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Influence of agglomerations on magnetic properties of polymer matrices filled with magnetic nanoparticles

Materials Today: Proceedings 2022年 67卷 792-796页

作者： Blachowicz, Tomasz Grzybowski, Jacek Ehrmann, Andrea Institute of Physics – Centre for Science and Education Silesian University of Technology Gliwice 44-100 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice 44-100 Poland Faculty of Engineering and Mathematics Bielefeld University of Applied Sciences Bielefeld 33619 Germany

Magnetic nanoparticles can be embedded in electrospun nanofibers and other polymeric matrices to prepare magnetic composites with defined magnetic and mechanical properties. Metal-oxide nanoparticles, such as magnetite or nickel-ferrite, are of special interest since they do not need a coating to avoid oxidation. Like other nanoparticles, these metal-oxide nanoparticles tend to form agglomerations, in this way modifying the magnetic properties of the composites. After studying this effect for the magnetic elements Co, Fe, Ni as well as permalloy (Py) in a previous study, defining a new method to quantify the nanoparticle distribution in a polymer, here we concentrate on the influence of agglomerations on the magnetic properties of metal-oxide nanoparticles with different diameters in non-magnetic matrices. © 2022

关键词： Magnetite

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Improving fNIRS Signal Quality Using Smoothing Filtering

Improving fNIRS Signal Quality Using Smoothing Filtering

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2023 Progress in Applied Electrical engineering, PAEE 2023

作者： Kawala-Sterniuk, Aleksandra Mikolajewski, Dariusz Leiva, Luis A. Ruotsalo, Tuukka Lysiak, Adam Grochowicz, Barbara Jacek Gorzenariczyk, Edward Luckiewicz, Adrian Wieczorek, Anna Pelc, Mariusz Automatic Control and Informatics Opole University of Technology Faculty of Electrical Engineering Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland University of Luxembourg Luxembourg Department of Computer Science Luxembourg Luxembourg University of Helsinki Denmark University of Copenhagen Finland Institute of Philosophy Kazimiez Wielki University Bydgoszcz Poland

ISBN: (纸本)9798350316254

Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared. © 2023 IEEE.

关键词： Information filtering

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Integrating Blockchain Technology in a Cyber Physical System to Secure Data

Integrating Blockchain Technology in a Cyber Physical System...

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International Conference on control Systems and computer Science (CSCS)

作者： Balaban Bèatrix-May Sacală Ioan Ştefan Petrescu-Niţă Alina-Claudia Niţă Răzvan Department of System Engineering Faculty of Automatic Control and Computers Politehnica University of Bucharest Romania

Considering the constant growth and evolution of technology, being able to secure data is a challenge. This is why researchers find this a top research topic. Cyber-Physical Systems are complex, large-scale systems that can be found in domains like healthcare, transportation, industrial controls systems or smart grids. Having many components that interact with each other, we can observe here the challenge in maintaining a secure environment for the data as data tampering or data extraction can occur, for example, in the actual transportation of data from one device to another. The main focus of this paper is to give an answer if blockchain technology provides a solution in building a secure network. We give a short review of the related work regarding blockchain integration in large-scale systems like Cyber-Physical Systems. It was also briefly analyzed the layered structure of a blockchain and discussed some solutions for each layer. We then discussed about consensus algorithms for validation and authentication process. In general, consensus algorithms are implemented to assure the validation process of the nodes in a network. In this paper we tried to analyze and propose a model that offers an extra layer of security by adding the authentication step. In this way, the nodes that are validated are also considered trusted nodes in the network.

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Tabular Dyna-Q Algorithm for Online Calculation of LQR Gains: A Simulation Study 9

Tabular Dyna-Q Algorithm for Online Calculation of LQR Gains...

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9th International Conference on engineering and Emerging Technology, ICEET 2023

作者： Farooghi, Kian Samadi, Mahdieh Khaloozadeh, Hamid K. N. Toosi University of Technology Department of Systems and Control Tehran Iran University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran

ISBN: (纸本)9798350316926

This paper presents a novel approach for the online calculation of Linear Quadratic Regulator (LQR) gains using the Tabular Dyna-Q algorithm. By leveraging Q-learning, this technique enables the determination of gains for unknown dynamic systems by using input-output data only. The proposed algorithm is particularly advantageous for situations where acquiring input-output data is expensive or time-consuming, as it effectively reduces computation time by reusing previous data. To validate the accuracy of the calculations and control scheme, a simulation example is provided. The results indicate the effectiveness of the Tabular Dyna-Q algorithm in accurately computing LQR gains and its potential application in real-world scenarios. This research contributes to advancing the field of control theory by offering an efficient and reliable method for online gain calculation in dynamic systems. © 2023 IEEE.

