Pixel-Oriented Visualization Techniques for Exploring Very Large Data Bases

Abstract

An important goal of visualization technology is to support the exploration and analysis of very large amounts of data. This article describes a set of pixel-oriented visualization techniques that use each pixel of the display to visualize one data value and therefore allow the visualization of the largest amount of data possible. Most of the techniques have been specifically designed for visualizing and querying large data bases. The techniques may be divided into query-independent techniques that directly visualize the data (or a certain portion of it) and query-dependent techniques that visualize the data in the context of a specific query. Examples for the class of query-independent techniques are the screen-filling curve and recursive pattern techniques. The screen-filling curve techniques are based on the well-known Morton and Peano–Hilbert curve algorithms, and the recursive pattern technique is based on a generic recursive scheme, which generalizes a wide range of pixel-oriented arrangements for visualizing large data sets. Examples for the class of query-dependent techniques are the snake-spiral and snake-axes techniques, which visualize the distances with respect to a data base query and arrange the most relevant data items in the center of the display. In addition to describing the basic ideas of our techniques, we provide example visualizations generated by the various techniques, which demonstrate the usefulness of our techniques and show some of their advantages and disadvantages.     

Some useful filtering techniques for illposed problems

Some useful filtering techniques for computing approximate solutions of illposed are presented. Special attention is given to the role of smoothness of the filters and the choice of time-dependent parameters used in these filtering techniques. Smooth filters and proper choice of time-dependent parameters in these filtering techniques allow numerical construction of more accurate approximate solutions of illposed problems. In order to illustrate this and the filtering techniques, a severely illposed fourth-order nonlinear wave equation is numercally solved using a three time-level finite difference scheme. Numerical examples are given showing the merits of the filtering techniques.     

Operations research practice on logistics management in Taiwan: An academic view

The opinions of logistics educators in Taiwan on OR practices in the domestic logistics industry are explored in this research. In this study, questionnaires were given to 42 pre-screened educators at 10 logistics departments and graduate institutes. According to the 37 valid returned questionnaires, 70% of the responding educators believe the major source of OR techniques in Taiwan’s logistics industry originates from individual employee training, while 92% believe OR is not widely used primarily because companies are unfamiliar with OR techniques. OR techniques were considered helpful in solving problems by 73%. Generally speaking, familiarity with OR techniques is not associated with implementation of OR techniques by educators. Additionally, logistics educators express concern about insufficient training for logistics students in Taiwan. However, they are optimistic about the logistics industry’s willingness to more actively adopt OR techniques in Taiwan in the next two years.     

Morphologie heuristischer Verfahren

Summary A morphological classification of heuristic techniques is presented. It shall serve as a step towards a design methodology of heuristic techniques. It should, therefore, be a tool for the development of new and efficient heuristic techniques.     

A review of expert systems

Expert systems have recently become popular and are attracting more and more attention. The high quality performance achieved by some systems in areas previously not considered practical for computational solutions has lead to great interest from many different disciplines. Most expert systems use a subset of techniques from the general area of computer science research known as artificial intelligence. However, some expert systems have been developed that incorporate more traditional mathematical modeling techniques. The combination of artificial intelligence techniques and more traditional mathematical techniques has been shown to be quite effective in developing several high quality performance computer software systems. The techniques used in expert systems may be what is needed to bridge the gap between classical operational research modeling and human decision making processes. This paper addresses how expert systems techniques are being used in problem solving and why someone in operational research might want to use them.     

Comparison of iterative improvement techniques for schedule optimization

Due to complexity reasons of realistic scheduling applications, often iterative improvement techniques that perform a kind of local search to improve a given schedule are proposed instead of enumeration techniques that guarantee optimal solutions. In this paper we describe an experimental comparison of four iterative improvement techniques for schedule optimization that differ in the local search methodology. These techniques are iterative deepening, random search, tabu search and genetic algorithms. To compare the performance of these techniques, we use the same evaluation function, knowledge representation and data from one application. The evaluation function is defined on the gradual satisfaction of explicitly represented domain constraints and optimization functions. The satisfactions of individual constraints are weighted and aggregated for the whole schedule. We have applied these techniques on data of a steel making plant in Linz (Austria). In contrast to other applications of iterative improvement techniques reported in the literature, our application is constrained by a greater variety of antagonistic criteria that are partly contradictory.     

