Proposal of a simple model for the characterization of aerosols in relation to the dominant air masses

In this work, we present a simple model that allows us to easily obtain the character of the dominant air mass for any location in the Northern Hemisphere at any time. Specifically, in this article the model has been tested at Valencia, Spain, for the years from 2006 to 2009. The classification of the air masses is performed analysing their trajectories over pre-defined source regions in the Northern Hemisphere. Daily trajectories were simulated by the hybrid single-particle Lagrangian integrated trajectory model (HYSPLIT) and then classified by our model. In order to verify our classification results, those cases identified as African were compared with the Saharan dust intrusions reported for Valencia by the Ministerio de Medio Ambiente y Medio Rural y Marino (MARM) in collaboration with the Centro Superior de Investigaciones Científicas (CSIC). The model we present in this article can be applied in the selection of an optimum aerosol model for the atmospheric correction of remote sensing products.     

Desert dust aerosols observed in a tropical humid city: a case study over Hong Kong

Observations from the AErosol RObotic NETwork (AERONET) sunphotometers, MODerate resolution Imaging Spectroradiometer (MODIS) satellite images, back-trajectory modelling and ‘in-situ’ PM10 measurements in Hong Kong confirmed that two dust storms on 16–17 April 2006 and 27–30 April 2009, with source areas in northwest China, affected the city. The impacts of the dust on the air quality of Hong Kong were quantified using aerosol optical properties from AERONET data and local PM10 (particle size less than 10 μm) concentrations. Combined analysis of back trajectories and the microphysical properties of the dust aerosols from AERONET inversion data suggest that the dust particulates are sometimes associated with industrial chemicals on arrival in Hong Kong. This is the first remote-sensing study to observe the presence and characteristics of Asian dust carried into the humid tropical region of south China.     

Characterising and understanding emission sources using bivariate polar plots and k-means clustering

This paper develops the idea of bivariate polar plots as a method for source detection and characterisation. Bivariate polar plots provide a graphical method for showing the joint wind speed, wind direction dependence of air pollutant concentrations. Bivariate polar plots provide an effective graphical means of discriminating different source types and characteristics. In the current work we apply k-means clustering techniques directly to bivariate polar plots to identify and group similar features. The technique is analogous to clustering applied to back trajectories at the regional scale. When applied to data from a monitoring site with high source complexity it is shown that the technique is able to identify important clusters in ambient monitoring data that additional analysis shows to exhibit different source characteristics. Importantly, this paper links identified clusters to known emission characteristics to confirm the inferences made in the analysis. The approaches developed should have wide application to the analysis of air pollution monitoring data and have been made freely available as part of the openair R package.     

Crowd behaviors analysis and abnormal detection based on surveillance data

Crowd analysis and abnormal trajectories detection are hot topics in computer vision and pattern recognition. As more and more video monitoring equipments are installed in public places for public security and management, researches become urgent to learn the crowd behavior patterns through the trajectories obtained by the intelligent video surveillance technology. In this paper, the FCM (Fuzzy c-means) algorithm is adopted to cluster the source points and sink points of trajectories that are deemed as critical points into several groups, and then the trajectory clusters can be acquired. The feature information statistical histogram for each trajectory cluster which contains the motion information will be built after refining them with Hausdorff distances. Eventually, the local motion coherence between test trajectories and refined trajectory clusters will be used to judge whether they are abnormal.     

METEX – A flexible tool for air trajectory calculation

Air trajectories are often used to study airflow pattern and source–receptor relation in environmental research. We developed the METeorological data EXplorer (METEX) for trajectory calculation with an emphasis on flexibility and ease-of-use.     

Behavior of a micron-sized air bubble in operating FDBs using the discrete phase modeling method

This paper investigates the motion of a micron-sized air bubble in the operating fluid dynamic bearings (FDBs) of a spindle motor in a computer hard disk drive. The flow field of FDBs is calculated by solving the Navier–Stokes equation and the continuity equation. The two-phase flow in the air-oil interface is simultaneously solved by using the finite volume method and the volume of fluid (VOF) method. We then analyze the motion of a micron-sized air bubble by applying the discrete phase modeling (DPM) method to the calculated flow field of FDBs. The motion of a micron-sized air bubble determined using the DPM method is verified by comparison with the trajectory of the micron-sized air bubble determined using the VOF method. The trajectories of a micron-sized air bubble with different initial positions in the FDBs are discussed.     

