The Dutch interbank computer network

At the end of 1980, a strategic decision was made by the Dutch banks and savings banks to commence the development of a Data Communications Infrastructure (DCI), to be used for a number of forthcoming interbank applications. It was agreed that this new data communications infrastructure should be based on the emerging Reference Model for Open Systems Interconnection (OSI). The first interbank application using the DCI (i.e. urgent money transfers) was introduced in the second quarter of 1985. Other interbank applications, which will also make use of the functions provided by the DCI, are currently being developed.\ud \ud This paper provides the background to the DCI project, discusses the selection of OSI standards for the network, and gives an overview of the design of the software package, which was developed to support the selected OSI standards

Polynomial (chaos) approximation of maximum eigenvalue functions: efficiency and limitations

This paper is concerned with polynomial approximations of the spectral abscissa function (the supremum of the real parts of the eigenvalues) of a parameterized eigenvalue problem, which are closely related to polynomial chaos approximations if the parameters correspond to realizations of random variables. Unlike in existing works, we highlight the major role of the smoothness properties of the spectral abscissa function. Even if the matrices of the eigenvalue problem are analytic functions of the parameters, the spectral abscissa function may not be everywhere differentiable, even not everywhere Lipschitz continuous, which is related to multiple rightmost eigenvalues or rightmost eigenvalues with multiplicity higher than one. The presented analysis demonstrates that the smoothness properties heavily affect the approximation errors of the Galerkin and collocation-based polynomial approximations, and the numerical errors of the evaluation of coefficients with integration methods. A documentation of the experiments, conducted on the benchmark problems through the software Chebfun, is publicly available.Comment: This is a pre-print of an article published in Numerical Algorithms. The final authenticated version is available online at: https://doi.org/10.1007/s11075-018-00648-

Some Special Cases in the Stability Analysis of Multi-Dimensional Time-Delay Systems Using The Matrix Lambert W function

This paper revisits a recently developed methodology based on the matrix Lambert W function for the stability analysis of linear time invariant, time delay systems. By studying a particular, yet common, second order system, we show that in general there is no one to one correspondence between the branches of the matrix Lambert W function and the characteristic roots of the system. Furthermore, it is shown that under mild conditions only two branches suffice to find the complete spectrum of the system, and that the principal branch can be used to find several roots, and not the dominant root only, as stated in previous works. The results are first presented analytically, and then verified by numerical experiments

Publish or patent?: Knowledge dissemination in agricultural biotechnology

"Plant transformation research has achieved outstanding progress in the development of transgenic crops over the past decades, and the research results have been spread through journal publications and patents. With the recent emergence of stronger intellectual property rights, investments in crop research and the landscape of plant transformation research have changed, along with the patterns of knowledge dissemination. In this paper, we discuss the recent trends in plant transformation research by examining patent and journal publication data during the last decade. The data analysis shows that there have been significant shifts toward applied research by developing countries and toward patenting as a means of knowledge dissemination during the past few decades, reflecting the increasing role of the private sector in developing countries in crop improvement research." from authors' abstractBiotechnology research, patents, Crop improvement, Science and technology, Genetic resources, Biodiversity, Journal publication, Developing countries,

Computing a partial Schur factorization of nonlinear eigenvalue problems using the infinite Arnoldi method

The partial Schur factorization can be used to represent several eigenpairs of a matrix in a numerically robust way. Different adaptions of the Arnoldi method are often used to compute partial Schur factorizations. We propose here a technique to compute a partial Schur factorization of a nonlinear eigenvalue problem (NEP). The technique is inspired by the algorithm in [8], now called the infinite Arnoldi method. The infinite Arnoldi method is a method designed for NEPs, and can be interpreted as Arnoldi's method applied to a linear infinite-dimensional operator, whose reciprocal eigenvalues are the solutions to the NEP. As a first result we show that the invariant pairs of the operator are equivalent to invariant pairs of the NEP. We characterize the structure of the invariant pairs of the operator and show how one can carry out a modification of the infinite Arnoldi method by respecting the structure. This also allows us to naturally add the feature known as locking. We nest this algorithm with an outer iteration, where the infinite Arnoldi method for a particular type of structured functions is appropriately restarted. The restarting exploits the structure and is inspired by the well-known implicitly restarted Arnoldi method for standard eigenvalue problems. The final algorithm is applied to examples from a benchmark collection, showing that both processing time and memory consumption can be considerably reduced with the restarting technique

An Inequality Constrained SL/QP Method for Minimizing the Spectral Abscissa

We consider a problem in eigenvalue optimization, in particular finding a local minimizer of the spectral abscissa - the value of a parameter that results in the smallest value of the largest real part of the spectrum of a matrix system. This is an important problem for the stabilization of control systems. Many systems require the spectra to lie in the left half plane in order for them to be stable. The optimization problem, however, is difficult to solve because the underlying objective function is nonconvex, nonsmooth, and non-Lipschitz. In addition, local minima tend to correspond to points of non-differentiability and locally non-Lipschitz behavior. We present a sequential linear and quadratic programming algorithm that solves a series of linear or quadratic subproblems formed by linearizing the surfaces corresponding to the largest eigenvalues. We present numerical results comparing the algorithms to the state of the art

Domain modelling and the co-design of business rules in the telecommunication business area.

This paper discusses the development of an enterprise domain model in an environment where part of the domain knowledge is vague and not yet formalised in company-wide business rules. The domain model was developed for a young company starting in the telecommunications sector. The company relied on a number of stand-alone business support systems and sought for a manner to integrate them. There was opted for the development of an enterprise-wide domain model that had to serve as an integration layer to coordinate the stand-alone applications. A specific feature of the company was that it could build up its information infrastructure form scratch, so that many aspects of its business were still in the process of being defined. The paper will highlight parts of the Enterprise Model where there was a need for co-designing business rules together with the domain model. A result of this whole effort was that the company got more insight into important domain knowledge and developed a common understanding across functional areas of the way of doing business.domain modelling; business rules; object-oriented analysis; business process modelling;

O(1) Computation of Legendre polynomials and Gauss-Legendre nodes and weights for parallel computing

A self-contained set of algorithms is proposed for the fast evaluation of Legendre polynomials of arbitrary degree and argument is an element of [-1, 1]. More specifically the time required to evaluate any Legendre polynomial, regardless of argument and degree, is bounded by a constant; i.e., the complexity is O(1). The proposed algorithm also immediately yields an O(1) algorithm for computing an arbitrary Gauss-Legendre quadrature node. Such a capability is crucial for efficiently performing certain parallel computations with high order Legendre polynomials, such as computing an integral in parallel by means of Gauss-Legendre quadrature and the parallel evaluation of Legendre series. In order to achieve the O(1) complexity, novel efficient asymptotic expansions are derived and used alongside known results. A C++ implementation is available from the authors that includes the evaluation routines of the Legendre polynomials and Gauss-Legendre quadrature rules