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PhDFaculty of Engineering & SciencesBahria UniversityThe PhD programs in Engineering Sciences at Bahria University are offered in following disciplinesComputer science (CS) Computer engineering (CE) Electrical engineering (EE) Software engineering (SE) Road MapThe proposed road map of the PhD program is presented in the following. After passing the 18 credit hours course work, preferably in the first two semesters, the candidate will have to pass comprehensive exam. After qualifying the comprehensive exam, candidate will have to defend the synopsis and will be offered Supervised Research (PhD Thesis) of 36 credit hours.SEMESTER ICourse CodeSubjectCreditsEEN-801Research Methods in PhD Studies3Elective-I3Elective-II3Total credit hours for the 1stsemester9SEMESTER IICourse CodeSubjectCreditsElective-III3Elective-IV3Elective-V3Total credit hours for the 2ndsemester9SEMESTER IIICourse CodeSubjectCreditsEEN-901Comprehensive Exam0EEN-902Supervised Research (PhD Thesis) including defense and acceptance9of research proposalTotal credit hours for the 3rdsemester9SEMESTER IVCourse CodeSubjectCreditsEEN-902Supervised Research (PhD Thesis) including design and9implementation of the proposed solutionTotal credit hours for the 4thsemester9SEMESTER VCourse CodeSubjectCreditsEEN-902Supervised Research (PhD Thesis) including analysis of the results9and thesis write-upTotal credit hours for the 5thsemester9SEMESTER VICourse CodeSubjectCreditsEEN-902Supervised Research (PhD Thesis) - Submission of the final thesis for9evaluation.Total credit hours for the 6thsemester9Total Credit hours for PhD Program54PhD Course List (Faculty of Engineering & Sciences)PhD students, as a part of their course work, are allowed to enroll in 700 or plus level courses (not in the PhD course list given below), if offered in MS programs at BU with the approval of FDRC.S. No.CourseTitle of the CourseCreditCodeHours1EEN-710MOS VLSI Circuit Design32EEN-711Real Time DSP Design and Applications33EEN-712Advanced Digital Communications34EEN-801Research Methods in PhD Studies35EEN-802Power management in wired and wireless systems36EEN-803Low Power System Design37EEN-804Advance System Modeling and Simulation38EEN-807Special Topics in distributed systems39EEN-808Power awareness in distributed systems310EEN-813Power System Stability and Dynamics311EEN-814Power System Transients312EEN-815HVDC and Flexible AC Transmission313EEN-816Rural Electrification and Distributed Generation314EEN-817Artificial Intelligence techniques in Power systems315EEN-818Power System Deregulation316EEN-819Advanced Computer Architecture317EEN-820Advanced Embedded Systems318EEN-821Advanced Digital Signal Processing319EEN-822Advanced Digital System Design320EEN-823ASIC Design Methodology321SEN-805Power Aware Computing322SEN-809Advanced Artificial Intelligence323SEN-810Advanced Neural Networks324SEN-811Data Ware housing and Mining325SEN-812Machine Learning326SEN-710Formal Methods and Specifications327SEN-719Human Aspects in Software Engineering328MAT-853Advanced Engineering Mathematics329*MGT-801Logic and Research330*MGT-802Advanced Qualitative Research Methods331*MGT-806Advanced Quantitative Research Methods332*MGT-803Critical Review of Literature333CSC-750Computer Vision334CSC-715Pattern Recognition335CSC-815Agent-Based Modeling336CSC-816Bio Medical Image Analysis3* Only one course may be allowed with the approval of FDRC.Course OutlinesMOS VLSI CIRCUIT DESIGNCourse Code:EEN-710Credit Hours:3Pre requisite:NoneObjectives:This is a graduate level course covering the design and analysisof low power and high performance digital CMOS integratedcircuits. Examples of such circuits that feature large-Digital,small-Analog architectures include microprocessors, FPGAs andDSP and multimedia SoC modules. The course covers thetraditional CMOS inverter in depth. Other topics includeinterconnects, layout, simulation techniques, hierarchicaldesign, timing issues, EDA tools, complex macro architectures,arithmetic building blocks and memory structures. Intensiveproject work is included using Mentor Graphic IC design tools.Fabrication of modern CMOS circuits is covered along with asurvey of the industry at the beginning of the course.Course Outline:? Introduction, course administrivia, outline, CMOSfabrication technology (video, trends, basicprocesses).?MOSFET device physics, second order effects,capacitance, layout related effects as it relates tothe design of a static CMOS inverter? CMOS inverter operation and analysis (continued),design metrics, area power delay, analog vs.digital, why CMOS?? General discussion on digital design, synthesis,P&R tools, simulators, EDA history and trends,custom/automated layout of custom digital andlarge digital ASICs and SOCs, introduction to FPGAand DSP architectures? Introduction to SPICE/ELDO for circuit simulation,BSIM models etc?Interconnects?Logic families? Sequential circuit element design (flip flop metricsand architectures)? Top level simulation and implementationstrategies for large chips, top level chip issues,package considerations? Timing issues in digital circuits, PLLs? Arithmetic building blocks (adders: transistor levelimplementations)? Arithmetic building blocks (multipliers, shifters androtators)? Memory structures? Review and other remaining or specialized topicsResources:1.Jan M. Rabaey, Digital Integrated Circuits, A DesignPerspective (2nd ed)2.Peter van Zant: Microchip Fabrication (4th ed)Real Time DSP Design and ApplicationsCourse Code:EEN-711Credit Hours:3Pre requisite:NoneObjectives:This course introduces real time application and design to thestudents.Course Outline:? Introduction to the Digital signal processorso Design challenges and attributeso Processor technologieso Review of the DSP concepts?FPGA and Micro processors Basics? Discrete time signal processing? Architecture of the Microprocessor? Peripheral Components, Real Time Implementationissues? Architecture of the DSP? Fixed and Floating point DSP architecture Designing? Efficient Computation of the Discrete Fouriertransform? Implementation of the DFT using Convolutionsynchronization, interrupts?Real time Communications? Fourier analysis of stationary random signals Realtime data bases? Designing and implementation of the Hilberttransform? Designing and implementation of the FiltersHardware Accelerators? Designing approach on DSK TMSc6713 System-on-chip? Case Studies (Applications of DSK)Resources:3. Kuo. S M, Gan W S,” Digital Signal Processor; Architectures,Implementations and Applications” Prentice Hallpublications4. Digital signal processing- application, algorithms andapplication, John G, Proakis et alAdvanced Digital CommunicationsCourse Code:EEN-712Credit Hours:3Pre requisite:NoneObjectives:This course introduces advance topics in digital communicationCourse Outline:? Introduction to Digital Communications? Random and Deterministic Signals? Bandpass Modulation and Demodulationo Bandpass Equivalent of baseband signaloGramSchmidth ProcedureoMatched Filter? Digital ModulationoMemory less modulationoMultidimensional signalingo Power spectrum of the Digitally modulatedsignalWaveform and vector channel model Waveform and vector AWGN channels Error of maximum likelihood detection Optimal Detection Error probability for power-limited signaling Synchronization Carrier and symbol synchronization Carrier phase estimation Symbol timing estimations Multichannel and multicarrier systems Fading channel and impacts on Communications Channel Coding Linear Block codes o Trellis and graph based codes o State Encodingo Hamming codeso LFSR, Gold sequence, Kasami