May 02, 2024  
2021-2023 Graduate Catalog 
    
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2021-2023 Graduate Catalog [ARCHIVED CATALOG]

College of Engineering

Lin Li, PE, Ph.D., Interim Dean
203 Andrew P. Torrence Hall (615) 963-5401
lli1@tnstate.edu

 

Tamara Rogers, Ph. D., Co-coordinator of Graduate Program 
Associate Professor 
005F McCord Hall (615) 963-1520 
trogers3@Tnstate.edu

 

Muhammad Akbar, Ph. D., P.E., Co-coordinator of Graduate Program 
Associate Professor 
138C Andrew P. Torrence Hall (615) 963-5392 
makbar@tnstate.edu 

The College of Engineering includes the departments of Civil and Architectural, Electrical and Computer Engineering, Mechanical and Manufacturing Engineering, Applied and Industrial Technologies, and Computer Science. The College has about 41 faculty full-time faculty and about 98 percent of them hold Ph.D. degrees. The Tiger Institute, TSU Interdisciplinary Graduate Engineering Research, has an average operating budget of 2 million dollars per year and supports about fifteen different research projects.

 

Degree Programs

Engineering and Computational Sciences (ENCS) Ph.D.
Computer, Information, and Systems Engineering M.S.
Computer Science M.S.
Data Science M.S.
Engineering M.E.

 

Major: Engineering and Computational Sciences (ENCS)
Degree: Doctor of Philosophy (Ph.D.)

Concentrations:
(1) Engineering Systems and (2) Computational Sciences

Major: Computer, Information and Systems Engineering (CISE)
Degree: Master of Science (M.S.)

Major: Data Science
Degree: Master of Science (M.S.)

Major: Computer Science
Degree: Master of Science (M.S.)

Concentrations:

  • Cyber Security & Networking
  • Data Science
  • High-Performance Computing & Bioinformatics

Major: Engineering
Degree: Master of Engineering (M.E.)

Concentrations:

Biomedical Engineering
Civil Engineering
Electrical Engineering
Environmental Engineering
Environmental Management
Manufacturing Engineering
Mechanical Engineering

The College of Engineering offers work leading to the Master of Engineering (M.E.) degree with six concentrations: Biomedical Engineering, Civil Engineering, Electrical Engineering, Environmental Engineering, Manufacturing Engineering, and Mechanical Engineering.

  

Programs

Master of Engineering

Master of Science

Doctor of Philosophy

Courses

Electrical Engineering

  • EECE 5610 - Stochastic Estimation Methods for Engineering Design (3)

    The linear Kalman Bucy filter, non-linear filtering, the extended Kalman filter, and second order filters. Structure of stochastic feedback control system. Interplay between modeling issues and mathematical design. Practical aspects of compensator realization. Prerequisite(s): ENGR 5300 .

  • EECE 5630 - Modern Control Systems (3)

    Analysis and design of multi-variable systems; matrix theory, state variable and state space analysis and design, Cayley-Hamilton Theory, continuous-time and discrete-time domain analysis and design, intrinsic properties of controllability and observability, stability analysis of linear and nonlinear dynamic systems with direct method of Lyapunov. Prerequisite(s): EECE 4000 or equivalent.

  • EECE 5640 - Advanced Topics in Control Systems (3)

    Methods for design and analysis of stationary and time-varying control systems are presented. Advanced control system design techniques such as observability and controllability using state-space representation are emphasized. Adaptive, optimal, and robust control system designs are also studied. Artificial Intelligence approaches to controller system designs are introduced. Prerequisite(s): ENGR 5200 - Modeling and Simulation of Dynamic Systems (3)  or equivalent.

  • EECE 6220 - Robust Control Theory (3)

    Introduction to the theory and techniques of Robust Control. The three distinct and major problem areas to be covered are the parametric approach, the H• theory and the L1 theory. As linear system basics, topics include stability, performance, robustness, stable factorization and YJBK parameterization, and approximation of linear systems. In the parametric approach, topics include Kharitonov’s theorem, parametric stability margins, polytopic systems, generalized Kharitonov’s theorem, edge theorem, mapping theorem as well as mixed uncertainty problems. In H• theory, topics include small gain theorem, Nevanlinna-Plok interpolations and factorization theory, various H• control problems, and DGKF solution. H•/H2 optimal control, and L1 optimal control problem are also covered in this course.

  • EECE 6230 - Nonlinear Control Systems (3)

    Introduction to the concepts of nonlinear control systems. Topics include nonlinear system representation, nonlinear transformation, phase plane analysis, linearization and local stability, Lyapunov direct method, Lyapunov analysis for non-autonomous systems, positive linear systems, passivity in linear systems, absolute stability and Popov criterion, and feedback linearization.

  • EECE 6250 - Digital Spectral Analysis (3)

    Review of classical parametric models of random processes and spectral estimation methods, autoregressive spectral estimation: block data algorithms and sequential data algorithms, autoregressive-moving average spectral estimation, Prony’s method, minimum variance spectral estimation and eigen analysis based frequency estimation. Prerequisite(s): EECE 5220  or equivalent.

