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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Haoyu Zhang Shiqi Xing Sinong Quan State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System CEMEE National University of Defense Technology ChangSha China

In response to the problem that the validation and evaluation of SAR active jamming effectiveness is more complicated and target detection of SAR image is seldom applied to active jamming, a method of SAR image active jamming detection based on image grayscale features is proposed in this paper. Herein, the principle and process of SAR image target detection algorithm processing, based on pulse coupled neural network are discussed. Through the simulation experiment, the active jamming region can be detected in the SAR jamming image.

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Formation Control of Unmanned Surface Vehicle for Actuator Failure

Formation Control of Unmanned Surface Vehicle for Actuator F...

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第34届中国控制与决策会议

作者： Yunsheng Fan Xinle Shen Dongdong Mu Guofeng Wang Yongsheng Zhao College of Marine Electrical Engineering Dalian Maritime University Key Laboratory of Technology and System for Intelligent Ships of Liaoning Province

This paper solves formation control problem for unmanned surface vehicle(USV) under actuator *** on virtual pilot-following control strategy and adopting the guidance law,an adaptive backstepping control formation strategy based on a nonlinear disturbance observer is *** into account the influence of external disturbances on the navigation of the USV,a nonlinear disturbance observer is designed to estimate and compensate in the control law.A robust term is designed to compensate the actuator fault parameters and effectively solve the problem of USVs formation stability control under actuator *** into account the jamming of the actuators,the formation needs to be reconstructed to change the formation to ensure the smooth progress of the formation *** simulation proved the effective operation of the formation control strategy.

关键词： actuator failure disturbance observer formation control

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There is plenty of room at the top:generation of hot charge carriers and their applications in perovskite and other semiconductor-based optoelectronic devices

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Light(Science & Applications) 2021年第9期10卷 1630-1657页

作者： Irfan Ahmed Lei Shi Hannu Pasanen Paola Vivo Partha Maity Mohammad Hatamvand Yiqiang Zhan State Key Laboratory of ASIC and System Centre of Micro-Nano SystemSISTFudan University200433ShanghaiChina Department of Physics Government Postgraduate College(Higher Education Department-HED)Khyber Pakhtunkhwa21300MansehraPakistan State Key Laboratory of Surface Physics Key Laboratory of Micro-and Nano-PhotonicsFudan University200433ShanghaiChina Faculty of Engineering and Natural Sciences Tampere UniversityFI-33014TampereFinland KAUST Solar Center Division of Physical Science and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal23955-6900RiyadhKingdom of Saudi Arabia

Hot charge carriers(HC)are photoexcited electrons and holes that exist in nonequilibrium high-energy states of photoactive *** cooling time and rapid extraction are the current challenges for the development of future innovative HC-based optoelectronic devices,such as HC solar cells(HCSCs),hot energy transistors(HETs),HC photocatalytic reactors,and lasing *** on a thorough analysis of the basic mechanisms of HC generation,thermalization,and cooling dynamics,this review outlines the various possible strategies to delay the HC cooling as well as to speed up their *** materials with slow cooling behavior,including perovskites and other semiconductors,are thoroughly *** addition,the opportunities for the generation of plasmon-induced HC through surface plasmon resonance and their technological applications in hybrid nanostructures are discussed in *** judiciously designing the plasmonic nanostructures,the light coupling into the photoactive layer and its optical absorption can be greatly enhanced as well as the successful conversion of incident photons to HC with tunable energies can also be ***,the future outlook of HC in optoelectronics is highlighted which will provide great insight to the research community.

关键词： optoelectronic charge plenty

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Strategic Bidding Behavior Analysis with Truthfully Modeled Generator Output Range

Strategic Bidding Behavior Analysis with Truthfully Modeled ...

