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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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?

Ensuring the integrity of transportation and logistics during the COVID-19 pandemic

P. 96–105.
Dorofeev A., Пашкова Т., Курганов В., Филиппова Н.

The unexpected, rapid spread of the COVID-19 coronavirus around the globe has almost completely paralyzed multiple industries in most nations. At the same time, even during lockdowns, many countries did practically no attempt to restrict road traffic, fearing that this would freeze the shipping of vital goods, primarily food. As a result, shipping by road transport has only been impacted by the drop in consumer demand. Nonetheless, shipping companies’ operations have undergone drastic changes due to the quarantine. Sending some of the personnel to work from home has been one of these changes. On the one hand, this has exacerbated certain risks. On the other hand, when personnel works from home, this helps reduce spending and may even be considered as a way of enforcing the lean transportation principle. The insights gained from remote controllers’ efforts to keep road shipping safe and reliable during the COVID-19 pandemic may find successful uses as a step towards greater shipping efficiency, not only in emergencies, but under other circumstances as well. In this paper, we consider the capabilities of a virtual machine-based architecture for a road shipping control system. We also elaborate on the practical results of deploying such an architecture. Our study proves that our concept of a geographically dispersed shipping company that uses a Virtual Desktop Infrastructure and Process Mining has the means to ensure productive remote controller operation, including operation through low-bandwidth Internet channels, and guarantees the integrity and confidentiality of the relevant business information.

Language: English
Full text
DOI
Keywords: process miningLean transportationshipping system reliability

In book

XIV International Conference on Organization and Traffic Safety Management in Large Cities (OTS-2020)
Vol. 50. , Elsevier, 2020.
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