detail teaching scheme · synthesize efficient algorithms in common engineering design situations...

DETAIL TEACHING SCHEME

SCHOOL OF ENGINEERING PROGRAM : M. TECH – COMPUTER ENGINEERING

ACADEMIC YEAR - 2018-19 SEMESTER – I (Batch: 2018-20)

DEFINATION OF ONE CREDIT : 1. Lecture(L): 1 hour / week / semester, 2. Practical(P): 2 hour / week / semester, 3. Tutorial(T): 2 hour /

week / semester

Course

Code Course Name

Teaching Hours Credits CIE PSEE

Theory Tutorial Practical

RM101 Research Methodology 3 0 0 3 Y N

CP101 Advance Computer Architecture 3 0 0 3 Y N

CP103 Advanced Algorithms 4 0 2 5 Y Y

CP212 Advanced Computer Graphics 4 0 2 5 Y Y

CP203 Wireless Ad hoc Networks 4 0 2 5 Y Y

CP108 Data Warehousing and Mining 3 0 2 4 Y Y

Total 21 0 8 25

Total Hours 29

N- No CIE – Continuous internal evaluation

Y – Yes PSEE – Practical semester end examination including ITD, Dissertation, Industrial project, Industrial training etc..

2018-19 M. TECH 1st SEM COMPUTER ENGINEERING (201

Course Title Advance Computer Architecture

Course Code CP101

Course Credits

Theory

Practical

Tutorial

Credits

Course Learning Outcomes:

At the end of the course, students will be able to:

Understand the advanced concepts of computer architecture.

Analyze the major differences of various processor architectural characteristics

Understand parallelism both in terms of a single processor and multiple

processors

Technical understanding

Investigate modern design structures of Pipelined and Multiprocessors systems

Demonstrate the implementation of pipeline, superpipeline and superscalar

architectures in high performance computers

Compare different types of scheduling and memory management schemes.

Detailed Syllabus

Sr. No.

Name of chapter & details

1. Processor and Memory hierarchy:superscalar and vector processor, Memory hierarchy technology, Virtual memory technology.

2. Bus, Cache, and Shared Memory: organization, Shared-memory organizations, sequential and weakconsistency models.

3. Pipelining and Superscalar techniques: Nonlinear Pipeline processors, Instruction pipeline design, arithmetic pipeline design, superscalar and super

SEM COMPUTER ENGINEERING (2018-20 BATCH)

Advance Computer Architecture

CP101

Theory :03

Practical :00

Tutorial :00

Credits :03


students will be able to:

the advanced concepts of computer architecture.

the major differences of various processor architectural characteristics

parallelism both in terms of a single processor and multiple

understanding of parallel hardware constructs.

modern design structures of Pipelined and Multiprocessors systems

the implementation of pipeline, superpipeline and superscalar

architectures in high performance computers.

different types of scheduling and memory management schemes.


SECTION-I

Processor and Memory hierarchy: Advance processor technology, superscalar and vector processor, Memory hierarchy technology, Virtual

Bus, Cache, and Shared Memory: backplane bus system, cache memory memory organizations, sequential and weak

Pipelining and Superscalar techniques: Liner pipeline processors, Nonlinear Pipeline processors, Instruction pipeline design, arithmetic pipeline design, superscalar and super-pipeline design.

SYLLABUS

Page 1

the major differences of various processor architectural characteristics

parallelism both in terms of a single processor and multiple

modern design structures of Pipelined and Multiprocessors systems

the implementation of pipeline, superpipeline and superscalar

different types of scheduling and memory management schemes.

Hours Allotted

Advance processor technology, superscalar and vector processor, Memory hierarchy technology, Virtual 06

backplane bus system, cache memory memory organizations, sequential and weak 07

Liner pipeline processors, Nonlinear Pipeline processors, Instruction pipeline design, arithmetic 08

Total 21


4. Multiprocessors and MultiMulticomputer, cache coherence and synchronization mechanisms, three generations of multicomputer, message

5. Multi-vector and SIMD Computers: vector multiprocessors, compound vector processing, SIMD computer Organizations, the connection machine CM

6. Scalable, Multithreaded, and dataflow architectures: techniques, Principle of multithreading, Fineand multithreaded architectures, dataflow and hybrid architectures.

Instructional Method and Pedagogy:

Lectures will be conducted with the aid of blackboard, OHP etc. Assignments based on to the students at the end of each unit/topic and will be evaluated at regular interval

Minimum five experiments shall be there in the laboratory related to course contents

Minimum six tutorials which includes solution of mini

each head

Reference Books:

Kai Hwang, Advanced computer architecture

John L. Hennessey and David A. Patterson,

Approach, Morgan Kaufmann

J.P.Hayes, Computer Architecture

V.Rajaranam&C.S.R.Murthy,

Hwang and Briggs, Computer Architecture

Additional Resources


SECTION-II

Multiprocessors and Multi-computers: Multiprocessors and Multicomputer, cache coherence and synchronization mechanisms, three generations of multicomputer, message-passing mechanisms.

vector and SIMD Computers: Vector processing principles, vector multiprocessors, compound vector processing, SIMD computer Organizations, the connection machine CM-5.

Scalable, Multithreaded, and dataflow architectures: Latencytechniques, Principle of multithreading, Fine-grain multicomputer, scalable and multithreaded architectures, dataflow and hybrid architectures.


Lectures will be conducted with the aid of multi-media proAssignments based on course contents will be given

to the students at the end of each unit/topic and will be evaluated at regular


Minimum six tutorials which includes solution of minimum five computer programs in

computer architecture, TMH.

nnessey and David A. Patterson, Computer Architecture: A Quantitative

Approach, Morgan Kaufmann, Fourth Edition.

