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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology

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issn 2310-6018

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metadata of articles for the last 2 years

Reducing redundancy of laser scanning data for building digital terrain models

2023. T.11. № 4. id 1467

Zaytseva E.V. Kochneva A.A. Katuntsov E.V.

DOI: 10.26102/2310-6018/2023.43.4.033

The main subtle aspects of airborne laser scanning (ALS) involve a large level of density of laser reflection points (LRP) within a certain unit area. This results in the need to process a large amount of information while building digital terrain models (DTMs). Such processing is computationally intensive. For this reason, the main task which is solved during DTM building is to create an accurate description of terrain features required for geodetic works. At the same time, it is necessary to observe the minimum number of LRPs related to the characteristic landforms in the considered location to minimize the use of computing power. Currently available algorithms of information distribution for DTMs built on standard coordinate grids do not allow to successfully resolve data arrays while preserving the proper detalisation level of certain locations. New software, which is used in geodesy and makes it possible to create sparse data arrays during DTM building, is based on a closed code. The paper proposes an algorithm for finding unknown intermediate data obtained with laser scanning of terrain relief, which allows effective thinning of laser reflection points that are insignificant when describing the terrain relief. An automatic technique of DTM building is developed. An algorithm for searching unknown intermediate LRP arrays is formed. Displot is available for sloped areas as well. At the same time detailisation in the quality of structure lines and special points is preserved.

Keywords: digital terrain model (DTM), digital relief model (DRM), airborne laser scanning, quality assessment of digital terrain models, digital mine model

Adaptive configuration of the fuzzy logic controller of unmanned aerial vehicle flight dynamics

2023. T.11. № 4. id 1466

Potudinskiy A.V.

DOI: 10.26102/2310-6018/2023.43.4.021

Along with the rapidly growing demand for unmanned aerial vehicles for surveillance and reconnaissance, advanced controllers are needed for these critical systems. This article proposes a design of a flight dynamics controller that takes into account various uncertainties for a medium-range unmanned aerial vehicle. In addition to the nonlinearities of flight dynamics, three main sources of uncertainties caused by unknown controller parameters, simulation errors and external interference are considered. A reliable adaptive fuzzy logic controller responsible for nonlinear flight dynamics under the conditions of many uncertainties has been developed. Nonlinear flight dynamics relies on a soft association of local linear models. When constructing the controller, the optimal reference model is defined, which is stabilized using the linear quadratic controller procedure. Then a fuzzy logic controller is developed for the nonlinear model. In order to eliminate uncertainties, the gain coefficients of the fuzzy logic controller are reconfigured and constantly adjusted for reliable adaptation. The performance of a reliable adaptive fuzzy logic controller is evaluated in terms of stabilizing the transverse and longitudinal flight dynamics and tracking the state variables of the reference model under the conditions of various uncertainties.

Keywords: controller, fuzzy logic, flight dynamics, nonlinearity, uncertainty, model, control, parameter, unmanned aerial vehicle

Authentication of information system users by facial image

2023. T.11. № 4. id 1465

Guzairov M.B. Ismagilova A.S. Lushnikov N.D.

DOI: 10.26102/2310-6018/2023.43.4.017

Authentication belongs to the classical means of information security management of enterprise computer systems, the quality of which determines the security of the information system. This paper describes the authentication procedure of information system users by facial image. The architecture of an artificial neural network has been developed, biometric personal data sets have been formed and trained based on the recognition of information system users by facial image. As part of this research, the functionality of the artificial neural network architecture has been evaluated using international data banks (Dataset). Descriptors such as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) were extracted when recognizing information system users by facial image. A neural network-training model based on categorical cross-entropy was compiled, and the configuration of the compilation model (mini-sample size, number of epochs, activation function, and optimization function) was generated. The developed software module authenticates users of the information system on “friend-or-for” basis. The use of these image descriptors allows increasing the accuracy of user authentication in the information system (accuracy) and reducing the value of loss function (loss). The program code of the multimodal biometric authentication system has been implemented. To assess the efficiency of the software module, the first and second type error rates are given.

Keywords: authentication, biometrics, facial image, identity recognition, information system

Application rules for destructive ability of genetic algorithm operators in the problem of structural and parametric synthesis of business process simulation models

2023. T.11. № 4. id 1463

Petrosov D.A. Surova N.Y. Polyakov A.V.

DOI: 10.26102/2310-6018/2023.43.4.013

This study proposes the application rules for destructive ability of genetic algorithm operators in the problem of structural and parametric synthesis of business process simulation models. The aim of the research is to confirm the hypothesis that it is possible to influence the performance of a genetic algorithm by changing the operating parameters of its operators, which allows increasing the convergence of this evolutionary procedure and helps the intelligent algorithm overcome “bottlenecks”. The “bottleneck” of a genetic algorithm is understood as attenuation of the algorithm, finding the population at local extrema of the fitness function, etc. Based on this hypothesis, it is proposed to use an add-on in the form of an artificial neural network to intervene in the process of finding solutions as a control model. It is planned to simulate this process using the mathematical apparatus of Petri nets theory. When implementing such an approach to solving the problem, it is necessary to consider the influence of the destructive ability of operators on the behavior of the population and determine the order of actions that need to be performed to control the evolutionary search for solutions in the problem of structural and parametric synthesis of dynamic business process simulation models. The paper discusses examples of population states of a genetic algorithm as well as the results of applying the proposed rules for making adjustments to operator activities. The main operators that significantly influence the state of the population are considered: the selection operator, the crossing operator, and the mutation operator; the influence of the reduction operator was not regarded in this study.

