Information Technology (IT)
School of Information Technology and Engineering
Graduate courses listed under the Departments of Computer Science; Electrical
and Computer Engineering; Civil, Environmental, and Infrastructure Engineering;
Information and Software Engineering; Systems Engineering and Operations Research;
and Applied and Engineering Statistics are appropriately considered as courses
forming an inherent part of this program.
100 Information Technology in Action (1:1:0). Prerequisite:
Permission of instructor. Designed for students pursuing the IT minor. Introduction
to current issues as well as career-related opportunities in the IT field. Appreciation
of the manifold implications of technological change, and motivation for continued,
enthusiastic learning in the area of IT.
101 Introduction to Information Technology (3:3:0). Introduces
students to the fundamental concepts in information technology that provide the
technical underpinning for state-of-the-art applications. A perspective on the
range of information technology is presented. Historical development and social
implications of efforts in information technology form an integral part of the
course.
103 Introduction to Computing (3:1:2). Prerequisite: Knowledge
of high school algebra. May not be taken for credit after receiving a grade
of C or better in any CS course numbered 112 or higher. An introduction, using
both lecture and laboratory practice, to the nature and uses of computers. Widely
used applications including word processing, spreadsheets, databases, and presentation
software are studied. Laboratory projects are required in these areas. Additional
lectures address computer systems organization, computer communications and networking,
legal and ethical considerations (including privacy, intellectual property, and
appropriate uses of technology), the effective presentation of information, computer
security, artificial intelligence and the future of computing and the Internet.
108 Programming Fundamentals (3:2:1). Prerequisite: IT
103. Introduction to programming fundamentals for non-technical majors. Software
development process is presented. Students learn to write programs in a high level
language. IT&E majors cannot receive credit for IT 108 after receiving a C
or better in CS 112. IT 108 does not fulfill any IT&E major requirements.
IT minor students may take both IT 108 and CS 112 for credit.
212 How Computers Work (3:3:0). Designed for students pursuing
the IT minor. A look inside today's personal computers. Covers, in a nontechnical
manner, what makes computers "tick" from transistor basics up to accessing
the Internet. Describes all the essential components within a PC and how they
interact. Also addresses the latest aspects of computer technology (e.g., DVD)
and how they affect computer use and operation. Presentations of actual hardware
(VLSI integrated circuits, modems, etc.) are included so that students can visually
appreciate the complexity of the circuitry involved.
213 Multimedia and Computer Graphics (3:2:1). Prerequisites:
IT 103, 108. Designed for students pursuing the IT minor. Introduces tools
to configure graphical user interfaces (GUIs), multimedia authoring systems, graphical
and multimedia components, and data types and provide web design principles.
214 Database Fundamentals (3:3:0). Designed for students pursuing
the IT minor. Study of relational database systems and their applications. The
creation and manipulation of tables and formulation of queries. The use of forms
and reports for end-users, with visual element enhancements. Data modeling and
the formation of relations. Examination of recent trends in database management,
including web applications.
221 Introduction to Information Security Technologies (3:3:0). Prerequisite:
IT 108. Overview of information security technologies as applied to operating
systems, database management systems, and computer networks. Symmetric and asymmetric
cryptography, application of cryptography in internet security protocols. Access
control models and mechanisms. Role-based access control. Intrusion detection
and response. Secure electronic commerce.
222 Introduction to Information Security Policy and Management (3:3:0).
Prerequisite: IT 108. Security policies, mandatory and discretionary
access control, Chinese walls, separation of duties and least privilege, security
objectives, architectures, models and mechanisms. Privacy policy and technologies.
Social implications of biometric identification. Intellectual property protection
in cyberspace.
250/STAT 250 Introductory Statistics I (3:3:0). Prerequisite:
High school algebra. Elementary introduction to statistics. Topics include
descriptive statistics, probability, estimation and hypothesis testing for means
and proportions, correlation, and regression. Students use statistical software
for assignments. f,s,sum
300 Modern Telecommunications (3:3:0). A comprehensive overview
of telecommunications, including current status and future directions. Topics
include a review of the evolution of telecommunications; voice and data services;
basics of signaling, digital transmission, network architecture and protocols;
local area, metropolitan and wide area networks and narrow band ISDN, asynchronous
transfer mode and broadband ISDN; and satellite systems, optical communications,
cellular radio, personal communication systems, and multimedia services. Examples
of real-life networks are provided to illustrate the basic concepts and gain further
insight.
331 Web I: Introduction to Web Development (3:3:0). This course
introduces the concepts needed to be successful in the web development environment.
Discussed are topics such as the similarities and differences in Internet browsers
and user computer configurations (connection speed, display settings, etc.). The
student learns to develop web pages with a text editor and HTML tags, images,
tables, forms, frames and associated attributes. A more powerful WYSIWYG HTML
editor. Other topics include introductory Dynamic HTML (DHTML) and Cascading Style
Sheets. A graphic development tool is used to allow students to develop graphics
files for their projectspng, gif, jpg, and animated gifs. A long-range web
development project is begun.
332 Web Site Administration (3:3:0). Web server administration
and web security. Property sheets related to these sites and security features.
Hosting multiple web sites on the same web server and associated performance issues.
Application-level password security. Project conclusion.
341 Network and Operating System Essentials (3:3:0). Prerequisites:
IT 101, 108, 212, or permission of instructor. This course introduces the
student to the basics of network security tools, administrative tools, network
protocols and fundamentals of TCP/IP, using standard operating systems such as
Windows and Unix.
342 Operating Systems for Administrators (3:3:0). This course
describes practices and procedures for installing and configuring modern operating
systems, including user accounts, file, print and terminal servers, mobile computing,
and disaster protection.
350 Introduction to Entrepreneurship (3:3:0). This course
introduces the student to the concept of entrepreneurship and the skills, concepts,
and information that entrepreneurs use. More specifically students will learn
about entrepreneurs and that they are neither super human nor particularly gifted.
