合金元素对6063铝合金组织性能的影响

以Al-Mg-Si系6063铝合金为研究对象，采用试验的方法研究了主要合金元素Mg、Si和杂质元素Fe,Zn对合金组织性能的影响，并在分析作用机理的基础上给出了改善材料性能的合理化建议。研究表明，主要合金元素Mg、Si对材料的强度和腐蚀性能有重要影响，生产实际中应使二者质量之比略小于正常值1．73；杂质元素Fe、Zn对合金组织的稳定性有一定影响，一般会使制品表面出现不同程度的点缺陷。     

改善铝合金导热性能途径的初探与分析

讨论晶粒细化、热处理制度、合金元素及稀土添加剂对6063铝合金导热性能的影响,在分析实验数据的基础上,阐述了各影响因素的作用机理.结果表明良好的铸态组织、适宜的时效制度、合理的合金元素配比与适量稀土处理剂均能不同程度的提高材料的导热系数.     

基于PSO-SVM的小电流接地故障选线方法

针对小电流接地系统,现有故障选线方法的精度不高,为此提出基于粒子群优化向量机（PSO‐SVM ）的选线方案。在搭建小电流接地系统仿真模型的基础上,采用M atlab进行PSO优化算法仿真实验,根据不同的接地情况获得故障时各线路零序电流,利用小波包变换（WPT ）与傅里叶变换（FFT ）从零序电流中提取暂态分量、谐波分量、五次谐波分量作为PSO‐SVM输入特征进行训练,用训练好的SVM 对测试样本行检测,得到选线结果。仿真结果表明,该方法使学习训练速度加快、自适应能力增强、选线精度提高进,且其不受接地电阻、故障距离等因素影响。     

Secure three-party computational protocols for triangle area

In this work, we have put forth two different protocols to address a concrete secure multi-party computational (MPC) problem related to a triangle, of which the coordinates of the three vertices are confidentially kept by the three participants, respectively. The three parties wish to collaboratively compute the area of this triangle while preserving their own coordinate privacy. As one of the merits, our protocols employ weaker assumptions of the existence of pseudorandom generators. In particular, unlike massive secure MPC protocols that rely a lot on oblivious transfer, ours utilize a new computing idea called “pseudorandom-then-rounding” method to avoid this burdensome obstacle. The two protocols are based on different theorems, while they both make use of the same underlying idea. At last, we provide a detailed proof for the first protocol by a series of security reductions of our newly defined games, which seems somewhat stronger than the previous simulation-based proofs and a proof sketch for the second one. Analysis and discussion about the reasons are provided as well to round off our work.     

模块主成分分析在人脸重建中的应用

模块主成分分析是人脸重建中一种重要的子空间学习方法,鲁棒性不足是传统的基于L2范数的模块主成分分析(BPCA-L2)的主要问题。为此,提出了一种新的基于L1范数的模块主成分分析(BPCA-L1)方法。该方法使用了对奇异值不太敏感的L1范数。基于L1范数的模块主成分分析方法简单并易于实现,在一些人脸数据集上的重建实验验证了其有效性。     

Improving MapReduce Performance with Partial Speculative Execution

The MapReduce framework has become the de facto standard for big data processing due to its attractive features and abilities. One is that it automatically parallelizes a job into multiple tasks and transparently handles task execution on a large cluster of commodity machines. The increasing heterogeneity of distributed environments may result in a few straggling tasks, which prolong job completion. Speculative execution is proposed to mitigate stragglers. However, the existing speculative execution mechanism could not work efficiently as many speculative tasks are still slower than their original tasks. In this paper, we explore an approach to increase the efficiency of speculative execution, and further improve MapReduce performance. We propose the Partial Speculative Execution (PSE) strategy to make speculative tasks start from the checkpoint. By leveraging the checkpoint of original tasks, PSE can eliminate the costs of re-reading, re-copying, and re-computing the processed data. We implement PSE in Hadoop, and evaluate its performance in terms of job completion time and the efficiency of speculative execution under several kinds of classical workloads. Experimental results show that, in heterogeneous environments with stragglers, PSE completes jobs 56 % faster than that with no speculation and 12 % faster than that with LATE, an improved speculative execution algorithm. In addition, on average PSE can improve the efficiency of speculative execution by 24 % compared to LATE.     

水资源复合系统协调性指标体系构建与调控措施研究

根据复合系统协调性理论,通过分析水资源复合系统内水资源子系统、社会经济子系统和生态环境子系统两两之间的相互作用关系,以全新的视角构建了水资源复合系统协调性评价指标体系,并针对指标反映的系统特征和系统间关系相应地提出了子系统之间协调性调控措施。     

基于VB技术开发学校电教管理系统

对区域性的学校电教管理系统的开发做了详细阐述,并提出了详细的解决方案。     

Characterising effective eLearning resources

The widespread availability of digital learning resources in a variety of media formats offers the possibility to make a profound difference in education. This potential has not been fully realised for range of interrelated reasons. In this paper we study the key characteristics of learning resources that have proved effective in changing learning and teaching, and relate them to existing frameworks for understanding resources. We outline the relationships between resources, their users, and the way they are used, and explore issues that influence practitioners in choosing a particular resource. Our study is based on a review of resources for e-learning and chemistry in post-compulsory education, undertaken for the UK Joint Information Systems Committees (JISC), as part of a wider study examining ‘The Effectiveness of Resources, Tools and Support Services used by Tutors in Designing and Delivering E-Learning Activities’.     

蚁群遗传算法的多目标优化

为了求解带有约束条件的多目标函数优化问题,提出基于连续空间优化的多目标蚁群遗传算法。针对多目标优化问题的特点,定义连续空间中利用信息量指导遗传搜索策略和信息更新方法,将信息量指导遗传搜索、优秀决策引入、决策集更新、改变算法终止条件等方式相结合,有效地加速了搜索的收敛速度,控制了Pareto最优决策集的数量,扩大了决策的分布范围,维持了决策的多样性。数值实验说明该算法能够快速找到一组分布广泛的Pareto最优决策。