Detail Syllabus MSc CSE : The People's University of Bangladesh

The People's University of Bangladesh

( Govt. & UGC Approved Private University, Established : 1996 )

3/2, Asad Avenue, Mohammadpur, Dhaka-1207

MSc in CSE

COURSE DESCRIPTION

MSCE 5001: Graph Theory 3.00 Credits

Introduction of graphs and graph theory, definitions & notation of graphs, spanning subgraphs, special graphs, trees, directed trees, counting trees, counting spanning trees of a labeled graph, searching techniques, shortest-paths, single-source single­ destination problem, single-source multiple-destination problem, multiple source­ destination problem, maximum flow, applications of maximum-flow, graph connectivities, connectivity generalizations, matching.

MCSE 5003: Parallel Algorithms 3.00 Credits

Fundamentals: Introduction to parallel and distributed computing, models of parallel computers, parallel programming models, Design methodology for parallel algorithms, Basic communication operations, introduction to MPI, Performance evaluation of parallel systems, Performance metrics, execution time, speedup, efficiency, cost, scalability and cost effectiveness, Sorting algorithms: Sorting on parallel computers, sorting networks, bubble sort, quick sort and other sorting algorithms, Graph algorithms: Definitions and representation, minimum spanning tree, single source shortest paths, all pairs shortest paths, transitive closure, connected components, algorithms for sparse graphs, Dense matrix algorithms: Mapping matrices on processors, matrix transposition, matrix vector multiplication, matrix multiplication, solving systems of linear equations.

MCSE 5005: Advanced Artificial Intelligence 3.00 Credits

Introduction to Al, Reasoning, Automating reasoning: formal inference, Correct & exhaustive reasoning, Constraint satisfaction search, Problem solving search, Automated planning, General first order representation, Planning in logic, First order inference, Prolog, Interpreting, Automating interpretation systems, Probability modeling, Structured probability models, Efficient probabilistic inference, Inference in complex models, Interpreting senses (perception), Interpreting natural language, Behaving, Optimal behavior: Decision theory, Optimal sequential decision making, Optimal behavior: Game theory, Scaling up: Partial observability, Robotics and control, Learning, Types of learning problems, Function learning algorithms, Generalization theory / Over fitting, Neural Networks.

MCSE 5007: Machine Learning 3.00 Credits

Introduction, Learning to predict, Linear prediction, Generalized linear prediction, Neural networks, Regularization, Learning theory: bias-variance, Automated complexity control, Learning to classify, Linear classification, Support Vector Machines, Duality, Kernel methods, Discrete classification, Computational complexity, Decision trees, Noise, Learning theory: Uniform convergence, Vapnik­Chervonenkis dimension, Probability models, Bayesian networks, Maximum likelihood estimation, Expectation-maximization algorithm, Bayesian learning, Ensemble learning methods, Boosting, Other learning problems, Unsupervised learning, Manifold learning, Reinforcement learning.

MCSE 5009: Fuzzy Logic 3.00 Credits

Introduction to Expert System and Fuzzy Logic, Fuzzy Expert Systems & Shell, Fuzzy Query, Applications, Knowledge Engineering & Acquisition (Computer Learning), Introduction to Fuzzy Control, Genetic Algorithms & Applications, Information (Data) Fusion & Data Mining, Application of Fuzzy Logic: Fuzzy applications, The Fuzzy World, Contradiction & Uncertainty, Multivalued logic & Fuzzy logic, Membership Degree of belonging, Membership Degree of membership, Fuzzy inference, Fuzzy set theory, Membership function, Many membership functions for one variable, Logic operations (pseudo Boolean algebra), Operation examples, Fuzzification (evaluating the degree of membership), Other operations, Fuzzy inference rules, Sum of Products, Multiple rules, Defuzzication/inference methods, Defuzzification action value, Defuzzification average weighted action value, Cut, Mamdani (COG) defuzzication aggregate, Mamdani (COG) defuzzication COG, Fuzzy calculus & function approximation, Membership function as interpolation functions (single input variable), Membership function as interpolation functions (two input variables), Fuzzy microcontroller

MCSE 5011: Data Mining 3.00 Credits

Introduction to Data mining: Data mining and knowledge discovery, application to information retrieval, text mining, search engines, character recognition, medical informatics, bioinformatics. Mining from Different Databases, Classification of Data Mining Techniques, Data Warehousing: General Principles, Modeling, Design, Implementation, and Optimization, On-Line Analytical Processing, Data Mining Primitives, Languages, and Interfaces, Concept Hierarchies, Description, Statistical Perspectives on Data Mining, Classification and Clustering, Time-Series Analysis, Deviation Detection, Sequential Patterns, Associations and Rule Generation, Genetic Algorithms, Incremental Mining, Scalability issues of Data Mining Algorithms, Visualization of Data Mining Results, High Performance Computing Applications in Data Mining.

