Download Syllabus for M Sc - Rajshahi University Alumni Association

UNIVERSITY OF RAJSHAHI
Faculty of Science
DEPARTMENT OF COMPUTER SCIENCE
AND ENGINEERING
(North Block, 4th Science Building)
Tel: 0721-750041/4103
Fax: 0721-750064
E-mail: [email protected]
Web Site: http://www.ru.ac.bd/cse
Syllabus for M.Sc.
Session: 2007–2008
EXAMINATION: 2008
Dept. of CSE, University of Rajshahi
University of Rajshahi
Faculty of Science
Department of Computer Science and Engineering
Syllabus for M.Sc. Degree
Session: 2007 - 2008
M.Sc. Examination: 2008
The Master of Science (M.Sc.) Courses in Computer Science and Engineering
(CSE) are of one academic year and is not more than three academic years from the
date of first admission. A student will study of 8 Units and 32 Credits with total 800
Marks. The courses have been designed for two groups: General (G) and Thesis (T).
The courses for the groups are distributed as follows:
Courses for General Group
Courses for Thesis Group
Theoretical Courses
Same as for G
Tutorial
Same as for G
General Viva-Voce
Same as for G
Practical and Project
Thesis and Viva-Voce on thesis
The detail distribution of Courses along with Title, Marks, Units, Credits and
Duration of Examinations are depicted below.
Distribution of Courses with Title, Marks etc.:
Courses
Marks
Unit
Credits
Duration of
Examination/
Hours
75
0.75
3
4
75
0.75
3
4
75
75
75
0.75
0.75
0.75
3
3
3
4
4
4
75
75
0.75
0.75
3
3
4
4
a. Theoretical courses for both General
and Thesis Groups:
Compulsory courses:
CSE 501: Pattern Recognition and
Computer Vision
CSE 502: Advanced Networking and
Network Security
CSE 503: Data Mining and Warehousing
CSE 504: Embedded Systems
CSE 505: Advanced Web Engineering
Optional courses: (One course should
be selected from the following courses)
CSE 506: Human Computer Interaction
CSE 507: Advanced Software
Engineering
2
M.Sc. Syllabus, Session: 2007-2008
Courses
Marks
Unit
Credits
CSE 508: Computer Animation and
Virtual Reality
CSE 509: Robotics and Computer Vision
CSE 510: Decision Support System
CSE 511: Knowledge Engineering
75
0.75
3
Duration of
Examination/
Hours
4
75
75
75
0.75
0.75
0.75
3
3
3
4
4
4
CSE 512GT: Tutorial
CSE 513GV: General Viva Voce
b. Practical Experiments and Project
for General Group:
50
100
0.5
1.0
2
4
-
25
25
0.25
0.25
1
1
3
3
25
0.25
1
3
25
25
0.25
0.25
1
1
3
3
25
0.25
1
3
25
0.25
1
3
25
0.25
1
3
25
0.25
1
3
25
0.25
1
3
25
0.25
1
3
Compulsory Labs: (CSE 514P)
CSE 514P(A): Pattern Recognition Lab.
CSE 514P(B): Advanced Networking &
Network Security Lab.
CSE 514P(C): Data Mining and
Warehousing Lab.
CSE 514P(D): Embedded Systems Lab.
CSE 514P(E): Advanced Web
Engineering Lab.
Optional Labs: (CSE 515P)
(One course should be selected from the
following courses)
CSE 515P(A): Human Computer
Interaction Lab
CSE 515P(B): Advanced Software
Engineering Lab.
CSE 515P(C): Computer Animation and
Virtual Reality Lab.
CSE 515P(D): Robotics and Computer
Vision Lab.
CSE 515P(E): Decision Support System
Lab.
CSE 515P(F): Knowledge Engineering
Lab.
