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Vertical distribution characteristics of PM in the surface layer of Guangzhou

Particuology 2015年第3期13卷 3-9页

作者： Xuejiao Deng Fei li yuanhong li Jianyong li Hongzhi Huang Xiantong liu Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction China Meteorological Administration(CMA) Guangdong Atmosphere Sounds Technology Centre

Measurements of particulate matter （PM）, i.e., PM10, PM2.5, and PM1, have been performed on the Can- ton Tower, a landmark building in Guangzhou, at heights of 121 and 454 m since November 2010, using a GRIMM 180 aerosol particle spectrometer （Germany）. Analyses of data from November 2010 to May 2013 showed that the annual average values of PM10, PM2.5, and PM 1 at the observation height of 121 m above the ground were 44.1, 38,2, and 34.9 μg/m3, respectively, and those at 454m above the ground were 35.7, 30,4, and 27.5 μg/m3, respectively. By considering the values of the secondary concentration limits given in the Ambient Air Quality Standards issued in 2012, it was observed that the annual average values of PM10 at the observation heights of 121 and 454 m, as well as those of PM2.5 at 454 m, reached those standards. Furthermore, the over-standard amplitude of the annual average value of PM2.5 at the observation height of 121 m was 9.1%. During the observation period, the maximum daily average val- ues of PM10, PM2.5, and PMI at the observation height of 121 m were 183.3, 144.8, and 123.8 μg/m3, respectively, and those at 454 m were 102.8, 92.7, and 86.4 μg/m3. The daily average values of PM10 at the observation height of 454 m were not above the standards. The over-standard frequencies of the daily average values of PM10 and PM2.5 at the observation height of 121 m were 0.6% and 10,7% respectively, and the over-standard amplitudes were 9.0% and 24.4%, respectively. The over-standard frequency of the daily average value of PM2.5 at the observation height of 454 m was 2.0%, and the over-standard amplitude was 10.4%. Accordingly, it can be stated that the air at the observation height 454 m above the ground did not reach the secondary limit of the new standards. The pollution was most serious during winter, and the air was relatively cleaner during summer, Overall, the vertical distributions of PM10, PM2.5, and PMI decreased with height. The lapse rates showed the fo

关键词： PM10PM2.5PM10ver-standardVertical distributionSurface layer

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Authenticated Digital Currency Redaction with Stronger Privacy and Usability

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China Communications 2024年第6期21卷 219-236页

作者： Tang Yongli li Ying Zhao Zongqu li yuanhong Guo Rui School of Computer Science and Technology Henan Polytechnic UniversityJiaozuo 454000China School of Cyberspace Security Xi’an University of Posts and TelecommunicationsXi’an 710121China

With the promotion of digital currency,how to effectively solve the authenticity,privacy and usability of digital currency issuance has been a key *** signature scheme(RSS)can provide the verification of the integrity and source of the generated sub-documents and solve the privacy problem in digital currency by removing blocks from the signed ***,it has not realized the consolidation of signed documents,which can not solve the problem of merging two digital ***,we introduce the concept of weight based on the threshold secret sharing scheme(TSSS)and present a redactable signature scheme with merge algorithm(RSS-MA)using the quasi-commutative *** scheme can reduce the communication overhead by utilizing the merge algorithm when transmitting multiple digital currency ***,this can effectively hide the scale of users’private monetary assets and the number of transactions between *** meeting the three properties of digital currency issuance,in order to ensure the availability of digital currency after redacting,editors shall not remove the relevant identification information block form digital ***,our security proof and the analysis of efficiency show that RSS-MA greatly improves the communication and computation efficiency when transmitting multiple signatures.

关键词： authenticity verification digital currency privacy protection RSS-MA TSSS usability

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Policy-Based Group Signature Scheme from Lattice

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Computers, Materials & Continua 2022年第8期72卷 4069-4085页

作者： Yongli Tang yuanhong li Qing Ye Ying li Xiaojun Wang School of Computer Science and Technology Henan Polytechnic UniversityJiaozuo454000China School of Electronic Engineering Dublin City UniversityDublin 9Ireland

