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preprocessing method of night vision image application in apple harvesting robot

International Journal of Agricultural and Biological Engineering 2018年第2期11卷 158-163页

作者： Weikuan Jia Yuanjie Zheng De’an Zhao Xiang Yin Xiaoyang Liu Ruicheng Du School of Information Science and Engineering Shandong Normal UniversityJinan 250358China Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Jiangsu UniversityZhenjiang 212013China School of Agricultural Engineering and Food Science Shandong University of TechnologyZibo 255000China Institute of Life Sciences and Key Lab of Intelligent Information Processing Shandong Normal UniversityJinan 250014China

Due to the low working efficiency of apple harvesting robots,there is still a long way to go for *** machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots,this study focused on the extended operating time and proposed a round-the-clock operation *** to the influences of light,temperature,humidity,etc.,the working environment at night is relatively complex,and thus restricts the operating efficiency of the apple harvesting *** different artificial light sources(incandescent lamp,fluorescent lamp,and LED lights)were selected for auxiliary light according to certain rules so that the apple night vision images could be *** addition,by color analysis,night and natural light images were compared to find out the color characteristics of the night vision images,and intuitive visual and difference image methods were used to analyze the noise *** results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night,and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper *** preprocessing method can provide a theoretical and technical reference for subsequent image processing.

关键词： apple harvesting robot night vision image preprocessing method color analysis noise analysis

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Effects of preprocessing method on TVOC Emission of Car Mat

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Journal of Thermal Science 2013年第1期22卷 80-85页

作者： Min Wang Li Jia1 Department of Power Engineering School of Mechanical and Electronic Control Engineering Beijing Jiaotong University Key Laboratory of Urban Stormwater System and Water Environment Ministry of Education

The effects of the mat preprocessing method on total volatile organic compounds （TVOC） emission of car mat are studied in this paper. An appropriate TVOC emission period for car mat is suggested. The emission factors for to- tal volatile organic compounds from three kinds of new car mats are discussed. The car mats are preprocessed by washing, baking and ventilation. When car mats are preprocessed by washing, the TVOC emission for all samples tested are lower than that preprocessed in other methods. The TVOC emission is in stable situation for a mini- mum of 4 days. The TVOC emitted from some samples may exceed 25001ag/kg. But the TVOC emitted from washed Polyamide （PA） and wool mat is less than 25001ag/kg. The emission factors of total volatile organic com- pounds （TVOC） are experimentally investigated in the case of different preprocessing methods. The air tempera- ture in environment chamber and the water temperature for washing are important factors influencing on emission of car mats.

关键词： TVOC Mat Environment chamber preprocessing method Emission

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Impact of the spotted microarray preprocessing method on fold-change compression and variance stability

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BMC BIOINFORMATICS 2011年第1期12卷 1-12页

作者： Ambroise, Jerome Bearzatto, Bertrand Robert, Annie Govaerts, Bernadette Macq, Benoit Gala, Jean-Luc Catholic Univ Louvain ICTEAM Inst ELEN Dept B-1348 Louvain Belgium Catholic Univ Louvain IREC Inst Ctr Appl Mol Technol B-1200 Brussels Belgium Catholic Univ Louvain IREC Inst Dept Epidemiol & Biostat B-1200 Brussels Belgium Catholic Univ Louvain Inst Stat Biotstat & Actuarial Sci B-1348 Louvain Belgium

Background: The standard approach for preprocessing spotted microarray data is to subtract the local background intensity from the spot foreground intensity, to perform a log2 transformation and to normalize the data with a global median or a lowess normalization. Although well motivated, standard approaches for background correction and for transformation have been widely criticized because they produce high variance at low intensities. Whereas various alternatives to the standard background correction methods and to log2 transformation were proposed, impacts of both successive preprocessing steps were not compared in an objective way. Results: In this study, we assessed the impact of eight preprocessing methods combining four background correction methods and two transformations (the log2 and the glog), by using data from the MAQC study. The current results indicate that most preprocessing methods produce fold-change compression at low intensities. Fold-change compression was minimized using the Standard and the Edwards background correction methods coupled with a log2 transformation. The drawback of both methods is a high variance at low intensities which consequently produced poor estimations of the p-values. On the other hand, effective stabilization of the variance as well as better estimations of the p-values were observed after the glog transformation. Conclusion: As both fold-change magnitudes and p-values are important in the context of microarray class comparison studies, we therefore recommend to combine the Edwards correction with a hybrid transformation method that uses the log2 transformation to estimate fold-change magnitudes and the glog transformation to estimate p-values.

