Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050115
Qi-hai Li, Wenxiao Fang, Jing Xiao, Weiming Li, W. Chen, Haimi Qiu, J. Cui, Bin Zhou
With the decrease in the overall size and the rapid increase in the working frequencies of printed circuit boards, the reliability of solder joints, especially the high frequency signal transmission reliability has become the key factor in system reliability. In this paper, changes in RF impedance of solder joints in a temperature cycling environment was studied using time-domain reflectometry measurements. It was found that with the increase in the temperature cycle, the intermetallic compound layer gradually thickened, and even if no macro damage was found, the RF impedance increased. The transmission reliability of the high frequency signal was degraded.
{"title":"TDR measurement of a solder under temperature cycle test","authors":"Qi-hai Li, Wenxiao Fang, Jing Xiao, Weiming Li, W. Chen, Haimi Qiu, J. Cui, Bin Zhou","doi":"10.1109/ICRMS.2016.8050115","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050115","url":null,"abstract":"With the decrease in the overall size and the rapid increase in the working frequencies of printed circuit boards, the reliability of solder joints, especially the high frequency signal transmission reliability has become the key factor in system reliability. In this paper, changes in RF impedance of solder joints in a temperature cycling environment was studied using time-domain reflectometry measurements. It was found that with the increase in the temperature cycle, the intermetallic compound layer gradually thickened, and even if no macro damage was found, the RF impedance increased. The transmission reliability of the high frequency signal was degraded.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129681752","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}
Large numbers of experiments have shown that grinding chatter is one of the major forms of host fault performance in grinding processes. In view of this, more advanced monitoring techniques are required to ensure the high reliability of grinders. The empirical mode decomposition (EMD) technique has shown promise for meeting this requirement. In general, EMD has been limited to processing one-dimensional signals and is unable to deliver the information fusion function required for reliable chatter detection. In this paper, a bivariate EMD (BEMD) was assessed as a grinding condition monitoring technique. Conventional EMD and BEMD were compared by using them to process a simulated chatter signal. The BEMD technique showed a more powerful capability to process non-stationary and non-linear chatter signals. Moreover, BEMD was more effective for extracting features from multiple signals and detecting the phase information of intrinsic mode functions. The instantaneous energy, peak to peak, standard deviation and kurtosis parameters of the signal were able to be used as chatter feature vectors to describe the different vibratory states encountered during grinding. These feature vectors exhibit distinctive behaviors and could be applied as detectors of early grinding chatter.
{"title":"Bivariate empirical mode decomposition of grinding chatter signals","authors":"Jianyang Shen, Huanguo Chen, Yongyu Yi, Jianwei Wu, Yajie Li, Chunshao Huang","doi":"10.1109/ICRMS.2016.8050145","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050145","url":null,"abstract":"Large numbers of experiments have shown that grinding chatter is one of the major forms of host fault performance in grinding processes. In view of this, more advanced monitoring techniques are required to ensure the high reliability of grinders. The empirical mode decomposition (EMD) technique has shown promise for meeting this requirement. In general, EMD has been limited to processing one-dimensional signals and is unable to deliver the information fusion function required for reliable chatter detection. In this paper, a bivariate EMD (BEMD) was assessed as a grinding condition monitoring technique. Conventional EMD and BEMD were compared by using them to process a simulated chatter signal. The BEMD technique showed a more powerful capability to process non-stationary and non-linear chatter signals. Moreover, BEMD was more effective for extracting features from multiple signals and detecting the phase information of intrinsic mode functions. The instantaneous energy, peak to peak, standard deviation and kurtosis parameters of the signal were able to be used as chatter feature vectors to describe the different vibratory states encountered during grinding. These feature vectors exhibit distinctive behaviors and could be applied as detectors of early grinding chatter.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116992283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050082
C. Quan, Liang Lingqiang, Yuan Dongping, Yingkui Gu
Based on the analyses systems of fuzzy fault tree and event tree, this paper proposes a method for a reliability risk analysis to mitigate problems associated with risk modeling of fuzzy and uncertain information. Risk event occurrence probabilities were obtained with fuzzy linguistic variables instead of exact values used in fault tree analysis. Quantitative analysis was applied to the fuzzy fault tree to determine the fuzzy importance degree of each basic event, which were then ranked and divided to distinguish the influence of these basic events. Based on this analysis, a fuzzy event tree was constructed and linguistic terms used to evaluate occurrence probabilities and outcomes. Mitigation measures were put forward for risk events and the expected risk magnitudes were calculated under the mitigation strategies. This ensured the mitigation measures were intuitive and accurate. Finally, an application example was illustrated to verify that the proposed method was effective and feasible.
