Keyword: «data processing»

The training of future librarians involves the use of innovative educational tools for the formation of demanded professional competences in accordance with the professional functions and priorities of the development of library science in Russia. The authors study the issue of using AR applications in training of future library specialists to provide additional conditions for the development of demanded digital skills, gaining experience in project- and research-based learning and other educational and cognitive activities; application of the fundamental theory of library science to the organization of cultural events, entertainment events. The purpose of the study is to identify the characteristic features of augmented reality technology use in training specialists in the library and information sphere to improve the quality of their training. The methodology is based on the analysis of the augmented reality technology potential for higher education, to support UNESCO initiatives, while identifying problems of their implementation in training specialists in the library and information sphere. The provisions of the professional standard for a specialist in library and information sphere, the strategy for the development of library science in Russia are taken into account in developing a system of educational tasks based on the AP applications. The following applications and tools were used to support augmented reality technology: Quiver, Star Walk, Mind Map AR, HISTARS, BBC Civilizations AR, AR Ruler, Arloon chemistry, Arloon geometry, ZOME, JigSpace, SketchAR, etc. As the results, the ideas of a methodological approach reflecting the necessary changes in the system of training highly qualified specialists in the library and information sphere are described, taking into account the provisions of the professional standard and the directions of the strategy for the development of library science in Russia. The conclusions are drawn about the characteristics of AR technology use in the work of a librarian (visualization of information, establishment of temporary and emotional connections, etc.). Methodological and technical difficulties of the proposed innovations are also formulated: high cost, technical failures of equipment in libraries. The obtained results can be used for the organization of cognitive research activities of students; in the work of museum-library type institutions.

The article reveals the problem of identifying operational risk and the main risk management factors. The study proves that modern market relations of various commercial organizations have led to the fact that risks have become an integral part of banking operations.

This article examines the synergy of computer science and mathematics through the prism of an interdisciplinary approach to studying Cauchy sequences and describes how the interaction of mathematical theories and algorithmic practices allows us to create more efficient and robust algorithms for solving complex problems. The article analyzes the use of Cauchy sequences in various areas of computer science, such as numerical computing, data processing and machine learning, and emphasizes the importance of a mathematical foundation for the development of algorithmic thinking. Conversely, examples of the practical application of an interdisciplinary approach are analyzed, demonstrating how the synergy of the two sciences can lead to new discoveries and innovations. But this is possible only if there is a developed skill of independent problem solving, using a variety of tools. Thus, the article talks not so much about an interdisciplinary approach, but about the formation of universal literacy of students through the synthesis of mathematics and computer science. This article explores the interaction between the mathematical concept of the Cauchy sequence and its application in computer science, especially in the context of algorithmic thinking. At the same time, both mathematics and computer science are considered in the dominant format, that is, the role of each of the subjects is not reduced to the level of a tool. That is, on the one hand, the article reveals mathematical principles that help to form clear and effective algorithmic solutions in programming and data analysis. On the other hand, machine learning and optimization algorithms help to improve mathematical calculations in data processing. Thus, the article includes examples of the application of Cauchy sequences in various areas of computer science, such as numerical methods, machine learning and data processing. The main approaches to teaching algorithmic thinking are also discussed, with an emphasis on the importance of a mathematical foundation. This article presents the mutual penetration of two disciplines, with an attempt to maintain a balance between them, without translating into a tool format.