Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software pack...Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software packages running clustering analysis,there is a lack of packages conducting clustering analysis within a structural equation modeling framework.The package,gscaLCA which is implemented in the R statistical computing environment,was developed for conducting clustering analysis and has been extended to a latent variable modeling.More specifically,by applying both fuzzy clustering(FC)algorithm and generalized structured component analysis(GSCA),the package gscaLCA computes membership prevalence and item response probabilities as posterior probabilities,which is applicable in mixture modeling such as latent class analysis in statistics.As a hybrid model between data clustering in classifications and model-based mixture modeling approach,fuzzy clusterwise GSCA,denoted as gscaLCA,encompasses many advantages from both methods:(1)soft partitioning from FC and(2)efficiency in estimating model parameters with bootstrap method via resolution of global optimization problem from GSCA.The main function,gscaLCA,works for both binary and ordered categorical variables.In addition,gscaLCA can be used for latent class regression as well.Visualization of profiles of latent classes based on the posterior probabilities is also available in the package gscaLCA.This paper contributes to providing a methodological tool,gscaLCA that applied researchers such as social scientists and medical researchers can apply clustering analysis in their research.展开更多
This paper reports a new derivative in the Eulerian description in flat space-the generalized covariant derivative with respect to time. The following contents are included:(a) the restricted covariant derivative with...This paper reports a new derivative in the Eulerian description in flat space-the generalized covariant derivative with respect to time. The following contents are included:(a) the restricted covariant derivative with respect to time for Eulerian component is defined;(b) the postulate of the covariant form invariability in time field is set up;(c) the generalized covariant derivative with respect to time for generalized Eulerian component is defined;(d) the algebraic structure of the generalized covariant derivative with respect to time is made clear;(e) the covariant differential transformation group in time filed is derived. These progresses reveal the covariant form invariability of Eulerian space and time.展开更多
The previous paper reported a new derivative in the Eulerian description in flat space—the generalized covariant derivative of generalized Eulerian component with respect to time. This paper extends the thought from ...The previous paper reported a new derivative in the Eulerian description in flat space—the generalized covariant derivative of generalized Eulerian component with respect to time. This paper extends the thought from the Eulerian description to the Lagrangian description:on the basis of the postulate of covariant form invariability in time field, we define a new derivative in the Lagrangian description in flat space—the generalized covariant derivative of generalized Lagrangian component with respect to time. Besides, the covariant differential transformation group is set up. The covariant form invariability of Lagrangian space-time is ascertained.展开更多
In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias es...In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.展开更多
A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relat...A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.展开更多
Objective Improvement in the quality of life is reflected in the narrowing of the gap between healthadjusted life expectancy(HALE)and life expectancy(LE).The effect of megacity expansion on narrowing the gap is rarely...Objective Improvement in the quality of life is reflected in the narrowing of the gap between healthadjusted life expectancy(HALE)and life expectancy(LE).The effect of megacity expansion on narrowing the gap is rarely reported.This study aimed to disclose this potential relationship.Methods Annual life tables were constructed from identified death records and population counts from multiple administrative sources in Guangzhou,China,from 2010 to 2020.Joinpoint regression was used to evaluate the temporal trend.Generalized principal component analysis and multilevel models were applied to examine the county-level association between the gap and social determinants.Results Although LE and HALE in megacities are increasing steadily,their gap is widening.Socioeconomic and health services are guaranteed to narrow this gap.Increasing personal wealth,a growing number of newborns and healthy immigrants,high urbanization,and healthy aging have helped in narrowing this gap.Conclusion In megacities,parallel LE and HALE growth should be highly considered to narrow their gap.Multiple social determinants need to be integrated as a whole to formulate public health plans.展开更多
