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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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?

BIG DATA-DRIVEN DIGITAL ECOSYSTEM FRAMEWORK FOR RAILWAY REPORTING

Ch. 70. P. 0499–0509.
Suleykin, A., Panfilov, P.

In our application research, we propose a Digital Ecosystem approach to overcome data integration, orchestration and quality challenges in railway reporting system using Big Data technologies. We are building a Digital Ecosystem Framework consisting of different Agents, where each Agent is an essential part of the Railway Reporting Management System. In this work, we address different problems in building digital ecosystem including integration problems, orchestration problems and data quality problems. We present a proprietary solution called the Digital Ecosystem Reporting Framework (DERF) for building robust, reliable, fault-tolerant, scalable and high-loaded data pipelines of the Railway Reporting Management System based on Big Data technologies. DERF integrates different Digital Agents such as main ETL-pipeline Agents, technical data quality Agents, business data quality Agents, BI-services integration Agents and high-level data orchestration Agent. A test implementation of DERF has been performed for Railway Reporting Management System using KPI reporting data of the real Railway company.

Language: English
DOI
Text on another site
Keywords: big datadigital ecosystemdata processing pipelinerailway reporting management system

In book

Annals of DAAAM and Proceedings of the International DAAAM Symposium
Vol. 31(1): Proceedings of the 31st International DAAAM Virtual Symposium ''Intelligent Manufacturing & Automation''. , Wien: DAAAM International Vienna, 2020.
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