DOI: 10.26102/2310-6018/2024.45.2.024
The relevance of the study is due to the fact that an important factor in the reliable operation of overhead power lines is the proper operation of insulator strings, and damage to the insulator strings’ insulation can lead to an increase in leakage currents, energy losses, including emergency situations when insulators are damaged. Also, adverse weather conditions such as ice, snow, rain, fog, and strong wind can lead to additional losses of electricity. In this regard, this article is aimed at describing a new mathematical model of the channel for measuring the mechanical load on the insulator to assess the technical condition of the insulators, which is implemented as a separate block of the information-measuring system for remote monitoring of overhead line insulators, and provides the control center operator with up-to-date information about the current condition insulators, and also allows you to reduce the number of emergency situations through timely repair or replacement of insulators. The leading method in constructing a mathematical model of a channel for measuring the mechanical load on an insulator is to consider the static load with the prospect of assessing the processes of ice formation on the wires of an overhead power line, which makes it possible to record the dynamics of the increase in the mechanical load on the insulator (fixation of ice formation), as well as without unnecessary labor costs and time resources create an easy-to-use digital model of the energy system, which provides the opportunity to implement the structure, state and operation of a real energy system with sufficient efficiency, completeness and reliability. The article presents a sequence of measured values of the mechanical load sensor on the insulator when quantized in time, which are then compared with the value of the static load on the insulator, determined by the weight of the wire on the span of overhead power lines, and as a result, an assessment of the increase in the mechanical load on the insulator is made and the formation of ice is recorded on overhead lines. The materials of the article are of practical value for operational services of electric grid companies.
Keywords: remote monitoring, overhead power line, insulator, diagnostics, mechanical load, channel
DOI: 10.26102/2310-6018/2024.45.2.023
The article presents approaches to predicting the dynamics of the state of supporting components of information and control systems using the example of modeling the power system of a manufacturing enterprise. A method for modeling other types of supporting components based on the proposed approaches is considered. Modeling the state of the power system of a manufacturing enterprise is based on its representation in the form of a set of T-shaped cells consisting of resistance, capacitance and inductance. Forecasting changes in the state of the supporting components of the information and control system is carried out using a multilayer feed-forward neural network, taking into account nonlinear factors determined by the external and internal state of the production environment. Environmental parameters, data on depreciation of actuators and equipment, and regulatory production requirements are used as independent variables, and the power of the enterprise's energy system is used as a dependent variable. In this case, the power calculation is carried out on the basis of the described power system model using T-shaped cells. The model was trained on the basis of accumulated data. The obtained results of modeling the state of the supporting components of information control systems show that using a feedforward neural network model with one hidden layer and six nodes in it to predict the dynamics allows one to obtain an accurate power forecast taking into account various nonlinear factors. Experimental data are presented that prove the effectiveness of the approaches proposed by the authors for predicting the state of supporting components.
Keywords: information and control systems, state forecasting, nonlinear factors, power systems, feedforward neural network
DOI: 10.26102/2310-6018/2024.46.3.006
To date, among the various applied tasks in electrodynamics, it is possible to note the development of various approaches aimed at evaluating and studying the scattering characteristics of various electrodynamic objects. Among them, three-dimensional objects can be distinguished, which include flat surfaces and angular structures. Their contribution to the levels of electromagnetic fields in certain directions can be quite noticeable. In order to correctly solve the problem of scattering of electromagnetic wave scattering characteristics, it is necessary to rely on appropriate methods. At the same time, it is necessary to minimize possible errors, but the three-dimensional problem in question needs to be solved in a relatively short time. In this paper, the construction of a technique related to the determination of the scattering characteristics of a structure in the form of a cube is carried out. This is due to the fact that such structures are part of a large number of modern technical facilities, this must be taken into account during their design. To solve this problem, the method of integral equations was chosen. The results of the simulation are presented. A comparison with experimental data is carried out, and it is shown that the solution converges. A comparison with the characteristics of the Huygens cube is also carried out.
