We present a high capacity reversible watermarking scheme using companding technique over integer DCT coefficients of image blocks. This scheme takes advantage of integer DCT coefficients' Laplacian-shape-like distribution, which permits low distortion between the watermarked image and the original one caused by the bit-shift operations of the companding technique in the embedding process. In our scheme, we choose AC coefficients in the integer DCT domain for the bit-shift operation, and therefore the capacity and the quality of the watermarked image can be adjusted by selecting different numbers of coefficients of different frequencies. To prevent overflows and underflows in the spatial domain caused by modification of the DCT coefficients, we design a block discrimination structure to find suitable blocks that can be used for embedding without overflow or underflow problems. We can also use this block discrimination structure to embed an overhead of location information of all blocks suitable for embedding. With this scheme, watermark bits can be embedded in the saved LSBs of coefficient blocks, and retrieved correctly during extraction, while the original image can be restored perfectly

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Fault diagnosis is part of the maintenance system, which can reduce maintenance costs, increase productivity, and ensure the reliability of the machine system. In the fault diagnosis system, the analysis and extraction of fault signal characteristics are very important, which directly affects the accuracy of fault diagnosis. In the paper, a fast bearing fault diagnosis method based on the ensemble empirical mode decomposition (EEMD), the moth-flame optimization algorithm based on Lévy flight (LMFO) and the naive Bayes (NB) is proposed, which combines traditional pattern recognition methods meta-heuristic search can overcome the difficulty of selecting classifier parameters while solving small sample classification under reasonable time cost. The article uses a typical rolling bearing system to test the actual performance of the method. Meanwhile, in comparison with the known algorithms and methods was also displayed in detail. The results manifest the efficiency and accuracy of signal sparse representation and fault type classification has been enhanced.

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