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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.
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Определение источников и механизмов государственного финансирования инновационных проектов

С. 171–176.
Lipatnikov V. S.

In the article the main features of state financing of innovative projects are examined. Major problems faced in defining of sources of financing are stated. Also suggestions on the main mechanisms of state financing of innovative projects are offered.

Language: Russian
Full text
Keywords: государственное финансированиеинновационный проектinnovative projectисточник финансированиямеханизм финансированияstate financingsource of financingmechanism of financing

In book

Всероссийский научно-практический симпозиум молодых ученых и специалистов «Экономика России: реальность и вызовы времени». 21 декабря 2012 года: Материалы симпозиума
Всероссийский научно-практический симпозиум молодых ученых и специалистов «Экономика России: реальность и вызовы времени». 21 декабря 2012 года: Материалы симпозиума
СПб.: Изд-во ИМЦ «НВШ-СПб», 2012.
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