Department of COMPUTER SCIENCE AND ENGINEERING

Syllabus for
Bachelor of Technology (Information Technology)
Academic Year  (2020)

 
3 Semester - 2019 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
CS331P DATABASE MANAGEMENT SYSTEMS 5 4 100
CS332P DATA STRUCTURES AND ALGORITHMS 5 4 100
CS333 SOFTWARE ENGINEERING 3 3 100
EC337 DIGITAL SYSTEMS 4 3 100
HS311 TECHNICAL WRITING 2 2 50
MA334 DISCRETE MATHEMATICS 3 3 100
MC321 CYBER SECURITY 2 0 50
MIMBA331 PRINCIPLES OF MANAGEMENT 6 4 100
MIPSY331 UNDERSTANDING HUMAN BEHAVIOR 4 4 100
4 Semester - 2019 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
BS451 BIO SCIENCE LABORATORY 2 1 50
CS431 PROBABILITY AND QUEUING THEORY 3 3 100
CS432P OPERATING SYSTEMS 5 4 100
CS433P PROGRAMMING PARADIGM 5 4 100
CS434 FORMAL LANGUAGE AND AUTOMATA THEORY 3 3 100
CS435P COMPUTER ORGANIZATION AND ARCHITECTURE 5 4 100
CS436 PROFESSIONAL ETHICS 3 3 100
MC422 ENVIRONMENTAL SCIENCE 2 1 50
MIMBA431 ORGANISATIONAL BEHAVIOUR 6 4 100
MIPSY431 PEOPLE THOUGHTS AND SITUATIONS 4 4 100
5 Semester - 2018 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
CS531 COMPUTER ORIENTED NUMERICAL ANALYSIS 3 3 100
CS532E01 FORMAL LANGUAGE AND AUTOMATA THEORY 3 3 100
CS532E02 COMPILER DESIGN 3 3 100
CS532E03 FUZZY LOGIC 3 3 100
CS533P INTERNET OF THINGS 5 4 100
CS534 DESIGN AND ANALYSIS OF ALGORITHMS 4 4 100
CS535 SOFTWARE ENGINEERING 3 3 100
CS536P INTERNET AND WEB PROGRAMMING 5 4 100
CSHO531AIP STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE 4 4 100
CSHO531CSP PROBABILITY AND RANDOM PROCESS 5 4 100
CSHO531DAP STATISTICAL FOUNDATION FOR DATA ANALYTICS 5 4 50
6 Semester - 2018 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
CE636OE1 SOLID WASTE MANAGEMENT 3 3 100
CE636OE2 ENVIRONMENTAL IMPACT ASSESSMENT 3 3 100
CE636OE4 DISASTER MANAGEMENT 4 3 100
CS631 CRYPTOGRAPHY AND NETWORK SECURITY 3 3 100
CS632P OBJECT ORIENTED ANALYSIS AND DESIGN 5 4 100
CS633P SYSTEM SOFTWARE 5 4 100
CSHO631AIP ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING 5 4 100
CSHO631CSP MOBILE AND NETWORK BASED ETHICAL HACKING 5 4 100
CSHO631DAP BIG DATA ANALYTICS 5 4 100
CSHO632AIP ROBOTICS AND PROCESS AUTOMATION 5 4 100
CSHO632CSP CYBER FORENSICS AND MALWARE DETECTION 5 4 100
CSHO632DAP BIG DATA SECURITY ANALYTICS 5 4 100
EC636OE1 EMBEDDED BOARDS FOR IOT APPLICATIONS 3 34 100
EC636OE4 FUNDAMENTALS OF IMAGE PROCESSING 3 3 100
EC636OE7 E-WASTE MANAGEMENT AND RADIATION EFFECT 3 3 100
EE636OE2 NONCONVENTIONAL ENERGY SOURCES 4 3 100
EE636OE3 INTRODUCTION OF HYBRID ELECTRIC VEHICLES 4 3 100
EE636OE6 ROBOTICS AND AUTOMATION 4 3 100
IT634P DATAWAREHOUSING AND DATAMINING 5 4 100
IT635 SOFTWARE TESTING 3 3 100
MA636OE3 NUMERICAL SOLUTION OF DIFFERENTIAL EQUATIONS 3 3 100
ME636OE3 BASIC AUTOMOBILE ENGINEERING 3 3 100
ME636OE4 PROJECT MANAGEMENT 3 3 100
ME636OE5 BASIC AEROSPACE ENGINEERING 3 3 100
7 Semester - 2017 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
BTGE 732 ACTING COURSE 2 2 100
BTGE 734 DIGITAL WRITING 2 2 100
BTGE 737 PROFESSIONAL PSYCHOLOGY 2 2 100
BTGE 744 DIGITAL MARKETING 2 2 100
BTGE 745 DATA ANALYTICS THROUGH SPSS 2 2 100
BTGE735 DIGITAL MEDIA 2 2 100
BTGE736 INTELLECTUAL PROPERTY RIGHTS 2 2 100
BTGE738 CORPORATE SOCIAL RESPONSIBILITY 2 2 100
BTGE739 CREATIVITY AND INNOVATION 2 2 100
BTGE741 GERMAN 2 2 100
BTGE749 PAINTING AND SKETCHING 2 2 100
BTGE750 PHOTOGRAPHY 2 2 100
BTGE754 FUNCTIONAL ENGLISH 4 2 100
CS731 ARTIFICIAL INTELLIGENCE 4 4 100
CS732 CLOUD COMPUTING 3 3 100
CS733P MOBILE APPLICATION DEVELOPMENT 5 4 100
CS735E01 NATURAL LANGUAGE PROCESSING 3 3 100
CS735E02 RESEARCH METHODOLOGY 3 3 100
CS736E01 GRAPH THEORY 3 3 100
CS736E03 WIRELESS NETWORKS 3 3 100
CS771 INTERNSHIP 2 2 50
CS772 SERVICE LEARNING 2 2 50
IT735E01 INFORMATION SECURITY 3 3 100
IT736E01 SIMULATION AND MODELING 3 3 100
IT736E03 ADVANCED DATABASES 3 3 100
IT736E04 NETWORK ADMINISTRATION 3 3 100
8 Semester - 2017 - Batch
Course Code
Course
Hours Per
Week
Credits
Marks
BTCY01 CYBER SECURITY 2 2 50
CS831E01 QUANTUM COMPUTING 3 3 100
CS831E02 GRID COMPUTING 3 3 100
CS831E03 MOBILE COMPUTING 3 3 100
CS832E01 SOFTWARE TESTING 3 3 100
CS832E02 SOFTWARE PROCESS AND PROJECT MANAGEMENT 3 3 100
CS833E02 INTRODUCTION TO DATA SCIENCE 3 3 100
CS833E03 SOFT COMPUTING 3 3 100
CS833E04 DIGITAL IMAGE PROCESSING 3 3 100
CS871 PROJECT WORK 12 6 200
CS872 COMPREHENSION 4 2 50
IT832E02 WEB SERVICES AND SERVICE ORIENTED ARCHITECTURE 3 3 100
IT833E04 PROFESSIONAL ETHICS AND HUMAN VALUES 3 3 100
        

  

Assesment Pattern

 

 

Category 

Weightage for CIA

Weightage for ESE

1

Courses with theory and practical

70

30

2

Courses with only theory 

50

50

3

Courses with only Practical

50

50

 

COURSES WITH THEORY AND PRACTICAL

 

Component

Assessed for

Minimum marks

 to pass 

Maximum 

marks 

1

Theory CIA

30

-

30

2

Theory ESE

30

12

30

3

Practical CIA

35

14

35

4

Attendance

05

-

05

4

Aggregate 

100

40

100

 

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY 

PRACTICAL 

 

Component

Assessed for

Scaled down to

Minimum marks to pass 

Maximum marks 

Component

Assessed for

Scaled down to

Minimum marks to pass 

Maximum marks 

1

CIA-1 

20 

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50 

10

-

10




3

CIA-3

20 

10

-

10




4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100 

30

12

30

ESE

NA

NA

-

-

   

TOTAL 

65

-

65

TOTAL

 

35

14

35

 

  • 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

 

II. ASSESSMENT - ONLY FOR THEORY COURSE (without practical component)

  • 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: 

  • 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. 

Question paper pattern is as follows. 

Two full questions with either or choices will be outlined from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a particular question. The objective of the question paper is to test the application and analytical skill of the student. The major purpose of the question paper is to bring clarity about the process of associating questions to their respective performance indicators and hence to improve the ratings in course outcomes. Further, these question papers demonstrate how bloom’s taxonomy can be used to map the quality of question papers along with their effectiveness in the assessment pattern.

 

III. ASSESSMENT OF COMPREHENSION, INTERNSHIP and SERVICE LEARNING

COMPREHENSION

Maximum Marks = 50

Passing marks 40% min

Do not have ESE and completely evaluated through continuous assessment only, 

 

The evaluation (minimum 2 presentations) shall be based on the 

  • Topic / report :40% 

  • Presentation: 40% 

  • Response to the questions asked during presentation : 20%.

INTERNSHIP

 

Maximum Marks = 50(Only credit will be displayed in the score card)

Passing marks 40% min

Do not have ESE and completely evaluated through continuous assessment only

Continuous Internal Assessment is based upon

  • No of Internship Days: 20 marks

  • Report on Internship: 15 marks

  • Presentation on Internship: 15 marks

 

SERVICE LEARNING

Maximum Marks = 50

Passing marks 40% min

Do not have ESE and completely evaluated through continuous assessment only, 

Comprising

  • Internal Assessment with components like tests/quiz/written assignments: 25 marks 

  • Field Work or equivalent assignment as approved by the department panel: 25 marks  

 

V. ASSESSMENT OF PROJECT WORK

       Project Phase-I  

Project work may be assigned to a single student (with due approval from department) or to a group of students not exceeding 4 per group.

Maximum Marks = 100

  • Continuous Assessment :50 marks.

  • End Semester Examination (project report evaluation and viva-voce) : 50 marks.

  • The continuous assessment and End Semester Examinations marks for Project Work and the Viva-Voce Examination will be distributed as indicated below.

 


CIA 50 MARKS


ESE 50 MARKS

REVIEW 1

REVIEW 2

REVIEW 3

 

REVIEW COMMITTEE

GUIDE

REVIEW COMMITTEE

GUIDE

REVIEW COMMITTEE

GUIDE

EXAMINERES

10

05

10

05

10

10

50

TOTAL

15

TOTAL

15

TOTAL

20

 

  • There shall be 3 reviews and the student shall make presentation on the progress made before the committee constituted by the Department

  • The total marks obtained in the 3 reviews shall be 100 marks.

