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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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Система поддержки принятия решений «ELECTRE»

Прикладная информатика. 2017. Т. 12. № 1 (67). С. 102–113.
Kravchenko T. K.

Problem statement: solutions analytical justification by using a decision support system (DSS) significantly increases the quality of decisions. The existing DSS generally employs methods analytic hierarchy process and analytical networks. It does not always lead to the desired results as each method is based on certain assumptions and is not universal. The creation of the DSS, including ELECTRE collection methods, will allow to obtain additional information about the relative importance of different variants of the solution for the task. Methodological basis for the creation the DSS «ELECTRE»: the family of ELECTRE methods, which include ELECTRE I, ELECTRE Iv, ELECTRE IS, ELECTRE II, ELECTRE III and others. Their key feature consists in the fact that they do not use the convolution operation of evaluation of the alternatives specified in different scales on different criteria. Results: developed software of DSS «ELECTRE», allowing to use any of the methods of this family to select the preferred alternatives based on multiple criteria and evaluations of their relative importance. Practical relevance: unlike other developments, the research results allow to analytically justify solutions using a variety of methods of collection in one software environment.

Research target: Computer Science Economics and Management
Priority areas: management business informatics
Language: Russian
Full text
Keywords: системы поддержки принятия решенийэкспертная система поддержки принятия решенийdecision support systemsExpert Decision Support System (EDSS)ELECTRE family methodsметоды семейства ELECTREdecision support system «ELECTRE»the task of choosing a platform for business intelligence for the enterpriseсистема поддержки принятия решений «ELECTRE»задача выбора платформы бизнес-интеллекта для предприятия
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