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 ...

The PV Fault Detection System is an advanced real-time simulation and monitoring solution for photovoltaic panels in microgrids. This project combines Digital Twin technology with ...

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 ...

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 ...

Discriminant-type analyses arise from the need to classify samples based on their measured characteristics (variables), usually with respect to some observable property. In the case of samples that ...

Poststroke recovery depends on multiple factors and varies greatly across individuals. Using machine learning models, this study investigated the independent and complementary prognostic role of ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Equivalent circulating density (ECD) is an important parameter ...

Your browser does not support the audio element. Let’s take a closer look at different C++ libraries that can become useful to every data scientist for traditional ...