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3 Semester - 2019 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CS331P | DATABASE MANAGEMENT SYSTEMS | Core Courses | 5 | 4 | 100 |
CS332P | DATA STRUCTURES AND ALGORITHMS | Core Courses | 5 | 4 | 100 |
CS333 | SOFTWARE ENGINEERING | Core Courses | 3 | 3 | 100 |
EC337 | DIGITAL SYSTEMS | Core Courses | 4 | 3 | 100 |
HS311 | TECHNICAL WRITING | Core Courses | 2 | 2 | 50 |
MA334 | DISCRETE MATHEMATICS | Core Courses | 3 | 3 | 100 |
MC321 | CYBER SECURITY | Skill Enhancement Courses | 2 | 0 | 50 |
MIMBA331 | PRINCIPLES OF MANAGEMENT | Minors and Honours | 6 | 4 | 100 |
MIPSY331 | UNDERSTANDING HUMAN BEHAVIOR | Minors and Honours | 4 | 4 | 100 |
4 Semester - 2019 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
BS451 | BIO SCIENCE LABORATORY | Core Courses | 2 | 1 | 50 |
CS431 | PROBABILITY AND QUEUING THEORY | Core Courses | 3 | 3 | 100 |
CS432P | OPERATING SYSTEMS | Core Courses | 5 | 4 | 100 |
CS433P | PROGRAMMING PARADIGM | Core Courses | 5 | 4 | 100 |
CS434 | FORMAL LANGUAGE AND AUTOMATA THEORY | Core Courses | 3 | 3 | 100 |
CS435P | COMPUTER ORGANIZATION AND ARCHITECTURE | Core Courses | 5 | 4 | 100 |
CS436 | PROFESSIONAL ETHICS | Core Courses | 3 | 3 | 100 |
MIMBA431 | ORGANISATIONAL BEHAVIOUR | - | 6 | 4 | 100 |
MIPSY431 | PEOPLE THOUGHTS AND SITUATIONS | - | 4 | 4 | 100 |
5 Semester - 2018 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CS531 | COMPUTER ORIENTED NUMERICAL ANALYSIS | - | 3 | 3 | 100 |
CS532E01 | FORMAL LANGUAGE AND AUTOMATA THEORY | - | 3 | 3 | 100 |
CS532E02 | COMPILER DESIGN | - | 3 | 3 | 100 |
CS532E03 | FUZZY LOGIC | - | 3 | 3 | 100 |
CS533P | INTERNET OF THINGS | - | 5 | 4 | 100 |
CS534 | DESIGN AND ANALYSIS OF ALGORITHMS | - | 4 | 4 | 100 |
CS535 | SOFTWARE ENGINEERING | - | 3 | 3 | 100 |
CS536P | INTERNET AND WEB PROGRAMMING | - | 5 | 4 | 100 |
CSHO531AIP | STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE | Minors and Honours | 4 | 4 | 100 |
CSHO531CSP | PROBABILITY AND RANDOM PROCESS | Minors and Honours | 5 | 4 | 100 |
CSHO531DAP | STATISTICAL FOUNDATION FOR DATA ANALYTICS | Minors and Honours | 5 | 4 | 50 |
6 Semester - 2018 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
CE636OE1 | SOLID WASTE MANAGEMENT | - | 3 | 3 | 100 |
CE636OE2 | ENVIRONMENTAL IMPACT ASSESSMENT | - | 3 | 3 | 100 |
CE636OE4 | DISASTER MANAGEMENT | - | 4 | 3 | 100 |
CS631 | CRYPTOGRAPHY AND NETWORK SECURITY | - | 3 | 3 | 100 |
CS632P | OBJECT ORIENTED ANALYSIS AND DESIGN | - | 5 | 4 | 100 |
CS633P | SYSTEM SOFTWARE | - | 5 | 4 | 100 |
CSHO631AI | ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | Minors and Honours | 5 | 4 | 100 |
CSHO631AIP | ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING | Minors and Honours | 5 | 4 | 100 |
CSHO631CS | MOBILE AND NETWORK-BASED ETHICAL HACKING | Minors and Honours | 5 | 4 | 100 |
CSHO631CSP | MOBILE AND NETWORK BASED ETHICAL HACKING | Minors and Honours | 5 | 4 | 100 |
CSHO631DA | BIG DATA ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO631DAP | BIG DATA ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO632AI | ROBOTICS AND PROCESS AUTOMATION | Minors and Honours | 5 | 4 | 100 |
CSHO632AIP | ROBOTICS AND PROCESS AUTOMATION | Minors and Honours | 5 | 4 | 100 |
CSHO632CS | CYBER FORENSICS AND MALWARE DETECTION | Minors and Honours | 5 | 4 | 100 |
CSHO632CSP | CYBER FORENSICS AND MALWARE DETECTION | Minors and Honours | 5 | 4 | 100 |
CSHO632DA | BIG DATA SECURITY ANALYTICS | Minors and Honours | 5 | 4 | 100 |
CSHO632DAP | BIG DATA SECURITY ANALYTICS | Minors and Honours | 5 | 4 | 100 |
EC636OE1 | EMBEDDED BOARDS FOR IOT APPLICATIONS | - | 3 | 34 | 100 |
EC636OE4 | FUNDAMENTALS OF IMAGE PROCESSING | - | 3 | 3 | 100 |
EC636OE7 | E-WASTE MANAGEMENT AND RADIATION EFFECT | - | 3 | 3 | 100 |
EE636OE2 | NONCONVENTIONAL ENERGY SOURCES | - | 4 | 3 | 100 |
EE636OE3 | INTRODUCTION OF HYBRID ELECTRIC VEHICLES | - | 4 | 3 | 100 |
EE636OE6 | ROBOTICS AND AUTOMATION | - | 4 | 3 | 100 |
IT634P | DATAWAREHOUSING AND DATAMINING | - | 5 | 4 | 100 |
IT635 | SOFTWARE TESTING | - | 3 | 3 | 100 |
MA636OE3 | NUMERICAL SOLUTION OF DIFFERENTIAL EQUATIONS | - | 3 | 3 | 100 |
ME636OE3 | BASIC AUTOMOBILE ENGINEERING | - | 3 | 3 | 100 |
ME636OE4 | PROJECT MANAGEMENT | - | 3 | 3 | 100 |
ME636OE5 | BASIC AEROSPACE ENGINEERING | - | 3 | 3 | 100 |
7 Semester - 2017 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
BTGE 732 | ACTING COURSE | - | 2 | 2 | 100 |
BTGE 734 | DIGITAL WRITING | - | 2 | 2 | 100 |
BTGE 737 | PROFESSIONAL PSYCHOLOGY | - | 2 | 2 | 100 |
BTGE 744 | DIGITAL MARKETING | - | 2 | 2 | 100 |
BTGE 745 | DATA ANALYTICS THROUGH SPSS | - | 2 | 2 | 100 |
BTGE735 | DIGITAL MEDIA | - | 2 | 2 | 100 |
BTGE736 | INTELLECTUAL PROPERTY RIGHTS | - | 2 | 2 | 100 |
BTGE738 | CORPORATE SOCIAL RESPONSIBILITY | - | 2 | 2 | 100 |
BTGE739 | CREATIVITY AND INNOVATION | - | 2 | 2 | 100 |
BTGE741 | GERMAN | - | 2 | 2 | 100 |
BTGE749 | PAINTING AND SKETCHING | - | 2 | 2 | 100 |
BTGE750 | PHOTOGRAPHY | - | 2 | 2 | 100 |
BTGE754 | FUNCTIONAL ENGLISH | - | 4 | 2 | 100 |
CS731 | ARTIFICIAL INTELLIGENCE | - | 4 | 4 | 100 |
CS732 | CLOUD COMPUTING | - | 3 | 3 | 100 |
CS733P | MOBILE APPLICATION DEVELOPMENT | - | 5 | 4 | 100 |
CS735E01 | NATURAL LANGUAGE PROCESSING | - | 3 | 3 | 100 |
CS735E02 | RESEARCH METHODOLOGY | - | 3 | 3 | 100 |
CS736E01 | GRAPH THEORY | - | 3 | 3 | 100 |
CS736E03 | WIRELESS NETWORKS | - | 3 | 3 | 100 |
CS771 | INTERNSHIP | - | 2 | 2 | 50 |
CS772 | SERVICE LEARNING | - | 2 | 2 | 50 |
IT735E01 | INFORMATION SECURITY | - | 3 | 3 | 100 |
IT736E01 | SIMULATION AND MODELING | - | 3 | 3 | 100 |
IT736E03 | ADVANCED DATABASES | - | 3 | 3 | 100 |
IT736E04 | NETWORK ADMINISTRATION | - | 3 | 3 | 100 |
8 Semester - 2017 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
BTCY01 | CYBER SECURITY | - | 2 | 2 | 50 |
CS831E01 | QUANTUM COMPUTING | - | 3 | 3 | 100 |
CS831E02 | GRID COMPUTING | - | 3 | 3 | 100 |
CS831E03 | MOBILE COMPUTING | - | 3 | 3 | 100 |
CS832E01 | SOFTWARE TESTING | - | 3 | 3 | 100 |
CS832E02 | SOFTWARE PROCESS AND PROJECT MANAGEMENT | - | 3 | 3 | 100 |
CS833E02 | INTRODUCTION TO DATA SCIENCE | - | 3 | 3 | 100 |
CS833E03 | SOFT COMPUTING | - | 3 | 3 | 100 |
CS833E04 | DIGITAL IMAGE PROCESSING | - | 3 | 3 | 100 |
CS871 | PROJECT WORK | - | 12 | 6 | 200 |
CS872 | COMPREHENSION | - | 4 | 2 | 50 |
IT832E02 | WEB SERVICES AND SERVICE ORIENTED ARCHITECTURE | - | 3 | 3 | 100 |
IT833E04 | PROFESSIONAL ETHICS AND HUMAN VALUES | - | 3 | 3 | 100 |
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Introduction to Program: | |
The Undergraduate program in Information Technology is aimed at creating computer science engineers by providing the fundamentals of engineering and basic skills in computing. The special focus on employability is clear from the inclusion of subjects based on demand of industry and mandatory internships. A well-chosen elective basket gives the ward an opportunity to widen their knowledge in any specific domain. | |
Programme Outcome/Programme Learning Goals/Programme Learning Outcome: PO1: Apply Engineering knowledge of computing, mathematics, science, and computer science & engineering fundamentals for Problem solving.PO2: Think critically to identify, formulate, and solve complex computer science & engineering problems by developing models, evaluating validity and accuracy of solutions in terms of computer science and engineering validity measures. PO3: Analyse, design of complex problems, implement, and evaluate a computer-based system, to meet expected needs with appropriate considerations such as economic / environmental/societal. PO4: Conduct experiments to investigate problems based on changing requirements, analyze and interpret results. PO5: Create, select, adapt appropriate techniques and use of the modern computational tools, techniques and skills, and best of engineering practices. PO6: Understand the impact of contextual knowledge on social aspects and cultural issues. PO7: Understand contemporary issues related to social & environmental context for sustainable development of engineering solutions. PO8: Understand professional & ethical responsibility to contribute for societal and national needs. PO9: Function and coordinate effectively as an individual, as a member or leader in diverse, multicultural& multidisciplinary teams PO10: Communicate effectively. PO11: Demonstrate an understanding of computer science and engineering & management principles to manage software projects. PO12: Demonstrate a recognition and realization of the need for, and an ability to engage in lifelong learning. | |
Assesment Pattern | |
II. ASSESSMENT - ONLY FOR THEORY COURSE (without practical component)
Components of the CIA CIA I: Subject Assignments / Online Tests: 10 marks CIA II: Mid Semester Examination (Theory): 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications: 10 marks Attendance: 05 marks Total: 50 marks
Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choices will be outlined from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a particular question. The objective of the question paper is to test the application and analytical skill of the student. The major purpose of the question paper is to bring clarity about the process of associating questions to their respective performance indicators and hence to improve the ratings in course outcomes. Further, these question papers demonstrate how bloom’s taxonomy can be used to map the quality of question papers along with their effectiveness in the assessment pattern.
III. ASSESSMENT OF COMPREHENSION, INTERNSHIP and SERVICE LEARNING COMPREHENSION Maximum Marks = 50 Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only,
The evaluation (minimum 2 presentations) shall be based on the
INTERNSHIP
Maximum Marks = 50(Only credit will be displayed in the score card) Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only Continuous Internal Assessment is based upon
SERVICE LEARNING Maximum Marks = 50 Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only, Comprising
V. ASSESSMENT OF PROJECT WORK Project Phase-I Project work may be assigned to a single student (with due approval from department) or to a group of students not exceeding 4 per group. Maximum Marks = 100
ESE 100 MARKS IS EVALUATED AS
Holistic Education: End Semester Examination :25 Marks Participation:25 Marks
Total :50 Marks
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Examination And Assesments | |
Continuous internal Assesment-CIA-I,CIA-II,CIA-III End Semester Examination |
CS331P - DATABASE MANAGEMENT SYSTEMS (2019 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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· To learn the fundamentals of data models and to conceptualize and depict a database system using ER diagram. · To make a study of SQL and relational database design. · To understand the internal storage structures using different file and indexing techniques which will help in physical DB design. · To know the fundamental concepts of transaction processing- concurrency control techniques and recovery procedure. · To have an introductory knowledge about the emerging trends in the area of distributed DB- OO DB- Data mining and Data Warehousing and XML. · To implement the design of the tables in DBMS. · To write queries to get optimized outputs. · To store, retrieve and view the contents. To generate report based on customized need.
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1 Summarize the fundamental concepts of databases and Entity-Relationship (E-R) model. L2 2 Apply E-R Model and Normalization principles to create relational databases for the given problems. L3 3 Compare and contrast different file organization concepts for data storage in Relational databases L4 4 Apply the transaction management principles on relational databases L3 5 Demonstrate the current trends such as object oriented databases, distributed data storage in database technology L2 |
Unit-1 |
Teaching Hours:15 |
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INTRODUCTION AND CONCEPTUAL MODELING
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Introduction to File and Database systems- Database system structure – Data Models – Introduction to Network and Hierarchical Models – ER model – Relational Model – Relational Algebra and Calculus. Lab Programs 1. Data Definition Language (DDL) commands in RDBMS 2. Data Manipulation Language (DML) and Data Control Language (DCL) commands in RDBMS. | |||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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RELATIONAL MODEL
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SQL – Data definition- Queries in SQL- Updates- Views – Integrity and Security – Relational Database design – Functional dependences and Normalization for Relational Databases (up to BCNF). Lab programs 3. High-level language extension with Cursors. 4.High level language extension with Triggers | |||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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DATA STORAGE AND QUERY PROCESSING
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Record storage and Primary file organization- Secondary storage Devices- Operations on Files- Heap File- Sorted Files- Hashing Techniques – Index Structure for files –Different types of Indexes- B-Tree - B+ Tree – Query Processing. Lab Programs 5. Procedures and Functions. 6. Embedded SQL. | |||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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TRANSACTION MANAGEMENT
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Transaction Processing – Introduction- Need for Concurrency control- Desirable properties of Transaction- Schedule and Recoverability- Serializability and Schedules – Concurrency Control – Types of Locks- Two Phases locking- Deadlock- Time stamp based concurrency control – Recovery Techniques – Concepts- Immediate Update- Deferred Update - Shadow Paging. Lab Programs 7. Database design using E-R model and Normalization. 8. Design and implementation of Payroll Processing System. | |||||||||||||||||||
Unit-5 |
Teaching Hours:15 |
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CURRENT TRENDS
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Object Oriented Databases – Need for Complex Data types- OO data Model- Nested relations- Complex Types- Inheritance Reference Types - Distributed databases- Homogenous and Heterogenous- Distributed data Storage – XML – Structure of XML- Data- XML Document- Schema- Querying and Transformation. – Data Mining and Data Warehousing. Lab Programs: 9. Design and implementation of Banking System 10.Design and implementation of Library Information System
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Text Books And Reference Books:
1. Abraham Silberschatz, Henry F. Korth and S. Sudarshan- “Database System Concepts”, Sixth Edition, McGraw-Hill, 2010.
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Essential Reading / Recommended Reading REFERENCE BOOKS 1. RamezElmasri and Shamkant B. Navathe, “Fundamental Database Systems”, Third Edition, Pearson Education, 2008. 2. Raghu Ramakrishnan, “Database Management System”, Tata McGraw-Hill Publishing Company, 2003
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Evaluation Pattern Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) · CIA 1 : Assignment and Quiz 10 marks CIA2 : Mid Semester Examination 10 marks CIA 3 : Practical Component and Mini Project 10 marks Lab : Laboratory program 35 marks Attendance -05 marks End Semester Examination(ESE) : 30% (30 marks out of 100 marks) | |||||||||||||||||||
CS332P - DATA STRUCTURES AND ALGORITHMS (2019 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Explain the basic concepts of data structures and solve the time complexity of the algorithm L3 2. Experiment with various operations on Linear Data structures L3 3. Examine the Structures and Operations of Trees and Heaps Data Structures L4 4 Compare various given sorting techniques with respect to time complexity L4 5 Choose various shortest path algorithms to determine the minimum spanning path for the given graphs L5 |
Unit-1 |
Teaching Hours:14 |
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INTRODUCTION
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Definition- Classification of data structures: primitive and non-primitive- Operations on data structures- Algorithm Analysis. LAB Programs: 1a. Sample C Programs 1b. To determine the time complexity of a given logic. | |||||||||||||||||||
Unit-2 |
Teaching Hours:17 |
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LISTS, STACKS AND QUEUES
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Abstract Data Type (ADT) – The List ADT – The Stack ADT: Definition,Array representation of stack, Operations on stack: Infix, prefix and postfix notations Conversion of an arithmetic Expression from Infix to postfix. Applications of stacks. LAB Programs: 2. Implement the applications Stack ADT. 3. Implement the applications for Queue ADT. 4.Operations on stack[e.g.: infix to postfix, evaluation of postfix] | |||||||||||||||||||
Unit-3 |
Teaching Hours:16 |
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TREES
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Preliminaries – Binary Trees – The Search Tree ADT – Binary Search Trees – AVL Trees – Tree Traversals – Hashing – General Idea – Hash Function – Separate Chaining – Open Addressing –Linear Probing – Priority Queues (Heaps) – Model – Simple implementations – Binary Heap. LAB PROGRAMS: 5. Search Tree ADT - Binary Search Tree | |||||||||||||||||||
Unit-4 |
Teaching Hours:14 |
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SORTING
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Preliminaries – Insertion Sort – Shell sort – Heap sort – Merge sort – Quicksort – External Sorting. LAB PROGRAMS 6. Heap Sort. 7. Quick Sort. 8.Applications of Probability and Queuing Theory Problems to be implemented using data structures. | |||||||||||||||||||
Unit-5 |
Teaching Hours:14 |
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GRAPHS
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Definitions – Topological Sort – Shortest-Path Algorithms – Unweighted Shortest Paths – Dijkstra‘s Algorithm – Minimum Spanning Tree – Prim‘s Algorithm – Applications of Depth- First Search – Undirected Graphs – Bi-connectivity – Introduction to NP-Completeness-case study LAB PROGRAMS 9. Implementing a Hash function/Hashing Mechanism. 10. Implementing any of the shortest path algorithms.
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Text Books And Reference Books: TEXT BOOK 1.Mark Allen Weiss , “Data Structures and Algorithm Analysis in C”, 2nd Edition, Addison-Wesley, 1997 | |||||||||||||||||||
Essential Reading / Recommended Reading 1. Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser , ―Data Structures and Algorithms in Python ‖, First Edition, John Wiley & Sons, Incorporated, 2013.ISBN1118476735, 9781118476734 | |||||||||||||||||||
Evaluation Pattern Components of the CIA CIA I : Assignment and Continuous Assessment : 10 marks CIA II : Mid Semester Examination (Theory) : 10 marks CIA III : Closed Book Test and Continuous Assessment: 10 marks Lab marks :35 marks Attendance : 05 marks End Semester Examination(ESE) : 30% (30 marks out of 100 marks) Total: 100 marks | |||||||||||||||||||
CS333 - SOFTWARE ENGINEERING (2019 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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· Learn different life cycle models and requirement elicitation process. · Understand various analysis modeling and specification, Architectural and detailed design methods. · Practice implementation methodologies and various testing strategies. · Analyze project planning and management concepts using various models and appropriate CASE tools. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL CO1 Explain the fundamental of Software development Life cycle and different software development process models. L2 CO2 Apply various requirement elicitation methods in software development process L3 CO3 Develop the software processes using various design techniques. L3 CO4 Analyze different testing techniques and maintenance principles in software development process. L4 CO5 Formulate the cost estimation techniques and project scheduling methods in software development process. L6 |
Unit-1 |
Teaching Hours:9 |
SOFTWARE PROCESS
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Introduction –S/W Engineering Paradigm – life cycle models (water fall, incremental, spiral, WINWIN spiral, evolutionary, prototyping, object oriented) - system engineering – computer based system – verification – validation – life cycle process – development process –system engineering hierarchy. | |
Unit-2 |
Teaching Hours:9 |
SOFTWARE REQUIREMENTS
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Functional and non-functional - user – system –requirement engineering process – feasibility studies – requirements – elicitation – validation and management – software prototyping – prototyping in the software process – rapid prototyping techniques – user interface prototyping -S/W document. Agile methods, Extreme Programming, SCRUM | |
Unit-3 |
Teaching Hours:9 |
DESIGN CONCEPTS AND PRINCIPLES
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Design process and concepts – modular design – design heuristic – design model and document. Architectural design – software architecture – data design – architectural design – transform and transaction mapping – user interface design – user interface design principles. Real time systems - Real time software design – system design – real time executives – data acquisition system - monitoring and control system. SCM – Need for SCM – Version control – Introduction to SCM process – Software configuration items. | |
Unit-4 |
Teaching Hours:9 |
TESTING
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Taxonomy of software testing – levels – test activities – types of s/w test – black box testing – testing boundary conditions – structural testing – test coverage criteria based on data flow mechanisms – regression testing – testing in the large. S/W testing strategies – strategic approach and issues - unit testing – integration testing – validation testing – system testing and debugging. | |
Unit-5 |
Teaching Hours:9 |
SOFTWARE PROJECT MANAGEMENT
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Measures and measurements – S/W complexity and science measure – size measure – data and logic structure measure – information flow measure. Software cost estimation – function point models – COCOMO model- Delphi method.- Defining a Task Network – Scheduling – Earned Value Analysis – Error Tracking - Software changes – program evolution dynamics – software maintenance – Architectural evolution. Taxonomy of CASE tools – Case Study. | |
Text Books And Reference Books: Roger S. Pressman, Software engineering- A Practitioner’s Approach, McGraw-Hill International Edition, 6th Edition 2014 | |
Essential Reading / Recommended Reading Anirban Basu, “Software Quality Assurance, Testing and Metrics”, First Edition, PHI Learning, 2015. Ian Sommerville, “Software engineering,” Pearson education Asia, 9th Edition, 2013. Pankaj Jalote- “An Integrated Approach to Software Engineering,” Narosa Publishing house, 2011. James F Peters and Witold Pedryez, “Software Engineering – An Engineering Approach”, John Wiley and Sons, New Delhi, 2010. Ali Behforooz and Frederick J Hudson, “Software Engineering Fundamentals”, OUP India 2012.
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Evaluation Pattern Continuos Internal Assessment CIA Marks 50 End Semester Exams ESE 50 | |
EC337 - DIGITAL SYSTEMS (2019 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· This course is an introduction to the VHDL language. The emphasis is on writing synthesizable code and enough simulation code to write a viable test-bench. · The information gained can be applied to any digital design by using a top-down synthesis design approach. |
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Course Outcome |
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At the end of the course, the student will be able to do: · Implement the VHDL portion of coding for synthesis. · Identify the differences between behavioral and structural coding styles. · Understand the basic principle of circuit design and analysis. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND METHODOLOGY
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Digital Systems and Embedded Systems, Boolean Functions and Boolean algebra, Binary Coding, Combinational Components and Circuits, Verification of Combinational Circuits. Number Basics: Unsigned and Signed Integers, Fixed and Floating-point Numbers, Binary representation and Circuit Elements, Real-World Circuits, Models, Design Methodology. | |
Unit-2 |
Teaching Hours:9 |
SEQUENTIAL BASICS & MEMORIES
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Storage elements, Counters, Sequential Data paths and Control, Clocked Synchronous Timing Methodology. Memories: Concepts, Memory Types, Error Detection and Correction. | |
Unit-3 |
Teaching Hours:9 |
IMPLEMENTATION FABRICS & PROCESSOR BASICS
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ICs, PLDs, Packaging and Circuit Boards, Interconnection and Signal Integrity. Processor Basics: Embedded Computer Organization, Instruction and Data, Interfacing with memory. | |
Unit-4 |
Teaching Hours:9 |
I/O INTERFACING, ACCELERATORS & DESIGN METHODOLOGY
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I/O devices, I/O controllers, Parallel Buses, Serial Transmission, I/O software. Accelerators: Concepts, case study, Verification of accelerators. Design Methodology: Design flow, Design optimization, Design for test. | |
Unit-5 |
Teaching Hours:9 |
SIMPLE SINGLE CYCLE AND MULTI CYCLE PROCESSOR DESIGN
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Introduction of Simple Single Cycle and Multi Cycle Processor Design. | |
Text Books And Reference Books: 1. C. H. Roth, Digital Systems Design Using VHDL, Thomson Publications, Fourth Edition, 2002. V. A. Pedroni, Circuit Design with VHDL, MIT Press/PHI, 2004. | |
Essential Reading / Recommended Reading 1. Parhami, Behrooz, Computer Arithmetic: Algorithms and Hardware Designs, Oxford University Press, 2009. 2. Z. Navabi, Verilog Digital System Design, Second Edition, Tata McGrawHill, 2008. 3. R. C. Cofer and B. F. Harding, Rapid System Prototyping with FPGAs: Accelerating the Design Process, Elsevier/Newness, 2005. Peter J. Ashenden, “Digital Design: An Embedded Systems Approach Using VERILOG”, Elesvier, 2010. | |
Evaluation Pattern Assessment is based on the performance of the student throughout the semester. Assessment of each paper · Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Mid Semester Examination (Theory) : 25 marks CIA II : Assignments : 10 marks CIA III : Quizzes/Seminar/Case Studies/Project Work : 10 marks Attendance : 05 marks Total : 50 marks For subjects having practical as part of the subject
Assessment of Practical paper Conduct of experiments : 25 marks Observations/Lab Record : 15 marks Viva voce : 10 marks Total : 50 marks (All the above assessments are carried for each experiment during regular lab classes and averaged to max 50 marks at the end of the semester) | |
HS311 - TECHNICAL WRITING (2019 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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The goal of this course is to prepare engineering students with individual and collaborative technical writing skills that are necessary to be effective technical communicators in academic and professional environments. |
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Course Outcome |
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CO1. Understand the basics of technical communication and the use of formal elements of specific genres of documentation. CO2. Demonstrate the nuances of technical writing, with reference to english grammar and vocabulary. CO3. Recognize the importance of soft skills and personality development for effective communication. CO4. Understand the various techniques involved in oral communication and its application. CO5. Realize the importance of having ethical work habits and professional etiquettes. |
Unit-1 |
Teaching Hours:6 |
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Design and Development
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Different kinds of technical documents, Information development life cycle, Organization structures, factors affecting information and document design, Strategies for organization, Information design and writing for print and for online media. | |||||||||||||||||||
Unit-2 |
Teaching Hours:6 |
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Grammar and Editing
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Technical writing process, writing drafts and revising, technical writing style and language. Basics of grammar, study of advanced grammar, editing strategies to achieve appropriate technical style. Introduction to advanced technical communication | |||||||||||||||||||
Unit-3 |
Teaching Hours:6 |
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Self Development and Assessment
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Self-assessment, Perception and Attitudes, Values and belief, Personal goal setting, career planning, Self- esteem. Managing Time; Personal memory, Rapid reading, Taking notes; Complex problem solving; Creativity | |||||||||||||||||||
Unit-4 |
Teaching Hours:6 |
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Communication and Writing
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Public speaking, Group discussion, Oral presentation, Interviews, Presentation aids, Personality Development. project proposals, brochures, newsletters, technical articles, manuals, business letters, memos | |||||||||||||||||||
Unit-5 |
Teaching Hours:6 |
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Business Etiquettes
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Etiquettes in social and office settings, Email etiquettes, Telephone Etiquettes, Engineering ethics, Time Management, Role and responsibility of engineer, Work culture in jobs | |||||||||||||||||||
Text Books And Reference Books: T1 : David F. Beer and David McMurrey, Guide to writing as an Engineer, John Willey. New York, 2004 T2: Diane Hacker, Pocket Style Manual, Bedford Publication, New York, 2003. (ISBN 0312406843) T3: Raman Sharma, Technical Communications, Oxford Publication, London, 2004 | |||||||||||||||||||
Essential Reading / Recommended Reading R1.Dale Jungk, Applied Writing for Technicians, McGraw Hill, New York, 2004. (ISBN: 07828357-4) R2. Sharma, R. and Mohan, K. Business Correspondence and Report Writing, TMH New Delhi 2002. R3. Xebec, Presentation Book, TMH New Delhi, 2000. (ISBN 0402213) | |||||||||||||||||||
Evaluation Pattern CIA 1 - 10 Marks Mid Semester Exams - 25 Marks CIA 2 - 10 Marks End Semester Exams - 50 Marks Attendance - 5 marks | |||||||||||||||||||
MA334 - DISCRETE MATHEMATICS (2019 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To extend student’s mathematical maturity and ability to deal with abstraction and to introduce most of the basic terminologies used in computer science courses and application of ideas to solve practical problems. The objective of the paper is to develop: · The knowledge of the concepts needed to test the logic of a program.· Knowledge which has application in expert system, in data base and a basic for the programing language.· An understanding in identifying patterns on many levels.· Awareness about a class of functions which transform a finite set into another finite set that relates to input output functions in computer science. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1 Checking the consistency of system of linear equations and solving by Gauss Jordan and Gauss Elimination methods, finding the spectral matrix with the aid of eigen values and eigen vector L3 2 Finding the differentiation of multivariable functions using the concept of total derivatives, Jacobian, evaluating definite integrals by Leibnitz rule of differentiation under integral sign L4 3 Evaluating the definite integrals as surface area and volume of solid of revolution by tracing the curves and using reduction formulae L4 4 Solving first order nonlinear differential equations by reducing into homogenous, linear and exact forms L3 5 Finding the velocity and acceleration of a moving particle, vector potential, scalar potential L3 |
Unit-1 |
Teaching Hours:9 |
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Propositional Calculus:
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Propositions Logical connectives Compound propositions Conditional and bi conditional propositions Truth tables Tautologies and contradictions Contrapositive Logical equivalences and implications De Morgans Laws - Normal forms Principal conjunctive and disjunctive normal forms Rules of inference Arguments - Validity of arguments. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Predicate Calculus:
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Predicates Statement Function Variables Free and bound variables Quantifiers Universe of discourse Logical equivalences and implications for quantified statements Theory of inference The rules of universal specification and generalization Validity of arguments | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Set Theory
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Basic concepts Notations Subset Algebra of sets The power set Ordered pairs and Cartesian product Relations on sets Types of relations and their properties Matrix and Graph representation of a relation Partial ordering Poset Hasse diagram Lattices and their properties Sublattices Boolean algebra. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Functions:
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Definitions of functions Classification of functions Types of functions - Examples Composition of functions Inverse functions Characteristic function of a set Hashing functions Permutation functions. | |||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Groups:
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Groups - Properties Subgroups - Cosets and Lagranges theorem Normal subgroups Algebraic system with two binary operations Preliminaries of Coding - Hamming Metric - group codes: Basic notions of error correction - Error recovery in group codes. | |||||||||||||||||||||||||||||
Text Books And Reference Books: Text Books T1. Trembly J.P and Manohar R, Discrete Mathematical Structures with Applications to Computer Science, Tata McGrawHill Pub.Co. Ltd, New Delhi, 2003. T2. Ralph. P. Grimaldi, Discrete and Combinatorial Mathematics: An Applied Introduction, Fifth Edition, Pearson Education Asia,Delhi, 2009. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Reference Books 1. R1. Bernard Kolman, Robert C. Busby, Sharan Cutler Ross, Discrete Mathematical Structures, Fourth Indian reprint, Pearson Education Pvt Ltd., New Delhi, 2003. 2. R2. Kenneth H. Rosen, Discrete Mathematics and its Applications, Fifth Edition, Tata McGraw Hill Pub. Co. Ltd., New Delhi, 2003. 3. R3. .Richard Johnsonbaugh, Discrete Mathematics, Fifth Edition,Pearson Education Asia, New Delhi, 2002. 4. R4. Dr K.S.C , Discrete Mathematical Structures, 5th Edition, Prism Engineering Education Series2018. 5. R5. S Santha, Discrete Mathematics with Combinatorics and Graph Theory Cengage, 1st Edition, 2019 | |||||||||||||||||||||||||||||
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII:Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks Mid Semester Examination (MSE) : Theory Papers:
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows. Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 % - Medium Level questions 25 % - Simple level questions 25 % - Complex level questions | |||||||||||||||||||||||||||||
MC321 - CYBER SECURITY (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:50 |
Credits:0 |
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Course Objectives/Course Description |
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This course is aimed at providing a comprehensive overview of the different facets of Cyber Security. In addition, the course will detail into specifics of Cyber Security with Cyber Laws both in Global and Indian Legal environments |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Summarize the network security concepts and cyber laws L2 2. Explain different cyber attacks with relevant examples L2 3. Illustrate risk management process handled in the organization with business continuity planning L2 4. Outline the vulnerabilities that affect the organizational network L2 5. Identify cryptography algorithms for authentication purposes in the organizational network L3 |
Unit-1 |
Teaching Hours:6 |
Security Fundamentals
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Security Fundamentals-4 As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security. Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber- Security Initiative CNCI – Legalities. | |
Unit-2 |
Teaching Hours:6 |
Cyber Attack and Cyber Services
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Cyber Attack and Cyber Services: Computer Virus – Computer Worms – Trojan horse. Vulnerabilities - Phishing - Online Attacks – Pharming - Phoarging – Cyber Attacks – Cyber Threats - Zombie- stuxnet - Denial of Service Vulnerabilities - Server Hardening-TCP/IP attack- SYN Flood. | |
Unit-3 |
Teaching Hours:6 |
Cyber Security Management
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Cyber Security Management : Risk Management and Assessment - Risk Management Process - Threat Determination Process -Risk Assessment - Risk Management Lifecycle. Security Policy Management - Security Policies - Coverage Matrix. Business Continuity Planning - Disaster Types - Disaster Recovery Plan - Business Continuity Planning Process. | |
Unit-4 |
Teaching Hours:6 |
Vulnerability - Assessment and Tools
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Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box Architectural Integration: Security Zones - Devices viz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security | |
Unit-5 |
Teaching Hours:6 |
Authentication and Cryptography
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Authentication and Cryptography: Authentication -Cryptosystems - Certificate Services .Securing Communications: Securing Services - Transport – Wireless - Steganography and NTFS Data Streams. Intrusion Detection and Prevention Systems: Intrusion - Defense in Depth - IDS/IPS - IDS/IPS Weakness and Forensic Analysis. Cyber Evolution: Cyber Organization - Cyber Future | |
Text Books And Reference Books:
1. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, Cyber Security Policy Guidebook, Wiley; 1 edition , 2012, ISBN-10: 1118027809 2. Dan Shoemaker and Wm. Arthur Conklin, Cybersecurity: The Essential Body Of Knowledge, Delmar Cengage Learning; 1 edition (May 17, 2011) ,ISBN-10: 1435481690 | |
Essential Reading / Recommended Reading 1. Matt Bishop, “Computer Security Art and Science”, Pearson/PHI, 2009. 2. Stuart Mc Clure, Joel Scrambray, George Kurtz, “Hacking Exposed”, 7th Edition Tata McGraw-Hill, 2012. 3. Jason Andress, The Basics of Information Security: Understanding the Fundamentals of InfoSec in Theory and Practice, Syngress; 1 edition (June 24, 2011) , ISBN-10: 1597496537 4. Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 3rd Edition 2002. 5. Bruce, Schneier, “Applied Cryptography”, 2nd Edition, Toha Wiley & Sons, 2007. 6. Man Young Rhee, “Internet Security”, Wiley, 2003. 7. Pfleeger & Pfleeger, “Security in Computing”, Pearson Education, 3rd Edition, 2003. | |
Evaluation Pattern Continuous Internal Assessment (CIA) for theory papers : 100% (50 marks out of 50 marks)
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MIMBA331 - PRINCIPLES OF MANAGEMENT (2019 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:6 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: This is offered as a core course in first trimester. This course will provide a general introduction to management principles and theories, and a brief outline on history and development of management thought. Course Objectives : This course describes the steps necessary to understand an organisation that are aligned with business objectives and provides an insight to address a range of challenges that every manager encounters. It aims to prepare students for an exciting challenging and rewarding managerial career through case studies on ‘Global Perspective’. |
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Course Outcome |
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Course Learning Outcomes: On having completed this course student should be able to: CLO1 Understand different management approaches CLO2 Demonstrate planning techniques CLO3 Able to work in dynamic teams within organizations CLO4 Analyze different processes in staffing and controlling |
Unit-1 |
Teaching Hours:12 |
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Unit 1. Nature, Purpose and Evolution of Management Thought
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Meaning; Scope; Managerial levels and skills; Managerial Roles; Management: Science, Art or Profession; Universality of Management. Ancient roots of management theory; Classical schools of management thought; Behavioral School, Quantitative School; Systems Approach, Contingency Approach; Contemporary Management thinkers & their contribution. Ancient Indian Management systems & practices. Comparative study of global management systems & practices.
