Статьи

The paper presents an option for determination of phase loads in the primary distribution network using the results of state estimation of the secondary distribution network that are obtained by smart meter measurements installed at the load and generator nodes. The problem of state estimation in the secondary distribution network based on measurements of the active and reactive nodal powers and voltage magnitudes rather than by the Newton method traditionally used for this purpose is solved by a method of simple iterations. Efficiency of using the proposed approach for determination of phase loads of the primary distribution network for each hour of daily curve of nodal powers is illustrated by the example of a 32-node test network.

The paper presents the background of creation and development of Mongolia’s electric power industry and its current state. Despite considerable energy resources, the country suffers from electric power shortage that is covered by electricity supplied from Russia and China. The expected considerable power consumption growth can be met by doubling generating capacities, enhancing electrical networks and by interconnecting the five existing electric power systems (EPSs) into an Integrated Power System (NPS) of Mongolia as a future component of the Northeast Asian Super Grid. To accomplish these tasks, we propose a number of conceptual structural and technological models for the development of Mongolian electric power systems that can form a basis for the future Integrated Power System of Mongolia.

The progressing distribution of the electricity supply necessitates redesigning the mechanism for providing ancillary services particularly by the distribution grid. Methods of voltage regulation and congestion management particularly have to satisfy new standards since, although the development of renewables is increasing the number of resources with an impact, these resources’ individual contribution is comparatively slight. Taking the state-of-the-art and the basic regulatory conditions in Germany as a point of departure, this paper analyzes the requirements for algorithms and communication systems that provide distributed support to distribution grid operation. A novel mathematical method that prevents voltage range deviations and feeder overloads based on sensitivities is presented and validated in simulations by a case study. An analysis of the communications systems for monitoring and control technologies for distributed energy resources, including the available communication channels, serves as the basis for an evaluation of the suitability of current control mechanisms in the future. The findings of a live field test in a real 110 kV distribution grid corroborate the necessity for coordinated grid support by distributed energy resources and demonstrate the limits of current methods.

In recent years, artificial intelligence methods have been developed in various fields, particularly in education. The development of computer systems for student learning is an important task and can significantly improve student learning. The development and implementation of deep learning methods in the educational process has gained immense popularity. The most successful among them are models that consider the multimodal nature of information, in particular the combination of text, sound, images, and video. The difficulty in processing such data is that combining multimodal input data by different channel concatenation methods that ignore the heterogeneity of different modalities is an inefficient approach. To solve this problem, an inter-channel attention module is proposed in this paper. The paper presents a computer vision-linguistic system of student learning process based on the concatenation of multimodal input data using the inter-channel attention module. It is shown that the creation of effective and flexible learning systems and technologies based on such models allows to adapt the educational process to the individual needs of students and increase its efficiency.

This article continues the cycle of works by the authors devoted to the problem of the age of information (AoI), a metric used in information systems for monitoring and managing remote sources of information from the control center. The theoretical analysis of information transmission systems requires a quantitative assessment of the “freshness” of information delivered to the control center. The process of transferring information from peripheral sources to the center is usually modeled using queuing systems. In this paper, a queuing system with phase-type distributions is used to estimate the maximum value of the information age, called the peak age. This takes into account the special requirement of the transmission protocol, which consists in the fact that information enters the system in groups of random size. For this case, an expression is obtained for the Laplace–Stieltjes transformation of the stationary distribution function of the peak age of information and its average value. Based on the results of analytical modeling, a numerical study of the dependence of the average value of the peak age of information on the system load was carried out. The correctness of the expressions obtained was verified by comparing the analytical results with the results of simulation modeling.

In this article, we propose fourth- and fifth-order two-step iterative methods for solving the systems of nonlinear equations in

В статье рассмотрена специфика digital-маркетинга, включая его основные инструменты для привлечения клиентов, влияние на потребителей, а также преимущества и недостатки этой формы маркетинга. Особое внимание автор уделяет тому, каким образом digital-маркетинг помогает компаниям результативно взаимодействовать с аудиторией через различные цифровые инструменты, какие преимущества и риски связаны с использованием такого подхода.

Relevance. Africa presents a unique case: despite having the lowest urbanization levels in the world, it demonstrates the highest rates of urban population growth. Universities in large African cities play a key role in developing human capital by providing educational opportunities and training in digital skills necessary for participation in the digital economy. Objective. This article aims to assess the relationship between digital higher education, a key component of human capital, and economic development in African countries. It also explores the Digital Education Index and the factors influencing it in African cities and countries. We hypothesize that the composite Digital Education Index will reveal connections between economic development, urbanization, digital infrastructure, and digital education. Data and Methods. The study uses data from African cities and countries for 2019-2022, sourced from Trading Economics, the World Bank, International Monetary Fund, Free Apply, UNESCO, and the World Intellectual Property Organization. The methodology is based on an index approach, using measures of central tendency. The Digital Education Index is calculated through three sub-indices: technical accessibility of digital technologies, financial-economic accessibility of digital education, and population digital skills. Results. Digital education contributes to human capital development in Africa while reducing inequality and social vulnerability. However, progress in improving the Digital Education Index has been limited, as African universities face challenges such as restricted technology access and low living standards, which limit access to paid education. Conclusion. The study provides policy recommendations highlighting the importance of a comprehensive approach to addressing the challenges of digital education development in Africa.