Keywords: numerical simulation of scattering, diffraction of electromagnetic waves, cube structure, integral equation, huygens cube
DOI: 10.26102/2310-6018/2024.45.2.010
As a result of the research, a method for classifying the adaptive potential of the human body was developed. The method is based on the use of data obtained by conducting a functional test associated with the Heaviside function, through which a model of the transition process in a living system is obtained. Representing a living system as quasi-linear, based on its impedance model, the spectral characteristics of the living system are obtained, on the basis of which descriptors are formed for the machine learning model. To obtain an impedance model of a living system, a three-phase experiment technique is proposed. The three-phase experiment technique consists of modeling the Heaviside function in the process of performing a bicycle ergometer functional test at three levels of the functional state of the human body. This allows us to calculate descriptors for the three “branches” of the adaptive potential classifier. The adaptive potential classifier includes a driver for constructing a linear impedance model of a living system, a descriptor generator, and a decision-making module. As a linear impedance model of a living system, the amplitude-phase-frequency characteristic of a four-terminal network is used, constructed from the transient characteristic of a model of a living system, and the descriptors are calculated using the Voight impedance model, which is adequate to the experimentally obtained amplitude-phase-frequency characteristic of a model of a living system. The quality indicators of the dichotomous classifier of adaptive potential were assessed on an experimental group of undergraduate and graduate students, divided into two classes using an indicator of the activity of regulatory systems. They showed that the level of true positive and true negative results when classifying unknown examples satisfactorily corresponds to expert estimates. This allows us to recommend it for use in practical medicine, for example, in biotechnical rehabilitation systems, sports medicine, as well as for monitoring the dynamics of the patient’s functional state during treatment.
Keywords: adaptation potential, transient response, impedance model, classifier, neural network, algorithm
DOI: 10.26102/2310-6018/2024.45.2.009
The method of computer-aided design of the exoskeleton of the lower extremities using parametric design is intended for creating medical exoskeletons of the lower extremities according to the anthropometric parameters of the operator, which allows reducing the error in combining the axes of movement of the exoskeleton joints and the axes of movement of the operator’s joints. The method is based on rebuilding a reference model of the exoskeleton of the lower extremities according to the anthropometric data of the operator and includes the following design procedures: the procedure for taking measurements from the operator, taking the image obtained as a result of 3D scanning, filling out the application form that takes into account operational requirements, outputting the rebuilt exoskeleton model and accompanying documentation. To determine the elemental base of the exoskeleton, a database of electrical and radio components selected for operational requirements is used. To construct a frame corresponding to anthropometric data, a previously created reference model of the lower extremity exoskeleton is used. To test the model, the method also includes a virtual simulation of work by superimposing a rebuilt exoskeleton model on a 3D model of the operator obtained as a result of 3D scanning, followed by checking the animation of movements and the combination of model collisions. To test the effectiveness, we tested the construction of exoskeletons for the anthropometric data of the user using manual and automatic methods.
Keywords: design, CAD, automation, exoskeletons, anthropometric parameters, 3D model
DOI: 10.26102/2310-6018/2024.45.2.001
The necessity of controlling the process of classifying information signals based on simple and two-connected Markov models is substantiated. The possibility of combining previously obtained models and a classification algorithm into a decision-making system in order to classify information signals (random processes) is shown according to the criterion of maximizing a posteriori probability. The article proposes a block diagram of the decision-making system, describes the developed software components that consistently implement both auxiliary and basic procedures that allow implementing previously synthesized Markov models and methods for evaluating their parameters, as well as a classification algorithm. The description of the possibility of learning the classification algorithm, both "with a teacher" and in the "self-learning" mode, is given, the volumes of samples of the observations provided by the studied signals for the formation of databases of Markov signal models, Markov models of signal classes are determined. The results of statistical simulation modeling of the dependence of the error probability on the size of the training sample are presented. Block diagrams of some software components of the decision support system are proposed. The results of the implementation of previously developed models, methods and algorithms in the form of software tools are considered, and the functionality of using these tools as part of a decision support system is shown. The results of calculations are presented, showing the adequacy of the solutions obtained and the functionality of the developed software tools. Conclusions are drawn about the possibility of using a decision support system in various subject areas, including when classifying the conditions of the patient's cardiovascular system according to the observed rhythmograms.
Keywords: process control, markov model, classification, a posteriori probability, decision support system, algorithm training
DOI: 10.26102/2310-6018/2024.45.2.002
The article discusses the analysis of the adequacy of Markov models of parameters of partially coherent signals in radio systems based on stochastic differential equations, carried out in the MATLAB software environment. The results of modeling one-dimensional non-Gaussian and Gaussian continuous, discrete-continuous and mixed random processes are presented. The method of functional (quasi-Gaussian) approximation represents the multidimensional probability distribution density through one-dimensional component densities and elements of the correlation matrix of a vector random process. For the multidimensional probability distribution densities obtained as a result of this representation and the multidimensional stochastic differential equations synthesized on their basis, the modeling of vector random processes describing the parameters of partially coherent signals in continuous communication channels is considered. The compliance of the obtained models with theoretical distributions is assessed using the Kolmogorov-Smirnov goodness-of-fit criterion. The ranges of changes in the parameters included in the SDE at which the model can be considered consistent, as well as the influence of the parameters on the shape of the distributions under consideration, are studied. Based on the results obtained, it is possible to estimate the ranges of changes in the parameters of the models that determine the form of stochastic differential equations, under which the requirements for the adequacy of the obtained models of partially coherent in the spatial and frequency sense of signals in radio systems are met.
