IEEE

Dynamic Machine Learning Framework for Secure, Ultra-Reliable, and Energy-Efficient Open RAN Systems

Abstract: This paper proposes a machine learning (ML)-driven framework for Open Radio Access Networks (ORAN) to address security, Ultra-Reliable Low-Latency Communication (URLLC), and energy ...
TMCnet

CompuChild Expands Its Suite of Artificial Intelligence and Machine Learning Classes for Children

DUBLIN, Calif., Jan. 16, 2026 /PRNewswire/ -- CompuChild, a children's education franchise business dedicated to offering after-school enrichment programs across the United States and Canada, today ...
Game Rant

I’ve Played Over 80 Hours of Each Diablo 4 Class, and Here’s My Official Ranking

Drew Swanson is a Features Article Editor from the Pacific Northwest of the United States. Being a gamer all his life and enjoying everything from ARPGs like Diablo to JRPGs like Pokemon and Persona, ...
Scientific Research Publishing

Diabetes Diagnosis Using Machine Learning: A SVM-Based Approach ()

1 Faculty of Mathematics and Computer Science,, Felix Houphouët-Boigny University, Abidjan, Côte d’Ivoire. 2 Institute for Mathematical Research (IRMA), Abidjan, Côte d’Ivoire. 3 Higher Teacher ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
GitHub

Lung Cancer Prediction Project

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...
Scientific Research Publishing

Erfani, S.M., Rajasegarar, S., Karunasekera, S. and Leckie, C. (2016) High-Dimensional and Large-Scale Anomaly Detection Using a Linear One-Class SVM with Deep Learning ...

ABSTRACT: Industrial appearance anomaly detection (AD) focuses on accurately identifying and locating abnormal regions in images. However, due to issues such as scarce abnormal samples, complex ...
labs.sogeti

MACHINE LEARNING ALGORITHMS FOR TEST AUTOMATION

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...