Noncontiguous processor allocation algorithms for mesh-connectedmulticomputers

Current processor allocation techniques for highly parallel systems are typically restricted to contiguous allocation strategies for which performance suffers significantly due to the inherent problem of fragmentation. As a result, message-passing systems have yet to achieve the high utilization levels exhibited by traditional vector supercomputers. We are investigating processor allocation algorithms which lift the restriction on contiguity of processors in order to address the problem of fragmentation. Three noncontiguous processor allocation strategies-paging allocation, random allocation, and the Multiple Buddy Strategy (MBS)-are proposed and studied in this paper. Simulations compare the performance of the noncontiguous strategies with that of several well-known contiguous algorithms. We show that noncontiguous allocation algorithms perform better overall than the contiguous ones, even when message-passing contention is considered. We also present the results of experiments on an Intel Paragon XP/S-15 with 208 nodes that show noncontiguous allocation is feasible with current technologies     

Availability-based noncontiguous processor allocation policies for 2D mesh-connected multicomputers

Various contiguous and noncontiguous processor allocation policies have been proposed for mesh-connected multicomputers. Contiguous allocation suffers from high external processor fragmentation because it requires that the processors allocated to a parallel job be contiguous and have the same topology as the multicomputer. The goal of lifting the contiguity condition in noncontiguous allocation is reducing processor fragmentation. However, this can increase the communication overhead because the distances traversed by messages can be longer, and messages from different jobs can interfere with each other by competing for communication resources. The extra communication overhead depends on how the allocation request is partitioned and mapped to free processors. In this paper, we investigate a new class of noncontiguous allocation schemes for two-dimensional mesh-connected multicomputers. These schemes are different from previous ones in that request partitioning is based on the submeshes available for allocation. The available submeshes selected for allocation to a job are such that a high degree of contiguity among their processors is achieved. The proposed policies are compared to previous noncontiguous policies using detailed simulations, where several common communication patterns are considered. The results show that the proposed policies can reduce the communication overhead and improve performance substantially.     

The effects of spatial contiguity within computer-based instruction of group personalized two-step mathematics word problems

This study investigated the effects of the spatial contiguity principle within computer-based instruction (CBI) of group personalized two-step mathematics word problems on the achievement and attitude of 98 sixth-grade predominantly Hispanic students. Students were randomly blocked by ability level based on their pretest scores to a spatially contiguous or non-spatially contiguous version of the CBI. The results revealed students who received the spatially contiguous treatment made significantly greater pretest-to-posttest gains than students who received the non-spatially contiguous treatment. In addition, lower-ability students made significantly greater pretest-to-posttest gains than higher-ability students. Findings from the student attitude survey revealed no significant difference in treatment responses to the two survey factors on CBI Satisfaction and Attitude About Math. Student comments from the open-ended questions on the attitude survey and the focus group interview indicated that the spatially contiguous version of the CBI was more helpful and less confusing than the non-spatially contiguous version.     

基于局部SIFT特征点的双阈值配准算法

针对SIFT匹配算法和SIFT与RANSAC结合的匹配算法都存在不同程度误匹配的问题,提出一种基于局部SIFT特征点的双阈值匹配算法。设计变步长迭代准则获取SIFT双阈值,其中大阈值匹配获得一组稀疏的精确匹配,小阈值匹配获得一组可能存在误匹配的密集匹配。以精确匹配建立目标的形变约束模型,以此为基础从密集匹配中删除误匹配。通过这些正确的匹配点估计两幅图像之间的变换矩阵。为了降低算法所需时间,提高效率,通过分析图像的纹理变化,采用提取其变化最为剧烈的区域来代表整幅图像进行匹配运算。实验结果表明,该算法在图像存在平移、旋转等仿射变化情况下具有配准精度高,稳定和快速等特点。     

基于多核并行和动态阈值的点云配准算法

针对点云配准中存在错误匹配点对、精度不高等问题,提出一种基于多核并行和动态阈值的点云配准算法。该算法采用改进的SAC-IA算法进行点云粗配准,利用OpenMP实现点云查询点的法向量、FPFH等特征的并行加速提取以及对应点对的并行查找,从而使整个配准算法的速度得到保持甚至提升。在点云精配准阶段,使用改进的ICP算法进行精配准,改进点着眼于错误对应点对的剔除及其阈值的动态确定,即以配准点重心作为参照点,按照动态阈值,使用点对距离约束剔除错误对应点对。实验结果表明,本文算法在提升配准精度的情况下,配准速度也得到了提升。     

