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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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Проблемы обеспечения информационной безопасности государственных баз данных и автоматизированных информационных систем российской федерации

Московский экономический журнал. 2021. № 2. Статья 51.
Баранов Р. Г., Гневанов М. В.

The article considers the current problem of ensuring the information security of state databases and automated information systems. The existing approaches to ensuring information security are analyzed. Using the analysis of various indicators, three blocks of threats to the information security of state databases and automated information systems were identified. Of these blocks, one is identified that is most at risk of data leakage, which is specific to the Russian environment. The conclusion about the need for an integrated approach in the formation of a database and AIS information security system is justified. A block diagram of the structure of an integrated approach to information security in the context of the public sector has been developed.

Research target: Engineering and Technology
Language: Russian
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DOI
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Keywords: защита информацииинформационная безопасностьбаза данныхавтоматизированная информационная системаdatabase information security information protectionautomated information system
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