关键词： Log2 Transformation Background Correction Class Comparison preprocessing method Lowess Curve

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Composite leading search index: a preprocessing method of internet search data for stock trends prediction

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ANNALS OF OPERATIONS RESEARCH 2015年第1期234卷 77-94页

作者： Liu, Ying Chen, Yibing Wu, Sheng Peng, Geng Lv, Benfu Univ Chinese Acad Sci Sch Management Beijing 100190 Peoples R China

Previous studies have revealed that Internet search data is a new source of data that can be used to predict the stock market. In this new, data-driven research field, choosing a method for preprocessing data is crucial to achieving accurate prediction performance. This paper proposes a preprocessing method of Internet search data: composite leading search index (CLSI), which is composed of three steps: (a) keyword selection, (b) time difference measurement, and (c) leading index composition. We demonstrate the validity of CLSI by comparing this method's results with the results from search volume index (SVI), which is most commonly used in previous literatures. We build a time series model (TS) with error correction and support vector regression (SVR) for stock trend prediction, and combine into four models for comparison: SVI-TS, CLSI-TS, SVI-SVR, and CLSI-SVR. We test these four models in the context of the Chinese stock market, which interests more and more investors nowadays, and analyzed results in nine datasets: stable periods, peak periods and trough periods of Shanghai Composite Index, Shenzhen Composite Index, and Hushen 300 index respectively. The results show that using TS and SVR as forecasting models, CLSI performs better than SVI on majority of the test dataset while has almost the same performance with that of SVI on the remaining test dataset. It is to some extent convincing that CLSI is a more efficient preprocessing method of Internet search data for stock trend prediction.

关键词： Internet search data preprocessing method Stock trend predication Investor attention Composite leading search index Search volume index Support vector regression

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The CNN-based Coronary Occlusion Site Localization with Effective preprocessing method

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IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING 2020年第10期15卷 1549-1551页

作者： Park, YeongHyeon Yun, Il Dong Kang, Si-Hyuck Hankuk Univ Foreign Studies Dept Comp & Elect Syst Engn Yongin 17035 South Korea Seoul Natl Univ Bundang Hosp Ctr Cardiovasc Internal Med Seongnam 13620 South Korea

The coronary artery occlusion (CAO) acutely comes to human, and it highly threats the human's life. When CAO detected, percutaneous coronary intervention (PCI) should be conducted timely. Before PCI, localizing the CAO is needed firstly, because the heart is covered with various arteries. We handle the three kinds of CAO in this paper and our purpose is not only localization of CAO but also improving the localizing performance via preprocessing method. We improve the area under the receiver operating characteristics curve at CAO site localization from a minimum of 0.150 to a maximum of 0.372 via our noise reduction and pulse extraction-based method. (c) 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

关键词： coronary artery occlusion localization preprocessing method

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The preprocessing method for software reliability failure data

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2nd International Conference on Chemical, Material and Metallurgical Engineering (ICCMME 2012)

作者： Li, Qiuying Zhang, Huiqi Beijing Univ Aeronaut & Astronaut Sch Reliabil & Syst Engn Beijing Peoples R China

ISBN: (纸本)9783037855898

The software reliability failure data is the foundation of the software reliability's quantitative evaluation based on the failure data, and it has an important influence on the accuracy of reliability evaluation. But there are always noises in the original software reliability failure data and make the reliability evaluation accuracy affected. This paper put forward the collecting method of reliability failure data and data preprocessing method including data cleaning and data analysis method, which based on the analysis of the importance and the source of failure data in the software reliability testing and the classification of software failure data. Finally through an example, it displayed the reduction of data noises and the promotion of data quality which produced by the preprocessing methods.

关键词： preprocessing method failure data software reliability data cleaning data noise

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A preprocessing method of AdaBoost for Mislabeled Data Classification 29

A Preprocessing Method of AdaBoost for Mislabeled Data Class...

