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13th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2021

作者： Ali, Haider Abdullah Goga, Nicolae Vasilateanu, Andrei Ali, Liwa Abdullah Abd-Almuhsen, Ghufran Saady Naji, Hasan K. University POLITEHNICA of Bucharest Faculty of Automatic Control and Computers Bucharest Romania Al-Emamain Al Kadhimain Medical City Department of Neurosurgery Baghdad Iraq Madenat Alelem University College Department of Computer Techniques Engineering Baghdad Iraq

ISBN: (纸本)9781665425346

Brain-computer Interface (BCI) identifies user thinking through different electrophysiological signals. These signals are detected through electrodes placed on the scalp, and the neuronal activity of the cortical is collected by electrodes implanted inside the brain. Regardless of reasons, limbs losses affect a large percentage of the world's people yearly. The necessity for solutions for those having these conditions can be related to health issues and research. Myoelectric and other types of prostheses are currently in use, but it has some drawbacks like the high-price, heaviness, and the dependency on the intact nerves. These drawbacks can be overcome using electroencephalography (EEG) mind-controlled prosthesis arm. The mind-controlled prosthesis arm uses EEG non-invasive technique which provides powerful help for disabled persons in their daily activities, particularly to help arm amputees move their prosthesis arm easily. In this paper, we present a quantitative questionnaire to identify and validate the user's functional and non-functional requirements and to know how users want to interact with the system. We aim to build inexpensive, lightweight, and smart functional prosthesis arm according to functional and non-functional requirements to meet users' goals and requirements. The participants' interests and recommendations are considered while designing and building a smart functional prosthesis arm system. This is one of the very few surveys that handle the user's requirements of a mind-controlled prosthesis arm according to the amputees and specialists' opinions. © 2021 IEEE.

关键词： Electroencephalography

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Setting up a Distributed control System Laboratory 11

Setting up a Distributed Control System Laboratory

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11th International Conference and Exposition on Electrical And Power engineering, EPE 2020

作者： Postovei, Danut Adrian Bulac, Constantin Tristiu, Ion Camachi, Balduino University Politehnica of Bucharest Faculty of Power Engineering Bucharest Romania University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania

ISBN: (纸本)9781728181264

This paper presents a practical laboratory for student education purpose in Distributed control Systems, with focus on applications for high voltage transmission substations. The monitoring, control and protection part is realized with a software platform and IED devices manufactured by AREVA TD France, while the primary equipment, like circuit breakers and disconnectors are simulated with latched relays. The system architecture and communication network are reproducing a real one usually used in transmission substations. The implementation of this laboratory, both through specific laboratory works and experiments, makes the theoretical part to be supported by a practical experience, resulting in future graduates with added value in the electric power industry. © 2020 IEEE.

关键词： Laboratories

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Magnetization Dynamics in Nanofiber Networks 11

Magnetization Dynamics in Nanofiber Networks

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11th IEEE International Conference "Nanomaterials: Applications and Properties", NAP 2021

作者： Blachowicz, Tomasz Steblinski, Pawel Grzybowski, Jacek Ehrmann, Andrea Institute of Physics Center for Science and Education Silesian University of Technology Gliwice Poland Faculty of Electronics and Informatics Koszalin University of Technology Koszalin Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Faculty of Engineering and Mathematics Bielefeld University of Applied Sciences Bielefeld Germany

ISBN: (纸本)9781665439077

Magnetic nanofibers are of great interest for applications like data transport and storage as well as in basic research. Especially bent nanofibers, which can unambiguously be produced by electrospinning, show a broad spectrum of possible magnetization reversal processes, depending on bending radius, geometry, magnetic field orientation, etc. Besides these quasistatic processes, dynamic investigations are necessary for investigating data transport properties of magnetic nanofibers. We report on domain wall transport through coupled bent nanowires, forming networks with multiple data inputs and outputs. Our results show diverse phenomena which have to be taken into account during these dynamic processes, such as domain wall instabilities or interference between converging signals, and suggest possible architectures of nanowire-based logics. ©2021 IEEE

关键词： Nanofibers

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Feature Selection via Genetic Multiobjective Optimization with Fuzzy Rejection Mechanisms

Feature Selection via Genetic Multiobjective Optimization wi...

