This thesis describes development of the Tarot game for mobile devices. The game is developed in Java - J2ME. The application allows to play Tarot to one through four people. The player intelligence represented by the mobile device is implemented as an expert system. The expert system rules can be changed without necessity to recompile the application. Designed and implemented expert system uses a lightweight version of Prolog language as a knowledge base. The system requires the rules of precisely defined form specified in this thesis.

The Virginia Integrated Pest Management Expert for Wheat was designed to combine the best available information regarding wheat pest management of disease pathogens, weeds, and insects into a decision support system that would provide potential outbreak risk and pest control information to the Comprehensive Resource Planning System (CROPS). In addition, the system stands alone as an educational tool for farmers and Extension personnel. This is a rule-based system developed on the Microsoft Windows platform. Knowledge about crops and pest management is represented in the form of IF/THEN rules, demons, and "when-changed" methods. The inference engine analyzes specific crop system information entered by the user to determine potential risks of outbreak for wheat crop pests common to Virginia. These potential outbreak risks are presented as low, medium, and high levels of risk and are presented for each of 15 pests of wheat in Virginia. The system was evaluated using thirty random cropping system scenarios. By comparing expert system output with output from human experts, it was shown that the expert system agreed with human expert opinions in 84 percent of the decisions made. Statistical analysis of the insect pest data showed that there was no significant statistical difference between the distribution of the human expert predictions and the expert system predictions. Statistical analysis of the disease pest data showed that there were some significant statistical differences between the distribution of the human expert predictions and the expert system predictions. / Master of Science

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The current study examined the impact of expert witness orientation (researcher or clinical practitioner) and type of testimony (testimony for the prosecution, for the defense, for both prosecution and defense, and no testimony) on mock jurors‟ decisions in a sexual abuse trial. Participants read a summary of a sexual abuse criminal trial based on recovered memory; the summary included expert witness testimony (varied across participants based on the conditions described above). Participants then completed a juror decision making task. Results showed that expert witness testimony provided by a researcher did not impact mock jurors‟ guilt ratings any differently than the expert witness testimony provided by a clinical practitioner. However, type of testimony had a significant effect on jurors‟ guilt ratings. The prosecution witness expert testimony influenced mock jurors‟ decision in favor of the prosecution and testimony by a defense expert influenced the jurors‟ decisions in favor of the defense.

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