curriculum of vii-viii semester
TRANSCRIPT
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
CURRICULUM OF VII-VIII SEMESTER
ACADEMIC YEAR 2020 – 21
Department: Information Science and Engineering
Semester: 7
Sl. No Subject Code Name of the Subject L T P S C
1 IS7T01 Mobile Application Development 4 0 0 0 4
2 CS7T02 Web Technologies 3 2 0 0 4
3 IS7T03 File Structures 3 0 0 1 4
4 CS7PE4XY /
IS7PE4XY Professional Elective - II 3 0 0 0 3
5 CS7PE5XY /
IS7PE5XY Professional Elective - III 3 0 0 0 3
6 IS7L01 Machine Learning Laboratory 0 0 3 0 1.5
7 CS7L02 Web Technology Laboratory 0 0 3 0 1.5
8 CS7PW01 Project Work Phase - I 0 8 0 0 4
Total 16 10 6 1 25
Professional Elective – II Credits: 3-0-0-0-3
Subject Code Name of the Subject
CS7PE411 Software Testing
IS7PE412 Natural Language Processing
IS7PE413 Multimedia Computing
IS7PE414 Network Analysis and Management
Professional Elective – III Credits: 3-0-0-0-3
Subject Code Name of the Subject
IS7PE521 Distributed Computing Systems
IS7PE522 Soft and Evolutionary Computing
CS7PE523 Agile Technologies
IS7PE524 Software Project Management
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: MOBILE APPLICATION DEVELOPMENT
Subject Code: IS7T01 L-T-P-S-C: 4-0-0-0-4
Course Objectives:
Sl. No Course Objectives
1 Learn the basic environment of an Android app.
2
Illustrate the user interface and app functionality.
3 Interpret the techniques of app data access and persistence.
4 Appraise the testing and publishing of an app.
UNIT Description Hours
I
Mobility and Android: Introduction, Mobility Panorama, Mobile
Platforms, App Development Approaches, Android Overview.
Getting Started with Android: Introduction, Setting up Development
Environment, Saying Hello to Android, Traversing an Android App
Project Structure, Logical Components of an Android App, Android Tool
Repository, Installing and Running App Devices. Learning with an
Application - 3CheersCable: Introduction, 3CheersCable App, Mobile
App Development Challenges, Tenets of a Winning App.
8
II
App User Interface: Introduction, Activity, UI Resources, UI Elements
and Events, Interaction among Activities, Fragments, Action Bar. App Functionality - Beyond UI: Introduction, Threads, AsyncTask,
Service, Notifications, Intents and Intent Resolution, Broadcast Receivers, Telephony and SMS.
12
III
App Data - Persistence and Access: Introduction, Flat Files, Shared Preferences, Relational Data, Data Sharing Across Apps, Enterprise Data. Graphics and Animation: Introduction, Android Graphics, Android Animation.
12
IV
Multimedia: Introduction, Audio, Video and Images, Playback 185, Capture and Storage. Location Services and Maps: Introduction, Google Play Services, Location Services, Maps.
10
V
Sensors: Introduction, Sensors in Android, Android Sensor
Framework, Motion Sensors, Position Sensors, Environment Sensors.
Testing Android Apps: Introduction, Testing Android App Components, App Testing Landscape Overview. Publishing Apps:
Introduction, Groundwork, Configuring, Packaging, Distributing.
10
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Text Book:
Sl No Title Author Volume and Year
of Edition
1 Composing Mobile Apps: Learn|
Explore|Apply using Android
Anubhav Pradhan,
Anil V. Deshpande
Wiley, First Edition-
2014
Reference Books:
Sl No Title Author Volume and Year
of Edition
1 Android Application Development
All in one for Dummies
Barry Burd Edition: 1st Edition
2 Teach Yourself Android
Application Development in 24
Hours
1st Edition,
Publication SAMS
Course Outcomes:
Course
outcome Descriptions
CO1 Able to understand various approaches and technologies for app
development.
CO2 Capable of understanding, designing app user interface and
implementing app functionality.
CO3 Able to develop location services using device sensors while building
android apps.
CO4 Capable of validating, packaging and moving apps to market.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: WEB TECHNOLOGIES
Subject Code: CS7T02 L-T-P-S-C: 3-2-0-0-4
Course Objectives:
Sl. No
Course Objectives
1 Illustrate the Semantic Structure and Compose different tags using XHTML.
2 Define and use user-defined tags for creating a XML framework.
3 Design Client-Side programs using JavaScript.
4 Design Server Side programs using PHP and to infer PHP‟s capabilities to
access database.
UNIT Description Hours
I
INTRODUCTION to XHTML Origins and Evolution of HTML and XHTML, Basic Syntax, Standard HTML Document Structure, Basic Text Markup, Images, Hypertext Links, Lists, Tables, Forms, The audio Element, The video Element, Organization Elements, The time Element, Syntactic Differences between HTML and XHTML.
8
II
Introduction to XML Introduction, Uses of XML, The Syntax of XML, XML Document Structure, Namespaces, XML Schemas, Displaying Raw XML Documents, Displaying XML Documents with CSS, XSLT Style Sheets, XML Processors, Web Services.
8
III
The Basics of JavaScript
Overview of JavaScript, Object Orientation and JavaScript, General Syntactic Characteristics, Primitives, Operations, and Expressions, Screen Output and Keyboard Input, Control Statements, Object Creation and Modification, Arrays, Functions , An Example , Constructors , Pattern Matching Using Regular Expressions, Another Example, Errors in Scripts.
8
IV
JavaScript and HTML Documents The JavaScript Execution Environment, The Document Object Model, Element Access in JavaScript, Events and Event Handling, Handling Events from Body Elements, Handling Events from Button Elements, Handling Events from Text Box and Password Elements, The DOM 2 Event Model, The canvas Element, The navigator Object, DOM Tree Traversal and Modification.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
V
Introduction to PHP Origins and Uses of PHP, Overview of PHP, General Syntactic
Characteristics, Primitives, Operations, and Expressions, Output, Control Statements, Arrays, Functions, Pattern Matching, Form Handling, Cookies, Session Tracking, Database Access with PHP and MySQL.
7
Text Book:
Sl No
Title Author Volume and Year of
Edition
1 Programming the World Wide
Web
Robert W. Sebesta 8th Edition, Pearson
Education, 2015
ISBN-13: 978-0-13-
377598-3
Reference Books:
Sl No
Title Author Volume and Year of
Edition
1
Professional JavaScript for Web Developers
Nicholas C Zakas 3rd Edition,
Wrox/Wiley India, 2012,
ISBN-13:
9788126535088
2
Fundamentals of Web
Development
Randy Connolly,
Ricardo Hoar
Pearson Education,
Inc., 2016, ISBN:
9789332575271, ISSN:
9332575274
3 Open Source Web Development
with LAMP
James Lee and
Brent Ware
Pearson Education,
Inc., 2002, ISBN-13: 978-
0201770612
Course Outcomes:
Course
outcome Descriptions
CO1 Develop Web Pages, Host web site and Deploy web based applications
using various web technologies.
CO2 Design topic – specific markup languages and understand web services.
CO3 Implement, Invoke and develop server side objects using PHP to generate
and display the content dynamically.
CO4 Understand, Implement and develop client side objects using JavaScript
and to achieve an interactive web page.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: FILE STRUCTURES
Subject Code: IS7T03 L-T-P-S-C: 3-0-0-1-4
Course Objectives:
Sl. No Course Objectives
1 Understand the techniques for organization and manipulation of
data in secondary storage.
2
Understand and analyze the high-level file structures tools which include
indexing, co-sequential processing, B trees, B+ trees, Hashing and Extendable Hashing.
3 Select the appropriate data structure and file structure for proper File
organization.
4 Build the structure, retrieving selected data, updating and maintaining
the appropriate structure.
UNIT Description Hours
I
Fundamental File Structure Concepts, Managing Files of Records: File Structures: The Heart of the file structure Design, A Short History of File Structure Design, A Conceptual Toolkit; Fundamental File Operations: Physical Files and Logical Files, Opening Files, Closing Files, Reading and Writing, Seeking, UNIX file System Commands. Storage as Hierarchy, A journey of a Byte, Buffer Management, Field and Record Organization, Using Classes to Manipulate Buffers, Using Inheritance for Record Buffer Classes, Managing Fixed Length, Fixed Field Buffers, An Object-Oriented Class for Record Files, Record Access, More about Record Structures, Encapsulating Record Operations in a Single Class, File Access and File Organization.
8
II
Organization of Files for Performance, Indexing: Data Compression, Reclaiming Space in files, Internal Sorting and Binary Searching, Key sorting; what is an Index? A Simple Index for Entry- Sequenced File, Template Classes in C++, Object-Oriented support for Indexed, Entry-Sequenced Files of Data Objects, Indexes that are too large to hold in Memory, Indexing to provide access by Multiple keys, Retrieval Using Combinations of Secondary Keys, Improving the Secondary Index structure, Inverted Lists, Selective indexes, Binding.
7
III
Co-sequential Processing and the Sorting of Large Files: A Model for Implementing Consequential Processes, Application of the Model to a General Ledger Program, Extension of the Model to include
Multi-way Merging, A Second Look at Sorting in Memory.
7
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
IV
Multi-Level Indexing and B-Trees, Indexed Sequential File Access
and Prefix B +TREES:
Introduction; Indexing with Binary Search Trees; Multi-Level Indexing; B- Trees; Example of Creating a B-Tree, An Object-Oriented Representation of B-Trees, B-Tree Methods; Nomenclature, Formal Definition of B-Tree Properties, Worst-case Search Depth, Deletion, Merging and Redistribution during insertion; A Way to improve storage utilization, B* Trees, Buffering of pages; Virtual B-Trees; Variable-length Records and keys. Indexed Sequential Access, Maintaining a Sequence Set, Adding a Simple Index to the Sequence Set, The Content of the Index: Separators Instead of Keys, The Simple Prefix B+ Tree and its maintenance, Index Set Block Size, Internal Structure of Index Set Blocks: A Variable-order B- Tree, Loading a Simple Prefix B+ Trees, B+ Trees, B+ Trees and Simple Prefix B+ Trees in Perspective.
9
V
Hashing, Extendible Hashing:
Introduction, A Simple Hashing Algorithm, Hashing Functions and Record Distribution, How much Extra Memory should be used?, Collision resolution by progressive overflow, Buckets, Making deletions, Other collision resolution techniques, Patterns of record access. How Extendible Hashing Works, Implementation, Deletion, Extendible Hashing Performance, Alternative Approaches.
8
Text Book:
Sl No
Title Author Volume and Year of
Edition
1
File Structures-An Object Oriented Approach with C++
Michael J. Folk, Bill
Zoellick, Greg
Riccardi
3rd Edition, Pearson,
Reference Books:
Sl No
Title Author Volume and Year of
Edition
1
File Structures Using C++ K.R. Venugopal,
K.G. Srinivas, P.M.
