一种改进的电力线通信系统脉冲噪声抑制方法

为了抑制脉冲噪声对电力线正交频分复用（OFDM）通信系统的影响，最常用的方法之一是在接收端OFDM解调器之前前置一个置零非线性单元，即传统置零法。然而，由于引入了非线性失真，其性能并不理想。针对传统置零法引起的非线性失真问题，提出了一种基于迭代消除非线性失真的改进置零法。首先，对接收到的时域OFDM信号进行脉冲噪声检测和置零处理；然后，在频域利用已检测的符号来重构时域置零处理引入的非线性失真，并通过迭代提高重构的准确性；最后，从频域接收信号中减去重构的非线性失真。仿真结果表明，所提改进算法与传统置零法相比，有非常大的性能提升，增强了电力线OFDM通信系统对脉冲噪声的抵抗能力。     

Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

结合全双工与协作干扰的无线网状网物理层安全策略

针对无线网状网中缺少窃听者先验知识不利场景中的安全连接问题，提出了一种结合全双工和协作干扰技术的物理层安全策略。利用全双工通信中的自干扰消除技术和协作干扰技术，提出的安全策略可有效劣化位于信息传播范围内包括潜伏在接收节点附近窃听者的接收性能。为保证信息的安全传输给出了协作干扰节点的选择方法，基于随机几何等数学方法导出了选定路径的安全连接概率表达式。性能分析和仿真结果表明，所提方法与仅基于全双工或协作干扰技术的方法相比，其安全性能有较大提升。     

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.     

Comparison of public perception and risk management decisions of aircraft noise near Taoyuan and Kaohsiung International Airports

This study uses multiple linear regression to identify factors contributing to perceived risk among residents near Taoyuan and Kaohsiung International Airports, the effect of perceived risk on their willingness to reduce risk, and consumption preferences that can reduce risk. Results indicated that residents' risk perception near Taoyuan Airport is lower than that near Kaohsiung Airport. Noise pollution experience, perceived probability of environmental contamination and negative effects, and perceived severity of catastrophic consequences significantly increase residents' perceived risks. Residents are willing to recognize and participate in mitigating the risks of aircraft noise pollution. The more risk residents perceive, the more willing they are to participate in disaster reduction and investigate means of improving the risk environment.     

基于模态应变能密度理论的网架结构损伤识别方法

为了研究网架结构的损伤检测方法,根据应变能密度理论,提出采用单元模态应变能密度差值作为网架结构损伤识别指标的方法,以损伤单元模态应变能密度差值的大小初步确定单元的损伤程度。分析了5种具有代表性的损伤工况,并在数值计算结果中引入了白噪声。结果显示,在一阶模态下,针对单损伤、多损伤和轻微损伤、严重损伤等不同损伤工况,损伤杆件的模态应变能密度差值均为高值。因此,该方法可以有效识别出网架结构的损伤位置,根据损伤单元的模态应变能密度差值大小初步确定单元的损伤程度,且在一定的噪声水平下具有较强的鲁棒性,对网架结构损伤识别具有参考价值。     

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.     

基于Gibbs采样的MIMO信号检测改进算法

针对传统Gibbs采样算法的“失控问题”,提出了一种改进算法,在Gibbs迭代采样过程中加入对噪声方差的估计,消除了失控问题。设计了信号检测流程,将最大似然（ML）检测的搜索过程嵌入Gibbs迭代采样过程,减少了最大似然检测的计算步骤。仿真结果表明,所提算法能估计噪声方差,具有接近最大似然检测的性能。     

对空情报雷达网密集假目标干扰机理分析

针对雷达网欺骗干扰问题,首先讨论了雷达网数据关联处理方法薄弱环节,给出了可以欺骗雷达网的假目标应该满足的条件,然后分析对空情报雷达网密集假目标干扰的产生机理和作用机理,为产生高逼真的假目标,将空间分布转化为非线性最优化问题。当进行多干扰机协同干扰时,将干扰机功率资源在空间的分配问题转化为非线性规划问题。仿真研究了对网络化雷达的假目标欺骗干扰效果以及影响干扰效果的因素,该结果可为对空情报雷达网电子对抗提供理论指导。     

不同调制方式下高斯信道容量的计算

计算不同调制方式下的信道容量对实际通信系统的信道编译码设计具有重要的理论意义。首先从Shannon信息论出发,介绍了平稳无记忆连续信道与加性白高斯噪声信道容量的定义。接着利用互信息与微分熵的相互关系,推导了几种常用的不同调制方式下高斯信道的容量,并给出了相应的信道容量闭合计算表达式。通过将电力卫星通信信道模拟为高斯信道,对采用无速率信道编码联合不同调制方式的卫星通信进行了数值仿真。仿真结果显示,通过推导得到的闭合表达式计算信道容量,能对实际卫星通信的编码速率、译码启动条件的确定起到很好的理论指导作用。