多分类计数配对资料Bowker检验的分割及其应用

目的检验多分类配对计数资料。方法采用Bowker检验并对平方表进行分割,再对四格表进行McNemar检验。结果对平方表分割后,可以对Bowker检验的结果进行更进一步的分析。结论Bowker检验及平方表分割后的McNemar检验都是非参数统计方法,用于检验多分类配对计数资料。

肉在零售过程中的重量损失

在国外的肉店里,肉品一般都是以小包装分割肉陈列在冷却橱窗中,加上灯光照明,供消费者选购.这种售货方式常造成重量损失,即经济损失.因国内已开始小包装肉的生产和销售,特将英国有关资料编摘如下,供参考.

动态楔形因子的研究

目的:在1978年,P.K.Kijewski等人[1]提出动态楔形技术(DW)之后,20世纪90年代,这项技术开始应用于Vari-an加速器上,并根据Varian加速器的特性给出了求增强型动态楔形因子(EDWF)的公式[2]。然而,这个公式是否能应用于所有的医用直线加速器呢?方法:以Siemens Primus医用直线加速器为对象进行了实验验证。对于其他类型的加速器,如果公式适用,公式中所出现的五个待定参量a0,a1,b1,α,β是否需要重新修正呢?结果:通过实验发现,Varian加速器的动态楔形因子的计算公式及公式中出现的参量用于Siemens Primus医用直线加速器时,将会出现3%误差。结论:用通过实验按照Siemens Primus加速器特性重新拟出的修正公式和修正参数则可以把误差控制在1%范围内。

快速排序算法的一点改进

数据排序是一项相当有意义的算法。根据[2]文译成的[1]文中在第三章介绍了几种不同的排序算法,并分析了各自的效率,指出快速排序算法的效率是最优的,该算法的框图参见[1]文中第33页、34页图Ⅲ-6a与Ⅲ-6b。然而,这个快速排序算法存在一个疏忽之处,当所排数据中出现三个或三个以上相同数据时,可能会出现部分错排。例如,对于如下这组数据:

谈谈“分帐”与“并帐”

谈谈“分帐”与“并帐”陈利瑜，沈熙元，傅宁人“分帐”是指将一套总帐及其所属的明细帐，划分为两套或两套以上总帐和明细帐的帐务处理；“并帐”与“分帐”相反，是指将两套或两套以上总帐及其所属明细帐，合并为一套总帐和明细帐的帐务处理。企业分帐一般有两种方式。...

基于可编程硬件的NFV数据包加速处理结构

针对网络功能虚拟化(Network Function Virtualization,NFV)在通用服务器中部署的处理性能受限问题,该文提出了一种基于硬件加速的虚拟网络功能(Virtual Network Function,VNF)处理结构:FARD(Function Adaptive and Resource Dividable hardware structure).通过可编程的包头解析器和动作处理器,FARD可实现任意L2/3/4层功能实例的硬件加速处理;通过动态可分割的匹配表结构,FARD支持不同功能实例间的资源动态分配和隔离.基于NetFPGA-10G的实验结果表明,对比基于纯软件实现的VNF,FARD加速结构提升了近60倍的包处理吞吐率.

Wheel-Individual Estimation of the Friction Potential for Split Friction and Changing Friction Conditions for the Application in an Automated Emergency Braking System

Including information of the current road surface conditions can significantly improve the effectiveness of an AEB （automated emergency braking） system to avoid accidents or reduce the injury severity in rear-end crashes. A method to estimate the friction potential based on on-board sensor information is shown in this work. This work expands the scope of existing investigations on whether the accuracy needed for the warning and intervention strategies of AEB can be reached with the proposed method. First, the bandwidth of surface conditions investigated is extended by including low friction surfaces comparable to ice. Second, situations of changing surface conditions and wheel-individual surface conditions were evaluated. Finally, estimation based on different sensor sets was conducted with regard to series application. The investigations are based on measurements performed on a proving ground. The main emphasis was placed on estimation during longitudinal driving conditions. The used sensors include advanced vehicle dynamics measurement equipment as well as standard on-board sensors of the vehicle.

UNSUPERVISED POLINSAR CLASSIFICATION BASED ON OPTIMAL COHERENCE SET

Aiming to solve the misclassification problems of unsupervised polarimetric Wishart clas- sification algorithm based on Freeman decomposition, an unsupervised Polarimetric Synthetic Aper- ture Radar （SAR） Interferotnery （PolInSAR） classification algorithm based on optimal coherence set parameters is studied and proposed. This algorithm uses the result of Freeman decomposition to divide the image into three basic categories including surface scattering, volume scattering, and double-bounce Then, the PolInSAR optimal coherence set parameters are used to finely divide each of the three basic categories into 9 categories, and the whole image is divided into 27 categories. Because both the Freeman decomposition result and optimal coherence set parameters indicate specific scattering characteristics, the whole image is merged into 16 categories based on physical meaning. At last, the Wishart cluster is employed to obtain the final classification result. To preserve the purity of scattering characteristics, pixels with similar scattering characteristics are restricted to be classified with other pixels. The final classification results effectively resolve the misclassification problem, not only the buildings can be effectively distinguished from vegetation in urban areas, but also the road is well distinguished from grass. In this paper, the E-SAR PolInSAR data of German Aerospace Center （DLR） are used to verify the effectiveness of the algorithm.

