Scientific Journal of KubSAU

In complex multiparameter technical systems there are numerous and varied physical processes which, on the one hand, have a significant impact on the performance of those systems, and on the other hand, it is extremely difficult amenable to description in the form of meaningful analytical models based on equations, because these models must take into account the specific features of the systems. As a consequence, the development of conceptual analytical models is a "hand-made work" and it is associated with a large number of simplifying assumptions that reduce their versatility and reliability. But there is also another principle of modeling: the construction of phenomenological information models, i.e. models that do not have analytical forms of representation that describes the simulated system superficially as a "black box". Such models can be built directly based on empirical data and with the appropriate software it can be a standard technology much faster and much less time consuming than developing meaningful analytical models. On the other hand, the phenomenological information model can be sufficient to determine the rational design features and parameters of the modes of operation of complex technical systems. Besides, such phenomenological models can be viewed as the first stage in the development of meaningful analytical models. It is proposed to use a new universal innovative method of artificial intelligence for creating phenomenological models of complex technical systems: automated system-cognitive analysis (ASC-analysis) and its programmatic Toolkit which is a universal cognitive analytical system called "Eidos". In the system of "Eidos" we have implemented a software interface that provides direct input into the system large amounts of empirical data from an Excel file. The system of "Eidos" can directly (based on empirical (experimental) data) calculate how much information about the results of the technical systems is contained in the facts of possessing certain specific structural elements and certain values of the parameters modes of its work. On this basis, the system provides research-based and appropriate recommendations for the rational choice of design features and parameters of the operation modes of the simulated system

The article briefly discusses the following questions. The classic definition of virtual reality systems. Effects of virtual reality: effects of the reality, presence, depersonalization (modification of consciousness), a modification of the consciousness of the user, virtualization, interests, goals, values, and motivations ("reals and virtuals"). The criteria of reality in various forms of consciousness and their application in virtual reality. Virtual reality systems and criteria of reality, the principles of equivalence (relativity) of Galileo and Einstein and the criteria for virtual reality. The virtual device I / o. The author's definition of virtual reality systems. Dreaming, hypnagogic state, and virtual reality. Augmented reality and augmented virtuality. The modification of consciousness and the consciousness of the user in virtual reality. Consideration of future and pathological changed forms of consciousness that arise in systems with intelligent interfaces. Observance of moral norms in virtual reality and the consequences of failure. The risk of effects of virtual reality and the need for serious scientific study. The transfer of knowledge and skills from virtual reality to true. The transfer of knowledge and skills from virtual reality to true. Mechanisms of formation of models of the true and the virtual reality of man and the principles of their correct and meaningful interpretation. Principles and perspectives correct meaningful interpretation of the subjective (virtual) models of the physical and social reality formed by the human consciousness. The application of virtual reality systems. There is also a test for understanding of virtual reality

The article discusses the use of automatic systemic-cognitive analysis (ASC-analysis), its mathematical model is a system of information theory and software tools – an intellectual system called "Eidos" for the solution of some problems of ampelography: 1) digitization of scanned images of the leaves and creation of their mathematical models; 2) the formation of mathematical models of specific leaves using the spreading of information theory; 3) the formation of models of generalized images of leaves of various sorts; 4) comparing an image of a specific leaf with a generalized image of the leaf of different varieties and finding a quantitative degree of similarity and differences between them, i.e. the identification of the varieties on the leaf; 5) quantification of the similarities and differences of the varieties, i.e. cluster-constructive analysis of generalized images of the leaves of different varieties. We propose a new approach to digitizing images of leaves, based on using the polar coordinate system, the center of gravity of the image and its external contour. Before scanning images we may use transformation to standardize the position of the still images, their sizes and rotation angle. Therefore, the results of digitization and ASC-analysis of the images might be invariant (independent) relatively to their position, size and rotation. The specific shape of the contour of the leaf is regarded as noise information on the variety, including information about the true shape of the leaf of the class (clean signal) and noise, which distort this true form, originating in a random environment. Software tools of ASC-analysis – intellectual "Eidos" system ensures noise reduction and the selection of the signal about the true shape of the leaf of each variety on the basis of a number of noisy concrete examples of the leaves of this variety. This creates a one way form of a leaf of each class, free from their concrete implementations, i.e., the "Eidos" of these images (in the sense of Plato) is a prototype or archetype (in the Jungian sense) of the images