Twenty-five years of natural coordinates

In the early eighties, the author and co-workers created and further developed the natural coordinates to describe the motion of 2-D and 3-D multibody systems. Natural coordinates do not need angles or angular parameters to define orientation, leading to constant inertia matrices and to the simplest form of the constraint equations. Natural coordinates are composed by the Cartesian coordinates of some points and the Cartesian components of some unit vectors distributed on the different bodies of the system. The points and vectors can be located in the joints, being shared by contiguous bodies, decreasing or even eliminating the need to set joint constraints and reducing the total number of variables. However, other authors prefer not to share variables in order to get even simpler equations and to keep a bigger decoupling of equations, which is preferable in some cases. In this paper the history of natural coordinates is reviewed, as well as the main contributions coming from other research groups. In the second part of the paper some application areas in which natural coordinates can be particularly advantageous are examined. Commemorative Contribution.     

一种权值约束的精确配准算法

针对数据与模型的精确配准问题,提出一种权值约束的配准算法,通过 对配准点施加不同的权值,利用权值约束保证模型重要区域的配准精度。首先,论文基于经 典配准模型,引入权重因子,建立了改进的权值约束的配准模型。针对配准模型的求解问题, 通过对现有SVD-ICP 算法进行适应性改进,提出并研究了带权SVD-ICP(wSVD-ICP)算法, 重点推导了基于wSVD 算法求解旋转矩阵R 和平移矩阵T 的过程。最后,论文利用仿真数 据和实测数据对配准模型进行了验证;计算结果表明,论文所提算法通过对精度要求较高区 域分配高权值进行约束,可有效提升该局部区域的配准精度;同时,可在一定程度上改进整 体配准精度和效率。     

基于法矢控制的B样条曲面逼近的PIA方法

提出了一种基于法矢控制的 B 样条曲面逼近的渐进迭代逼近(PIA)算法。一方面该方法将离散数据点的切失、曲率、法矢等几何特征充分应用到离散数据点的逼近问题上,利用数据点两个方向的切矢构造出数据点的法矢约束来控制逼近曲面形状,相比于无法矢控制的 B 样条曲面逼近的渐进迭代逼近(PIA)方法,逼近曲面更光顺,可获得更好的逼近效果。另一方面由于该算法选取主特征点作为控制顶点,所以允许在曲面拟合中控制顶点的数目小于数据点的数目。而且PIA算法的每次迭代过程中的各个步骤都是独立的,很容易被应用到并行计算上,可提高计算效率。本文还给出了一些实例来验证该算法的有效性。     

一类最优交通小区划分问题的一阶邻接约束建模方法

提出一种使用邻接矩阵保证最优交通小区划分一阶邻接约束的整数规划建模方法。从求解复杂度和质量两个角度,比较并分析了该邻接约束建模方法与其他3种方法对问题求解效率的影响。设计了聚合式层次聚类启发算法以求解所提出的模型。针对较大规模算例,将所提出的建模方法与其他3种邻接约束建模方法的结果进行了对比与分析。结果表明,基于邻接矩阵表示的建模方法能在允许时间内求得满意解,较其他3种方法更适合大规模问题。     

基于极线约束的ORB特征匹配算法

图像匹配是机器视觉领域的基础核心课题,针对当前ORB (Oriented FAST and Rotated BRIEF)图像特征匹配算法虽然执行速度快,但是匹配质量不高的问题,提出一种通过极线约束来改进ORB匹配的算法。通过合理设计Hamming阈值大小来提高初始匹配点数量,采用RANSAC和8点改进法计算基本矩阵,应用极线约束剔除误匹配保留大量优质匹配点。仿真实验结果证明,算法改进后的优质匹配点数量可达原始算法的2-3倍,同时极大地提高了匹配点的质量,证明了算法的有效性。     

An Exact Algorithm of Searching for the Largest Cluster in an Integer-Valued Problem of 2-Partitioning a Sequence

We analyze mathematical aspects of one of the fundamental data analysis problems consisting in the search (selection) for the subset with the largest number of similar elements among a collection of objects. In particular, the problem appears in connection with the analysis of data in the form of time series (discrete signals). One of the problems in modeling this challenge is considered, namely, the problem of finding the cluster of the largest size (cardinality) in a 2-partition of a finite sequence of points in Euclidean space into two clusters (subsequences) under two constraints. The first constraint is on the choice of the indices of elements included in the clusters. This constraint simulates the set of time-admissible configurations of similar elements in the observed discrete signal. The second constraint is imposed on the value of the quadratic clustering function. This constraint simulates the level of intracluster proximity of objects. The clustering function under the second constraint is the sum (over both clusters) of the intracluster sums of squared distances between the cluster elements and its center. The center of one of the clusters is unknown and defined as the centroid (the arithmetic mean over all elements of this cluster). The center of the other cluster is the origin. Under the first constraint, the difference between any two subsequent indices of elements contained in a cluster with an unknown center is bounded above and below by some constants. It is established in the paper that the optimization problem under consideration, which models one of the simplest significant problems of data analysis, is strongly NP-hard. We propose an exact algorithm for the case of a problem with integer coordinates of its input points. If the dimension of the space is bounded by a constant, then the algorithm is pseudopolynomial.     