sequencesResources:1. John. G. Proakis and Masoud Salehi, Digitalcommunications, 5th Edition, McGraw-Hill Internationaleditions,2008B. Sklar, Digital communication, Fundamental and applications, Prentice Hall,2006 R.G Gallager, “ Principles of Digital communications”. Cambridge University Press, 2008 Research Methods in PhD StudiesCourse Code:EEN-801Credit Hours:3Pre requisite:NoneObjectives:This course introduces students to a number of researchmethods useful for academic and professional investigations ofinformation practices, texts and technologies. By examiningthe applications, strengths and major criticisms ofmethodologies drawn from both the qualitative andquantitative traditions, this course permits an understandingof the various decisions and steps involved in crafting (andexecuting) a research methodology, as well as a criticallyinformedassessmentofpublishedresearch.The course offers an overview of the different approaches, considerations and challenges involved in social research. In addition to reviewing core human research methods such as interviews, ethnographies, surveys and experiments, we will explore methods used in critical analysis of texts and technologies (discourse/content/design analysis, historical case studies), with an emphasis on the digital (e.g. virtual worlds, videogames, and online ethnographies). We will also discuss mixed method approaches, case studies, participatory and user-centered research, as well as research involving minors.Course Outline:?The Research Process,? Choosing Your Supervisor (s),?Reviewing Literature,? Formulating a Research Problem,? Identification of Research Parameters,? Constructing Research Question and Hypothesis,? The Research Design, Selecting a Study Design,? Problem Formulation and Modeling,? Establishing the Validity and Reliability of a ResearchBench/ Simulator,?Sampling,?Research Proposal,?Ethical and Confidentiality Issues in the research,?Processing Data and coding,?Writing a Research Report/ Thesis/ Dissertation/Research PaperResources:1.Dr Ranjit Kumar, "Research Methodology: A Step-by-StepGuide for Beginners", Sage Publications Ltd; Second Edition2009, ISBN-10: 141291194X , ISBN-13: 978-14129119482.Gina Wisker, “Postgraduate Research Handbook: Succeedwith your MA, MPhil, EdD and PhD (Palgrave StudyGuides)”, Palgrave Macmillan; 2nd edition (December 26,2007), ISBN-10: 0230521304 , ISBN-13: 978-02305213083.R. Panneerselvam, "Research Methodology", Prentice Hallof India, 2005, ISBN: 81-203-2452-84.Dr. A. K. Phophalia, "Modern research methodology - Newtrends and techniques", Paradise Publishers, India, 2010,ISBN: 97893800330095.Loraine Blaxter,Christina Hughes And Ma, "How toResearch", ViVa Books, India, 1999, ISBN: 81-7649-089-X6.Anil Kumar (Edtr.), "Encyclopedia of Research MethodologyVol. I to Vol. IV", Alfa Publications, India, 2009, ISBN:9788190784337Power Management in wired and wireless systemsCourse Code:EEN-802Credit Hours:3Pre requisite:NoneObjectives:This is an introductory course on the fundamentals of electricalpower system in general. First a general introduction to theelements of the power system and the participants. Simplecalculations are introduced on transmission lines, which leadto the use of a power system simulator, a tool used to assessloadflow, short circuit and transient stability of power systems.Additional examples are introduced regarding transformers,protection systems, circuit breakers, coordination studies,conductor sizing, and other typical engineering assignmentsfrom the real world on power systems.Course Outline:?Introduction to power management?Power trends? Mobile devices and applications? Cellular handset: deep drive? Hierarchical view of energy conservation: Issues andchallenges, power versus energy types, hierarchy ofEnergy Conservation Techniques, Lower powerprocess and transistor technology, lower powerpacking technique?LowerPowerDesignTechnique,DesignMethodology and Tools: low power architectural andsubsystem technique, Low power SoC designmethodology , tools and standards, advance powermanagement, advanced configuration and powerinterface, the demand for application driven powermanagement?Batteries and Displays: Battery technology andchemistry selection, low power display technique?Power Management Integrated Circuits: VoltageRegulator, PMICs plus audio? System Level Approach to Energy Conservation: Lowpower system framework, low power software,Technology specific energy efficient algorithms, ARMintelligent energy manager, National SemiconductorPower Wise Technology,? Future trends in Power ManagementResources:?Findlay Shearer, “Power Management in MobileDevices”? Schaums Outline, Power Systems?Glover, Power SystemsLow Power System DesignCourse Code:EEN-803Credit Hours:3Pre requisite:NoneObjectives:Power consumption is one of the critical design factors inmodern VLSI design. The rapid increase in both power andperformance requirements are especially true in applicationssuch as wireless communication, notebook, and portablemulti-medium devices. As technology down scaling, heatdissipation and packaging cost also demand low power IC. Thiscourse will cover from fundamental of power consumption tosystem-level design. The course emphasizes the balancebetween theory and hand-on practices.Course Contents:Topics covered include:?Introduction to low-power system design?Low-power digital IC basics?Gate-level & RTL low-power implementation?Dynamic power management?Power-aware Verification?System-level power optimization?Power analysis and estimationResources:1.A. Bellaouar and M. Elmasry, “Low-power digital VLSIdesign: Circuits and Systems,” Kluwer, 19952. “Digital Integrated Circuits: A Design Perspective,” 2nd ed.,J. Rabaey, A. Chandrakasan, B. Nikolic, Prentice Hall, 2003.ISBN: 0-13-120764-4.3. “Advanced Digital Design with Verilog HDL,” Michael D.Ciletti, Prentice Hall, 2003. ISBN: 0-13-089161-4.4.“Low-Power CMOS VLSI circuit design,” by Kaushik Roy andSharat C. Prasad, John Wiley & Sons, INC, 2000. ISBN:0-471-11488-X.5.“Low-Power CMOS design,” edited by AnathaChandrakasan and Robert Brodersen, IEEE Presss, 1996.ISBN: 0-780-33429-9.“Low-Power Electronics Design,” edited by Christian Piguet, CRC Press, 2004. ISBN: 0-8493-1941-2. Michael Keating, David Flynn, Robert Aitken, Alan Gibbons, Kaijian Shi, “Low Power Methodology Manual for System-on-Chip Design,” Springer, 2007. Advance System Modeling and SimulationCourse Code:EEN-804Credit Hours:3Pre requisite:NoneObjectives:The course will cover both analytical methods (Markov Modelsand Queuing Networks) and simulation techniques (MonteCarlo Techniques and Event Driven Simulation) applied inperformance modeling of communication systems andnetworks.Course Outline:Topics covered include:? The Essentials of Probability?Monte Carlo Techniques?Discrete Event Stochastic?Markov Models with?Queuing ModelsResources:1. Discrete-Event System Simulation, J. Banks and B. Nelson,Prentice-Hall, 5th Edition, 2010.2. Simulation, S.M. Ross, Academic Press, 4th edition, 2006.3. Probability and Statistics with Reliability, Queuing andComputer Science Applications, K. Trivedi, Wiley, 2ndedition, 2002.Special Topics in Distributed SystemsCourse Code:EEN-807Credit Hours:3Pre requisite:NoneObjectives:The course will cover both analytical methods (Markov Modelsand Queuing Networks) and simulation techniques (MonteCarlo Techniques and Event Driven Simulation) applied inperformance modeling of communication systems andnetworks.Course Outline:Topics covered include:?Introduction to Distributed Systems, Introductionto Erlang?System Architecture, Communication Replication& Consistency, Distributed Shared Memory?Synchronization & Coordination?Fault Tolerance?Middleware?Naming, Distributed File Systems?Security?Parallel Programming and Cloud Computing?Distributed Systems in PracticeResources:1.George Coulouris, Jean Dollimore & Tim Kindberg:Distributed Systems: Concepts and Design, 5th ed,2011, Addison-Wesley.2.Andrew S. Tanenbaum & Maarten van Steen:Distributed Systems: Principles and Paradigms, 2nd ed,2007, Pearson Prentice Hall.3.Pradeep K. Sinha: Distributed Operating Systems, 1997,IEEE Press.4.Doreen L. Galli: Distributed Operating Systems, 1999,Prentice Hall.5.Mukesh Singhal & Niranjan G. Shivaratri: AdvancedConcepts in Operating Systems, 1994, McGraw-Hill.Power Awareness in Distributed SystemsCourse Code:EEN-808Credit Hours:3Pre requisite:NoneObjectives:Power systems are complex networks of generators and loadsinterconnected via transmission lines and various types ofequipment and apparatus (transformers, switchgear, etc). Anoverview of modern power systems meeting present andfuture challenges involves understanding the fast changingstructure of this system, the behavior of its components understeady state,dynamic and transient conditions, in order to be able toevaluate the response of this complex system to variation ofloads, and to determine how this system can be controlled tosupply the loads reliably while it is economical and safe to theenvironment.Course Outline:Topics covered include:?Review of the basic concepts used in powersystem analysis: phasors,complex power, threephase systems and per-unit.?Iintroduction of equivalent circuit models forpower system components including transformers,generators, transmission lines and loads?Application of network matrices techniques andpower flow analysis to study the steady-state anddynamic behavior of power systems?Power system fault calculations including:symmetrical components, symmetrical faults, andunsymmetrical faults; surge propagation duringtransients in power system?Power system stability by introduction of swingequation, and a multi-machine system; powersystem protection principles; power systemcontrol and economic dispatch.Resources:1.J.D. Glover, and M.S Sarma, T.J. Overbye, Power SystemAnalysis and Design, 5th Edition (SI), Cengage Learning,2012.2.B.M. Weedy, and B. Cory, Electric Power Systems, 4thedition, Wiley, 1998.ELEC4612 Power System Analysis - Course Outline - 2012 p.6/6 N. Mohan, First Course on Power Systems, Minneapolis, 2006. T.R. Bosela, Electrical Power System Technology, Prentice-Hall, 1997. J. Eaton, and E. Cohen, Electric Power Transmission Systems, 2nd ed., Prentice-Hall. M.E. El-Hawary, Electrical Power System Design and Analysis, Prentice-Hall, 1983. T. Gonen, Electric Power Distribution System Engineering, McGraw-Hill, 1986. P. Hasse, Overvoltage Protection in Low Voltage Systems, Peter Peregrinus, 1992. F. Kussy, and J. Warren, Design Fundamentals for Low Voltage Distribution and Control, Marcel Dekker, 1987. J.C. Whitaker, AC Power Systems Handbook, CRC Press, 1991. Stevenson, W D: Elements of Power System Analysis, 4th edition, McGraw-Hill, 1982 Greenwood, A: Electrical Transients in Power Systems. John Wiley. Wood, A & Wollenberg, B: Power Generation Operation & Control, Wiley,1984 Power System Stability and DynamicsCourse Code: EEN-813Credit Hours: 3Pre requisite: NoneObjectives:The objective of the course is to introduce the students to modeling the dynamics of power systems for stability studies, and provide them with the basic concepts and fundementals of power systems contro; and stability. Students will be able to analyze and solve voltage and frequency stability and control problems using classical and modern control theory tools, as well as graphical and simulation tools.Contents:Topics covered include:Introduction to stability theory and modeling of dynamic system State space and s-domain modeling of power systems General concepts of state estimation Synchronous machines and state space models System response to small disturbances System response to large disturbances Analysis of linearized dynamics Steady state stability of multi machine systems Linearized models and simulation of multi-machine systems Voltage stability and stability criteria Frequency stability Classical models based control of power systems State feedback and optimal control of power systems Voltage and frequency automatic control Resources:P.M. Anderson and A.A. Fouad, Power system control and stability, 2nd edition,Wiley-IEEE Press.Power System TransientsCourse Code:EEN-814Credit Hours:3Pre requisite:NoneObjectives:This course explores the topic of transient problems on electricutility and industrial power systems. The purpose is to teachstudents the fundamentals and to enable them to recognizeand solve transient problems in power networks andcomponents. Topics include: a review of the Laplace transformand dc circuit transients, ac switching transients, transients inthree-phase circuits, transients waves on transmission lines,system modeling, computer analysis methods, lightning, andinsulation coordination.Course Outline:?Electrical transients?Principle of superposition?The Laplace Transform?Solving differential equations?Closing transients? Removing short-circuits and the transient recoveryvoltage?RCL circuits? Resistance switching and damping?Capacitor switching? Magnetizing inrush and Ferroresonance? Three-phase reactor switching and capacitorswitching? Symmetrical components for solving three-phaseswitching transients? Electromagnetic induction, magnetic flux, andcurrents?Transient electromagnetic phenomena?Transmission lines, the wave equation, and lineterminations?Traveling wave attenuation and distortion?Power system components and frequency response?Frequency-dependent parameters?Lightning and the power system?Computation of lightning events?Lightning protection using shielding and surgearresters?Transient voltages and grounding practicesResources:1.Power System Analysis, 2nd Edition by AllanGreenwood Wiley-Interscience2.Software Tool:Electro-Magnetic Transients with DCAnalysisHVDC and Flexible AC TransmissionCourse Code:EEN-815Credit Hours:3Pre requisite:NoneObjectives:This course covers two very important applications of powerelectronics in the modern power system – High Voltage DCtransmissionand Flexible AC power transmission.High voltage DC transmission has been used worldwide to transmit bulk power over long distances. Recently the VSC-HVDC has been introduced for the applications in the connection of relatively weak grids. Modular multilevel converters based HVDC (MMC-HVDC) is the latest development in the HVDC transmission technology. MMC-HVDC will be the backbone for the proposed offshore DC super-grids.Flexible AC transmission technology refers to the application of power electronics in the power system which would allow the control series or shunt compensation techniques or their combination. Power electronic switches may also be used to switch passive devices like the shunt capacitors or the reactors.Course Outline:The course contents include:? Classic HVDC transmission (LCC HVDC) for the bulkpower transmission over long distances? Introduction,operationandcontrolofVSC-HVDC transmission for the connection ofrelatively weak grids, and grid connection ofrenewable energy sources? Introduction, operation, control and evolution of Modular Multi-level converters and MMC-HVDC?Introduction, operation, control and theory of reactive power compensation in power systemsPower converters and FACTS devices Shunt compensating devices SVC, STATCOM- introduction,operationandcontrolResources:1.R. S. Ramshaw: Power Electronics and SemiconductorSwitches, 2nd Edition, Kluwer Academic Press, 