DOI: 10.26102/2310-6018/2024.44.1.011
Today, the X-ray analysis procedure makes it possible to detect osteoarthritis (OA) in the early stages of the disorder. The presence or absence of the disorder is detected only when it has already manifested, and X-ray diagnostics have been carried out. The use of automated procedures for analyzing X-ray images and the availability of archives of such information with a long history can improve the results of predicting complications in patients. The article describes the experience of developing an application for computer analysis of radiographs, which, based on deep learning methods, allows us to identify the risks of developing osteoarthritis of the hip joint. The archive of a specialized medical institute is used as a training sample. In order to increase the size of the training set of radiographs, a data augmentation method is used, which increases the variability of the original data and, in some cases, increases the recognition efficiency. The research uses a convolutional network (U-net) designed for image segmentation, which is trained on X-ray images of a specific medical institution. As part of a project to segment and analyze the geometric characteristics of X-ray images of the hip joints, the software to automate the recognition of the joint space size was developed, which helps to clarify the patient’s diagnosis and prognosis for the development of the pathology.
Keywords: convolutional neural network, image segmentation, machine learning, osteoarthritis, hip joint
DOI: 10.26102/2310-6018/2024.44.1.021
The current stage of unmanned aircraft system development is characterized by the widespread introduction of automated and intelligent electronic systems. One of the most difficult and critical stages in the development of unmanned aerial vehicles is determining the optimal locations for placing on-board equipment in the fuselage space. To solve this problem, the approach for determining the optimal installation locations for on-board equipment in the fuselage space of an unmanned aerial vehicle is proposed. The approach is based on the use of a genetic algorithm. A meaningful and mathematical formulation of the problem of determining the optimal installation locations for on-board equipment in the fuselage space of an unmanned aerial vehicle is given. Criteria and restrictions have been developed. As optimization criteria, first of all, electromagnetic compatibility criteria are considered, which are characterized by minimizing the sensitivity of on-board equipment above the level of electromagnetic field strength at the installation sites of on-board equipment, as well as limiting the excess of the threshold level of susceptibility of on-board equipment over the electromagnetic environment resulting from electromagnetic influences or interactions. Additionally, criteria for minimizing the total weighted length of cable connections are considered, and the maximum load-carrying capacity of the fuselage compartments of an unmanned aerial vehicle is limited. The plan has been developed for the installation of on-board equipment in the fuselage space using a developed program that implements a genetic algorithm.
Keywords: placement, optimization, on-board equipment, genetic algorithm, unmanned aerial vehicle
DOI: 10.26102/2310-6018/2023.43.4.034
Mathematical modeling of computer virus epidemics is the most important area of theoretical research in the field of information security. This paper examines a Markov model of the computer virus spread based on the Reed–Frost model. The main aim of the article is to analyze the applicability of the modified Reed-Frost model to the class of networks associated with random Erdos-Renyi graphs. In particular, the effect of the ratio of the probability of cure to the probability of infection on stopping the spread of a computer virus was tested. The results of this model are compared with ones obtained via the simulation modeling for different values of epidemic parameters and network characteristics. In the calculations and experiments carried out, the following parameters changed: the probability of infection, the probability of cure, as well as the connectivity of the network. The Wolfram Mathematica symbolic computing system was used for calculations. A C++ program written earlier by the author and their supervisor was used to conduct the computational experiment. The studies show that, under certain parameters, the condition for ending the epidemic is confirmed by both theoretical calculations and experimental results. However, the epidemic vanishes before the threshold value calculated is reached. In the future, the author plans to give a more accurate theoretical assessment of the conditions for ending the epidemic.
Keywords: computer virus, probability of infection, probability of cure, random graph, reed-Frost model, susceptible node
DOI: 10.26102/2310-6018/2023.43.4.030
The article discusses and formally introduces the concepts of a number series anomaly and an anomaly filter function. The relevance of the research is due to the absence of a unified approach to understanding the concept of anomaly. At the same time, they play a key role in solving many practical problems. The study uses a method for measuring the stability of the selected method of statistical assessment for outliers using breakdown points and sliding windows. The method of filtering a number series for outliers is based on a combination of the median and the median absolute deviation. In relation to solving a wide range of issues in IT automation а modification of the Hampel method is proposed for determining outliers in a sample. Functions for filtering a number series for anomalies and determining the index of the first anomalous element are developed in Python. As an example, a script was developed using the Jupyter Notebook platform to solve the problem of quick search for anomalies in stock prices by means of the modified Hampel method. To obtain a sample with outliers, the author's library is used to generate test stock data. The experimental results confirm that the proposed algorithms can clearly filter anomalies for different values of adjustable parameters. The advantages and disadvantages of this method are noted. The Hampel filter is easy to optimize and parallelize. The article has practical application for solving the problem of automation and identifying anomalies in number series.
