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
The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes a...The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.展开更多
To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground moti...To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.展开更多
Based on 1,003 articles about empirical research on interpreting teaching from 2002 to 2022 retrieved from China National Knowledge Internet,this paper extracts three main research methods,uncovering common problems i...Based on 1,003 articles about empirical research on interpreting teaching from 2002 to 2022 retrieved from China National Knowledge Internet,this paper extracts three main research methods,uncovering common problems in interpreting education and practical teaching suggestions:(1)Corpus-based researches collect numerous audios to study typical mistakes made by interpreting learners,particularly pause and self-repair,and suggest interpreting teaching improve learners’ability to use language chunks and encourage students to interpret smoothly;(2)Questionnaire surveys help understand requirements for professional interpreters and how interpreting teaching meets market demands;(3)Teaching experiments last for one to two semesters,addressing issues like outdated teaching materials and modes,and show how teaching materials and modes integrate modern technology.But empirical researches need to build new corpora,professional interpreters’corpora and address problems that haven’t been adequately discussed.This paper is helpful for improving interpreting education in China and other countries and for making clear tasks to be fulfilled in empirical research on interpreting education.展开更多
The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data w...The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data were collected daily for 25 years starting in 2000.Daily rainfall data were converted to rainfall intensity for five duration periods ranging from one to five hours.The extreme values were checked,and data that deviated from the group trend were removed for each period,and then arranged in descending order using the Weibull formula to calculate the probability.Statistically,the model performance with a return period of two years is considered good when compared with observed results and other methods such as Talbot and Sherman with a coefficient of determination(R2)>0.97 and Nash-Sutcliffe efficiency(NSE)>0.80.The results showed that a mathematical equation was obtained that describes the relationship between rainfall intensity,probability,and rainfall duration,which can be used for a confined return period with a 50% probability.Therefore,decision-makers can rely on the model to improve the performance of the city’s current drainage system during flood periods in the future.展开更多
This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.The...This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content(VTEC)values collected across varied ionospheric conditions and measured over the region of interest.The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors.The reconstruction accuracy of the algorithm was found to be better than 4 TECU(TECU=1016electrons/m2)for more than 99.9%of the time when tested over the complete year of 2016 with only eight basis vectors.The containment factor,defined here,indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high,aiding in improved algorithm performance.The performance,however,was found to be sensitive to the seasons and geomagnetic conditions.Deteriorated performance was observed when tested for the St.Patrick's Day storm data.The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm.The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables,which may find utility in navigation,radar,and various other applications.展开更多
This paper is committed to an empirical study on the application of common English discourse patterns in the English reading teaching for non-English major students at an average or lower proficiency level.A quantitat...This paper is committed to an empirical study on the application of common English discourse patterns in the English reading teaching for non-English major students at an average or lower proficiency level.A quantitative research method is adopted.The research results show that the application of discourse patterns in teaching in the network environment can help improve students’reading comprehension ability to a certain extent.展开更多
Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility o...Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).展开更多
Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive met...Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive method for determining cardiac health.Various health practitioners use the ECG signal to ascertain critical information about the human heart.In this article,swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms(EWTs).At first,the white Gaussian noise is added to the input ECG signal and then applied to the EWT.The ECG signals are denoised by the proposed adaptive hybrid filter.The honey badge optimization(HBO)algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters.The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian,electromyogram and electrode motion artifact noises.A comparison of the HBO approach with recursive least square-based adaptive filter,multichannel least means square,and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter.The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising.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
Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting ...Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.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
