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Wenkuan Huang, Hongbin Chen and Qiyang Zhao
The main research focus of this paper is to explore the use of the cycle-generative adversarial network (GAN) method to address the inter-turn fault issue in permanent magnet-synchronous motors (PMSMs). Specifically, this study aims to overcome the chall...
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Chan-Sol Park, Soo-Jin Ahn, Yeong-Bae Lee and Chang-Ki Kang
In ultrasound diagnostics, acoustic absorbers block unwanted acoustic energy or prevent the reception of echo signals from structures outside the target area. Non-metallic absorbers provide a low-echoic signal that is suitable for observing the anatomy o...
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Fabi Prezja, Leevi Annala, Sampsa Kiiskinen and Timo Ojala
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dataset...
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Jaehan Jeon and Gerasimos Theotokatos
Digital twins (DTs) are gradually employed in the maritime industry to represent the physical systems and generate datasets, among others. However, the trustworthiness of both the digital twins and datasets must be assured. This study aims at developing ...
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Norah Fahd Alhussainan, Belgacem Ben Youssef and Mohamed Maher Ben Ismail
Brain tumor diagnosis traditionally relies on the manual examination of magnetic resonance images (MRIs), a process that is prone to human error and is also time consuming. Recent advancements leverage machine learning models to categorize tumors, such a...
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