(Course 2018) Course Book · 2 Index Sr. Contents Page No. No. 1 Institute Vision & Mission 3 2...

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G.H. Raisoni College of Engineering & Management, Wagholi, Pune – 412 207

(An Autonomous Institute Affiliated to SPPU, Pune)

Faculty of Engineering

Third Year B.Tech Computer Engineering

(Course 2018)

Course Book

(With effect from June 2018)

Autonomy Coordinator Head of the Department

(Mrs.B.Padmavathi) (Mrs. Poonam Gupta)

1

Department Information

The department of Computer Engineering was started in the year 2006

with Under graduate programme B. E. (computer Engineering) with intake

60 and increased to 120 in the year 2010. Postgraduate Programme M. E.

Computer Engineering was started in the year 2010. In Academic Year

2016-17 we have got autonomy, and currently we have 120 intake for UG

programme B. Tech (Computer Engineering) and 24 intake for M. Tech.

(Computer Engineering). In the year 2013-14, our department has got

permanent affiliation from SPPU for UG intake 60.

Department has all required infrastructure and resources such as well

equipped, state of art laboratories, spacious classrooms, Seminar hall, well

qualified and experienced faculty members most of them are perusing

their PhD from various renowned universities. Our faculty members’ expertise domains are Internet of Things, Vehicular Adhoc Networks,

Network Security, Database, Wireless Sensor Networks, Image Processing

and so on. Various activities such as Workshops, guest lectures, and

seminars are conducted for students to make them aware about current

trends of IT industry. Recently we have organized International conference

SPCN-2017, last academic year National conference ACCNET was also

organized. By now we have received Grant of Rs. 8, 71, 00 /- from SPPU.

We ensure that our students should possess required skill set for better

employability.

2

Index

Sr. Contents Page

No. No.

1 Institute Vision & Mission

3

2 Department Vision & Mission

4

3 List of PEO,PSO, POs

5

4 Course Structure

8

5 Course Structure

12

3

G.H.Raisoni College of Engineering & Management

VISION

To achieve excellent standards of quality education

byKeeping pace with rapidly changing technologies.To

create technical manpower of global standards

withCapabilities of accepting new challenges.

MISSION

Our efforts will be dedicated to impart quality andValue

based education to raise satisfaction level of all stake-

holders. Our strength will be directed to

createcompetent engineers. Our endeavor will be to

provide all support to promote research & development

activities.

4

Department of Computer Engineering

VISION

To produce global standard ethical professionals, innovators, and

entrepreneurs having strong knowledge and urge to learn latest

technologies in the field of computer engineering.

MISSION

The department continuously strives :

• To pursue excellence in all areas of computer engineering and

develop graduates with strong foundations, able to adapt with

rapidly changing technologies through effective Teaching-

Learning Process.

• To develop competent professionals for global market with the

spirit of self-study, team work, innovation and ethics among

them.

• To promote continuous learning, entrepreneurial skills and

research abilities amongst the graduates.

5

Program Educational Objectives (PEOs)

Our Graduates in Computer Engineering will be able to Demonstrate:

• PEO 1: To analyze, design and develop cost effective solutions to

the real life problems by applying the acquired knowledge.

• PEO 2: Adoptability to learn latest technological advancement

and interdisciplinary approaches by engaging in lifelong learning

process.

• PEO 3: Willingness to pursue higher education, entrepreneurship

and research in the field of computer engineering.

• PEO 4: Being responsible towards society, environment, and

ethical responsible team member with interpersonal and

leadership skills.

6

Program Specific Outcomes (PSOs)

At the end of the programme graduates will be able to demonstrate:

• PSO 1: The ability to analyze, design and develop software

systems applying the knowledge acquired in computer core

courses. (Operating system, database, computer network,

computer organization and architecture, software engineering).

• PSO 2: The utilization of skills assimilated in basic Computer

Engineering Courses to build up expertise in advanced areas of

Database, Networking (WSN, VANET, MANET), IoT, Computing

etc.

• PSO 3: Oneself as a global standard computer professional with

good morals, ethics and sensitivity towards mankind and as a

responsible team member.

7

Program Outcomes

PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering

fundamentals, and an engineering specialization for the solution of complex engineering problems.

PO 2: Problem analysis: Identify, formulate, research literature, and analyze complex engineering

problems reaching substantiated conclusions using first principles of mathematics, natural sciences,

and engineering sciences.

PO 3: Design/development of solutions: Design solutions for complex engineering problems and

design system components or processes that meet t h e specified needs with appropriate

consideration for public health and safety, and cultural, societal, and environmental considerations.

PO 4: Conduct investigations of complex problems: Use research-based knowledge and research

methods including design of experiments, analysis and interpretation of data, and synthesis of the

information to provide valid conclusions.

PO 5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern

engineering and IT tools, including prediction and modelling to complex engineering activities, with

an understanding of the limitations.

PO 6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess

societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the

professional engineering practice.

PO 7: Environment and sustainability: Understand the impact of the professional engineering

solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for

sustainable development.

PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and

norms of the engineering practice.

PO 9: Individual and team work: Function effectively as an individual, and as a member or leader in

diverse teams, and in multidisciplinary settings.

PO 10: Communication: Communicate effectively on complex engineering activities with the

engineering community and with t h e society at large, such as, being able to comprehend and write

effective reports and design documentation, make effective presentations, and give and receive

clear instructions.

PO 11: Project management and finance: Demonstrate knowledge and understanding of t h e

engineering and management principles and apply these to one’s own work, as a member and

leader in a team, to manage projects and in multidisciplinary environments.

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PO 12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in

independent and life-long learning in the broadest context of technological change.

Course Structure

TY B.Tech. (TermV &VI)

9

DEPARTMENT OF COMPUTER ENGINEERING

Scheme of TY B.Tech (COMPUTER ENGINEERING)

*TAE will be based on Home Assignment, Seminar, Quiz, Surprise Test, Group Discussion, Debate,

General Behavior, Attentiveness and Attendance

TERM V

Sub. Code

Name of the Course

Teaching Scheme

Credits

Evaluation Scheme

Duration

of Paper

(hrs.)

Theory Practical

Total

Th. Tu. Pr. Total (TAE)

(20)

(CAE)

(20)

ESE

(60) Int. Ext.

BCOL301 Database Management

Systems 4 - - 4 4 20

20 60 - - 100 3

BCOP301 Database Management

Systems - - 2 2 1 -

- - 25 25 50 3

BCOL302 Web Technology 3 1 - 4 4 20 20 60 - - 100 3

BCOP302 Web Technology - - 2 2 1 - - - 25 25 50 3

BCOL303 Theory of Computation 3 1 - 4 4 20 20 60 - - 100 3

BITL301 Computer Networks 4 - - 4 4 20 20 60 - - 100 3

BITP301 Computer Networks - - 2 2 1 - - - 25 - 25 3

BITL302 Software Engineering and

Project Management 4 - - 4 4 20

20 60 - - 100 3

BITP302 Mini Project - - 2 2 1 - - - 25 - 25 3

MBL104

GENERAL PROFICIENCY IV

(Advanced Communication

Skill)

2 - - 2 Audit

Course

- - - - - -- --

Total 20 2 08 30 24 100 100 300 100 50 650 --

10

DEPARTMENT OF COMPUTER ENGINEERING

Scheme of TY B.Tech (COMPUTER ENGINEERING)

TERM VI

Sub. Code Name of the

Course

Teaching Scheme

Credits

Evaluation Scheme Duration

of Paper

Hours Theory Practical

Total

Th. Tu Pr. Total (TAE)

(20)

CAE)

(20)

ESE

(60) Int. Ext.

BCOL304 System Programming 4 - - 4 4 20 20 60 - - 100 3

BCOP304 System Programming - - 2 2 1 - - - 25 25 50 3

BCOL305 Machine Learning 4 - - 4 4 20 20 60 - - 100 3

BCOP305 Machine Learning - - 4 4 2 - - 25 25 50 3

BCOL306

Design & Analysis of

Algorithms 4 - - 4 4 20

20

60 - - 100 3

BCOP306 Design & Analysis of

Algorithms - - 2 2 1 -

- 25 25 50 3

BITL306 Elective I 3 - - 3 3 20 20 60 - - 100 3

BCOL307 Elective II 3 - - 3 3 20 20 60 - - 100 3

XXXLXXX Open Elective 3 - - 3 3 20 20 60 - - 100 3

MBL105

GENERALPROFICIENCY-

V: Employability Skills

Technical Report

Writing

2 - - 2 Audit

Course

- - - - - --

MBL106

General

Proficiency – VI

Research

Methodology

Workshop

2 - 2 Audit

Course - - - - - - --

Total 23 - 8 31 25 120 120 360 75 75 750

11

Elective –I:

BITL306- A Multimedia System

BITL306- B Embedded System& IOT

BITL306-C Wireless Sensor Networks

BITL306- D Mobile Operating System

Elective –II:

BCOL307- A Software Testing & Quality Assurance

BCOL307 - B Distributed Systems

BCOL307 -C Soft Computing

BCOL307 - D Mobile Computing

OPEN ELECTIVES:

S.N. Code Course Name

S.N. Code Course Name

1 BHUL 302

Constitution of India 8

BECL406A Drives & Control

2 BHUL 303 IPR and Patents 9 BCEL 301 Environmental Engineering

3 BHUL 304

Biosystem in Engineering 10 BCEL 311 Integrated Water Resource

Planning AND Management

11

BMEL404 Unconventional Energy Sources 4

BCOL 307D Software Testing& Quality

Assurance

5

BEML 301

Optimization Techniques

12

BMEL 203 Material Engineering 6

BITL 307 Multimedia System

7 BECL 300 Fuzzy Logic

13 BMEL 317 Industrial & Engineering

Management

12

Course Syllabus

TYB.Tech. : TERM - V

13

G.H.Raisoni College of Engineering & Management, Pune

Third Year of Computer Engineering (2018 Course)

BCOL301: DATABASE MANAGEMENT SYSTEMS

Teaching Scheme:

TH: 04 Hours/Week

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Data Structures

Course Objectives: 1. To analyze basic database concepts such as database design and database languages.

2. To give systematic database Design approaches covering conceptual design, logical design and

an overview of physical design.

3. To provide a strong formal foundation in database concepts, technology and practice.

4. To be familiar with the basic issues of transaction processing and concurrency control.

5. To analyze various Database Architectures and Applications.

6. To analyzeadvance databases.

Course Outcomes:

Graduates shall be able to:

1. Explain basic concept of Database Management Systems

2. Design database using normalization techniques

3. Write queries to create and manipulate databases

4. Write procedures using PL / SQL to access and modify databases

5. Examine Atomicity, Consistency, Isolation and Durability of databases

Course Contents

Unit I Introduction 05 Hours

Introduction: Basic concepts, Advantages of a DBMS over file-processing systems, Database System

Applications, View of data, Database Languages, Data Models: Introduction to Hierarchical, Network,

Components and overall structure of DBMS, Database Design and ER Model: Entity, Attributes,

Relationships, Constraints, Keys, Design Process, Entity Relationship Model, ER Diagram, Design Issues,

Extended E-R Features, converting E-R & EER diagram into tables.

