Half-life estimation based on the bias-corrected bootstrap: A highest density region approach

The half-life is defined as the number of periods required for the impulse response to a unit shock to a time series to dissipate by half. It is widely used as a measure of persistence, especially in international economics to quantify the degree of mean-reversion of the deviation from an international parity condition. Several studies have proposed bias-corrected point and interval estimation methods. However, they have found that the confidence intervals are rather uninformative with their upper bound being either extremely large or infinite. This is largely due to the distribution of the half-life estimator being heavily skewed and multi-modal. A bias-corrected bootstrap procedure for the estimation of half-life is proposed, adopting the highest density region (HDR) approach to point and interval estimation. The Monte Carlo simulation results reveal that the bias-corrected bootstrap HDR method provides an accurate point estimator, as well as tight confidence intervals with superior coverage properties to those of its alternatives. As an application, the proposed method is employed for half-life estimation of the real exchange rates of 17 industrialized countries. The results indicate much faster rates of mean-reversion than those reported in previous studies.     

Simultaneous confidence intervals for ratios of means of several lognormal distributions: A parametric bootstrap approach

For constructing simultaneous confidence intervals for the ratios of means of several lognormal distributions, we propose a new parametric bootstrap method, which is different from an inaccurate parametric bootstrap method previously considered in the literature. Our proposed method is conceptually simpler than other proposed methods, which are based on the concepts of generalized pivotal quantities and fiducial generalized pivotal quantities. Also, our extensive simulation results indicate that our proposed method consistently performs better than other methods: its coverage probability is close to the nominal confidence level and the resulting intervals are typically shorter than the intervals produced by other methods.     

采用双向斜拉式弯曲划分的曲线渐进化简方法

目的 曲线化简是制图综合中的经典研究问题和重要研究内容,以往曲线化简以顶点压缩为主,而制图综合中曲线化简是渐进删除小弯曲,保留特征弯曲的过程,因此提出一种以弯曲为化简单元的曲线化简方法。方法 通过弯曲划分、弯曲渐进取舍实现线要素化简：分析斜拉式弯曲划分方法优点与不足的基础上,提出一种双向斜拉式弯曲划分方法,使弯曲划分结果更加准确、完整;在双向斜拉式弯曲划分的基础上,探测弯曲间关系,将具有不同关系的弯曲定义为3类弯曲,并在此基础上划分两类弯曲组;对不同类型的弯曲组采用不同的弯曲取舍方法及取舍顺序,渐进删除弯曲,避免化简过度;重复弯曲划分、弯曲关系探测、弯曲取舍等过程,直至化简结果中不存在目标尺度下不可见的细小弯曲为止,实现曲线渐进化简,充分化简曲线以满足目标尺度下视觉要求。结果 以某地区1：25万的水系数据为实验对象,实验1分别利用双向斜拉式弯曲划分方法和斜拉式弯曲划分方法对其中16条线状河流要素划分弯曲单元,双向斜拉式弯曲划分方法划分的弯曲单元形态上更符合认知规律,且划分结果较斜拉式弯曲划分结果更加完整,避免了弯曲遗漏;实验2分别利用D-P算法、基于三元组的曲线化简方法、本文方法将16条线状河流要素由1：25万分别化简至1：50万、1：100万、1：200万,本文方法的各尺度化简结果较另两种方法在认知层次、几何层次、地理层次上都具有一定优越性;实验3增加实验数据量,对956条不同形态曲线构成的水系依实验2进行对比化简实验。计算每条曲线利用不同方法化简至各尺度后产生的位置误差,并统计不同结果中所有曲线位置误差的平均数、加权平均数、中位数等统计值量化评估化简结果,本文方法各尺度化简结果中位置误差的统计值均小于另两方法同尺度化简结果中位置误差的统计值。结论 双向斜拉式弯曲划分方法划分曲线弯曲更加完整、准确、符合认知,采用双向斜拉式弯曲划分的曲线化简方法符合人工化简过程和认知规律,在形态保持、地理特征保持等方面都有一定优势,适于多种形态曲线化简,用于形态相对曲折、复杂的线要素化简时优势明显,适用于制图综合实际应用。     

Finding the best conic approximation to the convolution curve of two compatible conics based on Hausdorff distance

We consider the convolution of two compatible conic segments. First, we find an exact parametric expression for the convolution curve, which is not rational in general, and then we find the conic approximation to the convolution curve with the minimum error. The error is expressed as a Hausdorff distance which measures the square of the maximal collinear normal distance between the approximation and the exact convolution curve. For this purpose, we identify the necessary and sufficient conditions for the conic approximation to have the minimum Haudorff distance from the convolution curve. Then we use an iterative process to generate a sequence of weights for the rational quadratic Bézier curves which we use to represent conic approximations. This sequence converges to the weight of the rational quadratic Bézier curve with the minimum Hausdorff distance, within a given tolerance. We verify our method with several examples.     