Keywords: genetic algorithm, genetic algorithm operators, artificial neural network, structural and parametric synthesis, simulation models, business processes

Query cost estimation and development of an application for processing resource-intensive queries

2023. T.11. № 4. id 1462

Nurmatova E.V.

DOI: 10.26102/2310-6018/2023.43.4.026

Rapid growth of stored data volume necessitates integration of tools for monitoring, analysis and optimization of database queries for timely and correct identification of the most resource-intensive queries. These circumstances determine the relevance of developing software tools for assessing the causes of slow queries with the formation of various optimization options. This paper examines the reasons influencing the resource-intensive queries of data sampling. The reasons for slow queries are shown, such as the quality of collected statistics, use of indexes, hints, query structure, correctness of database initialization parameter settings, as well as possible solutions to the identified causes. The study is interesting from the point of view of explaining the basics of the physical operations provided by the query execution subsystem, which interprets the procedural plan of query execution to optimize the cost. To solve the problem of speeding up slow queries based on a correct procedural plan, we propose the development of an application that takes into account the composition of the analyzed cost, volume and time characteristics of queries to optimize them. The results of testing the developed system, which helps to improve the performance of queries, are described. The speed of query execution was evaluated by the following metrics: data access operation, expression cost, I/O operation cost, CPU time, time spent on processing the whole sample. Performing experiments to evaluate the correctness of identifying slow queries confirms the feasibility of applying in practice the results of the conducted research and the developed application.

Keywords: relational systems, query optimization, select, index efficiency, statistics, cost estimation

Environmental factors and bad habits in models of the malignancy prevalence in the municipalities of Altai Krai and other regions

2023. T.11. № 4. id 1460

Stepanov V.S. Rybkina I.D. Orlova E.S.

DOI: 10.26102/2310-6018/2023.43.4.022

The article proposes a regression relationship that connects the prevalence of malignant neoplasm cases in Altai Krai with a complex of explanatory variables, some of which are taken with lags. This complex consists of the purchasing power of the average wages for employees in large and medium-sized organizations, the average volume of alcoholic beverages consumption (per adult capita with age 15+), the share of the elderly population and several dummy variables. The latter characterize the level of technogenic pollution of the municipality territory due to various reasons, as well as the quality of its highways. As a result, a regression model with the variable structure was built. The model has a coefficient of determination of about 98 % and a mean absolute percentage error of 1,2 %. Its parameters were estimated using the ordinary least squares method on panel data for 2018-2019. After assessing the accuracy of the model, it predicts the prevalence of cancer within the municipality with a planning horizon of one year. Such forecasts were made both for a number of urban districts and for municipal districts of Altai Krai, as well as for many districts of Orel and Kurgan Oblasts and a number of other regions in Russia. Additionally, forecasting is performed by means of a roughly similar model that has been created using regional data for 2017-2018. Based on these two models, it is possible to make science-based management decisions aimed at the primary prevention of general cancer morbidity in the population of the municipality and development of specific activities against the morbidity.

Keywords: variable structure regression model, malignant neoplasm, technogenic pollution of territory, atmospheric air pollution, smoking, consumption of alcohol beverages, municipality, region

Functional near-infrared spectroscopy (fNIRS) as a hybrid system: a review

2024. T.12. № 1. id 1459

Samandari A.M.

DOI: 10.26102/2310-6018/2024.44.1.005

Sensor devices and biomedical imaging technologies used in clinical application scenarios are essential for providing a comprehensive portrait of patients’ state, but these technologies, despite their outstanding advantages, have their inherent disadvantages. Beginning with the principle of complementary images of medical imaging techniques, this review examines the functional near- infrared spectroscopy (fNIRS) technique and its use as a hybrid system. The fNIRS technology delivers impressive results in terms of the biological signal classification accuracy, but its use as a hybrid system with electroencephalography (EEG) and electromyography (EMG) achieved better results because it has become a complementary tool to fill the deficit of the common technology with it, and this has been highlighted in this review. The results show that the superiority in the biological signal classification accuracy provided by hybrid systems from fNIRS with EEG and EMG would provide a comprehensive and objective assessment of the patients’ state from the stage of illness to healing. In conclusion, we have no indication from the scientific studies of the previous four years (2020–2023) that demonstrate which of the hybrid systems is better than others when used in clinical practice, and this encourages further in-depth studies to validate the combination of methods to prove their success and preference.

Keywords: HBCIs, fNIRS, fMRI, EEG, EMG, MEG

Finite element modeling of thermohydraulic processes by the porous body method

2024. T.12. № 1. id 1457

Yaurov S.V. Danilov A.D. Gusev K.Y.

DOI: 10.26102/2310-6018/2024.44.1.006

The paper considers the best-known models of a porous body used to simplify the performance of thermohydraulic calculations by the finite element method. The main approaches and dependencies when using the porous body model in calculations are shown. The results of thermohydraulic calculations using the Darcy porous body model are presented. The calculation of a heat exchanger with spirally wound tubes was performed, the calculation of a complex technological system consisting of mechanical filters of different configurations was performed. The discrepancies between the calculated and actual parameters of the equipment are determined. The use of a porous body model as a hydraulic analogue of equipment using the example of mechanical filters and a heat exchanger showed acceptable results (deviations from the design values range from 0,1 % to 10 %). These discrepancies are related to the accuracy/correctness of the selection of porous body resistance laws (dependencies). The use of the porous body approach in modeling the operating modes of technological systems including equipment with a complex design is explained, first of all, when it is required to predict the operating modes of the system as a whole from the result of computational modeling, but local processes occurring inside the equipment are not. Secondly, when it is necessary to reduce the time for performing calculations with low available power capabilities of computers. However, the proposed approach has disadvantages, in particular, the procedure for determining the degree of porosity of the simulated object and the laws of hydraulic resistance selected from empirical dependencies is quite complex.

