CHRIST (Deemed to University), BangaloreDEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERINGSchool of Engineering and Technology 

Syllabus for

3 Semester  2022  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
CY321  CYBER SECURITY  Skill Enhancement Courses  2  0  0 
EC333P  ELECTRONIC DEVICES AND CIRCUITS  Core Courses  5  4  100 
ECHO341CSP  INTRODUCTION TO CRYPTOLOGY  Minors and Honours  4  4  50 
ELC331  MATHEMATICS FOR INTELLIGENT SYSTEMS  Core Courses  3  3  100 
ELC332P  DATA STRUCTURES AND ALGORITHMS  Core Courses  5  4  100 
ELC334  DIGITAL ELECTRONICS  Core Courses  5  4  100 
ELC335  PROGRAMMING LANGUAGE PARADIGM  Core Courses  3  3  100 
HS325  PROFESSIONAL ETHICS  Core Courses  2  2  50 
4 Semester  2022  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
BS451  ENGINEERING BIOLOGY LABORATORY  Core Courses  2  2  50 
EC434  COMPUTER ORGANIZATION AND PROCESSORS  Core Courses  3  3  100 
EC435  COMPUTER NETWORKS  Core Courses  3  3  100 
ECHO441CS  INTRODUCTION TO BLOCKCHAIN  Minors and Honours  12  4  100 
ELC431P  OBJECT ORIENTED PROGRAMMING  Core Courses  5  4  100 
ELC432  ARTIFICIAL INTELLIGENCE  Core Courses  3  3  100 
ELC433  SIGNALS AND SYSTEMS  Core Courses  3  3  100 
EVS421  ENVIRONMENTAL SCIENCE  Skill Enhancement Courses  2  0  0 
5 Semester  2021  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
CSOE561E04  PYTHON FOR ENGINEERS  Interdisciplinary Elective Courses  3  3  100 
CSOE561E05  BASICS OF MACHINE LEARNING  Interdisciplinary Elective Courses  3  3  100 
EC532P  DIGITAL SIGNAL PROCESSING  Core Courses  5  4  100 
EC533P  MICROCONTROLLER BASED SYSTEM DESIGN  Core Courses  5  4  100 
ECHO541CSP  INTRODUCTION TO CRYPTOLOGY  Minors and Honours  4  4  50 
ECHO542CS  INTRODUCTION TO BLOCKCHAIN  Minors and Honours  4  4  100 
EEOE531  HYBRID ELECTRIC VEHICLES  Interdisciplinary Elective Courses  4  3  100 
EEOE532  ROBOTICS AND AUTOMATION  Interdisciplinary Elective Courses  4  3  100 
EEOE533  SMART GRIDS  Interdisciplinary Elective Courses  3  3  100 
ELC531P  DATABASE MANAGEMENT SYSTEMS  Core Courses  5  4  100 
ELC541E04  OPERATING SYSTEMS  Discipline Specific Elective Courses  3  3  50 
IC521  CONSTITUTION OF INDIA  Skill Enhancement Courses  2  0  50 
NCCOE1  NCC1  Interdisciplinary Elective Courses  3  3  100 
6 Semester  2021  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
BTGE631  CORPORATE SOCIAL RESPONSIBILITY  Generic Elective Courses  2  2  100 
BTGE632  DIGITAL MEDIA  Generic Elective Courses  2  2  100 
BTGE633  FUNCTIONAL ENGLISH  Generic Elective Courses  2  2  100 
BTGE634  GERMAN  Generic Elective Courses  2  2  100 
BTGE635  INTELLECTUAL PROPERTY RIGHTS  Generic Elective Courses  2  2  100 
BTGE636  INTRODUCTION TO AVIATION  Generic Elective Courses  2  2  100 
BTGE637  PROFESSIONAL PSYCHOLOGY  Generic Elective Courses  2  2  100 
BTGE651  DATA ANALYTICS THROUGH SPSS  Generic Elective Courses  2  2  100 
BTGE652  DIGITAL MARKETING  Generic Elective Courses  2  2  100 
BTGE653  DIGITAL WRITING  Generic Elective Courses  2  2  100 
BTGE654  PHOTOGRAPHY  Generic Elective Courses  2  2  100 
BTGE655  ACTING COURSE  Generic Elective Courses  2  2  100 
BTGE656  CREATIVITY AND INNOVATION  Generic Elective Courses  2  2  100 
BTGE657  PAINTING AND SKETCHING  Generic Elective Courses  2  2  100 
BTGE658  DESIGN THINKING  Generic Elective Courses  2  2  100 
EC631P  VLSI DESIGN  Core Courses  5  4  100 
EC635  SERVICE LEARNING  Core Courses  2  2  100 
EC637  COMPUTER NETWORKS    3  3  100 
ECHO641CSP  COMPUTING SYSTEM SECURITY  Minors and Honours  75  3  100 
ECHO642CS  CRYTOGRAPHY AND SECURITY IMPLEMENTATION  Minors and Honours  3  3  100 
ELC632P  INTRODUCTION TO MACHINE LEARNING USING PYTHON  Core Courses  5  4  100 
ELC644E07  BIG DATA ANALYTICS  Electives  3  3  100 
ELC645E02  AUTOMOTIVE ELECTRONICS  Electives  3  3  100 
ELC645E03  RTOS  Electives  3  3  100 
HS621  PROJECT MANAGEMENT AND FINANCE  Core Courses  3  3  100 
MIIMBA634  DATA ANALYSIS FOR MANAGERS  Minors and Honours  3  4  100 
7 Semester  2020  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
CEOE731  SUSTAINABLE AND GREEN TECHNOLOGY  Interdisciplinary Elective Courses  3  3  100 
CEOE732  AIR POLLUTION AND CONTROL  Interdisciplinary Elective Courses  3  03  100 
CEOE733  GIS AND REMOTE SENSING TECHNIQUES AND APPLICATIONS  Interdisciplinary Elective Courses  3  3  100 
ELC731P  INTERNET OF THINGS  Core Courses  5  4  100 
ELC732  DIGITAL IMAGE PROCESSING  Core Courses  3  3  100 
ELC733  PYTHON FOR MACHINE LEARNING  Core Courses  3  3  100 
ELC744E01  MOBILE APPLICATION DEVELOPMENT  Discipline Specific Elective Courses  3  3  100 
ELC781  INTERNSHIP  Project  2  2  50 
ELC782  PROJECT WORK PHASE I  Project  12  6  100 
ME761E03  BASIC AUTOMOBILE ENGINEERING  Interdisciplinary Elective Courses  3  3  100 
ME761E04  SMART MATRIALS AND APPLICATIONS  Interdisciplinary Elective Courses  3  3  100 
PH736OE1  NANO MATERIALS AND NANOTECHNOLOGY  Interdisciplinary Elective Courses  3  3  100 
8 Semester  2020  Batch  
Course Code 
Course 
Type 
Hours Per Week 
Credits 
Marks 
ELC841E05  HIGH SPEED NETWORKS  Electives  3  3  100 
ELC881  PROJECT WORK PHASE II  Project  12  6  100 
CY321  CYBER SECURITY (2022 Batch)  
Total Teaching Hours for Semester:30 
No of Lecture Hours/Week:2 
Max Marks:0 
Credits:0 
Course Objectives/Course Description 

This mandatory course is aimed at providing a comprehensive overview of the different facets of Cyber Security. In addition, the course will detail into specifics of Cyber Security with Cyber Laws both in Global and Indian Legal environments 

Course Outcome 

CO1: Describe the basic security fundamentals and cyber laws and legalities CO2: Describe various cyber security vulnerabilities and threats such as virus, worms, online attacks, Dos and others. CO3: Explain the regulations and acts to prevent cyberattacks such as Risk assessment and security policy management. CO4: Explain various vulnerability assessment and penetration testing tools. CO5: Explain various protection methods to safeguard from cyberattacks using technologies like cryptography and Intrusion prevention systems. 
Unit1 
Teaching Hours:6 
UNIT 1