  • EECE 6260 - Pattern Recognition and Classification (3)

    Fundamental problems in pattern recognition system design, design of learning and adaptive machines, elementary decision theory, classification rules, pattern classification by distance functions and likelihood functions, deterministic and statistical approach to trainable pattern classifiers, pattern preprocessing and feature selection, elements of syntactic pattern recognition and adaptive classifiers, Prerequisite(s): Graduate standing.

  • EECE 7200 - Statistical Signal Processing (3)

    Introduction to random process, detection and estimation theory, maximum variance unbiased estimation, Cramer-Rao lower bound, general minimum variance unbiased estimation, best linear unbiased estimation, maximum likelihood estimation, Least square methods of estimation, method of moments: second moments analysis, Bayesian philosophy and Bayesian estimators, and applications to communications and radar systems. Pre-requisite: EECE 5220 and graduate level probability and statistics. Prerequisite(s): EECE 3200.

  • EECE 7210 - Adaptive Control Systems (3)

    Introduction and overview of the theoretical and practical aspects of adaptive control. Topics include real-time parameter estimation, deterministic self-tuning regulators, model reference adaptive control, auto tuning, gain scheduling, and robust systems. Some new results in adaptive neural networks are included.

  • EECE 7220 - Intelligent Control Systems (3)

    Study analysis and design of intelligent control systems using soft computing methodologies. Concept of intelligent systems, neural network architectures such as; recurrent neural networks, CMAC neural networks, radial basis function (RBF) networks, and reinforcement learning. The concept of fuzzy logic, fuzzy inference systems (FIS), and artificial neuro-fuzzy inference systems (ANFIS) will be introduced. Applications of intelligent control system to autonomous robots, flight control and other intelligent machines will be presented.

  • EECE 7230 - Adaptive Filtering and Stochastic Control Systems (3)

    Wiener filter theory, linear prediction, adaptive transversal filters using gradient-vector estimation, Kalman filter theory and its applications to transversal filters, method of least squares, adaptive transversal filters using recursive least squares, design of adaptive estimator and control systems. Prerequisite(s): Graduate standing.

Engineering & Computational Sciences

  • ENCS 5300 - Fundamentals of Nanomaterials (3)

    This course focuses on the chemical, physical and mathematical concepts that describe and explain the properties of matter at the nano-scale. It will emphasize the fundamental chemistry, physics, and mathematics needed to understand the molecular driving forces underlying self-assembly processes and the methods used to characterize the resulting nanomaterials. It will also cover applications of nanomaterials.

  • ENCS 6010 - Advanced Applied Mathematics (3)

    This course covers advanced mathematical topics including linear algebra, numerical methods, Fourier Analysis, discrete mathematics, probability and statistics, and algebraic structures, with special emphasis on applications in engineering and computational sciences.

  • ENCS 6020 - Advanced Computing (3)

    This course provides fundamental knowledge, skills, and tools for the computation undertaken on high-end computers, computer networks, or personal computers. The topics include: programming and programming languages; data structures, algorithms and computational complexity; high performance computing; distributed computing; optimizations; statistical data analysis; computational error analysis. Selected engineering applications of advanced computing techniques will also be covered

  • ENCS 6030 - Modeling and Simulation of Cyber Physical Systems (3)

    The principles of modeling, simulation and design, including establishment of specifications and conducting analysis of cyber-physical systems consisting of devices communicating with one another and interacting with the physical world via sensors and actuators are studied. Topics include synchronous and asynchronous models as well as timed model, safety and liveness requirements, and real-time scheduling. Some aspects of modeling and simulation of dynamics systems and hybrid systems are also studied.

  • ENCS 6110 - Advanced Robotic Systems (3)

    This course primarily presents a review of robot transformations, kinematics, dynamics, differential motion, motion and path planning, manipulation and mobility control. Advanced topics include: multi-robot system cooperative and collaborative task planning and execution, robotic sensors interfacing and integration, passive and active sensing, processing, and reasoning. Student will have opportunity to learn about robotic software, sensors, and hardware thru laboratory hands-on projects.

  • ENCS 6120 - Mechatronics Systems Design (3)

    This course is aimed to cover from preliminary knowledge of mechatronics theories to a project-based mechatronic system design. The multidisciplinary content of this course include: mechanisms, electronics, sensors, control strategies with software, firmware, and hardware in the control loop. This course also discusses techniques and skills related to integrating mechatronics systems with sensors, robotics systems, programmable logic controller (PLC), and man-machine interfaces. Students who successfully complete this course should be able to tackle multidisciplinary engineering design projects requiring tight integration of mechatronics components and sub-components in support of embedded electromechanical mechanism and control systems.

  • ENCS 6200 - Engineering Design Optimization (3)

    Computerized design methods for optimization techniques. Formulation of optimization problems using design variables and constraints. Problem solving with mathematical models, deterministic optimization methods in operations research, linear programming models, simplex method, duality and sensitivity in linear programming. Nonlinear optimization and multi-objective function optimization, constrained and unconstrained problems.

  • ENCS 6210 - Engineering Management And Quality Control (3)

    This course is an introduction to the engineering management strategies applied on the project and organization level in different engineering fields such as construction, manufacturing and energy management. It also introduces traditional methodologies and techniques applied in quality control of engineering projects.

