Kelly R. Debure

The Quantitative Excellence in Science and Technology (QuEST) Scholars Program facilitates the academic success of transfer students who enter Eckerd College intending a STEM major. Our primary goal is to create and nurture cohorts of STEM transfer students through specifically designed and carefully monitored academic and social-support activities. Transfer students face unique challenges as they transition to a new institution. Each student has completed a unique set of courses, requiring careful faculty mentoring to plan the successful completion of a STEM degree. Transfer students also lack the advantages of a natural cohort of peers, unlike native freshmen who are typically taking the same classes at the same stages throughout their undergraduate careers. To address these issues, we created a Scientific Inquiry Seminar, one course extending over two semesters, for all new QuEST Scholars. The discussion-based course included a wide range of topics, from ethical issues and cutting-edge research in science, to more mundane topics such as graduation requirements, career planning, and resume building. To foster success for all STEM majors, we improved the peer-tutoring program for students struggling with quantitative subjects presented in math and science courses. We unified peer-tutors for computer science, physics, mathematics, and chemistry under one umbrella with a dedicated faculty member to oversee the program and developed an on-line reporting system to track individual sessions. Tutor development seminars were held regularly. Building a learning community among students and tutors was one of the most frequently mentioned positive outcomes of the tutoring program, according to exit interviews with tutors. We are in the fifth year of our NSF grant (S-STEM #1154520) and have provided scholarship support for 28 undergraduates, including 15 who intended to major in Marine Science and one in Geosciences. Average awards are $8,000 per year and are renewable based on continued progress as a STEM major and unmet financial need. Ten students received scholarships until graduating with a bachelor's degree, 10 are still receiving support as STEM majors, and 8 left Eckerd and/or switched to a non-STEM major prior to graduation. We compare these results to those of native freshmen choosing STEM majors.

Boundary descriptors may be used effectively in various image based recognition problems. However, when images are acquired in uncontrolled conditions, changes in pose and illumination complicate the alignment process that must occur prior to comparison. The alignment is further complicated when the objects of interest are characterized by open contours and when distinct feature points are absent. We present an application that employs an iterative approach to the alignment of open contours and suggest a method for selecting corresponding points along a pair of contours for the purpose of determining similarity. We demonstrate the success of this approach in recognizing individual bottlenose dolphins from the profiles of their dorsal fins.

DARWIN is a computer vision system, which helps researchers identify individual bottlenose dolphins, Tursiops truncatus, by comparing digital images of the dorsal fins of newly photographed dolphins with a database of previously identified dolphin fins. In additional to dorsal fin images, textual information containing sighting data is stored for each of the previously identified dolphins. The software uses a semiautomated process to create an approximation of the fin outline. The outline is used to formulate a sketch- based query of the dolphin database. The system utilizes a variety of image processing and computer vision algorithms to perform the matching process, which is necessary to identify those previously identified fins, which most closely resemble the unknown fin. The program presents the database fin images to the researcher in rank order for comparison with the new fin image.

Transform-based image coders exploit the information packing ability of some mathematical transforms in order to reduce the number of significant transform coefficients needed to accurately represent an image. Large coefficients are often associated with those regions where an image changes a lot, such as the boundaries between objects with differing visual characteristics. One way to reduce the number of significant transform coefficients is to segment an image into regions of similarity and then apply the transform to each region separately. We propose a novel image compression technique which first segments an image into arbitrary regions and then applies a region-adapted wavelet transform to each region.

The software created for the Control Display Units (CDUs), used for the Advanced Transport Operating Systems (ATOPS) project, on the Transport Systems Research Vehicle (TSRV) is described. Module descriptions are presented in a standardized format which contains module purpose, calling sequence, a detailed description, and global references. The global reference section includes subroutines, functions, and common variables referenced by a particular module. The CDUs, one for the pilot and one for the copilot, are used for flight management purposes. Operations performed with the CDU affects the aircraft's guidance, navigation, and display software.

The Flight Management/Flight Controls (FM/FC) software for the Norden 2 (PDP-11/70M) computer installed on the NASA 737 aircraft is described. The software computes the navigation position estimates, guidance commands, those commands to be issued to the control surfaces to direct the aircraft in flight based on the modes selected on the Advanced Guidance Control System (AGSC) mode panel, and the flight path selected via the Navigation Control/Display Unit (NCDU).