Pub Date : 2019-09-01DOI: 10.1109/IDAACS.2019.8924332
J. M. Montoya, J. Chilo
This paper presents a measurement system to greenhouse gases (GHG) monitoring. GHGs are formed by the emission of Carbon Dioxide (CO2) and Methane (CH4) from vehicles and near located landfills in Juliaca city in Perú. A wireless system is developed using MOS sensors (MQ2, MQ4, TGS2611 and MQ-135), Arduino-nano, XBee wireless communications modules and the interface to the computer is written in Python. The system was tested in real field measurements and the results show gas concentration difference in different points of the city. We could observe that the CO2 content in places with a large number of vehicles is high and places with organic waste, like fresch product market, the CH4 content is also high.
{"title":"RealTime Wireless Monitoring System of CO2 and CH4 in Juliaca-Perú","authors":"J. M. Montoya, J. Chilo","doi":"10.1109/IDAACS.2019.8924332","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924332","url":null,"abstract":"This paper presents a measurement system to greenhouse gases (GHG) monitoring. GHGs are formed by the emission of Carbon Dioxide (CO2) and Methane (CH4) from vehicles and near located landfills in Juliaca city in Perú. A wireless system is developed using MOS sensors (MQ2, MQ4, TGS2611 and MQ-135), Arduino-nano, XBee wireless communications modules and the interface to the computer is written in Python. The system was tested in real field measurements and the results show gas concentration difference in different points of the city. We could observe that the CO2 content in places with a large number of vehicles is high and places with organic waste, like fresch product market, the CH4 content is also high.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114325860","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924234
Z. Ye, Yiheng Sun, Shuang Sun, Sikai Zhan, Han Yu, Quanfeng Yao
As one of the most important parts of network security, more significance is attached to intrusion detection system (IDS). Numerous techniques including support vector machine (SVM) have been applied to the intrusion detection. However, many methods are utilized to improve the original SVM whose performance is markedly depended on its kernel parameters. Evolutionary algorithms such as genetic algorithm (GA) and particle swarm algorithm (PSO) are also employed to search better kernel parameters while the traditional optimization methods are vulnerable to fall into local minima with slow speed of convergence. In order to improve the precision of SVM in intrusion detection, the support vector machine based on grasshopper optimization algorithm (GOA-SVM) is proposed in the paper. To verify the practicality of the proposed method, several contrast experiments have been carried out using tool of Matlab. The experimental results finally demonstrates the superior performance of the proposed method on intrusion detection.
{"title":"Research on Network Intrusion Detection Based on Support Vector Machine Optimized with Grasshopper Optimization Algorithm","authors":"Z. Ye, Yiheng Sun, Shuang Sun, Sikai Zhan, Han Yu, Quanfeng Yao","doi":"10.1109/IDAACS.2019.8924234","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924234","url":null,"abstract":"As one of the most important parts of network security, more significance is attached to intrusion detection system (IDS). Numerous techniques including support vector machine (SVM) have been applied to the intrusion detection. However, many methods are utilized to improve the original SVM whose performance is markedly depended on its kernel parameters. Evolutionary algorithms such as genetic algorithm (GA) and particle swarm algorithm (PSO) are also employed to search better kernel parameters while the traditional optimization methods are vulnerable to fall into local minima with slow speed of convergence. In order to improve the precision of SVM in intrusion detection, the support vector machine based on grasshopper optimization algorithm (GOA-SVM) is proposed in the paper. To verify the practicality of the proposed method, several contrast experiments have been carried out using tool of Matlab. The experimental results finally demonstrates the superior performance of the proposed method on intrusion detection.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114539410","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924395
M. Karpinski, S. Rajba, S. Zawislak, K. Warwas, M. Kasianchuk, S. Ivasiev, I. Yakymenko
A method for decimal number recovery from its residues based on the product module addition is presented in this paper. This makes it possible to avoid a complex operation of finding a modular multiplicative inverse and replace it with the addition operation that increases the speed of the computing system. The scheme of the developed method is given in the article. Analytical and graphical comparison of the time complexities of the proposed and known approaches shows that the use of the method of adding the product modules allows reducing the time complexity of decimal number recovery from its residues in comparison with the classical ones.
