Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance...Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance liquid chromatography(RP-HPLC) method allowing the separation of six alkaloids in Huanglian was for the first time developed under the quality by design(Qb D) principles. First, five chromatographic parameters were identified to construct a Plackett-Burman experimental design. The critical resolution, analysis time, and peak width were responses modeled by multivariate linear regression. The results showed that the percentage of acetonitrile, concentration of sodium dodecyl sulfate, and concentration of potassium phosphate monobasic were statistically significant parameters(P < 0.05). Then, the Box-Behnken experimental design was applied to further evaluate the interactions between the three parameters on selected responses. Full quadratic models were built and used to establish the analytical design space. Moreover, the reliability of design space was estimated by the Bayesian posterior predictive distribution. The optimal separation was predicted at 40% acetonitrile, 1.7 g·m L-1of sodium dodecyl sulfate and 0.03 mol·m L-1 of potassium phosphate monobasic. Finally, the accuracy profile methodology was used to validate the established HPLC method. The results demonstrated that the Qb D concept could be efficiently used to develop a robust RP-HPLC analytical method for Huanglian.展开更多
Abundant test data are required in assessment of weapon performance. When weapon test data are insufficient, Bayesian analyses in small sample circumstance should be considered and the test data should be provided by ...Abundant test data are required in assessment of weapon performance. When weapon test data are insufficient, Bayesian analyses in small sample circumstance should be considered and the test data should be provided by simulations. The several Bayesian approaches are discussed and some limitations are founded. An improvement is put forward after limitations of Bayesian approaches available are analyzed and the improved approach is applied to assessment of some new weapon performance.展开更多
In this work,we perform a Bayesian inference of the crust-core transition density ρ_(t) of neutron stars based on the neutron-star radius and neutron-skin thickness data using a thermodynamical method.Uniform and Gau...In this work,we perform a Bayesian inference of the crust-core transition density ρ_(t) of neutron stars based on the neutron-star radius and neutron-skin thickness data using a thermodynamical method.Uniform and Gaussian distributions for the ρ_(t) prior were adopted in the Bayesian approach.It has a larger probability of having values higher than 0.1 fm^(−3) for ρ_(t) as the uniform prior and neutron-star radius data were used.This was found to be controlled by the curvature K_(sym) of the nuclear symmetry energy.This phenomenon did not occur if K_(sym) was not extremely negative,namely,K_(sym)>−200 MeV.The value ofρ_(t) obtained was 0.075_(−0.01)^(+0.005) fm^(−3) at a confidence level of 68%when both the neutron-star radius and neutron-skin thickness data were considered.Strong anti-correlations were observed between ρ_(t),slope L,and curvature of the nuclear symmetry energy.The dependence of the three L-K_(sym) correlations predicted in the literature on crust-core density and pressure was quantitatively investigated.The most probable value of 0.08 fm^(−3) for ρ_(t) was obtained from the L-K_(sym) relationship proposed by Holt et al.while larger values were preferred for the other two relationships.展开更多
New armament systems are subjected to the method for dealing with multi-stage system reliability-growth statistical problems of diverse population in order to improve reliability before starting mass production. Aimin...New armament systems are subjected to the method for dealing with multi-stage system reliability-growth statistical problems of diverse population in order to improve reliability before starting mass production. Aiming at the test process which is high expense and small sample-size in the development of complex system, the specific methods are studied on how to process the statistical information of Bayesian reliability growth regarding diverse populations. Firstly, according to the characteristics of reliability growth during product development, the Bayesian method is used to integrate the testing information of multi-stage and the order relations of distribution parameters. And then a Gamma-Beta prior distribution is proposed based on non-homogeneous Poisson process（NHPP） corresponding to the reliability growth process. The posterior distribution of reliability parameters is obtained regarding different stages of product, and the reliability parameters are evaluated based on the posterior distribution. Finally, Bayesian approach proposed in this paper for multi-stage reliability growth test is applied to the test process which is small sample-size in the astronautics filed. The results of a numerical example show that the presented model can make use of the diverse information synthetically, and pave the way for the application of the Bayesian model for multi-stage reliability growth test evaluation with small sample-size. The method is useful for evaluating multi-stage system reliability and making reliability growth plan rationally.展开更多
A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data an...A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.展开更多
Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLL...Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLLC） is a challenge because of the reparability and large-scale. To address the challenge, a general Bayesian serial revision prediction method based on Bootstrap approach and moving average approach is put forward, which can make an accurately prediction for the failure number. To demonstrate the performance gains of our method, extensive experiments on the data of Los Alamos National Laboratory （LANL） cluster is implemented, which is a typical RLLC system. And experimental results show that the prediction accuracy of our method is 80.2 %, and it is a greatly improvement with 4 % compared with some typical methods. Finally, the managerial implications of the models are discussed.展开更多
