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News
July 9, 2026
HSE Economists Use Search Queries to Forecast Birth Rates
Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.
July 8, 2026
HSE Researchers Discover Who Eats Out in Russia-And Why
Around one-third of Russians (31.3%) rarely eat out or buy ready-made meals. The core group of active consumers—those who eat out or purchase prepared food almost every day or several times a week—accounts for only about 9% of the population. These are the findings of a study conducted by the HSE Institute for Social Policy. According to the researchers eating out is no longer a marker of high social status in Russia.
July 8, 2026
HSE University and RREDA Join Forces to Support 2026 Renewable Energy of the Planet Competition
HSE University and the Russia Renewable Energy Development Association (RREDA) have signed a partnership and information cooperation agreement to support Renewable Energy of the Planet—2026, a national competition with international participation for students and early-career researchers. Applications are open on the competition's website until September 20, 2026.

 

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Research and developing methods of solving engineering optimization problems for parallel structure robots

International Journal of Open Information Technologies. 2019. Т. 7. № 11. С. 1–7.
Maminov A., Posypkin M.

— We consider the optimization of the key design parameters of the 2-RPR parallel robot in this paper. Optimization is carried out according to two criteria: the area of the workspace of the 2-RPR robot and the controllability index - global dexterity index (GDI). In the process of analyzing the robot, the direct and inverse kinematic problems are solved, the Jacobi matrices of the input and output parameters are found, and the final complete Jacobi matrix is constructed. We use Monte Carlo method to compute the area of the workspace. The GDI index is calculated by approximating the integral to the sum of the values on a uniform grid. As a result, the Pareto-optimal set is calculated for one of the parameters of the robot, which is the solution of the problem. There was created software package, which includes visualization of the robot workspace, the dependence of the robot condition number on various parameters of the 2- RPR robot and plot of Pareto-optimal solution.

Research target: Mathematics
Priority areas: IT and mathematics
Language: Russian
Text on another site
Keywords: многокритериальная оптимизацияsingularityсингулярностьрабочая область робота multi-objective optimizationparallel robotworkspace areaпараллельный робот
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