Pub Date : 2016-10-19DOI: 10.1109/FSKD.2016.7603167
J. Liao, Hong-Tzer Yang
In response to higher and higher dimensions and complexity of optimization problems in engineering applications, the optimization algorithms face more and more challenges. This paper proposes a novel electron drifting algorithm (e-DA) to avoid the common disadvantages, such as easy to trap in a local optimal point and sensitive to initial solutions, of existing methods. A simple example is addressed in the paper to make readers easily understand the executed processes. Some benchmark functions are used for testing the effectiveness of the proposed e-DA. Besides, the performance of e-DA is compared with the existing optimization algorithms, including particle swarm optimization (PSO), differential evolution (DE), and artificial bee colony (ABC). Numerical results verify that the searching efficiency and capability of the proposed e-DA are enhanced and better than the existing algorithms.
{"title":"A novel electrons drifting algorithm for non-linear optimization problems","authors":"J. Liao, Hong-Tzer Yang","doi":"10.1109/FSKD.2016.7603167","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603167","url":null,"abstract":"In response to higher and higher dimensions and complexity of optimization problems in engineering applications, the optimization algorithms face more and more challenges. This paper proposes a novel electron drifting algorithm (e-DA) to avoid the common disadvantages, such as easy to trap in a local optimal point and sensitive to initial solutions, of existing methods. A simple example is addressed in the paper to make readers easily understand the executed processes. Some benchmark functions are used for testing the effectiveness of the proposed e-DA. Besides, the performance of e-DA is compared with the existing optimization algorithms, including particle swarm optimization (PSO), differential evolution (DE), and artificial bee colony (ABC). Numerical results verify that the searching efficiency and capability of the proposed e-DA are enhanced and better than the existing algorithms.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128499906","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603389
Kaiyu Wan, V. Alagar
Information technology has advanced during the last five decades to the stage where its impact is being felt by the society in every service that it gets from media, business, health care, consumer electronics, energy and power, and transportation domains. During this course of human-technology interaction enormous amount of data and knowledge transfer takes place directly between service providers and their clients, as well as indirectly between clients. Because human tendency is to “analyze” its past in order to predict the “future”, keeping track of this dynamically streaming voluminous heterogeneous data, called Big Data (BD), and analyzing it for meaningful discovery of knowledge that leads to value-added business becomes an important research activity. It is in this context that research in Big Data (BD) computing has emerged. Meaningful decisions can be based only on significant knowledge discovery, which in turn requires a good understanding of the characteristics of the accumulated data, an appropriate classification of this huge collection, and an efficient analysis of it. Health care sector is a critical infrastructure because its services affect the lives of humans and the lack of service continuity may be disastrous to the economy and human lives. The large amount of data collected by this sector from its clients is structured into Electronic Health Records (EHR) which is BD, and is used along with pharmaceutical and regulatory data in providing health services. More BD is generated while administering services and measuring their impacts on clients after administering the services. It is in this larger context that we investigate the types and sources of Health Care BD (HBD), its characteristics, and give a classification of it.
{"title":"Characteristics and classification of big data in health care sector","authors":"Kaiyu Wan, V. Alagar","doi":"10.1109/FSKD.2016.7603389","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603389","url":null,"abstract":"Information technology has advanced during the last five decades to the stage where its impact is being felt by the society in every service that it gets from media, business, health care, consumer electronics, energy and power, and transportation domains. During this course of human-technology interaction enormous amount of data and knowledge transfer takes place directly between service providers and their clients, as well as indirectly between clients. Because human tendency is to “analyze” its past in order to predict the “future”, keeping track of this dynamically streaming voluminous heterogeneous data, called Big Data (BD), and analyzing it for meaningful discovery of knowledge that leads to value-added business becomes an important research activity. It is in this context that research in Big Data (BD) computing has emerged. Meaningful decisions can be based only on significant knowledge discovery, which in turn requires a good understanding of the characteristics of the accumulated data, an appropriate classification of this huge collection, and an efficient analysis of it. Health care sector is a critical infrastructure because its services affect the lives of humans and the lack of service continuity may be disastrous to the economy and human lives. The large amount of data collected by this sector from its clients is structured into Electronic Health Records (EHR) which is BD, and is used along with pharmaceutical and regulatory data in providing health services. More BD is generated while administering services and measuring their impacts on clients after administering the services. It is in this larger context that we investigate the types and sources of Health Care BD (HBD), its characteristics, and give a classification of it.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115479622","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603424
Liping Du, Xiaoge Li, Dayi Lin
Point-wise Mutual Information(PMI) has been widely used in many areas of lexicon construction, term extraction and text mining. However, PMI has a well-known tendency, which is overvaluing the relatedness of word pairs that involve low-frequency words. To overcome this limitation, Expected Point-wise Mutual Information (PMIK) has been proposed empirically. In this paper, we propose an automatic term recognition system for Chinese and theoretically prove that with variant k ≥ 3, PMIK method can overcome the bias of low-frequency words. The experiment results on Chinese SINA blog and Baidu Tieba corpus show that with a proper k value of 5, the system can achieve a precision greater than 81% for top 1000 extracted terms without decreasing the recall.
