DETAILED SYLLABUS

COGNITIVE ROBOTICS

Year Semester Hours/Week Marks Total
C CIE SEE

L T P/D

2 - 2 3 40 60 100

Pre-requisite Nil

UNIT-I
CYBERNETIC VIEW OF ROBOT COGNITION AND PERCEPTION: Introduction to
the Model of Cognition,Visual Perception,Visual Recognition, Machine Learning, Soft
Computing Tools and Robot Cognition.
UNIT-II
MAP BUILDING: Introduction, Constructing a 2D World Map,Data Structure for Map
Building,Explanation of the Algorithm, An Illustration of Procedure Traverse Boundary, An
Illustration of Procedure Map Building ,Robot Simulation, Execution of the Map Building
Program. (12)
UNIT-III
RANDOMIZED PATH PLANNING: Introduction, Representation of the Robot‘s
Environment, Review of configuration spaces, Visibility Graphs, Voronoi diagrams, Potential
Fields and Cell Decomposition, Planning with moving obstacles, Probabilistic Roadmaps,
Rapidly exploring random trees,Execution of the Quadtree-Based Path Planner Program. (9)
UNIT-IV
SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM): Problem
Definition,Mathematical Basis, Example: SLAM in Landmark Worlds,Taxonomy of the
SLAM Problem, Extended Kalman filter, Graph-Based Optimization Techniques,Particle
MethodsRelation of Paradigms. (12)
UNIT-V
ROBOT PROGRAMMING PACKAGES: Robot Parameter Display,Program for
BotSpeak,Program for Sonar Reading Display, Program for Wandering Within the
Workspace,Program for Tele-operation, A Complete Program for Autonomous Navigation.

TEXT BOOKS:
1. Patnaik, Srikanta, "Robot Cognition and NavigationAn Experiment with Mobile Robots",

Springer-Verlag Berlin and Heidelberg, 2007.

2. Howie Choset, Kevin LynchSeth Hutchinson, George Kantor, Wolfram Burgard, Lydia
Kavraki, and Sebastian Thrun, ―Principles of Robot Motion-Theory, Algorithms, and
Implementation‖, MIT Press, Cambridge, 2005.

REFERENCES:
1. Sebastian Thrun, Wolfram Burgard, Dieter Fox, ―ProbabilisticRobotics‖, MIT Press,

2005.

2. Margaret E. Jefferies and Wai-Kiang Yeap, "Robotics and Cognitive Approaches to
Spatial Mapping", Springer-Verlag Berlin Heidelberg 2008.

151

MACHINE LEARNING FOR SIGNAL PROCESSING

Year Semester Hours/Week Marks Total
C CIE SEE

L T P/D

2 - 2 3 40 60 100

Pre-requisite Continuous And Discrete Time Signals And Systems,
Machine Learning

UNIT-I
Introduction to real world signals - text, speech, image, video. Feature extraction and front-
end signal processing - information rich representations, robustness to noise and artifacts.

UNIT-II
Basics of pattern recognition, Generative modeling - Gaussian and mixture Gaussian models,
hidden Markov models.

UNIT-III
Discriminative modeling - support vector machines, neural networks and back propagation.

UNIT-IV
Introduction to deep learning - convolutional and recurrent networks, pre-training and
practical considerations in deep learning, understanding deep networks.

UNIT-V
Deep generative models - Autoencoders, Boltzmann machines, Adverserial Networks,
Variational Learning. Applications in NLP, computer vision and speech recognition.

TEXTBOOKS
1. “Pattern Recognition and Machine Learning”, C.M. Bishop, 2nd Edition, Springer, 2011.
2. “Neural Networks”, C.M. Bishop, Oxford Press, 1995.
3. “Deep Learning”, I. Goodfellow, Y, Bengio, A. Courville, MIT Press, 2016.
4. “Fundamentals of speech recognition”, L. Rabiner and H. Juang, Prentice Hall, 1993.

REFERENCES
1. “Deep Learning : Methods and Applications”, Li Deng, Microsoft Technical Report.
2. “Automatic Speech Recognition - Deep learning approach” - D. Yu, L. Deng, Springer,

2014.
3. “Machine Learning for Audio, Image and Video Analysis”, F. Camastra, Vinciarelli,

Springer, 2007.

152

MOBILE ROBOTICS

Year Semester Hours/Week Marks SEE Total
C CIE 60 100

L T P/D

2- 23 40

Pre-requisite Machine Learning for Robotics

COURSE OBJECTIVES
1. Movement and communication of mobile robots.
2. Localization, navigation and control of mobile robots.

UNIT-I
Mobile Robots: Introduction to Wheeled Robots, Classification of wheels, Fixed wheel,
Centered Oriented Wheel, Off-centered oriented wheel, Swedish wheel, Mobile robot
locomotion, Differential Wheel, Tricycle, Synchronous drive, Omni-directional, Ackerman
Steering, Kinematics models of WMR.

UNIT-II
Mobile Robot Kinematics: Kinematic Models and Constraints: Representing robot position,
Forward kinematic models, Wheel kinematic constraints, Robot kinematic constraints.
Mobile Robot Maneuverability: Degree of mobility, Degree of steerability, Robot
maneuverability. Mobile Robot Workspace: Degrees of freedom, Holonomic robots, Path and
trajectory considerations, Beyond Basic Kinematics, Motion Control (Kinematic Control):
Open loop control (trajectory-following), Feedback control.

UNIT-III
Perception: Sensors for Mobile Robots: Sensor classification, Characterizing sensor
performance, Wheel/motor sensors, Heading sensors, Ground-based beacons, Active ranging,
Motion/speed sensors, Vision-based sensors. Representing Uncertainty: Statistical
representation, Error propagation: combining uncertain measurements, Feature Extraction:
Feature extraction based on range data (laser, ultrasonic, vision-based ranging), Visual
appearance based feature extraction.

UNIT-IV
Mobile Robot Localization: Introduction, Localization: Noise, Aliasing, LocalizationBased
Navigation, Programmed Solutions, Belief Representation, Map Representation: Continuous
representations, Decomposition strategies, Challenges in map representation. Probabilistic
Map-Based Localization: Markov localization, Kalman filter localization, Landmark-based
navigation, Positioning beacon systems, Route-based localization, Autonomous Map
Building, The stochastic map technique.

UNIT-V
Planning and Navigation: Introduction, Competences for Navigation: Planning and Reacting:
Path planning, Obstacle avoidance, Navigation Architectures: Modularity for code reuse and

153

sharing, Control localization, Techniques for decomposition, Introduction to IoT. Case
studies: ESP32 based Mobile Robot.
REFERENCES
1. Siegwart, Roland, Illah Reza Nourbakhsh, and DavideScaramuzza. “Introduction to

autonomous mobile robots “,MIT press, 2011.
2. H.R.Everett, “Sensors for Mobile Robots – Theory and Applications”, A.K.Peteres Ltd.

ISBN 1-56881- 048-2. 1995.
3. Siegwart, Roland, Illah Reza Nourbakhsh, and DavideScaramuzza. “Introduction to

autonomous mobile robots”. MIT press, 2011.
4. Kurfess, Thomas R., ed.“Robotics and automation handbook”. CRC press, 2004.
5. David Poole, Alan Mackworth “Artificial Intelligence: Foundations of Computational

Agents”, Cambridge University Press, 2010.
6. “Where am I? Sensors and Methods for Mobile Robot Positioning”, J. Borenstein, et al.,

The University of Michigan, 1996.
7. Janakiraman P.A, “Robotics and Image Processing”, Tata McGraw-Hill, 1995.
8. Siciliano, Bruno, and OussamaKhatib, eds. “Springer handbook of robotics”. Springer,

2016.

154

VIRTUAL REALITY

Year Semester Hours/Week C Marks SEE Total
L T P/D CIE 60 100

2- 23 40

Pre-requisite Deep Learning for Computer Vision

COURSE OUTCOMES
At the end of the course, the students will be able to:
1. Understand geometric modelling and Virtual environment.
2. Study about Virtual Hardware and Software
3. Develop Virtual Reality applications.

UNIT-I
Introduction to Virtual Reality: Virtual Reality and Virtual Environment: Introduction,
Computer graphics, Real time computer graphics, Flight Simulation, Virtual environment
requirement, benefits of virtual reality, Historical development of VR, Scientific Landmark
3D Computer Graphics: Introduction, The Virtual world space, positioning the virtual
observer, the perspective projection, human vision, stereo perspective projection, 3D
clipping, Colour theory, Simple 3D modelling, Illumination models, Reflection models,
Shading algorithms, Radiosity, Hidden Surface Removal, Realism-Stereographic image.

UNIT-II
Geometric Modelling: Geometric Modelling: Introduction, From 2D to 3D, 3D space
curves, 3D boundary representation Geometrical Transformations: Introduction, Frames of
reference, Modelling transformations, Instances, Picking, Flying, Scaling the VE, Collision
detection Generic VR system: Introduction, Virtual environment, Computer environment, VR
technology, Model of interaction, VR Systems.

UNIT-III
Virtual Environment: Animating the Virtual Environment: Introduction, The dynamics of
numbers, Linear and Nonlinear interpolation, the animation of objects, linear and non-linear
translation, shape & object in betweening, free from deformation, particle system. Physical
Simulation: Introduction, Objects falling in a gravitational field, Rotating wheels, Elastic
collisions, projectiles, simple pendulum, springs, Flight dynamics of an aircraft.

