LAMOST maps open cluster NGC 1647, linking broad main sequence to differential reddening

Using the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), astronomers have observed a nearby young open ...

Contrary to popular superstition, AES 128 is just fine in a post-quantum world

With growing focus on the existential threat quantum computing poses to some of the most crucial and widely used forms of ...
Thorax

At-risk registers integrated into primary care to stop asthma crises in the UK: cluster randomised controlled trial with economic evaluation

Background A regional trial indicated that implementing at-risk asthma registers in primary care could reduce hospital ...
MedPage Today

Strategy Reduces Inappropriate Proton Pump Inhibitor Use

Inappropriate proton pump inhibitor (PPI) use is associated with patient risks and higher healthcare costs. In a cluster ...
Frontiers

Testing network clustering algorithms with natural language processing

We propose a hybrid methodology to evaluate the alignment between structural communities inferred from interaction networks and the linguistic coherence of users' textual production in online social ...
Johns Hopkins Newsletter

Sohini Ramachandran discusses population genetics and computational clustering algorithms

Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...
Frontiers

Adaptive graph-theoretic localization of radiation sources via real-time density-aware clustering for IoT

The increasing complexity of Internet of Things and modern battlefield electromagnetic environments poses significant challenges to radiation source localization, especially under electronic ...
Scientific Research Publishing

On Prediction of Stock Return and Volatility Using Clustering Techniques: Taking an Example of Japanese Stock Market ()

Stock returns exhibit nonlinear dynamics and volatility clustering. It is well known that we cannot forecast the movements of stock prices under the condition that market is efficient. In most ...
GitHub

[ENH] Adding KModes and KPrototypes clustering algorithms

The workflow I want to enable is a seamless and native experience for clustering categorical and mixed data: This integrates categorical clustering directly into the robust and familiar scikit-learn ...
IEEE

An Enhanced Density Peak Clustering Algorithm With Dimensionality Reduction and Relative Density Normalization for High-Dimensional Duplicate Data

Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...