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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.
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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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Адаптация среднего класса к изменяющимся социально-­экономическим условиям в период кризиса

Журнал исследований социальной политики. 2023. Т. 21. № 1. С. 121–136.
Pishnyak A., Khalina N., Рогачева А. P.

The COVID‑19 pandemic affected the position of broad groups of the popula

‑

tion. When speaking about risk groups at the beginning of the pandemic, some

experts paid special attention to the middle class, predicting its significant

impoverishment. This work is devoted to assessing the impact of the corona

‑

virus and related social policy measures on the income and consumption of

the middle class, as well as analyzing the mechanisms of adaptation to crisis

conditions accompanied by a

decrease in income. Using the Statistical Survey

of Income and Participation in Social Programs 2017 with micro‑

modelling

methods, the consequences of the coronavirus lockdown for middle

‑ class

workers were evaluated. Also, we used the data of the survey 'Changes in the

volume of consumption of paid services in education by middle class members

and their readiness to invest in human capital development' conducted in 2018.

The data showed that there was no mass transition to poverty in the employed

middle class. In relative terms, the incomes of this stratum decreased less than

in other population groups. A

significant share of the middle class, in the event

of a drop in income, reduced spending on leisure and recreation. However,

access to these benefits in 2020 was limited and spending naturally decreased

for all strata. A

more acute problem was the forced savings on everyday ex

‑

penses, as well as the inability to pay for services related to education and

health. An attempt to assess the position of the middle class after the outbreak

of the pandemic indicates that there were high‑risk groups within the stratum,

which did not fall into the focus of social policy, and if the situation worsened

as a result of the pandemic, the middle class might have experienced significant

losses in income and lowered quality of life.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: Russian
Full text
DOI
Text on another site
Keywords: средний классбедностьстратификацияадаптацияобраз жизниэкономические стратегииMiddle classpovertyстратегии адаптацииstratificationadaptation strategiesmiddle classesmiddle classnew life styleslife styleseconomy strategies
Publication based on the results of:
Manifestations and determinants of well-being and disadvantage of various population groups in modern Russia (2022)
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