Abstract: Fault detection and classification in electrical motors are essential for condition monitoring and predictive maintenance. This study proposes a hybrid learning framework that combines ...

Abstract: This paper introduces a universal Hybrid Model Enhancement Framework (HMEF) aimed at improving the performance of traditional machine learning models on severely imbalanced datasets.

University of Patras, Laboratory of Automation and Robotics (LAR), Department of Electrical and Computer Engineering, Patras 26504, Greece ...

John Neff is a veteran automotive journalist with over two decades of experience leading major outlets such as Autoblog and Motor1. Beginning his career as Editor-in-Chief of Speed, Style & Sound, he ...

This framework is designed for automated testing of web applications, specifically targeting the Contact List application hosted at https://thinking-tester-contact ...

BrowserManager.java: Initializes and manages browser instances (e.g., Chrome, Firefox). JSONReader.java: Parses JSON test data files for dynamic inputs ...