1993.2.M. H. Rashid: Power Electronics, Circuit, Devices andApplication, 2nd Edition, Prince Hall, 1993.3.N. U. Mohan, T. M. Robbins and P. William: PowerElectronics, Converters, Application and Design, 2nd Edition,John Wiley & Sons, 2002.N. G. Hingorani and L. Gyugyi: Understanding of FACTS: Concept and Technology of Flexible AC Transmission System, Wiley-IEEE Press, December 1999. Rural Electrification and Distributed GenerationCourse Code:EEN-816Credit Hours:3Pre requisite:NoneObjectives:Rural electrification, which is requires huge investment, is animportant concern in Asian electric power utilities. Distributedgeneration is one new option being promoted to solve ruralelectrification problems along with the some other problems of urban distribution systems. The issues such as system capacity investments, grid expansions, etc. also benefit through distributed generation. This course is intended to provide the knowledge on the importance and benefit of rural electrification, availability of resources, distributed generation technologies, technical and financial feasibility of applying distributed generation to rural and urban areas.Course Outline:Topics covered include:Introduction to Power system Economics Economic Dispatch and Optimal Power Flow Market Overview in Electric Power Systems. Short-Term Load Forecasting. Electricity Price Forecasting. Price-Based Unit Commitment. Arbitrage in Electricity Markets. Market Power Analysis Based on Game Theory. Resources:1.Mohammad Shahidehpour, Hatim Yamin, Zuyi Li,Market Operations in Electric Power Systems:Forecasting, Scheduling, and Risk Management, April2002, Wiley-IEEE Press2.J. Wood and B. F. Wollenberg, Power generation,operation and control, 2nd Edition, 1996, Wiley-Interscience.Artificial Intelligence techniques in Power SystemsCourse Code:EEN-817Credit Hours:3Pre requisite:NoneObjectives:A reliable, continuous supply of electrical energy is essential forthe functioning of today's modern complex and advancedsociety. Electricity is one of the prime factors for the growthand determines the value of the society. Manual calculation,technical analysis and conclusions initially adopted the powersystem design, operation and control. As the power system grew it became more complex due to the technical advancements, variety and dynamic requirements. Conventional Power System analysis become more difficult due toComplex versatile and large amounts of data that are used in calculation, diagnosis and learning. The increase in the computational time period and the accuracy due to extensive system data handling. The modern power system operates close to their limits due to the increasing energy consumption and impediments of various kinds, and the extension of existing electric transmission networks. This situation requires a significantly less conservative power system operation and control regime which, in turn, is possible only by monitoring the system states in much more detail than was necessary previously using artificial intelligence techniques. Course Outline:?Technology ofIntelligent Systems : Introduction,Fuzzy Logic and Decision Trees, Artificial NeuralNetworks (ANN), Robust Artificial Neural Network,Expert Systems, Fuzzy Sets and Systems, Expertreasoning and Approximate reasoning? Application of ANN to Short-term Load Forecasting,An ANN approach to the Diagnosis of TransformerFaults, Real-Time Frequency and Harmonic Evaluationusing ANN.? Application of Artificial Intelligence to Angle StabilityStudies: Introduction, Transient Stability,CriticalClearing Time(CCT), Methods of Fast Assessment ofCCT . Knowledge-Based System for Direct StabilityAnalysis.?Application of Artificial Intelligence toVoltageStability Assessment and Enhancement to ElectricalPower System : ANN-Based VoltageStabilityAssessment, ANN-Based Voltage Enhancement, AKnowledge-Based Support System for VoltageCollapse Detection and Prevention (KBVCDP),Implementation of KBVCDP?EvolutionaryComputation: Introduction,GeneticAlgorithms (GAS), Object –oriented Analysis of GAS,Object oriented GA Design, Evolutionary Programming(EP), Object oriented analysis, Design andimplementation of EP.?An EP Approach to Reactive Power Planning, OptimalReactive Power Dispatch using EP, Application of EPto Transmission Network Planning: Introduction,Problem formulation, EP, Numerical Results,Resources:1.Intelligent System Applications in Power Engineering by LoiLei Lai John Wiley Publication2.Electrical Systems, Dynamics, and Stability with ArtificialIntelligence Application by James A. Momoh and MohamedE. El-Hawary Marcel Dekker, Inc Publication USA3.Genetic Algorithms by David E. Goldberg, PearsonEducation4.Introduction to Neural Systems by Jacek Zurada, JaicoPublishing HousePower System DeregulationCourse Code:EEN-818Credit Hours:3Pre requisite:Objectives:The main course goal is to provide students with an overviewof economic matters involved in operating and controlling thepower generation and transmission of a large scale,restructured, interconnected power system. At the conclusionof the course students should be able to understand differencebetween vertical integrated power system and deregulatedpower system and how they operate.Course outlineTopics covered include:? Introduction to Power system Economics? Economic Dispatch and Optimal Power Flow? Market Overview in Electric Power Systems.? Short-Term Load Forecasting.?Electricity Price Forecasting.? Price-Based Unit Commitment.? Arbitrage in Electricity Markets.? Market Power Analysis Based on Game Theory.Resources:?Mohammad Shahidehpour, Hatim Yamin, Zuyi Li,Market Operations in Electric Power Systems:Forecasting, Scheduling, and Risk Management, April2002, Wiley-IEEE Press? J. Wood and B. F. Wollenberg, Power generation,operation and control, 2nd Edition, 1996, Wiley-Interscience.Advanced Computer ArchitectureCourse Code:EEN-819Credit Hours:3Pre requisite:NoneObjectives:Course Outline:? Computer Organization review? Instruction Set Design principles and MIPSarchitecture? Principles of Scalable Performanceo Speedup Performance lawsScalability analysis and approaches Pipelining Basic pipelining Data and control Hazards Exceptions Branch Prediction Speculation Performance Evaluation Instruction level Parallelism Score Board Architecture Dynamic Scheduling Multiple instruction issue using superscalar approach VLIW – software based ILP Compilers and code optimization Caches Cache basics o Techniques to reduce miss rateTechniques to reduce miss penalty Programming for memory performance Main memory organization Virtual Memory and paging Storage devices Parallel Computers Multiprocessors o Parallel Architectures and applicationsoSynchronization MechanismsResources:1.John L. Hennessy and David A. Patterson, “ComputerArchitecture: A quantitative approach”, 4th edition 2006,ISBN 97801237049002.D. Sima, T. Fountain, P. Kacsuk, “Advanced ComputerArchitecture”,Addison-Wesley,19973.H.S. Stone, “High-performance Computer Architecture”,3rdedition,Addison-Wesley,19934.Patterson, D. A. and Hennessy, J. L., “ComputerOrganization and Design: The Hardware/ SoftwareInterface”, Morgan Kaufmann, 19985.Kai Hwang, “Advanced Computer Architecture”, McGrawHill, 20086.WilliamStallings,“ComputerOrganizationandArchitecture”, 5th Edition, Prentice Hall International Inc.,2000Advanced Embedded SystemsCourse Code:EEN-820Credit Hours:3Pre requisite:NoneObjectives:Advance embedded system introduces to the students theapplication of embedded systems and prepare them for thechallenges of the practical world.Course Outline:? Embedded Systems IntroductionoDesign challenges, MetricsoProcessor technologiesoIC technologyoProgrammable