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PL
Publikacja koncentruje się na modelowaniu i symulacji systemu nadawczo-odbiorczego wykorzystującego technikę OFDM (Orthogonal Frequency-Division Multiplexing) oraz algorytmu kodowania korekcyjnego zaimplementowanego w środowisku MATLAB/Simulink. Projekt opiera się na standardzie ETSI (Eu-Eu ropean Telecommunications Standards Institute) EN (European Standard) 300 401 v. 2.1.1 dla systemów DAB/DAB+ (Digital Audio Broqadcasting/ Digital Audio Broqadcasting Plus) i bazuje na zestawie modeli kanałów radiokomunikacyjnych imitujących warunki polowe, aby symulować realne środowisko operacyjne. Kluczowe badania skupiały się na analizie Bitowej Stopy Błędu (BER), która pozwoliła ocenić jakość transmisji radiowej. W pracy zaproponowano również kierunki przyszłych badań, w tym implementację FEC (Forward Error Correction), wykonanie testów subiektywnych i adaptację systemu do platformy SDR (Software Defined Radio), co ma na celu dalsze zwiększenie jego efektywności operacyjnej.
EN
This publication focuses on the modeling and simulation of a transmitter-receiver system utilizing Orthogonal Frequency Division Multiplexing (OFDM) techniques and corrective coding algorithms, implemented within the MATLAB/Simulink environment. The project adheres to the ETSI EN 300 401 v. 2.1.1 standard for DAB/DAB+ systems and employs channel models that mimic field conditions to simulate a realistic operational environment. Key studies concentrated on the analysis of the Bit Error Rate (BER), which assessed the quality of the radio transmission. The paper also proposes directions for future research, including the implementation of Forward Error Correction (FEC), conducting subjective tests, and adapting the system to a Software Defined Radio (SDR) platform, aimed at further enhancing its operational efficiency.
EN
The work concerns the selection of the programming language and environment for the needs of neural modeling of the power and electricity demand generation system in terms of uninhabited factories. Therefore, the main goal of the conducted research is to obtain the best possible Artificial Neural Network, i.e. to teach it a model of a real system, which is a system for generating demand for power and electricity based on numerical data on parts of the power system operation in terms of uninhabited factories. The learning capabilities of artificial neural networks were checked by comparing the MSE error and the Regression Index R2. In each of the examined programming languages and related programming environments, i.e. Matlab, Python and Wolfram, an Artificial Neural Network with the same structure and properties was designed and implemented, i.e. with the same number of input and output neurons, the number of hidden layers and the number of neurons in them, the activation function of neurons and the learning method. In addition to the ANN training of the system model, testing and validation as well as comparative studies were carried out.
EN
The article contains an analysis leading to the selection of an algorithm for classifying data listed on the Day-Ahead Market of TGE S.A. in MATLAB and Simulink using Deep Learning Toolbox. In this regard, an introduction to deep learning methods, classification methods, and classification algorithms is provided first. Particular attention was paid to the essence of three important deep learning methods in the classification, i.e. the methods called: Stochastic Gradient Descent Momentum, Root Mean Square Prop and Adaptive Moment Estimation. Then, three architectures of artificial neural networks used in deep learning were characterized, i.e.: Deep Belief Network, Convolutional Neural Network and Recurrent Neural Network. Attention was paid to the selection parameters of algorithms for learning deep artificial neural networks that can be used in classification, such as: accuracy, information losses and learning time. Practical aspects of research experiments were also shown, including selected results of research conducted on volume and fixing 1 data quoted on the TGE S.A. Day-Ahead Market. After analyzing the obtained test results for the hourly system, it was noted that the least suitable algorithm for classification purposes was the Stochastic Gradient Descent Momentum algorithm, which in each case had worse results than the other two algorithms, i.e. the Adaptive Moment Estimation algorithm and the Root Mean algorithm Square Prop. However, the best algorithm turned out to be the Adaptive Moment Estimation algorithm, which obtained the highest accuracy, which was at a level comparable to the Root Mean Square Prop algorithm, with the latter algorithm having larger losses.
