Data mining is a process that turns large volumes of raw data into actionable intelligence, and it's used by a wide variety ...

For decades, evidence guiding the diagnosis of postpartum haemorrhage has been constrained by traditional aggregate data ...

Cluster analysis is one of the core tasks in machine learning ... By combining the unique parallelism of quantum computing with the adaptive capabilities of classical neural networks, this method not ...

1 Department of Urology, The First Hospital of China Medical University, Shenyang, China 2 Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China Introduction: ...

COLLEGE STATION, Texas (KBTX) - With a city council vote approaching on Thursday, Priority Power CEO Brandon Schwertner is clearing the air about what he calls misconceptions about a proposed data ...

A new report on the impact of lithium mining in South America’s lithium triangle finds the rush to extract lithium in Chile’s Salar de Atacama has had a severe impact on the area’s water supplies.

ABSTRACT: Artisanal and Small-Scale Gold Mining (ASGM) operations are known to contribute significantly towards rural economic development. The operations which are widespread in about 80 countries ...

Abstract: Clustering neurodata, including electroencephalography (EEG) signals, is crucial for brain-computer interface (BCI) and neurological analysis. However, traditional methods struggle with ...

HypeFCM is a fuzzy clustering algorithm for non-Euclidean spaces, combining hyperbolic geometry with adaptive weight-based filtering in the Poincaré Disc model. It efficiently captures hierarchical ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c00731. Comparison of model complexity between scGANSL and other ...