Pub Date : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622231
W. Kinsner, Siavash Malektaji
Cognitive systems call for wireless communications with antennas having stringent requirements. For example, software-defined radio, cognitive radio, and cognitive sensor networks operate over very wide bandwidth, with small dimensions, high gain, and omnidirectionally. A candidate capable of addressing such requirements is the fractal antenna. This paper describes selected simulations results of the following two fractal antenna: Koch and Minkowski. The variation trends of the voltage standing-wave ratio, the reflection coefficient, and the S11 parameters of the antenna have been studied for several successive iterates of the fractal shapes.
{"title":"An analysis of Koch and Minkowski fractal antennas for cognitive systems","authors":"W. Kinsner, Siavash Malektaji","doi":"10.1109/ICCI-CC.2013.6622231","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622231","url":null,"abstract":"Cognitive systems call for wireless communications with antennas having stringent requirements. For example, software-defined radio, cognitive radio, and cognitive sensor networks operate over very wide bandwidth, with small dimensions, high gain, and omnidirectionally. A candidate capable of addressing such requirements is the fractal antenna. This paper describes selected simulations results of the following two fractal antenna: Koch and Minkowski. The variation trends of the voltage standing-wave ratio, the reflection coefficient, and the S11 parameters of the antenna have been studied for several successive iterates of the fractal shapes.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124285431","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622226
Du Zhang
We are faced with a torrent of data generated and captured in digital form as a result of the advancement of sciences, engineering and technologies, and various social, economical and human activities. This big data phenomenon ushers in a new era where human endeavors and scientific pursuits will be aided by not only human capital, and physical and financial assets, but also data assets. Research issues in big data and big data analysis are embedded in multi-dimensional scientific and technological spaces. In this paper, we first take a close look at the dimensions in big data and big data analysis, and then focus our attention on the issue of inconsistencies in big data and the impact of inconsistencies in big data analysis. We offer classifications of four types of inconsistencies in big data and point out the utility of inconsistency-induced learning as a tool for big data analysis.
{"title":"Inconsistencies in big data","authors":"Du Zhang","doi":"10.1109/ICCI-CC.2013.6622226","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622226","url":null,"abstract":"We are faced with a torrent of data generated and captured in digital form as a result of the advancement of sciences, engineering and technologies, and various social, economical and human activities. This big data phenomenon ushers in a new era where human endeavors and scientific pursuits will be aided by not only human capital, and physical and financial assets, but also data assets. Research issues in big data and big data analysis are embedded in multi-dimensional scientific and technological spaces. In this paper, we first take a close look at the dimensions in big data and big data analysis, and then focus our attention on the issue of inconsistencies in big data and the impact of inconsistencies in big data analysis. We offer classifications of four types of inconsistencies in big data and point out the utility of inconsistency-induced learning as a tool for big data analysis.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123761061","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622242
M. Nasri, W. Kinsner
This paper describes the application of extended and unscented Kalman filters for the identification of uncertainties in a process. The extended Kalman filter (EKF) is an optimal linear recursive algorithm that offers a solution to the filtering problem. The EKF is based on a first-order Taylor expansion to approximate the measurement and process models. This approach may cause the estimation process to diverge. Consequently, alternatives (e.g., the unscented Kalman filter, UKF) based on a fixed number of points to represent a Gaussian distribution have been introduced. The EKF and UKF have been applied for the identification of uncertainty in the attitude determination process for small satellites based on noisy measurements collected from Sun sensors and three-axis magnetometers. Simulation results indicate that the EKF and UKF perform equally well when small initial errors are present. However, when large errors are introduced, the UKF leads to a faster convergence and achieves a higher more accurate estimate of the state of the system.
