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International Conference on Actual Problems of Applied Mathematics and computer Systems, APAMCS 2022

作者： Gautam, Nandita Basu, Abhishek Kaplun, Dmitry Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata India Department of Computer Science and Engineering National Institute of Technology Durgapur Durgapur India Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9783031341267

One of the most common types of cancer in the world is lung cancer, which is a cause of increasing mortality. It is most often discovered in the middle and later stages as it does not have obvious symptoms due to which its treatment is often missed. Studies show that most lung cancers are in the form of lung nodules, which can be categorized as benign or malignant. Thus, accurate early identification of malignant lung nodules that might later become cancerous is essential for the prevention of lung cancer. Computed Tomography (CT) images can be useful for identifying and segmenting these nodules. In this paper, we propose an ensemble model, called BUS-UNet++, to segment lung nodules using CT images. We use a combination of the ConvLSTM up-sampling architecture from BUS-UNet and skip connections in aggregation blocks from the UNet++ model to build the BUS-UNet++ ensemble. The dataset for this study is collected from the Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI), where we have selected the modality of these images as CT images. These are further preprocessed to obtain nodule masks and nodule images, which constitute the Region of Interest (RoI). The accuracy achieved with the Adam Optimizer is 0.9731, the Intersection over Union (IoU) of about 0.8439, and the dice score coefficient (DSC) of about 0.958 are obtained by the proposed system. This ensemble model outperforms several state-of-the-art models used for the same purpose. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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Development of ANFIS Controller for Trajectory Tracking Control Using ROBO2L MATLAB Toolbox for KUKA Industrial Robot via RSI 21

Development of ANFIS Controller for Trajectory Tracking Cont...

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21st International Multi-Conference on Systems, Signals and Devices, SSD 2024

作者： Mousa, Mohamed Al-Mahasneh, Ahmad Baniyounis, Mohammed Biesenbach, Rolf Falkenhain, Jan Philadelphia University Mechatronics Engineering Department Amman Jordan Institute for Automation and Industry 4.0 Bochum University of Applied Sciences Bochum Germany Bochum University of Applied Sciences Electrical Engineering and Computer Science Department Bochum Germany

ISBN: (纸本)9798350374131

A new control scheme is proposed in the MATLAB/Simulink environment based on ANFIS technology using ROBO2L MATLAB toolbox with RSI to control the motion of the real KUKA robot. In detail, the control system has two subsystems designed for trajectory tracking error regulation in closed-loop control. One is a fuzzy logic controller, and the other is an ANFIS controller. These two controllers were used to control the velocity of the KUKA robot located inside the Hochschule Bochum laboratory. The testing process for these controllers was done by switching between FLC and ANFIS controllers and then studying each response separately. The results were compared with a linear controller produced in Hochschule Bochum experiments. The ROBO2L MATLAB toolbox provides many functions, such as sending and receiving positions and rotation for the end effector via UDP/IP communication, which RSI established to provide remote control for the robot using a PC. This work mainly emphasizes the ability to track the trajectories supported by the robotics toolbox in smooth motion. After observing the simulation results, the comparison between the linear, FLC, and ANFIS controllers is confirmed. The performance of the proposed approach is efficient for trajectory tracking control for the manipulator. © 2024 IEEE.

关键词： Controllers

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Toward quantum unmanned systems

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Science China(Technological Sciences) 2024年第7期67卷 2277-2280页

作者： CHENG ShuMing QI HongSheng SUN Yue LIU LiJun XIE ShaoRong REN XiaoQiang Department of Control Science and Engineering Tongji UniversityShanghai 200092China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Cipher Cloud Core Ltd. Beijing 100085China College of Mathematics and Computer Science Shanxi Normal UniversityLinfen 041081China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China

1 Quantum information technology Quantum information technology utilizes physical systems at the microscopic level, such as photon, atom, ion, and superconducting, to accomplish information-processing tasks that are impossible for the classical macroscopic world. During the past decade, significant process has been achieved in the pursuit of quantum technology into practical applications,generating great research interest from various domains, with the potential to radically change our information infrastructure [1–3].

关键词： quantum utilize generating

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Analysis of Electric Arc Furnace Influence on Power Quality in Low and Medium Voltage Networks 24

Analysis of Electric Arc Furnace Influence on Power Quality ...

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24th EEEIC International Conference on Environment and Electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Grabowski, Dariusz Klimas, MacIej Lange, Andrzej Silesian University of Technology Faculty of Electrical Engineering Department of Electrical Engineering and Computer Science Gliwice Poland University of Warmia and Mazury Faculty of Technical Sciences Department of Electrical and Power Eng. Electronics and Automation Olsztyn Poland

ISBN: (纸本)9798350355185

This paper focuses on analyzing power quality issues resulting from electric arc furnace operation. It highlights the challenges posed by the stochastic nature of the arc and proposes strategies to mitigate its impact on the power grid. Through measurements carried out on the medium and low voltage side of the furnace, fluctuations in parameters such as voltage, current, and power factor were observed, indicating significant disturbances in power quality. Mitigation strategies, including e.g. installing compensators, are suggested to stabilize the network and improve power quality, enhancing efficiency and reducing energy consumption and electrode usage. © 2024 IEEE.

关键词： Electric arc furnaces

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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

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computer Modeling in engineering & Sciences 2023年第12期137卷 2163-2192页

作者： Ali S.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： Stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

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Virtual Synchronous Generator Droop Control for Renewable Energy Sources

Virtual Synchronous Generator Droop Control for Renewable En...