Regularized system identification has become the research frontier of system identification in the past decade.One related core subject is to study the convergence properties of various hyper-parameter estimators as t...Regularized system identification has become the research frontier of system identification in the past decade.One related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to infinity.In this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been given.However,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is required.In general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance matrix.Thus,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter estimator.In this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting distribution.Moreover,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.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
Coal bursting liability refers to the mechanical property of the degree and possibility of coal burst.The bursting liability is important to evaluate coal burst in mining.In this paper,the needle penetration test was ...Coal bursting liability refers to the mechanical property of the degree and possibility of coal burst.The bursting liability is important to evaluate coal burst in mining.In this paper,the needle penetration test was carried out to determinate the coal bursting liability,and the empirical criterion of coal bursting liability was proposed.Moreover,the machine learning method was applied to coal bursting liability determination.Through analyzing the elastic strain energy release and failure time,the residual elastic strain energy release rate index K_(RE)was proposed to evaluate the coal bursting liability.According to the relationship between needle penetration index(NPI),K_(RE)and the critical value of K_(RE),the Needle Penetration Test-based Empirical Classification Criterion(NPT-ECC)was obtained.In addition,four machine learning classification models were constructed.After training and testing of the models,Needle Penetration Test-based Machine Learning Classification Model(NPT-MLCM)was proposed.The research results show that the accuracy of NPT-ECC is 6.66%higher than that of China National Standard Comprehensive Evaluation(CNSCE)according to verification of the coal fragment ejection ratio F.Gridsearch cross validation-extreme gradient boosting(GSCV-XGBoost)has the best prediction performance among all the models,and accuracy,Macro-Precision,Macro-Recall and Macro-F1-score of which were 86.67%,88.97%,87.50%and 87.37%.Based on this,the Needle Penetration Test-based GSCV-XGBoost(NPT-GSCV-XGBoost)was proposed.After comparative analysis and discussion,NPT-GSCV-XGBoost is superior to NPT-ECC and CNSCE in the comprehensive prediction ability.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
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.
基金funded by the Australian Research Council via the ARC Linkage(Grant No.LP16160100649).
文摘The complex behaviors of expansive soils,particularly their volumetric changes driven by moisture variations,pose significant challenges in urban geotechnical engineering.Although vegetation-induced moisture changes are known to affect ground movement,quantitative characterization of tree–soil interactions remains limited due to insufficient field data and unclear relationships between tree water uptake and soil response.This study investigates the mechanical behavior of expansive clay soils influenced by two Lophostemon confertus samples during a 14-month field monitoring program in Melbourne,Australia.The research methodology integrates measurements of soil displacement,total soil suction,moisture content,and tree water consumption through instrumentation and monitoring systems.Field measurements suggest that tree roots reached the limits of their water extraction capacity when total soil suction exceeded 2880 kPa within the active root zone.The spatial extent of tree-induced soil desiccation reached 0.6–0.7 times the tree height laterally and penetrated to depths of 2.5–3.3 m vertically.The mature sample,with an 86%greater crown area and a threefold larger sapwood area,exhibited 142%higher water consumption(35 kL),demonstrating the scalability of tree–soil interaction mechanisms.A multiple linear regression model was developed to quantify the coupled relationships between soil movement and key variables,achieving a high adjusted R2 value of 0.97,which provides engineers and practitioners with a practical tool for estimating ground movement near trees.These findings offer valuable insights for infrastructure design in tree-adjacent environments and can inform computational models and design codes to enable more accurate site assessments and sustainable urban development.
基金National Natural Science Foundation of China under Grant No.52478568National Key R&D Program of China under Grant Nos.2021YFC3100701 and 2022YFC3003503the Nature Science Foundation of Hubei Province under Grant No.2023AFA030。
文摘To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.
基金USST Construction Project of English-taught Courses for International Students in 2024Key Course Construction Project in Universities of Shanghai in 2024USST Teaching Achievement Award(postgraduate)Cultivation Project in 2024。
文摘Based on 1,003 articles about empirical research on interpreting teaching from 2002 to 2022 retrieved from China National Knowledge Internet,this paper extracts three main research methods,uncovering common problems in interpreting education and practical teaching suggestions:(1)Corpus-based researches collect numerous audios to study typical mistakes made by interpreting learners,particularly pause and self-repair,and suggest interpreting teaching improve learners’ability to use language chunks and encourage students to interpret smoothly;(2)Questionnaire surveys help understand requirements for professional interpreters and how interpreting teaching meets market demands;(3)Teaching experiments last for one to two semesters,addressing issues like outdated teaching materials and modes,and show how teaching materials and modes integrate modern technology.But empirical researches need to build new corpora,professional interpreters’corpora and address problems that haven’t been adequately discussed.This paper is helpful for improving interpreting education in China and other countries and for making clear tasks to be fulfilled in empirical research on interpreting education.
