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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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Участие российской молодежи в образовании взрослых: роль настойчивости и образовательного статуса

Образование и саморазвитие. 2024. Т. 19. № 4. С. 182–196.
Karmaeva N., Вологина Д. В.

Despite the expanding opportunities in adult education and learning (ALE) for young people, not all individuals take advantage of them. The paper aims to analyze the relationship between the educational status of young people and their parents, their perseverance (GRIT), with their participation in informal and informal ALE. We analyze whether perseverance enhances participation in ALE among young people with educational advantages. The study tends to contribute to the wider discussion on the reproduction of social structure through human capital accumulation. We analyze the data provided by the longitudinal study “Trajectories in education and profession (TROP)” using regression analysis. We found a positive relationship between an individual's level of education and perseverance (measured at the age of 14) and participation in job-relevant ALE in adulthood (23-25 years old), and a positive relationship between mothers’ higher education and participation in ALE, not relevant to the job. The hypotheses about the significant role of perseverance in further accumulation of educational advantages is partially confirmed: perseverance enhances the positive effect of higher mother’s education, in participation in work-related informal learning. The results can be used in the development of activities aimed at increasing the involvement of young people in ALE.

Research target: Education Sociology (including Demography and Anthropology
Language: Russian
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DOI
Text on another site
Keywords: непрерывное образованиемолодежьобразование взрослыхобразовательное неравенствоgritRussian youth educational inequalitygritadult learning and education
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