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Comparative Analysis of Gaussian Process Regression Modeling of an Induction Machine: Continuous vs. Mixed-Input Approaches
Bílek, Vladimír
This paper investigates the application of machine learning technique for modeling continuous and mixed-input parameters of electrical machines. The design of electrical machines typically requires the consideration of certain parameters as integer values due to their physical significance, including the number of stator/rotor slots, stator wires, and rotor bars. Traditional machine learning methods, which predominantly treat input parameters as purely continuous, may compromise modeling accuracy for such applications. To address this challenge, models capable of handling mixed-input parameters were used for the case study. Two training datasets were generated: one with purely continuous inputs and another with both continuous inputs and a categorical parameter, specifically, the number of stator conductors. Gaussian process regression was employed to build three models: two with continuous kernels, trained on both datasets, and one with a mixed kernel, trained only on the dataset containing a categorical parameter. A comparative analysis, demonstrated on a 1.5 kW induction machine - though applicable to a wide range of machines - illustrates the differences between the proposed approaches. The results highlight the importance of selecting an appropriate model for the Multi- Objective Bayesian optimization of electrical machines.
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Modelling of Magnetic Films: A Scientific Perspectives
Misiurev, Denis ; Vladimír, Holcman
Modeling magnetic thin films represents a dynamic intersection of scientific inquiry and technological progress, at the forefront of materials science exploration. Researchers use various computational methods, such as Monte Carlo simulations and molecular dynamics, to understand magnetism and thin-film growth on different surfaces. Recent advancements in multiscale modeling and machine learning have improved predictive abilities, leading to a better understanding of thin-film dynamics over different spatial and temporal scales. This interdisciplinary approach, coupled with advanced experimental techniques like in situ microscopy, promises significant advancements in magnetic materials. These advancements have wide-ranging implications in areas such as magnetic data storage, spintronics, and magnetic sensors. The integration of computational modeling and experimental validation marks a new era of scientific rigor, providing deep insights into the real-time behavior of magnetic films and enhancing the accuracy of predictive models. As researchers navigate unexplored territory, the field of magnetic thin-film modeling holds great promise for unlocking new possibilities in materials science and engineering. Through a combination of theoretical exploration and empirical validation, magnetic thin-film modeling is poised to drive innovation and revolutionize various industries in the future.
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Localization Accuracy of Autonomous Mobile Robots: A Comprehensive Evaluation of KISS-ICP Odometry
Cihlář, Miloš
This paper emphasizes the importance of accurate localization for the appropriate behavior of autonomous mobile robots. In particular, it provides a rigorous evaluation of the accuracy of the KISS-ICP algorithm, a lightweight lidar-based pose estimation algorithm known for its simplicity with minimal setup parameters. The algorithm works only with lidar data; unlike other more sophisticated SLAM algorithms, it does not use IMUs. The algorithm is shown to work under a variety of conditions and sensors. To comprehensively evaluate how the algorithm performs under varying conditions, several sensors were used in the experiments. The evaluation included a series of 3D lidars, namely Ouster OS0, OS1, and OS2. These lidars are characterized by different field-of-view settings and operating modes with different point per row. In order to facilitate this evaluation, a data set with extensive robot traversals over a distance of more than 9 km in two different environments, each equipped with different sensor types, was prepared.
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Perceptual Omnidirectional Image Quality: Subjective Ratings by Diverse User Aspects
Šimka, Marek ; Polak, Ladislav
This paper deals with an unconventional experiment of subjective quality assessment of omnidirectional images. Within the subjective tests with 36 volunteers, the study was carried out in terms of different aspects of each user. Based on the assessments of 100 images by each respondent, it offers a new source of results for further investigation and development of virtual reality (VR) content or quality of experience (QoE). It focuses on the subjective ratings of various types of users such as people using dioptric glasses, with VR experience, or users with vision impairments. The output is thus the results of the subjective scores, including an analysis of their correlations with several objective quality metrics. The initial results of this work suggest that, for example, subjects with corrected vision using dioptric glasses exhibit similar subjective perceptions of the quality of omnidirectional images as average respondents without visual impairment.
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Application of Auditory Masking based Speech Denoising in Automotive Environments
Malucha, Jan
This paper presents an application experiment of denoising speech in the automotive field. An algorithm based on the auditory masking phenomenon was programmed and deployed for this purpose. Synthetic composite recordings of speech and vehice interior noise were used for three types of vehicles equipped with internal combustion engines - truck, jeep and sports car. The final results after denoising process are evaluated by four speech quality metrics. The trend of quality improvement depending on the SNR of the input noisy signal is examined. A possibility of using denoised speech signals for further speech features analysis is briefly discussed.
