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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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Модернизация музеев: проблемы и пути решения (по материалам социологического опроса)

Вестник Томского государственного университета. Культурология и искусствоведение. 2026. № 61. С. 216–227.
Sizova I.

Modernization of a museum involves conceptual, structural, and technological changes that adapt it to its environment and to the future. Nevertheless, modernizing museums is not an easy process, so the study focused on identifying the reasons why this is happening. An ICOM Russia and Union of Museums of Russia survey was conducted in order to achieve this goal. A total of 113 museum professionals from 105 museums of varying profiles participated in the survey, as stipulated by the principle "survey of all who agree".
It was found that modern museum employees lack professional competencies not only due to internal and external barriers, but also due to lack of professional competencies. In addition to revealing some regularities in internal and external barriers' influence, as well as the limited competence of museum workers regarding the effective development of museum organizations, the study also provided a number of recommendations aimed at modernizing museum practice.
We have concluded by making recommendations aimed at improving museums' technical and technological infrastructure, gaining additional financial injections, and enhancing museum employees' professional skills.

Research target: Other social sciences Other Humanities
Language: Russian
Full text
DOI
Keywords: модернизацияmodernizationбарьерымузейbarriersmuseumstaff competenciesкомпетенции сотрудников
Publication based on the results of:
Systematic approach to transformation of the digital museum space (2021)
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