Although the existing group signature schemes from lattice have been optimized for efficiency,the signing abilities of eachmember in the group are relatively *** may not be suitable for complex *** by the pioneering work of Bellare and Fuchsbauer,we present a primitive called policy-based group *** policy-based group signatures,group members can on behalf of the group to sign documents that meet their own policies,and the generated signatures will not leak the identity and policies of the ***,the group administrator is allowed to reveal the identity of signer when a controversy *** the analysis of application scenarios,we concluded that the policy-based group signature needs to meet two essential security properties:simulatability and *** we construct a scheme of policy-based group signature from lattice through techniques such as commitment,zero-knowledge proof,rejection *** security of our scheme is proved to be reduced to the module short integer solution(MSIS)and module learning with errors(MLWE)hard ***,we make a performance comparison between our scheme and three lattice-based group signature *** result shows that our scheme has more advantages in storage overhead and the sizes of key and signature are decreased roughly by 83.13%,46.01%,respectively,compared with other schemes.

关键词： Group signature policy-based signature lattice-based cryptography zero-knowledge proof

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Optical Absorption Characterizations of Porous Al_2O_3Host/NiO Nanocomposites

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Journal of Materials Science & Technology 1997年第5期13卷 435-439页

作者： Cai, Weili Mo, Chimei Zhang, Lan li, yuanhong Yao, lianzeng Dept. of Materials Science and Engineering University of Science and Technology of China Hefei 230026 China

Porous Al2O3 host/NiO nanocomposites have been prepared by pyrolysis of Ni2(OH)2CO3 inthe nanostructured Al2O3 hosts. Diffuse reflection spectra in the wavelength range of 200 to800 nm were measured. Results show that (1) in each spectrum exist several absorption bandsof nano-NiO. With increasing the pyrolysis temperature from 550 to 1000℃, the numbers ofabsorption bands of NiO increase from 2 to 6 (P1-P6), (2) comparing with optical absorptionbands of single crystal NiO, for porous nanocomposites the P1, P2 and P4 present 'blue shift'and the P3, P5 and P6 exhibit 'red shift'; (3) when the pyrolysis temperature, Tp, is 550℃, theabsorption bands become so weak that only two bands (P1 and P6) can be observed and inverselywhen Tp=1000℃ all six absorption bands of NiO are strong, (4) for porous Al2O3/NiOnanocomposites prepared by pyrolysis at 1000℃ the PF+ caused by the F+ centers in theAl2O3 host moves towards the short wavelength at first with increasing the doping amount ofNiO from 5 to 50 wt pct and then shifts to the long wavelength with further increasing NiO. Inthis paper, the above phenomena and mechanism of the absorption bands of NiO are discussedin detail.

关键词： Nanostructured materials

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Monocular vision and calculation of regular three-dimensional target pose based on Otsu and Haar-feature AdaBoost classifier

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International Journal of Agricultural and Biological Engineering 2020年第5期13卷 171-180页

作者： yuanhong li Hongjun Wang Weiliang Zhou Zehao Xue Department of Engineering South China Agricultural UniversityGuangzhou 510642China Southern Key Laboratory of Agricultural Equipment Machinery South China Agricultural UniversityGuangzhou 510642China Department of Biological and Agricultural Engineering Texas A&M UniversityCollege StationTX77843USA

Using machine vision to identify and sort scattered regular targets is an urgent problem to be solved in automated production *** study proposed a three-dimensional(3D)recognition method combining monocular vision and machine learning *** to the color characteristics of the targets,to convert the original color picture into YCbCr mode and use the 2D Otsu algorithm to perform gray level image segmentation on the Cb *** the Haar-feature training was carried *** comparison of feature training and Haar method for Hough transform showed that the recognized time of Haar-feature AdaBoost trainer reached 31.00 ms,while its false recognized rate was 3.91%.The strong classifier was formed by weight combination,and the Hough contour transformation algorithm was set to correct the normal vector between plane coordinate and camera coordinate *** monocular vision system ensured that the field of camera view had not obstructed while the dots were being *** was measured and calculated angles between targets and the horizontal plane which coordinate points of the identified plane *** testing results were compared with the Otsu and AdaBoost trainer where the prediction and training set have an error of no more than 0.25 *** correct rate can reach 95%.It shows that the Otsu and Haar-feature based on AdaBoost algorithm is feasible within a certain error ranges and meet the engineering requirements for solving the poses of automated regular three-dimensional targets.

