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Subject
News
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.
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.

 

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Алгоритмы и программное обеспечение автоматизации процессов измерений и обработки данных оперативной диагностики ионосферы и ионосферных радиолиний

Журнал радиоэлектроники. 2022. № 10.
Shiriy A.

The article contains the main architectural principles and technical solutions in the development of the software part of the hardware and software complex for the operational diagnostics of the ionosphere and ionospheric radio channels, mainly through remote ground-based radiosonding. A brief description of measurement techniques and measuring equipment is given. The tasks of automating the measurement process itself and data recording have been solved, which allow organizing the work of the complex according to a given schedule without direct human participation. The tasks of extracting information from the obtained experimental data of radiosonding and ionosphere diagnostics have also been solved, including the possibilities for working with the hierarchy of experimental data, including the possibility of degeneration of derived data, the possibility of viewing available data and the possibility of batch processing of large data arrays to obtain and study their statistical characteristics. The organization of processing when collecting statistics of variations of intermode delays, amplitude-frequency characteristics of partial modes of propagation of short waves, as well as classification of these data according to the so-called empirical multipath models are considered; examples of results are given. The prospects and preliminary results of applying the achievements of the machine learning to solve the problems of automating the extraction of information from radiosonding data are shown; the software of marking data for the formation of training samples is described. The plans for further research are the development of quality metrics and the choice of optimal architectures of deep neural networks, as well as the development of markup tools, including instruments of cross-monitoring the results.

Research target: Computer Science Earth Sciences Electronics and Electrical Engineering
Language: Russian
DOI
Text on another site
Keywords: автоматизация измеренийобработка ионограмм
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