The head-related transfer function(HRTF)involves the cues for human auditory localization,which turns it into an essential item of virtual auditory display technology.In practice,the interpolation of HRTF is necessary...The head-related transfer function(HRTF)involves the cues for human auditory localization,which turns it into an essential item of virtual auditory display technology.In practice,the interpolation of HRTF is necessary for the virtual auditory display systems to achieve high spatial resolution.Traditional geometric-based interpolation methods are generally restrained by the spatial distribution of reference on HRTF.When the spatial distribution is sparse,the accuracy of interpolation decreases significantly.Therefore,an interpolation method using the common-pole/zero model and the fitting neural network is proposed.First,we propose a common-pole/zero model to represent HRTFs across multiple subjects,in which the low-dimensional features of the measured HRTFs are extracted.Then,for a new spatial direction,we predict the corresponding low-dimensional HRTF with a fitting neural network.Finally,we reconstruct the high-dimensional HRTF from the predicted low-dimensional HRTF.The simulation results suggest that the proposed method outperforms other interpolation methods such as Linear_AMBC,Bilinear_AMBC,and the Combination method.展开更多
基于MIKE ZERO 2020软件中的HD水动力学模块和AD对流扩散模块,建立郁江贵港市河段的水文、水质信息耦合模型,对郁江贵港河段的水位、流量以及污染物在水体中迁移扩散衰减情况进行了模拟分析。根据郁江近年来的水文资料对模型进行率定并...基于MIKE ZERO 2020软件中的HD水动力学模块和AD对流扩散模块,建立郁江贵港市河段的水文、水质信息耦合模型,对郁江贵港河段的水位、流量以及污染物在水体中迁移扩散衰减情况进行了模拟分析。根据郁江近年来的水文资料对模型进行率定并验证。将该模型应用于2023年6月21日~7月6日的洪水过程,结果表明,所建立的模型在率定和验证及应用期间模拟效果均表现良好,模拟精度高。充分证明该模型适用于模拟郁江贵港河段的水文、水质信息变化特征,为提高贵港市防洪、水情预报及水污染预测提供了重要的技术支撑。展开更多
The mortality of trees across diameter class model is a useful tool for predicting changes in stand structure.Mortality data commonly contain a large fraction of zeros and general discrete models thus show more errors...The mortality of trees across diameter class model is a useful tool for predicting changes in stand structure.Mortality data commonly contain a large fraction of zeros and general discrete models thus show more errors.Based on the traditional Poisson model and the negative binomial model,different forms of zero-inflated and hurdle models were applied to spruce-fir mixed forests data to simulate the number of dead trees.By comparing the residuals and Vuong test statistics,the zero-inflated negative binomial model performed best.A random effect was added to improve the model accuracy;however,the mixed-effects zero-inflated model did not show increased advantages.According to the model principle,the zeroinflated negative binomial model was the most suitable,indicating that the"0"events in this study,mainly from the sample"0",i.e.,the zero mortality data,are largely due to the limitations of the experimental design and sample selection.These results also show that the number of dead trees in the diameter class is positively correlated with the number of trees in that class and the mean stand diameter,and inversely related to class size,and slope and aspect of the site.展开更多
A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus...A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.展开更多
In a typical Kenyan HIV clinical setting, there is a likelihood of registering many zeros during the routine monthly data collection of new HIV infections among HIV exposed infants (HEI). This is attributed to the imp...In a typical Kenyan HIV clinical setting, there is a likelihood of registering many zeros during the routine monthly data collection of new HIV infections among HIV exposed infants (HEI). This is attributed to the implementation of the prevention of mother to child transmission (PMTCT) policies. However, even though the PMTCT policy is implemented uniformly across all public health facilities, implementation naturally differs from every facility due to differential health systems and infrastructure. This leads to structured zero among reported positive HEI (where PMTCT implementation is optimum) and non-structured zero among reported positive HEI (where PMTCT implementation is not optimum). Hence the classical zero-inflated and hurdle models that do not account for the abundance of structured and non-structured zeros in the data can give misleading results. The purpose of this study is to systematically compare performance of the various zero-inflated models with an application to HIV Exposed Infants (HEI) in the context of structured and unstructured zeros. We revisit zero-inflated, hurdle models, Poisson and negative binomial count models and conduct the simulations by varying sample size and levels of abundance zeros. Results from simulation study and real data analysis of exposed infant diagnosis show the negative binomial emerging as the best performing model when fitting data with both structured and non-structured zeros under various settings.展开更多
