With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in th...With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.展开更多
This note derives the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation for the bivariate normal distribution. This new derivation shows ...This note derives the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation for the bivariate normal distribution. This new derivation shows the relationship between the two correlation coefficients through an infinite cosine series. A computationally efficient algorithm is also provided to estimate the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation. The algorithm can be implemented with relative ease using current modern mathematical or statistical software programming languages e.g. R, SAS, Mathematica, Fortran, et al. The algorithm is also available from the author of this article.展开更多
Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July...Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July 23 of 2014, this article adopted Pearson correlation coefficient method to determine the relevance among each pollutant of these cities with the help of SPSS. The results showed that such three leading indexes as SO2, PM10 and PM2.5 had strong correlation in Beijing, Tianjin and main cities of Hebei. Finally, some suggestions and preventive measures for the cooperative governance of air pollution in Beijing-Tianjin-Hebei Region were put forward, hoping this can help them.展开更多
Many applications for control of autonomous platform are being developed and one important aspect is the excess of information, frequently redundant, that imposes a great computational cost in data processing. Taking ...Many applications for control of autonomous platform are being developed and one important aspect is the excess of information, frequently redundant, that imposes a great computational cost in data processing. Taking into account the temporal coherence between consecutive frames, the PCC (Pearson's Correlation Coefficient) was proposed and applied as: discarding criteria methodology, dynamic power management solution, environment observer method which selects automatically only the regions-of-interest; and taking place in the obstacle avoidance context, as a method for collision risk estimation for vehicles in dynamic and unknown environments. Even if the PCC is a great tool to help the autonomous or semi-autonomous navigation, distortions in the imaging system, pixel noise, slight variations in the object's position relative to the camera, and other factors produce a false PCC threshold. Whereas there are homogeneous regions in the image, in order to obtain a more realistic Pearson's correlation, we propose to use some prior known environment information.展开更多
Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical s...Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical structures.In view of the fact that there are many parameters of airborne induced polarization data in time domain,and the sensitivity diff erence between parameters is large,which brings challenges to the stability and accuracy of the inversion.In this paper,we propose an inversion mehtod for time-domain AEM data with IP effect based on the Pearson correlation constraints.This method uses the Pearson correlation coeffi cient in statistics to characterize the correlation between the resistivity and the chargeability and constructs the Pearson correlation constraints for inverting the objective function to reduce the non uniqueness of inversion.To verify the eff ectiveness of this method,we perform both Occam’s inversion and Pearson correlation constrained inversion on the synthetic data.The experiments show that the Pearson correlation constrained inverison is more accurate and stable than the Occam’s inversion.Finally,we carried out the inversion to a survey dataset with and without IP eff ect.The results show that the data misfit and the continuity of the inverted section are greatly improved when the IP eff ect is considered.展开更多
Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow ...Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.展开更多
Heatmap cluster figures are often used to represent data sets in the?omic sciences. The default option of the frequently used R heatmap function is to cluster data according to Euclidean distance, which groups data ma...Heatmap cluster figures are often used to represent data sets in the?omic sciences. The default option of the frequently used R heatmap function is to cluster data according to Euclidean distance, which groups data mainly to their numerical value and not to its relative behaviour. The disadvantage of using the default clustering?dendrograms of R is demonstrated. Instead, a script is provided that uses correlation as distance function, which better reveals biologically meaningful information. This optimized script was used to detect heterotic groups in Vitamaize hybrids (purple maize with high nutraceutical value). A field trial with different genetic combinations was performed through an agricultural phenomics approach (holistic evaluation of the phenotype). The grain yield data and other phenotypic variables were represented through heatmap figures. In the data set of Mexican tropical maize germplasm, at least three heterotic groups were detected, in contrast to only two heterotic groups reported earlier in temperate yellow maize from USA and Europe. This optimized script for heatmap correlation bicluster can also be used to better represent metabolomic fingerprints and transcriptomic data sets.展开更多
In this paper, a collection of statistical correlation methods is used in the study of aquifer potentials in Abia State of south-eastern Nigeria. The Physiology, geomorphology and hydrogeology of the area are first pr...In this paper, a collection of statistical correlation methods is used in the study of aquifer potentials in Abia State of south-eastern Nigeria. The Physiology, geomorphology and hydrogeology of the area are first presented. Sixty-six Vertical Electrical Sounding (VES) data sets are used to determine the aquifer. Demographic studies are then carried out in 220 communities in order to determine the relationship between population size on one hand and a unit draw-down of wells due to groundwater abstraction on the other. The relationship between geological Formation, aquifer potentials and depth of boreholes are then calculated using Pearson’s correlation matrix. Results show that the mean population of persons appears to be higher in Bende-Ameki Formation (of Eocene-Oligocene age) and the late Tetiary-Early Quaternary Coastal Plain Sands, than in the Cretaceous shale Formation of Asata Nkporo. The mean population of persons sitting on these Formations is 31,200, 18,370 and 5400 respectively. Furthermore, it is observed that a population increase of about 50 persons in a community in Abia State is accompanied by a unit volume (1 m3) draw-down of wells due to groundwater abstraction. It is therefore concluded that population size is positively correlated with groundwater abstraction, aquifer potentials and geological Formation favouring aquifer in Abia State.展开更多
Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency...Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency department of our hospital were rolled from December 2015 to December 2016, who were divided into minor trauma group (n=41), severe trauma group (n=43) and critical trauma group (n=36) according to the injury severity score (ISS). The levels of serum Cys C, BNP of the patients in the 3 groups were detected on 0 h, 24 h, 3 d and 7 d after admission respectively. Pearson correlation analysis of the levels of serum Cys C, BNP and ISS.Results: There were no significant differences in the levels of serum Cys C, BNP on 0 hours between the three groups;There were no significant differences in the levels of serum Cys C, BNP on 0 h, 24 h, 3 d and 7 d in minor trauma group;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in severe trauma group, and the levels of serum Cys C on 3 d and 7 d were both higher than those of 24 h;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in critical trauma group, the levels of serum Cys C, BNP on 3 d and 7 d were both higher than those of 24 h, and the levels of serum Cys C on 7 d were higher than those of 3 d;The levels of serum Cys C, BNP in severe trauma and critical trauma groups were significantly higher compared with minor trauma group on 24 h, 3 d and 7 d. Pearson correlation analysis, the level of serum Cys C were positively correlated with ISS, the level of serum BNP were positively correlated with ISS.Conclusion:Different levels of traumatic patients had different levels of serum Cys C, BNP increased at different times. Pearson correlation analysis showed that the levels of serum Cys C, BNP were both positively correlated with traumatic severity, which suggested that the levels of serum Cys C, BNP may be important indicators of traumatic severity and could provide important reference value for clinical evaluation of traumatic severity.展开更多
基金Shanghai Rising-Star Program(Grant No.21QA1403400)Shanghai Sailing Program(Grant No.20YF1414800)Shanghai Key Laboratory of Power Station Automation Technology(Grant No.13DZ2273800).
文摘With the improvement of equipment reliability,human factors have become the most uncertain part in the system.The standardized Plant Analysis of Risk-Human Reliability Analysis(SPAR-H)method is a reliable method in the field of human reliability analysis(HRA)to evaluate human reliability and assess risk in large complex systems.However,the classical SPAR-H method does not consider the dependencies among performance shaping factors(PSFs),whichmay cause overestimation or underestimation of the risk of the actual situation.To address this issue,this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the Pearson correlation coefficient.First,the dependence between every two PSFs is measured by the Pearson correlation coefficient.Second,the weights of the PSFs are obtained by considering the total dependence degree.Finally,PSFs’multipliers are modified based on the weights of corresponding PSFs,and then used in the calculating of human error probability(HEP).A case study is used to illustrate the procedure and effectiveness of the proposed method.
文摘This note derives the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation for the bivariate normal distribution. This new derivation shows the relationship between the two correlation coefficients through an infinite cosine series. A computationally efficient algorithm is also provided to estimate the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation. The algorithm can be implemented with relative ease using current modern mathematical or statistical software programming languages e.g. R, SAS, Mathematica, Fortran, et al. The algorithm is also available from the author of this article.
文摘Based on the analysis of monitoring data on six pollution indexes of SO2, NO2, CO, O3, PM10 and PM2.5 from 53 monitoring points in 7 cities, including Beijing, Tianjin, Shijiazhuang, etc., from April 8 of 2014 to July 23 of 2014, this article adopted Pearson correlation coefficient method to determine the relevance among each pollutant of these cities with the help of SPSS. The results showed that such three leading indexes as SO2, PM10 and PM2.5 had strong correlation in Beijing, Tianjin and main cities of Hebei. Finally, some suggestions and preventive measures for the cooperative governance of air pollution in Beijing-Tianjin-Hebei Region were put forward, hoping this can help them.
文摘Many applications for control of autonomous platform are being developed and one important aspect is the excess of information, frequently redundant, that imposes a great computational cost in data processing. Taking into account the temporal coherence between consecutive frames, the PCC (Pearson's Correlation Coefficient) was proposed and applied as: discarding criteria methodology, dynamic power management solution, environment observer method which selects automatically only the regions-of-interest; and taking place in the obstacle avoidance context, as a method for collision risk estimation for vehicles in dynamic and unknown environments. Even if the PCC is a great tool to help the autonomous or semi-autonomous navigation, distortions in the imaging system, pixel noise, slight variations in the object's position relative to the camera, and other factors produce a false PCC threshold. Whereas there are homogeneous regions in the image, in order to obtain a more realistic Pearson's correlation, we propose to use some prior known environment information.
基金This paper was fi nancially supported by the National Natural Science Foundation of China(Nos.42030806,41774125,41904104,41804098)the Pioneer Project of Chinese Academy of Sciences(No.XDA14020102).
