Journal archive

The issues of information support for decision-making during periodic maintenance of gas-cylinder equipment of vehicles running on natural gas, ensuring safe operation, contributing to an increase in the efficiency of transportation of goods and goods: reducing vehicle downtime due to failure of the fuel system using gas fuel by 10–18%; reducing the likelihood of functioning of gas equipment in hazardous modes by 12–17%. The technical requirements for gas equipment and procedures for its periodic maintenance are formulated. The concept of the formation and application of a unified state register of gas equipment, which is a tool for limiting admission to the turnover of products that does not meet regulatory and market requirements, is proposed. An information-logical model of decision-making support has been developed, which allows, depending on the current technical condition of assemblies and parts, based on the specified requirements for the duration of the period between maintenance, to propose the best option for carrying out diagnostic, repair and commissioning measures for gas-cylinder equipment of vehicles. The procedure for the formation of an extended list of measures for periodic maintenance of gas equipment is presented on the example of individual nodes of the fuel system of a vehicle running on compressed natural gas. The software implementation of the information- logical model is carried out in the form of a plug-in extension to the database core of the decision support information system for the operation of gas equipment, implemented on the Oracle database management system with integrated support for the high-level object- oriented language Java. For the convenience of working with the information-logical model, a computational and analytical module of the information system for decision-making support during the operation of gas-cylinder equipment with elements of fuzzy logic has been developed. The model was tested on the example of the implementation of measures during the periodic maintenance of the gas equipment of the KamAZ 65116 truck.

The article justifies actuality of application of neural network methods for identification of significant predictors of the transport and logistics infrastructure of regions of the Russian Federation. The condition of the logistics industry of the Russian Federation in comparison with foreign countries has been analyzed. It was concluded that it is necessary to increase the accuracy of estimation of indicators of transport and logistics infrastructure of regions in order to identify their impact on the development of logistics. The problem of the traditional methodology of building a model of transport and logistics infrastructure of regions based on the application of mathematical and econometric analysis lies in the inability of the latter to find and accurately describe the non-obvious dependencies in the data. The expediency of sequential coupling of econometric and neural network research tools has been determined. The two-step procedure of identification of factors influencing the logistics development of the Russian Federation has been tested. As a result, it was possible to select the most significant socio-economic (average per capita income of the population, retail trade turnover, imports of the subjects of the Russian Federation) and infrastructure factors (the share of paved roads, the shipment of goods by public rail, the departure of passengers by public rail, the density of public railway) logistics infrastructure on the basis of an econometric approach. In the second step of the study, a neural network model of the remaining factors was developed based on the development of classification trees and a neural network, acting as a kind of computational filter, which allowed solving the problem of attribution of macroeconomic data and achieving a high level of significance of forecasts. The proposed approach of sequential coupling of econometric methods and neural network modelling has universality and practical importance, therefore it is applicable to the study of a wide range of macroeconomic processes.

This work is devoted to mathematical modeling of the dynamics of inhomogeneous electrically charged media. A dusty environment - solid particles suspended in a gas – was considered as an inhomogeneous medium. The mathematical model implemented a continuous approach to modeling the dynamics of inhomogeneous media. The complete hydrodynamic system of equations was solved for each component. The system of equations for the dynamics of each component included the equations of mass continuity, momentum components, and the energy conservation equation for the mixture component. Intercomponent interaction took into account momentum exchange and intercomponent heat transfer. The carrier medium was described as a viscous compressible heat-conducting gas. The flow was described as a flow with a two- dimensional geometry. The equations of the mathematical model were supplemented with initial and boundary conditions. The mathematical model took into account the wall viscosity in the channel. The system of equations of the mathematical model was integrated by McCormack's explicit finite-difference method. To obtain a monotonic grid function, a nonlinear scheme for correcting the numerical solution was used. The mathematical model was supplemented by the Poisson equation describing the electric field formed by charged dispersed particles. Poisson's equation was integrated by finite-difference methods on a gas-dynamic grid. Such a choice of the computational grid was necessary to calculate the concentration of particles required both for solving the electric field equation and for calculating the physical fields of the dynamics of inhomogeneous media. The reciprocal motion of a gas suspension caused by the movement of dispersed particles under the action of the Coulomb force was numerically investigated. The values of the surface and mass densities are determined, at which the models of the surface and mass densities of charges in the simulation of such a process are the same. It is revealed that the surface and mass models of charges are identical with respect to the volumetric content.

