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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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?

Потенциал модернизации университетов Центрального Черноземья

С. 402–407.
Яцкова Д. С.

The paper brings up the question of the role of the university community in the implementation of modernization programs in the Russian regions. The article analyzes the theoretical and methodological foundations of the study of modernization processes and innovations, determines their place and role in the socio-cultural environment, identifies the main approaches to the development of innovative programs and their constituents. The author reveals the conditions for the development of innovative potential of the regional universities and the main problems affecting the development of innovative activity of universities. The article shows the mechanisms of modernization processes, the development of regional innovation activities, which will enhance the efficiency of research and production activities, its adaptation to the market economy. The author has studied the main conditions for the emergence, development and successful commercialization of innovation. The article analyzes the rating data of socio-economic development of regions of the Central Chernozem region, as well as the features of innovative development in the Kursk region. The author presents the results of a field sociological research devoted to the assessment of innovative activity of students of higher educational institutions of Kursk and Voronezh regions. The study is aimed to determine the level of development of modernization processes in the region and the attitudes of students, identified through their focus on innovation, including interests, goals and motives associated with innovations. The article explores the understanding of innovation by young respondents, presents the involvement of students in these regions in research activities. The author suggests that the solution of the problems of formation the innovative behavior of Russian youth can contribute to the involvement of this social group of the society to the implementation of the modernization of the main spheres of life of modern Russian society.

Language: Russian
Text on another site
Keywords: университетmodernizationрегиональная инновационная системаregional innovation systemнаучно-исследовательская деятельность в высшей школеинновационное развитие в образовании innovative development

In book

Вестник Омского университета. Серия «Экономика»
Вып. 3. , Омск: ОмГУ им. Ф.М. Достоевского, 2015.
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