正基与一类直接搜索法

本文对非线性规划中的一类直接搜索法给出了一个统一的收敛定理,这类方法被称为定步长下山法,它包括了轴向搜索法、Hooke-Jeeves方法以及对Hooke-Jeeves方法所作的简化与变形(文中给出)作为特例,从而这些算法的收敛性质均能根据上述统一的收敛定理得到,除了这些以外,单纯形调优法也能用同样的想法来进行分析,这由作者在另一文中给出,为了上述目的,本文还对代数中的正基作了若干研究。     

A Comparison of Discriminant Analysis versus Artificial Neural Networks

Artificial Neural Network (ANN) techniques have recently been applied to many different fields and have demonstrated their capabilities in solving complex problems. In a business environment, the techniques have been applied to predict bond ratings and stock price performance. In these applications, ANN techniques outperformed widely-used multivariate statistical techniques. The purpose of this paper is to compare the ANN method with the Discriminant Analysis (DA) method in order to understand the merits of ANN that are responsible for the higher level of performance. The paper provides an overview of the basic concepts of ANN techniques in order to enhance the understanding of this emerging technique. The similarities and differences between ANN and DA techniques in representing their models are described. This study also proposes a method to overcome the limitations of the ANN approach, Finally, a case study using a data set in a business environment demonstrates the superiority of ANN over DA as a method of classification of observations.     

Displacement decomposition—incomplete factorization preconditioning techniques for linear elasticity problems

Two preconditioning techniques for the numerical solution of linear elasticity problems are described and studied. Both techniques are based on spectral equivalence approach. The first technique consists in an incomplete factorization of the separate displacement component part of the stiffness matrix. The second technique uses an incomplete factorization of the isotropic approximation to the stiffness matrix. Results concerning existence, stability and efficiency of these preconditioning techniques are presented. The efficiency and robustness of the described techniques are illustrated by numerical experiments.     

On equivalence of the Gauss-Newton technique,the parameter influence coefficient technique,and the quasilinearization technique in dynamic system identification by least squares

The literature presents, among others, three general techniques for system identification by least squares. These techniques are the Gauss-Newton technique, the parameter influence technique and the quasilinearization technique. The purpose of this paper is to show the equivalence of all three techniques for the general case.     

Techniques for the analysis of risks in major projects

Risk management currently has an important bearing on the outcomes of major projects. It usually consists of three core areas: analysis, evaluation and control. One of the vital decisions to be made within the area of risk analysis is the choice of techniques to be used which are broadly classified under qualitative and quantitative methods. Through a questionnaire, this paper identifies the most successful risk analysis techniques within both categories. Over one hundred large companies within the construction industry, and every oil and gas operator in the UK were approached. The areas surveyed on were: risk analysis techniques employed by the companies; the relative success of the techniques; the size and range of activities of the company and the company's policy on identifying and responding to specific risks encountered during any particular project. The main conclusions are that personal and corporate experience, and engineering judgement are the most successful qualitative techniques; scenario analysis, EMV, ENPV, and break-even analysis being the principal quantitative techniques.     

Numerical integration by using nonlinear techniques

In this paper several nonlinear techniques, mainly based on the use of Padé approximation and rational interpolation, are given for computing the value of a definite integral. Some convergence properties of these methods are proved. A comparison is made between these non-linear techniques and classical linear techniques on the base of some numerical examples.     

Comparison of techniques for assessing effects of loading uncertainty upon a long term phosphorous model

This paper compares the feasibility of applying three stochastic techniques to a linear water quality model. The Monte Carlo, first order analysis, and generation of moment equation techniques are applied to a long term phosphorus model of Lake Washington. The effect of uncertainty of the phosphorus loading term on simulated phosphorus levels is analysed. The simulated concentrations of phosphorus in the water column are very responsive to uncertainty in annual phosphorus loading, but the sediment concentrations are relatively insensitive. All three stochastic techniques produced identical results, but the level of preparatory and computational effort required varies considerably. The Monte Carlo technique requires the most computation time of the three stochastic techniques examined. The first order analysis and generation of moment equation techniques are shown to be precise and efficient methods of stochastic analysis. In this application they required less than one-thousandth the computer time of the Monte Carlo technique     

Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review

This paper presents a comprehensive review of the work done, during the 1968–2005, in the application of statistical and intelligent techniques to solve the bankruptcy prediction problem faced by banks and firms. The review is categorized by taking the type of technique applied to solve this problem as an important dimension. Accordingly, the papers are grouped in the following families of techniques: (i) statistical techniques, (ii) neural networks, (iii) case-based reasoning, (iv) decision trees, (iv) operational research, (v) evolutionary approaches, (vi) rough set based techniques, (vii) other techniques subsuming fuzzy logic, support vector machine and isotonic separation and (viii) soft computing subsuming seamless hybridization of all the above-mentioned techniques. Of particular significance is that in each paper, the review highlights the source of data sets, financial ratios used, country of origin, time line of study and the comparative performance of techniques in terms of prediction accuracy wherever available. The review also lists some important directions for future research.     

多元Copula-GARCH模型及其在金融风险分析上的应用

针对传统风险分析模型的不足,结合Copula技术和GARCH模型,提出了多元Copula-GARCH模型。指出该模型不仅可以捕捉金融市场间的非线性相关性,还可以得到更灵活的多元分布进而用于资产投资组合VaR分析。在详细探讨了基于Copula技术的资产投资组合的MonteCarlo仿真技术的基础上,运用具有不同边缘分布的多元Copula-GARCH模型,对上海股市进行了研究,结果证实了所提模型和方法的可行性和有效性。     

Applications of Quantitative Techniques in Large and Small Organizations in the United States: An Empirical Analysis

Data was gathered from Fortune 500 companies (manufacturing and service organizations) and 500 small firms pertaining to the use of several quantitative techniques. Analysis was also done to see if differences existed within different classes of service companies. Also, respondents were asked for their opinion pertaining to specific barriers that may inhibit the use of these techniques. Results show little progress has been made in the applications of quantitative techniques in the last decade. The barriers cited by respondents are mostly related to management's lack of knowledge of quantitative techniques. Findings agree with previous studies conducted.     

Validation,verification, and testing techniques throughout the life cycle of a simulation study

Life cycle validation, verification, and testing (VV&T) is extremely important for the success of a simulation study. This paper surveys current software VV&T techniques and current simulation model VV&T techniques and describes how they can all be applied throughout the life cycle of a simulation study. The processes and credibility assessment stages of the life cycle are described and the applicability of the VV&T techniques for each stage is stated. A glossary is provided to explicitly define important terms and VV&T techniques.     

The Baire property in hit-and-miss hypertopologies

Recently, some techniques have been developed for the study of the Baire property in hyperspaces. These techniques have been applied to solve a long-standing open problem of McCoy in 1975 and a recent open problem of Zsilinszky. In this paper, we extend and apply these techniques further to investigate the Baire property of hyperspaces equipped with the general hit-and-miss topology.     

Change-of-bases abstractions for non-linear hybrid systems

We present abstraction techniques that transform a given non-linear dynamical system into a linear system, or more generally, an algebraic system described by polynomials of bounded degree, so that invariant properties of the resulting abstraction can be used to infer invariants for the original system. The abstraction techniques rely on a change-of-bases transformation that associates each state variable of the abstract system with a function involving the state variables of the original system. We present conditions under which a given change-of-bases transformation for a non-linear system can define an abstraction. Furthermore, the techniques developed here apply to continuous systems defined by Ordinary Differential Equations (ODEs), discrete systems defined by transition systems and hybrid systems that combine continuous as well as discrete subsystems.The techniques presented here allow us to discover, given a non-linear system, if a change-of-bases transformation involving degree-bounded polynomials yielding an algebraic abstraction exists. If so, our technique yields the resulting abstract system, as well. Our techniques enable the use of analysis techniques for linear systems to infer invariants for non-linear systems. We present preliminary evidence of the practical feasibility of our ideas using a prototype implementation.     

Self-Tuning Norm-Relaxed Method of Feasible Directions

This paper presents three updating techniques for the scaling matrix or the scalar weight used in the norm-relaxed method of feasible directions, a generalization of the popular Pironneau–Polak algorithm. These techniques include variable metric updates and tuning of a scalar weight in a way characteristic of trust-region methods, and also techniques based on the idea of multiple directions, where the update decision is made by comparing results of searching along several directions determined by distinct values of weights. Numerical results obtained on a standard test set are provided. These results indicate that the updating techniques allow considerable computational savings when compared with the original Pironneau-Polak method.