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) ...
Euclidean Minimum Spanning Trees using single-, sesqui-, and dual-tree Borůvka algorithms, which are quite fast in spaces of low intrinsic dimensionality, minimum spanning trees with respect to mutual ...
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 ...
Abstract: This study explores the implementation of lightweight binary classification algorithms on low-cost Field-Programmable Gate Arrays (FPGAs) for medical image analysis. Recognizing the growing ...
1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...
Introduction: We compare the use of two machine learning (ML) algorithms: random forests (RFs) and k-means clustering (KMC), for classification of presence or absence of amyloid deposition using 18 ...
Intrinsically disordered proteins lack a stable tertiary structure and form dynamic conformational ensembles due to their characteristic physicochemical properties and amino acid composition. They are ...
The Unified Huntington's Disease Rating Scale (UHDRS) is the primary clinical assessment tool for rating motor function in patients with Huntington's disease (HD). However, the UHDRS and similar ...
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