Manufacturing and structural safety evaluation of a composite train carbody

This paper explains the manufacturing process of a composite train carbody with a sandwich composite structure for bodyshell and a stainless steel structure for the under frame. In addition, the structural behavior and safety of the composite carbody of the Korean tilting train was investigated by the static load tests. From the test results, the stiffness of the composite carbody met the specified design. In the aspect of strength, the maximum stress of the composite bodyshell was of 12.2% of strength of CF1263 carbon/epoxy.     

Heat and Mass Transfer Analogy Studies of Binary Liquid Mixture in Comparison with Eteanol-n-Heptane Evaporating to Air

An expenmental and theoretical study of heat and mass transfer analogy and a comparison of that to a binary liquid mixture evaporation is presented. Common organic solvents, ethanol and n-heptane, were used to form an alcohol - hydrocarbon mixture. Studies were carried out in a horizontal rectangular channel having air flow velocities of 0.2 - 0.9 m/s. Heat transfer coefficients were measured with a copper plate resistor and mass transfer coefficients with a square pool. The heat and mass transfer analogy is presented for a system having two evaporating compounds with a fixed value of air flow and verified by measuring and comparing mass transfer coefficients for distilled water with air flow velocities of 0.2 - 0.9 mls. An illustrative example of the use of the theory for industrial ventilation is presented.     

蒸发冷凝法中气体压强和蒸发温度对粒子大小的影响

在Ｎ＿２气氛中，用蒸发冷凝法，制备了Ｓｎ细微粒和Ｆｅ及Ｆｅ－４７（ｗｔ）％Ｎｉ合金超细微粒。分别用ＳＥＭ和ＴＥＭ，直接观测粒子大小及其分布。结果表明，平均粒径不是随Ｎ＿２气压强增加单调上升，而是在某一压强Ｐ＿（ｍａｘ）下，出现最大值。随蒸发温度提高，Ｐ＿（ｍａｘ）值迅速增大。粒子大小及其分布与粒子生长机制密切相关。对粒子凝聚生长条件进行了简要讨论。     

模糊综合评判方法在碳酸盐岩油气勘探中的应用

详细地阐述了模糊综合评判方法的数学原理及其在油气勘探开发中的应用.根据某油田的生产层参数资料,运用MICROSOFT EXCEL软件,在对各参数进行统计研究并了解它们分布规律的基础上,合理地构造出一系列隶属函数,通过编制相应的计算机程序,完成综合评判.评判结果与勘探实际吻合较好.该方法有效地适用于碳酸盐岩油气藏的勘探开发.     

Choosing OWA operator weights in the field of Social Choice

One of the most important issues in the theory of OWA operators is the determination of associated weights. This matter is essential in order to use the best-suited OWA operator in each aggregation process. Given that some aggregation processes can be seen as extensions of majority rules to the field of gradual preferences, it is possible to determine the OWA operator weights by taking into account the class of majority rule that we want to obtain when individuals do not grade their pairwise preferences. However, a difficulty with this approach is that the same majority rule can be obtained through a wide variety of OWA operators. For this reason, a model for selecting the best-suited OWA operators is proposed in this paper.     

An efficient algorithm for mining frequent inter-transaction patterns

In this paper, we propose an efficient method for mining all frequent inter-transaction patterns. The method consists of two phases. First, we devise two data structures: a dat-list, which stores the item information used to find frequent inter-transaction patterns; and an ITP-tree, which stores the discovered frequent inter-transaction patterns. In the second phase, we apply an algorithm, called ITP-Miner (Inter-Transaction Patterns Miner), to mine all frequent inter-transaction patterns. By using the ITP-tree, the algorithm requires only one database scan and can localize joining, pruning, and support counting to a small number of dat-lists. The experiment results show that the ITP-Miner algorithm outperforms the FITI (First Intra Then Inter) algorithm by one order of magnitude.     

电梯交通系统(Ⅰ)──电梯交通配置现状及发展

本文对国内外电梯交通配置设计现状及发展趋势作了论述。指出了由统计特性描述进入到采用专家系统和模糊规则的动态特性描述这一总的发展趋势。     

瓶组气化站的建筑、结构设计要点

瓶组气化站的建筑，结构设计关系到安全，满足使用要求和投资的大小，本文根据多年的实践和最新的有关设计规范的要求，阐述瓶组气化站建筑，结构设计的要点。     

PLC顺控程序的计算机辅助设计

本文用C／C 语言研制了一个计算机辅助设计软件，可以自动设计PLC的SFC应用程序，并针对具体机型S7—200，利用其编程软件，将程序快速下载到PLC，极大地提高了效率。     

Tree-based partitioning of date for association rule mining

The most computationally demanding aspect of Association Rule Mining is the identification and counting of support of the frequent sets of items that occur together sufficiently often to be the basis of potentially interesting rules. The task increases in difficulty with the scale of the data and also with its density. The greatest challenge is posed by data that is too large to be contained in primary memory, especially when high data density and/or low support thresholds give rise to very large numbers of candidates that must be counted. In this paper, we consider strategies for partitioning the data to deal effectively with such cases. We describe a partitioning approach which organises the data into tree structures that can be processed independently. We present experimental results that show the method scales well for increasing dimensions of data and performs significantly better than alternatives, especially when dealing with dense data and low support thresholds. Shakil Ahmed received a first class BSc (Hons) degree from Dhaka University, Bangladesh, in 1990; and an MSc (first class), also Dhaka University, in 1992. He received his PhD from The University of Liverpool, UK, in 2005. From 2000 onwards he is a member of the Data Mining Group at the Department of Computer Science of the University of Liverpool, UK. His research interests include data mining, Association Rule Mining and pattern recognition. Frans Coenen has been working in the field of Data Mining for many years and has written widely on the subject. He received his PhD from Liverpool Polytechnic in 1989, after which he took up a post as a RA within the Department of Computer Science at the University of Liverpool. In 1997, he took up a lecturing post within the same department. His current Data Mining research interests include Association rule Mining, Classification algorithms and text mining. He is on the programme committee for ICDM'05 and was the chair for the UK KDD symposium (UKKDD'05). Paul Leng is professor of e-Learning at the University of Liverpool and director of the e-Learning Unit, which is responsible for overseeing the University's online degree programmes, leading to degrees of MSc in IT and MBA. Along with e-Learning, his main research interests are in Data Mining, especially in methods of discovering Association Rules. In collaboration with Frans Coenen, he has developed efficient new algorithms for finding frequent sets and is exploring applications in text mining and classification.