This paper develops a categorization of cloud security risks, elaborates how they impact information security, and discusses potential security benefits from cloud sourcing. This review integrates the literature on information systems and computer science to summarize managerial and technological mitigation measures that enhance cloud security. The analysis uncovers gaps regarding the empirical investigation of security considerations in the corporate decision-making process. Specifically, the micro level of how security comes into play in the decision-making process and whether mitigation measures proposed by scholars are practically feasible requires further investigation. Furthermore, the macro level, how stakeholders perceive cloud sourcing, is not yet well understood.
{"title":"Information Security Risks, Benefits, and Mitigation Measures in Cloud Sourcing","authors":"Frederik Wulf, Susanne Strahringer, M. Westner","doi":"10.1109/CBI.2019.00036","DOIUrl":"https://doi.org/10.1109/CBI.2019.00036","url":null,"abstract":"This paper develops a categorization of cloud security risks, elaborates how they impact information security, and discusses potential security benefits from cloud sourcing. This review integrates the literature on information systems and computer science to summarize managerial and technological mitigation measures that enhance cloud security. The analysis uncovers gaps regarding the empirical investigation of security considerations in the corporate decision-making process. Specifically, the micro level of how security comes into play in the decision-making process and whether mitigation measures proposed by scholars are practically feasible requires further investigation. Furthermore, the macro level, how stakeholders perceive cloud sourcing, is not yet well understood.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121689221","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}
The quality of medical care can be evaluated by three main components, which were proposed by Avedis Donabedian: the quality of structure, the quality of process and the quality of outcome. Donabedian's idea was that all three components are connected by sequential progression, i.e. the quality of structure provides for the quality of process and the quality of process provides for the quality of outcome. There are some papers on the study of causal model of structure - process - outcome, but they do not consider the assessment and analysis of the changes in the quality of care observed after certain changes in the administrative structure of a healthcare delivery unit. This paper proposes a model for evaluating the impact of changes in the structure of a healthcare delivery unit on the quality of medical care provided. The proposed method for the development and analysis of the model includes four steps: (1) sample determination and data collection; (2) data reduction by exploratory factor analysis to define the indicators for each of the dimensions of the Donabedian Model; (3) studying the indirect influence of structure changes using the apparatus of fuzzy binary relations; (4) calculating the change in the quality measures after those structure changes and modeling management scenarios. The model combines the apparatus of fuzzy binary relations with the analysis based on fuzzy cognitive modeling. The fusion of the two approaches is justified by the what-if analysis and allows define the optimal management strategy. The model is realized with data obtained by surveying ambulance patients.
{"title":"Fuzzy Model for Evaluating the Quality of Medical Care","authors":"S. V. Begicheva","doi":"10.1109/CBI.2019.10088","DOIUrl":"https://doi.org/10.1109/CBI.2019.10088","url":null,"abstract":"The quality of medical care can be evaluated by three main components, which were proposed by Avedis Donabedian: the quality of structure, the quality of process and the quality of outcome. Donabedian's idea was that all three components are connected by sequential progression, i.e. the quality of structure provides for the quality of process and the quality of process provides for the quality of outcome. There are some papers on the study of causal model of structure - process - outcome, but they do not consider the assessment and analysis of the changes in the quality of care observed after certain changes in the administrative structure of a healthcare delivery unit. This paper proposes a model for evaluating the impact of changes in the structure of a healthcare delivery unit on the quality of medical care provided. The proposed method for the development and analysis of the model includes four steps: (1) sample determination and data collection; (2) data reduction by exploratory factor analysis to define the indicators for each of the dimensions of the Donabedian Model; (3) studying the indirect influence of structure changes using the apparatus of fuzzy binary relations; (4) calculating the change in the quality measures after those structure changes and modeling management scenarios. The model combines the apparatus of fuzzy binary relations with the analysis based on fuzzy cognitive modeling. The fusion of the two approaches is justified by the what-if analysis and allows define the optimal management strategy. The model is realized with data obtained by surveying ambulance patients.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125471472","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 this paper, we propose a novel intelligent methodology to construct a Bankruptcy Prediction Computation Model, which is aimed to execute a company's financial status analysis accurately. Based on the semantic data analysis and management, our methodology considers Semantic Database System as the core of the system. It comprises three layers: an Ontology of Bankruptcy Prediction, Semantic Search Engine, and a Semantic Analysis Graph Database system. The Ontological layer defines the basic concepts of the financial risk management as well as the objects that serve as sources of knowledge for predicting a company's bankruptcy. The Graph Database layer utilises a powerful semantic data technology, which serves as a semantic data repository for our model. The article provides a detailed description of the construction of the Ontology and its informal conceptual representation. We also present a working prototype of the Graph Database system, constructed using the Neo4j application, and show the connection between well-known financial ratios. We argue that this methodology which utilises state of the art semantic data management mechanisms enables data processing and relevant computations in a more efficient way than approaches using the traditional relational database. These give us solid grounds to build a system that is capable of tackling the data of any complexity level.
