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2008 | Book

Formalization of Data Flow Computing and a Coinductive Approach to Verifying Flowware Synthesis Read chapter Read first chapter

Transactions on Computational Science I

Editors: Marina L. Gavrilova, C. J. Kenneth Tan

Publisher: Springer Berlin Heidelberg

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

We would like to present, with great pleasure, the inaugural volume of a new scholarly journal, Transactions on Computational Science. This journal is part of the Springer series Lecture Notes in Computer Science, and is devoted to the gamut of computational science issues, from theoretical aspects to application-dependent studies and the validation of emerging technologies. This new journal was envisioned and founded to represent the growing needs of computational science as an emerging and increasingly vital field, now widely recognized as an integral part of scientific and technical investigations. Its mission is to become a voice of the computational science community, addressing researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions. Transactions on Computational Science focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing facilitation of the theoretical foundations and the applications of lar- scale computations to massive data processing. The Journal is intended as a forum for practitioners and researchers to share computational techniques and solutions in the area, to identify new issues and to shape future directions for research, while industrial users may apply techniques of leading-edge, large-scale, high-performance computational methods.

Table of Contents

Frontmatter

Part 1 - Information Systems Design

Formalization of Data Flow Computing and a Coinductive Approach to Verifying Flowware Synthesis
Abstract
Reconfigurable computing refers to the notions of configware and flowware. Configware means structural programming, or programming in space to execute computation in space. Flowware means data-flow programming that schedules the data flow for output from or input to the configware architecture. In this paper, data flows of a synthesized computation are formalized. This means that data flow is specified as a behavioral stream function in stream calculus, which is used to underpin the semantics for Register Transfer Level (RTL) synthesis. A stream representation allows the use of coinductive principles in stream calculus. In particular, using the coinductive proof principle, we show that behavioral stream functions in the three-stage synthesis process (scheduling, register allocation and binding, allocation and binding of functional units) are always bisimilar regardless of changes in a scheduling, allocation or binding procedure. Our formalization makes pipelining possible, in which all functional units as well as registers of hardware resources are reused during different control steps (C-steps). Moreover, a coinductive approach to verifying flowware synthesis, which is independent of the heuristic during register allocating and binding step, is proposed as a practical technique.
Phan Cong Vinh, Jonathan P. Bowen
Partners Selection in Multi-Agent Systems by Using Linear and Non-linear Approaches
Abstract
Traditional negotiation approaches pay intensive attention to decision making models in order to reach the optimal agreements, while placing insufficient efforts on the problem of partner selection. In open and dynamic environments, when the number of potential partners is huge, it may be expensive or even impractical to perform complicated negotiations with all of its potential partners. In this paper, based on the proposed extended dual model, we propose both linear and non-linear approaches for partner selection in multi-agent systems. By employing these two approaches with the extended dual concern model, agents can adapt their individual behaviors for partners selection in negotiation. The proposed approaches have three merits, which are: (1) both agents’ own benefits and their potential partners’ benefits are considered during the partners selection process; (2) agents’ preferences are employed by the proposed approaches which ensure the selection results to accord with agents’ expectations; (3) the proposed approaches are sensitive to changes of the negotiation environment, so they can be adopted in open and dynamic negotiation environments. According to the case study in four scenarios, the selection results are reasonable and accord with agents’ expectations.
Fenghui Ren, Minjie Zhang
Topology Representing Network Map – A New Tool for Visualization of High-Dimensional Data
Abstract
In practical data mining problems high-dimensional data has to be analyzed. In most of these cases it is very informative to map and visualize the hidden structure of complex data set in a low-dimensional space. The aim of this paper is to propose a new mapping algorithm based both on the topology and the metric of the data.
The utilized Topology Representing Network (TRN) combines neural gas vector quantization and competitive Hebbian learning rule in such a way that the hidden data structure is approximated by a compact graph representation. TRN is able to define a low-dimensional manifold in the high-dimensional feature space. In case the existence of a manifold, multidimensional scaling and/or Sammon mapping of the graph distances can be used to form the map of the TRN (TRNMap).
The systematic analysis of the algorithms that can be used for data visualization and the numerical examples presented in this paper demonstrate that the resulting map gives a good representation of the topology and the metric of complex data sets, and the component plane representation of TRNMap is useful to explore the hidden relations among the features.
Agnes Vathy-Fogarassy, Attila Kiss, Janos Abonyi
Curve Fitting by Fractal Interpolation
Abstract
Fractal interpolation provides an efficient way to describe data that have an irregular or self-similar structure. Fractal interpolation literature focuses mainly on functions, i.e. on data points linearly ordered with respect to their abscissa. In practice, however, it is often useful to model curves as well as functions using fractal intepolation techniques. After reviewing existing methods for curve fitting using fractal interpolation, we introduce a new method that provides a more economical representation of curves than the existing ones. Comparative results show that the proposed method provides smaller errors or better compression ratios.
Polychronis Manousopoulos, Vassileios Drakopoulos, Theoharis Theoharis
Building Fuzzy Inference Systems with a New Interval Type-2 Fuzzy Logic Toolbox
Abstract
This paper presents the development and design of a graphical user interface and a command line programming Toolbox for construction, edition and simulation of Interval Type-2 Fuzzy Inference Systems. The Interval Type-2 Fuzzy Logic System (IT2FLS) Toolbox, is an environment for interval type-2 fuzzy logic inference system development. Tools that cover the different phases of the fuzzy system design process, from the initial description phase, to the final implementation phase, constitute the Toolbox. The Toolbox’s best qualities are the capacity to develop complex systems and the flexibility that allows the user to extend the availability of functions for working with the use of type-2 fuzzy operators, linguistic variables, interval type-2 membership functions, defuzzification methods and the evaluation of Interval Type-2 Fuzzy Inference Systems.
Juan R. Castro, Oscar Castillo, Patricia Melin, Antonio Rodríguez-Díaz

