Four studies examined the effect of an incidental similarity on compliance to a request. Undergraduates who believed they shared a birthday (Study 1), a first name (Study 2), or fingerprint similarities (Study 3) with a requester were more likely to comply with a request than participants who did not perceive an incidental similarity with the requester. The findings are consistent with past research demonstrating that people often rely on heuristic processing when responding to requests and with Heider's description of unit relationships in which perceived similarities lead to positive affect. Consistent with the unit relation interpretation, participants did not increase compliance when hearing about an incidental similarity with someone other than the requester or when they believed the feature they shared with the requester was common.

The use of Expert Systems as a means of providing satellite operators with a fast and reliable telemetry analysis tool has become increasingly widespread. We have developed a MATLAB-based Expert System that is intended to provide production rule based telemetry analysis functionality to the operator while leveraging the power and available support for the MATLAB software package. The initial phase of this project involves the development of production rule methodology code, which can quickly and efficiently provide the satellite operator with the engineering data required to make command decisions. Our efforts have also focused on support capabilities for the Expert System to include the ability to edit rules and update satellite specific threshold values. Initial code validation using archived telemetry from the Sapphire satellite has shown that the code functions as designed. A full test of the code during a live contact has yet to be accomplished. The flexibility of the MATLAB scripting language provides an Expert Systems platform that has a tremendous potential for evolving to include features like persistence-based reasoning and long term plotting.