Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Abstract: This paper addresses the demand for automatic electrocardiogram (ECG) arrhythmia detection in clinical settings by proposing an Adaptive Tree Support Vector Machine (AT-SVM) algorithm, which ...
Background: Permanent magnet synchronous motor (PMSM) may develop faults during long-term operation, affecting the stability and safety of the drive system. Objective: This paper aims to identify the ...
Space vector modulation (SVM) is a sophisticated digital control technique that improves three-phase inverter performance over traditional sinusoidal PWM (SPWM). SVM’s higher DC bus utilization ...
This project demonstrates the application of various machine learning algorithms for heart disease classification. By comparing the performance of SVM, MLP, and Random Forest models, we can determine ...
Abstract: Power transformers, as oil-immersed equipment, are primarily diagnosed using dissolved gas analysis (DGA), a widely recognized and effective fault detection method. Over time, numerous ...
As modern manufacturing increasingly relies on artificial intelligence (AI), automation, and real-time data processing, the need for faster and more energy-efficient computing systems has never been ...
Google’s June 2025 Core Update just finished. What’s notable is that while some say it was a big update, it didn’t feel disruptive, indicating that the changes may have been more subtle than game ...
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