Keywords: number series, anomalies, outliers, filtering, hampel
DOI: 10.26102/2310-6018/2023.43.4.036
This article presents one of the scientific results obtained by the author during the dissertation study. The problem of forming a convenient and safe pedestrian infrastructure, which is one of the urgent issues of the development of a modern city, is revealed. An analysis of Russian and foreign experience in organizing pedestrian infrastructure was carried out. It was revealed that in the Russian experience of organizing effective and safe pedestrian infrastructure, problems are often observed that occur in neighborhoods with any types of development, including such as the absence or irrational location of technical means of organizing traffic. A mathematical model has been developed that makes it possible to assess the probability of a pedestrian crossing a street in a particular place along the entire length. The parameters of the proposed model are defined. It is also proposed to apply the results of studies of human behavior in situations in which similar or the same psychoemotional motivators work, prompting the intersection of the street in a particular place, as well as to use dependencies that obviously correlate with the statistical dependencies necessary for conducting this study. The obtained results are proposed to be used in subsequent works in the development of a simulated model of traffic management, which allows assessing the congestion of the road network and subsequent optimization of transport and pedestrian flows in order to ensure the required road safety.
Keywords: model, parameters, traffic and pedestrian flows, probability, road network, road accident, road safety
DOI: 10.26102/2310-6018/2023.43.4.031
Ensuring the sustainability of web applications with respect to various security threats plays a crucial role in the development of modern information support technologies for industrial enterprises, financial structures and service organizations. This explains the high relevance of the development of new scientifically sound effective computational methods, algorithms and problem-oriented programs for testing web applications with a complex functional structure of internal and external interaction, which implement the capabilities of streaming data generated from the results of each of the test steps, and the application of the results in the process of managing the testing of web applications. The article describes the concept of modeling testing processes, research of the obtained models and development of analysis and prediction algorithms, based on a formalized apparatus of dynamic Bayesian networks. The Bayesian models proposed in the paper, built on the basis of statistical training, help to determine time relationships for each of the parameters determined during the test procedure, provide the opportunity to predict test results by performing simulations using probabilistic inference methods.
Keywords: web application vulnerabilities, bayesian network, probabilistic inference problems, testing process, monte Carlo method using Markov circuits, particle filtering algorithm
DOI: 10.26102/2310-6018/2023.43.4.037
In this paper, we propose a method for interpreting neural network solutions based on the use of Boolean integro-differential calculus. This method allows you to investigate the logic of decision-making by neural networks and determine the most important signs that affect their decisions. The method can be applied to classification problems, especially in cases where each feature can be represented as a k-valued variable. The paper considers local and global interpretations of solutions. At the first stage, each input vector is associated with the corresponding output of the neural network. Then, by solving a Boolean equation, logical functions are found that adequately reflect the input data and their corresponding outputs. At the second stage, global interpretation, functions are constructed that combine previously found logical functions. This choice of functions is based on their ability to most accurately reflect the decisions of the neural network and the study area. At the second stage, global interpretation, functions are constructed that combine previously found logical functions. This choice of functions is based on their ability to most accurately reflect the decisions of the neural network and the study area. The resulting function has interpretability, modifiability and the ability to represent a complete set of solutions corresponding to a given query. It also highlights the most significant features for each solution. The paper considers the practical implementation of the method on the example of a neural network trained on the basis of the structure and input data consisting of answers to questionnaire questions, with an output node predicting the diagnosis. In parallel with the development of the neural network, an interpretive model is being built, which allows identifying the most important signs for each diagnosis based on the decisions of the neural network. In addition, in cases with boundary solutions, when the neural network provides only one possible solution, the interpretative model is able to find all possible solutions with a predetermined accuracy, which helps to avoid mistakes in decision-making.
Keywords: neural networks, interpreter, connections, boolean differentiation, input data, analysis, hidden patterns
DOI: 10.26102/2310-6018/2023.43.4.029
The relevance of the article is due to the need to ensure information security of industrial control systems (ICS). Loss of control over industrial facilities can lead to undesirable consequences in a particular subject of the state or affect the economic indicators of the country as a whole as well as compromise the safety of the population. In this regard, this article aims to improve the procedure for quantitative assessment of information security risks as a necessary component of an integrated approach to ensuring information security, which helps to assess the feasibility of information security violation scenarios and identify their possible consequences for building an effective protection system. The architecture of a research prototype of an intelligent decision support system and a software implementation of tools for automating the modeling of attack scenarios and assessing the information security risks of ICS have been developed, the use of which makes it possible to increase the reliability and efficiency of information security risk assessment and, consequently, the choice of effective countermeasures at all stages of an industrial facility life cycle and its complex protection systems. The materials of the article are of practical value for information security specialists at all stages of the life cycle of distributed information and control systems of industrial facilities.
