北京地区中小套型住宅居住需求及对策研究

通过对北京地区中小套型住宅居住实态调研结果进行数据统计分析,探讨了住户在住宅使用过程中存在的共性问题,分析了住户的使用需求,并提出了相应的合理化建议．文中还选取两个典型实例进行改造,为以后住宅改造与设计提供了一定的借鉴与参考．     

可量测实景影像在城市部件管理中的应用

介绍了移动测量系统采集的可量测实景影像在城市部件管理中的应用,通过对城市立面街景影像与部件地图、属性关联技术,利用实景影像对部件量测技术,提出了一种集成地图、部件属性库和多角度影像的城市部件管理新手段．     

科学发展观视域下的教育创新对摆脱我国经济困境的作用

全球金融危机之下,我国经济出现了一定程度的发展困境,而摆脱困境的出路在于科学发展,科学发展关键在于人才和教育．目前我国教育在观念、方法、格局等方面与培养创新人才有诸多不适应,需要进行相应的调整、改革和创新．     

高层住宅厨房主支式集中排风系统的运行特性

目的 为探讨导致集中式排风系统排风量不足甚至出现倒烟的原因及确定最佳管道横截面积.方法 通过CFD方法模拟,建立层数为15层的仿真模型,分别计算了排风管道系统在几个不同规格截面积和设定不同的开机率条件下的典型气体流动工况.并且对照实验装置进行的实际测量数据,对模拟结果进行比较和修正.通过观察系统内压强和速度的分布,分析其排风效果.结果 400 mm×700 mm的管道截面积基本可以满足系统在各开机率下运行,其中30%开机率时,未开机用户全部无回流.而400 mm×500 mm、400 mm×600 mm两种截面积时,各工况下都有不同程度的回流.结论 主管道的截面积和开机率是影响系统排风效果的主要因素.     

基于LVQ神经网络的城市快速路事件自动检测算法

基于具有自组织功能的学习矢量量化(LVQ)神经网络设计了城市快速路异常事件的自动检测算法,提出分车道检测的构想。研究了原始数据筛选、输入向量模式、神经元个数及检测时段等参数的选择。基于小波分析技术对原始数据的高频噪声进行滤波,引入长车流量作为输入参数,并对比了引入前后的检测效果。选用加利福尼亚算法作为评价的参考依据,对其执行过程和门限值的选择进行了研究。     

SAMPAVE沥青混合料级配设计研究

SAMPAVE(Stress Absorbing Mixtures Pavement)沥青混合料是一种新型的延缓和防止反射裂缝的应力吸收层材料,具有抗裂、防渗、粘结等特性.根据变i法对SAMPAVE混合料进行矿料组成设计,并与AC-5、美国规范、科氏公司推荐的级配范围进行比较.结果表明,对于变i法设计的SAMPAVE混合料,级配上限、级配下限确定的沥青用量在设计工程级配沥青用量的±0.3%范围内,满足生产控制的要求,且SAMPAVE混合料具有优良的耐高温、耐低温、抗变形、耐疲劳、抗水损害等路用性能.     

Discrimination for ablative control mechanism in solid-propellant rocket nozzle

The ablation in solid-propellant rocket nozzle is a coupling process resulted by chemistry, heat and mass transfer. Based on the heat and mass transfer theory, the aero-thermo-dynamic, and thermo-chemical kinetics, the thermal-chemical ablation model is established. Simulations are completed on the heat flow field and chemical ablation in the nozzle with different concentrations, frequency factors and activation energy of H2. The calculation results show that the concentration and the activation energy of H...     

基于 ROS 改进算法的无线传感器网络耗能研究

成对广播同步（PBS）是无线传感器网络同步研究的重要协议。无线传感器节点具有体积受限、通信能力有限、存储空间较低、能量有限等特点,对传统的时钟同步协议改进是非常有必要的。因此,研究无线传感器网络的时钟同步算法将具有重要的意义。文章建立在仅接收端（ROS）同步基础上实现范围广阔的网络同步,并且能够在无线传感器网络节点的能耗方向有着不可忽视的作用。通过对单簇网络同步的研究,提出多簇网络同步并对多簇网络同步在无线传感器网络同步中全网成对选择算法（NPA）和基于组的成对选择算法（GPA）做出研究,并且做出了仿真对比。结果显示：在传感器节点数目较少的情况下,NPA 算法与 GPA算法处理消息包数目的性能几乎相同;在网络中传感器节点数目比较多的情况下,GPA 算法明显优于 NPA 算法,信息处理过程中大大减少了消息包数目。最后,对广播同步技术在应用中所出现的问题,提出了基于此算法的新的研究方向。     

An integrated emotional and physiological assessment for VR-based active shooter incident experiments

Unfortunately, active shooter incidents are on the rise in the United States. With the recent technological advancements, virtual reality (VR) experiments could serve as an effective method to prepare civilians and law enforcement personnel for such scenarios. However, for VR experiments to be effective for active shooter training and research, such experiments must be able to evoke emotional and physiological responses as live active shooter drills and events do. The objective of this study is thus to test the effectiveness of an active shooter VR experiment on emotional and physiological responses. Additionally, we consider different locomotion techniques (i.e., walk-in-place and controller) and explore their impact on users’ sense of presence. The results suggest that the VR active shooter experiment in this study can induce emotional arousal and increase heart rate of the participants immersed in the virtual environment. Furthermore, compared to the controller, the walk-in-place technique resulted in a higher emotional arousal in terms of negative emotions and a stronger sense of presence. The study presents a foundation for future active shooter experiments as it supports the ecological validity using VR for active shooter incident related work for the purposes of training or research.     

Evolutionary digital twin: A new approach for intelligent industrial product development

To fulfill increasingly difficult and demanding tasks in the ever-changing complex world, intelligent industrial products are to be developed with higher flexibility and adaptability. Digital twin (DT) brings about a possible means, due to its ability to provide candidate behavior adjustments based on received “feedbacks” from its physical part. However, such candidate adjustments are deterministic, and thus lack of flexibility and adaptability. To address such problem, in this paper an extended concept – evolutionary digital twin (EDT) and an EDT-based new mode for intelligent industrial product development has been proposed. With our proposed EDT, a more precise approximated model of the physical world could be established through supervised learning, based on which the collaborative exploration for optimal policies via parallel simulation in multiple cyberspaces could be performed through reinforcement learning. Hence, more flexibility and adaptability could be brought to industrial products through machine learning (such as supervised learning and reinforcement learning) based self-evolution. As a primary verification of the effectiveness of our proposed approach, a case study has been carried out. The experimental results have well confirmed the effectiveness of our EDT based development mode.