基于贝叶斯网络的多目标优化算法

针对多目标进化算法中存在的无效进化和计算浪费,本文探讨了基于贝叶斯网络的多目标进化算法,并提出一个新的贝叶斯多目标优化算法。该算法结合个体的强度值和密度值完成非劣择优,利用具有局部结构BD度量机制进行网络度量,采用树形模型构建网络结构。实验结果表明了该算法的有效性。     

Using Bytecode Instruction Counting as Portable CPU Consumption Metric

Accounting for the CPU consumption of applications is crucial for software development to detect and remove performance bottlenecks (profiling) and to evaluate the performance of algorithms (benchmarking). Moreover, extensible middleware may exploit resource consumption information in order to detect a resource overuse of client components (detection of denial-of-service attacks) or to charge clients for the resource consumption of their deployed components. The Java Virtual Machine (JVM) is a predominant target platform for application and middleware developers, but it currently lacks standard mechanisms for resource management.In this paper we present a tool, the Java Resource Accounting Framework, Second Edition (J-RAF2), which enables precise CPU management on standard Java runtime environments. J-RAF2 employs a platform-independent CPU consumption metric, the number of executed JVM bytecode instructions. We explain the advantages of this approach to CPU management and present five case studies that show the benefits in different settings.     

软件质量度量元的理想取值区间反推技术

针对软件质量度量元理想取值区间难以确定的问题,指出在推导一个度量元的理想取值区间时,应结合特定的（用户关心的）外部质量指标进行考虑,研究并提出了基于正交设计思想的度量元理想取值区间反推技术,该技术能够量化地给出度量元的理想取值区间,初步解决了度量元质量需求定义的问题。     

Reliability of force–time curve characteristics during maximal isometric leg press in differently trained high-level athletes

The aim of this research was to establish the metrologic values of the isometric force–time characteristics of leg extensors in differently trained, healthy male athletes and non-athletes. 99 subjects performed a standardized “isometric leg press” test. Even though the results showed a high statistical significance in terms of representativeness, generalizability and reliability for all contractile characteristics of observed measured variables, different methodological approaches were required in order to obtain the most valid results for differently trained and untrained subjects. Based on the results obtained, and from the aspect of the methodology of testing different isometric force characteristics, it was possible to conclude that the standardization of the isometric leg press requires two trials in football, where the most reliable data was from the first trial (the communality rates (H²) from 0.866 to 0.969). Water polo and basketball require three trials. The most reliable data was from the third and second trial in water polo (H² from 0.909 to 0.986). In basketball the most reliable data was from the second trial (H² from 0.824 to 0.987). The untrained healthy adult population requires four trials, and the most reliable data was from the third trial (H² from 0.961 to 0.995).     

基于三元采样图卷积网络的半监督遥感图像检索

该文提出了一种基于三元采样图卷积网络的度量学习方法,以实现遥感图像的半监督检索。所提方法由三元图卷积网络(TGCN)和基于图的三元组采样(GTS)两部分组成。TGCN由3个具有共享权重的并行卷积神经网络和图卷积网络组成,用以提取图像的初始特征以及学习图像的图嵌入。通过同时学习图像特征以及图嵌入,TGCN能够得到用于半监督图像检索的有效图结构。接着,通过提出的GTS算法对图结构内隐含的图像相似性信息进行评价,以选择合适的困难三元组(Hard Triplet),并利用困难三元组组成的样本集合对模型进行有效快速的模型训练。通过TGCN和GTS的组合,提出的度量学习方法在两个遥感数据集上进行了测试。实验结果表明,TGCN-GTS具有以下两方面的优越性：TGCN能够根据图像及图结构学习到有效的图嵌入特征及度量空间;GTS有效评估图结构内隐含的图像相似性信息选择合适的困难三元组,显著提升了半监督遥感图像检索效果。     

基于多幅未标定图像的三维度量重构

提出了一种基于多幅未标定图像，恢复场景三维几何的优化矩阵分解算法，该算法先通过迭代逼近得到射影重构，然后通过估计绝对二次曲面，将射影重构更新到度量重构。采用真实图像测试，获得好的实验结果，说明该方法简单易用。     

匹配位置对比特流随机性的影响研究

本文阐述了IP报文标识字段比特流随机性的评价标准,通过对大量实测报文进行统计分析证明了比特流的匹配位置对随机测度值有一定影响。结果表明,标识字段比特流随机测度值随着比特流长度的增加整体上呈递减趋势。对相同长度的比特流而言,右优先比特流随机测度值普遍最高,左优先比特流随机测度值普遍最低,其它位置比特流随机测度值普遍介于两者之间。     

健康运行的3G网络评价要素探讨

文章回顾了3G UMTS无线技术标准选拔、制定要素和近年移动网品质关注由QOS转向QOE的研究成果,并据此分析论述了这些指标体系对网络运行评价的影响,提出了提升网络运行健康质素的技术侧的思路建议。     

弯扭斜交网格结构参数化设计中的几何学理论与方法

从2008年北京奥运会主场馆鸟巢开始,国内出现了一批弯扭斜交网格结构造型的建筑,其中最具代表的是北鸟巢南春茧和北京凤凰国际中心。弯扭斜交网格结构以其优美而独特造型深受建筑师青睐。本文将几何学理论联系工程实际,给出了两种用于弯扭斜交网格结构参数化设计的几何方法。其一,用微分几何方法对弯扭斜交网格结构几何形体进行分析,给出其表面所在曲面参数方程的分析表达。其二,用运动学的观点,通过活动标架、扫掠及放样等造型方法,利用计算机辅助图形学方法得到弯扭斜交网格结构几何模型。两种方法的有效性通过2022年杭州亚运会乒乓球馆设计实践得到了验证。     

An empirical evaluation of intrinsic dimension estimators

We study the practical behavior of different algorithms and methods that aim to estimate the intrinsic dimension (IDim) in metric spaces. Some of them were specifically developed to evaluate the complexity of searching in metric spaces, based on different theories related to the distribution of distances between objects on such spaces. Others were originally designed for vector spaces only, and have been extended to general metric spaces. To empirically evaluate the fitness of various IDim estimations with the actual difficulty of searching in metric spaces, we compare two representatives of each of the broadest families of metric indices: those based on pivots and those based on compact partitions. Our conclusions are that the estimators Distance Exponent and Correlation fit best their purpose.