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News
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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Читательские отзывы в интернете: опыт междисциплинарного исследования

Этнографическое обозрение. 2020. № 1.
Khazova A., Kolozaridi P., Герасимова А.

In the study of online interaction, mixed methods are increasingly used: quantitative and qualitative, approaches of humanitarian and social disciplines. These combinations are not without problems, but the complexities that can arise when using several approaches are often analyzed only from one of the disciplines. In our study, we propose another way: to problematize the use of the quantitative method in linguistic analysis in combination with the theoretical foundations of digital Ethnography and the history of reading.
The topic of the research is the study of readers ' reviews of classical literature collected on Livelib and Bookmate platforms. The main field material is the result of linguistic quantitative analysis of texts of different groups. At the same time, the question of the study itself is the distance between readers and authors, which is manifested in the structure of the community and its text. Therefore, in the discussion part of the text, we turn to the resources of the ethnographic and anthropological tradition to understand exactly how different methods work in the online study of communities.

Research target: Philology and Linguistics
Priority areas: humanitarian
Language: Russian
Full text
Keywords: History of literatureистория литературыquantitative analysisколичественный анализon-line сообществаdigital ethnographyцифровая этнографияon-line communities
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