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Regulation of morphology and visible light-driven photocatalysis of WO_(3)nanostructures by changing pH

Rare Metals 2021年第7期40卷 1738-1745页

作者： You-Shu Fan Xiao-Li Xi Yang-Si Liu Zuo-Ren Nie Lin-Yan Zhao Qing-Hua Zhang College of Materials Science and Engineering Key Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaBeijing University of TechnologyBeijing 100124China National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of TechnologyBeijing 100124China

The controlled preparation of hexagonal tungsten trioxide(h-WO_(3))nanostructures was achieved by adjusting the pH of the precursor *** effect of the pH on the morphology,elemental composition,and photocatalytic performance of the samples was characterized via X-ray diffraction(XRD),scanning electron microscopy,energy dispersive X-ray spectroscopy,and Raman ***-visible(UV-Vis)spectra were used to evaluate the absorbance and the photocatalytic performance of methylene ***(PL),electrochemical impedance spectroscopy,photocurrent response and Brunauer-Emmett-Teller(BET)were used to study the optical properties,electrical performance,and specific surface area of the WO_(3)-nanostructures,*** results indicate that the WO_(3) nanorods prepared at pH=1.0 exhibit the highest photocatalytic performance(87.4%in 1 h),whereas the WO_(3) nanoblocks prepared at p H=3.0 show the *** photocatalytic performance of the one dimensional(1 D)-nanorods can be attributed to their high specific surface area and charge transfer *** h-WO_(3) nanostructures were synthesized via a simple method and without a capping *** show an excellent photocatalytic performance,which is promising for their application in environment purification.

关键词： h-WO_(3) Morphology pH Photocatalysis Charge transfer Optoelectrical properties

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Rapid determination of minced beef adulteration using hyperspectral reflectance spectroscopy and multivariate methods 7

Rapid determination of minced beef adulteration using hypers...

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7th Annual International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2019

作者： Guo, Bingqing Zhao, Jinling Weng, Shizhuang Yin, Xun Tang, Peipei National Engineering Research Center for Analysis and Application of Agro-Ecological Big Data Anhui University Hefei230601 China

This work aimed to assess the potential of hyperspectral reflectance spectroscopy for minced beef adulteration. For this, 30 samples of pure minced beef along with 90 samples adulterated beef at different levels were prepared and analyzed. Multivariate methods were used for spectral analysis to classify adulteration types. The best result was obtained by random forest (RF), where the accuracy of classification in prediction set was 87.78%. Considering the redundant information of reflectance spectra, the optimal wavelengths were selected by successive projection algorithm (SPA) to improve robustness. Selected important wavelengths models have a better classification effect than full wavelengths models. The optimal model developed by RF for detecting adulterantion types achieved an accuracy of 96.87% in prediction set with selected wavelengths. Accordingly, hyperspectral reflectance spectroscopy with multivariate methods can provide the accurate and rapid detection of minced beef adulteration. © Published under licence by IOP Publishing Ltd.

关键词： Beef

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Extraction of soybean planting areas based on multi-temporal Sentinel-1/2 data 3

Extraction of soybean planting areas based on multi-temporal...

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3rd International Conference on Computer Vision and Pattern analysis, ICCPA 2023

作者： Ding, Han Huang, Linsheng National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei230601 China

ISBN: (纸本)9781510667563

Accurate knowledge of soybean distribution is essential for regulating the soybean market and promoting sustainable development. This research presents a method for identifying soybean planting areas using multispectral data and feature selection models. The study area was the county of Guoyang, Anhui Province. Sentinel-1/2 data from three different time periods were used to calculate vegetation indices, textures, and other features. Initially, non-cropland elements in the study area were gradually masked by constructing decision trees. Then ReliefF algorithm was combined with Random Forest, Support Vector Machine, and BP Neural Network to develop three classification models: ReliefF-RF, ReliefF-SVM, and ReliefF-BPNN, and the best feature subsets were selected as input for each of the three models, an overall distribution map of soybeans in the study area was obtained. Finally, the performance of three models was evaluated by utilizing the distribution results of soybeans obtained from the classification of Planet images and seven uniformly distributed sample plots (500m × 500m) within the study area. The results showed that the Kappa coefficient was between 0.73 to 0.85, and the overall accuracy ranged from 87.42% to 93.22%. The ReliefF-RF model had the best performance in the experiment. © 2023 SPIE.

关键词： Decision trees

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Remote Sensing Based Monitoring of Winter Wheat Powdery Mildew at a Regional Scale Using Random Forest Model 6

Remote Sensing Based Monitoring of Winter Wheat Powdery Mild...

