Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Lutsenko Yevgeniy Veniaminovich

Scholastic degree


Academic rank

professor

Honorary rank

—

Organization, job position

Kuban State Agrarian University
   

Web site url

lc.kubagro.ru

Email

prof.lutsenko@gmail.com


Articles count: 276

224 kb

AN ALGORITHM AND A PROGRAM FOR CALCULATING THE NUMBER OF COMBINATIONS FOR LARGE NUMBERS WITHOUT CALCULATING THE INTERMEDIATE FACTORIALS BY THEIR DECOMPOSITION INTO PRIME FACTORS AND ABBREVIATIONS

abstract 1181604110 issue 118 pp. 1662 – 1671 29.04.2016 ru 833
Classical combinatorial formula to calculate the number of combinations from n on m: C(n,m)=n!/(m!(nm)!) involves the intermediate calculation of factorials, which is often impossible when n>170, due to limitations in the capacity of numbers that are used in programming languages and created through these systems. However, in some cases it is necessary to calculate the number of combinations for n and m much larger than this limit, such as when a value greater than 10000. In such cases, there is a definite problem, which manifests itself, for example in the fact that many on-line services meant to calculate the number of combinations with these parameters do not work properly. In this article, we present its solution in the form of an algorithm and software implementation. The essence of the approach is to first decompose the factorials into prime factors and reduce them, and then to produce multiplication. This approach differs from those cited in the Internet
4002 kb

INTELLIGENT SCALABLE OPEN INTERACTIVE ONLINE ENVIRONMENT FOR TEACHING AND RESEARCHING ON THE BASIS OF ASC-ANALYSIS AND "EIDOS" SYSTEM

abstract 1301706001 issue 130 pp. 1 – 55 30.06.2017 ru 820
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
4550 kb

HOW TO SOLVE THE TASK OF CLASSIFICATION OF TYPES OF RIFLE AMMUNITION USING THE METHOD OF ASCANALYSIS

abstract 1181604001 issue 118 pp. 1 – 40 29.04.2016 ru 746
In criminology, there are actual problems of determining the type (machine gun, rifle, large caliber, pistol) and a particular model of small rifle for its ammunition, in particular, discovered in the use of weapons. The article proposes a solution to this problem with the use of a new innovative method of artificial intelligence: automated system-cognitive analysis (ASCanalysis) and its programmatic toolkit – a universal cognitive analytical system called "Eidos". In the system of "Eidos", we have implemented a software interface that provides input to the system images, and the identification of their external contours on the basis of luminance and color contrast. Typing by multiparameter contour images of specific ammunition, we create and verify the system-cognitive model, with the use of which (if the model is sufficiently reliable), we can solve problems of system identification, classification, study of the simulated object by studying its model and others. For these tasks we perform the following steps: 1) enter the images of ammunitions into the system of "Eidos" and create mathematical models of their contours; 2) synthesis and verification of models of the generalized images of ammunition for types of weapons based on the contour images of specific munitions (multivariate typology); 3) quantification of the similarities-differences of the specific ammunition with generalized images of ammunition of various types and models of small rifle (system identification); 4) quantification of the similarities-differences of the types of munitions, i.e. cluster-constructive analysis
3036 kb

THE RATIONALE FOR SELECTING THE METHOD FOR THE RESEARCH OF THE INFLUENCE OF ENVIRONMENTAL FACTORS ON VARIOUS ASPECTS OF LIFE QUALITY IN THE REGION

abstract 1221608002 issue 122 pp. 18 – 31 31.10.2016 ru 706
To increase the validity of conclusions about the impact of the environment on the 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 are needed to be handled not just together, but in a comparable form approach, including technology and methodology, and to be implemented 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". Previously, the authors have 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 a research method; as well as 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. This work contains a description of the basic data sources for the study of the impact of environmental factors on various aspects of quality of life of the region's population, the source data for this study, the characteristics of the original data, substantiation of requirements to the method of research, choosing research methods appropriate to requirements; the development of steps to achieve the objectives of the study
2310 kb

