Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

While sensing technologies have advanced rapidly, the study identifies data fragmentation as one of the most persistent ...

A new study shows that machine-learning models can accurately predict daily crop transpiration using direct plant ...

While the potential benefits of AI in obesity prevention are substantial, the study devotes significant attention to ...

Artificial intelligence has become both the weapon and the shield in today’s cyber battlefield. From self-learning malware to ...

Droughts are lasting longer in Australia, particularly in some of our most populated regions, UNSW scientists have shown.

Soil microbial communities play a crucial role in maintaining multiple soil functions in terrestrial ecosystems. However, evidence linking soil ...

"Range anxiety" remains one of the major issues of electric vehicles (EVs). Most of the existing range prediction ...