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6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2018

作者： Huang, Linsheng Ding, Wenjuan Jiang, Jing Wu, Zhaochuan Zhao, Jinling National Engineering Research Center for Analysis and Application of Agro-Ecological Big Data Anhui University Hefei230601 China

Wheat powdery mildew is one of the main diseases of wheat. The emergence and spread have seriously affected the yield and quality of wheat. It is of great significance to accurately monitor the occurrence of such a plant disease at a regional scale. Satellite remote sensing imagery has been extensively utilized in monitoring and assessing various plant diseases, due to its own particular advantages of real-time performance, wide coverage, high tempo-spatial resolution, etc. It is therefore suitable as a data source for monitoring the occurrence of wheat powdery mildew. Gaocheng District, Zhao County and Jinzhou City of Hebei Province, China were used as the study area. A total of eleven features were extracted from Landsat 8 OLI (Operational Land Imager) remote sensing data. Due to the existence of inter-band correlation, the Relief-F algorithm was used to carry out the feature selection. According to the weight value of each feature, three features were determined as the input into the created monitoring model. Consequently, the monitoring model was respectively established using the random forest (RF) and support vector machine (SVM). The analysis results show that the overall accuracy (OA) of RF model reaches 84% with the Kappa coefficient of 0.67, which are better than the SVM model of 73% and 0.47. © Published under licence by IOP Publishing Ltd.

关键词： Landsat

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Comparision of eight topographic correction algorithms applied to landsat-8 oli imagery based on the dem 7

Comparision of eight topographic correction algorithms appli...

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7th Annual International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2019

作者： Fang, Yan Zhao, Jinling Liu, Lingling Wang, Jie National Engineering Research Center for Analysis and Application of Agro-Ecological Big Data Anhui University Hefei230601 China

Topographic correction is one of the most important procedures for remote sensing image preprocessing, and it is also the premise for quantitative remote sensing. According to the latest calibration parameters provided by the USGS website, four Lambert body reflectance models and four Non-Lambert body reflectance models were used to carry out the topographic correction combining the DEM data in R platform. A total of three indicators were used to assess the effects including visual contrast, normalized evaluation of shady slopes and sunny slopes, and linear fitting. The results show that the corrected image of Cosine correction method based on the Lambertian reflectivity model is visually overexposed, and the DN value on the shady slope is over-corrected. The corrected images of Minnaert and Minaret-scs based on the Non-Lambertian reflectivity model visually reduce the amplitude of the terrain fluctuations, and the linear fitting has a small separation factor, which produces a better correction effect. © Published under licence by IOP Publishing Ltd.

关键词： Reflection

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Real-time distance field acceleration based free-viewpoint video synthesis for large sports fields

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Computational Visual Media 2024年第2期10卷 331-353页

作者： Yanran Dai Jing Li Yuqi Jiang Haidong Qin Bang Liang Shikuan Hong Haozhe Pan Tao Yang School of Telecommunications Engineering Xidian UniversityXi’an 710071China National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology SAIIPthe School of Computer ScienceNorthwestern Polytechnical UniversityXi’an 710129China

Free-viewpoint video allows the user to view objects from any virtual perspective,creating an immersive visual *** technology enhances the interactivity and freedom of multimedia ***,many free-viewpoint video synthesis methods hardly satisfy the requirement to work in real time with high precision,particularly for sports fields having large areas and numerous moving *** address these issues,we propose a freeviewpoint video synthesis method based on distance field *** central idea is to fuse multiview distance field information and use it to adjust the search step size *** step size search is used in two ways:for fast estimation of multiobject three-dimensional surfaces,and synthetic view rendering based on global occlusion *** have implemented our ideas using parallel computing for interactive display,using CUDA and OpenGL frameworks,and have used real-world and simulated experimental datasets for *** results show that the proposed method can render free-viewpoint videos with multiple objects on large sports fields at 25 ***,the visual quality of our synthetic novel viewpoint images exceeds that of state-of-the-art neural-rendering-based methods.

关键词： free-viewpoint video view synthesis camera array distance field sports video

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Detection of scab in wheat ears using in situ hyperspectral data and support vector machine optimized by genetic algorithm

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International Journal of Agricultural and Biological engineering 2020年第2期13卷 182-188页

作者： Linsheng Huang Hansu Zhang Chao Ruan Wenjiang Huang Tingguang Hu Jinling Zhao National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefeiChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina

A new method was proposed to extract sensitive features and to construct a monitoring model for wheat scab based on in situ hyperspectral data of wheat ears to achieve effective prevention and control and provide theoretical support for its large-scale *** sensitive features were selected through correlation analysis and wavelet *** features were as follows:three original bands of 350-400 nm,500-600 nm,and 720-1000 nm;three vegetation indices of modified simple ratio(MSR),normalized difference vegetation index,and structural independent pigment index;and two wavelet features of WF01 and *** combining the selected sensitive features with support vector machine(SVM)and SVM optimized by genetic algorithm(GASVM),a total of 16 monitoring models were built,and the monitoring accuracies of the two types of models were *** ability of the monitoring models built by GASVM to identify scab was better than that of SVM algorithm under the same characteristic *** the 16 models,MSR combined with GASVM had an overall accuracy of 75%and a Kappa coefficient of *** can be used to monitor wheat scab and its application can improve the accuracy of disease monitoring.

