Scientific Research Publishing

SymPcNSGA-Testing: A Hybrid Approach to Mitigate Path Explosion in Software Programs ()

To address these shortcomings, we introduce SymPcNSGA-Testing (Symbolic execution, Path clustering and NSGA-II Testing), a ...
IEEE

Efficient Hardware Architecture Design of K-Means Clustering Algorithm for AV1 Palette Mode Coding

Abstract: The palette mode is a specialized coding tool for coding screen content video in Alliance for Open Media Video 1 (AV1), and K-means clustering is a necessary step in the palette mode.
PRIMETIMER on MSN

Why are astronomers studying brown dwarfs in the RCW 36 nebula? VLT image shares a cluster of faint objects

Astronomers using the Very Large Telescope study faint brown dwarfs in the RCW 36 nebula to understand substellar populations and the initial mass function in a young massive cluster.
PsyPost

American issue polarization surged after 2008 as the left moved further left

American political divisions surged between 2008 and 2020, but this trend is not happening globally. A new study in Royal Society Open Science uses machine learning to reveal how cultural issues drive ...
AZoM on MSN

Imaging silicon defects using Raman and PL multivariate imaging

PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
C&EN

Illuminating the Interface of Blocc Chemistry and Data Science: An Introduction to K-Nearest Neighbor Analysis and K-Medoids Clustering

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The discovery of functional small molecules, chemical matter ...
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 ...
IEEE

Examining the Impact of Distance-Based Similarity Metrics on the Performance of Projected Clustering Algorithm for Fingerprint Database Clustering

Abstract: The projected clustering (PROCLUS) algorithm is a subspace clustering algorithm based on the k-medoids clustering approach. It is designed to address the challenges of irrelevant received ...