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The effectiveness of management activities is largely determined by the degree of reasonableness and efficiency of selecting a decision-maker and delegating the necessary powers to him. To solve this problem, it is advisable to use mathematical methods and information technologies that ensure the specified selection in an automated mode. This approach involves the creation of a DSS using unpopulated decision-making technologies. This allows you to identify employees or groups of employees who are most suitable for the implementation of managerial functions in terms of certain quality indicators. The use of unpopulated decision-making technologies in the interests of economic entities makes it possible to reduce the time and cost of their adoption by automating the transit management level. The purpose of the study considered in this article is to solve the problem of organizing the effective selection of a decision maker (DPR), or a group of people, as well as transferring the task to be performed automatically. To achieve this goal, the mathematical modeling of the LPR selection algorithm (LPR group) was carried out by performing operations on sets containing significant indicators and solving a mathematical programming problem. The proposed mathematical apparatus makes it possible to create a subsystem of the DSS responsible for the selection of a DSS (group of DSS) capable of making a high-quality management decision under given constraints, and transferring tasks to it for execution. The specified restrictions contain the type of task to be solved, the possibility of its implementation with the help of unpopulated decision-making technologies, competence limitations of LPR (groups of LPR), time constraints. The DSS subsystem, created on the basis of the proposed mathematical apparatus containing the task of optimizing the selection of LPR (LPR group) according to the cost criterion, makes it possible to minimize the cost of decision-making.

The current period of technological progress is characterized by a significant penetration of digital technologies into all spheres of life and society. At the moment, a fairly extensive material has been accumulated with the results of research aimed at recognizing the effects, mostly implicit or weakly exposed, which are inherent in digital technologies, as well as to disclose the mechanisms producing them. However, work in which the task of creating a holistic representation would be solved, reflecting the most important effects in their entire entirety, have not yet been published. The article attempted to analyze all the main features of the application of such technologies in an academic environment, closely related to information processes and where the introduction of digital technologies is especially active. In order to summarize theoretically and practically proven strengths of digital technologies, to identify the most successful applications built on their base, to identify negative manifestations and effective steps taken to neutralize threats, a fairly representative set of research results on identifying individual factors and the study of the effects due to them, specific for digital technologies for a certain applied orientation. Based on the basic concepts, taking into account the experience of the implementation of organizational and administrative measures, focused on achieving the most positive effect of the introduction of digital technologies and elimination of sources of undesirable consequences, a set of key objects of comprehensive analysis is proposed, which should precede decision-making to integrate technologies into the practical activities of the academic structures and serve as the basis for the formation of general policy and strategic plan.

The article considers a fundamentally new generation of soft exoskeletons based on magnetic rheological modules. A model of an exoskeleton link with adjustable rigidity is proposed, for which a system of differential equations of motion is compiled. A model of an exoskeleton for human lower extremities, composed of modules with magnetic rheological fluid, has been developed. The problems of kinematics and dynamics that arise when controlling the movement of an exoskeleton are presented. A block diagram of an algorithm for controlling the movement of an exoskeleton has been developed, solving control problems taking into account neural network methods. A qualitative study by analytical methods of the proposed mathematical model of an exoskeleton with links with adjustable stiffness is carried out. The use of regulation of the rigidity of the links of the exoskeleton modules in the necessary way will make it possible to create devices that are comfortable for the user, both from the physiological and psychological points of view. Soft exoskeletons will be in demand in many industries and medicine. The use of electromagnetic actuators, which, as a rule, have smaller dimensions and energy consumption, an almost instantaneous response speed in comparison with pneumatic drives, hydraulic drives and electric drives, is promising and technically, energetically, environmentally, economically more acceptable. Under the action of electric or magnetic fields, the stiffness of electroelastic and magneto-rheological materials can change by more than an order of magnitude. This makes it possible to create exoskeleton links with adjustable stiffness. Regulation of the rigidity of the elements of the exoskeleton modules in real time is a complex control task. Therefore, exoskeleton motion control requires the development of adaptive type algorithms based on a neuro-fuzzy approach, using information received from feedback. Neural network algorithms for self-learning in the process of functioning are a logically expedient part of a soft bionic exoskeleton. Also, as a necessary component of the exoskeleton, along with the actuator part, a sensor system is needed with sensitive sensors for the user’s neuromuscular impulses and various sensors for position, speed, acceleration, force, moment of force of the exoskeleton. A comprehensive study of scientific and technical problems of the functioning of the model of the magnetic-rheological medium, exoskeleton modules and their compilation into a single multi-link structure, its movement using the technology of modern mathematical modeling was carried out. The construction of neuro-fuzzy control systems for soft exoskeletons is described as part of the development of new mathematical methods for modeling complex technical objects using modern mechatronics and cyborgics.

