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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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Моделирование оплаты труда учителей в условиях неоднородности социально-экономического состояния регионов

С. 41–44.
Богданова Т. К., Жукова Л. В.

The paper is devoted to the analysis and forecasting of the average salary of teachers. For 84 regions on the basis of their socio-demographic characteristics according to Rosstat data using Ward's method we obtained a two-cluster solution, which allowed us to identify quite strong differences in the level of wages, GRP per capita, level of consumption and the share of young people of working age. The results of the statistical analysis confirm that currently teachers' salaries are almost completely determined by the socio-economic development of the region. But in order to retain the most qualified personnel in the regions of the Russian Federation, the teacher's qualification level should be taken into account in the formation of wages, first of all. This will reduce the differentiation in the level of teachers' remuneration.

Language: Russian
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Keywords: кластеризациялинейная регрессияclusteringlinear regressionteacher salarysocio-demographic characteristics of the regionteacher salary forecastingзарплата учителейсоцио-демографические характеристики регионапрогнозирование зарплаты учителей

In book

XI-я международная конференция «Многомерный статистический анализ, эконометрика и моделирование реальных процессов» имени С.А. Айвазяна
М.: ЦЭМИ РАН, 2024.
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