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Subject
News
July 24, 2026
‘I Like Self-Fulfilling Prophecies
Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.

 

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Исследование возможности применения генетических алгоритмов к решению задач планирования работы электроподвижного состава метрополитена

Электроника и электрооборудование транспорта. 2017. № 6. С. 37–40.
Чжо М. А., Sidorenko V.

This paper is a part of continuation publications on the topic of genetic algorithms application to the scheduling of underground rolling stock maintenance. The authors implemented the adaptive crossover selection algorithms within the genetic algorithm framework according to the features of the scheduling problem. Then the authors investigated the possibilities of genetic algorithm by using the different crossover types in solving rolling stock scheduling problem, and the influence of parameters in genetic algorithm on the results obtained. The results of genetic algorithm application are described.

Research target: Computer Science Economics and Management Construction Mechanics and Mechanical Engineering Effective Natural Resource Management
Priority areas: management IT and mathematics business informatics engineering science
Language: Russian
Full text
Keywords: оптимизацияoptimizationтехническое обслуживаниепланированиеschedulingгенетический алгоритмgenetic algorithmelectrical rolling stockэлектроподвижной составtechnical maintenance
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