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Subject
News
June 19, 2026
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
June 5, 2026
'Im Used to Producing Distilled Knowledge'
Ivan Rubachev works in a HSE University laboratory established jointly with Yandex Research, where he focuses on machine learning with tabular data. In this interview with the HSE Young Scientists project, he discusses why following a vibe can be better than goal-setting, explains the concept of the Neural Turing Machine, and argues why withholding scientific knowledge is counterproductive.
June 17, 2026
Population Lifespan Is Governed by Mathematical Laws
Researchers at HSE University and MSU have established a universal law governing the time to extinction of a population in a random environment. Their analysis of the evolution of branching processes—complex probabilistic systems—shows that, regardless of the initial population size, extinction follows strict mathematical laws. The results have been published in the Journal of Applied Probability.

 

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Identification of JPEG files fragments on digital media using binary patterns based on Huffman code table

P. 137–141.
Sorokin A., Ekaterina Makushenko

File fragmentation proves to be a major challenge for the majority of file carving techniques. Following the works of Simson Garfinkel, Nasir Memon and other authors we seek to find a technique to identify digital fragments (clusters or sectors) of JPEG-files on the digital storage medium or at least sort all the fragments of the storage based on their probability of being the part of JPEG-file from the most probable to the least probable. This paper offers the technique of identifying clusters of JPEG-files on the storage medium based on binary patterns and the experimental results of an attempt to build a similar technique for sector identifying.

Language: English
DOI
Keywords: JPEGfragmentationfile recoveryHuffman code table

In book

2016 Third International Conference on Digital Information Processing, Data Mining, and Wireless Communications (DIPDMWC)
M.: IEEE, 2016.
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