求解定常不可压Stokes方程的两层罚函数方法

借助于两套有限元网格空间提出了一种求解定常不可压Stokes方程的两层罚函数方法.该方法只需要求解粗网格空间上的Stokes方程和细网格空间上的两个易于求解的罚参数方程（离散后的线性方程组具有相同的对称正定系数矩阵）.收敛性分析表明粗网格空间相对于细网格空间可以选择很小，并且罚参数的选取只与粗网格步长和问题的正则性有关.因此罚参数不必选择很小仍能够得到最优解.最后通过数值算例验证了上述理论结果，并且数值对比可知两层罚函数方法对于求解定常不可压Stokes方程具有很好的效果.     

Synthesis,spectral, DFT calculations and biological studies of solvatochromic copper(II)-ONS hydrazone derived from 2-aminochromone-3-carboxaldehyde

New ONS hydrazone ligand, 2-[(2-aminochromon-3-yl)methylidene]-N-phenylhydrazinecarbothioamide, HL , was synthesized and reacted with different salts of Cu (II) ion (OAc⁻, NO₃⁻, SO₄²⁻ and Cl⁻) in absence and presence of secondary ligands (L′); 8-hydroxyquinoline, 1,10-phenanthroline or SCN⁻; to form binary and ternary Cu(II)-chelates. The ligand and its Cu(II)-complexes were fully characterized by analytical, spectral, thermal, conductivity and magnetic susceptibility measurements. The metal chelates showed octahedral, square planar and /or distorted tetraherdal arrangements. Coats–Redfern equations used to calculate the kinetic parameters of the thermal decomposition stages (E_a, A, ΔH, ΔS and ΔG). The compounds exhibit luminescence property; promising interesting potential applications as photoactive materials. Lippert–Mataga, Bakhshiev, Kawski–Chamma–Viallet and microscopic solvent polarity parameter and E_T^N correlation methods were applied on the solvatochromic shifts of emission spectra to evaluate the ground (μ_g) and excited (μ_e) states dipole moments. Excited state dipole moment is larger than the ground state which may be attributed to π-π* transition. The coordinating anions play an important role on the position and intensity of emission band. The ligand and its metal complexes showed antimicrobial activity towards Gram–positive bacteria, Gram–negative bacteria, yeast and fungus. The molecular structural parameters of HL and its Cu(II)- complexes have been calculated on the basis of DFT engaged in the Gaussian 09 program at the B3LYP/6-31G(d,p) level; the theoretical data are correlated with the experimental data.     

Measurement of the surface excitation parameter of Kapton,polyethylene (PE), polymethyl methacrylate (PMMA), polystyrene (PS) and polytetrafluoroethylene (PTFE)

Reflection electron energy loss spectra (REELS) were measured for five insulating organic compounds: Kapton, polyethylene (PE), poly(methyl methacrylate) (PMMA), polystyrene (PS) and polytetrafluoroethylene (PTFE), as well as for Ni and Si, in the energy range between 200 and 1600 eV. The average number of surface excitations for a single surface crossing were determined from the experimental data and were found to be considerably smaller than for earlier studied materials, which mainly consisted of elemental metals [Surf. Sci. 486(2001)L461]. The surface excitation parameter, a material parameter used to quantify the relative intensity of surface losses in (photo)electron spectroscopy, was extracted from the data and compared with values found in the literature. The results indicate that surface excitations only have a minor influence on quantification of XPS spectra of polymers. On the other hand, a correction for surface excitations turns out to be essential for measurements of the electron inelastic mean free path of polymers when a metal is used as reference material.     

X射线荧光光谱扩展基本参数法测定不锈钢中的多种成分

针对多种类不锈钢多元素成分解析问题,应用X射线荧光光谱分析软件UniQuant,采用扩展基本参数法对多元不锈钢、双相不锈钢进行光谱干扰校正和基体校正,重新设定和优化多元不锈钢基体元素的测试条件,计算背景因子、杂质因子、谱线灵敏度系数和光谱重叠系数,测定Si、Mn、S、P、Ni、Cr、Cu、Mo、V、Al、Ti、Nb、Co、Ta、Fe的相对标准偏差在0.04%~3.8%,Ca、Zr、W、As、Sb、Sn的相对标准偏差在5.4%~20.3%,未知样品检测值与认定值比对结果相当理想,Ni、Cr的平均偏差小于0.05%,可以用很少标准样品实现各类型不锈钢多元素成分准确检测,检测范围宽,适用性好。     

一类新的(2n-1)点二重动态逼近细分

利用正弦函数构造了一类新的带有形状参数ω的(2n-1)点二重动态逼近细分格式.从理论上分析了随n值变化时这类细分格式的C~k连续性和支集长度;算法的一个特色是随着细分格式中参数ω的取值不同,相应生成的极限曲线的表现张力也有所不同,而且这一类算法所对应的静态算法涵盖了Chaikin,Hormann,Dyn,Daniel和Hassan的算法.文末附出大量数值实例,在给定相同的初始控制顶点,且极限曲线达到同一连续性的前提下和现有几种算法做了比较,数值实例表明这类算法生成的极限曲线更加饱满,表现力更强.     

基于改进的PSO-SVM的音频信号特征识别和分类

针对音频信号准确性分类的问题,提出一种基于改进的的粒子群优化算法(PSO)的支持向量机(SVM)音频信号分类的方法,简称IPSO-SVM.首先用Mel倒谱系数法对4种音频信号进行特征提取.其次在PSO中引入自适应变异因子,能够成功地跳出局部极小值点;然后对PSO中的惯性权重进行了改进,将惯性权重由常数变为指数型递减函数.随着迭代的进行,使权重逐渐减小,这样做有利于粒子进行局部寻优.最后用改进的PSO不断优化SVM中的惩罚因子c和核函数参数g来提高预测精度.实验结果表明,与传统的SVM、PSO-SVM、GA-SVM相比,我们提出的IPSO-SVM算法分类结果更精确.