{"title":"Extended and unscented Kalman filters for the identification of uncertainties in a process","authors":"M. Nasri, W. Kinsner","doi":"10.1109/ICCI-CC.2013.6622242","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622242","url":null,"abstract":"This paper describes the application of extended and unscented Kalman filters for the identification of uncertainties in a process. The extended Kalman filter (EKF) is an optimal linear recursive algorithm that offers a solution to the filtering problem. The EKF is based on a first-order Taylor expansion to approximate the measurement and process models. This approach may cause the estimation process to diverge. Consequently, alternatives (e.g., the unscented Kalman filter, UKF) based on a fixed number of points to represent a Gaussian distribution have been introduced. The EKF and UKF have been applied for the identification of uncertainty in the attitude determination process for small satellites based on noisy measurements collected from Sun sensors and three-axis magnetometers. Simulation results indicate that the EKF and UKF perform equally well when small initial errors are present. However, when large errors are introduced, the UKF leads to a faster convergence and achieves a higher more accurate estimate of the state of the system.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126915332","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622255
Camille Barot, D. Lourdeaux, D. Lenne
Virtual environments for training use technical systems simulation and virtual characters to put learners in training situations that emulate genuine work situations. In these environments, maintaining coherence is essential for the learning, whether in the perceived motivations of the characters or the reactions of the technical systems. However, with the complexification of simulated situations, it becomes difficult to maintain this coherence while exerting some control over the scenario, without having to define it explicitly a priori. We present in this paper the SELDON approach, which aims at dynamically adapting the scenario of a virtual environment for training to fit the learner's needs, and focuses on maintaining its coherence. We propose to generate this scenario by using a planning system with two different types of operators - prediction operators, and adjustment operators -, to influence the scenario unfolding in an indirect manner, while respecting the individual agent behaviours.
{"title":"Using planning to predict and influence autonomous agents behaviour in a virtual environment for training","authors":"Camille Barot, D. Lourdeaux, D. Lenne","doi":"10.1109/ICCI-CC.2013.6622255","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622255","url":null,"abstract":"Virtual environments for training use technical systems simulation and virtual characters to put learners in training situations that emulate genuine work situations. In these environments, maintaining coherence is essential for the learning, whether in the perceived motivations of the characters or the reactions of the technical systems. However, with the complexification of simulated situations, it becomes difficult to maintain this coherence while exerting some control over the scenario, without having to define it explicitly a priori. We present in this paper the SELDON approach, which aims at dynamically adapting the scenario of a virtual environment for training to fit the learner's needs, and focuses on maintaining its coherence. We propose to generate this scenario by using a planning system with two different types of operators - prediction operators, and adjustment operators -, to influence the scenario unfolding in an indirect manner, while respecting the individual agent behaviours.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"74 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127394643","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622220
Divesh Lala, T. Nishida
In order to produce agents which are effective social actors, behavior must be modeled in an appropriate way. Models exist for a wide range of agent components, but this paper focuses on communication through body expression. Additionally, rather than formulating communication models from scratch, this paper discusses modeling of agents based on existing communication theory in the real world. In this case, Herbert Clark's joint activity theory is used, where each collaborative act is regarded as a joint project between one or more parties. The generalized model is defined and its first implementation in the form of a virtual basketball game is also described. The use of a game provides an ideal testbed for the analysis of communication using Clark's theory.
{"title":"Modeling communicative virtual agents based on joint activity theory","authors":"Divesh Lala, T. Nishida","doi":"10.1109/ICCI-CC.2013.6622220","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622220","url":null,"abstract":"In order to produce agents which are effective social actors, behavior must be modeled in an appropriate way. Models exist for a wide range of agent components, but this paper focuses on communication through body expression. Additionally, rather than formulating communication models from scratch, this paper discusses modeling of agents based on existing communication theory in the real world. In this case, Herbert Clark's joint activity theory is used, where each collaborative act is regarded as a joint project between one or more parties. The generalized model is defined and its first implementation in the form of a virtual basketball game is also described. The use of a game provides an ideal testbed for the analysis of communication using Clark's theory.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134518453","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622276
Hiroyuki Nishiyama, F. Mizoguchi
In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.