{"title":"A Method for Decimal Number Recovery from its Residues Based on the Addition of the Product Modules","authors":"M. Karpinski, S. Rajba, S. Zawislak, K. Warwas, M. Kasianchuk, S. Ivasiev, I. Yakymenko","doi":"10.1109/IDAACS.2019.8924395","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924395","url":null,"abstract":"A method for decimal number recovery from its residues based on the product module addition is presented in this paper. This makes it possible to avoid a complex operation of finding a modular multiplicative inverse and replace it with the addition operation that increases the speed of the computing system. The scheme of the developed method is given in the article. Analytical and graphical comparison of the time complexities of the proposed and known approaches shows that the use of the method of adding the product modules allows reducing the time complexity of decimal number recovery from its residues in comparison with the classical ones.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128105775","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924431
Benjamin Williams, R. Hiromoto, Albert H Carlson
We proposes the design of a cryptographically secure pseudo random number generator (CSPRNG) that involves the permutation of the internal state of the PRNG. The design of the CSPRNG is described and Dieharder test comparisons are made against AES. The results of these tests are described and a discussion of future work concludes the paper.
{"title":"A Design for a Cryptographically Secure Pseudo Random Number Generator","authors":"Benjamin Williams, R. Hiromoto, Albert H Carlson","doi":"10.1109/IDAACS.2019.8924431","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924431","url":null,"abstract":"We proposes the design of a cryptographically secure pseudo random number generator (CSPRNG) that involves the permutation of the internal state of the PRNG. The design of the CSPRNG is described and Dieharder test comparisons are made against AES. The results of these tests are described and a discussion of future work concludes the paper.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115738243","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924253
V. Morozov, O. Kalnichenko, M. Proskurin
In this paper, the results of research into the use of two methods of proactive change management in complex IT projects are presented based on the consideration of deviations in two key parameters of projects - in time and cost. Forecast estimates of the status of projects as a result of impacts of changes in the external and internal environment of projects are modeled using neural networks of deep training. This approach allows to predict the level of changes in the results of the project activity at any time during the implementation of projects. The evaluation of the results of modeling the effects of changes on project parameters is carried out taking into account the context characteristics of projects, including resource allocations both in time and in project work, cost allocations, etc.
{"title":"Methods of Proactive Management of Complex Projects Based on Neural Networks","authors":"V. Morozov, O. Kalnichenko, M. Proskurin","doi":"10.1109/IDAACS.2019.8924253","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924253","url":null,"abstract":"In this paper, the results of research into the use of two methods of proactive change management in complex IT projects are presented based on the consideration of deviations in two key parameters of projects - in time and cost. Forecast estimates of the status of projects as a result of impacts of changes in the external and internal environment of projects are modeled using neural networks of deep training. This approach allows to predict the level of changes in the results of the project activity at any time during the implementation of projects. The evaluation of the results of modeling the effects of changes on project parameters is carried out taking into account the context characteristics of projects, including resource allocations both in time and in project work, cost allocations, etc.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131079633","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924294
Oleksandr V Lemeshko, Oleksandra Yeremenko, M. Yevdokymenko, A. Shapovalova, A. Hailan, A. Mersni
The paper is devoted to the research and development of the cyber resilience ensuring approach based on Traffic Engineering Fast ReRoute with the support of Traffic Policing features. The basis of the proposed approach is the mathematical model presented by the conditions of multipath routing, modified conditions of the flow conservation. It also takes into account traffic policing on the network edge, as well as conditions for protecting (reserving) the link, node, and network bandwidth adapted to cyber resilience requirements. The advantage of the proposed solution is problem formulation as a linear optimization. In the numerical example, the operability of the model and the adequacy of the results obtained on its basis have been demonstrated.
