The purpose of the article is to study, analyze and consider the general problems and prospects of developing software for trading RodOfEbisu with the possibility of automated trading based on a recommendation algorithm. The research methods are the basic methodologies and algorithms for successful trading. The article considers approaches to the development and operation of software for automated trading. The novelty of the research is the analysis of modern trading methods in different markets, the results of which can be used in the development of its own trading automation product, which is an assistant and, possibly, can become an independent unit. Conclusions. The paper investigates the existing views on the modern approach to decision-making and buying, which can be used to develop its own product – a trader’s assistant. Taking into account the results of the analysis, it was decided to develop software for trading RodOfEbisu, which can act as an advisor and executor, with the possibility of using different trading strategies.

The high incidence of children with recurrent episodes of acute obstructive bronchitis is a widespread problem. Correct identification of children at risk of developing bronchial asthma at school age may improve treatment and prevention approaches to this pathology, but the ability to identify these children remains limited. The purpose of the study was to determine the effectiveness of recombinant interferon alpha-2β in children with recurrent episodes of acute obstructive bronchitis in the course of treatment based on the assessment of cytokine profile. The study examined 59 children of the main group with recurrent episodes of acute obstructive bronchitis and 30 children of the comparison group who suffered from acute bronchitis, aged 2 to 8 years, who were in the hospital. The results of laboratory studies were compared with the data of 30 healthy children. In children with recurrent episodes of acute obstructive bronchitis, the content of serum interferon-γ and interleukin-4 was significantly reduced compared to healthy children, after treatment with recombinant human interferon alpha-2β, the content of interferon-γ and interleukin-4 in children significantly increased. The content of interleukin-1β in children with recurrent episodes of acute obstructive bronchitis was significantly higher than in healthy children, after immunomodulatory therapy with recombinant interferon alpha-2β, interleukin-4 normalised to its level in healthy children. It was found that children with recurrent episodes of acute obstructive bronchitis have an imbalance of cytokines, the effectiveness of recombinant human interferon alpha-2β therapy, which normalised the levels of the studied cytokines in the serum.

The article deals with current problems of ontological modeling of processes of design, construction and operation of buildings and structures in transport infrastructure. Such modeling involves use of standards and classifiers adopted in Europe and harmonized within BIM (Building Information Modeling) and EULYNX (European railway technology alliance). Multi-level ontological model of transport infrastructure is proposed. This model contributes to formation of understanding of essence of subject area, which is the field of transport infrastructure (transport repair enterprises, transport facilities (bridges, tunnels, tracks), transport depots, stations, etc.). Proposed model contributes to presentation of knowledge in form that is convenient for their processing in intelligent systems, ensuring intellectualization and digitization of processes in transport infrastructure. Proposed ontological approach ensures multiple use of knowledge and existing ontologies, allows the use of modern technologies (in particular, semantic ones), when objects of subject area correspond to their reflections in multi-level ontological model. Ontological approach to modeling of transport infrastructure makes it possible to move to automatic management of these objects and corresponding processes in systems that ensure intellectualization and digitalization of transport and transport infrastructure. Developed multi-level ontological model is planned to be supplemented with new components, imposing appropriate restrictions.

This paper considers the application of a method for maximizing polynomials in order to find estimates of the parameters of a multifactorial linear regression provided the random errors of the regression model follow an exponential power distribution. The method used is conceptually close to a maximum likelihood method because it is based on the maximization of selective statistics in the neighborhood of the true values of the evaluated parameters. However, in contrast to the classical parametric approach, it employs a partial probabilistic description in the form of a limited number of statistics of higher orders. The adaptive algorithm of statistical estimation has been synthesized, which takes into consideration the properties of regression residues and makes it possible to find refined values for the estimates of the parameters of a linear multifactorial regression using the numerical Newton-Rafson iterative procedure. Based on the apparatus of the quantity of extracted information, the analytical expressions have been derived that make it possible to analyze the theoretical accuracy (asymptotic variances) of estimates for the method of maximizing polynomials depending on the magnitude of the exponential power distribution parameters. Statistical modeling was employed to perform a comparative analysis of the variance of estimates obtained using the method of maximizing polynomials with the accuracy of classical methods: the least squares and maximum likelihood. Regions of the greatest efficiency for each studied method have been constructed, depending on the magnitude of the parameter of the form of exponential power distribution and sample size. It has been shown that estimates from the polynomial maximization method may demonstrate a much lower variance compared to the estimates from a least-square method. And, in some cases (for flat-topped distributions and in the absence of a priori information), may exceed the estimates from the maximum likelihood method in terms of accuracy

The article discusses an ontological approach to solving the problem of forming state policy of economic development of cultural and creative industries and the corresponding intellectual-information management systems. The purpose of this article is to develop an effective toolkit (based on ontologies) for making optimal decisions in the field of state regulation of the cultural and creative industries, taking into account the dynamic factors of the external environment. The ontological approach considered in the article assumes the presence of three levels of models: meta-ontology, models of subject areas of cultural and creative industries and models of making appropriate management decisions on the formation of economic development policy of cultural and creative industries. The novelty of the proposed approach lies in the purposeful nature of ontological modeling of such complex system as the state policy of economic development of cultural and creative industries. The system under consideration has certain goals, tasks, resources, processes, factors of influence, risks and other characteristics. These characteristics include, in particular, the structure of the model, the ability to highlight the essential objects of real relations of the considered subject areas, the ability to represent knowledge for the joint work of specialists in computer modeling, the processing of expert knowledge and the generation of management decisions within the framework of the corresponding intellectual-information systems.