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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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Шедевры научного творчества: анализ высокоцитируемых статей российских ученых

Научно-техническая информация. Серия 2: Информационные процессы и системы. 2011. № 12. С. 1–8.
Pislyakov V.

Highly cited scientific papers by Russian authors are studied. A definition of highly cited papers based on the interpretation provided by the Essential Science Indicators database is presented; the number of highly cited Russian papers is analyzed against the background of global indices and the disciplinary distribution of these papers is explored. It is shown that in all scientific areas the share of Russian papers that become highly cited is below world average. The impact of coauthorship with foreign scientists on the creation of highly cited papers is investigated. It is concluded that international collaboration has a key role in the related process.

Research target: Sociology (including Demography and Anthropology
Priority areas: humanitarian
Language: Russian
Full text
DOI
Keywords: международное сотрудничествостатистика наукиhighly cited papersвысокоцитируемые статьиscience of scienceнауковедениеBibliometricsбиблиометрияinternational collaborationdistribution across scientific areasраспределение по областям наукиобщие вопросы
Publication based on the results of:
Высокоцитируемые публикации российских ученых: детальный анализ  (2010)
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