Logic DevicesoFPGA Programming ModelsoHDLoEDK StructureoEDK Programming? Instruction Set Architecture Design? Real Time Task Scheduling?Scheduling Algorithms? Resource Sharing in RT Tasks? Scheduling RT Tasks in Multiprocessors? Case Studies of RTOS, posix, unix, windowsembedded, embed linux etc.? RTOS, processes, threads, context switching, inter-process communications, process synchronization,interrupts?Real time Communications? Real time Communications: Routing and RateControl? Real time data bases? Overview of Embedded System Architecture, I/Ointerface / Memory interface, Memory andCaches, etc.?Embedded Computing Platforms? Program Design, Dataflow Graphs, Simulation,Verification, Optimization, and Testing,?Hardware Accelerators?Device Drivers?System-on-chip? Case Studies (Applications of Embedded Systems)Resources:1. Rajib Mall, “Real-time Systems Theory and Practice”,Pearson Education, 20072. Wayne Wolf, “Computers as Components Principles ofEmbedded Computer System Design”, Morgan Kaufmann /Elsevier, 2005Advanced Digital Signal ProcessingCourse Code:EEN-821Credit Hours:3Pre requisite:NoneObjectives:This course introduces the digital filter design and itsapplications to the students.Course Outline:? Review of DSP( 2- 3 weeks for review )o Discrete-time Signalso Input-Output Relationshipso Discrete-Time Networkso Sampling of SignalsDiscrete Fourier Transform & FFT Algorithms IIR, FIR Filters Design of signal-processing system Numerical Computation Conversion technologies and data acquisition Implementation/description of algorithms for DSP architectures Advanced digital filter design Wiener filter Parks-McClellan algorithm Multi-rate DSP Decimation, Interpolation Sampling rate conversion Applications FFT applications Advance FFT Algorithms Efficient algorithm design e.g. Wireless Communication Transceivers DSP applications Modulation Schemes oSpeech Processing ApplicationsoImage ProcessingResources:1.Emmanuel Ifeachor and Barrie Jervis, “Digital SignalProcessing - A Practical Approach”, 2nd edition, PrenticeHall (Pearson Education), 20022.John G. Proakis, “Digital Signal Processing”, 4th edition,20063.John G. Proakis & Dimitris G. Manolakis , “Digital SignalProcessing: Principles, Algorithms and Applications”, 3rdedition, Prentice Hall, 19964.Vinay K. Ingle, John G. Proakis, “Digital Signal ProcessingusingMatlab”,20065.Alan Oppenhein & Ronald Schafer, “Discrete-Time SignalProcessing”, 2nd edition, Prentice Hall, 1999Advanced Digital System DesignCourse Code:EEN-822Credit Hours:3Pre requisite:NoneObjectives:The course introduces the students to the design and analysisof the digital system.Course Outline:? Application-Specific Integrated CircuitsoASICs: types, economicso The ASIC design flowoValidation methods? System on Chip (SoC)?Validation, Verificationo Simulation versus formal verificationoCombinational equivalence checkingoSequential equivalence checkingoModel checking?Simulation?Hardware acceleration? VHDL language, from specification to modelo Principles of Event Driven Simulationo Practical Organization of Files and ProjectsoCompilation UnitsoSyntax?Sequential VHDL?Concurrent VHDLoStandardized PackagesoLogic Synthesiso Symphony EDA (a full featured VHDLsimulator)? Application-specific instruction-set processor(ASIP) design? Field-programmable gate array (FPGA)?Hardware Design Methodologies?Case Study? gEDA (GPL Electronic Design Automation)?Programmable logic deviceso PLA, PAL, GAL, CPLD, FPGAoComparative AnalysisResources:1. MichaelJohn Sebastian Smith, “Application specificintegrated circuits”, Addison-Wesley, 19972. Peter J. Ashenden, “Designer's guide to VHDL”, MorganKaufmann, 20023. Mark Balch , “Complete digital design: a comprehensiveguide to digital electronics and computer systemarchitecture”, McGraw-Hill, 2003,4. Wayne Hendrix Wolf, “Modern VLSI design: systems on chipdesign” Prentice-Hall, 20025. Mark Zwolinski, “Digital system design with VHDL”,Prentice-Hall, 2004ASIC Design MethodologyCourse Code:EEN-823Credit Hours:3Pre requisite:NoneObjectives:The course gives an introduction to the design and analysis ofApplication Specific Integrated Circuits (ASICs). The main focuswould be on, logic and physical synthesis, verification andtesting. Describe the different phases of the design flow fordigital ASICs, how non-functional design constraints affect thedesign process, categorize different types of ASICs and explaintheir technology, apply techniques to analyze the timing of thefinal implementation.Course Outline:?The design and analysis of Application SpecificIntegrated Circuits (ASICs)?Logic and physical synthesis?Verification and testing?Introduction to analog mixed signal Integrated circuitdesign?The different phases of the design flow for digital ASICs?Non-functional design constraints?Categorize different types of ASICs and explain theirtechnology?Techniques to analyze the timing of the finalimplementation.Resources:1.M.J.S. Smith, “Application-Specific IntegratedCircuits”, Addison-Wesley, ISBN 0-201-50022-1, 1997.2.HimanshuBhatnagar, “Advanced ASIC Chip Synthesis UsingSynopsys Design Compiler Physical Compiler andPrimeTime”. 20013.N. H. E. Weste and D. Harris, “CMOS VLSI Design: A Circuitsand Systems Perspective”, 3rd Edition Addison-Wesley,20044.J. Rabaey , A. Chandrakasan , B. Nikolic , “Digital IntegratedCircuits: A Design Perspective” 2nd Edition, Prentice Hall,20035.W. Wolf, “Modern VLSI Design: System-on-Chip Design”,3rd Edition, Prentice Hall, 20026.Thoman Kropf, Formal Hardware Verification, Springer1999.Power Aware ComputingCourse Code:SEN-805Credit Hours:3Prerequisites:-Objectives:This course basically describes the Flip Flops and Applications of Data Gating indynamic Flip Flops for High Speed. LowPower Sandwich/Spin Tunneling MemoryDevices and Micro Architecture Design and Control Speculation for EnergyReduction are also discussed. From application point of view a CompilerTargeting ASICs and FPGAs with Power and Performance.Course outline:? Comparative analysis of Flip Flops and Applications of Data Gatingin dynamic Flip Flops for High Speed, Low active and Low LeakagePower Dissipation? Low Power Sandwich/ Spin Tunneling Memory Device? Power Efficient Issue Queue Design? Micro Architecture Design and Control Speculation for EnergyReduction? Energy Exposed Instruction Sets? Dynamic Management of Power? Power Management Points in Power Aware Real Time Systems? A Power Aware API for Embedded and Portable Systems?A Compiler Targeting ASICs and FPGAs with Power andPerformance Optimization.? Compiler Optimization for Low Power Systems? Power Performance Tradeoffs in Second Level Memory Used by anARM like RISC Architecture.? Application Level Power Awareness? Challenges for Architectural Level Power Modeling?Software Energy ProfilingResources:Power Aware Computingby Robert Graybill and Rami Melhem, 2010.Advanced Artificial IntelligenceCourse Code:SEN-809Credit Hours:3Prerequisites:Objectives:This course in Artificial Intelligence (AI)deals with the coverage of search,knowledge representation and reasoning, machine learning (paradigms, models,and algorithms), use of knowledge in learning, and AI applications. The emphasisof the course is on recent developments in AI, especially contributions thatforged novel connections among diverse areas, or addressedproblems ofsignificant impact. The goal is to emphasizecertain thematic issues that recur inAI systems and applications.Course outline:?Basics of intelligent agents?Uniformed search including breadth-first, depth-first, iterativedeepening, bidirectional etc.?Informed search including best-first, A*, iterative deepening A*,Heuristics?Understanding