基于多维评价模型及改进蚁群优化算法的云计算资源调度策略

针对云计算环境下资源调度模型未充分考虑资源评价的问题,为更好适应不同节点计算性能和大规模数据环境的处理需求,提出了一种基于多维评价模型的虚拟机资源调度策略。首先,在云计算环境下建立包括网络性能在内的多维资源评价模型,在此基础上提出一种改进的蚁群优化算法实现资源调度策略;然后在云计算仿真平台CloudSim上进行实现。实验结果表明,该算法可以更好适应不同网络性能的计算环境,显著提高了资源调度的性能,同时降低了虚拟机负载均衡离差,满足了云计算环境下的虚拟机资源负载均衡需求。     

基于TDLAS的CO检测系统调制参数优化与温度补偿

在可调谐激光吸收光谱(TDLAS)技术中,携带气体浓度信息的二次谐波信号易受激光扫描信号与调制信号的幅值、频率等参数影响。基于TDLAS技术搭建了CO浓度检测硬件系统,与对应仿真模型进行比较分析,研究了调制参数对二次谐波信号峰值、信噪比、对称性以及峰宽的影响,总结出具体变化规律。实验确定了系统最优调制参量,在硬件不变的情况下提高了检测精度。对CO在1567.7nm的吸收光谱进行了检测,发现测量浓度随着温度的升高而降低,最大相对误差已超过15%。为了减少温度变化对测量的影响,分别采用RBF及BP神经网络、PSO优化BP神经网络和WOA优化BP神经网络算法对系统进行补偿。结果表明,WOA优化BP神经网络方法的补偿效果最好,修正后浓度相对误差降至1%以下,有效提高了系统在变温环境下的准确性和稳定性。研究为系统的调制参数设置以及精准检测提供参考,为后续实验提供了有价值的指导。     

一种脉冲电流工况下晶闸管缓冲电路的优化方法

对脉冲工况下超导磁体失超保护系统的晶闸管阀组缓冲回路参数进行设计和优化。基于晶闸管反向恢复电流的指数衰减模型建立了晶闸管关断时刻的电流数学模型。通过测试实验获得关键参数之间的关系并结合晶闸管性能及系统要求在Matlab中建立晶闸管电流反向恢复模型。考虑关断时刻电流下降率、反向恢复电压峰值等性能指标要求及回路研制费用,提出了一种脉冲工况下晶闸管缓冲回路的参数设计及优化方法。在Matlab中搭建失超保护系统模型,对比优化前后缓冲回路对系统在晶闸管关断时刻电气性能的影响,仿真结果显示,相比于原参数,最优参数下,反向恢复电压峰值降低了11%,反向恢复电压变化率峰值降低了43%。同时,回路制造成本降低为原先的1/7。     

基于SOM和PSO的云计算异构资源聚类MPI并行算法

针对云计算环境下大量用户请求同时到来造成的短暂峰值,使得用户的QOS服务需求不能得到有效保证,设计了一种基于MPI并行计算模型和SOM的异构资源聚类方法;首先,设计了一种改进的MPI的树状层次结构模型,然后,定义了基于SOM自组织映射的资源聚类算法,为了提高资源聚类精度,将PSO算法用于SOM的参数优化中,使得SOM在初始时刻就具有一个较好的连接结构;最后,为了充分满足用户请求的QOS需求,将MPI树状层次结构与基于PSO的SOM资源聚类算法相结合,并提出了具体的基于MPI的SOM资源聚类算法;为了验证文中方法,在Matlab仿真环境中进行测试,实验结果表明文中方法聚类精度为100%,且与其它方法比较,具有较高的聚类精度和较少的执行时间,是一种云计算环境下的可行资源聚类方法。     

基于关键帧的核密度估计背景建模方法

在充分研究现有运动目标检测算法的基础上,提出了一种新的非参数核密度估计背景模型。应用高斯核密度估计进行背景建模,不需要事先假定背景特征的密度分布,根据视频序列像素灰度的相似性原理从训练样本中提取关键帧,减小了密度估计的样本量。将剩余的灰度值按距离最近原则归并到关键帧中去,降低目标检测的虚警率和误检率。实验结果表明:该算法在检测精度影响极小的情况下,大大提高了原算法的速度,可用于室外的实时视频监控系统。     

