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IEEE International Conference on Electronics and Communication Engineering (ICECE)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Chaoqun Feng Penghua Liu Hongyan Quan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Simulation Center Science and Technology on Space System Simulation Laboratory Beijing China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (纸本)9781728188577

In order to make full use of the concept of model-based systems engineering (MBSE) and the collaborative design capability of the open model-based engineering environment (OpenMBEE) in establishing complex product development platform, we propose an effective method to solve the problem of unified identity authentication in OpenMBEE integration. The proposed method is based on the Model View Controller(MVC) architecture in OpenMBEE, which has the characteristics strong plasticity and can be benefit for expanding the function in the controller layer. In our research, we make full use of the Software Development Kit (SDK) of OpenMBEE to expand the existing functions in the controller layer, and increase the function of communicating with the application development platform, then realize the function of sharing user authentication information between the development platform and OpenMBEE. After expansion, the system includes three modules, including the Front-end Service Module(FSM), MQ based Information Receiving Service Module(IFRSM), and the OpenMBEE Backend Server Module(BSM). The effectiveness of the proposed strategies is verified by some practical instances, which verifies that our study can provide an effective design idea for the identity authentication in OpenMBEE integration.

关键词： Analytical models Databases Authentication Computer architecture Control systems Data models Software

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technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN with Dual-Discriminators

arXiv

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arXiv 2023年

作者： Cong, Runmin Yang, Wenyu Zhang, Wei Li, Chongyi Guo, Chun-Le Huang, Qingming Kwong, Sam Institute of Information Science Beijing Jiaotong University Beijing100044 China School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan250061 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China College of Computer Science Nankai University Tianjin300350 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Department of Computer Science City University of Hong Kong Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen51800 China

Due to the light absorption and scattering induced by the water medium, underwater images usually suffer from some degradation problems, such as low contrast, color distortion, and blurring details, which aggravate the difficulty of downstream underwater understanding tasks. Therefore, how to obtain clear and visually pleasant images has become a common concern of people, and the task of underwater image enhancement (UIE) has also emerged as the times require. Among existing UIE methods, Generative Adversarial Networks (GANs) based methods perform well in visual aesthetics, while the physical model-based methods have better scene adaptability. Inheriting the advantages of the above two types of models, we propose a physical model-guided GAN model for UIE in this paper, referred to as PUGAN. The entire network is under the GAN architecture. On the one hand, we design a Parameters Estimation subnetwork (Par-subnet) to learn the parameters for physical model inversion, and use the generated color enhancement image as auxiliary information for the Two-Stream Interaction Enhancement subnetwork (TSIE-subnet). Meanwhile, we design a Degradation Quantization (DQ) module in TSIE-subnet to quantize scene degradation, thereby achieving reinforcing enhancement of key regions. On the other hand, we design the Dual-Discriminators for the style-content adversarial constraint, promoting the authenticity and visual aesthetics of the results. Extensive experiments on three benchmark datasets demonstrate that our PUGAN outperforms state-of-the-art methods in both qualitative and quantitative metrics. The code and results can be found from the link of https://***/proj_***. © 2023, CC BY-NC-SA.

关键词： Discriminators

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Quantitative evaluation modeling of mobile Ad Hoc networkcommunication service availability under failure|

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第6期11卷 250-267页

作者： Yanfang Fu Yichang Su Zan Wang Dengdeng Guo Fei Dai Lianjiong Zhong Jianing Wei Xi’an Technological University State and Provincial Joint Engineering Lab.of Advanced Network Monitoring and Control Xi’an 710021P.R.China Beijing Electromechanical Engineering Institute Beijing 100074 P.R.China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing 100074 P.R.China

The availability of network communication services is an important evaluation standard to measure the ability of the network to meet the user’s business *** current related research mostly focuses on the evaluation of network reliability,which cannot reflect the logical relationship between failure/maintenance and network performance *** Ad Hoc Network is a multi-hop,centerless and energy-constrained distributed *** to the dynamic change of communication environment and the instability of wireless link,Ad Hoc Network is facing great challenges in service avail*** this thesis,a fault-based quantitative evaluation model of traffic availability in Ad Hoc networks is *** studying the multi-state Markov fault model of communication networks and the performance analysis of delay index based on CSMA\CA protocol,the quantitative evaluation of traffic availability in Ad Hoc networks is *** the availability of tactical unit network under different typical network configuration conditions is analyzed through experiments.

关键词： Network reliability service availability fault model quantitative evaluation

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Exploring the Spatial Correlation of Shadowing in RF-based Device-Free Localization by Block Sparse Bayesian Learning

Exploring the Spatial Correlation of Shadowing in RF-based D...

