Pub Date : 2016-06-01DOI: 10.1109/RCIS.2016.7549372
O. Parisot, Patrik Hitzelberger, Y. Didry, G. Vierke, Helmut Rieder
In order to analyze the descriptions of various active start-ups, we have developed a web application to retrieve and to analyze available textual data about them. The tool aims at extracting the frequent topics and applying semantic similarity analysis to the start-up descriptions.
{"title":"Text analytics on start-up descriptions","authors":"O. Parisot, Patrik Hitzelberger, Y. Didry, G. Vierke, Helmut Rieder","doi":"10.1109/RCIS.2016.7549372","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549372","url":null,"abstract":"In order to analyze the descriptions of various active start-ups, we have developed a web application to retrieve and to analyze available textual data about them. The tool aims at extracting the frequent topics and applying semantic similarity analysis to the start-up descriptions.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128191126","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549324
Ian Basaille, Sergey Kirgizov, É. Leclercq, M. Savonnet, N. Cullot
In this article we show how a multi-paradigm framework can fulfil the requirements of tweets analysis and reduce the waiting time for researchers that use computational resources and storage systems to support large-scale data analysis. The originality of our approach is to combine concerns about data harvesting, data storage, data analysis and data visualisation into a framework that supports inductive reasoning in multidisciplinary scientific research. Our main contribution is a polyglot storage system with a generic data model to support logical data independence and a set of tools that can provide a suitable solution for mixing different types of algorithms in order to maximise the extraction of knowledge. We describe the software architecture of our framework, the generic model and we show how it has been used in major projects and what characteristics have been validated.
{"title":"Towards a Twitter observatory: A multi-paradigm framework for collecting, storing and analysing tweets","authors":"Ian Basaille, Sergey Kirgizov, É. Leclercq, M. Savonnet, N. Cullot","doi":"10.1109/RCIS.2016.7549324","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549324","url":null,"abstract":"In this article we show how a multi-paradigm framework can fulfil the requirements of tweets analysis and reduce the waiting time for researchers that use computational resources and storage systems to support large-scale data analysis. The originality of our approach is to combine concerns about data harvesting, data storage, data analysis and data visualisation into a framework that supports inductive reasoning in multidisciplinary scientific research. Our main contribution is a polyglot storage system with a generic data model to support logical data independence and a set of tools that can provide a suitable solution for mixing different types of algorithms in order to maximise the extraction of knowledge. We describe the software architecture of our framework, the generic model and we show how it has been used in major projects and what characteristics have been validated.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131553349","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549342
L. Parody, María Teresa Gómez López, I. Bermejo, I. Caballero, R. M. Gasca, M. Piattini
The successful execution of a Business Process implies to use data with an adequate level of quality, thereby enabling the output of processes to be obtained in accordance with users requirements. The necessity to be aware of the data quality in the business processes is known, but the problem is how the incorporation of data quality management can affect and increase the complexity of the software development that supports the business process life-cycle. In order to gain advantages that data quality management can provide, organizations need to introduce mechanisms aimed at checking whether data satisfies the established data-quality requirements. Desirably, the implementation, deployment and use of these mechanisms should not interfere into the regular working of the business processes. In order to enable this independence, we propose the PAIS-DQ framework as an extension of the classical Process-Aware Information System (PAIS) proposal. The PAIS-DQ addresses the concerns related to data quality management activities by minimizing the required time for the software developers. In addition, with the aim of guiding developers in the use of PAIS-DQ, a methodology has been also provided to facilitate organizations to deal with complex concerns. The methodology renders our proposal applicable in practice, and has been applied to a case study where a service architecture implementing the standard ISO/IEC 8000-100:2009 parts 100 to 140 is included.
