Abstract: With the advent of modernization, it is inevitable from various sources that there is a significant increase in the energy demand. In order to efficiently meet this demand, we need to ensure ...
Spectral Fault Receptive Fields (SFRFs) are a computational framework inspired by the concept of receptive fields in the retinal ganglion cells of primates. In condition monitoring and prognosis, ...
As the core equipment in industrial production, rotating machinery bearings play a critical role. However, traditional feature extraction algorithms for vibration signals are susceptible to noise ...
Abstract: Condition monitoring and fault detection of machine-level motors are critical in industrial environments. Traditional supervised approaches, which rely on extensive labeled fault data, are ...
HEADQUARTERS IN TOWSON. WE’VE LEARNED HUMAN ERROR, SPECIFICALLY A LACK OF COMMUNICATION IS RESPONSIBLE FOR THE POLICE RESPONSE AND NOT THE AI GUN DETECTION SYSTEM. COUNCILMAN JULIAN JONES AND IZZY ...
A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...
AWARE uses waveform signatures to detect and classify early-stage grid faults, enabling proactive intervention. The system combines physics-based models with AI/ML to interpret subtle electrical ...
1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...
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