Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00064
Jiangwei Tian, Qing Liu
Entity alignment (EA) is the core technology of building large-scale knowledge base and realizing knowledge fusion. In recent two years, many researches use the graph convolution neural network (GCN) for entity alignment and have achieved good results. However, the existing GCN-based EA algorithms do not effectively utilize the semantic information between entities. In this paper, an EA method combining GCN with translation model is proposed. It separately learns the embedded vectors of entities based on GCN and translation model, and then computes the distance of vectors to align entities. Experiments on real-world datasets show the effectiveness of the proposed approach.
{"title":"An Entity Alignment Algorithm Based on GCN and Translation Model","authors":"Jiangwei Tian, Qing Liu","doi":"10.1109/ICDSBA51020.2020.00064","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00064","url":null,"abstract":"Entity alignment (EA) is the core technology of building large-scale knowledge base and realizing knowledge fusion. In recent two years, many researches use the graph convolution neural network (GCN) for entity alignment and have achieved good results. However, the existing GCN-based EA algorithms do not effectively utilize the semantic information between entities. In this paper, an EA method combining GCN with translation model is proposed. It separately learns the embedded vectors of entities based on GCN and translation model, and then computes the distance of vectors to align entities. Experiments on real-world datasets show the effectiveness of the proposed approach.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129645998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00056
Jin Gao, Chen Cao, Wen-liang Li, Xuedeng Li
Based on intelligent vehicle and infrastructure system development and road transport risk prevention demand. This paper proposes. The risk prevention methods for commercial vehicles based on intelligent vehicle and infrastructure system (Referred to as "RPCS-IVIS")was proposed in this paper. RPCS-IVIS contains intelligent commercial vehicles, infrastructures, cloud platform, vehicle monitoring platform etc. Based on the risk prevention demand of commercial vehicles, the paper summarizes and extracts the prevention function such as Forward Vehicle Collision Warning (FCW), Advanced Emergency Braking (AEBS) and roll control. Based on the bottom, line principle of safety, the research is oriented to not lower than the individual intelligence indicators and make up the weak points of the individual intelligence risk prevention method. RPCS-IVIS was proposed in the study, and selected a typical scenario to carry out the real vehicle verification.
{"title":"Research and Verification of Risk Prevention Methods for Commercial Vehicles Based on Intelligent Vehicle and Infrastructure System","authors":"Jin Gao, Chen Cao, Wen-liang Li, Xuedeng Li","doi":"10.1109/ICDSBA51020.2020.00056","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00056","url":null,"abstract":"Based on intelligent vehicle and infrastructure system development and road transport risk prevention demand. This paper proposes. The risk prevention methods for commercial vehicles based on intelligent vehicle and infrastructure system (Referred to as \"RPCS-IVIS\")was proposed in this paper. RPCS-IVIS contains intelligent commercial vehicles, infrastructures, cloud platform, vehicle monitoring platform etc. Based on the risk prevention demand of commercial vehicles, the paper summarizes and extracts the prevention function such as Forward Vehicle Collision Warning (FCW), Advanced Emergency Braking (AEBS) and roll control. Based on the bottom, line principle of safety, the research is oriented to not lower than the individual intelligence indicators and make up the weak points of the individual intelligence risk prevention method. RPCS-IVIS was proposed in the study, and selected a typical scenario to carry out the real vehicle verification.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132317449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00061
Chengbo Hu, Ziquan Liu, Jinggang Yang
Power grid knowledge is an important component of power grid data. With the rapid development of power grid, the knowledge data of power grid is increasing greatly, and its data scale is becoming more and more huge. Through the research of graph data technology, the knowledge data of power grid is optimized. The optimized knowledge map can meet the needs of rapid, efficient, accurate and stable application of power grid knowledge data.