of game playing?understanding of propositional logic and inference procedures?First order logic and inference procedures?Introduction to neural networks?Different types of neural networks?Understanding of machine learning algorithms?Different clustering, classification and association algorithmsResources:1.Artificial Intelligence: The Basics by K. Warwick , 20112.Artificial Intelligence: A Modern Approach (3rd Edition) by Stuart Russelland Peter Norvig, 20093.A.I. Artificial Intelligence [Blu-ray] Starring Haley Joel Osment, Jude Law,Frances O'Connor, et al. , 2011Advanced Neural NetworksCourse Code:SEN-810Credit Hours:3Prerequisites:Artificial IntelligenceObjectives:This course presents an overview of the theory and applications of artificialneural network and fuzzy systems to computer science and software engineeringapplications. The objective of this course is on the understanding of variousneural network and fuzzy systems models and the applications of these modelsto solve computing/software engineering problems.Course outline:Introduction Contexts for and Motivation Neural Networks: Artificial IntelligenceArtificial Neural Network overview.Supervised Learning: Single-Layer Networks , Perceptrons , Adalines SupervisedLearning: Multi-Layer Networks.Multi-Layer Perceptrons (MLPs) , Backpropagation , Conjugate Gradient method ,Levenberg-Marquardt (LM) method , Madalines , Radial-Basis Networks ,Cascade-Correlation Networks , Polynomial Networks , Recurrent Networks(Time series , Backpropagation through time , Finite Impulse Response (FIR) MLP), Temporal Differences method (TD).Unsupervised LearningSimple Competitive Networks: Winner-take-all | Hamming network , LearningVector Quantization (LVQ), Counterpropagation Networks (CPN) , AdaptiveResonance Theory (ART) , Kohonen Self-Organizing Maps (SOMs) , PrincipalComponent Analysis networks (PCA)Associative ModelsLinear Associative Memory (LAM) , Hopfield Networks , Brain-State-in-a-Box ,BSB) , Boltzmann Machines and Simulated Annealing , Bi-Directional AssociativeMemory (BAM)Optimization ProblemsNeural Network Approaches, Evolutionary Programming , Fuzzy logic and its connection to NNsResources:1. Neural Networks: A Comprehensive Foundation, Simon Haykin, Prentice Hall,Upper Saddle River, NJ, SECOND EDITION, 1999Artificial neural networks: an introduction, by Kevin L. Priddy, Paul E. Keller-Technology & Engineering-2005 Neural networks: methodology and applications, by G. Dreyfus-computers-, 2005 Data Warehousing and MiningCourse Code:SEN-811Credit Hours:3Prerequisites:Database Management SystemData Structures and AlgorithmsObjectives:By the end of this course students will be familiar with concepts of DataWarehousing including: Strategic need of data warehousing, Building blocks of adata warehouse, Data warehouse project management, Business requirementsof a data warehouse, Architectural components of a data warehouse, Datawarehouse metadata management, Dimensionality Modeling, ETL & Dataquality, Online Analytical Processing, as well as the following areas of datamining: Motivation for data mining, Data Preprocessing, Data mining primitivesand query languages, Architectures of data mining systems, Major Data MiningTasks, Cluster Analysis , Statistical measures in large databases, Classificationsand Predictions, Anomaly DetectionCourse outline:Introduction to Data Warehouse, Planning and Requirements, DataWarehouse Architecture, Data Warehouse Infrastructure, DimensionalModeling, Metadata, Extraction, Transformation and Loading, OnlineAnalytical Processing, Data Preparation Techniques: outlier and missingdata analysis, Data Reduction Techniques, Introduction to Data Mining,Modeling and Principal Feature Extraction, Clustering, HierarchicalClustering, Partitional Clustering, Classification , Decision TreeClassification, Bayesian Classification, Nearest Neighbor Classification.Resources:1.Data Warehousing Fundamentals for IT Professionals, Paulraj Pooniah,Wiley, 2nd Edition, 2010.2.Data Mining Concepts & Techniques, Jaiwei Han, Micheline Kamber, 2ndEdition, 2005.3.Tutorial on Data Mining, Eamonn KeoghMachine LearningCourse Code:SEN-812Credit Hours:3Prerequisites:Computer ProgrammingStatisticsObjectives:This course is an overview of concepts and techniques in machinelearning, beginning with topics such as classification and linear regressionand ending up with more recent topics such as boosting, support vectormachines, hidden Markov models, and Bayesian networks. The course willgive the student the basic ideas behind modern machine learningmethods.Course outline:Introduction to Machine Learning, Concept learning, Decision treelearning, Linear models for regression, Linear models for classification,Artificial neural networks, Kernel methods, Sparse kernel machines,Mixture models and the EM algorithm, Evaluation, Combining multiplelearners, Support vector machines, Bayesian networksResources:1. C. M. Bishop, Pattern recognition and machine learning, Springer,2006.2. Tom M. Mitchell, Machine Learning. McGraw-Hill, 1997.Formal Methods and SpecificationsCourse Code:SEN-710Credit Hours:3+0Prerequisites:NoneObjectives:As more complex computational systems are used within criticalapplications, it is becoming essential that these systems are formallyspecified. Such specifications are used to give a precise and unambiguousdescription of the required system. While this is clearly important incritical systems such as industrial process management and air/space craftcontrol, it is also becoming essential when applications involving E-commerce and mobile code are developed. In addition, as computationalsystems become more complex in general, formal specification can allowus to define the key characteristics of systems in a clear way and so helpthe development process. Formal specifications provide the basis forverification of properties of systems.Course outline:Introduction to formal methods and specification, State-Based FormalMethods;Transformationalsystems,traditionalapproaches,Zspecification, formal development cycle, Refinement, TemporalSpecification : reactive systems; syntax and semantics of temporal logic,temporal specification of reactive systems (safety, aliveness, fairness),Model Checking : generating finite models;analysis of a simple modelchecking algorithm, symbolic model checking, overview of reductionmethods, "on the fly" model checking, Spin and Promela, Case study andpractical verification of properties.Resources:1. Using Z: Specification, Refinement and Proof, J. Woodcock and J.Davies Prentice Hall, 1996.Model Checking, E. M. Clarke, O. Grumberg, and D. Peled MIT Press, 2000. Human Aspects in Software EngineeringCourse Code:SEN-719Credit Hours:3Prerequisites:Software engineeringObjectives:Extensive human involvement in software development has made humansan important stakeholder in software process. Furthermore, due toemerging paradigm of end user development where end users also takeup the role of software enhancement, need for understanding humanaspects has become more critical. The goal of this course is to provide anintroduction to the fundamental human aspects in software developmentprocess. Students will also be introduced to end user softwareengineering paradigm and underlying issues.Course outline:Software Evolution, Program Comprehension, Development TeamProcesses, Software development tools and environments, Quantitative &qualitative evaluation of software engineering researchSoftwareDevelopment Environments, The Nature of Software Engineering (SE),Software as a Product, Software-Human Interaction, Learning Processes inSE, Program Comprehension, Code Inspections, and