FUZZY MULTICLASS GENERALIZATION OF THE CLASSICAL F-MEASURE OF PLAUSIBILITY MODELS BY VAN RIJSBERGEN IN ASK-THE ANALYSIS AND THE SYSTEM OF "EIDOS"

abstract 1231609001 issue 123 pp. 1 – 29 30.11.2016 ru 681
Classic quantitative measure of the reliability of the models: F-measure by van Rijsbergen is based on counting the total number of correctly and incorrectly classified and not classified objects in the training sample. In multiclass classification systems, the facility can simultaneously apply to multiple classes. Accordingly, when the synthesis of the model description is used for formation of generalized images of many of the classes it belongs to. When using the model for classification, it is determined by the degree of similarity or divergence of the object with all classes, and a true-positive decision may be the membership of the object to several classes. The result of this classification may be that the object is not just rightly or wrongly relates or does not relate to different classes, both in the classical F-measure, but rightly or wrongly relates or does not relate to them in varying degrees. However, the classic F-measure does not count the fact that the object may in fact simultaneously belongs to multiple classes (multicrossover) and the fact that the classification result can be obtained with a different degree of similarity-differences of object classes (blurring). In the numerical example, the author states that with true-positive and true-negative decisions, the module similarities-differences of the object classes are much higher than for false-positive and false-negative decisions. It would therefore be rational to the extent that the reliability of the model to take into account not just the fact of true or false positive or negative decisions, but also to take into account the degree of confidence of the classifier in these decisions. In the intellectual system called "Eidos", which is a software toolkit for the automated system-cognitive analysis (ASC-analysis), we use initially proposed by its developers measure of the reliability of the models, which is essentially a fuzzy multiclass generalization of the classical F-measure (it is proposed to call it the L-measure). In this article, L-measure is mathematically described and its application is demonstrated on a simple numerical example
3818 kb

QUANTITATIVE MEASUREMENT OF THE SIMILARITIES AND DIFFERENCES OF CLONES OF GRAPES USING CONTOURS OF LEAVES WITH THE USE OF ASC-ANALYSIS AND "EIDOS" SYSTEM

abstract 1161602077 issue 116 pp. 1200 – 1223 29.02.2016 ru 677
The article discusses the application of automated system-cognitive analysis (ASC-analysis), its mathematical model is a system of information theory and implements, its software tools – intellectual system called "Eidos" for solving one of the important tasks of ampelography: to quantify the similarities and differences of different clones of grapes using contours of the leaves. To solve this task we perform the following steps: 1) digitization of scanned images of the leaves and creation their mathematical models; 2) formation mathematical models of specific leaves with the application of information theory; 3) modeling the generalized images of leaves of different clones on the basis of specific leaves (multiparameter typing); 4) verification of the model by identifying specific leaf images with generic clones, i.e., classes (system identification); 5) quantification of the similarities and differences of the clones, i.e. cluster-constructive analysis of generalized images of leaves of various clones. The specific shape of the contour of the leaf is regarded as noise information on the clone to which it relates, including information about the true shape of a leaf of this clone (clean signal) and noise, which distort the real shape, due to the random influence of the environment. Software tools of ASA-analysis which is intellectual "Eidos" system provides the noise suppression and the detection of a signal about the true shape of a leaf of each clone on the basis of a number of noisy concrete examples of the leaves of this clone. This creates a single image of the shape of the leaf of each clone, independent of their specific implementations, i.e. "Eidos" of these images (in the sense of Plato) - the prototype or archetype (in the Jungian sense) of the images
9205 kb

IDENTIFICATION OF TYPES AND MODELS OF AIRCRAFT USING ASC-ANALYSIS OF THEIR SILHOUETTES (CONTOURS) (GENERALIZATION, ABSTRACTION, CLASSIFICATION AND IDENTIFICATION)