UNIT-IV
VR Hardware and Software: Human factors: Introduction, the eye, the ear, the somatic
senses. VR Hardware: Introduction, sensor hardware, Head-coupled displays, Acoustic
hardware, Integrated VR systems. VR Software: Introduction, Modelling virtual world,
Physical simulation, VR toolkits, Introduction to VRML

UNIT-V
VR Applications: Introduction, Engineering, Entertainment, Science, Training. The Future:
Virtual environment, modes of interaction

155

TEXT BOOKS
1. John Vince, “Virtual Reality Systems “, Pearson Education Asia, 2007.
2. Anand R., “Augmented and Virtual Reality”, Khanna Publishing House, Delhi.
4. Adams, “Visualizations of Virtual Reality”, Tata McGraw Hill, 2000.
5. Grigore C. Burdea, Philippe Coiffet , “Virtual Reality Technology”, Wiley Inter Science,

2nd Edition, 2006.
6. William R. Sherman, Alan B. Craig, “Understanding Virtual Reality: Interface,
7. Application and Design”, Morgan Kaufmann, 2008.
8. www.vresources.org
9. www.vrac.iastate.edu
10. www.w3.org/MarkUp/VRM

156

REAL TIME COMPUTER VISION WITH OPEN CV

Year Semester Hours/Week Marks Total
C CIE SEE 100

L T P/D

2 - 2 4 40 60

Pre-requisite Deep Learning for Computer Vision

UNIT I
INTRODUCTION TO OPENCV: Displaying a picture - playing a Video-Moving around-
Simple Transformation-getting input and writing to AVI from camera -OpenCV Primitive
Data Types-CvMat Matrix Structure-Ipl Image Data Structure- Matrix and Image Operators-
Drawing Things.

UNIT II
IMAGE PROCESSING AND TRANSFORMS: Smoothing- Image Morphology- Flood Fill-
Resize- Image Pyramids – Image Transforms: Convolution- Gradients and Sobel Derivatives-
Laplace- Canny- Hough Transforms- Remap- Stretch- Shrink- Warp- and Rotate- Cart to
Polar and Polar to Cart-Log Polar- DFT- DCT- Integral Images- Distance Transform-
Histogram Equalization Threshold.

UNIT III
CONTOURS, SEGMENTATION, TRACKING AND MOTION: Parts and Segments-
Background Subtraction- Watershed Algorithm Image Repair by Inpainting - The Basics of
Tracking- Corner Finding-Subpixel Corners- Invariant Features- Optical Flow-Mean-Shift
and Camshift Tracking.

UNIT IV
CAMERA CALIBRATION AND 3D VISION: Camera Model- Calibration-Undistortion-
Rodrigues Transform – Projection - 3D Pose Estimation- Stereo Imaging- Structure from
Motion- Fitting Lines in Two and Three Dimensions.

UNIT V
MACHINE LEARNING: Introduction - Mahalanobis Distance-K-Means- Naïve/Normal
Bayes Classifier- Binary Decision Trees- Face Detection or Haar Classifier- Other Machine
Learning Algorithms

REFERENCES:
1. Jayneil Dalal & Sohil Patel ―Instant OpenCV Starter: Get Started With OpenCV Using

Practical Hands-On Projects‖,Shroff/Packt, First edition, 2013.
2. Daniel Lelis Baggio, Shervin Emami& et al., ―Mastering OpenCV with Practical

Computer Vision Projects‖, Packt Publishing Limited, 2012.

157

COMPUTATIONAL NEURO SCIENCE

Year Semester Hours/Week Marks SEE Total
C CIE 60 100

L T P/D

2- 23 40

Pre-requisite Mathematics

COURSE OUTCOMES:
At the end of this course, learners will be able to:
1. To Design Models of single neurons , and small networks
2. Implementation of all simple as well as more complex numerical computations with few

neurons.
3. Analyse connected networks in the mean-field limit
4. Formalize biological facts into mathematical models
5. Understand a simple mathematical model of memory formation in the brain
6. Understand a simple mathematical model of decision processes

UNIT-I
History of Computational Neuroscience, Four components of Neural Signaling, From
artificial neural network to realistic neural networks - Introduction Memory Classification
Scheme – Declarative, Non-declarative Hebbian Learning-Hebbian versus Perceptron
Learning

UNIT-II
Models in Computational Neuroscience Four components of Neural Signaling Modelling the
ventral stream Auto-associative network and hippo campus - Learning and retrieval phase
Learning by Error Minimization, Computational Theory of the Brain Neurotransmission
Modelling the dorsa and auditory stream Point-attractor neural networks - Network dynamics
and training Gradient Descent Learning

UNIT-III
Biological Background Population dynamics Mechanical behavior of ceramics-flexural
strength -The Perceptron, Signal-to-noise analysis - Noisy weights and dilued attractor
networks Stabilizing Hebbian Learning, Basic synaptic mechanisms and dendritic processing
Modeling the average behavior of neurons Mapping function Sparse attractor neural networks
and correlated patterns-Sparse patterns and expansion recoding Principal Component
Analysis (PCA)- Eigenvectors-Eigen values Covariance matrix

UNIT-IV
The generation of action potentials Hodgkin Multi-layer Perceptron Control of sparseness in
attractor networks Singular Value Decomposition, Stimulation and rising phase Modeling the
average behavior of neurons Back-propagation – Initution , Derivation Chaotic networks-
Attractors Limits and Extensions of PCA

158

UNIT-V
Peak and falling phase Huxley Model Back-propagation –Loss Function Lyapunov functions
- The Cohen Grossberg theorem Variations of Hebbian Learning, After hyperpolarization and
Refractory Period Spiking neuron models - Single Back-propagation – Limitation
Asymmetrical networks Nonlinear Hebbian learning
LEARNING RESOURCES
1. Thomas Trappenberg, ―Fundamentals of Computational Neuroscience‖, Oxford

University Press, January2010
2. Peter Dayan & LF Abbot, ―Theoretical Neuroscience: Computational and Mathematical

Modeling of Neural Systems‖, MIT Pres,2005
3. Richard S. Sutton and Andrew G. Barto, ―Reinforcement Learning-An Introduction‖,2nd

Edition,The MIT Press,2018

159

ADVANCED ALGORITHMS

Year Semester Hours/Week Marks SEE Total
C CIE 60 100

L T P/D

2- 23 40

Pre-requisite Introduction to Programming

OBJECTIVES
1. To integrate the parallel and sequential algorithms.
2. Design and analysis of paradigms for sequential and parallel models.

UNIT I
INTRODUCTION TO ALGORITHMS: Introduction to Preliminaries - Design and
Analysis Fundamentals - Mathematical Tools for Algorithm Analysis - Trees and
Applications to Algorithms - More on Sorting Algorithms - Probability and Average
Complexity of Algorithms.

UNIT II
DESIGN STRATEGIES: Major Design Strategies - The Greedy Method – Divide and
Conquer - Dynamic Programming - Backtracking and Branch and Bound.

UNIT III
GRAPH AND NETWORK ALGORITHMS: Graph and Network Algorithms - Graphs
and Digraphs - Minimum Spanning Tree and Shortest-Path Algorithms - Graph Connectivity
and Fault-Tolerance of Networks - Matching and Network Flow Algorithms.

UNIT IV
PARALLEL AND DISTRIBUTED ALGORITHMS: Parallel and Distributed Algorithms
- Introduction to Parallel Algorithms and Architectures - Parallel Design Strategies - Internet
Algorithms -Distributed Computation Algorithms - Distributed Network Algorithms.

UNIT V
SEARCH ALGORITHMS: String Matching and Document Processing - Balanced Search
Trees - The Fast Fourier Transform - Heuristic Search Strategies: A* - Search and Game
Trees 24 - Probabilistic and Randomized Algorithms - Lower-Bound Theory - NP-Complete
Problems - Approximation Algorithms.

REFERENCES
1. Kenneth A. Berman, Jerome L. Paul , “Algorithms: Sequential, Parallel, and Distributed”,

Amazon Bestsellers, 2004.
2. Russ Miller, Laurence Boxer, “Algorithms Sequential and Parallel: A Unified Approach”,

Prentice Hall, 1 edition, 1999.
3. Dimitri P. Bertsekas and John N. Tsitsiklis, “Parallel and Distributed Computation:

Numerical Methods”, Prentice Hall, 1989.

160

ADVANCED COMPUTER NETWORKS

Year Semester Hours/Week Marks SEE Total
C CIE 60 100

L T P/D

2- 23 40

Pre-requisite Computer Networks

COURSE OUTCOMES
1. Introducing the fundamentals of conventional networking and software defined

networking
2. Implementation of software defined networks using Mininet and raspberry pi.
3. Understanding network management and security in software defined networks and

network data analysis using AI and ML algorithms

UNIT I
MODERN NETWORKING: Cloud Computing - Internet of Things - Types of Network
and Internet Traffic - Demand: Big Data, Cloud Computing, and Mobile Traffic -
Requirements: QoS and QoE - Routing Congestion Control - SDN and NFV - Modern
Networking Elements

UNIT II
SOFTWARE DEFINED NETWORKS: Network Requirements - The SDN Approach -
SDN- and NFV-Related Standards - SDN Data Plane - OpenFlow Logical Network Device -
OpenFlow Protocol - SDN Control Plane Architecture - REST API - SDN Application Plane
Architecture

UNIT III
VIRTUALIZATION: Background and Motivation for NFV - Virtual Machines - NFV
Concepts - NFV Reference Architecture - NFV Infrastructure - Virtualized Network
Functions - NFV Management and Orchestration - NFV Use Cases - SDN and NFV

UNIT IV
THE INTERNET OF THINGS: COMPONENTS: The IoT Era - Scope of the Internet of
Things - Components of IoT-Enabled Things - IoT World Forum Reference Model - ITU-T
IoT Reference Model - IoTivity - Cisco IoT System - ioBridge - SDN and NFV over IoT
Deployment

UNIT V
SECURITY: Security Requirements - SDN Security - NFV Security - ETSI Security
Perspective - IoT Security - The Patching Vulnerability - IoT Security and Privacy
Requirements Defined by ITU-T - An IoT Security Framework - The Impact of the New
Networking on IT Careers

161

REFERENCES
1. “Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud” William

Stallings Publisher: Addison-Wesley 2015 ISBN: 9780134175393
2. SDN and NFV Simplified: A Visual Guide to Understanding Software Defined Networks

and Network Function Virtualization 1st Edition by Jim Doherty
3. Network Function virtualization with a touch of sdn by Paresh Shah, Syed Farrukh

Hassan, RajendraChayapathi 4. Software Defined Networks A Comprehensive Approach
Ist Edition by Paul Goransson Chuck Black

162

MICROWAVE ENGINEERING

Year Semester Hours/Week C CIE Marks Total
L T P/D SEE 100
60
2- 23 40

Pre-requisite Electromagnetic Waves and Transmission Lines

COURSE OUTCOMES:
At the end of the coursework, the student will develop the ability to
1. Apply the concepts of electric and magnetic fields to analyze the modes and

characteristics of microwaves.
2. Explore the passive microwave devices using scattering matrices.
3. Investigate the active microwave devices using performance metrics.
4. Measure and analyze the various parameters of microwave devices.