{"title":"Research on Optimization Technology of Power Grid Knowledge Map Based on Graph Data Technology","authors":"Chengbo Hu, Ziquan Liu, Jinggang Yang","doi":"10.1109/ICDSBA51020.2020.00061","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00061","url":null,"abstract":"Power grid knowledge is an important component of power grid data. With the rapid development of power grid, the knowledge data of power grid is increasing greatly, and its data scale is becoming more and more huge. Through the research of graph data technology, the knowledge data of power grid is optimized. The optimized knowledge map can meet the needs of rapid, efficient, accurate and stable application of power grid knowledge data.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134309509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00075
F. Bi, Bo Yang, Jing Guo, Tianguo Jin, Changxi Liu, Xiaohong Wang
The fiber-reinforced composites elastic diaphragm is the key elastic element of the elastic coupling, and its laminate design method has not been finalized yet. Based on the micromechanics theory of composites, this paper uses ABAQUS software to establish the analysis model of different laminate schemes, compares the influence of different laminates on the performance parameters of the diaphragm disc, and gives the laminate computer aided design of the laminated fiber reinforced composites elastic diaphragm disc method.
{"title":"Research on the Computer Aided Design Method of Fiber Reinforced Composites Diaphragm Disc","authors":"F. Bi, Bo Yang, Jing Guo, Tianguo Jin, Changxi Liu, Xiaohong Wang","doi":"10.1109/ICDSBA51020.2020.00075","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00075","url":null,"abstract":"The fiber-reinforced composites elastic diaphragm is the key elastic element of the elastic coupling, and its laminate design method has not been finalized yet. Based on the micromechanics theory of composites, this paper uses ABAQUS software to establish the analysis model of different laminate schemes, compares the influence of different laminates on the performance parameters of the diaphragm disc, and gives the laminate computer aided design of the laminated fiber reinforced composites elastic diaphragm disc method.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132865301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00012
Zhansheng Hou, Shijun Sun, Lin Peng, Zhen Yu, Jinyin Song, He Wang, Min Xu, Gang Wang, Xingchuan Bao, Hai Yu, Zhimin He, Liang Zhu, Xiyuan Xu, Zehao Zhang, Shiyang Tang
At present domestic emergency information interaction lack of flexibility, after a natural disaster, on-site rescue workers with the rescue headquarters, emergency command center, sharing of information between were studied based on the scene of the electric power emergency mobile information real-time interactive methods, design a kind of power at the scene of the emergency mobile friendly each other, are at the scene of the emergency and emergency command center cluster information real-time interactive technology, gives the power emergency field information real-time interactive system prototype and power at the scene of the emergency information real-time interactive software and hardware integration solutions, to build the efficient method of multi-type information submitted by emergency disposal across departments and information interaction ability.
{"title":"The Utility Model Relates to a Real-Time Interaction Method of Mobile Terminal Information Based on Power Emergency Scene","authors":"Zhansheng Hou, Shijun Sun, Lin Peng, Zhen Yu, Jinyin Song, He Wang, Min Xu, Gang Wang, Xingchuan Bao, Hai Yu, Zhimin He, Liang Zhu, Xiyuan Xu, Zehao Zhang, Shiyang Tang","doi":"10.1109/ICDSBA51020.2020.00012","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00012","url":null,"abstract":"At present domestic emergency information interaction lack of flexibility, after a natural disaster, on-site rescue workers with the rescue headquarters, emergency command center, sharing of information between were studied based on the scene of the electric power emergency mobile information real-time interactive methods, design a kind of power at the scene of the emergency mobile friendly each other, are at the scene of the emergency and emergency command center cluster information real-time interactive technology, gives the power emergency field information real-time interactive system prototype and power at the scene of the emergency information real-time interactive software and hardware integration solutions, to build the efficient method of multi-type information submitted by emergency disposal across departments and information interaction ability.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125730242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00019
Ma Jie, Sun Shiming, Cen Hongxing, Qian Hanjia, Wang Xiaofei, Zhou Mengqi
In this study the customer load power curve characteristics with special line and private transformer, which can be obtained by big data technology processing, are analyzed for getting the time-varying characteristics of load power in typical power consumption industry and composition proportion of power consumption industry. Furthermore, an approach for systems automatic identification using artificial inteligence was proposed, so that the situation regarding the production of a factory is possible to grasp in real time. In the special period of the epidemic situation, it has provided a strong technical support for the power companies in Jiangsu Province and other cities to master the production situation of large-scale enterprises. In the long term, research into load model identification and cluster analysis technology based on bus in this paper, will constitute the basis of future work in bus load forecasting. Also it will be a good infrastructure for making value added services related to electricity industry.