关键词： Otsu Haar-feature AdaBoost 3D position target pose monocular vision error analysis

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Point Cloud Completion of Plant Leaves under Occlusion Conditions Based on Deep Learning

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Plant Phenomics 2023年第4期5卷 852-863页

作者： Haibo Chen Shengbo liu Congyue Wang Chaofeng Wang Kangye Gong yuanhong li Yubin Lan Experimental Basis and Practical Training Center South China Agricultural UniversityGuangzhouChina National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides Spraying Technology GuangzhouChina College of Electronics Engineering(College of Artificial Intelligence) South China Agricultural UniversityGuangzhouChina College of Engineering South China Agricultural UniversityGuangzhouChina Department of Biological and Agricultural Engineering Texas A&M UniversityCollege StationTXUnited States

The utilization of 3-dimensional point cloud technology for non-invasive measurement of plant phenotypic parameters can furnish important data for plant breeding,agricultural production,and diverse research ***,the utilization of depth sensors and other tools for capturing plant point clouds often results in missing and incomplete data due to the limitations of 2.5D imaging features and leaf *** drawback obstructed the accurate extraction of phenotypic ***,this study presented a solution for incomplete flowering Chinese Cabbage point clouds using Point Fractal Network-based *** study performed experiments on flowering Chinese Cabbage by constructing a point cloud dataset of their leaves and training the *** findings demonstrated that our network is stable and robust,as it can effectively complete diverse leaf point cloud morphologies,missing ratios,and multi-missing scenarios.A novel framework is presented for 3D plant reconstruction using a single-view RGB-D(Red,Green,Blue and Depth)*** method leveraged deep learning to complete localized incomplete leaf point clouds acquired by RGB-D cameras under occlusion ***,the extracted leaf area parameters,based on triangular mesh,were compared with the measured *** outcomes revealed that prior to the point cloud completion,the R^(2)value of the flowering Chinese Cabbage's estimated leaf area(in comparison to the standard reference value)was *** root mean square error(RMSE)was 15.88 cm^(2),and the average relative error was 22.11%.However,post-completion,the estimated value of leaf area witnessed a significant improvement,with an R^(2)of 0.9637,an RMSE of 6.79 cm^(2),and average relative error of 8.82%.The accuracy of estimating the phenotypic parameters has been enhanced significantly,enabling efficient retrieval of such *** development offers a fresh perspective for non-destructive identification of plant p

关键词： Deep incomplete Plant

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Modeling effectiveness and identification of multi-scale objects in farmland soils with improved Yee-FDTD methods

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International Journal of Agricultural and Biological Engineering 2020年第6期13卷 150-158页

作者： yuanhong li Zuoxi Zhao Zhi Qiu Yangfan Luo Yuchan Zhu Department of Engineering South China Agricultural UniversityGuangzhou 510642China Southern Key Laboratory of Agricultural Equipment Machinery South China Agricultural UniversityGuangzhou 510642China Department of Biological and Agricultural Engineering Texas A&M UniversityCollege StationTX77843USA

Finite-Difference Time-Domain(FDTD)is the most popular time-domain approach in computational *** to the Courant-Friedrich-Levy(CFL)condition and the perfect match layer(PML)boundary precision,FDTD cannot simulate soil medium whose surface is connected by multiple straight lines or curves(multi-scale)accurately and efficiently,which greatly limits the application of FDTD method to simulate buried objects in ***,this study proposed the absorption boundary and adopted two typical perfect matching layers(UPML and CPML)to compare their absorption effects,and then using the three forms of improved Yee-FDTD algorithm,alternating-direction implicit(ADI-FDTD),unconditionally stable(US-FDTD)and hybrid implicit explicit finite time-domain(HIE-FDTD)to divide and contrast the boundary model *** showed that the HIE-FDTD was suitable for inversion of multi-scale structure object modeling,while ADI-FDTD and US-FDTD were ideal for single-boundary objects in both uniaxial perfectly matched layer(UMPL)and convolution perfectly matched layer(CPML)finite element *** that,all the models were tested by computer performance for their simulated *** simulating single boundary objects,UPML-US-FDTD and ADI-FDTD could achieve the ideal results,and in the boundary inversion of multi-scale objects,HIE-FDTD modeling results and efficiency were the *** modeling speeds of CPML-HIE-FDTD were compared with three kinds of waveform sources,Ricker,Blackman-Harris and ***,under the computer condition in which the CPU was i5-8250,the HIE-FDTD model still had better performance than the traditional Yee-FDTD forward modeling *** modeling multi-scale objects in farmland soils,the methods used CPML combined with the HIE-FDTD were the most efficient and accurate *** study can solve the problem that the traditional FDTD algorithm cannot construct non-mesh objects by utilizing the diversity characteristics of Yee cell element

