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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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Out-of-class communication: are students and faculty interested and engaged? (A study at a Russian university)

Educational Research for Policy and Practice. 2021. Vol. 20. No. 2. P. 223–246.
Kuryan M., Elena Voronina

The study looks into the problem of student–faculty communication. It addresses the issue of claimed scarcity of such interaction that exists despite the recognized benefits it can bring to students and instructors. It is suggested that examination and comparison of the participants’ interest and actual engagement in out-of-class communication (OCC) may shed light on this. Two populations from a university in Russia: 148 students and 35 instructors, were analyzed to measure their overall interest and engagement in OCC. The paper also addressed the question whether the studied populations are interested and engage in the same types of OCC. The results demonstrate that the reported overall interest in OCC was higher than the actual engagement in it among both groups of the respondents. Besides, students and faculty chose different types of OCC as most interest evincing and most frequently practiced. The research outcomes may help the parties concerned (scholars, teaching staff, educational managers and students) enhance understanding of the nature of OCC and its specifics and consider ways of harmonizing it in the best interests of all stakeholders.

Research target: Psychology Other social sciences Social Sciences
Priority areas: sociology
Language: English
DOI
Text on another site
Keywords: студентыstudentsпреподаватели вузовteachershigher educationвнеаудиторное общение студентов и преподавателейstudent-faculty out-of-class communication
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