{"title":"Chinese term extraction from web pages based on expected point-wise mutual information","authors":"Liping Du, Xiaoge Li, Dayi Lin","doi":"10.1109/FSKD.2016.7603424","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603424","url":null,"abstract":"Point-wise Mutual Information(PMI) has been widely used in many areas of lexicon construction, term extraction and text mining. However, PMI has a well-known tendency, which is overvaluing the relatedness of word pairs that involve low-frequency words. To overcome this limitation, Expected Point-wise Mutual Information (PMIK) has been proposed empirically. In this paper, we propose an automatic term recognition system for Chinese and theoretically prove that with variant k ≥ 3, PMIK method can overcome the bias of low-frequency words. The experiment results on Chinese SINA blog and Baidu Tieba corpus show that with a proper k value of 5, the system can achieve a precision greater than 81% for top 1000 extracted terms without decreasing the recall.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117120930","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603212
Yinan Wu, H. Zhan, Junhe Yu
Knowledge about problem solving in business events is complex, besides, there is a dispersity in terms of the storage of the knowledge. As a result, islands of knowledge are common in problem solving of business events. Knowledge links established norms of the business problem to solve in the process of knowledge structure and connect with each other. Scenario links solving scenario factors of business problem to standardized and unified. In order to facilitate understanding and application of enterprise knowledge resources from a holistic perspective, by visualizing conceptual design solving business problem knowledge map model. Reduce enterprise business problem solving in the process of knowledge island phenomenon. Promote the reuse of knowledge.
{"title":"Knowledge map application of business-oriented problem solving","authors":"Yinan Wu, H. Zhan, Junhe Yu","doi":"10.1109/FSKD.2016.7603212","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603212","url":null,"abstract":"Knowledge about problem solving in business events is complex, besides, there is a dispersity in terms of the storage of the knowledge. As a result, islands of knowledge are common in problem solving of business events. Knowledge links established norms of the business problem to solve in the process of knowledge structure and connect with each other. Scenario links solving scenario factors of business problem to standardized and unified. In order to facilitate understanding and application of enterprise knowledge resources from a holistic perspective, by visualizing conceptual design solving business problem knowledge map model. Reduce enterprise business problem solving in the process of knowledge island phenomenon. Promote the reuse of knowledge.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127121590","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603522
Chuang Deng, Junyong Liu, Yang Liu, Zhen Yu
This paper discusses the characteristics of the cloud computing techniques and further compares the features of the cloud computing to those of the traditional distributed computing. The paper also studies the types and forms of the modern services and requirements in power systems, and therefore aiming at designing and constructing a high-performance platform in enabling scalable power system services based on cloud computing is presented. The details of the platform design including data distribution, process monitoring, data integration and resource scheduling have been fully presented. The application of the platform in a practical power system indicates that it can significantly simplify the design, development and implementation of the power system computing services and systems, which improves the efficiency of the daily services of power system.
