A study led by researchers at the Institute for Bioengineering of Catalonia (IBEC), in collaboration with the Proteomics ...

Abstract: A stochastic demand dynamic traffic model is presented to predict some traffic variables, such as link travel times, link flows, or link densities, and their time evolution in real networks.

Abstract: Uncertainty analyses have been considered critical analysis methods for identifying the risks in reliability evaluations. However, with multi-phase, multi-state, and repairable features, ...

PyHGF is a Python library for creating and manipulating dynamic probabilistic networks for predictive coding. These networks approximate Bayesian inference by optimizing beliefs through the diffusion ...

Implementation of BANSAC, a new guided sampling process for RANSAC. Previous methods either assume no prior information about the inlier/outlier classification of data points or use some previously ...

System identification learns models of dynamical systems from input–output measurements. Estimated models should generalize by predicting system’s output responses to new, previously unseen inputs.

Quantifying resilience of socio-ecological systems (SES) can be invaluable to delineate management strategies of natural resources and aid the resolution of socio-environmental conflicts. However, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The early stages of the drug design process involve identifying compounds with ...