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17th COTA International Conference of Transportation Professionals: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation, CICTP 2017

作者： Tian, Daxin Liu, Wenhao Guo, Peng Rong, Hui Wang, Wenyang Gong, Jinfeng Wang, Yunpeng Liu, He Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Beijing100191 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang Univ. Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing210096 China Quartermaster Equipment Institute of the General Logistics Dept. of CPLA Beijing100010 China

ISBN: (数字)9780784480915

ISBN: (纸本)9780784480915

This paper addresses the problem of receiving a timetable for a settled network with maximal synchronization. In this paper, a model has been developed to solve the problem which attaches importance to creating a timetable for maximizing their synchronization and enables the transfer of passengers from one route to another with least waiting times at transfer nodes. Next, this problem is formulated as a mixed integer linear programming problem, and a new algorithm based on the traditional particle swarm optimization (PSO) has been developed to solve the problem in a short time. Finally, the relationship of iterative time and the complexity of the given network is qualitatively established. © ASCE.

关键词： Synchronization

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Development of on-line detection system for simultaneous assessment of edible quality and internal defect in apple by NIR transmittance spectroscopy

Development of on-line detection system for simultaneous ass...

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2017 ASABE Annual International Meeting

作者： Guo, Zhiming Chen, Quansheng Wu, Jingzhu Ouyang, Qin Chen, Hua Zhao, Jiewen School of Food and Biological Engineering Jiangsu University Zhenjiang212013 China Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business University Beijing100048 China

In order to simultaneous nondestructive on-line inspect edible quality and internal defect of apple, this work presents the development of an on-line detection prototype system using near infrared transmittance technology as a novel approach for on-line detect quality attributes without sample destructiveness. The on-line detection system was designed and developed to improve spectra signal quality, lower heat damage, reduce mechanical damage. Special detection software was developed for real-time inspection based on multithread programming technology. This prototype on-line system needed 80 ms capture transmittance spectra of an apple. Linear discriminant analysis (LDA) model was developed to identify internal defects samples. The results obtained from LDA models, in validation, gave a positive predictive value of classification about 90.14%. Moreover, established model strategy is first selection characteristic spectral ranges by synergy interval partial least squares (siPLS), then on the extraction of feature wavelength by stepwise multiple linear regression (SMLR). Calibration models were performed applying siPLS-SMLR algorithm to predict the soluble solid content (SSC) in apple. Results of the siPLS-SMLR model using 9 selected feature wavelengths were correlation coefficient (R) of 0.8764 and root mean square error of prediction (RMSEP) of 0.8649 Brix, respectively.. The results showed that the e on-line detection prototype based on NIR transmittance technique was feasible to simultaneous inspect the edible quality and internal defect of apple. The present research provides the foundation for the future development of an automatic system based on transmittance spectroscopy which is extremely important from the economic point of view.

关键词： Infrared devices

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Flexible energy management protocol for cooperative EV-to-EV charging

arXiv

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arXiv 2018年

作者： Zhang, Rongqing Cheng, Xiang Yang, Liuqing State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Department of Electrical and Computer Engineering Colorado State University CO United States Shenzhen Research Institute of Big Data Shenzhen Guangdong China

In this paper, we investigate flexible power transfer among electric vehicles (EVs) from a cooperative perspective in an EV system. First, the concept of cooperative EV-to- EV (V2V) charging is introduced, which enables active cooperation via charging/discharging operations between EVs as energy consumers and EVs as energy providers. Then, based on the cooperative V2V charging concept, a flexible energy management protocol with different V2V matching algorithms is proposed, which can help the EVs achieve more flexible and smarter charging/discharging behaviors. In the proposed energy management protocol, we define the utilities of the EVs based on the cost and profit through cooperative V2V charging and employ the bipartite graph to model the charging/discharging cooperation between EVs as energy consumers and EVs as energy providers. Based on the constructed bipartite graph, a max-weight V2V matching algorithm is proposed in order to optimize the network social welfare. Moreover, taking individual rationality into consideration, we further introduce the stable matching concepts and propose two stable V2V matching algorithms, which can yield the EV-consumer-optimal and EVprovider- optimal stable V2V matchings, respectively. Simulation results verify the efficiency of our proposed cooperative V2V charging based energy management protocol in improving the EV utilities and the network social welfare as well as reducing the energy consumption of the EVs. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric vehicles

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Traceable certificateless ring signature scheme for no full anonymous applications