{"title":"PAIS-DQ: Extending process-aware information systems to support data quality in PAIS life-cycle","authors":"L. Parody, María Teresa Gómez López, I. Bermejo, I. Caballero, R. M. Gasca, M. Piattini","doi":"10.1109/RCIS.2016.7549342","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549342","url":null,"abstract":"The successful execution of a Business Process implies to use data with an adequate level of quality, thereby enabling the output of processes to be obtained in accordance with users requirements. The necessity to be aware of the data quality in the business processes is known, but the problem is how the incorporation of data quality management can affect and increase the complexity of the software development that supports the business process life-cycle. In order to gain advantages that data quality management can provide, organizations need to introduce mechanisms aimed at checking whether data satisfies the established data-quality requirements. Desirably, the implementation, deployment and use of these mechanisms should not interfere into the regular working of the business processes. In order to enable this independence, we propose the PAIS-DQ framework as an extension of the classical Process-Aware Information System (PAIS) proposal. The PAIS-DQ addresses the concerns related to data quality management activities by minimizing the required time for the software developers. In addition, with the aim of guiding developers in the use of PAIS-DQ, a methodology has been also provided to facilitate organizations to deal with complex concerns. The methodology renders our proposal applicable in practice, and has been applied to a case study where a service architecture implementing the standard ISO/IEC 8000-100:2009 parts 100 to 140 is included.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123543529","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549285
Thi-Mai-Huong Nguyen, A. Mammar, Régine Laleau, Samir Hameg
Currently, it is well recognized that coupling graphical and formal notations offers several advantages. Indeed, even if a graphical representation permits to design a visual, synthetic and user-friendly view of the system, it may be source of ambiguity and does not permit any formal verification. Formal methods help to remedy these shortcomings by giving a precise semantics to graphical notations such that it becomes possible to verify a large range of properties and even to generate correct implementations. Nevertheless, users cannot take a full advantage of the benefits of such a combination if it is not supported by an automatic tool that liberates them from the tedious translation activity. Following this direction, the present paper describes the main functionalities of a tool that automatically generates a formal secure access control filter for information systems. The goal of the filter is to regulate the access to data of an information system according to a set of static and dynamic rules. Data are described using a UML class diagram, whereas the static and dynamic rules are modeled using SECUREUML and UML activity diagrams respectively. Basically, the tool automatically generates the B formal specification corresponding to these diagrams and the filter.
{"title":"A tool for the generation of a secure access control filter","authors":"Thi-Mai-Huong Nguyen, A. Mammar, Régine Laleau, Samir Hameg","doi":"10.1109/RCIS.2016.7549285","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549285","url":null,"abstract":"Currently, it is well recognized that coupling graphical and formal notations offers several advantages. Indeed, even if a graphical representation permits to design a visual, synthetic and user-friendly view of the system, it may be source of ambiguity and does not permit any formal verification. Formal methods help to remedy these shortcomings by giving a precise semantics to graphical notations such that it becomes possible to verify a large range of properties and even to generate correct implementations. Nevertheless, users cannot take a full advantage of the benefits of such a combination if it is not supported by an automatic tool that liberates them from the tedious translation activity. Following this direction, the present paper describes the main functionalities of a tool that automatically generates a formal secure access control filter for information systems. The goal of the filter is to regulate the access to data of an information system according to a set of static and dynamic rules. Data are described using a UML class diagram, whereas the static and dynamic rules are modeled using SECUREUML and UML activity diagrams respectively. Basically, the tool automatically generates the B formal specification corresponding to these diagrams and the filter.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261055","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549281
A. Jalali
Data Visualization is an important area of research including different techniques to enhance the capability of people to understand and use data-driven information. The chord diagram is a technique that aims to support the visualization of relations among different participants in a social network. Although this technique is widely used and adopted in many disciplines, it is not currently implemented in Business Process Management (BPM). In this paper, we show the potential of the visualizing social network in BPM area using the chord diagram. The result shows the potential benefits and strength of this technique to discover social network patterns in BPM area.
{"title":"Reflections on the use of chord diagrams in social network visualization in process mining","authors":"A. Jalali","doi":"10.1109/RCIS.2016.7549281","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549281","url":null,"abstract":"Data Visualization is an important area of research including different techniques to enhance the capability of people to understand and use data-driven information. The chord diagram is a technique that aims to support the visualization of relations among different participants in a social network. Although this technique is widely used and adopted in many disciplines, it is not currently implemented in Business Process Management (BPM). In this paper, we show the potential of the visualizing social network in BPM area using the chord diagram. The result shows the potential benefits and strength of this technique to discover social network patterns in BPM area.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122294869","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549334
A. Jaffal, B. L. Grand
This paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to automatically identify the significant information that characterizes users' behavlors. In earlier work, we have used Formal Concept Analysis and Galois lattices to extract relevant knowledge from heterogeneous and complex contextual data; however, the interpretation of the obtained Galois lattices was performed manually. In this article, we aim at automating this interpretation process, through the provision of original metrics. Therefore our methodology returns relevant information without requiring any expertise in data analysis. We illustrate our contribution on real data collected from volunteer users.
