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Mixed Reality (MR) is of increasing interest within technology- driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the importance of its utility within medical applications. A classification of medical MR has been obtained by applying an unbiased text mining method to a database of...
Face recognition is an active and challenging task in pattern recognition and computer vision application. Sparse representation based classification has been verified to be powerful for face recognition. This paper proposes the metaface block sparse bayesian learning (MBSBL) based on the framework of sparse representation. The MBS-BL combines the metaface learning and block sparse bayesian learning...
Flash memory has been widely utilized in embedded systems and consumer electronics, because of its low-power consumption, high-performance access, non-volatility, and shock resistance. A flash-memory device is different from a typical hard-disk device and requires a sophisticated management method to improve the reliable endurance and provide the efficient storage management. To improve the reliable...
The traditional Nonintrusive Load Monitoring Systems (NILMs) often employ average power consumption ex. real power and reactive power to recognize electric loads ON/OFF status. However, aiming at variable loads owning variable property in their power, voltage, and frequency, the unsteady power signatures will increase the difficulty degree of load identification. A new extraction method of power signatures...
To solve the classification problems more adaptively and accurately, this paper studies the parametric t-norm and s-norm based fuzzy classification systems, where the fuzzy decision tree provides fuzzy rules and the system sensitivity on historical data works as a feedback controller. The system sensitivity with respect to the parameters of parametric t-norm and s-norm is investigated as the vehicle...
To make up for the insufficiency of the existing methods of decision model representation in supporting multilevel model users, a kind of hierarchical description framework of decision model is proposed. This framework is made up of basic layer, building block layer and conceptual layer that supporting three kinds of model users, which are the model constructors, the DSS constructors and the decision...
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