At present, in the thermal power stations, it always cost a lost to operate the boiler combustion system and the flue gas denitrification system. Under the premise in standard emission, it can improve the power units' economic performance by optimizing the comprehensive operating cost of the boiler combustion system and denitrification system. This paper has used LSSVM to build the model of the boiler combustion system and denitrification system. Furthermore, the genetic algorithm is applied to optimize the integrated cost on-line. For different working conditions, under the constraints of safety and environment protection, the minimal integrated cost is the optimizing target to prevent the SCR cost from reducing. At last, the result shows that the optimized cost has reduced a lot as well as the SCR cost. Otherwise, the NOx emissions in the SCR output has been lowered and met the policy requirement, and that the boiler efficiency is improved significantly. In conclusion, this paper has successfully built a integrated system based on the boiler combustion and denitrification, which has good performance in environment friendly and economic benefit.
{"title":"The Integrated System Optimization Based on the Boiler Combustion and Denitration with Denitration Operating Cost Consideration","authors":"Guo Kaixuan, Yang Jun, W. Hongwei","doi":"10.1109/ICEBE.2017.49","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.49","url":null,"abstract":"At present, in the thermal power stations, it always cost a lost to operate the boiler combustion system and the flue gas denitrification system. Under the premise in standard emission, it can improve the power units' economic performance by optimizing the comprehensive operating cost of the boiler combustion system and denitrification system. This paper has used LSSVM to build the model of the boiler combustion system and denitrification system. Furthermore, the genetic algorithm is applied to optimize the integrated cost on-line. For different working conditions, under the constraints of safety and environment protection, the minimal integrated cost is the optimizing target to prevent the SCR cost from reducing. At last, the result shows that the optimized cost has reduced a lot as well as the SCR cost. Otherwise, the NOx emissions in the SCR output has been lowered and met the policy requirement, and that the boiler efficiency is improved significantly. In conclusion, this paper has successfully built a integrated system based on the boiler combustion and denitrification, which has good performance in environment friendly and economic benefit.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129507170","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 adoption of cloud computing has increased significantly, but this has given rise to the problem of efficient energy usage. The efficient use of energy by data centers and the use of virtual machines can help to minimize cost deadlines, resources, and utilization and execution times. There is a consequent need for different approaches that can reduce energy consumption whilst still achieving the multiple objectives of cloud computing. In this study, we examine a number of different approaches that have been discussed in the recent literature w.r.t. energy-efficient cloud workflow management, and we compare these approaches for energy-efficient usage of data centers and virtual machines. The results show that virtual machine scheduling and virtual machine allocation approaches are the most commonly used approaches that achieve an optimal energy consumption.
{"title":"An Analysis of Energy-Efficient Approaches Used for Virtual Machines and Data Centres","authors":"S. Manzoor, Mirfa Manzoor, Walayat Hussain","doi":"10.1109/ICEBE.2017.23","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.23","url":null,"abstract":"The adoption of cloud computing has increased significantly, but this has given rise to the problem of efficient energy usage. The efficient use of energy by data centers and the use of virtual machines can help to minimize cost deadlines, resources, and utilization and execution times. There is a consequent need for different approaches that can reduce energy consumption whilst still achieving the multiple objectives of cloud computing. In this study, we examine a number of different approaches that have been discussed in the recent literature w.r.t. energy-efficient cloud workflow management, and we compare these approaches for energy-efficient usage of data centers and virtual machines. The results show that virtual machine scheduling and virtual machine allocation approaches are the most commonly used approaches that achieve an optimal energy consumption.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122847777","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}
Based on the organizational support theory, this paper studied the effect and mechanism of corporate engagement marketing strategy on customer perceived support and customer willingness to engagement. The cross level analysis methodology was adopted for analyzing 43 domestic video website of 215 employees and 1075 customers. The results showed that corporate engagement marketing strategy had a significant impact on customer perceived support, willingness to customer engagement and customer perceived support played a fully mediated role among them.
