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News
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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Агрессивность как предиктор дефицита ощущения счастья у подростков

Вестник Московского университета МВД России. 2019. № 3. С. 258–263.
Rean A., Кошелева Е. С.

Emotionally-regulative characteristics as spontaneous and reactive aggressiveness, irritability, steadiness, shyness are analyzed in the article. These personality traits are examined as predictors of deficit of feeling of happiness among teenagers. Authors use data of global research, which was done among high school students from eight regions of Russia in 2016. Sample size was more than 7000 people, high school students. Boys are 42%, girls – 58%. Subject of our analysis are data of social questionnaire and multi-factor personal questionnaire FPI. Analysis of regression models presents, that emotionally-regulative characteristics, such as spontaneous aggressiveness, irritability and steadiness, are predictors of deficit of feeling of happiness. Aggressive and unstable teenager forms negative attitude to family values and he is less happy, than others are.

Research target: Psychology
Language: Russian
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Keywords: счастьеагрессивностьhappinessaggressivenessemotionally-regulative characteristicsэмоционально-регулятивные свойства личности
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