基于改进图分解法的多材料车身结构优化设计方法

针对概念设计阶段的车身结构轻量化设计,提出了一种可实现车身多材料结构设计的分层迭代优化方法。该优化方法的设计变量中,除常见的板厚、材料外,还包括装配设计中的拓扑连接,以实现“将合适的材料用在合适的部位”的要求。分层迭代优化的第1层以拓扑连接为设计变量,采用图分解和NSGA-II对车身装配拓扑结构进行多目标优化,最大化车身弯扭刚度和1阶固有频率;第2层对板厚和材料进行多目标优化,最小化车身质量和材料成本。最终采用基于模糊集合的评分公式选定综合最优解,实现了考虑成本的车身结构轻量化设计。

思维导图分解法的公路工程投标过程风险分析

公路工程通过招标的方式授权给社会中的专业项目管理单位,并让其负责项目的投资管理和建设组织工作。但关于公路工程招投标的制度和监管措施还不够完善,所以这类公路工程招投标还存在一定风险。而运用思维导图分解法则能够很清晰地将公路工程投标过程的风险呈现出来,并在此基础上加强对工程投标风险的控制。本文从公路工程投标的流程、思维导图分解法、公路工程投标过程风险体系的三个方面分析来对公路工程投标过程进行风险分析。

结合思维导图分解法的EPC工程投标风险探究

结合兰州市某EPC工程,总结了EPC工程特点,介绍了投标风险分析流程,并借助思维导图分解法,对投标阶段风险因素进行了分析,提出相应防范措施,确保工程顺利中标,为类似工程提供参考。

几类r-冠图的星边染色

图的星边染色是指图G的一个正常边染色使得G中没有长为4的路或圈是2-边染色的.图G的星边色数是指图G有星边染色的最小颜色数.本文中研究路、圈、扇、轮的r-冠图的星边染色问题.使用图分解法,反证法,染色构造法,组合分析法等方法和理论,得到4类r-冠图的星边色数.

基于模块化设计的车身装配结构优化

本文在考虑车身制造和装配成本的基础上,提出了一种基于图分解算法的车身装配结构设计方法,并为解决以厚度为设计变量进行优化时的收敛问题引入了一种多层二次择优的优化方法。以白车身底板为例,依照最小可制造尺寸对结构进行分割,以分割单元之间的连接关系作为设计变量,结合NSGA-II算法进行优化,得到最优装配方案;以优化得到的Pareto解集中的装配方案为初始解,从中进行二次择优,选出满足稳定性条件的解,对各子部件内的厚度施加约束进行板厚优化,并将得到的板厚值返回到图分解法中进行迭代,直到问题收敛,最终实现对焊接位置和板厚的同时优化。

An Approach to Underwater Image Enhancement Based on Image Structural Decomposition

Underwater imaging posts a challenge due to the degradation by the absorption and scattering occurred during light propagation as well as poor lighting conditions in water medium Although image filtering techniques are utilized to improve image quality effectively, problems of the distortion of image details and the bias of color correction still exist in output images due to the complexity of image texture distribution. This paper proposes a new underwater image enhancement method based on image struc- tural decomposition. By introducing a curvature factor into the Mumford_Shah_G decomposition algorithm, image details and struc- ture components are better preserved without the gradient effect. Thus, histogram equalization and Retinex algorithms are applied in the decomposed structure component for global image enhancement and non-uniform brightness correction for gray level and the color images, then the optical absorption spectrum in water medium is incorporate to improve the color correction. Finally, the en- hauced structure and preserved detail component are re.composed to generate the output. Experiments with real underwater images verify the image improvement by the proposed method in image contrast, brightness and color fidelity.

Alternative Fuzzy Cluster Segmentation of Remote Sensing Images Based on Adaptive Genetic Algorithm

Remote sensing image segmentation is the basis of image understanding and analysis. However,the precision and the speed of segmentation can not meet the need of image analysis,due to strong uncertainty and rich texture details of remote sensing images. We proposed a new segmentation method based on Adaptive Genetic Algorithm(AGA) and Alternative Fuzzy C-Means(AFCM) . Segmentation thresholds were identified by AGA. Then the image was segmented by AFCM. The results indicate that the precision and the speed of segmentation have been greatly increased,and the accuracy of threshold selection is much higher compared with traditional Otsu and Fuzzy C-Means(FCM) segmentation methods. The segmentation results also show that multi-thresholds segmentation has been achieved by combining AGA with AFCM.

Chaotic system and QR factorization based robust digital image watermarking algorithm

In order to protect copyright of digital images,a new robust digital image watermarking algorithm based on chaotic system and QR factorization was proposed.The host images were firstly divided into blocks with same size,then QR factorization was performed on each block.Pseudorandom circular chain(PCC) generated by logistic mapping(LM) was applied to select the embedding blocks for enhancing the security of the scheme.The first column coefficients in Q matrix of chosen blocks were modified to embed watermarks without causing noticeable artifacts.Watermark extraction procedure was performed without the original cover image.The experimental results demonstrate that the watermarked images have good visual quality and this scheme is better than the existing techniques,especially when the image is attacked by cropping,noise pollution and so on.Analysis and discussion on robustness and security issues were also presented.

