Dislocation configurations in highT c oxide BiSrCaCuO

A study of dislocation configurations in superconducting oxide BiSrCaCuO has been made by transmission electron microscopy. Evidence was found for the presence of dislocation pairs composed of two parallel single dislocations holding together with the same Burgers vectors. The pair can further dissociate into partials, giving rise to a four-fold ribbon. Networks consisting of dislocation pairs were also observed. These phenomena are attributed to the possible ordering of strontium and calcium ions and the existence of some oxygen sheet of the Aurivillius type in the oxide crystal. Schemes to illustrate the configurations are suggested and discussed.     

基于XUL开发富客户端应用程序

首先本文介绍了开发富客户端应用程序的RIA技术,然后对当前一种可用的RIA技术—XUL的各方面特性以及由它实现富客户端的途径做了深入探讨,最后通过一个项目实例-订单管理系统演示了基于XUL开发富客户端应用程序的一种实现。     

动态力学及介电法研究蓖麻油丙烯酸酯共聚网络悬挂链的弛豫运动

用动态力学（内耗）和介电方法研究了由蓖麻油（ｃａｓｔｏｒｏｉｌ）、甲苯二异氰酸酯（ＴＤＩ）、丙烯酸羟乙酯（ＨＥＭＡ）组成的网络（Ａｉ）和由正己醇取代Ａ网络中部分ＨＥＭＡ组成的网络Ｂｉ（ｉ＝０，１，２，３）两种网络的内耗及介电损耗，内耗峰强度随悬挂链数目增加而升高，证实了网络破坏后形成的悬挂链的运动对内耗及介电损耗峰高有明显的贡献。     

V型立体纸雕的几何理论与算法的研究

立体书是一种独特的纸张艺术形式,有着精细的几何结构.针对一类特殊的V型立体纸雕进行了系统性的研究,给出了V型立体纸雕可实现性的充分条件,使其可以只借助2张支撑面的力量进行打开和关闭,同时在这个过程中所有的面片都保持刚性并且相互不产生自交.基于这些充分条件,文中分别实现了一个计算机辅助交互V型纸雕设计工具,以及一个基于体方法的自动生成算法.     

基于M-CDIO的C语言课程教学研究

提出了基于CDIO工程教育模式的本地化和微型化教学模式(M-CDIO),并将其运用于C语言程序设计课程教学过程中;重新修改和设置了教学目标、教学内容、教学体系、教学方法和团队项目等:课程组织方式以微型项目为导向而不沿用传统的知识点导向,知识内容为集成的而非传统的知识与能力割裂的,等等.这些创新对深化工程课程教学改革具有实际意义.     

基于BA-WPHM的滚动轴承两阶段剩余寿命预测方法

为了提高滚动轴承剩余寿命预测的准确性,根据滚动轴承运行过程的两阶段性特点,提出了一种基于蝙蝠算法(BA)和威布尔比例风险模型(WPHM)的滚动轴承两阶段剩余寿命预测方法。首先,构建基于WPHM的剩余寿命预测模型;其次,提出了两阶段极大似然估计法,建立新的似然函数,并利用BA算法进行求解,以提高参数估计的准确性;最后,建立BA-WPHM模型对滚动轴承进行剩余寿命预测。案例分析表明,相比于Newton-Raphson算法、自组织分层猴群算法(SHMA)和独特的自适应粒子群算法(UAPSO),提出的方法参数估计的准确性更高,剩余寿命的预测精度优于支持向量回归(SVR)方法,验证了所提方法的有效性,为滚动轴承维修决策的可行性提供了依据。     

受回水影响的矩形渠道流量推算方法分析

矩形渠道断面规则、稳定,一般情况下,其水位-流量关系曲线单一.实际测验过程中发现,矩形渠道受下游回水影响,测验断面处实测水位流量点散乱、关系曲线复杂,线上推流精度降低.本研究基于曼宁公式、水流运动能量方程推导出规则矩形渠道流量推算的公式,应用该公式推算渠道流量可以解决水位-流量关系曲线单一导致的线上推流精度降低问题.将本研究提出利用上下游比降、水位和糙率推算断面流量的方法并应用在某水文站的矩形渠道流量推算中,结果表明,实测流量Q和水位、糙率和水面比降的复合项P拟合度较好,具有一定的实际应用价值.     

Authority updating: An expert authority evaluation algorithm considering post‐evaluation and power indices in social networks

In group assessment, the focus is on finding high‐authority experts to improve the reliability of assessment results. In this study, we propose an authority updating algorithm while considering the power and judgement reliability of an expert on the basis of social networks and post‐evaluations. A network power index is established and used to reflect the power of an expert while considering social networks. The measurement of the judgement reliability of an expert considers the post‐evaluation of the objects selected by experts, thereby more scientifically reflecting the reliability of experts. The analysis shows the following: although the social‐network structure influences the authority of experts, the influence weakens when the assessment group is a highly or even fully connected group; the network effect may increase the authority of some experts and reduce that of others, and it will weaken as the network connectivity increases; moreover, the judgement reliability and authority of an expert while considering post‐evaluation can encourage him/her to make fair assessments and strive to reduce his/her motivation and cognitive biases.     

From text to graph: a general transition-based AMR parsing using neural network

Neural Computing and Applications - Semantic understanding is an essential research issue for many applications, such as social network analysis, collective intelligence and content computing,...     

Proactive replication for rare objects in unstructured peer-to-peer networks

Unstructured peer-to-peer (P2P) networks have become a very popular architecture for content distribution in large-scale and dynamic environments. The search efficiency problem in unstructured P2P networks has not been adequately addressed so far, especially concerning search for rare objects. In this paper, we propose a proactive replication strategy to improve search efficiency for rare objects. It uses an object-probing technique for peers to decide whether or not to establish replications for their objects when they join the network. This strategy can effectively increase the popularity of rare objects in order to enhance search efficiency. We also present a rare object search algorithm to reduce the overhead caused by the replication strategy. When a peer forwards a search request, the forward probability is calculated according to its neighbors' degrees and the number of neighbors' objects. Therefore, the search request is forwarded to the peers more likely containing target objects. Simulations show that our proactive replication strategy greatly improves search efficiency for rare objects with moderate communication overhead. The rare object search algorithm not only improves search efficiency for rare objects, but also achieves load balance in search.