The article deals with the problem of taking into account the existence constraints in the widespread task of identifying the properties inherent in an object (or features, or attributes) from an a priori determined set of properties measured in an object in the case of incompleteness and inconsistency of measurement results. The question is raised about the possibility of increasing the productivity of the author's methodological support developed for solving this problem by reducing the description dimension of the existence constraints of properties measured in an object. A natural model of existence constraints is a set of entities (for example, attributes of an object) with two binary coexistence relations defined on it - incompatibility and conditionality; the dimension of such a model is determined by the number of entities and the quantity of the noted existential relations. It is shown that the desired reduction of the existence constraints model of properties measured in an object is feasible based on the identification of equivalence classes in the set of measured properties and the definition of extended binary incompatibility and conditionality relations on the set of discovered classes. Quantitative assessment of the existence constraints reduction effectiveness was made by computer simulation statistical experiments. Of independent interest is the simulation tactics used, due to the multiply connected structure of existence constraints, as well as the multifaceted use of Höfding's inequality to estimate the appropriate number of statistical tests, which establishes exponentially decreasing estimates of the deviations probability of sums of independent random variables from the average of these sums. The results of the study confirmed the significance of dimension reducing of the existence constraints model and revealed the dependence nature of the gain obtained on the parameters that determine the configuration of these constraints.

The paper proposes a model of an immersive virtual simulator with biofeedback, which underlies the instrumental complex for creating, reproducing and maintaining immersive virtual simulators with biofeedback (IVT with BFB). The model is designed to form an information representation of a virtual simulator. The composition and interaction between the components of the model are shown, which make it possible to design, create, maintain and reproduce ICT with biofeedback. The stages of creation of ICT with biofeedback and the tools used are considered. The use of the instrumental complex is demonstrated in the example of the development of a virtual simulator. Currently, work is underway to describe scenarios for various research methods based on the presented model and their implementation.

The subject of the study is the algorithms of node localization in responsive wireless sensor networks (RWSN), which have a great prospect of application in many areas. The relevance of the work is due to the fact that the task of localization of nodes is one of the key ones in RWSN. Localization algorithms should be energy efficient, do not require additional hardware solutions and large computing resources, use a built-in routing protocol, noise-proof. Promising in this regard are variants of algorithms for localization of the transition along the distance vector (DV-Hop). However, they are characterized by a rather large error in estimating the location of sensor nodes. The purpose of the work is to analyze the accuracy of existing DV-Hop algorithms in determining the location of unknown nodes within the placement area using network infrastructure, radio exchange technology between nodes to assess their suitability for solving local positioning problems after performing the node ejection stage on the ground. Method. In the process of analysis, the method of sequential complication of the simulated algorithms for localization of sensor nodes in the RWSN was used, taking into account the types of nodes and their operating modes. The main results. Studies have shown that the most effective algorithm is one in which the minimum transition is corrected by using distance determination technology based on the received signal power (RSSI), and the average transition distance is corrected by the weighted average of the transition distance error and the estimated distance error. The simulation experiment showed a significant improvement in the characteristics of the classical DV-Hop algorithm in determining the location and a reduction to acceptable values of the error in determining the location of nodes. When conducting a simulation experiment in the Netlogo environment, the KNN algorithm was used. The results of the experiment show that the improved algorithm reduces the location error and has a higher accuracy of location determination. Practical significance. The expediency of applying the results obtained in the design of RVSN is substantiated.

The paper formalizes the semantic representation of the common digital profile of IoT devices, containing knowledge about the architectural solutions of the Internet of Things, the criteria for analyzing the network activity of information exchange participants in the Publisher-Broker-Subscriber scheme and the characteristics of controlled physical processes. In order to select the concepts underlying the formalization, current research in the areas of cybersecurity and data analysis of the Internet of Things are considered. The author has formed an ontology containing the concepts of the subject area and their relationships, reflecting IoTtechnology and instances of concepts that describe the implementation of the Internet of Things network in the Krasnoyarsk Scientific Center. The described network is used to monitor technological rooms with telecommunications equipment and includes measuring devices, telecommunications environment, virtual and physical servers, and application software. The instances of objects in the ontology have its own digital representation in databases, contains measurement results, statistical and spectral characteristics of data, and is used to solve practical problems.

