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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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Statistical Characteristics of Poetic Fragments in Literary Text (on the material of the Russian Short Story Corpus)

.
Колпащикова Е. О.
In press
Language: English
Keywords: statisticsliterary text
Publication based on the results of:
Text as Big Data: methods and models for big text data analysis (2024)

In book

Proc. of the 3rd International Conference LiLaC (Literature - Language - Computing: Russian Contribution)
[б.и.], 2024.
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