关键词： Reinforcement learning

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Security Issues in Software-Defined Networking (SDN) Environments

Security Issues in Software-Defined Networking (SDN) Environ...

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Roedunet International Conference (RoEduNet)

作者： Khirota Gorgees Yalda Diyar Jamal Hamad Nicolae Tapus Ibrahim Taner Okumus Faculty of Automatic Control and Computer Science Politehnica University of Bucharest Bucharest Romania IT department Soran Technical college Erbil Polytechnic University Kurdistan Region Erbil Iraq Computer Engineering Faculty of engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

Software-Defined Networking (SDN) represents a significant shift in network architecture, providing exceptional programmability, flexibility, and simplified management. However, this paradigm shift introduces a unique set of security challenges that must be addressed to fully realize the potential of SDN. This paper examines the security issues in SDN environments, detailing the threats and vulnerabilities at various layers of the SDN architecture, including the control plane, data plane, and application plane. Through an extensive review of current literature, critical security challenges such as controller attacks, data plane breaches, and vulnerabilities in inter-plane communications are identified. Existing security solutions and mitigation strategies, such as authentication and authorization mechanisms, encryption techniques, and intrusion detection systems, are also explored. Furthermore, the paper discusses recent advances and emerging trends in SDN security, offering insights into ongoing research and future directions. The findings underscore the importance of robust security measures in ensuring the reliability and integrity of SDN deployments, providing a foundation for future innovation and development in this dynamic field.

关键词： Technological innovation Prevention and mitigation Intrusion detection Distributed databases Organizations Robustness Encryption Security Software defined networking computer crime

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LQR-PID control Design of a Buck Converter 8

LQR-PID Control Design of a Buck Converter

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Torres-Pinzón, Carlos A. Flores-Bahamonde, F. Ramírez-Murillo, H. López-Santos, Oswaldo Mojica-Casallas, C.J. Davari, S. Alireza Universidad Santo Tomás Faculty of Electronic Engineering Colombia Universidad Andres Bello Faculty of Enigineering Energy Transformation Center Chile Universidad de la Salle Faculty of Engineering Department of Electrical Engineering Bogotá Colombia Rovira i Virgili University Group of Automatic Control and Industrial Electronics Tarragona Spain Shahid Rajaee Teacher Training University Department of Electrical Engineering Tehran Iran

ISBN: (纸本)9798350321128

In this paper, an optimal proportional integral derivative (PID) controller based on a linear quadratic regulator (LQR) is proposed for the regulation of the output voltage of a buck converter. Specifically, the work proposes to determine the gains of the PID controller through an LQR state feedback technique, formulated as a Linear Matrix Inequality (LMI), which allows for ensuring stability and guarantee a predefined performance index. Simulation results using PSIM are presented validating the theoretical study. © 2023 IEEE.

关键词： Buck converter LMI LQR-PID control PID control

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Improvement of the Predictive control Method for the High-Level controller 17

Improvement of the Predictive Control Method for the High-Le...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Budashko, Vitalii Sandler, Albert Glazeva, Oksana Educational and Scientific Institute of Automation and Electrical Engineering National University 'Odessa Maritime Academy' NUOMA Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of the theory of automatic control and computer technology Odesa Ukraine National University 'Odessa Maritime Academy' NUOMA Department of electrical engineering and electronics Odesa Ukraine

ISBN: (纸本)9798331520564

Automation of ship maneuvering in limited sailing conditions usually requires 100% redundancy of thrusters (THRs) of various modifications and their locations in accordance with the matrix. The hierarchy of the motion control system is branched by levels using high-level motion controllers and THRs control distribution algorithms, which allows for a modular design with software, where the high-level controller (HLC) can be designed without comprehensive information about the thruster motors, and the input signal branching and speed limits are handled by the motion controller. But, for certain THRs configurations, this branching leads to the decrease in control efficiency due to the limitation of data on the physical characteristics of the ships and the operation of the motion controller. This research examines different approaches to improving control efficiency using methods of nonlinear predictive control models as a basis for developing motion controllers with decision optimization based on relevant constraints. The implemented branched system is the result of solving two simple problems of ship's motion, which highlight the related problems. The use of different approaches to eliminate the identified shortcomings made it possible to develop the nonlinear controller that combines the motion controller with distributed control of the THRs and ensuring the certain level of system reliability. The modularity of the control system is provided by the expansion of the closed system, which made it possible to achieve an increase in efficiency during the combined mode of operation. The obtained solution of nonlinear control with time-varying constraints made it possible to increase the accuracy of the control with a decrease in the duration of the pause in response to the change of the disturbance within 10% © 2024 IEEE.

