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News
November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Верификация требований к имитационной модели производственного предприятия

Бизнес-информатика. 2018. № 2 (44). С. 65–78.
Kravchenko T. K., Golov N., Fomin A., Lipatnikov A.

Developing variants of scenarios for a production enterprise’s achieving a desirable fi nancial
position using simulation modeling tools requires a specifi cation and verifi cation of requirements for
the simulation model. Availability of such variants of scenarios allows stakeholders to select the most
effi cient solution. The verifi cation is performed by business analysts and key stakeholders; the aim is
to assess readiness of the requirements for fi nal approval and to check that the requirements provide
all material information for future work. Verifi cation includes evaluating the requirements regarding
their compliance with the company’s business analysis standards, as well as assessment of the model’s
completeness and common terminology used for description of the requirements. Understanding the
desired solution, which meets all the stakeholders’ requirements, is the most important element in
requirements verifi cation.
For developing a simulation model, which is essential for determining variants of development
scenarios and covers fi nancial fl ows of a typical production company, a list of verifi ed requirements
is determined. Criteria of requirements verifi cation include not only acceptance criteria, but also
the Graphical Requirements Analysis framework (GRA framework), that is used for verifi cation of
functional requirements. The verifi ed requirements should be used at diff erent stages of constructing the simulation model, which is focused on development of scenarios for achieving the production enterprise’s desired future
fi nancial position. Modeling scenarios of future development of the types “what will happen, if…?”
and “what to do to achieve the goal?”, using simulation modeling systems allows one to dramatically
increase the quality of decision making.

Research target: Economics and Management Computer Science
Priority areas: business informatics
Language: Russian
Full text
DOI
Keywords: имитационная модельсценарный анализscenario analysis simulation modelверификация требованийкритерии верификациикритерии приемки требованийGRA-фреймворкverification of requirementscriteria for verificationacceptance criteriaGRA framework
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