Relaxation method for unsteady convection–diffusion equations

We propose and implement a relaxation method for solving unsteady linear and nonlinear convection–diffusion equations with continuous or discontinuity-like initial conditions. The method transforms a convection–diffusion equation into a relaxation system, which contains a stiff source term. The resulting relaxation system is then solved by a third-order accurate implicit–explicit (IMEX) Runge–Kutta method in time and a fifth-order finite difference WENO scheme in space. Numerical results show that the method can be used to effectively solve convection–diffusion equations with both smooth structures and discontinuities.     

A Deductive Database Approach for Complex Objects

A deductive database approach for complex objects reasoning is proposed,which is characterized by handling predicates nesting in terms of mapping hierarchically structured rules and facts to a flattened Horn-clause implementation scheme.     

A New Approach for Automation of Distributed Systems

The concept Lean Web Automation (LWA) describes a new approach for web-based operation of automation devices in distributed systems, which can be used flexible by means of compact and low-cost software without installation expense on the client side. A dynamic process data transfer in the TCP/IP network is implemented by a javabased application model. This model uses a process data proxy to create at web clients an interface to process data of a remote automation device. A first practical …     

A Direct Approach for Finding Loop Transformation Matrices

Loop transformations,such as loop interchange,reversal and skewing,have been unified under linear matrix transformations.A legal transformation matrix is usually generated based upon distance vectors or direction vectors.Unfortunately,for some nested loops,distance vectors may not be computable and direction vectors, Unfortunately,for some nested loops,distance vectors may not be computable and direction vectors,on the other hand,may not contain useful information.We propose the use of linear equations or inequalities of distance vectors to approximate data dependence.This approach is advantageous since(1) many loops having no constant distance vectors have very simple equations of distance vectors;(2) these equations contain more information than direction vectors do,thus the chance of exploiting potential parallelism is improved.In general,the equations or inequalities that approximate the data dependence of a given nested loop is not unique,hence classification is discussed for the purpose of loop transformationEfficient algorithms are developed to generate all kinds of linear equations of distance vectors for a given nested loop.The issue of how to obtain a desired transformation matrix from those equations is also addressed.     

ELA—A new Approach for Learning Agents

In this paper we discuss a new incremental learning approach used to implement adaptive behavior in autonomous agents. Adaptive agents must increase their performance based on experience using some learning approach. Often, incremental learning techniques like memory-based reasoning (MBR) are used. However, traditional MBR algorithms require an adequate (generally complex) measure of similarity, need much data and spend much time for computing similarities between examples. Such problems are unacceptable for autonomous agents that live in very dynamic environments, because they have little time to make decisions. Our approach does not use similarity measures between examples, classifies examples very fast and can compact data. We represent data as a concept graph (CG), each node representing a partition of the data. We propose an algorithm that uses the partitions to classify new examples. We compare our results with other techniques and conclude that the method performs quite well. Finally, we apply the approach to an application of adaptive agents for personalizing web search.This research was funded by Région Picardie in France. We thank Emerson Paraiso and Cesar Tacla for comments and time spent with the discussions.     

A Test Approach for Look-Up Table Based FPGAs

This paper describes a test architecture for minimum number of test configurations in test of FPGA （Field Programmable Gate Array） LUTs （Look Up Tables）. The test architecture includes a TPG （Test Pattern Generator） that is tested while it is generating test data for LEs （Logic Elements） that form the CUT （Circuit Under Test）. This scheme eliminates the need for switching LEs between CUT, TPG and ORA （Output Response Analyzer） and having to perform many more reconfiguratioas of the FPGA. An external ORA locates faults of the FPGA under test. In addition to the LUTs, a scheme is presented for testing other parts of LEs. Compared with other methods, the presented scheme uses the least number of reconfigurations of an FPGA for its LUT testing.     