Security Fundamentals4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security.Cyber Laws, IT Act 2000IT Act 2008Laws for CyberSecurity, Comprehensive National CyberSecurity Initiative CNCI – Legalities  
Unit2 
Teaching Hours:6 
UNIT 2


Cyber Attack and Cyber Services Computer Virus – Computer Worms – Trojan horse.Vulnerabilities  Phishing  Online Attacks – Pharming  Phoarging – Cyber Attacks  Cyber Threats  Zombie stuxnet  Denial of Service Vulnerabilities  Server HardeningTCP/IP attackSYN Flood  
Unit3 
Teaching Hours:6 
UNIT 3


Cyber Security Management Risk Management and Assessment  Risk Management Process  Threat Determination Process Risk Assessment  Risk Management Lifecycle.Security Policy Management  Security Policies  Coverage Matrix Business Continuity Planning  DisasterTypes  Disaster Recovery Plan  Business Continuity Planning Process  
Unit4 
Teaching Hours:6 
UNIT 4


Vulnerability  Assessment and Tools: Vulnerability Testing  Penetration Testing Black box white box.Architectural Integration: Security Zones  Devicesviz Routers, Firewalls, DMZ. Configuration Management  Certification and Accreditation for CyberSecurity.  
Unit5 
Teaching Hours:6 
UNIT 5


Authentication and Cryptography: Authentication  Cryptosystems  Certificate Services, Securing Communications: Securing Services  Transport – Wireless  Steganography and NTFS Data Streams. Intrusion Detection and Prevention Systems: Intrusion  Defense in Depth  IDS/IPS IDS/IPS Weakness and Forensic AnalysisCyber Evolution: Cyber Organization – Cyber Future  
Text Books And Reference Books: R1. Matt Bishop, “Introduction to Computer Security”, Pearson, 6^{th} impression, ISBN: 9788177584257. R2. Thomas R, Justin Peltier, John, “Information Security Fundamentals”, Auerbach Publications. R3. AtulKahate, “Cryptography and Network Security”, 2^{nd} Edition, Tata McGrawHill.2003 R4. Nina Godbole, SunitBelapure, “Cyber Security”, Wiley India 1^{st} Edition 2011 R5. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, “Cyber Security Policy Guidebook”, Wiley; 1 edition , 2012 R6. Dan Shoemaker and Wm. Arthur Conklin, “Cyber security: The Essential Body Of Knowledge”, Delmar Cengage Learning; 1 edition, 2011 R7. Stallings, “Cryptography & Network Security  Principles & Practice”, Prentice Hall, 6th Edition 2014  
Essential Reading / Recommended Reading NIL  
Evaluation Pattern Only CIA will be conducted as per the University norms. No ESE Maximum Marks : 50  
EC333P  ELECTRONIC DEVICES AND CIRCUITS (2022 Batch)  
Total Teaching Hours for Semester:75 
No of Lecture Hours/Week:5 
Max Marks:100 
Credits:4 
Course Objectives/Course Description 

The aim of this course is to familiarize the student with the principle of operation, capabilities and limitation of various electron devices so that he or she will be able to use these devices effectively. 

Course Outcome 

CO1: Understand the biasing and small signal analysis of BJT. [L2] CO2: Understand the biasing and small signal analysis of FET. [L2] CO3: Construct the low frequency and high frequency BJT amplifiers. [L3] CO4: Examine the feedback amplifiers for different applications [L4] CO5: Perform analysis of the cascading stages of amplifiers and working principle of power devices. [L4] 
Unit1 
Teaching Hours:9 
BJT ? BIASING AND SMALL SIGNAL ANALYSIS


1. DC Biasing  BJTs : Operating Point, Transistor Biasing circuits (Fixed Bias, Emitter Bias, Voltage Divider Bias, DC Bias with voltage feedback. Transistor as a switch. 2. BJT AC Analysis: BJT as amplifier. Small signal equivalent circuits (Low frequency re and h models only). Small signal analysis of CE, CB, CC (Voltage Divider Bias) configurations using re and hybrid model – with and without bypass capacitor.  
Unit2 
Teaching Hours:9 
FET ? BIASING AND AMPLIFIERS


1. JFET: Construction, Operation, Characteristic, Shockley's Equation, Transfer Characteristics and Applications, MOSFET :Enhancement type MOSFET and Depletion MOSFET – Construction, Operation and Characteristics, Handling precautions for MOSFET 2. FET Biasing: Fixed Bias Configuration, Self – Bias Configuration, Voltage Divider Biasing. Depletion Type MOSFETs, Enhancement Type MOSFETs, FET Amplifiers: FET Small Signal Model  
Unit3 
Teaching Hours:9 
FREQUENCY RESPONSE AND HIGH FREQUENCY ANALYSIS


1. General shape of frequency response of amplifiers. Definition of bel, decibel, cut off frequencies and bandwidth. Low frequency analysis of amplifiers to obtain lower cut off frequency. 2. Hybrid – pi equivalent circuit of BJTs. High frequency analysis of BJT amplifiers to obtain upper cut off frequency  
Unit4 
Teaching Hours:9 
FEEDBACK AMPLIFIERS


Feedback Amplifiers: Negative and positive feedback. Properties of negative and positive feedback, negative feedback configurations, analysis of negative feedback amplifiers for gain, frequency response, input impedance, and output impedance of different configurations (voltage series, current series, voltage shunt, and current shunt)  
Unit5 
Teaching Hours:9 
CASCADE SYSTEMS AND POWER CONTROL DEVICES


CASCADE SYSTEMS: Analysis of frequency response and gain for BJT and FET amplifiers POWER CONTROL DEVICES: Power control devices: PNPN diode (Shockley diode) SCR characteristics – LASCR (Light Activated SCR) – TRIAC – DIAC – Structure & Characteristics. Characteristics and equivalent circuit of UJT  intrinsic standoff ratio  
Text Books And Reference Books: T1. Robert L. Boylestead & Louis Nashelsky, “Electronic Devices and Circuit Theory”, 10^{th} ed., Pearson Education, 2009. T2. Jacob Millman & Christos C. Halkias, “Electronic Devices and Circuits”, Tata McGrawHill Education Pvt. Ltd., 2010.  
Essential Reading / Recommended Reading R1. Millman J. and Halkias C. " Integrated Electronics ", Tata McGrawHill Publishing, 2000 R2. Donald A Neamen, “Electronic Circuit Analysis and Design”, 3/e, TMH. R3. Albert Paul Malvino, Electronic Principles, 8th Ed, McGrawHill Education, 2016. R4. Sedra and Smith.” Microelectronic Circuits”, 6/e, Oxford University Press, 2010. R5. David A. Bell, “Electronic Devices and Circuits”, 4th Edition, Prentice Hall of India, 2007.  
Evaluation Pattern Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII:Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.  
ECHO341CSP  INTRODUCTION TO CRYPTOLOGY (2022 Batch)  
Total Teaching Hours for Semester:60 
No of Lecture Hours/Week:4 
Max Marks:50 
Credits:4 
Course Objectives/Course Description 

Identify, formulate, research literature, and analyse complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. 

Course Outcome 

CO1: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialisation for the solution of complex engineering problems. 
Unit1 
Teaching Hours:9 

Basic Concepts of Number Theory and Finite Fields:


Divisibility and the divisibility algorithm, Euclidean algorithm, Modular arithmetic, Groups, Rings and Fields, Finite fields of the form GF(p), Polynomial arithmetic, Finite fields of the form GF(2n), Galois group of a field extensions, Fixed field and Galois extensions, Fundamental theorem of Galois Theory  
Unit2 
Teaching Hours:9 

Classical Encryption Techniques


Symmetric cipher model, Substitution techniques, Transposition techniques, Steganography, Traditional Block Cipher structure, Data Encryption Standard (DES)  
Unit3 
Teaching Hours:9 

PseudoRandomSequence Generators


The AES Cipher, Linear Congruential Generators, Linear Feedback Shift Registers, Design and analysis of stream ciphers, Stream ciphers using LFSRs  
Unit4 
Teaching Hours:9 

Principles of PublicKey Cryptosystems


 
Unit5 
Teaching Hours:9 

OneWay Hash Functions


 
Text Books And Reference Books:
 
Essential Reading / Recommended Reading Cryptography and Network Security, Atul Kahate, TMH, 2003.  
Evaluation Pattern CIA 50 ESE50  
ELC331  MATHEMATICS FOR INTELLIGENT SYSTEMS (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 

Max Marks:100 
Credits:3 

Course Objectives/Course Description 

The course will lay down the basic concepts and techniques of linear algebra, differential equation, Analytical optimization and graph theory as applied to intelligent system design. 