Keywords: partially coherent signals, stochastic differential equations, kolmogorov-Smirnov test, rayleigh and Gauss distribution models, functional approximation, white noise, poisson noise
DOI: 10.26102/2310-6018/2024.45.2.008
During their service in the penal system, employees continuously improve their knowledge, skills, and abilities through official training. This article discusses the problem of allocating training time to different areas in order to maximize the value of minimal average grades in those areas. A solution algorithm has been developed. The first step involves determining the maximum possible increase in the minimal average score for one area as well as the amount of time required for this increase. If the resultant score value is lower than the average score in other areas, the second step identifies the maximum possible increases for multiple areas and the corresponding amount of time needed. The article also determines the type of relationship between the increase in average grades for training areas and the time spent on training through the approximation of statistical data. This allows for the analytical solution of the problem. The analysis of the potential use of power and exponential functions for approximation, which allows for the approximate solution of a problem through numerical methods, is also conducted. The resulting values of the coefficient of determination confirm the high accuracy of the approximation. Graphs of the dependency are presented. Two examples of analytical solutions to the problem are provided, illustrating the use of the proposed method. In the first example, all employees have the same initial average training grades in all areas, and in the second example, average grades differ.
Keywords: average grade, average grade increment, learning time, learning curve, approximation, least squares method
DOI: 10.26102/2310-6018/2024.45.2.003
The relevance of the study is due to the need to obtain analytical expressions of approximate solutions to complex technical problems, the mathematical description of which leads to boundary value problems for systems of differential equations in network-like domains and, in particular, on graphs. The article presents the formulation of an initial boundary value problem for an inhomogeneous continuum transfer equation in an n-dimensional network-like region. In the case of n=1, a symbolic method for solving the initial boundary value problem under consideration on a tree graph is proposed. 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 used) and the subsequent application of the Laplace transform to the resulting differential-difference system. A block diagram of the algorithm is presented, and a description of the structure of the software package based on the developed algorithm is given. The software package is developed in the Java programming language. To enter 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 with a step-by-step demonstration of the calculation results is considered. The materials of the article are of practical value for specialists in the field of analysis of applied problems of network hydrodynamics, thermal engineering, as well as analysis of diffusion processes in biophysics.
Keywords: symbolic method, differential-difference system, initial boundary value problem, continuum transfer equation, graph-tree
DOI: 10.26102/2310-6018/2024.45.2.022
The article presents the results of a study involving the formation of an optimization model and an interactive procedure for making structural and component decisions based on the principles of building an integrated CAD of cyberphysical systems (CFS). A description is given of the five main levels within which the CFS design process is implemented. Some approaches that were used by the authors during the design of the design elements of the CFS are considered. The description of how the optimization model of structural and component synthesis is formed is given. The main components of such an optimization model are given. The structural elements of the CFS are described on the basis of a set of formed sets. Three groups of indicators in the model are identified. The first group includes reliability and cost, which are calculated for the entire CFS as a whole. The second group includes the indicators calculated for some digital threads. The third group of indicators is related to the principle of covering the entire life cycle of the CFS from project to operation. An interactive procedure for making a structural and component design decision is presented. The generation of solution options is carried out in an automatic randomized search mode by replacing Boolean variables with random ones.
Keywords: cyberphysical system, CAD, structural and component design, optimization, expert assessment
DOI: 10.26102/2310-6018/2024.45.2.007
The connection between the concepts of “security” and “development” is inextricable, since security is a process, not a state. The preservation of the regional socio-economic system as a goal of ensuring security is achievable if the process of maintaining development proceeds in a chronological manner – both today and in the long term. The paper outlines the theoretical and methodological foundations of the energy flow concept for regional socio-economic systems. Based on this concept, the possibility of applying a comprehensive model of assessing energy and environmental development and energy security in the context of the transition to sustainable development of developing economies is proposed and tested using the example of a group of BRICS member countries (with the exception of Ethiopia, Iran and the UAE). Technological generalized efficiency factor is introduced as a key indicator of energy security and development of the regional socio-economic system. A comparative assessment of the economies of the BRICS countries was carried out according to the following indicators: technological total capacity, economic total capacity, technological useful power, economic useful power, the ratio of technological efficiency to economic efficiency. As a result of the analysis, it was found that Egypt among the BRICS countries (with the exception of Ethiopia, Iran and the UAE) has the highest growth rate of technological useful capacity. Also, based on the results of the study, a ranking of the energy security of various countries was compiled.