To increase the validity of conclusions about the impact of environment on quality of life we need to move from generalities to the application of quantitative modeling techniques. This requires the joint processing environmental databases and databases depicting various aspects of quality of life. These databases need to be handled not just together, but in a comparable form approach, technology and methodology; and we need to implement them in one software system. For the first time in the environmental studies it has been planned to be done with the application of the ASK- analysis and the system called "Eidos". In this work, we set the goals and the objectives of the application of the ASK-analysis to study the effect of environmental factors on the quality of life of the population of the region. The article reveals the urgency of this study; the requirements for the method of conducting the study, the choice of research method, the contents of the objectives of the study. The proposed work is at the edge of mathematical ecology and mathematical modeling of quality of life (which refers to mathematical and instrumental methods of Economics), resulting from expected synergies, consists in obtaining of new knowledge in these fields, that is relevant to both ecology and economy. This knowledge will make it more meaningful and justified for the application of environmental criteria and concepts in the economy

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

Meat Academy website http://meatinfo.ru has a comparative table of breeds of cattle on 8 indicators, from which 2 are text and 6 are numerical http://meatinfo.ru/info/show?id=197. It is a natural question for business executives, which of these breeds are similar throughout the system of indicators characterizing them, and which ones differ and to what extent. There is also the question of which indicators are similar and different in meaning and by how much. This article is devoted to the solution of these problems. The results of the study can be used by anyone, due to the fact that Eidos the universal automated system, which is a tool of ask-analysis, is in full open free access on the author's website at: http://lc.kubagro.ru/aidos/_Aidos-X.htm, and numerical examples of solving the mentioned problems with the use of artificial intelligence technologies are placed as a cloud Eidos-application #131

One of the "points of growth" of applied statistics is methods of reducing the dimension of statistical data. They are increasingly used in the analysis of data in specific applied research, such as sociology. We investigate the most promising methods to reduce the dimensionality. The principal components are one of the most commonly used methods to reduce the dimensionality. For visual analysis of data are often used the projections of original vectors on the plane of the first two principal components. Usually the data structure is clearly visible, highlighted compact clusters of objects and separately allocated vectors. The principal components are one method of factor analysis. The new idea of factor analysis in comparison with the method of principal components is that, based on loads, the factors breaks up into groups. In one group of factors, new factor is combined with a similar impact on the elements of the new basis. Then each group is recommended to leave one representative. Sometimes, instead of the choice of representative by calculation, a new factor that is central to the group in question. Reduced dimension occurs during the transition to the system factors, which are representatives of groups. Other factors are discarded. On the use of distance (proximity measures, indicators of differences) between features and extensive class are based methods of multidimensional scaling. The basic idea of this class of methods is to present each object as point of the geometric space (usually of dimension 1, 2, or 3) whose coordinates are the values of the hidden (latent) factors which combine to adequately describe the object. As an example of the application of probabilistic and statistical modeling and the results of statistics of non-numeric data, we justify the consistency of estimators of the dimension of the data in multidimensional scaling, which are proposed previously by Kruskal from heuristic considerations. We have considered a number of consistent estimations of dimension of models (in regression analysis and in theory of classification). We also give some information about the algorithms for reduce the dimensionality in the automated system-cognitive analysis