UNIT – I
Microwave Transmission Lines: Introduction to Microwaves, Microwave regions and
bands, Applications, Rectangular Waveguides-Solution of Wave Equations in Rectangular
Coordinates, TE/TM mode analysis, Expressions for Fields, Characteristics Equation and cut-
off Frequencies, Dominant and Degenerate Modes, Sketches of TE and TM mode fields in
the cross-section.

UNIT – II
Waveguide Components: Microwave Multi port Junctions – E-plane Tee, H-plane Tee, and
Magic Tee, Directional coupler, Ferrites – Composition, Faraday rotation, Ferrite
components- Gyrator, isolator, and Circulator. Scattering Matrix – Significance, formulation
and properties, S-matrix of waveguide Tee junctions, Directional Coupler, Circulator, and
Isolator.

UNIT – III
Microwave Tubes: Limitations and losses of conventional tubes at Microwave frequencies
O-Type Tubes: 2 cavity Klystrons – structure, velocity modulation process, and Applegate
diagram, Bunching process, and Small Signal Theory - Expressions for output Power and
Efficiency. Reflex Klystrons-structure, velocity modulation, and Applegate diagram,
Mathematical Theory of Bunching, Power output, Efficiency.

UNIT-IV
M-Type Tubes and microwave solid state devices: : Cylindrical Traveling Wave
Magnetron – Hull cut-off condition, PI-mode, and its separation.
Gunn diode-principle, RWH theory, modes of operation and characteristics, Avalanche
Transit Time Devices-Introduction of IMPATT diodes and TRAPATT diodes.

UNIT – V

163

Microwave Measurements: Description of Microwave Bench - Different blocks and their
Features, Precautions; Microwave Power Measurement – Bolometer, Measurement of
Attenuation, Frequency, and VSWR.
TEXTBOOKS:
1. Microwave Devices and Circuits – by Samusel Y. Liao. PHI
2. Microwave Principles – by Herbert J.Reich J.G. Skolnik, P.F. Ordung,and H.L. Krauss,

AffiliatedEast-West Press Pvt., Ltd., New Delhi
3. Foundations for Microwave Engineering – by R.E. Collins, McGraw Hill Publication
4. Electronic and Radio Engineering – by Frederic E. Terman, McGraw Hill Publication
5. Microwave Engineering, Pozar, Wiley.
REFERENCE BOOKS:
1. Microwave and Radar Engineering – by M. Kulkarni
2. Electronic Communications Systems – by George Kennedy, McGraw Hill Publication
3. Microwave Engineering – by Annapurna Das and S.K. Das, Tata McGraw Hill
4. Microwave Engineering, M.L. Sisodiya, New Age

164

DIGITAL SIGNAL PROCESSORS AND ARCHITECTURE

Hours/Week Marks

Year Semester L T P/D C CIE SEE Total
100
2- 23 40 60

Pre-requisite Continuous And Discrete Time Signals And Systems, Microcontrollers
for Embedded Systems

COURSE OUTCOMES:
At the end of the course, the students will develop ability to
6. List out the various computational errors in DSP.
7. Differentiate various programmable architectures.
8. Apply programming of TMS320C54XX processors.
9. Interpret various DSP interfacing techniques.
10. Design different applications of programmable DSP devices.

UNIT –I
Computational Accuracy in DSP Implementations: Number formats for signals and
coefficients in DSP systems, Dynamic Range and Precision, Sources of error in DSP
implementations.

UNIT –II
Architectures for Programmable DSP Devices: Basic Architectural features, DSP
Computational Building Blocks, Bus Architecture and Memory, Data Addressing
Capabilities, Address Generation UNIT, Programmability and Program Execution, Speed
Issues, Features for External interfacing.

UNIT -III
Programmable Digital Signal Processors: Commercial Digital signal-processing
Devices, Data Addressing modes of TMS320C54XX DSPs, Data Addressing modes of
TMS320C54XX Processors, Memory space of TMS320C54XX Processors, Program
Control, TMS320C54XX Instructions and Programming, On-Chip Peripherals, Interrupts
of TMS320C54XX Processors, Pipeline Operation ofTMS320C54XX Processors.

UNIT –IV
Interfacing Memory and I/O Peripherals to Programmable DSP Devices: Memory
interface, Parallel I/O interface, Programmed I/O, Interrupts and I/O, Direct memory access
(DMA),MCBSP, CODEC interface circuit.

UNIT –V
Applications of Programmable DSP Devices:
DSP Based Biotelemetry Receiver- Pulse Position Modulation(PPM),Decoding Scheme
for the PPM Receiver, Biotelemetry Receiver Implementation, ECG Signal Processing for
heart rate Determination, A Speech Processing System.

165

TEXT BOOKS:
3. Avtar Singh and S Srinivasan, “Digital Signal Processing”, Thomson Publications, 2004.
4. B Venkata Ramani and M Bhaskar, “Digital Signal Processors,

Architecture, Programming and Applications”, TMH, 2004.
REFERENCE BOOKS:
4. Jonatham Stein, “Digital Signal Processing”, JohnWiley, 2005.
5. V.Udayshankara, “Modern Digital Signal Processing”, PHI Publication, 2nd Edition.
6. Richard G Lyons, “Understanding Digital Signal Processing”, Pearson, New

Delhi, 2nd Edition, 2004.

166

SPEECH AND LANGUAGE PROCESSING USING DEEP LEARNING

Year Hours/Week C Marks
Semester CIE SEE Total

L T P/D

3 - 2 4 40 60 100

Prerequisite : NIL

COURSE OUTCOMES:
4. Understanding the acoustics of speech production and perception
5. Analyzing efficient speech features used for modelling
6. Understanding various algorithms on Deep learning based Speech modelling
UNIT I
Overview of Speech Processing Systems, Speech Production, Speech Perception, Speech
Signal Characteristics, Sounds (Syllables, Phonemes, etc.), and Properties of speech sounds.
Introduction to speech technology:
Fundamentals of speech perception and speech production. Speech spectrum: STFT,
Spectrogram. Features: Cepstrum, MFCC, Pitch. Techniques: Vector Quantizers, Gaussian
Mixture Models.
UNIT II
Deep Learning:
Introduction to deep learning, neural nets, learning algorithms, momentum and RMSProp,
regularization, word embeddings, recursive neural networks. Applications to Natural
Language Processing.
UNIT III
Automatic speech recognition:
Pattern matching. Dynamic time warping Hidden Markov models. Isolated word recognition
Large vocabulary continuous ASR: Acoustic modelling. Language modelling Deep Learning
for language modelling and automatic speech recognition. Toolkits
UNIT IV
Speech synthesis:
Linguistic processing. Prosody modelling, Waveform generation. Concatenation and
statistical methods. Deep learning in speech synthesis.
UNIT V
Machine Translation.
Introduction to Machine Translation, Statistical Machine Translation, Neural Machine
Translation, Speech translation.
TEXT BOOKS
1. Goodfellow, I.; Bengio, Y.; Courville, A. Deep Learning [on line]. Cambridge,

Massachusetts: MIT Press, 2016 [Consultation: 22/06/2016]. Available on:
http://www.deeplearningbook.org/. ISBN 9780262035613.
2. Huang, X.; Acero, A.; Hon, H-W. Spoken language processing: a guide to theory,
algorithm and system development. Upper Saddle River: Prentice Hall, 2001. ISBN
0130226165.

167

DATA COMMUNICATION AND NETWORKS

Year Semester Hours/Week Marks Total
C CIE SEE 100

L T P/D

IV I 2 - 2 3 40 60

Pre-requisite Analog and Digital Communication

COURSE OUTCOMES
At the end of the course, the students will develop ability to
6. Describe the architecture of computer communication networks.

7. Analyze various multiplexing and switching techniques in physical layer

8. Apply error detection and correction methods in data link layer

9. Analyze various routing algorithms used in computer networks.

10. Apply different algorithms for congestion control and quality of service

UNIT I
Introduction to networks, internet, protocols and standards, the OSI model, layers in OSI
model, TCP/IP suite, Addressing.
UNIT II
Physical Layer
Digital transmission, multiplexing, transmission media, circuit switched networks, datagram
networks, virtual circuit networks.
UNIT III
Data Link Layer
Introduction, Block Coding, cyclic codes, checksum, framing, flow and error control,
Noiseless channels, noisy channels, HDLC, point to point protocols.
Medium Access Sub Layer: Random access, controlled access, channelization, IEEE
standards, Ethernet, Fast Ethernet. Giga-Bit Ethernet.
UNIT IV
Network Layer
Logical addressing, internetworking, uni-cast routing protocols, Multicast routing protocols.
UNIT V
Transport Layer
Process to process delivery, UDP and TCP protocol, congestion, congestion control
techniques, Quality Of Service(QOS), Quality Of Service techniques.
TEXT BOOKS
1. Andrew S Tanenbaum, “Computer Networks”, 4th Edition, Pearson Education.
2. Behrouz A. Forouzan, “Data Communications and Networking”, 4th Edition, TMH, 2006.
REFERENCE BOOKS
1. William Stallings, “Wireless Communications and Networks”, 2nd Edition, Pearson Hall.
2. WA Shay, “Understanding Communications and Networks”, 3rd Edition, Cengage Learning.
3. Nader F. Mir, “Computer and Communication Networks”, Pearson Education.

