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Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient
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作者 Xiaoyan Su Shuwen Shang +2 位作者 Zhihui Xu Hong Qian Xiaolei Pan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1813-1826,共14页
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
关键词 Reliability evaluation human reliability analysis SPAR-H performance shaping factors DEPENDENCE pearson correlation analysis
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Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019
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作者 YAO Tian ZHAO Qiang +6 位作者 WU Chuanhao HU Xiaonong XIA Chuan'an WANG Xuan SANG Guoqiang LIU Jian WANG Haijun 《Chinese Geographical Science》 SCIE CSCD 2024年第1期118-134,共17页
Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of... Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB. 展开更多
关键词 extreme climate indices Sen’s slope variation mutation test atmospheric circulation indices pearson’s correlation analysis Huaihe River Basin(HRB) China
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Crustal vertical deformation of Amazon Basin derived from GPS and GRACE/GFO data over past two decades 被引量:1
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作者 Jun Fang Meilin He +1 位作者 Wei Luan Jiashuang Jiao 《Geodesy and Geodynamics》 CSCD 2021年第6期441-450,共10页
In this study,the Gravity Recovery and Climate Experiment(GRACE)satellite observations,combining 71 continuous Global Positioning System(CGPS)data,are used to detect surface vertical loading deformation of the Amazon ... In this study,the Gravity Recovery and Climate Experiment(GRACE)satellite observations,combining 71 continuous Global Positioning System(CGPS)data,are used to detect surface vertical loading deformation of the Amazon Basin during 2002-2020.The results show that the maximal annual amplitude of the surface mass changes derived by GRACE is more than 80 cm in terms of the equivalent water height(EWH)in the Amazon Basin.Most part of Amazon experiences mass gain,especially the Amazon River,while there is little mass loss in the northern and eastern parts.Through the Pearson correlation analysis,the monthly de-trended time series of GPS-observed vertical deformation and GRACE-derived mass loading are in good agreement with an average correlation coefficient of about 0.75 throughout the Amazon region.The common seasonal signals of GPS vertical displacements and GRACE/GFO loading deformations are extracted using the stack averaging.The two kinds of common seasonal signals show a good consistency,and together indicate approximate 20 mm peak-to-peak seasonal amplitude.Strong annual variations are identified both in the monthly GPS and GRACE/GFO data by the wavelet analysis.However,the time-frequency spectrum of GPS has more signal details and more significant semi-annual variations than that of GRACE/GFO.These results may contribute to the understanding of secular crustal vertical deformation in the Amazon Basin. 展开更多
关键词 Amazon Basin GRACE/GFO GPS pearson correlation analysis Loading deformation
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Evaluation of Physico-Chemical Parameters as Veritable Indicators of Faecal Escherichia coli Contamination of Surface Waters
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作者 Emmanuel Amadi Emmanuel Eze Vincent Chigor 《Journal of Environmental Science and Engineering(A)》 2020年第6期205-216,共12页
There is need for alternate quick-search of pathogens’distribution in community water sources,instead of the cumbersome“Escherichia coli detection.”Physical and chemical(physico-chemical)parameters were evaluated a... There is need for alternate quick-search of pathogens’distribution in community water sources,instead of the cumbersome“Escherichia coli detection.”Physical and chemical(physico-chemical)parameters were evaluated as veritable indicators of faecal Escherichia coli contamination of surface waters,using Adada River in Nigeria as case-study.Thirty-two(32)physico-chemical parameters were analyzed in the river(at specified geographical coordinates)for their quality and quantity and connected(using Pearson’s Correlation Analysis)with the distribution of the river’s isolated Escherichia coli.The 32 physico-chemical parameters consist of 11 cations,6 anions,7 physical properties,3 properties relating to oxygen and 5 properties relating to anions/cations.Physico-chemical indices from the analysis,revealed very significant positive correlation relationship of Escherichia coli with the presence of Mg(Magnesium)and K(Potassium)in the dry and rainy season,respectively.E.coli affinity tests(Kirby-Bauer Disc Diffusion)for these metals were also positive.Mg and K also showed significant positive Pearson’s possible paired correlation relationship.From this evaluation,potential index analysis indicated that Mg and K could serve as markers for the faecal bacteria indicators,and possible index for future monitoring of the potability of such surface water.The method is straight forward,cost effective,less cumbersome than other currently existing approaches. 展开更多
关键词 Water analysis pearson Correlation analysis Escherichia coli physical and chemical indicator Kirby-Bauer Disc
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A Study on Economic Impact in the Context of American Election Based on AHP
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作者 Yang Yue Haomiao Niu Zhaoyun Gu 《Journal of Economic Science Research》 2021年第2期38-44,共7页