文摘The study aims to develop an empirical model to predict the rainfall intensity in Al-Diwaniyah City,Iraq,according to a statistical analysis based on probability and the specific rainfall return period.Rainfall data were collected daily for 25 years starting in 2000.Daily rainfall data were converted to rainfall intensity for five duration periods ranging from one to five hours.The extreme values were checked,and data that deviated from the group trend were removed for each period,and then arranged in descending order using the Weibull formula to calculate the probability.Statistically,the model performance with a return period of two years is considered good when compared with observed results and other methods such as Talbot and Sherman with a coefficient of determination(R2)>0.97 and Nash-Sutcliffe efficiency(NSE)>0.80.The results showed that a mathematical equation was obtained that describes the relationship between rainfall intensity,probability,and rainfall duration,which can be used for a confined return period with a 50% probability.Therefore,decision-makers can rely on the model to improve the performance of the city’s current drainage system during flood periods in the future.
文摘This paper demonstrates that the spatial distribution of the ionospheric TEC over the Indian region can be reconstructed with appreciable accuracy using minimal numbers of empirical orthogonal functions as a basis.These basis functions were derived using the Singular Value Decomposition of a matrix composed of pragmatic vertical Total Electron Content(VTEC)values collected across varied ionospheric conditions and measured over the region of interest.The reconstruction was achieved by linearly combining the appropriately chosen significant bases with corresponding weight factors.The reconstruction accuracy of the algorithm was found to be better than 4 TECU(TECU=1016electrons/m2)for more than 99.9%of the time when tested over the complete year of 2016 with only eight basis vectors.The containment factor,defined here,indicates the goodness of the chosen bases in representing the arbitrary VTEC distributions and is found to remain typically high,aiding in improved algorithm performance.The performance,however,was found to be sensitive to the seasons and geomagnetic conditions.Deteriorated performance was observed when tested for the St.Patrick's Day storm data.The deterioration was attributed to the structural alteration of the ionospheric plasma density and the presence of atypical modes during the storm.The results ascertain the prospect of a faithful representation of the spatial distribution of the ionospheric VTEC using limited parametric variables,which may find utility in navigation,radar,and various other applications.
基金General Project for Educational and Teaching Reform of Xinjiang Yili Normal University,2022:Empirical Study on the Reform of College English Reading Teaching Based on Discourse Patterns in Network Environment.Funding amount:CNY 10,000.Duration:April 2022-April 2025(Project No.:YSYB202268).
文摘This paper is committed to an empirical study on the application of common English discourse patterns in the English reading teaching for non-English major students at an average or lower proficiency level.A quantitative research method is adopted.The research results show that the application of discourse patterns in teaching in the network environment can help improve students’reading comprehension ability to a certain extent.
基金supported by National Key Research & Development Program of China (2022YFC3006201)。
文摘Emergency medical services (EMS) are a vital element of the public healthcare system in China,^([1])providing an opportunity to respond to critical medical conditions and save people’s lives.^([2])The accessibility of EMS has received considerable attention in health and transport geography studies.^([3])One of the optimal gauges for evaluating the accessibility of EMS is the response time,which is defined as the time from receiving an emergency call to the arrival of an ambulance.^([4])Beijing has already reduced the response time to approximately12 min,and the next goal is to ensure that the response time across Beijing does not exceed 12 min (the information comes from the Beijing Emergency Medical Center).
