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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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?

IoT-based Mine Ventilation Control System Architecture with Digital Twin

P. 1–5.
Kychkin A., Nikolaev A. V.

This paper considers a dynamic ventilation system of the underground mining. The research is relevant from the point of view of safety and energy saving of mining operations, since the process of ventilation of underground mining companies consumes from 30 to 50% of all company electricity. Existing methods of ventilation control often do not ensure rational energy consumption, as they do not take into account the dynamics of air distribution and changes in environmental parameters. The proposed method includes basic algorithms for calculating the interrelationship of physical parameters of general natural draught between the trunks. The method includes: calculation of the draught’s power; calculation of productivity and the choice of the required mode of operation for the main fan unit (MFU) considering the inertia of the ventilation system; dynamic calculation of the control signal on the fan unit taking into account the impact of the general natural draught. The method is focused on the implementation of the TICK stack used to create IoT applications as part of the Cyber-Physical System (CPS) for ventilation based on the InfluxData platform. The proposed CPS architecture consists of four subsystems: physical object subsystem, IoT network and computing infrastructure - ICT infrastructure, digital twin, user interface. CPS architecture provides processing of data from energy meters, controllers and air environment parameters, implemented in on-line and off-line calculation units

Language: English
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DOI
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Keywords: Information System ArchitectureModelica Internet of Thingscyber-physical systemsDigital TwinInfluxData Platform

In book

2020 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
Institute of Electrical and Electronics Engineers, 2020.
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