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.     

用频谱分析法对地下水位进行中长期预报

本文把影响地下水位变化过程作为随机过程，用频谱分析法建立随机水动力学模型模拟地下水位的变化过程，并将其用于地下水位的中长期预报。通过实例验证它具有较高的精度。     

水电水利工程压力钢管灌浆孔应力集中敏感性因素研究

水电水利工程压力钢管开孔灌浆后,需对灌浆孔严密封堵,处理不好会对工程安全运行留下隐患。在总结国内外灌浆孔常用封堵方案基础上,以某水电站地下埋管为例,建立平面有限元模型,分析其灌浆开孔后管壁应力集中现象,研究了补强板厚度及堵头坡口深度对压力钢管灌浆孔应力集中的敏感性。结果表明,应力集中程度随补强板厚度及堵头坡口深度增加递减,堵头坡口深度对其影响更加敏感。对于地下埋管管壁上开灌浆孔的非高强钢,建议灌浆后孔口进行封堵,补强板厚度宜与钢管壁厚相同,并适当增加坡口深度。当钢管壁厚较大时,堵头坡口深度宜不小于钢管壁厚的1/4~1/3。     

大万山岛海水抽水蓄能电站地下厂房自然通风模拟研究

针对目前抽水蓄能电站地下厂房自然通风规律尚不明确的问题,在考虑电站运行工况周期变化特点及室外风压的基础上,优化了现有的自然通风网络模型,使其可用于计算抽水蓄能电站地下厂房的自然通风情况。并且,利用优化后的模型,模拟计算了大万山岛海水抽水蓄能电站全年的自然通风情况。结果表明:热压是影响自然通风动力的最主要因素。整体上,自然通风量在冬季大于夏季;单日内,自然通风量受电站运行工况变化的影响。在发电和蓄能工况时,自然通风量较大,在卸载工况时,自然通风量较小。交通洞末端空气温度不受电站运行工况和自然通风量变化的影响,在单日内的变化幅度小于2℃,而在同季节的不同日之间的差异可达8.6℃。在过渡季的部分时段和整个夏季,交通洞末端空气温度高于规定的室内环境温度上限值,因此应开启空调制冷设备。通过优化后的模型与具体案例的分析,为其他类似工程的自然通风系统的设计及运行调控提供参考。     

城市洪涝试验研究进展

城市洪涝物理试验与原型试验是开展数值模型验证及提高预报预警精度的重要手段。从城市产流过程、地表洪水演进以及地表径流与管网水流交互三方面,综述了近年来国内外城市洪涝试验的研究进展。针对目前城市洪涝试验研究中存在的不足,指出今后应完善现有城市产汇流过程相关机理方面的试验研究,深入研究地表与管网垂向交互过程,加强与城市洪涝期间的流动行为密切相关过程的定量试验研究。     

华北中部平原地表水入渗试验 ——以南宫溹泸河为例

华北平原中部地区含水砂层颗粒细且薄,对地下水储蓄和地表水入渗不利。选择河道带进行地表水入渗试验,以获取最大地下储蓄空间,为该区水资源合理利用提供良策。试验区选在南宫溹泸河,人工引水1.5个月,获取大量监测数据,据此对地下水位和水量的变化特征、入渗量和地下水库调蓄能力进行研究,结果表明：干涸河道引水入渗,入渗比例可达80.54%;溹泸河上下游2个断面Ⅰ-Ⅰ′和Ⅱ-Ⅱ′河道垂向渗透速度为10.81 m/d和10.72 m/d;水平扩散速度为1.69 m/h和2.38 m/h。由于Ⅰ-Ⅰ′断面垂向渗透速度大于Ⅱ-Ⅱ′断面,而水平扩散速度小于Ⅱ-Ⅱ′断面,所以Ⅰ-Ⅰ′断面形成的水丘相比Ⅱ-Ⅱ′断面较为明显,且不易消散。计算结果显示,试验区调蓄库容为1.87亿m3。     

Active symbols and internal models: Towards a cognitive connectionism

In the first section of the article, we examine some recent criticisms of the connectionist enterprise: first, that connectionist models are fundamentally behaviorist in nature (and, therefore, non-cognitive), and second that connectionist models are fundamentally associationist in nature (and, therefore, cognitively weak). We argue that, for a limited class of connectionist models (feed-forward, pattern-associator models), the first criticism is unavoidable. With respect to the second criticism, we propose that connectionist modelsare fundamentally associationist but that this is appropriate for building models of human cognition. However, we do accept the point that there are cognitive capacities for which any purely associative model cannot provide a satisfactory account. The implication that we draw from is this is not that associationist models and mechanisms should be scrapped, but rather that they should be enhanced.In the next section of the article, we identify a set of connectionist approaches which are characterized by active symbols — recurrent circuits which are the basis of knowledge representation. We claim that such approaches avoid criticisms of behaviorism and are, in principle, capable of supporting full cognition. In the final section of the article, we speculate at some length about what we believe would be the characteristics of a fully realized active symbol system. This includes both potential problems and possible solutions (for example, mechanisms needed to control activity in a complex recurrent network) as well as the promise of such systems (in particular, the emergence of knowledge structures which would constitute genuine internal models).     

围岩一支护动态系统稳定性判据——变形速率比值判别法

本文以围岩稳定性判据现有研究成果为基础,总结若干新奥法软弱围岩隧道工程监控量测的经验教训,针对现行判据在现场往往难以掌握应用的问题,提出“围岩与支护动态系统稳定性判据(变形速率比值判别法)”,给出工程实例,并以开放的复杂巨系统方法论为指导,试图从原理和方法上加以阐明。     

Corrosion behaviour of Ni-Zr-Ti-Si-Sn amorphous plasma spray coating

Ni₅₉Zr₂₀Ti₁₆Si₂Sn₃ amorphous material was deposited by a vacuum plasma spraying technique onto steel and copper substrates in order to investigate their behaviour in a corrosive environment. For comparison, the same alloy was prepared as amorphous ribbons by melt spinning. The amorphous nature of the coatings and ribbons was characterized by XRD, DSC and TEM, while XPS and AES analyses were performed to understand the origin of passivation and mode of corrosion. The corrosion behaviour of the coating was studied in H₂SO₄ and HCl solutions open to air at room temperature. Potentiodynamic polarisation and galvanic coupling tests were carried out on the substrate and the coating. It was found that the formation of Zr-, Ti- and Si-rich passive oxide layers provide a high corrosion resistance in H₂SO₄ solution while the breakdown of the passive layer by chloride ion adsorption was responsible for pitting corrosion of the Ni₅₉Zr₂₀Ti₁₆Si₂Sn₃ amorphous ribbons in HCl solution. Galvanic corrosion was the dominant corrosion mechanism for the coating/copper hybrid structure, in contrast to the Ni₅₉Zr₂₀Ti₁₆Si₂Sn₃ amorphous coating, which efficiently protected the steel substrate in the corrosive environment.