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Multi-UAVs cooperative task assignment and path planning scheme

Journal of Physics: Conference Series 2021年第1期1856卷

作者： Xiaoyu Du Qicheng Guo Hui Li Yanyu Zhang International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Henan University Kaifeng Henan 475000 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng Henan 475000 China Henan University Minsheng College Kaifeng Henan 475000 China

The task assignment and path planning problems of multiple unmanned aerial vehicles (multi-UAVs) cooperative assistance roadside units (RSUs) for data collection are optimization problems with the goal of minimizing time and energy consumption. This paper proposes a hierarchical optimization scheme for multi-UAVs collaborative assistance RSUs data collection. This solution solves the problems that the number of UAVs needs to be set in advance, the convergence speed is slow when the number of tasks increases, and it is easy to fall into a local optimal solution, and the convergence accuracy is poor. First, the solution uses the K-means algorithm to allocate tasks and group RSUs to find the right number of UAVs to perform the task. Then, this paper proposes a hybrid optimization algorithm based on bionic learning for path planning. Finally, we set up a reasonable evaluation mechanism and conducted simulation experiments. The algorithm in this paper is compared with genetic algorithm, gray wolf algorithm and whale algorithm, the results show that the total cost of the task obtained by the proposed algorithm is the lowest, the algorithm stability is better, and the convergence accuracy is the highest.

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A New Free-Standing Aqueous Zinc-Ion Capacitor Based on MnO2–CNTs Cathode and MXene Anode

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Nano-Micro Letters 2019年第4期11卷 227-238页

作者： Siliang Wang Qiang Wang Wei Zeng Min Wang Limin Ruan Yanan Ma Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui UniversityNo.3 Feixi RoadHefei 230039Anhui ProvincePeople’s Republic of China National Engineering Research Center for Agro-Ecological Big Data Analysis and Application School of Electronics and Information EngineeringAnhui UniversityNo.111 Jiulong RoadHefei 230601Anhui ProvincePeople’s Republic of China School of Sciences Hubei University of Automotive TechnologyNo.167 Checheng West RoadShiyan 442002Hubei ProvincePeople’s Republic of China

Restricted by their energy storage mechanism,current energy storage devices have certain drawbacks,such as low power density for batteries and low energy density for ***,the nearest ion capacitors,such as lithium-ion and sodium-ion capacitors containing battery-type and capacitor-type electrodes,may allow achieving both high energy and power *** the inspiration,a new zinc-ion capacitor(ZIC)has been designed and realized by assembling the free-standing manganese dioxide-carbon nanotubes(MnO2-CNTs)battery-type cathode and MXene(Ti3C2Tx)capacitortype anode in an aqueous *** ZIC can avoid the insecurity issues that frequently occurred in lithium-ion and sodium-ion capacitors in organic *** expected,the ZIC in an aqueous liquid electrolyte exhibits excellent electrochemical performance(based on the total weight of cathode and anode),such as a high specific capacitance of 115.1 F g?1(1 mV s?1),high energy density of 98.6 Wh kg?1(77.5 W kg?1),high power density of 2480.6 W kg?1(29.7 Wh kg?1),and high capacitance retention of^83.6%of its initial capacitance(15,000 cycles).Even in an aqueous gel electrolyte,the ZIC also exhibits excellent *** work provides an essential strategy for designing next-generation high-performance energy storage devices.

关键词： Energy storage Zinc-ion capacitor Battery-type and capacitor-type electrodes MXene Electrochemical performance

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A new runoff calculation model based on multi-source radar remote sensing technology 6

A new runoff calculation model based on multi-source radar r...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Zhao, Jianhui Wang, Ning Wu, Lin Min, Lin College of Computer and Information Engineering Henan University Kaifeng475004 China College of Environment and Planning Henan University Kaifeng475004 China Network Information Center Office Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China