Evolution of Management: Teaching management through Indian Mythology (Videos of Devdutt Pattanaik, Self-learning mode) | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:12 |
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Unit 2. Planning
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Types of Plans; Steps in Planning Process; Strategies, level of Strategies, Policies and Planning; Decision making, Process of Decision Making, Techniques in Decision Making, Forecasting & Management by Objectives (MBO).
Planning: HBS Case and Projects of Events | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:12 |
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UnitUnit 3. Organizing
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Organizational structure and design; types of organizational structures; Span of control, authority, delegation, decentralization and reengineering. Social responsibility of managers, Managerial Ethics.
Organizing: Holacracy form of organization structure, HBS Case | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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Unit 4. Staffing
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Human resource planning, Recruitment, selection, training & development, performance appraisal, managing change, compensation and employee welfare. Motivation: Concept, Forms of employee motivation, Need for motivation, Theories of motivation, Stress Management Staffing: Stress Management & Career path, HBS Case | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:12 |
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Unit 5. Leading and Controlling
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Leadership concept, leadership Styles, leadership theories, leadership communication. Nature of organizational control; control process; Methods and techniques of control; Designing control systems, Quality Management Leading: Article on Styles of leadership by Daniel Goleman Controlling: HBS Case and Projects of Events | |||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: Text Books: T1. Heinz Weihrich, Mark V Cannice & Harold Koontz (2019). Management (15th Edition). McGraw Hill Publications. | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Reference Books: R1. Daft, R. L. (2016). The new era of management (11th Edition). Cengage Publications. R2. Prasad, L.M., Principles and practices of management. New Delhi: Sultan Chand & Sons. | |||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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MIPSY331 - UNDERSTANDING HUMAN BEHAVIOR (2019 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This course focuses on the fundamentals of psychology. It is an introductory paper that gives an overall understanding about the human behavior. It will provide students with an introduction to the key concepts, perspectives, theories, and sub-fields on various basic processes underlying human behavior. Objectives
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Course Outcome |
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After the completion of this course students will be able to: |
Unit-1 |
Teaching Hours:12 |
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SENSATION
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Definition, Characteristics of Sensory modalities: Absolute and difference threshold; Signal detection theory; sensory coding; Vision, Audition, Other Senses. Assessment of Perception and Sensation | |||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:12 |
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PERCEPTION
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Definition, Understanding perception, Gestalt laws of organization, Illusions and Perceptual constancy; Various sensory modalities; Extrasensory perception. Practicum: Muller-Lyer Illusion | |||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:12 |
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LEARNING
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Learning:Definition, Classical conditioning, Instrumental conditioning, learning and cognition; | |||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:12 |
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MEMORY
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Types of Memory; Sensory memory, working memory, Long term memory, implicit memory, Constructive memory, improving memory; Assessment of memory. Practicum: Memory drum | |||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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INDIVIDUAL DIFFERENCES
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Concepts and nature of Individual differences; Nature vs. nurture; Gender difference in cognitive processes and social behavior; | |||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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INTELLIGENCE
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Definition, Contemporary theories of intelligence; Tests of intelligence; Emotional, Social and Spiritual intelligence. Practicum: Bhatia’s Battery of Performance | |||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:12 |
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PERSONALITY
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Definition, Type and trait theories of personality, Type A, B & C. Psychoanalytic - Freudian perspective; Types of personality assessment. Practicum: NEO-FFI 3 | |||||||||||||||||||||||||||
Text Books And Reference Books: Baron, R. A. (2001). Psychology. New Delhi: Pearson Education India. Rathus, S. A. (2017). Introductory Psychology, 5thEd. Belmont, CA: Wadsworth. Nolen-Hoeksema, S., Fredrickson, B.L. & Loftus, G.R. (2014). Atkinson & Hilgard'sIntroduction to Psychology.16th Ed. United Kingdom: Cengage Learning. | |||||||||||||||||||||||||||
Essential Reading / Recommended Reading Feldman, R. S. (2011). Understanding Psychology. New Delhi: Tata McGraw Hill. Morgan, C. T., King, R. A., & Schopler, J. (2004). Introduction to Psychology. New Delhi: Tata McGraw Hill. Kalat, J. W. (2016). Understanding Psychology. New York: Cengage Learning. | |||||||||||||||||||||||||||
Evaluation Pattern
Mid Semester Examination
End Semester Examination
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BS451 - BIO SCIENCE LABORATORY (2019 Batch) | |||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:50 |
Credits:1 |
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Course Objectives/Course Description |
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Course Outcome |
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Course outcomes: At the end of the course, the student will be able to do: ● Examine the applications of bioengineering and using common tool boxes for analysing medical information. |
Unit-1 |
Teaching Hours:30 |
list of experiments
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1. Blood Pressure Measurement using Arduino 2. To determine the R peaks in given ECG and to find HRV using Matlab. 3. To familiarize with the fundamentals of image processing in Matlab using simple tools and functions. 4. To determine the presence of fractures in the given X-ray file using simple Matlab image processing 5. To determine the presence of fractures in the given X-ray file using simple Matlab image processing toolbox. 6. Introduction to Tinkercad and using the various tools available for running a simple program of lighting a LED bulb using Arduino (digital). 7. To design a temperature sensor in Tinkercad using Arduino and TMP36.. 8. To design and simulate muscle contraction using potentiometers, Arduino and servo motors. 9. To design and simulate measuring pulse sensors using photodiodes, IR LED and Arduino. 10. Preparation of biopolymers (polylactic acid) at home using home-based ingredients. | |
Text Books And Reference Books: NA | |
Essential Reading / Recommended Reading NA | |
Evaluation Pattern As per the university criteria | |
CS431 - PROBABILITY AND QUEUING THEORY (2019 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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At the end of the course, the students would have a fundamental knowledge of the basic probability concepts. Have a well – founded knowledge of standard distributions which can describe real life phenomena. Acquire skills in handling situations involving more than one random variable and functions of random variables. Understand and characterize phenomena which evolve with respect to time in a probabilistic manner. Be exposed to basic characteristic features of a queuing system and acquire skills in analyzing queuing models. |
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Course Outcome |
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CO1: Explain the basic perceptions of probability of an event and associated random variables. CO2: Compare and contrast various standard distributions with suitable statistical analysis. CO3: Apply and solve two dimensional random variable problems through joint distributions and central limit theorem. CO4: Analyze probabilistic environment using random process and markov chain techniques. CO5: Build and implement queuing model associated to stochastic process. |
Unit-1 |
Teaching Hours:9 |
PROBABILITY AND RANDOM VARIABLE
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Axioms of probability - Conditional probability - Total probability – Baye’s theorem Random variable - Probability mass function - Probability density function - Properties – Moments - Moment generating functions and their properties. | |
Unit-2 |
Teaching Hours:9 |
STANDARD DISTRIBUTIONS
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Binomial, Poisson, Geometric, Negative Binomial, Uniform, Exponential,Gamma, Weibull and Normal distributions and their properties - Functions of a random variable. | |
Unit-3 |
Teaching Hours:9 |
TWO DIMENSIONAL RANDOM VARIABLES
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Joint distributions - Marginal and conditional distributions – Covariance Correlation and regression - Transformation of random variables - Central limit theorem. | |
Unit-4 |
Teaching Hours:9 |
RANDOM PROCESSES AND MARKOV CHAINS
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Classification - Stationary process - Markov process - Poisson process - Birth and death process - Markov chains - Transition probabilities - Limiting distributions. Transition Diagram. | |
Unit-5 |
Teaching Hours:9 |
QUEUING THEORY
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Markovian models – M/M/1, M/M/C, finite and infinite capacity - M/M/∞ queues - Finite source model - M/G/1 queue (steady state solutions only) – Pollaczek – Khintchine formula – Special cases.Single and Multiple Server System. | |
Text Books And Reference Books: 1. Ross, S., “A first course in probability”,Sixth Edition, Pearson Education, Delhi, 2002. 2. Medhi J., “Stochastic Processes”, New Age Publishers, New Delhi, 1994. (Chapters 2, 3,4) 3. T.Veerarajan, “Probability, Statistics and Random process”, Second Edition, Tata McGraw Hill, New Delhi, 2003 | |
Essential Reading / Recommended Reading 1. Allen A.O., “Probability, Statistics and Queuing Theory”, Academic press, New Delhi, 1981. 2. Taha H. A., “Operations Research-An Introduction”,Seventh Edition, Pearson Education Edition Asia, Delhi, 2002. 3. Gross, D. and Harris, C.M., “Fundamentals of Queuing theory”, John Wiley. | |
Evaluation Pattern
● End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS432P - OPERATING SYSTEMS (2019 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Objectives of this course is to have an overview of different types of operating systems. They also include an understanding of the components of an operating system; To develop knowledge of process management and have a thorough knowledge of storage management; To know the concepts of I/O and file systems.
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Course Outcome |
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CO1: Demonstrate the Structure, Components and its basic functionalities of Operating System CO2: Distinguish various process management principles for given problem using appropriate tool CO3: Elucidate the process synchronization mechanisms, deadlock environment and its solutions in the given processes CO4: Inspect various memory management strategies for the given problems in memory systems CO5: Build file structure to distribute the same across the memory. |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Introduction : What operating systems do, Computer System Architecture, Operating System Structure, Operating System Operations, Process Management, Memory Management, Storage Management, Protection and Security; System Structures: Operating System Services, User Operating System Interface, System Calls, Types of System Calls | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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PROCESS MANAGEMENT
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Process Management: Process Concept, Process Scheduling, Operations on Processes, Inter-process Communication; Threads: Overview, Multithreading Models, Thread Libraries; CPU Scheduling: Basic Concepts, Scheduling Criteria, Scheduling Algorithms, Multiple- Processor Scheduling | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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PROCESS SYNCHRONIZATION AND DEADLOCKS
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Process Synchronization: Background, The Critical Section Problem, Peterson’s Solution, Synchronization Hardware, Semaphores, Classical Problems of Synchronization, Monitors, Synchronization Examples, Deadlocks | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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MEMORY MANAGEMENT AND VIRTUAL MEMORY
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Memory Management: Background, Swapping, Contiguous Memory Allocation, Paging, Virtual Memory: Background, Demand Paging, Copy on Write, Page Replacement, Allocation of frames, Thrashing, Allocating Kernel Memory
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Unit-5 |
Teaching Hours:9 |
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FILE SYSTEM INTERFACE AND FILE SYSTEM IMPLEMENTATION & MASS STORAGE STRUCTURE
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File System Interface: File System: File Concept, Access Methods, Directory Structure, File System Mounting, File Sharing, Protection; File System Implementation & Mass Storage Structure: Implementing File Systems: File System Structure, File System Implementation, Directory Implementation, Allocation Methods, Free Space Management. Disk structure, Disk Attachment, Disk Scheduling Methods, Disk Management, Swap-Space Management | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Abraham Silberschatz, Peter Baer Galvin and Greg Gagne, “Operating System Concepts”, Ninth Edition, John Wiley & Sons (ASIA) Pvt. Ltd, 2013. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Harvey M. Deitel, “Operating Systems”, Third Edition, Pearson Education Pvt. Ltd, 2007. 2. Andrew S. Tanenbaum, “Modern Operating Systems”, Prentice Hall of India Pvt. Ltd, 2009. 3. William Stallings, “Operating System”, Pearson Education 2009 4. Pramod Chandra P. Bhatt – “An Introduction to Operating Systems, Concepts and Practice”, PHI, 2010. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CS433P - PROGRAMMING PARADIGM (2019 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Software development in business environment has become more sophisticated, the software implementation is becoming increasingly complex and requires the best programming paradigm which helps to eliminate complexity of large projects. Object Oriented Programming (OOP) has become the predominant technique for writing software at present. Many other important software development techniques are based upon the fundamental ideas captured by object-oriented programming. The course also caters to the understanding of event driven programming, generic programming and concurrent programming. By the end of this COURSE, the student should acquire the basic knowledge and skills necessary to implement the concepts of various programming paradigms. |
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Course Outcome |
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CO1: Demonstrate the fundamental concepts of Object Oriented Programming.(L2) CO2: Make use of the inheritance and interface concepts for effective code reuse.(L3) CO3: Inspect dynamic and interactive graphical applications using AWT and SWING.(L4) CO4: Build an application using generic programming and exception handling concepts.(L6) CO5: Assess and design concurrent and parallel applications using multithreaded concepts.(L5) |
Unit-1 |
Teaching Hours:9 |
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OBJECT-ORIENTED PROGRAMMING - FUNDAMENTALS
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Review of OOP - Objects and classes in Java – defining classes – methods - access specifiers – static members – constructors – finalize method – Arrays – Strings - Packages – JavaDoc comments. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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OBJECT-ORIENTED PROGRAMMING - INHERITANCE
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Inheritance – class hierarchy – polymorphism – dynamic binding – final keyword – abstract classes – the Object class – Reflection – interfaces – object cloning – inner classes. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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EVENT-DRIVEN PROGRAMMING
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Graphics programming – Frame – Components – working with 2D shapes – Using color, fonts, and images - Basics of event handling – event handlers – adapter classes – actions – mouse events – AWT event hierarchy – introduction to Swing – Model-View- Controller design pattern – buttons – layout management – Swing Components | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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GENERIC PROGRAMMING
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Motivation for generic programming – generic classes – generic methods – generic code and virtual machine – inheritance and generics – reflection and generics – exceptions – exception hierarchy – throwing and catching exceptions. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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CONCURRENT PROGRAMMING
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Multi-threaded programming – interrupting threads – thread states – thread properties – thread synchronization – thread-safe Collections – Executors – synchronizers – threads and event-driven programming, Parallel programming –fork, join framework. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Herbert Schildt, “Java The Complete Reference” , Ninth Edition, McGraw Hill Publishers 2014. 2. Cay S. Horstmann and Gary Cornell, “Core Java: Volume I – undamentals”, Eighth Edition, Sun Microsystems Press, 2008. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Paul Deitel and Harvey Deitel , “Java How to program”, Tenth Edition, Deitel, 2016. 2. Ivan BratikoPROLOG: Programming for Artificial Intelligence, Third Edition, Pearson Publisher, 2002. 3. Bruce Eckel, “Thinking in Java”, 4th Edition, February 20, 2006. 4. Doug Rosenberg, Matt Stephens, “Use Case Driven Object Modeling with UML: Theory and Practice (Expert's Voice in UML Modeling)”, January 16, 2013. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CS434 - FORMAL LANGUAGE AND AUTOMATA THEORY (2019 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To have an understanding of finite state and pushdown automata. To have a knowledge of regular languages and context free languages. To know the relation between regular language, context free language and corresponding recognizers. To study the Turing machine and classes of problems. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Design finite automata with conversion between types of finite automata. L2 2. Develop regular expression and minimize the given finite automata for any regular language. L3 3. Develop context free grammar, parse trees and pushdown automata for a given context free language. L3 4. Experiment with CFLs and design of Turing machine for a given language. L3 5. Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis. L2 |
Unit-1 |
Teaching Hours:8 |
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Automaton
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Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:10 |
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Regular Expressions and Languages
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Regular Expression – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:10 |
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Context-Free Grammar and Languages
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Context-Free Grammar (CFG) – Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata – Equivalence of Pushdown automata and CFG, Deterministic Pushdown Automata. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Properties of Context-Free Languages
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Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Programming Techniques for TM. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:8 |
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Undecidability
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A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 200 | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. H.R. Lewis and C.H. Papadimitrou, “Elements of the Theory of Computation”, Second Edition, Pearson Education/PHI, 2003 R2. J.Martin, “Introduction to Languages and the Theory of Computation”, Third Edition, TMH, 2003. R3. Michael Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 1997. | |||||||||||||||||||||||||||||||
Evaluation Pattern Assessment of each paper
Components of the CIA
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CS435P - COMPUTER ORGANIZATION AND ARCHITECTURE (2019 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This course will help the students to learn about basic structure of computer system, design of arithmetic and logic unit with the implementation of fixed and floating point numbers. Further, it will give knowledge about design of control unit and pipelined processing concepts. It discusses about various parallel processing architectures, different memory systems and I/O Communication systems |
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Course Outcome |
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CO1: Demonstrate the functions of basic components of computer system and Instruction set Architecture CO2: Identify suitable control unit design and pipelining principles in computer architecture design CO3: Utilize appropriate instruction level parallelism concepts in multiprocessing environment CO4: Select suitable arithmetic algorithm to solve given arithmetic and logical problems CO5: Choose suitable memory and I/O system design |
Unit-1 |
Teaching Hours:9 |
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FUNDAMENTALS OF COMPUTER SYSTEM
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Functional Units – Basic Operational Concepts – Performance – Instructions: Language of the Computer – Operations, Operands – Instruction representation – Logical operations – decision making – MIPS Addressing.
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Unit-2 |
Teaching Hours:9 |
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COMPUTER ARTHIMETIC
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Addition and Subtraction – Multiplication – Division – Floating Point Representation – Floating Point Operations – Subword Parallelism
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Unit-3 |
Teaching Hours:9 |
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BASIC PROCESSING AND CONTROL UNIT
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A Basic MIPS implementation – Building a Datapath – Control Implementation Scheme – Pipelining – Pipelined datapath and control – Handling Data Hazards & Control Hazards – Exceptions.
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Unit-4 |
Teaching Hours:9 |
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PARALLELISM
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Parallel processing challenges – Flynn‘s classification – SISD, MIMD, SIMD, SPMD, and Vector Architectures - Hardware multithreading – Multi-core processors and other Shared Memory Multiprocessors - Introduction to Graphics Processing Units, Clusters, Warehouse Scale Computers and other Message-Passing Multiprocessors.
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Unit-5 |
Teaching Hours:9 |
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MEMORY AND I/O
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Memory Hierarchy - memory technologies – cache memory – measuring and improving cache performance – virtual memory, TLB‘s – Accessing I/O Devices – Interrupts – Direct Memory Access – Bus structure – Bus operation – Arbitration – Interface circuits - USB.
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Text Books And Reference Books: T1. David A. Patterson and John L. Hennessy, “Computer Organization and Design: The Hardware/Software Interface”, Fifth Edition, Morgan Kaufmann / Elsevier, 2014. T2. Carl Hamacher, ZvonkoVranesic, SafwatZaky and NaraigManjikian, “Computer Organization and Embedded Systems”, Sixth Edition, Tata McGraw Hill, 2012. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. William Stallings, “Computer Organization and Architecture – Designing for Performance”, Eighth Edition, Pearson Education, 2010. R2. John L. Hennessey and David A. Patterson, “Computer Architecture – A Quantitative Approach”, Fifth Edition, Morgan Kaufmann / Elsevier Publishers, 2012. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CS436 - PROFESSIONAL ETHICS (2019 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Able to understand the importance of Values and Ethics in their personal and professional lives. Able to learn the rights and responsibilities as an employee, team member and a global citizen. |
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Course Outcome |
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CO1: Describe the values of Ethics in our lives. CO2: Illustrate the professional Ethical theories CO3 Discuss the ethics in working place. CO4: Investigate the need of ethics as global issue. CO5: Summarize professional ethics, professional rights , responsibilitiesof an engineer. |
Unit-1 |
Teaching Hours:9 |
Introduction to Professional Ethics
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Basic Concepts, Governing Ethics, Personal & Professional Ethics, Ethical Dilemmas, Life Skills, Emotional Intelligence, Thoughts of Ethics, Value Education, Dimensions of Ethics, Profession and professionalism, Professional Associations, Professional Risks, Professional Accountabilities, Professional Success, Ethics and Profession. | |
Unit-2 |
Teaching Hours:9 |
Ethical Theories
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Ethical Theories: Basic Ethical Principles, Moral Developments, Deontology, Utilitarianism, Virtue Theory, Rights Theory, Casuist Theory, Moral Absolution, Moral Rationalism, Moral Pluralism, Ethical Egoism, Feminist Consequentialism, Moral Issues, Moral Dilemmas, Moral Autonomy. | |
Unit-3 |
Teaching Hours:9 |
Ethics in Engineering profession
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Professions and Norms of Professional Conduct, Norms of Professional Conduct vs. Profession; Responsibilities, Obligations and Moral Values in Professional Ethics, Professional codes of ethics, the limits of predictability and responsibilities of the engineering profession. Central Responsibilities of Engineers – The Centrality of Responsibilities of Professional Ethics; lessons from 1979 American Airlines DC-10 Crash and Kansas City Hyatt Regency Walk away Collapse. | |
Unit-4 |
Teaching Hours:9 |
Work Place Rights & Responsibilities
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Ethics in changing domains of Research, Engineers and Managers; Organizational Complaint Procedure, difference of Professional Judgment within the Nuclear Regulatory Commission (NRC), the Hanford Nuclear Reservation. Ethics in changing domains of research – The US government wide definition of research misconduct, research misconduct distinguished from mistakes and errors, recent history of attention to research misconduct, the emerging emphasis on understanding and fostering responsible conduct, responsible authorship, reviewing & editing. | |
Unit-5 |
Teaching Hours:9 |
Global issues
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Introduction – Current Scenario, Technology Globalization of MNCs, International Trade, World Summits, Issues, Business Ethics and Corporate Governance, Sustainable Development Ecosystem, Energy Concerns, Ozone Deflection, Pollution, Ethics in Manufacturing and Marketing, Media Ethics; War Ethics; Bio Ethics, Intellectual Property Rights. | |
Text Books And Reference Books: T1. Professional Ethics: R. Subramanian, Oxford University Press, 2015. T2. Ethics in Engineering Practice & Research, Caroline Whitbeck, 2e, Cambridge University Press 2015. | |
Essential Reading / Recommended Reading R1.Engineering Ethics, Concepts Cases: Charles E Harris Jr., Michael S Pritchard, Michael J Rabins, 4e ,Cengage learning, 2015. R2. Business Ethics concepts & Cases: Manuel G Velasquez, 6e, PHI, 2008 | |
Evaluation Pattern Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) End Semester Examination(ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I : Mid Semester Examination (Theory) : 25 marks CIA II : Assignments : 10 marks CIA III : Quizzes/Seminar/Case Studies/Project Work : 10 marks Attendance : 05 marks Total : 50 marks | |
MIMBA431 - ORGANISATIONAL BEHAVIOUR (2019 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:6 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: The course is offered as a mandatory core course for all students in Trimester II. The course introduces students to a comprehensive set of concepts and theories, facts about human behaviour and organizations that have been acquired over the years. The subject focuses on ways and means to improve productivity, minimize absenteeism, increase employee engagement and so on thus, contributing to the overall effectiveness. The basic discipline of the course is behavioral science, sociology, social psychology, anthropology and political science. Course Objectives: To make sense of human behaviour, use of common sense and intuition is largely inadequate because human behaviour is seldom random. Every human action has an underlying purpose which was aimed at personal or societal interest. Moreover, the uniqueness of each individual provides enough challenges for the managers to predict their best behaviour at any point of time. A systematic study of human behaviour looks at the consistencies, patterns and cause effect relationships which will facilitate understanding it in a reasonable extent. Systematic study replaces the possible biases of intuition that can sabotage the employee morale in organizations. |
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Course Outcome |
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Course Learning Outcomes: On having completed this course student should be able to: At the end of the course the student will be able to: CLO1: Determine the individual and group behavior in the workplace. CLO2: Assess the concepts of personality, perception and learning in Organizations. CLO3: Analyze various job-related attitudes. CLO4: Design motivational techniques for job design, employee involvement, incentives, rewards & recognitions. CLO5: Manage effective groups and teams in organizations. |
Unit-1 |
Teaching Hours:12 |
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Unit-1: Introduction to Organizational Behaviour
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Historical Development, Behavioural sciences and Organizational behaviour, Meaning, Importance, Basic concepts, methods and tools for understanding behaviour, Challenges and Opportunities, OB model, ethical issues in organizational Behaviour. Cross-cultural management, managing multicultural teams, communicating across cultures, OB in the digital age. | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:12 |
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Unit-2: Individual Behaviour ? Personality, Perception and Learning
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Personality: Foundations of individual behaviour, Personality, Meaning and Importance, Development of personality, Determinants of personality, Theories of personality, Relevance of personality to managers. Perception: Nature, Importance and Definition of Perception, Factors involved in perception, The Perceptual Process, Perceptual Selectivity and Organization, Applications in Organizations. Learning: Definition and Importance, Theories of learning, Principles of learning, Shaping as managerial tool. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:12 |
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Unit-3: Attitudes, Values & Job Satisfaction
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Attitudes: Sources and types of attitudes, Attitude formation and change, Cognitive Dissonance Theory. Effects of employee attitude, Job related attitudes Values: meaning, importance, source and types, and applications in organizations. Job satisfaction: Measuring Job Satisfaction, Causes of Job Satisfaction, impact of satisfied and dissatisfied employees on the workplace. | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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Unit-4: Motivation
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Meaning, process and significance of motivation, Early Theories of motivation: Hierarchy of Needs, Theory X Theory Y, Two Factor theory, McClelland Theory of Needs, Contemporary Theories of Motivation: Goal Setting theory, Self-Efficacy theory, Equity theory/Organizational justice, Expectancy theories, Motivation theories applied in organizations: Job design, employee involvement, rewards and global implications | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:12 |
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Unit-5: Groups & Teams
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Groups: Meaning, classification and nature of groups, Stages of group development, an alternative model for Temporary Groups with punctuated equilibrium model, Group properties: Roles, Norms, Status, Size and Cohesiveness, Group decision making. Teams: Meaning of teams, Types of teams, Creating Effective teams, what makes individuals into effective team players, Team development, Team decision making. | |||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: Core Text Books: T1. Robbins, S P., Judge, T A and Vohra, N (2016). Organizational Behavior. 16th Edition, Prentice Hall of India. | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Rao V S P & V Sudeep 2018, Managing Organisational Behavior, Trinity Press, 3rd edition, New Delhi. | |||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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MIPSY431 - PEOPLE THOUGHTS AND SITUATIONS (2019 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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The course is an exploration of the prevailing theories and empirical methods that explain about people’s thoughts, feelings and behaviors in a social context. This throws light on cognitive and social factors that influence human behavior, especially in situations populated by others. Objectives
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Course Outcome |
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At the end of the course students will be able: |
Unit-1 |
Teaching Hours:9 |
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SOLUTION OF EQUATIONS AND EIGENVALUE PROBLEMS
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Introduction to Errors and their computations. Linear interpolation methods (method of false position) – Newton’s method, Solution of linear system by Gaussian elimination and Gauss-Jordon methods- Iterative methods: Gauss Jacobi and Gauss-Seidel methods- Inverse of a matrix by Gauss Jordon method – Eigenvalue of a matrix by power method | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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INTERPOLATION AND APPROXIMATION
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Lagrangian Polynomials – Divided differences – Interpolating with a cubic spline – Newton’s forward and backward difference formulas. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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NUMERICAL DIFFERENTIATION AND INTEGRATION
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Derivatives from difference tables – Divided differences and finite differences –Numerical integration by trapezoidal and Simpson’s 1/3 and 3/8 rules – Romberg’s method – Two and Three point Gaussian quadrature formulas – Double integrals using trapezoidal and Simpson’s rules. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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INITIAL VALUE PROBLEMS FOR ORDINARY DIFFERENTIAL EQUATIONS
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Single step methods: Taylor series method – Euler and modified Euler methods – Fourth order Runge – Kutta method for solving first and second order equations – Multistep methods: Milne’s and Adam’s predictor and corrector methods. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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BOUNDARY VALUE PROBLEMS IN ORDINARY AND PARTIAL DIFFERENTIAL EQUATIONS
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Finite difference solution of second order ordinary differential equation – Finite difference solution of one dimensional heat equation by explicit and implicit methods – One dimensional wave equation and two dimensional Laplace and Poisson equations- Case Studies - implement concepts using python | |||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. JaanKiusalaas, “Numerical Methods in Engineering with Python”, Cambridge University Press; 3rd Edition, 2013. 2. P. B. Patil, U. P. Verma , “Numerical Computational Methods” , Alpha Science Intl Ltd., Revised Edition Reprint 2013. 3. J. N. Sharma , “Numerical Methods for Engineers and Scientists”, Alpha Science Intl Ltd., 2nd Edition Reprint 2008. 4. P. Dechaumphai, N. Wansophark , “Numerical Methods in Engineering Theories with MATLAB, Fortran, C and Pascal Programs”, Alpha Science Intl Ltd., 2015. 5. E. Balagurusamy, “Numerical Methods”, Tata McGraw-Hill Pub. Co. Ltd, Reprint Edition, 2008. 6. V. Rajaraman “Computer Oriented Numerical Methods”, PHI, 5th Edition. | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. P. Kandasamy, K. Thilagavathy, and K. Gunavathy, “Numerical Methods”, S.Chand Co. Ltd., New Delhi, 2003. 2. C.F Gerald, and P.O Wheatley, “Applied Numerical Analysis”, 6th Edition, Pearson Education Asia, New Delhi, 2002. 3. Burden, R.L and Faires, T.D., “Numerical Analysis”, 7th Edition, Thomson Asia Pvt. Ltd., Singapore, 2002. | |||||||||||||||||||||||||||||||
Evaluation Pattern
Components of the CIA: CIA I : Assignment and Open Book Test: 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Case study and MCQ Quiz : 10 marks ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Total : 50 marks
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CS532E01 - FORMAL LANGUAGE AND AUTOMATA THEORY (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To have an understanding of finite state and pushdown automata. To have a knowledge of regular languages and context free languages. To know the relation between regular language, context free language and corresponding recognizers. To study the Turing machine and classes of problems. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Design finite automata with conversion between types of finite automata. L2 2. Develop regular expression and minimize the given finite automata for any regular language. L3 3. Develop context free grammar, parse trees and pushdown automata for a given context free language. L3 4. Experiment with CFLs and design of Turing machine for a given language. L3 5. Explain decidable and undecidable problems, solvable and unsolvable problems with their complexity analysis. L2 |
Unit-1 |
Teaching Hours:8 |
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Automaton
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Introduction to formal proof – Additional forms of proof – Inductive proofs –Finite Automata (FA) – Deterministic Finite Automata (DFA) – Non-deterministic Finite Automata (NFA) – Finite Automata with Epsilon transitions. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:10 |
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Regular Expressions and Languages
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Regular Expression – FA and Regular Expressions – Proving languages not to be regular – Closure properties of regular languages – Equivalence and minimization of Automata. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:10 |
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Context-Free Grammar and Languages
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Context-Free Grammar (CFG) – Parse Trees – Ambiguity in grammars and languages – Definition of the Pushdown automata – Languages of a Pushdown Automata – Equivalence of Pushdown automata and CFG, Deterministic Pushdown Automata. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Properties of Context-Free Languages
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Normal forms for CFG – Pumping Lemma for CFL - Closure Properties of CFL – Turing Machines – Programming Techniques for TM. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:8 |
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Undecidability
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A language that is not Recursively Enumerable (RE) – An undecidable problem that is RE – Undecidable problems about Turing Machine – Post’s Correspondence Problem - The classes P and NP. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. J.E.Hopcroft, R.Motwani and J.D Ullman, “Introduction to Automata Theory, Languages and Computations”, Pearson Education, 200 | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. H.R. Lewis and C.H. Papadimitrou, “Elements of the Theory of Computation”, Second Edition, Pearson Education/PHI, 2003 R2. J.Martin, “Introduction to Languages and the Theory of Computation”, Third Edition, TMH, 2003. R3. Michael Sipser, “Introduction of the Theory and Computation”, Thomson Brokecole, 1997. | |||||||||||||||||||||||||||||||
Evaluation Pattern Assessment of each paper
Components of the CIA
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CS532E02 - COMPILER DESIGN (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To have the better understanding of:
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Course Outcome |
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At end of the course, the students will able to CO1 - Explain the concepts and different phases of compilation with Compiler Construction Tools. CO2 - Interpret language tokens using regular expressions and design lexical analyzer for a language. CO3 - Build top down parsing, bottom up parsing and parse tree representation of the input. CO4 - Outline intermediate code for the statements during the process of compilation. CO5 - Experiment the optimization techniques to intermediate code and generate machine code for high level language program. |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION TO COMPILERS
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Translators-Compilation and Interpretation-Language processors -The Phases of Compiler-Errors encountered in Different Phases-The Grouping of Phases-Compiler Construction Tools - Programming Language basics. | ||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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LEXICAL ANALYSIS
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Need and Role of Lexical Analyzer-Lexical Errors-Expressing Tokens by Regular Expressions- Converting Regular Expression to DFA- Minimization of DFA-Language for Specifying Lexical Analyzers-LEX-Design of Lexical Analyzer for a sample Language. | ||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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SYNTAX ANALYSIS
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Need and Role of the Parser-Context Free Grammars -Top Down Parsing -General Strategies- Recursive Descent Parser Predictive Parser-LL(1) Parser-Shift Reduce Parser-LR Parser-LR (0)Item- Construction of SLR Parsing Table -Introduction to LALR Parser - Error Handling and Recovery inSyntax Analyzer-YACC-Design of a syntax Analyzer for a Sample Language | ||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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SYNTAX DIRECTED TRANSLATION & RUN TIME ENVIRONMENT
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Syntax directed Definitions-Construction of Syntax Tree-Bottom-up Evaluation of S-Attribute Definitions- Design of predictive translator - Type Systems-Specification of a simple type checker- Equivalence of Type Expressions-Type Conversions.
