1D and 2D structured mass-spring models with preload

In this paper, the objective is to enrich the existing 1D and 2D mass-spring models with physical accuracy as well as visual realism. It is found that using nonzero preloads on the springs is a necessary condition for the models to approximate their continuum counterparts. First, the parameters of the 1D mass-spring model of a beam are derived based on pure bending and axial action. It is proved that the mass-spring model with this set of parameter has correct characteristics of resistance against lateral displacement, which is one of the most important aspects of the accuracy of the 1D mass-spring model. Then, the method is extended to the 2D mass-spring models of the continuum plate with two different mesh structures. The mass-spring model with equilateral triangle meshes is shown to be physically more accurate than that with rectangular meshes. Finally, the physical accuracy that the mass-spring models with preload can achieve is investigated under different load conditions by comparison with the finite element method (FEM) to demonstrate the efficacy of our approach.     

一种3维模型的网格盲水印算法

3维模型的数字水印是数字水印研究的热点之一,鲁棒性、嵌入可读性水印和盲检测是3维模型数字水印的难点所在。从增强3维模型数字水印的鲁棒性出发,提出一种基于局部几何空间的3维模型数字水印算法,它以模型三角网格顶点在其一环邻居顶点为所确定的局部几何空间;通过改变顶点在局部几何空间中的位置来嵌入水印,并以调整其间的夹角来嵌入水印序列的索引,而调整顶点与圆心的距离来嵌入较高比特的二进制数值。本文算法在水印检测时,无需原始模型,且可抵抗平移、旋转、均匀缩放、顶点乱序、剪切及网格简化等攻击。实验结果表明, 该水印算法具有很好的鲁棒性、可读水印的不可感知性和盲水印检测的优势。     

An optimized GPU implementation of a 2D free surface simulation model on unstructured meshes

This work is related with the implementation of a finite volume method to solve the 2D Shallow Water Equations on Graphic Processing Units (GPU). The strategy is fully oriented to work efficiently with unstructured meshes which are widely used in many fields of Engineering. Due to the design of the GPU cards, structured meshes are better suited to work with than unstructured meshes. In order to overcome this situation, some strategies are proposed and analyzed in terms of computational gain, by means of introducing certain ordering on the unstructured meshes. The necessity of performing the simulations using unstructured instead of structured meshes is also justified by means of some test cases with analytical solution.     

Removing local irregularities of triangular meshes with highlight line models

The highlight line model is a powerful tool in assessing the quality of a surface. It increases the flexibility of an interactive design environment. In this paper, a method to generate a highlight line model on an arbitrary triangular mesh is presented. Based on the highlight line model, a technique to remove local shape irregularities of a triangular mesh is then presented. The shape modification is done by solving a minimization problem and performing an iterative procedure. The new technique improves not only the shape quality of the mesh surface, but also the shape of the highlight line model. It provides an intuitive and yet suitable method for locally optimizing the shape of a triangular mesh. Supported by National Science Foundation of China (Grant Nos. 60533070, 60625202), National Basic Research Program of China (Grant No. 2004CB719400), National High-Tech Research & Development Program of China (Grant No. 2007AA040401), Fok Ying Tung Education Foundation (Grant No. 111070), National Science Foundation of USA (Grant Nos. DMI-0422126, DMS-0310645), and Kentucky Science & Technology Corporation (Grant No. COMM-Fund-712)     

三角网格曲面上离散曲率改进算法

计算三角网格离散曲面曲率的Meyer方法几何意义简明,计算量较小,但其计算效果仍有进一步提高的潜力。通过对Meyer方法的深入分析,提出了平均曲率构造向量和Gauss曲率构造角的概念,并指出了它们的几何意义,在此基础上构造了对Meyer方法的改进算法。经分析,提出的改进算法精简了各个主要计算步骤,避免了不必要的计算误差。仿真计算结果表明,改进算法是有效的,提高了三角网格离散曲率的计算精度和计算效率。     

二维限定三角网格质量优化方法

使用拓扑优化和几何优化相结合的方法对限定Delaunay三角网格进行质量优化,首先针对普通的拉普拉斯算法会造成网格局部收缩的缺陷,对拉普拉斯算子进行了改进,改进后的拉普拉斯算子克服了这一缺陷;然后对网格顶点的度进行优化,使每个顶点都有一个优化的度数;最后对拓扑优化的网格使用改进的拉普拉斯算子进行几何优化,优化后的网格质量得到了显著的提高,算例表明了算法是可行的。     

改进的蚁群算法及其在2DHP模型中的应用

为了提高蛋白质折叠问题解的质量,采用蚁群算法对蛋白质的折叠问题进行研究,并且在现有的蚁群算法的基础上成功引入了淘汰和克隆机制,使其具有更好的运算效率,并成功应用到2DHP模型中.在蚁群对最优值进行搜索的过程中,容易出现局部最优点,导致影响解的质量.为了避免计算结果收敛到局部最优点,引入了一种最大最小蚁群策略.选择测试序列进行实验,实验结果表明,该算法在保证解的质量的同时,还具有较高的效率.     

