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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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Методические аспекты оценки технологического потенциала региона

С. 49–54.
Rastvortseva S.

The article deals with a method for assessing the technological potential of a region through the calculation of indices of economic complexity and technological proximity. Approbation of the approach is carried out on the basis of the regions of Russia

Language: Russian
Full text
Keywords: регионы Россииregions of Russiaтехнологический потенциал регионаeconomic complexity indextechnological proximity indextechnological potential of the regionиндекс экономической сложностииндекс технологической близости

In book

Современные проблемы социально-экономических систем в условиях глобализации
Белгород: ИД "Белгород", НИУ "БелГУ", 2019.
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