Architecture and organization, MGH.

C.S.R.Murthy, Parallel computer, PHI Learning.

Computer Architecture and Parallel Processing,

SYLLABUS

Page 2

Multiprocessors and Multicomputer, cache coherence and synchronization mechanisms, three 07

Vector processing principles, Multi-vector multiprocessors, compound vector processing, SIMD computer 08

Latency-hiding multicomputer, scalable

and multithreaded architectures, dataflow and hybrid architectures. 06

Total 21

ia projector, course contents will be given



mum five computer programs in

Computer Architecture: A Quantitative

Processing, MGH.


Course Title Advanced Algorithms

Course Code CP103

Course Credits

Theory

Practical

Tutorial

Credits


At the end of the course, students

Demonstrate a familiarity with major algorithms and data structures.

Apply important algorithmic design paradigms and methods of analysis.

Analyze the asymptotic performance of algorithms. Understand and design

approach, dynamic programming, and max flow Synthesize efficient algorithms in common engineering design situations Understand basic knowledge of graph and matching algorithms. Analyze lower-bounds and the theory of NP

Detailed Syllabus

Sr. No.


1. Pre-requisite of Data Structure & Analysis of Algorithms:Overview of Data Structures, Space & Time Complexity, Asymptotic Notations (Growth of Functions), analysis, Elementary operation, Analyzing control statement, Amortized analysis, Sorting Algorithms, Binary Tree Search.

2. Recurrences Intelligent guesswork,recurrences,Change of variable,Range transformations,Recurrence tree

3. Divide & Conquer Overview of divide and conquer technique, MultiplyingProblem, Problem Solving using divide and conquer algorithm Search, Sorting (Merge Sort, Quick Sort), Matrix Multiplication, Exponential.


Advanced Algorithms

CP103

Theory :04

Practical :01

Tutorial :00

Credits :05



a familiarity with major algorithms and data structures.

important algorithmic design paradigms and methods of analysis.

the asymptotic performance of algorithms. Understand and design algorithms using greedy strategy, divide and conquer approach, dynamic programming, and max flow - min cut theory.

efficient algorithms in common engineering design situationsbasic knowledge of graph and matching algorithms.

bounds and the theory of NP-completeness


SECTION-I

requisite of Data Structure & Analysis of Algorithms: Overview of Data Structures, Space & Time Complexity,

otations (Growth of Functions), Average and worst case analysis, Elementary operation, Analyzing control statement, Amortized analysis, Sorting Algorithms, Binary Tree Search.

Intelligent guesswork, Homogeneous recurrences,Inhomogeneous recurrences,Change of variable,Range transformations,Recurrence tree

Overview of divide and conquer technique, Multiplying large Integers Problem, Problem Solving using divide and conquer algorithm Search, Sorting (Merge Sort, Quick Sort), Matrix Multiplication,

SYLLABUS

Page 1

a familiarity with major algorithms and data structures.

important algorithmic design paradigms and methods of analysis.

algorithms using greedy strategy, divide and conquer min cut theory.

efficient algorithms in common engineering design situations basic knowledge of graph and matching algorithms.

Hours Allotted

Average and worst case analysis, Elementary operation, Analyzing control statement, Amortized

08

Inhomogeneous recurrences,Change of variable,Range transformations,Recurrence tree

10

large Integers Problem, Problem Solving using divide and conquer algorithm - Binary Search, Sorting (Merge Sort, Quick Sort), Matrix Multiplication,

10


4. Dynamic ProgrammingIntroduction,The Principle of Optimality, Problem Solving using Dynamic Programming Calculating the Binomial Coefficient, Problem, Assembly LineKnapsack problem, Shortest path, Matrix chain multiplication, Longest Common Subsequence.

5. Greedy Algorithms General Characteristics of greedy algorithms, Problem solving using Greedy Algorithm – Activity selection problem, strategy, Minimum Spanning trees (Kruskal’s algorithm, Prim’s algorithm),Graphs: Shortest paths, TScheduling Problem.

6. Introduction to Graph and Graph AlgorithmsIntroduction, Storage Representation for Undirected Graph & Directed Graph,Traversing Techniques queens problem, General

7. Introduction to NP-CompletenessThe class P and NP, Polynomial reduction, NPNP-Hard Problems.

8. External-Memory AlgorithmsAccounting for the Cost of Accessing Data from Slow Memory, Buffer Trees,Cache-oblivious Algorithms for Matrix Multiplication.Computational GeometryConvex Hull, Line-segment Intersection, Sweep Lines, Voronoi Diagrams, Range Trees, Seidel's Low


Lectures will be conducted with the aid of blackboard, OHP etc.

Assignments based on course contents will be given to the students at the end of each unit/topic and will be evaluated at regular interval

Reference Books:


SECTION-II

Dynamic Programming The Principle of Optimality, Problem Solving using Dynamic

Programming Calculating the Binomial Coefficient, Making Change Problem, Assembly Line-Scheduling,

Shortest path, Matrix chain multiplication, Longest

General Characteristics of greedy algorithms, Problem solving using Activity selection problem, Elements of Greedy

strategy, Minimum Spanning trees (Kruskal’s algorithm, Prim’s algorithm),Graphs: Shortest paths, The Knapsack Problem, Job

Introduction to Graph and Graph Algorithms Introduction, Storage Representation for Undirected Graph & Directed Graph,Traversing Techniques – DFS &BFS,Backtracking: The Eight queens problem, General Template.

Completeness The class P and NP, Polynomial reduction, NP- Completeness Problem,

Memory Algorithms Accounting for the Cost of Accessing Data from Slow Memory, Buffer

oblivious Algorithms for Matrix Multiplication. Computational Geometry

segment Intersection, Sweep Lines, Voronoi Diagrams, Range Trees, Seidel's Low-dimensional LP Algorithm.