EN
The main purpose of the research was to examine the properties of models for two kinds of neural networks, a deep learning models in which the Long Short-Term Memory was chosen and shallow neural model in which the Perceptron Neural Network was chosen. The subject of the examination was the Day-Ahead Market system of PPE S.A. The article presents the learning results of both networks and the results of the predictive abilities of the models. The research was conducted based on data published on the Polish Stock Exchange for the 2018 year. The MATLAB environment was chosen as a tool for providing the examinations. The determination index (R2) and the mean square error (MSE) was adopted as the network evaluation criterion for the learning ability and for the prediction ability of both networks.
EN
The article contains selected results of comparative research on the quality of the parametric model, corrected in selected situations with the use of ANN and the Day-Ahead Market system of TGE S.A. carried out in MATLAB and Simulink. The System Identification Toolbox library was used for identification tests and Simulink for simulation and comparative tests. The comparative studies used such measures of model and system quality as: efficiency, effectiveness and robustness. Their waveforms as well as their average values and absolute errors and relative errors between the identification model or the identification-neural model and the system were obtained. The results of general tests were shown for the hours: 6:00, 12:00, 18:00 and 24:00 in 2019, and the detailed tests for 6:00. The sensitivity of the waveforms obtained in terms of model quality and the Day-Ahead Market system was also tested, depending on the assumed values of such parameters as e.g. electricity volume or volume-weighted average price of electricity.
EN
An analysis of the web application supporting the management of the gym was carried out, which was designed in terms of the theory of control and systems. The obtained results of measurements of input and output quantities of selected subsystems were used to carry out the identification, as a result of which models of web application subsystems were obtained. On the basis of the obtained subsystem models, appropriate models were then designed in Simulink for the purposes of simulation and comparative studies of the behavior of subsystem models in relation to real systems that are web applications, including an appropriate analysis of the web application system model was carried out under the name of the gym on its selected subsystems, including in particular the subsystem called Generating a diet. In addition, testing and simulation studies were carried out to check the correct functioning of the web application management system model and the introduction of appropriate changes to the model was proposed, and the obtained research results were discussed, indicating the high accuracy of the obtained web application models.
EN
A beam scanner based on electrowetting with controllable field of view is designed. Depending on the first-order paraxial approximation, the scanning path and scanning radius of the beam scanner are derived. Its physical model and properties are established and analyzed with the help of by using the COMSOL and MATLAB. The results show that the scanning beam emitting from the beam scanner realizes 360° scanning freely, and its controllable field of view varies from 0 to 65.3 m successfully under the action of working voltage. The two liquid interfaces in the beam scanner can rotate clockwise or counterclockwise independently, and their inclination angle ranges from 0° to 45°. When the two liquid interfaces turn in the same direction, the scanning effect of edge field is better than that of the central zone. While the scanning effect of the central area is greatly improved and better than that of the edge field when the two liquid interfaces turn in the different direction. In addition, the rotation frequencies of the two interfaces affect the performance of the beam scanner.
PL
Sztuczne sieci neuronowe stanowią jedną z najszybciej rozwijających się metod przetwarzania danych. W diagnostyce obrazowej znajdują one zastosowania do analiz obrazów uzyskiwanych w różnych systemach diagnostycznych. Rezonans magnetyczny wydaje się być najbardziej obiecującym źródłem danych ze względu na różnorodność uzyskiwanych obrazów. W niniejszej pracy została zaprezentowania metoda analizy i segmentacji obrazu na podstawie kształtu funkcji opisującej zależności intensywności sygnału od czasów repetycji (TR) oraz czasu echa (TE). W pierwszym przypadku krzywa opisywała zmienność sygnału dla określania czasu relaksacji podłużnej (T1), natomiast w drugim krzywa odpowiadała relaksacji poprzecznej (T2). W pierwszej części pracy zaprezentowano wyniki analizy obrazu fantomu składającego się z trzech probówek zawierających różne wodne roztwory CuSO4. Druga część to próba zastosowania metody do badania wycinków tkanek nowotworowych prostaty. Do analiz wykorzystano pakiet programowy MATLAB (prod. The MathWorks). Zaimplementowano w nim zarówno odczyt danych bezpośrednio z plików DICOM, jak również zaproponowaną sieć neuronową. Za wykorzystaniem tegoż oprogramowania przemawiały ogromne możliwości pakietu, jak również względna łatwość implementacji kodu. We wnioskach zapisano, iż zaproponowana sieć neuronowa w sposób zadowalający dokonała segmentacji obrazu. Zastosowanie sieci neuronowej wydatnie skróciło obliczenia z uwagi na pominięcie pikseli obrazujących przestrzenie upowietrznione. Ograniczeniu uległy również elementy obrazu prezentujące całkowicie zafałszowane wartości czasów relaksacji, a więc artefakty.