Relevance. The adoption of new technologies and the rapid emergence of innovation spur high-tech production and export-led economic growth. We aim to provide fresh evidence on the determinants of high-tech exports, considering different macroeconomic factors within the framework of the gravity model. Research Objective. The aim of the research is to empirically assess the impact of macroeconomic instability, tax policies, natural resources endowment, human capital, and institutional environment on the promotion of high-tech exports. Data and Methods. In considering the institutional indicator, six distinct indices from the World Bank are examined, and a common indicator is computed using principal component analysis. The econometric modeling uses a panel dataset covering the world’s 80 largest economies from 1996 to 2019. To test the assumptions of the gravity model and tackle the heteroscedasticity problem, the Poisson Pseudo Maximum Likelihood methodology is employed. Results. Higher inflation and unemployment rates are found to significantly decrease high-tech exports, while government external debt contributes to their enhancement. Tight tax policy and an increase in tax contribution are counterproductive in spurring high-tech exports. A negative and significant result is found for resource endowment, indicating that an increase in resource exports is counterproductive for technological advances and high-tech production. In most cases, the institutional environment and human capital significantly promote high-tech exports. Conclusions. Based on the presented empirical findings, we offer recommendations for the government to stimulate high-tech exports.

Relevance. The digital economy and the digitalization of business and public administration are progressing rapidly in Russia. However, significant disparities in ICT access, usage, and outcomes between regions persist, potentially contributing to widening socio-economic inequalities. Research objective. This study aims to demonstrate that digital skills are a key factor in regional development. It tests the hypothesis that regions with disparities in Internet adoption and digital skills also experience disparities in regional development, as reflected in key socio-economic indicators. Additionally, the study analyzes the impact of digital skills on per capita income and unemployment. Data and methods. The study uses data from a sociological survey conducted by the Federal Statistics Service (Rosstat) and the Higher School of Economics to characterize the digital skills of the population. Principal component analysis is applied to construct a composite index, the Internet Adoption Index, which reflects both the accessibility and use of the Internet across Russian regions. This index, alongside digital skills data, is used to group regions. Two-sample t-tests for equal and unequal variances are employed for initial comparisons of regional indicators. In the second stage, regression analysis is used to test the hypothesis that without improved digital skills, access to ICT does not lead to higher personal income or lower unemployment. Results. The study reveals that only 12 out of the considered 83 Russian regions exhibit relatively high levels of Internet adoption and above-average digital skills. Despite well-developed infrastructure, many regions still have low levels of digital proficiency. The age and gender structure of the population have little impact on regional digital skills. However, regions with greater access to the Internet and higher digital skills show higher economic growth, higher incomes, and lower unemployment. Conclusion. The findings provide strong evidence that digital skills are closely linked to socio-economic development. The results highlight the importance of policies aimed at improving digital literacy, particularly as the digital economy continues to expand.

В статье на материале русской культурно-языковой традиции анализируется явление, при котором тот или иной мифологический персонаж ранее не существовал в системе верований, а был порожден языковым знаком или фрагментом текста. По своей природе имена изучаемых персонажей восходят к вербальным знакам двух типов: 1) имена персонажей, образованные от узуальных единиц лексической системы — нарицательных слов (роди́мчик ‘припадок, сопровождающийся судорогами и потерей сознания’ > персонаж Ро́дька) или имен собственных (лес Хéмерово в Архангельской области, топоним > леший Хéмеровский); 2) имена персонажей, имеющие текстовую природу, — это конструкции, синтагмы, которые существуют как взаимосвязанное целое только в составе «материнского» текста, а затем «мигрируют» за его пределы (Лель, И́лия < песенные припевы алё-ле, ай люли). Для возникновения нового персонажа требуется два стимула — собственно языковой (наличие имени, которое «ищет» себе план содержания) и культурный (семиотически насыщенный контекст: ситуация, связанная с опасностью, запретом, предзнаменованием, агрессией, магическими практиками). Комбинация этих стимулов встречается нередко, поэтому мифологическому номинативному фонду практически гарантировано постоянное обновление. Авторы показывают, что творение персонажей на основе языковых стимулов в рамках кабинетной мифологии реализует те же механизмы, что и в рамках «простонародной» традиции.

This paper describes the development of an agile project management system. This research is relevant because of the feature of agile projects consisting of changing requirements. We developed the architecture of the backlog and tasks management system, including a duration prediction module. Using the developed system, managers have the opportunity to divide project processes into sprints depending on the prediction and value for the stakeholders. The authors propose a method for predicting agile project duration by formalising the application of expert Story Point evaluation and subsequent Monte Carlo simulation. Based on the developed method, an algorithm for the dynamic prediction of task duration was designed. Integration of the developed method into the system made it possible to reduce the assumptions and limitations associated with updating user story data and participation in the projects of new and cross-functional teams. The developed system allows managers to cope with agile project bottlenecks.