Computer Engineering Commons^™

Cs 415: Social Implications Of Computing, Leo Finkelstein

Computer Science & Engineering Syllabi

CS 415 is a communication skills course using as its subject matter current salient issues associated with the social implications of computing. In addition to the course text, you will need to use certain reading materials in the library and elsewhere, and you will be responsible for using concepts and theories provided in class lectures and discussions.

Cs 480/680: Comparative Languages, Krishnaprasad Thirunarayan

Computer Science & Engineering Syllabi

This course will introduce fundamental concepts and paradigms underlying the design of modern programming languages. For concreteness, we study the details of an object-oriented language (e.g. Java), and a functional language (e.g., Scheme). The overall goal is to enable comparison and evaluation of existing languages. The programming assignments will be coded in Java 5 and in Scheme.

Cs 765: Foundations Of Neurocomputation, Mateen M. Rizki

Computer Science & Engineering Syllabi

This course is designed to help you develop a solid understanding of neural network algorithms and architectures. At the end of this course you should be able to read and critically evaluate most neural network papers published in major journals, (e.g. IEEE Transaction on Neural Networks, Neural Networks, and Neural Computation). In addition, you should be able to implement a broad range of network architectures and learning algorithms for a variety of applications.

Cs 209: Computer Programming For Business Ii, Dennis Kellermeier

Computer Science & Engineering Syllabi

CS 209 is the second of a two quarter sequence in programming for business students. It is required for Management Information Science majors. The courses are designed to help students achieve a high degree of facility in intermediate level programming.

Cs 241: Computer Science Ii, Eric Maston

Computer Science & Engineering Syllabi

This course is the second in the Introduction to Computer Science (24X) series. It focuses on object oriented concepts and an introduction to data structures.

Cs 405/605-01: Introduction To Database Management Systems, Guozhu Dong

Computer Science & Engineering Syllabi

Survey of logical and physical aspects of database management systems. Data models including entity-relationship (ER) and relational are presented. Physical implementation (data organization and indexing) methods are discussed. Query languages including SQL, relational algebra, relational calculus, and QBE are introduced. Students will also gain experience in creating and manipulating a database.

Cs 141-01: Computer Programming - I, Ronald F. Taylor

Computer Science & Engineering Syllabi

This course provides a general introduction to the fundamentals of computer programming. Examples from and applications to a broad range of problems are given. No prior knowledge of programming is assumed. The concepts covered will be applied to the Java programming language. Students must register for both lecture and one laboratory section. 4 credit hours. Prerequisite: MTH 127 (College Algebra) or equivalent.

Cs 240: Computer Science - I, Ronald F. Taylor

Computer Science & Engineering Syllabi

Basic concepts of programming and programming languages are introduced. Emphasis is on structured programming and stepwise refinement. For CS/CEO majors with familiarity of a high-level programming language. Co-requisite: MTH 130 and 131; or MTH 134. 4 credit hours.

Ceg 720-01: Computer Architecture, Jack Jean

Computer Science & Engineering Syllabi

No abstract provided.

Ceg 260-01: Digital Computer Hardware/Switching Circuits, Eric Maston

Computer Science & Engineering Syllabi

We will discuss and cover basic digital, combinational and sequential logic systems. Labs will be used to gain valuable practical experience in implementing elementary circuits and logic designs.

Ceg 360/560-01: Digital System Design, Travis E. Doom

Computer Science & Engineering Syllabi

Design of digital systems. Topics include flip-flops, registers, counters, programmable logic devices, memory devices, register-level design, and microcomputer system organization. Students must show competency in the design of digital systems. 3 hours lecture, 2 hours lab. Prerequisite: CEG260.

Cs 206-01: Advanced Concepts/Techniques And Software Productivity Tools, John P. Herzog

Computer Science & Engineering Syllabi

By the end of this course, the students will have a greater depth of understanding in the areas of spreadsheets, databases, and presentation software using Microsoft Excel, Access, and PowerPoint.

Ceg 220-01: Introduction To C Programming For Engineers, Robert Helt

Computer Science & Engineering Syllabi

This course provides a general introduction to computers as a problem-solving tool using the C programming language. Emphasis is on algorithms and techniques useful to engineers. Topics include data representation, debugging, and program verification. 4 credit hours. Prerequisite: Mm 229 (Calculus I).