{"title":"Cloud computing based high-performance platform in enabling scalable services in power system","authors":"Chuang Deng, Junyong Liu, Yang Liu, Zhen Yu","doi":"10.1109/FSKD.2016.7603522","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603522","url":null,"abstract":"This paper discusses the characteristics of the cloud computing techniques and further compares the features of the cloud computing to those of the traditional distributed computing. The paper also studies the types and forms of the modern services and requirements in power systems, and therefore aiming at designing and constructing a high-performance platform in enabling scalable power system services based on cloud computing is presented. The details of the platform design including data distribution, process monitoring, data integration and resource scheduling have been fully presented. The application of the platform in a practical power system indicates that it can significantly simplify the design, development and implementation of the power system computing services and systems, which improves the efficiency of the daily services of power system.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125184312","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603444
Weidong Zhang, Mingyue Xu, Zhou Lu, Zhichao Qin
This paper partitions original user and emergency user specific downtilts through dynamic vertical beamforming in 3-dimension (3D) emergency networks. The coordination scheme aims to maximize the throughput of both original users and emergency users, subject to per wireless access point (AP) power and downtilt constraints. We propose a relative narrow-band transmit power (RNTP) based coordinated resource allocation scheme to solve this optimization problem, by interacting RNTP bit maps among eNBs. Here, power and downtilts adjustment, resource block (RB) allocationare jointly optimized. Simulation results show that such RNTP-based resource allocation scheme is efficient.
{"title":"RNTP-based coordinated resource allocation in 3D emergency networks","authors":"Weidong Zhang, Mingyue Xu, Zhou Lu, Zhichao Qin","doi":"10.1109/FSKD.2016.7603444","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603444","url":null,"abstract":"This paper partitions original user and emergency user specific downtilts through dynamic vertical beamforming in 3-dimension (3D) emergency networks. The coordination scheme aims to maximize the throughput of both original users and emergency users, subject to per wireless access point (AP) power and downtilt constraints. We propose a relative narrow-band transmit power (RNTP) based coordinated resource allocation scheme to solve this optimization problem, by interacting RNTP bit maps among eNBs. Here, power and downtilts adjustment, resource block (RB) allocationare jointly optimized. Simulation results show that such RNTP-based resource allocation scheme is efficient.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126157209","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603281
Wuying Liu, Lin Wang, Xing Zhang
Syntax matching is a challenging basic issue, and related algorithms can be widely used in natural language processing. This paper addresses the problem of how to efficiently match a sentence with the most similar syntactic structure to a given Japanese sentence from a big set of Japanese sentences, designs a novel lexical index data structure of hiratoken-sentence index (HSI) according to our Japanese syntax identification hypothesis of hiragana token, and proposes a HSI-based Japanese syntax matching (HSIJSM) algorithm. Supported by the HSI data structure, the HSIJSM algorithm can approximately get the syntactic similarity after the fast calculating of formal similarity between two Japanese sentences. The experimental results show that the HSIJSM algorithm can achieve the preferable performance with greatly reduced time costs.
{"title":"Lexical-index-based Japanese syntax matching","authors":"Wuying Liu, Lin Wang, Xing Zhang","doi":"10.1109/FSKD.2016.7603281","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603281","url":null,"abstract":"Syntax matching is a challenging basic issue, and related algorithms can be widely used in natural language processing. This paper addresses the problem of how to efficiently match a sentence with the most similar syntactic structure to a given Japanese sentence from a big set of Japanese sentences, designs a novel lexical index data structure of hiratoken-sentence index (HSI) according to our Japanese syntax identification hypothesis of hiragana token, and proposes a HSI-based Japanese syntax matching (HSIJSM) algorithm. Supported by the HSI data structure, the HSIJSM algorithm can approximately get the syntactic similarity after the fast calculating of formal similarity between two Japanese sentences. The experimental results show that the HSIJSM algorithm can achieve the preferable performance with greatly reduced time costs.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123277000","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603336
Gang Sun, Zhongxin Wang, Jia Zhao, Hao Wang, Huaping Zhou, Kelei Sun
Monitoring data in coal mine is essentially data stream. With the change of environment, coal mine monitoring data stream implied concept drifts. Coal mine safety evaluation can be seen as concept drifting data stream classification. The method proposed in this paper is based on random decision tree model, and it uses Hoeffding Bounds inequality and information entropy instead of random selection to determine the split point, and it uses the threshold determined by Hoeffding Bounds inequality detect concept drift. Experimental results show the method can better detect concept drifts in data stream, and it has better classification accuracy for data stream, and it provides a new practical approach for coal mine safety evaluation.
