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In this paper, we propose a novel high resolution remote sensing image change detection algorithm based on image fusion and fuzzy clustering models. The original images are fused based on the Wavelet to get the comprehensive differencing map which reserves enough variation characteristics as well as reducing the noise. The idea of modifying traditional clustering algorithms will enhance the final result of the change map. This method is able to achieve the higher detection accuracy based on the revised fuzzy clustering algorithm and could obtain better differencing map with integration of image fusion. Experiments on real images point out the effectiveness and feasibility of the proposed methodology compared with other state-of-the-art ones visually and numerically.

The related theories of Web and Web mining in semantic are concluded and analyzed in this paper. The description on RDF resource is analyzed on the semantic step, and the clustering method for RDFMS data clustering based on Semantic distance is proposed, with the detailed description for the algorithm and examples. With the discussion on the data mining techniques for semantic Web mining, the design on inductive logic programming is proposed for the data mining techniques that are suitable to the semantic Web. Additionally, how to apply to the description of the algorithm is given through the specific examples to verify the feasibility for the data mining in the semantic Web environment.

A 3.3V 8Gb NAND flash memory with a synchronous double-data-rate (DDR) interface is designed and fabricated using 3M 50nm technology to meet the requirements of the markets. This paper achieves a NAND flash program throughput of 100 MB/s with quad-plane operation, which is 5x previously reported. I/O read/write throughput of 200MB/s is achieved using a newly developed DDR interface and data path. The chip features a dual interface, supporting both the newly developed synchronous DDR interface as well as the standard, asynchronous NAND flash interface.