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9th Computer Science On-line Conference, CSOC 2020

作者： Pokorný, Pavel Ševčík, Daniel Department of Computer and Communication Systems Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 05 Czech Republic Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 05 Czech Republic

ISBN: (纸本)9783030519643

Nowadays, many technical devices are controlled by logic circuits. These circuits evaluate the situation based on the proposed truth functions, which they then use to perform one of the defined actions. In line with the increasing complexity of individual technical devices, the logic circuits and truth functions are also increasingly complex. For this reason, it makes sense to minimise these functions since they can thereby achieve a simpler technological process and the higher reliability of whole logic systems. This paper describes the Karnaugh Studio application, which resolves the minimisation of these truth functions - and was developed at our faculty (FAI, TBU in Zlín). The minimisation is performed using the Karnaugh Map Method - with support for up to eight variables on input. The application is based on the C++ programming language and the Dear ImGui and Magick++ libraries. Its functionality has been verified on a number of examples. This proved its applicability and ability to be used in the solution of logic circuits in industrial practice. © 2020, Springer Nature Switzerland AG.

关键词： Boolean functions

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Data-driven leak localization in water distribution networks via dictionary learning and graph-based interpolation

arXiv

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arXiv 2021年

作者： Irofti, Paul Romero-Ben, Luis Stoican, Florin Puig, Vicenç Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Romania Institut de Robòtica i Informàtica Industrial Universitat Politècnica de Catalunya Barcelona Spain Politehnica University of Bucharest Dept. of Automation Control and Systems Engineering Romania

In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete WDN hydraulic state (i.e., hydraulic heads) from real measurements at certain nodes and the network graph. Then, these actual measurements, together with a subset of valuable estimated states, are used to feed and train the dictionary learning scheme. Thus, the meshing of these two methods is explored, showing that its performance is superior to either approach alone, even deriving different mechanisms to increase its resilience to classical problems (e.g., dimensionality, interpolation errors, etc.). The approach is validated using the L-TOWN benchmark proposed at BattLeDIM2020. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems

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What is the cost and potential of low carbon electricity transition in the MENA region?

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Energy Strategy Reviews 2025年 59卷

作者： Bamisile, Olusola Xing, Yankai Acen, Caroline Cai, Dongsheng Zhang, Guangdou Adun, Humphrey Staffell, Iain Electrical Engineering Department College of Nuclear Science and Automation Engineering Chengdu University of Technology Sichuan China Centre for Environmental Policy Faculty of Natural Science Imperial College London United Kingdom Energy and Environmental Science Division CEPMLP University of Dundee United Kingdom Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University China Operational Research Centre in Healthcare Near East University TRNC Mersin 10 Nicosia99138 Turkey

Replacing fossil fuels with renewable energy sources, including wind and solar power, is a validated approach for mitigating carbon emissions. To maximize renewable energy potential and account for costs and impacts of low carbon energy transitions, research models or modelling tools must provide an accurate representation of the technological and economic capabilities of renewable energy technologies. Hence, this study assesses the electricity generation potential, and costs associated with onshore and offshore wind power, and solar photovoltaic (PV) system, in the Middle East and North Africa (MENA) region based on wind and solar atlas datasets. Unlike existing works in literature, the assessment of offshore wind energy potential and the calculation of the levelized cost of electricity (LCOE) in this study incorporates factors like water depth, distance from shore, and wind speed. Also, the potential of onshore wind energy and solar photovoltaic systems is evaluated by considering variables such as population density, availability of suitable land area, and geographical location, for every grid cell in the MENA region. We found that the average LCOE can be as low as US$40/MWh for solar PV and US$45/MWh for wind power, achieved in Saudi Arabia and Kuwait respectively. This work contributes to existing literature by providing reliable LCOE, capacity factor, and productivity data for solar and wind energy potential estimation in the MENA region. © 2025 The Authors

关键词： Solar fuels

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Optimization and economic assessment of renewable energy sources and their combinations for Central Europe

Optimization and economic assessment of renewable energy sou...

