course curriculum for computer science engineering 2018 batch
TRANSCRIPT
Course Curriculum for Computer Science Engineering – 2018 Batch
Semester-VII (2018 Batch)
Serial no. Course code Course name Instructor
1 Elective IV
2 Elective V
3 Elective VI / project
Electives for CSE VII Semester
S.No Department Course
code
Course name Instructor Pre-requisite(s) Level/
Programme
1 CSE CS 421 Logic for Computer
Science
Prof.
Ramchandra Phawade
Discrete mathematics, theory of
computation
B.Tech
2 CS 402 Distributed Systems Prof. Kedar
Khandeparkar
Operating Systems, Data Structures
and Algorithms, Programming in C++
B.Tech
3 CS423 Advanced topics in Embedded Systems
Prof. Gayathri A CS 301 (Computer Architecture). Exposure to Operating Systems is
preferred
B. Tech. / MS / PhD
4 CS 407 Parameterized
Algorithms and Complexity
Prof. Sandeep
RB
Data Structures and Algorithms, Design
and Analysis of Algorithms
MS/B.Tech
5 CS 601 Software
Development for Scientific Computing
Prof. Nikhil
Hegde
Exposure to Data Structures and
Algorithms, C / C++ / Java / Matlab
MS/B.Tech
6 CS 433 Cloud Software
Development [ First Half semester course]
Prof. Girish
Dhahakshirur Desirable: Exposure on Operating
System, Database, Cloud
Programming language (Java, .Net,
NodeJS, HTML/CSS, etc.)
B. Tech. / MS /
PhD
7 CS 305 Software Engineering Dr Raghu Hudli Data structures and algorithms,
Programming in C,C++ and Java.
B.Tech
8
Electrical
CS 427 Mathematics for data science
Prof. Bharath Exposure to basic concepts in calculus and linear algebra
B.Tech
9 EE 429 Design of Power
converters
Prof. Satish Naik EE 222: Introduction to Power Electronics
or equivalent as determined by the
instructor or faculty advisor.
B. Tech. / MS /
PhD
10 EE 431 Advanced Power
Systems
Prof. Pratyasa
Bhui
EE223: Introduction to Power Systems or
equivalent as determined by the instructor
or faculty advisor.
B. Tech. / MS /
PhD
11 EE 323 Digital Communication and
Coding Theory
Prof. Rahul Signals and Systems, Introduction to Communication Systems, Introduction to
Probability
Note:Those who are taken Wireless
Communication course they can not
take this course.
B.Tech
12 EE 409 Speech processing Prof. Prasanna and
Prof.
Samudhravijaya
Exposure to probability concepts. B. Tech. / MS / PhD
13 EE 414 Speech processing
Lab
Prof. Prasanna
and
Prof. Samudhravijaya
Currently taking or already taken Speech
Processing theory course
B. Tech. / MS /
PhD
14 MMAE ME 429 Solar Energy
Collector Systems
Prof. Dhiraj Nil B.Tech
15 ME 323 Introduction to Aerospace
Engineering
Prof. Meenatchidevi
M
Fluid mechanics and thermodynamics B.Tech
16 ME 421 Turbomachines Prof. Sudheer & Prof. Dhiraj
Nil B.Tech
17 ME 403 Vibrations of Linear Systems
Prof. Shrikanth Mechanics of Materials B.Tech
18 ME 401 Finite Element
Analysis
Prof. Seshu,
Prof. Amlan, Prof. Amar
Engineering Mechanics and
Mechanics of Materials
B.Tech
19 ME 435 Design of
Mechatronic Systems
(NPTEL course)
Prof. Sangamesh
and Prof.
Meenatchidevi M.
B. Tech. / MS /
PhD
20 Chemistry CH 405 Our Health and
Medicine
Prof. Nilkamal
Mahanta
Nil B. Tech. / MS /
PhD
21 CH 303 Bioenergy and
Biofuels
Prof. Nilkamal
Mahanta
Exposure to basic concepts in
biochemistry, chemistry, energy
B.Tech
22 CH 402 Quantum field theory Prof. B.L. Tembe Exposure to Physics, Chemistry and
Mathematics
B. Tech. / MS /
PhD
23 HSS HS 301 Philosophy Prof. Jolly
Thomos
Nil B.Tech
24 HS 305 Principles of Finance:
Instruments &
Investment
Prof. Gopal
Sharan P,
Prof.Vipin Choudry
Nil B.Tech
25 HS 405 Macroeconomics Prof. Pushpa
Trivedi, Prof. Gopal
Sharan P
HS201 (for B.Tech. students) B. Tech. / MS /
PhD
26 HS 307 Introduction to
Linguistics
Prof. SRM
Prasanna, Prof. Leena Dihingia
Nil B.Tech
27 HS 403 Happiness and Well-
being
Prof. BL Tembe Nil B. Tech. / MS /
PhD
28 Mathematics MA 501 Measure Theory Prof. Amlan and Dhriti
Real analysis B. Tech. / MS / PhD
29 MA 503 Homological Algebra (Second half)
Prof. Shreedevi Masuti
Basics of Group Theory, Ring Theory and Module
Theory, Linear Algebra
B. Tech. / MS / PhD
30 MA 403 Introduction to
number theory
Prof. NSN Sastry Nil B.Tech
31 MA 401 Numerical Linear
Algebra
Prof. Rekha
Kulkarni
Calculus, Linear Algebra B.Tech
32 Physics PH 402 Astrophysics for
Engineers
Prof. D.
Narasimha
Electricity & Magnetism, Calculus, Linear
Algebra and Differential Equation
B.Tech
33 PH 301 Physics of
Photovoltaics ( First
Half Sem)
Dr. Dhriti Sundar
Ghosh
Nil B.Tech
34 PH 303 Thin-Film Science and Technology
(Second Half Sem)
Dr. Dhriti Sundar Ghosh
Nil B.Tech
Electives Syllabus CSE Department
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech.
Programme: B.Tech
i Title of the course CS 421 Logic for Computer Science
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be offered
Autumn
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course
number(s)
Discrete Mathematics, Theory of computation.
vii Course Content* Module 1 :Propositional Logic: Syntax, Semantics, Normal Forms, Boolean Functions.
Module 2: Computational complexity of Satisfiability P
vs NP, SAT: hardest among NP.
Module 3: Syntactic SAT solvers :
Resolution, Tableaux.
Module 4:proof Systems: Semantic entailment,
Compactness, Soundess Completeness, Natural
Deduction, Gentzen Sequent Calculus, Hilbert System.
Module 5: Predicate Logic. Randomized SAT solvers.
Programming assignments: using SAT/SMT solver z3.
Viii Texts/References (1) Logic in Computer Science, Michael Huth and Mark
Ryan, Cambridge University Press.
(2) SAT/SMT by example, Dennis Yurichev.
ix Name(s) of Instructor(s) *** Ramchandra Phawade
x Name(s) of other Departments/
Academic Unitsto whom the
course is relevant
Nil
xi Is/Are there any course(s) in the
same/ other academic unit(s)
which is/ are equivalent to this course? If so, please give details.
No
xii Justification/ Need for
introducing the course
This course introduces notions and methods of formal
logic from a computer science standpoint, covering
propositional logic, predicate logic and foundations of
SAT solvers. It presents applications and themes of
computer science research such as resolution and
automated deduction.
Name of the Academic Unit: Computer Science & Engineering
Level: B.Tech.
Programme: B.Tech
i Title of the course CS 402 Distributed Systems
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be
offered
VII
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Operating Systems, Data Structures and
Algorithms, Programming in C++
vii Course Content Introduction to distributed systems,
Message Passing, Leader Election,
Distributed Models, Causality and
Logical Time
Logical Time, Global State & Snapshot
and Distributed Mutual Exclusion-Non-
Token and Quorum based approaches
Distributed Mutual Exclusion-Token
based approaches, Consensus &
Agreement, Checkpointing & Rollback
Recovery
Deadlock Detection, DSM and
Distributed MST
Termination Detection, Message
Ordering & Group Communication, Fault
Tolerance and Self-Stabilization, Gossip
Style communication, chord, pastry
Concurrency and Replication Control,
RPCs, Transactions
Distributed Randomized Algorithms,
DHT and P2P Computing
Case Studies: GFS, HDFS, Map Reduce
and Spark
viii Texts/References 1. Distributed Computing: Principles,
Algorithms, and Systems- Ajay D.
Kshemkalyani and Mukesh Singhal
2. Distributed Computing: Fundamentals,
Simulations and Advanced Topics-Hagit
Attiya and Jennifer Welch
3. Distributed Algorithms-Nancy Lynch
4. Elements of Distributed Computing-Vijay
K. Garg
5. Advanced Concepts in Operating
Systems-Mukesh Singhal, Niranjan G.
Shivaratri
ix Name(s) of Instructor(s) Dr. Kedar Khandeparkar
x Name(s) of other Departments/
Academic Units to whom the course
is relevant
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
is/ are equivalent to this course? If
so, please give details.
No
xii Justification/ Need for introducing
the course
Technologies such as Hadoop, Cassandra, Spark,
etc., that have emerged in the recent times are
mainly based on the principles of distributed
systems. This course aims to develop an in-depth
understanding of the various distributed
algorithms and discuss some use cases.
Name of the Academic Unit: Computer Science & Engineering
Level: UG/PG.
Programme: B. Tech
i Title of the course CS 423 Advanced topics in Embedded Computing
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to
be offered
July to December (Odd)
v Whether Full or
Half Semester Course
Full
vi Pre-requisite(s), if any (For
the students) – specify
course number(s)
CS 301 (Computer Architecture).
Exposure to Operating Systems is preferred.
vii Course Content Introduction to systems software in embedded platforms
Boot loader, Embedded Linux kernel (Processes, Threads,
Interrupts), Device Drivers, Scheduling Policies (including
Real Time), Memory Management, Optimizations (Data
level and Memory level), Embedded Systems Security,
Introduction to Embedded GPUs and
Accelerators, Embedded Heterogenous Programming
with Open CL Application Case Study on Embedded
Platforms – eg. Neural Network inferencing on Embedded
Platforms, Advanced Driver Assistance Systems
viii Texts/References Building Embedded Linux Systems, 2nd Edition by Gilad
Ben-Yossef, Jon Masters, Karim Yaghmour, Philippe Gerum,
O'Reilly Media, Inc. 2008
Linux Device Drivers, Third Edition By Jonathan Corbet,
Alessandro Rubini, Greg Kroah-Hartman, O'Reilly Media,
Inc. 2005
Embedded Systems: ARM Programming and Optimization
by Jason D Bakos, Elsevier, 2015
Learning Computer Architecture with Raspberry Pi by Eben
Upton, Jeff Duntemann, Ralph Roberts, Tim Mamtora, Ben
Everard, Wiley Publications, 2016
Real Time Systems by Jane S. Liu, 1 edition, Prentice Hall;
2000
Practical Embedded Security: Building Secure Resource-
Constrained Systems by Timothy Stapko, Elsevier, 2011
ix Name(s) of Instructor(s) Dr Gayathri Ananthanarayanan
x Name(s) of other
Departments/ Academic Units
to whom the course is relevant
Electrical Engineering
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are equivalent
to this course? If so, please
give details.
