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
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
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
A new method has recently developed,the solution sampling method(SMM),to quantify the binary rubber blends of NR/BR by pyrolysis/gas chromatography/mass spectrometry(PY/GC/MS).The rubbers were swelled in the cyclohexa...A new method has recently developed,the solution sampling method(SMM),to quantify the binary rubber blends of NR/BR by pyrolysis/gas chromatography/mass spectrometry(PY/GC/MS).The rubbers were swelled in the cyclohexane,using the hydrogen peroxide solution to destroy the cross-linked structure of the rubbers and then the rubbers can be sloved in the cyclohexane.The rubber solution was applied to the spiral section of the injector.The solvent was evaporated depositing the rubber on the spiral section,and the rubber was prolyzed at 550℃.Then calculate the weight percentage by the characteristic peak area ratio.One test rubber,NR/BR where the weight percentage of NR is 50% was calculated.The error was 5.64%.展开更多
Purpose: This paper aims to improve the classification performance when the data is imbalanced by applying different sampling techniques available in Machine Learning.Design/methodology/approach: The medical appointme...Purpose: This paper aims to improve the classification performance when the data is imbalanced by applying different sampling techniques available in Machine Learning.Design/methodology/approach: The medical appointment no-show dataset is imbalanced, and when classification algorithms are applied directly to the dataset, it is biased towards the majority class, ignoring the minority class. To avoid this issue, multiple sampling techniques such as Random Over Sampling(ROS), Random Under Sampling(RUS), Synthetic Minority Oversampling TEchnique(SMOTE), ADAptive SYNthetic Sampling(ADASYN), Edited Nearest Neighbor(ENN), and Condensed Nearest Neighbor(CNN) are applied in order to make the dataset balanced. The performance is assessed by the Decision Tree classifier with the listed sampling techniques and the best performance is identified.Findings: This study focuses on the comparison of the performance metrics of various sampling methods widely used. It is revealed that, compared to other techniques, the Recall is high when ENN is applied CNN and ADASYN have performed equally well on the Imbalanced data.Research limitations: The testing was carried out with limited dataset and needs to be tested with a larger dataset.Practical implications: This framework will be useful whenever the data is imbalanced in real world scenarios, which ultimately improves the performance.Originality/value: This paper uses the rebalancing framework on medical appointment no-show dataset to predict the no-shows and removes the bias towards minority class.展开更多
An outdoor flapping wing micro air vehicle （FWMAV） should be able to withstand unpredictable perturbations in the flight condition. The responses of the time-averaged thrust coefficient and the propulsive efficiency...An outdoor flapping wing micro air vehicle （FWMAV） should be able to withstand unpredictable perturbations in the flight condition. The responses of the time-averaged thrust coefficient and the propulsive efficiency with respect to a stochastic flight velocity deviation were numerically investigated. The deviation was assumed to obey the Gauss distribution with a mean value of zero and a specified standard deviation. The probability distributions of the flapping performances were quantified by the non-intrusive polynomial chaos method. It was observed that both of the time-averaged thrust coefficient and the propulsive efficiency obeyed Gauss-like but not the exact Gauss distribution. The velocity deviation had a large effect on the time-averaged thrust coefficient and a small effect on the propulsive efficiency.展开更多
We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-r...We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-resolution remote sensing （RS） satellite images. Deforestation identified in this way （hereafter, RSD） was compared to administrative data on deforestation. We also compared high-resolution satellite images （HR-RSD） and actual deforestation based on categories which were Intergovernmental Panel on Climate Change data. RSD generated by medium-resolution satellite images overesti- mated the amount of deforested area by 1.5-2.4 times the actual deforested area, whereas RSD generated by HR- RSD underestimated the amount of deforested area by 0.4-0.9 times the actual area. The highest degree of matching （90 %） was found in HR-RSD with a grid interval of 500 m and the accuracy of HR-RSD was the highest, at 67 %. The results also revealed that the largest cause of deforestation was the establishment of settlements followed by conversion to cropland and grassland. We conclude that for the identification of deforestation using satellite images, HR-RSD with a grid interval of 500 m is most suitable.展开更多
Formation testing while drilling is an innovative technique that is replacing conventional pressure testing in which the fluid sampling is conducted in a relatively short time following the drilling. At this time, mud...Formation testing while drilling is an innovative technique that is replacing conventional pressure testing in which the fluid sampling is conducted in a relatively short time following the drilling. At this time, mud invasion has just started, mudcake has not formed entirely and the formation pressure is not stable. Therefore, it is important to study the influence of the downhole dynamic environment on pressure testing and fluid sampling. This paper applies an oil-water two phase finite element model to study the influence of mudcake quality and mud filtrate invasion on supercharge pressure, pretest and sampling in the reservoirs of different permeability. However, the study is only for the cases with water based mud in the wellbore. The results illustrate that the mudcake quality has a significant influence on the supercharge pressure and fluid sampling, while the level of mud filtrate invasion has a strong impact on pressure testing and sampling. In addition, in-situ formation pressure testing is more difficult in low permeability reservoirs as the mud filtrate invasion is deeper and therefore degrades the quality of fluid sampling. Finally, a field example from an oil field on the Alaskan North Slope is presented to validate the numerical studies of the effects of downhole dynamic conditions on formation testing while drilling.展开更多
The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is stil...The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.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.
