Designing random nanofiber networks, optimized for strength and toughness

In nature, random fiber networks such as some of the tissues in the human body, are strong and tough with the ability to hold ...
The Malaysian Reserve

MicroCloud Hologram Inc. Quantum Computing-Driven Multi-Class Classification Model Demonstrates Superior Performance

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, introduced a significant development—Multi-Class Quantum Convolutional Neural Network (Quantum ...
TMCnet

WiMi Launches Quantum-Assisted Unsupervised Data Clustering Technology Based on Neural Networks

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the launch of a disruptive technology—quantum ...

The $100M OpenAI partnership is nice, but Databricks' real breakthrough makes AI up to 90x cheaper

Databricks shows enterprises how to get frontier AI performance for 90x less cost through breakthrough automated prompt ...
Scientific Research Publishing

A New Method to Predict the Mechanical Behavior for a Family of Composite Materials ()

Mînzu, V. and Arama, I. (2025) A New Method to Predict the Mechanical Behavior for a Family of Composite Materials. Journal ...
pv magazine International

Optimum tilt angle for PV systems ranging from 0° to 90°

A Slovak research team has developed a mathematical model for determining the optimum tilt angle of a solar system ranging from 0° to 90°. Their framework was tested on an experimental setup in ...
TMCnet

WiMi Has Developed a Scalable Quantum Neural Network (SQNN) Technology Based on Multi-quantum-device Collaborative Computing

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of a Scalable Quantum Neural ...
IEEE

AI-Based Graph Neural Networks for Predictive Energy Optimization in IoT-Enabled Consumer Electronics

Abstract: This study presents an innovative framework leveraging Graph Neural Networks (GNNs) integrated with reinforcement learning (RL) and meta-learning for predictive energy optimization in ...
IEEE

Graph Neural Network Based Energy-Efficient Optimization for RIS-Assisted Wireless Networks

Abstract: Reconfigurable Intelligent Surfaces (RISs) are recognized as a promising solution for enhancing the energy efficiency (EE) of next-generation wireless networks, attributable to their low ...