CSE 516J: Project
c. Thesis Group:
CSE 517Th: Thesis
CSE 518V: Viva Voce
50
0.5
150
50
1.5
0.5
6
2
Grand Total
800
8
32
3
6
-
Dept. of CSE, University of Rajshahi
Brief Ordinance for M.Sc. Degree, The faculty of Science, University of
Rajshahi,
Master of Science (M.Sc.)
Admission Requirements:
For admission to the M.Sc. course in CSE Department a student must have the
following qualifications:
The Bachelor of Science with Honours Degree of four years duration of this
University or of a recognised University in the CSE or similar subject. A
maximum of two years’ break of study after passing B.Sc. Honours Examination
shall be allowed.
The number of seats in CSE Department will be determined by the CSE Academic
Committee based on facilities available in the Department. Admission will be on the
basis of merits (and if necessary), through admission test to be decided by the CSE
Department.
Eligibility for examination:
In order to be eligible for taking the M.Sc. Examination, a candidate must have
pursued a regular course of study by attending not less than 75% of the total number
of classes held (theoretical, practical, tutorials etc.) provided that the Academic
Committee of the CSE Department on special grounds and on such documentary
evidence, as may be necessary, may recommend to the Vice-Chancellor cases of
shortage of attendance ordinarily not below 60% for condonation. A candidate
appearing in the examination under the benefit of this provision shall have to pay in
addition to the examination fees, the requisite fee prescribed by the Syndicate for the
purpose.
A candidate, who failed to appear at the examination or fails to pass the
examination, may on the approval of the relevant Department be readmitted to the
following session.
Pass Marks:
(a) The credit points achieved by an examinee for a 0.25, 0.5, 0.75 and 1.0
unit course will be 1, 2, 3 and 4, respectively, on securing 25% marks or
more and 40% marks or more in the relevant Theory courses and
Practical/Project/Dissertation/In-Plant Training etc, respectively.
In order to pass the Master of Science Examination in CSE, a candidate
must obtain (i) at least 30% (33% for Mathematics) of the total marks in
theory papers, Tutorials, Viva voce, (ii) 40% marks in Practical,
Dissertation, In_Project (iii) 36% marks in the aggregate and (iv) 24 credit
points. A score of less than 25% marks in any Theory course. Tutorial,
Viva voce, and less than 40% marks in Practical. Thesis/Dissertation.
Project shall not be counted.
4
M.Sc. Syllabus, Session: 2007-2008
(b) The gradation of the results shall be as follows:
Average 60% marks and above
: First Class
Average 45% marks (but below 60%)
: Second Class
Average 36% marks (but below 45%)
: Third Class
A student who marginally gets a Second class or Third class may be given
grace marks to improve the result. The Examination Committee may
recommend maximum of 3 marks for improving results of a candidate from the
Second Class to First Class and a maximum of 5 marks for improving the
results from Third Class to the Second Class. The grace mark should clearly be
shown in the Tabulation sheet.
Names of candidates placed in the First and Second Class shall be arranged in
order of merit and those placed in the Third Class shall be arranged in
accordance with their examination roll numbers in the list of successful
candidates.
Improvements of Results:
A student obtaining a Third Class in M.Sc. Final Examination may be allowed to
improve his/her result once as irregular candidate under the following
conditions:
(a) A student willing to improve his/her result shall be required to sit for the
improvement Examination in all Courses (except Tutorials) with regular
students within five years from the date of publication of his/her result.
Previous marks for Tutorials shall remain valid.
(b) A student shall be allowed to appear in examination of those courses
(maximum 4 units) having marks less than 45% to improve his/her result
in the next immediate batch by paying special fee determined by the
Syndicate.
(c) A candidate appearing at the improvement examination shall not be
awarded grace marks to improve the Degree and shall not be placed in the
merit list.
(d) If a student fails to improve the Degree the previous results shall remain
valid.
