Semi-Parametric Analysis of Extreme Forest Fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper incidences of extreme wildland fires are modelled by a point process model which incorporates time-trend. A model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach, which is very useful in exploratory analysis of changes in extremes, is illustrated with the maximum likelihood method to estimate model parameters.

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.

Statistical analysis of extreme forest fires

Forest fires can cause extensive damage to natural resources and properties. They can also destroy wildlife habitat, affect the forest ecosystem and threaten human lives. In this paper extreme wildland fires are analysed using a point process model for extremes. The model based on a generalised Pareto distribution is used to model data on acres of wildland burnt by extreme fire in the US since 1825. A semi-parametric smoothing approach is adapted with maximum likelihood method to estimate model parameters.

AC & DC magnetic levitation and semi-levitation modelling

This work presents computation analysis of levitated liquid thermal and flow fields with free surface oscillations in AC and DC magnetic fields. The volume electromagnetic force distribution is continuously updated with the shape and position change. The oscillation frequency spectra are analysed for droplets levitation against gravity in AC and DC magnetic fields at various combinations. For larger volume liquid metal confinement and melting the semi-levitation induction skull melting process is simulated with the same numerical model. Applications are aimed at pure electromagnetic material processing techniques and the material properties measurements in uncontaminated conditions.

The semi-automatic parallelisation of scientific application codes using a computer aided parallelisation toolkit

The shared-memory programming model can be an effective way to achieve parallelism on shared memory parallel computers. Historically however, the lack of a programming standard using directives and the limited scalability have affected its take-up. Recent advances in hardware and software technologies have resulted in improvements to both the performance of parallel programs with compiler directives and the issue of portability with the introduction of OpenMP. In this study, the Computer Aided Parallelisation Toolkit has been extended to automatically generate OpenMP-based parallel programs with nominal user assistance. We categorize the different loop types and show how efficient directives can be placed using the toolkit's in-depth interprocedural analysis. Examples are taken from the NAS parallel benchmarks and a number of real-world application codes. This demonstrates the great potential of using the toolkit to quickly parallelise serial programs as well as the good performance achievable on up to 300 processors for hybrid message passing-directive parallelisations.

'Re-using an existing wheel' developing data architecture for cooperating autonomous and semi-autonomous, agent-based web services

This short position paper considers issues in developing Data Architecture for the Internet of Things (IoT) through the medium of an exemplar project, Domain Expertise Capture in Authoring and Development ­Environments (DECADE). A brief discussion sets the background for IoT, and the development of the ­distinction between things and computers. The paper makes a strong argument to avoid reinvention of the wheel, and to reuse approaches to distributed heterogeneous data architectures and the lessons learned from that work, and apply them to this situation. DECADE requires an autonomous recording system, ­local data storage, semi-autonomous verification model, sign-off mechanism, qualitative and ­quantitative ­analysis ­carried out when and where required through web-service architecture, based on ontology and analytic agents, with a self-maintaining ontology model. To develop this, we describe a web-service ­architecture, ­combining a distributed data warehouse, web services for analysis agents, ontology agents and a ­verification engine, with a centrally verified outcome database maintained by certifying body for qualification/­professional status.

Numerical optimisation techniques applied to evacuation analysis

A common problem faced by fire safety engineers in the field of evacuation analysis concerns the optimal design of an arbitrarily complex structure in order to minimise evacuation times. How does the engineer determine the best solution? In this study we introduce the concept of numerical optimisation techniques to address this problem. The study makes user of the buildingEXODUS evacuation model coupled with classical optimisation theory including Design of Experiments (DoE) and Response Surface Models (RSM). We demonstrate the technique using a relatively simple problem of determining the optimal location for a single exit in a square room.

The UK 9/11 evacuation study: Analysis of survivors’ recognition and response phase in WTC1

The September 11th 2001 impact on the World Trade Centre (WTC) resulted in one of the most significant evacuations of a high-rise building in modern times. The UK High-rise Evacuation Evaluation Database (HEED) study aimed to capture and collate the experiences and behaviours of WTC evacuees in a database, which would facilitate and encourage future research, which in turn would influence the design construction and use of safer built environments. A data elicitation tool designed for the purpose comprised a pre-interview questionnaire followed by a one-to-one interview protocol consisting of free-flow narratives and semi-structured interviews of WTC evacuees. This paper, which is one in a series dealing with issues relating to the successful evacuations of towers 1 and 2, focuses on cue recognition and response patterns within WTC1. Results are presented by vertical floor clusters and include information regarding cues experienced, activities prior and subsequent to occupants first becoming aware that something was wrong, perceived personal risk, time taken to respond and the inter-relationships between them. The results indicate differences in occupant activities across the floor clusters and suggest that these differences can be explained in terms of the perception of risk and the nature and extent of cues received by the participants.

Economic restructuring in New Zealand: A classical account

New Zealand's recent experiment with radical neoliberalism is well rehearsed in international policy circles. Yet, given the economic restructuring premise for the reforms, there has been little assessment of their structural impact. In this paper I take up this challenge, utilising [Shaikh, A., Tonak, E. Measuring the wealth of nations: the political economy of national accounts. Cambridge: Cambridge University Press; 1994] methodology for deriving classical value categories from official national accounts data but extending this to the industry level. This approach allows changes to the production and appropriation of surplus value in different industries during the period to be identified, underpinning a Marxian interpretation of restructuring. Beyond the methodology, the research makes four contributions. First, conventional analysis is found limited by its concentration on changes to the distribution of value rather than its creation. Second, land rents are significant. Third, the role of financial capital is found more complex than traditionally argued. Finally, the approach provides a firm grounding for the unfashionable concept of class fraction.