Krishnaraj
Tata McGraw-Hill, 2017
2 The C++ Programming
Language
Bjarne Stroustrup 3rd Edition, Pearson, 2018
Course Outcomes:
Course
outcome Descriptions
CO1 Describe the Concept of File Structures and File Organization
Techniques.
CO2 Apply the Concepts of File Structures in the Data Storage and
Manipulation Techniques.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
CO3 Analyze and Choose field structures and record structures to different
applications.
CO4 Use high level file structure to provide solution building, retrieving and
updating files.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: SOFTWARE TESTING
Subject Code: CS7PE411 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Learn the design of test cases.
2 Investigate the reason for bugs and analyze the principles in software testing to prevent and remove bugs.
3 Learn to apply software testing techniques in commercial environment.
4 Expose how to plan a test project, design test cases and data, conduct testing operations, manage software problems and defects and generate a testing report.
UNIT Description Hours
I
A Perspective on Testing: Basic definitions, Test cases, Insights from
a Venn diagram, Identifying test cases, Error and fault taxonomies,
Levels of testing.(1.1 to 1.6) Examples: Generalized pseudo code, The
triangle problem, The NextDate function, The commission problem,
The SATM (Simple Automatic Teller Machine) problem, The currency
converter, Saturn windshield wiper (2.1 to 2.7).
8
II
Boundary Value Testing: Boundary value analysis, Robustness testing, Worst-case testing, Special value testing, Examples, Random testing (5.1 to 5.6) Equivalence Class Testing: Equivalence test cases for the triangle problem, NextDate function, and the commission problem, Guidelines and observations 6.4 to 6.8). Decision Table-Based Testing: Decision tables, Test cases for the triangle problem, Next Date function, and the commission problem, Guidelines and observations (7.1 to 7.5 and 7.7).
8
III
Path Testing, Data Flow Testing and Life Cycle - Based Testing Path Testing: DD paths, Test coverage metrics, Basis path testing,
guidelines and observations (8.1 to 8.4). Data Flow Testing: Definition-Use testing, Slice-based testing (9.1 and 9.2) Life Cycle - Based Testing: Traditional Waterfall Testing, Testing in Iterative Life Cycles, Agile Testing, Agile Model–Driven Development (11.1 to 11.4).
7
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
IV
Integration Testing: Decomposition-Based Integration, Call Graph–
Based Integration, Path-Based Integration, Example: integration
NextDate (13.1 to 13.4), System Testing: Threads, Basis Concepts for
Requirements Specification, Model-Based Threads, Use Case–Based
Threads, Long versus Short Use Cases (14.1 to 14.5).
8
V
Test and Analysis Activities within a Software Process: The quality process, Planning and monitoring, Quality goals, Dependability properties, Analysis, Testing, Improving the process, Organizational factors (4.1 to 4.8). Fault- Based Testing: Overview, Assumptions in fault-based testing, Mutation analysis, Fault-based adequacy criteria, Variations on mutation analysis 16.1 to 16.5). Test Execution: Overview, From test case specifications to test cases, Scaffolding, Generic versus specific scaffolding, Test oracles, Self-checks as
oracles, Capture and replay (17.1 to 17.7).
8
Text Books:
Sl
No Title Author
Volume and Year of
Edition
1 Software Testing: A Craftsman’s Approach
Paul C. Jorgensen 4th Edition, Auerbach Publications, 2013, ISBN-10: 1466560681
2 Software Testing and Analysis : process, Principles and Techniques
Mauro Pezze, Michal Young
1st Edition, Wiley India, 2008, ISBN-13: 9788126517732 ISBN-10: 8126517735
Reference Books:
Sl
No Title Author
Volume and Year of
Edition
1
Foundations of Software Testing Aditya P Mathur 1st Edition, Pearson Education, 2012, ISBN: 8131707954, 9788131707951
2 Software testing Principles and Practices
Srinivasan Desikan, Gopalaswamy Ramesh
2nd Edition, Pearson Education, 2007, ISBN: 9788177581218
3
The Craft of Software Testing Brian Marrick 1st Edition, MARICK, 1995 ISBN: 813171571X, 9788131715710
Course Outcomes:
Course outcome
Descriptions
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
CO1 Clear understanding and knowledge of the foundations, techniques in the area of software testing and its practice in the industry.
CO2 Compare and pick out the right type of software testing process for any given real world problem.
CO3 Able to plan a test project, design test cases, conduct testing operations, manage software problems and defects.
CO4 Implement various test processes for quality improvement.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: NATURAL LANGUAGE PROCESSING
Subject Code: IS7PE412 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Learn the techniques in natural language processing.
2 Be familiar with the natural language generation.
3 Be exposed to Text Mining.
4 Understand the information retrieval techniques
UNIT Description Hours
I
Overview and language modeling: Overview: Origins and challenges of NLP Language and Grammar-Processing Indian Languages- NLP Applications-Information Retrieval. Language Modeling: Various Grammar- based Language Models-Statistical Language Model.
7
II
Word level and syntactic analysis: Word Level Analysis: Regular Expressions- Finite-State Automata- Morphological Parsing-Spelling Error Detection and correction-Words and Word classes-Part-of Speech Tagging. Syntactic Analysis: Context-free Grammar-Constituency- Parsing-Probabilistic Parsing.
7
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
III
Extracting Relations from Text: From Word Sequences to Dependency Paths: Introduction, Subsequence Kernels for Relation Extraction, A Dependency- Path Kernel for Relation Extraction and Experimental Evaluation. Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles: Introduction, Domain Knowledge and Knowledge Roles, Frame Semantics and Semantic Role Labeling, Learning to Annotate Cases with Knowledge Roles and Evaluations. A Case Study in Natural Language Based Web Search:
In Fact System Overview, the GlobalSecurity.org Experience.
8
IV
iSTART: Evaluation of Feedback Systems, Textual Signatures: Identifying Text-Types Using Latent Semantic Analysisto Measure the Cohesion of Text Structures: Introduction, Cohesion, Coh-Metrix, Approaches to Analyzing Texts, Latent Semantic Analysis,
Predictions, Results of Experiments. Automatic Document Separation: A Combination of Probabilistic Classification and
Finite-State Sequence Modeling: Introduction, Related Work, Data Preparation, Document Separation as a Sequence Mapping Problem,
Results. Evolving Explanatory Novel Patterns for Semantically-Based Text Mining: Related Work, A Semantically Guided Model for Effective Text Mining.
8
V
Information Retrieval and Lexical Resources: Information Retrieval: Design features of Information Retrieval Systems- Classical, Non classical, Alternative Models of Information Retrieval – valuation Lexical Resources: World Net-Frame Net- Stemmers-POS Tagger- Research Corpora.
9
Text Books:
Sl No
Title Author Volume and Year of
Edition
1 Natural Language Processing and Information Retrieval
Tanveer Siddiqui, U.S. Tiwary
Oxford University Press, 2008
2 Natural Language Processing and Text Mining
Anne Kao and Stephen R.Poteet
(Eds)
Springer-Verlag London Limited 2007.
Reference Books:
Sl No
Title Author Volume and Year of
Edition
1
Speech and Language Processing: An introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
Daniel Jurafsky and James H Martin
2nd Edition, Prentice Hall, 2008.
2 Natural Language
Understanding
James Allen 2ndEdition, Benjamin / Cummings publishing company, 1995
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
3 Information Storage and Retrieval systems
Gerald J. Kowalski and Mark.T.
Maybury
Kluwer academic Publishers, 2000.
Course Outcomes:
Course outcome
Descriptions
CO1 Understand and analyze the natural language text.
CO2 Generate the natural language and apply word level and syntactic level
analysis.
CO3 Make use of Text mining and generate report.
CO4 Apply information retrieval techniques.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: MULTIMEDIA COMPUTING
Subject Code: IS7PE413 L-T-P-S-C: 3-0–0-0-3
Course Objectives:
Sl. No Course Objectives
1 Learn and understand technical aspect of Multimedia Systems.
2 Understand the standards available for different audio, video and text applications.
3 Design and develop various Multimedia Systems applicable in
realtime.
4 Learn various multimedia authoring systems.
UNIT Description Hours
I
Introduction, Media and Data Streams, Audio Technology: Multimedia Elements; Multimedia Applications; Multimedia Systems Architecture; Evolving Technologies for Multimedia Systems; Defining Objects for Multimedia Systems; Multimedia Data Interface Standards; The need for Data Compression; Multimedia Databases. Media: Perception Media, Representation Media, Presentation Media, Storage Media, Transmission Media, Information Exchange Media, Presentation Spaces & Values, and Presentation Dimensions; Key Properties of a Multimedia System: Discrete & Continuous Media, Independence Media, Computer Controlled Systems, Integration; Characterizing Data Streams: Asynchronous Transmission Mode, Synchronous Transmission Mode, Isochronous Transmission Mode; Characterizing Continuous Media Data Streams. Sound: Frequency, Amplitude, Sound Perception and Psychoacoustics; Audio
Representation on Computers; Three Dimensional Sound Projection; Music and MIDI Standards; Speech Signals; Speech Output; Speech Input; Speech Transmission.
8
II
Graphics and Images, Video Technology, Computer-Based Animation: Capturing Graphics and Images Computer Assisted Graphics and Image Processing; Reconstructing Images; Graphics and Image Output Options. Basics; Television Systems; Digitalization of Video Signals; Digital Television; Basic Concepts; Specification of Animations; Methods of Controlling Animation; Display of Animation; Transmission of Animation; Virtual Reality Modeling Language.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
III
Data Compression 1: Storage Space; Coding Requirements; Source, Entropy, and Hybrid
Coding; Basic Compression Techniques; JPEG: Image Preparation, Lossy Sequential DCT-based Mode, Expanded Lossy DCT-based Mode, Lossless Mode, Hierarchical Mode. Data Compression 2: H.261 (Px64) and H.263: Image Preparation, Coding Algorithms, Data Stream, H.263+ and H.263L; MPEG: Video Encoding, Audio Coding, Data Stream, MPEG-2, MPEG-4, MPEG-7; Fractal Compression.
8
IV
Optical Storage Media: History of Optical Storage; Basic Technology; Video Discs and Other WORMs; Compact Disc Digital Audio; Compact Disc Read Only Memory; CD-ROM Extended Architecture; Further CD-ROM-Based Developments; Compact Disc Recordable; Compact Disc Magneto-Optical; Compact Disc Read/Write; Digital Versatile Disc. DATA AND
FILE FORMAT STANDARDS: Rich-Text Format; TIFF File Format; Resource Interchange File Format (RIFF); MIDI File Format; JPEG DIB File Format for Still and Motion Images; AVI Indeo File Format; MPEG Standards; TWAIN.
7
V
Content Analysis: Simple Vs. Complex Features; Analysis of Individual Images; Analysis
of Image Sequences; Audio Analysis; Applications. MULTIMEDIA
APPLICATION DESIGN: Multimedia Application Classes; Types of Multimedia Systems; Virtual Reality Design; Components of Multimedia Systems; Organizing Multimedia Databases; Application Workflow Design Issues; Distributed Application Design Issues.
