Pub Date : 2014-09-01DOI: 10.1109/ICTS.2014.7010567
Mutia Nurulhusna Hussain, M. F. Abdul Khir, M. H. Hisham, Zalhan Md Yusof
Detection of adulteration in food is one of the most important issues in food industry today. In this study, the feasibility of classifying canola oil samples from the one adulterated with palm oil using NIR spectroscopy in combination with multivariate analysis is investigated. An experiment to obtain the NIR spectra was conducted and analyzed using multivariate analysis. The result using open source R software has shown that adulterated oil samples could be detected with an overall correct classification rate of 100 % with minimum detection level of 3.23 %.
{"title":"Feasibility study of detecting canola oil adulteration with palm oil using NIR spectroscopy and multivariate analysis","authors":"Mutia Nurulhusna Hussain, M. F. Abdul Khir, M. H. Hisham, Zalhan Md Yusof","doi":"10.1109/ICTS.2014.7010567","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010567","url":null,"abstract":"Detection of adulteration in food is one of the most important issues in food industry today. In this study, the feasibility of classifying canola oil samples from the one adulterated with palm oil using NIR spectroscopy in combination with multivariate analysis is investigated. An experiment to obtain the NIR spectra was conducted and analyzed using multivariate analysis. The result using open source R software has shown that adulterated oil samples could be detected with an overall correct classification rate of 100 % with minimum detection level of 3.23 %.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133350878","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010601
Kevin Syahlie, Kho I Eng, Charles Lim, M. Galinium
In this modern era of computer technology, virtualization emerges as a solution to maximize the resource of computing. Education therefore also implements virtualization to help day-to-day activities, and they need to know which hypervisor may suit their activities. This paper describes the assessment using OpenBRR, including the result of the assessment, how do the OpenBRR methodology works and also how the data gathered by using qualitative interviews. The assessment covers several categories, taken from OpenBRR which related to the hypervisor operations in the educational institution, they are functionality, usability, performance, documentation, scalability and support. This assessment uses two open-source hypervisor that already implemented in the market, namely Proxmox Virtual Environment and Citrix Xen Server 6. As a result of assessment, both hypervisors shows good quality, can be seen from the BRR score calculated from normalizing the data and calculate into BRR score, a hypervisor may not good in all categories, but there are some categories that better inProxmox, and other categories are better in Citrix Xen Server.
在这个计算机技术的现代时代，虚拟化作为一种最大化计算资源的解决方案而出现。因此，教育部门也实现虚拟化来帮助日常活动，他们需要知道哪个管理程序适合他们的活动。本文描述了使用OpenBRR的评估，包括评估的结果，OpenBRR方法是如何工作的，以及如何通过使用定性访谈收集数据。评估涵盖了几个类别，它们来自OpenBRR，与教育机构的管理程序操作相关，它们是功能、可用性、性能、文档、可伸缩性和支持。该评估使用了两个已经在市场上实现的开源管理程序，即Proxmox Virtual Environment和Citrix Xen Server 6。经过评估，两个hypervisor都显示出良好的质量，可以从将数据归一化计算得到的BRR分数中看出，一个hypervisor可能不是在所有类别中都很好，但在proxmox中有一些类别更好，而在Citrix Xen Server中有一些类别更好。
{"title":"Hypervisors assessment in education industry: Using OpenBRR methodology","authors":"Kevin Syahlie, Kho I Eng, Charles Lim, M. Galinium","doi":"10.1109/ICTS.2014.7010601","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010601","url":null,"abstract":"In this modern era of computer technology, virtualization emerges as a solution to maximize the resource of computing. Education therefore also implements virtualization to help day-to-day activities, and they need to know which hypervisor may suit their activities. This paper describes the assessment using OpenBRR, including the result of the assessment, how do the OpenBRR methodology works and also how the data gathered by using qualitative interviews. The assessment covers several categories, taken from OpenBRR which related to the hypervisor operations in the educational institution, they are functionality, usability, performance, documentation, scalability and support. This assessment uses two open-source hypervisor that already implemented in the market, namely Proxmox Virtual Environment and Citrix Xen Server 6. As a result of assessment, both hypervisors shows good quality, can be seen from the BRR score calculated from normalizing the data and calculate into BRR score, a hypervisor may not good in all categories, but there are some categories that better inProxmox, and other categories are better in Citrix Xen Server.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159193","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010564
E. Ratnasari, M. Mentari, Ratih Kartika Dewi, R. V. Hari Ginardi
About 15% of sugarcane leaf is defective because of diseases, it reduces the quantity and quality of sugarcane production significantly. Early detection and estimation of plant disease is a way to control these diseases and minimize the severe infection. This paper proposes a model to identify the severity of certain spot disease which appear on leaves based on segmented spot. The segmented spot is obtained by thresholding a* component of L*a*b* color space. Diseases spots are extracted with maximum standard deviation of segmented spot that use for detection the type of disease using classification techniques. The classifier is a Support Vector Machine (SVM) which uses L*a*b* color space for its color features and Gray Level Co-Occurrence Matrix (GLCM) as its texture features. This proposed model capable to determine the types of spot diseases with accuracy of 80% and 5.73 error severity estimation average.