  • ENCS 6260 - Engineering Statistics And Probability (3)

    The course discusses and applies rigorous and systematic statistical methods for solving applied science problems, identification of the empirical setting of the research problem and methodology, data management, choice of statistical, and analysis mechanics and ability of student to use statistical analysis tools for solving engineering problems. Different statistical modeling approaches will be covered (linear, categorical, generalized, time series, survival models, etc.) using statistical analysis software packages and interpreting statistical results.

  • ENCS 6280 - Finite System Analysis (3)

    Theoretical basis of finite element method. The physical and mathematical modeling using various element types. Application to various engineering problems. Application of commercial FAE software to solving complex engineering problems.

  • ENCS 6300 - Micro- and Nano-fabrication and Characterization Techniques (3)

    This course presents the fundamental principles and techniques used in fabricating micro- and nano-scale structures and devices including lithography, oxidation, diffusion, ion implantation, and methods of film deposition and etching. Further, an overview of the characterization of materials and micro-/nano-scale structures, measurement techniques, and packaging will also be covered. Future trends and challenges in micro-/nano-device manufacturing will also be discussed.

  • ENCS 6410 - Transportation Facilities Evaluation and Design (3)

    Analysis of quantity, capacity, quality and accessibility of transportation systems, concepts and applications of transportation facilities. Public and non-motorized transportation, decision-making techniques in transportation planning and economic analysis of transportation systems. Design, construction, maintenance and management of transportation structures.

  • ENCS 6420 - Transportation and Environmental Sustainability (3)

    Evaluation of transportation and environmental engineering relationship; transportation impact to land use and growth management; transportation and environmental impacts, equity and policies; the role of non-motorized and transit transportation to sustainability; environmental justice; alternative fuel; autonomous and connected vehicles; complete streets, environmental and energy policies; air pollution and vehicle emission estimation models; green-house gases and climate change.

  • ENCS 6430 - Pavement, Environmental and Ground Water Design (3)

    Evaluation of transportation and environmental engineering relationship; transportation impact to land use and growth management; transportation and environmental impacts, equity and policies; the role of non-motorized and transit transportation to sustainability; environmental justice; alternative fuel; autonomous and connected vehicles; complete streets, environmental and energy policies; air pollution and vehicle emission estimation models; green-house gases and climate change.

  • ENCS 6440 - Environmental and Transportation Risk Analysis (3)

    Statistical Applications for Transportation Safety and Environmental Risk Assessment. Statistical methods used to determine the nature and extent of the problem, evaluate the potential environmental risks; theory, evaluation, analytic and techniques for quantifying the potential effects on transportation and environmental impact risks.

  • ENCS 6530 - Analysis of Modern Energy Conversion and Conservation Systems (3)

    This course will cover energy needs; Energy sources - Fossil Fuel, Nuclear Energy, Coal; Green and Renewable Energy sources - Hydrogen, Solar energy, Wind, Geothermal, Biomass and Ethanol. Energy conversion systems - photovoltaic power conversion, wind turbine generators, fuel cells, battery storage systems, and power electronics. Energy saving methods and analysis. Smart power grid design and analysis will also be presented.

  • ENCS 6620 - Data Mining (3)

    This course will expose the students to the principles of data mining and data analytics. The fundamentals of data warehousing and architectures, multidimensional data model, statistical and machine learning techniques and implementations will be covered. Data mining and data analysis approaches such as classification, estimation, prediction, clustering, data visualization, statistical inference and learning, and database management will also be discussed. Students will learn the use of a statistical or mathematical programming language for the purpose of performing the tasks in data mining and data analysis. Prerequisite(s): ENCS 6010

  • ENCS 6800 - Introduction to Cyber Security (3)

    This course introduces cyber security, focusing on the interdisciplinary aspects of the field from theory to practical implications. The course presents the growth from information security, cyber security theory. It will present the relationships of cyber security to people, societies, organizations and countries. Various technologies and tools will be presented for a basis for analysis of cyber threats and their mitigation. Case studies at various levels of impact will be discussed.

  • ENCS 6960 - Digital and Computer Communications (3)

    This course provides an in-depth understanding of the modern digital and computer communications for wired and wireless applications. The topics include channel characterization; baseband and passband data transmission; optimum transmitter-receiver design; synchronous and asynchronous data exchange; synchronization and detection; spread spectrum; multiplexing; diversity; multiple antennas and space-time communications; digital signaling; channel capacity; error-control codes; Open System Interconnection models; cellular concept and implementation; modern wired and wireless communications standards; and protocols such as TCP/IP and UDP. Prerequisite(s): EECE 3500 or equivalent.

  • ENCS 7070 - Professional Development and Ethics (0)

    This course will introduce PhD students to ethical issues related to the research enterprise and the responsible conduct of research, it will also cover topics related to professional development and preparation for careers in academia, research, and industry.

