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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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Применение систем регистраций движений глаз в оценке зрительно-пространственной памяти у детей дошкольного возраста

Национальный психологический журнал. 2024. Т. 19. № 4. С. 58–77.
Панфилова Е. А., Асланова М. С., Леонов С. В., Сухочев П. Ю., Седогин Е. А., Polikanova I.

Background. Neuropsychological diagnostics of visual perception is of great importance in childhood, as it is the basis for the formation of basic writing and reading skills. The integration of objective methods with the classical ones is a widespread trend, allowing to detect signs of disorders at early stages. Objective. This study is aimed at identifying the relationship between oculomotor patterns in preschool children using the Pupil Invisible eye tracker and their performance on nonverbal visual tasks related to working memory. Study Participants. The study involved preschool children from a preschool educational institution in Moscow (N = 53, 25 girls 6.76±0,32 years old and 28 boys 6.74±0,31 years old). Results. Significant differences were found in the number of fixations between children who showed high and low results in memorizing the spatial location of stimuli (p < 0.01). The results were also compared with the results of tests on cognitive flexibility, nonverbal intelligence, and fine motor skills, allowing for a clearer separation of visual working memory functions from other control processes. The level of cognitive flexibility, nonverbal intelligence, and fine motor skills did not affect these differences. The number of fixations is related to the Location scale (Rh = 0.35, p < 0.01). Oculomotor performance decreased from level one to level four (0.001 < p < 0.01) per stimulus. Conclusions. The use of eye movement recording systems in conjunction with the assessment of nonverbal visual working memory has been successfully tested, reflecting the promising use of modern technologies in the study of cognitive processes. Participants demonstrating high levels of spatial memory show more fixations while viewing an image. Overall attentional focus increased with increasing task difficulty. Oculomotor responses may play an additional role in the success of memorizing visual information, reflecting the modulation processes of visual working memory

Research target: Psychology
Language: Russian
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Keywords: eye-trackingдошкольникисаккадыpreschoolersайтрекингsaccadesfixationsфиксацииvisual-spatial memorynonverbal working memoryзрительно-пространственная памятьневербальная рабочая память
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