Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

云南壮剧民间土戏形成与发展过程的二次文献分析——国家级非物质文化遗产·云南壮剧保护研究（之二）

以《云南壮剧史》为据,运用二次文献分析的方法对云南壮剧民间土戏形成与发展的历史过程进行专业分析,发现民间土戏从清朝中晚期形成至今,其发展轨迹呈现＂山＂字形状,具有曲折波动的特点,尤其是历史上的两次重创为云南壮剧民间土戏的后续发展埋下了诸多隐患,出现了目前发展缓慢、传承困境等问题。如何应对云南壮剧民间土戏传承与可持续发展的困境问题,笔者认为应同时兼顾其自身的专业建设和文化空间的保护,二者缺一不可。     

新型防腐喷涂系统优化设计

防腐喷涂系统的设计主要用于石油管道焊缝处理机器人中，对喷涂系统整体结构进行了设计，找到了系统要实现设计目的所需要解决的关键问题，从而通过建立数学模型来对系统的结构进行优化。为降低压力损失进行优化，采用Solidworks／Flow Simulation对气缸内部通道进行流体分析。     

当代大学生意志品质的现状与应对

意志品质主要包括自觉性、果断性、坚持性和自制性等方面。对大学生来说，意志品质越是优良，对其个人的成长越是能够起着积极的促进作用。针对目前高校大学生意志品质的现状进行了分析总结，探讨了意志品质作为非智力因素的作用，并针对问题，提出了具体的应对策略。     

国内外羊毛西装面料加工性能的比较

选择35种国内外羊毛西装面料,利用FAST仪对其加工性能进行测试,运用主成分分析方法对其差距与缝纫质量进行比较.结果表明,国内外毛西装面料的主要差异是可成型性,其他依次为湿膨胀性、厚重性、松驰回缩性等.这些差距表明国外毛西装面料加工时制作难度小,尺寸稳定性好,缝纫缩皱较轻,而国内面料制作难度大,缝纫缩皱严重.     

基于WEB的实验教学管理系统的设计

针对开放性实验教学模式中实验开放管理这一难点,开发了基于Web的实验教学管理系统.文章介绍了系统的架构和主要功能,并结合物理实验课程详细阐述了必修实验和选修实验两种实验类型所采取的三种不同实验预约管理方法的设计思想.同时介绍了实验材料管理和成绩管理.     

化妆品中25种激素的检测方法

采用液相色谱-串联质谱法对化妆品中25种违禁激素进行了测定,探求了多种激素同时测定的条件.研究结果表明,样品通过饱和氯化钠溶液分散,乙腈从分散液中提取激素类药物,沉淀大分子物质后经固相萃取小柱净化,平均回收率为70.0%～110.0%,相对标准偏差2.1%～18.8%（n=10）,检测低限均为0.02mg/kg.     

基于数字滤波ZPW-2000R接收机交流阻抗检测

针对ZPW-2000R型移频自动闭塞系统接收机生产中的质量测试,介绍了系统对于关键测试项目—接收机交流输入阻抗的测试过程与方法.系统采用高速DSP芯片TMS320F2812作为主控芯片,由AD9833信号发生器模块产生相应测试信号,由F2812内部AD采集待测信号,通过校正算法和数字滤波器进行交流数据处理.通过分压原理间接测得接收机的交流输入阻抗.经实验验证,系统测量交流输入阻抗时效率高、测量结果准确,具有较高的实用价值和推广意义.     

广播媒体内容资产管理模式的构建与发展

媒体内容资产管理的重要性在传媒企业发展过程中日益突出。针对广播媒体内容信息管理体系与产业发展的关联,提出了以"融入与拓展"为出发点的信息系统建设框架和发展模型,对系统内容建设、运行方式和管理机制进行了剖析,并提出相应的对策与建议。     

Testing for the usefulness of forecasts

Ashley (Journal of Forecasting 1983; 2 (3): 211–223) proposes a criterion (known as Ashley's index) to judge whether the external macroeconomic variables are well forecast to serve as explanatory variables in forecasting models, which is crucial for policy makers. In this article, we try to extend Ashley's work by providing three testing procedures, including a ratio‐based test, a difference‐based test, and the Bayesian approach. The Bayesian approach has the advantage of allowing the flexibility of adapting all possible information content within a decision‐making environment such as the change of variable's definition due to the evolving system of national accounts. We demonstrate the proposed methods by applying six macroeconomic forecasts in the Survey of Professional Forecasters. Researchers or practitioners can thus formally test whether the external information is helpful. Copyright © 2010 John Wiley & Sons, Ltd.