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  • ПРИМЕНЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ЖИЗНЕННОМ ЦИКЛЕ ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ: КАРТА РЕШЕНИЙ ПО ПРОЦЕССАМ
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News
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.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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ПРИМЕНЕНИЕ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В ЖИЗНЕННОМ ЦИКЛЕ ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ: КАРТА РЕШЕНИЙ ПО ПРОЦЕССАМ

Информационное общество. 2027. № 2.
Окусков И. С.
In press

The paper presents a map of domestic artificial intelligence solutions aligned with software life cycle processes and intended to support the selection of tools for automating software development and maintenance. The methodological basis is the process approach and classification by software life cycle process groups. The sample is formed from open data on the Russian software market using criteria of artificial intelligence scope, currency, and relevance to the life cycle. Mapping to process groups is done by matching software classes to processes. The results include a “block — process groups” matrix, distribution of artificial intelligence products across groups, and areas of highest and lowest coverage. The map is aimed at project managers and software architects.

Language: Russian
Full text
Keywords: искусственный интеллект artificial intelligencesoftware life cyclelife cycle processesdecision mapжизненный цикл программного обеспеченияпроцессы жизненного циклакарта решений
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