White Layer of Hard Turned Surface by Sharp CBN Tool

White layers in hard turned surfaces were identified and measured as a function ot turning parameters based on the Taguchi method. It reveals that white layers generate on the machine surface in the absence of tool flank wear, and white layer depth varies with the different combinations of hard turning parameters. Turning speed has the most important impact on white layer depth, feed rate follows, and cutting depth at last. The white layer generation consequently suggests a strong couple relation to the heat generation and thermal process of hard turning operation. White layer disappears under an optimal combination of turning parameters by Taguchi method. It suggests that a superior surface integrity without white layer is feasible under some selected combinations of turning parameters by a sharp CBN cutting tool.

Facial Expression Recognition by Split Rectangle Based Adaboost

The facial expression recognition systn using the Ariaboost based on the Split Rectangle feature is proposed in this paper. This system provides more various featmes in increasing speed and accuracy than the Haarolike featrue of Viola, which is commonly used for the Adaboost training algorithm. The Split Rectangle feature uses the nmsk-like shape composed with 2 independent rectangles, instead of using mask-like shape of Haar-like feature, which is composed of 2 --4 adhered rectangles of Viola. Split Rectangle feature has less di- verged operation than the Haar-like feaze. It also requires less oper- ation because the stun of pixels requires ordy two rectangles. Split Rectangle feature provides various and fast features to the Adaboost, which produrces the strong classifier with increased accuracy and speed. In the experiment, the system had 5.92 ms performance speed and 84 %--94 % accuracy by leaming 5 facial expressions, neutral, happiness, sadness, anger and surprise with the use of the Adaboost based on the Split Rectangle feature.

Dividing Process in Base-10 Number System Reversed Dividing Process for 1/X

A new set of steps for dividing process, the Reversed Dividing Process, is introduced, in which the position based number representation digits for the value of l/X are reversely output one by one compared with digit output order of the normal dividing process.

Correct Path-Integral Formulation of Quantum Thermal Field Theory in Coherent State Representation

The path-integral quantization of thermal scalar, vector, and spinor fields is performed newly in the coherent-state representation. In doing this, we choose the thermal electrodynamics and psi(4) theory as,examples. By this quantization, correct expressions of the partition functions and the generating functionals for the quantum thermal electrodynamics and psi(4) theory are obtained in the coherent-state representation. These expressions allow us to perform analytical calculations of the partition functions and generating functionals and therefore are useful in practical applications. Especially, the perturbative expansions of the generating functionals are derived specifically by virtue of the stationary-phase method. The generating functionals formulated in the position space are re-derived from the ones given in the coherent-state representation.

A flower image retrieval method based on ROI feature

Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

Building Extraction from DSM Acquired by Airborne 3D Image

Segmentation and edge regulation are studied deeply to extract buildings fromDSM data produced in this paper. Building segmentation is the first step to extract buildings, anda new segmentation method-adaptive iterative segmentation considering rati-o mean square-is proposedto extract the contour of buildings effectively. A sub-image (such as 50X50 pixels) of the image isprocessed in sequence, the average gray level and its ratio mean square are calculated first, thenthreshold of the sub-image is selected by using iterative threshold segmentation. The current pixelis segmented according to the threshold, the average gray level and the ratio mean square of thesub-image. The edge points of the building are grouped according to the azimuth of neighbor points,and then the optimal azimuth of the points that belong to the same group can be calculated by usingline interpolation.

Semantic image segmentation with fused CNN features

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network(CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field(CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Surface Reconstruction of Scanned Human Body Using Radial Basis Functions and Adaptive Partition of Unity

It is important to reconstruct a continuous surface representation of the point cloud scanned from a human body. In this paper a new implicit surface method is proposed to reconstruct the human body surface from the points based on the combination of radial basis functions （RBFs） and adaptive partition of unity （PoU）. The whole 3D domain of the scanned human body is firstly subdivided into a set of overlapping subdomalns based on the improved octrees. The smooth local surfaces are then computed in the subdomalns based on RBFs. And finally the global human body surface is reconstructed by blending the local surfaces with the adaptive PoU functions. This method is robust for the surface reconstruction of the scanned human body even with large or non-uniform point cloud which has a sharp density variation.