This paper introduces persistent homology, which is a powerful tool to characterize the
shape of data using the mathematical concept of topology. We explain the fundamental idea …

The emergence of the information age in the last few decades brought with it an explosion of
biomedical data. But with great power comes great responsibility: there is now a pressing …

An elementary question in porous media research is in regard to the relationship between
structure and function. In most fields, the porosity and permeability of porous media are …

Abstract Machine learning and high-throughput computational screening have been
valuable tools in accelerated first-principles screening for the discovery of the next …

The purpose of this study is to evaluate the accuracy for classification of hepatic tumors by
characterization of T1-weighted magnetic resonance (MR) images using two radiomics …

Abstract The Representative Elementary Volume (REV) concept, a cornerstone in porous
system heterogeneity assessment, was initially conceived to determine the minimal domain …

We have successfully proposed and demonstrated a clustering method that overcomes the
“needle-in-a-haystack problem”(finding minuscule important regions from massive spectral …

Topological data analysis is an emerging concept of data analysis for characterizing shapes.
A state-of-the-art tool in topological data analysis is persistent homology, which is expected …

This study proposes a method for predicting three-dimensional (3D) local strain distribution
under compressive deformation of as-cast Mg/LPSO two-phase alloys from 3D …

Despite considerable mechanics modeling-based efforts, accurate predictions of failure
progressions of structural materials remain challenging in real-world environments primarily …