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第29届中国控制与决策会议

作者： Xiangyang Liu Yaping Dai Yan Zhang Qiao Yuan Linhui Zhao School Of Automation Beijing Institute Of Technology

ISBN: (纸本)9781509046584

AdaBoost is one of the most popular algorithm for classification and has been successfully used for text classification,face detection and *** noise sensitivity is regarded as a major disadvantage and previous works show that AdaBoost will be overfitting when dealing with the data sets with noisy *** improve the noise tolerance of conventional AdaBoost,this paper proposed a preprocessing method of AdaBoost for mislabeled data to find the noisy data and correct *** decision stump is selected as the weak learner of the AdaBoost algorithm for *** comparison of simulation results between conventional AdaBoost and the method proposed in this paper shows that the proposed algorithm has improved testing accuracy of the data sets with the noisy data.

关键词： AdaBoost Classification Mislabeled data preprocessing method decision stump

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The preprocessing method of Control Points in Geometric Correction for UAV Remote Sensing Image

The Preprocessing Method of Control Points in Geometric Corr...

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2016 5th International Conference on Advanced Materials and Computer Science(ICAMCS 2016)

作者： Lirong Diao Riuan Liu Tingting Chen School of electronic and communication engineering Tianjin Normal University

This paper focuses on the preprocessing method of control points in geometric correction for UAV(Unmanned Aerial Vehicle) remote sensing *** points preprocessing refers to find out the calibration points from the selected control points,so as to use the calibration points to fit the geometric correction *** in traditional K-means algorithm,clustering results have a strong dependence on initial clustering centers,so selecting initial clustering centers randomly will lead to the clustering results instability when preprocessing control points with traditional K-means algorithm,and it will influence the effect of the UAV remote sensing image geometric ***,the paper imports the thought of Huffman tree to traditional K-means algorithm,aiming at optimizing the selection of initial clustering centers and improving the effect of UAV remote sensing image geometric correction ultimately.

关键词： Control points preprocessing method K-means algorithm Huffman tree

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PCA-Based preprocessing method of Electronic Data in Power Grid

PCA-Based Preprocessing Method of Electronic Data in Power G...

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2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Shuyuan Wang Tienan He Xiantu Ma School of Mechatronics Engineering Baicheng Vocational and Technical College Baicheng City Jilin Pro School of Mechatronics Engineering Baicheng Vocational and Technical College Baicheng Cityjilin Prov School of Mechatronics Engineering Baicheng Vocational and Technical College Baicheng City Jilin Pro

ISBN: (纸本)9781424479573

The electronic data which are acquired respectively by SCADA (Supervisory Control and Data Acquisition) and WAMS (wide-area measurement system) have different structures and characters, therefore these two kinds of data could not be merged easily as well as used conveniently. This problem makes online analysis in SASOPG (Stabilization and Security of Power Grid) difficult Aiming the problem, this paper proposes a PCA-based preprocessing method of electronic data in power grid. The method is based on a two-stage state estimation algorithm optimized by PCA. By using linear/non-linear mixed state estimation algorithm, the origin data from SCADA/WAMS are transformed into state values. To accelerate the state estimation restrained rapidly, a data value optimized algorithm of principal component analysis is provided, and finally the basic message of online analysis is obtained. The result shows that the processing method merges the electronic data well, and it also has higher execution efficiency.

关键词： electronic data preprocessing method Power Grid online analysis

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PCA-Based preprocessing method of Electronic Data in Power Grid

PCA-Based Preprocessing Method of Electronic Data in Power G...

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2010 International Conference on Computer,Mechatronics, Control and Electronic Engineering (CMCE 2010)

作者： Shuyuan Wang Tienan He Xiantu Ma School of Mechatronics Engineering Baicheng Vocational and Technical College Baicheng City,Jilin Province,china

The electronic data which are acquired respectively by SCADA (Supervisory Control and Data Acquisition) and WAMS (wide-area measurement system) have different structures and characters, therefore these two kinds of data could not be merged easily as well as used conveniently. This problem makes online analysis in SASOPG (Stabilization and Security of Power Grid) difficult. Aiming the problem, this paper proposes a PCA-based preprocessing method of electronic data in power grid. The method is based on a two-stage state estimation algorithm optimized by PCA. By using linear/non-linear mixed state estimation algorithm, the origin data from SCADA/WAMS are transformed into state values. To accelerate the state estimation restrained rapidly, a data value optimized algorithm of principal component analysis is provided, and finally the basic message of online analysis is obtained. The result shows that the processing method merges the electronic data well, and it also has higher execution efficiency.

关键词： electronic data preprocessing method Power Grid online analysis

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