ESE 100 MARKS IS EVALUATED AS

  • Initial Write Up    : 10marks

  • Viva Voce: 25 marks

  • Demonstration: 40 marks

  • Project Report: 25 marks

 

Holistic Education:

   End Semester Examination          :25 Marks

   Participation:25 Marks

 

   Total :50 Marks

 

Examination And Assesments

Continuous internal Assesment-CIA-I,CIA-II,CIA-III

End Semester Examination

Department Overview:
BRIEF HISTORY OF DEPARTMENT Department of Computer Science and Engineering started of journey to produce qualified Engineers to society with variety of skills. The department offers the degrees Bachelor of Technology, Master of Technology, and Doctor of Philosophy in the areas of Computer Science and Engineering and Information Technology. The department has rich knowledge pool of faculty resource who are well trained in various fields like Artificial Intelligence, Machine learning, Computer Vision, Algorithms design, Cryptography, Computer Networking, Data mining, Data science, BIG DATA, Digital Image Processing, text mining, knowledge representation, soft computing, Cloud computing, etc.. The department has wide variety of labs setup namely open source lab, Machine learning lab, CISCO Networking Lab etc.. Specifically for students for their lab curriculum and for their research. The department periodically conducts hands-on workshop on recent technology like Internet of Things, Cloud computing, Machine learning etc..for the students so that they should be updated with current technology. The department imparts teaching in Holistic method, where students who are trained under holistic education will be better citizens of Nation .The main educational goal is to prepare students for research and career in industry or in universities.
Mission Statement:
DEPARTMENT VISION Ethical Computational Excellence MISSION STATEMENT 1. Imparts core and contemporary knowledge in the areas of Computation and Information Technology 2. Promotes the culture of research and facilitates higher studies 3. Acquaints the students with the latest industrial practices, team building and entrepreneurship 4. Sensitizes the students to serve for environmental, social & ethical needs of society through lifelong learning
Introduction to Program:
The Undergraduate program in Information Technology is aimed at creating computer science engineers by providing the fundamentals of engineering and basic skills in computing. The special focus on employability is clear from the inclusion of subjects based on demand of industry and mandatory internships. A well-chosen elective basket gives the ward an opportunity to widen their knowledge in any specific domain.
Program Objective:
The Undergraduate program in Information Technology is aimed at creating computer science engineers by providing the fundamentals of engineering and basic skills in computing. The special focus on employability is clear from the inclusion of subjects based on demand of industry and mandatory internships. A well-chosen elective basket gives the award an opportunity to widen their knowledge in any specific domain. PROGRAM OUTCOMES An ability to apply Engineering knowledge of computing, mathematics, science, and computer science & engineering fundamentals for Problem solving. An ability to think critically to identify, formulate, and solve complex computer science & engineering problems by developing models, evaluating validity and accuracy of solutions in terms of computer science and engineering validity measures. An ability to analyze, design of complex problems, implement, and evaluate a computer-based system, to meet expected needs with appropriate considerations such as economic / environmental/societal. An ability to conduct experiments to investigate problems based on changing requirements, analyze and interpret results. An ability to create, select, adapt appropriate techniques and use of the modern computational tools, techniques and skills, and best of engineering practices. To understand the impact of contextual knowledge on social aspects and cultural issues. An ability to understand contemporary issues related to social & environmental context for susta

CS331P - DATABASE MANAGEMENT SYSTEMS (2019 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

·       To learn the fundamentals of data models and to conceptualize and depict a database system using ER diagram.

·       To make a study of SQL and relational database design.

·       To understand the internal storage structures using different file and indexing techniques which will help in physical DB design.

·       To know the fundamental concepts of transaction processing- concurrency control techniques and recovery procedure.

·       To have an introductory knowledge about the emerging trends in the area of distributed DB- OO DB- Data mining and Data Warehousing and XML.

·       To implement the design of the tables in DBMS.

·       To write queries to get optimized outputs. 

·       To store, retrieve and view the contents. To generate report based on customized need.

 

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1

Summarize the fundamental concepts of databases and Entity-Relationship (E-R) model.

L2

2

Apply E-R Model and Normalization principles to create relational databases for the given problems.

L3

3

Compare and contrast different file organization concepts for data storage in Relational databases

L4

4

Apply the transaction management principles on relational databases

L3

5

Demonstrate the current trends such as object oriented databases, distributed data storage in database technology

L2

Unit-1
Teaching Hours:15
INTRODUCTION AND CONCEPTUAL MODELING
 

Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra and Calculus.

Lab Programs

1. Data Definition Language (DDL) commands in RDBMS

2. Data Manipulation Language (DML) and Data Control Language (DCL) commands in   RDBMS.

Unit-2
Teaching Hours:15
RELATIONAL MODEL
 

SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependences and Normalization for Relational Databases (up to BCNF).

Lab programs

3. High-level language extension with Cursors.

4.High level language extension with Triggers

Unit-3
Teaching Hours:15
DATA STORAGE AND QUERY PROCESSING
 

Record storage and Primary file organization- Secondary storage Devices- Operations on Files- Heap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree - B+ Tree – Query Processing.

Lab Programs 

5. Procedures and Functions.

6. Embedded SQL.

Unit-4
Teaching Hours:15
TRANSACTION MANAGEMENT
 

Transaction Processing – Introduction- Need for Concurrency control- Desirable properties of Transaction- Schedule and Recoverability- Serializability and Schedules – Concurrency Control – Types of Locks- Two Phases locking- Deadlock- Time stamp based concurrency control – Recovery Techniques – Concepts- Immediate Update- Deferred Update - Shadow Paging.

Lab Programs

7. Database design using E-R model and Normalization.

8. Design and implementation of Payroll Processing System.

Unit-5
Teaching Hours:15
CURRENT TRENDS
 

Object Oriented Databases – Need for Complex Data types- OO data Model- Nested relations- Complex Types- Inheritance Reference Types - Distributed databases- Homogenous and Heterogenous- Distributed data Storage – XML – Structure of XML- Data- XML Document- Schema- Querying and Transformation. – Data Mining and Data Warehousing.

Lab Programs:

9. Design and implementation of Banking System

10.Design and implementation of Library Information System

 

Text Books And Reference Books:

 

1.     Abraham Silberschatz, Henry F. Korth and S. Sudarshan- “Database System Concepts”, Sixth Edition, McGraw-Hill, 2010.

 

Essential Reading / Recommended Reading

REFERENCE BOOKS

1.     RamezElmasri and Shamkant B. Navathe, “Fundamental Database Systems”, Third Edition, Pearson Education, 2008.

2.     Raghu Ramakrishnan, “Database Management System”, Tata McGraw-Hill Publishing Company, 2003

 

Evaluation Pattern

 Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) ·

 CIA 1 : Assignment and Quiz   10 marks

 CIA2  : Mid Semester Examination  10 marks

 CIA 3 : Practical Component and Mini Project  10 marks

Lab    :  Laboratory program  35 marks

Attendance -05 marks

End Semester Examination(ESE) : 30% (30 marks out of 100 marks)

CS332P - DATA STRUCTURES AND ALGORITHMS (2019 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 
  • To learn the systematic way of solving problems.
  • To understand the different methods of organizing large amounts of data.
  • To efficiently implement the different data structures.
  • To efficiently implement solutions for specific problems.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1.

Explain the basic concepts of data structures and solve the time complexity of the algorithm

L3

2.

Experiment with various operations on Linear Data structures

L3

3.

Examine the Structures and Operations of Trees and Heaps Data Structures

L4

4

Compare various given sorting techniques with respect to time complexity

L4

5

 Choose various shortest path algorithms to determine the minimum spanning path for the given graphs

L5

Unit-1
Teaching Hours:14
INTRODUCTION
 

Definition- Classification of data structures: primitive and non-primitive- Operations on data structures- Algorithm Analysis.

LAB Programs:

1a. Sample C Programs 1b. To determine the time complexity of a given logic. 

Unit-2
Teaching Hours:17
LISTS, STACKS AND QUEUES
 

Abstract Data Type (ADT) – The List ADT – The Stack ADT: Definition,Array representation of stack, Operations on stack: Infix, prefix and postfix notations Conversion of an arithmetic Expression from Infix to postfix. Applications of stacks. 

LAB Programs:

2. Implement the applications Stack ADT.

3. Implement the applications for Queue ADT.

4.Operations on stack[e.g.: infix to postfix, evaluation of postfix]

Unit-3
Teaching Hours:16
TREES
 

Preliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees – AVL Trees – Tree Traversals – Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing –Linear Probing – Priority Queues (Heaps) – Model – Simple implementations – Binary Heap.

LAB PROGRAMS:

5. Search Tree ADT - Binary Search Tree

Unit-4
Teaching Hours:14
SORTING
 

Preliminaries – Insertion Sort – Shell sort – Heap sort – Merge sort – Quicksort – External Sorting.

LAB PROGRAMS

6. Heap Sort.

7. Quick Sort.

8.Applications of Probability and Queuing Theory Problems to be implemented using data structures. 

Unit-5
Teaching Hours:14
GRAPHS
 

Definitions – Topological Sort – Shortest-Path Algorithms – Unweighted Shortest Paths – Dijkstra‘s Algorithm – Minimum Spanning Tree – Prim‘s Algorithm – Applications of Depth- First Search – Undirected Graphs – Bi-connectivity – Introduction to NP-Completeness-case study

LAB PROGRAMS

9. Implementing a Hash function/Hashing Mechanism.

10. Implementing any of the shortest path algorithms. 

 

Text Books And Reference Books:

TEXT BOOK

1.Mark Allen Weiss , “Data Structures and Algorithm Analysis in C”, 2nd  Edition, Addison-Wesley, 1997

Essential Reading / Recommended Reading

1. Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser , ―Data Structures and Algorithms in Python  ‖, First  Edition, John Wiley & Sons, Incorporated, 2013.ISBN1118476735, 9781118476734

Evaluation Pattern

Components of the CIA

CIA I : Assignment  and Continuous Assessment : 10 marks

CIA II : Mid Semester Examination (Theory) : 10 marks

CIA III : Closed Book Test and Continuous Assessment: 10 marks

Lab marks :35 marks

Attendance : 05 marks

End Semester Examination(ESE) : 30% (30 marks out of 100 marks)

Total: 100 marks

CS333 - SOFTWARE ENGINEERING (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

·         Learn different life cycle models and requirement elicitation process.

·         Understand various analysis modeling and specification, Architectural and detailed design methods.

·         Practice implementation methodologies and various testing strategies.

·         Analyze project planning and management concepts using various models and appropriate CASE tools.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

CO1

Explain the fundamental of Software development Life cycle and different software development process models.

L2

CO2

Apply various requirement elicitation methods in software development process

L3

CO3

Develop the software processes using various design techniques.

L3

CO4

Analyze different testing techniques and maintenance principles in software development process.

L4

CO5

Formulate the cost estimation techniques and project scheduling methods in software development process.

L6

Unit-1
Teaching Hours:9
SOFTWARE PROCESS
 

Introduction –S/W Engineering Paradigm  – life cycle models (water fall, incremental, spiral, WINWIN spiral, evolutionary, prototyping, object oriented) - system engineering – computer based system  – verification – validation – life cycle process – development process –system engineering hierarchy.