A new evolutionary approach to cutting stock problems with and without contiguity

Evolutionary algorithms (EAs) have been applied to many optimization problems successfully in recent years. The genetic algorithm (GAs) and evolutionary programming (EP) are two different types of EAs. GAs use crossover as the primary search operator and mutation as a background operator, while EP uses mutation as the primary search operator and does not employ any crossover. This paper proposes a novel EP algorithm for cutting stock problems with and without contiguity. Two new mutation operators are proposed. Experimental studies have been carried out to examine the effectiveness of the EP algorithm. They show that EP can provide a simple yet more effective alternative to GAs in solving cutting stock problems with and without contiguity. The solutions found by EP are significantly better (in most cases) than or comparable to those found by GAs.Scope and purposeThe one-dimensional cutting stock problem (CSP) is one of the classical combinatorial optimization problems. While most previous work only considered minimizing trim loss, this paper considers CSPs with two objectives. One is the minimization of trim loss (i.e., wastage). The other is the minimization of the number of stocks with wastage, or the number of partially finished items (pattern sequencing or contiguity problem). Although some traditional OR techniques (e.g., programming based approaches) can find the global optimum for small CSPs, they are impractical to find the exact global optimum for large problems due to combinatorial explosion. Heuristic techniques (such as various hill-climbing algorithms) need to be used for large CSPs. One of the heuristic algorithms which have been applied to CSPs recently with success is the genetic algorithm (GA). This paper proposes a much simpler evolutionary algorithm than the GA, based on evolutionary programming (EP). The EP algorithm has been shown to perform significantly better than the GA for most benchmark problems we used and to be comparable to the GA for other problems.     

Locating straight-line edge segments on outdoor scenes

Straight-line edge segments are often used as key features in building scene models. This paper presents techniques for extracting edge segments from a digital picture. First, an edge detection is performed on the entire picture to obtain a list of edge elements. Second, these edge elements are parametrically transformed. Third, using this parametric representation, the edge elements are divided into several groups. Each group consists of edge elements which lie on a contiguous portion of a straight line. The line segments extracted are represented by the positions of their two end points. Results of line extraction on a few outdoor scenes are also presented.     

Time-optimal parabolic interpolation with velocity,acceleration, and minimum-switch-time constraints

Time-optimal trajectories with bounded velocities and accelerations are known to be parabolic, i.e. piecewise constant in acceleration. An important characteristic of this class of trajectories is the distribution of the switch points – the time instants when the acceleration of any robot joint changes. When integrating parabolic trajectory generation into a motion planning pipeline, especially one that involves a shortcutting procedure, resulting trajectories usually contain a large number of switch points with a dense distribution. This high frequency acceleration switching intensifies joint motor wear as well as hampers the robot performance. In this paper, we propose an algorithm for planning parabolic trajectories subject to both physical bounds, i.e. joint velocity and acceleration limits, and the minimum-switch-time constraint. The latter constraint ensures that the time duration between any two consecutive switch points is always greater than a given minimum value. Analytic derivations are given, as well as comparisons with other methods to demonstrate the efficiency of our approach.     

Processors selection and traffic splitting in a parallel processors system

This paper considers a general design problem for a parallel processors system which consists of a set of non-homogeneous potential processors and a set of traffic distributing points. For this problem, two levels of technology choice are made: 1) which candidate processors to establish with capacity option, 2) how to allocate the incoming traffic among established processors generated at each distributing point. The associated model is formulated as a linear fractional integer program whose objective is to minimize the maximum mean queue length on any established processor, while satisfying a side constraint such as budget constraint. Within the framework of branch and bound procedure, fractional subproblems are optimized by solving a sequence of linear programming problems. Computational experience with randomly generated 25 test problems is presented.     

