Pub Date : 2004-09-20DOI: 10.1109/IAT.2004.1342957
Xiaolong Jin, Jiming Liu, Zhen Yang
In a peer-to-peer grid, tasks are distributed to grid nodes in a decentralized fashion. We present an agent-based task handling mechanism in a peer-to-peer grid and then provide a macroscopic model to characterize the process of task handling. Our model consists of functional differential equations. Through case studies: (1) we show that our model is effective in characterizing the process of task handling; (2) we examine the effects of time delay, service time, etc. on the global performance of a peer-to-peer grid. Based on our model, we further simulate a complete process of task handling in a grid and show the main characteristics of a real grid.
{"title":"Modeling agent-based task handling in a peer-to-peer grid","authors":"Xiaolong Jin, Jiming Liu, Zhen Yang","doi":"10.1109/IAT.2004.1342957","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342957","url":null,"abstract":"In a peer-to-peer grid, tasks are distributed to grid nodes in a decentralized fashion. We present an agent-based task handling mechanism in a peer-to-peer grid and then provide a macroscopic model to characterize the process of task handling. Our model consists of functional differential equations. Through case studies: (1) we show that our model is effective in characterizing the process of task handling; (2) we examine the effects of time delay, service time, etc. on the global performance of a peer-to-peer grid. Based on our model, we further simulate a complete process of task handling in a grid and show the main characteristics of a real grid.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133210549","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}
Summary form only given. Data mining is a fast-growing area. The first Knowledge Discovery in Databases Workshop was held in August 1989, in conjunction with the 1989 International Joint Conference on Artificial Intelligence, and this workshop series became the International Conference on Knowledge Discovery and Data Mining (KDD) in 1995. In 2003, there were a total of 15 data mining conferences, most of which are listed at http://www.kdnuggets.com/meetings/meetings-2OO3-past.html. These 15 conferences do not include various artificial intelligence (AI), statistics and database conferences (and their workshops) that also solicited and accepted data mining related papers, such as DC AI, ICML, ICTAI, COMPSTAT, AI & Statistics, SIGMOD, VLDB, ICDE, and CIKM. Among various data mining conferences, KDD and ICDM (the IEEE International Conference on Data Mining) are arguably (or unarguably) the two premier ones in the field. ICDM was established in 2000, sponsored by the IEEE Computer Society, and had its first annual meeting in 2001. This work reviews the topics of interest from ICDM from an AI perspective, and analyze common topics in data mining and AI, including key AI ideas that have been used in both data mining and machine learning. We also discuss two current research projects on (1) user-centered agents for biological information exploration on the Web, and (2) dynamic classifier selection in dealing with streaming data. Both projects apply data mining techniques for intelligent analysis of large volumes of data.
{"title":"Data mining: artificial intelligence in data analysis","authors":"Xindong Wu","doi":"10.1109/WI.2004.49","DOIUrl":"https://doi.org/10.1109/WI.2004.49","url":null,"abstract":"Summary form only given. Data mining is a fast-growing area. The first Knowledge Discovery in Databases Workshop was held in August 1989, in conjunction with the 1989 International Joint Conference on Artificial Intelligence, and this workshop series became the International Conference on Knowledge Discovery and Data Mining (KDD) in 1995. In 2003, there were a total of 15 data mining conferences, most of which are listed at http://www.kdnuggets.com/meetings/meetings-2OO3-past.html. These 15 conferences do not include various artificial intelligence (AI), statistics and database conferences (and their workshops) that also solicited and accepted data mining related papers, such as DC AI, ICML, ICTAI, COMPSTAT, AI & Statistics, SIGMOD, VLDB, ICDE, and CIKM. Among various data mining conferences, KDD and ICDM (the IEEE International Conference on Data Mining) are arguably (or unarguably) the two premier ones in the field. ICDM was established in 2000, sponsored by the IEEE Computer Society, and had its first annual meeting in 2001. This work reviews the topics of interest from ICDM from an AI perspective, and analyze common topics in data mining and AI, including key AI ideas that have been used in both data mining and machine learning. We also discuss two current research projects on (1) user-centered agents for biological information exploration on the Web, and (2) dynamic classifier selection in dealing with streaming data. Both projects apply data mining techniques for intelligent analysis of large volumes of data.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133536852","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}
Summary form only given. Grids are a distributed computing technology whose objective is to provide the basic mechanisms for forming and operating dynamic distributed collaborations, or virtual organizations as they are sometimes called. While grid infrastructure has focused on such things as the means for discovering and monitoring dynamic services, managing faults and failures, creating and managing service level agreements, creating and enforcing dynamic policy, to name a few - to date, only limited progress has been made on creating the higher level reactive behaviors that would enable truly dynamic formation of virtual organizations. What is needed are the basic algorithms that enable independently operating entities to interact with one another with partial knowledge and have emerge a robust desirable behavior. This is exactly the range of problems that are being addressed by intelligent agent technologies. Hence, it seems likely that agent technology plays an important role in the development of the grid as a pervasive infrastructure and the grid offers an exciting range of applications for agents. In This work the author explores the relationship of intelligent agents to the grid and in particular focus on how agent technology can be applied to some specific challenges faced by grid infrastructure and applications.
