A Study of Noise &Development of Traffic Noise Annoyance Models

Although noise annoyance is a major public health problem in urban areas, noise problem is still a great challenge for both public and transportation planners. The quantitative study of traffic noise and its relationship with annoyance & traffic volume was discussed in the paper and at the same time we tried to develop new statistical regression models to relate them. In the present study we also tried to fit different regression models such as Log-Linear, Linear, Log-Log Linear and Quadratic over noise data and decided which model fitted the best by using mathematics of principle of maxima & minima. After the identification of best fit curve we use this to fit our data. The aim of the study was to assess the predictive value of various factors on noise annoyance in noisy and quiet urban streets of New Delhi, capital of India.

3D Analysis and Investigation of Traffic Noise Impact from Hemmat Highway Located in Tehran on Buildings and Surrounding Areas

This study analyzes and investigates the impact of traffic noise on high rise buildings and surrounding areas by the side of Hemmat Highway that links west of Tehran to the east. In this study, a 3D traffic noise simulation model is applied on a GIS system. Visualized noise levels are formulated by the proposed model for noise mapping on all surfaces of the buildings and surrounding ground in a 3D platform. The investigation shows that there is a high traffic noise impact on the foreground and front facades of buildings, rendering these areas unsuitable for residential purposes. The ground area by the sides of buildings and the building side panels receive a lower noise impact. Most of these areas are still not acceptable for residential and even commercial use, only the back yards and back panels, have the lowest traffic noise impact. It also shows that the building height is not an effective factor for reducing motorway noise on the upper part of the building. Finally, construction cantilever barriers with a height of seven meters, close to the outer edge of the highway was presented as an effective way to reduce noise within the allowable range of noise pollution for commercial and residential purposes.

Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.

A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

Transitions in a genotype selection model driven by coloured noises

This paper investigates a genotype selection model subjected to both a multiplicative coloured noise and an additive coloured noise with different correlation time τ1 and τ2 by means of the numerical technique. By directly simulating the Langevin Equation, the following results are obtained. （1） The multiplicative coloured noise dominates, however, the effect of the additive coloured noise is not neglected in the practical gene selection process. The selection rate μ decides that the selection is propitious to gene A haploid or gene B haploid. （2） The additive coloured noise intensity and the correlation time τ2 play opposite roles. It is noted that α and τ2 can not separate the single peak, while can make the peak disappear and ^-2 can make the peak be sharp. （3） The multiplicative coloured noise intensity D and the correlation time τ1 can induce phase transition, at the same time they play opposite roles and the reentrance phenomenon appears. In this case, it is easy to select one type haploid from the group with increasing D and decreasing τ1.

Enhancement of density divergence in an insect outbreak model driven by colored noise

The steady states and the transient properties of an insect outbreak model driven by Gaussian colored noise are studied in this paper. According to the Fokker-Planck equation in the unified colored-noise approximation, we analyse the stationary probability distribution and the mean first-passage time of this model. By numerical analysis, the effects of the self-correlation time of insect birth rate and predation rate respectively reveal a manifest population divergence on the insect density. The decrease of the mean first-passage time indicates an enhancement dynamic on the density divergency with colored noise of a large self-correlation time based on the insect outbreak model.

Efficient Time-Domain Signal and Noise FET Models for Millimetre-Wave Applications

Based on the active coupled line concept, a novel approach for efficient signal and noise modeling of millimeter-wave field-effect transistors is proposed. The distributed model considers the effect of wave propagation along the device electrodes, which can significantly affect the device performance especially in the millimetre-wave range. By solving the multi-conductor transmission line equations using the Finite-Difference Time-Domain technique, the proposed procedure can accurately determine the signal and noise performance of the transistor. In order to demonstrate the proposed FET model accuracy, a distributed low-noise amplifier was designed and tested. A model selection is often a trade-off between procedure complexity and response accuracy. Using the proposed distributed model versus the circuit-based model will allow increasing the model frequency range.

Rnoise 系统中的道路声屏障设计方法

介绍了一种基于综合数字地面模型以及随机车流声源等效替代和分解技术的户外道路交通噪声分析方法与系统．详细论述了基于该系统的道路声屏障设计与优化方法．该方法能够近似模拟实地各种环境条件的影响，如建筑物、地形、树木、植被以及大气条件等，在一定程度上实现了道路交通噪声和声屏障降效果的可视化设计与评价．

A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.

Impact of Noise Barriers on Air-Pollution Dispersion

The impact of noise barriers on gaseous air-pollution dispersion was examined using the high-resolution CLMM (Charles University LES (Large Eddy Simulation) Microscale Model). The dispersion of a mixture of nitrogen oxides (denoted as NOx—a mix of NO and NO2) was computed, providing the simulation in which wind direction is approximately perpendicular to the noise barriers. The barriers were assumed to be straight and infinitely long, with a height of 3 m. Dispersion of NOx was modeled for situations with no noise barriers along the highway, barriers on both sides, and for a single barrier on the upwind and downwind sides of the highway. The modelling results are presented and discussed in relation to previous studies and the implications of the results are considered for pollution barriers along highways.

