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In this paper, we propose techniques for detecting anomalies in user accesses by learning profiles of normal access patterns of users based on both the syntactic and semantic features of past users queries stored in database logs. New accesses are checked upon these profiles and deviations are considered anomalous accesses which may be indications of potential insider attacks. We consider two scenarios...
Lower extremity exoskeletons are intelligent wearable robots that integrate human intelligence with the strength of humanoid robots. Recently, lower extremity exoskeletons have been developed for rehabilitation and assistance of paralysis patients. This paper presents design of a novel anthropomorphic lower extremity exoskeleton with compatible hip joints and knee joints that help paralysis patients...
Most current approaches in action recognition face difficulties that cannot handle recognition of multiple actions, fusion of multiple features, and recognition of action in frame by frame model, incremental learning of new action samples and application of position information of space-time interest points to improve performance simultaneously. In this paper, we propose a novel approach based on...
In this paper, we propose a framework which fuses multiple features for action recognition in depth sequence. The fusion of multiple features is important for recognizing action since a single feature-based representation is inadequate to capture the variants. Hence, we use two types of features: i) a quantized vocabulary of local spatio-temporal descriptor HOG3D, and ii) a global projection based...
A new image restoration method was presented and investigated based on genetic algorithm BP neural network. The method combined the characteristics of global optimization of genetic algorithm with local optimization of BP neural network. The mapping relationship between degenerated image and clear image was established by training genetic algorithm BP neural network. Experimental results show that...
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