Lectures will be conducted with the aid of multi-media pro

Assignments based on course contents will be given to the students at the end of each unit/topic and will be evaluated at regular interval

SYLLABUS

Page 2

Total 28

The Principle of Optimality, Problem Solving using Dynamic Making Change

Shortest path, Matrix chain multiplication, Longest

06

General Characteristics of greedy algorithms, Problem solving using Elements of Greedy

Job

05

Introduction, Storage Representation for Undirected Graph & Directed Backtracking: The Eight

06

Completeness Problem, 03

Accounting for the Cost of Accessing Data from Slow Memory, Buffer

segment Intersection, Sweep Lines, Voronoi Diagrams, 08

Total 28

ia projector,

Assignments based on course contents will be given to the students at the


Thomas Coremen, Introduction to ALGORITHMS, PHI, 3rd Edition

Gilles Brassard & Paul Bratley,Fundamental of Computer Algorithmics, PHI

Aho, Hopcroft and Ullman, The Design and Analysis of Computer Algorithms,

Addison-Wesley

Computer Algorithms, Ellis Horowitz


NPTEL Lecture Series on Data structure and Algorithm in Computer

Science and Engineering, By Naveen Garg, IIT Delhi.


Coremen, Introduction to ALGORITHMS, PHI, 3rd Edition



Ellis Horowitz , SartajSahni , SanguthevarRajasekaran


Science and Engineering, By Naveen Garg, IIT Delhi.

SYLLABUS

Page 3

Coremen, Introduction to ALGORITHMS, PHI, 3rd Edition



SanguthevarRajasekaran,



Course Title Advanced Computer Graphics

Course Code CP212

Course Credits

Theory

Practical

Tutorial

Credits



Understand recent research in Computer Graphics, Modelling Geometry,

Interactive Techniques, and Visualization.

Understand and design

pipeline and an interactive render loop.

Develop and implement

geometry.

Understand and apply

transparency.

Understand the various color models and animation techniques.

Developand demonstr

Detailed Syllabus

Sr. No.


1. Three Dimensional geometric and Modeling Transformations: Introduction, 3D Scaling,3D Shearing, 3D Rotation, 3D Reflection, Translation, Multiple Transformations, Rotation about arbitrary axis.

2. Three Dimensional projectionsParallel Orthographic, Axonometric: trimetric, diametric, isometric, Oblique: Cavalier and cabinet and perspective: Single point, two point.


Advanced Computer Graphics

CP212

Theory :04

Practical :01

Tutorial :00

Credits :05


students will be able to:

recent research in Computer Graphics, Modelling Geometry,

Interactive Techniques, and Visualization.

Understand and design 3D modelling transformation and viewing. the graphics

pipeline and an interactive render loop.

Develop and implement efficient and accurate surface modelling and solid

apply different visual surface determination, shading, shadow,

the various color models and animation techniques.

demonstrate programming skills in 3D computer graphics


SECTION-I

Three Dimensional geometric and Modeling Transformations: Introduction, 3D Scaling,3D Shearing, 3D Rotation, 3D Reflection, Translation, Multiple Transformations, Rotation about arbitrary axis.

Three Dimensional projections Parallel Orthographic, Axonometric: trimetric, diametric, isometric, Oblique: Cavalier and cabinet and perspective: Single point, two point.

SYLLABUS

Page 1

recent research in Computer Graphics, Modelling Geometry,

3D modelling transformation and viewing. the graphics

efficient and accurate surface modelling and solid

different visual surface determination, shading, shadow,

the various color models and animation techniques.

programming skills in 3D computer graphics

Hours Allotted

Three Dimensional geometric and Modeling Transformations: Introduction, 3D Scaling,3D Shearing, 3D Rotation, 3D Reflection, 3D Translation, Multiple Transformations, Rotation about arbitrary axis.

07

Parallel Orthographic, Axonometric: trimetric, diametric, isometric, Oblique: 07


3. Representing Curves and SurfacesPolygon meshes, Parametric cubic curves, Hermit curves, Bezier curve, spline: uniform B-splines, nonsubdividing curves, Parametric bicubic surfaces: Hermite surfaces, Bezier surfaces, quadric surfaces.

4. SOLID MODELING Representing Solids, Regularized Boolean Set Operations, Primitive Instancing, Sweep Representations, Boundary Representation, Spatialpartitioning Representations, Constructive Solid Geometry, and Comparison of Representations.

5. Visual Realism: Why realism?, Rendering techniques for line drawings, Rendering technique for shaded images, improved object models, Dynamics, Improved displays, interacting with our other senses, Aliasing and antialiasing.

6. Visible-surface Determination Techniques for efficient visibleline determination, Z-buffer algorithm, Listsubdivision algorithms, algorithm for Octree, algorithm for curved surface, visible-surface ray tracing.

7. Illumination and shadingIllumination models, shading model for polygons, surface detail, shadows, Transparency, Recursive ray tracing, Radiosity methods.

8. Achromatic and Colored LightAchromatic light, chromatic color, color models for raster graphics.

9. Animation Design of animation sequences, general computerraster animation, key- frame system, morphing, simulating accelerations, motion specification, direct motion specification, goal



Representing Curves and Surfaces Polygon meshes, Parametric cubic curves, Hermit curves, Bezier curve,

splines, non- uniform B-splines and βsubdividing curves, Parametric bicubic surfaces: Hermite surfaces, Bezier

uadric surfaces.

