Scientific Journal of KubSAU

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

Antibacterial chemotherapeutic drugs, which include antibiotics and synthetic antimicrobial agents, are widely used in veterinary medicine for the prevention and treatment of diseases caused by microorganisms. Antibacterial agents can be classified by type of action and chemical structure. It is also known that when several drugs are used in combination with each other, they interact within the body with each other, which can lead to strengthening or weakening of their action. For these reasons, it is of scientific and practical interest to develop a classification of antibiotics by their characteristics and principle of action (task 1), as well as by mutual compatibility (task 2). The article solves these problems using a new method of agglomerative cognitive clustering, implemented in automated system-cognitive analysis (ASK-analysis). This method of clustering has a number of advantages over the known traditional methods of clustering. These advantages allow us to obtain clustering results that are understandable to specialists and amenable to meaningful interpretation, which are well consistent with the experts ' assessments, their experience and intuitive expectations, which is often a problem for classical clustering methods. The article provides detailed numerical examples of solving two problems. The universal automated system called "Eidos", which is a tool of ASK-analysis, is in full open access on the author's website: http://lc.kubagro.ru/aidos/_Aidos-X.htm. Numerical examples of solving veterinary problems with the use of artificial intelligence technologies are placed as cloud Eidos-applications and are available to everyone

At present, databases of 27-year observations of various adverse weather conditions and dangerous hydrometeorological phenomena leading to social and economic losses on the territory of Russia are in full open free access. Some of these natural hazards also cause significant damage to agriculture, especially crop production, horticulture and viticulture. Therefore, a great scientific and practical interest is the intellectual analysis of these data, which will create more favorable conditions for the prediction of such adverse events and decision-making, taking into account their possible negative impact on human activity. To achieve this goal, it is necessary to solve the following tasks, which are obtained by decomposition of the goal and are the stages of its achievement: Task 1: cognitive structuring of the subject area. Task 2: preparation of initial data and formalization of the subject area. Task 3: synthesis and verification of statistical and system-cognitive models and selection of the most reliable model. Task 4: solving problems in the most reliable model: - subtask 4.1. Forecasting (diagnostics, classification, recognition, identification); - subtask 4.2. Support decision-making; - sub-task 4.3. Study of the simulated subject area by studying its model (cognitive diagrams of classes and values of factors, agglomerative cognitive clustering of classes and values of factors, nonlocal neurons and neural networks, 3d-integral cognitive maps, cognitive functions). It is proposed to use automated system-cognitive analysis (ASC-analysis) to solve the tasks. The article provides a detailed numerical example illustrating the solution of all these problems

Sommelier evaluates the quality of wine on the basis of their subjective feelings. At the same time, what the sommelier says when evaluating wine, it is difficult or impossible to rationally understand for the uninitiated to this art. The process of assessing the quality of wine by sommelier can not be formalized and is carried out entirely at the sensual level. Sometimes, different sommeliers differently evaluate the same wine poured from the same barrel into bottles of different prestige, with stickers differing in the number of stars. This raises at least two legitimate and natural questions. The first question is whether any subjective sommelier evaluations of the quality of wine are connected with its objective physical and chemical properties? The second question arises in the case of a positive answer to the first one: is it possible to analyze the objective methods of physical and chemical properties of wine to predict its subjective assessment by various sommeliers or some "generalized sommelier", generalizing many such subjective assessments? This article is devoted to obtaining reasoned answers to these questions. The purpose of this work, which is of great scientific and practical interest, is to create a model that provides an automated assessment of the quality of wine based on the analysis of its objective physical and chemical properties, coinciding with its sommelier-evaluation. To achieve this goal, we use Automated system-cognitive analysis (ASC-analysis) and its software tools – the intelligent system called "Eidos". A detailed numerical example based on 1599 real-world examples of sommelier evaluation of wine quality with known physical and chemical properties is considered. In addition to the answer to the two questions in the article, there is a study of the created system-cognitive model

The article is devoted to the use of automated system-cognitive analysis for the study of probiotics for the growth of bulls. Moreover, as growth indicators we have not used live weight, but indices characterizing the shape and proportions of the body of animals. A detailed numerical example of solving the problem using real data is given

