Strategies for product recovery decisions

Product recovery is beset by uncertainty regarding the quality of end-of-life (EOL) products, and in order to ascertain the reusability of these products, they have to undergo expensive tests. This undermines the profitability of the recovery process. The key to improve the effectiveness of product recovery is to improve the quality of information available before testing. Emerging data capture technologies can significantly improve the availability of information. However, in order to maximise the potential of these technologies, appropriate decision-making algorithms that exploit such information must be developed. We model the recovery process using a decision-theoretic approach, and derive strategies to ascertain the reusability of EOL products, and also to decide when tests are beneficial. We show that improving the quality of information leads to increase in effectiveness of the recovery process by reducing the need for tests. Copyright © 2009 Inderscience Enterprises Ltd.

Auto-calibration of a camera system using Image Alignment

Calibration of a camera system is a necessary step in any stereo metric process. It correlates all cameras to a common coordinate system by measuring the intrinsic and extrinsic parameters of each camera. Currently, manual calibration of a camera system is the only way to achieve calibration in civil engineering operations that require stereo metric processes (photogrammetry, videogrammetry, vision based asset tracking, etc). This type of calibration however is time-consuming and labor-intensive. Furthermore, in civil engineering operations, camera systems are exposed to open, busy sites. In these conditions, the position of presumably stationary cameras can easily be changed due to external factors such as wind, vibrations or due to an unintentional push/touch from personnel on site. In such cases manual calibration must be repeated. In order to address this issue, several self-calibration algorithms have been proposed. These algorithms use Projective Geometry, Absolute Conic and Kruppa Equations and variations of these to produce processes that achieve calibration. However, most of these methods do not consider all constraints of a camera system such as camera intrinsic constraints, scene constraints, camera motion or varying camera intrinsic properties. This paper presents a novel method that takes all constraints into consideration to auto-calibrate cameras using an image alignment algorithm originally meant for vision based tracking. In this method, image frames are taken from cameras. These frames are used to calculate the fundamental matrix that gives epipolar constraints. Intrinsic and extrinsic properties of cameras are acquired from this calculation. Test results are presented in this paper with recommendations for further improvement.

A matrix-calculation-based algorithm for numerical change propagation analysis

Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.

福尔马林固定铜鱼基因组DNA的提取与扩增

铜鱼(Coreius heterodon)作为长江中、上游的重要经济鱼类是研究三峡大坝阻隔效应的重要材料之一。然而,过去的铜鱼标本都保存在福尔马林溶液中,有必要探讨从福尔马林固定的铜鱼标本中有效提取基因组DNA的方法以及这些DNA用于微卫星和线粒体分析的可行性。本实验通过改进的酒精梯度浸泡法去除标本中的甲醛,然后用酚-氯仿抽提法成功地提取到了铜鱼标本的基因组DNA;设计引物后进行了线粒体和微卫星的PCR扩增,扩增产物经银染检测。微卫星扩增结果显示只有部分个体可以扩出目的带,而线粒体控制区部分区段在所有个体

一株异养硝化细菌的分离鉴定及其亚硝化作用研究

从复合垂直流人工湿地表层基质中分离出一株硝化活性较强的异养硝化细菌H-1,进行biolog菌种鉴定,鉴定系统中没有与该菌株特性相似的数据记录。16SrDNA的序列分析结果显示,菌株H-1与产碱杆菌属(Alcaligenes)粪产碱杆菌(A.faecalis)有98%相似性,认为分离菌株H-1可能为Alcaligenes A.faecalis。通过4因素3水平的正交试验,结果显示,当温度为30℃,pH为7.5,接种量为107CFU,溶氧2.25mg·L-1时,该菌株亚硝化反应效果最佳;影响亚硝化反应效果的因

武汉月湖和莲花湖表层沉积物中持久性有机物的污染状况

采用气-质联用技术分析了武汉汉阳月湖和莲花湖的4个表层沉积物样品中的有机污染物,探讨了两湖沉积物受持久性有机物污染的程度。月湖中共检测出124种有机物,其中属环境优先控制污染物和美国EPA筛选的内分泌干扰物19种;莲花湖中共检测出186种有机物,环境优先控制污染物和美国EPA筛选的内分泌干扰物34种。主要污染物包括:酞酸酯、酯类、酚类、杂环和苯及其衍生物等。污染物浓度顺序为L1>L2>Y2>Y1,莲花湖中有机物浓度明显高于月湖。两湖邻苯二甲酸酯的含量最高,占了污染物总量的96%～98%,邻苯二甲酸乙基己基