{"title":"Design of a cognitive tool to detect malicious images using the smart phone","authors":"Hiroyuki Nishiyama, F. Mizoguchi","doi":"10.1109/ICCI-CC.2013.6622276","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622276","url":null,"abstract":"In this study, we design a cognitive tool to detect malicious images using a smart phone. This tool can learn shot images taken with the camera of a smart phone and automatically classify the new image as an malicious image in the smart phone. To develop the learning and classifier tool, we implement an image analysis function and a learning and classifier function using a support vector machine (SVM) with the smart phone. With this tool, the user can collect image data with the camera of a smart phone, create learning data, and classify the new image data according to the learning data in the smart phone. In this study, we apply this tool to a user interface of a cosmetics recommendation service system and demonstrate its effectiveness by in reducing the load of the diagnosis server in this service and improving the user service.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131228397","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622267
Yi Tang, Runhua Wang, Zhiming Dong
In this paper, the delay-dependent robust stability is investigated for uncertain neutral-type delayed neural networks with discrete interval time-varying delays. The parameter uncertainties are assumed to be norm bounded. Based on the Lyapunov-Krasovskii functional, the Leibniz-Newton formula and the linear matrix inequality (LMI) technique, some robust stability conditions are proposed by introducing some free-weighting matrices. A numerical example is presented to illustrate the efficiency of proposed result.
{"title":"Novel delay-dependent robust stability criteria for uncertain neutral-type delayed neural networks with discrete interval time-varying delays","authors":"Yi Tang, Runhua Wang, Zhiming Dong","doi":"10.1109/ICCI-CC.2013.6622267","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622267","url":null,"abstract":"In this paper, the delay-dependent robust stability is investigated for uncertain neutral-type delayed neural networks with discrete interval time-varying delays. The parameter uncertainties are assumed to be norm bounded. Based on the Lyapunov-Krasovskii functional, the Leibniz-Newton formula and the linear matrix inequality (LMI) technique, some robust stability conditions are proposed by introducing some free-weighting matrices. A numerical example is presented to illustrate the efficiency of proposed result.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124255742","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622260
Natsuki Sano, K. Yada
In grocery stores, discount flyers act as an important tool to provide discount information to customers and spur buying motivation among them. However, discount flyer have limited space. As customers purchase popular products even if they are not actively promoted, mentioning them on discount flyers is an ineffective strategy. Therefore, the proper allocation of discounted products is an important topic which is related to category management. In this paper, we propose a prediction model for the number of purchased products based on the data obtained through radio frequency identification (RFID), point of sales (POS), and discount flyers. We propose a method to determine the share of product categories on discount flyers by evaluating the interaction effect between sales area and bargain scale using the prediction model. The experimental results show that the sales area near the register has a significant interaction effect on bargain sales, suggesting that discounted products should be arranged in front of the register.
{"title":"Determining the share of product categories on discount flyers based on the interaction effect between bargain scale and sales area","authors":"Natsuki Sano, K. Yada","doi":"10.1109/ICCI-CC.2013.6622260","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622260","url":null,"abstract":"In grocery stores, discount flyers act as an important tool to provide discount information to customers and spur buying motivation among them. However, discount flyer have limited space. As customers purchase popular products even if they are not actively promoted, mentioning them on discount flyers is an ineffective strategy. Therefore, the proper allocation of discounted products is an important topic which is related to category management. In this paper, we propose a prediction model for the number of purchased products based on the data obtained through radio frequency identification (RFID), point of sales (POS), and discount flyers. We propose a method to determine the share of product categories on discount flyers by evaluating the interaction effect between sales area and bargain scale using the prediction model. The experimental results show that the sales area near the register has a significant interaction effect on bargain sales, suggesting that discounted products should be arranged in front of the register.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122490550","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622233
Takuma Oide, Atsushi Takeda, Akiko Takahashi, T. Suganuma
There are many obstacles to overcome when we use network services during a large-scale disaster, such as poor communication with unstable networks. Under such network environment, computers need to save network resources and to balance loads among nodes without user's operation. We propose the P2P Safety Confirmation System in which each node sufficiently achieves autonomous dynamic load balancing. This system is based on our proposed structured P2P network called Well-distribution Algorithm for an Overly Network (Waon), which does not require any network restriction and not incur additional maintenance costs during its load balancing. We implemented the system and evaluated node's behavior while nodes autonomously balance loads. Moreover we applied this framework to build a communication support system in natural disaster.
