BS in Computer Science Curriculum The breakdown of the total 132 credits and degree requirements is given as follows:

Degree Core Courses 93 Credits

GED Courses 18 Credits

Electives 12 Credits

Open Electives 9 Credits

Total 132 Credits

Degree core courses (93 credits):

Courses Titles Credits

CSE 115 Computing Concepts 3

CSE 115L Computing Concepts Lab 1

CSE 135 Fundamentals of Computer Programming 3

CSE 135L Fundamentals of Computer Programming Lab 1

CSE 173 Discrete Mathematics 3

CSE 225 Data Structures 3

CSE 225L Data Structures Lab 1

CSE 231 Digital Logic 3

CSE 232 Computer Organization and Design 3

CSE 273 Introduction to Theory of Computation 3

CSE 257 Numerical Methods 3

CSC 281 Introduction to Digital Electronics 3

CSC 311 Database Systems 3

CSE 323 Operating Systems Design 3

CSC 325 Programming Language Principles 3

CSC 326 Compiler Construction 3

CSC 327 Software Engineering 3

CSE 331 Microprocessors and Assembly Language Programming

3

CSE 338 Computer Networks 3

CSC 348 Artificial Intelligence 3

CSC 373 Design and Analysis of Algorithms 3

CSC 382 Internet & Web Technology 3

CSE 498/499 Internship / Project 3

MAT 116 Pre-Calculus 3

MAT 120 Calculus and Analytical Geometry I 3

MAT 125 Introduction to Linear Algebra 3

MAT 130 Calculus and Analytical Geometry II 3

MAT 240 Calculus and Analytical Geometry III 3

MAT 250 Calculus and Analytical Geometry IV 3

MAT 361 Probability and Statistics 3

PHY 107 General Physics I 3

PHY 108 General Physics II 3

CHE 101 General Chemistry 3

BIO 210 Introduction to Molecular Biology 3

Total Credits 93

General Education courses (18 credits):

The university requirement for the GED courses is 27 credits. A total of 9 credit comprising 3 credits each in Computer Science, Mathematics and Science are fulfilled in the core requirement. Therefore, students take only 18 credits of GED including:

ENG 103 Intermediate Composition

ENG 105 Advanced Writing Skills

ENV 107/ENV 214 Environmental Science/Environmental Management

GED Any 3 courses (9 credits) from the approved list of GED courses

Specialized Courses and Open Electives (21 Credits):

Students must choose any one of the following Trails:

(a) Minor in other subject Trail

A student may find it attractive to choose 21-credit Minor in Computer Engineering tract specially designed for the student of Computer Science program. There will be no open electives left but has to take 3 credits extra to fulfil the minor in CEG track.

(b) Minor in other subject Track

A student may choose to follow the minor program in BBA, Economics, English, Environmental studies or Mathematics. Any credits remaining should be filled by open electives. Students choosing this option must bring a confirmation from the respective Academic Department indicating the fulfillment of the minor requirements.

(c) MIS Trail

MGT 210 Principles of Management CSC 410 Management of Information Technology MIS 440 Introduction to Management Information System MIS 460 Management Support Systems MIS 470 Systems Analysis and Design

(d) CSE Electives Track

Students must take any 4 CSC courses from the list below. The remaining 3 courses are open electives. In addition; any 400-level course from the CSE, CEG and ETE Curriculum will be counted towards CSC Electives.

CSE 410 Management of Information Technology

CSE 411 Advanced Database Systems

CSE 412 VLSI Chip Design with Programmable Logic Device

CSE 413 Verilog-HDL: Modeling, Simulation

CSE 414 Advanced VLSI Chip Design

CSE 418 Computer Graphics

CSE 419 Data Mining

CSE 423 Advanced Operating Systems

CSE 424 Object Oriented Software Development

CSE 425 Programming Languages Principles

CSE 426 Advanced Compiler

CSE 427 Software Quality Assurance

CSE 430 Formal Methods in Software Engineering

CSC 433 Computer Architecture

CSE 434 Feedback Control Systems

CSE 435 Introduction to VLSI Design

CSE 436 Industrial Electronics and Instrumentation

CSE 437 Fundamentals of Telecommunications

CSE 438 Networks and Distributed Systems

CSC 439 Computer Networks II

CSE 441 Symbolic Logic

CSE 444 Artificial Intelligence

CSE 445 Machine Learning

CSE 446 Introduction to Bioinformatics

CSE 447 Functional Bioinformatics

CSE 448 Neural Networks

CSE 451 Genetic Algorithm

CSE 456 Petri Nets

CSE 457 Numerical Analysis

CSE 461 Cryptography

CSE 463 Integrated Circuit Logic Design

CSE 465 Pattern Recognition

CSE 467 Image Processing.

CSE 468 Computer Vision

CSE 470 Theory of Fuzzy Systems

CSC 472 Advanced Algorithm

CSE 473 Parallel Processing

CSE 474 Computational Complexity

CSE 475 Automata Theory and Formal Languages

CSE 478 Graph Theory

CSE 485 Digital Signal Processing

CSE 487 Microprocessor Based System Design

CSC 492 Mobile and Wireless Communication System

CSE 497 Special Topics

Course Description

BS-CSC Core and Elective Engineering Courses

CSE 115: Computing Concepts

The first course for computer science majors and other students with a deep interest in the subject. The course introduces such fundamental concepts in computing as data abstraction, algorithms, dynamic data structures, and complexity theory. Implementation is done in a formalized pseudo code only. An introduction to ethics in computer science including philosophical ethics theories. 4 credits (Theory 3 + Lab 1 credit).

CSE 135: Fundamentals of Computer Programming

This is a more traditional programming course for computer science majors and other students with deep interest in the subject. Actual programs are constructed using one or more high level languages with emphasis placed on the concepts introduced in the previous course. Reusability, readability, and documentation are also strongly stressed. Prerequisite: CSE 115 and MAT 120. 4 credits (Theory 3 + Lab 1 credit).

CSE 173: Discrete Mathematics

Introduction to discrete mathematical structures. Topics include sets, propositions, Boolean algebra, relations, functions, algebraic systems, monoids, fields, groups, ring, induction, recursion, permutations and combinations, recurrence relation, generating functions and solutions, principles of counting, principles of inclusion and exclusion, discrete probability. Prerequisite: CSE 135, CSE 225. 3 credits.

CSE 225: Data Structures & Algorithms

An introduction to the theory and practice of data structuring techniques. Topics include internal data representation, abstract data types, stacks, queues, list structures, recursive data structures, graphs and networks. Concept of object orientation as a data abstraction technique will be introduced. Prerequisite: CSE 135. 4 credits (Theory 3 + Lab 1 credit).

