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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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От фабрики к платформе: автономия и контроль в цифровой экономике

Социология власти. 2020. Т. 32. № 1. С. 30–54.
Shevchuk A.

The sociology of work paid close attention to the factory and office as the physical and social space where the labor process was directly carried out and where workers faced managerial supervision, control, and power. The article discusses new decentralized forms of labor organization based on digital platforms which connect self-employed workers with clients and customers. The rapid spread of platforms in many spheres of the economy (from the IT sector and creative industries to consumer services, taxi services, and delivery) puts the task of rethinking the concepts of labor sociology, labor legislation and social policy models on the agenda. Generally, organizational decentralization was discussed in the context of increasing the autonomy of workers. However, information and communication technologies made possible not only the effective coordination of dispersed workers, but also tight algorithmic control. Workers who are outside the enterprise, both physically and legally, nevertheless experience a strong influence of digital platforms on the key conditions of their work and employment. The article discusses the nature and types of digital work platforms, sources of platform power, forms of algorithmic management, the role of user ratings, as well as the possible regulation of platform employment. The author conceptualizes the problems of labor autonomy and control within the typology of platforms: marketplace vs. shadow corporation.

Research target: Sociology (including Demography and Anthropology Economics and Management
Priority areas: economics sociology management
Language: Russian
Full text
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Text on another site
Keywords: нестандартная занятостьсоциология трудаорганизация трудаdependent self-employmentтрудовая автономиязависимая самозанятостьnon-standard employmentsociology of workorganization of workсоциология труда, профессий и занятийsociology of work, professions and occupationsцифровые платформыdigital platformsself-employmentбиржи удаленной работыonline labor marketsplatform employmentплатформенная занятостьgig economy digital platforms classificationlabour platformsplatform workгигономикатрудовые платформы
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