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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
'The Humanities Serve as a Conscience'
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
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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О некоторых социально-демографических факторах интенсивности антиправительственных демонстраций: доля молодежи в населении, урбанизация и протесты

Социологическое обозрение. 2021. Т. 20. № 3. С. 98–128.
Korotayev Andrey, Sawyer Patrick, Gladyshev Maxim, Romanov Daniil, Shishkina Alisa

Demographic changes associated with the transition from traditional to modern economies underlie many modern theories of protest formation. Both the level of urbanization and the “Youth Bulge” effect have proven to be particularly reliable indicators for predicting protest events. However, given that in the course of economic development these processes often occur simultaneously, it seems logical to put forward the hypothesis that the combined effect of urbanization growth and an increase in the number of young people will be a more relevant factor for predicting protests. Our study of cross-national time series from 1950 to 2016 shows that the combined effect of these two parameters is an extremely strong predictor of anti-government protests in a single country, even more so than traditional indicators such as democratization, per capita GDP, and the level of education.

Research target: Mathematics Computer Science Social Sciences Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration
Language: Russian
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Keywords: экономическое развитиеeconomic developmentсоциальные движенияурбанизацияurbanizationпротестыprotestssocial movementsмолодежный бугорyouth bulge
Publication based on the results of:
Reconfiguration of the regional world order in the "Afrasian" zone of instability (2021)
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