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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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Сиротство в России: основные тенденции и приоритеты государственной политики

SPERO. Социальная политика: экспертиза, рекомендации, обзоры. 2013. № 18. С. 57–80.
Sinyavskaya O., Biryukova S., Varlamova M. A.

For the last years the issues of child abandonment are on top of political and public agenda. Socio-economical and political transformations of 1990-2000s led to significant changes in living standards, rejected the ability of family as institution to provide child guidance and care. At the same time the system of identifying families and children in unfavorable living conditions has enhanced that led to the growing number of abandoned children and children without parental care. Current policy of preventing and overcoming of orphanhood in Russia is not a holistic system, current measures are often inadequate and do not lead to serious improvements, so the primary risks of social orphanhood among Russian children currently is at the same level as it was 10 years ago. The policy of orphanhood deinstitualization that has been realized over a number of years leads to a substantial change in the contingent of children in the institutions, which poses new challenges for the system of placing orphans and further support for them.

Research target: Mathematics Sociology (including Demography and Anthropology Political Science, International Relations, and Public Administration
Priority areas: sociology state and public administration
Language: Russian
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Keywords: Социальное сиротствосиротствоchild abandonmentchildren in institutional careпрофилактика сиротствадеинституционализация сиротства
Publication based on the results of:
The concept and main components of state family policy in the Russian Federation (2013)
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