两阶段不定核支持向量机

近年来,在机器学习的各个领域出现了越来越多不定的度量核矩阵,使得不定核支持向量机(IKSVM)得到了广泛关注。但是,现有IKSVM算法通常不能较好地解决高维数据所带来的信息冗余和样本稀疏等问题。针对此研究现状,对现有主流的IKSVM算法进行了研究,并基于再生核Kre?n空间(RKKS)中对IKSVM问题的稳定化定义,从理论上证明了IKSVM问题的本质为不定核主成分分析(IKPCA)降维后空间中的支持向量机(SVM)问题,进一步地提出求解IKSVM问题的新型学习框架TP-IKSVM。TP-IKSVM通过将IKSVM问题的求解拆分为IKPCA和SVM两个阶段,充分地发挥了IKPCA在处理高维数据的信息冗余和样本稀疏等方面的优势,同时结合SVM以有效分类。在真实数据集上的实验结果表明,TP-IKSVM的分类精度优于现有主流的IKSVM算法。     

轻量级移动支付协议公平性分析

为保证移动支付安全、顺利进行,必须采用安全的移动支付协议。针对计算和存储能力有限的移动设备和不可靠的移动环境,选择采用对称加密的轻量级移动支付协议PCMS,使用串空间理论对其建模,进行形式化分析。通过图的方式直观描述协议的执行过程,分析协议安全目标,基于串空间理论的认证测试方法,对该协议的公平性形式化分析。针对PCMS协议不满足公平性,提出增加时间戳来解决,同时增加一个退款子协议完成后续退款操作。结合模型检测工具验证分析,结果表明,改进后的协议满足公平性。     

Reproducing kernel Hilbert spaces and variable metric algorithms in PDE-constrained shape optimization

In this paper we investigate and compare different gradient algorithms designed for the domain expression of the shape derivative. Our main focus is to examine the usefulness of kernel reproducing Hilbert spaces for PDE-constrained shape optimization problems. We show that radial kernels provide convenient formulas for the shape gradient that can be efficiently used in numerical simulations. The shape gradients associated with radial kernels depend on a so-called smoothing parameter that allows a smoothness adjustment of the shape during the optimization process. Besides, this smoothing parameter can be used to modify the movement of the shape. The theoretical findings are verified in a number of numerical experiments.     

一类分数次Hardy算子的交换子在齐次Morrey—Herz空间上的有界性

先介绍了一类分数次Hardy算子及交换子的概念,然后再结合齐次Morrey--Herz空间的定义,得到此类分数次Hardy算子和单侧二进CMO函数所生成的交换子在齐次Morrey—Herz空间上一些有界性性结果．     

Banach空间有界线性算子加权群逆的存在性

将一类加权群逆的存在性推广到Banach空间有界线性算子,并给出相关结果．     

Banach空间中半线性混合型发展方程mild解的存在性

利用凝聚映像的Sadovskii不动点定理,讨论了Banach空间中一类半线性混合型发展方程初值问题,获得了其mild解的存在性,推广了一些文献的结果.     

复内积空间上的一个等式

讨论了复内积空间上某向量与另一(两)个向量所张成的线性子空间的距离间的关系,得到了复内积空间上有关这些距离的一个等式.利用这一重要等式,首先证明了复内积空间上有关三个向量夹角余弦的一个不等式;其次,将G.Güss不等式在复内积空间下做了进一步的推广;最后利用这一等式对Ostrowski不等式做了推广.     

User scheduling based on angles with block diagonalization in MU‐MIMO broadcast

This paper investigates user selection scheme in the multiuser multiple‐input multiple‐output (MU‐MIMO) broadcast (BC) scene with block diagonalization precoding. Block diagonalization is a suboptimal but practical linear precoding method, which can eliminate the multiuser interference by turning the MU‐MIMO BC channel into parallel MIMO channels. With this precoding method, we propose the best user from the user subset to maximize the total throughput in the MU‐MIMO BC system. The angles between subspaces used in this paper are induced from n ‐inner product, an extension from norm space to the n ‐dimensional space, which characterizes the orthogonality between subspaces. One of the algorithms achieves good performance by comparing the capacity greedily, the other one attains high capacity by reducing the cardinality of the user subset to improve the orthogonality between the user channels, which could be seen as a complexity reduction algorithm with respect to the former one. Indeed, they are all based on the angles between subspaces. Analysis shows that both of the proposed algorithms have lower complexity and better performance than the classical algorithms. The numerical results also confirm our analysis.     

紫薇田园都市国际学校和国家级示范高中

新的教育模式和新的教学理念对校园功能布局、总体规划及单体建筑提出了新的要求。学校创作主题应是创造功能齐全、环境亲切、空间渗透并有时代气息和文化品位的人文学校建筑,紫薇田园都市国际学校和国家级示范高中项目就此作出了尝试。     

Verification of a CFD model for indoor airflow and heat transfer

The SST k–ω based model is applied to calculate air-flow velocities and temperatures in a model office room. Calculations are compared with experiments and with the results of the standard k–ε, the RNG k–ε model and the laminar model. It is concluded that (a) all the three tested turbulent models predict satisfactorily the main qualitative features of the flow and the layered type of temperature fields and (b) computations with the SST k–ω based model show the best agreement with measurements. The use of this model is proposed combined with a suitable grid.