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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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Дистанционный стенд для синхронной работы с оборудованием на основе ПЛИС

Проблемы разработки перспективных микро- и наноэлектронных систем (МЭС). 2022. № 4. С. 117–121.
Измайлова Л. Г., Белоруков А. М., Romanov A.

Remote laboratories are of growing interest to researchers around the world. Such laboratories are mainly created for specific learning conditions, so it is impossible to fully use a third-party laboratory for conducting online classes at the MIEM, HSE University, in disciplines where FPGAs (programmable integrated logic circuits) are used. The proposed solution is a remote laboratory consisting of server and client parts, and experiments are interaction with FPGA boards with the ability to control buttons and switches, which makes it possible to bring the work in a remote laboratory to practical exercises for studying FPGAs as close as possible. Several boards are available in the remote laboratory at once, which allows students to perform various practical work and study disciplines on their own. Particular attention is paid to ensuring safety when working in a remote laboratory. The use of a remote laboratory reduces demand from students to work with the boards, as well as encourages those conducting their own experiments outside the practical classes. The results of the experiments show that the remote laboratory has a number of advantages over the existing facilities for conducting practical exercises. The paper considers the options for further development of the learning process using the developed laboratory; the introduction of a remote laboratory in the learning process allows students to study FPGAs remotely even during the period of current restrictions on conducting face-to-face classes.

Research target: Electronics and Electrical Engineering
Language: Russian
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Text on another site
Keywords: дистанционное образованиеFPGAПЛИСdistant learningremote laboratoryудаленная лаборатория
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