Refactoring,Abstraction and Other Heuristics of Software Development, Meta Design,System Design and Tailor ability, Technology Appropriation, End UserSoftware Engineering, Psychological issues in end user softwareengineering, Integrated software engineering approach to end userdevelopment.Resources:1. End-User Computing, Development, and Software Engineering:New Challenges: New Challenges Ashish Dwivedi and Steve Clarke,2012Human Aspects of Software Engineering James Tomayko, Orit Hazzan 2004 End User Development Henry Lieberman, Fabio Paterno, and Volker Wulf, Springer 2006 Advanced Engineering MathematicsCourse Code:MAT-853Credit Hours:3Prerequisites:-Objectives:There are three main objectives of this course. First, an introduction theconcepts of partial differential equations and complex variables and some basictechniques for analyzing these problems. Second, by studying the application ofPDE's to physics, engineering, and biology, the student will begin to acquireintuition and expertise about how to use these equations to model scientificprocesses. Finally, by utilizing numerous numerical techniques, the student willbegin to visualize, hence better understand, what a PDE is and how it can beused to study the Natural Sciences.Course outline:Review of main topics of B.S.Engineering Mathematics: Multivariable calculus,ordinary differential equations, linear algebra, numerical methods, mathematicalstatistics. Partial Differential Equations: Classical PDE’s and boundary valueproblems, separation of variables, boundary value problems in cylindrical andspherical polar coordinates. Non-homogeneous boundary valueproblems.Mathematical Modeling:Stochastic Techniques, Generationfunctions,Convolutions, Compound distributions, Introductory Stochastic processes,Simulation, Introductory simulations, Generation of random numbers.Probabilistic modeling: Markovian Models, Exponential distributions, Poissonprocesses. Complex Analysis: Taylor and Laurent series, zeros, singularities andresidues, Integration of analytic functions, conformal mapping. Linear Algebra:Unitary, Normal and Hermition matrices, Decomposition of matrices intotriangular factors, Eigen values and Eigen Vectors, Diagonalization, powers ofmatrices, method of least squares.Resources: 1. E. Kreyszig, Advanced Engineering Mathematics, 9th Edition, John Wiley and Sons, New York.Nguyen V.M. Man, Mathematical Modeling and Simulation. E.C. Zachmanoglou and D.W. Thoe, Introduction to Partial Differential Equations with Applications, Dover, 1986. Dennis G.Zill And Warren S. Wright, Advanced Engineering Mathematics Jones and Bartlett, 2011 G. Strang, Linear Algebra and its Applications, 4th Edition, Wellesley-Cambridge Press, 2009. Logic and ResearchCourse Code:MGT-801Credit Hours:3Prerequisites:-Objectives:This course will look at the domain of logic in terms of its structure, dynamicsand intellectual debates within it.The course also aims at enabling the studentsto understand the articulation of the principles of logic with the process ofresearch and knowledge production within behavioral sciences with a particularfocus on Management research.The course would also discuss the interfacebetween logic and construction of theory and see how theory can be utilized inthe process of research.Course outline:The course will discuss in detail the field of logic, with reference to its history,nature, types and composition. The course would also discuss the interfacebetween logic and construction of theory and see how theory can be utilized inthe process of research. Of pivotal significance for this course would be adiscussion of the relationship between language and research with reference tothe product of research as well as the interaction between the researcher andthe researched. It would also look in detail at the domain of philosophy ofscience. It will also comprise a discussion of issues of significance in behavioral &management research to include concepts, laws, explanations, causation,measurement and models. The course would also strive to look at discussion ofhow values can affect behavioral and management science research and variousmeans of dealing with the same.Resources:1.The Logic of Social Research by Arthur L. Stinchcombe, 20052.Constructing Social Theories by Arthur L. StinchcombeAdvanced Qualitative Research MethodsCourse Code:MGT-802Credit Hours:3Prerequisites:-Objectives:This course aims at offering an introduction to qualitative research methods.Participants will learn about the usefulness of qualitative research methods, thephilosophical and theoretical underpinnings of this type of research, the variousapproaches and schools of thought, as well as about particular researchmethods. Finally, the course will also place qualitative approaches and methodswithin the broader research design, i.e., in the case of engineers, often as acomplement to quantitative research. But most of all, the course will help theparticipants to make progress in the formulation of their problem statement,their research design, qualitative data collection, and analysis of qualitative data.Course outline:? Bases of classification of research? Qualitative research vis-à-vis quantitative research? Major dimensions of differences between quantitative researchand qualitative research? Explain and apply different approaches to qualitative researchincluding the following:- grounded theory, ethnography, phenomenology, narrativeinquiry, and case study- Select and use different tools of data collection suchas:Interviewing,Focus Group, Observation methods, and Visualmethods.Resources:Qualitative Research Methods for the Social Sciences, 7th Edition by Bruce L. BergDec 13, 2008 Qualitative Research & Evaluation Methods by Michael Quinn PattonOct 2001 Qualitative Research: A Guide to Design and Implementation by Sharan B. Merriam , Apr 6, 2009 Advanced Quantitative Research MethodsCourse Code:MGT-806Credit Hours:3Prerequisites:-Objectives:The purpose of this course is to introduce some important fundamental conceptsof quantitative research especially to novice researchers. It comprises types ofresearch, definitions of quantitative research, different types and assumptions ofquantitative research, when to use and not to use quantitative methods,advantages, common approaches and samples of quantitative research, andcommon misconceptions. Besides, a set of criteria for evaluating quantitativeresearch proposal is provided. The main focus is on the assumptions underlyingthe quantitative research and some of the misconceptions that many researchershave when they are conducting a research study.Course outline:Introduction to Research, Quantitative Research,Interpreting the Natural WorldTestable and Untestable, Logic and Arguments, Types of Research, TheHypothesis, Introduction to Testing Observations, Theory and Hypothesis,Formulating a Technical Hypothesis, Relationships Between Variables,Conceptual, Operational, Measurable, Observation of Human Systems,Research Plan , P-value and the Null, Problems in Observation, DescriptiveStatistics, Overview of Descriptive Statistics, Standard Deviation and Variance,Types of Variables, The Experiment, Sources of Variability, ANOVA, The Survey,Introduction to the Survey, Survey Design, Asking Questions, The Index ,TheScale, Survey Stats Overview,Sampling, Designing a Study, The Task ofWriting,Statistical Testing Overview ,Graphing Data.Resources:1. Quantitative Research: An Introduction by Benjamin Mis, 2012.2. Quantitative and Statistical Research Methods: From Hypothesis toResults , William E. Martin and Krista D. Bridgmon, 2012.3. Research Design: Qualitative, Quantitative, and Mixed