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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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Качественный сетевой анализ на практике: сравнение способов построения сетевых карт

Социология: методология, методы, математическое моделирование. 2023. № 56. С. 113–142.
Kim A.

This article is devoted to the application of qualitative network analysis on the example of studying the social interactions of young parents in migration. A conceptual description of qualitative network analysis, network visualization features, design of qualitative network research, comparison of two approaches to building network maps and an example of their analysis are presented. Qualitative network analysis is aimed at studying relationships in the network and consists of interpretative and structural components, which are implemented through interviews and building a network map. The two approaches to building network maps differ in that in one case, network maps are built by the researcher based on an interview, and in the other case, the construction of the map is delegated to the informant himself. The first method is limited by the interview data and is their structural visualization. The second method of building a network map by the informant himself creates additional resources for interpretation – contrasting narratives and visual structuring of the informant's interactions.

Research target: Sociology (including Demography and Anthropology
Language: Russian
DOI
Text on another site
Keywords: миграциясетевой анализmigrationродительствокачественные методыRussian migrantsnetwork analysisParentingqualitative methodsqualitative social network analysisкачественный сетевой анализnetwork visualizationnetwork mapsвизуализация сетисетевые картыроссийские мигранты
Publication based on the results of:
Development of network analysis in Russia: adaptation of theoretical and methodological approaches and practical application (2024)
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