IEEE

Semi-Supervised Anomaly Detection Using Restricted Distribution Transformation

Abstract: Anomaly detection (AD) is typically regarded as an unsupervised learning task, where the training data either do not contain any anomalous samples or contain only a few unlabeled anomalous ...
GitHub

[Xcode 26] Build time regression in Azure pipeline: 15 mins → 40+ mins with xcode@5

After upgrading from Xcode 16.1 to Xcode 26.0, the build step using xcode@5 in our Azure pipeline has experienced a significant regression. With Xcode 16.1, the build consistently completed in about ...
GitHub

aws-cloudwatch: CloudWatch Anomaly Detection Alarm not honoring Period set in Metrics

CloudWatch AnomalyDetectionAlarm uses the default 5 minutes period (or a deprecated period field in alarm props) for instead of the period we specify in metrics. Create metric as shown above and ...
C&EN

Rapid, On-Site SARS-CoV-2 Variant Detection and Differentiation Using GLAD-Pristine Silver Nanorod Arrays and Machine Learning-Enhanced SERS

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Pune, a metropolitan city in western India, where this study ...
C&EN

3D Bioprinting and Artificial Intelligence for Tumor Microenvironment Modeling: A Scoping Review of Models, Methods, and Integration Pathways

Division of Applied Oral Sciences and Community Dental Care, Faculty of Dentistry, The University of Hong Kong, Hong Kong SAR 999077, China ...
IEEE

Energy-Aware and Explainable Automated Machine Learning for Anomaly Detection in Healthcare IoT

Abstract: With the widespread adoption of Healthcare Internet of Things devices, the need for effective intrusion and anomaly detection has become pivotal in ensuring network security. However, the ...