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June 2, 2026
Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan
On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.

 

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Оценка эффективности инвестиционных проектов с государственным участием

Вестник Удмуртского университета. Серия 2: Экономика и право. 2017. Т. 27. № 6. С. 31–40.
Kosov M.

The main factor of economic growth of developing countries is the implementation of investment projects by economic entities, oriented to the growth of key performance indicators, attraction of labor resources, modernization and development, reducing production risks and increasing the investment attractiveness. However, the main disadvantages of current models of assessment of investment projects with state support are the lack of consideration of alternative financing sources, the inability to use the script approach in the analysis of project cash flows. This study presents a selection of the optimal model for an investment project, allowing to reduce the risk of probability of default, reduce the expected losses for the state (in the case of damages resulting from the occurrence of a warranty event), to reduce the probability of the expected deficit in the framework of the project tax revenues to the budget of the appropriate level. Implementation of these measures involves the use of scenarios and probabilistic approach that allows considering all possible alternatives to the investment project and the subsequent implementation of this measure allows to increase the efficiency of using budgetary funds.

Priority areas: economics
Language: Russian
Text on another site
Keywords: инвестицииналогибюджетэкономикаeconomyбюджетное финансированиепроизводство стали investmentsgovernment funding taxes budgetmining and production of coalsteel productionдобыча и производство угля
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