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Utilizing multivariable data, the motion state of complex nonlinear systems could be well described by phase space reconstruction theory. In this paper, a novel fusion data algorithm is proposed via local weighted zero-order prediction algorithm. For effectively reserving the motion information of original system, the weighted coefficients are rationally designed Euclidean distance. Experimental results...
Protein structure prediction is a long standing problem in the filed of structural bioinformatics. To address this problem, on the basis of Monte Carlo (MC), a double estimation of distribution guided sampling algorithm for de-novo protein structure prediction (DED) is proposed. Serval MC trajectories are launched simultaneously at the begining of DED. And two probability distribution are designed...
Quantifying team dynamics and predicting team performance in social physics have become increasingly important research problems. In this paper, the multi-model dataset of interaction networks about cooperating teams is collected through wearable sensing technologies, that allows gathering information on team performance and dynamics. Based on this dataset, the predictive power of team discussion...
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