一种固定帧长的EPON MAC算法

提出了一种固定大小帧结构的EPON MAC协议,采用固定的帧长,提高了以太网交换机速率。将一帧周期分成三段,光网络单元不仅报告队列长度信息,而且报告帧到达分布信息,降低了高优先级业务时延抖动,授权采取高优先级优先授权的原则,降低了高优先级业务的接入时延,满足了对时延和时延抖动敏感语音业务的要求。     

含多滞量的中立型差分方程的有界正解

考虑一类含有多个滞量的中立型差分方程，获得了该方程存在有界正解的一个充分必要条件。     

人格特质对立即提取和延缓提取的影响

采用知觉-再认和学习-回忆测试,考察了内外倾和神经质的联合效应对立即提取和延缓提取的影响。研究表明:(1)高、低唤醒被试(NIs、SEs)立即提取的效果均优于延缓提取;(2)NIs对负性词的再认错误率最低,衰减最快,对正性词的再认错误出现在30分钟以后,SEs的提取模式与此相反;(3)NIs对同音配对词、SEs对同义配对词的回忆优势不随间隔时间的延长而减弱;(4)对于同形、同音和同义配对词,被试的遗忘发生在记忆保持间隔的前30分钟。     

变时滞Lurie间接控制系统的绝对稳定性

利用Lyapunov定理讨论了具有多个时变时滞的Lurie间接控制系统的绝对稳定性 给出了系统绝对稳定的时滞相关充分准则,并用示例说明此方法的可行性和有效性.     

一类具连续分布滞量的中立型双曲方程的振动性

获得了一类具连续分布滞量的非线性中立型双曲方程所有解振动的若干充分条件.     

A review and discussion of prospective statistical surveillance in public health

Summary. A review of methods suggested in the literature for sequential detection of changes in public health surveillance data is presented. Many researchers have noted the need for prospective methods. In recent years there has been an increased interest in both the statistical and the epidemiological literature concerning this type of problem. However, most of the vast literature in public health monitoring deals with retrospective methods, especially spatial methods. Evaluations with respect to the statistical properties of interest for prospective surveillance are rare. The special aspects of prospective statistical surveillance and different ways of evaluating such methods are described. Attention is given to methods that include only the time domain as well as methods for detection where observations have a spatial structure. In the case of surveillance of a change in a Poisson process the likelihood ratio method and the Shiryaev–Roberts method are derived.     

家庭收入与新发涂阳肺结核诊治延迟的关系

目的:了解家庭收入与新发涂阳肺结核患者就诊延迟、确诊延迟和治疗延迟的关系。方法:采用分层随机抽样方法,抽取镇江市3个县(区)192例新发涂阳肺结核患者为调查对象,采用自制调查问卷进行调查。结果:就诊延迟、确诊延迟和治疗延迟的均数为15.92、13.97和1.27天。家庭人均收入均值为14 983.26元。不同家庭收入水平的患者,发生2周以上就诊延迟比例的差异没有统计学意义(P=0.128);但患者选择的医疗机构级别不同,不同级别医疗机构间2周以上确诊延迟比例的差异有统计学意义(P<0.001)。结论:收入水平已不是影响镇江市新发涂阳肺结核患者就诊延迟的主要因素,但是家庭经济水平仍然通过首诊机构影响着患者的确诊延迟。     

Reducing Hospital Readmissions by Integrating Empirical Prediction with Resource Optimization

Hospital readmissions present an increasingly important challenge for health‐care organizations. Readmissions are expensive and often unnecessary, putting patients at risk and costing $15 billion annually in the United States alone. Currently, 17% of Medicare patients are readmitted to a hospital within 30 days of initial discharge with readmissions typically being more expensive than the original visit to the hospital. Recent legislation penalizes organizations with a high readmission rate. The medical literature conjectures that many readmissions can be avoided or mitigated by post‐discharge monitoring. To develop a good monitoring plan it is critical to anticipate the timing of a potential readmission and to effectively monitor the patient for readmission causing conditions based on that knowledge. This research develops new methods to empirically generate an individualized estimate of the time to readmission density function and then uses this density to optimize a post‐discharge monitoring schedule and staffing plan to support monitoring needs. Our approach integrates classical prediction models with machine learning and transfer learning to develop an empirical density that is personalized to each patient. We then transform an intractable monitoring plan optimization with stochastic discharges and health state evolution based on delay‐time models into a weakly coupled network flow model with tractable subproblems after applying a new pruning method that leverages the problem structure. Using this multi‐methodologic approach on two large inpatient datasets, we show that optimal readmission prediction and monitoring plans can identify and mitigate 40–70% of readmissions before they generate an emergency readmission.     

Risk,Process Maturity,and Project Performance: An Empirical Analysis of US Federal Government Technology Projects

In recent years, there has been increasing pressure on the US federal government to reduce spending and improve the management of its technology projects. Mitigating the adverse impact of risks on the performance of these projects presents a significant challenge for its stakeholders. Our research examines this challenge in two steps. First, we identify and define a set of salient risks in federal technology projects—specifically, complexity risk and contracting risk in the planning process, and execution risk in the execution process. Next, we investigate whether higher levels of process maturity, assessed by the Capability Maturity Model Integration (CMMI) framework, mitigate the negative effect of project risks on project performance. The analysis of time‐series data collected from 82 federal technology projects across 519 quarterly time periods indicates that each of the three types of risks has a significant negative effect on project performance. This finding highlights the practical significance of managing these risks in the federal technology project context. Further, we find that increasing levels of process maturity attenuate the negative effect of project risks on the performance of federal technology projects. However, the attenuation effects are consequential only at high levels of project risks; at low levels of project risk, increasing levels of process maturity can adversely affect project performance. To demonstrate the financial implications of increasing process maturity levels in federal technology projects, we examine the magnitude of project cost savings (and overruns) across different levels of CMMI and project risks. In summary, our study contributes to the sparse literature on public sector operations by addressing the understudied context of federal technology projects, and provides a nuanced examination of the implications of process maturity in managing the risk to performance relationship in such projects.     

韩国大学结构调整现状的审视与反思

随着韩国低生育率和高龄化社会的到来,高等教育学龄人口不断减少,为此,韩国教育科学技术部从2011年开始着手实施大学结构调整,成立专门负责停办私立大学和撤并国公立大学工作的"大学结构改革委员会",正式推进大学结构调整工作。结构调整评价的关键指标包括在校生率、就业率、专任教师比率、新生入学率和学生管理等,对处于下游15%的大学采取各种行政和财政手段,督促其制定"自我结构改革计划",自觉推进类似学科专业、大学合并等结构改革。此次结构调整影响较大,为此,政府和大学还应努力做好以下几方面的工作:一是重视从量的追求到质的提高,二是制定大学整顿及结构调整法案,三是加强特色大学建设,四是积极开拓有效的替代性财源。