When solving practical problems, quite often there is a need for the simultaneous application of machine learning and operations research methods. Since many methods for solving problems in both areas can be based on fundamentally different mathematical tools, it will be impossible to combine their results into a single model. This article presents an interconnected set of machine learning and operations research models designed to select the parameters of the technological processes. All models have a common mathematical formulation based on the mathematical programming problems with the partial-integer variables. The models have been tested on a real problem of selecting the composition of the charge and technological parameters of sinter production. It is presented in the sequence of their occurrence in the process of solving the problems set by the customers of the research. The first stage is based on solution of the regression problems with a selection of the most informative features and the degree of their influence on the output features is carried out. Then, based on the classification problems, the recommended areas of controlled input features are determined to obtain the high-quality products. These areas can have a rather complex geometric configuration in a feature space. Further, within the framework of the operations research problems, the reference states of a process are determined, to which it is necessary to strive. At the final stage, the results of all previous studies are combined into a single optimization model, which can be supplemented with the results of the researches obtained from other sources of information, if these results can be represented as the linear constraints. The proposed approach to the parameter optimization can be used in the various subject areas.

The paper presents a non-stationary model of the flow of a viscous compressible heat-conducting gas, which makes it possible to describe the thermal and velocity fields created by the main high-temperature flow flowing from the outside of the plate, the internal cooling flow and the jet that creates a cooling film on the protected surface. The gas dynamics is described based on the numerical solution of the Navier-Stokes system of equations by the explicit McCormack method with splitting of the original operator in spatial directions and a nonlinear correction scheme. The block finite-difference grid was constructed by the Thompson method with clustering of nodes in the near-wall region. The algebraic Smagorinsky model is used as a subgrid turbulence model. The Seidel iterative scheme for the stationary heat conduction equation in generalized curvilinear coordinates is written.

A mathematical model of a micromechanical gyroscope (MMG) of a hybrid type is constructed, in which, in order to eliminate the "zero displacement", the principle of modulation of primary information in a mechanical circuit and its removal in a rotating coordinate system, well-established in rotary vibrating gyroscopes, is used. In addition, a mode of parametric excitation of the sensitive element has provided, which allows expanding the measuring capabilities of the device without interfering with its mechanical circuit and increasing the accuracy of the MMG. The simulation of the model has carried out in the Matlab-Simulink environment, which makes it possible to solve the differential equations of the model in an interactive mode with various input parameters. Based on the results obtained, the conditions for the implementation of parametric excitation of the MMG by modulating its angular velocity of rotation (dynamic rigidity) have formulated. The possibility of a significant increase in the accuracy of measuring the angular velocity by changing the level of parametric "pumping" of the device, as well as the ability of the device to determine the third component of the angular velocity, which coincides in direction with the gyroscope angular momentum vector, has shown. The constructed simulation model makes it possible to design an absolute angular velocity sensor capable of solving inertial navigation problems with the required accuracy.

The results of computer implementation of the basic model of the action potential of Hodgkin-Huxley nerve fibers and the modified model of the electrical activity of heart cells (Purkinje fibers) proposed by Noble are presented. To solve the differential equations of models in the Matlab high-level programming environment, user interfaces have been developed that allow you to work with models in an interactive mode. Simulation of the models has carried out for different values of the parameters. The analysis of the obtained results and their comparison with the available experimental and theoretical data of other authors confirmed the conclusion that the Noble model (unlike the Hodgkin-Huxley model) adequately describes the electrical processes occurring in myocardial cells. However, to use this model for practical purposes, it is necessary to supplement it with some parameters that take into account, for example, the effect of calcium ions. The authors of this article have proposed a modification of the Noble model, including an external stimulating current, and carried out numerical experiments. Graphical results are presented, practically important conclusions are made.