168

ELECTRONIC MEASUREMENT AND INSTRUMENTATION
(Professional Elective )

Year Semester Hours/Week Marks Total
C CIE SEE

L T P/D

IV I 2 - 2 3 40 60 100

Pre-requisite Analog Circuit Analysis, Linear and Digital Circuits

COURSE OUTCOMES
At the end of the course, the students will develop ability to

1. Demonstrate various Electronic Instruments and their utilization.
2. Design and analyze the performance characteristics of instruments to select for

applications.
3. Illustrate the measurement of resistance, capacitance, inductance and frequency using

Bridge
4. Explain about different types of Oscilloscopes and signal analyzers.
5. Analyze various types of Active and passive transducers and select for applications

UNIT I
Characteristics of Measuring Instruments
Significance of Measurement and block diagram of Measurement System, Static
characteristics- Accuracy, Precision, Sensitivity, Linearity, Repeatability, Reproducibility,
Resolution, Threshold, Drift ,Stability, Dead zone, hysteresis, Dynamic Characteristics-
speed of response, measuring lag, fidelity, dynamic error, Types of Errors – Gross error,
systematic errors, Random errors.

UNIT II
Measuring Instruments
PMMC, DC voltmeter and current meters and its Extension ranges, True RMS Responding
Voltmeter, Average responding rectifier type voltmeter, electronic voltmeter, block diagram
approach for measurement of voltage, current and Resistance using Digital Multi Meter
(DMM), Q-meter – Series Method .

UNIT III
Bridges and Analyzers
DC Bridge- Wheatstone bridge, Kelvin's Double Bridge, AC Bridge- Maxwell’s Bridge,
Schering bridge and Wien’s Bridge.
Signal Analyzers
Frequency Selective and Heterodyne Wave Analyzers, Harmonic distortion Analyzers, Total
Harmonic distortion, Spectrum Analyzers.

UNIT IV
Oscilloscopes
Cathode Ray Tube (CRT), Electrostatic Deflection, Post Deflection and Acceleration of
Electron Beam, Screens for CRT’s, Block diagram of CRO- Time-Base Generator, Delay

169

line, Attenuators, probes, Dual beam oscilloscope, Dual trace oscilloscope, Digital Storage
Oscilloscope , Applications of CRO: Measurement of Phase and Frequency using Lissajous
Patterns.
UNIT V
Transducers
Transducer and its classification, Introduction to Strain Gauge type- Bonded and unbounded
strain gauges, Variable gap type and variable area type Capacitive Transducers, LVDT, Piezo
electric transducer, Introduction to Temperature transducers-Thermocouple, RTD and
Thermister.
Intelligent and smart transducers
Principle-design approach, interface design, configuration support, communication in smart
transducer networks.
TEXT BOOKS
1. Helfrick AD and Cooper WD, “Modern Electronic Instrumentation and Measurement

Techniques”, PHI.
2. AK Sawhney, “A Course in Electrical and Electronics Measurements and

Instrumentation”, Dhanpat Rai Publications, New Delhi, 2002.
REFERENCE BOOKS
1. Oilver and Cage, “Electronic Measurements and Instrumentation”, McGraw Hill

International Edition.
2. Golding EW and Wides FC, “Electrical Measurements and Measuring Instruments”,

Wheeler Publications.
3. BC Nakra and KK Chowdary, “Instrumentation Measurement and Analysis”, TMH, New

Delhi.

170

ADVANCED WIRELESS TECHNOLOGIES

Hours/Week Marks
SEE
Year Semester L T P/D C CIE 60 Total
100
2- 23 40

Pre-requisite Analog and Digital Communications

COURSE OUTCOMES:
After the successful completion of this course, the student will be able to
5. Recognize the significance of cellular concept and the capacity of wireless

communication.
6. Explain the mobile radio propagation mechanism.
7. Describe the working and application of GSM, CDMA and 3G (UMTS, IMT 2000)

mobile systems.
8. Describe the techniques and technological advancement in LTE and 4G networks.

UNIT I
Introduction to cellular system, Frequency reuse, handoff, interference, methods of improving
the capacity of cellular systems, Packet radio.
Mobile Radio Propagation
Large scale path loss, reflection, ground reflection model (2 ray model), diffraction, practical
link budget design using path loss models, small scale fading and multi-path, small-scale
multipath propagation, parameter of multi-path channels, types of small scale fading,
Rayleigh and Ricean distribution.

UNIT II
2G Technologies:
Global System for Mobile Communication (GSM)
GSM-services, features, radio specifications, system architecture, channel types, frame
structure, security aspects, and network operations
GSM evolution: GPRS and EDGE; Architecture and services offered, Code Division
Multiple Access (CDMA) digital cellular standard: Soft hand off and power control, radio
specifications, forward and reverse CDMA channel.

UNIT III
3G Technologies:
Universal Mobile Terrestrial System (UMTS):
System architecture, air interface specification, forward and reverse channels in Wideband
CDMA (WCDMA) and CDMA 2000.

UNIT IV
3GPP LTE and 4G
Introduction and system overview, Frequency bands and spectrum, network structure, and
protocol structure, Frame slots and symbols,

171

Logical and Physical Channels: Mapping of data on to logical sub-channels physical layer
procedures, establishing a connection, retransmission and reliability, power control.
4G: Introduction, features and architecture Multi antenna Technologies: MIMO
UNIT V
Emerging Technologies:
5G
Characteristics envisioned for 5G, Specifications and architecture
SDN (Software Defined Network)
Objective and architecture
REFERENCES

1. Ekram Hossain, Dong In Kim, Vijay K. Bhargava , “Cooperative Cellular Wireless
Networks”, Cambridge University Press, 2011.

2. Ekram Hossain, Vijay K. Bhargava(Editor), Gerhard P. Fettweis (Editor), “Green Radio
Communication Networks”, Cambridge University Press, 2012.

3. F. Richard Yu, Yu, Zhang and Victor C. M. Leung “Green Communications and
Networking”, CRC press, 2012.

4. Mazin Al Noor, “Green Radio Communication Networks Applying Radio-Over-Fibre
Technology for Wireless Access”, GRIN Verlag, 2012.

5. Mohammad S. Obaidat, Alagan Anpalagan and Isaac Woungang, “Handbook of Green
Information and Communication Systems”, Academic Press, 2012.

6. Ramjee Prasad and Shingo Ohmori, Dina Simunic, “Towards Green ICT”, River
Publishers, 2010.

7. Jinsong Wu, Sundeep Rangan and Honggang Zhang, “Green Communications:
Theoretical Fundamentals, Algorithms and Applications”, CRC Press, 2012.

172

CMOS RF CIRCUIT DESIGN

(Year Semester Hours/Week P/D C Marks Total
LT CIE SEE

2- 23 40 60 100

Pre-requisite Solid state devices and modeling, Analog electronic circuits

COURSE OUTCOMES:

At the end of the course, the students will develop ability to
1. Understand the fundamentals of RF circuit design.
2. Analyze the performance of single port and multiport networks.
3. Apply different models to RF diodes, BJT etc.
4. Implement different active filters.
5. Design RF and Low noise amplifiers, oscillators and mixers.

UNIT –I

Introduction to RF Circuit Design: RF behavior of passive components-High frequency

resistors, inductors and capacitors, Chip Components and Circuit Board Considerations: Chip

Resistors, Chip Capacitors, and Surface Mount inductors. Transmission Line Analysis: Two

wire, coaxial and microstrip lines, Equivalent circuit representation. Terminated lossless

transmission line, Input impedance matching, Return loss and insertion loss.
UNIT –II

Single and Multiport Networks: Interconnecting networks, Scattering parameters, Smith

Chart: Reflection coefficient, Impedance transformation, admittance transformation, Parallel

and series connections.

UNIT -III

Active RF Devices and modeling: RF diodes-BJT, RF field effect transistors, High electron

mobility transistors, RF Diode models, RF BJT models and RF FET models.
UNIT –IV

RF Filter Design: Basic filter configurations, Butterworth and Chebyshev filter realizations,

Filter implementations, Coupled filter.
UNIT –V

RF Amplifiers, Oscillators and Mixers:

Characteristics of amplifiers, stability considerations, Broadband, high power and multistage

amplifiers, RF power amplifiers, Low noise amplifiers (LNA).

High frequency oscillator configurations, Basic characteristics of mixers.

TEXT BOOKS:
1. Reinhold Ludwig, Pavel Bretchko, “RF Circuit Design: Theory and Applications”,

Prentice Hall, 2000.
2. Thomas H Lee, “The design of CMOS radio-frequency integrated

circuits”, Cambridge University Press, 1998.

REFERENCE BOOKS:
1. Christopher Bowick, Cheryl Ajluni and John Blyler, “RF Circuit Design”,

Elsevier, 2007.
2. Joseph J Carr, “Secrets of RF Circuit Design”, McGraw-Hill, 3rd Edition. 2000.
3. Matthew M. Radmanesh, “Radio Frequency and Microwave Electronics”,

Prentice Hall,2000.

173

DISTRIBUTED IOT

Year Semester Hours/Week Marks SEE Total
C CIE 60 100
40
L T P/D

2- 23

Pre-requisite Introduction to IoT

COURSE OUTCOMES
At the end of the course, the students will develop ability to
1. Illustrate the key components of distributed IoT system.
2. Explain various sensor networks and topologies
3. Describe the IoT Gateway Mechanism
4. Describe the goals of Real-time operating systems
5. Develop complete IoT system involving high-level and low level design

UNIT I
Smart Objects
The “Things” in IoT, Sensors, Actuators, and Smart Objects, Hardware Communications
Criteria (Ethernet, Wi-Fi, Bluetooth, Zigbee) M2M To IOT -M2M Vs IOT

UNIT II
Communication & Networking Technologies in IoT
Introduction Sensor Networks, Network Layer Model (OSI or TCP/IP), Network Topologies,
Communication Models; Wired: RS232, RS485, CAN, Ethernet. Wireless: Bluetooth,
WLAN, GPS, LoRa, Cellular.