References
1:
2:
3:
4:
AC No. 221, date: 21-05-2008
Extra ordinary Syndicate, date: 05-06-2008
AC No. 209, date: 14-09-2004
Syndicate No. 388, date: 23-09-2008
5
Dept. of CSE, University of Rajshahi
Detail Syllabus for M.Sc. Program
CSE 501: Pattern Recognition and Computer Vision
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Introduction: Pattern and feature, Problems in pattern recognition, Design concepts
and methodologies, Classification techniques, Minimum distance pattern classifier,
Training and learning in Pattern recognition approaches-Neural pattern recognition,
Pattern recognition tasks by feed forward neural networks.
Statistical Pattern Recognition: Gaussian model-Supervised learning-Parametric
and non-Parametric estimation-Maximum likelihood estimation-Bayesian
parameters estimation-Perception algorithm-LMSE algorithm-Problems with Bayes
approach-Pattern classification by distance functions.
Cluster Analysis: Unsupervised learning-Clustering for Unsupervised learning and
classification-K-means algorithm-Hierarchical procedures-Graph theoretic approach
to pattern clustering-Validity of clustering solutions.
Syntactic Pattern Recognition: Elements of formal grammar-String generation as
pattern description-Recognition of syntactic description-Parsing-Stochastic grammar
and applications-Graph based structural representation.
Feature Extension and Recent Advances: Entropy minimization - KarhunenLoeve transformation-Neural Network structures for pattern recognitionUnsupervised learning -self organizing networks-Fuzzy pattern classifiers-Genetic
algorithms-Application to pattern recognition. Hidden Markov Model (HMM).
Biometrics system: Biometric behavioral features and physical features, person
identification system.
Computer Vision: Definition, Image formation in the eye and the camera,
Geometric camera models and calibration, color and color models, early level vision
– edge/object/shape detection, motion, mid level vision – segmentation and tracking,
model based vision.
References:
1.
E.G. Richard,
Johnsonbaugh and S. Jost
:
2.
R.O. Duda and P.E. Hart
:
3.
Morton Nadler and P.
Eric Smith
Tou and R. Gonzaler
:
4.
:
Pattern Recognition and Image Analysis,
Prentice Hall of India Private Ltd., NewDelhi110001,1999
Pattern classification and Scene analysis,
Wiley, New York, 1973
Pattern Recognition Engineering, John Wiley
and Sons, New York, 1993
Pattern Recognition Principles, Addison
Wesley, 1974
6
M.Sc. Syllabus, Session: 2007-2008
5.
Robert J. Schalkoff
:
6.
Melanie Mitchell
:
7.
8.
B. Yegnanarayana
David A Forsyth, Jean
Ponce, Prentice Hall of
India Private Ltd.
:
:
Pattern Recognition: Statistical and Neural
Approaches, John Wesley & Sons Inc.,
NewYork,1992.
An Introduction to Genetic Algorithms,
Prentice Hall of India Private Ltd., New
Delhi,1998
Artificial Neural Networks
“Computer Vision” A modern Approach
CSE 502: Advanced Networking and Network Security
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Overview of networking: Network architecture, planning and designing networks,
Protocols, TCP/IP, IPv6, Agent. Ad hoc network architecture and protocols: Blue
Tooth, IEEE802.11; Voice-over-IP, Combination of IP and ATM Technologies:
Classical IP-over-ATM, LAN emulation. Concepts and principles of client-server
architecture, networks, and distributed computing.
Client/Server and Distributed Computing: Network management and
programming in a network environment: programming with sockets in UNIX and
Windows or client-server model, including IPC, RPC, the role of the GUI and frontend development tools, middleware, two-tier and three-tier architectures, operating
systems, and database interaction. The role of standards in client-server
development, including DCE, CORBA, ODBC, COM, and OLE, along with objectoriented aspects of client-server and distributed computing.
Security: Concepts and principles of system and data security. Risks and
vulnerabilities, policy formation, controls and protection methods, database security,
encryption, authentication technologies, host-based and network-based security
issues, personnel and physical security issues, issues of law and privacy. Firewall
design and implementation, secure Internet and intranet protocols, and techniques
for responding to security breaches.