RUN-TIME ENVIRONMENT: Source Language Issues-Storage Organization-Storage Allocation- Parameter Passing-Symbol Tables-Dynamic Storage Allocation-Storage Allocation in FORTAN. | ||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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CODE OPTIMIZATION AND CODE GENERATION
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Principal Sources of Optimization-DAG- Optimization of Basic Blocks-Global Data Flow Analysis- Efficient Data Flow Algorithms-Issues in Design of a Code Generator - A Simple Code Generator Algorithm. | ||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Internal Assessment - 50 Marks (CIA 1: 10 Marks, CIA 2: 25 Marks, CIA 3: 10 Marks, Attendance: 5 Marks) End Semester Examination (ESE) - 50 Marks Total = 100 Marks
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CS532E03 - FUZZY LOGIC (2018 Batch) | ||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To understand the concepts of:
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Course Outcome |
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Demonstrate Fuzzy Set concepts. L2 Construct suitable membership functions for a given problem. L3 Comprehend Fuzzy Logic and Fuzzy Arithmetic concepts. L2 Implement Fuzzy Inference and Approximate Reasoning for real time projects. L3 Develop in a team, Fuzzy Classification and Clustering using any programming tool. L6 |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Classical Sets and Fuzzy Sets: Background, Uncertainty and Imprecision, Statistics and Random Processes, Uncertainty in Information, Fuzzy Sets and Membership, Chance versus Ambiguity. Classical Sets - Operations on Classical Sets, Properties of Classical (Crisp) Sets, Mapping of Classical Sets to Functions.Fuzzy Sets. | ||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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MEMBERSHIP FUNCTIONS
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Features of the Membership Function, Standard Forms and Boundaries, Fuzzification, Membership Value Assignments – Intuition, Inference, Rank Ordering, Angular Fuzzy Sets, Neural Networks, Genetic Algorithms, Inductive Reasoning. Fuzzy- To- Crisp Conversions: Lambda- Cuts for Fuzzy Sets, Lambda- Cuts for Fuzzy Relations, Defuzzification Methods. Extension Principle - Crisp Functions, Mapping and Relations, Functions of fuzzy | ||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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FUZZY ARITHMETIC
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Fuzzy Numbers, Interval Analysis in Arithmetic, Approximate Methods of Extension - Vertex method, DSW Algorithm, Restricted DSW Algorithm, Comparisons. Fuzzy Vectors. Classical Logic And Fuzzy Logic: Classical Predicate Logic – Tautologies, Contradictions, Equivalence, Exclusive OR and Exclusive NOR. | ||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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FUZZY RULE
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Based Systems: Natural Language, Linguistic Hedges, Rule- Based Systems - Canonical Rule Forms, Decomposition of Compound Rules, Likelihood and Truth Qualification, Aggregation of Fuzzy Rules, Graphical Techniques of Inference.Fuzzy Decision Making. | ||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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FUZZY CLASSIFICATION
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Classification by Equivalence Relations - Crisp Relations, Fuzzy Relations. Cluster Analysis, Cluster Validity, c-Means Clustering- Hard c-Means (HCM), Fuzzy c-Means (FCM). Classification Metric, Hardening the Fuzzy c-Partition, Similarity Relations from Clustering.
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Text Books And Reference Books: Text Books: 1. Fuzzy Logic with Engineering Applications by Timothy J. Ross, McGraw- Hill, III Edition | ||||||||||||||||||||||||||
Essential Reading / Recommended Reading Reference Books:
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Evaluation Pattern Internal Assessment - 50 Marks(CIA 1: 10 Marks, CIA 2: 25 Marks, CIA 3: 10 Marks, Attendance: 5 Marks)End Semester Examination (ESE) - 50 MarksTotal = 100 Marks
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CS533P - INTERNET OF THINGS (2018 Batch) | ||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This course introduces [1]. The basic concepts of IoT, [2]. The functionalities of different types of sensors, actuators and micro controllers. [3]. Covers the protocols used in different layers and gives insight on programming IoT for different domains. |
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Course Outcome |
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Sl.No Description Revised Blooms Taxonomy (RBT Level) CO1 Explain the fundamental building blocks of an IoT environment from a logical and physical perspective. L2 CO2 Summarize various IoT protocols in Application and Network layers by outlining their advantages and disadvantages L2 CO3 Develop programming skills to design IoT solutions using Arduino and Raspberry Pi to solve real life problems L3 CO4 Experiment with Arduino, CDAC, and Raspberry Pi to choose the appropriate hardware for different IoT projects L3 CO5 Survey successful IoT products and solutions to analyze their architecture and technologies L4 |
Unit-1 |
Teaching Hours:15 |
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INTRODUCTION AND BACKGROUND
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Definition and Characteristics of IoT, Physical Design of IoT: Things in IoT, Logical Design of IoT: IoT functional Blocks, IoT Communication Blocks, IoT communication APIs, IoT Enabling Technologies: WSN, Cloud Computing, Big Data Analysis, Communication Protocols, Embedded Systems. Labs: [1]. Controlling LEDs blinking pattern through UART [2]. On-chip Temperature measurement through ADC. | |||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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IOT HARDWARE, DEVICES AND PLATFORMS
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Basics of Arduino: The Arduino Hardware, The Arduino IDE, Basic Arduino Programming, Basics of Raspberry pi: Introduction to Raspberry Pi, Programming with Raspberry Pi, CDAC IoT devices: Ubimote, Wi-Fi mote, BLE mote, WINGZ gateway, Introduction to IoT Platforms, IoT Sensors and actuators. Labs: [1]. Communication of two Motes over the radio frequency [2]. Generation of alarm through Buzzer. | |||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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IOT ARCHITECTURE AND PROTOCOLS
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IoT Architecture: Web of Things versus Internet of Things – Two Pillars of the Web – Unified Multitier WoT Architecture, Cloud Providers and Systems,The Cloud of Things Architecture. IoT Protocols: Application Protocols, Service Discovery Protocols, Infrastructure Protocols.
Labs: [1]. Proximity detection with IR LED. [2]. Demonstration of a Peer-to-Peer network topology using Coordinator and end device network device types | |||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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IOT PROGRAMMING
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Arduino Programming: Serial Communications, Getting input from sensors, Visual, Physical and Audio Outputs, Remotely Controlling External Devices, Wireless Communication. Programming with Raspberry Pi: Basics of Python Programming, Python packages of IoT, IoT Programming with CDAC IoT devices.
Labs: [1]. IP based sensor monitoring through Ubi-Sense [2]. IP based lighting control through Data Acquisition Card | |||||||||||||||||||
Unit-5 |
Teaching Hours:15 |
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DOMAIN SPECIFIC IOT
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Home automation, Smart cities, Smart Environment, IoT in Energy, Logistics, Agriculture, Industry and Health & Life style secors. Case Studies: A Case study of Internet of Things Using Wireless Sensor Networks and Smartphones, Security Analysis of Internet-of-Things: A Case Study of August Smart Lock, OpenIoT platform.
Labs: [1]. Transmitting the measured physical value from the UbiSense over the Air [2]. Pushing data from device to cloud | |||||||||||||||||||
Text Books And Reference Books:
[1]. Vijay Madisetti and ArshdeepBahga, “Internet of Things (A Hands-on-Approach)”, 1st Edition, VPT, 2014. [2]. Margolis, Michael. “Arduino Cookbook: Recipes to Begin, Expand, and Enhance Your Projects. " O'Reilly Media, Inc.", 2011. [3]. Monk, Simon. Raspberry Pi cookbook: Software and hardware problems and solutions. " O'Reilly Media, Inc.", 2016.
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Essential Reading / Recommended Reading
[1]. The Internet of Things: Applications to the Smart Grid and Building Automation by – Olivier Hersent, Omar Elloumi and David Boswarthick – Wiley Publications -2012. [2]. Honbo Zhou, “The Internet of Things in the Cloud: A Middleware Perspective”, CRC Press, 2012. [3]. David Easley and Jon Kleinberg, “Networks, Crowds, and Markets: Reasoning About a Highly Connected World”, Cambridge University Press, 2010. [4]. Al-Fuqaha, Ala, et al. "Internet of things: A survey on enabling technologies, protocols, and applications." IEEE Communications Surveys & Tutorials 17.4 (2015): 2347-2376. [5]. Tsitsigkos, Alkiviadis, et al. "A case study of internet of things using wireless sensor networks and smartphones." Proceedings of the Wireless World Research Forum (WWRF) Meeting: Technologies and Visions for a Sustainable Wireless Internet, Athens, Greece. Vol. 2325. 2012. [6] Ye, Mengmei, et al. "Security Analysis of Internet-of-Things: A Case Study of August Smart Lock."
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Evaluation Pattern
Evaluation Pattern: Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) Marks CIA I : 10 Marks CIA II : 10 Marks CIA III : 10 Marks Lab : 35 Marks Attendance : 05 Marks Total Marks: 70 Marks End Sem: 30 Marks | |||||||||||||||||||
CS534 - DESIGN AND ANALYSIS OF ALGORITHMS (2018 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This course is designed to
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Course Outcome |
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After completion of this course students are able to SNO DESCRIPTION RBT LEVEL 1 Analyze a given software problem as an algorithm. L4 2 Experiment whether the algorithm found is the most efficient. L3 3 Formulate the time order analysis for an algorithm. L6 4 Formulate the space needs for the implementation of an algorithm. L6 5 Prove the correctness of an algorithm. L5 |
Text Books And Reference Books: | |||||||||||||||||||
Essential Reading / Recommended Reading | |||||||||||||||||||
Evaluation Pattern
Evaluation Pattern: Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) Marks CIA I : 10 Marks CIA II : 10 Marks CIA III : 10 Marks Lab : 35 Marks Attendance : 05 Marks Total Marks: 70 Marks End Sem: 30 Marks | |||||||||||||||||||
CS535 - SOFTWARE ENGINEERING (2018 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Course Outcome |
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Sl No Description Revised Bloom’s Taxonomy (RBT)Level CO1 Explain the fundamental of Software development Life cycle and different software development process models. L2 CO2 Build software requirements elicitation process and SRS document. L6 CO3 Develop the software processes using various design techniques. L3 CO4 Evaluate the different techniques of software testing and maintenance. L5 CO5 Measure the cost estimation techniques and project scheduling methods in software development process. L6 |
Unit-1 |
Teaching Hours:9 |
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SOFTWARE PROCESS
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Introduction –S/W Engineering Paradigm – life cycle models (waterfall, incremental, spiral, WINWIN spiral, evolutionary, prototyping, object-oriented) - system engineering – computer-based system – verification – validation – life cycle process – development process –system engineering hierarchy. | ||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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SOFTWARE REQUIREMENTS
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Functional and non-functional - user – system –requirement engineering process – feasibility studies – requirements – elicitation – validation and management – software prototyping – prototyping in the software process – rapid prototyping techniques – user interface prototyping -S/W document. Agile methods, Extreme Programming, SCRUM. | ||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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DESIGN CONCEPTS AND PRINCIPLES
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Design process and concepts – modular design – design heuristic – design model and document. Architectural design – software architecture – data design – architectural design – transform and transaction mapping – user interface design – user interface design principles. Real time systems - Real time software design – system design – real time executives – data acquisition system - monitoring and control system. SCM – Need for SCM – Version control – Introduction to SCM process – Software configuration items. | ||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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TESTING
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Taxonomy of software testing – levels – test activities – types of s/w test – black box testing – testing boundary conditions – structural testing – test coverage criteria based on data flow mechanisms – regression testing – testing in the large. S/W testing strategies – strategic approach and issues - unit testing – integration testing – validation testing – system testing and debugging. | ||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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SOFTWARE PROJECT MANAGEMENT
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Measures and measurements – S/W complexity and science measure – size measure – data and logic structure measure – information flow measure. Software cost estimation – function point models – COCOMO model- Delphi method.- Defining a Task Network – Scheduling – Earned Value Analysis – Error Tracking - Software changes – program evolution dynamics – software maintenance – Architectural evolution. Taxonomy of CASE tools – Case Study. | ||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Assessment of each paper
Components of the CIA
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CS536P - INTERNET AND WEB PROGRAMMING (2018 Batch) | ||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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1. To explain the use of HTML5 tags and web programming concepts. 2. To illustrate the use of CSS3. 3. To understand the basics of JavaScipt and implement Client-side scripts. 4. To understand the use of MariaDB database and queries. 5. To learn how to build server-side web applications using Node.js |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Build the basic web page using HTML concepts. L5 2 Experiment with the concepts of CSS to build the web pages. L4 3 Determine the usage of Java script scripts for making the effective web pages. L5 4 Develop backend connection using MariaDB. L3 5 Design web applications using platforms like Node.js L5 |
Unit-1 |
Teaching Hours:15 |
HTML5
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Contents: Why HTML5 exists? Structuring a Web Page, Forms, Multimedia (video, audio) markup and APIs, Canvas, Data Storage, Drag & Drop, Messaging & Workers. List of Experiments: 1.Creating static pages, forms [validating user i/p] using the features/attributes available in HTML5 and applying basic styling to the elements in an HTML5 page.
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Unit-2 |
Teaching Hours:15 |
CSS3
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Contents: Understanding CSS and the Modern Web, Learning CSS Syntax and Adding Presentational Styles, Creating Styles Using Property Values, Adding Presentational Styles, Creating A Basic Page Structure, Understanding Display, Position, and Document Flow, Changing and styling fonts, Adding transitions and animations. List of Experiments: 1. Style text elements on an HTML5 page by using CSS3. Apply styling to block elements by using CSS3. Use CSS3 selectors to specify the elements to be styled in a Web application.
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Unit-3 |
Teaching Hours:15 |
JAVASCRIPT
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Contents: Basic JavaScript Instructions, Functions, Methods & Objects, Decisions & Loops, Document Object Model, Events. List of Experiments: 1. Implement graphical effects and transformations by using the new CSS3 properties.
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Unit-4 |
Teaching Hours:15 |
NOSQL
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Contents: Installing MariaDB, Configuring MariaDB, MariaDB Security, MariaDB User Account Management, Using MariaDB. List of Experiments: 1. Implementing JavaScript with HTML5. Writing Java Scripts to validate user inputs. Applying object-oriented programming concepts to Java script. | |
Unit-5 |
Teaching Hours:15 |
CASE STUDY ? Node.js
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Contents: The Node Module System, The Node Programming Model, Events and Timers, The Command Line Interface, The File System, Streams, Binary Data, Executing Code, Network Programming, HTTP. List of Experiments: 1. Connecting to Maria DB and doing CRUD operations. | |
Text Books And Reference Books: TEXT BOOKS: 1. Bruce Lawson, Remy Sharp, “Introducing HTML 5”, Pearson Education, 2011. 2. Ian Lunn, “CSS3 Foundations”, Wiley Publishers, 2012. 3. Jon Duckett, “JavaScript and JQuery: Interactive Front-End Web Development”, Wiley Publishers: 2014. 4. Daniel Bartholomew, “Getting started with MariaDB”, 2013. 5. Colin J. Ihrig, “Pro Node.js for Developers”, APRESS, 2013. | |
Essential Reading / Recommended Reading REFERENCE BOOKS: 1. Matt west, “HTML5 Foundations”, Wiley Publishers: 2012. 2. Training Guide Programming in HTML5 with JavaScript and CSS3 (MCSD) (Microsoft Press Training Guide), 2013. 3. Elizabeth Castro, Bruce Hyslop, “HTML and CSS: Visual QuickStart Guide” 8th edition, 2013. | |
Evaluation Pattern Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) Marks CIA I: 10 Marks CIA II: 10 Marks CIA III: 10 Marks Lab: 35 Marks Total Marks: 70 Marks End Sem: 30 Marks | |
CSHO531AIP - STATISTICAL FOUNDATION FOR ARTIFICIAL INTELLIGENCE (2018 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course objectives: •Discuss the core concepts Statistical Analytics and Data manipulation •Apply the basic principles, models, and algorithms supervised and unsupervised learning mechanisms. •Analyse the structures and algorithms of regression methods •Explain notions and theories associated to Convolutional Neural Networks •Solve problems in High-Dimensional Regression
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Course Outcome |
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•Understand and explain concepts associated to Statistical Analytics and Data manipulation L2 •Infer details of supervised and unsupervised learning mechanisms. L2 •Solve problems connected to regression methods. L3 •Analyse concepts of Convolutional Neural Networks. L4 • Appraise concepts of High-Dimensional Regression. L5 |
Unit-1 |
Teaching Hours:11 |
Statistical Analytics and Data manipulation
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Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool. | |
Unit-2 |
Teaching Hours:11 |
Techniques for supervised and unsupervised learning
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The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis. | |
Unit-3 |
Teaching Hours:11 |
Neural Networks
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Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, 0 Computational Considerations. | |
Unit-4 |
Teaching Hours:11 |
Random Forests and Ensemble Learning
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Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles. | |
Unit-5 |
Teaching Hours:11 |
High-Dimensional Problems: p ≫ N
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Diagonal Linear Discriminant Analysis and Nearest Shrunken Centroids, Linear Classifiers with Quadratic Regularization, Linear Classifiers with L1 Regularization, Classification When Features are Unavailable, High-Dimensional Regression, Feature Assessment and the Multiple-Testing Problem | |
Text Books And Reference Books: Text Books: 1.Hastie, Trevor, Robert Tibshirani, and Jerome Friedman. The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media, 2017. 2.Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,, 2016.
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Essential Reading / Recommended Reading Reference Books: 1.Ghahramani, Zoubin. "Probabilistic machine learning and artificial intelligence." Nature 521.7553 (2015): 452. 2.Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018. 3.Wu, James, and Stephen Coggeshall. Foundations of predictive analytics. Chapman and Hall/CRC, 2012. 4.Marcoulides, George A., and Scott L. Hershberger. Multivariate statistical methods: A first course. Psychology Press, 2014. 5.Morgan, George A., et al. IBM SPSS for introductory statistics: Use and interpretation. Routledge, 2012
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Evaluation Pattern Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) End Semester Examination (ESE): 30% (30 marks out of 100 marks) Marks CIA I: 10 Marks CIA II: 10 Marks CIA III: 10 Marks Lab: 35 Marks Total Marks: 70 Marks End Sem: 30 Marks | |
CSHO531CSP - PROBABILITY AND RANDOM PROCESS (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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After learning the course for a semester, the student will be aware of the important statistical information for addressing cryptography, error correction and coding, information theory and cryptanalysis. The student would also get a clear idea on some of the cases with their analytical studies in information coding and its related fields. |
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Course Outcome |
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CO 1: To define pattern searching algorithms for different applications CO 2: To classify vulnerability of subsystem based on the information gathered from different resources CO 3: To estimate different optimized process and models CO 4: To provide means to find the similarities between the applications and vulnerabilities of the sub-system/system CO 5: To analyze about best possible patterns to cluster the possible solutions for different vulnerabilities |
Unit-1 |
Teaching Hours:11 |
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Probability Fundamentals, Bayes’ rule, Markov chains and application to pattern search algorithms, Classical statistical inference, Bayesian statistical inference, Regression techniques | |||||||||||||||||||
Unit-2 |
Teaching Hours:11 |
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Information coding, Pseudorandom number generators, discrete random variables, special distributions and mixed random variables, link and rank analysis , probability bounds, limiting theorem and convergence | |||||||||||||||||||
Unit-3 |
Teaching Hours:11 |
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Risk M Basics of statistical learning: models, regression, curse of dimensionality, overfitting, etc. Optimization and convexity, Gradient descent, Newton’s method | |||||||||||||||||||
Unit-4 |
Teaching Hours:11 |
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Classification and similarity analysis, linear discriminative analysis, regression analysis, iterative permutation analysis, Support vector machines, nearest neighbor and application of entropy | |||||||||||||||||||
Unit-5 |
Teaching Hours:11 |
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Clustering algorithms, graph analysis, pattern detection, Knowledge driven system design, learning with errors, Basics of neural networks | |||||||||||||||||||
Text Books And Reference Books: 1.Gnedenko, Boris V. Theory of probability. Routledge, 2018. 2.Beichelt, Frank. Applied Probability and Stochastic Processes. Chapman and Hall/CRC, 2016. 3.Li, X. Rong. Probability, random signals, and statistics. CRC press, 2017 | |||||||||||||||||||
Essential Reading / Recommended Reading 1.Grimmett, Geoffrey, Geoffrey R. Grimmett, and David Stirzaker. Probability and random processes. Oxford university press, 2001. 2.Papoulis, Athanasios, and S. Unnikrishna Pillai. Probability, random variables, and stochastic processes. Tata McGraw-Hill Education, 2002. 3.Rozanov, Yu. Probability theory, random processes and mathematical statistics. Vol. 344. Springer Science & Business Media, 2012. | |||||||||||||||||||
Evaluation Pattern Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks)
End Semester Examination(ESE) : 30% (30 marks out of 100 marks)
Components of the CIA
CIA I :Closed Book Test and Quiz: 10 marks
CIA II :Mid Semester Examination (Theory): 10 marks
CIA III :Closed Book Test and Quiz:10 marks
Lab marks :35 marks
Attendance: 05 marks
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CSHO531DAP - STATISTICAL FOUNDATION FOR DATA ANALYTICS (2018 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:50 |
Credits:4 |
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Course Objectives/Course Description |
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•Discuss the core concepts Statistical Analytics and Data manipulation •Apply the basic principles, models and algorithms supervised and unsupervised learning mechanisms. •Analyse the structures and algorithms of regression methods •Analyse the use of SVM in Data Science •Explain notions and theories associated to Convolutional Neural Networks
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Understand and explain concepts associated to Statistical Analytics and Data manipulation L2 2. Infer details of supervised and unsupervised learning mechanisms. L2 3. Analyse concepts of Convolutional Neural Networks. L4 4. Appraise concepts of Support Vector Machine. L5 5. Solve problems using Random Forests and Ensemble Learning. L3 |
Unit-1 |
Teaching Hours:9 |
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Statistical Analytics and Data manipulation
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Knowledge discovery: finding structure in data, Data quality versus data quantity, Statistical modeling versus statistical description. Data types, Data summarization, Means, medians, and central tendency, Summarizing variation, Summarizing (bivariate) correlation, Data diagnostics and data transformation, Outlier analysis, Entropy, Data transformation Simple smoothing techniques, Binning, Moving averages, Exponential smoothing. Introduction to SPSS (IBM’s) statistical tool. Statistical parameters (eg: Correlation analysis)
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Unit-2 |
Teaching Hours:9 |
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Techniques for supervised and unsupervised learning
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The simple linear model, Multiple inferences and simultaneous confidence bands, Regression diagnostics, Weighted least squares (WLS) regression, Correlation analysis. Unsupervised versus supervised learning, Principal component analysis, Principal components, Implementing a PCA, Exploratory factor analysis Linear and polynomial Regression | ||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Neural Networks
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Projection Pursuit Regression, Neural Networks, Fitting Neural Network, Some Issues in Training Neural Networks, Bayesian Neural Nets, Computational Considerations. Prediction analysis (eg: Stocks)
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Unit-4 |
Teaching Hours:9 |
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Support Vector Machines and Flexible Discriminants
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Introduction, The Support Vector Classifier, Support Vector Machines and Kernels, Generalizing Linear Discriminant Analysis, Flexible Discriminant Analysis, Penalized Discriminant Analysis, Mixture Discriminant Analysis Time Series: predict web traffic | ||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Random Forests and Ensemble Learning
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Definition of Random Forests, Details of Random Forests- Out of Bag Samples, Variable Importance, Proximity Plots; Analysis of Random Forests; Ensemble Learning, Boosting and Regularization Paths, Learning a Good Ensemble, Rule Ensembles.
Convolutional Neural Network - Step by Step | ||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Continuous Internal Assessment (CIA) for Theory papers: 70% (70 marks out of 100 marks) End Semester Examination(ESE) : 30% (30 marks out of 100 marks) Components of the CIA CIA I :Closed Book Test and Quiz: 10 marks CIA II :Mid Semester Examination (Theory): 10 marks CIA III :Closed Book Test and Quiz:10 marks Lab marks :35 marks Attendance: 05 marks
1) CIA ASSESSMENT DETAILS - THEORY
2) LAB ASSESSMENT DETAILS
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CE636OE1 - SOLID WASTE MANAGEMENT (2018 Batch) | ||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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This course give introduction to solid waste management, collection and transportation, treatment/processing techniques, incineration , composting, sanitary land filling, disposal methods, recycle and reuse. Objective of this course is to provide insight to manage solid waste. It is designed as a source of information on solid waste management , includiing the principles of solid waste management , processing and treatment, final disposal, recycle and reuse
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Course Outcome |
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CO1Define and explain important concepts in the field of solid waste management, such as waste hierarchy, waste prevention, recirculation, municipal solid waste etc. CO2 Suggest and describe suitable technical solutions for biological and thermal treatment. CO3Suggest, motivate and describe a way to tackle the problem from a system analysis approach. CO4 Describe the construction and operation of a modern landfill according to the demands CO5 Discuss social aspects connected to handling and recirculation of solid waste from a local as well as global perspective. |
Unit-1 |
Teaching Hours:9 |
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Sources
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Classification and characteristics – municipal, commercial & industrial. Methods of quantification | |||||||||||||||||||||||||||||||
Unit-1 |
Teaching Hours:9 |
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Introduction
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Definition, Land Pollution – scope and importance of solid waste management, functional elements of solid waste management. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Collection and Transportation
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Systems of collection, collection equipment, garbage chutes, transfer stations – bailing and compacting, route optimization techniques and problems. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Treatment/Processing Techniques
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Components separation, volume reduction, size reduction, chemical reduction and biological processing problems. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Incineration
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Process – 3 T’s, factors affecting incineration process, incinerators – types, prevention of air pollution, pyrolsis, design criteria for incineration. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Composting
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Aerobic and anaerobic composting, factors affecting composting, Indore and Bangalore processes, mechanical and semi mechanical composting processes. Vermi composting. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Sanitary land filling
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Different types, trench area, Ramp and pit method, site selection, basic steps involved, cell design, prevention of site pollution, leachate & gas collection and control methods, geo-synthetic fabricsin sanitary landfills. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Recycle and Reuse
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Material and energy recovery operations, reuse in other industries, plastic wastes, environmental significance and reuse. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Disposal Methods
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Open dumping – selection of site, ocean disposal, feeding to hogs, incineration, pyrolsis, composting, sanitary land filling, merits and demerits, biomedical wastes and disposal. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: T1 Bhide and Sunderashan “Solid Waste Management in developing countries”, T2 Tchobanoglous “Integrated Solid Waste Management”, Mc Graw Hill. | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. Peavy and Tchobanoglous “Environmental Engineering”, R2. Garg S K “Environmental Engineering”, Vol II R3. “Biomedical waste handling rules – 2000”. R4. Pavoni J.L. “Hand book on Solid Waste Disposal” | |||||||||||||||||||||||||||||||
Evaluation Pattern
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CE636OE2 - ENVIRONMENTAL IMPACT ASSESSMENT (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Over the past three decades, environmental impact assessment has been an important foundation for public and private development and planning decisions. In development disputes, the interaction between communities and government and special interests and the private sector shape the fabric of neighborhoods, cities and regions around the world. The objective of this paper is to create awareness about the environmental impact on the earth and for assessment among the student's community this paper has been introduced as elective. Course Objectives:
1. 1. To study and understand the basics of EIA and the need for it and explain the step-by-step procedure for conducting EIA.
2. 2. To plan the framework of Impact Assessment with methodologies and techniques of EIA
3. 3. To explain the impact of activities on different environmental elements
4. 4. To study and develop the guideline for the projects and public participation in the decision-making process
5. 5. To understand the salient feature of the project activity and categorize various developmental activities. |
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Course Outcome |
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Course Outcomes: Upon completion of Course the student would be able to 1.Outline need for EIA studies, Baseline information and Explain step-by-step procedure for conducting EIA 2. Plan the framework of Impact Assessment with methodologies and techniques of EIA 3. Assess the impact of activities on different elements of Environment. 4. Develop guidelines for projects and public participation in the decision-making process 5. Categorize various developmental activities and list salient features of the project activity |
Unit-1 |
Teaching Hours:9 |
UNIT 1
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Development Activity and Ecological Factors EIA, EIS, FONSI. Need for EIA Studies, Baseline Information, Step-by-step procedures for conducting EIA, Limitations of EIA | |
Unit-2 |
Teaching Hours:9 |
UNIT 2
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Frame work of Impact Assessment. Development Projects-Environmental Setting, Objectives and Scope, Contents of EIA, Methodologies, Techniques of EIA. | |
Unit-3 |
Teaching Hours:9 |
UNIT 3
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Assessment and Prediction of Impacts on Attributes Air, Water, Noise, Land Ecology, Soil, Cultural and Socio-economic Environment. EIA guidelines for Development Projects, Rapid and Comprehensive EIA | |
Unit-4 |
Teaching Hours:9 |
UNIT 4
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EIA guidelines for Development Projects, Rapid and Comprehensive EIA. Public Participation in Environmental Decision making. Practical Considerations in preparing Environmental Impact Assessment and Statements | |
Unit-5 |
Teaching Hours:9 |
UNIT 5
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Salient Features of the Project Activity-Environmental Parameter Activity Relationships- Matrices. EIA for Water resource developmental projects, Highway projects: Nuclear-Power plant projects, mining project (Coal, Iron ore). | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading NEPA - National Environmental Protection agency reports on Various projects | |
Evaluation Pattern
· Assessment is based on the performance of the student throughout the semester. Assessment of each paper · Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I: Assignments : 10 marks CIA II: Mid Semester Examination (Theory) : 25 marks CIA III: Quizzes/Seminar/Case Studies/Project Work : 10 marks Attendance : 05 marks Total : 50 marks
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CE636OE4 - DISASTER MANAGEMENT (2018 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To study the emerging approaches in Disaster Reduction & Management. The emphasis will be on programmes of National & International organizations for Disaster preparedness, Mitigation and awareness to prevent or reduce losses that occur due to hazards, disaster and emergencies. |
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Course Outcome |
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CO1 : Explain Hazards and Disasters (L1, L2) CO2 : Outline the managerial aspects of Disaster Management, plan and explain risk analysis (L2,L3,L4,L5) CO3 : Relate Disasters and Development (L3,L4) CO4 : Classify climate change impacts and develop scenarios (L3,L4) CO5: Categorize policies and institutional mechanisms in Disaster Management and the impacts on society (L3,L4,L5) |
Unit-1 |
Teaching Hours:9 |
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Types of Global Disasters
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Principles of Disaster Management, Natural Disasters such as Earthquake, Floods, Fire, Landslides, Tornado, Cyclones, Tsunamis, Nuclear, Chemical, Terrorism, Extra Terrestrial and other natural calamities. Hazards, Risks and Vulnerabilities. Assessment of Disaster Vulnerability of a location and vulnerable groups, National policy on disaster Management, | ||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:10 |
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Disaster Mitigation
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Prevention, Preparedness and Mitigation measures for various Disasters, Post Disaster Relief & Logistics Management, Emergency Support Functions and their coordination mechanism, Resource & Material Management, Management of Relief Camp, Information systems & decision making tools, Voluntary Agencies & Community Participation at various stages of disaster management, Integration of Rural Development Programmes with disaster reduction and mitigation activities. | ||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Renewable and Non-Renewable resources
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Renewable and non-renewable resources, Role of individual in conservation of natural resources for sustainable life styles. Use and over exploitation of Forest resources, Deforestation, Timber extraction, Mining, Dams and their effects on forest and tribal people. Use and over exploitation of surface and ground water resources, Floods, Drought, Conflicts over water, Dams- benefits and problems. Causes, effects and control measures of Air pollution, Water pollution, soil pollution, Noise pollution, Thermal pollution, Nuclear hazards.
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Unit-4 |
Teaching Hours:8 |
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Global Environmental Issues
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Global Environmental crisis, Current global environment issues, Global Warming, Greenhouse Effect, role of Carbon Dioxide and Methane, Ozone Problem, CFC‟s and Alternatives, Causes of Climate Change Energy Use: past, present and future, Role of Engineers. | ||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Disaster Management organisations and Media
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Mitigation- Institutions- the work of-. Meteorological observatory – Seismological observatory - Volcano logy institution - Hydrology Laboratory - Industrial Safety inspectorate - Institution of urban & regional planners -. Chambers of Architects. Engineering Council-. National Standards CommitteeIntegration of public policy: Planning and design of infrastructure for disaster management, Community based approach in disaster management, methods for effective dissemination of information, ecological and sustainable development models for disaster management.Role of Media Monitoring Management- programme of disaster research &mitigation ofdisaster of following organizations. International Council for Scientific Unions (ICSU)- Scientific committee on problems of the Environment (SCOPE), International Geosphere-Biosphere programme (IGBP) – World federation of Engineering Organizations(WFED)-National Academy of Sciences-World Meteorological organizations(WMO)-Geographical Information System(GIS)- International Association of Seismology & Physics of Earth’s Interior(IASPEI)-Various U.N agencies like UNCRD, IDNDR, WHO, UNESCO, UNICEF,UNEP. | ||||||||||||||||||||||||||||||||||||
Text Books And Reference Books:
1. Sharma, Dutt Varun; Pandey, S K; Sharma, Vimal Kumar “Environmental Education and Disaster Management” CBS Publishers and Distributors, New Delhi, 2008.2. Shaw, Rajib; Krishnamurthy, R R. “Disaster Management: Global Challenges and Local Solutions” Universities Press, Hyderabad, 2009.3. Yadav, Rajesh K; Singh, Rajbir. “Recent Approaches in Disaster Management” Oxford Book Company, Jaipur, 2013.4. Sharma, Sanjay K. “Environment Engineering and Disaster Management” University Science Press, New Delhi, 2014.5. Singh, Jagbir. “DisasterManagement: Future Challenges and Opportunities” I K International Publishing, New Delhi, 2007.
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Essential Reading / Recommended Reading
1. Rajat, B C Bose ”Modern Encyclopaedia of Disaster and Hazard Management “.2. Singh R.B “Disaster Management” Rawat Publications.3. Narayan “Disaster Management” B A.P.H. Publishing Corporation.Case Studies on Global disasters. | ||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CS631 - CRYPTOGRAPHY AND NETWORK SECURITY (2018 Batch) | ||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To understand the principles of encryption algorithms; conventional and public key cryptography. To have a detailed knowledge about authentication, hash functions and application level security mechanisms.
