Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the ...Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.展开更多
This paper proposes an innovative approach to social science research based on quantum theory,integrating quantum probability,quantum game theory,and quantum statistical methods into a comprehensive interdisciplinary ...This paper proposes an innovative approach to social science research based on quantum theory,integrating quantum probability,quantum game theory,and quantum statistical methods into a comprehensive interdisciplinary framework for both theoretical and empirical investigation.The study elaborates on how core quantum concepts such as superposition,interference,and measurement collapse can be applied to model social decision making,cognition,and interactions.Advanced quantum computational methods and algorithms are employed to transition from theoretical model development to simulation and experimental validation.Through case studies in international relations,economic games,and political decision making,the research demonstrates that quantum models possess significant advantages in explaining irrational and context-dependent behaviors that traditional methods often fail to capture.The paper also explores the potential applications of quantum social science in policy formulation and public decision making,addresses the ethical,privacy,and social equity challenges posed by quantum artificial intelligence,and outlines future research directions at the convergence of quantum AI,quantum machine learning,and big data analytics.The findings suggest that quantum social science not only offers a novel perspective for understanding complex social phenomena but also lays the foundation for more accurate and efficient systems in social forecasting and decision support.展开更多
Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,...Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.展开更多
Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can a...Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.展开更多
The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,ma...The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications.But there is no comprehensive evaluation of these models for the whole China region,which features complicated topography and climate.In this study,we completely assess the typical empirical models,the IGGtropSH model(gridded,non-meteorology),the SHAtropE model(scattered,non-meteorology),and the GPT3 model(gridded,meteorology)using the Crustal Movement Observation Network of China(CMONOC)network.In general,the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63,37.13/2.20,and 38.27/1.34 mm for the GPT3,SHAtropE and IGGtropSH model,respectively.However,the models had a distinct performance regarding geographical distribution,elevation,seasonal variations,and daily variation.In the southeastern region of China,RMSE values are around 50 mm,which are much higher than that in the western region,approximately 20 mm.The SHAtropE model exhibits better performance for areas with large variations in elevation.The GPT3 model and the IGGtropSH model are more stable across different months,and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs.展开更多
This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a disti...This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a distinctive boundary structure.This approach capitalizes on the boundary’s capacity to attenuate the high-frequency component of fault signals,resulting in a variation in the high-frequency transient energy ratio when faults occur inside or outside the line.During internal line faults,the high-frequency transient energy at the checkpoints located at both ends surpasses that of its neighboring lines.Conversely,for faults external to the line,the energy is lower compared to adjacent lines.EWT is employed to decompose the collected fault current signals,allowing access to the high-frequency transient energy.The longitudinal protection for the traction network line is established based on disparities between both ends of the traction network line and the high-frequency transient energy on either side of the boundary.Moreover,simulation verification through experimental results demonstrates the effectiveness of the proposed protection scheme across various initial fault angles,distances to faults,and fault transition resistances.展开更多
In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistic...In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistics are established for the parameters of the MESS model.It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions,which are used to construct the confidence regions of model parameters.Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method.展开更多
The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lin...The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.展开更多
Electric vibrators find wide applications in reliability testing, waveform generation, and vibration simulation, making their noise characteristics a topic of significant interest. While Variational Mode Decomposition...Electric vibrators find wide applications in reliability testing, waveform generation, and vibration simulation, making their noise characteristics a topic of significant interest. While Variational Mode Decomposition (VMD) and Empirical Wavelet Transform (EWT) offer valuable support for studying signal components, they also present certain limitations. This article integrates the strengths of both methods and proposes an enhanced approach that integrates VMD into the frequency band division principle of EWT. Initially, the method decomposes the signal using VMD, determining the mode count based on residuals, and subsequently employs EWT decomposition based on this information. This addresses mode aliasing issues in the original method while capitalizing on VMD’s adaptability. Feasibility was confirmed through simulation signals and ultimately applied to noise signals from vibrators. Experimental results demonstrate that the improved method not only resolves EWT frequency band division challenges but also effectively decomposes signal components compared to the VMD method.展开更多