To assess the economic impact of the different policies of the Trump and Biden candidates,we formulate metrics on five aspects:Covid-19 prevention and control measures,environmental protection policies,taxation,health... To assess the economic impact of the different policies of the Trump and Biden candidates,we formulate metrics on five aspects:Covid-19 prevention and control measures,environmental protection policies,taxation,health care reform,foreign trade.Moreover,each metric is subdivided into several secondary metrics,making a three-tier hierarchical structure.Take environmental protection policy as an example:Without direct data under Biden’s policies,we collected data on U.S.CO2 emissions and U.S.oil consumption during Obama’s presidency as Biden’s legacy.First,use the analytic hierarchy process(AHP)to select indicators that can reflect the U.S.economy and determine the weight of each indicator.For the U.S.economy,Biden scored 2.6498,Trump 2.3502,suggesting that the election of Biden might make things better for the economy.For China’s economy,Biden scored 0.6810 and Trump 0.3245,meaning Biden could give the Chinese economy more room to grow.To reduce the influence of AHP subjectivity on the results,the Pearson correlation coefficient is introduced to establish the P-AHP model.Take the impact on China’s economy.Biden scored 0.5846 and Trump 0.4154. 展开更多
关键词 AHP American presidential election pearson correlation analysis ECONOMY
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Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA
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作者 Qin Qian Mengjie He +1 位作者 Frank Sun Xinyu Liu 《Water Science and Engineering》 EI CAS 2024年第1期21-32,共12页
Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collec... Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions.The statistical and Pearson correlation analysis on historical water samples determines that alkalinity,chloride,hardness,conductivity,and pH are highly correlated,and they decrease with increasing flow rate due to dilution.The flow rate has positive correlations with Escherichia coli,total suspended solids,and turbidity,which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river.The correlation between E.coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E.coli to indicate the bacterial outbreak.A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers,fill missing values,and filter spikes of the sensor measurements.The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover.Therefore,utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality,then in turn to provide early alerts on water resources management decisions. 展开更多
关键词 Water quality pearson correlation analysis Lower Neches River YSI wireless sensors Non-point pollution
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Acute toxicity assessment of drinking water source with luminescent bacteria: Impact of environmental conditions and a case study in Luoma Lake, East China 被引量:3
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作者 Xuewen Yi Zhanqi Gao +3 位作者 Lanhua Liu Qian Zhu Guanjiu Hu Xiaohong Zhou 《Frontiers of Environmental Science & Engineering》 SCIE EI CAS CSCD 2020年第6期201-209,共9页
Protecting the quality of lake watersheds by preventing and reducing their contamination is an effective approach to ensure the sustainability of the drinking water supply.In this study,acute toxicity assessment was c... Protecting the quality of lake watersheds by preventing and reducing their contamination is an effective approach to ensure the sustainability of the drinking water supply.In this study,acute toxicity assessment was conducted on the basis of acute bioluminescence inhibition assay using the marine bacterium Vibrio fischeri as the test organism and Luoma Lake drinking water source in East China as the research target.The suitable ranges of environmental factors,including pH value,organic matter,turbidity,hardness,and dissolved oxygen of water samples were evaluated for the toxicity testing of bioluminescent bacteria.The physicochemical characteristics of water samples at the selected 43 sites of Luoma Lake watershed were measured.Results showed that the variations in pH value(7.31-8.41),hardness(5-20°d)and dissolved oxygen(4.44-11.03 mg/L)of Luoma Lake and its main inflow and outflow rivers had negligible impacts on the acute toxicity testing of V.fischeri.The luminescence inhibition rates ranged from-11.21%to 10.80%at the 43 sites.Pearson's correlation analysis in the experiment revealed that temperature,pH value,hardness,and turbidity had no correlation with luminescence inhibition rate,whereas dissolved oxygen showed a weak statistically positive correlation with a Pearson correlation coefficient of 0.455(p<0.05). 展开更多
关键词 Bioluminescent bacteria Acute toxicity pearson correlation analysis Drinking water source Vibrio fischeri
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Concentrations and classification of HCHs and DDTs in soil from the lower reaches of the Jiulong River, China
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作者 Jiaquan ZHANG Shihua QI +5 位作者 Xinli XING Lingzhi TAN Wei CHEN Ying HU Dan YANG Chenxi WU 《Frontiers of Environmental Science & Engineering》 SCIE EI CAS CSCD 2012年第2期177-183,共7页
关键词 Jiulong River hexachlorocyclohexane (HCH)and dichlorodiphenyltrichloroethan (DDT) classification Hierarchical Cluster analysis (HCA) pearson's bivariateCorrelations analysis (PCA)
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