Ceg 460/660-01: Introduction To Software Computer Engineering, John A. Reisner

Computer Science & Engineering Syllabi

This course introduces established practices for engineering large-scale software systems. Emphasis is placed on both the technical and managerial aspects of software engineering, and the software development process. This includes techniques for requirements elicitation, analysis, design, testing, and project management. The course emphasizes object-oriented development with the Unified Modeling Language (UML). Hands-on experience is provided through individual homework problems and a group project.

Cs 701: Database Systems And Design I, Guozhu Dong

Computer Science & Engineering Syllabi

An introduction to database design, database system implementation issues and techniques, and advanced data models.

Time-Domain Isolated Phoneme Classification Using Reconstructed Phase Spaces, Michael T. Johnson, Richard J. Povinelli, Andrew C. Lindgren, Jinjin Ye, Xiaolin Liu, Kevin M Indrebo

Electrical and Computer Engineering Faculty Research and Publications

This paper introduces a novel time-domain approach to modeling and classifying speech phoneme waveforms. The approach is based on statistical models of reconstructed phase spaces, which offer significant theoretical benefits as representations that are known to be topologically equivalent to the state dynamics of the underlying production system. The lag and dimension parameters of the reconstruction process for speech are examined in detail, comparing common estimation heuristics for these parameters with corresponding maximum likelihood recognition accuracy over the TIMIT data set. Overall accuracies are compared with a Mel-frequency cepstral baseline system across five different phonetic classes within TIMIT, and a …

Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 21, Number 9, June 2005, College Of Engineering And Computer Science, Wright State University

BITs and PCs Newsletter

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.

Towards Combining Probabilistic And Interval Uncertainty In Engineering Calculations: Algorithms For Computing Statistics Under Interval Uncertainty, And Their Computational Complexity, Vladik Kreinovich, Gang Xiang, Scott A. Starks, Luc Longpre, Martine Ceberio, Roberto Araiza, J. Beck, R. Kandathi, A. Nayak, R. Torres, J. Hajagos

Departmental Technical Reports (CS)

In many engineering applications, we have to combine probabilistic and interval uncertainty. For example, in environmental analysis, we observe a pollution level x(t) in a lake at different moments of time t, and we would like to estimate standard statistical characteristics such as mean, variance, autocorrelation, correlation with other measurements. In environmental measurements, we often only measure the values with interval uncertainty. We must therefore modify the existing statistical algorithms to process such interval data.

In this paper, we provide a survey of algorithms for computing various statistics under interval uncertainty and their computational complexity. The survey includes both known …

Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 20, Number 8, June 2004, College Of Engineering And Computer Science, Wright State University

BITs and PCs Newsletter

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.

Which Fuzzy Logic Is The Best: Pragmatic Approach (And Its Theoretical Analysis), Vladik Kreinovich, Hung T. Nguyen

Departmental Technical Reports (CS)

In this position paper, we argue that when we are looking for the best fuzzy logic, we should specify in what sense the best, and that we get different fuzzy logics as ``the best'' depending on what optimality criterion we use.

Kolmogorov Complexity Leads To A Representation Theorem For Idempotent Probabilities (Sigma-Maxitive Measures), Vladik Kreinovich, Luc Longpre

Departmental Technical Reports (CS)

In many application areas, it is important to consider maxitive measures (idempotent probabilities), i.e., mappings m for which m(A U B)=max(m(A),m(B)). In his papers, J. H. Lutz has used Kolmogorov complexity to show that for constructively defined sets A, one maxitive measure - fractal dimension - can be represented as m(A)= sup{f(x): x in A}. We show that a similar representation is possible for an arbitrary maxitive measure.

If An Exact Interval Computation Problem Is Np-Hard, Then The Approximate Problem Is Also Np-Hard: A Meta-Result, Aline B. Loreto, Laira V. Toscani, Leila Robeiro, Dalcidio M. Claudio, Liara S. Leal, Luc Longpre, Vladik Kreinovich

Departmental Technical Reports (CS)

In interval computations, usually, once we prove that a problem of computing the exact range is NP-hard, then it later turns out that the problem of computing this range with a given accuracy is also NP-hard. In this paper, we provide a general explanation for this phenomenon.

Consortium Of Cise-Mii Funded Institutions: Initial Recommendations On Broadening Participation Of Hispanics, Ann Q. Gates

Departmental Technical Reports (CS)

No abstract provided.

