Combining method engineering with activity theory: theoretical grounding of the method component concept

The complex and demanding business of developing information systems often involves the use of different systems development methods such as the Rational Unified Process or the Microsoft Solution Framework. Through these methods the development organisation can be viewed as a collective of actors following different rules in the form of prescribed actions in order to guide a work process in accord with activity theory. Very often standardised systems development methods need tailoring for unique projects and strategies for this process have been labelled method engineering. Method configuration, a sub-discipline to method engineering, is applicable in situations where a single base method is used as a starting point for the engineering process. A meta-method (method for method configuration) has been developed addressing these issues. A fundamental part of this meta-method is the method component construct as a means to facilitate efficient and rationally motivated modularisation of systems development methods. This paper is an exploration of possible benefits of combining activity theory and method engineering as theoretical grounding of the method component concept.     

Meta-modelling based assembly techniques for situational method engineering

Method engineering for information system development is the discipline to construct new advanced development methods from parts of existing methods, called method fragments. To achieve this objective, we need to clarify how to model the existing methods and how to assemble method fragments into new project-specific methods, so-called situational methods. Especially, to produce meaningful methods, we should impose some constraints or rules on method assembly processes. In this paper, we propose a framework for hierarchical method modelling (meta-modelling) from three orthogonal dimensions: perspectives, abstraction and granularity. According to each dimension, methods and/or method fragments are hierarchically modelled and classified. Furthermore, we present a method assembly mechanism and its formalization as a set of rules. These rules are both syntactic and semantic constraints and presented in first order predicate logic so that they can play an important role in the assembly process of syntactically and semantically meaningful methods from existing method fragments. The benefit of our technique is illustrated by an example of method assembly, namely the integration of the Object Model and Harel's Statechart into Objectcharts.     

Recursion method for electronic structure calculations

We present a new recursion method based on the Trotter formula for the electronic structure calculations of molecules or solids. The proposed method has the feature to be more effective at high temperatures in contrast with direct calculations methods (real space or plane waves methods).     

Discontinuous Galerkin method on three-dimensional tetrahedral grids: Using the operator programming method

In the numerical simulation of gas-dynamic flows in domains with a complex geometry, it is necessary to use detailed unstructured grids and highly accurate numerical methods. The Galerkin method with discontinuous base functions (or the discontinuous Galerkin method) works well in dealing with such problems. This technique has several advantages inherent both in finite-element and in finite-difference approximations. At the same time, the discontinuous Galerkin method is computationally complex; therefore, the question arises about the most efficient use of the full potential of computers. In order to speed up the computations, we applied the operator programming method to develop the computational module. It allows presenting mathematical formulas in programs in compact form and helps to port programs to parallel architectures such as NVidia CUDA and Intel Xeon Phi. Earlier the operator programming method was implemented for regular three-dimensional Cartesian grids and three-dimensional locally adaptive grids. In this work, this method is applied to threedimensional tetrahedral grids. This example demonstrates that the method in question can be efficiently implemented on arbitrary three-dimensional grids. Besides, we demonstrate the use of the template metaprogramming methods of the C++ programming language in order to speed up computations.     

Iterative methods improving newton's method by the decomposition method

In this paper, we present a sequence of iterative methods improving Newton's method for solving nonlinear equations. The Adomian decomposition method is applied to an equivalent coupled system to construct the sequence of the methods whose order of convergence increases as it progresses. The orders of convergence are derived analytically, and then rederived by applying symbolic computation of Maple. Some numerical illustrations are given.     