Keywords: porous body model, complex technological systems, heat exchanger, finite element method, hydraulic resistance, mechanical filters

Automated generation of a complete data model of production facilities in a unified information environment

2024. T.12. № 1. id 1456

Filimonova A.A. Chizhov M.I. Vetokhin V.V. Sobenina O.V.

DOI: 10.26102/2310-6018/2024.44.1.003

The article examines the problem of developing an integration platform to facilitate end-to-end business processes supporting the life cycle of heterogeneous information objects. The platform topology is chosen according to the functionality of the integrated systems and the structure of the information object. To create a unified enterprise information environment, various topologies are considered, including peer-to-peer, message broker, centralized, and hybrid topologies. The basis for the description of an object is a complete data model, including defining attributes and transformation rules corresponding to each of the integrated systems. Using the object model of the information support system for digital products and special templates, a methodology for forming policies, methods and documents (PMD) and organizing a unified digital environment of the enterprise is proposed. However, to solve this problem, the development of a specialized integration platform is required which is capable of processing data from production facilities on a centralized basis and facilitating their interaction in a unified information environment. Such a platform must take into account the characteristics of each system component and ensure the security of information exchange; it also should be able to scale and adapt to the changing needs of the enterprise. In addition, this article discusses in detail various topologies for creating a unified enterprise information space. Peer-to-peer, message brokered, centralized, and hybrid topologies are included. Each of these topologies has its own characteristics and advantages, and the choice of the optimal one depends on the requirements and characteristics of a particular enterprise. To successfully implement integration and create a unified digital environment of the enterprise, it is suggested to use an object model of an information support system for digital products. This model helps to structure information and determine the relationships between various components of the system. Furthermore, the article proposes a methodology for the formation of PMD, which is the basis for organizing a unified digital environment of the enterprise. This methodology takes into account the requirements for security, consistency and efficiency of the system and also ensures standardization and consistency of processes within the enterprise.

Keywords: information production facilities, integration, digital environment, full data model, process automation

The model for developing the schedule for a project to counteract criminal threats of a preventive type

2023. T.11. № 4. id 1455

Zhirnov A.A.

DOI: 10.26102/2310-6018/2023.43.4.015

The paper examines the capabilities of the project-based approach applied to the management of preventive activities of criminal investigation units. The problem of constructing a model for developing the schedule of a project to counteract criminal threats of a preventive type is underscored. The features of schedule development problem in this subject area that do not allow using existing models of project schedule development are listed. One of them implies determining types and number of preventive measures which will potentially have a greater impact on the level of criminal threats with consideration to seasonal fluctuations in the levels of these criminal threats and possible reduction in the effectiveness of the activities to curb them. The main parameters of this type of project are defined, which are required for building a schedule development model, making it possible to formulate the problem of developing its schedule. To solve this problem, a mathematical model of integer programming is proposed with the maximization of the objective function characterizing the expected implementation effect of this type of project. The results of a computational example of solving the problem according to the proposed model are presented. Possible limitations in the practical application of this model caused by the computational complexity of problems of this class are noted. Possible approaches to their leveling are proposed, the development of which can be studied in subsequent research. The author suggests that the application of the suggested model for project schedule development will increase the efficiency of such preventive measures.

Keywords: project schedule, anti-criminal threats project, preventive measures, project approach, project management

Software for solving the integrated nesting and routing problem applied to CNC sheet cutting machines

2023. T.11. № 4. id 1454

Tavaeva A.F. Petunin A.A.

DOI: 10.26102/2310-6018/2023.43.4.011

The paper discusses the issue of developing algorithms and software for solving the integrated nesting and routing problem (INRP). This problem combines two known matters: 2D nesting problem (belongs to the class of Cutting & Packing) and the problem of cutting process optimization (Cutting Path Problem). The integrated additive objective function in INRP is a sum of used material cost for nesting and cutting process cost. The paper proposes a general software structure and a functional model of the automatic nesting and routing subsystem for solving an integrated problem in relation to the CNC sheet cutting equipment. The subsystem of automatic cutting and routing implements algorithms for finding an admissible nesting pattern for some types of parts and corresponding to this nesting pattern algorithms for the tool path generation focused on minimizing the integrated cost criterion. The algorithms are implemented as open source software using Python. The paper presents the results of numerical experiments for the CNC laser complex of sheet cutting. The developed software has also been tested for several types of practical tasks in control programs generation for various sheet cutting equipment.

Keywords: CNC sheet cutting machine, integrated nesting and routing problem, sheet cutting, tool path, cutting process cost, optimization

Simulation model of call service in a satellite network with consideration to frequency resource utilization

2023. T.11. № 4. id 1453

Ponomarev D.Y. Demicheva A.A. Gaipov K.E.

