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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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Политические граффити в России 1990-х гг.: опыт ретроспективного анализа

Вестник Удмуртского университета. 2013. № 4. С. 25–33.
Abramov R.

The article analyzes the evolution and forms of political graffiti in Russia 1990. First, the author problematizes the methods of analysis of political graffiti and graffiti function in a situation of civil activity. Secondly, the author shows that political graffiti of the 1990s. reflect a serious transformation of public opinion and civil society in Russia this period. Thirdly, the author concludes that the political graffiti became an illustration of the cultural reaction to trauma.

Research target: Philosophy, Ethics, and Religious Studies Political Science, International Relations, and Public Administration Philology and Linguistics Sociology (including Demography and Anthropology
Priority areas: sociology humanitarian
Language: Russian
Full text
Text on another site
Keywords: идеологияideologyграффитиgraffiti
Publication based on the results of:
Граффити и стрит-арт в культурном пространстве мегаполиса (2013)
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