The role of machine learning and deep learning in wildfire prediction remains limited by geographic concentration, uneven ...

Yeshwanth Macha developed explainable AI models improving insurance fraud detection accuracy, transparency, compliance and ...

Professor Kyungwho Choi's team of the School of Mechanical Engineering at Sungkyunkwan University, in collaboration with ...

Most public talk about AI focuses on large language models and flashy generative tools. But honestly, the most dependable ...

Proton exchange membrane fuel cells (PEMFCs) are promising for zero-emission vehicles, but their sub-zero start-up capability remains a major hurdle. Freezing of product water inside the membrane ...

The two-stage AI framework for geopolymer concrete mix design significantly improves predictive accuracy, facilitating the shift to low-carbon construction.

The team from Bluesky has built another app — and this time, it’s not a social network but an AI assistant that allows you to design your own algorithm, create custom feeds, and, one day, vibe-code ...

ABSTRACT: Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often ...

The challenge for modern marketers is not whether to trust the data, but how to translate it into work that still feels human. Modern marketing has shifted from simple messaging to utilizing real-time ...

We propose a hybrid approach that combines the time-series forecasting model and the ensemble learning algorithm to generate investor views in the Black-Litterman model. Specifically, we first use ...

From litigation to federal prisons to criminal investigations, artificial intelligence appears to have touched nearly every corner of the Department of Justice in the past year. Just two years ago, ...