Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross...Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross error due to HE.So it is essential to analyze HE in construction.The crucial work of human error analysis(HEA) is the estimation of human error probability(HEP) in construction.The method for estimating HEP,analytic hierarchy process and failure likelihood index method(AHP-FLIM),is introduced in this paper.The method also uses the process of expert judgment within the failure likelihood index method(FLIM).A numerical example shows the effectiveness of the methods proposed.展开更多
A new and convenient method is presented to calculate the total sensitivity indices defined by variance-based sensitivity analysis. By decomposing the output variance using error propagation equations, this method can...A new and convenient method is presented to calculate the total sensitivity indices defined by variance-based sensitivity analysis. By decomposing the output variance using error propagation equations, this method can transform the ＂double-loop＂ sampling procedure into ＂single-loop＂ one and obviously reduce the computation cost of analysis. In contrast with Sobors and Fourier amplitude sensitivity test （FAST） method, which is limited in non-correlated variables, the new approach is suitable for correlated input variables. An application in semiconductor assembling and test manufacturing （ATM） factory indicates that this approach has a good performance in additive model and simple non-additive model.展开更多
The indexing transmission chain error of gear cutting machines is an obviously periodic timefunction. If data are acquired properly while surveying and analyzing the error with grating typeinstrument attached to a mic...The indexing transmission chain error of gear cutting machines is an obviously periodic timefunction. If data are acquired properly while surveying and analyzing the error with grating typeinstrument attached to a micro-computer, the analysis will be easier and quicker. In this paper,such a system is introduced; a data acquiring interface is designed. Therefore, real-time samplingcan be performed. The results obtained from the indexing tramsmission chain error of several gearhobbing and shaping machines with this system were satisfactory.展开更多
Purpose: This study provides a simple protocol for validation of the gamma passing rates and to identify the optimum values of % dose and mm criteria for dose distributions measured with a detector array. Methods: We ...Purpose: This study provides a simple protocol for validation of the gamma passing rates and to identify the optimum values of % dose and mm criteria for dose distributions measured with a detector array. Methods: We chose ArcCHECK detector array to illustrate the concepts. We used plans with uniform or quasi-uniform dose distributions along the detector array for testing in the presence of dose errors. For testing sensitivity to spatial shift we employed a plan with approximately constant dose gradient along the axis of the instrument. Results: We identified a representative set of parameters which describe performance of a detector array. We determined the minimum gamma-index acceptance criteria allowing the passing rates to reach 100% in the absence of errors, and identified the minimum fully detectable errors for such criteria. For our baseline plans delivered to ArcCHECK, 100% passing rates were obtained for 1.5% dose criterion together with ±3% minimum error detectable at 100% rate, and for 1.5 mm criterion together with the minimum fully detectable error of ±3 mm. We inspected the impact of selected program options on the passing rates. Conclusions: The protocol we developed provides a simple method of commissioning-style analysis of a detector array without a need for analysis of a large number of clinical plans.展开更多
