Use of discrete gradient operators for the automatic determination of vanishing points: Comparative analysis

Thales’ second theorem can be used for the automatic detection of the vanishing points of an image. This paper explores its reliability and accuracy according to the type of operator used for the detection of edges. An algorithm has been used which processes a photographic image according to the operator selected. The result is a point cloud which is then used to find the desired solution. The comparison between the four discrete gradient operators (Frei-Chen, Prewitt, Roberts and Sobel) has been made taking into account the resolution of the image and the number of vanishing points. The results obtained show that Frei-Chen’s operator shows good performance in determining vanishing points with respect to the spatial X axis, Sobel’s operator is the best for determining the vanishing point with respect to the spatial Y axis, Roberts’ operator gives good results for calculating vanishing points in both spatial axes, and Prewitt’s operator is not appropriate for processing this type of image.     

Government policy,public value and IT outsourcing: The strategic case of ASPIRE

The paper examines government IT outsourcing polices. The paper critiques the concept of ‘the Contract State’, and suggests how more disciplined uses of outsourcing can assist the creation of public value, more broadly conceived. Within the context of international developments, we study the United Kingdom Inland Revenue (IR), Customs and Excise (HMRC) and Department of Social Security (DSS) and their IT outsourcing contracts. The evidence suggests that outsourcing and marketization initiatives have adverse public value impacts, and may need to be rethought. Major IT operations and innovations, for example e-government, National Health Service (NHS) and identity card IT policies in the UK, are managed and generate legacies that do not always make efficient and effective use of the market. Moreover, their objectives, implementation and management over time may truncate their value to the public at large. Applying a revised Public Value policy approach offers a richer perspective to guide central government decisions worldwide about future IT outsourcing.     

Multi‐objective optimization using metaheuristics: non‐standard algorithms

In recent years, the application of metaheuristic techniques to solve multi‐objective optimization problems has become an active research area. Solving this kind of problems involves obtaining a set of Pareto‐optimal solutions in such a way that the corresponding Pareto front fulfils the requirements of convergence to the true Pareto front and uniform diversity. Most of the studies on metaheuristics for multi‐objective optimization are focused on Evolutionary Algorithms, and some of the state‐of‐the‐art techniques belong this class of algorithms. Our goal in this paper is to study open research lines related to metaheuristics but focusing on less explored areas to provide new perspectives to those researchers interested in multi‐objective optimization. In particular, we focus on non‐evolutionary metaheuristics, hybrid multi‐objective metaheuristics, parallel multi‐objective optimization and multi‐objective optimization under uncertainty. We analyze these issues and discuss open research lines.     

Evaluation of graded-channel SOI MOSFET operation at high temperatures

This paper presents a comparative analysis between graded-channel (GC) and conventional fully depleted SOI MOSFETs devices operating at high temperatures (up to 300 °C). The electrical characteristics such as threshold voltage and subthreshold slope were obtained experimentally and by two-dimensional numerical simulations. The results indicated that GC transistors present nearly the same behavior as the conventional SOI MOSFET devices with similar channel length. Experimental analysis of the g_m/I_DS ratio and Early voltage demonstrated that in GC devices the low-frequency open-loop gain is significantly improved in comparison to conventional SOI devices at room and at high-temperature due to the Early voltage increase. The multiplication factor and parasitic bipolar transistor gain obtained by two-dimensional numerical simulations allowed the analysis of the breakdown voltage, which was demonstrated to be improved in the GC as compared to conventional SOI transistors in thin silicon layer devices in the whole temperature range under analysis.     

A new methodology to solve non‐linear equation systems using genetic algorithms. Application to combined cyclegas turbine simulation

This paper shows a methodology to sort out the equations of a non‐linear system in order to solve it by the fixed‐point method. The arrangement of the equations is established by a genetic algorithm that deals with a population of possible resolution processes of the system. The method is specially useful in the following situations: first, when the system is very non‐linear and has many variables (where the Newton–Raphson method does not work properly); second, when the number of equations and variables may be altered because the equation system may change in each simulation and, therefore, more than one only solution process is needed if the fixed‐point process is employed. As an example, the methodology has been applied to solve the equation system that models the behaviour of a heat recovery steam generator of a combined cycle power plant at full load and part load conditions. Copyright © 2005 John Wiley & Sons, Ltd.     

Soft component adaptation

Component adaptation is widely recognised to be one of the crucial problems in Component-Based Software Engineering (CBSE). We present here a formal methodology for the soft adaptation of components presenting mismatching interaction behaviours. The notions of access rights (associating components with the services they are allowed to use) and subservicing (providing alternative services in place of those requested by components lacking the required access rights) are exploited to feature a secure and flexible adaptation of third-party components.     

Inflating examples to obtain rules

A new machine learning system is presented in this article. It is called INNER and induces classification rules from a set of training examples. The process followed by this system starts with the random selection of a subset of examples that are iteratively inflated in order to cover the surroundings provided that they are inhabited by examples of the same class, thus becoming rules that will be applied by means of a partial matching mechanism. The rules so obtained can be seen as clusters of examples and represent clear evidence to support explanations about their future classifications and may be used to build intelligent advisors. The whole algorithm can be seen as a set of elastic transformations of examples and rules and produces concise, accurate rule sets, as is experimentally demonstrated in the final section of the article. © 2003 Wiley Periodicals, Inc.     

Parameter estimation in Bayesian reconstruction of SPECT images: An aid in nuclear medicine diagnosis

Despite the adequacy of Bayesian methods to reconstruct nuclear medicine SPECT (single‐photon emission computed tomography) images, they are rarely used in everyday medical practice. This is primarily because of their computational cost and the need to appropriately select the prior model hyperparameters. We propose a simple procedure for the estimation of these hyperparameters and the reconstruction of the original image and test the procedure on both synthetic and real SPECT images. The experimental results demonstrate that the proposed hyperparameter estimation method produces satisfactory reconstructions. Although we have used generalized Gaussian Markov random fields (GGMRF) as prior models, the proposed estimation method can be applied to any priors with convex potential and tractable partition function with respect to the scale hyperparameter. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 21–27, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20003