Course Outcome 

CO1: Apply the understanding of working with data in matrix form for solving systems of linear algebraic equations, for finding the basic matrix decompositions with the general understanding of their applicability in intelligent systems. CO2: Understand the notion of an abstract vector space and how coordinates, and matrices of linear transformations, arise from the underlying linearity structures imposed on the system CO3: Apply multivariable and vectorvalued functions and their derivatives, using gradient algorithms to determine local/global maxima and minima, saddle points. CO4: Analyze the type of optimization problem and apply suitable algorithm to find the optimum value of the objective function CO5: Understand the fundamental concepts in graph theory and Apply algorithms and theorems from graph theory on solving problems 
Unit1 
Teaching Hours:9 
Linear Algebra


Introduction, Gaussian Elimination ( for solutions and Inverse, Nonsingular versus Singular) ,Determinants and Properties of the Determinant. Vector Spaces (column, Row Null and left nullspace), Linear Independence, Basis and Dimension, Linear Transformations, Eigenvalues and Eigenvectors, Diagonalization of a Matrix, Positive Semi definite and Positive Definite.  
Unit2 
Teaching Hours:9 
Multivariant Calculus


Partial derivatives,Taylors Series and Linearization, Gradient, directional derivative. Vector and matrix calculus, Calculus: Convexity and concavity of functions of one and two variables, local/global maxima and minima, saddle point  
Unit3 
Teaching Hours:9 
Statistics and Probability


Principles of Probablity Theory( Expectation, Variance, density , Bayes theorem, Central limit Theory), Standard Distributions (Binomial, Poisson, Normal, Chisquared,tdistribution) , Maximum Likelyhood Theory, Statistical Tests(type I, Type II error, Ttest, Chisquared Test), Confidence Intervals  
Unit4 
Teaching Hours:9 
Optimization


 
Unit5 
Teaching Hours:9 
Graph Theory


Graph Theory: Graph Terminology and Special Types of Graphs, Planar Graphs, Graph Coloring, Trees, Graph Minor. Vertex cover, matching, path cover, connectivity, edge coloring, vertex coloring, list coloring; Planarity, Perfect graphs; other special classes of Graphs Connectivity, Hamilton PathsTravelling salesman problem . Shortest path algorithmDijkstra’s algorithm  
Text Books And Reference Books: T1. Gilbert Strang, Linear Algebra and its applications, 4th Ed, Cengage Learning, 2006 T2. MP Deisenroth, A A Faisal, C S Ong, Mathematics for Machine learning, Cambridge University, 2020 T3. Phil Dyke, Advanced Calculus, Macmillan International Higher Education, 1998 T4. Fletcher R., Practical Methods of Optimization, John Wiley, 2000 T5. Reinhard Diestel, "Graph Theory", Springer (2010)  
Essential Reading / Recommended Reading R1. Singiresu S Rao, Engineering Optimization, 4th ed, Wiley, 2009 R2. Jorge Nocedal and Stephen J. Wright: "Numerical Optimization", second ed,1999  
Evaluation Pattern · Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII:Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution.  
ELC332P  DATA STRUCTURES AND ALGORITHMS (2022 Batch)  
Total Teaching Hours for Semester:75 
No of Lecture Hours/Week:5 
Max Marks:100 
Credits:4 
Course Objectives/Course Description 

This course is designed to make the students familiar with basic techniques of algorithm analysis, to understand concepts of searching and sorting techniques and to assess how the choice of data structures impacts the performance of a program. 

Course Outcome 

CO1: Explain linear and nonlinear data structures like stack, queue, linked list, tree and graph CO2: Explain data structures operations including insertion, deletion, traversal, searching, and sorting CO3: Understand the concept and operations of singly linked list, circular linked list and double linked list CO4: Understand the functions of data warehousing including the components, architecture mapping, data extraction and data cleanup CO5: Demonstrate online analytical processing (OLAP) as per the OLAP guidelines using OLAP tools CO6: Implement programs to summarize the operations of data structures 
Unit1 
Teaching Hours:9 

INTRODUCTION


Definition and basics of: Data Structure, ADT, Algorithms, Time and Space Complexity, Asymptotic Notations (O, θ, Ω), Time complexity computation of nonrecursive algorithms (like Matrix addition, Selection sort – using step count), Array – basic operations, concept of multidimensional array, Polynomial operations using Array, Sparse Matrix  
Unit2 
Teaching Hours:9 

STACK AND QUEUE


Stack ADT: basic operations, Queue ADT: basic operations, Circular Queue, Evaluation of Expressions, Another application or Mazing Problem  
Unit3 
Teaching Hours:9 

LINKED LIST


Singly Linked List: concept, representation and operations, Circular Linked List, Polynomial and Sparse Matrix operations using LL, Doubly Linked List: basic concept  
Unit4 
Teaching Hours:9 

INTRODUCTION TO ALGORITHMS


Introduction, Notion of Algorithm, Fundamentals of Algorithmic Solving, Fundamentals of the Analysis Framework, Asymptotic Notations and Basic Efficiency Classes, Mathematical Analysis of Nonrecursive Algorithm, Mathematical Analysis of Recursive Algorithm and examples, Empirical Analysis of Algorithms and Algorithm Visualization  
Unit5 
Teaching Hours:9 

ALGORITHM DESIGN TECHNIQUES


Brute Force and Exhaustive Search: Selection Sort, Bubble Sort, Sequential Search and Bruteforce string matching, Travelling Salesman Problem, Knapsack Problem, Assignment Problem, DFS and BFS. Decrease and Conquer: Insertion Sort and Topological Sorting and Binary Search, Warshall’s and Floyd’s Algorithm. Greedy Techniques: Prim’s Algorithm, Kruskal’s Algorithm, Dijkstra’s Algorithm and Huffman trees  
Text Books And Reference Books: T1. Sahni Horwitz,, Freed Anderson, Fundamentals of Data Structures in C, 2nd Edition (or latest) , University Press.\ T2. Anany Levitin, “Introduction to the Design and Analysis of Algorithm”, 3/e, Pearson Education Asia, 2008, (Reprint 2012). T3. Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser, “Data Structures and Algorithms in Java”, 6/e, Wiley, 2014.  
Essential Reading / Recommended Reading R1. TharejaReema, Data Structures Using C, 2nd Edition, Oxford University Press R2Tanenbaum, Langsam, Augenstein, Data Structures using C, Pearson R3. T. H Cormen, C E Leiserson, R L Rivest and C Stein: “Introduction to Algorithms”, 3rd Edition, The MIT Press, 2014. R4.Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, Computer Algorithms, Second Edition, Universities Press, 2007.  
Evaluation Pattern
·
Minimum marks required to pass in practical component is 40%. · Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. · A minimum of 40 % required to pass in ESE Theory component of a course. · Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. · There is no minimum pass marks for the Theory  CIA component. · Less than 40% in practical component is refereed as FAIL. · Less than 40% in Theory ESE is declared as fail in the theory component. · Students who failed in theory ESE have to attend only theory ESE to pass in the course  
ELC334  DIGITAL ELECTRONICS (2022 Batch)  
Total Teaching Hours for Semester:75 
No of Lecture Hours/Week:5 

Max Marks:100 
Credits:4 

Course Objectives/Course Description 

The aim of this course is to study the basics of digital circuits and learn methods and fundamental concepts used in the design of digital systems. 

