83 resultados para McSloy, Hugh E.


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During the past century, significant improvements in the prevention, detection and treatment of infectious disease have positively impacted upon quality and quantity of life for many people worldwide. Despite this progress, there are large numbers of people currently living in developing regions of the world where infectious disease continues unabated. SurfAid International is a humanitarian organisation that has brought significant health improvements to the people living on the Mentawai and Nias islands of Indonesia. The SurfAid International Schools Program aims to develop global citizenship and social responsibility by providing a bridge between school settings and the critical work of SurfAid International. This paper provides a rationale for the development of contextualised school based programs and identifies potential impact upon the thoughts and actions of young people in schools.

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The climatic conditions of tropical and subtropical regions within Australia present, at times, extreme risk of physical activity induced heat illness. Many administrators and teachers in school settings are aware of the general risks of heat related illness. In the absence of reliable information applied at the local level, there is a risk that inappropriate decisions may be made concerning school events that incorporate opportunities to be physically active. Such events may be prematurely cancelled resulting in the loss of necessary time for physical activity. Under high or extremely high risk conditions however, the absence of appropriate modifications or continuation could place the health of students, staff and other parties at risk. School staff and other key stakeholders should understand the mechanisms of escalating risk and be supported to undertake action to reduce the level of risk through appropriate policies, procedures, resources and action plans.

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1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

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Environmental impacts caused during Australia's comparatively recent settlement by Europeans are evident. Governments (both Commonwealth and States) have been largely responsible for requiring landholders – through leasehold development conditions and taxation concessions – to conduct clearing that is now perceived as damage. Most governments are now demanding resource protection. There is a measure of bewilderment (if not resentment) among landholders because of this change. The more populous States, where most overall damage has been done (i.e. Victoria and New South Wales), provide most support for attempts to stop development in other regions where there has been less damage. Queensland, i.e. the north-eastern quarter of the continent, has been relatively slow to develop. It also holds the largest and most diverse natural environments. Tree clearing is an unavoidable element of land development, whether to access and enhance native grasses for livestock or to allow for urban developments (with exotic tree plantings). The consequences in terms of regulations are particularly complex because of the dynamic nature of vegetation. The regulatory terms used in current legislation – such as 'Endangered' and 'Of concern' – depend on legally-defined, static baselines. Regrowth and fire damage are two obvious causes of change. A less obvious aspect is succession, where ecosystems change naturally over long timeframes. In the recent past, the Queensland Government encouraged extensive tree-clearing e.g. through the State Brigalow Development Scheme (mostly 1962 to 1975) which resulted in the removal of some 97% of the wide-ranging mature forests of Acacia harpophylla. At the same time, this government controls National Parks and other reservations (occupying some 4% of the State's 1.7 million km2 area) and also holds major World Heritage Areas (such as the Great Barrier Reef and the Wet Tropics Rainforest) promulgated under Commonwealth legislation. This is a highly prescriptive approach, where the community is directed on the one hand to develop (largely through lease conditions) and on the other to avoid development (largely by unusable reserves). Another approach to development and conservation is still possible in Queensland. For this to occur, however, a more workable and equitable solution than has been employed to date is needed, especially for the remote lands of this State. This must involve resident landholders, who have the capacity (through local knowledge, infrastructure and daily presence) to undertake most costeffectively sustainable land-use management (with suitable attention to ecosystems requiring special conservation effort), that is, provided they have the necessary direction, encouragement and incentive to do so.

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Marinas currently exist primarily to service recreational boats, and these vessels are a potential cause of both problems and opportunities in environmental management. Thus, on the one hand, destructive fuel and other pollutants may be expelled, boat wakes can cause littoral soil erosion, physical damage results from collisions with marine life, and litter and noise pollution occur in otherwise pristine habitat. Boats also provide access to otherwise inaccessible natural environments for educational and other management reasons. In this study, boat traffic at three large marinas located along the Queensland coastline has been field surveyed for introductory information. No attempt was made at this juncture to survey the behaviour of the boat crews and passengers (concerning actual destinations, activities on board, etc. or to survey the recreational boat industry. Such studies rely on boat registration records and personal questionnaires. Some other surveys relating to fishing draw on boat ramp surveys and direct submissions by recreational fishers; these provide some data on daily usage of boat ramps, but without particular attention to boats. We believe field observations of overall boat activities in the water are necessary for environmental management purposes. The aim of the survey was to provide information to help prioritize the potential impacts that boats’ activities have on the surrounding natural environment. Any impact by boats will be a product of their numbers, size, frequency of movement, carrying capacity and routes/destinations. The severity of impacts will dictate the appropriate management action.

