Dengue fever and el nino-southern oscillation in Queensland, Australia : a time series predictive model

Background It remains unclear over whether it is possible to develop an epidemic forecasting model for transmission of dengue fever in Queensland, Australia. Objectives To examine the potential impact of El Niño/Southern Oscillation on the transmission of dengue fever in Queensland, Australia and explore the possibility of developing a forecast model of dengue fever. Methods Data on the Southern Oscillation Index (SOI), an indicator of El Niño/Southern Oscillation activity, were obtained from the Australian Bureau of Meteorology. Numbers of dengue fever cases notified and the numbers of postcode areas with dengue fever cases between January 1993 and December 2005 were obtained from the Queensland Health and relevant population data were obtained from the Australia Bureau of Statistics. A multivariate Seasonal Auto-regressive Integrated Moving Average model was developed and validated by dividing the data file into two datasets: the data from January 1993 to December 2003 were used to construct a model and those from January 2004 to December 2005 were used to validate it. Results A decrease in the average SOI (ie, warmer conditions) during the preceding 3–12 months was significantly associated with an increase in the monthly numbers of postcode areas with dengue fever cases (β=−0.038; p = 0.019). Predicted values from the Seasonal Auto-regressive Integrated Moving Average model were consistent with the observed values in the validation dataset (root-mean-square percentage error: 1.93%). Conclusions Climate variability is directly and/or indirectly associated with dengue transmission and the development of an SOI-based epidemic forecasting system is possible for dengue fever in Queensland, Australia.

Validating the functional capacity index : a comparison of predicted versus observed total body scores

Background: The Functional Capacity Index (FCI) was designed to predict physical function 12 months after injury. We report a validation study of the FCI. Methods: This was a consecutive case series registered in the Queensland Trauma Registry who consented to the prospective 12-month telephone-administered follow-up study. FCI scores measured at 12 months were compared with those originally predicted. Results: Complete Abbreviated Injury Scale score information was available for 617 individuals, of whom 587 (95%) could be assigned at least one FCI score (range, 1-17). Agreement between the largest predicted FCI and observed FCI score was poor ([kappa] = 0.05; 95% confidence interval, 0.00-0.10) and explained only 1% of the variability in observed FCI. Using an encompassing model that included all FCI assignments, agreement remained poor ([kappa] = 0.05; 95% confidence interval, -0.02-0.12), and the model explained only 9% of the variability in observed FCI. Conclusion: The predicted functional capacity poorly agrees with actual functional outcomes. Further research should consider including other (noninjury) explanatory factors in predicting FCI at 12 months.

Specifying and enforcing a fine-grained information flow policy : model and experiments

In this paper we present a model for defining and enforcing a fine-grained information flow policy. We describe how the policy can be enforced on a typical computer and present experiments using the proposed model. A key feature of the model is that it allows the expression of rules which detail precisely which information elements are allowed to mix together. For example, the model allows the expression of a policy which forbids a doctor from mixing the personal medical details of the patients. The enforcement mechanisms tracks and records information flows within the system so that dynamic changes to the policy can be made with respect to information elements which may have propagated to different locations in the system.

Creation of a validated 3D finite element model of an ovine tibia

Introduction Ovine models are widely used in orthopaedic research. To better understand the impact of orthopaedic procedures computer simulations are necessary. 3D finite element (FE) models of bones allow implant designs to be investigated mechanically, thereby reducing mechanical testing. Hypothesis We present the development and validation of an ovine tibia FE model for use in the analysis of tibia fracture fixation plates. Material & Methods Mechanical testing of the tibia consisted of an offset 3-pt bend test with three repetitions of loading to 350N and return to 50N. Tri-axial stacked strain gauges were applied to the anterior and posterior surfaces of the bone and two rigid bodies – consisting of eight infrared active markers, were attached to the ends of the tibia. Positional measurements were taken with a FARO arm 3D digitiser. The FE model was constructed with both geometry and material properties derived from CT images of the bone. The elasticity-density relationship used for material property determination was validated separately using mechanical testing. This model was then transformed to the same coordinate system as the in vitro mechanical test and loads applied. Results Comparison between the mechanical testing and the FE model showed good correlation in surface strains (difference: anterior 2.3%, posterior 3.2%). Discussion & Conclusion This method of model creation provides a simple method for generating subject specific FE models from CT scans. The use of the CT data set for both the geometry and the material properties ensures a more accurate representation of the specific bone. This is reflected in the similarity of the surface strain results.

