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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
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Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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The method of automated synthesis of thermal control systems of microelectronic devices

P. 1–6.
Громов И. Ю., Kozhevnikov A., Kofanov Y. N.

This paper presents a description of the method of automated parametric and structural optimization of systems for ensuring thermal regime of microelectronic devices using modern information technologies.

Language: English
Full text
DOI
Keywords: optimizationautomationdesignthermal regimesmicroelectronic devices

In book

2018 Moscow Workshop on Electronic and Networking Technologies (MWENT). Proceedings
2018 Moscow Workshop on Electronic and Networking Technologies (MWENT). Proceedings
M.: IEEE, 2018.
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