In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance ...In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.展开更多
The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are pa...The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are particularly important. In this paper, three spatial sampling programs, including spatial random sampling, spatial stratified sampling, and spatial sandwich sampling, are used to analyze the data from meteorological stations of northwestern China. We compared the accuracy of ordinary Kriging interpolation methods on the basis of the sampling results. The error values of the regional annual pre-cipitation interpolation based on spatial sandwich sampling, including ME （0.1513）, RMSE （95.91）, ASE （101.84）, MSE （？0.0036）, and RMSSE （1.0397）, were optimal under the premise of abundant prior knowledge. The result of spatial stratified sampling was poor, and spatial random sampling was even worse. Spatial sandwich sampling was the best sampling method, which minimized the error of regional precipitation estimation. It had a higher degree of accuracy compared with the other two methods and a wider scope of application.展开更多
Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other meth...Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other methods,it still faces challenges.Training a GCN model for large-scale graphs in a conventional way requires high computation and storage costs.Therefore,motivated by an urgent need in terms of efficiency and scalability in training GCN,sampling methods have been proposed and achieved a significant effect.In this paper,we categorize sampling methods based on the sampling mechanisms and provide a comprehensive survey of sampling methods for efficient training of GCN.To highlight the characteristics and differences of sampling methods,we present a detailed comparison within each category and further give an overall comparative analysis for the sampling methods in all categories.Finally,we discuss some challenges and future research directions of the sampling methods.展开更多
In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks...In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks and improve the level of food safety.展开更多
Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bi...Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bijie City, Guizhou Province, China. Datasets were collected from 614 landslides and 500 non-landslides, and four sampling methods were proposed. Recurrent Neural Network(RNN), Gated Recurrent Unit(GRU), K-Nearest Neighbor(KNN), and Extreme Gradient Boosting(XGB) models were assessed utilising 15 metrics(Elevation, Slope, Aspect, Plan curvature, Profile curvature, Stream Power Index, Sediment Transport Index, Vector Ruggedness Measurement, Topographic Roughness Index, Lithology, Land use, Normalized Difference Vegetation Index(NDVI), Rainfall, Distance from Road, Distance from River). The results demonstrated that the GRU model combined with a 5-m sample boundary from the interior of the landslide and non-landslide areas exhibited superior performance with F1, Accuracy, and Area Under Curve(AUC) scores of 0.9700, 0.9450, and 0.8925, respectively. LSM will be projected for the next decade by coupling the Geophysical Fluid Dynamics Laboratory Earth System Model version 4(GFDLESM4) with the Shared Socioeconomic Pathway(SSP119). This study provides valuable insights into landslide risk management in landslide-prone areas.展开更多
When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes...When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.展开更多
The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engin...The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.展开更多
Terrestrial arthropods are extremely important ecosystem components. The choice of best approaches to collect the wide range of terrestrial arthropods has been a topic of long-lasting debates. This article provides a ...Terrestrial arthropods are extremely important ecosystem components. The choice of best approaches to collect the wide range of terrestrial arthropods has been a topic of long-lasting debates. This article provides a brief overview of common sampling methods for terrestrial arthropod assemblages. We divide sampling methods into three main categories： passive sampling methods without any ＂activity density＂ bias, passive sampling methods with an ＂activity density＂ bias, and active sampling methods with inherent ＂activity density＂ and often further species-dependent biases, discussing their individual advantages and shortcomings as basis for biodiversity studies and pest control management. The selection of the optimal sampling methods depends strongly on the purpose of individual studies and the ecology and behavior of the arthropod groups targeted. A combination of different suitable methods is highly recommended in many cases.展开更多
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.展开更多
Accelerating materials discovery crucially relies on strategies that efficiently sample the search space to label a pool of unlabeled data.This is important if the available labeled data sets are relatively small comp...Accelerating materials discovery crucially relies on strategies that efficiently sample the search space to label a pool of unlabeled data.This is important if the available labeled data sets are relatively small compared to the unlabeled data pool.Active learning with efficient sampling methods provides the means to guide the decision making to minimize the number of experiments or iterations required to find targeted properties.We review here different sampling strategies and show how they are utilized within an active learning loop in materials science.展开更多