Course Outcome 

CO1: To apply the principles of Boolean algebra and Kmap to design combinational circuits CO2: To analyze the operation of sequential circuits built with various flipflops and design of counters, registers CO3: To use state machine diagrams to design finite state machines using various types of flipflops and combinational circuits with prescribed functionality. CO4: To understand the concepts of data paths, control units, and microoperations and building blocks of digital systems CO5: To design combinational and sequential circuits using Verilog HDL modeling. 
Unit1 
Teaching Hours:9 
COMBINATIONAL CIRCUITS


Design procedure – Four variable Karnaugh Maps, AddersSubtractors – Serial adder/Subtractor  Parallel adder/ Subtractor Carry look ahead adder BCD adder, Magnitude Comparator. Multiplexer/ Demultiplexer,Encoder / decoder, parity checker, Code converters. Implementation of combinational logic using MUX, ROM, PAL and PLA  
Unit2 
Teaching Hours:9 
SEQUENTIAL CIRCUITS


Classification of sequential circuits, Moore and Mealy Design of Synchronous counters: state diagram State table –State minimization –State assignment ASMExcitation table and mapsCircuit implementation  Universal shift register – Shift counters – Ring counters  
Unit3 
Teaching Hours:9 
ASYNCHRONOUS SEQUENTIAL CIRCUITS


Design of fundamental mode and pulse mode circuits – primitive state / flow table – Minimization of primitive state table –state assignment – Excitation table – Excitation map cycles – Races, Hazards: Static –Dynamic –Essential –Hazards elimination.  
Unit4 
Teaching Hours:9 
DIGITAL INTEGRATED CIRCUITS


Introduction – Special Characteristics – Bipolar Transistor Characteristics – RTL and DTL circuits – TransistorTransistor Logic (TTL) Emitter Coupled Logic (ECL) – Metal Oxide Semiconductor (MOS) – Complementary MOS (CMOS) – CMOS Transmission Gate circuits  
Unit5 
Teaching Hours:9 
VERILOG HDL


Basic Concepts: VLSI Design flow, identifiers, gate primitives, value set, ports, gate delays, structural gate level modeling, Behavioral modeling, Data flow modeling, Design hierarchies, Structural gate level description of combinational and sequential circuits.  
Text Books And Reference Books:
T1. M. Morris Mano, Michael D. Ciletti, “Digital Design” 5^{th}Edition, Prentice Hall of India Pvt. Ltd., New Delhi, 2015/Pearson Education (Singapore) Pvt. Ltd., New Delhi, 2003.
T2. Samir Palnitkar, “Verilog HDL”, 2 edition, Pearson Education, 2003 T3. Peter.J.Ashenden, “Digital Design: An Embedded Systems Approach Using Verilog”, Elsevier 2010  
Essential Reading / Recommended Reading
R1. John .M Yarbrough,” Digital Logic Applications and Design”, Thomson Vikas Publishing house, New Delhi, 2006.
R2. S. Salivahanan and S. Arivazhagan, “Digital Circuits and Design”, 5th ed., Vikas Publishing House Pvt. Ltd, New Delhi, 2016.
R3. Charles H.Roth, ” Fundamentals of Logic Design”, Thomson Publication Company, 2012. R4. Donald P.Leach and Albert Paul Malvino, “Digital Principles and Applications”,6th Edition, Tata McGraw Hill Publishing Company Limited, New Delhi, 2012.  
Evaluation Pattern Theory CIA  30 marks CIA will be conducted for 50 marks. Later the marks will be scaled down to 30 marks. Components of the CIA: Theory ESE  30 marks End Semester Examination (ESE):
Practical  35 marks Practical assessment depends on the student's lab discipline, regular attendance, conduction of the lab, observation and record submission and final lab exam. Attendance  5 marks In total, the course is evaluated for 100 (30+30+35+5) marks.  
ELC335  PROGRAMMING LANGUAGE PARADIGM (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

This course aims to explore modern programming languages and the techniques used for programming in order to get idea on evaluation of programming languages and also helps students to analyze a given program from good programming practice perspective 

Course Outcome 

CO1: Write programs related to syntax and semantics CO2: Compare programs between C, Ada, Perl and Small Talk CO3: Write programs using scripting languages CO4: Demonstrate eventdriven and concurrent programming using prolog CO5: Apply prolog for developing distributed systems 
Unit1 
Teaching Hours:9 
INTRODUCTION


The art of Language design – Programming language spectrum  Compilation and Interpretation – Evaluation of Programming languages – Syntax and Semantics of Language Clite  Names – Types – Type Systems  Binding – Scope – Static – Dynamic – Abstract Data types  
Unit2 
Teaching Hours:9 
SEMANTICS


Expression – Assignment  Control Flow – Input/Output – Exception Handling – State Transformation – Partial Functions – Semantics with Dynamic Typing – Formal Treatment of Semantics  
Unit3 
Teaching Hours:9 
FUNCTIONS


Call and Return – Parameter Passing – Function Declaration – Semantics Of Call and Return – Formal Treatment of Types and Semantics – Memory Management – Dynamic Arrays – Garbage Collection.  
Unit4 
Teaching Hours:9 
PROGRAMMING TECHNIQUES


Imperative programming – C – ADA – Perl – Object Oriented Programming – Small TalkJava– Python – Functional Programming – Scheme – Haskell  
Unit5 
Teaching Hours:9 
MODERN PROGRAMMING TECHNIQUES


Logic Programming – Prolog – EventDriven programming – Concurrent Programming – Concepts – Synchronization Strategies – Language Level Mechanism  Interprocess COMMUNICATION – Scripting LANGUAGES  
Text Books And Reference Books: T1. Allen B. Tucker and Robert E. Noonan, ―Programming Languages – Principles and Paradigms‖, Second Edition, Tata McGraw Hill, 2009  
Essential Reading / Recommended Reading R1. Robert W. Sebesta, ―Concepts of Programming Languages‖, Sixth Edition, Addison Wesley, 2003 R2. Michael L Scott, ―Programming Language Pragmatics‖, Third Edition, Morgan Kauffman, 2009  
Evaluation Pattern As per University Norms  
HS325  PROFESSIONAL ETHICS (2022 Batch)  
Total Teaching Hours for Semester:30 
No of Lecture Hours/Week:2 
Max Marks:50 
Credits:2 
Course Objectives/Course Description 

(a) To understand the moral values that ought to guide the Engineering profession. (b) To resolve the moral issues in the profession.


Course Outcome 

CO1: Outline professional ethics and human values by realizing the holistic attributes.{L1}{PO6,PO8} CO2: Specify the Engineering Professional Ethics to identify problems related to society, safety, health & legal aspects. {L1}{PO6,PO8} CO3: Explain the importance of being ethical while using technology in the digital space. {L2}{PO8,PO12} CO4: Understand the ethical principles and behaviors laid down by IEEE. {L2}{PO6,PO8,PO9,PO12} CO5: Explain the Importance of ethical conduct to safeguard environment and its resources with respect to electronics engineering. {L1}{PO7,PO8} 
Unit1 
Teaching Hours:6 
INTRODUCTION TO ETHICS


Introduction to Profession, Engineering and Professionalism, Three types of Ethics / Morality , Positive and Negative faces of Engineering Ethics  
Unit2 
Teaching Hours:6 
RESPONSIBILITY IN ENGINEERING AND ENGINEERING ETHICS


Introduction, Engineering Standards, Blame – Responsibility and Causation, Liability, Design Standards. Senses of 'Engineering Ethics'  variety of moral issued  types of inquiry  moral dilemmas  moral autonomy  Kohlberg's theory  Gilligan's theory  consensus and controversy – Models of Professional Roles  theories about right action  Selfinterest  customs and religion  uses of ethical theories.
 
