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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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Маломобильные в российских печатных СМИ: анализ репрезентаций уязвимых групп до и во время пандемии

Вестник Томского государственного университета. Философия. Социология. Политология. 2023. Т. 71. № 1. С. 215–224.
Iarskaia-Smirnova E. R., Ярская В. Н., Косова О. А.

The article presents the results of content analysis and network media analysis in the dynamics of changes in the discourse about low-mobility groups in Russian print media before and during the coronavirus pandemic. The following subgroups were classified in the study as low-mobility: persons with impairments and disabilities, elderly people, pregnant women, people with small children. The research is based on the analysis of materials from the archives of the daily editions of Rossiyskaya Gazeta (RG) and Komsomolskaya Pravda (KP). The discourse about the accessible environment has significantly decreased over the past four years on the pages of RG and KP, and this suggests that the issues of comfort and accessibility of public spaces for all citizens have lost their former problematic relevance. At the same time, the discourse about persons with disabilities (PWD) remains quite noticeable. But, if in RG its intensity has hardly changed, then in KP the discourse about PWD has shrunk in the first two years of the pandemic. In RG, on the contrary, with the beginning of the pandemic, more materials about the experience of the disease of PWD began to be published. Most of the other materials in RG and KP wrote about the elderly and PWD. They are represented as needing support or initiators of any social actions. The analysis revealed the emphasis on self-sufficiency and activity of representatives of the studied groups associated with an imbalance in the distribution of responsibility for solving the problems of socially vulnerable citizens. 

Research target: Sociology (including Demography and Anthropology
Language: Russian
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DOI
Text on another site
Keywords: инвалидыпожилыемаломобильные группы населенияpeople with disabilities mass mediaпандемияpandemic COVID-19low mobility groupsnetwork media analysiscontent analysis of newspapersродители с маленькими детьмисетевой медиа анализконтент-анализ СМИ
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