Abstract: Isolation Forest (IF) remains widely used for unsupervised anomaly detection in financial and cybersecurity applications, but its effectiveness is highly sensitive to the contamination ...
Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...
Abstract: Cognitive radio (CR) technology aims to address spectrum scarcity by allowing sensor nodes (SNs) to detect and opportunistically access channels that are not utilized by primary users (PUs), ...
Short-Circuit Diagnosis of Lithium-Ion Batteries Using Deep Isolation Forest in Energy Power Systems
Abstract: Short-circuit faults in lithium-ion batteries (LIBs) pose serious safety risks, including thermal runaway, making timely detection critical for the safe operation of battery systems, ...
Abstract: With the rapid growth of residential electricity consumption data, traditional anomaly detection methods suffer from low detection rates and high false alarm rates when detecting ...
Timothy Graham receives funding from the Australian Research Council (ARC) for the Discovery Project, 'Understanding and Combatting "Dark Political Communication"'. A new study published today in ...
People often blame social media algorithms that prioritize extreme content for increasing political polarization, but this effect has been difficult to prove. Only the platform owners have access to ...
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