{"title":"Applications of intelligent agent technology to the grid","authors":"C. Kesselman","doi":"10.1109/WI.2004.10008","DOIUrl":"https://doi.org/10.1109/WI.2004.10008","url":null,"abstract":"Summary form only given. Grids are a distributed computing technology whose objective is to provide the basic mechanisms for forming and operating dynamic distributed collaborations, or virtual organizations as they are sometimes called. While grid infrastructure has focused on such things as the means for discovering and monitoring dynamic services, managing faults and failures, creating and managing service level agreements, creating and enforcing dynamic policy, to name a few - to date, only limited progress has been made on creating the higher level reactive behaviors that would enable truly dynamic formation of virtual organizations. What is needed are the basic algorithms that enable independently operating entities to interact with one another with partial knowledge and have emerge a robust desirable behavior. This is exactly the range of problems that are being addressed by intelligent agent technologies. Hence, it seems likely that agent technology plays an important role in the development of the grid as a pervasive infrastructure and the grid offers an exciting range of applications for agents. In This work the author explores the relationship of intelligent agents to the grid and in particular focus on how agent technology can be applied to some specific challenges faced by grid infrastructure and applications.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134237299","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 : 2004-09-20DOI: 10.1109/IAT.2004.1342980
Yun-Fei Chen, C. A. Fattah, Yu-shu Liu, Gangway Yan
We present a new heuristic density-based ant colony clustering algorithm (HDACC). Firstly, the device of "memory bank" is proposed, which can bring forth heuristic knowledge guiding an ant to move in the bi-dimensional grid space. Hence the randomness of the ant's motion decreases and algorithm convergence speeds up. In addition, the memory bank makes it possible for every object to be inspected before the algorithm is terminated, which avoids the production of an "unassigned data object". So the classification error rate drops subsequently. Secondly, we proposed a density-based method which permits each ant to "look ahead", which reduces the times of region-inquiry. Consequently, clustering time is saved. We carried out experiments on real data sets and synthetic data sets. The results demonstrated that HDBCSI is a viable and effective clustering algorithm.
{"title":"HDACC: a heuristic density-based ant colony clustering algorithm","authors":"Yun-Fei Chen, C. A. Fattah, Yu-shu Liu, Gangway Yan","doi":"10.1109/IAT.2004.1342980","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342980","url":null,"abstract":"We present a new heuristic density-based ant colony clustering algorithm (HDACC). Firstly, the device of \"memory bank\" is proposed, which can bring forth heuristic knowledge guiding an ant to move in the bi-dimensional grid space. Hence the randomness of the ant's motion decreases and algorithm convergence speeds up. In addition, the memory bank makes it possible for every object to be inspected before the algorithm is terminated, which avoids the production of an \"unassigned data object\". So the classification error rate drops subsequently. Secondly, we proposed a density-based method which permits each ant to \"look ahead\", which reduces the times of region-inquiry. Consequently, clustering time is saved. We carried out experiments on real data sets and synthetic data sets. The results demonstrated that HDBCSI is a viable and effective clustering algorithm.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134304856","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 : 2004-09-20DOI: 10.1109/IAT.2004.1342921
Yinglong Ma, Yulin Feng, Beihong Jin, Jun Wei
Description Logic is now an active research area, which is applied universally to knowledge representation, Semantic Web and Ontology language. Compared with Description Logic, Distributed Description Logic can be used to better establish distributed ontologies from distributed information sources. But little attention has been paid to the problem of endowing Distributed Description Logic with default reasoning capabilities to deal with incomplete or conflict information. In this paper we present a default extension to Distributed Description Logics to handle the heterogeneity and incompleteness of different information sources. We extend Distributed Description Logics by adding default information into a distributed knowledge base, and discuss the default satisfiability based on Distributed Description Logics with default rules. To perform default reasoning, a default Tableau algorithm is developed to check satisfiability of complex concepts and subsumption assertions.