云计算环境下动态数据聚集算法研究

云计算技术的普及带动了数据的增长,为了对云环境下动态数据进行管理,防止数据损坏甚至丢失,方便后续利用,需要对云计算环境下动态数据进行聚集。但目前大多数算法都是基于线性时间概率计数的数据聚集算法,通过数据聚集操作在中间节点预先对数据进行处理,去除数据冗余,减少数据传输,实现节能,对于云计算环境下数据聚集操作存在的重复计数问题,通过研究对副本不敏感的概要结构并优化某些特性,从而完成数据聚集,但这种方法存在占用的存储空间较大,且不能保证动态数据聚集的准确性的问题。为此,提出一种基于粒子群优化算法的云计算环境下动态数据聚集算法,该算法通过对云计算环境下动态数据聚集算法数学模型进行分析,在此基础上,提出基于粒子群优化算法的云计算环境下动态数据聚集算法。首先对云计算环境中的动态数据结构模型进行分析,完成对云计算环境下动态数据的离散样本频谱特征的计算,实现云计算环境下动态数据聚集样本的特征提取和信息模型构建。针对粒子群算法收敛速度慢的问题,本文通过混沌映射方法对其进行优化,通过生成混沌序列,解决粒子群算法存在的问题,利用粒子群优化算法进行特征聚集,从而完成云计算环境下动态数据聚集算法。实验结果表明,本文所提算法能够有效提高动态数据聚集的可靠性和稳定性,降低聚集时间,减少所占内存空间,具有较强的实践性,为该领域的发展创造了条件。     

基于嵌入式和运动检测的井下视频监控系统

针对传统模拟信号监控的不足,设计了一种基于S3C6410硬件平台、Linux2.6软件平台、H.264标准及运动检测算法和WIFI无线网络传输的井下视频监控系统;针对井下监控背景基本不变,采用H.264图像压缩算法以及改进的单高斯模型运动检测算法;并提出了整体监控软件的设计方案;最后通过PSNR、压缩比、压缩时间以及压缩速率等参数对算法进行了实验,实验结果表明:该系统能在较低的编码速率上实现较好的成像质量,具有较高的压缩质量,可满足实时编码需求。     

船用星敏感器探测灵敏度计算及分析

星敏感器作为一种被广泛应用于各种载体上的高精度自主导航定位设备,探测灵敏度影响着其工作效率及测量精度。与航天器载体上的星敏感器不同,船用星敏感器工作在海平面环境下,其探测灵敏度不仅由镜头及成像传感器的各项参数决定,还要受到夜空背景以及大气透射等外部因素的影响。为了给船用星敏感器的研制与应用提供理论依据,通过对星光传播、传感器成像以及信号提取过程的研究分析,推导出了船用星敏感器探测灵敏度的计算模型,并通过实验验证了该模型的有效性,在此基础上,分析了各项因素对船用星敏感器探测灵敏度的影响情况,根据分析结果对船用星敏感器系统的设计研制提出了相应建议。     

湍流大气光通信系统误码率分析与实验研究

自由空间光通信(FSO)系统的性能由于受大气湍流影响会产生剧烈波动。根据系统和大气参数评估系统差错性能的研究具有现实意义。以大气湍流信道和光电探测两个模型为基础,建立了FSO系统差错性能的数学仿真模型,提出了湍流条件下系统误码率计算公式。对仿真结果与弱湍流条件下获得的实验数据进行了比较,并依据此模型对光强起伏和背景噪声等因素的影响进行仿真。仿真结果表明,基于该模型的仿真结果与实验数据一致,光强起伏是引起系统性能波动的主要因素,最优判决阈值需根据实际大气条件进行调整。该模型可有效评估湍流条件下FSO系统性能,并为相关理论研究提供参考。     

基于Storm的城市消防联网远程监控系统的实时数据处理应用

针对城市消防联网远程监控系统中实时信息数据逐渐增长而引出的大数据问题,传统的消防系统无法实时、高效地处理消防实时数据的问题,提出了一种基于云计算和Storm实时数据处理系统的解决方案;对于开源的Storm框架进行需求和性能分析,实现对其技术架构上的改进,并结合消防系统的特点,提出一套高实时性、高可扩展性的消防联网监控中心的数据实时处理的体系架构,同时也进行了云计算平台的搭建,利用心跳检测机制保证各个监控单位的实时性连接;研究表明,基于云计算和Storm平台架构完全适用于消防联网监控中心的实时消防数据的处理,具有高效性、高可靠性、性能显著等特性。     

