Case study 1 : a subtropical urban community : investigating medium to high density residential typologies by design charrette

The public transport corridor bordering the study site runs NW to SE and is perceived as a source of noise and pollution. The key urban planning strategies adopted by this team were: • Acoustic separation from transport corridor noise source, • A regular grid pattern of urban blocks, and • A clear hierarchy of accessible open space throughout the development.

Report : Case study 2 : a subtropical urban community : investigating medium to high density residential typologies by design charrette

The case study site is physically disconnected from its surrounding community by the rail corridor and future bus lanes and is unlikely to be able to sustain its own commercial retail centre. As a result, it may also be socially disconnected from surrounding suburbs. However, it does offer proximity and access to an extensive „natural‟ area, and this is seen as key opportunity for the proposed development to develop a strong relationship with surrounding suburbs...

Geometric and force relationships for the development of a scaled model hydraulic excavator

Hydraulic excavators in the mining industry are widely used owing to the large payload capabilities these machines can achieve. However, there are very few optimisation studies for producing efficient hydraulic excavator backets. An efficient bucket can avoid unnecessary weight; greatly influence the payload and optimise the efficiency of hydraulic mining excavators. This paper presents a framework for the development of a scaled hydraulic excavator by examining the geometry and force relationships. A small hydraulic excavator was purchased and fitted with a broom scaled to a factor. Geometric and force relationships of the model were derived to assist computer instrumentation to retrieve necessary variable input for bucket design.

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

A stochastic model for natural feature representation

This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

Empirical Bayes method in the study of traffic safety via heterogeneous negative multinomial model

In the study of traffic safety, expected crash frequencies across sites are generally estimated via the negative binomial model, assuming time invariant safety. Since the time invariant safety assumption may be invalid, Hauer (1997) proposed a modified empirical Bayes (EB) method. Despite the modification, no attempts have been made to examine the generalisable form of the marginal distribution resulting from the modified EB framework. Because the hyper-parameters needed to apply the modified EB method are not readily available, an assessment is lacking on how accurately the modified EB method estimates safety in the presence of the time variant safety and regression-to-the-mean (RTM) effects. This study derives the closed form marginal distribution, and reveals that the marginal distribution in the modified EB method is equivalent to the negative multinomial (NM) distribution, which is essentially the same as the likelihood function used in the random effects Poisson model. As a result, this study shows that the gamma posterior distribution from the multivariate Poisson-gamma mixture can be estimated using the NM model or the random effects Poisson model. This study also shows that the estimation errors from the modified EB method are systematically smaller than those from the comparison group method by simultaneously accounting for the RTM and time variant safety effects. Hence, the modified EB method via the NM model is a generalisable method for estimating safety in the presence of the time variant safety and the RTM effects.

Design of a model-generated repository as a service for USDL

SAP and its research partners have been developing a lan- guage for describing details of Services from various view- points called the Unified Service Description Language (USDL). At the time of writing, version 3.0 describes technical implementation aspects of services, as well as stakeholders, pricing, lifecycle, and availability. Work is also underway to address other business and legal aspects of services. This language is designed to be used in service portfolio management, with a repository of service descriptions being available to various stakeholders in an organisation to allow for service prioritisation, development, deployment and lifecycle management. The structure of the USDL metadata is specified using an object-oriented metamodel that conforms to UML, MOF and EMF Ecore. As such it is amenable to code gener-ation for implementations of repositories that store service description instances. Although Web services toolkits can be used to make these programming language objects available as a set of Web services, the practicalities of writing dis- tributed clients against over one hundred class definitions, containing several hundred attributes, will make for very large WSDL interfaces and highly inefficient “chatty” implementations. This paper gives the high-level design for a completely model-generated repository for any version of USDL (or any other data-only metamodel), which uses the Eclipse Modelling Framework’s Java code generation, along with several open source plugins to create a robust, transactional repository running in a Java application with a relational datastore. However, the repository exposes a generated WSDL interface at a coarse granularity, suitable for distributed client code and user-interface creation. It uses heuristics to drive code generation to bridge between the Web service and EMF granularities.

A subtropical urban community : medium to high density residential typologies - case study 4

On the case study site, using these strategies, the site density achieved was approximately 180 dwellings per hectare. According to ASK consulting engineers‟ acoustic report (in Ecolateral‟s report) the design gives solid consideration to the environmental noise issues associated with the site. The subject structure not only provides significant shielding of transport corridor noise to the suburb, it also minimises the potential for adverse impact on residential amenity within the building itself...