{"title":"A default extension to distributed description logics","authors":"Yinglong Ma, Yulin Feng, Beihong Jin, Jun Wei","doi":"10.1109/IAT.2004.1342921","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342921","url":null,"abstract":"Description Logic is now an active research area, which is applied universally to knowledge representation, Semantic Web and Ontology language. Compared with Description Logic, Distributed Description Logic can be used to better establish distributed ontologies from distributed information sources. But little attention has been paid to the problem of endowing Distributed Description Logic with default reasoning capabilities to deal with incomplete or conflict information. In this paper we present a default extension to Distributed Description Logics to handle the heterogeneity and incompleteness of different information sources. We extend Distributed Description Logics by adding default information into a distributed knowledge base, and discuss the default satisfiability based on Distributed Description Logics with default rules. To perform default reasoning, a default Tableau algorithm is developed to check satisfiability of complex concepts and subsumption assertions.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114982006","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 : 2004-09-20DOI: 10.1109/IAT.2004.1342982
Ying Guo, G. Poulton, G. James, P. Valencia, V. Gerasimov, Jiaming Li
We present a genetic algorithm-based approach to designing specific self-assembling structures that act as building blocks for assembling more complex objects. Our simulated environment models 2D square blocks as autonomous agents. A specific class of multi-agent self-assembled products is termed "enzymes" which are capable of producing other multi-agent self-assembled products whilst themselves remaining unchanged. The global goal of our self-assembly process is to produce large stable structures by evolving the enzyme and block parameters. Our experiments show that the "enzymes" can interact with the other blocks to produce a wide variety of stable self-assembling structures.
{"title":"Designing stable structures in a multi-agent self-assembly system","authors":"Ying Guo, G. Poulton, G. James, P. Valencia, V. Gerasimov, Jiaming Li","doi":"10.1109/IAT.2004.1342982","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342982","url":null,"abstract":"We present a genetic algorithm-based approach to designing specific self-assembling structures that act as building blocks for assembling more complex objects. Our simulated environment models 2D square blocks as autonomous agents. A specific class of multi-agent self-assembled products is termed \"enzymes\" which are capable of producing other multi-agent self-assembled products whilst themselves remaining unchanged. The global goal of our self-assembly process is to produce large stable structures by evolving the enzyme and block parameters. Our experiments show that the \"enzymes\" can interact with the other blocks to produce a wide variety of stable self-assembling structures.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123547818","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}
Because of the complexity of the outdoor terrain and the variety of the robot missions, the outdoor autonomous intelligent robot (OAIR) has to carry out missions in unstructured and impossibly predicted environment, which brings forward the higher challenge for the simulation environment. So the interactive simulation idea is introduced in This work. By means of classification, the outdoor simulation environments are divided into several sub-environments. The environmental entities modeled by a Scene Modeling Language (SML) can be edited interactively in accordance with requisition. And on the basis of the path-planning, the mission-planning method is introduced to simulate the complicated environment. The method not only simulates path-planning algorithms, but also verifies the validity and robustness of intelligent agents through editing or modifying the robot's geometric, and kinetic parameters to accomplish the interactive simulation between the running environment and the mission-planning. At last, a visual monitoring tool is designed to evaluate the performance and the coordination of the intelligent agents.
