Devdiscourse

Food industry turns to machine learning to boost efficiency, cut waste and improve quality

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
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 ...
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 ...
Chromatography Online

A Novel Machine Learning Method for Predicting Retention Time of Small Molecule Pharmaceutical Compounds Across Reversed-phase HPLC Columns

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
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, ...