{"title":"Analysis and Application of Customer Load with Special Line and Private Transformer Based on Artificial Intelligence","authors":"Ma Jie, Sun Shiming, Cen Hongxing, Qian Hanjia, Wang Xiaofei, Zhou Mengqi","doi":"10.1109/ICDSBA51020.2020.00019","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00019","url":null,"abstract":"In this study the customer load power curve characteristics with special line and private transformer, which can be obtained by big data technology processing, are analyzed for getting the time-varying characteristics of load power in typical power consumption industry and composition proportion of power consumption industry. Furthermore, an approach for systems automatic identification using artificial inteligence was proposed, so that the situation regarding the production of a factory is possible to grasp in real time. In the special period of the epidemic situation, it has provided a strong technical support for the power companies in Jiangsu Province and other cities to master the production situation of large-scale enterprises. In the long term, research into load model identification and cluster analysis technology based on bus in this paper, will constitute the basis of future work in bus load forecasting. Also it will be a good infrastructure for making value added services related to electricity industry.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121779583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00085
Yu Liu, Min Xiang, Xiaoxiang Zhao, Run Zhou
Due to the limited resources of the Internet of things terminal, the speed of image recognition is difficult to meet the application requirements. A design method of a fast image recognition accelerator based on a convolutional neural network (CNN) is proposed. A pipeline processing scheme combining software and hardware is designed. The operation strategy of the parallel image block, parallel input channel, and parallel output channel is adopted. Based on this strategy, a model of terminal resources and recognition time is established. By solving the model, the optimal number of image partition blocks and convolution parallel parameters are obtained. The experimental results show that the computational performance of the proposed accelerator is improved from 8.86 GOPs to 12.26 GOPs, which effectively improves the speed of image recognition.
{"title":"Design of Fast Image Recognition Accelerator Based on Convolutional Neural Network","authors":"Yu Liu, Min Xiang, Xiaoxiang Zhao, Run Zhou","doi":"10.1109/ICDSBA51020.2020.00085","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00085","url":null,"abstract":"Due to the limited resources of the Internet of things terminal, the speed of image recognition is difficult to meet the application requirements. A design method of a fast image recognition accelerator based on a convolutional neural network (CNN) is proposed. A pipeline processing scheme combining software and hardware is designed. The operation strategy of the parallel image block, parallel input channel, and parallel output channel is adopted. Based on this strategy, a model of terminal resources and recognition time is established. By solving the model, the optimal number of image partition blocks and convolution parallel parameters are obtained. The experimental results show that the computational performance of the proposed accelerator is improved from 8.86 GOPs to 12.26 GOPs, which effectively improves the speed of image recognition.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124209503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00078
Qingda Guo, Quan Yanming
Different view point clouds of objects can be achieved through machine vision and need to be translated into a coherent coordinate system for registration. To reduce the number of iterations of accurate registration algorithm and avoid local optical algorithm, coarse registration can provide the initial value of good posture for precise registration. For solving the issues, we proposed a practical coarse registration method of point clouds based on image feature points. In the proposed method, 3D feature point detection methods were respectively established based on dense point clouds derived from monocular structured light vision according to 2D feature points detected by using Speeded Up Robust Features (SURF) algorithm. Through the combination of rigid body posture measurement method and removing method of gross error points, the precise rotation matrix and translation vector before and after moving point clouds were obtained. In the experiment, we introduced the method of dense point clouds derived from structured light in detail. The experimental results indicated that the method could provide good initial postures for precise registration of point clouds.
