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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.
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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Анализ методологии стандарта NSWC-11 прогнозирования надёжности механического оборудования

С. 773–776.
Zhadnov V. V.

In this work the process of results of the analysis of methodology of reliability prediction mechanical equipment. The author proves the possibility and necessity of creation of databases on the characteristics of reliability of mechanical elements.

Language: Russian
Full text
Keywords: прогнозированиенадёжностьмеханическое оборудование
Publication based on the results of:
Разработка методов прогнозирования надежности электронных средств (2014)

In book

Сборник трудов VIII международной научно-практической конференции "Информационные и коммуникационные технологии в образовании, науке и производстве"
Сборник трудов VIII международной научно-практической конференции "Информационные и коммуникационные технологии в образовании, науке и производстве"
Протвино: Управление образования и науки г. Протвино, 2014.
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