In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean func...In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean function with the classical kernel estimator,the proposed test statistics are built upon a modified minimum distance between a nonparametric fit and a parametric estimator under the null hypothesis for the variance function.Asymptotic properties of the estimator of the parameters in the variance function are discussed,and the large sample distribution of the test statistics under the null hypothesis is established,as well as the consistency and the power under some local alternative hypotheses.Extensive numerical studies demonstrate that the proposed test procedures have satisfactory finite sample performance.Finally,two real data examples further showcase the effectiveness of the proposed test in real applications.展开更多
Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitionin...Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.展开更多
The valuation of financial derivatives often assumes risk neutrality with respect to the risk-neutral martingale measure,which prevents arbitrage opportunities.However,casual traders may still incur substantial losses...The valuation of financial derivatives often assumes risk neutrality with respect to the risk-neutral martingale measure,which prevents arbitrage opportunities.However,casual traders may still incur substantial losses when trading at this risk-neutral price,especially when the price has to be paid now and the payoff is only realized in the future.This study proposes a new valuation framework that provides risksensitive investors with an additional safeguard.The proposed framework embraces a worst-case perspective while exploiting the underlier’s stochastic process,representing a combination of robust optimization and stochastic programming.Notably,it aims to mitigate losses in the likelier scenarios of the underlying asset’s prices.When the underlier’s returns are independent and lognormally but not necessarily identically distributed,our approach for pricing variance and volatility swaps could be greatly simplified,benefit from parallel computing,and be solved by a two-dimensional grid search.We further derive a closed-form solution in some special stationary cases and provide experimental results to highlight the effect of risk aversion on fending off sizable trading losses.展开更多
The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained expe...The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained experimentally through tests on specimens under multiaxial loading with that calculated by the variance method. In the statistical approach criteria, several methods have been developed but we have presented only one method, namely the variance method using the equivalent stress. She assumes that the fracture plane orientation is the one on which the variance of the equivalent stress is maximum. Three types of equivalent stress are defined for this method [1]: normal stress, shear stress and combined normal and shear stress. The results obtained were compared with experimental results for multiaxial cyclic stress states, and it emerges that the variance method for the case of combined loading is conservative as it gives a better prediction of the fracture plane.展开更多
In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance c...In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.展开更多
Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control ...Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.展开更多
[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate diff...[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate different P. grandiflorum and breeding new varieties. [ Method] According to shape morphological characters of capsule from the same population of perennial purple P. gandiflorum, seven types of distinct di- versity capsule were selected, variance analysis and multiple comparison on the length, diameter, length/diameter of the different types of capsule were carried out. [ Result] There is unicolor and bicolor, even trichrome, among main color was brown and purple. Capsule shape was main cone, furthermore, containing long roller type, spheroidicity and sphericity. [ Conclusion] P. gandiflorum capsule was divided into long form, short form and middle type from length/diameter size in perennial culture P. gandiflorum population.展开更多
An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances ...An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...展开更多
Multi-dimensional arrays are referred to as tensors.Tensor-valued predictors are commonly encountered in modern biomedical applications,such as electroencephalogram(EEG),magnetic resonance imaging(MRI),functional MRI(...Multi-dimensional arrays are referred to as tensors.Tensor-valued predictors are commonly encountered in modern biomedical applications,such as electroencephalogram(EEG),magnetic resonance imaging(MRI),functional MRI(fMRI),diffusion-weighted MRI,and longitudinal health data.In survival analysis,it is both important and challenging to integrate clinically relevant information,such as gender,age,and disease state along with medical imaging tensor data or longitudinal health data to predict disease outcomes.Most existing higher-order sufficient dimension reduction regressions for matrix-or array-valued data focus solely on tensor data,often neglecting established clinical covariates that are readily available and known to have predictive value.Based on the idea of Folded-Minimum Average Variance Estimation(Folded-MAVE:Xue and Yin,2014),the authors propose a new method,Partial Dimension Folded-MAVE(PF-MAVE),to address regression mean functions with tensor-valued covariates while simultaneously incorporating clinical covariates,which are typically categorical variables.Theorems and simulation studies demonstrate the importance of incorporating these categorical clinical predictors.A survival analysis of a longitudinal study of primary biliary cirrhosis(PBC)data is included for illustration of the proposed method.展开更多