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A Humanoid Robot on the Basis of Modules Controlled Through a Serial Half-duplex UART Bus
Matoušek, Sebastian ; Maršálek, Roman
Just a few decades ago the concept of humanoid robots assisting us at work would be something better suited for a movie plot than as a business plan. However, nowadays tests of such robots are already being performed, with big companies exploring the possibilities of such robots assisting in warehouses, robotic assistants roaming around airports directing lost passengers and more. In the future, such robots could very well be employed in many more areas of work – thanks to their construction being similar to humans, they integrate well into our everyday environment and make cooperation more intuitive. This thesis is the result of an attempt at building a small-scale humanoid robot. It expands upon the thesis ”Bipedal Walking Robot” [1] from last year, which described the process of building a two-legged robot capable of walking, at that time still lacking arms and a head, however. This thesis focuses on the expansion of the robot, mainly the addition of the upper limbs and a head missing in the previous project, thus finally creating a humanoid robot. Furthermore, a custom ecosystem of modules on the basis of the ESP32-C3FH4 microcontroller is discussed; communicating through a serial half-duplex UART bus, these modules were used to construct the upper body, smoothen the movement of the robot, and collect additional data about the robots movement. Such modules can be further used in other projects requiring the usage of numerous interconnected, yet independent, electronics parts.
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Innovative Control Systém for Water Supply Management at a Farm
Doležal, Aleš
The thesis deals with the implementation of an innovative control system for the management and supply of water to the farm. The innovation focuses on all areas of the control system such as hardware part as well as software part. In the hardware part, it is mainly about the communication between the PLC and the pumps in the boreholes Where contact switching has been replaced by fiber optic communication. Furthermore, the non-compliant components were replaced by components that are more suitable for this placation. In the software area, tools have been used to simplify both the programming and the actual operation of the control system. The use of structures, the use of equations, and, more efficient sampling of measured data. A PLC from Unitronics was selected to control the entire application. The program for the PLC was written in the UniLogic programming environment from Unitronics.
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Android Tracking Application Based on LTE Timing Advance
Michálek, Jakub
This article introduces a novel Android application developed in the Kotlin programming language, which enables users to tracking the location of their devices through the implementation of a custom algorithm. The focal point of this innovation lies in leveraging the Timing Advance parameter derived from the Long-Term Evolution (LTE) network to ascertain the most optimal track for location tracking. The technical overview describes the technologies used, while the tracking application chapter offers a detailed look at the architecture and implementation details. Special emphasis is placed on the use of Timing Advance and its role in the position tracking algorithm. The testing results confirm the efficiency and accuracy of the proposed solution. The article further deals with possible problems and proposed future extensions of the application. This work provides a comprehensive view of an innovative approach to location tracking in mobile devices.
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Lattice-based Threshold Signature Optimization for RAM Constrained Devices
Shapoval, Vladyslav ; Ricci, Sara
The DS2 scheme is a lattice-based (n, n)-threshold signature based on the standardized Dilithium signature. However, deploying DS2, as well as Dilithium, on microcontrollers is a challenge due to the memory limitations of these devices. While the decryption phase can be implemented relatively straightforwardly, the key generation and signing phases require the generation and manipulation of large matrices and vectors, which can quickly exhaust the available memory on the microcontroller. In this paper, we propose an optimization of the DS2 key generation and signing algorithms tailored for microcontrollers. Our approach focuses on minimizing memory consumption by generating large elements, such as the commitment key ck and the random commitment parameter r, on the fly from random and non-random seeds. This approach significantly reduces the overall size of the signature from 143 KB to less than 5 KB, depending on the number of signers involved. We also split the algorithms into two distinct components: a security-critical part and a non-security-critical part. The security-critical part contains operations that require secret knowledge and must be run on the microcontroller itself. Conversely, the non-critical part contains operations that do not require secret knowledge and can be performed on a connected, more powerful central host.
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Navigation of UAV in GNSS denied area
Pintér, Marco ; Marcoň, Petr
This paper examines the concept of navigation of of Unmanned aerial vehicle (UAV) in three-dimensional space using visual odometry. In the near future navigation of the UAV without GNSS is becoming a critical part of autonomous navigation systems, using information from on-board cameras to estimate the UAV’s movement and position. In the paper, different types of visual odometry, sensors for visual odometry, components of the implementation, and scenarios of usage. For the development and future application we utilize widely used Robotic Operating System (ROS).
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