DOI: 10.26102/2310-6018/2023.43.4.014

The paper considers a simulation model of a multiservice satellite network. The network under review provides services for voice and data transmission. Depending on the subscriber equipment, interference environment and location of satellite systems, the requirements for the queried frequency resources of the network are adjusted, and the capabilities of the spacecraft payload to allocate a given bandwidth are determined. This study takes into account the processes of resource frequency allocation for each call when developing a simulation model. Due to the high complexity of call processing in satellite networks, various types of modeling are used to assess their characteristics at various stages of development and design. At the same time, the analytical representation of the processes occurring in such networks is associated with some difficulties. In this paper, simulation modeling is used in the GPSS Studio environment, and the main goal is to develop algorithms for modeling the processes of connection establishing and transmitting information in a satellite network and evaluating the probabilistic and time characteristics of this network using the algorithm developed. The software implementation of the algorithm has demonstrated the capabilities of GPSS Studio and allowed us to obtain results for estimating the probability of call losses in various parts of the network. The findings can be used both in the analysis of existing satellite networks and in the design and development of new technologies of the networks under review.

Keywords: satellite network, simulation modeling, maintenance algorithm, probability of losses, frequency resource

Solving the problem of transferring a continuous medium over a network medium in symbolic form

2023. T.11. № 4. id 1451

Rybakov M.A.

DOI: 10.26102/2310-6018/2023.43.4.010

When studying the evolutionary processes of transferring a continuous medium over network media, special emphasis is placed on the issues of the existence and approximate finding of solutions to initial boundary value problems for differential systems of equations, the formalisms of which describe mathematical models of these processes. In engineering practice, such models are usually considered linear or allow linearization (a classic example is linearized Navier-Stokes systems). The core idea is based on the use of symbolic mathematics theory tools which determined the entire direction of the research; it predetermines the understanding of the transfer phenomena patterns in the branching places (nodal places) of the process carrier and the subsequent mathematical description of such phenomena in terms of differential or other relationships. The paper presents a mathematical model of an evolutionary network-like process of continuum transfer (linear differential system) and its corresponding differential-difference system obtained by semi-sampling the differential system with respect to a time variable. To prove the solvability of the latter and empirically determine the approximations of the solution to the original differential system, methods of symbolic mathematics are used. At the same time, an algorithm for finding a symbolic-numerical solution to a differential-difference system and approximations of solutions to the initial boundary value problem for the continuum transport equation are proposed and validated. The algorithm is based on the approximation of the partial derivative with respect to a time variable by a difference ratio (a two-layer approximation scheme is utilized) and the subsequent application of the Laplace transform to the resulting differential-difference system. A block diagram of the algorithm is presented; a description of the software complex structure based on the developed algorithm is given. The software package is developed using the Java programming language. To upload the initial data of the initial-boundary value problem and output the solution, the web interface of the software package based on the Spring framework is used. To illustrate the operation of the software package, an example of solving an initial-boundary value problem is considered with a step-by-step demonstration of the calculation results. The presented method can be used in the analysis of applied problems of network hydrodynamics, heat engineering, as well as the analysis of diffusion processes in biophysics.

Keywords: network-like domain, graph, continuum transport equation, initial-boundary value problem, differential-difference system, laplace transform, symbolic-numerical solution algorithm

Methods of expert evaluation of construction projects according to qualitative criteria

2023. T.11. № 4. id 1450

Serebryakova E.A.

DOI: 10.26102/2310-6018/2023.43.4.007

The article discusses methods of individual and group expert assessment of construction projects in order to select the most promising for implementation. The proposed model for obtaining a generalized assessment of the quality of construction projects by one expert is based on a mathematical model of expert assessment using one or more criteria reflecting the requirements for construction projects. In addition to the traditional method of analyzing hierarchies, alternative methods based on the method of latent variables and correlation analysis have been proposed. For group expert assessment, a method for processing expert information is suggested with the competence of experts accounted for. The method is based on the assumption that the expert’s competence is proportional to how closely the expert’s opinion on all projects coincides with the average opinion of all experts on the same set of projects. In this way, the influence of unscrupulous or incompetent experts on the results of evaluating construction projects will be reduced. In addition, a method for processing group expertise based on the theory of latent variables has been proposed. The method being suggested is based on the Rasch model for estimating latent variables. The proposed models make it possible to increase the efficiency of decision-making when choosing construction projects.

Keywords: expertise, project management, construction, latent variables, mathematical modeling

Models of resource management in the construction sector

2023. T.11. № 4. id 1449

Barkalov S.A. Moiseev S.I. Serebryakova E.A.

DOI: 10.26102/2310-6018/2023.43.4.006

The paper presents three mathematical models that facilitate resource management of construction works. The model of the efficient support of construction sites makes it possible to optimize the distribution of resources to sites with logistics accounted for. It helps to organize the optimal supply of construction sites or projects with resources of various types both to fully satisfy the needs of consumers and to minimize the costs of organizing supply activities. The model for the optimal distribution of scarce resources between objects enables the distribution of limited resources while minimizing the disruption of construction work. It is shown that the efficiency of the presented model for distributing scarce resources is about 34 % on average. Models for timely replenishment of resource reserves will allow for probabilistic forecasting of resource availability over time. This model facilitates probabilistic methods to predict the volume of necessary resource reserves at a particular construction site under the conditions of unstable dynamics of their use. When developing the models, methods of mathematical programming and Markov random processes were employed. These models will make it possible to carry out operational management of construction project inventories under the conditions of unstable supply and consumption, as well as to plan measures to increase the volume of supplied stocks to objects depending on the speed of their consumption with the influence of external conditions and internal factors accounted for.