  • ENCS 7080 - PhD Seminar (0)

    TBA

  • ENCS 7090 - Dissertation Courses (24)

    TBA

  • ENCS 7100 - Artificial Intelligence Robotics (3)

    The principles of artificial intelligent robotics are studied. Topics include; theory of robot autonomy, robot hierarchical functional decomposition, and robot biologically-inspired intelligent control schemes such as: reflexive, reactive, deliberative and hybrid, visual and remote sensing, world and task perception modeling and learning, and applications of embedded intelligence systems. Hands on laboratory projects are required. Prerequisite(s): ENGR 5070 or equivalent courses.

  • ENCS 7110 - Principles of Cyber Physical Systems (3)

    An introduction to the principles of design, including: specification, modeling, and analysis of cyber-physical systems consisting of computing devices communicating with one another and interacting with the physical world via sensors and actuators. Topics include synchronous and asynchronous models as well as timed model, safety and liveness requirements, and real-time scheduling. Some aspects of dynamics systems and hybrid systems are also studied.

  • ENCS 7200 - Estimation Theory and System Identification (3)

    This course provides an introduction to estimation theory and system identification including: estimation methods; hypothesis testing; method of moment’s estimators; Least squares estimators; Maximum likelihood estimators and; Bayesian estimators. Introduction to the system identification; non-parametric and parametric models for identification; parametric estimation and prediction; identification of parametric time series models; AR, MA, ARMA models and, input-output models. Identification of state-space models; Kalman filter and subspace identification methods.

  • ENCS 7300 - Solid State Physics and Devices (3)

    Introduces the physical principles of semiconductor materials and devices. Presents the semiconductor device operation based on energy bands and carrier statistics. Describes the operation of p-n junctions and metal semiconductor junctions. Extends this knowledge to descriptions of bipolar and field effect transistors, and other microelectronic devices. Prerequisite(s): EECE 3300 Electronics or Permission of Instructor.

  • ENCS 7700 - High-Performance Computing Applications (3)

    This course is a graduate-level application and algorithm design for High-Performance Scientific Computing. The topics include computing in multiple-core computer, distributed computing, solving non-trivial n-body problems, dense linear algebra on multi processors, parallel tree search and efficiency/scalability/performance of parallel algorithms. The practical application of this course is the implementation of the parallel algorithms and techniques into programming models, such as OpenMP, CUDA, Pthreads and MPI and try these applications in a real super computer. Prerequisite(s): COMP 4700 Algorithms and COMP 5520 Introduction High Performance Computing.

  • ENCS 7800 - Graph Theory and Networks Analysis (3)

    This course provides an introduction to graph theory and network analysis. The topics include Introduction to graph theory and graph concepts; Representations of graphs and graph isomorphism; Trees as a Special case of graphs; Connectivity, covering, matching, and coloring in graphs; Directed graphs and Planar graphs; and the application of graph theory in the analysis of Internet, social networks, and information networks.

  • ENCS 7900 - Computer Vision (3)

    This course discusses computer vision techniques for image and video processing. Topics include: image color spaces, color, binary and color image processing, image features quantization and extraction, weak and strong features mitigation and integration, object detection and matching, object motion estimation and tracking, object classification, stereo imaging, and scene understanding. Student will develop strong intuitions and sound mathematical background for adaptive computer vision learning and this ability will be reinforced thru multiple practical class projects.

  • ENCS 7930 - Applied Signal Processing (3)

    This project-based course provides students with the opportunity to develop and implement signal processing algorithms to various deterministic or stochastic signal systems. This course incorporates advanced topics from applied speech, audio, image, video and communications signal processing. Topics include: discrete and continuous Fast Fourier Transforms, analysis of stochastic signals, statistical pattern recognition, application of discrete wavelet transform (Haar wavelets, Daubechies wavelets), and applications of fast and low-complexity signal processing and data fusion.

Mechanical Engineering

  • MEEN 5010 - Introduction to Manufacturing (3)

    Traditional and non-traditional manufacturing concepts, processes, and practices including: engineering metrology, quality assurance, inspection, human-factors in manufacturing, safety, product reliability, industrial robots, group technology, and cellular manufacturing. Laboratory Projects Required.

  • MEEN 5030 - Artificial Neural Networks (3)

    This course introduces one of the parallel processing techniques: Artificial Neural Networks (ANN). Introduction to neural networks, biological inspiration, definitions, comparison with conventional digital computers, vector mapping, classification of neural networks based on the input, paradigms, self-adaptions and learning algorithms, mapping networks and their architectures. Applications to power systems, control systems, communications, signal Processing, quality control, and robotics. Prerequisite(s): Sound knowledge of any higher-level language. (C, Pascal or Fortran) or consent of the instructor.

  • MEEN 5040 - Vibrations Analysis (3)

    Undamped and damped vibrations for one and multi-degrees of freedom, solutions for transient and forced vibrations in lumped parameter systems, vibration control treatments, noise control and experimental techniques.

  • MEEN 5050 - Energy Conservation Systems (3)

    Energy needs; solar energy collection; principle of nuclear power plants; direct energy conversion; thermodynamic analysis and design of direct energy conversion devices, e.g., fuel cells, thermoelectric, photovoltaic and magnetohydrodnyamic (MHD) power generators and systems.

