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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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SMEs and Mass Collaborative Knowledge Management: Toward Understanding the Role of Social Media Networks

Information Systems Management. 2017. Vol. 34. No. 3. P. 280–290.
Scuotto V., Del Giudice M., Omeihe K. O.

This article proposes that mass collaborative knowledge management (MCKM) and social media networks (SMNs) tend to enhance productivity in small- and medium-sized enterprises (SMEs). A case study methodology was employed to highlight the complementary advantages of MCKM related to the use of SMNs in a small business operating in southern Italy. The research aims to contribute to the ongoing discussion on MCKM. This article offers a fresh perspective by discussing the relevance of this construct for SMEs.

Priority areas: economics management
Language: English
DOI
Text on another site
Keywords: социальные сетиcase studyкейс стадиSMEsпредприятия малого и среднего бизнесаSocial media networksmass collaborative knowledge managementмассовое совместное управление знаниями
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