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, ...

Alarm bells rang for the special master in the case, he said, when he used Westlaw to verify details in the briefing—only to discover, he said, that some of the quotations and court decisions cited by ...

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: The study utilizes a K-Means clustering analysis model to analyze the learning behavior data generated by online learners on an online learning platform ...

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 ...

This project consists in the implementation of the K-Means and Mini-Batch K-Means clustering algorithms. This is not to be considered as the final and most efficient algorithm implementation as the ...