Representing Solids, Regularized Boolean Set Operations, Primitive Instancing, Sweep Representations, Boundary Representation, Spatialpartitioning Representations, Constructive Solid Geometry, and

Representations.

SECTION-II

Rendering techniques for line drawings, Rendering technique for shaded images, improved object models, Dynamics, Improved displays, interacting with our other senses, Aliasing and

surface Determination efficient visible-surface algorithms, algorithms for visible

buffer algorithm, List-priority algorithms, area subdivision algorithms, algorithm for Octree, algorithm for curved surface,

surface ray tracing.

and shading Illumination models, shading model for polygons, surface detail, shadows, Transparency, Recursive ray tracing, Radiosity methods.

Achromatic and Colored Light Achromatic light, chromatic color, color models for raster graphics.

Design of animation sequences, general computer- animation functions, frame system, morphing, simulating accelerations,

motion specification, direct motion specification, goal- directed system.

Method and Pedagogy:

SYLLABUS

Page 2

Polygon meshes, Parametric cubic curves, Hermit curves, Bezier curve, splines and β-splines,

subdividing curves, Parametric bicubic surfaces: Hermite surfaces, Bezier 08

Representing Solids, Regularized Boolean Set Operations, Primitive Instancing, Sweep Representations, Boundary Representation, Spatial-partitioning Representations, Constructive Solid Geometry, and

06

Total 28

Rendering techniques for line drawings, Rendering technique for shaded images, improved object models, Dynamics, Improved displays, interacting with our other senses, Aliasing and

06

surface algorithms, algorithms for visible priority algorithms, area

subdivision algorithms, algorithm for Octree, algorithm for curved surface, 06

Illumination models, shading model for polygons, surface detail, shadows, 06

Achromatic light, chromatic color, color models for raster graphics. 06

animation functions, frame system, morphing, simulating accelerations,

directed system.

04

Total 28


Lectures will be conducted with the aid of etc. Assignments based on course contents will be given to the students at the end of each unit/topic and will be evaluated at regular interval



each head

Reference Books:

1. James D. Foley, Andries

Addison-Weslely Publication.

2. David F. Rogers, “Procedural Elements for computer graphics



Lectures will be conducted with the aid of multi-media projectAssignments based on course contents will be given to the students at the end of

each unit/topic and will be evaluated at regular interval five experiments shall be there in the laboratory related to course contents


James D. Foley, Andries Van Dam, “Fundamental of Interactive Computer Graphics”,

Weslely Publication.

Procedural Elements for computer graphics”, TMH.

SYLLABUS

Page 3

ctor, blackboard, OHP Assignments based on course contents will be given to the students at the end of

five experiments shall be there in the laboratory related to course contents


Van Dam, “Fundamental of Interactive Computer Graphics”,

, TMH.


Course Title Data Warehousing and Data Mining

Course Code CP108

Course Credits

Theory

Practical

Tutorial

Credits



Understand the basic concepts of

Analyze the major techniques of preprocessing for different types of data.

Understand and Compare

Recognize the different

Differentiate the technique of data mining and

implementing them.

Investigate modern Trends and technique of data mining.

Detailed Syllabus

Sr. No.


1. Introduction to Data WarehousingWhat is data warehousing warehouses and data marts the data warehouse - Need for data warehousing

2. Preprocessing TechniquesOverview, Need for prehandling (Extraction, Transformation, And updating of large databases (ADDED), Data Cleaning, Data Integration & Transformation, Data Reduction, Discretization & Concept Hierar

3. Business analysis Multi-dimensional Data Cubes, Star, Snow Flakes, & Fact Constellation Schema, Concept Hierarchies, OLAP, Data Warehouse Architecture Steps for design and construction of data warehouse, A 3architecture, ROLAP, MOLAP, HOLAP, Data Warehouse Implementation


Data Warehousing and Data Mining

CP108

Theory :03

Practical :01

Tutorial :00

Credits :04


course, students will be able to:

concepts of data warehousing.

the major techniques of preprocessing for different types of data.

Compare different types of data warehouse architecture.

the different type of data mining methods.

the technique of data mining and Demonstrate that technique with

Trends and technique of data mining.


SECTION-I

Introduction to Data Warehousing What is data warehousing - The building Blocks: Defining Features warehouses and data marts - Overview of the components - Metadata in

Need for data warehousing

Techniques Overview, Need for pre-processing, Issues related to efficient data handling (Extraction, Transformation, And updating of large databases (ADDED), Data Cleaning, Data Integration & Transformation, Data Reduction, Discretization & Concept Hierarchy Generation

dimensional Data Cubes, Star, Snow Flakes, & Fact Constellation Schema, Concept Hierarchies, OLAP, Data Warehouse Architecture Steps for design and construction of data warehouse, A 3-tier data warehouse

tecture, ROLAP, MOLAP, HOLAP, Data Warehouse Implementation

SYLLABUS

Page 1

the major techniques of preprocessing for different types of data.

different types of data warehouse architecture.

that technique with

Hours Allotted

The building Blocks: Defining Features – Data Metadata in

04

processing, Issues related to efficient data handling (Extraction, Transformation, And updating of large databases (ADDED), Data Cleaning, Data Integration & Transformation, Data

05

dimensional Data Cubes, Star, Snow Flakes, & Fact Constellation Schema, Concept Hierarchies, OLAP, Data Warehouse Architecture Steps

tier data warehouse tecture, ROLAP, MOLAP, HOLAP, Data Warehouse Implementation

06


4. Implementation and MaintenancePhysical design process, data warehouse deployment, growth and maintenance.

5. Introduction to DATA MININGIntroduction, Data, Types of Data, Data Mining Functionalities, Interestingness of Patterns, Classification of Data Mining Systems, Data Mining Task Primitives, Integration of a Data Mining System with a Data Warehouse Issues, Data Preprocessing