Unit3 
Teaching Hours:6 
SOCIAL AND VALUE DIMENSIONS IN TECHNOLOGY


Technology – The Promise and Perils, Computer Technology – Privacy and Social Policy, Ownership of Computer Software and public Policy, Engineering Responsibility in Democratic Deliberation on Technology Policy, The Social Embeddedness of Technology.  
Unit4 
Teaching Hours:6 
ELECTRONICS ENGINEERING ETHICS


Ethics in Electronics Engineering  IEEE Code of Ethics, Computer Ethics, Case Studies on ethical conflicts, Corporate Social Responsibility Ethics in Electronics Business – HR, Marketing, Finance and Accounting, Production and Operation, Tendering and contracts, Ethical behaviour expected out of a electronic contractor
 
Unit5 
Teaching Hours:6 
ETHICS AND ENVIRONMENT


Environment in Law and Court Decisions, Criteria for “Clean Environment”, EWaste Management, ethical responsibility towards ewaste management, radiation effects on the society, ethical behaviour of the stakeholders running the communication business  
Text Books And Reference Books: T1. Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGrawHill, New York 1996. T2. Govindarajan M, Natarajan S, Senthil Kumar V. S, “Engineering Ethics”, Prentice Hall of India, New Delhi, 2004.
 
Essential Reading / Recommended Reading R1. Charles D. Fleddermann, “Engineering Ethics”, Pearson Education / Prentice Hall, New Jersey, 2004 (Indian Reprint). R2. Charles E Harris, Michael S. Protchard and Michael J Rabins, “Engineering Ethics – Concepts and Cases”, Wadsworth Thompson Learning, United States, 2000 (Indian Reprint now available) R3. John R Boatright, “Ethics and the Conduct of Business”, Pearson Education, New Delhi, 2003 R4. Edmund G Seebauer and Robert L Barry, “Fundamentals of Ethics for Scientists and Engineers”, Oxford University Press, Oxford, 2001.
 
Evaluation Pattern Components of the CIA
 
BS451  ENGINEERING BIOLOGY LABORATORY (2022 Batch)  
Total Teaching Hours for Semester:30 
No of Lecture Hours/Week:2 
Max Marks:50 
Credits:2 
Course Objectives/Course Description 

Understanding and application of MATLAB and TINKERCAD for biological analysis which would results in better healthcare and any engineer, irrespective of the parent discipline (mechanical, electrical, civil, computer, electronics, etc.,) can use the disciplinary skills toward designing/improving biological systems. This course is designed to convey the essentials of human physiology.The course will introduce to the students the various fundamental concepts in MATLAB and TINKERCAD for numerical analysis and circuit design using arduino.


Course Outcome 

CO1: Examine the various applications of bioengineering and using common tool boxes for analysing medical information. 
Unit1 
Teaching Hours:30 

LIST OF EXPERIMENTS


 
Text Books And Reference Books: NIL
 
Essential Reading / Recommended Reading NIL
 
Evaluation Pattern As per university norms  
EC434  COMPUTER ORGANIZATION AND PROCESSORS (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 

Max Marks:100 
Credits:3 

Course Objectives/Course Description 

To discuss the basic structure of a digital computer and to study in detail the organization of the Control unit, the Arithmetic and Logical unit, Memory unit and Intel Processors. 

Course Outcome 

CO1: Summarize the architectural features of a computer CO2: Discover the basic functional units in ALU and perform various arithmetic operations of ALU CO3: Demonstrate the dataflow and program execution process in Computer CO4: Summarize various memory architectures and their data storage behaviour CO5: Interpret unique architectural features of 8086 and Pentium processors. 
Unit1 
Teaching Hours:9 
BASIC STRUCTURE OF COMPUTERS


A Brief History of computers, Von Neumann Architecture, Harvard architecture, Computer Components, Functional units  Basic operational concepts  Bus structures  Software performance – Memory locations and addressesAddition and subtraction of signed numbers – Design of fast adders – Multiplication of positive numbers  Hardware Implementation Signed operand multiplication.  
Unit2 
Teaching Hours:9 
ARITHMETIC & LOGIC UNIT


Booths Algorithm fast multiplication – Integer division & it’s Hardware Implementation – Restoring and Non Restoring algorithmsFundamental concepts – Execution of a complete instruction – Multiple bus organization – Hardwired control – Microprogrammed control  Pipelining – Basic concepts – Data hazards – operand forwardingInstruction hazards Instruction Set architecture for logical operation  
Unit3 
Teaching Hours:9 
8086 MICROPROCESSOR


Intel 8086 Microprocessor  Internal architecture – segment registers 8086 memory organization–Flag Registerlogical and physical address calculationBlock diagram of Minimum and maximum mode and its operations – Interrupt and Interrupt applicationsAssembly language programming of 8086.  
Unit4 
Teaching Hours:9 
INTERFACING WITH 8086


Memory Interfacing and I/O interfacing  Parallel communication interface – Serial communication interface – Timer –Interrupt controller – DMA controller – Programming and applications  
Unit5 
Teaching Hours:9 
PENTIUM MICROPROCESSOR


Advanced Intel Microprocessors Reduced Instruction cycle – five stage instruction pipe line – Integrated coprocessor – On board cache – Burst Bus mode. Pentium – super scalar architecture – uv pipe line – branch prediction logic – cache structure – BIST (built in selftest) – Introduction to MMX technology. Case Study  
Text Books And Reference Books: T1. Carl Hamacher, Zvonko Vranesic and Safwat Zaky, 7^{th }Edition “Computer Organization”, McGrawHill, 2011 T2. Douglous V. Hall “Microprocessor and Interfacing” 3^{rd} edition ,Tata McGraw Hill,2015. T3.James L. Antonakos , “ The Pentium Microprocessor ‘’ Pearson Education, 2007  
Essential Reading / Recommended Reading R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, 10h Edition, Pearson Education, 2015. R2. David A.Patterson and John L.Hennessy, “Computer Organization and Design: The hardware / software interface”, 3rd Edition, Morgan Kaufmann, 2008 R3. John P.Hayes, “Computer Architecture and Organization”, 4^{th} Edition, McGrawHill, 2003.  
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIA III : Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks
Mid Semester Examination (MSE) : Theory Papers: The MSE is conducted for 50 marks of 2 hours duration. Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal weightage in terms of marks distribution.  
EC435  COMPUTER NETWORKS (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

This course aims to introduce the concepts, terminologies, and technologies used in modern data communication and computer networking. It also gives an introduction to the IEEE standards used for WLAN for physical ant MAC layer. 

Course Outcome 

CO1: Explain the network models and terminologies including topologies, transmission media and line coding for a data communication system. CO2: Understand the data link layer services for error control using parity check, Hamming & cyclic codes and flow control techniques using stop & wait, stop & wait ARQ, Goback n ARQ protocols. CO3: Find the path for network layer packet delivery for a given topology using intradomain routing protocols CO4: Understand the essential principles of transport layer including reliable data transfer, congestion control and quality of service CO5: Describe the MAC layer functions including DCF,PCF access schemes of Wireless LAN from IEEE 802.11 draft standard 
Unit1 
Teaching Hours:9 
DATA COMMUNICATIONS


Components – Direction of Data flow – networks – Components and Categories – types of Connections – Topologies –Protocols and Standards – ISO / OSI model – Transmission Media – Coaxial Cable – Fiber Optics – Line Coding – Modems – RS232 Interfacing sequences. TCP/IP.  
Unit2 
Teaching Hours:9 
DATA LINK LAYER


Error – detection and correction – Parity – LRC – CRC – Hamming code – Flow Control and Error control: stop and wait – go back N ARQ – selective repeat ARQ sliding window techniques – HDLC. LAN: Ethernet IEEE 802.3, IEEE 802.4, and IEEE 802.11  
Unit3 
Teaching Hours:9 
NETWORK LAYER


Internetworks  Packet Switching and Datagram approach – IP addressing methods IP Multicasting and broadcasting– Subnetting – Routing – Distance Vector Routing – Link State Routing – Routers.  
Unit4 
Teaching Hours:9 
TRANSPORT LAYER


Duties of transport layer – Multiplexing – Demultiplexing – Sockets – User Datagram Protocol (UDP) – Transmission Control Protocol (TCP) – Congestion Control – Quality of services (QOS) – Integrated Service  
Unit5 
Teaching Hours:9 
IEEE 802.11 WIRELESS LAN ? MAC & NETWORK LAYER