CSE 231: Digital Logic

Introduction to Boolean algebra and logic gates, simplification of Boolean functions, combinational and sequential logic, digital functions: decoders, encoders, multiplexers, demultiplexers; registers, counters, memory organizations. Prerequisite: CSE 225, CSE 173. 3 credits.

CSE 232: Computer Organization and Design

Design of a simple processor, control logic design: random logic and microprogramming; machine-level programming, instruction sets, data representations; subroutines; input/output hardware and software; pipelining; relation to high-level languages. Prerequisite: CSE 231. 3 credits.

CSE 243: Electrical Circuits

Formulation and solution of circuit equations, network theorems, sinusoidal steady-state analysis. Topics include loop and nodal analysis, superposition and Thevenin theorem, properties of sinusoids, phasor representation and vector diagrams. This course has mandatory laboratory sessions every week. Prerequisite: MAT 120. 3 Credits.

CSE 253: Electronics

Small and large signal characteristics and models of electronic devices; analysis and design of elementary electronic circuits. This course has mandatory laboratory sessions every week. Prerequisite: CSE 243. 3 Credits.

CSE 257: Numerical Methods

Techniques of linear algebra include system of linear equation, matrices and inverses, determinants, vector spaces, Eigen values and Eigen vectors. Solution of linear system: Gaussian elimination. Iterative methods: Gaussian method, inverse of a matrix by Gauss Jordan method. Interpolation and approximation: Lagrange polynomials, Newtons formula, Numerical differentiation and integration.

Prerequisite: CSE 225, MAT 125, MAT 240 3 credits.

CSE 263: Kinematics and Robotics

Vector representation of forces and moments; general three dimensional theorems of statics; free bodies; two-and three-dimensional statically determinate frames; centroids and moments of inertia of areas. Absolute motion of a particle; motion of rigid bodies; rotating axes and the Coriolis component of acceleration; Newtons laws applied to translating and rotating rigid bodies; principles of work and energy and impulse and momentum in translation and rotation; moments of inertia of masses. Prerequisite: CEG 100, PHY108 and MAT 250. 3 Credits.

CSE 273: Introduction to Theory of Computation

Theorem proving, propositional logic, first order logic, finite automata, formal languages, Turing machines, uncomputability, computational complexity and NP completeness. Prerequisite: CSE 173, CSE 225. 3 credits.

CSE 281: Introduction to Digital Electronics

Theory and operation of circuits used in digital computers including basic electrical circuit principles, diodes, bipolar and MOS transistors, digital logic circuits, memory circuits, and the fundamentals of analog circuits. Prerequisite: PHY108, CSE 231. 3 credits.

CSE 283: Electrical and Electronics Circuit Design Laboratory I

Principles of instrumentation and data analysis and the development of methods of experimental analysis for testing theories and hypotheses. Prerequisite: CSE 243. 2 Credits.

CSE 311: Database Management Systems

Examines the logical organization of databases: the entity-relationship model; the hierarchical, network, and relational data models and their languages. Functional dependencies and normal forms. Design, implementation, and optimization of query languages; security and integrity; concurrency control, and distributed database systems. Prerequisites: CSE 225. 3 credits.

CSE 323: Operating Systems Design

Operating Systems Design: An introduction to the structure of modern operating systems. Topics include operating systems structure, asynchronism, mutual exclusion, deadlocks, monitors, process state transition, interrupts, context switching, storage management for both real and virtual storage, processor scheduling, multi-processing, auxiliary storage management, computer systems performance, network and security. Prerequisite: CSE 225 and CSE 232. 3 credits.

CSC 325: Programming Languages Principles

An introduction to the structure of programming languages. Formal specification of syntax and semantics; structure of algorithmic, list processing, string manipulating, data description, and simulation languages: basic data types, operations, statement types, and program structure; macro language and their implementation; and run-time representation of programs and data. Prerequisite: CSE 225. 3 credits.

CSE 326: Compiler Construction

Compiler structure; Lexical analysis, syntax analysis grammars, description of programming languages, automatically constructed recognizers and error recovery; and semantic analysis, semantic languages, semantic processes, intermediate language, optimization techniques, and extendible compilers. Prerequisite: CSE 232 and CSE 273. 3 credits.

CSE 327: Software Engineering

Follows the software life cycle from the requirement, specification, and design phases through the construction of actual software. Topics include management of programming teams, programming methodologies, debugging aids, documentation, evaluation and measurement of software, verification and testing techniques, and the problems of maintenance, modification, and portability. Prerequisite: CSE 225. 3 credits.

CSE 331: Microcomputer Systems

Study of microprocessor architectures, hardware modules, and interfaces; programming, software tools, development systems, and applications; and microprocessor system design methodology. Prerequisite: CSE 232. 3 credits.

CSE 338: Computer Networks I

Introduction to International Standards Organization open System Interconnection (ISO-OSI) reference model, design issues and protocols in the physical layer, data link layer and network layer; architectures and control algorithms of local area networks, point-to-point networks and satellite networks; standards in network access protocols; models of network interconnection, and overview of networking and communication software: Prerequisite: CSE 232 and MAT 361. 3 credits.

CSE 348: Artificial Intelligence

An introductory description of the major subjects and directions of research in artificial intelligence; topics include all languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. Prerequisite: CSE 225 and CSE 232; or consent of instructor. 3 credits.

CSE 351: Electronics II

This course develops an in-depth knowledge of the frequency response and design methods to fix gain - bandwidth specifications in amplifier circuitry. Design use of feedback techniques is also presented in this course. Properties and design application of operational amplifies are elaborately studied. Signal generators: Basic principle of sinusoidal oscillation, different types of oscillators also included in this course. This course has mandatory laboratory sessions every week. Prerequisite: CEG 253. 3 Credits.

CSE 353: Electrical and Electronics Circuit Design Laboratory II

Principles of instrumentation and data analysis and the development of methods of experimental analysis for testing theories and hypotheses. Prerequisite: CSE 283. 2 Credits

CSE 373: Design and Analysis of Algorithms

Advanced data structures, complexity analysis, sorting and searching, graph algorithms, arithmetic algorithms, geometric algorithms, string problems, parallel algorithms, NP-Completeness. Prerequisite: CSE 273 and MAT 361 or consent of instructor. 3 credits.

