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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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Устойчивое развитие территорий нового хозяйственного освоения: инновационные решения

Региональная экономика: теория и практика. 2018. Т. 16. № 5. С. 942–955.
Plisetskiy E., Плисецкий Е. Л., Шедько Ю. Н.

Importance This article examines the problems of spatial organization of economy and management of territories of new economic development in Russia and discusses the issues of development and practical application of new organizational and economic solutions and decisions. Objectives The article aims to develop approaches to the management of sustainable development of new economic development areas in the context of the transition to an innovative economy. Methods For the study, we used the methods of comparative and systems analyses, and empirical data on innovative economic development regions of Russia. Conclusions With regard to the areas' economic development, innovative solutions can be implemented in more effective forms of spatial organization of economy and management of regional development, and in modern technologies, expanding opportunities to engage new resources, as well. The article concludes that an integrated approach to the management of territories' sustainable development can be effective. It recommends focusing on harmonious changes in the quality of life and economic activity of the population.

Research target: Social and Economic Geography (including Urban and Transportation Studies) Economics and Management
Priority areas: economics state and public administration
Language: Russian
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Keywords: умный городустойчивое развитиекомплексный подходтерриториальные кластерыterritorySmart Cityсоциокультурные инновацииcomplex approachsustainable developmentnew developmentgrowth areaPriority Social and Economic Development Area territorial clusterтерритории нового освоенияточки экономического роста
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