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(3R,3aS,6R,6aR)-3-(1-Nitroethyl)perhydrofuro[3,2-b]furan-3,6-diol
Jing-Yu Zhang,Jing Yang
Acta Crystallographica Section E , 2010, DOI: 10.1107/s1600536810022774
Abstract: The molecule of the title compound, C8H13NO6, a sucrose derivative, consists of two fused tetrahydrofuran rings having the cis arrangement at the ring junctions, giving a V-shaped molecule. An intramolecular O—H...O interaction occurs. Intermolecular O—H...O hydrogen bonds help to stabilize the crystal structure.
Study on collimation and shielding of the back-streaming neutrons at the CSNS target
Jing Han-Tao,Tang Jing-Yu,Yang Zheng
Physics , 2013,
Abstract: The back-streaming neutrons from the spallation target at CSNS are very intense, and can pose serious damage problems for the devices in the accelerator-target interface region. To tackle the problems, a possible scheme for this region was studied, namely a specially designed optics for the proton beam line produces two beam waists, and two collimators are placed at the two waist positions to maximize the collimation effect of the back-streaming neutrons. Detailed Monte Carlo simulations with the beams in the two different CSNS phases show the effectiveness of the collimation system, and the radiation dose rate decreases largely in the interface section. This can ensure the use of epoxy coils for the last magnets and other devices in the beam transport line with reasonable lifetimes, e.g. thirty years. The design philosophy for such an accelerator-target interface region can also be applicable to other high-power proton beam applications.
Skew Document Image Detection Method Based on Windows Transform
基于视窗的OCR页面图像倾斜检测方法

JIN Cong,WEI Zhi-lai,YANG Jing-yu,JIN Cong,WEI Zhi-lai,YANG Jing-yu,JIN Cong,WEI Zhi-lai,YANG Jing-yu,
靳从
,魏之来,杨静宇

中国图象图形学报 , 2004,
Abstract: During OCR(optical character recognition) image scanning, the document images, are always placed slantwise to some extent. When the skew degree is big enough, it will influence the effect of document analysis and lower the recognition accuracy as the algorithm for layout analysis and character recognition are very sensitive to page skew. So the skew degree detection is a very important step during the preprocessing of document analysis. In this paper, a skew detection method based on the window analysis is presented. First it chooses the suitable windows which are not in the margin but in the layout of a printed page. Then according to the kind of contents, just like tables, text lines, images and etc., it uses the different methods to pre-processing the windows image. To overcome the large computing, the third step is to blur the text lines and image from the window. The forth step is to detect the edges of the blurring regions .At last it uses a straight line fitting to the edges, and gets the skew angle. By this method, experimental results show that the skew angles of many kinds of document images can be efficiently and accurately detected, and it has sufficient adaptability.
Theory of Fisher Linear Discriminant Analysis and Its Application
Fisher线性鉴别分析的理论研究及其应用

YANG Jian,YANG Jing-Yu,Ye Hui,
杨健
,杨静宇,叶晖

自动化学报 , 2003,
Abstract: In high dimensional and small sample size case, how to extract the optimal Fisher discriminant features efficiently remains unsolved. In this paper, we take advantage of the idea of compressive mapping and isomorphic mapping, and gain a general algorithm for the computation of the optimal discriminant vectors in high dimensional and singular case. Our algorithm runs in a low dimensional transformed space, and leads to significant computational reduction. Furthermore, a uniform algorithm framework for Fisher discriminant analysis in singular case is developed. Based on this framework, the generalized Foley Sammon discriminant analysis (FSDA) and Jin Yang uncorrelated discriminant analysis (JYDA) are presented firstly. Then, a combined Fisher discriminant analysis (CFDA) is developed, which not only has the advantages of FSDA and JYDA but also overcomes their weakness. The CFDA is tested on the ORL face image database, the classification result is very robust, with a recognition accuracy of 97%. Experimental results demonstrate that CFDA is better than FSDA and JYDA and is superior to Eigenfaces and Fisherfaces as well.
The Theory Analysis on FSDVS and an Optimal Model
Foley—Sammon鉴别矢量集理论分析及优化模型

