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A method for decreasing the impact of depth-of-focus to accurate location of particle

Zhongguo Jiguang/Chinese Journal of Lasers 2009年第SUPPL.期36卷 270-275页

作者： Li, Zhibin Zheng, Gang Zhang, Lixin Xia, Fei Faculty of Electric and Automatic Engineering Shanghai University of Electric Power Shanghai 200090 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China College of Power Engineering University of Shanghai for Science and Technology Shanghai 200093 China

The particle fields is generally measured by digital in-line holographic technique. But the resolution of particle axial position is lower due to the impact of zero-order image, twin-image noise and the depth of focus(DOF). Generally, DOF is tens of times as many as particle diameter. The large DOF has been a vexing problem in extraction of particle position from digital in-line holograms. DOF is affected by some recording parameters, i.e. NA of recording system, size of CCD, recording distance and the wavelength. Resolution of particle axial position can be improved by reducing depth of focus and recording distance. In this paper, an auto-focusing algorithm based on the most gradient for accurate location of particle by selecting proper window in accordance with particle size is proposed. At present, there are a lot of auto-focusing algorithms based on gradient, which calculate the gradient value only in appointed fixed directions, but the real gradient direction may not be the appointed direction. In order to solve the problem, an auto-focusing algorithm based on the most gradient and threshold is proposed. The gradients in all possible directions are calculated, then compare all of the possible gradients, and choose the largest gradient as the result. At the same time, in order to improve the precision and stability of auto-focusing algorithm, another threshold parameter is introduced. Through simulations and experiments, the algorithm has the characteristics such as strong single peak feature and good stability, which could decrease the impact of DOF to resolution of particle axial position.

关键词： Particle size

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Trends and Challenges of Sustainable Agriculture in the Iraqi Environment

Trends and Challenges of Sustainable Agriculture in the Iraq...

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Blockchain, Smart Healthcare and Emerging Technologies (SmartBlock4Health), IEEE International Conference on

作者： Hanan Hussein Al-asadi Maria Goga Haider Abdullah Ali Ramona Cristina Popa Awodele Oludele Faculty of Automatic Control and Computers University POLITEHNICA of Bucharest Bucharest Romania University of Technology-Iraq Baghdad Iraq UTCB Department for Training of Teaching Personnel Technical University of Civil Engineering of Bucharest Bucharest Romania Madenat Alelem University College Baghdad Iraq Faculty of Engineering in Foreign Languages University POLITEHNICA of Bucharest Bucharest Romania computer science department Babcock University Ogun State Nigeria

ISBN: (纸本)9781665460156

The use of Agriculture Intelligent Systems (AISs) in Iraq has become popular among farmers. The greenhouse is a solution for plant growth, which uses an effective microclimate to simulate seasons and to use alternative energy sources like solar, thermal, and photovoltaic systems for microclimate control. Greenhouses are considered a successful solution with developments and achievements in the technology of this field. However, problems like high costs, difficulties in installation and maintenance, or the need for some procedures should be considered. Because Iraq is close to the equator (3669 km), it receives sufficient solar power. It also has large areas available for the building of solar greenhouse systems. The farmers need an affordable and functional smart greenhouse to enable and encourage them to use the environment efficiently. We intend to develop low-cost, accurate, and easy-to-use greenhouse systems controlled by artificial intelligence algorithms. Farmers will be able to control the greenhouse by using simple commands. Machine learning algorithms provide real-time and effective analysis that could support farmers in decision-making and provide relevant data for researchers and policymakers. AISs algorithms can lead to a sustainable and productive agriculture system. The system can be used in Iraq with sufficient government support and subsidy.

