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sampling-Based Approaches to Estimating Two-Dimensional Large Wood Area from UAS Imagery

Journal of Geographic Information System 2022年第6期14卷 571-588页

作者： Matthew I. Barker Jonathan D. Burnett Francisco Mauro Gutiérrez Steven M. Wondzell Michael G. Wing Forest Engineering Resources and Management Department College of Forestry Oregon State University Corvallis OR USA USDA Forest Service Pacific Northwest Research Station Corvallis OR USA EiFAB—iuFOR Campus Duques de Soria s/n Universidad de Valladolid Soria Spain

Large in-stream wood (LW) is a critical component of riparian systems that increases heterogeneity of flow regimes and provides high quality habitat for salmonids and other fishes. We present four sampling-based methods to estimate two-dimensional LW for a 61-hectare river restoration project on the South Fork McKenzie River near Rainbow, OR (USA). We manually delineated LW area, from unoccupied aircraft systems (UAS) multispectral imagery for 40 randomly selected 51.46 m2 hexagonal plots. Seven auxiliary variables were extracted from the imagery and imagery derivatives to be incorporated in four estimators by summarizing spectral statistics for each plot including Random forest (RF) classification of segmented imagery (Cohen’s kappa = 0.75, balanced accuracy = 0.86). The four estimators were: difference estimator, simple linear regression estimator with one auxiliary variable, general regression estimator with seven auxiliary variables, and simple random sample without replacement. We assessed variance of the estimators and found that the simple random sample without replacement produced the largest estimate for LW area and widest confidence interval (17,283 m2, 95% CI 10,613 - 23,952 m2) while the generalized regression approach resulted in the smallest estimate and narrowest confidence interval (16,593 m2, 95% CI 13,054 - 20,133 m2). These methods facilitate efficient estimates of critical habitat components, that are especially suited to efforts that seek to quantify large amounts of these components through time. When combined with traditional sampling methods, classified imagery acquired via UAS promises to enhance the temporal resolution of the data products associated with restoration efforts while minimizing the necessity for potentially hazardous field work.

关键词： UAS Large in-Stream Wood sampling Image Classification River Restoration

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Precise monocular vision-based pose measurement system for lunar surface sampling manipulator

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Science China(Technological Sciences) 2019年第10期62卷 1783-1794页

作者： WANG Gang SHI ZhongChen SHANG Yang SUN XiaoLiang ZHANG WenLong YU QiFeng College of Aerospace Science and Engineering National University of Defense TechnologyChangsha410073China Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation Changsha410073China

Space manipulator has been playing an increasingly important role in space exploration due to its flexibility and versatility. This paper is to design a vision-based pose measurement system for a four-degree-of-freedom(4-DOF) lunar surface sampling manipulator relying on a monitoring camera and several fiducial markers. The system first employs double plateaus histogram equalization for the markers to improve the robustness to varying noise and illumination. The markers are then accurately extracted in sub-pixel based on template matching and curved surface fitting. Finally, given the camera parameters and 3D reference points, the pose of the manipulator end-effector is solved from the 3D-to-2D point correspondences by combining a plane-based pose estimation method with rigid-body transformation. Experiment results show that the system achieves highprecision positioning and orientation performance. The measurement error is within 3 mm in position, and 0.2° in orientation,meeting the requirements for space manipulator operations.

关键词： vision-based pose measurement pose estimation lunar surface sampling sub-pixel corner detection Chang’e 5

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A landscape shape index-based sampling approach for land cover accuracy assessment

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Science China Earth Sciences 2016年第12期59卷 2263-2274页

作者： CHEN Fei CHEN Jun WU Hao HOU DongYang ZHANG WeiWei ZHANG Jun ZHOU XiaoGuang CHEN LiJun School of Geosciences and Info-Physics Central South University National Geomatics Center of China

Spatial sampling design is one of the key steps in land cover accuracy assessment,and many traditional sampling approaches may not achieve credible spatial sampling due to the high spatial heterogeneity of land *** paper characterizes the spatial heterogeneity with three-level LSIs and determines the subsequent sample sizes and their spatial *** three-level LSIs are rLSI in a region,cLSI for each land cover class and uLSI in each geographic sampling unit in the *** rLSIs are used to derive appropriate sample sizes in the target *** cLSIs are used to assure that larger sample numbers are allocated to land cover classes with higher spatial *** uLSIs provide useful measures for selecting optimal geographic units in which sample sites will be *** LSI-based sampling approach can derive the sample sizes and determine their distributions in an adaptive way according to the spatial *** experimental case study further demonstrates that the LSI-based sampling approach obtains more appropriate sample sizes for each region,sufficient sample numbers for rare classes,and optimal sample distributions in the geographical space.