IEEE 802.11–– Architecture, Types of stations, 802.11 MAC DCF, PCF, Hidden Node Problem, RTS,CTS, 802.11 Frame Format, Adhoc Routing Protocols – Proactive Routing, OLSR, Reactive Routing, AODV, Multipath Routing.  
Text Books And Reference Books: T1. Behrouz A. Foruzan, “Data communication and Networking”,5th edition , Tata McGrawHill, 2012  
Essential Reading / Recommended Reading R1. James .F. Kurouse & W. Rouse, “Computer Networking: A Topdown Approach Featuring”, 7^{th} edition,Pearson Education,2016 R2. Larry L.Peterson & Peter S. Davie, “COMPUTER NETWORKS”, Harcourt Asia Pvt. Ltd., 5^{th} Edition,2011 R3. Andrew S. Tannenbaum, “Computer Networks”, PHI, 5^{th} Edition, 2016 R4. William Stallings, “Data and Computer Communication”, 8^{th} Edition, Pearson Education, 2013 R5. Azzedine Boukerche “Algorithms and Protocols for Wireless, Mobile AdHoc Networks”, WileyIEEE Press, 2008  
Evaluation Pattern Components of the CIA  
ECHO441CS  INTRODUCTION TO BLOCKCHAIN (2022 Batch)  
Total Teaching Hours for Semester:60 
No of Lecture Hours/Week:12 
Max Marks:100 
Credits:4 
Course Objectives/Course Description 

The students should be able to understand a broad overview of the essential concepts of blockchain technology. Course Objectives:


Course Outcome 

1: Explain the concepts of Distributed systems, and the fundamentals and types of blockchain 2: Illustrate the various techniques in distributed computing in connection with the crypto primitives 3: Infer the operation of blockchain, the various architectures and structures used in it and essential components in Blockchain 1.0 4: Illustrate the various applications of blockchain technologies and components of Blockchain 2.0 5: Analyse the security issues in blockchain technology 
Unit1 
Teaching Hours:12 
Introduction


Distributed DBMS – Limitations of Distributed DBMS, Introduction to Block chain – History, Definition, Distributed Ledger, Blockchain Categories – Public, Private, Consortium, Blockchain Network and Nodes, PeertoPeer Network, Mining Mechanism, Generic elements of Blockchain, Features of Blockchain, and Types of Blockchain  
Unit2 
Teaching Hours:12 
Basic Distributed Computing & Crypto primitives


Atomic Broadcast, Consensus, Byzantine Models of Fault tolerance Hash functions, Puzzle friendly Hash, Collison resistant hash, digital signatures, public key crypto, verifiable random functions, Zeroknowledge systems.  
Unit3 
Teaching Hours:12 
Blockchain 1.0


Operation of Bitcoin Blockchain, Blockchain Architecture – Block, Hash, Distributer P2P, Structure of Blockchain Consensus mechanism: Proof of Work (PoW), Proof of Stake (PoS), Byzantine Fault Tolerance (BFT), Proof of Authority (PoA) and Proof of Elapsed Time (PoET)  
Unit4 
Teaching Hours:12 
Blockchain 2.0


Ethereum and Smart Contracts, The Turing Completeness of Smart Contract Languages and verification challenges, Using smart contracts to enforce legal contracts, comparing Bitcoin scripting vs. Ethereum Smart Contracts
 
Unit5 
Teaching Hours:12 
Privacy, Security issues in Blockchain


Pseudoanonymity vs. anonymity, Zcash and ZkSNARKS for anonymity preservation, attacks on Blockchains – such as Sybil attacks, selfish mining, 51% attacks  advent of algorand, and Sharding based consensus algorithms to prevent these
 
Text Books And Reference Books:
 
Essential Reading / Recommended Reading
 
Evaluation Pattern Evaluation Pattern:  
ELC431P  OBJECT ORIENTED PROGRAMMING (2022 Batch)  
Total Teaching Hours for Semester:75 
No of Lecture Hours/Week:5 
Max Marks:100 
Credits:4 
Course Objectives/Course Description 

This course presents the concept of object oriented programming and also introduces the concept in C++ . The students will be familiarized with concepts like data abstraction, polymorphism and inheritance. 

Course Outcome 

CO1: Write Java programs using the object oriented concepts  classes, objects, constructors, data hiding, inheritance and polymorphism [L3] CO2: Utilise datatypes, operators, control statements, built in packages & interfaces, Input/ Output Streams and Files in Java to develop programs[L3] CO3: Illustrate how robust programs can be written in Java using exception handling mechanism[L2] CO4: Write application programs in Java using multithreading and database connectivity [L3] CO5: Write Graphical User Interface based application programs by utilising event handling features and Swing in Java [L3] 
Unit1 
Teaching Hours:9 
INTRODUCTION


Approaches to Software Design  Functional Oriented Design, Object Oriented Design, Case Study of Automated Fire Alarm System. Object Modeling Using Unified Modeling Language (UML) – Basic Object Oriented concepts, UML diagrams, Use case model, Class diagram, Interaction diagram, Activity diagram, State chart diagram. Introduction to Java  Java programming Environment and Runtime Environment, Development Platforms Standard, Enterprise. Java Virtual Machine (JVM), Java compiler, Bytecode, Java applet, Java Buzzwords, Java program structure, Comments, Garbage Collection, Lexical Issues  
Unit2 
Teaching Hours:9 
CORE JAVA FUNDAMENTALS


Primitive Data types  Integers, Floating Point Types, Characters, Boolean. Literals, Type Conversion and Casting, Variables, Arrays, Strings, Vector class. Operators  Arithmetic Operators, Bitwise Operators, Relational Operators, Boolean Logical Operators, Assignment Operator, Conditional (Ternary) Operator, Operator Precedence. Control Statements  Selection Statements, Iteration Statements and Jump Statements. Object Oriented Programming in Java  Class Fundamentals, Declaring Objects, Object Reference, Introduction to Methods, Constructors, this Keyword, Method Overloading, Using Objects as Parameters, Returning Objects, Recursion, Access Control, Static Members, Final Variables, Inner Classes, Command Line Arguments, Variable Length Arguments. Inheritance  Super Class, Sub Class, The Keyword super, protected Members, Calling Order of Constructors, Method Overriding, the Object class, Abstract Classes and Methods, using final with Inheritance  
Unit3 
Teaching Hours:9 
PRIMARY FEATURES OF JAVA


Packages and Interfaces  Defining Package, CLASSPATH, Access Protection, Importing Packages, Interfaces. Exception Handling  Checked Exceptions, Unchecked Exceptions, try Block and catch Clause, Multiple catch Clauses, Nested try Statements, throw, throws and finally. Input/Output  I/O Basics, Reading Console Input, Writing Console Output, PrintWriter Class, Object Streams and Serialization, Working with Files  
Unit4 
Teaching Hours:9 
ADVANCED JAVA FEATURES


Java Library  String Handling – String Constructors, String Length, Special String Operations  Character Extraction, String Comparison, Searching Strings, Modifying Strings, using valueOf(), Comparison of StringBuffer and String. Collections framework  Collections overview, Collections Interfaces Collection Interface, List Interface. Collections Class – ArrayList class. Accessing a Collection via an Iterator. Event handling  Event Handling Mechanisms, Delegation Event Model, Event Classes, Sources of Events, Event Listener Interfaces, Using the Delegation Model. Multithreaded Programming  The Java Thread Model, The Main Thread, Creating Thread, Creating Multiple Threads, Synchronization, Suspending, Resuming and Stopping Threads  
Unit5 
Teaching Hours:9 
GRAPHICAL USER INTERFACE AND DATABASE SUPPORT OF JAVA


Swings fundamentals  Swing Key Features, Model View Controller (MVC), Swing Controls, Components and Containers, Swing Packages, Event Handling in Swings, Swing Layout Managers, Exploring Swings –JFrame, JLabel, The Swing Buttons, JTextField. Java DataBase Connectivity (JDBC)  JDBC overview, Creating and Executing Queries – create table, delete, insert, select  
Text Books And Reference Books: T1. Herbert Schildt, Java: The Complete Reference, 8/e, Tata McGraw Hill, 2011. T2. Rajib Mall, Fundamentals of Software Engineering, 4th edition, PHI, 2014 T3. Paul Deitel, Harvey Deitel, Java How to Program, Early Objects 11th Edition, Pearson, 2018  
Essential Reading / Recommended Reading R1. Y. Daniel Liang, Introduction to Java Programming, 7/e, Pearson, 2013 R2. Nageswararao R., Core Java: An Integrated Approach, Dreamtech Press, 2008 R3. Flanagan D., Java in A Nutshell, 5/e, O'Reilly, 2005 R4. Barclay K., J. Savage, Object Oriented Design with UML and Java, Elsevier, 2004 R5. Sierra K., Head First Java, 2/e, O'Reilly, 2005 R6. Balagurusamy E., Programming JAVA a Primer, 5/e, McGraw Hill, 2014  
Evaluation Pattern As per University Norms  
ELC432  ARTIFICIAL INTELLIGENCE (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

This course aims to introduce artificial intelligence by knowledge representation using semantic networks and rules, concepts of logic in artificial intelligence, concepts of planning and learning with an introduction of the expert systems. 

