Scientific Journal of KubSAU

We are developing a new organizational-economic theory - solidary information economy, based on the views of Aristotle. The name of this theory has changed over time. Initially, we used the term "nonformal information economy of the future", and then began to use the term "solidary information economy." In connection with Biocosmology and neo-Aristotelism preferred is an adequate term "functionalist organic information economy". This article summarizes the first phase of work on the solidary information economy. We have analyzed the array of publications. The main problems are discussed, the solution of which is devoted to research related to the considered basic organizational and economic theory. The founder of the economic theory is Aristotle. We discuss Aristotle's positions, on which the economic theory is based, in particular, solidary information economy. We prove that the market economy has remained in the XIX century and the mainstream in modern economic science - justification of insolvency of a market economy and the need to move to a planned system of economic management. We examine the impact of ICT on economic activity. We develop the approaches to decision-making in the solidary information economy. On the basis of modern decision theory (especially expert procedures) and informationcommunication technologies people can get rid of chrematistics and will understand the term of "economy" according to Aristotle

Adequate and effective assessment of the efficiency, effectiveness and the quality of scientific activities of specific scientists and research teams is crucial for any information society and a society based on knowledge. The solution to this problem is the subject of scientometrics and its purpose. The current stage of development scientometrics differs greatly from his previous appearance in the open as well as paid on-line access to huge amount of detailed data on a large number of indicators on individual authors and on scientific organizations and universities. The world has well-known bibliographic databases: Web of Science, Scopus, Astrophysics Data System, PubMed, MathSciNet, zbMATH, Chemical Abstracts, Springer, Agris, or GeoRef. In Russia, it is primarily the Russian scientific citing index (RSCI). RSCI is a national information-analytical system, accumulating more than 9 million publications of Russian scientists, as well as the information about citation of these publications from more than 6,000 Russian journals. There is too much information; it is so-called "Big data". But the problem is how to make sense of these large data, more precisely, to identify the meaning of scientometric indicators) and thus to convert them into great information ("great information"), and then apply this information to achieve the objective of scientometrics, i.e. to transform it into a lot of knowledge ("great knowledge") about the specific scientists and research teams. The solution to this problem is creating a "Scientific smart metering system" based on the use of the automated system-cognitive analysis and its software tools – an intellectual system called "Eidos". The article provides a numerical example of the creation and application of Scientometric intelligent measurement system based on a small amount of real scientific data that are publicly available using free on-line access to the RSCI

In various applications, it is necessary to analyze several expert orderings, i.e. clustered rankings objects of examination. These areas include technical studies, ecology, management, economics, sociology, forecasting, etc. The objects can be some samples of products, technologies, mathematical models, projects, job applicants and others. In the construction of the final opinion of the commission of experts, it is important to find clustered ranking that averages responses of experts. This article describes a number of methods for clustered rankings averaging, among which there is the method of Kemeny median calculation, based on the use of Kemeny distance. This article focuses on the computing side of the final ranking among the expert opinions problem by means of median Kemeny calculation. There are currently no exact algorithms for finding the set of all Kemeny medians for a given number of permutations (rankings without connections), only exhaustive search. However, there are various approaches to search for a part or all medians, which are analyzed in this study. Zhikharev's heuristic algorithms serve as a good tool to study the set of all Kemeny medians: identifying any connections in mutual locations of the medians in relation to the aggregated expert opinions set (a variety of expert answers permutations). Litvak offers one precise and one heuristic approaches to calculate the median among all possible sets of solutions. This article introduces the necessary concepts, analyzes the advantages of median Kemeny among other possible searches of expert orderings. It identifies the comparative strengths and weaknesses of examined computational ways