To date,the concept of sustainable development has gained global attention from companies and investors.One important reason for this is the increasing interest of investors in incorporating environmental,social,and g...To date,the concept of sustainable development has gained global attention from companies and investors.One important reason for this is the increasing interest of investors in incorporating environmental,social,and governance(ESG)elements into their investments.The purpose of this dissertation is to analyze the correlation between ESG factor performance and corporate financial performance in Chinese technology enterprises.Additionally,the study focuses on Internet and medical technology companies to ensure relevance.The findings of the study provide guidance on ESG investment and sustainability for both companies and individual investors.展开更多
With the deepening of globalization,cultivating college students’critical thinking ability has become the core goal of foreign language education in China.On the basis of clarifying the theoretical connotation of cri...With the deepening of globalization,cultivating college students’critical thinking ability has become the core goal of foreign language education in China.On the basis of clarifying the theoretical connotation of critical thinking ability,this paper attempts to construct the evaluation criteria of its core elements and expounds the internal relationship between Model United Nations(MUN)activities and its cultivation in line with this evaluation criteria.Then,through questionnaire and individual interview,this paper conducts an empirical research on the effect of MUN on the cultivation of students’critical thinking ability.The results show that MUN activities have a positive effect on the cultivation of students’critical thinking ability.展开更多
The development of smart education has led to the integration of emerging technologies such as artificial intelligence with education.It is a prerequisite for teachers to have high information literacy for conducting ...The development of smart education has led to the integration of emerging technologies such as artificial intelligence with education.It is a prerequisite for teachers to have high information literacy for conducting education and teaching work.This study conducted a questionnaire survey on 412 teachers in a certain area.The results showed that teachers’information literacy is above the middle level,and there are significant differences in information literacy between teaching experience and educational background.The evaluation showed that information ethics,information awareness,and information application have a significant positive impact on professional development,and information knowledge and information awareness have a positive predictive effect on information ethics.展开更多
The Moral and Law course serves as a critical platform for educating university students about ideals and beliefs,and it has a significant impact on the effectiveness of ideals and beliefs education.This paper establi...The Moral and Law course serves as a critical platform for educating university students about ideals and beliefs,and it has a significant impact on the effectiveness of ideals and beliefs education.This paper establishes a mechanism through which Moral and Law course teaching influences the effectiveness of ideals and beliefs education and conducts an empirical evaluation.The results reveal that factors such as the relevance and applicability of the teaching content,the integration of theory and practice,the innovation,interactivity,and participation of teaching methods,as well as classroom atmosphere,teaching facilities,and campus culture,all have a significant positive impact on the effectiveness of ideals and beliefs education for university students.展开更多
In longitudinal data analysis, our primary interest is in the estimation of regression parameters for the marginal expectations of the longitudinal responses, and the longitudinal correlation parameters are of seconda...In longitudinal data analysis, our primary interest is in the estimation of regression parameters for the marginal expectations of the longitudinal responses, and the longitudinal correlation parameters are of secondary interest. The joint likelihood function for longitudinal data is challenging, particularly due to correlated responses. Marginal models, such as generalized estimating equations (GEEs), have received much attention based on the assumption of the first two moments of the data and a working correlation structure. The confidence regions and hypothesis tests are constructed based on the asymptotic normality. This approach is sensitive to the misspecification of the variance function and the working correlation structure which may yield inefficient and inconsistent estimates leading to wrong conclusions. To overcome this problem, we propose an empirical likelihood (EL) procedure based on a set of estimating equations for the parameter of interest and discuss its <span style="font-family:Verdana;">characteristics and asymptotic properties. We also provide an algorithm base</span><span style="font-family:Verdana;">d on EL principles for the estimation of the regression parameters and the construction of its confidence region. We have applied the proposed method in two case examples.</span>展开更多
