At present, the optimization of teaching strategies is mainly based on teachers' self-knowledge and policy promotion, which can not well meet the needs of teaching, and can not be adjusted objectively according to the actual situation of teaching. This paper designs a teaching strategy evaluation mechanism, and on this basis, using genetic algorithm to optimize the teaching strategy, to achieve the teaching strategy with the change of teaching content and teaching object and constantly evolve and optimize the purpose. At the same time, the teaching strategy optimization system based on genetic algorithm is designed and implemented, and it is applied in practice.
{"title":"Research on classroom management system based on genetic algorithm","authors":"Wu Yang, Bihui Cheng","doi":"10.1145/3544109.3544139","DOIUrl":"https://doi.org/10.1145/3544109.3544139","url":null,"abstract":"At present, the optimization of teaching strategies is mainly based on teachers' self-knowledge and policy promotion, which can not well meet the needs of teaching, and can not be adjusted objectively according to the actual situation of teaching. This paper designs a teaching strategy evaluation mechanism, and on this basis, using genetic algorithm to optimize the teaching strategy, to achieve the teaching strategy with the change of teaching content and teaching object and constantly evolve and optimize the purpose. At the same time, the teaching strategy optimization system based on genetic algorithm is designed and implemented, and it is applied in practice.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115457074","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}
As an important part of battery electric vehicles, lithium-ion batteries will generate much heat in the working process. If heat dissipation measures are not taken in time, the accumulated heat will have a great impact on the battery temperature rise, seriously causing some battery safety incidents. To solve the cooling problem of lithium-ion batteries during charging and discharging cycle, in this paper, a square cooling module of lithium-ion power battery with phase change material (PCM) was designed, whose heat production and heat dissipation were established, which were coupled with the air-cooling heat dissipation model. Finally, a two-dimensional active and passive heat dissipation model of lithium battery module was formed, based on the thermal model, the simulation module in ANSYS Fluent was made use of simulating the thermal dissipation characteristics. The simulation results show that when the coefficient of convective heat transfer is 12, 60, 120W/(m2·K), the highest temperature of the battery module is 142.8℃, 74.6℃, 41.9℃, respectively, which indicates that the coefficient has an important influence on its maximum temperature. Secondly, during the whole charging-discharging cycle, its maximum temperature is 82.2℃, 79.1℃, 77.7℃and 75.1℃, respectively, when the standing time is 0, 5, 10 and 20min. Obviously, increasing the standing time can reduce its maximum temperature. In addition, the continuous heat accumulation will lead to the failure of PCM, at this time, the PCM needs to be coupled with other cooling technologies such as forced air cooling.
{"title":"Research on Thermal Dissipation Characteristics of Power Lithium-Ion Battery Module with Phase Change Cooling","authors":"Biao Jin, Qiang Fei, Wuyuan Zou","doi":"10.1145/3544109.3544188","DOIUrl":"https://doi.org/10.1145/3544109.3544188","url":null,"abstract":"As an important part of battery electric vehicles, lithium-ion batteries will generate much heat in the working process. If heat dissipation measures are not taken in time, the accumulated heat will have a great impact on the battery temperature rise, seriously causing some battery safety incidents. To solve the cooling problem of lithium-ion batteries during charging and discharging cycle, in this paper, a square cooling module of lithium-ion power battery with phase change material (PCM) was designed, whose heat production and heat dissipation were established, which were coupled with the air-cooling heat dissipation model. Finally, a two-dimensional active and passive heat dissipation model of lithium battery module was formed, based on the thermal model, the simulation module in ANSYS Fluent was made use of simulating the thermal dissipation characteristics. The simulation results show that when the coefficient of convective heat transfer is 12, 60, 120W/(m2·K), the highest temperature of the battery module is 142.8℃, 74.6℃, 41.9℃, respectively, which indicates that the coefficient has an important influence on its maximum temperature. Secondly, during the whole charging-discharging cycle, its maximum temperature is 82.2℃, 79.1℃, 77.7℃and 75.1℃, respectively, when the standing time is 0, 5, 10 and 20min. Obviously, increasing the standing time can reduce its maximum temperature. In addition, the continuous heat accumulation will lead to the failure of PCM, at this time, the PCM needs to be coupled with other cooling technologies such as forced air cooling.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121002443","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}
With the rapid development of new technology in China, the combination of new technology and project management can improve the overall quality level of project cost as a whole. China’s engineering cost industry has been severely challenged, and the previous management methods have been difficult to meet the requirements of the times. The superiority of data mining technology based on statistical analysis is becoming more and more obvious. Data mining is a new and promising field gradually formed as the application research of database and data warehouse. The project cost management department needs to record more and more project cost data, which requires the introduction of data mining based on statistical analysis. Data mining realizes the functions of establishing database, data purification, data query and sharing, analysis and early warning in project cost management. In practical application, data screening can also be carried out by selecting factors such as project unilateral cost index, cost reduction rate, completion settlement price, project structure form and so on. This paper focuses on its application advantages in project cost management.