改进的蚁群算法求解蛋白质折叠问题

针对蛋白质折叠问题的二维格点模型(2DHP)提出了一种改进的蚁群算法(ACO).受链生长型算法Pruned-Enriched Rosenbluth Mvthod(PERM)的启发,在计算迹的时候增加了一个新的信息量,使得改进后的蚁群算法具有较快的收敛速度,同时采用基于极值动力学的优化方法(EO)进行局部搜索.求解基准实例的结果表明,该算法能够在保证解质量的前提下能大大缩短计算时间.     

MOEA/D线性插入方向向量策略研究

MOEA/D具有良好的收敛性、均匀的分布性、求解效率高等优点,普遍应用于求解多目标优化问题.然而对于Pareto前端复杂的多目标优化问题,预先设定均匀的权重向量并不能够维持Pareto最优解集的良好分布性.本文,首先分析均匀分布的权重向量、均匀分布的搜索方向二者与均匀分布的解集之间的关系,提出一种新的权重向量设置方式;其次基于进化过程中解集的分布,提出线性插入搜索方向策略,并将其转换为对应的权重向量,同时在MOEA/D中周期性应用该策略调整搜索方向,获取分布均匀的解集;最后将该算法在WFG系列测试问题上进行性能测试,并采用世代距离指标(GD)、Spacing指标(S)、超体积指标(HV)对算法收敛性和多样性进行对比分析,实验结果表明,与原始的MOEA/D、使用均匀分布的搜索方向MOEA/D、使用预处理的M OEA/D、M OEA/D-DU相比,改进的算法求出解集的多样性极大提高,收敛性明显增强,解集的整体质量显著提高.     

解析二维非结构网格生成方法及其应用

提出弱区域指示函数描述流场形状并证明了其存在和不唯一性;利用该函数基于Delaunay方法依据流场尺度生成二维非结构网格。其中,边界引力有效解决了流场边界恢复和内嵌边界问题,弹簧振子和正三角形趋进技术有效改善网格质量。最后,弹簧振子随着弱区域指示函数的演变与监测函数的指导成功应用到自适应网格生成。     

A neural network model to develop actions in urban complex systems represented by 2D meshes

The main idea of this work is to present a tool which may be useful to generate a mesh of points where urban actions may be taken after analysing and understanding complex urban situations. By the word complex we mean urban concentrations without precise limits and without a recognizable geometry pattern. In these situations, it is very hard for the architects to understand the system. Therefore, it is very difficult to define an action plan for this type of urban situations. What we propose is an adaptation of a neural network algorithm to work in the context of urban networks. Our objective is to develop a strategy to change this weakness of sparse urban development by activating public spaces with new meanings. A new 2D triangle mesh simplification model is introduced with the central property of preserving the shape of the original mesh. The mathematical model presented consists of a self-organizing algorithm whose objective is to generate the positions of the nodes of the simplified mesh; afterwards, a triangulation algorithm is carried out to reconstruct the triangles of the new simplified mesh. With this algorithm, it is possible to perform specific actions in an urban space, because the urban territory can be considered as a complex mesh with nodes and edges. A real example of an urban action is shown with the introduction of a wireless network in a residential area.     

基于蚁群算法的非结构化P2P网络搜索的改进

针对非结构化的对等网络一般以广播方式作为其搜索的基本策略而引发较大的网络流量和盲目性这一问题,引入人工智能领域的蚁群算法,利用蚂蚁信息素的多样性和正反馈机制,有效地指导节点选择查询,以便更快地找到查询结果.仿真结果表明,该算法有效地减少了查询带来的网络流量和盲目性,提高了查找的成功率.     

