Abstract: Federated learning emerges as a key enabler toward pervasive intelligence across IoT ecosystems with provable privacy guarantees. While recent efforts on client selection have been made for ...

Abstract: Existing ac/dc power flow computations necessitate sequential convergence-oriented trial-and-error under various dc control modes, rising computational ...

A near-100-year-old debate between the theoretical physicists Albert Einstein and Niels Bohr has finally been settled—and not in the former’s favor. A team of physicists in China have realized a ...

Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...

In February 2024, without warning, YouTube deleted the account of independent British journalist Robert Inlakesh. His YouTube page featured dozens of videos, including numerous livestreams documenting ...

Abstract: Due to the increasing demand for electricity and the inherent uncertainty in power generation, finding efficient solutions to the stochastic alternating current optimal power flow (AC-OPF) ...

(Bloomberg) — Quantitative firm Y-Intercept (Hong Kong) Ltd. has gathered more than $1.7 billion in one of the most successful Asia hedge fund capital raisings in recent years, said people with ...

The slope-intercept form is a foundational concept in algebra, offering a clear and intuitive way to represent linear equations and their corresponding graphs. Mastering this form unlocks the ability ...

This paper proposes a physics-informed graph neural network (GNN) framework for scalable and efficient AC power flow-based N-2 contingency screening in large-scale power systems. Formulated as a graph ...

Two massive anvils meet in a high-stakes physics experiment from 45 meters above the ground. The impact generates incredible kinetic energy, testing the strength, hardness, and resilience of both ...