Unit-2
Teaching Hours:9
SOFTWARE REQUIREMENTS
 

Functional and non-functional - user – system –requirement engineering process – feasibility studies – requirements – elicitation – validation and management – software prototyping – prototyping in the software process – rapid prototyping techniques – user interface prototyping -S/W document. Agile methods, Extreme Programming, SCRUM

Unit-3
Teaching Hours:9
DESIGN CONCEPTS AND PRINCIPLES
 

Design process and concepts – modular design – design heuristic – design model and document. Architectural design – software architecture – data design – architectural design – transform and transaction mapping – user interface design – user interface design principles. Real time systems - Real time software design – system design – real time executives – data acquisition system - monitoring and control system. SCM – Need for SCM – Version control – Introduction to SCM process – Software configuration items.

Unit-4
Teaching Hours:9
TESTING
 

Taxonomy of software testing – levels – test activities – types of s/w test – black box testing – testing boundary conditions – structural testing – test coverage criteria based on data flow mechanisms – regression testing – testing in the large. S/W testing strategies – strategic approach and issues - unit testing – integration testing – validation testing – system testing and debugging.

Unit-5
Teaching Hours:9
SOFTWARE PROJECT MANAGEMENT
 

Measures and measurements – S/W complexity and science measure – size measure – data and logic structure measure – information flow measure. Software cost estimation – function point models – COCOMO model- Delphi method.- Defining a Task Network – Scheduling – Earned Value Analysis – Error Tracking - Software changes – program evolution dynamics – software maintenance – Architectural evolution. Taxonomy of CASE tools – Case Study.

Text Books And Reference Books:

 Roger S. Pressman, Software engineering- A Practitioner’s Approach, McGraw-Hill International Edition, 6th Edition 2014 

Essential Reading / Recommended Reading

Anirban Basu, “Software Quality Assurance, Testing and Metrics”, First Edition, PHI Learning, 2015.

Ian Sommerville, “Software engineering,” Pearson education Asia, 9th Edition, 2013.

Pankaj Jalote- “An Integrated Approach to Software Engineering,” Narosa Publishing house, 2011.

James F Peters and Witold Pedryez, “Software Engineering – An Engineering Approach”, John Wiley and Sons, New Delhi, 2010.

Ali Behforooz and Frederick J Hudson, “Software Engineering Fundamentals”, OUP India 2012.

 

Evaluation Pattern

Continuos Internal Assessment CIA Marks 50

End Semester Exams ESE 50

EC337 - DIGITAL SYSTEMS (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:4
Max Marks:100
Credits:3

Course Objectives/Course Description

 

·         This course is an introduction to the VHDL language. The emphasis is on writing synthesizable code and enough simulation code to write a viable test-bench.

·         The information gained can be applied to any digital design by using a top-down synthesis design approach.

Learning Outcome

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

·         Implement the VHDL portion of coding for synthesis.

·         Identify the differences between behavioral and structural coding styles.

·         Understand the basic principle of circuit design and analysis.

Unit-1
Teaching Hours:9
INTRODUCTION AND METHODOLOGY
 

Digital Systems and Embedded Systems, Boolean Functions and Boolean algebra, Binary Coding, Combinational Components and Circuits, Verification of Combinational Circuits. Number Basics: Unsigned and Signed Integers, Fixed and Floating-point Numbers, Binary representation and Circuit Elements, Real-World Circuits, Models, Design Methodology.

Unit-2
Teaching Hours:9
SEQUENTIAL BASICS & MEMORIES
 

Storage elements, Counters, Sequential Data paths and Control, Clocked Synchronous Timing Methodology. Memories: Concepts, Memory Types, Error Detection and Correction.

Unit-3
Teaching Hours:9
IMPLEMENTATION FABRICS & PROCESSOR BASICS
 

ICs, PLDs, Packaging and Circuit Boards, Interconnection and Signal Integrity. Processor Basics: Embedded Computer Organization, Instruction and Data, Interfacing with memory.

Unit-4
Teaching Hours:9
I/O INTERFACING, ACCELERATORS & DESIGN METHODOLOGY
 

I/O devices, I/O controllers, Parallel Buses, Serial Transmission, I/O software. Accelerators: Concepts, case study, Verification of accelerators. Design Methodology: Design flow, Design optimization, Design for test.

Unit-5
Teaching Hours:9
SIMPLE SINGLE CYCLE AND MULTI CYCLE PROCESSOR DESIGN
 

Introduction of Simple Single Cycle and Multi Cycle Processor Design.

Text Books And Reference Books:

1.      C. H. Roth, Digital Systems Design Using VHDL, Thomson Publications, Fourth Edition, 2002.

V. A. Pedroni, Circuit Design with VHDL, MIT Press/PHI, 2004. 

Essential Reading / Recommended Reading

1.      Parhami, Behrooz, Computer Arithmetic: Algorithms and Hardware Designs, Oxford University Press, 2009.

2.      Z. Navabi, Verilog Digital System Design, Second Edition, Tata McGrawHill, 2008.

3.      R. C. Cofer and B. F. Harding, Rapid System Prototyping with FPGAs: Accelerating the Design Process, Elsevier/Newness, 2005.

Peter J. Ashenden, “Digital Design: An Embedded Systems Approach Using VERILOG”, Elesvier, 2010.

Evaluation Pattern

Assessment is based on the performance of the student throughout the semester.

Assessment of each paper

·         Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out

of 100 marks)

·         End Semester Examination(ESE) : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :   Mid Semester Examination (Theory)                    : 25 marks                  

CIA II  :  Assignments                                                            : 10 marks

CIA III            : Quizzes/Seminar/Case Studies/Project Work     : 10 marks

Attendance                                                                             : 05 marks

            Total                                                                                         : 50 marks

For subjects having practical as part of the subject

 

Assessment of Practical paper

Conduct of experiments                                                       : 25 marks

Observations/Lab Record                                                   : 15 marks

Viva voce                                                                                : 10 marks

Total                                                                                        : 50 marks

(All the above assessments are carried for each experiment during regular lab classes and averaged to max 50 marks at the end of the semester)

HS311 - TECHNICAL WRITING (2019 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:2

Course Objectives/Course Description

 

The goal of this course is to prepare engineering students with individual and collaborative technical writing skills that are necessary to be effective technical communicators in academic and professional environments.

Learning Outcome

CO1.  Understand the basics of technical communication and the use of formal elements of specific genres of documentation.

CO2.  Demonstrate the nuances of technical writing, with reference to english grammar and vocabulary.

CO3.  Recognize the importance of soft skills and personality development for effective  communication.

CO4.  Understand the various techniques involved in oral communication and its application.

CO5.  Realize the importance of having ethical work habits and professional etiquettes.

Unit-1
Teaching Hours:6
Design and Development
 

Different kinds of technical documents, Information development life cycle, Organization structures, factors affecting information and document design, Strategies for organization, Information design and writing for print and for online media.

Unit-2
Teaching Hours:6
Grammar and Editing
 

Technical writing process, writing drafts and revising,   technical writing style and language. Basics of grammar, study of advanced grammar, editing strategies to achieve appropriate technical style. Introduction to advanced technical communication

Unit-3
Teaching Hours:6
Self Development and Assessment
 

Self-assessment, Perception and Attitudes, Values and belief, Personal goal setting, career planning, Self- esteem. Managing Time; Personal memory, Rapid reading, Taking notes; Complex problem solving; Creativity

Unit-4
Teaching Hours:6
Communication and Writing
 

Public speaking, Group discussion, Oral presentation, Interviews, Presentation aids, Personality Development.  project proposals, brochures, newsletters, technical articles, manuals,  business letters, memos

Unit-5
Teaching Hours:6
Business Etiquettes
 

Etiquettes in social and office settings, Email etiquettes, Telephone Etiquettes, Engineering ethics, Time Management, Role and responsibility of engineer, Work culture in jobs

Text Books And Reference Books:

T1 : David F. Beer and David McMurrey, Guide to writing as an Engineer, John Willey. New    York, 2004 

       T2: Diane Hacker, Pocket Style Manual, Bedford Publication, New York, 2003. (ISBN 0312406843)

T3: Raman Sharma, Technical Communications, Oxford Publication, London, 2004

Essential Reading / Recommended Reading

R1.Dale Jungk, Applied Writing for Technicians, McGraw Hill, New York, 2004. (ISBN: 07828357-4)

R2. Sharma, R. and Mohan, K. Business Correspondence and Report Writing, TMH New Delhi 2002.

R3. Xebec, Presentation Book, TMH New Delhi, 2000. (ISBN 0402213)

Evaluation Pattern

CIA 1 - 10 Marks

Mid Semester Exams - 25 Marks

CIA 2 - 10 Marks

End Semester Exams - 50 Marks

Attendance - 5 marks

MA334 - DISCRETE MATHEMATICS (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

To extend student’s mathematical maturity and ability to deal with abstraction and to introduce most of the basic terminologies used in computer science courses and application of ideas to solve practical problems.

The objective of the paper is to develop:

·  The knowledge of the concepts needed to test the logic of a program.

·    Knowledge which has application in expert system, in data base and a basic for the programing language.

·    An understanding in identifying patterns on many levels.

·    Awareness about a class of functions which transform a finite set into another finite set that relates to input output functions in computer science.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1

Checking  the  consistency of system of linear equations and solving by Gauss Jordan and Gauss Elimination methods, finding the spectral matrix with the aid of eigen values and eigen vector

L3

2

Finding the differentiation of multivariable functions using the concept of total derivatives, Jacobian,  evaluating definite integrals by Leibnitz rule of differentiation under integral sign

L4

3

Evaluating the definite integrals as surface area and volume of solid of revolution by   tracing the curves and using reduction formulae

L4

4

Solving first order nonlinear differential equations by reducing into homogenous, linear and exact forms

L3

5

Finding the velocity and acceleration of a moving particle, vector potential, scalar potential

L3

Unit-1
Teaching Hours:9
Propositional Calculus:
 

Propositions Logical connectives Compound propositions Conditional and bi conditional propositions Truth tables Tautologies and contradictions Contrapositive Logical equivalences and implications De Morgans Laws - Normal forms Principal conjunctive and disjunctive normal forms Rules of inference Arguments - Validity of arguments.

Unit-2
Teaching Hours:9
Predicate Calculus:
 

Predicates Statement Function Variables Free and bound variables Quantifiers Universe of discourse Logical equivalences and implications for quantified statements Theory of inference The rules of universal specification and generalization Validity of arguments

Unit-3
Teaching Hours:9
Set Theory
 

Basic concepts Notations Subset Algebra of sets The power set Ordered pairs and Cartesian product Relations on sets Types of relations and their properties Matrix and Graph representation of a relation Partial ordering Poset Hasse diagram Lattices and their properties Sublattices Boolean algebra.

Unit-4
Teaching Hours:9
Functions:
 

Definitions of functions Classification of functions Types of functions - Examples Composition of functions Inverse functions Characteristic function of a set Hashing functions Permutation functions.

Unit-5
Teaching Hours:9
Groups:
 

Groups - Properties Subgroups - Cosets and Lagranges theorem Normal subgroups Algebraic system with two binary operations Preliminaries of Coding - Hamming Metric - group codes: Basic notions of error correction - Error recovery in group codes.

Text Books And Reference Books:

Text Books

T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. 

T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009.

Essential Reading / Recommended Reading

Reference Books 

1.      R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures,  Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003.