Probabilistic assessment of seismic performance(SPPA)is a crucial aspect of evaluating the seismic behavior of structures.For complex bridges with inherent uncertainties,conducting precise and efficient seismic reliab...Probabilistic assessment of seismic performance(SPPA)is a crucial aspect of evaluating the seismic behavior of structures.For complex bridges with inherent uncertainties,conducting precise and efficient seismic reliability analysis remains a significant challenge.To address this issue,the current study introduces a sample-unequal weight fractional moment assessment method,which is based on an improved correlation-reduced Latin hypercube sampling(ICLHS)technique.This method integrates the benefits of important sampling techniques with interpolator quadrature formulas to enhance the accuracy of estimating the extreme value distribution(EVD)for the seismic response of complex nonlinear structures subjected to non-stationary ground motions.Additionally,the core theoretical approaches employed in seismic reliability analysis(SRA)are elaborated,such as dimension reduction for simulating non-stationary random ground motions and a fractional-maximum entropy single-loop solution strategy.The effectiveness of this proposed method is validated through a three-story nonlinear shear frame structure.Furthermore,a comprehensive reliability analysis of a real-world long-span,single-pylon suspension bridge is conducted using the developed theoretical framework within the OpenSees platform,leading to key insights and conclusions.展开更多
The laboratories in the bauxite processing industry are always under a heavy workload of sample collection, analysis, and compilation of the results. After size reduction from grinding mills, the samples of bauxite ar...The laboratories in the bauxite processing industry are always under a heavy workload of sample collection, analysis, and compilation of the results. After size reduction from grinding mills, the samples of bauxite are collected after intervals of 3 to 4 hours. Large bauxite processing industries producing 1 million tons of pure aluminium can have three grinding mills. Thus, the total number of samples to be tested in one day reaches a figure of 18 to 24. The sample of bauxite ore coming from the grinding mill is tested for its particle size and composition. For testing the composition, the bauxite ore sample is first prepared by fusing it with X-ray flux. Then the sample is sent for X-ray fluorescence analysis. Afterwards, the crucibles are washed in ultrasonic baths to be used for the next testing. The whole procedure takes about 2 - 3 hours. With a large number of samples reaching the laboratory, the chances of error in composition analysis increase. In this study, we have used a composite sampling methodology to reduce the number of samples reaching the laboratory without compromising their validity. The results of the average composition of fifteen samples were measured against composite samples. The mean of difference was calculated. The standard deviation and paired t-test values were evaluated against predetermined critical values obtained using a two-tailed test. It was found from the results that paired test-t values were much lower than the critical values thus validating the composition attained through composite sampling. The composite sampling approach not only reduced the number of samples but also the chemicals used in the laboratory. The objective of improved analytical protocol to reduce the number of samples reaching the laboratory was successfully achieved without compromising the quality of analytical results.展开更多
The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.On...The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.展开更多
Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure...Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.展开更多
Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the...Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.展开更多
We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the f...We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the first part,we obtain the well-posedness of the direct scattering problem by the variational method.In the second part,we establish the mathematical basis of the linear sampling method to recover both the shape of the cavity,and the shape of the external obstacle,however the exterior transmission eigenvalue problem also plays a key role in the discussion of this paper.展开更多
Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 h...Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments （private vehicles, busses, taxis and subways） was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.展开更多
In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy ...In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy far field data.展开更多
文摘In this study, for accuracy and cost an optimal inventory method was examined and introduced to obtain information about Zagros forests, Iran. For this purpose,three distance sampling methods(compound, order distance and random-pairs) in 5 inventory networks(100 m × 100 m, 100 m × 150 m, 100 m × 200 m,150 m × 150 m, 200 m × 200 m) were implemented in GIS environment, and the related statistical analyses were carried out. Average tree density and canopy cover in hectare with 100% inventory were compared to each other.All the studied methods were implemented in 30 inventory points, and the implementation time of each was recorded.According to the results, the best inventory methods for estimating density and canopy cover were compound150 m × 150 m and 100 m × 100 m methods, respectively. The minimum amount of product inventory time per second(T), and(E%)2 square percent of inventory error of sampling for the compound 150 m × 150 m method regarding density in hectare was 691.8, and for the compound 100 m × 100 m method regarding canopy of 12,089 ha. It can be concluded that compound method is the best for estimating density and canopy features of the forests area.
