横向各向同性介质中的初至波旅行时计算

本文直接采用Thomsen导出的横向各向同性介质中的相速度、群角与相角、群速度与相速度的精确函数关系,提出了一种新的具有任意各向异性强度的横向各向同性介质中的初至波旅行时计算方法,它不同于Faria等人给出的采用群速度近似公式(Byun)的仅适应弱各向异性的初至波旅行时计算方法。该新算法在计算具有任意各向异性强度的横向各向同性介质中的初至波旅行时时,并不显著地增大计算时间。分析对比由新算法得到的初至波旅行时的等值线图和由交错网格有限差分波场模拟得到的波场快照表明,无论是对弱各向异性还是对强弱各向异性,新算法都具有较高的精度;随着各向异性强度的增大,新算法的计算结果与采用近似公式计算结果的差值也随之增大。     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.     

Synthesis, Characterization and Crystal Structure of Quaternary Complex of Gadolinium （Ⅲ）

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A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

在系统可编程通用数字开关ispGDS14的原理及应用

介绍了Lattice公司生产的在系统可编程通用数字开关芯片ispGDS14的内部结构和性能特点，并通过实例说明了在GDS开发环境下对ispGDS14进行编程的方法。     

基于嵌入式Linux的远程数据采集系统

以嵌入式微控制器为核心,将传感器网络收集来的数据通过无线电发射机发送到远程接收机,从而实现远程数据采集.系统的优势是充分利用了短波无线链路资源,适合于工作在无人区等场合.以ARM7为控制器,功耗小,性能稳定,维护方便;通信方式采用串口通信,连接线少,实现相对简单.系统设计主要应用嵌入式μCLinux系统设计、无线电发射、调制解调器等方面的知识,文中给出了调制解调器拨号协议、系统原理和软件流程等.     

基于复数主成分分析的磁共振波谱信号衰减系数的自动校正

衰减系数的校正是磁共振波谱信号处理和分析过程中的一个关键难题。本文基于复数主成分分析，提出了一种自动的磁共振波谱衰减系数的校正方法，较成功地解决了这个难点问题。文中的模拟数据及其实现结果充分验证了该方法的有效性。     

基于聚类算法实现信号盲分类

本文解决了信号处理、工业控制等领域存在的非平稳信号盲分类问题。在聚类中广泛应用的K-Means算法及其它基于中心的聚类算法有两个共同的缺陷-需要预先确定类数目且随机初始化中心引起性能不稳定。本文提出的算法较好地解决了这两个问题，提高了算法稳定性，实现了非平稳信号盲分类。提取非平稳信号的小波系数作为聚类的样本空间，分析聚类结果的统计偏差以估计类的数目，采用调和均值准则进行分类。最后给出的仿真结果表明本文提出的方法较传统的K-Means算法明显降低分类错误率。     

宏蜂窝模型的传播模型校正研究

详细介绍了 宏蜂窝传播模 型校正的基本操作流程 结果分析及注意事项 对工程 ,人员了解和开展模型校正工作有一定的指导作用 。