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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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?

Designing Sustainable Digitalization: Crisisology-Based Tradeoff Optimization in Sociotechnical Systems

P. 250–260.
Zykov S. V., Babkin E., Ulitin B., Demidovskij A.

Design and development of modern information systems represent a
bright ex-ample of a complex decision problem. In that context our especial interest
lays in proposing a new approach to decision support in the tasks of multicriteria
tradeoff optimization of information systems which will facilitate sustainable
development of the application domain where the information system will
be used. In that work we propose a method and a corresponding decision support
software service for linguistic multi-criteria choice among multiple design alternatives.
Our method is based on a hierarchy of cross-disciplinary criteria which
reflect the concept of crisisology. The decision support service uses an ontologybased
mechanism for dynamic customization of user interface. Application of our
method and the decision support service are demonstrated for the case of designing
a CRM information system for the enterprise.

Language: English
DOI
Text on another site
Keywords: многокритериальный выборmulti-criteria choiceприкладной сервисcrisisologyкризисологияdecision supportSoftware servicesПоддержка принятия решений

In book

Intelligent Decision Technologies. Proceedings of the 15th KES-IDT 2023 Conference
Vol. 352. , Singapore: Springer, 2023.
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