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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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Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Макроэкономическая модель стресс тестирование с использованием VAR подхода

С. 25–29.
Khasyanova S. Y., Малов Д. Н.
Language: Russian
Keywords: банковский сектордостаточность капиталамакроэкономические индикаторыметод VaRстресс тестирование

In book

Современные проблемы в области экономики, менеджмента, бизнес-информатики, юриспруденции социально-гуманитарных наук: материалы XI научно-практической конференции студентов и преподавателей НИУ ВШЭ - Нижний Новгород
Современные проблемы в области экономики, менеджмента, бизнес-информатики, юриспруденции социально-гуманитарных наук: материалы XI научно-практической конференции студентов и преподавателей НИУ ВШЭ - Нижний Новгород
Н. Новгород: Нижегородский филиал НИУ ВШЭ, 2013.
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