Scientific Journal of KubSAU

In forensics there is an urgent need to determine the type of rifle (automatic, rifle, large caliber pistol) depending on its used ammunition found at the scene of the use of weapons. We offer a solution to this problem with the use of new innovative method of artificial intelligence: automated system-cognitive analysis (ASC-analysis) and its program toolkitwhich is a universal cognitive analytical system called "Eidos". In the "Eidos" system we have implemented the software interface that allows posting of images and identifying their outer contours. By multivariable typing, the system creates a systemic-cognitive model, the use of which, if the model is sufficiently accurate, may be helpful in solving problems of system identification, prediction, classification, decision support and research of the modeled object by studying its model. For this task the following stages: 1) input images of ammunitions into the "Eidos" system and creation of their mathematical models; 2) the synthesis and verification of the models of generalized images of ammunition for types of weapons based on the contour images of specific munitions (multiparameter typing); 3) improving the quality of the model by separating classes for typical and atypical parts; 4) quantification of the similarities-the differences between specific types of munitions with generic images of different types of ammunition of the weapon (system identification); 5) quantification of the similarity-differences between types of ammunition, i.e. cluster-constructive analysis of generalized images of ammunition. A numerical example is given. We also possess a successful experience of solving similar problems in other subject areas

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

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

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

The article proposes to use the automated systemcognitive analysis (ASC-analysis) and its software tool which is "Eidos" system to solving multiparameter typing, system identification and cartographic visualization of spatially-distributed natural, environmental and socio-economic systems. Imagine, that we have an original point cloud with coordinates (X,Y,Z), each with known values of gradation descriptive scales of nominal, ordinal, or numeric type S(s1,s2,...,sn). Then the "Eidos" system provides: 1) building a model that contains generalized knowledge about the strength and the direction of the influence of descriptive gradations of scales at Z=M(S); 2) estimation of the values of Z for points (X,Y) described in the same descriptive scales S(s1,s2,...,sn), but not a part of the original point cloud; 3) a cartographic visualization of the spatial distribution of values of the function Z=M(S) for points outside the initial cloud, using Delaunay triangulation. Basically, this means that the "Eidos" system ensures recovery of the unknown function values on the grounds of the argument and implements it in a generic setting, independent of subject area. We propose a new scientific concept called "Geo-cognition system", which is defined as a software system that provides conversion of source data into information, and knowledge in visualization and mapping of this knowledge, resulting in the cognitive map becomes graphics. This feature can be used to quantify the degree of suitability of the watersheds for cultivation of certain crops, the evaluation of the ecological situation on particular territories on the structure and intensity of anthropogenic load, visualization of results of forecasting of earthquakes and other unwanted risks or emergencies, as well as for solving many other similar mathematical essence of tasks in a variety of subject areas. We have also shown a simple numerical example

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

On the basis of local semantic information of the models of California the dependence of parameters seismic activity on the position of the space objects has been investigated and the model of short-term earthquake prediction has been created. The formal criteria of astronomical parameters of high informative value in the preparation and implementation of earthquakes have been established. On the example of semantic models, we have developed criteria for seismic hazard zones for individual study of the region of California 2x2 degrees of longitude and latitude with regard to the intended depth of the hypo-center and magnitude of possible earthquakes

Dependence of the Earth polar motion on celestial bodies’ positions is examined on the basis of semantic information models

The new methods for system-cognitive analysis to identify and present graphical visualization of causal functions from the large dimension empirical data and its software tools - «EIDOS» system are discussed.