This paper describes lessons learned in developing the linguistic, cognitive, emotional, and gestural models underlying virtual human behavior in a training application designed to train civilian police officers how to recognize gestures and verbal cues indicating different forms of mental illness and how to verbally interact with the mentally ill. Schizophrenia, paranoia, and depression were all modeled for the application. For linguistics, the application has quite complex language grammars that captured a range of syntactic structures and semantic categories. For cognition, there is a great deal of augmentation to a plan-based transition network needed to model the virtual humans knowledge. For emotions and gestures, virtual human behavior is based on expert-validated mapping tables specific to each mental illness. The paper presents five areas demanding continued research to improve virtual human behavior for use in training applications

Codesign of hardware and software for high performance signal processing systems is important if the potential benefits of VLSI are to be realized. This article describes a CAD system developed to support the codesign of hardware and software architectures for high performance digital signal processors which is based on a directed graph methodology. A comprehensive example is developed to demonstrate the use of the system, the fundamentals of the modeling and analysis methodology are discussed, and an overview of the tools in the system is presented along with a discussion of the enhancements currently being developed.