8
Text Books:
Sl
No Title Author Volume and Year of Edition
1
Multimedia
Fundamentals
Ralf Steinmetz, Klara
Narstedt:
Vol 1-Media Coding andContent
Processing, 2nd Edition, Pearson
Education, 2003.Chapters 2,3,4,
5, 6, 7, 8, 9).
2 Multimedia Systems
Design
Prabhat K. Andleigh,
Kiran Thakrar
PHI, 2003. (Chapters 1, 3,7)
Reference Books:
Sl No
Title Author Volume and Year of Edition
1
Multimedia
Communication
Systems: Techniques,
Standards, and
Networks
K.R Rao, Zoran S.
Bojkovic and
Dragorad A.
Milovanovic
Pearson Education, 2002
2
Multimedia
Information
Networking
Nalin K Sharad: PHI, 2002.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Course Outcomes:
Course outcome
Descriptions
CO1 Know the challenges of handling media files.
CO2 Able to use different compression techniques to reduce the storage space
for media files.
CO3 Use different techniques to ensure better quality of audio and video
stream.
CO4 Understand the need for different types of file formats for audio and video
data.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: NETWORK ANALYSIS AND MANAGEMENT
Subject Code: IS7PE414 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Learn network devices functions and configurations hub, switch, tap and
routers.
2 Be familiar with network Security Devices.
3 Be exposed to network services.
4 Understand and analyze application performance.
UNIT Description Hours
I
A System Approach to Network Design and Requirement Analysis: Introduction-Network Service and Service based networks- Systems and services- characterizing the services. Requirement Analysis: Concepts – Background–User Requirements- Application Requirements- Host Requirements-Network Requirements – Requirement Analysis: Guidelines – Requirements gathering and listing- Developing service metrics to measure performance – Characterizing behavior- developing performance threshold – Distinguish between service performance levels. Requirement Analysis: Practice –Template, table and maps –simplifying the
requirement analysis process –case study.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
II
Flow Analysis: Concepts, Guidelines and Practice : Background-
Flows- Data sources and sinks- Flow models- Flow boundaries- Flow
distributions- Flow specifications- Applying the flow model-
Establishing flow boundaries-Applying flow distributions- Combining
flow models, boundaries and distributions- Developing flow
specifications-prioritizing flow- simplifying flow analysis process –
examples of applying flow specs- case study.
8
III
Logical Design: Choices, Interconnection Mechanisms, Network
Management and Security: Background- Establishing design goals- Developing criteria for technology evolution- Making technology choices for design-case study- Shared Medium- Switching and Routing: Comparison and contrast- Switching- Routing-Hybrid Routing/Switching Mechanisms – Applying Interconnection Mechanism to Design – Integrating Network management and security
into the Design- Defining Network Management- Designing with manageable resources- Network Management Architecture- Security- Security mechanism- Examples- Network Management and security plans- Case study.
8
IV
Network design: physical, addressing and routing: Introduction-
Evaluating cable plant design options – Network equipment placement-
diagramming the physical design- diagramming the worksheet – case
study. Introduction to Addressing and routing- establishing routing
flow in the design environments- manipulating routing flows-
developing addressing strategies- developing a routing strategy- case
study.
8
V
Network Management and SNMP Protocol Model: Network and
System management, Network management system platform; Current
SNMP Broadband and TMN management, Network management
standards. SNMPV1, SNMPV2 system architecture, SNMPV2, structure
of management information. SNMPV2 – MIB – SNMPV2 protocol,
SNMPV3- Architecture, Application, MIB, security user based security
model, access control RMON.
7
Text Books:
Sl No
Title Author Volume and Year of
Edition
1 “Practical Computer Network
Analysis and Design”
James.D.McCabe 1st Edition,Morgan
Kaufaman, 1997.
2 “Network Management –
Principles & Practice”
Mani Subramanian 2nd Edition Prentice
Hall, 2012.
Reference Books:
Sl
No Title Author
Volume and Year
of Edition
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
1 Fundamentals of Computer Network Analysis and Engineering: Basic Approaches for Solving Problems in the Networked Computing Environment
J.Radz, Universe, 2005.
2 Networks: An Introduction
Mark Newman Kindle Edition, 2010.
3 Wireshark 101: Essential Skills for Network Analysis
Laura Chappel
and Gerald
Combs
Kindle Edition, 2013.
4 SNMP, SNMP2, SNMP3 and RMON1 and 2
William Stallings
Pearson Education, 2004.
5 Network Management DawSudira Sonali Publications, 2004.
Course Outcomes:
Course outcome
Descriptions
CO1 Explain the key concepts and algorithms in complex network analysis.
CO2 Apply a range of techniques for characterizing network structure.
CO3 Discuss methodologies for analyzing networks of different fields.
CO4 Describe network management protocol models.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: DISTRIBUTED COMPUTING SYSTEMS
Subject Code: IS7PE521 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1
Explain distributed system, their characteristics, challenges and system models.
2
Describe IPC mechanisms to communicate between distributed objects.
3
Illustrate the operating system support and File Service architecture in a distributed system.
4
Analyze the fundamental concepts, algorithms related to synchronization.
UNIT Description Hours
I
Characterization of Distributed Systems:
Characterization of Distributed Systems: Introduction, Examples of DS,
Resource sharing and the Web, Challenges. System Models: Architectural
Models, Fundamental Models.
8
II
Inter Process Communication and Distributed Objects and RMI:
Inter Process Communication: Introduction, API for Internet Protocols,
External Data Representation and Marshalling, Client – Server
Communication, Group Communication .Distributed Objects and RMI:
Introduction, Communication between Distributed Objects, RPC, Events and
Notifications.
8
III
Operating System Support and Distributed File Systems:
Operating System Support: Introduction, the OS layer, Protection, Processes
and Threads, Communication and Invocation, Operating system architecture.
Distributed File Systems: Introduction, File Service architecture, Sun Network file systems.
7
IV
Time and Global States and Coordination and Agreement:
Time and Global States: Introduction, Clocks, events and process status,
Synchronizing physical clocks, Logical time and logical clocks, Global states.
Coordination and Agreement: Introduction, Distributed mutual exclusion,
elections.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
V
Distributed Transactions:
Distributed Transactions: Introduction, Flat and nested distributed
transactions, Atomic commit protocols, Concurrency control in distributed
transactions, distributed deadlocks.
8
Text Book:
Sl No
Title
Author
Volume and Year of Edition
1 Distributed Systems – Concepts and
Design,
George Coulouris,
Jean Dollimore and
Tim Kindberg
5th Edition, Pearson
Publications, 2009.
Reference Books:
Sl
No
Title
Author
Volume and Year
of Edition
1 Distributed Operating Systems Andrew S Tanenbaum 3 rd edition, Pearson
publication, 2007.
2 Distributed Computing: Principles,
Algorithms andSystems,
Ajay D. Kshemkalyani and
MukeshSinghal,
Cambridge
University Press,
2008.
3 “Distributed Computing” Sunita Mahajan, Seema Shan
Oxford University Press, 2015.
Course Outcomes:
Course
outcome Descriptions
CO1 Explain the characteristic of a distributed system along with its and design Challenges.
CO2 Illustrate the mechanism of IPC between distributed objects.
CO3 Describe the distributed file service architecture and the important characteristics of SUN NFS.
CO4 Discuss concurrency control algorithms applied in distributed transactions.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: SOFT AND EVOLUTIONARY COMPUTING
Subject Code: IS7PE522 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1
Familiarize with the basic concept of soft computing and intelligent systems.
2 Compare with various intelligent systems.
3 Analyze the various soft computing techniques.
4
Understand the concepts of fuzzy logic and other machine intelligence applications.
UNIT Description Hours
I
Introduction to soft computing: ANN, FS,GA, SI, ES, Comparing among
intelligent systems ANN: introduction, biological inspiration, BNN&ANN,
classification, first Generation NN, perceptron, illustrative problems
Text Book 1: Chapter1: 1.1-1.8, Chapter2: 2.1-2.6
8
II
Adaline, Medaline, ANN: (2nd generation), introduction, BPN, KNN, HNN,
BAM, RBF, SVM and illustrative problems
Text Book 1: Chapter2: 3.1,3.2,3.3,3.6,3.7,3.10,3.11
8
III
Fuzzy logic: introduction, human learning ability, undecidability, probability
theory, classical set and fuzzy set, fuzzy set operations, fuzzy relations, fuzzy
compositions, natural language and fuzzy interpretations, structure of fuzzy
inference system, illustrative problems
Text Book 1: Chapter 5
9
IV
Introduction to GA, GA, procedures, working of GA, GA applications,
applicability, evolutionary programming, working of EP, GA based Machine
learning classifier system, illustrative problems
Text Book 1: Chapter 7
7
V
Swarm Intelligent system: Introduction, Background of SI, Ant colony
system Working of ACO, Particle swarm Intelligence (PSO).
Text Book 1: 8.1-8.4, 8.7
7
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Text Book:
Sl No
Title
Author
Volume and Year of Edition
1 Soft computing N. P Padhy and S P
Simon
Oxford University
Press 2015
Reference Book:
Sl
No
Title
Author
Volume and Year
of Edition
1 Principles of Soft Computing Shivanandam, Deepa
S. N
Wiley India, ISBN
13: 2011
Course Outcomes:
Course
outcome Descriptions
CO1 Understand soft computing techniques.
CO2 Apply the learned techniques to solve realistic problems.
CO3 Differentiate soft computing with hard computing techniques.
CO4 Hybridize the Neural Network and fuzzy logicto form aNeuro-fuzzy Networks.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: AGILE TECHNOLOGIES
Subject Code: CS7PE523 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Understand the background and driving forces for taking an Agile approach to software development.
2 Understand the business value of adopting Agile approaches and the Agile development practices.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
3 Learn design principles, refactoring, automated build tools, version control and continuous integration.
4 Understand testing activities within an Agile project.
UNIT Description Hours
I
Fundamentals of Agile:
The Genesis of Agile, Introduction and background, Agile Manifesto and
Principles, Overview of Scrum, Extreme Programming, Feature Driven
development, Lean Software Development, Agile project management, Design
and development practices in Agile projects, Continuous Integration,
Refactoring, Pair Programming, Simple Design.
8
II
Agile Scrum Framework:
Introduction to Scrum, Project phases, Agile Estimation, Planning game,
Product backlog, Sprint backlog, Iteration planning, User Stories,
Characteristics and content of user stories, Project velocity, Burn down chart,
Sprint planning and retrospective, Daily scrum, Scrum roles – Product Owner,
Scrum Master, Scrum Team, Key challenges to implementing Agile
Development and Project management Frameworks.
8
III
Agile Software Design and Development:
Agile design practices, Difference between Agile and Traditional Approach,
Role of design Principles including Single Responsibility Principle, Open
Closed Principle, Liskov Substitution Principle, Dependency Inversion
Principle in Agile Design, Interface Segregation Principles, Refactoring
Techniques, Automated build tools, Version control.