基于元胞自动机考虑传播延迟的复杂网络病毒传播研究

基于元胞自动机,研究传播延迟对复杂网络病毒传播动力学行为的影响,提出一种新的易染状态-感染状态-易染状态(SIS)传播模型.研究表明,传播延迟的存在显著降低了网络的传播临界值,增强了网络中病毒爆发的危险性.研究还发现,随着传播延迟的增大,病毒的感染程度以及传播速率都明显增大.此外,SIS传播模型不仅能够反映病毒的平均传播趋势,而且可以描述病毒随时间的动态演化过程以及病毒的爆发和消亡等概率事件,从而有效地克服了利用平均场方法构建的微分方程模型只能反映病毒平均传播趋势的局限性.同时,还给出有效控制网络中病毒传 关键词： 复杂网络 病毒传播 元胞自动机 传播延迟     

The role of nonlinear effects in the propagation of noise from high-power jet aircraft

To address the question of the role of nonlinear effects in the propagation of noise radiated by high-power jet aircraft, extensive measurements were made of the F-22A Raptor during static engine run-ups. Data were acquired at low-, intermediate-, and high-thrust engine settings with microphones located 23-305 m from the aircraft along several angles. Comparisons between the results of a generalized-Burgers-equation-based nonlinear propagation model and the measurements yield favorable agreement, whereas application of a linear propagation model results in spectral predictions that are much too low at high frequencies. The results and analysis show that significant nonlinear propagation effects occur for even intermediate-thrust engine conditions and at angles well away from the peak radiation angle. This suggests that these effects are likely to be common in the propagation of noise radiated by high-power aircraft.     

Correlation and trust mechanism-based rumor propagation model in complex social networks

In real life, the rumor propagation is influenced by many factors. The complexity and uncertainty of human psychology make the diffusion model more challenging to depict. In order to establish a comprehensive propagation model, in this paper, we take some psychological factors into consideration to mirror rumor propagation. Firstly, we use the Ridenour model to combine the trust mechanism with the correlation mechanism and propose a modified rumor propagation model. Secondly, the mean-field equations which describe the dynamics of the modified SIR model on homogenous and heterogeneous networks are derived. Thirdly, a steady-state analysis is conducted for the spreading threshold and the final rumor size. Fourthly, we investigate rumor immunization strategies and obtain immunization thresholds. Next, simulations on different networks are carried out to verify the theoretical results and the effectiveness of the immunization strategies. The results indicate that the utilization of trust and correlation mechanisms leads to a larger final rumor size and a smaller terminal time. Moreover, different immunization strategies have disparate effectiveness in rumor propagation.     

The opportunistic transmission of wireless worms between mobile devices

The ubiquity of portable wireless-enabled computing and communications devices has stimulated the emergence of malicious codes (wireless worms) that are capable of spreading between spatially proximal devices. The potential exists for worms to be opportunistically transmitted between devices as they move around, so human mobility patterns will have an impact on epidemic spread. The scenario we address in this paper is proximity attacks from fleetingly in-contact wireless devices with short-range communication range, such as Bluetooth-enabled smart phones.An individual-based model of mobile devices is introduced and the effect of population characteristics and device behaviour on the outbreak dynamics is investigated. The model uses straight-line motion to achieve population, though it is recognised that this is a highly simplified representation of human mobility patterns. We show that the contact rate can be derived from the underlying mobility model and, through extensive simulation, that mass-action epidemic models remain applicable to worm spreading in the low density regime studied here. The model gives useful analytical expressions against which more refined simulations of worm spread can be developed and tested.     

A novel dynamic model on power failure propagation and its application to load shedding optimization

In this letter, we proposed a novel individual-based dynamical model to study failure propagation in power system. In this model, a transmission line fails with a probability related to additional load transferred by other failed lines, where load upon failure of power lines is based on global and equal redistribution. Besides, the line recovers with a certain probability, and the failure levels of lines is depicted as a probability rather than a Boolean value subject to the mean-field theory. Based on this model, the outbreak threshold of the power system was analyzed. We gave the mathematical expression of the threshold for the outbreak of power failure scale and conducted simulation experiments to verify the theoretical value. Additionally, we discussed the optimal load shedding problem to minimize the objective function related to the cost of failure and load shedding. Lastly, the numerical simulations were provided to illustrate our theoretical results.     

