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23rd International Conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Kotowski, Krzysztof Andrzejewski, Jacek Musial, Alicja Evans, David Zelenevskiy, Vladimir Bammens, Sam Laurinovics, Rodrigo Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland European Space Agency/ESOC Robert-Bosch-Str. 5 Darmstadt64293 Germany Telespazio Germany GmbH Europaplatz 5 Darmstadt64293 Germany IrbGS ltd "Viraki" Ance Parish IrbeneLV-3601 Latvia

ISBN: (纸本)9783031359941

Detecting anomalies in satellite telemetry data is pivotal in ensuring its safe operations. Although there exist various data-driven techniques for the task of determining abnormal parts of the signal, they are virtually never validated over real telemetries. Analyzing such data is challenging due to its intrinsic characteristics, as telemetry may be noisy and affected by incorrect acquisition, resulting in missing parts of the signal. In this paper, we tackle this issue and propose a machine learning approach for detecting anomalies in single-channel satellite telemetry. To validate its capabilities in a practical scenario, we build a dataset capturing the nominal and anomalous telemetry data captured on board OPS-SAT—a nanosatellite launched and operated by the European Space Agency. Our extensive experimental study showed that the proposed algorithm offers high-quality anomaly detection in real-life satellite telemetry, reaching 98.4% accuracy over the unseen test set. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Cooperative adaptive cruise control with string stability based on DMPC for vehicle platooning 27

Cooperative adaptive cruise control with string stability ba...

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27th International Conference on System Theory, control and Computing, ICSTCC 2023

作者： Pauca, Ovidiu Lazar, Mircea Caruntu, Constantin F. Dept. of Automatic Control and Applied Informatics Gheorghe Asachi" Technical University of Iasi Iasi Romania Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798350337983

The cooperative adaptive cruise control (CACC) functionality received significant interest in the state-of-the-art due to its advantages in optimizing traffic flow. The model-based predictive control (MPC) strategy was used in various studies due to its advantages in improving the performance of the vehicles (reducing the travel costs, improving the quality of the travel by reducing sudden accelerations, and ensuring the stability of the platoons). Moreover, MPC solutions are built to maximize the advantages of vehicular communication by sharing predictions on states of vehicles (e.g., velocities, accelerations, trajectories). In addition, MPC is also used to compensate for the disturbances added by communications. Thus, this paper proposes a CACC strategy for a vehicle platoon. The solution is based on the distributed MPC (DMPC) strategy, and the controller is proposed in discrete time, ensuring predecessor-follower string stability for the whole platoon. © 2023 IEEE.

关键词： Vehicles

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A Markov Model for a Self-Powered Green IoT Device with State-Dependent Energy Consumption

A Markov Model for a Self-Powered Green IoT Device with Stat...

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2023 IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2023

作者： Kuaban, Godlove Suila Czachorski, Tadeusz Gelenbe, Erol Sharma, Sapana Czekalski, Piotr Gliwice Poland Mmec Maharishi Markandeshwar Department of Mathematics Haryana Mullana133203 India Silesian University of Technology Faculty of Automatic Control Electronics and Informatics Gliwice Poland

ISBN: (纸本)9798350336917

The growing concerns about the resource sustainability and environmental impact of deploying billions or trillions of IoT devices in the various sectors of society or economy have given rise to an energy research field known as Green-IoT (G-IoT). G-IoT emphasises the need to prioritise energy efficiency and the reduction of pollution in the IoT ecosystem. This paper presents a Markov model for a self-powered Green IoT device with state-dependent energy consumption. The model evaluates the energy performance of a self-powered Green IoT device. We derive the probability distribution of the energy content of the battery, including the probability that the energy stored in the battery is completely depleted and the density of the lifetime of the IoT device. We investigate the influence of some design parameters on the results. Introducing the threshold at which the device is forced to enter an energy-saving regime significantly increases a G-IoT device's lifetime. Apart from deploying energy-efficient mechanisms to increase the lifetime of a G-IoT device, integrating an efficient energy harvesting system into the device will increase its lifetime and reduce the frequency of battery replacement. © 2023 IEEE.