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To achieve best environmental management practice in Queensland, effort needs to be extended into the private sector. A Regional Landscape Strategy compiled for any substantial new proposal must identify the most promising technique(s) (from an available tool kit of 13) by which a developer (of any type) is more likely to sustain on-site resources while assisting government deliver its future plans in any region of the State. Offsetting may prove to be one of the most effective of these tools. However, policy must address‘offset land mitigation’, whereby the necessary financial incentives are introduced. Practicable methods by which offset sites can be selected, and measurement of their consequent environmental benefit, have now been devised and tested to assist this process.

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A method of selecting land in any region of Queensland for offsetting purposes is devised, employing uniform standards. The procedure first requires that any core natural asset lands, Crown environmental lands, prime urban and agricultural lands, and highly contentious sites in the region be eliminated from consideration. Other land is then sought that is located between existing large reservations and the centre of greatest potential regional development/disturbance. Using the criteria of rehabilitation (rather than preservation) plus proximity to those officially defined Regional Ecosystems that are most threatened, adjacent sites that are described as ‘Cleared’ are identified in terms of agricultural land capability. Class IV lands – defined as those ‘which may be safely used for occasional cultivation with careful management’,2 ‘where it is favourably located for special usag€™,3 and where it is ‘helpful to those who are interested in industry or regional planning or in reconstruction’4 – are examined for their appropriate area, for current tenure and for any conditions such as Mining Leases that may exist. The positive impacts from offsets on adjoining lands can then be designed to be significant; examples are also offered in respect of riparian areas and of Marine Parks. Criteria against which to measure performance for trading purposes include functional lift, with other case studies about this matter reported separately in this issue. The procedure takes no account of demand side economics (financial additionality), which requires commercial rather than environmental analysis.

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From 19 authoritative lists with 164 entries of ‘endangered’ Australian mammal species, 39 species have been reported as extinct. When examined in the light of field conditions, the 18 of these species thought to be from Queensland consist of (a) species described from fragmentary museum material collected in the earliest days of exploration, (b) populations inferred to exist in Queensland by extrapolation from distribution records in neighbouring States or countries, (c) inhabitants of remote and harsh locations where search effort is extraordinarily difficult (especially in circumstances of drought or flooding). and/or (d) individuals that are clearly transitory or peripheral in distribution. ‘Rediscovery’ of such scarce species - a not infrequent occurrence - is nowadays attracting increasing attention. Management in respect of any scarce wildlife in Queensland presently derives from such official lists. The analyses here indicate that this method of prioritizing action needs review. This is especially so because action then tends to be centred on species chosen out of the lists for populist reasons and that mostly addresses Crown lands. There is reason to believe that the preferred management may lie private lands where casual observation has provided for rediscovery and where management is most desirable and practicable.

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The process of offsetting land against unavoidable disturbance of development sites in Queensland will benefit from a method that allows the best possible selection to be made of alternative lands. With site selection now advocated through a combination of Regional Ecosystem and Land Capability classifications state-wide, a case study has determined methods of assessing the functional lift – that is, measures of net environmental gain – of such action. Outcomes with potentially high functional lift are determined, that offer promise not only for endangered ecosystems but also for managing adjacent conservation reserves.

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Tributyl tin (TBT) deposits in the sediments are one of many impacts that have been imposed on both the environment and the up-coming development of Boat Haven, Airlie Beach, Queensland. The current costly solution to this problem (that is, removal and re-burial) could be put in future to the credit of the developer rather than be treated (as at present) as a penalty. The Queensland Government’s Offsets Scheme provides an opportunity to promote effective conservation of regional landscapes. Because this scheme plans for offsetting in terrestrial vegetation systems through rehabilitation, so credits could be given to those approved developers who rehabilitate valuable marine habitats disturbed by TBT deposits.

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This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

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This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

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This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

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The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

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In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.