In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural charact...In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined wfth the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.展开更多
The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because ...The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because it has a mean value function that reflects the delay in failure reporting: there is a delay between failure detection and reporting time. The model captures error detection, isolation, and removal processes, thus is appropriate for software reliability analysis. Predictive analysis in software testing is useful in modifying, debugging, and determining when to terminate software development testing processes. However, Bayesian predictive analyses on the delayed S-shaped model have not been extensively explored. This paper uses the delayed S-shaped SRGM to address four issues in one-sample prediction associated with the software development testing process. Bayesian approach based on non-informative priors was used to derive explicit solutions for the four issues, and the developed methodologies were illustrated using real data.展开更多
Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for geotechnical analyses involving ...Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for geotechnical analyses involving unsaturated soils. Determining SWCC can be achieved by fitting data points obtained according to the prescribed experimental scheme, which is specified by the number of measuring points and their corresponding values of the control variable. The number of measuring points is limited since direct measurement of SWCC is often costly and time-consuming. Based on the limited number of measuring points, the estimated SWCC is unavoidably associated with uncertainties, which depends on measurement data obtained from the prescribed experimental scheme. Therefore, it is essential to plan the experimental scheme so as to reduce the uncertainty in the estimated SWCC. This study presented a Bayesian approach, called OBEDO, for probabilistic experimental design optimization of measuring SWCC based on the prior knowledge and information of testing apparatus. The uncertainty in estimated SWCC is quantified and the optimal experimental scheme with the maximum expected utility is determined by Subset Simulation optimization (SSO) in candidate experimental scheme space. The proposed approach is illustrated using an experimental design example given prior knowledge and the information of testing apparatus and is verified based on a set of real loess SWCC data, which were used to generate random experimental schemes to mimic the arbitrary arrangement of measuring points during SWCC testing in practice. Results show that the arbitrary arrangement of measuring points of SWCC testing is hardly superior to the optimal scheme obtained from OBEDO in terms of the expected utility. The proposed OBEDO approach provides a rational tool to optimize the arrangement of measuring points of SWCC test so as to obtain SWCC measurement data with relatively high expected utility for uncertainty reduction.展开更多
The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of ...The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.展开更多
Objectives This study aimed to quantify the impact of major chronic diseases on changes in healthy life expectancy(HLE)from 2011 to 2020 in China using an age-specific disability weights(DW)estimation method.Methods H...Objectives This study aimed to quantify the impact of major chronic diseases on changes in healthy life expectancy(HLE)from 2011 to 2020 in China using an age-specific disability weights(DW)estimation method.Methods HLE at age 60(HLE_(60))was used as the indicator of HLE in China.Cause-specific mortality rates were obtained from the cause-of-death database of the National Health Commission.Selfreported disease and disability status were derived from the China Health and Retirement Longitudinal Study.A total of 55,861 participants were included for DW estimation.Rates of disability,which was assessed using the Activities of Daily Living questionnaires,were estimated using data from 5,465 participants in 2011 and 9,910 participants in 2020.Age-specific DWs were calculated using a Bayesian logistic regression model.Changes in HLE_(60) were decomposed into mortality and disability effects by cause,based on the estimated DWs.Results HLE_(60) in China increased by 0.83 years from 2011 to 2020.Ischemic heart disease(IHD)contributed the most to the decline in HLE_(60),remaining the leading cause of reduction in terms of mortality effects.Diabetes showed the greatest impact on HLE_(60) due to disability,followed by stroke.The largest sex disparities in HLE_(60) were associated with disability from arthritis.Conclusion HLE_(60) in China improved from 2011 to 2020 and IHD remained the leading contributor to its decline,particularly through increased mortality.Disabilities related to diabetes,stroke,and arthritis had significant negative impacts.These findings highlight the need to strengthen integrated chronic disease prevention and rehabilitation services at community health centers.展开更多