{"title":"Sugarcane leaf disease detection and severity estimation based on segmented spots image","authors":"E. Ratnasari, M. Mentari, Ratih Kartika Dewi, R. V. Hari Ginardi","doi":"10.1109/ICTS.2014.7010564","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010564","url":null,"abstract":"About 15% of sugarcane leaf is defective because of diseases, it reduces the quantity and quality of sugarcane production significantly. Early detection and estimation of plant disease is a way to control these diseases and minimize the severe infection. This paper proposes a model to identify the severity of certain spot disease which appear on leaves based on segmented spot. The segmented spot is obtained by thresholding a* component of L*a*b* color space. Diseases spots are extracted with maximum standard deviation of segmented spot that use for detection the type of disease using classification techniques. The classifier is a Support Vector Machine (SVM) which uses L*a*b* color space for its color features and Gray Level Co-Occurrence Matrix (GLCM) as its texture features. This proposed model capable to determine the types of spot diseases with accuracy of 80% and 5.73 error severity estimation average.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114595963","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010470
Spits Warnars
Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as a new data mining technique, combines two data mining techniques i.e. Attribute Oriented Induction (AOI) and Emerging Patterns (EP). The AOI-HEP application is implemented as a hybrid between AOI characteristic rule mining and HEP algorithms. AOI-HEP combines the powerful features of AOI and EP by using concept hierarchy in AOI to generalize into high level data and applying growth rates in EP and produces powerful discrimination for high level data. AOI-HEP can be implemented to discriminate datasets such as finding bad and good customers for banking loan systems or credit card applicants and etc. Meanwhile, AOI-HEP can be implemented to mine similar patterns such as similar customer loan patterns or similar customer credit card rating and etc. Since AOI-HEP is a new data mining technique, then future research can be explored such as inverse discovery learning, learning more than two datasets, learning other knowledge rules and etc. AOI-HEP future research will give research idea for data mining researchers community particularly for bachelor and master degree students. Indeed, AOI-HEP as new comer data mining technique will be completed in discovery process, having rich interesting patterns and become interested mining technique.
{"title":"Attribute Oriented Induction High Level Emerging Pattern (AOI-HEP) future research","authors":"Spits Warnars","doi":"10.1109/ICTS.2014.7010470","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010470","url":null,"abstract":"Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as a new data mining technique, combines two data mining techniques i.e. Attribute Oriented Induction (AOI) and Emerging Patterns (EP). The AOI-HEP application is implemented as a hybrid between AOI characteristic rule mining and HEP algorithms. AOI-HEP combines the powerful features of AOI and EP by using concept hierarchy in AOI to generalize into high level data and applying growth rates in EP and produces powerful discrimination for high level data. AOI-HEP can be implemented to discriminate datasets such as finding bad and good customers for banking loan systems or credit card applicants and etc. Meanwhile, AOI-HEP can be implemented to mine similar patterns such as similar customer loan patterns or similar customer credit card rating and etc. Since AOI-HEP is a new data mining technique, then future research can be explored such as inverse discovery learning, learning more than two datasets, learning other knowledge rules and etc. AOI-HEP future research will give research idea for data mining researchers community particularly for bachelor and master degree students. Indeed, AOI-HEP as new comer data mining technique will be completed in discovery process, having rich interesting patterns and become interested mining technique.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131100537","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010595
Omar Najah, K. Seman, K. Abdulrahim
Packet contention in photonic packet switches is a key issue in network performance. Without using a proper contention scheme, switches will get congested earlier. Although Optical Code Division Multiplexing, Wavelength Division Multiplexing (OCDM/WDM) applies a code and wavelength as a path in the node, the capacity granularity of OCDM/WDM may become too large to switch the packets among input and output. A possible solution for this issue is to employ optical buffering techniques that incorporate fiber delay lines (FDLs) in OCDM/WDM architecture. The proposed scheme takes the advantage of shared buffering, optical coding and wavelength conversion to enhance the switch performance. The performance evaluation of the hybrid optical switch architecture is validated through extensive simulation. This paper analyzes the performance of proposed system based on fixed sized packet (synchronized packet). It is shown that with this algorithm, the hybrid optical-buffered switch can achieve a throughput of ~ 0.99 and a loss rate of 1.9*10-3 respectively, at a heavy load of 0.9.