References:
1.
2.
3.
Coulouris, Jean
Dollimore, Tim
Kindberg
Amjad Umar,
Piscataway, New Jersey
:
Dieter Gollmann
:
:
Distributed Systems: Concepts and Design,
ISBN: 0201619180; Edition: 3rd, 2000;
Publisher: Addison Wesley Longman Inc
Object-Oriented
Client/Server
Internet
Environments, Author: Edition: 1st Edition;
ISBN: 0-13-375544-4
Computer Security; ISBN: 0-471-97844-2;
Edition: 1999, Publisher: John Wiley and Son
Ltd
7
Dept. of CSE, University of Rajshahi
4.
Edward Amoroso
:
5.
W. Stallings
:
6.
:
7.
E. Biham and A.
Shamir
D.Denning
8.
N.Kobliz
:
:
Fundamentals
of
Computer
Security
Technology, ISBN: 0-13-108929-3; Publisher:
Prentice Hall
Cryptography and Network Security Principles
and Practice, Prentice Hall, New Jersey, 1999
Diffential Crypt analysis of the data encryption
standard, Springer Verlag, 1993
Cryptography and data security, Addison
Wesley, 1982
A course on Number theory and Cryptography,
Springer Verlag, 1994.
CSE 503: Data Mining and Warehousing
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Data Mining Introduction
Data mining-introduction-information and production factor - Data mining Vs
Query tools - Data mining in marketing - self learning computer systems - Concepts
learning - Data learning - Data mining and the data warehouse.
Knowledge Discovery Process
Knowledge discovery process - data selection - cleaning - Enrichment - Coding preliminary analysis of the data set using traditional query tools - Visualization
techniques - OLAP tools - Decision trees – Association rules - Neutral networks
Genetics algorithms - KDD (Knowledge Discover in Databases) environment.
Data Warehouse - Architecture
Data warehouse architecture - System process - Process architecture - Design Database schema – partitioning strategy - Aggregations - Data marting - Meta data system and data warehouse process managers.
Hardware And Operational Design
Hardware and operational design of data warehouse - Hardware architecture Physical layout - Security -Backup and recovery - Service level agreement Operating the data warehouse.
Planning, Tuning and Testing
Capacity planning - Tuning the data warehouse - testing the data warehouses - Data
warehouse features.
References:
1.
Pieter Adriaans, Dolf
Zantinge
:
Data Mining, Addison Wesley, 1996
8
M.Sc. Syllabus, Session: 2007-2008
2.
Sam Anahory,
Dennis Murray
:
Data Warehousing in the real world, Addison
Wesley, 1996
CSE 504: Embedded Systems
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Embedded System: Introduction to embedded systems, Example, Typical
Hardware needs of a software Engineer, Timing Diagrams, Memory
Advanced Hardware, DMA, Interrupts, Built-ins on the Microprocessor, Schematics
Interrupt and shared data problem, interrupt latency
Survey of Software architectures, Round Robin, Function queues scheduling
architecture, real time operating system architecture. Semaphore and shared data
Embedded software development tools.
Microcontroller programming: Architecture of microcontroller of 8051 family,
programming model, register, Instruction set, Enhanced 8051 Features, Application
Design..
Hardware description using VHDL/Verilog HDL: Dataflow, Behavioral,
structural, mixed style of design, Language Elements, Compiler directives, Value
set, data types, Expressions
Gate level Modeling, MOS Switches, Master slave flip flop example, user defined
primitives, sequential and combinational UDP Models
Data flow model, Timing controls, block statement, procedural assignments,
looping, handshaking example
Structural Models, ports, tasks, functions, display and file I/O tasks
Verification, Test bench examples, Modeling synchronous logic, shift registers
References:
1.
2.
3.
4.
Donovan
J Bhaskar
Samir Palnitkar
David E Simon
:
:
:
:
5.
6.
Douglas Perry
Kenneth
J.