6. Concept Description andWhat is concept description?, Data Generalization and summarization based characterization, Attribute relevance, class comparisons Association Rule Mining: Market basket analysis basic concepts, Finding frequent item sets: Apriori algorithm, generating rules, Improved Apriori algorithm

7. Classification and predictionWhat is classification and prediction?, Issues regarding Classification andprediction: Classification methods: Decision tree, Bayesian Classification, Rule based, CART, Neural Network, CBR, Rough set Approach, Fuzzy Logic, Genetic AlgorithmsPrediction methods: Linear and non linear regression, Logistic Regression

8. Clustering and applications and trends in data mining Cluster Analysis, Types of Data, Categorization of Major Clustering Methods Kmeans, Partitioning Methods, Hierarchical Methods, DensityBased Methods, Grid Based Methods, ModelClustering High Dimensional Data, ConstraintOutlier Analysis, Data Mining Applications.

9. Application and Trends in Data MiningApplications, Systems products and researchthemes in data mining, Trends in data mining, Mining TimeSequence Data – Mining Text Databases Data Mining Application



Implementation and Maintenance Physical design process, data warehouse deployment, growth and

SECTION-II

Introduction to DATA MINING Types of Data, Data Mining Functionalities,

Interestingness of Patterns, Classification of Data Mining Systems, Data Mining Task Primitives, Integration of a Data Mining System with a Data Warehouse Issues, Data Preprocessing

Concept Description and Association Rule Mining What is concept description?, Data Generalization and summarization based characterization, Attribute relevance, class comparisons Association Rule Mining: Market basket analysis basic concepts, Finding frequent item

algorithm, generating rules, Improved Apriori algorithm

Classification and prediction What is classification and prediction?, Issues regarding Classification

: Classification methods: Decision tree, Bayesian Classification, Rule based, CART, Neural Network, CBR, Rough set Approach, Fuzzy Logic, Genetic AlgorithmsPrediction methods: Linear and non linear regression, Logistic Regression

ications and trends in data mining Cluster Analysis, Types of Data, Categorization of Major Clustering Methods Kmeans, Partitioning Methods, Hierarchical Methods, DensityBased Methods, Grid Based Methods, Model-Based Clustering Methods,

Dimensional Data, Constraint– Based Cluster Analysis, Outlier Analysis, Data Mining Applications.

Application and Trends in Data Mining Applications, Systems products and research prototypes, Additional themes in data mining, Trends in data mining, Mining Time-Series and

Mining Text Databases – Mining the World Wide Web Data Mining Application – Web mining


SYLLABUS

Page 2

Physical design process, data warehouse deployment, growth and 06

Total 21

Interestingness of Patterns, Classification of Data Mining Systems, Data Mining Task Primitives, Integration of a Data Mining System with a Data

04

What is concept description?, Data Generalization and summarization based characterization, Attribute relevance, class comparisons Association Rule Mining: Market basket analysis basic concepts, Finding frequent item

algorithm, generating rules, Improved Apriori algorithm

04

What is classification and prediction?, Issues regarding Classification : Classification methods: Decision tree, Bayesian

Classification, Rule based, CART, Neural Network, CBR, Rough set Approach, Fuzzy Logic, Genetic AlgorithmsPrediction methods: Linear and

04

Cluster Analysis, Types of Data, Categorization of Major Clustering Methods Kmeans, Partitioning Methods, Hierarchical Methods, Density-

Based Clustering Methods, Based Cluster Analysis,

06

prototypes, Additional Series and

Mining the World Wide Web – 03

Total 21


Lectures will be conducted with the aid of blackboard, OHP etc. Assignments based on course contents will be given to the students at the end of each unit/topic and will be evaluated at regular interval

Minimum five experiments shall

Minimum ten tutorials which includes solution of minimum their case studies in each

head

Reference Books:

J. Han, M. Kamber, Data Mining Concepts and Techniques, Morgan Kaufmann Publishers

ReemaThareja, Data Warehousing, Oxford PaulrajPonnian, Data Warehousing Fundamentals,John Willey Alex Berson and Stephen J. Smith,Data Warehousing, Data Mining &

OLAP, Tata McGraw – Hill


http://cquestionbank.blogspot.com www.intelligentedu.com/ www.hermetic.ch/cfunlib.htm N.P.T.L. Video Lecture Series N.I.T.T.I. Instructional Resources Videos. www.cprogramming.com/ www.c-program.com/


Lectures will be conducted with the aid of multi-media proAssignments based on course contents will be given




J. Han, M. Kamber, Data Mining Concepts and Techniques, Morgan

ReemaThareja, Data Warehousing, Oxford Data Warehousing Fundamentals,John Willey

Alex Berson and Stephen J. Smith,Data Warehousing, Data Mining & Hill

http://cquestionbank.blogspot.com www.intelligentedu.com/ www.hermetic.ch/cfunlib.htm N.P.T.L. Video Lecture Series N.I.T.T.I. Instructional Resources Videos. www.cprogramming.com/

SYLLABUS

Page 3

ia projector, Assignments based on course contents will be given


be there in the laboratory related to course contents


J. Han, M. Kamber, Data Mining Concepts and Techniques, Morgan

Alex Berson and Stephen J. Smith,Data Warehousing, Data Mining &


Course Title Research Methodology

Course Code RM101

Course Credits

Theory

Practical

Tutorial

Credits


At the end of the course, students

Apply appropriate communication skills across settings, purposes, and audiences and Demonstrate knowledge of communication theory and application.

Use technology to communicate effectively in various settings and contexts and demonstrate appropriate a

Demonstrate competency in critical thinking skills related to the analysis, interpretation, and criticism of messages.