A Monolithic Approach to Fluid–Composite Structure Interaction

We study a nonlinear fluid–structure interaction (FSI) problem between an incompressible, viscous fluid and a composite elastic structure consisting of two layers: a thin layer (membrane) in direct contact with the fluid, and a thick layer (3D linearly elastic structure) sitting on top of the thin layer. The coupling between the fluid and structure, and the coupling between the two structures is achieved via the kinematic and dynamic coupling conditions modeling no-slip and balance of forces, respectively. The coupling is evaluated at the moving fluid–structure interface with mass, i.e., the thin structure. To solve this nonlinear moving-boundary problem in 3D, a monolithic, fully implicit method was developed, and combined with an arbitrary Lagrangian–Eulerian approach to deal with the motion of the fluid domain. This class of problems and its generalizations are important in e.g., modeling FSI between blood flow and arterial walls, which are known to be composed of several different layers, each with different mechanical characteristics and thickness. By using this model we show how multi-layered structure of arterial walls influences the pressure wave propagation in arterial walls, and how the presence of atheroma and the presence of a vascular device called stent, influence intramural strain distribution throughout different layers of the arterial wall. The detailed intramural strain distribution provided by this model can be used in conjunction with ultrasound B-mode scans as a predictive tool for an early detection of atherosclerosis (Zahnd et al. in IEEE international on ultrasonics symposium (IUS), pp 1770–1773, 2011).     

A Holistic Approach for E?cient Contour Detection

Object contours contain important visual information which can be applied to numerous vision tasks. As recent algorithms focus on the accuracy of contour detection, the entailed time complexity is sign...     

A Sequential Design Approach for Switching ℌ∞ LPV Control

This paper proposes a sequential design scheme for switching ℌ_∞ LPV (Linear Parameter-Varying) control, aiming to reduce the computational complexity of the associated optimization problem. Different from the traditional approach that simultaneously designs switching LPV controllers and solves a high-dimensional optimization problem, the proposed sequential design approach renders a bundle of low-dimensional optimization problems to be solved iteratively. Individual ℌ_∞ LPV controller for each subregion is synthesized by independent PLMIs (Parametric Linear Matrix Inequalities) to guarantee ℌ_∞ performance, and controller variables are interpolated on the overlapped subregions such that the ℌ_∞ performance is also guaranteed on the overlapped subregion. Numerical examples are used to demonstrate the effectiveness of this method to reduce the computational load in each design iteration and improved ℌ_∞ performance over the conventional simultaneous design method with well-tuned interpolation coefficient.

     

A Least-Squares/Relaxation Method for the Numerical Solution of the Three-Dimensional Elliptic Monge–Ampère Equation

In this article, we address the numerical solution of the Dirichlet problem for the three-dimensional elliptic Monge–Ampère equation using a least-squares/relaxation approach. The relaxation algorithm allows the decoupling of the differential operators from the nonlinearities. Dedicated numerical solvers are derived for the efficient solution of the local optimization problems with cubicly nonlinear equality constraints. The approximation relies on mixed low order finite element methods with regularization techniques. The results of numerical experiments show the convergence of our relaxation method to a convex classical solution if such a solution exists; otherwise they show convergence to a generalized solution in a least-squares sense. These results show also the robustness of our methodology and its ability at handling curved boundaries and non-convex domains.     

A Domain Knowledge Driven Approach for User Interface Software Development

A domain knowledge driven user interface development approach is described.As a conceptual design of the user interface,the domain knowledge defines the user interface in terms of objects,actions and their relationships that the user would use to interact with the application system.It also serves as input to a user interface management system (UIMS) and is the kernel of the target user interface.The principal ideas and the implementation techniques of the approach is discussed.The user interface model,user interface designer oriented high-level specification notatiopn,and the transformation algorithms on domain knowledge are presented.     

