A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

Hooker says she wants to “eliminate prompt engineering” with AI models that intuitively adapt to varying tasks.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Adaptive systems were supposed to simplify decision-making. Instead of hard-coded rules, engineers built models that could learn from data, respond to change, and improve over time. That promise still ...

Abstract: Optimization methods often face a trade-off between the fast convergence of second-order methods and the low computational cost of first-order methods. Motivated by the need to bridge this ...

1 Department of Information Technology, Central University of Kashmir, Ganderbal, Jammu and Kashmir, India 2 Department of Computer Science and Engineering, National Institute of Technology, Srinagar, ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...