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Course Outcome |
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CO1: Explain various features of Security mechanisms and services to study Standard Block Ciphers along with their design principles CO2: Utlize the basic concepts and algorithms of Public key encryption mechanism for secure data transmission. CO3: Compare various Cryptographic authentications protocols, Hash Functions, Algorithms and Standards. CO4: Identify Various Protocols and Standards in Network Security CO5: Make use of various applications at system level security |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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OSI Security Architecture - Classical Encryption techniques – Cipher Principles – Data Encryption Standard – Block Cipher Design Principles and Modes of Operation - Evaluation criteria for AES – AES Cipher – Triple DES – Placement of Encryption Function – Traffic Confidentiality | |
Unit-2 |
Teaching Hours:9 |
PUBLIC KEY CRYPTOGRAPHY
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Key Management - Diffie-Hellman key Exchange – Elliptic Curve Architecture and Cryptography - Introduction to Number Theory – Confidentiality using Symmetric Encryption – Public Key Cryptography and RSA | |
Unit-3 |
Teaching Hours:9 |
AUTHENTICATION AND HASH FUNCTION
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Authentication requirements – Authentication functions – Message Authentication Codes – Hash Functions – Security of Hash Functions and MACs – MD5 message Digest algorithm - Secure Hash Algorithm – RIPEMD – HMAC Digital Signatures – Authentication Protocols – Digital Signature Standard | |
Unit-4 |
Teaching Hours:9 |
NETWORK SECURITY
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Authentication Applications: Kerberos – X.509 Authentication Service – Electronic Mail Security – PGP – S/MIME - IP Security – Web Security. | |
Unit-5 |
Teaching Hours:9 |
Application Security
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Intrusion detection – password management – Viruses and related Threats – Virus Counter measures – Firewall Design Principles – Trusted Systems, CASE-Study. | |
Text Books And Reference Books: TEXT BOOKS 1. William Stallings, “Cryptography And Network Security – Principles and Practices”, Pearson Education, 2013 | |
Essential Reading / Recommended Reading REFERENCE BOOKS 1. Atul Kahate, “Cryptography and Network Security”, Tata McGraw-Hill, 2011. 2. Bruce Schneier, “Applied Cryptography”, John Wiley & Sons Inc, Reprint 2001. 3. Charles B. Pfleeger, Shari Lawrence Pfleeger, “Security in Computing”, 5th Edition, Pearson Education, 2015. | |
Evaluation Pattern Internal Assessment - 50 Marks (CIA 1: 10 Marks, CIA 2: 25 Marks, CIA 3: 10 Marks, Attendance: 5 Marks) End Semester Examination (ESE) - 50 Marks Total = 100 Marks | |
CS632P - OBJECT ORIENTED ANALYSIS AND DESIGN (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To understand the object oriented life cycle; To know how to identify objects, relationships, services and attributes through UML; To understand the use-case diagrams; To know the Object Oriented Design process; To know about software quality and usability. |
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Course Outcome |
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CO1: Explain the basic concepts and the lifecycle of Object -Oriented System Development CO2: Develop UML diagrams based on Unified Approach CO3: Draw Class diagrams for Real Time Systems CO4: Demonstrate the concept of design axioms and object interoperability in Modeling Language. CO5: Validate UML frameworks for real world systems with assured quality and user satisfaction |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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An Overview of Object Oriented Systems Development - Object and Classes Basics – Object Oriented Systems Development Life Cycle. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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OBJECT ORIENTED METHODOLOGIES
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Rumbaugh Methodology - Booch Methodology - Jacobson Methodology - Patterns – Frameworks – Unified Approach – Unified Process Model – Unified Modeling Language – Use case - class diagram - Interactive Diagram - Package Diagram - Collaboration Diagram - State Diagram - Activity Diagram | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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OBJECT ORIENTED ANALYSIS
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Identifying use cases - Object Analysis - Classification – Identifying Object relationships - Attributes and Methods. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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OBJECT ORIENTED DESIGN
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Design axioms - Designing Classes – Access Layer - Object Storage - Object Interoperability | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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SOFTWARE QUALITY AND USABILITY
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Designing Interface Objects – Software Quality Assurance – System Usability - Measuring User Satisfaction – Case Study | |||||||||||||||||||||||||||||||
Text Books And Reference Books: TEXT BOOKS 1. Ali Bahrami, “Object Oriented Systems Development”, Tata McGraw-Hill, 2008 (Unit I, III, IV, V). 2. Martin Fowler, “UML Distilled”, Third Edition, PHI/Pearson Education, 2011 Edition. (UNIT II). | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading REFERENCE BOOKS 1. Robert A. Maksimchuk , Bobbi J. Young ,Grady Booch , Jim Conallen , Michael W. Engel , Kelli A. Houston, “Object-Oriented Analysis and Design with Applications”, Pearson India, 3rd Edition 2009. 2. James Rumbaugh, Ivar Jacobson, Grady Booch “The Unified Modeling Language User Guide”, Pearson Education, 2nd Edition, 2007. 3. Hans-Erik Eriksson, Magnus Penker, Brain Lyons, David Fado, “UML2 Toolkit”, OMG Press Wiley Publishing Inc., 1st Edition 2011. | |||||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||||
CS633P - SYSTEM SOFTWARE (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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To understand the relationship between system software and machine architecture; To know the design and implementation of assemblers; To know the design and implementation of linkers and loaders; To have an understanding of macro processors; To have an understanding of system software tools.
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Course Outcome |
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CO1: Summarize the basic concepts of SIC and SIC/XE architecture. CO2: Make Use of the concept of assembler according to SIC and SIC/XE architecture with real world cases. CO3: Utilize the detailed working of linker and loader with respect to SIC and SIC/XE architecture for real world cases . CO4: Make use of Microprocessor functionalities according to SIC and SIC/XE architecture with real world cases CO5: Examine the role of compiler in programming environment. |
Unit-1 |
Teaching Hours:9 |
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MACHINE STRUCTURE AND EVOLUTION OF A PROGRAMMING SYSTEM
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Introduction to System Software, Components of System Software, Evolution of System Software, Assembler, Loader, Macros, Compilers, Simplified Instructional Computer: SIC machine architecture, SIC/XE machine architecture, SIC programming examples. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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ASSEMBLER
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Basic assembler functions (SIC assembler, algorithm and data structure), Machine dependent assembler features (Instruction formats and addressing modes, program relocation), Machine independent assembly features (Literals, Symbol defining statements, expressions, program blocks, control sections and program linking), Assembler design options (One pass assembler, multi pass assembler)
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Unit-3 |
Teaching Hours:9 |
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LOADERS AND LINKERS
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Basic loader functions (Design of an absolute loader, simple bootstrap loader), Machine dependent loader features (Relocation, program linking, algorithm and data structures for a linking loader), Machine independent loader features (Automatic library search, loader options), Loader design options (Linkage editor, dynamic linking, bootstrap loaders). | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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MACRO PROCESSOR
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Macro Instructions, Features of a macro facility (Macro instruction arguments, Conditional macro expansion, Macro calls within macro, Macro instructions defining macros), Implementation (Two pass algorithm, Single pass algorithm). | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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COMPILERS
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Part1: Basic elements, Syntactic units and interpreting meaning, Intermediate form (Arithmetic statements, Non-arithmetic statements, Non-executable statements), Storage allocation, Code generation, Optimization (Machine independent, Machine dependent, Assembly phase). Part2: Phases of the compiler (Lexical phase, Syntax phase, Interpretation phase, Optimization, Storage assignment, Code generation, Assembly phase), Passes of a compiler. Case study. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: TEXT BOOKS
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Essential Reading / Recommended Reading REFERENCE BOOKS
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Evaluation Pattern
| |||||||||||||||||||||||||||||||
CSHO631AI - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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•Discuss the core concepts Statistical Analytics and Regression •Apply the basic principles, models, and algorithms for Multiple and Non Linear Regression •Analyse the structures and algorithms of Convolutional Neural Networks •Explain notions and theories associated to Convolutional Neural Networks •Solve problems in Deep Unsupervised Learning |
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Course Outcome |
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CO1: Understand and explain concepts associated Statistical Analytics and Regression CO2: Infer details of Multiple and Non Linear Regression mechanisms. CO3: Solve problems connected to Convolutional Neural Networks. CO4: Analyse concepts of Convolutional Neural Networks. CO5: Appraise concepts of Deep Unsupervised Learning. |
Unit-1 |
Teaching Hours:9 |
Regression
|
|
Relationship between attributes using Covariance and Correlation, Relationship between multiple variables: Regression (Linear, Multivariate) in prediction. Residual Analysis, Identifying significant features, feature reduction using AIC, multi-collinearity, Non-normality and Heteroscedasticity | |
Unit-2 |
Teaching Hours:9 |
Multiple and Non Linear Regression
|
|
Polynomial Regression, Regularization methods, Lasso, Ridge and Elastic nets, Categorical Variables in Regression, Logit function and interpretation, Types of error measures (ROCR), Logistic Regression in classification | |
Unit-3 |
Teaching Hours:9 |
Convolutional Neural Networks I
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|
Invariance, stability. Variability models (deformation model, stochastic model). Scattering networks, Group Formalism, Supervised Learning: classification. Properties of CNN representations: invertibility, stability, invariance. Covariance/invariance: capsules and related models. | |
Unit-4 |
Teaching Hours:9 |
Convolutional Neural Networks II
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|
Connections with other models: dictionary learning, LISTA. Other tasks: localization, regression. Embeddings (DrLim), inverse problems, Extensions to non-euclidean domains Dynamical systems: RNNs. | |
Unit-5 |
Teaching Hours:9 |
Deep Unsupervised Learning
|
|
Autoencoders (standard, denoising, contractive, Variational Autoencoders Adversarial Generative Networks, Maximum Entropy Distributions | |
Text Books And Reference Books: T1.Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018. T2.Sebastian Raschka and Vahid MirjaliliPython Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition, Packt, 2019 | |
Essential Reading / Recommended Reading R1. Seber, Linear Regression Analysis 2ed,Wiley India Exclusive (Cbs), 2018 R2. Jeremy Arkes, Regression Analysis: A Practical Introduction, Routledge, 2019 R3. Aurelien Geron, Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow: Concepts, Tools and Techniques to Build Intelligent Systems, Shroff/O'Reilly, 2019 R4. Andreas Muller, Introduction to Machine Learning with Python: A Guide for Data Scientists, Shroff/O'Reilly, 2016 R5. François Chollet, Deep Learning with Python, Manning Publications, 2017 | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO631AIP - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
Discuss the core concepts Statistical Analytics and RegressionApply the basic principles, models, and algorithms for Multiple and Non Linear RegressionAnalyse the structures and algorithms of Convolutional Neural NetworksExplain notions and theories associated to Convolutional Neural NetworksSolve problems in Deep Unsupervised Learning |
|
Course Outcome |
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|
Unit-1 |
Teaching Hours:9 |
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Regression
|
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Relationship between attributes using Covariance and Correlation, Relationship between multiple variables: Regression (Linear, Multivariate) in prediction. Residual Analysis, Identifying significant features, feature reduction using AIC, multi-collinearity, Non-normality and Heteroscedasticity | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Multiple and Non Linear Regression
|
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Polynomial Regression, Regularization methods, Lasso, Ridge and Elastic nets, Categorical Variables in Regression, Logit function and interpretation, Types of error measures (ROCR), Logistic Regression in classification | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Convolutional Neural Networks 1
|
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Invariance, stability. Variability models (deformation model, stochastic model). Scattering networks, Group Formalism, Supervised Learning: classification. Properties of CNN representations: invertibility, stability, invariance. Covariance/invariance: capsules and related models | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Convolutional Neural Network II
|
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Connections with other models: dictionary learning, LISTA. Other tasks: localization, regression. Embeddings (DrLim), inverse problems, Extensions to non-euclidean domains Dynamical systems: RNNs | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Deep Unsupervised Learning
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Autoencoders (standard, denoising, contractive, Variational Autoencoders Adversarial Generative Networks, Maximum Entropy Distributions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: Ian Goodfellow and Yoshua Bengio and Aaron Courville,” Deep Learning ”, MIT Press, March 2018. Sebastian Raschka and Vahid MirjaliliPython Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition, Packt, 2019 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Seber, Linear Regression Analysis 2ed,Wiley India Exclusive (Cbs), 2018Jeremy Arkes, Regression Analysis: A Practical Introduction, Routledge, 2019Aurelien Geron, Hands-On Machine Learning with Scikit-Learn, Keras and Tensor Flow: Concepts, Tools and Techniques to Build Intelligent Systems, Shroff/O'Reilly, 2019Andreas Muller, Introduction to Machine Learning with Python: A Guide for Data Scientists, Shroff/O'Reilly, 2016François Chollet, Deep Learning with Python, Manning Publications, 2017 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CSHO631CS - MOBILE AND NETWORK-BASED ETHICAL HACKING (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Course Objectives/Course Description |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
After learning the course for a semester, the student will be aware of the hacking concepts in cyber security for addressing cryptography, data protection, information-network security and detection of attacks. The student would also get a clear idea on some of the cases with their analytical studies in cyber-attacks and hacking in the related fields. |
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Course Outcome |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CO 1: to describe the vulnerability scanning for network CO 2: to identify the information gathering resources for any attack on the network CO 3: to evaluate different hacking process and corresponding attacks for mobile platforms CO 4: to provide means to evade fire-walls and other security parameter for ethical hacking CO 5: to analyze about best possible solutions for different vulnerabilities that are exploited for hacking |
Unit-1 |
Teaching Hours:9 |
Unit-1
|
|
Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, and vulnerability assessment OpenVAS, Nessus, etc. of computation device (mobile, pc, etc.) and network of the system
| |
Unit-2 |
Teaching Hours:9 |
Unit-2
|
|
Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats and different cyber-related attacks | |
Unit-3 |
Teaching Hours:9 |
Unit-3
|
|
Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms and corresponding vulnerabilities | |
Unit-4 |
Teaching Hours:9 |
Unit-4
|
|
Evading firewalls, standard detection systems and frameworks, and other possible ways of detecting attacks | |
Unit-5 |
Teaching Hours:9 |
Unit-5
|
|
Case studies: various hacking scenarios and their information gathering along with possible solutions. | |
Text Books And Reference Books: T1. Thompsons, Josh. Hacking: Hacking For Beginners Guide On How To Hack, Computer Hacking, And The Basics Of Ethical Hacking (Hacking Books). CreateSpace Independent Publishing Platform, 2017. T2. Weidman, Georgia. Penetration testing: a hands-on introduction to hacking. No Starch Press, 2014. T3. Dwivedi, Himanshu. Mobile application security. Tata McGraw-Hill Education, 2010 | |
Essential Reading / Recommended Reading R1. Engebretson, Patrick. The basics of hacking and penetration testing: ethical hacking and penetration testing made easy. Elsevier, 2013. R2. McNab, Chris. Network security assessment: know your network. " O'Reilly Media, Inc.", 2007. R3. Simpson, Michael T., Kent Backman, and James Corley. Hands-on ethical hacking and network defense. Cengage Learning, 2010 | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO631CSP - MOBILE AND NETWORK BASED ETHICAL HACKING (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
After learning the course for a semester, the student will be aware of the hacking concepts in cyber security for addressing cryptography, data protection, information-network security and detection of attacks. The student would also get a clear idea on some of the cases with their analytical studies in cyber-attacks and hacking in the related fields |
|
Course Outcome |
|
To describe the vulnerability scanning for network To identify the information gathering resources for any attack on the network To evaluate different hacking process and corresponding attacks for mobile platforms To provide means to evade fire-walls and other security parameter for ethical hacking To analyze about best possible solutions for different vulnerabilities that are exploited for hacking |
Unit-1 |
Teaching Hours:9 |
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Introduction
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Introduction to ethical hacking, IP addressing, Network routing protocols, network security, network scanning, and vulnerability assessment OpenVAS, Nessus, etc. of computation device (mobile, pc, etc.) and network of the system | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Threat Analysis
|
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Computation system hacking, modes of gathering information, password cracking, penetration testing including backdoor issues, Malware threats and different cyber-related attacks | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Mobile Hacking
|
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Introduction to Mobile Hacking, encryption types and attacks, different mobile platforms and corresponding vulnerabilities | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Detection of Threats
|
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Evading firewalls, standard detection systems and frameworks, and other possible ways of detecting attacks | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Case Studies
|
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Case studies: various hacking scenarios and their information gathering along with possible solutions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: Thompsons, Josh. Hacking: Hacking For Beginners Guide On How To Hack, Computer Hacking, And The Basics Of Ethical Hacking (Hacking Books). CreateSpace Independent Publishing Platform, 2017.Weidman, Georgia. Penetration testing: a hands-on introduction to hacking. No Starch Press, 2014.Dwivedi, Himanshu. Mobile application security. Tata McGraw-Hill Education, 2010 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Engebretson, Patrick. The basics of hacking and penetration testing: ethical hacking and penetration testing made easy. Elsevier, 2013.McNab, Chris. Network security assessment: know your network. " O'Reilly Media, Inc.", 2007.Simpson, Michael T., Kent Backman, and James Corley. Hands-on ethical hacking and network defense. Cengage Learning, 2010 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CSHO631DA - BIG DATA ANALYTICS (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
•To Understand big data for business intelligence •To Learn business case studies for big data analytics •To Understand Nosql big data management •To manage Big data without SQL •To understanding map-reduce analytics using Hadoop and related tools |
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Course Outcome |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CO1: Describe big data and use cases from selected business domains CO2: Discuss open source technologies CO3: Explain NoSQL big data management CO4: Discuss basics of Hadoop and HDFS CO5: Discuss map-reduce analytics using Hadoop along with as HBase, Cassandra, Pig, and Hive for big data Analytics |
Unit-1 |
Teaching Hours:9 |
UNDERSTANDING BIG DATA
|
|
What is big data – why big data –.Data!, Data Storage and Analysis, Comparison with Other Systems, Rational Database Management System , Grid Computing, Volunteer Computing, convergence of key trends – unstructured data – industry examples of big data – web analytics – big data and marketing – fraud and big data – risk and big data – credit risk management – big data and algorithmic trading – big data and healthcare – big data in medicine – advertising and big data– big data technologies – introduction to Hadoop – open source technologies – cloud and big data – mobile business intelligence – Crowd sourcing analytics – inter and trans firewall analytics. | |
Unit-2 |
Teaching Hours:9 |
NOSQL DATA MANAGEMENT
|
|
Introduction to NoSQL – aggregate data models – aggregates – key-value and document data models – relationships –graph databases – schema less databases – materialized views – distribution models – sharding –– version – Map reduce –partitioning and combining – composing map-reduce calculations | |
Unit-3 |
Teaching Hours:9 |
BASICS OF HADOOP
|
|
Data format – analyzing data with Hadoop – scaling out – Hadoop streaming – Hadoop pipes – design of Hadoop distributed file system (HDFS) – HDFS concepts – Java interface – data flow – Hadoop I/O – data integrity – compression – serialization – Avro – file-based data structures | |
Unit-4 |
Teaching Hours:9 |
MAPREDUCE APPLICATIONS
|
|
MapReduce workflows – unit tests with MRUnit – test data and local tests – anatomy of MapReduce job run – classic Map-reduce – YARN – failures in classic Map-reduce and YARN – job scheduling – shuffle and sort – task execution –MapReduce types – input formats – output formats | |
Unit-5 |
Teaching Hours:9 |
HADOOP RELATED TOOLS
|
|
Hbase – data model and implementations – Hbase clients – Hbase examples –praxis. Cassandra – Cassandra data model –cassandra examples – cassandra clients –Hadoop integration. Pig – Grunt – pig data model – Pig Latin – developing and testing Pig Latin scripts. Hive – data types and file formats – HiveQL data definition – HiveQL data manipulation –HiveQL queries-case study. | |
Text Books And Reference Books: T1. Tom White, "Hadoop: The Definitive Guide", 4th Edition, O'Reilley, 2012. T2. Eric Sammer, "Hadoop Operations",1st Edition, O'Reilley, 2012. | |
Essential Reading / Recommended Reading R1. VigneshPrajapati, Big data analytics with R and Hadoop, SPD 2013. R2. E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012. R3. Lars George, "HBase: The Definitive Guide", O'Reilley, 2011. R4. Alan Gates, "Programming Pig", O'Reilley, 2011. | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO631DAP - BIG DATA ANALYTICS (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To Understand big data for business intelligenceTo Learn business case studies for big data analyticsTo Understand Nosql big data managementTo manage Big data without SQLTo understanding map-reduce analytics using Hadoop and related tools |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
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Understanding Big Data
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What is big data – why big data –.Data!, Data Storage and Analysis, Comparison with Other Systems, Rational Database Management System , Grid Computing, Volunteer Computing, convergence of key trends – unstructured data – industry examples of big data – web analytics – big data and marketing – fraud and big data – risk and big data – credit risk management – big data and algorithmic trading – big data and healthcare – big data in medicine – advertising and big data– big data technologies – introduction to Hadoop – open source technologies – cloud and big data – mobile business intelligence – Crowd sourcing analytics – inter and trans firewall analytics | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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NOSQL Data Management
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Introduction to NoSQL – aggregate data models – aggregates – key-value and document data models – relationships –graph databases – schema less databases – materialized views – distribution models – sharding –– version – Map reduce –partitioning and combining – composing map-reduce calculations | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Basics of Hadoop
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Data format – analyzing data with Hadoop – scaling out – Hadoop streaming – Hadoop pipes – design of Hadoop distributed file system (HDFS) – HDFS concepts – Java interface – data flow – Hadoop I/O – data integrity – compression – serialization – Avro – file-based data Structures | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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MapReduce Applications
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MapReduce workflows – unit tests with MRUnit – test data and local tests – anatomy of MapReduce job run – classic Map-reduce – YARN – failures in classic Map-reduce and YARN – job scheduling – shuffle and sort – task execution –MapReduce types – input formats – output formats | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Hadoop Related Tools
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Hbase – data model and implementations – Hbase clients – Hbase examples –praxis. Cassandra – Cassandra data model –cassandra examples – cassandra clients –Hadoop integration. Pig – Grunt – pig data model – Pig Latin – developing and testing Pig Latin scripts. Hive – data types and file formats – HiveQL data definition – HiveQL data manipulation –HiveQL queries-case study | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Tom White, "Hadoop: The Definitive Guide", 4th Edition, O'Reilley, 2012.Eric Sammer, "Hadoop Operations",1st Edition, O'Reilley, 2012. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. VigneshPrajapati, Big data analytics with R and Hadoop, SPD 2013.E. Capriolo, D. Wampler, and J. Rutherglen, "Programming Hive", O'Reilley, 2012.Lars George, "HBase: The Definitive Guide", O'Reilley, 2011.Alan Gates, "Programming Pig", O'Reilley, 2011. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CSHO632AI - ROBOTICS AND PROCESS AUTOMATION (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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•To understand about RPA and its concepts •Apply RPA tools and functionalities •Understand the challenges and risks in RPA implementation
•Understand about bots and its usage in real time applications |
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Course Outcome |
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CO1: Illustrate the advantages, techniques of RPA CO2: Experiment with data manipulation and sequencing CO3: Experiment with Conditional and Control activities CO4: Implement event handling and launching the bots CO5: Organize the project using project management tools |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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Introduction to RPA, what should be automated, what can be automated, Techniques of automation, Benefits of RPA, Components of RPA, RPA Platforms, Record and Play. | |
Unit-2 |
Teaching Hours:9 |
CONTROL FLOW AND DATA MANIPULATION
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Sequence, Activities, Control flow and Decision Making, Variables and Scope, Collections, Arguments-Purpose and use, Data Table, File Operation. | |
Unit-3 |
Teaching Hours:9 |
TAKING CONTROL OF THE CONTROLS
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Finding and attaching windows, Finding the control, Techniques for waiting for a control, Act on controls – mouse and keyboard activities, Handling events | |
Unit-4 |
Teaching Hours:9 |
HANDLING USER EVENTS AND ASSISTANT BOTS
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Assistant Bots, Monitoring system event triggers, Monitoring image and element triggers, Launching an assistant bot on a keyboard event, Exception handling. | |
Unit-5 |
Teaching Hours:9 |
MANAGING THE CODE AND MAINTAINING THE BOT
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Project organization, Nesting workflows, Reusability of workflows, Overview of Orchestration Server, Using Orchestration Server to control bots, Using Orchestration Server to deploy bots. | |
Text Books And Reference Books: T1. Tripathi Alok Mani,” Learning Robotic Process Automation”, Packt Publishing, March 2018.
| |
Essential Reading / Recommended Reading NIL | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO632AIP - ROBOTICS AND PROCESS AUTOMATION (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
To understand about RPA and its conceptsApply RPA tools and functionalitiesUnderstand the challenges and risks in RPA implementationUnderstand about bots and its usage in real time applications |
|
Course Outcome |
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|
Unit-1 |
Teaching Hours:9 |
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Introduction
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Introduction to RPA, what should be automated, what can be automated, Techniques of automation, Benefits of RPA, Components of RPA, RPA Platforms, Record and Play | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Sequencing and Data Manipulation
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Sequence, Activities, Control flow and Decision Making, Variables and Scope, Collections, Arguments-Purpose and use, Data Table, File Operation | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Taking Control of Controls
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Finding and attaching windows, Finding the control, Techniques for waiting for a control, Act on controls – mouse and keyboard activities, Handling events | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Handling User Events and Assistant Bots
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Assistant Bots, Monitoring system event triggers, Monitoring image and element triggers, Launching an assistant bot on a key board event, Exception handling | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Managing the code and Maintaining the Bot
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Project organization, Nesting workflows, Reusability of workflows, Overview of Orchestration Server, Using Orchestration Server to control bots, Using Orchestration Server to deploy bots | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: Tripathi Alok Mani,” Learning Robotic Process Automation”, Packt Publishing, March 2018. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CSHO632CS - CYBER FORENSICS AND MALWARE DETECTION (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
This course is designed to explore fundamental concepts of cyber forensic, cyber laws and Data recovery and its analysis. This course covers the topics of malware detection, classification, tools & methodology applied to analysis and protection from malware. |
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Course Outcome |
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CO1: To understand the fundamentals of Cyber forensic over different platforms. CO2: To understand concepts of Malware Forensics; Web Attack Forensics; Bitcoin Forensics; Cyber Laws and Data Recovery & Analysis CO3: To understand the nature of malware, its capabilities, and how it is combated through detection and classification CO4: To apply the tools and methodologies used to perform static and dynamic analysis on unknown executables. CO5: To understand the malware functionality and malware detection techniques |
Unit-1 |
Teaching Hours:9 |
Unit-1
|
|
Introduction to Cyber Forensics; Windows Forensics; Linux Forensics, Mac OS Forensics; Anti-forensics; Network Forensics; Mobile Forensics; Cloud Forensics
| |
Unit-2 |
Teaching Hours:9 |
Unit-2
|
|
Malware Forensics; Web Attack Forensics; Emails and Email Crime, Bitcoin Forensics; Cyber Law and Cyberwarfare; Data Recovery & Data Analysis | |
Unit-3 |
Teaching Hours:9 |
Unit-3
|
|
Introduction to malware, OS security concepts, malware threats, evolution of malware, malware types- viruses, worms, rootkits, Trojans, bots, spyware, adware, logic bombs, malware analysis, static malware analysis, dynamic malware analysis | |
Unit-4 |
Teaching Hours:9 |
Unit-4
|
|
STATIC ANALYSIS: Analyzing Windows programs, Anti-static analysis techniques- obfuscation, packing, metamorphism, polymorphism DYNAMIC ANALYSIS: Live malware analysis, dead malware analysis, analyzing traces of malware- system-calls, api-calls, registries, network activities. Anti-dynamic analysis techniques- anti-vm, runtime-evasion techniques, Malware Sandbox, Monitoring with Process Monitor, Packet Sniffing with Wireshark, Kernel vs. User-Mode Debugging, OllyDbg, Breakpoints, Tracing, Exception Handling, Patching | |
Unit-5 |
Teaching Hours:9 |
Unit-5
|
|
Malware Functionality: Downloader, Backdoors, Credential Stealers, Persistence Mechanisms, Privilege Escalation, Covert malware launching- Launchers, Process Injection, Process Replacement, Hook Injection, Detours, APC injection Malware Detection Techniques: Signature-based techniques: malware signatures, packed malware signature, metamorphic and polymorphic malware signature Non-signature based techniques: similarity-based techniques, machine-learning methods, invariant inferences | |
Text Books And Reference Books: T1. Practical Cyber Forensics: An Incident-Based Approach to Forensic Investigations: Reddy, Niranjan, Published by Apress, Berkeley, CA, DOIhttps://doi.org/10.1007/978-1-4842-4460-9, Print ISBN 978-1-4842-4459-3, 2019 T2. Practical malware analysis The Hands-On Guide to Dissecting Malicious Software by Michael Sikorski and Andrew Honig ISBN-10: 159327-290-1, ISBN-13: 978-1-59327-290-6, 2012 | |
Essential Reading / Recommended Reading R1. Malware Detection A Complete Guide - 2019 Edition, Gerardus Blokdyk, Published by 5STARCooks, 2019, ISBN: 0655900845, 9780655900849 | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO632CSP - CYBER FORENSICS AND MALWARE DETECTION (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
|
This course is designed to explore fundamental concepts of cyber forensic, cyber laws and Data recovery and its analysis. This course covers the topics of malware detection, classification, tools & methodology applied to analysis and protection from malware. |
|
Course Outcome |
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|
Unit-1 |
Teaching Hours:9 |
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Introduction
|
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Introduction to Cyber Forensics; Windows Forensics; Linux Forensics, Mac OS Forensics; Anti-forensics; Network Forensics; Mobile Forensics; Cloud Forensics | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Malware Forensics
|
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Malware Forensics; Web Attack Forensics; Emails and Email Crime, Bitcoin Forensics; Cyber Law and Cyberwarfare; Data Recovery & Data Analysis | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Malware types and analysis
|
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Introduction to malware, OS security concepts, malware threats, evolution of malware, malware types- viruses, worms, rootkits, Trojans, bots, spyware, adware, logic bombs, malware analysis, static malware analysis, dynamic malware analysis | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Static and Dynamic Analysis
|
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STATIC ANALYSIS: Analyzing Windows programs, Anti-static analysis techniques- obfuscation, packing, metamorphism, polymorphism
DYNAMIC ANALYSIS: Live malware analysis, dead malware analysis, analyzing traces of malware- system-calls, api-calls, registries, network activities. Anti-dynamic analysis techniques- anti-vm, runtime-evasion techniques, Malware Sandbox, Monitoring with Process Monitor, Packet Sniffing with Wireshark, Kernel vs. User-Mode Debugging, OllyDbg, Breakpoints, Tracing, Exception Handling, Patching | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Malware Detection and Analysis
|
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Malware Functionality: Downloader, Backdoors, Credential Stealers, Persistence Mechanisms, Privilege Escalation, Covert malware launching- Launchers, Process Injection, Process Replacement, Hook Injection, Detours, APC injection Malware Detection Techniques: Signature-based techniques: malware signatures, packed malware signature, metamorphic and polymorphic malware signature Non-signature based techniques: similarity-based techniques, machine-learning methods, invariant inferences | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Practical Cyber Forensics: An Incident-Based Approach to Forensic Investigations: Reddy, Niranjan, Published by Apress, Berkeley, CA, DOIhttps://doi.org/10.1007/978-1-4842-4460-9, Print ISBN 978-1-4842-4459-3, 2019Practical malware analysis The Hands-On Guide to Dissecting Malicious Software by Michael Sikorski and Andrew Honig ISBN-10: 159327-290-1, ISBN-13: 978-1-59327-290-6, 2012 2 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Malware Detection A Complete Guide - 2019 Edition, Gerardus Blokdyk, Published by 5STARCooks, 2019, ISBN: 0655900845, 9780655900849 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CSHO632DA - BIG DATA SECURITY ANALYTICS (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
To provide the fundamental techniques and principles of security model in Big Data |
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Course Outcome |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CO1: Explain the various security models and threats CO2: Outline the need of security services, manage and address the challenges in web applications CO3: Examine various network security models CO4: Classify the various security threats, attacks and counter measures in securing data. CO5: Conclude the attacks and counter measure tools using watermarking technique |
Unit-1 |
Teaching Hours:9 |
SECURITY MODELS
|
|
Critical characteristics of Information - NSTISSC Security Model -Components of information System –SDLC – Information assurance - Security Threats and vulnerabilities - Overview of Security threats-– Security Standards. | |
Unit-2 |
Teaching Hours:9 |
WEB SECURITY
|
|
Introduction, Basic security for HTTP Applications and Services, Basic Security for SOAP Services, Identity Management and Web Services, Authorization Patterns, Security Considerations, Challenges. | |
Unit-3 |
Teaching Hours:9 |
NETWORK SECURITY
|
|
Network security - Intrusion Prevention, detection and Management - Firewall – Ecommerce Security - Computer Forensics - Security for VPN and Next Generation Networks. | |
Unit-4 |
Teaching Hours:9 |
ATTACKS & SECURITY MECHANISMS
|
|
Host and Application security -Control hijacking, Software architecture and a simple buffer overflow - Common exploitable application bugs, shellcode - Buffer Overflow - Side-channel attacks - Timing attacks, power analysis, cold-boot attacks, defenses – Malware - Viruses and worms, spyware, key loggers, and botnets; defenses auditing, policy - Defending weak applications - Isolation, sandboxing, virtual machines. | |
Unit-5 |
Teaching Hours:9 |
DIGITAL WATER MARKING
|
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Introduction, Difference between Watermarking and Steganography, Types and techniques (Spatial-domain, Frequency-domain, and Vector quantization based watermarking), Attacks and Tools (Attacks by Filtering, Remodulation, Distortion, Geometric Compression, Linear Compression), Watermark security & authentication. | |
Text Books And Reference Books: T1. William Stallings, “Cryptography and Network Security: Principles and Practice”, 6th Edition,PHI, 2014. T2. Michael E. Whitman and Herbert J Mattord, "Principles of Information Security", 6th edition,Vikas Publishing House, 2017. T3. Peter Wayner, Disappearing Cryptography–Information Hiding: Steganography & Watermarking, Morgan Kaufmann Publishers, New York, 2002. T4. Ingemar J. Cox, Matthew L. Miller, Jeffrey A. Bloom, Jessica Fridrich, TonKalker, Digital Watermarking and Steganography, Margan Kaufmann Publishers, New York, 2008. | |
Essential Reading / Recommended Reading R1. Bill Nelson, Amelia Phillips, F.Enfinger and Christopher Stuart, “Guide to Computer Forensics and Investigations, 4 th ed., Thomson Course Technology, 2010. R2. Matt Bishop, “Computer Security: Art and Science”, 1 st edition, Addison-Wesley Professional, 2015. R3. Neil F. Johnson, Zoran Duric, Sushil Jajodia, Information Hiding: Steganography and Watermarking-Attacks and Countermeasures, Springer, 2012. R4. Stefan Katzenbeisser, Fabien A. P. Petitcolas, Information Hiding Techniques for Steganography and Digital Watermarking, Artech House Print on Demand, 1999. | |
Evaluation Pattern CIA-70 Marks ESE-30 Marks | |
CSHO632DAP - BIG DATA SECURITY ANALYTICS (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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To provide the fundamental techniques and principles of security model in Big Data |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
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Security Models
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Critical characteristics of Information - NSTISSC Security Model -Components of information System –SDLC – Information assurance - Security Threats and vulnerabilities - Overview of Security threats-– Security Standards | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Web Security
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Introduction, Basic security for HTTP Applications and Services, Basic Security for SOAP Services, Identity Management and Web Services, Authorization Patterns, Security Considerations, Challenges | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Network Security
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Network security - Intrusion Prevention, detection and Management - Firewall – Ecommerce Security - Computer Forensics - Security for VPN and Next Generation Networks | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Attacks and Security Mechanisms
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Host and Application security -Control hijacking, Software architecture and a simple buffer overflow - Common exploitable application bugs, shellcode - Buffer Overflow - Side-channel attacks - Timing attacks, power analysis, cold-boot attacks, defenses – Malware - Viruses and worms, spyware, key loggers, and botnets; defenses auditing, policy - Defending weak applications - Isolation, sandboxing, virtual machines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Digital Watermarking
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Introduction, Difference between Watermarking and Steganography, Types and techniques (Spatial-domain, Frequency-domain, and Vector quantization based watermarking), Attacks and Tools (Attacks by Filtering, Remodulation, Distortion, Geometric Compression, Linear Compression), Watermark security & authentication | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: William Stallings, “Cryptography and Network Security: Principles and Practice”, 6 th Edition, PHI, 2014. Michael E. Whitman and Herbert J Mattord, "Principles of Information Security", 6 th edition, Vikas Publishing House, 2017. Peter Wayner, Disappearing Cryptography–Information Hiding: Steganography & Watermarking, Morgan Kaufmann Publishers, New York, 2002. Ingemar J. Cox, Matthew L. Miller, Jeffrey A. Bloom, Jessica Fridrich, TonKalker, Digital Watermarking and Steganography, Margan Kaufmann Publishers, New York, 2008. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Bill Nelson, Amelia Phillips, F.Enfinger and Christopher Stuart, “Guide to Computer Forensics and Investigations, 4 th ed., Thomson Course Technology, 2010.Matt Bishop, “Computer Security: Art and Science”, 1 st edition, Addison-Wesley Professional, 2015.Neil F. Johnson, Zoran Duric, Sushil Jajodia, Information Hiding: Steganography and Watermarking-Attacks and Countermeasures, Springer, 2012.Stefan Katzenbeisser, Fabien A. P. Petitcolas, Information Hiding Techniques for Steganography and Digital Watermarking, Artech House Print on Demand, 1999 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
● Minimum marks required to pass in practical component is 40%. ● Pass in practical component is eligibility criteria to attend Theory End semester examination for the same course. ● A minimum of 40 % required to pass in ESE -Theory component of a course. ● Overall 40 % aggregate marks in Theory & practical component, is required to pass a course. ● There is no minimum pass marks for the Theory - CIA component. ● Less than 40% in practical component is refereed as FAIL. ● Less than 40% in Theory ESE is declared as fail in the theory component. ● Students who failed in theory ESE have to attend only theory ESE to pass in the course | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
EC636OE1 - EMBEDDED BOARDS FOR IOT APPLICATIONS (2018 Batch) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:34 |
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Course Objectives/Course Description |
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· To introduce the architecture, programming and interfacing of peripheral devices with embedded boards for IOT applications. · To design IOT based smart applications.