{"title":"The performance of OCDM/WDM with buffering based on shared fiber delay line","authors":"Omar Najah, K. Seman, K. Abdulrahim","doi":"10.1109/ICTS.2014.7010595","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010595","url":null,"abstract":"Packet contention in photonic packet switches is a key issue in network performance. Without using a proper contention scheme, switches will get congested earlier. Although Optical Code Division Multiplexing, Wavelength Division Multiplexing (OCDM/WDM) applies a code and wavelength as a path in the node, the capacity granularity of OCDM/WDM may become too large to switch the packets among input and output. A possible solution for this issue is to employ optical buffering techniques that incorporate fiber delay lines (FDLs) in OCDM/WDM architecture. The proposed scheme takes the advantage of shared buffering, optical coding and wavelength conversion to enhance the switch performance. The performance evaluation of the hybrid optical switch architecture is validated through extensive simulation. This paper analyzes the performance of proposed system based on fixed sized packet (synchronized packet). It is shown that with this algorithm, the hybrid optical-buffered switch can achieve a throughput of ~ 0.99 and a loss rate of 1.9*10-3 respectively, at a heavy load of 0.9.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"3 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120821239","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010554
K. Nisa, Y. Cariens
The growth process of a flowering plant can be manipulated by treating on its genes and controlling its exogenous factors. This manipulation is aimed for specific reason, for example: to accelerate the flowering process, to lengthen juvenility, or to regenerate certain parts of the flower. Biology molecular researcher used to do this manipulation in a costly research and it usually takes a long period to watch its impact on a plant. A system is developed to simulate vegetative and generative growth process of a plant when its exogenous factors and genes are controlled. The vegetative system uses rules generated using C4.5 algorithm and gives 100% accuracy when SN DNE and HR are both active. When one of SN DNE and HR is nonactive, the rules are no longer accurate and generated manually. The generative system uses rules based inference. It predicts the effect of controlling the level of genes and exogenous factors. It can be estimated whether the plant would produce flowers, become sterile, stay juvenile or even die. The system is also able to predict the shape of the flower, whether it would be a perfect flower or inactive in some part of the flower.
{"title":"Simulation of plant growth manipulation using rule based inference and C4.5 algorithm","authors":"K. Nisa, Y. Cariens","doi":"10.1109/ICTS.2014.7010554","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010554","url":null,"abstract":"The growth process of a flowering plant can be manipulated by treating on its genes and controlling its exogenous factors. This manipulation is aimed for specific reason, for example: to accelerate the flowering process, to lengthen juvenility, or to regenerate certain parts of the flower. Biology molecular researcher used to do this manipulation in a costly research and it usually takes a long period to watch its impact on a plant. A system is developed to simulate vegetative and generative growth process of a plant when its exogenous factors and genes are controlled. The vegetative system uses rules generated using C4.5 algorithm and gives 100% accuracy when SN DNE and HR are both active. When one of SN DNE and HR is nonactive, the rules are no longer accurate and generated manually. The generative system uses rules based inference. It predicts the effect of controlling the level of genes and exogenous factors. It can be estimated whether the plant would produce flowers, become sterile, stay juvenile or even die. The system is also able to predict the shape of the flower, whether it would be a perfect flower or inactive in some part of the flower.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"1961 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129469492","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010565
Ratih Kartika Dewi, R. V. Hari Ginardi
This research propose an image pattern classification to identify rust disease in sugarcane leaf with a combination of texture and color feature extraction. The purpose of this research is to find appropriate features that can identify sugarcane rust disease. Firstly, normal and diseased images are collected and pre-processed. Then, features of shape, color and texture are extracted from these images. After that, these images are classified by support vector machine classifier. A combination of several features are used to evaluate the appropriate features to find distinctive features for identification of rust disease. When a single feature is used, shape feature has the lowest accuracy of 51% and texture feature has the highest accuracy of 96.5%. A combination of texture and color feature extraction results a highest classification accuracy of 97.5%. A combination of texture and color feature extraction with polynomial kernel results in 98.5 % classification accuracy.
