660 resultados para Real environment


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Accessibility to housing for low to moderate income groups in Australia has experienced a severe decline since 2002. On the supply side, the public sector has been reducing its commitment to the direct provision of public housing. Despite strong demand for affordable housing, limited supply has been generated by non-government housing providers. This paper identifies and discusses some current affordable housing solutions which have been developed by non-government housing providers to ameliorate the problem. This study utilises case studies generated from nineteen housing providers during in-depth interviews in South East Queensland in 2007-2008. The case studies are classified into four categories which relate to the nature of their product: affordable rental housing, mixed housing, affordable housing for people with special needs and low cost home ownership. Each category is discussed on the basis of the characteristics typical of that organisation of housing provider, their partnership arrangements and main target market. In addition, the special design and facilities required for people with special needs which include high care accommodation and aged care are highlighted. Finally, this study recommends offering a continuum of solutions to affordable housing for low income people by means of a rent-to-buy scheme.

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Accessibility to housing for low to moderate income groups in Australia has been experiencing a severe decline since 2002. On the supply side, the public sector has been reducing its commitment to the direct provision of public housing. Despite strong demand for affordable housing, limited supply has been generated by nongovernment housing providers. This paper identifies and discusses some current affordable housing solutions to ameliorate the problem which have been developed by non-government housing providers. This study utilises case studies generated from nineteen housing providers during indepth interviews in South East Queensland in 2007-2008. The case studies are classified into four categories which relate to the nature of their product: affordable rental housing, mixed housing, affordable housing for people with special needs and low cost home ownership. Each category is discussed on the basis of the characteristics typical of that organisation of housing provider, their partnership arrangements and main target market. In addition, the special design and facilities required for people with special needs which include high care accommodation and aged care are highlighted. Finally, this study recommends offering a continuum of solutions to affordable housing for low income people by means of a rent-to-buy scheme.

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Real-world design education projects present particular challenges when in a place remote from and distinctively different to students’ familiar territory. The teaching challenge is to assist students to translate the skills they learn at university into an entirely new context, facilitating a project they will learn from, and the community will value. In 2008 QUT design and engineering students undertook a project called Linking Karumba for this remote Queensland town. They engaged with a landscape, climate and community dramatically different from their base in urban Brisbane, and in a fortnight produced locally responsive strategic planning options. The theoretical approach to this was twofold: they needed to make a rapid shift along a continuum from being “outsiders” towards becoming “insiders” (Relph 1976), and to create designs responsive to local distinctiveness (Cumberlidge and Musgrave 2007). This paper outlines Linking Karumba’s teaching strategy via an analogy with the “immersion” method in bilingual education. Three teaching methods were adopted. Firstly, the overall framework drew on Brockbank and McGill (1998), and Thomas’ (2006a) approaches to student reflective practice. Within this, Girot’s “Four Trace Concepts” (1999) inspired exercises for finding Karumba and moving toward insideness; and a program of community engagement sought immersion in local distinctiveness, and “conversation” between the differing forms of knowledge and capacities embedded within the community and students (Armstrong 1999, Thomas 2006). The responsiveness of the student work to the character of Karumba’s culture and environment indicated remarkable levels of immersion, and the community highly valued the project outcomes: four strategic planning options which attracted $830 000 in state government funding for implementation.

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The coral reefs around the world may be likened to canaries down the mineshaft of global warming. These sensitive plant-like animals have evolved for life in tropical seas. Their needs are quite specific – not too cold, not too hot. A rise of as little as one degree Celsius is enough to cause some bleaching of these colourful jewels of the sea. Many climate models indicate we can expect sea temperature increases of between two and six degrees Celsius. Research - such as that detailed in a 2004 report by the University of Queensland’s Centre for Marine Studies – indicates that by the year 2050 most of the worlds major reef systems will be dead. Many of us have heard this kind of information, but it remains difficult to comprehend. It’s almost impossible to imagine the death of the Great Barrier Reef. Some six to nine thousand years old and visible from space, it is the world’s largest structure created by living organisms. Yet whilst it is hard to believe, this gentle, sensitive giant is at grave risk because it cannot adapt quickly enough to the changes in the environment. This cluster of fluffy felt brain coral sculptures are connected in real time to temperature data collected by monitoring stations within the Great Barrier Reef, that form part of the Australian Institute of Marine Science’s Great Barrier Reed Ocean Observing System. These corals display illumination patterns showing changes in sea temperature at Heron Reef, one of the 2,900 reefs that comprise the Great Barrier Reef. Their spectrum of colour ranges from cool hues, through warm tones to bright white when temperatures exceed those that tropical corals are able to tolerate over sustained periods. The Flower Animals also blush in colour and make sound when people come within close proximity. In a reef, fishes and other creatures generate significant amounts of sound. These cacophonies are considered an indicator of reef health, and are used by reef fish to determine where they can best live and forage.

