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 ...

Michael O. Lawanson, a Nigerian data scientist at the University of Arkansas, United States, is at the forefront of global ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

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

Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.

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 ...