Keywords: neonatal incubator, neonatal tissue-like phantom, numerical model, heat and mass transfer, system for monitoring physiological parameters, microclimate control, environmental neonatology
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
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
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
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: Модель разработки расписания проекта противодейств
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
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
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
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
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
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
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
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
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
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, cartographic scenes, scene analysis
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
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
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
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
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
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
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
The paper deals with the issue of safe ship movement under the conditions of heavy traffic. The problem of avoiding the collision of groups of vessels is considered. It is noted that avoiding the collision of autonomous (unmanned) ships has its own specific nature. When moving in groups, an autonomous ship needs to “know” the intentions of other participants in order to correctly interpret the regulations for passing ships. This requires an extension of known collision avoidance algorithms for the cases of group locomotion. The paper describes a mathematical model of the ship collision avoidance problem based on traditional geometric representations of the relative motion of ships. The plan of actions for a vessel under the conditions of group locomotion is given. The software tools used to set up computational experiments in collision avoidance of groups of autonomous ships are described. It is noted that the proposed algorithm can be successfully applied to ships with a crew and implemented in automated onboard ship controls. An example of calculating maneuvers for collision avoidance of a group of seven vessels is shown. It is pointed out that setting up full-scale experiments for groups of small-sized models of autonomous surface vessels is necessary in order to test the proposed algorithm and assess the prospects for its use in practice. Recommendations on the possible design of such vessels are given with a view to setting up experiments along with the guidelines for the development of appropriate coastal infrastructure which will provide support for autonomous navigation in the future.
Keywords: ship traffic management, maritime safety, unmanned navigation, е-Navigation, a-Navigation, near collision, evasive action, group of vessels
The article considers the application of an optimization approach to making management decisions with random variations of the investment resource allocated by the managing center of a sectoral organizational system for implementing the subsystem of development. The limitations of traditional expert assessments in the distribution of investments between organizational system objects and the reasons for using random variations to smooth the costs of non-optimal decisions are shown. The article presents the statement of investment management optimization problem. Algorithmization of management decision-making based on expert and optimization assessment integration is proposed. The article also determines the purpose and objectives of the research. The structure of the combined algorithmic procedure for making management decisions based on a synchronous search in the spaces of the development program performance indicators and a variable investment resource by means of the immersion in a randomized environment is substantiated. For this purpose, the probabilistic characteristics of indicator significance are introduced and determined at each iteration in their additive convolution and object investment in the coordination of an expert assessment of the need for a resource with a numerical solution. In order to navigate the indicators space, a modification of the particle swarm algorithm is suggested which is integrated into the scheme of random search for the volume of investments with random variation in accordance with uniform and normal distribution laws. To implement the algorithmic procedure in the case of two variants of the distribution law, a sequence of actions is considered when introducing initial conditions and the topology of a particle neighborhood while moving from the current iteration to the next one when using the stop rule and determining the optimal control decision.
Keywords: investment process, sectoral organizational system, development program, optimization, expert assessment, random search
The paper discusses the development of an algorithm for analyzing profilogram images obtained using the ZYGO ZeGage Pro HR optical profilometer in order to determine some parameters of material surface treatment: grinding directions and the angle between them. The analysis of such data makes it possible to make a connection between the applied material processing technology and the quality of the resulting surface. The need to automate this process is a relevant objective. Solving it will reduce the time taken to analyze a large volume of test samples and accelerate their quality control. This paper presents the process of the developed algorithm operation based on the application of methods for detecting geometric objects in images. The algorithm consists of several stages, including pre-processing of input data, methods for detecting straight lines in the image, extracting surface grinding directions, and determining the angle between them. In addition, as part of the study, a modification of the algorithm based on image frequency analysis was proposed. This modification allows eliminating the shortcomings of the main implementation described in the paper determined by the specifics of the input data; it also enables the increase in the efficiency of the program. Also, conclusions are given on the results of accuracy tests for the developed algorithm and its modification obtained using different samples of the surfaces under study.
