Using concept mapping as a planning tool: Child welfare citizen review panels

Citizen Review Panels (CRPs) are groups of citizen volunteers authorized by U.S. federal law to examine state child welfare agencies. These groups inspect policies and practices related to child protection responsibilities and are tasked with making recommendations for systemic improvement. Despite the federal mandate for each state to develop a CRP and the potential of these groups to positively impact child welfare practices, there is a dearth in the literature related to CRPs. Consequently, planning and evaluation processes of these groups vary widely. This study reports on the use of concept mapping (CM) to outline a framework for planning and subsequently evaluating the CRP in one southeastern state. CM is a mixed-method research approach that uses multi-dimensional scaling and hierarchical cluster analyses to explore an area of study. Through these analyses, the method creates visual depictions of conceptual relationships between ideas. Data yielded a seven cluster concept map that CRP members (N = 36) utilized for planning processes, and subsequently for developing an internal evaluation tool. Results from this study offer a unifying framework by which CRPs, and similar groups in other areas can utilize for planning and evaluation purposes. After a review of pertinent literature on CRPs, this article explicates CM processes utilized in this study, describes results, discusses lessons learned, and outlines apposite areas for future CRP research.     

德语空间性状形容词的时间映射特质研究

基于认知隐喻理论，选择德语中14个表征空间性状的形容词，探究其时间映射特质。研究发现:长/短、大/小、远/近、高、深可表征时间，其余则无法表征时间。具体特质如下:存在“一维＞二维＞三维”映射维度等级；存在“长短＞远近＞高深/大小”映射宽幅等级；正向形容词比负向更易表征时间。这种映射特质主要与时空相似性、认知思维及隐喻操作有关。     

具有带误差逼近的赋值伪压缩映像的公共不动点迭代序列

在实一致光滑Banach空间中引入了一类新的逼近三个极值强伪压缩映象唯一公共不动点的带误差迭代序列,以及通过Petryshyn不等式讨论了该带误差迭代序列的收敛性.     

如何行成关系数据模型到面向对象数据模型的映射

关系数据模型是基于记录的基本数据模型;面向对象数据模型是基于对象的基本数据模型;两种数据模型在某种程度上应存在相互映射和相互转变的可能性,它们的相互映射和相互转变将使关系数据库和面向对象数据库之间的转变成为可能。     

浅谈网络管理与商业性地质工作

商业性地质工作是相对公益性地质工作提出来的。在公益性地质工作得到初步加强的同时,如何利用网络管理促进商业性地质工作加快发展,是当前政府部门和地勘单位值得关注的一个重要问题。互联网加速了信息的沟通与交流,为中小矿业企业提供了公正、平等的参与竞争的机会。商业性地质工作的网络管理任务是:制定网络战略,实现更大范围内的资源优化配置;培养知识主管;疏通交流渠道;创造智力群体;发布详实信息。实现以上任务,需要有效的网络管理予以支持。     

LiNbO_3电光调制器行波电极优化设计

分析了厚电极厚缓冲层的共面波导Mach-Zehnder行波电极LiNbO3光调制器,讨论了电极厚度和缓冲层厚度对调制器特性参数的影响,得到了调制器的有效折射率、特征阻抗、半波电压及损耗系数等参数。通过对比分析,选择合适的电极厚度和缓冲层厚度,优化调制器性能,近似满足速度和阻抗匹配,实现了图宽带调制。     

On Block Updating in Markov Random Field Models for Disease Mapping

Gaussian Markov random field (GMRF) models are commonly used to model spatial correlation in disease mapping applications. For Bayesian inference by MCMC, so far mainly single-site updating algorithms have been considered. However, convergence and mixing properties of such algorithms can be extremely poor due to strong dependencies of parameters in the posterior distribution. In this paper, we propose various block sampling algorithms in order to improve the MCMC performance. The methodology is rather general, allows for non-standard full conditionals, and can be applied in a modular fashion in a large number of different scenarios. For illustration we consider three different applications: two formulations for spatial modelling of a single disease (with and without additional unstructured parameters respectively), and one formulation for the joint analysis of two diseases. The results indicate that the largest benefits are obtained if parameters and the corresponding hyperparameter are updated jointly in one large block. Implementation of such block algorithms is relatively easy using methods for fast sampling of Gaussian Markov random fields ( Rue, 2001 ). By comparison, Monte Carlo estimates based on single-site updating can be rather misleading, even for very long runs. Our results may have wider relevance for efficient MCMC simulation in hierarchical models with Markov random field components.     

Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

拓扑型KKM定理和Riesz空间中的极大极小定理

证明了广义区间空间中几个新的参数型KKM定理,由此得到了Riesz空间中几个新型极大极小定理。