Keywords: energy and environmental development, energy security, BRICS countries, technological efficiency, economic efficiency
DOI: 10.26102/2310-6018/2024.44.1.033
This paper considers the problem of detecting machine-generated texts using various regression model building tools – classical linear regression, logistic regression and quantile regression. Advances in machine learning are creating increasingly realistic texts, which opens the door to misuse. As text generation algorithms become more sophisticated, the complexity of the task of detecting such texts increases, which also requires more sophisticated mathematical modeling methods and more efficient numerical methods. The proposed adaptive quantile regression algorithm is a tool that allows building models with emphasis on different quantiles, which makes it particularly useful for detecting atypical values that may indicate the artificial nature of the texts. The paper also presents a detailed description of the initial open dataset for model training, which is a set of generated texts using the GhatGPT 3 model and random texts from various forums, and analyzes the computational experiments performed. The results show the high efficiency of the proposed method in this field of application.
Keywords: text classification, quantile regression, adaptive algorithm, gradient descent, mathematical modeling, numerical methods
DOI: 10.26102/2310-6018/2024.45.2.005
This work is devoted to the problem of the security of image recognition systems based on the use of neural networks. Such systems are used in various fields and it is extremely important to ensure their safety from attacks aimed at artificial intelligence methods. The convolutional neural network ResNet18, the ImageNet verification set for recognizing objects in an image and classifying it to a class, and adversarial attacks aimed at changing the image processed by this neural network are considered. Convolutional neural networks detect and segment the objects that are in the images. The attack was carried out at the detection stage in order not to recognize the presence of objects in the image, as well as at the segmentation stage, the modified image attributed the recognized object to another class. A series of experiments was implemented that showed how an adversarial attack changes different images. To do this, images with animals were taken and an adversarial attack was carried out on them, the analysis of their results allowed us to determine the number of iterations necessary to make a successful attack. The original images were also compared with their versions modified during the attack.
Keywords: neural networks, attacks on neural networks, adversarial attacks, resNet18, transformation matrix
DOI: 10.26102/2310-6018/2024.45.2.006
During the research, a new modeling method was developed that makes it possible to adapt the electromagnetic response of the environment of a spontaneously ordered nanocomposite in time, using the concept of a temporarily effective environment, which can be used to create new nanostructured materials with specified electrical properties. Using computer technology and mathematical methods, modeling of the dielectric constant of temporal nanocomposites with a complex structure was carried out. A mathematical model developed to describe the dielectric constant of temporal nanocomposites is presented. The model takes into account various factors, such as the geometric parameters of nanoparticles, their concentration, orientation and characteristics of the dielectric matrix. Using the proposed model, numerical experiments were carried out to evaluate the influence of structural features on the dielectric constant of temporal nanocomposites. The work studied the distribution of the electric field in the time domain for nanocomposites with complex configurations and having a dielectric constant that varies periodically with time. The study demonstrated the possibility of using the effective medium model in problems of designing temporal nanocomposites of complex configurations. The research results can be used in practice-oriented problems related to the design of metamaterials with specified electrical properties.
Keywords: mathematical modeling, software, materials made of nanocomposites, computational research, permittivity
DOI: 10.26102/2310-6018/2024.44.1.029
The paper examines the issue of coordinating two processes by directing them towards the design values of the flow realized by these processes. The production process is considered random (since it is associated with the actions of personnel) and, in the first Markov approximation, is described by the Fokker-Planck-Kolmogorov equation. A study of the problem of optimal control of process coordination using probabilistic quality criteria shows that if one thread follows the other according to a tracking scheme, and the other provides the necessary level of readiness for the meeting, both threads will complicate each other’s management. Therefore, design symmetrization has been introduced, in which both the output of one process and the input of the second tend to the value specified by the design. Analysis of the first approximation obtained by the small decision parameter method shows that even with optimal control, the magnitude of control actions increases in proportion to the design value of the probability density and control duration; the increase in control actions over time should occur according to the cube of the exponential, that is, very slowly at the beginning of control and very sharply at the end, a similar pattern of increase is demonstrated by the dependence of control actions on the magnitude of the flow intensity, but it is expressed through hyperbolic functions.