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23rd International Conference on Circuits, Systems, Communications and Computers, CSCC 2019

作者： Skovajsa, Jan Zálešák, Martin Tomas Bata University in Zlin Faculty of Applied Informatics Department of Automation and Control Engineering Nad Stranemi 4511 Zlin Czech Republic

The article deals with the economic evaluation of investment and optimization of the renewable energy sources for family houses. For example, from the point of view of solar systems, the optimal solution is based on the specific application of it. The design is dependent on the location of the panels and ration between active aperture area and real daytime consumption. Common calculations according to actual standards often give overstated results, which also reflected in the value of the investments. The article shows the research of optimal parameters of the thermal solar system for preparing of domestic hot water. A combination of related standards and software TRNSYS are used to find optimal parameters. Thanks to created and verified simulation models, it is possible to design parameters so as to avoid under-dimensioning or over-dimensioning of the each system. Energy price is another factor affects the payback period of investments. This is affected by the used energy sources and their combination. For example, buildings that use electricity to heat water or heating have different energy charges than a building that uses natural gas. So, the aim is to find optimal solution of the combination of renewable energy sources. © 2019 The Authors, published by EDP Sciences.

关键词： Investments

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Automated Leukemia Screening and Sub-types Classification Using Deep Learning

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Computer Systems Science & engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

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EEG-Based Brain-Computer Interfaces Are Vulnerable to Backdoor Attacks

Research Square

引用

Research Square 2021年

作者： Meng, Lubin Huang, Jian Zeng, Zhigang Jiang, Xue Yu, Shan Jung, Tzyy-Ping Lin, Chin-Teng Chavarriaga, Ricardo Wu, Dongrui Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Brainnetome Center and National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China La Jolla CA United States Center for Advanced Neurological Engineering Institute of Engineering in Medicine UCSD La Jolla CA United States Centre of Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Australia ZHAW DataLab Zürich University of Applied Sciences Winterthur8401 Switzerland

Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to the wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks, e.g., the attacker can add tiny adversarial perturbations to a test sample to fool the model, or poison the training data to insert a secret backdoor. Previous research has shown that adversarial attacks are also possible for EEG-based BCIs. However, only adversarial perturbations have been considered, and the approaches are theoretically sound but very difficult to implement in practice. This article proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which is more feasible in practice and has never been considered before. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the training set. Test samples with the backdoor key will then be classified into the target class specified by the attacker. What most distinguishes our approach from previous ones is that the backdoor key does not need to be synchronized with the EEG trials, making it very easy to implement. The effectiveness and robustness of the backdoor attack approach is demonstrated, highlighting a critical security concern for EEG-based BCIs. © 2021, CC BY.

关键词： Electroencephalography

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Experimental Prototype of High-Efficiency Wind Turbine Based on Magnus Effect

Experimental Prototype of High-Efficiency Wind Turbine Based...

引用

International Workshop on Electric Drives: Optimization in control of Electric Drives (IWED)

作者： Aleksandr Lukin Galina L. Demidova Dmitry V. Lukichev Anton Rassõlkin Ants Kallaste Toomas Vaimann Anouar Belahcen Faculty of Control System and Robotics ITMO University Saint Petersburg Russia Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallin Estonia Department of Electrical Engineering and Automation Aalto University Helsinki Finland

ISBN: (数字)9781728141589

ISBN: (纸本)9781728141596

The main feature of Magnus wind turbine is the ability to produce energy at low wind speed. This benefit lets to use such types of turbines in smart homes, which are an important part of the development of distributed energy systems, growth of blockchain electricity technology and needs for duplication of the solar energy system in the private buildings. This paper presents topology of two cylinders Magnus wind turbine in order to ensure the highest values of power coefficient and the Magnus force. The optimal ratio of wind speed and cylinder rotation speed were detected to eliminate the oscillations caused by the Von Karman vortex street phenomenon.

