There are two demanding needs which must be fulfilled to further the development of automatic target recognition systems. One is analytical modeling for performance prediction and the other is a disciplined evaluation methodology for automatic target recognition algorithms. Currently both areas are in their infancy.The analytical modeling for automatic target recognition performance evaluation and for prediction of algorithm performances has been investigated, both as they relate to human visual performances and as a tool for algorithm development.The matched filter approach presented a good limiting performance for target detection in uncluttered scenes with complete knowledge-of the target characteristics. The comparision of the matched filter detection performance to human performance model have produced some interesting results.

Recent popularity of the smartphone market, with the explosive growth of mobile location-based SNS(Social Network Service), is into the mainstream. SNS aims to cooperate and share information with all users, but mobile SNS is still not easy people with disabilities. In addition to using the Web, it has difficulty to provide an appropriate interface to access such as smartphone for people with disabilities.This paper will specify and analyze the context-awareness technology and SNS function, and study a variety of information that students with disabilities such as time, location and activity states including data collection and analysis of the situation by converting the status information. It has provide that students with disabilities to lead comfortable life in school according to the various types of disabilities, and school information and safety services using mobile location-based SNS.

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The complex relationships between the vast number of system parameters make the evaluation of automatic target recognition algorithms a most complicated task. The sensor and system parameters, and environment, all play a key role in the performance of ATR systems. Consequently, a more complete performance model will require some or all of these parameters to be incorporated in the model design. Unfortunately, parameters like environment and opponent's strategy are virtually impossible to model at all but the most abstract levels.When the actual approach angle differs from the expected approach angle, several errors occur in template matching ATR algorthms and degrades the performance of ATR systems. This paper describes an effort which concentrated on the modeling of geometrically induced errors in ATR performance. Our effort was focused on the performance degradation caused by geometrically induced errors such as an aspect error. There is much merit to matched filter techniques and therefore the matched filter based analytical model is enhanced for the detection performance measure in the problem depicted above.

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