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

Recent global warming has driven substantial changes in terrestrial vegetation, yet long-term global patterns remain insufficiently characterized. The Normalized Difference Vegetation Index (NDVI) ...

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, ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

Abstract: For radar signal sorting based on pulse descriptors, the inherent limitations of the traditional K-means algorithm include the requirement of a predefined number of clusters, the sensitivity ...

The K-shaped economy is the latest take on the conflicting signals issued by stalled hiring, sluggish but recovering consumption and roaring financial markets. It acknowledges the gap separating ...

ABSTRACT: The use of machine learning algorithms to identify characteristics in Distributed Denial of Service (DDoS) attacks has emerged as a powerful approach in cybersecurity. DDoS attacks, which ...

A K-Means algorithm implementation involving various optimization techniques. Used to group MNIST dataset of hand-written numbers 0-9.