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1st IEEE China International Youth Conference on Electrical Engineering, CIYCEE 2020

作者： Wei, Yiheng Xu, Zhiren Cheng, Huanchao Yang, Lijun Meng, Xiangdi Chongqing University State Key Lab. of Transmission Distribution Equipment and Power System Safety and New Technology Chongqing400044 China China Electric Power Research Institute Beijing100085 China

ISBN: (纸本)9781728196596

The insulation field strength of the UHV transformer is close to the design limit, which leads to the continuous increase of the working field strength of the oilpaper insulation structure. In order to explore the correlation between the development of PD and surface discharge marks on pressboard under high field strength, this paper used an extremely uneven electric field with a strong vertical component to study the development process of discharge marks and PD parameters under high field strength. The research found that PD under high field strength could cause serious damage to pressboard, resulted in white marks, spark discharge channels and carbonized marks. Based on the discharge repetition rate and discharge energy, the PD could be divided into three stages named initial stage, fast extension stage and near breakdown stage respectively. The development of cumulative discharge energy and the growth of carbonized mark have the same law in three stages. © 2020 IEEE.

关键词： Oil filled transformers

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Gan/Moo3 N-N Heterojunction Based Anti-Humidity Gas Sensor for No2 Real-Time Monitoring

SSRN

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SSRN 2024年

作者： Hong, Yutao Han, Dan Duan, Qi Li, Donghui He, Xiuli Li, Bing Liang, Hua Li, Hongwei Sang, Shengbo Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Integrated Circuits Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of Technology Taiyuan030024 China State Key Laboratory of Transducer Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials Shanxi Medical University School and Hospital of Stomatology Shanxi Taiyuan030001 China Shanxi Province Cancer Hospital Shanxi Hospital Affiliated to Cancer Hospital Chinese Academy of Medical Sciences Cancer Hospital Affiliated to Shanxi Medical University Taiyuan030000 China University of Chicago United States

Effective and accurate detection of NO2 gas is crucial for protecting the environment and public health. In this work, balsam pear-like GaN/MoO3 porous nanosheets (GaN/MoO3) composites were synthesized by in situ assembling, the hydrothermal method, and the nitridation process to detect NO2. A series of characterization methods were used to manifest the successful synthesis and to analyze the morphology and elemental composition features of GaN/MoO3 composites. The results of the gas-sensing experiments show that, at the operating temperature of 225°C, the gas sensor based on the optimal ratio of GaN/MoO3 composites exhibits a 25-fold lower limit of detection for NO2 than that of MoO3, with a reduction of baseline resistance drift. Further, the response value of the sensor based on GaN/MoO3 composites to 200 ppm NO2 (44.74) is 4.36 times higher than that of the sensor based on pure GaN, with an improvement in stability. Meanwhile, the sensor possessed excellent repeatability, selectivity, stability, and splendid anti-humidity ability at 15-70% RH. The improved gas-sensing performance is ascribed to the unique microstructure of both GaN and MoO3 and the heterojunction effect between them. In addition, we constructed a real-time NO2 monitoring device based on the gas-sensing characteristic of GaN/MoO3, which realizes the alarm of excessive concentrations of NO2. Overall, this work provides a way to improve the ability of NO2 monitoring for the sensors of MoO3-based composites. © 2024, The Authors. All rights reserved.

关键词： Gallium nitride

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Gan/Moo3 N-N Heterojunction Based Anti-Humidity Gas Sensor for No2 Real-Time Monitoring

SSRN

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SSRN 2024年

作者： Hong, Yutao Han, Dan Duan, Qi Li, Donghui He, Xiuli Li, Bing Liang, Hua Li, Hongwei Sang, Shengbo Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Integrated Circuits Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China State Key Laboratory of Transducer Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials Shanxi Medical University School Hospital of Stomatology Shanxi Taiyuan030001 China Shanxi Province Cancer Hospital Shanxi Hospital Affiliated to Cancer Hospital Chinese Academy of Medical Sciences Cancer Hospital Affiliated to Shanxi Medical University Taiyuan030000 China University of Chicago United States

