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Protein subcellular location prediction is an important problem in bioinformatics. It is highly desirable to predict a protein's subcellular location from its sequence. We propose a novel prediction model combined with locality-sensitive hashing (LSH)-based approximate nearest neighbor searching (ANNS) and a global alignment dynamic programming algorithm. LSH was used to hash map protein sequence...
This paper presents a multiple-model hypothesis testing (MMHT) approach using a representative model (RM) for detecting unknown events that may have multiple distributions. It addresses various difficulties of MMHT for composite, multivariate, nondisjoint, and mis-specified hypothesis sets with correlated observations, and decides which region of the mode space covered by the model set is better....
Joint decision and estimation (JDE) is for solving problems involving inter-dependent decision and estimation and was proposed recently based on a generalized Bayes risk. The currently available JDE algorithm processes data in a batch manner. This batch method is computationally inefficient or infeasible for many dynamic JDE problems where measurements are made available sequentially. Therefore, this...
With the research on Levenberg-Marquardt algorithm to establish a neural network model for predicting the damage of the oil and gas layers, it can protect the layers and provide effective assistance. One predicting software system designed according to this algorithm model which is operated in the Karamay Oilfield, shows the accuracy of the predicted damage can achieve favorable expectation. And it...
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