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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.
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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Оценка влияния инновационной активности в сельскохозяйственном производстве на уровень жизни сельского населения

Международный сельскохозяйственный журнал. 2022. № 2. С. 111–115.
Petukhova M., Рудой Е. В., Orlova N.

The article attempts to assess the impact of various indicators characterizing the level of innovation activity in agricultural production on the indicators of the level and quality of life of the rural population of Russia. The costs of innovation, the number of high-performance jobs, labor productivity, and the level of innovation activity were determined as independent variables. Dependent variables are the level of employment of the rural population, the coefficient of migration growth of the rural population. The integrating indicator assessing the level and quality of life of the rural population was the rating assessment received by the All-Russian Institute of Agrarian Problems and Informatics named after A.A. Nikonov within the framework of the developed rating of the subjects of the Russian Federation on the quality of life of the rural population in 2019. As a result of the conducted research, it was revealed that the indicators of innovative activity in agricultural production have a positive, moderate relationship with the quality of life of the rural population. The introduction of innovative technologies has a cumulative effect that allows to increase labor productivity, and, accordingly, the wages of workers, increases the level of employment in rural areas and is one of the factors ensuring migration inflow to rural areas. The latter is due to the fact that the influx of population into rural areas is largely ensured by the attractiveness of agricultural production and the availability of high-performance jobs for qualified specialists. At the same time, a negative consequence of the introduction of innovations may be the strengthening of social stratification by the income level of the rural population. Since there is a creation of new jobs for highly qualified specialists with higher wages and the release of low-skilled jobs.

Research target: Economics and Management
Language: Russian
Full text
DOI
Keywords: производительность трудаинновационная активностькорреляционно-регрессионный анализinnovation activityсельскохозяйственное производствоlabor productivityсельские территориизатраты на инновацииcorrelation and regression analysis agricultural production rural areasinnovation costs
Publication based on the results of:
Влияние инноваций на устойчивое развитие сельских территорий: возможные сценарии на долгосрочную перспективу (2023)
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