With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach...With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach based on time-varying dependence analysis. The dependence between the two performance indicators of rotary lip seals, namely leakage rate and friction torque, is modeled by time-varying copula function with polynomial to denote the time-varying parameters, and an efficient copula selection approach is utilized to select the optimal copula function. Parameter estimation is carried out based on a Bayesian method and the reliability during the whole lifetime is calculated based on a Monte Carlo method. Degradation test for rotary lip seal is conducted and the proposed model is validated by test data. The optimal copula function and optimal order of polynomial are determined based on test data. Results show that this model is effective in estimating the reliability of rotary lip seals and can achieve a better goodness of fit.展开更多
In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a sup...In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a superior performance compared to the Bayesian approach as well as the widely used maximum likelihood estimation （MLE） method in fitting the real variation of b-values. We then apply the improved Bayesian approach to North China and find that the b-value has a clear relevance to seismicity. Temporal changes of b-values are also investigated in two specific areas of North China. We interpret sharp decreases in the b-values as useful messages in earthquake hazard analysis.展开更多
This study proposed a new analytical approach to identify the excessive comovement of two markets as contagion.This goal is achieved by linking latent-factor and single-equation error correction models and evaluating ...This study proposed a new analytical approach to identify the excessive comovement of two markets as contagion.This goal is achieved by linking latent-factor and single-equation error correction models and evaluating the breaks in the short-and long-term relationships and correlatedness in the linked model.The results demonstrated that a short-term relationship representing the market speed ratio between two markets plays a key role in contagion dynamics.When a long-term relationship or correlatedness is broken(comovement change)due to a break in the short-term relationship(market speed ratio),contagion is highly likely and should be formally declared.Bayesian posterior probabilities were calculated to determine the cause.Furthermore,this study applied this analytical Bayesian approach to empirically test the contagion effects of the U.S.stock market during the global financial crisis between 2007 and 2009 using 22 developed equity markets.展开更多
Although the degree of mate competition, given extreme differences in sex ratio, explains much of the pattern of male-biased size dimorphism among diverse taxa, it fails for some species which have potential for inten...Although the degree of mate competition, given extreme differences in sex ratio, explains much of the pattern of male-biased size dimorphism among diverse taxa, it fails for some species which have potential for intense male competition for mates and yet exhibit little or no sexual size dimorphism （SSD）. This fact suggest that species with low SSD should be express the effect of evolutionary pressure in non-obvious geometrical shape promoted by sex ratio in an evolutionary time scale. To evaluate this hypothesis we used phylogenetic comparative method in a Bayesian framework to investigate the evolution of SSD and the role of sex ratio at inter-specific level in the species of Ceroglossus （Coleoptera： Carabidae）. In our results the proportion farthest from 1：1 is associated with more disparate body shape, even though the entire group has minimum variation in sex ratio, which is an intrinsic life history character of this group considering its phylogenetic conservatism or phylogenetic signal. We suggest that the sex ratio has determined the dimorphism degree during evolution of this group, since both traits have increased or decreased together during the species divergence （i.e. positive phylogenetic correlation： r2=0.85）. We suggest that morphological studies of SSD will benefit from using comparative method with Bayesian approaches to assess the effect of phylogenetic history and its uncertainty. Finally, this will be allow to researchers to quantify the uncertainty of specific evolutionary hypotheses accounting for observed sexual dimorphism patterns.展开更多
Quantifying the tool–tissue interaction forces in surgery can be utilized in the training of inexperienced surgeons,assist them better use surgical tools and avoid applying excessive pressures.The voltages read from ...Quantifying the tool–tissue interaction forces in surgery can be utilized in the training of inexperienced surgeons,assist them better use surgical tools and avoid applying excessive pressures.The voltages read from strain gauges are used to approximate the unknown values of implemented forces.To this objective,the force-voltage connection must be quantified in order to evaluate the interaction forces during surgery.The progress of appropriate statistical learning approaches to describe the link between the genuine force applied on the tissue and numerous outputs obtained from sensors installed on surgical equipment is a key problem.In this study,different probabilistic approaches are used to evaluate the realized force on tissue using voltages read from strain gauges,including bootstrapping,Bayesian regression,weighted least squares regression,and multi-level modelling.Estimates from the proposed models are more precise than the maximum likelihood and restricted maximum likelihood techniques.The suggested methodologies are proficient of assessing tool-tissue interface forces with an adequate level of accuracy.展开更多
By analyzing the shortage of reliability test design and thinking over the producer's risk and consumer's risk, the information fusion technology is used to set up a reliability test design model( RTDM). By an...By analyzing the shortage of reliability test design and thinking over the producer's risk and consumer's risk, the information fusion technology is used to set up a reliability test design model( RTDM). By analyzing the demands and constraint conditions of the RTDM and with applications of Bayesian approach and Monte Carlo method( MCM),this paper puts forward the exponential distributed subsystems and the information fusion technology among them. According to the posteriori risk criteria,formulas of producer's risk and consumer's risk were also inferred,and with the help of Matlab software,selection of the optimum test plan was solved. Finally,validity of the model had been proved by a test of series parallel system.展开更多
