iPlots eXtreme: next-generation interactive graphics design and implementation of modern interactive graphics

Interactive graphics provide a very important tool that facilitates the process of exploratory data and model analysis which is a crucial step in real-world applied statistics. Only a very limited set of software exists that provides truly interactive graphics for data analysis, partially because it is not easy to implement. Very often specialized software is created to offer graphics for a particular problem, but many fundamental plots are omitted since it is not considered new research. In this paper we discuss a general framework that allows to create interactive graphics software on a sound foundation that offers consistent user interface, fast prototyping of new plots and extensibility to support interactive models. In addition, we also discuss one implementation of the general framework: iPlots eXtreme—next-generation interactive graphics for analysis of large data in R. It provides most fundamental plot types and allows new interactive plots to be created. The implementation raises interactive graphics performance to an entirely new level. We will discuss briefly several methods that allowed us to achieve this goal and illustrate the use of advanced programmability features in conjunction with R.     

Designing Modular Software: A Case Study in Introductory Statistics

Modular programming is a development paradigm that emphasizes self-contained, flexible, and independent pieces of functionality. This practice allows new features to be seamlessly added when desired, and unwanted features to be removed, thus simplifying the software's user interface. The recent rise of web-based software applications has presented new challenges for designing an extensible, modular software system. In this article, we outline a framework for designing such a system, with a focus on reproducibility of the results. We present as a case study a Shiny-based web application called intRo, that allows the user to perform basic data analyses and statistical routines. Finally, we highlight some challenges we encountered, and how to address them, when combining modular programming concepts with reactive programming as used by Shiny. Supplementary material for this article is available online.     

BertiniLab: A MATLAB interface for solving systems of polynomial equations

A MATLAB interface to the numerical homotopy continuation package Bertini is described. Bertini solves systems of polynomial equations. BertiniLab can be used to create input files for Bertini, run Bertini and process the solutions. All features of Bertini 1.5 are supported. The user can define the system of equations using a MATLAB numerical function, and vector and matrix operations are allowed. An object-oriented design allows the user to separate the statement of the problem from the details of the solution; the user can create subclasses to provide shortcuts or to tailor BertiniLab to a specific kind of problem. A complete example of an application to ferromagnetism is presented.     

Time adaptivity in the diffusive wave approximation to the shallow water equations

We discuss the use of time adaptivity applied to the one dimensional diffusive wave approximation to the shallow water equations. A simple and computationally economical error estimator is discussed which enables time-step size adaptivity. This robust adaptive time discretization corrects the initial time step size to achieve a user specified bound on the discretization error and allows time step size variations of several orders of magnitude. In particular, the one dimensional results presented in this work feature a change of four orders of magnitudes for the time step over the entire simulation.     

Iterative Denoising

One problem in many fields is knowledge discovery in heterogeneous, high-dimensional data. As an example, in text mining an analyst often wishes to identify meaningful, implicit, and previously unknown information in an unstructured corpus. Lack of metadata and the complexities of document space make this task difficult. We describe Iterative Denoising, a methodology for knowledge discovery in large heterogeneous datasets that allows a user to visualize and to discover potentially meaningful relationships and structures. In addition, we demonstrate the features of this methodology in the analysis of a heterogeneous Science News corpus.     

Hybrid Answer Set Programming

This paper discusses an extension of Answer Set Programming (ASP) called Hybrid Answer Set Programming (H-ASP) which allows the user to reason about dynamical systems that exhibit both discrete and continuous aspects. The unique feature of Hybrid ASP is that it allows the use of ASP type rules as controls for when to apply algorithms to advance the system to the next position. That is, if the prerequisites of a rule are satisfied and the constraints of the rule are not violated, then the algorithm associated with the rule is invoked.     

Some software aspects of DAE simulation & optimization software

Considerable numerical software has been written for simulation and optimization of dynamical systems. From the beginning of their development, differential algebraic equations (DAEs) have often been proposed as a way to make modeling easier. The modeler need only write down equations relating the variables in the model. However, much DAE software requires at least as much user numerical and mathematical expertise as explicit methods. An important aspect of our research has been working toward helping the idea of DAEs achieve its promise in modeling and simulation by both pushing the software to handle more general problems and to also allow for less user expertise. Some recent examples are presented where this research impacts on software and their underlying algorithms. Space necessitates we assume the reader has a rough idea of what a DAE is. The examples are implicit Scicos, and optimization of DAE models. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Sparse principal component analysis via regularized low rank matrix approximation

