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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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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.
May 25, 2026
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?

Modeling Intermittent Protest Campaigns

Ch. 1. P. 1–5.
Petrov A., Sergey Zheglov, Akhremenko A. S.

The paper studies protest campaigns consisting of both days with protest activity and days without activity. A dynamical agent-based model has been constructed. Numerical experiments showed that repression reduces the surviving probability of the campaign, but moderate repression may increase the turnout for the campaigns that survive. 

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Keywords: математическое моделированиечисленный эксперимент mathematical modelполитический протестагентное моделированиеnumerical experimentspolitical protestagent-based model

In book

16th International Conference Management of large-scale system development (MLSD)
IEEE, 2023.
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