No
Name of Academic Unit : Computer Science and Engineering
Level : MS/B.Tech
Programme : MS/B.Tech
i Title of the course CS 407 Parameterized Algorithms and Complexity ii Credit Structure (L-T-P-C) (3 0 0 6) iii Type of Course Elective course iv Semester in which normally to be
offered Spring
v Whether Full or Half Semester Course
Full
vi Prerequisite(s), if any (For the students) – specify course number(s)
Data Structures and Algorithms, Design and Analysis of Algorithms
vi i
Course Content*
Introduction. Kernelization, Bounded Search Trees, Iterative Compression, Treewidth, Advanced kernelization algorithms. Lower bounds: Fixed-parameter intractability, lower bounds based on ETH, lower bounds for kernelization.
V iii
Texts/References Textbook: (1) Parameterized Algorithms, Marek Cygan, Fedor V. Fomin, Lukasz Kowalik. Daniel Lokshtanov, Daniel Marx, Marcin Pilipczuk, Michal Pilipczuk, and Saket Sourabh. Springer. 2015
Reference: (1) Parameterized Complexity, R. G. Downey, and M. R. Fellows. Springer Science and Business Media. 2012
x Name(s) of Instructor(s) *** SRB x Name(s) of other Departments/
Academic Units to whom the course is relevant
Nil
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xi i
Justification/ Need for introducing the course
Parameterized Algorithms and Complexity is a relatively new and vibrant subfield in Theoretical Computer Science. The main focus of this area is to improve the understanding of computationally hard algorithmic problems and to device practically efficient algorithms for the same.
Name of Academic Unit: Computer Science and Engineering
Level: B. Tech./MS
Programme: B.Tech./MS
i Title of the course CS 601 Software Development for Scientific Computing
ii Credit Structure (L-T-P- C)
3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered
Autumn
v Whether full or half semester course
Full
vi Pre-requisite(s), if any (for the students) – specify course number(s)
Exposure to Data Structures and Algorithms, C / C++ / Java / Matlab
vii Course content Algorithmic Patterns in Scientific Computing: dense and sparse linear algebra, structured and unstructured grid methods, particle methods (N- body, Particle-Particle, Particle-in-cell, Particle-in-a-mesh), Fast Fourier Transforms, Implementing PDEs, C++ standard template library (STL), Introduction to debugging using GDB, GMake, Doxygen, Version Control System, Profiling and Optimization, asymptotic analysis and algorithmic complexity. Mixed-language programming using C, Fortran, Matlab, and Python, Performance analysis and high-performance code, Data locality and auto tuning, Introduction to the parallel programming world.
viii Texts/References - Stroustrup C++ Language Reference
(https://www.stroustrup.com/4th.html)
- Suely Oliveira, David Steward: Writing Scientific Software: A
Guide to Good Style. Cambridge University Press, 2006
- Web references to GNU Make, GDB, Git, GProf, Gcov.
- Code Complete: A Practical Handbook of Software Construction
- https://www2.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS- 2006-183.html
ix Name (s) of the instructor (s)
Nikhil Hegde
x Name (s) of other departments / Academic Units to whom the course is relevant
EE, ME
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xii Justification/ Need for Creating software in Computational Science and Engineering requires
introducing the course skills and tools from many disciplines. This course focuses on how the skills and tools are applied towards larger software development goals in the context of dominant algorithmic patterns or motifs found in scientific computing. The aim of the course is to provide knowledge on how advanced numerical methods and complex algorithms in Scientific Computing can be implemented using C++ to engineer larger systems through software development principles of refactoring, composition, correctness and performance analysis, and debugging. The course initiates students into CS305: Software engineering, a rigorous study of software development principles. Also, the course provides a base for subsequent parallelization optimizations, which is the subject of CS410: Parallel Computing that focuses on parallelizing scientific code (often) using different parallel programming paradigms.
Name of Academic Unit: Computer Science
Level: B.Tech/MS/PhD
Program: B.Tech /MS/PhD
i Title of the course CS 433 Cloud Software Development
ii Credit Structure (L-T-P-C) 1.5-0-0-3
iii Type of Course Elective
iv Semester in which normally to be
offered
Autumn
v Whether Full or Half Semester
Course
Half
vi Pre-requisite(s), if any (For the
students) – specify course number(s) Desirable: Exposure on Operating System, Database, Cloud
Programming language (Java, .Net, NodeJS, HTML/CSS, etc.)
vii Course Content Module 1 - Introduction to Cloud Computing Landscape
● Understand how industries rely on the cloud computing global
infrastructure, Identify the applications and use cases
● Identify the principles and characteristics of Cloud Computing -
IaaS, PaaS, SaaS
● Validate the different patterns of cloud computing adoption
including public cloud services, private and hybrid approaches
● Identify common challenges associated with the adoption of
cloud computing solutions and associated myths
● Compare and contrast with on-premise/traditional versus cloud
● Understand in-country data regulations, data sovereignty
considerations
Module 2 - Cloud Computing Technology
● Understand Virtualization Concepts - data, compute, network,
operating system, HCI
● Understand Cloud Infrastructure -Backup, Restore, Migration,
DC/DR, HA use cases
● Understand Programming concepts Cloud-native apps,
Serverless, Containers
● Learn Containers– Kubernetes, Docker, containers
Module 3 - Using Managed Cloud Services
● Learn 12-factor Application Architecture, api, Microservices,
databases - sql, no-sql, object store
● Application and Microservice Security- OAuth, access tokens
● Understand Autoscale - horizontal and vertical scaling, logging
and monitoring aspects of apps and infrastructure
● Learning DevOps frameworks - toolchains, ci/cd, blue/green
deployment, canary deployment
Module 4 - Case Studies - Public Cloud Provider – aws, azure,
ibmcloud
viii Texts/References Text Books:
- Thomas Erl, Zaigham Mahmood, Ricardo Puttini, “Cloud
Computing Concepts, Technology & Architecture”, Pearson,
2013.
Reference Books: - Boris Scholl, Trent Swanson, Peter Jausovec, “Cloud Native”,
O’Reilly, 2019.
Resources from Internet:
- Public Cloud Documentations:
- https://learning.oreilly.com/library/view/cloud-computing-concepts/9780133387568/
- https://www.amazon.in/Cloud-Computing-Concepts-Technology-Architecture/dp/0133387526/
Class Notes/Lectures
ix Name(s) of Instructor(s) Girish Dhanakshirur
Supported by Rajshekar K
x Name(s) of other Departments/
Academic Units to whom the course
is relevant
EE
xi Is/Are there any course(s) in the
same/ other academic unit(s) which
is/ are equivalent to this course? If
so, please give details.
No
xii Justification/ Need for introducing
the course
The course aims at preparing the students for the next technology
frontier - Cloud computing. While the field is vast, this course
prepares students in core cloud concepts, architectures,
programming languages, frameworks, deployments, etc., with
hands-on labs. The course will act as a foundation for further
research or certification. Many Public Cloud vendors offer free
students access to get hands-on experience on what they learn in the
course. Students will complete few labs using those Public Cloud
platforms.
Name of Academic Unit: Computer Science and Engineering
Level: B.Tech.
Programme: B.Tech
i Title of the course CS 305 Software Engineering
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Core
iv Semester in which normally
to be offered
Spring
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For
the students) – specify course
number(s)
vii Course Content Introduction
What is Software Engineering.
Software Development Life-cycle
Requirements analysis, software design, coding,
testing, maintenance, etc.
Software life-cycle models
Waterfall model, prototyping, interactive
enhancement, spiral model. Role of Management in
software development. Role of metrics and
measurement.
Software Requirement Specification
Problem analysis, requirement specification,
validation, metrics, monitoring and control.
System Design
Problem partitioning, abstraction, top-down and
bottom-up design, Structured approach. Functional
versus object-oriented approach, design specification
and verification metrics, monitoring and control.
Software Architecture
Coding
Top-down and bottom-up, structured programming,
information hiding, programming style, and internal
documentation. Verification, Metrics, monitoring and
control.
Testing
Levels of testing functional testing, structural testing,
test plane, test cases specification, reliability
assessment.
Software Project Management
Cost estimation, Project scheduling, Staffing, Software
configuration management, Quality assurance, Project
Monitoring, Risk management, etc. including tools for
software development to release, supporting the whole
life cycle.
viii Texts/References 1. Software Engineering: A Practioner’s approach,
R.S. Pressman, McGraw Hill, 8th edition
2. Introduction to Software Engineering, Pankaj Jalote,
Narosha Publishing
3. The Unified Software Development Process, I.
Jacobson, G. Booch, J. Rumbaugh, Pearson Education
4. Software Architecture in Practice, L. Bass, P.
Clements, R. Kazmann, 3rd ed., Addison Wesley
ix Name(s) of Instructor(s) NLS
x Name(s) of other
Departments/ Academic
Units to whom the course is
relevant
No
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are
equivalent to this course? If
so, please give details.
No
xii Justification/ Need for
introducing the course
To teach students the engineering approach to software
development starting from understanding and
documenting user requirements to the design,
development, testing and release management where
we all take into account non-functional requirements
and engineer them explicitly. The course brings out
various lifecycle activities in the conventional as well
as agile methodologies. It emphasizes modern
practices and tools for a successful engineering of a
usable and maintainable product.
EE Department Name of Academic Unit: Electrical Engineering
Level: UG
Programme: B.Tech.
i. Title of the Course CS 427 Mathematics for Data Science
ii. Credit Structure L T P C 3 0 0 6
iii. Prerequisite, if any Exposure to basic concepts in calculus and linear algebra iv. Course Content
(separate sheet may be used, if necessary)
Introduction to Data science and Motivation for the course. Review of calculus, naïve set theory, notion of limits, ordering, series and its convergence. Introduction to Linear Algebra in Data science, notion of vector space, dimension and rank, algorithms for solving linear equations, importance of norms and notion of convergence, matrix decompositions and its use. Importance of optimization in data science: Birds view of Linear Regression, Multivariate Regression, Logistic Regression etc. Convex Optimization: Convex sets, convex functions, duality theory, different types of optimization problems, Introduction to linear program. Algorithms: Central of gravity method, Gradient descent methods,Nestrov acceleration, mirror descent/Nestrov dual averaging, stochastic gradient methods,Rmsprop,SIGNSGD, ADAMalgorithm etc. Non-convex optimization: Demonstration of convex methods on non- convex problems; merits and disadvantages.
v. Texts/References (separate sheet may be used, if necessary)
1. C. Bishop, “Pattern Recognition and Machine Learning,” Springer, 2006.
2. S. Boyd and L. Vandenberghe, “Convex Optimization,” Cambridge university press, 2018 (reprint).
3. Prateek Jain and PurushotamKar, “Non-Convex Optimization
for Machine Learning,” Now publisher, 2017. vi. Instructor (s) B. N. Bharath vii. Name of
departments to whom the course is relevant
Computer Science and Engineering, Electrical Engineering and Mechanical Engineering
viii Justification Solving optimization problem is a key ingredient of any data science/Machine Learning (ML) task. It is important to understand how to state problem of practical interests in the language of optimization, and solve it. This course aims to achieve this goal by providing theory and algorithms to solve optimization problems that arise in typical ML problems.