EN
Artificial neural networks are one of the fastest growing image processing methods. In diagnostic imaging, they are finding applications for analyzing images obtained by various diagnostic systems. Magnetic resonance imaging (MRI) seems to be the most promising source of data - images due to the variety of images obtained. This paper presents a method of image analysis and segmentation based on the shape of a function describing the dependence of signal intensity on repetition times (TR) and echo times (TE). In the first case, the curve described the signal variation for determining the longitudinal relaxation time (T1), while in the second case the curve corresponded to transverse relaxation (T2). The first part of the paper presents the results of image analysis of a phantom consisting of three test tubes containing different aqueous CuSO4 solutions. The second part is an attempt to apply the method to the examination of prostate cancer tissue ex vivo. The MATLAB software package by The MathWorks was used for the analyses. It implemented both the reading of data directly from DICOM files and the proposed neural network. The huge capabilities of the package as well as the relative ease of code implementation were in favor of using the software. In conclusion, it should be said that the proposed neural network satisfactorily performed image segmentation. The use of the neural network significantly shortened the calculations due to the omission of pixels depicting aerated spaces. Also reduced were the image elements presenting completely falsified values of relaxation times and thus artifacts.
EN
Industrial high-speed rotating machines entail constant and consistent monitoring to prevent downtime, affecting quantity and quality. Complex machines need advanced intelligent fault diagnosis showing minimal errors. This work offers a MATLAB-based fault diagnosis for sugar industry machines. The vibration behavior of physical industrial machines is obtained, and the signals are provided to a MATLAB program to identify the fault. The information helps to suggest remedies to include in the maintenance schedule. The ease and comprehensible nature of the method reduce time and enhance the reliability of condition monitoring for industrial machines.
EN
The self-adaptive population Rao algorithms (SAP-Rao) are employed in this study to produce the optimal designs for steel grillage structures. The size variables in the optimization problem consist of the cross-sectional area of the discrete W-shapes of these beams. The LRFD-AISC design code was used to optimize the constrained size of this kind of structure. The solved problem’s primary goal is to determine the grillage structure’s minimum weight. As constraints, it is decided to use the maximum stress ratio and the maximum displacement at the inner point of the steel grillage structure. The finite element method (FEM) was employed to compute the moment and shear force of each member, as well as the joint displacement. A computer program for the study and design of grillage structures, as well as the optimization technique for SAP-Rao, was created in MATLAB. The outcomes of this study are compared to earlier efforts on grillage structures. The findings demonstrate that the optimal design of grillage structures can be successfully accomplished using the SAP-Rao method described in this paper.
EN
The article proposes an adaptive algorithm that generates all object signals, including those for which measurements are not performed due to the difficulties associated with on-line measurements. The algorithm is modeled on the idea of the Kalman filter using its equation, however, the selection of gains is optimized in a different way, i.e. the constant values depend on the adopted ranges of adaptation errors. Moreover, the knowledge of the statistics of all noise signals is not imposed and there is no linearity constraint. This approach allowed to reduce the complexity of calculations. This algorithm can be used in real-time systems to generate signals of objects described by non-linear differential equations and it is universal, which allows it to be used for various objects. In the conducted research, on the example of a biochemically contaminated river, only easily measurable signals were used to generated the object signals, and in addition, in the case of absence some measurements, the functioning of the algorithm did not destabilize.
EN
Progress in the industry is accompanied by the development of new materials and more efficient technological production processes. At present, additive production is becoming very attractive in all industries (research, development, production), which brings a number of advantages compared to subtractive methods (customization, production speed, control of material properties by users, etc.). The main advantage of 3D printing is the controlled deposition of material in defined places. Instead of demanding manual labour, fully automated production via computers leads to the manufacturing of complex components from materials whose production in conventional ways would be problematic or even impossible. Because these are new technologies, the main direction of research at present is to identify the basic physical properties of these materials under different types of loading. The main goal of this article is to observe the dependence of the behaviour of the extruded material (thermoplastic reinforced with chopped carbon fibre) on the printing parameters (thickness of the lamina, the orientation of the fibres of the printed material, etc.). Based on published scientific works, it appears that these settings have a significant impact on the achieved physical properties. This is the reason why the authors decided to analyze the influence of these parameters on the basis of processed data from experimental measurements of mechanical properties in the MATLAB program. As this is FFF printing, an essential condition is to identify and specify the directional dependence of the behavior of the printed material. This physical phenomenon is a necessary condition for gradual knowledge for the purposes of a subsequent mathematical description of the material properties. According to the authors, for the purposes of modeling these materials in FEM-based programs, it is essential to define the directional dependence in the plane of the lamina.