To improve the accuracy of fault location system, several short-circuit tests need to be conducted before being brought into service in autotransformer （AT） feeding systems for high-speed railways in China. However,...To improve the accuracy of fault location system, several short-circuit tests need to be conducted before being brought into service in autotransformer （AT） feeding systems for high-speed railways in China. However, no systematic algorithm yet exists to evaluate the consistency of the current distribution of short-circuit tests. A methodology is proposed in this paper to address this problem. Based on Kirchhoff’s current law and the generalized method of symmetrical components, the current deviations of the AT feeding systems are analysed and then normalized with the short-circuit current as they vary greatly with systems and short-circuit sites. It is also found that the short-circuit current varies with the calculation methods, and its unbiased standard deviation also reflects the consistency of the short-circuit test. The mean and maximum of the current deviations, as well as the unbiased standard deviation of the short-circuit current, show the consistency of the short-circuit test from different aspects,although the last two items are highly relevant. Therefore, a unified evaluation index is defined as the sum of the three items, and then applied in two case studies to test its performance. The results show that, the proposed index canclearly distinguish the consistency of the short-circuit tests and may be used to sort the short-circuit tests for fault location systems. Besides, some short-circuit tests may have very poor consistency indices, and thus are not applicable to the tuning of fault location systems. In the authors’ opinion, the determination of the threshold of the proposed index needs further investigation.展开更多
The Council on Environmental Quality’s Climate and Economic Justice Screening Tool defines“disadvantaged communities”(DAC)in the USA,highlighting census tracts where benefits of climate and energy investments are n...The Council on Environmental Quality’s Climate and Economic Justice Screening Tool defines“disadvantaged communities”(DAC)in the USA,highlighting census tracts where benefits of climate and energy investments are not accruing.We use a principal component generalized linear model(PCGLM),which addresses the intertwined nature of economic factors,income and employment and model their relationship to DAC status.Our study(1)identifies the most significant income groups and employment industries that impact DAC status(2)provides the probability of DAC status across census tracts and compares the predictive accuracy with widely used machine learning(ML)approaches,(3)obtains historical predictions of the probability of DAC status,(4)obtains spatial downscaling of DAC status across block groups.Our study provides valuable insights for policymakers and stakeholders to develop strategies that promote sustainable development and address inequities in climate and energy investments in the USA.展开更多
基金supported by the Yonsei University Research Fund of 2021(2021-22-0060).
文摘Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software packages running clustering analysis,there is a lack of packages conducting clustering analysis within a structural equation modeling framework.The package,gscaLCA which is implemented in the R statistical computing environment,was developed for conducting clustering analysis and has been extended to a latent variable modeling.More specifically,by applying both fuzzy clustering(FC)algorithm and generalized structured component analysis(GSCA),the package gscaLCA computes membership prevalence and item response probabilities as posterior probabilities,which is applicable in mixture modeling such as latent class analysis in statistics.As a hybrid model between data clustering in classifications and model-based mixture modeling approach,fuzzy clusterwise GSCA,denoted as gscaLCA,encompasses many advantages from both methods:(1)soft partitioning from FC and(2)efficiency in estimating model parameters with bootstrap method via resolution of global optimization problem from GSCA.The main function,gscaLCA,works for both binary and ordered categorical variables.In addition,gscaLCA can be used for latent class regression as well.Visualization of profiles of latent classes based on the posterior probabilities is also available in the package gscaLCA.This paper contributes to providing a methodological tool,gscaLCA that applied researchers such as social scientists and medical researchers can apply clustering analysis in their research.
基金Project supported by the National Natural Sciences Foundation of China(No.11272175)the Specialized Research Found for Doctoral Program of Higher Education(No.20130002110044)
文摘This paper reports a new derivative in the Eulerian description in flat space-the generalized covariant derivative with respect to time. The following contents are included:(a) the restricted covariant derivative with respect to time for Eulerian component is defined;(b) the postulate of the covariant form invariability in time field is set up;(c) the generalized covariant derivative with respect to time for generalized Eulerian component is defined;(d) the algebraic structure of the generalized covariant derivative with respect to time is made clear;(e) the covariant differential transformation group in time filed is derived. These progresses reveal the covariant form invariability of Eulerian space and time.
