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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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Удовлетворенность различными аспектами работы мужчин и женщин в России

Мониторинг общественного мнения: Экономические и социальные перемены. 2017. № 5. С. 271–288.
Poplavskaya A., Soboleva N.

The paper aims at revealing gender differences in the level of satisfaction with different aspects of job in Russia. The research is based upon the analysis of two waves of "Complex observation of living conditions in Russia" conducted by the Russian Federal State Statistics Service in 2011 and 2014. It is shown that during the period of three years the level of job satisfaction for both men and women increased in Russia. Men turned out to be more satisfied with wage, whereas women are happier with other job characteristics such as job security, job content, working hours, working conditions, and distance from home to work. In other words, gender paradox is present in Russia, as other things being equal, women in Russia are more satisfied with work than man. Generally the described gender differences are stable when taking into account age, education and type of contract of the employees. However, the largest gender differences in job satisfaction were found for the middle-aged, especially for the belonging to 36-45 age group, whereas for the group above 55 years the gender gap is less. Gender differences are significant for all educational groups, but they become slightly weaker for people with higher education. Compared with employees with permanent and temporary contract, workers without written contract demonstrate larger gender differences in satisfaction with various job aspects. At the same time, gender differences in wage satisfaction for workers without written contract disappear.

Research target: Sociology (including Demography and Anthropology
Priority areas: sociology
Language: Russian
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DOI
Text on another site
Keywords: рынок трудасравнительный анализemploymentудовлетворенность работойgender differencesгендерные различияcomparative analysisгендерзанятостьgenderjob satisfactionlabor marketsatisfaction with job characteristicsdynamics of job satisfactionудовлетворенность аспектами работыдинамика удовлетворенности работой
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