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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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Металитературность русского рэпа 2010-х годов: на пути к медиальной автономности

Новое литературное обозрение. 2023. Т. 180. № 2. С. 204–218.
Рыжков А. А., Ткачук С. В.

The article explores the metaliterary dimensions of Russian Rap in the 2010s. The very recent Rap legacy is analyzed and theorized in terms of certain functions of metareferentiality under the global metareferential turn and in the light of technological and sociocultural contexts. The metapoetics of Russian Rap reflects the grand-scale trend toward the mutual blending and interference of different media with one one another. At the same time, it attests to the immanent need for a musical genre to reestablish its medial essence in a new sociocultural space, rebuild its own history, and join the literary tradition. The study contributes to the current rise in our awareness of the blurred borders of literature, which are increasingly dependent on individual experiential parameters, so that verbal means migrate easily from one artistic medium to another.

Research target: Philology and Linguistics
Language: Russian
Full text
DOI
Keywords: интермедиальностьintermediality"металитература"MetapoeticsRussian rapрусский рэп
Publication based on the results of:
Литературность современных художественных медиа (2022)
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