The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in ...The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in signal damage and limited denoising. Second, decomposing the real and imaginary parts of complex data may lead to inconsistent decomposition numbers. Thus, we propose a new method named f–x spatial projection-based complex empirical mode decomposition（CEMD） prediction filtering. The proposed approach directly decomposes complex seismic data into a series of complex IMFs（CIMFs） using the spatial projection-based CEMD algorithm and then applies f–x predictive filtering to the stationary CIMFs to improve the signal-to-noise ratio. Synthetic and real data examples were used to demonstrate the performance of the new method in random noise attenuation and seismic signal preservation.展开更多
In this paper, we construct the EB estim ation for the parameter of the two-dimensional one side truncat ed distribution fam ilies using Linex loss. The convergence rate of EB estimation is given and it is shown tha...In this paper, we construct the EB estim ation for the parameter of the two-dimensional one side truncat ed distribution fam ilies using Linex loss. The convergence rate of EB estimation is given and it is shown that the proposed empirical Bayes estimaiton can be arbitrarily close to 1 under certain conditions.展开更多
Capital structure decision is an important issue of corporate finance.Theories show that,the corporate debt ratio is determined by many factors.This study conducts empirical work on capital structure theories,focusing...Capital structure decision is an important issue of corporate finance.Theories show that,the corporate debt ratio is determined by many factors.This study conducts empirical work on capital structure theories,focusing on the corporate data of Chinese listed companies,by considering the intrinsic characteristics,utilizing the principal factor analysis and the ridge regression method.Our results suggest that a firms debt ratio has a positive relationship with its size,profitability and operating risk and has a negative relationship with its growth and non debt tax shield,while the long term leverage has a positive relationship with its collateral value of assets.展开更多
Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of ...Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.展开更多
Since the empirical mode decomposition （EMD） lacks strict orthogonality, the method of orthogonal empirical mode decomposition （OEMD） is innovationally proposed. The primary thought of this method is to obtain the...Since the empirical mode decomposition （EMD） lacks strict orthogonality, the method of orthogonal empirical mode decomposition （OEMD） is innovationally proposed. The primary thought of this method is to obtain the intrinsic mode function （IMF） and the residual function by auto-adaptive band-pass filtering. OEMD is proved to preserve strict orthogonality and completeness theoretically, and the orthogonal basis function of OEMD is generated, then an algorithm to implement OEMD fast, IMF binary searching algorithm is built based on the point that the analytical band-pass filtering preserves perfect band-pass feature in the frequency domain. The application into harmonic detection shows that OEMD successfully conquers mode aliasing, avoids the occurrence of false mode, and is featured by fast computing speed. Furthermore, it can achieve harmonic detection accurately combined with the least square method.展开更多
This study uses <span style="font-family:Verdana;">an empirical</span><span style="font-family:Verdana;"> analysis to quantify the downstream analysis effects of data pre-processi...This study uses <span style="font-family:Verdana;">an empirical</span><span style="font-family:Verdana;"> analysis to quantify the downstream analysis effects of data pre-processing choices. Bootstrap data simulation is used to measure the bias-variance decomposition of an empirical risk function, mean square error (MSE). Results of the risk function decomposition are used to measure the effects of model development choices on </span><span style="font-family:Verdana;">model</span><span style="font-family:Verdana;"> bias, variance, and irreducible error. Measurements of bias and variance are then applied as diagnostic procedures for model pre-processing and development. Best performing model-normalization-data structure combinations were found to illustrate the downstream analysis effects of these model development choices. </span><span style="font-family:Verdana;">In addition</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;">, results found from simulations were verified and expanded to include additional data characteristics (imbalanced, sparse) by testing on benchmark datasets available from the UCI Machine Learning Library. Normalization results on benchmark data were consistent with those found using simulations, while also illustrating that more complex and/or non-linear models provide better performance on datasets with additional complexities. Finally, applying the findings from simulation experiments to previously tested applications led to equivalent or improved results with less model development overhead and processing time.</span>展开更多
基金Supported by the National Natural Science Foundation of China(12061017,12361055)the Research Fund of Guangxi Key Lab of Multi-source Information Mining&Security(22-A-01-01)。
文摘Existing blockwise empirical likelihood(BEL)method blocks the observations or their analogues,which is proven useful under some dependent data settings.In this paper,we introduce a new BEL(NBEL)method by blocking the scoring functions under high dimensional cases.We study the construction of confidence regions for the parameters in spatial autoregressive models with spatial autoregressive disturbances(SARAR models)with high dimension of parameters by using the NBEL method.It is shown that the NBEL ratio statistics are asymptoticallyχ^(2)-type distributed,which are used to obtain the NBEL based confidence regions for the parameters in SARAR models.A simulation study is conducted to compare the performances of the NBEL and the usual EL methods.