2.      R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003.

3.      R3. .Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002.

4.      R4. Dr K.S.C , Discrete Mathematical Structures, 5th Edition, Prism Engineering Education Series2018.

5.      R5. S Santha, Discrete Mathematics with Combinatorics and Graph Theory  Cengage, 1st Edition, 2019

Evaluation Pattern

Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks)

End Semester Examination(ESE)      : 50% (50 marks out of 100 marks) 

 

 

S.No

Assessment

Marks

Weightagemarks

1

CIA I

20

10

2

CIA II

     (MSE: Mid Semester Examination)

50

25

3

CIA III

20

10

4

Attendance

10

05

5

ESE

(End Semester Examination)

100

50

Total

100

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:

  • 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.

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

MC321 - CYBER SECURITY (2019 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:0

Course Objectives/Course Description

 

This 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

Learning Outcome

 

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1.

Summarize the network security concepts and cyber laws

L2

2.

Explain different cyber attacks with relevant examples

L2

3.

Illustrate risk management process handled in the organization with business continuity planning

L2

4.

Outline the vulnerabilities that affect the organizational network

L2

5.

Identify cryptography algorithms for authentication purposes in the organizational network

L3

Unit-1
Teaching Hours:6
Security Fundamentals
 

Security Fundamentals-4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security.

Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber- Security Initiative CNCI – Legalities.

Unit-2
Teaching Hours:6
Cyber Attack and Cyber Services
 

 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 Hardening-TCP/IP attack- SYN Flood. 

Unit-3
Teaching Hours:6
Cyber Security Management
 

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 - Disaster Types - Disaster Recovery Plan - Business Continuity Planning Process.

Unit-4
Teaching Hours:6
Vulnerability - Assessment and Tools
 

Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box Architectural Integration: Security Zones - Devices viz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security

Unit-5
Teaching Hours:6
Authentication and Cryptography
 

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 Analysis. Cyber Evolution: Cyber Organization - Cyber Future 

Text Books And Reference Books:

  

1.      Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, Cyber Security Policy Guidebook, Wiley; 1 edition , 2012,    ISBN-10: 1118027809 

2.      Dan Shoemaker and Wm. Arthur Conklin, Cybersecurity: The Essential Body Of Knowledge,   Delmar Cengage Learning; 1 edition (May 17, 2011) ,ISBN-10: 1435481690

Essential Reading / Recommended Reading

     

1.      Matt Bishop, “Computer Security Art and Science”, Pearson/PHI, 2009.

2.      Stuart Mc Clure, Joel Scrambray, George Kurtz, “Hacking Exposed”, 7th Edition Tata McGraw-Hill, 2012.

3.      Jason Andress, The Basics of Information Security: Understanding the Fundamentals of InfoSec in Theory and Practice, Syngress; 1 edition (June 24, 2011) ,  ISBN-10: 1597496537

4.      Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 3rd Edition 2002.

5.      Bruce, Schneier, “Applied Cryptography”, 2nd Edition, Toha Wiley & Sons, 2007.

6.      Man Young Rhee, “Internet Security”, Wiley, 2003.

7.      Pfleeger & Pfleeger, “Security in Computing”, Pearson Education, 3rd Edition, 2003.   

Evaluation Pattern

 Continuous Internal Assessment (CIA) for theory papers : 100% (50 marks out of 50 marks)

 

MIMBA331 - PRINCIPLES OF MANAGEMENT (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:6
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course Description: This is offered as a core course in first trimester. This course will provide a general introduction to management principles and theories, and a brief outline on history and development of management thought. 

Course Objectives : This course describes the steps necessary to understand an organisation that are aligned with business objectives and provides an insight to address a range of challenges that every manager encounters. It aims to prepare students for an exciting challenging and rewarding managerial career through case studies on Global Perspective.

Learning Outcome

Course Learning Outcomes: On having completed this course student should be able to:

CLO1   Understand different management approaches 

CLO2   Demonstrate planning techniques

CLO3   Able to work in dynamic teams within organizations 

CLO4   Analyze different processes in staffing and controlling

Unit-1
Teaching Hours:12
Unit 1. Nature, Purpose and Evolution of Management Thought
 

Meaning; Scope; Managerial levels and skills; Managerial Roles; Management: Science, Art or Profession; Universality of Management.

Ancient roots of management theory; Classical schools of management thought; Behavioral School, Quantitative School; Systems Approach, Contingency Approach; Contemporary Management thinkers & their contribution. Ancient Indian Management systems & practices. Comparative study of global management systems & practices. 

 

Evolution of Management: Teaching management through Indian Mythology (Videos of Devdutt Pattanaik, Self-learning mode)

Unit-2
Teaching Hours:12
Unit 2. Planning
 

Types of Plans; Steps in Planning Process; Strategies, level of Strategies, Policies and Planning; Decision making, Process of Decision Making, Techniques in Decision Making, Forecasting & Management by Objectives (MBO).

 

Planning: HBS Case and Projects of Events

Unit-3
Teaching Hours:12
UnitUnit 3. Organizing
 

Organizational structure and design; types of organizational structures; Span of control, authority, delegation, decentralization and reengineering. Social responsibility of managers, Managerial Ethics.

 

Organizing: Holacracy form of organization structure, HBS Case

Unit-4
Teaching Hours:12
Unit 4. Staffing
 

Human resource planning, Recruitment, selection, training & development, performance appraisal, managing change, compensation and employee welfare.

Motivation: Concept, Forms of employee motivation, Need for motivation, Theories of motivation, Stress Management

Staffing: Stress Management & Career path, HBS Case

Unit-5
Teaching Hours:12
Unit 5. Leading and Controlling
 

Leadership concept, leadership Styles, leadership theories, leadership communication.

Nature of organizational control; control process; Methods and techniques of control; Designing control systems, Quality Management

 Leading: Article on Styles of leadership by Daniel Goleman

Controlling: HBS Case and Projects of Events

Text Books And Reference Books:

Text Books:

T1. Heinz Weihrich, Mark V Cannice & Harold Koontz (2019). Management (15th Edition). McGraw Hill Publications.

Essential Reading / Recommended Reading

Reference Books:

R1. Daft, R. L. (2016). The new era of management (11th Edition). Cengage Publications.

R2. Prasad, L.M., Principles and practices of management. New Delhi: Sultan Chand & Sons.   

Evaluation Pattern

Test & Exam

 

Max Marks

Weightage

Total

CIA – I

20

10

20%

10

CIA – II

50

25

25%

25

CIA – III

20

10

10%

10

Attendance

5

5%

5

CIA – I, II, and III

 

50

50%

50

End – term

100

50

50%

50

Total

100

MIPSY331 - UNDERSTANDING HUMAN BEHAVIOR (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course focuses on the fundamentals of psychology. It is an introductory paper that gives an overall understanding about the human behavior. It will provide students with an introduction to the key concepts, perspectives, theories, and sub-fields on various basic processes underlying human behavior.

 Objectives

  1. To understand the fundamental processes underlying human behavior
  2. To become aware of one’s idiosyncrasies and predispositions
  3. To apply the understanding of concepts in day-to-day activities

Learning Outcome

After the completion of this course students will be able to:

  1. Explain human behaviors using theoretical underpinnings
  2. Understand oneself and others, respecting the differences
  3. Demonstrate their understanding of psychological processes in daily activities. 

Unit-1
Teaching Hours:12
SENSATION
 

Definition, Characteristics of Sensory modalities: Absolute and difference threshold; Signal detection theory; sensory coding; Vision, Audition, Other Senses. Assessment of Perception and Sensation

Unit-2
Teaching Hours:12
PERCEPTION
 

Definition, Understanding perception, Gestalt laws of organization, Illusions and Perceptual constancy; Various sensory modalities; Extrasensory perception.

Practicum:  Muller-Lyer Illusion

Unit-3
Teaching Hours:12
LEARNING
 

Learning:Definition, Classical conditioning, Instrumental conditioning, learning and cognition; 

Unit-3
Teaching Hours:12
MEMORY
 

Types of Memory; Sensory memory, working memory, Long term memory, implicit memory, Constructive memory, improving memory; Assessment of memory.

Practicum: Memory drum

Unit-4
Teaching Hours:12
INDIVIDUAL DIFFERENCES
 

Concepts and nature of Individual differences; Nature vs. nurture; Gender difference in cognitive processes and social behavior; 

Unit-4
Teaching Hours:12
INTELLIGENCE
 

Definition, Contemporary theories of intelligence; Tests of intelligence; Emotional, Social and Spiritual intelligence.

Practicum: Bhatia’s Battery of Performance

Unit-5
Teaching Hours:12
PERSONALITY
 

Definition, Type and trait theories of personality, Type A, B & C. Psychoanalytic -  Freudian perspective; Types of personality assessment.

Practicum: NEO-FFI 3

Text Books And Reference Books:

Baron, R. A. (2001). Psychology. New Delhi: Pearson Education India.

Rathus, S. A. (2017). Introductory Psychology, 5thEd. Belmont, CA: Wadsworth.

Nolen-Hoeksema, S., Fredrickson, B.L. & Loftus, G.R. (2014). Atkinson & Hilgard'sIntroduction to Psychology.16th Ed. United Kingdom: Cengage Learning.

Essential Reading / Recommended Reading

Feldman, R. S. (2011). Understanding Psychology. New Delhi: Tata McGraw Hill.

Morgan, C. T., King, R. A., & Schopler, J. (2004). Introduction to Psychology. New Delhi: Tata     McGraw Hill.

Kalat, J. W. (2016). Understanding Psychology. New York: Cengage Learning.

Evaluation Pattern

Group Assignment

Individual Assignment

Mid semester

20

20

25

 

Mid Semester Examination

Section A

(Definition)

Section B

(Short note)

Section C

(Essay)

Section D

(Case Question)

Total

5×2=10

4×5=20

1×10=10

1×10=10

50

 

End Semester Examination

Section A

(Definition)

Section B

(Short note)

Section C

(Essay)

Section D

(Case Question)

Total

5×2=10

4×5=20

1×10=10

1×10=10

50

 

BS451 - BIO SCIENCE LABORATORY (2019 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:1

Course Objectives/Course Description

 

 

 

 

 

Learning Outcome

Course outcomes:

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

● Examine the applications of bioengineering and using common tool boxes for

analysing medical information.

Unit-1
Teaching Hours:30
list of experiments
 

1. Blood Pressure Measurement using Arduino 

2. To determine the R peaks in given ECG and to find HRV using Matlab.

3. To familiarize with the fundamentals of image processing in Matlab using simple tools and functions.

4. To determine the presence of fractures in the given X-ray file using simple Matlab image processing

5. To determine the presence of fractures in the given X-ray file using simple Matlab image processing toolbox.

6. Introduction to Tinkercad and using the various tools available for running a simple program of

lighting a LED bulb using Arduino (digital).