{"title":"Project Cost Management Information Solution Based on Data Mining Technology","authors":"Zeyang Li, Ling Liu","doi":"10.1145/3544109.3544363","DOIUrl":"https://doi.org/10.1145/3544109.3544363","url":null,"abstract":"With the rapid development of new technology in China, the combination of new technology and project management can improve the overall quality level of project cost as a whole. China’s engineering cost industry has been severely challenged, and the previous management methods have been difficult to meet the requirements of the times. The superiority of data mining technology based on statistical analysis is becoming more and more obvious. Data mining is a new and promising field gradually formed as the application research of database and data warehouse. The project cost management department needs to record more and more project cost data, which requires the introduction of data mining based on statistical analysis. Data mining realizes the functions of establishing database, data purification, data query and sharing, analysis and early warning in project cost management. In practical application, data screening can also be carried out by selecting factors such as project unilateral cost index, cost reduction rate, completion settlement price, project structure form and so on. This paper focuses on its application advantages in project cost management.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115253693","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}
In order to overcome the difficulties in the formulation and decision-making of power distribution schemes, this paper proposes a novel decision-making model for optimal power distribution schemes based on multiple linear regression and Lingo multi-objective programming models. From the perspective of multiple linear regression and Lingo’s multi-objective programming models, the decision-making model follows the "safety first" principle and the principle of minimum cost in the organization, dispatch, and distribution of power grid companies. And according to the load forecast and transaction rules, the optimal power distribution scheme can be designed for the power personnel. The research results show that the difference in load demand leads to different transmission congestion principles and cost settlement methods. Therefore, this paper divides the forecast load demand into three intervals (0,982.9136], (982.9136,1094.500], (1094.500,+ ∞ ], the simulation test was carried out. When the forecasted load demand for the next period is 984.2MV and 1052.8MV, LINGO and MATLAB software are used to solve the deployment mentioned above plan model according to the transmission congestion management principle to obtain the adjusted units. And find the blocking cost is 18232.2 yuan and 22506 yuan.
{"title":"Decision-making Model of Optimal Power Distribution Scheme Based on Multiple Linear Regression and Lingo Multi-objective Programming Model","authors":"Xinyu Zhang, Qiushi Wang, Hongru Zhou, Zhenyao Shen","doi":"10.1145/3544109.3544158","DOIUrl":"https://doi.org/10.1145/3544109.3544158","url":null,"abstract":"In order to overcome the difficulties in the formulation and decision-making of power distribution schemes, this paper proposes a novel decision-making model for optimal power distribution schemes based on multiple linear regression and Lingo multi-objective programming models. From the perspective of multiple linear regression and Lingo’s multi-objective programming models, the decision-making model follows the \"safety first\" principle and the principle of minimum cost in the organization, dispatch, and distribution of power grid companies. And according to the load forecast and transaction rules, the optimal power distribution scheme can be designed for the power personnel. The research results show that the difference in load demand leads to different transmission congestion principles and cost settlement methods. Therefore, this paper divides the forecast load demand into three intervals (0,982.9136], (982.9136,1094.500], (1094.500,+ ∞ ], the simulation test was carried out. When the forecasted load demand for the next period is 984.2MV and 1052.8MV, LINGO and MATLAB software are used to solve the deployment mentioned above plan model according to the transmission congestion management principle to obtain the adjusted units. And find the blocking cost is 18232.2 yuan and 22506 yuan.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"442 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116151159","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}
In the traditional sense, early warning models for real estate financial risks are based on economic-financial data. However, this method is not intelligent enough, takes a long time, and is too inefficient. Therefore, it is necessary to use new Internet technology to develop an efficient financial risk early warning system in the Internet age. Therefore, based on the above background, this paper reconstructs the above-mentioned real estate financial risk management system by integrating the relevant technical characteristics of neural networks. Then can accurately calculate the corresponding indicators to judge better the company’s economic situation and real estate financial risk. In the above design process, the characteristics of cost-sensitive learning are also considered in this paper, the structure of the neural network is optimized accordingly through the above method, and the indicators are more precisely defined.
