483 resultados para Operational planning


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10 page document containing expert assessment of shortcomings of Western Australian State Planning Policy SPP3.7- Planning for Bushfire Risk Management. Document produced on behalf of QUT and submitted to and published by the WAPC as part of their public consultation process for their draft policy.

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Every university in Australia has a set of policies that guide the institution in its educational practices, however, the policies are often developed in isolation to each other. Now imagine a space where policies are evidence-based, refined annually, cohesively interrelated, and meet stakeholders’ needs. Is this happenstance or the result of good planning? Culturally, Queensland University of Technology (QUT) is a risk-averse institution that takes pride in its financial solvency and is always keen to know “how are we going?” With a twenty-year history of annual reporting that assures the quality of course performance through multiple lines of evidence, QUT’s Learning and Teaching Unit went one step further and strategically aligned a suite of policies that take into consideration the needs of their stakeholders, collaborate with other areas across the institution and use multiple lines of evidence to inform curriculum decision-making. In QUT’s experience, strategic planning can lead to policy that is designed to meet stakeholders’ needs, not manage them; where decision-making is supported by evidence, not rhetoric; where all feedback is incorporated, not ignored; and where policies are cohesively interrelated, not isolated. While many may call this ‘policy nirvana’, QUT has positioned itself to demonstrate good educational practice through Reframe, its evaluation framework. In this case, best practice was achieved through the application of a theory of change and a design-led logic model that allows for transition to other institutions with different cultural specificity. The evaluation approach follows Seldin’s (2003) notion to offer depth and breadth to the evaluation framework along with Berk’s (2005) concept of multiple lines of evidence. In summary, this paper offers university executives, academics, planning and quality staff an opportunity to understand the critical steps that lead to strategic planning and design of evidence-based educational policy that positions a university for best practice in learning and teaching.

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This paper presents an extension to the Rapidly-exploring Random Tree (RRT) algorithm applied to autonomous, drifting underwater vehicles. The proposed algorithm is able to plan paths that guarantee convergence in the presence of time-varying ocean dynamics. The method utilizes 4-Dimensional, ocean model prediction data as an evolving basis for expanding the tree from the start location to the goal. The performance of the proposed method is validated through Monte-Carlo simulations. Results illustrate the importance of the temporal variance in path execution, and demonstrate the convergence guarantee of the proposed methods.

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There is a need for systems which can autonomously perform coverage tasks on large outdoor areas. Unfortunately, the state-of-the-art is to use GPS based localization, which is not suitable for precise operations near trees and other obstructions. In this paper we present a robotic platform for autonomous coverage tasks. The system architecture integrates laser based localization and mapping using the Atlas Framework with Rapidly-Exploring Random Trees path planning and Virtual Force Field obstacle avoidance. We demonstrate the performance of the system in simulation as well as with real world experiments.

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Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

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This invention concerns the control of rotating excavation machinery, for instance to avoid collisions with obstacles. In a first aspect the invention is a control system for autonomous path planning in excavation machinery, comprising: A map generation subsystem to receive data from an array of disparate and complementary sensors to generate a 3-Dimensional digital terrain and obstacle map referenced to a coordinate frame related to the machine's geometry, during normal operation of the machine. An obstacle detection subsystem to find and identify obstacles in the digital terrain and obstacle map, and then to refine the map by identifying exclusion zones that are within reach of the machine during operation. A collision detection subsystem that uses knowledge of the machine's position and movements, as well as the digital terrain and obstacle map, to identify and predict possible collisions with itself or other obstacles, and then uses a forward motion planner to predict collisions in a planned path. And, a path planning subsystem that uses information from the other subsystems to vary planned paths to avoid obstacles and collisions. In other aspects the invention is excavation machinery including the control system; a method for control of excavation machinery; and firmware and software versions of the control system.