基金conducted within the National Major Scientific Research Project (No. 2013CBA01806)the National Natural Science Foundation of China (No. 41271085)the National Scientific and Technological Support Project (No. 2013BAB05B03)
文摘The accuracy of spatial interpolation of precipitation data is determined by the actual spatial variability of the precipitation, the interpolation method, and the distribution of observatories whose selections are particularly important. In this paper, three spatial sampling programs, including spatial random sampling, spatial stratified sampling, and spatial sandwich sampling, are used to analyze the data from meteorological stations of northwestern China. We compared the accuracy of ordinary Kriging interpolation methods on the basis of the sampling results. The error values of the regional annual pre-cipitation interpolation based on spatial sandwich sampling, including ME （0.1513）, RMSE （95.91）, ASE （101.84）, MSE （？0.0036）, and RMSSE （1.0397）, were optimal under the premise of abundant prior knowledge. The result of spatial stratified sampling was poor, and spatial random sampling was even worse. Spatial sandwich sampling was the best sampling method, which minimized the error of regional precipitation estimation. It had a higher degree of accuracy compared with the other two methods and a wider scope of application.
基金supported by the National Natural Science Foundation of China(61732018,61872335,61802367,61876215)the Strategic Priority Research Program of Chinese Academy of Sciences(XDC05000000)+1 种基金Beijing Academy of Artificial Intelligence(BAAI),the Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing(2019A07)the Open Project of Zhejiang Laboratory,and a grant from the Institute for Guo Qiang,Tsinghua University.Recommended by Associate Editor Long Chen.
文摘Graph convolutional networks(GCNs)have received significant attention from various research fields due to the excellent performance in learning graph representations.Although GCN performs well compared with other methods,it still faces challenges.Training a GCN model for large-scale graphs in a conventional way requires high computation and storage costs.Therefore,motivated by an urgent need in terms of efficiency and scalability in training GCN,sampling methods have been proposed and achieved a significant effect.In this paper,we categorize sampling methods based on the sampling mechanisms and provide a comprehensive survey of sampling methods for efficient training of GCN.To highlight the characteristics and differences of sampling methods,we present a detailed comparison within each category and further give an overall comparative analysis for the sampling methods in all categories.Finally,we discuss some challenges and future research directions of the sampling methods.
文摘In this paper,by combining sampling methods for food statistics with years of sample sampling experience,various sampling points and corresponding sampling methods are summarized.It hopes to discover food safety risks and improve the level of food safety.
基金supported by the Technological Innovation Center of Geological Disaster Prevention and ecological Restoration in the western region of the Ministry of Natural Resources opened the fund (Grant No.TICGP2023K003)the Project of Sichuan Disaster Economic Research Center (Grant No.ZHJJ2024YJS004)。
文摘Landslide susceptibility mapping(LSM) is crucial for reducing disaster risk in complex mountainous regions. This study evaluated the impact of various sampling methods on the accuracy of LSM over the next decade in Bijie City, Guizhou Province, China. Datasets were collected from 614 landslides and 500 non-landslides, and four sampling methods were proposed. Recurrent Neural Network(RNN), Gated Recurrent Unit(GRU), K-Nearest Neighbor(KNN), and Extreme Gradient Boosting(XGB) models were assessed utilising 15 metrics(Elevation, Slope, Aspect, Plan curvature, Profile curvature, Stream Power Index, Sediment Transport Index, Vector Ruggedness Measurement, Topographic Roughness Index, Lithology, Land use, Normalized Difference Vegetation Index(NDVI), Rainfall, Distance from Road, Distance from River). The results demonstrated that the GRU model combined with a 5-m sample boundary from the interior of the landslide and non-landslide areas exhibited superior performance with F1, Accuracy, and Area Under Curve(AUC) scores of 0.9700, 0.9450, and 0.8925, respectively. LSM will be projected for the next decade by coupling the Geophysical Fluid Dynamics Laboratory Earth System Model version 4(GFDLESM4) with the Shared Socioeconomic Pathway(SSP119). This study provides valuable insights into landslide risk management in landslide-prone areas.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2024JC-YBMS-026).