EN
Many particle accelerators rely on maintaining low pressures to ensure efficient operation, minimize beam losses, and reduce radiation background. To ensure a beam lifetime of 1–20 hours for the Synchrotron-light for Experimental Science and Applications in the Middle East (SESAME) vacuum system, an ideal average dynamic pressure of 1×10-9 mbar was targeted. This pressure was intended to be maintained while running the accelerator at a current of 400 mA after a cumulative dose of 100 Ah. In this study, a MATLAB code was employed to develop a series of one-dimensional equations that simulate the behavior of the vacuum system within the SESAME storage ring. The proposed model was then compared with the results generated by the VACCALC software and the Particle Monte Carlo (TPMC) MOLFLOW code, establishing a comprehensive assessment framework. The collected data from the model was subsequently compared with the recorded static and dynamic pressure measurements obtained during more than 1000 Ah of beam conditioning at 2.5 GeV. In results, the projected and actual values of dynamic pressures exhibited a satisfactory degree of agreement across the investigated range of beam conditioning doses, with a consistency factor exceeding 2 after a 100 Ah dose.
EN
In this study, a functional diagram for an automatic sliding mode control system for a three-phase bridge buck current converter was developed. To achieve this, a simulation program was created in MATLAB/Simulink which analyzed the dynamic performance of the developed automatic control system, operating in the active rectifier and network current inverter modes. The results present the mathematical modeling outputs, along with the analyzed control algorithm and the automatic control system of the buck current converter evaluated.
EN
This article, which is a continuation of the article under the same main title and subtitle: part 1 Design and its implementation, includes the obtained results of research experiments with the use of a designed and implemented racing game. It uses a neural model of the vehicle motion control system on the racetrack in the form of a Perceptron Artificial Neural Network (ANN). In designing the movement of vehicles on the racetrack, the following were used, inter alia, Godot Engine and MATLAB and Simulink programming environment. The numerical data (14 input quantities and two output quantities) for ANN training were prepared with the use of semi-automatic measurement of the race track control points. This article shows, among others, the results of 10 selected research experiments, testing and simulation, confirming the correct functioning of both the computer game and the model of the neural control system. As a result of simulation tests, it turned out that the longest lap of the track in the conducted experiments lasted 4 minutes and 55 seconds, and the shortest - 10.47 seconds. In five minutes, the highest number of laps was 34, while the lowest numbers of laps were 1 and 5. In the course of the experiments it was noticed that under the same conditions the ANN learning outcomes are sometimes different.
EN
The publication consist of two parts. Part 1 contains the results of research on the design, learning and implementation of the Perceptron Artificial Neural Network as a model of neural control of car movement on the racetrack. This part 1 presents the results of studies, including review of the methods used in video racing games from the point of view of the selection of a method that can be used in the own research experiment, selection of the Artificial Neural Network architecture, its teaching method and parameters for the intended research experiment, selection of the data measurement method to be used in ANN training, as well as development design of a car game, its implementation and conducting simulation tests. In designing the game of vehicle traffic on the racetrack, among others, Godot Engine game engine and MATLAB and Simulink programming environment. The numerical data (14 input quantities and two output quantities) for ANN training were prepared with the use of semi-automatic measurement of the race track control points. Part 2 shows i.a. the results of the testing and simulation experiments that confirm the correct functioning of both the game and the model of the neural control system. There were also shown, among others, the possibility of continuing research in the field of increasing the flexibility of the racing game, in particular the flexibility of the vehicle traffic control system through the use of other artificial intelligence methods, such as ant algorithms or evolutionary algorithms.
