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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.
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'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.
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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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Green infrastructure dynamics in the urban areas of subarctic Western Siberia

Urban Ecosystems. 2025. No. 28. Article 155.
Moskovchenko D., Roman Fedorov, Fakhretdinov A.

The northern part of western Siberia, which comprises the Khanty-Mansiysk and Yamalo-Nenets Autonomous Districts of Tyumen Oblast, Russia, is one of the most urbanized areas exposed to the subarctic climate. Here, we study the specifc socio-natural interactions afected by the development of urban green infrastructure in such climatic zones as middle and northern taiga, as well as forest-tundra. Analysis of vegetation indices allowed the tracing of general trends in the dynamics of green space transformations. Most cities located in the forest tundra and northern taiga zone show a trend towards greening. In the cities located in the middle taiga zone, which has a warmer climate and large areas of primary woody vegetation, the warming efect and artifcial landscaping do not have the same noticeable infuence on the overall growth trends of phytomass. At the same time, a tendency towards the leveling of Normalized Diference Vegetation Index (NDVI) can be seen in the oldest, well-landscaped cities and younger cities with developing green infrastructure.

Research target: Social and Economic Geography (including Urban and Transportation Studies) Effective Natural Resource Management History and Archeology
Language: English
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DOI
Text on another site
Keywords: dynamicsRemote Sensinggreen infrastructureWestern SiberiaSubarctic climateSocio-environmental interactions
Publication based on the results of:
War and Post-War Peace in the Russian Empire and the USSR (2025)
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