CSE 382: Internet and Web Technology

The course develops an in-depth knowledge of the concepts, principles and implementation techniques related to the Internet and web technology. Details about the Internet, Intranet, Extranet, and e-commerce will be covered. Topics include Web server management, threats, security of client and server, network security like firewall, SSL, etc., authentication and authorization, legislation, privacy and IP act, electronic payment, e-business, search engine, Internet protocols like TCP/IP, SGML, XML. Design and development of Web applications using Java Applets, ASP, Java Script, CGI and other Web tools is discussed. Prerequisite: CSE 338. 3 credits.

CSE 410: Management of Information Technology

Definition of technology in the manufacturing, service and IT industry; Importance of R&D management and technology transfer; Importance of integrating technology planning, product planning, business planning and the market demands Human, social and environmental concerns associated with technological change. Case studies: (a) Lessons from successful corporations: Intel and Microsoft, (b) Applications in Bangladesh Industries: IT, software, energy, garments, telecom, and agriculture. Cross-listed with MGT410 Prerequisite: 100 credits completed. 3 credits.

CSE 411: Advanced Database

Physical data organization, design and administration including schema, normalization and relational algebra, database implementation, CODASYL implementation and network database, distributed database, database machines, DATA LOG and intelligent databases. Prerequisite: CSE 311. 3 credits.

CSE 412: VLSI Chip Design with Programmable Logic Devices. (FPGA/CPLD)

Introduction to the design and layout of Very Large Scale Integrated Circuits (VLSI). Emphasis is placed on digital CMOS circuits. Static and dynamic properties of MOSFET devices, along with integrated circuit fabrication are examined. ASIC and FPGA will be reviewed. Computer-aided design tools are used to produce working integrated circuit designs. Students will also learn to use a hardware descriptive language (VHDL) in the digital design process. This course has mandatory laboratory sessions every week. Prerequisite: ETE 411. 3 Credits.

CSE 413: Digital Microprocessor Design Laboratory

Design of digital systems with integrated circuits and MSI/LSI and microprocessor interfacing. Prerequisite: CSE 331. 2 Credits.

CSE 414: Advanced VLSI Chip Design Methodology and Optimization

This course covers rapidly developing high-tech VLSI chip design area and a flourishing field within Electronic Design Automation (EDA) tools. The course discusses advanced VLSI chip design methodology which includes physical design, system partitioning, FPGA partitioning, partitioning methods, estimating ASIC size, floorplaning, placement, physical design flow, global routing, detailed routing, special routing, circuit extraction and DRC, scan-chain design, clock-tree routing and signal-net routing. The course introduces the systematic top-down design methodology to design complex digital hardware such as FPGA, EPLD and ASIC. Verilog Hardware Description Language and sophisticated EDA tools are utilized to elaborate the material covered throughout the course. Course projects of this course will lead to open research topics. Prerequisite: CSE 413. 3 Credits.

CSE 415: VLSI Chip Testing

This course examines the theory and practice of fault analysis, test generation, and design for testability for digital circuits and systems. The topics to be covered include: circuit and system modeling, fault sources and models, fault simulation methods, test generation algorithms for combinational and sequential circuits including PODEM, testability; testability measures; design-

for-testability techniques; built-in- self-testing (BIST), processor and memory testing, design verification, quantum computing circuits. Current research issues, including topics suitable for MS or PhD research will be discussed. A term project is also part of this course. The term project will be tailored to individual student interests and involve one of the: (a) Programming a test generation or simulation algorithm covered in the course. (b) In-depth literature survey of some advanced topic. (c) Individual research into some topic or problem (d) Experimental testing of VLSI chips. (e) Experiments with commercial test and simulation CAD hardware or software. All projects will require a written report and brief oral presentation to the class at the end of the term. Prerequisite: CSE 413. 3 credits

CSE 416: Digital Integrated Circuit Technology

This course is concerned with integrated circuit fabrication, relationships between processing choices, and device performance characteristics. Also discussed will be long-channel device I-V review, short-channel MOSFET I-V characters tics including velocity saturation, mobility degradation, hot carriers, gate depletion, MOS device scaling strategies, silicon-on-insulator, lightly-doped drain structures, on-chip interconnect parasitics and performance, major CMOS scaling challenges and finally, process and circuit simulation. Prerequisite: CSE351. 3Credits.

CSE 417: Logic Circuit Synthesis and Optimization

This course is indeed to give an understanding of the theory and practical algorithms used in the synthesis of digital circuits. In the introductory logic course (CSE 231, ETE 212), students learn how to construct digital systems to perform specific tasks. This course is concerned with optimizing these systems in terms of various metrics, such as circuit size or speed. Theoretical foundations are explored side-by-side with algorithms implementing the various optimization methods. Prerequisite: CSE331. 3 Credits.

CSE 418: Computer Graphics

Topics include software, hardware, and mechanical tools for the representation, manipulation, and display of topological and two- and three-dimensional objects; applications of these tools to specific problems. Prerequisite: CSE 225, and CSE 232. 3 credits. CSE 419: Data Mining Definition of Data Mining, Data Mining Functionalities, Major Issues in Data Mining, Data Warehouse, Data Warehouse Implementation, Data Processing and Data Cleaning, Data Mining Primitives, Languages and Systems Architecture, Mining Association Rules in Large Databases: The Apriori Algorithm, Classification and Prediction: Preparing the Data for Classification, Classification by Decision Tree Induction, Bayesian Classification, Other Classification Methods, Clustering Analysis, Mining Complex Types of Data, Applications and Trends in Data Mining. Prerequisite: CSE 311 3 Credits.

CSE 421: Advanced Enterprise Java

This is more advanced object oriented programming course for computer science majors and other students with deep knowledge and interest in this subject. This course introduces in depth study of the Java Virtual Machine (JVM), client-server application architecture with Java project life cycle. This course includes multi-threaded programming, thread pool, deep cloning, java security and Java database connectivity using JDBC. It also introduces current enterprise java technology like distributed computing protocols and APIs using RMI and CORBA technology; Server frameworks and architectures using Java Servlets and Java Beans. This course includes several projects to relate students in extensive programming. Prereq. CSE 135 and CSE 338. 3 credits. 3 Credits.

CSE 422: Principles of Digital Communication

System level analysis and design for digital and analog and communications systems: analog-to-digital conversion, digital and analog modulation types, PC and delta modulations, matched filters, receiver design, link budgets, signal to noise ratios and bit error rates in noisy channels. Prerequisite: ETE 321. 3 credits.

