West (side) and south (front) elevations, public housing, Cotton Tree Housing Estate, Maroochydore

This pilot project at Cotton Tree, Maroochydore, on two adjacent, linear parcels of land has one of the properties privately owned while the other is owned by the public housing authority. Both owners commissioned Lindsay and Kerry Clare to design housing for their separate needs which enabled the two projects to be governed by a single planning and design strategy. This entailed the realignment of the dividing boundary to form two approximately square blocks which made possible the retention of an important stand of mature paperbark trees and gave each block a more useful street frontage. The scheme provides seven two-bedroom units and one single-bedroom unit as the private component, with six single-bedroom units, three two-bedroom units and two three-bedroom units forming the public housing. The dwellings are deployed as an interlaced mat of freestanding blocks, car courts, courtyard gardens, patios and decks. The key distinction between the public and private parts of the scheme is the pooling of the car parking spaces in the public housing to create a shared courtyard. The housing climbs to three storeys on its southern edge and falls to a single storey on the north-western corner. This enables all units and the principal private outdoor spaces to have a northern orientation. The interiors of both the public and private units are skilfully arranged to take full advantage of views, light and breeze.

Boosting the tree augmented naive bayes classifier

The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the Naïve Bayes approach by taking account of conditional probabilities. It does this in a limited sense, by incorporating the conditional probability of each attribute given the class and (at most) one other attribute. The method of boosting has previously proven very effective in improving the performance of Naïve Bayes classifiers and in this paper, we investigate its effectiveness on application to the TAN classifier.

Cutting management of multipurpose tree legumes: effects on green herbage production, leaf retention and water-use-efficiency during the dry season in Timor, Indonesia

Edible herbage production and water-use-efficiency of three tree legumes (Leucaena leucocephala cv. Tarramba, L. pallida x L. leucocephala (KX2) and Gliricidia sepium), cut at different times of the year (February, April, June and uncut) were compared in a semi-arid area of Timor Island, Indonesia. Cutting in the early and mid dry-season (April and June) resulted in higher total leaf production (P< 0.05) and water-use-efficiency (P< 0.05), than cutting late in the wet-season (February) or being left uncut. For the leucaena treatments removing leaf in the early to mid dry-season reduced transpiration, saving soil water for subsequent regrowth as evidenced by the higher relative water contents of leaves from these treatments. This cutting strategy can be applied to local farming conditions to increase the supply of feed for livestock during the dry season.

BM+-tree: A hyperplane-based index method for high-dimensional metric spaces

In this paper, we propose a novel high-dimensional index method, the BM+-tree, to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a rotary binary hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the M+-tree. Compared with the key dimension concept in the M+-tree, the binary hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Experimental results using two types of real data sets illustrate a significantly improved filtering efficiency.