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News
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.
September 17, 2026
'I Wish That People Would Place Greater Trust in Science'
When Tatiana Eremicheva chose Fundamental and Computational Linguistics as her field of study, she thought it would be about learning languages. Instead, she discovered it was about helping people. In this interview for the HSE Young Scientists project, she discusses science as a way of understanding the world, billiards as a team-building activity, and why learning to read is not always as easy as it seems.
September 15, 2026
Immunity to Chaos: How Personal Resources Help Us Cope with the Challenges of a Turbulent World
International conflicts, crises and digital overload—the modern world puts our minds to the test every day. Traditional psychology often focuses on the consequences: anxiety, depression, and psychosomatic disorders. But what if we looked at the problem differently—through the lens of the resources that prevent us from breaking down? Psychological immunity is precisely this set of resources. Alena Zolotareva and her group, Psychological Immunity as a Resource for Positive Functioning, are developing an integrative model of this phenomenon, adapting diagnostic tools and preparing for large-scale empirical research. Why do psychologists need to collaborate with medical professionals, and how could their research transform preventive care in clinics and corporations?

 

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?

Methodology of Mean Shift Clustering Algorithm Implementation Based on Dataflow Computer

P. 177–180.
Sergey Salibekyan, Elena Ivanova, Andrey Vishnekov

The article discusses the development of a methodology for implementing on a dataflow computer the Mean shift clustering algorithm, namely its subtype - Mean shift with flat core, also called FOREL (Formal Element). We have formalized the Mean shift algorithm for the dataflow implementation. We have also developed architecture of dataflow computer, identified the types of execution units, formulated algorithms of their operation and the information exchanging. The proposed computing methodology allows to reduce information traffic in the dataflow computing system for solving the clustering problem by combining a set of points located in the features space into a computational grid and reduce the time of finding clusters by parallelizing calculations. The methodology provides finding several clusters in the linear metric space, the number of which is unknown in advance due to the convergence of the mean shift algorithm.

Language: English
Full text
DOI
Keywords: dataflowclustering algorithms

In book

Proceedings of 2019 XVI International Symposium "Problems of Redundancy in Information and Control Systems" (REDUNDANCY)
IEEE, 2019.
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