文摘This paper proposes an innovative approach to social science research based on quantum theory,integrating quantum probability,quantum game theory,and quantum statistical methods into a comprehensive interdisciplinary framework for both theoretical and empirical investigation.The study elaborates on how core quantum concepts such as superposition,interference,and measurement collapse can be applied to model social decision making,cognition,and interactions.Advanced quantum computational methods and algorithms are employed to transition from theoretical model development to simulation and experimental validation.Through case studies in international relations,economic games,and political decision making,the research demonstrates that quantum models possess significant advantages in explaining irrational and context-dependent behaviors that traditional methods often fail to capture.The paper also explores the potential applications of quantum social science in policy formulation and public decision making,addresses the ethical,privacy,and social equity challenges posed by quantum artificial intelligence,and outlines future research directions at the convergence of quantum AI,quantum machine learning,and big data analytics.The findings suggest that quantum social science not only offers a novel perspective for understanding complex social phenomena but also lays the foundation for more accurate and efficient systems in social forecasting and decision support.
基金funded by the National Natural Science Foundation of China(Grant Nos.U22A20166 and 12172230)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515012654)+1 种基金funded by the National Natural Science Foundation of China(Grant Nos.U22A20166 and 12172230)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515012654)。
文摘Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation.
基金financial supports from National Natural Science Foundation of China(No.62205172)Huaneng Group Science and Technology Research Project(No.HNKJ22-H105)Tsinghua University Initiative Scientific Research Program and the International Joint Mission on Climate Change and Carbon Neutrality。
文摘Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.
基金supported by the National Natural Science Foundation of China(42204022,52174160,52274169)Open Fund of Hubei Luojia Laboratory(230100031)+2 种基金the Open Fund of State Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University(23P02)the Fundamental Research Funds for the Central Universities(2023ZKPYDC10)China University of Mining and Technology-Beijing Innovation Training Program for College Students(202302014,202202023)。
文摘The precise correction of atmospheric zenith tropospheric delay(ZTD)is significant for the Global Navigation Satellite System(GNSS)performance regarding positioning accuracy and convergence time.In the past decades,many empirical ZTD models based on whether the gridded or scattered ZTD products have been proposed and widely used in the GNSS positioning applications.But there is no comprehensive evaluation of these models for the whole China region,which features complicated topography and climate.In this study,we completely assess the typical empirical models,the IGGtropSH model(gridded,non-meteorology),the SHAtropE model(scattered,non-meteorology),and the GPT3 model(gridded,meteorology)using the Crustal Movement Observation Network of China(CMONOC)network.In general,the results show that the three models share consistent performance with RMSE/bias of 37.45/1.63,37.13/2.20,and 38.27/1.34 mm for the GPT3,SHAtropE and IGGtropSH model,respectively.However,the models had a distinct performance regarding geographical distribution,elevation,seasonal variations,and daily variation.In the southeastern region of China,RMSE values are around 50 mm,which are much higher than that in the western region,approximately 20 mm.The SHAtropE model exhibits better performance for areas with large variations in elevation.The GPT3 model and the IGGtropSH model are more stable across different months,and the SHAtropE model based on the GNSS data exhibits superior performance across various UTC epochs.