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Course Outcome |
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Understand the architecture and imporatnce of wireless sensor network Understand the architecture, programming and interfacing principles of ATMEGA32 AVR microcontroller Understand the architecture, programming and interfacing principles of Raspberry pi Understand the applications of ATMEGA32 AVR microcontroller, Microprocessor and Rasberry Pi in IOT. Analyze the design scheme for IOT using Microcontrollers. |
Unit-1 |
Teaching Hours:9 |
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NETWORKING SENSORS
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Network Architecture - Sensor Network Scenarios- Optimization Goals and Figures of Merit- Physical Layer and Transceiver Design Considerations-MAC Protocols for Wireless Sensor Networks- Introduction of sensors and transducers. | |||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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ARDUINO BOARD AND its? INTERFACING
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ATMEGA328 microcontroller - Architecture- memory organisation – Operating modes – On chip peripherals- Embedded communication interfaces- Example programs using Arduino IDE- Integration of peripherals (Buttons & switches, digital inputs, Matrix keypad, Basic RGB color-mixing, electromechanical devices- Displays- sensors(Temperature, Pressure, Humidity, Water level etc.), camera, real time clock, relays, actuators, Bluetooth, Wi-fi).
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Unit-3 |
Teaching Hours:9 |
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IOT BASED SYSTEM DESIGN
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Definition of IoT- Applications and Verticals- System Architecture-Typical Process Flows-Technological Enablers- Open Standard Reference Model- Design Constraints and Considerations- IoT Security- Experiments using Arduino Platform (3 hours). | |||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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RASBERRY-PI
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Introduction to Raspberry pi – configuration of Raspberry pi – programming raspberry pi - Implementation of IOT with Rasberry pi | |||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Unit-5 {This unit is entirely practical based}
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Implementation of a IOT based real time system. The concept of the specific embedded design has to be discussed. Eg: Smart Irrigation using IOT/ IoT Based Biometrics Implementation on Raspberry Pi/ Automation etc. Note: Unit – V will be based on a group project. Each group comprising of maximum 3 members. Any microcontroller can be used in Unit-V. | |||||||||||||||||||
Text Books And Reference Books:
1. Slama, Dirak “Enterprise IOT : Strategies and Best Practices for Connected Products and services”, Shroff Publisher, 1st edition,2015. 2. "Protocols and Architectures for Wireless Sensor Networks", John Wiley, 2007. 3. Ali Mazidi, Sarmad Naimi, Sepehr Naimi “AVR Microcontroller and Embedded Systems: Using Assembly and C”, Pearson 2013. 4. Wentk, “Richard Raspberry Pi”, John Wiley & Sons, 2014 | |||||||||||||||||||
Essential Reading / Recommended Reading 1. A.K. Ray & K.M.Bhurchandi, “Advanced Microprocessors and peripherals- Architectures, Programming and Interfacing”, Tata McGraw Hill, 2002 reprint. 2. Gibson, “Microprocessor and Interfacing” Tata McGraw Hill,II edition Muhammad Ali Mazidi, Rolin D. Mckinlay, Danny Causey “8051 Microcontroller and | |||||||||||||||||||
Evaluation Pattern CIA marks=70 ESE marks= 30 | |||||||||||||||||||
EC636OE4 - FUNDAMENTALS OF IMAGE PROCESSING (2018 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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This Course is for third year students and is offered as interdisciplinary course. Students will be understanding the concepts and apply in their respective domains
1) COURSE OBJECTIVES
1. Understand the basic principles of digital image processing.
2. Analyze and apply the algorithms based on the applications given
3. Implement the algorithms of a given application using MATLAB/Python
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Course Outcome |
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At the end of the course, students will be able to CO1-Understand the basic principles of image processing L2 CO2-Understand the tools used for image processing applications L2 CO3-Analyze the methods used for image preprocessing L4 CO4-Apply the compression techniques and analyze the results L3 CO5-Develop an image processing system for a given application L5 |
Unit-1 |
Teaching Hours:9 |
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Digital Image Fundamntals
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Concept of Digital Image, conversion of analog image to digital, General Applications of image processing, Fundamental Steps in Digital Image Processing. Components of an Image Processing System. Elements of Visual Perception. Light and the Electromagnetic Spectrum. Image Sensing and Acquisition. Image Sampling and Quantization
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Unit-2 |
Teaching Hours:9 |
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Introduction MATLAB and IP toolbox
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Introduction to MATLAB, Introduction to IP Tool box, Exercises on image enhancement, image restoration, and image segmentation | |||||||||||
Unit-3 |
Teaching Hours:9 |
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IMAGE PROCESSING TECHNIQUES PART 1
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Image Enhancement in the Spatial Domain: Some Basic Gray Level Transformations. Histogram Processing. Enhancement Using Arithmetic/Logic Operations. Basics of Spatial Filtering. Smoothing Spatial Filters. Sharpening Spatial Filters. Importance of Image Restoration, Model of the Image Degradation/Restoration Process. Noise Models. Filters for Image Restoration: Minimum Mean Square Error (Wiener) Filtering. Constrained Least Squares Filtering. Geometric Mean Filter | |||||||||||
Unit-4 |
Teaching Hours:9 |
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IMAGE PROCESSING TECHNIQUES PART 2
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Image Compression: Fundamentals. Image Compression Models. Elements of Information Theory. Error-Free Compression. Lossy Compression. Image Compression Standards. Image Segmentation: Detection of Discontinuities. Edge Linking and Boundary Detection. Thresholding. Region-Based Segmentation. Segmentation by Morphological Watersheds | |||||||||||
Unit-5 |
Teaching Hours:9 |
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APPLICATION OF IMAGE PROCESSING
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Applications of image processing in the field of Biomedical, Remote sensing, Machine vision, Pattern recognition, and Microscopic Imaging | |||||||||||
Text Books And Reference Books: T1. Rafael C. Gonzalez, Richard E.Woods, Digital Image Processing using MATLAB, PHI, 2005
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Essential Reading / Recommended Reading R1. Rafael C. Gonzalez, Richard E.Woods, Digital Image Processing‘, Pearson Education, Inc., Third Edition, 2016 R2. Anil K. Jain, Fundamentals of Digital Image Processing‘, Prentice Hall of India, 2002 | |||||||||||
Evaluation Pattern
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EC636OE7 - E-WASTE MANAGEMENT AND RADIATION EFFECT (2018 Batch) | |||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Describe E-waste disposal, collection, recycling, and materials recovery techniques and technologies and effect of mobile radiation on human health and life .
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Course Outcome |
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Summarize the history of E-waste management including impacts from early human civilization to current day. Describe the major categories of E-waste. Assess the major regulatory developments surrounding E-waste management. Characterize the components and chemical and physical properties Summarize the impact of radiation, smartphones and mobile devices on human health and life |
Unit-1 |
Teaching Hours:12 |
Magnitude of the Global E-Waste Problem
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Scope Of The Problem, Refurbishing Discarded Electronic Devices , Recycling Of Devices Manufactured With Newer High Technology Alloy Nano-materials, Global Distribution Steams Of E-Waste— Where Does It Go?, Uptake Of Toxic Chemicals Originating From E-Waste Into Food , Biological Effects Of E-Waste Chemicals, Refurbishing Of Outdated Electronic Devices, Inter-country Variations In The Collection Of Electronic Devices For Recycling, Recycling Of Component Materials In Electronic Devices, Differences In E-Waste Handling Between Developed And Developing Countries, Child Labor, Occupational And Environmental Safety Issues, Landfill Operations, Waste Ponds, Incineration. | |
Unit-2 |
Teaching Hours:8 |
Metals, Metallic Compounds, Organic Chemicals, E-Waste Chemical Mixtures and Toxicology of E-Waste
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Metals And Metallic Compounds, Nano-materials, Representative Organic E-Waste Chemicals, ChemicalMixtures Exposures In E-Waste Recycling, Risk Assessment Approaches For E-Waste, Public Health Implications And Directions Forward, Toxic Metals/Metalloids, Organic Chemicals. | |
Unit-3 |
Teaching Hours:9 |
Risk Assessment/Risk Communication Approaches for E-Waste Sites
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In Utero Exposure To E-Waste Chemicals, Children And Adult, Genetic Inheritance, Persons Of Poor Nutritional Status, Subsistence Farmers/Hunters And Fishers/ Low Socioeconomic Status, Contamination Of Local Food Supplies And House Dust,Individual Chemical Approaches,Mixture Approaches, Perceptions Of Risk At Toxic Waste Sites In Relation To Economic And Food Concerns: The Role Of Risk Communication. | |
Unit-4 |
Teaching Hours:6 |
Translation of Risk Assessment Information Into Effective International Policies and Actions.
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Communication Of Scientific Information In Practical Terminology, Information Mapping Technology Approaches, Collaborations Among Interested International Stakeholders/Government Agencies/Industrial Groups/Ngos, International Conferences And Diplomatic Interactions—Both Formal And Informal
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Unit-5 |
Teaching Hours:9 |
The impact of radiation, smartphones and mobile devices on human health and life
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Introduction, Effect of electromagnetic waves on human brains, Effect on human’s upper extremities, back and neck caused by handheld devices, Effect of smartphones on drivers, Advantages and disadvantages of using smartphones and HHDs, Can people live without cell phones, Cellular Tower Radiation effects, Solutions to mitigate impact of cell phones and mobile devices on human health and life. Harmful Effects of Radiation, Health Effects of Radiation, Threshold Effects of Radiation, Non-threshold Effects of Radiation,Sources of radiation to the human population,Doses and risks associated with diagnostic radiology, interventional radiology/cardiology, and nuclear medicine, cellular response to radiation, risk associated with diagnostic radiology, radiation sickness ,radiation therapy
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Text Books And Reference Books: 1. 1. Bruce A. Fowler., “ Electronic WasteToxicology and Public Health Issues”,Acadamic press 2. Johri R., “E-waste: implications, regulations, and management in India and current global best a. practices”, TERI Press, New Delhi. 3. R.E Hester and R.M Harrison., “E-waste Recycling”, RSC publication. 4. Leonid Miakotko., “The impact of smartphones and mobile devices on human health and life”, https://www.nyu.edu/classes/keefer/waoe/miakotkol.pdf.
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Essential Reading / Recommended Reading 1. Daniel Grosch., “Biological Effects of Radiations’’, 2nd Edition Academic Press 2. Electronic Waste Management Rules 2016, Govt. of India, available online at CPCB website. | |
Evaluation Pattern CIA=70 ESE=30 | |
EE636OE2 - NONCONVENTIONAL ENERGY SOURCES (2018 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To recognize the need of renewable energy technologies and their role in the current scenario of energy crisis · .Distinguish between the sustainable energy sources and fossil energy sources · Describe the principles of renewable energy production from various renewable sources |
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Course Outcome |
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Upon completion of this course, the students will be able · Demonstrate an understanding of the scientific principles of methodology of Non-conventional energy. · Acquire working knowledge of different Renewable energy science-related topics |
Unit-1 |
Teaching Hours:12 |
Introduction
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Conventional energy resources-availabilty and sustainability issues-,Non conventional sources-advantages over conventional sources- Renewable Energy sources-Advantages and limitations | |
Unit-2 |
Teaching Hours:12 |
Solar energy
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Solar energy – Introduction to solar energy: solar radiation, availability, measurement and estimation. Solar Thermal systems- Solar collectors(fundamentals only)- Applications -Solar heating system, Air conditioning and Refrigeration system ,Pumping system, solar cooker, Solar Furnace, Solar Greenhouse -Design of solar water heater | |
Unit-3 |
Teaching Hours:12 |
Solar Photovoltaic Systems
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Solar Photovoltaic Systems:- Photovoltaic conversion- Solar Cell, module, Panel and Array Solar cell- materials-characteristics- efficiency-Battery back up-Charge controller- MPPT-PV system classification- Design of stand-alone PV system. | |
Unit-4 |
Teaching Hours:12 |
Wind Power Systems
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Wind source – wind statistics - energy in the wind –betz criterion-,mechanical components-aerodynamic force-angle of attack-pitch angle-yaw-rotor types, wind driven generators-fixed speed drives- variable speed drives- –-environmental aspects. | |
Unit-5 |
Teaching Hours:12 |
Ocean, Geothermal and other resources
|
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OTEC systems-types, wave energy-types, tidal energy-different schemes, Renewable Hydro –Power -Small, Mini and Micro hydro power-Types of turbines and generators Geothermal energy-geothermal resources, limitations and environmental aspects of each type Fuel cells, MHD power generation, Biomass energy | |
Text Books And Reference Books: 1. Non Conventional Energy Resources-B.H.Khan 2. G.D.Rai ,Non Conventional Energy Sources, Khanna Publishers,4 th Edition,2009 3. D.P.Kothari, K.C.Singal, Rakesh Ranjan, Renewable Energy Sources and Emerging Technologies, Prentice Hall of India, New Delhi, 2009 4. Mukund R Patel “Wind and solar power systems Design ,Analysis and operation” Taylor and Francis publishers ,2nd edition,2006,ISBN978-0-8493-1570-1 | |
Essential Reading / Recommended Reading 1. A.K. Mukherjee, Nivedita Takur Photovoltaic Systems –Analysis and Design(PHI-2011) 2. Ahmed Hemami, Wind Turbine Technology, (Cengate Learning,2012,First India Edition) 3. Wind energy Conversion Systems – Freris L.L. (Prentice Hall,1990) 4. Wind Turbine Technology: Fundamental concepts of wind turbine technology Spera D.A. (ASME Press, NY, 1994) | |
Evaluation Pattern CIA I - 20 marks CIA II - midsem - 50 marks CIA III - 20 marks ESE - 100 marks | |
EE636OE3 - INTRODUCTION OF HYBRID ELECTRIC VEHICLES (2018 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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This course introduces the fundamental concepts, principles, analysis and design of hybrid and electric vehicles. |
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Course Outcome |
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· To understand concepts of hybrid and electric drive configuration, types of electric machines that can be used, suitable energy storage devices etc · To recognize the application of various drive components and selection of proper component for particular applications. |
Unit-1 |
Teaching Hours:12 |
HYBRID VEHICLES
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History and importance of hybrid and electric vehicles, impact of modern drive-trains on energy supplies. Basics of vehicle performance, vehicle power sources, transmission characteristics, and mathematical models to describe vehicle performance. | |
Unit-2 |
Teaching Hours:12 |
HYBRID TRACTION
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Basic concept of hybrid traction, introduction to various hybrid drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis. Basic concepts of electric traction, introduction to various electric drive-train topologies, power flow control in hybrid drive-train topologies, fuel efficiency analysis. | |
Unit-3 |
Teaching Hours:12 |
MOTORS AND DRIVES
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Introduction to electric components used in hybrid and electric vehicles, configuration and control of DC Motor drives, Configuration and control of Induction Motor drives, configuration and control of Permanent Magnet Motor drives, Configuration and control of Switch Reluctance Motor drives, drive system efficiency. | |
Unit-4 |
Teaching Hours:12 |
INTEGRATION OF SUBSYSTEMS
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Matching the electric machine and the internal combustion engine (ICE), Sizing the propulsion motor, sizing the power electronics, selecting the energy storage technology, Communications, supporting subsystems | |
Unit-5 |
Teaching Hours:12 |
ENERGY MANAGEMENT STRATEGIES
|
|
Introduction to energy management strategies used in hybrid and electric vehicle, classification of different energy management strategies, comparison of different energy management strategies, implementation issues of energy strategies. | |
Text Books And Reference Books: 1. BimalK. Bose, ‘Power Electronics and Motor drives’ , Elsevier, 2011 2. IqbalHussain, ‘Electric and Hybrid Vehicles: Design Fundamentals’, 2nd edition, CRC Pr I Llc, 2010 | |
Essential Reading / Recommended Reading 1. Sira -Ramirez, R. Silva Ortigoza, ‘Control Design Techniques in Power Electronics Devices’, Springer, 2006 2. Siew-Chong Tan, Yuk-Ming Lai, Chi Kong Tse, ‘Sliding mode control of switching Power Converters’, CRC Press, 2011 3. Ion Boldea and S.A Nasar, ‘Electric drives’, CRC Press, 2005 | |
Evaluation Pattern CIA I - 20 marks CIA II -midsem 50 marks CIA III - 20 marks ESE - 100 marks | |
EE636OE6 - ROBOTICS AND AUTOMATION (2018 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To understand concepts in kinematics and dynamics of robotic system. · To introduce control strategies of simple robotic system. · To study the applications of computer based control to integrated automation systems. |
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Course Outcome |
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· Understand the basic concept of robotics and automation. · Mechanical requirement and design of control system for robot. · Applications of robots in various domains. |
Unit-1 |
Teaching Hours:12 |
Introduction
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Robot definitions - Laws of robotics - Robot anatomy - History - Human systems and Robotics - Specifications of Robots - Flexible automation versus Robotic technology - Classification applications | |
Unit-2 |
Teaching Hours:12 |
Robotic systems
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Basic structure of a robot – Robot end effectors - Manipulators - Classification of robots – Accuracy - Resolution and repeatability of a robot - Drives and control systems – Mechanical components of robots – Sensors and vision systems - Transducers and sensors - Tactile sensors – Proximity sensors and range sensors - Vision systems - RTOS - PLCs - Power electronics | |
Unit-3 |
Teaching Hours:12 |
Robot kinematics, dynamics and programming
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Matrix representation - Forward and reverse kinematics of three degree of freedom – Robot Arm – Homogeneous transformations – Inverse kinematics of Robot – Robo Arm dynamics - D-H representation of forward kinematic equations of robots - Trajectory planning and avoidance of obstacles - Path planning - Skew motion - Joint integrated motion – Straight line motion - Robot languages- Computer control and Robot programming/software | |
Unit-4 |
Teaching Hours:12 |
Control system design
|
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Open loop and feedback control - General approach to control system design - Symbols and drawings - Schematic layout - Travel step diagram, circuit and control modes - Program control - Sequence control - Cascade method - Karnaugh-Veitch mapping - Microcontrollers - Neural network - Artificial Intelligence - Adaptive Control – Hybrid control | |
Unit-5 |
Teaching Hours:12 |
Robot applications
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Material handling - Machine loading, Assembly, inspection, processing operations and service robots - Mobile Robots - Robot cell layouts - Robot programming languages | |
Text Books And Reference Books: 1. Nagrath and Mittal, “Robotics and Control”, Tata McGraw-Hill, 2003. 2. Spong and Vidhyasagar, “Robot Dynamics and Control”, John Wiley and sons, 2008. 3. S. R. Deb and S. Deb, ‘Robotics Technology and Flexible Automation’, Tata McGraw Hill Education Pvt. Ltd, 2010. | |
Essential Reading / Recommended Reading 1. Saeed B. Niku, ‘Introduction to Robotics’,Prentice Hall of India, 2003. 2. Mikell P. Grooveret. al., "Industrial Robots - Technology, Programming and Applications", McGraw Hill, New York, 2008. | |
Evaluation Pattern CIA I -20 marks CIA II - midsem 50 marks CIA III - 20 marks ESE - 100 marks | |
IT634P - DATAWAREHOUSING AND DATAMINING (2018 Batch) | |
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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● To serve as an introductory course to under graduate students with an emphasis on the design aspects of Data mining and Data Warehousing ● To introduce the concept of data mining with in detail coverage of basic tasks, metrics, issues, and implication. Core topics like classification, clustering and association rules are exhaustively dealt with. ● To introduce the concept of data warehousing with special emphasis on architecture and design. ● Practical exposure on implementation of well known data mining tasks. ● Exposure to real life data sets for analysis and prediction. ● Learning performance evaluation of data mining algorithms in a supervised and an unsupervised setting. |
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Course Outcome |
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CO1: Identify the differences between relational database and data warehouses, the need for data warehousing to formulate the decision support system an engineering specialization for the prediction and modeling to complex engineering activities.(L3) CO2: Summarize the dominant data warehousing architectures and analyze their implementation details to develop multidimensional data models to analyze complex engineering problems.(L2) CO3: Implement various data pre-processing techniques to design data warehouses that meet the specified needs of the society with appropriate environmental considerations.(L3) CO4: Analyze the various clustering and classification algorithm functionalities and evaluate their merits and demerits to acquire research based knowledge for the synthesis of the information to provide valid conclusions.(L4) CO5: Explain the advanced data mining concepts and outline their scope of providing IT solutions for different domains which helps in the betterment of life.(L5) |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION AND DATA WAREHOUSING
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Introduction, Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture, Implementation, Further Development, Data Warehousing to Data Mining | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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DATA PREPROCESSING, LANGUAGE, ARCHITECTURES, CONCEPT DESCRIPTION
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Why Preprocessing, Cleaning, Integration, Transformation, Reduction, Discretization, Concept Hierarchy Generation, Data Mining Primitives, Query Language, Graphical User Interfaces, Architectures, Concept Description, Data Generalization, Characterizations, Class Comparisons, Descriptive Statistical Measures. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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ASSOCIATION RULES
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Association Rule Mining, Single-Dimensional Boolean Association Rules from Transactional Databases, Multi-Level Association Rules from Transaction Databases | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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CLASSIFICATION AND CLUSTERING
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Classification and Prediction, Issues, Decision Tree Induction, Bayesian Classification, Association Rule Based, Other Classification Methods, Prediction, Classifier Accuracy, Cluster Analysis, Types of data, Categorization of methods, Partitioning methods, Outlier Analysis | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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RECENT TREND
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Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Databases, Multimedia Databases, Time Series and Sequence Data, Text Databases, World Wide Web, Applications and Trends in Data Mining
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Text Books And Reference Books: 1. J. Han, M. Kamber, “Data Mining: Concepts and Techniques”, Harcourt India / Morgan Kauffman, 2011. 2. Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining, Pearson Education, 2012. | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. K.P.Soman, Shyam Diwakar, V.Ajay: Insight into Data Mining – Theory and Practice, PHI, 2012. 2. David Hand, Heikki Manila, Padhraic Symth, “Principles of Data Mining”, PHI 2012. 3. W.H.Inmon, “Building the Data Warehouse”, 3rd Edition, Wiley, 2011. 4. Alex Bezon, Stephen J.Smith, “Data Warehousing, Data Mining & OLAP”, MeGraw-Hill Edition, 2001 5. Paulraj Ponniah, “Data Warehousing Fundamentals”, Wiley-Interscience Publication, 2003. | |||||||||||||||||||||||||||||||
Evaluation Pattern
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IT635 - SOFTWARE TESTING (2018 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To give an overview of the software testing techniques. To design and understand test cases, various levels of testing and related concepts. |
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Course Outcome |
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CO1: Identify the reason for bugs and device mechanism for preventing /fixing bugs with respect to the principles in software testing . (L3) CO2: Interpret the existing procedures for software testing which would enhance the software quality. (L2) CO3: Construct a software test plan to validate the software with respect to defined test scenarios. (L3) CO4: Justify the test processes applied in the testing framework and incorporate the procedures as a formatted report.(L5) CO5: Analyze the available techniques in software testing which would validate any given software product in a commercial environment. (L4) |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Testing as an Engineering Activity – Role of Process in Software Quality – Testing as a Process – Basic Definitions – Software Testing Principles – The Tester’s Role in a Software Development Organization – Origins of Defects – Defect Classes – The Defect Repository and Test Design – Defect Examples – Developer/Tester Support for Developing a Defect Repository | |||||
Unit-2 |
Teaching Hours:9 |
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TEST CASE DESIGN
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Introduction to Testing Design Strategies – The Smarter Tester – Test Case Design Strategies – Using Black Box Approach to Test Case Design Random Testing – Requirements based testing – positive and negative testing – Boundary Value Analysis – decision tables - Equivalence Class Partitioning state-based testing – cause effect graphing – error guessing - compatibility testing – user documentation testing – domain testing Using White–Box Approach to Test design – Test Adequacy Criteria – static testing vs. structural testing – code functional testing - Coverage and Control Flow Graphs – Covering Code Logic – Paths – Their Role in White–box Based Test Design – code complexity testing – Evaluating Test Adequacy Criteria. | |||||
Unit-3 |
Teaching Hours:9 |
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LEVELS OF TESTING
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The Need for Levels of Testing – Unit Test – Unit Test Planning –Designing the Unit Tests. The Test Harness – Running the Unit tests and Recording results – Integration tests – Designing Integration Tests – Integration Test Planning – scenario testing – defect bash elimination -System Testing – types of system testing - Acceptance testing – performance testing - Regression Testing – internationalization testing – ad-hoc testing - Alpha – Beta Tests – testing OO systems – usability and accessibility testing | |||||
Unit-4 |
Teaching Hours:9 |
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TEST MANAGEMENT
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People and organizational issues in testing – organization structures for testing teams – testing services - Test Planning – Test Plan Components – Test Plan Attachments – Locating Test Items – test management – test process - Reporting Test Results – The role of three groups in Test Planning and Policy Development – Introducing the test specialist – Skills needed by a test specialist – Building a Testing Group. | |||||
Unit-5 |
Teaching Hours:9 |
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CONTROLLING AND MONITORING
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Software test automation – skills needed for automation – scope of automation – design and architecture for automation – requirements for a test tool – challenges in automation - Test metrics and measurements –project, progress and productivity metrics – Status Meetings – Reports and Control Issues – Criteria for Test Completion – SCM – Types of reviews – Developing a review program – Components of Review Plans– Reporting Review Results. – Evaluating software quality – defect prevention – testing maturity model – Case Studies. | |||||
Text Books And Reference Books: TEXT BOOKS 1. Boris Beizer, “Software Testing Techniques”, Dreamtech. Second Edition, 2009 2. Srinivasan Desikan and Gopalaswamy Ramesh, “Software Testing – Principles and Practices”, Pearson education, 2008. | |||||
Essential Reading / Recommended Reading REFERENCE BOOKS 1. Elfriede Dustin, “Effective Software Testing”, Pearson Education, First Edition, 2008. 2. Edward Kit, “Software Testing in the Real World”, Pearson Education, 2008. 3. Aditya P.Mathur, “Foundations of Software Testing”, Pearson Education, 2011.
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Evaluation Pattern
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MA636OE3 - NUMERICAL SOLUTION OF DIFFERENTIAL EQUATIONS (2018 Batch) | |||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Many physical laws are couched in terms of rate of change of one/two or more independent variables, most of the engineering problems are characterized in the form of either nonlinear ordinary differential equations or partial differential equations. The methods introduced in the solution of ordinary differential equations and partial differential equations will be useful in attempting any engineering problem. |
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Course Outcome |
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CO1: Operate multistep numerical techniques to solve first and second order ordinary differential equations. L3 CO2: Discuss finite difference approximations to solve boundary value problems. L4 CO3: Discuss finite difference schemes for Parabolic equation. L3 CO4: Operate finite difference method to solve boundary value problems of hyperbolic and elliptic differential equations L4 CO5: Construct finite volume method to solve differential equations. L3 |
Unit-1 |
Teaching Hours:9 |
Ordinary Differential Equations
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Multistep (explicit and implicit) methods for initial value problems | |
Unit-2 |
Teaching Hours:9 |
Finite Difference Methods
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Finite difference approximations for derivatives, boundary value problems with explicit boundary conditions, implicit boundary conditions, error analysis | |
Unit-3 |
Teaching Hours:9 |
Partial Differential Equations
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Classification of partial differential equations, finite difference schemes for Parabolic equations, multilevel explicit and implicit methods for one dimensional heat equation, iterative methods for one dimensional heat equation | |
Unit-4 |
Teaching Hours:9 |
Hyperbolic And Elliptic Equations
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Finite difference schemes for hyperbolic and elliptic equations, implicit method of solving one dimensional wave equation, iterative scheme of solving Laplace and Poisson equation, ADI method | |
Unit-5 |
Teaching Hours:9 |
Discretization
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The Discretization Concept: Methods of deriving the discretization equation: Taylor series formulation, control –Volume Formation: Illustrative example: One dimensional heat conduction equation, Steady one dimensional Convection and Diffusion Equation and its Physical Phenomena. | |
Text Books And Reference Books: M.K. Jain, “Numerical Solution of Differential Equations”, Wiley Eastern, 1984. | |
Essential Reading / Recommended Reading R1. G.D. Smith, “Numerical Solution of Partial Differential Equations”, Oxford Univ. Press, 2004. R2. M.K.Jain, S.R.K. Iyengar and R.K. Jain, “Computational Methods for Partial Differential Equations”, Wiley Eastern, 2005. R3. S. S. Sastry, “Numerical Analysis for Engineers”, Tata Mcgraw Hill Edition. | |
Evaluation Pattern Continuous Internal Assessment (CIA): 50% (50 marks out of 100 marks) End Semester Examination(ESE): 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII:Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications: 10 marks Attendance : 05 marks Total : 50 marks
Mid Semester Examination (MSE) : The MSE is conducted for 50 marks of 2 hours duration. Question paper pattern; Five out of Six questions have to be answered. Each question carries 10 marks
End Semester Examination (ESE): The ESE is conducted for 100 marks of 3 hours duration. The syllabus for the theory papers are divided into FIVE units and each unit carries equal Weightage in terms of marks distribution. Question paper pattern is as follows: Two full questions with either or choice will be drawn from each unit. Each question carries 20 marks. There could be a maximum of three sub divisions in a question. The emphasis on the questions is to test the objectiveness, analytical skill and application skill of the concept, from a question bank which reviewed and updated every year The criteria for drawing the questions from the Question Bank are as follows 50 % - Medium Level questions 25 % - Simple level questions 25 % - Complex level questions | |
ME636OE3 - BASIC AUTOMOBILE ENGINEERING (2018 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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The objective of this course isto impact knowledge to students in various systems of Automobile Engineering and to learn the fundamental principles, construction and auxiliary systems of automotive engines |
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Course Outcome |
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CO1: To describe chassis, body and engine components of automobile CO2: To demonstrate knowledge of transmission, cooling and lubrication systems CO3: To demonstrate knowledge of engine injection and ignition systems CO4: To demonstrate knowledge of steering, brakes and suspension systems CO5: To describe environmental impact of emissions from vehicles and methods for controlling it. |
Unit-1 |
Teaching Hours:9 |
Engine
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Engine classifications, number of strokes, cylinders, types of combustion chambers for petrol and diesel engines, valves, valve arrangements and operating mechanisms, piston, design basis, types, piston rings, firing order, fly wheel. | |
Unit-1 |
Teaching Hours:9 |
Introduction
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Classification of vehicles, options of prime movers, transmission and arrangements. | |
Unit-2 |
Teaching Hours:9 |
Fuel Supply Systems
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Petrol and diesel engines, fuel pumps, Mechanical and electrical diaphragm pumps, air and fuel filters. | |
Unit-2 |
Teaching Hours:9 |
Carburettors and Injection Systems
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carburetors, fuel injection systems for diesel and petrol engines, electronic fuel injection, super chargers, muffers. | |
Unit-3 |
Teaching Hours:9 |
Electrical System
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Ignition system, distributor, electronic ignition, magneto, dynamo, alternator, regulator, starting motor, introduction to various accessories, typical wiring diagram.
