A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.     

相关信噪比对天线组阵相位估计性能的影响

传统天线组阵理论为了简化分析，均假设反正切相位鉴别器是一种最大似然估计器，其估计方差能够达到克拉美-罗下界。然而当相关信噪比在中等值以下时，这一假设条件不再适用。为此，分析了相关信噪比对相位估计性能的影响。针对传统天线组阵合成性能分析方法在描述低相关信噪比条件下相位估计性能方面存在的问题，通过引入修正因子，得到了相位估计方差的理论公式，实现了对低相关信噪比条件下相位估计性能的准确描述。     

浅议设计阶段几个重要方面的工程成本控制

本文从设计阶段的角度论述工程成本控制,同时提出相应的政策,为地产公司降低工程成本,实现自身的持续长期提供参考依据。     

The influence of intraday seasonality on volatility transmission pattern

Using data on a five-minute interval basis, this article analyses the effects of intraday seasonality on volatility transmission between the spot and futures markets of the CAC40, DAX30 and FTSE100. Remarkable differences in the impulse response analysis and in the dynamic and directional measurement of volatility spillovers are encountered depending on whether the intraday periodic component is considered. Thus, the convenience of removing intraday seasonality seems to be critical to reduce the risk of spurious causality when employing high-frequency data in volatility transmission. Moreover, the impact of market microstructure noise seems negligible when using an optimal frequency of observations.     

A systematic approach to assess the effectiveness of airport noise mitigation strategies

Regional airports are often located very close to the urban area they serve and the increasing traffic rate that many of them have experienced in the last years has produced several impacts on the communities living close to the airport area, mainly aviation noise. If not properly managed, noise impacts produced by airport operations can cut down significantly the development of airport air traffic with direct effects on the economic and territorial systems. Aeronautical noise has greatly reduced in the last decade, due to aircraft design technological improvements and more severe regulations. However, the noise reduction during a single event does not make the issue of the airport location – and then the whole noise impact – less significant. This paper proposes an assessment process to evaluate the effects of actions adopted to reduce airport noise impacts on populated areas. Both airport-related factors – such as number of take-off; day-evening-night distributions of movements; aircraft type; flying paths – and land-use characteristics have been considered and combined in a density index that synthesizes the impacts of airport noise on the territory. The assessment process has been tested on a real case, the airport of Bologna in Northern Italy. The predicted results, compared with available real data for the test case, are significant and encourage the use of the proposed assessment process as decision support system for the airport management.     

Does High Stock Price Synchronicity Always Hurt Mutual Fund Industry? Sentiment Matters

Investors have agreed that high synchronicity of stock returns adversely influences professional funds' profitability. However, different market conditions where high synchronicity exists may have different effects on this relationship. This study incorporates aggregate investor sentiment as a market condition in the equation to explore whether and when the negative association between synchronicity and fund performance holds. The authors use a sample of actively managed U.S. equity mutual funds from 2000 to 2014 and employ a portfolio of 11 passively managed funds as the benchmark to measure fund performance and fund management skill. They find empirical evidence that synchronicity negatively impacts mutual funds' profitability when the investor sentiment is low. This negative relationship disappears in high-sentiment periods. They also find that in both low- and high-sentiment states, fund managers with superior stock selection skill make more profits from high synchronicity than the average.     

扩频系统多通道相位差测量技术

论述了扩频无线电信号侦收和测向等应用领域中,在多通道天线和接收机后端采用数 字处理手段,在低信噪比下实现多通道相位差精确提取的方法。阐 述了多通道相位差提取的基本工程模型、中频信号采样处理方法、普通ASK调制信号的相位 差提取方法,以及BPSK调制的扩频信号的相位差提取方法,给出了基于MATLAB7.0.1平台的 仿真图形和结果。该技术已在工程中成功实现。     

超临界二氧化碳和脂肪酸及其酯的相平衡计算

对超临界ＣＯ２ 和脂肪酸及其酯相平衡计算问题进行了研究。用Ｐｅｎｇ－Ｒｏｂｉｎ－ｓｏｎ 状态方程和Ｐａｎａｇｉｏｔｏｐｏｕｌｏｓ－Ｒｅｉｃ混合规则,以及对能量参数ａ（Ｔ）做了改进后,用于计算脂肪酸及其酯和超临界ＣＯ２ 二元体系的相平衡,理论计算与实验数据拟合精度很好。此模型可为用超临界ＣＯ２ 萃取脂肪酸及其酯的工业化设计提供理论依据。     

反相高效液相色谱法快速分析紫脲酸

为了给咖啡因生产中的亚硝化反应、还原工艺提供准确的中间体检测数据,寻找紫脲酸含量快速分析方法,利用反相高效液相色谱法,通过进行紫脲酸样品波长选择实验、系统适用性实验、定量摸索实验、精密度实验、线性实验,确定了检测波长和紫脲酸样品质量浓度与样品峰面积之间的线性关系。在15.80~188.60mg/L范围内,紫脲酸样品质量浓度与样品峰面积之间的线性方程为y=71.785x,相关系数R2=0.999 8,表明紫脲酸样品质量浓度与样品峰面积之间具有良好的线性关系。使用反相高效液相色谱法能准确、快速检测紫脲酸样品含量,及时对还原反应进行过程监控。     

单光子卫星量子通信噪声和干扰分析

卫星量子通信是建立全球量子通信网络的最佳选择之一。针对采用偏振编码的卫星量子通信中的偏振保持问题,研究了大气散射和卫星与地面站间相对运动等因素对量子偏振态相位和对准的影响以及相位延迟和对准误差对系统量子误码率的影响,分析了背景噪声和系统硬件噪声对通信产生的影响以及单光子通信过程中可能受到的光子分离攻击干扰,为量子信号认知设计提供借鉴意义。