Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predi...Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.展开更多
In several instances of statistical practice, it is not uncommon to use the same data for both model selection and inference, without taking account of the variability induced by model selection step. This is usually ...In several instances of statistical practice, it is not uncommon to use the same data for both model selection and inference, without taking account of the variability induced by model selection step. This is usually referred to as post-model selection inference. The shortcomings of such practice are widely recognized, finding a general solution is extremely challenging. We propose a model averaging alternative consisting on taking into account model selection probability and the like-lihood in assigning the weights. The approach is applied to Bernoulli trials and outperforms Akaike weights model averaging and post-model selection estimators.展开更多
The deep learning models hold considerable potential for clinical applications, but there are many challenges to successfully training deep learning models. Large-scale data collection is required, which is frequently...The deep learning models hold considerable potential for clinical applications, but there are many challenges to successfully training deep learning models. Large-scale data collection is required, which is frequently only possible through multi-institutional cooperation. Building large central repositories is one strategy for multi-institution studies. However, this is hampered by issues regarding data sharing, including patient privacy, data de-identification, regulation, intellectual property, and data storage. These difficulties have lessened the impracticality of central data storage. In this survey, we will look at 24 research publications that concentrate on machine learning approaches linked to privacy preservation techniques for multi-institutional data, highlighting the multiple shortcomings of the existing methodologies. Researching different approaches will be made simpler in this case based on a number of factors, such as performance measures, year of publication and journals, achievements of the strategies in numerical assessments, and other factors. A technique analysis that considers the benefits and drawbacks of the strategies is additionally provided. The article also looks at some potential areas for future research as well as the challenges associated with increasing the accuracy of privacy protection techniques. The comparative evaluation of the approaches offers a thorough justification for the research’s purpose.展开更多
The study on seismic anisotropy is one of the difficult problems in the field of geophysics nowadays.As a method of ray theory,the seismic anisotropy ray tracing is an important means to study the anisotropic seismic ...The study on seismic anisotropy is one of the difficult problems in the field of geophysics nowadays.As a method of ray theory,the seismic anisotropy ray tracing is an important means to study the anisotropic seismic wave propagation. The traditional ray tracing system formulated in terms of elastic parameters in the anisotropy is more complicated than that in the isotropic case. Considering the difficulty,a kind of ray tracing system formulated in terms of phase velocity and group velocity is introduced. The new method is similar to the expressions for isotropic media,and avoids the trouble of determining the eigenvalue vector at each time. Besides the ray tracing numerical simulation of different models of vertical transversely isotropic( VTI) medium is carried out,in order to verify the accuracy and applicability of the method and further study the characteristics of wave field propagation in different VTI mediums. The study is certainly valuable in reference for later processing of the anisotropic seismic data.展开更多
文摘Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.
文摘In several instances of statistical practice, it is not uncommon to use the same data for both model selection and inference, without taking account of the variability induced by model selection step. This is usually referred to as post-model selection inference. The shortcomings of such practice are widely recognized, finding a general solution is extremely challenging. We propose a model averaging alternative consisting on taking into account model selection probability and the like-lihood in assigning the weights. The approach is applied to Bernoulli trials and outperforms Akaike weights model averaging and post-model selection estimators.
文摘The deep learning models hold considerable potential for clinical applications, but there are many challenges to successfully training deep learning models. Large-scale data collection is required, which is frequently only possible through multi-institutional cooperation. Building large central repositories is one strategy for multi-institution studies. However, this is hampered by issues regarding data sharing, including patient privacy, data de-identification, regulation, intellectual property, and data storage. These difficulties have lessened the impracticality of central data storage. In this survey, we will look at 24 research publications that concentrate on machine learning approaches linked to privacy preservation techniques for multi-institutional data, highlighting the multiple shortcomings of the existing methodologies. Researching different approaches will be made simpler in this case based on a number of factors, such as performance measures, year of publication and journals, achievements of the strategies in numerical assessments, and other factors. A technique analysis that considers the benefits and drawbacks of the strategies is additionally provided. The article also looks at some potential areas for future research as well as the challenges associated with increasing the accuracy of privacy protection techniques. The comparative evaluation of the approaches offers a thorough justification for the research’s purpose.
文摘The study on seismic anisotropy is one of the difficult problems in the field of geophysics nowadays.As a method of ray theory,the seismic anisotropy ray tracing is an important means to study the anisotropic seismic wave propagation. The traditional ray tracing system formulated in terms of elastic parameters in the anisotropy is more complicated than that in the isotropic case. Considering the difficulty,a kind of ray tracing system formulated in terms of phase velocity and group velocity is introduced. The new method is similar to the expressions for isotropic media,and avoids the trouble of determining the eigenvalue vector at each time. Besides the ray tracing numerical simulation of different models of vertical transversely isotropic( VTI) medium is carried out,in order to verify the accuracy and applicability of the method and further study the characteristics of wave field propagation in different VTI mediums. The study is certainly valuable in reference for later processing of the anisotropic seismic data.