7. To design a temperature sensor in Tinkercad using Arduino and TMP36..

8. To design and simulate muscle contraction using potentiometers, Arduino and servo motors.

9. To design and simulate measuring pulse sensors using photodiodes, IR LED and Arduino.

10. Preparation of biopolymers (polylactic acid) at home using home-based ingredients.

Text Books And Reference Books:

NA

Essential Reading / Recommended Reading

NA

Evaluation Pattern

As per the university criteria

CS431 - PROBABILITY AND QUEUING THEORY (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

At the end of the course, the students would have a fundamental knowledge of the basic probability concepts. Have a well – founded knowledge of standard distributions which can describe real life phenomena. Acquire skills in handling situations involving more than one random variable and functions of random variables. Understand and characterize phenomena which evolve with respect to time in a probabilistic manner. Be exposed to basic characteristic features of a queuing system and acquire skills in analyzing queuing models.

Learning Outcome

CO1: Explain the basic perceptions of probability of an event and associated random variables.

CO2: Compare and contrast various standard distributions with suitable statistical analysis.

CO3: Apply and solve two dimensional random variable problems through joint distributions and central limit theorem.

CO4: Analyze probabilistic environment using random process and markov chain techniques.

CO5: Build and implement queuing model associated to stochastic process.

Unit-1
Teaching Hours:9
PROBABILITY AND RANDOM VARIABLE
 

Axioms of probability - Conditional probability - Total probability – Baye’s theorem Random variable - Probability mass function - Probability density function  - Properties – Moments - Moment generating functions and their properties.

Unit-2
Teaching Hours:9
STANDARD DISTRIBUTIONS
 

Binomial, Poisson, Geometric, Negative Binomial, Uniform, Exponential,Gamma,

Weibull and Normal distributions and their properties - Functions of a random variable.

Unit-3
Teaching Hours:9
TWO DIMENSIONAL RANDOM VARIABLES
 

Joint distributions - Marginal and conditional distributions – Covariance Correlation and regression - Transformation of random variables - Central limit theorem.

Unit-4
Teaching Hours:9
RANDOM PROCESSES AND MARKOV CHAINS
 

Classification - Stationary process - Markov process - Poisson process - Birth and death process - Markov chains - Transition probabilities - Limiting distributions. Transition Diagram.

Unit-5
Teaching Hours:9
QUEUING THEORY
 

Markovian models – M/M/1, M/M/C, finite and infinite capacity - M/M/∞ queues - Finite source model -  M/G/1 queue (steady state solutions only) – Pollaczek – Khintchine formula – Special cases.Single and Multiple Server System.

Text Books And Reference Books:

1.      Ross, S., “A first course in probability”,Sixth Edition, Pearson Education, Delhi, 2002.

2.      Medhi J., “Stochastic Processes”, New Age Publishers, New Delhi, 1994. (Chapters 2, 3,4)

3.      T.Veerarajan, “Probability, Statistics and Random process”, Second  Edition, Tata McGraw Hill, New Delhi,  2003

Essential Reading / Recommended Reading

1.      Allen A.O., “Probability, Statistics and Queuing Theory”, Academic press, New Delhi, 1981.

2.      Taha H. A., “Operations Research-An Introduction”,Seventh Edition, Pearson Education Edition Asia, Delhi, 2002.

3.      Gross, D. and Harris, C.M., “Fundamentals of Queuing theory”, John Wiley.

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

CS432P - OPERATING SYSTEMS (2019 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Objectives of this course is to have an overview of different types of operating systems. They also include an understanding of the components of an operating system; To develop knowledge of process management and have a thorough knowledge of storage management; To know the concepts of I/O and file systems.

 

Learning Outcome

CO1: Demonstrate the Structure, Components and its basic functionalities of Operating System

CO2: Distinguish various process management principles for given problem using appropriate tool

CO3: Elucidate the process synchronization mechanisms, deadlock environment and its solutions in the given processes

CO4: Inspect various memory management strategies for the given problems in memory systems

CO5: Build file structure to distribute the same across the memory.

Unit-1
Teaching Hours:9
INTRODUCTION
 

Introduction : What operating systems do, Computer System Architecture, Operating System Structure, Operating System Operations, Process Management, Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls

Unit-2
Teaching Hours:9
PROCESS MANAGEMENT
 

Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling

Unit-3
Teaching Hours:9
PROCESS SYNCHRONIZATION AND DEADLOCKS
 

Process Synchronization: Background, The Critical Section Problem, Petersons Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples, Deadlocks 

Unit-4
Teaching Hours:9
MEMORY MANAGEMENT AND VIRTUAL MEMORY
 

Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging,

Virtual Memory: Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory

 

Unit-5
Teaching Hours:9
FILE SYSTEM INTERFACE AND FILE SYSTEM IMPLEMENTATION & MASS STORAGE STRUCTURE
 

File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection;

File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management

Text Books And Reference Books:

1.  Abraham Silberschatz, Peter Baer Galvin and Greg Gagne, “Operating System Concepts”, Ninth Edition, John Wiley & Sons (ASIA) Pvt. Ltd, 2013.

Essential Reading / Recommended Reading

1.      Harvey M. Deitel, “Operating Systems”, Third Edition, Pearson Education Pvt. Ltd, 2007.

2.      Andrew S. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India Pvt. Ltd, 2009.

3.      William Stallings, “Operating System”, Pearson Education 2009

4.      Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts and Practice”, PHI, 2010.

Evaluation Pattern

COURSES WITH THEORY AND PRACTICAL

 

Component

Assessed for

Minimum marks

 to pass

Maximum

marks

1

Theory CIA

30

-

30

2

Theory ESE

30

12

30

3

Practical CIA

35

14

35

4

Attendance

05

-

05

4

Aggregate

100

40

100

 

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY

PRACTICAL

 

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

1

CIA-1

20

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50

10

-

10

 

 

 

3

CIA-3

20

10

-

10

 

 

 

4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100

30

12

30

ESE

NA

NA

-

-

 

 

TOTAL

65

-

65

TOTAL

 

35

14

35

CS433P - PROGRAMMING PARADIGM (2019 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Software development in business environment has become more sophisticated, the software implementation is becoming increasingly complex and requires the best programming paradigm which helps to eliminate complexity of large projects. Object Oriented Programming (OOP) has become the predominant technique for writing software at present. Many other important software development techniques are based upon the fundamental ideas captured by object-oriented programming. The course also caters to the understanding of event driven programming, generic programming and concurrent programming. By the end of this COURSE, the student should acquire the basic knowledge and skills necessary to implement the concepts of various programming paradigms.

Learning Outcome

CO1:   Demonstrate the fundamental concepts of Object Oriented Programming.(L2)

CO2:   Make use of the inheritance and interface concepts for effective code reuse.(L3)

CO3:   Inspect dynamic and interactive graphical applications using AWT and SWING.(L4)

CO4:   Build an application using generic programming and exception handling concepts.(L6)

CO5:   Assess and design concurrent and parallel applications using multithreaded concepts.(L5)

Unit-1
Teaching Hours:9
OBJECT-ORIENTED PROGRAMMING - FUNDAMENTALS
 

Review of OOP - Objects and classes in Java – defining classes – methods - access specifiers – static members – constructors – finalize method – Arrays – Strings - Packages – JavaDoc comments. 

Unit-2
Teaching Hours:9
OBJECT-ORIENTED PROGRAMMING - INHERITANCE
 

Inheritance – class hierarchy – polymorphism – dynamic binding – final keyword – abstract classes – the Object class – Reflection – interfaces – object cloning – inner classes.

Unit-3
Teaching Hours:9
EVENT-DRIVEN PROGRAMMING
 

Graphics programming – Frame – Components – working with 2D shapes – Using color, fonts, and images - Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View- Controller design pattern – buttons – layout management – Swing Components

Unit-4
Teaching Hours:9
GENERIC PROGRAMMING
 

Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – exceptions – exception hierarchy – throwing and catching exceptions.

Unit-5
Teaching Hours:9
CONCURRENT PROGRAMMING
 

Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – thread-safe Collections – Executors – synchronizers – threads and event-driven programming, Parallel programming –fork, join framework.

Text Books And Reference Books:

1.              Herbert Schildt, “Java The Complete Reference” , Ninth Edition, McGraw Hill Publishers 2014.

2.              Cay S. Horstmann and Gary Cornell, “Core Java: Volume I – undamentals”, Eighth Edition, Sun Microsystems Press, 2008.

Essential Reading / Recommended Reading

1.              Paul Deitel and Harvey Deitel , “Java How to program”, Tenth Edition, Deitel, 2016.

2.             Ivan BratikoPROLOG: Programming for Artificial Intelligence, Third Edition, Pearson Publisher, 2002.

3.            Bruce Eckel, “Thinking in Java”, 4th Edition, February 20, 2006.

4.          Doug Rosenberg, Matt Stephens, “Use Case Driven Object Modeling with UML: Theory and Practice (Expert's Voice in UML Modeling)”, January 16, 2013.

Evaluation Pattern

COURSES WITH THEORY AND PRACTICAL

 

Component

Assessed for

Minimum marks

 to pass

Maximum

marks

1

Theory CIA

30

-

30

2

Theory ESE

30

12

30

3

Practical CIA

35

14

35

4

Attendance

05

-

05

4

Aggregate

100

40

100

 

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY

PRACTICAL

 

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

1

CIA-1

20

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50

10

-

10

 

 

 

3

CIA-3

20

10

-

10

 

 

 

4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100

30

12

30

ESE

NA

NA

-

-

 

 

TOTAL

65

-

65

TOTAL

 

35

14

35

CS434 - FORMAL LANGUAGE AND AUTOMATA THEORY (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

To have an understanding of finite state and pushdown automata.

To have a knowledge of regular languages and context free languages.

To know the relation between regular language, context free language and corresponding recognizers.

To study the Turing machine and classes of problems.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1.

Design finite automata with conversion between types of finite automata.

L2

2.

Develop regular expression and minimize the given finite automata for any regular language.

L3

3.

Develop context free grammar, parse trees and pushdown automata for a given context free language.

L3

4.

Experiment with CFLs and design of Turing machine for a given language.

L3

5.

Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis.

L2

Unit-1
Teaching Hours:8
Automaton
 

Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions.

Unit-2
Teaching Hours:10
Regular Expressions and Languages
 

Regular Expression  – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata.

Unit-3
Teaching Hours:10
Context-Free Grammar and Languages
 

Context-Free Grammar (CFG) – Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata – Equivalence of Pushdown automata and CFG, Deterministic Pushdown Automata.

Unit-4
Teaching Hours:9
Properties of Context-Free Languages
 

Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Programming Techniques for TM.

Unit-5
Teaching Hours:8
Undecidability
 

A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP.

Text Books And Reference Books:

1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 200

Essential Reading / Recommended Reading

R1. H.R. Lewis and C.H. Papadimitrou, “Elements of the Theory of Computation”, Second Edition, Pearson Education/PHI, 2003

R2. J.Martin, “Introduction to Languages and the Theory of Computation”, Third Edition, TMH,       2003.

R3. Michael Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 1997. 

