893 resultados para rural distribution planning


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This report provides an introduction to our analyses of secondary data with respect to violent acts and incidents relating to males living in rural settings in Australia. It clarifies important aspects of our overall approach primarily by concentrating on three elements that required early scoping and resolution. Firstly, a wide and inclusive view of violence which encompasses measures of violent acts and incidents and also data identifying risk taking behaviour and the consequences of violence is outlined and justified. Secondly, the classification used to make comparisons between the city and the bush together with associated caveats is outlined. The third element discussed is in relation to national injury data. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in five subsequent reports in this series.

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This report focuses on our examination of extant data which have been sourced with respect to intentional violence perpetrated or experienced by males in regional and remote Australia. The nature of intentional violent acts can be physical, sexual or psychological or involve deprivation or neglect. We have presented under the headings of: self-harm including suicide; homicide; assault, sexual assault and the threat of assault; child abuse; other family and intimate partner violence; harassment, stalking and bullying; alcohol related social violence; and animal abuse. State variations in interpersonal violence are also presented. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

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This report focuses on our examination of extant data which have been sourced with respect to unintentional serious and violent injuries to males living in regional and remote Australia. Such injuries typically might be caused by, for example, transport accidents, occupational exposures and hazards, burns and so on. Thus unintentional violent incidents cause physical trauma the consequences of which can sometimes lead to chronic conditions including psychological harm or substance abuse. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

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This report focuses on our examination of extant data which have been sourced with respect to personally and socially risky behaviour associated with males living in regional and remote Australia . The AIHW (2008: PHE 97:89) defines personally risky behaviour, on the one hand, as working, swimming, boating, driving or operating hazardous machinery while intoxicated with alcohol or an illicit drug. Socially risky behaviour, on the other hand, is defined as creating a public disturbance, damaging property, stealing or verbally or physically abusing someone while intoxicated with alcohol or an illicit drug. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

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This report considers extant data which have been sourced with respect to some of the consequences of violent acts and incidents and risky behaviour for males living in regional and remote Australia . This has been collated and presented under the headings: juvenile offenders; long-term health consequences; anxiety and repression; and other chronic disabilities. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

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Participatory research methodologies and interactive communication technologies (ICTs) are increasingly seen as offering ways of enhancing women’s empowerment and rural community development. However, some researchers suggest the need for caution about such claims. This book details findings from an evaluation of a feminist action research project that explored the impacts of ICTs for rural women in Queensland, Australia, in terms of personal, business and community development. Using praxis and poststructuralist feminist theories and methodologies, this innovative study presents a rigorous analysis and critique of women's empowerment and participation. This study demonstrates the value of adopting a critical yet pragmatic approach that takes diversity and difference, power-knowledge relations, and the contradictory effects of participation into account. This is argued to enable the development of more effective strategies for women’s empowerment, participation and inclusion. This book should be of particular interest to researchers, postgraduate students, and others working in the fields of communication, gender, and rural development, and feminist evaluation and ethnography.

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Mobile robots are widely used in many industrial fields. Research on path planning for mobile robots is one of the most important aspects in mobile robots research. Path planning for a mobile robot is to find a collision-free route, through the robot’s environment with obstacles, from a specified start location to a desired goal destination while satisfying certain optimization criteria. Most of the existing path planning methods, such as the visibility graph, the cell decomposition, and the potential field are designed with the focus on static environments, in which there are only stationary obstacles. However, in practical systems such as Marine Science Research, Robots in Mining Industry, and RoboCup games, robots usually face dynamic environments, in which both moving and stationary obstacles exist. Because of the complexity of the dynamic environments, research on path planning in the environments with dynamic obstacles is limited. Limited numbers of papers have been published in this area in comparison with hundreds of reports on path planning in stationary environments in the open literature. Recently, a genetic algorithm based approach has been introduced to plan the optimal path for a mobile robot in a dynamic environment with moving obstacles. However, with the increase of the number of the obstacles in the environment, and the changes of the moving speed and direction of the robot and obstacles, the size of the problem to be solved increases sharply. Consequently, the performance of the genetic algorithm based approach deteriorates significantly. This motivates the research of this work. This research develops and implements a simulated annealing algorithm based approach to find the optimal path for a mobile robot in a dynamic environment with moving obstacles. The simulated annealing algorithm is an optimization algorithm similar to the genetic algorithm in principle. However, our investigation and simulations have indicated that the simulated annealing algorithm based approach is simpler and easier to implement. Its performance is also shown to be superior to that of the genetic algorithm based approach in both online and offline processing times as well as in obtaining the optimal solution for path planning of the robot in the dynamic environment. The first step of many path planning methods is to search an initial feasible path for the robot. A commonly used method for searching the initial path is to randomly pick up some vertices of the obstacles in the search space. This is time consuming in both static and dynamic path planning, and has an important impact on the efficiency of the dynamic path planning. This research proposes a heuristic method to search the feasible initial path efficiently. Then, the heuristic method is incorporated into the proposed simulated annealing algorithm based approach for dynamic robot path planning. Simulation experiments have shown that with the incorporation of the heuristic method, the developed simulated annealing algorithm based approach requires much shorter processing time to get the optimal solutions in the dynamic path planning problem. Furthermore, the quality of the solution, as characterized by the length of the planned path, is also improved with the incorporated heuristic method in the simulated annealing based approach for both online and offline path planning.

