976 resultados para framework species
Resumo:
This report provides a current overview and analysis of the role of universities in local community development in the State of Victoria. Drawing on successful programs of community engagement in Victoria, Australia, Europe, Africa, and North America, the report proposes policy strategies for fostering community development for Victorian Higher Education through effective community engagement programs.
Resumo:
Relative powerlessness resulting from colonial dispossession and associated passive welfare policies has long been recognised as a critical factor influencing the health and wellbeing of Indigenous Australians, yet it is hard to find well-evaluated health and social interventions that take an explicit empowerment approach. This paper presents the findings of a Family Wellbeing Empowerment programme pilot delivered to Cairns Region Department of Families Indigenous youth workers and family and community workers in 2003/2004. The aim of the pilot was to build the capacity of these workers to address personal and professional issues as a basis for providing better support for their clients. The pilot demonstrated the effectiveness of the programme as a tool for worker empowerment and, to a lesser degree, organisational change.
Resumo:
The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.
Resumo:
In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.