文摘Due to the induced polarization(IP)eff ect,the sign reversal often occurs in timedomain airborne electromagnetic(AEM)data.The inversions that do not consider IP eff ect cannot recover the true umderground electrical structures.In view of the fact that there are many parameters of airborne induced polarization data in time domain,and the sensitivity diff erence between parameters is large,which brings challenges to the stability and accuracy of the inversion.In this paper,we propose an inversion mehtod for time-domain AEM data with IP effect based on the Pearson correlation constraints.This method uses the Pearson correlation coeffi cient in statistics to characterize the correlation between the resistivity and the chargeability and constructs the Pearson correlation constraints for inverting the objective function to reduce the non uniqueness of inversion.To verify the eff ectiveness of this method,we perform both Occam’s inversion and Pearson correlation constrained inversion on the synthetic data.The experiments show that the Pearson correlation constrained inverison is more accurate and stable than the Occam’s inversion.Finally,we carried out the inversion to a survey dataset with and without IP eff ect.The results show that the data misfit and the continuity of the inverted section are greatly improved when the IP eff ect is considered.
文摘Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.
文摘Heatmap cluster figures are often used to represent data sets in the?omic sciences. The default option of the frequently used R heatmap function is to cluster data according to Euclidean distance, which groups data mainly to their numerical value and not to its relative behaviour. The disadvantage of using the default clustering?dendrograms of R is demonstrated. Instead, a script is provided that uses correlation as distance function, which better reveals biologically meaningful information. This optimized script was used to detect heterotic groups in Vitamaize hybrids (purple maize with high nutraceutical value). A field trial with different genetic combinations was performed through an agricultural phenomics approach (holistic evaluation of the phenotype). The grain yield data and other phenotypic variables were represented through heatmap figures. In the data set of Mexican tropical maize germplasm, at least three heterotic groups were detected, in contrast to only two heterotic groups reported earlier in temperate yellow maize from USA and Europe. This optimized script for heatmap correlation bicluster can also be used to better represent metabolomic fingerprints and transcriptomic data sets.
文摘In this paper, a collection of statistical correlation methods is used in the study of aquifer potentials in Abia State of south-eastern Nigeria. The Physiology, geomorphology and hydrogeology of the area are first presented. Sixty-six Vertical Electrical Sounding (VES) data sets are used to determine the aquifer. Demographic studies are then carried out in 220 communities in order to determine the relationship between population size on one hand and a unit draw-down of wells due to groundwater abstraction on the other. The relationship between geological Formation, aquifer potentials and depth of boreholes are then calculated using Pearson’s correlation matrix. Results show that the mean population of persons appears to be higher in Bende-Ameki Formation (of Eocene-Oligocene age) and the late Tetiary-Early Quaternary Coastal Plain Sands, than in the Cretaceous shale Formation of Asata Nkporo. The mean population of persons sitting on these Formations is 31,200, 18,370 and 5400 respectively. Furthermore, it is observed that a population increase of about 50 persons in a community in Abia State is accompanied by a unit volume (1 m3) draw-down of wells due to groundwater abstraction. It is therefore concluded that population size is positively correlated with groundwater abstraction, aquifer potentials and geological Formation favouring aquifer in Abia State.
文摘Objective:To observe the levels of serum cystatin C (Cys C), brain natriuretic peptide (BNP) in traumatic patients and correlation analysis with traumatic severity.Methods:120 emergency traumatic patients in emergency department of our hospital were rolled from December 2015 to December 2016, who were divided into minor trauma group (n=41), severe trauma group (n=43) and critical trauma group (n=36) according to the injury severity score (ISS). The levels of serum Cys C, BNP of the patients in the 3 groups were detected on 0 h, 24 h, 3 d and 7 d after admission respectively. Pearson correlation analysis of the levels of serum Cys C, BNP and ISS.Results: There were no significant differences in the levels of serum Cys C, BNP on 0 hours between the three groups;There were no significant differences in the levels of serum Cys C, BNP on 0 h, 24 h, 3 d and 7 d in minor trauma group;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in severe trauma group, and the levels of serum Cys C on 3 d and 7 d were both higher than those of 24 h;The levels of serum Cys C, BNP on 24 h, 3 d and 7 d were all higher than those of 0 h in critical trauma group, the levels of serum Cys C, BNP on 3 d and 7 d were both higher than those of 24 h, and the levels of serum Cys C on 7 d were higher than those of 3 d;The levels of serum Cys C, BNP in severe trauma and critical trauma groups were significantly higher compared with minor trauma group on 24 h, 3 d and 7 d. Pearson correlation analysis, the level of serum Cys C were positively correlated with ISS, the level of serum BNP were positively correlated with ISS.Conclusion:Different levels of traumatic patients had different levels of serum Cys C, BNP increased at different times. Pearson correlation analysis showed that the levels of serum Cys C, BNP were both positively correlated with traumatic severity, which suggested that the levels of serum Cys C, BNP may be important indicators of traumatic severity and could provide important reference value for clinical evaluation of traumatic severity.