A multi-expert approach for developing testing and diagnostic systems based on the concept-effect model

With the popularization of computer and communication technologies, researchers have attempted to develop computer-assisted testing and diagnostic systems to help students improve their learning performance on the Internet. In developing a diagnostic system for detecting students’ learning problems, it is difficult for individual teachers to address the exact relationships between the test items and the concepts. To cope with this problem, this study proposes an innovative approach to eliciting and integrating the weightings of test item-concept relationships from multiple experts. Based on the proposed approach, a testing and diagnostic system has been implemented; moreover, an experiment was conducted to evaluate the performance of our approach. By analyzing the results from four groups of students using learning suggestions provided by different models, it was found that the learning performance of the students who received learning suggestions by applying the innovative approach was significantly better than for those who received guidance based on the original model.     

Biomedical system based on the Discrete Hidden Markov Model using the Rocchio-Genetic approach for the classification of internal carotid artery Doppler signals

When the maximum likelihood approach (ML) is used during the calculation of the Discrete Hidden Markov Model (DHMM) parameters, DHMM parameters of the each class are only calculated using the training samples (positive training samples) of the same class. The training samples (negative training samples) not belonging to that class are not used in the calculation of DHMM model parameters. With the aim of supplying that deficiency, by involving the training samples of all classes in calculating processes, a Rocchio algorithm based approach is suggested. During the calculation period, in order to determine the most appropriate values of parameters for adjusting the relative effect of the positive and negative training samples, a Genetic algorithm is used as an optimization technique. The purposed method is used to classify the internal carotid artery Doppler signals recorded from 136 patients as well as of 55 healthy people. Our proposed method reached 97.38% classification accuracy with fivefold cross-validation (CV) technique. The classification results showed that the proposed method was effective for the classification of internal carotid artery Doppler signals.     

基于色彩均匀度的自然图像色彩-纹理分割方法

针对现有图像分割方法中存在的计算复杂,分割结果平滑性不好等问题,提出了基于色彩均匀度的自然图像色彩—纹理分割方法ISBEC。该方法首先对输入图像进行色彩量化,然后利用量化得到的索引图同时进行色彩分割和基于色彩均匀度的多尺度纹理分析,接着将纹理和色彩分割的结果加以结合,最后合并去掉过分割区域。将灰度图像转为色彩分量相同的彩色图像后,ISBEC算法同样可以用于灰度图像的分割。实验结果验证了ISBEC对自然图像色彩—纹理分割的有效性。     

基于一种改进的多端元混合像元分解方法的三江源中东部地区植被盖度信息的提取

三江源地处青海省南部,近年来生态环境不断恶化、草地退化严重。植被盖度是研究草地退化的重要指标之一,如何快速、准确、大面积地获取植被信息对三江源的生态环境变化监测尤为重要。传统的固定端元混合像元分解(TSMA)不适用于地域辽阔、地物类型复杂多样的三江源区,而多端元混合像元分解(MESMA)允许端元的类型和数量随像元的不同而变化,更符合三江源的实际情况。基于已有相关研究提出一种改进的多端元混合像元分解(IMESMA),即加入端元组分合理性最优端元模型判断规则,分两步对影像进行分解并获得像元的植被盖度信息。第一步利用多端元模型探测出含有植被信息和完全不含植被信息的像元,并对非植被像元进行掩膜,以提高分解精度;第二步仅对含有植被信息的像元进行分解,获得最终的三江源中东部植被盖度信息。通过多端元分布图、混淆矩阵和与实测数据的均方根误差(RMSE)对比表明,相比TSMA,IMESMA考虑了同物异谱现象,并且其分解精度高、分解结果可信,更适合三江源区的植被信息提取。本方法也可用于其他复杂环境地表组分信息的提取。     

A novel approach to determine cell formation,intracellular machine layout and cell layout in the CMS problem based on TOPSIS method

This paper deals with the cellular manufacturing system (CMS) that is based on group technology (GT) concepts. CMS is defined as identifying the similar parts that are processed on the same machines and then grouping them as a cell. The most proposed models for solving CMS problems are focused on cell formation and intracellular machine layout problem while cell layout is considered in few papers. In this paper we apply the multiple attribute decision making (MADM) concept and propose a two-stage method that leads to determine cell formation, intracellular machine layout and cell layout as three basic steps in the design of CMS. In this method, an initial solution is obtained from technique for order preference by similarity to the ideal solution (TOPSIS) and then this solution is improved. The results of the proposed method are compared with well-known approaches that are introduced in literature. These comparisons show that the proposed method offers good solutions for the CMS problem. The computational results are also reported.