13th Annual National Black Graduate Student Conference Texas Tech University March 28 - April 1, 2001
Photos
Dr. Cheryl Lewis, McNair Program Director, attended the conference with student representatives of the ECSU Ronald McNair Program. Abstracts from the McNair student presentations follow below.
Abstracts for Poster Presentations
Keisha Harrison, ONR Scholar, Elizabeth City State University "Innovative Visualization of Geospatial Data for Transportation Engineering Applications" The problem of determining an optimal site for a truck and weight enforcement facility along an interstate highway interested a collaborative effort by the Wisconsin Department of Transportation (DOT), KL Engineering and the University of Wisconsin Environmental Remote Sensing Center (ERSC). The study is for site location was located along the I-90 corridor between the Illinois/Wisconsin border and Madison, Wisconsin. The project goal was to pilot innovation in geospatial visualization technology for comparing possible sites for a truck safety and weight enforcement facility. Visualization technology enabled the presentation of spatial information reflecting complex engineering, environmental, transportation and design issues in ways that were clear and understandable to DOT and public stakeholders. EOS-era Landsat-7 satellite data was integrated and synthesized with digital elevation models (DEMs), aerial photography, and other geospatial data to represent current terrain and land cover. Visualization technology and "fly-through" simulations created with ERDAS Imagine software and made accessible through movie files displayed this information at public hearings in forms that were meaningful to general audiences. The NASA-sponsored program for the commercialization of remote sensing Affiliated Research Center (ARC) at UW-Madison provided the suport and resources for piloting this geospatial visualization technology.
Shameika T. Vick, McNair Scholar, Elizabeth City State University "Influence of Particle Size Distribution and Refractive Index of Aerosol Extinctions at SAGE II Wavelengths" The influence of particle size distribution and refractive index on Aerosol Extinctions at Stratospheric Aersol and Gas Experiment (SAGE) II wavelengths is investigated. With the purpose of obtaining the real parts of the complex refractive index N=n+ik, at stratospheric temperatures, we have made extrapolation of quantitative measurements of special transmissions of sulfuric acid solutions in the visible and near infrared at room temperature. On the basis of the results, we have obtained values for n at 210K on sulfuric acid solutions having concentrations by weight of 95.6, 84.5, 75, 50, 38 and 25 percent. The application of the purposed method for identifying a common aerosol size distribution is discussed.
Emmanuel L. Basnight, Jr., McNair Scholar, Elizabeth City State University "What is Requin au Four? The Effects of Gender and the Male Answer Syndrome on Perceptions of Targets in a First Date Situation" A sample of 40 students from Elizabeth City State University participated in a study of how people who exhibit the Male Answer Syndrome are perceived. The Male Answer Syndrome is when a person feels "compelled to generate a rational-sounding answer rather than admit they don't know the answer". Research shows that those who identify with the masculine sex role more often exhibit this behavior. The 40 students consisted of 33 women and 7 men. Of the 40 students, 25 were African Americans, 14 were White Americans, and one was Asian American. The ages of the participants ranged from 18 to 49 years of age with a mean age of 27.82 years. Participants were shown video clips of first date scenarios that varied in gender and whether or not the target gave the Male Answer Syndrome response or an "I don't know" response. Following the video clips, participants's perceptions of the target were assessed. The experimenter then provided the participant with an explanation "Requin Au Four". The participants perceptions of the target were assessed again using the same questionnaire. A 2 (gender) x 2 (type of response) x 2 (before/after answer) analysis of covariance was used to analyze the data.
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