Keywords: image analysis, finding lines in an image, calculating angles, diamond plate, surface polishing
The relevance of this study is due to the need to improve the efficiency of extracting key phrases and words from the Russian-language patent array. Currently, patent office experts have to analyze texts of patent applications manually in order to identify key phrases and words that are then used to search for patent counterparts. This process is time-consuming and can be error-prone. Another problem is the lack of a system similar to Google Patents but for Russian-language patents. Currently, there is no reliable and effective tool for automatic identification of key patent phrases and words in Russian-language patents. This limits the ability of experts to search and analyze patent analogues as well as to make decisions on patenting. Improving the efficiency of extracting key phrases and words from the Russian-language patent array is of great practical importance. This will reduce the time spent on the analysis of patent applications, improve the accuracy of the search for similar patents and provide more reliable patenting solutions. Such a tool will be useful for patent offices, legal consultants, engineers and researchers who work with Russian-language patents. In general, this study is conditioned by the need to improve and automate the process of analyzing patent applications, which will lead to an increase in the efficiency and accuracy of managing the Russian-language patent array and make it more accessible and user-friendly.
Keywords: patents, patent search, keyword extraction, full-text search, HDFS, apache Solr, django, keyT5
This article presents one of the scientific results obtained by the author in the course of the dissertation research. The problem considered in the study, namely the problem of ensuring the safety of road users, is raised. It was demonstrated that in megacities the installation of the “necessary minimum set of means” is not observed in all areas, which, in turn, causes violations by road users. Existing methods for assessing and improving the safety of road users are considered, limitations are highlighted. A possible tool for solving the analyzed problem with the aid of the identified restrictions is proposed which is the rational placement of technical means of traffic organization. An algorithmic apparatus has been developed that allows predicting and recommending suitable places for installing technical means of organizing traffic on those streets where they are located either irrationally or not at all based on the Decision Tree machine learning algorithm. A proprietary method for preparing input data with a description of the stages is proposed. The use of the semantic differential method to determine the weights / importance of attributes is proposed. Testing of the developed algorithmic apparatus was carried out both using the example of the “model” and using the example of a real site. It is noted that the proposed algorithm is able to generate a large amount of input data, which will further expand the algorithm and take into account even more various factors. It is expected that the developed algorithmic apparatus will significantly minimize the number of traffic accidents. It is assumed that the scientific results obtained in the research will allow a comprehensive assessment of the problems of organizing traffic in existing built-up areas or areas planned for development.
Keywords: technical means of traffic management, algorithmic apparatus, method, semantic differential, decision tree machine learning algorithm
Agricultural administration in the context of the digital transformation of the economy is becoming more important when ensuring the competitive advantages of our country, especially taking into account the challenges of the modern geopolitical situation. The introduction of various kinds of innovations requires prompt actions in order to facilitate the development of domestic technical, technological and information products. The article deals with the issue of automation of decision support in the management of agriculture subsystems by means of a developed software product with adaptive characteristics that does not require additional digital and qualification resources. Methods of system analysis, logical approach and synthesis, optimization, algorithmization, etc., were used. Official statistical data were used, which made it possible to present the dynamics of a number of indicators (acreage and yield of fodder crops, number of cows and milk production, etc.) of agricultural production in Russia for the period 2017–2021. The conclusion is made about the intensification of production activities in the field of dairy cattle breeding. Special attention is paid to the development of algorithms and their software implementation with a view to adjusting the diet of dairy cows with consideration to scientifically based requirements, breed restrictions, norms, etc. Flowcharts for designing a user interface and functions for calculating the required amount of minerals, algorithms for calculating energy and protein requirements are given. Developed in Python, the program takes into account the selected parameters for calculating the productive feeding ration of cows and is an integral part of the intellectual system being developed. By means of simulation, it helps to choose the most suitable values of output parameters for their further use in the form of numerical restrictions when solving the problem of minimizing the cost of the feeding ration by linear programming methods. The program has a universal character regarding the introduction and use by agricultural producers, provides automation of the decision support system and does not require additional time-consuming training of decision makers who aim to achieve the efficiency of domestic agriculture performance.