Left-turn movements at signalized intersections pose significant safety risks to drivers and raise efficiency concerns for traffic operations in urban networks.Restricting left-turn movements at selected locations has...Left-turn movements at signalized intersections pose significant safety risks to drivers and raise efficiency concerns for traffic operations in urban networks.Restricting left-turn movements at selected locations has been shown to be effective at improving operational efficiency and mitigating safety concerns.However,determining optimal locations to restrict left-turns is a complex combinatorial optimization problem that is compounded by the lack of analytical forms for the objective function and constraints,as well as poten-tial interdependencies among the decision variables.Following the common solution para-digm for this type of optimization problems,this paper presents a novel Bayesian approach that utilizes dictionary-based embeddings,and is tailored for high-dimensional combina-torial(or even mixed)spaces.Simulation studies conducted using the Aimsun software under perfect or imperfect grid networks demonstrate that the presented method can con-sistently find promising left-turn restriction configurations that outperform the all-or-nothing strategies(to restrict all or none left-turn movements at all intersections),as well as the population based incremental learning algorithm.In addition,the presented method often does so with less simulation cost,thus showcasing its potential for efficient solution of more general traffic optimization problems.展开更多
This paper introduces some Bayesian optimal design methods for step-stress accelerated life test planning with one accelerating variable, when the acceleration model is linear in the accelerated variable or its functi...This paper introduces some Bayesian optimal design methods for step-stress accelerated life test planning with one accelerating variable, when the acceleration model is linear in the accelerated variable or its function, based on censored data from a log-location-scale distributions. In order to find the optimal plan,we propose different Monte Carlo simulation algorithms for different Bayesian optimal criteria. We present an example using the lognormal life distribution with Type-I censoring to illustrate the different Bayesian methods and to examine the effects of the prior distribution and sample size. By comparing the different Bayesian methods we suggest that when the data have large（small） sample size B1（τ）（B2（τ）） method is adopted. Finally, the Bayesian optimal plans are compared with the plan obtained by maximum likelihood method.展开更多
Bayesian adaptive randomization has attracted increasingly attention in the literature and has been implemented in many phase II clinical trials. Doubly adaptive biased coin design(DBCD) is a superior choice in respon...Bayesian adaptive randomization has attracted increasingly attention in the literature and has been implemented in many phase II clinical trials. Doubly adaptive biased coin design(DBCD) is a superior choice in response-adaptive designs owing to its promising properties. In this paper, we propose a randomized design by combining Bayesian adaptive randomization with doubly adaptive biased coin design. By selecting a fixed tuning parameter, the proposed randomization procedure can target an explicit allocation proportion, and assign more patients to the better treatment simultaneously. Moreover, the proposed randomization is efficient to detect treatment differences. We illustrate the proposed design by its applications to both discrete and continuous responses, and evaluate its operating features through simulation studies.展开更多
基金supported by National Natural Science Foundation of China(No.81403112)Beijing Natural Science Foundation(No.7154217)+1 种基金Scientific Research Program of Beijing University of Chinese Medicine(No.2015-JYB-XS104)Special Program for Beijing Key Laboratory of Chinese Medicine Manufacturing Process Control and Quality Evaluation(No.Z151100001615065)
文摘Coptis chinensis(Huanglian) is a commonly used traditional Chinese medicine(TCM) herb and alkaloids are the most important chemical constituents in it. In the present study, an isocratic reverse phase high performance liquid chromatography(RP-HPLC) method allowing the separation of six alkaloids in Huanglian was for the first time developed under the quality by design(Qb D) principles. First, five chromatographic parameters were identified to construct a Plackett-Burman experimental design. The critical resolution, analysis time, and peak width were responses modeled by multivariate linear regression. The results showed that the percentage of acetonitrile, concentration of sodium dodecyl sulfate, and concentration of potassium phosphate monobasic were statistically significant parameters(P < 0.05). Then, the Box-Behnken experimental design was applied to further evaluate the interactions between the three parameters on selected responses. Full quadratic models were built and used to establish the analytical design space. Moreover, the reliability of design space was estimated by the Bayesian posterior predictive distribution. The optimal separation was predicted at 40% acetonitrile, 1.7 g·m L-1of sodium dodecyl sulfate and 0.03 mol·m L-1 of potassium phosphate monobasic. Finally, the accuracy profile methodology was used to validate the established HPLC method. The results demonstrated that the Qb D concept could be efficiently used to develop a robust RP-HPLC analytical method for Huanglian.