{"title":"Coarse registration of dense point clouds based on image feature points","authors":"Qingda Guo, Quan Yanming","doi":"10.1109/ICDSBA51020.2020.00078","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00078","url":null,"abstract":"Different view point clouds of objects can be achieved through machine vision and need to be translated into a coherent coordinate system for registration. To reduce the number of iterations of accurate registration algorithm and avoid local optical algorithm, coarse registration can provide the initial value of good posture for precise registration. For solving the issues, we proposed a practical coarse registration method of point clouds based on image feature points. In the proposed method, 3D feature point detection methods were respectively established based on dense point clouds derived from monocular structured light vision according to 2D feature points detected by using Speeded Up Robust Features (SURF) algorithm. Through the combination of rigid body posture measurement method and removing method of gross error points, the precise rotation matrix and translation vector before and after moving point clouds were obtained. In the experiment, we introduced the method of dense point clouds derived from structured light in detail. The experimental results indicated that the method could provide good initial postures for precise registration of point clouds.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130912097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00033
Yuehua Yue, Lianyin Jia, Hongsong Zhai, Ming Kong, Mengjuan Li
Octane number (ON) is the most important index of vehicle gasoline specification. Due to the complexity of refining process, the equipment variety, a large number of features are collected, which makes it difficult to predict ON of gasoline. In this paper, we propose a combined feature selection and decision tree based prediction method, CFS-DT, which combines low variance filtering, high correlation filtering and random forest to execute feature selection on a large number of original feature first. After that, a decision tree(DT) is trained for ON prediction on selected features. Experiments are carried out on datasets collected from 2020 Huawei cup Mathematical Modeling show that our model has a good effectiveness and achieves a 89% prediction precision.
{"title":"CFS-DT : a Combined Feature Selection and Decision Tree based Method for Octane Number Prediction","authors":"Yuehua Yue, Lianyin Jia, Hongsong Zhai, Ming Kong, Mengjuan Li","doi":"10.1109/ICDSBA51020.2020.00033","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00033","url":null,"abstract":"Octane number (ON) is the most important index of vehicle gasoline specification. Due to the complexity of refining process, the equipment variety, a large number of features are collected, which makes it difficult to predict ON of gasoline. In this paper, we propose a combined feature selection and decision tree based prediction method, CFS-DT, which combines low variance filtering, high correlation filtering and random forest to execute feature selection on a large number of original feature first. After that, a decision tree(DT) is trained for ON prediction on selected features. Experiments are carried out on datasets collected from 2020 Huawei cup Mathematical Modeling show that our model has a good effectiveness and achieves a 89% prediction precision.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123684249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/ICDSBA51020.2020.00027
Wei Ye Shi, Hong Xing Xu
The event-based quantitative trading system can avoid human subjective judgment errors in the stock and futures trading markets, and the development of quantitative trading strategies based on "high probability" events in history can obtain ideal returns. It is essentially a discrete event processing system. It uses a computer to simulate and process random events with high probability. The core of the quantitative trading system is its engine part driven by transaction data. These transaction data can be regarded as a series of discrete events. This article summarizes and introduces the strategy-driven engine part of the quantitative trading system based on the open source quantitative trading framework VNPY as an example. It mainly includes a real trading operation engine module and a strategy backtesting module. The real trading engine links the trading market to obtain real-time data and uses quantitative strategies for trading; the backtest module runs to test trading strategies and optimizes the strategy parameters.
{"title":"The Driving Engine of Quantitative Trading Strategy Based on Event Processing","authors":"Wei Ye Shi, Hong Xing Xu","doi":"10.1109/ICDSBA51020.2020.00027","DOIUrl":"https://doi.org/10.1109/ICDSBA51020.2020.00027","url":null,"abstract":"The event-based quantitative trading system can avoid human subjective judgment errors in the stock and futures trading markets, and the development of quantitative trading strategies based on \"high probability\" events in history can obtain ideal returns. It is essentially a discrete event processing system. It uses a computer to simulate and process random events with high probability. The core of the quantitative trading system is its engine part driven by transaction data. These transaction data can be regarded as a series of discrete events. This article summarizes and introduces the strategy-driven engine part of the quantitative trading system based on the open source quantitative trading framework VNPY as an example. It mainly includes a real trading operation engine module and a strategy backtesting module. The real trading engine links the trading market to obtain real-time data and uses quantitative strategies for trading; the backtest module runs to test trading strategies and optimizes the strategy parameters.","PeriodicalId":354742,"journal":{"name":"2020 4th Annual International Conference on Data Science and Business Analytics (ICDSBA)","volume":"56 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113941067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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