论破窗理论对高校班级管理的启示

班级管理在大学教育中的作用十分重要。从破窗理论出发．明确了班级环境在班级建设与发展中的重要地位，论述了班级中潜抑力量与压抑力量转化的意义，在此基础上进一步提出，要从加强日常管理、形成良性反馈机制、处理好突发事件三个方面预防“破窗现象”，并针对破窗理论的运用提出了建议。     

采用二阶特征窗的语音盲分离方法

利用语音信号的短时平稳特性,提出了一种二阶特征窗语音盲分离方法。该方法采用新的联合差分相关矩阵白化算法去除有色噪声影响;用长度等于语音信号基音周期的等距特征窗连续分割预白化观测数据,在每个加窗的数据帧计算不同的时滞协方差矩阵。利用联合近似对角化时滞协方差矩阵集合得到旋转参数,最终达到语音信号的盲分离。该方法消除了有色噪声的影响,只需用到二阶信息就能很好地分离语音信号。仿真实验验证了该方法的有效性。     

谈音长在教学和修辞中的作用

语言是声音和意义的结合体。语音是语言的物质外壳。语音的音长决定着言语的速度 ,在交际中 ,对内容的表达起积极作用 ,在教学和修辞的语言实践中 ,应重视音长的作用。     

Bayesian analysis of elapsed times in continuous‐time Markov chains

The authors consider Bayesian analysis for continuous‐time Markov chain models based on a conditional reference prior. For such models, inference of the elapsed time between chain observations depends heavily on the rate of decay of the prior as the elapsed time increases. Moreover, improper priors on the elapsed time may lead to improper posterior distributions. In addition, an infinitesimal rate matrix also characterizes this class of models. Experts often have good prior knowledge about the parameters of this matrix. The authors show that the use of a proper prior for the rate matrix parameters together with the conditional reference prior for the elapsed time yields a proper posterior distribution. The authors also demonstrate that, when compared to analyses based on priors previously proposed in the literature, a Bayesian analysis on the elapsed time based on the conditional reference prior possesses better frequentist properties. The type of prior thus represents a better default prior choice for estimation software.     

师专热学教学改革的几点体会

介绍了在热学教学改革中引入“热学中的创造性思维”．为前沿课题“开窗口”．为后续课程“留接口”的思考与实践。     

Estimation of critical points in the mixture inverse Gaussian model

The maximum likelihood estimation for the critical points of the failure rate and the mean residual life function are presented in the case of mixture inverse Gaussian model. Several important data sets are analyzed from this point of view. For each of the data sets, Bootstrapping is used to construct confidence intervals of the critical points.     

Why do participants in voluntary organizations leave? Exploring the relationship between value congruence and length of stay

Recognizing the importance of values and the specific characteristics of participants and situations in voluntary organizations, we examine how value congruence—the fit or compatibility of values between participants and the organization, or among participants—interacts with personal and situational factors to predict participants' length of stay in their organizations. Introducing the case of a voluntary organization that offers shared housing, we measure value congruence through textual similarity in the self‐introduction documents of 49 participants and the organization's mission statement. This approach differs from the self‐reported measures based on participants' perceptions or recalled interactions used in previous studies. In line with expectation‐disconfirmation theory, participants with the strongest beliefs in organizational values had shorter lengths of stay. The amount of intraorganizational communication also moderated the relationship between value congruence and length of stay. This study provides theoretical and methodological implications for nonprofit management by considering personal and situational factors and evaluating value congruence by textual similarity.     

A bootstrap control chart for inverse Gaussian percentiles

The conventional Shewhart-type control chart is developed essentially on the central limit theorem. Thus, the Shewhart-type control chart performs particularly well when the observed process data come from a near-normal distribution. On the other hand, when the underlying distribution is unknown or non-normal, the sampling distribution of a parameter estimator may not be available theoretically. In this case, the Shewhart-type charts are not available. Thus, in this paper, we propose a parametric bootstrap control chart for monitoring percentiles when process measurements have an inverse Gaussian distribution. Through extensive Monte Carlo simulations, we investigate the behaviour and performance of the proposed bootstrap percentile charts. The average run lengths of the proposed percentage charts are investigated.     

An EWMA chart for monitoring process mean

In the statistical process control literature, there exists several improved quality control charts based on cost-effective sampling schemes, including the ranked set sampling (RSS) and median RSS (MRSS). A generalized cost-effective RSS scheme has been recently introduced for efficiently estimating the population mean, namely varied L RSS (VLRSS). In this article, we propose a new exponentially weighted moving average (EWMA) control chart for monitoring the process mean using VLRSS, named the EWMA-VLRSS chart, under both perfect and imperfect rankings. The EWMA-VLRSS chart encompasses the existing EWMA charts based on RSS and MRSS (named the EWMA-RSS and EWMA-MRSS charts). We use extensive Monte Carlo simulations to compute the run length characteristics of the EWMA-VLRSS chart. The proposed chart is then compared with the existing EWMA charts. It is found that, with either perfect or imperfect rankings, the EWMA-VLRSS chart is more sensitive than the EWMA-RSS and EWMA-MRSS charts in detecting small to large shifts in the process mean. A real dataset is also used to explain the working of the EWMA-VLRSS chart.