Nonsaturation Throughput Enhancement of IEEE 802.11b Distributed Coordination Function for Heterogeneous Traffic under Noisy Environment

In this paper, we propose a mechanism named modified backoff （MB） mechanism to decrease the channel idle time in IEEE 802.11 distributed coordination function （DCF）. In the noisy channel, when signal-to-noise ratio （SNR） is low, applying this mechanism in DCF greatly improves the throughput and lowers the channel idle time. This paper presents an analytical model for the performance study of IEEE 802.11 MB-DCF for nonsaturated heterogeneous traffic in the presence of transmission errors. First, we introduce the MB-DCF and compare its performance to IEEE 802.11 DCF with binary exponential backoff （BEB）. The IEEE 802.11 DCF with BEB mechanism suffers from more channel idle time under low SNR. The MB-DCF ensures high throughput and low packet delay by reducing the channel idle time under the low traffic in the network. However, to the best of the authors＇ knowledge, there are no previous works that enhance the performance of the DCF under imperfect wireless channel. We show through analysis that the proposed mechanism greatly outperforms the original IEEE 802.11 DCF in the imperfect channel condition. The effectiveness of physical and link layer parameters on throughput performance is explored. We also present a throughput investigation of the heterogeneous traffic for different radio conditions.

The effect of stochastic acceleration and delay probability on the velocity and the gap between vehicles in traffic flow

This paper proposes a new combined cellular automaton （CA） model considering the driver behavior of stochastic acceleration and delay with the velocity of the preceding vehicle and the gap between the successive vehicles based on the WWH model and the noise-first NaSch model. It introduces the delay probability varying with the gap, adds the anticipation headway and increases the acceleration with a certain probability. Through these simulations, not only can the metastable state and start-stop wave be obtained but also the synchronized flow which the wide moving jam results in. Moreover, the effect of stochastic acceleration and delay on traffic flow is discussed by analyzing the correlation of traffic data. This indicates that synchronized flow easily emerges in the critical area between free flow and synchronized flow when acceleration and delay are synchronized or their probability is close to 0.5.

桥梁预拱度对行车舒适性的影响及桥面线形调整

为研究成桥预拱度对连续刚构桥行车舒适性的影响,以多座主跨跨径为110~200 m的连续刚构桥为研究对象,首先,采用滤波白噪声法建立桥面时域模型,并与按余弦曲线设置的成桥线形叠加模拟成桥后的桥面不平度;其次,采用MATLAB/Simlink搭建车辆-桥面系统模型,以加速度均方根值(RMS)作为桥梁边跨、中跨桥面的行车舒适性评价指标,以最大瞬态振动值(MTVV)作为边跨峰值处短时内的行车舒适性评价指标;最后,分析采取经验法按照余弦曲线设置成桥预拱度的桥梁其跨径和设计时速对边、中跨RMS值的影响,以及成桥预拱度取值对边跨3L/8处MTVV值的影响。研究结果表明:在边跨、中跨处RMS值均小于0.315 m/s^(2),说明采取经验法按照余弦曲线设置成桥预拱度并不影响中跨处的行车舒适性;在边跨3L/8处MTVV值在短时内存在大于0.345 m/s^(2)的情况,说明在边跨峰值处短时内会产生一定不舒适感。提出了一种基于桥面铺装层施工优化边跨3L/8处和边墩墩顶桥面线形的方法,改善了边跨的行车舒适性。

基于分布式光纤声传感火车噪声属性的车型识别及运行规律

火车运行时产生强烈的移动噪声传播至地下空间,形成一种绿色环保、强能量的人工地震波.由于载荷系统形态基本固定,火车运行时间规律,震源重复性高,这种火车震源被广泛应用于轨道安全监测、近地表成像和城市地下空间探测等领域.分布式光纤声传感是一种新兴的地震采集技术,拥有密集采样、布设简单、抗电磁干扰能力强等优点,近年来在城市交通事件微震监测、裂隙探测和地下空间成像领域逐步应用.本研究基于分布式光纤声传感技术获得的秦皇岛试验场火车移动噪声数据,拾取了30个火车交通事件,开展火车噪声视速度、波形和频谱、能量时空变化的属性分析.结果表明:试验区光纤传感的火车噪声具有明显的属性差异,低速度重载荷的火车比高铁引起的地震振幅更大、能量更强,低速火车产生的噪声包含了丰富的低频信息;根据已知的视速度、振幅属性、时频属性,划分了4种类型的火车,并揭示了它们的进出站规律.本研究拓展了分布式光纤传感的应用场景,证明分布式光纤声传感有望应用于不同车型的通勤监测.