关键词： Wind turbines Force Drag Rotors Mathematical model Wind speed Generators

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A PCNN model for infrared pedestrian segmentation in complex environments

引用

Infrared Physics and Technology 2025年 149卷

作者： Cao, Honggui Ye, Bo Zou, Yangkun Zhu, Zhizhen Wan, Zijie Yin, Shsoda Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China Faculty of Civil Aviation and Aeronautics Kunming University of Science and Technology Kunming650500 China The First Military Representative Office of the Chongqing Military Representative Bureau of the Army Equipment Department Kunming650500 China

Pulse Coupled Neural Network (PCNN) is widely used in infrared pedestrian image segmentation. Due to the complex background, heat source interference, uneven brightness distribution of human targets and easy aliasing with the background in infrared pedestrian images, the segmentation of human targets is incomplete and the segmentation effect is poor. An improved PCNN algorithm for segmenting infrared pedestrian targets in complex environments and a new idea of preferentially segmenting background regions are proposed. The infrared pedestrian image is represented as a graph structure, and the superpixels in the infrared image are represented as nodes of the graph. The score of each node becoming the background region is evaluated by analyzing the structure of the graph, and the score is mapped to the original image as the connection strength of the model. Correspondingly, the dynamic threshold is set as the clustering center of the image background, and the background region of the image is prioritized for classification and output. Infrared pedestrian images with complex environment can be effectively segmented by the model, especially for infrared images with more heat source interference in the background. © 2025 The Authors

关键词： Image segmentation

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Magnus Wind Turbine: Finite Element Analysis and control System

Magnus Wind Turbine: Finite Element Analysis and Control Sys...

引用

International Symposium on Power Electronics, Electrical Drives, automation and Motion, SPEEDAM

作者： Galina L. Demidova Alecksey Anuchin Aleksandr Lukin Dmitry Lukichev Anton Rassõlkin Anouar Belahcen Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia Department of Electrical Engineering and Automation Aalto University Helsinki Finland

ISBN: (数字)9781728170190

ISBN: (纸本)9781728170206

Due to its special features, the Magnus effect wind turbine allows you to produce energy at a very low speed of the wind. This fact, as well as the growing interest in the of blockchain technology, makes it possible to use this type of wind turbine in private household as part of a distributed energy system in addition to solar panels. The article describes a two blades Magnus wind turbine whose cylinders rotate by means of embedded motors. To avoid a von Karman vortex street effect that occur when the cylinders rotate in the air flow, as well as to ensure maximum power, the optimal ratio between the wind speed and the cylinder rotation speed is determined using finite element analysis. Further, the obtained relations are used in the algorithms of the wind turbine control system.

关键词： Wind turbines Force Wind speed Generators Mathematical model Torque control systems

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Weak Scratch Detection of Optical Components Using Attention Fusion Network

Weak Scratch Detection of Optical Components Using Attention...

引用

IEEE International Conference on automation Science and engineering (CASE)

作者： Xian Tao Dapeng Zhang Avinash K Singh Mukesh Prasad Chin-Teng Lin De Xu Chinese Academy of Sciences Research Center of Precision Sensing and Control Institute of Automation Beijing China faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Scratches on the optical surface can directly affect the reliability of the optical system. Machine vision-based methods have been widely applied in various industrial surface defect inspection scenarios. Since weak scratches imaging in the dark field has an ambiguous edge and low contrast, which brings difficulty in automatic defect detection. Recently, many existing visual inspection methods based on deep learning cannot effectively inspect weak scratches due to the lack of attention-aware features. To address the problems arising from industry-specific characteristics, this paper proposes “Attention Fusion Network;”, a convolutional neural network using attention mechanism built by hard and soft attention modules to generate attention-aware features. The hard attention module is implemented by integrating the brightness adjustment operation in the network, and the soft attention module is composed of scale attention and channel attention. The proposed model is trained on a real-world industrial scratch dataset and compared with other defect inspection methods. The proposed method can achieve the best performance to detect the weak scratch inspection of optical components compared to the traditional scratch detection methods and other deep learning-based methods.

关键词： Conferences automation Computer aided software engineering

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