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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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Полнота понимания цифровых и печатных текстов: результаты экспериментального исследования

Психология. Журнал Высшей школы экономики. 2024. Т. 21. № 4. С. 710–728.
Sherbakova O., Исаева Т. Е.

This article describes the results of a study aimed at revealing a potential correlation between the level of understanding of a text and the format of its presentation (printed or digital). Namely, we expected a lower level of comprehension for digitally presented text compared to its hard copy printed analogue due to the higher cognitive ‘cost’ of reading in digital environment. We also expected that the use of extra materials (EM) providing additional information to the main text is related to the format of text’s presentation. Sixty volunteers (39 females, mean age = 20 ± 0.6 years old) participated in the study. They were administered Raven’s Stan dard Progressive Matrices (SPM); then, they read the stimuli (pop-science text) in either digital, printed, or hybrid format, completed a questionnaire assessing the level of text’s understanding and, finally, answered questions of a semi-structured interview. The crosstab, F-test and Kruskal-Wallis test were used for statistical analysis. We found no significant differences between the levels of understanding of texts of different formats. However, most participants showed low levels of comprehension; also, they used EM (hyperlinks) less when working with digital text compared to its printed analogue. The latter result might be due to higher cognitive load when reading a text on the screen than reading a printed text. The low level of understanding suggests that basic cognitive skills are more important in reconstruction of text’s meaning than the format of text’s presentation.

Research target: Psychology Philology and Linguistics
Language: Russian
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DOI
Text on another site
Keywords: чтениепониманиеreadingцифровая средаreading comprehensionсмысловое чтениеdigital textprinted textпечатная среда
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