Keywords: resource management, construction, mathematical modeling, optimization, inventory management

Practice of requirement management application in the problem domain based on model-driven system engineering of high-tech systems

2023. T.11. № 4. id 1445

Knyazeva I.O. Kuznetsova Y.A.

DOI: 10.26102/2310-6018/2023.43.4.024

Insufficient attention is paid to the stakeholder requirements coverage and their quality in the traditional approach regarding the development of high-tech products. Requirement engineering is widely being implemented. Its application based on the MBSE methodology contributes to a comprehensive consideration of the designed product, helps to avoid errors in its production, and satisfies all stakeholder requirements. Researchers present various interpretations of this process using different MBSE tools and high-level design software for complex systems. The practice presented in this paper is a synthesis of analysis and validation of MBSE approaches as well as their successful application by the authors in R&D when designing high-tech systems. The presented material is unique not only because it is limited to specific software products and, but also due to being suitable for subsequent extensions dictated by the subject domain of the designed system. The purpose of the study is to describe the practice of applying requirement management in the field of problems of a knowledge-intensive system based on MBSE. In requirement engineering process, the MBSE methodology was utilized by means of the System Modeling Language (SysML) for architectural system modeling. Within the scope of the research, stakeholders were identified and ranked according to the importance of their requirements in the project. The planned functionalities and directions for system requirement development were modelled. Requirements in the problem domain were identified, and their dependencies were analyzed in a SysML requirements diagram. The requirements were verified for correctness and structured in tabular form with assigned attributes. The materials of the article present structured stages of MBSE tool application for requirements identification in the problem domain, which can be applied to any knowledge-intensive system.

Keywords: model-Based Systems Engineering, MBSE, requirement engineering, problem domain requirements, stakeholders, sysML

Development of business process simulation models based on the IDEF0 methodology using Petri net theory

2023. T.11. № 4. id 1444

Petrosov D.A.

DOI: 10.26102/2310-6018/2023.43.4.009

The relevance of the research is due to the requirements for modern tools for automating the process of developing business process models. Modern design tools have greater functionality and support various methodologies which makes it possible to develop models in various subject areas. One of the disadvantages of this type of system is the absence of means for presenting simulation models based on the graphical models obtained during development. Owing to this, we can talk about the relevance of developing new methods and approaches that will enable simultaneous construction of simulation models and development of the graphical representation of a business process based on modern methodologies. The approach proposed in this study is aimed at helping developers of CASE applications. Additionally, it facilitates the automation of creating business process simulation models using the theory of Petri nets. The methodology of the IDEF family – IDEF0 – was used as the main methodology for modeling the functional features of business processes. When developing the proposed approach, the limitations adopted in the IDEF0 methodology were accounted for. The following restrictions were considered: rules for creating a context diagram, decomposition rules, and the use of all possible arrows in this methodology. The approach presented in the study allows for the construction of business process simulation models based on the IDEF0 methodology in parallel with their development when integrating the corresponding software design into the CASE tool.

Keywords: mathematical modeling, business processes, system analysis, petri net theory, CASE tools, IDEF family of methodologies, IDEF0 methodology

Structuring of a multifunctional digitalized system and managing it using optimization models of disaggregation of resources and volumes of activity

2023. T.11. № 4. id 1441

Gusev P.Y. Lvovich Y.E.

DOI: 10.26102/2310-6018/2023.43.4.004

The paper discusses the application of a structural-functional and optimization approach for solving the problems of managing the disaggregation of resources and volumes of activities in a multifunctional digitalized organizational system (MDOS). The definition of MDOS is given from the standpoint of integrating management, resource, multifunctional digital and activity monitoring fields. It is shown that the structure of interaction between the control center and the activities of the components is determined by the features of the organizational system class which is being investigated: multi-layeredness, a variety of components for each layer, the nature of control center requirements, the system-forming nature of the functional areas of the digital environment, the distributive nature of resource support use and the implementation of volumes of activity. A set of tasks aimed at disaggregation of resources and volumes of MDOS activities is proposed and their optimization nature is substantiated. It is demonstrated that the problem of disaggregation of resource provision planned volume is formalized as an optimization model of linear programming with variable boundary requirements, which makes it possible to solve it by combining the transition to the dual problem and, on its basis, to carry out multi-alternative optimization. The formalized statement of resource disaggregation problem accounting for their types and involvement in the implementation of activities in the functional areas of the digital environment and disaggregation of the planned volume of activity leads to an optimization model of block linear programming. To solve these problems, it is proposed to develop a problem-oriented algorithm based on a combination of iterative methods for solving block programming problems. Solving the selection problem at the component level requires preliminary identification of the dependences of disaggregation process characteristics on the methods of implementation and parameters of the components. Decision-making algorithms based on the tasks listed above are the basis for the intellectual support of experts in the proposed structural scheme for managing the MDOS.

Keywords: organizational system, multifunctional digital environment, management, structuring, optimization, expert evaluation

Features of molecular system transformation technique program realization

2023. T.11. № 4. id 1440

Smirnova Y.A. Marienkov A.N.

