WPI researchers aim to revolutionize on-site additive manufacturing by combining materials science, artificial intelligence, and 3D printing ...

Electric vehicles (EVs) that run on lithium-ion batteries have restricted range, battery deterioration and safety issues that ...

Snowflake is addressing the complexity of migrating legacy data systems into the Snowflake ecosystem with SnowConvert AI, a ...

X Engineered Materials demonstrates how AI offers a path toward more resilient, sustainable, and future-ready manufacturing.

A deep dive into the technological progress of today’s smart valves, bearings, brakes, gearboxes and actuators, and what’s ...

Lastly, sigma nought coefficients were used in semiempirical inversion models, and sigma nought coefficients and polarimetric decomposition components were used as input to machine learning methods.

Chronic pain conditions, long-lasting medical conditions characterized by persistent pain in specific areas of the body, are ...

The prediction of long-term outcomes in ischemic stroke patients may be useful in treatment decisions. Machine learning techniques are being increasingly adapted for use in the medical field because ...

In the rapidly evolving digital landscape, Artificial Intelligence (AI) stands as one of the most transformative technologies of our era.

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

Abstract: The success of deep learning has been a catalyst to solving increasingly complex machine-learning problems, which often involve multiple data modalities. We review recent advances in deep ...