The course also examines why and how entrepreneurs start companies and how this
is different from the way large companies expand their operations. Finally, the
course is designed to help the student build the skills for starting a company.
To this end it provides an introduction through readings, lectures, and exercises
to all of the concepts and methods needed to do so. After completing this course
the student should have the skills needed to develop and write a good first draft
of a business plan.
362/STAT 362 Introduction to Computer Statistical Packages (3:3:0).
Prerequisite: IT 250/STAT 250 or equivalent. Use of computer
packages in the statistical analysis of data. Topics include data entry, checking,
and manipulation, as well as the use of computer statistical packages for regression
and analysis of variance.
422 Data Communication and Networks (3:3:0). Introduction
to concepts in data communication systems. Emphasis on impact of communications
technology on information systems.
431 Web II: Intermediate Web Development (3:3:0). Continuation
of Web I. Rapid Application Development (RAD), client and server-side scripting
for user and database interaction. The students continue to build their skills
in both client and server-side scripting using the Document Object Model. Session/cookie
management. Continuation of project.
441 Network Servers and Infrastructures (3:3:0). This course
covers networking concepts and practices for using DHCP, DNS, WINS, Public Key
infrastructure, routing, remote address services, web servers, and network connectivity
between operating systems.
443 IT Resources Planning (3:3:0). This course provides students
with essential strategies and procedures for planning, organizing, staffing, monitoring,
and controlling the process of designing, developing, and producing a system that
will meet a stated IT-related need in an effective and efficient manner.
462/INFS 462 Information Security Principles (3:3:0). Prerequisite:
INFS 312 Computer Architecture and Operating Systems or equivalent. Study
of security policies, models, and mechanisms for secrecy, integrity, availability
and usage controls. Topics include models and mechanisms for mandatory, discretionary
and role-based access controls; authentication technologies; control and prevention
of viruses and other rogue programs; common system vulnerabilities and countermeasures;
privacy and security policies and risk analysis; intellectual property protection;
legal and social issues.
466/INFS 466 Network Security (3:3:0). Prerequisite: INFS
312 Computer Architecture and Operating Systems or equivalent. Symmetric
and asymmetric cryptography; encryption, message authentication codes and digital
signatures; cryptographic authentication; digital certificates and public key
infrastructure; the standards process; cryptographic protocols; SSL, IPSEC and
related protocols; secure e-mail; intrusion detection.
491 IT Seminar (1:1:0). Prerequisite: 90 credits in the
B.S. in Information Technology program. IT ethics, professionalism, the role
of the IT professional in society, current IT issues, and employment opportunities.
492 Synthesis I (3:3:0). Prerequisite: Senior standing
in the B.S. in Information Technology program. Work includes developing a
proposal for a project that can demonstrate the student's preparedness as a practicing
IT professional. Oral and written reports are required during the preparation
of the proposal and also after the proposal is completed.
493 Synthesis II (3:3:0). Prerequisite: IT 492, preferably
in the preceding semester. Implementation of the project for which preliminary
work was done in IT 492. Oral and written reports are required during the project
and also at the project's completion.
498 Independent Study in Information Technology (1-3:0:0).
Directed self-study of special topics of current interest in IT. Topics must be
arranged with an instructor and approved by the department chair before registering.
Course can be taken for a maximum of 3 credits.
499 Special Topics in Information Technology (1-3:0:0). Prerequisites:
Permission of instructor; specific prerequisites vary with the nature of the topic.
Topics of special interest to undergraduates. May be repeated for a maximum of
6 credits if the topics are substantially different.
500 Quantitative Foundations for Information Systems Analysis (3:3:0).
Prerequisite: MATH 108 or an equivalent. Provides a common background
in basic quantitative areas focused on decision making, information processing
and telecommunications. Topics include a review of pre-calculus, introduction
to matrix algebra, problems in optimization, and introduction to probability and
statistics. This course does not fulfill any IT&E graduate degree requirement.
557 Introduction to Network Science (3:3:0). Prerequisites:
Bachelor's degree in math, science, or engineering; Math 114 and 351. This
course is the first of a sequence of two intended to provide a broad treatment
of the principles and technologies of modern telecommunications, combined with
computing, that create computer networks. Emphasis is on providing sufficient
breadth and depth to allow a technical professional to function as an effective
entry-level network engineer. This course includes modules in telecommunications
principles, telcommunications carrier systems, data communications, local area
networks, and wide area network protocols.
657 Advanced Network Science (3:3:0). Prerequisite: IT
557 or permission of instructor. This course is the second of a sequence
of two intended to provide a broad treatment of the principles and technologies
of modern telecommunications, combined with computing, that create computer networks.
Emphasis is on providing sufficient breadth and depth to allow a technical professional
to function as an effective entry-level network engineer. This course includes
modules in wireless telecommunications, network security, network management,
and advanced network protocols.
746/CSI 776 Calculus of Random Signals (3:3:0). Prerequisite:
STAT 652 or CE 630 or 632. Introduction to modern theory of stochastic calculus
such as stochastic integrals, martingales, counting processes, diffusion processes,
and Ito-type processes in general. Presents applications of the methods to engineering
and biology. Focus is on developing the necessary concepts rather than mathematical
proofs. Suited for graduate students in information technology, electrical engineering,
mathematics, operations research, and statistics. a,f
750/CS 750 Theory and Applications of Data Mining (3:3:0).
Prerequisite: CS 681, 687, or 688, or permission of the instructor. Concepts
and techniques in data mining and their multidisciplinary applications. Topics
include databases, data cleaning and transformation, concept description, association
and correlation rules, data classification and predictive modeling, performance
analysis and scalability, data mining in advanced database systems including text,
audio and images, and emerging themes and future challenges. Term project and
topical review required.