{"title":"A reliability risk analysis method based on the fuzzy fault tree and fuzzy event tree","authors":"C. Quan, Liang Lingqiang, Yuan Dongping, Yingkui Gu","doi":"10.1109/ICRMS.2016.8050082","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050082","url":null,"abstract":"Based on the analyses systems of fuzzy fault tree and event tree, this paper proposes a method for a reliability risk analysis to mitigate problems associated with risk modeling of fuzzy and uncertain information. Risk event occurrence probabilities were obtained with fuzzy linguistic variables instead of exact values used in fault tree analysis. Quantitative analysis was applied to the fuzzy fault tree to determine the fuzzy importance degree of each basic event, which were then ranked and divided to distinguish the influence of these basic events. Based on this analysis, a fuzzy event tree was constructed and linguistic terms used to evaluate occurrence probabilities and outcomes. Mitigation measures were put forward for risk events and the expected risk magnitudes were calculated under the mitigation strategies. This ensured the mitigation measures were intuitive and accurate. Finally, an application example was illustrated to verify that the proposed method was effective and feasible.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721737","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 preventive maintenance requirement of test equipment is determined by the reliability centered maintenance (RCM) analysis. In the first step of RCM analysis procedure, the important degree evaluations of test equipment play a significant way to identify the functionally significant item (FSI) list. To evaluate the important degree of test equipment, a systematic methodology integrating the fuzzy “decision-making and trial evaluation laboratory” (DEMATEL) method and the hierarchical fuzzy “technique for order reference by similarity to ideal solution” (TOPSIS) method is proposed. According to the designed hierarchical criteria about important degree evaluation for test equipment, the fuzzy DEMATEL method is used to determine the value of the criteria weights and hierarchical fuzzy TOPSIS method is used for rating the important degree of alternative components. After the steps of the hybrid method are listed, a case study about a certain type of test equipment is presented to illustrate its effectiveness.
{"title":"Important degree evaluation of test equipment based on fuzzy DEMATEL and fuzzy hierarchical TOPSIS","authors":"Chun-yu Zhao, Lun Ma, Lifei Huo, Yun Liu, Xuefeng Zhao","doi":"10.1109/ICRMS.2016.8050162","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050162","url":null,"abstract":"The preventive maintenance requirement of test equipment is determined by the reliability centered maintenance (RCM) analysis. In the first step of RCM analysis procedure, the important degree evaluations of test equipment play a significant way to identify the functionally significant item (FSI) list. To evaluate the important degree of test equipment, a systematic methodology integrating the fuzzy “decision-making and trial evaluation laboratory” (DEMATEL) method and the hierarchical fuzzy “technique for order reference by similarity to ideal solution” (TOPSIS) method is proposed. According to the designed hierarchical criteria about important degree evaluation for test equipment, the fuzzy DEMATEL method is used to determine the value of the criteria weights and hierarchical fuzzy TOPSIS method is used for rating the important degree of alternative components. After the steps of the hybrid method are listed, a case study about a certain type of test equipment is presented to illustrate its effectiveness.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126698674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050104
Renya He, Longli Tang, Shihai Wang, Zhengwei Yu
An unconventional software testing method, fault injection based on fault model, is enhanced to improve the software reliability testing and measurements. Dynamic fault models for injecting faults through software are investigated and reported in this paper including memory faults, CPU faults and communication fault models. Dynamic fault models can be used to simulate influences which are caused by environmental disturbances. They are suited to injecting faults in memory, CPU and bus directly while the software is running. At the same time, the methods of how to inject dynamic faults into the system are given, including the dynamic environment fault injection and the dynamic binary fault injection.