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International Journal of Network Security 2018年第4期20卷 762-773页

作者： Gu, Ke Wang, LinYu Wu, Na Liao, NianDong School of Computer and Communication Engineering Changsha University of Science and Technology Wangjiali Rd Tianxin district Changsha Hunan Province410114 China Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology China

With the rapid development of identity-based cryptography, several traceable (or linkable) identity-based ring signature (TIBRS) schemes have been proposed. Compared with ring signature based on public key cryptography, TIBRS can simplify public key management and be used for more applications. However, identity-based cryptography still has the problem of private key management and few traceable ring signature schemes are constructed in the standard model. In this paper, we present a fully traceable certificateless ring signature (TCRS) scheme in the standard model, which has a security reduction to the computational Diffie-Hellman (CDH) assumption. © 2018, Femto Technique Co., Ltd.

关键词： Public key cryptography

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A Hybrid BPSO-GA Algorithm for 0-1 Knapsack Problems 4th

A Hybrid BPSO-GA Algorithm for 0-1 Knapsack Problems

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4th Euro-China Conference on Intelligent data Analysis and Applications, ECC 2017

作者： Wang, Jinshui Liu, Jianhua Pan, Jeng-Shyang Xue, Xingsi Huang, Lili College of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town FuzhouFujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town FuzhouFujian350118 China College of Ecological Environment and Urban Construction Fujian University of Technology No. 3 Xueyuan Road University Town FuzhouFujian350118 China

ISBN: (纸本)9783319685267

0-1 knapsack problems (KPs) is a typical NP-hard problem in combinatorial optimization problem. For the sake of efficiency, it becomes increasingly popular for researchers to apply heuristic techniques to solve the 0-1 KPs. Due to its simplicity and convergence speed, an increasing number of techniques based on binary particle swarm optimization (BPSO) has been presented. However, BPSO-based techniques suffered from a major shortcoming which is the premature convergence of a swam. To address the problem, this paper proposed a hybrid BPSO-GA algorithm which combines the strengths of BPSO and genetic algorithm (GA). Experimental results show that our proposal is able to find more optimal solutions than BPSO-based algorithm. © 2018, Springer International Publishing AG.

关键词： Genetic algorithms

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A Model-Embedded Trend Test with Incorporating Hardy-Weinberg Equilibrium Information

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Journal of Systems Science & Complexity 2017年第1期30卷 101-110页

作者： HU Xiaonan DUAN Xiaogang PAN Dongdong ZHANG Sanguo LI Qizhai School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China KeyLaboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190China. School of Statistics Beijing Normal University Beijing 100875 China. Department of Statistics Yunnan University Kunming 650091 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy ofSciences Beijing 100190 China.

The genetic models are greatly important in the analysis of genetic epidemiologic studies and many of the studies are conducted using the trend test under the additive model. However, for many complex diseases and traits, the underlying genetic model for a genetic locus is usually uncertain. So a robust test free of genetic model is appropriate. In this paper, the authors propose a model-embedded trend test by incorporating Hardy-Weinberg equilibrium information and obtain the explicit formula to calculate its statistical significance. Extensive simulation studies show the proposed test is more robust than the existing procedures. Finally, a real application is further analyzed to show the performance of the proposed test.

关键词： Genetic model hardy-weinberg equilibrium power robust trend test.

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Correction to: Performance study of trial M-THGEM

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Radiation Detection Technology and Methods 2020年第1期4卷 83-83页

作者： Shao-Qing Deng Wen-Qi Yan Dao-Jin Hong Bo-Xiang Yu Gao-Long Zhang Yu-Guang Xie School of Physics and Nuclear Energy Engineering Beihang University Beijing China Institute of High Energy Physics Chinese Academy of Sciences Beijing China University of Science and Technology of China Hefei China State Key Laboratory of Particle Detection and Electronics Beijing China University of Chinese Academy of Sciences Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China

Upon request from the authors, the sequence of grant numbers are corrected as: Nos. 11575221, 11975040, U1832130, 11475013.