Kaluza-Klein 5d Ideas Made Fully Geometric, Scott A. Starks, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

After the 1916 success of General relativity that explained gravity by adding time as a fourth dimension, physicists have been trying to explain other physical fields by adding extra dimensions. In 1921, Kaluza and Klein has shown that under certain conditions like cylindricity (dg_{ij}/dx^5=0), the addition of the 5th dimension can explain the electromagnetic field. The problem with this approach is that while the model itself is geometric, conditions like cylindricity are not geometric. This problem was partly solved by Einstein and Bergman who proposed, in their 1938 paper, that the 5th dimension is compactified into a small circle S^1 …

Some Usability Issues And Research Priorities In Spoken Dialog Applications, Nigel Ward, Anais G. Rivera, Karen Ward, David G. Novick

Departmental Technical Reports (CS)

As a priority-setting exercise, we examined interactions between users and a simple spoken dialog system in comparison to interactions with a human operator. Based on analysis of the observed usability differences and their root causes we propose seven priority issues for spoken dialog systems research.

Computing Best-Possible Bounds For The Distribution Of A Sum Of Several Variables Is Np-Hard, Vladik Kreinovich, Scott Ferson

Departmental Technical Reports (CS)

In many real-life situations, we know the probability distribution of two random variables x1 and x2, but we have no information about the correlation between x1 and x2; what are the possible probability distributions for the sum x1+x2? This question was originally raised by A. N. Kolmogorov. Algorithms exist that provide best-possible bounds for the distribution of x1+x2; these algorithms have been implemented as a part of the efficient software for handling probabilistic uncertainty. A natural question is: what if we have several (n>2) variables with known distribution, we have no information about their correlation, and we are interested …

Why Product Of Probabilities (Masses) For Independent Events? A Remark, Vladik Kreinovich, Scott Ferson

Departmental Technical Reports (CS)

For independent events A and B, the probability P(A&B) is equal to the product of the corresponding probabilities: P(A&B)=P(A)*P(B). It is well known that the product f(a,b)=a*b has the following property: once P(A1)+...+P(An)=1 and P(B1)+...+P(Bm)=1, the probabilities P(Ai&Bj)=f(P(Ai),P(Bj)) also add to 1: f(P(A1),P(B1))+...+f(P(An),P(Bm))=1. We prove that the product is the only function that satisfies this property, i.e., that if, vice versa, this property holds for some function f(a,b), then this function f is the product. This result provided an additional explanation of why for independent events, we multiply probabilities (or, in the Dempster-Shafer case, masses).

In this paper, we strengthen …

A Jbi Information Object Engineering Environment Utilizing Metadata Fragments For Refining Searches On Semantically-Related Object Types, Felicia N. Harlow

Theses and Dissertations

The Joint Battlespace Infosphere (JBI) architecture defines the Information Object (IO) as its basic unit of data. This research proposes an IO engineering methodology that will introduce componentized IO type development. This enhancement will improve the ability of JBI users to create and store IO type schemas, and query and subscribe to information objects, which may be semantically related by their inclusion of common metadata elements. Several parallel efforts are being explored to enable efficient storage and retrieval of IOs. Utilizing relational database access methods, applying a component-based IO type development concept, and exploiting XML inclusion mechanisms, this research improves …

Auto-Pipe: A Pipeline Design And Evaluation System, Mark A. Franklin, John Maschmeyer, Eric Tyson, James Buckley, Patrick Crowley

All Computer Science and Engineering Research

Auto-Pipe is a tool that aids in the design, evaluation, and implementation of pipelined applications that are distributed across a set of heterogeneous devices including multiple processors and FPGAs. It has been developed to meet the needs arising in the domains of communications, computation on large datasets, and real time streaming data applications. In this paper, the Auto-Pipe design flow is introduced and two sample applications, developed for compatibility with the Auto-Pipe system, are presented. The sample applications are the Triple-DES encryption standard and a subset of the signal-processing pipeline for VERITAS, a high-energy gamma-ray astrophysics experiment. These applications are …

Motion Detection Using Randomized Methods, Howaida Mohamed Naguib

Archived Theses and Dissertations

The detection and recogni6on of a moving object in a sequence of time varying images proves to be a very important task in machine intelligence in general and computer vision in particular. Recently, parametric domain techniques have been successfully used with a number of variants. In such melhods, the image is transfonned into some parameter space and the motion detection process is applied in that space. A recent parametric domain is the Randomized Hough Transform (RHT) that uses random sampling mechanism in the image space, score accumulation in the parameter space, and bridge between them using a converging mapping. The …