In this paper we examine 5 indexes (the two Yule’s indexes, the chi square, the odds ratio and an elementary index) of a two-by-two table, which estimate the correlation coefficient ρ in a bivariate Bernoulli distri...In this paper we examine 5 indexes (the two Yule’s indexes, the chi square, the odds ratio and an elementary index) of a two-by-two table, which estimate the correlation coefficient ρ in a bivariate Bernoulli distribution. We will find the compact expression of the influence functions, which allow the quantification of the effect of an infinitesimal contamination of the probability of any pair of attributes of the bivariate random variable distributed according to the above-mentioned model. We prove that the only unbiased index is the chi square. In order to determine the indexes, which are less sensitive to contamination, we obtain the expressions of three synthetic measures of the influence function, which are the maximum contamination (gross sensitivity error), the mean square deviation and the variance. These results, even if don’t allow a definitive assessment of the overall optimum properties of the five indexes, as not all of them are unbiased, nevertheless they allow to appreciating the synthetic entity of the effect of the contaminations in the estimation of the parameter ρ of the bivariate Bernoulli distribution.展开更多
【目的】解决现有地形复杂度误差评价方法主观性强、缺少误差解析式的问题。【方法】利用误差传播定律推导了局部高差、局部标准差、局部褶皱度和局部全曲率的中误差表达式,依据复合地形因子误差传递规律构建了复合地形复杂度指标(compo...【目的】解决现有地形复杂度误差评价方法主观性强、缺少误差解析式的问题。【方法】利用误差传播定律推导了局部高差、局部标准差、局部褶皱度和局部全曲率的中误差表达式,依据复合地形因子误差传递规律构建了复合地形复杂度指标(compound terrain complexity index,CTCI)提取的误差估计模型(error estimation model for CTCI,CEEM)。通过模拟数字高程模型(digital elevation model,DEM)试验验证了该模型的有效性,并采用三个不同地貌区域的实体DEM进行CEEM泛化试验。【结果】在不同噪声影响下,CEEM平均误差、均方差、残差和平均绝对百分比误差最大值分别为-2.1×10^(-3)、7.99×10^(-6)、8.4×10^(-3)和22.8%,决定系数均在0.961以上,CEEM整体误差微小;不同地貌类型的地形复杂度提取误差存在差异,试验统计结果表明误差由大到小依次为高山、中山、丘陵。【结论】CEEM能定量化描述地形复杂度的提取误差,可为不同复杂地形地貌区域提取复合地形复杂度指标提供参考。展开更多
在林业研究中,胸径-树高二元联合分布多由相同边缘分布构造,而林分的胸径与树高的实际分布状况可能有所差异。为降低这种差异带来的影响,依据佳木斯市孟家岗林场的115块长白落叶松人工林数据,选择适用条件低、适应范围广的Copula函数方...在林业研究中,胸径-树高二元联合分布多由相同边缘分布构造,而林分的胸径与树高的实际分布状况可能有所差异。为降低这种差异带来的影响,依据佳木斯市孟家岗林场的115块长白落叶松人工林数据,选择适用条件低、适应范围广的Copula函数方法拟合落叶松胸径-树高二元联合分布模型。首先选择威布尔(Weibull)、广义威布尔(G-Weibull)、逻辑斯蒂(Logistic)、轻量逻辑斯蒂(Logit-Logistic)、伽马(Gamma)、对数正态(Log-Normal)6个分布函数作为备选基础模型,根据K-S(kolmogorov smirnov test)检验与半参数估计结果筛选并构建Copula胸径-树高二元联合分布模型,再通过负对数似然(negative log-likelihood,NLL)、Sn拟合优度统计量和似然比检验(likelihood ratio test,LRT)与二元对数logistic分布函数和二元Weibull分布函数进行比较,最后使用雷诺误差指数(error index of Reynolds,EI)对模型预测能力进行评估。结果表明,基于Copula函数的二元分拟合结果与模型(EI=0.3184)预估能力皆优于二元Weibull分布(EI=0.6381)和二元对数Logistic分布(EI=0.9490),说明此方法构建胸径-树高二元联合Copula分布模型能够很好地描述落叶松人工林胸径树高联合分布,以Copula方法构建树高-胸径联合分布是可行的。展开更多
文摘Human error(HE) is the most important factor influencing on structural safety because its effect often exceeds the random deviation.Large numbers of facts have shown that structural failures may be caused by the gross error due to HE.So it is essential to analyze HE in construction.The crucial work of human error analysis(HEA) is the estimation of human error probability(HEP) in construction.The method for estimating HEP,analytic hierarchy process and failure likelihood index method(AHP-FLIM),is introduced in this paper.The method also uses the process of expert judgment within the failure likelihood index method(FLIM).A numerical example shows the effectiveness of the methods proposed.
文摘A new and convenient method is presented to calculate the total sensitivity indices defined by variance-based sensitivity analysis. By decomposing the output variance using error propagation equations, this method can transform the ＂double-loop＂ sampling procedure into ＂single-loop＂ one and obviously reduce the computation cost of analysis. In contrast with Sobors and Fourier amplitude sensitivity test （FAST） method, which is limited in non-correlated variables, the new approach is suitable for correlated input variables. An application in semiconductor assembling and test manufacturing （ATM） factory indicates that this approach has a good performance in additive model and simple non-additive model.
文摘The indexing transmission chain error of gear cutting machines is an obviously periodic timefunction. If data are acquired properly while surveying and analyzing the error with grating typeinstrument attached to a micro-computer, the analysis will be easier and quicker. In this paper,such a system is introduced; a data acquiring interface is designed. Therefore, real-time samplingcan be performed. The results obtained from the indexing tramsmission chain error of several gearhobbing and shaping machines with this system were satisfactory.