DOI: 10.26102/2310-6018/2023.43.4.023

The paper provides the analysis of molecular system model transformation problem with respect to any element of this system, where the molecular system (MS) is understood as a formalized computer representation of the geometric coordinates of the atoms in a molecule. The analysis has demonstrated that the existing software used to simulate molecular interaction does not enable MS transformation. At the same time, MS transformation becomes more complex as the number of elements in the system increases. A new technique of MS transformation based on converting MS into a molecular graph is proposed, where the transformation is understood as a graph rearrangement with respect to a new vertex. The necessity of automating the process of analysis and processing of the formalized representation of the transformed MS is substantiated. In addition, the algorithm of the program module based on the transformation technique is described. The demonstration of the developed software product using the example of transformation of methionine molecule is given, the molecular graph and formalized computer representation of the obtained MS are presented. The software product helps to save a formalized computer representation of the transformed molecule structure. Repeated use of the methionine molecule structure representation transformed earlier will further improve efficiency and speed in modeling the interaction of methionine with other molecular systems.

Keywords: molecular systems, synthesis of molecular systems, transformation technique, data conversion, rearrangement of molecular systems, molecular graph, formalized representation, program

Generalized ecological model of a dynamic distributed computing system

2023. T.11. № 4. id 1439

Bryukhanova E.R. Antamoshkin O.A.

DOI: 10.26102/2310-6018/2023.43.4.002

The paper presents a generalized model that enables a structural analysis of a distributed computational dynamic system and makes it possible to investigate the applicability of various control methods taking into account the environmental parameters of its operation. With the advent of the information society era, distributed computing systems for data processing and performing various tasks are being increasingly used. However, with the growth of their number and scale, the issues of energy consumption and negative impact on the environment are becoming more acute. The proposed model provides tools for assessing the impact of such systems on the environment as well as for taking measures to minimize their ecological footprint. It includes a set of parameters that help to analyze and take into account such factors as energy consumption, carbon emissions and resource efficiency. This model is designed to promote the development of more environmentally positive approaches to the management of distributed computing systems. This is of particular importance in the light of the growing attention to environmental issues and the desire of society for a more responsible use of resources. The results of this study open the way to creating more efficient and environmentally friendly computing solutions reducing the negative impact on the environment and a more sustainable future ensuring a balance between performance and environmental friendliness of distributed computing systems.

Keywords: distributed computing systems, dynamic systems, environmental sustainability, energy consumption, optimization

Resistance of the method for associative stegosecurity of cartographic scene data

2023. T.11. № 4. id 1438

Vershinin I.S.

DOI: 10.26102/2310-6018/2023.43.4.003

For further consideration, the article presents earlier introduced concept of a two-dimensional associative masking mechanism used to protect the data of cartographic scenes represented by point objects. The masking mechanism is the basis of associative steganography. In this case, the objects and coordinates of the scene are represented by code words using the alphabet of postal symbols and are masked with stegocontainers developed later. A set of masks is a secret key employed then to recognize a scene represented in a protected form by a set of stegocontainers. The method offence resistance is evaluated from the standpoint of the availability of information about some objects and their coordinates (associations with the terrain map). Two cases of such attacks are considered – the enemy's actual knowledge of the location of an object familiar to them as well as the analysis of the scene for plausibility after recognition using a key. The results of experimental studies are presented, which makes it possible to assert the unconditional or provable (i.e. computational associated with the impossibility of a complete search for keys) resistance of the method. Additionally, a resistance analysis is carried out for the case of excessive masking introduced to increase the noise immunity of stored or transmitted data, when not one, but several sets of masks are used to protect this data.

Keywords: associative steganography, resistance, cartographic scenes, information security, scene analysis

Algorithm for selecting data analysis model for predicting the performance of industrial robots

2023. T.11. № 4. id 1437

Goncharov A.S. Savelev A.O. Pisankin A.S. Chepkasov A.Y.

DOI: 10.26102/2310-6018/2023.43.4.028

Due to the intensive pace of development of systems for data collection, accumulation and analysis, more and more methods, approaches and systems are being created for decision-making in the field of predictive maintenance in modern robotic industries in order to increase productivity and efficiency of resource use (time, finances and material resources). Maintaining fixed assets of production is crucial to ensuring safe, efficient and continuous production. Modern equipment is fitted with a variety of monitoring systems, self-diagnosis and intelligent sensors that allow collecting a significant amount of primary data that may contain useful knowledge. The article presents an approach to developing an algorithm for selecting machine learning models when analyzing data on the performance of industrial manipulators as part of the predictive maintenance process. The developed algorithm makes it possible to reduce the time spent on training data analysis models (including machine learning and artificial neural networks) by selecting arrays of data collected from a fleet of equipment (for example, industrial robots) that have the greatest degree of similarity relative to the data collected from single equipment; this helps to avoid training additional data analysis models with satisfactory test results. Data was collected from four different industrial robots. The following methods were used for the analysis: linear model, convolutional neural network, multilayer perceptron. The algorithm of dynamic transformation of the timeline was used to assess the degree of similarity.

Keywords: predictive analytics, performance forecasting, machine learning, industrial robot, system analysis

Formalized assessment and decision support models for regional development management based on measurable indicators

2023. T.11. № 4. id 1436

Shamaeva E.F.

DOI: 10.26102/2310-6018/2023.43.4.001

The complex crisis situation in the world poses a challenge to the scientific community as to how accurately measure and forecast energy needs, environmental, social and economic factors. This requires the design of an interdisciplinary decision support model that comprehensively reflects the opportunities, local and global needs of regional development as well as the interrelation of decisions made in the region, socio-economic and environmental processes. The paper presents models that use measurable indicators and methods of system and energy analysis related to the consumption, transformation and distribution of energy resources in the production activities of regional organizational systems. Formalized concepts related to the management of regional system development, measurable indicators of environmental, socio and economic state of the regional system are presented. Capabilities of using the research results are given in the form of mathematical and software information system of decision support on the basis of measurable indicators. The results of the study confirm the applicability of the model of formalized assessment and decision support on the basis of measurable indicators as one of the alternatives under the conditions of non-monetary evaluations when making decisions with consideration to environmental, social, economic factors. The results of the study are of practical value when solving the problems of decision assessment.