776/CSI 778 Real Analysis and Statistics (3:3:0). Prerequisites:
STAT 652 or ECE 620, 621, and 630. Advanced calculus and linear algebra needed
for doctoral work in statistics and related fields. Topology, vector spaces, atrices,
continuity, differentiation, sequences and series of real numbers and real-valued
functions, Riemann and Riemann-Stieltjes integrals, and multidimensional calculus.
Applications in probability and statistics including response surface methodology
are presented. ir
796, 797 Directed Reading and Research (1-3:0:0). Reading
and research on a specific topic in information technology under the direction
of a faculty member. May be repeated as needed.
803, 804 Doctoral Tutorial in Information Technology (3:3:0). Individualized
intensive study of particular aspects of information technology. May be repeated
as needed.
809 Scaling Technologies for E-business (3:3:0). Prerequisites:
at least one operating systems and one networking course, and admission to an
IT&E doctoral program. This course discusses, from a quantitative point
of view, the characteristics of the most important technologies used to support
the implementation of e-business sites. The discussion includes topics such as
hardware and software architectures of e-business sites, authentication, and payment
services, understanding customer behavior, workload characterization, scalability
analysis, and performance prediction. A term paper and a project are required.
811 Principles of Machine Learning and Inference (3:3:0).
Prerequisite: CS 80, 681, or permission of instructor. Presentation of
unifying principles tat underlie diverse methods, paradigms, and approaches to
machine earning and inference. Reviews the most known learning and inference systems,
discusses their strengths and limitations, and suggests the most appropriate areas
of their application. Students get a hands-on experience by experimenting with
the state-of-the-art learning and inference systems and work on projects tailored
to their research interests.
812 Advanced Topics in Natural Language Processing (3:3:0).
Prerequisite: CS 680. Advanced treatment of topics in syntax, semantics,
and generation of linguistic output. Implementation and applications are also
discussed.
814/CSI 801 Foundations of Computational Science (3:3:0).
Prerequisite: CS 735 or equivalent. Investigation methods for scientific
questions in the presence of teraops computation, gigabyte memory, and gigabit
transmission. Mapping of mathematical models to parallel algorithm and architectures,
associated data structures, languages, operating systems, networks, and global
change demonstrate important scientific accomplishments enabled by computation.
Working in teams with scientists and information technologists, students learn
the mathematical models, abstract algorithms, and concrete algorithms for these
cases, and conduct experiments and simulations with them.
815 Parallel Computation (3:3:0). Prerequisite: CS 635
or IT 816 or CSI 801. Topics illustrating some of the contemporary thinking
on architectures, application, development environments, algorithms, operating
system related issues, language requirements, and performance for parallel computation.
816 Parallel Architectures, Algorithms, and Applications (3:3:0). Prerequisites:
CS 583 and computer architecture course. Familiarization for students in
area of parallel architectures, algorithms, and parallel computers. Various algorithms
and their applicability to certain architectures are discussed. Comparisons of
these parallel algorithms with certain tools are studied, and applications to
artificial intelligence, image processing, and database machines are explored.
817 Neural Networks (3:3:0). Prerequisite: CS 688 or permission
of instructor. Study of adaptive and competitive principles using distributed
and parallel computation. Topics include background from statistics, control,
adaptive signal processing, and neurosciences. Basic models, such as those suggested
by Grossberg, Hopfield, and Kohonen, are discussed in terms of their analytical
characteristics and applications. Neural networks are assessed as universal approximators.
Connections to the fuzzy approach are established through the Radial Basis Function
approach. Applications to perception, knowledge-based systems, and robotics are
presented.
818 Topics in High Performance Computer Systems (Scalable E-business
Site Technologies and Models) (3:3:0). Study of technologies and architectures
used to support ebusiness sites: multi-tier software and hardware architectures,
security protocols, and payment protocols. Performance metrics for e-business.
Performance impacts of e-business technologies. Performance models of ecommerce
technologies. Workload characterization for e-business.
819 Computational Models for Probabilistic Inference (3:3:0). Prerequisite:
SYST 664 or 652. Graphical models for encoding conditional independence assumptions
in a multivariate discrete probability distribution. Includes computational methods
for updating probabilities when evidence is observed on some variables in the
model. Algorithms for finding the most probable instantiation of the network.
Applications in expert systems and decision analysis.
821 Software Engineering Seminar (3:3:0). Prerequisite:
SWE 621. Study of the application of software engineering principles, design
methods, and support tools through real-life problems extracted from faculty/industry
projects. May be repeated with a change in topic.
822 Software Maintenance and Reuse (3:3:0). Prerequisites:
CS/SWE 621 (or equivalent), data structures, principles of modern programming,
discrete mathematics, or permission of instructor. Perfective maintenance, reuse
of software components and patterns, evolving software systems, principles of
object-oriented analysis and development. Issues regarding technologies supporting
perfective software maintenance and reuse are presented.
823 Software for Critical Systems (3:3:0). Prerequisites:
SWE 620 and STAT 554. Study of software for systems in which failure can
be catastrophic. Techniques to construct and analyze software for critical applications
and examination of inherent limitations of such techniques are presented, as well
as interaction between techniques used during development and behavior of software
during operation. Topics include tolerance of software faults, design redundancy,
data redundancy, software safety, formal methods, statistical testing, design
for analyzability, and design for testability.
824 Program Analysis for Software Testing (3:3:0). Prerequisite:
CS 540 or CS/SWE 637, or permission of instructor. Different methods for
analyzing software, primarily for the purpose of testing. Analysis techniques,
specific algorithms, tools, and applications. Goals are to explore the current
research issues, learn how to build software analysis tools, and understand how
these techniques can be applied to software development activities. The primary
focus is on applications for testing software, including automatic test data generation,
object-oriented testing, and testing client-server applications. Analysis techniques
for other software-related activities such as maintenance, reuse, object-oriented
development, metrics, and optimization are also considered.