Keywords: optimal control, markov process, probabilistic quality criteria, design symmetrization, small parameter method
DOI: 10.26102/2310-6018/2024.44.1.026
It is well known that digitalization in the logistics field can significantly increase the awareness of all stakeholders about the presence, status and movements of inventories, help to reduce losses, damage and theft of equipment and materials, and reduce the burden on personnel responsible for inventory control. Nevertheless, the subject area of inventory accounting in telecom-outsourcing organizations is not a widely researched area. The managers solve the arising practical issues of inventory accounting and its optimization following the example of the enterprises in other industries. The purpose of this study is to systematize the directions and methods of optimization of inventory accounting in telecom-outsourcing organization with the help of modern information technologies. The paper examines the links between traditional approaches to inventory accounting, their re-engineering, coordination and digitalization. The methodological aspect of the study includes identification of practical problems in the field of inventory accounting, systematization of terms, search for solutions to similar problems in other industries, identification of problem-solving options and analysis of relevant modern technologies. The main result is a systematized overview of the problems under consideration and ways to solve them with the help of organizational measures and IT. This paper can be useful both for researchers in the field of logistics and optimization theory to choose directions for in-depth study of the mentioned problems, and for practicing managers searching an overview of approaches to inventory optimization.
Keywords: telecom outsourcing, inventory accounting, reengineering, digitalization of business processes, supply chain management
DOI: 10.26102/2310-6018/2024.44.1.028
The article considers the problem of temperature distribution in the strip and working rolls during hot rolling under the conditions of uncertainty of input parameters. The zone of the deformation gap with the formation of a rolling scale strip on the surface is regarded, as a result of which a system of thermal conductivity equations with different initial and boundary conditions is solved in the area of the deformation gap being studied. Next, the zone of the interstand gap is considered, where the heat exchange of the strip with the environment occurs. In all zones, the input parameters are represented as interval numbers. The deformation gap and the interstand gap were discretized from a continuous region into a grid one, systems of linear algebraic equations with tridiagonal interval coefficient matrices were derived using finite difference approximation, and a counter-run method with interval coefficients was presented to solve the obtained systems. The article considers the calculation results for 7 stands running one after another and consisting of a deformation gap and an interstand gap for the case with real input parameters and for the case with interval input parameters, calculations were performed using the developed software for both cases.
Keywords: equation of thermal conductivity, two-sided Thomas algorithm, interval arithmetic, hot rolling, finite difference approximation
DOI: 10.26102/2310-6018/2024.44.1.024
The paper examines the creation of a hardware and software prototype of an unmanned vehicle and testing its hardware and software architecture in an attempt to create a universal standard solution for this type of device. The problem of controlling a drone is considered in such a way that it is possible to flexibly switch the sources of control commands and control algorithms. For this purpose, the subsystems for generating and executing control commands are proposed to be connected via a message queue. It is makes possible to combine autonomous and manual controlled modes of operation of the drone. A method for generating control commands when an object follows a program trajectory, based on a neural network, is proposed. The input data of the network are the coordinates of the program trajectory and the current state of the object, and the output data are control actions. The paper describes the hardware and software components of an automobile-type device, the architecture of its control system, the architecture of a neural network, and possible approaches to its training. The creation of a training set using both simulated and real traffic data is discussed, which allows the self-driving device to “learn” different driving styles. The results of experiments with various training samples are presented, which demonstrate the practical applicability of the proposed control method. Attention is paid to aspects of the neural network structure, including the choice of the number of layers and neurons. The possibility of using “intermediate” points of the program trajectory to improve the properties of the object’s movement is indicated. In general, it is concluded that the use of neural networks is promising in the control of drones, in cases where combining and flexible switching of control algorithms is required.
Keywords: unmanned vehicle, vehicle control, navigation, autonomous vehicle, neural network
DOI: 10.26102/2310-6018/2024.44.1.022
The process of underwater oil and gas production is accompanied by high values of well pressure, which can reach thousands of atmospheres, while the service life of this equipment, laid down in the technical specifications, can reach 20 years or more. To ensure the safety of the subsea production process throughout the life of the equipment, it is important to pay special attention to the tightness and strength characteristics of metal seals as part of the design. In this regard, this article is aimed at identifying the degree of influence of such a geometric parameter as the depth of the recess on the characteristics of the tightness and strength of metal seals. The finite element method was modelled, using the Ansys calculation complex, of the stress-strain state of the metal seal of a tubing hanger of a standard design during installation and under the influence of well and test pressure. Finite element modeling was carried out using elastoplastic models of material deformations. To analyze the performance of a metal seal design, criteria for assessing strength and tightness are given. During the modeling, parameters characterizing the tightness and strength of the structure were determined. In order to study the degree of influence of the recess depth of the metal seal on the characteristics of tightness and strength, modeling was performed with an increase in this parameter to 80 %. The results of calculations of tightness and strength parameters with different recess depths are presented. The materials of the article are of practical value for design engineers and scientists dealing with the problems of ensuring a hermetic underwater connection using metal seals.
