Development of a Ph. D. in Computer and Information Systems Engineering

DEVGAN, Satinderpaul Singh

Professor and Head, Department of Electrical and Computer Engineering, Tennessee State University, 3500 John Merritt Blvd., Nashville, TN 37209, sdevgan@harpo.tnstate.edu

Abstract: An analysis of national critical technologies and the grand challenges indicates that two of the most critical technologies are manufacturing, and information and communications. The two most critical computer intensive technologies are CFD and SIP. Additionally, the need for the right information anywhere any time is critical for success in global competition. Solutions to these critical technologies is responsible for the emergence of Computer and Information Systems Engineering (CISE) program, an interdisciplinary field that integrates different aspects of computer engineering, computer science, electrical engineering, systems engineering and information systems. This paper describes systematic development of a Ph.D. program with concentrations in Computer Communications and Networks, Control System and Signal Processing, and Robotics and Computer Integrated Manufacturing. The Ph.D. in CISE program requires 72 semester credit hours, including 21 credit hours for thesis, after the B.S. degree. This Ph.D. degree program provides a base in systems approach to integration of computer hardware and software systems through a unique combination of 18 semester credit hours of core courses. The depth and breadth in areas of concentration is provided through 33 credit hours of required and elective courses. This paper also details a sample program cycle and outlines of the courses needed for the three concentrations.

Keywords: systems, computer, information, networks

1 Motivation

The goal of the College of Engineering and Technology at Tennessee State University is to offer educational programs that:

1. Support the mission of Tennessee State University to prepare its students for careers in industry or to pursue higher education.
2. Address the critical technology areas of importance to the national well being, and its competitive position in the global market.
3. Build upon the strengths of its faculty expertise, research and educational programs.
4. Are unique and address new thinking and approaches.

With these as the guiding principles, and an understanding of our faculty expertise, existing program strengths, and funded research, we reviewed the national critical technology areas, the persistent top ten hot telecommunication technologies, and the ten computationally critical technology areas (CTA)[1, 2, 3]. We also studied projections of skill requirements for future career [4], the employment projections for future manpower needs at the local, regional and national levels [5, 6], and the student enrollment trends in existing and new programs, and the areas of competencies desired for new faculty positions and engineering positions advertised. It is clear that future careers will require a strong understanding of computer hardware and software, and a systems engineering or the life cycle approach to the whole system development, starting from need analysis, through development of functional requirements, design and development of the complete systems, its operational phase and finally its retirement [7,8,9].

2 Background

Tennessee State University started as a normal school for Negroes in 1912 and has since developed to be a comprehensive, major urban and lad-grant university offering doctoral level programs. As a HBCU, it has a long history of producing some of the outstanding Afro-American engineers. The University has two state supported Centers of Excellence. The Center of Excellence in Information Systems Engineering and Management (COE-ISEM) has a Crest Center funded by NSF to increase the number of under-represented minorities with advanced degrees. The College of Engineering and Technology at Tennessee State University offers ABET accredited B.S. degree programs in Architectural Engineering, Civil Engineering, Electrical Engineering and Mechanical Engineering. The College also offers a Master of Science degree in Computer and Information Systems Engineering (CISE) and a Master of Engineering with options in Electrical Engineering, Civil and Environmental Engineering and Mechanical Engineering. Most of the popular concentrations in the Master of Engineering program are the communication systems and signal processing, the environmental engineering and the manufacturing engineering. The M.S. in CISE, initiated in fall 1996, is the most popular and fast growing program.

The College has a total of 29 faculty members of whom about 75 percent hold Ph.D. degrees. About 85 percent of the faculty in the Departments of Electrical and Computer Engineering and Mechanical Engineering are pursuing funded research. The College has a well established Center for Neural Engineering that is funded by the US Navy and five research laboratories in Computer and Information Systems Engineering (CISE), Signal and Image Processing (SIP), Intelligent Control Systems, Computational Fluid Dynamics (CFD), and the Computer Integrated Manufacturing, which are well equipped with latest hardware and software needed for research. The COE-ISEM has NASA and NSF funded research projects in the areas of control systems and CFD. Some of the funded research areas of our faculty include signal and image processing, control systems, applications of artificial NN, fuzzy logic and genetic algorithms to machine health monitoring, computer communication and networks, robots and manufacturing. Each of the faculty members involved in research have a long track record of securing funded research, publishing in journal and refereed papers and supervising graduate student research projects. About sixty percent of the graduate students have presented and published papers with faculty.

The Department of Computer Science in the College of Arts and Science has ten faculty members and three are involved in research in data structures and algorithms, computer networks and database management.