{"title":"Software dynamic fault model and injection method","authors":"Renya He, Longli Tang, Shihai Wang, Zhengwei Yu","doi":"10.1109/ICRMS.2016.8050104","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050104","url":null,"abstract":"An unconventional software testing method, fault injection based on fault model, is enhanced to improve the software reliability testing and measurements. Dynamic fault models for injecting faults through software are investigated and reported in this paper including memory faults, CPU faults and communication fault models. Dynamic fault models can be used to simulate influences which are caused by environmental disturbances. They are suited to injecting faults in memory, CPU and bus directly while the software is running. At the same time, the methods of how to inject dynamic faults into the system are given, including the dynamic environment fault injection and the dynamic binary fault injection.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127905497","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}
Two-Sample prediction is useful to develop scientific maintenance strategies, but its application is restricted due to the computation complexity. In this paper, lifetime prediction method is studied through constructing predictor and prediction limits for the minimum or, more generally, the jth smallest of a set of future observations from a Weibull population. For the sake of computation simplification, Newtonian binomial law is integrated into the modeling process, and explicit formulae for Weibull future order statistics are developed by classical Two-Sample prediction method only using current failure observations, and by Bayes Two-Sample prediction method using both previous and current failure data under Gamma prior distribution. A case study is presented, which illustrates methods to predict mud pump life. The predictor and one-sided lower prediction limits with different confidence level 0.80, 0.85, 0.90, 0.95 are given.
{"title":"Classical and Bayes methods for Two-Sample prediction of a Weibull distribution","authors":"Yongquan Sun, Yingchao Jin, Bo Liu, Quanwu Liu, Chunyu Yu, Jiahai Zhang","doi":"10.1109/ICRMS.2016.8050044","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050044","url":null,"abstract":"Two-Sample prediction is useful to develop scientific maintenance strategies, but its application is restricted due to the computation complexity. In this paper, lifetime prediction method is studied through constructing predictor and prediction limits for the minimum or, more generally, the jth smallest of a set of future observations from a Weibull population. For the sake of computation simplification, Newtonian binomial law is integrated into the modeling process, and explicit formulae for Weibull future order statistics are developed by classical Two-Sample prediction method only using current failure observations, and by Bayes Two-Sample prediction method using both previous and current failure data under Gamma prior distribution. A case study is presented, which illustrates methods to predict mud pump life. The predictor and one-sided lower prediction limits with different confidence level 0.80, 0.85, 0.90, 0.95 are given.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129557646","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}
Accelerated life testing (ALT) is one of the major methods of rapidly evaluating product field reliability and life. The topic of how to improve assessment precision using ALT and field observation data has attracted research interest recently. A new method of field reliability assessment is proposed in this paper. Firstly, in view of data fusion, a more accurate model is established by integrating failure information from both the field and ALT data. Secondly, posterior parameter estimation, and field reliability and life are rapidly obtained through Bayesian analysis based on MCMC, which can effectively reduce the computational complexity of the model. Finally, a comprehensive set of experiments is conducted and the results show that reliability and life assessment based on this method is more precise.
{"title":"A new method for product field reliability assessment based on accelerated life test","authors":"Guolong Zhang, Junhu Li, Guohui Bao, Busheng Zhang","doi":"10.1109/ICRMS.2016.8050035","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050035","url":null,"abstract":"Accelerated life testing (ALT) is one of the major methods of rapidly evaluating product field reliability and life. The topic of how to improve assessment precision using ALT and field observation data has attracted research interest recently. A new method of field reliability assessment is proposed in this paper. Firstly, in view of data fusion, a more accurate model is established by integrating failure information from both the field and ALT data. Secondly, posterior parameter estimation, and field reliability and life are rapidly obtained through Bayesian analysis based on MCMC, which can effectively reduce the computational complexity of the model. Finally, a comprehensive set of experiments is conducted and the results show that reliability and life assessment based on this method is more precise.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115035094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050058
G. Kumar, M. Kaushik, Preeti
The present paper deals with the study of a Software-Hardware system under the consideration of software and hardware failures. The concept of degradation is considered for both the Software and Hardware components. For improving the degradation in the performance of Software and Hardware, we have supposed some maintenance policies in the Software as well as Hardware components. To enrich and improve the performance of the software components, the idea of Software rejuvenation has been incorporated. To develop a Markovian model, multi-level Software rejuvenation policy is taken in to consideration. While in the case of Hardware components, maintenance policies for different types of repairs such as corrective and preventive repairs have been considered. Various performance indices of the Software-Hardware system are determined using steady state probabilities. The illustrations are performed to validate the analytical model.
