain hands-on experience with,

common microprocessor peripherals such as UARTs, timers, and analog-to-digital and digital-to-analog converters;

6. To understand interfacing of 16 bit microprocessor with memory andperipheral chips involving system design.

7. Be exposed to the tools and techniques used by practicing engineers to design,implement, and debug microprocessor-based systems (during the Lab).

Learning Outcome:


1. Design and conduct experiments related to microprocessor based systemdesign and to analyze their outcomes.


23 | 9 1

2. Design, debug and test a small scale microprocessor system.3. Design system using memory chips and peripheral chips for 16 bit 8086

microprocessor.4. Identify, formulate, and solve engineering problems in microprocessor based

system design.5. Use design tools for microprocessor system design, test and evaluation.6. Understand multicore processor and its advantages.

Course Contents:


I

Introduction: Memory & Microprocessor

Introduction: Memory Unit-Primary Memory: RAM,SRAM, DRAM, ROM, PROM, EPROM andEEPROM, Secondary Memory: Magnetic Memory,Tap, disc; cache memory; Real and virtual memory;Addressing capacity of CPU; Evolution ofMicroprocessor and its types; Microprocessorarchitecture and operation of its components;Addressing modes ;Interrupts; Data transfer schemes;Instruction and data flow; Timer and timing diagram;Interfacing devices; Architectural advancement ofmicroprocessors; Typical microprocessordevelopment schemes.

30Hours

1

II

8085 Microprocessor

8 bit Microprocessor: Internal architecture; PINdiagram; interrupt and machine cycle; Instructionsets: Addressing modes; Instruction Classification;machine control and assembler directives; Technicalfeatures of: The Pentium, PentiumPro MicroProcessor, Pentium II, Pentium III, Pentium – IVMicroprocessor.

30Hours

1

III

8086 Microprocessor & Assembly LanguageProgramming

16-bit Microprocessor: Architecture of 8086microprocessor, Register organization, Bus interfaceunit, Execution unit, Memory addressing, Operatingmodes; Instruction sets: Instruction format, Types ofinstructions; Introduction to 8086 family: Procedureand macros, connection, Timing and Troubleshooting,Interrupts.

Programming: Assembly language programmingbased on Intel 8085/8086: Instructions- data transfer,arithmetic, logic, branch operations, looping,counting, indexing, programming techniques,

30Hours

1


24 | 9 1

counters and time delays, stacks, subroutines,Conditional calls and returns instructions;Introduction to Debugging program; Modularprogramming; Structured programming; Top-down;Bottom-up design; MACRO microprogramming.

IV

Peripheral Interfacing

Introduction to Peripheral Devices 8237 4.2 DMAController;8255 programmable peripheral interface;8253/8254 programmable timer/counter; 8259programmable interrupt controller; 8251 USART andRS232C.

30Hours

1


1. Gaonkar, Ramesh S: “Microprocessor Architecture, Programming andApplications with 8085”, Penram International Publishing.

2. Ray A K , Bhurchandi K M : “Advanced Microprocessors and Peripherals”,TMH

3. Hall D V: “Microprocessor Interfacing”, TMH4. Liu and Gibson G A: “Microcomputer System: The 8086/8088 family’’, PHI5. Aditya P Mathur: “Introduction to Microprocessor”, TMH6. Brey, Barry B: “INTEL Microprocessors”, PHI7. Renu Singh & B. P. Singh, “Microprocessor, Interfacing and Applications”, 8.

M Rafiqzzaman, “Microprocessors, Theory and Applications”, Prentice Hall,1992

BCS3503 Computer Networks

Course Objectives:

1. Build an understanding of the fundamental concepts of computer networking.2. To understand the organization of computer networks, factors influencing

computer network development and the reasons for having variety of differenttypes of networks.

3. To apply knowledge of different techniques of error detection and correctionto detect and solve error bit during data transmission.

4. To demonstrate proper placement of different layers of ISO model andilluminate its function.

5. To understand internals of main protocols such as FTP, SMTP, TCP, UDP, IP6. To analyze simple protocols and can independently study literature concerning

computer networks.7. Have a basic knowledge of the use of cryptography and network security.

Learning Outcomes:

At the end of the course, the student should be able to:1. Independently understand basic computer network technology.2. Identify the different types of network topologies and protocols.3. Enumerate the layers of the OSI model and TCP/IP. Explain the function(s) of

each layer.


25 | 9 1

4. Identify the different types of network devices and their functions within anetwork

5. Understand and building the skills of routing mechanisms.6. Analysis the requirements for a given organizational structure and select the

most appropriate networking architecture and technology.

Course Contents:


I

Introduction

Introduction: Network objectives and applications;network structure and architecture; OSI referencemodel; network services; network standardization;examples of network; Physical layer: Fundamentals ofdata communication; transmission media; analogtransmission; digital transmission; switching;ISDN; terminal handling; Broadcast channels andmedium access: LAN protocols.

30Hours

1

II

Data link layer and network layer

Data link layer: Design issues; error detection andcorrections; elementary data link protocols; slidingwindow protocols. Examples; Network layer: Designissues; routing algorithms; congestion control;internetworking. Examples. CSMA with collisiondetection; collision free protocols; IEEE standard 802for LANs; comparison of LANs; Fiber optic networksand FDDI.

30Hours

1

III

Transport, Session and Presentation layer

Transport layer: Design Issues; connectionmanagement; example of a simple transportprotocol. Session layer: Design issues; remoteprocedure call; examples, Presentation layer:Design issues; data compression and encryption;network security and privacy. Examples;

30Hours

1

IV

Application Layer

Application layer: Design issues; File transfer andfile access; electronic mail; virtual terminals; otherapplications, Case study based on available networksoftware.

30Hours

1


1. Andrew S. Tanenbaum “Computer Networks” Prentice Hall of India.2. William Stallings “Local Networks” Maxwell Macmillan International

Edition.


26 | 9 1

3. B.A. Forouzan “Data Communication and Networking”. Tata McGraw Hill.

BCS3504 Automata Theory and Formal Languages

Course Objective:Students will learn several formal mathematical models of computation alongwith their relationships with formal languages. They will learn regularlanguages and content free languages which are crucial to understand howcompilers and programming languages are built. Also students will learn thatnot all problems are solvable by computers and some problems do not admitefficient algorithms. Throughout this course, students will strengthen theirrigorous mathematical reasoning skills.

Learning Outcome:


1. Demonstrate an understanding of abstract models of computing, includingdeterministic (DFA), non deterministic (NFA) and Turing Machine (TM)models.

2. Understand the relative computing power of the different abstract machinemodels.

3. Demonstrate an understanding of regular expression and grammars.4. Understand the associations between language classes and machine models.5. Understand the associations between language classes and language

descriptors.6. Understand decidable and undecidable problems.7. Understand the application of machine models and descriptors to compiler

theory and parsing.

Course Contents:


Credits

I

Introduction to Automata

Introduction, Alphabets, Strings and Languages,Automata and Grammars, Deterministic finiteAutomata (DFA)-Formal Definition- State transitiongraph, Transition table, Language of DFA.

Nondeterministic finite Automata (NFA)-NFA withepsilon transition, Language of NFA, Equivalence ofNFA and DFA, Minimization of Finite Automata,Myhill-Nerode Theorem.

30 Hours 1


27 | 9 1

II

Regular expression

Operators of regular expression and their precedence,Algebraic laws for Regular expressions, Kleen’sTheorem, Regular expression to FA, Application andLimitations of FA, DFA to Regular expression-Arden Theorem, Non Regular Languages, PumpingLemma for regular Languages - Application ofPumping Lemma, Closure and Decision properties ofRegular Languages, FA with output -Moore andMealy machine, Equivalence of Moore and MealyMachine.

30Hours 1

III

Context free grammar and Context FreeLanguages

Definition, Examples, Derivation , Derivation trees,Ambiguity in Grammar, -Inherent ambiguity ,Ambiguous to Unambiguous CFG, Useless symbols,Simplification of CFGs, Normal forms for CFGs:CNF and GNF, Closure and Decision properties ofCFL,

Pumping lemma for CFLs.

Push Down Automata (PDA)-Description andDefinition, Instantaneous description, Language ofPDA Acceptance by Final state, Acceptance byempty stack-Deterministic PDA, Equivalence ofPDA and CFG, CFG to PDA and PDA to CFG ,Twostack PDA.

30 Hours 1

IV

Turing machines (TM):

Basic model, definition and representation,Instantaneous description, Language acceptance byTM, Variants of Turing Machine, Universal TM,TMas computer of integer function, Church’s Thesis,Recursive and recursively enumerable languages.,Halting problem , Introduction to Undecidability -Undecidable problems about TMs, Postcorrespondence problem (PCP), Modified PCP andIntroduction to recursive function theory .

30Hours

1


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

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


28 | 9 1

3. Peter Linz, "An Introduction to Formal Language and Automata", NarosaPublishing house.

4. Y. N. Singh “Mathematical Foundation of Computer Science”, New AgeInternational.

5. Papadimitrou, C. and Lewis, C.L., “Elements of the Theory of Computation”,PHI Learning Private Limited, Delhi India.

6. K. Krithivasan and R. Rama; Introduction to Formal Languages, AutomataTheory and Computation; Pearson Education.

7. Harry R. Lewis and Christos H. Papadimitriou, Elements of the theory ofComputation, Second Edition, Prentice-Hall of India Pvt. Ltd.

8. Micheal Sipser, “Introduction of the Theory and Computation”, ThomsonLearning

BCS3505 Computer Graphics

Course Objective:1. Identify and explain the core concepts of computer graphics.2. To learn various line and circle drawing algorithm.3. To learn the basic principles of 3D Computer graphics.4. Providing an understanding of mapping from world coordinate to device

coordinate, clipping and projection.5. Basic introduction to curves and surfaces.

Learning Outcome:

At the end of the course, the student will be able to:

1. Have a basic understanding of the core concepts of computer graphics.2. To implement various Line and Circle drawing algorithms.3. To describe the importance of viewing and projection.4. Design and implementation of various 2D Clipping algorithm.5. Construct and apply composite transformation.

Course Contents:


Credits

I

INRODUCTION TO COMPUTER GRAPHICS,GRAPHIC DISPLAYS, LINE AND CIRCLEDRAWING ALGORITHM

Introduction to computer graphics, Advantages andapplication of computer graphics, Classification ofcomputer graphics

Graphic displays: Random scan displays, Raster scandisplays, Frame buffer and Video Controller, Linedrawing algorithms: DDA algorithm, Bresenham’salgorithm, Parallel line algorithm, Circle drawingalgorithm: DDA circle drawing algorithm,Bresenham’s circle drawing algorithm , Midpoint

30 Hours 1


29 | 9 1

circle drawing algorithm

II

TRANSFORMATIONS, WINDOWING ANDCLIPPING AND 3-D TRANSFORMATION

Basic transformation: Translation, Rotation, Scaling,Matrix representations, Homogenous coordinates,Composite transformations

Reflections and shearing transformations, ViewingPipeline

Viewing transformations, 2D Clipping algorithms,Cohen Sutherland line clipping algorithm, LiangBarsky algorithm, Line clipping against non-rectangular clip windows, Polygon Clipping,Sutherland Hodgeman polygon clipping, Weiler andAtherton polygon clipping, Curve clipping and Textclipping, 3-D geometric primitives, 3-D Objectrepresentation, 3-D Transformation, 3-D viewing andprojections, 3-D Clipping

30Hours 1

III

Unit 3: CURVES AND SURFACES, HIDDENLINES AND SURFACES AND BASICILLUMINATION MODEL

Introduction to Curves and Surfaces, Quadricsurfaces, Spheres, Ellipsoid, Blobby objects,Introductory concepts of Spline, Bspline and Beziercurves and surfaces, Introduction to Hidden Lines andSurfaces, Back Face Detection algorithm, Depthbuffer method, A- buffer method, Scan line method,basic illumination models

Ambient light, Diffuse illumination, Specularreflection and Phong model, Combined approach,Warn model, Intensity Attenuation, Colourconsideration, Transparency and Shadows

30 Hours 1


1. Donald Hearn and M Pauline Baker, “Computer Graphics C Version”, PearsonEducation

2. Amrendra N Sinha and Arun D Udai, “Computer Graphics”, TMH3. Donald Hearn and M Pauline Baker, “Computer Graphics with OpenGL”,

Pearson education4. Steven Harrington, “Computer Graphics: A Programming Approach”, TMH5. Rogers, “Procedural Elements of Computer Graphics”, McGraw Hill


30 | 9 1

BCS3552 Microprocessor and Interfacing Lab



1. To study 8085 microprocessor System.2. To study 8086 microprocessor System.3. To develop and run a program to find out largest and smallest number.4. To develop and run a program for converting temperature from F to C degree.5. To develop and run a program to compute square root of a given number.6. To develop and run a program for computing ascending/descending order of a

number.7. To perform interfacing of RAM chip to 8085/8086.8. To perform interfacing of keyboard controller.9. To perform interfacing of DMA controller.10. To perform interfacing of UART/USART.11. To develop and run a program to add two 8 bit number.12. To develop and run a program to add two 16 bit number.13. To develop and run a program to subtract two 8 bit number.14. To develop and run a program to multiply two 8 bit number.

BCS3553 Computer Networks Lab

List of Experiments1. Study of different type of Network cables and practically implement the cross

wired cable.2. Study and implementation of basic network command and network

configuration commands.3. Connect the computers in local area network.4. To write a socket program for implementation of echo.5. Write a program in C, to perform character stuffing.6. Write a program in C, to perform Bit stuffing.7. Implement CRC (Cyclic redundancy check) in C.8. Study of Network Simulators like NS2, OPNET.9. Write a program in C, to implement sliding window protocol.10. To create Scenario and Study the performance of Ring topology through

simulation.11. To create Scenario and Study the performance of Bus topology through

simulation.

BCS3555 Computer Graphics Lab

Tools/software used: Turbo C/ OpenGL1. Implementation of DDA line algorithm.2. Implementation of Bresenham’s line algorithm3. Implementation of midpoint circle algorithm4. Implementation of midpoint ellipse algorithm5. Implementation of Two Dimensional transformations - Translation, Rotation,

Scaling, Reflection, Shear.6. Implementation of composite 2D Transformations.7. Cohen Sutherland 2D line clipping and Windowing.


31 | 9 1

8. Sutherland — Hodgeman Polygon clipping Algorithm.9. Three dimensional transformations – Translation, Rotation, Scaling10. Composite 3D transformations.11. Drawing three dimensional objects and Scenes.12. Generating Fractal images

BCS3601 Core Java

Course Objective:

1. Introduction to Java programming and fundamentals of object-Orientedprogramming, including defining classes, Invoking methods, using Clan-Libraues etc.

2. Understanding the basic of polymorphism through use of super classes andinterface.

3. Understand fundamental of programming such as reusable conditional anditerative execution etc.

4. Learn the essentials of the Java class library, and learn how to learn aboutother parts of the library when you need them.

5. Introduce event driven Graphical User Interface (GUI) programming.6. Understand now to handle exception, implement check and unchecked

exceptions.7. Understand the user of input and output objects.8. To develop interaction use interfaces using Java swing class.

Learning Outcome:


1. Understand the basic concepts of OOPs.2. Understand the concepts of inheritance, polymorphism.3. Understand the concepts of swing.4. Student will be able to develop interaction page java swing java.