基金supported by the National Natural Science Foundation of China(51767012)Curriculum Ideological and Political Connotation Construction Project of Kunming University of Science and Technology(2021KS009)Kunming University of Science and Technology Online Open Course(MOOC)Construction Project(202107).
文摘This paper proposes a longitudinal protection scheme utilizing empirical wavelet transform(EWT)for a through-type cophase traction direct power supply system,where both sides of a traction network line exhibit a distinctive boundary structure.This approach capitalizes on the boundary’s capacity to attenuate the high-frequency component of fault signals,resulting in a variation in the high-frequency transient energy ratio when faults occur inside or outside the line.During internal line faults,the high-frequency transient energy at the checkpoints located at both ends surpasses that of its neighboring lines.Conversely,for faults external to the line,the energy is lower compared to adjacent lines.EWT is employed to decompose the collected fault current signals,allowing access to the high-frequency transient energy.The longitudinal protection for the traction network line is established based on disparities between both ends of the traction network line and the high-frequency transient energy on either side of the boundary.Moreover,simulation verification through experimental results demonstrates the effectiveness of the proposed protection scheme across various initial fault angles,distances to faults,and fault transition resistances.
基金Supported by the National Natural Science Foundation of China(12061017,12161009)the Research Fund of Guangxi Key Lab of Multi-source Information Mining&Security(22-A-01-01)。
文摘In this paper,we study spatial cross-sectional data models in the form of matrix exponential spatial specification(MESS),where MESS appears in both dependent and error terms.The empirical likelihood(EL)ratio statistics are established for the parameters of the MESS model.It is shown that the limiting distributions of EL ratio statistics follow chi-square distributions,which are used to construct the confidence regions of model parameters.Simulation experiments are conducted to compare the performances of confidence regions based on EL method and normal approximation method.
文摘The most prominent risk assessment techniques are founded on the values of measuring and controlling the frequency and the consequences of risks in order to assure an“acceptable level”of“safeness”mainly in the lines of environmental,health and hygiene and port product issues.This paper examines security risk assessment approaches within the emerging role of ports.This paper contributes to the current literature by considering the ports of Greece as a case in point and by measuring the degree of its security risk orientation based on certain valid risk factors drawn from the current literature.Moreover,it presents a security risk assessment methodology into the domain of port container terminals.Their potential for ports were quantitatively and qualitatively assessed by discussing issues of security approaches within the maritime industry,in order to facilitate improvement strategies.A two-dimension empirical study was conducted,in a time range of ten years(2010-2020)in order to provide evidence regarding security risk assessment in the port container terminal of Thessaloniki,in Greece.The findings of this study have significant strategic policy implications and shed more light on the role of security risks in the overall risk orientation of container terminals in practice.Finally,further research directions in security risk in ports are proposed.
文摘Electric vibrators find wide applications in reliability testing, waveform generation, and vibration simulation, making their noise characteristics a topic of significant interest. While Variational Mode Decomposition (VMD) and Empirical Wavelet Transform (EWT) offer valuable support for studying signal components, they also present certain limitations. This article integrates the strengths of both methods and proposes an enhanced approach that integrates VMD into the frequency band division principle of EWT. Initially, the method decomposes the signal using VMD, determining the mode count based on residuals, and subsequently employs EWT decomposition based on this information. This addresses mode aliasing issues in the original method while capitalizing on VMD’s adaptability. Feasibility was confirmed through simulation signals and ultimately applied to noise signals from vibrators. Experimental results demonstrate that the improved method not only resolves EWT frequency band division challenges but also effectively decomposes signal components compared to the VMD method.
文摘To date,the concept of sustainable development has gained global attention from companies and investors.One important reason for this is the increasing interest of investors in incorporating environmental,social,and governance(ESG)elements into their investments.The purpose of this dissertation is to analyze the correlation between ESG factor performance and corporate financial performance in Chinese technology enterprises.Additionally,the study focuses on Internet and medical technology companies to ensure relevance.The findings of the study provide guidance on ESG investment and sustainability for both companies and individual investors.