Principal component analysis (PCA) is a widely used tool for data analysis and dimension reduction in applications throughout science and engineering. However, the principal components (PCs) can sometimes be difficult to interpret, because they are linear combinations of all the original variables. To facilitate interpretation, sparse PCA produces modified PCs with sparse loadings, i.e. loadings with very few non-zero elements. In this paper, we propose a new sparse PCA method, namely sparse PCA via regularized SVD (sPCA-rSVD). We use the connection of PCA with singular value decomposition (SVD) of the data matrix and extract the PCs through solving a low rank matrix approximation problem. Regularization penalties are introduced to the corresponding minimization problem to promote sparsity in PC loadings. An efficient iterative algorithm is proposed for computation. Two tuning parameter selection methods are discussed. Some theoretical results are established to justify the use of sPCA-rSVD when only the data covariance matrix is available. In addition, we give a modified definition of variance explained by the sparse PCs. The sPCA-rSVD provides a uniform treatment of both classical multivariate data and high-dimension-low-sample-size (HDLSS) data. Further understanding of sPCA-rSVD and some existing alternatives is gained through simulation studies and real data examples, which suggests that sPCA-rSVD provides competitive results.     

Decision tables in Algol 60

This paper defines an extension to Algol 60, which allows the programmer to write decision tables in his Algol program. A pre-processor converts the decision tables to Algol, and its output is used as input to the ordinary Algol compiler. The generated Algol program uses a straight-forward and efficient algorithm for choosing the appropriate decision rule.     

基于代理的网上智能购物系统

随着电子商务的快速发展,急切需要一个独立的、稳健的系统来为顾客提供决策支持.为了克服用户所经历回应时间太长的通讯困难,减少通讯的管理费用,介绍了一种移动的基于代理的智能购物系统.基于移动代理的系统应用不同的技术来发送一个移动软件代理到远程系统,从而用嵌入远程系统的软件来指挥多重交互,交互完成后输出结果返回到用户.实验结果证实对基于web的电子商务应用来说,基于移动代理的系统比现有的C/S系统更灵活.     

A modified fuzzy clustering for documents retrieval: application to document categorization

The paper advocates the use of a new fuzzy-based clustering algorithm for document categorization. Each document/datum will be represented as a fuzzy set. In this respect, the fuzzy clustering algorithm, will be constrained additionally in order to cluster fuzzy sets. Then, one needs to find a metric measure in order to detect the overlapping between documents and the cluster prototype (category). In this respect, we use one of the interclass probabilistic reparability measures known as Bhattacharyya distance, which will be incorporated in the general scheme of the fuzzy c-means algorithm for measuring the overlapping between fuzzy sets. This enables the introduction of fuzziness in the document clustering in the sense that it allows a single document to belong to more than one category. This is in line with semantic multiple interpretations conveyed by single words, which support multiple membership to several classes. Performances of the algorithms will be illustrated using a case study from the construction sector.     

Fuzzy criteria for feature selection

The presence of less relevant or highly correlated features often decrease classification accuracy. Feature selection in which most informative variables are selected for model generation is an important step in data-driven modeling. In feature selection, one often tries to satisfy multiple criteria such as feature discriminating power, model performance or subset cardinality. Therefore, a multi-objective formulation of the feature selection problem is more appropriate. In this paper, we propose to use fuzzy criteria in feature selection by using a fuzzy decision making framework. This formulation allows for a more flexible definition of the goals in feature selection, and avoids the problem of weighting different goals is classical multi-objective optimization. The optimization problem is solved using an ant colony optimization algorithm proposed in our previous work. We illustrate the added value of the approach by applying our proposed fuzzy feature selection algorithm to eight benchmark problems.     

Flow-level performance and capacity of wireless networks with user mobility

The performance evaluation of wireless networks is severely complicated by the specific features of radio communication, such as highly variable channel conditions, interference issues, and possible hand-offs among base stations. The latter elements have no natural counterparts in wireline scenarios, and create a need for novel performance models that account for the impact of these characteristics on the service rates of users. Motivated by the above issues, we review several models for characterizing the capacity and evaluating the flow-level performance of wireless networks carrying elastic data transfers. We first examine the flow-level performance and stability of a wide family of so-called α-fair channel-aware scheduling strategies. We establish that these disciplines provide maximum stability, and describe how the special case of the Proportional Fair policy gives rise to a Processor-Sharing model with a state-dependent service rate. Next we turn attention to a network of several base stations with inter-cell interference. We derive both necessary and sufficient stability conditions and construct lower and upper bounds for the flow-level performance measures. Lastly we investigate the impact of user mobility that occurs on a slow timescale and causes possible hand-offs of active sessions. We show that the mobility tends to increase the capacity region, both in the case of globally optimal scheduling and local α-fair scheduling. It is additionally demonstrated that the capacity and user throughput improve with lower values of the fairness index α.     

