Pub Date : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343471
Jiao Xuan, Huang Ming
Compared to other intelligent optimization algorithms, Quantum Particle Swarm Optimization (QPSO) possesses the characteristics like rapid convergence rate and outstanding global optimization performance etc. It is more applicable to solve workshop scheduling problems. The article proposes the strategy of improved dynamic reglation of rotation angle to solve multi-objective FJSP problems on the basis of Quantum Particle Swarm Optimization. The method can ensure the position with large variation of adaptive value not over optimal regulation measure, increase the capability to search optimal solution at the position with small variation of adaptive value, and verify the effectiveness of new algorithm through simulation experiement.
{"title":"An improved Quantum Particle Swarm Optimization and its application","authors":"Jiao Xuan, Huang Ming","doi":"10.1109/ICCSNT.2017.8343471","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343471","url":null,"abstract":"Compared to other intelligent optimization algorithms, Quantum Particle Swarm Optimization (QPSO) possesses the characteristics like rapid convergence rate and outstanding global optimization performance etc. It is more applicable to solve workshop scheduling problems. The article proposes the strategy of improved dynamic reglation of rotation angle to solve multi-objective FJSP problems on the basis of Quantum Particle Swarm Optimization. The method can ensure the position with large variation of adaptive value not over optimal regulation measure, increase the capability to search optimal solution at the position with small variation of adaptive value, and verify the effectiveness of new algorithm through simulation experiement.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"35 33","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113984309","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343692
Yi Chen, Yusong Tan, Q. Wu, Wei Wang
Entity linking has an important basic research value for Natural Language Processing, the task of which is to link different entity mentions in the given text with their referent entities in a knowledge base. And it is widely used in such fields as expanding knowledge base, Q&A system, machine translation. We propose a Chinese collective entity linking algorithm based on the extracted topic features. We construct the topic relation graph of ambiguous entities in the same text, extract the topic characteristics from the multiple topic models, calculate the topic relevance, and select the topic subgraph with maximum score to reason and realize the batch linking. We experiment with both the news test corpus and the microblog test corpus, compare the performance of the adopted topic model, and analyze their applicable scene. When compared with the traditional algorithm, the maximum performance of our algorithm is improved by about 9% in microblog corpus and over 15% in news corpus, which indicates that our algorithm is potentially effective.
{"title":"TGCEL: A Chinese entity linking method based on topic relation graph","authors":"Yi Chen, Yusong Tan, Q. Wu, Wei Wang","doi":"10.1109/ICCSNT.2017.8343692","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343692","url":null,"abstract":"Entity linking has an important basic research value for Natural Language Processing, the task of which is to link different entity mentions in the given text with their referent entities in a knowledge base. And it is widely used in such fields as expanding knowledge base, Q&A system, machine translation. We propose a Chinese collective entity linking algorithm based on the extracted topic features. We construct the topic relation graph of ambiguous entities in the same text, extract the topic characteristics from the multiple topic models, calculate the topic relevance, and select the topic subgraph with maximum score to reason and realize the batch linking. We experiment with both the news test corpus and the microblog test corpus, compare the performance of the adopted topic model, and analyze their applicable scene. When compared with the traditional algorithm, the maximum performance of our algorithm is improved by about 9% in microblog corpus and over 15% in news corpus, which indicates that our algorithm is potentially effective.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122683567","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343702
A. Xie, D. Liu
This paper proposed a new general framework for intelligent optimization based on organizing tactics rather than probability rules. Compared with the existing intelligent optimization algorithms, like Particle Swarm Optimization, this framework has several significant advantages. First, the “intelligence” does not depend on the probability rules of the operators, but their organizing tactics. Thus there are no probability equations that need to be updated, and involved control parameters are fewer, so it is easier to use in practice. Second, synergistic coexistence and automatic balance of the exploration and the exploitation are achieved in the running. Third, population diversity has been kept during the running. Fourth, most useless and ineffective repetitious operations are avoided, and thus the needed consumption of storage space and running time are lessened largely.
