Agent Based Approaches to Engineering Autonomous Space Software

Current approaches to the engineering of space software such as satellite control systems are based around the development of feedback controllers using packages such as MatLab's Simulink toolbox. These provide powerful tools for engineering real time systems that adapt to changes in the environment but are limited when the controller itself needs to be adapted. We are investigating ways in which ideas from temporal logics and agent programming can be integrated with the use of such control systems to provide a more powerful layer of autonomous decision making. This paper will discuss our initial approaches to the engineering of such systems.Comment: 3 pages, 1 Figure, Formal Methods in Aerospac

Is It In The Name, Or In The Game? Can News Affect Firm Value? A Case For Athletes Sponsored By Nike, Inc.

Until recently, little of the celebrity endorsement literature has focused on how the activities of an athlete affect a company’s value.  Those that do, tend to focus on the impact of one star, such as Tiger Woods in golf, on a variety of companies.  This paper adopts the behavioral finance viewpoint and examines the impact of news relating to various sport stars’ performance, both on and off the field, on the sponsoring/endorsing firm’s value.  This research analyzes the impact across seven sports under Nike Inc.’s endorsement umbrella.  In doing so, this study finds that news pertaining to the very best “athletic stars” in their respective sports do not directly affect Nike’s stock price.  In fact, the only sport having a significant impact on stock price is professional golf.  Surprisingly, news relating to basketball, the sport generating one the largest endorsement expenses for Nike, Inc., did not have a significant influence on stock price.  Such results lead the authors to conclude that 1) the success of those sports stars under Nike’s endorsement umbrella does not directly add value to the firm, and 2) other factors may play a role in influencing investor behavior, to include airtime, public perception, and the size of the market, itself

ILIAD's Role in the Generalization of Learning Across a Medical Domain

Conference PaperBiomedical Informatic

ILIAD Training Enhances Medical Students' Diagnostic Skills

journal articleBiomedical Informatic

ILIAD's Role in the Generaliztion of Learning Across a Medical Domain

Conference PaperBiomedical Informatic

Characterization of Speakers for Improved Automatic Speech Recognition

Automatic speech recognition technology is becoming increasingly widespread in many applications. For dictation tasks, where a single talker is to use the system for long periods of time, the high recognition accuracies obtained are in part due to the user performing a lengthy enrolment procedure to ‘tune’ the parameters of the recogniser to their particular voice characteristics and speaking style. Interactive speech systems, where the speaker is using the system for only a short period of time (for example to obtain information) do not have the luxury of long enrolments and have to adapt rapidly to new speakers and speaking styles. This thesis discusses the variations between speakers and speaking styles which result in decreased recognition performance when there is a mismatch between the talker and the systems models. An unsupervised method to rapidly identify and normalise differences in vocal tract length is presented and shown to give improvements in recognition accuracy for little computational overhead. Two unsupervised methods of identifying speakers with similar speaking styles are also presented. The first, a data-driven technique, is shown to accurately classify British and American accented speech, and is also used to improve recognition accuracy by clustering groups of similar talkers. The second uses the phonotactic information available within pronunciation dictionaries to model British and American accented speech. This model is then used to rapidly and accurately classify speakers