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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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A New Electronic System for Comparative Analysis of Verse and Prose

Компьютерная лингвистика и интеллектуальные технологии. 2021. No. 20. P. 378–384.
Kazartsev (Evgenii Kazartcev) E., Zemskova T.

This paper will focus on the development of a new computational system, which enables comparative statistical studies of the rhythm of verse and prose in different languages (currently 10 languages are operative, with the possibility of adding more). The results of the analysis can be used not only for studying the processes for the genesis, expansion, and modification of various versification systems, but also for commenting on and interpreting the verse rhythm in different national poetic traditions in comparison with their foreign sources and language prosody. In addition, the possibility to model various processes of poetic speech generation and to analyze rhythmic vocabularies of prose allows hypotheses about the cognitive mechanisms of verse generation. This system operates in a semiautomatic mode and, by minimizing errors and enabling the processing of large amounts of data, provides a unique tool for computer research on the rhythm of different modes of speech.

Research target: Philology and Linguistics
Language: English
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DOI
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Keywords: rhythmprose and poetrycomparative statistical analysisversification modelsречевой ритмпроза и стихсравнительный статистический анализмодели стихосложения
Publication based on the results of:
Метрическая организация стиха во взаимодействии традиций (2021)
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