EurekAlert!

Beyond small data limitations: Transfer learning-enabled framework for predicting mechanical properties of aluminum matrix composites

A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Frontiers

Digital innovations in bioprocess optimization: The role of AI, machine learning, and digital twins

Bioprocess modeling is undergoing a transformative phase with the advent of digital technologies like artificial intelligence (AI) and machine learning ...
Machine Design

Q&A: Applying AI and Digital Twins to Improve Machine Design and Manufacturing Processes

FLO, offers practical guidance on leveraging artificial intelligence, digital twins and streamlined workflows to improve ...
YouTube on MSN

Adam M Root: How to use machine learning to reduce costs and boost output

Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...
TMCnet

Stony Brook University Develops Machine Learning Models that Predict PV System Underperformance on Heterogeneous Portfolios

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...

New machine-learning models capture the rapid evolution of antimicrobial resistance

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...