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In vitro cardiovascular device performance evaluation in a mock circulation loop (MCL) is a necessary step prior to in vivo testing.A MCL that accurately represents the physiology of the cardiovascular system accelerates the assessment of the device’s ability to treat pathological conditions. To serve this purpose, a compact MCL measuring 600 ¥ 600 ¥ 600 mm (L ¥ W¥ H) was constructed in conjunction with a computer mathematical simulation.This approach allowed the effective selection of physical loop characteristics, such as pneumatic drive parameters, to create pressure and flow, and pipe dimensions to replicate the resistance, compliance, and fluid inertia of the native cardiovascular system. The resulting five-element MCL reproduced the physiological hemodynamics of a healthy and failing heart by altering ventricle contractility, vascular resistance/compliance, heart rate, and vascular volume. The effects of interpatient anatomical variability, such as septal defects and valvular disease, were also assessed. Cardiovascular hemodynamic pressures (arterial, venous, atrial, ventricular), flows (systemic, bronchial, pulmonary), and volumes (ventricular, stroke) were analyzed in real time. The objective of this study is to describe the developmental stages of the compact MCL and demonstrate its value as a research tool for the accelerated development of cardiovascular devices.

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The Queensland University of Technology badges itself as “a university for the real world”. For the last decade the Law Faculty has aimed to provide its students with a ‘real world’ degree, that is, a practical law degree. This has seen skills such as research, advocacy and negotiation incorporated into the undergraduate degree under a University Teaching & Learning grant, a project that gained international recognition and praise. In 2007–2008 the Law Faculty undertook another curriculum review of its undergraduate law degree. As a result of the two year review, QUT’s undergraduate lawdegree has fewer core units, a focus on first year student transition, scaffolding of law graduate capabilities throughout the degree,work integrated learning and transition to the workplace. The revised degree commenced implementation in 2009. This paper focuses on the “real world” approach to the degree achieved through the first year programme, embedding and scaffolding law graduate capabilities through authentic and valid assessment and work integrated learning.

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Sustainability Declarations were introduced by the Queensland State Government on 1 January 2010 as a compulsory measure for all dwelling sales. The purpose of this policy decision was to improve the relevance of sustainability in the home ownership decision making process. This paper assesses the initial impact of this initiative over its first year in operation. In partnership with the Real Estate Institute of Queensland, real estate agents and salespeople in Queensland were surveyed to determine what impact the Sustainability Declaration has had on home buyer decision making. The level of compliance by the real estate industry was also reviewed. These preliminary findings indicate a high level of compliance from the real estate industry, however results confirm that sustainability is yet to become a criterion of relevance to the majority of home buyers in Queensland. The Sustainability Declarations are a first step in raising awareness in home owners of the importance of sustainability in housing. Further monitoring of this impact will be carried out over time.

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We examine the impact of continuous disclosure regulatory reform on the likelihood, frequency and qualitative characteristics of management earnings forecasts issued in New Zealand’s low private litigation environment. Using a sample of 720 earnings forecasts issued by 94 firms listed on the New Zealand Exchange before and after the reform (1999–2005), we provide strong evidence of significant changes in forecasting behaviour in the post-reform period. Specifically, firms were more likely to issue earnings forecasts to pre-empt earnings announcements and, in contrast to findings in other legal settings, those earnings forecasts exhibited higher frequency and improved qualitative characteristics (better precision and accuracy). An important implication of our findings is that public regulatory reforms may have a greater benefit in a low private litigation environment and thus add to the global debate about the effectiveness of alternative public regulatory reforms of corporate requirements.

