基于法线网格的渐进压缩

多分辨率分析(Multi-resolution Analysis)和法线网格(Normal meshes)是近年来进行三维网格图形处理和网格压缩的新方法。该文在这两项技术的基础上，提出并实现了三维网格的多分辨率分析及其渐进几何压缩(Progressive Geometry Compression)方案，研究了基于细分的法线网格在多分辨率分析中的边界处理问题。实验结果表明，利用法线网格的多分辨率分析结合法向多边形构造方法来处理边界，可以取得非常高的压缩率和较好的重构效果。     

网格的渐进几何压缩

提出一种渐进几何压缩算法.通过对简化算法的改进,网格模型由基网格及多组顶点分裂操作序列表达.当从一层网格向下一层精网格细化时,该组顶点分裂操作序列中的分裂操作顺序是任意的.因此,改进的渐进网格表示可改变每组顶点分裂操作的排序,实现高效率编码.设计了Laplacian几何预测器,通过相邻顶点来预测新增顶点位置,并对位置校正值进行量化及Huffman编码.实验结果表明,该算法可获得高压缩比,适合几何模型的网络渐进传输.     

多码流渐进几何压缩

提出一种几何模型分组渐进压缩算法．利用偏移细分曲面的模型表示方法，通过网格分块准则将模型的控制网格划分为多个chart．在对曲面的偏移量进行小波变换后，采用零树编码算法对每个chart上的小波系数压缩编码，生成多条相互独立的渐进压缩码流．该算法支持动态多分辨率解码，能够从压缩结果中直接获得模型的视点相关多分辨率表示．实验结果表明，该算法有利于提高多分辨率模型表示和绘制的效率，降低分布式系统的网络带宽需求．     

渐进网格中真实选择细化技术的探讨

三维几何模型的选择性细化,是在几何网格LOD技术基础上,依据某种标准(如视点的位置、角度)对网格进行局域精简或细化,以尽可能少的顶点数来再现原模型的细节.其核心是顶点拓扑信息记录、检索方式.真实选择细化技术的优点在于将精简和细化操作局限在顶点及其领域上,不会产生可能失控的连锁反应.就此方法应用于采用半边缩减的渐进网格上,提出了具体的拓扑压缩数据结构方案,并对该结构的实现条件提出建议.该方案结构紧凑,适用于大型三维几何模型通过互联网进行传榆并适于在个人电脑上进行动态显示.     

率-失真优化的渐进几何压缩

提出一种率-失真优化的渐进几何压缩方法. 根据三维模型细节信息分布的不均匀性, 该方法将细节信息分块并对各块独立编码, 然后以一定位率下重构网格几何失真最小为准则, 将各块的位流优化组装成最终的码流, 从而在渐进传输时使有限的网络带宽能优先分配给那些细节信息较为丰富的块. 实验结果表明, 与渐进几何压缩方法 (Progressive geometry compression, PGC) 相比, 在低位率时本文方法重构网格的峰值信噪比 (Peak signal-to-noise ratio, PSNR) 提高了约 2.25dB. 此外, 该方法也为实现三维网格感兴趣区域编码提供了新的方案.     

采用渐进网格方法简化网格的使用及其实现

渐进网格表示方法，是一种新的网格储存以及网格数据传送的方法。这种有效的、无损耗的表示方法能够解决图形学中一些实际的问题：渐进传送、网格压缩、以及层次细节只存在有限个模型的问题。本文介绍了DirectX3D中如何进行采用渐进优化网格的方法。     

一种适用于网络环境的三维网格压缩算法

为了使位流可以适应网络带宽的异构、时变以及各个网络终端的不同图形处理能力，提出了一种基于小波变换的三维网格分块渐进传输的压缩算法。利用细分曲面的模型表示方法，按照控制网格将几何体分块，采用嵌入式位平面编码方法对小波变换后每个小波子带的系数进行独立编码，生成多条独立的渐进压缩码流。该算法支持动态的质量可扩展性和分辨率可扩展性，能够从压缩结果中直接获得视点相关的模型表示。实验结果表明，该算法有利于提高多分辨率表示和传输效率，降低网络带宽需求。     

有损网络中三维模型渐进传输策略

采用渐进压缩网格(CPM)算法将其产生的数据流进行重要度分组,按照重要度的不同分成若干组,结合流式传输技术,对各重要度的数据组采用不同的网络信道进行传输,并根据网络状况和用户需求,动态改变通过可靠信道传输的数据量,从而提高系统的实时性,提出一种新的三维模型远程交互显示解决方案及相应的数据传输策略。仿真实验结果表明,该方法能在满足用户视觉需求和精度要求的前提下,获得较好的实时性。     