Course Contents:


Credits

I

INTRODUCTION TO CORE JAVAPROGRAMMING

History and evolution, Features of java environment,Difference from C and C++, The java architecture,Java Development Kit, Types of java programs, Asample java program, Compilation and Execution,

Variable Declaration, Data types in java, Java Tokens,

Variable Declaration, Type casting and conversion,Arrays, Operators in java, Operators-Introduction,Operator Precedence, Control Statements, Introductionto classes, Instance Variables, Class Variables,Instances Methods, Constructors, Declaring Object,Garbage collection, Method Overloading, Constructor

30Hours

1


32 | 9 1

Overloading, this reference, Using objects in methods,Recursion, Access modifiers, Inner class.

II

INHERITANCE, ABSTRACT CLASSES ANDINERFACES, EXCEPTION HANDLING ANDMULTITHRAEDED PROGRAMMING

Inheritance, Super class variables and subclassObjects, The super reference, Constructor chaining,Method overriding, The final keyword, AbstractClasses and Interfaces, The abstract classes, Theabstract methods, Defining interface, Implementinginterface, Extending interface, Interface References,Exception handling, Hierarchy of exception classes,Types of exception, Exception classes, Uncaughtexceptions, Handling Exception, User definedException ,Multithreaded Programming, The javaThread model, The runnable interface, The threadclass, Thread creation, Thread’s Life cycle, Threadscheduling, Synchronization and Deadlock, Inter-thread communication, Joining threads, Suspending,resuming and stopping threads

30Hours

1

III

PACKAGES AND ACCESS MODIFIERS,HANDLING STRING, INPUT OUTPUTCLASSES

Packages and access modifier, Recommended packagenaming convention, The Package Declaration, TheCLASSPATH variable, The import statement, The javalanguage packages , Importance of Package Design ,Access Protection, Handling strings, Create Strings,Operations on strings, Character Extraction method,String comparison method, Searching and modifyingstrings, Data conversions and ValueOf( ) methods,string buffer and to methods, Changing case ofcharacters, The StringBuffer classes, Wrapper classes,Input and output classes, Hierarchy of classes in java.iopackage, File classes, InputStream and OutputStreamclasses , FilterInputStream andFilterOutputStreamClasses, Reader and writer classes,Basics of networking , Java’s Networking protocol

Hierarchy of classes in java.net package, Connectionoriented protocol classes.

30Hours

1

IV

AWT, LAYOUT MANAGEMENT AND EVENTHANDLING, SWING.

Applet Life Cycle, Running Applets, Methods ofApplet class, Graphics class, color class, font class,Limitation of applets, Interfaces of java. applet

30Hours

1


33 | 9 1

package AWT Classes, Hierarchy of classes injava.awt package, Component Classes, ContainerClasses, Frame Window in an Applet, Menus Layoutmanagement and event handling , Standard layoutmanagers, Handling events, Event classes , EventListener interface , Adapter classes, The Swing and theAWT, Swing packages, Structure of swing application,Top-Level swing containers, Lightweight swingcontainer, JComponent Classes, Basic swingcomponents, Swing Text Components


1. Patrick Naughton and HerbertzSchildt, “Java-2: The Complete Reference”,TMH, 1999.

2. Bill Vanners, “Inside Java Virtual Machine”, TMH, 2nd Ed.3. Rick Dranell, “HTML 4 unleashed”, Techmedia Publication, 20004. Shelley Powers, “Dynamic Web Publishing”, 2nd Ed., Techmedia, 1998.5. Paul Dietel and Harvey Deitel, “Java How to Program”, PHI, 8th Ed., 20106. E. Balaguruswamy, “Programming with Java: A Primer”, TMH, 1998.

BCS3602 Design & Analysis of Algorithm

Course Objective:1. Analyze the asymptotic performance of algorithms.2. Write rigorous correctness proofs for algorithms.3. Demonstrate a familiarity with major algorithms and data structures.4. Apply important algorithmic design paradigms and methods of analysis.5. Synthesize efficient algorithms in common engineering design situations

Learning Outcome:


1. Argue the correctness of algorithms using inductive proofs and invariants.2. Analyze worst-case running times of algorithms using asymptotic analysis.3. Describe the divide-and-conquer paradigm and explain when an

algorithmic design situation calls for it. Recite algorithms that employ thisparadigm. Synthesize divide-and-conquer algorithms. Derive and solverecurrences describing the performance of divide-and-conquer algorithms.

4. Describe the dynamic-programming paradigm and explain when analgorithmic design situation calls for it. Recite algorithms that employ thisparadigm. Synthesize dynamic-programming algorithms, and analyzethem.

5. Describe the greedy paradigm and explain when an algorithmic designsituation calls for it. Recite algorithms that employ this paradigm.Synthesize greedy algorithms, and analyze them.

6. Explain the major graph algorithms and their analyses. Employ graphs tomodel engineering problems, when appropriate. Synthesize new graphalgorithms and algorithms that employ graph computations as keycomponents, and analyze them.


34 | 9 1

7. Explain the different ways to analyze randomized algorithms (expectedrunning time, probability of error). Recite algorithms that employrandomization. Explain the difference between a randomized algorithmand an algorithm with probabilistic inputs.

8. Explain what amortized running time is and what it is good for. Describethe different methods of amortized analysis (aggregate analysis,accounting, and potential method). Perform amortized analysis.

Course Contents:


I

Introduction and Advanced Data Structure

Notion of Algorithm, Analysis of algorithms,Designing of Algorithms, Growth of Functions,Master's TheoremAsymptotic Notations and Basic Efficiency Classes,Shorting and Searching Algorithm: Insertion SortSelection Sort and Bubble SortDivide and conquer - Merge sort , Quick Sort, HeapSort, Sequential Search and Binary SearchBinary Search Tree and AVL tree: Traversal andRelated Properties, Binomial Heaps, FibonacciHeaps; Data Stricture for Disjoint Sets

30Hours

1

II

Advanced Design and Analysis Techniques

Dynamic Programming: Matrix chain multiplicationProblem, Optimal Binary search tree etc., GreedyAlgorithms; Amortized Analysis

30Hours

1

III

Graph Algorithms

Graph Algorithms: Elementary Graphs Algorithms,Depth first Search and Breadth First Search,Minimum Spanning Trees, Shortest paths problemSingle-source Shortest Paths, All-Pairs Shortest PathsMaximum Flow and Flow networks, Back Tracking

30Hours

1

IV

Selected Topics

Randomized Algorithms, String Matching, TravellingSalesman Problem, NP Completeness ,Approximation Algorithms

30Hours

1


1. Thomas H Cormen, Charles E Lieserson, Ronald L Rivest and Clifford Stein,“Introduction to Algorithms”, Second Edition, MIT Press/McGraw-Hill, 2001.

2. Jon Kleinberg and ÉvaTardos, “Algorithm Design”, Pearson, 2005.


35 | 9 1

3. Michael T Goodrich and Roberto Tamassia, “Algorithm Design: Foundations,Analysis”, and Internet Examples, Second Edition, Wiley, 2006

BCS3603 Advanced Computer Architecture

Course Objective:

1. Provide in-depth coverage of current and emerging trends in computerarchitectures, focusing on performance and the hardware/software interface.

2. The course emphasis is on analyzing fundamental issues in architecture designand their impact on application performance.

3. Understand the concept of parallel processing and its application.4. Analyse the performance of different scalar computers.5. Distinguish the performance of pipeline and non pipelining environment in

processor.

Learning Outcome:

At the end of the course, the student should be able to:1. Understand advanced issues in design of computer processors, caches, and

memory.2. Analyze performance trade-offs in computer design.3. Apply knowledge of processor design to improve performance in algorithms

and software systems.4. Acquire experience with tools for statistical analysis of instruction set trade-

offs.5. Implement the concept of parallel processing and its application.6. To be able to describe the challenges faced in the implementation of this high

performance system.

Course Contents:


Credits

I

Introduction

Introduction Parallel Computing, Parallel ComputerModel, Program and Network Properties, ParallelArchitectural Classification Schemes. Flynn’s & Feng’sClassification. Performance Metrics and Measures,Multiprocessor System and Interconnection Networks.Speedup Performance Laws.

30Hours

1

II

Pipelining and Memory Hierarchy

Basic and Intermediate Concepts: Instruction SetPrinciple, ILP: Basics, Exploiting ILP, Limits on ILP.Linear and Nonlinear Pipeline Processors, Super Scalarand Super Pipeline Design. Memory Hierarchy Design,Advanced Optimization of Cache Performance,Memory Technology and Optimization, CacheCoherence and Synchronization Mechanisms.

30Hours

1


36 | 9 1

III

Thread and Process Level Parallel Architecture

Introduction to MIMD Architecture, MultithreadedArchitectures, Clustering, Instruction Level DataParallel Architecture. SIMD Architecture, Associativeand Neural Architecture, Data Parallel Pipelined,Systolic Architectures, Vector Architectures, ParallelAlgorithms: Parallel Reduction, Prefix Sums, Pre-orderTree Traversal, Merging two Sorted lists; MatrixMultiplication: Row Column Oriented Algorithms,Parallel Algorithm Design Strategies.

30Hours

1


1. Kai Hwang,” Advance Computer Architecture”, TMH2. Matthew, ”Beginning Linux Programming”, SPD/WROX3. Hennessy and Patterson, “Computer Architecture: A Quantitative Approach”,

Elsevier4. Dezso and Sima, “Advanced Computer Architecture”, Pearson5. Quinn, “Parallel Computing: Theory & Practice”, TMH6. Quinn, “Parallel Programming in C with MPI and Open MP”, TMH7. Open MP Specification and Usage (www.openmp.org)

BCS3604 Compiler Design

Course Objective:

1. The aim of this module is to show how to apply the theory of languagetranslation introduced in the prerequisite courses to build compilers andinterpreters.

2. It covers the building of translators both from scratch and using compilergenerators.

3. In the process, the module also identifies and explores the main issues of thedesign of translators.

4. The construction of a compiler/interpreter for a small language is a necessarycomponent of this module, so students can obtain the necessary skills.

Learning Outcome:

At the end of the course, the student should be able to:1. Understand the structure of compilers.2. Understand the basic techniques used in compiler construction such as lexical

analysis, top-down, bottom-up parsing, context-sensitive analysis, andintermediate code generation.

3. Understand the basic data structures used in compiler construction such asabstract syntax trees, symbol tables, three-address code, and stack machines


37 | 9 1

Course Contents:


I

Introduction to CompilerIntroduction-Compiler and features, Analysis –Synthesis model, Phases of compiler, Grouping ofPhase, Concept of pass, Bootstrapping. Lexicalanalyzer-Implementation and Role of lexicalanalyzer, Token, Pattern and Lexemes and function,Finite state machine and Regular expression. Formalgrammar and their application to syntax analysis-CFG, derivation and Parse treesBasics Parsing Techniques –I: Top-Down Parser-Back tracking, Predictive Parser

30Hours

1

II

Basic parsing techniques-II: Bottom –Up ParserShift –Reduce Parser, Operator Precedence parsing,Recursive descent parsing, LR Parser-LR(0) Parser ,SLR parser , Canonical LR Parser, LALR Parser.Syntax-Directed Translation-Syntax Directeddefinition and type, Construction of Syntax Tree andDAG representation. Symbols Table- StorageAllocation strategies, Runtime Storage Organization,Structure Storage Allocation, Error detection andRecovery-Lexical, syntax and semantic error.

30Hours

1

III

Intermediate code GeneratorIntermediate code- forms of intermediate code,Implementation of 3-address code- Quadruple, directand triple, Translation of Assignment statements,Translation of Boolean expression- Flow of ControlStatement, and Case statements. Code Generation-Design issues, The Target code and addresses intarget code, Code generator algorithm.

30Hours

1

IV

Code OptimizationMachine-independent optimization, Basic Blocks,Flow graph- DAG representation of basic blocks,Loop in Flow graph .Transformation, LoopOptimization ,Peephole Optimization, Global DataFlow-Control Flow Analysis, Data Flow Analysis

30Hours

1


1. Aho, Sethi& Ullman, “Compilers: Principles, Techniques and Tools”, PearsonEducation

2. V Raghvan, “Principles of Compiler Design”, TMH3. Kenneth Louden, “Compiler Construction”, Cengage Learning.


38 | 9 1

4. 4.. Charles Fischer and Ricard LeBlanc, “Crafting a Compiler with C”,Pearson Education

Generic Elective-I

GE33211 Multimedia Systems

Course Objective:

1. The aim of the course is that to acquaint a student with number concepts aboutthe signal processing exploited in the field of multimedia applications.

2. Some basic tools, such as Fourier and Cosine transforms, are presented.3. Nyquist's theorem and a short introduction to digital filter design and usage.4. The general notion of waveform is introduced and discussed along with a

short presentation of typical filter arrangements: low-band, high-band, pass-band, etc...

5. Different color models are also discussed and the concepts of Chrominance,Luma and Luminance are introduced within the general mechanism of humanvision system.

6. The most popular compression algorithms are widely discussed as well asaudio systems such as MIDI, MPEG and MPEG4.

7. The JPEG compression is presented as an instance of the so called DiscreteCosine Transform even if the complete compression cycle is built on theentropy-based compression algorithms.

Learning Outcome:

By studying this course, students will be able to

1. Be familiar with multimedia data types and the conversion between analogueand digital forms.

2. Understand the characteristics of different media; understand therepresentations of different multimedia data; understand different dataformats; be able to take into considerations in multimedia system designs;

3. Understand the characteristics of human’s visual system; understand thecharacteristics of human’s audio system; be able to take into considerations inmultimedia techniques design and implementation;

4. Understand different compression principles; understand differentcompression techniques; understand different multimedia compressionstandards; be able to design and develop multimedia systems according to therequirements of multimedia applications.

Course Contents:


Credits

I

Introduction

Introduction: What is multimedia? Defining the scopeof multimedia. Applications of multimedia, hardwareand software requirements, multimedia database.

30Hours

1


39 | 9 1

II

Digital representation

Digital representation: Introduction, Analogrepresentation, waves, digital representation, needfor digital representation, A to D conversion, D to Aconversion, relation between sampling rate and bitdepth, Quantization error, Fourier representation,pulse modulation. Importance and drawback ofdigital representation.

30Hours

1

III

Text ,Image, Audio and Video

Text and Image: Introduction, Types of text, Font,insertion, compression, File formats. Types ofimages, color models, Basic steps for imageprocessing, principle and working of scanner anddigital camera, Gamma and gamma correction.

Audio and Video technology: Fundamentalcharacteristics of sound, psycho- acoustics, Rasterscanning principles, sensors for TV cameras, colorfundamentals, additive and subtractive colormixing, Liquid crystal display (LCD), PlasmaDisplay, Panel (PDP), file formats

30Hours

1

IV

Compression and use of authoring tools

Compression and coding: What is compression?Need for compression, Types of compression- basiccompression techniques-run length, Huffman’scoding, JPEG, zip coding. Overview of Image andVideo compression techniques. Multimediapresentation and authoring: Overview, multimediaauthoring metaphor, multimedia production,presentation and automatic authoring, Designparadigms and user interface, Overview of tools likeAdobe Premier, Director, Flash and Dreamweaver.