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IEEE International Conference on robotics and Biomimetics

作者： Jiaju Tan Xin Zhao Xuemei Guo Guoli Wang School of Mathematics and Computational Science Wuyi University Jiangmen China Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Institute of Robotics and Automatic Information System (IRAIS) Nankai University Tianjin China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education School of Data and Computer Science Sun Yat-sen University Guangzhou China

ISBN: (纸本)9781665405362

Device-Free Localization (DFL) realized by the Radio Frequency (RF) signal sensing, is an emerging technology to obtain the target’s position without needing the target carrying any electronic devices or tags. Due to its through-wall detectability and privacy protection, the RF-based DFL is becoming a promising research topic in the Location-based Services (LBS) applications based on Internet of Things (IoT). Among the RF-based DFL approaches, Radio Tomographic Imaging (RTI) is a low-cost and novel computational imaging method to reconstruct the target-induced shadowing effect in the RF monitored area and then estimate the target’s position. However, the multipath interference in the RF sensing network often induces the reconstruction degradation in the RTI system and leads to the position misestimation in DFL applications. Addressing this problem, considering that the target’s shadowing may occupy a small spatial range and then express some spatial structure, this aricle focuses on the spatial correlation of the target’s shadowing. Then an RTI reconstruction methods based on the Block Sparse Bayesian Learning is proposed to explore the spatial correlation in the sparse target’s shadowing. Moreover, the actual localization experiments are conducted to validate the spatial correlation in shadowing is an important property to improve the RTI reconstruction performance and DFL accuracy.

关键词： Performance evaluation Location awareness Radio frequency Correlation Robot sensing systems Bayes methods Sensors

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Figure-ground image segmentation via semantic information

Figure-ground image segmentation via semantic information

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Yuan, Ding Qiang, Jingjing Li, Jianfei Zhang, Hong Luo, Xiaoyan school of Astronautics Beihang University Beijing China Institute of Shanghai Academy of Space Flight Technology China Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Institute of Spacecraft System Engineering CAST China

ISBN: (纸本)9781728137261

—Image segmentation is a technique to segment the image into particular regions which are consistent in some specific characteristics. It is still a non-trivial task to segment the foreground from the background completely, as these regions are seldom uniform in color or texture which are defined as commonly-used low-level features adopted in the traditional techniques. In this work we present a new segmentation framework by employing the semantic information, which is classified as the high-level visual features and holds important clue to indicate the foreground from the background. Firstly, the image is segmented hierarchically by using the semantic edge constraint, and the result is represented as an Ultrametric Contour Map (UCM). Then the UCM is employed in the segmentation energy function as the data term and smoothness term. Finally, the optimal segmentation labels are obtained via the Graph-cut. Experiments achieve good performance testing on the MSRC 21 dataset. © 2018 IEEE

关键词： Textures

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RSG-Net: Towards Rich Sematic Relationship Prediction for intelligent Vehicle in Complex Environments

arXiv

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arXiv 2022年

作者： Tian, Yafu Carballo, Alexander Li, Ruifeng Takeda, Kazuya Graduate School of Informatics Nagoya University Furo-cho Chikusa-ku Nagoya464-8603 Japan Institute of Innovation for Future Society Nagoya University Furo-cho Chikusa-ku Nagoya464-8601 Japan Tier IV Inc. Nagoya University Open Innovation Center 1-3 Mei-eki 1-chome Nakamura-Ward Nagoya450-6610 Japan State Key Laboratory of Robotic and Intelligent System Harbin Institute of Technology Heilongjiang China

Behavioral and semantic relationships play a vital role on intelligent self-driving vehicles and ADAS systems. Different from other research focused on trajectory, position, and bounding boxes, relationship data provides a human understandable description of the object's behavior, and it could describe an object's past and future status in an amazingly brief way. Therefore it is a fundamental method for tasks such as risk detection, environment understanding, and decision making. In this paper, we propose RSG-Net (Road Scene Graph Net): a graph convolutional network designed to predict potential semantic relationships from object proposals, and produces a graph-structured result, called "Road Scene Graph". The experimental results indicate that this network, trained on Road Scene Graph dataset, could efficiently predict potential semantic relationships among objects around the ego-vehicle. © 2022, CC BY.

