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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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Сценарное планирование в управлении обеспечением национальной безопасности: методологические основы

Национальная безопасность / nota bene. 2023. № 5. С. 36–61.
Shults V., Чернов И. В., Кульба В. В., Шелков А. Б.

The article deals with the study of methodological problems of increasing the efficiency of planning and management of ensuring the national security of the Russian Federation in context of uncertainty and risk. The results of the analysis of the main features of national security as a subject area and a complex object of public administration management are presented. The main features of management processes to ensure Russia's national security within the framework of closely interconnected external and internal contours of the subject area under consideration are highlighted. The analysis of the problems and tasks of planning as the central function of the national security management process, which determines the ways to achieve the goals set in the conditions of continuous changes in the external and internal environments, as well as the threats and challenges associated with them, is carried out. To improve the efficiency of managing processes to ensure national security, it is proposed to use a scenario approach, which provides the possibility to develop a complex of planning and management decisions taking into account the alternatives for the future events at the management object and in the external environment under uncertainty and risk. The basic strategies for using scenarios in the processes of long-term and medium-term planning are highlighted and the results of evaluating the effectiveness of various approaches to converting scenarios into concrete plans are presented. The results of the analysis showed that the use of the developed automation technology for scenario-forecast research based on the signed oriented graphs mathematical model as a means of information support for the decision-making processes significantly expands the possibilities of using the scenarios as the planning processes basis in order to increase the validity, efficiency, effectiveness and sustainability of the developed plans and programs.

Research target: Economics and Management
Language: Russian
DOI
Text on another site
Keywords: рискимитационное моделированиеуправлениепланированиесценарный анализнеопределённостьнациональная безопасностьугрозаоценка эффективности решений
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