阿兰·奈斯论深层生态学的哲学基础

在阿兰·奈斯看来 ,深层生态学既是一种社会思潮 ,又是以这种思潮为指导的一场旨在改变现行实践模式的社会运动。作为一种社会思潮 ,它是一个由一系列基本原理构成的演绎性的逻辑体系。奈斯认为 ,深层生态学的理论内核是八大原理 ,而在其背后 ,还有更为基本的前提与终极规范 ,即各种生态智慧。而奈斯本人的生态智慧的终极规范是 (大 )自我实现     

Testing Equality of Mean Vectors in Two Sample Problem with Missing Data

Finding the influence of traffic accident on the road is helpful to analyze the characteristics of traffic flow, and take reasonable and effective control measures. Here, the detrended fluctuation analysis method is applied to investigate the complexity of time series in mixed traffic flow with a blockage induced by an accident. As a parameter to depict the long-term evolutionary behavior of the time series in traffic flow, the scaling exponent is analyzed. According to the scaling exponent, it is shown that the traffic flow time series can display long-range correlation characteristics, short-range correlation characteristics, and non-power-law relation in the long-range correlation characteristics, which is strongly dependent on the entering probability of vehicle, the ratio of slow vehicle and the blockage duration time.     

On constructing T 2 control charts for retrospective examination

In this paper we consider the issue of constructing retrospective T ² control chart limits so as to control the overall probability of a false alarm at a specified value. We describe an exact method for constructing the control limits for retrospective examination. We then consider Bonferroni-adjustments to Alt's control limit and to the standard x ² control limit as alternatives to the exact limit since it is computationally cumbersome to find the exact limit. We present the results of some simulation experiments that are carried out to compare the performance of these control limits. The results indicate that the Bonferroni-adjusted Alt's control limit performs better that the Bonferroni-adjusted x ² control limit. Furthermore, it appears that the Bonferroni-adjusted Alt's control limit is more than adequate for controlling the overall false alarm probability at a specified value.     

Detection and Interpretation of a Multivariate Signal Using Combined Charts

A control procedure is presented in this article that is based on jointly using two separate control statistics in the detection and interpretation of signals in a multivariate normal process. The procedure detects the following three situations: (i) a mean vector shift without a shift in the covariance matrix; (ii) a shift in process variation (covariance matrix) without a mean vector shift; and (iii) both a simultaneous shift in the mean vector and covariance matrix as the result of a change in the parameters of some key process variables. It is shown that, following the occurrence of a signal on either of the separate control charts, the values from both of the corresponding signaling statistics can be decomposed into interpretable elements. Viewing the two decompositions together helps one to specifically identify the individual components and associated variables that are being affected. These components may include individual means or variances of the process variables as well as the correlations between or among variables. An industrial data set is used to illustrate the procedure.     

High dimensional asymptotics for the naive Hotelling T2 statistic in pattern recognition

Abstract

This paper examines the high dimensional asymptotics of the naive Hotelling T² statistic. Naive Bayes has been utilized in high dimensional pattern recognition as a method to avoid singularities in the estimated covariance matrix. The naive Hotelling T² statistic, which is equivalent to the estimator of the naive canonical correlation, is a statistically important quantity in naive Bayes and its high dimensional behavior has been studied under several conditions. In this paper, asymptotic normality of the naive Hotelling T² statistic under a high dimension low sample size setting is developed using the central limit theorem of a martingale difference sequence.     

Maximum Value of Hotelling's T 2 Statistics Based on the Successive Differences Covariance Matrix Estimator

In statistical process control applications, the multivariate T ² control chart based on Hotelling's T ² statistic is useful for detecting the presence of special causes of variation. In particular, use of the T ² statistic based on the successive differences covariance matrix estimator has been shown to be very effective in detecting the presence of a sustained step or ramp shift in the mean vector. However, the exact distribution of this statistic is unknown. In this article, we derive the maximum value of the T ² statistic based on the successive differences covariance matrix estimator. This distributional property is crucial for calculating an approximate upper control limit of a T ² control chart based on successive differences, as described in Williams et al. (2006 Williams , J. D. , Woodall , W. H. , Birch , J. B. , Sullivan , J. H. ( 2006 ). On the distribution of T ² statistics based on successive differences . J. Qual. Technol. 38 : 217 – 229 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]).     

T.S.艾略特在《四个四重奏》中的本土意识

T.S.艾略特的《四个四重奏》反映出诗人的本土意识,即美国及美国文化的烙印.虽然艾略特并没有像其他美国诗人如惠特曼那样成为真正"美国制造"的本土诗人,《四个四重奏》却不妨被贴上"美国制造"的标签--诗歌中流露出的美国哲学思想的影响,具有美国本土影像的意象清晰可辨.文章着重挖掘诗歌中体现美国文化的哲学内容和诗歌意象,从而证明本土意识在艾略特《四个四重奏》创作中的重要意义.     

Ethnic differences in the academic achievement process in Canada

This research examines the extent to which differences in achievement between German-speaking and French-speaking students are accounted for by theoretically related intervening variables and the extent to which the entire achievement process differs across the two ethnic groups. For the two ethnic groups, both main effects and interaction effects have significant consequences for the academic achievement process, even when a number of other variables are controlled. The results suggest that the whole process works to the benefit of the German-speaking students and to the detriment of the French-speaking students.     

FDI 对安徽省装备制造业发展的影响分析

外商直接投资（FDI）在拓宽国内资金需求渠道的同时,具有较强的技术溢出效应,迎合了装备制造业资本和技术密集的双重特征。当前,安徽省装备制造业处在资本密集型占主导的发展阶段,对 FDI的偏好性较强。研究表明,安徽省装备制造业与FDI间具有较强的相关性,FDI能够有效促进安徽省装备制造业发展,但安徽省装备制造业对FDI的吸引力较弱,且各具体行业对 FDI依赖程度存在较大差异。据此提出相应的建议,一方面,安徽省应注重装备制造业转型升级,提升行业整体竞争力;另一方面,要优化投资环境,增强安徽省装备制造业对FDI的引致能力。