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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
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
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Студенческие речевые ошибки и актуальные тенденции в развитии русского языка

С. 157–178.
Kuvshinskaya Y. M.

The article is devoted to the new field of corpus linguistic that is the research of speech errors of native speakers. Mistakes of Russian-speaking students are considered in line with the grammar errors of A. Frey and modern research of non-standard texts. Special attention is paid to one of modern trends in non-standard speech – the usage of the excess participle. The linguistic mechanism of the error and the linguistic and social causes of the frequency of such occurrences are analyzed.

Language: Russian
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Keywords: русский языкRussian languagespeech errorsречевые ошибкиcorpus methodsпричастияparticipleкорпусные методы в лингвистике
Publication based on the results of:
Tendencies of language change in the mirror of corpora (2016)

In book

Leo philologiae. Фестшрифт в честь 70-летия Льва Иосифовича Соболева
М.: [б.и.], 2016.
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