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

作者： Corina Cimpanu Lavinia Ferariu Tiberius Dumitriu Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University of Iași Iași Romania

ISBN: (纸本)9781665409773

In pattern identification, embedded Feature Selection (FS) determines a detailed data description and an efficient and accurate classification. Most Genetic Algorithm (GA) based optimization procedures tackle the minimization of a classifier's error rate. Independent of how feature selection procedures are configured, either in Single (SOO) or Multi-Objective Optimization (MOO) manners, the major problem with all classifiers is multidimensionality and quantity of redundant and noisy data recordings. This paper compares six GA-based optimizations as viable solutions for an accurate and efficient assessment of working memory load levels during arithmetic computations based on Electroencephalogram (EEG) data. An objective layout analysis of a randomly generated population motivates both SOO and MOO further explorations. The single objective error-based optimization, the aggregation of error, and the number of selected features illustrate the limitations of SOOs. The third SOO incorporates a fuzzy rejection mechanism for unnecessary features. The baseline for MOO comparison is Deb's NSGA. Two new MOO procedures for feature selection are proposed: a MOO Fuzzy Rejection of Irrelevant Features (MOO-FRIF) and a Fuzzy Progressive Deletion of Irrelevant Features (MOO-FPDIF). Both new MOO approaches gradually eliminate or discourage the EEG features that negatively influence the classifier. Two classifiers address the problem distinctively, namely Random Forests (RF) and a multi-class Support Vector Machine (SVM) with one vs. one comparison mechanism and RBF kernel.

关键词： Support vector machines Feature extraction Minimization Genetics Electroencephalography Task analysis Statistics

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Adaptive Identification of Linear Systems with a Mix of Static and Time-Varying Parameters

SSRN

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SSRN 2022年

作者： Niedźwiecki, Maciej Gańcza, Artur Shen, Lu Zakharov, Yuriy the Faculty of Electronics Telecommunications and Computer Science Department of Automatic Control Gdá nsk University of Technology Gdańsk80-233 Poland Department of Electronic Engineering University of York United Kingdom

We consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics, for instance, in applications requiring identification of the acoustic channel, such as underwater acoustic communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identifying time-varying systems. In this paper, we further improve the performance of the fLBF algorithm by exploiting properties of the system. Specifically, we propose an adaptive time-invariance test to identify whether a particular system tap is static or time-varying and exploit this knowledge for choosing the number of basis functions. We also propose a regularization scheme that exploits the system sparsity and an adaptive technique for estimating the regularization parameter. Finally, a debiasing technique is proposed to reduce an inherent bias of fLBF estimates. The high performance of the fLBF algorithm with the proposed techniques is demonstrated in scenarios of underwater acoustic communications, using numerical and real experiments. © 2022, The Authors. All rights reserved.

关键词： Continuous time systems

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Improving fNIRS Signal Quality Using Smoothing Filtering

Improving fNIRS Signal Quality Using Smoothing Filtering

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Progress in Applied Electrical engineering (PAEE)

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

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.

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Pilot Study on Using Hybrid–Cascade Filtering on Brain Signals for the control Purposes

Pilot Study on Using Hybrid–Cascade Filtering on Brain Sign...

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

作者： Mariusz Pelc Dariusz Mikołajewski Edward Jacek Gorzelańczyk Anna Wieczorek Henryk Racheniuk Adam Sudoł Kayhan Latifzadeh Luis A. Leiva Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland Faculty of Physical Education and Physiotherapy Opole University of Technology Opole Poland Faculty of Natural and Technical Sciences University of Opole Opole Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg

We present an initial study conducted on fNIRS signals using Hybrid-Cascade filters for the purpose of their quality improvement. Whilst many studies focus on filtering brain signals, so that their frequency domain properties would allow e.g. widely understood diagnostics, here we focus on the study of time-domain signal characteristics, which is relevant for potential control purposes. Taking into account various kinds of artifacts, we propose a novel cascade 1D Kalman filter to handle fNIRS signals.

