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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.
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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Протестная активность россиян в 2012-2013 гг.

Социологические исследования. 2018. № 11. С. 54–63.
Semyonov A.

The focus of this paper is the dynamics of contention in Russia in 2012-2013. Using the protest event analysis developed within the sociology of social movements data on 4,475 protest actions in all Russian regions have been compiled. The data reveal the spatial aspect of collective mobilization, organizational sponsors, repertoire and major targets of the protests. Among the stable characteristics of protest activity are the symbolic nature of the repertoire and public authorities as the most frequent aim. The Communist Party (KPRF) and trade unions constitute the organizational backbone for collective actions. Local residents and initiative groups are among the most active organisers as well. Citizens protested against electoral fraud during the 2012–2013 «For Fair Elections!» campaign; they also raised demands about social policy, economy, and the quality of governance. Principal component analysis (PCA) on the host of regional indicators reveals the underlying structure in the cross-regional variation in protest activity: the most significant covariates of public contention in the regions are the population size, level of urbanization, GRP, and the level of political openness.

Research target: Political Science, International Relations, and Public Administration Sociology (including Demography and Anthropology
Language: Russian
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Keywords: региональная политикамобилизациясоциальные движенияколлективные действияsocial movementsmobilizationcollective actionssubnational politicscontentious politicsсостязательная политикабазы данных по протестам
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