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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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Masculinity Constructing in Dagestani Male Youth Communities

Europe-Asia Studies. 2021.
Sviatoslav Poliakov
In press

Drawing on 60 in-depth interviews with adolescents and young men in Dagestan, I examine the construction of masculinity in the context of a postcolonial and peripheral society undergoing a transformation associated with deindustrialization, urbanization, and globalization. I focus on three male communities: freestyle wrestlers, street workout athletes, and devout Muslim youth. Members of these communities develop their variants of male identity, which differ in their attitudes toward violence, their view of the power of elders, and their form of moral sovereignty. These versions of masculinity are supported and stabilized both by configurations of power relations and mechanisms of intragroup homosociality.

Research target: Sociology (including Demography and Anthropology
Language: English
Full text
Keywords: ДагестанDagestanмаскулинностьmasculinityгомосоциальностьhomosociality
Publication based on the results of:
Созидательные поля межэтнического взаимодействия и молодежные культурные сцены российских городов (2017)
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