Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics
Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847
Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce
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Článekpeer-reviewedpostprint Omezený přístup Theorems for Boyd-Wong Contraction Mappings on Similarity Spaces(MDPI, 2023) Rozinek, Ondřej; Borkovcová, MonikaIn this article, we introduce novel fixed point results for Boyd-Wong-type contraction mappings within the framework of similarity spaces, which have broad practical applications. The development of these results extends the classical theory of Boyd-Wong contractions by exploiting the unique structure and properties of similarity spaces. We provide an in-depth examination of the derived contractions, establishing conditions under which fixed points exist and are unique. In the latter part of the paper, we illustrate the applicability and effectiveness of the proposed results with representative examples.Článekpeer-reviewedpostprint Omezený přístup Verification and estimation of uncertainties of Tobias Mayer's 18th century astronomical observations(Elsevier Science BV, 2023) Marek, Jaroslav; Tuček, JiříPerceiving the uncertainty of the measurement has been changing over the past centuries, reflecting the advancement in the experimental techniques, the urge for reliable and reproducible measurement methodology, and development of mathematical data processing and evaluating algorithms. From the historical perspective, the concepts of considering the measurement uncertainty were firstly introduced with geographic and cartographic measurements. In this context, the works of Tobias Mayer on lunar landscape measurements are widely highlighted which, at that time, presented innovative approaches in data processing with the method of averages and pioneeringly addressed the issue of measurement error. In this study, we analyze in details the Mayer's set of 27 non-linear equations with 3 unknown parameters and discuss the effect of Mayer's linearization and subsequent mathematical procedures on the accuracy of the parameter values in contrast with the results from rigorous treatment of non-linear regression model involving the least-square method. In particular, we compare the values of the unknown parameters and their uncertainties in several variants in the linearized and nonlinearized model, providing monitoring of a small deviation of the Mayer's linearization. The results, presented here, show that despite the conceptual and computational simplification of the Mayer's method, such an approach to data processing can be exploited, with an acceptable level of accuracy, in several practical situations even today.Článekpeer-reviewedpostprint Omezený přístup Survey of Point Cloud Registration Methods and New Statistical Approach(MDPI, 2023) Marek, Jaroslav; Chmelař, PavelThe use of a 3D range scanning device for autonomous object description or unknown environment mapping leads to the necessity of improving computer methods based on identical point pairs from different point clouds (so-called registration problem). The registration problem and three-dimensional transformation of coordinates still require further research. The paper attempts to guide the reader through the vast field of existing registration methods so that he can choose the appropriate approach for his particular problem. Furthermore, the article contains a regression method that enables the estimation of the covariance matrix of the transformation parameters and the calculation of the uncertainty of the estimated points. This makes it possible to extend existing registration methods with uncertainty estimates and to improve knowledge about the performed registration. The paper's primary purpose is to present a survey of known methods and basic estimation theory concepts for the point cloud registration problem. The focus will be on the guiding principles of the estimation theory: ICP algorithm; Normal Distribution Transform; Feature-based registration; Iterative dual correspondences; Probabilistic iterative correspondence method; Point-based registration; Quadratic patches; Likelihood-field matching; Conditional random fields; Branch-and-bound registration; PointReg. The secondary purpose of this article is to show an innovative statistical model for this transformation problem. The new theory needs known covariance matrices of identical point coordinates. An unknown rotation matrix and shift vector have been estimated using a nonlinear regression model with nonlinear constraints. The paper ends with a relevant numerical example.Článekpeer-reviewedpostprint Omezený přístup An Optimized Low-Power VLSI Architecture for ECG/VCG Data Compression for IoHT Wearable Device Application(IEEE (Institute of Electrical and Electronics Engineers), 2023) Janveja, Meenali; Sharma, Ashwani Kumar; Bhardwaj, Abhyuday; Pidanič, Jan; Trivedi, GauravContinuous monitoring of the electrical activity of heart signals using wearable Internet of Healthcare Things (IoHTs) devices plays a crucial role in decreasing mortality rates. However, this continuous monitoring using an electrocardiogram (ECG) or vectorcardiogram (VCG) generates huge clinical data. Moreover, these devices are constrained in terms of on-chip storage, data transmission capacity, and power. Thus, handling a large amount of data is difficult with these devices, making it necessary to compress these data for storage and transmission. Lossless or near-lossless data compression solves this problem, ensuring that no relevant physiological/clinical information is lost in the compression process. Therefore, low-power, resource-efficient, and lossless VLSI architectures are proposed in this article to compress multichannel ECG/VCG data. The designs are tested using the PTB database for both ECG and VCG data and can achieve compression ratios (CRs) of $3.857$ and $4.45$ with minimal power and area requirements making them suitable for low-power wearable healthcare devices.