Numeral eddy current sensor modelling based on genetic neural network

This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network （GNN） according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method.     

遗传算法用于多组分拉曼光谱定量分析的研究

拉曼光谱是一种分子散射光谱,利用物质的特征拉曼光谱,可实现对其结构、成分、浓度等的检测.多组分物质拉曼光谱的定量分析是一个有待深入研究的课题.采用遗传算法程序对10组分的混合矿石样品的拟合拉曼光谱数据进行了分析,对同一条件下算法多次计算的结果和不同条件下算法的表现进行了讨论,分析了算法设计和基本参数的不同对算法收敛速度以及对计算结果的精确性和稳定性的影响,验证了遗传算法用于多组分样品拉曼光谱数据分析的可行性、有效性和精确性.     

Seasonal variability of cloud optical depth over northwestern China derived from CERES/MODIS satellite measurements

The seasonal variability of cloud optical depth over northwestern China derived from Clouds and the Earth＇s Radiant Energy System （CERES） Single Scanner Footprint （SSF） Aqua Moderate Resolution Imaging Spectroradiometer （MODIS） Edition IB data from July 2002 to June 2004 is presented. The regions of interest are those with Asia monsoon influence, the Tianshan and Qilian Mountains, and the Taklimakan Desert. The results show that the instantaneous measurements presented here are much higher than the previous results derived from International Satellite Cloud Climatology Project （ISCCP） D2 monthly mean data. Generally the measurements of cloud optical depth are the highest in summer and the lowest in winter, however, Taklimakan Desert has the lowest measurements in autumn. The regional variation is quite significant over northwestern China.     

Characterization and comparison of metal accumulation in two Escherichia coli strains expressing either CopA or MntA, heavy metal-transporting bacterial P-type adenosine triphosphatases

MntA from Lactobacillus plantarum and copA from Enterococcus hirae both encode membrane proteins that are members of the P-type family of adenosine triphosphatases (ATPases). Both transporters act as metal importers to take up nutritionally required substrates; MntA translocates Mn(II) and CopA translocates Cu(I). Both ATPases can also translocate secondary substrates, Cd(II) and Ag(I), respectively. Although functionally and sequentially similar, these ATPases differ in several key residues and in their membrane topologies. The bioaccumulation properties of these two proteins were examined by coexpressing the transporters with overexpressed metallothionein in Escherichia coli cells, a system that has previously shown high levels of substrate-specific uptake. Both strains exhibited rapid metal accumulation, both saturated at around 50 μM metal, and both displayed temperature-sensitive uptake. However, the transporters responded differently when external conditions were varied; MntA displayed increased sensitivity to ionic strength, while CopA was more pH sensitive and more inhibited by chelating agents. The differences in accumulation are likely owing to structural differences in the transmembrane region of these two ATPases.     

Matrix Continued Fraction for the Resolvent Function of the Band Operator

The aim of this paper is the expansion of a matrix function in terms of a matrix-continued fraction as defined by Sorokin and Van Iseghem. The function under study is the Weyl function or resolvent function of an operator, given in the standard basis by a bi-infinite band matrix, with p subdiagonals and q superdiagonals, where the p + q – 1 intermediate diagonals are zero. The main goal of this paper is to find, for the moments, an explicit form in terms of the coefficients of the continued fraction, called genetic sums, which lead to a generalization of the notion of a Stieltjes continued fraction. These results are extension of some results already found for the vector case (p = 1) and are a step in the direction towards the solution of the direct and inverse spectral problem. The actual computation of the approximants of the given function as the convergents of the continued fraction is shown to be effective. Some possible extensions are considered.     

Efficient inverse radiation analysis in a cylindrical geometry using a combined method of hybrid genetic algorithm and finite-difference Newton method

An inverse radiation problem was considered to estimate boundary conditions such as temperature distribution and emissivity in axisymmetric absorbing, emitting, and scattering medium, given the measured incident radiative heat fluxes. The finite-volume method was employed to solve a direct radiative transfer equation for a two-dimensional axisymmetric geometry. Various parameter estimators, such as conjugate-gradient method, hybrid genetic algorithm, and finite-difference Newton method, were employed to solve the inverse problems, while discussing their performances in terms of estimation accuracy and computational efficiency. Based on this, we proposed, as a best inverse analysis tool, a new combined method that adopted the hybrid genetic algorithm as an initial value selector and used the finite-difference Newton method as a parameter estimator.     

Initial guess by improved population-based intelligent algorithms for large inter-frame deformation measurement using digital image correlation

Digital image correlation (DIC) has received a widespread research and application in experimental mechanics. In DIC, the performance of subpixel registration algorithm (e.g., Newton-Raphson method, quasi-Newton method) relies heavily on the initial guess of deformation. In the case of small inter-frame deformation, the initial guess could be found by simple search scheme, the coarse-fine search for instance. While for large inter-frame deformation, it is difficult for simple search scheme to robustly estimate displacement parameters and deformation parameters simultaneously with low computational cost. In this paper, we proposed three improving strategies, i.e. Q-stage evolutionary strategy (T), parameter control strategy (C) and space expanding strategy (E), and then combined them into three population-based intelligent algorithms (PIAs), i.e. genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO), and finally derived eighteen different algorithms to calculate the initial guess for qN. The eighteen algorithms were compared in three sets of experiments including large rigid body translation, finite uniaxial strain and large rigid body rotation, and the results showed the effectiveness of proposed improving strategies. Among all compared algorithms, DE-TCE is the best which is robust, convenient and efficient for large inter-frame deformation measurement.     

Simultaneous analysis of multiple PCR amplicons enhances capillary SSCP discrimination of MHC alleles

Major histocompatibility complex (MHC) genotyping still remains one of the most challenging issues for evolutionary ecologists. To date, none of the proposed methods have proven to be perfect, and all provide both important pros and cons. Although denaturing capillary electrophoresis has become a popular alternative, allele identification commonly relies upon conformational polymorphisms of two single‐stranded DNA molecules at the most. Using the MHC class II (β chain, exon 2) of the black kite (Aves: Accipitridae) as our model system, we show that the simultaneous analysis of overlapping PCR amplicons from the same target region substantially enhances allele discrimination. To cover this aim, we designed a multiplex PCR capable to generate four differentially sized and labeled amplicons from the same allele. Informative peaks to assist allele calling then fourfold those generated by the analysis of single PCR amplicons. Our approach proved successful to differentiate all the alleles (N=13) isolated from eight unrelated birds at a single optimal run temperature and electrophoretic conditions. In particular, we emphasize that this approach may constitute a straightforward and cost‐effective alternative for the genotyping of single or duplicated MHC genes displaying low to moderate sets of divergent alleles.     

Schemata, Distributions and Graphical Models in Evolutionary Optimization

In this paper the optimization of additively decomposed discrete functions is investigated. For these functions genetic algorithms have exhibited a poor performance. First the schema theory of genetic algorithms is reformulated in probability theory terms. A schema defines the structure of a marginal distribution. Then the conceptual algorithm BEDA is introduced. BEDA uses a Boltzmann distribution to generate search points. From BEDA a new algorithm, FDA, is derived. FDA uses a factorization of the distribution. The factorization captures the structure of the given function. The factorization problem is closely connected to the theory of conditional independence graphs. For the test functions considered, the performance of FDA—in number of generations till convergence—is similar to that of a genetic algorithm for the OneMax function. This result is theoretically explained.