The article presents the development of a mathematical model of video monitoring based on a self-organizing network of unmanned aerial vehicles. The necessity of developing models and algorithms for providing geoecological monitoring using a wireless self-organizing network based on unmanned aerial vehicles is shown. Models are presented that allow calculating the speed of information transfer in the network and reducing the number of failures in the process of transmitting video data. With the help of models, it is possible to substantiate the power of network transmitting devices, at which the losses of transmitted packets are significantly reduced. The practical use of the model contributes to the achievement of the required quality of video surveillance in a wireless self-organizing network of unmanned aerial vehicles in the process of geoecological monitoring.
This article aims to achieve more efficient automated software systems use in the geo-ecological monitoring of agro-industrial sector resources. A method of detecting resource-intensive inquiries to agricultural resources databases is developed. Self-Organizing Map is used for clustering inquiries to databases in the method. Additionally, an algorithm is proposed to discover resource-intensive inquiries and the corresponding software. The performance evaluation demonstrates that the suggested method considerably increases the correctness of detecting resource-intensive inquiries to databases compared to other counterparts. Accordingly, in geo-ecological monitoring of agricultural objects and resources, the method is recommended for practical application.
In life, a chaotic system has many applications in different fields, including physics, biology, communication, and cryptography. In this study, a new hyperchaotic system is introduced. This hyperchaotic system is a two-dimensional system that is based on three maps-namely, logistic, iterative chaotic, and Henon maps. The dynamics of this system are investigated using maximal Lyapunov exponents, bifurcation diagrams, phase portraits, basin of attraction, and complexity via entropy. This system shows highly complicated dynamics. On the basis of the proposed system, a new algorithm for image encryption is also introduced. Confusion and diffusion can be achieved with this algorithm, which are fundamental demands. The stochastic behavior of this system is used to reinforce the security of the encrypted image. The image is divided into four parts, each of which uses a different random key established by the proposed chaotic system. The security of this cryptosystem is validated on the basis of key security parameters and common attacks.
This article depicts a decision support system (DSS) devoted to the coordinated administration of urban frameworks. This framework defines the information and related treatments normal to a few civil managers and characterizes the necessities and functionalities of the PC devices created to enhance the conveyance, execution, and coordination of metropolitan administrations to the populace. The cooperative framework called Decision Support System for Urban Planning (DSS-UP) is made out of a universal planning and coordination framework. So, it helps the decision-making process, a DSS was created as a learning-based framework gave derivation components that empower urban architect to settle on key decisions as far as specialized meditations on civil foundations. The learning-based framework stores experts_ information and additionally answers for past issues. Preparatory execution comes about demonstrate that DSS-UP viably and effectively underpins the decision-making process identified with overseeing urban foundations by using K-means++ data mining algorithm.
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