  • MEEN 5100 - Theory of Elasticity and Applications (3)

    Analysis of stress and strain in two and three dimensions, constitutional relation between stresses and strains, hooke’s law, stress functions, strain potentials, two dimensional problems in rectangular and polar coordinates. Torsion, bending of bars, axisymmetric stress and deformation in solid, and thermal stress. Prerequisite(s): CVEN 3120.

  • MEEN 5110 - Theory of Plasticity and Application (3)

    Elastic vs plastic deformation, general theories and approach to stress analysis,Trescaand von Mises’ yield criteria,Prandtl-Reuss and other plastic stress-strain relations, work-hardening, plastic instability, strain rate and deformation, sliplinefield theories, load bounding and applications in engineering design. Prerequisite(s): CVEN 3120.

  • MEEN 5130 - Flexible Manufacturing Systems (3)

    Introduction to Flexible Manufacturing Systems including: flexible and hard-automation, robotic systems, automated guided vehicles, programmable controllers, automated storage and retrieval systems, flexible end-of-arm tooling, sensors, machine visions, and flexible manufacturing integration. Design Projects Required.

  • MEEN 5200 - Advanced Dynamics (3)

    Relative motion, transformation of coordinates, , dynamics of system of particles, analytical mechanics, holonomic and non-holonomic constraints, virtual displacements and virtual work, D’Alembert’s principle, Hamilton principles, Lagrange’s equation, Rigid body geometry, rigid body dynamics.

  • MEEN 5310 - Dynamics and Thermodynamics of Compressible Fluid Flow (3)

    One-dimensional isentropic flow, shock waves, flow in constant air ducts with friction, flow in ducts with heating or cooling and generalized one-dimensional continuous flow. Applications of theory to the design of compressible flow systems, e.g. wind tunnels, gas pipelines, etc. Prerequisite(s): CVEN 3100.

  • MEEN 5400 - Conduction and Radiation Heat Transfer (3)

    Steady, periodic, and transient heat conduction in single and multidimensional systems. Both analytical and numerical methods are presented. Properties and laws of radiation, absorbing and emitting media and radiant exchange between surfaces separated by non-participating media. Problems involving combined radiation and conduction. Applications of theory to the design of engineering systems, e.g., cooling fins, heat shields, etc. Prerequisite(s): MEEN 4150 and MATH 3120.

  • MEEN 5410 - Convection Heat Transfer (3)

    Fundamental principles - conservation laws. parallel and boundary layer flows, scale analysis, similarity solutions, external and internal flows, laminar and turbulent convection, forced and free convection. Analogy between momentum and heat transfer. Prerequisite(s): MEEN 4150 and MATH3120.

  • MEEN 5420 - Advanced Thermodynamics (3)

    Basic laws of classical thermodynamics power, refrigeration, and heat pump cycles, introduction to real gas and equations of state. Irreversibility, availability, energy, and lost work analysis. Development of the relations of classical thermodynamics. Prerequisite(s): MATH 3120 and ENGR 2010.

  • MEEN 5430 - Introduction to Computational Fluid Dynamics (3)

    Navier Stokes equations; Classification of Flows; General Solution Techniques- Finite Element Method, Finite Difference Method, and Finite Volume Method. Hands on experience of ANSYS FLUENT solution techniques; Boundary conditions; Mesh generation; Incompressible flow; Turbulence modeling; Energy equation; Eulerian and discrete phase flows; Post-processing of simulated results; A detailed case study of a research problem chosen by student (individual project).

  • MEEN 5610 - Computer-Aided Design and Manufacturing (3)

    Introduction to various topics related to computer-aided design(CAD),computer-aided manufacturing(CAM), computer-aided engineering(CAE),computer-integrated manufacturing(CIM), finite element modeling and analysis (FEM), and manufacturing information processing (MIP). Prerequisite(s): Sound knowledge of any CAD engineering design software or consent of the instructor. Laboratory Projects required.

  • MEEN 5620 - Design for Manufacturability (3)

    Design of products; Decision Making in Design, Form and Functions Interchange, Design for Manufacturability, Design axioms, Robust Design, and Optimum Design. Laboratory Design Projects Required.

  • MEEN 5630 - Manufacturing Management and Control (3)

    Introduction to theories and practices of manufacturing management. General management techniques discussed include: organizational planning, logistic control, Inventory management, manufacturing information processing and safety. Laboratory Projects Required.

  • MEEN 5640 - Manufacturing Modeling and Simulation (3)

    Introduction to queue theory and manufacturing system modeling Prerequisite(s): Sound knowledge of any higher-level language. (C, Pascal or FORTRAN) or consent of the instructor.

  • MEEN 5650 - Predictive and Preventive Maintenance (3)

    Introduction to predictive and preventive maintenance of electromechanical systems. Prediction of failure of machine components, practical techniques for detection and prevention of machine failure. Data acquisition and Signal processing. Prerequisite(s): Familiarity with the subject of vibration control in mechanical systems or consent of the instructor. Laboratory Projects Required.

  • MEEN 5660 - Concurrent Manufacturing (3)

    ntroduction to concurrent manufacturing and life-cycle engineering. Design conceptualization to product retirement including life-cycle engineering, design for recycleability, design for testability, design for serviceability, design for assembly, design for disassembly, and design for functionability. Laboratory Design Projects Required.

