虚拟社会与道德构建

随着网络的普及 ,虚拟社会中人们的思想、行为、生存方式都发生了新的变化。虚拟社会具有虚拟性、自由性、开放性、非人性化的特点 ;虚拟社会的自由和民主精神、权利意识和平等意识、自主精神、奉献精神、开放思想为道德建设提供了新的生长点 ,但同时带来了一系列负效应。因此 ,道德建设要采取一系列相应的措施 ,以构造文明虚拟社会     

高性能可重构DSP处理器的数据通路设计

介绍了高性能定点可重构DSP处理器的数据通路设计。该数据通路以功能强大的16位定点计算单元为基础,搭建起高速16位数据处理平台;并能以单指令流多数据流的方式灵活支持多维向量运算;通过重构的方法有效地支持了32位数据处理。     

阅读与语篇理解的相关理论分析

阅读是外语教学和学习中的重要环节。阅读不仅是读者知识积累和经验积淀的反映,而且可以构架起作者和读者之间沟通的桥梁。掌握了语篇生成的理论基础和技巧,读者就能在阅读中驾轻就熟地理解作者的意图和观点,从而达到理解语篇的目的。     

小波分析在管理数据处理中的应用

提出了一种基于小波变换的管理数据处理方法，把公司管理上的数据看成一个非平稳的时间序列，利用小渡函数将该时间序列分解到不同的频率通道上，然后将分解后的信号当作近似的平稳时间序列，用一些传统的统计方法进行预测，同时对中国足球彩票若干期的销售量数据进行了处理和预测，并将结果与实际销量以及用传统的AR模型的预测值进行了比较。     

档案信息利用服务网络化现状的思考

在社会信息化的趋势下,档案信息化已被高度关注。档案信息利用服务网络化是新形势下档案利用的一种新方式。由于诸多因素的制约,使得基于Internet平台的B S模式的网络利用服务明显滞后。本文从档案信息利用服务网络化的现状、产生的原因及对策三个方面做出分析。     

论现行大学生体质检测方法的科学性

本文通过回顾我国大学生体质检测标准的发展历程,对新颁布的大学生体质监测方法和标准的科学性进行技术分析,在此基础上,对新的体质检测方法的进一步深层次的应用进行探索。     

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.     

王夫之对义、利的层次性及相对性的分析

义利观问题是中国伦理思想史的核心问题之一，历代思想家都十分重视对它的研究。王夫之在总结、继承前哲义利思想的基础上，提出了自己的义利观，并对义利进行了层次性及相对性的分析，既继承了传统道义论的精华，又极大地丰富了中国古代伦理思想的内涵。     

Olive Oil Consumption in Greece: A Microeconometric Analysis

In this paper, the factors affecting at-home demand for three types of oils and fats in Greece, with emphasis on olive oil, are investigated using the linear approximation of the Almost Ideal Demand System and family budget survey data. To overcome the econometric problem created with the existence of zero expenditure, a generalization of the two-stage Heckman procedure is employed. In order to investigate the role of self-consumption, two different samples were used. The first includes all households; the second excludes those that acquire olive oil only from own production. According to the results, there are important differences in the first stage of the decision process between the two samples. Unlike the first stage, the second stage of the decision process found no important differences between the results for the two samples.     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.