Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have di...Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have directly compared empirical methods with modelling approaches.This study investigated rockfalls in five settlements within the Cappadocia region of Türkiye,employing both empirical methods and advanced three-dimensional(3D)probabilistic modeling.The energy line angle approach was applied to identify rockfall propagation zones,while high-resolution digital surface models derived from unmanned aerial vehicle(UAV)imagery facilitated detailed 3D rockfall simulations.Cappadocia’s unique geological setting—comprising alternating layers of ignimbrites and weaker fluviolacustrine deposits—renders it highly susceptible to rockfalls intensified by wetting-drying and freeze-thaw cycles.Results indicate that rockfall propagation characteristics vary markedly between settlements:Göre and Tatlarin exhibit shorter runout distances due to basalt-dominated slopes,whereas Akköy,SoğanlıandŞahinefendi display longer trajectories associated with welded ignimbrites.Empirical cone propagation analyses correspond broadly with field observations,but variations in energy line angles(23°-33°)highlight the necessity for site-specific calibration.Comparative evaluations demonstrate that 3D probabilistic modeling better captures local-scale block dynamics and identifies high-risk areas affected by topographic and structural features such as rockfall ditches.These findings emphasize the importance of integrating empirical and 3D approaches to improve hazard zoning,optimize mitigation structures and guide the protection of Cappadocia’s unique cultural heritage landscape.展开更多
Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of ...Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.展开更多
In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-pin...In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.展开更多
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 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
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
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
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
Crystal structure prediction aims to predict stable and easily experimentally synthesized materials,which accelerates the discovery of new materials.It is worth noting that the stability of materials is the basis for ...Crystal structure prediction aims to predict stable and easily experimentally synthesized materials,which accelerates the discovery of new materials.It is worth noting that the stability of materials is the basis for ensuring high performance and reliable application of materials.Among which,the thermodynamic and molecular dynamics stability is especially important.Therefore,this paper proposes a method to predict stable crystal structures using formation energy and Lennard-Jones potential as evaluation indicators.Specifically,we use graph neural network models to predict the formation energy of crystals,and employ empirical formulas to calculate the Lennard-Jones potential.Then,we apply Bayesian optimization algorithms to search for crystal structures with low formation energy and Lennard-Jones potential approaching zero,in order to ensure the thermodynamic stability and dynamics stability of materials.In addition,considering the impact of the bonding situation between atoms in the crystal on the structural stability,this article uses contact map to analyze the atomic bonding situation of each crystal to screen out more stable materials.Finally,the experimental results show that the method we proposed can not only reduce the time for crystal structure prediction,but also ensure the stability of crystal materials.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
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
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
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financially supported by The Scientific and Technological Research Council of Türkiye(T??B1TAK)with the project number 121C420。
文摘Rockfall hazards pose significant risks to both cultural heritage and populated areas,necessitating comprehensive assessment methodologies.Despite extensive research on rockfalls,only a small number of studies have directly compared empirical methods with modelling approaches.This study investigated rockfalls in five settlements within the Cappadocia region of Türkiye,employing both empirical methods and advanced three-dimensional(3D)probabilistic modeling.The energy line angle approach was applied to identify rockfall propagation zones,while high-resolution digital surface models derived from unmanned aerial vehicle(UAV)imagery facilitated detailed 3D rockfall simulations.Cappadocia’s unique geological setting—comprising alternating layers of ignimbrites and weaker fluviolacustrine deposits—renders it highly susceptible to rockfalls intensified by wetting-drying and freeze-thaw cycles.Results indicate that rockfall propagation characteristics vary markedly between settlements:Göre and Tatlarin exhibit shorter runout distances due to basalt-dominated slopes,whereas Akköy,SoğanlıandŞahinefendi display longer trajectories associated with welded ignimbrites.Empirical cone propagation analyses correspond broadly with field observations,but variations in energy line angles(23°-33°)highlight the necessity for site-specific calibration.Comparative evaluations demonstrate that 3D probabilistic modeling better captures local-scale block dynamics and identifies high-risk areas affected by topographic and structural features such as rockfall ditches.These findings emphasize the importance of integrating empirical and 3D approaches to improve hazard zoning,optimize mitigation structures and guide the protection of Cappadocia’s unique cultural heritage landscape.