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Research on Agricultural Environment Prediction Based on Deep Learning

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Procedia Computer Science 2018年 139卷 33-40页

作者： Shuchang Chen Bingchan Li Jie Cao Bo Mao College of Information Engineering Collaborative Innovation Center for Modern Grain Circulation and Safety Jiangsu Key Laboratory of Grain Big-data Mining Nanjing University of Finance & Economics Nanjing 210023 China School of Electrical and Automation Engineering Jiangsu Maritime Institute Nanjing 211170 China Computer Science and Technology Computer Science and Engineering College Nanjing University of Science and Technology Nanjing 210094 China

The environmental security of agriculture is closely related to human beings. Analytical training of agricultural environmental data, forecasting its development trend, has positive significance for the protection of the safety of agricultural products. This paper proposes an agricultural environment prediction model based on deep learning LSTM (Long Short-Term Memory). By analyzing the agricultural environment parameters of the current period, the environmental parameters of the next moment can be predicted to achieve the purpose of early warning. The experimental results show that the model’s prediction results have little deviation from the actual values; on this basis, the LSTM model is optimized to replace LSTM with GRU(Gated Recurrent Unit), and the model is more effective.

关键词： Deep learning Agricultural environment LSTM GRU

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Multilingual Focused Crawler System based on Web Content Extraction and Path Configuration

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IOP Conference Series: Materials Science and engineering 2019年第5期569卷

作者： Jie Wang Sanhong Deng Lijuan Wang School of Information Management Nanjing University Nanjing 210023 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service (Nanjing University) Nanjing 210023 China Geological Survey of Jiangsu Province Nanjing 210018 China

The multilingual focused crawler system combines web content extraction with path configuration to make use of their advantages and achieve automatic collection of network information in multiple languages. Firstly, system selects foreign language keywords according to crawling webpage language and Chinese keywords, and uses initial link to obtain webpage information. Then, it uses path configuration information or web content extraction algorithm based on the distribution line block to get webpage content, and adopts rules or configuration information to acquire new links, published time and title. Next, keywords are used to filter irrelevant information. Finally, results are presented as a list. When users use focused crawler system, the webpage path information can be configured or not according to requirements, and the collected network resources can also be searched or filtered.

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Mapping essential urban land use categories in China(EULUC-China):preliminary results for 2018

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Science Bulletin 2020年第3期65卷 182-187页

作者： Peng Gong Bin Chen Xuecao Li Han Liu Jie Wang Yuqi Bai Jingming Chen Xi Chen Lei Fang Shuailong Feng Yongjiu Feng Yali Gong Hao Gu Huabing Huang Xiaochun Huang Hongzan Jiao Yingdong Kang Guangbin Lei Ainong Li Xiaoting Li Xun Li Yuechen Li Zhilin Li Zhongde Li Chong Liu Chunxia Liu Maochou Liu Shuguang Liu Wanliu Mao Changhong Miao Hao Ni Qisheng Pan Shuhua Qi Zhehao Ren Zhuoran Shan Shaoqing Shen Minjun Shi Yimeng Song Mo Su Hoi Ping Suen Bo Sun Fangdi Sun Jian Sun Lin Sun Wenyao Sun Tian Tian Xiaohua Tong Yihsing Tseng Ying Tu Hong Wang Lan Wang Xi Wan Zongming Wang Tinghai Wu Yaowen Xie Jian Yang Jun Yang Man Yuan Wenze Yue Hongda Zeng Kuo Zhang Neng Zhang Tao Zhang Yu Zhang Feng Zhao Yichen Zheng Qiming Zhou Nicholas Clinton Zhiliang Zhu Bing Xu Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Tsinghua Urban Institute Tsinghua UniversityBeijing 100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing 100084China Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616-8627USA Department of Geological and Atmospheric Sciences Iowa State UniversityAmesIA 50011USA State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China AI for Earth Laboratory Cross-Strait InstituteTsinghua UniversityBeijing 100084China International Institute for Earth System Sciences Nanjing UniversityNanjing 210093China Research Center for Ecology and Environment of Central Asia Chinese Academy of SciencesUrumchi 830011China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China National Engineering Laboratory for Applied Technology in Forestry&Ecology in South China College of Life Science and TechnologyCentral South University of Forestry and TechnologyChangsha 410004China College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Department of Urban Planning College of Architecture and Urban PlanningTongji UniversityShanghai 200092China Beijing Institute of Urban Planning Beijing 100045China Department of Urban Planning School of Urban DesignWuhan UniversityWuhan 430072China College of Earth Sciences Jilin UniversityChangchun 130061China Research Center for Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Department of Urban and Regional Planning School of Geography and PlanningSun Yat-sen Univ

Land use reflects human activities on *** land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and *** areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2].However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city *** mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping *** address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping *** is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental ***,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same *** at big country or regional levels such as for the United States,China and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://***/open_land_use/).

关键词： EULUC-China 土地利用类型

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