The aim of this work is to study the strength and the direction of the influence of morphological and biochemical properties of tomatoes on the quantitative, qualitative, financial and economic results of their cultivation and the degree of determinism of these results. Achieving this goal is of great scientific and practical interest for scientists, breeders and vegetable growers-practitioners. This allows breeders to obtain new high-performance varieties of tomato hybrids, and farms to choose hybrids, the cultivation of which is most effective from a financial and economic point of view. To achieve this goal, we use automated system-cognitive analysis (ASC-analysis) and its software tool which is the intelligent system called "Eidos". A numerical example based on real data on tomato hybrids has been considered in detail

In the article the application of systemic-cognitive analysis, its mathematical model - the system theory of the information and its program toolkit - "Eidos" system for synthesis of the generalized images of classes, their abstraction, classification of the generalized images (clusters and constructs) comparisons of concrete images with the generalized images (identification) are examined. We suggest a new approach to the digitization of images, based on the use of the polar coordinate system, the center of gravity of the image and its contour. Before digitizing images we can use their changes to standardize the position of the picture-frames, their size and rotation. Therefore, if you specify this option, the results of digitization and image ASC-analysis can be invariant (independent) to their position, size and rotation. This means that in the model on the basis of a number of specific examples we will create one image of each class of images, independent of their specific implementations, i.e., the "Eidos" of these images (in the sense of Plato) - a prototype or archetype (in the Jungian sense) images. But the "Eidos" system provides not only the formation of prototype images, which quantitatively reflects the amount of information in the image elements of the prototype, but the removal of all irrelevant to identification (abstraction), and the comparison of specific images with generic (identification) and the generalized images of images together (classification). The article provides a detailed numerical example of ASC- analysis of images

In the article the application of systemic-cognitive analysis and its mathematical model i.e. the system theory of the information and its program toolkit which is "Eidos" system for loading images from graphics files, synthesis of the generalized images of classes, their abstraction, classification of the generalized images (clusters and constructs) comparisons of concrete images with the generalized images (identification) are examined. We suggest using the theory of information for processing the data and its size for every pixel which indicates that the image is of a certain class. A numerical example is given in which on the basis of a number of specific examples of images belonging to different classes, forming generalized images of these classes, independent of their specific implementations, i.e., the "Eidoses" of these images (in the definition of Plato) – the prototypes or archetypes of images (in the definition of Jung). But the "Eidos" system provides not only the formation of prototype images, which quantitatively reflects the amount of information in the elements of specific images on their belonging to a particular proto-types, but a comparison of specific images with generic (identification) and the generalization of pictures images with each other (classification)

In the article the main problem of management of agro industrial holding is generated and approaches to its decision are briefly reviewed on a basis of "management of knowledge", also a parity of data, information and knowledge, procedure of revealing of knowledge from data, a way of use of knowledge for forecasting and decision-making, stages of life cycle of the intellectual appendix and the basic results of application of the modern automated technology of management of knowledge - the Systemic cognitive analysis for management of agro industrial holding are examined

Techniques of value analysis and "Direct-costing" are well-known and popular. The ideas and principles of value analysis and the method of "Direct costing" are very similar, if not identical. On the one hand, these ideas are very reasonable, well grounded theoretically and proved its effectiveness in practice. On the other hand, the wide use of these methods is hampered by the difficulty of obtaining large amounts of detailed technological and financial-economic information, as well as the need for careful research by competent professionals, well-versed in substantive subject area. This is the contradiction between the desire to apply the methods of the value analysis and "Direct costing" and difficulty to perform it in practice. This contradiction constitutes a real problem and may often be discouraging and frustrating. In this work, we propose a simple and effective solution to this problem, theoretically well-informed with all the necessary methodological and software tools and widely and successfully tested in practice. The proposed solution is based on two simple ideas: 1) instead of collecting and holding a meaningful large amount of technological and financial-economic information we might apply approaches, pleasant management theory; 2) to create systems for automated control of natural and financial-economic efficiency of expenses we might use the automated system-cognitive analysis and its software tool – an intellectual system called "Eidos". In the name of the specialty 08.00.05 – Economics and national economy management, there are such words: "management of enterprises, branches, complexes, innovation." The use of the term "Management" implies that there is a model that reflects the influence of factors on the object of control, and there is the management system making decisions based on this model. However, as a rule, the dissertations in this field have nothing of this, except only financial and economic calculations. The article proposes an approach based on the control theory, removing this disadvantage