7
IV
Agile Testing:
Agile Testing, How is Agile Testing Different, Ten Principles for Agile
Testers, Agile Testing Quadrants, Test-Driven Development(TDD), TDD
Lifecycle, Acceptance tests, Managing testing cycle, Exploratory testing, Risk
based testing, Regression tests, Why Automation, Tools to support the Agile
tester.
8
V
Industry Trends:
Agile Marketing, Challenges in Enterprise adoption of Agile methods, Agile
ALM, Roles in an Agile project, Agile applicability framework, Agile in
Distributed teams, Challenges in Agile, Agile methodology with cloud
computing, Balancing Agility with Discipline, Agile rapid application
development technologies.
8
Text Books:
Sl No
Title Author Volume and Year of Edition
1 Agile Software Development with Scrum.
KenSchawber, Mike Beedle
1st Edition, Prentice Hall, 2001, ISBN: 0130676349,
9780130676344
2 Agile Testing: A Practical Guide for Testers and Agile Teams.
Lisa Crispin, Janet Gregory
1st Edition, Pearson Education,2010, ISBN: 9788131730683
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
3 Agile Software Development, Principles, Patterns and Practices.
Robert C. Martin 1st Edition, Pearson, 2011, ISBN:9780132760584, 0132760584
Reference Books:
Sl No
Title Author(s) Edition, Publisher, Year, ISBN
1 Agile Software Development: The Cooperative Game
Alistair Cockburn 2nd Edition, Addison Wesley,2006, ISBN:9780321630070, 0321630076
2 User Stories Applied: For Agile Software
Mike Cohn 1st Edition, Addison Wesley,2004, ISBN:9780321205681,
0321205685
Course Outcomes:
Course outcome
Descriptions
CO1 Interpret the business values of adopting Agile approaches to Software Development.
CO2 Apply agile development practices, design principles and refactoring to achieve agility.
CO3 Deploy automated build tools, version control and continuous integration.
CO4 Perform various testing activities within an Agile project.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: SOFTWARE PROJECT MANAGEMENT
Subject Code: IS7PE524 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Understand the Software Project Planning and Evaluation techniques to manage projects at each stage of the software development life cycle (SDLC).
2 Learn the concepts of activity planning and risk management principles.
3 Manage software projects and control software deliverables.
4
Develop skills to manage the various phases involved in project management and
people management, to deliver successful software projects that support
organization strategic goals.
UNIT Description Hours
I
Project Evaluation and Project Planning:
Importance of Software Project Management – Activities Methodologies –
Categorization of Software Projects – Setting objectives – Management
Principles – Management Control – Project portfolio Management – Cost
benefit evaluation technology – Risk evaluation – Strategic program
Management – Stepwise Project Planning.
8
II
Project Life Cycle and Effort Estimation:
Software process and Process Models – Choice of Process models - mental
delivery – Rapid Application development – Agile methods – Extreme
Programming – SCRUM – Managing interactive processes – Basics of
Software estimation – Effort and Cost estimation techniques – COSMIC Full
function points - COCOMO II A Parametric Productivity Model - Staffing
Pattern.
8
III
Activity Planning and Risk Management:
Objectives of Activity planning – Project schedules – Activities – Sequencing
and scheduling – Network Planning models – Forward Pass & Backward Pass
techniques – Critical path (CRM) method – Risk identification – Assessment –
Monitoring – PERT technique – Monte Carlo simulation – Resource
Allocation – Creation of critical patterns – Cost schedules.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
IV
Project Management and Control:
Framework for Management and control – Collection of data Project
termination – Visualizing progress – Cost monitoring – Earned Value
Analysis-Project tracking–Change control-Software Configuration
Management – Managing contracts – Contract Management.
7
V
Staffing in Software Projects:
Managing people – Organizational behavior – Best methods of staff selection – Motivation – The Oldham-Hackman job characteristic model – Ethical and
Programmed concerns – Working in teams – Decision making – Team
structures – Virtual teams – Communications genres – Communication plans.
8
Text Book:
Sl
No
Title
Author
Volume and Year
of Edition
1 Software Project Management Bob Hughes, Mike
Cotterell andRajib
Mall:
Fifth Edition, Tata
McGraw Hill,New
Delhi, 2012.
Reference Books:
Sl No
Title
Author
Volume and Year of Edition
1 “Effective Software Project Management”
Robert K. Wysocki Wiley Publication, 2011.
2 “Software Project Management” Walker Royce Addison-Wesley,
1998.
3 “Managing Global Software Projects” Gopalaswamy
Ramesh
McGraw Hill
Education (India),
FourteenthReprint 2013.
Course Outcomes:
Course outcome
Descriptions
CO1 Analyze Project Management principles, project management concepts, and framework and software effort estimation techniques.
CO2 Estimate the risks involved in various project activities.
CO3 Define the checkpoints, project reporting structure, project progress and tracking mechanisms using project management principles.
CO4 Plan staff selection process and the issues related to people management.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: BLOCKCHAIN TECHNOLOGY
Subject Code: CS7PE525 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Understand the working of Blockchain systems.
2 Design, build, and deploy smart contracts and distributed applications.
3 Integrate ideas from Blockchain technology into their own projects.
4 Evaluate security, privacy, and efficiency of a given Blockchain system.
UNIT Description Hours
I
Introduction:
Background and history, what is Blockchain? Characteristics of Blockchain,
Do we really need a Blockchain? Applicability of Blockchain, Pros and cons
of Blockchain compared to centralized system.
8
II
Cryptography requirements for Blockchain Hash functions, Asymmetric key
cryptography -Encryption, Decryption, Digital Signature (ECDSA),
Blockchain Architecture - Transaction, Transaction types - UTXO, world state,
Addresses and Address derivation, Private key storage, Ledgers, Merkel trees,
Blocks, Chaining Blocks.
8
III
Blockchain Categorization - Permissonless, Permissioned, Forking issues in
Permissonless Blockchain, Applications considerations for Permissonless /
Permissioned Blockchain, smart contracts, Synchronous and Asynchronous
distributed system, Crash faults, Byzantine faults, Distributed Consensus
mechanism-properties.
8
IV
Consensus for synchronous system, OM and SM synchronous consensus
algorithms, PBFT, Consensus algorithms based on Proof of Work, Proof of
Stake, Proof of Elapsed Time, Round Robin, Proof of Knowledge, History of
Money, Dawn of Bitcoin, Crypto currency.
8
V
Blockchain platforms architecture, transaction-structure, life cycle, block creation,
smart contract, Bitcoin (BTC), Ethereum, Hyper Ledger, CORDA. 7
Reference Papers:
1. Andreas M Antonopoulos, Mastering Bitcoin, O’Reilly Media publications, First Edition,
ISBN: 978-1-449-37404-4, Dec. 2014. (only theory part must be taught, coding not
included).
2. Nancy A. Lynch, Distributed Algorithms, Elsevier, 2013.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
3. Dylan Yaga, Peter Mell, Nik Roby Karen Scarfone , Blockchain Technology Overview-
NISTIR 8202.
4. Karl Wüst, Arthur Gervais, "Do you need a Blockchain?”
https://eprint.iacr.org/2017/375.pdf.
5. Ferguson, Niels, Schneier, Bruce Schneier , Practical Cryptography
6. Castro, M. and Liskov, B. 1999. Practical Byzantine Fault Tolerance. Proc. Usenix OSDI,
Berkeley, California.
7. Satoshi Nakamoto, Bitcoin: A Peer-to-Peer Electronic Cash System,
https://bitcoin.org/bitcoin.pdf.
8. Elli Androulaki, Artem Barger, Vita Bortnikov, Christian Cachin, Kon-stantinos Christidis,
Angelo De Caro, David Enyeart, Christopher Ferris, Gennady Laventman, Yacov
Manevich, et al. Hyperledger fabric: A distributed operating system for permissioned
blockchains. ArXiv, preprint arXiv:1801.10228, 2018.
9. Gavin, Wood, ETHEREUM: A Secure Decentralized Generalized Transaction Ledger,
https://ethereum.github.io/yellowpaper/paper.pdf.
10. Richard Gendal Brown, The Corda Platform: An Introduction,
https://www.corda.net/content/corda-platform-whitepaper.pdf.
Course Outcomes:
Course outcome
Descriptions
CO1 Describe the working of block chain technology and architectures.
CO2 Analyze different smart contracts and distributed applications.
CO3 Compare Synchronous and Asynchronous distributed system.
CO4 Analyze the design principles of Bitcoin and Ethereum.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: MACHINE LEARNING LABORATORY
Subject Code: IS7L01 L-T-P-S-C: 0-0-3-0-1.5
Course Objectives:
Sl. No
Course Objectives
1
Make use of Data sets in implementing the machine learning algorithms
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
2
Implement the machine learning concepts and algorithms in any suitable language of choice.
3
Understand and present the key algorithms and theory that form the core of machine learning.
4
Discuss how the learning performance varies with the number of training examples presented.
Lab
cycles Description
I
Description (If any):
1. The programs can be implemented in either JAVA or Python.
2. For Problems 1 to 6 and 10, programs are to be developed without using the built-in
classes or APIs ofJava/Python.
3. Data sets can be taken from standard repositories
(https://archive.ics.uci.edu/ml/datasets.html) or constructed by the students.
1. Implement and demonstrate the FIND-S algorithm for finding the most specific
hypothesis based on a given set of training data samples. Read the training data
from a .CSVfile.
2. For a given set of training data examples stored in a .CSV file, implement and
demonstrate the Candidate-Elimination algorithm to output a description of the
set of all hypotheses consistent with the training examples.
3. Write a program to demonstrate the working of the decision tree based ID3
algorithm. Use an appropriate dataset for building the decision tree and
apply this knowledge to classify a new sample.
II
4. Build an Artificial Neural Network by implementing the Backpropagation
algorithm and test the same using appropriate datasets.
5. Write a program to implement the naïve Bayesian classifier for a sample training
data set stored as a .CSV file. Compute the accuracy of the classifier, considering
few test datasets.
6. Assuming a set of documents that need to be classified, use the naïve Bayesian
Classifier model to perform this task. Built-in Java classes/API can
beusedtowritetheprogram.Calculatetheaccuracy,precision,andrecallfor
your data set.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
III
7. Write a program to construct a Bayesian network considering medical data. Use
this model to demonstrate the diagnosis of heart patients using standard Heart
Disease Data Set. You can use Java/Python ML libraryclasses/API.
8. Apply EM algorithm to cluster a set of data stored in a .CSV file. Use the same
data set for clustering using k-Means algorithm. Compare the results of these two
algorithms and comment on the quality of clustering. You can add Java/Python ML
library classes/API in the program.
9. Write a program to implement k-Nearest Neighbour algorithm to classify the iris
data set. Print both correct and wrong predictions. Java/Python ML library classes
can be used for this problem.
Implement the non-parametric Locally Weighted Regression algorithm in order to fit
data points. Select appropriate data set for your experiment and draw graphs.