洪水预报经验模型的混合蛙跳优化率定

PI模型广泛应用于洪水预报和水资源管理等领域,为防汛、抗旱和水资源利用等重大决策提供了重要依据。API模型定线往往采用人工的方式进行绘制,在精度上和效率上比较欠缺。江苏省洪水预警预报平台在研发过程中为提高API模型预报精度,采用了混合蛙跳算法（SFLA）对API模型定线进行优化。本文主要介绍了混合蛙跳算法对API模型进行参数优化和智能定线的方法,并通过混合蛙跳算法、传统方法对71场洪水进行绘制,与传统定线方法相比,证实混合蛙跳法能有效提高API模型预报精度。     

Improved robust model predictive control with structured uncertainty

In this paper, a dilation of the LMI characterization is presented to address constrained robust model predictive control (MPC) for a class of uncertain linear systems with structured time-varying uncertainties. The uncertainty is described in linear fractional transformation (LFT) form. By introducing slack variables and using parameter dependent Lyapunov functions, the design conservativeness is reduced compared with other existing MPC approaches. The proposed approach is applied to an industrial CSTR benchmark system to demonstrate the merits of our proposed solution.     

DrTrust: 一种非结构化P2P网络信任模型

P2P网络的动态性、匿名性和自治性带来许多安全问题,传统的结构化的P2P信任模型并不能很好的适应对等网络环境。提出了一种应用于非结构化P2P网络中的信任模型——DrTrust。该模型充分利用直接信任值和推荐信任值相结合方式的优点,实现了精确计算信任值,并采用分布式存储方式和激励、惩罚机制分别存储和更新信任值。仿真结果表明,DrTrust在准确计算节点信任值和抑制恶意节点行为等问题上较已有的信任模型有一定的改进。     

Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization

Software reliability growth model (SRGM) with testing-effort function (TEF) is very helpful for software developers and has been widely accepted and applied. However, each SRGM with TEF (SRGMTEF) contains some undetermined parameters. Optimization of these parameters is a necessary task. Generally, these parameters are estimated by the Least Square Estimation (LSE) or the Maximum Likelihood Estimation (MLE). We found that the MLE can be used only when the software failure data to satisfy some assumptions such as to satisfy a certain distribution. However, the software failure data may not satisfy such a distribution. In this paper, we investigate the improvement and application of a swarm intelligent optimization algorithm, namely quantum particle swarm optimization (QPSO) algorithm, to optimize these parameters of SRGMTEF. The performance of the proposed SRGMTEF model with optimized parameters is also compared with other existing models. The experiment results show that the proposed parameter optimization approach using QPSO is very effective and flexible, and the better software reliability growth performance can be obtained based on SRGMTEF on the different software failure datasets.     

An efficient unstructured MUSCL scheme for solving the 2D shallow water equations

The aim of this paper is to present a novel monotone upstream scheme for conservation law (MUSCL) on unstructured grids. The novel edge-based MUSCL scheme is devised to construct the required values at the midpoint of cell edges in a more straightforward and effective way compared to other conventional approaches, by making better use of the geometrical property of the triangular grids. The scheme is incorporated into a two-dimensional (2D) cell-centered Godunov-type finite volume model as proposed in Hou et al. (2013a,c) to solve the shallow water equations (SWEs). The MUSCL scheme renders the model to preserve the well-balanced property and achieve high accuracy and efficiency for shallow flow simulations over uneven terrains. Furthermore, the scheme is directly applicable to all triangular grids. Application to several numerical experiments verifies the efficiency and robustness of the current new MUSCL scheme.     

一种改进的三维人脸重建方法

以径向基函数散乱数据插值算法为基础,针对该算法在三维人脸建模中的不足,提出一种改进的算法：在三维人脸建模中,根据特征点和非特征点的不同特性对基函数选择不同的参数值,使通用人脸模型的调整变换更加合理;然后应用二元三次多项式插值方法对特征点局部区域进行二次平滑,避免了畸变模型的产生,最终得到完整的三维人脸模型。实验结果表明,使用该算法构建的三维人脸模型生成速度快,且具有较高的精确度。     

NS2错误模型的改进

分析了随机变量对NS2错误模型的影响,解释了当随机变量的分布的参数发生变化时,错误模型的丢失率偏离预期值这一现象的原因,并在此基础上通过对NS2错误模型的修正,使得rate_与分布参数的变化无关.最后对修正过的NS2错误模型进行了仿真,仿真结果表明,该修正是有效的、可行的.     

改进的红外图像2维Otsu分割算法

针对红外图像有别于一般灰度图像的特点,常用的灰度级平均灰度级2维直方图区域划分在红外图像分割中效果不佳,为此提出一种改进的灰度级梯度2维Otsu阈值选取方法,选取合适的梯度算子,利用改进的粒子群优化算法寻找分割阈值,在算法中加入有效判断早熟停滞的方法,一旦检索到早熟迹象,便随机改变最优解的任意1维分量值,使其跳出局部最大,实现全局寻优过程的快速收敛。仿真实验结果表明,该算法由于使用新的2维直方图,分割后的红外图像边界形状准确,特征细节清晰,运算速度也得到了有效提高。