Ellen Walker

Teaching Web development with limited resources

Computer Science programs are faced with demand from both students and employers for courses in hot topics such as Internet Administration, but resources such as course time and laboratory facilities are often scarce. Another trend facing our programs is the need to increase availability to non-traditional students. This paper describes a course in Internet Administration for both traditional and non-traditional students and how it addressed the issues of limited time, diverse student population, and limited laboratory facilities.

Combining geometric invariants with fuzzy clustering for object recognition

Object recognition is the process of identifying the types and locations of objects in the image. Earlier work has shown the desirability of using fuzzy compatibility for local feature correspondence and fuzzy clustering for pose estimation of two dimensional objects. The paper extends the methodology to images of three dimensional objects by applying geometric invariants, specifically the cross ratio of four collinear points. The recognition process is divided into three subtasks: local feature correspondence, object identification, and pose determination. Algorithms are described for each subtask.

Mechanics of undergraduate research at liberal arts colleges: lessons learned

The benefits of engaging undergraduate students in research are numerous and well-known. Therefore, many schools are encouraging undergraduate research. However, carrying out undergraduate research in a liberal arts school can be challenging – liberal arts schools usually lack the resources typically available in larger research universities; the research programs of faculty at such schools are often insular; undergraduates may not always be adequately prepared or motivated for research; and research is only one of the many activities competing for the time and energy of undergraduate students. The objective of this panel is to discuss how undergraduate research can be successfully carried out in liberal arts schools in spite of all these constraints. We want to examine the mechanics of undergraduate research in such an environment which practices work and which do not.

Generation CS: the growth of computer science

Across North America, universities and colleges are facing a significant increase in enrollment in both undergraduate computer science (CS) courses and programs. The current enrollment surge has exceeded previous CS booms, and there is a general sense that the current growth in enrollment is substantially different from that of the mid-1980s and late 1990s. For example, since the late 1990s, the U.S. Bureau of Labor data shows that the number of jobs where computing skills are needed is on an upward slope [1], illustrating the increased reliance our society has on computing. We also know that more disciplines are becoming increasingly reliant on large amounts of data, and that handling this data effectively depends on having good computational skills. This makes computer science courses at all levels of greater interest to students from other majors.

A fuzzy approach to pose determination in object recognition

Object recognition is the process of identifying and locating known objects in complex images. It includes extracting relevant features, grouping these features together, selecting an appropriate object model, and determining the pose (position and orientation) of the object in the scene. In earlier work, the author has shown that fuzzy methods are appropriate for representing geometric relationships that are used for both perceptual grouping of geometric features and for associating geometric image features with models. The paper explores fuzzy methods for the final step in object recognition, that of global pose determination. She develops a method based on fuzzy c means (FCM) clustering, and demonstrates its effectiveness over traditional crisp pose clustering.

Automatic extraction of invariant features for object recognition

A powerful technique for three-dimensional object recognition has been the use of geometric invariants: measurable relationships between geometric objects that are invariant to transformations such as projection. Because of the invariance, these measurements will be the same whether measured on the actual three-dimensional object, or in the image. Therefore, objects in the image can be recognized if the same invariant can be found. In this paper, we investigate the automatic extraction of cross-ratio invariant features for object recognition. We show that clustering is a promising technique in this extraction, because it reduces the dependency on tuning parameters in the image processing phase.

Generation CS: the mixed news on diversity and the enrollment surge

I the June issue of ACM Inroads [1], we consider the phenomenal growth of computer science (CS) in both CS undergraduate degree programs and CS courses at doctoral-granting and non-doctoral-granting units.1 This article examines the impact of the undergraduate enrollment surge on diversity (i.e., women and underrepresented minorities) using two existing data sets (i.e., the CRA Taulbee Survey [3] and IPEDS [5]) and data collected from the CRA Enrollment Survey [2]. We also highlight relationships discovered from the CRA Enrollment Survey between actions taken by units to manage the surge and their impact on diversity.

Communicating What Liberal Arts Colleges Contribute to Computer Science (Abstract Only)

How can CS faculty at liberal arts colleges better communicate with colleagues and the public about the value our institutions offer? Liberal arts colleges play an important role in undergraduate CS education. Liberal arts skills are widely valued in the tech industry, many liberal arts undergraduates go on to earn Ph.D.s in STEM, and many of the educational innovations presented at SIGCSE are developed by liberal arts faculty. Yet, our colleagues at research universities often misunderstand what we do at liberal arts colleges. And while we see the liberal arts and computer science as supporting each other, the popular media tends to portray them as diametrically opposed. These misconceptions limit our opportunities to attract new students and colleagues, as well as opportunities to contribute to public discourse about the important role of information technology in our society. In this BoF, we aim to collaboratively develop communication strategies for individual participants and for the liberal arts CS community as a whole.

Generation CS: the challenges of and responses to the enrollment surge

I the June issue of ACM Inroads [1], we explored the phenomenal growth of computer science (CS) in CS undergraduate degree programs and CS courses at both doctoral-granting and non-doctoral-granting units1. In the September issue of ACM Inroads [2], we investigated the impact of this enrollment surge on diversity. This article examines (1) the impact of increasing enrollments on computer science units, as reported by the units, and (2) the actions taken or not taken by the 134 doctoraland 93 non-doctoral-granting units that responded to the CRA Enrollment Survey.

News from the SIGs

Welcome once again to reports highlighting trends within the computing education community from three Special Interest Groups (SIGs) within ACM. One SIG focuses on computer science education (SIGCSE), another on information technology education (SIGITE), and another on management information systems (SIGMIS).