关键词： Yee-FDTD multi-scale objects modeling effectiveness Ground Penetrating Radar farmland soils

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Classification method of cultivated land based on UAV visible light remote sensing

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International Journal of Agricultural and Biological Engineering 2019年第3期12卷 103-109页

作者： Weicheng Xu Yubin Lan yuanhong li Yangfan Luo Zhenyu He College of Engineering South China Agricultural UniversityGuangzhou 510642China National Center for International Collaboration Research on Precision Agricultural Aviation Pesticide Spraying Technology Guangzhou 510642China

The accurate acquisition of the grain crop planting area is a necessary condition for realizing precision *** remote sensing has the advantages of low cost use,simple operation,real-time acquisition of remote sensor images and high ground *** is difficult to separate cultivated land from other terrain by using only a single feature,making it necessary to extract cultivated land by combining various features and hierarchical *** this study,the UAV platform was used to collect visible light remote sensing images of farmland to monitor and extract the area information,shape information and position information of *** on the vegetation index,texture information and shape information in the visible light band,the object-oriented method was used to study the best scheme for extracting cultivated land *** repeated experiments,it has been determined that the segmentation scale 50 and the consolidation scale 90 are the most suitable segmentation *** crops and other features are separated by using the band information and texture *** overall accuracy of this method is 86.40%and the Kappa coefficient is *** experimental results show that the UAV visible light remote sensing data can be used to classify and extract cultivated land with high ***,there are some cases where the finely divided plots are misleading,so further optimization and improvement are needed.

关键词： UAV visible band remote sensing extraction of cultivated land area object oriented method

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Detection of the foreign object positions in agricultural soils using Mask-RCNN

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International Journal of Agricultural and Biological Engineering 2023年第1期16卷 220-231页

作者： yuanhong li Chaofeng Wang Congyue Wang Xiaoling Deng Zuoxi Zhao Shengde Chen Yubin Lan South China Agricultural University College of Electronic EngineeringGuangzhou 510642China National Center for International Collaboration Research on Precision Agricultural Aviation Pesticides SprayingTechnology(NPAAC)South China Agricultural UniversityGuangzhou 510642China Department of Biological and Agricultural Engineering Texas A&M UniversityCollege StationTX77843USA Guangdong Laboratory for lingnan Modern Agriculture Guangzhou 510642China

Objects in agricultural soils will seriously affect the farming operations of agricultural *** present,it still relies on human experience to judge abnormal Gounrd-penetrting Radar(GPR)*** is difficult for traditional image processing technology to form a general positioning method for the randomness and diversity characteristics of GPR signals in *** many scholars had researched a variety of image-processing techniques,most methods lack *** this study,the deep learning algorithm Mask Region-based Convolutional Neural Network(Mask-RCNN)and a geometric model were combined to improve the GPR positioning ***,a soil stratification experiment was set to classify the physical parameters of the soil and study the attenuation law of electromagnetic ***,a SOIL-GPR geometric model was proposed,which can be combined with Mask-RCNN's MASK geometric size to predict object *** results proved the effectiveness and accuracy of the model for position detection and evaluation of objects in soils;then,the improved Mask RCNN method was used to compare the feature extraction accuracy of U-Net and Fully Convolutional Networks(FCN);Finally,the operating speed of agricultural machinery was simulated and designed the A-B survey line *** detection accuracy was evaluated by several indicators,such as the survey line direction,soil depth false alarm rate,Mean Average Precision(mAP),and Intersection over Union(IoU).The results showed that pixel-level segmentation and positioning based on Mask RCNN can improve the accuracy of the position detection of objects in agricultural soil effectively,and the average error of depth prediction is 2.87 *** results showed that the detection technology proposed in this study integrates the advantage of soil environmental parameters,geometric models,and artificial intelligence algorithms to provide a high-precision and technical solution for the GPR non-destructive detection of soils

关键词： foreign object soil object position agricultural soil Mask R-CNN GPR image

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Development of Rainwater Harvesting

Development of Rainwater Harvesting

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作者： Zhu Qiang li yuanhong

＜正＞Rainwater harvesting （RWH） is defined in China as"mini-scale water re- sources scheme that collects,stores rainwater by structural measures and regulates and makes use of it for domestic and production use."It...

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