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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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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Run time dynamic digital twins and dynamic digital twins networks

Future Generation Computer Systems. 2025. Vol. 172. Article 107823.
Vodyaho A., Delhibabu R., Ignatov D. I., Zhukova N.

Digital twins are widely used for building various types of cyber–physical systems. There are a huge number of publications devoted to the use of digital twins in production systems. Much less attention is paid to the issues of building runtime digital twins. The article describes an approach to building complex distributed cyber–physical systems with a high level of architectural dynamics built on fog and edge computing platforms based on the use of digital twins. The issues of implementing runtime digital twins and distributed systems of runtime digital twins are considered. The requirements to runtime digital twins are defined. Typical problem statements for constructing and maintaining a runtime digital twin system are formulated. A reference architecture of a dynamic runtime digital twin is proposed, which includes a model of the observed system (or the object) and a model processor. The dynamic model of the observed and managed system is considered as a key element of the digital twin. Possible approaches to the synthesis of built-in models of runtime digital twins are discussed. Examples of using the proposed approach to solve practical problems are given. The described approach may be of interest to specialists involved in research and development of various types of information systems implemented on Internet of Things platforms, such as smart cities, smart transport, medical information systems, etc. It is proposed to conduct further research and development in the areas of creating human digital twins.
 

Research target: Computer Science Mathematics
Language: English
DOI
Text on another site
Keywords: цифровые двойникиDynamic digital threadsModel synthesis Digital twin Digital twin networksсети цифровых двойниковдинамические цифровые потокисинтез моделей
Publication based on the results of:
Complex language and semantic models in artificial intelligence (2025)
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