文摘Purpose: This study provides a simple protocol for validation of the gamma passing rates and to identify the optimum values of % dose and mm criteria for dose distributions measured with a detector array. Methods: We chose ArcCHECK detector array to illustrate the concepts. We used plans with uniform or quasi-uniform dose distributions along the detector array for testing in the presence of dose errors. For testing sensitivity to spatial shift we employed a plan with approximately constant dose gradient along the axis of the instrument. Results: We identified a representative set of parameters which describe performance of a detector array. We determined the minimum gamma-index acceptance criteria allowing the passing rates to reach 100% in the absence of errors, and identified the minimum fully detectable errors for such criteria. For our baseline plans delivered to ArcCHECK, 100% passing rates were obtained for 1.5% dose criterion together with ±3% minimum error detectable at 100% rate, and for 1.5 mm criterion together with the minimum fully detectable error of ±3 mm. We inspected the impact of selected program options on the passing rates. Conclusions: The protocol we developed provides a simple method of commissioning-style analysis of a detector array without a need for analysis of a large number of clinical plans.
文摘In this paper we examine 5 indexes (the two Yule’s indexes, the chi square, the odds ratio and an elementary index) of a two-by-two table, which estimate the correlation coefficient ρ in a bivariate Bernoulli distribution. We will find the compact expression of the influence functions, which allow the quantification of the effect of an infinitesimal contamination of the probability of any pair of attributes of the bivariate random variable distributed according to the above-mentioned model. We prove that the only unbiased index is the chi square. In order to determine the indexes, which are less sensitive to contamination, we obtain the expressions of three synthetic measures of the influence function, which are the maximum contamination (gross sensitivity error), the mean square deviation and the variance. These results, even if don’t allow a definitive assessment of the overall optimum properties of the five indexes, as not all of them are unbiased, nevertheless they allow to appreciating the synthetic entity of the effect of the contaminations in the estimation of the parameter ρ of the bivariate Bernoulli distribution.
文摘【目的】解决现有地形复杂度误差评价方法主观性强、缺少误差解析式的问题。【方法】利用误差传播定律推导了局部高差、局部标准差、局部褶皱度和局部全曲率的中误差表达式,依据复合地形因子误差传递规律构建了复合地形复杂度指标(compound terrain complexity index,CTCI)提取的误差估计模型(error estimation model for CTCI,CEEM)。通过模拟数字高程模型(digital elevation model,DEM)试验验证了该模型的有效性,并采用三个不同地貌区域的实体DEM进行CEEM泛化试验。【结果】在不同噪声影响下,CEEM平均误差、均方差、残差和平均绝对百分比误差最大值分别为-2.1×10^(-3)、7.99×10^(-6)、8.4×10^(-3)和22.8%,决定系数均在0.961以上,CEEM整体误差微小;不同地貌类型的地形复杂度提取误差存在差异,试验统计结果表明误差由大到小依次为高山、中山、丘陵。【结论】CEEM能定量化描述地形复杂度的提取误差,可为不同复杂地形地貌区域提取复合地形复杂度指标提供参考。
文摘在林业研究中,胸径-树高二元联合分布多由相同边缘分布构造,而林分的胸径与树高的实际分布状况可能有所差异。为降低这种差异带来的影响,依据佳木斯市孟家岗林场的115块长白落叶松人工林数据,选择适用条件低、适应范围广的Copula函数方法拟合落叶松胸径-树高二元联合分布模型。首先选择威布尔(Weibull)、广义威布尔(G-Weibull)、逻辑斯蒂(Logistic)、轻量逻辑斯蒂(Logit-Logistic)、伽马(Gamma)、对数正态(Log-Normal)6个分布函数作为备选基础模型,根据K-S(kolmogorov smirnov test)检验与半参数估计结果筛选并构建Copula胸径-树高二元联合分布模型,再通过负对数似然(negative log-likelihood,NLL)、Sn拟合优度统计量和似然比检验(likelihood ratio test,LRT)与二元对数logistic分布函数和二元Weibull分布函数进行比较,最后使用雷诺误差指数(error index of Reynolds,EI)对模型预测能力进行评估。结果表明,基于Copula函数的二元分拟合结果与模型(EI=0.3184)预估能力皆优于二元Weibull分布(EI=0.6381)和二元对数Logistic分布(EI=0.9490),说明此方法构建胸径-树高二元联合Copula分布模型能够很好地描述落叶松人工林胸径树高联合分布,以Copula方法构建树高-胸径联合分布是可行的。
