A robust edge detection method with sub-pixel accuracy

In this paper, a new edge detection approach combining gray-moments operator with smoothing spline algorithm is proposed, which is invariant to additive and multiplicative noises in the image. This approach consists of two steps: firstly, a continuous blurred edge model is obtained using the smoothing spline algorithm in the edge region detected by Sobel operator; then a gray-moment solution is derived for both the one- and two-dimensional situations using the blurred edge model. Testing of this new detection approach demonstrates more robustness against the white Gaussian noise and speckle noise, and run time very close to the gray-moment and space-moment operators. The above advantages indicate this approach is very suitable for on-line accurate detection.     

A genetic algorithm-based approach for solving the target Q-coverage problem in over and under provisioned directional sensor networks

Target coverage and network lifetime extension have been addressed as two major research topics over the last two decades. This paper focuses on “target $Q$-Coverage” in Directional Sensor Networks (DSNs) where coverage requirement of each target in the environment differs from that of the others. In such network, how to achieve the coverage requirement and simultaneously prolong the network lifetime is a major problem. In this study, two target-oriented genetic-based algorithms were developed to solve the problem. The first algorithm was developed to cover the targets in an over-provisioned environment, and the second algorithm was developed in an under-provisioned environment. The main objective of the first algorithm is satisfying the coverage requirement of targets by activating minimal sensors, while the second algorithm was developed to achieve a maximum balanced coverage for all the targets in the network. To evaluate the performance of the developed algorithms, they were compared with some state-of-the-art algorithms presented in recent studies. In this regard, several parameters, including Distance Index, Q-Balancing Index, Coverage Quality, Power Consumption, and Activate Sensors were taken into account. The comparative results indicated that the developed algorithms performed efficiently in solving the $Q$-coverage problem in both environments.     

基于改进遗传算法的移动机器人路径规划

针对传统遗传算法存在的搜索效率低、易于陷入局部最优解的问题,提出了一种改进的遗传算法。采用简单的一维编码替代复杂的二维编码,节约了存储空间。在遗传算子的设计中,重新定义了交叉算子和变异算子,避免了陷入局部最优。最后将最短路径和免碰撞相结合作为适应度函数进行遗传优化。实验结果表明,改进的算法能够快速、有效的规划出最优路径。     

基于亚像素扫描的超分辨技术在高分辨X射线显微镜中的应用

在不改变现有硬件条件的情况下,开展超分辨扫描重建方法,可以在不增加系统成本的基础上提高高分辨X射线显微镜的成像性能.设计了基于亚像素扫描的超分辨扫描模式,按照设计的调制方式进行亚像素位移的移动,采集多幅具有互补信息的低分辨率图像;然后基于系统的点扩散函数,对高分辨率图像进行复原;最后结合POCS超分辨重建算法重建出高分辨图像.实验结果表明,10倍光耦探测器下的衬度噪声比提高了20%左右,空间分辨力提高了0.2μm(约15%),细节分辨能力超过探测器像素尺寸1.35μm的限制,可以看到在低分辨率图像中看不到的细节.实验说明用超分辨技术提高高分辨X射线显微镜的分辨率是有意义的.     

Designing a genetic watermarking approach for 3D scenes

A new watermarking algorithm based on genetic algorithm (GA) in the transform domain is proposed. Unlike the existing computer-generated integral imaging based watermarking methods, the proposed method utilizes GA searching to the optimized transform domain to serve as a trade-off for watermark embedding. In this paper, 3D scene to be captured by using a virtual pinhole array and be computationally recorded as an elemental image array (EIA), watermarking with GA optimization and computer-generated holography is implemented. In the proposed GA optimization process, we utilize the fitness function to improve the visual quality of watermarked images and the robustness. Simulation results show that the proposed algorithm yields a holographic watermark that is imperceptibility to human eyes and robust to standard watermarking attacks. A comparison of the proposed watermarking method to the existing similar watermarking methods demonstrated that the proposed method generally outperforms completing methods in terms of imperceptibility and robustness.     