A Right-Preconditioning Process for the Formal–Algebraic Approach to Inner and Outer Estimation of AE-Solution Sets

Aright-preconditioning process for linear interval systems has been presented by Neumaier in 1987. It allows the construction of an outer estimate of the united solution set of a square linear interval system in the form of a parallelepiped. The denomination “right-preconditioning” is used to describe the preconditioning processes which involve the matrix product AC in contrast to the (usual) left-preconditioning processes which involve the matrix product AC, where A and C are respectively the interval matrix of the studied linear interval system and the preconditioning matrix.The present paper presents a new right-preconditioning process similar to the one presented by Neumaier in 1987 but in the more general context of the inner and outer estimations of linear AEsolution sets. Following the spirit of the formal-algebraic approach to AE-solution sets estimation, summarized by Shary in 2002, the new right-preconditioning process is presented in the form of two new auxiliary interval equations. Then, the resolution of these auxiliary interval equations leads to inner and outer estimates of AE-solution sets in the form of parallelepipeds. This right-preconditioning process has two advantages: on one hand, the parallelepipeds estimates are often more precise than the interval vectors estimates computed by Shary. On the other hand, in many situations, it simplifies the formal algebraic approach to inner estimation of AE-solution sets. Therefore, some AE-solution sets which were almost impossible to inner estimate with interval vectors, become simple to inner estimate using parallelepipeds. These benefits are supported by theoretical results and by some experimentations on academic examples of linear interval systems.     

A Systolic Approach for an Improvement of a Finite Field Multiplier

This paper proposes a systolic finite multiplier, which appears to functionreasonably. And it shows that systolic architecture is a useful design tool for compute-bound applications.     

Image Fusion for Enhanced Visualization: A Variational Approach

We present a variational model to perform the fusion of an arbitrary number of images while preserving the salient information and enhancing the contrast for visualization. We propose to use the structure tensor to simultaneously describe the geometry of all the inputs. The basic idea is that the fused image should have a structure tensor which approximates the structure tensor obtained from the multiple inputs. At the same time, the fused image should appear ‘natural’ and ‘sharp’ to a human interpreter. We therefore propose to combine the geometry merging of the inputs with perceptual enhancement and intensity correction. This is performed through a minimization functional approach which implicitly takes into account a set of human vision characteristics.     

TAPISTRY—A Software Process Improvement Approach Tailored for Small Enterprises

TAPISTRY is a tutored process improvement approach tailored for small enterprises. The approach was developed, used and validated in an ongoing ESSI Esprit project (No 24238), called “TAPISTRY.” The TAPISTRY project adopted a downscaled assessment model of the BOOTSTRAP assessment methodology, called BootCheck, and developed a workshop-based assessment and improvement method, to form together a process improvement approach for small-to-medium-sized enterprises. In TAPISTRY workshops the participants are tutored in self-assessment and improvement planning by software process improvement experts. The resulting TAPISTRY approach was validated through the experiments performed during the TAPISTRY project. This revised version was published online in August 2006 with corrections to the Cover Date.     

The Neural Network Approach to Input–Output Analysis for Economic Systems

Economic practitioners in China are giving up the classical Leontief’s Input–Output analysis methods. This paper offers an alternative method of input–output analysis. The proposed method is based on the layered neural network model. It shows that neural networks method can be useful for input–output analysis for a dynamic economic system.       

A New Subdivision Algorithm for the Bernstein Polynomial Approach to Global Optimization

In this paper,an improved algorithm is proposed for unconstrained global optimization to tackle non-convex nonlinear multivariate polynomial programming problems.The proposed algorithm is based on the Bernstein polynomial approach.Novel features of the proposed algorithm are that it uses a new rule for the selection of the subdivision point,modified rules for the selection of the subdivision direction,and a new acceleration device to avoid some unnecessary subdivisions.The performance of the proposed algorithm is numerically tested on a collection of 16 test problems.The results of the tests show the proposed algorithm to be superior to the existing Bernstein algorithm in terms of the chosen performance metrics.