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The problem of solving the task of discrete optimization is not completely solved. Lack of publications, scientific developments, algorithms and software products do not give the ability to transfer the mathematical apparatus of solving discrete optimization problems to the class P of computational complexity. All analytical and combinatorial algorithms for solving problems of linear and non-linear optimization are NP completeness. There are developments to improve the efficiency of robotic algorithms, they are filled with requests and actual ones. In this paper, it is proposed to use deterministic and probabilistic methods for forming a priority queue of decision vector components in order to assign positive values to them. After the formation of the variant of the solution, it is possible to vectorize as if the approached solution is taken away from the record value of the goal function, which in exact algorithms is like a solution, which results in a polyp. In this paper has a method for forming a priority line for concretizing the components of the solution vector. The basis of deterministic methods is the idea of a greedy algorithm. The location in the queue is determined by the value of the corresponding component of the cost vector. The appearance of the value of non-visibility in the system of restrictions increases the priority of the component. Behind such a way, another method of determination is modified. Probability assessment probability of priorities is based on the ideas of algorithms in an ant colony and simulated annealing. The scope of probability indicates the significance of the component - a contender for a positive value. A numerical example of a small variability of the task about a knapsack has been introduced, which demonstrates the imitation of a nearby solution. [ABSTRACT FROM AUTHOR]

Steganography methods are considered to be one of the most common technologies for the protection of any digital data when transmitted over open communication channels at a given time. The solution of the problem of digital data protection using steganography methods is used not only by government services, but also by terrorist organizations. Therefore, the need for research, development and continuous improvement of steganoanalytical methods is becoming extremely important. The steganoanalytical algorithm based on the study of the singular decomposition of digital image matrix blocks is proposed in the paper. The main purpose of this paper is to increase the efficiency of digital image steganoanalysis, in the absence of a container, by developing a new steganoanalytical algorithm based on the study of the singular decomposition of digital image matrix blocks. As a result of a detailed study of the steganography algorithm using the singular decomposition of digital image matrix blocks, the statistical characteristics of the singular values of image matrix blocks are established. Based on the defined characteristics, the paper presents the main steps of the stegananoanalytical algorithm. As a criterion for assessing the effectiveness of the developed steganoanalytical algorithm, the probability of detecting additional information was used. Errors of the first and second type are considered. To compare the results of the developed steganoanalytical algorithm with existing algorithms in open access, the following applications are selected: XSteg; StegSpy. The software product "StegoAnalysis" has been implemented for the automated solution of the stegananalytical problem for digital image. [ABSTRACT FROM AUTHOR]

The task of path finding by an agent is one of the basic tasks and is of great practical importance. As a rule, this is an optimization task that is solved in the space of the state graph in order to minimize the length of the path. Such a task becomes more difficult and becomes even more popular if it is solved on the basis of one graph space by several agents. In this case, another practically important optimization parameter appears, which is expressed by the number of conflicts between agents. Such an abstract formulation of the task has numerous variants of formalization and a large number of approaches to its solution. In this paper, the main element of the approach is the application of the classic Dijkstra algorithm, which is executed sequentially by each agent. When finding the shortest route, each agent modifies the graph space in such a way as to reduce the probability of conflicts with subsequent agents. This approach is original and a number of computational experiments were performed to verify it using software developed for this purpose. The experiments that were conducted demonstrate the adequate behavior of the main algorithm. The work analyzes the limitations inherent in the proposed approach within the framework of the abstract formulation of the task. The directions of further development of the basic approach have been determined. [ABSTRACT FROM AUTHOR]

At a time when the use of digital content in all spheres of life is constantly growing, the ability to verify the authenticity of digital files, in particular digital images, is extremely important in protecting information from integrity violations. In the information war, photo fakes are always used to achieve certain, often criminal, goals. Both society as a whole and individuals must take care of information security and protect their information space from unverified information. Modern methods of detecting violations of the integrity of graphic information to some extent address some issues of information security, however, they are not universal and often require development, improvement, additional research and so on. Thus, existing methods for detecting such a common method of image falsification as scaling are effective only in cases where the falsified part is enlarged, however, when reducing part of the image, they are not effective. Moreover, in open printing the problem of detecting reduced scalable parts of the image is not covered. Therefore, the aim of this work is to increase the efficiency of scaling detection as digital image falsification by developing an algorithm for detecting scaling with a negative coefficient. In this paper, the method of error level analysis is adapted to detect reduced parts of the digital image. The efficiency of the adapted method in terms of errors of the 1st and 2nd kind was: errors of the 1st kind - 2%, 2nd kind - 7%. In addition, it has been found that this method is also effective in detecting simultaneously scalable (reduced) and moved parts of a digital image. This method detects artifacts (errors) in the digital image, which occur when reducing its part - the falsified area has a higher high-frequency component than the rest of the image, which is amplified under the influence of compression after saving the falsification in a lossy format. [ABSTRACT FROM AUTHOR]

Objectives: Partial errors⁃in⁃variables (PEIV) model is a more general form of errors in variables (EIV) model. It has been widely used in the data processing of global navigation satellite system (GNSS), coordinate conversion, deformation monitoring and data fitting in the past ten years.Methods: First, the development history of PEIV model is reviewed. Then, five core problems of PEIV model are summarized and analyzed, including parameter estimation algorithm, precision estimation, random model estimation, expansion algorithm and data processing application. Finally, the applications of PEIV model are outlined. Results: We point out three questions for further research, including how to process big data by PEIV parameter estimation method, how to correct the bias of weighted total least squares(WTLS) adjustment by sampling method, and how to derive the formula of higher order parameter estimation covariance matrix are.Conclusions: This review paper aims to further promote the development of surveying and mapping da⁃ ta processing and provide readers with suggestions and references. [ABSTRACT FROM AUTHOR]