Abstract: This article proposes a graphical method to evaluate the feasibility of intentional islanding of distributed synchronous generators. The approach is based on the combination of the ...

A research team from the Aerospace Information Research Institute of the Chinese Academy of Sciences (AIRCAS) has developed a new method combining deep learning with physical radiative transfer ...

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under ...

In this video, we explain vectors and derivatives as essential math methods used in physics, showing how they describe motion, direction, and change. Clear explanations and examples help connect ...

In this video, we provide an overview and summary of Chapter 1 from Introduction to Electrodynamics by David J. Griffiths. We cover the basics of electrostatics, vector calculus, and the fundamental ...

Researchers created scalable quantum circuits capable of simulating fundamental nuclear physics on more than 100 qubits. These circuits efficiently prepare complex initial states that classical ...

Decadal surveys of the National Academies of Sciences, Engineering, and Medicine bring together leading experts to identify a field’s most compelling science challenges and frontiers for the next ...

A new technical paper titled “Phase-Change Memory for In-Memory Computing” was published by researchers at IBM Research-Europe. “We review the current state of phase-change materials, PCM device ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...