Neural network architecture based on polymer macrocells acting as neural elements and capable to generate electrically conductive synaptic junctions is developed. The architecture of a neural network processor where each component can record and produce a response to energy effects of different nature: electrical, optical and electrostatic has been developed. This function of the neural network eliminates the limitations related to the perception of the input information only by the input layer of the neural network processor. The impact of the influence of different input data representations on the information processing by the macrocell has been studied. The efficiency of temporal and electrical degradation of a neural network macrocell as a complex phenomenon directed on adaptation of a neural network to this process and generation of an algorithm for distribution of elements of a tutorial sample evenly over the total volume of available neural cells has been studied. The article studies a method of generation of episodic circulating memory, which significantly improves the speed of generation of a solution by the network, taking into account the gravitational interaction with macrocells. The revealed specific nature of the influence of the gravitational field on the functioning of neural network clusters was the basis for natural selection of cells by the performed properties depending on the spatial position in the neural network architecture. A method of exposure of the cell to physical equivalents of tutorial sample elements converted into different energy patterns to control the configuration of the macrocell using all available modes of information perception has been provided. Each exposure containing information on the tutorial element (optical and electrostatic) supports the generated generalising abilities of the neural macrocells composition. Practical significance of the performed research comprises the designed neural network system, which achieves an increase in performance due to self-organising oscillating neural clusters. The developed neural network model is used to reduce radio deviation and associated navigation errors due to conductive obstacles or atmospheric formations.

The results of a study are presented, the purpose of which was to develop a steganography algorithm for hiding text messages in video files. The algorithm is based on the use of a diffusion-probability model with noise reduction, which is implemented by a deep artificial neural network. The algorithm consists of two parts – for the parties sending and receiving the message. On the transmitting side, the following is carried out: synthesis of handwritten images of symbols (signatures) of the line of the hidden message, alignment of their frequency; applying direct diffusion to signatures, resulting in the generation of a noisy image that is deposited into a video stego container. At the receiving end, signatures are extracted from the video content, back diffusion is performed to obtain signatures of handwritten string characters, which are recognized using a convolutional neural network. The novelty of the research lies in the original developed algorithm for steganographic information protection in video files, as well as in a modified method of signature deposition based on the method of replacing the least significant bits. The method consists of bitwise embedding of bytes characterizing the pixel brightness level in the signature into the same blue brightness digits in a sequence of 8 frames of a video stego container. This method made it possible to significantly reduce the visible changes made to the video content when replacing not the least significant bits, but the middle significant bits in the stego container. This, in turn, provides greater resistance to compression attacks when transmitting information over the stegochannel. The practical significance of the research results lies in the developed software, with the help of which the algorithm for steganographic information protection in video files was tested, which showed high values of the peak signal-to-noise ratio and the index of structural similarity of images when embedding information in the middle bits of the bytes that set the brightness of the pixels of the stego container.

The presence of vulnerabilities in software is a pressing problem. Vulnerabilities can serve as a basis for breach of confidentiality and information leakage. The purpose of this study is to increase the level of software security at all stages of the life cycle from development and implementation to operation. Achieving this goal is possible through automated analysis of program code and increasing the types of vulnerabilities detected. The work proposes a secure software delivery pipeline that allows for static and dynamic analysis of program code, analysis of the search for vulnerabilities in third-party components and Docker images. The article reviewed popular software tools, their distinctive features, and provided justification for the choice of software solutions that form the basis of the developed secure delivery pipeline. The novelty of the work is the ability of the pipeline to automatically detect vulnerabilities at all stages of the software life cycle, from planning and design to testing, deployment and monitoring in a production environment, which allows you to eliminate vulnerabilities at an early stage, thereby increasing the level of software security. Conducted testing and approbation of a secure software delivery pipeline. Based on the assessment results, the developed secure software delivery pipeline showed that on average 98% of vulnerabilities were identified using the Semgrep tool, 90% of vulnerabilities using the OWASP ZAP tool, 96% of vulnerabilities using the Dependency-Track tool, and 88% using the Trivy tool. The results of the study and experimental data showed that on average, as a result of testing, the accuracy of detecting vulnerabilities is 93%. The practical value of the work lies in the fact that the developed secure software delivery pipeline can be used as a tool for detecting program code vulnerabilities by software development specialists, as well as information security specialists of IT companies. The results obtained can be used in the field of secure software development, formalization and interpretation of vulnerabilities in program code, which will make it possible to create new rules for their identification and development of countermeasures to neutralize them.

Land use processes are the basic economic processes that determine the efficiency of the functioning of socio-economic systems. This is especially true for large urban agglomerations, for which these processes directly and indirectly significantly affect the volume of revenues to the budgets of various levels, as well as determine the investment attractiveness of the regions. As a result, the principles of rational land use should be based on the results of system analysis and mathematical modeling of the impact of external and internal environmental factors on all subjects involved in the processes of using land plots as the most important resource of the urban economy. The article is devoted to the development of two-level models that involve the use of regression analysis to determine the characteristics of the game matrix in the presence of a sufficiently large number of players with different interests. This approach is distinguished by the possibility of more complete consideration of factors influencing the efficiency of land use when assessing the intensity of land use in large cities and agglomerations, in conditions of external volatility. As a result, the construction of a multiple regression model describing the influence of factors, and the subsequent matrix modeling of game-theoretic conflict situations in land use makes it possible to support decision-making in the development of investment programs for the development of territories. The article discusses an example of the application of the proposed approach to the analysis of factors that have a significant impact on the efficiency of land use in the Moscow agglomeration. The results of the regression analysis led to the conclusion that the predicate of increasing financial and economic returns in the implementation of land use processes is the level of investment in fixed assets. On the example of the Moscow agglomeration, it is also shown that the obtained results of regression analysis can be used in the construction of game-theoretic models of land use, which, in turn, are expedient to apply to support decisions on state management of the market of land plots for various purposes.