理性与感性的融合——浙江舟山新城中学规划设计

新城中学是一所省级重点中学的迁建项目.通过介绍这一项目的立意和方案设计过程,为当前时代背景下创造中学校园特色空间提供思路与理念.     

基于nRF24L01的小车自动识别红绿灯的设计

为了防止汽车闯红灯,初步设计了一个智能小车自动识别十字路口红绿灯的系统.以STC89C52最小操作系统为控制核心、采用nRF24L01无线通讯等智能模块,实现车自动识别十字路口红绿灯功能.小车通过nRF24L01无线通讯识别直行方向是红灯还是绿灯,绿灯则通行、红灯则等待.主要给出了设计方案、无线通信模块的原理和2.4G...     

上行高峰时段蒙特卡罗电梯交通流预测方法研究

摘要：为实现电梯的合理选型配置,需对大楼内上行高峰时段的交通流做出准确预测。通过改进传统蒙特卡罗交通流模型．计算累积概率值可以提高预测精确度。理论分析和仿真结果表明在上行高峰时段．改进的蒙特卡罗交通流预测方法比传统的方法预测精度更高。     

基于建筑物交通流量分析的电梯交通配置方法

对建筑物的属性、建筑物所安装的电梯属性以及电梯运行模式进行了详细分析;提出了一种基于建筑物垂直交通流量分析的电梯交通配置软件编程思路。     

基于CR-LDP TLV的流量工程实现策略

为了在MPLS网络中使流量分布趋于合理,提出了一种基于CR-LDP(限制路由标记分配协议)中TLV(类型长度值)的流量工程实现策略及算法。该策略通过对网络资源属性和业务流属性的综合考虑,依据对特定业务流进行裁决的判别函数,将适于迁移的TLV结构业务流进行合理地及时迁移,从而达到提高网络资源利用率的目的。仿真结果验证了该策略及算法的正确性和有效性。     

一种均衡网络流量的遗传算法

基于整数规划的多限制条件下流量分布优化数学模型,该文设计了一种基于遗传算法的优化算法来求解计算复杂度高的均衡网络流量问题,进行全空间并行搜索,采用自然数编码及选择交叉变异算子,结合最优个体保存策略进行选择,融入自动信息。仿真结果证明算法是有效的,改善了传统路由算法易于导致的网络流量分布不均衡的状况。     

无线局域网帧数据流量研究的问题和挑战

无线局域网中的信道要比有线局域网信道复杂得多,研究运载其上的流量成为评估和了解无线局域网行为模式的关键。本文比较了有线和无线局域网在体系结构和协议机制上的差异,进而从AP节点处理帧数据流程上分析了无线局域网IP数据流量和帧数据流量上的差异,提出了无线局域网流量研究中存在的问题,探讨了无线局域网帧数据流量的研究内容和方向。     

一种控制BT流量的方法及其对用户的影响

针对BT流量占用大量带宽资源的问题,提出了BT令牌桶流量控制算法。分析了在网络出口控制BT带宽前后,内网用户的下载速率和内网平均用户数的变化。结果表明,控制出口BT带宽后,内网peer之间的数据传输速率会适当增加,平均每个peer的下载速率有所减少,平均内网peer数增加。将具有BT令牌桶流控功能的设备应用于试验网络环境中,测试结果表明,该算法有效,分析结果正确。     

Impulsivity and risky decision making among taxi drivers in Hong Kong: An event-related potential study

Taxi drivers play an important role in providing safe and professional public transport services. However, they tend to be more involved than other professional driver groups in accidents caused by deliberate recklessness. This study used an event-related potential (ERP) experiment to examine risk-taking behavior arising from impulsivity by comparing the underlying neural processes of taxi drivers with and without traffic offence records in Hong Kong. A sample of 15 traffic offenders and 15 nonoffenders, matched by sociodemographic characteristics, was recruited. The results show that the offender group demonstrated significantly less negative-going (less negative) feedback-related negativity but more positive-going (more positive) feedback-related P300 when than with their nonoffending counterparts. These findings show that taxi drivers with traffic offence records were less sensitive to the consequences of behavior and more attuned to the magnitude of potential reward. In addition, behavioral data revealed that they were more willing to make risky decisions. All these characteristics pertain to impulsive personality traits. Based on these findings, we can conclude that the offenders in this sample were more impulsive than their nonoffending counterparts.     

The sensitivity of estimates of regression to the mean

Estimations of the effectiveness of remedial treatments in road safety analysis are frequently bedevilled by the problem of regression to the mean (RTM). The number of accidents x observed at a site in the “before” period is a “noisy” quantity: x is Poisson distributed about an (unknown) true mean m for that site, so that x = m + e. Sites selected for treatment tend to have a positive random error component e, which will on average be zero in the “after” period, even if no treatment is applied.Methods for estimating RTM usually require some assumption about the underlying (prior) between-site distribution of the true means f₀(m): for example, in the empirical Bayes method, a gamma distribution is assumed. The paper considers the impact of different assumptions for this distribution and, indeed, whether any distributional form needs to be assumed. Using Markov Chain Monte Carlo methods, a variety of distributional forms are assumed for f₀(m) and applied to each of a number of real data sets, including that from a major study on the effectiveness of speed cameras. It is shown that, in some cases, the size of the estimated RTM effect can be quite sensitive to the choice of distribution.