Effective and accurate detection of NO2 gas is crucial for protecting the environment and public health. In this work, balsam pear-like GaN/MoO3 porous nanosheets (GaN/MoO3) composites were synthesized by in situ assembling, the hydrothermal method, and the nitridation process to detect NO2. A series of characterization methods were used to manifest the successful synthesis and to analyze the morphology and elemental composition features of GaN/MoO3 composites. The results of the gas-sensing experiments show that, at the operating temperature of 225℃, the gas sensor based on the optimal ratio of GaN/MoO3 composites exhibits a 25-fold lower limit of detection for NO2 than that of MoO3, with a reduction of baseline resistance drift. Further, the response value of the sensor based on GaN/MoO3 composites to 200 ppm NO2 (44.74) is 4.36 times higher than that of the sensor based on pure GaN, with an improvement in stability. Meanwhile, the sensor possessed excellent repeatability, selectivity, stability, and splendid anti-humidity ability at 15-70% RH. The improved gas-sensing performance is ascribed to the unique microstructure of both GaN and MoO3 and the heterojunction effect between them. In addition, we constructed a real-time NO2 monitoring device based on the gas-sensing characteristic of GaN/MoO3, which realizes the alarm of excessive concentrations of NO2. Overall, this work provides a way to improve the ability of NO2 monitoring for the sensors of MoO3-based composites. © 2024, The Authors. All rights reserved.

关键词： III-V semiconductors

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Metasurfaces for manipulating terahertz waves

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Light(Advanced Manufacturing) 2021年第2期2卷 40-64页

作者： Xiaofei Zang Bingshuang Yao Lin Chen Jingya Xie Xuguang Guo Alexei VBalakin Alexander P.Shkurinov Songlin Zhuang Terahertz Technology Innovation Research Institute Terahertz Spectrum and Imaging Technology Cooperative Innovation CenterShanghai Key Lab of Modern Optical SystemUniversity of shanghai for Science and TechnologyShanghai 200093China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai200092China Department of Physics and International Laser Center Lomonosov Moscow State UniversityLeninskie Gory 1Moscow 19991 Russia ILIT RAS-Branch of the FSRC《Crystallography and Photonics》RAS Svyatoozerskaya 1140700ShaturaMoscow RegionRussia

Terahertz(THz)science and technology have attracted significant attention based on their unique applications in non-destructive imaging,communications,spectroscopic detection,and ***,traditional THz devices must be sufficiently thick to realise the desired wave-manipulating functions,which has hindered the development of THz integrated systems and ***,which are two-dimensional metamaterials consisting of predesigned meta-atoms,can accurately tailor the amplitudes,phases,and polarisations of electromagnetic waves at subwavelength resolutions,meaning they can provide a flexible platform for designing ultra-compact and high-performance THz *** review focuses on recent advancements in metasurfaces for the wavefront manipulation of THz waves,including the planar metalens,holograms,arbitrary polarisation control,special beam generation,and active metasurface *** ultra-compact devices with unique functionality make metasurface devices very attractive for applications such as imaging,encryption,information modulation,and THz *** progress report aims to highlight some novel approaches for designing ultra-compact THz devices and broaden the applications of metasurfaces in THz science.

关键词： surfaces designing attractive

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Traj-LLM: A New Exploration for Empowering Trajectory Prediction with Pre-trained Large Language Models

arXiv

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arXiv 2024年

作者： Lan, Zhengxing Li, Hongbo Liu, Lingshan Fan, Bo Lv, Yisheng Ren, Yilong Cui, Zhiyong The School of Transportation Science and Engineering Beihang University Beijing100191 China The State Key Lab of Intelligent Transportation System Beijing100191 China The Research Institute for Frontier Science Beihang University Beijing100191 China The Beijing Key Laboratory of Traffic Engineering College of Metropolitan Transportation Beijing University of Technology Beijing100124 China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The Zhongguancun Laboratory Beijing100194 China The Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China

