AI captures particle accelerator behavior to optimize machine performance

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 ...
IEEE

Memristor-Based Feature Recall Neural Network Circuit With Temporal Differentiation of Emotion and its Application in Parts Inspection

Abstract: From the perspective of time, the generation of emotion has not only emotional generalization but also emotional differentiation. Most studies of emotional systems only consider the present ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
IEEE

Coupled Physics-Informed Neural Network for Multi-Physics Modeling in Additive Friction Stir Deposition

Abstract: Additive Friction Stir Deposition (AFSD) is an emerging metal additive manufacturing process gaining increased attention due to its solid-state processing nature, resulting in desirable ...
PsyPost on MSN

What brain scans reveal about people who move more

New research indicates that physical movement may help preserve the ability to recall numbers over short periods by ...
GitHub

Neural-Network-with-Financial-Time-Series-Data

An evnet driven model that uses financial time series data with New York Times information to form a LSTM recurrent neural network. There are 3 models. The first 2 models are based on price and volume ...