MethodsApproaches by John W. Creswell , 2008.Critical Review of LiteratureCourse Code:MGT-803Credit Hours:3Prerequisites:-Objectives:This course deals with the various methods for searching and reviewing ofthe literature. Developing an argument, its analysis and building theargument of discovery are also discussed in this course. The course alsoaims to describe Tools for structuring a research thesis and how to citereferences, and prepare bibliography in different styles.Course outline:The Literature Review in Research: Why?For Whom?How? TheLiterature Review Process – Getting Started, Reviewing and the ResearchImagination,Search the Literature, Developing an Argument:Argumentation and Analysis,Survey the Literature: Building the Argumentof Discovery, Critique of the Literature and Structure of Criticism, Mappingand Analyzing Ideas, Structuring the Literature Review, Writing theLiterature Review and the Writing Process, Being Critical in Writing theLiterature Review, and Academic Writing,Managing Information andKeeping the Records, The Research Proposal and its Format, Tools forStructuring a Research Thesis and How to Cite References, and PrepareBibliography in APA Style.Resources:1. Writing Literature Reviews Fourth EDITION by Jose L. Galvan, 20092. The Literature Review: Six Stepsto Success by Lawrence A.Machi and Brenda T. McEvoy, 20083. Preparing Literature Reviews: Qualitative andQuantitativeApproaches by M. Ling Pan, 2008Computer VisionCourse Code:CSC-750Credit Hours:3Prerequisites:Digital Image ProcessingObjectives:B y the end of this course, the students would have developed an understandingof the problems in simulating human perception into machines. Students willhave a thorough understanding of the state of the art computer vision methods,algorithms and results. The students will also be able to apply the tools andtechniques learned to solve practical vision related problems.Course outline:Introduction to Computer Vision and related areas along with applications,Image formation and representation: imaging geometry, digitization, camerasand projections, rigid and affine transformations, Filtering: convolution,smoothing,. Segmentation: region splitting and merging; quadtree structures forsegmentation; Feature detection: edge detection, corner detection, line andcurve detection, SIFT and HOG descriptors, shape context descriptors. Modelfitting: Hough transform, line fitting, ellipse and conic sections fitting, algebraicand Euclidean distance measures. Camera calibration: camera models; intrinsicand extrinsic parameters; affine, and perspective camera models. Epipolargeometry: introduction to projective geometry; epipolar constraints; theessential and fundamental matrices; Motion analysis: the motion field of rigidobjects; motion parallax; optical flow, the image brightness constancy equation,affine flow; differential techniques; feature-based techniques; Motion tracking:the Kalman filter; Object recognition and shape representation.Resources:1. Computer Vision: Algorithms and Applications, R. Szeliski, Springer, 2011.2. Computer Vision: A Modern Approach, D. Forsyth and J. Ponce, Prentice Hall,2nd ed., 2011.3. Computer Vision: A Modern Approach, By David Forsyth, Jean Ponce,Prentice Hall, 2003.4. Computer Vision, By Linda G. Shapiro, George C. Stockman, Prentice Hall,2001.5. Handbook of Mathematical Models in Computer Vision, By Nikos Paragios,Yunmei Chen, Olivier Faugeras, Birkh?user, 2006Pattern RecognitionCourse Code:CSC-715Credit Hours:3Prerequisites:1.Probability and Statistics2.Linear AlgebraObjectives:The goal of this course is to provide an introduction to the fundamentalconcepts of machine learning and pattern recognition with examples fromseveral application areas. The students will be acquainted with real worldregression and classification problems and the models and classifiers tosolve these problems. Students will also be introduced to dimensionalityreduction and feature selection concepts. Additionally, students will beexposed to various clustering techniques. A key objective to this course isfor the students to also acquire hands-on experience related toclassification and clustering tasks.Course outline:Introduction to Pattern recognition and Machine learning, Matrices andvectors: Toeplitz and Vendermonde matrices, classification and regression,Bayesian Decision theory, Normal Density and decision functions fornormal distribution, Maximum likelihood estimation, Dimensionalityreduction – Component analysis, feature selection, Hidden MarkovModels and Artificial neural networks, Non-parametric methods,Unsupervised learning and clustering: Clustering techniques.Resources:1. Pattern Classification, Duda, Hart and Stork, Second Edition, Wiley, 2001.2. Pattern recognition and Machine Learning, Christopher M. Bishop,Springer, 2007.3. Introduction to Machine Learning, Ethem Alpaydin, MIT Press, 2004.4. The Elements of Statistical Learning, Trevor Hastie, Robert Tibshirani andJerome Friedman, Springer, 2009.5. Pattern Recognition, S. Theodoridis & K. Koutroumbas, Academic Press,2008.Agent Based ModelingCourse Code:CSC-815Credit Hours:3Prerequisites:-Objectives:After taking this course, the participants:?will have an understanding of the agent system terminology anddevelopment process of agent-based systems.?will have learned techniques to design agent-based system.?will know how to modify architecture of the current softwaresystems and re-structure them to be agent-based.Course outline:1.Introduce the basic concepts of agent-based modeling;2.When and why agent-based models are used;3.Methodologies for agent-based modeling, analysis and design.4.Agent-based Unified Modeling Language (AUML)5.Agent communication and knowledge sharing.6.Agent-based System Architecture and Organization.7.FIPA: Foundation for Intelligent Physical Agents.8.Agents and web services9.Mobile Agents10.Simulation of agent Based Modeling11. Standards for Agents and Agents based SystemsResources:1.The Agent Modeling Language--AML: A Comprehensive Approachto Modeling Multi-agent Systems by Radovan Cervenka and IvanTrencansky 20072.Multiagent Systems : A Modern Approach to Distributed ArtificialIntelligence, Gerhard Weiss, MIT Press, 1999.3.Readings in Agents, M.N. Huhns and M.P. Singh, MorganKaufmann Publishers. 1998.4.Heterogeneous Agent Systems, V. S. Subrahmanian, Piero Bonatti,Jurgen Dix, Thomas Eiter and Fatma Ozcan. 20005.Constructing Intelligent Agents Using Java: ProfessionalDeveloper's Guide, (432 pages) Joseph P. Bigus, Jennifer Bigus,(2nd Edition) John Wiley and Sons. 2001.6.Agent-Oriented Methodologies, Brian Henderson-Sellers, PaoloGiorgini. 2005Bio Medical Image AnalysisCourse Code:CSC-816Credit Hours:3Prerequisites:Computer Vision/Digital Image ProcessingObjectives:The objective of the course is to learn how to “process” signals to obtainmedical images for each modality (based on its physics, mathematicalmodeling and instrumentation) but not digital signal processing (DSP) ofmedical imaging.Course outline:?Course overview? Introduction of medical imaging?Signals and system?Imaging quality?Physics of radiography?Projection radiography?Computed tomography (CT)? Physics of nuclear medicine?Planer scintigraphy? Emission computed tomography (SPECT, PET)?Physics of ultrasound?Ultrasonic imaging systems? Electrical impedance tomography (Guest lecture by Prof. A. Adler)? Physics of magnetic resonance? Magnetic resonance imaging (MRI)?Project presentation? Course review and wrap upResources:Medical Imaging Signals and Systems, by J.L. Prince and J.M. Links,Pearson Prentice Hall, 2006 ................
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