Pattern for practical exam conduction:
Course Outcomes:
Course outcome
Descriptions
CO1 Understand the implementation procedures for the machine learning algorithms.
CO2 Design Java/Python programs for various Learning algorithms.
CO3 Apply appropriate data sets to the Machine Learning algorithms.
CO4 Identify and apply Machine Learning algorithms to solve real world problems.
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: WEB TECHNOLOGY LABORATORY
Subject Code: CS7L02 L-T-P-S-C: 0-0-3-0-1.5
a. Experiment Distribution:
For laboratories having only one part: Students are allowed to pick one experiment from
the lot with equal opportunity.
For laboratories having PART A and PART B: Students are allowed to pick one
experiment from PART A and one experiment from PART B, with equal opportunity.
b. Change of experiment is allowed only once and 20% of the maximum marks to be
deducted.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Course Objectives:
Sl. No Course Objectives
1 Design and develop static and dynamic web pages.
2 Know different Framework like PHP and JavaScript.
3
Familiarize with Client-Side Programming, Server-Side Programming.
4 Learn Database Connectivity to web applications.
Lab cycles
Description
I
1. Develop and demonstrate a HTML document that illustrates the use of external
style sheet, ordered list, table, borders, padding, color, and the tag.
2. Write a JavaScript to design a simple calculator to perform the following
operations: sum, product, difference and quotient.
3. Write a JavaScript that calculates the squares and cubes of the numbers from 0 to
10 and outputs XHTML text that displays the resulting values in an XHTML table
format.
4. Write a JavaScript code that displays text “TEXT-GROWING” with increasing
font size in the interval of 100ms in RED COLOR, when the font size reaches 50pt
it displays “TEXT-SHRINKING” in BLUE color. Then the font size decreases
to5pt.
5. Develop and demonstrate a XHTML file that includes JavaScript script that uses
functions for the following problems:
a. Parameter: A string b. Output: The position in the string of the left-most vowel
c. Parameter: A number d. Output: The number with its digits in the reverse order
6. Create a XHTML form with Name, Address Line2 and E-mail text fields. On
Submitting, store the values in MYSQL table. Retrieve and display the data based
on Name.
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Information Science and Engineering
II
7. Write a PHP program to keep track of the number of visitors visiting the web page
and to display this count of visitors, with proper headings.
8. Write a PHP program to display a digital clock which displays the current time of
the server.
9. Write the PHP programs to do the following:
a. Find the transpose of a matrix b. Multiplication of two matrices c. Addition of
two matrices (Note: Students have to execute either a & c or b & c).
10. Write a PHP program to sort the student records based on USN which are stored in
the database.
III
Practice Programs:
1. Design an XHTML that uses CSS to illustrate the usage of: hover and: focus
pseudo classes.
2. Design an XHTML that uses CSS to illustrate the usage of Font and Color
properties and Text Decoration Elements.
3. Design an XHTML that uses CSS to test External Style Sheets.
4. Design an XHTML that uses CSS to illustrate usage of borders, margin, padding
and Background images.
5. Design an XML document to store information about a student in an engineering
college SSIT. The information must include USN, Name, and Name of the College,
Branch, Year of Joining, and email id. Make up sample data for 3 students. Create
a CSS style sheet and use it to display the document.
Pattern for practical exam conduction:
a. Experiment Distribution:
For laboratories having only one part: Students are allowed to pick one experiment from
the lot with equal opportunity.
For laboratories having PART A and PART B: Students are allowed to pick one
experiment from PART A and one experiment from PART B, with equal opportunity.
b. Change of experiment is allowed only once and 20% of the maximum marks to be
deducted.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Course Outcomes:
Course outcome
Descriptions
CO1 Design and develop dynamic web pages with good aesthetic sense of designing and latest technical know-how's.
CO2 Embed JavaScript and PHP into XHTML.
CO3 Apply Web Application Terminologies, Internet Tools and other web services.
CO4 Developing the Website and storing and retrieving the data dynamically.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020 - 2021
Department: Information Science and Engineering Semester: 7
Subject Name: PROJECT WORK PHASE – I
Subject Code: CS7PW01 L-T-P-S-C: 0-8-0-0-4
Description
Scheme of Evaluation
1. Students shall carry out a detailed survey on the Area and the Topic on
which they are interested to do the Project work. Students are expected to
prepare documentation and submit three different Synopses to the
Evaluation Committee.
2. Evaluation Committee will review the synopsis and suggest suitable area
for project. If project proposals are not to the expected standards or outdates
then recommend the students resubmit the refined synopsis.
3. Students are expected to give a detailed presentation on the Topic approved
and justify the panel members to start their project work.
4. Presentation consists of Basic Overview of the Project which includes
Introduction, Literature Survey, Problem Statement, Motivation,
Objectives, Requirement Analysis and Specification, Features of Existing
and Proposed System and Algorithms Selected.
Evaluation Scheme - I (50% percent of CIE):
Continuous evaluation will be done by respective Project Guides based on the
Regularity, Technical Knowledge and Competence, Programming Skills,
Communication Skills, Demonstration skills, Collaborative Learning and
Documentation Skills of the students.
Evaluation Scheme - II (50% percent of CIE):
Students are evaluated by the team of faculty members based on the
Presentation, Technical Competence, Slides Preparation, Team Working
Abilities, Questionnaires and overall Performance in the Seminar-1 and
Seminar-2 of Project Phase-I.
Course Outcomes:
Course Outcome
Descriptions
CO1 Identify the problem in the specified area by a literature survey.
CO2 Analyze the problem and identify the different modules/algorithms tosolve the problems.
CO3 Choose the platform to solve the selected problem.
CO4 Document and present the proposed plan of the project development.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Department: Information Science and Engineering
Semester: 8
Sl. No. Subject
Code Name of the Subject L T P S C
1 IS8T01 Cryptography, Network Security
and Cyber Law 4 0 0 0 4
2 CS8T02 Big Data and Analytics 3 0 0 1 4
3 IS8PE3XY Professional Elective - IV 3 0 0 0 3
4 IS8PE4XY Professional Elective – V 3 0 0 0 3
5 CS8PW02 Project Work Phase-II 2 4 12 0 10
6 CS8TS01 Technical Seminar 0 0 0 1 1
Total 15 4 12 2 25
Professional Elective – IV Credits: 3-0-0-0-3
Subject Code Name of the Subject
IS8PE311 Information Retrieval
IS8PE312 Social Network Analysis
IS8PE313 Information Storage and Management
IS8PE314 Computer Vision and Robotics
Professional Elective – V Credits: 3-0-0-0-3
Subject Code Name of the Subject
IS8PE421 Artificial Neural Networks
IS8PE422 Software Architecture and Design Pattern
IS8PE423 Wireless Sensor Networks
IS8PE424 Cloud Computing
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: CRYPTOGRAPHY, NETWORK SECURITY and CYBER LAW
Subject Code: IS8T01 L-T-P-S-C: 4-0-0-0-4
Course Objectives:
Sl. No Course Objectives
1 Understand the fundamentals of cryptography and network security
2 Illustrate the key management issues and solutions.
3 Familiarize the cryptography and very essential algorithms.
4 Understand the concepts of cyber security and introduces cyber laws and ethics to be followed.
UNIT Description Hours
I
Introduction, Symmetric Ciphers: Introduction: The OSI Security Architecture, Security Attacks, Security Services, Security Mechanisms, A Model for Network
Security. Classical Encryption Techniques: Symmetric Cipher
Model, Substitution Techniques, Transposition Techniques,
Steganography. Block Cipher and the Data Encryption Standard:
Block Cipher principles, The Data Encryption Standard, The Strength of DES, Block Cipher Operation: Multiple Encryption and triple DES, Electronic Code Book, Cipher Block Chaining Mode, Cipher Feedback Mode, Output Feedback Mode, Counter Mode.
10
II
Number Theory and Public Key Cryptosystem:
Number Theory: Prime Numbers, Format's and Euler's Theorems,
Testing for Primality. Public-Key Cryptography and RSA: Principles of Public- Key Cryptosystems, The RSA Algorithm. Diffie-Hellman Key Exchange. Cryptographic Data Integrity Algorithms: Cryptographic Hash Functions, Applications of Cryptographic hash functions, Two simple hash Functions, Secure Hash Algorithm. Digital Signatures: Digital Signatures, Digital Signature Standard.
10
III
Key Management, Transport-Level Security: Key Management and Distribution: Symmetric Key distribution using symmetric encryption, Symmetric Key distribution using Asymmetric encryption, Distribution of public keys, X.509 Certificates, Kerberos. Transport level security: Web Security considerations, Secure Sockets Layer and Transport Layer Security.
10
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
IV
Internet Security, System Security: Electronic Mail Security: Pretty Good Privacy. IP Security: Overview, IP
Security Policy. Intruders: Intruders, Intrusion detection. Malicious Software: Types of Malicious Software Viruses. Firewalls: The need for Firewalls, Firewall Characteristics, Types of Firewalls.
10
V
Internet Law and Cyber Crimes: Internet and Need for Cyber Law, Modes of Regulation of internet, Types of Cyber Terror Capability, Net Neutrality, Types of Cyber Crimes, India and the Cyber Law, Cyber Crimes and ‘The Information Technology Act’, 2000, Internet Censorship, Cyber Crimes and Enforcement Agencies. IT act aim and objectives, Scope of the act, Major Concepts, Important provisions, Attribution, acknowledgement, and dispatch of electronic records, Secure electronic records and secure digital signatures, Regulation of certifying authorities: Appointment of Controller and Other officers, Digital Signature
certificates, Duties of Subscribers, Penalties and adjudication, The cyber regulations appellate tribunal, Offences, Network service providers not to beliable in certain cases, Miscellaneous Provisions.
12
Text Books:
Sl No
Title
Author
Volume and Year of Edition
1 Cryptography and Network Security
William Stallings Fifth Edition, Prentice Hall of India, 2005.
2 Cryptography, Network Security andCyber Laws
Ber nard Menezes Cengage Learning, 2010 Edition
Reference Books:
Sl No
Title Author Volume and Year of Edition
1 Network Security: Private
Communication in a Public
World,
Charlie Kaufman,
Radia Perlman,
Mike Speciner,
Second Edition,
Pearson,Education
Asia, 2002.
2 Cryptography and Network
Security
AtulKahate Tata McGrawHill,
2003
3 Cyber Security and Cyber Laws Alfred Basta,
Nadine Basta, Mary
Brown,
Ravindrakumar
Cengage Learning.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Course Outcomes:
Course Outcome
Descriptions
CO1
Define the security principles and understand the working of typical
symmetric and asymmetric ciphers.
CO2
Analyze and use cryptographic data integrity algorithms and user authentication protocols.
CO3
Apply effective cryptographic techniques for information security and
other applications.
