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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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?

Expertise Search in unstructured data in ECM using S-BPM approach

P. 94–105.
Gromoff A., Bilinkis (Stavenko) J., Kazantsev N.

This article describes the application of currently most promising methods of (1) network (graph) theory, (2) content analysis and (3) subject-oriented approach to business process modelling for creating and automation of innovative process and therefore for maximization of ROI (return on investments) in intellectual and social capital of enterprises.

Described approach delivers opportunities for unstructured information utilization in order to increase efficiency of innovation activity in organizations. As a result, virtual community with a multiple content centers is created presenting a prototype of intellectual neural network with distributed association nodes.

In a course of development, instant full-text indexation takes place and taxonomic picture of different branches for such community is formed. In due course system gathers the statistics and builds-up maps of intercommunication with priority allocation of most discussed topics. A group of predetermined experts begins discussion on development prospects of this or that subject afterwards. The strategic map of investments into innovative development that can be offered to group of investors for competitive investments eventually turns out. In this process all steps except final (gathering of experts) are human non-dependant, what increase efficiency of this process in general.

Language: English
Full text
Keywords: социальные сетиинновациитехнологииinnovationуправление знаниямиknowledge managementtechnologyresearch projectsinformation entropysocial systementerprise contentECMself-organizing systemopen systemknowledge workersunstructured informationS-BPMcommunication networkнаучно-исследовательские проектыинформационная энтропиясоциальная системаанализ контентаECMсамоорганизующаяся системаоткрытая системаработники умственного труданеструктурированная информацияBPMS-BPM

In book

Proceedings of Modeling, Simulation, verification and validation of enterprise information systems and web intelligence
Proceedings of Modeling, Simulation, verification and validation of enterprise information systems and web intelligence
Wrocław: ICEIS, 2012.
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