The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

Objective To (1) develop and evaluate a machine learning model incorporating gait and physical activity to predict medial tibiofemoral cartilage worsening over 2 years in individuals without advanced ...

Background Machine learning is an artificial intelligence technique, consisting of learning from data and making predictions (such as classifications), which could provide access to an injury risk ...

Researchers have recast diffusion in multicomponent alloys as a sum of individual contributions, called 'kinosons.' Using machine learning to compute the statistical distribution of the individual ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control. AI-driven robotics and digital twins are closing the gap between simulation and ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

A study has used the power of machine learning to overcome a key challenge affecting quantum devices. For the first time, the findings reveal a way to close the 'reality gap': the difference between ...

Researchers Yue Zhao and Kang Pu from Stony Brook University—in collaboration with Ecosuite's John Gorman and Philip Court, and leveraging historical datasets provided by Ecogy Energy—have devised a ...