基金Project supported by the National Natural Sciences Foundation of China(No.11272175)the Specialized Research Found for Doctoral Program of Higher Education(No.20130002110044)
文摘The previous paper reported a new derivative in the Eulerian description in flat space—the generalized covariant derivative of generalized Eulerian component with respect to time. This paper extends the thought from the Eulerian description to the Lagrangian description:on the basis of the postulate of covariant form invariability in time field, we define a new derivative in the Lagrangian description in flat space—the generalized covariant derivative of generalized Lagrangian component with respect to time. Besides, the covariant differential transformation group is set up. The covariant form invariability of Lagrangian space-time is ascertained.
文摘In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.
基金The National Natural Science Foundation of China (No. 60675017) The National Basic Research Program (973) of China (No. 2006CB303103)
文摘A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.
基金supported by the Guangdong Basic and Applied Basic Research Foundation[grant 2020A1515011294,2020A1515110230,and 2021A1515011765]the China Postdoctoral Science Foundation[grant 2021M693594]+1 种基金the Guangzhou Municipal Health Commission[grant No.2021-2023-12,No.20201A011054]Guangzhou Municipal Science and Technology Bureau[grant 2021BRP004]。
文摘Objective Improvement in the quality of life is reflected in the narrowing of the gap between healthadjusted life expectancy(HALE)and life expectancy(LE).The effect of megacity expansion on narrowing the gap is rarely reported.This study aimed to disclose this potential relationship.Methods Annual life tables were constructed from identified death records and population counts from multiple administrative sources in Guangzhou,China,from 2010 to 2020.Joinpoint regression was used to evaluate the temporal trend.Generalized principal component analysis and multilevel models were applied to examine the county-level association between the gap and social determinants.Results Although LE and HALE in megacities are increasing steadily,their gap is widening.Socioeconomic and health services are guaranteed to narrow this gap.Increasing personal wealth,a growing number of newborns and healthy immigrants,high urbanization,and healthy aging have helped in narrowing this gap.Conclusion In megacities,parallel LE and HALE growth should be highly considered to narrow their gap.Multiple social determinants need to be integrated as a whole to formulate public health plans.
文摘To improve the accuracy of fault location system, several short-circuit tests need to be conducted before being brought into service in autotransformer （AT） feeding systems for high-speed railways in China. However, no systematic algorithm yet exists to evaluate the consistency of the current distribution of short-circuit tests. A methodology is proposed in this paper to address this problem. Based on Kirchhoff’s current law and the generalized method of symmetrical components, the current deviations of the AT feeding systems are analysed and then normalized with the short-circuit current as they vary greatly with systems and short-circuit sites. It is also found that the short-circuit current varies with the calculation methods, and its unbiased standard deviation also reflects the consistency of the short-circuit test. The mean and maximum of the current deviations, as well as the unbiased standard deviation of the short-circuit current, show the consistency of the short-circuit test from different aspects,although the last two items are highly relevant. Therefore, a unified evaluation index is defined as the sum of the three items, and then applied in two case studies to test its performance. The results show that, the proposed index canclearly distinguish the consistency of the short-circuit tests and may be used to sort the short-circuit tests for fault location systems. Besides, some short-circuit tests may have very poor consistency indices, and thus are not applicable to the tuning of fault location systems. In the authors’ opinion, the determination of the threshold of the proposed index needs further investigation.
基金supported by the Agile Initiative,a multi-disciplinary Pacific Northwest National Laboratory(PNNL)initiative.PNNL is operated by Battelle Memorial Institute under Contract DE-AC06-76RL01830.
文摘The Council on Environmental Quality’s Climate and Economic Justice Screening Tool defines“disadvantaged communities”(DAC)in the USA,highlighting census tracts where benefits of climate and energy investments are not accruing.We use a principal component generalized linear model(PCGLM),which addresses the intertwined nature of economic factors,income and employment and model their relationship to DAC status.Our study(1)identifies the most significant income groups and employment industries that impact DAC status(2)provides the probability of DAC status across census tracts and compares the predictive accuracy with widely used machine learning(ML)approaches,(3)obtains historical predictions of the probability of DAC status,(4)obtains spatial downscaling of DAC status across block groups.Our study provides valuable insights for policymakers and stakeholders to develop strategies that promote sustainable development and address inequities in climate and energy investments in the USA.
