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Wenhao Sun, Yidong Zou, Yunhe Wang, Boyi Xiao, Haichuan Zhang and Zhihuai Xiao
In the practical production environment, the complexity and variability of hydroelectric units often result in a need for more fault data, leading to inadequate accuracy in fault identification for data-driven intelligent diagnostic models. To address th...
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Alessandro Massaro
In the proposed paper, an artificial neural network (ANN) algorithm is applied to predict the electronic circuit outputs of voltage signals in Industry 4.0/5.0 scenarios. This approach is suitable to predict possible uncorrected behavior of control circu...
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Dongeun Kim and Yoon Hyeok Bae
Generally, new and renewable energy systems generate electricity by installing and operating multiple modules simultaneously. In the Republic of Korea, recent studies and developments have focused on asymmetric wave energy converters (hereafter referred ...
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Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
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Monica Fira, Hariton-Nicolae Costin and Liviu Goras
We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people?s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediat...
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