Scientific Journal of KubSAU

The quality of a system is seen as an emergent property of systems, due to their composition and structure, and it reflects their functionality, reliability and cost. Therefore, when we speak about quality management, the purpose of management is the formation of pre-defined system properties of the object of management. The stronger the object of the control expresses its system properties, the stronger the nonlinearity manifests of the object: both the dependence of the management factors from each other, and the dependence of the results of the action of some factors from the actions of others. Therefore, the problem of quality management is that in the management process the management object itself changes qualitatively, i.e. it changes its level of consistency, the degree of determinism and the transfer function itself. This problem can be viewed as several tasks: First is the system identification of the condition of the object of management, 2nd – making decisions about controlling influence that changes the composition of the control object in a way its quality maximally increases at minimum costs. To solve the 2nd problem we have proposed an application of the component selection of the object by functions based on the resources allocated for the implementation of different functions; costs associated with the choice of the components and the degree of compliance of various components to their functional purpose. In fact, we have proposed a formulation and a solution of the new generalization of a variant of the assignment problem: "multi backpack", which differs from the known with the fact that the selection has been based not only on the resources and costs, but also with taking into account the degree of compliance of the components to their functional purpose. A mathematical model, which provides a solution to the 1st problem, and reflecting the degree of compliance of the components to their functionality, as well as the entire decision-making process for selections, i.e. 2nd task, has been implemented in the ASC-analysis and in the system called "Eidos" X++". The article also provides a simplified numerical example of the proposed approach with the selection of staff members

Recently, the process of monetization of the evaluation of scientific activity was initiated, and there is a need for quantitative methods and comparable assessment of the effectiveness and quality of work of a scientist. There are numerous methods to reward for these results. What is common to all these techniques covered is the role of the Hirsch index or h-index. By itself, this index is well founded. However, in connection with the practice of application of h-index in our environment in the minds of the scientific community it has started some kind of mania, which the author proposes to call "Hirsch-mania". This mania is characterized by elevated unhealthy interest to the value of the Hirsch index, especially inadequate artificial exaggeration of this value, as well as a number of negative implications of this interest. In this article we have made an attempt to briefly describe some of the negative effects of this new mental infection that hit the public consciousness of the scientific community. And also we want to identify ways of overcoming at least some of their causes. This is the problem solved in this work. To solve the formulated problem, we propose to apply multi-criteria approach based on information theory, namely those options, which are implemented in an automated system-cognitive analysis (ASC-analysis) and its software tools - intelligent system called "Eidos

The article is devoted to the solution of the problem which is the fact that on the one hand, the rating of Russian universities is in demand and on the other hand it hasn’t been created yet. The proposed idea of solving the problem consists in the application of domestic licensing of innovative intelligent technologies for these purposes: we have suggested using an automated system-cognitive analysis (ASC-analysis) and its software tools – the intelligent system called "Eidos". These methods are described in detail in this context. It is proposed to consider the possibility of applying these tools on the example of the Guardian University ranking. The article discusses its private criteria (indicators of universities). We specify the sources of data and the methods of their preparation for processing in "Eidos" system. In accordance with ASC-analysis methodology the article describes the installation of "Eidos", the data input into it, and the formalization of the subject area, synthesis and verification of models, their display and use to solve problems of assessment of the Guardian rating for Russian universities and research object modeling. It also discusses the prospects and ways of development of the integrated rating of Russian universities and operation of rating in adaptive mode. We have also specified the limitations of the proposed approach and the prospects of its development

The article presents a theoretical substantiation, methods of numerical calculations and software implementation of the decision of problems of statistics, in particular the study of statistical distributions, methods of information theory. On the basis of empirical data by calculation we have determined the number of observations used for the analysis of statistical distributions. The proposed method of calculating the amount of information is not based on assumptions about the independence of observations and the normal distribution, i.e., is non-parametric and ensures the correct modeling of nonlinear systems, and also allows comparable to process heterogeneous (measured in scales of different types) data numeric and non-numeric nature that are measured in different units. Thus, ASC-analysis and "Eidos" system is a modern innovation (ready for implementation) technology solving problems of statistical methods of information theory. This article can be used as a description of the laboratory work in the disciplines of: intelligent systems; knowledge engineering and intelligent systems; intelligent technologies and knowledge representation; knowledge representation in intelligent systems; foundations of intelligent systems; introduction to neuromaturation and methods neural networks; fundamentals of artificial intelligence; intelligent technologies in science and education; knowledge management; automated system-cognitive analysis and "Eidos" intelligent system which the author is developing currently, but also in other disciplines associated with the transformation of data into information, and its transformation into knowledge and application of this knowledge to solve problems of identification, forecasting, decision making and research of the simulated subject area (which is virtually all subjects in all fields of science)