30Hours

1


1. “Data Compression” – David Salomon, Springer Publication, 4th

Edition.2. “Introduction to Data Compression” – Khalid Sayood, Morgan Kaufmann

Series, 3rd

Edition

GE33212 Soft Computing

Course Objective:

1. Learn the basic concept of fuzzy set theory.2. Understand the working principle of various AI techniques and heuristic

search algorithms.


40 | 9 1

3. Learn about the architecture of artificial neural networks and implement themin fuzzy environment.

4. Study the concept behind genetic algorithm and its various operations.5. Learn different levels of CPN Networks and ART algorithms.

Learning Outcome:


1. Implement numerical methods in soft computing.2. Design the algorithms which can work as an intelligent production system.3. Demonstrate various learning methods in artificial neural networks, like:

supervised and unsupervised learning.4. Familiar about the various mutation and cross over techniques of genetic

algorithm for producing new strings.5. Design and Implement different predicate logic rules for solving any specific

AI problem.

Course Contents:


I

Artificial Intelligence

Soft Computing; Introduction of soft computing, softcomputing vs. hard computing, various types of softcomputing techniques; Artificial neural networks,Fuzzy logic, Genetic Algorithms. Applications of softcomputing. Artificial Intelligence; Introduction of AI.Production systems; Types of production systems,Characteristics of production systems. SearchAlgorithms; Breadth first search, Depth first search.Heuristic Search Algorithms; Hill Climbing, Best firstSearch, A* algorithm, AO* Algorithms. Knowledgerepresentation issues. Prepositional and predicatelogic. Forward Reasoning and backward reasoning.Weak & Strong Slot & filler structures. NaturalLanguage Processing (NLP).

30Hours

1

II

Neural networks

Structure of Biological neuron; Neuron, NerveStructure and synapse. Artificial Neuron and itsmodel. Activation functions. Neural networkarchitecture; Single layer feed forward networks,multilayer feed forward networks, Recurrentnetworks. Various learning techniques; Perceptrontraining algorithm; Linear separability, Widrow &Hebb’s learning rule/Delta rule. ADALINE v/sMADALINE. Introduction of MLP and BPN. Error

30Hours

1


41 | 9 1

back propagation algorithm (EBPA); Characteristicsand application of EBPA, momentum factor andlimitation of EBPA. Difference between ANN andhuman brain. Characteristics and applications ofANN. Associative Memory and its characteristics.Counter propagation network (CPN); Architecture ofCPN, functioning & characteristics of CPN. Hopfield/Recurrent network. Hopfield v/s Boltzman machine.Adaptive Resonance Theory (ART); Architecture ofART, Classification and training of ART.

III

Fuzzy logic

Basic concepts of fuzzy logic. Fuzzy sets versus Crispsets. Fuzzy set theory and operations. Properties offuzzy sets and crisp sets. Fuzzy relations and Crisprelations. Fuzzy to Crisp conversion. Membershipfunctions. Fuzzyfications & Defuzzifications. Fuzzypreposition. Fuzzy inference System. Fuzzy RuleBase. Fuzzy reasoning and decision making. FuzzyLogic Controller (FLC). Formation, decomposition &aggregation of fuzzy rules. Industrial applications ofFuzzy.

30Hours

1

IV

Genetic Algorithm(GA)

Introduction of Genetic Algorithm; Fundamentals ofGA, Basic concepts of GA, Working principle,Encoding, fitness function,

Reproduction. Genetic modeling; Inheritanceoperator, Cross over Operators, Inversion & deletion,Mutation operator, Bitwise operators. GenerationalCycle of GA. Convergence of GA. Applications &advances in GA. Differences& similarities betweenGA & other traditional methods.

30Hours

1


1. S. Rajsekaran & G.A. Vijayalakshmi Pai, “Neural Networks, Fuzzy Logic andGenetic Algorithm: Synthesis and Applications” Prentice Hall of India.

2. Sivanandani, Deepa, “Principles of Soft Computing”, Wiley India (2007)3. Jang J.S.R. Sun C.T. and Mizutani E., “Neuro-Fuzzy and Soft computing”,

Prentice Hall4. Timothy J. Ross. “Fuzzy Logic with Engineering Applications”, McGraw Hill5. Laurene Fausett. ‘Fundamentals of Neural Networks”, Prentice Hall


42 | 9 1

6. D.E. Goldbery, “Genetic Algorithms: Search, Optimization and MachineLearning”. Addison Wesley.

GE33213 Evolutionary Algorithms

Course Objective:

1. How to solve hard problems without using complex mathematicalformulations

2. Design algorithms that are robust yet easy to program3. To solve optimization related problems efficiently.

Learning Outcome:

Upon completion of this course, students will be able to:1. Explain the principles underlying Evolutionary Computation in general and

Genetic Algorithms in particular.2. Apply Evolutionary Computation Methods to find solutions to complex

problems3. Analyze and experiment with parameter choices in the use of Evolutionary

Computation4. Summarize current research in Genetic Algorithms and Evolutionary

Computing

Course Contents:


Credits

I

Introduction to Evolutionary Computation,Biological Background: Principles of Darwiniannatural selection, Historical Development of EC,Genetic Algorithms, Genetic Programming,Evolutionary Strategies and EvolutionaryProgramming, Features of Evolutionary Computation,Advantages of Evolutionary Computation

Applications of Evolutionary Computation.

30Hours

1

II

Genetic Algorithms: Overview of ConventionalOptimization and Search Techniques, Simple GeneticAlgorithm, terminology: Individual, Genes, Fitness,Population, Encoding, Breeding, Termination,Comparison with Other Optimization , TechniquesGA in search, optimization, and machine learning.Case Study of Travelling Salesman Problem

30Hours

1

III

Evolutionary Strategies: Introduction, Comparisonwith GA & GP Operators: Gaussian MutationOperator and Intermediate Recombination Operator.Application of ES for Image Enhancement

30Hours

1

IVFoundations of Evolutionary Algorithms , Schemasand the two-armed bandit problem, Advantages and

30Hours

1


43 | 9 1

disadvantages of evolutionary algorithms overalternative methods. Co-evolutionary Algorithms:Cooperative co-evolution, Competitive co-evolution,Swarm intelligence and ant colony optimization.


1. Sivanandam, Deepa “Introduction to Genetic Algorithm”, Springer.2. Melanie Mitchell: “An Introduction to Genetic Algorithm”, Prentice Hall of

India.3. D. E. Goldberg, “Genetic Algorithms in Search, Optimisation and Machine

Learning”, Addison-Wesley.4. Zbigniew Michalewics, “Genetic Algorithms + Data Structures = Evolution

Programs”, Springer Verlag, 1997.5. Goldberg, “Genetic Algorithms”, Pearson Eduction.6. T. Back, D. B. Fogel and Michalewicz, “Evolutionary Computation1: Basic

Algorithms and Operators”, 2000.

GE33214 Distributed Database System

Course Objective:

1. Learn to manage large volume of shared data2. To understand fundamental concepts in a parallel environment.3. To implement large database in a distributed environment.4. To provide insight into related research problems.5. Techniques to learn distributed database design.

Learning Outcome:


1. Explain the techniques used for data fragmentation, replication, and allocationduring the distributed database design.

2. Evaluate simple strategies for executing a distributed query to select thestrategy that minimizes the amount of data transfer.

3. Explain how the two phase commit protocol is used to deal with committing atransaction that accesses databases stored on multiple nodes.

4. Describe distributed concurrency control based on the distinguished copytechniques and the voting methods.

Course Contents:


Credits

I

INTRODUCTION: Distributed data processing,What is a DDBS?, Advantages and disadvantages ofDDBS, Problem areas, Overview of database andcomputer network conceptsDISTRIBUTED DATABASE MANAGEMENTSYSTE ARCHITECTURE: Transparencies in a

30 Hours 1


44 | 9 1

distributed DBMS, Distributed DBMS architecture,Global directory issues

II

DISTRIBUTED DATABASE DESIGN:Alternative design strategies, Distributed designissues, Fragmentation, Data allocationTRANSACTION MANAGEMENT: Thetransaction concept, Goals of transactionmanagement, Characteristics of transactions,Taxonomy of transaction modelsCONCURRENCY CONTROL: Concurrencycontrol in centralized database systems, Concurrencycontrol in DDBSs, Distributed concurrency controlalgorithms, Deadlock management

30Hours 1

III

SEMANTICS DATA CONTROL: Viewmanagement, Data security, Semantic IntegrityControlQUERY PROCESSING ISSUES: Objectives ofquery processing, Characterization of queryprocessors, Layers of query processing, Querydecomposition, Localization of distributed dataDISTRIBUTED QUERY OPTIMIZATION:Factors governing query optimization, Centralizedquery optimization, Ordering of fragment queries,Distributed query optimization algorithms

30 Hours 1

IV

RELIABILITY: Reliability issues in DDBSs, Typesof failures, Reliability techniques, Commit protocols,Recovery protocolsPARALLEL DATABASE SYSTEMS: Parallelarchitectures, Parallel query processing andoptimization, Load balancingADVANCED TOPICS : Mobile Databases,Distributed Object Management, Multi-databases

30 Hours 1

Text/Reference Books:1. Principles of Distributed Database Systems, M.T. Ozsu and P. Valduriez,

Prentice-Hall, 1991. (Required).2. Distributed Database Systems, D. Bell and J. Grimson, Addison-Wesley,

1992. (Referenced).3. Distributed Database Management Systems: A Practical Approach by Saeed

K. Rahimi (Author), Frank S. Haug.

GE33215 Internet of ThingsCourse Objective:

1. To assess the vision and introduction of IoT.2. To Understand IoT Market perspective.


45 | 9 1

3. To Implement Data and Knowledge Management and use of Devices in IoTTechnology.

4. To Understand State of the Art - IoT Architecture.5. To classify Real World IoT Design Constraints, Industrial Automation in IoT.

Learning Outcome:1. Interpret the vision of IoT from a global context.2. Determine the Market perspective of IoT.3. Compare and Contrast the use of Devices, Gateways and Data Management in

IoT.4. Implement state of the art architecture in IoT.5. Illustrate the application of IoT in Industrial Automation and identify Real

World Design Constraints.

Course Contents:


Credits

I

OverviewAn Architectural Overview– Building an architecture,Main design principles and needed capabilities, AnIoT architecture outline, standards considerations.M2M and IoT Technology Fundamentals- Devicesand gateways, Local and wide area networking, Datamanagement, Business processes in IoT, Everythingas a Service (XaaS), M2M and IoT Analytics,Knowledge Management.

30Hours

1

II

Reference ArchitectureIoT Architecture-State of the Art – Introduction, Stateof the art, Reference Model and architecture, IoTreference Model - IoT Reference ArchitectureIntroduction, Functional View, Information View,Deployment and Operational View, Other Relevantarchitectural views. Real-World Design Constraints-Introduction, Technical Design constraints-hardwareis popular again, Data representation andvisualization, Interaction and remote control.

30Hours

1

III

Iot Data Link Layer & Network Layer ProtocolsPHY/MAC Layer(3GPP MTC, IEEE 802.11, IEEE802.15), WirelessHART,Z-Wave,Bluetooth LowEnergy, Zigbee Smart Energy, DASH7 - NetworkLayer-IPv4, IPv6, 6LoWPAN, 6TiSCH,ND, DHCP,ICMP, RPL, CORPL, CARP.

30Hours

1

IV

Transport Layer , Session Layer And ServiceLayer Protocols & Security Transport Layer (TCP,MPTCP, UDP, DCCP, SCTP)-(TLS, DTLS) –Session Layer-HTTP, CoAP, XMPP, AMQP, MQTT,

30Hours

1


46 | 9 1

Service Layer -oneM2M, ETSI M2M, OMA, BBF –Security in IoT Protocols – MAC 802.15.4 ,6LoWPAN, RPL, Application Layer

Text/Reference Books:1. Samuel Greengard , “TheInternet of Things” .2. Klaus Schwab, “The Fourth Industrial Revolution”.1. CunoPfister,“Getting started with Internet of Things”.3. Peter Waher, “Learning Internet of Things”.

BCS3651 Java Lab

Implement Following Programs in Lab

1. Write a program to print ―Hello Worldǁ on the screen.2. Write a program that calculates how long it takes to drive from New York to

Los Angeles at 75 mile per hour (Use 3000 miles as the approximate distancebetween two cities).

3. Write a program that creates and initializes a four-element int array. Calculateand display the average of its values

4. Write a program to swap two values using object reference.5. WAP that describes a class person. It should have instance variables to record

name, age and salary. Create a person object. Set and display its instancevariables.

6. WAP that creates a class circle with instance variables for the Centre and theradius. Initialize and display its variables.

7. Modify experiment 1 to have a constructor in class circle to initialize itsvariables.

8. Modify experiment 2 to show constructor overloading.9. WAP to display the use of this keyword.10. WAP that implements method overloading.11. WAP that shows passing object as parameter.12. WAP that illustrates method overriding.13. WAP to illustrate simple inheritance14. WAP illustrating all uses of super keywords.15. Create an abstract class shape. Let rectangle and triangle inherit this shape

class. Add necessary functions.16. Write an application that creates a package P1. Add some classes in it. Write

an application that uses the package p1 created in the program17. Write an application that creates an i̳nterface‘ and implements it.18. Write an application to illustrate Interface Inheritance.19. Write an application that shows the usage of try, catch, throws and finally.20. Write an application that shows how to create a user-defined exception21. Write an application that executes two threads. One thread displays ―An‖

every 1000 milliseconds and other displays ―Bǁ every 3000 milliseconds.Create the threads by extending the Thread class.31. Write an application thatshows thread synchronization.

22. Write an application that displays deadlock between threads.23. Write an application that shows thread priorities.


47 | 9 1

24. Write an Applet that displays ―Hello World‖ (Background color-black, textcolor-blue and your name in the status window.)

25. Write a program that displays the life cycle of an Applet.26. Write an Applet displaying line, rectangle, rounded rectangle, filled rectangle,

filled rounded rectangle, circle, ellipse, arc, filled arc and polygon, all indifferent colors.

27. Write an Applet that illustrates how to process mouse click, enter, exit,press and release events. The background color changes when the mouseis entered, clicked, pressed, released or exited.

BCS3652 Algorithms Lab

Programming assignments on each algorithmic strategy:

1. Divide and conquer method (quick sort, merge sort, Strassen’s matrixmultiplication),

2. Greedy method (knapsack problem, job sequencing, optimal merge patterns,minimal spanning trees).

3. Dynamic programming (multistage graphs, OBST, 0/1 knapsack, travelingsalesperson problem).

4. Back tracking (n-queens problem, graph coloring problem, Hamiltoniancycles).

5. Sorting : Insertion sort, Heap sort, Bubble sort6. Searching : Sequential and Binary Search7. Selection : Minimum/ Maximum, K-th smallest element

BCS3701 Artificial Intelligence

Course Objective:

1. To have an understanding of the achievements of AI.2. To have an appreciation for the engineering issues underlying the design

of AI systems.3. To have a basic proficiency in a traditional AI language4. To have an understanding of the basic issues of knowledge representation5. For understanding the concept of blind and heuristic search,6. Understanding of min-max and resolution concept of AI.

Learning Outcome:


1. Write simple to intermediate programs written in LISP/PROLOG.2. To understand code written in above language.3. To implement AI topics such as learning, natural language processing.4. Understand and Design agents and robotics, expert systems.