文摘A new method has recently developed,the solution sampling method(SMM),to quantify the binary rubber blends of NR/BR by pyrolysis/gas chromatography/mass spectrometry(PY/GC/MS).The rubbers were swelled in the cyclohexane,using the hydrogen peroxide solution to destroy the cross-linked structure of the rubbers and then the rubbers can be sloved in the cyclohexane.The rubber solution was applied to the spiral section of the injector.The solvent was evaporated depositing the rubber on the spiral section,and the rubber was prolyzed at 550℃.Then calculate the weight percentage by the characteristic peak area ratio.One test rubber,NR/BR where the weight percentage of NR is 50% was calculated.The error was 5.64%.
文摘Purpose: This paper aims to improve the classification performance when the data is imbalanced by applying different sampling techniques available in Machine Learning.Design/methodology/approach: The medical appointment no-show dataset is imbalanced, and when classification algorithms are applied directly to the dataset, it is biased towards the majority class, ignoring the minority class. To avoid this issue, multiple sampling techniques such as Random Over Sampling(ROS), Random Under Sampling(RUS), Synthetic Minority Oversampling TEchnique(SMOTE), ADAptive SYNthetic Sampling(ADASYN), Edited Nearest Neighbor(ENN), and Condensed Nearest Neighbor(CNN) are applied in order to make the dataset balanced. The performance is assessed by the Decision Tree classifier with the listed sampling techniques and the best performance is identified.Findings: This study focuses on the comparison of the performance metrics of various sampling methods widely used. It is revealed that, compared to other techniques, the Recall is high when ENN is applied CNN and ADASYN have performed equally well on the Imbalanced data.Research limitations: The testing was carried out with limited dataset and needs to be tested with a larger dataset.Practical implications: This framework will be useful whenever the data is imbalanced in real world scenarios, which ultimately improves the performance.Originality/value: This paper uses the rebalancing framework on medical appointment no-show dataset to predict the no-shows and removes the bias towards minority class.
基金Supported by the National Natural Science Foundation of China(10972034)the National Science Foundation for Postdoctoral Scientists of China(20090460216)the National Defense Fundamental Research Foundation of China(B222006060)
文摘An outdoor flapping wing micro air vehicle （FWMAV） should be able to withstand unpredictable perturbations in the flight condition. The responses of the time-averaged thrust coefficient and the propulsive efficiency with respect to a stochastic flight velocity deviation were numerically investigated. The deviation was assumed to obey the Gauss distribution with a mean value of zero and a specified standard deviation. The probability distributions of the flapping performances were quantified by the non-intrusive polynomial chaos method. It was observed that both of the time-averaged thrust coefficient and the propulsive efficiency obeyed Gauss-like but not the exact Gauss distribution. The velocity deviation had a large effect on the time-averaged thrust coefficient and a small effect on the propulsive efficiency.
文摘We evaluated the use of spatial sampling and satellite images to identify deforested areas in Wonju, South Korea. The changes in land cover were identified using a grid of sample points overlaid onto medium and high-resolution remote sensing （RS） satellite images. Deforestation identified in this way （hereafter, RSD） was compared to administrative data on deforestation. We also compared high-resolution satellite images （HR-RSD） and actual deforestation based on categories which were Intergovernmental Panel on Climate Change data. RSD generated by medium-resolution satellite images overesti- mated the amount of deforested area by 1.5-2.4 times the actual deforested area, whereas RSD generated by HR- RSD underestimated the amount of deforested area by 0.4-0.9 times the actual area. The highest degree of matching （90 %） was found in HR-RSD with a grid interval of 500 m and the accuracy of HR-RSD was the highest, at 67 %. The results also revealed that the largest cause of deforestation was the establishment of settlements followed by conversion to cropland and grassland. We conclude that for the identification of deforestation using satellite images, HR-RSD with a grid interval of 500 m is most suitable.
基金supported by the National Natural Science Foundation of China (No. 50674098)Major Project of Chinese Science and Technology (No. 2011ZX 05000-020-04)Major Project of SINOPEC Science and Technology (No. P13147)
文摘Formation testing while drilling is an innovative technique that is replacing conventional pressure testing in which the fluid sampling is conducted in a relatively short time following the drilling. At this time, mud invasion has just started, mudcake has not formed entirely and the formation pressure is not stable. Therefore, it is important to study the influence of the downhole dynamic environment on pressure testing and fluid sampling. This paper applies an oil-water two phase finite element model to study the influence of mudcake quality and mud filtrate invasion on supercharge pressure, pretest and sampling in the reservoirs of different permeability. However, the study is only for the cases with water based mud in the wellbore. The results illustrate that the mudcake quality has a significant influence on the supercharge pressure and fluid sampling, while the level of mud filtrate invasion has a strong impact on pressure testing and sampling. In addition, in-situ formation pressure testing is more difficult in low permeability reservoirs as the mud filtrate invasion is deeper and therefore degrades the quality of fluid sampling. Finally, a field example from an oil field on the Alaskan North Slope is presented to validate the numerical studies of the effects of downhole dynamic conditions on formation testing while drilling.
基金supported by the National Key Research and Development Program of China(No.2019YFD0901701)National Natural Science Foundation of China(Nos.12174359and 61975190)Provincial Key Research and Development Program of Shandong,China(No.2019GHZ010)。
文摘The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.