Keywords: subsea production system, metal seal, stress-strain state, tubing hanger, subsea Christmas tree, contact pressure
DOI: 10.26102/2310-6018/2024.44.1.027
The technological process of single-parameter selective assembly of two elements with parameters that are random variables, the values of which are determined by the finishing operations of the manufacturing processes, is considered. It is considered that the dependence between input and output parameters is nonlinear (nonlinear input-output models) and is represented in the form of quotient, and the completing rule is elementary. For a dependence of this type, expressions linking the values of tolerances (including group tolerances), limit deviations and limit values of input and output parameters are given. A method is proposed that helps to calculate group tolerances to fulfil the requirements to the accuracy of the output parameter in the whole area of its permissible values, as well as to determine the boundaries of selective groups. It is based on an iterative procedure, with each iteration consisting of sequentially executed steps. The output data of the previous iteration are the initial data for the next one. As a criterion for the end of the procedure, a given level of accuracy in calculating the average group tolerances is taken. The analytical and probabilistic model is developed, which takes into account the calculated boundaries of selective groups and helps to determine the most important indicators of selective assembly, such as the probability of formation of assembly sets, probabilities of formation of incomplete elements. An example of modelling is given, in which process indicators are determined using the developed method and model with given initial data. Prospects for further research are outlined.
Keywords: selective assembly, mathematical model, nonlinear dependence, quotient, iterative method
DOI: 10.26102/2310-6018/2024.45.2.004
Scientific studies have differed on the interpretation of activity in the primary motor cortex of the brain. Various studies have found that the primary motor cortex is activated only during physical motor tasks. Whereas other studies have appeared that a similar measurable activity can be observed and recorded when arousing or stimulating the motor cortex when performing a mental representation of movement. Consequently, our purpose of this review was to compare the triggers of motor cortex activation during the physical execution and mental representation of the movement by recording the brain signals resulting from the stimulation by using the technique of near-infrared functional spectroscopy based on the neural interface (brain-computer interface). This research reveals differences and comparisons based on various approaches to analyze and systematically realize target triggers of motor cortex activation during training at neural interface (fNIRS). Based on the above, this review concludes by emphasising the fact that triggers of cortical activation in general and under different names cause activity that can be recorded by measuring the various changes that occur in hamoglobin concentration, in other words, that both physical task performance and similar mental representations of movement cause perceptible activity in the motor cortex. This provides the rationale for prosthetic, rehabilitation and other applications. Furthermore, this encourages future research to identify positive triggers for cortical activation to study psychological states of cognitive function and certain pathological conditions, as well as neurophysiological studies.
Keywords: near-infrared functional spectroscopy, triggers, motor cortex, brain-computer interface, physical movement, mental representation of movement
DOI: 10.26102/2310-6018/2024.44.1.025
Modern approaches to solving the problem of controlling walking robots with rotary links are disparate algorithms built either on a ready-made locomotor program with its further adaptation or on complex kinematic-dynamic models that require extensive knowledge about the dynamics of the system and the environment, which is often unfeasible in applied problems. Also, the approaches used are strictly related to the configuration of the walking robot, which makes it impossible to use the method in applications with a different configuration (a different number and type of limbs). This article proposes a universal approach to controlling the motion of walking robots based on reinforcement learning methodology. A mathematical model of a control system based on finite discrete Markov processes in the context of reinforcement learning methods is considered. The task is set to build a universal and adaptive control system capable of searching for the optimal strategy for implementing a locomotor program in a previously unknown environment through continuous interaction. The results distinguished by scientific novelty include a mathematical model of this system, which makes it possible to describe the process of its functioning using Markov chains. The difference from existing analogues is the unification of the description of the robot.
Keywords: control system, reinforcement learning, markov decision processes, neural networks, walking robot, artificial intelligence
DOI: 10.26102/2310-6018/2024.44.1.023
The increasing density of water transport traffic in Moscow requires regulating the movement of numerous tourist, pleasure and scheduled boats, as well as ensuring the necessary level of safety for passenger transportation. The government of Moscow is creating a system for organizing the movement of passenger ships (SOMPS), which is designed to solve these problems in the waters of the central pool of Moscow between locks No. 9 and No. 10. The SOMPS concept for Moscow based on the engineering-cybernetic approach is developed in the paper. The choice of a higher-level system (meta-system), the requirements of which the designed system must satisfy, is justified. A block diagram of the SOMPS, which includes five subsystems, is presented. The factors determining the properties of the designed system and the limitations affecting the functioning of the SOMPS are considered. The developed concept of the SOMPS makes it possible to isolate the optimal structure of the telecommunication subsystem, which provides the necessary channels of control, management and information exchange between the SOMPS elements and external systems, and to determine its tasks. The communication channels that are part of the telecommunication subsystem are described. External and internal factors that can affect the functioning of the designed SOMPS and its telecommunication subsystem are presented. The necessity of introducing a module for calculating the meeting point of vessels under bridges into the designed SOMPS is substantiated. Methods for transmitting alarm signals between the SOMPS and external systems are described. An example of the VHF repeaters placement along the passenger route No. 1 on the river bends is presented. A conclusion about the optimality of the telecommunication subsystem structure, which ensures the fulfillment of assigned tasks while minimizing the resources involved is made.