Course Contents:


Credits

IIntroduction to Artificial Intelligence, Simulation ofSophisticated & Intelligent Behavior, Problem

30Hours

1


48 | 9 1

solving in games, Natural language, Automatedreasoning , Visual Perception, Heuristic algorithmversus solution guaranteed algorithms.

II

First order predicate calculus, Horn Clauses,Semantic Nets, Partitioned Nets, Minskey framesKnowledge Sources Expert, Knowledge Acquisition,Knowledge Representation, Knowledge Base,Production Rules Knowledge Base, InterferenceStrategies, Forward and Backward Chaining

30Hours

1

IIIExpert System : Existing Systems (DENDRAL,MYCIN), Domain exploration, Meta Knowledge,Expertise Transfer, Self Explaining System

30Hours

1

IV

Introduction to pattern Recognition, StructuredDescription, Symbolic Description, Machineperception, Line Finding, Interception, SemanticModelObject Identification, Speech Recognition,Programming Language: Introduction toprogramming Language LISP, Introduction toprogramming Language PROLOG

30Hours

1


1. Russell and Norvig “Artificial Intelligence: A Modern Approach”, 2nd edition,Prentice Hall.

2. Robert Wilensky “LISPcraft”, W.W. Norton. Software Allegro Common Lisp.3. Charnick “Introduction to Artificial Intelligence.” Addision Wesley4. Rich & Knight, “Artificial Intelligence”.5. Winston, “LISP”, Addison Wesley

BCS3702 Network Security and Cryptography

Course Objective:

1. Have a fundamental understanding of the objectives of cryptography andnetwork security

2. Getting familiar with the cryptographic techniques that provide informationand network security

3. To know the different types of algorithms of exchanging information in asecret way.

4. To know the possible threats which can breach the secure communication

Learning Outcome:


1. Understanding cryptography and network security concepts and applications2. Apply security principals to system design and Real time Scenarios.3. Identify and investigate network security threats4. Analysis of network traffic and security threats


49 | 9 1

Course Contents:


I

Introduction to Cryptography and SymmetricCiphersSecurity Attacks: Security Services and mechanism;Classical encryption techniques: Substitution ciphersand Transposition ciphers, Steganography,Cryptanalysis;Modern Block Ciphers: Stream and Block Cipher,Block Cipher Principles, Block Cipher Modes ofOperations; Shannon’s theory of Confusion andDiffusion; Fiestal structure; Data encryptionstandard(DES); Strength of DES; Idea of differentialcryptanalysis; Triple DES; Symmetric KeyDistribution; Finite Fields: Introduction to groups,rings and fields, Modular Arithmetic, EuclideanAlgorithm, Finite Fields of the form GF(p).

30Hours

1

II

Basics of Number Theory and Public keyCryptographyIntroduction to Number Theory: Prime and RelativePrime Numbers, Fermat’s and Euler’s theorem,Testing for Primality, Chinese Remainder theorem,Discrete Logarithms; Public Key Cryptography:Principles of Public-Key Cryptography, RSAAlgorithm, Security of RSA; Key Management:Deffie-Hellman Key Exchange.

30Hours

1

III

Hash Functions and Digital SignaturesMessage Authentication; Hash Functions; SecureHash Functions; Security of Hash functions andMACs; Digital Signatures; Digital SignatureStandards (DSS); Proof of digital signature algorithm;Advanced Encryption Standard (AES) encryption anddecryption.

30Hours

1

IV

Network and System Security

Authentication Applications: Kerberos, X.509Certificates; Electronic Mail Security: Pretty GoodPrivacy, S/MIME; IP Security: IP SecurityArchitecture, Authentication Header, Encapsulatingsecurity payloads, Combining Security Associations;Web Security: Secure Socket Layer and TransportLayer Security, Secure Electronic transaction;Intruder; Viruses; Firewalls.

30Hours

1


1. William Stallings, “Cryptography and Network Security: Principals andPractice”, Pearson Education.


50 | 9 1

2. Behrouz A. Frouzan: “Cryptography and Network Security”, Tata McGraw-Hill

3. Bruce Schiener, “Applied Cryptography”. John Wiley & Sons4. Bernard Menezes, “Network Security and Cryptography”, Cengage Learning.5. Atul Kahate, “Cryptography and Network Security”, Tata McGraw-Hill

Generic Elective II

GE33221 System Programming & System Administration

Course Objective:

1. To explain the basic operations that are performed from the time a computer isturned on until a user is able to execute programs.

2. To work effectively in a UNIX-style environment.3. To provide you with a basic understanding of the issues involved in writing

system programs, manipulating system processes, system I/O, systempermissions, files, directories, signals, threads, sockets, terminal, etc.

4. To operate in and self-manage in programming teams.5. Design and implement programs making direct use of operating system

facilities to perform low- level file I/O and directory manipulations

Learning Outcomes:


1. Access the UNIX system and perform basic operations, including using helpfeatures.

2. Access and manipulate files and directories, including basic and advanceddirectory and file

3. Use file system utilities.4. Troubleshoot system processes.5. Perform environment customization.

Course Contents:


Credits

I

Introduction to System Programming

Evolution of Components Systems Programming,Assemblers, Loaders, Linkers, Macros, Compilers.Software tools: Text editors, Interpreters and programgenerators, Debug Monitors; Compiler: Brief overviewof compilation process, Incremental compiler;Assembler : single phase and two phase assembler,symbol table; Loader : Loader schemes, compile and goLoader, general loader schemes, absolute loader,Subroutine linkage, Reallocating loader, Direct linkageLoader, Binders, Linking loader; Macros :Macrolanguage and macro-processor, macro instructions,

30 Hours 1


51 | 9 1

features of macro facility, macro instruction arguments,conditional macro expansion, macro calls with macroinstruction defining macros.

II

Concept of UNIX Operating System

Basic Features Of Operating System, CPU scheduling;Memory Management: Swapping, and demand paging;File system; Getting Started with UNIX: User namesand groups, logging in, Format of UNIX commands,Changing your password;, Characters0with specialmeaning; UNIX documentation.

30 Hours 1

III

Files and directories: Directories, Current directory,looking at the directory contents, Absolute and relativepathnames, Some UNIX directories and files;

Files: Looking at the file contents; File permissions,Basic operation on files, changing permission modes;Standard files, standard output; Standard input, Standarderror; filters and pipelines.

Processes: Finding out about processes; Stoppingbackground process; UNIX editor vi, Test Manipulation,Inspecting files, File statistics, Searching for patterns,Comparing files, Operating on files, Printing files,Rearranging files, Sorting files, Splitting files,Translating characters, AWK utility.

30 Hours 1

IV

Shell programming and System Administration:Shell programming, Programming in the Borne and C-Shell, Wild cards, Simple shell programs, Shellvariables, Shell programming constructs, Interactiveshell scripts, Advanced features; SystemAdministration: Definition of system administration,Booting the system Maintaining user accounts, Filesystems and special files, Backups and restoration, Roleand functions of a system manager; Overview of theLinux operating system.

30 Hours 1


1. “Systems Programming” by Donovan, Tata McGraw-Hill.2. “The UNIX Programming Environment” by Brain Kernighen& Rob Pike,

1984, Prentice Hall of India & Rob Pike.


52 | 9 1

3. “Design of the UNIX Operating System” by Maurich Bach, 1986, PrenticeHall of India.

4. “Introduction to UNIX and LINUX” by John Muster, 2003, Tata McGraw-Hill.

5. “Advanced UNIX programmer’s Guide” by Stephen Prato, BPB6. “UNIX- Concept and Applications” by Sumitabha Das, 2002, T.M.H.

GE33222 System Modeling & Simulation

Course Objective:

1. The basic system concept and definitions of system.2. Techniques to model and to simulate various systems the ability to analyze a

system and to make use of the information to improve the performance.

Learning Outcome:


1. Define basic concepts in modelling and simulation (M&S)2. Classify various simulation models and give practical examples for each

category3. Construct a model for a given set of data and motivate its validity4. Generate and test random number variants and apply them to develop

simulation models5. Analyze output data produced by a model and test validity of the model6. Explain parallel and distributed simulation methods

Course Contents:


Credits

I

INTRODUCTION TO SIMULATIONSimulation: Simulation as a tool, Advantages andDisadvantages of Simulation, Areas of Application,Systems and System Environment. Components of aSystem. Discrete and Continuous Systems. Model ofa System, Types of Models, Discrete-Event SystemSimulation. Steps of Simulation Study

30Hours

1

II

GENERAL PRINCIPLESConcepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance: Algorithm, WorldViews. Manual simulation, Using Event Scheduling.Properties of Random Numbers, Generation ofPseudo-Random Numbers. Techniques for GeneratingRandom Numbers. Tests for Random Numbers

30Hours

1

III

RANDOM-VARIATE GENERATIONInverse Transform technique: ExponentialDistribution, Uniform Distribution, DiscreteDistributions, Acceptance-Rejection Technique,Poisson Distribution. Data Collection, Identifying thedistribution with Data, Parameter Estimation,Goodness of Fit Tests, Selecting Input Models

30Hours

1


53 | 9 1

without Data Multivariate and Time-Series InputModels.

IV

VERIFICATION AND VALIDATION OFSIMULATION MODELSModel Building, Verification and Validation:Verification of Simulation Models, Calibration andValidation of Models.Types of Simulations with Respect to OutputAnalysis .Stochastic Nature of Output Data. Measuresof Performance and Their Estimation. OutputAnalysis for Terminating Simulations, OutputAnalysis for Steady-State Simulations. SimulationTools, Model Input. High-Level Computer-SystemSimulation, CPU Simulation, Memory Simulation.

30Hours

1


1. Jerry Banks, John S. Carson, Barry L. Nelson, David M. Nicol, “Discrete-Event System Simulation”, Third Edition, Prentice-Hall India

2. Averill M. Law, W. David Kelton, "Simulation Modelling and Analysis"Third Edition, McGraw Hill.

3. Geoffrey Gordon, "System Simulation", Second Edition, Prentice-Hall India.

GE33223 Web Technology

Course Objective:

1. Discuss how XML DTDs differ from XML schemas. Recognize and correctvalidity errors in XML documents. Write documents that make appropriateuse of XML namespaces.

2. Write client-server applications that communicate via XML documents.Discuss ways in which an XSL transform differs from processing an XMLdocument using a DOM API.

3. Describe how a given web server responds to an HTTP request for a dynamicresource. Describe sessions conceptually and explain how the concept can beimplemented using cookies and URL rewriting.

4. Discuss the concept and implementation of cookies as well as related privacyconcerns.

5. Explain common security threats such as cross-site scripting and misformedHTTP requests and demonstrate avoidance techniques for each.

6. Use CSS to implement a variety of presentation effects in HTML and XMLdocuments, including explicit positioning of elements

7. Demonstrate techniques for improving the accessibility of an HTMLdocument

8. Write a valid standards-conformant HTML document involving a variety ofelement types, including hyperlinks, images, lists, tables, and forms

9. Describe the actions, including those related to the cache, performed by abrowser in the process of visiting a Web address

10. Install a web server and perform basic administrative procedures, such astuning communication parameters, denying access to certain domains, andinterpreting an access log


54 | 9 1

Learning Outcome:


1. Install, configure, and maintain a Web server;2. Identify and successfully manage issues of Web caching, Web security, and

Web performance;3. Students will be able to understand proficient in Web technologies like

HTML, XML, DOM, SAX4. java technologies for the Web like JAXP, Java Beans, Servlet, JSP, JDBC

with proficiency in Web server configuration5. Create XML documents. Create XML Schema. Build dynamic web pages

using JavaScript (client side programming).6. Create web pages using XHTML and Cascading Styles sheets.7. Analyze a web page and identify its elements and attributes.8. Build web applications using JSP.

Course Contents:


I

HTML, XML and Java ScriptingHTML Common tags: List, Tables, images, forms,

Frames; Cascading Style sheets, Introduction to JavaScripts, Objects in Java Script, Dynamic HTML withJava Script, XML, Document type definition, XMLSchemas, Document Object model, Presenting XML,Using XML Processors, DOM and SAX and XSTL,Java API for XML Processing (JAXP)

30 Hours 1

II

Java Beans: Introduction to Java Beans, Advantagesand properties of Java Beans, BDK , Introspection,Using Bound properties, Bean Info Interface,Constrained properties, Introduction to EJB, JavaBeans API, Introduction to Servelet, Lifecycle of aServelet, JSDK , HTTP package, Handling HttpRequest & Responses, Using Cookies-SessionTracking, Security Issues

30 Hours 1

III

Introduction to JSP,JSP Processing, JSP ApplicationDesign ,Tomcat Server ,Implicit JSP Objects,Conditional Processing, Declaring Variables andMethods, Error Handling and Debugging, SharingData Between JSP pages, Sharing Session andApplication Data

30 Hours 1

IV

Database Access, Database Studying Javax.sql.*package, Accessing a Database from a JSP Page,Application – Specific Database Actions, DeployingJAVA Beans in a JSP Page, Introduction to strutsframework.

30 Hours 1


1. “Programming world wide web”-Sebesta, Pearson


55 | 9 1

2. “Java: The Complete Reference”, 7th edition, Herbert Schildt, Tata McGraw-Hill.

3. “Core Servelet and Java Server Pages Volume 1: Core Technologies” byMarty Hall and Larry Brown Pearson

4. “Java Server Pages”, 2nd Edition by Hans Bergsten, Publisher: O'Reilly5. “Internet and World Wide Web – How to program” by Dietel and Nieto

Prentice Hall of India/Pearson Education Asia.

GE33224 Embedded System Design

Course Objective:

1. To impart fundamental concepts in the area of Embedded Systems.2. To impart the design an embedded system.3. To impart the partition a system to hardware and software parts efficiently.4. To impart the Hardware/software Co-design concepts.

Learning Outcome:


1. Design embedded system architectures for various applications.2. Identify, formulate, and solve engineering problems3. Learn Function on multidisciplinary teams.4. Apply knowledge of mathematics, science and engineering.5. Explain applications, benefits, and limitations of networked embedded

systems for environmental science, health, and safety, industrial, andconsumer usage objectives.

6. Develop standard project plans for a software development team includinginterface definition.

Course Contents:


Credits

I

Introduction

Definition, Embedded System Project Management,Embedded System Design and Issues, Design Cycle,Use of Target System and In-Circuit Emulator, Use ofSoftware Tools for Development of EmbeddedSystem

30Hours

1

II

RTOS and Microcontroller

Task and Task States, Task and Data, Semaphoresand Shared Data Operating System Services:Message Queues, Timer Functions, Events, Memorymanagement, Interrupts Routines in an RTOS,Microprocessor Vs. microcontroller, 8051microcontroller

30Hours

1


56 | 9 1

III

Embedded System Development

Embedded System Evolution Trends, Round Robin,Robin with Interrupts, Function One SchedulingArchitecture, Assembler, Compiler, Cross Compilerand IDE, Object Oriented Interfacing, Recursion,Debugging Strategies, Simulators

30Hours

1

IV

Networks for Embedded System

I2C Bus, CAN Bus, SHARC Link Ports, Ethernet,Myrinet, Internet, Bluetooth, IEEE 1149.1 (JTAG)Testability

30Hours

1


1. “Embedded Systems”, Raj Kamal,TMH.2. “The 8051 Microcontroller”, K. J. Ayala, Penram International.3. “Design with PIC Icrocontroller”, J. b. Peatman, Printice Hall.4. “Real Time Systems”, H.Kopetz, Kluwer, 1997.5. “Co-synthesis of hardware and software for embedded systems”, R. Gupta,

Kluwer, 1996.