{"title":"SS5 design of a P2P information sharing system and its application to communication support in natural disaster","authors":"Takuma Oide, Atsushi Takeda, Akiko Takahashi, T. Suganuma","doi":"10.1109/ICCI-CC.2013.6622233","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622233","url":null,"abstract":"There are many obstacles to overcome when we use network services during a large-scale disaster, such as poor communication with unstable networks. Under such network environment, computers need to save network resources and to balance loads among nodes without user's operation. We propose the P2P Safety Confirmation System in which each node sufficiently achieves autonomous dynamic load balancing. This system is based on our proposed structured P2P network called Well-distribution Algorithm for an Overly Network (Waon), which does not require any network restriction and not incur additional maintenance costs during its load balancing. We implemented the system and evaluated node's behavior while nodes autonomously balance loads. Moreover we applied this framework to build a communication support system in natural disaster.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125835021","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 : 2013-07-16DOI: 10.1109/ICCI-CC.2013.6622244
Dilruba Showkat, M. Kabir
Multi-objective optimization plays a significant role in optimizing many real life problems, where we desire to optimize more than one objective. Numerous multi-objective optimization algorithm exists in research. NSGA-II and SPEA2 are widely used multi-objective optimization algorithms. SPEA2+ algorithm performs better than the other multi-objective optimization algorithms in terms of searching and maintaining diversity in the optimal solution. In this research, to reconstruct the gene regulatory network we have proposed a new Hybrid SPEA2+ algorithm based inference method. We have proposed a new objective function to obtain sparse gene network structure more precisely. To reverse engineer the gene regulatory network we have used linear time variant model. The proposed approach is at first tested against synthetic noise free time series datasets. It has successfully inferred all the correct regulations from noise free time series datasets. Then it was applied on synthetic noisy time series datasets. Even with the presence of noise, the proposed method have correctly captured all the correct gene regulations successfully. The proposed reconstruction method has been further validated by analyzing the real gene expression datasets of SOS DNA repair system in Escherichia coli. Our proposed method have shown its potency in finding more correct regulations and this has been confirmed by comparing the obtained gene regulations with the results of other existing researches.
{"title":"Inference of genetic networks using multi-objective hybrid SPEA2+ from Microarray data","authors":"Dilruba Showkat, M. Kabir","doi":"10.1109/ICCI-CC.2013.6622244","DOIUrl":"https://doi.org/10.1109/ICCI-CC.2013.6622244","url":null,"abstract":"Multi-objective optimization plays a significant role in optimizing many real life problems, where we desire to optimize more than one objective. Numerous multi-objective optimization algorithm exists in research. NSGA-II and SPEA2 are widely used multi-objective optimization algorithms. SPEA2+ algorithm performs better than the other multi-objective optimization algorithms in terms of searching and maintaining diversity in the optimal solution. In this research, to reconstruct the gene regulatory network we have proposed a new Hybrid SPEA2+ algorithm based inference method. We have proposed a new objective function to obtain sparse gene network structure more precisely. To reverse engineer the gene regulatory network we have used linear time variant model. The proposed approach is at first tested against synthetic noise free time series datasets. It has successfully inferred all the correct regulations from noise free time series datasets. Then it was applied on synthetic noisy time series datasets. Even with the presence of noise, the proposed method have correctly captured all the correct gene regulations successfully. The proposed reconstruction method has been further validated by analyzing the real gene expression datasets of SOS DNA repair system in Escherichia coli. Our proposed method have shown its potency in finding more correct regulations and this has been confirmed by comparing the obtained gene regulations with the results of other existing researches.","PeriodicalId":130244,"journal":{"name":"2013 IEEE 12th International Conference on Cognitive Informatics and Cognitive Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126375650","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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