Evaluation Pattern

Assessment of each paper 

  • Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) 
  • End Semester Examination(ESE): 50% (50 marks out of 100 marks)

 Components of the CIA

  • CIA I: Quiz and Assignment                          : 10 marks
  • CIA II: Mid Semester Examination (Theory) : 25 marks
  • CIA III: Closed Book Test and  Assignment  : 10 marks
  • Attendance                                                           : 05 marks

Sl No

CIA Component

Unit(s) Covered

CO

RBT Level

1

CIA 1 Assignment

1

CO 1

2

2

CIA 1 Test

2

CO 2

2

3

MSE

1,2,3

CO 1, CO 2, CO3

3

4

CIA 3 Test

4

CO 4

2

5

CIA 3 Assignment

5

CO 5

2

CS435P - COMPUTER ORGANIZATION AND ARCHITECTURE (2019 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course will help the students to learn about basic structure of computer system, design of arithmetic and logic unit with the implementation of fixed and floating point numbers. Further, it will give knowledge about design of control unit and pipelined processing concepts. It discusses about various parallel processing architectures, different memory systems and I/O Communication systems

Learning Outcome

CO1: Demonstrate the functions of basic components of computer system and Instruction set Architecture

CO2: Identify suitable control unit design and pipelining principles in computer architecture design

CO3: Utilize appropriate instruction level parallelism concepts in multiprocessing environment

CO4: Select suitable arithmetic algorithm to solve given arithmetic and logical problems

CO5: Choose suitable memory and I/O system design

Unit-1
Teaching Hours:9
FUNDAMENTALS OF COMPUTER SYSTEM
 

Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.

 

Unit-2
Teaching Hours:9
COMPUTER ARTHIMETIC
 

Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism

 

Unit-3
Teaching Hours:9
BASIC PROCESSING AND CONTROL UNIT
 

A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined datapath and control – Handling Data Hazards & Control Hazards – Exceptions.

 

Unit-4
Teaching Hours:9
PARALLELISM
 

Parallel processing challenges – Flynn‘s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.

 

Unit-5
Teaching Hours:9
MEMORY AND I/O
 

Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‘s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits - USB.

 

Text Books And Reference Books:

T1. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The Hardware/Software Interface”, Fifth Edition, Morgan Kaufmann / Elsevier, 2014.

T2. Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012.

Essential Reading / Recommended Reading

R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, Eighth Edition, Pearson Education, 2010.

R2.  John L. Hennessey and David A. Patterson, “Computer Architecture – A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers, 2012.

Evaluation Pattern

COURSES WITH THEORY AND PRACTICAL

 

Component

Assessed for

Minimum marks

 to pass

Maximum

marks

1

Theory CIA

30

-

30

2

Theory ESE

30

12

30

3

Practical CIA

35

14

35

4

Attendance

05

-

05

4

Aggregate

100

40

100

 

DETAIL OF MARK FOR COURSES WITH THOERY AND PRACTICAL

THEORY

PRACTICAL

 

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

Component

Assessed for

Scaled down to

Minimum marks to pass

Maximum marks

1

CIA-1

20

10

-

10

Overall CIA

50

35

14

35

2

CIA-2

50

10

-

10

 

 

 

3

CIA-3

20

10

-

10

 

 

 

4

Attendance

05

05

-

05

Attendance

NA

NA

-

-

5

ESE

100

30

12

30

ESE

NA

NA

-

-

 

 

TOTAL

65

-

65

TOTAL

 

35

14

35

CS436 - PROFESSIONAL ETHICS (2019 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

Able to understand the importance of Values and Ethics in their personal and professional lives.

Able to learn the rights and responsibilities as an employee, team member and a global citizen.

Learning Outcome

CO1:  Describe the values of Ethics in our lives.

CO2: Illustrate the professional Ethical theories

CO3 Discuss the ethics in working place.

CO4: Investigate the need of ethics as global issue.

CO5: Summarize professional ethics, professional rights , responsibilitiesof an engineer.

Unit-1
Teaching Hours:9
Introduction to Professional Ethics
 

Basic Concepts, Governing Ethics, Personal & Professional Ethics, Ethical Dilemmas, Life Skills, Emotional Intelligence, Thoughts of Ethics, Value Education, Dimensions of Ethics, Profession and professionalism, Professional Associations, Professional Risks, Professional Accountabilities, Professional Success, Ethics and Profession.

Unit-2
Teaching Hours:9
Ethical Theories
 

Ethical Theories: Basic Ethical Principles, Moral Developments, Deontology, Utilitarianism, Virtue Theory, Rights Theory, Casuist Theory, Moral Absolution, Moral Rationalism, Moral Pluralism, Ethical Egoism, Feminist Consequentialism, Moral Issues, Moral Dilemmas, Moral Autonomy.

Unit-3
Teaching Hours:9
Ethics in Engineering profession
 

Professions and Norms of Professional Conduct, Norms of Professional Conduct vs. Profession; Responsibilities, Obligations and Moral Values in Professional Ethics, Professional codes of ethics, the limits of predictability and responsibilities of the engineering profession. Central Responsibilities of Engineers – The Centrality of Responsibilities of Professional Ethics; lessons from 1979 American Airlines DC-10 Crash and Kansas City Hyatt Regency Walk away Collapse.

Unit-4
Teaching Hours:9
Work Place Rights & Responsibilities
 

Ethics in changing domains of Research, Engineers and Managers; Organizational Complaint Procedure, difference of Professional Judgment within the

Nuclear Regulatory Commission (NRC), the Hanford Nuclear Reservation. Ethics in changing domains of research – The US government wide definition of research misconduct, research misconduct distinguished from mistakes and errors, recent history of attention to research misconduct, the emerging emphasis on understanding and fostering responsible conduct, responsible authorship, reviewing & editing.

Unit-5
Teaching Hours:9
Global issues
 

Introduction – Current Scenario, Technology Globalization of MNCs, International Trade, World Summits, Issues, Business Ethics and Corporate Governance, Sustainable Development Ecosystem, Energy Concerns, Ozone Deflection, Pollution, Ethics in Manufacturing and Marketing, Media Ethics; War Ethics; Bio Ethics, Intellectual Property Rights.

Text Books And Reference Books:

T1.       Professional Ethics: R. Subramanian, Oxford University Press, 2015.

T2.       Ethics in Engineering Practice & Research, Caroline Whitbeck, 2e, Cambridge University Press 2015.

Essential Reading / Recommended Reading

R1.Engineering Ethics, Concepts Cases: Charles E Harris Jr., Michael S Pritchard, Michael J Rabins, 4e ,Cengage learning, 2015.

R2. Business Ethics concepts & Cases: Manuel G Velasquez, 6e, PHI, 2008

Evaluation Pattern

Assessment of each paper

Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks)

 End Semester Examination(ESE) : 50% (50 marks out of 100 marks)

Components of the CIA

CIA I   :   Mid Semester Examination (Theory)                       : 25 marks                  

CIA II  :  Assignments                                                              : 10 marks

CIA III            : Quizzes/Seminar/Case Studies/Project Work     : 10 marks

                       Attendance                                                             : 05 marks

                                   Total                                                                   : 50 marks

MC422 - ENVIRONMENTAL SCIENCE (2019 Batch)

Total Teaching Hours for Semester:30
No of Lecture Hours/Week:2
Max Marks:50
Credits:1

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. 

Learning Outcome

CO1. Explain the components and concept of various ecosystems in the environment (L2)

CO2. Explain the necessity of natural resources management (L2)

CO3. Relate the causes and impacts of environmental pollution (L4)

CO4. Relate climate change/global atmospheric changes and adaptation (L4)

CO5. Appraise the role of technology and institutional mechanisms for environmental protection (L5)

Unit-1
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.

Unit-2
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

Unit-3
Teaching Hours:6
Environmental Pollution:
 

  Causes and Impacts – Air pollution, Water pollution, Soil Pollution, Noise Pollution, Marine Pollution, Municipal Solid Wastes, Bio Medical and E-Waste. Solid Waste Management

Unit-4
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

Unit-5
Teaching Hours:6
Environmental Protection-
 

Technology, Modern Tools – GIS & Remote Sensing, Institutional Mechanisms - Environmental Acts & Regulations, Role of government, Legal aspects. Role of Nongovernmental Organizations (NGOs) , Environmental Education & Entrepreneurship

Text Books And Reference Books:

Gopinath, R & Balasubramanya, N (2018), “Environmental Science and Engineering”, CENGAGE.

Benny Joseph (2005), “Environmental Studies”, Tata McGraw – Hill Publishing

Company Limited.

R Rajagopalan, “Environmental Studies – From Crisis to Cure”, Oxford University Press, 2005,

Aloka Debi, “Environmental Science and Engineering”, Universities Press (India)Pvt. Ltd. 2012.

Essential Reading / Recommended Reading

Masters, G & Ela, W.P (2015), Introduction to environmental Engineering and Science, 3rd Edition. Pearson. 

Raman Sivakumar, “Principals of Environmental Science and Engineering”, Second Edition, Cengage learning Singapore, 2005.

P. Meenakshi, “Elements of Environmental Science and Engineering”, Prentice Hall of India Private Limited, New Delhi, 2006.

S.M. Prakash, “Environmental Studies”, Elite Publishers Mangalore, 2007

Erach Bharucha, “Textbook of Environmental Studies”, for UGC, University press, 2005.

Dr. Pratiba Sing, Dr. AnoopSingh and Dr. Piyush Malaviya, “Textbook of Environmental and Ecology”, Acme Learning Pvt. Ltd. New Delhi.

Evaluation Pattern

As per university norms

MIMBA431 - ORGANISATIONAL BEHAVIOUR (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:6
Max Marks:100
Credits:4

Course Objectives/Course Description

 

Course Description: The course is offered as a mandatory core course for all students in Trimester II.  The course introduces students to a comprehensive set of concepts and theories, facts about human behaviour and organizations that have been acquired over the years. The subject focuses on ways and means to improve productivity, minimize absenteeism, increase employee engagement and so on thus, contributing to the overall effectiveness. The basic discipline of the course is behavioral science, sociology, social psychology, anthropology and political science.

Course Objectives: To make sense of human behaviour, use of common sense and intuition is largely inadequate because human behaviour is seldom random. Every human action has an underlying purpose which was aimed at personal or societal interest. Moreover, the uniqueness of each individual provides enough challenges for the managers to predict their best behaviour at any point of time. A systematic study of human behaviour looks at the consistencies, patterns and cause effect relationships which will facilitate understanding it in a reasonable extent. Systematic study replaces the possible biases of intuition that can sabotage the employee morale in organizations.

Learning Outcome

Course Learning Outcomes: On having completed this course student should be able to:

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

CLO1: Determine the individual and group behavior in the workplace. 

CLO2: Assess the concepts of personality, perception and learning in Organizations. 

CLO3: Analyze various job-related attitudes. 

CLO4: Design motivational techniques for job design, employee involvement, incentives, rewards & recognitions. 

CLO5: Manage effective groups and teams in organizations.

 

Unit-1
Teaching Hours:12
Unit-1: Introduction to Organizational Behaviour
 

Historical Development, Behavioural sciences and Organizational behaviour, Meaning, Importance, Basic concepts, methods and tools for understanding behaviour, Challenges and Opportunities, OB model, ethical issues in organizational Behaviour.

Cross-cultural management, managing multicultural teams, communicating across cultures, OB in the digital age.