基金funded by Scion's Strategic Science Investment Fund(SSIF)the Forest Growers Levy Trust(FGLT)through the Resilient Forests Programme(Task No.A89220)。
文摘Pinus radiata(D.Don)dominates New Zealand's forestry industry,constituting 91%of plantations,and is among the world's most important plantation species.Given the socio-economic and environmental importance of this species,it is important to have accurate and precise projections over time to make efficient decisions for forest management and greenfield investments in afforestation projects,especially for permanent carbon forests.Future projections of any natural resource systems rely on modeling;however,the acceleration of climate change makes future projections of yield less certain.These challenges also impact national expectations of the contribution planted forests will provide to address climate change and meet international commitments under the Paris Agreement.Using a large national-scale set of contemporary ground-measured data(2013–2023),this study investigates the performance of two growth models developed over 30 years ago that are widely used by NZ plantation growers:1)the Pumice Plateau Model 1988(PPM88)and 2)the 300-index(including a model variant of regional drift).Model simulations were made using the FORECASTER modeling suite with geographic boundaries to adjust for drift in space and time.Basal area(BA,m^(2)⋅ha^(-1))and volume(m^(3)⋅ha^(-1))were simulated,and standard errors and goodness-of-fit metrics calculated up to a typical rotation age of 30 years.Model residuals were then separated and analysed for the main plantation growing regions.The models overpredicted observed growth by between 6.8%and 16.2%,but model predictions and errors varied significantly between regions.The results of this study provided clear evidence of divergence between the outputs of both models and the measured data.Finally,this study suggests future measures to address challenges posed by these discrepancies that will provide better information for forest management and investment decisions in a changing climate.
基金funded by the National Natural Science Foundation of China,grant number U24A20135Inner Mongolia Natural Science Foundation major project,grant number 2023ZD12+7 种基金Inner Mongolia Autonomous Region key research and development and achievement transformation plan project,grant number 2023YFHH0090Natural Science Foundation of Inner Mongolia,grant number 2022MS05006Inner Mongolia Autonomous Region Talent Development FundUniversity basic research business expenses,grant number 2023RCTD012University basic research business expenses,grant number 2023QNJS075Postgraduate Research Innovation Program and of Inner Mongolia Autonomous Region,grant number KC2024053BUniversity basic research business expenses,grant number 2024YXXS012National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology,grant number GZ2023KF012.
文摘In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.
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.
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.
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 the Nature Science Foundation of China(Nos.61671362 and 62071366)。
文摘Crystal structure prediction aims to predict stable and easily experimentally synthesized materials,which accelerates the discovery of new materials.It is worth noting that the stability of materials is the basis for ensuring high performance and reliable application of materials.Among which,the thermodynamic and molecular dynamics stability is especially important.Therefore,this paper proposes a method to predict stable crystal structures using formation energy and Lennard-Jones potential as evaluation indicators.Specifically,we use graph neural network models to predict the formation energy of crystals,and employ empirical formulas to calculate the Lennard-Jones potential.Then,we apply Bayesian optimization algorithms to search for crystal structures with low formation energy and Lennard-Jones potential approaching zero,in order to ensure the thermodynamic stability and dynamics stability of materials.In addition,considering the impact of the bonding situation between atoms in the crystal on the structural stability,this article uses contact map to analyze the atomic bonding situation of each crystal to screen out more stable materials.Finally,the experimental results show that the method we proposed can not only reduce the time for crystal structure prediction,but also ensure the stability of crystal materials.
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.
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.
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>
