On control charts for monitoring the variance of a time series

In this paper we derive control charts for the variance of a Gaussian process using the likelihood ratio approach, the generalized likelihood ratio approach, the sequential probability ratio method and a generalized sequential probability ratio procedure, the Shiryaev–Roberts procedure and a generalized modified Shiryaev–Roberts approach. Recursive presentations for the calculation of the control statistics are given for autoregressive processes of order 1. In an extensive simulation study these schemes are compared with existing control charts for the variance. In order to asses the performance of the schemes both the average run length and the average delay are used.     

Robust Transformations in Univariate and Multivariate Time Series

It is well known that transformation of the response may improve the homogeneity and the approximate normality of the errors. Unfortunately, the estimated transformation and related test statistic may be sensitive to the presence of one, or several, atypical observations. In addition, it is important to remark that outliers in one transformed scale may not be atypical in another scale. Therefore, it is important to choose a transformation which does not depend on the presence of particular observations. In this article we suggest an efficient procedure based on a robust score test statistic which quantifies the effect of each observation on the choice of the transformation.     

分布式入侵检测系统修复机制

提出了一种基于移动代理的新型分布式入侵检测系统的修复机制。该系统是针对WAN环境设计的,数据的处理通过各节点所设置的代理来进行分布式计算,能实现全网络范围内的入侵检测功能,具有良好的可移植性;对网络系统和主机的资源占用较低,减少出现网络瓶颈的可能。讨论了系统各个层次上的修复和抗毁功能,实验证明,该机制具有较好的性能。     

Biodiversity conservation implications of landscape change in an urbanizing desert of Southwestern Peru

Internal migration from the Peruvian highlands and rural areas has burdened urban areas with rapid growth. Urban expansion is threatening the desert habitat and unique vegetation communities surrounding Arequipa, one of Peru's largest cities. A 511 ha tract contiguous to the city of Arequipa has been informally designated an ecological park. Analysis of Landsat satellite imagery over a 16-year interval indicates that urban expansion is occurring in the direction of the park. The land use/land cover change analysis revealed other landscape patterns and processes, such as agricultural expansion, which are relevant to the study area. These dynamics, plus principles of landscape ecology, suggest that the park's size and shape may not be the most suitable. Conservation alternatives include the expansion of the park, the spatial connection to another nature reserve, or the design of co-management strategies. Given local historical events and the paucity of regional conservation efforts, social actors in Arequipa and in national governmental institutions will need to find practical ways to collaborate.     

基于梯度矢量流snake与多尺度分析的血管内超声图像轮廓提取

提取血管内超声(IVUS)图像的血管内腔轮廓对冠状动脉疾病的诊断有积极意义。本文提出了一种基于梯度矢量流(GVF)snake与多尺度分析的轮廓提取新方法。针对传统GVF snake的轮廓初始化、抑制噪声和伪像干扰两个难点,本文方法在如下两个方面进行了改进:第一,利用序列图像的特性产生时间方差图并得到初始轮廓,从而实现轮廓提取过程的全自动化;第二,引入多尺度分析,使GVF snake在离散小波变换得到的多尺度图中形变,从而增强了算法的鲁棒性。对仿真图像和实际IVUS图像的实验表明,该方法在轮廓提取的精度方面优于传统的GVF snake方法。     

最优故障诊断系统设计

为改善系统的故障诊断性能，在设备设计阶段考虑增加故障诊断子系统是十分必要的．本文从信息论的观点，提出了确定系统中最优状态检测器数目及其安装位置的方法，研究结果为指导故障诊断系统的设计提供了科学依据．     

WAS IT THERE? DEALING WITH IMPERFECT DETECTION FOR SPECIES PRESENCE/ABSENCE DATA†

Species presence/absence surveys are commonly used in monitoring programs, metapopulation studies and habitat modelling, yet they can never be used to confirm that a species is absent from a location. Was the species there but not detected, or was the species genuinely absent? Not accounting for imperfect detection of the species leads to misleading conclusions about the status of the population under study. Here some recent modelling developments are reviewed that explicitly allow for the detection process, enabling unbiased estimation of occupancy, colonization and local extinction probabilities. The methods are illustrated with a simple analysis of presence/absence data collected on larvae and metamorphs of tiger salamander (Ambystoma tigrinum) in 2000 and 2001 from Minnesota farm ponds, which highlights that misleading conclusions can result from naive analyses that do not explicitly account for imperfect detection.     

Empirical null distribution-based modeling of multi-class differential gene expression detection

In this paper, we study the multi-class differential gene expression detection for microarray data. We propose a likelihood-based approach to estimating an empirical null distribution to incorporate gene interactions and provide a more accurate false-positive control than the commonly used permutation or theoretical null distribution-based approach. We propose to rank important genes by p-values or local false discovery rate based on the estimated empirical null distribution. Through simulations and application to lung transplant microarray data, we illustrate the competitive performance of the proposed method.     

Change Point Detection in The Skew-Normal Model Parameters

Bayesian inference under the skew-normal family of distributions is discussed using an arbitrary proper prior for the skewness parameter. In particular, we review some results when a skew-normal prior distribution is considered. Considering this particular prior, we provide a stochastic representation of the posterior of the skewness parameter. Moreover, we obtain analytical expressions for the posterior mean and variance of the skewness parameter. The ultimate goal is to consider these results to one change point identification in the parameters of the location-scale skew-normal model. Some Latin American emerging market datasets are used to illustrate the methodology developed in this work.     

基于粗糙集理论的入侵检测方法研究

为了克服入侵检测系统存在着在先验知识较少情况的推广能力差的问题,提出了基于粗糙集理论的入侵检测方法。利用粗糙理论,建立了系统调用短序列的检测模型并应用于sendmail调用序列检测。实验结果表明:它不需要全部的正常和异常的信息,在给出较少的正常和异常调用序列数据的情况下,能得到较为理想的检测效果。