Model and prototype for querying multiple linked scientific datasets

Scientists need to transfer semantically similar queries across multiple heterogeneous linked datasets. These queries may require data from different locations and the results are not simple to combine due to differences between datasets. A query model was developed to make it simple to distribute queries across different datasets using RDF as the result format. The query model, based on the concept of publicly recognised namespaces for parts of each scientific dataset, was implemented with a configuration that includes a large number of current biological and chemical datasets. The configuration is flexible, providing the ability to transparently use both private and public datasets in any query. A prototype implementation of the model was used to resolve queries for the Bio2RDF website, including both Bio2RDF datasets and other datasets that do not follow the Bio2RDF URI conventions.

Theoretical model of user acceptance : in the view of measuring success in web personalization

This paper attempts to develop a theoretical acceptance model for measuring Web personalization success. Key factors impacting Web personalization acceptance are identified from a detailed literature review. The final model is then cast in a structural equation modeling (SEM) framework comprising nineteen manifest variables, which are grouped into three focal behaviors of Web users. These variables could provide a framework for better understanding of numerous factors that contribute to the success measures of Web personalization technology. Especially, those concerning the quality of personalized features and how personalized information through personalized Website can be delivered to the user. The interrelationship between success constructs is also explained. Empirical validations of this theoretical model are expected on future research.

Indoor and outdoor nitrogen dioxide concentration in residential houses in Australia

As part of a larger indoor environmental study, residential indoor and outdoor levels of nitrogen dioxide (NO2) were measured for 14 houses in a suburb of Brisbane, Queensland, Australia. Passive samplers were used for 48-h sampling periods during the winter of 1999. The average indoor and outdoor NO2 levels were 13.8 ± 6.3 and 16.7 ± 4.2 ppb, respectively. The indoor/outdoor NO2 concentration ratio ranged from 0.4 to 2.3, with a median value of 0.82. The results of statistic analyses indicated that there was no significant correlation between indoor and outdoor NO2 concentrations, or between indoor and fixed site NO2 monitoring station concentrations. However, there was a significant correlation between outdoor and fixed site NO2 monitoring station concentrations. There was also a significant correlation between indoor NO2 concentration and indoor submicrometre (0.007–0.808 μm) aerosol particle number concentrations. The results in this study indicated indoor NO2 levels are significantly affected by indoor NO2 sources, such as a gas stove and cigarette smoking. It implies that the outdoor or fixed site monitoring concentration alone is a poor predictor of indoor NO2 concentration.

Sharing with Creative Commons : a business model for content creators

Creative Commons (CC) is often seen as a social movement, dismissed by critics as a tool for hobbyists or academics who do not sell their creations to make a living. However, this paper argues that the licensing of creative copyright works under a CC licence does not preclude commercial gain. If used wisely, CC licences can be a useful tool for creators in their quest for commercial success. In particular, this paper argues that the sharing of creative works online under a CC licence allows creators to circumvent traditional distribution channels dominated by content intermediaries, whilst maintaining a level of control over their copyright works (i.e. explicitly reserving some rights but not all rights). This will be illustrated by case studies on how CC is being used by content creators and intermediaries respectively, and how successful their respective methods are in harnessing this tool.

Variability of input parameters related to pollutants build-up in stormwater quality modelling

The variability of input parameters is the most important source of overall model uncertainty. Therefore, an in-depth understanding of the variability is essential for uncertainty analysis of stormwater quality model outputs. This paper presents the outcomes of a research study which investigated the variability of pollutants build-up characteristics on road surfaces in residential, commercial and industrial land uses. It was found that build-up characteristics vary highly even within the same land use. Additionally, industrial land use showed relatively higher variability of maximum build-up, build-up rate and particle size distribution, whilst the commercial land use displayed a relatively higher variability of pollutant-solid ratio. Among the various build-up parameters analysed, D50 (volume-median-diameter) displayed the relatively highest variability for all three land uses.

An application of the CBBE model to assess brand loyalty for a long haul travel destination

In the past two decades there has been increasing interest in branding tourism destinations in an effort to meaningfully differentiate against a myriad of competing places that offer similar attractions and facilities. The academic literature relating to destination branding commenced only as recently as 1998, and there remains a dearth of empirical data that tests the effectiveness of brand campaigns, particularly in terms of enhancing destination loyalty. This paper reports the results of an investigation into destination brand loyalty for Australia as a long haul destination in a South American market. In spite of the high level of academic interest in the measurement of perceptions of destinations since the 1970s, few previous studies have examined perceptions held by South American consumers. Drawing on a model of consumer-based brand equity (CBBE), antecedents of destination brand loyalty was tested with data from a large Chilean sample of travelers, comprising a mix of previous visitors and non-visitors to Australia. Findings suggest that destination brand awareness, brand image, and brand value are positively related to brand loyalty for a long-haul destination. However, destination brand quality was not significantly related. The results also indicate that Australia is a more compelling destination brand for previous visitors compared to non-visitors.