The use of a biased heuristic by a genetic algorithm applied to the design of multipoint connections in a local access network

This paper presents a genetic algorithm for finding a constrained minimum spanning tree. The problem is of relevance in the design of minimum cost communication networks, where there is a need to connect all the terminals at a user site to a terminal concentrator in a multipoint (tree) configuration, while ensuring that link capacity constraints are not violated. The approach used maintains a distinction between genotype and phenotype, which produces superior results to those found using a direct representation in a previous study.

Local likelihood smoothing of sample extremes

Trends in sample extremes are of interest in many contexts, an example being environmental statistics. Parametric models are often used to model trends in such data, but they may not be suitable for exploratory data analysis. This paper outlines a semiparametric approach to smoothing example extremes, based on local polynomial fitting of the generalized extreme value distribution and related models. The uncertainty of fits is assessed by using resampling methods. The methods are applied to data on extreme temperatures and on record times for the womens 3000m race.

Distributed belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

Local models for exploratory analysis of hydrological extremes

Trend analysis is widely used for detecting changes in hydrological data. Parametric methods for this employ pre-specified models and associated tests to assess significance, whereas non-parametric methods generally apply rank tests to the data. Neither approach is suitable for exploratory analysis, because parametric models impose a particular, perhaps unsuitable, form of trend, while testing may confirm that trend is present but does not describe its form. This paper describes semi-parametric approaches to trend analysis using local likelihood fitting of annual maximum and partial duration series and illustrates their application to the exploratory analysis of changes in extremes in sea level and river flow data. Bootstrap methods are used to quantify the variability of estimates.

Evaluation of distortions in laser welded shipbuilding parts using local-global finite element approach

In recognition of the differences of scale between the welding pool and the heat affected zone along the welding line on one hand, and the overall size of the components being welded on the other, a local-global finite element approach was developed for the evaluation of distortions in laser welded shipbuilding parts. The approach involves the tandem use of a 'local' and a 'global' step. The local step involves a three-dimensional finite element model for the simulation of the laser welding process using the Sysweld finite element code, which takes into account thermal, metallurgical, and mechanical aspects. The simulation of the laser welding process was performed using a non-linear heat transfer analysis, based on a keyhole formation model, and a coupled transient thermomechanical analysis, which takes into account metallurgical transformations using the temperature dependent material properties and the continuous cooling transformation diagram. The size and shape of the keyhole used in the local finite element analysis was evaluated using a keyhole formation model and the Physica finite volume code. The global step involves the transfer of residual plastic strains and the stiffness of the weld obtained from the local model to the global analysis, which then provides the predicted distortions for the whole part. This newly developed methodology was applied to the evaluation of global distortions due to laser welding of stiffeners on a shipbuilding part. The approach has been proved reliable in comparison with experiments and of practical industrial use in terms of computing time and storage.

A robust tri-state election algorithm for scalable applications

Existing election algorithms suffer limited scalability. This limit stems from the communication design which in turn stems from their fundamentally two-state behaviour. This paper presents a new election algorithm specifically designed to be highly scalable in broadcast networks whilst allowing any processing node to become coordinator with initially equal probability. To achieve this, careful attention has been paid to the communication design, and an additional state has been introduced. The design of the tri-state election algorithm has been motivated by the requirements analysis of a major research project to deliver robust scalable distributed applications, including load sharing, in hostile computing environments in which it is common for processing nodes to be rebooted frequently without notice. The new election algorithm is based in-part on a simple 'emergent' design. The science of emergence is of great relevance to developers of distributed applications because it describes how higher-level self-regulatory behaviour can arise from many participants following a small set of simple rules. The tri-state election algorithm is shown to have very low communication complexity in which the number of messages generated remains loosely-bounded regardless of scale for large systems; is highly scalable because nodes in the idle state do not transmit any messages; and because of its self-organising characteristics, is very stable.

Predicting toxic gas concentrations resulting from enclosure fires using local equivalence ratio concept linked to fire field models

A practical CFD method is presented in this study to predict the generation of toxic gases in enclosure fires. The model makes use of local combustion conditions to determine the yield of carbon monoxide, carbon dioxide, hydrocarbon, soot and oxygen. The local conditions used in the determination of these species are the local equivalence ratio (LER) and the local temperature. The heat released from combustion is calculated using the volumetric heat source model or the eddy dissipation model (EDM). The model is then used to simulate a range of reduced-scale and full-scale fire experiments. The model predictions for most of the predicted species are then shown to be in good agreement with the test results

Local examination of skin diffusion using FTIR spectroscopic imaging and multivariate target factor analysis

In the context of trans-dermal drug delivery it is very important to have mechanistic insight into the barrier function of the skin's stratum corneum and the diffusion mechanisms of topically applied drugs. Currently spectroscopic imaging techniques are evolving which enable a spatial examination of various types of samples in a dynamic way. ATR-FTIR imaging opens up the possibility to monitor spatial diffusion profiles across the stratum corneum of a skin sample. Multivariate data analyses methods based on factor analysis are able to provide insight into the large amount of spectroscopically complex and highly overlapping signals generated. Multivariate target factor analysis was used for spectral resolution and local diffusion profiles with time through stratum corneum. A model drug, 4-cyanophenol in polyethylene glycol 600 and water was studied. Results indicate that the average diffusion profiles between spatially different locations show similar profiles despite the heterogeneous nature of the biological sample and the challenging experimental set-up.

Putting down routes: an examination of local government cultural policy shaping the development of heritage trails

This paper explores the significance of trails within local government cultural strategies by presenting the results of an audit of 1000 trails, content analysis of local cultural strategies and a series of interviews with local government cultural officers. It highlights the growing sophistication of trails as flexible and multi-faceted products promising an array of social, environmental, cultural and economic benefits. However, key issues emerge as challenges for local government cultural officers. These include the need for a realistic assessment of the relative importance of competing rationales, the design of methodologies to enable evidence-based policy making and more effective engagement with commercial organisations.