MCSE 5013: Data Encryption and Cryptography 3.00 Credits

Introduction to Cryptography, Security, cryptanalysis (e.g., frequency analysis), Stream Ciphers, Block Ciphers, Feistel Ciphers, Multiple Encryptions, DES/AES, Hash Functions, More on Hash Functions, Data Integrity, Authentication, Assymmetric Cryptosystems, Probabilistic Primality Testing, Introduction to RSA, Security of RSA Encryption, Security of RSA Key Generation, Discrete Logarithm Cryptographic Schemes, Key Establishment, Identification Protocols, Digital Signatures, Public Key Management I, Public Key Management , Wireless Security, Internet Security, Huffman Encodings and Entropy.

MCSE 5015: Advanced Multimedia Systems 3.00 Credits

Introduction, Text and fonts, Sounds, Images, BMP & JPEG, Animation and videos, Image and video compression, describing the general properties of image and video compression using wavelet transformation, Huffman code and MPEG format for videos, Multimedia design for WWW, Multimedia through the network and the Internet, Managing multimedia project, Image Processing.

MCSE 5017: Advanced Syntactic Pattern Recognition 3.00 Credits

Introduction, Process of Classifier Design, Bayes Decision Theory – Decision Rules, The Bayes Decision Rule for Minimum Error, The Bayes Decision Rule for Minimum Cost, The Neyman-Pearson Decision Rule, The Minimax Decision Rule, Bayes Decision Theory – Error Bounds, Parametric Classifier Design, The Bayes Linear Classifier, Linear Classifier Design, Quadratic Classifier Design, Piecewise Classifier Design, Parameter Estimation, Maximum-Likelihood Estimation, Bayesian Estimation, Feature Extraction and Mapping for Representation, Redundancy Reduction – Data Reduction, Dimensionality Reduction, Feature Extraction and Mapping for Classification, Linear Discriminant Analysis, Nonlinear Discriminant Analysis – Kernel Methods, Statistical Learning Theory, Structural Risk Minimization, Support Vector Machines (SVM), Applications: Biometrics , Face Detection, Face Tracking, Face Recognition, , Nonparametric Density Estimation, Nonparametric Classifier Design, Clustering Machine Learning for Pattern Recognition, Bayesian Learning, Decision Trees, Evolutionary Computation for Pattern Recognition.

MCSE 5019: Advanced Microprocessor 3.00 Credits

The Interrupt system for the 8088/86 microprocessors, 80286 microprocessor, 80386, 80486, and Pentium software architecture and ISA bus, Hardware architecture of 80386, 80486, and Pentium, Comparison, of microprocessors, Microprocessor interface: minimal systems, expanding, address decoding, Memory and memory management, Cache memory techniques, DMA, Microprocessor architectures, Design of Memory Systems, Multi-Processing Systems, RISC Processor Based Designs and Applications, Instruction set, UO Structures of Micro Computers, Integrating Multiple Computers on Shared Resources, Self tracking and repair type of systems, Microcontroller hardware and UO, General purpose UO, timers, serial 1/0, A/D conversion, System-on-a-chip, low power issues, Low power microcontroller operation, Programming Microcontrollers.

MCSE 5021: Robotics 3.00 Credits

Introduction to robotics and its applications in industries and services, Classification of robot systems, forward and inverse kinematics associated to manipulator motion, robot design, control, sensing and programming.

MCSE 5023: Advanced Machine Vision and Image Processing 3.00 Credits

Image models, image acquisition, statistical operations, spatial operations and transformations, segmentation and edge detection, morphological and area operations, finding 2-D basic shapes, scene labeling, 3-D shape from stereo, motion, boundary, shading and texture.

