A novel approach to adaptive relational association rule mining

The paper focuses on the adaptive relational association rule mining problem. Relational association rules represent a particular type of association rules which describe frequent relations that occur between the features characterizing the instances within a data set. We aim at re-mining an object set, previously mined, when the feature set characterizing the objects increases. An adaptive relational association rule method, based on the discovery of interesting relational association rules, is proposed. This method, called ARARM (Adaptive Relational Association Rule Mining) adapts the set of rules that was established by mining the data before the feature set changed, preserving the completeness. We aim to reach the result more efficiently than running the mining algorithm again from scratch on the feature-extended object set. Experiments testing the method's performance on several case studies are also reported. The obtained results highlight the efficiency of the ARARM method and confirm the potential of our proposal.     

Geothermal energy utilization trends from a technological paradigm perspective

The use of geothermal energy and its associated technologies has been increasing worldwide. However, there has been little paradigmatic research conducted in this area. This paper proposes a systematic methodology to research the development trends for the sustainable development of geothermal energy. A novel data analysis system was created to research the geothermal energy utilization trends, and a technological paradigm theory was adopted to explain the technological changes. A diffusion velocity model was used to simulate and forecast the geothermal power generation development in the diffusion phase. Simulation results showed that the development of installed capacity for geothermal generation had a strong inertia force along with the S-curve. Power generation from geothermal power sources reached a peak in 2008 and is estimated to be saturated by 2030. Geothermal energy technologies in hybrid power systems based on other renewable energy sources look to be more promising in the future.     

综采工作面粉尘防治问题分析与技术改进

针对新桥煤矿2301综采工作面机载喷雾系统喷雾效果差、喷雾耗水量大造成煤质含水量超标、喷嘴雾化程度不高、喷嘴容易发生堵塞等问题,提出了高压喷雾系统设计方案,选择了1.2mm的锥形引射喷嘴和1.5mm的扇形引射喷嘴。采用固定水泵供水方式,结合工作面实际情况,计算出喷雾总用水量247.5L/min,提高了喷雾射程,提升了除尘效果。     

一种基于Spark的不确定数据集频繁模式挖掘算法

如何在海量不确定数据集中提高频繁模式挖掘性能是目前研究的热点.传统算法大多是以期望、概率或者权重等单一指标为数据项集支持度，在大数据背景下，同时考虑概率和权重支持度的算法难以兼顾其执行效率.为此，本文提出一种基于Spark的不确定数据集频繁模式挖掘算法（UWEFP），首先，为了同时兼顾数据项的概率和权重，计算一项集的最大概率权重值并进行剪枝；然后，为了减少对数据集的多次扫描，结合Spark框架的优点，设计了一种具有FP-tree特征的新颖的UWEFP-tree结构进行模式树的构建及挖掘；最后在Spark环境下，以UCI数据集进行实验验证.实验结果表明本文的方法在保证挖掘结果的同时，提高了效率.     

Stress-strain relations in elastoplastic solids with Dugdale-type cracks

Mechanical behavior of a two-dimensional elastoplastic solid with rectilinear cracks is investigated. Plastic strip model is used to reduce plasticity problem to the equivalent linear elasticity formulation. Two realizations of the mixed mode plastic strip model are considered: in-line plastic strips as proposed by Becker and Gross [Int. J. Fract. 37 (1988) 163], and inclined plastic strips of Panasyuk and Savruk [Appl. Mech. Rev. 47 (1994) 151]. The effective mechanical response predictions are based on the procedure presented in Kachanov et al., [Appl. Mech. Rev. 47 (1994) 151]. Stress-strain relations are obtained for parallel and randomly oriented non-interacting cracks. Results are compared with known elastic solutions.     

分类挖掘技术在高校人事管理中的应用

探讨分类挖掘技术在高校实际工作中的应用方式与应用领域。以高校人事管理为模型，应用数据挖掘中决策树算法，对高校人力资源数据源中的信息进行分析，发现其中有价值的数据模式，寻找其中存在的关系和规则，对高校人才规划提供比较客观的决策支持。     

基于数据挖掘的OLAP分析技术及应用

数据仓库和数据挖掘技术是目前信息技术研究的热点问题之一,介绍了数据挖掘(data mining)、数据仓库(datawarehouse)及联机分析处理(OLAP)技术。并以零售业决策支持系统为例,介绍了该系统的体系结构、数据仓库的设计、系统实现关键技术及各子系统功能,着重论述了如何利用OLAP技术实现企业决策支持系统。     

USERS' TWO-DIMENSIONAL INTEREST AND ITS STORAGE METHOD

The users' interest can be mined from the web cache and can be used widely. The interest can be specialized by the two-tuple (term, weight) in the simple interest model, in which the association relations are not mined, and then the interest cannot be associated in expressing the users' interest. Based on analyzing the WWW cache model, this letter brings forward a two-dimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.     

USERS’ TWO-DIMENSIONAL INTEREST AND ITS STORAGE METHOD

The users‘ interest can be mined from the web cache and can be used widely.The interest can be specialized by the two-tuple(term,weight) in the simple interest model,in which the association relations are not mined.and then interest cannot be associated in expressing the users‘interest.Based on analyzing the WWW cache model,this letter brings forward a twodimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.