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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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Отбор источников для систематического обзора литературы: сравнение экспертного и алгоритмического подходов

Социология: методология, методы, математическое моделирование. 2018. Т. 47. С. 7–43.
Maltseva D., Moiseev S.

Two approaches to the selection of sources for a systematic literature review are compared — expert approach and algorithmic approach, based on an analysis of citation networks. Comparative analysis is conducted on the example of the research field of studying mass behavior. A comparison of two approaches according to formal and substantive criteria allows us to draw conclusions about significant difference, but also complementarity of the obtained results. Sources selected by the algorithmic approach do not reproduce the history of development of the research field described through sources selected by the expert approach. Adding expert elements to the algorithmic approach leads to a result that gives an idea of the links between classical and modern publications and groups of modern works that are interesting for study. The data obtained allow to draw a conclusion about the main reasons for the inconsistency of the results and formulate recommendations for the implementation of the proposed methodology in other areas.

Priority areas: sociology
Language: Russian
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Keywords: сетевой анализмассовое поведениебиблиометрический анализliterature reviewbibliometric analysismass behaviorcitation networksСети цитированияsystematic literature reviewобзор литературыотбор источников
Publication based on the results of:
Measurement of social processes in political sciences, business and society in general with the use of network analysis instruments (2019)
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