Abstract: This paper presents a comprehensive fault classification framework for three-phase Induction Motors (IMs) using a novel Grey Wolf Optimization-enhanced Support Vector Machine (GWO-SVM) ...
Abstract: The purpose of (IDS) is to protect digital data from cyber threats. By quickly distinguishing and reacting to risks, IDS minimizes possible damage to systems and data. However, it can suffer ...
This project investigates the application of Deep Neural Networks (DNNs) for automated fault classification and fault location in power transmission lines. Using data generated from a simulated 4-bus ...
Department of Chemical and Biomolecular Engineering, University of Connecticut, Storrs, Connecticut 06269, United States Center for Clean Energy Engineering, University of Connecticut, Storrs, ...
Monitoring nociception, the flow of information associated with harmful stimuli through the nervous system even during unconsciousness, is critical for proper anesthesia care during surgery. Currently ...
Detection and analysis of spontaneous synaptic events is an extremely common task in many neuroscience research labs. Various algorithms and tools have been developed over the years to improve the ...
Ovarian cancer, a deadly female reproductive system disease, is a significant challenge in medical research due to its notorious lethality. Addressing ovarian cancer in the current medical landscape ...
This repository hosts the official implementation of the paper "On the Transferability of Learning Models for Semantic Segmentation for Remote Sensing Data." Recent deep learning-based methods ...
aQuantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA bEmerging Pathogens Institute, University of Florida, Gainesville, ...
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