KamiWaAI – interactive 3D sketching with Java based on Cl(4, 1) conformal model of Euclidean space

This paper introduces the new interactive Java sketching software KamiWaAi, recently developed at the University of Fukui. Its graphical user interface enables the user without any knowledge of both mathematics or computer science, to do full three dimensional “drawings” on the screen. The resulting constructions can be reshaped interactively by dragging its points over the screen. The programming approach is new. KamiWaAi implements geometric objects like points, lines, circles, spheres, etc. directly as software objects (Java classes) of the same name. These software objects are geometric entities mathematically defined and manipulated in a conformal geometric algebra, combining the five dimensions of origin, three space and infinity. Simple geometric products in this algebra represent geometric unions, intersections, arbitrary rotations and translations, projections, distance, etc. To ease the coordinate free and matrix free implementation of this fundamental geometric product, a new algebraic three level approach is presented. Finally details about the Java classes of the new GeometricAlgebra software package and their associated methods are given. KamiWaAi is available for free internet download.     

无线通信中的最优资源分配―复杂性分析与算法设计

最优资源分配问题是无线通信系统设计中的基本问题之一.最优地分配功率、传输波形和频谱等资源能够极大地提高整个通信系统的传输性能.目前,相对于通信技术在现实生活中的蓬勃发展,通信系统优化的数学理论和方法显得相对滞后,在某些方面已经成为影响其发展和应用的关键因素.无线通信中的最优资源分配问题常常可建模为带有特殊结构的非凸非线性约束优化问题.一方面,这些优化问题常常具有高度的非线性性,一般情况下难于求解;另一方面,它们又有自身的特殊结构,如隐含的凸性和可分结构等.本文着重考虑多用户干扰信道中物理层资源最优分配问题的复杂性刻画,以及如何利用问题的特殊结构设计有效且满足分布式应用等实际要求的计算方法.     

Detecting Features in Spatial Point Processes with Clutter via Local Indicators of Spatial Association

We consider the problem of detecting features of general shape in spatial point processes in the presence of substantial clutter. Our goal is to remove clutter from images where one or several features are present and have to be detected. We use a method based on local indicators of spatial association (LISA) functions, particularly on the development of a local version of the product density which is a second-order characteristic of spatial point processes. The classification method is built upon a stochastic version of the EM algorithm (SEM). This method can be applied without user input about the number or shapes of the regions. Our proposal, compared with the kth nearest-neighbor technique, is tested through simulated examples yielding high detection and low false-positive rates. Two real case studies of connective loose tissues in human organs and earthquakes are also presented.     

An interactive visual simulation system for industrial management

This paper describes a discrete event interactive simulation system which allows a user to watch the progress of a simulation model on a visual display terminal. The user may interact with the model in a flexible manner, in order to explore the consequence of alternative decisions or strategies. Output from the simulation may be directed, in an animated form, to a refresh display computer graphics screen, a black and white visual display unit or an intelligent colour visual display divice. The interactive system has been specifically designed to assist in decision making processes associated with industrial management problem situations.     

基于质量安全投入的乳制品企业与经销商合作沟通机制形成的演化博弈分析

从我国乳制品企业和经销商尽快建立规范、高效的沟通机制的客观要求出发,本文探讨了乳制品企业和经销商之间的演化博弈关系。在阐述乳制品企业和经销商合作策略的基础上,基于有限理性,应用演化博弈模型分析基于质量安全投入的乳制品企业和经销商合作沟通机制形成的长期演化趋势,并运用Matlab 6.0软件对研究结果进行仿真分析。研究发现,降低经销商的“质量安全投入”成本、降低乳制品企业采取“建立沟通机制”所支付的成本、提高经销商的销售额外收益、增加在“质量安全不投入”策略下乳制品企业采取“不建立沟通机制”所多付出的损失成本、增加在“建立沟通机制”策略下经销商采取“质量安全不投入”所需缴纳的罚金、增加在“不建立沟通机制”策略下经销商给乳制品企业带来的损失,有助于乳制品企业和经销商合作沟通机制的形成。     

A dexterous feature selection artificial immune system algorithm for keystroke dynamics

The main problem in security protecting the computer or resources from intruders. The password and username are the most common means to provide security. But this method has many loop holes such as password sharing, shoulder surfing, brute-force attack, dictionary attack, guessing, and many more. Keystroke dynamics is one popular and inexpensive behavioral biometric technology, which identifies the authenticity of a user when the user is working via a keyboard. Keystroke features like dwell time and flight time of every user are evaluated in this paper by preprocessing techniques such as Hausdroff timing, mean, median, and standard deviation. The artificial immune system is used for feature selection, and comparison between preprocessing techniques is shown.