CSE 423: Advanced Operating Systems

Studies the design and implementation of operating systems. Reviews algorithms for concurrent processes, deadlock resolution, process management, performance evaluation, and monitoring. Compares a variety of solutions to major problems in the field. Advanced topics like interprocess communication and disk drivers will also be discussed. Prerequisite: CSE 323. 3 credits

CSE 424: Object Oriented Software Development

Survey of the paradigm including analysis, design and implementation. Booch methodology, Rumbugh methodology, Van-Den Goor meta-methodology, Unified methodology. Comparison of C++, SMALLTALK and Eiffel in implementing object oriented concepts. Prerequisite: CSE 225 and consent of the instructor. 3 Credits.

CSE 425: Advanced Data Structures

Examines graphs and sub-graphs, trees, connectivity, Euler tours and Hamilton cycles, matchings, edge colorings, independent sets and cliques, vertex colorings, planar graphs, directed graphs, networks, the cycles space, and bond space. Prerequisite: CSE 225. 3credits.

CSE 426: Advanced Compiler

In depth study of Compiler technology. Syntax directed translation, type checking, run time environments, intermediate code generation, code optimization, survey of existing compilers including EQN, Pascal, C, FORTRAN H, Bliss/11, Modula 2. Prerequisite: CSE 326. 3 credits.

CSE 427: Advanced Software Engineering

An in-depth study of software nature and its qualities, software engineering principles with emphasis on rigor and formality and anticipation of change. Software design, specification, verification, production process, management of software engineering,, software engineering tools and environments. Case studies. Prerequisite: CSE 327. 3 credits.

CSE 428: Software Project Management

This course provides the insight of the software project management in every aspect. This course elaborately describe different life cycle model. Topics include software project initiation, software project scope management; cost estimation, software project planning, organization. It also includes the time and resource management for assuring the quality of the software. This course also asses the risk for developing the software and provide a plan for mitigating the risk. Prerequisite: CSE 327. 3 Credits.

CSE 429: Software Architecture

This course focuses on choosing the right software systems architecture for complex software systems. A proper architecture for a software helps to meet the organizational business goals. The topics include an overview of software systems architecture, architectural patterns, reference models and reference architectures, system quality attributes (availability, scalability, performance, modifiability, security, testability, usability), designing and documenting the system architecture, analyzing architectures, software product lines, and component and service-oriented architectures. A substantial amount of architecture issues will help to choose the suitable architectural pattern for software. That eventually helps to build, maintain and extend the system. Prerequisite: CSE 327. 3 Credits.

CSE 432: Computer Interfacing and Peripherals

Peripherals and Interfacing: Design and operation of interface between computer and outside world, Sensors, transducers and signal conditioning circuits, interfacing memory and I/O devices-such as monitors, printers, disc drives, optical displays, some special purpose interface cards, stepper motors and peripheral devices, IEEE-488, RS-232 and other buses, Study and applications of peripheral chips including 8212, 8155, 8255 and 8251. Character peripherals: Keyboards, printers (dot matrix, laser, ink jet), VDUS, Computer graphics hardware, plotters, disc-drivers, CD-ROM. Prerequisite: CSE 331. 3 Credits.

CSE 433: Computer Architecture

Computer system analysis and design; performance and cost, instruction set architecture, processor implementation techniques, pipelining, vector processors, memory-hierarchy design, input/output. Prerequisite: CSE 331. 3 credits.

CSE 434: Feedback Control System

System Modeling : Modeling in the frequency domain, Modeling in the time domain. Time response, Reduction of Multiple Subsystems, Stability, Steady State Errors, Root Locus Techniques, Design via root locus, Frequency response techniques, Design via frequency response, Design via state space. Design of feedback control system : Cascade compensation networks, System design using Integration networks, System design on the Bode diagram using analytical and computer methods, design for deadbeat response, Rotor Winder control system. Elements of PID controllers. Digital control system : Sampled data system, Closed loop

feedback sampled-data systems, closed loop systems with Digital Computer Compensation. Microcomputer-based Control Systems. 3 Credits.

CSE 435: Introduction to VLSI Design

Complementary Metal-Oxide Semiconductor (CMOS) technology and theory; CMOS circuit and logic design; layout rules and techniques; circuit characterization and performance estimation; CMOS subsystem design; Very-Large-Scale Integrated (VLSI) systems design methods; VLSI Computer Aided Design (CAD) tools; laboratory experience in custom VLSI chip design on workstations using concepts of hierarchy; final project involving specification, design and evaluation of a VLSI chip or VLSI CAD program; and written report and oral presentation on the final project. Prerequisite: CSE 232. 3 credits.

CSE 436: Industrial Electronics and Instrumentation

Power Electronics: Review of power semiconductor devices, relative advantages and limitations, triggering and snubber circuits, device protection, series and parallel operations, switching into resistive, inductive and machine loads, Rectification, inversion, chopper circuits.Polyphase: rectifiers, ignitrons, thyratrons and mercury rectifiers. Semiconductors power devices: Thyristors, SCRs TRIAC & DIACs and their applications for control of electrical powers. Amplifiers for Industrial Electronics Servoamplifier and Magnetic amplifiers. Electronic control of Motors & Generators: Servo-mechanism, control elements & circuits for position control, Instrumentation for control of temperature and other non-electrical quantities, high frequency heating in Induction and Dielectric heating. Elements of microprocessor based control system for industries. Instrumentation: Oscilloscopes, Signal Generators, Frequncy Analyzers, Logic Analyzers. 3 Credits.

CSE 437: Fundamentals of Telecommunications

The objective of this course is to develop a fundamental understanding of the communication systems. The students will be introduced to the concept of Fourier transform, probability density function and random process. Digital modulation techniques will be emphasized. Examples of practical mobile systems employed in Bangladesh like the GSM and CDMA based IS-95 will be presented. Prerequisite: CSE 338 and MAT 361. 3 Credits.

CSE 438: Networks and Distributed Systems

Introduction to concepts of transport connections and sessions; design issues in transport layer and session layer protocols, terminal and file transfer protocols, message handling protocols, etc.; methods to ensure network security and privacy; algorithms for deadlock detection, concurrency control and synchronization in distributed systems; models of distributed computation; networking facilities and resource control and management methods in network and distributed operating systems. Prerequisite: CSE 323 and CSE 338. 3 credits. CSE 439: Computer Networks II Computer Networks is a graduate course that introduces fundamental concepts in the design and implementation of computer communication networks and their protocols. Topics include: layered network architectures, applications, transport and routing, IP version 6, mobile IP,

multicasting, session initiation protocol, quality of service, network security, network management, and TCP/IP in wireless networks. An emphasis will be placed on the protocols used in the Internet. Prerequisite: CSE 338. 3 credits

CSE 441: Symbolic Logic

Propositional logic; First-order logic: Prenex normal forms; Herbrands theorem: Skolem standard forms; Resolution principle: Unification algorithm; Semantic resolution and Lock resolution; Linear resolution; Equality relation; Proof procedures: Prawitz procedure, V-resolution procedure, Splitting rule of Davis and Putnam; Program analysis; Deductive question answering, Problem solving, and Program synthesis. Prerequisite: CSE 348. 3credits.

