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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.
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'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.
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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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EDP Sciences - Web of Conferences

Issue 383: International Scientific Conference Transport Technologies in the 21st Century (TT21C-2023) “Actual Problems of Decarbonization of Transport and Power Engineering: Ways of Their Innovative Solution”. 2023.

The present paper presents the rolling stock vibrodynamic impact model on railway pipelines, obtained on the basis of experimental studies conducted under field conditions at a railway station. The experimental research program provided for the determination of the effect of vibration-dynamic effects of rolling stock on the working condition of pipes and butt joints by conducting vibration-measuring work on the investigated section of the railway pipeline during the passage of various series of locomotives. The proposed modeling method makes it possible to obtain a correlation function of the oscillatory process of a railway pipeline, on the basis of which a spectral density is constructed to identify the amplitude-frequency range at which a stable resonance region occurs, leading to the destruction of the pipeline

Research target: Engineering and Technology Physics Mathematics
Language: English
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DOI
Text on another site
Keywords: resonancespectral densitycorrelation functionrolling stockrailway pipelinevibration dynamic effectsvibration accelerationoscillatory process oscillation frequencyoscillation amplitude
EDP Sciences - Web of Conferences
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