{"title":"A Study on the Influence of Engagement Marketing Strategy on Customer Perceived Support and Willingness to Customer Engagement","authors":"Qian Li, Xiu-cun Wang","doi":"10.1109/ICEBE.2017.33","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.33","url":null,"abstract":"Based on the organizational support theory, this paper studied the effect and mechanism of corporate engagement marketing strategy on customer perceived support and customer willingness to engagement. The cross level analysis methodology was adopted for analyzing 43 domestic video website of 215 employees and 1075 customers. The results showed that corporate engagement marketing strategy had a significant impact on customer perceived support, willingness to customer engagement and customer perceived support played a fully mediated role among them.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127027591","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}
Guangyi Xiao, Even Chow, Hao Chen, Jiqian Mo, J. Guo, Zhiguo Gong
Question classification is an essential part of Question Answering system(QA). This paper introduces our research work on automatic question classification that depends on the sample set including questions from legal forum. We propose a taxonomy for law question, and divide questions into three main parts: civil, criminal and administrative according to Chinese legal system. We have experimented with four machine learning algorithms: Nearest Neighbors (NN), Naïve Bayes (NB), Logistic Regression (LR) and Support Vector Machines (SVM) using two kinds of features: TF-IDF and word2vec embeddings. Further, we used fastText and adjusted the parameters to get the better results. The research shows high accuracy in Chinese question classification in law domain. Moreover, to the best of our knowledge, our work is the first attempt in this promising domain.
{"title":"Chinese Questions Classification in the Law Domain","authors":"Guangyi Xiao, Even Chow, Hao Chen, Jiqian Mo, J. Guo, Zhiguo Gong","doi":"10.1109/ICEBE.2017.41","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.41","url":null,"abstract":"Question classification is an essential part of Question Answering system(QA). This paper introduces our research work on automatic question classification that depends on the sample set including questions from legal forum. We propose a taxonomy for law question, and divide questions into three main parts: civil, criminal and administrative according to Chinese legal system. We have experimented with four machine learning algorithms: Nearest Neighbors (NN), Naïve Bayes (NB), Logistic Regression (LR) and Support Vector Machines (SVM) using two kinds of features: TF-IDF and word2vec embeddings. Further, we used fastText and adjusted the parameters to get the better results. The research shows high accuracy in Chinese question classification in law domain. Moreover, to the best of our knowledge, our work is the first attempt in this promising domain.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114076398","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}
Moufida Aouachria, Abderrahmane Leshob, J. Gonzalez-Huerta, A. R. Ghomari, P. Hadaya
Business process integration (BPI) is a crucial technique for supporting inter-organizational business interoperability. BPI allows automation of business processes and the integration of systems across numerous organizations. The integration of organizations' process models is one of the most addressed and used approach to achieve BPI. However, this model integration is complex and requires that designers have extensive experience in particular when organizations' business processes are incompatible. This paper considers the issue of modeling cross-organization processes out of a collection of organizations' private process models. To this end, we propose six adaptation patterns to resolve incompatibilities when combining organizations' processes. Each pattern is formalized with workflow net.
{"title":"Business Process Integration: How to Achieve Interoperability through Process Patterns","authors":"Moufida Aouachria, Abderrahmane Leshob, J. Gonzalez-Huerta, A. R. Ghomari, P. Hadaya","doi":"10.1109/ICEBE.2017.26","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.26","url":null,"abstract":"Business process integration (BPI) is a crucial technique for supporting inter-organizational business interoperability. BPI allows automation of business processes and the integration of systems across numerous organizations. The integration of organizations' process models is one of the most addressed and used approach to achieve BPI. However, this model integration is complex and requires that designers have extensive experience in particular when organizations' business processes are incompatible. This paper considers the issue of modeling cross-organization processes out of a collection of organizations' private process models. To this end, we propose six adaptation patterns to resolve incompatibilities when combining organizations' processes. Each pattern is formalized with workflow net.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804492","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}
Nandor Verba, K. Chao, Anne E. James, J. Lewandowski, Xiang Fei, Chen-Fang Tsai
Increased adoption of Fog Computing concepts into Cyber Physical Systems (CPS) is a driving force for implementing Industry 4.0. The modern industrial environment focuses on providing a flexible factory floor that suits the needs of modern manufacturing through the reduction of downtimes, reconfiguration times, adoption of new technologies and the increase of its production capabilities and rates. Fog Computing through CPS aims to provide a flexible orchestration and management platform that can meet the needs of this emerging industry model. Proposals on Fog Computing platform and Software Defined Networks (SDN) for Industry allow for resource virtualization and access throughout the system enabling large composite application systems to be deployed on multiple nodes. The increase of reliability, redundancy and runtime parameters as well as the reduction of costs in such systems are of key interest to Industry and researchers as well. The development of optimization algorithms and methods is made difficult by the complexity of such systems and the lack of real-world data on fog systems resulting in algorithms that are not being designed for real world scenarios. We propose a set of use-case scenarios based on our Industrial partner that we analyze to determine the graph based parameters of the system that allows us to scale and generate a more realistic testing scenario for future optimization attempts as well as determine the nature of such systems in comparison to other networks types. To show the differences between these scenarios and our real-world use-case we have selected a set of key graph characteristics based on which we analyze and compare the resulting graphs from the systems.
