Likelihood testing populations modeled by autoregressive process subject to the limit of detection in applications to longitudinal biomedical data

Dependent and often incomplete outcomes are commonly found in longitudinal biomedical studies. We develop a likelihood function, which implements the autoregressive process of outcomes, incorporating the limit of detection problem and the probability of drop-out. The proposed approach incorporates the characteristics of the longitudinal data in biomedical research allowing us to carry out powerful tests to detect a difference between study populations in terms of the growth rate and drop-out rate. The formal notation of the likelihood function is developed, making it possible to adapt the proposed method easily for various different scenarios in terms of the number of groups to compare and a variety of growth trend patterns. Useful inferential properties for the proposed method are established, which take advantage of many well-developed theorems regarding the likelihood approach. A broad Monte-Carlo study confirms both the asymptotic results and illustrates good power properties of the proposed method. We apply the proposed method to three data sets obtained from mouse tumor experiments.     

Asymptotic variances of maximum likelihood estimator for the correlation coefficient from a BVN distribution with one variable subject to censoring

This paper deals with the problem of estimating the Pearson correlation coefficient when one variable is subject to left or right censoring. In parallel to the classical results on the Pearson correlation coefficient, we derive a workable formula, through tedious computation and intensive simplification, of the asymptotic variances of the maximum likelihood estimators in two cases: (1) known means and variances and (2) unknown means and variances. We illustrate the usefulness of the asymptotic results in experimental designs.     

沙发检测装置应力及疲劳性能研究

为提高折叠沙发检测装置可靠性，满足技术机构开展检测工作的需求，提出采用有限元分析的方法，对装置的腿 部、座部和背部受力单元进行应力和疲劳性能研究。根据应力云图优化装置结构，利用疲劳分析模块Fatigue Tool模拟 装置耐久性能。模拟结果验证了装置耐久性设计的合理性。     

GDSS的基本决策网络模型

为构建 GDSS决策网络引入一个分析模型——决策网络图来研究任务环境和组织设计之间的交互作用 ,提出 GDSS的基本决策网络结构为级联式和二层多分支树型结构 ,借助概率影响图对该决策网络的优化问题进行了形式描述 ,并给出协同工作方式的分类和任务环境的分析步骤 .     

一种非正交多址接入下行链路信号检测方法

非正交多址接入（non-orthogonal multiple access，NOMA）下行链路存在严重的多址干扰。软解调-串行干扰消除（successive interference cancellation，SIC）检测方法是一种性能较好的信号检测方法，但是接收机的复杂度比较高。考虑到软解调算法对其他用户信号的信号特征信息并未充分利用，提出一种基于软解调算法改进的联合检测算法，该算法直接利用多用户叠加信号的联合星座图计算用户信号信息比特的软信息，不需要对干扰信号进行检测和重构，可以降低接收机的复杂度。仿真分析表明，与软解调-SIC检测方法相比，联合检测方法在性能损失不超过1．5 dB的情况下，可以将接收机的复杂度降低一半。     

LED显示屏专用插件机的优化设计

为了提高LED显示屏的插装生产效率，提出了优化设计LED显示屏插件机的方案，采用锥形孔来校正LED管 脚，利用LED外形定位的方法来进行精准插件，省略LED管脚的裁剪环节和传输环节，使结构变得简洁，有效地节省产 品成本，通过对关键部件进行仿真分析，表明初步实现了目标。     

小波变换在液氮制冷式露点自动检测中的应用

采用小波变换的Ｍａｌｌａｔ算法，求取智能露点仪温度曲线的拐点，这种算法的显著特点是可于背景噪音中很好地提取用用信号，在３－５次测量中，即可得到重复性极好的曲线拐点值，与传统的最小二乘拟合建模方法相比，不但可以减少测量次数，而且使露点温度值的自动检测达到了更高的准确性和稳定性。