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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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Ценности индивидуального уровня представителей Перми и Пермского края

Аспирант. 2016. Т. 7. № 16. С. 50–55.
Fedotova (Goldyreva) V.

In this research the features of valuable orientations of residents of Perm and Perm region has been analysed. This problem is interesting to regional science, in particular, for understanding of psychological specifics of the population of the region. Residents of Perm and Perm region (n=557) - representatives of Perm, Kudymkar, Kungur, Gubakha, Solikamsk, Berezniki and some municipal districts as Ilyinsky, Kishertsky, Nytvensky, Osinsky, Suksunsky have acted as respondents. As a result it has been revealed that for respondents values such as Self-Direction Action, Self-Direction Thought, Security Societal, Security Personal, Humility, Conformity Interpersonal, Power Resources, Benevolence: care are more important; and values of Hedonism and Universalism Concern less important.

Research target: Psychology
Language: Russian
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Keywords: культураценностиПермский крайПермьculture, values, system of measurement values, Perm, Perm regionсистема измерения ценностей
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