Unit-2
Teaching Hours:12
Unit-2: Individual Behaviour ? Personality, Perception and Learning
 

Personality:  Foundations of individual behaviour, Personality, Meaning and Importance, Development of personality, Determinants of personality, Theories of personality, Relevance of personality to managers.

Perception: Nature, Importance and Definition of Perception, Factors involved in perception, The Perceptual Process, Perceptual Selectivity and Organization, Applications in Organizations.

Learning: Definition and Importance, Theories of learning, Principles of learning, Shaping as managerial tool.

Unit-3
Teaching Hours:12
Unit-3: Attitudes, Values & Job Satisfaction
 

Attitudes: Sources and types of attitudes, Attitude formation and change, Cognitive Dissonance Theory. Effects of employee attitude, Job related attitudes

Values: meaning, importance, source and types, and applications in organizations.

Job satisfaction: Measuring Job Satisfaction, Causes of Job Satisfaction, impact of satisfied and dissatisfied employees on the workplace.

Unit-4
Teaching Hours:12
Unit-4: Motivation
 

Meaning, process and significance of motivation, Early Theories of motivation: Hierarchy of Needs, Theory X Theory Y, Two Factor theory, McClelland Theory of Needs, Contemporary Theories of Motivation: Goal Setting theory, Self-Efficacy theory, Equity theory/Organizational justice, Expectancy theories, Motivation theories applied in organizations: Job design, employee involvement, rewards and global implications

Unit-5
Teaching Hours:12
Unit-5: Groups & Teams
 

Groups: Meaning, classification and nature of groups, Stages of group development, an alternative model for Temporary Groups with punctuated equilibrium model, Group properties: Roles, Norms, Status, Size and Cohesiveness, Group decision making.

Teams: Meaning of teams, Types of teams, Creating Effective teams, what makes individuals into effective team players, Team development, Team decision making. 

Text Books And Reference Books:

Core Text Books:

T1. Robbins, S P., Judge, T A and Vohra, N (2016).  Organizational Behavior. 16th Edition, Prentice Hall of India.

Essential Reading / Recommended Reading

Rao V S P & V Sudeep 2018, Managing Organisational Behavior, Trinity Press, 3rd edition, New Delhi.

Evaluation Pattern

Test & Exam

Exam conducted for

Marks conversion

Weightage

Total

CIA – I

20

10

20%

10

CIA – II

50

25

25%

25

CIA – III

20

10

10%

10

Attendance

5

5%

5

CIA – I, II, and III

 

50

50%

50

End – term

100

50

50%

50

Total

100

MIPSY431 - PEOPLE THOUGHTS AND SITUATIONS (2019 Batch)

Total Teaching Hours for Semester:60
No of Lecture Hours/Week:4
Max Marks:100
Credits:4

Course Objectives/Course Description

 

The course is an exploration of the prevailing theories and empirical methods that explain about people’s thoughts, feelings and behaviors in a social context. This throws light on cognitive and social factors that influence human behavior, especially in situations populated by others. 

Objectives

  1. To understand different ways of thinking about people and the perception of self in social situations
  2. To comprehend factors of affect related to cognition in a social context
  3. To develop knowledge about the dynamics of person in different situation in a social living

Learning Outcome

At the end of the course students will be able:

  1. To understand the thinking patterns of people and the perception of self in various cultural contexts
  2. To comprehend factors of affect related to cognition in a social context
  3. To inculcate dynamics of person in different situation
  4. To evaluate the person and situation by using psychometric tests

Unit-1
Teaching Hours:12
Introduction to Self
 

Definition, Person perception; Self-concept; Self-presentation; Self-esteem.

Unit-2
Teaching Hours:12
Affect and Cognition
 

Emotions - Positive and negative affect; Thoughts and expressions; Selective attention; Information processing; Memory; Cognitive appraisal; Judgment and Decision Making; Problem Solving.

Practicum: Decision making & Problem Solving scale

 

Unit-3
Teaching Hours:12
The Person in the Situation - I
 

Justifying our actions, Social Relations: Stereotypes; Prejudice: Definition and Types, Sources of Prejudice, Consequences of Prejudice; Strategies to reduce prejudice; Attribution, Attitude and Attitude Change.

Unit-4
Teaching Hours:12
The Person in the Situation - II
 

Aggression: Perspectives, Causes; Prevention and Control of Aggression; Pro-social Behavior.

Practicum: Pro-social behavior scale

Unit-5
Teaching Hours:12
Group Dynamics
 

Nature of Groups; Basic Processes, Group Performance, Group Decision Making; Group Interaction (Facilitation, Loafing)

Practicum: Sociometry

Text Books And Reference Books:

Myers, D.G (2002) Social Psychology,.New York: McGraw Hill Companies.

Baron, Robert A. and Byrne, D. (2001) .Social Psychology 8 th Edition (Reprint).New Delhi:Prentice-Hall of India Pvt Ltd.

Baumeister.R.F. and Bushman,B.J. (2008).Social Psychology and Human nature. Belmont,CA:Thomson Wadsworth

Essential Reading / Recommended Reading

Tuffin, K. (2005). Understanding critical social psychology. London: Sage Publications.

Brehm, S.S. and Kassin, SN. (1996) Social Psychology. Boston : Houghton Mifflin Company.

Crisp, R.J. and Turner, R.N. (2007), Essential Social Psychology. New Delhi: Sage Publications India Pvt., Ltd.

Taylor ,S .E, Peplau, L.A and Sears, D.O. (2006) Social Psychology. New Delhi: Pearson Prentice-Hall of India.

Misra, G., & Dalal, A. K. (2001). Social Psychology in India: Evolution and Emerging Trends. In K. A. Dala, & G. Misra, New Directions in Indian Psychology. New Delhi: Sage.

Evaluation Pattern

CIA Evaluation pattern

Group Assignment

Individual Assignment

Mid semester

20

20

25

 

Mid Semester Examination

Section A

(Definition)

Section B

(Short note)

Section C

(Essay)

Section D

(Case Question)

Total

5×2=10

4×5=20

1×10=10

1×10=10

50

 

End Semester Examination

Section A

(Definition)

Section B

(Short note)

Section C

(Essay)

Section D

(Case Question)

Total

5×2=10

4×5=20

1×10=10

1×10=10

50

CS531 - COMPUTER ORIENTED NUMERICAL ANALYSIS (2018 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 
  • With the present development of computer technology, it is necessary to develop efficient algorithms for solving problems in science, engineering and technology.
  • This course gives a complete procedure for solving different kinds of problems occurring in engineering numerically.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1.

Illustrate the interpretation and convergence criteria of numerical errors in Linear Interpolation techniques

L2

2.

Solve a range of problems numerically based on Interpolation and Approximation.

L3

3.

Plan approximate solutions for Numerical Differentiation and Integration and to validate its effectiveness

L3

4.

Examine the accuracy of Initial Value problems for Ordinary Differential equations.

L4

5.

Evaluate mathematical models for Boundary value problems in ordinary and partial differential equations.

L5

Unit-1
Teaching Hours:9
SOLUTION OF EQUATIONS AND EIGENVALUE PROBLEMS
 

Introduction to Errors and their computations. Linear interpolation methods (method of false position) – Newton’s method, Solution of linear system by Gaussian elimination and Gauss-Jordon methods- Iterative methods: Gauss Jacobi and Gauss-Seidel methods- Inverse of a matrix by Gauss Jordon method – Eigenvalue of a matrix by power method

Unit-2
Teaching Hours:9
INTERPOLATION AND APPROXIMATION
 

Lagrangian Polynomials – Divided differences – Interpolating with a cubic spline – Newton’s forward and backward difference formulas.

Unit-3
Teaching Hours:9
NUMERICAL DIFFERENTIATION AND INTEGRATION
 

Derivatives from difference tables – Divided differences and finite differences –Numerical integration by trapezoidal and Simpson’s 1/3 and 3/8 rules – Romberg’s method – Two and Three point Gaussian quadrature formulas – Double integrals using trapezoidal and Simpson’s rules.    

Unit-4
Teaching Hours:9
INITIAL VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL EQUATIONS
 

 Single step methods: Taylor series method – Euler and modified Euler methods – Fourth order Runge – Kutta method for solving first and second order equations – Multistep methods: Milne’s and Adam’s predictor and corrector methods. 

Unit-5
Teaching Hours:9
BOUNDARY VALUE PROBLEMS IN ORDINARY AND PARTIAL DIFFERENTIAL EQUATIONS
 

Finite difference solution of second order ordinary differential equation – Finite difference solution of one dimensional heat equation by explicit and implicit methods – One dimensional wave equation and two dimensional Laplace and Poisson equations- Case Studies - implement  concepts using python

Text Books And Reference Books:

1. JaanKiusalaas, “Numerical Methods in Engineering with Python”, Cambridge University Press; 3rd Edition, 2013. 

2. P. B. Patil, U. P. Verma , “Numerical Computational Methods” , Alpha Science Intl Ltd.,       Revised Edition  Reprint 2013.

3. J. N. Sharma , “Numerical Methods for Engineers and Scientists”, Alpha Science Intl Ltd., 2nd Edition Reprint 2008.

4. P. Dechaumphai, N. Wansophark , “Numerical Methods in Engineering Theories with MATLAB, Fortran, C and Pascal Programs”, Alpha Science Intl Ltd., 2015. 

5. E. Balagurusamy, “Numerical Methods”, Tata McGraw-Hill Pub. Co. Ltd, Reprint Edition, 2008.

 6. V. Rajaraman “Computer Oriented Numerical Methods”, PHI, 5th Edition.

Essential Reading / Recommended Reading

1. P. Kandasamy, K. Thilagavathy, and K. Gunavathy, “Numerical Methods”, S.Chand Co. Ltd., New Delhi, 2003.

 2. C.F Gerald, and P.O Wheatley, “Applied Numerical Analysis”, 6th Edition, Pearson Education Asia, New Delhi, 2002.

3. Burden, R.L and Faires, T.D., “Numerical Analysis”, 7th Edition, Thomson Asia Pvt. Ltd., Singapore, 2002.

Evaluation Pattern
  • Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks)

Components of the CIA:

CIA I : Assignment and Open Book Test: 10 marks

CIA II : Mid Semester Examination (Theory) : 25 marks

CIAIII: Case study and MCQ Quiz : 10 marks

● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)

  • Attendance : 05 marks

Total : 50 marks

Sl No

CIA Component

Unit(s) Covered

CO

RBT Level

1

CIA – I – Component I

Assignment

UNIT – I, II

1, 2

3

 

 

CIA – I – Component II

Open Book Test

UNIT – I, II

1,2

2

2

CIA – II - MSE

UNIT -I, II & PART OF III

1 TO 3

3

3

CIA – III-Component I

Case Study Implementation

UNIT – REMAINING PART OF III, IV AND V

3, 4, 5

4 & 5

4

CIA III – Component II

MCQ Quiz

Unit IV and V

4,5

2

CS532E01 - FORMAL LANGUAGE AND AUTOMATA THEORY (2018 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

To have an understanding of finite state and pushdown automata.

To have a knowledge of regular languages and context free languages.

To know the relation between regular language, context free language and corresponding recognizers.