Define research and describe the research Develop testable hypotheses, differentiate research design and/or statistics,

evaluate aptness of research conclusions, and generalize them appropriately. Effectively use the library and

learners' research project. Understand the process of sampling, the uses of questionnaires as data

gathering instruments, how a survey is carried out in terms of process and method,

the uses of surveys and to be able to capture their own data.

Detailed Syllabus

Sr. No.


1. Concepts of Communications: Definition, Forms of Communication, Objectives of Communication, Characteristics of Communication, Process of Communication, Communication, Roadblocks, Role of Verbal and NonCommunication, Barriers to Effective Communication, OvercominCommunication Barriers


Research Methodology

RM101

Theory :03

Practical :00

Tutorial :00

Credits :03



appropriate communication skills across settings, purposes, and audiences knowledge of communication theory and application.

technology to communicate effectively in various settings and contexts and demonstrate appropriate and professional ethical behavior.

competency in critical thinking skills related to the analysis, interpretation, and criticism of messages.

research and describe the research process and research methodstestable hypotheses, differentiate research design and/or statistics,

evaluate aptness of research conclusions, and generalize them appropriately.the library and its resources in gathering information related to the

learners' research project. the process of sampling, the uses of questionnaires as data


and to be able to capture their own data.


SECTION-I

Concepts of Communications: Definition, Forms of Communication, Objectives of Communication,

Characteristics of Communication, Process of Communication, Communication, Roadblocks, Role of Verbal and Non-verbal, Symbols in Communication, Barriers to Effective Communication, Overcomin

SYLLABUS

Page 1

appropriate communication skills across settings, purposes, and audiences knowledge of communication theory and application.

technology to communicate effectively in various settings and contexts and

competency in critical thinking skills related to the analysis,

process and research methods testable hypotheses, differentiate research design and/or statistics,

evaluate aptness of research conclusions, and generalize them appropriately. its resources in gathering information related to the

the process of sampling, the uses of questionnaires as data-


Hours Allotted

Definition, Forms of Communication, Objectives of Communication, Characteristics of Communication, Process of Communication,

verbal, Symbols in Communication, Barriers to Effective Communication, Overcoming

07


2. Nonverbal communicationBody Language, Gestures, Postures, Facial Expressions, Dress codes; the Cross Cultural Dimensions of Business Communication; Listening and Speaking, techniques of electing response, probing questions, Observation. Business and social etiquettes; Listening Skills: Definition, Anatomy of poor Listening, Features of a good Listener, Role Play,Discussion and Interviews,Meetings: Ways and Means of conducting meetings effectively, Mock Meetings and Interviews

3. Reading and language skillsThe reading process, purpose, different kinds of texts, reference material, scientific and technical texts, active and passive reading, strategies vocabulary skills, eye reading and visual perception, prediction techniques, scanning skills, distinguishing facts and opinions, drawing inferences and conclusions, comprehension of technical material texts, instructions and technical manuals, graphic information. Forms of Communication in Written mode: Basics Body language of Business Letters and Memos, Tone of writing, enquiries, orders and replying to them, sales etters, Job asmart e-mail, Writing Business Reports and Proposals, Practice for Writing

4. Referencing and Writing skillsBusiness letters: Enquiries, Circulars, Quotations, Orders, Acknowledgments, Executions, Collection letter, Bankingcorrespondence, Agency correspondence, Bad news and persuading letters, Sales letters, Job application letters Interview Letters, Letter of Reference, Memos, minutesnotices Types of Business Reports coherence and cohesion, paragraph writing, organization reportsby individual, Report by committee.

5. Introduction to Research and Research DesignNature and scope of research, information based decision making and source of knowledge. The research process; basic approaches and terminologies used in research. Defining research question and framing of hypotheses, Preparing aresearch plan, qualitative research designs, Experimentation, Observational studies, Exploring secondary data.


Nonverbal communication: Body Language, Gestures, Postures, Facial Expressions, Dress codes; the

Dimensions of Business Communication; Listening and Speaking, techniques of electing response, probing questions, Observation. Business and social etiquettes; Listening Skills: Definition, Anatomy of poor Listening, Features of a good Listener, Role Play,Discussion and Interviews,Meetings: Ways and Means of conducting meetings effectively, Mock Meetings and Interviews

Reading and language skills The reading process, purpose, different kinds of texts, reference material,

al texts, active and passive reading, strategies vocabulary skills, eye reading and visual perception, prediction techniques, scanning skills, distinguishing facts and opinions, drawing inferences and conclusions, comprehension of technical material – scientific and technical texts, instructions and technical manuals, graphic information. Forms of Communication in Written mode: Basics Body language of Business Letters and Memos, Tone of writing, enquiries, orders and replying to them, sales etters, Job applications and resume, E-mail: How to make

Writing Business Reports and Proposals, Practice for Writing

Referencing and Writing skills: Business letters: Enquiries, Circulars, Quotations, Orders, Acknowledgments, Executions, Complaints, Claims and adjustments, Collection letter, Banking correspondence, Agency correspondence, Bad news and persuading letters, Sales letters, Job application letters - Biodata, Covering Letter, Interview Letters, Letter of Reference, Memos, minutes, Circulars & notices Types of Business Reports - Format, Choice of vocabulary, coherence and cohesion, paragraph writing, organization reports by individual, Report by committee.