Ayata
Myke Predko
:
:
7.
:
Systems Programming, McGraw-Hill, 1987
A VHDL Primer, BS Publications
Verilopg HDL, Pearson
An Embedded Software Premier, Pearson Education
Asia
VHDL, Tata McGraw Hill Edition
The 8051 Microcontroller, Thomson and Delmar
Learning
Programming and Customizing 8051 Microcontroller,
McGraw-Hill
9
Dept. of CSE, University of Rajshahi
CSE 505: Advanced Web Engineering
Lecture: 45 (Hours), Credit:3, Full Marks: 75
ASP.NET programming model, Web development in Microsoft Visual Studio .NET,
Anatomy of an ASP.NET page, ASP.NET core server controls, ADO.NET data
providers, ADO.NET data containers, The data-binding model, report design using
crystal report, Master page, user role, linq, website security, DAL , BLL, SQL
server.
PHP: dealing with forms, HTTP authentication with PHP, cookies, sessions, using
remote files, persistent database connections, smarty, mambo, joomla, ADODB.
Ajax, XML, DOM, WML.
References:
1.
Dino Esposito
:
2.
Matt J. Crouch
:
3.
Jesus Castagnetto,Harish Rawat,
Sascha Schumann, Chris Scollo
and Deepak Veliath
Leon Atkinson
:
4.
:
Programming Microsoft ASP.NET
2.0
ASP.NET and VB.NET web
programming
Professional PHP Programming,
Wrox Publications
Core PHP Programming, Prentice
Hall PTR
Optional Courses
CSE 506: Human Computer Interaction
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Foundations:
The human: introduction, input-output channels, human memory, reasoning and
problem solving, Psychology and the design of interactive systems.
The computer: introduction, text entry devices, positioning, pointing and drawing
devices, display devices, devices for virtual reality and 3D interaction, physical
controls, sensors and special devices, paper printing and scanning, Memory.
The Interaction: introduction, models of interaction, terms of interaction, the
execution evaluation cycle, the interaction framework, ergonomics: - arrangement of
controls and displays, the physical environment of interaction, health issues, the use
of color, different types of interaction styles, element of WIMP interface.
Paradigms: introduction, paradigms for interaction.
10
M.Sc. Syllabus, Session: 2007-2008
Design Process:
Interaction design basics: introduction, what is design, the process of design, user
focus, scenarios, navigation design, screen design and layout, iteration and
prototyping.
HCI in the software process: introduction, the software life cycle, usability
engineering, interactive design and prototyping, design rationale.
Design rules: introduction, principles to support usability, standards, guidelines,
golden rules and heuristics, HCI patterns.
Implementation support: introduction, elements of windowing systems,
programming the application, using toolkits, user interface management system.
Universal design: introduction, universal design principles, multi-modal interaction,
designing for diversity.
Models and Theories:
Cognitive models: introduction, goal and task hierarchies, linguistic models, the
challenge of display-based systems, physical and device models, and cognitive
architectures.
Socio-organizational Issues and stakeholders Requirements: introduction,
organizational issues, and capturing requirements.
Communication and collaboration models: introduction, face
communication, conversation, text-based communication, group working
to
face
Task Analysis: introduction, task decomposition, knowledge based analysis, entityrelationship based technique, sources of information and data collection, uses of task
analysis.
Dialog notation and design: what is dialog, dialog design notations, diagrammatic
notations, textual dialog notation, dialog semantics, dialog analysis and design.
Application Areas:
Groupware: introduction, groupware systems, computer mediated communication,
meeting and decision support systems, shared applications and artifacts, framework
for groupware, implementing synchronous groupware.
CSCW and social issues: introduction, face-to-face communication, conversation,
text-based communication, and organizational issues.
Hypertext, multimedia and the World Wide Web: introduction, understanding
hypertext, finding things, web technology and issues, static web content, dynamic
web content.
References:
1.