830/ECE 734 Detection and Estimation Theory (3:3:0). Prerequisites:
ECE 528, or permission of instructor. Introduction to detection and estimation
theory with communication applications. Topics include M-hypotheses, Bayes, minimax,
Neyman-Pearson criterion, detection of signals in AWGN and ACGN, Bayes estimation,
ML estimation of signal parameters in AWGN and ACGN, estimation of Gaussian waveforms
in Gaussian noise, linear MSE estimation, and Kalman and Wiener filters.
832/ECE 735 Speech and Image Coding (3:3:0). Prerequisites:
ECE 632 and 635. A study of waveform coding concepts and algorithms
and their applications to the analysis and design of data compression systems.
Specific schemes involving speech and image coding are discussed. Topics include
statistical properties of speech and image signals, rate distortion theory, predictive
and adaptive coding techniques, optimum quantization, and bit assignment algorithms.
833/ECE 739 Satellite Communication (3:3:0). Prerequisite:
ECE 631. Introduction to the theory and applications of modern satellite
communications. Topics include satellite channel characterization, channel impairment
and transmission degradation, link calculations, modulation, coding, multiple
access, broadcasting, random access schemes, demand assignment, synchronization,
satellite switching and onboard processing, integrated service digital satellite
networks, and satellite transponder, ground stations, packet switching, and optical
satellite communications.
834/ECE 742 Telecommunications Networks (3:3:0). Prerequisites:
ECE 528 and 642, or permission of instructor. Open Systems Interconnection
Reference Model, analysis and modeling of layered network architectures including
transport and higher layers, performance evaluation of System Network Architecture,
DEC Network Architecture, and other telecommunication architectures. Protocols
and standards for local, metropolitan, and wide area networks are also discussed.
Topics include high-speed packet switching, broadband multimedia protocols, and
congestion control in broadband integrated networks.
835 Computational Vision (3:3:0). Prerequisites: CS 682
and 686, or permission of instructor. Study of recent advances in development
of machine vision algorithms and knowledge-based vision systems. Topics include
scalespace; Gabor and wavelet processing; distributed and hierarchical processing
using neural networks; motion analysis; active, functional, and selective perception;
object and target recognition; expert systems; data fusion; and machine learning.
Emphasis is on system integration in terms of perception, control, action, and
adaptation. Applications to robotics, intelligent highways, inspection, forensic,
and data compression are presented.
836/ECE 836 Special Topics in Detection and Estimation Theory (3:3:0).
Prerequisite: ECE 734. Advanced topics in detection, estimation,
and signal processing in areas of current research interest. Topics may include
spectral estimation, speech recognition, array processing, SAR, underwater acoustics,
or higher order spectra.
837/ECE 754 Optimum Array Processing I (3:3:0). Prerequisite:
ECE 734. Optimum antenna array processing for communications, radar, and
sonar systems. Classical synthesis of linear and planar arrays. Characterization
of space-time processes. Spatial AR and ARMA models. Optimum waveform estimation.
MVDR and MMSE estimators. LCMV beamformers. Generalized sidelobe cancelers. Robust
algorithms. Diagonal loading.
838/ECE 638 Signal Processing Algorithms and Architectures (3:3:0).
Prerequisite: ECE 635 or permission of instructor. Study of
recent advances in the development of fast-signal processing algorithms and parallel
architectures. Topics include fast transforms, multirate processing of digital
signals, adaptive filtering, high-resolution spectral analysis, parallel computational
arrays, and mapping of signal processing algorithms into array processors.
840/CS 685/ECE 750/SYST 672 Intelligent Systems for Robots (3:3:0).
Prerequisite: SYST 611, ECE 650, CS 580, SYST 555, or equivalent.
Review recent developments in the area of intelligent autonomous systems. The
applications of artificial intelligence, control theory, operations research,
decision sciences, computer vision, and machine learning to robotics are studied
as well as correspondences between various fields. Topics include analysis and
design of methods, algorithms and architecture for planning, navigation, sensory
data understanding, visual inspection, spatial reasoning, motion control, learning,
self-organization, and adaption to the environment.
841/ECE 722 Kalman Filtering with Applications (3:3:0). Prerequisite:
ECE 521 and 528 or equivalent, or permission of instructor. Detailed treatment
of Kalman Filtering Theory and its applications, including some aspects of stochastic
control theory. Topics include state-space models with random inputs, optimum
state estimation, filtering, prediction and smoothing of random signals with noisy
measurements, all within the framework of Kalman filtering. Additional topics
are nonlinear filtering problems, computational methods, and various applications
such as Global Positioning system, tracking, system control, and others. Stochastic
control problems include linear-quadratic-Gaussian problem and minimum-variance
control.
842 Models of Probabilistic Reasoning (3:3:0). Prerequisite:
STAT 544 and OR 681. Survey of alternative views about how incomplete, inconclusive,
and possibly unreliable evidence might be evaluated and combined. Among the views
discussed are the Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic
reasoning.
843/ECE 720 Multivariable and Robust Control (3:3:0). Prerequisite:
ECE 620 or permission of instructor. Eigenstructure assignment for multivariable
systems, the Smith-McMillan form, internal stability, modeling system uncertainty,
performance specifications and principal gains, parametrization of controllers,
loop shaping and loop transfer recovery, and the H methodology.
844/ECE 749 Pattern Recognition (3:3:0). Prerequisite:
ECE 549 and 620; CS 580 and 688; or equivalents. Study of the fundamentals
of statistical pattern recognition, functional and density approximation, and
adaptive systems. Topics include the Bayesian approach, non-parametric statistics
and neural networks, adaptive fuzzy systems and control, Bayesian nets and Hidden
Markov Models (HMM), and evolutionary computation and genetic algorithms. Applications
to clustering and recognition, time-series prediction and model-based identification,
forensics, and knowledge-mining are presented.
845/ECE 780 High-Frequency Electronics (3:3:0). Prerequisite:
ECE 520. Study of devices and circuits used in high-speed communication systems.
