Geotechnical study for optimizing the slope design of a deep open-pit mine,India

The study was undertaken to determine the optimal overall slope angle of a lead–zinc mine, which could extend down to a depth of 170 m. Detailed geotechnical investigations were conducted, including geotechnical mapping of existing benches to establish the geometrical and mechanical properties of the discontinuities, the drilling of eight boreholes and the establishment of the physico-mechanical properties of the intact rock. Based on these data, limit equilibrium and numerical simulation techniques were applied to assess the stability of the slopes and determine an optimal slope angle. It was concluded that the overall foot-wall and hanging-wall slopes should be 42 and 48° respectively.      

Development of materials database system for cae system of heat treatment based on data mining technology

Computer simulation for materials processing needs of materials. In order to employ the accumulated large data on a huge database containing a great deal of various physical properties materials heat treatment in the past years, it is significant to develop an intelligent database system. Based on the data mining technology for data analysis, an intelligent database web tool system of computer simulation for heat treatment process named as IndBASEweb-HT was built up. The architecture and the arithmetic of this system as well as its application were introduced.     

IPTV及相关技术

IPTV是基于IP协议的新一代技术,介绍了IPTV的主要业务功能和系统组成,并阐述了IPTV系统的关键技术。     

Adherence clustering: an efficient method for mining market-basket clusters

We explore in this paper the efficient clustering of market-basket data. Different from those of the traditional data, the features of market-basket data are known to be of high dimensionality and sparsity. Without explicitly considering the presence of the taxonomy, most prior efforts on clustering market-basket data can be viewed as dealing with items in the leaf level of the taxonomy tree. Clustering transactions across different levels of the taxonomy is of great importance for marketing strategies as well as for the result representation of the clustering techniques for market-basket data. In view of the features of market-basket data, we devise in this paper a novel measurement, called the category-based adherence, and utilize this measurement to perform the clustering. With this category-based adherence measurement, we develop an efficient clustering algorithm, called algorithm k-todes, for market-basket data with the objective to minimize the category-based adherence. The distance of an item to a given cluster is defined as the number of links between this item and its nearest tode. The category-based adherence of a transaction to a cluster is then defined as the average distance of the items in this transaction to that cluster. A validation model based on information gain is also devised to assess the quality of clustering for market-basket data. As validated by both real and synthetic datasets, it is shown by our experimental results, with the taxonomy information, algorithm k-todes devised in this paper significantly outperforms the prior works in both the execution efficiency and the clustering quality as measured by information gain, indicating the usefulness of category-based adherence in market-basket data clustering.     

农村饮水工程适宜水质净化技术

农村饮水工程根据不同的原水水质条件，宜采用不同的水质净化技术。对地表水浑浊度长年低于20NTU、瞬间不超过60NTU原水，可采用微絮凝直接过滤加消毒或慢滤加消毒净化工艺；浑浊度长年低于500NTU、瞬间不超过1000NTU的原水，采用混凝沉淀（澄清）过滤、消毒的常规净水工艺。对于特殊水质如氟超标的地下水、砷超标的地下水、苦咸水及其他污染水，根据不同情况，可分别采用活性氧化铝吸附法、混凝沉淀法、多介质过滤法、铁盐混凝沉淀法、电渗析法、反渗透法等不同方式予以处理。     

运用炸药混装车技术开采堆石坝级配料

葛洲坝集团公司成功地将乳化炸药混装车技术引入三峡水电工程的土石方开挖中，取得了良好的效益，在国内还未曾有人将该技术应用于堆石坝级配料开采。本文结合清江水布垭工程爆破试验，对运用混装车技术开采堆石料进行了研究。事实证明：把混装车技术引入堆石坝级配料开采可大大提高开采强度，降低工程成本；增加细颗粒石料，优化堆石料级配；爆破效果良好，安全可靠。     

数据挖掘在现代作战中的应用研究

随着装备技术的发展,现代作战具有作战单元种类数量多、攻防战术复杂、干扰性欺骗性数据充斥等特点,尤其是协同作战能力和数据交换能力逐步增强,以上都使得现代作战中涉及的信息呈现＂海量＂特征。为了取得理想的作战效果,指挥员必须对以上海量信息进行处理,从中提取出有用的信息和知识。近年来迅速发展的数据挖掘技术,在处理海量信息方面具有非常明显的优势。文章在介绍现代作战特点和数据挖掘技术的基础上,对数据挖掘技术在现代作战中的应用做了初步的研究。     

基于Sql Server BI平台和决策树技术的CET-4成绩分析

文章首先对Sql Server 2008商业智能平台及决策树技术相关理论作了介绍,然后对挖掘数据源数据进行了一系列预处理。利用Sql Server 2008商业智能平台下的决策树技术并采用数据挖掘扩展语言即DMX语言创建了CET-4成绩分析决策树模型。分类矩阵和挖掘提升图分别对该模型的评估结果表明了模型具有较高的可靠性和分类准确度,同时模型对应的一些规则可作为英语教学管理和改革的重要参考依据。     

基于间接关联规则的数据挖掘算法研究

简单数据集可以通过关联规则得到在数据间的相互关系;相当多的情况下,由于不能从关联规则得到隐藏在数据间的相互关系,需要按间接关联规则分析出数据项集在交易集合中出现的频度,挖掘隐藏在数据间的相互关系。文中通过使用概念分层和基于近邻的方法,探讨利用FP树产生的频繁项集,对候选关联检验其是否满足项对支持度条件,并利用这个频繁项集挖掘事务的间接关联,找到挖掘事务的间接关联的内在规律,构造出不依赖中介条件的间接关联挖掘算法。     

数据挖掘课程案例教学研究

数据挖掘是一门交叉性学科,是情报学专业的重要课程之一。它主要介绍数据挖掘的基本概念、原理、方法和技术,涉及多个学科和算法因而教学难度较大。由于数据挖掘学科交叉性强涉及的挖掘方法和相关算法多并繁杂,造成学生对数据挖掘的整体工作流程缺乏了解形成“不识庐山真面目只缘身在此山中”现象。文中以时间序列服装销售额预测挖掘项目为教学案例让学生首先掌握数据挖掘的标准流程,重点讲解用到的相关挖掘方法和算法及其在实际挖掘环境中的开发方法,达到“会当I临绝顶一览众山小”的教学目标。通过教学实践教学效果良好。