A ranking method for multiple-criteria decision-making

Fuzzy logic is applied in more and more applications. Non-stochastic, inexact and uncertain concepts and decisions can thus be treated in a more natural way. Ranking methods based on fuzzy logic play an important role in practice and are widely applicable in decision-making. In a ranking task of a legal case these ordering methods are used, or, more exactly, a new one is developed that is similar to the R. Jain ordering method of multiple aspect alternatives; as such it is a special case of that. This 'mark-based method’ is based on the principle of ranking progress used in education. By considering the values of fuzzy attributes which characterize the alternatives as a mark (or after their transformation into marks) and aggregating the fuzzy sets of marks, the method orders only one 'extra’ mark to each alternative. The alternatives are ordered by their extra marks. The mark-based method is generally applicable in ranking tests, as several examples show. Compared to other methods (for example, ELECT RE II, NAIADE or Yager's method) the proposed ranking method leads to similar results.     

Comparison of the Singer method and the constraints method for molecular dynamics with linear molecules on the vector computer CYBER 205

The vectorization of FORTRAN programmes for the computation of the forces in molecular dynamics (MD) calculations are described. For systems containing linear molecules, two equivalent MD methods can be used: the Singer method and the constraints method. The FORTRAN vector code is presented and discussed for both methods. A comparison of computational times on the CYBER 205 is presented. For the two-centre Lennard-Jones potential, the constraints algorithm becomes increasingly less efficient than the Singer algorithm when executed on the CYBER 205. The reason for this is the difference in the neighbour-list which is made for the centre of each molecule in the Singer method and for each site in the molecule in the constraints method. Both programmes run about a factor of 15 faster on the Cyber 205 than on the conventional computer Cyber 175, for 108 or 256 linear molecules.     

基于改进模糊Borda法的直觉模糊组合多属性群决策方法

总结比较5种广泛应用的直觉模糊决策方法,发现针对同一问题,运用不同的决策方法可能得到不同的决策结果.针对这一现象,借鉴明确集范畴内的组合评价思想,提出基于改进模糊Borda法的直觉模糊组合多属性群决策方法,并对权重信息完全未知的直觉模糊组合决策问题进行研究,提出解决思路.将所提方法应用于多机种保障预案决策这一实际问题中,发现组合决策结果符合一致性检验要求,说明该方法具有一定的适用性,可以为直觉模糊决策提供一种新的思路和方法.     

Data hiding method using image interpolation

Data hiding is to conceal the existence of secret data. A reversible data hiding method can extract the cover image without any distortion from the stego-image after the hidden data have been extracted. This paper proposes a new interpolation and a data hiding method. The proposed scaling-up neighbor mean interpolation method has a low-time complexity and high-calculation speed. The proposed data hiding method is based on interpolation. Comparison on data hiding methods is divided into reversible or not. Our experimental results show the proposed method can embed a large amount of secret data while keeping a very high visual quality, the PSNR is guaranteed to be higher than 35 dB compared with other reversible data hiding methods. And also capacity is larger than any other reversible data hiding methods and comparable to other data hiding methods.     

基于Monte Carlo method的均衡度确定模型

蒙特卡罗方法(Monte Carlo method),也称统计模拟方法,是一种以概率统计理论为指导的一类非常重要的数值计算方法,是指使用随机数(或更常见的伪随机数)来解决很多计算问题的方法,本文尝试建立警察服务平台的均衡度模型并用蒙特卡罗方法求解,实验结果可以满足一般的应用需求。     

A B-spline collocation method for solving the incompressible Navier-Stokes equations using an ad hoc method: the Boundary Residual method

Collocation methods using piece-wise polynomials, including B-splines, have been developed to find approximate solutions to both ordinary and partial differential equations. Such methods are elegant in their simplicity and efficient in their application. The spline collocation method is typically more efficient than traditional Galerkin finite element methods, which are used to solve the equations of fluid dynamics. The collocation method avoids integration. Exact formulae are available to find derivatives on spline curves and surfaces. The primary objective of the present work is to determine the requirements for the successful application of B-spline collocation to solve the coupled, steady, 2D, incompressible Navier-Stokes and continuity equations for laminar flow. The successful application of B-spline collocation included the development of ad hoc method dubbed the Boundary Residual method to deal with the presence of the pressure terms in the Navier-Stokes equations. Historically, other ad hoc methods have been developed to solve the incompressible Navier-Stokes equations, including the artificial compressibility, pressure correction and penalty methods. Convergence studies show that the ad hoc Boundary Residual method is convergent toward an exact (manufactured) solution for the 2D, steady, incompressible Navier-Stokes and continuity equations. C¹ cubic and quartic B-spline schemes employing orthogonal collocation and C² cubic and C³ quartic B-spline schemes with collocation at the Greville points are investigated. The C³ quartic Greville scheme is shown to be the most efficient scheme for a given accuracy, even though the C¹ quartic orthogonal scheme is the most accurate for a given partition. Two solution approaches are employed, including a globally-convergent zero-finding Newton's method using an LU decomposition direct solver and the variable-metric minimization method using BFGS update.     