Keywords: telecommunication subsystem, system for organizing the movement of passenger ships, moscow water area, engineering-cybernetic approach, communication channel, traffic management center of Moscow Government, AIS, automated operator workstation
DOI: 10.26102/2310-6018/2024.44.1.020
The article discusses the process of working on a project in a team-oriented IT system using optimization modeling of the iterative process of purposeful team activity based on management principles in an Agile-oriented organizational system. For such a system, the general principles of flexible development methodologies aimed at accelerating the creation of projects by dividing the final requirements into smaller parts in order to take into account feedback from stakeholders at each stage of work are transformed into problem-oriented ones, which allows us to highlight the management features from the point of view used to consider the process of working on the project. It is shown that these principles are initially implemented at the level of the management center, in particular, the project manager should be well-acquainted with them, then at the team level and only after that the developed optimization programs should be implemented. The results of their application are shown in the description of each management feature. For an objective assessment of the effectiveness of the developed software tools, a comparison of the results of work on similar projects is given. In one, only the principles of flexible project management methodologies were applied; in the other, developed software tools were additionally employed to manage the iterative process of goal achievement in a team-oriented organizational system.
Keywords: agile-oriented organizational system, team activity, multi-alternative optimization, expert assessment, management decision-making
DOI: 10.26102/2310-6018/2024.44.1.016
The relevance of the research is due to the growing need for fast and accurate tools for building mathematical models. This paper discusses approaches to building adaptive quantile regression because selecting the optimal quantile during the training process can save a large amount of researcher's time. The correct choice of quantile can significantly improve the performance of the model on test datasets and, as a consequence, obtain more reliable predictions when such a mathematical model is actually used. The developed approach is a combination of modified quantile regression and gradient descent, which improves the adaptation of the model to different data. A detailed description of the developed algorithm is given. The paper also presents a comparison of the performance accuracy of the proposed model with traditional quantile regression and gradient descent along with their combinations. It also analyzes the training time of the models, including the number of training epochs. Experiments show that adaptive quantile regression exhibits improved accuracy with reduced training time. The results emphasize the effectiveness of this method in data analysis and prediction, opening new perspectives for more efficient and faster machine learning models.
Keywords: quantile regression, adaptive algorithm, gradient descent, mathematical modeling, numerical methods
DOI: 10.26102/2310-6018/2024.44.1.009
The article proposes a method for solving the problem of adapting a discrete inventory management model to the problem of combat operations of two armies. The aim is to identify the control effect on the linear system of difference equations, which allows it to be transferred from the initial to the final state in the specified parameters provided that costs are minimized. Discrete controlled processes play an important role in the theory and practice of optimal control since many planning tasks are described precisely by systems of difference equations. A system of equations of this type is characterized by a discrete type of control of the number of combat units at the current stage. Deliveries are formed at fixed intervals. The effectiveness of management is controlled (verified) by a quadratic quality criterion, which characterizes the cost of conducting combat operations. The criterion shows the total cost of supplies and maintenance of combat units, the change in the number of which is determined by three factors: the rate of losses as a result of hostilities, natural losses and the rate of receipt of reinforcements. The construction of an optimal control effect is carried out by the feedback method. It is noted that the solving this task is complicated by the fact that it is necessary to find among all possible solutions those that will make it possible to achieve your goals with the least expenditure of human and material resources. These costs are presented as functions of several variables, the values of which are known at the initial time. The article proves that in order to solve the problem of optimal resource management in relation to the case of combat operations of two armies, the feedback method is the most preferable. Several examples have been analyzed. The implementation of the feedback method clearly shows that a longer period of confrontation significantly reduces losses. The materials of the article are of practical value for strategic planning in the context of military conflicts.