Predicting the future trajectories of dynamic traffic actors is a cornerstone task in autonomous driving. Though existing notable efforts have resulted in impressive performance improvements, a gap persists in scene cognitive and understanding of the complex traffic semantics. This paper proposes Traj-LLM, the first to investigate the potential of using Large Language Models (LLMs) without explicit prompt engineering to generate future motion from agents’ past/observed trajectories and scene semantics. Traj-LLM starts with sparse context joint coding to dissect the agent and scene features into a form that LLMs understand. On this basis, we innovatively explore LLMs’ powerful comprehension abilities to capture a spectrum of high-level scene knowledge and interactive information. Emulating the human-like lane focus cognitive function and enhancing Traj-LLM’s scene comprehension, we introduce lane-aware probabilistic learning powered by the pioneering Mamba module. Finally, a multi-modal Laplace decoder is designed to achieve scene-compliant multi-modal predictions. Extensive experiments manifest that Traj-LLM, fortified by LLMs’ strong prior knowledge and understanding prowess, together with lane-aware probability learning, outstrips state-of-the-art methods across evaluation metrics. Moreover, the few-shot analysis further substantiates Traj-LLM’s performance, wherein with just 50% of the dataset, it outperforms the majority of benchmarks relying on complete data utilization. This study explores equipping the trajectory prediction task with advanced capabilities inherent in LLMs, furnishing a more universal and adaptable solution for forecasting agent motion in a new way. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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AU Nanoparticles Decorated Gan Nanoflowers with Enhanced Nh3 Sensing Performance at Room Temperature

SSRN

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SSRN 2023年

作者： Han, Dan Chen, Yi Li, Donghui Shi, Jiexu Wang, Hongtao He, Xiuli Zhao, Li Wang, Weidong Sang, Shengbo Ji, Jianlong Shanxi Key Laboratory of Micro Nano Sensors and Artificial Intelligence Perception College of Electronic Information and Optical Engineering Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System The Ministry of Education Taiyuan University of Technology Taiyuan030024 China State Key Laboratory of Transducer Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100190 China Bioengineering Research Center Medical Innovation Research Division Chinese PLA General Hospital Beijing China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science China

Surface modification with noble metal is considered as an effective strategy to enhance sensing performance of semiconductor gas sensors. In this work, gold nanoparticles (Au NPs) decorated Gallium Nitride nanoflowers (Au-GaN NFs) have been synthesized successfully by a feasible hydrothermal method combined with high temperature nitridation and followed by in-situ reduction process. The characterizations of the structure and morphology of as-obtained Au-GaN NFs indicated that the Au NPs were successfully loaded on the surface of GaN. The excellent gas sensing performance was observed for GaN of 2 mol% Au loaded, including the high response (86.8%) to 100 ppm NH3 with fast response/recovery time (41 s/169 s) at room temperature, low theoretical limit of detection (72 ppb), good stability and selectivity. Besides, the influence of humidity on the performance of sensors was explored, where the response can be reached 56.5% towards 100 ppm NH3 under 70% RH. The improvement of the sensing performance of Au-GaN NFs sensor can be attributed to the combined action of chemical and electronic sensitization of Au NPs. This work provides a candidate of Au-GaN NFs for the development of wireless sensing system in NH3 monitoring. © 2023, The Authors. All rights reserved.

关键词： Nanoflowers

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Variable stiffness design optimization of fiber-reinforced composite laminates with regular and irregular holes considering fiber continuity for additive manufacturing

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Chinese Journal of Aeronautics 2025年第3期 338-358页

作者： Yi LIU Zunyi DUAN Chunping ZHOU Yuan SI Chenxi GUAN Yi XIONG Bin XU Jun YAN Jihong ZHU School of Mechanics Civil Engineering & ArchitectureNorthwestern Polytechnical University Research & Development Institute of Northwestern Polytechnical University in Shenzhen Key Lab for Airborne Hi-performance Electro-magnetic Window RISAC School of System Design and Intelligent Manufacturing Southern University of Science and Technology State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of Technology State IJR Center of Aerospace Design and Additive Manufacturing MIIT Lab of Metal Additive Manufacturing and Innovative DesignNorthwestern Polytechnical University

Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel,and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization(NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples consid

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Limit-Cycle-Based Design of Formation Control for Mobile Agents

Limit-Cycle-Based Design of Formation Control for Mobile Age...

