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In the on-line monitoring for the fault of rolling bearing, we have no information about the cluster number of the obtained data signal, which cause great challenges for on-line fault diagnosis when using clustering algorithms. In this paper, we extract three features of the vibration signals of rolling bearings as the parameters in time-domain, and then multi-scale possibilistic clustering (MPCM)...
With the aim to improve the performance of feature matching, we present an unsupervised approach for adaptive description selection in the space of homographies. Inspired by the observation that the homographies of correct feature correspondences vary smoothly along the spatial domain, our approach stands on the unsupervised nature of feature matching, and can choose a good descriptor locally for...
We present a novel approach to boost image matching performance by fusing multiple local descriptors in the homography space. Traditional matching methods find correspondences based on a single descriptor and the performance becomes unstable due to the goodness of the chosen descriptor To address this problem, our method uses multiple descriptors and select a good descriptor for matching each feature...
This paper presents a novel mutual identity authentication scheme which can be applied securely in Internet of Things. Based on secure hash algorithm(SHA), feature extraction and elliptic curve cryptography(ECC), we propose an asymmetric mutual authentication scheme between the platform and the terminal node, which imposes light computation and communication cost, through security analysis it is also...
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