In 2011 – 2015, the scientific community was represented by a new paradigm of mathematical methods of research in the field of organizational and economic modeling, econometrics and statistics. There was a talk about a new paradigm of applied statistics, mathematical statistics, mathematical methods of economics, the analysis of statistical and expert data in problems of economics and management. We consider it necessary to develop organizational and economic support for solving specific application area, such as the space industry, start with a new paradigm of mathematical methods. The same requirements apply to the teaching of the respective disciplines. In the development of curricula and working programs, we must be based on a new paradigm of mathematical methods of research. In this study, we present the basic information about a new paradigm of mathematical methods of research. We start with a brief formulation of a new paradigm. The presentation in this article focuses primarily on the scientific field of "Mathematical and instrumental methods of economy", including organizational and economic and economic-mathematical modeling, econometrics and statistics, and decision theory, systems analysis, cybernetics, operations research. We discuss the basic concepts. We talk about the development of a new paradigm. We carry out a detailed comparison of the old and the new paradigms of mathematical methods of research. We give information about the educational literature, prepared in accordance with the new paradigm of mathematical methods of researches

Some estimators of the probability density function in spaces of arbitrary nature are used for various tasks in statistics of non-numerical data. Systematic exposition of the theory of such estimators has been started in our articles [3, 4]. This article is a direct continuation of these works [3, 4]. We will regularly use references to conditions and theorems of the articles [3, 4], in which introduced several types of nonparametric estimators of the probability density. We have studied linear estimators. In this article, we consider particular cases - kernel density estimates in discrete spaces. When estimating the density of the one-dimensional random variable, kernel estimators become the Parzen-Rosenblatt estimators. Under different conditions, we prove the consistency and asymptotic normality of kernel density estimators. We have introduced the concept of "preferred rate differences" and are studied nuclear density estimators based on it. We have introduced and studied natural affinity measures which are used in the analysis of the asymptotic behavior of kernel density estimators. Kernel density estimates are considered for sequences of spaces with measures. We give the conditions under which the difference between the densities of probability distributions and of the mathematical expectations of their nuclear estimates uniformly tends to 0. Is established the uniform convergence of the variances. We find the conditions on the kernel functions, in which take place these theorems about uniform convergence. As examples, there are considered the spaces of fuzzy subsets of finite sets and the spaces of all subsets of finite sets. We give the condition to support the use of kernel density estimation in finite spaces. We discuss the counterexample of space of rankings in which the application of kernel density estimators can not be correct

We consider an approach to the transition from continuous to discrete scale which was defined by means of step of quantization (i.e. interval of grouping). Applied purpose is selecting the number of gradations in sociological questionnaires. In accordance with the methodology of the general stability theory, we offer to choose a step so that the errors, generated by the quantization, were of the same order as the errors inherent in the answers of respondents. At a finite length of interval of the measured value change of the scale this step of quantization uniquely determines the number of gradations. It turns out that for many issues gated it is enough to point 3 - 6 answers gradations (hints). On the basis of the probabilistic model we have proved three theorems of quantization. They are allowed to develop recommendations on the choice of the number of gradations in sociological questionnaires. The idea of "quantization" has applications not only in sociology. We have noted, that it can be used not only to select the number of gradations. So, there are two very interesting applications of the idea of "quantization" in inventory management theory - in the two-level model and in the classical Wilson model taking into account deviations from it (shows that "quantization" can use as a way to improve stability). For the two-level inventory management model we proved three theorems. We have abandoned the assumption of Poisson demand, which is rarely carried out in practice, and we give generally fairly simple formulas for finding the optimal values of the control parameters, simultaneously correcting the mistakes of predecessors. Once again we see the interpenetration of statistical methods that have arisen to analyze data from a variety of subject areas, in this case, from sociology and logistics. We have another proof that the statistical methods - single scientificpractical area that is inappropriate to share by areas of applications

The article begins with the letter of the chief engineer of chemical plant near Moscow. He requests to analyze of data by means of modern statistical methods and give an opinion on the presence (or absence) of the relationship between the two methods of determining the viscosity of the mastic. For each of the batches of mastic It was presented two numbers - the viscosity measurement results of the two methods. These numbers form two paired samples. We want to install, give whether two specific methods similar results. The true values of viscosity in different batches are not equal. Their difference is not allows us to combine the results of the first measurement method in first sample, the results of the second method - in the second sample, as we can do in the case of testing the homogeneity of two independent samples. For solutions to this problem we discuss four statistical criterions, based on a study of the differences between corresponding values in two paired samples. We test the hypothesis of equality 0 of median of these differences (sign test) and of equality 0 of the mathematical expectation of these differences. Hypothesis of testing of equality of the distribution functions of two paired samples is reduced to the hypothesis of symmetry of the distribution function of these differences with respect to 0. In the alternative of the shift is proposed to use the Wilcoxon signed rank criterion. In the total alternative is proposed to use criterion of the omega-square type which is developed by the author of this article