To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the disea...To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the diseased samples collected from five Chinese herbal medicine planting areas in Heilongjiang Province between the years of 2021 and 2022.Repetitive extragenic palindromic polymerase chain reaction(Rep–PCR)was used to amplify 57 isolates of gray leaf spot pathogen on D.dasycarpus from different regions of Heilongjiang Province.The polymorphic bands amplified by three sets of primers accounted for more than 80%.Cluster analysis results showed that at a similarity coefficient of 0.67,the gray leaf spot pathogen on D.dasycarpus in Heilongjiang Province could be divided into five major genetic groups.Genetic diversity parameter analysis indicated that there were certain differences in genetic richness among the geographic populations of gray leaf spot pathogen on D.dasycarpus from different regions.Analysis of molecular variance(AMOVA)revealed that genetic variation among strains mainly originated within populations.The genetic differentiation and relationships of gray leaf spot pathogen on D.dasycarpus from different geographic regions of Heilongjiang Province indicated that genetic differentiation and kinship among populations were somewhat related to their geographic distance.The greater the geographic distance,the higher the genetic differentiation coefficient,and the lower the genetic uniformity among populations.展开更多
This paper is concerned with the control performance assessment based on the multivariable generalized minimum variance benchmark.An explicit expression for the feedback controller-invariant(the generalized minimum va...This paper is concerned with the control performance assessment based on the multivariable generalized minimum variance benchmark.An explicit expression for the feedback controller-invariant(the generalized minimum variance)term of the multivariable control system is obtained,which is used as a standard benchmark for the assessment of the control performance for multi input multi output(MIMO)process.The proposed approach is based on the multivariable minimum variance benchmark.In comparison with the minimum variance benchmark, the developed method is more reasonable and practical for the control performance assessment of multivariable systems.The approach is illustrated by a simulation example and an industrial application.展开更多
This paper describes the application of the variance method for flux estimation over a mixed agricultural region in China. Eddy covariance and flux variance measurements were conducted in a near-surface layer over a n...This paper describes the application of the variance method for flux estimation over a mixed agricultural region in China. Eddy covariance and flux variance measurements were conducted in a near-surface layer over a non-uniform land surface in the central plain of China from 7 June to 20 July 2002. During this period, the mean canopy height was about 0.50 m. The study site consisted of grass （10% of area）, beans （15%）, corn （15%） and rice （60%）. Under unstable conditions, the standard deviations of temperature and water vapor density （normalized by appropriate scaling parameters）, observed by a single instrument, followed the Monin-Obukhov similarity theory. The similarity constants for heat （CT） and water vapor （Cq） were 1.09 and 1.49, respectively. In comparison with direct measurements using eddy covariance techniques, the flux variance method, on average, underestimated sensible heat flux by 21% and latent heat flux by 24%, which may be attributed to the fact that the observed slight deviations （20% or 30% at most） of the similarity ＂constants＂ may be within the expected range of variation of a single instrument from the generally-valid relations.展开更多
The phenotypir characteristies of the phs trees of Larix principis ruppre chtii such as stem form,branch angk,branch/stem ratio,bra nch density,the crowmn width,crown leng th,number of short branch over 5-cm branch se...The phenotypir characteristies of the phs trees of Larix principis ruppre chtii such as stem form,branch angk,branch/stem ratio,bra nch density,the crowmn width,crown leng th,number of short branch over 5-cm branch se gment in length,and the leaf number of each short branch were investigated in seed orchard in the Changcheng Mountain,Shaanxi Province.According to the morphological characteis,the phs tree clones of Lanix principis-rupprechti were classified into 4 natual types:the narrow-dense-crown type,wide-dense-crown type,wide-sparse-ciown type,and the narow-spase-crown type.The re sult ofthe cluster analysis showed there was a very significant difference in tree growth among the four na turaltypes.Whie comparingthe tree growth of four na twral types for the last ten yeas,it was found that the performance order ofvanious types fiom good toba d i as folbws:the narrow-dense crown type the wide-dense crown type the wide-spase crown type the narow-spasecrown type.The plus trees of narrow-dense-ciown,as a fine type,should be paid great attention to production and pre pared topo pula nize.展开更多
Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor va...Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor variables. Also, we have highlighted systematic ways to identify suppression effect in multiple regressions using statistics such as: R2, sum of squares, regression weight and comparing zero-order correlations with Variance Inflation Factor (VIF) respectively. We also establish that suppression effect is a function of multicollinearity;however, a suppressor variable should only be allowed in a regression analysis if its VIF is less than five (5).展开更多
