An Algorithm for Mining Gradual Moving Object Clusters Pattern From Trajectory Streams

The discovery of gradual moving object clusters pattern from trajectory streams allows characterizing movement behavior in real time environment,which leverages new applications and services.Since the trajectory streams is rapidly evolving,continuously created and cannot be stored indefinitely in memory,the existing approaches designed on static trajectory datasets are not suitable for discovering gradual moving object clusters pattern from trajectory streams.This paper proposes a novel algorithm of gradual moving object clusters pattern discovery from trajectory streams using sliding window models.By processing the trajectory data in current window,the mining algorithm can capture the trend and evolution of moving object clusters pattern.Firstly,the density peaks clustering algorithm is exploited to identify clusters of different snapshots.The stable relationship between relatively few moving objects is used to improve the clustering efficiency.Then,by intersecting clusters from different snapshots,the gradual moving object clusters pattern is updated.The relationship of clusters between adjacent snapshots and the gradual property are utilized to accelerate updating process.Finally,experiment results on two real datasets demonstrate that our algorithm is effective and efficient.

What Causes the Springtime Tropospheric Ozone Maximum over Northeast Asia?

Scientists have long debated the relative importance of tropospheric photochemical production versus stratospheric influx as causes of the springtime tropospheric ozone maximum over northern mid-latitudes. This paper investigates whether or not stratospheric intrusion and photochemistry play a significant role in the springtime ozone maximum over Northeast Asia, where ozone measurements are sparse. We examine how tropospheric ozone seasonalities over Naha （26°N, 128°E）, Kagoshima （31°N, 131°E）, and Pohang （36°N, 129°E）, which are located on the same meridional line, are related to the timing and location of the jet stream. The ozone seasonality shows a gradual increase from January to the maximum ozone month, which corresponds to April at Naha, May at Kagoshima, and June at Pohang. In order to examine the occurrence of stratospheric intrusion, we analyze a correlation between jet stream activity and tropospheric ozone seasonality. From these analyses, we did not find any favorable evidence supporting the hypothesis that the springtime enhancement may result from stratospheric intrusion. According to trajectory analysis for vertical and horizontal origins of the airmass, a gradual increasing tendency in ozone amounts from January until the onset of monsoon was similar to the increasing ozone formation tendency from winter to spring over China's Mainland, which has been observed during the build-up of tropospheric ozone over Central Europe in the winter-spring transition period due to photochemistry. Overall, the analyses suggest that photochemistry is the most important contributor to observed ozone seasonality over Northeast Asia.

Fluid mechanics of ventilation system generated by buoyancy and momentum sources and experiments research

This paper presents fluid mechanics of ventilation system formed by the momentum source and the buoyancy source,which investigates inter-action between the plume and the non-isothermal air jet since buoyancy source is produced by the plume and momentum source is generated by the air jet,respectively. The interaction is discussed by a mathematical model,an idealized situation of the plume rising from a point heat source of buoyancy alone-in particular the initial momentum flux at the source is zero. Furthermore,the paper discusses the effects of the parameters such as strength of source,air-flow volume and air-flow velocity used in the mathematical-physical model. Considering the effect of the plume generated by the indoor heat source,one expression of trajectory of the non-isothermal air jet produced by jet diffuser is deduced. And field-experiment has also been carried out to illustrate the effect on flowing-action of the air jet and validate the theoretical work. It can be concluded that the heat sources do have effect on the flowing-action of the air jet,and the effect mainly depends on the interaction produced by the plume and the air jet. The results show that the thermal buoyant effect of plumes on the air jet should be taken into account if the indoor heat sources are large enough. Numerical simulation is conducted and coincides with the experimental results as well.

Online clustering of streaming trajectories

With the increasing availability of modern mobile devices and location acquisition technologies, massive trajectory data of moving objects are collected continuously in a streaming manner. Clustering streaming trajectories facilitates finding the representative paths or common moving trends shared by different objects in real time. Although data stream clustering has been studied extensively in the past decade, little effort has been devoted to dealing with streaming trajectories. The main challenge lies in the strict space and time complexities of processing the continuously arriving trajectory data, combined with the difficulty of concept drift. To address this issue, we present two novel synopsis structures to extract the clustering characteristics of trajectories, and develop an incremental algorithm for the online clustering of streaming trajectories （called OCluST）. It contains a micro-clustering component to cluster and summarize the most recent sets of trajectory line segments at each time instant, and a macro-clustering component to build large macro-clusters based on micro-clusters over a specified time horizon. Finally, we conduct extensive experiments on four real data sets to evaluate the effectiveness and efficiency of OCluST, and compare it with other congeneric algorithms. Experimental results show that OCluST can achieve superior performance in clustering streaming trajectories.