Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
Opinion

The 3D-Flow Architecture Breakthrough: A Universal, Scalable Digital Processor for Real-Time Pattern Recognition in High-Rate Data Streams — A Platform to Save Millions of ...

Worse, the most recent CERN implementation of the FPGA-Based Level-1 Trigger planned for the 2026-2036 decade is a 650 kW system containing an incredibly high number of transistor, 20 trillion in all, ...
Frontiers

A multi-graph convolutional network method for Alzheimer’s disease diagnosis based on multi-frequency EEG data with dual-mode connectivity

Objective: Alzheimer’s disease (AD) is mainly identified by cognitive function deterioration. Diagnosing AD at early stages poses significant challenges for both researchers and healthcare ...
IEEE

Transient Error Analysis of the LMS and RLS Algorithm for Graph Signal Estimation

Abstract: Recently, the proposal of the least mean square (LMS) and recursive least squares (RLS) algorithm for graph signal processing (GSP) provides excellent solutions for processing signals ...
EurekAlert!

Metallic glass discovery using AI-guided graph learning from Wikipedia data

A research team from the Songshan Lake Materials Laboratory has developed an AI-guided "Recommendation System" to discover new metallic glasses (MG). By combining element embeddings learned from ...
IEEE

Blind source separation method of graph signal based on dynamic weight

Blind source separation (BSS) techniques have been extensively applied within the realm of graph signal processing (GSP). The existing BSS approaches for graph signal construct a composite objective ...