{"title":"Organizing tactics based optimization theory","authors":"A. Xie, D. Liu","doi":"10.1109/ICCSNT.2017.8343702","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343702","url":null,"abstract":"This paper proposed a new general framework for intelligent optimization based on organizing tactics rather than probability rules. Compared with the existing intelligent optimization algorithms, like Particle Swarm Optimization, this framework has several significant advantages. First, the “intelligence” does not depend on the probability rules of the operators, but their organizing tactics. Thus there are no probability equations that need to be updated, and involved control parameters are fewer, so it is easier to use in practice. Second, synergistic coexistence and automatic balance of the exploration and the exploitation are achieved in the running. Third, population diversity has been kept during the running. Fourth, most useless and ineffective repetitious operations are avoided, and thus the needed consumption of storage space and running time are lessened largely.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126188531","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343709
Jing Tao, Hongbo Wang, Xinyu Zhang, Xiaoyu Li, Hua-wei Yang
We build an object detection system for images in traffic scene. It is fast, accurate and robust. Traditional object detectors first generate proposals. After that the features are extracted. Then a classifier on these proposals is executed. But the speed is slow and the accuracy is not satisfying. YOLO an excellent object detection approach based on deep learning presents a single convolutional neural network for location and classification. All the fully-connected layers of YOLO's network are replaced with an average pool layer for the purpose of reproducing a new network. The loss function is optimized after the proportion of bounding coordinates error is increased. A new object detection method, OYOLO (Optimized YOLO), is produced, which is 1.18 times faster than YOLO, while outperforming other region-based approaches like R-CNN in accuracy. To improve accuracy further, we add the combination of OYOLO and R-FCN to our system. For challenging images in nights, pre-processing is presented using the histogram equalization approach. We have got more than 6% improvement in mAP on our testing set.
{"title":"An object detection system based on YOLO in traffic scene","authors":"Jing Tao, Hongbo Wang, Xinyu Zhang, Xiaoyu Li, Hua-wei Yang","doi":"10.1109/ICCSNT.2017.8343709","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343709","url":null,"abstract":"We build an object detection system for images in traffic scene. It is fast, accurate and robust. Traditional object detectors first generate proposals. After that the features are extracted. Then a classifier on these proposals is executed. But the speed is slow and the accuracy is not satisfying. YOLO an excellent object detection approach based on deep learning presents a single convolutional neural network for location and classification. All the fully-connected layers of YOLO's network are replaced with an average pool layer for the purpose of reproducing a new network. The loss function is optimized after the proportion of bounding coordinates error is increased. A new object detection method, OYOLO (Optimized YOLO), is produced, which is 1.18 times faster than YOLO, while outperforming other region-based approaches like R-CNN in accuracy. To improve accuracy further, we add the combination of OYOLO and R-FCN to our system. For challenging images in nights, pre-processing is presented using the histogram equalization approach. We have got more than 6% improvement in mAP on our testing set.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126369071","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343750
P. He, Hongli Chang, Han Gao, ZiYi Wang
Nowadays, People put increasingly higher demands on the quality of life. How to develop a set of health and efficient dairy farm system has become an important issue. This paper mainly researches dairy farm management, using AVR and 24L01 wireless module to design a set of zap automation management system. It realizes the full automation of the dairy farm management. First, this paper puts forward the implementation of the system function and the overall scheme. I design the structure of the system, then, I design the hardware circuit of the system, including the function of each module and the working process of the system, Finally, the cow management system software is designed.
{"title":"Research on cattle farm management information system","authors":"P. He, Hongli Chang, Han Gao, ZiYi Wang","doi":"10.1109/ICCSNT.2017.8343750","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343750","url":null,"abstract":"Nowadays, People put increasingly higher demands on the quality of life. How to develop a set of health and efficient dairy farm system has become an important issue. This paper mainly researches dairy farm management, using AVR and 24L01 wireless module to design a set of zap automation management system. It realizes the full automation of the dairy farm management. First, this paper puts forward the implementation of the system function and the overall scheme. I design the structure of the system, then, I design the hardware circuit of the system, including the function of each module and the working process of the system, Finally, the cow management system software is designed.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122876054","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343732
Wenying Mo, Ying Gao
In recent years, more and more approaches were proposed for vehicle logo recognition. However, most of the approaches achieve high performance only when the images have high resolution and the number of vehicle type to be classified is few. In this paper, a novel algorithm is proposed to treat with various resolutions of vehicle images and recognize a large number of vehicle logos. This algorithm is based on adaptive scaling sliding window and template matching with screening masks that is applied to detect the most accurate size and feature position of the target logo. In order to solve the problem that complicated texture noise affects the accuracy of template matching seriously, different screening masks are utilized for different vehicles. The algorithm avoids the difficulties of features localization and can recognize a great number of vehicle logos. This algorithm is applied on a dataset comprised of 10000 vehicle images with 102 types of vehicle logos taken in different environment by different traffic cameras. Experiment results show an overall recognition ratio of 91.62%.