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Unit-3 |
Teaching Hours:9 |
Cooling and Lubrication system for IC Engines
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Necessity, methods of cooling, air cooling, water cooling, components of water cooling systems, Objective of lubrication, requirements of lubricant, types of lubricant, various systems of engine lubrication. | |
Unit-4 |
Teaching Hours:9 |
Chassis
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Introduction of chassis, classification, conventional construction, frameless construction, introduction to vehicle dimensions. | |
Unit-4 |
Teaching Hours:9 |
Transmission System
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Introduction to single plate clutch, wet and dry type, clutch actuating mechanisms, study of clutch components, fluid fly wheel. Gear box , Theory, four speed and five speed sliding mesh, constant mesh and synchromesh type, selector mechanism, automatic transmission, overdrive, transfer box four wheel drive, torque converter, propeller shaft. | |
Unit-5 |
Teaching Hours:9 |
Suspension System
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Systems, springs, shock absorbers, axles, front and rear, different methods of floating rear axle, front axle and wheel alignment, types of rims and tyres. | |
Unit-5 |
Teaching Hours:9 |
Steering System
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Steering mechanisms, types of brakes and brake actuation mechanisms. | |
Text Books And Reference Books:
1. Kripal Singh,“Automobile Engineering”, Vol.-1 & 2, Standard publisher distributors 2015.
2. Joseph Heitner,“Automotive Mechanics”, East-West student edition 2014. | |
Essential Reading / Recommended Reading 1. Crouse. W.H. and Angling, D.L “Automobile Mechanics”2009. 2. Judge, A.W ,“Automobile Electrical System”
3. K.k.Ramalingam,“Automobile engineering”, scitech publications 2001 | |
Evaluation Pattern CIA1-10MARKS CIA2-25MARKS CIA3-10MARKS ATTENDANCE-5MARKS ESE-50MARKS | |
ME636OE4 - PROJECT MANAGEMENT (2018 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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The course aims at the following learning targets · To understand the concepts of project definition, life cycle, and systems approach; · To develop competency in project scooping, work definition, and work breakdown structure (WBS) · To handle the complex tasks of time estimation and project scheduling, including PERT and CPM
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Course Outcome |
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CO1: Apply the concept of project management in engineering field through project management life cycle.(L3)(PO11) CO2: Analyze the quality management and project activity in engineering field through work breakdown structure. (L4)(PO10) CO3: Analyze the fundamentals of project and network diagram in engineering and management domain through PDM techniques. (L4)(PO1) CO4: Evaluate the concept of network analysis through PERT and CPM techniques. (L5)(PO2) CO5: Apply the concept of scheduler based on resource availability in engineering and management field through project proposal. (L3)(PO11) |
Unit-1 |
Teaching Hours:9 |
Project Management
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Principles of Project Management: Defining, Planning, Executing, Controlling, Closing; Project Management Life Cycle: Phases of Project Management, Levels of Project Management | |
Unit-1 |
Teaching Hours:9 |
Introduction to Project
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Definition of a Project, Sequence of Activities, Unique activities, Complex Activities, Connected Activities, One Goal, Specified Time, Within Budget, According to Specification. Defining a Program, Project parameters: Scope, Quality, Cost, Time, Resources; The scope triangle: Time, Cost, and Resource Availability, Project Classification | |
Unit-2 |
Teaching Hours:9 |
Quality Management
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Continuous Quality Management Model, Process Quality Management Model; Risk Management, Risk Analysis; Relationship between Project Management and other Methodologies | |
Unit-2 |
Teaching Hours:9 |
Project Activities
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Work Breakdown Structure, Uses of WBS, Generating the WBS: Top-Down/ Bottom-Up Approach, WBS for Small Projects, Intermediate WBS for large projects; Criteria to Test for Completeness in the WBS: Measurable Status, Bounded, Deliverable, Cost/Time Estimate, Acceptable Duration Limits, Activity Independence; Approaches to Building the WBS: various approaches, Representing WBS | |
Unit-3 |
Teaching Hours:9 |
Activity Duration, Resource Requirements, & Cost
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Duration: Resource Loading versus Activity Duration, Variation in Activity Duration, Methods for Estimating Activity Duration, Estimation Precision; Resources; Estimating Cost, JPP Session to Estimate Activity Duration & Resource Requirements, Determining Resource Requirements | |
Unit-3 |
Teaching Hours:9 |
Fundamentals of Project Network Diagram
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Project Network Diagram, Benefits to Network- Based Scheduling, Building the Network Diagram Using the PDM, Analyzing the Initial Project Network Diagram. | |
Unit-4 |
Teaching Hours:9 |
Network Analysis ? PERT
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Introduction to Project Evaluation and Review Technique, Event, Activity, Dummy, Network rules, Graphical guidelines for network, Common partial situations in network, numbering the events, Cycles; Developing the Network, Planning for network construction, modes of network construction, steps in developing network, hierarchies; Time Estimates in PERT, Uncertainties and use of PERT, Time estimates, Frequency distribution, Mean, Variance & standard deviation, Probability distribution, Beta distribution, Expected time; Time Computations in PERT, Earliest expected time, Formulation for TE, Latest allowable occurrence time, Formulation for TL, Combined tabular computations for TE, TL; Slack, Critical Path, Probability of meeting schedule date. | |
Unit-4 |
Teaching Hours:9 |
Network Analysis- CPM
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Introduction to Critical Path Method, Procedure, Networks, Activity time estimate, Earliest event time, Latest allowable occurrence time, Combined tabular computations for TE and TL, Start & Finish times of activity, Float, Critical activities & Critical path. Crashing of project network, Resource leveling and Resource allocation | |
Unit-5 |
Teaching Hours:9 |
Schedules Based on Resource Availability
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Resources, Leveling Resources, Acceptability Leveled Schedule, Resource Leveling Strategies, Work Packages: Purpose of a Work Package, Format of a Work Package | |
Unit-5 |
Teaching Hours:9 |
Joint Project Planning Session
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Planning the Sessions, Attendees, Facilities, Equipments, Complete Planning Agenda, Deliverables, Project Proposal | |
Text Books And Reference Books: TEXT BOOKS: T1.“Effective Project Management”, Robert K. Wysocki, Robert Beck. Jr., and David B. Crane; - John Wiley & Sons 2003. T2. Project Planning and Control with CPM and PERT” Dr. B.C. Punmia & K.K.Khandelwal; - Laxmi Publications, New Delhi 2011.
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Essential Reading / Recommended Reading R1. “Project Management” S. Choudhury, - TMH Publishing Co. Ltd, New Delhi 1998. R2. “Total Project Management- The Indian Context” P. K. Joy, - Macmillan India Ltd., Delhi 2017. R3. “Project Management in Manufacturing and High Technology Operations” Adedeji Bodunde Badiru, - John Wiley and Sons 2008. R4. “Course in PERT & CPM” R.C.Gupta, - DhanpatRai and Sons, New Delhi R5. “Fundamentals of PERT/ CPM and Project Management” S.K. Bhattacharjee; - Khanna Publishers, New Delhi 2004. | |
Evaluation Pattern CIA1-10Marks CIA2-25Marks CIA3-10Marks ESE-50Marks Attendance-5Marks | |
ME636OE5 - BASIC AEROSPACE ENGINEERING (2018 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Description: This first part of the course “Basic Aeronautical Engineering” presents an overall picture of the aeronautics domain. This overview involves a number of different perspectives on the aerospace domain, and shows some basic principles of the most important concepts for flight. Then the basic aerodynamics are covered, followed by flight mechanics Course Objectives: · To familiarize with the basics of aerodynamics · To familiarize with the basics of aircraft structures, systems & instruments · To give exposure to the power plants cased in Aircraft |
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Course Outcome |
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Upon completion of this course, the students will be able to CO1: To explain flow regimes (viscous/non-viscous; compressible/incompressible aerodynamics) and to estimate viscous and thermal effects |
Unit-1 |
Teaching Hours:9 |
Introduction to Principles of Flight
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Physical properties and structure of the atmosphere, Temperature, pressure and altituderelationships, Evolution of lift, drag and moment, different types of drag. | |
Unit-1 |
Teaching Hours:9 |
AIRCRAFT CONFIGURATION
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Brief History- airplanes and Helicopters – Components of an airplane and their functions. Different types of flightvehicles, classifications, Basic instruments for flying | |
Unit-2 |
Teaching Hours:9 |
Introduction to Aerodynamics
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Aerodynamic forces on aircraft,Basic characteristics of aerofoils, NACA nomenclature, Classification of NACA aerofoils, propagation of sound, Mach number, subsonic, transonic, supersonic, hypersonic flows. | |
Unit-2 |
Teaching Hours:9 |
Elements of Airplane Performance
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Introduction, Equation of motion, Thrust required for level unaccelerated flight, Thrust available and maximum velocity, Power required for level unaccelerated flight, Power available and maximum velocity for reciprocating engine – propeller combination and jet engine, Altitude effect of power available and power required. Rate of climb, gliding flight, Absolute and Ceiling, Time of climb, Range & Endurance for propeller driven and jet air plane. | |
Unit-3 |
Teaching Hours:9 |
Aircraft Structures
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General types of construction, Monocoque and Semi-monocoque - construction, Typical wing and fuselage Structures
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Unit-3 |
Teaching Hours:9 |
Landing Gears
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Introduction to Landing Gears, Types of Landing Gears | |
Unit-4 |
Teaching Hours:9 |
Aircraft Materials
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Metallic and non-metallic materials, Use of aluminium alloy, titanium, stainless steel and composite materials
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Unit-4 |
Teaching Hours:9 |
Systems and Instruments
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Conventional control, Powered controls, Basic instruments for flying, typical systems for control actuation | |
Unit-5 |
Teaching Hours:9 |
Jet Propulsion
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Basic ideas about piston, turboprop and jet engines – comparative merits, Propellers and Jet for thrust production. | |
Unit-5 |
Teaching Hours:9 |
Rocket Propulsion
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Principle of operation of rocket, types of rocket and typical applications, Exploration into space, Use of multistage rockets | |
Text Books And Reference Books: 1. Kermode,A.C., ‘Flight without Formulae’, Pearson,2004 2. Shevell,R.S., Fundamentals of flights, Pearson education 2004 | |
Essential Reading / Recommended Reading 1. Anderson.J.D., Introduction to Flight, McGraw Hill,2010 2. McKinley.J.L. and R.D. Bent, Aircraft Power Plants, McGraw Hill1993 3. Pallet.E.H.J. Aircraft Instruments & Principles, Pearson 2010 | |
Evaluation Pattern CIA1-10MARKS CIA2-25MARKS CIA3-10MARKS ATTENDANCE-5MARKS ESE-50MARKS
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BTGE 732 - ACTING COURSE (2017 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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In this course the students are introduced different aspects of the theatre such as, acting, direction, scenic design, costume, make-up. At the end of the course the learners will put up one-act plays. The course aims at the study and practice of Classical Acting. The development of individual imagination, insight, skills and disciplines in the presentation of drama to audience. |
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Course Outcome |
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* To gain an understanding of acting principles and techniques • Develop skills in the analysis and interpretation of dramatic texts for performance • Explore basic voice and movement skills to create dramatic effect on stage • Understand the basic production processes • The ability and willingness to engage in a structured play in an ensemble as an actor |
Unit-1 |
Teaching Hours:12 |
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Method of acting from ?inside out? that?s introduced in the Stanislavsky?s System
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The Keys of the “System”: Objective, Super-objective, given circumstances, emotional memory, “Magic If”, subtext, method of physical action, through line. | |||||||||||||||||||
Unit-2 |
Teaching Hours:10 |
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The opposite method from ?outside in? by Jacques Lecoq
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Energy centers, Sectors of gestures, Animals in characterization. | |||||||||||||||||||
Unit-3 |
Teaching Hours:10 |
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Adaptation of the ?system? by Lee Strasberg, Stella Adler
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Adaptation of the “system” by Lee Strasberg, Stella Adler, Sanford Meisner and putting it in their “methods”. Work with the senses. Discovering the sensory base of the work: learning to memorize and recall sensations, often called “sense memory” and /or “affective memory”; | |||||||||||||||||||
Unit-4 |
Teaching Hours:11 |
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Technical aspects
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The students are introduced to scenic design and costume. | |||||||||||||||||||
Unit-5 |
Teaching Hours:17 |
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Creating a scene
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Analyzing, rehearsing and performing a short scene from any of famous classical plays by using rehearsal steps for active analysis through physical actions | |||||||||||||||||||
Text Books And Reference Books: Stanislavsky, Constantine. An Actor prepares. New Delhi: Research Press, 2006.Print | |||||||||||||||||||
Essential Reading / Recommended Reading Stanislavsky, Constantine. An Actor prepares. New Delhi: Research Press, 2006.Print | |||||||||||||||||||
Evaluation Pattern 1. Monologue 2. Dialogue Delivery 3. Skit 4. Story Telling | |||||||||||||||||||
BTGE 734 - DIGITAL WRITING (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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· Planning the content for a website and writing it · Writing news reports, feature articles, listicles · Understanding the audience and developing audience personas · Content strategy and creating a content calendar · Executing a content calendar and writing for social media |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1 Planning the content for a website and writing it Understanding, applying, analysing, evaluating, creating 2 Writing news reports, feature articles, listicles Understanding, analysing, evaluating, creating 3 Understanding the audience and developing audience personas Analysing, evaluating, creating 4 Content strategy and creating a content calendar Analysing, evaluating, creating 5 Executing a content calendar and writing for social media Remembering, understanding, applying, analysing, evaluating, creating |
Unit-1 |
Teaching Hours:6 |
UNIT I Introduction
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Introduction to Digital Writing: What is online writing? Narrative structure for online and digital stories, Writing for university publications, Writing for specific platforms (eg various social and new media platforms), The Progress from Blogging to Freelancing, Copyright, Ownership, and authorship, Theorizing online spaces | |
Unit-2 |
Teaching Hours:6 |
UNIT II Digital Writing Approaches
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Approaches to Digital Writing: Approach to digital storytelling, Interactive narratives, Sourcing information, Exploring Trans media stories, data visualization, online identities and the self, alternate realities. | |
Unit-3 |
Teaching Hours:6 |
UNIT III Writing Techniques
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Writing Techniques: Online news writing, Headlines, Sentences, Links, Tables and Info graphics, Meaningful Linking, Effective Illustrations, Content Strategy, Message, Media, Style and Tone, Purposes, Personas and Scenarios | |
Unit-4 |
Teaching Hours:6 |
UNIT IV Publishing and Editing
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Editing: What is Deep Editing, Organization of your write up, refining your writing through the stages of editing, Content editing as first step of Deep Editing, Structure Editing, Relooking at your piece: Style Edit, Final Stage of Editing: Presentation Editing Understanding Publishing, What is the difference between academic and op-ed publishing?, The role of insights in the publication process, Choosing the right platform for publishing, Marking your social presence | |
Unit-5 |
Teaching Hours:6 |
UNIT V Publications
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Domains related to publishing: Understanding the role of Keywords, Examination of websites – Topics covered, Regions covered, Author Guidelines, ORCID &DOI, Predatory Publications: The Cons, What are the common features of Predatory Publications? Open and Close Access Journals | |
Text Books And Reference Books: Carroll, Brian. Writing and Editing for Digital Media, 1st edition. ISBN 978-0-415-99201-5. Routledge. | |
Essential Reading / Recommended Reading Peter Clark, Roy. How to Write Short: Word Craft for Fast Times. Little Brown and Company. ISBN 0316204323. Online Journalism: Reporting, Writing and Editing for New Media, Richard Craig. Broadcast News Handbook: Writing, Reporting & Producing in a Converging Media World 2007, Third Edition, C.A. Tuggle, Forrest Carr and Suzanne Huffman Writing New Media Theory and Applications for Expanding the Teaching of Composition; Anne Frances Wysocki, Johndan Johnson-Eilola, Cynthia L. Selfe, & Geoffrey Sirc Publication Year: 2004. | |
Evaluation Pattern CIA 50 Marks ESE 50 Marks | |
BTGE 737 - PROFESSIONAL PSYCHOLOGY (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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To provide students with frameworks from psychology of human development To enhance their personal and professional development. To examine their behavioural and relational styles, develop skills of managing work life interface issues and become more sensitive cultural differences and diversity in groups. |
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Course Outcome |
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By the end of the course the learner will be able to: 1. Upon successful completion of the course and through participation in the class room lectures and activities 2. Students will have greater awareness of their thinking styles, relational styles and behavioural styles of functioning. 3. Students will develop interpersonal awareness and skills especially in the context of diversity and difference. 4. Students will develop preparatory skills towards effective work – life balance. 5. Students will develop overall understanding of the psychosocial skills required in professional world |
Unit-1 |
Teaching Hours:6 |
Human Development and Growth- Introduction,
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Psychosocial development (Erickson). Development of Cognition (Piaget), Moral Development (Kohlberg), Faith Development (Fowler) | |
Unit-2 |
Teaching Hours:6 |
Self-Awareness
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Thinking Styles (Cognitive distortions), Interpersonal relationship styles (adult attachment theories), personality styles (Jung type indicator or Myers Briggs Type Indicator), Coping styles (Emotion focused and Problem focused) | |
Unit-3 |
Teaching Hours:5 |
Social Networks and self
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Family Genogram (Bowen), Community, Genogram (Ivey) | |
Unit-4 |
Teaching Hours:5 |
Work Life Balance
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Work life balance and Emotion – decision link in Work life balance, Connecting life goals with work goals, | |
Unit-5 |
Teaching Hours:8 |
Professional development and Diversity
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Coaching skills, Mentoring skills, Effective feedback, Developing a competency framework, Self Determination Theory (Ryan and Deci), Burke –Litwin change model. Diversity and challenge Cross cultural communication, respecting diversity, Intercultural awareness, Multicultural awareness. | |
Text Books And Reference Books: Mohan Krishnan, R. HR Strategy to optimize human capital: an integrated approach through talent management. Huselid, M.A., Becker, B.E., & Beatty, R.W. (2005). The Workforce Scorecard: Managing Human Capital to execute strategy. Harvard Business School Press. | |
Essential Reading / Recommended Reading [1] Nelson Goud and Abe Arkoff, Psychology and Personal Growth, Edition, Allyn and Bacon, 2005. [2] Richard Nelson Jones, Human Relationship skills: Coaching and self coaching, 4th edition, Routledge, 2006 | |
Evaluation Pattern CIA – 1 for 20 marks reduced to 10 CIA – 2 for 50 marks reduced to 25 CIA – 3 for 20 marks reduced to 10 Attendance is for 5 marks End Semester Exam for 100 marks reduced to 50 Total marks = 100 | |
BTGE 744 - DIGITAL MARKETING (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: Developing a successful digital marketing strategy and implementation is both an art and science. It involves in-depth knowledge of dynamics of new media (Social Media, Mobile) and utilizing the right resources and marketing skills to design and launch successful customer engagement campaigns. Digital Marketing course has been designed to help students to understand both functional and management roles required to plan and execute effective Digital Marketing campaigns. The course also helps students gain an insight how to plan and implement Digital Marketing initiatives. Course Objectives:This course attempts to help students to understand both functional and management roles required to plan and execute effective Digital Marketing campaigns. |
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Course Outcome |
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On having completed this course student should be able to: CLO 1: Outline the basics of digital marketing and digital marketing plan CLO 2: Utilize the concepts of display ads and e-mail marketing in digital campaigns CLO 3: Choose the appropriate social media for achieving the objectives of the campaign CLO 4: Appraise the SEO and SEM efforts of any business organization CLO 5: Explain Mobile Marketing and Web Analytics pertaining to any business CLO 6: Design and run a digital marketing campaign for a client |
Unit-1 |
Teaching Hours:5 |
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Introduction to Digital Marketing
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Digital Marketing: Origin of digital marketing; Traditional Vs Digital Marketing; Internet Users in India; Grehan’s 4Ps of digital marketing; The consumer decision journey; The P-O-E-M Framework; The digital landscape; Digital Marketing Plan. Ethical Challenges: Frauds on the Web, Data and Identity Theft, Issue of Privacy. Information Technology Act, 2000. | |||||||
Unit-2 |
Teaching Hours:6 |
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Display Advertising and e-mail Marketing
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Concept of Display Advertising; Types of display Ads; Buying Models; Display Plan; Targeting – Contextual targeting- Placement Targeting-Remarketing- Interest categories- Geographic Language Tagging; What makes a good Ad? Programmatic digital advertising; Analytics tools – viewability, on target reach, Ad fraud, Brand Health. e-mail Marketing – Building a List- Content Strategies – e-mail newsletter – Automating e-mail marketing- Analytics | |||||||
Unit-3 |
Teaching Hours:9 |
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Social Media Marketing
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How to build a successful social media strategy? Facebook Marketing- Facebook for Business-Anatomy of an Ad campaign – Adverts - Facebook Insights Linkedin Marketing – Linkedin Strategy- Sales lead generation – Content Strategy – Linkedin Analytics – Targeting – Ad Campaign,Twitter Marketing – Getting started with Twitter – Building a content strategy – Twitter Ads – Twitter Analytics Instagram Marketing – Objectives – Content Strategy – Style guidelines – Hashtags – Videos- Sponsored Ads – Apps – Generate leads | |||||||
Unit-4 |
Teaching Hours:6 |
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Search Engine Advertising and Search Engine Optimisation
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Why pay for Search Advertising? Understanding Ad Placement; Understanding Ad ranks; Creating the first Ad campaign; Enhancing the Ad campaigns; Performance reports. Google Adsense. Search Engine Optimisation – How search engine works? SEO Phases; On page Optimisation; Off-page Optimisation; Social Media Reach; Maintenance | |||||||
Unit-5 |
Teaching Hours:4 |
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Mobile Marketing and Web Analytics
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Mobile Advertising – Mobile Marketing toolkit – Mobile Marketing Features – Mobile Analytics Web Analytics – Key Metrics – Making web analytics actionable – Types of tracking codes
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Text Books And Reference Books: Seema Gupta. (2018). Digital Marketing (1st Ed). Tata Mc Graw Hill | |||||||
Essential Reading / Recommended Reading Evans ( Social Media Marketing: An Hour a Day (
3) Teixeira, J. (2010). Your Google Game Plan for Success: Increasing Your Web Presence with Google AdWords, Analytics and Website Optimizer. | |||||||
Evaluation Pattern
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BTGE 745 - DATA ANALYTICS THROUGH SPSS (2017 Batch) | |||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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.As an enormous amount of data gets generated, the need to extract useful insights is a must for a business enterprise. Data Analytics has a key role in improving any business.This course provides an overview of approaches facilitating data analytics on huge datasets.As the word suggests Data Analytics refers to the techniques to analyze data to enhance productivity and business gain. Data is extracted from various sources and is cleaned and categorized to analyze different behavioral patterns. 1)COURSE OBJECTIVES a)To make students understand the concepts used to analyse business data b)To enable students to analyse data using softwares like SPSS
c)To enable students to understand how Analytics helps decision makers
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Course Outcome |
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At the end of the course, students will be able to Co 01: Understand the concepts involved for analyzing Business data Co 02: Understand how to use software like SPSS to analyse data CO 03: Appreciate the use of Data Analytics for business decision making |
Unit-1 |
Teaching Hours:6 |
Introduction to Data Analytics
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Introduction to Data Analytics, Steps involved in data Analysis, Types of Data, Data cleaning
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Unit-2 |
Teaching Hours:6 |
Introspection to SPSS
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Understanding SPSS, Creating SPSS files, importing Data,SPSS Interface, Modules, Importing Data From excel, Creating a SPSS File | |
Unit-3 |
Teaching Hours:6 |
Data Types and manipulation
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Entering Differing types of Data, Defining Variables, Data Manipulation in SPSS, Recoding Variables, Splitting File, Merging Files, Weight Cases,Saving File and Building Charts | |
Unit-4 |
Teaching Hours:6 |
Hypothesis Testing and Univariate Analysis
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T Test, correlation and Regression, 1-Way and 2-Way ANOVA, Univariate Analysis,Chi Square Test | |
Unit-5 |
Teaching Hours:6 |
Multivariate analysis
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2-Way ANOVA, Multiple Regression, Logistic Regression,2-Way ANOVA, Multiple Regression, Logistic Regression, Multiple Discriminant, Analysis, Decision Tree | |
Text Books And Reference Books: 1)TEXT BOOKS 1.Darren George|Paul Mallery, “SPSS for Windows Step by Step”, Pearson, Tenth Edition, 2012.
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Essential Reading / Recommended Reading 2)REFERENCE BOOKS 1.Andy field, “Discovering Statistics Using SPSS”, SAGE Publications, Second Edition, 2006.
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Evaluation Pattern CIA-1 MID SEM (CIA-2) CIA -3 | |
BTGE735 - DIGITAL MEDIA (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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This course provides students the insight on search engine optimization, social media and digital marketing techniques that helps them understand how each of the social media platforms works and how to strategize for any type of objectives from clients. Students will discover the potential of digital media space and will have hands on experience with different digital platforms. |
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Course Outcome |
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Unit-1 |
Teaching Hours:10 |
Concepts
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Website Hosting/Design/Development/Content, Website Optimization, Fundamentals of SEO, Voice Search Optimization, Local SEO, Advanced/Technical SEO, SEO Audit, Competition Analysis, App Store Optimization, Concepts of Digital Marketing | |
Unit-2 |
Teaching Hours:10 |
Marketing
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Marketing on platforms – Facebook/Twitter/LinkedIn/Instagram/YouTube, Quora, Basics of Video Editing, Inbound Marketing, Email Marketing, Digital Marketing Planning and Strategy, Marketing Automations and Tools | |
Unit-3 |
Teaching Hours:10 |
Growth Hacking
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Ethical vs. Unethical, Funnels, KPI’s, Viral Coefficient, Cohorts, Segments, Multivariate Testing, Lifetime Value of a Customer, Customer Acquisition Cost, Analytics Types, Tools, Project | |
Text Books And Reference Books: Phillip J. Windley, "Digital Identity" O'Reilly Media, 2005 | |
Essential Reading / Recommended Reading Dan Rayburn, Michael Hoch, "The Business of Streaming and Digital Media", Focal Press, 2005 | |
Evaluation Pattern
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BTGE736 - INTELLECTUAL PROPERTY RIGHTS (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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The course consists of five units. Theories behind the protection of intellectual property and its role in promoting innovations for the progress of the society is the focus of first unit. Second unit deals with protection of inventions through patent regime in India touching upon the process of obtaining international patents. The central feature of getting patent is to establish new invention through evidence. This is done through maintaining experimental/lab records and other necessary documents. The process of creating and maintain documentary evidence is dealt in Unit 3. Computers have become an integral part of human life. Till 1980, computer related inventions were not given much importance and lying low but today they have assumed huge significance in our economy. Computer related inventions and their protection which requires special treatment under legal regimes are discussed in Unit 4. The last module deals with innovations in e-commerce environment. |
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Course Outcome |
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Unit-1 |
Teaching Hours:6 |
Philosophy of intellectual property
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Intellectual Property & Intellectual Assists – Significance of IP for Engineers and Scientists – Types of IP – Legal framework for Protection of IP – Strategies for IP protection and role of Engineers and Scientists | |
Unit-2 |
Teaching Hours:6 |
Patenting Inventions
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Meaning of Invention – Product and Process Patents – True inventor – Applications for Patent – Procedures for obtaining Patent – Award of Patent – rights of patentee – grounds for invalidation – Legal remedies – International patents | |
Unit-3 |
Teaching Hours:6 |
Inventive Activities
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Research Records in the patent process – Inventorship - Internet patent document searching and interactions with an information specialist - Interactions with a patent agent or attorney - Ancillary patent activities - Technology transfer, patent licensing and related strategies | |
Unit-4 |
Teaching Hours:6 |
Patents and software
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Business Method Patents – Data protection – Administrative methods – Digital Rights Management (DRM) – Database and Database Management systems - Billing and payment – Graphical User Interface (GUI) – Simulations – E-learning – Medical informatics – Mathematical models | |
Unit-5 |
Teaching Hours:6 |
Innovations in e-commerce
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IP issues in e-commerce - Protection of websites – website hosting agreements – Copyright issues – Patentability of online business models – Jurisdiction – Digital signatures – Evidentiary value of Electronic signature certificates – Role of Certifying Authorities – Protection of Semiconductor ICs | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern CIA 1: 10 M | |
BTGE738 - CORPORATE SOCIAL RESPONSIBILITY (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course will familiarize the students with the concept ofcorporate social responsibility. The evolution of CSR has far reaching consequences on the development sector in India. The collaboration of companies and NGOs with the community has initiated a new paradigm of change in the country. The students will have an overview of the theories and the frameworks developed in the area of CSR. The paper will discuss a few prominent case studies of CSR.
Course Objectives
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Course Outcome |
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The student will understand the different dimensions of the concept of CSR. They will understand the theoretical framework of CSR and the legal guidelines developed to undertake CSR. |
Unit-1 |
Teaching Hours:7 |
Corporate social responsibility
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Defining CSR. Aim and Objectives, Components of CSR, Key drivers, History and Evolution of CSR in the Indian and international context, CSR policies and Governance, Laws and Regulations. Competencies of CSR Professionals. | |
Unit-2 |
Teaching Hours:7 |
Stakeholder Engagement
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Stakeholder engagement, Interaction in a Multi-Stakeholder Context: CSR role on internal environment: Employees, Human Resource Management - labour security and human rights, Health and Safety.CSR role on External environment: 1) Customers: Consumer rights and movements affecting CSR; (2) Community: Community involvement, (3) Shareholders (4) Suppliers. | |
Unit-3 |
Teaching Hours:6 |
CSR towards Environment and Biodiversity
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Environment: Need for Environmental assessments. Governments’ response to CSR. Role of Biodiversity, Climate change and Environment in business. Environmental compliance. | |
Unit-4 |
Teaching Hours:5 |
Sustainability models
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Benefits of CSR to Business. Factors hindering CSR activities in companies | |
Unit-5 |
Teaching Hours:5 |
Theories of CSR
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Theories of CSR: A.B Carroll, Wood, and stakeholders Theories. The triple bottom line approach. Stakeholder engagement, Standards and Codes – SA 8000, the Global Compact, GRI, etc as well as international standards including ISO 26000. | |
Text Books And Reference Books: § Agarwal, S. (2008). Corporate social responsibility in India. Los Angeles: Response. § Visser, W. (2007). The A to Z of corporate social responsibility a complete reference guide to concepts, codes and organisations. Chichester, England: John Wiley & Sons.
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Essential Reading / Recommended Reading
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Evaluation Pattern CIA I=10 CIA II =25 CIA III-10 Attendance - 05 | |
BTGE739 - CREATIVITY AND INNOVATION (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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1. To equip students with skill and aptitude for creativity and innovation through 2. Analysizing Problems: To stimulate curiosity in students to identify the areas of gaps and opportunities and solutions that can be provided 3. Creating Ideas: To stimulate creativity in students to come up with ideas for the areas of gaps and opportunities To understand the creative process: Smart storming 4. Engineering Solutions: To understand Proof of Concept, Minimum Viable Proposition, and the Rapid Iteration Process |
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Course Outcome |
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At the end of the course 1. Students will have developed and aptitude for creative thinking and problem solving in the areas that drive their interest. 2. Students will have appreciated the benefits of team work and collaborative thinking 3. Students will understand the three keys aspects of the creative process viz. ACES 4. Students will have carried out hands on projects to understand the various principles and elements of creativity and innovation 5. Students groups might have emerged with projects which may be patentable, design and copyright protected. |
Unit-1 |
Teaching Hours:9 |
Introduction: Creativity and Creative Thinking
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Activity based introduction to creativity, Creativity and Innovation - Activity based introduction to InnovationA journey through major breakthrough innovations around the world, Team work in Creativity: Theory and Practice, Communicating Ideas Effectively | |
Unit-2 |
Teaching Hours:9 |
The Creative Process Part I (Analyzing Problems)
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Analyzing Problems (Smart Storming) Theory and practice - Rethinking, Thinking, Imagination, Observing, Abstracting, Recognizing Patterns Forming Patterns | |
Unit-3 |
Teaching Hours:9 |
The Creative Process Part II (Creating Ideas)
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Creative Thinking Techniques and Methods Body Thinking Empathizing (Design Thinking) Dimensional Thinking Evolution and Evaluation of Ideas through design Thinking | |
Unit-4 |
Teaching Hours:9 |
The Creative Process Part III (Engineering Solutions)
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Proof of Concept, Minimum Viable Proposition, Rapid Iteration Process | |
Unit-5 |
Teaching Hours:9 |
Innovation and IPR
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Patents, Designs, Copyrights, Geographical Indications, Trademarks, Trade Secret | |
Text Books And Reference Books: Activity based teaching learning. So no additional references. | |
Essential Reading / Recommended Reading Activity based teaching learning. So no additional references. | |
Evaluation Pattern This course will have an overall CIA which will be evaluated out of 100 marks and converted out of 100 marks. Students will have a portfolio prepared as per the classes that they have undergone which will be evaluated vis-à-vis the learning aspects associated at the appropriate course level. | |
BTGE741 - GERMAN (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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To learn a new language, viz.German. To understand the culture and differences of the new environment and be prepared to adapt.
Sensitize the students to the environment of a foreign country. To enable the students adapt to a new environment and culture.
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Course Outcome |
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Can understand and use familiar, everyday expressions and very simple sentences, which relate to the satisfying of concrete needs. |
Unit-1 |
Teaching Hours:6 |
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INTRODUCTION, SELF AND OTHERS
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Introduction: Greeting and saying goodbye, Introducing yourself and others, Talking about yourself and others. Numbers, telephone numbers and mail-addresses, the alphabet (spelling), countries and languages. Question words, sentences, verbs and personal pronouns.
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Unit-2 |
Teaching Hours:6 |
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AROUND YOU :FRIENDS, COLLEAGUES
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Hobbies, meeting friends, Weekdays, months and seasons, work and working times Articles, verbs, Yes/ no questions, Plurals, The verbs : to have and to be.
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Unit-3 |
Teaching Hours:6 |
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PLACES TO VISIT
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Places in the city, asking for directions, Means of transport. Orientation in a city. Imperative sentences.
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Unit-4 |
Teaching Hours:6 |
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FOOD
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Shopping for food, conversation during food shopping, ordering food and drinks, general greetings during eating out. Word position in sentence, accusative case.
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Unit-5 |
Teaching Hours:6 |
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TIME WITH FRIENDS
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Telling time and organizing meetings with family and friends. Making plans, Birthday invitations, in Restaurants. Finding information in a text, event tips in the radio, leisure activities, brochures. Possessive articles, Modal verbs ,simple Past tense (to have and to be)
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Text Books And Reference Books: Netzwerk – Deutsch als Fremdsprache A1, Publisher- Langenscheidt
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Essential Reading / Recommended Reading Netzwerk – Deutsch als Fremdsprache A1, Publisher- Langenscheidt
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Evaluation Pattern
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BTGE749 - PAINTING AND SKETCHING (2017 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Objective Global elective for a beginner level artist course, will focus on establishing the necessary basics for the students to start art practice. The course is ideal for students who are keen on developing their skills. The course looks into basic aspects of different media and strengthens the basic understanding necessary for a beginner level artist. |
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Course Outcome |
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Curriculum aims to help students: |
Unit-1 |
Teaching Hours:6 |
Module 1: Pencil/Pen - 3class/6hours
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Unit-1 |
Teaching Hours:6 |
Module 1: Pencil/Pen - 3class/6hours Materials
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Unit-2 |
Teaching Hours:6 |
Module 2: Charcoal and Pastels - 3class/6hours
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Unit-2 |
Teaching Hours:6 |
Module 2: Charcoal and Pastels - 3class/6hours Materials
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Unit-3 |
Teaching Hours:6 |
Module 3: Watercolour - 3class/6hours
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Unit-3 |
Teaching Hours:6 |
Module 3: Watercolour - 3class/6hours
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Unit-4 |
Teaching Hours:2 |
Module 4: Creative Thinking & Studio Practice 1class/2hour
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Unit-5 |
Teaching Hours:6 |
Module 5: Acrylic 3class/6 hour
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Week 11 Introduction to Acrylic media, Conceptualising of subject, Basic-techniques
Week 12-13 Process of working on canvas & completion (final Project) | |
Unit-5 |
Teaching Hours:6 |
Module 5: Acrylic 3class/6 hour Materials
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Unit-6 |
Teaching Hours:4 |
Exhibition & Submission 2class/4hours
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Week 14-15 Exhibition & Portfolio Submission | |
Essential Reading / Recommended Reading https://www.behance.net/galleries/illustration/sketching https://www.pinterest.com/litchick2911/sketching-references/ https://www.creativebloq.com/inspiration
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Evaluation Pattern
Consistency,abilities to understand the concept and explore.time management,precision etc. | |
BTGE750 - PHOTOGRAPHY (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Outcome |
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Unit-1 |
Teaching Hours:6 |
Introduction and Development of Films
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Introduction to the course, discussion of lenses, aperture, shutter, depth of field, loading film, Places to shoot. Functions and Usage of a camera. | |
Unit-2 |
Teaching Hours:6 |
Printing
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Role of natural light in creating expressive print, Development of Coherent Portfolio, Printing Skills. | |
Unit-3 |
Teaching Hours:6 |
Unit - III
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Role depth of field, lens choice, focal point and strong design plays. Group discussion on prints. | |
Unit-4 |
Teaching Hours:6 |
Urban Shooting and Portrait
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Angles, reflections, corners, street life. Emphasis on design and abstraction, Creation of visual relationships. | |
Unit-5 |
Teaching Hours:6 |
Final Portfolio
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Revisit of your favourite place, printing for final critique, Matting of prints. | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading 1. Craven, George M., Object and Image, An Introduction to Photography. Prentice Hall, Englewood Cliffs, New Jersey, 1990. | |
Evaluation Pattern Overall CIA - 100. ESE - 100. Note :Students are expected to publish papers in reputed journal | |
BTGE754 - FUNCTIONAL ENGLISH (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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This course aims at strengthening English proficiency amongst 7th semester students. It focuses on three key areas – 1.Spoken English 2.Written English (Workplace and Academic writing) 3.Public Speaking The course deploys BLENDED AND EXPERIENTIAL LEARNING as CAPS will use classroom teaching, hands on CIAs and E-learning modules.