Tennessee State University presently offers four doctoral degree programs in Biology, Public Administration, Psychology and Education, and has over 28 million dollars funded research each year. It has a unique opportunity to be classified as a Research Universities I institution if it offers another Ph.D. degree program. The College of Engineering and Technology is one of the most progressive schools and has submitted a proposal for a Ph.D. in CISE. The systems approach used to develop this Ph.D. program is described in this paper.

3 Need Analysis

The need analysis for a unique program was carried from the point of view of student interest, manpower needs for the local, regional and national markets and the future career opportunities.

Analysis of local, state and regional manpower projections indicates almost 62% increase, from 1996 to 2005, in the demand for systems analysts, database managers, and operations research analysts [5]. Similarly the national demand for computer engineers and systems analysts will increase by 100% from 1994 to 2005[6]. It also indicates that the demand for programmers is not high. This points to the need for a type of program different than computer science.

Enrollment growth in computer engineering and computer related programs including robotics and manufacturing, both locally and nationally, is a strong indication of student interest to prepare for careers in the information age. Student enrollment in our M.S. degree in CISE experienced a 400% growth in just two years. Also a large percentage of faculty positions advertised indicate the need for expertise in computer communication and networks, distributed computing, software engineering and system integration.

U.S. has issued 150,000 visas to foreigners to fill the need for information technology services [10]. U.S. could loose its leadership role in the world because of its dependence on foreign experts. We must develop our own human resources with appropriate computer background to design and develop comprehensive integrated systems needed.

The percent of minorities and women receiving Ph.D. degrees in science and mathematics is less that 3%. It is even lower for engineering, especially manufacturing and electrical engineering areas [10]. We need to develop this important resource to meet our national needs. The nation's graduate programs have not been successful in changing this trend.

4 Functional requirements and preliminary program design

The national demand for professionals in information technology areas focuses on the areas of systematic development of computer intensive whole systems. The new approach to the development of the whole system that addresses the national critical technology areas will require an interdisciplinary program that combines the best of systems engineering, computer science, electrical and computer engineering, and mechanical engineering. Our M.S. in Computer and Information Systems Engineering program is such an interdisciplinary program and will serve as the core for the Ph.D degree program. The reason for the common core courses is to provide every student a strong base in systems approach to development of computer-based systems. This is also the uniqueness and strength of this program. We also have graduate academic programs and strong research effort in the areas of control systems, signal processing, communication systems and networks, preventive maintenance, computational fluid dynamics, robotics and manufacturing. The Ph. D. program will build upon the existing expertise to offer three concentrations in the areas of computer communication and networks, control system and signal processing, robotics and computer integrated manufacturing. Further the required and elective courses in each concentration will provide the necessary depth and breadth at the advanced level leading to a research-based thesis. The concentrations address the critical technology areas of manufacturing, information and communication, the CFD and SIP and data mining, very high-speed networks and embedded systems. They are closely related and various combinations of these programs can address many of the critical technology areas. The student's advisory committee will help design and define such programs.

5 Proposed Program

The Ph. D. in CISE curriculum consists of 51 credit hours of course work and 21 credit hours of research thesis after the B.S degree. The course work consists of eighteen (18) credit hours of core courses, eighteen (18) credit hours of concentration, and fifteen (15) credit hours of guided electives. All graduate students must attend graduate seminars for at least two semesters.

This Ph.D. degree program will admit students with B.S. degrees in computer science, mechanical engineering, electrical and computer engineering with a minimum gpa of 3.30 or better. Other engineering and related program graduates may qualify after completing prerequisites.

6 Candidacy for the Ph.D. degree

After completing the core and concentration required courses, the student must pass a comprehensive written examination and successfully defend the dissertation proposal orally to be classified as a candidate for the Ph.D. degree.

7 Faculty and curriculum development needs for new program

Presently there are fourteen faculty members who are involved in graduate level teaching, student research supervision and funded research. The university has approved funds for competitive salaries to hire six new experienced faculty with superior teaching, research and publications records. They will strengthen our existing faculty in the areas of computer science, systems engineering, computer engineering, manufacturing, robotics and image processing. Six graduate faculty from the Department of Computer Science and the Center of Excellence will also be involved.

8 Student support and support facilities

The research facilities include the Center of Excellence in Information Systems Engineering and Management, Center of Neural Engineering, the CISE laboratory, the Intelligent Signal Processing Laboratory, the Intelligent Controls Systems laboratory, the CFD laboratory, and the Computer Integrated Manufacturing facility with equipment, instrumentation, computer hardware and software that is worth several millions. Additional computer equipment needed for the CISE program will be provided from the University Computer Facilities program and faculty research. The Crest Center funded by NSF and the Title III grant will provide funds for attracting and supporting under-represented minority and female students.

Our extensive experience, as an HBCU in addition to such unique programs, gives us a distinct advantage to help increase the numbers of under-represented minorities and women engineering graduates. This will contribute to the diversity in work force and integration of the best minds from our cultural diversity to address the national critical technology needs.

