The study addresses heterogeneous UAV cooperative task assignment under complex constraints via an energy learning ...

In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Houston-area parents are worried about the future of a groundbreaking program for students with learning differences and neurological conditions as the University of St. Thomas shuffles the program to ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Introduction: Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) ...

At Pueblo Elementary, a dual-language school in Scottsdale, Ariz., students, including English learners, learn core subjects in both English and Spanish. The schedule looks like this: Students in ...

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...

Abstract: Induction motors are important to the industrial sector, acting as the backbone to various processes and machinery in several fields. In fact, with the huge consumption of electrical energy ...

As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...