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Problem, research strategy and findings: On January 10, 2011, the town of Grantham, Queensland (Australia), was inundated with a flash flood in which 12 of the town's 370 residents drowned. The overall damage bill in Queensland was AUD∃2.38 billion (USD∃2.4 billion) with 35 deaths, and more than three-quarters of the state was declared a flood disaster zone. In this study, we focus on the unusual and even rare decision to relocate Grantham in March 2011. The Lockyer Valley Regional Council (LVRC) acquired a 377-hectare (932-acre) site to enable a voluntary swap of equivalent-sized lots. In addition, planning regulations were set aside to streamline the relocation of a portion of the town. We review the natural hazard literature as it relates to community relocation, state and local government documents related to Grantham, and reports and newspaper articles related to the flood. We also analyze data from interviews with key stakeholders. We document the process of community relocation, assess the relocation process in Grantham against best practice, examine whether the process of community relocation can be upscaled and if the Grantham relocation is an example of good planning or good politics. Takeaway for practice: Our study reveals two key messages for practice. Community relocation (albeit a small one) is possible, and the process can be done quickly; some Grantham residents moved into their new, relocated homes in December 2012, just 11 months after the flood. Moreover, the role of existing planning regulations can be a hindrance to quick action; political leadership, particularly at the local level, is key to implementing the relocation.

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One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.

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This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. In this vignette, Christophe Garonne and Per Davidsson examine the value of business planning for business start-ups.

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Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment.

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Australia’s governance of land and natural resources involves multiple polycentric domains of decision-making from global through to local levels. Although certainly complex, these arrangements have not necessarily translated into better decision-making or better environmental outcomes as evidenced by the growing concerns over the health and future of the Great Barrier Reef, (GBR). However within this system, arrangements for natural resource management (NRM) and reef water quality, which both use Australia’s integrated regional NRM model, have showed signs of improving decision-making and environmental outcomes in the GBR. In this paper we describe the latest evolutions in the governance and planning for natural resource use and management in Australia. We begin by reviewing the experience with first generation NRM as published in major audits and evaluations. As our primary interest is the health and future of the GBR, we then consider the impact of changes of second generation planning and governance outcomes in Queensland. We find that first generation plans, although developed under a relatively cohesive governance context, faced substantial problems in target setting, implementation, monitoring and review. Despite this, they were able to progress improvements in water quality in the Great Barrier Reef Regions. Second generation plans, currently being developed, face an even greater risk of failure due to the lack of bilateralism and cross-sectoral cooperation across the NRM governance system. The findings highlight the critical need to re-build and enhance the regional NRM model for NRM planning to have a positive impact on environmental outcomes in the GBR.

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The focus of this paper is on two World Heritage Areas: the Great Barrier Reef in Queensland, Australia and the Everglades in Florida. While both are World Heritage listed by the UNESCO, the Everglades is on the "World Heritage in Danger" list and the Great Barrier Reef could be on this list within the next year if present pressures continue. This paper examines the planning approaches and governance structures used in these two areas (Queensland and Florida) to manage the growth and development pressures. To make the analysis manageable, given the scale of these World Heritage areas, case studies at the local government level will be used: the Cairns Regional Council in Queensland and Monroe County in Florida. The case study analysis will involve three steps: (1) examination of the various plans at the federal, state, local levels that impact upon environmental quality in the Great Barrier Reef and Everglades; (2) assessing the degree to which these plans have been implemented; and (3) determine if (and how) the plans have improved environmental quality. In addition to the planning analysis we will also examine the governance structures (Lebel et al. 2006) within which planning operates. In any comparative analysis context is important (Hantrais 2009). Contextual differences between Queensland and Florida have previously been examined by Sipe, et al. (2007) and will be used as the starting point for this analysis. Our operating hypothesis and preliminary analysis suggests that the planning approaches and governance structures used in Florida and Queensland are considerably different, but the environmental outcomes may be similar. This is based, in part, on Vella (2004) who did a comparative analysis of environmental practices in the sugar industry in Florida and Queensland. This research re-examines this hypothesis and broadens the focus beyond the sugar industry to growth and development more broadly.

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This research developed and applied an evaluative framework to analyse multiple scales of decision-making for environmental management planning. It is the first exploration of the sociological theory of structural-functionalism and its usefulness to support evidence based decision-making in a planning context. The framework was applied to analyse decision-making in Queensland's Cape York Peninsula and Wet Tropics regions.