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.     

Neural networks and blood cell identification

The objective of this project is to propose a method of identifying cells found in human blood and to classify them based upon their morphological features using neural networks. The project focuses on three major blood cell types, namely, erythrocytes, leukocytes and platelets. The data are collected using peripheral blood smears from clinical patients. The image acquisition requires 100x magnification on all the blood smears, the preprocessing involves the use of median and edge enhance filters; the feature extraction is done by performing the wavelet transform on the images. Finally classification of the blood cell types is done using ALOPEX and Back Propagation trained neural networks. The efficacy of both networks is then compared by comparing their outputs and number of iterations required to reach the final result.     

清代皇家园林规划设计控制的量化研究——以圆明三园、清漪园为例

本文通过量化分析探索了清代皇家园林规划设计的控制规律及相关理论。     

适用于啤酒行业能源管理的智能冷量积算仪

介绍了智能冷量积算仪的测量原理以及软硬件设计，该仪表适用于啤酒行业中冰水和乙二醇水溶液冷量计量，并得到成功应用，具有广阔的应用前景。     

东营市CNG公交汽车改装及加气站经济性研究

对东营市公交汽车改装方案和建设相应的加气站进行了研究，结果表明，以2006年当地90号汽油、0号柴油和CNG价格计算，改装为柴油CNG双燃料公交车比柴油车，每天每车可节省燃料费92．24元，成本回收期为3．6个月；建一座年设计加气量为547．5万m^3、可供200-250辆汽车加气的常规开放式加气站，投资回收期为8年零8个月。改装汽车和建设加气站可利用当地丰富的天然气资源，节约石油，保护环境。     

Impact of microstructure on stability of permanent magnet biasedmagnetoresistive heads

This work pertains to output voltage stability of soft adjacent layer biased magnetoresistive heads with abutted permanent magnetic films for domain stabilization. A micromagnetic model has been developed to study the effect of the permanent magnet film microstructure and the micromagnetic properties of the abutted junction interface on head stability. The impact on head stability is analyzed with respect to interfacial ferromagnetic coupling across the junction interface and intergranular exchange coupling in the permanent magnet films among other film properties     

镨掺杂分布对1.3μm光纤放大器特性影响

对掺氟化镨玻璃光纤放大器的小信号增益，用广义的高斯近似公式可获得精确的分析表达。文中研究了限制光纤芯层中央部分的镨掺杂对光纤放大器特性的影响，结果发现限制镨掺杂分布能改进光纤放大器的工作效率，且截止波长比芯层全部均匀掺镨的光纤更长。