基于SIMULINK的空空导弹无线电修正通道仿真

中远程空对空导弹中制导阶段通常采用惯导＋指令制导复合制导方式.在某型空对空导弹研制中,要在不同攻击弹道的情况下对无线电数据链路的传输情况进行仿真,以分析导弹无线电修正通道的工作效能,确定改进方案,计算导弹的最大攻击距离.本文基于Simulink建立了导弹、载机和目标三者空中运动平台,并在此平台中建立了无线电修正通道数据链路.最后,给出了无线电修正通道数据链路中导弹的无线电数据链路与载机-导弹距离、导弹姿态角和导弹弹道之间的关系的数字仿真结果.     

舰载机拦阻系统动力学建模与控制

提出了一种液压吸能和滑轮机构相结合的舰载机拦阻系统模型,然后建立了计入拦阻索弹性的拦阻系统非线性动力学模型．基于高斯伪谱方法获得了舰载机拦阻过程的最优控制轨迹,并应用线性二次型最优控制跟踪该最优轨迹,数值结果验证了该方法的可行性,最后讨论了空气阻力与甲板摩擦力对控制过程的影响．     

Modeling of indoor airflow and dispersion of aerosols using immersed boundary and random flow generation methods

Numerical modeling of environmental flows involves complex geometry, moving bodies, multi-phase flow, and buoyant jet effects. An in-house CFD code has been developed using finite volume and immersed boundary methods. The transport and dispersion of virus-laden aerosols in a ventilated room is investigated by this numerical code. The uniqueness of this numerical code is that it can efficiently compute small-scale turbulent flow in which most commercial CFD software will suffer from large numerical error. Random flow generation (RFG) [33] is an ideal choice for small-scale turbulence for low-Reynolds number flow in a ventilated room. In addition, Lagrangian stochastic (LS) walk model is applied to directly compute probability density function (PDF) of aerosols and estimate the risk factor of aerosol dispersion from a point source. The present study focuses on aerosols with small diameter (<10 μm) in which the effects of evaporation on the dispersion of aerosols could be neglected. Different location of aerosol sources and a typical ventilation layout are discussed in detail. The numerical results with PDF yield more useful quantitative information to assess the risk area of virus transport in a ventilated room than that shown in random trajectories of particles as widely reported in the literature. This study provides valuable information for ventilation control strategies with respiratory protection, such as enhanced air exchange, air filtration rate, and improved airflow patterns to reduce indoor infection risk via airborne virus laden droplets.     

Dynamic classification of ballistic missiles using neural networks and hidden Markov models

This paper addresses dynamic classification of different ranges of ballistic missiles (BM) for air defense application based on kinematic attributes acquired by radars for taking appropriate measures to intercept them. The problem of dynamic classification is formulated using real-time neural network (RTNN) and hidden Markov model (HMM). The idea behind these algorithms is to calculate the output in one pass rather than training and computing over large number of iterations. Besides, to meet the conflicting requirements of classifying small as well as long-range trajectories, we are also proposing a formulation for partitioning the trajectory by using moving window concept. This concept allows us to use parameters in localized frame which helps in handling wide-range of trajectories to fit into the same network. These algorithms are evaluated using the simulated data generated from 6 degree-of-freedom (6DOF) mathematical model, which models missile trajectories. Experimental results show that both the networks are classifying above 95% with real-time neural network outperforming HMM in terms of time of computation on same data. The small classification time enables the use of real-time classification neural network in complex scenario of multi-radar, multi-target engagement by interceptor missiles. To the best of our knowledge this is the first time an attempt is made to classify ballistic missiles using RTNN and HMM.     

Model-based iterative learning control strategies for precise trajectory tracking in gasoline engines

In this paper trajectory tracking algorithms for gasoline engines are devised. Specifically, precise reference tracking in engine speed and air-to-fuel ratio is enabled while satisfying initial and final conditions on the center of combustion. Such a tracking of multiple reference trajectories requires a coordinated control action for the air path, the fuel path, and the ignition timing actuators. Combining a dedicated feedforward and feedback controller structure and multivariable model-based norm-optimal parallel iterative learning control strategies, feedforward control trajectories are generated that enable a precise tracking of desired reference trajectories. Experimental results focusing on the termination of the catalyst heating mode show the effectiveness of the proposed methodology, resulting in a control error reduction above 85%.     

