Abstract: The present application relates to a method for measuring the similarity of images/image blocks, which comprises: S1: acquiring two three-dimensional airspace images V and W; S2: decomposing the images V and W to obtain a plurality of sub-bands; S3: calculating a Laplacian probability corresponding to each high-frequency sub-band of V and W, weighting the high-frequency sub-hand; S4: marking two image blocks as X and Y, taking out data blocks corresponding to the image blocks X and Y, and calculating the statistics of the data blocks; S5: calculating the similarities of X and Y in each channel of each sub-band according to the statistics of the data blocks; S6: calculating an average value of the similarities of X and Y in each channel of each sub-band, and taking the average value as the similarity between X and Y.

Abstract: The present application relates to a method for measuring the similarity of images/image blocks, which comprises: S1: acquiring two three-dimensional airspace images V and W; S2: decomposing the images V and W to obtain a plurality of sub-bands; S3: calculating a Laplacian probability corresponding to each high-frequency sub-band of V and W, weighting the high-frequency sub-hand; S4: marking two image blocks as X and Y, taking out data blocks corresponding to the image blocks X and Y, and calculating the statistics of the data blocks; S5: calculating the similarities of X and Yin each channel of each sub-band according to the statistics of the data blocks; S6: calculating an average value of the similarities of X and Y in each channel of each sub-band, and taking the average value as the similarity between X and Y.

Abstract: The present invention discloses a construction method for heuristic metabolic co-expression network and the system thereof. Based on the max-dependent criteria, the present invention treats the characterized multivariate mutual information of a plurality of metabolites as mutual function value, and applies an optimization searching for the best feature subset, with a heuristics computational intelligence multimodal optimization algorithm. And by running the optimization process in a plurality of times, combining and studying the results in each time running, a co-expression network structure is built. Finally, a threshold for segmentations is calculated through probability models, and an exact and stable metabolic co-expression network is obtained.

Abstract: The present invention discloses a metabolic mass spectrometry screening method for diseases based on deep learning and the system thereof. The present invention is based on the prior metabolic mass spectrometry database, and by extracting and integrating specific types of metabolic mass spectrometry samples (such as a disease), which are applied to train a deep learning network, and make it be able to determinate a plurality of types or states simultaneously. Then applying the specific network into screening a real input metabolic mass spectrometry.

Abstract: The present invention discloses a data compression system for DNA sequence, which is a lossless compression system for DNA sequence data, based on the MA-ARV codebook, which is able to search the approximate repeat fragment of the MA-ARV code vector in the whole sequence, and use a heuristic optimization algorithm of memetic algorithm to optimize the construction process of the compressed codebook, so as to fully use the repeat nature of DNA sequence data, and eliminate the redundancy effectively.