{"title":"Computational Modelling for Bankruptcy Prediction: Semantic Data Analysis Integrating Graph Database and Financial Ontology","authors":"Natalia Yerashenia, A. Bolotov","doi":"10.1109/CBI.2019.00017","DOIUrl":"https://doi.org/10.1109/CBI.2019.00017","url":null,"abstract":"In this paper, we propose a novel intelligent methodology to construct a Bankruptcy Prediction Computation Model, which is aimed to execute a company's financial status analysis accurately. Based on the semantic data analysis and management, our methodology considers Semantic Database System as the core of the system. It comprises three layers: an Ontology of Bankruptcy Prediction, Semantic Search Engine, and a Semantic Analysis Graph Database system. The Ontological layer defines the basic concepts of the financial risk management as well as the objects that serve as sources of knowledge for predicting a company's bankruptcy. The Graph Database layer utilises a powerful semantic data technology, which serves as a semantic data repository for our model. The article provides a detailed description of the construction of the Ontology and its informal conceptual representation. We also present a working prototype of the Graph Database system, constructed using the Neo4j application, and show the connection between well-known financial ratios. We argue that this methodology which utilises state of the art semantic data management mechanisms enables data processing and relevant computations in a more efficient way than approaches using the traditional relational database. These give us solid grounds to build a system that is capable of tackling the data of any complexity level.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116647424","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}
Tax compliance requires businesses to implement compliant processes but also documenting and reporting mechanisms to proof a compliant process execution. Non-compliance has far-reaching consequences ranging from financial penalties to criminal investigations, thus threatening the competitive position of a business. Therefore, the Organisation for Economic Co-operation and Development (OECD) investigates means, among others the blockchain technology, to ease the tax compliance efforts of businesses. However, ensuring tax compliance in business processes is a complex and challenging task, which is why tax compliance management is often implemented as an independent area of responsibility within a business. Nevertheless, an integration of tax compliance into the business processes is necessary to enable compliance by design, resulting in efficient processes. In this paper, we investigate whether blockchain technology can contribute to tax compliance by design in business processes. To meet this end, we provide a conceptual design and a prototype for compliant process execution in the context of value-added taxes.
{"title":"Towards Tax Compliance by Design: A Decentralized Validation of Tax Processes Using Blockchain Technology","authors":"Filip Fatz, Philip Hake, P. Fettke","doi":"10.1109/CBI.2019.00071","DOIUrl":"https://doi.org/10.1109/CBI.2019.00071","url":null,"abstract":"Tax compliance requires businesses to implement compliant processes but also documenting and reporting mechanisms to proof a compliant process execution. Non-compliance has far-reaching consequences ranging from financial penalties to criminal investigations, thus threatening the competitive position of a business. Therefore, the Organisation for Economic Co-operation and Development (OECD) investigates means, among others the blockchain technology, to ease the tax compliance efforts of businesses. However, ensuring tax compliance in business processes is a complex and challenging task, which is why tax compliance management is often implemented as an independent area of responsibility within a business. Nevertheless, an integration of tax compliance into the business processes is necessary to enable compliance by design, resulting in efficient processes. In this paper, we investigate whether blockchain technology can contribute to tax compliance by design in business processes. To meet this end, we provide a conceptual design and a prototype for compliant process execution in the context of value-added taxes.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127072207","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}
Alexander Wurl, Andreas A. Falkner, Alois Haselböck, Alexandra Mazak
In rail automation, failure analysis is a crucial task in the maintenance phase. Domain experts are often faced with various challenges in analyzing large data volumes of highly complex data structures. Finding causes for potential failures and deciding how to optimize or repair the system may be extensively time consuming. We propose the concept of a digital companion which assists experts during analysis and recommends optimizations for the installed system. A sequence of different data analytics methods within the digital companion enables the domain experts to manage and control the process of failure analysis. In illustrative examples, we give insights in the workflow of the digital companion and discuss its application in the domain of rail automation.
