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Mingfeng Huang, Jianping Sun, Kang Cai and Qiang Li
Although widely used in various fields due to its powerful capability of signal processing, empirical mode decomposition has to decompose signals separately, which limits its application for multivariate data such as the structural monitoring data record...
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Ang Su, Liang Zhang, Xuefeng Zhang, Shaoqing Zhang, Zhao Liu, Caili Liu and Anmin Zhang
Due to the model and sampling errors of the finite ensemble, the background ensemble spread becomes small and the error covariance is underestimated during filtering for data assimilation. Because of the constraint of computational resources, it is diffi...
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Hanen Mhamdi, Jérémie Bourdon, Abdelhalim Larhlimi and Mourad Elloumi
The integration of high-throughput data to build predictive computational models of cellular metabolism is a major challenge of systems biology. These models are needed to predict cellular responses to genetic and environmental perturbations. Typically, ...
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Shinyoung Kwag, YongHee Ryu and Bu-Seog Ju
In the event of an earthquake, it is essential to accurately assess the seismic fragility of piping systems to ensure the continued safety of society. When evaluating the seismic fragility of a piping system, which is generally a secondary structural sys...
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Jordi Mas-Soler, Antonio Souto-Iglesias and Alexandre N. Simos
An innovative Bayesian motion-based wave inference method is derived and assessed in this work. The evaluation of the accuracy of the proposed prior distribution has been carried out using the results obtained during a dedicated experimental campaign wit...
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