GE33225 Big Data

Course Objective:1. Understand what Big Data is and why classical data analysis techniques are no

longer adequate2. Understand the benefits that Big Data can offer to businesses and organizations3. Understand conceptually how Big Data is stored4. Understand how Big Data can be analyzed to extract knowledge5. Communicate with data scientistsLearning Outcome:1. To provide an overview of an exciting growing field of big data analytics.2. To introduce the tools required to manage and analyze big data like Hadoop,

NoSql MapReduce.3. To teach the fundamental techniques and principles in achieving big

data analytics with scalability and streaming capability.4. To enable students to have skills that will help them to solve complex real-

world problems in for decision support.

Course Contents:


Credits

I

UNDERSTANDING BIG DATA

What is big data, Why big data, Convergence of keytrends, Unstructured data, Industry examples of bigdata, Web analytics, Big data and marketing, Fraud

30Hours

1


57 | 9 1

and big data, Risk and big data, Credit riskmanagement, Big data and algorithmic trading, Bigdata in healthcare, Medicine and Advertising, Bigdata technologies, Introduction to Hadoop, Opensource technologies, Cloud and big data mobilebusiness intelligence, Crowd sourcing analytics, interand trans firewall analytics.

II

NOSQL DATA MANAGEMENT

Introduction to NoSQL, Aggregate data models, Key-value and document data models, Relationships,Graph databases, Schema less databases, Materializedviews, Distribution models, Sharding, Master-slavereplication , peer-peer replication, Sharding andreplication, consistency, relaxing consistency, versionstamps, map-reduce, partitioning and combining,Composing map-reduce calculations.

30Hours

1

III

BASIC OF HADOOP and MAP ReduceApplication

Data format, Analyzing data with Hadoop, Scalingout, Hadoop streaming, Hadoop pipes, Design ofHadoop Distributed file system (HDFS) , HDFSconcepts, Java interface, Data flow, Hadoop I/O, Dataintegrity, Compression, Serialization, Avro file-baseddata structures, Map Reduce workflows, Unit testswith MRUnit , Test data and local tests – anatomy ofMap Reduce job run, Classic Map-reduce, YARN,Failures in classic Map-reduce and YARN, Jobscheduling, Shuffle and Sort, Task execution ,MapReduce types, Input-Output formats.

30Hours

1

IV

HADOOP RELATED TOOLS

Hbase, Data model and implementations, Hbaseclients, Hbase examples– praxis. Cassandra,Cassandra data model, Cassandra examples,Cassandra Clients, Hadoop integration. Pig Grunt, Pigdata model, Pig Latin, Developing and testing PigLatin scripts. Hive, data types and file formats,HiveQL data definition, HiveQL data manipulation –HiveQL queries.

30Hours

1



58 | 9 1

1. Michael Minelli, Michelle Chambers, and Ambiga Dhiraj, “Big Data, BigAnalytics:Emerging Business Intelligence and Analytic Trends for Today'sBusinesses”, Wiley, 2013.

2. “Big-Data Black Book”, DT Editorial Services, Wily India3. P. J. Sadalage and M. Fowler, “NoSQL Distilled: A Brief Guide to the Emerging

World of Polyglot Persistence”, Addison-Wesley Professional, 2012.4. Tom White, “Hadoop: The Definitive Guide”, Third Edition, O'Reilley,2012.5. Eric Sammer, “Hadoop Operations”, O'Reilley, 2012.

Generic Elective – III

GE33231 Cyber Law and Security

Course Objective:

1. Teach students the basics of information security and computercommunication.

2. Familiarize students with Cyber Laws and Security policies and Cryptography.3. Learn some of the convention and experience the ways of improving from

existing experiences.

Learning Outcome:


1. They can help the organization to continue its commercial activities in theevent of significant information security incidents

2. Students can establish responsibility and accountability for informationsecurity in organizations

3. To be proficient in various forensic tools and usage of tools for diskimaging and recovery processes

4. The students will be able to design security procedures and policies5. They can be well versed in various security standards and security testing

techniques

Course Contents:


Credits

I

Information Systems and its Importance, History ofInformation Systems and its basics, Changing Natureof Information Systems, Need of DistributedInformation Systems, Role of Internet and WebServices, Information System Threats and attacks,

Classification of Threats and Assessing DamagesSecurity in Mobile and Wireless Computing , SecurityChallenges in Mobile Devices, authentication ServiceSecurity, Security Implication for organizations,Laptops Security Concepts in Internet and WorldWide Web: Brief review of Internet Protocols-TCP/IP, IPV4, IPV6, Functions of various networking

30Hours

1


59 | 9 1

components routers, bridges, switches, hub, gatewayand Modulation Techniques.

II

Basic Principles of Information Security,Confidentiality, Integrity Availability and other termsin Information Security, Information Classificationand their Roles, Security Threats to E Commerce,Virtual Organization, Business Transactions on

Web, E Governance and EDI, Concepts in Electronicspayment systems, E Cash, Credit/Debit Cards,Physical Security- Needs, Disaster and Controls,Basic Tenets of Physical Security and Physical EntryControls, Access Control- Biometrics, Factors inBiometrics Systems, Benefits ,Criteria for selection ofbiometrics, Design Issues in Biometric Systems,Interoperability Issues, Economic and SocialAspects, Legal. Challenges Framework forInformation Security, ISO 27001, SEE-CMM,Security Metrics, Information Security Vs. Privacy

30Hours

1

III

Cryptographic Systems, Model of CryptographicSystems, Issues in Documents Security, System ofKeys, Public Key Cryptography, Digital Signature,Requirement of Digital Signature System, FingerPrints, Firewalls Design and Implementation Issues,Policies Network Security, Basic Concepts,Dimensions, Perimeter for Network Protection,Network Attacks, Overview of IDS, Need of IntrusionMonitoring and Detection, Intrusion Detection VirtualPrivate Networks- Need, Use of Tunneling with VPN,Authentication Mechanisms, VPN, Types of VPNsand their Usage, Security Concerns in VPN.

30Hours

1

IV

Laws, Investigation and Ethics, Cyber Crime ,Information Security and Law ,Types & overview ofCyber Crimes, Cyber Law, Issues in E-BusinessManagement Overview of Indian IT Act, EthicalIssues in Intellectual property rights, Copy Right,Patents, Data privacy and protection, Domain Name,Software piracy, Plagiarism, Issues in ethical hacking.

30Hours

1


1. Godbole, “ Information Systems Security”, Willey2. Merkov, Breithaupt, “ Information Security”, Pearson Education3. Yadav, “Foundations of Information Technology”, New Age, Delhi4. Schou, Shoemaker, “ Information Assurance for the Enterprise”, Tata

McGraw Hill5. Sood,“ Cyber Laws Simplified”, McGraw Hill6. Furnell, “Computer Insecurity”, Springer


60 | 9 1

7. IT Act 2000

GE33232 Real Time Operating System

Course Objective:

1. This course will provide students with an introduction to operating systemstheory

2. Practical problem solving approaches to real-time systems.3. Real-time scheduling and schedulability analysis4. Formal specification and verification of timing constraints and properties5. Design methods for real-time systems

Learning Outcome:


1. List characteristics of real-time operating systems (RTOS).2. Compare hard and soft real-time systems.3. List features and services that are typically provided by an RTOS.4. Configure the scheduler that is used in an RTOS.5. Write applications that create and delete tasks, control task scheduling, and

obtain task information.6. Compare binary semaphores, counting semaphores, and mutexes.7. Describe how semaphores are typically used in RTOS applications.8. Write applications that create, delete, acquire and release a semaphore.

Course Contents:


Credits

I

Definition of Real Time Operating Systems,Classification of RTOS, Concept of computer control,Sequence, loop and supervisor control, Centralized,hierarchical and distributed systems, HumanComputer interface , Hardware requirement for realtime applications, Specialized processors, interfacesand communications

30Hours

1

II

Scheduling strategies, Priority structures and Taskmanagement, Real Time Clock Handler, Codesharing, Resource Control, Inter task Communicationand Control , Example of Creating and RTOS basedon Modula-2 kernel

30Hours

1

III

Introduction to Design of Real Time Systems:Specification, Preliminary Design, MultitaskingApproach, Monitors and Rendezvous, Fault ToleranceTechniques: Introduction, Faults, Fault types,Detection and Containment, Redundancy, Errors andFailures, Integrated Failure Handling.

30Hours

1


61 | 9 1

IV

Introduction to Semaphores, Semaphore States, Typesof Semaphores, Semaphores Implementation,Applications of RTOS, Semaphores in RTOSApplications, Examples: Creating Semaphores,Deleting Semaphores, Acquiring Semaphores,Releasing Semaphores

30Hours

1


1. Silberschatz, Galvin and Gagne, “Operating Systems Concepts”, Wiley2. Phillip. A. Laplante, “Real-Time Systems Design and Analysis”, second

edition, PHI, 2005.3. Jane. W. S. Liu, “Real Time Systems”, Pearson education, 2005

GE33223 Robotics

Course Objective:

1. This course provides an introduction to the mechanics of robots and spatialmechanics and motion planning.

2. The theoretical focus is on kinematics and dynamics of robotic manipulatorsand control design for non-linear mechanical systems.

3. Laboratory practice to learn simple robot programming.4. This course will also expose students to some of the contemporary happenings

in robotics, including current robotics research, applications, robot contestsand robot web surfing.

Learning Outcome:


1. Be familiar with the history, concept development and key components ofrobotics technologies.

2. Understand basic mathematic manipulations of spatial coordinaterepresentation and transformation.

3. Understand and able to solve basic robot forward and inverse kinematicsproblems.

4. Understand and able to solve basic robotic dynamics, path planning andcontrol problems.

5. Able to undertake practical robotics experiments that demonstrate the aboveskills.

Course Contents:


Credits

I

Introduction

Definition, Classification of Robots, geometricclassification and control classification. RobotElements: Drive system, control system, sensors, end

30Hours

1


62 | 9 1

effectors, gripper actuators and gripper design.

II

Robot Coordinate Systems and ManipulatorKinematics

Robot Coordinate Systems and ManipulatorKinematics: Robot co-ordinate system representation,transformation, homogenous transform and itsinverse, relating the robot to its world. ManipulatorsKinematics, parameters of links and joints, kinematicchains, dynamics of kinematic chains, trajectoryplanning and control, advanced techniques ofkinematics and dynamics of mechanical systems,parallel actuated and closed loop manipulators.

30Hours

1

III

Robot Control

Robot Control: Fundamental principles, classification,position, path velocity and force control systems,computed torque control, adaptive control, Seroosystem for robot control, and introduction to robotvision, Robot Programming: Level of robotprogramming, language based programming, tasklevel programming, robot programming synthesis,robot programming for welding, machine tools,material handling, assembly operations, collision freemotion planning.

30Hours

1

IV

Applications

Applications: Application of robot in welding,machine tools, material handling, and assemblyoperations parts sorting and parts inspection.

30Hours

1


1. Coifet Chirroza, “An Introduction to Robot Technology” Kogan Page.2. Y. Koren “Robotics for Engineers” Mcgraw Hill.3. K. S. Fu, R.C. Gonzalez Y& CSG Lee, “Robotics” McGraw Hill.4. J.J. Craig, “Robotics” Addison-Wesley.5. Grover, Mitchell Weiss, Nagel Octrey, “Industrial Robots” Mcgraw Hill.6. Asfahl, “Robots & Manufacturing Automation” Wily Eastern.

GE33234 Computer Vision

Course Objective:

1. To introduce students with practice and theory of computer vision.


63 | 9 1

2. To give basics of pattern recognition concepts with application to computervision.

3. Study about the concept of facial recognition system.4. To provide students with necessary theory and skills for automatic analysis of

digital images.5. Learn basics of video processing and object recognition systems.

Learning Outcome:


1. Understand the vision technology in conjunction with real world application.2. Students will able to implement the functioning methods of surveillance

cameras.3. Apply all the enhancement methods of digital images.4. Make automatic decision based on extracted feature information of images.5. Understand the basic and commonly used paradigms of vision technology.

Course Contents:


I

Introduction to Recognition and MorphologicalImage Processing

Recognition Methodology; Conditioning, Labeling,Grouping, Extracting, Matching. MorphologicalImage Processing; Introduction, Dilation and Erosion,Opening and Closing, Hit-or-Miss transformation.Morphological algorithm operations on binaryimages;

Morphological algorithm, Operations on gray-scaleimages, Thinning and Thickening, Region growingand region shrinking. Image Representation andDescription. Representation schemes. Boundarydescriptors. Region descriptors.

30Hours

1

II

Segmentation and Edge detection in BinaryMachine Vision

Binary Machine Vision; Thresholding, Segmentation;Hierarchal segmentation, Rule-based segmentation,Motion-based segmentation. Connected componentLabeling. Spatial Clustering; Split and Merge. AreaExtraction in an image; Basic Concepts, DataStructures. Edge; Line Linking, Hough Transform.Line fitting and Curve fitting (Least-Square fitting).

30Hours

1

IIIProjection and Image Matching Techniques

Region Analysis; Region properties, External points,Spatial 05 moments, Mixed spatial gray-level

30Hours

1


64 | 9 1

moments. Boundary Analysis;

Signature properties, Shape numbers. Facet ModelRecognition; Labeling lines, Understanding linedrawings. Classification of shapes by labeling ofedges; Recognition of shapes, Consisting labelingproblem, Back-tracking Algorithm. Projection;Perspective Projective geometry, Inverse perspectiveProjection, Photogrammetry - from 2D to 3D. Imagematching; Intensity matching of ID signals, Matchingof 2D image, Hierarchical image matching.

IV

Object Modeling and Object Recognition

Object Models And Matching; 2D representation,Global vs. Local features. General Frame Works ForMatching; Distance relational approach, Orderedstructural matching, View class matching, Modelsdatabase organization. Knowledge Based Vision;Knowledge representation, Control strategies,Information Integration. Object recognition; Houghtransforms and other simple object recognitionmethods. Shape correspondence and shape matching.Principal component analysis (PCA). Shape priors forrecognition

30Hours

1


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

2. David A. Forsyth, Jean Ponce, “Computer Vision: A Modern Approach”3. Milan Sonka,Vaclav Hlavac, Roger Boyle, “Image Processing, Analysis, and

Machine Vision”, Thomson Learning

GE33235 Cloud ComputingCourse Objective:1. To learn how to use Cloud Services.2. To implement Virtualization3. To implement Task Scheduling algorithms.4. Apply Map-Reduce concept to applications.5. To build Private Cloud.6. Broadly educate to know the impact of engineering on legal and societal issues

involved.Learning Outcome:1. Analyze the Cloud computing setup with its vulnerabilities and applications using

different architectures.2. Design different workflows according to requirements and apply map reduce

programming model.3. Apply and design suitable Virtualization concept, Cloud Resource Management

and design scheduling algorithms.

