496 resultados para movement planning


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Rapid urbanization has brought environmentally, socially, and economically great challenges to cities and societies. To build a sustainable city, these challenges need to be faced efficiently and successfully. This paper focuses on the environmental issues and investigates the ecological approaches for planning sustainable cities through a comprehensive review of the relevant literature. The review focuses on several differing aspects of sustainable city formation. The paper provides insights on the interaction between the natural environment and human activities by identifying environmental effects resulting from this interaction; provides an introduction to the concept of sustainable urban development by underlining the important role of ecological planning in achieving sustainable cities; introduces the notion of urban ecosystems by establishing principles for the management of their sustainability; describes urban ecosystem sustainability assessment by introducing a review of current assessment methods, and; offers an outline of indexing urban environmental sustainability. The paper concludes with a summary of the findings.

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This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

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This paper addresses the research question, ‘What are the diffusion determinants for green urbanism innovations in Australia?’ This is a significant topic given the global movement towards green urbanism. The study reported here is based on desktop research that provides new insights through (1) synthesis of the latest research findings on green urbanism innovations and (2) interpretation of diffusion issues through our innovation system model. Although innovation determinants have been studied extensively overseas and in Australia, there is presently a gap in the literature when it comes to these determinants for green urbanism in Australia. The current paper fills this gap. Using a conceptual framework drawn from the innovation systems literature, this paper synthesises and interprets the literature to map the current state of green urbanism innovations in Australia and to analyse the drivers for, and obstacles to, their optimal diffusion. The results point to the importance of collaboration between project-based actors in the implementation of green urbanism. Education, training and regulation across the product system is also required to improve the cultural and technical context for implementation. The results are limited by their exploratory nature and future research is planned to quantify barriers to green urbanism.

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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.