{"title":"The interactive simulation environments of OAIR","authors":"Qiqian Zhang, Miaoliang Zhu, Benye Gui, Shaojun Xu","doi":"10.1109/IAT.2004.1342922","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342922","url":null,"abstract":"Because of the complexity of the outdoor terrain and the variety of the robot missions, the outdoor autonomous intelligent robot (OAIR) has to carry out missions in unstructured and impossibly predicted environment, which brings forward the higher challenge for the simulation environment. So the interactive simulation idea is introduced in This work. By means of classification, the outdoor simulation environments are divided into several sub-environments. The environmental entities modeled by a Scene Modeling Language (SML) can be edited interactively in accordance with requisition. And on the basis of the path-planning, the mission-planning method is introduced to simulate the complicated environment. The method not only simulates path-planning algorithms, but also verifies the validity and robustness of intelligent agents through editing or modifying the robot's geometric, and kinetic parameters to accomplish the interactive simulation between the running environment and the mission-planning. At last, a visual monitoring tool is designed to evaluate the performance and the coordination of the intelligent agents.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121688259","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 : 2004-09-20DOI: 10.1109/IAT.2004.1342950
S. Albayrak, D. Milosevic
In order to obtain acceptable quality of filtering services in real time conditions trade-off between result relevance and response time has to be addressed. Ignoring resource availability is a major drawback for many existed systems which try to boost quality by making different synergies between filtering strategies. The essence of the proposed solution for combining filtering strategies is in a comprehensive coordination which both takes care about current resource usability and tries to improve itself during a runtime. The applicability of the presented coordination between filtering strategies is illustrated in a system serving as intelligent personal information assistant (PIA). Experimental results show that long lasting jobs with duration over 1000 seconds are eliminated and that at the same time jobs, being shorter than 10 seconds, can be effectively used for adaptation.
{"title":"Self improving coordination in multi agent filtering framework","authors":"S. Albayrak, D. Milosevic","doi":"10.1109/IAT.2004.1342950","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342950","url":null,"abstract":"In order to obtain acceptable quality of filtering services in real time conditions trade-off between result relevance and response time has to be addressed. Ignoring resource availability is a major drawback for many existed systems which try to boost quality by making different synergies between filtering strategies. The essence of the proposed solution for combining filtering strategies is in a comprehensive coordination which both takes care about current resource usability and tries to improve itself during a runtime. The applicability of the presented coordination between filtering strategies is illustrated in a system serving as intelligent personal information assistant (PIA). Experimental results show that long lasting jobs with duration over 1000 seconds are eliminated and that at the same time jobs, being shorter than 10 seconds, can be effectively used for adaptation.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123927833","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 : 2004-09-20DOI: 10.1109/IAT.2004.1343000
Xin Li, Leen-Kiat Soh
We propose an innovative two-step learning approach to planning-instantiation for multi-agent coalition formation in dynamic, uncertain, real-time, and noisy environments. The first step learns about the planning of a coalition to improve its quality, adapting to the real-time and environmental requirements. The second step learns about the instantiation of the plan to improve the formation process, taking into account uncertain and dynamic behaviors of the peer agents. Decomposing the approach into two steps allows for modularity and flexibility in learning: learning how to plan a coalition is strategic while learning how to instantiate a plan is tactical. Our approach employs a case-based reinforcement learning (CBRL) framework.
{"title":"Learning how to plan and instantiate a plan in multi-agent coalition","authors":"Xin Li, Leen-Kiat Soh","doi":"10.1109/IAT.2004.1343000","DOIUrl":"https://doi.org/10.1109/IAT.2004.1343000","url":null,"abstract":"We propose an innovative two-step learning approach to planning-instantiation for multi-agent coalition formation in dynamic, uncertain, real-time, and noisy environments. The first step learns about the planning of a coalition to improve its quality, adapting to the real-time and environmental requirements. The second step learns about the instantiation of the plan to improve the formation process, taking into account uncertain and dynamic behaviors of the peer agents. Decomposing the approach into two steps allows for modularity and flexibility in learning: learning how to plan a coalition is strategic while learning how to instantiate a plan is tactical. Our approach employs a case-based reinforcement learning (CBRL) framework.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126296487","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 : 2004-09-20DOI: 10.1109/IAT.2004.1342964
F. Neri
An agent based tool for analysing market behaviour under several rate of information diffusion is described. This methodology allows for the study of tradeoffs among several variables of information like product advertisement efforts, consumers' memory span, and passing word among friends in determining market shares. Insights gained by using this approach on a hypothetical economy are reported.
{"title":"Agent based simulation of information diffusion in a virtual market place","authors":"F. Neri","doi":"10.1109/IAT.2004.1342964","DOIUrl":"https://doi.org/10.1109/IAT.2004.1342964","url":null,"abstract":"An agent based tool for analysing market behaviour under several rate of information diffusion is described. This methodology allows for the study of tradeoffs among several variables of information like product advertisement efforts, consumers' memory span, and passing word among friends in determining market shares. Insights gained by using this approach on a hypothetical economy are reported.","PeriodicalId":281008,"journal":{"name":"Proceedings. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004).","volume":"2159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127469802","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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