Unit II Relational Model 07 Hours

Relational Model: Basic concepts, Attributes and Domains, CODD's Rules, Integrity constraint: Domain,

Referential Integrities.Database Design: Features of Good Relational Designs, Normalization, Atomic

Domains and First Normal Form, Decomposition using Functional Dependencies, Algorithms for

Decomposition, 2NF, 3NF, BCNF, join dependencies and Fifth Normal Form.

Unit III SQL AND PL/SQL 08 Hours

Structured Query Language (SQL), Characteristics and advantages, SQL Data Types and Literals, DDL,

DML, SQL Operators.

Tables: Creating, Modifying, Deleting, Views: Creating, Dropping, Updating using Views, Indexes, Nulls.

SQL DML Queries:SELECT Query and clauses, Set Operations, Predicates and Joins, Set membership,

Tuple Variables, Set comparison, Ordering of Tuples, Aggregate Functions, Nested Queries, Database

Modification using SQL Insert, Update and Delete Queries.

Introduction to PL/SQL:Concept of stored procedure and functions, Cursors, Triggers.

Unit IV Database Transaction and Query Processing 08 Hours

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Introduction: Basic concept of Transaction, Desirable properties of Transaction, Transaction state,

Concept of a schedule.

Serializability: based on recoverability, Serial, Non-serial and Conflict serializable schedules.

Concurrency control: Need,Locking Method, Deadlock, Lock based protocols and time stamp based

protocols. Database Recovery Methods: Deferred and Immediate, Checkpoint, Shadow paging,

Database buffering.

Query Processing: overview, Measures of a query cost, Selection and Join Operations, Evaluation of

Expression. Introduction to query optimization.

Unit V Advances in database technology Parallel and Distributed Databases 08 Hours

Introduction to parallel databases, Parallel Database architectures, Inter-query and Intra-query

parallelism, I/O parallelism, speedup and scale up.

Introduction to distributed databases, comparison of homogeneous and heterogeneous databases,

Distributed transactions, commit protocol.

Unit VI Large Scale Databases 08 Hours

What is NoSql, History of NoSQL, Important characteristics of NoSQL, Types of NoSQL. Comparative

study of SQL and NoSQL. Introduction to MongoDB, Big Data, HADOOP: HDFS, MapReduce, HBase.

Books:

Text:

1. Silberschatz A., Korth H., Sudarshan S., "Database System Concepts", 6th

Edition, McGraw Hill

Publishers, ISBN 0-07-120413-X.

Reference:

1. Connally T., Begg C., "Database Systems", 3rd

Edition, Pearson Education, 2002, ISBN 81-7808-

861-4.

2. Ivan Bayross, ―SQL, PL/SQL: The Programming Language of Oracle, BPB Publication, ISBN- 10:

8176560723; ISBN-13: 978-8176560726.

3. Kevin Roebuck, ―Storing and Managing Big Data - NoSQL, HADOOP and More,Emereopty

Limited, ISBN: 1743045743, 9781743045749.

15


Third Year of Computer Engineering (2018 Course) BCOP301 DATABASE MANAGEMENT SYSTEM

Teaching Scheme:

PR: 04 Hours/Week

Credit

02

Examination Scheme:

Cont. Ass: 25 Marks

Ext. : 25 Marks

Total: 50 Marks

Guidelines for Instructor's Manual

The instructor‘s manual is to be developed as a hands-on resource and reference. The instructor's

manual need to include prologue (about University/program/ institute/ department/foreword/

preface etc), University syllabus, conduction & Assessment guidelines, topics under consideration-

concept, objectives, outcomes.

Guidelines for Student's Lab Journal

The laboratory assignments are to be submitted by student in the form of journal. Journal consists

of prologue, Certificate, table of contents, and handwritten write-up of each assignment (Title,

Objectives, Problem Statement, Outcomes, software & Hardware requirements, Date of

Completion, Assessment grade/marks and assessor's sign, Theory- Concept, conclusion/analysis).

As a conscious effort and little contribution towards Green IT and environment awareness,

attaching printed papers as part of write-ups and program listing to journal may be avoided.

Guidelines for Lab /TW Assessment

Continuous assessment of laboratory work is done based on overall performance and lab

performance of student. Each lab assignment assessment should assign grade/marks based on

parameters with appropriate weightage. Suggested parameters for overall assessment as well as

each lab assignment assessment include- timely completion, performance, innovation, efficiency,

punctuality and neatness.

Guidelines for Laboratory Conduction

The instructor is expected to frame the assignments by understanding the prerequisites,

technological aspects, utility and recent trends related to the topic. The assignment framing policy

need to address the average students and inclusive of an element to attract and promote the

intelligent students. The instructor may set multiple sets of assignments and distribute among

batches of students. It is appreciated if the assignments are based on real world

problems/applications.

Guidelines for Practical Examination

Both internal and external examiners should jointly set problem statements. During practical

assessment, the expert evaluator should give the maximum weightage to the satisfactory

implementation of the problem statement. The supplementary and relevant questions may be

asked at the time of evaluation to test the student‘s for advanced learning, understanding of the

fundamentals, effective and efficient implementation. So encouraging efforts, transparent

evaluation and fair approach of the evaluator will not create any uncertainty or doubt in the minds

of the students. So adhering to these principles will consummate our team efforts to the promising

start of the student's academics.

Course Objectives:---

1. To apply skills to design databases using Entity Relationship diagram.

2. To develop basic, intermediate and advanced Database Programming Skills.

3. To develop basic database administration skills.

16

4. To percept transaction processing.

5. To use advance database programming concept.

Course Outcomes:-

Student shall be able to:

1. Explain basic concept of Database Management Systems

2. Design database using normalization techniques

3. Write queries to create and manipulate databases

4. Write procedures using PL / SQL to access and modify databases

5. Examine Atomicity, Consistency, Isolation and Durability of databases

Sr.No

.

List of Laboratory Assignments

1 Draw E-R diagrams for payroll database.

2 Illustrate the use of constraints on employee schema: NULL, NOT NULL,PRIMARY KEY, UNIQUE,

CHECK, DEFAULT, REFERENCES.

3 Design at least 10 SQL queries for suitable database application using SQL DML Statements:

Insert, Select, Update, Delete with operators, Functions, Set Operators, Clauses.

4 Design and develop SQL DDL statements which demonstrate the use of SQL Objects such as

Table, View, Index, Sequence, Synonym.

5 Aggregate functions in SQL (Count, Sum, Max, Min, Avg), Commit, Rollback and Savepoint

commands.

6 Database security And Privileges: Use GRANT and REVOKE command.

7 Design SQL queries for suitable database application using SQL DML Statements: all types of

Join, Sub-Query.

8 Write a PL/SQL block to calculate the grade of minimum 10 students.

9 Write a PL/SQL block to implement all types of cursors.

10 Write a PL/SQL stored procedure and function.

11 Write a Row level and Statement level database Trigger.

12 Design and Develop MongoDB Queries using CRUD operations.

13 Implement aggregation and indexing with suitable example using MongoDB.

14 Implement MAP Reduce operation with suitable example using MongoDB.

15 Write a program to implement SQL database connectivity with Visual

Basic/JAVA/Perl/Python /Php Implement Database navigation operations (add, delete, edit

etc. ) using ODBC/ OLEDB.

17

G. H. Raisoni College of Engineering & Management, Pune


BCOL302 WEB TECHNOLOGY Teaching Scheme:

TH: 03 Hours/Week

TUT:01 Hours/Week

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite: Data Communication

Course Objectives:

1. To understand the principles and methodologies of web based applications development

process

2. To be familiar with Client Server Architecture

3. To understand current client side and server side web technologies

4. To understand current client side and server side frameworks

5. To understand web services and content management

6. To gain skill and Project based Skills

Course Outcomes:

On completion of the course, student will be able to–

1. Explain basic concepts for web application development

2. Develop static and dynamic web pages

3. Suggest web technologies to develop various web applications

4. Demonstrate connectivity of databases to frontend

5. Explain various advanced design methodologies used in web technologies

Course Contents

Unit I Introduction to Web Technologies 8 Hours

Introduction to Web Technologies: WWW, Protocols, application and development tools, web browser,

The URL, Domain Name System, Web Server, Design and Develop dynamic and static web pages, Web

Design: Web site design principles, planning the site and navigation.

Unit II Introduction to HTML 7 Hours

Introduction to HTML : The development process, Html tags, Adding Graphics to Html Document, List,

Frames, Table tags, Linking Document and simple HTML forms, Web site structure.

Introduction to XML: XML, XML Schema and DTD document definitions, XSLT transformations and

programming, other XML related standards like XHTML, and DOM interface.

Unit III Style sheets 7 Hours

Style sheets : Need for CSS, introduction to CSS, basic syntax and structure, using CSS, background

images, colors and properties, manipulating texts, using fonts, borders and boxes, margins, padding lists,

positioning using CSS.

Unit IV JavaScript 8 Hours

JavaScript : Java Script in Web Pages, Client side scripting, Advantages of JavaScript, Writing

JavaScript in HTML, Develop JavaScript, simple JavaScript, variables, functions, Elements of

Array conditions, loops and repetition

Unit V PHP 8 Hours

PHP : Starting to script on server side, Arrays, function and forms, advance PHP Databases : Basic

command with PHP examples, Connection to server, creating database, selecting a database, listing

18

database, listing table names creating a table, inserting data, altering tables, queries, deleting database,

deleting data and tables.

Unit VI Web Services 7 Hours

Overview, types of WS, difference between SOAP and REST, EJB: types of EJB, benefits, Architecture,

Introduction to Content Management System(CMS) ,Wordpress, Advanced Technology: Spring.

Text Book: 1. BAYROSS IVAN ,”Web Enabled Commercial Application Development Using …”,BPB

Publications,ISBN 978-81-8333-008-4

2. Robin Nixon, “Learning PHP, Mysql and Javascript with JQuery, CSS & HTML5”, O'REILLY, ISBN:

13:978-93-5213-015-3

Reference Books:

1. HOLZNER STEVEN,”The Complete Reference PHP”,TATA McGraw-Hill Professional,ISBN:978-0-07-

022362-2

2. Web Technologies, Black Book, Dreamtech Press

19



BCOP302 Web Technology

Teaching Scheme:

PR: 02 Hours/Week

Credit

01

Examination Scheme:

Int: 25 Marks

Ext: 25 Marks

Total: 50 Marks


The instructor‘s manual is to be developed as a hands-on resource and reference. The

instructor's manual need to include outline (program/ institute/ department/foreword/ preface

etc), conduction & Assessment guidelines, topics under consideration-concept, objectives,

outcomes.


