Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

Cr-Mo solid solutions forced by high-energy ball milling

Mixtures of Cr and Mo elemental powders, with the nominal compositions Cr₂₅Mo₇₅, Cr₅₀Mo₅₀, and Cr₇₅Mo₂₅, are processed by high-energy ball milling at ambient temperature. Milling is observed to force the mixing of the immiscible bcc elements Cr and Mo into solid solutions. The lattice parameter of these solid solutions, measured by X-ray diffraction (XRD), displays the expected positive deviation from Vegard’s law. These deviations are compared to the ones predicted by Eshelby’s inclusion model for dilute alloys. The conventional Williamson-Hall approach is shown to fail to determine the grain size in as-milled samples, probably due to the high density of dislocations. Annealing at 700 °C for 10 hours under argon leads to a large reduction in structural defect density, without inducing any significant decomposition. The mixing measured in Cr-Mo is discussed in the broader context of the mechanical mixing forced by ball milling in moderately immiscible systems.     

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.     

分置式牛津型斯特林制冷机的数值分析与实验验证

对分置式牛津型斯特林制冷机进行了数值计算 ,介绍了计算模型考虑到的众多不可逆因素。通过对计算结果与实验结果的对比 ,验证了本文数值计算的准确性 ,说明本文计算模型与数值处理方法是切实可行的     

IPv6和基于IPv6的网络设计

对IPv6协议的主要内容进行了简要介绍,并针对IPv6的特点对基于IPv6的网络设计进行了探讨。     

裂缝性油气藏采收率：100个裂缝性油气田实例的经验总结

通过对世界上100个裂缝性油气藏的综合评价，研究储集层及流体本身的性质(包括孔隙度、渗透率、黏度、可动油比例、含水饱和度、润湿性及裂缝分布特征等)和驱动机制及油藏管理战略(优化日产量和采用不同类型的提高采收率技术)对其最终采收率的影响。将裂缝性油气藏分为4类：I类的基质几乎没有孔隙度和渗透率，裂缝是储存空间和流体流动的通道；Ⅱ类的基质有较低的孔隙度和渗透率，基质提供储存空间，裂缝提供流动通道；Ⅲ类(微孔隙)的基质具有高孔隙度和低渗透率，基质提供储存空间，裂缝提供流动通道；Ⅳ类(大孔隙)的基质具有高的孔隙度和渗透率，基质提供储存空间和流动通道，裂缝仅增加渗透率。对26个Ⅱ类油气藏和20个Ⅲ类油气藏的开采历史的研究表明：Ⅱ类油气藏的采收率受水驱强度和最优日产量控制，日产量过高会很容易破坏Ⅱ类油气藏，一些Ⅱ类油气藏如果管理得当，采收率可以很高，不需要二次或三次采油；Ⅲ类油气藏的采收率主要受岩石和流体本身性质的影响，特别是基质渗透率、流体重度、润湿性以及裂缝强度等，不进行二次或三次采油不可能完全开采，往往需要采用一些提高采收率的专门技术。以往将Ⅱ类和Ⅲ类裂缝性油气藏归为一类，认识它们的区别将有助于选择更好的开发策略。     

Parallel multilevel fast multipole method for solving large-scale problems

The Multilevel Fast Multipole Method (FMM) is a well-established method and can be applied to solve electromagnetic (EM) scattering problems. Compared with other traditional methods, it requires less computational time and memory. However, constrained by a single processor's speed and memory limitations, the problem size that can be solved by serial implementation is still relatively small. For a million-unknown target, the computational time on a single processor is intolerable, and memory could be easily exhausted. Parallel-computing technology, which can utilize multiprocessors, provides an efficient way to solve electrically large-scale EM problems. This paper will focus on discussing the parallel methodologies applied to a multilevel FMM code, as well as demonstrating the computational efficiency of the parallel approach.