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作者： Wang, Chen Xia, Weiguo Xie, Guangming National Engineering Research Center for Software Engineering Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian116024 China State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

In this article, we study the formation problem for a group of mobile agents in a plane, in which the agents are required to maintain a distribution pattern, as well as to rotate around or remain static relative to a static/moving target. The prescribed distribution pattern is a class of general formations where the distances between neighboring agents or the distances between each agent and the target do not need to be equal. Each agent is modeled as a double integrator and can merely perceive the relative information of the target and its neighbors, and the acceleration of the target. In order to solve the formation problem, a limit-cycle-based controller design is delivered. We divide the overall control objective into two subobjectives, where the first is target circling that each agent keeps its own desired distance to the static/moving target as well as rotating around or remaining static relative to the target as expected, and the second is distribution adjustment that each agent maintains the desired distance to its neighbors. Then, we propose a controller comprised of two parts, where a limit cycle oscillator named a converging part is designed to deal with the first subobjective, while a layout part is introduced to address the second subobjective. One key merit of the controller is that it can be implemented by each agent in its local frame so that only local information is utilized without knowing global information. Theoretical analysis of the convergence to the desired formation, of which the agents are required to be evenly distributed on a circle around the target, is provided for the multiagent system under the proposed controller. Numerical simulations are given to validate the effectiveness of the proposed controller for the cases of general formations, and to show that no collision between agents ever takes place throughout the system's evolution. © 1963-2012 IEEE.

关键词： Multi agent systems

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Joint Counting, Detection and Re-Identification for Multi-Object Tracking

arXiv

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arXiv 2022年

作者： Ren, Weihong Wu, Denglu Cao, Hui Chen, Xi'ai Han, Zhi Liu, Honghai The School of Mechanical Engineering and Automation State Key Lab of Robotics and Systems Harbin Institute of Technology Shenzhen518055 China The Shenzhen Duorou Intelligent System Co. Ltd. Shenzhen518055 China The School of Electrical Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Beijing110169 China

The recent trend in 2D multiple object tracking (MOT) is jointly solving detection and tracking, where object detection and appearance feature (or motion) are learned simultaneously. Despite competitive performance, in crowded scenes, joint detection and tracking usually fail to find accurate object associations due to missed or false detections. In this paper, we jointly model counting, detection and re-identification in an end-to-end framework, named CountingMOT, tailored for crowded scenes. By imposing mutual object-count constraints between detection and counting, the CountingMOT tries to find a balance between object detection and crowd density map estimation, which can help it to recover missed detections or reject false detections. Our approach is an attempt to bridge the gap of object detection, counting, and re-Identification. This is in contrast to prior MOT methods that either ignore the crowd density and thus are prone to failure in crowded scenes, or depend on local correlations to build a graphical relationship for matching targets. The proposed MOT tracker can perform online and real-time tracking, and achieves the state-of-the-art results on public benchmarks MOT16 (MOTA of 79.7%), MOT17 (MOTA of 81.3%) and MOT20 (MOTA of 78.9%). Source code is availab.e at https://***/weihong9/CountingMOT. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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DQ-RM: Deep Reinforcement Learning-based Route Mutation Scheme for Multimedia Services 16

DQ-RM: Deep Reinforcement Learning-based Route Mutation Sche...

引用

16th IEEE International Wireless Communications and Mobile Computing Conference, IWCMC 2020

作者： Zhang, Tao Xu, Changqiao Zhang, Bingchi Kuang, Xiaohui Wang, Yue Yang, Shujie Muntean, Gabriel-Miro State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of International Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Science and Technology on Information System Security Beijing China Beijing Key Laboratory of Network System Architecture and Convergence Beijing China Performance Engineering Lab. School of Electronic Engineering Dublin City University Dublin Ireland

ISBN: (纸本)9781728131290

Increasingly growing various multimedia services (e.g., interactive live video and so on) have brought tremendous pressure on existing static defense techniques. To cope with inherent drawback of static defense techniques, Network Moving Target Defense (NMTD) such as route mutation (RM) was proposed. What's more, applying reinforcement learning (RL) into RM has been proved feasible in our previous work. But two main problems still need to be considered in this combination of RL with RM: 1) It lacks the consideration of multiple flows situation. 2) With the state-action space grow larger, current solution can't handle efficiently. In this paper, we propose a deep Q-learning method for RM (DQ-RM) to solve above two problems. Firstly, benefited from the satisfiability module theory, we formalize RM space considering single flow and multiple flows concurrently. Then we further propose a deep reinforcement learning-based RM scheme based on our previous work, which is suitable for large-scale state-action space. Finally, extensive experimental results highlight the improvement of DQ-RM in defense performance and convergence speed compared to the representative solution. © 2020 IEEE.

关键词： Reinforcement learning

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