音乐物联网的设计与研究

音乐物联网(Internet of musical things,IoMusT)是一个涉及多学科、多专业的综合工程,以往的研究都是单一的从某一个方面着手,缺乏一个统一的研究框架,完整的研究体系还不健全。研究重点是从工程的角度定义音乐事件,并结合当下互联网各个环节的技术特性,从工程的角度定义音乐事件,构造一个小范围的IoMusT生态系统,从软硬件方面测试IoMusT性能,进而验证IoMusT设计架构效。     

An Overview of Control Charts for High‐quality Processes

Major difficulties in the study of high‐quality processes with traditional process monitoring techniques are a high false alarm rate and a negative lower control limit. The purpose of time‐between‐events control charts is to overcome existing problems in the high‐quality process monitoring setup. Time‐between‐events charts detect an out‐of‐control situation without great loss of sensitivity as compared with existing charts. High‐quality control charts gained much attention over the last decade because of the technological revolution. This article is dedicated to providing an overview of recent research and presenting it in a unifying framework. To summarize results and draw a precise conclusion from the statistical point of view, cross‐tabulations are also given in this article. Copyright © 2016 John Wiley & Sons, Ltd.     

MODIS imagery of turbid plumes in San Diego coastal waters during rainstorm events

Data of normalized water-leaving radiance, nLw, obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite at spatial resolution of 250 m (band 1 centered at 645 nm) and 500 m (band 4 at 555 nm) are used to study turbid plumes in coastal waters of southern California during rainstorm events in winter of 2004-2005. Our study area includes San Diego coastal waters, which extend approximately 25 km offshore between Point Loma and 10 km south of the US-Mexican border. These waters are influenced by terrigenous input of particulate and dissolved materials from San Diego and Tijuana watersheds and non-point sources along the shore. Optimum threshold values of satellite-derived normalized water-leaving radiances at both wavebands were established for distinguishing the plume from ambient ocean waters. These threshold values were determined by searching for a maximum correlation between the estimates of satellite-derived plume area calculated using a broad range of nLw values and the environmental variables characterizing rainfall, river discharge, wind, and tides. A correlation analysis involving the amount of precipitated water accumulated during a storm event over the San Diego and Tijuana watersheds was selected as the basis for final determinations of the optimum threshold nLw_thr and subsequent calculations of the plume area. By applying this method to a sequence of MODIS imagery, we demonstrate the spatial extent and evolution of the plume during rainstorm events under various conditions of precipitation, river discharge, wind forcing, and coastal currents.     

基于稀有事件仿真的商业银行IT操作风险评估研究

系统仿真是风险评价的一种重要手段,针对商业银行IT操作风险预警问题,提出了一种基于稀有事件仿真的IT操作风险评估方法。采用商业银行IT操作风险的概率作为衡量IT操作风险高低的标准,构造基于稀有事件的商业银行IT操作风险识别模型,利用交叉熵方法构建了一种稀有事件仿真的有效算法,并由此估计出发生损失的概率。实证分析结果表明,模型对商业银行IT操作风险具有很强的识别能力,从而提供了一个风险预警的新视角。     

基于LS-BSVR的旅游地理经济预测应用

基于改进的LS-BSVR(least squares B support vector regression)算法对旅游地理经济进行分析预测。提出了时政指数、景区景点分布指数概念,设计了时政指数、景区景点分布指数,并应用于旅游地理经济进行分析预测。设计了用于分析预测的数据模式。数值实验和预测平台结果表明,改进的LS-BSVR算法和设计的旅游地理经济数据指标以及数据模式是有效的。     

嵌入式Linux内核运行态性能可视化分析方法的设计与实现

介绍了嵌入式Linux操作系统下的一种内核运行态可视化性能分析方法.它采用Linux的字符设备驱动技术,Linux内核源代码内的探针嵌入以及内核补丁技术,基于Socket的Linux端与Windows端的TCP通信技术和Windows端的图形化显示技术,以模块化方式实现了在Windows宿主操作系统下对Linux操作系统运行时系统事件状态变化的图形化地观察手段,从而辅助软件开发人员方便地去诊断和解决嵌入式Linux系统中存在的调度问题、性能问题以及定时问题等.     

一种面向突发事件的文本语料自动标注方法

事件语料库是研究语义Web中事件知识的抽取、表示、推理和挖掘的基础和关键技术之一。该文以事件作为文本知识单元,在LTP分析的基础上,用序列模式挖掘算法PrefixSpan从现有的小规模语料库中挖掘事件要素的词性规则等,用同义词词林(扩展版)对触发词表进行了扩充,结合自定义的事件要素词典,采用多遍过滤、逐遍完善的思想提出一种针对大规模突发事件语料库构建的自动标注方法,在实验部分不仅与人工标注做了对比,同时与Stanford CoreNLP NER进行了对比,实验效果理想。     

VB中通信控件的设置与应用

介绍了利用MSComm控件进行通信时串行口的打开与关闭,缓冲区的设置和数据的收发形式,同时也介绍了握手协议和通信时错误信号的捕获。     

混合监测技术在并行与分布式性能监测中的应用

主要介绍了混合监测技术在并行与分布式系统性能分析评价中的应用。分析比较了常用的几种监测技术,给出了各自的优缺点,介绍了混合监测中的事件的定义,自动装备的过程。事件的采集和分析这向个关键步骤,提出装备的层交化。最后提出了混合监测中会遇到一些问题并给出了相应的解决方法。     

Timestamping messages and events in a distributed system using synchronous communication

Determining order relationship between events of a distributed computation is a fundamental problem in distributed systems which has applications in many areas including debugging, visualization, checkpointing and recovery. Fidge/Mattern’s vector-clock mechanism captures the order relationship using a vector of size N in a system consisting of N processes. As a result, it incurs message and space overhead of N integers. Many distributed applications use synchronous messages for communication. It is therefore natural to ask whether it is possible to reduce the timestamping overhead for such applications. In this paper, we present a new approach for timestamping messages and events of a synchronously ordered computation, that is, when processes communicate using synchronous messages. Our approach depends on decomposing edges in the communication topology into mutually disjoint edge groups such that each edge group either forms a star or a triangle. We show that, to accurately capture the order relationship between synchronous messages, it is sufficient to use one component per edge group in the vector instead of one component per process. Timestamps for events are only slightly bigger than timestamps for messages. Many common communication topologies such as ring, grid and hypercube can be decomposed into edge groups, resulting in almost 50% improvement in both space and communication overheads. We prove that the problem of computing an optimal edge decomposition of a communication topology is NP-complete in general. We also present a heuristic algorithm for computing an edge decomposition whose size is within a factor of two of the optimal. We prove that, in the worst case, it is not possible to timestamp messages of a synchronously ordered computation using a vector containing fewer than components when N ≥ 2. Finally, we show that messages in a synchronously ordered computation can always be timestamped in an offline manner using a vector of size at most . An earlier version of this paper appeared in 2002 Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS). The author V. K. Garg was supported in part by the NSF Grants ECS-9907213, CCR-9988225, an Engineering Foundation Fellowship. This work was done while the author C. Skawratananond was a Ph.D. student at the University of Texas at Austin.