{"title":"Vehicle type recognition based on adaptive scaling window and masks","authors":"Wenying Mo, Ying Gao","doi":"10.1109/ICCSNT.2017.8343732","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343732","url":null,"abstract":"In recent years, more and more approaches were proposed for vehicle logo recognition. However, most of the approaches achieve high performance only when the images have high resolution and the number of vehicle type to be classified is few. In this paper, a novel algorithm is proposed to treat with various resolutions of vehicle images and recognize a large number of vehicle logos. This algorithm is based on adaptive scaling sliding window and template matching with screening masks that is applied to detect the most accurate size and feature position of the target logo. In order to solve the problem that complicated texture noise affects the accuracy of template matching seriously, different screening masks are utilized for different vehicles. The algorithm avoids the difficulties of features localization and can recognize a great number of vehicle logos. This algorithm is applied on a dataset comprised of 10000 vehicle images with 102 types of vehicle logos taken in different environment by different traffic cameras. Experiment results show an overall recognition ratio of 91.62%.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127809155","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}
AC filter in converter station is an important part of HVDC transmission system, and the tripping accident of AC filter will directly affect the transmission power of the DC transmission system. This paper presents a method for on-line identification of AC filter's health status based on the opening/closing current of AC filter's breaker. Firstly, a series of time domain feature and frequency domain feature of the opening/closing current of AC filter's breaker are defined. On this basis, radial basis function (RBF) neural network-based artificial intelligence method is used to identify the fault warning of AC filter. The results of an actual converter station show that the proposed method has high fault warning accuracy. It can alert staff to check and maintain AC filter before the abnormal status enlarges or causes adverse effects, and the occurrence of AC filter's tripping phenomenon can be reduced a lot.
{"title":"Research on fault warning of AC filter in converter station based on RBF neural network","authors":"Lei Shi, Shenxi Zhang, Junhong Li, Peng Wei, Zhiyuan Liu, Zhixian Zhang","doi":"10.1109/ICCSNT.2017.8343707","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343707","url":null,"abstract":"AC filter in converter station is an important part of HVDC transmission system, and the tripping accident of AC filter will directly affect the transmission power of the DC transmission system. This paper presents a method for on-line identification of AC filter's health status based on the opening/closing current of AC filter's breaker. Firstly, a series of time domain feature and frequency domain feature of the opening/closing current of AC filter's breaker are defined. On this basis, radial basis function (RBF) neural network-based artificial intelligence method is used to identify the fault warning of AC filter. The results of an actual converter station show that the proposed method has high fault warning accuracy. It can alert staff to check and maintain AC filter before the abnormal status enlarges or causes adverse effects, and the occurrence of AC filter's tripping phenomenon can be reduced a lot.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"606 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132657298","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343711
J. Huo, Zhinan Ren, Yongru Yang, Milin Ren
The harsh natural environments of the High altitude, cold and arid areas led to the deficient acquisition ability of field monitoring data and the insufficient networking researches and so on. Thus, it seriously restricts the Geoscience researches in these areas. Combining the practical situation of the observation systems deployed in the field station, this paper studies the key technologies of observation instruments networking based on the IPv6 technology to construct the observation instruments' network in the cold and arid areas. The research is to realize the tasks of data collection, data transmission and status monitoring of observation devices. It can enhance the automation level, real-time performance and quality of field observation data for the cold and arid areas.