SECTION-II

Introduction to Research and Research Design Nature and scope of research, information based decision making and source of knowledge. The research process; basic approaches and terminologies used in research. Defining research question and framing of hypotheses, Preparing aresearch plan, qualitative and quantitative research designs, Experimentation, Observational studies, Exploring

SYLLABUS

Page 2

Body Language, Gestures, Postures, Facial Expressions, Dress codes; the Dimensions of Business Communication; Listening and

Speaking, techniques of electing response, probing questions, Observation. Business and social etiquettes; Listening Skills: Definition, Anatomy of poor Listening, Features of a good Listener, Role Play, Group Discussion and Interviews,Meetings: Ways and Means of conducting

07

The reading process, purpose, different kinds of texts, reference material, al texts, active and passive reading, strategies -

vocabulary skills, eye reading and visual perception, prediction techniques, scanning skills, distinguishing facts and opinions, drawing inferences and

ientific and technical texts, instructions and technical manuals, graphic information. Forms of Communication in Written mode: Basics Body language of Business Letters and Memos, Tone of writing, enquiries, orders and replying to

mail: How to make

07

Business letters: Enquiries, Circulars, Quotations, Orders, Complaints, Claims and adjustments,

correspondence, Agency correspondence, Bad news and persuading Biodata, Covering Letter,

, Circulars & Format, Choice of vocabulary,

07

Total 28

Nature and scope of research, information based decision making and source of knowledge. The research process; basic approaches and terminologies used in research. Defining research question and framing of

and quantitative research designs, Experimentation, Observational studies, Exploring

07


6. Measurement and Scaling, Data Source and Data CollectionField research; primary data collection from observations, surveys and experimentation. Measurement and scaling; commonly used scales in reliability and validity of scales. Designing instrument for data collection; testing the instrument, data collection process, Sampling methods and procedures and sample size decisions.

7. Data Analysis and PresentationEditing and coding of data, tabulation, graphic presentation of data, cross tabulation, Testing of hypotheses; type I and II errors, one tailed and two tailed tests of significance, Parametric and nonparametric tests for Univariate and Bivariate data. Tests of association; simple linear regression and other nonparametric tests.

8. Technical Writing Technical Proposal writing: Definition, Purpose, types, characteristics, Elements of structure, style and appearance, evaluation, exercises,Research report writing, Proposal writing, referencing, forms of reports, bibliography, etc.Research paper, Dissertation, and Thesis, Instruction Manuals, Type of instructions, Writing Instructions, TechnicalDescriptions, Process descriptions, Guidelines


Lectures will be conducted with the aid of multiboard,Transperencies etc.

Assignments and Exercise will be given to the students for each unit/topic evaluated at regular interval.

Surprise tests/Quizzes/Seminar/Tutorials will be conducted.

Reference Books:

1. Lesikar, R. V. &Flatley Basic Business Communication Skills for Empowering the Internet Generation. Tata McGrawHill

2. Meenakshi Raman, Sangeeta Sharma Technical Communications Oxford Latest Edition

3. D. K. Bhattacharyya Research Methodology Excel Books 2nd Edition



Measurement and Scaling, Data Source and Data Collection Field research; primary data collection from observations, surveys and

Measurement and scaling; commonly used scales in reliability and validity of scales. Designing instrument for data collection; testing the instrument, data collection process, Sampling methods and procedures and sample size decisions.

and Presentation Editing and coding of data, tabulation, graphic presentation of data, cross tabulation, Testing of hypotheses; type I and II errors, one tailed and two tailed tests of significance, Parametric and nonparametric tests for

ariate data. Tests of association; simple linear regression and other nonparametric tests.

Technical Proposal writing: Definition, Purpose, types, characteristics, Elements of structure, style and appearance, evaluation, exercises,Research report writing, Proposal writing, referencing, forms of reports, bibliography, etc.Research paper, Dissertation, and Thesis, Instruction Manuals, Type of instructions, Writing Instructions, TechnicalDescriptions, Process descriptions, Guidelines for Writing Good Descriptions


Lectures will be conducted with the aid of multi-media projector, black board,Transperencies etc. Assignments and Exercise will be given to the students for each unit/topic evaluated at regular interval. Surprise tests/Quizzes/Seminar/Tutorials will be conducted.

Lesikar, R. V. &Flatley Basic Business Communication Skills for Empowering the Internet Generation. Tata McGrawHill 2005 or Latest Meenakshi Raman, Sangeeta Sharma Technical Communications Oxford Latest

D. K. Bhattacharyya Research Methodology Excel Books 2nd Edition

SYLLABUS

Page 3

Field research; primary data collection from observations, surveys and

Measurement and scaling; commonly used scales in reliability and validity of scales. Designing instrument for data collection; testing the instrument, data collection process, Sampling methods and

07

Editing and coding of data, tabulation, graphic presentation of data, cross tabulation, Testing of hypotheses; type I and II errors, one tailed and two tailed tests of significance, Parametric and nonparametric tests for

ariate data. Tests of association; simple linear

07

Technical Proposal writing: Definition, Purpose, types, characteristics, Elements of structure, style and appearance, evaluation, exercises, Research report writing, Proposal writing, referencing, forms of reports, bibliography, etc.Research paper, Dissertation, and Thesis, Instruction Manuals, Type of instructions, Writing Instructions, TechnicalDescriptions,

07

Total 28

media projector, black

Assignments and Exercise will be given to the students for each unit/topic and will be

Lesikar, R. V. &Flatley Basic Business Communication Skills for Empowering the

Meenakshi Raman, Sangeeta Sharma Technical Communications Oxford Latest

D. K. Bhattacharyya Research Methodology Excel Books 2nd Edition


Course Title Wireless Adhoc Networks

Course Code CP203

Course Credits

Theory

Practical

Tutorial

Credits


At the end of the course, students will be able to: Recognize needs of different set of MAC, routing and transport protocols for

wireless computer networks compared to wired networks. Understand and Compare

protocols for Ad hoc Networks. Analyzeperformance of MANET Routing Protocols under different mobility

patterns. Idenfitydifferent methods for energy saving Identify future research

Detailed Syllabus

Sr. No.