UNIT III
IoT Gateway
Introduction Gateway, Edge vs Fog Computing, Communication Models - Edge, Fog and
M2M, Data Exchange Formats (JSON, XML), MQTT Protocol, HTTP REST, CoAP, XMPP
and AMQP, Protocol Interoperability & Bridging, Data Aggregation using Gateway.

UNIT IV
Real-Time Operating System
Introduction, Real-Time Systems Concepts, Kernel Structure, Task Management,
Semaphores, Mutual Exclusion (MUTEX), Message Mailbox, Message Queue, Memory
Management, Porting RTOS.

UNIT V
Case Studies
Smart and Connected Cities, An IoT Strategy for Smarter Cities, Smart City IoT
Architecture. IoT Wearables, Health care systems, Agri and Allied sectors.

174

TEXT BOOKS
1. Hands-On Industrial Internet of Things: Create a powerful Industrial IoT infrastructure

using Industry 4.0 - by Giacomo Veneri and Antonio Capasso.
2. Mastering the FreeRTOS Real Time Kernel – a Hands On Tutorial Guide
REFERENCES
1. Rethinking the Internet of Things: A Scalable Approach to Connecting Everything, by

Francis daCosta, ISBN: 978-1-4302-5740-0, 2013
2. Architecting the Internet of Things, by Dieter Uckelmann, Mark Harrison and Florian

Michahelles, ISBN: 978-3-642-19157-2, 2011 Arduino Yun”, Packt Publishing, 2014.
3. IoT and Edge Computing for Architects: Implementing edge and IoT systems from

sensors to clouds with communication systems, analytics, and security, 2nd Edition by
Perry Lea.

175

SECURITY IN IOT

Year Hours/Week Marks
Semester C

L T P/D/J CIE SEE Total

2 - 2 3 40 60 100 2

Pre-requisite Cloud Computing

COURSE OUTCOMES
At the end of the course, the students will be able to
1. Acquire good understanding of the Internet of Things concept and systems architecture;

2. Operate with wireless technologies and networking protocols specific to IoT systems;

3. Become familiar with standard security and privacy preserving mechanisms, and

understand different cloud integration methods;

4. Design, implement, and test a simple IoT system equipped with sensors and wireless

transceivers;

5. Write technical documentation of a research project and results obtained by means of

experiments in a workshop style paper format.

UNIT I
Introduction: Introduction to IoT Security – Vulnerabilities, Attacks and Countermeasures.
Information Assurance. Attack types. New security threats and vulnerabilities. Fault Trees
and CPS. Countermeasures to thwart attack. Threat Modeling.
UNIT II
Security:
Security Management & Cryptology- Security Controls - Authentication, Confidentiality,
Integrity; Access Control, Key Management and Protocols, Cipher – Symmetric Key
Algorithms, Public Private Key Cryptography; Attacks – Dictionary and Brute Force, Lookup
Tables, Reverse Look Tables, Rainbow Tables, Hashing – MDS, SHA256. SHA 512, Ripe
MD, WI, Data Mining
UNIT III
Attack Surface and Threat Assessment: Embedded Devices – UART, SPI, I2C, JTAG,
Attacks – Software and cloud components, Firmware devices, Web and Mobile Applications.
IoT Protocol Built-in Security Features – Transport Layer, SSL/TLS and DTLS, Kerberos,
Cloud security for IoT
UNIT IV
Trust Computing:
The Trusted Computing Architecture- Introduction to Trusted Computing, TPM
Provisioning, Exact Mechanics of TPM.
UNIT V
Case Studies and Discussion: Smart Agriculture, Cities, Grid, Healthcare, Homes, Supply
Chain, and Transportation, Application of Security Concepts to Create IoT system.
TEXT BOOKS:
1. Practical Internet of Things Security, Brian Russell & Drew Van Duren – 2016

2. Security and the IoT ecosystem, KPMG International, 2015

REFERENCES:Internet of Things: Privacy & Security in a Connected World, Federal Trade
Comission, 2015.Internet of Things: IoT Governance, Privacy and Security Issues by
European Research Cluster

176

OPEN ELECTIVES

177

OPEN ELECTIVES L T P Cr

S.
No. Code Title

1 Design for Social Impact I 33

2 Essentials of Entrepreneurship 33

3 Foundations to Cognitive Science 33

4 Visual Communication and Computer Art 3 3

5 Cognitive Management 33

6 Business Modelling and Validation 3 3

7 Design Cognition 33

8 Image Manipulation in Adobe Photoshop 3 3

9 Design for Social Impact II 33

10 Startup Launch 33

11 Operations Research 33

12 Advanced Visual Organization and After Effects 3 3

13 Philosophy 33

14 Psychology 33

15 Sociology 33

16 Engineering Ethics 33

17 Environmental Sciences 33

18 MORSE 33

19 Design for Social Impact III 33

20 Discrete Mathematical Structures 33

21 Marketing for Engineers 33

22 Business Analytics 33

23 Disaster Management 33

24 Pollution and Control Engineering 33

25 Smart Cities 33

26 Intellectual Property Rights 33

27 Project Management 33

Computational Methods In Cognitive 3 3
28 Neuroscience

29 Management Consulting 33

30 Learn Management 33

178

DESIGN FOR SOCIAL IMPACT I

Pre-requisite: Basics of Engineering design process

COURSE OUTCOMES
At the end of the course the student will be able to

1. Understand the design process
2. Practice Team work and code of cooperation
3. Identify the real problems
4. Develop project concepts
5. Design low fidelity prototypes
UNIT I
Introduction
Basic definitions & Overview of the engineering design process - problem identification,
analysis of the existing solutions, Idea generation, specifications and concept development,
prototyping, failure analysis, detailed design, usability test, product delivery – Team
formation, Roles and code of cooperation.
UNIT II
Project management: Project charter- setting goals for the project, project time line- to
manage the project, Teamwork- Team roles and responsibilities, good practices for teams,
code of cooperation
UNIT III
Human Centered Design and Design Thinking: IDEO case studies, IDEO design tool kit,
ideal wallet / Personal hydration design activity, partnership with the communities and
NGOs, Prototyping- as a communication tool, learning to do low fidelity, rapid prototypes to
get user feedback and develop specifications
UNIT IV
Problem Identification: Societal survey: Demographic, Ethnographic and Geographic, Data
collection through Experiencing, Observation & Interaction, needs assessment, problem
statement, persona development, stakeholder analysis, customer requirements
UNIT V
Market Survey: Detailed analysis of the existing products (Patents, Papers and commercial
market), limitations of the available products
Concept Generation: Design target specifications, Project concepts development and Low-
fidelity design for mockup, 3D models
TEXT BOOKS
1. Product Design & Development, Karl T. Ulrich, Steven D. Eppinger – Mc Graw Hill

Irwin
REFERENCE BOOKS

1. World changing: A User’s Guide for the 21st Century, Alex Steffen (2006). World
changing: A User’s Guide for the 21st Century, New York, Harry N. Abrams

2. This is Service Design thinking, Marc Stickdorn, Jakob Schneider and the co-authors
(2011). The Netherlands, BIS Publishers

179

ESSENTIALS OF ENTREPRENEURSHIP

COURSE OUTCOMES
At the end of the course the student will be able to

1. Describe the elements of the entrepreneurial mindset
2. Identify new opportunities at the intersection of technology and business
3. Develop innovative concepts that create win-win for the stakeholders
4. Design unique value proposition for the customers
5. Express business pitch effectively
UNIT I
Overview of Entrepreneurship
Overview, Importance, Definition - The Role and Promise of Entrepreneurship -
Entrepreneurial Style – Find your Entrepreneurial Flow – Principles of Effectuation – Team
formation - Problem Identification and the tools & Techniques – Identify Problem worth
solving
UNIT II
Design Thinking & Product
Idea Generation - Elements of Design Thinking - Customer Centric Product Solution fit -
Unique Value Proposition
UNIT III
Customer & Value Proposition
Markets, Segmentation & Targeting – Personas – Run problem interviews with Prospects -
Value Proposition Canvas - Crafting Value Proposition - Estimating Market Size - Making a
Business Case
UNIT IV
Minimum Viable Product & Pivoting
Develop MVP & Validation - Build Measure Learn Loop - Lean Canvas and its Elements
UNIT V
Lean Methodology & Elevator Pitch
Application of Lean Canvas - Elements of Pitch – Pitch the Problem you Love along with
elements of Canvas

Textbooks:
1. Disciplined Entrepreneurship, Bill Aulet John Wiley & Sons Inc, ISBN:
9781118692288, 9781118692288
2. The Startup Owner's Manual: The Step-By-Step Guide for Building a Great
Company, Bob Dorf and Steve Blank, Wiley Publications
3. Scaling Lean - Mastering the Key Metrics for Startup Growth, Ash Mourya,
O 'Reilly, ISBN: 9789351100867, 9351100863, 1st Edition, 2013

REFERENCES
1. Christensen, Clayton M., The Innovator's Dilemma: When New Technologies Cause

Great Firms to Fail, Boston, Mass.: Harvard Business School Press, 1997.

