大规模生物网络马尔可夫聚类的并行化算法

马尔可夫聚类算法（MCL）是在大规模生物网络中寻找模块的一个有效方法，能够挖掘网络结构和功能影响力较大的模块。算法涉及到大规模矩阵计算，因此复杂度可达立方阶次。针对复杂度高的问题，提出了基于消息传递接口（MPI）的并行化马尔可夫聚类算法以提高算法的计算性能。首先，生物网络转化成邻接矩阵；然后，根据算法的特性，按照矩阵的规模判断并重新生成新矩阵以处理非平方倍数矩阵的计算；其次，并行计算通过按块分配的方式能够有效地实现任意规模矩阵的运算；最后，循环并行计算直至收敛，得到网络聚类结果。通过模拟网络和真实生物网络数据集的实验结果表明，与全块集体式通信（FCC）并行方法相比，平均并行效率提升了10个百分点以上，因此可以将该优化算法应用在不同类型的大规模生物网络中。     

一种基于小字典不对等语料的跨语言词嵌入方法

双语词嵌入通常采用从源语言空间到目标语言空间映射,通过源语言映射嵌入到目标语言空间的最小距离线性变换实现跨语言词嵌入。然而大型的平行语料难以获得,词嵌入的准确率难以提高。针对语料数量不对等、双语语料稀缺情况下的跨语言词嵌入问题,该文提出一种基于小字典不对等语料的跨语言词嵌入方法,首先对单语词向量进行归一化,对小字典词对正交最优线性变换求得梯度下降初始值,然后通过对大型源语言(英语)语料进行聚类,借助小字典找到与每一聚类簇相对应的源语言词,取聚类得到的每一簇词向量均值和源语言与目标语言对应的词向量均值,建立新的双语词向量对应关系,将新建立的双语词向量扩展到小字典中,使得小字典得以泛化和扩展。最后,利用泛化扩展后的字典对跨语言词嵌入映射模型进行梯度下降求得最优值。在英语—意大利语、德语和芬兰语上进行了实验验证,实验结果证明该文方法可以在跨语言词嵌入中减少梯度下降迭代次数,减少训练时间,同时在跨语言词嵌入上表现出较好的正确率。     

On global Hessenberg based methods for solving Sylvester matrix equations

In the first part of this paper, we investigate the use of Hessenberg-based methods for solving the Sylvester matrix equation $AX+XB=C$. To achieve this goal, the Sylvester form of the global generalized Hessenberg process is presented. Using this process, different methods based on a Petrov–Galerkin or on a minimal norm condition are derived. In the second part, we focus on the SGl-CMRH method which is based on the Sylvester form of the Hessenberg process with pivoting strategy combined with a minimal norm condition. In order to accelerate the SGl-CMRH method, a preconditioned framework of this method is also considered. It includes both fixed and flexible variants of the SGl-CMRH method. Moreover, the connection between the flexible preconditioned SGl-CMRH method and the fixed one is studied and some upper bounds for the residual norm are obtained. In particular, application of the obtained theoretical results is investigated for the special case of solving linear systems of equations with several right-hand sides. Finally, some numerical experiments are given in order to evaluate the effectiveness of the proposed methods.     

On the Barzilai-Borwein basic scheme in FFT-based computational homogenization

Building upon the equivalence of the basic scheme in the work of Moulinec and Suquet with gradient descent methods, we investigate the effect of using the celebrated Barzilai-Borwein step size selection technique in this context. We provide an overview of recent convergence theory and present efficient implementations in the context of computational micromechanics, with and without globalization. In contrast to polarization schemes and fast gradient methods, no lower bound on the eigenvalues of the material tangent is necessary for the Barzilai-Borwein scheme. We demonstrate the power of the proposed method for linear elastic and inelastic large scale problems with finite and infinite material contrast.     

Studying the effect of particle size on the antibacterial activity of some N-nicotinyl phosphoric triamides

Using ultrasonic top-to-down method, nanoparticles of two N-nicotinyl phosphoric triamides: C₅H₄NC(O)NHP(O)R, R?=?4-CH₃-NC₅H₁₀ (1), (CH₃)₃CNH₂ (2) were prepared for the first time and characterized by ³¹P, ¹³C, ¹H NMR, FTIR, scanning electron microscopy, energy dispersive X-ray. The average particle size of 1 and 2 were 60–70 and 40–50?nm, respectively, and the morphology was spherical for 1 and rod for 2. Solid state (powder) antibacterial effect of these compounds and two other similar reported ones, in their macro- and nanosizes, were evaluated with colony counting method on one Gram-positive (Staphylococcus aureus) and one Gram-negative (Escherichia coli) bacteria in Brain–Heart infusion culture medium. Results showed that all the macro- and nanosized compounds, except macrosized 1, were antibacterial and all nanoscaled ones had stronger antibacterial activity than their macroscaled analogues. The most effect of the particle size was observed for 1: by decreasing the particle sizes, the antibacterial activity state of 1 was changed from inactive (for macro) to potent (for nano).     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

载气热提取法测定熔敷金属中扩散氢收集条件的探究

探究了GB/T 3965—2012《熔敷金属中扩散氢测定方法》中载气热提取法收集条件对测定扩散氢含量的影响,并与水银法进行了对比。研究结果表明,样本炉温设定为400℃,A型试块的内部温度大约在51 min时稳定在358℃左右,B型试块内部温度大约在27 min时稳定在391℃左右;载气热提取法电信号曲线收集结束点的电信号及斜率均接近0时获得的结果与水银法具有较好的一致性。     

Modification of the Wu-Mendel approach for linguistic summarization

This paper presents versatile modification of the Wu-Mendel approach for linguistic summarisation and concentrates on eliminating the following main drawbacks of the approach: significant user/expert involvement, significant and rapidly increasing computational cost, some flaws in quality measures formulae. The techniques and formulae proposed to eliminate the aforesaid drawbacks are put through the experimental verification process involving several real-world datasets. The results of the experimental verification demonstrate the increased efficiency and effectiveness of the modified Wu-Mendel approach for linguistic summarisation.