关键词： Predictive control systems

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Natural language processing for the automation of operations in an online bookstore

Natural language processing for the automation of operations...

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IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Elena Iorga Tiberius Dumitriu Faculty of Automatic Control and Computer Engineering ˶Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

The use of Natural Language Processing Algorithms (NLP) for automation purposes in various applications is frequently encountered recently. Some research managed to identify the dominant emotion from a text using neural networks (ANN), Random Forest (RF) and Support Vectors Machines (SVM) while other studies classified documents with the aim of mechanizing the extraction process of *** paper presents a study on different Natural Language Processing Algorithms (NLP) used for automation of a virtual bookstore. The objective was the application of artificial intelligence algorithms to streamline the necessary processes of an online bookstore or library, taking into consideration the short descriptions and summaries of the books. The aim is to improve the results obtained by supervised algorithms using various techniques such as aggregating unsupervised classifications. In order to boost their understanding of natural language, GPT is used to enhance the dataset by adding additional context. Finally, some of the methods utilized in improving accuracy can be used to create a personalized recommendation system that suits each reader’s needs.

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Sensor Fault Estimation and Ftc Design for Fractional Linear Systems Using the Conformable Derivative

Sensor Fault Estimation and Ftc Design for Fractional Linear...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Ali Omar M. Alsharif A. Jmal O. Naifar Ausama H. Ahmed H. Gassara A. Ben Makhlouf Control and Energy Management laboratory (CEM lab) Sfax University Engineering National School Tunisia Department of Electrical & Computer Engineering Faculty of Engineering Elmergib University Alkhums Libya Control and Energy Management laboratory (CEM lab) Monastir University Tunisia Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Tunisia Department of Mathematics Faculty of Sciences of Sfax Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

In this paper, Fault Tolerant control (FTC) for fractional-order systems (FOS) has not received as much attention in the literature as it has for standard integer-order systems. This work aims to bridge that gap. We propose a practical approach to fault estimation and fault-tolerant control (FTC) specifically designed for linear (FOS) with sensor failures. Our method leverages fractional exponential stability within the Lyapunov framework and employs the Conformable formulation of fractional derivatives. Notably, the primary contribution of this paper is the first application of the Conformable fractional derivative (CFD) in the context of (FTC). To accurately estimate states and faults, the proposed approach utilizes an observer coupled with a customized adaptation law. To validate our theoretical contributions, we present a detailed simulation of a numerical case study.

关键词： Linear systems Bridges Stability Fault tolerant systems Fault tolerant control Observers control theory Standards Lyapunov methods

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On the Impact of Noisy Labels on Supervised Classification Models 23rd

On the Impact of Noisy Labels on Supervised Classificatio...

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23rd International Conference on Computational Science, ICCS 2023

作者： Dubel, Rafal Wijata, Agata M. Nalepa, Jakub Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Faculty of Biomedical Engineering Silesian University of Technology Roosevelta 40 Zabrze41-800 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland

ISBN: (纸本)9783031360206

The amount of data generated daily grows tremendously in virtually all domains of science and industry, and its efficient storage, processing and analysis pose significant practical challenges nowadays. To automate the process of extracting useful insights from raw data, numerous supervised machine learning algorithms have been researched so far. They benefit from annotated training sets which are fed to the training routine which elaborates a model that is further deployed for a specific task. The process of capturing real-world data may lead to acquring noisy observations, ultimately affecting the models trained from such data. The impact of the label noise is, however, under-researched, and the robustness of classic learners against such noise remains unclear. We tackle this research gap and not only thoroughly investigate the classification capabilities of an array of widely-adopted machine learning models over a variety of contamination scenarios, but also suggest new metrics that could be utilized to quantify such models’ robustness. Our extensive computational experiments shed more light on the impact of training set contamination on the operational behavior of supervised learners. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital storage

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