This paper presents a curve reconstruction algorithm based on discrete data points and normal vectors using B-splines.The proposed algorithm has been improved in three steps:parameterization of the discrete data point...This paper presents a curve reconstruction algorithm based on discrete data points and normal vectors using B-splines.The proposed algorithm has been improved in three steps:parameterization of the discrete data points with tangent vectors,the B-spline knot vector determination by the selected dominant points based on normal vectors,and the determination of the weight to balancing the two errors of the data points and normal vectors in fitting model.Therefore,we transform the B-spline fitting problem into three sub-problems,and can obtain the B-spline curve adaptively.Compared with the usual fitting method which is based on dominant points selected only by data points,the B-spline curves reconstructed by our approach can retain better geometric shape of the original curves when the given data set contains high strength noises.展开更多
This paper studies the nonzero normal vector fields of immersions homotopic to a map g: Mn→N2n-1. In the case of the stable normal bundle of g being orientable, rather complete results are obtained.
Gradient vector flow （GVF） is an effective external force for active contours, but its iso- tropic nature handicaps its performance. The recently proposed gradient vector flow in the normal direction （NGVF） is ani...Gradient vector flow （GVF） is an effective external force for active contours, but its iso- tropic nature handicaps its performance. The recently proposed gradient vector flow in the normal direction （NGVF） is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it has difficulties forcing a snake into long, thin boundary indentations. In this paper, a novel external force for active contours called normally generalized gradient vector flow （NGGVF） is proposed, which generalizes the NGVF formulation to include two spatially varying weighting functions. Consequently, the proposed NGGVF snake is anisotropic and would improve ac- tive contour convergence into long, thin boundary indentations while maintaining other desirable properties of the NGVF snake, such as enlarged capture range, initialization insensitivity and good convergence at concavities. The advantages on synthetic and real images are demonstrated.展开更多
A molecular vector-type descriptor containing 6 variables is used to describe the structure of aromatic hydrocarbons (AHs) and relate to normal boiling points (bp) of AHs. The col relation coefficient (R) between the ...A molecular vector-type descriptor containing 6 variables is used to describe the structure of aromatic hydrocarbons (AHs) and relate to normal boiling points (bp) of AHs. The col relation coefficient (R) between the estimated bp and experimental bp is 0.9988 and the root mean square error (RMS) is 7.907 degreesC for 66 AHs. The RMS obtained by cross-validation is 9.131 degreesC, which implies the relationship model having good prediction ability.展开更多
粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快...粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快速检测方法。该研究基于近红外光谱分析技术建立了霉情检测模型,对不同霉变程度稻谷进行近红外光谱的快速识别预测研究,旨在开发一种可以快速鉴别霉变稻谷定性、定量模型。研究对4种(2018年牡丹江27号、2019年牡丹江27号、龙粳长粒香和牡响1号)不同霉变程度共960组霉变稻谷样品进行定性判别模型研究,其中一阶导数+9点平滑+因子化法建立的定性判别模型准确度较高,样品之间的距离S均值大于1,分辨效果好,通过留一交互验证验证模型的平均准确率为93.00%;基于近红外光谱对4种不同霉变程度共300组霉变稻谷样品进行霉菌菌落总数的定量模型研究,通过矢量归一化法+偏最小二乘法(partial least squares,PLS)定量分析建立定量判别模型,其交叉验证的均方根误差(root mean square error of cross-validation,RMSECV)、决定系数(corrlation coefficient of determination,R^(2))、性能与偏差之比(ratio of performance to deviation,RPD)和预测均方根误差(root mean squared error of predicition,RMSEP)分别为0.470、0.904 5、3.24和0.45,模型精确度较好的。经过分析方法优选后而建立的霉变判别模型显示,霉变是影响近红外光谱变化的主导因素,而稻谷的品种与年际对其影响较小。研究结果可为基于近红外光谱分析技术对不同运输过程中的稻谷实现快速预测其霉变程度或其霉菌数量以及用于集装箱内粮食霉变情况监控在线实时监测装备的研究提供参考。展开更多