ISBN: (纸本)9781728129129

River runoff changing will directly affect the safety of the surrounding areas. In theory, river runoff can be calculated from water depth, river width and flow velocity. But in the actual monitoring, the observation of water depth, river width and flow velocity is complex. Radar remote sensing can observe target all-time and all-weather, and has the ability to penetrate clouds, rain and fog. The common Radar remote sensing runoff calculation model is depth-runoff relationship model, which is constructed by fitting water depth and in-situ runoff. The river depth is derived from Radar Altimetry (RA) data. But this model has only one input parameter, the accuracy of this model inverted runoff is not high. In view of the above problems, this paper proposed the Multi-source Radar Remote Sensing Runoff Calculation Model (MRRS-RCM). Firstly, river width and relative water depth were derived from Synthetic Aperture Radar (SAR) images and RA data. Secondly, based on the Manning's equation, the flow velocity were described from river width and relative water depth. Thirdly, river width relative water depth, and in-situ runoff were fitted to construct MRRS-RCM. Experiments show the accuracy of MRRS-RCM estimated runoff is better than depth-runoff relationship model, the RRMSE values of MRRS-RCM reach 13%. © 2019 IEEE.

关键词： Synthetic aperture radar

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Waterline mapping of inland great lake with subpixel accuracy from GF-3 SAR images 6

Waterline mapping of inland great lake with subpixel accurac...

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6th Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2019

作者： Li, Ning Niu, Shilin Wang, Robert Wu, Lin Guo, Zhengwei College of Computer and Information Engineering Henan University Kaifeng475004 China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng475004 China Henan Engineering Research Center of Intelligent Technology and Application Kaifeng475004 China Department of Space Microwave Remote Sensing System Institute of Electronics Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781728129129

High-accuracy waterline mapping with Synthetic Aperture Radar (SAR) images is a challenging task because of the inhomogeneities of SAR imagery caused by the speckle noise and complex terrain. This paper presents a novel method for waterline mapping with subpixel accuracy. The proposed method mainly consists of three steps. Firstly, an improved Non-Local filter is adapted to suppress the speckle noise. Secondly, a Fuzzy C-Means (FCM) clustering algorithm is used to extract the pixel-level waterline. Thirdly, along the pixel-level waterline, a novel subpixel-scale waterline extraction method based on bicubic convolution and Geometric Active Contour (GAC) model is presented to further improve the accuracy of the waterline. Without loss of generality, the Danjiangkou reservoir (DJKR), which is the largest artificial freshwater lake in Asia, is selected as a study case. SAR images from Chinese GaoFen-3 (GF-3) satellite working on different modes are processed to demonstrate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Synthetic aperture radar

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Prediction model of physical activity level and hypertension based on artificial neural network

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Journal of Physics: Conference Series 2021年第1期1848卷

作者： Liang Hua Wang Yu Li Jinying Zhang Wanjun Wang Yiting school of Physical Education Henan University Kaifeng Henan 475001 China Department of Health Management People's Hospital of Henan Province People's Hospital of Henan University People's Hospital of Zhengzhou University Zhengzhou 450003 China Key Laboratory of Big Data Analysis and Processing of Henan province Henan University Kaifeng 475004 PR China school of Foreign Language Henan University Kaifeng Henan 475001 China

Purpose: Taking the population of henan Provincial People's Hospital Chronic Disease Control Center from July 1, 2020 to December 31, 2020 who came to the hospital for physical examination as the research object, analyze and explore the role and contribution of physical activity level in the prediction of hypertension by using the LSTM network model, which can provide references for the clinical diagnosis of hypertension. Methods: Randomly select 2000 physical examination data, remove missing and invalid data, and preprocess them. Finally, select factors such as gender, age, body mass index, weight grade, waist-to-hip ratio, physical activity level, body fat percentage and other factors to establish a neural network prediction model. Then test and study the model, focusing on exploring the contribution of physical activity level to prediction. Result: The level of physical activity has certain advantages in predicting the prevalence of hypertension, but the predictive ability in the later stage is insufficient

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A Fabric Defect Detection System Based Improved YOLOv5 Detector

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Journal of Physics: Conference Series 2021年第1期2010卷