文摘Abundant test data are required in assessment of weapon performance. When weapon test data are insufficient, Bayesian analyses in small sample circumstance should be considered and the test data should be provided by simulations. The several Bayesian approaches are discussed and some limitations are founded. An improvement is put forward after limitations of Bayesian approaches available are analyzed and the improved approach is applied to assessment of some new weapon performance.
基金supported by the Shanxi Provincial Foundation for Returned Overseas Scholars (No. 20220037)Natural Science Foundation of Shanxi Province (No. 20210302123085)Discipline Construction Project of Yuncheng University
文摘In this work,we perform a Bayesian inference of the crust-core transition density ρ_(t) of neutron stars based on the neutron-star radius and neutron-skin thickness data using a thermodynamical method.Uniform and Gaussian distributions for the ρ_(t) prior were adopted in the Bayesian approach.It has a larger probability of having values higher than 0.1 fm^(−3) for ρ_(t) as the uniform prior and neutron-star radius data were used.This was found to be controlled by the curvature K_(sym) of the nuclear symmetry energy.This phenomenon did not occur if K_(sym) was not extremely negative,namely,K_(sym)>−200 MeV.The value ofρ_(t) obtained was 0.075_(−0.01)^(+0.005) fm^(−3) at a confidence level of 68%when both the neutron-star radius and neutron-skin thickness data were considered.Strong anti-correlations were observed between ρ_(t),slope L,and curvature of the nuclear symmetry energy.The dependence of the three L-K_(sym) correlations predicted in the literature on crust-core density and pressure was quantitatively investigated.The most probable value of 0.08 fm^(−3) for ρ_(t) was obtained from the L-K_(sym) relationship proposed by Holt et al.while larger values were preferred for the other two relationships.
基金supported by Sustentation Program of National Ministries and Commissions of China (Grant No. 51319030302 and Grant No. 9140A19030506KG0166)
文摘New armament systems are subjected to the method for dealing with multi-stage system reliability-growth statistical problems of diverse population in order to improve reliability before starting mass production. Aiming at the test process which is high expense and small sample-size in the development of complex system, the specific methods are studied on how to process the statistical information of Bayesian reliability growth regarding diverse populations. Firstly, according to the characteristics of reliability growth during product development, the Bayesian method is used to integrate the testing information of multi-stage and the order relations of distribution parameters. And then a Gamma-Beta prior distribution is proposed based on non-homogeneous Poisson process（NHPP） corresponding to the reliability growth process. The posterior distribution of reliability parameters is obtained regarding different stages of product, and the reliability parameters are evaluated based on the posterior distribution. Finally, Bayesian approach proposed in this paper for multi-stage reliability growth test is applied to the test process which is small sample-size in the astronautics filed. The results of a numerical example show that the presented model can make use of the diverse information synthetically, and pave the way for the application of the Bayesian model for multi-stage reliability growth test evaluation with small sample-size. The method is useful for evaluating multi-stage system reliability and making reliability growth plan rationally.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education(20114307120032)the National Natural Science Foundation of China(71201167)
文摘A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.
基金supported by the National Natural Science Foundationof China (60701006 60804054 71071158)
文摘Failure prediction plays an important role for many tasks such as optimal resource management in large-scale system. However, accurately failure number prediction of repairable large-scale long-running computing （RLLC） is a challenge because of the reparability and large-scale. To address the challenge, a general Bayesian serial revision prediction method based on Bootstrap approach and moving average approach is put forward, which can make an accurately prediction for the failure number. To demonstrate the performance gains of our method, extensive experiments on the data of Los Alamos National Laboratory （LANL） cluster is implemented, which is a typical RLLC system. And experimental results show that the prediction accuracy of our method is 80.2 %, and it is a greatly improvement with 4 % compared with some typical methods. Finally, the managerial implications of the models are discussed.