Adaptive photograph retrieval method

Access to electronic books, electronic journals, and web portals, which may contain graphics (drawings or diagrams) and images, is now ubiquitous. However, users may have photographs that contain graphics or images and want to access an electronic database to retrieve this information. Hence, an effective photograph retrieval method is needed. Although many content-based retrieval methods have been developed for images and graphics, few are designed to retrieve graphics and images simultaneously. Moreover, existing graphics retrieval methods use contour-based rather than pixel-based approaches. Contour-based methods, which are concerned with lines or curves, are inappropriate for images. To retrieve graphics and images simultaneously, this work applies an adaptive retrieval method. The proposed method uses histograms of oriented gradient (HOG) as pixel-based features. However, the characteristics of graphics and images differ, and this affects feature extraction and retrieval accuracy. Thus, an adaptive method is proposed that selects different HOG-based features for retrieving graphics and images. Experimental results demonstrate the proposed method has high retrieval accuracy even under noisy conditions.     

A new method for MR grayscale inhomogeneity correction

Intensity inhomogeneity is a smooth intensity change inside originally homogeneous regions. Filter-based inhomogeneity correction methods have been commonly used in literatures. However, there are few literatures which compare effectiveness of these methods for inhomogeneity correction. In this paper, a new filter-based inhomogeneity correction method is proposed and the effectiveness of the proposed method and other filter-based inhomogeneity correction methods are compared. The methods with different kernel sizes are applied on MRI brain images and the quality of inhomogeneity correction of different methods are compared quantitatively. Experimental results show the proposed method in a kernel size of 20 * 20 performs almost better than or equal the performance of other methods in all kernel sizes.     

A robust multi-scale integration method to obtain the depth from gradient maps

We describe a robust method for the recovery of the depth map (or height map) from a gradient map (or normal map) of a scene, such as would be obtained by photometric stereo or interferometry. Our method allows for uncertain or missing samples, which are often present in experimentally measured gradient maps, and also for sharp discontinuities in the scene’s depth, e.g. along object silhouette edges. By using a multi-scale approach, our integration algorithm achieves linear time and memory costs. A key feature of our method is the allowance for a given weight map that flags unreliable or missing gradient samples. We also describe several integration methods from the literature that are commonly used for this task. Based on theoretical analysis and tests with various synthetic and measured gradient maps, we argue that our algorithm is as accurate as the best existing methods, handling incomplete data and discontinuities, and is more efficient in time and memory usage, especially for large gradient maps.     

On the abstraction method for the container relocation problem

The container relocation problem or the blocks relocation problem is a classic combinatorial optimisation problem that occurs in day-to-day operations for facilities that use block stacking systems. A typical place where this problem arises is a container terminal where containers can be stacked vertically in order to utilise the scarce resource of yard surface, thus at times resulting in the unproductive reshuffling moves for containers stacked above the target container for retrieval. Due to the problem class being NP-hard, a number of studies on this topic propose heuristic approaches to solve this problem. There are a few exact methods (search-based algorithms or mathematical programming) proposed for this problem but the feasible problem size of such methods is quite restricted, limiting their practical significance. In this paper, we propose a new insight into reducing the search space of this problem by the abstraction method. Our main contribution to the existing literature is two-fold: the reduction in the search space by the abstraction method and the bidirectional search using the pattern database. Our computational results confirm that our approach enables instances of a near-practical size to be solved optimally within a reasonable computation time.     