Článekpeer-reviewedpostprint Omezený přístup Road to Repair (R2R): An Afrocentric Sensor-Based Solution to Enhanced Road Maintenance(IEEE (Institute of Electrical and Electronics Engineers), 2023) Jordan, Darryn Anton; Paine, Stephen; Mishra, Amit Kumar; Pidanič, JanPotholes are one of the most important issues in African road-networks. They pose a major threat to mobility and, with time, cause accelerated degradation of the underlying road infrastructure as well as extensive vehicle damage. To address the need for improved infrastructure management, an advanced data gathering solution is required. This paper presents one such solution. The pothole detection, classification and logging (PDCL) system is under active development by Sensorit (Pty) Ltd in collaboration with the University of Cape Town (UCT) Radar Remote Sensing Group (RRSG). This system represents the initial step in Sensorit's modular approach to producing fully autonomous vehicles for African markets. In this paper, an overview of the PDCL system is presented and early results are shown. The efficacy of the system's unique combination of active infrared stereo vision and mmWave frequency-modulated continuous-wave (FMCW) radar sensors is explored. Under various experimental conditions, range-Doppler maps (RDMs) produced by the radar were unable to provide meaningful pothole detections. In contrast, processed depth maps produced by the stereo vision system are demonstrated to successfully detect even shallow potholes.Článekpeer-reviewedpostprint Omezený přístup The variable-inertia modified computed-torque control of robot manipulators(Springer, 2023) Cvejn, JanThis paper describes a modification of the computed-torque method of motion control of robot manipulators, which utilizes inner feedback to partially decouple the inertial effects of individual links, but at the same time it minimizes the influence of the inner feedback component of the control input. In this way, it is possible to increase the control efficiency for a given magnitude of the control signals, which are also more easily kept within saturation limits. It is shown that uniform asymptotical stability of the control error during reference trajectory tracking can be ensured by choosing sufficiently high controller gains, and that the region of attraction can be made arbitrarily large. For the situations when some robot model parameters are not known precisely, an adaptive extension of the algorithm preserving asymptotical stability of the control error is proposed.Článekpeer-reviewedpostprint Omezený přístup Automated Construction of Mesoscopic Railway Infrastructure Models Supporting Station Throat Capacity Assessment(2023) Veselý, Petr; Kavička, Antonín; Krýže, PavelAssessment of the traffic capacity of a rail infrastructure involved within railway stations is one of the basic components of the rail transport planning process. An important part of the rail infrastructure in the stations is station throat, which typically comprises many switches and track crossings. Station throat acts as operating bottleneck that frequently has the largest impact on the station’s traffic capacity. The capacity of a station throat is often conveniently assessed based on the use of mesoscopic computer simulation. This requires (among other things) a suitable submodel of the throat infrastructure to be set up. This article presents innovative algorithms for the automated creation of mesoscopic target model of station throat based on consecutive transformations of an initial (intuitive) microscopic model. Compared to the hitherto used manual process, the automated procedure accelerates the construction of the target station throat model and eliminates its structural errors. The applied research method is based both on the original design of the target mathematical model graph (a vertex-weighted directed graph) for the representation of the station throat infrastructure and on the design and verification of innovative graph algorithms that perform multiple aggregation transformations of this model in order to perform its maximum admissible topological simplification. The results of the research conducted have helped to enhance and efficiently use the station throat capacity assessment methodology. The use of the algorithms is demonstrated in a case study concerning station throats within a minor railway station in the Czech Republic.