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

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

The key idea behind our framework is that life produces molecules with purpose, while nonliving chemistry does not. Cells ...

MIT researchers have designed a printable aluminum alloy that’s five times stronger than cast aluminum and holds up at ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...

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

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

Machine learning (ML) is rapidly emerging as a powerful tool to improve the safety, reliability, and long-term performance of marine structures exposed to harsh ocean environments. This study presents ...

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 ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

A research team led by Professor Kanghyun Nam from the Department of Robotics and Mechanical Engineering at DGIST has ...