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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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Конструктор 3D-интерфейсов для системы управления умным домом

С. 455–455.
Polyakov E. V.
Language: Russian
Full text
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Keywords: 3D object3D-объектsmart homeумный дом

In book

Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов им. Е.В. Арменского
М.: МИЭМ НИУ ВШЭ, 2017.
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This paper examines the problem of clustering consumption patterns for a private household. An ensemble algorithm based on the Wasserstein metric was developed and applied to cluster daily load profiles. The proposed approach allows for identifying typical energy consumption scenarios and interpreting consumer behavior. Results from computational experiments using real data are presented. ...
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The rapid advancement of AI technologies, particularly Large Language Models (LLMs), has sparked interest in their integration into Multi-Agent Systems (MAS). This holds substantial promise for applications such as smart homes, where it can significantly enhance user experience by optimizing comfort, energy efficiency, and security. Despite the potential benefits, the implementation of MAS based on ...
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The global changes that have taken place in the economy since 2020 as a result of the Covid-19 pandemic have affected many areas of the economy. The facility-management sphere is no exception. Many owners of commercial real estate, offices and business centers faced a massive outflow of tenants, which led to a forced optimization of ...
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