Name of Academic Unit: Electrical Engineering
Level: UG/PG
Programme: B.Tech./M.S./Ph.D.
i. Title of the Course EE 429 Design of Power Converters
ii. Credit Structure (2-0-1-6)
iii. Type of Course Elective
iv. Prerequisite, if any EE222: Introduction to Power Electronics or equivalent as determined by the instructor or faculty advisor.
v. Course Content
(separate sheet may be used, if necessary)
Gate drives for BJT, MOSFET and IGBT, heatsink selection, snubber
circuits, buck, boost, and buck-boost converters, isolated converters like
forward, push-pull, half-bridge, full-bridge, and flyback types, design of
magnetics for inductors and transformers, inverters, PWM generation,
control of power converters: single loop and double loop controls;
voltage mode and current mode control, peak current control,
hysteresis control space vector PWM, d-q axis theory for 2 and 3 phase
applications, intro to induction machine design and winding.
vi. Texts/References (separate sheet may be used, if necessary)
1. Power Electronics: Essentials & Applications., L Umanand,
Wiley 2009.
2. Fundamentals of Power Electronics, Robert W Erickson and Dragan Maksimovic, Springer, 3ed, 2020.
3. Daniel W Hart, Introduction to Power Electronics, Prentice-Hall, 1997.
4. Mohan, N., et al, Power Electronics, John Wiley, 1989.
vii. Instructor (s) Satish Naik
viii .
Name of dept to whom the course is relevant
Electrical Engineering
ix Justification This course is a design-oriented course aimed at power converter
system design. The course focuses on the design of switched-mode
converter circuits. The following topics are discussed with emphasis on
design: gate drives for BJT, MOSFET and IGBT, heatsink selection,
snubber circuits, buck, boost, and buck-boost converters, isolated
converters like forward, push-pull, half-bridge, full-bridge, and flyback
types, design of magnetics for inductors and transformers, inverters,
PWM generation, space vector PWM, d-q axis theory for 2 and 3 phase
applications, intro to induction machine design and winding.
Name of Academic Unit: Electrical Engineering Level:
UG/PG
Programme: B.Tech./M.S./Ph.D.
i. Title of the Course EE 431 Advanced Power Systems
ii. Credit Structure (L-T-P-C) 3-0-0-6
iii. Type of Course Elective
iv. Semester in which normally to be offered
Autumn
v. Whether full or half semester course Full
vi. Prerequisite, if any EE223: Introduction to Power Systems or equivalent as determined by the instructor or faculty advisor.
vii. Course Content
(separate sheet may be used, if necessary)
Symmetrical Components; Fault Analysis in Power Systems; Power System Stability; Power System Transients; Circuit Breakers; Protection of Transmission Lines, Generators, Transformers; Economic Dispatch; Automatic Generation Control.
viii .
Texts/References (separate sheet may be used, if necessary)
1. Power System Analysis, Bergen & Vittal, 2nd Ed,
Pearson, 1999.
2. Power System Analysis, Hadi Saadat, 2011, ISBN-
10: 0984543864.
3. Power System Analysis, Grainger & Stevenson,
McGraw Hill, 2017, ISBN-10: 9780070585157
4. Power System Engineering, Nagrath & Kothari,
McGraw-Hill, 3rd Ed, 2019, ISBN-10 :
9353165113.
ix. Instructor (s) Pratyasa Bhui
x. Name (s) of other departments / Academic Units to whom the course is relevant
Electrical Engineering
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xii. Justification This course is important to learn essential topics like fault
calculations, stability analysis of power systems after
disturbances, transients in voltage during with fault clearing,
designing power system protection for lines transmission
lines, generators and transformers. This will also cover some
aspects of power system operation like economic dispatch
and automatic generation control. There will be MATLAB
based simulation experiments on every topic covered in this
course.
Name of Name of Academic Unit: Electrical Engineering Level: B. Tech. Programme: B.Tech.
i Title of the course EE 323 Digital Communication and Coding Theory ii Credit Structure (L-T-P-C) 2-0-2-6 iii Type of Course Elective iv Semester in which normally to be
offered Autumn
v Whether Full or Half Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
Signals and Systems, Introduction to Communication Systems, Introduction to Probability
vii Course Content Digital Modulation - Signal constellations, Nyquist’s Sampling Theorem and Criterion for ISI Avoidance, Linear modulation Optimal Demodulation – Review of Hypothesis Testing, ML and MAP decision rules, Signal Space Concepts, Optimal Reception in AWGN and performance analysis of various modulation schemes. Source Coding - Entropy, Shannon’s source coding theorem (without proof), Huffman Codes Channel Coding – Mutual information, Shannon’s channel coding theorem (without proof), Linear codes, soft decisions and introduction to cyclic codes
Lab Component: Practical experiments in-line with the content of “Digital Communication and Coding Theory” course covering transmission and reception mechanisms corresponding to digital communication.
● Digital modulation and demodulation – PSK
and QAM
● Channel Modelling
● Performance analysis of Huffman
coding Performance Analysis of linear
and cyclic codes
viii Texts/References 1. Upamanyu Madhow, ̀ `Introduction to
Communication Systems," Cambridge
university press, 2008 edition.
2. Cover and Thomas, “Elements of Information
Theory,” Wiley India Pvt. Ltd., 2006.
ix Name(s) of Instructor(s) Naveen M B x Name(s) of other Departments/
Academic Units to whom the course is relevant
None
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xii Justification/ Need for introducing the course
The current and next generation wireless communication technologies use digital communication. The underlying procedures in these systems mainly involve digital modulation and source coding and channel coding. This course enables the student to understand the basic principles behind these topics. The lab component provides a hands-on experience of various topics covered in the theory course. Together, they will enable the student to have a strong background of the basics of digital communication.
Name of Academic Unit: Electrical Engineering Level: PG/UG
Programme: B. Tech/MS/PhD
i Title of the course EE 406 Speech Processing
ii Credit Structure (L-T-P-C) (3 0 0 6)
iii Type of Course Elective course
iv Semester in which
normally to be offered
Autumn or Spring
v Whether Full or Half Semester
Course
Full
vi Pre-requisite(s), if any (For
the students) – specify course
number(s)
Exposure to probability concepts.
vii Course Content* Introduction: Speech production and perception, nature of
speech; short-term processing: need, approach, time,
frequency and time- frequency analysis.
Short-term Fourier transform (STFT): overview of
Fourier representation, non-stationary signals,
development of STFT, transform and filter-bank views
of STFT.
Cepstrum analysis: Basis and development, delta, delta-
delta and mel-cepstrum, homomorphic signal processing,
real and complex cepstrum.
Linear Prediction (LP) analysis: Basis and development,
Levinson- Durbin’s method, normalized error, LP spectrum, LP
cepstrum, LP residual.
Sinusoidal analysis: Basis and development, phase
unwrapping, sinusoidal analysis and synthesis of speech.
Applications: Speech recognition, speaker recognition, speech synthesis, language and dialect identification and speech coding.
Viii Texts/References 1. L.R. Rabiner and R.W. Schafer, Digital Processing of
Speech Signals Pearson Education, Delhi, India, 2004
2. J. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis, Discrete-
Time Processing of Speech Signals, Wiley-IEEE Press, NY,
USA, 1999.
3. D. O’Shaughnessy, Speech Communications:
Human and Machine, Second Edition, University Press,
2005.
4. T. F. Quatieri, “Discrete time processing of speech
signals”, Pearson Education, 2005.
5. L. R. Rabiner, B. H. Jhuang and B. Yegnanarayana,
“Fundamentals of speech recognition”, Pearson
Education, 2009.
ix Name(s) of Instructor(s) *** S R Mahadeva Prasanna
x Name(s) of other
Departments/ Academic
Units to whom the course is
relevant
CS
xii Justification/ Need for
introducing the course
This course aims at providing an overview to the speech processing area. Speech processing being an application area of probability, signal processing and pattern recognition, the same will be suitable for both electrical engineering and computer science and engineering students. The course contents include introduction to speech processing, speech signal processing methods like short term Fourier transform, Cepstral analysis, linear prediction analysis, sinusoidal analysis. Some of the applications like speech recognition and speech synthesis will also be taught.
Name of Academic Unit: Electrical Engineering Level: PG/UG Programme: B. Tech/MS/PhD
i. Title of the Course EE 414 Speech Processing Laboratory
ii. Credit Structure L T P C
0 0 3 3
iii. Prerequisite, if any Currently taking or already taken Speech Processing theory course
iv. Course Content
(separate sheet may
be used, if
necessary)
The lab will closely follow the theory course. The idea is to have the students
implement the basic algorithms on different topics studied in the speech
processing theory course.
v. Texts/References
(separate sheet may
be used, if
necessary)
1. L.R. Rabiner and R.W. Schafer, Digital Processing of Speech
Signals Pearson Education, Delhi, India, 2004
2. J. R. Deller, Jr., J. H. L. Hansen and J. G. Proakis, Discrete-Time
Processing of Speech Signals, Wiley-IEEE Press, NY, USA, 1999.
3. D. O’Shaughnessy, Speech Communications: Human and
Machine, Second Edition, University Press, 2005.
4. T. F. Quatieri, “Discrete time processing of speech signals”,
Pearson Education, 2005.
5. L. R. Rabiner, B. H. Jhuang and B. Yegnanarayana,
“Fundamentals of speech recognition”, Pearson Education, 2009.
vi. Instructor (s) S. R. Mahadeva Prasanna
vii. Name of
departments to
whom the course is
relevant
Computer Science and Engineering, Electrical Engineering and Mechanical
Engineering
viii Justification Speech Processing Laboratory is important to reinforce different concepts
that will be studied as part of the theory course.