Topics include microwave bipolar transistors, GaAs MOSFETs, and high-speed integrated
circuits; and the design of linear and power amplifiers using S-parameter techniques
and computer simulation.
846/ECE 721 Nonlinear Systems (3:3:0). Prerequisite: ECE
521. Nonlinear dynamical systems. Motivating examples. Analysis techniques
include basic fixed point theory, implicit function theorem, dependence of trajectories
on initial data and parameters. Course also covers computational simulation techniques,
stability theory, including Lyapunov's direct method, nonlinear control systems:
input-output stability, and absolute stability, strong positive real transfer
functions. Feedback linearization of nonlinear systems, nonlinear canonical forms;
nonlinear decoupling; sliding control; and applications to adaptive control, neural
networks, and robotics are also included.
847/ECE 847 Topics in Photonics (3:3:0). Prerequisite:
ECE 565 or permission of instructor. In-depth discussion of specific topics
in photonics. Topics include optical storage (disks, holographic, 3D), digital
optical computing, integrated optics, photonic switching networks, and optoelectronic
devices. May be repeated when covering different topics.
848/ECE 743 Digital Video Communications (3:3:0). Prerequisites:
ECE 535 and 642. Coding, transport, and modeling of digital video signals;
digital coding of waveforms with emphasis on compression techniques for video
signals, transform coding including DCT and rate distortion theory for images,
subband/wavelet coding of images, treatment of video signals for different television
formats, colorimetry and motion estimation/compensation, general characterization
of video traffic, modeling of variable bit rate video codecs, transport protocols
for video and multimedia, network-delay compensation for video over ATM, VBR video
flow control, and discussion of applications ranging from HDTV/TV over ATM, digital
HDTV for terrestrial broadcast, to videoconferencing/desktop multimedia over LAN/WAN.
850 Systems Integration Engineering (3:3:0). Prerequisite
SYST 510 or 520. Lifecycles in systems engineering. Large systems comprised
of heterogeneous components. The human, organizational, and technological basis
for integration. Societal and cultural basis for systems integration. Conceptual
frameworks for systems integration. Structure, function, and purpose of the systems
integration industry. Risk management and systems integration. User requirements
and functional specifications in systems integration. The bid and proposal process
for systems integration. Systems integration and the federal government. Standards
and Systems Integration. Integration of systems and federations of systems. Integrated
process and product development, and systems integration. Systems integration
architectures. Systems management and cost estimation in systems integration.
Systems integration reengineering. Quality management for systems integration.
Increasing returns to scale, network effects, and path dependency issues in systems
integration. Systems integration ecology and evolutionary systems integration.
851 Seminar: Topics in Software Requirements (3:3:0). Prerequisite:
SWE 620 or 624, or CS 624. Emphasis on the latest research ideas in the requirements
engineering domain. Discusses the current state-of-the-art and state-of-the-practice
in requirements engineering. Focuses on the most critical problems and discusses
how their resolutions might further the requirements research knowledge base and
enhance the quality and productivity of real software and system developments
in industry. May be repeated when the topic is different.
852 Graphical Real-Time Simulation (3:3:0). Prerequisite:
CS 652 or IT 875. Current research in advanced computer graphics and its
applications in realistic real-time simulations. Topics include physically based
modeling, real-time simulation, distributed interactive simulation (DIS), network
virtual environments (NVE), and virtual reality (VR).
858 Logic Models in Artificial Intelligence (3:3:0). Prerequisite:
CS 580. Examination of the relevance of logic theory to artificial intelligence.
Familiarizes students with a variety of formal logics that are used in artificial
intelligence, as well as ongoing research in new logics. Topics include first-order
predicate calculus, resolution and nonresolution theorem proving, nonmonotonic
logic, assumption-based reasoning, the relationship between symbolic and quantitative
theories of uncertainty, temporal logics, and their application to planning and
metareasoning.
860 Software Analysis and Design of Real-Time Systems (3:3:0). Prerequisite:
SWE 623. Background for students who want to conduct research in the software
engineering of real-time systems. Students gain an understanding of key real-time
software system analysis, design concepts and methods, and how they are used in
the development of large-scale, real-time software systems. Students also gain
an understanding of the potential impact of emerging technologies in this field.
Term project in the design and analysis of a complex real-time software system
is undertaken.
861 Distributed Database Management Systems (3:3:0). Prerequisite:
INFS 614 or equivalent. Topics in distributed database management including
transaction management, concurrency control, deadlocks, replicated database management,
query processing reliability, and surveys of commercial systems and research prototypes.
862 Computer Security Models and Architectures (3:3:0). Prerequisite:
Six credits from INFS 762, 765, 766 and 767. This course covers
modern computer security models and architectures in the context of large-scale
distributed systems, including cross-enterprise systems. Models for role-based
access control, lattice-based access control, and delegated administration are
studied and compared with respect to formal and pragmatic criteria. Architectures
to implement these models based on public-key infrastructure, trusted servers,
and other components are studied.
863 Empirical Methods in Information Technology (3:3:0). Prerequisite:
STAT 654. Examination of alternative paradigms of scientific research and
their applicability to research in information technology. Topics include fundamental
elements of scientific investigation, basic principles of experimental design
and statistical induction, philosophy of science and its relation to the information
technology sciences, and case studies of information technology research.
864 Scientific Databases (3:3:0). Prerequisite: INFS 614.
Study of database support for scientific data management. Requirements and properties
of scientific databases; data models for statistical and scientific databases;
semantic and object-oriented modeling of application domains; statistical database
query languages and query optimization; advanced logic query languages; and case
studies such as the human genome project and the earth orbiting satellite are
covered.
865 Networks and Distributed Systems Security (3:3:0). Prerequisite:
INFS 612 or equivalent. A detailed study of network and distributed
systems security. Review of basic cryptography and threats and vulnerabilities
in distributed systems. Security services and confidentiality, authentication,
integrity, access control, nonrepudiation, and their integration in network protocols
are covered. Topics also include key management, cryptographic protocols and their
analysis; access control, delegation, and revocation in distributed systems; and
security architectures, multilevel systems, and security management and monitoring.
