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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?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Возможности использования корпусов при обучении англоязычной академической лексике

С. 204–217.
Dugartsyrenova V.
This paper addresses the pedagogical affordances of using open-access corpora of English language academic texts to teach academic vocabulary to non-native English speakers mastering the art of research writing in English. We show how such corpora can provide valuable authentic material for linguistic researchers, educators, and students alike to examine the linguistic features of research writing. We also present a local corpus of scientific articles from social disciplines compiled as part of a scientific project at the National Research University Higher School of Economics.
Language: Russian
Full text
Keywords: корпусные технологииcorpus technologycorpora of academic textsteaching academic vocabularyresearch writing in the English languageкорпусы научных текстовобучение академической лексикеподготовка научных работ на английском языке
Publication based on the results of:
SAAWR (Self-Access Academic Writing Resource) – онлайн-помощник в овладении письменной научной речью на английском языке (2016)

In book

Материалы трудов VII Международной научно-практической конференции "Информационно-коммуникационные технологии в лингвистике, дидактике и межкультурной коммуникации"
Вып. 7. , М.: Университетская книга, 2016.
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