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Purpose: The purpose of this article is to investigate the engineering of creative urban regions through knowledge-based urban development. In recent years city administrators realised the importance of engineering and orchestrating knowledge city formation through visioning and planning for economic, socio-cultural and physical development. For that purpose a new development paradigm of ‘‘knowledge-based urban development’’ is formed, and quickly finds implementation ground in many parts of the globe.----- Design/methodology/approach: The paper reviews the literature and examines global best practice experiences in order to determine how cities are engineering their creative urban regions so as to establish a base for knowledge city formation.----- Findings: The paper sheds light on the different development approaches for creative urban regions, and concludes with recommendations for urban administrations planning for knowledge-based development of creative urban regions.----- Originality/value: The paper provides invaluable insights and discussion on the vital role of planning for knowledge-based urban development of creative urban regions.

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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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Motorised countries have more fatal road crashes in rural areas than in urban areas. In Australia, over two thirds of the population live in urban areas, yet approximately 55 percent of the road fatalities occur in rural areas (ABS, 2006; Tziotis, Mabbot, Edmonston, Sheehan & Dwyer, 2005). Road and environmental factors increase the challenges of rural driving, but do not fully account for the disparity. Rural drivers are less compliant with recommendations regarding the “fatal four” behaviours of speeding, drink driving, seatbelt non-use and fatigue, and the reasons for their lower apparent receptivity for road safety messages are not well understood. Countermeasures targeting driver behaviour that have been effective in reducing road crashes in urban areas have been less successful in rural areas (FORS, 1995). However, potential barriers to receptivity for road safety information among rural road users have not been systematically investigated. This thesis aims to develop a road safety countermeasure that addresses three areas that potentially affect receptivity to rural road safety information. The first is psychological barriers of road users’ attitudes, including risk evaluation, optimism bias, locus of control and readiness to change. A second area is the timing and method of intervention delivery, which includes the production of a brief intervention and the feasibility of delivering it at a “teachable moment”. The third area under investigation is the content of the brief intervention. This study describes the process of developing an intervention that includes content to address road safety attitudes and improve safety behaviours of rural road users regarding the “fatal four”. The research commences with a review of the literature on rural road crashes, brief interventions, intervention design and implementation, and potential psychological barriers to receptivity. This literature provides a rationale for the development of a brief intervention for rural road safety with a focus on driver attitudes and behaviour. The research is then divided into four studies. The primary aim of Study One and Study Two is to investigate the receptivity of rural drivers to road safety interventions, with a view to identifying barriers to the efficacy of these strategies.

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This book is a thorough investigation of the relationship between land use planning and the railways in Britain, through review of the factors affecting the two sectors and their integration during the period of public ownership. The rationale behind the book is explained as a timely analysis of the dynamic correlation involving town planning and management of the railway in a period when growing congestion on the road network is forcing people to look for alternative modes and capacity is badly needed to accommodate this increased demand for travel. The book calls for a modal shift from road to rail for passenger and freight traffic.

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In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us to understand the impact of estimation error on the performance of in-sample optimal portfolios. Key Words: minimum-variance frontier; efficiency set constants; finite sample distribution

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A comprehensive voltage imbalance sensitivity analysis and stochastic evaluation based on the rating and location of single-phase grid-connected rooftop photovoltaic cells (PVs) in a residential low voltage distribution network are presented. The voltage imbalance at different locations along a feeder is investigated. In addition, the sensitivity analysis is performed for voltage imbalance in one feeder when PVs are installed in other feeders of the network. A stochastic evaluation based on Monte Carlo method is carried out to investigate the risk index of the non-standard voltage imbalance in the network in the presence of PVs. The network voltage imbalance characteristic based on different criteria of PV rating and location and network conditions is generalized. Improvement methods are proposed for voltage imbalance reduction and their efficacy is verified by comparing their risk index using Monte Carlo simulations.

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In this paper, the placement and sizing of Distributed Generators (DG) in distribution networks are determined optimally. The objective is to minimize the loss and to improve the reliability. The constraints are the bus voltage, feeder current and the reactive power flowing back to the source side. The placement and size of DGs are optimized using a combination of Discrete Particle Swarm Optimization (DPSO) and Genetic Algorithm (GA). This increases the diversity of the optimizing variables in DPSO not to be stuck in the local minima. To evaluate the proposed algorithm, the semi-urban 37-bus distribution system connected at bus 2 of the Roy Billinton Test System (RBTS), which is located at the secondary side of a 33/11 kV distribution substation, is used. The results finally illustrate the efficiency of the proposed method.