In modern conditions of quantitative and qualitative degradation of science in general and economics in particular, especially in our country, the scientific direction of "Controlling" stands out not only for its activity, but also the rapid intensive and extensive growth. This work is the summary of the main publications of scientific results on controlling obtained at the Laboratory of economicmathematical methods in controlling of Scientific and Educational Center "Controlling and management innovations" of Bauman Moscow State Technical University. We discuss the concept of "method", "tool", "mechanism", "algorithm" in relation to the Controlling. Adequate use of these terms is necessary for the formulation of sound scientific results, and to provide their perception of the scientific community. Innovations in the field of management in industry and other sectors of the economy based, in particular, on the use of new adequate organizational and economic methods. Controlling in this area - it is the development of relevant management procedures used and the newly established (implanted) organizational and economic methods to the task. Development, systematization and application of modern mathematical tools of controlling are the main theme of our work. We have considered the problems of controlling new areas - controlling risks, quality controlling, controlling organizational and economic support for control tasks in the aerospace industry, controlling research activities. We have also obtained new scientific results in controlling personnel and ecological safety controlling

The article is devoted to the discussion of the organization of clinical-statistical studies and experiments. We have considered the examples of the application of statistical methods in scientific medical research. Under the clinical-statistical research we understand specially organized collection and analysis of medical data about the course of disease in patients, research of the dynamics of objective and subjective indicators of the state of reaction to these or other therapeutic effects. We study one, two or more groups of individuals (patients or healthy), conclusions are drawn on the whole group, but not for each individual patient. The purpose of research - to transfer the conclusions reached for the sample to the general population, i.e., clinical and statistical study focused on the production of useful recommendations concerning those patients who fall into the field of view of doctors after the end of the study. There are two main types of research - prospective and retrospective. The first related to the analysis of the last patients, the second - to monitoring the course of their disease in the future. We have considered typical mistakes in the organization of clinical-statistical studies. When planning a research, we usually distinguish the experimental and control groups, which are identical or similar in all respects except for the studied factors (exposure). We discuss the various options for blind methods and consider the application of statistical models and methods in scientific medical research. We have analyzed examples of confidence estimation of proportion (probability) and the homogeneity test of probabilities. For statistical modeling we use the Poisson distribution in the case of small probability. With its help, we analyze statistical data on the opisthorchiasis

We consider the methods for estimation of the effectiveness and quality of the scientific activities of the researcher, of the organization, of the magazine. Performance indicators of scientific activity are used as an important part in the estimation of higher education institutions, the innovative capacity of enterprises, etc. To estimate the effectiveness of scientific activity is natural to use intellectual tools which are well-established in other subject areas. This will include, in particular, the balanced scorecard, based on key performance indicators (hence the title of this article), as well as controlling, primarily controlling of research activities. There are two more developed and widely used types of tools for estimation the effectiveness of the scientific activity - the scientometric indicators and the expert estimators. Their critical analysis is the subject of this article. The goal - to choose the most effective tool. Different versions of manipulating of values of scientometric indicators in the Russian Federation, in our estimation, are still relatively rare. Perhaps this is due to the relatively short period of their use in the management of science. Since an indicator such as citation index (the number of citations of publications) of researcher, allows estimating its contribution to science, the use of this scientometric indicator for the management of science is justified. At the same time, the number of publications and especially h-index is not possible to objectively estimate the effectiveness of research activities, particularly in view of the properties of the real bibliometric databases. Expert procedures have several disadvantages. In this article we discuss the real effectiveness of expert procedures in the areas of their application, as conferring academic degrees and elections to the National Academy of Sciences (primarily in the Russian Academy of Sciences), as well as appointments to senior positions. The basic principles of expertise in these areas remain the same for the past 70 years. Based on an analysis of practice it is necessary to ascertain the lack of efficacy of expert estimators in these areas. Rationale to what has been said is given in the article