Transfer Learning for Anomaly Detection in Rotating Machinery Using Data-Driven Key Order Estimation
Abstract: The detection of anomalous behavior of an engineered system or its components is an important task for enhancing reliability, safety, and efficiency across various engineering applications.
Abstract: Contribution: This study identifies the types of interaction that contribute to student learning with student-led tutorials (SLTs). The quality of these interactions include peer discussion, ...
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