Course Contents:


65 | 9 1


Credits

I

Overview of Computing ParadigmRecent trends in Computing Grid Computing, ClusterComputing, Distributed Computing, UtilityComputing, and Cloud Computing Evolution of cloudcomputing Business driver for adopting cloudcomputing.Introduction to Cloud Computing Cloud Computing(NIST Model), History of Cloud Computing, Cloudservice providers Properties, Characteristics &Disadvantages, Pros and Cons of Cloud Computing,Cloud computing vs. Cluster computing vs. Gridcomputing Role of Open Standards

30Hours

1

II

Cloud Computing ArchitectureCloud computing stack Comparison with traditionalcomputing architecture (client/server), Servicesprovided at various levels, How Cloud ComputingWorks, Role of Networks in Cloud computing,protocols used, Role of Web services Service Models(XaaS), Infrastructure as a Service(IaaS), Platform asa Service (PaaS), Software as a Service(SaaS),Deployment Models Public cloud, Private cloud,Hybrid cloud, Community cloud.

30Hours

1

III

Service (IaaS, PaaS, SaaS)Introduction to IaaS, IaaS definition, Introduction tovirtualization, Different approaches to virtualization,Hypervisors, Machine Image, Virtual Machine(VM),Resource Virtualization Server, Storage, NetworkVirtual Machine (resource) provisioning andmanageability, storage as a service, Data storage incloud computing (storage as a service) ExamplesAmazon EC2 Renting, EC2 Compute Unit, Platformand Storage, pricing, customers Eucalyptus Platformas a Service (PaaS), Introduction to PaaS, What isPaaS, Service Oriented Architecture (SOA), CloudPlatform and Management, Computation StorageExamples Google App Engine, Microsoft AzureSoftware as a Service (PaaS) Introduction to SaaS,Web services, Web 2.0, Web OS, Case Study onSaaS.

30Hours

1

IV

Service Management and Cloud Security

Service Level Agreements(SLAs), Billing &Accounting, Comparing Scaling Hardware:Traditional vs. Cloud, Economics of scaling:Benefitting enormously Managing Data Looking atData, Scalability & Cloud Services Database & DataStores in Cloud Large Scale Data Processing.

30Hours

1


66 | 9 1

Infrastructure Security Network level security, Hostlevel security, Application level security Data securityand Storage Data privacy and security Issues,Jurisdictional issues raised by Data location Identity& Access Management, Access Control, Trust,Reputation, Risk, Authentication in cloud computing,Client access in cloud, Cloud contracting Model,Commercial and business considerations


1. Ronald L. Krutz, Russell Dean Vines, “Cloud Security: A ComprehensiveGuide to Secure Cloud Computing”, Wiley-India, 2010

2. Bible, Barrie Sosinsky, “Cloud Computing”, Wiley-India, 20103. Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, “Cloud Computing:

Principles and Paradigms” ,Wile, 20114. Nikos Antonopoulos, Lee Gillam, “Cloud Computing: Principles, Systems and

Applications”, Springer, 2012

Open Elective-I

OE33211 Electronic Commerce

Course Objective:

1. The fundamentals of the business and economic motivations for e-Commerceas well as the needs and desires of individuals.

2. The underlying computation, information and communication environmentsthat encompass and enable e-Commerce transactions, and

3. The evolving role of new highly portable, place-aware, always-with-youpersonal devices in e-Commerce, i.e., M-commerce

Learning Outcome:


1. Understand the nature and trends in e-Commerce and Mobile commerce2. Recognize the business impact and potential of e-Commerce3. Explain the technologies required to make e-Commerce viable4. Discuss the current drivers and inhibitors facing the business world in

adopting and using e-Commerce5. Explain the economic consequences of e-Commerce

Course Contents:


I

Politics, Science and Business of Sustainability:Introduction to Electronic Commerce, What is E-commerce?, Traditional Commerce vs. E-commerce,Advantages and Disadvantages of E-commerce,Impact of E-commerce, Classification of E-commerce, Applications of E-commerce, Limitations

30 Hours 1


67 | 9 1

of E-commerce, Electronic Commerce, BusinessModels, Native Content based Model, TransplatedContent Model, Native Transaction Model,Transplated Transaction Models, ArchitecturalFramework of Electronic Commerce, Network,Infrastructure, Information Distribution Technology,Networked Multimedia Content PublishingTechnology, Security issues, Payment Services,Business Service Infrastructure, Public Policy andLegal Infrastructure

II

Electronic Commerce Infrastructure: ElectronicCommerce: Network Infrastructure, Local AreaNetworks, Wide Area Networks, Internet, DomainName Systems, Electronic Commerce: InformationDistribution and Messaging, File Transfer Protocol(FTP) Application, Electronic Mail, World Wide WebServer, HTTP, Electronic Commerce: InformationPublishing Technology, Information Publishing, WebBrowser, Hypertext Markup Language, CommonGateway Interface, Multimedia Content

30 Hours 1

III

Electronic Commerce Security and PaymentSystem: Securing the Business on Internet,Vulnerability of Information on Internet, SecurityPolicy, Procedures and Practices, Site Security,Protecting the Network, Firewalls, Securing NetworkTransaction, Transaction Security, Cryptology,Cryptographic Algorithms, Public Key Algorithms,Authentication Protocols, Digital Signatures,Electronic Mail Security, Security Protocols for WebCommerce, Electronic Payment System, Introductionto Payment Systems, Online Payment Systems, Pre-Paid Electronic Payment Systems, Post-paidElectronic Payment Systems

30 Hours 1

IV

Mobile Commerce: Introduction, Framework, andModels: What is Mobile Commerce?, Benefits ofMobile Commerce, Impediments in MobileCommerce, Mobile Commerce Framework, WirelessNetwork Infrastructure, Information DistributionProtocols, Mobile Commerce Payment Systems,Mobile Payment Models, Mobile CommerceApplications

30 Hours 1


1. Bharat Bhaskar, “Electronic Commerce: Framework, Technologies &Applications 4/e”, TMH

2. Ravi Kalakota, Andrew Winston, “Frontiers of Electronic Commerce”,Addison-Wesley


68 | 9 1

3. Bajaj and Nag, “E-Commerce: The Cutting Edge of Business”, Tata McGrawHill

4. P. Loshin, John Vacca, “Electronic Commerce”, Firewall Media, New Delhi5. P. T. Joseph, “E-Commerce: An Indian Perspective”, PHI Learning Pvt. Ltd.6. Norman, Sadeh , “M Commerce: Technologies, Services, and Business

Models”, Wiley Computer Publishing

BCS3751 Artificial Intelligence Lab

Tools/Software used: PROLOG and LISP

List of Programs:

1. Write simple fact for the statements using PROLOG.2. Write predicates one converts centigrade temperatures to Fahrenheit, the other

checks if a temperature is below freezing.3. Write a program to solve the Monkey Banana problem.4. WAP in turbo prolog for medical diagnosis and show the advantage and

disadvantage of green and red cuts.5. WAP to implement factorial, Fibonacci of a given number.6. Write a program to solve 4-Queen problem.7. Write a program to solve traveling salesman problem.8. Write a program to solve water jug problem using LISP.

BCS3752 Network Security Lab

Tools/Software used: C/C++/Java

1. Write program for Mono alphabetic cipher.2. Implementation of Play Fair cipher.3. Implementation of Vigenere cipher (Polyalphabetic substitution).4. Implementation of Hill cipher.5. Implementation of Gauss cipher.6. Implementation of Rail Fence cipher.7. Implementation of S-DES algorithm for data encryption.8. Implement RSA asymmetric (public key and private key)-Encryption.

Encryption key (e, n) & (d,n)9. Generate digital signature using Hash code.10. Generate digital signature using MAC code.

BCS3801 Digital Image Processing

Course Objective:

1. Cover the basic theory and algorithms that are widely used in digital imageprocessing

2. Expose students to current technologies and issues that are specific toimage processing systems

3. Develop hands-on experience in using computers to process images


69 | 9 1

Learning Outcome:

1. Understand image formation and the role human visual system plays inperception of gray and color image data.

2. Get broad exposure to and understanding of various applications of imageprocessing in industry, medicine, and defense.

3. Learn the signal processing algorithms and techniques in imageenhancement and image restoration.

4. Acquire an appreciation for the image processing issues and techniquesand be able to apply these techniques to real world problems.

5. Be able to conduct independent study and analysis of image processingproblems and techniques.

Course Contents:


I

Introduction & Fundamentals

Introduction: Motivation and Perspective,Applications, Components of Image ProcessingSystem.

Fundamentals: Element of Visual Perception, ASimple Image Model, Sampling and Quantization;Image Enhancement in Spatial Domain Introduction;Basic Gray Level Functions: Piecewise-LinearTransformation Functions-Contrast Stretching;Histogram Specification: Histogram Equalization,Local Enhancement, Enhancement usingArithmetic/Logic Operations-Image Subtraction,Image Averaging; Basics of Spatial Filtering:Smoothing - Mean filter, Ordered Statistic Filter;Sharpening – The Laplacian;

30Hours

1

II

Image Enhancement in Frequency DomainFourier Transform and the Frequency Domain &Image Restoration

Basis of Filtering in Frequency Domain: Filters, Low-pass, High-pass, Correspondence Between Filtering inSpatial and Frequency Domain, SmoothingFrequency Domain Filters-Gaussian Lowpass Filters;Sharpening Frequency Domain Filters-GaussianHighpass Filters; Homomorphic Filtering.

Image Restoration: A Model of Restoration Process,Noise Models, Restoration in the presence of Noiseonly-Spatial Filtering-Mean Filters: Arithmetic Meanfilter, Geometric Mean Filter, Order Statistic Filters –Median Filter, Max and Min filters; Periodic NoiseReduction by Frequency Domain Filtering- Bandpass

30Hours

1


70 | 9 1

Filters; Minimum Mean-square Error Restoration.

III

Colour & Morphological Image Processing &Registration

Color Fundamentals: Color Models- ConvertingColors to different models; Color Transformation,Smoothing and Sharpening, Color Segmentation.

Morphological Image Processing: Introduction, LogicOperations involving Binary Images, Dilation andErosion, Opening and Closing, MorphologicalAlgorithms- Boundary Extraction, Region Filling,Extraction of Connected Components, Convex Hull,Thinning, Thickening. Registration: Introduction,Geometric Transformation-Plane to Planetransformation; Mapping, Stereo Imaging-Algorithmsto Establish Correspondence; Algorithms to RecoverDepth.

30Hours

1

IV

Segmentation & Object Recognition

Segmentation: Introduction, Region Extraction, Pixel-Based Approach, Multi-level Thresholding, LocalThresholding, Region-based Approach, Edge andLine Detection-Edge Detection, Edge Operators,Pattern Fitting Approach, Edge Linking and EdgeFollowing, Edge Elements. Feature ExtractionRepresentation: Topological Attributes, GeometricAttributes. Description: Boundary-based Description,Region-based Description, Relationship.

Object Recognition: Deterministic Methods,Clustering, Statistical Classification, SyntacticRecognition, Tree Search, Graph Matching.

30Hours

1

Text/ Reference Books:

1. Rafael C. Gonzalvez and Richard E. Woods, “Digital Image Processing” 2ndEdition, Pearson Education.

2. R.J. Schalkoff, “Digital Image Processing and Computer Vision”, John Wileyand Sons, NY.

3. A.K. Jain, “Fundamentals of Digital Image Processing”, Published by PrenticeHall, Upper Saddle River, NJ.


71 | 9 1

Generic Elective – IV

GE33241 Data mining and Warehousing

Course Objective:

1. Understand data mining principles and techniques.2. Building basic terminology.3. Learning how to gather and analyze large sets of data to gain useful business

understanding.4. Learning how to produce a quantitative analysis report/memo with the

necessary information to make decisions.5. Describing and demonstrating basic data mining algorithms, methods, and

tools.6. Identifying business applications of data mining.7. Overview of the developing areas - web mining, text mining, and ethical

aspects of data mining.8. Develop and apply critical thinking, problem-solving, and decision-making

skills.

Learning Outcome:


1. Learn the concepts of database technology evolutionary path which has led tothe need for data mining and its applications.

2. Examine the types of the data to be mined and present a general classificationof tasks and primitives to integrate a data mining system.

3. Apply preprocessing statistical methods for any given raw data.4. Explore DWH and OLAP, and devise efficient & cost effective methods for

maintaining DWHs.5. Discover interesting patterns from large amounts of data to analyze and extract

patterns to solve problems, make predictions of outcomes.6. Comprehend the roles that data mining plays in various fields and manipulate

different data mining techniques.7. Select and apply proper data mining algorithms to build analytical

applications.

Course Contents:

Module Course Topics

TotalHours Credits

I

Data MiningOverview , Motivation(for Data Mining),Data Mining,Definition & Functionalities, Data Processing, Form ofData Preprocessing ,Data Cleaning: Missing Values,Noisy Data, Inconsistent Data, Data Integration andTransformation. , Data Reduction, Data CubeAggregation, Dimensionality reduction, DataCompression, Numerosity Reduction, Clustering,Discretization and Concept Hierarchy generation.

30Hours

1


72 | 9 1

II

Data Mining Statistics and Association ruleConcept Description, Definition, Data Generalization,Analytical Characterization, Analysis of attributerelevance, Mining Class comparisons ,Statisticalmeasures in large Databases, Measuring CentralTendency, Measuring Dispersion of Data ,Range,Quartiles, Outliers, Box plots, Variance, StandardDeviation, Graph Displays of Basic Statistical classDescription, Mining Association Rules in LargeDatabases, Association rule mining, Mining Single-Dimensional Boolean Association rules fromtransactional Databases– A priori Algorithm, MiningMultilevel Association rules from Transaction Databases,Mining Multi-Dimensional Association rules fromRelational Databases.

30Hours

1

III

Classification and PredictionsWhat is Classification & Prediction ,Issues regardingClassification and prediction, Decision tree, BayesianClassification ,Classification by Back propagation,Multilayer feed-forward Neural Network, Backpropagation Algorithm, Classification methods ,K nearestneighbor classifiers, Genetic Algorithm, Cluster Analysis,Data types in cluster analysis, Categories of clusteringmethods, Partitioning methods, Hierarchical Clustering-,CURE and Chameleon, Density Based Methods-DBSCAN, OPTICS, Grid Based Methods-STING,CLIQUE ,Model Based Method –Statistical Approach,Neural Network approach, Outlier Analysis.

30Hours

1

IV

Data Warehousing and OLAPOverview ,Definition, Delivery Process ,Differencebetween Database System and Data Warehouse, Multi-Dimensional Data Model, Data Cubes ,Stars ,SnowFlakes ,Fact Constellations ,Concept hierarchy,ProcessArchitecture,ThreeTierArchitecture,DataMarting,Aggregation,Historical information ,Query Facility,OLAP function and Tools, OLAP Servers, ROLAP,MOLAP, HOLAP, Data Mining interface, Security,Backup and Recovery, Tuning Data Warehouse, TestingData Warehouse.

30Hours

1


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

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

3. Sam Anahory, Dennis Murray, “Data Warehousing in the Real World : APractical Guide for Building Decision Support Systems, 1/e”, PearsonEducation

4. Mallach, “Data Warehousing System”, McGraw –Hill


73 | 9 1

GE33242 Artificial Neural Networks (ANN) and Fuzzy Logic

Course Objective:

1. To introduce the neural networks as means for computational learning.2. To present the basic network architectures for classification and regression.3. To provide knowledge for network tuning and over fitting avoidance.4. Learn various methods of fuzzy computing and the basic concepts of neuro

fuzzy systems.5. Study the various methods of genetic algorithm and implement them into fuzzy

environment.

