Using state diagrams for hilbert curve mappings

The Hilbert Curve describes a method of mapping between one and n dimensions. Such mappings are of interest in a number of application domains including image processing and, more recently, in the indexing of multi-dimensional data. Relatively little work, however, has been devoted to techniques for mapping in more that 2 dimensions. This paper presents a technique for constructing state diagrams to facilitate mappings and is a specialization of an incomplete generic process described by Bially. Although the storage requirements for state diagrams increase exponentially with the number of dimensions, they are useful in up to about 9 dimensions.     

Drawing Trees Symmetrically in Three Dimensions

Symmetric graph drawing enables a clear understanding of the structure of the graph. Previous work on symmetric graph drawing has focused on two dimensions. Symmetry in three dimensions is much richer than that of two dimensions. This is the first paper to extend symmetric graph drawing into three dimensions. More specifically, the paper investigates the problem of drawing trees symmetrically in three dimensions. First, we suggest a model for drawing trees symmetrically in three dimensions. Based on this model, we present a linear time algorithm for finding the maximum number of three-dimensional symmetries in trees. We also present a three-dimensional symmetric drawing algorithm for trees.     

Drawing Trees Symmetrically in Three Dimensions

Abstract. Symmetric graph drawing enables a clear understanding of the structure of the graph. Previous work on symmetric graph drawing has focused on two dimensions. Symmetry in three dimensions is much richer than that of two dimensions. This is the first paper to extend symmetric graph drawing into three dimensions. More specifically, the paper investigates the problem of drawing trees symmetrically in three dimensions. First, we suggest a model for drawing trees symmetrically in three dimensions. Based on this model, we present a linear time algorithm for finding the maximum number of three-dimensional symmetries in trees. We also present a three-dimensional symmetric drawing algorithm for trees.     

Selecting Coherent and Relevant Plots in Large Scatterplot Matrices

The scatterplot matrix (SPLOM) is a well‐established technique to visually explore high‐dimensional data sets. It is characterized by the number of scatterplots (plots) of which it consists of. Unfortunately, this number quadratically grows with the number of the data set’s dimensions. Thus, an SPLOM scales very poorly. Consequently, the usefulness of SPLOMs is restricted to a small number of dimensions. For this, several approaches already exist to explore such ‘small’ SPLOMs. Those approaches address the scalability problem just indirectly and without solving it. Therefore, we introduce a new greedy approach to manage ‘large’ SPLOMs with more than 100 dimensions. We establish a combined visualization and interaction scheme that produces intuitively interpretable SPLOMs by combining known quality measures, a pre‐process reordering and a perception‐based abstraction. With this scheme, the user can interactively find large amounts of relevant plots in large SPLOMs.     

A heuristic for packing boxes into a container

Given a container of known dimensions and a collection of rectangular boxes with known dimensions and number of boxes of each type, the problem is to find suitable positions for placing the boxes in the container in such a way that all the boxes can be fitted in. A heuristic for computer or manual operation is described.     

Humour, Relationship Maintenance and Personality Matching in automated dialogue: A controlled study

We built an automated dialogue system whose style of interaction can be varied along the three dimensions of Humour, Relationship Maintenance and Personality Matching. We then ran a longitudinal experiment which investigated manipulations of these three dimensions. We explored the interaction of these separate dimensions on user perception of the system using a controlled study design. We showed a strong positive effect for the use of Humour and Relationship Maintenance, while the use of Personality Matching raised a number of questions which need further investigation.     

带权图的多重分形度量

分形维数及多重分形是分形理论的重要研究内容.复杂网络的多重分形已经得到了较为深入的研究,但对复杂网络多重分形的度量目前并没有可行的方法.带权图是复杂网络研究的重要对象,其中的节点权重及边权重可以为正实数、负实数、纯虚数及复数等多种不同的类型.除节点权重及边权重均为正实数的情形外,其他类型的带权图都具有多重分形特性,且均...     

