درخت حوزه‌های تخصصی

The article is devoted to solving the problems of internal economic relations in Ukraine in modern conditions in order to increase the efficiency of their functioning. Studied, systematized and generalized theoretical approaches regarding the features of the interaction of internal and external economic relations, which significantly complement the theory and methodology of the scientific principles of the branch economy. In Ukraine, during the period of restoration of trade and economic relations with the CIS countries and active integration processes in the world economy, the volumes and structure of exports and imports undergo significant changes. In this regard, it is advisable to forecast the export and import in the near future. Conceptual provisions regarding the formation of a national strategy, a mechanism for managing the development of Ukraine’s integration processes on the principles of improving the current legislative and regulatory regulation in the country are proposed. In addition to the convenience for calculations, the hierarchical model also has other significant advantages. So, a high degree of independence of groups from each other makes it extremely flexible.

Security is one of the most important aspects of data transmission. To provide controlled access to the network, user authorization and authentication are often used with the help of an AAA server. RADIUS servers provide users with access to data, user authentication, and configuration information. When designing networks with such access control method implementation, it is necessary to understand how the characteristics of the communication channel affect the switching time of IP-TV channels, and therefore the overall quality of IP-TV services. The principles of the main protocols for IP-TV using a RADIUS server are described. The main parameters of the communication channel were identified. The mathematical model and the graphs demonstrate how IP-TV service access time depends on telecommunication channel parameters. The results of a practical experiment are presented to prove the formed mathematical model. The results of a practical experiment and theoretical calculation are compared.

The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated where it considers eventuality. So, it is necessary to consider the highly data-driven technologies and to use new methods of analysis, like machine learning and visualization tools, with the ability of interaction and connection to different data resources with varieties of data regarding the type of big data aimed at reducing the risks of policy-making institution’s investment in the field of IT. The main scientific contribution of this article is presenting a new approach of policy-making for the now-casting of economic indicators in order to improve the performance of forecasting through the combination of deep nets and deep learning methods in the data and features representation. In this regard, a net under the title of P-V-L Deep: Predictive Variational Auto Encoders - Long Short-term Memory Deep Neural Network was designed in which the architecture of variational auto-encoder was used for unsupervised learning, data representation, and data reconstruction; moreover, long short-term memory was adopted in order to evaluate now-casting performance of deep nets in time-series of macro-econometric variations. Represented and reconstructed data in the generative network of variational auto-encoder to determine the performance of long-short-term memory in the forecasting of the economic indicators were compared to principal data of the net. The findings of the research argue that reconstructed data which are derived from variational auto-encoder embody shorter training time and outperform of prediction in long short-term memory compared to principal data.

Falls are a serious concern among the elderly people, causing severe physical pain to them and placing a strain on medical infrastructure. The global elderly population is expected to grow significantly in the coming years, as advances in healthcare allow lifespans to increase globally. This will bring more chances for falls to occur. With this in mind, there is a need for new research to be conducted on finding ways to reduce this problem. One area which shows promise is the use of Machine Learning to perform fall detection. Machine Learning is a rapidly growing field, and it has many applications in various fields such as finance, technology and medicine. When it comes to fall detection, Machine Learning systems are often able to detect falls much better and efficiently than a human can, given the same input data. The goal of this paper is to conduct a survey study on the main and most common machine learning algorithms implemented in the field of early fall detection for elderly people and the characteristics. The paper will discuss the different types of fall detection systems, algorithms, tools, datasets, applications, and challenges.  By conducting this research, a better understanding of the context, progress and trends in the field will be possible so that future research will have a guide to build upon.

In the digital age, e - learning systems have been employed as new equipment in the higher education system in different universities. Consideringthe importance of optimization of this system, this research is aimed at providing a modelfor the effectiveness of e - learning at in higher education systems . The study is a descriptive survey study in terms of its data collection method . The population includes all the students of electronic courses at the University of Tehran . This population includes 1481 students of the University of Tehran in the academic year 2019 - 2020 . Regarding the population size, 300 students were selectedbased onstratified sampling, using Cochran ’ s formula.Lisrel and Amos softwarewere used for data analysis . In the first step, byliterature review, and based on the collected information, 87 components were identified to be related toe - learning effectiveness . Then, based on the highest frequency of the identified components in one hand, and their significance from the experts ’ viewpoints, on the other hand, 14 components were finally selected and classified in three major classes including;pedagogical, individual and technicalrelated factors.

At this time in history that the world is becoming smaller every day due to globalization; it is important to achieve an acceptable degree of trust and confidence in any field; and blockchain can put the world on this path. Since there is no central authority governing blockchain, its decentralized nature can turn it into an appropriate platform for project management. Implementing blockchain eliminates project management bureaucracies and allows a single, unchangeable, controllable, and encrypted source to be accessible to everybody and extensible throughout the project life cycle. This approach is the key to achieve an integrated information system and is one of the important reasons for blockchain applicability as an ideal platform for project management and construction. This issue that using blockchain technology in project management will bring about capacities and capabilities has not yet been seriously addressed. Changing the management of construction projects by blockchain is just an idea for now. This study aims to identify the capacity and platforms for developing blockchain technology in project management and construction using systematic and scoping literature reviews. Moreover, it provides some suggestions about the development and improvement areas of this technology. The review results showed that in all areas of project management and construction, there are applications relevant to blockchain technology that confirm the gradual understanding of the significance and positive impact of this technology on enhancing project management and construction performance. According to the results, a major part of blockchain studies was focused on “program and project management”, and two fields of human resources and behavioural areas and research in project management and schools of thought with a share of less than 2% of existing studies were neglected.

The influence of disintegration processes on the development of regional trade agreements is revealed. Opportunities and threats to cooperation between Ukraine and the EU within the Deep and Comprehensive Free Trade Area at the state level, for enterprises and the population have been identified. To achieve the aim of the research, the method of hypotheses, the method of developing search questions and questionnaires, the method of expert questionnaire survey of government officials, business community and the scientific community were applied in combination with statistical methods of primary information processing and the software SPSS Statistics 23. The aim of article is to identify threats and opportunities of the Ukraine - EU Free Trade Area and priority forms of cooperation. Ukraine is exposed to disintegration tendencies and destabilizing political processes, influence of loss of control over the most industrially developed eastern territories, disruption and severance of established internal economic ties. The efficiency of cooperation forms in ensuring the stability of international economic relations is estimated. Based on results of the study, practical recommendations were developed for both enterprises (micro-level of international cooperation) and for the government (macro-level). In the context of digitalization and informatization in the global environment and the dynamic growth of the IT sector, international cooperation in this area is becoming especially important. According to the results of the study, Ukraine and the EU have mutual economic interests to develop cooperation in the IT field, which requires support and involvement of both parties in improving regulatory conditions and integration mechanisms.

Information technology is becoming a basic tool for many industries, as well as creating an opportunity for direct active communication of all market participants, which significantly increases competition. As a result, customers have a very large selection of goods and services, fairly easy access to them, and significant price diversification. All this leads to new requirements for modern marketing. Modern marketing significantly changes not only the functions but also the approaches to business processes. A highly competitive environment requires companies to use a system of interconnected marketing tools using an integrated marketing approach. The paper is devoted to investigating advertising prices and advertising strategies of Google. The list of major Google products is analyzed. The relevance of advertising strategies to goals, ad placement, message creation, budget constraints, and ad delivery is determined. The difference in advertising prices in different countries has been studied. The cost per click analysis of European countries is carried out. Using the DEA model analyzed advertisement efficiency by VRS technology and input-oriented efficiency for European countries.