Parallel Implementation of a Lagrangian Stochastic Model for Pollutant Dispersion

Lagrangian dispersion models have shown to be effective and reliable tools for simulating the airborne pollutant dispersion. However, the main drawback for their use as regulatory models is the associated high computational costs. Consequently, in this paper a parallel version of a Lagrangian particle model—LAMBDA—is developed using the MPI message passing communication library. Performance tests were executed in a distributed memory parallel machine, a multicomputer based on IA-32 architecture. Portions of the pollutant in the air emitted from its source are simulated as fictitious particles whose trajectories evolve under stochastic forcing. This yields independent evolution equations for each particle of the model that can be computed by a different processor in a parallel implementation. Speed-up results show that the parallel implementation is suitable for the used architecture.     

基于MEBN的大型舰船舰面保障作业检测

大型舰船舰面保障作业指驻扎于大型舰船的飞机的一次出动过程中,发生于舰面的针对飞机的出动回收准备活动（如飞机调运、物资转运、飞机滑跑起飞等）。基于舰面监控视频检测舰面保障作业,利于分析并提高保障作业效率。在大型舰船携带的机群出动过程中,各飞机的保障作业同时进行,涉及数以百计的操作员、高级器械及设施设备的协作。针对大型舰船舰面保障作业检测问题中,同一视频场景内同时发生多个保障作业且参与者位置交叉、重叠的难点,提出一种基于多实体贝叶斯网络的大型舰船舰面保障作业检测技术。该技术假设在视频数据预处理阶段获取视频中各目标物清晰连贯的运动轨迹;在保障作业检测阶段,输入目标物轨迹,先基于带约束的轨迹自动聚类算法,自动计算聚类个数,并将参与同一保障作业的轨迹聚至同一类;在各聚类内,采用基于MEBN的保障作业识别技术,推断保障作业类型。大型舰船舰面监控视频数据集上的实验表明,该方法对同一视频场景中同时发生的且参与者位置交叉的舰面保障作业具有良好的检测效果。     

Estimating and source analysis of surface PM2.5 concentration in the Beijing–Tianjin–Hebei region based on MODIS data and air trajectories

Particulate matter (PM) with an aerodynamic diameter of <2.5 μm (PM_2.5) has become the primary air pollutant in most major cities in China. Some studies have indicated that there is a positive correlation between the aerosol optical thickness (AOT) and surface-level PM_2.5 concentration. In order to estimate PM_2.5 concentration over large areas, a model relating the concentration of PM_2.5 and AOT has been established. The scale height of aerosol and relative humidity as well as the effect of surface temperature and wind velocity were introduced to enhance the model. 2013 full year Moderate Resolution Imaging Spectroradiometer (MODIS) AOT data and ground measurements of the PM_2.5 concentration in the Beijing–Tianjin–Hebei region were used to fit a seasonal multivariate linear equation relating PM_2.5 concentration and AOT, and the accuracy of the model has been determined. When comparing MODIS-estimated PM_2.5 with the measurements from ground monitoring stations during spring, summer, autumn and winter, we found the R² values were 0.45, 0.45, 0.37, and 0.31, respectively. Based on this model, the spatial distribution of PM_2.5 concentration during four typical haze events sampled by seasons was derived, and displayed with the backward air trajectories calculated using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. We undertook a preliminary analysis about the source of surface-level PMs and the process of its accumulation and dispersion during the haze episodes by analysing the effect of terrain and topography in the specific location of the Beijing–Tianjin–Hebei region. The spatial distribution of the PM_2.5 concentration showed that the high value region was generally in the southeast of the study area, which approximately overlapped an area of lower vegetation coverage, and the temporal variation of PM_2.5 concentration indicated that the air pollution was more severe during winter and spring than summer and autumn. The results of the analysis of backward air trajectories suggested that the hazy weather in the Beijing–Tianjin–Hebei region was mainly caused by unfavourable terrain and weather conditions.     

An observation tool to study air traffic control and flightdeck collaboration

The complex systems of the flightdeck (FD) and the Air Traffic Control Centre (ATC) are characterised by numerous concurrently operating and interacting communication channels between people and between people and machines/computer systems. This paper describes work in support of investigating the impact of changes to technologies and responsibilities within this system with respect to human factors. It focuses primarily on the introduction of datalink (text-based communication rather than traditional radio communication) and the move towards freeflight (pilot-mediated air traffic control). Air traffic management investigations have outlined these specific changes as strategies to enable further increases in the volume of air traffic. A systems approach was taken and field studies were conducted. Small numbers of domain experts such as air traffic controllers (ATCOs) were involved in the field-based observations of how people interact with systems and each other. This paper summarises the overall research approach taken and then specifically reports on the field-based observations including the justification, development, and findings of the observation tool used. The observation tool examined information propagation through the air traffic control-flightdeck (ATC-FD) system, and resulted in models of possible information trajectories through the system.     