A novel approach is proposed to detect the normal vector to product surface in real time for the robotic precision drilling system in aircraft component assembly, and the auto-normalization algorithm is presented base...A novel approach is proposed to detect the normal vector to product surface in real time for the robotic precision drilling system in aircraft component assembly, and the auto-normalization algorithm is presented based on the detection system. Firstly, the deviation between the normal vector and the spindle axis is measured by the four laser displacement sensors installed at the head of the multi-function end effector. Then, the robot target attitude is inversely solved according to the auto-normalization algorithm. Finally, adjust the robot to the target attitude via pitch and yaw rotations about the tool center point and the spindle axis is corrected in line with the normal vector simultaneously. To test and verify the auto-normalization algorithm, an experimental platform is established in which the laser tracker is introduced for accurate measurement. The results show that the deviations between the corrected spindle axis and the normal vector are all reduced to less than 0.5°, with the mean value 0.32°. It is demonstrated the detection method and the autonormalization algorithm are feasible and reliable.展开更多
Over the past few years,nonlinear manifold learning has been widely exploited in data analysis and machine learning.This paper presents a novel manifold learning algorithm,named atlas compatibility transformation(ACT)...Over the past few years,nonlinear manifold learning has been widely exploited in data analysis and machine learning.This paper presents a novel manifold learning algorithm,named atlas compatibility transformation(ACT),It solves two problems which correspond to two key points in the manifold definition:how to chart a given manifold and how to align the patches to a global coordinate space based on compatibility.For the first problem,we divide the manifold into maximal linear patch(MLP) based on normal vector field of the manifold.For the second problem,we align patches into an optimal global system by solving a generalized eigenvalue problem.Compared with the traditional method,the ACT could deal with noise datasets and fragment datasets.Moreover,the mappings between high dimensional space and low dimensional space are given.Experiments on both synthetic data and real-world data indicate the effection of the proposed algorithm.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.1187113711572081)the Program for Liaoning Innovation Talents in University(No.LCR2018001)
文摘This paper presents a curve reconstruction algorithm based on discrete data points and normal vectors using B-splines.The proposed algorithm has been improved in three steps:parameterization of the discrete data points with tangent vectors,the B-spline knot vector determination by the selected dominant points based on normal vectors,and the determination of the weight to balancing the two errors of the data points and normal vectors in fitting model.Therefore,we transform the B-spline fitting problem into three sub-problems,and can obtain the B-spline curve adaptively.Compared with the usual fitting method which is based on dominant points selected only by data points,the B-spline curves reconstructed by our approach can retain better geometric shape of the original curves when the given data set contains high strength noises.
文摘This paper studies the nonzero normal vector fields of immersions homotopic to a map g: Mn→N2n-1. In the case of the stable normal bundle of g being orientable, rather complete results are obtained.
基金Supported by the National Natural Science Foundation of China(60805004)the State Key Lab of Space Medicine Fundamen-tals and Application(SMFA09A16)
文摘Gradient vector flow （GVF） is an effective external force for active contours, but its iso- tropic nature handicaps its performance. The recently proposed gradient vector flow in the normal direction （NGVF） is anisotropic since it only keeps the diffusion along the normal direction of the isophotes; however, it has difficulties forcing a snake into long, thin boundary indentations. In this paper, a novel external force for active contours called normally generalized gradient vector flow （NGGVF） is proposed, which generalizes the NGVF formulation to include two spatially varying weighting functions. Consequently, the proposed NGGVF snake is anisotropic and would improve ac- tive contour convergence into long, thin boundary indentations while maintaining other desirable properties of the NGVF snake, such as enlarged capture range, initialization insensitivity and good convergence at concavities. The advantages on synthetic and real images are demonstrated.