CSE 444: Artificial Intelligence

An introductory description of the major subjects and directions of research in artificial intelligence; topics include all languages (LISP and PROLOG), basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts. Prerequisite: CSE 225 and CSE 232; or consent of instructor. 3 credits.

CSE 445: Machine Learning

Introduction to Machine Learning; Classification of learning: Unsupervised and supervised learning, Connectionist learning, Reinforcement learning, Machine discovery; Supervised learning: Information theoretic decision tree learner, Best current hypothesis search, Candidate elimination (version space) algorithm, Learning in the first order Horn clause representation, Inductive logic programming, Application; Unsupervised learning: Hierarchical clustering, Category utility, Incremental and nonincremental algorithms for hierarchical clustering, Applications; Connectionist learning: Introduction to Neural Network, Feedforward and recurrent network, Perceptron, Multilayer feedforward network, Backpropagation algorithm for training a feedforward network, Applications; Genetic Algorithms: Genetic operators, Fitness function, Genetic algorithm in supervised learning framework, Applications. Prerequisite: CSE 348. 3 credits.

CSE 446: Introduction to Bioinformatics

Bioinformatics and the Internet, Overview of Molecular Biology and Biological Chemistry,The Genetic Material, Gene Structure and Information Content,Protein Structure and Function, Bioinformatics tools,The NCBI Data Model,The GenBank sequence database,DNA sequencing,Editing DNA sequences,Submitting DNA sequences to the Database,Sequence Retrieval from Biological Databases ( NCBI, EMBL, ExPasy),Sequence similarity searches ( BLAST, FASTA, EMBL databases),Sequence Alignment ( CLUSTAL X, Genedoc, Bioedit) Phylogenetic Analysis. Prerequisite: 60 credits completed. 3 credits.

CSE 447: Functional Bioinformatics

Overview of Bioinformatics ,Molecular Biology of the Gene ,Gene Structure and Function,Introduction to Human Genome Project NCBI Resources and Sequence Retrieval

,Alignment and Phylogenetic Analysis,Data Visualization:Sequence Visualization, Structure Visualization, User Interface,Data Mining,Text Mining,Protein and RNA structure prediction,Introduction to drug discovery,Automating Data Analysis with Perl. Prerequisite: 60 credits completed. 3 credits.

CSE 448: Neural Networks

Elementary Neurophysiology - Biological Neurons to Artificial Neurons. Adaline and the Medaline. Perceptron. Backpropagation Network. Bidirectional Associative Memories. Hopfield Networks. Counterpropagation Networks. Kohonens Self Organizing Maps. Adaptive Resonance Theory. ART1 - ART2 - ART3. Boltzman Machines, Spatiotemporal Pattern Classifier, Neural Network models: Neocognitron , Application of Neural Networks to various disciplines. Prerequisite: CSE 348 and consent of the instructor. 3 credits.

CSE 453: Verilog HDL: Modeling, Simulation and Synthesis

This course is designed to cover a global understanding of Verilog HDL- based design. Topics treated include: Event-Driven Simulation, hardware modeling and simulation in Verilog, data types and logic system in Verilog, Structural and behavioral modeling, user-defined tasks and functions in Verilog and interactive debugging in Verilog using software tools. Prerequisite: CSE 231 / ETE 212. 3 Credits.

CSE 456: Petri Nets

Definition and type of Petri Nets, terms and notations, marking, transition firing rules, examples of modelling using Petri Nets, Siphons and Traps, Liveness and Safeness, Behavioral properties, Deadlock, Structural properties. Prerequisite: CSE 273. 3 Credits.

CSE 457: Numerical Analysis

A Comprehensive Introduction. Introduction to numerical analysis that includes linear system solvers, optimization techniques, interpolation and approximation of functions, solving systems of nonlinear equations, eigen value problems, least squares, quadratic as well as numerical handling of ordinary and partial differential equations. Prerequisite: MAT 361 or consent of instructor. 3 credits.

CSE 463: Integrated Circuit Logic Design

IC fabrication techniques; survey of different IC logic families; logic design procedures for each IC logic family; design of masks; logic design of digital networks with IC packages; use of ROMs as substitutes for gates; computer-aided design; and comparison of different implementation approaches based on different IC logic families, from the viewpoints of economy, performance and design time. Prerequisite: CSE 232, or consent of instructor. 3credits.

CSE 465: Pattern Recognition

Introduction: Basic concepts, Design concepts, Examples; Decision functions: Linear decision functions, Generalized decision functions; Pattern classification by distance functions: Minimum distance pattern classification, Cluster seeking; Pattern classification by likelihood functions:

Bayes classifier; Structural pattern representation: Grammars for pattern representation, Picture description language and grammars, Stochastic grammars; Structural pattern recognition: String to string distance; Matching other structures: Relational structures, Graph matching, Matching by relaxation, Random graph. Prerequisite: CSE 373. 3 credits.

CSE 467: Image Processing

Introduction; Point operations; Histograms; Spatial operations; Affine transformations; Image rectification; Interpolation and other transformations; Contrast enhancement; Convolution operation, Magnification and Zooming; Fourier transform; Edge detection; Boundary extraction and representation; Mathematical morphology. Prerequisite: CSE 373. 3 credits.

CSE 470: Theory of Fuzzy Systems

Introduction to Neuro-Fuzzy and Soft Computing, Soft Computing and AI, Neural Networks, Fuzzy Set Theory, MF Formulation and Parameterization, Fuzzy Union, Intersection, and Complement, Fuzzy Rules and Fuzzy Reasoning, Fuzzy Inference Systems, Regression and Optimization, Supervised Learning Neural Networks, Neuro-Fuzzy Modeling, ANFIS, Neuro-Fuzzy Control, ANFIS Applications. Prerequisite: CSE 348. 3 credits.

CSE 472: Advanced Algorithms

Principles underlying the design and analysis of efficient algorithms. Topics to be covered include: divide-and-conquer algorithms, graph algorithms, matroids and greedy algorithms, randomized algorithms, NP-completeness, approximation algorithms, linear programming. Prerequisite: CSE 373 3 credits.