The main problem of particle filter(PF)in nonlinear state estimation is the particle degeneracy.Resampling operation solves degeneracy to some extent,but it results in the problem of sample impoverishment.Variance red...The main problem of particle filter(PF)in nonlinear state estimation is the particle degeneracy.Resampling operation solves degeneracy to some extent,but it results in the problem of sample impoverishment.Variance reduction technique is proposed to deal with the degeneration phenomenon in this paper,which reduces the variance of the particle weights by selecting an exponential fading factor,and this factor can be chosen adaptively and iteratively in terms of the effective particle number.A theorem is presented to show that this idea is feasible,and the procedure of this new adaptive particle filtering(APF)algorithm is presented.Then,the principle of parameter choice and the limitation of APF are discussed.Finally,a numerical example illustrates that the proposed APF has a higher estimation precision than particle filter-sampling importance resampling(PF-SIR),genetic particle filter(GPF),and particle swarm optimization particle filter(PSOPF),while the computation load of APF is mild.展开更多
The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of R...The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm （VFDA）. Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to improve its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in indoor environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.展开更多
This article studies the optimal proportional reinsurance and investment problem under a constant elasticity of variance （CEV） model. Assume that the insurer＇s surplus process follows a jump-diffusion process, the ...This article studies the optimal proportional reinsurance and investment problem under a constant elasticity of variance （CEV） model. Assume that the insurer＇s surplus process follows a jump-diffusion process, the insurer can purchase proportional reinsurance from the reinsurer via the variance principle and invest in a risk-free asset and a risky asset whose price is modeled by a CEV model. The diffusion term can explain the uncertainty associated with the surplus of the insurer or the additional small claims. The objective of the insurer is to maximize the expected exponential utility of terminal wealth. This optimization problem is studied in two cases depending on the diffusion term＇s explanation. In all cases, by using techniques of stochastic control theory, closed-form expressions for the value functions and optimal strategies are obtained.展开更多
Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity ...Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.12071267。
文摘In this paper,the authors propose a class of test procedures to check the fitness of parametric forms of the variance function in regression models when the mean function is unknown.By evaluating the unknown mean function with the classical kernel estimator,the proposed test statistics are built upon a modified minimum distance between a nonparametric fit and a parametric estimator under the null hypothesis for the variance function.Asymptotic properties of the estimator of the parameters in the variance function are discussed,and the large sample distribution of the test statistics under the null hypothesis is established,as well as the consistency and the power under some local alternative hypotheses.Extensive numerical studies demonstrate that the proposed test procedures have satisfactory finite sample performance.Finally,two real data examples further showcase the effectiveness of the proposed test in real applications.
基金supported by the Biological Breeding-Major Projects in National Science and Technology(No.2023ZD0404405)the Earmarked Fund for China Agriculture Research System(No.CARS-pig-35)+2 种基金the National Natural Science Foundation of China(No.3227284,32302708)the 2115 Talent Development Program of China Agricultural University,the Chinese Universities Scientific Fund(No.2023TC196)the Seed Industry Revitalization Action Project of Guangdong Province(No.2024-XPY-06-001)。
文摘Background Multibreed genomic prediction(MBGP)is crucial for improving prediction accuracy for breeds with small populations,for which limited data are often available.Recent studies have demonstrated that partitioning the genome into nonoverlapping blocks to model heterogeneous genetic(co)variance in multitrait models can achieve higher joint prediction accuracy.However,the block partitioning method,a key factor influencing model performance,has not been extensively explored.Results We introduce mbBayesABLD,a novel Bayesian MBGP model that partitions each chromosome into nonoverlapping blocks on the basis of linkage disequilibrium(LD)patterns.In this model,marker effects within each block are assumed to follow normal distributions with block-specific parameters.We employ simulated data as well as empirical datasets from pigs and beans to assess genomic prediction accuracy across different models using cross-validation.The results demonstrate that mbBayesABLD significantly outperforms conventional MBGP models,such as GBLUP and BayesR.For the meat marbling score trait in pigs,compared with GBLUP,which does not account for heterogeneous genetic(co)variance,mbBayesABLD improves the prediction accuracy for the small-population breed Landrace by 15.6%.Furthermore,our findings indicate that a moderate level of similarity in LD patterns between breeds(with an average correlation of 0.6)is sufficient to improve the prediction accuracy of the target breed.Conclusions This study presents a novel LD block-based approach for multibreed genomic prediction.Our work provides a practical tool for livestock breeding programs and offers new insights into leveraging genetic diversity across breeds for improved genomic prediction.
