New method separates brain signals to show how complex actions are organized

A new Northwestern Medicine study has introduced a novel machine learning method for analyzing how the brain organizes ...
Tech Xplore

Self-driving cars: Near-miss driving data can expedite AV algorithm training

The safety performance of autonomous vehicle (AV) algorithms is boosted by 90% using simulation data that better incorporates ...

Demystifying the molecular mechanisms of general anesthesia

Researchers at Weill Cornell Medicine and Birkbeck, University of London, have identified a site where a commonly used ...

Tiny worms reveal backup circuits that keep survival reflexes from failing

A research team led by Professor Chaogu Zheng from the School of Biological Sciences at the University of Hong Kong (HKU), in ...
technologynetworks

AI for GWAS and Population Genomics: Improving Power, Prioritization, and Interpretation

Genome-wide association studies (GWAS) have catalogued hundreds of thousands of genetic variants linked to complex human traits and diseases, with more than 625,000 variant-trait associations across ...
PNAS

Correction for Anand et al., Convolutional neural networks outperform other presence-only species distribution modeling algorithms

The authors note that, due to a production error, Figures 1–4 appeared in the incorrect order. Figure 1 should appear as Figure 2, Figure 2 should appear as Figure 3, Figure 3 should appear as Figure ...
AlphaGalileo

Breakthrough in Efficient GNN Training Architecture: Research Team Proposes Hardware-Algorithm Co-Optimization Solution

A Chinese research team has achieved a breakthrough in improving the training efficiency of Graph Neural Networks (GNNs). They introduced an ...
IEEE

Multiscale Convolutional Neural Network With Self-Attention Mechanism and Soft Thresholding for Industrial Process Fault Diagnosis

Abstract: This article proposes a multiscale convolutional neural network (MSCNN)-based fault diagnosis method (AM-MAST) using a self-attention mechanism and soft thresholding. It aims to improve the ...
Scientific Research Publishing

Viterbi, A. (1967) Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm. IEEE Transactions on Information Theory, 13, 260-269.

ABSTRACT: A new nano-based architectural design of multiple-stream convolutional homeomorphic error-control coding will be conducted, and a corresponding hierarchical implementation of important class ...