In this paper,we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model.We address the problem...In this paper,we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model.We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction.This is often the case of natural images composed of both homogeneous and textured regions.Because these images cannot be in general directly processed by the gray-level information,we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry.Then,we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest.The existence of a minimizing solution to the proposed segmentation model is proven.Finally, a texture segmentation algorithm based on the Split-Bregman method is introduced to extract meaningful objects in a fast way.Promising synthetic and real-world results for gray-scale and color images are presented.展开更多
A modified Gauss-type Proximal Point Algorithm (modified GG-PPA) is presented in this paper for solving the generalized equations like 0 ∈T(x), where T is a set-valued mapping acts between two different Bana...A modified Gauss-type Proximal Point Algorithm (modified GG-PPA) is presented in this paper for solving the generalized equations like 0 ∈T(x), where T is a set-valued mapping acts between two different Banach spaces X and Y. By considering some necessary assumptions, we show the existence of any sequence generated by the modified GG-PPA and prove the semi-local and local convergence results by using metrically regular mapping. In addition, we give a numerical example to justify the result of semi-local convergence.展开更多
A detailed quantum mechanical analysis of electronic disposition of five aminopyrimidoisoquinolinequinones (APIQs) was performed after extraction of this subset of compounds from a larger data set of APIQs via a repor...A detailed quantum mechanical analysis of electronic disposition of five aminopyrimidoisoquinolinequinones (APIQs) was performed after extraction of this subset of compounds from a larger data set of APIQs via a reported clustering methodology (Elfaki, et al. 2020). Both semi empirical PM3 method and DFT quantum mechanical methods were used to calculate global and local quantum mechanical descriptors (QMDs) to define the electronic environment of these molecules in attempt to rationalize their observed anti-cancer response variability. The biological response is the anticancer activity against human gastric adenocarcenoma (AGS) cell line. The correlation matrix between the calculated global electronic descriptors and biological activity demonstrated that the global dipole moment gives the highest correlation. The local electronic environment was analysed by The Mullikan charges (MC) and Fukui functions for N-5, C-6, C-8 in addition to the N atom of phenylamino side group at C-8. MCs furnished no useful information as each of these atoms had almost identical MC values for all the five compounds with exception of C-6 which gave varied values. Regressing MCs of C-6 against the response traces 60% of the latter variability. As C-6 is an extra annular methyl carbon adjacent to N-5 in isoquinoline residue of APIQ, we reasoned that the chemical reactivities of 4 out of the 5 APIQs might be due to a Chichibabin-type tautomerism implying a possible alkylation aspect in their mechanism of action. The corresponding Fukui functions (f<sup>-</sup>, f<sup>+</sup> and f<sup>0</sup>) showed a considerable consistency with the patterns of chemical reactivity exhibited by this small set of APIQs.展开更多
针对有标记故障样本不足和故障特征集维数过高的问题,提出基于正交半监督局部Fisher判别分析(Orthogonal semi-supervised local Fisher discriminant analysis,OSELF)的故障诊断方法。所提出的OSELF能够充分地利用蕴含于无标记故障样...针对有标记故障样本不足和故障特征集维数过高的问题,提出基于正交半监督局部Fisher判别分析(Orthogonal semi-supervised local Fisher discriminant analysis,OSELF)的故障诊断方法。所提出的OSELF能够充分地利用蕴含于无标记故障样本中的故障信息,避免了因有标记故障样本不足引起的过学习问题,同时采用正交迭代方式求解最优正交映射矩阵,克服现有方法无法得到正交映射矩阵的不足。正交映射矩阵的基矢量统计不相关,可有效地提高所得低维特征矢量的可辨识性。通过正交映射矩阵对故障样本集和新增样本进行维数约简,并将维数约简的结果输入粗糙优化k最近邻分类器(Coarse to fine k nearest neighbor classifier,CFKNNC)进行学习训练和故障识别。所提方法集成了OSELF在维数约简和CFKNNC在模式识别的优势,有效地提高了故障诊断的精度。通过齿轮箱故障模拟试验验证了该方法的有效性。展开更多
基金supported by Swiss National Science Foundation Grant #205320-101621supported by ONR N00014-03-1-0071
文摘In this paper,we present an efficient approach for unsupervised segmentation of natural and textural images based on the extraction of image features and a fast active contour segmentation model.We address the problem of textures where neither the gray-level information nor the boundary information is adequate for object extraction.This is often the case of natural images composed of both homogeneous and textured regions.Because these images cannot be in general directly processed by the gray-level information,we propose a new texture descriptor which intrinsically defines the geometry of textures using semi-local image information and tools from differential geometry.Then,we use the popular Kullback-Leibler distance to design an active contour model which distinguishes the background and textures of interest.The existence of a minimizing solution to the proposed segmentation model is proven.Finally, a texture segmentation algorithm based on the Split-Bregman method is introduced to extract meaningful objects in a fast way.Promising synthetic and real-world results for gray-scale and color images are presented.