基金supported by the National Science and Technology Support Program of China (Program for the Eleventh Five-Year Plan, Grant No. 2006BAC14B03 and 2006BAC05B03)the National Natural Science Foundation of China (Grant No. 50679043)
文摘In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined wfth the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.
文摘The delayed S-shaped software reliability growth model (SRGM) is one of the non-homogeneous Poisson process (NHPP) models which have been proposed for software reliability assessment. The model is distinctive because it has a mean value function that reflects the delay in failure reporting: there is a delay between failure detection and reporting time. The model captures error detection, isolation, and removal processes, thus is appropriate for software reliability analysis. Predictive analysis in software testing is useful in modifying, debugging, and determining when to terminate software development testing processes. However, Bayesian predictive analyses on the delayed S-shaped model have not been extensively explored. This paper uses the delayed S-shaped SRGM to address four issues in one-sample prediction associated with the software development testing process. Bayesian approach based on non-informative priors was used to derive explicit solutions for the four issues, and the developed methodologies were illustrated using real data.
文摘Soil-water characteristic curve (SWCC) is significant to estimate the site-specific unsaturated soil properties (such as unsaturated shear strength and coefficient of permeability) for geotechnical analyses involving unsaturated soils. Determining SWCC can be achieved by fitting data points obtained according to the prescribed experimental scheme, which is specified by the number of measuring points and their corresponding values of the control variable. The number of measuring points is limited since direct measurement of SWCC is often costly and time-consuming. Based on the limited number of measuring points, the estimated SWCC is unavoidably associated with uncertainties, which depends on measurement data obtained from the prescribed experimental scheme. Therefore, it is essential to plan the experimental scheme so as to reduce the uncertainty in the estimated SWCC. This study presented a Bayesian approach, called OBEDO, for probabilistic experimental design optimization of measuring SWCC based on the prior knowledge and information of testing apparatus. The uncertainty in estimated SWCC is quantified and the optimal experimental scheme with the maximum expected utility is determined by Subset Simulation optimization (SSO) in candidate experimental scheme space. The proposed approach is illustrated using an experimental design example given prior knowledge and the information of testing apparatus and is verified based on a set of real loess SWCC data, which were used to generate random experimental schemes to mimic the arbitrary arrangement of measuring points during SWCC testing in practice. Results show that the arbitrary arrangement of measuring points of SWCC testing is hardly superior to the optimal scheme obtained from OBEDO in terms of the expected utility. The proposed OBEDO approach provides a rational tool to optimize the arrangement of measuring points of SWCC test so as to obtain SWCC measurement data with relatively high expected utility for uncertainty reduction.
基金supported by the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(No.GLAB 2024ZR03)the National Natural Science Foundation of China(No.42407248)+2 种基金the Guizhou Provincial Basic Research Program(Natural Science)(No.QKHJC-[2023]-YB066)the Key Laboratory of Smart Earth(No.KF2023YB04-02)the Fundamental Research Funds for the Central Universities。
文摘The constitutive model is essential for predicting the deformation and stability of rocksoil mass.The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors.However,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain curves.This paper proposes a Bayesian analysis framework to address this issue.It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models.Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework.Moreover,the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated.Results show that reasonable assessments of the constitutive model parameter can be well realized.The variability of stress-strain curves is strongly related to the model prediction performance.The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation.Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.
基金National Key Research and Development Plan of China(2022YFC3600800)Shenzhen Medical Academy of Research and Translation(Grants C2302001)。
文摘Objectives This study aimed to quantify the impact of major chronic diseases on changes in healthy life expectancy(HLE)from 2011 to 2020 in China using an age-specific disability weights(DW)estimation method.Methods HLE at age 60(HLE_(60))was used as the indicator of HLE in China.Cause-specific mortality rates were obtained from the cause-of-death database of the National Health Commission.Selfreported disease and disability status were derived from the China Health and Retirement Longitudinal Study.A total of 55,861 participants were included for DW estimation.Rates of disability,which was assessed using the Activities of Daily Living questionnaires,were estimated using data from 5,465 participants in 2011 and 9,910 participants in 2020.Age-specific DWs were calculated using a Bayesian logistic regression model.Changes in HLE_(60) were decomposed into mortality and disability effects by cause,based on the estimated DWs.Results HLE_(60) in China increased by 0.83 years from 2011 to 2020.Ischemic heart disease(IHD)contributed the most to the decline in HLE_(60),remaining the leading cause of reduction in terms of mortality effects.Diabetes showed the greatest impact on HLE_(60) due to disability,followed by stroke.The largest sex disparities in HLE_(60) were associated with disability from arthritis.Conclusion HLE_(60) in China improved from 2011 to 2020 and IHD remained the leading contributor to its decline,particularly through increased mortality.Disabilities related to diabetes,stroke,and arthritis had significant negative impacts.These findings highlight the need to strengthen integrated chronic disease prevention and rehabilitation services at community health centers.