To study the Turing machine and classes of problems.

Learning Outcome

Sl NO

DESCRIPTION

REVISED BLOOM’S TAXONOMY (RBT)LEVEL

1.

Design finite automata with conversion between types of finite automata.

L2

2.

Develop regular expression and minimize the given finite automata for any regular language.

L3

3.

Develop context free grammar, parse trees and pushdown automata for a given context free language.

L3

4.

Experiment with CFLs and design of Turing machine for a given language.

L3

5.

Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis.

L2

Unit-1
Teaching Hours:8
Automaton
 

Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions.

Unit-2
Teaching Hours:10
Regular Expressions and Languages
 

Regular Expression  – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata.

Unit-3
Teaching Hours:10
Context-Free Grammar and Languages
 

Context-Free Grammar (CFG) – Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata – Equivalence of Pushdown automata and CFG, Deterministic Pushdown Automata.

Unit-4
Teaching Hours:9
Properties of Context-Free Languages
 

Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Programming Techniques for TM.

Unit-5
Teaching Hours:8
Undecidability
 

A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP.

Text Books And Reference Books:

1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 200

Essential Reading / Recommended Reading

R1. H.R. Lewis and C.H. Papadimitrou, “Elements of the Theory of Computation”, Second Edition, Pearson Education/PHI, 2003

R2. J.Martin, “Introduction to Languages and the Theory of Computation”, Third Edition, TMH,       2003.

R3. Michael Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 1997. 

Evaluation Pattern

Assessment of each paper 

  • Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) 
  • End Semester Examination(ESE): 50% (50 marks out of 100 marks)

 Components of the CIA

  • CIA I: Quiz and Assignment                          : 10 marks
  • CIA II: Mid Semester Examination (Theory) : 25 marks
  • CIA III: Closed Book Test and  Assignment  : 10 marks
  • Attendance                                                           : 05 marks

Sl No

CIA Component

Unit(s) Covered

CO

RBT Level

1

CIA 1 Assignment

1

CO 1

2

2

CIA 1 Test

2

CO 2

2

3

MSE

1,2,3

CO 1, CO 2, CO3

3

4

CIA 3 Test

4

CO 4

2

5

CIA 3 Assignment

5

CO 5

2

CS532E02 - COMPILER DESIGN (2018 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

To have the better understanding of: 

  • Design principles of a Compiler. 
  • Various parsing techniques 
  • Different levels of translation
  • Optimization  and  generation of machine codes

 

 

Learning Outcome

At end of the course, the students will able to 

CO1 - Explain the concepts and different phases of compilation with Compiler Construction Tools.

CO2 - Interpret language tokens using regular expressions and design lexical analyzer for a language.

CO3 - Build top down parsing, bottom up parsing and parse tree representation of the input.

CO4 - Outline intermediate code for the statements during the process of compilation.

CO5 - Experiment the optimization techniques to intermediate code and generate machine code for high level language program.

Unit-1
Teaching Hours:9
INTRODUCTION TO COMPILERS
 

 

Translators-Compilation and Interpretation-Language processors -The Phases of Compiler-Errors encountered in Different Phases-The Grouping of Phases-Compiler Construction Tools - Programming Language basics.

Unit-2
Teaching Hours:9
LEXICAL ANALYSIS
 

 

Need and Role of Lexical Analyzer-Lexical Errors-Expressing Tokens by Regular Expressions- Converting Regular Expression to DFA- Minimization of DFA-Language for Specifying Lexical Analyzers-LEX-Design of Lexical Analyzer for a sample Language.

Unit-3
Teaching Hours:9
SYNTAX ANALYSIS
 

Need and Role of the Parser-Context Free Grammars -Top Down Parsing -General Strategies- Recursive Descent Parser Predictive Parser-LL(1) Parser-Shift Reduce Parser-LR Parser-LR (0)Item- Construction of SLR Parsing Table -Introduction to LALR Parser - Error Handling and Recovery inSyntax Analyzer-YACC-Design of a syntax Analyzer for a Sample Language

Unit-4
Teaching Hours:9
SYNTAX DIRECTED TRANSLATION & RUN TIME ENVIRONMENT
 

Syntax directed Definitions-Construction of Syntax Tree-Bottom-up Evaluation of S-Attribute Definitions- Design of predictive translator - Type Systems-Specification of a simple type checker- Equivalence of Type Expressions-Type Conversions.

 

RUN-TIME ENVIRONMENT: Source Language Issues-Storage Organization-Storage Allocation- Parameter Passing-Symbol Tables-Dynamic Storage Allocation-Storage Allocation in FORTAN.

Unit-5
Teaching Hours:9
CODE OPTIMIZATION AND CODE GENERATION
 

 

Principal Sources of Optimization-DAG- Optimization of Basic Blocks-Global Data Flow Analysis- Efficient Data Flow Algorithms-Issues in Design of a Code Generator - A Simple Code Generator Algorithm.

Text Books And Reference Books:

 

  1. Alfred V Aho, Monica S. Lam, Ravi Sethi and Jeffrey D Ullman, “Compilers – Principles, Techniques and Tools”, 2nd Edition, Pearson Education, 2007

 

Essential Reading / Recommended Reading
  1. Randy Allen, Ken Kennedy, “Optimizing Compilers for Modern Architectures: A Dependence-based Approach”, Morgan Kaufmann Publishers, 2002.
  2. Steven S. Muchnick, “Advanced Compiler Design and Implementation, “Morgan Kaufmann Publishers - Elsevier Science, India, Indian Reprint 2003.
  3. Keith D Cooper and Linda Torczon, “Engineering a Compiler”, Morgan Kaufmann Publishers Elsevier Science, 2004.
Evaluation Pattern

Internal Assessment - 50 Marks

(CIA 1: 10 Marks, CIA 2: 25 Marks, CIA 3: 10 Marks, Attendance: 5 Marks)

End Semester Examination (ESE) - 50 Marks

Total = 100 Marks

Sl No

CIA Component

Unit(s) Covered

CO

RBT Level

1

Closed Book Test

Unit 1 and 2

1, 2

L2

2

Assignment on DFA

Unit 2

2

L2

3

Closed Book Test

Unit 4

4

L3

4

Assignment on Code Optimization

Unit 5

5

L3

CS532E03 - FUZZY LOGIC (2018 Batch)

Total Teaching Hours for Semester:45
No of Lecture Hours/Week:3
Max Marks:100
Credits:3

Course Objectives/Course Description

 

To understand the concepts of:

  • Fuzzy sets
  • Knowledge representation using fuzzy rules
  • Approximate reasoning
  • Fuzzy inference systems, and fuzzy logic control
  • Machine intelligence applications of fuzzy logic.

Learning Outcome

  

  1.  

Demonstrate Fuzzy Set concepts.

L2

  1.  

Construct suitable membership functions for a given problem.

L3

  1.  

Comprehend Fuzzy Logic and Fuzzy Arithmetic concepts.

L2

  1.  

Implement Fuzzy Inference and Approximate Reasoning for real time projects.

L3

  1.  

Develop in a team, Fuzzy Classification and Clustering using any programming tool.

L6

 

Unit-1
Teaching Hours:9
INTRODUCTION
 

Classical Sets and Fuzzy Sets: Background, Uncertainty and Imprecision, Statistics and Random Processes, Uncertainty in Information, Fuzzy Sets and Membership, Chance versus Ambiguity. Classical Sets - Operations on Classical Sets, Properties of Classical (Crisp) Sets, Mapping of Classical Sets to Functions.Fuzzy Sets.

Unit-2
Teaching Hours:9
MEMBERSHIP FUNCTIONS
 

Features of the Membership Function, Standard Forms and Boundaries, Fuzzification, Membership Value Assignments – Intuition, Inference, Rank Ordering, Angular Fuzzy Sets, Neural Networks, Genetic Algorithms, Inductive Reasoning. Fuzzy- To- Crisp Conversions: Lambda- Cuts for Fuzzy Sets, Lambda- Cuts for Fuzzy Relations, Defuzzification Methods. Extension Principle - Crisp Functions, Mapping and Relations, Functions of fuzzy 

Unit-3
Teaching Hours:9
FUZZY ARITHMETIC
 

Fuzzy Numbers, Interval Analysis in Arithmetic, Approximate Methods of Extension - Vertex method, DSW Algorithm, Restricted DSW Algorithm, Comparisons. Fuzzy Vectors. Classical Logic And Fuzzy Logic: Classical Predicate Logic – Tautologies, Contradictions, Equivalence, Exclusive OR and Exclusive NOR.

Unit-4
Teaching Hours:9
FUZZY RULE
 

Based Systems: Natural Language, Linguistic Hedges, Rule- Based Systems - Canonical Rule Forms, Decomposition of Compound Rules, Likelihood and Truth Qualification, Aggregation of Fuzzy Rules, Graphical Techniques of Inference.Fuzzy Decision Making.

Unit-5
Teaching Hours:9
FUZZY CLASSIFICATION
 

Classification by Equivalence Relations - Crisp Relations, Fuzzy Relations. Cluster Analysis, Cluster Validity, c-Means Clustering- Hard c-Means (HCM), Fuzzy c-Means (FCM). Classification Metric, Hardening the Fuzzy c-Partition, Similarity Relations from Clustering.

 

Text Books And Reference Books:

Text Books: 

1. Fuzzy Logic with Engineering Applications by Timothy J. Ross, McGraw- Hill, III Edition

Essential Reading / Recommended Reading

Reference Books:

  1. Guanrong Chen & Trung Tat Pham Introduction to Fuzzy Systems, Chapman & hall /CRC, 2006
  2. Driankov D., Hellendoorn H., Reinfrank M, An Introduction to Fuzzy Control., Narosa Publications ,1993.
  3. Robert Babuska, Fuzzy Modeling for Control, International Series in Intelligent Technologies, Kluwer Academic Publications, 1998
  4.  Ronald R Yager and Dimitar P Filev, Essentials of Fuzzy Modelling &Control., John Wiley & Sons, Inc, 2002.
  5.  J.-S.R.Jang, C.-T.Sun,E.Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997. 
  6.  B.Kosko, Fuzzy Engineering, Prentice Hall, 1997
Evaluation Pattern

Internal Assessment - 50 Marks

(CIA 1: 10 Marks, CIA 2: 25 Marks, CIA 3: 10 Marks, Attendance: 5 Marks)

End Semester Examination (ESE) - 50 Marks

Total = 100 Marks

Sl No

CIA Component

Unit(s) Covered

CO

RBT Level

1

Quiz

Unit 1 and 2

1, 2

L2

3

Problem Solving

Unit 3

3

L2

4

Literature Review

Applications of Fuzzy Rules

4

L3

5

Development  and Implementation

Unit 5

5

L3

CS533P - INTERNET OF THINGS (2018 Batch)

Total Teaching Hours for Semester:75
No of Lecture Hours/Week:5
Max Marks:100
Credits:4

Course Objectives/Course Description

 

This course introduces

[1].  The basic concepts of IoT,

[2].  The functionalities of different types of sensors, actuators and micro controllers.

[3].  Covers the protocols used in different layers and gives insight on programming IoT for different domains.

Learning Outcome