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Power Electronic and Drive Systems and Technologies Conference (PEDSTC)

作者： Mirhamed Pourmirasghariyan Mirsajed Pourmirasghariyan Seyed Saeid Heidari Yazdi Seyyed Yousef Mousazadeh Mousavi Kumars Rouzbehi G. B. Gharehpetian Departement of Electrical and Computer Engineering Amirkabir University of Technology Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Electrical & Computer Engineering School of Engineering and Digital Science Nazarbayev University Nur-Sultan Kazakhstan Faculty of Engineering and Technology University of Mazandaran Sari Iran Department of Systems and Automatic Control Engineering University of Seville Seville Spain

The performance of Interline DC Power Flow controllers (IDC-PFCs) in Voltage Source Converters (VSC)-based High Voltage Direct Current (HVDC) grids, can be affected due to different issues. The current limitation of HVDC lines, the voltage limitation of HVDC buses, and DC voltage of the IDC-PFC intermediary capacitor prevent effective and efficient operation of IDC-PFCs. In this paper, it is shown that this issue can be overcome by using a virtual capacitor in parallel with the IDC-PFC intermediary capacitor. Also, an energy control-based scheme is proposed for the operation of IDC-PFCs in VSC-HVDC grid. The benefits of using the virtual capacitor are: widening the operational area of the IDC-PFCs for the determined duty cycle and injecting more voltage in series to the interconnected HVDC line to control the related HVDC line current. The proposed solution is successfully evaluated on a CIGRE three-terminal VSC-HVDC grid which is modeled by linearized space-state equations.

关键词： Fluctuations HVDC transmission Capacitors High-voltage techniques Boosting Mathematical models Power conversion

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The OPS-SAT benchmark for detecting anomalies in satellite telemetry

arXiv

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arXiv 2024年

作者： Ruszczak, Bogdan Kotowski, Krzysztof Evans, David Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska Str. 76 Opole45-758 Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka Str. 16 Gliwice44-100 Poland KP Labs Bojkowska Str. 37J Gliwice44-100 Poland European Space Agency ESOC Robert-Bosch-Str. 5 Darmstadt64293 Germany

Detecting anomalous events in satellite telemetry is a critical task in space operations. This task, however, is extremely time-consuming, error-prone and human dependent, thus automated data-driven anomaly detection algorithms have been emerging at a steady pace. However, there are no publicly available datasets of real satellite telemetry accompanied with the ground-truth annotations that could be used to train and verify anomaly detection supervised models. In this article, we address this research gap and introduce the AI-ready benchmark dataset (OPSSAT-AD) containing the telemetry data acquired on board OPS-SAT—a CubeSat mission which has been operated by the European Space Agency which has come to an end during the night of 22–23 May 2024 (CEST). The dataset is accompanied with the baseline results obtained using 30 supervised and unsupervised classic and deep machine learning algorithms for anomaly detection. They were trained and validated using the training-test dataset split introduced in this work, and we present a suggested set of quality metrics which should be always calculated to confront the new algorithms for anomaly detection while exploiting OPSSAT-AD. We believe that this work may become an important step toward building a fair, reproducible and objective validation procedure that can be used to quantify the capabilities of the emerging anomaly detection techniques in an unbiased and fully transparent way. © 2024, CC BY.

关键词： Anomaly detection

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New class of impulsive noise reduction filters based on kernel density estimation

New class of impulsive noise reduction filters based on kern...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： B. Smolka K.N. Plataniotis R. Lukac A.N. Venetsanopoulos Department of Automatic Control Silesian University of Technology Poland The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada Slovak Image Processing Center Dobsina Slovakia Faculty of Applied Science and Engineering University of Toronto Toronto ONT Canada

The paper presents a new filtering scheme for the removal of impulsive noise in color images. It is based on estimating the probability density function for color pixels in a filter window by means of the kernel density estimation method. A quantitative comparison of the proposed filter with the vector median filter shows its excellent ability to reduce noise while simultaneously preserving fine image details.

关键词： Noise reduction Filters Kernel Colored noise Color Histograms Filtering Probability density function Shape Multidimensional systems

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IEEE International Conference on Multimedia and Expo (ICME)

In this paper a novel approach to the problem of impulsive noise removal in color images based on the nonparametric density estimation is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The new method is faster than the standard vector median filter and preserves better edges and fine image details. Simulation results show that the proposed method outperforms other standard algorithms of the reduction of impulsive noise in color images.

关键词： Colored noise Color Filtering Pixel Strontium Educational institutions Image processing Noise reduction Nonlinear filters Gray-scale

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment

Integration of ANN for Accurate Estimation and Control in Wa...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Andreea Elena Țîru Iulian Vasiliev Larisa Diaconu Ramon Vilanova Daniel Voipan Harsha Ratnaweera Department of Automatic Control and Electrical Engineering "Dunărea de Jos" University of Galaţi Galaţi Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain Department of Computer Science and Information Technology "Dunărea de Jos" University of Galaţi Galaţi Romania Faculty of Science and Technology (Realtek) Norwegian University of Life Sciences Ås Norway

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so.

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Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results

Cybersecurity Threat Detection in the Behavior of IoT Device...

