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 ...
Scientific Research Publishing

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ()

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...
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 ...