The paper considers the problem of recovering the horizontal wind speed from lidar scanning data, which provide measurements of the radial component. An approach is proposed in which the wind speed components are calculated not at a single point, but at a given set of nodes located along a given direction. The proposed algorithm uses the idea of coordinate-wise calculation of vector components. Each component is calculated by the spline approximation of a specially selected subset of measurements. The results of numerical calculations are presented.

The paper presents a graph-analytical approach to the problem of minimizing risks in the Demand Response (DR) Aggregator’s operation under adverse external influences. An example of drawing up a Bow-Tie diagram containing proactive and reactive protection measures of the DR-Aggregator is given. That approach is proposed to increase the number of proactive protection measures by transferring some reactive measures to the category of proactive.

The situation with fires in the Irkutsk region in 2010-2021 is considered. The analysis was carried out with the help of a comprehensive fire hazard indicator, which allows assessing the situation on the territory relative to the level of fire danger for the subject as a whole (Irkutsk region). The most and least prosperous territories are marked. It is shown that the main part of the territories is characterized by an increased level of fire danger, and some territories in some years are high and extreme. Since the complex indicator used for calculations characterizes the situation in statics, it is proposed to perform a similar calculation relative to the base year 2010 to assess the dynamics. It is shown that the dynamics of the situation looks somewhat better, but the changes are not fundamental. It is assumed that the high level of fire danger in the region is associated with a high proportion of wooden buildings and a long (more than six months) heating period with poor provision of fire protection facilities in the residential sector, where up to 80% of fires occur

The article presents the implementation of the mathematical model. By constructing multiple regression, it was possible to assess the reliability of the counterparty. Evaluation of the reliability of counterparties is one of the main tasks when working with counterparties at an enterprise. Conducting a reliability assessment will allow an organization to avoid financial risks and unwanted tax audits. The proposed approach of using multiple regression in assessing the reliability of a counterparty in an organization is suitable for use for 6 months of current work. Therefore, for greater efficiency, it is recommended to carry out this work at intervals, once every six months. The values of the coefficients of the turnover of accounts receivable and the indicator of profitability of sales can be used to assess the reliability of the counterparties of the enterprise.

The article presents an analysis of documents and news on the corporate website of the Siberian Branch of the Russian Academy of Sciences - the SB RAS portal www.sbras.ru. A feature of the corporate website is that it contains extensive information about the activities of the Department since its foundation in 1957. The portal of the SB RAS began its work in 1996, and since that time, the systematization of documents has been carried out, which allows for a deep analysis. In total, the corporate website stores more than 16 thousand records on research in the field of exact, natural and human sciences. A large layer of documents refers to the development of Siberia. Currently, the corporate website provides brief and detailed information about the developments of institutes and universities of the Siberian macroregion, which carry out the task of achieving the technological sovereignty of Russia. The authors propose to provide reliable, scientifically based information to link the resources of the websites of institutes, universities and social networks into a common information space.

Today, knowledge graphs are widely used in various domains, for example, in industry, commerce, finance, and social networks. A knowledge graph is a powerful means of information combination and representation using standardized knowledge modelling methods. However, the development of knowledge graphs and, in particular, their population with new specific entities (facts) remains a difficult task. The use of various information sources can facilitate this process. Such a source can be tables that potentially contain rich semantic information. In this paper proposes an approach and its software implementation for automated extraction of significant information from tabular data in the form of facts and population of a target knowledge graph with them. The main feature of the proposed approach is the combination of heuristic methods with deep machine learning models for semantic table annotation. The applicability of the proposed approach is demonstrated by two examples: labor market analyzing for the Irkutsk region and assessing the technical state of petrochemical equipment.

The article considers the basic principles of categorization of security events, formulates the requirements to it and offers a methodology for its application. Examples of event categorization options for various information protection tools are given. Possibilities of scaling the categorization system and methods of its adaptation for use in industrial automation and control systems are determined. The results of an experiment on the application of the methodology to improve the protection of automated systems on the example of a virtual cyber polygon are also presented, confirming the effectiveness of this methodology and the possibility of its application to the protection of industrial systems.