180

FOUNDATIONS TO COGNITIVE SCIENCE

COURSE OUTCOMES
At the end of the course the student will be able to

1. Appreciate the multidisciplinary nature of cognitive science
2. Recognize the different cognitive processes and phenomena in this field
3. Explore the impact of the knowledge categorization on the design process
4. Discover the influence of cognitive biases on the thought process
5. Understand the cognitive aspects of problem solving and decision making processes

UNIT I
Introduction to Cognition: Cognition and cognitive processes, Interdisciplinary nature,
History of cognitive science and its permeation to engineering and business management,
Structural organization of the brain and neural system
UNIT II
Attention and Perception: Sensation, attention and perception phenomena, Selective
attention, Cross-modal attention, Priming, Visual and auditory perception, Signal detection
theory, Top-down and Bottom-up processing, Gestalt psychology – principles and
applications, Neuroscience of perception
UNIT III
Knowledge Representation: Human knowledge in representation, Categorization, Semantic
networks, Schematic representation, Working memory, Long-term memory, Encoding and
retrieval, Encoding specificity principle, Recall, Recognition, Mind maps and Concept maps
UNIT IV
Reasoning and Imperfection in Thinking: Logic,Different types of reasoning – Deductive,
Inductive, Abductive; Applications of reasoning in design, Techniques in reasoning – RGA
and Laddering in consumer research; Cognitive biases, Fallacies, Mental blocks, Design
fixation
UNIT V
Decision Making and Problem Solving: Strategies of decision-making, Affinity maps,
Expected utility and benefits models, Satisficing, Heuristics in decision making, Influence of
cognition on consumer decision making, Price cognition, Gestalt accounts of problem
solving, Problem types, Well and ill defined problems, Problem solving cycle,Problem
representation and structure, Problem solving – algorithms and heuristics, Problem solving by
reinforcement and six hat thinking
TEXT BOOKS

1. Cognitive Psychology: Mind and Brain by E. E. Smith & S. M. Kosslyn
2. Cognition by M. W. Matlin& T. A. Farmer
REFERENCE BOOKS
1. Cognitive Psychology-A Student’s Handbook by Michael W. Eysenck and Mark

Keane 2.Cognitive Psychology-Connecting Mind, Research, and Everyday
Experience by Bruce Goldstein E3.Cognitive Psychology and its Implications by John
R. Anderson4.Emerging Perspectives on Learning, Teaching and Technology by
MichealOrey

181

SUGGESTED BOOKS
1. How People Learn by J. D. Bransford, A. L. Brown & R. R. Cocking
2. Emotional Design: Why we Love (or Hate) Everyday Things by Norman, Donald A
3. Conceptual Blockbusting-A Guide to Better Ideas by James L. Adams
4. The Nature of Cognition by Robert J. Sternberg

182

VISUAL COMMUNICATION & COMPUTER ART
COURSE OUTCOMES
At the end of the course the student will be able to
UNIT I
Shape and Space - Geometric and biomorphic shapes, positive and negative space, shape
tools, anchor points, anchor point manipulation, fill and stroke, warp tool, layers
UNIT II
Line - Width, weight, texture, opacity and direction of line, dynamic, static, smooth, and
angular lines, brush tool, pen tool, pencil tool, width tool
UNIT III
Text - Fonts and the type tools in Illustrator
Color - Hue, value, saturation, and opacity.
UNIT IV
Color -gradient panel and tool, mesh tool, opacity options
Texture - Implied vs. actual texture, pattern panel, symbol sprayer tool
UNIT V
Content - Form, subject, and context, eraser tool and the effects menu

183

DESIGN FOR SOCIAL IMPACT II

Pre-requisite: Engineering design process

COURSE OUTCOMES
At the end of the course the student will be able to

1. Design the working prototype
2. Conduct Failure mode analysis
3. Perform validation and user test
4. Deliver the products to the partners
5. Learn leadership skills

UNIT I
Project management revisited: Critical path analysis, learning to use Gantt charts, risk
analysis for project timeline, analyzing semester one lessons learned, planning for delivery.

UNIT II
Prototyping: Implementation of the best concept, Concept detailed sketch, functional
decomposition and budget approval. High-fidelity design for proof of concepts, for
components and required technology

UNIT III
Failure mode analysis: DFMEA, design for failure mode analysis, identify failure modes or
potential modes and create plans to address in the design, detailed design of complete product

UNIT IV
Testing: Test plans, user testing, component tests, and system tests, addressing risk in
design and project timeline, interaction with users, iterating using customer feedback,
redesign product

UNIT V
Product delivery and support plan: Testing with users, field testing, user manual, user
feedback - video record, maintenance agreement and support strategy for future batches
Teamwork and leadership: Teaming skills, leadership styles and approaches, methods for
resolving conflict.

TEXT BOOKS
1. Product Design & Development, Karl T.Ulrich, Steven D.Eppinger – Mc Graw Hill
Irwin

REFERENCE BOOKS
1. Design Thinking Methodology Book, Emrah Yayici, ArtBizTech
2. Change by Design: How Design Thinking Transforms Organizations and Inspires
Innovation Brown, Tim (2009). Change by Design, Harper Collins. ISBN:
9780061766084

184

BUSINESS MODELING AND VALIDATION

COURSE OUTCOMES
At the end of the course the student will be able to

1. Apply strategies to create new products for blue oceans
2. Develop and test a hypothesis
3. Restate and pivot based on rapid experimentation
4. Apply strategic tools to identify an appropriate strategy to entrepreneurial success
5. Create business value canvas and structure opportunities based on the insights

UNIT I
Revisiting Lean Start-up Methodology
Vision – Start, Define, Learn and Experiment - Steer – Leap, Test, Measure and Pivot -
Accelerate – Batch, Grow, Adapt and Innovate – Start Building your final Product

UNIT II
Blue Ocean Strategy
Red Oceans vs Blue Oceans - Uncontested Market Space - Blue Ocean Strategy Framework –
Raise, Reduce, Eliminate and Create - Blue Ocean Strategy Canvas - Applications

UNIT III
Positioning – Channels – Sales
Positioning your Product - Channels & Strategy - Building Digital Presence and leveraging
Social media - Creating your company profile page - Budgeting and planning – Develop a
Sales Plan - Unique Sales Proposition – Defining your Sales Process

UNIT IV
Business Model Canvas
Definition of Business Model - Building Business Model Canvas - Business Model
Environment - Evaluating Business Models

UNIT V
Entrepreneurial Finance
Revenue Streams - Basics of how companies make money - Identify primary and secondary
revenue streams
Pricing and Costs - Value, price, and costs; Different pricing strategies - Understand product
costs and operations costs; Basics of unit costing
Financing Your New Venture - Various sources of funds available to an entrepreneur and
pros and cons of each - What investors expect from you - What investors expect from you

185

TEXTBOOKS:
1. Disciplined Entrepreneurship, Bill Aulet John Wiley & Sons Inc, ISBN:
9781118692288, 9781118692288
2. The Startup Owner's Manual: The Step-By-Step Guide for Building a Great
Company, Bob Dorf and Steve Blank, Wiley Publications
3. Scaling Lean - Mastering the Key Metrics for Startup Growth, Ash Mourya, O
'Reilly, ISBN: 9789351100867, 9351100863, 1st Edition, 2013

REFERENCE BOOKS
1. Kim, W. C., & Mauborgne, R. (2004). Blue ocean strategy. If you read nothing else on
strategy, read thesebest-selling articles., 71.
2. Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation
to create radically successful businesses. Crown Books.
3. Porter, M. E. (2008). The five competitive forces that shape strategy. Harvard business
review, 86(1), 25-40.
4. Osterwalder, A., &Pigneur, Y. (2010). Business model generation: a handbook for
visionaries, game changers, and challengers. John Wiley & Sons.
5. Mullins, John W., The New Business Road Test, Second edition, Harlow, England: FT
Prentice Hall, 2006

186

DESIGN COGNITION

COURSE OUTCOMES
At the end of the course the student will be able to

1. Understand the different fronts at the interface between cognitive science and
design/entrepreneurship

2. Identify user’s needs, abilities, expectations etc. in design from a cognitive
perspective

3. Explorethe importance and role of analogical thinking and mental models in daily life
4. Understand the role of different cognitive tools in the design process
5. Realize the significance of cognition in the field of interaction design

UNIT I
Observing and Understanding Users: Descriptive and prescriptive design processes,
Double diamond design process, Identifyingdesign insights from observations, Ethnographic
methods, Qualitative versus Quantitative research, Conceptual frameworks for cognition,
Users – how to observe, data collection, interpreting and presentation, Understanding the
socio-cultural, economic and technological influence

UNIT II
User Journey: Modeling Users, User personas, Persona analysis – Application of Affinity
Maps,Lean Personas, Storyboards, User goals

UNIT III
Analogical Thinking:Importance of analogizing, Types of analogies, Design by analogy,
TILMAG method, Bio-mimicry, Generating own analogies, Expository and aesthetic
analogies

UNIT IV
Mental Models: Characteristics, Mental models in daily life, Constituent elements,Role of
mental models in design, Building blocks - Affordances, Constraints, Mapping; Matching
designer’s and user’s mental models

UNIT V
Interaction Design:Measures of the brain (Signals perspective),Introduction to Human-
Computer Interaction (HCI) and Brain-Computer Interfaces (BCI), Display and control
design, Visual ergonomics, Human factors in engineering design, Neural networks and
artificial intelligence, Distributed, situated and embodied cognition, Degrees of user
involvement, Participatory design, Co-create process, Shared mental models, Methodology in
cognitive science

TEXT BOOKS
1. Cognitive Psychology and Its Implications by John R. Anderson
2. The Design of Everyday Things by Norman, Donald A

REFERENCE BOOKS

187

1. An Introduction to the Study of Mind by Jay Friedenberg and Gordon Silverman
2. Applied Imagination-Principles and Procedures of Creative Problem Solving by Alex

F. Osborn.
3. Mental Models-Aligning Design Strategy with Human Behavior by Indi Young
4. Living with Complexity by Norman, Donald A
SUGGESTED BOOKS
1. Emotional Design: Why we Love (or Hate) Everyday Things by Norman, Donald A
2. Set Phasers on Stun: And Other True Tales of Design, Technology and Human Error

by S. M Casey
3. Designing from Both Sides of the Screen: How Designers and Engineers

canCollaborate to Build Cooperative Technology by I. Ellen & W. Alan
4. Universal Principles of Design: 125 ways to enhance usability, influence perception,

increase appeal, make better design decisions, and teach through designby William
Lidwell, Kritina Holden, and Jill Butler
5. Observing the User Experience: A Practitioner's Guide to User Research by Mike
Kuniavsky
6. Cognition in the Wild by Edwin Hutchins
7. Change by Design by Tim brown
8. Don’t Make Me Think! by Steve Krug
9. Handbook of Usability Testing-How to Plan, Design, and Conduct Effective Tests by
Jeffrey Rubin and Dana Chisnell
10. Designing Interactions by Bill Moggridge

188

IMAGE MANIPULATION IN ADOBE PHOTOSHOP
COURSE OUTCOMES
At the end of the course the student will be able to

