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。     

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...     

基于分形的机械加工表面轮廓评价参数的计算方法

通过对机械加工表面轮廓特征的分析,说明了在表面轮廓参数测量中,消除各种误差影响的必要性。提出利用非倾向性振荡分析方法对机械加工表面轮廓稳定性问题进行了分析,以去除各种误差对表面轮廓参数的影响,并对表面轮廓评价参数提出了一种有效的计算方法。     

知行交会学之大成——太仓国际科教园概念规划方案

以科教园与城市的关系为整个设计的出发点,强调在城市范围内以及不同学科领域之间对于教育资源的重组与开发利用。该文介绍了此次设计的规划概念与特色,力图体现知识经济时代的教育发展趋向。     

城市分形与城市建筑策划

从分形角度研究城市,得出传统城市的精髓,并将之应用到未来的城市建筑策划。     

一种新的直流系统环网接地故障检测方法

在传统低频信号注入法的基础上提出了一种新的基于小波变换和分形理论的直流系统环网接地故障检测方法,引入分形理论中的凹凸度参数,利用凹凸度参数和分形维数唯一确定的二维平面上点的位置来识别不同情况下的环网接地故障。该方法弥补了低频信号注入法难以解决环网问题的缺陷,大量的仿真计算验证了该方法的有效性。