Abstract: The object of research is the dynamic characteristics for target groups of social networks. The subject of this study is to analyze the methods and models of the evolutionary characteristics of the social graphs of large dimension. The study examines in detail the approaches of analysis, quantitative characteristics graph models. Synthesized an algorithm to analyze the dynamic characteristics for target groups of social networks. The experimental results show the fact of adding a user to the subject area of interest, as well as visualize the entire process in real time. The developed software tools can be useful for further development and research topics related to the social network. When solving tasks used methods of mathematical logic, graph theory, mathematical statistics, the apparatus of mathematical analysis, linear algebra, mathematical modeling methods, theory of algorithms, as well as object-oriented programming techniques. The novelty of the study is to determine the dynamic characteristics of the target groups of social networks, as well as the visualization of the entire process in real time. The main conclusions of the study is that the developed software tool will enable to trace cause and effect indicators of changes in the social graph. The proposed prototype of the software will be of interest primarily marketers, system analysts, and professionals involved in the analysis and the study of social networks.

Abstract: The object of research is the image of a dynamically changing scene of artificial origin on the complex and statistically inhomogeneous background. The subject of research is the transformation methods and standard approaches of representation of color digital images in three dimensions. The study focuses on almost all basic colorimetric spaces used in building a clusters of object / background. Formation of the samples is carried out by the method of supervised learning. Calculation of objective indicators and comparison of subjective characteristics allows to determine the optimal color space for subsequent synthesis of algorithm for effective segmentation of this class of images. When solving the task authors used image processing techniques, probability theory, mathematical logic, mathematical statistics, the unit of mathematical analysis, linear algebra, mathematical modeling methods, theory of algorithms and methods of object-oriented programming. The novelty of the study is in determination of the optimal color space separation of clusters object / background for images of a given class. Visual characteristics of considered methods of representation of colorimetric spaces confirmed objective indicators of calculus. The main conclusions of the study is that RGB color space is the best choice for color segmentation algorithm synthesized as the representation of objects and the background form a weakly overlapping clusters.

Abstract: Modern systems of computer vision use intelligent algorithms that solve a wide class of problems from simple text recognition to complex systems of spatial orientation. One of the main problems for developers of such systems is in selection of unique attributes which remain invariant to various kinds of transformations. The article presents a comparative analysis of methods of detection and spatial localization of groups of point objects. The reviewed methods are compared by the performance and efficiency at specified dimensions. As of today there are no universal approaches to determine of such attributes, and its’ selection depends on the context of the problem being solved and on the registered conditions of observation. Various kinds of descriptors such as points, lines, angles and geometric primitives can be selected as dominating attributes. The authors study  algorithms for detection of groups of point objects based on the minimum spanning tree (MST) and using a model of associated continuous image (ACI).

Abstract: In this paper we propose a new systematic approach to monitor forest fires over large areas. Established architecture of the complex, as well as effective methods of centralization and decision-making. Scientific and technical challenge is to create a system of distributed video surveillance to solve the problem of early detection of forest fires. This article discusses the existing fire detection approaches: the use of specialized towers, fire detection methods from the air, with the use of aircraft of various classes, a holistic approach to forest fire monitoring system uses satellite monitoring, video monitoring system. The described system is designed for the detection of forest fires and the determination of their spatial coordinates in real time. For the operation of the software complex towers and existing infocommunication data transmission medium can be used. This article analyzes existing approaches in the field of forest fire monitoring. A new systematic approach to problems of this kind, which is characterized by high performance and maximum efficiency of the concept solutions with minimal resource costs.