Keywords: information security risk assessment, intelligent decision support system, cognitive modeling, scenario modeling, graph models
DOI: 10.26102/2310-6018/2023.43.4.025
The article is devoted to the formation of principles for constructing a data access system for a multifunctional digitalized system (MDS). The features of data generation and storage in the MDS are described. The importance of the unified information space of the MDS is shown and the peculiarity of the formation of a unified information space is described. Taking into account the peculiarities of the functioning of the MDS, the main tasks have been identified, the solution of which forms the model of access to data in the system. The dependence of the relevance of data on the assignment of those responsible for the data is indicated. The task has been set to ensure information security of a single information space. It is shown that the task of securing responsibility for data in the MDS is related to the task of disaggregating resources by type of activity attracted through functional areas. The dependence of MDS performance indicators on types of activities, functional areas and types of resources is shown. The paper examines mandatory, discretionary and role-based models of access to data. The shortcomings of access models in relation to the features of the MDS are identified. An architecture for regulating access to data using software modules and services is proposed. It is suggested to create a monitoring environment based on the construction of data sets determined through the performance indicators of the MDS.
Keywords: multifunctional digital environment, management, data, access rights, common information space
DOI: 10.26102/2310-6018/2023.43.4.016
The history of neonatal incubator development and the evolution of its design were described. A generalized structural and functional diagram of a modern neonatal incubator was presented. Airflow patterns have been studied in detail, including illustration of typical airflow paths in double-walled incubators. A classification of neonatal incubators was given. Information about manufacturers of modern incubators was presented in a table that includes 51 manufacturers from 17 countries with the addresses of web sites that contain specifications of medical products they manufacture. Publications that discuss modeling heat and mass transfer processes in incubators for newborns were analyzed. It was concluded that modern computational aerodynamics packages are usually used for numerical modeling with consideration to the infant’s thermoregulation, their 3D-model, air circulation, convective, radiant and conductive heat transfer. Numerical modeling research is usually combined with physical modeling. The movement of air flows is analyzed using visible and infrared video cameras. The use of anatomically correct neonatal phantoms created by means of additive manufacturing was demonstrated. The thermoregulation process is simulated with the help of electric heaters, temperature sensors and control systems based on microcontrollers. The methods for monitoring the physiological parameters of an infant placed inside a neonatal incubator were reviewed. The advantages of non-contact monitoring methods using video cameras and thermometry has been illustrated. Modern neonatal incubator control systems were examined. The proportional integral derivative controllers are the basis of almost all control algorithms in neonatal incubation systems. The studies on the application of fuzzy logic control and various types of adaptive control in neonatal incubators were presented. It has been concluded that the structural and functional diagram of a neonatal incubator needs to be improved with a view to protecting from noise, electromagnetic radiation, infections, and harmful airborne contaminants. Potential approaches to improving the efficiency of maintaining neonatal-appropriate environmental conditions in neonatal incubators have been demonstrated.
Keywords: neonatal incubator, neonatal tissue-like phantom, numerical model, heat and mass transfer, system for monitoring physiological parameters, microclimate control, environmental neonatology
DOI: 10.26102/2310-6018/2024.44.1.017
An analytical study was carried out on the problem of preventing emergency situations and predictive diagnostics of equipment during hydrocarbon production in oil and gas fields as well as the ways to solve this problem by means of artificial intelligence based on deep neural networks. One of the key factors hindering the development of predictive equipment diagnostic systems is the lack of data describing pre-emergency situations, which is necessary for high-quality training of neural network models. An analysis of recent publications and research on the subject of telemetry data analysis and emergency recognition is provided. Neural network models are considered that can be used to predict the failure of pumping and compressor equipment and other units. Cases of the use of neural network models specially trained to solve this problem, as well as neural network models used in other tasks but analyzing similar data structures, were studied. The issue of transfer learning is raised to adapt neural network models originally developed and trained for other areas to use in the area under consideration in order to reduce the sample size when training industrial artificial intelligence. A comparison of the achieved results was carried out, and the advantages and disadvantages of existing technical solutions were identified.