MMAE Department Academic Unit: Mechanical Engineering
Level: UG
Programme: B. Tech
i Title of the course ME 429 Solar Energy Collector Systems
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of course Elective
iv Semester in which normally
to be offered
Odd/Even
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For
the students) – specify course
number(s)
--
vii Course content Recap of solar energy: Solar angles, Declination of
Sun, Solar Tracking, Sun path diagram, Solar radition
(4 hrs) Solar thermal-energy collectors: Basic
construction and design aspects of flat-plate collector,
stationary compound parabolic collector, evacuated
tube collector, Sun-tracking concentrating collectors:
Parabolic trough collector, Linear Fresnel reflector,
Parabolic dish reflector, Heliostat field collector: Solar
thermal-electric power. (6 hrs)
Thermal analysis of solar collectors: Thermal
analysis of flat-plate collectors including air- collectors,
Thermal analysis of compound parabolic collectors,
Thermal analysis of parabolic trough collectors,
Collector thermal efficiency, Collector incidence angle
modifier, acceptance angle of concentrating collectors,
Uncertainty quantification in solar collector testing. (8
hrs)
Solar water-heating (SWH) systems: Passive systems
as thermosiphon, integrated collector storage, Active
systems as direct circulation, indirect water-heating, air-
water-heating, and Pool heating, Heat storage as
sensible or latent hear, Solar ponds, Applications of
SWHs, Module and array design of SWH systems. (8
hrs)
Solar air-heating (SAH) systems: Active, hybrid or
passive, With or without storage, With or without fins,
Single/double pass, performance enhancement
techniques for SAHs, intergartion of thermal-storage
unit with SAHs, Applications of SAHs, Solar sterling
engine. (8 hrs)
Photovoltaic (PV) systems: Photovoltaic effect, PV
cell characteristics, Module and array design of PV
systems, PV technology and materials, PV module
equipment, Applications of PVs, Design and sizing of
PVs, Hybrid PV/T systems. (8 hrs)
viii Texts/References Textbooks: 1. S.A. Kalogirou, Solar Energy
Engineering: Processes and Systems, Elsevier; 2nd Ed.,
2014. 2. S.P. Sukhatme, J.K. Nayak, Solar Energy:
Principles of Thermal Collection and Storage, Tata
McGraw-Hill Education, 3rd Ed.,1996.
References: 1. V. Sivaram, Taming the Sun –
Innovations to Harness Solar Energy and Power the
Planet, 1st Ed., MIT Press, 2018. 2. JA. Duffie, WA.
Beckman, Solar Engineering of Thermal Processes,
Wiley, 4th Edition, 2013.
ix Name(s) of the Instructor(s) Dhiraj V Patil
x Name(s) of other
Departments/ Academic
Units to whom the course is
relevant
Electrical Engineering
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are
equivalent to this course? If
so, please give details.
No
xii
Justification/ Need for
introducing the course
The origin and continuation of humankind is based on
solar energy. This course introduces basics of solar
energy harvesting, thermal-analysis of various
collectors. Next, the course introduces the design and
performance aspects of solar water-heating, air-heating
systems and photovoltaic modules. The course is
essential for the current technologist foreseeing the
future use of green, renewable and sustainable energy.
Name of Academic Unit: Mechanical, Materials and Aerospace Engineering
Level: UG Only Programme: B.Tech.
i Title of the course ME 323 Introduction to Aerospace Engineering
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Even/Odd
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any – specify course number(s) Thermodynamics, Fluid Mechanics during UG
vii Course
Content
Historical Developments in Aviation, Aviation milestones, Components of an aircraft, Types of
aerial vehicles.
Basic Aerodynamics: Fluid dynamic equations & their basis, Ideal fluid, viscous flows, Flow past a
body, Flow Separation, Generation of Lift, Drag & Moment, Non-dimensional coefficients, Airfoils
& Wings, Airfoil families, Supersonic flight, Wave Drag, Aircraft Drag Polar,
Properties of atmosphere: ISA, IRA, Pressure altitude, Altimeter; Aircraft speeds TAS, EAS, CAS,
IAS.
Aircraft Performance: Steady level flight, Altitude effects, Absolute ceiling, steady climbing flight,
Energy methods, V-n diagram, Range and Endurance, Sustained level turn, pullup, Take-off and
Landing
Longitudinal Static Stability, Control systems and Neutral Point
Propulsion: Introduction to various aircraft propulsive devices: Piston-prop, Turbo-prop, Turbojet,
Turbofan, Turboshaft, Vectored- thrust, Lift engines. Gas Turbine Cycles and cycle based
performance analysis; Introduction to gas turbine components - Intake, Compressors, Turbines,
Combustion Chamber, Afterburner, and Nozzle. Single spool and Multi- spool engines. Power-plant
performance with varying speed and altitude.
Aircraft structures: Introduction to Flight Vehicle Structures and Materials, Forces Acting on an
aircraft.
viii Texts/
References 1. Anderson, J. D., The Aeroplane, a History of its Technology, AIAA Education Series, 2002.
2. Anderson, J. D., Introduction to Flight, McGraw-Hill Professional, 2005.
3. Hill, P., and Peterson, C., Mechanics and Thermodynamics of Propulsion, ISBN 978-0132465489,
Pearson Education, 2009.
4. Sun, C.T., Mechanics of Aircraft Structures, John Wiley and Sons, New York, 2006.
5. Megson, T.H.G., Aircraft Structures for Engineering Students, Butterworth-Heinemann, Oxford,
2013. Lecture notes.
ix Name(s) of Instructor(s) MM
x Name(s) of other Departments/ Academic Units to whom the course is relevant
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are
equivalent to this course? If so, please give details. Nil
xii Justification/ Need for
introducing the course This course would introduce fundamental principles of flight including the basic aerodynamics, flight
mechanics, propulsion, aircraft structures and materials. To a Mechanical Engineering student, this
course is important to understand the similarities and differences between the operations of ground-
based and aerospace vehicles. At the end of this course, students will be able to estimate various
flight parameters, their variation with respect to varying speed and altitude, and understand the
importance of different modifications brought in the development of aerospace vehicles.
Name of Academic Unit: Mechanical Engineering
Level: B. Tech.
Programme: B.Tech.
i Title of the course ME 421 Turbomachines
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Even
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any – specify course number(s) Fluid Mechanics; Thermodynamics
vii Cour
se
Cont
ent
Introduction: (2)
Classifications of Turbomachines, Advantages of Rotary over Reciprocating, Applications
Basic Fluid Mechanics, Thermodynamics: (3)
Conservation of Mass, Momentum and Energy, Work and Energy Equations in a Rotating Frame with
Constant Angular Velocity, Static and Stagnation Properties, Compressible gas flow relations,
Mechanical Efficiency and Internal Efficiency, Internal Energy & Entropy
Dynamic Similitude: (4)
Definition, Dimensionless Parameter Groups with a Constant Density Fluids, Buckingham PI Theorem
and its Significance, Characteristic Numbers of Turbomachines, Specific Speed and Specific Diameter,
Power Specific Speed, Imperfect Similitude,
Hydraulic Pumps: (6)
Components, Priming of Pumps, Head Developed by pump, NPSHA and NPSHR, Cavitation,
Characteristics of pumps, Types of vanes, Specific speed, Special Pumps e.g. Borehole Pumps, Slurry
Pumps, Vertical Submerged Pumps.
Hydraulic Turbines: (6)
Hydraulic Energy, Types, Pelton Turbines: Impulse Turbines: Performance Characteristics, Velocity
triangles, Specific Speed, Francis and Kaplan Turbines: Reaction Turbines: Velocity Triangles, Degree
of Reaction and Speed Ratio, Cavitation, Draft Tubes, Conditions for maximum efficiency
Steam Turbines: (6)
Types of Turbines: Impulse and Reaction, Velocity triangles, Efficiencies, Condition for maximum
efficiencies, Compounding of turbines - Velocity and Pressure, Degree of reaction, Reaction Turbines
CD Nozzles: (6)
Relation between area and velocity, Mach Number and Mach Cone, 1D steady isentropic flow, Choking
in isentropic flow, Nozzle efficiency, CD Nozzle and characteristics.
Gas Turbines: (6)
Turbine and compressor cascade, Elementary cascade theory, Cascade nomenclature, Lift and drag,
Turbine cascade correlation, Optimum space-chord ratio of turbine blades (Zweifel), Axial flow turbines:
Two-dimensional Theory, Stage losses and efficiency
Compressors: (4) Axial Flow Compressors, Principle of operation, Work done, power input factor, efficiency, Passage
Vortex and Trailing Vortices, Loss Assessment, Diffuser, Losses in centrifugal compressors, Axial
velocity distribution along blade height, Degree of Reaction, performance characteristics, Radial
compressors
viii Texts /
Ref.
1. Fluid Mechanics and Thermodynamics of Turbomachinery – SL Dixon, Elsevier; 7th edition, BH
2. Gas Turbine Theory, Cohen, Rogers and Saravanamuttoo, Pearson India 3. Turbines, compressors and Fans, SM Yahya, McGraw Hill Education, 2017.
4. Hydraulic Machines, VP Vasandani, Khanna Publishers
5. An Introduction to Energy Conversion: Turbomachinery - Vol. III, Kadambi & Prasad, NAIP, 2011.
ix Name(s) of Instructor(s) DVP, SS
x Name(s) of other Departments/ Academic Units to whom the course is relevant --
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are
equivalent to this course? If so, please give details. NA
xii Justification/ Need
for introducing
the course
Turbomachines are essential fluid machinery which is present in a day-today practical
usage. The working principles, design principles are essential for a BTech (Mech.). As this
is an application of the core Mechanical courses, the course is listed as an elective.
Academic Unit: Mechanical Engineering
Level: UG
Programme: B. Tech
i Title of the course ME 403 Vibrations of Linear Systems
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of course Elective
iv Semester in which normally
to be offered
VII
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For
the students) – specify course
number(s)
--
vii Course content • Concepts of Vibrations: Harmonic motion and
definitions and terminology, Harmonic analysis,
Fourier series expansion, Importance of vibration, Basic
concepts of vibration, Classification of Vibration,
Vibration analysis procedure.
• Characteristics of Discrete System Components,
Equivalent Springs, Dampers and Masses, Modeling of
Mechanical Systems, System Differential Equations of
Motion, Nature of Excitations, System and Response
Characteristics – Superposition Principle, Vibration
about Equilibrium Point.
• One DOF systems: Free Vibrations – Undamped and
damped vibrations, Harmonic Oscillator, Types of
damping, Viscously Damped Single DOF Systems,
Measurement of Damping, Coulomb Damping – Dry
Friction.
• Forced Vibrations – Response of Single DOF System to
Harmonic Excitations, Frequency Response Plots,
Systems with Rotating Unbalanced Masses, Whirling of
Rotating Shafts, Harmonic Motion of the Base,
Vibration Isolation, Vibration Measuring Instruments –
Accelerometers, Seismometers, Energy Dissipation,
Structural Damping, Response to Periodic Excitations,
Fourier Series.