Abstract Accurate simulation of seismic wave propaga- tion in complex geological structures is of particular interest nowadays. However conventional methods may fail to simulate realistic wavefields in environments wi...Abstract Accurate simulation of seismic wave propaga- tion in complex geological structures is of particular interest nowadays. However conventional methods may fail to simulate realistic wavefields in environments with great and rapid structural changes, due for instance to the presence of shadow zones, diffractions and/or edge effects. Different methods, developed to improve seismic model- ing, are typically tested on synthetic configurations against analytical solutions for simple canonical problems or ref- erence methods, or via direct comparison with real data acquired in situ. Such approaches have limitations,especially if the propagation occurs in a complex envi- ronment with strong-contrast reflectors and surface irreg- ularities, as it can be difficult to determine the method which gives the best approximation of the ＂real＂ solution, or to interpret the results obtained without an a priori knowledge of the geologic environment. An alternative approach for seismics consists in comparing the synthetic data with high-quality data collected in laboratory experi- ments under controlled conditions for a known configuration. In contrast with numerical experiments, laboratory data possess many of the characteristics of field data, as real waves propagate through models with no numerical approximations. We thus present a comparison of laboratory-scaled measurements of 3D zero-offset wave reflection of broadband pulses from a strong topographic environment immersed in a water tank with numerical data simulated by means of a spectral-element method and a discretized Kirchhoff integral method. The results indicate a good quantitative fit in terms of time arrivals and acceptable fit in amplitudes for all datasets.展开更多
Zero-Inflated Poisson model has found a wide variety of applications in recent years in statistical analyses of count data, especially in count regression models. Zero-Inflated Poisson model is characterized in this p...Zero-Inflated Poisson model has found a wide variety of applications in recent years in statistical analyses of count data, especially in count regression models. Zero-Inflated Poisson model is characterized in this paper through a linear differential equation satisfied by its probability generating function [1] [2].展开更多
This paper discusses the estimation of parameters in the zero-inflated Poisson (ZIP) model by the method of moments. The method of moments estimators (MMEs) are analytically compared with the maximum likelihood estima...This paper discusses the estimation of parameters in the zero-inflated Poisson (ZIP) model by the method of moments. The method of moments estimators (MMEs) are analytically compared with the maximum likelihood estimators (MLEs). The results of a modest simulation study are presented.展开更多
A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model wi...A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars.展开更多
基金the National Key R&D Program of China(No.2017YFB1002803)National Nature Science Foundation of China(No.61801334,No.61761044)Basic Research Project of Science and Technology Plan of Shenzhen(JCYJ20170818143246278)。
文摘The head-related transfer function(HRTF)involves the cues for human auditory localization,which turns it into an essential item of virtual auditory display technology.In practice,the interpolation of HRTF is necessary for the virtual auditory display systems to achieve high spatial resolution.Traditional geometric-based interpolation methods are generally restrained by the spatial distribution of reference on HRTF.When the spatial distribution is sparse,the accuracy of interpolation decreases significantly.Therefore,an interpolation method using the common-pole/zero model and the fitting neural network is proposed.First,we propose a common-pole/zero model to represent HRTFs across multiple subjects,in which the low-dimensional features of the measured HRTFs are extracted.Then,for a new spatial direction,we predict the corresponding low-dimensional HRTF with a fitting neural network.Finally,we reconstruct the high-dimensional HRTF from the predicted low-dimensional HRTF.The simulation results suggest that the proposed method outperforms other interpolation methods such as Linear_AMBC,Bilinear_AMBC,and the Combination method.
文摘基于MIKE ZERO 2020软件中的HD水动力学模块和AD对流扩散模块,建立郁江贵港市河段的水文、水质信息耦合模型,对郁江贵港河段的水位、流量以及污染物在水体中迁移扩散衰减情况进行了模拟分析。根据郁江近年来的水文资料对模型进行率定并验证。将该模型应用于2023年6月21日~7月6日的洪水过程,结果表明,所建立的模型在率定和验证及应用期间模拟效果均表现良好,模拟精度高。充分证明该模型适用于模拟郁江贵港河段的水文、水质信息变化特征,为提高贵港市防洪、水情预报及水污染预测提供了重要的技术支撑。
基金supported by the "948" Project of the State Forestry Administration of China(No.2013-4-66)
文摘The mortality of trees across diameter class model is a useful tool for predicting changes in stand structure.Mortality data commonly contain a large fraction of zeros and general discrete models thus show more errors.Based on the traditional Poisson model and the negative binomial model,different forms of zero-inflated and hurdle models were applied to spruce-fir mixed forests data to simulate the number of dead trees.By comparing the residuals and Vuong test statistics,the zero-inflated negative binomial model performed best.A random effect was added to improve the model accuracy;however,the mixed-effects zero-inflated model did not show increased advantages.According to the model principle,the zeroinflated negative binomial model was the most suitable,indicating that the"0"events in this study,mainly from the sample"0",i.e.,the zero mortality data,are largely due to the limitations of the experimental design and sample selection.These results also show that the number of dead trees in the diameter class is positively correlated with the number of trees in that class and the mean stand diameter,and inversely related to class size,and slope and aspect of the site.
