Simulating peer-to-peer cloud resource scheduling

Resource scheduling in large-scale distributed systems, such as grids and clouds, is difficult due to the size, dynamism, and volatility of resources. These resources are eclectic and autonomous, and may exhibit different usage policies, levels of participation, capabilities, local load, and reliability. Moreover, applications are likely to exhibit various patterns and levels, and distributed resources may organize into various different overlay topologies for information and query dissemination. Researchers have proposed a wide variety of approaches and policies for mapping offered load onto resources and for solving the various component parts of the scheduling problem. However, production clouds and grids may be underutilized, and may not exhibit the load to effectively characterize all of the scheduling system inputs. The composition of large-scale systems is also changing, potentially to include more individual and peer-to-peer resources. These factors will influence the effectiveness of proposed scheduling solutions. Therefore, a simulation environment is necessary to study different approaches under different scenarios, especially those that are expected, but that are not currently characteristic of existing systems. This article describes a general-purpose peer-to-peer simulation environment that allows a wide variety of parameters, protocols, strategies and policies to be varied and studied. To provide a proof of concept, utilization of the simulation environment is presented in a large-scale distributed system problem that includes a core model and related mechanisms. In particular, this article presents a definition and possible peer-to-peer solutions for the large-scale scheduling problem. Moreover, this article describes a general simulation model, some policies that can be varied, an implementation, and some sample results.     

Organisation and management of shared documents in super-peer networks based semantic hierarchical cluster trees

A super-peer semantic network defines the semantic groups that client peers and their super peers use to connect with each other according to the semantic similarity of shared documents in peers. This will result in a query that can be evaluated locally thus reducing query process time and the amount of communication required to obtain related data. In this study, new algorithms are proposed to arrange shared documents in peers into hierarchical cluster tree structures, and links will be set up to connect semantically related super peers. During query evaluation, only related peers will be searched thus the complexity of computing is significantly reduced. Consideration is also given to automatically deciding the threshold for clustering and the construction and other essential operations for hierarchical cluster trees. The experiment results illustrate the features of the approach developed in this study.     

处理器验证激励在线筛选技术

如何生成高质量的验证激励是功能验证中的核心问题之一.随着功能验证的不断进行,验证激励的有效性也随之降低.为了提高验证激励的质量,提出一种在线筛选技术来处理验证激励.该技术采用单分类支持向量机来在线地构建分类器,以对新生成的验证激励是否冗余进行预测,如果是冗余的,则不进入仿真阶段进行仿真.在此基础上,进一步提出指令序列核函数来衡量不同指令序列的相似程度.实验结果表明,与约束随机生成技术相比,文中技术可以减少约83%的验证激励及79%的验证时间.     

虚拟肝脏的规则和非规则手术切除技术

为了提高肝癌手术治疗计划的可靠性,在利用腹部CT图像数据进行肝脏三维重建的基础上,实现了任意角度对虚拟肝脏进行平面切割和切割面结构的显示;通过构造可以调节大小、位置的球体模型,实现了球体切除;通过在肝脏三维模型表面上勾画不规则封闭区域,实现了任意曲面肝脏切除;并依据肝内血管结构进行肝段划分,实现了解剖性肝段切除.临床实验结果表明,文中所述的技术能够满足虚拟手术的需求,有利于医生制定安全可靠的术前计划,提高手术成功率.     

医院排队叫号系统应用现状综述

为了减少患者在医院的滞留量和高效服务于患者,很多医院都采用了排队叫号系统。医院排队叫号系统产品繁多,医院的实施机制也各不相同,因此分析了目前医院排队叫号系统的应用现状,以及硬、软件实施情况,以求发现系统的主要组成部分和可更新、扩展部分。结合挂号方式、就诊流程优化和物联网技术分析了医院排队叫号系统的发展趋势,这对今后其他领域排队叫号系统的研究有参考意义。     

基于JSP工厂模式的工资查询系统设计与实现

分层思想在JSP技术的开发过程中的优点是层次清楚,这有利于不同程序员分式开发,从而提高效率;但是在应用每一层相关类的时候需要实例化,这会增加系统开销。采用工厂模式在开发过程中向程序员提供一个"工厂"供程序员选择"零件",可以减少实例化次数。工厂开发模式在JSP+tomcat的开发中,可结合分层思想,按照不同的层次进行开发,同时也可独立出公共模块切入到其他模块中,有效地避免了代码重复,提高了开发效率。     

基于损失自注意力机制的立体匹配算法研究

针对现有的立体匹配算法在阴影、物体边缘和光照反射等区域匹配困难且存在大量错误结果的问题,设计了一种可拆卸的损失自注意力网络（loss self-attention net,LSAnet）查找图像中的匹配困难区域。LSAnet的网络各层相互稠密连接,应用了空洞卷积来扩大感受野,并以立体匹配算法生成的损失分布为标签,能够动态地进行有监督训练,最终生成匹配困难区域掩膜辅助立体匹配网络进行更好的优化;同时,改进了立体匹配网络中经典的特征匹配代价卷结构,降低了后续3D卷积的计算负荷,提高了匹配效率。实验结果表明,该算法相比于基准算法精度更高,并且可以提高算法对于匹配困难区域的鲁棒性。     

昌平区地下水位变化特征分析

昌平区近年来水资源的需求量持续增加,供水主体仍然为地下水,然而地下水资源的可利用量却有所降低.利用GIS技术,结合昌平区的水文地质条件,分析了昌平区地下水位年内变化、年际变化特征和地下水埋深的空间分布变化规律.结果表明,地下水位的年内波动较大;年际来看,2009-2015年地下水位逐年下降,自2016年起开始恢复和抬升;与2009年相比,2019年地下埋深大于30 m的区域面积明显增加,小于20 m的区域面积明显缩减,水位平均下降3.62 m,最大下降深度13.86 m,西部降深较大,东部降深较小,八仙庄、东二旗地区水位有所回升.此研究对昌平区地下水资源管理和利用具有重要意义.     

T300/648复合材料迭层板接头挤压疲劳累积损伤问题的实验研究

本篇论文根据“剩余强度,剩余刚度”理论,讨论了碳纤维增强复合材料迭层板承载孔的挤压疲劳损伤,应用孔的永久变形描述损伤的产生和扩展,提出了“损伤函数”的定义和测定方法,并提出了新的“疲劳损伤点”的概念。实验还研究了温度对连接孔静挤压强度和疲劳寿命的影响。实验结果表明,温度的影响尤为重要。对损伤失效试件,采用“揭层方法”、“X射线”及“SEM方法”进行检测和损伤机理的研究。     

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.