Searching for similar trajectories in spatial networks

In several applications, data objects move on pre-defined spatial networks such as road segments, railways, and invisible air routes. Many of these objects exhibit similarity with respect to their traversed paths, and therefore two objects can be correlated based on their motion similarity. Useful information can be retrieved from these correlations and this knowledge can be used to define similarity classes. In this paper, we study similarity search for moving object trajectories in spatial networks. The problem poses some important challenges, since it is quite different from the case where objects are allowed to move freely in any direction without motion restrictions. New similarity measures should be employed to express similarity between two trajectories that do not necessarily share any common sub-path. We define new similarity measures based on spatial and temporal characteristics of trajectories, such that the notion of similarity in space and time is well expressed, and moreover they satisfy the metric properties. In addition, we demonstrate that similarity range queries in trajectories are efficiently supported by utilizing metric-based access methods, such as M-trees.     

Analysis of a manipulator in relation to collision between a link and an object

In this article, equations of motion of a manipulator are derived after consideration of the characteristics of the driving source. By considering a collision between a link and an object, and considering the active motion to absorb the kinetic energy of the object, the trajectories for saving energy are calculated by the iterative dynamic programming (IDP) method. The dynamic characteristics of manipulator control based on the trajectory for saving energy are also analyzed theoretically and investigated experimentally.     

Synergy of satellite-based aerosol optical thickness analysis and trajectory statistics for determination of aerosol source regions

ABSTRACT

Over 10 years of satellite-based remote sensing data with trajectory statistics are used to determine sources of air mass related to different aerosol types. Aerosol typing is based on analysis of sun-photometer data and then extended in time with the use of satellite data. Supplemental analysis of Gaussian distributions of aerosol optical thickness changes during transport, based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, is performed. It allows for differentiating between primary and secondary aerosol sources as well as to prove air mass source as a source of aerosol. It appears that source regions of air mass and aerosols’ sources are collocated in most cases. For western advection from Germany, the most probable aerosol sources are located between air mass source regions and the receptors. These are mostly associated with the industrial/urbanized aerosol type. Additionally, aerosols from intermittent and strong episodes of biomass burning to the east of the Polish border are found to originate from sources located closer to the receptors than backward trajectory analysis alone suggested.     

基于轮廓系数的参数无关空中交通轨迹聚类方法

为消除专家经验的主观性、避免依赖轨迹特征并且减轻实验调参的负担，提出一种基于轮廓系数的参数无关聚类分析（PICBASIC）算法。首先，比较了现有基于欧氏距离的航迹配对方法，并且建立基于动态时间弯曲（DWT）距离和高斯核函数的轨迹相似度计算模型；其次，利用谱聚类对空中交通轨迹进行聚类划分；最后，提出一种基于轮廓系数的最佳簇数寻优方法，并且其具有对聚类结果量化评价功能。利用真实进场轨迹进行实验验证，PICBASIC判断将28L跑道的365条轨迹聚为5个簇，28R跑道的530条轨迹聚为6个簇时聚类质量最佳，平均轮廓系数分别为0.8099和0.8056。相同实验数据条件下，PICBASIC与MeanShift聚类的平均轮廓系数差异率分别为-1.23%和0.19%。实验结果表明：PICBASIC包容轨迹的速度和长度差异，全程无需人工指导或实验调参，而且能够筛除异常轨迹对聚类质量的不利影响。     

Virtual motion camouflage based phantom track generation through cooperative electronic combat air vehicles

As an example of complex cooperative missions, coherent phantom track generation through controlling multiple electronic combat air vehicles is currently an area of great interest to the defense agency for the purpose of deceiving a radar network. However, it has been a challenge to design the optimal or even feasible coherent trajectories for this type of problem due to the high dimensionality and the strong coupling between the phantom and actual vehicles. This problem becomes even more difficult to solve when realistic kinematic, dynamics, and geometric constraints in a three-degree-of-freedom formation have to be considered. This paper describes how an interesting bio-inspired motion strategy can be used to design real-time trajectories for a (1) feasible constant speed coherent mission, (2) maximum-duration constant speed coherent mission, and (3) optimal trajectory mission for general cases. The proposed method will dramatically reduce the dimension of the problem and thus real-time optimal trajectory design can be achieved. Also the fact that fewer equality constraints are involved in solving the formulated nonlinear programming will make the convergence a lot easier.