基金Project(2014ZX04014-011)supported by State Key Science&Technology Program of ChinaProject([2016]414)supported by the 13th Five-year Program of Education Department of Jilin Province,China
文摘A new problem that classical statistical methods are incapable of solving is reliability modeling and assessment when multiple numerical control machine tools(NCMTs) reveal zero failures after a reliability test. Thus, the zero-failure data form and corresponding Bayesian model are developed to solve the zero-failure problem of NCMTs, for which no previous suitable statistical model has been developed. An expert-judgment process that incorporates prior information is presented to solve the difficulty in obtaining reliable prior distributions of Weibull parameters. The equations for the posterior distribution of the parameter vector and the Markov chain Monte Carlo(MCMC) algorithm are derived to solve the difficulty of calculating high-dimensional integration and to obtain parameter estimators. The proposed method is applied to a real case; a corresponding programming code and trick are developed to implement an MCMC simulation in Win BUGS, and a mean time between failures(MTBF) of 1057.9 h is obtained. Given its ability to combine expert judgment, prior information, and data, the proposed reliability modeling and assessment method under the zero failure of NCMTs is validated.
文摘In a typical Kenyan HIV clinical setting, there is a likelihood of registering many zeros during the routine monthly data collection of new HIV infections among HIV exposed infants (HEI). This is attributed to the implementation of the prevention of mother to child transmission (PMTCT) policies. However, even though the PMTCT policy is implemented uniformly across all public health facilities, implementation naturally differs from every facility due to differential health systems and infrastructure. This leads to structured zero among reported positive HEI (where PMTCT implementation is optimum) and non-structured zero among reported positive HEI (where PMTCT implementation is not optimum). Hence the classical zero-inflated and hurdle models that do not account for the abundance of structured and non-structured zeros in the data can give misleading results. The purpose of this study is to systematically compare performance of the various zero-inflated models with an application to HIV Exposed Infants (HEI) in the context of structured and unstructured zeros. We revisit zero-inflated, hurdle models, Poisson and negative binomial count models and conduct the simulations by varying sample size and levels of abundance zeros. Results from simulation study and real data analysis of exposed infant diagnosis show the negative binomial emerging as the best performing model when fitting data with both structured and non-structured zeros under various settings.
基金the INSIS Institute of the French CNRS,Aix-Marseille Universitythe Carnot Star Institute,the VISTA Projectthe Norwegian Research Council through the ROSE Project for financial support
文摘Abstract Accurate simulation of seismic wave propaga- tion in complex geological structures is of particular interest nowadays. However conventional methods may fail to simulate realistic wavefields in environments with great and rapid structural changes, due for instance to the presence of shadow zones, diffractions and/or edge effects. Different methods, developed to improve seismic model- ing, are typically tested on synthetic configurations against analytical solutions for simple canonical problems or ref- erence methods, or via direct comparison with real data acquired in situ. Such approaches have limitations,especially if the propagation occurs in a complex envi- ronment with strong-contrast reflectors and surface irreg- ularities, as it can be difficult to determine the method which gives the best approximation of the ＂real＂ solution, or to interpret the results obtained without an a priori knowledge of the geologic environment. An alternative approach for seismics consists in comparing the synthetic data with high-quality data collected in laboratory experi- ments under controlled conditions for a known configuration. In contrast with numerical experiments, laboratory data possess many of the characteristics of field data, as real waves propagate through models with no numerical approximations. We thus present a comparison of laboratory-scaled measurements of 3D zero-offset wave reflection of broadband pulses from a strong topographic environment immersed in a water tank with numerical data simulated by means of a spectral-element method and a discretized Kirchhoff integral method. The results indicate a good quantitative fit in terms of time arrivals and acceptable fit in amplitudes for all datasets.
文摘Zero-Inflated Poisson model has found a wide variety of applications in recent years in statistical analyses of count data, especially in count regression models. Zero-Inflated Poisson model is characterized in this paper through a linear differential equation satisfied by its probability generating function [1] [2].
文摘This paper discusses the estimation of parameters in the zero-inflated Poisson (ZIP) model by the method of moments. The method of moments estimators (MMEs) are analytically compared with the maximum likelihood estimators (MLEs). The results of a modest simulation study are presented.
文摘A new covariate dependent zero-truncated bivariate Poisson model is proposed in this paper employing generalized linear model. A marginal-conditional approach is used to show the bivariate model. The proposed model with estimation procedure and tests for goodness-of-fit and under (or over) dispersion are shown and applied to road safety data. Two correlated outcome variables considered in this study are number of cars involved in an accident and number of casualties for given number of cars.