{"title":"A Conceptual Design of a Digital Companion for Failure Analysis in Rail Automation","authors":"Alexander Wurl, Andreas A. Falkner, Alois Haselböck, Alexandra Mazak","doi":"10.1109/CBI.2019.00073","DOIUrl":"https://doi.org/10.1109/CBI.2019.00073","url":null,"abstract":"In rail automation, failure analysis is a crucial task in the maintenance phase. Domain experts are often faced with various challenges in analyzing large data volumes of highly complex data structures. Finding causes for potential failures and deciding how to optimize or repair the system may be extensively time consuming. We propose the concept of a digital companion which assists experts during analysis and recommends optimizations for the installed system. A sequence of different data analytics methods within the digital companion enables the domain experts to manage and control the process of failure analysis. In illustrative examples, we give insights in the workflow of the digital companion and discuss its application in the domain of rail automation.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116557555","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}
This article describes a software package for solving the problem of personnel assessment. A matrix convolution block is used. The software package important feature is the ability to visualize the obtained results of the "traffic light" type.
{"title":"Development of Software Complex Personnel Assessment in RDS Environment","authors":"O. Kuznetsova, Anastasia Marencova","doi":"10.1109/CBI.2019.10104","DOIUrl":"https://doi.org/10.1109/CBI.2019.10104","url":null,"abstract":"This article describes a software package for solving the problem of personnel assessment. A matrix convolution block is used. The software package important feature is the ability to visualize the obtained results of the \"traffic light\" type.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122118055","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}
There are few empirical studies that directly investigate the relationships between mobile device usage and four constructs (student-student dialogue, student-instructor dialogue, self-regulation, and learning outcomes) in university online education. Structural equation modeling is applied to examine the effects of mobile device usage on students' perceived learning outcomes. A total of 350 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest USA were used to examine the structural model. The results of this study showed that mobile device usage affect student-instructor dialogue positively and facilitate the self-regulation process, which in turn positively affect the learning outcomes.
{"title":"The Effects of Mobile Device Usage on Students' Perceived Level of Dialog, Self-Regulated Learning Strategies and E-Learning Outcomes","authors":"Sean B. Eom","doi":"10.1109/CBI.2019.00044","DOIUrl":"https://doi.org/10.1109/CBI.2019.00044","url":null,"abstract":"There are few empirical studies that directly investigate the relationships between mobile device usage and four constructs (student-student dialogue, student-instructor dialogue, self-regulation, and learning outcomes) in university online education. Structural equation modeling is applied to examine the effects of mobile device usage on students' perceived learning outcomes. A total of 350 valid unduplicated responses from students who have completed at least one online course at a university in the Midwest USA were used to examine the structural model. The results of this study showed that mobile device usage affect student-instructor dialogue positively and facilitate the self-regulation process, which in turn positively affect the learning outcomes.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131953235","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}
This research investigates the effect of IT-related financial innovation on banks' risk-taking based on the patent applications of the 100 largest U.S. Bank Holding Companies (BHCs) from 2005 until 2015. The results show that financial innovation within the research period is not only product-focused and in contrast mainly determined by IT-related innovations like risk management systems, credit scoring models and risk or pricing algorithms. The present empirical analysis furthermore addresses the simultaneous causality between innovation and risk-taking, which causes an endogeneity problem in the regression analysis. Two potential instrumental variables for innovation have been examined, which focus on the open-mindedness of the banks' headquarter environments in terms of racial and ethnic diversity and sexual orientation. The results underline the positive effects of an open-minded environment on the innovativeness of the financial industry. Innovation, synthesized by the instrumental variable Ssex, tends to decrease bank risk-taking.
{"title":"How IT-Related Financial Innovation Influences Bank Risk-Taking: Results from an Empirical Analysis of Patent Applications","authors":"Christian Dietzmann, R. Alt","doi":"10.1109/CBI.2019.00059","DOIUrl":"https://doi.org/10.1109/CBI.2019.00059","url":null,"abstract":"This research investigates the effect of IT-related financial innovation on banks' risk-taking based on the patent applications of the 100 largest U.S. Bank Holding Companies (BHCs) from 2005 until 2015. The results show that financial innovation within the research period is not only product-focused and in contrast mainly determined by IT-related innovations like risk management systems, credit scoring models and risk or pricing algorithms. The present empirical analysis furthermore addresses the simultaneous causality between innovation and risk-taking, which causes an endogeneity problem in the regression analysis. Two potential instrumental variables for innovation have been examined, which focus on the open-mindedness of the banks' headquarter environments in terms of racial and ethnic diversity and sexual orientation. The results underline the positive effects of an open-minded environment on the innovativeness of the financial industry. Innovation, synthesized by the instrumental variable Ssex, tends to decrease bank risk-taking.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126445695","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}
Rongjia Song, J. Vanthienen, Weiping Cui, Ying Wang, Lei Huang
IoT (Internet of Things) has the capability of capturing dynamic context from the physical world into the digital world. Context-aware BPM (Business Process Management) should integrate IoT as a key perspective of dynamic context of a business process and to enhance the decision making in a business process. IoT is often used to automate the process execution or integrated in the process model as resources of smart devices and additional concepts. In this way, IoT data is directly used without processing or reasoning with other contextual data to obtain higher-order contextual knowledge, which impairs its potential capability. The context layer and the decision layer are still missing while integrating IoT in BPM to obtain context-awareness. Decisions are still considered within context-aware BPM in a traditional way. This paper provides a separate concern of decisions from the process flow. We propose that the context-aware BPM ecosystem consists of four components which are: context-aware process models, context models, decision models and context-aware process execution. A framework is proposed to connect the IoT infrastructure to the context-aware BPM ecosystem using IoT-integrated ontologies and IoT-enhanced decision models, which enables the capabilities of IoT to make business processes and the decision making involved aware of the dynamic context.