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Course Outcome |
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Students will be able to develop a clear understanding principles and characteristics of communication in professional settings. They would have developed skills for grammatical accuracy, precise vocabulary, clear style and appropriate tone for formal, professional communication |
Unit-1 |
Teaching Hours:15 |
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UNIT 1: VERBAL
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· Training on Nouns, Pronouns, Homophones, Homonyms · Verbs and Gender · Training on Tenses · Active Voice, Passive Voice and Sentence Formation · Direct and Indirect Speech · Adjectives and Adverbs · Barriers of communication and effective solutions · Workplace English · Pleasantries and networking · Cross-cultural understanding | |||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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UNIT- 2 WRITTEN Workplace English
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· Professional Writing • Analytical • Instructional including writing MOMs • Project Planning • Creative writing • Blogging · Event management proposal meeting · Professional communication – Email Etiquette, Cover letters, Resume | |||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Academic Writing
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· Application in technical fields and written communication · Project writing, essays and theories · Paper presentation skills and creative writing Final project writing | |||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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UNIT-3 PUBLIC SPEAKING
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· Training on Presentation Skills · Body Language and Accent Training · Voice projection · Group Discussion Do’s and Don’ts · Getting individual feedback · Training on appropriate grooming code and body language in a professional workplace and delivery of apt elevator pitch. | |||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
1. CIA 1- CLASS presentation The students need to convince their teachers to give a presentation to their own class or a different class. The teachers will be given choices of CAPS modules from which a module/topic will be chosen and will be delivered to the class.
2. CIA 2 - Content creation The students will be divided into groups of 5 each. They will develop content for a current, idea based topic/ concept eg: TED Ex type topic with handout and PPT with maximum 30 slides.
3. CIA -3 - (The students will be evaluated on one of the following) Stress Interview/ Panel Discussion/ Group Discussion Blog Exploration - The blog exploration could be a whole class exercise or students could work in small groups. | |||||||||||||||||||||||
CS731 - ARTIFICIAL INTELLIGENCE (2017 Batch) | |||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Outcome |
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Sl. NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Identify the fundamental knowledge of Intelligent agents, searching strategies and syntax and semantics of first order logic. L3 2. Discover the complex problem solving agents, constraint satisfaction problems and optimal decisions in game. L4 3. Inspect the knowledge engineering in first order logic, knowledge representation and chaining mechanisms, knowledge in learning and different forms of learning. L4 4. Determine and build planning strategies, Communication and analysis of grammar and its interpretation. L5 5. Asses a system that utilize artificial intelligence to a complicated task with limited resources in the form of time and computations. L5 |
Unit-1 |
Teaching Hours:12 |
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INTRODUCTION
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Unit-2 |
Teaching Hours:12 |
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SEARCHING TECHNIQUES
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Unit-3 |
Teaching Hours:12 |
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KNOWLEDGE REPRESENTATION
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Unit-4 |
Teaching Hours:12 |
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LEARNING
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Unit-5 |
Teaching Hours:12 |
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APPLICATIONS
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Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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CS732 - CLOUD COMPUTING (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Specifically, the course has the following objectives. Students will learn: •The fundamental ideas behind Cloud Computing, the evolution of the paradigm, its applicability; benefits, as well as current and future challenges; •The basic ideas and principles in data center design and management; •About cloud storage technologies and relevant distributed file systems; •The variety of programming models and develops working experience in one of them. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT) LEVEL 1. Illustrate the core concepts of the cloud computing paradigm. L2 2. Interpret the functioning of data-centers, its trade-offs in power, efficiency and cost. L2 3. Summarize the concept of virtualization and its role in providing services under cloud computing model. L2 4. Utilize the services of cloud storage systems. L3 5 Examine the various cloud application from various vendors. L4 |
Text Books And Reference Books: | |||||||||||||||||||
Essential Reading / Recommended Reading | |||||||||||||||||||
Evaluation Pattern
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CS733P - MOBILE APPLICATION DEVELOPMENT (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:75 |
No of Lecture Hours/Week:5 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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· To know the concepts corresponding to the Mobile applications. · To be in a position to develop applications for all the mobile manufacturers. · To learn and know the various architectures for different mobile systems. · To design mobile systems that meets the need for the current world requirements. · Know the components and structure of mobile application development frameworks for Android and windows OS based mobiles. · Understand how to work with various mobile application development frameworks. · Learn the basic and important design concepts and issues of development of mobile applications. · Understand the capabilities and limitations of mobile devices.
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Explain the concepts in mobile applications and its development. L2 2. Build interface for mobile applications and web applications L6 3. Construct mobile application for Windows platform L6 4 Design mobile application for Android platform.(L6) L6 5 Develop mobile application for IOS platform. L3 |
Unit-1 |
Teaching Hours:15 |
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INTRODUCTION
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Introduction to mobile applications – cost of development - Market and business drivers for mobile applications – Publishing and delivery of mobile applications – Requirements gathering and validation for mobile applications. Third party Frameworks. - Mobile Content- Mobile Applications. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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BASIC DESIGN
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Introduction to Web Services– Web service language Format –Creating a Web service using Microsoft stack – Using the Linux Apache MySQL PHP (LAMP) Stack-Debugging Web Services. Mobile User Interface Design.-Mobile Web Apps Using HTML5.Designing applications with multimedia and web access capabilities – Integration with GPS and social media networking applications – Accessing applications hosted in a cloud computing environment – Design patterns for mobile applications. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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TECHNOLOGY I WINDOWS 7
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Introduction- architecture of windows 7- Establishing the development environment-Tools- Hardware- Visual studio and windows phone SDK- Windows 7 Project-Building the Derby App in Windows 7-Offline Storage-Notifications-GPS-Accelerometer-Web Services. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:33 |
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TECHNOLOGY II : ANDROID
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Introduction – Establishing the development environment – Android architecture – Activities and views – Interacting with UI – Persisting data using SQLite – Packaging and deployment – Interaction with server side applications – Using Google Maps, GPS and Wifi – Integration with social media applications. | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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TECHNOLOGY III - IOS
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Introduction to Objective C – iOS features – UI implementation – Touch frameworks – Data persistence using Core Data and SQLite – Location aware applications using Core Location and Map Kit – Integrating calendar and address book with social media application – Using Wifi – CASE STUDY- iPhone marketplace and mobile application development. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Jeff McWherter and Scott Gowell, "Professional Mobile Application Development", Wrox, 2012,Wiley Publications. 2. Charlie Collins, Michael Galpin and Matthias Kappler, “Android in Practice”, DreamTech, 2012. 3. Dawn Griffiths, David Griffiths “Head First Android Development: A Brain-Friendly Guide 1st Edition” O'Reilly Media; 1 edition (July 3, 2015) 4. James Dovey and Ash Furrow, “Beginning Objective C”, Apress, 2013 | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. David Mark, Jack Nutting, Jeff LaMarche and Frederic Olsson, “Beginning iOS 6 Development: Exploring the iOS SDK”, Apress, 2013. | |||||||||||||||||||||||||||||||
Evaluation Pattern Assessment of each paper: CIA 1: 10 Marks CIA 2 (MSE): 10 Marks CIA3: 10 Marks Laboratory: 35 Marks Attendance :05 Marks End Semester Examination: 30 Marks Total : 100 Marks
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CS735E01 - NATURAL LANGUAGE PROCESSING (2017 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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· Teach student about various Linguistics Rules, representation and understanding of Natural Language Processing · Make students to understand the concepts of morphology, syntax, semantics and pragmatics of the language and that they are able to give the appropriate examples that will illustrate the above-mentioned concepts. · Enable students to recognize the significance of language model for Natural Language Processing
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Demonstrate the representation of language with the levels of language analysis L2 2. Illustrate the process of top down parsing and bottom up parsing of strings and morphological analysis of lexicons L2 3. Experiment the techniques for handling questions and ambiguity resolution with analyzing movement phenomenon in language L3 4 Examine the semantic interpretation of words and linkage between and syntax and semantics L4 5 Explains language models required to verify its significance with recent trends in natural language L2 |
Unit-1 |
Teaching Hours:9 |
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Introduction to Natural Language Processing
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Introduction to Natural Language Processing, Different Levels of language analysis, Representation and understanding, Linguistic background. | |||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Grammars and parsing
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Grammars and parsing, Top down and Bottom up parsers, Transition Network Grammars, Feature systems and augmented grammars, Morphological analysis and the lexicon, Parsing with features, Augmented Transition Networks. | |||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Grammars for natural language
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Grammars for natural language, Movement phenomenon in language, Handling questions in context free grammars, Hold mechanisms in ATNs, Gap threading, Human Preference in parsing, Shift reduce parsers, Deterministic parsers, Statistical methods for Ambiguity resolution. | |||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Semantic Interpretation
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Semantic Interpretation, word senses and ambiguity, Basic logical form language, Encoding ambiguity in logical from, Thematic roles, Linking syntax and semantics, Recent trends in NLP. | |||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Language Model
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Language Model: the Milton Model , THE META MODEL, Vision for the Future’, Strategies, NLP Change Techniques, Principle based NLP, Reframing, and Chunking Patterns, Recent Trends, Research Issues, Case studies. | |||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: TEXT BOOKS 1. Steven Bird, Ewan Klein, Edward Loper, “Natural Language Processing with Python”, O'Reilly Media; 1 edition (July 10, 2009) 2. Pushpak Bhattacharyya, “Machine Translation”, Chapman and Hall/CRC; 1 edition (January 22, 2015) 3. Matthew A Russell , “Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More”, O'Reilly Media; Second Edition edition (October 20, 2013) | |||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading REFERENCE BOOKS 1. James Allen, Natural Language Understanding, Second Edition, 2003, Pearson Education. 2. Daniel Jurafsky & James H.Martin, “ Speech and Language Processing”, Pearson Education (Singapore) Pte. Ltd., 2002. | |||||||||||||||||||||||||||||||||||||
Evaluation Pattern Components of CIA Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) CIA I: Assignment 1 and 2 : 10 marks CIA II: Mid Semester Examination : 25 marks CIA III: Mini Project and Presentation : 10marks Attendance : 5marks Total : 50marks End Semester Examination (ESE) : 50% (50 marks out of 100 marks)
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CS735E02 - RESEARCH METHODOLOGY (2017 Batch) | |||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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Course Outcome |
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CO1: Explain the research methodology and defining the research problem CO2: Experiment thestatistical techniques such as scaling, skewness, correlation, and association techniques to process the data CO3: Examine the algorithm to find the order of growth of best, worst and average cases. CO4: Experiment thepopulation using sampling fundamentals, variance and covariance methods CO5: Evaluate the research results and presenting the research report |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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An Introduction Meaning of Research, Objectives of Research , Motivation in Research , Types of Research , Research approaches ,Research Method versus Methodology ,Research and Scientific Method, Importance of Knowing How Research is Done , Research Process, Criteria of Good Research, problem Encountered by Researchers in India. Defining the Research Problem: Definition of Research Problem, Selecting the Problem, Necessity of Defining the Problem Technique Involved in Defining a Problem | |||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Measurement and Scaling Technique
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Measurement in Research, Measurement Scales, Sources of Error in Measurement, Tests of Sound Measurement, Technique of Developing Measurement Tools, Scaling, Meaning of Scaling, Scale Classification Bases, Important Scaling Techniques, Scale Construction Techniques. | |||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Analysis of Algorithms
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Analysis of algorithm: The role of algorithm in computing –Insertion sort–Analyzing and designing algorithms | |||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Sampling Fundamentals
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Need for Sampling, Some Fundamental Definitions, Central Limit Theorem, Sampling Theorem, Sandler’s A-test, Concept of Standard Error, Estimation, Estimating the Population Mean, Estimating the Population Proportion, Sample size and its Determination, Determination of Sample Size through the Approach, Based on Precision Rate and Confidence Level, Determination of Sample Size through the Approach, Based on Bayesian Statistics. | |||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Interpretation and Report Writing
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Meaning Of Interpretation, Technique of Interpretation: Precaution in Interpretation, Significance of Report Writing, Different Steps in Writing Report, Layout of the Research Report, Types of Reports, Oral Presentation, Mechanics of Writing a Research Report, Precautions for Writing a Research Report, Case study . | |||||||||||||||||||
Text Books And Reference Books: 1. Kothari C.R., “Research Methodology – Methods and Techniques”, New Age International , New Delhi, (reprint 2011) 2. Montgomery, Douglas C., “Design and Analysis of Experiments”, Willey India, 2007 3. Montgomery, Douglas C. & Runger, George C. “Applied Statistics & Probability for Engineers”, Wiley India , 2010 | |||||||||||||||||||
Essential Reading / Recommended Reading 1. Krishnaswamy, K.N. Sivkumar , Appa Iyer and Mathiranjan M., “Management Research Methodology: Integration of Principles, Method and Techniques”, Pearson Education, New Delhi, 2006. 2. Charlie Catlett, Wolfgang Gentzsch, Lucio Grandinetti, Gerhard Joubert, and José Luis Vasquez-Poletti, “Cloud computing and Big data”, Published/Distributed: Amsterdam : Washington, DC : IOS Press, [2013] | |||||||||||||||||||
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |||||||||||||||||||
CS736E01 - GRAPH THEORY (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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· Understand basic notions of Graph Theory |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Explain the basic terminologies of graph theory. L2 2. Examine the fundamentals of planar graphs, circuits and network flows. L4 3. Solve the problems on chromatic numbers, matrix and Euler graphs. L4 4. Inspect the algorithms and set of fundamental circuits for the graphs L4 5. Determine the shortest path algorithm and planarity testing L4 |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Graphs – Introduction – Isomorphism – Sub graphs – Walks, Paths, Circuits – Connectedness – Components – Euler Graphs – Hamiltonian Paths and Circuits – Trees – Properties of trees – Distance and Centers in Tree – Rooted and Binary Trees. | |||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Spanning trees
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Spanning trees – Fundamental Circuits –Spanning Trees in a Weighted Graph – Cut Sets – Properties of Cut Set – All Cut Sets – Fundamental Circuits and Cut Sets – Connectivity and Separability – Network flows – 1-Isomorphism – 2-Isomorphism – Combinational and Geometric Graphs – Planer Graphs – Different Representation of a Planer Graph. | |||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Incidence matrix
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Incidence matrix – Submatrices – Circuit Matrix – Path Matrix – Adjacency Matrix – Chromatic Number – Chromatic partitioning – Chromatic polynomial - Matching - Covering – Four Color Problem – Directed Graphs – Types of Directed Graphs – Digraphs and Binary Relations – Directed Paths and Connectedness – Euler Graphs – Adjacency Matrix of a Digraph. | |||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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Algorithms-1
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Algorithms: Connectedness and Components – Spanning tree – Finding all Spanning Trees of a Graph –Set of Fundamental Circuits – Cut Vertices and Separability – Directed Circuits. | |||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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Algorithms-2
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Algorithms: Shortest Path Algorithm – DFS – Planarity Testing – Isomorphism-Case studies. | |||||||||||||||||||
Text Books And Reference Books: · Narsingh Deo, “Graph Theory: With Application to Engineering and Computer Science”, PHI, 2009. | |||||||||||||||||||
Essential Reading / Recommended Reading · R.J. Wilson, “Introduction to Graph Theory”, Fourth Edition, Pearson Education, 2003. | |||||||||||||||||||
Evaluation Pattern
Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks)Components of the CIACIA I : Subject Assignments / Online Tests/Quiz : 10 marksCIA II : Mid Semester Examination (Theory) : 25 marksCIAIII: Quiz/Seminar/Case Studies/Project/InnovativeAssignments/presentations/publications : 10 marksAttendance : 05 marksTotal : 50 marks
End Semester Examination(ESE) : 50% (50 marks out of 100 marks) | |||||||||||||||||||
CS736E03 - WIRELESS NETWORKS (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To learn the basics of wireless communication, cellular communication, GSM and CDMA technologies and emerging wireless technologies in wireless networks. |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Outline the basic concepts and terminologies in wireless communication systems L2 2. Interpret modulation techniques in wireless communication L4 3 Make use of the principles in cellular communications and multiple access techniques to solve real-world problems L3 4 Examine the principles of GSM, GPRS and DECT Standards in real time environments L4 5 Explain the emerging wireless technologies with respect to different parameters L2 |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION TO WIRELESS NETWORKS
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Elements of a wireless communication system – signal and noise - the radio – frequency spectrum –Analog modulation schemes -Amplitude modulation – frequency and phase modulation – sampling – pulse code modulation – delta modulation – data compression. | |||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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DIGITAL MODULATION AND RADIO PROPAGATION
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Digital communication- sampling –pulse code modulation – delta modulation - Frequency shift keying – Phase shift keying – Multiplexing and Multiple access – spread spectrum systems - radio propagation. | |||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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PRINCIPLES OF CELLULAR COMMUNICATION AND MULTIPLE ACCESS TECHNIQUES
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Cellular terminology - Cell structure and Cluster – Frequency reuse concept – Cluster size and system capacity – method of locating co channel cells – frequency reuse distance – frequency division multiple access – time division multiple access – space division multiple access – code division multiple access. | |||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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GSM AND CDMA DIGITAL CELLULAR STANDARDS
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GSM network architecture –GSM signaling protocol architecture – Identifiers in GSM – GSM channels –GSM handoff procedures – Edge technology – wireless local loop – DECT system – GPRS. | |||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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EMERGING WIRELESS TECHNOLOGIES
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IEEE 802.11 system architecture – mobile ad hoc networks – Mobile IP and mobility management – Mobile TCP - wireless sensor networks – RFID technology – Blue tooth – Wi –Fi standards – Wimax standards. – Femtocell network – Push -to –talk technology for SMS. Case Study. | |||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Roy Blake, “Wireless communication technology” CENGAGE Learning, Sixth Indian reprint 2010. (Chapter 1, 2, 3, 4, 7, 14) 2. Singal T.L. , “Wireless communication” Tata Mc Graw Hill Education. Private limited, 2011. (Chapter 4, 8, 11, 13, 14) 3. Dharma Prakash Agrawal, Qing –An Zeng, “Introduction to wireless and Mobile systems” CENGAGE Learning, first edition 2012.(Chapter 16). | |||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Upena Dalal, “Wireless communication” Oxford University press, first edition 2009. 2. Kaveh Pahlavan, Prashant Krishnamurthy, “Wireless Networks” PHI. Learning Private Limited. | |||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern Continuous Internal Assessment (CIA ) for theory papers : 50% (50 marks out of 100 marks) End Semester Examination (ESE): 50 % (50 marks out of 100 marks)
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CS771 - INTERNSHIP (2017 Batch) | |||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:50 |
Credits:2 |
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Course Objectives/Course Description |
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To create an opportunity to the students to experience the industry working process. |
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Course Outcome |
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Gaining knowledge about working infrastucture and latest market trends. |
Unit-1 |
Teaching Hours:30 |
INTRODUCTION
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All students should complete internship either in Industry/MOOC/Research labs before 7th semester. This component carries 2 credits. § Continuous Internal Assessment:2 credits o Presentation assessed by Panel Members Pursuing internships is beneficial because they provide the opportunity to: ▪ Get an inside view of an industry and organization/company ▪ Gain valuable skills and knowledge ▪ Make professional connections and enhance student's network ▪ Get experience in a field to allow the student to make a career transition Regulations 1.The student shall undergo an Internship for 60 days starting from the end of 2nd semester examination and completing it during the initial period of 7th semester. Due to the pademic Situations department has allowed students to complete the requirement of internship by completing a MOOC approved by the internal guide. 2.The department shall nominate a faculty as a mentor for a group of students to prepare and monitor the progress of the students 3. The students shall report the progress of the internship/MOOC to the mentor/guide at regular intervals and may seek his/her advise. 4. The Internship shall be completed before the mid semester of 7th semester. 5. The students are permitted to carry out the internship outside India with the following conditions, the entire expenses are to be borne by the student and the University will not give any financial assistance. 6. Students can also undergo internships arranged by the department during vacation. 7. After completion of Internship, students shall submit a report to the department with the approval of both internal and external guides/mentors. 8. There will be an assessment for the internship for 2 credits, in the form of report assessment by the guide/mentor and a presentation on the internship given to department constituted panel. | |
Text Books And Reference Books: Relevant to the internship domain | |
Essential Reading / Recommended Reading Recommended based on the area of the internship domain. | |
Evaluation Pattern Maximum Marks = 50(Only credit will be displayed in the score card) Passing marks 40% min Do not have ESE and completely evaluated through continuous assessment only Continuous Internal Assessment is based upon
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CS772 - SERVICE LEARNING (2017 Batch) | |
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
Max Marks:50 |
Credits:2 |
Course Objectives/Course Description |
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This course attempts to utilize the academic capability and skill of the B.Tech students to develop and suggest practicable solutions to enduring societal problems. Thus the course inculcates among the students the ability of utilizing acquired knowledge to explore strategies to overcome practical problems, while helping them to become a socially aware global citizen. |
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Course Outcome |
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Unit-1 |
Teaching Hours:2 |
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INTRODUCTION
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Conceptualization, Security essentials
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Unit-2 |
Teaching Hours:1 |
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Security Essentials
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Service attacks, Spoofing, Phishing | |||||||||||||||||||
Unit-3 |
Teaching Hours:1 |
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Security Threats
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Threats , security, counter measure, payment systems, Penetration Testing | |||||||||||||||||||
Unit-4 |
Teaching Hours:20 |
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Community Projects
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Perform a survey to identify the community and their needs. This will start in the first week immediately after the introduction class. Define problem statement ,upon completion of survey. Design of methodology, frequent interaction with the community. | |||||||||||||||||||
Unit-5 |
Teaching Hours:6 |
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Practical implementations
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Testing and validation of the project, Practical implimentation of the proposed project will be evaluated by community as well as the academic panel. | |||||||||||||||||||
Text Books And Reference Books: 1. Jason Andress, “The Basics of Information Security: Understanding the Fundamentals of InfoSec in Theory and Practice”, Elsevier Science & Technology, ISBN: 978-1-59749-653-7. Jun 10, 2011 2. Michael Bazzell, “Personal Digital Security: Protecting Yourself from Online Crime Paperback – Import”, 31 Jul 2013
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Essential Reading / Recommended Reading
1. PatrickEngebretson ,”The Basics of Hacking and Penetration Testing: Ethical Hacking and Penetration Testing Made Easy”. Elsevier Science & Technology, ISBN: 978-1-59749-655-1, Jun 10, 2011,
2. Bruce Schneier , “Secrets and Lies: Digital Security in a Networked World”, January 2004,.
3. Arthur Mikel., “Digital Security: Protect Your Online Products With Digital Protection Which Are Cheap And Easy To Implement “ Paperback – 2 Jul 2012,
Note : Apart from the above mentioned books, reading meterials based on the selected project domain are mandatory. | |||||||||||||||||||
Evaluation Pattern Content and creativity - 10 marks Weekly progress - 20 marks Team work - 5 marks Evaluation from the participating community - 10 marks Report Submission - 5 marks Delivery/Demo - 50 marks | |||||||||||||||||||
IT735E01 - INFORMATION SECURITY (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To understand the basics of Information Security, legal, ethical and professional issues, aspects of risk management, aware of various standards in this area and technological aspects of Information Security |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. CO1: Explain the potential sources of vulnerability within an information system. L2 2. CO2: Illustrate the need of security and outline threats, attacks, legal issues. L2 3. CO3: Experiment with various risks, vulnerable and possible controls. L3 4. CO4: Understand the policies, standards and practices of information security. L2 5. CO5: Examine the IDS, scanning, tools and access control devices. L4 |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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History, what is Information Security, Critical Characteristics of Information, NSTISSC Security Model, Components of an Information System, Securing the Components, Balancing Security and Access, The SDLC, The Security SDLC. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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SECURITY INVESTIGATION
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Need for Security, Business Needs, Threats, Attacks, Legal, Ethical and Professional Issues | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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SECURITY ANALYSIS
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Risk Management: Identifying and Assessing Risk, Assessing and Controlling Risk | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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LOGICAL DESIGN
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Blueprint for Security, Information Security Policy, Standards and Practices, ISO 17799/BS 7799, NIST Models, VISA International Security Model, Design of Security Architecture, Planning for Continuity. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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PHYSICAL DESIGN
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Security Technology, IDS, Scanning and Analysis Tools, Cryptography, Access Control Devices, Physical Security, Security and Personnel, Case Study. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. T1. Michael E Whitman and Herbert J Mattord, ―Principles of Information Security, Cengage Learning India 2011. 2. T2. Micki Krause, Harold F. Tipton, ―Handbook of Information Security Management, Vol 6 CRC Press LLC, 2012. 3. T3. Stuart Mc Clure, Joel Scrambray, George Kurtz, ―Hacking Exposed, 7th Edition Tata McGraw-Hill, 2012. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading R1. Matt Bishop, ―Computer Security Art and Science‖, Pearson/PHI, 2009 | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern
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IT736E01 - SIMULATION AND MODELING (2017 Batch) | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To understand the concept of simulation, modeling, testing randomness, various case studies like inventory, traffic flow networks, practice on simulation tools and impart knowledge on building simulation systems. |
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Course Outcome |
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1 Understand the concepts which include the technique of simulation, major application areas, concept of a system, environment, continuous and discrete systems models L2 2 Study of probability concepts in simulation including discrete and continuous, probability functions, numerical evaluation of continuous probability functions etc. L3 3 Developing Simulation experiments and sampling concepts. L3 4 Analyze discrete system and Continues system simulation and study on different simulation languages. L4 5 Analyze the role of simulation studies in practical systems. L4 |
Unit-1 |
Teaching Hours:9 |
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INTRODUCTION
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Systems, modeling, general systems theory, Concept of simulation, Simulation as a decision making tool, types of simulation. | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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RANDOM NUMBERS
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Pseudo random numbers, methods of generating random variables, discrete and continuous distributions, testing of random numbers. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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DESIGN OF SIMULATION EXPERIMENTS
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Problem formulation, data collection and reduction, time flow mechanism, key variables, logic flow chart, starting condition, run size, experimental design consideration, output analysis and interpretation validation. | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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SIMULATION LANGUAGES:
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Comparison and selection of simulation languages, study of anyone simulation language. | |||||||||||||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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CASE STUDIES:
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Development of simulation models using simulation language studied for systems like queuing systems, Production systems, Inventory systems, maintenance and replacement systems and Investment analysis. | |||||||||||||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Geoffrey Gordon, “System Simulation”, 2nd Edition, Prentice Hall, India, 2011 2. NarsinghDeo, “System Simulation with Digital Computer, “Prentice Hall, India, 2009. | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading 1. Jerry Banks and John S.Carson, Barry L. Nelson, David M.Nicol, “Discrete Event System Simulation”, 3rd Edition, Prentice Hall, India, 2002. 2. Shannon, R.E. “Systems simulation: The art and science”, Prentice Hall, 1975. 3. Thomas J. Schriber, “Simulation using GPSS”, John Wiley, 1991. | |||||||||||||||||||||||||||||||||||||||||
Evaluation Pattern 1) CIA COMPONENTS – EVALUATION RUBRICS CIA I Component 1: Assignment Description/Technical presentation · An Assignment will be given in order to ensure that students have understood the topics and following up well with the curriculum.
