728 resultados para post-deformation softening modelling


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Passenger experience has become a major factor that influences the success of an airport. In this context, passenger flow simulation has been used in designing and managing airports. However, most passenger flow simulations failed to consider the group dynamics when developing passenger flow models. In this paper, an agent-based model is presented to simulate passenger behaviour at the airport check-in and evacuation process. The simulation results show that the passenger behaviour can have significant influences on the performance and utilisation of services in airport terminals. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

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Post-earthquake fire (PEF) is considered one of the most high risk and complicated problems affecting buildings in urban areas and can cause even more damage than the earthquake itself. However, most standards and codes ignore the implications of PEF and so buildings are not normally designed with PEF in mind. What is needed is for PEF factors to be routinely scrutinized and codified as part of the design process. A systematic application is presented as a means of mitigating the risk of PEF in urban buildings. This covers both existing buildings, in terms of retrofit solutions, and those yet to be designed, where a PEF factor is proposed. To ensure the mitigation strategy meets the defined criteria, a minimum time is defined – the safety guaranteed time target – where the safety of the inhabitants in a building is guaranteed.

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Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

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1. Biodiversity, water quality and ecosystem processes in streams are known to be influenced by the terrestrial landscape over a range of spatial and temporal scales. Lumped attributes (i.e. per cent land use) are often used to characterise the condition of the catchment; however, they are not spatially explicit and do not account for the disproportionate influence of land located near the stream or connected by overland flow. 2. We compared seven landscape representation metrics to determine whether accounting for the spatial proximity and hydrological effects of land use can be used to account for additional variability in indicators of stream ecosystem health. The landscape metrics included the following: a lumped metric, four inverse-distance-weighted (IDW) metrics based on distance to the stream or survey site and two modified IDW metrics that also accounted for the level of hydrologic activity (HA-IDW). Ecosystem health data were obtained from the Ecological Health Monitoring Programme in Southeast Queensland, Australia and included measures of fish, invertebrates, physicochemistry and nutrients collected during two seasons over 4 years. Linear models were fitted to the stream indicators and landscape metrics, by season, and compared using an information-theoretic approach. 3. Although no single metric was most suitable for modelling all stream indicators, lumped metrics rarely performed as well as other metric types. Metrics based on proximity to the stream (IDW and HA-IDW) were more suitable for modelling fish indicators, while the HA-IDW metric based on proximity to the survey site generally outperformed others for invertebrates, irrespective of season. There was consistent support for metrics based on proximity to the survey site (IDW or HA-IDW) for all physicochemical indicators during the dry season, while a HA-IDW metric based on proximity to the stream was suitable for five of the six physicochemical indicators in the post-wet season. Only one nutrient indicator was tested and results showed that catchment area had a significant effect on the relationship between land use metrics and algal stable isotope ratios in both seasons. 4. Spatially explicit methods of landscape representation can clearly improve the predictive ability of many empirical models currently used to study the relationship between landscape, habitat and stream condition. A comparison of different metrics may provide clues about causal pathways and mechanistic processes behind correlative relationships and could be used to target restoration efforts strategically.

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Since the outbreak of Severe Acute Respiratory Syndrome (SARS) in 2003, there has been much discussion about whether the international community has moved into a new post-Westphalian era, where states increasingly recognize certain shared norms that guide what they ought to do in responding to infectious disease outbreaks. In this article I identify this new obligation as the ‘duty to report’, and examine competing accounts on the degree to which states appreciate this new obligation are considered by examining state behaviour during the H5N1 human infectious outbreaks in East Asia (since 2004). The article examines reporting behaviour for H5N1 human infectious cases in Cambodia, China, Indonesia, Thailand and Vietnam from 2004 to 2010. The findings lend strong support to the claim that East Asian states have come to accept and comply with the duty to report infectious disease outbreaks and that the assertions of sovereignty in response to global health governance frameworks have not systematically inhibited reporting compliance.

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Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models.

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This thesis investigates the influence of passenger group dynamics on passengers' behaviour in an international airport. A simulation model is built to analyse passengers' behaviour during airport departure processes and during an emergency event. Results from the model showed that passengers' group dynamics have significant influences on the performance and utilisation of airport services. The agent-based model also provides a convenient way to investigate the effectiveness of space design and service allocations, which may contribute to the enhancement of passenger airport experiences.

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Recent research has demonstrated that the same experiences that may elicit symptoms of post-traumatic stress disorder (PTSD) in emergency service personnel can also provide a catalyst for positive personal changes such as posttraumatic growth (PTG). In this research newly recruited police officers (N = 412) participated in a randomised control trial of a program specifically designed to promote mental health. On entry to the academy, new recruits were randomly allocated, by classrooms, to either a treatment as usual condition (i.e., existing psychoeducation program) or to the intervention group. The Promoting Resilient Officers (PRO) program is a resilience building intervention adapted from an earlier resilience building program in collaboration with the police service. The PRO program also includes additional components on trauma and PTG. The current research included the participants who had experienced trauma prior to or during the research period (N = 246). It was hypothesised that participation in the PRO program would increase levels of PTG and lower levels of PTSD when compared to recruits in the control condition. Using multilevel modelling and post-hoc analyses, results indicated there were significantly higher levels of PTG across multiple dimensions when compared to the control group. There was no effect on PTSD symptoms with both conditions showing a floor effect. The research indicated the potential value of developing interventions that elicit reflections on the potential for positive as well as negative outcomes of experiencing traumatic and other highly challenging events.