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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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Verification of Chaos in a Human Cardiovascular System Model

Regular and Chaotic Dynamics. 2025. Vol. 30. No. 2. P. 291–305.
Kuptsov P., Ishbulatov Y., Karavaev A., Stankevich N.

This study discusses an approach for estimation of the largest Lyapunov exponent for the mathematical model of the cardiovascular system. The accuracy was verified using the confidence intervals approach. The algorithm was used to investigate the effects of noises with different amplitudes and spectral compositions on the dynamics of the model. Three sets of parameters are considered, corresponding to different states of the human cardiovascular system model. It is shown that, in each case, the model exhibited chaotic dynamics. The model gave different responses to the changes in the characteristics of the noise, when using different sets of parameters. The noise had both constructive and destructive effects, depending on the parameters of the model and the noise, by, respectively, amplifying or inhibiting the chaotic dynamics of the model.

Research target: Mathematics
Language: English
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Keywords: chaosLyapunov exponentnoisecardiovascular system modelingconfidence intervalaccuracy verification
Publication based on the results of:
Математическое и радиофизическое моделирование сложной динамики живых систем для развития методов анализа экспериментальных данных (2025)
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