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May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Шарль де Голль в СССР: к юбилею визита 1966 года

Вестник Пермского национального исследовательского политехнического университета. Культура, история, философия, право. 2016. № 3. С. 30–41.
Khromova E.
Language: Russian
Keywords: Президент Франциитеория конвергенциидекларация разрядки
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