文摘Cardiovascular diseases are the world’s leading cause of death;therefore cardiac health of the human heart has been a fascinating topic for decades.The electrocardiogram(ECG)signal is a comprehensive non-invasive method for determining cardiac health.Various health practitioners use the ECG signal to ascertain critical information about the human heart.In this article,swarm intelligence approaches are used in the biomedical signal processing sector to enhance adaptive hybrid filters and empirical wavelet transforms(EWTs).At first,the white Gaussian noise is added to the input ECG signal and then applied to the EWT.The ECG signals are denoised by the proposed adaptive hybrid filter.The honey badge optimization(HBO)algorithm is utilized to optimize the EWT window function and adaptive hybrid filter weight parameters.The proposed approach is simulated by MATLAB 2018a using the MIT-BIH dataset with white Gaussian,electromyogram and electrode motion artifact noises.A comparison of the HBO approach with recursive least square-based adaptive filter,multichannel least means square,and discrete wavelet transform methods has been done in order to show the efficiency of the proposed adaptive hybrid filter.The experimental results show that the HBO approach supported by EWT and adaptive hybrid filter can be employed efficiently for cardiovascular signal denoising.
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the Gansu Province Soft Scientific Research Projects(No.2015GS06516)the Funds for Distinguished Young Scientists of Lanzhou University of Technology,China(No.J201304)。
文摘Predicting wind speed accurately is essential to ensure the stability of the wind power system and improve the utilization rate of wind energy.However,owing to the stochastic and intermittent of wind speed,predicting wind speed accurately is difficult.A new hybrid deep learning model based on empirical wavelet transform,recurrent neural network and error correction for short-term wind speed prediction is proposed in this paper.The empirical wavelet transformation is applied to decompose the original wind speed series.The long short term memory network and the Elman neural network are adopted to predict low-frequency and high-frequency wind speed sub-layers respectively to balance the calculation efficiency and prediction accuracy.The error correction strategy based on deep long short term memory network is developed to modify the prediction errors.Four actual wind speed series are utilized to verify the effectiveness of the proposed model.The empirical results indicate that the method proposed in this paper has satisfactory performance in wind speed prediction.
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 in part by the National Natural Science Foundation of China(No.62273287)by the Shenzhen Science and Technology Innovation Council(Nos.JCYJ20220530143418040,JCY20170411102101881)the Thousand Youth Talents Plan funded by the central government of China.
文摘Regularized system identification has become the research frontier of system identification in the past decade.One related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to infinity.In this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been given.However,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is required.In general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance matrix.Thus,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter estimator.In this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting distribution.Moreover,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.
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.
基金supported by the National Natural Science Foundation of China(52225402 and U1910206).
文摘Coal bursting liability refers to the mechanical property of the degree and possibility of coal burst.The bursting liability is important to evaluate coal burst in mining.In this paper,the needle penetration test was carried out to determinate the coal bursting liability,and the empirical criterion of coal bursting liability was proposed.Moreover,the machine learning method was applied to coal bursting liability determination.Through analyzing the elastic strain energy release and failure time,the residual elastic strain energy release rate index K_(RE)was proposed to evaluate the coal bursting liability.According to the relationship between needle penetration index(NPI),K_(RE)and the critical value of K_(RE),the Needle Penetration Test-based Empirical Classification Criterion(NPT-ECC)was obtained.In addition,four machine learning classification models were constructed.After training and testing of the models,Needle Penetration Test-based Machine Learning Classification Model(NPT-MLCM)was proposed.The research results show that the accuracy of NPT-ECC is 6.66%higher than that of China National Standard Comprehensive Evaluation(CNSCE)according to verification of the coal fragment ejection ratio F.Gridsearch cross validation-extreme gradient boosting(GSCV-XGBoost)has the best prediction performance among all the models,and accuracy,Macro-Precision,Macro-Recall and Macro-F1-score of which were 86.67%,88.97%,87.50%and 87.37%.Based on this,the Needle Penetration Test-based GSCV-XGBoost(NPT-GSCV-XGBoost)was proposed.After comparative analysis and discussion,NPT-GSCV-XGBoost is superior to NPT-ECC and CNSCE in the comprehensive prediction ability.
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.