关键词： wheat scab hyperspectral data correlation analysis genetic algorithm wavelet transform support vector machine

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CATIRI:An Efficient Method for Content-and-Text Based Image Retrieval

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Journal of Computer Science & Technology 2019年第2期34卷 287-304页

作者： Mengqi Zeng Bin Yao Zhi-Jie Wang Yanyan Shen Feifei Li Jianfeng Zhang Hao Lin Minyi Guo Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Data and Computer Science Sun Yat-sen University Guangzhou 510006 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou 510006 China National Engineering Laboratory for Big Data Analysis and Applications Beijing 100871 China School of Computing University of Utah Salt Lake City 84112 U.S.A. Alibaba Group Hangzhou 311121 China

The combination of visual and textual information in image retrieval remarkably alleviates the semantic gap of traditional image retrieval methods,and thus it has attracted much attention *** retrieval based on such a combination is usually called the content-and-text based image retrieval(CTBIR).Nevertheless,existing studies in CTBIR mainly make efforts on improving the retrieval *** the best of our knowledge,little attention has been focused on how to enhance the retrieval ***,image data is widespread and expanding rapidly in our daily ***,it is important and interesting to investigate the retrieval *** this end,this paper presents an efficient image retrieval method named CATIRI(content-and-text based image retrieval using indexing).CATIRI follows a three-phase solution framework that develops a new indexing structure called *** MHIM-tree seamlessly integrates several elements including Manhattan Hashing,Inverted index,and *** use our MHIM-tree wisely in the query,we present a set of important metrics and reveal their inherent *** on them,we develop a top-k query algorithm for *** results based on benchmark image datasets demonstrate that CATIRI outperforms the competitors by an order of magnitude.

关键词： image retrieval text-and-visual feature indexing top-k

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Heterogeneous-attributes enhancement deep framework for network embedding

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Frontiers of Computer Science 2021年第6期15卷 121-131页

作者： Lisheng QIAO Fan ZHANG Xiaohui HUANG Kai LI Enhong CHEN Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of ChinaHefei 230022China National Key Laboratory of Blind Signal Processing Chengdu 610041China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230022China

Network embedding,which targets at learning the vector representation of vertices,has become a crucial issue in network ***,considering the complex structures and heterogeneous attributes in real-world networks,existing methods may fail to handle the inconsistencies between the structure topology and attribute ***,more comprehensive techniques are urgently required to capture the highly non-linear network structure and solve the existing inconsistencies with retaining more *** that end,in this paper,we propose a heterogeneous-attributes enhancement deep framework(HEDF),which could better capture the non-linear structure and associated information in a deep learningway,and effectively combine the structure information of multi-views by the combining *** this line,the inconsistencies will be handled to some extent and more structure information will be preserved through a semi-supervised *** extensive validations on several real-world datasets show that our model could outperform the baselines,especially for the sparse and inconsistent situation with less training data.

关键词： network embedding heterogeneous-attributes deep framework inconsistent

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Design of real-time feedback control of vertical growth rate on EAST

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Nuclear Science and Techniques 2021年第7期32卷 99-107页

作者： Na-Na Bao Yao Huang Bing-Jia Xiao Qi-Ping Yuan Zheng-Ping Luo Yue-Hang Wang Shu-Liang Chen School of Internet Anhui UniversityHefei 230039China Institute of Plasma Physics Chinese Academy of SciencesHefei 230031China National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefei 230039China

Real-time feedback control of vertical growth rate,called gamma control,has been successfully applied to experimental advanced superconducting tokamak(EAST).In this paper,a new gamma control method is proposed to regulate the vertical growth rate,which is an estimator of plasma vertical ***,the gamma controller can be utilized to keep the tokamak plasma away from its unstable *** this work,the main development process includes three steps:(1)real-time implementation of model-based vertical growth rate calculation,taking advantage of GPU parallel computing capability,(2)design of plasma shape response for dynamic shape control using a slight modification to the plasma boundary,and(3)development of a gamma control algorithm integrated into the EAST plasma control system(PCS).The gamma control was experimentally verified in the EAST 2019 experiment *** is shown that the time evolution of the real-time vertical growth rate agrees with the target value,indicating that the real-time vertical growth rate can be regulated by gamma control.

关键词： Experimental advanced superconducting tokamak(EAST) Dynamic shape response Gamma control Vertical growth rate

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