Robust pairwise matching of interest points with complex wavelets

We present a matching framework to find robust correspondences between image features by considering the spatial information between them. To achieve this, we define spatial constraints on the relative orientation and change in scale between pairs of features. A pairwise similarity score, which measures the similarity of features based on these spatial constraints, is considered. The pairwise similarity scores for all pairs of candidate correspondences are then accumulated in a 2-D similarity space. Robust correspondences can be found by searching for clusters in the similarity space, since actual correspondences are expected to form clusters that satisfy similar spatial constraints in this space. As it is difficult to achieve reliable and consistent estimates of scale and orientation, an additional contribution is that these parameters do not need to be determined at the interest point detection stage, which differs from conventional methods. Polar matching of dual-tree complex wavelet transform features is used, since it fits naturally into the framework with the defined spatial constraints. Our tests show that the proposed framework is capable of producing robust correspondences with higher correspondence ratios and reasonable computational efficiency, compared to other well-known algorithms. © 1992-2012 IEEE.

Distribution matching for transduction

Many transductive inference algorithms assume that distributions over training and test estimates should be related, e.g. by providing a large margin of separation on both sets. We use this idea to design a transduction algorithm which can be used without modification for classification, regression, and structured estimation. At its heart we exploit the fact that for a good learner the distributions over the outputs on training and test sets should match. This is a classical two-sample problem which can be solved efficiently in its most general form by using distance measures in Hilbert Space. It turns out that a number of existing heuristics can be viewed as special cases of our approach.

HLA-DRB1等位基因多态性与食管癌遗传易感性研究

目的 :从基因水平探讨湖北地区汉族人食管癌HLA -DRB1等位基因的遗传易感性。方法 :运用序列特异性引物聚合酶链反应结合基因序列分析等技术 ,检测无亲缘关系湖北汉族健康人 136例、食管癌组 4 2例患者的HLA -DRB1等位基因。SAS统计软件数据处理。结果 :湖北地区汉族人食管癌患者与正常人比较 ,HLA -DRB1 0 90 1基因频率显著增高 (0 2 5 0 0vs 0 1397,P =0 0 2 8,OR =2 0 5 3,病因分数 =0 12 82 ) ;两者间其余HLA -DRB1等

HLA-DRB1、-DQB1基因多态性与食管鳞癌遗传关联性

目的　从基因水平探讨食管鳞癌HLA DRB1 , DQB1等位基因的遗传易感性 ,以阐述其免疫遗传学特征。方法　运用序列特异性引物聚合酶链反应技术 ,检测无亲缘关系湖北汉族健康人 1 36例、食管鳞癌患者 42例的HLA DRB1 , DQB1等位基因。结果　湖北汉族人食管鳞癌患者与正常人比较 ,HLA DRB1 0 90 1等位基因分布频率显著增高 (0 .2 50 0比 0 .1 397,P =0 .0 2 8,OR =2 .0 53 ,病因分数 =0 .1 2 82 ) ,HLA DQB1 0 30

HLA-DRB1与胃腺癌临床特征及Hp感染关联性研究

<正> 人类主要组织相容性复合体(major histocompatibility complex,MHC)即人类白细胞抗原(human leucocyte antigen,HLA)复合体,定位于人第6号染色体短臂(6p23)上,具有单倍体(haplotype)遗传、高度多态性(polymorphism)、连锁不平衡(linkage disequilibrium)等遗传特征。我们运用序列特异性引物聚合酶链反应(sequence specific primer based polymerase chain

湖北汉族人大肠癌HLA-DRB1等位基因遗传易感性研究

目的　探讨湖北汉族人 HL A- DRB1等位基因与大肠癌遗传相关性。方法　针对 HL A- DRB1等位基因第 2外显子多态性 ,设计 2 3对引物的序列特异性引物聚合酶链反应 ,结合等位基因序列分析 ,检测了无亲缘关系的湖北籍汉族健康人 136名及大肠癌患者 72例的 HL A- DRB1基因。 SAS软件进行数据处理。结果　湖北地区汉族人大肠癌患者与正常人比较 ,HL A- DRB1* 0 90 1等位基因分布频率 0 .2 2 92 vs0 .1397(P<0 .0 0 5 ,OR=2 .182

HLA-DQB1*0301与胃腺癌及幽门螺杆菌感染的关系

为探讨HLA DQB1等位基因与胃腺癌临床特征及其幽门螺杆菌 (Hp)感染的关联性 ,运用序列特异性引物聚合酶链反应技术 ,检测无亲缘关系湖北汉族健康人 136例、胃癌组 6 3例患者的HLA DQB1基因。内镜活检、Giemsa染色和 (或 )外周血ELISA检查胃粘膜Hp感染情况。SAS软件统计处理。结果表明HLA DQB1 0 30 1与湖北汉族人胃腺癌呈正关联。携带与非携带该等位基因患者 ,其临床特征包括患者平均患病年龄、性别比、肿瘤原发部位、肿瘤TNM分期、肿瘤细胞分化程度 ,以及Hp感染率等情

湖北食管癌HLA-DQB1的基因多态性

目的从基因水平探讨湖北地区汉族人食管癌 HEN-DQB1等位基因的遗传易感性.方法运用序列特异性引物聚合酶链反应技术,检测无亲缘关系湖北汉族健康人136例、食管癌组42例患者的 HLA-DQB1等位基因.SAS system 统计软件数据处理.结果湖北汉族人食管癌患者与正常人比较,HEN-DQB1*0301基因频率显著增高(0.2976 vs 0.1875),P=0.046,OR=1.835,病因分数=0.1354);两组间 HLA-DQB1其余各等位基因分布频率的比较,HLA-DQB1*0201(0.0

湖北汉族人胃腺癌HLA-DRB1等位基因遗传易感性

湖北省教委自然科学基金资 助项目( 98A0 47)

Matching an oscillator model to a phase response curve

The Phase Response Curve (PRC) has proven a useful tool for the reduction of complex oscillator models. It is also an information often experimentally available to the biologist. This paper introduces a numerical tool based on the sensitivity analysis of the PRC to adapt initial model parameters in order to match a particular PRC shape. We illustrate the approach on a simple biochemical model of circadian oscillator. © 2011 IEEE.

Probability-Matching Predictors for Extreme Extremes

A location- and scale-invariant predictor is constructed which exhibits good probability matching for extreme predictions outside the span of data drawn from a variety of (stationary) general distributions. It is constructed via the three-parameter {\mu, \sigma, \xi} Generalized Pareto Distribution (GPD). The predictor is designed to provide matching probability exactly for the GPD in both the extreme heavy-tailed limit and the extreme bounded-tail limit, whilst giving a good approximation to probability matching at all intermediate values of the tail parameter \xi. The predictor is valid even for small sample sizes N, even as small as N = 3. The main purpose of this paper is to present the somewhat lengthy derivations which draw heavily on the theory of hypergeometric functions, particularly the Lauricella functions. Whilst the construction is inspired by the Bayesian approach to the prediction problem, it considers the case of vague prior information about both parameters and model, and all derivations are undertaken using sampling theory.

Output feedback H2 model matching for decentralized systems with delays

This paper gives a new solution to the output feedback H2 model matching problem for a large class of delayed information sharing patterns. Existing methods for similar problems typically reduce the decentralized problem to a centralized problem of higher state dimension. In contrast, this paper demonstrates that the decentralized model matching solution can be constructed from the original centralized solution via quadratic programming. © 2013 AACC American Automatic Control Council.