867 Intelligent Databases (3:3:0). Prerequisite: INFS
760 or permission of instructor. Study of models and techniques that empower
database systems with intelligent and cooperative behavior, with emphasis on subjects
such as knowledge-rich databases, logic databases, epistemological queries, intentional
answering, and knowledge discovery. Topics include user interfaces cooperative
query interfaces, interactive query constructors, graphical interfaces, and browsers;
uncertainty representing, manipulating, and retrieving uncertain, imprecise, or
incomplete information; and formulating and interpreting vague or incomplete queries.
870 Organizational Informatics (3:0:0). Prerequisite:
doctoral status or permission of instructor. An examination of the effects
of informatics on national and international policy; setting of international
policy on informatics; ethical and social change in governments and organization;
shaping of national policy in informatics; industry growth; and research methods
from various scientific discipline.
874 Analysis of Complex Surveys (3:3:0). Prerequisites:
STAT 656, 665, and 674 or permission of instructor. Presentation of current
theory and methods of statistical analysis of data from complex surveys of finite
populations. Includes contingency table analysis and regression analysis; modeling
structured populations by multilevel models; and loglinear, logistic, and regression
models for stratified and multistage cluster samples. Case studies are used to
illustrate the methodology. ir
875/CSI 803 Scientific and Statistical Visualization (3:3:0).
Prerequisite: STAT 554 or CS 651. Presentation of visualization methods
used to provide new insights and intuition concerning measurements of natural
phenomena and scientific and mathematical models. Case study examples from a variety
of disciplines to illustrate what can be done are presented. Topics include human
perception and cognition, an introduction to the graphics laboratory, elements
of graphing data, representation of space-time and vector variables, representation
of 3D and higher dimensional data, dynamicgraphical methods, and virtual reality.
Students are required to work on a visualization project. Emphasizes software
tools on the Silicon Graphics workstation, but other workstations and software
may be used for the project.
876/CSI 876 Measure and Linear Spaces (3:3:0). Prerequisite:
IT 776/CSI 778. Measure theory and integration, convergence theorems, and
the theory of linear spaces and functional analysis, including normed linear spaces,
inner product spaces, Banach and Hilbert spaces, Sobelev spaces, and reproducing
kernels. Topics include wavelets, applications to stochastic processes, and nonparametric
functional inference. as
877/CSI 877 Geometric Methods in Statistics (3:3:0). Prerequisite:
STAT 751 or permission of instructor. Develops the foundations of geometric
methods for statistics. Topics include n-dimension Euclidian geometry, projective
geometry, differential geometry including curves, surfaces, and n-dimensional
differentiable manifolds, and computational geometry including computation of
convex hulls, and tessellations of 2-, 3-, and n-dimensional spaces. Examples
include applications to statistics and scientific visualization. af
879 Topics in Stochastic System Simulation (3:3:0). Prerequisite:
OR 635 or permission of instructor. Special topics and recent developments
in the Monte Carlo simulation methodology for discrete-event stochastic systems.
Contents vary and possible topics include statistical analysis of simulation output
data, random number and random ariate generation, variance reduction techniques,
sensitivity analysis and optimization of simulation models, distributed and parallel
simulation, object-oriented simulation, and specialized applications. May be repeated
for credit when topics are distinctly different.
880 Queuing Modeling of Computer-Communication Networks (3:3:0). Prerequisite:
OR 645, 647; ECE 542; or equivalents. Study of analytical modeling of computer
and communication networks and performance evaluations. Topics include Markovian
systems, open networks, closed networks, approximations, decomposition, simulation,
sensitivity analysis, and optimal operation of systems. Local area networks, manufacturing
systems, and other applications are presented.
882 Advanced Topics in Combinatorial Optimizations (3:3:0).
Prerequisites: OR 641 and 642. Study of problems using the most recent
developments.Topics include cutting plane procedures based on polyhedral combinatorics,
column-generation procedures for large complex problems, heuristic approaches
(genetic algorithms, simulated annealing, tabu search), the study of special structures,
reformulation techniques and bounding approaches. Topics stress the most recent
developments in the field. May be repeated for credit when topics are distinctly
different.
884 Advanced Topics in Nonlinear Programming (3:3:0). Prerequisite:
OR 644. Study of theory and algorithms for solving nonlinear optimization
problems. Contents vary, and possible topics include large-scale and parallel-unconstrained
optimization, theoretical issues in constrained optimization, duality theory,
Lagrangian and sequential quadratic programming methods. May be repeated for credit
when topics are distinctly different.
885/ECE 752 Spectral Estimation (3:3:0). Prerequisite:
ECE 528 or STAT 652 or permission of instructor. In-depth study of spectral
analysis and its application to statistical signal processing. Topics include
classical Fourier analysis of deterministic signals and Wiener theory of spectral
analysis for random processes; spectral estimation using the Periodogram and the
window approaches; maximum entropy spectral estimation and its relation to autoregression
modeling; signal subspace approaches for frequency estimation; and the wavelet
transform and its relation to the short-time Fourier transform.
886/ECE 751 Information Theory (3:3:0). Prerequisite:
ECE 630 or STAT 644 or equivalent or permission of instructor. Indepth study
of information theory and its application to communication theory. Topics include
measures of information such as entropy, mutual information, and relative entropy;
the asymptotic equipartition property; noiseless source coding; Universal Source
Coding and the Lemple-Ziv algorithm; channel capacity and the channel coding theorem;
the Gaussian channel; and rate distortion theory and quantization.
888/ECE 753 Distributed Estimation and Multisensor Tracking and Fusion
(3:3:0). Prerequisite: ECE 734 or SYST 611. Centralized and
distributed estimation theory, hierarchical estimation, tracking and data association,
multisensor multitarget tracking and fusion, distributed tracking in distributed
sensor networks, track-to-track association and fusion, and Bayesian networks
for fusion.