{"title":"Feature extraction for identification of sugarcane rust disease","authors":"Ratih Kartika Dewi, R. V. Hari Ginardi","doi":"10.1109/ICTS.2014.7010565","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010565","url":null,"abstract":"This research propose an image pattern classification to identify rust disease in sugarcane leaf with a combination of texture and color feature extraction. The purpose of this research is to find appropriate features that can identify sugarcane rust disease. Firstly, normal and diseased images are collected and pre-processed. Then, features of shape, color and texture are extracted from these images. After that, these images are classified by support vector machine classifier. A combination of several features are used to evaluate the appropriate features to find distinctive features for identification of rust disease. When a single feature is used, shape feature has the lowest accuracy of 51% and texture feature has the highest accuracy of 96.5%. A combination of texture and color feature extraction results a highest classification accuracy of 97.5%. A combination of texture and color feature extraction with polynomial kernel results in 98.5 % classification accuracy.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134645233","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010553
M. Rivai, Eddy Lybrech Talakua
Vapor identification system having high sensitive and discriminative capabilities is much needed in various applications such as in monitoring of environmental condition, detecting of hazardous substances, and producing of flavored foods or drinks and others. Nowadays, electronic nose technology which consists of gas sensor array and neural network pattern recognition could not recognize well for the low concentration vapors. In this research, the implementation of a preconcentrator was used to increase the vapor concentration allowing the electronic nose system to gain its high sensitivity and selectivity. The experimental result showed that the electronic nose system equipped with the preconcentrator could distinguish ethanol, benzene and acetone vapors in low concentrations successfully.
{"title":"The implementation of preconcentrator in electronic nose system to identify low concentration of vapors using neural network method","authors":"M. Rivai, Eddy Lybrech Talakua","doi":"10.1109/ICTS.2014.7010553","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010553","url":null,"abstract":"Vapor identification system having high sensitive and discriminative capabilities is much needed in various applications such as in monitoring of environmental condition, detecting of hazardous substances, and producing of flavored foods or drinks and others. Nowadays, electronic nose technology which consists of gas sensor array and neural network pattern recognition could not recognize well for the low concentration vapors. In this research, the implementation of a preconcentrator was used to increase the vapor concentration allowing the electronic nose system to gain its high sensitivity and selectivity. The experimental result showed that the electronic nose system equipped with the preconcentrator could distinguish ethanol, benzene and acetone vapors in low concentrations successfully.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133823491","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 : 2014-09-01DOI: 10.1109/ICTS.2014.7010587
Chris Tjandra, C. Lim, I. E. Kho, Meis Musida
With the new era of cloud service, as more and more people use their mobile device to perform their daily activities anywhere, anytime, the use of cloud service for personal storage has become inevitable. PT. XL Axiata Tbk. is one of the first cloud service provider that provides retail cloud service, i.e. XCloud Free 2GB (XF2GB). The company has been putting several strategies to promote XF2GB service to attract its customers. The purpose of this research is to understand perception or knowledge from consumers, and find the best strategies in promotion XF2GB to increase the usage of XCloud service. The survey conducted on the students studying in Swiss German University (SGU) on the personal cloud storage use shown to be low. Several promotional strategies have been recommended to improve the XCloud service awareness and to attract XL consumers to use more XF2GB service.
{"title":"Analysis model of promotion strategies to increase the usage of cloud retail","authors":"Chris Tjandra, C. Lim, I. E. Kho, Meis Musida","doi":"10.1109/ICTS.2014.7010587","DOIUrl":"https://doi.org/10.1109/ICTS.2014.7010587","url":null,"abstract":"With the new era of cloud service, as more and more people use their mobile device to perform their daily activities anywhere, anytime, the use of cloud service for personal storage has become inevitable. PT. XL Axiata Tbk. is one of the first cloud service provider that provides retail cloud service, i.e. XCloud Free 2GB (XF2GB). The company has been putting several strategies to promote XF2GB service to attract its customers. The purpose of this research is to understand perception or knowledge from consumers, and find the best strategies in promotion XF2GB to increase the usage of XCloud service. The survey conducted on the students studying in Swiss German University (SGU) on the personal cloud storage use shown to be low. Several promotional strategies have been recommended to improve the XCloud service awareness and to attract XL consumers to use more XF2GB service.","PeriodicalId":325095,"journal":{"name":"Proceedings of International Conference on Information, Communication Technology and System (ICTS) 2014","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126723649","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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