{"title":"Maintenance policies for improving the availability of a software-hardware system","authors":"G. Kumar, M. Kaushik, Preeti","doi":"10.1109/ICRMS.2016.8050058","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050058","url":null,"abstract":"The present paper deals with the study of a Software-Hardware system under the consideration of software and hardware failures. The concept of degradation is considered for both the Software and Hardware components. For improving the degradation in the performance of Software and Hardware, we have supposed some maintenance policies in the Software as well as Hardware components. To enrich and improve the performance of the software components, the idea of Software rejuvenation has been incorporated. To develop a Markovian model, multi-level Software rejuvenation policy is taken in to consideration. While in the case of Hardware components, maintenance policies for different types of repairs such as corrective and preventive repairs have been considered. Various performance indices of the Software-Hardware system are determined using steady state probabilities. The illustrations are performed to validate the analytical model.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114924340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050064
Qihai Liang, Hai-ping Dong, X. Yi, Bin Qin, Xiaoyu Yang
A reliability optimization allocation method for multifunctional systems using Hybrid Particle Swarm Optimization (HPSO) is proposed in this paper. First, researchers established a mathematical model for system reliability optimization allocation with the constraints of multi-function failure rates. Then, the HPSO was used to solve the optimization allocation model for multifunctional systems. Finally, researchers used an integrated transmission device with five functions as an example. They allocated reliability indexes of five functions by the method proposed in this paper. The result was compared with the results of basic Particle Swarm Optimization (PSO) and the result of Genetic Algorithm (GA). This comparison showed that the method proposed in this paper has a more powerful search capability, higher solving precision, fewer required parameters, better engineering adaptability and operability, and provides a new method of reliability allocation for complex systems with multiple functions.
{"title":"A reliability optimization allocation method for multifunctional systems using new hybrid particle swarm optimization","authors":"Qihai Liang, Hai-ping Dong, X. Yi, Bin Qin, Xiaoyu Yang","doi":"10.1109/ICRMS.2016.8050064","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050064","url":null,"abstract":"A reliability optimization allocation method for multifunctional systems using Hybrid Particle Swarm Optimization (HPSO) is proposed in this paper. First, researchers established a mathematical model for system reliability optimization allocation with the constraints of multi-function failure rates. Then, the HPSO was used to solve the optimization allocation model for multifunctional systems. Finally, researchers used an integrated transmission device with five functions as an example. They allocated reliability indexes of five functions by the method proposed in this paper. The result was compared with the results of basic Particle Swarm Optimization (PSO) and the result of Genetic Algorithm (GA). This comparison showed that the method proposed in this paper has a more powerful search capability, higher solving precision, fewer required parameters, better engineering adaptability and operability, and provides a new method of reliability allocation for complex systems with multiple functions.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133725741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1109/ICRMS.2016.8050166
Xin He, Yufeng Sun, Yaqiu Li
During the system design process, there are numerous factors that should be taken into account to incorporate reliability requirements into subsystems. The AGREE method is one of the most applicable methods to achieve system reliability allocation. However, when applied to some complex systems, this traditional method may become invalid. Firstly, the allocation results may become distorted and a computation method for the degree of importance is not proposed. Generally, this method can be only used for systems in series or parallel. To address these issues, the traditional AGREE allocation method needs to be modified. This paper proposes a novel degree computational method for complex system allocation whereby the traditional AGREE method is integrated with a mathematical model of system reliability. A framework for the new reliability allocation method is described. In practice, this novel method is used for the reliability allocation of a ship power system. A sensitivity analysis was conducted across several design requirements. The allocation results were verified, demonstrating the use in practical applications.
{"title":"An improved AGREE method with reliability mathematical model for complex system importance degree computation","authors":"Xin He, Yufeng Sun, Yaqiu Li","doi":"10.1109/ICRMS.2016.8050166","DOIUrl":"https://doi.org/10.1109/ICRMS.2016.8050166","url":null,"abstract":"During the system design process, there are numerous factors that should be taken into account to incorporate reliability requirements into subsystems. The AGREE method is one of the most applicable methods to achieve system reliability allocation. However, when applied to some complex systems, this traditional method may become invalid. Firstly, the allocation results may become distorted and a computation method for the degree of importance is not proposed. Generally, this method can be only used for systems in series or parallel. To address these issues, the traditional AGREE allocation method needs to be modified. This paper proposes a novel degree computational method for complex system allocation whereby the traditional AGREE method is integrated with a mathematical model of system reliability. A framework for the new reliability allocation method is described. In practice, this novel method is used for the reliability allocation of a ship power system. A sensitivity analysis was conducted across several design requirements. The allocation results were verified, demonstrating the use in practical applications.","PeriodicalId":347031,"journal":{"name":"2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132714009","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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