文摘A modified Gauss-type Proximal Point Algorithm (modified GG-PPA) is presented in this paper for solving the generalized equations like 0 ∈T(x), where T is a set-valued mapping acts between two different Banach spaces X and Y. By considering some necessary assumptions, we show the existence of any sequence generated by the modified GG-PPA and prove the semi-local and local convergence results by using metrically regular mapping. In addition, we give a numerical example to justify the result of semi-local convergence.
文摘A detailed quantum mechanical analysis of electronic disposition of five aminopyrimidoisoquinolinequinones (APIQs) was performed after extraction of this subset of compounds from a larger data set of APIQs via a reported clustering methodology (Elfaki, et al. 2020). Both semi empirical PM3 method and DFT quantum mechanical methods were used to calculate global and local quantum mechanical descriptors (QMDs) to define the electronic environment of these molecules in attempt to rationalize their observed anti-cancer response variability. The biological response is the anticancer activity against human gastric adenocarcenoma (AGS) cell line. The correlation matrix between the calculated global electronic descriptors and biological activity demonstrated that the global dipole moment gives the highest correlation. The local electronic environment was analysed by The Mullikan charges (MC) and Fukui functions for N-5, C-6, C-8 in addition to the N atom of phenylamino side group at C-8. MCs furnished no useful information as each of these atoms had almost identical MC values for all the five compounds with exception of C-6 which gave varied values. Regressing MCs of C-6 against the response traces 60% of the latter variability. As C-6 is an extra annular methyl carbon adjacent to N-5 in isoquinoline residue of APIQ, we reasoned that the chemical reactivities of 4 out of the 5 APIQs might be due to a Chichibabin-type tautomerism implying a possible alkylation aspect in their mechanism of action. The corresponding Fukui functions (f<sup>-</sup>, f<sup>+</sup> and f<sup>0</sup>) showed a considerable consistency with the patterns of chemical reactivity exhibited by this small set of APIQs.
文摘针对有标记故障样本不足和故障特征集维数过高的问题,提出基于正交半监督局部Fisher判别分析(Orthogonal semi-supervised local Fisher discriminant analysis,OSELF)的故障诊断方法。所提出的OSELF能够充分地利用蕴含于无标记故障样本中的故障信息,避免了因有标记故障样本不足引起的过学习问题,同时采用正交迭代方式求解最优正交映射矩阵,克服现有方法无法得到正交映射矩阵的不足。正交映射矩阵的基矢量统计不相关,可有效地提高所得低维特征矢量的可辨识性。通过正交映射矩阵对故障样本集和新增样本进行维数约简,并将维数约简的结果输入粗糙优化k最近邻分类器(Coarse to fine k nearest neighbor classifier,CFKNNC)进行学习训练和故障识别。所提方法集成了OSELF在维数约简和CFKNNC在模式识别的优势,有效地提高了故障诊断的精度。通过齿轮箱故障模拟试验验证了该方法的有效性。