MCSE 5025: Advanced Distributed Database Systems 3.00 Credits

Introduction to distributed database management, Database distribution architectures, Distributed database design, Distributed query processing, Distributed query optimization, Distributed transaction management, Distributed concurrency control, Distributed reliability protocols, Multi-database systems, Mobile distributed database management

MCSE 5027: Satellite Communication 3.00 Credits

Satellite communications systems have been developed for applications ranging from DOMSAT (domestic satellite), INTELSAT (international satellite) to VSAT (very small aperture terminal). Recent development in LEO (low-earth orbit) systems, such as Iridium and Globalstar, opens the door for personal communications through satellite systems. This course consists of three parts. The first part addresses the satellite systems covering the topics of orbits and constellations, satellite space segment, and propagation and satellite links. The second part reviews satellite communications techniques including modulation, coding, multiple access and on-board processing. The third part presents various satellite communications systems and applications with emphasis on recent development in LEO satellite systems for personal communications.

MCSE 5029: Web Programming 3.00 Credits

The World Wide Web (WWW) is the most successful by-product of the Internet. It is used daily by millions of people in order to find, manage, track, and manipulate information. Furthermore, the explosive growth of e-commerce continues as people increasingly research and purchase goods and services on-line via the WWW. In this course, we will explore the fundamental principles and technologies behind the WWW including both how information on the WWW is generated, represented, transmitted, and manipulated. The course will concentrate on key client-side and server-side technologies that are essential for dynamic content generation and interactivity. The course is intended for majors in Computer Science and is a prerequisite for COMP 118, which explores more advanced WWW techniques. Motivated non-majors are welcome, but some experience with programming is highly recommended.

MCSE 5031: Bio- informatics 3.00 Credits

Within the last 20 years there has been a literal explosion in the quantity and variety of information in molecular biology. In order to cope with this ocean of data, molecular biologists have had to develop new tools that rely heavily on the power of statistics and computing yet still incorporate an understanding of the underlying biological principles. The development and application of these tools in conjunction with assembled databases of biological information has become a field of its own, known as either Bio-informatics or as Computational Biology. In the sister courses Bio-informatics I and Bio-informatics II, we explore the principles underlying the analyses of sequence and molecular databases and work to provide students with the understanding and practical experience for intelligent and efficient application of these tools. In part one; we focus primarily on the analysis of nucleic acid sequences. In part two, we expand these studies to include gene prediction, protein function and structure studies and analysis of whole genomes. Both of these courses are core components of the Interdepartmental Master’s Degree in Bio-informatics. In addition, they are open to any graduate student with relevant experience in molecular biology. This course does assume that the student has some familiarity with both basic molecular biology and with the use of computers and the Internet

MCSE 5033: Advanced Mobile Cellular Communication 3.00 Credits

Wireless communication is fundamentally the art of communicating information without wires. In principle, wireless communication encompasses any number of techniques including underwater acoustic communication, semaphores, smoke signals, radio communication, and satellite communication, among others. The term was coined in the early days of radio, fell out of fashion for about fifty years, and was rediscovered during the cellular telephony revolution. Wireless now implies communication using electromagnetic waves — placing it squarely within the domain of electrical engineering. This brings us to the course at hand. Wireless communication techniques can be classified as either analog or digital. The first commercial systems were analog including AM radio, FM radio, television, and first generation cellular systems. Analog communication is gradually being replaced with digital communication. The fundamental difference between the two is that in digital communication, the source is assumed to be digital. Every major wireless system being developed and deployed is built around digital communication including cellular communication, wireless local area networking, personal area networking, and high-definition television. Thus the spotlight of this class will focus on digital wireless communication.

MCSE 5035: Management Information System 3.00 Credits

Integrates topics of management and organization theory, information and communication theory, and systems theory relevant to managing an organization’s information resources. Includes computer hardware and software, telecommunications, and database concepts and emphasizes the e-commerce and Internet based business models to get a competitiveness of global based business environments. This course meets the requirements for a Technology Intensive course.

MCSE 5037: Advanced Logic Design 3.00 Credits

Functional decomposition and Symmetric functions; Linear sequential machines; Reed-Muller expansions and their minimizations; Ex- or based logic design; self-timed circuits; asynchronous design techniques; Digital logic circuit testing and testable design: testing of combinational and sequential logic circuits, design for testability and built-in self test; Digital logic simulation.