关键词： Energy harvesting

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Custom-made Near Infrared Spectroscope as a Tool for Obtaining Information Regarding the Brain Condition

Custom-made Near Infrared Spectroscope as a Tool for Obtaini...

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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Anna Wieczorek Edward Jacek Gorzelańczyk Mariusz Pelc Saravanakumar Duraisamy Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We can obtain valuable information about the human brain using functional Near Infrared Spectroscopy (fNIRS). This paper describes the theoretical basis associated with this neuroimaging method through a custom-made prototype of a single-channel fNIRS device. The optodes were soldered to a milled Printed Circuit Board (PCB) and enclosed in a 3D printed housing. Using this fNIRS device, we performed a preliminary study to measure emotional responses from participants. Our results suggest that fNIRS allows for accurate measurement of emotions evoked by positive and negative images.

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Implementation of smoothing filtering methods for the purpose of trajectory improvement of single and triple inverted pendulums 6th

Implementation of smoothing filtering methods for the purpos...

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6th International Conference on Advanced Engineering Theory and Applications, AETA 2019

作者： Kawala-Sterniuk, Aleksandra Slanina, Zdenek Ozana, Stepan Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland FEECS Department of Cybernetics and Biomedical Engineering VSB – Technical University Ostrava Ostrava Czech Republic

ISBN: (纸本)9783030530204

In this paper smoothing filters were applied in order to improve inverted pendulum’s movement trajectory. The filtering was implemented in order to remove some signals’ artifacts. The authors tested various classical filters such as Savitzky-Golay and median filters. The authors decided to test the data from two types of inverted pendulums – single and triple. © Springer Nature Switzerland AG 2021.

关键词： Inverted pendulum

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Influence of the variables describing brain signals on the performance of the Naive Bayesian Classifier

Influence of the variables describing brain signals on the p...

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2022 Progress in Applied Electrical Engineering, PAEE 2022

作者： Kawala-Sterniuk, Aleksandra Zygarlicki, Jaroslaw Lysiak, Adam Grochowicz, Barbara Pelc, Mariusz Bauer, Waldemar Baczkowicz, Dawid Krecisz, Krzysztof Dylag, Katarzyna A. Wieczorek, Wiktoria Kahankova, Radana Martinek, Radek Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole Poland University of Greenwich School of Computing and Mathematical Sciences London United Kingdom Agh University of Science and Technology Department of Automatic Control and Robotics Krakow Poland Opole University of Technology Faculty of Physical Education and Physiotherapy Opole Poland St. Louis Children Hospital Krakow Poland Jagiellonian University in Krakow-Collegium Medicum Department of Pathophysiology Krakow Poland Jagiellonian University in Krakow-Collegium Medicum Department of Bioinformatics and Telemedicine Krakow Poland Vsb - Technical University Ostrava Department of Cybernetics and Biomedical Engineering-FEECS Ostrava-Poruba Czech Republic

ISBN: (纸本)9781665455152

In this paper various variables describing brain signals such as near-infrared spectroscopy (NIRS) and electroencephalography (EEG) on the Naive Bayesian Classifier were presented. Analysis of biomedical signals is a very challenging task - therefore the authors of this work decided to analyse two types of brain signals - EEG and NIRS, which have different features, character, nature and are differently prone to various artifacts occurrence. The applied classifiers can be applied for various features extraction and pattern comparisons, which is useful in diagnostic processes. © 2022 IEEE.