The laboratory assignments are to be submitted by student in the form of journal. Journal

consists of Outline, Certificate, table of contents, and write-up of each assignment (Title,


Completion, Assessment grade/marks and assessor's sign, Theory- Concept/technology/tool in

brief, design, test cases, conclusion/analysis. Program codes with sample output of all

performed assignments are to be submitted as softcopy.

As a conscious effort and little contribution towards Eco Friendly and environment awareness,


Use of Google Class room containing students programs.



assignments performance of student. Each lab assignment assessment will assign grade/marks

based on parameters with appropriate weightage. Suggested parameters for overall

assessment as well as each lab assignment assessment include- timely completion,

performance, innovation, efficient codes, punctuality and neatness.



technological aspects, utility and recent trends related to the topic. The assignment framing

policy need to address the average students and inclusive of an element to attract and promote

the intelligent students. The instructor may set multiple sets of assignments and distribute

among batches of students. It is appreciated if the assignments are based on real world

applications. Encourage students for appropriate use of Hungarian notation, proper indentation

. Use of open source software is to be encouraged. In addition to these, instructor may assign

one real life application in the form of a mini-project based on the concepts learned. Instructor

may also set one assignment or mini-project that is suitable to respective branch beyond the

scope of syllabus.

20





asked at the time of evaluation to test the student‘s for advanced learning, understanding of

the fundamentals, effective and efficient implementation. So encouraging efforts, transparent

evaluation and fair approach of the evaluator will not create any uncertainty or doubt in the

minds of the students. So adhering to these principles will consummate our team efforts to the

promising start of the student's academics.

Course Objectives:

1. To use current client side and server side web technologies

2. To implement communication among the computing nodes using current client side and

server side technologies

3. To design and implement web services with content management

Course Outcomes:


1. Explain basic concepts for web application development

2. Develop static and dynamic web pages

3. Suggest web technologies to develop various web applications

4. Demonstrate connectivity of databases to frontend

5. Explain various advanced design methodologies used in web technologies

Sr.No List of Laboratory Assignments.

1. Design web pages for college containing a description of the courses, departments,

faculties, library etc, use href, list tags.

2. Create class timetable using table tag.

3. Create user Student feedback form (use textbox, text area , checkbox, radio button,

select box etc.)

4. Design a web page of home town with an attractive background color, text color, an

Image, font etc. (use internal CSS)

5. Write a program to design Student registration form for students by using HTML and

CSS.

6. Develop a JavaScript to display today’s date.

7. Develop simple calculator for addition, subtraction, multiplication and division

operation using JavaScript

8. Create HTML Page with JavaScript which takes Integer number as input and tells

whether the number is ODD or EVEN.

9. Use Inline CSS to format your resume that you created.

10. Design and develop web application using PHP and MySQL as a back-end for Customer

21

data with insert, Display operations.

11. Design and develop dynamic web application using PHP and MySQL as a back-end for

Student data with Update, view operations.

22



BCOL303 THEORY OF COMPUTATION

Teaching Scheme:

TH: 03 Hours/Week

TU:01 Hour/Week

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Discrete Structures

Course Objectives:

1. To gain knowledge about basic concepts of theory of computation.

2. To learn the representation, implementation and applications of finite automata

3. To acquire knowledge of regular expressions with their applications.

4. To make students aware about regular languages and context free languages and their

usefulness in finite state machines

5. To understand the concepts and applications of Push Down Automata and Turing

Machines

6. To develop skills to provide solutions to variety of real life applications which involve

finite automata.

Course Outcomes:


1. Explain basics of finite state and automata theory

2. Apply an appropriate technique for finite state problem

3. Compare relationship among machines, languages and grammar

4. Design Push Down Automata and Turing machine

Course Contents

Unit I Formal Language & Automata Basic Concepts 06 Hours

Languages in abstract, Defining languages, Closure:Klenne closure, Symbol /alphabets,

string/word, Importance of Automata Theory. Automata- Formal Definition & Designing Finite

Automata examples, Simplified Notation, Non determinism-Formal Definition & Designing Non

deterministic Finite Automata.

Language Acceptor: Concept, Machine as a language acceptor, example, Finite Automata-

Formal Definition & Designing Finite Automata –basic examples, Simplified Notation.

Unit II Finite automata & regular expressions 09 Hours

Finite automata: DFA, NFA: Definition and description, Transition Function of a DFA and NFA.

Є-NFA: Definition and description,Transition Function of a NFA, Conversion of Є -NFA NFA ,

Conversion of NFA to DFA, Conversion of Є -NFA to DFA (direct method and subset

construction method), Minimization of a DFA. Inter-conversion RE and FA: Construction of FA

equivalent to RE using Arden’s Theorem. Construction of RE equivalent to FA(RE to Є-NFA, Є-

NFA to DFA). FA with output: Moore and Mealy machines -Definition, models, inter conversion.

Regular Expressions and Languages:

Regular expression, regular set, regular expressions, examples and FA. Identity Rules And

23

Algebraic laws for R.E. Regular languages and examples. Pumping lemma for regular languages.

Properties of Regular Languages and FA: Closure and Decision properties, Limitations of FA.

Unit III Regular grammar & context free grammar 06 Hours

Pumping lemma for regular sets- closure properties of regular sets- decision properties for

regular sets, equivalence between regular language and regular grammar. Context – free

languages – parse trees and ambiguity, reduction of CFGS, Chomsky and Griebach normal

forms, Application of CFG: Parser, Markup languages, XML and Document Type Definitions.

Unit IV Push – down Automata 07 Hours

non Determinism – acceptance by two methods and their equivalence, The Language of PDA,

Equivalence of PDA's and CFG- CFG to PDA, conversion of PDA to CFG,CFLs and PDAs- closure

and decision properties of CFLs Deterministic Push Down Automata (DPDA) - Regular language

and DPDA, DPDA and CFL, Non-deterministic Push Down Automata (NPDA).

Unit V Turing machines 12 Hours

The Turing Machine(TM)-Notation, the language of TM, TM and Halting, Extensions to basic TM,

TM and Computers. Techniques for TM Construction, Variants of Turing Machines, The Model

of Linear Bounded Automata , TM & Type 0 grammars, TM‘s Halting Problem.

Post Machine: Introduction to Post Machines, Comparison between FA, PDA, Post Machine and

TM.variants – recursively enumerable (r.e.) set – recursive sets ,TM as computer of function –

decidability and solvability – Halting Problem – reductions – Post correspondence Problem

(PCP) and unsolvability of ambiguity problem of CFGs.

Unit VI Trends and Applications of Automata 04 Hours

Recent trends in Theory of computation, Advanced topics & its Application-Attributed

Grammar, Contextual Grammar, Concurrent Grammar, Formal methods in concurrency, Graph

Grammar, Aspect of Concurrency in Graph Grammar, set theoretic approaches to Graph

Grammar, Graph Grammar for parallel computation

Books:

Text:

1. Introduction Of Automata Theory, Languages and computation- J.E. Hopcroft

,J.D.Ulman, Pearson education.

2. Introduction to the Theory of Computation (2nd ed.), Sipser, Michael, Course

Technology Inc, 2005.

Reference:

1. John Martin, ‘Introduction Of Automata Theory, Languages and computation’ 2. Peter Linz , ‘Introduction to formal languages and automata’,Norasa,2000.

3. Mishra and Chandrashekharan, ‘ Theory Of Computer Science’



BITL301 Computer Networks

Teaching Scheme: Credit Examination Scheme:

24

TH: 04 Hours/Week

TU:---Hour/Week

04 TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Data Communication

Course Objectives:

1. To understand services offered by layers of OSI model

2.To understand various topological network architectures and essential components to design

it.

3.To provide routing and network management techniques

4.To understand various application layer protocols and its applications in client / server.

5.To fathom wireless network and different wireless standards.

6.To explore recent trends in networking.

Course Outcomes: Graduates shall be able to:

1. Describe & classify various protocols, models in network.

2. Discuss & design the network using various routing algorithms.

3. Differentiate & summarize various congestion control & avoidance algorithm.

4. Categorize & explain recent technologies in computer network.

Course Contents

Unit I Introduction to Computer Networks and

Logical Link Medium Access Control

07 Hours

Introduction – Network architecture -Design. Reference models- The OSI Reference Model- The

TCP/IP Reference Model - A Comparison of the OSI and TCP/IP Reference Models

Design Issues, Switching Techniques: Circuit and Packet Switching, Connectionless and

Connection-oriented Services, Virtual Circuit and Datagram Subnets .Autonomous system

Unit II Network Layer-I 07 Hours

Routing Algorithms: Optimality principle, shortest path routing, flooding, Distance Vector

routing, link state routing, hierarchical routing. Network layer services, IP protocol, IPv4,

Problems with IPv4,IPV6,Subnetting, Network layer Protocols: ARP, RARP, ICMP, DHCP, Unicast

Routing Algorithms: RIP, OSPF, BGP

Unit III Transport Layer 08 Hours

UDP : UDP functionality, UDP Header;

TCP : TCP Features, byte-stream, Connection-oriented, TCP Header Format, 2-way, 3-way

Handshake, TCP State Diagram, TCP Sliding Window, Congestion Control Algorithms, Leaky

Bucket, Token Bucket, Congestion Avoidance, TCP Tahoe, Fast Retransmit, Fast Recovery,

Timer Management.

Unit IV Application Layer 07 Hours

Domain Name System (DNS), Naming and Address Schemes, DNS servers, Email: MIME, SMTP

and POP3. Remote login, File Transfer Protocol (FTP), SNMP, DHCP and BOOTP.

World Wide Web, HTTP

Unit V WIRELESS LAN,MAN,WAN 08 Hours

Introduction (Infrastructure and Ad-hoc Networks),Fundamentals of WLAN – technical issues,

25

Network Architecture, IEEE 802.11- physical layer, Mac Layer Mechanism, CSMA/CA, Bluetooth

- Specification, Transport Layer, Middleware Protocol Group,

Bluetooth Profiles of IEEE 802.16 –differences between IEEE 802.11 and 802.16,

Unit VI SENSOR NETWORKS and Protocol 07 Hours

Sensor Node Architecture (hardware components),Sensor Network Architectures (Concept of

sink and source, Topologies, Design Principles)

Routing in MANET : AODV, DSDV, DSR

Routing Protocols for WSNs: Flooding, SPIN, LEACH,PEGASIS, Directed Diffusion, Geographic

Routing

Books:

Text:

1. Andrew S. Tanenbaum, "Computer Networks", PHI, Fifth Edition, ISBN : 978-0132-

126953

2. Behrouz A. Forouzan, TCP/IP Protocol Suite, McGraw Hill Education, ISBN: 978-0-07-

070652-1,

4th Edition.