Článekpeer-reviewedpostprint Omezený přístup Analysis and modelling of single domain core-shell (?FeNi/chromite) nanoparticles emitted during selective laser melting, and their magnetic remanence(Elsevier Science, 2023) Dvorsky, Richard; Kukutschova, Jana; Pagac, Marek; Svoboda, Ladislav; Simonova, Zuzana; Dedlkova, Katerina Peterek; Bednar, Jiri; Mendes, Rafael Gregorio; Matysek, Dalibor; Malina, Ondrej; Tuček, Jiří; Vilamova, Zuzana; Kiselev, Sergei; Gemming, Thomas; Filip, PeterDespite recent intense implementation of increasingly eco-friendly additive manufacturing, the properties of nanoparticulate pollutants emitted during Laser Powder Bed Fusion are still not fully understood, and have generally been overlooked. This study aims to fill this gap in current research by providing new insights into distinct metal/oxide core-shell nanoparticles (3-36 nm) that are produced during 3D printing using stainless steel. It also suggests possible ways for the removal of these potentially harmful by-products. Further, this research also provides a newly developed kinetic model that predicts a metal core growth time of below 200 mu s and confirms the predicted theory for the formation of these by-products. In the current study it was found that the cores produced during this process are purely metallic and consist of meteoroid phase kamacite (alpha FeNi). Within this study there was found to be a complete dominance of single-domain cores of kamacite with pre-vailing particles below the superparamagnetic threshold showing strong magnetic response and remanence. This new knowledge can be used to minimize potential health risks and reduce contamination of raw materials by this nanoparticulate pollutant, which can adversely affect the quality of printed metal parts, the environment, and the health of the operator. These findings also provide a new possibility of targeted efficient production of super-paramagnetic core-shell nanoparticles with a metallic kamacite core during laser powder bed fusion of austenitic steel 316L powder, which can be used in the production of sensors.Článekpeer-reviewedpostprint Omezený přístup Genetic Algorithm-Based Task Assignment for Fleet of Unmanned Surface Vehicles in Dynamically Changing Environment(Taylor & Francis Inc, 2023) Dvořák, Miroslav; Doležel, Petr; Štursa, Dominik; Chouai, MohamedUnmanned vehicles are gaining the attention of professional operators and the general public. The implementation of unmanned vehicles is evident in, among other fields, emergency management, agriculture, traffic monitoring, post-disaster operations, and delivery of goods. Naturally, a group of unmanned vehicles can cooperatively complete operations more proficiently than a single vehicle. However, several issues must be resolved before a stable and reliable group of unmanned vehicles can be generally deployed to solve tasks in civil infrastructures and in industrial facilities. Here, a framework for the guidance of a fleet of unmanned surface vehicles is proposed. The framework utilizes several levels of control, namely Global Planning Level, Local Planning Level, and Low-Level Control. While the individual vehicles are completely autonomous in their operational locomotion and obstacle avoidance (low-level control and local planning), the task assignment for each vehicle (or group of them) is provided by a global planning process, based on the genetic algorithm. The framework provides a concept to solve complex tasks for the fleet of unmanned surface vehicles (USVs). This includes, but is not necessarily limited to, a dynamically changing environment, different types of USVs with special abilities, multiple types of areal restrictions and obstacles, different restrictions for individual USVs, cooperation of multiple USVs to solve their subtasks, energy consumption optimization, etc. The framework can be advantageously applied to tasks such as warehouse logistics, surface maintenance, area exploration, etc. At the end of the study, the application of the framework is presented using a simulated example of cooperative problem solving using six vehicles.Článekpeer-reviewedpostprint Omezený přístup Generalized first-principle model of magnetic levitation(2023) Dušek, František; Tuček, Jiří; Novotný, Aleš; Honc, DanielSince its first demonstration more than a half century ago, magnetic levitation (MagLev) has gained eminent scientific attention from both the fundamental and applied points of view. In essence, MagLev shows highly nonlinear dynamics, described with nonlinear differential equations. Thus, in order to exploit the MagLev phenomenon, both mathematical models and control algorithms must be constructed. Frequently authors use simplifications of the model, and in doing so, limit the application of the MagLev model around a nominal operating point. In these simplified cases, the MagLev models may contain parameters that are not represented by proper physical quantities. Thus, in this work, we revised the issue of MagLev modelling from the first-principle approach. More specifically, we theoretically derived expressions for the interaction between the magnetic fields of the solenoid and a small magnetic object. The behaviour of the inductance on a distance from the solenoid was then described. The suggested MagLev modelling concept was verified experimentally, confirming the validity and correctness of the proposed MagLev mathematical model. The results presented here could thus be regarded as highly beneficial for formulating more complex MagLev designs exploitable in the field of model predictive control of the position of a levitating object.