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

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

From a governance perspective, the use of explainable AI is particularly significant. Infrastructure decisions involve public ...

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

A research paper by scientists from Beihang University proposed a machine learning (ML)-driven cerebral blood flow (CBF) prediction model, featuring multimodal imaging data integration and an ...

Maintaining adequate CBF is crucial for astronauts' cognitive function during long-duration microgravity, but real-time monitoring in space is ...

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

Researchers unveiled a “physical AI” system that detects electric vehicle stability loss in real time to improve EV safety.

By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...

The group created a physical AI-based vehicle state estimation system designed to track how electric vehicles behave in real ...

Nic Johnson on Melinda Cooper, Counterrevolution. Neoliberalism as programme to head off the radical potential of the ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.