  • MEEN 5780 - Finite Element Analysis (3)

    Theoretical basis of the finite Element method. The physical and mathematical modeling using various elements. The applications of the method to various engineering problems. The generation of the finite element program.

  • MEEN 5820 - Principles of Design (3)

    Development of design theories; design for manufacturability; evaluation of design; redesign principles; case studies.

  • MEEN 6430 - Manufacturing Diagnosis and Prognosis Techniques (3)

    Techniques for effective machinery fault diagnosis and prognosis, signal condition, filtering, and processing, signature analysis, fault pattern recognition and classification, fatigue characterization, and life prediction using artificial intelligence techniques.

  • MEEN 6450 - Transport Phenomena in Manufacturing (3)

    Energy, momentum and mass transports encountered in typical engineering applications. Gas-liquid, two-phase flow patterns, basic and empirical models; conservation equations and closure relations, phase change, aerosol transport, Approximate solutions and numerical simulation techniques.

Computer, Information, and Systems Engineering

  • CISE 5005 - Introduction to Computer Hardware Systems (3)

    Introduction to circuits elements and techniques of circuits analysis. Operational amplifier and techniques of Op-Amp circuit design. Boolean algebra and logic gates, design of combinational and sequential logic circuits, registers and counters, digital integrated circuits. Machine language, RISC and CISC architectures, and design of arithmetic unit, processor, memory system and input/output systems. Prerequisite(s): Graduate standing.

  • CISE 5006 - Introduction to Information Systems (3)

    Introduction to linear system theory: Fourier series, Fourier transform, Laplace transform, Z-transform, power spectrum, and linear system analysis. Probability theory and random variables. Theory of information and communication systems, modulation theory, multiplexing, introduction to digital communications, computer communication systems and network protocols. Prerequisite(s): Graduate standing.

  • CISE 5007 - Introduction to Computation and Computer Software (3)

    This course provides background of computation and computer software for CISE students who are deficient in these areas. It is designed to introduce the concepts of discrete mathematics, data structures and algorithms, and operation system organization. Students study the selected topics which include (1) basic discrete structures such as sets, logic, functions, relations, counting and probability, and graph theory; (2) fundamental data structures such as array, list, stack, queue and binary search tree; algorithm design techniques such as divide-and-conquer, dynamic programming, and greedy technique; algorithm complexity analysis; well-known algorithms for sorting, searching, pattern matching, networked computing and communication; (3) important concepts of operating systems such as processes, thread, scheduling, deadlock, memory management, virtual memory, page replacement algorithm. This course will not be used to meet degree requirements. Prerequisite(s): Basic programming skills (ENGR 2230 or equivalent).

  • CISE 5010 - Data Structures and Algorithms (3)

    Files and data structures used in computing such as lists, etc., techniques of storing and retrieving data such as hashing, indexing, etc., relational data-base models, SQL databases and servers, and data-base management systems. Selection and design of algorithms, search and sorting techniques, pattern matching, mathematical problems. Prerequisite(s): COMP 3200, ENGR 2230 or equivalent.

  • CISE 5020 - Computer Architecture and Operating Systems (3)

    An understanding of capabilities, limitations and applications of different computer architectures of large supercomputers to smaller workstations. Basic computer resource management techniques, discussion of types of operating systems, distributed and parallel processing, real time programming and inquire-response systems. An overview of different implementations. Prerequisite(s): COMP 4110 or COMP 3410 or EECE 4300 or equivalent.

  • CISE 5030 - Software Systems Design (3)

    Concept of software product life cycle, software design methodologies, stages in software development, metrics and models, reliability and reusability of code, software development tools, analysis, and design validation, small team projects involving architectural design and software specifications, computer aided software engineering (CASE). Prerequisite(s): EECE 3061 or COMP 3050 or EECE 4310.

  • CISE 5040 - Systems Engineering (3)

    Introduction to systems, the system design process, systems analysis tools, including decision making, economic evaluation, optimization, queuing theory, statistical methods and process control concepts. Design for operational feasibility, human factors, logistics and systems engineering management. A systems engineering based technical report is required. Prerequisite(s): ENGR 3200, 3200, 4400, MATH 3210 or equivalent.

  • CISE 5050 - Advanced Discrete Mathematics (3)

    Selected topics in discrete mathematics, formal systems, mathematical deduction, logical concepts, theorem proving sets, relations on sets, operations on sets, functions, graphs, mathematical structures, morphism, algebraic structures, semigroups, finite state machines and simulation, Kleene theorem. Prerequisite(s): COMP 3200.

  • CISE 5060 - Error Control Codes (3)

    Introduction to codes for error detection and correction, linear algebra over finite fields, bounds, perfect and quasi-perfect codes, probability of error checking , Hamming, BCH, MDS, Reed-Solomon codes, and non-linear codes. Prerequisite(s): COMP 3200, EECE 3500 or equivalent.

  • CISE 5110 - Introduction to Artificial Intelligence (3)

    Studies of different artificial intelligent concepts and techniques including; neural network topologies and training algorithms, fuzzy logic and decision making systems, genetic algorithms and search algorithms, probabilistic reasoning and belief functions. Applications in engineering will be discussed. Prerequisite(s): ENGR 5200  or equivalent.