基金supported by the Ministry of Education,Singapore,under its Academic Research Fund Tier 2 Grant MOE-T2EP20222-0003.
文摘The valuation of financial derivatives often assumes risk neutrality with respect to the risk-neutral martingale measure,which prevents arbitrage opportunities.However,casual traders may still incur substantial losses when trading at this risk-neutral price,especially when the price has to be paid now and the payoff is only realized in the future.This study proposes a new valuation framework that provides risksensitive investors with an additional safeguard.The proposed framework embraces a worst-case perspective while exploiting the underlier’s stochastic process,representing a combination of robust optimization and stochastic programming.Notably,it aims to mitigate losses in the likelier scenarios of the underlying asset’s prices.When the underlier’s returns are independent and lognormally but not necessarily identically distributed,our approach for pricing variance and volatility swaps could be greatly simplified,benefit from parallel computing,and be solved by a two-dimensional grid search.We further derive a closed-form solution in some special stationary cases and provide experimental results to highlight the effect of risk aversion on fending off sizable trading losses.
文摘The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained experimentally through tests on specimens under multiaxial loading with that calculated by the variance method. In the statistical approach criteria, several methods have been developed but we have presented only one method, namely the variance method using the equivalent stress. She assumes that the fracture plane orientation is the one on which the variance of the equivalent stress is maximum. Three types of equivalent stress are defined for this method [1]: normal stress, shear stress and combined normal and shear stress. The results obtained were compared with experimental results for multiaxial cyclic stress states, and it emerges that the variance method for the case of combined loading is conservative as it gives a better prediction of the fracture plane.
基金supported by the National Natural Science Foundation of China(No.42174011)。
文摘In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.
文摘Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.
文摘[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate different P. grandiflorum and breeding new varieties. [ Method] According to shape morphological characters of capsule from the same population of perennial purple P. gandiflorum, seven types of distinct di- versity capsule were selected, variance analysis and multiple comparison on the length, diameter, length/diameter of the different types of capsule were carried out. [ Result] There is unicolor and bicolor, even trichrome, among main color was brown and purple. Capsule shape was main cone, furthermore, containing long roller type, spheroidicity and sphericity. [ Conclusion] P. gandiflorum capsule was divided into long form, short form and middle type from length/diameter size in perennial culture P. gandiflorum population.
基金National Basic Research Program of China (JW132006093)
文摘An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...
文摘Multi-dimensional arrays are referred to as tensors.Tensor-valued predictors are commonly encountered in modern biomedical applications,such as electroencephalogram(EEG),magnetic resonance imaging(MRI),functional MRI(fMRI),diffusion-weighted MRI,and longitudinal health data.In survival analysis,it is both important and challenging to integrate clinically relevant information,such as gender,age,and disease state along with medical imaging tensor data or longitudinal health data to predict disease outcomes.Most existing higher-order sufficient dimension reduction regressions for matrix-or array-valued data focus solely on tensor data,often neglecting established clinical covariates that are readily available and known to have predictive value.Based on the idea of Folded-Minimum Average Variance Estimation(Folded-MAVE:Xue and Yin,2014),the authors propose a new method,Partial Dimension Folded-MAVE(PF-MAVE),to address regression mean functions with tensor-valued covariates while simultaneously incorporating clinical covariates,which are typically categorical variables.Theorems and simulation studies demonstrate the importance of incorporating these categorical clinical predictors.A survival analysis of a longitudinal study of primary biliary cirrhosis(PBC)data is included for illustration of the proposed method.
