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July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
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Detection types of steganographic attacks based on semi-fragile watermarks using machine learning

P. 1–4.
Isaeva M. N.

This article discusses how to detected types of steganographic attacks on digital images using semi-fragile watermarks using machine learning techniques. This article discusses different methods of introducing watermarks: into the spatial domain and the transformation domain. The attacks in this case are filters that can be applied to images: blurring, adding noise, sharpness, contrast, color balance. Methods have been identified that allow you to determine with higher accuracy the specific type of attack on the embedded digital watermark in the image. The peculiarity of this method is that the original image does not need to be used to determine the attack (blind method [1]).

Language: English
DOI
Keywords: digital watermarkssteganographydigital imagessemi-fragile watermarksimage filters

In book

WAVE ELECTRONICS AND ITS APPLICATION IN INFORMATION AND TELECOMMUNICATION SYSTEMS. 2021. (WECONF 2021) St. Petersburg, Russia, 31 May - 4 June 2021
IEEE, 2021.
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