The public's knowledge of and support for conservation of Australia's tree-kangaroos and other animals

After providing background on Dendrolagus species in Australia, two consecutive surveys of Brisbane's residents are used to assess public knowledge of tree-kangaroos and the stated degree of support for their conservation in Australia. The responses of participants in Survey I are based on their pre-survey knowledge of wildlife. The same set of participants completed Survey II after being provided with additional information on all the wildlife species mentioned in Survey I. Changes in the attitudes of respondents and their degree of support for the protection and conservation of Australia's tree-kangaroos are measured, including changes in their contingent valuations and stated willingness to provide financial support for such conservation. Reasons for wanting to protect tree-kangaroos are specified and analysed. Furthermore, changes that occur in the relative importance of these reasons with increased knowledge are also examined. Support for the conservation of tree-kangaroos is found to rise with the additional knowledge supplied about all species and is compared with variations in support for protection of other mammals. Support for the conservation of Australia's less well known tropical mammals is found to increase relative to better known mammals (icons) present in temperate areas, such as koalas and red kangaroos. Possible implications of the results for government conservation policies in Australia are examined.

Estimating the abundance of eastern grey kangaroos (Macropus giganteus) in south-eastern New South Wales, Australia

To provide an estimate of kangaroo numbers for harvest management, a survey was designed for an area of 29500 km(2) encompassing the agricultural and grazing lands of the Braidwood, Cooma, Goulburn, Gundagai and Yass Rural Lands Protection Board (RLPB) districts in south-east New South Wales. An aerial survey using a helicopter was considered more efficient than ground survey because of the size of the area, relatively high relief and dense tree cover, and the need for regular monitoring. Tree cover and landscape relief was used to stratify the five RLPB districts into areas of probable high, medium and low kangaroo density. Kangaroo density estimated from helicopter surveys conducted in the Northern Tablelands of New South Wales was used to suggest densities and thereby allocate survey effort in each stratum. A survey comprising 735 km of transect line was conducted in winter 2003 with a target precision of 20%. The survey returned an estimate of 286600 32300 eastern grey kangaroos for the whole of the proposed south-east New South Wales kangaroo-management zone. In 2004, a trial harvest of slightly less than 15% of this estimate was taken. Success of the trial will be determined by the impact of harvesting on the population's dynamics, by landholder and industry participation, and by the capacity to monitor population size, harvest offtake and compliance with regulations.

K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Document clustering with K-tree

This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

Thai word segmentation with hidden Markov Model and decision tree

The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

Tree of knowledge memorial

This article discusses the design of a memorial space of the Tree of Knowledge, located in Oak Street, Barcaldine, Queensland designed by Brian Hooper Architect and M3 Architecture. Features of the design include the dead tree trunk underneath pieces of timber hanging down to show the original size of the tree in the 1890s and the root ball visible under a glass floor.

Clustering with random indexing K-tree and XML structure

This paper describes the approach taken to the clustering task at INEX 2009 by a group at the Queensland University of Technology. The Random Indexing (RI) K-tree has been used with a representation that is based on the semantic markup available in the INEX 2009 Wikipedia collection. The RI K-tree is a scalable approach to clustering large document collections. This approach has produced quality clustering when evaluated using two different methodologies.