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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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Социальное самочувствие молодежи постсоциалистических стран (на примере России, Казахстана и Чехии) сравнительный анализ ценностных ориентаций (Часть 1)

Вестник Российского университета дружбы народов. Серия: Социология. 2018. Т. 18. № 1. С. 131–155.
Trotsuk I., Нарбут Н. П.

The article presents the empirical results of a three-year study conducted by the Sociology Chair of the RUDN University in cooperation with foreign colleagues to compare the worldview priorities of the today’s student youth. Due to the article size limitations the authors divided the data into two parts: in the first part, they focus on the identification of the values ​​that serve as reference points specifying the social action limits and criteria for assessing events and situations. The data does not allow for broad generalizations due to the non-equivalence of the questionnaires used in three countries, but points to a number of characteristics that make the Russian youth look more similar to their Czech or Kazakhstan peers than to themselves a decade ago. Such a conclusion is based on the analysis conducted according to the thematic structure of the questionnaire. Thus, the article presents the educational values ​​of students (pragmatic-instrumental perception of the higher education), labor values ​​(a mixture of optimism and pessimism when assessing chances to find a job after graduation, and different attitudes to the combination of study and work), interpersonal interaction features (a high credit of trust in parents, especially in a difficult situation, does not depend on the self-perception and the circle of personal responsibility), political values ​​(the ratio of the lack of political activity and interest in politics, and the level of social trust differ despite the same leaders of national pride), general value ​​priorities (attitudes towards religion, interpretations of the life success and qualities necessary for achieving it, the horizons of planning) and problems (assessing one’s generation in terms of actual threats).

Research target: Social Sciences
Priority areas: sociology
Language: Russian
DOI
Text on another site
Keywords: ценностные ориентациимолодежьсравнительный анализстуденчествоопросный инструментарий
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