基金co-supported by the National Natural Science Foundation of China (51875015,51620105010,51675019)Natural Science Foundation of Beijing Municipality(L171003)。
文摘With several attractive properties, rotary lip seals are widely used in aircraft utility system, and their reliability estimation has drawn more and more attention. This work proposes a reliability estimation approach based on time-varying dependence analysis. The dependence between the two performance indicators of rotary lip seals, namely leakage rate and friction torque, is modeled by time-varying copula function with polynomial to denote the time-varying parameters, and an efficient copula selection approach is utilized to select the optimal copula function. Parameter estimation is carried out based on a Bayesian method and the reliability during the whole lifetime is calculated based on a Monte Carlo method. Degradation test for rotary lip seal is conducted and the proposed model is validated by test data. The optimal copula function and optimal order of polynomial are determined based on test data. Results show that this model is effective in estimating the reliability of rotary lip seals and can achieve a better goodness of fit.
基金jointly funded by the National Natural Science Foundation of China (Grant No.41274052)the Seismological Research Project of China (Grant No.201208009)financially supported by Peking University President’s Research Funding for undergraduate students (2012–2013)
文摘In this study, we adopt an improved Bayesian approach based on free-knot B-spline bases to study the spatial and temporal distribution of the b-value. Synthetic tests show that the improved Bayesian approach has a superior performance compared to the Bayesian approach as well as the widely used maximum likelihood estimation （MLE） method in fitting the real variation of b-values. We then apply the improved Bayesian approach to North China and find that the b-value has a clear relevance to seismicity. Temporal changes of b-values are also investigated in two specific areas of North China. We interpret sharp decreases in the b-values as useful messages in earthquake hazard analysis.
基金HS Lee’s supported by Sejong University.TY Kim’s work was supported by a grant from the National Research Foundation of Korea(NRF-2019R1F1A1060152)。
文摘This study proposed a new analytical approach to identify the excessive comovement of two markets as contagion.This goal is achieved by linking latent-factor and single-equation error correction models and evaluating the breaks in the short-and long-term relationships and correlatedness in the linked model.The results demonstrated that a short-term relationship representing the market speed ratio between two markets plays a key role in contagion dynamics.When a long-term relationship or correlatedness is broken(comovement change)due to a break in the short-term relationship(market speed ratio),contagion is highly likely and should be formally declared.Bayesian posterior probabilities were calculated to determine the cause.Furthermore,this study applied this analytical Bayesian approach to empirically test the contagion effects of the U.S.stock market during the global financial crisis between 2007 and 2009 using 22 developed equity markets.
文摘Although the degree of mate competition, given extreme differences in sex ratio, explains much of the pattern of male-biased size dimorphism among diverse taxa, it fails for some species which have potential for intense male competition for mates and yet exhibit little or no sexual size dimorphism （SSD）. This fact suggest that species with low SSD should be express the effect of evolutionary pressure in non-obvious geometrical shape promoted by sex ratio in an evolutionary time scale. To evaluate this hypothesis we used phylogenetic comparative method in a Bayesian framework to investigate the evolution of SSD and the role of sex ratio at inter-specific level in the species of Ceroglossus （Coleoptera： Carabidae）. In our results the proportion farthest from 1：1 is associated with more disparate body shape, even though the entire group has minimum variation in sex ratio, which is an intrinsic life history character of this group considering its phylogenetic conservatism or phylogenetic signal. We suggest that the sex ratio has determined the dimorphism degree during evolution of this group, since both traits have increased or decreased together during the species divergence （i.e. positive phylogenetic correlation： r2=0.85）. We suggest that morphological studies of SSD will benefit from using comparative method with Bayesian approaches to assess the effect of phylogenetic history and its uncertainty. Finally, this will be allow to researchers to quantify the uncertainty of specific evolutionary hypotheses accounting for observed sexual dimorphism patterns.
