Scientific Research Publishing

A Spatio-Temporal Prediction Model for Wall Turbulence Based on Hybrid Neural Networks ()

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...
The Malaysian Reserve

NetAirus Technologies Launches Panatem™ an Industry-First World-Model Artificial Intelligence Framework for Augmented Reality Headsets

SAN DIEGO, March 12, 2026 /PRNewswire/ — NetAirus Technologies – NetAirus introduces Panatem™ an Artificial Intelligence World Model framework that enables next-gen AR/VR and smart glasses to ...
University of Geneva

Clonability of anti-counterfeiting printable graphical codes: a machine learning approach

Citation O. Taran, S. Bonev, and S. Voloshynovskiy, "Clonability of anti-counterfeiting printable graphical codes: a machine learning approach," in Proc. IEEE International Conference on Acoustics, ...
IEEE

Deep Learning-Based Iterative Residual Encoder-Decoder Solution for Electromagnetic Modeling over a Broad Frequency Band

Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...
ahajournals.org

Abstract P3089: Predicting Reductions In Hemoglobin A1c From Large Dietary Datasets Using Artificial Intelligence Pipeline With Interpretable Encoder-Decoder Deep Neural Networks

Introduction: Artificial intelligence algorithms can help understand and predict the complex interactions between dietary intake and health outcomes, especially from large datasets. Precision ...
VentureBeat

AI uses Google Trends data to predict how many people will get the flu

Influenza results in over 31.4 million outpatient visits and more than 200,000 trips to emergency rooms and hospitals each year, according to estimates. The flue outbreak occurring between 2017 and ...