Course Outcome 

CO1: Formulate an efficient problem space for a problem in artificial intelligence CO2: Select a search algorithm for a problem and characterize its time and space complexities CO3: Understand the concepts of knowledge representation using an appropriate technique CO4: Apply AI techniques to solve problems of Game Playing, Expert Systems, Machine Learning and Natural Language Processing CO5: Explain expert systems based on architecture, roles and knowledge acquisition. 
Unit1 
Teaching Hours:9 
INTRODUCTION


Introduction, History, Intelligent Systems, Foundations of AI, Sub areas of AI, Applications. Problem Solving – StateSpace Search and Control Strategies: Introduction, General Problem Solving, Characteristics of Problem, Exhaustive Searches, Heuristic Search Techniques, IterativeDeepening A*, Constraint Satisfaction. Game Playing, Bounded Lookahead Strategy and use of Evaluation Functions, AlphaBeta Pruning.  
Unit2 
Teaching Hours:9 
KNOWLEDGE REPRESENTATION AND LOGIC


Logic Concepts and Logic Programming: Introduction, Propositional Calculus, Propositional Logic, Natural Deduction System, Axiomatic System, Semantic Tableau System in Propositional Logic, Resolution Refutation in Propositional Logic, Predicate Logic, Logic Programming. Knowledge Representation: Introduction, Approaches to Knowledge Representation, Knowledge Representation using Semantic Network, Extended Semantic Networks for KR, Representing Knowledge using rules – Rules based deduction system, Knowledge Representation using Frames  
Unit3 
Teaching Hours:9 
REASONING UNDER UNCERTAINITY


Introduction to uncertain knowledge review of probability – Baye’s Probabilistic inferences and Dempster Shafer theory –Heuristic methods – Symbolic reasoning under uncertainty Statistical reasoning – Fuzzy reasoning – Temporal reasoning Non monotonic reasoning.  
Unit4 
Teaching Hours:9 
PLANNING AND LEARNING


Planning  Introduction, Planning in situational calculus  Representation for planning – Partial order planning algorithm Learning from examples Discovery as learning – Learning by analogy – Explanation based learning –Introduction to Neural nets – Genetic Algorithms  
Unit5 
Teaching Hours:9 
EXPERT SYTEMS


Expert Systems – Architecture Of Expert Systems, Roles Of Expert Systems – Knowledge Acquisition –Meta Knowledge, Heuristics. Typical Expert Systems – MYCIN, DART, XOON, Expert Systems Shells.  
Text Books And Reference Books: T1.Saroj Kaushik. Artificial Intelligence. Cengage Learning. 2011 T2. Patrick Henry Winston,” Artificial Intelligence”, Addison Wesley, Third edition, 2010 T3. Kevin Night And Elaine Rich, Nair B., “Artificial Intelligence (SIE)”, McGraw Hill 2008  
Essential Reading / Recommended Reading R1. George F Luger, Artificial Intelligence, Pearson Education, 6th edition,2009 R2. Engene Charniak and Drew Mc Dermott,” Introduction to Artificial intelligence, Addison Wesley, 2009 R3. Nils J. Nilsson,”Principles of Artificial Intelligence“, Narosa Publishing House, 2000  
Evaluation Pattern As per University norms  
ELC433  SIGNALS AND SYSTEMS (2022 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

This course provides the mathematical representation of signals and systems using various transforms such as laplace, fourier and ztransforms. The course is designed to make the students familiar with the signals and their variations so that the fundamental of electronics engineering is well placed out. 

Course Outcome 

CO1: Understand the relation among transfer function, convolution and the impulse response CO2: Understand the relationship between the stability and causality of systems and the region of convergence of their Laplace transforms CO3: Express periodic signals in terms of Fourier series and represent an arbitrary signal in terms of a fourier transform CO4: Apply the Z transform of continuoustime and discretetime signals for stability analysis CO5: Explain basics of signals and systems to find the response of LTI system using convolutio 
Unit1 
Teaching Hours:9 
INTRODUCTION


Definition, types of signals and their representations: continuoustime/discretetime, periodic/nonperiodic, even/odd, energy/power, deterministic/ random, one dimensional/ multidimensional; commonly used signals (in continuoustime as well as in discretetime): unit impulse, unit step, unit ramp (and their interrelationships), exponential, rectangular pulse, sinusoidal; operations on continuoustime and discretetime signals (including transformations of independent variables)  
Unit2 
Teaching Hours:9 
LAPLACE TRANSFORM


Onesided LT of some common signals, important theorems and properties of LT, inverse LT, solutions of differential equations using LT, Bilateral LT, Regions of convergence (ROC  
Unit3 
Teaching Hours:9 
FOURIER TRANSFORM


Definition, conditions of existence of FT, properties, magnitude and phase spectra, Some important FT theorems, Parseval’s theorem, Inverse FT, relation between LT and FT, Discrete time Fourier transform (DTFT), inverse DTFT, convergence, properties and theorems, Comparison between continuous time FT and DTFT.  
Unit4 
Teaching Hours:9 
LINEAR TIME INVARIANT SYSTEMS


Continuous Time Systems: Linear Time invariant Systems and their properties. Differential equation & Block diagram representation, Impulse response, Convolution integral, Frequency response (Transfer Function), Fourier transforms analysis. Discrete Time System: Difference equations, Block diagram representation, Impulse response, Convolution sum, MATLAB tutorials  
Unit5 
Teaching Hours:9 
LINEAR TIME INVARIANT SYSTEMS


Continuous Time Systems: Linear Time invariant Systems and their properties. Differential equation & Block diagram representation, Impulse response, Convolution integral, Frequency response (Transfer Function), Fourier transforms analysis. Discrete Time System: Difference equations, Block diagram representation, Impulse response, Convolution sum, MATLAB tutorials  
Text Books And Reference Books: T1. P. Ramakrishna Rao, `Signal and Systems’ 2008 Ed., Tata McGraw Hill, New DelhIi. T2. Signals, Systems & Communications  B.P. Lathi, BS Publications, 2003  
Essential Reading / Recommended Reading R1. Signals & Systems  Simon Haykin and Van Veen, Wiley, 2nd Edition R2. Principles of Linear Systems and Signals, BP Lathi, Oxford University Press, 2015 R3. Fundamentals of Signals and Systems Michel J. Robert, MGH International Edition, 2008
 
Evaluation Pattern · Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIA III : Quiz/Seminar/Case Studies/Project/ Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 %  Medium Level questions 25 %  Simple level questions 25 %  Complex level questions
 
EVS421  ENVIRONMENTAL SCIENCE (2022 Batch)  
Total Teaching Hours for Semester:30 
No of Lecture Hours/Week:2 
Max Marks:0 
Credits:0 
Course Objectives/Course Description 

To understand the scope and importance of environmental science towards developing a conscious community for environmental issues, both at global and local scale. 