It is well known that genetics studies the mechanisms of variation/heredity and widely uses the concept of "genetic information". While genetics considers the information as the content of the genetic code - structure of DNA and RNA included in the cell of a living organism. Genetics examines the mechanisms of recording, copying, readout of genetic information, the possibility of its modification and its influence on the characteristics and properties of the organism. In conversational and scientific language we know phrases, such as "Genes contain information about the characteristics/properties of the body." Paradoxically, we see no attempts to determine the amount of information contained in specific genes on specific characteristics or phenotypic properties of the organism. It would seem that the application of information theory in genetics is a completely natural and suggests itself. More strange that there are practically no works devoted to the application of information theory for solving problems of genetics. This article is intended, to some extent, to fill this gap on the example of calculating the amount of information in the genes of the characteristics or properties of different grape varieties. It examines the application of automated system-cognitive analysis (ASC-analysis), its mathematical model – system of information theory and software tools – intellectual system called "Eidos" for solving one of the important tasks of genetics: determine the amount of information contained in the genes on various phenotypic characteristics/properties of the grapes. To solve this problem, we perform the following steps: 1) cognitive-targeted structuring of the subject area; 2) the formalization of the subject area, i.e. development of classification and descriptive dials and graduations and training samples; 3) synthesis and verification of information model, reflecting the amount of information in the genes on the phenotypic characteristics/properties (multiparameter typing); 4) displaying the information about the genetic determination system of phenotypic characteristics/properties (SWOT analysis of Fennovoima); 5) displaying the information about the strength and direction of influence of a specific gene on phenotypic characteristics/properties (SWOT-diagrams of genes); 6) the solution to the problem of system identification phenotypic characteristics/properties by the presence of certain genes; 7) quantification of the similarities-differences of the various phenotypic characteristics/properties, upon determination system genes. A specific phenotypic property (or characteristic) is regarded as a noisy genetic text, including genetic information about the true gene property (clean signal) and the noise that distorts this information due to the random effects of the environment. The software tool of the ask-analysis which is "Eidos" intellectual system provides the noise suppression and the selection of true signal

In this article we consider application of the automated systemic and cognitive analysis (ASK-analysis), its mathematical model – a systemic information theory and the program tools realizing them – the intellectual Eidos system, for input (digitization) of images from graphic files, synthesis of the generalized images of classes, their abstraction, classification of the generalized images of classes (clusters and constructs), comparison of concrete images with the generalized images (identification) of classes, comparisons of classes with each other and creations of the generalized images of genus of ground beetles on the basis of images of the types. The new approach to digitization of images of ground beetles based on use of a polar frame, the center of weight of the image and its external contour is offered. Before digitization of images, their transformations standardizing the provision of images, their sizes and an angle of rotation can be applied. Therefore, the results of digitization and the ASK-analysis of images can be invariant (are independent) concerning their situation, the sizes and turn. There is a successful experience of the solution of similar tasks in other subject domains. This article can be considered as a continuation of series of the works devoted to application of the automated systemic and cognitive analysis (ASK-analysis) and its program tools – the Eidos system

In the author's interpretation we consider concepts and methods of science, such as science, knowledge, model, gnosticism and agnosticism, the principle of Ashby, facts, empirical regularity, empirical law, scientific law, and others. We have formulated the main problem of the science, concluding that cognitive abilities of a human are limited and do not provide effective knowledge in a very large volume of data. The solution to this problem is to look at ways of automation of scientific research. Traditionally, we use information-measuring systems and automated systems research (ASNI) for this. However, the mathematical methods used in these systems, impose strict impracticable requirements to the source data, which dramatically reduces the effectiveness and applicability of these systems in practice. Instead of having to submit to the source data impracticable requirements (like the normality of the distribution, absolute accuracy and complete replications of all combinations of values of factors and their full independence and additivity) automated system-cognitive analysis (ASC-analysis) offers (without any pre-processing) to understand the data and thereby convert them into information and then convert this information to knowledge by its application to achieve targets (i.e. for controlling) and for solution for problems of classification, decision support and meaningful empirical research of the modeled subject area. ASC-analysis is a systematic analysis, considered as a method of scientific cognition. This is a highly automated method of scientific knowledge that has its own developed and constantly improving software tool – an intellectual system called "Eidos". The system of "Eidos" has been developed in a generic setting, independent of any domain and can be applied in all subject areas, in which people apply their natural intelligence. The "Eidos" system is a tool of cognition, which greatly increases the possibility of natural intelligence, just like microscopes and telescopes multiply the possibilities of vision (but in this case only if you have this possibility). The study proposes a new view of the models: phenomenological meaningful model, which is currently represented only by systemic cognitive models, and which is currently in the middle between empirical and theoretical knowledge. The system called "Eidos" is considered as a tool of automation of the learning process, providing meaningful synthesis of phenomenological models directly on the basis of empirical data