{"title":"A coal mine safety evaluation method based on concept drifting data stream classification","authors":"Gang Sun, Zhongxin Wang, Jia Zhao, Hao Wang, Huaping Zhou, Kelei Sun","doi":"10.1109/FSKD.2016.7603336","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603336","url":null,"abstract":"Monitoring data in coal mine is essentially data stream. With the change of environment, coal mine monitoring data stream implied concept drifts. Coal mine safety evaluation can be seen as concept drifting data stream classification. The method proposed in this paper is based on random decision tree model, and it uses Hoeffding Bounds inequality and information entropy instead of random selection to determine the split point, and it uses the threshold determined by Hoeffding Bounds inequality detect concept drift. Experimental results show the method can better detect concept drifts in data stream, and it has better classification accuracy for data stream, and it provides a new practical approach for coal mine safety evaluation.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125531913","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603265
Haipeng Liu, Defeng Wang, Ka Sing Wong, Yinglan Gong, L. Xia
A variation of spherical coordinate system is proposed for the simplification of illustration of Listing's law. With this method, the rotation of an eye is decomposed into two independent rotations, largely simplified its math expression. The robotics method of motion matrix transformation is then applied to derive the math interpretation of primary Listing's law and half-angle rule respectively. Based on the results, a new algorithm for eyeball position and orientation measurement is proposed. In this algorithm, all the parameters can be directly measured from photos, thus makes rapid diagnosis of strabismus possible.
{"title":"An improved spherical coordinate system applied in oculomotor system-the possibility for rapid strabismus diagnosis","authors":"Haipeng Liu, Defeng Wang, Ka Sing Wong, Yinglan Gong, L. Xia","doi":"10.1109/FSKD.2016.7603265","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603265","url":null,"abstract":"A variation of spherical coordinate system is proposed for the simplification of illustration of Listing's law. With this method, the rotation of an eye is decomposed into two independent rotations, largely simplified its math expression. The robotics method of motion matrix transformation is then applied to derive the math interpretation of primary Listing's law and half-angle rule respectively. Based on the results, a new algorithm for eyeball position and orientation measurement is proposed. In this algorithm, all the parameters can be directly measured from photos, thus makes rapid diagnosis of strabismus possible.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546554","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 : 2016-08-01DOI: 10.1109/FSKD.2016.7603217
Aiping Xu, Di Wu, Wuping Xu
Although at present a lot of big data use the ways of column store, traditional row store is still the mainstream storage way of relational database management system. There is no universal transformation tool facing of the requirements which column stored be transform into row store in heterogeneous database integration systems. The transpose mapping table of column store to row store, data extraction process based on this mapping table, corresponding transposing algorithm are researched and the effectiveness of these key technologies are verified through examples and implementation in this paper. This result is suitable to data extraction from column store to row store for different source table to destination table. Any prerequisites need not be set to the table structure and the type of database of source table and destination table in this research. Therefore, this result possess good generality and compatibility to heterogeneous data sources.
{"title":"Research of key technology about column store to row store in multi-source heterogeneous database","authors":"Aiping Xu, Di Wu, Wuping Xu","doi":"10.1109/FSKD.2016.7603217","DOIUrl":"https://doi.org/10.1109/FSKD.2016.7603217","url":null,"abstract":"Although at present a lot of big data use the ways of column store, traditional row store is still the mainstream storage way of relational database management system. There is no universal transformation tool facing of the requirements which column stored be transform into row store in heterogeneous database integration systems. The transpose mapping table of column store to row store, data extraction process based on this mapping table, corresponding transposing algorithm are researched and the effectiveness of these key technologies are verified through examples and implementation in this paper. This result is suitable to data extraction from column store to row store for different source table to destination table. Any prerequisites need not be set to the table structure and the type of database of source table and destination table in this research. Therefore, this result possess good generality and compatibility to heterogeneous data sources.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126716968","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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