Budoen, A. , Zhang, M. and Jr., L. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, 1-22. doi: ...

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory, Machine Learning: Science and Technology (2024). DOI: 10.1088/2632-2153/ad7ad6 S. Goldenberg et al, Data-driven ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Get Instant Summarized Text (Gist) Unsupervised machine learning identified three distinct clusters of social and economic factors associated with elevated suicide risk across US counties. These ...

a domain where conventional machine learning approaches fail. Unlike many previous methods, the model is trained on real-world data instead of simulations. “It sets a precedent for using real, scarce ...

A University of Cincinnati study found machine learning models can aid in the automation and detection ... using one voltage reading per 10 seconds, compared to the typical method of collecting ...

DDoS attacks ... Traditional methods of detection and mitigation often struggle to keep pace with the evolving nature of these attacks. Machine learning, with its ability to analyze vast amounts of ...

DDoS attacks have ... posing challenges for detection using traditional methods. These challenges highlight the importance of reliable detection and prevention measures. This paper introduces a novel ...