Tech Xplore

New pellet-making method points to safer, more predictable high-explosive manufacturing

For decades, manufacturing plastic-bonded high explosives, or PBXs, has relied on legacy processes like slurry coating. In ...

New physics-based machine-learning method speeds search for 2D quantum materials

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional ...
Tech Xplore

New federated learning algorithm enables private, robust, and fast AI development

Three heads are better than one. Versions of this proverb are found worldwide and throughout history. Yet in the race to ...

Study compares machine learning models of raindrop formation

Raindrops form inside clouds when tiny particles of water collide and stick together, forming larger droplets that eventually ...
Visual Studio Magazine

Support Vector Regression with SGD Training Using C#

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.
The Manila Times

WiMi Explores the Application of Neural Networks in Parameter Optimization for Dual-Field Quantum Key Distribution

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ('WiMi' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, announced that they are researching the use of neural ...
Intelligent CIO

Classiq and UC Chile launch quantum AI research for biomedical image analysis

Classiq and Pontificia Universidad Católica de Chile (UC Chile) have announced a joint research project to develop hybrid quantum algorithms for biomedical image analysis – assisted by classical ...
IEEE

Accurate Strain Extraction via Kernel Extreme Learning Machine for Fiber Bragg Grating Sensor

Abstract: A novel machine learning based FBG sensing interrogation method is proposed in this paper. The method uses a Kernel Regularized Extreme Learning Machine optimized by Quantum Particle Swarm ...
IEEE

Target Tracking Using Machine Learning and Kalman Filter in Wireless Sensor Networks

Abstract: This paper describes an original method for target tracking in wireless sensor networks. The proposed method combines machine learning with a Kalman filter to estimate instantaneous ...