Railway Systems has recently been involved in several demonstrator projects of its zentrak portfolio across Europe.

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

Robot legs developed by SUSTech researchers reduce walking effort by 35% and cut foot pressure in half when carrying heavy loads up to 44 pounds.

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

“Industrial AI must start with trusted data,” said Steve Mason, COO of Canary Labs. “Our historian has long been the foundation for operational visibility. By natively integrating with SORBA.ai’ SORBA ...

At New America, our work spans across five issue areas—each essential to building a nation and a world where everyone can thrive. For over 25 years, New America’s insights and policy solutions have ...

When legislative, judicial and regulatory functions converge in technical infrastructure controlled by few actors, the system enhances those actors' power.

However, there is still no consensus on the most effective algorithm or model. Objective: To evaluate and compare the performance of existing GDM prediction models constructed using AI algorithms and ...