Keywords: algorithm development, optimization problems, agricultural administration, decision support system, dairy cattle breeding, feeding ration, decision-maker, flowchart, program
The article examines the problem of collecting time series data by AIOps system for monitoring the IT infrastructure with subsequent processing of the received data in real time. The relevance of the study is due to the growing interest in systems of this class on the part of large enterprises and organizations with a high degree of production process digitalization. In its turn, the organization of the process of collecting such information is conditioned by a number of features: firstly, software modules must be designed taking into account a significant load (collection and processing of about 10 million metrics per minute); secondly, end devices are not often used to collect data, other monitoring systems are employed instead. It is also required to consider the current state of the IT infrastructure characterized by its dynamism caused by the development and widespread implementation of hardware virtualization technologies, application containerization and automated configuration management. Based on a comparison of approaches to the collection and processing of time series data implemented in various monitoring tools, the paper concludes that the application and development of the Prometheus approach in AIOps monitoring systems is promising. The authors offer their own version of the adaptation and development of this approach. Distinctive features of the proposed option are a multi-status model of thresholds with a lifetime as well as the indirect establishment of links between objects in the resource-service model and the collected metric information, which helps to implement the functionality required by enterprises for collecting and processing metrics for an AIOps monitoring system under the conditions of high load and dynamism of modern IT infrastructure. In conclusion, the results of the developed software module preliminary testing are presented, and the possibility of using the approach proposed by the authors to implement the function of controlling the degree of monitoring object coverage is underscored. Currently, the described version of the architecture is used in the commercial software product "MONQ" and is being tested in several key Russian enterprises.
Keywords: monitoring system, time series, IT service, resource-service model, service management system, AIOps, big data
Radar signal scatterers (space, air, ground and water-based radar targets) and electromagnetic wave energy converters (spatial light modulators, means of reducing visibility in the radio wave range, antenna devices in the ultra-high frequency wave range) have complex geometry and large electrical dimensions and also contain absorbing and nonlinear elements. The analysis and synthesis of this electrodynamic technique based on rough knowledge of the physical processes occurring in these objects can cause significant and difficult-to-control errors in the assessment of their main characteristics, which change rapidly with changes in frequency, type of polarization and angle of incidence of electromagnetic waves. This paper examines a methodological approach aimed at evaluating and optimizing the scattering characteristics of electromagnetic waves that occur when electromagnetic fields interact with electrodynamic structures containing dielectric inclusions. To calculate these characteristics, the method of integral equations is used, and a genetic algorithm is employed to optimize them. The results of the study demonstrate the efficiency of the proposed approaches. The methodological approach considered in the paper can be used to improve the electromagnetic compatibility of devices, reduce their radar visibility.
Keywords: modeling, optimization, electromagnetic wave scattering, integral equation, genetic algorithm, radio communication
The article examines the mechanisms of intercomponent interaction in multi-agent systems. The paper discusses various approaches to messaging between components as well as the advantages and disadvantages of each of them. The key problems of intercomponent interaction are identified and their solutions are proposed. Particular attention is paid to the messaging mechanism based on the message broker. The principles of the broker, its advantages and disadvantages as well as examples of use in multi-agent systems are described. The results of the study showed that the use of the message broker makes it possible to create a flexible and scalable system that can efficiently process a large number of messages and maintain high reliability in operation. The paper presents a description of the data transfer format structure between the components of a multi-agent system. Message routing schemes within the system using a message broker are shown. The configuration for the implementation of the intercomponent interaction schemes is described. A mechanism for encoding messages based on tag keys is proposed, which enables their identification for further processing by software agents. This approach can be useful in the design and development of various multi-agent systems, where it is necessary to exchange messages between different software agents.
Keywords: multi-agent system, message broker, data format, JSON, rabbitMQ, MAS, coding