• Response of Single DOF systems to Nonperiodic
Excitations, The Unit Impulse - Impulse Response, The
Unit Step Function - Step Response, The Unit Ramp
Function - Ramp Response, Response to Arbitrary
Excitations - The Convolution Integral, Shock
Spectrum, System Response by the Laplace
Transformation Method -Transfer Function, General
System Response.
• Two DOF Systems: System Configuration, Equations
of Motion-2 DOF Systems, Free Vibration of
Undamped Systems, Natural Modes, Response to Initial
Excitations, Coordinate Transformations – Coupling,
Orthogonality of
3
Modes - Natural Coordinates, Beat Phenomenon,
Response of Two-Degree-of-Freedom Systems to
Harmonic Excitations, Undamped Vibration Absorbers.
• Vibrations of Continuous Systems: Vibrating String,
Longitudinal vibrations of Bar, Torsional vibrations of
Rod. Lateral vibrations of Beam.
viii Texts/References TEXTBOOKS 1. S S Rao, Mechanical Vibrations, Pearson
Education, 5th Edition, 2004.
REFERENCES
1. W T Thomson, M D Dahleh and C Padmanabha,
Theory of Vibration with applications, Pearson
Education, 2008.
2. Leonard Meirovitch, Fundamentals of
Vibrations,
3. McGraw-Hill, 2000.
4. Den Hartog, Mechanical Vibrations, Dover
Publications.
ix Name(s) of the Instructor(s) Shrikanth V.
x Name(s) of other
Departments/ Academic
Units to whom the course is
relevant
Electrical Engineering
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are
equivalent to this course? If
so, please give details.
No
xii
Justification/ Need for
introducing the course
This course deals with the study of vibration in
mechanical systems which is concerned with the
oscillatory motions of bodies and the forces associated
with them. This course aims to provide you with an
understanding of the nature and behaviour of dynamic
engineering systems and the capability of applying the
knowledge of mathematics, science, and engineering to
solve engineering vibration problems.
Academic Unit: Mechanical Engineering
Level: UG
Programme: B. Tech
i Title of the course ME 401 Finite Element Analysis
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of course Elective
iv Semester in which normally
to be offered
Odd/Even
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any (For
the students) – specify course
number(s)
Mechanics of Materials
vii Course content Approximate solution of differential equations -
- Weighted residual techniques. Collocation,
Least Squares and Galerkin methods. Piecewise
approximations. Basis of Finite Element
Method. Formulation of the matrix method --
"stiffness matrix"; transformation and assembly
concepts. Example problems in one dimensional
structural analysis, heat transfer and fluid flow.
Elements of Variational calculus. Minimisation
of a functional. Principle of minimum total
potential. Piecewise Rayleigh - Ritz method and
FEM. Comparison with weighted residual
method.
Two dimensional finite element formulation.
Isoparametry and numerical integration.
Algorithms for solution of equations.
Convergence criteria, patch test and errors in
finite element analysis.
Finite element formulation of dynamics.
Applications to free vibration problems.
Lumped
and consistent mass matrices. Algorithms for
solution of eigenvalue problems
viii Texts/References 1. Bathe, K. J., Finite element procedures in
Engineering Analysis, Prentice Hall of India,
1990.
2. Cook, R.D., D. S. Malkus and M. E. Plesha,
Concepts and Applications ofFinite element
analysis, John Wiley, 1989.
3. Reddy, J. N., An Introduction to the Finite
Element Method, 2nd ed., McGraw Hill, 1993.
4. Seshu, P. Finite Element Method, Prentice Hall
of India, New Delhi, 2003.
5. Zienkiewicz, O. C., and K. Morgan, Finite
elements and approximation, John Wiley, 1983.
6. Zienkiewicz, O. C., and R. L. Taylor, The finite
element method, vol.1&2, Tata McGraw Hill
ix Name(s) of the Instructor(s) Prof. Amar Gaonkar
x Name(s) of other
Departments/ Academic
NA
Units to whom the course is
relevant
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are
equivalent to this course? If
so, please give details.
No
xii Justification/ Need for
introducing the course
FEM is a numerical method to solve PDEs. The course
introduces the basic concepts and principles involved in
FE formulation of PDEs. Applications to domains
spanning structural mechanics , fluid mechanics and
heat transfer are taken to illustrate the concepts
Name of Academic Unit: Mechanical, Materials and Aerospace Engineering
Level: UG-PG Programme: B.Tech./M. Tech./M.S./PhD
i Title of the course ME 435 Design of Mechatronic Systems
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to be offered Even/Odd
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any – specify course number(s)
vii Course
Content
Introduction: Elements of mechatronics system: Sensor, actuator, plant, and controller.
Applications of mechatronics system. Systems like CDROM, scanner opened to see whats there
inside and why?.
Integrated mechanical-electronics design philosophy. Examples of real life systems. Smart sensor
concept and utility of compliant mechanisms in mechatronics.
Microprocessor building blocks, combinational and sequential logic elements, memory, timing and
instruction execution fundamentals with example of primitive microprocessor.
Microcontrollers for mechatronics: Philosophy of programming interfaces, setting sampling time,
and Getting started with TIVA programming
Microcontroller programming philosophy emphasis on TIVA, programming different interfaces
PWM, QEI etc. Mathematical modeling of mechatronic systems, Modeling friction, DC motor,
Lagrange formulation for system dynamics.
Dynamics of 2R manipulator, Simulation using Matlab, Selection of sensors and actuators.
Concept of feedback and closed loop control, mathematical representations of systems and control
design in linear domain, Basics of Lyapunov theory for nonlinear control, notions of stability,
Lyapunov theorems and their application
Trajectory tracking control development based on Lyapunov theory, Basics of sampling of a signal,
and signal processing
Digital systems and filters for practical mechatronic system implementation. Research example/
case studies of development of novel mechatronics system: 3D micro-printer, Hele Shaw system
for microfabrication.
viii Texts/
References Devdas Shetty, Richard A. Kolk, “Mechatronics System Design,” PWS Publishing company
Boukas K, Al-Sunni, Fouad M “Mechatronic,Systems Analysis, Design and Implementation,”
Springer,
Sabri Cetinkunt, “Mechatronics with Experiments,” 2nd Edition, Wiley
Janschek, Klaus, “Mechatronic Systems Design,” Springer
ix Name(s) of Instructor(s) SDR, MM
x Name(s) of other Departments/ Academic Units to whom the course is relevant EE
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are
equivalent to this course? If so, please give details. Nil
xii Justification/ Need for
introducing the course This course is geared towards developing skills of candidates towards conceiving new mechatronics
products based on raw ideas and develop them. The course focuses on hands-on experience along
with a project, and offers a lot of practical tips to make theory work in practice. Furthermore, the
course catalyzes integrated thinking in mechanical and electronics domain, which is crucial to
successful product design and development.
Chemistry Department Name of Academic Unit: Chemistry
Level: UG/PG
Programme: B.Tech. / MS /M.Tech. /Ph.D.
i Title of the course CH 405 Our Health and Medicine
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Elective
iv Semester in which normally to
be offered
Autumn
v Whether full or half semester
course
Full Semester
vi Pre-requisite(s), if any (for the
students) – specify course
number(s)
None
vii Course content Health and nutrition, role of different nutrients
(carbohydrates, proteins, fats, vitamins, and minerals),
diet and metabolism, basic introduction to human
physiology, communicable diseases (common bacterial
and fungal infections, antibiotics and resistance, common
viral infections, corona virus (SARS, MERS, SARS-
COV-2), vaccine and antivirals, non-communicable
diseases (diabetes, cancer), basic medicinal chemistry,
preventative and community medicine, health policies,
healthcare system, health awareness and best practices
viii Texts/References 1. Oxford textbook of medicine: Infection ed. by
David Warrell and Timothy Cox, 1st edition, OUP, 2012.
2. Textbook of community medicine ed. by Rajvir
Bhalwar, 2nd edition, Wolters Kluwer, 2017. 3. Koneman's textbook of diagnostic microbiology,
7th edition, Wolters Kluwer, 2017.
4. Principles of therapeutic nutrition and dietetics,
by Avantina Sharma, 1st edition, CBS, 2017. 5. Textbook of medical biochemistry by Rajinder
Chawla, E.H. El-Metwally and Suchanda Sahu,
2nd edition, Wolters Kluwer, 2017.
6. An introduction to medicinal chemistry by
Graham L. Patrick, 3rd edition, OUP, 2005. ix Name (s) of the instructor (s) Nilkamal Mahanta
x Name (s) of other departments
/ Academic Units to whom the
course is relevant
All departments with B. Tech/MS and PhD courses are
encouraged
xi Is/Are there any course(s) in
the same/ other academic
unit(s) which is/ are equivalent
to this course? If so, please
give details.
No
xii Justification/ Need for
introducing the course This course is designed to spread awareness among
students on the best practices to maintain a good health
and to emphasize on the role of diet and nutrition. It will
also encompass common diseases that we encounter
often and various ways to prevent and mitigate them with
the basic understanding of human physiology and
medicinal chemistry. In the wake of this global COVID-
19 pandemic, fundamental information on good health
and community medicine as well as healthcare
system/policies has become indispensable. This course
will provide the necessary foundation on the mechanism
of various commonly used drugs, preventative medicine,
and suitable family health practices which will facilitate
one in making informed decisions on prevention,
diagnosis, treatment, care, and support when required.
i. Title of the Course CH 303 Bioenergy and Biofuels
ii. Credit Structure L T P C
3 0 0 6
iii. Prerequisite, if any Exposure to basic concepts in biochemistry, chemistry, energy
iv. Course Content
(separate sheet may
be used, if necessary)
Introduction to bioenergy, basics of biomass technology and resources,
cellular metabolism and bioenergetics, quantitative methods, enzymes
involved in bioenergy production, biofuels (biodiesel, bio methanol,
biomethane, bioethanol, biobutanol, biohydrogen etc.) sources and uses,
bioenergy crops, fermentation and photobiological methods, microbial
production of biofuels, bioreactors, bio gas, microbial fuel cells, thermal
conversion technologies and gasification, biooil and biopower, biorefineries,
bioenergy systems analysis, economics, bioenergy for a sustainable future
v. Texts/References
(separate sheet may
be used, if necessary)
1. Y. Li, and S. K. Khanal, “Bioenergy: Principles and applications” Wiley-
Blackwell, 1st Edition, 2016.
2. N. G. Halford “An introduction to bioenergy” Imperial college press,
1st edition, 2015.
3. O. Konur, “Bioenergy and biofuels,” CRC press, 1st edition, 2017.
4. A. Dahiya, “Bioenergy: Biomass to biofuels,” Academic press, 1st
edition, 2014
5. C. Drapcho, N.P. Nhuan, T. Walker, “Biofuels Engineering Process
Technology” McGraw Hills, 1st Edition, 2008.