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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Yi Wang Zhifang Yang Juan Yu State Key Laboratory of Power Transmission Equipment & System Security and New Technology College of Electrical Engineering Chongqing University Chongqing China

As the foundation of the electricity market, the pricing scheme can affect the bidding behavior of market participants and thus determine the market clearing results. In this paper, we compare and analyze the characteristics of the strategic bidding behavior of generators and corresponding market clearing results with truthfully modeled generator output range under the pay-as-bid pricing scheme and locational marginal pricing scheme. First, we formulate the bi-level strategic bidding problems under two pricing schemes. Second, through the theoretical derivation, we show that the minimum output of the generator has a significant impact on the comparative conclusion between two pricing schemes, which is commonly neglected by existing studies. Then, considering the minimum output of the generator, the quantitative analysis of consumer payment and system operational cost under two pricing schemes is summarized. Finally, the numerical analysis shows some new insights about the comparative conclusion for two pricing schemes.

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Urban Damage Mapping With Reconstructed Quad-Pol SAR Data From Dual-Pol SAR mode

Urban Damage Mapping With Reconstructed Quad-Pol SAR Data Fr...

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General Assembly and Scientific Symposium, URSI

作者： Jun-Wu Deng Ming-Dian Li Hao-Liang Li Si-Wei Chen State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE) National University of Defense Technology Changsha China

Polarimetric synthetic aperture radar (PolSAR) has the advantage of all-day and all-weather work, which can obtain high-resolution radar images and polarimetric scattering matrix of the target. The dual polarimetric SAR can obtain a wider observation swath with lower energy budget than quad-pol SAR. In this paper, the pseudo quad-pol SAR data is reconstructed from dual polarization SAR data based on the proposed deep convolutional neural network. The urban damage level mapping index is established based on the co-polarization coherence pattern and the reconstructed quad-pol SAR data. The experiments have been conducted on the multi-temporal ALOS/PALSAR data from the March 11 Eastern Japan earthquake. Compared with the existing quad-pol SAR data reconstructed method, the proposed method has superior reconstruction performance. The quantitative experiment results indicate the proposed method can effectively achieve urban damage level mapping based on the dual polarization SAR data.

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Point cloud segmentation network based on multi-scale feature fusion

Point cloud segmentation network based on multi-scale featur...

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2024 China Automation Congress, CAC 2024

作者： Deng, Hao Cheng, Peng Cheng, Shengmei Liu, Cheng Du, Shaoyi Wang, Lin State-Province Joint Engineering and Research Center of Advanced Networking and Intelligent Information Service School of Information Science and Technology Northwest University Xi’an China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (纸本)9798350368604

Aiming at improving the local feature extraction for point cloud learning, we introduce a point cloud segmentation network that enhances the PointNet++ framework with a local feature transformation module and a multi-scale feature fusion module. The local feature transformation module employs operations akin to convolution to restructure the point cloud's local feature dimensions, thus boosting the network's ability to extract detailed local features. Additionally, the multi-scale feature fusion module integrates semantic features of point clouds across various scales using a layered network design, aiming to heighten segmentation precision. Experimental results indicate that the proposed network can achieve a robust point cloud segmentation accuracy, reaching an accuracy rate of 85.8%. © 2024 IEEE.

关键词： Cloud platforms

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Shape Optimization of Magnetorheological Brake for Performance Enhancement

Shape Optimization of Magnetorheological Brake for Performan...

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IEEE International Conference on Robotics and Biomimetics

作者： Qiuyu Shi Fajiang Liu Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Magnetorheological (MR) rotary brakes leverage the magnetically controllable rheological properties of MR fluids to provide damping torque in lower limb assistance devices. This paper utilizes an optimization algorithm (Whale Optimization Algorithm (WOA)) to optimize the geometric dimension of the MR brake to enhance field-dependent brake torque. First, the mechanical design and optimization process of the MR brake were outlined. Then, the magnetic density of the MR fluid is evaluated using the ANSYS platform. With that, the WOA was exploited to optimize key design parameters across multiple iterations. According to the simulated results, the torque was improved from 17.39 Nm to 25.89 Nm, which increased by 48%. Finally, a prototype with the initial dimension was fabricated and preliminarily tested.

关键词： Stator cores Torque Fluids Shape Magnetomechanical effects Prototypes Magnetic liquids Whale optimization algorithms Brakes Optimization

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Design of permanent magnet with high magnetic induction intensity and high uniformity based on Halbach array 7

Design of permanent magnet with high magnetic induction inte...