{"title":"Towards an automatic extraction of smartphone users' contextual behaviors","authors":"A. Jaffal, B. L. Grand","doi":"10.1109/RCIS.2016.7549334","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549334","url":null,"abstract":"This paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to automatically identify the significant information that characterizes users' behavlors. In earlier work, we have used Formal Concept Analysis and Galois lattices to extract relevant knowledge from heterogeneous and complex contextual data; however, the interpretation of the obtained Galois lattices was performed manually. In this article, we aim at automating this interpretation process, through the provision of original metrics. Therefore our methodology returns relevant information without requiring any expertise in data analysis. We illustrate our contribution on real data collected from volunteer users.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127945441","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549363
Dalila Koulougli, A. Hadjali, Idir Rassoul
In recent years, crowdsourcing has become essential in a wide range of Web applications. Human factors play a key role in achieving high quality answers in crowdsourcing-based solving tasks. The most major factor is pertained to the uncertainty of workers about the responses that they provide to resolve the task at hand. On the other hand, workers may have diverse levels of expertise and skill. It is then important to take into account both the degrees of uncertainty and expertise when aggregating the set of worker answers. In this paper, we investigate some advanced crowdsourcing aggregation methods to find the correct answers by leveraging both expertise and uncertainty of workers in a unified way. Workers' uncertainty is represented in a possibilistic way, while a fine-grained scale for interpreting the degrees of skill is introduced. Finally, we present some comprehensive experiments to validate the effectiveness of our proposal.
{"title":"Leveraging human factors to enhance query answering in crowdsourcing systems","authors":"Dalila Koulougli, A. Hadjali, Idir Rassoul","doi":"10.1109/RCIS.2016.7549363","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549363","url":null,"abstract":"In recent years, crowdsourcing has become essential in a wide range of Web applications. Human factors play a key role in achieving high quality answers in crowdsourcing-based solving tasks. The most major factor is pertained to the uncertainty of workers about the responses that they provide to resolve the task at hand. On the other hand, workers may have diverse levels of expertise and skill. It is then important to take into account both the degrees of uncertainty and expertise when aggregating the set of worker answers. In this paper, we investigate some advanced crowdsourcing aggregation methods to find the correct answers by leveraging both expertise and uncertainty of workers in a unified way. Workers' uncertainty is represented in a possibilistic way, while a fine-grained scale for interpreting the degrees of skill is introduced. Finally, we present some comprehensive experiments to validate the effectiveness of our proposal.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132470033","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549345
M. Schramm, M. Daneva
Today many organizations use service-oriented architecture and agile software development as their software paradigms. While both certainly have their advantages, in the fields of Empirical Software Engineering and Information Systems these have been treated in relative isolation and their impact on each other is not well understood. This paper performs a grounded theory research by empirically analyzing professional blog posts published in IBM's Developerworks platform, to find good practices and common pitfalls of using a service-oriented architecture and agile software development together. The perspective taken in this study is the one of service-oriented architecture practitioners involved in agile projects. We found that continuous integration, collaboration, governance and continuous improvement are good practices that result out of merging the two paradigms. We found that the challenges of the joint use of service-oriented architecture and agile lie in the engineering of non-functional requirements, compliance requirements as well as up-front architecture evaluation.