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Drink driving causes more fatal crashes than any other single factor on Australian roads, with a third of crashes having alcohol as a contributing factor. In recent years there has been a plateau in the numbers of drink drivers apprehended by RBT, and around 12% of the general population in self report surveys admit to drinking and driving. There is limited information about the first offender group, particularly the subgroup of these offenders who admit to prior drink driving, the offence therefore being the “first time caught”. This research focuses on the differences between those who report drink driving prior to apprehension for the offence and those who don’t. Methods: 201 first time drink driving offenders were interviewed at the time of their court appearance. Information was collected on socio-demographic variables, driving behaviour, method of apprehension, offence information, alcohol use and self reported previous drink driving. Results: 78% of respondents reported that they had driven over the legal alcohol limit in the 6 months prior to the offence. Analyses revealed that those offenders who had driven over the limit previously without being caught were more likely to be younger and have an issue with risky drinking. When all variables were taken into account in a multivariate model using logistic regression, only risky drinking emerged as significantly related to past drink driving. High risk drinkers were 4.8 times more likely to report having driven over the limit without being apprehended in the previous 6 months. Conclusion: The majority of first offenders are those who are “first time apprehended” rather than “first time drink drivers”. Having an understanding of the differences between these groups may alter the focus of educational or rehabilitation countermeasures. This research is part of a larger project aiming to target first time apprehended offenders for tailored intervention.

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Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

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Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

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Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

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Harmful Algal Blooms (HABs) have become an important environmental concern along the western coast of the United States. Toxic and noxious blooms adversely impact the economies of coastal communities in the region, pose risks to human health, and cause mortality events that have resulted in the deaths of thousands of fish, marine mammals and seabirds. One goal of field-based research efforts on this topic is the development of predictive models of HABs that would enable rapid response, mitigation and ultimately prevention of these events. In turn, these objectives are predicated on understanding the environmental conditions that stimulate these transient phenomena. An embedded sensor network (Fig. 1), under development in the San Pedro Shelf region off the Southern California coast, is providing tools for acquiring chemical, physical and biological data at high temporal and spatial resolution to help document the emergence and persistence of HAB events, supporting the design and testing of predictive models, and providing contextual information for experimental studies designed to reveal the environmental conditions promoting HABs. The sensor platforms contained within this network include pier-based sensor arrays, ocean moorings, HF radar stations, along with mobile sensor nodes in the form of surface and subsurface autonomous vehicles. FreewaveTM radio modems facilitate network communication and form a minimally-intrusive, wireless communication infrastructure throughout the Southern California coastal region, allowing rapid and cost-effective data transfer. An emerging focus of this project is the incorporation of a predictive ocean model that assimilates near-real time, in situ data from deployed Autonomous Underwater Vehicles (AUVs). The model then assimilates the data to increase the skill of both nowcasts and forecasts, thus providing insight into bloom initiation as well as the movement of blooms or other oceanic features of interest (e.g., thermoclines, fronts, river discharge, etc.). From these predictions, deployed mobile sensors can be tasked to track a designated feature. This focus has led to the creation of a technology chain in which algorithms are being implemented for the innovative trajectory design for AUVs. Such intelligent mission planning is required to maneuver a vehicle to precise depths and locations that are the sites of active blooms, or physical/chemical features that might be sources of bloom initiation or persistence. The embedded network yields high-resolution, temporal and spatial measurements of pertinent environmental parameters and resulting biology (see Fig. 1). Supplementing this with ocean current information and remotely sensed imagery and meteorological data, we obtain a comprehensive foundation for developing a fundamental understanding of HAB events. This then directs labor- intensive and costly sampling efforts and analyses. Additionally, we provide coastal municipalities, managers and state agencies with detailed information to aid their efforts in providing responsible environmental stewardship of their coastal waters.

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Autonomous Underwater Vehicles (AUVs) are revolutionizing oceanography through their versatility, autonomy and endurance. However, they are still an underutilized technology. For coastal operations, the ability to track a certain feature is of interest to ocean scientists. Adaptive and predictive path planning requires frequent communication with significant data transfer. Currently, most AUVs rely on satellite phones as their primary communication. This communication protocol is expensive and slow. To reduce communication costs and provide adequate data transfer rates, we present a hardware modification along with a software system that provides an alternative robust disruption- tolerant communications framework enabling cost-effective glider operation in coastal regions. The framework is specifically designed to address multi-sensor deployments. We provide a system overview and present testing and coverage data for the network. Additionally, we include an application of ocean-model driven trajectory design, which can benefit from the use of this network and communication system. Simulation and implementation results are presented for single and multiple vehicle deployments. The presented combination of infrastructure, software development and deployment experience brings us closer to the goal of providing a reliable and cost-effective data transfer framework to enable real-time, optimal trajectory design, based on ocean model predictions, to gather in situ measurements of interesting and evolving ocean features and phenomena.