文摘When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.
基金supported by the National Natural Science Foundation of China(No.42207175)。
文摘The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.
基金the China Bureau of Foreign Experts,the Ministry of Education of China (111 Program,Grant 2008B08044)the Chinese Academy of Sciences’Fellowship for Young International Scientists (Fellowship Number 2010Y1SA16)the Key Basic Research Project"973"(2010CB951301-5)
文摘Terrestrial arthropods are extremely important ecosystem components. The choice of best approaches to collect the wide range of terrestrial arthropods has been a topic of long-lasting debates. This article provides a brief overview of common sampling methods for terrestrial arthropod assemblages. We divide sampling methods into three main categories： passive sampling methods without any ＂activity density＂ bias, passive sampling methods with an ＂activity density＂ bias, and active sampling methods with inherent ＂activity density＂ and often further species-dependent biases, discussing their individual advantages and shortcomings as basis for biodiversity studies and pest control management. The selection of the optimal sampling methods depends strongly on the purpose of individual studies and the ecology and behavior of the arthropod groups targeted. A combination of different suitable methods is highly recommended in many cases.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324)。
文摘Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.
基金the National Key Research and Development Program of China(Grant No.2017YFB0702401)the National Natural Science Foundation of China(Grant Nos.51571156,51671157,51621063,and 51931004).
文摘Accelerating materials discovery crucially relies on strategies that efficiently sample the search space to label a pool of unlabeled data.This is important if the available labeled data sets are relatively small compared to the unlabeled data pool.Active learning with efficient sampling methods provides the means to guide the decision making to minimize the number of experiments or iterations required to find targeted properties.We review here different sampling strategies and show how they are utilized within an active learning loop in materials science.
基金Sichuan Science and Technology Program under Grant No.2024NSFSC0932the National Natural Science Foundation of China under Grant No.52008047。
文摘Probabilistic assessment of seismic performance(SPPA)is a crucial aspect of evaluating the seismic behavior of structures.For complex bridges with inherent uncertainties,conducting precise and efficient seismic reliability analysis remains a significant challenge.To address this issue,the current study introduces a sample-unequal weight fractional moment assessment method,which is based on an improved correlation-reduced Latin hypercube sampling(ICLHS)technique.This method integrates the benefits of important sampling techniques with interpolator quadrature formulas to enhance the accuracy of estimating the extreme value distribution(EVD)for the seismic response of complex nonlinear structures subjected to non-stationary ground motions.Additionally,the core theoretical approaches employed in seismic reliability analysis(SRA)are elaborated,such as dimension reduction for simulating non-stationary random ground motions and a fractional-maximum entropy single-loop solution strategy.The effectiveness of this proposed method is validated through a three-story nonlinear shear frame structure.Furthermore,a comprehensive reliability analysis of a real-world long-span,single-pylon suspension bridge is conducted using the developed theoretical framework within the OpenSees platform,leading to key insights and conclusions.