890 Special Topics in Urban Transportation (3:3:0). Prerequisite:
CEIE 660,560 or equivalent; or permission of instructor. Special topics and
recent developments in Urban Transportation. Possible subjects include traffic
safety analysis, simulation in transportation, intelligent transportation systems,
and advanced public transportation systems. Congestion management, travel demand
management, geographic information systems in transportation, innovative refinancing
and public -private partnerships in transportation, information technology in
transportation. May be repeated for credit when topics are distinctly different.
891 Special Topics in Applications of Information Technology to Urban
Systems Engineering (3:3:0). Prerequisites: CEIE 670 or permission
of the instructor. Special topics and recent developments in the area of
Information Technology as applied to civil engineering. Possible topics include
inventive engineering, design engineering, network computing, building and using
intelligent agents in engineering, proactive design, etc. May be repeated for
credit when topics are distinctly different.
892 Special Topics in Environmental and Water Resource Systems Engineering
(3:3:0). Prerequisite: CEIE 601. Special topics and recent developments
in environmental and water resources systems engineering analysis and design.
Possible topics include studies in waste minimization; pollution prevention; hazardous
waste management; wastewater management; air pollution control; solid waste management;
environmental decision making; sustainability; water resource and environmental
economics; wetlands management, design and construction; groundwater contamination
modeling; stochastic hydrology; river basin planning and management and water
quality modeling. May be repeated for credit when topics are distinctly different.
894 Design and Inventive Engineering (3:3:0). Prerequisite:
SYST 573, CEIE 670, or OR 681 or permission of instructor. Topics include
evolution of engineering, design engineering, inventive engineering, general design
methodology, conceptual versus detailed design, axiomatic design theory, inferential
design theory, engineering method in design, design paradigms, case-based design,
proactive design, design evaluation, virtual design studio, Internet and browsers
in design, creative problem solving, problem solving methods, and computer tools
to support design creativity.
910 Advanced Topics in Artificial Intelligence (3:3:0). Prerequisite:
Graduate course in artificial intelligence. Special topics in artificial
intelligence not occurring in the regular computer science sequence. Requires
substantial student participation. Subject matter may include continuation of
existing 600- or 700-level courses in artificial intelligence and/or other topics.
May be repeated for credit when subject matter differs.
915 Advanced Topics in Parallel Computation (3:3:0). Prerequisite:
IT 815. Discussion of current research topics in parallel computation. Topics
vary according to student and faculty interest. Possible topics include formal
models of concurrency, specification and design of parallel programming languages,
logic programming in a parallel environment, and parallel distributed processing
(neural networks).
922 Concurrent Object-Oriented Systems (3:3:0). Prerequisite:
IT 822. Comparative study of existing concurrent object-oriented approaches
to problem analysis and software construction. Introduces current research issues
in concurrent object-oriented systems, concurrency models, and concurrent object-oriented
programming languages and development tools.
932/ECE 737 Spread Spectrum Communications (3:3:0). Prerequisite:
ECE 731. Fundamentals of spread spectrum communications. Major topics include
pseudonoise spread spectrum systems, acquisition, synchronization, timehopping,
frequency hopping, and multiple access communication.
937/ECE 755 Optimum Array Processing II (3:3:0). Prerequisite:
IT 837. Adaptive beamformers. SMI and RLS estimators. Spatial smoothing and
FB averaging. QR decomposition. LMS algorithm. Optimum detection. Optimum parameter
estimation. UML and CML estimation. Cramer-Rao bounds. IQML. Weighted subspace
fitting. Subspace algorithms: MUSIC, ESPRIT. Root-versions. Beamspace algorithms.
Sensitivity, robustness, and calibration.
940 Advanced Topics in Control and Robotics (3:3:0). Prerequisites:
ECE 620, 621, 624, and 650. Advanced and newly developed topics in control
and robotics. Content varies depending on current faculty interests and student
demand. Topics such as knowledge-based control, intelligent control, hierarchical
and distributed control, robust control, and reasoning under uncertainty are included.
941 System Identification and Adaptive Control (3:3:0). Prerequisite:
ECE 621 or permission of instructor. Advanced treatment of identification
and adaptive control. Topics include identification algorithms, their convergence
and accuracy, and computational aspects; model reference and self-tuning adaptive
control, transients, stability and robustness; and intelligent schemes to improve
robustness. Students are also required to study the literature and to complete
a computer project.
944 The Process of Discovery and Its Enhancement in Engineering Applications
(3:3:0). Prerequisite: IT 842 or permission of instructor. Study
of ingredients of imaginative reasoning as it concerns the efficient discovery
of new ideas and valid evidential test of them. Topics include different interpretations
of Peirce's theory of abductive reasoning, other forms of reasoning, Hintikka's
analysis of the process of inquiry, and current attempts to design systems that
provide assistance in discovery-related or investigative activities.
945/ECE 945 Advanced Topics in Microelectronics (3:3:0).
Prerequisite: IT 845. Current topics of advanced research in microelectronics.
Topics include very high speed integrated circuits, monolithic microwave integrated
circuits, optoelectronic integrated circuits, novel device structures, and advances
in semiconductor device technology. May be repeated with a change in topic.
950 Design and Management Aspects of Information Systems (3:3:0).
Prerequisite: INFS 790 or equivalent. Impact of organizations and management
of information systems (IS) and vice versa. Topics include problems of introducing
IS; the effect on organizational economic and political framework; participative
design and new techniques for specification, analysis, design, and implementation
of IS; rapid prototyping and expert systems; possible conflicts; methods in life-cycle
management; and economic analysis.