作者： Ying Wang Zhengyang Hao Fang Zuo Shanshan Pan Institute of Intelligence Networks System Henan University Kaifeng Henan 475001 China Henan International Joint Laboratory of Theories and Key Technologies on Intelligence Networks Henan University Kaifeng Henan 475001 China Intelligent Data Processing Engineering Research Center of Henan Province Kaifeng Henan University Kaifeng Henan 475001 China

Fabric defect detection is a key part of product quality assessment in the textile industry. It is important to achieve fast, accurate and efficient detection of fabric defects to improve productivity in the textile industry. For the problems of irregular shapes and many small objects, an improved YOLOv5 object detection algorithm for fabric defects is propose. In order to improve the detection accuracy of small objects, the ASFF(Adaptively Spatial Feature Fusion) feature fusion method is adopted to improve the PANet's bad effect on multi-scale feature fusion. The transformer mechanisms can enhance fused features, allowing the network to focus on useful information. Experimental results show that the mean average precision of the improved YOLOv5 object detection algorithm in fabric defect map detection is 71.70%. The improved algorithm can quickly and accurately improve the accuracy of fabric defect detection and the accuracy of defect localization.

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Universal Sub-Nanoreactor Strategy for Synthesis of Yolk-Shell MoS2Supported Single Atom Electrocatalysts toward Robust Hydrogen Evolution Reaction

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Angewandte Chemie 2023年第40期135卷

作者： Feilong Gong Yuheng Liu Yang Zhao Prof. Wei Liu Prof. Guang Zeng Prof. Guoqing Wang Prof. Yonghui Zhang Lihua Gong Prof. Jian Liu Key Laboratory of Surface and Interface Science and Technology of Henan Province College of Material and Chemical Engineering Zhengzhou University of Light Industry Zhengzhou Henan 450001 P. R. China Contribution: Conceptualization (equal) Formal analysis (equal) Funding acquisition (lead) Investigation (lead) Visualization (equal) Writing - original draft (lead) Contribution: Data curation (lead) Formal analysis (equal) Investigation (equal) Validation (equal) Visualization (equal) State Key Laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian Liaoning 116023 P. R. China Contribution: Data curation (equal) Formal analysis (equal) Resources (equal) Validation (equal) Visualization (equal) Contribution: Data curation (equal) Formal analysis (equal) Investigation (equal) Contribution: Data curation (equal) Methodology (equal) Software (equal) Validation (equal) Contribution: Formal analysis (equal) Software (equal) Writing - review & editing (equal) Contribution: Conceptualization (equal) Data curation (equal) Formal analysis (lead) Software (lead) Writing - review & editing (equal) DICP-Surrey Joint Centre for Future Materials Department of Chemical and Process Engineering and Advanced Technology Institute of University of Surrey Guildford Surrey GU2 7XH UK College of Chemistry and Chemical Engineering Inner Mongolia University Hohhot Inner Mongolia 010021 P. R. China Contribution: Conceptualization (lead) Formal analysis (equal) Funding acquisition (equal) Project administration (lead) Supervision (lead) Writing - review & editing (lead)

The coordination structure determines the electrocatalytic performances of single atom catalysts (SACs), while it remains a challenge to precisely regulate their spatial location and coordination environment. Herein, we report a universal sub-nanoreactor strategy for synthesis of yolk-shell MoS 2 supported single atom electrocatalysts with dual-anchored microenvironment of vacancy-enriched MoS 2 and intercalation carbon toward robust hydrogen-evolution reaction. Theoretical calculations reveal that the “E-Lock” and “E-Channel” are conducive to stabilize and activate metal single atoms. A group of SACs is subsequently produced with the assistance of sulfur vacancy and intercalation carbon in the yolk-shell sub-nanoreactor. The optimized C−Co−MoS 2 yields the lowest overpotential (η 10 =17 mV) compared with previously reported MoS 2 -based electrocatalysts to date, and also affords a 5–9 fold improvement in activity even comparing with those as-prepared single-anchored analogues. Theoretical results and in situ characterizations unveil its active center and durability. This work provides a universal pathway to design efficient catalysts for electro-refinery.

