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Subject
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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Динамика основных коммуникативных практик россиян

Коммуникации. Медиа. Дизайн. 2019. Т. 4. № 3. С. 48–68.
Задорин И.В., Saponova A. V.

This article presents complex dynamic of Russian’s communicative practices, based on the ZIRCON Research group monitoring data for the period 2009-2019. Authors highlight three main communicative trends: 1) including new users in digital sphere; 2) appearing of the new communicative practices and redistribution of the audience among different media channels; 3) decreasing trust in Russian media (state TV and radio, newspapers and magazines) and in information from Internet sources as well. At the same time the level of trust in information from social networks and search systems (Google News, Yandex.Novosti) was not changing. It also provides justification for the representative mass survey as a valid method for the research of some communicative practices.

Research target: Media and Communications
Priority areas: sociology
Language: Russian
Full text
Text on another site
Keywords: мониторингcommunicationmonitoringcommunicative practicesкоммуникативные практикимедиапотреблениемедиаповедениедоверие медиаtrust in the mediarepresentative mass surveyвсероссийский опрос
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