一种新的遗传算法交叉算子及其在GNSS星座选择中的应用

针对全球导航卫星系统（GNSS）星座选择的需要,分析了多星座卫星导航定位系统选星问题的数学描述形式,根据选星问题的实质要求,将选星问题转换为单约束组合优化问题。而在采用遗传算法求解诸如选星求解类组合优化问题时,由于其对1基因（或0基因）的数量有特别的约束要求,已有的一些交叉算子不能满足该约束要求。针对基因数约束条件,提出了一种新的交叉算子——变异交叉,新的交叉算子仅以1基因或0基因为交换对象实现交叉操作来产生原始后代、以变异作为辅助方式来实现后代的合法化。实验结果表明,所提出的交叉算子能有效应用于遗传算法实现多星座卫星导航定位系统选星求解,且运算量较少,可以实现简单、快速求解,满足实时选星要求。     

Modified Heisenbeg Model and the Structure of Its Energy Spectrum

In this paper, we show the interesting structure of energy spectrum for a modified Heisenberg XX model, explicit examples for low dimensions N=2,3,…,6 are also provided.     

Broad omnidirectional high-precision filters design using genetic algorithm

An application of the genetic algorithm in designing omnidirectional optical filters is reported in this paper. Concerning different periodic numbers and thickness ratios in the heterostructure, we gave some optimization examples and finally achieved a photonic heterostructure with very broad omnidirectional filter bandwidth as well as a very narrow transmission window. And it is found that when the normal incident beam is tilted at a negligibly small angle, the perfect transmittance peak will vanish. Hence, this heterostructure can be regarded as omnidirectional high-precision filters with potential application in optical filters, optical switches, and many other optical telecommunication areas.     

基于复合胞化空间的图胞映射方法

为了提高计算的准确性和效率,通过引入复合胞化空间概念,构建了一种迭代的图胞映射方法.该方法能够对任意感兴趣的空间区域进行细化处理,细化过程采用代数运算完成不会额外增加计算机内存且能保持细化前后图动力系统性质不变.为了便于计算机实施,也给出了相应的有效算法.通过对典型例子Henon映射的应用分析,证实了该方法的有效性. 关键词： 图胞映射方法 迭代方法 Henon映射     

Using genetic algorithms to characterize ferrofluid topographies in externally applied magnetic fields

Both ferrofluidics and genetic algorithms are relatively new fields. Due to complex physical interactions, ferrofluidic topographies and assemblies have only been solved using finite time step, Lattice Boltzmann, and finite-element methods in very simple magnetic field configurations. In this paper, we show that it is possible (and highly advantageous) to employ genetic algorithms to solve for the fluid topographies, which can be extended to include more complex magnetic fields.     

Low-threshold performance of fiber Bragg grating external-cavity semiconductor lasers using genetic algorithms

The lowest threshold current of the external-cavity semiconductor laser with fiber Bragg grating using genetic algorithms is investigated. Effects of the external cavity length, coupling efficiency and anti-reflection coating reflectivity on static characteristics, such as L-I curves and side mode suppression ratios (SMSR) are investigated by using multi-mode rate equation. It is found that the reflectivity of the anti-reflection coating for low-threshold performance needs to be increased at the cost of the stability of the fiber grating external-cavity semiconductor laser. The optimal external cavity length obtained by genetic algorithms can be used to obtain the lowest threshold current for sacrificing a little SMSR. However, with the decrease of AR-coating reflectivity, output powers and SMSRs are slightly dependent on the external cavity length.     

说话人识别使用遗传RBF网络

针对RBF网络普遍采用的一种训练算法所存在的局部最佳问题,本文将遗传算法用于RBF网络训练过程,增强了该网络的全局寻优能力,提高了RBF网络的模式识别性能.说话人识别实验显示,改进训练算法后,RBF网络的说话人识别率有稍许提高.     

Finding the reconstructions of semiconductor surfaces via a genetic algorithm

In this article we show that the reconstructions of semiconductor surfaces can be determined using a genetic procedure. Coupled with highly optimized interatomic potentials, the present approach represents an efficient tool for finding and sorting good structural candidates for further electronic structure calculations and comparison with scanning tunneling microscope (STM) images. We illustrate the method for the case of Si(1 0 5), and build a database of structures that includes the previously found low-energy models, as well as a number of novel configurations.     

Homotopic mapping solution of an oscillator for the El Nino / La Nina-southern oscillation

This paper considers a class of oscillator for the El Nin o/La Nin a-southern oscillation (ENSO) model.By using the homotopic mapping method,it obtains approximations of the solution for the ENSO model.     