  • CISE 5210 - Probability, Statistics and Risk Analysis (3)

    Fundamental concepts of probability and statistics with practical applications to analyze and manage risks inherent in computer, information, and system engineering projects. Emphasis on basic concepts of probability; random variables; discrete and continuous probability distributions; sampling; statistical inference; tests of hypotheses; uncertainty measurement and modeling; Bayesian method; risk identification, analysis and management. Prerequisite(s): Graduate standing;

  • CISE 5220 - Computer Aided Systems Design (3)

    Advanced computer-aided analysis and design tools for analysis of system properties and performance, study of structure and theory of computer aided design software and hardware and the small scale design of such tools. Prerequisite(s): EECE 3100, 3101, CISE 5010 or equivalent.

  • CISE 5230 - Computer Communication and Network (3)

    Covers theory of various information and computer communication networks and operation of open systems that enable exchange of information (data) in an open way to facilitate a range of distributed applications. Topics include - fundamental issues related to reliable transfer of data across serial data link following ISO reference model; data transmission over various types of communication medium; various types of computer networks that provide a switched communication facility over which computers can communicate; and the ISO layered network protocol, network topology, packet switching, routing, networks management, discussion of narrowband and broadband ISDN. Application of basic traffic theory, switching fundamentals and routing strategies. Prerequisite(s): EECE 3210, EECE 3500, EECE 4350 or equivalent.

  • CISE 5240 - Management of Information Systems (3)

    This course will discuss current methods in use for the design and implementation of modern information technology in organizational systems. It will also provide a comprehensive introduction to basic principles of the legal, economic, and regulatory environment of the information industry. Prerequisite(s): MEEN 5020 , EECE 3500 or equivalent.

  • CISE 5250 - Introduction to System Modeling and Simulation (3)

    This course will cover concepts and skills required to design, program, implement, and use computers to solve complex systems analysis problems. The students will learn how to formulate modeling problems, build effective models, analyze data, and use models to evaluate alternative designs and processes that arise in the development of complex systems and products. The students will obtain an overview of modeling techniques used in decision analysis, including Monte Carlo simulation and system dynamics modeling. The techniques include concept graphs, Bayesian nets, Markov models, Petri nets, system dynamics, Bond graphs, cellular automata, and parallel and distributed simulation systems. Students will report on a particular technique and team to implement a chosen system model. Prerequisite(s): Graduate standing. CISE 5210  or Instructor Approval

  • CISE 5260 - Wireless Communications, Principles and Practice (3)

    This course will introduce fundamental theory and design of high capacity wireless communications systems. Topics include modern wireless standards and applications, cellular concept and implementation, mobile radio propagation, fading and multipath, modulation techniques, equalization, diversity, channel coding, multiple access technique, wireless networking. Prerequisite(s): EECE 3210, EECE 3500 or equivalent.

  • CISE 5300 - Fundamentals of Robotics (3)

    Two-dimensional and three-dimensional transformation techniques, manipulator kinematics and dynamics, robot differential motion and control, path planning and trajectory generation, task execution and robot programming will be discussed in details. Robot integration and simulation tools also will be presented. Prerequisite(s): ENGR 5100  or equivalent.

  • CISE 5400 - Special Topics in CISE (3)

    Recent advanced topics in Computer and Information Systems Engineering will be studied based on faculty and students’ needs Prerequisite(s): instructor’s approval.

  • CISE 5900 - Systems Engineering Design (3)

    This is a capstone course for the M.S. in CISE (Computer, Information and Systems Engineering) program where the knowledge gained in prerequisite required courses will be applied. Various steps used in the systemic development and design of system of interest (SOI) will be practiced. System development phases such as; systems requirements, conceptual and logical alternatives, top-down and bottom-up system integration and life cycle issues, and system management and support plan will be applied to selected projects. Prerequisite(s): Student must have a grade of ‘B’ in CISE 5030 , CISE 5040  and CISE 5230  or their equivalents. A written report and oral presentation will be required.

  • CISE 5905 - Master of Science Thesis I (3)

    Thesis topics to be selected in consultation with the chairman of thesis committee and approval of the department head. The thesis will involve hardware, software and systems approach to the design and development of an integrated system. Student must have completed need analysis, identified operational and functional requirements, TPMs, and bench marks for design evaluation and selected an appropriate solution to pursue. Student must also develop a management plan with milestones, define maintenance concepts for life cycle evaluation of optimum system. Student must complete these activities to receive a grade and as a prerequisite for next course. Prerequisite(s): Admission to Candidacy.

  • CISE 5906 - Master of Science Thesis II (3)

    Continuation and completion of thesis and oral presentation defense. Prerequisite(s): CISE 5905 .

  • CISE 6000 - Database Management Systems (3)

    Database concepts. Database design Data models: entity-relationship and relational. Data manipulation languages including SQL. Data dictionaries. Query processing. Concurrency, software development environments use a database system. Expert, object-oriented, multimedia and distributed database systems. Database systems architecture. Use of a commercial database management system.