基于超复数系的分形准全息图象生成

提出了一种新型分形准全息图象，并采用基于超复数系分形图象的生成方法进行分形准全息图象序列的生成，生成的分形准全息图象在激光防伪等领域有着良好的应用前景。文中还给出了超复数系中分形三维图象生成的快速算法和生成结果。     

Fast mining of distance-based outliers in high-dimensional datasets

Defining outliers by their distance to neighboring data points has been shown to be an effective non-parametric approach to outlier detection. In recent years, many research efforts have looked at developing fast distance-based outlier detection algorithms. Several of the existing distance-based outlier detection algorithms report log-linear time performance as a function of the number of data points on many real low-dimensional datasets. However, these algorithms are unable to deliver the same level of performance on high-dimensional datasets, since their scaling behavior is exponential in the number of dimensions. In this paper, we present RBRP, a fast algorithm for mining distance-based outliers, particularly targeted at high-dimensional datasets. RBRP scales log-linearly as a function of the number of data points and linearly as a function of the number of dimensions. Our empirical evaluation demonstrates that we outperform the state-of-the-art algorithm, often by an order of magnitude.     

Reuse-Driven Tiling for Improving Data Locality

This paper applies unimodular transformations and tiling to improve data locality of a loop nest. Due to data dependences and reuse information, not all dimensions of the iteration space will and can be tiled. By using cones to represent data dependences and vector spaces to quantify data reuse in the program, a reuse-driven transformational approach is presented, which aims at maximizing the amount of data reuse carried in the tiled dimensions of the iteration space while keeping the number of tiled dimensions to a minimum (to reduce loop control overhead). In the special case of one single fully permutable loop nest, an algorithm is presented that tiles the program optimally so that all data reuse is carried in the tiled dimensions. In the general case of multiple fully permutable loop nests, data dependences can prevent all data reuse to be carried in the tiled dimensions. An algorithm is presented that aims at localizing data reuse in the tiled dimensions so that the reuse space localized has the largest dimensionality possible.     

基于Markov 逻辑网的事件表象统一方法

为解决Web数据集成中大量事件表象语句共指现实世界同一事件,导致数据冗余问题,提出一种基于Markov逻辑网的事件表象统一方法。方法从共指事件表象集合中获得较准确详细的一条表象,作为统一的事件表象对应现实事件,为数据集成提供高质量数据。本文将事件表象使用8个维度的形式表示,训练Markov逻辑网从共指事件表象集合中推理出准确详细的维度内容,重新组合后形成一条事件表象。本文使用少量一阶谓词从维度内容、事件表象和数据源等多角度制定相应规则,通过推理解决数据不一致、不完整、不详细问题。实验结果表明基于Markov逻辑网的事件表象统一方法能获得较准确详细的统一事件表象。     

Evaluation of the multivariate accommodation performance of the grid method

The present study examined the multivariate accommodation performance (MAP) of the grid method, a distributed representative human models (RHM) generation method, in the context of men’s pants sizing system design. Using the 1988 US Army male anthropometric data and ±2.5 cm of fitting tolerance, the grid method selected two key dimensions (waist girth and crotch height) out of 12 anthropometric dimensions and identified 25 RHMs to accommodate 95% of the population. The average MAP of the RHMs decreased dramatically as the number of anthropometric dimensions considered increased (99% for single dimension and 14% for 12 dimensions). A standardized regression model was established which explains the effects of two factors (sum of anthropometric dimension ranges; adjusted R² between key dimensions and other anthropometric dimensions) on the MAP of RHMs. This regression model can be used to prioritize anthropometric dimensions for efficient MAP improvement of men’s pants design.     

一种基于模式的XML文档存储方法

提出了一种基于模式的XML文档存储方法,在考虑映射维度和独立于后台关系数据库的基础上,通过在模式中针对多种映射维度添加注释来定义映射,从而支持多种映射策略,简化了映射过程.给出了应用示例和原型系统的设计与实现.     

