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Subject
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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?

Development of Wireless Camera Sensor Network model

С. 188–195.
A. Karpov, S. Efremov, L. Voskov
In press

This paper describes a model of wireless camera sensor network with \sloppy autonomous power sources, taking into account the specifics of such networks. We present new approach to definition of the energy efficiency in camera sensor networks based on user requirements. We also discuss the factors which influence on the image recognition process in sensor nodes and distinguish the levels of intelligence of camera sensor network.

Language: Russian
Full text
Keywords: математическая модельэнергетическая эффективность mathematical modelQoS energy efficiencywireless camera sensor networkintelligence levelсенсорная сеть камертребования пользователейуровни интеллектуальности

In book

DISTRIBUTED COMPUTER AND COMMUNICATION NETWORKS: CONTROL, COMPUTATION, COMMUNICATIONS (DCCN-2015), proceedings of the eighteenth international scientific conference
M.: -, 2015.
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Biological and Social Phases of Big History and Universal Evolution: Similarities, Differences, and the Growth of Complexity
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In this paper, Grinin et al. survey general similarities and differences between biological and social macroevolution and phases of Big History. The comparison of biological and social evolution is an important but (regrettably) understudied subject. The authors have endeavored to make a systematic comparison between biological and social evolution at different levels of analysis and ...
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Национальные цели развития России и ключевые индикаторы устойчивости
Kurdin A., Бобылев С. Н., Барабошкина А. В. et al., Вестник Московского университета. Серия 6: Экономика 2025 Т. 60 № 1 С. 40–59
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The article analyzes how AI contributes to improving emission monitoring, optimizing resource use, and predicting environmental risks. The study examines the potential of Al to automate and enhance the accuracy of data on companies environmental performance. The use of Al helps reduce carbon footprints, improve energy efficiency, making it a critical tool for achieving sustainable ...
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