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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Analysis of the Situation Connotation on the Example of Assessing the Reaction of Society

International Journal of Future Generation Communication and Networking. 2020. Vol. 13. No. 3. P. 37–44.
Kharlamov A. A., Pilgun M.

The goal of the study is to demonstrate a method for automated determination of the connotation of linguistic units, based on the neural network paradigm for the use of neural-like elements with temporary summation of signals. Objectives: the analysis of the situation connotation related to the construction of the Kommunarskaya metro line in Moscow using the example of evaluating the reaction of society according to social media data. Methods: the study involved a cross-disciplinary approach using neural network technologies. Findings: the reactions of society and the users’ attitude were analyzed, as well as the reasons for the residents’ negative perception; conflict zones and the level of social stress were revealed. Application: the proposed methodology can be used in predictive analytics.

Research target: Computer Science Sociology (including Demography and Anthropology
Language: English
DOI
Text on another site
Keywords: psycholinguisticsperceptionconnotation social medianeural network approach
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