3. KazemSohraby, Daniel Minoli, TaiebZnati, Wireless Sensor Network”, Wiley, ISBN :978-0-

471-

74300-2.

4. C. K. Toh, Ad Hoc Mobile Wireless Networks Protocols and Systems, Prentice Hall, ISBN:

978-01-

324-42046.

Reference:

1. James F. Kurose and Keith W. Ross, "Computer Networking: A Top-Down Approach

Featuring

the Internet", Pearson Education, 6th Edition, ISBN : 978-02737-68968

2. Holger Karl and Andreas Willig, “Protocols and Architectures for Wireless Sensor

Networks”,

Wiley, ISBN: 0-470-09510-5

3. Feng Zhao and Leonidas J. Guibas, “Wireless Sensor Networks: An Information

Processing

Approach” Morgan Kaufmann, 2004

26



BITP301Computer Networks

Teaching Scheme:

TH: 02 Hours/Week

Credit

01

Examination Scheme:

Cont. Ass: 25 Marks

Ext. : --

Total: 25 Marks







The laboratory assignments are to be submitted by student in the form of journal. Journal consists of

prologue, Certificate, table of contents, and handwritten write-up of each assignment (Title,

Objectives, Problem Statement, Outcomes, software & Hardware requirements, Date of Completion,

Assessment grade/marks and assessor's sign, Theory- Concept, conclusion/analysis).

As a conscious effort and little contribution towards Green IT and environment awareness, attaching

printed papers as part of write-ups and program listing to journal may be avoided.

















implementation of the problem statement. The supplementary and relevant questions may be asked

at the time of evaluation to test the student‘s for advanced learning, understanding of the





Pre-requisite: NA

Course Objectives:

1. To understand services offered by layers of OSI model

2.To understand various topological network architectures and essential components to design it.

3.To provide routing and network management techniques

27

4.To understand various application layer protocols and its applications in client / server.

5.To fathom wireless network and different wireless standards.

6.To explore recent trends in networking.


1. Describe & classify various protocols, models in network.

2. Discuss & design the network using various routing algorithms.

3. Differentiate & summarize various congestion control & avoidance algorithm.

4. Categorize & explain recent technologies in computer network.

Sr.No List of Laboratory Assignments

1 Explore and Study of TCP/IP utilities and Network Commands

a) Ping b) Tracer c) ipconfig / ifconfig d) Netstat

e) Arp f) Whois

2 Using a Network Simulator (e.g. packet tracer) Configure

Sub-netting of a given network

3 Using a Network Simulator (e.g. packet tracer) configure

1 Static Routing 2. RIPv2 routing protocol


1. EIGRP 2.OSPF


RIPv2 and EIGRP on same network.


a. VLAN, Dynamic trunk protocol and spanning tree protocol

7 TCP UDP Socket Programming for Client Server Application


WLAN with static IP addressing and DHCP with MAC security and filters

9 Using Network Simulator 2/ OMNET simulate(Any one)

a. Local Area Network

b. WSN

28



BITL302 Software Engineering& Project Management

Teaching Scheme:

TH: 04 Hours/Week

TU: Nil

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:-

Course Objectives:

1. To learn the life cycle of software development process as per requirements

2. To Study functional & non-functional requirements & analyze requirement’s feasibility basics.

3. To understand design system components & environment to build detail models.

4. To learn writing test cases for maximum coverage & identify errors.

5. Tostudythe various metrics and how it impacts the quality of metrics.

6. This course provides career opportunities in subject area of software requirement, software

design, and software testing quality management,Configuration management.

Course Outcomes:


1. Describe & adapt the life cycle of software development process.

2. List requirements & prepare SRS document for a given problem.

3. Apply various modelling techniques to design a system

4. Demonstrate various testing strategies.

5. Apply appropriate cost estimation techniques for the development of software.

Course Contents


An Introduction to Software Engineering, Software Myths, Software Engineering- A Layered

Technology, Software Process Framework, Software Process Models, The Waterfall Model,

Incremental Process Models, Evolutionary Process Models, Specialized Process Models, The Unified

Process Model, Agile Process Models.

Unit II Software Planning& Requirement Engineering 8 Hours

Software Engineering Practice An overview, Communication Practices, Planning Practices, Modeling

Practices, Construction Practice & Deployment, System Engineering Hierarchy, Business Process

Engineering, Product Engineering, System Modeling, Requirements Engineering. Requirements

Capturing - requirements engineering (elicitation, specification, validation, negotiation) equirements

monitoring, validating requirements, prioritizing requirements (kano diagram) ,Requirements

Analysis – basics.

Unit III Software Analysis and Design 09 Hours

Software Engineering Analysis & Design An overview, Requirements Analysis, Analysis Modeling

Approaches, Data Modeling, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented

Modeling, Class-based Modeling, Behavioral Model. Design Engineering Concepts, Design Model,

Pattern-Based Software Design. Unified modeling language (UML) concepts. UML views ,Static view,

Design view ,Use case view, State machine view , Activity view, Interaction view, Deployment view,

29

Model management view .

Unit IV Software Testing

06 Hours

Testing Strategies and Tactics an overview, level of testing: Unit Testing, Integration Testing,

Validation Testing, System Testing, Debugging techniques. Software Testing Fundamentals, Black-

Box Testing, White-Box Testing.

Unit V Software Metrics and Software Quality

Management

08 Hours

Product Metrics: An overview, Software Quality, A Framework for Product Metrics, Metrics for

Analysis & Design Models, Metrics for Source Code, Metrics for Testing & Maintenance, Software.

Project Management: An overview, Software Measurements, Metrics for Software Quality, Software

Project Estimation Techniques, Project Scheduling, Risk Management, Quality Management, Change

Management, and Software Reengineering. Cost estimation models

Unit VI Trends in Software Engineering and Project

Management

03 Hours

management (PERT/CPM):Developing a network plan ,overview of PERT /CPM, basic rules for

developing network, basic rules for developing project network. Recent trends in Software

Engineering and Project Management, Advanced topics & its Application.

Books:

Text:

1. Software Engineering- A Practitioner’s Approach (Sixth Edition) - Roger Pressman (TMH) Reference

1. Software Engineering (Seventh Edition)- Ian Summerville, Pearson Education. 2. Software

Engineering Theory and Practice by Pfleeger, Pearson Education.

3. Software Engineering- Schaum’s Series (TMH).4. The Unified modeling language reference

manual, Second edition, James Rumbag,Ivar Jacobson, Grady Booch.

Reference: 5. Software Engineering (Seventh Edition)- Ian Summerville, Pearson Education.

2. Brooks, F. (1995). The Mythical Man Month - Essays on Software Engineering ANV SUB

2nd

Edition.Addison Wesley, ISBN – 9780201835953

3. Software Engineering- Schaum’s Series (TMH)

3. Shailesh Mehta, "Project Management and Tools and Technologies", SPD ,ISBN-9789351104520

30



BITP302 Mini Project

Teaching Scheme:

PR: 02 Hours/Week

Credit

01

Examination Scheme:

Int: 25 Marks

Ext: -- Marks

Total: 25 Marks



manual need to include outline (program/ institute/ department/foreword/ preface etc), conduction &

Assessment guidelines, topics under consideration-concept, objectives, outcomes.



Outline, Certificate, table of contents, and write-up of each assignment (Title, Objectives, Problem

Statement, Outcomes, software & Hardware requirements, Date of Completion, Assessment

grade/marks and assessor's sign, Theory- Concept/technology/tool in brief, design, test cases,

conclusion/analysis. Program codes with sample output of all performed assignments are to be

submitted as softcopy.

As a conscious effort and little contribution towards Eco Friendly and environment awareness, attaching

printed papers as part of write-ups and program listing to journal may be avoided. Use of Google Class

room containing students programs.


Continuous assessment of laboratory work is done based on overall performance and lab assignments

performance of student. Each lab assignment assessment will assign grade/marks based on parameters

with appropriate weightage. Suggested parameters for overall assessment as well as each lab

assignment assessment include- timely completion, performance, innovation, efficient codes,



The instructor is expected to frame the assignments by understanding the prerequisites, technological

aspects, utility and recent trends related to the topic. The assignment framing policy need to address

the average students and inclusive of an element to attract and promote the intelligent students. The

instructor may set multiple sets of assignments and distribute among batches of students. It is

appreciated if the assignments are based on real world applications. Encourage students for appropriate

use of Hungarian notation, proper indentation . Use of open source software is to be encouraged. In

addition to these, instructor may assign one real life application in the form of a mini-project based on

the concepts learned. Instructor may also set one assignment or mini-project that is suitable to

respective branch beyond the scope of syllabus.




implementation of the problem statement. The supplementary and relevant questions may be asked at

the time of evaluation to test the student‘s for advanced learning, understanding of the fundamentals,

effective and efficient implementation. So encouraging efforts, transparent evaluation and fair approach

31

of the evaluator will not create any uncertainty or doubt in the minds of the students. So adhering to

these principles will consummate our team efforts to the promising start of the student's academics.

Course Objectives:

The Mini Project Lab has been developed by keeping in mind the following objectives:

1. To impart state-of-the-art knowledge on Software Engineering and UML in an

interactive manner through the Web.

2. Present case studies to demonstrate practical applications of different concepts.

3. Provide a scope to students where they can solve small, real life problems.

Course Outcomes:


1. Describe & adapt the life cycle of software development process.

2. List requirements & prepare SRS document for a given problem.

3. Apply various modelling techniques to design a system

4. Demonstrate various testing strategies.

5. Apply appropriate cost estimation techniques for the development of software.


1 Requirement analysis for identified project.

2 Creation of Software Requirement Specification Document.

3 Entity Relationship Diagrams.

4 UML diagrams using Star UML for identified project.

5 Construction of Code using Web Technology Concepts.

6 Database Connectivity using database concepts.

7 Writing Test Cases for the Project .(Manual Testing)

32

Course Syllabus

TY B. Tech. :TERM - VI

33



BCOL305MACHINE LEARNING

Teaching Scheme:

TH: 04 Hours/Week

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Course Objectives:

1. To acquire basic knowledge of machine learning concepts

2. To understand the process of selecting features for model construction

3. To learn supervised and unsupervised machine learning algorithms

4. To get knowledge about reinforcement Learning and deep learning

5. To understand ensemble methods in machine learning

6. To be aware about combined working of all learning.

Course Outcomes:

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

1. Explain different machine learning techniques

2. Apply feature selection to create accurate predictive model

3. Analyze various machine learning models

4. Compare and combine machine learning models for improved accuracy

Course Contents

Unit I Introduction to Machine Learning 04 Hours

What Is Machine Learning, Examples of Machine Learning Applications: Learning Associations,

Classification, Regression, Unsupervised Learning, Reinforcement Learning.