基于变分贝叶斯算法的多模型车载组合导航算法

在行车过程中强机动引起全球卫星导航系统(GNSS)量测噪声产生野值,表现出厚尾特性导致常规状态估计精度下降的问题,为此提出一种基于变分贝叶斯的SINS/GNSS组合导航信息融合方法。构建车载组合导航系统模型,采用Student’s t分布对量测异常情况下噪声建模,并用变分贝叶斯的方法对系统状态和隐变量进行求解,实现对模型参数的后验估计。针对城市行车存在GNSS测量失效的问题,利用交互式多模型算法实现了GNSS量测中断情况下的SINS/GNSS和SINS/OD子系统的动态交互融合。通过跑车实验进行验证,实验结果表明,所提算法可有效抑制GNSS量测野值噪声对SINS/GNSS/OD组合导航系统的影响,与传统交互式多模型算法相比,具有较高的精度和鲁棒性。

Impact of Colored Noise on Population Model with Allee Effect

We study a population model with strong and weak Allee effect driven by internal noise and external noise.Firstly, a single-species population model with Allee effect under environmental colored noise is established, then stable and unstable states are analyzed and interpreted in biology. After that, stationary probability distribution(SPD) of population is derived based on Fokker-Planck equation. Next, mean first-passage time(MFPT) is defined in order to quantify the transition between extinction state and survival state with Allee effect. It is found that population will not extinct when weak Allee effect exists. It is not beneficial to survival of the population with the increase of Allee threshold no matter whether strong Allee effect or weak Allee effect. When strong Allee effect occurs, the correlation time of multiplicative noise plays a positive role in survival of population, while the correlation time of additive noise has a negative effect. Crucially, the phenomenon of resonant activation is firstly discovered in population dynamics with Allee effect. The conclusions we obtain can be applied to the further research of population dynamics in ecology.

结合特征选择的抗噪声网络流分类

在现代网络管理中,网络环境愈加复杂,网络流噪声已经成为不可忽视的因素,然而现有的抗噪声流分类方法在实际效果上仍有不尽人意之处。针对这一问题,本文提出了一种结合特征选择的抗噪声网络流分类方法NNTC-FS,该方法采用投票机制判定噪声并搭建级联结构,实现先过滤再分类的线上任务。在公共数据集上的实验表明,NNTC-FS能实现90%以上的分类正确率,并在分类精度和时间性能上优于文献方法。

南京市典型快速路交通噪声监测与影响分布研究

为科学全面地开展城市道路交通噪声影响评估,更精确地服务道路交通噪声污染治理工作,选取南京市具有代表性的道路交通干线,采用手工监测和自动连续监测的方法,进行不同路段噪声污染程度及其随时间、空间变化规律的研究。结果表明,地面快速路段、高架路段以及衔接路段两侧噪声敏感建筑物受道路交通噪声影响较大,夜间均超标;相邻区域要达到2类声环境功能区昼间标准限值要求,需距离地面快速路慢车道约45 m,距离高架路段慢车道约92 m;要达到2类声环境功能区夜间标准限值要求,需距离地面快速路慢车道约175 m,距离高架路段慢车道约172 m;敏感建筑物所受噪声影响随楼层高度升高而增大,同时噪声影响情况与道路两侧建筑物密度、道路车辆行驶速度有关。建议严格道路及噪声敏感建筑物规划控制,采取阻断传声路径、受声建筑物强化保护等措施控制噪声影响。

基于道路交通噪声预防的规划指标研究

道路交通噪声已成为影响城市居民生活最大的环境污染源之一。为推动降噪型用地布局模式落地应用、推进宁静城市建设,针对既有规划指标体系尚未纳入噪声预防相关指标的现状,提出将空间噪声指数作为定量化的噪声预防规划指标。进而提出空间噪声指数的理想指标值计算模型,并结合拉萨、张家港等10个案例进行指标计算与评估。对于实际指标值偏大的案例,建议参考降噪型用地布局模式,以空间噪声指数为约束对用地空间布局进行优化调整。降噪型用地布局模式揭示了城市交通与土地利用之间的互动新机制,而借助空间噪声指数可对该机制进行客观评估。最后提出将空间噪声指数作为空间品质类约束指标纳入城市总体规划指标体系并向下传导落实,对中远期规划实践以及城市更新等近期治理行动进行约束、引导和评估。

南京市典型道路交通噪声三维分析

作为一种非稳态、不连续的流动污染源,交通噪声影响范围广,时间长,程度深。本文以南京市为例,从水平分布、垂直分布和24 h连续监测三个维度分析典型道路交通噪声。结果表明,随着距慢车道水平距离的扩大,非高架段道路昼夜声级逐步衰减;高架段道路夜间噪声受居民生活噪声的影响显著,距离增加导致声级下降;高架道路和非高架道路混合路段,噪声水平和垂直分布变化呈现一定规律,24 h声源状况与车流量存在一定相关性。