Learning Outcome:


1. Design single and multi-layer feed-forward neural networks and Backpropagation networks.

2. Explain the differences between networks for supervised and unsupervisedlearning.

3. Comprehend neuro fuzzy modelling and demonstrate some applications ofcomputational intelligence.

4. Understand the fuzzy approximate reasoning and fuzzy rule based systems.5. Implement the genetic algorithms concept in heuristic search methods.

Course Contents:


Credits

I

Neural Networks Introduction and Architecture

Structure of Biological neuron; Neuron, NerveStructure and synapse. Artificial Neuron and itsmodel. Activation functions. Neural networkarchitecture; Single layer feed forward networks,multilayer feed forward networks, Recurrentnetworks, Technologies. Various learning techniques;Supervised learning, Un-Supervised learning,Reinforcement learning. Perception and convergencerule. Associative memory; Auto-associative memory,Hetro-associative memory.

30Hours

1

II

Neural networks - (BPN)

Back propagation network (BPN) Architecture.Perceptron model; Single layer artificial neuralnetwork, multilayer perception model, LinearSeperability. Back propagation learning methods;Effect of learning rule co-efficient, Back propagationalgorithm; factors affecting back propagation training,Momentum Factor of EBPA. Application of Neuralnetworks.

30Hours

1

III Fuzzy logic 30 1


74 | 9 1

Basic concepts of fuzzy logic. Fuzzy sets and Crispsets. Fuzzy set theory and operations. Properties offuzzy sets. Fuzzy and Crisp relations. Fuzzy to Crispconversion. Membership functions. Interference infuzzy logic. Fuzzy if-then rules. Fuzzy implicationsand Fuzzy algorithms. Fuzzyfications &Defuzzifications. Fuzzy Logic Controller(FLC).Industrial applications of Fuzzy.

Hours

IV

Genetic Algorithm(GA)

Introduction of Genetic Algorithm; Fundamentals ofGA, Basic concepts of GA, Working principle,Encoding, fitness function,

Reproduction. Genetic modeling; Inheritanceoperator, Cross over Operators, Inversion& deletion,Mutation operator, Bitwise operators. GenerationalCycle of GA. Convergence of GA. Applications &advances in GA. Differences & similarities betweenGA & other traditional methods.

30Hours

1


1. S. Rajsekaran & G.A. Vijayalakshmi Pai, “Neural Networks,Fuzzy Logic andGenetic Algorithm: Synthesis and Applications”, Prentice Hall of India.

2. N. P. Padhy, “Artificial Intelligence and Intelligent Systems”, OxfordUniversity Press.

3. Siman Haykin, “Neural Networks”, Prentice Hall of India4. Timothy J. Ross, “Fuzzy Logic with Engineering Applications”, Wiley I

GE33243 Mobile Computing

Course Objective:

1. To provide guidelines, design principles and experience in developingapplications for small, mobile devices, including an appreciation of context andlocation aware services

2. To develop an appreciation of interaction modalities with small, mobile devices(including interface design for non-standard display surfaces) through theimplementation of simple applications and use cases.

3. To introduce wireless communication and networking principles, that supportconnectivity to cellular networks, wireless internet and sensor devices.

4. To understand the use of transaction and e-commerce principles over suchdevices to support mobile business concepts

5. To appreciate the social and ethical issues of mobile computing, includingprivacy.

Learning Outcome:

At the end of the module, the student will be able to:


75 | 9 1

1. Demonstrate a working understanding of the characteristics and limitations ofmobile hardware devices including their user-interface modalities

2. Demonstrate the ability to develop applications that are mobile-device specificand demonstrate current practice in mobile computing contexts.

3. Demonstrate a comprehension and appreciation of the design and developmentof context-aware solutions for mobile devices.

4. Demonstrate an awareness of Generic and ethical issues, in particular thoserelating to security and privacy of user data and user behavior.

Course Contents:


I

Evolution from 2G over 3G to 4G: Beyond 3GNetwork Architectures, Overview: UMTS, HSPA(HSDPA and HSUPA)

Introduction to Network Architecture, Air Interfaceand Radio Network, LTE-Introduction, NetworkArchitecture, Air Interface and Radio Network, BasicProcedures, Summary and Comparison with HSPA.

30Hours

1

II

802.16 WiMAX: Introduction, NetworkArchitecture, The 802.16d Air Interface and RadioNetwork, The 802.16e Air Interface and RadioNetwork, Basic Procedures, Summary andComparison with HSPA and LTE, 802.16m:Complying with IMT Advanced, 802.16j: MobileMulti-hop Relay , 802.11Wi-Fi: Introduction,Network Architecture

The Air Interface –from 802.11b to 802.11n AirInterface and Resource Management, BasicProcedures, Wi-Fi Security, Quality of Service:802.11e.

30Hours

1

III

Network Capacity and Usage Scenarios: Usage inDeveloped Markets and Emerging Economies, Howto Control Mobile Usage, Per Minute Charging,Volume Charging, Split Charging, Small-screen FlatRates

Strategies to Inform Users When Their SubscribedData, Measuring Mobile Usage from a FinancialPoint of View, Cell Capacity in Downlink, Currentand Future Frequency Bands for Cellular Wireless

Cell Capacity in Uplink, Per-user Throughput inDownlink, Per-user Throughput in the Uplink TrafficEstimation Per user, Overall Wireless NetworkCapacity, Network Capacity for Train Routes,Highways and Remote Areas, A Hybrid Cellular/Wi-

30Hours

1


76 | 9 1

Fi Network for the Future

IV

Voice over Wireless, Circuit-switched Mobile VoiceTelephony: Circuit Switching, A Voice-optimizedRadio Network, The Pros of Circuit Switching,Packet-switched Voice Telephony, Network andApplications are Separate in Packet-SwitchedNetworks, Wireless Network Architecture forTransporting IP packets, Benefits of Migrating VoiceTelephony to IP, Voice Telephony Evolution andService Integration, Voice Telephony over IP: theEnd of the Operator Monopoly, SIP Telephony overIP network.

30Hours

1


1. J. Schiller, “Mobile Communications”, Addison Wesley.2. A. Mehrotra, “GSM System Engineering”.3. M. V. D. Heijden, M. Taylor, “Understanding WAP”, Artech House.4. Charles Perkins, “Mobile IP”, Addison Wesley.5. Charles Perkins, “Ad hoc Networks”, Addison Wesley.

GE33244 Natural Language Processing

Course Objective:

1. Develop familiarity with lexical, syntactic, semantic and pragmatic aspects ofNLP

2. Understand the basic concepts of context free grammar and Parsing methodsof NLP.

3. Study the basic problem regarding NLP and removal methods of it.4. Develop an understanding of NLP Models and Algorithms.5. Develop background in statistical and machine learning approaches to NLP.

Learning Outcome:


1. Show sensitivity to linguistic phenomena and an ability to model them withformal grammars.

2. Understand and carry out proper experimental methodology for training andevaluating empirical NLP systems.

3. Be able to manipulate probabilities, construct statistical models over stringsand trees, and estimate parameters using supervised and unsupervised trainingmethods.

4. Apply NLP algorithms into Machine Learning Techniques.5. Be able to design, implement, and analyse NLP algorithms.

Course Contents:


Credits

I Introduction of NLP 30 1


77 | 9 1

Introduction to Natural Language Understanding; Thestudy of Language, Applications of NLP, EvaluatingLanguage Understanding Systems. Different levels ofLanguage Analysis; Representations andUnderstanding. Organization of Natural languageUnderstanding Systems. Linguistic Background. Anoutline of English syntax.

Hours

II

Knowledge Representation schemes in NLP

Introduction to semantics and knowledgerepresentation, Some applications, machinetranslation, database interface. Grammars andParsing, Grammars and sentence Structure, Top-Down and Bottom-Up Parsers, Top-Down ChartParsing. Transition Network Grammars.

Feature Systems and Augmented Grammars; BasicFeature system for English, Morphological Analysisand the Lexicon, Parsing with Features. AugmentedTransition Networks (ATN).

30Hours

1

III

Grammar and Parsing Techniques in NLP

Grammars for Natural Language, Auxiliary Verbs andVerb Phrases, Movement Phenomenon in Language.Handling questions in Context-Free Grammars.Human preferences in Parsing. Encoding uncertainty.Deterministic Parser.

30Hours

1

IV

Ambiguity Resolution and Probabilistic grammar

Ambiguity Resolution in NLP, Statistical Methods,Probabilistic Language Processing, EstimatingProbabilities. Part-of- Speech tagging. ObtainingLexical Probabilities. Probabilistic Context-FreeGrammars. Best First Parsing. Semantics and LogicalForm. Word senses and Ambiguity. EncodingAmbiguity in Logical Form.

30Hours

1


1. Akshar Bharti, Vineet Chaitanya and Rajeev Sangal, “NLP: A PaninianPerspective”, Prentice Hall, New Delhi.

2. James Allen, “Natural Language Understanding”, 2/e, Pearson Education,2003.

3. D. Jurafsky, J. H. Martin, “Speech and Language Processing”, PearsonEducation, 2002.

4. L.M. Ivansca, S. C. Shapiro, “Natural Language Processing and LanguageRepresentation”.


78 | 9 1

GE33245 Augmented & Virtual Reality

Course Objective:

1. To provide students with a solid background in alternative 3D compositingtechniques using computer vision with applications in interactive interfaces – mostnotably augmented reality interfaces on mobile devices.

2. Provide students with a comprehensive knowledge in 3D vision.

3. Develop skills in the design and development of interactive augmented realitygames

Learning Outcome:

At the end of the course, the student should be able to:.

1. Develop interactive augmented reality applications for both PC based mobiledevices using a variety of novel input devices.

2. Demonstrate a knowledge of the research literature in Augmented Reality for bothcompositing and interactive applications

Course Contents:


I

VIRTUAL REALITY AND VIRTUALENVIRONMENTS: The historical development ofVR: Scientific landmarks Computer Graphics, Real-time computer graphics, Flight simulation, Virtualenvironments, Requirements for VR, benefits ofVirtual reality.HARDWARE TECHNOLOGIES FOR 3D USERINTERFACES: Visual Displays Auditory Displays,Haptic Displays, Choosing Output Devices for 3DUser Interfaces.3D USER INTERFACE INPUT HARDWARE:Input device characteristics, Desktop input devices,Tracking Devices, 3D Mice, Special Purpose InputDevices, Direct Human Input, Home Brewed InputDevices, Choosing Input Devices for 3D Interfaces.

30Hours

1

II

SOFTWARE TECHNOLOGIES:Database - World Space, World Coordinate, WorldEnvironment, Objects - Geometry, Position /Orientation, Hierarchy, Bounding Volume, Scriptsand other attributes, VR Environment - VR Database,Tessellated Data, LODs, Cullers and Occluders,Lights and Cameras, Scripts, Interaction - Simple,Feedback, Graphical User Interface, Control Panel,2D Controls, Hardware Controls, Room / Stage / AreaDescriptions, World Authoring and Playback, VR

30Hours

1


79 | 9 1

toolkits, Available software in the market.

III

3D INTERACTION TECHNIQUES:3D Manipulation tasks, Manipulation Techniques andInput Devices, Interaction Techniques for 3DManipulation, Deign Guidelines - 3D Travel Tasks,Travel Techniques, Design Guidelines - TheoreticalFoundations of Wayfinding, User CenteredWayfinding Support, Environment CenteredWayfinding Support, Evaluating Wayfinding Aids,Design Guidelines - System Control, Classification,Graphical Menus, Voice Commands, GestrualCommands, Tools, Mutimodal System ControlTechniques, Design Guidelines, Case Study: MixingSystem Control Methods, Symbolic Input Tasks,symbolic Input Techniques, Design Guidelines,Beyond Text and Number entry .VIRTUAL REALITY APPLICATIONS:Engineering, Architecture, Education, Medicine,Entertainment, Science, Training.

30Hours

1

IV

Augmented and Mixed Reality, Taxonomy,technology and features of augmented reality,difference between AR and VR, Challenges with AR,AR systems and functionality, Augmented realitymethods, visualization techniques for augmentedreality, wireless displays in educational augmentedreality applications, mobile projection interfaces,marker-less tracking for augmented reality, enhancinginteractivity in AR environments, evaluating ARsystems.

30Hours

1


1. Alan B Craig, William R Sherman and Jeffrey D Will, “Developing VirtualReality Applications: Foundations of Effective Design”, Morgan Kaufmann,2009.

2. Gerard Jounghyun Kim, “Designing Virtual Systems: The Structured Approach”,2005.

3. Doug A Bowman, Ernest Kuijff, Joseph J LaViola, Jr and Ivan Poupyrev, “3DUser Interfaces, Theory and Practice”, Addison Wesley, USA, 2005.

4. Oliver Bimber and Ramesh Raskar, “Spatial Augmented Reality: Meging Realand Virtual Worlds”, 2005.

5. Burdea, Grigore C and Philippe Coiffet, “Virtual Reality Technology”, WileyInterscience, India, 2003.

6. John Vince, “Virtual Reality Systems”, Addison Wesley, 1995.7. Howard Rheingold, “Virtual Reality: The Revolutionary Technology and how it

Promises to Transform Society”, Simon and Schuster, 1991.


80 | 9 1

8. William R Sherman and Alan B Craig, “Understanding Virtual Reality: Interface,Application and Design (The Morgan Kaufmann Series in Computer Graphics)”.Morgan Kaufmann Publishers, San Francisco, CA, 2002

9. Alan B. Craig, Understanding Augmented Reality, Concepts and Applications,Morgan Kaufmann, 2013.

Generic Elective – V

GE33251 Data Compression

Course Objective:

1. To provide students with contemporary knowledge in Data Compression andCoding.

2. To equip students with skills to analyze and evaluate different DataCompression and Coding methods.

3. Student knows basic algorithms used in lossless and lossy compression.4. Student knows basic mathematical models used in lossless and lossy

compression.

Learning Outcome:


1. Display competence in the fundamental ideas of the lossless data compression.2. Demonstrate understanding of the underlying mathematical theory and

algorithms.3. Understand fundamental ideas of quantization and transform coding.4. Understand how lossless and lossy compression algorithms can be used for

solving scientific and engineering problems.

Course Contents:


Credits

I

Introduction

Compression Techniques: Lossless and LossyCompression, Measures of performance, Modelingand Coding; Mathematical Preliminaries for Losslesscompression: A brief introduction to informationtheory; Models: Physical models, Probability models,Markov models, Composite source model; Coding:Uniquely decodable codes, Prefix codes.

30Hours

1

II

Huffman and Arithmetic Coding

Huffman coding algorithm: Minimum varianceHuffman codes; Adaptive Huffman coding: Updateprocedure, Encoding procedure, Decoding procedure;Golomb codes, Rice codes, Tunstall codes

30Hours

1


81 | 9 1

Applications of Huffman coding: Lossless imagecompression, Text compression and AudioCompression

Arithmetic Coding: Introduction, Coding a Sequence,Generating a Tag, Deciphering a Tag, Comparison ofHuffman and Arithmetic Coding, Applications.

III

Dictionary Coding and Context BasedCompression

Dictionary Techniques: Introduction, StaticDictionary: Diagram Coding; Adaptive Dictionary:The LZ77Approach, TheLZ78Approach,Applications: File Compression-UNIX compress,Image Compression-Graphics Interchange Format(GIF) and Portable Network Graphics (PNG),Compression over modems-V.42 bits.