{"title":"Research on Early Warning System of Real Estate Financial Risk Based on Convolutional Neural Network","authors":"Chen Jiang, Yiheng Luo","doi":"10.1145/3544109.3544159","DOIUrl":"https://doi.org/10.1145/3544109.3544159","url":null,"abstract":"In the traditional sense, early warning models for real estate financial risks are based on economic-financial data. However, this method is not intelligent enough, takes a long time, and is too inefficient. Therefore, it is necessary to use new Internet technology to develop an efficient financial risk early warning system in the Internet age. Therefore, based on the above background, this paper reconstructs the above-mentioned real estate financial risk management system by integrating the relevant technical characteristics of neural networks. Then can accurately calculate the corresponding indicators to judge better the company’s economic situation and real estate financial risk. In the above design process, the characteristics of cost-sensitive learning are also considered in this paper, the structure of the neural network is optimized accordingly through the above method, and the indicators are more precisely defined.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114064154","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}
E-business involves a huge amount of data, and the emergence of data mining technology can help enterprises quickly and accurately find and obtain valuable data information from the huge amount of data. Data mining is the process of discovering new association patterns by storing a large amount of data. In the environment of e-business websites, the analysis of click stream is becoming more and more valuable, which has gone far beyond the scope of click stream. Deep analysis of these data has become an effective tool for e-business websites to understand the business situation and user behavior. Based on the analysis of click stream data of e-business users, this paper analyzes the function and process of data mining in e-business, and on this basis, puts forward the application method of data mining technology based on click stream data in e-business. Enterprises should establish the concept of keeping pace with the times and constantly strengthen the application of data mining technology to ensure that the e-business industry can develop in a positive, stable, healthy and sustainable direction.
{"title":"Research on Online E-business User Data Mining Based on Clickstream Data","authors":"Hua Zhang","doi":"10.1145/3544109.3544364","DOIUrl":"https://doi.org/10.1145/3544109.3544364","url":null,"abstract":"E-business involves a huge amount of data, and the emergence of data mining technology can help enterprises quickly and accurately find and obtain valuable data information from the huge amount of data. Data mining is the process of discovering new association patterns by storing a large amount of data. In the environment of e-business websites, the analysis of click stream is becoming more and more valuable, which has gone far beyond the scope of click stream. Deep analysis of these data has become an effective tool for e-business websites to understand the business situation and user behavior. Based on the analysis of click stream data of e-business users, this paper analyzes the function and process of data mining in e-business, and on this basis, puts forward the application method of data mining technology based on click stream data in e-business. Enterprises should establish the concept of keeping pace with the times and constantly strengthen the application of data mining technology to ensure that the e-business industry can develop in a positive, stable, healthy and sustainable direction.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122059229","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}
Prediction is the premise of decision-making, and scientific decision-making can only be made on the basis of correct prediction. Macroeconomic forecasting and decision-making is an important research direction in the field of management science, and an important problem that must be solved in regional and national economic development planning and decision-making. By using the self-learning, self-adapting and nonlinear characteristics of BPNN (BP neural network), economic data analysis and intelligent prediction can be realized. By establishing the evaluation index system of economic system, the data of economic variables are normalized, and then sent to BPNN for training to get the corresponding parameters before prediction. In this paper, PCA (principal component analysis) algorithm and BPNN algorithm are combined, and the PCA algorithm's advantage of dimension reduction and neural network's advantage of nonlinear expression are fully utilized, and the PCA-BPNN prediction model is established, and the algorithm is applied to the analysis of social fixed assets investment data. Compared with the linear prediction method, it is found that PCA-BPNN prediction algorithm has better effect.
{"title":"Research on Economic Data Analysis and Intelligent Prediction Based on BP Neural Network","authors":"Zheng Huang","doi":"10.1145/3544109.3544372","DOIUrl":"https://doi.org/10.1145/3544109.3544372","url":null,"abstract":"Prediction is the premise of decision-making, and scientific decision-making can only be made on the basis of correct prediction. Macroeconomic forecasting and decision-making is an important research direction in the field of management science, and an important problem that must be solved in regional and national economic development planning and decision-making. By using the self-learning, self-adapting and nonlinear characteristics of BPNN (BP neural network), economic data analysis and intelligent prediction can be realized. By establishing the evaluation index system of economic system, the data of economic variables are normalized, and then sent to BPNN for training to get the corresponding parameters before prediction. In this paper, PCA (principal component analysis) algorithm and BPNN algorithm are combined, and the PCA algorithm's advantage of dimension reduction and neural network's advantage of nonlinear expression are fully utilized, and the PCA-BPNN prediction model is established, and the algorithm is applied to the analysis of social fixed assets investment data. Compared with the linear prediction method, it is found that PCA-BPNN prediction algorithm has better effect.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122182510","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}
In order to improve the security of cloud computing data center in the virtualized environment, a security system design of cloud computing data center is proposed based on the virtualization environment. Firstly, the security architecture of cloud computing data center is constructed, and the security of data center is evaluated. By optimizing the system equipment structure and operation steps, the security performance of cloud computing data center can be improved. The experimental results show that the design method of cloud computing data center security architecture based on Virtualization environment has high precision, good practical effect and fully meets the research requirements.