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Application of Machine Learning to Performance Assessment for a class of PID-based control Systems

arXiv

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arXiv 2021年

作者： Grelewicz, Patryk Khuat, Thanh Tung Czeczot, Jacek Nowak, Pawel Klopot, Tomasz Gabrys, Bogdan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Automatic Control and Robotics Gliwice44100 Poland University of Technology Sydney Faculty of Engineering and IT Advanced Analytics Institute NSW2007 Australia

In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed. It is dedicated for a wide class of PID-based control industrial loops with processes exhibiting dynamical properties close to second order plus delay time (SOPDT). The proposed concept is very general and easy to configure to distinguish between acceptable and poor closed loop performance. This approach allows for determining the best (but also robust and practically achievable) closed loop performance based on very popular and intuitive closed loop quality factors. Training set can be automatically derived off-line using a number of different, diverse control performance indices (CPIs) used as discriminative features of the assessed control system. The proposed extended set of CPIs is discussed with comprehensive performance assessment of different machine learning based classification methods and practical application of the suggested solution. As a result, a general-purpose CPA system is derived that can be immediately applied in practice without any preliminary or additional learning stage during normal closed loop operation. It is verified by practical application to assess the control system for a laboratory heat exchange and distribution *** Codes 93 © 2021, CC BY-NC-SA.

关键词： Three term control systems

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Machine Learning-Based Cascade Filtering System for fNIRS Data Analysis

Machine Learning-Based Cascade Filtering System for fNIRS Da...

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Progress in Applied Electrical engineering (PAEE)

作者： Mariusz Pelc Dariusz Mikołajewski Tuukka Ruotsalo Luis A. Leiva Adam Sudoł Edward Jacek Gorzelańczyk Adam Łysiak Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland University of Helsinki Finland University of Copenhagen Denmark Department of Computer Science University of Luxembourg Luxembourg Luxembourg Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

This paper presents a preliminary study on the use of machine learning-based methods to select the appropriate parameters of cascade filters in the analysis of brain signals recorded using functional infrared spectroscopy (fNIRS), which shows the level of oxygenation in the brain and, unlike EEG signals (showing electrical brain activity), are less prone to potential interference, disturbances or artifacts occurrence.

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Modelling and implementation of Single Line Diagram data in IEC 61850 environment

Modelling and implementation of Single Line Diagram data in ...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Dănuţ Adrian Poştovei Constantin Bulac Ion Triştiu Balduino Camachi Nicolae Anton Faculty of Power Engineering University POLITEHNICA of Bucharest Bucharest Romania Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Bucharest Romania

ISBN: (数字)9781728180533

ISBN: (纸本)9781728180540

The aim of this paper is to improve the automation processes of electrical power substations based on IEC 61850 standard, with the focus on data management related to data structure, path, and communication model. When modelling substations items a simple and clear approach is necessary to effectively match binary or analog data from the switchyard with the IEC 61850 data object model. The study is made by simply transforming data from a single line diagram and its functionalities into object model by explaining its hierarchy structure and how to use it to create an operational process interface. This possible through the three key components of the IEC 61850 standard: Client-Server based on TCP/IP MMS (Manufacturing Messaging Specification) which perform the monitoring and control functions, GOOSE (Generic Object-Oriented Substation Event) protocol used in applications between IEDs (Intelligent Electronic Device) like interlocking signals and trip messages and Sampled Values (SV) protocol used for fast transmission of analogue values over the network.

关键词： Performance evaluation Substations Protocols Object oriented modeling Data models IEC Standards Standards

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