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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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Проблема обеспокоенности общественных природоохранных организаций: пример промышленного освоения Арктики

Корпоративное управление и инновационное развитие экономики Севера: Вестник Научно-исследовательского центра корпоративного права, управления и венчурного инвестирования Сыктывкарского государственного университета. 2016. № 2. С. 124–130.
Villo S.

The article discusses the burning managerial issue — public environmental organizations’ concern. A situation of public environmental organizations’ concern in connection with the development of Arctic oil field Prirazlomnoe by Gazprom group of companies forms the empirical basis of the study. The author analyzed the available secondary data, conducted in-depth semi-structured and unstructured interviews with respondents from public environmental organizations and Gazprom Group of companies. The results of empirical research revealed the dynamics of public environmental organizations’ concern and the causes of public environmental organizations’ concern. These results provide an explanation for increasing environmentalists’ counter-actions towards a company, the activities of which involve environmental risks. The author proposed necessary measures for the management of public environmental organizations’ concern and indicated the areas for further research. 

Priority areas: management
Language: Russian
Full text
Keywords: ГазпромЭкологическая безопасностьGazpromenvironmental safetyENGOsобщественные природоохранные организацииобеспокоенность общественных природоохранных организацийстадии обеспокоенности общественных природоохранных организацийпротиводействие экологов компании
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