XU Yong YANG Qiang YANG Jing-Yu,
徐勇
,杨强,杨静宇

计算机科学 , 2003,
Abstract: The attribute of the maximum of R(ξ) in arbitrary subspace of Rn is discussed dedicatedly. The theory anal-ysis indicates that every F-S discriminant vector is better than respective vector in other discriminant vectors sets,which consist of eigenvectors of sbξ=λswξ. But,the fact that the F-S vectors are statistically correlated degrade the F-S vectors set. Two ways are used to obtain“good“ F-S vectors set. The experiments on Concordia University CEN-PARMI handwritten numeral database suggest that the new vectors set is better than the origin. A new problem mod-el on F-S discriminant vectors set is proposed in this paper. It‘s easily understanding that the problem model is superi-or to the original F-S discriminant vectors set problem model.
A New Method of Fisher Discriminant Analysis with Schur Decomposition
一种新的基于Schur分解的Fisher鉴别分析方法

LIN Yu-Sheng,YANG Jing-Yu,
林宇生
,杨静宇

计算机科学 , 2007,
Abstract: Feature extraction is one of the hot topics in the field of pattern recognition.In this paper,we point out the weakness of the previous methods anda new method of Fisher discriminant analysis with Schur decomposition is pro- posed.Conception of null space is introduced in this paper.Experimental results on ORL face database indicate that the proposed method is valid.
Characteristic Gene Selection via Weighting Principal Components by Singular Values
Jin-Xing Liu, Yong Xu, Chun-Hou Zheng, Yi Wang, Jing-Yu Yang
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0038873
Abstract: Conventional gene selection methods based on principal component analysis (PCA) use only the first principal component (PC) of PCA or sparse PCA to select characteristic genes. These methods indeed assume that the first PC plays a dominant role in gene selection. However, in a number of cases this assumption is not satisfied, so the conventional PCA-based methods usually provide poor selection results. In order to improve the performance of the PCA-based gene selection method, we put forward the gene selection method via weighting PCs by singular values (WPCS). Because different PCs have different importance, the singular values are exploited as the weights to represent the influence on gene selection of different PCs. The ROC curves and AUC statistics on artificial data show that our method outperforms the state-of-the-art methods. Moreover, experimental results on real gene expression data sets show that our method can extract more characteristic genes in response to abiotic stresses than conventional gene selection methods.
Quadratic Discriminant Analysis Method Based on Virtual Training Samples
采用虚拟训练样本的二次判别分析方法

WANG Wei-Dong,YANG Jing-Yu,
王卫东
,杨静宇

自动化学报 , 2008,
Abstract: The"small sample size"(SSS)problem will cause the singularity and instability of the per class covariance matrices.This paper uses perturbing training samples to produce virtual training samples to overcome singularity of the per class covariance matrices.As a consequence,the classifier based on quadratic discriminant analysis(QDA)can be used directly in classification.The proposed QDA overcomes the problem that the parameters of regularized discriminant analysis(RDA)needs optimizing.Our experiments show that the QDA's recognition accuracy is superior to that of RDA if its parameters are optimized.
SHAPE-BASED HUMAN DETECTION IN INFRARED IMAGE SEQUENCES
红外序列图像中基于形状的人体检测

WANG Jiang-Tao,YANG Jing-Yu,
王江涛
,杨静宇

红外与毫米波学报 , 2007,
Abstract: The human detection problem in infrared image sequences was studied,and a novel detecting approach was presented.GMM(Gauss mixture model)was first adopted to construct a background model.And then on the basis of accurately segmenting the forward objects,a shape-based human representing model was designed.By taking account of occlusions and merging among multi-body,the intensity projection curve was applied to separate single ones.By using human shape models as input vectors,a SVM(support vector machine)was constructed to classify and identify the human bodies.Experimental results on different infrared video sequences show that the proposed method is robust and feasible in single body and multi-body cases.
Model Based Vehicle Detection and Tracking
基于模型的车辆检测与跟踪

HU Yin,YANG Jing-yu,
胡铟
,杨静宇

中国图象图形学报 , 2008,
Abstract: Robust and reliable vehicle detection is the first step in automotive driver assistance systems.In this paper,a new approach of model matching based on curve projection is presented.The similarity measurement is based on the weighted sum of integrity of projection,offset expectation and variance of matched point.A scheme for vehicle detection and tracking is presented based on model matching.Results for natural traffic scenes demonstrate high reliability of the proposed method.
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