Keywords: sustainable development of the region, modeling, management decisions, measurable indicators, formalized assessment, mathematical models, software

Development of methods for forecasting the dynamics of morbidity in the case of COVID-19

2023. T.11. № 3. id 1434

Kashirina I.L. Matykina O.V.

DOI: 10.26102/2310-6018/2023.42.3.014

The COVID-19 pandemic has had global repercussions and has led to severe restrictive measures in all areas of activity that have changed the working and living conditions of the world's population. Even after the end of the pandemic, predicting the incidence of COVID-19 remains an important task as it is necessary to monitor the development of the situation and the results of research on this issue can be extrapolated to other epidemics. Scientific studies on the analysis of factors that have a significant impact on the course of the epidemic have a particular importance. This study proposes a set of models and machine learning algorithms based on big data processing to predict the dynamics of the spread of the COVID-19 virus at the mesolevel, which analyzes the impact of various exogenous factors on the incidence. As the initial data for building machine learning models, we use a depersonalized data set provided by Voronezh Regional Clinical Consultative and Diagnostic Center and containing information on all tests for COVID-19 conducted in Voronezh Oblast. To effectively combat epidemics, it is necessary to forecast the development of the incidence dynamics for a sufficiently long period of time, e.g. from two weeks or more, while various studies, in general, propose short-term methods that allow making a fairly accurate forecast only for 1–5 days. Therefore, the goal of this study is to find the optimal method for predicting incidence over an average period of time using exogenous factors. Information about the weather, day of the week and month, and the popularity of search queries related to COVID-19 were selected as exogenous variables to improve the quality of forecasting.

Keywords: COVID-19, machine learning, time series, dynamics prediction, hybrid neural network

Problem of hydrocannon nozzle form optimization for maximizing the force pulse of the ultrajet

2023. T.11. № 4. id 1433

Dmitruk I.V. Tolstykh V.K.

DOI: 10.26102/2310-6018/2023.43.4.012

Pulsed high-pressure liquid jets can destroy the rock of any hardness. The use of ultrajets can accelerate the dissociation of rocks and hasten the construction of buildings. However, due to the low reliability of hydraulic pulse equipment, the commercial use of pulsed jets is currently limited. It is possible to increase the reliability and efficiency of the hydrocannon by optimizing the design. Therefore, the article examines a direct extreme approach aimed at the piston hydrocannon nozzle form optimization in order to achieve the maximum average force of the jet on the barrier. The form of the nozzle (cross-sectional area) is present in the equations as a spatial derivative. The function of the derivative is chosen as a control, which makes it possible to exclude errors in numerical differentiation. Direct extreme approach involves iterative maximization of the functional by extremal methods based on the gradient. An analytical expression for the gradient as a function of the nozzle length and a necessary nozzle form optimality condition are obtained. The gradient is a function of spatial variables, which makes the optimization problem infinite-dimensional. The value of the gradient is determined by the solution of the conjugate problem. The gradient indicates the direction of maximizing the target functional, which can be used in infinite-dimensional extreme optimization algorithms. The criterion for achieving the optimal nozzle form is the fulfilment of the required condition with the best possible accuracy.

Keywords: hydrocannon, gradient of the target, optimality condition, infinite-dimensional extreme problem

Formalization of the enterprise information security model in the multicriteria linear programming problem form

2023. T.11. № 3. id 1431

Bazilevskiy M.P. Nasedkin P.N.

DOI: 10.26102/2310-6018/2023.42.3.021

Previously, the authors proposed a methodology for assessing the functional efficiency of the software and technical solutions (STS) subsystem of an information security complex system (ISCS) of an enterprise. Using it makes it possible to evaluate not only the overall efficiency of the ISCS STS subsystem, but also the efficiency of its components, such as subsystems and their functions. In this article, based on the proposed methodology, an optimization model of enterprise information security is formulated in the form of a multicriteria linear programming problem. Its target functions are the efficiency estimations of all possible components of the ISCS STS subsystem. The variables are the expected estimates of the auditors after modernizing the ISCS and the costs that provide the corresponding estimates. The solution to this problem gives an answer to the question of how to distribute the available amount of funds in such a way as to maximize not only the efficiency of the ISCS STS subsystem, but also the efficiency of all its components. The proposed multi-criteria problem is reduced to a single-criteria problem, in which, instead of maximizing all efficiency criteria, the minimum of them is maximized. A problem is also proposed, the solution to which gives an answer to the question of what minimum costs are necessary to ensure a given level of efficiency of the ISCS STS subsystem and all its components.

Keywords: information security, assessment of the information security efficiency, object of influence, optimization model, linear programming

The high-level structure of modules for building special computer-aided design systems

2023. T.11. № 3. id 1430

Trotsenko A.S. Uspehov A.A. Chizhov M.I.

