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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.
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'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.
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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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Сегментирование рынка EdTech при растущем спросе на цифровые технологии в образовании

Проблемы современного образования. 2021. № 4. С. 79–91.
Obukhov A., Томилина М. В.

The rapid development of educational technologies in the last two decades has affected all levels of education and has largely changed the approaches to learning, as well as its methods and forms. Educators all around the world are using digital technologies, apps and online platforms to find the most effective and productive ways to boost their educational practices. The markets respond appropriately to the increasing demand: the EdTech industry is growing at an extremely high rate, giving the consumer the opportunity to choose and search for the most suitable educational technologies for their purposes. The analysis and systematization of various ways of segmenting the market of educational technologies allowed us to identify the most typical of them. Thus, two types of segmentation provide higher importance for the EdTech market and the agents operating on it, both on the demand side and on the supply side: 1) by end user, 2) by product type. In the course of the study, it was found that EdTech manufacturers do not always seek for strictly sticking to their target audience but are ready to provide several groups of consumers with their products at once, initially adjusting the functionality to the needs and goals of each.

Language: Russian
DOI
Text on another site
Keywords: образовательные технологиимировой опытeducational technologiesEdTechEdTechTeselection and use of educational technologiesworld experienceEdTech marketвыбор и использование образовательных технологийрынок EdTech
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