IEEE

Uncertainty Quantification in PEEC Method: A Physics-Informed Neural Networks-Based Polynomial Chaos Expansion

Abstract: In this article, we propose a novel machine learning approach for uncertainty quantification (UQ) within the partial equivalent element circuit (PEEC) framework, employing physics-informed ...
isixsigma on MSN

The Harada Method: Templates to Measure Long-term Goal Achievement – Part 2 of 2

The Harada method helps individuals achieve self-reliance which in turn facilitates a company’s process improvement journey.
C&EN

Theoretical Analysis of Chemical Isotope Fractionation by Orthogonal Polynomial Methods

Chapter Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
IEEE

A Fault Location Method Based on Polynomial Chaos Expansion for Non-uniform Power Transmission Lines With Uncertainty Parameters

Abstract: This article introduces a novel fault location method utilizing polynomial-chaos expansion (PCE) designed specifically for non-uniform transmission lines affected by uncertain parameters. It ...
GitHub

ClairS - a deep-learning method for long-read somatic small variant calling

ClairS is a somatic variant caller designed for paired samples and primarily ONT long-read. It uses Clair3 to eliminate germline variants. It ensembles the pileup and full-alignment models in Clair3, ...