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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.
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Moving Other Way: Exploring Word Mover Distance Extensions

P. 92–97.
Smirnov, I., Yamshchikov I. P.
Language: English
DOI
Text on another site
Keywords: semantic similarity
Publication based on the results of:
Metrics of Semantic and Stylistic Similarity of Natural Language Texts (2022)

In book

COMPLEXIS 2022. Proceedings of the 7th International Conference on Complexity, Future Information Systems and Risk. April 23-24, 2022
Science and Technology Publications, Lda, 2022.
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