文摘With the deepening of globalization,cultivating college students’critical thinking ability has become the core goal of foreign language education in China.On the basis of clarifying the theoretical connotation of critical thinking ability,this paper attempts to construct the evaluation criteria of its core elements and expounds the internal relationship between Model United Nations(MUN)activities and its cultivation in line with this evaluation criteria.Then,through questionnaire and individual interview,this paper conducts an empirical research on the effect of MUN on the cultivation of students’critical thinking ability.The results show that MUN activities have a positive effect on the cultivation of students’critical thinking ability.
基金Chongqing Vocational Education Society Project“Postgraduate Study on the Current Status and Enhancement Strategies of Information Literacy of Vocational Learning Teachers in the Context of Smart Education”(Project number:2022ZJXH431099)Chongqing Education Science“14th Five-Year Plan”Program Key Project“Research on Construction and Evaluation of Collaborative Learning Model in Smart Education Environment”(Project number:2021-GX-014)。
文摘The development of smart education has led to the integration of emerging technologies such as artificial intelligence with education.It is a prerequisite for teachers to have high information literacy for conducting education and teaching work.This study conducted a questionnaire survey on 412 teachers in a certain area.The results showed that teachers’information literacy is above the middle level,and there are significant differences in information literacy between teaching experience and educational background.The evaluation showed that information ethics,information awareness,and information application have a significant positive impact on professional development,and information knowledge and information awareness have a positive predictive effect on information ethics.
文摘The Moral and Law course serves as a critical platform for educating university students about ideals and beliefs,and it has a significant impact on the effectiveness of ideals and beliefs education.This paper establishes a mechanism through which Moral and Law course teaching influences the effectiveness of ideals and beliefs education and conducts an empirical evaluation.The results reveal that factors such as the relevance and applicability of the teaching content,the integration of theory and practice,the innovation,interactivity,and participation of teaching methods,as well as classroom atmosphere,teaching facilities,and campus culture,all have a significant positive impact on the effectiveness of ideals and beliefs education for university students.
文摘In longitudinal data analysis, our primary interest is in the estimation of regression parameters for the marginal expectations of the longitudinal responses, and the longitudinal correlation parameters are of secondary interest. The joint likelihood function for longitudinal data is challenging, particularly due to correlated responses. Marginal models, such as generalized estimating equations (GEEs), have received much attention based on the assumption of the first two moments of the data and a working correlation structure. The confidence regions and hypothesis tests are constructed based on the asymptotic normality. This approach is sensitive to the misspecification of the variance function and the working correlation structure which may yield inefficient and inconsistent estimates leading to wrong conclusions. To overcome this problem, we propose an empirical likelihood (EL) procedure based on a set of estimating equations for the parameter of interest and discuss its <span style="font-family:Verdana;">characteristics and asymptotic properties. We also provide an algorithm base</span><span style="font-family:Verdana;">d on EL principles for the estimation of the regression parameters and the construction of its confidence region. We have applied the proposed method in two case examples.</span>
基金supported financially by the National Natural Science Foundation(No.41174117)the Major National Science and Technology Projects(No.2011ZX05031–001)
文摘The frequency–space（f–x） empirical mode decomposition（EMD） denoising method has two limitations when applied to nonstationary seismic data. First, subtracting the first intrinsic mode function（IMF） results in signal damage and limited denoising. Second, decomposing the real and imaginary parts of complex data may lead to inconsistent decomposition numbers. Thus, we propose a new method named f–x spatial projection-based complex empirical mode decomposition（CEMD） prediction filtering. The proposed approach directly decomposes complex seismic data into a series of complex IMFs（CIMFs） using the spatial projection-based CEMD algorithm and then applies f–x predictive filtering to the stationary CIMFs to improve the signal-to-noise ratio. Synthetic and real data examples were used to demonstrate the performance of the new method in random noise attenuation and seismic signal preservation.