关键词： Land cover sampling Landscape index Spatial heterogeneity Accuracy assessment

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Reconstruction of sampling in shift-invariant space using generalized inverse

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Journal of Systems Engineering and Electronics 2011年第2期22卷 200-205页

作者： Zhaoxuan Zhu Institute of Astronautics & Aeronautics University of Electronic Science and Technology of China Chengdu 611731 P. R. China

A method that attempts to recover signal using generalized inverse theory is presented to obtain a good approximation of the signal in reconstruction space from its generalized samples. The proposed approaches differ with the assumptions on reconstruction space. If the reconstruction space satisfies one-to-one relationship between the samples and the reconstruction model, then we propose a method, which achieves consistent signal reconstruction. At the same time, when the number of samples is more than the number of reconstruction functions, the minimal-norm reconstruction signal can be obtained. Finally, it is demonstrated that the minimal-norm reconstruction can outperform consistent signal reconstruction in both theory and simulations for the problem.

关键词： sampling reconstruction generalized inverse shift-invariant space.

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A Bayesian validation approach to practical boson sampling

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Science China(Physics,Mechanics & Astronomy) 2020年第5期63卷 39-46页

作者： Zhe Dai Yong Liu Ping Xu WeiXia Xu XueJun Yang JunJie Wu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer National University of Defense TechnologyChangsha 410073China

Boson sampling is a promising candidate for demonstrating quantum supremacy. The validation that involves judging whether a quantum setup outputs photons following the boson sampling model is an essential task in the experiments. However, the current validation methods may result in an incorrect conclusion being reached in realistic experiments, in which no ideally identical photons exist. Accordingly, this study proposes a slope-based approach, which is an extended Bayesian validation, to model the degree of photon indistinguishability. Through numerical simulations and performance evaluations, we demonstrate that the proposed approach can correctly validate boson sampling against the distribution of classical particles. In addition to offering a useful approach for validation, our research indicates that physicists should pay more attention to the quality of photon indistinguishability in boson sampling experiments.

关键词： boson sampling quantum supremacy Bayesian validation photon indistinguishability

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Optimizational production of phenyllactic acid by a Lactobacillus buchneri strain via uniform design with overlay sampling methodology

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Chinese Journal of Chemical Engineering 2019年第2期27卷 418-425页

作者： Jintao Guan Chaofei Han Yixin Guan Songhong Zhang Junxian Yun Shanjing Yao College of Chemical and Biological Engineering Zhejiang University State Key Laboratory Breeding Base of Green Chemistry Synthesis Technology College of Chemical Engineering Zhejiang University of Technology

A Lactobacillus buchneri GBS3 strain isolated from the traditional Chinese pickles was used for the production of 3-phenyllactic acid(PLA), an important compound with antimicrobial activities against a wide species of grampositive and gram-negative bacteria and some fungi. The growth performance of this strain in the de Man, Rogosa and Sharpe(MRS) medium, the production of metabolites of valuable organic acids, and the biosynthesis of PLA using this strain as the whole-cell biocatalyst and phenylpyruvic acid(PPA) as the precursor, were investigated experimentally. The uniform design method with overlay sampling was developed for the optimization of the biotransformation conditions. The results showed that although it produced naturally lactic acid with the maximum concentration of 1.84 g·L^(-1) and PLA with the concentration of 0.015 g·L^(-1) after 66 to 72 h cultivation in MRS broth by fermentation, the present strain displayed an effective utilization ability by transforming PPA to PLA. By the uniform design method with overlay sampling for the design and optimization of transformation conditions, a maximum yield of 10.93 g·L^(-1) PLA with the mole conversion ratio of 83.07% from PPA to PLA was achieved under the optimized condition, i.e., 20 g·L^(-1) glucose, 270 g·L^(-1) cells, 13 g·L^(-1) PPA, pH 8.0 and the reaction time of 15 h, indicating that Lactobacillus buchneri GBS3 was an interesting strain for the biosynthesis of PLA via the microbial transformation. The prediction of PLA yield under different conditions was achieved successfully based on the limited information of only a small number of experiments by the uniform design with overlay sampling. Therefore, the present methodology is effective and helpful for the optimization of the biosynthesis processes of PLA.

