遗传算法参数寻优的分形插值方法研究

分形插值是一种构造分形曲线的方法。分形插值方法中的垂直比例因子的大小影响拟合函数曲线的起伏，控制插值曲线的拟合精度。该文在深人分析分形插值方法的基础上，结合遗传算法可以有导向的实现参数随机搜索优化的特点，将其应用到分形插值自由参数的选取中，实现分形插值曲线与实际函数的最佳拟合。仿真结果验证了遗传算法在垂直比例因子的寻优上的有效性。     

基于分形理论的斯太尔汽车发动机故障诊断的研究

研究了斯太尔汽车发动机气缸在不同状态下的关联维数，给出了获得反映其真实状态的关联维数方法。研究结果表明：该发动机气缸振动的时间序列在不同状态下关联维数不同，可以将其关联维数作为识别其状态的特征量，给出了利用分形理论判断斯太尔汽车发动机气缸状态的判椐。     

基于支持向量机的复杂地质分形特征自动提取

为了提升勘探工作效率,准确提取复杂地质分形特征,提出一种支持向量机的复杂地质分形特征自动提取方法。在两种线性可分情况下,将最佳的分类面简化为最佳分类直线,获得最佳分类平面;考虑噪声及其它干扰因素造成线性不可分的状况,得到广义的最佳分类面;基于两点可以得出支持向量机内积;通过抽取异常重磁分维数的频率域角度获得分维值,反映出不同频率能量关系,计算地质图像内的方差、均值、相关性、对比度以及角二阶矩,即可完成地质分形特征自动提取。实验结果表明,所提方法能够很好区分各类泥岩样本,特征提取效果准确。     

A multiobjective box-covering algorithm for fractal modularity on complex networks

The box-covering method is widely used on measuring the fractal property on complex networks. The problem of finding the minimum number of boxes to tile a network is known as a NP-hard problem. Many algorithms have been proposed to solve this problem. All the current box-covering algorithms regard the box number minimization as the only objective. However, the fractal modularity of the network partition divided by the box-covering method, has been proved to be strongly related to the information transportation in complex networks. Maximizing the fractal modularity is also important in the box-covering method, which can be divided into two objectives: maximization of ratio association and minimization of ratio cut. In this paper, to solve the dilemma of minimizing the box number and maximizing the fractal modularity at the same time, a multiobjective discrete particle swarm optimization box-covering (MOPSOBC) algorithm is proposed. The MOPSOBC algorithm applies the decomposition approach on the two objectives to approximate the Pareto front. The proposed MOPSOBC algorithm has been applied to six benchmark networks and compared with the state-of-the-art algorithms, including two classical box-covering algorithms, four single objective optimization algorithms and six multiobjective optimization algorithms. The experimental results show that the MOPSOBC algorithm can get similar box numbers with the current best algorithm, and it outperforms the state-of-the-art algorithms on the fractal modularity and normalized mutual information.     

Cloud enabled fractal based ECG compression in wireless body sensor networks

E-health applications deal with a huge amount of biological signals such as ECG generated by body sensor networks (BSN). Moreover, many healthcare organizations require access to these records. Therefore, cloud is widely used in healthcare systems to serve as a central service repository. To minimize the traffic going to and coming from cloud ECG compression is one of the proposed solutions to overcome this problem. In this paper, a new fractal based ECG lossy compression technique is proposed. It is found that the ECG signal self-similarity characteristic can be used efficiently to achieve high compression ratios. The proposed technique is based on modifying the popular fractal model to be used in compression in conjunction with the iterated function system. The ECG signal is divided into equal blocks called range blocks. Subsequently, another down-sampled copy of the ECG signal is created which is called domain. For each range block the most similar block in the domain is found. As a result, fractal coefficients (i.e. parameters defining fractal compression model) are calculated and stored inside the compressed file for each ECG signal range block. In order to make our technique cloud friendly, the decompression operation is designed in such a way that allows the user to retrieve part of the file (i.e. ECG segment) without decompressing the whole file. Therefore, the clients do not need to download the full compressed file before they can view the result. The proposed algorithm has been implemented and compared with other existing lossy ECG compression techniques. It is found that the proposed technique can achieve a higher compression ratio of 40 with lower Percentage Residual Difference (PRD) Value less than 1%.     

Forecasting conditional climate-change using a hybrid approach

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.     

Influence of physicochemical binder properties on agglomeration of wheat powder in couscous grain

Wet agglomeration mechanisms developing in low shear mixers have been described considering a fractal morphogenesis process that links the median size of the agglomerates with their solid volume fraction via a fractal dimension. It appears fundamental to integrate the polydispersity of the generated structures (nuclei, agglomerates, dough pieces) in the analysis of the agglomeration process in order to approach the industrial problems. The objective of this study is to correlate the influence of the physicochemical characteristics of several liquid binders, on the fractal agglomeration mechanisms. To do so, we considered the values of the fractal model parameters. The obtained results confirmed that semolina wet agglomeration follows a fractal morphogenesis for the different applied liquid binders. Our results also showed a marked influence of the studied physicochemical properties of the liquid binder on the value of the fractal model parameters. During wet agglomeration in low shear mixers, the mechanisms implied during agglomeration (wetting, nucleation and growth) do not occur consecutively, but they coexist throughout at each water contents.     

技术进步与建筑界面形态的演变

技术进步正大跨步地改变着人们的生产方式、生活习惯,亦影响着人们的审美观念,尤其是迅猛发展的高新技术给社会带来巨大变革的同时,也对建筑领域产生了极大的影响。建筑材料类型的丰富、建筑结构技艺的更迭、建筑设备性能的升级都直接或者间接地牵制着建筑形态。本文通过对技术变革剧烈的近现代时期典型建筑界面形态在结构技术及计算技术两个层面的解析,厘清其在技术演进路线上的演绎步进,探讨建筑界面发展趋势,以及对其产生影响的各种技术因素的内在联系。     

Microstructure–function relationships of heat-induced gels of porcine haemoglobin

The purpose of this work was to use image analysis to study the microstructural properties of haemoglobin gels, with structural changes induced by pH conditions, and their correlations with physical properties such as texture and water holding capacity (WHC). Two types of networks showing great differences in the dimensions of the gel structure were obtained as influenced by pH. At pH < 5.5 there was a shift from an aggregated to a fine-stranded gel type. Fractal dimension values revealed that more complex structures corresponded to softest and non-exudative gels. Lacunarity and pore size, which were used to study the pore distribution within the network, confirmed that softest gels with high WHC showed large number of small cavities. Finally, correlations between textural attributes, i.e. springiness and adhesiveness, and spatial variability, referred quantitatively to the degree of compactness, were also established.