Course Outcome 

CO1: Explain the components and concept of various ecosystems in the environment (L2, PO7) CO2: Explain the necessity of natural resources management (L2, PO1, PO2 and PO7) CO3: Relate the causes and impacts of environmental pollution (L4, PO1, PO2, and PO3, PO4) CO4: Relate climate change/global atmospheric changes and adaptation (L4,PO7) CO5: Appraise the role of technology and institutional mechanisms for environmental protection (L5, PO8) 
Unit1 
Teaching Hours:6 
Introduction


Environment and Eco systems – Definition, Scope and importance. Components of environment. Concept and Structure of eco systems. Material Cycles – Nitrogen, Carbon, Sulphur, Phosphorous, Oxygen. Energy Flow and classification of Eco systems.  
Unit2 
Teaching Hours:6 
Natural Resources


Classification and importance Forest, Water, Mineral, Food, Energy. Management of natural resources – challenges and methods. Sustainable development – Goals, Agriculture, Industries  
Unit3 
Teaching Hours:6 
Environmental Pollution


Causes and Impacts – Air pollution, Water pollution, Soil Pollution, Noise Pollution, Marine Pollution, Municipal Solid Wastes, Bio Medical and EWaste. Solid Waste Management  
Unit4 
Teaching Hours:6 
Climate change/Global Atmospheric Change


Global Temperature, Greenhouse effect, global energy balance, Global warming potential, International Panel for Climate Change (IPCC) Emission scenarios, Oceans and climate change. Adaptation methods. Green Climate fund. Climate change related planning small islands and coastal region. Impact on women, children, youths and marginalized communities  
Unit5 
Teaching Hours:6 
Environmental Protection


Technology, Modern Tools – GIS and Remote Sensing,. Institutional Mechanisms  Environmental Acts and Regulations, Role of government, Legal aspects. Role of Nongovernmental Organizations (NGOs) , Environmental Education and Entrepreneurship  
Text Books And Reference Books: T1Kaushik A and Kaushik. C. P, “Perspectives in Environmental Studies”New Age International Publishers, New Delhi, 2018 [Unit: I, II, III and IV] T2Asthana and Asthana, “A text Book of Environmental Studies”, S. Chand, New Delhi, Revised Edition, 2010 [Unit: I, II, III and V] T3Nandini. N, Sunitha. N and Tandon. S, “environmental Studies” , Sapana, Bangalore, June 2019 [Unit: I, II, III and IV] T4R Rajagopalan, “Environmental Studies – From Crisis to Cure”, Oxford, Seventh University Press, 2017, [Unit: I, II, III and IV]
 
Essential Reading / Recommended Reading R1.Miller. G. T and Spoolman. S. E, “Environmental Science”, CENAGE Learning, New Delhi, 2015 R2.Masters, G andEla, W.P (2015), Introduction to environmental Engineering and Science, 3rd Edition. Pearson., New Delhi, 2013. R3.Raman Sivakumar, “Principals of Environmental Science and Engineering”, Second Edition, Cengage learning Singapore, 2005. R4.P. Meenakshi, “Elements of Environmental Science and Engineering”, Prentice Hall of India Private Limited, New Delhi, 2006. R5.S.M. Prakash, “Environmental Studies”, Elite Publishers Mangalore, 2007 R6.ErachBharucha, “Textbook of Environmental Studies”, for UGC, University press, 2005. R7. Dr. Pratiba Sing, Dr. AnoopSingh and Dr. PiyushMalaviya, “Textbook of Environmental and Ecology”, Acme Learning Pvt. Ltd. New Delhi.  
Evaluation Pattern No Evaluation  
CSOE561E04  PYTHON FOR ENGINEERS (2021 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

Specifically, the course has the following objectives. By the end of the course, students will be able to: ● Develop a working knowledge for how computers operate and how computer programs are executed. ● Evolve critical thinking and problemsolving skills using an algorithmic approach. ● Learn about the programmer’s role in the software development process. Translate realworld issues into computersolvable problems. 

Course Outcome 

CO1: Demonstrate the basic methods of formatting, outputting data, kinds of data, operators and variables. CO2: Interpret with the concepts of Boolean values, utilization of loops and operators. CO3: Experiment with functions, passing arguments and data processing. CO4: Illustrate the concept of modules, exceptions, strings and lists. CO5: Apply the fundamentals of OOP and its implementation. 
Unit1 
Teaching Hours:9 
INTRODUCTION


Introduction to Python and computer programming: Programming – absolute basics, Python – a tool, not a reptile, First program, Python literals, Operators – data manipulation tools, Variables  
Unit2 
Teaching Hours:9 
CONDITIONAL STATEMENTS LOOPING AND ARRAY


Making decisions in Python, Python's loops, Logic and bit operations in Python, Lists – collections of data, Sorting simple lists – the bubble sort algorithm, Lists – some more details, Lists in advanced applications  
Unit3 
Teaching Hours:9 
FUNCTIONS


Writing functions in Python, How functions communicate with their environment, Returning a result from a function, Scopes in Python. Creating functions, Tuples and dictionaries  
Unit4 
Teaching Hours:9 
MODULES


Using modules, Some useful modules, Package, Errors, The anatomy of an exception, Some of the most useful exceptions, Characters and strings vs. computers, The nature of Python's strings, String methods, Strings in action.  
Unit5 
Teaching Hours:9 
FUNDAMENTALS OF OOP


Basic concepts of object programming, A short journey from the procedural to the object approach, Properties, Methods, Inheritance – one of object programming foundations, Generators and closures, Processing files, Working with real files.  
Text Books And Reference Books: T1. Eric Matthes, “Python Crash Course”, 2nd Edition: A HandsOn, ProjectBased Introduction to Programming, No Starch Press, Inc, 2016T2. Paul Barry, “Head first Python”, 2nd Edition, O’Reilly, 2017.  
Essential Reading / Recommended Reading R1: Paul Barry, “Head First Python: A BrainFriendly Guide”, Shroff/O'Reilly; Second edition (1 December 2016)R2: Martin C. Brown,”Python: The Complete Reference”, McGraw Hill Education; Forth edition (20 March 2018)  
Evaluation Pattern CIA Marks : 50 ESE Marks : 50  
CSOE561E05  BASICS OF MACHINE LEARNING (2021 Batch)  
Total Teaching Hours for Semester:45 
No of Lecture Hours/Week:3 
Max Marks:100 
Credits:3 
Course Objectives/Course Description 

Course objectives: • To understand the need for machine learning • To discover supervised and unsupervised learning paradigms of machine learning • To learn various machine learning techniques • To design suitable machine learning algorithms for solving problems 

Course Outcome 

CO 1: Describe various supervised learning methods CO 2: Discuss various unsupervised learning methods. CO 3: Explain the basics of neural networks and back propagation algorithm for problem solving. CO 4: Describe the usage of genetic algorithms in problem solving. CO 5: Use the concept of Bayesian theory to machine learning. 
Unit1 
Teaching Hours:9 
Unit1 SUPERVISED LEARNING


Basic methods: Distancebased methods, NearestNeighbours, Decision Trees, Naive Bayes. Linear models: Linear Regression, Logistic Regression, Generalized Linear Models.Support Vector Machines.  
Unit2 
Teaching Hours:9 
Unit2 UNSUPERVISED LEARNING


Clustering: Kmeans/Kernel Kmeans,Dimensionality Reduction: PCA and kernel PCA, Matrix Factorization and Matrix Completion.  
Unit3 
Teaching Hours:9 
Unit3 NEURAL NETWORKS


Neural Network Representation – Problems – Perceptrons – Multilayer Networks and Back Propagation Algorithms – Advanced Topics.  
Unit4 
Teaching Hours:9 
Unit4 BAYESIAN AND COMPUTATIONAL LEARNING


Bayes Theorem – Concept Learning – Maximum Likelihood – Minimum Description Length Principle – Bayes Optimal Classifier – Gibbs Algorithm – Naïve Bayes Classifier – Bayesian Belief Network – EM Algorithm.  
Unit5 
Teaching Hours:9 
Unit5 INSTANCEBASED, ANALYTICAL LEARNING AND INDUCTIVE BASED LEARNING

