Various systems have explored the idea of inferring 3D models from sketched 2D outlines. In all of these systems the underlying modeling methodology limits the complexity of models that can be created interactively. T...
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We present a novel approach for point-set implicit surface sampling that is able to rapidly distribute particles over the surface of 3D objects. Our methods benefit from the inner structure of a MPU implicit to obtain...
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This survey on control Configuration Selection (CCS) includes methods based on relative gains, gramian-based interaction measures, methods based on optimization schemes, plantwide control, and methods for the reconfig...
Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods...
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Magnetic measurement is a typical inverse problem in Biomedical field. In this kind of problem we always need to locate the positions and moments of one or more magnetic dipoles. Although using the traditional methods to solve this kind of inverse problem has all kinds of shortcomings, BPNN (Back Propagation Neural Networks) method can be used to solve this typical inverse problem fast enough for real time measurement. In the traditional BPNN method, gradient descent search method is performed for error propagation. In this paper the authors propose a new algorithm that Newton method is performed for error propagation. For the cost function is highly nonconvex in the magnetic measurement problem, the new kind of BPNN can get convergent results quickly and precisely. A simulation result for this method is also presented.
A handwritten character recognition system using the hierarchical algorithm to extract displacement between a template pattern and an input pattern is proposed. In the proposed system, the displacement can be computed...
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Faceted search is becoming the standard searching method on modern web sites. To implement a faceted search system, a well defined metadata structure for the searched items must exist. Unfortunately, online text docum...
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This paper proposes a novel approach for finding an optimized solution for the online coverage path planning in unknown environments problem employing cooperative multi robotic agents. The suggested approach lessens t...
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Sharing unstructured knowledge between peers is a must in virtual organizations. The huge number of documents available for sharing makes modern recommender systems indispensable. Recommender systems use several infor...
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ISBN:
(纸本)9789898565303
Sharing unstructured knowledge between peers is a must in virtual organizations. The huge number of documents available for sharing makes modern recommender systems indispensable. Recommender systems use several information retrieval techniques to enhance the quality of their results. Unfortunately, every peer has his/her own point of view to categorize his/her own data. The problem arises when a user tries to search for some information in his/her peers' exposed data. The seeker categories must be matched with its responders categories. In this work, we propose a way to enhance the recommendation process based on using simple implicit ontology relations. This helps in recognizing better matched categories in the exposed data. We show that this approach improves the quality of the results with an acceptable increase in computation cost.
Due to digitalization, credit card fraud has become one of the most prevalent global risks. The global economy loses billions of dollars annually due to credit card fraud. Financial institutions adopt a strategic appr...
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