Keywords: artificial neural networks, predictive diagnostics, machine learning, time series, telemetry, maintenance, data sets
DOI: 10.26102/2310-6018/2024.44.1.002
The relevance of the paper is due to the difficulties of oral interaction between people with speech disorders and normotypic interlocutors as well as the low quality of abnormal speech recognition by standard speech recognition systems and the inability to create a system capable of processing any speech disorders. In this regard, this article is aimed at developing a method for automatic recognition of dysarthric speech using a pre-trained neural network for recognizing phonemes and hidden Markov models for converting phonemes into text and subsequent correction of recognition results using a search in the space of acceptable words of the nearest Levenshtein word and a dynamic algorithm for splitting the output of the model into separate words. The main advantage of using hidden Markov models in comparison with neural networks is the small size of the training data set collected individually for each user, as well as the ease of training the model further in case of progressive speech disorders. The data set for model training is described, and recommendations for collecting and marking data for model training are given. The effectiveness of the proposed method is tested on an individual data set recorded by a person with dysarthria; the recognition quality is compared with neural network models trained on the data set used. The materials of the article are of practical value for creating an augmented communication system for people with speech disorders.
Keywords: hidden Markov models, dysarthria, automatic speech recognition, phonemes recognition, phoneme correction
DOI: 10.26102/2310-6018/2023.43.4.019
The article presents a mathematical model of the decision-making process by a command group in the context of conflict interaction of the requirements for the efficiency and validity of the decision. The proposed mathematical model reflects the physical and practical features of the decision-making process by the command group and takes into account the main factors influencing it. To model the decision-making process, the following are defined: stages of decision-making; the indicator characterizing the qualification of the officials included in the group; the indicator characterizing the quality of information support; an indicator characterizing the novelty of the task; the indicator characterizing the scale of activities, the indicator characterizing process automation. The model introduces a decision-making efficiency coefficient, which helps to link two main indicators of an optimal solution: validity (through the average time of development and analysis of several decision options) and efficiency (through the ratio of the total average decision-making time and the allocated time); this makes it possible to account for the influence of the quality of the decision made for the subsequent planning process. A coefficient of adopted decision obsolescence has been introduced, which helps to assess the relevance of the adopted decision after a certain period of time. Using a mathematical model, analytical expressions are obtained that make it possible to evaluate the effectiveness of decision-making while taking into account the average time of the decision-making stages and the quality factor of the command group.
Keywords: command group, decision-making process, validity of decision-making, efficiency of decision-making, quality factor of the combat control group, probability of making a well-founded and prompt decision, decision-making efficiency factor
DOI: 10.26102/2310-6018/2023.43.4.027
The analysis of electrolytes in the blood serum helpsto identify the pathological state of the human body by means of indicators of calcium, sodium and potassium. It is possible to quantify the indicated indicators by means of spectroscopy (LIBS), which makes it possible to identify sufficiently accurate data in numerical values. The aim of the study is to form the possibility of a more accurate prediction of probable diseases by means of indicators of sodium, calcium and potassium in the blood. The research process was carried out by using the available biomaterials presented by the INVITRO laboratory of Makhachkala, the Republic of Dagestan, which were subsequently used for the analysis of electrolytes in blood serum on filter paper and slides. In order to predict the concentrations of potassium, sodium and calcium under consideration by means of LIBS, the method of partial least squares regression was applied. For serum samples, higher prediction accuracy with excellent linearity was achieved both on slides and on filter paper. For blood serum on slides, the prediction accuracy of K, Na, Ca was 1,45 %, 0,61 % and 3,80 %. Moreover, for blood serum on filter paper with the existing errors were 7,47 %, 1,56 % and 0,52 %. Results. The results of the study suggest that LIBS portable tools will be an excellent tool for clinical practice in real time.
Keywords: blood serum, clinical practice, analytical method, real time
DOI: 10.26102/2310-6018/2024.44.1.032
Underwater optical wireless communications are promising and future-oriented wireless carriers to support underwater activities focused on 5G and beyond (5GB) wireless systems. The main challenges for the deployment of underwater applications are the physicochemical properties and strong turbulence in the transmission channel. Therefore, this paper analyzes the end-to-end performance of a hybrid free space optics (FSO) and underwater wireless visible light communication (UVLC) system under intensity modulation or direct detection (IM/DD) in a method considering a pulse amplitude modulation (PAM) scheme. In this study, a fading model with Gamma-Gamma (GG) distribution is used to deal with channel conditions with moderate and strong turbulence, and the links are designed by combining plane wave modeling in the corresponding links, respectively. The proposed performance methods excel in higher achievable data rates with minimal delay response and improves network connectivity in real-time monitoring scenarios compared to conventional underwater wireless communication techniques. The simulation results provide reliable estimates of system performance metrics such as average bit error rate (ABER) and probability of failure (Pout) in the presence of pointing errors. Finally, this paper uses a Monte Carlo approach for best curve fitting and validate the numerical expression with simulation results.
Keywords: 5G and 5GB networks, cooperative communication, optical communication, underwater communication, underwater sensor networks (USNs), VLC light communication
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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