{"title":"Cyber Resilience Approach Based on Traffic Engineering Fast ReRoute with Policing","authors":"Oleksandr V Lemeshko, Oleksandra Yeremenko, M. Yevdokymenko, A. Shapovalova, A. Hailan, A. Mersni","doi":"10.1109/IDAACS.2019.8924294","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924294","url":null,"abstract":"The paper is devoted to the research and development of the cyber resilience ensuring approach based on Traffic Engineering Fast ReRoute with the support of Traffic Policing features. The basis of the proposed approach is the mathematical model presented by the conditions of multipath routing, modified conditions of the flow conservation. It also takes into account traffic policing on the network edge, as well as conditions for protecting (reserving) the link, node, and network bandwidth adapted to cyber resilience requirements. The advantage of the proposed solution is problem formulation as a linear optimization. In the numerical example, the operability of the model and the adequacy of the results obtained on its basis have been demonstrated.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133033452","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924457
E. Zaitseva, V. Levashenko, I. Lukyanchuk, M. Kvassay, J. Rabcan, Patrik Rusnak
The intensive development of information technologies and the need to process big information and data lead to elaboration of new technologies in the hardware design. One of the important aspects here is to increase the information capacity of gates and interconnections that is possible by application of non-binary elements. Employing non-binary (Many-Valued) cells as computing and memory units enables to pack unprecedented high-density information. In turn, use of non-binary units calls for development of new methods in logic design. These methods should be based on a non-binary logic and application of Multiple-Valued Logic in design of non-binary logical circuits and networks. In this paper, a new technique of the Programmable Logic Array design based on Many-Valued units is considered. This technique is based on the use of generalised Reed-Muller expansion of Multi-Valued Logic function representation.
{"title":"Application of Generalised Reed-Muller Expansion in Development of Programmable Logic Array","authors":"E. Zaitseva, V. Levashenko, I. Lukyanchuk, M. Kvassay, J. Rabcan, Patrik Rusnak","doi":"10.1109/IDAACS.2019.8924457","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924457","url":null,"abstract":"The intensive development of information technologies and the need to process big information and data lead to elaboration of new technologies in the hardware design. One of the important aspects here is to increase the information capacity of gates and interconnections that is possible by application of non-binary elements. Employing non-binary (Many-Valued) cells as computing and memory units enables to pack unprecedented high-density information. In turn, use of non-binary units calls for development of new methods in logic design. These methods should be based on a non-binary logic and application of Multiple-Valued Logic in design of non-binary logical circuits and networks. In this paper, a new technique of the Programmable Logic Array design based on Many-Valued units is considered. This technique is based on the use of generalised Reed-Muller expansion of Multi-Valued Logic function representation.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114521826","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924322
Haoqiu Song, Z. Ye, Chunzhi Wang, Lingyu Yan
Image classification is one of the most important tasks in image analysis and computer vision. BP neural network is a successful classifier for the task. However, with regard to the low study efficiency and the slow convergence speed in BP algorithm, some optimization algorithms have been proposed for achieving better results. Among all these methods, BP neural network improved by particle swarm optimization (PSO) and genetic algorithm (GA) may be the most successful and classical ones. Nevertheless, both GA and PSO are easy to fall into the local optimal solution, which has a great impact on the precision of classification. As a result, a novel optimization algorithm called sine cosine algorithm (SCA) is presented to improve the classification performance. The experimental results manifest that the proposed method has good performances, and the classification accuracy is better than BP neural network optimized by GA, PSO or other algorithms.