CSE 473: Parallel Processing

Von Neumann Model, Need of Parallel Processing, Flynns Classifications. Shared Memory Models, Network Based Models, Simulations. Definitions of Parallel Algorithms. Measures of Complexities, Algorithms for non-numerical and numerical problems on various parallel models such as Finding Summation. Finding Minimum, Maximum, Sorting, Searching, Selection, Graph Theoretical Problems, Combinatorial Problems, Matrix Transpose, Matrix Multiplication. Solution of simultaneous Linear Equations etc. Prerequisite: CSE 373. 3 credits.

CSE 474: Computational Complexity

Basic Concepts - Problem: Definition, encoding, instance, size, decision & optimization problems. Turing Machines - Deterministic and Nondeterministic polynomial Reducibility. Classification of Problems - P, NP, NP-complete, NP-hard. Examples of similarly defined easy and difficult problems. Cooks Theorem, several important NP-complete problems, techniques of proving a problem, NP-complete restriction, component design, local replacement problems of intermediate complexity, problems beyond NP. Prerequisite: CSE 373. 3 credits.

CSE 475: Automata and Formal Languages

Finite automata and regular languages, pushdown automata and context-free languages; Turing machines and recursively enumerable sets; linear-bounded automata and context sensitive

languages; computability and the halting problem; undecidable problems; recursive functions; chomsky hierarchy; computational complexity. Prerequisite: CSE 373 and MAT 361 or consent of instructor. 3 credits.

CSE 478: Graph Theory

An introduction to the theory of graphs: fundamental concepts and basic definitions, trees, spanning trees in graphs, distance in graphs, Eulerian graphs, digraphs, matchings and factors, cuts and connectivity, k-connected graphs, Mengers theorem, network flow problems, graph coloring: vertex coloring and edge coloring, line graphs, Hamiltonian cycles, plannar graphs. Perfect graphs. Prerequisite: CSE 373. 3 Credits.

CSE 482: Internet and Web Technology

The course develops an in-depth knowledge of the concepts, principles and implementation techniques related to the Internet and web technology. Details about the Internet, Intranet, Extranet, and e-commerce will be covered. Topics include Web server management, threats, security of client and server, network security like firewall, SSL, etc., authentication and authorization, legislation, privacy and IP act, electronic payment, e-business, search engine, Internet protocols like TCP/IP, SGML, XML. Design and development of Web applications using Java Applets, ASP, Java Script, CGI and other Web tools is discussed. Prerequisite: CSE 338. 3 credits.

CSE 485: Digital Signal Processing

The purpose of this course is to give the students of Computer Science/Engineering the basic background in Digital Signal Processing. This course introduces how a computer (a general purpose or special purpose DSP chip) could be used to solve Signal Processing problems digitally. The topics include introduction to discrete signal and systems, difference equations, discrete convolution, Z-transform and Fast Fourier transform techniques. Prerequisite: CSE 331. 3 credits.

CSE 487: Microprocessor Based System Design

Overview of Microcomputers Structure and Operation. Computers, Microcomputers and Microprocessor; an introduction: The 8086 Microprocessors family overview, 8086 internal structure. 8086 family assembly language programming: Writing programs to use with an assembler, Assembly language program development tools. System development: Using a logic analyzer, 8086 interrupts and their uses and system operations, Priority interrupts controllers. Digital interfacing: Programmable parallel ports and handshaking, Interfacing a Microprocessor to various Input/Output devices, Interfacing Microcomputer ports to high-power devices e.g. rotating systems, motors, Industrial production process. Analog interfacing and industrial control: Sensors, transducers, A/D and D/A converters, Microcomputer based industrial process control, Robotics and embedded control. Advanced digital techniques: DMA data transfer, Concepts of Math Co processor, Computer based design and development tools, GPIB, IEE-488 and RS- 232 bus. Prerequisite: CSE 331. 3 Credits.

CSE 497: Special Topics

Availability of a faculty to teach a course on current topic of interests not listed in the curriculum. (as an example: CSE 497 Quantum Computing, CSE 497 Optical Computing etc.) Variable Credits.

CSE 490: Internship

The course involves 2 credits of research and 1 credit of internship. Prerequisite: 100 credits completed. 3 credits.

CSE 499: Project

Prerequisite: 100 credits completed. 3 credits.

Math, General Science and GED Courses for EECS:

ENG 102 (Introduction to Composition): Development of Integrated language skills with special focus on the mechanics of the writing process. Study of grammar, with emphasis on sentence structures, paragraph writing and topic sentence; 0 credits.

ENG 103 (Intermediate Composition): Continued work on analytic reading and on fluency and control of the writing process. Development of expressive, persuasive and referential writing with emphasis on planning, organization, cohesion and coherence. Prerequisite: ENG 102 3 credits.

ENG 105 (Advanced Composition): Continued work on analytic reading and on fluency and control of the writing process. Emphasis on sentence structure, organization, paragraphing, coherence and cohesion. Besides, the course is to develop the skills to communicate effectively as an engineer. The course focuses on enhancing an engineers ability in written and verbal communications, writing technical reports, and effective presentation of project proposals, and techniques of oral and visual communication with in-class practices. Prerequisite: ENG 103. 3 credits.

ENV 107 (Environmental Science): Man and environment. Major components of the environment. Basic population dynamics. Bio-geo-chemical cycles. Biosphere: ecological concepts and ecosystems; flow of matter and energy through an ecosystem; biodiversity. Lithosphere: agriculture and environment; urbanization; solid and hazardous waste management. Atmosphere: chemistry of air; urban air pollution; acid rain; global warming; ozone layer depletion. Hydrosphere: water chemistry; water pollution and treatment; wetland and coastal management. Renewable and non-renewable energy. Environmental health and toxicology. 3 credits.

ACT 201 (Introduction to Financial Accounting): An introduction to the accounting model and financial statements with emphasis on the concepts and terminologies needed to understand a corporate report. Topics include accounting processes for service and merchandising

enterprises; current assets and liabilities; long-term assets; stockholders equity; revenues and expenses; methods of depreciation; inventory pricing; and accounting cycle for both service and merchandising companies. 3 credits.

ENV 214 (Environmental Management): A problem-solution approach to resource and resource management with particular focus on natural resource management; management of forests, range-lands, parks, and biodiversity; soil and water resource management; solid and hazardous waste management; management issues arising out of legal, economic and social aspects of environmental factors; eco-centric and human approaches to environmental management; basic theory of renewable and non-renewable resources and their management, environmental issues related to power generation technologies; theory of holistic and proactive environmental management; green information systems, industrial structure and corporate policy; role of the Department of Environment (DOE) and environmental conservation act 1995, environmental dimensions of normative and strategic management; environmental management tools for businesses; risk management and liability. 3 credits.