文摘Quantifying the tool–tissue interaction forces in surgery can be utilized in the training of inexperienced surgeons,assist them better use surgical tools and avoid applying excessive pressures.The voltages read from strain gauges are used to approximate the unknown values of implemented forces.To this objective,the force-voltage connection must be quantified in order to evaluate the interaction forces during surgery.The progress of appropriate statistical learning approaches to describe the link between the genuine force applied on the tissue and numerous outputs obtained from sensors installed on surgical equipment is a key problem.In this study,different probabilistic approaches are used to evaluate the realized force on tissue using voltages read from strain gauges,including bootstrapping,Bayesian regression,weighted least squares regression,and multi-level modelling.Estimates from the proposed models are more precise than the maximum likelihood and restricted maximum likelihood techniques.The suggested methodologies are proficient of assessing tool-tissue interface forces with an adequate level of accuracy.
基金National Natural Science Foundation of China(No.70971133)
文摘By analyzing the shortage of reliability test design and thinking over the producer's risk and consumer's risk, the information fusion technology is used to set up a reliability test design model( RTDM). By analyzing the demands and constraint conditions of the RTDM and with applications of Bayesian approach and Monte Carlo method( MCM),this paper puts forward the exponential distributed subsystems and the information fusion technology among them. According to the posteriori risk criteria,formulas of producer's risk and consumer's risk were also inferred,and with the help of Matlab software,selection of the optimum test plan was solved. Finally,validity of the model had been proved by a test of series parallel system.
文摘Left-turn movements at signalized intersections pose significant safety risks to drivers and raise efficiency concerns for traffic operations in urban networks.Restricting left-turn movements at selected locations has been shown to be effective at improving operational efficiency and mitigating safety concerns.However,determining optimal locations to restrict left-turns is a complex combinatorial optimization problem that is compounded by the lack of analytical forms for the objective function and constraints,as well as poten-tial interdependencies among the decision variables.Following the common solution para-digm for this type of optimization problems,this paper presents a novel Bayesian approach that utilizes dictionary-based embeddings,and is tailored for high-dimensional combina-torial(or even mixed)spaces.Simulation studies conducted using the Aimsun software under perfect or imperfect grid networks demonstrate that the presented method can con-sistently find promising left-turn restriction configurations that outperform the all-or-nothing strategies(to restrict all or none left-turn movements at all intersections),as well as the population based incremental learning algorithm.In addition,the presented method often does so with less simulation cost,thus showcasing its potential for efficient solution of more general traffic optimization problems.
基金Supported by the Natural Science Foundation of China(11401341,11271136 and 81530086)111 Project(B14019)+2 种基金Natural Science Foundation of Fujian Province,China(2015J05014,2016J01681 and 2017N0029)Scientific Research Training Program of Fujian Province University for Distinguished Young Scholar(2015)New Century Excellent Talents Support Project of Fujian Province University([2016]23)
文摘This paper introduces some Bayesian optimal design methods for step-stress accelerated life test planning with one accelerating variable, when the acceleration model is linear in the accelerated variable or its function, based on censored data from a log-location-scale distributions. In order to find the optimal plan,we propose different Monte Carlo simulation algorithms for different Bayesian optimal criteria. We present an example using the lognormal life distribution with Type-I censoring to illustrate the different Bayesian methods and to examine the effects of the prior distribution and sample size. By comparing the different Bayesian methods we suggest that when the data have large（small） sample size B1（τ）（B2（τ）） method is adopted. Finally, the Bayesian optimal plans are compared with the plan obtained by maximum likelihood method.
基金supported by National Natural Science Foundation of China (Grant No. 11371366)Doctoral Research Fund of Henan Polytechnic University (Grant No. 672103/001/147)
文摘Bayesian adaptive randomization has attracted increasingly attention in the literature and has been implemented in many phase II clinical trials. Doubly adaptive biased coin design(DBCD) is a superior choice in response-adaptive designs owing to its promising properties. In this paper, we propose a randomized design by combining Bayesian adaptive randomization with doubly adaptive biased coin design. By selecting a fixed tuning parameter, the proposed randomization procedure can target an explicit allocation proportion, and assign more patients to the better treatment simultaneously. Moreover, the proposed randomization is efficient to detect treatment differences. We illustrate the proposed design by its applications to both discrete and continuous responses, and evaluate its operating features through simulation studies.