6. J. Cheng Ed. “Biomass to Renewable Energy Processes” CRC press, 1st
Ed, 2017.
vi. Instructor (s) Prof. Nilkamal Mahanta and other instructors (if any)
vii. Name of
departments to
whom the course is
relevant
Computer Science and Engineering, Electrical Engineering and Mechanical
Engineering, Chemical Engineering, Chemistry, BSBE
viii Justification This course focuses on bioenergy which is an alternate renewable source of
energy as well as forms the basis for an environmentally friendly technology.
Students will be introduced to different forms of bioenergy and biofuels and
their applications in the society. As clean forms of energy are the need of the
hour, this course is aptly suited to be offered for bachelor level students to
get them interested in energy and environmental related technologies.
Name of Academic Unit : Chemistry
Level : B.Tech
Programme : B.Tech.
i Title of the course CH 402 Quantum field theory
ii Credit Structure (L-T-P-C) 2-1-0-6
iii Type of Course Elective course
iv Semester in which normally
to be offered
Autumn
v Whether Full or Half
Semester Course
Full
vi Pre-requisite(s), if any
(For the students) – specify
course number(s)
Exposure to Physics, Chemistry and Mathematics
vii Course Content* Introduction: Review of Classical Field Theories and the need for Quantum
Field Theory Bosonic Fields: Second quantization of bosons; non-
relativistic quantum fields and the Landau Ginzburg theory; relativistic free
particles and the KleinGordon field; causality and the Klein-Gordon
propagator; quantum electromagnetic fields and photons. Fermionic Fields:
Second quantization of fermions; particle-hole formalism; Dirac equation
and its nonrelativistic limit; quantum Dirac field; spinstatistics theorem;
Dirac matrix techniques; Lorentz and discrete symmetries. Interacting Fields
and Feynman Rules: Perturbation theory; correlation functions; Feynman
diagrams; S-matrix and crosssections; Feynman rules for fermions;
Feynman rules for QED. Functional Methods: Path integrals in quantum
mechanics; "path" integrals for classical fields and functional quantization;
functional quantization of QED; QFT and statistical mechanics; symmetries
and conservation laws. Quantum Electrodynamics: Some elementary
processes; radiative corrections; infrared and ultraviolet divergencies;
renormalization of fields and of the electric charge; Ward identity.
Renormalization Theory: Systematics of renormalization; `integration out'
and the Wilsonian renormalization; `running' of the coupling constants and
the renormalization group. Non-Abelian Gauge Theories: Non-abelian
gauge symmetries; Yang-Mills theory; interactions of gauge bosons and
Feynman rules; Fadde'ev-Popov ghosts and BRST; renormalization of the
YM theories and the asymptotic freedom; the Standard Model.
Viii Texts/References 1. “An Introduction to Quantum Field Theory”, Michael Peskin and
Daniel Schroeder (Addison Wesley)
2. “Introduction to Quantum Field Theory”, A. Zee
3. “Quantum Field Theory”, Lewis H. Ryder
4. “Quantum Field Theory and Critical Phenomena”, by Jean Zinn-
Justin.
5. “Quantum field Theory for the Gifted Amateur”, T. Lancaster and
Stephen J. Blundell
6. NPTEL lectures in Quantum Field Theory
(https://nptel.ac.in/courses/115106065/)
ix Name(s) of Instructor(s)
***
Prof. B. L. Tembe
x Name(s) of other B.Tech. students of all departments
Departments/ Academic
Units to whom the course
is relevant
xi Is/Are there any course(s)
in the same/ other academic
unit(s) which is/ are
equivalent to this course?
If so, please give details.
No
xii Justification/ Need for
introducing the course Quantum Field Theory is one of the basic theories in physics which has met
with great success in explaining a large number of natural phenomena. This
could be of interest to most students with a desire to learn physics and
mathematics and who have a basic background in science in engineering of
up to the third year of IIT B.Tech courses.
HSS Department Name of Academic Unit: HSS Level: B. Tech.
Programme: B.Tech.
i Title of the course HS 301: Philosophy
ii Credit Structure (L-T-P-C) 3-0-0-6
iii Type of Course Core – Humanities
iv Semester in which normally to be offered 1
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
None
vii Course Content 1. What is Philosophy? (Philosophy in Indiaand West)
2. Main Branches of Philosophy
3. Three Laws of Thought
4. Epistemology and Logic (Indian and Western)
5. Metaphysics (Universal and Particular, Substance
and Attributes, Causality, Space, Time, Soul, God,
Freedom)
6. Three Great Greek Philosophers:
Socrates,Plato and Aristotle
7. Modern Philosophy: Rationalism andEmpiricism
(Descartes, Locke, Berkeley and Hume)
8. Ethics (Utilitarianism, Categorical Imperative of
Kant, Ethical Relativism, Bio-Medical Ethics,
Ethical Issues)
9. Indian Philosophy Component(Nishkama-karma of
Gita, Virtue Ethics of Buddhism, Advaita Vedanta).
10. Meaning of Life.
viii Texts/References 1. Ganeri, Jonardon, Philosophy in Classical India: An
Introduction and Analysis (London: Routledge, 2001).
2. Maritain, Jacques, An Introduction of Philosophy
(New York and Oxford: Rowman & Littlefield, 2005). 3. Mohanty, J. N. Classical Indian Philosophy: An
Introductory Text (New York and Oxford: Rowman &
Littlefield, 2000).
4. Nagel, Thomas, What Does It All Mean? A Short
Introduction to Philosophy (Oxford: Oxford University
Press, 2004).
5. Russel, Bertrand, The Problems of Philosophy
(Oxford: Oxford University Press, Reprint by Kalpaz
Publication, 2017).
6. Sharma, Chandradhar, A Critical Survey of Indian
Philosophy (Delhi: Motilal Banarsidass, 2016).
7. Thilly, Frank, A History of Philosophy (New Delhi: SBW Publishers, 2018).
8. Williams, Bernard, Morality: An Introduction to
Ethics (Cambridge: Cambridge University Press, 2012).
ix Name(s) of Instructor(s) Prof. Jolly Thomas.
x Name(s) of other Departments/ Academic Units to whom the course is relevant
All
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xii Justification/ Need for introducing the course
HS 301 is a unique course that aims to provide the BTech students an understanding of philosophy and history of ideas. Through this course they are expected to develop philosophical analysis and critical thinking which will enhance their engineering imagination as a skill and profession with the training in epistemology, logic, philosophical speculation and creativity. The ethics-module of the course will help them to think and act ethically in their profession with relation to the societal expectations of their fellow humans in India.
Name of Academic Unit: HSS
Level: UG
Programme: B.Tech.
i Title of the course HS 305 Principles of Finance: Instruments & Investment
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered
Autumn
v Whether Full or Half Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
Nil
vii Course Content* Financial Assets:
Structure of Financial Markets: including Money and Capital
Market and various underlying
Valuation:
Understanding time value of money, Risk adjusted Return
Intrinsic Valuation of financial assets: Debt and Equity with
discounted cash flow model
Risk Management:
Basics of risk assessment, covering Market, Credit, Liquidity,
Operational and Reputational Risk, and risk mitigation using
hedging tools
Macroeconomics and Financial Market
Central banks and financial markets, Liquidity
management, Quantitative Easing, inflation expectations
Investments Rationale:
Behavioural Finance and current studies, role on non-linearity
in financial investment, modelling and real world divergence,
heuristics
Viii Texts/References 1. “Investments”: Zvi Bodie, Alex Kane, Alan J. Marcus and Pitabas Mohanty; 11th edition, McGraw Hill
2. “Options and Other Derivatives”; John C. Hull and
Sankarshan Basu; 10th Edition; Pearson Education
3. “The Psychology of Money”: Morgan Housel
4. Principles of Corporate Finance by Richard A. Brealey,
Stewart C. Myers, and Franklin Allen, McGraw Hill,
2017
Relevant handouts where required will be handed out
and students are expected to refer to the material
covered in the handouts during the course
ix Name(s) of Instructor(s) ***
Vipin Chaudhary
x Name(s) of other Departments/ Academic Units to whom the course is relevant
Undergraduate students of all departments.
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
This course has certain overlaps with the course “Introduction to Mathematical Finance I” offered by the Mathematics department which aims to introduce different concepts of mathematical finance/ financial engineering with a focus on underlying mathematics.
However, this new proposed course of HSS department looks forward to cover Financial Assets and Valuation, Risk Management, Macro Economics, and Investment Rationale. Only the first two topics are the possible areas of overlap with the Maths course, for which it would be more about a broad outlook and practical aspects from industry.
xii Justification/ Need for introducing the course
The course is targeted at undergraduate students to gain specific interest in finance. The course is designed with the following specific objectives and learning outcomes:
a. To build the understanding of fundamental concepts of
finance, financial markets instruments and market
participants
b. To link theories of valuation to practical aspects of investing
and risk management
At the end of the course, students should be able to familiarise
with structure of financial markets and securities traded therein
and appreciate how global economy impact markets and
investment behaviour.
This is to be seen as preliminary course for introduction to finance, with detailed technical understanding requiring specific courses in later semesters.
Name of Academic Unit: HSS
Level: Ph.D./B.Tech.
Programme: Ph.D./B.Tech. (may be admitted with some CPI criterion)
i Title of the course HS 405 Macroeconomics
ii Credit Structure (L-T-P- C)
(3-0-0-6)
iii Type of Course Elective course
iv Semester in which normally to be offered
Spring
v Whether Full or Half Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
HS201 (for B.Tech. students)
vii Course Content* 1. Introduction: The major macroeconomic issues-Economic Growth,
Inflation, Unemployment, Inequalities in Distribution of Income and
Wealth, Financial Stability, Sustainable Balance of payments.
2. National Income (NI): Concepts, Definitions and Identities, Approaches
to measurement of NI, Limitations and Omissions in Measurement of
NI
3. Major Schools of thought in Macroeconomics:
3.1. Classical and Neoclassical Schools of Thought: Theories of
output, employment, prices and interest rate, Quantity theory of
money, Cash Transactions and Cash Balance versions, Classical
dichotomy.
3.2. Keynes and Keynesians-Aggregate Demand, Aggregate Supply,
Consumption (Savings) Function and Investment Multiplier,
Output Determination, Role of Government-Monetary and Fiscal
Policies in Growth Promotion, Demand for Money: Active and
Idle cash balances, Liquidity Preference and Liquidity Trap,
Phillips Curve, Inflation-Unemployment trade-off, IS-LM Model
and Policy Effectiveness
3.3. Monetarism: Restatement of Quantity Theory of Money, Stability
of Demand Function for Money, Expectations Augmented Phillips
Curve, Adaptive Expectations, Short-run vs Long-run Phillips
Curve
3.4. New Classicists: Rational Expectations, Lucas Critique and Policy
Ineffectiveness, Rules vs Discretion, Monetary Policy Rules:
Friedman, Taylor and McCallum Rules
3.5. New Keynesians: Sticky Wages and Prices and Coordination
Failures, Asymmetric Information and Moral Hazard, Adverse
Selection
3.6. New Consensus Macroeconomics.
4. Inflation: Measurement, Causes, Consequences and Remedies
5. Fiscal Policy: Growth and Equity, concepts of deficits, internal and
external debt, debt vs money financing, sustainability of debt.
