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Gestures are important communication medium. However, their semantic ambiguities make it difficult for computer systems to accurately recognize and deliver them. The interpretation of gestural motions is not even consistent in human-to-human communications. In this paper, we compare gestures in order to establish a method to reveal the influence of gesture speed on semantic interpretation. We captured whole-body motions as movie files with a depth camera and converted them into biological motion movie files. The speed of these motion images was then systematically altered, and a perceptual experiment was conducted on 11 participants. Using the results from the experiment, we identified speed dependencies of human gesture recognition.

Summary Handling hardware‐dependent properties at a low level is usually required in developing microcontroller‐based applications. One of these hardware‐dependent properties is cautions, which are described in microcontrollers hardware manuals. The process of verifying these cautions is performed manually, as there is currently no single tool that can directly handle this task. This research aims at automating the verification of these cautions. To obtain the typical cautions of microcontrollers, we investigate two sections which have a considerable number of required cautions in the hardware manual of a popular microcontroller. Subsequently, we analyse these cautions and categorize them into several groups. Based on this analysis, we propose a semi‐automatic approach for verifying the cautions which integrates two static programme analysis techniques (i.e., pattern matching and abstract interpretation). To evaluate our approach, we conducted experiments with generated source code, benchmark source code, and industrial source code. The generated source code, which was created automatically based on several aspects of the C programme, was used to evaluate the performance of the approach based on these aspects. The benchmark and the industrial source code, which were provided by Aisin Software Co., Ltd., were used to assess the feasibility and applicability of the approach. The results show that all expected violations in the benchmark source code were detected. Unexpected but real violations in the benchmark programme were also detected. For the industrial source code, the approach successfully handled and detected most of the expected violations. These results show that the approach is promising in verifying the cautions.

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