MCSE 5039: Advanced Database System 3.00 Credits

Object Oriented Database; Data Model, Design, Languages; Object Relational Database: Complex data types, Querying with complex data types, Design; Distributed Database: Levels of distribution transparency, Translation of global queries to fragment queries, Optimization of access strategies, Management of distributed transactions, Concurrency control, Reliability, Administration; Parallel Database: Different types of parallelism, Design of parallel database; Multimedia Database Systems Basic concepts, Design, Optimization of access strategies, Management of Multimedia Database Systems, Reliability; Database Wire-housing/Data mining: Basic Concepts and algorithms

MCSE 5041: Speech Recognition 3.00 Credits

Introduction, Speech signal: production, perception and characterization, Signal processing and analysis; Pattern comparison techniques: distortion measures, spectral-distortion measures, time alignment and normalization; Recognition system design and implementation: source-coding, template training, performance analysis; Connected word models: two level DP, level building algorithm, one-pass algorithm; Continuous speech recognition: sub word units, statistical modeling, context-dependent units; Task oriented models.

MCSE 5043: Neural Network 3.00 Credits

Fundamentals of Neural Networks; Back propagation and related training algorithms; Hebbian learning; Cohonen-Grossberg learning; The BAM and the Hopfield Memory; Simulated Annealing; Different types of Neural Networks: Counter propagation, Probabilistic, Radial Basis Function, Generalized Regression, etc; Adaptive Resonance Theory; Dynamic Systems and neural Control; The Boltzmann Machine; Self-organizing Maps; Spatiotemporal Pattern Classification, The Neocognition; Practical Aspects of Neural Networks.

MCSE 5045: Elements of Cryptography 3.00 Credits

Classical Cryptography: Introduction to simple cryptosystems, Cryptanalysis; Shannon’s Theory: Perfect secrecy, Entropy, Product cryptosystems; Data Encryption Standard: Description of DES, Differential cryptanalysis; RSA System and Factoring: Public-key cryptography, RSA cryptosystem, Attacks on RSA, Factroing algorithms; Other Public-key cryptosystems: ElGamal cryptosystem and discrete logs, Merkle-Hellman Knapsack System; Signature Schemes: ElGamal signature schemes, Digital signature standard, Fail-stop signatures; Hash Functions: Signatures and Hash functions, Collision-free Hash functions, Birthday attack; Key Distribution and Key Agreement: Key predistribution, Kerboros, Diffie-Hellman key exchange; Identification Schemes: Schnorr identification scheme, Okamoto identification schemes; Authentication Codes: Computing deception probabilities, Combinatorial bounds, Entropy bounds; Secret Sharing Schemes: Shamir threshold scheme, Access structure and general secret sharing; Pseudo-random Number Generation: Indistinguishable probability distribution, probabilistic encryption; Zero-knowledge proofs: Interactive proof systems, computational Zero-knowledge proofs.

MCSE 5047: Computer Graphics and Animation 3.00 Credits

Advanced Graphic Techniques: Graphics basics, Three dimensional drawings, Geometric forms and models, Hidden surfaces, Fractals; Advanced rendering Techniques: Shadow generation techniques, Texture and environment mapping techniques, Procedural texture mapping and modeling, Ray tracing, Radiosity methods, Global illumination models, Volume rendering techniques; Advanced Animation: Animation articulated structures, Soft object animation, Procedural animation.

MCSE 5049: Mathematical Programming 3.00 Credits

Basic concept of Mathematical Programming, Concepts of linear and quadratic programming, Convexity, Convex sets and convex functions, Concept of integer programming, Some examples of integer programming problems, Linear programming techniques, Graphical solution of linear programming problems, Simplex method, Dual simplex method, Different integer programming techniques, Revised simplex method.

MCSE 6000: Thesis (18 credit hours for thesis group)/Project or Industrial Attachment (9 credit hours for non-thesis group).

Depend on Thesis or Project/Industrial Attachment supervisor.

EXAMINATION AND EVALUATION:

There will be a final examination generally 2 weeks after the teaching session of each course. Normally, the duration for the examination is 3 hours.

APPLICATION PROCEDURES:

Applicants are required to submit an application form to the Department of CSE, PUB. Upon evaluating the applications, the department will invite selected applicants for interview. The application form can be obtained from the CSE Department, PUB.

GRADING SYSTEM:

Numerical Grade

Letter Grade

Grade Point

80% or above

A+

4.00

75% to less than 80%

A

3.75

70% to less than 75%

A-

3.50

65% to less than 70%

B+

3.25

60% to less than 65%

B

3.00

55% to less than 60%

B-

2.75

50% to less than 55%

C+

2.50

45% to less than 50%

C

2.25

40% to less than 45%

D

2.00

Less than 40%

F (Fail)

0.00

ASSESSMENT SYSTEM:

Attendance

10%

Mid Term

20%

Quiz, Surprise/ Class test (5+5)

10%

Assessment

10%

Final

50%

Total

100%

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