Jose Antonio Vilán Vilán

TL;DR: In this paper, a support vector machine (SVM) was used to estimate the state of charge (SOC) of a high capacity LiFeMnPO4 battery cell from an experimental dataset using a SVM approach.

TL;DR: This work deals with the characterization of a hyperelastic material and the subsequent validation in different stressed states using the well-known three-parameter Mooney–Rivlin model.

TL;DR: A classification method based on machine learning techniques fed with spectral information for the rock, supplied in the form of discrete values captured by a suitably parameterized spectrophotometer, suitable for automatically classifying ornamental rock is described.

TL;DR: In this article, a complex detector based on scintillation crystals, called CALIFA (CALorimeter for In-Flight detection of gamma-rays and high energy charged pArticles), is presented.

TL;DR: A methodology for automatically identifying granite varieties by processing spectral information captured by a spectrophotometer at various stages of processing using functional machine learning techniques is described.