{"title":"Implementations of service oriented architecture and agile software development: What works and what are the challenges?","authors":"M. Schramm, M. Daneva","doi":"10.1109/RCIS.2016.7549345","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549345","url":null,"abstract":"Today many organizations use service-oriented architecture and agile software development as their software paradigms. While both certainly have their advantages, in the fields of Empirical Software Engineering and Information Systems these have been treated in relative isolation and their impact on each other is not well understood. This paper performs a grounded theory research by empirically analyzing professional blog posts published in IBM's Developerworks platform, to find good practices and common pitfalls of using a service-oriented architecture and agile software development together. The perspective taken in this study is the one of service-oriented architecture practitioners involved in agile projects. We found that continuous integration, collaboration, governance and continuous improvement are good practices that result out of merging the two paradigms. We found that the challenges of the joint use of service-oriented architecture and agile lie in the engineering of non-functional requirements, compliance requirements as well as up-front architecture evaluation.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126478908","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549335
M. Maiza, Chiheb-Eddine Ben N'cir, N. Essoussi
Overlapping Clustering is an important technique in machine learning which aims to organize data into a set of non-disjoint groups rather than the disjoint one which is the case of conventional clustering methods. Several machine learning applications require that data object be assigned to one or several groups resulting in non-disjoint partitioning of data such as document clustering where each document can discuss one or many topics and then must be assigned to one or several groups. This paper presents a new partitional overlapping clustering method based on the additive model of overlaps. Compared to existing methods which build clusters with fixed size of overlaps, the proposed method gives users the ability to regulate this size. Experiments performed on simulated and real datasets show the performance of the proposed regulation principle to control the size of overlaps among groups.
{"title":"Overlap regulation for additive overlapping clustering methods","authors":"M. Maiza, Chiheb-Eddine Ben N'cir, N. Essoussi","doi":"10.1109/RCIS.2016.7549335","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549335","url":null,"abstract":"Overlapping Clustering is an important technique in machine learning which aims to organize data into a set of non-disjoint groups rather than the disjoint one which is the case of conventional clustering methods. Several machine learning applications require that data object be assigned to one or several groups resulting in non-disjoint partitioning of data such as document clustering where each document can discuss one or many topics and then must be assigned to one or several groups. This paper presents a new partitional overlapping clustering method based on the additive model of overlaps. Compared to existing methods which build clusters with fixed size of overlaps, the proposed method gives users the ability to regulate this size. Experiments performed on simulated and real datasets show the performance of the proposed regulation principle to control the size of overlaps among groups.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130701509","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 : 2016-06-01DOI: 10.1109/RCIS.2016.7549282
Danillo Sprovieri, Daniel Diaz, R. Mazo, Knut Hinkelmann
Context: Organizations act in highly competitive markets, which forces them to be flexible. Constantly changing business requirements require flexible business processes. Case Management Model and Notation (CMMN) supports modeling run-time flexibility of partially structured business process models, but does not fully specify the control flow. Objective: The goal is to develop a planning algorithm that supports the case worker in planning case-based business processes at run-time. Method: We identify the requirements of run-time planning of partly structured processes by analyzing the admission process for the master degree at FHNW. To plan the process instance, we develop a planning algorithm. Our planning algorithm is evaluated using concrete cases provided by FHNW in order to demonstrate real application. Results: The planning algorithm reflects the requirements for serializing tasks at run-time. Conclusion: Our planning algorithm allows to automatically deriving context-specific execution plans for CMMN models at run-time.
{"title":"Run-time planning of case-based business processes","authors":"Danillo Sprovieri, Daniel Diaz, R. Mazo, Knut Hinkelmann","doi":"10.1109/RCIS.2016.7549282","DOIUrl":"https://doi.org/10.1109/RCIS.2016.7549282","url":null,"abstract":"Context: Organizations act in highly competitive markets, which forces them to be flexible. Constantly changing business requirements require flexible business processes. Case Management Model and Notation (CMMN) supports modeling run-time flexibility of partially structured business process models, but does not fully specify the control flow. Objective: The goal is to develop a planning algorithm that supports the case worker in planning case-based business processes at run-time. Method: We identify the requirements of run-time planning of partly structured processes by analyzing the admission process for the master degree at FHNW. To plan the process instance, we develop a planning algorithm. Our planning algorithm is evaluated using concrete cases provided by FHNW in order to demonstrate real application. Results: The planning algorithm reflects the requirements for serializing tasks at run-time. Conclusion: Our planning algorithm allows to automatically deriving context-specific execution plans for CMMN models at run-time.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116418534","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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