一种改进的射频识别数据自适应清洗算法

根据射频识别(RFID)数据特性,对RFID数据自适应清洗算法SMURF进行改进,使其能够更加高效率地处理RFID漏读数据.实验证明,改进后算法较原算法性能更加优越,准确率和稳定性有了进一步提高.     

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.     

基于匹配分布和混合高斯模型的车辆检测算法

为解决高斯混合模型GMM（Gaussian Mixture Model）在车辆检测中存在的车辆断裂等问题, 提出了一种基于匹配度分布的混合高斯车辆检测算法。该算法采用c均值聚类法计算混合高斯模型初始值, 得到初步的背景模型； 匹配度分布的提出充分考虑了背景变化的时间性和空间性的特性； 根据前几帧检测结果得到每个点的匹配度分布, 对当前图片改变背景学习的规则, 去除了干扰, 适应了背景的变化。实验结果表明, 该算法较传统的混合高斯检测方法检测率平均提高16%以上, 使背景也更稳定和准确, 克服了车辆检测的断裂以及光照突变等问题, 提高了车辆区域检测的准确性。     

A brief introduction to neutron activation analysis in China

The history, the major achievements in both methodology and applications, the current trends and future perspectives of neutron activation analysis (NAA) in China are briefly described.     

Research on Thermal Properties of Nomex Fiber and Nomex/Viscose Blended Fabric

Based on the analysis of the properties of Nomex 450 and Nomex 462,the thermal properties of Nomex 462/Lenzing Viscose Flame retardent(FR)blending materials were analyzed.It was discovered through burning test and Thermal Gravity(TG)analysis that the blended material was superior in thermal behaviors to the material made from either Nomex or Viscose FR filament,when the ratio of Nomex and Lenzing Viscose FR reached 80∶20,and excellent thermal properties were achieved with the value of Limiting Oxygen Index(...     

Modeling and Experimental Study of PEM Fuel Cell Transient Response for Automotive Applications

This paper presents an analysis of the dynamic response of a low pressure proton exchange membrane (PEM) fuel cell stack to step changes in load, which are characteristic of automotive fuel cell system applications. The goal is a better understanding of the electrical and electrochemical processes when accounting for the characteristic cell voltage response during transients. The analysis and experiment are based on a low pressure 5 kW proton exchange membrane fuel cell (PEMFC) stack, which is similar to those used in several of Tsinghua's fuel cell buses. The experimental results provide an effective improvement reference for the power train control scheme of the fuel cell buses in Olympic demonstration in Beijing 2008.     

The RCT approach for cell coverage prediction (II): Experiment and early results

We study on the implementation flow of the radio computerized tomography (RCT) prediction method. A case in real cellular mobile radio (CMR) system together with the prediction results are also presented. As shown by the results, the RCT prediction method is marked for its convenience and rapidity, as well as its relative high precision even when the prediction procedure is highly simplified. Since it is developed according to the characteristics of wireless communication environments of our country and has concurrently merits from both statistical and deterministic prediction models, the RCT prediction method is in good agreement with engineering practices in cellular mobile communication in cities at home. Optimized by combining with other techniques, further improvement could be achieved in the stability and precision of the RCT prediction method which now serves as the core part of a software tool for commercial use in CMR system analysis and optimization. Biography: Yu Sheng-bing (1974-), male, Ph. D candidate, research interest: theory analysis and application development of radio propagation in wireless communication systems.     

分光光度法研究邻菲罗啉亚铁与Fenton体系的作用

建立一种以Fe（phen）3^2＋为显色剂，用分光光度法测定Fenton反应产生的·OH的新方法．该方法是在pH=3．0条件下，利用Fenton反应所产生的羟自由基与Fe（phen）3^2＋作用后使吸光度（A）降低，在510nm处用紫外可见分光光度计测定其A值变化，可间接测定羟自由基的生成量．通过测定条件的研究，探讨了最佳实验条件，以及在最佳条件下进一步探讨抗氧化性药物苯甲酸对羟自由基的清除率的量效关系．该方法稳定，可作为一种简便的筛选抗氧化剂的方法．