基金Supported by the Green Plant Protection Project of Heilongjiang Province(2130108)Key R&D Program Project of Heilongjiang Province(2023ZX02B0502)Heilongjiang Province Rice Modern Agriculture Industry Technology Collaborative Innovation System Project(2025)。
文摘To ascertain the genetic diversity of gray leaf spot pathogen on Dictamnus dasycarpus popoulation in Heilongjiang Province,a total of 57 strains of Paracercospora dictamnicola were isolated and purified from the diseased samples collected from five Chinese herbal medicine planting areas in Heilongjiang Province between the years of 2021 and 2022.Repetitive extragenic palindromic polymerase chain reaction(Rep–PCR)was used to amplify 57 isolates of gray leaf spot pathogen on D.dasycarpus from different regions of Heilongjiang Province.The polymorphic bands amplified by three sets of primers accounted for more than 80%.Cluster analysis results showed that at a similarity coefficient of 0.67,the gray leaf spot pathogen on D.dasycarpus in Heilongjiang Province could be divided into five major genetic groups.Genetic diversity parameter analysis indicated that there were certain differences in genetic richness among the geographic populations of gray leaf spot pathogen on D.dasycarpus from different regions.Analysis of molecular variance(AMOVA)revealed that genetic variation among strains mainly originated within populations.The genetic differentiation and relationships of gray leaf spot pathogen on D.dasycarpus from different geographic regions of Heilongjiang Province indicated that genetic differentiation and kinship among populations were somewhat related to their geographic distance.The greater the geographic distance,the higher the genetic differentiation coefficient,and the lower the genetic uniformity among populations.
基金Supported by the National High Technology Research and Development Program of China(2008AA042902)the National Basic Research Program of China(2007CB714006)the Graduate Creative Research Program of Zhejiang Province (YK2008024)
文摘This paper is concerned with the control performance assessment based on the multivariable generalized minimum variance benchmark.An explicit expression for the feedback controller-invariant(the generalized minimum variance)term of the multivariable control system is obtained,which is used as a standard benchmark for the assessment of the control performance for multi input multi output(MIMO)process.The proposed approach is based on the multivariable minimum variance benchmark.In comparison with the minimum variance benchmark, the developed method is more reasonable and practical for the control performance assessment of multivariable systems.The approach is illustrated by a simulation example and an industrial application.
文摘This paper describes the application of the variance method for flux estimation over a mixed agricultural region in China. Eddy covariance and flux variance measurements were conducted in a near-surface layer over a non-uniform land surface in the central plain of China from 7 June to 20 July 2002. During this period, the mean canopy height was about 0.50 m. The study site consisted of grass （10% of area）, beans （15%）, corn （15%） and rice （60%）. Under unstable conditions, the standard deviations of temperature and water vapor density （normalized by appropriate scaling parameters）, observed by a single instrument, followed the Monin-Obukhov similarity theory. The similarity constants for heat （CT） and water vapor （Cq） were 1.09 and 1.49, respectively. In comparison with direct measurements using eddy covariance techniques, the flux variance method, on average, underestimated sensible heat flux by 21% and latent heat flux by 24%, which may be attributed to the fact that the observed slight deviations （20% or 30% at most） of the similarity ＂constants＂ may be within the expected range of variation of a single instrument from the generally-valid relations.
文摘The phenotypir characteristies of the phs trees of Larix principis ruppre chtii such as stem form,branch angk,branch/stem ratio,bra nch density,the crowmn width,crown leng th,number of short branch over 5-cm branch se gment in length,and the leaf number of each short branch were investigated in seed orchard in the Changcheng Mountain,Shaanxi Province.According to the morphological characteis,the phs tree clones of Lanix principis-rupprechti were classified into 4 natual types:the narrow-dense-crown type,wide-dense-crown type,wide-sparse-ciown type,and the narow-spase-crown type.The re sult ofthe cluster analysis showed there was a very significant difference in tree growth among the four na turaltypes.Whie comparingthe tree growth of four na twral types for the last ten yeas,it was found that the performance order ofvanious types fiom good toba d i as folbws:the narrow-dense crown type the wide-dense crown type the wide-spase crown type the narow-spasecrown type.The plus trees of narrow-dense-ciown,as a fine type,should be paid great attention to production and pre pared topo pula nize.