EN
The purpose of this article is to provide an understanding of possible techniques through which a H1 31.25 kbps Foundation Fieldbus Manchester coded signal can be modulated or demodulated. This understanding will be rendered through MATLAB and SIMULINK models, simulating both ideal and practical as well as noiseless and noisy conditions during the modulation/demodulation process. The simulation models will differentiate between the modulation methods adopted to generate ideal rectangular as well as practical trapezoidal waveforms for the Manchester coded signal. The analysis of the simulation results will describe the mechanisms through which distortion induced by additive white Gaussian noise can be eliminated during the demodulation process either by using recursive filters, such as a Kalman filter, or by calculating wave energy levels in specific time intervals.
EN
An article herein considers the development of a fiber-optic sensor system, based on fiber Bragg gratings. Presently, fiber-optic sensors has become world-widely known amongst sensor technologies, used for monitoring engineering and construction structures. The work is linked with developing the system from fiber-optic sensors on the basis of fiber optic gratings, its characteristics, deformation behavior and temperature, acting at fiber Bragg grating by means of computer modeling. The research is focused at the analysis of characteristics and deformation and temperature behavior of fiber-optic Bragg sensor. Fiber-optic Bragg sensor with tilted grating is used for measuring deformation of the object, the strength of which is changed, dependent on the applied force, as well, for measuring and detecting any temperature deviations, influencing at fiber Bragg grating, which might bring to fire and accidents. In the research, simulation modeling there was made in the MATLAB (Simulink) software.
PL
W artykule opisano modelowanie w programie MATLAB procesu z wykorzystaniem wirtualnych modeli odwzorowujących rzeczywiste elementy turbozespołu. Analizie poddano model turbiny składający się z czterech submodeli, które mogą pracować niezależnie od siebie. Są to modele części WP, SP, NP oraz model skraplacza pary. Analizę procesu przeprowadzono symulując pracę bloku energetycznego przy obniżonym minimum (129-90 MW). Za pomocą wirtualnych modeli można określić sprawność danej części turbiny oraz moc jaką generuje. Przedstawiono przykładowe kierunki dalszego rozwoju modelowania w programie MATLAB w tym możliwość integracji z modelami termo-mechanicznymi wykonanymi w programie ANSYS.
EN
The article describes process modeling based on virtual models representing real elements of turbo-generator set. The turbine model analyzed consist of four submodels (HP, IP LP and steam condenser), which can work separately of themselves. Process analyze was performed to simulate power unii operation at reduced technical minimum (129-90 MW). Virtual models can define the efficiency of the given turbine part and the power which it generates. The simulation was performed using MATLAB software. In summary, the exemplary directions for further development of modeling in MATLAB, including the possibility of integration with thermo-mechanical models made in ANSYS software are shown.
PL
W artykule dokonano pomiaru rozkładu wielkości cząstek próbek bentonitowych, pochodzących z firmy Certech znajdującej się w Niedomicach koło Tarnowa. Próbkami były: bentonit, granulat oraz żwirki shaggy, kukurydziany oraz zapachowy. Analizę granulometryczną wykonano z wykorzystaniem skryptu napisanego w środowisku programu MATLAB. Przed wykonaniem analizy wykorzystując smartphone wykonano fotografie próbek. Skrypt po wgraniu zdjęcia poszczególnych próbek dokonuje analizy rozkładu cząstek. Pomiar rozkładu granulometrycznego badanej próbki dostarcza kluczowych informacji na temat jej budowy, a także pozwala na efektywniejsze dobranie metodyki dalszych badań. Wykonanie pomiaru opisanego w poniższym artykule pozwoliło na ocenę przydatności opisanej metody do badań rozkładu ziarnowego materiałów, jak również ocenę możliwości wykorzystania smartphone’ów do badań materiałów.
EN
The article measures the particle size distribution of bentonite samples from Certech, located in Niedomice near Tarnów. The samples were: bentonite, granules and shaggy, corn and scented cat litter. The granulometric analysis was performed using script written in the MATLAB. Before the analysis, photographs of the samples were taken using a smartphone. The MATLAB script, after uploading the samples’ photos, performs the particle distribution analysis. Measuring the granulometric distribution of the sample under study provides key information about the sample's structure and also allows for a more effective selection of the methodology of further research. The performance of the measurement described in the following article made it possible to assess the suitability of the described method for studying the grain distribution of materials as well as to evaluate the possibility of using smartphones for materials testing.
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