UNIT I
Image Correction
Introduction to pixel selection, color balance and temperature correction, value correction,
retouching skin, changing human form, using the image adjustment menu, the retouch tools,
and the liquefy function in Photoshop
UNIT II
Image Combination and Separation
Advanced Pixel selection, subtraction of imagery, addition of imagery, layers
Image Distortion - Filters
UNIT III
Creative Color - Layer modes, gradient tool, brush tool, image adjustment menu
UNIT IV
Effective Black and White Imagery
Taking photographs, converting color photographs to aesthetically pleasing black and white
photographs, image adjustment menu, and the burn and dodge tools
UNIT V
Text Special Effects - Text tools, layers, masks, selection, and filters

189

DESIGN FOR SOCIAL IMPACT III

Pre-requisite: Team work and Leadership
COURSE OUTCOMES
At the end of the course the student will be able to
1. Conduct market research
2. Understand the start-up models
3. Write Proposals for social entrepreneurship
4. Initiate the start-up company
5. Mentor the new student teams
UNIT I
Market Analysis
Market research, understanding target market, potential customers, analysis of the present
competitors, challenges and opportunities
UNIT II
Entrepreneurship
Business models in commercial entrepreneurship and social entrepreneurship - Case studies,
financial resources, and Start-up models
UNIT III
Social Entrepreneurship
Social entrepreneurship tool kit – idea assessment, impact assessment, risk assessment,
market assessment and financial assessment, using project in the delivery stage as the case to
explore entrepreneurship opportunities
UNIT IV
Launch pad
Legal structures, financial plan, risk mitigation plan, start-up enterprise, mass level
production and marketing
Leadership and Mentoring Role
Taking on leadership of teams and mentoring the next batch. Paired with students in the next
batch to put leadership tools into practice to on-board the new batch.
UNIT V
Leadership and Mentoring Role (continued)
Helping the new teams during DSI-I modules, Identifying new projects with existing partners
– or new ones. Handing off projects to next batch, completed and field support or for new
design or redesign.
TEXT BOOKS

1.Product Design & Development, Karl T. Ulrich, Steven D. Eppinger – Mc Graw Hill
Irwin

REFERENCE BOOKS
1. Design for the other 90%, Smith, Cynthia (2007). New York, Cooper Hewitt
Smithsonian Design Museum
2. How to Change the World: Social Entrepreneurs and the Power of New Ideas, David
Bornstein

190

STARTUP LAUNCH

COURSE OUTCOMES
At the end of the course the student will be able to

1. Categorize technology adoption life cycle and identify strategies to cross the chasm
2. Appraise scaling of the venture
3. Apply Bullseye framework to improve the operational efficiency
4. Select appropriate pricing & investment strategy
5. Create the business plan
UNIT I
Strategy Tools
Five Competitive Forces that Shape Strategy - Disruptive Innovation - Ansoff Matrix -
Product Positioning - Adjacency Mapping
UNIT II
Crossing the Chasm
Technology Adoption Life Cycle - Crossing the Chasm - Innovators, Early Adopters & Early
Majority
UNIT III
Scaling & Traction
Strategies and Critical Obstacles for Scaling - Anticipating, Planning and Managing Growth -
Bull’s-eye Framework - Customer Lifetime Value - Improving Efficiency of Operation
UNIT IV
Support Services
Business regulation - legal issues and their impact on entrepreneurs - Patents and Intellectual
property – Trade marks – Role of Mentors, Advisors, and Experts
UNIT V
Business Plan & Capstone
Elements of a Business Plan - Evaluating a Business Plan (DPR) – Launch your business /
Pitch your Venture

TEXTBOOKS:
1. Disciplined Entrepreneurship, Bill Aulet John Wiley & Sons Inc, ISBN:
9781118692288, 9781118692288
2. The Startup Owner's Manual: The Step-By-Step Guide for Building a Great
Company, Bob Dorf and Steve Blank, Wiley Publications
3. Scaling Lean - Mastering the Key Metrics for Startup Growth, Ash Mourya, O
'Reilly, ISBN: 9789351100867, 9351100863, 1st Edition, 2013

REFERENCE BOOKS
1. Mares, J., & Weinberg, G. (2014). Traction: A Startup Guide to Getting Customers. S
Curve Publishing.

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COGNITIVE MANAGEMENT

COURSE OUTCOMES
At the end of the course the student will be able to

1. Identify and structure new opportunities based on cognitive insights
2. Apply the effectuation theory for the development of entrepreneurial ideas
3. Motivate team members to contribute to overall success of the team or organization
4. Understand and apply emotional intelligence strategies for everyday situations
5. Explore the cognitive principles behind leadership and organizational management

UNIT I
Opportunity Recognition: Interaction to entrepreneurial businesses, Culture and methods,
Lean startups, Opportunity recognition cognitive theories, Prototype theory, Pattern
recognition, Connections for identifying and making opportunities

UNIT II
Effectuation Theory: Effectual problem space, Principles of effectuation - The bird in hand,
The affordable loss, The crazy quilt, The lemonade, and the Pilot-in-the-Plane

UNIT III
Team Cognition: Perspectives on team cognition, Cognitive systems engineering perspective
on shared cognition, Interactive team cognition, Collaborative contributions, Activity
awareness

UNIT IV
Emotional Intelligence: Personality and EQ, Models of EI - Trait model, Mixedmodel, Bar-
on model, EI and Personal relationship, Strategies for improving EI, EI and Strategic thinking

UNIT V
Leadership: Cognitive resource theory of leadership, Different types of leadership, Trait
theory, Behavioral theory, Transactional and transformational leadership, Values,
Contingency theory of leadership, Leadership lessons, Innovation&culture

TEXT BOOKS
1. Effectuation: Elements of Entrepreneurial Expertise by Saras D. Sarasvathy
2. Primal Leadership: Unleashing the Power of Emotional Intelligence by Daniel
Goleman, Richard Boyatzis, and Annie McKee
3. Theories of Team Cognition: Cross-Disciplinary Perspectives Edited by Eduardo
Salas, Stephen M. Fiore, Michael P. Letsky

REFERENCE BOOKS
1. Entrepreneurship for Physicists: A Practical Guide to Move Inventions from
University to Market by DavideIannuzzi
2. Opportunity Identification and Entrepreneurial Behavior Edited by John E. Butler

192

3. Role of Emotions in the Entrepreneur's Opportunity Recognition Process by Malavika
Sundararajan

4. Introducing Emotional Intelligence: A Practical Guide by David Walton
SUGGESTED BOOKS

1. Shared Leadership: Reframing the Hows and Whys of Leadership by Craig L Pearce,
Jay A. Conger

2. Collaborative Communication Processes and Decision Making in Organizations
Edited by Nikoi, Ephraim

3. Emotional Intelligence for Dummies by Steven J. Stein

193

ADVANCED VISUAL ORGANIZATION AND AFTER EFFECTS
COURSE OUTCOMES
At the end of the course the student will be able to

UNIT I
Size - Scale and proportion of shapes, layers and transform controls in After Effects
Placement - Static and dynamic placement, proximity and distance of lines, layers and
transform controls in After Effects
UNIT II
Unity - Proximity and repetition, transform controls, effects and presets
Variety - Shape, color, texture, size, and placement, transform controls, effects and presets
UNIT III
Balance - Symmetrical and asymmetrical balance, text tool in After Effects
Focus - Main elements identified through contrast in shape, color, texture, size and/or
placement, shape creation in After Effects

UNIT IV
Logo Design - Shape, line, text, color, and texture, simplicity, reproducibility, and
recognition, Illustrator,
Text and image organization for three dimensional object in Illustrator
UNIT V
Page Advertisement Design - Information hierarchy, unity, variety, balance and focus using
both images and text, the grid, and borders, Illustrator and Photoshop
Motion Graphic Advertisement - Information hierarchy, unity, variety, balance, and focus
using both images and text, the grid, and borders, Illustrator, Photoshop, and After Effects

194

ENGINEERING ETHICS

COURSE OUTCOMES
At the end of the course, the students will develop ability to
1. Instill moral values that ought to guide ones profession
2. Identify risks and apply safety measures to reduce risk
3. Interpret their rights and responsibilities in their profession
4. Examine various global issues and resolve the situations as a professional
5. Examine the various code of ethics in various programs of Engineering
UNIT I
Scope of Engineering Ethics: Engineering Ethics, need of Engineering Ethics, Profession
and Professionalism; Engineering as Social Experimentation, Engineers responsibilities in
Experimentation.
UNIT II
The Engineer’s Responsibility for Safety: Safety and Risk- Assessment of Safety and Risk,
Risk-Benefit Analysis - Reducing Risk-The Government Regulators Approach to Risk - Case
Studies.
UNIT III
Responsibility to Employer’s and Rights of Engineers:
Collegiality and Loyalty –Respect for Authority – Collective Bargaining – Confidentiality –
Conflicts of Interest –Occupation Crime; Rights of Engineers- Professional rights, Employee
rights, Whistle blowing, IPR, Plagiarism – Case studies.
UNIT IV
Global Issues and Responsibilities as Engineers:
Multinational Corporations – Business Ethics - Environmental Ethics – Computer Ethics –
Weapons Development – Engineers as Managers – Consulting Engineers – Engineers as
Expert Witnesses and Advisors – Moral Leadership –Code of Conduct – Corporate Social
Responsibility
UNIT V
Sample Code of Conduct: Role of codes and its function, Limitation of Codes, Role of Law
in Engineering, The problem of law in Engineering, Code of Engineering Societies, and Code
of Ethics for Engineers – ASME, NSPE, IEEE.
TEXT BOOKS
1. Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGraw Hill, New

York, 2005. (Reprint 2013)
2. Ibo Van de Poel and Lamber Royakkers “Ethics, Technology, and Engineering – An

Introduction”, John wiley publication, 2011.