关键词： Smart agriculture Machine learning algorithms Costs Green buildings Soil control systems Agriculture

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Initial Study on Implementation of Smoothing Filters for the Purpose of Bioimpedance Spectroscopy Parameters Classification

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IFAC-PapersOnLine 2022年第4期55卷 393-398页

作者： Aleksandra Kawala-Sterniuk Amir F. Al-Bakri Mariusz Pelc Katarzyna Cichoń Wojciech Chlewicki Stepan Ozana Radek Martinek Jakub Możaryn Volodymyr Khoma Halyna Kenyo Edward Jacek Gorzelańczyk Michał Podpora Jarosław Zygarlicki Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45-758 Opole Poland Department of Biomedical Engineering College of Engineering University of Babylon 51001 Babylon Iraq University of Greenwich School of Computing and Mathematical Sciences SE10 9LS London UK West Pomeranian University of Technology in Szczecin Faculty of Electrical Engineering 70-313 Szczecin Poland Faculty of Mechatronics Warsaw University of Technology 02-525 Warsaw Poland Lviv Polytechnic National University Institute of Computer Technologies Automation and Metrology Lviv Ukraine Institute of Philosophy Kazimierz Wielki University 85-092 Bydgoszcz Poland Faculty of Mathematics and Computer Science Adam Mickiewicz University in Poznań 61-614 Poznań Poland

Bioimpedance is a commonly used method for various conditions monitoring. In this paper, the authors carried out some research where they implemented various smoothing filters to enable identification of the bioimpedance spectroscopy parameters. The proposed filtering methods may also be used for application on embedded systems, which have smaller computing power but have become recently very popular. The obtained results with the implementation of smoothing filters were promising, however, some of the obtained results were unsatisfactory. This work also contains a brief introduction to bioimpedance spectroscopy and smoothing filters.

关键词： Bioimpedance Spectroscopy smoothing-filtering Savitzky-Golay Filter Median Filtering Moving-Average Filters

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A Topology for Five-Level Active Neutral Point-Clamped Inverter

SSRN

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SSRN 2023年

作者： Obe, Emeka Simon Mtengi, Bokani Amuhaya, Lilian Livutse Obe, Pauline Ijeoma Ugwuishiwu, Helen Chikodili Odeh, Charles Ikechukwu Department of Electrical Engineering University of Nigeria Nsukka Nigeria Department of Electrical Computer and Telecommunications Engineering Botswana International University of Science and Technology Palapye Botswana Department of Industrial Technical Education University of Nigeria Nsukka Nigeria Department of Computer Science University of Nigeria Nsukka Nigeria Department of Electric Drives and Energy Conversions Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdańsk Poland

A combination of two shared input splitting capacitor banks and varying number of individualized inverter-leg flying-capacitors characterized topological feature of a large group of 5L ANPC inverters configurations. The inconveniences in the provision of these per phase flying-capacitors make these configurations less attractive in most applications. The 5L E-type inverter, characterized by four shared input capacitor banks, becomes a viable alternative topology. However, the high blocking-voltage rating of the constituent switches still places restrictions on the use of the 5L E-type inverter within this voltage range. In view of this, this paper presents a reconfiguration of the 5L E-type inverter. To lessen the voltage stress on the switching devices used here, the common node of the E-type inverter’s bidirectional switch is investigated. Inverter costs and losses are influenced by the decreased voltage stress. The carrier-overlapped pulse-width modulation, or COPWM, perspective serves as the foundation for the inverter control technique. Simulated results of the inverter performances are presented together with an analysis of the cost competitiveness of the proposed inverter power circuit. A 17.68% reduction in loss dissipation and a 13.61% cost savings were recorded by using the proposed power circuit. © 2023, The Authors. All rights reserved.

关键词： Pulse width modulation

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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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Foreword

Lecture Notes in Electrical Engineering

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Lecture Notes in electrical engineering 2020年 554卷 v-vi页

作者： Zelinka, Ivan Brandstetter, Pavel Dao, Tran Trong Duy, Vo Hoang Kim, Sang Bong Department of Computer Science Faculty of Electrical Engineering VŠB-TUO Poruba Ostrava Czech Republic Department of Electronics Faculty of Electrical Engineering VŠB-TUO Ostrava Czech Republic International Cooperation Research and Training Institute Ton Duc Thang University Ho Chi Minh Viet Nam Department of Automatic Control Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Mechanical Design Engineering Pukyong National University Busan Korea Republic of

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Optimal Power control Based-Metaheuristic Algorithm Based Variable Speed Wind Energy System of DFIG

Optimal Power Control Based-Metaheuristic Algorithm Based Va...

