ECAP法制备超细晶铜的再结晶行为研究

在室温下，采用ECAP技术对纯铜进行了1-10道次的挤压，使其组织大大细化，得到了均匀、细小的等轴晶，平均晶粒尺寸为0．75μm。通过对不同ECAP道次后的退火试样的硬度测量和观察组织，结果表明：随ECAP道次的增加．开始再结晶的温度降低，再结晶软化的速率增加，ECAP8道次试样在433K发生静态再结晶。     

Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Decision recommendations are a set of alternative options for clinical decisions (e.g., diagnosis, prognosis, treatment selection, follow-up, and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a “reasoning over domain” approach for the generation of decision recommendations by gathering and inferring conclusions from production rules. In order to rationalize our approach, we present a specification that will sustain the logic models supported in the knowledge bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey toward the solution of the reported needs. The starting point of our approach is the proposition of Reflexive Ontologies (RO). Here, we go a step further, proposing an extension of RO that includes the handling and reasoning that production rules provide. Our approach speeds up the recommendation generation process.     

地下结构震害风险信息融合方法研究

为提高地下结构震害风险判决的科学性和智能化水平,提出一种基于证据理论的地下结构震害风险信息融合方法。在地下结构震害风险智能监测的基础上,根据震害风险融合原理,构建基于智能监测和专家判决的地下结构震害风险融合模型。遵循证据理论的原则和模型规则,构造统一的地下结构震害状态空间和风险概率表达方式,建立风险融合证据框架,确定判决规则,设计风险融合证据模型组件。计算结果表明,该模型能有效提高地下结构震害信息诊断的可信度,充分显示了该融合模型组件的有效性。     

一种基于EQ规则的组合服务运行时自适应方法

组合服务通常运行在开放、变化和不确定的互联网环境中.动态复杂的运行环境,使得组合服务的执行具有不确定性和不可靠性,从而制约了服务组合技术的实际可用性.针对该问题,面向环境的分析与建模,提出了一种基于EQ规则的组合服务运行时自适应方法.该方法在记载组合服务的执行日志和各备选服务的运行环境数据的基础上,挖掘得到反映“一个备选服务在特定的环境状态下所表现出的质量会如何”的EQ规则库,从而指导组合服务如何响应实时产生的各类环境变化事件,以驱动组合服务的运行时自适应,保障其可靠运行.仿真实验结果表明:该方法能够提高组合服务在动态环境中的服务质量,增强其运行稳定性,是一种有效的组合服务运行时自适应方法.     

不一致决策表规则获取的粒计算方法

针对不一致决策表的规则获取,从属性多粒度角度考虑,按粒度由粗到细将决策表划分成不同的粒度空间,通过定义相容粒关系矩阵和不相容粒关系矩阵,并充分挖掘隐含在矩阵中的启发式信息,实现对不同粒度空间确定性规则和不确定性规则的获取.最后,从实例分析以及UCI测试对算法进行验证,并与现有算法进行实验对比,实验结果与分析表明了所提出算法的可行性和有效性,而且按此方法获取的规则集的泛化能力更强.     

Time Averaging Algorithms with Stopping Rules for Multi‐Agent Consensus with Noisy Measurements

A time averaging technique is introduced to consensus algorithms in networked multi‐agent systems under a noisy environment. Each agent communicates with its neighboring agents via a constant gain, while the time averaging states of the agents are considered as the values for agreement. The variation of the time averaging states then is evaluated at a specific number of iterations, where the number is given explicitly in terms of parameters related to the consensus accuracy and its probabilistic guarantee. This result establishes a rigorous stopping rule for the multi‐agent consensus with noisy measurements. Several results on this type of stopping rules are provided for undirected, directed, and time‐varying communication graphs. These theoretical results are illustrated through numerical examples.     

Mining fuzzy temporal association rules by item lifespans

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach.     

Protel DXP 2004应用中的常见问题及解决方法

Protel DXP 2004软件是一款应用广泛的印制电路板设计软件,学习该软件比较容易入门,但是要熟练掌握并且灵活处理软件使用中的常见问题并非易事。从电气规则检查、载入网络表、制作元件封装等方面,分析Protel DXP 2004软件操作中的常见问题及产生原因,并提出了解决这些问题的方法。     

数据挖掘技术在教育学中的应用

随着信息化时代的不断发展,数据挖掘技术日趋成熟,满足了人们对于大量信息的处理要求。目前,数据挖掘技术已经越来越多的应用于金融、通讯和交通等各行各业,但是在教育领域的应用相对较少。针对这一现状,在传统的分析方法上采用了关联规则挖掘,聚类挖掘等多种算法,对青少年同伴关系、人际关系和网络成瘾等各方面进行研究,得到不同性别的青少年同伴亲疏程度不同等一系列结论,提出了数据挖掘技术在教育学领域的应用的新前景。