{"title":"Graph Analysis of Fog Computing Systems for Industry 4.0","authors":"Nandor Verba, K. Chao, Anne E. James, J. Lewandowski, Xiang Fei, Chen-Fang Tsai","doi":"10.1109/ICEBE.2017.17","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.17","url":null,"abstract":"Increased adoption of Fog Computing concepts into Cyber Physical Systems (CPS) is a driving force for implementing Industry 4.0. The modern industrial environment focuses on providing a flexible factory floor that suits the needs of modern manufacturing through the reduction of downtimes, reconfiguration times, adoption of new technologies and the increase of its production capabilities and rates. Fog Computing through CPS aims to provide a flexible orchestration and management platform that can meet the needs of this emerging industry model. Proposals on Fog Computing platform and Software Defined Networks (SDN) for Industry allow for resource virtualization and access throughout the system enabling large composite application systems to be deployed on multiple nodes. The increase of reliability, redundancy and runtime parameters as well as the reduction of costs in such systems are of key interest to Industry and researchers as well. The development of optimization algorithms and methods is made difficult by the complexity of such systems and the lack of real-world data on fog systems resulting in algorithms that are not being designed for real world scenarios. We propose a set of use-case scenarios based on our Industrial partner that we analyze to determine the graph based parameters of the system that allows us to scale and generate a more realistic testing scenario for future optimization attempts as well as determine the nature of such systems in comparison to other networks types. To show the differences between these scenarios and our real-world use-case we have selected a set of key graph characteristics based on which we analyze and compare the resulting graphs from the systems.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131229740","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}
B. Xiong, Zhiyong Huang, Shuangmei Peng, Xiang Fei, N. Shah
Videos captured in car often suffer from duston the wind screen glass. The dust particles on wind screendecrease the video quality and make them blur. Removingdust and restoring high quality dust-free video is a challengingtask in the field of video stream processing. In this paper, we propose an improved iterative optimization pipeline toremove dust from the videos. Our method employs boundaryconstraint to keep transmission map in a reasonable rangeand use spatial constraint on the transmission map to avoidintroduction of significant halo artifacts into the resultantvideo. With optimized transmission map as an initial condition, our method can separate dust layer and background layer frominput video frames and keeps the background frames beingcolor faithful with fine details. Test results demonstrate thatour proposed method can recover dust-free videos from thedust contaminated input videos and keep the resultant video color faithful.
{"title":"Dust Removal with Boundary and Spatial Constraint for Videos Captured in Car","authors":"B. Xiong, Zhiyong Huang, Shuangmei Peng, Xiang Fei, N. Shah","doi":"10.1109/ICEBE.2017.57","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.57","url":null,"abstract":"Videos captured in car often suffer from duston the wind screen glass. The dust particles on wind screendecrease the video quality and make them blur. Removingdust and restoring high quality dust-free video is a challengingtask in the field of video stream processing. In this paper, we propose an improved iterative optimization pipeline toremove dust from the videos. Our method employs boundaryconstraint to keep transmission map in a reasonable rangeand use spatial constraint on the transmission map to avoidintroduction of significant halo artifacts into the resultantvideo. With optimized transmission map as an initial condition, our method can separate dust layer and background layer frominput video frames and keeps the background frames beingcolor faithful with fine details. Test results demonstrate thatour proposed method can recover dust-free videos from thedust contaminated input videos and keep the resultant video color faithful.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114799814","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}
Hanchao Li, David Yee Fan Zuo, Xiang Fei, K. Chao, Ming Yang, Chaobo He
There are a number of existing music data storage formats and a number of existing music manipulating formats, each of which possess certain features and limitations. Thus, for the new coding scheme introduced, Music Definition Language (MDL) and Music Manipulation Language (MML), we analyse how well it can act as storage media. We carried out experiments on whether the new coding scheme can make the music easier to represent by comparing the sound waveform, the storage data size and other relevant features. The result shows that the file size, of 14.3kB (size on disk: 15.0kB) for the first 18 seconds, is larger than a MIDI file but relatively small compared to audio file such as an MP3 file. More importantly, the soundwave that MDL and MML generated is better than MIDI files, as it is closer to audio files and able to do more variations. Therefore, the overall performance of MDL and MML lies between symbolic-coded files and audio files.