Part 2 - Data Processing and Industrial Applications

Comparative Analysis of Electrocardiogram Data by Means of Temporal Locality Approach with Additional Normalization
Abstract
Evolution of cardiac activity is investigated by means of nonlinear dynamics, namely the method of temporal localization on the attractor reconstructed from a digitized electrocardiogram signal. Convergence for the function of topological instability at changing dimensionality is proven both theoretically and numerically, independently from personal features of subjects in a latter case. This provides an opportunity to estimate the complexity (expressed through the number of freedom degrees) of cardiac dynamics. On the other hand, this instability function normalized by its average displays a different kind of behavior that somewhat differs for various persons and reflects their individual features. The essential reduction of computation time and necessary statistics are also attained by means of the developed algorithm.
Victor F. Dailyudenko
Missing Value Imputation Based on Data Clustering
Abstract
We propose an efficient nonparametric missing value imputation method based on clustering, called CMI (Clustering-based Missing value Imputation), for dealing with missing values in target attributes. In our approach, we impute the missing values of an instance A with plausible values that are generated from the data in the instances which do not contain missing values and are most similar to the instance A using a kernel-based method. Specifically, we first divide the dataset (including the instances with missing values) into clusters. Next, missing values of an instance A are patched up with the plausible values generated from A’s cluster. Extensive experiments show the effectiveness of the proposed method in missing value imputation task.
Shichao Zhang, Jilian Zhang, Xiaofeng Zhu, Yongsong Qin, Chengqi Zhang
Laminar Forced Convection in Circular Duct for Power-Law Fluid
Abstract
This paper considers the problem of viscous dissipation in power-law fluid flow through a tube of circular cross section. The solution to the problem is obtained by a series expansion about the complete eigenfunctions system of a Sturm-Liouville problem. The eigenfunctions and eigenvalues of this Sturm-Liouville problem are obtained by Galerkin’s method. The Graetz problem is also considered. Numerical examples are given for a viscous fluid with unit Brinkman number.
Tudor Boaca, Ioana Boaca
The Homotopy Wiener-Hermite Expansion and Perturbation Technique (WHEP)
Abstract
The Wiener-Hermite expansion linked with perturbation technique (WHEP) was used to solve perturbed non-linear stochastic differential equations. In this article, the homotopy perturbation method is used instead of the conventional perturbation methods which generalizes the WHEP technique such that it can be applied on non-linear stochastic differential equations without the necessity of the presence of the small parameter. The technique is called homotopy WHEP and is demonstrated through many non-linear problems.
Magdy A. El-Tawil
Backmatter
Metadata
Title
Transactions on Computational Science I
Editors
Marina L. Gavrilova
C. J. Kenneth Tan
Copyright Year
2008
Publisher
Springer Berlin Heidelberg
Electronic ISBN
978-3-540-79299-4
Print ISBN
978-3-540-79298-7
DOI
https://doi.org/10.1007/978-3-540-79299-4

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