CO4
Interpret the structure, mechanics and evolution of the internet in the
context of cyber-crimes and cyber laws.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: BIG DATA AND ANALYTICS
Subject Code: CS8T02 L-T-P-S-C: 3-0-0-1-4
Course Objectives:
Sl. No
Course Objectives
1 To optimize business decisions and create competitive advantage with Big Data analytics.
2 To explore the fundamental concepts of big data analytics.
3 To understand the applications using Map Reduce Concepts.
4 To introduce programming tools PIG & HIVE in Hadoop echo system.
UNIT Description Hours
I
Getting an Overview of Big Data:
What is Big Data? History of Data Management-Evolution of Big Data,
Structuring Big Data-Types of Data, Elements of Data, Advantages of
Big Data Analytics Introducing Technologies for Handling Big Data
Distributed and Parallel Computing for Big Data, Introducing Hadoop,
Cloud Computing and Big Data: Cloud Delivery Models, Cloud
Services for Big Data, Cloud Providers in Big Data Market, In-Memory
Computing Technology for Big Data.
10
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
II
Big Data Analytics and Technology Landscape:
Where do we Begin? What is Big Data Analytics? What Big Data
Analytics Isn’t? Why this Sudden Hype Around Big Data Analytics?
Classification of Analytics, Greatest Challenges that Prevent
Businesses from Capitalizing on Big Data, Top Challenges Facing Big
Data, Why is Big Data Analytics Important? What Kind of
Technologies are we looking Toward to Help Meet the Challenges
Posed by Big Data? Data Science, Data Scientist...Your New Best
Friend!!! , Terminologies Used in Big Data Environments, Basically
Available Soft State Eventual Consistency (BASE) , Few Top Analytics
Tools.NoSQL (Not Only SQL) , Hadoop.
10
III
Introduction to Hadoop and MongoDB:
Introducing Hadoop, Why Hadoop? Why not RDBMS? RDBMS versus
Hadoop, Distributed Computing Challenges ,History of Hadoop ,
Hadoop Overview, Use Case of Hadoop ,Hadoop Distributors ,HDFS
(Hadoop Distributed File System),Processing Data with Hadoop,
Managing Resources and Applications with Hadoop YARN (Yet another
Resource Negotiator),Interacting with Hadoop Ecosystem .
Introduction to MongoDB: What is and Why MongoDB? Terms used in
RDBMS and MongoDB, Data types in MongoDB, MongoDB Query
language.
10
IV
Introduction to Cassandra and MAPREDUCE: Apache Cassandra, features, CQL data types, CQLSH, key spaces, CRUD, collections, TTL, using a counter, ALTER commands, import and export, query system tables. MAPREDUCE Programming: Mapper, Reducer, Combiner, Partitioner, Searching, Sorting, Compression.
11
V
Introduction to Hive and Pig: What is Hive? , Hive Architecture, Hive Data Types, Hive File Format, Hive Query Language (HQL), RCFile Implementation, SerDe, and User-defined Function (UDF). What is Pig? The Anatomy of Pig, Pig on Hadoop , Pig Philosophy, Use Case for Pig: ETL Processing, Pig Latin Overview , Data Types in Pig ,Running Pig, Execution Modes of Pig ,HDFS Commands ,Relational Operators, Eval Function, Complex Data Types ,Piggy Bank, User- Defined Functions (UDF) ,Parameter Substitution , Diagnostic Operator , Word Count Example using Pig ,When to use Pig? When not to use Pig? Pig at Yahoo!, Pig versus Hive.
11
Text Books:
Sl No
Title Author(s) Edition, Publisher, Year, ISBN
1 Big Data: Black Book
Dt Editorial Services 1st Edition, Dream tech Press, 2016, ISBN -13:9789351197577
2 Big Data and Analytics
Seema Acharya, Subhashini Chellappan
1st Edition, Wiley India 2015, ISBN:978-81-265-5478-2
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Reference Books:
Sl No
Title Author Volume and Year of Edition
1 Hadoop in Practice Alex Holmes 2nd Edition, Manning
Publications Co., January 2015, ISBN-13:978-9351197423
2 Programming Pig Alan Gates 2nd Edition, O'Reilly Media,
2017, ISBN-978-1-491-93709-9
3 Programming Hive Dean Wampler 1st Edition, O'Reilly Media, 2012,
ISBN:978-1-449-31933-5
Course Outcomes:
Course Outcome
Descriptions
CO1 Identify the characteristics of datasets and compare the trivial data and big data for various applications.
CO2 Demonstrate the concept to interact with Big data using open source software called Hadoop and supporting tools.
CO3 Comparative study of traditional tools with Big data programming tools.
CO4 Outline the concepts of analytics in Big data.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: INFORMATION RETRIEVAL
Subject Code: IS8PE311 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Learn the information retrieval situations for text and hyper media.
2 Understand how to store, and retrieve information from www using semantic approaches.
3 Familiar with the usage of data/file structures in building computational
search engines.
4
Analyze the performance of information retrieval using advanced techniques such as classification, clustering, and filtering over multimedia.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
UNIT Description Hours
I
Introduction: Introduction -History of IR- Components of IR - Issues –Open source Search engine Frameworks - The impact of the web on IR - The role of artificial intelligence (AI) in IR – IR Versus Web Search - Components of a Search engine- Characterizing the web.
7
II
Information Retrieval:
Boolean and vector-space retrieval models- Term weighting - TF-IDF weighting- cosine similarity – Preprocessing - Inverted indices - efficient processing with sparse vectors – Language Model based IR - Probabilistic IR – Latent Semantic Indexing - Relevance feedback and query expansion.
7
III
Web Search Engine – Introduction and Crawling:
Web search overview, web structure, the user, paid placement, search engine optimization/ spam. Web size measurement - search engine optimization/spam– Web Search Architectures - crawling - meta-crawlers- Focused Crawling - web indexes –- Near-duplicate detection- Index Compression - XML retrieval.
8
IV
iSTA0052T: Evaluation of Feedback Systems, Textual Signatures: Identifying Text-Types Using Latent Semantic Analysisto Measure the Cohesion of Text Structures: Introduction, Cohesion, Coh-Metrix, Approaches to Analyzing Texts, Latent Semantic Analysis, Predictions, Results of Experiments. Automatic Document Separation: A Combination of Probabilistic Classification and Finite-State Sequence Modeling: Introduction, Related Work, Data Preparation, Document Separation as a Sequence Mapping Problem, Results. Evolving Explanatory Novel Patterns for Semantically-Based Text Mining: Related Work, A Semantically GuidedModel for Effective Text Mining.
8
V
Information Retrieval and Lexical Resources: Information Retrieval: Design features of Information Retrieval Systems-Classical, Non classical, Alternative Models of Information Retrieval – valuation Lexical Resources: World Net- Frame Net- Stemmers-POS Tagger- Research Corpora.
9
Text Books:
Sl No
Title Author Volume and Year of
Edition
1 “Natural Language Processing and Information Retrieval”
Tanveer Siddiqui,
U.S. Tiwary,
OxfordUniversity Press, 2008.
2 “Natural Language Processing and Text Mining”
Anne Kao and Stephen R. Poteet (Eds),
Springer-Verlag London Limited 2007
Reference Books:
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Sl No
Title Author Volume and Year of
Edition
1
“Speech and Language Processing: An introduction to Natural Language Processing, Computational Linguistics and Speech Recognition”
Daniel Jurafsky and James H Martin,
2nd Edition, Prentice Hall, 2008.
2 “Natural Language Understanding”
James Allen 2ndEdition, Benjamin /Cummings publishing company,1995.
3 “Information Storage and Retrieval systems”
Gerald J. Kowalski and Mark. T. Maybury
Kluwer academic Publishers, 2000.
Course Outcomes:
Course Outcome
Descriptions
CO1 Apply information retrieval models.
CO2 Design Web Search Engine.
CO3 Make use of Link Analysis and apply document text mining techniques.
CO4 Apply Hadoop and Map Reduce techniques.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: SOCIAL NETWORK ANALYSIS
Subject Code: IS8PE312 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl.
No Course Objectives
1 Understand the concept of semantic web and related applications.
2 Learn knowledge representation using ontology.
3 Understand human behavior in social web and related communities.
4 Learn visualization of social networks.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
UNIT Description Hours
I
The Semantic Web and Social Networks:
Introduction to Semantic Web: Limitations of current Web – Development of Semantic Web -Emergence of the Social Web – Social Network analysis: Development of Social Network Analysis- Key concepts and measures in network analysis.
8
II
Semantic Technology for Social Network Analysis:
Electronic sources for network analysis: Electronic discussion networks, Blogs and online communities – Web-based networks-Ontology-based knowledge Representation –Resource Description Framework – Web Ontology Language- Modeling and aggregating social network data: State-of-the-art in network data representation - Ontological representation of social individuals –Ontological representation of social relationships - Aggregating and reasoning with social network data.
8
III
Extraction and Mining Communities in Web Social Networks: Detecting communities in social networks – Definition of community – Evaluating communities – Methods for community detection and mining – Applications of community mining algorithms – Tools for detecting communities - social network infrastructures and communities – Decentralized online social networks – Challenges of DOSNs - General Purpose DOSNs.
8
IV
Predicting Human Behavior and Privacy Issues: Understanding and predicting human behavior for social communities – User data management, Inference and Distribution – Enabling new human experiences – The Technologies - Privacy in online social networks – Trust in online environment – Trust models based on subjective logic – Trust network analysis – Trust transitivity analysis – Combining trust and reputation – Trust derivation based on trust comparisons.
8
V
Visualization and Applications of Social Networks: Graph theory – Centrality – Clustering – Node-Edge Diagrams – Matrix representation – Visualizing online social networks, Visualizing social
networks with matrix-based representations – Matrix and Node-Link Diagrams– Hybrid representations – Applications – Cover networks – Community welfare -Collaboration networks – Co-Citation networks.
7
Text Books: NIL
Reference Books:
Sl No
Title Author Volume and Year
of Edition
1
“Social Networks and the Semantic Web”
Peter Mika First Edition, Springer 2007
2
“Handbook of Social Network Technologies and Applications”
BorkoFurht, 1st,Edition, Springer, 2010.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
3
“Web Mining and Social Networking – Techniques and applications”
GuandongXu,Yanch
un Zhang and Lin
Li,
First Edition Springer, 2011.
4
“Social information Retrieval Systems: Emerging Technologies and Applications for Searching the Web Effectively”
Dion Goh and Schubert Foo
IGI Global Snippet, 2008
5
“Collaborative and Social Information Retrieval and Access: Techniques for Improved user Modelling”
Max Chevalier, Christine Julien andChantal Soulé-Dupuy
IGI Global Snippet, 2009.
6 “The Social Semantic Web” John G.Breslin,
Alexander Passant and Stefan Decker
Springer, 2009.
Course Outcomes:
Course
Outcome Descriptions
CO1 Develop semantic web related applications.
CO2 Represent knowledge using ontology.
CO3 Predict human behavior in social web and related communities.
CO4 Visualize social networks.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: INFORMATION STORAGE AND MANAGEMENT
Subject Code: IS8PE313 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl.
No Course Objectives
1
Learn about the various storage infrastructure components in data center environments
2
Familiarize in making decisions on storage-related Technologies in an increasingly complex IT environment.
