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Spatial data clustering is an effective method to find interesting spatio-temporal clustering patterns. There are many uncertainties in sea surface temperature (SST) clustering, so clustering methods with uncertainy must be used. Type-2 fuzzy theory takes into account the uncertainty of membership grade while fuzzy C means (FCM) not. Based on the analysis(More)
In the title compound, Bi(2)B(8)O(15), the Bi atom is coordinated to five or six O atoms. The B atoms exhibit two kinds of hybridization, sp(2) and sp(3), seen in the BO(3) triangles and BO(4) tetrahedra, respectively. Three BO(3) triangles are connected to form a B(3)O(6) planar ring. All atoms in the structure are connected together to form an infinite(More)
Bias phenomenon has been a ubiquitous problem in the designs of digital True Random Number Generator (TRNG). Circuit performance can be improved with some auxiliary modules such as analog circuits and post-processing components, which usually involve the compromising of cost, compatibility, throughput, and security as well. In some cases only sub-optimal(More)
The time series remote sensing data and meteorological satellite data offer new opportunities for understanding the earth system. Spatio-temporal data clustering becomes a kind of idea tool to explore huge data space of spatio-temporal data. Because there are many uncertainties in the huge spatio-temporal data, including fuzziness and randomness, the(More)
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