Context Based Compression: Introduction ,Prediction with Partial Match (ppm)-The basicalgorithm, The ESCAPE SYMBOL, Length ofcontext, The Exclusion Principle; The Burrows-Wheeler Transform: Move-to-front coding ,DynamicMarkov Compression.

Lossless image compression: Introduction, CALIC,JPEG-LS, Multi-resolution Approaches, FacsimileEncoding.

30Hours

1

IV

Mathematical Preliminaries for Lossy Coding,Scalar and Vector Quantization

Mathematical Preliminaries for Lossy Coding:Introduction, Distortion criteria, Models.

Scalar Quantization: Introduction, The QuantizationProblem, Uniform Quantizer, Adaptive Quantization,Non- uniform Quantization

Vector Quantization: Introduction, Advantages ofVector Quantization over Scalar Quantization, TheLinde -Buzo- Gray Algorithm, Tree structured VectorQuantizers.

30Hours

1


1. David Salomon, “Data Compression”, Springer Publication, 4th Edition.2. Khalid Sayood, “Introduction to Data Compression”, Morgan Kaufmann

Series, 3rd Edition


82 | 9 1

GE33252 Distributed System

Course Objective:

1. To learn issues related to clock synchronization and the need for global statein distributed system.

2. Have knowledge and understanding of the main principles, techniques andmethods involved when dealing with distributed systems.

3. To get the knowledge of how distributed objects communicate by means ofremote invocation.

4. To provide an in-depth overview of research topics in distributed systems.5. To learn distributed mutual exclusion and Deadlock detection algorithms.

Learning Outcome:


1. Understand the foundations and issues of distributed systems.2. Understand in detail how distributed applications work and what requirements

they aim to satisfy.3. Understand the various synchronization issues and global state for distributed

system.4. Understand in detail how distributed applications work and what architecture

they exhibit.5. Understand in detail how distributed applications work and what techniques

and infrastructures they are built upon.

Course Contents:


Credits

I

Introduction to distributed systems: Definitions andExamples of Distributed systems; System Models:Architectural models and Fundamental models;limitations of distributed systems.

Logical Clocks: Lamport’s clocks, Vector logicalclock, NTP; Message Passing System: Causalordering of messages, Sates of a Distributed system,Local and Global State, Consistent and inconsistentstates; Termination detection.

30Hours

1

II

Mutual Exclusion: Requirements of MutualExclusion, Classification of distributed mutualexclusion: Non-token based Quorum Based andToken Based mutual exclusion with examples;Performance metric for distributed mutual exclusionalgorithms.

Deadlock Detection: System models, Preliminaries,Deadlock prevention, Deadlock avoidance,Deadlock detection & resolution

Agreement Protocols: Classification of Agreement

30Hours

1


83 | 9 1

Problem: Byzantine agreement problem, Consensusproblem, Interactive consistency Problem; Solution toByzantine Agreement problem; Application ofAgreement problem.

III

Resource Management: Distributed File Systems,Issues in distributed File System.

Failure Recovery: Backward and Forward recovery,Recovery in Concurrent systems: Checkpoints;Recovery in Distributed Database Systems; FaultTolerance: Issues in Fault Tolerance, VotingProtocols.

Transaction Control: Nested Transactions, Locks;Concurrency Control: Methods and their comparison,Concurrency control in Distributed Transactions,Replication: Fault tolerant services, Transactionswith replicated data.

30Hours

1


1. Singhal & Shivaratri, “Advanced Concept in Operating Systems”, McGrawHill

2. Ramakrishna, Gehrke, “Database Management Systems”, McGrawhill3. Coulouris, Dollimore, Kindberg, “Distributed System: Concepts and Design”,

Pearson Education4. Tenanuanbaum, Steen, “Distributed Systems”, Prentice Hall of India5. Gerald Tel, “Distributed Algorithms”, Cambridge University Press

GE33253 Bioinformatics

Course Objective:

1. Study to develop methods and software tools for understanding biologicaldata.

2. To introduce students to the fundamentals of evolution, molecular biology,and molecular evolution.

3. To study DNA, RNA important molecules, protein data, etc. their structure,replication and transcription.

4. Study on biological databases which help in analyzing biological data andtheir interpretation.

5. Introduction of Perl programming for developing tools for genome sequencingand other applications.

Learning Outcome:

After completing the course, the students should be able to:

1. Have a good working knowledge of basic bioinformatics tools and databasessuch as GenBank, BLAST, multiple alignment, and phylogenetic treeconstruction.


84 | 9 1

2. Describe the contents and properties of the most important bioinformaticaldatabases, perform text- and sequence-based searches, and analyse and discussthe results in light of molecular biological knowledge.

3. Explain the major steps in pair wise and multiple sequence alignment, explainsthe principle for, and executes pair wise sequence alignment by dynamicprogramming.

4. give examples of methods for describing and analysing genes, genomes andgene expression

5. explain the major features of methods for modelling protein structures and useprograms for visualizing and analysing such structures

Course Contents:


I

Introduction

Bioinformatics objectives and overviews,Interdisciplinary nature of Bioinformatics, Dataintegration, Data analysis, Major Bioinformaticsdatabases and tools. Metadata: Summary & referencesystems, finding new type of data online. MolecularBiology and Bioinformatics: Systems approach inbiology, Central dogma of molecular biology,problems in molecular approach and thebioinformatics approach, Overview of thebioinformatics applications.

30Hours

1

II

The Information Molecules and Information Flow

Basic chemistry of nucleic acids, Structure of DNA,Structure of RNA, DNA Replication, -Transcription, -Translation, Genes- the functional elements in DNA,Analyzing DNA,DNA sequencing. Proteins: Aminoacids, Protein structure, Secondary, Tertiary andQuaternary structure, Protein folding and function,Nucleic acid-Protein interaction; Perl: Perl Basics,Perl applications for bioinformatics- Bioperl, LinuxOperating System, Understanding and UsingBiological Databases, Java clients, CORBA,Introduction to biostatics

30Hours

1

III

Nucleotide sequence data

Genome, Genomic sequencing, expressed sequencetags, gene expression, transcription factor bindingsites and single nucleotide polymorphism.Computational representations of molecularbiological data storage techniques: databases (flat,relational and object oriented), and controlledvocabularies, general data retrieval techniques:indices, Boolean search, fuzzy search and

30Hours

1


85 | 9 1

neighboring, application to biological datawarehouses.

IV

Biological data types and their specialrequirements

Sequences, macromolecular structures, chemicalcompounds, generic variability and its connection toclinical data. Representation of patterns andrelationships: alignments, regular expressions,hierarchies and graphical models.

30Hours

1


1. O’Reilly, “ Developing Bio informatics computer skills”, Indian Edition’spublication

2. Rastogi, Mendiratta, Rastogi, “Bioinformatics concepts, skills &Applications”, CBS Publishers

3. Rashidi, Hooman and Lukas K. Buehler, “Bioinformatics Basic Applications”CRC Press.

4. “Bioinformatics” , Addison Wesley5. Stephen Misner& Stephen Krawetz, “ Bioinformatics- Methods & Protocols”6. Cynthia Gibas and Per Jambeck, “Introduction to Bioinformatics computer

Skills”, 2001 SPD7. Atwood, “Introduction to Bioinformatics”, Person Education8. James Tisdall, “Beginning Perl for Bioinformatics”, SPD

GE33254 Pattern Recognition

Course Objective:

1. Learn the fundamental concepts and applications of pattern recognition.2. Learn the concepts of Bayes decision theory.3. Understand the concepts of linear and nonlinear classifiers.4. Understand the concepts of feature selection and generation techniques.5. Understand the concepts of supervised learning and system evaluation.6. Understand the concepts of unsupervised learning and clustering algorithms.7. Develop some applications of pattern recognition.

Learning Outcome:


1. Understand the fundamental pattern recognition and machine learning theories.2. Design and implement certain important pattern recognition techniques.3. Applying the pattern recognition theories to applications of interest.4. Design systems and algorithms for pattern recognition (signal classification),

with focus on sequences of patterns.5. Analyze classification problems probabilistically and estimate classifier

performance.


86 | 9 1

Course Contents:


I

Introduction to Pattern Recognition, Basics of patternrecognition, Design principles of pattern recognitionsystem, Learning and adaptation, Pattern recognitionapproaches, Mathematical foundations – Linear algebra,Probability Theory, Expectation, mean and covariance,Normal distribution, Multivariate normal densities, Chisquared test.

30Hours

1

IIStatistical Patten Recognition, Bayesian DecisionTheory, Classifiers, Normal density, Discriminantfunctions.

30Hours

1

III

Parameter Estimation Methods, Maximum-Likelihoodestimation, Bayesian Parameter estimation, Dimensionreduction methods, Principal Component Analysis(PCA),Fisher Linear discriminate analysis, Expectation-maximization (EM),Hidden Markov Models(HMM),Gaussian mixture models

30Hours

1

IV

Nonparametric Techniques and Unsupervised Learning,Density Estimation, Parzen Windows, K-NearestNeighbor Estimation, Nearest Neighbor Rule, Fuzzyclassification, Clustering, Criterion functions forclustering, Clustering Techniques, Iterative square -error partitioned clustering – K means, Agglomerativehierarchical clustering, Cluster validation.

30Hours

1


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

2. C. M. Bishop, “Pattern Recognition and Machine Learning”, Springer, 2009.3. S. Theodoridis and K. Koutroumbas, “Pattern Recognition”, 4th Edition,

Academic Press, 2009.

GE33255 Deep Learning

Course Objective:1. Deep learning is a class of machine learning algorithms which enables computers to

learn from examples.2. Deep learning techniques have been used successfully for variety of applications,

including: automatic speech recognition, image recognition, natural languageprocessing, drug discovery, and recommendation systems.

3. In this course, students will learn the fundamentals of deep learning, and the mainresearch activities in this field.

4. Students will also learn to implement, train, and validate their own neural network,


87 | 9 1

and they will improve their understanding of the on-going research in computer visionand multimedia field.

Learning Outcome:Knowledge and understanding

1. To understand the fundamentals of deep learning.2. To know the main techniques in deep learning and the main research in this field.

Applying knowledge and understanding1. Be able to design and implement deep neural network systems.2. Be able to identify new application requirements in the field of computer vision.

Course Contents:


Credits

I

INTRODUCTION :Introduction to machine learning- Linear models(SVMs and Perceptrons, logistic regression)- Intro toNeural Nets: What a shallow network computes-Training a network: loss functions, back propagationand stochastic gradient descent- Neural networks asuniversal function approximates.

30Hours

1

II

DEEP NETWORKS :History of Deep Learning- A Probabilistic Theory ofDeep Learning- Backpropagation and regularization ,batch normalization- VC Dimension and Neural Nets-Deep Vs Shallow Networks-Convolutional Networks-Generative Adversarial Networks (GAN),Semisupervised Learning.

30Hours

1

III

DIMENTIONALITY REDUCTION9 Linear (PCA, LDA) and manifolds, metric learning –Auto encoders and dimensionality reduction innetworks - Introduction to Convnet - Architectures –AlexNet, VGG, Inception, ResNet - Training aConvnet: weights initialization, batch normalization,hyper parameter optimization

30Hours

1

IV

OPTIMIZATION AND GENERALIZATION:Optimization in deep learning– Non-convexoptimization for deep networks- StochasticOptimization Generalization in neural networks- SpatialTransformer Networks- Recurrent networks, LSTM -Recurrent Neural Network Language Models- Word-Level RNNs & Deep Reinforcement Learning -Computational & Artificial Neuroscience

30Hours

1


88 | 9 1


1. Cosma Rohilla Shalizi, “Advanced Data Analysis from an Elementary Point ofView”, 2015.

2. Deng & Yu, “Deep Learning: Methods and Applications”, Now Publishers,2013.

3. Ian Goodfellow, Yoshua Bengio, Aaron Courville, “Deep Learning”, MITPress, 2016.

4. Michael Nielsen, “Neural Networks and Deep Learning”, DeterminationPress, 2015.

Open Elective-II

OE33221 Human Computer Interaction

Course Objective:

1. Learn basic concepts of designing of interface devices.2. Recognize how a computer system may be modified to include human

diversity.3. Select an effective design style for a specific application.4. Demonstrate an understanding of guidelines, principles, and theories

influencing human computer interaction.5. Learn the different levels of interfacing devices for the purpose of human

easiness.

Learning Outcome:


1. Design mock ups and carry out user and expert evaluation of interfaces.2. Carry out the steps of experimental design, usability and experimental testing,

and evaluation of3. Human computer interaction systems.4. Use the information sources available, and be aware of the methodologies and

technologies5. Supporting advances in HCI.6. Able to build a basic prototype of interactive devices.

Course Contents:


Credits

I

Essentials and framework for designing interactivesystems

Essentials of designing interactive systems.Designing interactive systems; A fusion of skills.PACT: A framework for designing interactivesystems; Peoples, Activities, Contexts, Technologies.The process of human-centred interactive systemsdesign. Usability. Experience design. The Home

30Hours

1


89 | 9 1

Information Centre (HIC); A case study in designinginteractive systems.

II

Techniques for designing interactive Systems

Techniques for designing interactive systems;Understanding, Environment, Design, Evaluation,Task analysis. Contextual Design; The contextualinterview and work modeling; From models todesign. Interface design; Visual Aspects,Multimodality, Mixed Reality.

30Hours

1

III

Interface Designing of interactive systems

Design process; Human interaction with computers,Importance of human characteristics, Humanconsideration. Human interaction speeds.Understanding business junctions. Components ofinterface;

Text and messages. Icons and increases in interface;Multimedia, Colors, Uses problems, Choosing colors.

30Hours

1

IV

Contexts for designing interactive systems andIntroduction to Windows

Contexts for designing interactive systems; Designingwebsites, Web 2.0. CSCW; working in groups.Agents and avatars. Ubiquitous computing. Mobilecomputing. Screen Designing; Design goals – Screenplanning and purpose, organizing screen elements,ordering of screen data and content. Technologicalconsideration in interface design. Foundations ofdesigning interactive systems; Memory and attention;Emotion and affective computing, Cognition andaction,

Social interaction, Perception and navigation.Introduction of Windows; New and Navigationschemes selection of window,

Selection of devices based and screen based controls.

30Hours

1


1. David Benyon, “Designing Interactive Systems: A comprehensive guide toHCI and interaction design”, (Second Edition), Pearson Education Limited,2010.

2. Andrew Sears, Julie A. Jacko, “The Human-Computer Interaction Handbook:Fundamentals”.

3. “Evolving Technologies and Emerging Applications", Second Edition, CRCPress, 2007


90 | 9 1

4. Wilbert O Galitz, “The essential guide to user interface design”, WileyDreamaTech.

5. Ben Shneidermann, “Designing the user interface”; 3rd Edition, PearsonEducation Asia.

BCS3851 Digital Image Processing Lab

Tools/Software used: MATLAB


Implement the following on MATLAB-

1. Display of Gray scale Images.2. Histogram Equalization.3. Design of Non-linear Filtering4. Determination of Edge detection using Operators.5. 2-D DFT and DCT.6. Filtering in frequency domain.7. Display of colour images.8. Conversion between colour spaces.9. DWT of images.10. Segmentation using watershed transform.