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7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering

作者： Hei, Guoyu Xu, Zheng Zhang, Bin Qu, Yongjie School of Electronic Information and Communication Engineering Chongqing Aerospace Polytechnic Chongqing400021 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China

ISBN: (纸本)9781510656437

Nuclear magnetic resonance (NMR) is a nondestructive testing technology, which is mainly used in the aging state detection of composite insulators in the field of electrical engineering. To detect the aging state of composite insulator by NMR technology, the most important is to establish a static magnetic field with high magnetic induction intensity and high uniformity, which will help to greatly improve the signal-to-noise ratio of detection signal and obtain more accurate aging state information. At present, the establishment method of static magnetic field is mostly based on permanent magnet, but the static magnetic field with high magnetic induction intensity and high uniformity requires a large permanent magnet sensor, which does not have portability, so the detection scene is limited. In order to solve the problem of limited detection scene, a permanent magnet structure based on Halbach array is studied in this paper. The space volume is small and easy to carry. The magnetic induction intensity can reach 1.2T and the magnetic field uniformity can reach less than 10ppm. © 2022 SPIE. All rights reserved.

关键词： Permanent magnets

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Enhancing Robotics Online 3D Bin Packing: A Comparative Study of Conventional Heuristic and Deep Reinforcement Learning Approaches

Enhancing Robotics Online 3D Bin Packing: A Comparative Stud...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Heng Xiong Kai Ding Wan Ding Xuchong Qiu Klaus Janschek Jianfeng Xu State Key Laboratory of Intelligent Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China BOSCH Corporate Research Technische Universität Dresden Germany

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Robotic object packing holds a wide array of practical applications across logistics and manufacturing sectors. The online 3D Bin Packing Problem (BPP) is a challenging task that involves online packing of three-dimensional boxes into a container while considering constraints and objectives. Unlike the offline version, where all boxes are known in advance, the online variant requires decisions about how to pack each box as it arrives, without prior knowledge of upcoming *** maximize space utilization, our study explores two distinct strategies: conventional heuristics-based algorithms and a deep reinforcement learning (DRL)-based approach. For the heuristic strategy, we propose four heuristic criteria alongside two variants of multi-objective optimization (MOO) algorithms. Quantitative experiments reveal that MOO outperforms single-objective approaches for online bin packing. In our DRL-based approach, we introduce a framework that leverages a candidate map that indicates the potentially feasible placements, ensuring a balanced exploration and exploitation in the considerable discrete action space. Experiments demonstrate the superior performance of our DRL-based approach compared to both DRL-based baseline methods and conventional approaches. Additionally, we discuss the limitations of DRL-based methods and offer practical recommendations for real-world applications.

关键词： Three-dimensional displays Computer aided software engineering Heuristic algorithms Containers Deep reinforcement learning Explosions Manufacturing Robots Optimization Logistics

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Fast Probabilistic TTC Assessment Based on Copula Theory and Deep Ensemble Learning 7

Fast Probabilistic TTC Assessment Based on Copula Theory and...

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7th Asia Conference on Power and Electrical Engineering, ACPEE 2022

作者： Zhang, Shaopeng Yan, Jiongcheng Li, Xin Yang, Dong Ma, Huan Li, Changgang Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong Jinan China State Grid Shandong Electric Power Company Shandong Jinan China Electric Power Research Institute State Grid Shandong Electric Power Company Shandong Jinan China

ISBN: (纸本)9781665418195

Wind power integration makes the uncertainty of power system increasing dramatically, which brings new challenges to the calculation of Total Transfer Capability (TTC). A fast assessment method for probabilistic TTC based on Copula and deep ensemble learning is proposed. Considering wind power output uncertainties and correlation of wind speed in geographical close wind farms, Copula function is adopted to generate scenarios. Stacked Denoising Autoencoder (SDAE) is used to extract features directly from source data. Support Vector Regression (SVR) is selected as regressor and bagging ensemble strategy is applied to further improve the accuracy of the TTC estimation. The case study in simplified Shandong grid validates the effectiveness of the proposed method. © 2022 IEEE.

关键词： Learning systems

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