6. Opening Up the Economy: Balance of payments, Exchange rates-
nominal and real, bilateral and effective, exchange rate systems, fixed vs flexible exchange rates
Vii i Texts/References 1. Dilip M. Nachane, 2019, Critique of the New Consensus
Macroeconomics and Implications for India, Springer Nature
Switzerland AG
2. Macroeconomics by G. Mankiw, Worth Publishers, 7th edition
(2009).
3. Macroeconomics by R. Dornbusch, S. Fisher & R. Startz, McGraw-
Hill education, 11th edition (2017).
4. Errol D'Souza, Macroeconomics, 2/e, Pearson Education,
2012.
5. Macroeconomics Theories and Practices by R. T. Froyen, Pearson
Education India, 10th edition (2013).
ix Name(s) of Instructor(s) ***
Gopal Sharan Parashari
x Name(s) of other Departments/ Academic Units to whom the course is relevant
NA
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
NA
xii Justification/ Need for introducing the course
This course provides essential concepts of Macroeconomics for PhD students. It may also be offered to senior B.Tech. students with good CPI and may help them understand different Macroeconomic concepts.
Name of Academic Unit: Humanities and Social Sciences
Level: Undergraduate
Programme: B.Tech.
i Title of the course HS 307 Introduction to Linguistics
ii Credit Structure (L-T-P- C) (3-0-0-6)
iii Type of Course Elective Course
iv Semester in which normally to be offered
Spring
v Whether Full or Half Semester Course
Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
It is a first level course and no prerequisite needed
vii Course Content Introduction to Linguistics course has been designed to provide an overview of the nature of language, linguistic knowledge and the scientific study of human language. It will introduce students to the basic concepts in Linguistics and will provide a reasonable taste of the core subfields of Linguistics. Under this course, the following topics will be covered.
1. Introduction: What is language? Introducing the study of
language. Design features of language.
2. Phonetics: The sounds of human languages, articulatory and
acoustic properties, classification and description of speech
sounds, measuring acoustic properties of speech sounds,
using the Praat software.
3. Phonology: Organization of speech sounds, phoneme
inventories, phonological processes, using features to
build larger phonological units of syllables and words,
acoustic analysis of syllable or phrase level features.
4. Morphology: The internal structure of words, morphological
processes, word formation rules, using morphological
knowledge in text processing.
5. Syntax: Grammaticality, syntactic properties, sentence
structures, variation and universals of syntactic
structures, syntax enhanced machine translation.
6. Semantics: Components of linguistic meaning, lexical and compositional semantics.
viii Texts/References 1. Dawson, Hope, and Michael Phelan. Language files: Materials
for an Introduction to Language and Linguistics. The Ohio State
University Press. 2016.
2. Fromkin, Victoria, Robert Rodman, and Nina Hyams. An Introduction to Language. Walsworth, Cengage Learning, 2011.
3. Ladefoged, Peter, and Keith Johnson. A course in phonetics. Cengage learning, 2014.
4. Ladefoged, Peter, and Sandra Ferrari Disner. Vowels and consonants. John Wiley & Sons, 2012.
5. Katamba, Francis and John Stonham. Morphology. 2nd edn. London: Palgrave Macmillian. 2006.
6. Schmitt, Norbert, ed. An introduction to applied linguistics.
Routledge, 2013. 7. Jurafsky, Dan. Speech & language processing. Pearson Education India, 2000.
ix Name(s) of Instructor(s) Leena Dihingia, Dept of Linguistics, University of Delhi S R M Prasanna, Dept of EE, IITDh (co-instructor)
x Name(s) of other Departments/ Academic Units to whom the course is relevant
It is going to be a first level HSS elective taken by any department student
xi Is/Are there any course(s) in the same/ other academic unit(s) which is/ are equivalent to this course? If so, please give details.
No
xii Justification/ Need for introducing the course
Linguistics, which is concerned with the nature of language and communication, is a growing field and its importance as a discipline has been increasingly felt on other areas, with foci ranging from formal linguistic theory to several applications oriented to understanding the role of language in society, pedagogy, human development, psychological functioning as well as computer science, and artificial intelligence. An introductory course in Linguistics will provide students with a reasonable understanding of the major subfields and also equip them with some tools, techniques, and skills for linguistic analysis. This course will help students to not only understand the complex organization and systematic nature of language but also explore its several applications and acquaint them with the basic concepts necessary to pursue linguistic studies further, if they wish.
Name of Academic Unit: HSS
Level: UG
Programme: B.Tech/M.S./M. Tech/Ph.D
i Title of the Course HS 403 Happiness and Well-Being
ii Credit Structure L T P C
2 1 0 6
iii Type of Course Elective
iv Semester in which normally to be offered
Autumn/Spring
v Whether Full or Half Semester Course
Full
vi Prerequisite(s), if any (For the students) – specify course number(s)
None
vii Course Content In this course, we will explore the concept and different definitions of happiness and well-being, and the connection between happiness, positive attitude, relationships and the purpose and meaning of life. Techniques to achieve happiness in life will be studied. The course will be primarily participatory in nature with class discussions, presentations and journal assignments. The course material will be taken from a variety of sources. The causes that disturb the harmony in life will be analysed and practices to address these satisfactorily will be investigated. The methods of yoga, pranayama different meditation paths and healing techniques will be evaluated so that each student can adopt a suitable combination to suit her needs. Assignments will be aimed at a better understanding of oneself and the society and the environment that we live in. Learning Objectives. After studying this course, the students will be able to: ● Identify key psychological, social, cultural and biological factors in
happiness and well being
● Understand the relationship between happiness, human
connections, and qualities such as compassion, altruism, and
gratitude
● Describe the principles behind the specific activities that
boost happiness
● Apply lessons from positive & social psychology to their personal
and professional lives, enhancing their self-understanding
● Practice research-tested techniques for enhancing happiness
● Analyse human nature in terms of the three gunas and
the panchakosha model of beings.
● Adopt methods of yoga and meditation for self-improvement
and social well-being
Course Contents Happiness and wellbeing: definitions and measurement. The Hedonic tradition. Role of social connections in fostering happiness. Kindness and compassion, altruism and happiness, Success, money and happiness. Cooperation, reconciliation and happiness. Mindfulness, attention and focus. Mental habits of happiness: self-compassion, flow, and optimism. The Pursuit of Happiness: Does Being Good or Bad Produce More Happiness? Understanding the Causes of “Suffering.” Cultivating Right” Attention and “Right” Desire. Meaningful Relationships. The strong links between gratitude and happiness. Curiosity, Play, and Creativity. The art of letting go. Finding Your Happiness Fit and the New Frontiers. Happiness and Meaning in Life Yoga, Panchakoshas and Gunas: Guna concept: satwa, rajas and tamas and balancing the gunas. Ashtanga Yoga: Yama, Niyama, Aasana and Pranayama Pratyahar, Dharana and Dhyana. Vipassana Meditation and Reiki
Kindness and compassion, altruism and happiness, Success, money and happiness. Cooperation, reconciliation and happiness. Mindfulness, attention and focus. Mental habits of happiness: self-compassion, flow, and optimism. The Pursuit of Happiness: Does Being Good or Bad Produce More Happiness? Understanding the Causes of “Suffering.” Cultivating Right” Attention and “Right” Desire. Meaningful Relationships. The strong links between gratitude and happiness. Curiosity, Play, and Creativity. The art of letting go. Finding Your Happiness Fit and the New Frontiers. Happiness and Meaning in Life Yoga, Panchakoshas and Gunas: Guna concept: satwa, rajas and tamas and balancing the gunas. Ashtanga Yoga: Yama, Niyama, Aasana and Pranayama Pratyahar, Dharana and Dhyana. Vipassana Meditation and Reiki
Mathematics Department
Name of Academic Unit: Mathematics
Level: UG/PG
Programme: UG/PG
i Title of the course MA 501 Measure Theory
ii Credit Structure (L-T-P-C) 3-1-0-8 (8 credit full semester course )
iii Type of Course PhD course work
iv Semester in which normally to be offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students) –
specify course number(s)
Real analysis
vii Course Content Construction of Lebesgue measure on Real line,
Introduction to abstract measure theory, Measurable functions,
Caratheodory's Extension Theorem, MCT, Fatou's Lemma,
DCT, Product space, Product measure, Fubini's Theorem,
Definition of signed measures, Positive and negative sets.
Hahn-Jordan Decomposition. Absolute continuity of two σ-
finite measures. Radon-Nikodyme Theorem and Lebesgue
Decomposition.
viii Texts/References H. L. Royden; Real analysis. Third edition. Macmillan
Publishing Company, New York, 1988.
W. Rudin; Real and complex analysis. Third edition. McGraw-
Hill Book Co., New York, 1987.
S. Athreya and V.S. sunder; Measure & probability. CRC
Press, Boca Raton, FL, 2018.
K.R. Parthasarathy; Introduction to probability and measure,
Hindustan Book Agency, 2005.
Name(s) of Instructor(s) Dhriti Ranjan Dolai
x Name(s) of other Departments/ Academic Units
to whom the course is relevant
Physics
xi Is/Are there any course(s) in the same/ other
academic unit(s) which is/ are equivalent to this
course? If so, please give details.
No
xii Justification/ Need for introducing the course This course will be beneficial for PhD students who wants to
work in the area of analysis (like functional analysis, Harmonic
analysis, PDE).
Name of Academic Unit: Mathematics
Level: UG/PG
Programme: UG/PG
i Title of the course MA 503 Homological Algebra
ii Credit Structure (L-T-P-C) (3-1-0-4)
iii Type of Course N/A
iv Semester in which normally to be
offered
v Whether Full or Half Semester Course Half Semester
vi Pre-requisite(s), if any (For the students)
– specify course number(s)
Basics of Group Theory, Ring Theory and Module
Theory, Linear Algebra
vii Course Content Categories and functors: definitions and examples.
Functors and natural transformations, equivalence of
categories,. Products and coproducts, the hom
functor, representable functors, universals and
adjoints. Direct and inverse limits. Free objects.