3
Understand the storage technologies, architectures, features, and benefits of intelligent storage systems
4
Exposed to block-based, file-based, object-based, unified storage and software-defined storage.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
UNIT Description Hours
I
Introduction to Information Storage, Data center Environment: Information Storage, Evolution of Storage Architecture Data Center Infrastructure, Virtualization and Cloud computing(1.1 to 1.4), Application, Database Management systems, Host, Connectivity(2.1 to 2.4).
8
II
Data Protection: RAID, Intelligent Storage System:\RAID implementation methods, RAID array components, RAID Techniques, RAID, Levels, RAID impact on Disk Performance, RAID comparison, Hot spares(3.1 to 3.7), Components of an Intelligent Storage System, Storage Provisioning, Types of Intelligent Storage Systems(4.1 to 4.3).
8
III
Fibre Channel Storage Area Networks: Fibre Channel overview, The SAN and its evolution, Components of SAN, FC connectivity, Switched
Fabric Ports, Fibre Channel Architecture, Fabric Services, Switched Fabric Login Types, Zoning, FC SAN Topologies, Virtualization and SAN(5.1 to 5.11).
7
IV
IP SAN, FCoE and NAS: Network Attached Storage iSCSI(internet Small Computer System Interface), FCIP(Fibre Channel over Internet Protocol), FCoE(Fibre Channel over Ethernet)(6.1 to 6.3), General purpose servers versus NAS devices, Benefits of NAS, File Systems and Network File Sharing, Components of NAS, NAS I/O Operation, NAS Implementations, NAS File Sharing Protocols, Factors Affecting NAS Performance, File Level Virtualization(7.1 to 7.9).
8
V
Introduction to Business Continuity and Backup and archive: Information Availability, BC Terminology, BC Planning Life Cycle, failure Analysis, Business Impact Analysis, BC Technology Solutions (9.1 to 9.6), backup Purpose, backup Considerations, backup Granularity, recovery Considerations, Backup Methods, Backup Architecture, Backup and Restore Operations, Backup Topologies, Backup in NAS Environments.(10.1 to 10.9)
8
Text Book:
Sl No
Title Author Volume and Year of Edition
1 Information Storage and Management
G.Somasundaram, Alok Shrivastava
EMC Education
Services, Wiley- India, Second Edition.
Reference Books:
Sl No
Title Author Volume and Year of Edition
1 Storage Networks Explained Ulf Troppens,
RainerErkes and Wolfgang Muller
Wiley India, 2003.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
2 Storage Networks, The Complete Reference.
Rebert Spalding Tata McGraw Hill, 2003
3 Storage Area Networks Essentials A
Complete Guide to Understanding and Implementing SANs
Richard Barker and Paul Massiglia
Wiley India, 2002
Course Outcomes:
Course
Outcome
Descriptions
CO1 Understand Storage Area Networks characteristics and Architectures.
CO2 Explain Storage Network Technologies and Virtualization.
CO3 Analyze the Securing and Managing of Storage Infrastructure.
CO4 Configure and Simulate Storage Area Network Technologies.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: COMPUTER VISION AND ROBOTICS
Subject Code: IS8PE314 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Review image processing techniques for computer vision
2 Explain shape and region analysis.
3 Illustrate Hough Transform and its applications to detect lines, circles,
ellipses.
4 Contrast three-dimensional image analysis techniques, motion analysis
and applications of computer vision algorithms.
UNIT Description Hours
I
CAMERAS: Pinhole Cameras, Radiometry – Measuring Light: Light in Space, Light Surfaces, Important Special Cases, Sources, Shadows, And Shading: Qualitative Radiometry, Sources and Their Effects, Local Shading Models, Application: Photometric Stereo, Inter reflections: Global Shading Models, Color: The Physics of Color, Human Color Perception, Representing Color, A
Model for Image Color, Surface Color from Image Color.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
II
Linear Filters:
Linear Filters and Convolution, Shift Invariant Linear Systems, Spatial
Frequency and Fourier Transforms, Sampling and Aliasing, Filters as
Templates, Edge Detection: Noise, Estimating Derivatives, Detecting
Edges, Texture: Representing Texture, Analysis (and Synthesis) Using
Oriented Pyramids, Application: Synthesis by Sampling Local Models,
Shape from Texture.
7
III
The Geometry of Multiple Views:
Two Views, Stereo sis: Reconstruction, Human Sternposts, Binocular Fusion, Using More Cameras, Segmentation by Clustering: What Is Segmentation?, Human Vision: Grouping and Gestalt, Applications: Shot Boundary Detection and Background Subtraction, Image Segmentation by Clustering Pixels, Segmentation by Graph-Theoretic Clustering,
8
IV
Segmentation by Fitting a Model: The Hough Transform, Fitting
Lines, Fitting Curves, Fitting as a Probabilistic Inference Problem,
Robustness, Segmentation and Fitting Using Probabilistic Methods:
Missing Data Problems, Fitting, and Segmentation, The EM Algorithm
in Practice, Tracking With Linear Dynamic Models: Tracking as an
Abstract Inference Problem, Linear Dynamic Models, Kalman Filtering,
Data Association, Applications andExamples.
8
V
Geometric Camera Models: Elements of Analytical Euclidean
Geometry, Camera Parameters and the Perspective Projection, Affine
Cameras and Affine Projection Equations, Geometric Camera
Calibration: Least-Squares Parameter Estimation, A Linear Approach
to Camera Calibration, Taking Radial Distortion into Account,
Analytical Photogrammetry, An Application: Mobile Robot Localization,
Model- Based Vision: Initial Assumptions, Obtaining Hypotheses by
Pose Consistency, Obtaining Hypotheses by pose
Clustering, Obtaining Hypotheses Using Invariants, Verification,
Application: Registration In Medical Imaging Systems, Curved Surfaces
and Alignment.
8
Text Books:
Sl No
Title Author Volume and Year of Edition
1
Computer Vision – A Modern Approach
David A. Forsyth andJean Ponce
PHI Learning (IndianEdition), 2009.
Reference Books:
Sl
No Title Author
Volume and Year
of Edition
1 Computer and Machine Vision– Theory, Algorithms and Practicalities
E. R. Davies Elsevier(Academic Press), 4thedition, 2013.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Course Outcomes:
Course
Outcome Descriptions
CO1 Implement fundamental image processing techniques required for Computer vision.
CO2 Perform shape analysis.
CO3 Implement boundary tracking techniques.
CO4 Apply chain codes and other region descriptors.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: ARTIFICIAL NEURAL NETWORKS
Subject Code: IS8PE421 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Perceive the basic concepts of ANN, applications and learning techniques.
2 Explain the working of perceptron and multilayer perceptron and
related learning algorithms.
3 Gain essential knowledge on convolution neural networks and
applications.
4 Explore structured probabilistic models for deep learning.
UNIT Description Hours
I
Artificial Neural Networks – Introduction and Learning Process-I: What is a Neural Network? Human Brain, Models of a Neuron, Neural Networks Viewed as DG, Feedback, Network Architectures, Error-correction learning, Memory-based learning, Hebbian Learning, Competitive learning, Boltzmann Learning.
7
II
Learning Process-II and Perceptron:
Learning with a teacher, learning without a teacher, Learning tasks,
Memory and adaptation. Statistical Learning Theory, VC dimension,
Probably approximately correct model of learning, Single-Layer
Perceptrons: Adaptive filtering problem, Unconstrained optimization
techniques: Steepest Descent, Newton’s, Gauss-Newton; Linear Least-
Squares Filter, LMS algorithm, Learning curves, Learning rate
annealing techniques, Perceptron and Convergence theorem.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
III
Multilayer Perceptron and Generalization:\ BP algorithm, Two passes of computation, Sequential and Batch
Modes of training, Stopping Criteria, XOR problem, Heuristics for BP algorithm to perform better, Output representation and Decision rule, Generalization, Universal approximation theorem, Cross-validation.
8
IV
Convolution Networks: Convolution Operation, Motivation, Pooling, Convolution and Pooling as an Infinitely Strong Prior, Variants of the basic convolution function, Structured Outputs, Data types, Efficient Convolution Algorithms, Random or Unsupervised features, The Neuroscientific basis for convolutional networks.
8
V
Structured Probabilistic Models for Deep Learning: The challenge of unstructured modeling, Using graphs to describe model structure: Directed, Undirected, Partition function, Energy-
based models, Factor graphs; Sampling from graphical models, Advantages of structured modeling, learning about dependencies, Inference and approximate inference, The deep learning approach to structured probabilistic models.
8
Text Books: NIL
Reference Books:
Sl No
Title Author Volume and Year of Edition
1 Neural Networks – A Comprehensive Foundation
Simon Haykin 2nd Edition,2005. PHI, (Units I to III).
2 Deep Learning (Adaptive Computation and Machine Learning Series)
Ian Good fellow, YoshuaBengioand Aaron Courville
(3 January 2017), MIT Press, ISBN-13: 978- 0262035613.
3 Introduction to Artificial Neural Networks
Gunjan Goswami 2012 Edition, S.K.Kataria & Sons; ISBN-13: 978-9350142967.
4 Fundamentals of Deep
Learning: Designing Next-Generation Machine Intelligence Algorithms
Nikhil Buduma 2016 Edition,byO’Reilly
Publications, ISBN- 13:9781491925614.
Course Outcomes:
Course Outcome
Descriptions
CO1 Describe basic concepts of neural network, its applications and various
learning models.
CO2 Analyze different Network Architectures, learning tasks, convolutional
networks, and deep learning models.
CO3 Investigate and apply neural networks model and learning techniques
to solve problems related to society and industry.
CO4 Demonstrate a prototype application developed using any NN tools and
APIs.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: SOFTWARE ARCHITECTURE AND DESIGN PATTERNS
Subject Code: IS8PE422 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl.
No Course Objectives
1 Learn How to add functionality to designs while minimizing
complexity.
2 Understand the code qualities required to maintain to keep code flexible.
3 To understand the common design patterns.
4 To explore the appropriate patterns for design problems.
UNIT Description Hours
I
Introduction: What is a design pattern? Describing design patterns,
the catalog of design pattern, organizing the catalog, how design
patterns solve design problems, how to select a design pattern, how to
use a design pattern. What is object- oriented development? , key
concepts of object oriented design other related concepts, benefits and
drawbacks of the paradigm.
8
II
Analysis a System: overview of the analysis phase, stage 1: gathering the requirements functional requirements specification, defining conceptual classes and relationships, using the knowledge of the domain. Design and implementation, discussions and further reading.
8
III
Design Pattern Catalog: Structural patterns, Adapter, bridge, composite, decorator, facade, flyweight, proxy.
7
IV
Interactive systems and the MVC architecture: Introduction , The MVC architectural pattern, analyzing a simple drawing program , designing the system, designing of the subsystems, getting into implementation , implementing undo operation , drawing incomplete items, adding a new feature , pattern based solutions.
