Andrew Bernat

Structuring the student research experience

The benefits of working in a research group are clear: students develop domain expertise, gain an understanding and appreciation of the research process and its practice, and acquire team, communication, problem-solving, and higher-level thinking skills. Students with this experience are better equipped to make informed judgments about technical matters and to communicate and work in teams to solve complex problems. However, it is difficult to provide a quality experience to large numbers of students, particularly to students of differing abilities.The Systems and Software Engineering Affinity Research Group model provides a socialization mechanism and infrastructure that supports the development and management of large research groups that engage undergraduate and graduate students, who have a wide range of skill levels and experiences, in research and projects. This non-hierarchical model integrates students into both small research groups and an encompassing large research group, and uses structured activities to develop their research, technical, communication, and group skills.In this paper we introduce the model and report how the model meets independently developed Best Practice guidelines for student research experiences and we provide indicators of success for use by other projects.

Affinity groups: a framework for developing workplace skills

This paper describes the affinity group concept and model as an alternative to traditional research groups in university computer science programs. The affinity research groups provide a physical setting in a cooperative environment in which undergraduate and graduate college students engage in research. Affinity groups involve students with a wide range of experiences, talents, interests and skill levels, and provide them with an opportunity to deepen their knowledge in a computer science area and to develop skills and strategies that will make them effective leaders and successful in academia and industry. The structured activities that are characteristic of affinity groups facilitate the transfer of knowledge and skills from an academic setting to the workplace. The paper addresses issues in the development of workplace skills, the challenges of the transfer of knowledge and skills and the particular ways in which the affinity group processes take into account what is known about transfer and the development of research, technical and social skills.

Evaluating the undergraduate research experience in computer science: developing a framework for gathering information about effectiveness and impact

As undergraduate research experience programs proliferate to include all students, the need to evaluate and assess these types of programs also grows. This paper presents an overview of the evaluation/assessment process and a framework for developing an evaluation plan to assess the effectiveness and impact of the undergraduate research experience. Drawing on the ongoing evaluation of the Affinity Research Group at the University of Texas at El Paso, USA, the framework is designed to: (1) focus on issues and questions that form the basis for the design and implementation of the evaluation of undergraduate research experience programs in computer science; and (2) provide examples of indicators and tools for assessing program outcomes and process.

Developing the Breadth-First Curriculum: Results of a Three-Year Experiment

This article summarizes the results of designing, class-testing, and developing teaching materials (texts, laboratory manuals, and software) for a novel introductory curriculum in computer science ...

Is Solar System Stable? A Remark

It is not yet known (1997) whether the Solar system is stable or not. Common belief is that the Solar system is stable if and only if it is not a resonant system, i.e., whenever its orbital frequencies ωi satisfy an inequality |Σ niωi| ≤ ε for Σi|ni| ≤ N; a similar inequality is true for randomly chosen frequencies. In this paper, we show that the Solar system does not have such resonances, and therefore (if the above-mentioned belief is correct), it is stable.

Comparison Of Three Motion Detection Techniques

The accuracy of motion detection in an image by three proposed techniques is explored using synthetic images with varying contrasts and noise levels. The maximum likelihood test consistently results in a higher probability of detection of true motion than either mean or median tests. However, the maximum likelihood test also consistently has a higher probability of false alarms, that is, the detection of stationary objects as moving objects, than either mean or median tests. For applications in which execution efficiency is at least as important as a high probability of detection, the mean or median tests may be used to advantage.

Security Applications Of Computer Motion Detection

An important area of application of computer vision is the detection of human motion in security systems. This paper describes the development of a computer vision system which can detect and track human movement across the international border between the United States and Mexico. Because of the wide range of environmental conditions, this application represents a stringent test of computer vision algorithms for motion detection and object identification. The desired output of this vision system is accurate, real-time locations for individual aliens and accurate statistical data as to the frequency of illegal border crossings. Because most detection and tracking routines assume rigid body motion, which is not characteristic of humans, new algorithms capable of reliable operation in our application are required. Furthermore, most current detection and tracking algorithms assume a uniform background against which motion is viewed - the urban environment along the US-Mexican border is anything but uniform. The system works in three stages: motion detection, object tracking and object identi-fication. We have implemented motion detection using simple frame differencing, maximum likelihood estimation, mean and median tests and are evaluating them for accuracy and computational efficiency. Due to the complex nature of the urban environment (background and foreground objects consisting of buildings, vegetation, vehicles, wind-blown debris, animals, etc.), motion detection alone is not sufficiently accurate. Object tracking and identification are handled by an expert system which takes shape, location and trajectory information as input and determines if the moving object is indeed representative of an illegal border crossing.