A rigorous comparison of the Ewald method and the fast multipole method in two dimensions

The most efficient and proper standard method for simulating charged or dipolar systems is the Ewald method, which asymptotically scales as where N is the number of charges. However, recently the “fast multipole method” (FMM) which scales linearly with N has been developed. The break-even of the two methods (that is, the value of N below which Ewald is faster and above which FMM is faster) is very sensitive to the way the methods are optimized and implemented and to the required simulation accuracy.In this paper we use theoretical estimates and simulation results for the accuracies to carefully compare the two methods with respect to speed. We have developed and implemented highly efficient algorithms for both methods for a serial computer (a SPARCstation ELC) as well as a parallel computer (a T800 transputer based MEIKO computer). Breakevens in the range between N = 10 000 and N = 30 000 were found for reasonable values of the average accuracies found in our simulations. Furthermore, we illustrate how huge but rare single charge pair errors in the FMM inflate the error for some of the charges.     

Some properties of the output error method

The output error identification method is studied in various respects. The stationary points of the associated loss function are investigated. Sufficient conditions for a unique local minimum are given. The loss functions can be minimized using a quasilinearization algorithm. Such an algorithm will give good local convergence. It is, however, shown that global convergence does not always occur. The output error method is also compared with some other estimation methods from the accuracy point of view. It is proved that a prediction error method will give better accuracy. An instrumental variable technique may give better or worse accuracy depending on the actual noise correlation.     

An evolutionary method for efficient computation of mutual capacitance for VLSI circuits based on the method of images

The problem of computing the capacitance coupling in Very Large Scale Integrated (VLSI) circuits is studied in this work. The proposed method is an approximate extended version of the method of images. The initial problem is formulated here as an optimization problem for the solution of which a genetic algorithm (GA) is employed. The proposed method is fast, general, does not rely on fitting techniques and is applicable to an arbitrary 2D or 3D geometry configuration of conductors. Extensive simulation results are presented for several practical case studies. Comparative results are given with other methods from literature and a commercial tool employing the Finite Element Method (FEM). The results show that the capacitance value computed by our method is in close agreement to the value obtained by the other methods from literature and also by the commercial tool with the average difference ranging between 2% and 5% while demonstrating better scalability as the problem complexity rises.     

Hermite interpolation and a new iterative method¶for the computation of the roots¶of non-linear equations

We present a new iterative method, derived from Hermite interpolation, with order of convergence p = 1+ , which requires, at each step, only two function evaluations. The efficiency index of the method is better than those of classical methods, such as the secant method or Newton's method, and those of the recent methods introduced by Costabile et al. [1,2] as well. This method has the best efficiency index in a family of methods derived from Hermite interpolation. Received: September 2002 / Accepted: January 2003 Work supported by the Italian agency MURST.     

Combination of the boundary integral equation method and the extrapolation method

Many numerical methods including the boundary integral equation method start with division of the domain of calculation into intervals. The accuracy of their results can be improved considerably by extrapolation. To be able to apply the extrapolation method it is necessary to know the asymptotic expansion of the error.In this paper the principle of the extrapolation method and subjects important for its application are described. Above all it is shown how to determine the asymptotic expansions numerically by trial and error. In the first sections the matter is explained in a general manner to encourage users of various numerical methods—among them users of the finite element method—to try to extrapolate their results. Then the investigations are exemplified in detail by the boundary integral equation method. The accuracy of approximate solutions of integral equations for plane elastostatic problems with prescribed boundary tractions and displacements is improved by extrapolation. Particular attention is paid to boundary tractions and displacements with discontinuous derivatives.To induce also practically orientated readers without specialized mathematical knowledge to think about applying the extrapolation method the basic topics are represented in an extensive manner and illustrated by simple examples. (For a survey of this paper see end of Section 1.)