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2024 IEEE Global Energy Conference, GEC 2024

作者： Cakmak, Fevzi Aykat, Sukru Kazanbaş, Mehmet Cemil Akgul, Sabahattin Department of Electricity and Energy Mardin Atuklu University Mardin Turkey Department of Computer Engineering Mardin Atuklu University Mardin Turkey Department of Control and Automation Engineering Yildiz Technical University Istanbul Turkey Department of Handicrafts Mardin Atuklu University Mardin Turkey

ISBN: (纸本)9798331532611

The connection of large-scale RES (renewable energy source) to the grid and the increase in the efficiency of energy production also causes different power quality problems. It has become mandatory for these inverter-based systems to participate in load frequency control. For this purpose, the design and simulation of a virtual synchronous generator (VSG), which enables RES to operate like synchronous generators, has been carried out in Matlab/Simulink environment. It is observed that the VSG keeps the load frequency stable according to different load conditions. ©2024 IEEE.

关键词： Synchronous generators

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Heterogeneous multi-player imitation learning

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Control Theory and Technology 2023年第3期21卷 281-291页

作者： Bosen Lian Wenqian Xue Frank L.Lewis Department of Electrical and Computer Engineering Auburn UniversityAuburnAL 36849USA State Key Laboratory of Synthetical Automation for Process Industries and International Joint Research Laboratory of Integrated Automation Northeastern UniversityShenyang 110819LiaoningChina UTA Research Institute University of Texas at Arlington(UTA)Fort WorthTX 76118USA

This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input *** propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the cost functions of a N-player Nash expert system given the expert's states and control *** allows us to address the imitation learning problem without prior knowledge of the expert's system *** achieve this,we provide a basic model-based algorithm that is built upon RL and inverse optimal *** serves as the foundation for our final model-free inverse RL algorithm which is implemented via neural network-based value function *** analysis and simulation examples verify the methods.

关键词： Imitation learning Inverse reinforcement learning Heterogeneous multi-player games Data-driven model-free control

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computer Modeling in engineering & Sciences 2022年第11期133卷 377-387页

作者： Angyan Tu Jiancheng Chen Bing Wang School of Mechatronic Engineering and Automation Shanghai UniversityShanghai200444China Department of Computer Science and Engineering Shaoxing UniversityShaoxing312000China Zhejiang Industry Polytechnic College Shaoxing312000China

A neutrosophic multi-valued set(NMVS)is a crucial representation for true,false,and indeterminate multivalued ***,a consistent single-valued neutrosophic set(CSVNS)can effectively reflect the mean and consistency degree of true,false,and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in ***,there has been no research on consistent single-valued neutrosophic similarity measures in the existing *** paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued *** cosine similarity measures showthe cosine of the angle between two vectors projected into amultidimensional space,rather than their *** cotangent similaritymeasures in this study can alleviate several shortcomings of cosine similarity measures in vector space to a certain ***,a decisionmaking approach is presented in viewof the established cotangent similarity measures in the case of ***,the developed decision-making approach is applied to selection problems of potential *** proposed approach has obtained two different results,which have the same sort sequence as the compared *** decision results prove its validity and ***,it also provides a new manner for neutrosophic multi-valued decision-making issues.

关键词： Neutrosophic multi-valued set consistency single-valued neutrosophic sets cotangent similarity measure multiple attribute decision-making

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Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 231-239页

作者： Yahui Liu Bin Tian Yisheng Lv Lingxi Li Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190 IEEE the Transportation and Autonomous Systems Institute(TASI)and the Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis(IUPUI)Indianapolis 46202 USA

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://***/yahuiliu99/PointC onT.

关键词： Content-based Transformer deep learning feature aggregator local attention point cloud classification

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Formation Control and Sub-Swarm Generation of Multirotor UAVs

Formation Control and Sub-Swarm Generation of Multirotor UAV...

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2023 International Conference on Robotics and automation in Industry, ICRAI 2023

作者： Shahzad, Muhammad Muzamal Asad, Muhammad Haroon Haris, Muhammad Munawar, Hammad Yousaf, Muhammad Haroon University of Engineering and Technology Taxila Swarm Robotics Lab National Center of Robotics and Automation Taxila Pakistan University of Engineering and Technology Taxila Computer Engineering Department Taxila Pakistan

ISBN: (纸本)9781665464727

The research field of collective behaviors takes inspiration from natural self-organizing systems like honeybees, fish schools, social insects, bird flocks, and other social animals. These behaviors can be transformed into robots by replicating the same set of rules as found in the natural swarms. The deployment of aerial swarm robotics has become significant due to their multiple applications in surveillance, agriculture, and military. These applications lead to the development of aerial swarm robotic platforms to solve real-world problems. For example, a swarm of low-tech, cost-effective small UAVs can engage a high-tech target effectively. Similarly, a swarm of UAVs can perform surveillance and rescue missions in disastrous areas and build an emergency communication network through multiple UAV swarms. The critical part of swarm technology is multiple swarm intelligence algorithms that have been proposed and tested by various simulation platforms such as V-rep, Gazebo and MATLAB. Very few of them have been deployed on hardware to solve real scenarios that include formation control, navigation, pattern formation, and a few sub-swarm generation algorithms. Team connectivity is one of the essential aspects of a swarm network that emerges the collective intelligence of the group and ensures the readiness of the algorithm to deploy and solve real-world problems. Many researchers proposed the team connectivity algorithms in a single swarm network but still left the connectivity gap between the sub-swarms during a mission. This research work contributes toward designing a swarm intelligence algorithm to improve the connectivity techniques and team connectivity between the swarm agents and the sub-swarm groups. © 2023 IEEE.

关键词： Antennas

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