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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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AIP Conference Proceedings 2872: 11th Int’l Conference on Mathematical Modeling in Physical Sciences. Belgrade, Serbia, 5-8 September 2022

AIP Publishing LLC, 2023.
Under the general editorship: D. Vlachos
Chapters
Continuum Model of an Avalanche-Like Spread of Information on Twitter
Dmitriev A., Lebedev A., Abbas N. et al., , in: AIP Conference Proceedings 2872: 11th Int’l Conference on Mathematical Modeling in Physical Sciences. Belgrade, Serbia, 5-8 September 2022.: AIP Publishing LLC, 2023. Ch. 080002 P. 1–12.
The research results devoted to the construction and analysis of the stochastic nonlinear dynamic system of equations that simulate the self-organization of Twitter into the critical state are presented. A nonlinear dynamic system links three dynamic variables. The first variable corresponds to the order parameter determined by the average size of avalanches of microposts (tweets, retweets). The second ...
Added: December 10, 2022
Research target: Computer Science Physics
Language: English
DOI
Keywords: physicsastronomy
AIP Conference Proceedings 2872: 11th Int’l Conference on Mathematical Modeling in Physical Sciences. Belgrade, Serbia, 5-8 September 2022
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