Evaluation of the multivariate accommodation performance of the grid method

The present study examined the multivariate accommodation performance (MAP) of the grid method, a distributed representative human models (RHM) generation method, in the context of men’s pants sizing system design. Using the 1988 US Army male anthropometric data and ±2.5 cm of fitting tolerance, the grid method selected two key dimensions (waist girth and crotch height) out of 12 anthropometric dimensions and identified 25 RHMs to accommodate 95% of the population. The average MAP of the RHMs decreased dramatically as the number of anthropometric dimensions considered increased (99% for single dimension and 14% for 12 dimensions). A standardized regression model was established which explains the effects of two factors (sum of anthropometric dimension ranges; adjusted R² between key dimensions and other anthropometric dimensions) on the MAP of RHMs. This regression model can be used to prioritize anthropometric dimensions for efficient MAP improvement of men’s pants design.     

An algorithm for the minimum weight design of a telescopic jib

The purpose of the algorithm presented in this paper is to determine the discrete cross sectional dimensions of members of a telescopic jib which minimize the total weight of the structure subject to some simplified strength conditions and to the technology and matching requirements. The algorithm can be applied effectively even in such extreme cases as that of a jib consisting of five members, when the number of dimensions to be determined amounts to 35.     

A New Genetic Algorithm for Loop Tiling

Tiling is a known problem especially in the field of computational geometry and its related engineering branches. In fact, a tile is a set of points in the Cartesian space. The goal is to partition the space of the points as tiles with optimal dimensions and shapes such that a number of predefined semantic relations holds amongst the tiles. So far, this problem has been solved in special cases with two or three dimensions. The problem of determining the optimal tile is an NP-Hard problem. Presenting a novel constraint genetic algorithm in this paper, we have been able to solve the tiling problem in Cartesian spaces with more than two dimensions, for the loop parallelization problem.     

Multidimensional declustering schemes using Golden Ratio and Kronecker Sequences

We propose a new declustering scheme for allocating uniform multidimensional data among parallel disks. The scheme, aimed at reducing disk access time for range queries, is based on Golden Ratio Sequences for two dimensions and Kronecker Sequences for higher dimensions. Using exhaustive simulation, we show that, in two dimensions, the worst-case (additive) deviation of the scheme from the optimal response time for any range query is one when the number of disks (M) is at most 22; its worst-case deviation is two when M /spl les/ 94; and its worst-case deviation is four when M /spl les/ 550. In two dimensions, we prove that whenever M is a Fibonacci number, the average performance of the scheme is within 14 percent of the (generally, unachievable) strictly optimal scheme and its worst-case response time is within a multiplicative factor three of the optimal response time for any query, and within a factor 1.5 of the optimal for large queries. We also present comprehensive simulation results, on two-dimensional as well as on higher-dimensional data, that compare and demonstrate the advantages of our scheme over some recently proposed schemes in the literature.     

基于维度扩展的Radviz可视化聚类分析方法

Radviz是一种多维数据可视化技术,它通过径向投影机制将多维数据映射到低维空间,使具有相似特征的数据点投影到相近位置,从而形成可视化聚类效果.Radviz圆周上的维度排列顺序对数据投影结果影响很大,提出将原始维度划分为多个新维度来拓展Radviz圆周上的维度排序空间,从而获得比原始维度条件下更好的可视化聚类效果.该维度划分方法首先计算数据在每个原始维度的概率分布直方图,然后使用均值漂移算法对直方图进行划分,最后根据划分结果将原始维度扩展为多个新维度.提出使用Dunn指数和正确率来量化评估Radviz可视化聚类效果.进行了多组对比实验,结果表明,维度扩展有利于多维数据在Radviz投影中获得更好的可视化聚类效果.     

Base invariance of feasible dimension

Effective fractal dimensions were introduced by Lutz (2003) in order to study the dimensions of individual sequences and quantitatively analyze the structure of complexity classes. Interesting connections of effective dimensions with information theory were also found, implying that constructive dimension as well as polynomial-space dimension are invariant under base change while finite-state dimension is not.We consider the intermediate case, polynomial-time dimension, and prove that it is indeed invariant under base change by a nontrivial argument which is quite different from the Kolmogorov complexity ones used in the other cases.Polynomial-time dimension can be characterized in terms of prediction loss rate, entropy, and compression algorithms. Our result implies that in an asymptotic way each of these concepts is invariant under base change.A corollary of the main theorem is any polynomial-time dimension 1 number (which may be established in any base) is an absolutely normal number, providing an interesting source of absolute normality.