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News
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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?

Изучение и моделирование совместной деятельности в сетевых сообществах

M. : Московский городской педагогический университет, 2024.
Patarakin Y.

The monograph is dedicated to the practice of studying and modeling collaborative activities in the educational process. The foundation of the monograph consists of case studies obtained during training or research. It is intended for students of pedagogical specialties who aim to gain a deeper understanding of the mechanisms that determine the behavior of participants in educational network communities, such as Wiki, Scratch, and MESH. The study of behavior is based on the analysis of traces left by participants on digital objects. These traces allow us to reveal the dynamics of collaborative activity. The book offers open tools for modeling and analyzing collaborative activity, contributing to the development of effective methods of pedagogical practice in the digital space.

Research target: Education Sociology (including Demography and Anthropology
Language: Russian
Full text
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Keywords: многоагентное моделированиесетевое сообществоcommunityagent based modelingNetLogoNetlogoSemantic MediaWikiSemantic MediaWiki
Изучение и моделирование совместной деятельности в сетевых сообществах
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