Researchers at The University of Texas MD Anderson Cancer Center have developed a new imaging method, known as RF-SIRF, that ...

A candidate profile looks clear inside a PDF, but the moment details are copied into an internal system or shared document, the structure starts breaking and small errors begin to appear. In many ...

Drew Szabo from the Centre of Excellence in Mass Spectrometry at the University of York, UK discusses his talk at HTC-19, ...

A study on visual language models explores how shared semantic frameworks improve image–text understanding across ...

A physics-constrained AI model called VLSet-AE automates feature extraction from DRIE cross-sections with 96 percent accuracy, replacing slow manual SEM analysis in MEMS fabrication.

Rising energy transmission needs are evolving pipelines into integrated, coupled Energy Transportation Systems (ETS), where ...

Abstract: In the context of advancing intelligent accounting systems within the broader field of computational methods and data processing, this study focuses on overcoming critical limitations ...

An overview of attention detection using EEG signals, which includes six steps: an experimental paradigm design, in which the task and the stimuli are defined and presented to the subjects; EEG data ...

Abstract: Feature extraction and selection in the presence of nonlinear dependencies among the data is a fundamental challenge in unsupervised learning. We propose using a Gram-Schmidt (GS) type ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In contrast, data-driven methods do not rely on fixed models or ...

ABSTRACT: This paper reviews fault identification and predictive maintenance techniques essential for the reliable operation of high-voltage power systems. The increasing integration of renewable ...