A New Pullulan-Producing Yeast and Medium Optimization for Its Exopolysaccharide Production

Yeast strain Y68 producing high level of pullulan was isolated from the phyton collected in Toulouse, France. This strain was identified to be Rhodotorula bacarum by BIOLOG analysis. This is the first report that pullulan was produced by Rhodotorula bacarum. The optimal medium (g L -1) for pullulan production by this strain was 80 glucose, 20 soybean cake hydrolysate, 5 K 2HPO 4, 1 NaCl, 0.2 MgSO 4·7H 2O, 0.6 (NH 4) 2SO 4, pH 7.0. Under this condition, 54 g L -1 pullulan was produced within 60 h at 30 ℃. Pullulan is a better starting material for producing marine prodrugs.

A Study on sEMG Simulation Modeling and Its Decomposition Methods

In this paper, we establish a surface electromyography(sEMG) signal model and study the signal decomposition method from noisy background. Firstly, single fiber action potential (SFAP), motor unit action potential (MUAP) and motor unit action potential train(MUAPT) are simulated based on the tripolar signal source model, and then the sEMG is obtained; secondly, the simulated sEMG signal is extracted from the mixed signals that consists of white noises, power frequency interference signal and electrocardio signal by independent component analysis (ICA) algorithms; lastly, the spikes corresponding to each motor unit action potential from the simulated sEMG signals were detected by applying the wavelet transform (WT) method. Simulation results showed that sEMG model could describe the physiological process of sEMG, ICA and WT methods could extract the sEMG signal and its features, which will lay a foundation for further classifying the MUAP.

A Modified Fixed Point Method for the Perona Malik Equation

In this work we present a new method to solve the Perona Malik equation for the image denoising. The method is based on a modified fixed point algorithm which is fast and stable. We discretize the equation using a finite volume method by integrating the equation using a fuzzy measure on the control volume. To make our algorithm move faster in time, we have used an optimized domain decomposition which generalize the wave relaxation method. Several test of noised images illustrate this approach and show the efficiency of the proposed new method.

Image Fusion Based on Complex Contourlet Transform and Nonnegative Matrix Factorization

An image fusion method combining complex contourlet transform(CCT) with nonnegative matrix factorization(NMF) is proposed in this paper.After two images are decomposed by CCT,NMF is applied to their highand low-frequency components,respectively,and finally an image is synthesized.Subjective-visual-quality of the image fusion result is compared with those of the image fusion methods based on NMF and the combination of wavelet /contourlet /nonsubsampled contourlet with NMF.The experimental results are evaluated quantitatively,and the running time is also contrasted.It is shown that the proposed image fusion method can gain larger information entropy,standard deviation and mean gradient,which means that it can better integrate featured information from all source images,avoid background noise and promote space clearness in the fusion image effectively.

Graph Theory Methods for Decomposition w.r.t. Outputs of Boolean Control Networks

This paper focuses graph theory method for the problem of decomposition w.r.t. outputs for Boolean control networks(BCNs). First, by resorting to the semi-tensor product of matrices and the matrix expression of BCNs, the definition of decomposition w.r.t. outputs is introduced. Second, by referring to the graphical structure of BCNs, a necessary and sufficient condition for the decomposition w.r.t. outputs is obtained based on graph theory method. Third, an effective algorithm to realize the maximum decomposition w.r.t. outputs is proposed. Finally, some examples are addressed to validate the theoretical results.

Detection and identification of S1 and S2 heart sounds using wavelet decomposition method

Phonocardiogram （PCG）, the digital recording of heart sounds is becoming increasingly popular as a primary detection system for diagnosing heart disorders and it is relatively inexpensive. Electrocardiogram （ECG） is used during the PCG in order to identify the systolic and diastolic parts manually. In this study a heart sound segmentation algorithm has been developed which separates the heart sound signal into these parts automa- tically. This study was carried out on 100 patients with normal and abnormal heart sounds. The algorithm uses discrete wavelet decomposition and reconstruction to pro- duce PCG intensity envelopes and separates that into four parts： the first heart sound, the systolic period, the second heart sound and the diastolic period. The performance of the algorithm has been evaluated using 14,000 cardiac periods from 100 digital PCG recordings, including normal and abnormal heart sounds. In tests, the algorithm was over93% correct in detecting the first and second heart sounds. The presented automatic seg- mentation Mgorithm using w^velet decomposition and reconstruction to select suitable frequency band for envelope calculations has been found to be effective to segment PCG signals into four parts without using an ECG.

Hour-to-hour variability of the ionosphere: An application of the classical multidimensional scaling method

The classical multidimensional scaling(MDS) method is introduced and applied in the study of the hour-to-hour ionospheric variability based on the ionospheric fo F2 observed at three ionosonde stations in East-Asia in 2002 and 2007. Results from the matrix eigen decompositions indicate that the annual part of the ionospheric variation is large in middle latitude and solar maximum period(2002) while low in the low latitude and solar minimum period(2007). The connectivity maps of the hour-to-hour ionospheric variability based on MDS method show some common diurnal features. The ionospheric connectivity between adjacent hours near noon hours and near midnight hours is high. The ionospheric connectivity between adjacent hours near sunrise hours and near sunset hours is poor, especially for the sunrise hours. Also there are latitudinal and solar activity dependences in this kind of connectivity. These results revealed from the ionospheric connectivity maps are useful physically and in practice for the ionospheric forecasting on the hour-to-hour scale.