{"title":"Image Classification Based on BP Neural Network and Sine Cosine Algorithm","authors":"Haoqiu Song, Z. Ye, Chunzhi Wang, Lingyu Yan","doi":"10.1109/IDAACS.2019.8924322","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924322","url":null,"abstract":"Image classification is one of the most important tasks in image analysis and computer vision. BP neural network is a successful classifier for the task. However, with regard to the low study efficiency and the slow convergence speed in BP algorithm, some optimization algorithms have been proposed for achieving better results. Among all these methods, BP neural network improved by particle swarm optimization (PSO) and genetic algorithm (GA) may be the most successful and classical ones. Nevertheless, both GA and PSO are easy to fall into the local optimal solution, which has a great impact on the precision of classification. As a result, a novel optimization algorithm called sine cosine algorithm (SCA) is presented to improve the classification performance. The experimental results manifest that the proposed method has good performances, and the classification accuracy is better than BP neural network optimized by GA, PSO or other algorithms.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117025399","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924377
I. Draganov, R. Mironov, A. Manolova, N. Neshov
In this paper a comparative analysis is presented among 4 algorithms employing tensor representation of videos for background modelling and subtraction aiming the estimation of fire dispersal. The algorithms are HoRPCA by IALM, Tucker-ALS, CP-ALS, and t-SVD. They are applied over a database of 6 videos containing fires at different stage of spreading, recorded at different scale and angle of perspective. In part of the videos intense smoke is also present. Decomposition times, full processing times with preprocessing stage and accuracy of fire dispersal in terms of relative number of correctly detected pixels forming the flame areas to all flame pixels from the original recordings are registered. Positive results are obtained which reveal the applicability of the tested algorithms for fire dispersal estimation and with the in-depth analysis of experimental results a selection in order of preference could be made for future applications given the circumstances at which fire breaks out.
本文对采用视频张量表示进行背景建模的4种算法进行了比较分析，并对针对火灾扩散估计的4种算法进行了减法。算法有:HoRPCA by IALM、Tucker-ALS、CP-ALS和t-SVD。它们被应用于一个包含6个视频的数据库，这些视频包含了不同蔓延阶段的火灾，以不同的规模和角度记录。在部分视频中还出现了强烈的烟雾。分解时间、预处理阶段的完整处理时间以及火焰扩散的准确性(根据形成火焰区域的正确检测像素的相对数量)与原始记录的所有火焰像素进行注册。通过对实验结果的深入分析，可以根据火灾发生的情况，按优先顺序进行选择，以供未来应用。
{"title":"Fire Dispersal Estimation in Videos using Background Modelling and Subtraction by Tensor Decomposition","authors":"I. Draganov, R. Mironov, A. Manolova, N. Neshov","doi":"10.1109/IDAACS.2019.8924377","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924377","url":null,"abstract":"In this paper a comparative analysis is presented among 4 algorithms employing tensor representation of videos for background modelling and subtraction aiming the estimation of fire dispersal. The algorithms are HoRPCA by IALM, Tucker-ALS, CP-ALS, and t-SVD. They are applied over a database of 6 videos containing fires at different stage of spreading, recorded at different scale and angle of perspective. In part of the videos intense smoke is also present. Decomposition times, full processing times with preprocessing stage and accuracy of fire dispersal in terms of relative number of correctly detected pixels forming the flame areas to all flame pixels from the original recordings are registered. Positive results are obtained which reveal the applicability of the tested algorithms for fire dispersal estimation and with the in-depth analysis of experimental results a selection in order of preference could be made for future applications given the circumstances at which fire breaks out.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"23 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116375419","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 : 2019-09-01DOI: 10.1109/IDAACS.2019.8924349
D. Gaifulina, A. Fedorchenko, Igor Kotenko
The paper is devoted to issues of the network traffic analysis in conditions of uncertain network protocol specifications. We propose an approach to identify typical structures of network protocols and determine their lexical specifications based on text-inspired methods for the structural analysis of raw data. High heterogeneity, partial lexical uncertainty and use of new, proprietary or modified data transfer protocols in computer networks explain high relevance of the research topic. We present the technique of network traffic analysis and the results of experiments, that confirm the applicability of the proposed approach.
{"title":"Network Protocols Determination Based on Raw Data Analysis for Security Assesment under Uncertainty","authors":"D. Gaifulina, A. Fedorchenko, Igor Kotenko","doi":"10.1109/IDAACS.2019.8924349","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924349","url":null,"abstract":"The paper is devoted to issues of the network traffic analysis in conditions of uncertain network protocol specifications. We propose an approach to identify typical structures of network protocols and determine their lexical specifications based on text-inspired methods for the structural analysis of raw data. High heterogeneity, partial lexical uncertainty and use of new, proprietary or modified data transfer protocols in computer networks explain high relevance of the research topic. We present the technique of network traffic analysis and the results of experiments, that confirm the applicability of the proposed approach.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116398883","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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