文摘Suppression effect in multiple regression analysis may be more common in research than what is currently recognized. We have reviewed several literatures of interest which treats the concept and types of suppressor variables. Also, we have highlighted systematic ways to identify suppression effect in multiple regressions using statistics such as: R2, sum of squares, regression weight and comparing zero-order correlations with Variance Inflation Factor (VIF) respectively. We also establish that suppression effect is a function of multicollinearity;however, a suppressor variable should only be allowed in a regression analysis if its VIF is less than five (5).
基金Supported by National Natural Science Foundation of China(6063403060702066)Aerospace Science Foundation(20090853013)Doctoral Program Foundation of China(20060699032)
文摘The main problem of particle filter(PF)in nonlinear state estimation is the particle degeneracy.Resampling operation solves degeneracy to some extent,but it results in the problem of sample impoverishment.Variance reduction technique is proposed to deal with the degeneration phenomenon in this paper,which reduces the variance of the particle weights by selecting an exponential fading factor,and this factor can be chosen adaptively and iteratively in terms of the effective particle number.A theorem is presented to show that this idea is feasible,and the procedure of this new adaptive particle filtering(APF)algorithm is presented.Then,the principle of parameter choice and the limitation of APF are discussed.Finally,a numerical example illustrates that the proposed APF has a higher estimation precision than particle filter-sampling importance resampling(PF-SIR),genetic particle filter(GPF),and particle swarm optimization particle filter(PSOPF),while the computation load of APF is mild.
基金supported by the National Natural Science Foundation of China(6120200461472192)+1 种基金the Special Fund for Fast Sharing of Science Paper in Net Era by CSTD(2013116)the Natural Science Fund of Higher Education of Jiangsu Province(14KJB520014)
文摘The multipath effect and movements of people in indoor environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength indication （RSSI） and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm （VFDA）. Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to improve its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in indoor environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.
文摘This article studies the optimal proportional reinsurance and investment problem under a constant elasticity of variance （CEV） model. Assume that the insurer＇s surplus process follows a jump-diffusion process, the insurer can purchase proportional reinsurance from the reinsurer via the variance principle and invest in a risk-free asset and a risky asset whose price is modeled by a CEV model. The diffusion term can explain the uncertainty associated with the surplus of the insurer or the additional small claims. The objective of the insurer is to maximize the expected exponential utility of terminal wealth. This optimization problem is studied in two cases depending on the diffusion term＇s explanation. In all cases, by using techniques of stochastic control theory, closed-form expressions for the value functions and optimal strategies are obtained.
基金The authors gratefully acknowledge the support of the National Natural Science Foundation of China(No.11574250).
文摘Underwater acoustic signal processing is one of the research hotspots in underwater acoustics.Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing.Owing to the complexity of marine environment and the particularity of underwater acoustic channel,noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing.In order to solve the dilemma,we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),minimum mean square variance criterion(MMSVC) and least mean square adaptive filter(LMSAF).This noise reduction technique,named CEEMDAN-MMSVC-LMSAF,has three main advantages:(i) as an improved algorithm of empirical mode decomposition(EMD) and ensemble EMD(EEMD),CEEMDAN can better suppress mode mixing,and can avoid selecting the number of decomposition in variational mode decomposition(VMD);(ii) MMSVC can identify noisy intrinsic mode function(IMF),and can avoid selecting thresholds of different permutation entropies;(iii) for noise reduction of noisy IMFs,LMSAF overcomes the selection of deco mposition number and basis function for wavelet noise reduction.Firstly,CEEMDAN decomposes the original signal into IMFs,which can be divided into noisy IMFs and real IMFs.Then,MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs.Finally,both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained.Compared with other noise reduction techniques,the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals,which has the better noise reduction effect and has practical application value.CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection,feature extraction,classification and recognition of underwater acoustic signals.