Validating the IS-Impact model in Australasian universities

This paper presents a novel study that aims to contribute to understanding the phenomenon of Enterprise Systems (ES) evaluation in Australasian universities. The proposed study addresses known limitations of arguably the most significant dependent variable in the Information System (IS) field - IS Success or IS-Impact. This study adopts the IS-Impact measurement model, reported by Gable et al. (2008), as the primary commencing theory-base and applies research extension strategy described by Berthon et al. (2002); extending both theory and the context. This study employs a longitudinal, multi-method research design, with two interrelated phases – exploratory and confirmatory. The exploratory phase aims to investigate the applicability and sufficiency of the IS-Impact dimensions and measures in the new context. The confirmatory phase will gather quantitative data to statistically validate IS-Impact model as a formative index.

Structural equation model of construction contract dispute potential

This paper presents the results of a structural equation model (SEM) for describing and quantifying the fundamental factors that affect contract disputes between owners and contractors in the construction industry. Through this example, the potential impact of SEM analysis in construction engineering and management research is illustrated. The purpose of the specific model developed in this research is to explain how and why contract related construction problems occur. This study builds upon earlier work, which developed a disputes potential index, and the likelihood of construction disputes was modeled using logistic regression. In this earlier study, questionnaires were completed on 159 construction projects, which measured both qualitative and quantitative aspects of contract disputes, management ability, financial planning, risk allocation, and project scope definition for both owners and contractors. The SEM approach offers several advantages over the previously employed logistic regression methodology. The final set of structural equations provides insight into the interaction of the variables that was not apparent in the original logistic regression modeling methodology.

Public-private partnerships in the promotion of sport and well-being : a governance model

This research focuses on exploring the links between sport, Indigenous self determination and deeper engagement within mainstream Australia especially with regard to the issue of promoting healthy lifestyles and the role of governance, through sport governance. Against all social, economic and health criteria Indigenous Australians are disadvantaged – despite government attention and financial input. It is well understood that education is a basis to better health, employment and lifestyle (Furneaux and Brown, 2008). However, many of the issues confronting Indigenous people have not responded to conventional government approaches based on program development and policy initiatives from single organisations (Ryan et al 2006). As a consequence, new approaches that both tap into the specific interests of Indigenous people and better engage them in the process of governance are required. The case material of the research focuses on the Australian Football League (AFL) Kickstart program.

Measuring export readiness using a multiple-item index

Since the 1970s the internationalisation process of firms has attracted wide research interest. One of the dominant explanations of firm internationalisation resulting from this research activity is the Uppsala stages model. In this paper, a pre-internationalisation phase is incorporated into the traditional Uppsala model to address the question: What are the antecedents of this model? Four concepts are proposed as the key components that define the experiential learning process underlying a firm’s pre-export phase: export stimuli, attitudinal/psychological commitment, resources and lateral rigidity. Through a survey of 290 Australian exporting and non-exporting small-medium sized firms, data relating to the four pre-internationalisation concepts is collected and an Export Readiness Index (ERI) is constructed through factor analysis. Using logistic regression, the ERI is tested as a tool for analysing export readiness among Australian SMEs.

Delivering value for money in the procurement of public sector major infrastructure : a new first-order decision making model

The significant challenge faced by government in demonstrating value for money in the delivery of major infrastructure resolves around estimating costs and benefits of alternative modes of procurement. Faced with this challenge, one approach is to focus on a dominant performance outcome visible on the opening day of the asset, as the means to select the procurement approach. In this case, value for money becomes a largely nominal concept and determined by selected procurement mode delivering, or not delivering, the selected performance outcome, and notwithstanding possible under delivery on other desirable performance outcomes, as well as possibly incurring excessive transaction costs. This paper proposes a mind-set change in this particular practice, to an approach in which the analysis commences with the conditions pertaining to the project and proceeds to deploy transaction cost and production cost theory to indicate a procurement approach that can claim superior value for money relative to other competing procurement modes. This approach to delivering value for money in relative terms is developed in a first-order procurement decision making model outlined in this paper. The model developed could be complementary to the Public Sector Comparator (PSC) in terms of cross validation and the model more readily lends itself to public dissemination. As a possible alternative to the PSC, the model could save time and money in preparation of project details to lesser extent than that required in the reference project and may send a stronger signal to the market that may encourage more innovation and competition.

