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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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Kids, streets, and activities

2016. No. 71.
Bochaver Alexandra, Корзун А. Н., Polivanova K. N.
Street activities are recognized as playing significant role in children and teenage socialization. However, the socialization mechanism of street activities is gradually changing. Active play and street gangs remain in past, as most parents today acknowledge. The present article investigates the forms of street leisure activities of Russian kids and teenagers born in different decades of late XX and early XXI centuries. The research is based on the answers of 251 participants to the two developed thematic questionnaires. Content-analysis of the answers allows to identify five principal categories of street leisure activities, namely: games, communication, exploratory activities, risk behaviors, and cultural activities. The article describes the main components of each of the categories and analyses their representation in both adult and teenage samples’ leisure time. The results allow to manifest the relation between children's leisure activities dynamics and their social environment, as regards increased social insecurity and uncertainty, urbanization rates, overpopulation, etc. The research also investigates the areas of street leisure activities, level of parental control, as well as types of rules and regulations set by parents regarding their children’s travel and leisure. The future research suggestions given the results are made.
Research target: Psychology
Priority areas: humanitarian
Language: English
Full text
Keywords: детстводосугChildhoodподростковый возрастleisureгородская средаurban environmentadolescencestreet leisure activityуличный досуг
Publication based on the results of:
New Trends in Socialization of Children and Teenagers in Educational Institutions and beyond them (2016)
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