关键词： Electrocatalyst Nanostructures Sub-Nanoreactor Universal Strategy Water Splitting

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Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation

arXiv

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arXiv 2021年

作者： Jin, Yu Zhang, Jiayi Huang, Chongwen Yang, Liang Xiao, Huahua Ai, Bo Wang, Zhiqin The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China Zhejiang Provincial Key Lab of Information Processing Communication and Networking Zhejiang University Hangzhou310007 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China ZTE Corporation State Key Laboratory of Mobile Network Mobile Multimedia Technology Shenzhen518057 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen518055 China China Academy of Information and Communications Technology Beijing100191 China

Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm that relies programmable wireless environment and provides capability for space-intensive communications, due to the use of low-cost massive reflecting elements over the entire surfaces of man-made structures. However, accurate channel estimation is a fundamental technical prerequisite to achieve the huge performance gains from RIS. By leveraging the low rank structure of RIS channels, three practical residual neural networks, named convolutional blind denoising network, convolutional denoising generative adversarial networks and multiple residual dense network, are proposed to obtain accurate channel state information, which can reflect the impact of different methods on the estimation performance. Simulation results reveal the evolution direction of these three methods and reveal their superior performance compared with existing benchmark schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Channel estimation

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Comparison of Satellite-retrieved NO2 Vertical Column Density with Ground-level NO2 concentration in a provincial scale region

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IOP Conference Series: Earth and Environmental Science 2020年第1期615卷

作者： Fengbin Zheng Yu Xia Qiang Ge Kun Cai Henan Engineering Laboratory of Spatial Information Processing Henan University Henan 475004 PR China Henan Key Laboratory of Big Data Analysis and Processing Henan University Henan 475004 PR China School of Computer and Information Engineering Henan University Henan 475004 PR China

Satellite remote sensing will have certain errors in data retrieval accuracy, which requires further ground observation verification. This paper examines and verifies 2019 Jiangsu provincial Ground-level monitoring data and TROPOMI data to evaluate the applicability of TROPOMI tropospheric NO2 Vertical Column Density (VCD) data and compares the results to OMI data analysis verification results. The results show that the correlation coefficient r between the TROPOMI NO2 data and Ground-level monitoring data at the monthly mean scale is as high as 0.9, and consistent seasonal cyclic changes are observed. The correlation between Ground-level monitoring data and OMI NO2 data is lower than TROPOMI (r=0.78 < 0.9). Compared to OMI satellites, the TROPOMI attains a smaller deviation in tropospheric NO2 monitoring. Jiangsu province had the highest monthly average concentration in January, which were 38.67 ug/m3 (Ground-level), 17.35 × 1015 molec/cm2 (TROPOMI) and 20.04 × 1015 molec/cm2 (OMI). The lowest concentration in August was 13.39 ug/m3 (Ground-level), 5.2 × 1015 molec/cm2 (TROPOMI) and 7.03 × 1015 molec/cm2 (OMI).

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An extragradient algorithm for fixed point problems and pseudomonotone equilibrium problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 89-96页

作者： Yao, Zhangsong Liou, Yeong-Cheng Zhu, Li-Jun School of Information Engineering Nanjing Xiaozhuang University Nanjing211171 China Department of Healthcare Administration and Medical Informatics Research Center of Nonlinear Analysis and Optimization Kaohsiung Medical University Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung807 Taiwan The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province and Health Big Data Research Institute Advanced Intelligent Perception and Control Technology Innovative Team of NingXia North Minzu University Yinchuan750021 China

Iterative methods for solving fixed point problems and pseudomonotone equilibrium problems have been considered. An extragradient algorithm has been presnted for finding a common element of the fixed points of pseudocontractive operators and the solutions of pseudomonotone equilibrium problems in Hilbert spaces. Weak convergence result of the suggested algorithm is proved. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Iterative methods

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