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Federated Conference on computer science and Information Systems (FedCSIS)

作者： Michał Czerwiński Marcin Michalak Piotr Biczyk Błażej Adamczyk Daniel Iwanicki Iwona Kostorz Maksym Brzęczek Andrzej Janusz Marek Hermansa Łukasz Wawrowski Artur Kozłowski QED Software Warsaw Poland Faculty of Mathematics University of Warsaw Warsaw Poland Łukasiewicz Research Network - Institute of Innovative Technologies EMAG Katowice Poland Department of Computer Networks and Systems Silesian<file://Silesian> University of Technology Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Silesian<file://Silesian> University of Technology Gliwice Poland EFIGO sp. z o.o. Katowice Poland

The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems.

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A Distributed control framework for the optimal operation of DC microgrids

arXiv

引用

arXiv 2022年

作者： Fu, Zao Cucuzzella, Michele Cenedese, Carlo Yu, Wenwu Scherpen, Jacquelien M.A. School of Cyber Science and Engineering Southeast University Nanjing211189 China Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia27100 Italy Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zürich Physikstrasse 3 Zürich8092 Switzerland

In this paper we propose an original distributed control framework for DC mcirogrids. We first formulate the (optimal) control objectives as an aggregative game suitable for the energy trading market. Then, based on the dual theory, we analyze the equivalent distributed optimal condition for the proposed aggregative game and design a distributed control scheme to solve it. By interconnecting the DC mcirogrid and the designed distributed control system in a power preserving way, we steer the DC microgrid's state to the desired optimal equilibrium, satisfying a predefined set of local and coupling constraints. Finally, based on the singular perturbation system theory, we analyze the convergence of the closed-loop system. The simulation results show excellent performance of the proposed control framework. © 2022, CC BY-NC-SA.

关键词： Perturbation techniques

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A Case for Online Real-Time Barcode Readers

A Case for Online Real-Time Barcode Readers

引用

Telecommunications Forum Telfor

作者： Ovidiu Parvu Andrei G. Balan Andrei S. Homorogan "Politehnica" University of Timisoara Faculty of Automatic Control and Computer Science and with "Ufo Media Design" "Politehnica" University of Timisoara and with "Ufo Media Design" Ufo Media Design

ISBN: (纸本)9781457714993

In this paper we are advocating for the development and adoption of mainstream online real-time barcode reading systems that go beyond common current usage scenarios. The goal is to deliver a reliable and accessible alternative to native applications and proprietary readers. As such we analyze resource dependencies and limitations from a fresh and unconventional perspective in relation to the "in-browser" environment. To attain this feat we propose two barcode service delivery systems: the first one, a modular client-oriented detection framework suited for immediate implementation and the second one, a hybrid system designed for complex cloud infrastructures.

关键词： Barcode Cloud Framework In-browser Markers Online Reader Real-time Service

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Brightbox - A Rough Set Based Technology for Diagnosing Mistakes of Machine Learning Models

SSRN

引用

SSRN 2023年

作者： Janusz, Andrzej Zalewska, Andżelika Wawrowski, Lukasz Biczyk, Piotr Ludziejewski, Jan Sikora, Marek Ślęzak, Dominik QED Software sp. z o.o. Mazowiecka 11/49 Warsaw00-052 Poland Institute of Informatics University of Warsaw Banacha 2 Warsaw02-097 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

The paper presents a novel approach to investigating mistakes in machine learning model operations. The considered approach is the basis for BrightBox - a diagnostic technology that can be used for analyzing prediction models and identifying model- and data-related issues. The idea is to induce from data the surrogate rough set-based models that approximate decisions made by the monitored black box models. Such approximators are used to compute neighborhoods of instances that undergo the diagnostic process - the neighborhoods consist of historical instances that were processed in a similar way by rough set-based models. The diagnostic process is then based on the analysis of mistakes registered in such neighborhoods. The experiments performed on real-world data sets confirm that such analysis can provide us with efficient and valid insights about the reasons for the poor performance of machine learning models. © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Modeling and control of a New Quadrotor Manipulation System

Modeling and Control of a New Quadrotor Manipulation System

引用

International Conference on Innovative Engineering Systems

作者： Ahmed Khalifa Mohamed Fanni Ahmed Ramadan Ahmed Abo-Ismail Mechatronics and Robotics Engineering Dept. School of Innovative Design Engineering Egypt-Japan University of Science and Technology New Borg-El-Arab city Alexandria Egypt Prod. Eng. & Mechanical Design Dept. Faculty of Engineering Mansoura University Mansoura Egypt Computer & Automatic Control Dept. Faculty of Engineering Tanta University Tanta Egypt

ISBN: (纸本)9781467344401

This paper introduces a new quadrotor manipulation system that consists of a 2-link manipulator attached to the bottom of a quadrotor. This new system presents a solution for the drawbacks found in the current quadrotor manipulation system which uses a gripper fixed to a quadrotor. Unlike the current system, the proposed system enables the end-effector to achieve any arbitrary orientation and thus increases its degrees of freedom from 4 to 6. Also, it provides enough distance between the quadrotor and the object to be manipulated. This is useful in some applications such as demining applications. System kinematics and dynamics are derived which are highly nonlinear. controller is designed based on feedback linearization to track desired trajectories. controlling the movements in the horizontal directions is simplified by utilizing the derived nonholonmic constraints. Finally, the proposed system is simulated using MATLAB/SIMULINK program. The simulation results show the effectiveness of the proposed controller.

关键词： Aerial manipulation Quadrotor 2-link manipulator Feedback linearization Demining devices

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