TG 328B型机械天平的示值误差测量不确定度评定

本文主要介绍了TG328B型机械天平示值误差测量不确定度的评定和分析。     

An analysis of the transition proportion for binarization in handwritten historical documents

In this paper, we will present a mathematical analysis of the transition proportion for the normal threshold (NorT) based on the transition method. The transition proportion is a parameter of NorT which plays an important role in the theoretical development of NorT. We will study the mathematical forms of the quadratic equation from which NorT is computed. Through this analysis, we will describe how the transition proportion affects NorT. Then, we will prove that NorT is robust to inaccurate estimations of the transition proportion. Furthermore, our analysis extends to thresholding methods that rely on Bayes rule, and it also gives the mathematical bases for potential applications of the transition proportion as a feature to estimate stroke width and detect regions of interest. In the majority of our experiments, we used a database composed of small images that were extracted from DIBCO 2009 and H-DIBCO 2010 benchmarks. However, we also report evaluations using the original (H-)DIBCO?s benchmarks.     

Reliability of an Independent Component,s-Spare System with Exponential Life Times and General Repair Times

In this paper, the reliability of a system with N independent components supplied with a pool of s spares is investigated. The components have an exponential life time distribution and the failed components are repaired, one at a time, with a general repair time distribution. Numerical results are presented for the mean time to system failure (system is said to fail when a component fails with no spare available) and the reliability of the system in some special cases of interest.     

Blind image quality assessment with improved natural scene statistics model

No-reference (NR)/blind image quality assessment (IQA) metrics play an important role in the area of image processing. Natural scene statistics (NSS) model assumes that natural images possess certain regular statistical properties and is widely used in NR IQA metrics. Most existing NSS-based NR algorithms are achieved by measuring the variation of image statistics, which are characterized by the fitting parameters of NSS model, across different distortions. However, distortions not only change the image statistics, but also disturb the statistical regularity held by natural images. As a result, the distribution of distorted images can not well follow the NSS model. There exists fitting error between the real distribution of the distorted image and the fitted one under certain NSS model. In this paper, the statistical distributions of the distorted images are discussed in detail. We suggest to take the fitting errors into account as well as the fitting parameters for feature extraction, and propose a novel NR IQA algorithm. Experimental results on several image databases demonstrate that the proposed metric performs highly consistent with human visual perception.     

An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images

Malignant and benign types of tumor infiltrated in human brain are diagnosed with the help of an MRI scanner. With the slice images obtained using an MRI scanner, certain image processing techniques are utilized to have a clear anatomy of brain tissues. One such image processing technique is hybrid self-organizing map (SOM) with fuzzy K means (FKM) algorithm, which offers successful identification of tumor and good segmentation of tissue regions present inside the tissues of brain. The proposed algorithm is efficient in terms of Jaccard Index, Dice Overlap Index (DOI), sensitivity, specificity, peak signal to noise ratio (PSNR), mean square error (MSE), computational time and memory requirement. The algorithm proposed through this paper has better data handling capacities and it also performs efficient processing upon the input magnetic resonance (MR) brain images. Automatic detection of tumor region in MR (magnetic resonance) brain images has a high impact in helping the radio surgeons assess the size of the tumor present inside the tissues of brain and it also supports in identifying the exact topographical location of tumor region. The proposed hybrid SOM-FKM algorithm assists the radio surgeon by providing an automated tissue segmentation and tumor identification, thus enhancing radio therapeutic procedures. The efficiency of the proposed technique is verified using the clinical images obtained from four patients, along with the images taken from Harvard Brain Repository.     

Interference in the Manufacture of Nuclepore Filters

In connection with the manufacture of Nuclepore filters at Vallecitos, considerations that are probabilistic in nature become important. One such consideration deals with the probabilities of interference of circles of uniform radius placed at random on a surface. Such probabilities have been found by several investigators in different contexts. A second consideration is three dimensional in that one must find the probability that cyclinders formed by passing the circles through a plate of given thickness at random angles will intersect completely through the plate. An approximate solution is found to this problem as a function of the ratio of plate thickness to circle radius. Small scale simulations are included to check the adequacy of the approximations.     

电学计量检定及测量的误差原因讨论构建

电学计量检定及测量在实际的操作过程中容易受到相关存在因素的影响，可能会产生系统误差，对于各种数据的真实有效性造成了较大的影响。因此，技术人员需要对电学计量检定及测量过程中误差产生的原因进行必要地分析，找出各种误差因素，为后续工作的顺利完成奠定坚实的基础。     

管道结蜡对计量误差的影响

油品计量交接过程中,温度直接影响K值(温度体积修正系数)和流量计检定的准确性,从而直接影响油品交接的计量误差。本文通过对管道结蜡原因和结蜡过程的分析得出结蜡是引起温度计量误差的主要因素,并提出了有效的预防和处理措施,确保了计量交接准确,减少了交接纠纷,维护了各方的经济利益。     

Fast Two-Output Secure Computation with Optimal Error Probability

Cut-and-choose paradigm makes Yao's protocol for two-party computation secure in malicious model with an error probability.In CRYPTO 2013,based on multi-phase cut-and-choose,Lindell reduced this probability to the optimal value.However,this work can only compute single-output functions with optimal error probability.We transform multi-phase cut-and-choose for singleoutput case into one that can deal with two-output functions,meanwhile maintaining the optimal error probability.Based on this new paradigm,we propose an efficient two-output secure computation protocol.Besides,by utilizing the specific property of the output garbled keys,we solve the authenticity issue of the generator's output with only symmetric cryptographic operations linear in the output length of the generator,which is the most efficient method so far in standard model without Random oracle (Ro).     

Modeling of female human body shapes for apparel design based on cross mean sets

This paper is concerned with a method to build prototypes of human bodies that can be used for apparel design. One of the most important issues in the apparel development process is to define a sizing system to provide a good fitting for the majority of the population. Since anthropometric measures do not present the same linear growth with size in each dimension, it is very important to find a prototype that represents as accurately as possible each class in the sizing system. In this paper we propose a method based on the concept of random compact mean set to define prototypes in apparel design. From a cloud of 3D points obtained with a 3D scanner a solid that represents the human body is obtained. 2D cross sections of this solid are extracted at certain heights corresponding to key points of the body. These different cross-sections can be seen as a realization of a random compact set in the plane. A very popular definition on mean set is applied to each sample of 2D cross sections, and finally the prototype is obtained as the 3D reconstruction of these 2D mean sections. As a real example, the proposed methodology is applied to the 3D database obtained from a anthropometric survey of the Spanish female population conducted in this country in 2006.