一种改进ε约束飞蛾火焰优化算法及其在约束优化问题中的应用

提出一种改进ε约束法的飞蛾火焰优化算法(ε improved moth-flame optimization algorithm, εIMFO)求解约束优化问题.该算法采用ε约束法对约束进行处理,考虑种群整体的约束违反度变化,提出一种基于火焰种群约束违反度的阈值ε计算公式;改进火焰种群的更新方法,首先,根据种群中个体的约束违反度与ε的关系将其分为两类:一类是约束违反度小于等于ε的个体,按照目标函数值排序,另一类是约束违反度大于ε的个体,按约束违反度排序;然后,先选择第1类中的个体,若数量没有达到种群数量的要求,继续从第2类中选取个体形成新一代火焰种群;最后,提出一种改进的飞蛾变异策略,在原始飞蛾变异策略的基础上引入2个随机火焰个体影响飞蛾变异,并增加优秀火焰个体对飞蛾变异的指导作用.通过25个测试函数以及2个实际的工程优化问题分别与其他13种算法进行的算法性能测试对比表明, εIMFO算法在求解精度和稳定性等方面具有优势.     

Simultaneously Estimating the Fundamental Matrix and Homographies

The estimation of the fundamental matrix (FM) and/or one or more homographies between two views is of great interest for a number of computer vision and robotics tasks. We consider the joint estimation of the FM and one or more homographies. Given point matches between two views (and assuming rigid geometry of the camera-scene displacement), it is well known that all of the matched points satisfy the epipolar constraint that is usually characterized by the FM. Subsets of these point matches may also obey a constraint characterized by a homography (all matches in the subset coming from three-dimensional (3-D) points lying on a 3-D plane). The estimations of homographies and the FM are well-studied problems, and therefore, the (separate) estimation of the FM, or the homography matrices, can be considered as effectively solved problems with mature algorithms. However, the homographies and FM are not independent of each other: therefore, separate estimation of each is likely to be suboptimal. In this paper, we propose to simultaneously estimate the FM and homographies by employing the compatibility constraint between them. This is done by first concentrating on a set of parameters that (jointly) parameterize the entire set of homographies and FM (simultaneously) and that also implicitly enforce the compatibility between the estimates of each set. We then derive a reduced form with the purpose of improving the speed. We propose a solution method in which the Sampson error for the FM and homographies is minimized by the Levenberg–Marquardt (LM) algorithm. Experiments show that the gains can be compared with separate estimates (the FM and/or the homographies).      

Motion estimation of elastic articulated objects from points and contours with volume invariable constraint

This paper presents a model of elastic articulated objects based on revolving conic surface and a method of model-based motion estimation. The model includes 3D object skeleton and deformable surfaces that can represent the deformation of human body surfaces. In each limb, surface deformation is represented by adjusting one or two deformation parameters. Then, the 3D deformation parameters are determined by corresponding 2D image points and contours with volume invariable constraint from a sequence of stereo images. The 3D motion parameters are estimated based on the 3D model. The algorithm presented in this paper includes model-based parameter estimation of motion and parameter determination of deformable surfaces.     

Recursive observer‐based fault detection for a class of nonlinear uncertain systems with output constraints

This paper investigates the fault detection (FD) problem for a class of nonlinear uncertain systems in strict feedback form with an output constraint. The key idea is to design an observer to generate the FD signals and the output estimate, which also satisfies the output constraint. To facilitate constraint handling, the constraints on the output and the output estimate are transformed into the output estimation error constraint. Then, the FD observer is designed in a recursive framework. By employing a barrier Lyapunov function, the output estimation error constraint is incorporated in the last step of the recursive observer design algorithm to prevent constraint violation. It is shown that the output estimation error is uniformly bounded and satisfies the constraint for the fault‐free case. Furthermore, the residual signal is constructed by the output estimation error, and its corresponding bound is used as threshold. Compared with the FD method without considering the constraints, the proposed FD scheme provides a smaller threshold and characterizes a larger set of faults, which can be detected. Finally, simulation results are presented to illustrate the benefits of the proposed FD scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

Three-dimensional data acquisition by trinocular vision

For recognition of three-dimensional (3D) shapes and measurement of 3D positions of objects it is important for a vision system to be able to measure the 3D data of dense points in the environment. One approach is to measure the distance on the basis of the triangulation principle from the disparity of two images. However, this binocular vision method has difficulty in finding a correspondence of features between two images. This correspondence problem can be solved geometrically by adding another camera, i.e. by trinocular vision. This paper presents the principles and implementation details of trinocular vision. On the basis of the proposed method, we carried out several experiments, from which we found that many correct correspondences could be established, even for images of a complex scene, by only the geometrical constraint of trinocular vision. However, when there are dense points in the image, multiple candidate points are found and a unique correspondence cannot be established. Two approaches to solve this problem are discussed in this paper.