关键词： Phenyllactic Acid Biotransformati on Lactobacillus Buchneri Uniform Design Overlap sampling

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Efficient multi-response adaptive sampling algorithm for construction of variable-fidelity aerodynamic tables

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Chinese Journal of Aeronautics 2019年第3期32卷 547-558页

作者： Maxim TYAN Jae-Woo LEE Department of Aerospace Information Engineering Konkuk University

Adaptive sampling is an iterative process for the construction of a global approximation model. Most of engineering analysis tools computes multiple parameters in a single run. This research proposes a novel multi-response adaptive sampling algorithm for simultaneous construction of multiple surrogate models in a time-efficient and accurate manner. The new algorithm uses the Jackknife cross-validation variance and a minimum distance metric to construct a sampling criterion function. A weighted sum of the function is used to consider the characteristics of multiple surrogate models. The proposed algorithm demonstrates good performance on total 22 numerical problems in comparison with three existing adaptive sampling algorithms. The numerical problems include several two-dimensional and six-dimensional functions which are combined into singleresponse and multi-response systems. Application of the proposed algorithm for construction of aerodynamic tables for 2 D airfoil is demonstrated. Scaling-based variable-fidelity modeling is implemented to enhance the accuracy of surrogate modeling. The algorithm succeeds in constructing a system of three highly nonlinear aerodynamic response surfaces within a reasonable amount of time while preserving high accuracy of approximation.

关键词： Adaptive sampling Aerodynamic database Multi-response system Surrogate modeling Variable fidelity modeling

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Research on variance of subnets in network sampling

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Journal of Systems Engineering and Electronics 2014年第6期25卷 1098-1106页

作者： Qi Gao Xiaoting Li Feng Pan School of Automation Beijing Institute of Technology

In the recent research of network sampling, some sampling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as well as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor（CNN） model, random network and small-world network to explore the variance in network sampling. As proved by the results, snowball sampling obtains the most variance of subnets, but does well in capturing the network structure. The variance of networks sampled by the hub and random strategy are much smaller. The hub strategy performs well in reflecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.

关键词： complex network sampling sample variance of sub-nets

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Transfer synthetic over-sampling for class-imbalance learning with limited minority class data

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Frontiers of Computer Science 2019年第5期13卷 996-1009页

作者： Xu-Ying LIU Sheng-Tao WANG Min-Ling ZHANG School of Computer Science and Engineering Southeast University Nanjing 210096 China Key Laboratory of Computer Network and Information Integration (Southeast University) Ministry of Education Nanjing 210096 China Collaborative Innovation Center for Wireless Communications Technology Nanjing 210096 China

The problem of limited minority class data is encountered in manyclass imbalanced applications, but has received little attention. Synthetic over-sampling, as popular class-imbalance learning methods, could introduce much noise when minority class has limited data since the synthetic samples are not i.i.d. samples of minority class. Mos t sophisticated synthetic sampling methods tackle this problem by denoising or generating samples more consistent with ground-truth data distribution. But their assumptions about true noise or ground-truth data distribution may not hold. To adapt synthetic sampling to the problem of limited minority class data, the proposed Traso framework treats synthetic minority class samples as an additional data source, and exploits transfer learning to transfer knowledge from them to minority class. As an implementation, TrasoBoost method firstly generates synthetic samples to balance class sizes. Then in each boosting iteration, the weights of synthetic samples and original data decrease and increase respectively when being misclassified, and remain unchanged otherwise. The misclassified synthetic samples are potential noise, and thus have smaller influence in the following iterations. Besides, the weights of minority class instances have greater change than those of majority class instances to be more influential. And only original data are used to estimate error rate to be immune from noise. Finally, since the synthetic samples are highly related to minority class, all of the weak learners are aggregated for prediction. Experimental results show TrasoBoost outperforms many popular class-imbalance learning methods.

关键词： machine learning data mining class imbalance over sampling boosting transfer learning

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Full waveform inversion based on the ensemble Kalman filter method using uniform sampling without replacement

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Science Bulletin 2019年第5期64卷 321-330页

作者： Jian Wang Dinghui Yang Hao Jing Hao Wu Department of Mathematical Sciences Tsinghua University

Full waveform inversion(FWI) has been increasingly more and more important in seismology to better understand the interior structure of the Earth. FWI, by taking advantage of both the traveltime and amplitude in the data, provides high-resolution model parameters of the earth which can produce images with high resolution. However, this inversion method conventionally suffers from non-uniqueness due to many local minima of the objective function and large computing costs. In this study, we propose a new FWI method in a semi-random framework by integrating the ensemble Kalman filter and uniform sampling without replacement. Numerical results demonstrate that the new method can achieve highresolution results and a wider convergence domain. Accordingly, the new method overcomes the disadvantage of conventional FWIs that depend strongly on the initial model.

关键词： Data assimilation Ensemble Kalman filter Uniform sampling without replacement Full waveform inversion

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