关键词： Near infrared spectroscopy

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Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization 63

Real-time Pricing Mechanism for V2G Using Distributed Bileve...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： You, Jiawei Dai, Xinliang Jiang, Yuning Yin, Haoyu Shi, Yuanming Jones, Colin N. ShanghaiTech University School of Information Science and Technology China Epfl Switzerland Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Germany Epfl Automatic Control Laboratory Switzerland Washington University in St. Louis Department of Electrical and Systems Engineering United States

ISBN: (纸本)9798350316339

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled with their energy storage capabilities. We propose an advanced real-time pricing model for the electricity market, employing a novel distributed bilevel optimization framework. This framework distinguishes between the distribution system operator (DSO) at the upper level and the EVs at the lower level, each aiming to optimize profit margins. The optimization includes power flow constraints at the upper level to ensure efficient operation within safe system limits, while model predictive control (MPC) is used to optimize lower-level EV responses. Additionally, we provide a rigorous convergence analysis of the proposed bilevel optimization method. Detailed convergence studies and simulation results demonstrate the effectiveness and superiority of the proposed algorithm. © 2024 IEEE.

关键词： Predictive control systems

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An identification of bioimpedance spectroscopy parameters by the least squares method 6th

An identification of bioimpedance spectroscopy parameters by...

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6th International Conference on Advanced Engineering Theory and Applications, AETA 2019

作者： Ozana, Stepan Prauzek, Michal Konecny, Jaromir Kawala-Sterniuk, Aleksandra Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava-Poruba Czech Republic Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

ISBN: (纸本)9783030530204

This contribution deals with identification of bioimpedance spectroscopy parameters for implementation on embedded platforms. The paper’s goal is to present method which is suitable for implementation in microcontrollers or field programmable gate arrays. The paper brings brief description of the state of the art and it reviews an equivalent electrical model and the least squares method as background of the work. In experimental part, the author presenting an experimental setup for data acquisition for electrical model and an identification approach including the implementation details of calculation of inverse matrix. In the result section the comparison between real and identified parameters is presenting and the results are evaluated in terms of accuracy. The proposed method can be considered as precise identification for the particular electrical model. The paper conclusion includes discussion about method accuracy and brief outline for future work. © Springer Nature Switzerland AG 2021.

关键词： Field programmable gate arrays (FPGA)

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Noise Reduction in Industry Based on Virtual Instrumentation

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Computers, Materials & Continua 2021年第10期69卷 1073-1096页

作者： Radek Martinek Rene Jaros Jan Baros Lukas Danys Aleksandra Kawala-Sterniuk Jan Nedoma Zdenek Machacek Jiri Koziorek Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical EngineeringVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia Faculty of Electrical Engineering Automatic Control and InformaticsOpole University of TechnologyOpolePoland Faculty of Electrical Engineering and Computer Science Department of TelecommunicationsVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia

This paper discusses the reduction of background noise in an industrial environment to extend *** the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G *** study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a *** experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from *** tested a hybrid algorithm for noise reduction and its impact on voice command recognition *** virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested *** welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+*** workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

关键词： 5G hybrid algorithms signal processing speech recognition

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The Use of Multilayer ConvNets for the Purposes of Motor Imagery Classification

The Use of Multilayer ConvNets for the Purposes of Motor Ima...

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International Conference on Automation, AUTOMATION 2021

作者： Paszkiel, Szczepan Dobrakowski, Pawel Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-271 Poland Humanitas University Kilinskiego 43 Sosnowiec41-200 Poland

ISBN: (纸本)9783030748920

An electroencephalographic signal is characterized by high complexity and character, which changes dynamically over time. At the same time, it should be noted that EEG signals in the field of Motor Imagery are increasingly more often used by scientists, among others, to help people with disabilities. Decoding these signals is important from the perspective of modern solutions based on the brain-computer interface technology. It is possible to isolate both spatial, as well as temporal features from an EEG signal using a ConvNet. This research paper suggests combining numerous ConvNet – Convolutional Neural Network models in terms of the EEG signal. The suggested multilayer ConvNets indicate high performance coefficients on a test data set. The method advocated in this article achieves a degree of accuracy on a data set at a precision level of 74.5%. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image classification

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