Unit II Feature Selection

08 Hours

Scikit- learn Dataset, Creating training and test sets, managing categorical data, Managing missing

features, Data scaling and normalization, Feature selection and Filtering, Principle Component

Analysis(PCA)-non negative matrix factorization, Sparse PCA, Kernel PCA.

Unit III Supervised Learning 09 Hours

Learning a Class from example, Linear Regression, Logistic Regression , Naïve bayes classifier, Support

Vector Machines, KNN Algorithm, Decision Trees, Random Forests, Model Evaluation: Overfitting

&Underfitting

Unit IV Unsupervised Learning 09 Hours

Clustering: k-Means Clustering, Hierarchical Clustering, Agglomerative Clustering- Dendrograms;

Expectation-Maximization Algorithm, The Curse of Dimensionality, Dimensionality Reduction, Factor

Analysis

Unit V Combining Multiple Learners 09 Hours

34

Rationale, Generating Diverse Learners, Voting, Bagging, Boosting, Mixture of Experts Revisited, Stacked

Generalization, Fine-Tuning an Ensemble, Cascading.

Unit VI Advances in Machine Learning 09 Hours

Reinforcement Learning- Introduction, Elements of Reinforcement Learning, Model-Based Learning:

Value Iteration, Policy Iteration

Deep Learning- Defining Deep learning, common architectural principles of deep networks, building

blocks of deep networks.

Books:

Text:

1. Ethemalpaydin, “Introduction to machine Learning”, The MIT Press Cambridge, Second Edition,2010.

2. Tom M. Mitchell ,Machine Learning, McGraw-Hill, 1997

Reference:

1. Giuseppe Bonaccorso, “Machine Learning Algorithms”, Packt Publishing Limited, ISBN-10:

1785889621, ISBN-13: 978-1785889622

2.ParagKulkarni, Reinforcement and Systemic Machine Learning for Decision Making, July

2012, Wiley-IEEE Press.

3. Josh Patterson, Adam Gibson, “Deep Learning: A Practitioners Approach”, O‟REILLY, SPD, ISBN: 978-

93-5213-604-9, 2017 Edition 1st.

4. Peter Flach, “Machine Learning: The Art and Science of Algorithms that Make Sense of Data”,

Cambridge University Press, Edition 2012, ISBN-10: 1107422221; ISBN-13: 978-1107422223

35



BCOP305 Machine Learning

Teaching Scheme:

PR: 04 Hours/Week

Credit

02

Examination Scheme:

Int: 25 Marks

Ext: 25 Marks

Total: 50 Marks



manual need to include prologue (about University/program/ institute/ department/foreword/ preface

etc), University syllabus, conduction & Assessment guidelines, topics under consideration-concept,

objectives, outcomes.



prologue, Certificate, table of contents, and handwritten write-up of each assignment (Title, Objectives,

Problem Statement, Outcomes, software & Hardware requirements, Date of Completion, Assessment

grade/marks and assessor's sign, Theory- Concept, conclusion/analysis).

As a conscious effort and little contribution towards Green IT and environment awareness, attaching

printed papers as part of write-ups and program listing to journal may be avoided.


Continuous assessment of laboratory work is done based on overall performance and lab performance

of student. Each lab assignment assessment should assign grade/marks based on parameters with

appropriate weightage. Suggested parameters for overall assessment as well as each lab assignment

assessment include- timely completion, performance, innovation, efficiency, punctuality and neatness.


The instructor is expected to frame the assignments by understanding the prerequisites, technological

aspects, utility and recent trends related to the topic. The assignment framing policy need to address

the average students and inclusive of an element to attract and promote the intelligent students. The

instructor may set multiple sets of assignments and distribute among batches of students. It is

appreciated if the assignments are based on real world problems/applications.




implementation of the problem statement. The supplementary and relevant questions may be asked at

the time of evaluation to test the student‘s for advanced learning, understanding of the fundamentals,

effective and efficient implementation. So encouraging efforts, transparent evaluation and fair approach

of the evaluator will not create any uncertainty or doubt in the minds of the students. So adhering to

these principles will consummate our team efforts to the promising start of the student's academics.

Course Objectives:

1. To learn data formats of pandas

2. To learn data formats of Numpy, data visualization and graph plotting using pandas

3. To learn scipy and Scikit-learn

4. To prepare the dataset for training and testing

5. To learn supervised learning algorithms

6. To learn unsupervised learning algorithms

Course Outcomes:

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

36

1. Explain different machine learning techniques

2. Apply feature selection to create accurate predictive model

3. Analyze various machine learning models

4. Compare and combine machine learning models for improved accuracy


1 Understanding data formats of Pandas: Series, Dataframe, Panel; Creating, Appending,

Deleting. Importing different types of Datasets. Working with Dimensions

2 Type conversions from different datatype into Series, Dataframe and Panel, Necessary

operations like renaming, traversing columns and indexes, Statistics on data formats of Pandas

3 Understanding data formats of Numpy: ndarrays (1D, 2D and 3D arrays), Array creation

routines

4 Matplotlib plotting for Data visualization

5 Tweaking Colors, Symbols, Formulations. Plotting Categorical data, 3D Axes, Parametric Curves,

Trigonometry functions, Histogram, Bar, Pie chart. Graph plotting using Pandas

6 Introduction to Scipy, Scikit-learn, Importing Algorithm Classes and creating objects with

parametric values

7 Dataset selection: Dataset for Classification / Regression / Associative Rule Mining. and

Analysis: Independent Variables, Dependent Variables, Handling Missing Values, Categorical

data, and Feature Scaling

8 Preparing Dataset for Training and Testing

9 Regression: Performing Simple Linear Regression over a salary dataset and predict salaries

according to their experience years

10 Regression & Data Valuation: Performing Multi-linear Regression (using appropriate Model) to

evaluate with data which is useful for model training

11 Regression: Using Polynomial regression resolve bluff query for new employee salary

12 Classification: Using KNN (with WCSS), NB Predicting if a customer with certain age and Salary

will purchase a product or not

13 Classification: Using DT and SVM Predicting if a customer with certain age and Salary will

purchase a product or not

14 Classification: Using RFC Predicting if a customer with certain age and Salary will purchase

15 Clustering: Using K-Means clustering, determine Customers of a Mall according to Categories

so as to launch a scheme for business growth a product or not for imbalanced data and

determining Fitting issues and Sampling methods and Optimizing techniques

37

16 Mini Project based on Machine Learning using suitable python libraries

Reference:

1. Dr. Randal S. Olson, Python Machine Learning, Packet Publishing

38



BCOL302 Design & Analysis of Algorithm

Teaching Scheme:

TH: 04 Hours/Week

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Data Structures, Discrete Mathematics ,Theory of Computation

Course Objectives: 1. To design and analyze the performance of algorithms by mathematical logic building

2. To evaluate instances by using Divide and Conquer techniques.

3. To apply problem solving techniques using Greedy and Dynamic Programming strategy.

4. To demonstrates Backtracking and Branch-Bound algorithmic design strategies

5. To identifies and analyze NP-Hard and NP-Complete algorithms

6. To study Parallel and String Matching algorithms.


1. Describe concepts of Algorithmic characteristics

2. Interpret various problem solving techniques using algorithmic types

3. Explain performance of algorithms using mathematical formulas

4. Demonstrate design strategies for solving various applications

5. Analyze complexity of problems for different computing areas

Course Contents


What is an algorithm, Mathematical Notations, Algorithm specification, Analysis of Algorithm-

Introduction, Analyzing control structures, Asymptotic notations, space complexity, time complexity,

Performance measurement, Solving Recurrence Relations, Masters theorem, Proof Techniques.

Unit II Divide and Conquer 06 Hours

Divide and Conquer: General method, Binary search, Finding Max and Min, Quick Sort-Performance

measurement, Merge Sort, Heap Sort.

Unit III Greedy strategy and Dynamic Programming 09 Hours

Greedy strategy: General Method, control abstraction, Knapsack problem, Job sequencing with

deadlines, Minimal-Cost Spanning Trees –Prim’s algorithm, Kruskal’s algorithm ,Optimal merge patterns,

Single-source shortest path algorithm.

Dynamic Programming: General Method, Elements of Dynamic Programming, Multistage graphs, OBST,

0/1 knapsack. Travelling salesman problem, All pair shortest path.

Unit IV Backtracking &Branch and Bound 08 Hours

Backtracking: General method, 8 Queen's problem, Graph Coloring, Hamiltonian Cycles.

Branch and Bound: General method, method- LC search, Control abstraction of LC search, Bounding,

FIFO and LC Branch-and-Bound, Traveling Salesperson Problem.

Unit V Complexity Theory 08 Hours

Basic Concepts: Non deterministic algorithms, The classes NP Hard and NP Complete, Reduction

Techniques, Cook's Theorem, NP Hard graph problems: Clique Decision problem, Node cover Decision

problem, Chromatic number decision problem, Directed Hamiltonian Cycle Problem. Study of NP-Hard

39

and NP-COMPLETE problems. Solving NP-COMPLETE problem.

Unit VI Parallel and Advanced Algorithms 08 Hours

Computational Model, Basic Techniques and Algorithms, Complete Binary Tree, Pointer Doubling, Prefix

Computation, Selection, Merging, Sorting, Graph Problems, String Matching- Introduction, The Naive

string matching algorithm, The Rabin-Karp algorithm.

Books:

Text:

1. Horowitz and Sahani, "Fundamentals of Computer Algorithms", University Press, ISBN: 978

81 7371 6126, 81 7371 61262

2. Gilles Brassard, Paul Bratley, “Fundamentals of Algorithmics”, PHI, ISBN 978-81-203-1131-2

Reference:

1. Thomos H. Corman, Charls E. Leiserson, Ronald E. Rivest, Clifford Stein, “Introduction to

Algorithms”, Third Edition,Prentice Hall India Learning Pvt. Ltd.

2. Parag Himanshu Dave, HimanshuBhalchandra Dave, “Design And Analysis of Algorithms”,

Pearson Education, ISBN 81-7758-595-9

40



BCOP302 Design & Analysis of Algorithm

Teaching Scheme:

PR: 02 Hours/Week

Credit

01

Examination Scheme:

Cont. Ass: 25 Marks

Ext.: 25 Marks

Total: 50 Marks




































1. To develop problem solving abilities using mathematical theories

2. To analyze the performance of algorithms with time complexity.

3. To apply algorithmic design strategies with optimization problems.

41

4. To solve real life problems with various designs of algorithms.

Course Outcomes:-


1. Describe concepts of Algorithmic characteristics

2. Interpret various problem solving techniques using algorithmic types

3. Explain performance of algorithms using mathematical formulas

4. Demonstrate design strategies for solving various applications

5. Analyze complexity of problems for different computing areas


1 Create a Java/C++ class called Student with the following details as variables within it.

(i) USN

(ii) Name

(iii) Branch

(iv) Phone

Write a Java/C++ program to create n Student objects and print the USN, Name, Branch, and

Phone of these objects with suitable headings.