Keywords: optimal control, discrete system, feedback principle, combat operations, control influence
DOI: 10.26102/2310-6018/2024.44.1.012
The paper considers the methods of authorship identification for fanfiction texts based on popular works of literature and cinema. The data for the study include texts from 5 popular topics of Ficbook online library. The most common is the closed set attribution task. Regarding practical issues, it can be assumed that the true author of an anonymous text will not always be included in the candidates set. Therefore, the process of author identification was regarded as a more complex version of the typical classification problem – the open set of authors. The proposed methods are based on the machine learning methods: fastText and One-Class SVM with informative features selection and statistical approaches of vector representation similarity measures. Statistical methods have proven to be the least effective even for the simple cross-thematic case. In comparison with the method based on One-Class SVM, the difference in accuracy reaches 15 %. For cross-thematic attribution, the average accuracy of the method based on the combination of One-Class SVM with feature selection and fastText was 85 %, while for the more complex task – classification within a group – it ranged from 75 to 78 % depending on the thematic group.
Keywords: text authorship attribution, fastText, machine learning, text analysis, information security
DOI: 10.26102/2310-6018/2024.44.1.018
Currently, managing computing resources in modern distributed computing systems is the relevant problem. As a result of infrastructure capability evolution, distributed computing can be organized in dynamic, heterogeneous and geographically distributed computing environments, examples of which are “fog” and “edge” ones. The dynamics of both load and topology imply the need to change the system configuration, namely, assigning user tasks to computing devices with the allocation of the necessary resources. The latter raises the issue of increasing the efficiency of the scheduler (broker), which facilitates management of network resources within the allocated fragment. Algorithmic and software schedulers are based on models and methods of scheduling theory and implement either simple heuristics, mathematical programming methods or metaheuristics. However, an analysis of publicly available problem statements has shown that, firstly, they are special cases and implement certain situations of computing resource distribution, and secondly, they do not fully reflect the properties of heterogeneity, geographical distribution and dynamics of computing environments. As part of this study, a general model of computing resource allocation problem is proposed with consideration to the listed properties, and a solution method using the subject ontology of metaheuristic methods is proposed. The feasibility of constructing and applying an ontology is shown using the example of analyzing the effectiveness of genetic algorithms depending on the values of the computing resource allocation problem parameters which is being solved.
Keywords: ontology, resource allocation, distributed computing, distributed computing management, resource management, optimization
DOI: 10.26102/2310-6018/2024.44.1.013
The paper proposes two approaches to analyzing time series of bacterioplankton abundance in three different layers of the water column in Lake Baikal. In the first approach, the values of the seasonal component of the series are calculated using the moving average method, and additive and multiplicative models are constructed, from which the best models are selected on the basis of the calculated reliability coefficients. The seasonal component values in each of them are estimated. In the second one, correlation and regression analysis of joint changes in bacterioplankton abundance, temperature and lake water level is performed. Statistical hypotheses about the significance of correlation coefficients between the considered factors are put forward and tested. A mathematical model of multiple regression with inclusion of dummy variables describing the influence of seasonal fluctuations on changes in bacterioplankton abundance is constructed. Statistical assessment of the significance of the model and the factors included in the model is calculated. The results of correlation-regression analysis are interpreted in relation to the subject area under study. The findings can be used in predicting the amount of bacterioplankton in different periods of time, in making an ecological substantiation of the state of the lake, as well as in forecasting its microbiological state.
Keywords: time series, bacterioplankton, moving average method, seasonal component, correlation and regression analysis, multiple regression model, lake Baikal
DOI: 10.26102/2310-6018/2024.44.1.014
Planning is an important process for a project. The main planning processes include defining activities, planning resources, determining the duration of work, and developing a schedule. The paper examines projects with independent activities. The purpose of the study is to optimize project schedule by period. Three particular problems are considered. The first problem is to distribute activities over periods in order to achieve the maximum total effect of their implementation taking into account cost constraints in each period and the possibility of partial implementation of the activities in a given period. The solution algorithm is based on the Cost-Effect method. The validity of the proposed algorithm has been proved. The second problem deals with the distribution of work over periods with the prohibition of transferring part of the work to other periods and limitation of costs in each period. Based on the method of dichotomous programming, we propose an algorithm for solving the problem for two periods. For the number of periods greater than two, an approximate algorithm is suggested. For the case when information on unperformed activities in the course of project implementation changes, the problem of maximizing the total effect from the implementation of project activities in the current period is considered. Additionally, the effect from the implementation of a set of activities is visible after their completion and a certain effect manifests from the partial implementation of another set of activities. The effect obtained is proportional to the part of the amount of work performed. An algorithm for solving the problem based on obtaining parametric dependences of the total effect for each set of activities on the value of costs is proposed. The validity of the algorithm has been proved. Examples illustrating the application of the proposed algorithms are presented.
Keywords: project, work, period, effect, costs, resource, satchel problem, dichotomous programming method