The Gaussian scale-space paradigm and the multiscale local jet

A representation of local image structure is proposed which takes into account both the image's spatial structure at a given location, as well as its deep structure, that is, its local behaviour as a function of scale or resolution (scale-space). This is of interest for several low-level image tasks. The proposed basis of scale-space, for example, enables a precise local study of interactions of neighbouring image intensities in the course of the blurring process. It also provides an extrapolation scheme for local image data, obtained at a given spatial location and resolution, to a finite scale-space neighbourhood. This is especially useful for the determination of sampling rates and for interpolation algorithms in a multilocal context. Another, particularly straightforward application is image enhancement or deblurring, which is an instance of data extrapolation in the high-resolution direction.A potentially interesting feature of the proposed local image parametrisation is that it captures a trade-off between spatial and scale extrapolations from a given interior point that do not exceed a given tolerance. This (rade-off suggests the possibility of a fairly coarse scale sampling at the expense of a dense spatial sampling large relative spatial overlap of scale-space kernels).The central concept developed in this paper is an equivalence class called the multiscale local jet, which is a hierarchical, local characterisation of the image in a full scale-space neighbourhood. For this local jet, a basis of fundamental polynomials is constructed that captures the scale-space paradigm at the local level up to any given order.     

Comparing notions of randomness

It is an open problem in the area of effective (algorithmic) randomness whether Kolmogorov-Loveland randomness coincides with Martin-Löf randomness. Joe Miller and André Nies suggested some variations of Kolmogorov-Loveland randomness to approach this problem and to provide a partial solution. We show that their proposed notion of injective randomness is still weaker than Martin-Löf randomness. Since in this proof some of the ideas we use are clearer, we also show the weaker theorem that permutation randomness is weaker than Martin-Löf randomness.     

Logic programming for combinatorial problems

Combinatorial problems appear in many areas in science, engineering, biomedicine, business, and operations research. This article presents a new intelligent computing approach for solving combinatorial problems, involving permutations and combinations, by incorporating logic programming. An overview of applied combinatorial problems in various domains is given. Such computationally hard and popular combinatorial problems as the traveling salesman problem are discussed to illustrate the usefulness of the logic programming approach. Detailed discussions of implementation of combinatorial problems with time complexity analyses are presented in Prolog, the standard language of logic programming. These programs can be easily integrated into other systems to implement logic programming in combinatorics.     

Worst case bounds on the point-wise discretization error in boundary element method for the elasticity problem

In this work, point-wise discretization error is bounded via interval approach for the elasticity problem using interval boundary element formulation. The formulation allows for computation of the worst case bounds on the boundary values for the elasticity problem. From these bounds the worst case bounds on the true solution at any point in the domain of the system can be computed. Examples are presented to demonstrate the effectiveness of the treatment of local discretization error in elasticity problem via interval methods.     

Board-Level Information Technology Governance Effects on Organizational Performance: The Roles of Strategic Alignment and Authoritarian Governance Style

ABSTRACT

We report on two empirical studies that explore key factors that help translate information technology governance by the board of directors into organizational performance. The first study shows that strategic alignment partially mediates the effect of board-level information technology governance on performance. The second study demonstrates that authoritarian governance style negatively moderates the effect of board-level information technology governance on performance. Together, these studies open up the black box between board-level information technology governance and organizational performance.     

Analyzing execution traces: critical-path analysis and distance analysis

International Journal on Software Tools for Technology Transfer - System designers make trade-offs between metrics of interest such as execution time, functional quality and cost to create a...     

Predicting the unexpected

Dagstuhl seminar no. 10102 on discrete event logistic systems recognized a network of persistent models to be a “Grand Challenge.” Such on-line model network will offer an infrastructure that facilitates the management of logistic operations. This ambition to create a network of persistent models implies a radical shift for model design activities as the objective is an infrastructure rather than application-specific solutions. In particular, model developers can no longer assume that they know what their model will be used for. It is no longer possible to design for the expected.This paper presents insights in model development and design in the absence of precise knowledge concerning a model's usage. Basically, model developers may solely rely on the presence of the real-world counterpart mirrored by their model and a general idea about the nature of the application (e.g. coordination of logistic operations). When the invariants of their real-world counterpart suffice for models to be valid, these models become reusable and integrate-able. As these models remain valid under a wide range of situations, they become multi-purpose and durable resources rather than single-purpose short-lived components or legacy, which is even worse.Moreover and more specifically, the paper describes how to build models that allow their users to generate predictions in unexpected situations and atypical conditions. Referring to previous work, the paper concisely discusses how these predictions can be generated starting from the models. This prediction-generating technology is currently being transferred into an industrial MES.     

Performance of classification models from a user perspective

This paper proposes a complete framework to assess the overall performance of classification models from a user perspective in terms of accuracy, comprehensibility, and justifiability. A review is provided of accuracy and comprehensibility measures, and a novel metric is introduced that allows one to measure the justifiability of classification models. Furthermore, taxonomy of domain constraints is introduced, and an overview of the existing approaches to impose constraints and include domain knowledge in data mining techniques is presented. Finally, justifiability metric is applied to a credit scoring and customer churn prediction case.     

Resource-efficient routing and scheduling of time-constrained streaming communication on networks-on-chip

Network-on-chip-based multiprocessor systems-on-chip are considered as future embedded systems platforms. One of the steps in mapping an application onto such a parallel platform involves scheduling the communication on the network-on-chip. This paper presents different scheduling strategies that minimize resource usage by exploiting all scheduling freedom offered by networks-on-chip. It also introduces a technique to take the dynamism in applications into account when scheduling the communication of an application on the network-on-chip while minimizing the resource usage. Our experiments show that resource-utilization is improved when compared to existing techniques.     

Misfit versus latency

In this paper we present a framework that combines some ideas of the behavioral modeling approach and the prediction error modeling approach. It is shown that the proposed model selection procedure can be rephrased as an optimization problem that only depends on the model parameters. Experiments illustrate the potential of the so-called misfit versus latency framework.