Dix, Finlay, Abowd
& Beale
:
Human Computer Interaction, 3rd
Prentice Hall
11
edition,
Dept. of CSE, University of Rajshahi
2.
Ben Shneiderman
:
3.
Suchman
:
4.
:
5.
Newman and
Lamming
Monk & Wright
6.
Jordan, Patrick
:
:
Designing the user Interface: Strategies for
Effective Human Computer Interaction, ISBN: 074840-762-6, Addison-Wesley, 3rd Edition, 1998
Plans and Situated Action: The Problem of
Human - Machine Communication, Cambridge
University Press, 1987
Interactive Systems Design, Addison Wesley,
1995
Improving Your Human-Computer Interface,
Prentice Hall, 1993
Introduction to Usability, ISBN: 0-74840-762-6,
Taylor and Francis, Levittown, PA, 1998
(Paperback)
CSE 507: Advanced Software Engineering
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Introduction and review:
Software quality assurance – quality, quality plan, quality metric, validation &
verification, Introduction to ISO-90000 practices for Software Quality Assurance
Software Testing – Purpose, test case and expected output, test coverage, testing of
various areas: unit, domain, path, equivalent class based portion, component,
aggregation, system testing, requirement based testing, acceptance testing. Test
reporting, bug fixing, regression and stress testing, testing for performance, security,
installation recovery, configuration sensitivity capture/reply, report data base, test
automation.
Software project Management-Software, metrics estimation, planning, software
tools, change management and version release assessment, software valuation.
Software Maintenance – Maintainability, documentation to facilitate maintenance,
reverse engineering.
Software reuse – measuring software reuse, reuse matrices, economic model, life
cycle & reuse assessment for continuing corporate business activity.
Industrial practice in Software Engineering – software integration, systems
installation/generation, and commissioning including parameter tuning for various
end users, training by software developers to the marketing & customer support
services personnel, ISO-9000 Certified Quality Assurance Program.
References:
1.
Wilson
:
Software Architecture: Prospective on an Emerging
Discipline
12
M.Sc. Syllabus, Session: 2007-2008
CSE 508: Computer Animation and Virtual Reality
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Computer Animation
Introduction
Perception, The Heritage of Animation: Early Devices, The Early Days of
"Conventional" Animation, Disney, Contributions of Others, Other Media for
Animation, Principles of Animation, Principles of Filmmaking; Animation
Production: Computer Animation Production Tasks, Digital Editing, Digital Video;
A Brief History of Computer Animation.
Technical Background
Spaces and Transformations: The Display Pipeline, Homogeneous Coordinates and
the Transformation Matrix, Compound Transformation: Concatenating
Transformation Matrices, Basic Transformations, Representing an Arbitrary
Orientation, Extracting Transformations from a Matrix, Description of
Transformations in the Display Pipeline, Round-off error considerations; Orientation
Representation: Fixed Angle Representation, Euler Angle Representation, Angle and
Axis Representation;
Interpolation and Basic Techniques:
Interpolation: The appropriate function: Controlling the motion along curve,
Computing Arc length, Speed control, ease-in/ease-out, General distance time
functions, Path following: Orientation along path, Smoothing a path, Determining a
path along a surface; Key frame systems, Animation Languages: Artist oriented
animation language, Articulation variables, Graphical languages, Actor based
animation languages; Deforming objects: Warping an object, Coordinate grid
deformation, Morphing (2D): coordinate grid approach, feature based approach; 3D
shape interpolation.