958 Basic and Applied Decision Support Systems Technology (3:3:0).
Prerequisite: SYST 642. Analysis of tools, techniques, and methods
that contribute to the design, development, application, and evaluation of interactive
computer-based decision support systems. State of the art and state of the expectation
of basic and applied decision support systems technologies like requirements definition,
software engineering, analytical methods assessment, and structured evaluation
are analyzed.
962 Advanced Topics in Computer Security (3:3:0). Prerequisite:
IT 862 or 865, or permission of instructor. Current topics of advanced research
in computer security. Content varies depending on faculty interests, research
developments, and student demand. Requires substantial student participation.
Representative topics include formal models for computer security, multilevel
data models, multilevel database management system architectures, secure concurrency
control protocols, distributed secure system architectures, integrity models and
mechanisms, security policy, and requirements analysis.
972/CSI 972 Mathematical Statistics I (3:3:0). Prerequisite:
STAT 652 or equivalent. Focus on the theory of estimation. Principles of
estimation are explored, including the method of moments, least squares, maximum
likelihood, and maximum entropy methods. Methods of minimum variance unbiased
estimation are covered in detail. Topics include sufficiency and completeness
of statistics, Fisher information, Cramer-Rao bounds, Bhattacharyya bounds, asymptotic
consistency and distributions, statistical decision theory, minimax and Bayesian
decision rules, and applications to engineering and scientific problems. af
973/CSI 973 Mathematical Statistics II (3:3:0). Prerequisite:
IT 972. Continuation of IT 972. Concentration on the theory of hypothesis
testing. Topics include characterizing the decision process, simple versus simple
hypothesis tests, Neyman-Pearson Lemma, uniformly most powerful tests, unbiasedness
of tests, invariance of tests, randomized tests, and sequential tests. Applications
of the testing principles are made to situations in the normal distribution family
and to other families of distributions. as
976/CSI 976 Statistical Inference for Stochastic Processes (3:3:0).
Prerequisite: IT 746/CSI 776. Modern theory of parameter estimation
and hypothesis testing for stochastic processes, counting processes with random
intensities, and solutions to stochastic differential equations driven by martingales.
Applications to engineering, biology, and economics are considered. as
978/CSI 978 Statistical Analysis of Signals (3:3:0). Prerequisites:
STAT 544 and 658 or equivalent. Advanced course in the analysis of discrete-
and continuous-time signals using methods of stochastic differential equations
and time series. Familiarity with the methods of harmonic analysis and times series
modeling is presumed. Topics include state-space modeling and eigen-value processing,
nonlinear modeling of signals, non-Gaussian stochastic process structure, detection
and estimation of vector-valued signals, robust signal detection, with applications
to array processing and target tracking.
979/CSI 979 Topics in Statistical Aspects of Information Technology
(3:3:0). Prerequisite: STAT 652 or equivalent. Study of statistical
science and the body of methods and techniques that convert raw data into information.
Contents vary. Such topics as high-interaction statistical graphics, stochastic
methods for parallel computing, cryptography and covert communications, order-restricted
inference, treatments of imprecision, and the foundations of inference are covered.
May be repeated when topics are distinctly different.
980 Advanced Topics in Applied Probability (3:3:0). Prerequisite:
OR 645, 647, or permission of instructor depending on the topic(s) for the semester.
Special topics and recent developments in the field of applied probability. Contents
vary and possible topics include computational probability, stochastic point processes,
advanced queuing theory, traffic and transportation models, percolation, processes
of random aggregation and coagulation, and Markov decision processes. May be repeated
for credit when topics are distinctly different.
981 Advanced Topics in Optimization (3:3:0). Prerequisite:
IT 741, 750, 881, 882, or 884. Special topics and recent developments in
optimization theory and computation. Contents vary and may include topics in linear,
nonlinear, combinatorial, network, global, or stochastic optimization. Prepares
students to perform research in optimization, and requires active student participation.
May be repeated for credit when topics are distinctly different.
983 Advanced Topics in Network Optimization (3:3:0). Prerequisite:
OR 643. Recent developments in solving optimization problems on networks.
Prepares doctoral students to perform advanced research on network-related problems.
Topics include linear, discrete, nonlinear, and stochastic problems. Several aspects
of these problems are also studied, including computational complexity, exact
algorithms, heuristics, solvable special cases, and computer implementation issues.
990 Dissertation Topic Presentation (1:0:0). Prerequisite:
Completion of all course requirements for Ph.D. in IT or permission of instructor.
Opportunity for Ph.D. students to
present their research proposal for critique to interested faculty and students.
Covers the presentation of the research topic for the Ph.D. in Information Technology,
and is required of all Ph.D. students.
The student will complete a dissertation research proposal. May be repeated with
a change in topic, although degree credit is given once.
991 Engineer Project Presentation (1:0:0). Prerequisite:
Completion of all course requirements for the engineer degree in information technology,
or permission of instructor. Opportunity for engineer degree students to
present their project proposal for critique to interested faculty and students.
Covers the presentation of the project topic for the engineer degree in information
technology, and is required of all engineer degree students. The student will
complete a project proposal. May be repeated with a change in topic, although
degree credit is only given once.
996 Engineer Project Proposal (1-6:0:0). Work on a project
proposal that forms the basis for the dissertation for the engineer degree. May
be repeated. No more than 12 credit hours of IT 996 and 997 may be applied to
engineer degree requirements.
997 Engineer Project Dissertation (1-6:0:0). Prerequisite:
Admission to candidacy. Formal record of commitment to engineer project dissertation
under the direction of an advisory committee in information technology. May be
repeated as needed.
998 Doctoral Dissertation Proposal (1-12:0:0). Work on a research
proposal that forms the basis for a doctoral dissertation. May be repeated. No
more than 24 credit hours of IT 998 and 999 may be applied to doctoral degree
requirements.
999 Doctoral Dissertation (1-12). Prerequisite: Admission
to candidacy. Formal record of commitment to doctoral dissertation research
under the direction of a faculty member in information technology. May be repeated
as needed.
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