2 Write Java/C++ program to find factorial of a given number using

(i) Recursion

(ii) Iteration

Compare time and space complexity of both the designs.

3 Implement Binary search program with Divide and Conquer design strategy for n numbers using

Java/C++.

4 Sort a given set of n integer elements using Quick Sort method and compute its time complexity.

Run the program for varied values of n and record the time taken to sort. The elements can be

read from a user or can be generated using the random number generator. Demonstrate using

Java/C++ how the divide and conquer method works along with its time complexity analysis:

worst case, average case and best case.

5 A business house has several offices in different countries; they want to lease phone lines to

connect them with each other and the phone company charges different rent to connect

different pairs of cities. Business house want to connect all its offices with a minimum total cost.

Solve the problem by suggesting appropriate data structures in Java/C++.

6 From a given vertex in a weighted connected graph, find shortest paths to other vertices using

Dijkstra's algorithm. Write the program in Java/C++.

7 Implement a program in Java/C++ for 0/1 Knapsack problem using Dynamic Programming

method.

8 Write Java/C++ program to implement Travelling Sales Person problem using Dynamic

programming.

42

9 Implement Java/C++ program for solving N-Queen’s problem using Back tracking. (Assume N=4)

10 Implement Travelling salesman problem using branch and bound approach using Java/C++.

11 Design and implement the presence of Hamiltonian Cycle in an undirected Graph G of n vertices

using Java/C++.

43



BCOL304SYSTEM PROGRAMMING

Teaching Scheme:

TH: 04 Hours/Week

TU: ---

Credit

04

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Data Structures, Theory of Computation

Course Objectives:

1. To study concepts in assemblers, Macro, loaders and linkers.

2. To learn the design principles of a Compiler

3. To introduce the various parsing techniques and different levels of translation.

4. To know how to optimize and effectively generate machine codes

5. To understand systems and methods of compilation

6. To introduce the recent trends in System Programming.

Course Outcomes:


1. Explain basic concepts of various system software

2. Construct symbol table for various phases phases of Compiler

3. Describe techniques for intermediate code and machine code optimization

4. Write a scanner, parser and semantic analyzer without the aid of automatic generators

Course Contents


Assemblers: Overview of System Programming, Design of two pass assemblers, single pass assemblers.

MACRO: Macro definition- macro call – macro expansion- nested macro.

LINKERS & LOADERS:Absolute loaders, relocating loaders.

Linkers: Relocation and linking concepts, Design of linker, self-relocating programs.

Unit II Lexical Analysis 06 Hours

Compilers and translators, Phases of compiler design, cross compiler, Bootstrapping, Design of Lexical

analyzer, Study of LEX.

Unit III Syntax Analysis 08 Hours

Specification of syntax of programming languages using CFG, Top-down parser, design of LL (1) parser,

bottom up parsing technique, LR parsing algorithm, Design of SLR, LALR, CLR parsers, Study of YACC.

Unit IV Syntax Directed Translation 06 Hours

Study of syntax directed definitions & syntax directed translation schemes, implementation of SDTS,

intermediate notations: postfix, syntax tree, DAG

Unit V Intermediate Code Generation 06 Hours

Intermediate Code Generation: Intermediate languages, Declarations, assignment statements, iterative

statements, case statements, arrays, structures, conditional statements, Boolean expressions, back

patching, procedure calls.

Unit VI Code Generation and Recent Trends in Compilers 08 Hours

44

Code Optimization: Principle sources Of Optimization, Optimization of basic blocks, loops in flow graphs,

Peephole optimization.

Code Generation: Introduction: Issues in code generation, Basic blocks and flow graphs, next-use

information, Target machine description, Register allocation and assignment, Dag representation of

basic blocks, Generating code from a DAG.

Recent trends in Compilers: Compiler tools, Advanced topics & its Application

Books:

Text:

1. Leland L. Beck, “System Software – An Introduction to Systems Programming”, 3rd

Edition, Pearson Education Asia, 2000.

2. Alfred V. Aho, Ravi Sethi Jeffrey D. Ullman, “Compilers- Principles, Techniques, and

Tools”, Pearson Education Asia, 2007.

Reference:

1. D. M. Dhamdhere, “Systems Programming and Operating Systems”, Second

Revised Edition, Tata McGraw-Hill, 1999.

2. Steven S. Muchnick, “Advanced Compiler Design & Implementation”, Morgan

Kaufmann Pulishers, 2000.

45



BCOP304 SYSTEM PROGRAMMING

Teaching Scheme:

PR: 02 Hours/Week

Credit

01

Examination Scheme:

Cont. Ass: 25 Marks

Ext. : 25 Marks

Total: 50 Marks




































1. To study concepts in assemblers, Macro, loaders and linkers.

2. To learn the design principles of a Compiler

3. To introduce the various parsing techniques and different levels of translation.

46

4. To know how to optimize and effectively generate machine codes

5. To understand systems and methods of compilation

6. To introduce the recent trends in System Programmings.

Course Outcomes:-


1. Explain basic concepts of various system software

2. Construct symbol table for various phases phases of Compiler

3. Describe techniques for intermediate code and machine code optimization

4. Write a scanner, parser and semantic analyzer without the aid of automatic generators

Sr.No List of Laboratory Assignments

1 Understand syntax of LEX specifications built-in functions and variables. And write a LEX

program to convert a number in words to integer.

2 Write a LEX program to calculate the average of given numbers.

3 Write a LEX Program to Count no. of lines, blanks, words & characters supplied at a command

prompt.

4 Write a LEX program to calculate the average of given numbers

5 Write a LEX Program to convert lower case to upper case and upper case to lower case.

6 Implement a LEX program to convert Roman Number to Decimal Number.

7 Write a LEX program to find the number of vowels and consonants.

8 Implement Finite Automata in LEX for Odd numbers of a’s

9 Implement a LEX program to recognize whether a given sentence is a simple or compound.

10 Implementation of Lexical Analyzer using Lex Tool

11 Implementation of desktop Calculator using LEX and YACC

12 Implementation of three address code using LEX and YACC

47


Second Year of Computer Engineering (2018 Course)

BCOL307 A Software Testing & Quality Assurance

Teaching Scheme:

TH: 03 Hours/Week

TU:Nil

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Prerequisites: Software Engineering

Course Objectives:

1 Introduction to software testing lifecycle.

2 Understanding various types of software tests and quality control standards

3 Understand quality management processes

Course Outcomes:


1 apply software testing and quality assurance as a fundamental component of software life cycle

2 Understand About project process control and software Metrics

3 Understand the importance of standards in the quality management process and their impact on

the final product.

4 Efficiently perform T&QA activities using modern software tools

Course Contents

Unit I Basics of Software Testing 08 Hours

Principles of testing software development life cycle models , errors, defect, failure ,testing life cycle and

phases ,defect life cycle defect report ,test plan(IEEE format), , test bed

Unit II Types of Testing 09 Hours

White box testing, black box testing, integrated testing, system and acceptance testing, performance and

regression testing ,Ad-hoc and internationalization testing concepts

Unit III Test Planning and Management 08 Hours

Test planning, test management, test process ,test report and best practices

Unit IV Testing Metrics and measurement 07 Hours

Test organization, Structure of testing, Measurement tools, Testing metrics: Type of metric ,progress

metrics, productivity metrics and release metrics

Unit V Software test automation 08Hours

Test automation and its scope, architecture of automation, requirement of test tools, process model of

automation, selection of test and challenges in automation

Unit VI Testing Tools 9 Hours

Manual testing, Automated Testing Tools & Case studies, Study of Testing tools (QTP, Rational Robot, Win

runner, Load runner

Books

Text:

Text Books:

1. Software testing Principle and Practices By Ramesh Desikan, Pearson Education, ISBN 81-7758-

48



BCOL307B DISTRIBUTED SYSTEMS

Teaching Scheme:

TH: 03 Hours/Week

TU:---Hour/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Data Communication

Course Objectives:

1. To Understand foundations of distributed Systems.

2. Introduce the communication in distributed system.

3. Understand in synchronization and replication in distributed system.

4. Understand the issues involved in studying process and resource management.

5. To acquaint with the distributed File Systems.

6. To explore the distributed Transaction.

121-X 5.

2. Software Testing Concepts and Tools By Nageshwar Rao Pusufuri,ISBN 81-7722-712-2

Reference:

1.“Foundations of Software Testing”2E by Aditya P. Mathur , Pearson Education

2.Effective Methods for Software Testing (William E Perry(Wiley).

3.Software Testing Principles, Techniques and tools, 1st

Edition, by M.G. Limaye

McGraw Hills

1.Software Testing and Quality Assurance by KshirsagerNaik and Priyadarshini

Tripathi (Wiley)

49

Course Outcomes:


1. To know Responsibilities, services offered distributed system.

2. Explain various communication systems.

3. Use and apply synchronization and replication in distributed system.

4.Understand working principle of process and resource management

5. Use and apply the concept of distributed file system.

6. Explore recent trends in distributed system

Course Contents

Unit I INTRODUCTION 06 Hours

Introduction - Examples of Distributed Systems-Trends in Distributed Systems - Focus on resource

sharing - Challenges. Case study: World Wide Web.

Unit II COMMUNICATION IN DISTRIBUTED SYSTEM 08 Hours

System Model - Inter process Communication - the API for internet protocols - External data

representation and Multicast communication. Network virtualization: Overlay networks.

MPI, Remote Method Invocation And Objects: Remote Invocation - Introduction - Request-reply

protocols - Remote procedure call - Remote method invocation.

Java RMI - Group communication - Publish-subscribe systems - Message queues - Shared memory

approaches -

Unit III SYNCHRONIZATION AND REPLICATION 07 Hours

Introduction - Clocks, events and process states - Synchronizing physical clocks- Logical time and

logical clocks - Global states - Coordination and Agreement - Introduction - Distributed mutual

exclusion - Elections - Transactions and Concurrency Control- Transactions -Nested transactions -

Locks - Optimistic concurrency control - Timestamp ordering - Atomic Commit protocols -Distributed

deadlocks - Replication - Case study - Coda.

Unit IV PROCESS & RESOURCE MANAGEMENT 07 Hours

Process Management:

Process Migration: Features, Mechanism - Threads: Models, Issues,Implementation.

Resource Management:

Introduction- Features of Scheduling Algorithms –Task Assignment Approach - Load Balancing Approach

- Load Sharing Approach

Unit V Distributed File Systems 07 Hours

Distributed consensus: Consensus in asynchronous systems, Consensus in synchronous systems, Paxo‟s algorithm, Failure detectors. Distributed Transactions: Classification of transactions, Implementing

Transactions, Concurrency control and serializability, Atomic Commit protocols, Recovery from Failures.

