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José Pinto, João R. C. Ramos, Rafael S. Costa and Rui Oliveira
In this paper, a computational framework is proposed that merges mechanistic modeling with deep neural networks obeying the Systems Biology Markup Language (SBML) standard. Over the last 20 years, the systems biology community has developed a large numbe...
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Simone Castelli and Andrea Belleri
In recent years, structural health monitoring, starting from accelerometric data, is a method which has become widely adopted. Among the available techniques, machine learning is one of the most innovative and promising, supported by the continuously inc...
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Ferenc Izsák and Taki Eddine Djebbar
We propose neural-network-based algorithms for the numerical solution of boundary-value problems for the Laplace equation. Such a numerical solution is inherently mesh-free, and in the approximation process, stochastic algorithms are employed. The chief ...
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Byoung-Gyu Song, Jong-Jin Bae and Namcheol Kang
We investigated the stochastic response of a person sitting in a driving vehicle to quantify the impact of an uncertain parameter important in controlling defect reduction in terms of ride comfort. Using CarSim software and MATLAB/Simulink, we developed ...
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Boutros El Hajj, Bruno Castanier, Franck Schoefs and Emilio Bastidas-Arteaga
The objective of this paper is to propose tools for the lifecycle management of infrastructure by showing the slow degradation processes for which inspection data are accessible, especially the data obtained from non-destructive testing (NDT) and structu...
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