{"title":"Context-Aware BPM Using IoT-Integrated Context Ontologies and IoT-Enhanced Decision Models","authors":"Rongjia Song, J. Vanthienen, Weiping Cui, Ying Wang, Lei Huang","doi":"10.1109/CBI.2019.00069","DOIUrl":"https://doi.org/10.1109/CBI.2019.00069","url":null,"abstract":"IoT (Internet of Things) has the capability of capturing dynamic context from the physical world into the digital world. Context-aware BPM (Business Process Management) should integrate IoT as a key perspective of dynamic context of a business process and to enhance the decision making in a business process. IoT is often used to automate the process execution or integrated in the process model as resources of smart devices and additional concepts. In this way, IoT data is directly used without processing or reasoning with other contextual data to obtain higher-order contextual knowledge, which impairs its potential capability. The context layer and the decision layer are still missing while integrating IoT in BPM to obtain context-awareness. Decisions are still considered within context-aware BPM in a traditional way. This paper provides a separate concern of decisions from the process flow. We propose that the context-aware BPM ecosystem consists of four components which are: context-aware process models, context models, decision models and context-aware process execution. A framework is proposed to connect the IoT infrastructure to the context-aware BPM ecosystem using IoT-integrated ontologies and IoT-enhanced decision models, which enables the capabilities of IoT to make business processes and the decision making involved aware of the dynamic context.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121856222","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}
Online news comment sections face a surge in uncivil, abusive and even straightforwardly hateful and threatening posts. In Germany especially the refugee crisis beginning in 2015 has sparked a lot of controversial and even unacceptable user comments. Overwhelmed by the amount of content and facing the risk of fines and a churn of readers as well as advertisers, many platforms shut down their comment sections as a last resort. To reduce their moderation effort, academics started applying machine learning to classify comments automatically. However, these efforts so far have been mostly focused on English texts. To provide similar systems for German, this paper implements and evaluates six different machine learning classifiers and five different strategies to convert textual comments into machine-compatible vectors. Contrary to common belief in the domain, comments often evade binary classification: Often comments are not only hateful, or insulting or threatening but fall within multiple of these categories. Hence, we will go beyond traditional multi-class classification models and prototypically evaluate the use of multi-label techniques. The first evaluations indicate that systems for abusive language detection are transferable to the German language and that supporting multi-labels might not only help to improve the detection of rare abusiveness types but also lead to a more realistic representation of actual online commentary.
{"title":"Abusiveness is Non-Binary: Five Shades of Gray in German Online News-Comments","authors":"Marco Niemann","doi":"10.1109/CBI.2019.00009","DOIUrl":"https://doi.org/10.1109/CBI.2019.00009","url":null,"abstract":"Online news comment sections face a surge in uncivil, abusive and even straightforwardly hateful and threatening posts. In Germany especially the refugee crisis beginning in 2015 has sparked a lot of controversial and even unacceptable user comments. Overwhelmed by the amount of content and facing the risk of fines and a churn of readers as well as advertisers, many platforms shut down their comment sections as a last resort. To reduce their moderation effort, academics started applying machine learning to classify comments automatically. However, these efforts so far have been mostly focused on English texts. To provide similar systems for German, this paper implements and evaluates six different machine learning classifiers and five different strategies to convert textual comments into machine-compatible vectors. Contrary to common belief in the domain, comments often evade binary classification: Often comments are not only hateful, or insulting or threatening but fall within multiple of these categories. Hence, we will go beyond traditional multi-class classification models and prototypically evaluate the use of multi-label techniques. The first evaluations indicate that systems for abusive language detection are transferable to the German language and that supporting multi-labels might not only help to improve the detection of rare abusiveness types but also lead to a more realistic representation of actual online commentary.","PeriodicalId":193238,"journal":{"name":"2019 IEEE 21st Conference on Business Informatics (CBI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121867450","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：