Unit VI SECURITY IN DISTRIBUTED SYSTEMS 07 Hours

Introduction to Security: Security Threats, Policies, and Mechanisms, Design Issues, Cryptography.

Secure Channels: Authentication, Message Integrity and Confidentiality, Secure Group Communication,

Access Control: General Issues in Access Control, Firewalls, Secure Mobile Code, Denial of Service (DOS).

Security Management: Key Management, Secure Group Management, Authorization Management.

Emerging Trends In Distributed Systems: Grid Computing, Service Oriented Architectures (SOA). Case

Study: Kerberos.

50

Books:

Text: 1. 1. George Coulouris, Jean Dollimore and Tim Kindberg, “Distributed Systems Concepts and Design”, Fifth

Edition, Pearson Education, 2012.

Reference:

1. Pradeep K Sinha, "Distributed Operating Systems: Concepts and Design", Prentice Hall of

India, 2007.

2. Tanenbaum A.S., Van Steen M., “Distributed Systems: Principles and Paradigms”, Pearson

Education, 2007.

3. Liu M.L., “Distributed Computing, Principles and Applications”, Pearson Education, 2004.

4. Nancy A Lynch, “Distributed Algorithms”, Morgan Kaufman Publishers, USA, 2003



BCOL307C – Soft Computing

Teaching Scheme:

TH: 03 Hours/Week

TU:---Hour/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:-

51

Course Objectives:

1. Learn the various soft computing frame works

2. Be familiar with design of various neural networks

3. Be exposed to fuzzy logic

4. Learn genetic programming.

Course Outcomes:


1. Apply various soft computing frame works.

2. Design of various neural networks.

3. Use fuzzy logic.

4. Apply genetic programming.

5. Discuss hybrid soft computing

Course Contents


Artificial neural network: Introduction, characteristics- learning methods – taxonomy – Evolution of

neural networks- basic models – important technologies – applications. Fuzzy logic: Introduction – crisp

sets- fuzzy sets – crisp relations and fuzzy relations: cartesian product of relation – classical relation,

fuzzy relations, tolerance and equivalence relations, non-iterative fuzzy sets. Genetic algorithm-

Introduction – biological background – traditional optimization and search techniques – Genetic basic

concepts.

Unit II NEURAL NETWORKS 08Hours

McCulloch-Pitts neuron – linear separability – hebb network – supervised learning network: perceptron

networks – adaptive linear neuron, multiple adaptive linear neuron, BPN, RBF, TDNN- associative

memory network: auto-associative memory network, hetero-associative memory network, BAM,

hopfield networks, iterative autoassociative memory network & iterative associative memory network –unsupervised learning networks: Kohonenself organizing feature maps, LVQ – CP networks, ART

network.

Unit III FUZZY LOGIC 08 Hours

Membership functions: features, fuzzification, methods of membership value assignments-

Defuzzification: lambda cuts – methods – fuzzy arithmetic and fuzzy measures: fuzzy arithmetic –

extension principle – fuzzy measures – measures of fuzziness -fuzzy integrals – fuzzy rule base and

approximate reasoning : truth values and tables, fuzzy propositions, formation of rules-decomposition of

rules, aggregation of fuzzy rules, fuzzy reasoning-fuzzy inference systems-overview of fuzzy expert

system-fuzzy decision making.

Unit IV GENETIC ALGORITHM 08 Hours

Genetic algorithm and search space – general genetic algorithm – operators – Generational cycle –

stopping condition – constraints – classification – genetic programming – multilevel optimization – real

life problem- advances in GA

Unit V HYBRID SOFT COMPUTING TECHNIQUES &

APPLICATIONS

08 Hours

Neuro-fuzzy hybrid systems – genetic neuro hybrid systems – genetic fuzzy hybrid and fuzzy genetic

hybrid systems – simplified fuzzy ARTMAP – Applications: A fusion approach of multispectral images

with SAR, optimization of traveling salesman problem using genetic algorithm approach, soft computing

based hybrid fuzzy controllers.

Books:

52

Text:

1. J.S.R.Jang, C.T. Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI / Pearson Education

2004.

2. S.N.Sivanandam and S.N.Deepa, “Principles of Soft Computing”, Wiley India Pvt Ltd, 2011.

Reference:

1. S.Rajasekaran and G.A.VijayalakshmiPai, “Neural Networks, Fuzzy Logic and Genetic Algorithm:

Synthesis & Applications”, Prentice-Hall of India Pvt. Ltd., 2006.

2. George J. Klir, Ute St. Clair, Bo Yuan, “Fuzzy Set Theory: Foundations and Applications” Prentice

Hall, 1997.

3. David E. Goldberg, “Genetic Algorithm in Search Optimization and Machine Learning” Pearson

Education India, 2013.

4. James A. Freeman, David M. Skapura, “Neural Networks Algorithms, Applications, and

Programming Techniques, Pearson Education India, 1991.

5. Simon Haykin, “Neural Networks Comprehensive Foundation” Second Edition, Pearson

Education, 2005.



BCOL307 D - MOBILE COMPUTING

Teaching Scheme:

TH: 03 Hours/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:-

53

Course Objectives:

1. To study foundations of Mobile Computing

2. To develop problem solving abilities using Mobile Computing

3. To study different operating systems in mobile devices

4. To learn advances in Mobile Computing

CourseOutcomes:

1. Remembering basic concepts of wireless networks.

2. Understanding concept of mobile communication and computing

3. Studying and comparing GSM and other architectures.

4. Analysing network and transport layers for mobile.

5. Understanding data Dissemination and data synchronization in mobile computing

6. Studying advanced mobile devices and operating systems.

Course Contents

Unit I Basics of Wireless Networks 06 Hours

Digital communication, wireless communication system and limitations, wireless media, frequency

spectrum, technologies in digital wireless communication, wireless communication channel

specification, wireless network, wireless switching technology.

Unit II Mobile Communications and Computing 08 Hours

An Overview Mobile Communication, Mobile Computing, Mobile Computing Architecture, Mobile

Devices, Mobile System Networks, Data Dissemination, Mobility Management, Security, Mobile Devices

and Systems, Mobile Phones, Digital Music Players, Hand-held Pocket Computers, Hand-held Devices:

Operating Systems, Smart Systems, Limitations of Mobile Devices, Automotive Systems.

Unit III GSM and other architectures 08 Hours

GSM-Services & System Architectures ,Radio Interfaces, Protocols of GSM, Localization, Calling,

Handover, Security, New Data Services, modulation, multiplexing, controlling the medium access, spread

spectrum, coding methods, CDMA, IMT 2000, WCDMA and CDMA 2000,4G Networks, Mobile satellite

communication Networks.

Unit IV Mobile IP Network and Transport Layer 08 Hours

IP & Mobile IP Network Layers, Packet Delivery & Handover Management, Location Management,

Registration, Tunneling & Encapsulation, Route Optimization, Dynamic Host Configuration Protocol,

IPSec, Mobile Transport Layer, Conventional TCP/IP Transport Layer Protocol, Indirect TCP, Snooping

TCP, Mobile TCP, Mobile Ad-hoc Networks(MANET), Routing and Routing Algorithms in MANET, security

in ad-hoc networks.

54



BITL307 A Multimedia System

Teaching Scheme:

TH: 03 Hours/Week

TU: -- /Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Unit V Data Dissemination and Data Synchronization in

Mobile Computing

08 Hours

Communication Asymmetry, classification of data delivery mechanism, data dissemination broadcast

models, selective tuning and indexing techniques, synchronization, synchronization software for mobile

devices, synchronization protocols, SMIL

Unit VI Mobile Device application server and advanced

Operating system

08 Hours

Mobile agent, applications framework, application server, gateways, service discovery, device

management, Mobile Operating Systems, Characteristics, Basic functionality of Operating Systems,

Window 8, iOS, Android OS, Mini operating system ,Advances in mobile generations( 1G to 5G)

Books:

Text:

1.Raj Kamal, Mobile Computing, 2/e , Oxford University Press-New Delhi

2. Dr. Sunil kumar S. Manavi, Mahabaleshwar S. Kakkasageri, Wireless and Mobile Networks, concepts

and protocols, Wiley, India.

Reference:

1. Andrew Tanenbaum, Modern Operating System, 3rd/e, Pearson Education International,

ISBN Q-lB-_lBMST-L

1. 2. Digital Content: iOS Technology Overview: IOSTechOverview.pdf, Apple Inc. Copyright 2014

2. 3.http://www.ccis2k.org/iajit/PDF/vol.9,no.1/1614-7.pdf

4 Jochen Burkhardt, Horst Henn, Stefan Hepper, Klaus Rindtor_, Thomas Schaeck,

3. Pervasive Computing, Pearson, Eighteenth Impression, 2014.

4.

http://www.ccis2k.org/iajit/PDF/vol.9,no.1/1614-7.pdf

55

Prerequisite:-

Course Objectives:

1. Students will be able to understand therelevance and underlining of theInfrastructure of

multimedia systems.

2. Students will be able to understand the processing, storage, generation, manipulation and

rendition of multimedia information.

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

1. Apply basics of multimedia systems like audio, video, image, text, tools, etc.

2. Use the Multimedia hardware and platform for providing real time solutions

3. Develop an appropriate multimedia tool for multimedia system problems

4. Analyze the requirement of multimedia system in various domains

5. Identify the exact need of multimedia systems involved in the real life applications.

6. Identify the latest tools for Multimedia

Course Contents

Unit I 07 Hours

Multimedia- definitions, CD-ROM and themultimedia highways, uses of multimedia

introduction to making multimedia, the stages ofprojects, requirements to make good multimedia,

multimedia skills and training, the multimedia tea, training opportunities in multimedia.

Unit II 07 Hours

Multimedia hardware, Macintosh and windows production platforms, hardware peripherals

connections, memory and storage devices, input devices output hardware, communication devices,

media software, basic tools, making instant multimedia authoring tools.

Unit III 08 Hours

Multimedia building blocks- text, sound, images animations, video assembling and delivering a

project, planning and costing, designing and producing Content and talent, delivering, CD-ROM

technology, DVD Tech

Unit IV 07 Hours

Multimedia Authoring & User Interface –Hypermedia messaging - Mobile Messaging –

Hypermedia message component – CreatingHypermedia message

Unit V 08 Hours

Multimedia and Internet- History, web servers, webbrowsers, VRML, working on the web: text,

animation, images and sound for the web, multimedia Applications, media communication,

media consumption, media entertainment andMultimedia games.

Unit VI 08 Hours

Integrated multimedia message standards –Integrated Document management –Distributed

Multimedia Systems. Recent trends/ advance topic.