  • CISE 6100 - Optimization in Operations Research (3)

    Problem solving with mathematical models, deterministic optimization models in operations research, improving search, linear programming models, simplex search and interior point methods, duality and sensitivity in linear programming, multi objective optimization, shortest paths and discrete dynamic programming, network flows, discrete optimization methods and constrained and unconstrained nonlinear programming.

  • CISE 6200 - Introduction to Computational Intelligence (3)

    This course introduces the parallel computation techniques based on various artificial neural networks architectures. Learning rules for feed forward networks, Associative learning, competitive networks, Grossberg network, Hopfield network and their applications. Introduction to fuzzy logic theory, membership functions, fuzzy relations, fuzzy measures, approximate reasoning and design and applications of fuzzy and neuro-fuzzy systems. Introduction to genetic algorithms and their applications. Prerequisite(s): Graduate standing.

  • CISE 6300 - Statistical Information Theory (3)

    Foundations of modern digital communication systems. Random variables and random processors, autocorrelation functions; Digital signaling waveforms and their spectra. Probability of error in digital receivers. Information measure and source coding; channels and codes for error detection and correction. Introduction to traffic theory for telecommunications and optical communication. Prerequisite(s): EECE 3200 or equivalent.

  • CISE 6340 - Computer Communication and Networks II (3)

    Principles and issues underlying provision of wide area connectivity through interconnection of autonomous networks. Internet architecture and protocols today and likely evolution in future. Case studies of particular protocol practical Topics related to high-speed networks such as: frame relay, high-speed LANs and MANs, the asynchronous transfer mode (ATM)architecture, adaptation layers, switch architectures, preventive and reactive congestion control schemes, schemes for connectionless services over ATM, transmission schemes and signaling.

  • CISE 6360 - Distributed Computing Theory and Design (3)

    Fundamental and systems design aspects of distributed systems, paradigms for distributed computing, client-server computing, concurrency control, distributed file systems, resource management, high-performance computing aspects.

  • CISE 6400 - Fundamentals of Robotics in Manufacturing (3)

    Introduction to robotic automation, robot classifications, robot specifications, direct and inverse kinematics, workspace analysis; Trajectory planning, manipulator dynamics; Robot control, robot interface to manufacturing processes, machine interface, end-of-arm tooling, robot programming, and sensor integration and utilization in manufacturing. Laboratory projects are required. Prerequisite(s): Sound knowledge of static and dynamics, matrix operations, computer language programming or consent of the instructor.

  • CISE 6440 - Numerical Visualization (3)

    Essential algorithms for three-dimensional rendering and modeling techniques; viewing transformations, illumination, surface modeling; methodologies for visualization of scalar and vector fields in three dimensions; applications of visualization.

  • CISE 7240 - Computer Vision (3)

    This course covers the digital image processing and computer vision fundamentals, image analysis, image transforms, image restoration, image enhancement, image compression, image segmentation, image representation and description, image recognition and interpretation. Use of Matlab toolbox, Khoros, CVIPtools and LabVIEW based image acquisition and visualization will be required for image data collection, processing and visualization. Prerequisite(s): Graduate standing.

  • CISE 7300 - Network Programming (3)

    Review of TCP/IP and UDP, transport layer, elementary and advanced sockets, TCP sockets and client server examples I/O multiplexing, socket options, elementary and advanced UDP sockets, name and address conversions, daemon processes and intend supersaver, advanced I/O functions, Unix Domain protocols, non-blocking I/O, routing sockets, broadcasting, multicasting, threads, and streamers. Prerequisite(s): Unix Operating System, networking protocols or equivalent.

  • CISE 7310 - Metrics and Models in Software Quality Engineering (3)

    Software development and quality, process models, measurement theory, software quality metrics, Ishikawa’s seven basic quality tools in software development, defect removal, effectiveness, the Rayleigh model, reliability growth models, quality management models, complexity metrics and models, measuring and analyzing customer needs, AS/400 software quality management. Prerequisite(s): CISE 5030 , CISE 5040 , or equivalent.

  • CISE 7340 - High Performance Computer Applications (3)

    Design and analysis of parallel algorithms in fixed-connection network and PRAM models. Numerical computations, sorting, and routing. Comparisons of various parallel machine models. Relating machine models to architectural characteristics.

  • CISE 7350 - Network Security and Risk Analysis (3)

    Network security fundamental, security in layered protocol architecture, cryptographic techniques, authentication, access control, confidentiality and integrity, standard security techniques, electronic mail and EDI security, Network security, security evaluation measures.

  • CISE 7370 - Optical Communication (3)

    Optical communication systems, optical wave propagation, photodetection statistics, heterodyne receiver, and noise sources. Evaluation of communication performance for the free-space channel. Introduction to fiber optic communication and fiber optic networks communication.

  • CISE 7420 - Advanced Robotics (3)

    Mobile robotics platforms, both unmanned ground vehicles and aerial vehicles, will be studied. Robot system integrations, applications of intelligent technologies in robotics, robot behaviors, robot sensing and control, vision systems and sensor fusion techniques will be explained in detail. Prerequisite(s): CISE 5300  and ENGR 5070  or their equivalent.
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