{"title":"Music Definition Language & Music Manipulation Language: A Coding Scheme for Music Representation and Storage","authors":"Hanchao Li, David Yee Fan Zuo, Xiang Fei, K. Chao, Ming Yang, Chaobo He","doi":"10.1109/ICEBE.2017.44","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.44","url":null,"abstract":"There are a number of existing music data storage formats and a number of existing music manipulating formats, each of which possess certain features and limitations. Thus, for the new coding scheme introduced, Music Definition Language (MDL) and Music Manipulation Language (MML), we analyse how well it can act as storage media. We carried out experiments on whether the new coding scheme can make the music easier to represent by comparing the sound waveform, the storage data size and other relevant features. The result shows that the file size, of 14.3kB (size on disk: 15.0kB) for the first 18 seconds, is larger than a MIDI file but relatively small compared to audio file such as an MP3 file. More importantly, the soundwave that MDL and MML generated is better than MIDI files, as it is closer to audio files and able to do more variations. Therefore, the overall performance of MDL and MML lies between symbolic-coded files and audio files.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130841083","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}
Qianqiao Liang, Xiaolin Zheng, Menghan Wang, Haodong Chen, Pin Lu
With the rapid development of e-commerce, recommender systems have been widely studied. Many recommendation algorithms utilize ratings and reviews information. However, as the number of users and items grows, these algorithms face the problems of sparsity and scalability. Those problems make it hard to extract useful information from a highly sparse rating matrix and to apply a trained model to larger datasets. In this paper, we aim at solving the sparsity and scalability problems using rating and review information. Three possible solutions for sparsity and scalability problems are concluded and a novel recommendation model called TCR which combines those three ideas are proposed. Experiments on real-world datasets show that our proposed method has better performance on top-N recommendation and has better scalability compared to the state-of-the-art models.
{"title":"Optimize Recommendation System with Topic Modeling and Clustering","authors":"Qianqiao Liang, Xiaolin Zheng, Menghan Wang, Haodong Chen, Pin Lu","doi":"10.1109/ICEBE.2017.13","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.13","url":null,"abstract":"With the rapid development of e-commerce, recommender systems have been widely studied. Many recommendation algorithms utilize ratings and reviews information. However, as the number of users and items grows, these algorithms face the problems of sparsity and scalability. Those problems make it hard to extract useful information from a highly sparse rating matrix and to apply a trained model to larger datasets. In this paper, we aim at solving the sparsity and scalability problems using rating and review information. Three possible solutions for sparsity and scalability problems are concluded and a novel recommendation model called TCR which combines those three ideas are proposed. Experiments on real-world datasets show that our proposed method has better performance on top-N recommendation and has better scalability compared to the state-of-the-art models.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129182488","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}
For online business markets with a large customer base, the use of market-platforms is leading to a rapid generation of a huge amount of data. Such businesses face challenges to satisfy their users. A quantitative research approach has been used to examine big data in online markets, but there is also a need for qualitative research in this area, so as to understand the relationship between big data, online markets. The present research presents an analysis of the various case study approaches that are employed by researchers in this area. We also analyze trends in case study techniques in this area. The research problem is taken on as a research case for the present study. The results of the study should contribute the implementation of big-data in online markets research.
{"title":"A Review of Case Study Approaches and Techniques in Studies on Big Data in Online Markets","authors":"Mirfa Manzoor","doi":"10.1109/ICEBE.2017.54","DOIUrl":"https://doi.org/10.1109/ICEBE.2017.54","url":null,"abstract":"For online business markets with a large customer base, the use of market-platforms is leading to a rapid generation of a huge amount of data. Such businesses face challenges to satisfy their users. A quantitative research approach has been used to examine big data in online markets, but there is also a need for qualitative research in this area, so as to understand the relationship between big data, online markets. The present research presents an analysis of the various case study approaches that are employed by researchers in this area. We also analyze trends in case study techniques in this area. The research problem is taken on as a research case for the present study. The results of the study should contribute the implementation of big-data in online markets research.","PeriodicalId":347774,"journal":{"name":"2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122153580","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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