Community detection based on modularity and an improved genetic algorithm

Complex networks are widely applied in every aspect of human society, and community detection is a research hotspot in complex networks. Many algorithms use modularity as the objective function, which can simplify the algorithm. In this paper, a community detection method based on modularity and an improved genetic algorithm (MIGA) is put forward. MIGA takes the modularity Q$Q$ as the objective function, which can simplify the algorithm, and uses prior information (the number of community structures), which makes the algorithm more targeted and improves the stability and accuracy of community detection. Meanwhile, MIGA takes the simulated annealing method as the local search method, which can improve the ability of local search by adjusting the parameters. Compared with the state-of-art algorithms, simulation results on computer-generated and four real-world networks reflect the effectiveness of MIGA.     

Empirical pseudopotential band structure parameters of 4H-SiC using a genetic algorithm fitting routine

In this paper, the viability of using a genetic algorithm to find band structure parameters for empirical pseudopotential method (EPM) calculations is demonstrated by applying a genetic algorithm to find the EPM parameters for 4H-SiC. The form of the pseudopotential for 4H-SiC and the 19 form factors found by the genetic algorithm to fit the band structure to experimentally measured indirect energy gap and direct optical gaps are given. In addition, the effective masses for the conduction band minimum are extracted from the calculated band structure. It is shown that the genetic algorithm provides an effective, automated way to find parameters that give reasonably good fits to both the band gaps and the effective masses simultaneously.     

Thermal characterization of dielectric thin films using an improved genetic algorithm

This paper presents theoretical and experimental investigations of the thermal conductivity and the contact resistance of dielectric materials deposited as thin films. Silicon dioxide and poly(p-phenylene) films deposited on alumina substrates are studied in order to determine simultaneously the thermal conductivity of the film and the resistance of the contact between the film and the substrate. Measurements are obtained by using a photothermal technique, and an improved genetic algorithm (GA), especially suitable for thermal characterizations of thin film structures in the sub-micron range. A theoretical study for evaluating the optimal conditions for the photothermal measurements is presented. This is done by studying the sensitivity of the unknown parameters to the thin film thickness and to the properties of the materials. As the photothermal analysis is basically performed in unsteady state conditions, this study highlights the relation between the intrinsic and effective conductivity of the materials.     

Optimisation with genetic algorithm of the acoustic performance of T-shaped noise barriers with a reactive top surface

In this study, the aim is to optimise the acoustical efficiency of T-shaped noise barriers whose top is covered with a series of wells. This research work uses an optimisation method in order to find the best noise barrier profile considering several variable parameters. Numerical simulations of the acoustical propagation are achieved by use of a 2D boundary element method code. The optimisation part is carried out with a global and direct evolutionary optimisation method: a genetic algorithm. The parameters to optimise are the shape of the protection (the depths of the wells on the crowning) and the flow resistivity of absorbing materials considered. The cost function to maximize is defined through a mean value of the acoustical efficiency of the protection compared to a reference configuration, averaged on several receiver points. Final results show significant optimised values of parameters for efficient protections in order to improve classical noise barriers.     

Optimal design of acoustical sandwich panels with a genetic algorithm

An optimization study is performed to design a sandwich panel with a balance of acoustical and mechanical properties at minimal weight. An acoustical model based on higher-order sandwich beam theory is used with mechanical analysis of the maximum deflection at the center of the sandwich panel under a concentrated force. First, a parametric study is performed to determine the effects of individual design variables on the sound transmission loss of the sandwich panel. Next, by constraining the acoustical and mechanical behavior of the sandwich panel, the area mass density of the sandwich panel is minimized using a genetic algorithm. The sandwich panels are constructed from eight face-sheet and sixteen core materials, with varying thicknesses of the face sheets and the core. The resulting design is a light-weight, mechanically efficient sound insulator with strength and stiffness comparable to sandwich structures commonly used in structural applications.     

改进的线性混合模型用于高光谱分离实验模拟

从考虑成份光谱的噪声出发,提出了改进的线性混合模型来补偿成份光谱噪声的影响,并在假定成份光谱和混合光谱噪声源于同一噪声源的前提下,给出了改进线性模型的数学求解过程及数值计算思路,且通过合成的含噪声的混合光谱对两种方法做了对比验证,实验证明:改进的线性混合模型有效地克服传统线性模型的不足,大大减弱了成份光谱的噪声对计算精度的影响.