The production of nitrogen from air using membrane gas separation processes is widely used in many industries. The problem of controlling the gas separation process is associated with multi-loop control using control of several variables. To build a model of a gas separator, a detailed analysis of the gas separation process was carried out in this work. This article proposes a fuzzy logic controller used to match pressure fluctuations and air flow of a gas separator. The performance of the proposed controller was evaluated in comparison with traditional controllers. The proposed fuzzy logic controller makes it possible to increase the accuracy of the gas separation control system and reduce the duration of transient processes.
Keywords: fuzzy logic, controller, gas separation, membrane technology, nitrogen, control system
The article considers a method of automated formation of a training data set for machine learning algorithms for classification of electronic documents, which differs from the known ones by forming training data sets based on the synthesis of clustering and data augmentation methods based on calculating the distance between objects in multidimensional spaces.
Keywords: teaching with a teacher, clustering, pattern recognition, machine learning algorithm, electronic document, vectorization, formalized documents
The concept of a two-dimensional associative masking mechanism, introduced earlier and necessary for further consideration, is used to protect the data of cartographic scenes represented by point, linear and areal 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 in the alphabet of postal symbols and are masked with the further formation of stegocontainers. A set of masks is a secret key used further to recognize a scene represented in a protected form by a set of stegocontainers. The article deals with the organization of specialized DBMS for the protection of cartographic scene data with the introduction of two levels of such DBMS – server and client. Mono- and multicluster organization of request processing is offered for the server part of the DBMS. Practical recommendations on the use of mono- and multiclusters are given.
Keywords: associative steganography, masking, stegomessage, cartographic databases, parallel DBMS, mono- and multicluster, scene analysis, cryptography, stegostability, information security
The paper proposes a hybrid method of packet routing in a wireless sensor network based on a genetic algorithm that allows you to build a routing table taking into account restrictions on the maximum number of transmissions through each node of the network and, as a result, increase its energy efficiency. The results of experimental studies on BSS with a random configuration of nodes in space are presented and it is shown that the congestion of data packet relay nodes is reduced by 30-40% with an increase in the total length of routes by 10%.
Keywords: wireless sensor network, sensor node, coordinator node, network structure, packet routing, energy efficiency of a wireless network, network model
The aim of the work is to increase the productivity of the iron ore concentrate dehydration process. In the course of previous research, an automated system with individual control of each vacuum filter technological parameters was developed. In this paper, it is proposed to supplement this system of an extreme step regulator hybrid intelligent control unit. A structural and functional scheme and an algorithm for the functioning of the control system have also been developed. The implementation of the developed control system will improve the productivity of the vacuum filter, reduce the wear of the actuators, reduce the specific consumption of energy resources used, and save the financial resources of the enterprise. The proposed control system can be adapted for a large class of technological units of a similar principle of operation used in various industries.
Keywords: iron ore concentrate dehydration, disk vacuum filter, artificial neural network, fuzzy neural network, automated control system, individual regulation, extreme regulator, vacuum, pulp density, vacuum filter productivity sludge moisture
Currently, tracing the movements of various objects (in particular a person) occupies a central place in video surveillance and video analytics systems. It is a system for tracking people's movements by localizing their positions on each frame within the entire video stream and is the basis of many intellectual computer vision systems. The purpose of this article is to develop a new algorithm for tracing human movements in a video stream with the possibility of selecting motion trajectories. The main stages of the algorithm include: dividing the video into frames with a difference of one second, selecting the person under study in the video stream, implementing a digital processing process based on recognizing the clothes of the person under study and obtaining its color histogram, predicting localization and recognizing the person under study on all subsequent frames of the video stream using the developed methods of forecasting the direction of movement of this object. The output data of the proposed algorithm is used in the procedure of forming and displaying a general picture of the movement of a particular person within the entire video stream. The information and materials contained in this article may be of interest to specialists and experts who, in their work, pay special attention to data processing when analyzing fragments of the video stream.
Keywords: surveillance cameras, u2– net neural network, rembg library, pattern recognition, clothing recognition, delta E, tracing, direction prediction, object detection, tracking, mathematical statistics, predicted area, RGB pixels
Tests to determine the seismic stability of elements of pipeline systems, in particular pipeline fittings, are included in the list of those necessary to confirm the operability of the element. In this study, a stand was developed for testing to determine the seismic stability of butterfly check valves, which are a type of pipeline fittings. A finite element analysis was carried out, data on maximum deformations, stresses and displacements of structural elements were obtained, and the response of the installation table to seismic impact was calculated. The resulting displacement values of the table structure do not exceed the limit values specified by the technical requirements and do not lead to distortion of the structure or destruction of joints, which makes it possible to move from design to manufacturing and commissioning of the stand.
Keywords: vibration tests, seismic resistance test bench, pipeline, pipeline valves, swing back gate, mathematical modeling, finite element method, strength calculation, simulation modeling, stress-strain state
The effectiveness of the modified Fourier method associated with the use of orthogonal splines is shown when solving the problem of dynamics of a circular membrane with an elliptical hole. A posteriori estimates of the accuracy of the obtained approximate solutions complement the previously proven theoretical convergence of the algorithm and characterize the high accuracy of solutions to the problem of membrane dynamics with a curved boundary. The differences between the approximate solutions of the problem presented in the form of finite series decrease with an increase in the number of grid nodes used in calculations.