{"title":"Design of cloud computing data center security system based on Virtualization environment","authors":"Shaochen Zhang, Youyang Qu, Peng-Yu Wang","doi":"10.1145/3544109.3544134","DOIUrl":"https://doi.org/10.1145/3544109.3544134","url":null,"abstract":"In order to improve the security of cloud computing data center in the virtualized environment, a security system design of cloud computing data center is proposed based on the virtualization environment. Firstly, the security architecture of cloud computing data center is constructed, and the security of data center is evaluated. By optimizing the system equipment structure and operation steps, the security performance of cloud computing data center can be improved. The experimental results show that the design method of cloud computing data center security architecture based on Virtualization environment has high precision, good practical effect and fully meets the research requirements.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128499625","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}
With the rise of buildings, how to reduce the vibration of buildings has become a research topic. Structural vibration control in civil engineering is a new subject which studies the theories, methods and measures of structural control. After analyzing the current situation of structural control field based on cluster analysis method, this paper uses fuzzy control strategy to control the force output of semi-active control device MR damper. As a branch of intelligent control, fuzzy control can well bring the subjective experience and intuition of skilled operators into the control system. It analyzes and synthesizes the system from the perspective of system function and overall optimization. After using the basic fuzzy controller to control the structural model, the original fuzzy controller is modified, that is, the three key factors are automatically adjusted to form a self-adjusting factor fuzzy controller.
{"title":"Fuzzy control algorithm of civil engineering structure vibration based on cluster analysis","authors":"Shuai Ma, Shuai Xiao, Xiaoyu Wang","doi":"10.1145/3544109.3544347","DOIUrl":"https://doi.org/10.1145/3544109.3544347","url":null,"abstract":"With the rise of buildings, how to reduce the vibration of buildings has become a research topic. Structural vibration control in civil engineering is a new subject which studies the theories, methods and measures of structural control. After analyzing the current situation of structural control field based on cluster analysis method, this paper uses fuzzy control strategy to control the force output of semi-active control device MR damper. As a branch of intelligent control, fuzzy control can well bring the subjective experience and intuition of skilled operators into the control system. It analyzes and synthesizes the system from the perspective of system function and overall optimization. After using the basic fuzzy controller to control the structural model, the original fuzzy controller is modified, that is, the three key factors are automatically adjusted to form a self-adjusting factor fuzzy controller.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128715170","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}
Due to the global warming trend, focus on flight operation hazards should be maintained linked to season changes, especially for summer operation. In this paper, a statistics based detection strategy is present to perform the flight hazard analysis of the approach and landing phases. The risk linked with approach speed high on short final is identified and assessed by quantitative strategy. Then some risk mitigations are also suggested to perform the hazard controls. Practical flight data are collected to show the validity of hazard analysis process. The experimental results show that the proposed scheme is effective for the seasonal flight hazard analysis.
{"title":"A Statistics Based Detection Strategy for Seasonal Flight Hazard Analysis","authors":"Rui-peng Yang, Peng Zhang","doi":"10.1145/3544109.3544128","DOIUrl":"https://doi.org/10.1145/3544109.3544128","url":null,"abstract":"Due to the global warming trend, focus on flight operation hazards should be maintained linked to season changes, especially for summer operation. In this paper, a statistics based detection strategy is present to perform the flight hazard analysis of the approach and landing phases. The risk linked with approach speed high on short final is identified and assessed by quantitative strategy. Then some risk mitigations are also suggested to perform the hazard controls. Practical flight data are collected to show the validity of hazard analysis process. The experimental results show that the proposed scheme is effective for the seasonal flight hazard analysis.","PeriodicalId":187064,"journal":{"name":"Proceedings of the 3rd Asia-Pacific Conference on Image Processing, Electronics and Computers","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124770549","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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