基于邻域预测的三角形网格几何信息压缩

在现有的代表性三角形网格压缩方法中,先采用一定的网格遍历方法来压缩连接信息,同时用遍历路径上的相邻顶点来对每个顶点的几何坐标进行平行四边形预测,以压缩几何信息。它们的主要缺点是平行四边形预测不太准确,且受到所采用的遍历方法的制约。文章提出一种新的几何信息压缩方法。编码时,对每个顶点的几何坐标,采用比平行四边形预测更为准确、且与遍历方法无关的邻域预测。解码时,采用预处理共轭梯度法,联立求解所有顶点的预测公式组成的稀疏线性方程组,同时求出所有顶点的坐标。文章采用渐进解码方法来减少求解稀疏线性方程组时,用户的等待时间。     

渐进网格及其在移动计算中的应用

在移动计算中,3维图形通常是由几何造型的网格来表示。为了解决移动图形的存储、传输和显示问题,提出了一种基于逆细分的构建渐进网格的算法,给出了渐进网格通过网格传输和在移动终端上渲染3维图形的方法。细密的网格通过逐层地、分批地删除其冗余信息,最后生成由基网格和一系列误差值组成的渐进网格。在算法实施时,将Loop逼近型细分模式作为插值型细分模式进行操作。该算法共分3个关键步骤:网格分裂、奇点预测、网格更新。简化后的渐进网格可以无损还原。实验结果表明,该算法效率高,比以往的方法速度快。     

Design and Optimization of an XYZ Parallel Micromanipulator with Flexure Hinges

In this paper, a nearly decoupled XYZ translational compliant parallel micromanipulator (CPM) is designed for micro/nano scale manipulation with features of piezo-driven actuators and flexure hinges. The CPM structure improvement is made to enlarge the workspace and eliminate or reduce the stress stiffening, buckling phenomenon, and parasitic motions of the original XYZ CPM, which leads to a new CPM with a more compact structure. The CPM kinematics, parasitic motions, and workspace are determined analytically, and the mathematical models describing statics and dynamics of the CPM are established to evaluate its related performances, which are verified by the finite element analysis (FEA) undertaken in ANSYS environment. Based on the analytic models, the CPM dimensions have been optimized by resorting to the particle swarm optimization (PSO) approach, which produces a CPM having minimum parasitic motions and satisfying other performance specifications as validated by the FEA simulations.     

基于Ptolemy的通用CPM调制器的建模与仿真

连续相位调制（CPM）是一类具有良好频谱利用率和恒包络特性的调制方式，非常适合应用于带宽及功率都受限的无线环境中，然而建模与仿真工具的缺乏大大限制了这类调制方式的应用。文中采用递归的方法，在ADS Ptolemy环境下定制出CPM调制器的核心模块——通用相位产生模块，并结合库中已有模块，实现了对一个通用CPM调制器的建模，最后给出了不同调制参数下CPM信号的频谱及与测试仪表协同仿真的结果。从仿真得出的频谱和仪表观察的波形可以看出，模型具有良好的通用性，适合对各种CPM调制方式的建模和仿真。     

基于约束的CPM动态优化算法

利用基于蒙特卡罗模拟的关键路径(CPM)优化算法模型,通过分析项目计划中各任务之间可能存在工序约束和期限约束对CPM的影响,提出了基于约束的CPM动态优化算法.该算法可得到CPM,工期及其统计特性和相关的冲突信息,为决策者提供更好的决策信息支持.采用Matlab,C#和SQL Server实现了所提出算法,实例分析验证了该算法的有效性.     

Change-point monitoring for the detection of DoS attacks

This paper presents a simple and robust mechanism, called change-point monitoring (CPM), to detect denial of service (DoS) attacks. The core of CPM is based on the inherent network protocol behavior and is an instance of the sequential change point detection. To make the detection mechanism insensitive to sites and traffic patterns, a nonparametric cumulative sum (CUSUM) method is applied, thus making the detection mechanism robust, more generally applicable, and its deployment much easier. CPM does not require per-flow state information and only introduces a few variables to record the protocol behaviors. The statelessness and low computation overhead of CPM make itself immune to any flooding attacks. As a case study, the efficacy of CPM is evaluated by detecting a SYN flooding attack - the most common DoS attack. The evaluation results show that CPM has short detection latency and high detection accuracy     

The current state of control loop performance monitoring – A survey of application in industry

Control loop performance monitoring (CPM) in industrial production processes is an established area of research for which many methods to detect malfunctioning loops have been developed. However, it is unclear which methods are successful in an industrial environment. Often, there are additional aspects such as organizational issues, data availability and access that can compromise the use of CPM. In this paper, we are reporting on the results of a survey amongst CPM users. The survey takes stock of existing methods and their use in industry as well as which faults are most frequent and can be detected. Organizational as well as implementation issues are investigated and discussed. This paper aims to identify open research topics and the direction of development of CPM in industrial production processes.     

