Northwestern's McCormick School of Engineering

Adaptive Algorithm Aims to Reduce Kidney Discards and Improve Transplant Access

Developed by Professor Sanjay Mehrotra, the Sliding Scale AdaptiVe Expedited (SAVE) algorithm could improve organ allocation ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
Mashable

TikTok deal adds new U.S. owners. Here's what this means for users.

TikTok will officially remain in the U.S. for the foreseeable future. A new, majority U.S.-owned company had been established to continue running the popular video-sharing app in the country, and has ...
Frontiers

K-means classification of long-term global vegetation index variation

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

Can J.K. Dobbins return for the playoffs? What it would mean for Broncos’ run game

J.K. Dobbins could give Denver a big playoff boost. Matthew Stockman / Getty Images J.K. Dobbins has the kind of smile that produces other smiles. His wide grin is contagious, and as he ran for 772 ...
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, ...
Scientific Research Publishing

Wang, Q., Wang, C., Feng, Z. Y. et al. (2012). Survey of K-Means Clustering Algorithm Research. Electronic Design Engineering, 20, 21-24. (In Chinese)

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.
IEEE

Energy Optimization in Three-Dimensional Wireless Sensor Networks Using Hybrid K-Means and Mixed Integer Linear Programming

Abstract: Energy optimization is a critical challenge in wireless sensor networks (WSNs) due to its direct impact on the network lifetime. This paper proposes the use of the K-means algorithm combined ...
Scientific Research Publishing

Application of the K-Means Algorithm in the Study of Influenza Transmission Patterns ()

As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable strain on ...
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.