Assessing the leanness in product design : a model for planned design reuse

Shrinking product lifecycles, tough international competition, swiftly changing technologies, ever increasing customer quality expectation and demanding high variety options are some of the forces that drive next generation of development processes. To overcome these challenges, design cost and development time of product has to be reduced as well as quality to be improved. Design reuse is considered one of the lean strategies to win the race in this competitive environment. design reuse can reduce the product development time, product development cost as well as number of defects which will ultimately influence the product performance in cost, time and quality. However, it has been found that no or little work has been carried out for quantifying the effectiveness of design reuse in product development performance such as design cost, development time and quality. Therefore, in this study we propose a systematic design reuse based product design framework and developed a design leanness index (DLI) as a measure of effectiveness of design reuse. The DLI is a representative measure of reuse effectiveness in cost, development time and quality. Through this index, a clear relationship between reuse measure and product development performance metrics has been established. Finally, a cost based model has been developed to maximise the design leanness index for a product within the given set of constraints achieving leanness in design process.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

A measurement instrument for process modeling research : development, test and procedural model

Process modeling is an emergent area of Information Systems research that is characterized through an abundance of conceptual work with little empirical research. To fill this gap, this paper reports on the development and validation of an instrument to measure user acceptance of process modeling grammars. We advance an extended model for a multi-stage measurement instrument development procedure, which incorporates feedback from both expert and user panels. We identify two main contributions: First, we provide a validated measurement instrument for the study of user acceptance of process modeling grammars, which can be used to assist in further empirical studies that investigate phenomena associated with the business process modeling domain. Second, in doing so, we describe in detail a procedural model for developing measurement instruments that ensures high levels of reliability and validity, which may assist fellow scholars in executing their empirical research.

Spatial stimulus : Model making in the architectural design studio

This action research examines the enhancement of visual communication within the architectural design studio through physical model making. „It is through physical model making that designers explore their conceptual ideas and develop the creation and understanding of space,‟ (Salama & Wilkinson 2007:126). This research supplements Crowther‟s findings extending the understanding of visual dialogue to include physical models. „Architecture Design 8‟ is the final core design unit at QUT in the fourth year of the Bachelor of Design Architecture. At this stage it is essential that students have the ability to communicate their ideas in a comprehensive manner, relying on a combination of skill sets including drawing, physical model making, and computer modeling. Observations within this research indicates that students did not integrate the combination of the skill sets in the design process through the first half of the semester by focusing primarily on drawing and computer modeling. The challenge was to promote deeper learning through physical model making. This research addresses one of the primary reasons for the lack of physical model making, which was the limited assessment emphasis on the physical models. The unit was modified midway through the semester to better correlate the lecture theory with studio activities by incorporating a series of model making exercises conducted during the studio time. The outcome of each exercise was assessed. Tutors were surveyed regarding the model making activities and a focus group was conducted to obtain formal feedback from students. Students and tutors recognised the added value in communicating design ideas through physical forms and model making. The studio environment was invigorated by the enhanced learning outcomes of the students who participated in the model making exercises. The conclusions of this research will guide the structure of the upcoming iteration of the fourth year design unit.

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 hierarchical security assessment model for object-oriented programs

We present a hierarchical model for assessing an object-oriented program's security. Security is quantified using structural properties of the program code to identify the ways in which `classified' data values may be transferred between objects. The model begins with a set of low-level security metrics based on traditional design characteristics of object-oriented classes, such as data encapsulation, cohesion and coupling. These metrics are then used to characterise higher-level properties concerning the overall readability and writability of classified data throughout the program. In turn, these metrics are then mapped to well-known security design principles such as `assigning the least privilege' and `reducing the size of the attack surface'. Finally, the entire program's security is summarised as a single security index value. These metrics allow different versions of the same program, or different programs intended to perform the same task, to be compared for their relative security at a number of different abstraction levels. The model is validated via an experiment involving five open source Java programs, using a static analysis tool we have developed to automatically extract the security metrics from compiled Java bytecode.