This article briefly discusses the mathematical nature of the author's proposed modification of the weighted least squares, in which the amount of the data is used as the weights of observations. There are two variants of this modification. In the first one, the weighting of the observations was made by replacing one observation with a certain amount of the information in it by the corresponding number of observations for unit weight, and then we applied the standard method of least squares. In the second method, the weighting of the observations was performed for each value of the argument by replacing all observations with a certain amount of information in one observation of unit weight which had been obtained as a weighted average of them, and then we applied the standard method of least squares. We have described in detail the technique of numerical calculations of the amount of information in the observations, based on the theory of automated system-cognitive analysis (ASC-analysis) and implemented it with a help of software tools - intelligent system called "Eidos". The article provides an illustration of the proposed approach on a simple numerical example. In the future, we are planning to give more detailed mathematical basis of the method of weighted least squares, which is modified by using the amount of information as weights, but also to explore its properties

The article describes a numerical example of creating intellectual application designed to predict solar flares of different classes on the basis of the history of their development in the environment of "Eidos" system. As the source data, we used the database of UCI repository

The method of ordinary least squares (OLS) is widely known and deservedly popular. However, some attempts to improve this method. The result of one of such attempts is the weighted least squares (WMNC), the essence of which is to give the observation a weight which is inversely proportional to the errors of their approximation. Thereby, in fact, monitoring is ignored the more the difficult to approximate it. The result of this approach, formally, is the approximation error decreasing, but in fact, this occurs by partial refusal to consider the "problem" of observations, making a big mistake. If the idea underlying WMNC to bring to the extreme (and absurd), then in the limit, this approach will lead to the fact that from the entire set of observations there will be only those that lie almost exactly on the trend obtained by the method of least squares, and the rest will simply be ignored. However, according to the author, it's not a problem, and the failure of its decision, though it might look like a solution. In the work we have proposed a solution, based on the theory of information: to consider the weight of observations, the number of the argument of the value function. This approach was validated in the framework of a new innovative method of artificial intelligence: methods for automated system-cognitive analysis (ASA-analysis) and implemented 30 years ago in its software toolkit, which is "Eidos" intelligent system in the form of so-called "cognitive functions". This article presents an algorithm and software implementation of this approach, illustrated in detailed numerical example. In the future it is planned to give a detailed mathematical basis of the method of weighted least squares, which is modified by the application of information theory to calculate the weights of the observations, and investigate its properties

The problem of identifying authors and literary sources for bibliographic descriptions in the literature in recent years become increasingly important scientific and practical value. This is, in particular, due to the policy of the Ministry of education and science of the Russian Federation in the field of quality assessment of the results of scientific activity, which involves the use of a number of references to publications of authors and the Hirsch index. In Russia, appropriate analytical tools to evaluate the results of scientific activity, functionally similar to the well-known foreign bibliographic databases such as Scopus, Web of Science and other. Currently, the most famous Russian similar service is the Russian science citation index (RSCI): http://elibrary.ru/. However, as experience shows, references in bibliography list of publications are often made with a violation of GOST 7.1-2003 rule, and with the erroneous output, for example, incorrectly specified page numbers, name of publisher, etc., In practice, this leads to the fact that software system of bibliographic database cannot determine what is the right reference for the article and who were the authors of this article. As a result, for these authors we lost the citation, which leads to an underestimation of their Hirsch indexes and evaluation of the results of their research activities and leadership. It is clear that these negative consequences should be overcome. This article is devoted to the presentation of the ap-proach, which allows to solve the problem by apply-ing an ASC-analysis and intelligent system named "Aidos", which is a modern innovative smart technology ready for implementation

Since there are many artificial intelligence systems, there is a need of comparable quality assessment of their mathematical models. For this purpose, these systems can be tested on the same database source data, for which it is very convenient to use a public database of the UCI repository. This work is aimed at the study and development of model practices of the database of the UCI repository to assess the quality of mathematical models of artificial intelligence systems

In this article, in accordance with the methodology of SC analysis, we consider particular implementation stages of the synthesis of the numerical model and its analysis. We have also presented the results of the determination of the different states of the processing complex function of various factors on these states and their classification, as well as semantic networks and cognitive class diagrams and factors. On the basis of the analysis we made specific findings and recommendations for decision making at the management level of the region. After execution of the stages of cognitive structuring and formalization of the subject area the further stages of automated SC analysis have been accomplished, the first of which is the phase of the input database of precedents. All these steps are performed directly using "Eidos" universal cognitive analytical system