文摘The laboratories in the bauxite processing industry are always under a heavy workload of sample collection, analysis, and compilation of the results. After size reduction from grinding mills, the samples of bauxite are collected after intervals of 3 to 4 hours. Large bauxite processing industries producing 1 million tons of pure aluminium can have three grinding mills. Thus, the total number of samples to be tested in one day reaches a figure of 18 to 24. The sample of bauxite ore coming from the grinding mill is tested for its particle size and composition. For testing the composition, the bauxite ore sample is first prepared by fusing it with X-ray flux. Then the sample is sent for X-ray fluorescence analysis. Afterwards, the crucibles are washed in ultrasonic baths to be used for the next testing. The whole procedure takes about 2 - 3 hours. With a large number of samples reaching the laboratory, the chances of error in composition analysis increase. In this study, we have used a composite sampling methodology to reduce the number of samples reaching the laboratory without compromising their validity. The results of the average composition of fifteen samples were measured against composite samples. The mean of difference was calculated. The standard deviation and paired t-test values were evaluated against predetermined critical values obtained using a two-tailed test. It was found from the results that paired test-t values were much lower than the critical values thus validating the composition attained through composite sampling. The composite sampling approach not only reduced the number of samples but also the chemicals used in the laboratory. The objective of improved analytical protocol to reduce the number of samples reaching the laboratory was successfully achieved without compromising the quality of analytical results.
基金the National Natural Science Foundation of China (No40625001)the Knowledge Innovation Pro-gram of the Chinese Academy of Sciences (NoKZCX2-YW-409)the Jiangsu Provincial Natural Science Foundation of China (NoBK2004167)
文摘The vertical distribution and migration of Cu,Zn,Pb,and Cd in two forest soil profiles near an industrial emission source were investigated using a high resolution sampling method together with reference element Ti.One-meter soil profile was sectioned horizontally at 2 cm intervals in the first 40 cm,5 cm intervals in the next 40 cm,and 10 cm intervals in the last 20 cm.The migration distance and rate of heavy metals in the soil profiles were calculated according to their relative concentrations in the profiles,as calibrated by the reference element Ti.The enrichment of heavy metals appeared in the uppermost layer of the forest soil,and the soil heavy metal concentrations decreased down the profile until reaching their background values.The calculated average migration rates of Cd,Cu,Pb,and Zn were 0.70,0.33,0.37,and 0.76 cm year-1,respectively,which were comparable to other methods.A simulation model was proposed,which could well describe the distribution of Cu,Zn,Pb,and Cd in natural forest soils.
基金National Natural Science Foundation of China (10572117,10802063,50875213)Aeronautical Science Foundation of China (2007ZA53012)+1 种基金New Century Program For Excellent Talents of Ministry of Education of China (NCET-05-0868)National High-tech Research and Development Program (2007AA04Z401)
文摘Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.
文摘Based on the observation of importance sampling and second order information about the failure surface of a structure, an importance sampling region is defined in V-space which is obtained by rotating a U-space at the point of maximum likelihood. The sampling region is a hyper-ellipsoid that consists of the sampling ellipse on each plane of main curvature in V-space. Thus, the sampling probability density function can be constructed by the sampling region center and ellipsoid axes. Several examples have shown the efficiency and generality of this method.
基金supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region of China(2019D01A05)supported by the NSFC(11571132)。
文摘We consider the interior inverse scattering problem for recovering the shape of a penetrable partially coated cavity with external obstacles from the knowledge of measured scattered waves due to point sources.In the first part,we obtain the well-posedness of the direct scattering problem by the variational method.In the second part,we establish the mathematical basis of the linear sampling method to recover both the shape of the cavity,and the shape of the external obstacle,however the exterior transmission eigenvalue problem also plays a key role in the discussion of this paper.
基金support by the Hi-Tech Research and Development Program(863) of China(No.2010AA064902)the National Key Technologies R&D Program(No.2016YFC0207100)+1 种基金the National Natural Science Foundation of China(No.21207116)the Brain Bridge project with Philips(No.BB3-2016-01)
文摘Based on previous research, the sampling and analysis methods for phthalate esters （PAEs） were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments （private vehicles, busses, taxis and subways） was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.
文摘In this paper, we consider the inverse scattering by chiral obstacle in electromagnetic fields, and prove that the linear sampling method is also effective to determine the support of a chiral obstacle from the noisy far field data.
