Scientific Journal of KubSAU

A determination system of the population health is a big complex hierarchical system. The current level of management of such systems involves the use of mathematical models and corresponding software tools for the accumulation of baseline data (monitoring), identification, prediction and decision-making. However, when modeling such large complex systems, we face a number of problems. The main problem is that in one model it is necessary to process a very large number of factors in a proper and comparable way, that are measured in different units, and different types of scales (numeric and text). Traditionally, to solve this problem and determine the values of individual criteria we use expert evaluation and desirability functions, and the integral criterion is the geometric mean. However, the traditional approach, currently applied in this field, has several disadvantages. First, in the traditional model it is defined in an expert way, which factors influence the decision of different problems in a positive way, which ones are negative and which ones do not affect. Second, for the numerical evaluation of influence factors on the solution of the problem we use different algorithms for calculating values of the desirability function for positively and negatively influencing factors which, when used as an integral criterion of the geometric average, leads to comparable results. Third, the use of normalized utility functions leads to the leveling force of the impact factors resulting in weak impact and the influencing factors are given the same variation in numeric values and have similar influence on integral criteria. All of the mentioned problems of the traditional approach have been resolved using Automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – Universal cognitive analytical system called "Eidos". In the proposed systemic cognitive model, for the values of environmental and economic factors, without the participation of the experts, we have calculated the amount and the sign of the information contained there about some values of indicators of population health

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

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 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

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

It has been proved that theoretical scientific models created as a result of the learning process, reflect not the reality of "what it really is" and only the reality "what it is" in the process of interaction with tools of empirical knowledge, i.e. the organs of perception of a certain organism that supports a corresponding form of consciousness, experimental instruments and information-measuring systems of a certain functional level. Examples and consequences of the major mistakes that have been historically made by scientists for the substantial interpretation of theoretical scientific models: this error is unwarranted giving the model the ontological status ("hypostatizations") and its associated error model giving the status of universality. The history of the emergence and development of science was viewed as a process of sequential application of natural scientific method to the study of objects of knowledge, previously studied in the framework of philosophy. We have formulated a promising idea of solving problems of philosophy of natural science methods. In the framework of implementation of this idea, we have proposed a natural-scientific formulation and solution of the basic question of philosophy. This new scientific concept of "Relatively objective and Relatively subjective" and discusses the relationship of the content of these concepts from forms of consciousness. The article gives a natural-scientific definition of consciousness and offers periodic multi-criteria classification of forms of consciousness, including 49 forms of consciousness: the 7 types of 7 consciousness and cognition methods. It examines the dialectics of the changing ideological paradigms from antiquity to the present day and a place of scientific paradigms in the process. It also describes the law of denial-denial in the change of ideological paradigms and on the basis; it explores the hypothesis about the main features of the future ideological paradigm, formed in the present. We have formulated the correct principles of interpreting scientific models of natural-scientific method – scientific method of induction and the principles of open consciousness, i.e. the principles, opening the way for the formation of new, improved and more adequate models of reality than the existing ones which were considered the only true models

The article considers the application of Eidos intellectual technologies for implementation of developed veterinary and medical diagnostics statistical tests without programming in the convenient form for the individual and mass testing, the analysis of the results and development of the individual and group recommendations. It is possible to merge several tests in one supertest

In this article, in accordance with the methodology of the Automated system-cognitive analysis (ASCanalysis), we examine the implementation of the 3rd ASC-analysis: synthesis and verification of forecasting models of development of diversified agro-industrial corporations. In this step, we have synthesis and verification of 3 statistical and 7 system-cognitive models: ABS – matrix of the absolute frequencies, PRC1 and PRC2 – matrix of the conditional and unconditional distributions, INF1 and INF2 private criterion: the amount of knowledge based on A. Kharkevich, INF3 – private criterion: the Chi-square test: difference between the actual and the theoretically expected absolute frequencies INF4 and INF5 – private criterion: ROI - Return On Investment, INF6 and INF7 – private criterion: the difference between conditional and unconditional probability (coefficient of relationship). The reliability of the created models was assessed in accordance with the proposed metric is similar to the known F-test, but does not involve the performance of normal distribution, linearity of the object modeling, the independence and additivity acting factors. The accuracy of the obtained models was high enough to resolve the subsequent problems of identification, forecasting and decision making, as well as studies of the modeled object by studying its model, scheduled for consideration in future articles

There are three main growth points of modern information technologies: global network and mobile communication, advanced human-machine interfaces, intelligent technologies. As it is known, the system (synergistic) effect is usually observed in multidisciplinary and interdisciplinary researches. This means that an interesting direction of research and development is located at the overlap of these three promising areas, namely: advanced interfaces in the global mobile networks, advanced intelligent interfaces and the application of artificial intelligence technologies in the Internet and mobile communications. In addition, a particularly high relevance goes to the development and application prospective of intelligent interfaces to the Internet and mobile communications. The Internet intellectualities gradually, it turns from non-local storage of large data (big data) in information space that contains meaningful big data, i.e. "great information" (great info), and then in the space of knowledge or "cognitive space" in which most information is actively used to achieve goals (management) and turns into the "great knowledge" (great knowledge). There are more sites devoted to artificial intelligence, free databases for machine learning (UCI, Kaggle, and others) and even on-line intelligent applications, and interfaces used in the Internet are improving. Recently, there was an acquisition of company Oculus, which is the world's leading developer and manufacturer of ammunition of virtual reality by the developer of one of the first global social networking Facebook - Mark Zuckerberg. However, students and scientists still do not notice that open, scalable, interactive, intelligent on-line environment for learning and researches already exists and operates, based on automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit – intellectual "Eidos" and the author's website. This article is an original presentation and it is designed to familiarize potential users with the capabilities of this environment