7
V
Designing with Distributed Objects: Client server system, java remote method invocation, implementing an object oriented system on the web (discussions and further reading) a note on input and output, selection statements, loops arrays.
8
Text Books:
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Sl No
Title Author Volume and Year of Edition
1 Object-oriented analysis, design and
implementation
Brahma Dathan,
Sarnathrammath,
Universities Press,
2013.
2 Design patterns, erich gamma Richard helan,
Ralphjohman,johnvl
issides
PEARSON
Publication, 2013.
Reference Books:
Sl No
Title Author Volume and Year of Edition
1
“Pattern Oriented Software
Architecture”
Frank Bachmann,
Regine Meunier,
Hans Rohnert
Volume 1, 1996.
2
"Anti-Patterns: Refactoring
Software, Architectures and Projects
in Crisis"
William J Brown et
al.
John Wiley, 1998.
Course Outcomes:
Course Outcome
Descriptions
CO1 Design and implement codes with higher performance and lower
complexity.
CO2 Aware of code qualities needed to keep code flexible.
CO3 Experience core design principles and be able to assess the quality of a
design with respect to these principles.
CO4 Capable of applying these principles in the design of object oriented
systems.
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8th
Subject Name: WIRELESS SENSOR NETWORKS
Subject Code: IS8PE423 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Understand the basic WSN technology and supporting protocols, basic
sensor systems and provide a survey of sensor technology.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
2 Understand the medium access control protocols and address physical layer issues.
3 Learn key routing protocols for sensor networks and main design issues.
4 Learn transport layer protocols for sensor networks, and design
requirements.
UNIT Description Hours
I
Introduction: Unique Constraints and Challenges, Advantages of Sensor Networks - Energy advantage and Detection advantage, Sensor Network Applications - Habitat monitoring, Wildlife conservation through autonomous, non-intrusive sensing, Tracking chemical plumes, Ad hoc, just-in-time deployment mitigating disasters, Smart
Transportation: networked sensors making roads safer and less congested, Collaborative Processing, Key Definitions of Sensor Networks, Canonical Problem: Localization and Tracking: - Tracking Scenario, Problem Formulation - Sensing model, Collaborative localization, Bayesian state estimation.
8
II
Canonical Problem: Localization and Tracking contd..
Distributed Representation and Inference of States, Impact of choice
of representation, Design in Distributed Tracking, Tracking Multiple
Objects, State Space Decomposition, Data association, Sensor Models,
Performance Comparison and Metrics. Networking Sensors: - Key
Assumptions, Medium Access Control - The SMAC Protocol, IEEE
802.15.4 Standard and ZigBee, General Issues.
8
III
Networking Sensors contd..
Geographic-Energy-Aware Routing, Unicast Geographic Routing,
Routing on a Curve, Energy-Minimizing Broadcast, Energy- Aware
Routing to a Region, Attribute-Based Routing – Directed Diffusion,
Rumor Routing, Geographic Hash Tables. Infrastructure
Establishment: - Topology Control, Clustering, Time Synchronization -
Clocks and Communication Delays, Interval Methods, Reference
Broadcasts.
7
IV
Infrastructure Establishment contd.. Localization and Localization Services - Ranging Techniques, Range-Based Localization Algorithms, Other Localization Algorithms, Location Services. Sensor Tasking and Control: - Task-Driven Sensing, Roles of Sensor Nodes and Utilities, Information Based Sensor Tasking - Sensor Selection, IDSQ: Information-Driven Sensor Querying, Cluster Leader Based Protocol, Sensor Tasking in Tracking Relations.
8
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
V
Sensor Tasking and Control contd.. Joint Routing and Information Aggregation – Moving Center of
Aggregation, Multistep Information- Directed Routing, Sensor Group Management. Sensor Network Platforms and Tools: Sensor Node Hardware – Berkeley Motes, Sensor Network Programming Challenges, Node-Level Software Platforms, Operating system: Tiny OS, Imperative language: nesC, Dataflow style language: Tiny GALS, Node-Level Simulators, The NS-2 Simulator and its Sensor Network Extensions, The Simulator TOSSIM.
8
Text Book:
Sl No
Title Author Volume and Year of Edition
1 Wireless Sensor Networks – An
Information ProcessingApproach,
Feng Zhao,
Leonidas Guibas
Elsevier, 2004.
Reference Books:
Sl No
Title Author Volume and Year of Edition
1 “Protocols and Architectures
for Wireless Sensor Networks”
Holger Karl, Andreas
Willig
John Wiley &
Sons, Inc., 2005.
2
“Ad Hoc Mobile Wireless Networks” Subir Kumar Sarkar,
T G Basavaraju, C
Puttamadappa,
Auerbach
Publications, 2008.
Course Outcomes:
Course
Outcome Descriptions
CO1 Identify different issues in wireless sensor networks and its
applications.
CO2 Capable of analyzing the protocols developed for sensor networks.
CO3 Design sensor networks using sensor tasking and controls.
CO4 Understand about various tools used for simulating sensor networks.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: CLOUD COMPUTING
Subject Code: IS8PE424 L-T-P-S-C: 3-0-0-0-3
Course Objectives:
Sl. No Course Objectives
1 Provide comprehensive view to different aspects of cloud computing like;
service models, Deployment models and challenges.
2 Introduce to cloud virtualization, with different type of virtualization and
capacity planning metrics to clouds.
3 To know the concrete concepts of cloud security and their standards.
4 Contrast how Service oriented Architecture principles is helpful in Cloud
Computing.
UNIT Description Hours
I
Examining the value proposition: Cloud Types, The NIST model, The Cloud Cube Model, Deployment models, Service models, Examining the Characteristics of Cloud Computing, Paradigm shift, Benefits of cloud computing, Disadvantages of cloud computing; Assessing the value proposition: Early adopters and new applications, the laws of cloudonomics, cloud computing obstacles, behavioral factors relating to
cloud adoption, measuring cloud computing costs, specifying SLAs.
8
II
Continuation of Examining, the value Proposition: Understanding Cloud Architecture: Exploring the Cloud Computing Stack, Composability, Infrastructure, Platforms, Virtual Appliances, Communication Protocols; Understanding Services and Applications
by Type: Defining IaaS, Defining PaaS, Defining SaaS, Defining IDaaS.
8
III
Understanding Platform:
Using Virtualization Technologies, Load balancing and Virtualization, Understanding Hypervisors; Capacity Planning: Defining Baseline and Metrics, Baseline measurements, System metrics, Load testing, Resource ceilings, Server and instance types, Network Capacity, Scaling.
8
IV
Exploring Cloud Infrastructure:
Securing the Cloud, The security boundary, Security service boundary, Security mapping, Securing Data, Brokered cloud storage access, Storage location and tenancy, Encryption, Auditing and compliance, Establishing Identity and Presence, Identity protocol
standards, Windows Azure identity standards.
7
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
V
Understanding Services and Applications: Understanding Service Oriented Architecture: Introducing Service
Oriented Architecture, Event-driven SOA or SOA 2.0, The Enterprise Service Bus, Service catalogs, Defining SOA Communications, Business Process Execution Language, Business process modeling, Managing and Monitoring
SOA, SOA management tools , SOA security , The Open Cloud
Consortium, Relating SOA and Cloud Computing.
8
Text Book:
Sl No
Title Author Volume and Year of Edition
1 “Cloud Computing Bible” Barrie Sosinsky Wiley Publishing Inc.
2011 (free e- book available).
Reference Books:
Sl
No
Title
Author
Volume and Year of Edition
1 Cloud Computing and SOA Convergence in YourEnterprise: David S.
Linthicum
A Step-by-Step
Guide(freee-bookavailable)
2 “Distributed and Cloud
Computing – From Parallel
Processing to the Internetof
Things”
Kai Hwang,
Geoffrey
C. Fox, and Jack
J. Dongarra,
Morgan Kaufman
Publishers,2012.
3 Enterprise Cloud Computing
Technology Architecture Applications
Gautam Shroff (free e-bookavailable)
4 Cloud Computing, A Practical
Approach
Toby Velte,
Anthony
Velte,Robert
Elsenpeter
(free e-book
available)
Course Outcomes:
Course Outcome
Descriptions
CO1 Define Cloud computing and characteristics and various types of cloud
services.
CO2 Describe benefits and drawbacks of Cloud computing.
CO3 Explain various types of virtualization and capacity planning metrics.
CO4 Discuss Cloud Security and various challenges, SOA and various issues.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: PROJECT WORK PHASE – II
Subject Code: CS8PW02 L-T-P-S-C: 2-4-12-0-10
Description
Scheme of Evaluation
1. Students shall present on the System Design Phase which includes System
Architecture, High Level Design, Low Level Design, System Models, System
Modules, Implementation Tools used and Algorithms used and implemented.
2. Final seminar on the complete project is presented by thestudents.
Project Phase - II Demonstration
Students have to demonstrate the working model of the Project to their respective
guides.
Evaluation Scheme-I (50% percent of CIE):
Continuous evaluation will be done by respective Project Guides based on the
Regularity, Technical Knowledge and Competence, Programming Skills,
Communication Skills, Demonstration skills, Collaborative Learning and
Documentation Skills of the students.
Evaluation Scheme II (50% percent of CIE):
Students are evaluated by the team of faculty members based on the
Presentation, Technical Competence, Slides Preparation, Team Working Abilities,
Questionnaires and overall Performance in the Seminar-1 and Seminar-2 of
Project Phase-I.
Students are required to meet their respective project guides on a stipulatedday
once in a week and update their progress and get signature from the guides
without fail.
Course Outcomes:
Course Outcome
Descriptions
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
CO1 Design a suitable system to solve the problem identified in project work
phase I and plan to work as a team.
CO2 Implement the design using necessary algorithms and by incorporating the necessary suggestions, if any.
CO3 Test the performance of the system with suitable data and demonstrate the project.
CO4 Document the project work and present the work carried out to the
audience.
SRI SIDDHARTHA INSTITUTE OF TECHNOLOGY- TUMAKURU (A constituent College of Siddhartha Academy of Higher Education, Tumakuru)
Information Science and Engineering
Syllabus for the Academic Year – 2020-2021
Department: Information Science and Engineering Semester: 8
Subject Name: TECHNICAL SEMINAR
Subject Code: CS8TS01 L-T-P-S-C: 0-0-0-1-1
Description
Guidelines for preparing Technical Seminar
1. Selection of topic/area:
Select a paper according to the specialization of students. Papers from
any other approved journals can also be selected.
2. Approval to the selected topic:
After selecting the paper, get approval from the concerned faculty in charge.
3. Study of topic:
Students are requested to acquire a thorough knowledge on the subject by referring back papers and reference books (These may be included as references at the end of the paper) on the corresponding area.
4. Seminar:
Final seminar is presented by the students through slides.
Course Outcomes:
Course Outcome
Descriptions
CO1 Survey the changes in the technologies relevant to the topic selected.
CO2
Discuss the technology and interpret the impact on the society, environment and domain.
CO3 Compile report of the study and present to the audience.