o Max. Marks : 10 o Tentative Date : 20 – 27 June2020. o Venue : Class room/Online
Learning Outcome(s) (i) Understand the concepts of Systems, Systems Environment (ii) Illustration of Discrete and Continuous Systems (iii) Describing various the Mathematical models (iv) Simulation as a Decision making tool
Evaluation Rubrics
Component 2: Closed Book/Online Mode A closed book test to be conducted in order to ensure that students are following up well with the curriculum Marks: 10 Tentative date: 05/07/2020 Venue: Classroom/Google meet/ Online Learning objectives: 1. To make them practice with Continues and Discrete Systems and Role of Models in Simulation Studies and problems of 1 &2 units. 2. To equip them well for further examinations Evaluation Rubrics:
CIA III Component 1: 1. Technical – Individual Presentations & Group Presentations on Simulation studies Assignment Description: Presentations to be conducted in order to ensure that students are following up well with the curriculum and able to apply the simulation principles in real time environment. Marks: 10 Tentative date: 02/09/2020 Venue: Classroom Learning objectives: 1. To make them practice with Design of Models in Simulation Studies and problems of 3, 4 & 5 units. 2. To equip them well for further examinations Evaluation Rubrics:
Component 2: Closed Book
A closed book test to be conducted in order to ensure that students are following up well with the curriculum Marks: 10 Tentative date: 20/10/2020 Venue: Classroom Learning objectives: 1. To make them practice with Design and Modeling with simulation languages of Simulation Studies and to solve problems of 3 & 4 units. 2. To equip them well for further examinations Evaluation Rubrics:
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IT736E03 - ADVANCED DATABASES (2017 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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To understand the basics of DBMS and Object-Oriented databases. To interpret XML, Database Schemas and validate using DTD To perform query and transaction processing for optimization. To incorporate concurrency control and Recovery mechanisms for a Database. To analyse various Database security issues. |
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Course Outcome |
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Sl NO REVISED BLOOM’S TAXONOMY (RBT)LEVEL Interpret ER models for relational database design L2 Experiment with Object Databases and XML for advanced databases. L3 Identify query optimization parameters and appropriate scheduling for improved transactions. L3 Compare the working principles of concurrency and recovery methods for a database. L3 Examine solutions to problems pertaining to security aspects for a database. L4 |
Unit-1 |
Teaching Hours:9 |
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DATABASE MANAGEMENT
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Relational Data Model – SQL - Database Design - Entity-Relationship Model – Relational Normalization – EER- Relational Database Design Using ER-to-Relational Mapping -Mapping EER Model Constructs to Relations. | |||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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ADVANCED DATABASES
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Object Databases – Object database Extensions to SQL-ODMG and ODL –Object Database Conceptual Design – XML Hierarchical model– XML Documents DTD and XML Schema – Distributed Data bases – Types and Architectures- data fragmentation, Replication and Allocation Techniques. | |||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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QUERY AND TRANSACTION PROCESSING
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Query Processing Basics – Heuristic Optimization –Selectivity, Cost, Size Estimation – Transaction and System Concepts-Properties of Transactions – Architecture – Characterizing Schedules Based on Recoverability – Characterizing Schedules Based on Serializability – Transaction Support in SQL. | |||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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CONCURRENCY CONTROL AND RECOVERY
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Concurrency Control – Two-Phase Locking Techniques for Concurrency Control - Concurrency Control Based on Timestamp Ordering - Multiversion Concurrency Control Techniques - Granularity of Data Items and Multiple Granularity Locking- Recovery Concepts- Recovery Techniques Based on Immediate Update- The ARIES Recovery Algorithm - Recovery in Multidatabase Systems | |||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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DATABASE SECURITY
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Introduction to Database Security Issues- Discretionary Access Control Based on Granting and Revoking Privileges- Mandatory Access Control and Role-Based Access Control for Multilevel Security - SQL Injection- Statistical Database Security- Flow Control- Encryption and Public Key Infrastructures- Privacy Issues and Preservation- Challenges of Database Security- Oracle Label-Based Security | |||||||||||||||||||
Text Books And Reference Books: 1. R. Elmasri and S.B. Navathe, “Fundamentals of Database Systems”, 6th Edition, Addison Wesley, 2014 2. Abraham Silberschatz, Henry. F. Korth, S.Sudharsan, “Database System Concepts”, 6th Edition., Tata McGraw Hill, 2014 | |||||||||||||||||||
Essential Reading / Recommended Reading 1. Raghu Ramakrishnan & Johannes Gehrke, “Database Management Systems”, 3rd Edition, TMH, 2003 2. Philip M. Lewis, Arthur Bernstein, Michael Kifer, “Databases and Transaction Processing: An Application-Oriented Approach”, Addison-Wesley, 2002. | |||||||||||||||||||
Evaluation Pattern Assessment of each paper Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) End Semester Examination (ESE) : 50% (50 marks out of 100 marks) Components of the CIA CIA I: Closed Book Test and Quiz : 10 marks CIA II: Mid Semester Examination (Theory) : 25 marks CIA III: Closed Book Test and Quiz : 10 marks Attendance : 05 marks | |||||||||||||||||||
IT736E04 - NETWORK ADMINISTRATION (2017 Batch) | |||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:3 |
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Course Objectives/Course Description |
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In this syllabus the basics of network planning and Red Hat installation and configuration is taught. Configuring a database server, creating a VNC server, monitoring performance, providing Web services, exploring SELinux security basics, and exploring desktops |
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Course Outcome |
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Sl NO DESCRIPTION REVISED BLOOM’S TAXONOMY (RBT)LEVEL 1. Illustrate the basic principles of system administration and role of System administrator. L2 2. Apply the concept of network services to configure a database server and a VNC server. L3 3. Explain the different types network services with their configuration and optimization. L2 4. Identify the responsibilities of system administrator with respect to data storage. L3 5. Analyze the network security issues and troubleshoot them. L4 |
Unit-1 |
Teaching Hours:9 |
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Introduction
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Introduction to System Administration, The Unix Way, Essential Administrative Tools and Techniques, Startup and Shutdown. System and Network Administration Defined, Duties of the System Administrator, Planning the Network, Standard Installation , Kick start Installation , Exploring the Desktops, System Startup and Shutdown , The File System Explained , Examining the System Configuration Files. | |||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:9 |
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Network Services
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Network Services, Managing the X Window System , Configuring Printers , TCP/IP Networking , Managing user and groups, Security, managing network services, The Network File System, The Network Information System ,Connecting to Microsoft and Novell Networks, Configuring a Database Server, Creating a VNC Server, Providing Additional Network Services, Optimizing Network Services. | |||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:9 |
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Internet Services
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Internet Services, Configuring BIND: The Domain Name System, Configuring Mail Services, Configuring FTP Services, Configuring a Web Server, Providing Web Services, Optimizing Internet Services. | |||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:9 |
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System Administration
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System Administration, Upgrading and Customizing the Kernel, Configuring the System at the Command Line , Administering Users and Groups , Installing and Upgrading Software Packages, Backing Up and Restoring the File System , Performance Monitoring | |||||||||||||||||||||||||||||||
Unit-5 |
Teaching Hours:9 |
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System Security and Problem Solving
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System Security and Problem Solving, Exploring SELinux Security, Implementing Network Security, Troubleshooting and Problem Solving, Case studies. | |||||||||||||||||||||||||||||||
Text Books And Reference Books: 1. Thomas A. Limoncelli, ”The Practice of System and Network Administration”, Addison-Wesley Professional, second edition ,Published Feb 2012. 2. Terry Collings, Kurt Wall, “Red Hat Linux Networking and System Administration”, 3rd Edition 3. Leen Frisch, “Essential System Administration”, 3rd Edition , O'Reilly Media, 2002. | |||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
1. Evi Nemeth, Garth Snyder, Trent R. Hein, Ben Whaley, “Unix and Linux System Administration Handbook” , Prentice Hall
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Evaluation Pattern Assessment of each paper · Continuous Internal Assessment (CIA) for Theory papers: 50% (50 marks out of 100 marks) · End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of CIA CIA 1 Assignment and MCQ - 10 marks CIA 2 Mid Semester Examination - 25 marks CIA 3 MOOC Course and Closed book test - 10 marks Attendance - 5 marks
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BTCY01 - CYBER SECURITY (2017 Batch) | |||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:50 |
Credits:2 |
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Course Objectives/Course Description |
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This course is aimed at providing a comprehensive overview of the different facets of Cyber Security. In addition, the course will detail into specifics of Cyber Security with Cyber Laws both in Global and Indian Legal environments. |
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Course Outcome |
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Providing knowledge about different Cyber Crimes, Threats and Laws .Creating awareness about risk management and protection from the cyber threats. |
Unit-1 |
Teaching Hours:6 |
Security Fundamentals
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As Architecture Authentication Authorization Accountability, Social Media, Social Networking and Cyber Security. Cyber Laws, IT Act 2000-IT Act 2008-Laws for Cyber-Security, Comprehensive National Cyber-Security Initiative CNCI – Legalities. | |
Unit-2 |
Teaching Hours:12 |
Cyber Attack and Cyber Services
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Computer Virus – Computer Worms – Trojan horse. Vulnerabilities - Phishing - Online Attacks – Pharming - Phoarging – Cyber Attacks - Cyber Threats - Zombie- stuxnet - Denial of Service Vulnerabilities - Server Hardening-TCP/IP attack-SYN Flood. | |
Unit-3 |
Teaching Hours:12 |
Cyber Security Management
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Risk Management and Assessment - Risk Management Process - Threat Determination Process -Risk Assessment - Risk Management Lifecycle. Security Policy Management - Security Policies - Coverage Matrix, Business Continuity Planning – Disaster Types - Disaster Recovery Plan - Business Continuity Planning Process. | |
Unit-4 |
Teaching Hours:12 |
Vulnerability
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Vulnerability - Assessment and Tools: Vulnerability Testing - Penetration Testing Black box- white box., Architectural Integration: Security Zones - Devicesviz Routers, Firewalls, DMZ. Configuration Management - Certification and Accreditation for Cyber-Security. | |
Unit-5 |
Teaching Hours:12 |
Authentication and Cryptography
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Authentication and Cryptography: Authentication - Cryptosystems - Certificate Services Securing Communications: Securing Services - Transport – Wireless - Steganography and NTFS Data Streams., Intrusion Detection and Prevention Systems: Intrusion - Defense in Depth - IDS/IPS -IDS/IPS Weakness and Forensic Analysis, Cyber Evolution: Cyber Organization - Cyber Future | |
Text Books And Reference Books: REFERENCES 1. Matt Bishop, Introduction to Computer Security, Pearson, 6th impression, ISBN: 978-81-7758-425-7. 2. Thomas R, Justin Peltier, John, Information Security Fundamentals, Auerbach Publications. 3. AtulKahate, Cryptography and Network Security 2nd Edition, Tata McGrawHill. | |
Essential Reading / Recommended Reading Nina Godbole, SunitBelapure, Cyber Security, Wiley India 1st Edition 2011. 5. Jennifer L. Bayuk and Jason Healey and Paul Rohmeyer and Marcus Sachs, Cyber Security Policy Guidebook, Wiley; 1 edition , 2012, ISBN-10: 1118027809 6. Dan Shoemaker and Wm. Arthur Conklin, Cybersecurity: The Essential Body Of Knowledge, Delmar Cengage Learning; 1 edition (May 17, 2011) ,ISBN-10: 1435481690
7. Stallings, “Cryptography & Network Security - Principles & Practice”, Prentice Hall, 3rd Edition 2002. | |
Evaluation Pattern Evaluation based on CIAI, CIAII and on ESE ESE will be based multiple choice questions | |
CS831E01 - QUANTUM COMPUTING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Course Outcome |
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CO1: Outline basic concepts and practices of Quantum Computing.(L3) CO2: Identify the key components in the field of Quantum Computing.(L3) CO3: Demonstrate the components of Quantum Computers with respect to Quantum principles.(L3) CO4: Categorize the Quantum Information with respect to Quantum Computing process.(L4) CO5: Understand the error handling process in Quantum Computing.(L4) |
Unit-1 |
Teaching Hours:9 |
FUNDAMENTAL CONCEPTS
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Global Perspectives, Quantum Bits, Quantum Computation, Quantum Algorithms, Quantum Information, Postulates of Quantum Mechanisms. | |
Unit-2 |
Teaching Hours:9 |
QUANTUM COMPUTATION
|
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Quantum Circuits – Quantum algorithms, Single Orbit operations, Control Operations, Measurement, Universal Quantum Gates, Simulation of Quantum Systems, Quantum Fourier transform, Phase estimation, Applications, Quantum search algorithms – Quantum counting – Speeding up the solution of NP – complete problems – Quantum Search for an unstructured database. | |
Unit-3 |
Teaching Hours:9 |
QUANTUM COMPUTERS
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Guiding Principles, Conditions for Quantum Computation, Harmonic Oscillator Quantum Computer, Optical Photon Quantum Computer – Optical cavity Quantum electrodynamics, Ion traps, Nuclear Magnetic resonance. | |
Unit-4 |
Teaching Hours:9 |
QUANTUM INFORMATIONS
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Quantum noise and Quantum Operations – Classical Noise and Markov Processes, Quantum Operations, Examples of Quantum noise and Quantum Operations – Applications of Quantum operations, Limitations of the Quantum operations formalism, Distance Measures for Quantum information. | |
Unit-5 |
Teaching Hours:9 |
QUANTUM ERROR CORRECTION
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Introduction, Shor code, Theory of Quantum Error –Correction, Constructing Quantum Codes, Stabilizer codes, Fault – Tolerant Quantum Computation, Entropy and information – Shannon Entropy, Basic properties of Entropy, Von Neumann, Strong Sub Additivity, Data Compression, Entanglement as a physical resource. Case study. | |
Text Books And Reference Books: 1. Michael A. Nielsen. & Issac L. Chiang, “Quantum Computation and Quantum Information”, Cambridge University Press, 2007. | |
Essential Reading / Recommended Reading 1. Mika Hiravensalo, “Quantum computing” II edition, ACM computing classification, Springer- 2004 | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS831E02 - GRID COMPUTING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To provide in-depth knowledge in Computing techniques with grid as the platform. · To know the concepts pertaining to the grid Computing environment. · To understand various techniques to enhance the performance and scalability of Grids. · To nurture the students to design and applications and infrastructures for Grid. · To understand Grid technology for the present market scenarios. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
INTRODUCTION TO GRID COMPUTING
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Introduction to Grid Computing: Grid Computing Concept, History of Distributed Computing Computational Grid Applications, Grid Computing Infrastructure Development, Grid Computing Software Interface Job Submission: Introduction, Globus Job Submission, Transferring Files. | |
Unit-2 |
Teaching Hours:9 |
SCHEDULING AND SECURITY
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Schedulers: Scheduler Features, Scheduler Examples, Grid Computing Meta-+Schedulers, Distributed Resource Management Application (DRMAA). Security Concepts: Introduction, Symmetric Key Cryptography, Asymmetric Key Cryptography, (Public Key Cryptography), Public Key Infrastructure, Systems/Protocols Using Security Mechanisms. Grid Security: Introduction, Grid Security Infrastructure (GSI), Delegation, Higher-Level Authorization Tools. | |
Unit-3 |
Teaching Hours:9 |
GRID INFRASTRUCTURE
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System Infrastructure I Web Services: Service-Oriented Architecture, Web Services and Web Service Implementation. System Infrastructure II: Grid Computing Services: Grid Computing and Standardization Bodies, Interacting Grid Computing Components, Open Grid Services Architecture (OGSA), WSRF. User-Friendly Interfaces: Introduction Grid Computing Workflow Editors, Grid Portals. | |
Unit-4 |
Teaching Hours:9 |
APPLICATIONS IN GRID COMPUTING
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Grid-Enabling Applications: Introduction, Parameter Sweep, Using an Existing Program on Multiple Grid Computers, Writing an Application Specifically for a Grid, Using Multiple Grid Computers to Solve a Single Problem. | |
Unit-5 |
Teaching Hours:9 |
CASE STUDIES
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Globus: Overview of Globus Toolkit 4, Installation of Globus, GT4 Configuration, Main Components and programming Model, Using Globus. gLite: Introduction, Internal Workings of gLite, Logging and Bookkeeping (LB), Security Mechanism Using gLite. Resource management using Gridway and Gridbus. Scheduling using Condor, SGE, PBS, LSF Grid scheduling with QoS. | |
Text Books And Reference Books: 1. Barry Wilkinson, "Grid Computing Techniques and Applications", CRC Press, 2010. 2. Frederic Magoules, Jie Pan, Kiat-An Tan, Abhinit Kumar, “Introduction to Grid Computing”, CRC Press, 2009. | |
Essential Reading / Recommended Reading 1. Vladimir Silva, "Grid Computing for Developers ", Dreamtech Press, 2006. 2. Ian Foster, Carl Kesselman. "The Grid 2- Blueprint for a new computing Infrastructure", Elsevier Series, 2004. 3. Fran Berman, Geoffrey Fox. Anthony J.G Hey, "Grid Computing: Making the Global Infrastructure a Reality", Wiley, 2003. 4. Joshey Joseph, Craig Fellenstein, "Grid computing", IBM Press, 2004. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS831E03 - MOBILE COMPUTING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
At the end of the course, the student should understand to provide basics for various techniques in Mobile Communications and Mobile Content services. To learn the basics of wireless voice and data communications technologies. To build working knowledge on various telephone and satellite networks. To study the working principles of wireless LAN and its standards. To build knowledge on various mobile computing algorithms. To build skills in working with wireless application protocols to develop mobile content applications. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
WIRELESS COMMUNICATION FUNDAMENTALS
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Introduction – Wireless transmission – Frequencies for radio transmission – Signals – Antennas – Signal Propagation – Multiplexing – Modulations – Spread spectrum – MAC – SDMA – FDMA – TDMA – CDMA – Cellular Wireless Networks. | |
Unit-2 |
Teaching Hours:9 |
TELECOMMUNICATION NETWORKS
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|
Telecommunication systems – GSM – GPRS – DECT – UMTS – IMT-2000 – Satellite Networks - Basics – Parameters and Configurations – Capacity Allocation – FAMA and DAMA – Broadcast Systems – DAB - DVB. | |
Unit-3 |
Teaching Hours:9 |
WIRLESS LAN
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Wireless LAN – IEEE 802.11 - Architecture – services – MAC – Physical layer – IEEE 802.11a -802.11b standards – HIPERLAN – Blue Tooth. | |
Unit-4 |
Teaching Hours:9 |
MOBILE NETWORK LAYER
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Mobile IP – Dynamic Host Configuration Protocol - Routing – DSDV – DSR – Alternative Metrics. | |
Unit-5 |
Teaching Hours:9 |
TRANSPORT AND APPLICATION LAYERS
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Traditional TCP – Classical TCP improvements – WAP, Case Study. | |
Text Books And Reference Books: 1. Jochen Schiller, ―Mobile Communications‖, PHI/Pearson Education, Second Edition, Reprint edition 2012. 2. William Stallings, ―Wireless Communications and Networks‖, PHI/Pearson Education, 2009. (Unit I Chapter – 7&10-Unit II Chap 9) | |
Essential Reading / Recommended Reading 1. Kaveh Pahlavan, Prasanth Krishnamoorthy, ―Principles of Wireless Networks‖, PHI/Pearson Education, 2003. 2. Uwe Hansmann, Lothar Merk, Martin S. Nicklons and Thomas Stober, ―Principles of Mobile Computing‖, Springer, New York, 2003. 3. Hazysztof Wesolowshi, ―Mobile Communication Systems‖, John Wiley and Sons Ltd, 2002. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS832E01 - SOFTWARE TESTING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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To give an overview of the software testing techniques. To design and understand test cases, various levels of testing and related concepts. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
INTRODUCTION
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Testing as an Engineering Activity – Role of Process in Software Quality – Testing as a Process – Basic Definitions – Software Testing Principles – The Tester‘s Role in a Software Development Organization – Origins of Defects – Defect Classes – The Defect Repository and Test Design – Defect Examples – Developer/Tester Support for Developing a Defect Repository. | |
Unit-2 |
Teaching Hours:9 |
TEST CASE DESIGN
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Introduction to Testing Design Strategies – The Smarter Tester – Test Case Design Strategies – Using Black Box Approach to Test Case Design Random Testing – Requirements based testing – positive and negative testing – Boundary Value Analysis – decision tables -Equivalence Class Partitioning state-based testing – cause effect graphing – error guessing -compatibility testing – user documentation testing – domain testing Using White–Box Approach to Test design – Test Adequacy Criteria – static testing vs. structural testing – codefunctional testing - Coverage and Control Flow Graphs – Covering Code Logic – Paths – Their Role in White–box Based Test Design – code complexity testing – Evaluating Test Adequacy Criteria. | |
Unit-3 |
Teaching Hours:9 |
LEVELS OF TESTING
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The Need for Levels of Testing – Unit Test – Unit Test Planning –Designing the Unit Tests.The Test Harness – Running the Unit tests and Recording results – Integration tests – Designing Integration Tests – Integration Test Planning – scenario testing – defect bash elimination -System Testing – types of system testing - Acceptance testing – performance testing - Regression Testing – internationalization testing – ad-hoc testing - Alpha – Beta Tests – testing OO systems – usability and accessibility testing | |
Unit-4 |
Teaching Hours:9 |
TEST MANAGEMENT
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People and organizational issues in testing – organization structures for testing teams – testing services - Test Planning – Test Plan Components – Test Plan Attachments – Locating Test Items – test management – test process - Reporting Test Results – The role of three groups in Test Planning and Policy Development – Introducing the test specialist – Skills needed by a test specialist – Building a Testing Group. | |
Unit-5 |
Teaching Hours:9 |
CONTROLLING AND MONITORING
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|
Software test automation – skills needed for automation – scope of automation – design and architecture for automation – requirements for a test tool – challenges in automation - Test metrics and measurements –project, progress and productivity metrics – Status Meetings – Reports and Control Issues – Criteria for Test Completion – SCM – Types of reviews –Developing a review program – Components of Review Plans– Reporting Review Results. – Evaluating software quality – defect prevention – testing maturity model – Case Studies. | |
Text Books And Reference Books: 1. Boris Beizer, ―Software Testing Techniques‖, Dreamtech. Second Edition, 2009 2. Srinivasan Desikan and Gopalaswamy Ramesh, ―Software Testing – Principles and Practices‖, Pearson education, 2008. | |
Essential Reading / Recommended Reading 1. Elfriede Dustin, ―Effective Software Testing‖, Pearson Education, First Edition, 2008. 2. Edward Kit, ―Software Testing in the Real World‖, Pearson Education, 2008. 3. Aditya P.Mathur, ―Foundations of Software Testing‖, Pearson Education, 2011. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS832E02 - SOFTWARE PROCESS AND PROJECT MANAGEMENT (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
|
To provide basics for various Process and Project management models, also it provide students a systematic approach to initiate, plan, execute, control and close a software project and understanding of the best practices, and techniques used in project management processes, knowledge of ISO 9000 and CMMI, and process improvement techniques. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
SOFTWARE PROCESS MATURITY
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Software maturity Framework, Principles of Software Process Change, Software Process Assessment, The Initial Process. | |
Unit-2 |
Teaching Hours:9 |
PROCESS REFERENCE MODELS
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Capability Maturity Model (CMM), CMMi, PCMM, PSP, TSP, IDEAL, Process Definition Techniques. | |
Unit-3 |
Teaching Hours:9 |
SOFTWARE PROJECT MANAGEMENT RENAISSANCE
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Conventional Software Management, Evolution of Software Economics, Improving Software Economics, The old way and the new way. | |
Unit-4 |
Teaching Hours:9 |
SOFTWARE MANAGEMENT PROCESS FRAMEWORK
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A Software management process framework: life-cycle phases, artifacts of the process, model based software architecture, work flow process, check points of the process. | |
Unit-5 |
Teaching Hours:9 |
SOFTWARE MANAGEMENT DISCIPLINES
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Software management disciplines: iterative process planning, project organization and responsibilities, Process automation. CCPDS-R Case Study and Future Software Project Management Practices Modern Project Profiles, Next-Generation software Economics, Modern Process Transitions | |
Text Books And Reference Books: 1. Watts S. Humphrey, ―Managing the Software Process‖, Pearson Education 2012. 2. Walker Royce, ―Software Project Management‖, Pearson Education 2010. | |
Essential Reading / Recommended Reading 1. Watts S. Humphrey, ―An Introduction to the Team Software Process‖, Pearson Education 2007. 2. Watts S. Humphrey, ―A Discipline to Software Engineering‖, Pearson Education 2008. 3. Pankaj Jalote, ―Software Project Management in Practice‖, Pearson Education 2010. 4. Chris Kemerer, ―Software Project Management Readings and Cases‖, 2010. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS833E02 - INTRODUCTION TO DATA SCIENCE (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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●To study the concepts of data pre-process. •To study various pattern discovery methods. •To study the basic concepts of classification techniques. •To study the basic concepts of clustering techniques. •To learn about the recent trends in Data Science
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Course Outcome |
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CO1: Demonstrate the fundamental concepts, applications and preprocessing of data science. CO2: Illustrate the concepts of association rule mining for various applications. CO3: Examine different classification algorithms with data sets. CO4: Apply and evaluate various clustering techniques and principles in mining the knowledge. CO5: Analyze the latest trends in data science. |
Unit-1 |
Teaching Hours:9 |
INTRODUCTION AND DATA PRE-PROCESSING
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Why Data Mining?, What Is Data Mining?, What Kinds of Data Can Be Mined?, What Kinds of Patterns Can Be Mined?, Which Technologies Are Used? Which Kinds of Applications Are Targeted?, Major Issues in Data Mining, Data Pre-processing: An Overview, Data Cleaning, Data Integration, Data Reduction, Data Transformation and Data Discretization | |
Unit-2 |
Teaching Hours:9 |
Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods
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Basic Concepts, Frequent Itemset Mining Methods, Which Patterns Are Interesting?—Pattern Evaluation Methods , Advanced Pattern Mining: Pattern Mining: A Road Map, Pattern Mining in Multilevel, Multidimensional Space, Constraint-Based Frequent Pattern Mining, Mining High-Dimensional Data and Colossal Patterns, Mining Compressed or Approximate Patterns | |
Unit-3 |
Teaching Hours:9 |
CLASSIFICATION: BASIC CONCEPTS
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Basic Concepts, Decision Tree Induction, Bayes Classification Methods, Rule-Based Classification, Model Evaluation and Selection, Techniques to Improve Classification Accuracy, Support Vector Machines, Lazy Learners (or Learning from Your Neighbors) | |
Unit-4 |
Teaching Hours:9 |
CLUSTER ANALYSIS: BASIC CONCEPTS AND METHODS
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Cluster Analysis, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Evaluation of Clustering, Clustering High-Dimensional Data, Clustering Graph and Network Data | |
Unit-5 |
Teaching Hours:9 |
Data Mining Trends and Research Frontiers
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Mining Complex Data Types, Other Methodologies of Data Mining, Data Mining Applications, Data Mining and Society, Data Mining Trends | |
Text Books And Reference Books: 1. J. Han, M. Kamber, “Data Mining: Concepts and Techniques”, Harcourt India / Morgan Kauffman, 2011. 2. Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining, Pearson Education,
| |
Essential Reading / Recommended Reading 1. K.P.Soman, ShyamDiwakar, V.Ajay: Insight into Data Mining – Theory and Practice, PHI, 2012 2. David Hand, Heikki Manila, PadhraicSymth, “Principles of Data Mining”, PHI 2012. 3. W.H.Inmon, “Building the Data Warehouse”, 3rd Edition, Wiley, 2011. 4. Alex Bezon, Stephen J.Smith, “Data Warehousing, Data Mining & OLAP”, MeGraw-Hill Edition, 2001 5. PaulrajPonniah, “Data Warehousing Fundamentals”, Wiley-Interscience Publication, 2003.
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Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS833E03 - SOFT COMPUTING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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The course will provide students to understand the techniques of soft computing, ideas of fuzzy sets, optimization associated with neural network learning and adaptive neuro-fuzzy inferencing systems which differ from conventional AI and computing in terms of its tolerance to imprecision and uncertainty. It also provide case studies utilizing the above and illustrate the intelligent behavior of programs based on soft computing. |
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Course Outcome |
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Unit-1 |
Teaching Hours:9 |
FUZZY SET THEORY
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Overview of clustering , classification, regression-Introduction to Neuro – Fuzzy and Soft Computing – Fuzzy Sets – Basic Definition and Terminology – Set-theoretic Operations –Member Function Formulation and Parameterization – Fuzzy Rules and Fuzzy Reasoning – Extension Principle and Fuzzy Relations – Fuzzy If-Then Rules – Fuzzy Reasoning – Fuzzy Inference Systems. | |
Unit-2 |
Teaching Hours:9 |
OPTIMIZATION
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Derivative-based Optimization – Descent Methods – The Method of Steepest Descent – Classical Newton‘s Method – Step Size Determination – Derivative-free Optimization | |
Unit-3 |
Teaching Hours:9 |
GENETIC ALGORITHM
|
|
Genetic Algorithm (GA): Biological terminology –elements of GA: encoding, types of selection, types of crossover, mutation, reinsertion–a simple genetic algorithm –Theoretical foundation: schema, fundamental theorem of GA, building block hypothesis. Simulated Annealing – Random Search – Downhill Simplex Search. | |
Unit-4 |
Teaching Hours:9 |
NEURAL NETWORKS
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Supervised Learning Neural Networks – Perceptrons - Adaline – Backpropagation Mutilayer Perceptrons – Radial Basis Function Networks – Unsupervised Learning Neural Networks – Competitive Learning Networks – Kohonen Self-Organizing Networks. | |
Unit-5 |
Teaching Hours:9 |
SOFT COMPUTING SYSTEMS
|
|
Introduction to Extreme Learning Machines- Convolutional Neural networks – Deep Neural Networks. Hybrid Systems – ANFIS. Case studies (ONE EACH)- Fuzzy systems, Genetic Algorithm, ANN | |
Text Books And Reference Books: 1. J.S.R.Jang, C.T.Sun and E.Mizutani, ―Neuro-Fuzzy and Soft Computing‖, PHI, 2004, Pearson Education 2004. 2. Kumar S Ray, ―Soft Computing and Its Applications, Volume One: A Unified Engineering Concept‖, Apple Academic Press; 1 edition (September 16, 2014) 3. Timothy J. Ross, ―Fuzzy Logic with Engineering Application‖, Wiley 2011. 4. Davis E. Goldberg, ―Genetic Algorithms: Search, Optimization and Machine Learning 5. S.Rajasekaran and G.A.V.Pai, ―Neural Networks, Fuzzy Logic and Genetic Algorithms‖, PHI, 2003. 6. R.Eberhart, P.simpson and R.Dobbins, ―Computional Intelligence PC Tools‖, AP Professional,Boston Pearson 2002. | |
Essential Reading / Recommended Reading 1. S. N. Sivanandam, S. Sumathi, S. N. Deepa, ―Introduction to Neural Networks using MATLAB 6.0‖, Tata McGraw Hill, New Delhi, 2006. 2. S. N. Sivanandam, S.N. Deepa, ―Principles of Soft Computing‖, Wiley India, 2008. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS833E04 - DIGITAL IMAGE PROCESSING (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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It provide a strong foundation in image processing concepts and technique like image enhancement, image restoration, image compression , image segmentation, representation, pattern recognition and interpretation of the application areas. |
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Course Outcome |
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CO1: Identify the fundamental concepts of image formation and image transformations. CO2: Interpret histograms and their use to enhance quality of images based on matching and specification techniques CO3: Demonstrate the use of degradation function for distorted images and compare compression techniques CO4: Evaluate Morphological processing for image representation CO5: Utilize descriptors and patterns to describe an image for Object recognition |
Unit-1 |
Teaching Hours:9 |
DIGITAL IMAGE FUNDAMENTALS
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Image formation (chapter1, chapter 2 Gonzalez), Image transforms – Fourier transforms | |
Unit-2 |
Teaching Hours:9 |
IMAGE ENHANCEMENT
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Histogram modification techniques - Image smoothening - Image Sharpening | |
Unit-3 |
Teaching Hours:9 |
IMAGE RESTORATION, COMPRESSION
|
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Introduction to Image Restoration -Compression Models -– Region based segmentation | |
Unit-4 |
Teaching Hours:9 |
MORPHOLOGY AND REPRESENTATION
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Morphology-Representation schemes | |
Unit-5 |
Teaching Hours:9 |
DESCRIPTION AND OBJECT RECOGNITION
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Boundary descriptors- Regional descriptors - Relational Descriptors Patterns and pattern classes - Structural methods-Case studies | |
Text Books And Reference Books: 1. Gonzalez.R.C & Woods. R.E., ―Digital Image Processing‖, 3rd Edition, Pearson Education, Indian edition published by Dorling Kindersely India Pvt. Ltd. Copyright © 2009, Third impression 2011. 2. Gonzalez.R.C & Woods. R.E., ―Digital Image Processing using MATLAB‖, 2nd Edition, McGraw Hill Education (India) Pvt Ltd 2011 (Asia) 3. Madan, ―An Introduction to MATLAB for Behavioral Researchers‖ , Sage Publications, 2014 | |
Essential Reading / Recommended Reading 1. Anil Jain.K, ―Fundamentals of Digital image Processing‖, Prentice Hall of India, 2011. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
CS871 - PROJECT WORK (2017 Batch) | |
Total Teaching Hours for Semester:180 |
No of Lecture Hours/Week:12 |
Max Marks:200 |
Credits:6 |
Course Objectives/Course Description |
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students were expected to develop products using differnet languages using their class works |
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Course Outcome |
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Unit-1 |
Teaching Hours:180 |
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Assessment of Project Work
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¨ Presentation assessed by Panel Members ¨ Assessed by Guide
§ End Semester Examination:100 Marks ¨ Viva Voce ¨ Demonstration ¨ Project Report
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Text Books And Reference Books: Based on the project domain the reference meterials will be suggested | |||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading Guide will give the recommendations based on their project work | |||||||||||||||||||||||||||||||||||
Evaluation Pattern
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CS872 - COMPREHENSION (2017 Batch) | |||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:4 |
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Max Marks:50 |
Credits:2 |
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Course Objectives/Course Description |
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Aim to develope the presentation skills of the students. |
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Course Outcome |
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Unit-1 |
Teaching Hours:30 |
Assessment of Comprehension
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§ Continuous Internal Assessment:50 Marks
¨ Presentation assessed by Panel Members | |
Text Books And Reference Books: Based on the topic selected the reading meterials will be recommended. | |
Essential Reading / Recommended Reading Based on the topic selected the reading meterials will be recommended. | |
Evaluation Pattern Comprehension Maximum Marks = 50
Passing marks 40% min
Do not have ESE and completely evaluated through continuous assessment only, The evaluation (minimum 2 presentations) shall be based on the Topic / report :40% Presentation: 40% Response to the questions asked during presentation : 20%.
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IT832E02 - WEB SERVICES AND SERVICE ORIENTED ARCHITECTURE (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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Students are expected to understand the meaning of service-oriented paradigm and the aspects affecting the efficient utilization of it. Students achieve understanding of SOA for sustainable service development. Students are able to design and implement service-oriented applications. |
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Course Outcome |
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CO1: Demonstrate the applicability of SOA Concepts and the goals of the REST Architectural Style CO2: Apply requirements towards the creation of a REST web service , Design Principles and Constraints. CO3: Analyze Service Modeling, Service Contract in SOA and Service Oriented Desgin With REST. CO4: Develop RESTful services as part of service-oriented solutions in conjunction with service-oriented architecture (SOA). CO5: Design solutions for web services that follow the REST architectural style. |
Unit-1 |
Teaching Hours:9 |
UNIT I INTRODUCTION TO SOA - TERMINOLOGY, CONCEPTS AND GOALS
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Service Terminology - Service Terminology Context - Basic Terminology and Concepts - Further Reading - Case Study Example - REST Constraints - Goals of the REST Architectural Style | |
Unit-2 |
Teaching Hours:9 |
SERVICE CONTRACTS AND SERVICE-ORIENTATION WITH REST
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Uniform Contract Elements - REST Service Capabilities and REST Service Contracts - REST Service Contracts vs. Non-REST Service Contracts - The Role of Hypermedia - REST Service Contracts and Late Binding - ―SOA vs. REST" or "SOA + REST"? - Design Goals - Design Principles and Constraints | |
Unit-3 |
Teaching Hours:9 |
SOA METHODOLOGY, ANALYSIS AND SERVICE MODELING AND SERVICE-ORIENTED DESIGN WITH REST
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Service Inventory Analysis - Service-Oriented Analysis (Service Modeling) - Service-Oriented Design (Service Contract) - Service Logic Design - Service Discovery - Service Versioning and Retirement - Uniform Contract Modeling and REST Service Inventory Modeling - REST Service Modeling - Uniform Contract Design Considerations - REST Service Contract Design - Complex Method Design | |
Unit-4 |
Teaching Hours:9 |
FUNDAMENTAL AND ADVANCED SERVICE COMPOSITION WITH REST WITH CASE STUDY
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Service Composition Terminology - Service Composition Design Influences - Composition Hierarchies and Layers - REST Service Composition Design Considerations - A Step-by-Step Service Activity - Service Compositions and Stateless - Cross-Service Transactions with REST - Event-Driven Interactions with REST - Service Composition with Dynamic Binding and Logic Deferral - Service Composition Across Service Inventories - Revisiting the Confer Student Award Process - Application Submission and Task Service Invocation - Confer Student Award Service Composition Instance - Review of Pending Applications and Task Service Invocation | |
Unit-5 |
Teaching Hours:9 |
DESIGN PATTERNS, SERVICE VERSIONING WITH REST AND UNIFORM CONTRACT PROFILES
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REST-Inspired SOA Design Patterns - Other Relevant SOA Design Patterns - Versioning Basics - Version Identifiers - Uniform Contract Profile Template - REST Service Profile Considerations – Case Study Example | |
Text Books And Reference Books: 1. Thomas Erl, Benjamin Carlyle, Cesare Pautasso, Raj Balasubramanian, ―SOA with REST: Principles, Patterns & Constraints for Building Enterprise Solutions with REST‖, Prentice Hall Service Technology 2012. 2. Arnon Rotem-Gal-Oz, ―SOA Patterns, Manning‖. | |
Essential Reading / Recommended Reading 1. Java Web Services: Up and Running, 2nd Edition, A Quick, Practical, and Thorough Introduction‖, O'Reilly 2013. 2. Bill Burke, ―Restful Java with JAX-RS 2.0, Designing and Developing Distributed Web Services‖, 2nd Edition, O'Reilly 2013. 3. Developing RESTful Services with JAX-RS 2.0, WebSockets, and JSON, A complete and practical guide to building RESTful Web Services with the latest Java EE7 API‖, Packet Publishing, 2013. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks | |
IT833E04 - PROFESSIONAL ETHICS AND HUMAN VALUES (2017 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:3 |
Course Objectives/Course Description |
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· To create an awareness on Engineering Ethics and Human Values. · To instill Moral and Social Values and Loyalty · To appreciate the rights of Others |
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Course Outcome |
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CO2: Specify the Engineering Professional Ethics to identify and solve problems related to society, safety, health & legal aspects. CO3: Explain the basic perception of profession, professional ethics, various moral issues &uses of ethical theories CO4: Review case studies related to safety, security, society, health, employee rights and intellectual Property Rights. CO5: Summarize professional ethics, professional rights,and responsibilities of an engineer. |
Unit-1 |
Teaching Hours:9 |
HUMAN VALUES
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Morals, Values and Ethics – Integrity – Work Ethic – Service Learning – Civic Virtue – Respect for Others – Living Peacefully – caring – Sharing – Honesty – Courage – Valuing Time – Co-operation – Commitment – Empathy – Self-Confidence – Character – Spirituality
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Unit-2 |
Teaching Hours:9 |
ENGINEERING ETHICS
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Senses of 'Engineering Ethics' - variety of moral issued - types of inquiry - moral dilemmas - moral autonomy - Kohlberg's theory - Gilligan's theory - consensus and controversy – Models of Professional Roles - theories about right action - Self-interest - customs and religion - uses of ethical theories. | |
Unit-3 |
Teaching Hours:9 |
ENGINEERING AS SOCIAL EXPERIMENTATION
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Engineering as experimentation - engineers as responsible experimenters - codes of ethics - a balanced outlook on law - the challenger case study
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Unit-4 |
Teaching Hours:9 |
SAFETY, RESPONSIBILITIES AND RIGHTS
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Safety and risk - assessment of safety and risk - risk benefit analysis and reducing risk - the Three Mile Island and Chernobyl case studies. Collegiality and loyalty - respect for authority - collective bargaining - confidentiality - conflicts of interest - occupational crime - professional rights - employee rights - Intellectual Property Rights (IPR) - discrimination. | |
Unit-5 |
Teaching Hours:9 |
GLOBAL ISSUES
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Multinational corporations - Environmental ethics - computer ethics - weapons development - engineers as managers-consulting engineers-engineers as expert witnesses and advisors -moral leadership-sample code of Ethics like ASME, ASCE, IEEE, Institution of Engineers (India), Indian Institute of Materials Management, Institution of electronics and telecommunication engineers (IETE),India, etc. | |
Text Books And Reference Books:
1. Mike Martin and Roland Schinzinger, “Ethics in Engineering”, McGraw-Hill, New York 1996. 2. Govindarajan M, Natarajan S, Senthil Kumar V. S, “Engineering Ethics”, Prentice Hall of India, New Delhi, 2004. | |
Essential Reading / Recommended Reading
1. Charles D. Fleddermann, “Engineering Ethics”, Pearson Education / Prentice Hall, New Jersey, 2004 (Indian Repri 2. Charles E Harris, Michael S. Protchard and Michael J Rabins, “Engineering Ethics – Concepts and Cases”, Wadsworth Thompson Learning, United States, 2000 (Indian Reprint now available) 3. John R Boatright, “Ethics and the Conduct of Business”, Pearson Education, New Delhi, 2003. 4. Edmund G Seebauer and Robert L Barry, “Fundamentals of Ethics for Scientists and Engineers”, Oxford University Press, Oxford, 2001. | |
Evaluation Pattern · Continuous Internal Assessment (CIA) : 50% (50 marks out of 100 marks) ● End Semester Examination(ESE) : 50% (50 marks out of 100 marks)
Components of the CIA CIA I : Subject Assignments / Online Tests : 10 marks CIA II : Mid Semester Examination (Theory) : 25 marks CIAIII: Quiz/Seminar/Case Studies/Project/Innovative Assignments/presentations/publications : 10 marks Attendance : 05 marks Total : 50 marks |