Development of an Event Stream Processing System for the Vehicle Telematics Environment

In this letter, we present an event stream processing system that can evaluate a pattern query for a data sequence with predicates. We propose a pattern query language and develop a pattern query processing system. In our system, we propose novel techniques for run‐time aggregation and negation processing and apply our system to stream data generated from vehicles to monitor unusual driving patterns.     

压力条件对不同尺寸条缝喷嘴换热的影响

以条缝喷嘴型的上下冲击式速冻机内部流场为研究对象,利用计算流体力学(Computational Fluid Dynamics,CFD)数值模拟和实地测试,对比了3种尺寸的喷嘴结构分别在不同压力(190,170,160Pa)条件下3种不同尺寸的喷嘴结构,条件下内部流场及换热特性的区别。结果表明:条缝喷嘴T_0在190Pa条件下的出口风速、努塞尔特数、均匀性比在170Pa条件下的理想,同时横流风速也低。条缝喷嘴T_1在170Pa条件下的出口风速、努塞尔特数、均匀性比在160Pa条件下的理想,但横流风速反而增加。条缝喷嘴T_2与T_0在同一入口压力下相比,只有横流风速较低。在换热强度方面,当入口压力为190Pa时,条缝喷嘴T_1所对应的钢带表面的局部努塞尔特数最大,而T_0与T_1的平均努塞尔特数相差不大。在换热均匀度方面,条缝喷嘴T_0在入口压力为190Pa时的不均匀度最低,换热最均匀。故当空气的质量流量相同时,入口压力为190Pa时所对应的条缝喷嘴T_0能更好地提升换热效率,有利于提升食品的冻结速率。     

Study on Liquid-Like Behaviors of Dense Granular Impinging Jets

Particle dynamic behaviors of dense granular impinging jets are experimentally studied by a high-speed camera and numerically simulated using discrete element method (DEM). Effects of the granular jet velocity, impinging angle, and solid fraction of the granular jet on the flow patterns and interparticle collision are investigated. Results show that as the solid fraction of the granular jet (x_p) increases, three patterns, that is, the penetrating pattern, diffuse pattern, and thin, liquid-like granular sheet display in turns. The shape and velocity of the granular sheet have been characterized and compared with the liquid sheet. An increase in the impinging angle obviously enlarges the granular sheet and decreases the sheet velocity. The flow patterns and sheet velocity are successfully predicted by DEM simulation. The simulation results further reveal that rising x_p increases the interparticle collision frequencies, which decreases interparticle collision forces and relative velocities, and consequently gives rise to the granular sheet. © 2018 American Institute of Chemical Engineers AIChE J, 65: 49–63, 2019     

撞击气流床气化炉内雾化过程中颗粒运动特性

基于实验室规模的撞击气流床气化炉,以水煤浆为原料进行气化实验,采用高温内窥镜及工业相机组成的可视化成像系统,在操作条件下,对水煤浆雾化过程进行拍摄。运用图像处理算法来识别和检测所得图像中的颗粒信息,利用颗粒示踪算法对颗粒进行轨迹测算。对颗粒的平均粒径、速度及角度进行统计分析。结果表明,喷嘴出口射流区内平均粒径主要集中在325～375 μm,相较于原煤颗粒较大;大部分颗粒速度集中在1～2 m·s^-1且运动过程中速度变化不大;大部分颗粒运动方向不随时间而变化,呈简单直线运动;颗粒轨迹呈现以喷嘴为起始点的扇形射线。     

Proper Orthogonal Decomposition and Statistical Analysis of 2D Confined Impinging Jets Chaotic Flow

Proper orthogonal decomposition (POD) is shown to be a statistical operation that identifies the main characteristics of chaotic flows and separates them into a few modes. The dynamic chaotic flow is obtained from two‐dimensional (2D) computational fluid dynamics simulations, for different Reynolds numbers, of a confined impinging jets mixer. POD enables reconstruction of the dynamic flow from a few modes that are related to coherent flow structures. The POD flow reconstruction enables a large compression of the flow data set. The decomposition of the flow field into orthogonal modes related to coherent structures provides direct insight into the mixing dynamics and scales which are not accessible from flow dynamics statistic quantities, which were introduced in the context of turbulence and are here applied to chaotic flow.     

Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times

Business processes are dynamic and change due to diverse factors. While existing approaches aim to detect drifts in the process structure, Tesseract looks for temporal drifts in activity interim times. This orthogonal view on the process extends the traditional data cube of events – case id, activities and timestamps – by a fourth dimension and improves the operational support by a visualization of temporal drifts in real-time.Insights about temporal deviations lead to an augmented awareness of imminent failures or improved service times. The detection of related structural concept drifts can be improved by early warning, as operation times of critical parts often increase before they catastrophically fail.     

A survey of outlier detection in high dimensional data streams

The rapid evolution of technology has led to the generation of high dimensional data streams in a wide range of fields, such as genomics, signal processing, and finance. The combination of the streaming scenario and high dimensionality is particularly challenging especially for the outlier detection task. This is due to the special characteristics of the data stream such as the concept drift, the limited time and space requirements, in addition to the impact of the well-known curse of dimensionality in high dimensional space. To the best of our knowledge, few studies have addressed these challenges simultaneously, and therefore detecting anomalies in this context requires a great deal of attention. The main objective of this work is to study the main approaches existing in the literature, to identify a set of comparison criteria, such as the computational cost and the interpretation of outliers, which will help us to reveal the different challenges and additional research directions associated with this problem. At the end of this study, we will draw up a summary report which summarizes the main limits identified and we will detail the different directions of research related to this issue in order to promote research for this community.     

Trapping region of impinging jets in a cross-shaped channel

This study follows our previous report (Zhang et al., Phys. Fluids, vol. 31, 2019, 034105) by describing the formation and evolution of the engulfment flow in the cross-shaped channel. First, the flow regimes were studied by planar laser induced fluorescence (PLIF). Results show the formation of a spiral vortex in the center of the chamber and the appearance of a well-mixed zone inside the spiral vortex. Second, we proposed a novel experimental method to analyze the residence time of the fluid in the chamber, and discover an unexpected trapping region inside the well-mixed zone. There is almost no fluid transport into or out of this region. Furthermore, three-dimensional numerical simulation is used to reveal the origination of this trapping region. Simulation results reveal that the fluid recirculates in the trapping region and the flow feature is caused by the bubble-type vortex breakdown.     

Biofilm early stage development in two nutrient‐rich streams with different urban impacts

The aim of this study was to describe the colonization of the biofilm during its early stages under different concentrations of nutrients and organic matter, specifically in urban streams influenced by agriculture and urbanization. We hypothesized that in a stream with higher concentrations of nutrients and organic matter, the initial biomass growth would be faster, and the changes in the structure of the community would be greater. Sterile glass substrates were placed in 2 urban streams that differed in nutrient and organic matter concentrations; samples were collected during their first week of colonization to measure total biomass, bacterial biomass, chlorophyll a, activity of the electron transfer system, and the community composition. Results show that biofilm development in both streams began within a few hours and differed under different conditions of nutrients; in the stream with a better water quality, the colonization dynamics consisted of 2 increments of bacterial biomass linked with an increase of algal biomass. In the urban stream with higher nutrient and organic matter concentrations, biofilm development was slower and consisted of a simultaneous increase of bacteria and algae, consistent with a lower electron transfer system activity. Therefore, the dynamics of the colonization process in addition to those characteristics of the fully developed biofilm could have potential applications in water monitoring of urban streams.     

Detection and removal of infrequent behavior from event streams of business processes

Process mining aims at gaining insights into business processes by analyzing the event data that is generated and recorded during process execution. The vast majority of existing process mining techniques works offline, i.e. using static, historical data, stored in event logs. Recently, the notion of online process mining has emerged, in which techniques are applied on live event streams, i.e. as the process executions unfold. Analyzing event streams allows us to gain instant insights into business processes. However, most online process mining techniques assume the input stream to be completely free of noise and other anomalous behavior. Hence, applying these techniques to real data leads to results of inferior quality. In this paper, we propose an event processor that enables us to filter out infrequent behavior from live event streams. Our experiments show that we are able to effectively filter out events from the input stream and, as such, improve online process mining results.