关键词： Forecasting

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Design of an Active Battery Equalization Circuit with DC-DC Converter

Design of an Active Battery Equalization Circuit with DC-DC ...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Kun Li Xiao Zong Qing Liu Yanfang Sun Fengjun Xue Tianjin Key Laboratory of Film Electronic and Communication Device Tianjin University of Technology Tianjin PR China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin PR China Wuhan Running Education Research Institute Wuhan PR China

ISBN: (纸本)9781665425513;9781665430791

An active balanced topology circuit based on DC-DC converter is proposed in this paper. It uses the energy of the whole battery pack to charge the lowest voltage cell. In the control strategy, starting and stopping the equalization is well controlled by setting the appropriate thresholds of voltage difference between each cell. Experiment board which can sample and equalize 16 batteries is manufactured, and the experimental results verify the effectiveness of the proposed equalization system.

关键词： Electrical engineering Energy exchange Asia DC-DC power converters Threshold voltage Batteries Topology

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An Area-variant Type MEMS Capacitive Sensor Based on A Novel Bionic Swallow Structure for High Sensitive Nano-indentation Measurement

TechRxiv

引用

TechRxiv 2022年

作者： Gao, Wendi Liu, Cunlang Liu, Tao Zhao, Libo Wang, Chenying Shakoor, Adnan Luo, Tao Jing, Weixuan Yang, Ping Lin, Qijing He, Yongqing Dong, Tao Jiang, Zhuangde Sun, Dong Research Institute for Intelligent Sensing Technology and System Xi’an Jiaotong University Xi’an710049 China School of Mechanical Engineering Xi’an Jiaotong University Xi’an710049 China Harbin150006 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing10081 China Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician Workstation Chongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of Things Chongqing Technology and Business University Chongqing400067 China Department of Biomedical Engineering City University of Hong Kong 999099 Hong Kong Department of Mechanical & Electrical Engineering Xiamen University Xiamen361101 China

In this paper, a high sensitive area-variant type MEMS capacitive sensor was proposed for nano-indentation measurement. The proposed bionic swallow structure processed a high mechanical sensitivity without influences from the load coupling effect. Six comb arrays were optimized and integrated into the proposed sensor with a novel comb sensing configuration for eliminating electrostatic interferences resulting from multiple combs and maintaining compact chip size. Based on the proposed micro-machined process, comb arrays have been fabricated with great consistency, which exhibited a static differential output of 0.0554 pF. The fabricated sensor has been characterized with rigid glass cube and AFM cantilevers, and the measured force sensitivity can reach 98.54 aF/nN for a larger measurement range of 142 µN with a linearity of 0.9996. The fabricated sensor also exhibited a high resolution of 0.9819 nN, indicating its great feasibility in nano-indentation measurement at the sub-nano-Newton level. © 2022, CC BY-NC-SA.

关键词： Indentation

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Direct Upcycling of Degraded LiCoO2Towards High-Performance Cathodes via a Multifunctional Organic Lithium Salt

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Angewandte Chemie 2025年

作者： Difan Fang Prof. Feng Wu Xixue Zhang Xiaodong Zhang Prof. Dr. Yusheng Ye Prof. Renjie Chen Prof. Li Li Beijing Key Laboratory of Environmental Science and Engineering School of Materials Science and Engineering Beijing Institute of Technology Beijing 100081 China Innovative Research Team in High-Safety Energy Storage System Smart Microgrids of Guangdong Province Beijing Institute of Technology (Zhuhai) Zhuhai 519088 China Shandong Key Laboratory of Advanced Chemical Energy Storage and Intelligent Safety Advanced Technology Research Institute Beijing Institute of Technology Jinan 250300 China Collaborative Innovation Center of Electric Vehicles in Beijing Beijing 100081 China

Direct recycling of spent lithium-ion batteries (LIBs) is a promising technology for resource sustainability and environmental conservation. However, the lithium sources for cathode regeneration are typically mono-functional, resulting in low performance enhancement of the recycled material. Herein, we report a one-step direct upcycling method to recycling degraded lithium cobalt oxide (D-LCO) with lithium lignosulfonate (Li−L). Li−L as a multifunctional organic lithium salt can spontaneously attach to the surface of the D-LCO molecules, thus providing replenishment of Li and doping of elemental sodium and sulfur during the regeneration process. Benefiting from the more stable structure of regenerated LCO supported by Na and S elements, the diffusion efficiency of Li ions and electrons can be improved during charging/discharging. As a result, the cell with upcycling LCO cathode exhibits a high capacity of 220.7 mAh g −1 at 0.1 C and retention rate of 89.7 % after 300 cycles at 10 C with a maximum cut-off voltage of 4.6 V. More importantly, life-cycle analysis shows that the upcycling method performs optimally in environmental protection and energy conservation, as well as economic benefits, providing a prospective pathway for the large-scale application of recycling spent batteries.

关键词： spent LIBs degraded LiCoO2 lithium lignosulfonate direct recycling doping

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