1. Wireless Network Mobile Communication: Past, Present, and Future HomeRF - 802.11 - 802.16 Internet - Ad Hoc Networks

2. MAC Layer Protocols for Ad Hoc Wireless NetworksImportant Issues and Need Channel, Energy-Efficient

3. Routing Protocols for Ad Hoc Wireless NetworksBasics – Design Issues –Reactive Routing Protocols

4. Multicast Routing Protocols for Mobile Ad Hoc NetworksIssues – Classification –Multicast with QoS and EnergyRouting


Wireless Adhoc Networks

CP203

Theory :04

Practical :01

Tutorial :00

Credits :05


students will be able to: needs of different set of MAC, routing and transport protocols for

wireless computer networks compared to wired networks. Compare different types of MAC, Routing and Transport

protocols for Ad hoc Networks. performance of MANET Routing Protocols under different mobility

different methods for energy saving in a mobile device. future research directions.


SECTION-I

Mobile Communication: Past, Present, and Future - Bluetooth 802.16 – Hotspots - Mesh Networking -

Ad Hoc Networks

MAC Layer Protocols for Ad Hoc Wireless Networks Important Issues and Need – Classification – MAC Protocols: Multiple

Efficient

ocols for Ad Hoc Wireless Networks – Classification – Proactive Routing Protocols

Reactive Routing Protocols - Hybrid Routing Protocols

Multicast Routing Protocols for Mobile Ad Hoc Networks MAODV – Mesh Based Protocols – SRMP

Multicast with QoS and Energy-Efficient - Application-Dependent Multicast

SYLLABUS

Page 1

needs of different set of MAC, routing and transport protocols for

different types of MAC, Routing and Transport

performance of MANET Routing Protocols under different mobility

Hours Allotted

Bluetooth – IrDA – - Wireless

05

MAC Protocols: Multiple- 05

Proactive Routing Protocols - 09

SRMP – Dependent Multicast

09


5. Transport Protocols for Ad Hoc NetworksChallenges – Design Goals Transport Protocols – ACTP

6. QoS in Ad Hoc Networks & Energy ManagementIssues and Challenges –- Transmission Power Management Schemes Control – Variants of AODV

7. Mobility Models for Multihop Wireless Networks & ApplicationModels – Patterns - CrossDevelopments in Ad HocNetworks

8. Issues and ChallengesTime synchronization – Localization Management


Lectures will be conducted with the aid of blackboard, OHP etc. Assignments based on course contents will be to the students at the end of each unit/topic and will be evaluated at regular interval

Minimum five experiments shall be there in the laboratory related to course contents Minimum six tutorials which includes solution of minimum five computer progra

each head

Reference Books:

SahaMisra,Wireless Communications Asoke K Talukder and RoopaR Yavagal,Mobile Computing Technology, Appl

and Service Creation, Tata McGraw Hill Raj Pandya ,Mobile and Personal KavehPahlavan and Prashant Krishnamurthy, P Theodore S. Rappaport Yi-Bing Lin and ImrichChlamtac, Wireless and Mobile Network Arc Raj Kamal, Mobile Computing,



SECTION-II

Transport Protocols for Ad Hoc Networks Design Goals – Performance Comparison - Ad Hoc

ACTP

QoS in Ad Hoc Networks & Energy Management – Classification - Energy-Efficient Routing Protocol

Transmission Power Management Schemes - Transmission Power Variants of AODV

Mobility Models for Multihop Wireless Networks & ApplicationCross-Layer Design Issues - Applications and Recent

Developments in Ad HocNetworks

Issues and Challenges Localization - Resource Allocation - Data


Lectures will be conducted with the aid of multi-media proAssignments based on course contents will be


Minimum five experiments shall be there in the laboratory related to course contentsMinimum six tutorials which includes solution of minimum five computer progra

SahaMisra,Wireless Communications and Networks, 3G and beyond,Asoke K Talukder and RoopaR Yavagal,Mobile Computing Technology, Appl

Tata McGraw Hill Mobile and Personal Communication Systems and Services, PHI

KavehPahlavan and Prashant Krishnamurthy, Principle of wireless Networks,PHITheodore S. Rappaport, Wireless Communication Principles and Practice, PHI

Bing Lin and ImrichChlamtac, Wireless and Mobile Network ArcRaj Kamal, Mobile Computing, Oxford Press

SYLLABUS

Page 2

Total 28

Ad Hoc 07

Efficient Routing Protocol Transmission Power

08

Mobility Models for Multihop Wireless Networks & Application Applications and Recent 06

Data 07

Total 28

ia projector, Assignments based on course contents will be given


Minimum five experiments shall be there in the laboratory related to course contents Minimum six tutorials which includes solution of minimum five computer programs in

and Networks, 3G and beyond, TMH. Asoke K Talukder and RoopaR Yavagal,Mobile Computing Technology, Application

Communication Systems and Services, PHI rinciple of wireless Networks,PHI

ation Principles and Practice, PHI Bing Lin and ImrichChlamtac, Wireless and Mobile Network Architectures, WILEY


http://www.3gpp.org

http://www.3gpp2.org

http://www.vicomsoft.com/learning

NPTEL video lectures of Wireless Communications course of Electronics &

Communication Engineering by Prof. Ranjan Bose,


http://www.vicomsoft.com/learning-center/wireless-networking/


Communication Engineering by Prof. Ranjan Bose, IIT Delhi

SYLLABUS

Page 3


detail teaching scheme · synthesize efficient algorithms in common engineering design situations...

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