BIO 210 (Introduction to Molecular Biology) Description: The course focuses on the basic concepts in the molecular biology of the gene; cell structuring; the chemistry of Nucleic Acids, DNA, RNA; basic structure and function of proteins, three dimensional structure of DNA, replication, transcription, translation of the gene, characterization of gene products, control of gene expression and gene regulation, cloning of gene, practical applications. 3 credits.

BUS 101 (Introduction to Business): This course will give students basic understanding of the business and its environment with context to Bangladesh. Principles of various functional areas would be discussed to understand the successful operations of a business. Special focus would be on Ethnic and Social Responsibility of stakeholders.

CHE 101: (General Chemistry )For students having basic knowledge of Chemistry: Introduction to atomic structure, quantum mechanical atom, chemical bonding, valence shell electron pair repulsion theory for predicting molecular geometry. Their theory of chemical bond formation, Periodic table and period classification of elements with their properties, Transition elements and coordination chemistry, application of valence bond theory to coordination compounds, Chemistry of solids and crystals, States of matter, Different gas laws & kinetic theory of gases, stoichiometry, chemical equilibrium, environmental chemistry. Prerequisite: Chemistry in HSC. 3 credits.

MAT 100: (Preparatory Mathematics) For students with the basic ability to cope with MAT 112. Students are required to attend MAT 112 lectures plus extra hours of supervised practice on topics covered in MAT 112. 0 credit.

MAT 112: (Elementary Mathematics) Topics include sets, real numbers system, algebraic expressions, systems of equations, functions and relations matrices, determinant (applications), exponents and radicals, exponential and logarithmic functions, functions of integers, permutations, combinations, and binomial theorem. Prerequisite: High School Mathematics. 0 credit.

MAT116 (Precalculus): Topics includes sets, real number system, algebraic expressions, systems of equations, functions and relations, quadratic functions, synthetic division, the zeros of a polynomial function, exponential and logarithmic functions, trigonometric functions, graphs of trigonometric functions, analytic trigonometry, additional applications of trigonometry, mathematical induction, the binomial theorem, sequences. Prerequisite: High School Mathematics. 0 credit.

MAT120 (Calculus and Analytic Geometry-I): A first course in calculus and analytic geometry. Coordinates, Graphs and Lines; Functions and Limits; Differentiations; Application of Differentiation; Integration; Logarithmic and Exponential Functions. Prerequisite: MAT116. 3 credits.

MAT125 (Introduction to Linear Algebra): Basic concepts and techniques of linear algebra; includes system of linear equations, matrices and inverses, determinants, and a glimpse at vector spaces, eigenvalues and eigenvectors, Markov processes, . Prerequisite: MAT116 or an adequate test score. 3 credits.

MAT130 (Calculus and Analytic Geometry II): Second course in calculus and analytic geometry. Applications of Definite Integral; Hyperbolic Functions, Inverse Trigonometric and Hyperbolic Functions; Techniques of Integration; Improper Integrals: LHospitals Rule; Topics of Analytical Geometry; Polar Coordinates and Parametric Equations. Prerequisite: MAT120. 3 credits.

MAT240 (Calculus and Analytic Geometry III): Third course in calculus and analytic geometry. Infinite Series; Three Dimensional Spaces, Vectors; Vactor valued Functions; First and Second Order Differential Equations. Prerequisite: MAT130. 3 credits.

MAT250 (Calculus and Analytic Geometry IV): Partial Derivatives: Functions of two variables, limits and continuity, partial derivatives, differentiability and chain rule, directional derivatives and gradients, tangent planes and normal vectors, maxima and minima of functions of two variables. Multiple Integrals: Double integrals, double integrals over non-rectangular regions, double integrals in polar coordinates, triple integrals, centroid, center of gravity, triple integrals in cylindrical and spherical coordinates, change of variables in multiple. Topics in vector calculus: Vector fields, line integrals, Greens theorem, surface integrals, the divergence theorem, stokes theorem. Prerequisite: MAT240. 3 credits.

MAT350 (Engineering Mathematics): First order ordinary differential equations, linear differential equations with constant coefficients, Laplace transformations, power-series solutions of differential equations, Bessel functions. Prerequisite: MAT250. 3 credits.

MAT 361 (Probability and Statistics): Introduction to Statistics, Descriptive Statistics, summarizing data sets, Markov, Chebyshev's inequality, the sample correlation coefficient. Elements of Probability, Types of random variables, jointly distributed random variables, expectation, conditional distributions, computing probability and expectation by conditioning, variance, covariance, moment generating functions. Special Random Variables- Bernoulli, binomial, Poisson, hypergeometric, uniform, normal, exponential, gamma distribution,

distributions arising from the normal-the chi square distribution, the t-distribution, the F-distribution. Distributions of Sampling Statistics, Parameter Estimation, Hypothesis Testing, Regression analysis and distribution of its parameters. Prerequisite: MAT 250. 3 credits.

MAT 370 (Real & Complex Analysis) The Real Numbers, Sequences, Limits, Continuity and Uniform Continuity of Functions, Differentiation, The Riemann Integral, Sequences of Functions and their Convergence, Infinite Series, The Topology of Real Numbers. Prerequisite: MAT 250. 3 credits.

MAT 480 (Differential Equations) Introduction to Differential Equations, first-order Differential Equations, applications of first order Differential Equations, Linear Differential Equations of higher-order, Applications of second-order Differential Equations with variable coefficients, Systems of Linear Differential Equations. Prerequisite: MAT 250. 3 credits.

MAT 490 (Advanced Engineering Mathematics) Laplace Transform, Existence of Laplace Transform, Inverse Laplace Transform, Laplace Transform of Derivatives and Integrals, Shifting on the s-axis, Shifting on the t-axis, Differentiation and Integration of Laplace Transform , Convolution, Inverse Laplace Transform of partial Fractions, Inverse Laplace Transform of periodic Functions, Fourier Series (FS) for Functions of period 2 or arbitrary period, Fourier Series for Even and odd Functions, HalfRange Fourier Expansion, Determination of Fourier Coefficients without Integration, Fourier Approximation and minimum square error, The Fast Fourier Transform, Complex Variable Functions, Limits and Continuity, Derivatives, Analyticity and Cauchy-Riemann Equations, Conformal Mapping, Relation between Analyticity and Conformality, Mobius and other Transformations, Complex Integrals, Cauchys Integral Formulae, Taylors Series, Singular Points, Laurents Series, Residues and Residue Theorem, Evaluation of Real Definite Integrals using Complex Integrals.. Prerequisite: MAT 250. 3 credits.