Analysis of HIV/AIDS Epidemic and Socioeconomic Factors in Sub-Saharan Africa

Sub-Saharan Africa has been the epicenter of the outbreak since the spread of acquired immunodeficiency syndrome (AIDS) began to be prevalent. This article proposes several regression models to investigate the relationships between the HIV/AIDS epidemic and socioeconomic factors (the gross domestic product per capita, and population density) in ten countries of Sub-Saharan Africa, for 2011–2016. The maximum likelihood method was used to estimate the unknown parameters of these models along with the Newton–Raphson procedure and Fisher scoring algorithm. Comparing these regression models, there exist significant spatiotemporal non-stationarity and auto-correlations between the HIV/AIDS epidemic and two socioeconomic factors. Based on the empirical results, we suggest that the geographically and temporally weighted Poisson autoregressive (GTWPAR) model is more suitable than other models, and has the better fitting results.     

Propagation dynamics of ring Airy Gaussian beams with cosine modulated optical vortices

We numerically investigate the propagation properties of ring Airy Gaussian beams(RAGBs) with cosine modulated optical vortices(CMOV). In comparison to the common RAGBs without any modulation, the dynamic propagation of RAGBs with CMOV exhibits a unique feature: the rings of RAGBs with CMOV will gradually shrink into several main lobes with the increase of the propagation distance. The number of lobes and the peak intensity of each lobe are determined by the factors of cosine modulated function. By designing the initial phase,we can easily change the transversal location of the peak intensity. Our results may find potential applications in optical manipulations.     

Ergodic stationary distribution of a stochastic rumor propagation model with general incidence function

In daily lives, when emergencies occur, rumors will spread widely on the internet. However, it is quite difficult for the netizens to distinguish the truth of the information. The main reasons are the uncertainty of netizens' behavior and attitude, which make the transmission rates of these information among social network groups be not fixed. In this paper, we propose a stochastic rumor propagation model with general incidence function. The model can be described by a stochastic differential equation. Applying the Khasminskii method via a suitable construction of Lyapunov function, we first prove the existence of a unique solution for the stochastic model with probability one. Then we show the existence of a unique ergodic stationary distribution of the rumor model, which exhibits the ergodicity. We also provide some numerical simulations to support our theoretical results. The numerical results give us some possible methods to control rumor propagation. Firstly, increasing noise intensity can effectively reduce rumor propagation when $\widehat{\mathcal{R}}$₀>1. That is, after rumors spread widely on social network platforms, government intervention and authoritative media coverage will interfere with netizens' opinions, thus reducing the degree of rumor propagation. Secondly, speed up the rumor refutation, intensify efforts to refute rumors, and improve the scientific quality of netizen (i.e., increase the value of β and decrease the value of α and γ), which can effectively curb the rumor propagation.     

TAGSM光束在大气湍流中传输

基于广义惠更斯－菲涅耳原理,利用部分相干光复曲率张量研究了有扭曲的各向异性高斯－谢尔模型光束在湍流大气中的传输规律.根据有扭曲的各向导性高斯-谢尔模型光束在大气湍流中传播距离z处的部分相干复曲率张量给出了光束参量的表达式和详细的数值计算结果.结果表明：大气湍流减缓了光束扭曲参量随传播距离的衰减趋势,增大了主方向上的波前曲率的峰值,而且大气湍流退化了光束的相干性,使得光束扩展严重;光源扭曲参量大小和相干性也都会影响TAGSM光束在大气湍流中传输时各个光束参量的变化规律.     

The effective hydrodynamic radius in the Stokes–Einstein relation is not a constant

Variants based on the assumption of effective hydrodynamic radius being a constant are usually adopted to test the Stokes–Einstein (SE) relation. The rationality of the assumption is examined by performing molecular dynamics simulations with the truncated Lennard-Jones-like (TLJ) model, Kob–Andersen model and ortho-terphenyl (OTP) model. The results indicate the assumption is generally not established except for special case. The effective hydrodynamic radius is observed to increase with decreasing temperature for TLJ model but is decreased for Kob–Andersen and OTP model; and which is almost a constant for TLJ particle with enough rigidity. The variant of SE relation $D\sim T/\eta $ is invalid for the three models except for the TLJ particle with enough rigidity. We propose similar inconsistency may be also existed in other liquids and the assumption should be critically evaluated when adopted to test the SE relation.