9 Course descriptions

CISE 501 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, relational data-base models, SQL databases and servers, and data-base management systems. Selection and design of algorithms, search and sorting techniques, and pattern matching. Prerequisite: CS 320, Engr 223 , EE 306L or equivalent

CISE 502 Computer Architecture and Operating Systems (3): An understanding of capabilities, limitations and applications of different computer architectures from 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: CS 411, CS 341 or EE 430 or equivalent.

CISE 503 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, software specifications, and computer aided software engineering (CASE). Prerequisite: EE 306L and CS 304 or EE 431.

CISE 504 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 of operation feasibility, human factors, logistics and systems engineering management. Introduction to data-base design and decision support systems. Prerequisite: Engr 223, 320, 340 or equivalent.

CISE 505 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: CS 320.

CISE 506 Error Correction 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: CS 320, EE 350 or equivalent.

CISE 522 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. Prerequisites: EE 310, 310L, CISE 501 and CS 504 or equivalent.

CISE 523 Computer Communication and Networks (3): Review of theory of various information and communication systems and current trends in the application of computers and information networks in their design. Topics include - an introduction to digital communication, data link control protocols, control of data transmission over communication lines, data acquisition through smart sensors, scanners and wireless communications, and user interface, LANS, WANS and high speed networks. 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. Prerequisites: EE 321, EE 350 or equivalent.

CISE 524 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: ME 502, EE 350 or equivalent.

EE 622 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.

EE 623 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.

CISE 600 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 using a database system. Expert, object-oriented, multimedia and distributed database systems. Database systems architecture. Use of a commercial database management system.

CISE 610 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, multiobjective optimization, shortest paths and discrete dynamic programming, network flows, discrete optimization methods and constrained and unconstrained nonlinear programming.

CISE 620 Introduction to Computational Intelligence (3): This course introduces the parallel computation techniques based on various artificial neural networks architectures. Learning rules for feedforward 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. Prereq: Graduate standing.

EE 625 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. Pre-requisite: EE 522 or equivalent.

EE 626 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. Pre-req: Graduate standing.

CISE 630 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: EE 320, 350 or equivalent.

CISE 634 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 636 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 640 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. Prerequisites: Sound knowledge of static and dynamics, matrix operations, computer language programming or consent of the instructor.

ME 643 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

CISE 644 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.

ME 645 Transport Phenomena in Manufacturing (3): Energy, momentum and mass transports encountered in typical manufacturing and material processing applications. Heat transfer by conduction, convection and radiation, flow of liquid and/or vapor, transport of chemical species, phase change, volumetric heating, magnetic and thermoelectric effects. Numerical simulation and visualization techniques.

CISE 710: System Modeling and Simulation (3): Modeling and analysis of systems under uncertainty. Integrated approach of stochastic analysis and simulation. Elementary queuing systems and networks. Discrete event simulation, choice of distributions, output analysis, animations.

EE 720 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: EE 522 and graduate level probability and statistics. Prereq: EE 320.

EE 721 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.

EE 722 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.

EE 723 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. Prereq: Graduate standing.

CISE 724: 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, CVIP tools and LabVIEW based image acquisition and visualization will be required for image data collection, processing and visualization. Prereq: Graduate standing.

CISE 730 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.

CISE 731 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: CISE 503, CISE 504, or equivalent

CISE 734 High Performance Computing 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 735 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 737 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 742 Robotics and Machine Intelligence in Manufacturing (3): Introduction to robot languages and programming techniques, robot modeling and simulation, applied artificial intelligence to robot task planning and manipulation, demonstration of neural networks, fuzzy logic, genetic algorithms, and rule-based system to control of intelligent stationary and mobile robot manipulators, intelligence robot senses, image and speech recognition and classification, robot sensor -based communication based, behavior-based coordination and synchronization in time and space. Demonstration of intelligence robotic systems in manufacturing systems. Laboratory design projects required. Prerequisites: CISE 640

CISE 743 Mechatronics Systems (3): Introduction to electro-mechanical systems. General design and fabrication, and integration of electro-mechanical systems including: transducers, active and passive sensors, measurement devices, actuation systems, open, closed, and adaptive controllers, microprocessors and system components electronic interfacing and communication. Laboratory projects required. Prerequisites: basic familiarity with the subject of measurement, instrumentation, control, vibration, and signal processing of electro-mechanical systems or consent of the instructor.

CISE 750a, b, c Special Topics (3): Covers topics of specific area interest including special research topics. To be approved by advisor and program director.

CISE 760 Seminar (0): To be taken by all Ph.D. candidates for a duration of one year during the final year and the approval of the advisor.

CISE 790a,b,c CISE Ph.D. Thesis (3): Research in area of specialization to be carried out under the direction of Advisory Committee.

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