Books:

Text:

1. Multimedia Making Work- by Tay Vaughan (TMH), 3rd Ed.

2. Multimedia systems design by K.Andleigh, K.Thakkar (PHI Pub.)

Reference:

1. Multimedia: Computing Communications & Applications By Ralf Stein and Klara Nahrtedt.

2. Advanced Multimedia Programming by Steve Rimmer (McGraw Hill Pub.)

3. Multimedia Literacy by Fred T. Hoftstetter (McGraw Hill Pub.)

56



BITL306 B Embedded System & IOT

Teaching Scheme:

TH: 03 Hours/Week

TU:---Hour/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite: 1. Data communication

2. Computer Network

Course Objectives:

1.To understand fundamentals, design strategies of IOT and Embedded System

57

2. To develop comprehensive approach towards building low cost Embedded IOT system.

3. To learn security in IOT infrastructure.

4. To learn real world applications.

Course Outcomes:


1. To understand the concepts of internet of things.

2. To learn architecture and design of IoT.

3. Apply the underlying Technologies.

4. To get knowledge of different platforms in IoT.

5. To Implement cloud interface to IoT.

Course Contents

Unit I INTRODUCTION TO INTERNET OF THINGS 08 Hours

Introduction to Internet of Things: Internet of Things Definitions and Frameworks : IoT Definitions, IoT

Architecture, General Observations, ITU-T Views, Working Definition, IoT Frameworks, Basic Nodal

Capabilities, Physical Design of IoT: IoT Protocols, Logical Design of IoT: Functional block, communication

Model, Communication API’s, IoT Enabling Technologies: WSN, cloud computing, Big data Analytics,

communication Protocols, Embedded systems, IoT levels and Deployment templates: Level 1 to Level 5.

Unit II IOT NETWORK ARCHITECTURE AND DESIGN 08Hours

A Simplified IoT Architecture, IoT protocol stack, The Core IoT Functional Stack, IoT Data Management

and Compute Stack: Fog Computing, Edge Computing, The Hierarchy of Edge, Fog, and Cloud IoT and

M2M: Introduction to M2M, Difference between IoT and M2M, SDN and NFV for IoT.

Unit III SMART OBJECTS: THE “THINGS” IN IOT 08 Hours

Sensors, Actuators, and Smart Objects, Sensor Networks, Connecting Smart Objects: Communications

Criteria, IoT Access Technologies: IEEE 802.15.4, IEEE 802.15.4g and 802.15.4e, IEEE 1901.2a, LoRaWAN.

Unit IV ADDRESSING TECHNIQUES FOR THE IoT 08 Hours

Address Capabilities, IPv6 Protocol Overview, IPv6 Tunneling, IPsec in IPv6, Header Compression

Schemes, Quality of Service in IPv6, Migration Strategies to IPv6, Mobile IPV6 technologies for the IoT:

Protocol Details, IPv6 over low-power WPAN (6LoWPAN).

Unit V IOT PHYSICAL SERVERS AND CLOUD OFFEREINGS 08 Hours

What is an IoT Device, Exemplary Devices: Raspberry Pi, Raspberry Pi Interfaces, Other IoT Devices:

pcDuino, Beagle Bone Black, ARDUINO.

Unit VI IoT PHYSICAL SERVERS AND CLOUD OFFEREINGS

08 Hours

Introduction to cloud storage models and communication API’s, WAMP-AutoBahn for IoT, Python web

application framework, Designing a RESTful web API, AMAZON web services for IoT, SkyNetIoT

messaging platform, IoT case studies: Home Automation, Cities, Environment.

Books:

Text:

1. Internet of Things: A Hands-On Approach ArshdeepBahga, Vijay Madisetti VPT – Paperback 2015 978-

0996025515 628/- 2.

2. IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things

David Hanes, Gonzalo Salgueiro, Patrick Grossetete Cisco Press – Paperback – 16 Aug 2017 978-1-

58714-456- 1 599.

3. Building the Internet of Things with IPv6 and MIPv6: The Evolving World of M2M Communications

Daniel Minoli Willy Publication s - 2013 978-1-118- 47347-4, 466.

58

Reference:

1. Smart Internet of things projects AgusKurniawanPackt - Sep 2016 978-1- 78646- 651-8 2 The Internet

of Things Key Olivier Willy Publication 2nd Edition 978

2. Applications and protocols Hersent s 119- 99435-0, 3 The Internet of Things Connecting Objects to the

Web HakimaChaouchi, Willy Publications 978-1- 84821- 140-7.



BITL306 C – Wireless Sensor Networks

Teaching Scheme:

TH: 03 Hours/Week

TU:---Hour/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

59

ESE: 60 Marks

Prerequisite:- Computer Networks

Course Objectives:

1. Students will be introduced to some existing applications of wireless sensor networks

2. Students will understand the concepts of distributed computing and protocol design

3. Students will know about various network level protocols

4. Students will learn the hardware and software platforms for sensor network

5. Students will get aware of programming concepts of WSN

6. Students will determine the research areas in WSN

Course Outcomes:


1. Understandexisting applications of wireless sensor networks

2. Students will get aware of elements of distributed computing and network protocol design and

will learn to apply these principles in the context of wireless sensor networks

3. Students will get an overview of the various network level protocols for MAC, routing etc.

4. Students will learn the various hardware, software platforms that exist for sensor networks

5. Students will implement programs sensor network platforms using TinyOS, C and Java

6. Students will recognize the research problems in wireless sensor networks pose in different

disciplines

Course Contents


Basics of Wireless Sensors and Applications, The Mica Mote, Sensing and Communication Range,

Design Issues, Energy consumption, Clustering of Sensors, Applications

Unit II WSN Networking 08Hours

Data Retrieval in Sensor Networks, Classification of WSNs, MAC Layer, Routing Layer, High-Level

Application Layer Support, Adapting to the Inherent Dynamic Nature of WSNs Sensor Network

Unit III Wireless Sensor Networks Platforms& Tools 08 Hours

Wireless sensor network Platforms and Tools, Sensor Network Hardware, Sensor Network

Programming Challenges, Node-Level Software Platforms.

Unit IV Operating Systems for Wireless Sensor Networks 08 Hours

Operating System: TinyOS, Imperative Language: nesC, Dataflow Style Language: TinyGALS, Node-

Level Simulators, ns-2 and its Sensor Network Extension, TOSSIM.

Unit V Sensor Network Databases 08 Hours

Sensor Network Databases : Challenges ,Query Interfaces, High level Database Organization, In-

Network Aggregation, Data-centric Storage, Temporal Data.

Books:

Text:

1. Wireless Sensor Networks: An Information Processing Approach, Feng Zhao, Leonidas Guibas,

Elsevier Science Imprint, Morgan Kauffman Publishers, 2005, rp2009.

Reference:

60

1. Adhoc Wireless Networks: Architectures and Protocols, C.Siva Ram Murthy, B.S.Murthy, Pearson

Education, 2004

2. Wireless Sensor Networks: Principles and Practice, Fei Hu, Xiaojun Cao, An Auerbach Book, CRC

Press, Taylor & Francis Group, 2010

3. Wireless Ad hoc Mobile Wireless Networks: Principles, Protocols and Applications, Subir Kumar

Sarkar et al., Auerbach Publications, Taylor & Francis Group, 2008.

4. Wireless Sensor Networks: Signal Processing and Communications Perspectives

61


Third Year of Information Technology (2018 Course)

BITL306 –D– Mobile Operating System

Teaching Scheme:

TH: 03 Hours/Week

TU:---Hour/Week

Credit

03

Examination Scheme:

TAE: 20 Marks

CAE: 20 Marks

ESE: 60 Marks

Prerequisite:- Computer Networks,Operating System

Course Objectives:

1. To provide a thorough introduction to the Android environment and tools for creating

Android applications.

2. To impart knowledge of Objective-C and Apple iOS application design and development.

Course Outcomes:


1. Learn existing mobile operating systems.

2. capable to develop, manage and maintain mobile device based application

3. Learn the various platforms for mobile operating systems.

4. Recognize the recent trends in mobile operating system in different disciplines

Course Contents

Unit I Introduction to Mobile Devices 08 Hours

Mobile devices: Device Overview, Input mechanism, Wireless communication, Mobile Device

classification Introduction to various mobile deviceOS.Architectures for mobile computing. Mobile

Generations: Devices and Applications for: 1G, 2G, 2.5G, 3G

Unit II MOBILE APPLICATION ARCHITECTURES 08Hours

Choosing the right architecture: Application architecture, Device type, Enterprise connectivity,

Enterprise data, Enterprise integration, User notification, security, battery life

Application Architectures: Wireless internet, Smart Client, messaging

Smart Client Overview: architecture

Smart Client Development process: Need analysis phase, design phase, implementation and testing

phase, deployment phase

Unit III Introduction to Android and Working with Basic UI 10 Hours

Evaluation of Android and OHA

Architecture of Android OS, Introduction to Android SDK, Android Development tools : The Android

Virtual Device and SDK Manager, The Android Emulator, Dalvik Debug Monitor

Service (DDMS), The Android Debug Bridge (ADB), Android Application Structure: AndroidManifest.xml,

Resources,& R.java, Assets, Layouts &Drawable Resources, .apk structure

Working with Basic UI in with Android Activity, Widgets, Layouts

Menus: Option menu, Context menu, Sub menu Adapters for data binding

Unit IV Android Application Components& Data

Persistency

08 Hours

Android Activity and Activity lifecycle ,Fragments , Intents , Android Services and Activity lifecycle ,

Broadcasting events and actions , Data Persistency in Android ,Working with SQLite Database ,Content

Provider and its operations

Unit V Introduction to iOS and Objective-C Basics 08 Hours

62

Introduction to Mac OS architecture ,installing iPhone SDK , Components of SDK ,Objective-C basics ,

Classes, Objects, and Methods , Data Types and Expressions , Control Structures , Inheritance ,

Categories & Protocols

Unit V Building basic iOS apps & Working with X-code 8 Hours

Building basic iOS applications , Interface builder , Action, Outlets, Delegates, View Controllers ,

Designing Basic UI , UI event handing ,Working with X-code ,Building and running iOS program , Using

iPhone simulator , Debugging & working with console

Books:

Text:

1. Beginning Android 4 Application Development, WEI-MENG LEE, WROX Publication-Wiley-India

2. Professional Android 4 Application Development by Reto Meier WROX Publication-Wiley-India, 2012

3. Android Programming Unleashed, B.M. Harwani ,Sams Publishing

4. Beginning Android 4 OnurCinarApressPublication

Reference:

1. Programming in Objective-C 2.0 by Stephen Kochan, Addison- Wesley publication, 2009

2. Beginning iPhone SDK Programming with Objective-C, Wei- Meng Lee, Wrox

3. iOS 5 Programming Cookbook by VandadNahavandippor, O’reilly Publication

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