Advanced Algorithms:
Automatic camera control, Hierarchical kinematics modeling: Representing
hierarchical models, Forward kinematics, local coordinate frames, Inverse
kinematics, Rigid body simulation: Bodies in free fall, Bodies in contract; Enforcing
soft and hard constraints: Flexible objects, virtual springs, energy minimization,
space time constraints: Controlling groups of objects: particle system, flocking
behavior, Autonomous behavior; Implicit Surface;
Virtual Reality
Basics of Designing Virtual Reality Systems
Introduction: What Is Virtual Reality? Goals and Applications of Virtual Reality,
Pillars of VR: Presence and 3D Multimodal Interaction Building a Virtual Reality
System
Requirements Engineering and Storyboarding, Ship Simulator Design,
13
Dept. of CSE, University of Rajshahi
Object and Scene Modeling: Object Modeling, Scene Construction, Object
Placement, Multiple Frames of Reference, Re-Expressing Coordinates, Function and
Behavior Modeling, Ship Simulator Example Revisited
Putting It All Together: Ship Simulator, Level 2 Design,
Performance Estimation and System Tuning, Tuning with LOD Models,
Presence/Special Effects, Using Images and Textures.
References:
1.
Rick Parent
:
2.
Gerard Jounghyun
Kim
:
3.
Alan Watt and
Mark Watt
Howard Rheingold
:
4.
Computer Animation: Algorithms and Techniques
Publisher: MKP (Morgan Kaufmann Publishers)
Designing Virtual Reality Systems: The Structured
Approach
Publisher: Springer
Advanced Animation and Rendering Techniques
:
Virtual Reality: The Revolutionary Technology of
Computer-Generated Artificial Worlds
CSE 509: Robotics and Computer Vision
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Robotics manipulation direct kinematics: The arm equation, inverse Kinematics:
Solving the arm equation, work space analysis and trajectory planning differential
motion and static manipulator dynamics, robot control, task planning.
Relationship between image and world structure, image representation,
segmentation, pattern perspective transformation, camera calibration, shape analysis,
object recognition and picture languages.
References:
1.
Robert J Schillin
:
Fundamentals of Robotics: Analysis and Control
CSE 510: Decision Support System
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Introduction to Decision support system (DSS), Decision making models, Underlayer framework for DSS, Hardware and Software for DSS, Use of decision tools.
Developments of DSS, issues of model management and interface design, DSS
applications: Executive information system (EIS), Computer mediated
communication within an organization and special aspects.
14
M.Sc. Syllabus, Session: 2007-2008
References:
1.
2.
3.
Bonczek R. H, Holsapple C.
W. & Whinston A. B
Moove J. H. & Change M. G.
Cadson E. D.
:
Foundations of Decision Support System
:
:
Design of Decision Support Systems
An Approach for Designing Decision
Support Systems
CSE 511: Knowledge Engineering
Lecture: 45 (Hours), Credit:3, Full Marks: 75
Knowledge Engineering Basic Knowledge Representation and Utilization:
Production Systems (PS), Semantic Networks, Frames, Logic, Object-Oriented
Paradigm, Logic Programming, Neural nets. Incomplete Knowledge and NonMonotonic Logic. Uncertain Knowledge: Bayesian Probability Theory, DempsterShafer Theory, Fuzzy Set Theory.
Application Diagnosis. Knowledge Acquisition and Machine Learning: Problems of
and Approaches to Knowledge Acquisition, Knowledge Acquisition Support
Systems, Machine Learning. Meta - reasoning and Meta-knowledge. Knowledge
System Development Environment: Al languages, Shells.
References:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Aleksander, H. Morton
(1990)
P. Hayes Roth, A. Waterman
and B. Lenat (1983)
A. Barr and E. A.
Feigenbaum
P. Harmon and D. King,
(1985)
Kowalski (1979)
J. W. Lloyd (1984)
C.V. Negoita (1985)
M . R. Genesereth, N. T.
Nilsson (1987)
Indea Pearl (1988)
:
An Introduction to Neural Computing
:
Building Expert Systems
:
The Handbook of Artificial Intelligence,
Vols. I-IV
Expert Systems: Artificial Intelligence in
Business
Logic for Problem Solving
Foundation of Logic Programming
Expert Systems and Fuzzy Systems
Logical Foundation of AL
:
:
:
:
:
:
Probabilistic Reasoning in Intelligent
Systems: Networks of Plausible Inference
15