MAT 495 (Abstract Algebra) Sets and Equivalence Relations, Semigroups & Monoids, Free Semigroup & Free Monoid, Congruence Relations and Quotient Structures, Fundamental Theorem of Semigroup Homomorphism, Groups, Sn, Zn, Subgroups, Normal Subgroups, Cayleys Theorem, Lagranges Theorem, Quotient Group, Cyclic Subgroups, Generating Sets, Generators, Fundamental Theorem of group Homomorphism, Rings and Ideals, Fundamental Theorem of Ring Homomorphism, Integral Domain, Principal Ideal Domain, Divisibility in Integral Domain, Unique Factorization Domain, Field, K[t]- the polynomials over a field K, K[t] as a Principal Ideal Domain and Unique Factorization Domain, Fundamental Theorem of Algebra, Ordered Sets and Lattices, Principle of Duality, Bounded Lattices, Distributive Lattices, Complemented Lattices, Boolean Algebra as a Bounded, Distributive and Complemented Lattice. Prerequisite: MAT 250. 3 credits.

MIS 440: Introduction to Management Information Systems

Examines the role of information technology in managerial decision making, Topics include role of information systems in business; types and components of information systems; computer hardware and software; end-user computing and collaboration; role of information systems in operational and strategic management; role of database management and telecommunication systems in business; impact of information systems in organizational development and change

and global management; security and ethical issues facing information systems managers. Prerequisite: MGT210. 3 Credits.

MIS 460: Management Support Systems

Overview of decision support systems and their types, normative, behavioral theories, and cognitive biases in decision making, DSS architecture, introduction to DSS development tools, Modeling and decision analysis (preferably by using Excel), programming concepts (Linear Programming), Review of database concept (with oracle), Overview of OLAP and data mining, Introduction to data warehousing, group support system, Artificially Intelligent Decision Support System: tools and applications, discussion of design appropriateness, risk assessment and implementation issues of DSS. The course will provide the students with the opportunity to design a simple decision support system and to evaluate and justify the design. Prerequisite: MGT210. 3 Credits.

MIS 470: Systems Analysis and Design

Examines techniques required to conduct information systems analysis. Topics include concepts, phases, activities, and roles of SDLC, system feasibility study, cost benefit analysis of information systems, proposal evaluation; techniques for analyzing and documenting existing and proposed systems, form design, structured analysis, data flow diagrams, data dictionaries, decision tables, state-transition diagrams, ER diagrams, and object oriented techniques, selection of hardware and software; implementation and post implementation evaluation of systems. The course also teaches the applications of necessary project management tools and techniques. The course may deploy a CASE tool to teach systematic analysis and documentation through hypothetical case situations or a semester long field project. Prerequisite: MGT210. 3 Credits.

MGT210 (Principles of Management): Provides a basic discussion of the environments, approaches, principles and process of management. Topics include environmental forces, planning, organizing and control processes, motivation, teamwork, group dynamics and leadership in business and non-business organizations.

PHY 107 (Physics I): Vectors, Kinematics, Newtons Law, Conservation of Energy and Momentum, Rotational Kinematics, Conservation of Angular Momentum, Collision, Compton Effect, Nuclear Theory, DeBrogglie, Oscillations and Waves, Gravitation. Prerequisite: MAT 120 and Physics in HSC/A Level. 3 credits.

PHY 107L (Physics I Lab): Measurement of length area and volume of solids of regular shapes using vernier caliper, micrometer screw gauge and spherometers. This simple experiment will introduce the students to precision in measurements, error and propagation of error. This knowledge is of fundamental importance, which will be applied in all subsequent experiments, Free fall experiment. To find the time of fall through a given distance and to determine the acceleration of free fall. Apparatus required: Light gates and timer, To study equilibrium of a rigid body. Apparatus needed: force table, pulleys, and weights, To study rectilinear motion on an inclined plane. Apparatus: board, electronic timers or ticker tape timers,

light gate etc. Plot of v-t and a-t graphs, To find acceleration of free fall using Atwoods machine. Apparatus: pulley, known masses and electronic timer, Measurements of the coefficients of static and dynamic friction. Apparatus: wooden blocks, spring balance, known weights etc, Motion of a ball bearing through a resistive medium. To measure the viscosity of glycerin by Stokes law. Apparatus: measuring cylinder, stop watch, steel ball bearings, meter rule, and thermometer, Simple harmonic motion 1. Measurement of g by simple pendulum, Simple harmonic motion 2. Vibration of a vertical spring-mass system, measurements of the spring constant and the acceleration of free fall, Study of damped and forced harmonic oscillator. Apparatus: carts, motor, springs, motion sensors etc, Rotational motion. Measurement of moment of inertial of a flywheel, Foucaults pendulum and the effect of Earths rotation, To study the rotational motion of a cylinder down an incline. The objective of this experiment is to become familiar with the relationships involving angular acceleration and moments of inertia, Conservation of momentum and kinetic energy in elastic collisions. Apparatus: air track, gliders, light gates, timers etc, Study of one-dimensional inelastic collisions. Apparatus: air track.0 Credits

PHY 108 (Physics II): Electric Charge, Coulombs Law. The Electric Field: Electric Field Lines, The Electric Field Lines Due to a Point Charge, The Electric Field Lines Due to an Electric Dipole, The Electric Field Lines Due to a Line of Charge, The Electric Field Lines Due to a Charged Disk. Gauss Law: Gausss Law in Cylindrical, Planar and Spherical Symmetries. Electric Potential: Equipotential Surfaces, Potential Due to an Electric Dipole. Capacitance: Capacitors in Parallel and Series, Capacitors with a Dielectric. Electric Current, Current Density, Resistance and Resistivity, Ohms Law. Circuits, Work, Energy and EMF, Single Loop Circuits, Potential Differences, Multiloop Circuits, RC Circuits. The Magnetic Field, Amperes Law, Solenoids and Torroids, Faradays Law of Induction, Alternating Currents, Maxwells Equations. Prerequisite: MAT 240 and PHY107. 3 credits.

PHY 108L (Physics II Lab): Electricity and Magnetism: Introduction to Oscilloscope and Lissajous Patterns, Measurement of large capacitive time-constant using multimeter and stop watch, Measurement of small capacitive time-constant using oscilloscope, Measurement of parallel & series capacitances and combination of capacitances, Measurement of Inductance and combination of Inductances, Measurement of Current and Magnetic fields, Measurement of Galvanometer Sensitivity, I-V Characteristics of LED, Characteristics of Light Dependent Resistor (LDR) 0 Credits