{"title":"Networking research of observation instruments based on IPv6 technology","authors":"J. Huo, Zhinan Ren, Yongru Yang, Milin Ren","doi":"10.1109/ICCSNT.2017.8343711","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343711","url":null,"abstract":"The harsh natural environments of the High altitude, cold and arid areas led to the deficient acquisition ability of field monitoring data and the insufficient networking researches and so on. Thus, it seriously restricts the Geoscience researches in these areas. Combining the practical situation of the observation systems deployed in the field station, this paper studies the key technologies of observation instruments networking based on the IPv6 technology to construct the observation instruments' network in the cold and arid areas. The research is to realize the tasks of data collection, data transmission and status monitoring of observation devices. It can enhance the automation level, real-time performance and quality of field observation data for the cold and arid areas.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115951630","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 : 2017-10-01DOI: 10.1109/ICCSNT.2017.8343751
Tong Zhang, Changxian Li, Zong-Liang Li
Train communication network has become the application mainstream of EMU and urban rail traffic operation. However, practical problems such as transmission delay and packet loss of communication network can cause a significant threat to the train stability and operation safety. In this paper, the delay of the train communication network was studied and controlled, and the experimental platform was built to test and analyze the forward delay transmission characteristics of the train network. The self-adaptive prediction was achieved by using the autoregressive model. At the same time, the generalized predictive control method was designed to realize the control and delay compensation of the system. On the experimental platform, joint simulation method was used with the configuration software. The results showed that the proposed method is superior to the PID control, which can meet the real time control requirements of the high speed EMU operation process.
{"title":"Generalized predictive control and delay compensation for high — Speed EMU network control system","authors":"Tong Zhang, Changxian Li, Zong-Liang Li","doi":"10.1109/ICCSNT.2017.8343751","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343751","url":null,"abstract":"Train communication network has become the application mainstream of EMU and urban rail traffic operation. However, practical problems such as transmission delay and packet loss of communication network can cause a significant threat to the train stability and operation safety. In this paper, the delay of the train communication network was studied and controlled, and the experimental platform was built to test and analyze the forward delay transmission characteristics of the train network. The self-adaptive prediction was achieved by using the autoregressive model. At the same time, the generalized predictive control method was designed to realize the control and delay compensation of the system. On the experimental platform, joint simulation method was used with the configuration software. The results showed that the proposed method is superior to the PID control, which can meet the real time control requirements of the high speed EMU operation process.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114154413","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}
During the 13th Five-Year period, the internal and external environment of Jiangsu Grid development has changed a lot. The first provincial UHVAC ring grid is built in China. Installed capacity of clean energy has doubled and the proportion of electricity consumption achieved 45%. The increased number of electric cars is expected to millions, which will be charged in the city center. Changes in different aspects require that Jiangsu Grid can quickly response to grid emergency exceptions and coordinate user load to guarantee grid stable operation with the minimal cost when grid is broken down. Thus the large-scale supply and demand friendly interactive system is being built by Jiangsu Grid to realize the intelligence interaction and quick control of user load. This paper discusses different technologies of how large-scale supply and demand friendly interactive system can rapidly control the load of interactive user. Several aspects like load control mode, load interactive terminal of smart grid, as well as the master station are all considered in realizing load quick control.
{"title":"Research on load fast control technology in large-scale supply-demand friendly interaction system","authors":"Wei Yu, Shubo Liu, Zheng Xiong, Yu Song, Daoqiang Xu","doi":"10.1109/ICCSNT.2017.8343752","DOIUrl":"https://doi.org/10.1109/ICCSNT.2017.8343752","url":null,"abstract":"During the 13th Five-Year period, the internal and external environment of Jiangsu Grid development has changed a lot. The first provincial UHVAC ring grid is built in China. Installed capacity of clean energy has doubled and the proportion of electricity consumption achieved 45%. The increased number of electric cars is expected to millions, which will be charged in the city center. Changes in different aspects require that Jiangsu Grid can quickly response to grid emergency exceptions and coordinate user load to guarantee grid stable operation with the minimal cost when grid is broken down. Thus the large-scale supply and demand friendly interactive system is being built by Jiangsu Grid to realize the intelligence interaction and quick control of user load. This paper discusses different technologies of how large-scale supply and demand friendly interactive system can rapidly control the load of interactive user. Several aspects like load control mode, load interactive terminal of smart grid, as well as the master station are all considered in realizing load quick control.","PeriodicalId":163433,"journal":{"name":"2017 6th International Conference on Computer Science and Network Technology (ICCSNT)","volume":"273 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114482208","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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