Class testing the breadth-first curriculum (abstract): summary results for courses I–IV

Several different undergraduate programs have been designing and class-testing alternative curricula for their f~st four courses using the 7-course “breadth-first” approach described in the ACM/IEEE-CS report Computing Curricula 1991 [1]. These courses have several major goals: 1. Broad subject matter coverage, beginning with the first course; 2. Integration of mathematics, science, and engineering points of view with the subject matter; 3. Inclusion of social issues (such as the risks and liabilities that surround software failures); and 4. Weekly coordinated laboratory activities. The goals of this approach, generally speaking, are to provide an introduction to the discipline of computing that more directly reflects its nature and breadth than does the traditional approach, especially in its fwst four courses. A complete set of teaching materials for the first four courses in the breadth-f~st curriculum has been developed and class–tested. These four courses are titled: Course I: Logic, Problem Solving, Programs, and Computers Course II: Abstraction, Data Structures, and Large Soflware Systems Course III: Levels of Architecture, Lunguages, and Machines Course A? Algorithms, Concurrency, and the Limits of Computation This panel session will focus on these four courses in the breadth-first curriculum, which have been class-tested in a variety of different institutional settings (including Bowdoin, UConn, UTEP, Allegheny, and Swarthrnore) during the 1991-92, 1992–93, and 1993–94 academic years. The panelists will present the results of class–testing these courses and address the topics summarized in the paragraphs below. There will be time for questions and discussion between presentations. 1. Course L Origination, class-testing, and revision (Bernat). Experience with Course I in the breadtl-first curriculum has led to several modifications: stronger integration of the mathematics and programming methodology, in particular to provide motivation for the introduction and development of logic; stronger integration of specifications as a design tool, in particular to motivate the need for precision in specifications; stronger emphasis on abstraction, in particular as adesigntool for handling detail. At the same time we retain the strong computer science emphasis, the understanding of societal issues, and the suitability for use as an introduction of computer science for non–majors. 2. Courses Z1 Object-orientation, data structures, and operating systems (Cupper). The goals of course II are reflected in the title of the tex~ ZWzdamenrals of Computing 11; Abstraction, Data Structures, and Large So@are Systems [2]. Object~rientation provides a natural and efllcient vehicle for accomplishment of these goals. The course begins with an overview of the principles of software design. Object~rientation is presented as an appropriate way to meet these principles of software design.

Building Systems the Old Fashioned Way

Most real real-time systems are hybrid systems with certain deadlines which must be met, others which are slippable and other computations which may run as resources permit. In astronomy, computers are used to drive the telescope, rotate the dome, control the instrument and record, display and even reduce (analyse) the data. Some of these tasks have no real deadlines: data reduction can always be done later, off-line, but with a reduction in the ability of the scientist to modify his/her experiment as the evening progresses. Some of these tasks have soft deadlines: rotating the dome may be delayed as long as the slit still clears the telescope field of view; displaying the data need not be 100% up-to-date. Still other tasks must meet hard deadlines: the telescope must be driven consistently across the sky to keep the object centered; the instrument must be controlled as required to record data at precise intervals, etc. But even some of these hard tasks have widely varying time scales. The result is a very complicated system.

Computer science research and instuction at institutions with large minority enrollments (panel session)

This panel focuses on computer science research and educational activities involving minorities. In addition to highlighting various research in progress, this panel will emphasize how research at a given institution has impacted the corresponding computer curriculum. Specific information to be discussed by the panel will include: 1) a brief overview of computer science research projects at institutions represented by panel members, 2) a short discussion on how the research conducted has impacted the computer science educational programs, and 3) a question and answer session addressing ways other institutions can make use of the research presented in an educational setting, Finally, some attention will be given to addressing ways researchers from predominately minority institutions can embark on more joint research projects with researchers from predominantly majority universities,