Within the framework of the concept of a circular economy, research in the field of creating technological systems for recycling waste from mining and processing plants occupies one of the key positions. This is connected, on the one hand, with significant volumes of such waste, reaching tens of millions of tons and posing a significant environmental hazard to air and water basins, human health, and, on the other hand, with their rich chemical and mineralogical composition, which makes it possible to call them accumulations of technogenic deposits. In this regard, the task of creating control systems for technological processes of processing such waste and their information support, including support for all stages of the passage of information processes, is urgent. The novelty of the presented research lies in the proposed structure of an intelligent control system for a complex chemical and energy technological system for processing apatite-nepheline ores, as well as in an algorithm for predicting technological parameters, which is part of the information support of the control system under consideration. The algorithm is based on the use of the apparatus of deep recurrent neural networks and Kalman filtering, which is used at the stage of data preprocessing to train the neural network. The paper describes the proposed algorithm for predicting multidimensional time series, adapted to the considered technological process, presents the software executed in the MatLab environment to demonstrate the efficiency of the specified combination of methods for processing technological parameters. In a model experiment, it has been shown that the use of filtering makes it possible to increase the accuracy of the forecast, which is especially noticeable at its large horizons. The practical significance of the research results is the proposed structure of an intelligent control system for the processing of apatite-nepheline ore waste and software for predicting its parameters, which can be used in various decision support systems.

Open biometric images (fingerprint, iris, face) are "in sight" and therefore compromised in the natural environment. In this work, it is proposed to use data on the internal structure of the outer ear obtained using echography as biometric images. The individual characteristics of the ear canal of subjects are hidden from direct observation and cannot be copied by photographing. The proposed authentication method is based on cepstral analysis of echograms of the ear canal using neural network biometrics to code converters, trained in accordance with GOST R 52633.5. The neural network biometrics-code converter allows you to associate a user's cryptographic key or password with his biometric image. This is a shallow neural network of one or two layers of neurons, which is configured to generate a key specified during training when an image of a known user arrives, and when an unknown image arrives at its inputs, generate a random code with high entropy. At the entrance to this network, cepstral signs of echograms were received. To apply the method in practice, you need a special device that combines a headphone with a sound-proof housing and a microphone. The results obtained can be called optimistic EER = 0.031 (FAR = 0.001 at FRR = 0.23). The use of neural network converters biometrics-code showed a relatively higher percentage of errors in comparison with multilayer neural networks and the naive Bayes classification scheme, however, neural network biometrics to code converters allows you to implement authentication in a protected mode. This means that the subject's biometric data will be protected from compromise at the stages of storage, execution and transmission via communication channels.

The effectiveness of fuzzy cognitive modeling methods for analyzing and predicting the state of complex technical systems (STS) is justified by the following reasons: significant interdependence, non-linear nature and incompleteness of information about the mutual influence of the analyzed parameters of the CTS; a variety of effects of internal and external factors on the CTS; complexity and cost of conducting experimental studies during the operation of these systems. The main limitations of fuzzy cognitive models for modeling STS dynamics are: the complexity of taking into account the mutual influence of parameters with their different time lags relative to each other; the need for their constant operational adjustment and training of component models for all parameters during the operation of the CTS. In this paper, Fuzzy Relational Cognitive Temporal Models (FRCTM) are developed. These models combine the advantages of various types of fuzzy cognitive models, and at the same time neutralize the main limitations of the analysis and prediction of the state of the CTS, which are inherent in the well- known fuzzy cognitive models. The paper also proposes models of system dynamics that take into account the specifics of the FRCTM. We have also developed an approach and implemented a method for calculating fuzzy dependencies in vector-matrix form for dynamic modeling of the CTS. The proposed method makes it possible to solve the problems of increasing the uncertainty of the results and the output of fuzzy values of the FRCTM concepts beyond the ranges of the base sets due to the execution of mass iterative computations. An example of modeling heterogeneous electromechanical systems based on FRCTM is given. The results obtained are the basis for solving a whole range of tasks of analysis, predictive evaluation, modeling of different scenarios of the functioning and development of heterogeneous electromechanical systems for various system factors, operating modes and external conditions.

In recent years, simulation has been actively used to study socio-economic processes in order to test various management decisions (for analyzing risks, projects, regional processes, logistics, etc.). Today, three simulation systems (Actor Pilgrim, AnyLogic, GPSS World), each of which has its own areas of application, are the most widespread in Russia. So, the system Actor Pilgrim is most suitable for modeling socio- economic processes. The first version of this system was developed by a group led by Professor Alexander Anatolyevich Yemelyanov more than 35 years ago to solve experimental problems in the direction of "Flexible automated production". It was based on a new modeling paradigm, which was built on the actor-network theory. The transition to solving new problems, primarily in the economics, led to the need for its further system development through the implementation of temporal, financial and spatial dynamics. Currently, the system development is carried out through the construction of hybrid simulation models, which is associated with the introduction of various analysis methods. So, when modeling actual technical and economic processes (for example, import substitution of high- tech products), it is proposed to use artificial intelligence methods that allow you to get informed decisions in conditions of information uncertainty. Models that include fuzzy logic methods and swarm algorithms (in particular, bacterial optimization) have shown good results. For example, fuzzy logic methods have been used to assign "fair" priorities to option projects through a detailed analysis of the factors of the internal and external environment of enterprises that will implement them. Bacterial optimization algorithms have been used to search for "promising" areas for the implementation of the projects of import substitution of high-tech products. These swarm algorithms are distinguished by the ability to simultaneously study favorable and negative factors, i. e. allow taking into account various risk situations. The modern version of Actor Pilgrim is intended for systems analysts, economists-mathematicians and other professionals who are familiar with programming, but are not professional programmers.

