理论创新：推进党的建设的强大引擎

中国共产党善于破解不同时代的基本理论问题,从而推进党的理论创新。作为马克思主义中国化和党的理论创新的产物,毛泽东思想为党的新民主主义革命提供了实践指南,中国特色社会主义理论体系不仅解决党如何建设社会主义以及怎样建设党的问题,更致力解决在新世纪的机遇与挑战面前党如何发展中国特色社会主义的理论问题。这些理论创新成果具有鲜活的时代特征,成为推进党的建设的强大引擎。     

CAXA在化工设备设计中的应用

随着化工设备设计过程中对零部件标准化、系列化程度的要求不断提高,应用计算机辅助技术进行优化设计和快速绘制化工设备图成为必然的发展趋势.应用国产计算机辅助技术软件-CAXA电子图板可实现化工设备零部件标准化、系列化设计,快速进行化工设备优化设计,降低设计人员劳动强度,提高化工设备制图速度.     

一体化医学语言系统在医学科技信息检索中的应用

一体化医学语言系统 (UMLS)是美国国立医学图书馆 (NLM)主持开发的计算机化的生物医学检索语言集成系统。现已广泛应用于医学科技文献检索、医学搜索引擎和医疗决策支持系统等方面     

试析互联网中的“人肉搜索”现象

近年来,在互联网领域出现的"人肉搜索"现象,已经受到人们越来越多的关注.一方面,"人肉搜索"具有一定的社会舆论监督意义;另一方面,其通常是一个群体针对某个人进行所谓的道德审判,往往会涉及侵害个人的隐私权以及侵犯公民的其他正当权益.因此,在保护公民合法权益的同时,发挥"人肉搜索"的正面作用,并对其加以理性约束,具有重要的理论和现实意义.     

小型汽油机恒转速QFT鲁棒控制

给出了某小型无人直升机汽油发动机的恒转速鲁棒控制。根据阶跃响应,可辨识得到用于控制器设计的发动机线性区间模型。针对该模型具有不确定性以及进气-做功之间存在时变时滞等特点,采用基于定量反馈理论(QFT)的鲁棒控制方法实现发动机的恒转速控制,使其在严重的负载扰动条件下能准确地跟踪期望的发动机转速。仿真结果表明,该控制器动态响应速度快、对旋翼总距变化等干扰抑制作用强,能使发动机转速稳定在目标转速允许误差范围内,并具有一定的鲁棒性。     

发动机分析仪的组成及其计算机测控系统的研究

本文以华燕HFZF2000型发动机分析仪为例,介绍发动机分析仪的组成和计算机系统测试(CAN)的特点,利用华燕HFZF2000型发动机分析仪对发动机点火波形特征及其故障诊断,分析影响发动机的单缸转速降和点火性能等参数.     

基于振动信号的柴油机HUMS研究

本文主要是研究柴油机的健康及运行监测系统(HUMS),并以连杆铜套磨损为例进行分析。利用基于神经网络和小波分析的故障诊断方法进行健康状况的定量识别。实验和仿真结果表明:对于各设定工况,诊断模型可以定量的识别出来,准确率达到100%;对于待定工况,诊断模型也可以给出定量的健康状况描述。从而使操作者能及时地了解柴油机的健康状况,并根据定量的输出结果对相应部件进行维护。     

我国传统美术图形语境下的品牌视觉设计研究

经济全球化为外来品牌的大量进入中国提供了契机，但以我国传统美术图形作为品牌视觉设计的形式在发展过程中逐渐失去了特色。随着品牌视觉设计需求的日新月异以及在图形设计语言探究方面的力度加强，以具有我国特色的美术图形为依据的视觉设计越来越受到人们的关注，因此，有必要对我国传统美术图形语境下的品牌视觉设计进行研究。     

Tornado Warning Perception and Response: Integrating the Roles of Visual Design,Demographics, and Hazard Experience

Recent advancements in severe weather detection and warning dissemination technologies have reduced, but not eliminated, large‐casualty tornado hazards in the United States. Research on warning cognition and behavioral response by the public has the potential to further reduce tornado‐related deaths and injuries; however, less research has been conducted in this area compared to tornado research in the physical sciences. Extant research in this vein tends to bifurcate. One branch of studies derives from classic risk perception, which investigates cognitive, affective, and sociocultural factors in relation to concern and preparation for uncertain risks. Another branch focuses on psychological, social, and cultural factors implicated in warning response for rapid onset hazards, with attention paid to previous experience and message design. Few studies link risk perceptions with cognition and response as elicited by specific examples of warnings. The present study unites risk perception, cognition, and response approaches by testing the contributions of hypothesized warning response drivers in one set of path models. Warning response is approximated by perceived fear and intended protective action as reported by survey respondents when exposed to hypothetical tornado warning scenarios. This study considers the roles of hazard knowledge acquisition, information‐seeking behaviors, previous experience, and sociodemographic factors while controlling for the effects of the visual warning graphic. Findings from the study indicate the primacy of a user's visual interpretation of a warning graphic in shaping tornado warning response. Results also suggest that information‐seeking habits, previous tornado experience, and local disaster culture play strong influencing roles in warning response.     

Variations of Q–Q Plots: The Power of Our Eyes!

In statistical modeling, we strive to specify models that resemble data collected in studies or observed from processes. Consequently, distributional specification and parameter estimation are central to parametric models. Graphical procedures, such as the quantile–quantile (Q–Q) plot, are arguably the most widely used method of distributional assessment, though critics find their interpretation to be overly subjective. Formal goodness of fit tests are available and are quite powerful, but only indicate whether there is a lack of fit, not why there is lack of fit. In this article, we explore the use of the lineup protocol to inject rigor into graphical distributional assessment and compare its power to that of formal distributional tests. We find that lineup tests are considerably more powerful than traditional tests of normality. A further investigation into the design of Q–Q plots shows that de-trended Q–Q plots are more powerful than the standard approach as long as the plot preserves distances in x and y to be the same. While we focus on diagnosing nonnormality, our approach is general and can be directly extended to the assessment of other distributions.