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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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Возобновляемая энергетика XXI век: Энергетическая и экономическая эффективность

M. : ОИВТ РАН, 2016.
Safonov G.
Academic editor: О. С. Попель, Д. О. Дуников

The proceedings of International Congress REENCON-XXI "Renewable energy in 21st Century: energy and economic effectiveness" 2016 presents the thesis of Congress participants devoted to the key aspects of development and practical use of renewable energy sources in Russia and the world. One of the challenges relates to deep decarbonization of the world economy aiming at mitigation of global climate change.

Research target: Economics and Management Earth Sciences Biology Construction Mechanics and Mechanical Engineering Effective Natural Resource Management Political Science, International Relations, and Public Administration
Priority areas: economics management state and public administration engineering science
Language: Russian
Full text
Keywords: изменение климатаэнергоэффективностьclimate changerenewable energy energy efficiencyвозобновляемая энергетикаdecarbonizationlow carbon developmentнизкоуглеродное развитиедекарбонизация экономики
Возобновляемая энергетика XXI век: Энергетическая и экономическая эффективность
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