文摘A molecular vector-type descriptor containing 6 variables is used to describe the structure of aromatic hydrocarbons (AHs) and relate to normal boiling points (bp) of AHs. The col relation coefficient (R) between the estimated bp and experimental bp is 0.9988 and the root mean square error (RMS) is 7.907 degreesC for 66 AHs. The RMS obtained by cross-validation is 9.131 degreesC, which implies the relationship model having good prediction ability.
文摘粮食的霉变严重影响其品质与食品安全,而常规检测手段存在速度慢以及需要大量专业实验室设备和操作人员等缺陷,近红外光谱分析技术具有分析速度快、非破坏性、测试重现性好、易于实现在线分析和操作简单等诸多优点,是一种很有潜力的快速检测方法。该研究基于近红外光谱分析技术建立了霉情检测模型,对不同霉变程度稻谷进行近红外光谱的快速识别预测研究,旨在开发一种可以快速鉴别霉变稻谷定性、定量模型。研究对4种(2018年牡丹江27号、2019年牡丹江27号、龙粳长粒香和牡响1号)不同霉变程度共960组霉变稻谷样品进行定性判别模型研究,其中一阶导数+9点平滑+因子化法建立的定性判别模型准确度较高,样品之间的距离S均值大于1,分辨效果好,通过留一交互验证验证模型的平均准确率为93.00%;基于近红外光谱对4种不同霉变程度共300组霉变稻谷样品进行霉菌菌落总数的定量模型研究,通过矢量归一化法+偏最小二乘法(partial least squares,PLS)定量分析建立定量判别模型,其交叉验证的均方根误差(root mean square error of cross-validation,RMSECV)、决定系数(corrlation coefficient of determination,R^(2))、性能与偏差之比(ratio of performance to deviation,RPD)和预测均方根误差(root mean squared error of predicition,RMSEP)分别为0.470、0.904 5、3.24和0.45,模型精确度较好的。经过分析方法优选后而建立的霉变判别模型显示,霉变是影响近红外光谱变化的主导因素,而稻谷的品种与年际对其影响较小。研究结果可为基于近红外光谱分析技术对不同运输过程中的稻谷实现快速预测其霉变程度或其霉菌数量以及用于集装箱内粮食霉变情况监控在线实时监测装备的研究提供参考。
基金co-supported by Key Technology Research and Development Program of Jiangsu Province, China (No. BE2011178)the Aviation Industry Innovation Fund (No. AC2011214)
文摘A novel approach is proposed to detect the normal vector to product surface in real time for the robotic precision drilling system in aircraft component assembly, and the auto-normalization algorithm is presented based on the detection system. Firstly, the deviation between the normal vector and the spindle axis is measured by the four laser displacement sensors installed at the head of the multi-function end effector. Then, the robot target attitude is inversely solved according to the auto-normalization algorithm. Finally, adjust the robot to the target attitude via pitch and yaw rotations about the tool center point and the spindle axis is corrected in line with the normal vector simultaneously. To test and verify the auto-normalization algorithm, an experimental platform is established in which the laser tracker is introduced for accurate measurement. The results show that the deviations between the corrected spindle axis and the normal vector are all reduced to less than 0.5°, with the mean value 0.32°. It is demonstrated the detection method and the autonormalization algorithm are feasible and reliable.
基金supported by National Natural Science Foundation of China(No.61171145)Shanghai Educational Development Fundation(No.12ZZ083)
文摘Over the past few years,nonlinear manifold learning has been widely exploited in data analysis and machine learning.This paper presents a novel manifold learning algorithm,named atlas compatibility transformation(ACT),It solves two problems which correspond to two key points in the manifold definition:how to chart a given manifold and how to align the patches to a global coordinate space based on compatibility.For the first problem,we divide the manifold into maximal linear patch(MLP) based on normal vector field of the manifold.For the second problem,we align patches into an optimal global system by solving a generalized eigenvalue problem.Compared with the traditional method,the ACT could deal with noise datasets and fragment datasets.Moreover,the mappings between high dimensional space and low dimensional space are given.Experiments on both synthetic data and real-world data indicate the effection of the proposed algorithm.
