Abstract: In this paper, an improved K-means clustering algorithm, EGLK-Means, is proposed, which optimizes the clustering results by enhancing global and local information. The traditional K-means ...

️ An intelligent system that takes a document and classifies different writing styles within the document using stylometric techniques.

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, ...

Rocky high steep slopes are among the most dangerous disaster-causing geological bodies in large-scale engineering projects, like water conservancy and hydropower projects, railway tunnels, and metal ...

1 Department of Applied Sciences, Intelligent Asset Reliability Centre, Institute of Emerging Digital Technologies, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia 2 Bursa Malaysia Berhad, ...

As the U.S. rolls back aid and protections, these contemporary artists are making the art world, at least, more open. By Julia Halperin Photographs by Melody Melamed ON A SPRING afternoon in 1991, the ...

Abstract: The paper presents a detailed research study of the k-means clustering algorithm to be used for image compression tasks, where the RGB values of the colors are considered XYZ coordinates of ...

ABSTRACT: Domaining is a crucial process in geostatistics, particularly when significant spatial variations are observed within a site, as these variations can significantly affect the outcomes of ...

A high-performance Parallel K-Means Clustering algorithm implemented in C++ with OpenMP for parallelization. This project demonstrates the use of advanced clustering techniques with efficient ...

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 ...