Homological algebra: Additive and abelian
categories, Complexes and homology, long exact
sequences, homotopy, resolutions, derived functors,
Ext, Tor, cohomology of groups, extensions of groups.
viii Texts/References 1. M. Artin, Algebra, 2nd Edition, Prentice Hall of
India, 1994. 2. N. Jacobson, Basic Algebra, Vol. 1, 2nd Edition,
Hindustan Publishing Corporation, 1985. 3. N. Jacobson, Basic Algebra, Vol. 2, 2nd Edition,
Hindustan Publishing Corporation, 1989. 4. S. Lang, Algebra, 3rd Edition, Addison Wesley,
1993. 5. O. Zariski and P. Samuel, Commutative Algebra,
Vol.1, Corrected reprinting of the 1958 edition,
Springer-Verlag, New York, 1975. 6. O. Zariski and P. Samuel, Commutative Algebra,
Vol.1, Reprint of the 1960 edition, Springer-Verlag,
1975. ix Name(s) of Instructor(s) Shreedevi Masuti
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
1) Computer Science and Engineering
2) Electrical Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
xii Justification/ Need for introducing the
course
This is a foundational course for any student pursuing
doctoral studies in pure Mathematics. The course
includes the topics which are useful for research in
Geometry, Topology, Number Theory, Algebra and
Combinatorics.
Name of Academic Unit: Mathematics Level: UG Programme: B.Tech.
i Title of the course MA 403 Introduction to Number theory
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course UG Elective
iv Semester in which normally to be
offered
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the students) – specify course number(s)
None
vii Course Content Primes and Factorization; Fundamental theorem
of Arithmetic; Congruences, Euclidean
Algorithm, Chinese Reminder theorem;
Algebraic and transcendental numbers;
algebraic integers, Euler’s phi-function;
primitive elements; Wilson's theorem;
Introduction to public-key encryption systems;
Mobius inversion formula; quadratic law of
reciprocity;
Viii Texts/References 1. I. N. Niven, H. S. Zuckermann,and H. L. Montgomery, An introduction to theory
of numbers, Sixth edition (Student edition), US,
Wiley, 2018.
2.T. M. Apostol, Introduction to Analytic
number theory, Springer international student
edition, Narosa publishing house, New Delhi,
2013. 3.H. Davenport, The Higher Arithmetic,
ix Name(s) of Instructor(s) N. S. N. Sastry
x Name(s) of other Departments/ Academic
Units to whom the course is relevant
xi Is/Are there any course(s) in the same/ other
academic unit(s) which is/ are equivalent to
this course? If so, please give details.
No
xii Justification/ Need for introducing the
course
This is an introductory course on number theory,
which will allow undergraduate students to learn
certain aspects of Number Theory. The
prerequisites are kept to minimum.
Name of Academic Unit: Mathematics
Level: B. Tech. / MS(R) / PhD
Programme: B.Tech. / MS(R) / PhD
i Title of the
course MA 401 Numerical Linear Algebra
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course UG Elective
iv Semester in which normally to be
offered
v Whether Full or Half Semester Course Full Semester
vi Pre-requisite(s), if any (For the Calculus, Linear Algebra
students) – specify course number(s)
vii Course Content Vector and Matrix Norms, Gram Schmidt
Orthogonalization, Singular Value Decomposition, QR
factorization, Householder Triangularization
Floating point number system, Condition
number
and Stability, Stability of Back substitution,
Gauss
Elimination and Householder methods
Numerical techniques for finding eigenvalues,
Rayleigh Quotient, QR methods, Divide and
Conquer strategies
Krylov subspace techniques, GMRES and
Conjugate
Gradient
viii
Texts/Reference
s 1.Lloyd N. Trefethen and David Bau, Numerical
Linear Algebra, SIAM, US, 1997
2.Gene Golub and Charles Van Loan, Matrix
Computations, 4th
Edition, John Hopkins
University
Press, US, 2013
3. Iterative Methods for Sparse Linear Systems,
Yousef
Saad, 2nd
Edition, SIAM, US, 2003
ix
Name(s) of
Instructor(s) Amlan K. Barua
x Name(s) of
othe
r Departments/
Academic Units to whom the course is relevant
xi
Is/Are there any course(s) in the same/
other
academi
c unit(s) which
is/ are equivalent
to
this course? If so,
please
give details.
xii
Justification/ Need for introducing the
course This course will enable a student to gain advanced
knowledge on the numerical perspectives of linear
algebra. The potential applications can be in
large
scale computations in engineering
Physics Department Name of Academic Unit : Physics
Level : B.Tech
Programme : B.Tech.
i Title of the course PH 402 Astrophysics for Engineers
ii Credit Structure (L-T-P-C) (3-0-0-6)
iii Type of Course Elective
iv Semester in which normally to be offered Autumn
v Whether Full or Half Semester Course Full
vi Pre-requisite(s), if any (For the
students) – specify course number(s)
Nil
vii Course Content 1. a. An inventory of the Universe, b. Celestial sphere, Coordinates
c. Units, sizes, masses and distance scale
2. Electromagnetic spectrum
a. Radio, Microwave, Infrared, Optical, X-ray and
Gamma Ray
b. Telescopes and Detectors
3. Stars A. General
a. Sun, Planets, (Earth)
b. Mass, Radius, Luminosity, Temperature,
Chemistry, Age and Types of stars
c. Hertzsprung-Russell Diagram
d. Birth and Evolution of stars
c. Limits on Mass - Quantum mechanism at large
scale: Brown Dwarf
B: Structure of a star:
a. Virial Theorem (qualitative)
b. Nuclear Energy, Pressure, Interaction with
radiation.
c. Basic Equations of Stellar Structure d. Thermal Equilibrium, Radiation and Convection
- Schwarzchild Criterion
e. Helioseismology
4. Galactic and Extragalactic Astronomy
a. The Milky Way and Andromeda
b. Rotation Curve - Dark Matter
c. Structures within 500 mega light years
d. Clusters of Galaxies, Superclusters, Filaments
and Voids
5. Special Topics: a. White Dwarf - Quantum Mechanics and
Gravitation: Chandrasekhar limit
b. Supernova, Neutron Stars, (Pulsar astronomy),
c. Black Holes, Gravitational Wave Astronomy
d. Gamma Ray Burst
e. Quasars and Active Galactic Nuclei
6. Topics in Cosmology
a. Hubble Expansion - Cosmic Distance Scale - Age
of the Universe
b. Standard Model of Cosmology
c. Cosmic Microwave Background
d. Supernova Cosmology Project and Dark Energy
e. Gravitational Lens
7. Major Astronomical facilities where India is
involved:
GMRT, SKA, Thirty Metre Telescope, LIGO,
ASTROSAT
8. Open questions in Astrophysics and Cosmology
viii Texts/References 1. The New Cosmos (A. Unsold, B. Baschek)
2. An Introduction to Modern Astrophysics (B.W.
Carroll, D.A. Ostlie)
3. Elements of Cosmology (J.V. Narlikar)
ix Name(s) of Instructor(s) DN
x Name(s) of other Departments/
Academic Units to whom the course is
relevant
All
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please
give details.
Nil
xii Justification/ Need for introducing the
course
Astrophysics and Cosmology have a few fundamental
unsolved problems. This course is an attempt to
convey to the students that there are upcoming
powerful astronomical facilities capable of solving
some of them. But both at hardware and software
level, it is Technology that drives what observations
are feasible. India is one of the main contributors for
development of some of the technologies.
Name of Academic Unit: Physics
Level: BTech
Programme: BTech
i Title of the course PH 303 Thin-Film Science and Technology
ii Credit Structure (L-T-P-C) 2-1-0-3
iii Type of Course Elective
iv Semester in which normally to be offered Autumn semester
v Whether full or half semester course Half semester course
vi Pre-requisite(s), if any (for the students) –
specify course number(s)
NA
vii Course content Basic definitions, importance of thin-film;
Thin-film deposition methods: physical vapor
deposition, chemical vapor deposition, atomic
layer deposition, solution processed deposition,
Epitaxy;
Theory of nucleation & growth in thin films,
defects, diffusion, methods of control and
measurement of film thickness;
Structural, optical, electrical and mechanical
characterization of thin-films;
Applications of thin films, examples of thin-film
and devices: optical mirrors, transistors, solar
cells, LEDs, displays, touchscreens, etc.
viii Texts/References 1. M Ogring, “The Material Science of Thin
Films,” 2nd edition, Academic Press, 2001.
2. A Goswami, “Thin Film Fundamentals,”
New Age International, 1996.
3. A Wagendristel, Y Wang, “An Introduction
to Physics and Technology of Thin Films”,
World Scientific, 1994.
ix Name (s) of the instructor (s) Dr. Dhriti Sundar Ghosh
x Name (s) of other departments / Academic
Units to whom the course is relevant
Electrical Engineering, Mechanical Engineering
and Computer Science and Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please give
details.
NA
xii Justification/ Need for introducing the
course Thin-film technology shares the knowledge from
multi-disciplines (e.g., materials science,
chemistry, solid-state physics, and mechanics).
This course is designed for those students who
are interested in thin-film fundamentals and
processing for various industrial applications.
Name of Academic Unit: Physics
Level: BTech
Programme: BTech
i Title of the course PH 301 Physics of Photovoltaics
ii Credit Structure (L-T-P-C) 2-1-0-3
iii Type of Course Elective
iv Semester in which normally to be offered Autumn semester
v Whether full or half semester course Half semester course
vi Pre-requisite(s), if any (for the students) –
specify course number(s)
NA
vii Course content Basic principles of Photovoltaics- photons in,
electrons out, Importance in the present world
scenario;
Fundamentals of photoelectric conversion:
charge excitation, recombination, separation,
conduction, and collection;
Design of photovoltaic cells, electrical
characterization parameters, material aspects;
Solar cell technologies, emerging concepts, latest
breakthroughs.
viii Texts/References 1. Jenny Nelson, “Physics of Solar Cells,” 2nd
edition, Imperial College Press, 2003.
2. P. Wurfel, “Physics of Solar Cells: From
Principles to New Concepts,” 2nd edition,
Wiley-VCH, 2009.
3. L A Kosyachenko, “Solar Cells- New
Approaches and Reviews”, Intech Open,
2015.
ix Name (s) of the instructor (s) Dr. Dhriti Sundar Ghosh
x Name (s) of other departments / Academic
Units to whom the course is relevant
Electrical Engineering, Mechanical Engineering
and Computer Science and Engineering
xi Is/Are there any course(s) in the same/
other academic unit(s) which is/ are
equivalent to this course? If so, please give
details.
NA
xii Justification/ Need for introducing the
course
Solar and Renewable energy is attracting
attention not only in the research, industry and
policy domain, but also in academic institutions.
One of the most important scientific and
technical challenges facing humanity in the 21st
century is energy security. There is no doubt
about the fact that for the widespread substitution
of fossil fuel and to meet future energy needs,
photovoltaic/solar cells have to play a key role in
that.
This course will cover basic understanding of the
solar cells, types, fabrication, characterization,
etc., from the physics point of view and enable a
student to have great basis in the field of
photovoltaics.