The article 30 of the Federal Law "On the Securities Market" establishes that significant facts are information that, if disclosed, may have a significant impact on the value or quotations of the issuer's securities and (or) on the decision to acquire or alienate the issuer's securities by any interested person acting reasonably and in good faith. At the same time, there are very few empirical studies proving the influence of significant facts on the value or quotations of securities of Russian issuers. Modeling of such influence in order to manage the value and capitalization level of Russian issuers is advisable for investors, owners and management of Russian public joint stock companies to study the possibilities of managing the value and capitalization level of companies. The solution to this problem is based on measuring the results of the joint-stock company's activities and publicly disclosing the information necessary for making managerial decisions, which in the Russian Federation includes, among other things, significant facts. Significant facts are events that can change the current state of the company, in particular, affect such an indicator of its activity as the level of capitalization, therefore, affect the decisions made by the interested person. A few studies on the impact of significant facts on the level of capitalization of Russian companies have already been conducted earlier, however, since their implementation, a number of regulatory documents have come into force that change the legislative environment and affect, among other things, the composition of mandatory registration and disclosure of significant facts. This paper presents the results of a study aimed at establishing a list of the most significant events characteristic of companies' activities, identifying events that are universal in terms of the frequency of occurrence and significance of consequences, and finding out whether there is a connection between their occurrence and the effects caused in the form of changes in the values of financial indicators. For the research, data from 20 large Russian companies representing the oil and gas, metallurgical, chemical and energy industries were used, and received in the form of reports for the period following the introduction of changes in the regulatory environment.

Ensuring information security of automated process control systems (IACS) is a difficult task and its solution requires an integrated approach. Various computer threats need to be considered, which may be external, internal, accidental or deliberate. With the global growth of cybercrimes and the constant improvement of cyberattacks, it is necessary to increase the level of security of IACS, web resources, information systems, etc. Achieving the goal of increasing the level of security is possible by solving the problem of training users to respond to the facts of the implementation of computer threats during the operation of the IACS, i. e. information security incidents. The article describes software, the main task of which is to provide users of an industrial automated system with practical skills for an adequate response to incidents, which will increase the level of users' knowledge in the field of information security. The paper presents an analysis of the information security of an automated process control system, which showed that, on average, in 89.5% of cases, attackers use malicious software to gain access to information unauthorizedly, and on average, in 83% of cases, they use social engineering methods. An industrial automated system of a large enterprise in the machine- building industry of the Republic of Tatarstan was selected for the study. The results of the study and experimental data showed that as a result of training and after it, users more correctly and adequately respond to emerging information security incidents due to the fact that most situations were considered and analyzed during the training period using software. On average, the number of attacks in the analyzed periods as a whole decreased by 28%: the number of attacks carried out using social engineering methods decreased by 51.75%, the number of attacks using malicious software by 40.25%, the number of DoS-type attacks – by 11.75%, the number of credential brute-force attacks – by 7.5%.

The geographical location and tourist features of St. Petersburg require a specialized web service for owners and tenants of river transport, aggregating all the information necessary for them. Currently, such information is available in various news sources, web portals and groups in social networks. The work presents a prototype of a service for small river transport users. Information needs and functional and requirements for it were identified during in-depth interviews with stakeholders of the project. The web service database is implemented in the PostgreSQL DBMS with the PostGIS extension. The work presents the structure of the service, which includes 10 pages, describes its main sections, such as current regulatory documents, news, interactive maps, reference information, as well as technical information about ships and restrictions on their movement due to technical characteristics. During its development, an analysis of existing solutions related to each section was carried out. During the "Maps" section development, an analysis of existing web tools for displaying interactive maps and the selection of the best solutions was carried out. Using the Google Maps designer, interactive maps were created for the web service being developed. The first of them is a map of the city's water bodies, containing such layers as: floating gas stations, lighthouses, customs, checkpoint and Ministry of Emergencies, private yacht clubs and marinas, berths and quayes, bridges, etc. The interactive weather map allows the user to get acquainted with the weather conditions, as well as their 5-day forecast. One of the priority functional requirements of the web service, called stakeholders, was the determination of water barriers and bridges that were inappropriate in the size of the vessel. The "Your Ship" section of the developed prototype web service offers a solution to meet this requirement. The developed web service is one of the favorable incentives for the development of the water tourism sphere and the use of river transport in St. Petersburg.