Simplifying activity networks under generalized precedence relations to extended CPM networks

The critical path method (CPM) is a network planning technology with a simple and intuitive representation. However, it can only represent a special precedence relation—the finish‐to‐start minimum time lag. Currently, generalized precedence relations (GPRs) are represented by complex activity networks. We simplify complex activity networks under GPRs by representing the GPRs in a new way. This new extended CPM network is similar to the standard CPM network with the exception that arcs may have negative lengths and cycles. The extended CPM network facilitates problems with GPRs. Although many current models and algorithms are advanced and efficient for the CPM network problem, they are difficult or impossible to improve for GPRs applications. The extended CPM network, however, combats these problems and serves as an illustration of resource leveling with activity splitting. The current 0‐1 binary model formulation for the resource leveling with just finish‐to‐start minimum time lags is also applied to the problem with GPRs using the extended CPM network.     

Real‐Time Fluid Effects on Surfaces using the Closest Point Method

The Closest Point Method (CPM) is a method for numerically solving partial differential equations (PDEs) on arbitrary surfaces, independent of the existence of a surface parametrization. The CPM uses a closest point representation of the surface, to solve the unmodified Cartesian version of a surface PDE in a 3D volume embedding, using simple and well‐understood techniques. In this paper, we present the numerical solution of the wave equation and the incompressible Navier‐Stokes equations on surfaces via the CPM, and we demonstrate surface appearance and shape variations in real‐time using this method. To fully exploit the potential of the CPM, we present a novel GPU realization of the entire CPM pipeline. We propose a surface‐embedding adaptive 3D spatial grid for efficient representation of the surface, and present a high‐performance approach using CUDA for converting surfaces given by triangulations into this representation. For real‐time performance, CUDA is also used for the numerical procedures of the CPM. For rendering the surface (and the PDE solution) directly from the closest point representation without the need to reconstruct a triangulated surface, we present a GPU ray‐casting method that works on the adaptive 3D grid.     

Six-DOF micro-manipulator based on compliant parallel mechanism with integrated force sensor

This paper describes the design of a micro-scale manipulator based on a six-DOF compliant parallel mechanism (CPM), which is featured by piezo-driven actuators and integrated force sensor capable of delivering six-DOF motions with high precision and providing real-time force information for feedback control. Particularly, the position and screw-based Jacobian analyses of the CPM are presented. Then, the compliance model and the workspace evaluation of the CPM are proposed in order to account for the compliance and obtain design guidelines. Finally, the integrated sensor is introduced. The static features of such a mechanism include high positioning accuracy, structural compactness and smooth and continuous displacements.     

A parallel implementation of the Cellular Potts Model for simulation of cell-based morphogenesis

The Cellular Potts Model (CPM) has been used in a wide variety of biological simulations. However, most current CPM implementations use a sequential modified Metropolis algorithm which restricts the size of simulations. In this paper we present a parallel CPM algorithm for simulations of morphogenesis, which includes cell-cell adhesion, a cell volume constraint, and cell haptotaxis. The algorithm uses appropriate data structures and checkerboard subgrids for parallelization. Communication and updating algorithms synchronize properties of cells simulated on different processor nodes. Tests show that the parallel algorithm has good scalability, permitting large-scale simulations of cell morphogenesis (10(7) or more cells) and broadening the scope of CPM applications. The new algorithm satisfies the balance condition, which is sufficient for convergence of the underlying Markov chain.     

Solving Sturm-Liouville problems by piecewise perturbation methods, revisited

We present the extension of the successful Constant Perturbation Method (CPM) for Schrödinger problems to the more general class of Sturm-Liouville eigenvalue problems. Whereas the original CPM can only be applied to Sturm-Liouville problems after a Liouville transformation, the more general CPM presented here solves the Sturm-Liouville problem directly. This enlarges the range of applicability of the CPM to a wider variety of problems and allows a more efficient solution of many problems. The CPMs are closely related to the second-order coefficient approximation method underlying the SLEDGE software package, but provide for higher order approximations. These higher order approximations can also be obtained by applying a modified Neumann method. The CPM approach, however, leads to simpler formulae in a more convenient form.