A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

Real-world deployments show 40% test cycle efficiency improvement, 50% faster regression testing, and 36% infrastructure cost savings.

Fragments of DNA from long-extinct human relatives still circulate in modern genomes, and in some cases they do more than ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...

Dinosaur footprints are iconic fossils, but it is challenging to identify their makers. This is illustrated by a long-standing debate about whether some footprints from the Late Triassic-Early ...

According to Sawyer Merritt, Tesla's Full Self-Driving (FSD) V14 system, which relies solely on camera-based AI perception, demonstrated strong performance in severe fog conditions. In a recent ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

The semiconductor industry is increasingly turning to artificial intelligence as the solution for increasing complexity in test analytics, hoping algorithms can tame the growing flood of production ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...