DOI: 10.26102/2310-6018/2023.42.3.018

In modern production, there is a need to design specialized products predetermined by a certain set of changing parameters. Re-designing of a product associated with adjusting some of these parameters becomes one of the tasks for an engineer to complete. Using of heavy computer-aided design systems in such cases can lead to a significant increase in labor costs. Creating a history of building a solid model of a product balanced according to a given set of its parameters has a significant impact on the overall complexity of the design process. Increasing the efficiency of this process allows the use of special computer-aided design systems aimed at creating a parameterized model of a particular product. This paper presents the structure of high-level modules that ensures the rapid development of special computer-aided design systems. One of the methods that provide rapid development is the reduction of a large amount of knowledge of the classes and methods of the geometric core being used. The presence of separate functional blocks helps to build various solid-state modeling systems: from simple linear systems to systems with advanced modeling, analysis and data import/export capabilities. To reduce the dependency of the developed systems on a specific geometric core, the high-level structure that is being proposed provides the hiding of the geometric core being used by means of the private implementation design pattern.

Keywords: architecture, solid modeling, computer-aided design systems, design patterns, pointer to implementation

Indicator framework for evaluating the performance of multi-factor authentication procedures in Web applications

2023. T.11. № 3. id 1426

Bogdanov D.S.

DOI: 10.26102/2310-6018/2023.42.3.015

The relevance of the study is due to the increasing use of multi-factor authentication mechanisms in Web applications, the popularization of Web technologies as well as the lack of specific standards in the Russian Federation describing the operation of multi-factor authentication procedures and establishing requirements for Web applications that use these procedures. The purpose of the research is to develop an indicator framework for assessing the performance of multi-factor authentication procedure information security in Web applications based on the previously developed classification of the procedures under consideration. An analysis of scientific publications on the issue under study was carried out; linguistic scales for indicators were proposed: costs, reliability, safety, efficiency as well as factors affecting the indicators. Acceptable indicator values were identified, which will be clarified using the method of expert assessments in subsequent publications on this issue. As part of the study, methods for calculating the values of cost, reliability, safety, and efficiency indicators were proposed. The findings of the study can later be specified in compliance with the list of the objectives aimed at ensuring the information security of multi-factor authentication procedures. The materials of the research are of theoretical value for further research in this field.

Keywords: multi-factor authentication, web application, two-factor authentication, classification, indicators of authentication procedures, efficiency assessment

Neural fuzzy networks for remote monitoring systems for outpatients with respiratory diseases

2023. T.11. № 3. id 1425

Butusov A.V. Alawsi H.A. Karachevtsev R.A. Filist S.A.

DOI: 10.26102/2310-6018/2023.42.3.016

The article proposes a decisive module for monitoring the functional state of the respiratory system, which provides intellectual support in making decisions by medical personnel regarding the hospitalization of a patient. To control the severity of community-acquired pneumonia, a hybrid multi-agent classifier has been developed based on Internet technologies with a structure that includes segments of risk factors associated with “its own” fuzzy inference system. A metaclassifier has been designed to aggregate the solutions of these systems, which allows monitoring the functional state of the patient breathing system in remote interactive mode. Based on the Mamdani-Larsen algorithm, a five-layer fuzzy network has been developed for classifying the severity of community-acquired pneumonia according to the input vector, which allows estimating the severity of community-acquired pneumonia on a 0–1 scale according to the segment of risk factors used in traditional pneumonia risk scales. A neuro-fuzzy classifier of community-acquired pneumonia severity based on the CRB-65 pneumonia risk scale was synthesized. The base of fuzzy decision rules of the fuzzy inference system is formed and the membership functions for input and output variables in the selected segment of risk factors are determined. The neuro-fuzzy model of a hybrid classifier of the severity of community-acquired pneumonia was tested using an experimental group of 200 patients with community-acquired pneumonia of varying severity. The classifier model on the control sample demonstrated a diagnostic sensitivity of 90 % and diagnostic specificity of 86 %. The results of the obtained risk model for community-acquired pneumonia were compared with the results of expert evaluation and the results obtained on known regression models. The quality indicators of the classification of the synthesized neuro-fuzzy classifier make it possible to recommend it for telecommunication systems for remote monitoring of community-acquired pneumonia severity.

Keywords: remote monitoring, interior, vein-hospital pneumonia risk scales, multi-agent classification system, neuro-fuzzy classifier, classification quality indicators

Optimization of modeling processes of balancing and rebalancing investments for the implementation of multi-object organizational system development program

2024. T.12. № 1. id 1419

Bukholtsev I.M. Lvovich Y.E.

DOI: 10.26102/2310-6018/2024.44.1.015

The article examines the optimization of investment management in the formation and implementation of multi-object information system development program. The stage connected with the transition from the development program executed for a certain time period to a new development program with a given planning horizon is considered. It is shown that the investments are balanced at the moment of transition and the need to rebalance them arises in the process of implementation. For the first problem, a multilevel system of balance conditions is formed, which is the basis for the construction of optimization models of the balancing process. Since the lower level of balance conditions is associated with the requirement to increase the value of organizational system development indicators of objects up to a certain value set by the managing center, the optimization problems are based on predictive assessments. These estimates are calculated either using the results of neural network modeling or expert evaluation. When forming optimization models of the investment rebalancing process, two ways of detecting the deviation of the development indicators value from the planned growth trajectory are considered: at a given point in time; when the threshold value is exceeded. In these cases, the point in time is determined, at which the optimal strategy of investment allocation between time transitions is adjusted in order to reach a given level of development indicators at the end point. Thus, the proposed transition makes it possible to optimize the distribution of investments as part of the development program both in the process of their balancing and rebalancing.

Keywords: multi-object organization system, development program, investment, optimization, neural-network modeling, expert assessment