Open Access. Powered by Scholars. Published by Universities.®

Social and Behavioral Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 3 of 3

Full-Text Articles in Social and Behavioral Sciences

Planning Your Way To A More Usable Web Site, Pamela Gore, Sandra Hirsh May 2003

Planning Your Way To A More Usable Web Site, Pamela Gore, Sandra Hirsh

Faculty Publications

Planning for long-term periodic usability assessment is therefore as important as adding regularly fresh content and tracking usage. Fortunately, usability assessments need not be time consuming or expensive, unless your site is large and complex and you want to test it thoroughly each time. In a practical sense, usability assessment can reveal problems in the design, navigation, layout, or labeling that prevent users from finding what they need quickly. After analyzing your environment and setting the stage for ongoing usability assessment, it is time to develop the usability assessment plan, which will serve as the blueprint for usability assessment activities …


Search And Recovery Of The Space Shuttle Columbia: A Geospatial 1st Responder Perspective, Jeffrey M. Williams Apr 2003

Search And Recovery Of The Space Shuttle Columbia: A Geospatial 1st Responder Perspective, Jeffrey M. Williams

Faculty Publications

A first person account of the Texas geospatial volunteers and their efforts to recover the remains of the Space Shuttle Columbia and her crew lost over eastern Texas and western Louisiana on February 1st, 2003.


A Memory-Based Approach To Cantonese Tone Recognition, Deryle W. Lonsdale, Michael Emonts Jan 2003

A Memory-Based Approach To Cantonese Tone Recognition, Deryle W. Lonsdale, Michael Emonts

Faculty Publications

This paper introduces memory-based learning as a viable approach for Cantonese tone recognition. The memorybased learning algorithm employed here outperforms other documented current approaches for this problem, which is based on neural networks. Various numbers of tones and features are modeled to find the best method for feature selection and extraction. To further optimize this approach, experiments are performed to isolate the best feature weighting method, the best class voting weights method, and the best number of k-values to implement. Results and possible future work are discussed.