文摘In this paper, we construct the EB estim ation for the parameter of the two-dimensional one side truncat ed distribution fam ilies using Linex loss. The convergence rate of EB estimation is given and it is shown that the proposed empirical Bayes estimaiton can be arbitrarily close to 1 under certain conditions.
文摘Capital structure decision is an important issue of corporate finance.Theories show that,the corporate debt ratio is determined by many factors.This study conducts empirical work on capital structure theories,focusing on the corporate data of Chinese listed companies,by considering the intrinsic characteristics,utilizing the principal factor analysis and the ridge regression method.Our results suggest that a firms debt ratio has a positive relationship with its size,profitability and operating risk and has a negative relationship with its growth and non debt tax shield,while the long term leverage has a positive relationship with its collateral value of assets.
基金the supported by National Natural Science Foundation of China(No.61871318 and 11574250)Scientific Research Plan Projects of Shaanxi Education Department(No.19JK0568).
文摘Feature extraction is an important part of signal processing,which is significant for signal detection,classification,and recognition.The nonlinear dynamic analysis method can extract the nonlinear characteristics of signals and is widely used in different fields.Reverse dispersion entropy(RDE)proposed by us recently,as a nonlinear dynamic analysis method,has the advantages of fast computing speed and strong anti-noise ability,which is more suitable for measuring the complexity of signal than traditional permutation entropy(PE)and dispersion entropy(DE).Empirical wavelet transform(EWT),based on the theory of wavelet analysis,can decompose a complex non-stationary signal into a number of empirical wavelet functions(EWFs)with compact support set spectrum,which has better decomposition performance than empirical mode decomposition(EMD)and its improved algorithms.Considering the advantages of RDE and EWT,on the one hand,we introduce EWT into the field of underwater acoustic signal processing and fault diagnosis to improve the signal decomposition accuracy;on the other hand,we use RDE as the features of EWFs to improve the signal separability and stability.Finally,we propose a novel signal feature extraction technology based on EWT and RDE in this paper.Experimental results show that the proposed feature extraction technology can effectively extract the complexity features of actual signals.Moreover,it also has higher distinguishing ability for different types of signals than five latest feature extraction technologies.
基金National Natural Science Foundation of China(No.50575233)
文摘Since the empirical mode decomposition （EMD） lacks strict orthogonality, the method of orthogonal empirical mode decomposition （OEMD） is innovationally proposed. The primary thought of this method is to obtain the intrinsic mode function （IMF） and the residual function by auto-adaptive band-pass filtering. OEMD is proved to preserve strict orthogonality and completeness theoretically, and the orthogonal basis function of OEMD is generated, then an algorithm to implement OEMD fast, IMF binary searching algorithm is built based on the point that the analytical band-pass filtering preserves perfect band-pass feature in the frequency domain. The application into harmonic detection shows that OEMD successfully conquers mode aliasing, avoids the occurrence of false mode, and is featured by fast computing speed. Furthermore, it can achieve harmonic detection accurately combined with the least square method.
文摘This study uses <span style="font-family:Verdana;">an empirical</span><span style="font-family:Verdana;"> analysis to quantify the downstream analysis effects of data pre-processing choices. Bootstrap data simulation is used to measure the bias-variance decomposition of an empirical risk function, mean square error (MSE). Results of the risk function decomposition are used to measure the effects of model development choices on </span><span style="font-family:Verdana;">model</span><span style="font-family:Verdana;"> bias, variance, and irreducible error. Measurements of bias and variance are then applied as diagnostic procedures for model pre-processing and development. Best performing model-normalization-data structure combinations were found to illustrate the downstream analysis effects of these model development choices. </span><span style="font-family:Verdana;">In addition</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;">, results found from simulations were verified and expanded to include additional data characteristics (imbalanced, sparse) by testing on benchmark datasets available from the UCI Machine Learning Library. Normalization results on benchmark data were consistent with those found using simulations, while also illustrating that more complex and/or non-linear models provide better performance on datasets with additional complexities. Finally, applying the findings from simulation experiments to previously tested applications led to equivalent or improved results with less model development overhead and processing time.</span>