Keywords: Fourier method, orthogonal splines, finite series, dynamics of membrane, a posteriori estimation
The problem of reducing communication interaction in the chain between a natural language message and a BPMN model is considered. For this purpose, a number of authors have proposed a special notation called a mechanism. The procedure for constructing a mechanism using a given BPMN model is considered. The possibility of building a mechanism only for BPMN models that satisfy certain conditions is shown: the model must contain at least one artifact associated with one of the gateway actions; gateways should not contain more than two choices; the model should not end with a gateway; the model should not contain an AND-OR gateway. The procedure for constructing a BPMN model using a given mechanism is considered. The possibility of such a transformation is shown if the following conditions are met: the presence of a one-to-one correspondence of the elements and functions of the mechanism, the use of a single tool and a single strip in the mechanism. For models that do not satisfy these conditions, the use of the mechanism is problematic: it turns out to be either too cumbersome or too simple, which does not facilitate the simplification of communicative interaction. It is concluded that additional research is necessary in order to either improve the mechanism or use a different notation that does not have the disadvantages of the mechanism.
Keywords: BPMN, communication, business model, modeling, mechanisms, natural language, translation into BPMN
The development and implementation of decision support systems (DSS) based on modern methods of data processing, storage and analysis is an urgent task. As part of this work, an algorithm for optimizing the business processes of an IT company and a model for the functioning of a DSS were developed. The implementation of the proposed methods will improve the efficiency of IT companies.
Keywords: decision support system, business process, optimization, algorithm, IT company, data analysis, software, program code
In this experiment, a solver (NEAT) and a simulator (an inverted pendulum cart object) are implemented, where the solver will influence the object in order to keep it in a stable state, i.e. don't let the pendulum fall. The main objective of the experiment is to study the possibility of implementing a simulator of a real physical object and use it to determine the target function of the neuroevolutionary algorithm NEAT. Solving this problem will make it possible to implement controllers based on the NEAT algorithm, capable of controlling real physical objects.
Keywords: machine learning, non-revolutionary algorithms, genetic algorithms, neural networks
In this paper, a physics-informed neural network containing natural gradient descent is proposed to solve the boundary value problem of the Poisson equation. Machine learning methods used in solving partial differential equations are an alternative to the finite element method. Traditional numerical methods for solving differential equations are not capable of solving arbitrary problems of mathematical physics with equivalent efficiency, unlike machine learning methods. The loss function of the neural network is responsible for the accuracy of solving initial and boundary value problems of partial differential equations. The more efficiently the loss function is minimized, the more accurate the resulting solution is. The most traditional optimization algorithm is adaptive moment estimation, which is still used in deep learning today. However, this approach does not guarantee achieving a global minimum of the loss function. We propose to use natural gradient descent with the Dirichlet distribution which increase the accuracy of solving the Poisson equation.
Keywords: natural gradient descent, Poisson equation, Fisher matrix, finite element method, neural networks
The paper presents a new approach to assessing the level of contamination with heavy metals of the soil-like fraction from landfills using Monte Carlo simulation using the example of landfills located within the borders of Volgograd.It was found that with a probability of 36.2%, the contamination level of a soil-like fraction from the landfill located in the Voroshilovsky district will correspond to moderately hazardous, and with a probability of 63.8%, hazardous. It is economically justified to isolate a soil-like fraction with a low level of pollution to detoxify it and further use it in the territory reclamation. For a soil-like fraction from landfill located in the Traktorozavodsky district, the pollution level was determined as extremely hazardous and hazardous with a probability of 87.1% and 3.1%, respectively. It is shown that a useful and usable part cannot be isolated from a soil-like fraction. A soil-like fraction must be neutralized and placed at waste disposal facilities.The presented approach is a useful instrument for pollution level assessment of a soil-like fraction, which can increase the accuracy of an estimate and the management effectiveness of a soil-like fraction during landfill development.
Keywords: landfill, soil-like fraction, heavy metals, pollution level, Monte Carlo method, modeling
The relevance of the topic of the article is due to the fact that currently there is no linking of the calendar plan to the schedule for the development of capital investments. The principle of constructing a schedule for the development of capital investments is proposed, which ensures the uniformity and proportionality of the use of financial resources. Schedules for the development of capital investments are constructed, each schedule for the development of capital investments corresponds to an image describing the change in the absolute value of the profitability of the investment and construction project. The use of a mathematical apparatus describing the movement of a material point can be used in the development of investment schedules and calendar plans for construction. The construction of construction schedules in the section of the construction organization project based on investment schedules will have a significant impact on the economic efficiency of investment projects.
Keywords: construction schedule, investments, return on investment, development of capital investments, duration of construction, efficiency of capital investments
This work solves the problem of increasing the effectiveness of educational activities by predicting student performance based on external and internal factors. To solve this problem, a model for predicting student performance was built using the Python programming language. The initial data for building the decision tree model was taken from the UCI Machine Learning Repository platform and pre-processed using the Deductor Studio Academic analytical platform. The results of the model are presented and a study was conducted to evaluate the effectiveness of predicting student performance.
Keywords: forecasting, decision tree, student performance, influence of factors, effectiveness assessment