REFERENCE BOOKS:
1. Edmund G. Seebauer and Robert L. Barry, “Fundamentals of Ethics for Scientists and
Engineers”, Oxford University Press, 2014.
2. Caraline whitbeck, “Ethics in Engineering practice and Research”, Cambridge
University press,2012

195

ENVIORNMENTAL SCIENCES

COURSE OUTCOMES
1. Interpretation of integrated, quantitative and interdisciplinary approach to the study of

environmental systems.
2. Analysing and understanding of human relationships, perceptions and policies towards

the environment.
3. Applying focus on design and technology for improving environmental quality.
4. Defining the earth processes, evaluating alternative energy systems, pollution control and

mitigation,
5. Analysis of Natural resource management and the effects of global climate change of

environment.

UNIT I
Concepts of Environmental Sciences, Biodiversity and its conservation
Introduction to Environment, Levels of organizations in environment, Structure and functions
in an ecosystem.
Introduction to Biodiversity at global, national and local levels; India as a mega-diversity
nation; Threats to biodiversity (biotic, abiotic stresses), and strategies for conservation.

UNIT II
Natural Resources
Introduction to Renewable and Non-renewable Resources, Forests, water, minerals, Food and
land (with example of one case study); Energy, Growing energy needs, energy sources
(conventional and alternative). Bio energy (alcohol, methane, hydrogen)

UNIT III
Environmental Pollution
Pollution- introduction, types - Air, water (including urban, rural, marine), soil, noise,
thermal, nuclear; Pollution prevention; Management of pollution- Rural/Urban/Industrial
waste management [with case study of any one type, e.g., power (thermal/nuclear),
pesticides, fertilizer, tannin, leather, chemical, sugar], Solid/Liquid waste management,
disaster management.

UNIT IV
Environmental Biotechnology
Introduction to Biotechnology for environmental protection- Biological indicators, bio-
sensors; Remedial measures- Bio-remediation, phytoremediation, bio-pesticides, bio-
fertilizers; Bio-reactors- Design and application

UNIT V
Social Issues and Environment
Introduction to Problems relating to urban environment- Population pressure, water scarcity,
industrialization; remedial measures; Climate change- Reasons, effects (global warming,

196

ozone layer depletion, acid rain) with one case study; Legal issues- Environmental legislation
(Acts and issues involved), Environmental ethics GMO – Genetically Modified organisms
(BT- cotton, BT- Brinjal).
Field Work
Field Work covering, Plotting of biogeographical zones and expanse of territorial waters on
the map of India; Identification of 28 biological resources (plants, animals, birds) at a specific
location. Industrial visit for environmental biotechnology processes (e.g., any one of the
fermentation, Bread making, Tannery Industry Desaipet, Lake and Dairy (Mulukanoor).
Laboratory work
Determination of physico-chemical parameters (pH, alkalinity, acidity, salinity, COD, BOD)
of tap water, well water, rural water supply industrial effluent and sea water & potability
issues.
TEXT BOOKS:
1. Richard T. Wright, Dorothy F. Boorse., “Environmental Science”, Towards a sustainable

Future12/E, PHI Learning Pvt. Ltd., M97, Ashok Goshal, Connaught circuit, New Delhi.
2. Erach Barucha, “Environmental Studies”, UGC-India, Pune.
REFERENCE BOOKS:
1. Gilbert M. Masters and Ela Wendell P, Introduction to “Environmental Engineering and

Science”- LPE Pearson educations.
2. Henry J.G. and Heinke G.W., “Environmental Science and Engineering”, Prentice Hall of

India, New Delhi.
3. M. Anji Reddy, “Text book of Environmental Science and Technology”, BS Publications

(2010).
4. Benny Joseph, “Environmental Studies”, Tata McGraw Hill, New Delhi (2009).

197

MATHS OPERATIONS RESEARCH STATISTICS ECONOMICS - MORSE

UNIT I 8 Hours

Calculus: Functions, Limit of a Function, Continuity and Derivative of a function,

Differentiation: Definition, rules of differentiation, Partial Differentiation of first and second
order, Extreme values of functions, Indeterminate Forms and L-Hospital’s Rule.

UNIT II 10 Hours

Matrix Algebra - Definition, types of matrices, Matrix operations: Addition, Subtraction and

Multiplication; Transpose of Matrix, Determinant of matrix, Inverse of Matrix, Rank of

Matrix, Solutions of Linear System of equations, Characteristic equations, Eigen values,

Eigen vectors(2X2 matrices) and properties, Cayley-Hamilton theorem and its use in finding

inverse and powers of a matrix

UNIT III 10 Hours

Statistics: Measures of Central tendency - Averages for ungrouped and grouped data, Mean,

Median, Mode. Measures of Dispersion - Range, Quartile Deviation, Mean Deviation,

Standard Deviation, Variance.
Correlation: Types of correlation, Karl Pearson’s correlation coefficient, Spearman’s Rank

correlation coefficient.

Regression: Simple linear regression, scatter graphs, least squares method, forecasting and

use of linear regression equations in forecasting.

UNIT IV 9 Hours

Operations Research: Nature and scope of Operations research, Origin of OR, Applications

of OR in different Managerial areas, Problem solving and decision making, Linear

Programming Problem: Introduction, Mathematical formulation of LPP, Graphical Solution

of LPP, solving LPP by Simplex method.

UNIT V 8 Hours

Microeconomics: Consumer theory, Supply and demand, Market equilibrium, Producer

theory, Monopoly, Oligopoly, Capital markets, Welfare economics, Public goods,

Externalities

Macroeconomics: Basics of macroeconomics, Aggregate demand and aggregate supply,

Business cycles, Unemployment and inflation, Economic stabilization policies, Economic

growth and development theories of International trade.

REFERENCE BOOKS
1. Thomas' Calculus: Early Transcendentals, 14/E, Joel R. Hass, Davis, Christopher E.
Heil, Maurice D. Weir, Pearson publications, 2018.
2. S.C. Gupta and V.K. Kapoor, Fundamentals of Mathematical Statistics, 11/e, S.
Chand and Sons, 2012.
3. S. D. Sharma, Operations Research, Kedarnath Ramnath and Company, 2008.
4. Shayle R. Searle, Matrix Algebra useful for statistics: , 2/e, Wiley Publications.

198

OPERATIONS RESEARCH

UNIT I Linear Programming Problem 10 Hours

Introduction to Operations Research – Linear Programming - Mathematical Formulation –

Graphical method – Simplex method – Penalty methods: M-method, Two Phase method.

UNIT II Transportation and Assignment 10 Hours

Introduction - Formulation - Solution of the transportation problem (Min and Max):

Northwest Corner rule, row minima method, column minima method, Least cost method,
Vogel’s approximation method – Optimality test: MODI method.
Assignment problems – Applications - Minimization and Maximization, Travelling Salesman

Problem

UNIT III Sequencing and Replacement Models 8 Hours

Sequencing – Introduction, Flow, Shop sequencing, n jobs through two machines, n jobs

through three machines, Job shop sequencing, two jobs through ‘m’ machines

Replacement Models: Introduction, Replacement of items that deteriorate with time, when

money value is not counted and counted, Replacement of items that fail completely, Group

Replacement.

UNIT IV Game Theory and Queuing Models 10 Hours

Game theory: Competitive games - Useful terminology - Rules for game theory - Two
person zero sum game – Property of dominance - Graphic solution – Algebraic method.
Queuing Models: Poisson arrivals and Exponential service times – Single channel models

and Multi-channel models - Simulation: Basic concepts, Advantages and disadvantages -

Random number generation - Monte Carlo Simulation applied to queuing problems.

UNIT V Project Management 7 Hours

Introduction - Phases of project management-Construction of Network diagrams- Critical

path method (CPM) and Project evaluation and review technique (PERT) - Crashing of

project network.

TEXT BOOKS
1. S. D. Sharma, “Operation Research”, Kedarnath Ramnath Publishers, 2008
2. J. K. Sharma, “Operation Research”, MacMilan, 4th Ed., 2009, ISBN Number: 978-

9350593363.

REFERENCE BOOKS
1. R. Pannerselvam, “Operations Research”, PHI Publications, 2nd Ed. Jan. 2006, ISBN

Number: 978-8120329287.
2. Belgundu, Ashok.D & Chandrupatla, Trupathi.R, “Optimization Concepts And

Applications”.

199

DISCRETE MATHEMATICAL STRUCTURES

COURSE OUTCOMES:
At the end of the course the student will be able to:
1. Understand the basic concepts of Discrete Mathematical Structures.
2. Apply the concepts of Discrete Mathematical Structures in theorem proving, lattices and

graph theory.
3. Apply the concepts of counting techniques and generating functions in solving recurrence

relations.
4. Develop the ability to solve practical recurrence problems.
5. Solve practical engineering problems using the concepts of graph theory.

UNIT I
Mathematical Logic
Statements and notations, Connectives, Well-formed formulas, Truth Tables, tautology,
equivalence implication, Normal forms.
Predicates
Predicative logic, Free and Bound variables, Rules of inference, Consistency, proof of
contradiction.

UNIT II
Set Theory
Introduction, Sets and Elements, Subsets, Venn Diagrams, Set Operations, Power Sets,
Partitions
Relations
Introduction, Product Sets, Relations, Pictorial Representatives of Relations, Composition of
Relations, Types of Relations, Closure Properties, Equivalence Relations, compatibility and
Partial Ordering Relations
Ordered Sets
Ordered Sets, Hasse Diagrams of Partially Ordered Sets, Supremum and Infimum,
Isomorphic (Similar) Ordered Sets, Well-Ordered Sets, Lattices and its Properties
Functions: Introduction, Functions, One-to-One, Onto and Bijective Functions, Invertible
Functions, Recursive Functions.

UNIT III
Techniques of Counting
Introduction, Basic Counting Principles, Permutations, Combinations, The Pigeonhole
Principle and its applications, The Inclusion–Exclusion Principle, Combinations with
Repetitions, Binomial and Multinomial Theorems

UNIT IV
Recurrence Relation
Generating Functions, Function of Sequences Calculating Coefficient of generating function,
Recurrence relations, Solving recurrence relation by substitution and Generating functions.

200