abstract 1141510099 issue 114 pp. 1319 – 1370 30.12.2015 ru 674
The article discusses the application of automated system-cognitive analysis (ASC-analysis), its mathematical model which is system theory of information and its software tool, which is intellectual system called "Eidos" for solving problems related to identification of types and models of aircraft by their silhouettes on the ground, to be more precise, their external contours: 1) digitization of scanned images of aircraft and creation of their mathematical models; 2) formation of mathematical models of specific aircraft with the use of the information theory; 3) modeling of the generalized images of various aircraft types and models and their graphic visualization; 4) comparing an image of a particular plane with generalized images of various aircraft types and models, and quantifying the degree of similarities and differences between them, i.e., the identification of the type and model of airplane by its silhouette (contour) on the ground; 5) quantification of the similarities and differences of the generalized images of the planes with each other, i.e., clusterconstructive analysis of generalized images of various aircraft types and models. The article gives a new approach to digitizing images of aircraft, based on the use of the polar coordinate system, the center of gravity of the image and its external contour. Before digitizing images, we may use their transformation, standardizing the position of the images, their sizes (resolution, distance) and the angle of rotation (angle) in three dimensions. Therefore, the results of digitization and ASC-analysis of the images can be invariant (independent) relative to their position, dimensions and turns. The shape of the contour of a particular aircraft is considered as a noise information on the type and model of aircraft, including information about the true shape of the aircraft type and its model (clean signal) and noise, which distort the real shape, due to noise influences, both of the means of countering detection and identification, and environment. Software tool of ASC-analysis, i.e. Eidos intellectual system, provides identification of the type and the model of airplane by its silhouette, as it was shown in a simplified numerical example
3720 kb

MATHEMATICAL AND NUMERICAL MODELING OF THE RELATIONSHIP BETWEEN MORPHOLOGICAL, BIOCHEMICAL AND TRACE ELEMENT COMPOSITION OF BLOOD OF HEREFORD BREED CALVES AND THEIR SIZE

abstract 1431809033 issue 143 pp. 49 – 88 30.11.2018 ru 670
The researchers obtained data on the morphological, biochemical and trace element composition of the blood of bull-calves of Hereford breed of different sizes. In this regard, scientists and business executives have three natural questions: 1) whether it is possible to predict the size and thus the meat productivity of bulls using these blood indicators; what are the strength and direction of the influence of certain values of blood indicators on the size and weight of bulls; what blood indicators are similar in meaning, and what are different and how much (to what extent). The article is devoted to the reasoned answers to these questions by applying modern methods of mathematical and numerical modeling to solve the corresponding 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 #133
140 kb

COGNITIVE MODELS OF PREDICTION THE DEVELOPMENT OF A DIVERSIFIED CORPORATION

abstract 1221608003 issue 122 pp. 32 – 42 31.10.2016 ru 665
The application of classical forecasting methods applied to a diversified corporation faces some certain difficulties, due to its economic nature. Unlike other businesses, diversified corporations are characterized by multidimensional arrays of data with a high degree of distortion and fragmentation of information due to the cumulative effect of the incompleteness and distortion of accounting information from the enterprises in it. Under these conditions, the applied methods and tools must have high resolution and work effectively with large databases with incomplete information, ensure the correct common comparable quantitative processing of the heterogeneous nature of the factors measured in different units. It is therefore necessary to select or develop some methods that can work with complex poorly formalized tasks. This fact substantiates the relevance of the problem of developing models, methods and tools for solving the problem of forecasting the development of diversified corporations. This is the subject of this work, which makes it relevant. The work aims to: 1) analyze the forecasting methods to justify the choice of system-cognitive analysis as one of the effective methods for the prediction of semi-structured tasks; 2) to adapt and develop the method of systemic-cognitive analysis for forecasting of dynamics of development of the corporation subject to the scenario approach; 3) to develop predictive model scenarios of changes in basic economic indicators of development of the corporation and to assess their credibility; 4) determine the analytical form of the dependence between past and future scenarios of various economic indicators; 5) develop analytical models weighing predictable scenarios, taking into account all prediction results with positive levels of similarity, to increase the level of reliability of forecasts; 6) to develop a calculation procedure to assess the strength of influence on the corporation (sensitivity) of its member enterprises; 7) to finalize the software tools the ask analysis to the level of information technology, given its adaptation and development to predict actions in a diversified corporation
9686 kb

FORECASTING THE NUMBER AND THE CLASSES OF SOLAR FLARES BASED ON THEIR BACKGROUND ACCORDING TO THE UCI REPOSITORY USING ASCANALYSIS AND "EIDOS" INTELLIGENT SYSTEMS

abstract 1041410099 issue 104 pp. 1328 – 1389 30.12.2014 ru 654
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
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