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International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Boussaid Ibrahim Harrouz Abdelkader Merahi Farid Ibrahim Yaichi Ilhami Colak Korhan Kayisli Virgil Dumbrava Electrical Engineering Department Laboratory of sustainable development and computer science (LDDI) University of Adrar Adrar Algeria Laboratory of sustainable development and computer science (LDDI) University of Adrar Adrar Algeria Electrical Engineering Department Automatic Laboratory of Setif University of Ferhat Abbas Setif1 Setif Algeria Department of Electrical Electronics Eng. Faculty of Engineering Architecture Nisantasi University Istanbul Turkey Department of Electric Power Systems Polytechnic University of Bucharest Bucharest Romania

This article presents a novel method for controlling a doubly fed induction generator (DFIG) wind energy system in the presence of variable wind speeds. In order to achieve decoupling control of the active and reactive power, the rotor-side converter (RSC) of the DFIG is controlled using field-oriented control (FOC). The system is very complicated and nonlinear, making it challenging to adjust the PI gains appropriately. The present research proposes the utilization of the Grey Wolf Optimization (GWO) algorithm as an approach to optimize the gains of a Proportional-Integral (PI) regulator. The simulation results demonstrate that the GWO-PI provides a lower criterion value and an improved response than the conventional PI.

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Picture array generation using flat splicing operation

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3568-3577页

作者： Pan, Linqiang Nagar, Atulya K. Subramanian, K.G. Song, Bosheng School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

The operation of splicing on words was introduced by Tom Head while proposing a theoretical model of DNA recombination. Subsequent investigations on splicing on linear and circular strings of symbols have resulted in a number of theoretical properties. A different kind of splicing on two words, referred to as flat splicing, has been considered recently. This operation is extended to flat splicing on picture arrays, thus defining a new model of generation of digitized pictures, which is called as array flat splicing system (AFS). Results on the generative power of AFS in comparison with certain well-known picture array defining models and certain non-closure results are obtained. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Nanoscience

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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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The learning of fuzzy cognitive maps with noisy data: A rapid and robust learning method with maximum entropy

arXiv

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arXiv 2019年

作者： Feng, Guoliang Lu, Wei Pedrycz, Witold Yang, Jianhua Liu, Xiaodong School of Control Science and Engineering Dalian University of Technology Dalian116023 China School of Automation Engineering Northeast Electric Power University Jilin132012 China School of Control Science and Engineering Dalian University of Technology Dalian116023 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia

Numerous learning methods for fuzzy cognitive maps (FCMs), such as the Hebbian-based and the population-based learning methods, have been developed for modeling and simulating dynamic systems. However, these methods are faced with several obvious limitations. Most of these models are extremely time consuming when learning the large-scale FCMs with hundreds of nodes. Furthermore, the FCMs learned by those algorithms lack robustness when the experimental data contain noise. In addition, reasonable distribution of the weights is rarely considered in these algorithms, which could result in the reduction of the performance of the resulting FCM. In this article, a straightforward, rapid, and robust learning method is proposed to learn FCMs from noisy data, especially, to learn large-scale FCMs. The crux of the proposed algorithm is to equivalently transform the learning problem of FCMs to a classic-constrained convex optimization problem in which the least-squares term ensures the robustness of the well-learned FCM and the maximum entropy term regularizes the distribution of the weights of the well-learned FCM. A series of experiments covering two frequently used activation functions (the sigmoid and hyperbolic tangent functions) are performed on both synthetic datasets with noise and real-world datasets. The experimental results show that the proposed method is rapid and robust against data containing noise and that the well-learned weights have better distribution. In addition, the FCMs learned by the proposed method also exhibit superior performance in comparison with the existing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Fuzzy rules

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