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Subject
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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ПОИСК ПУТЕЙ СОВЕРШЕНСТВОВАНИЯ ЦИФРОВОГО ПРЕДСТАВЛЕНИЯ ТЕКСТИЛЬНЫХ МАТЕРИАЛОВ С ЦЕЛЬЮ ОБНАРУЖЕНИЯ ДЕФЕКТОВ

Известия высших учебных заведений. Технология текстильной промышленности. 2022. № 2 (398). С. 104–108.
Карева Т. Ю., Мирошниченко Д. А., Голубеева Г. И., Болсуновская М. В., Бойков А. В., Lodyshkin A.

The article discusses the possibility of using neural network technologies for the automated search for defects in textile materials. A developed laboratory stand is presented, where samples are photographed to form a training sample. A number of studies have been conducted on the influence of various types of illumination of the material when obtaining an image from the camera. A study was performed on the effect of changing the camera angle relative to the fabric sample. Various options for eliminating the undesirable image distortion are proposed.

Research target: Computer Science Electronics and Electrical Engineering
Language: Russian
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DOI
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Keywords: контроль качестванейронная сетьquality controlimage processing ARTIFICIAL NEURAL NETWORKSкомпьютерная обработка изображенийDEFECTS OF TEXTILE MATERIALSДефекты текстильных материалов
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