Robustness to non-normality of various tests for the one-sample location problem

This paper studies the effect of the normal distribution assumption on the power and size of the sign test, Wilcoxon's signed rank test and the t-test when used in one-sample location problems. Power functions for these tests under various skewness and kurtosis conditions are produced for several sample sizes from simulated data using the g-and-k distribution of MacGillivray and Cannon.

Australian and New Zealand untapped biotechnology opportunities

Focuses on biotechnology opportunities in Australia and New Zealand. Increase in investments into the Australian and New Zealand biotechnology sector; Rank of Australia among biomedical research and development cost-effective countries; Application of New Zealand's biotechnology research in fields such as forestry and human healthcare.

Integrating local one-class classifiers for image retrieval

In content-based image retrieval, learning from users’ feedback can be considered as an one-class classification problem. However, the OCIB method proposed in [1] suffers from the problem that it is only a one-mode method which cannot deal with multiple interest regions. In addition, it requires a pre-specified radius which is usually unavailable in real world applications. This paper overcomes these two problems by introducing ensemble learning into the OCIB method: by Bagging, we can construct a group of one-class classifiers which emphasize various parts of the data set; this is followed by a rank aggregating with which results from different parameter settings are incorporated into a single final ranking list. The experimental results show that the proposed I-OCIB method outperforms the OCIB for image retrieval applications.

High performance low-energy buildings

The era of legislation and creditable methods towards producing sustainable buildings is upon us. Yet, a major barrier to achieving environmental responsive design is in the lack of available information at the programming or pre-design phases of a project. The review and evaluation of climate as well as energy-efficient strategies could be difficult to consider at these preliminary stages. Until recently, introducing energy simulation tools at the design stage has been difficult and perhaps next to impossible at a pre-design or programming stage. However, analysis of this sort is essential to ‘green building rating’ or performance assessment schemes such as LEED (Leadership in Energy and Environmental Design) and BREEAM (Building Research Establishment Environment Assessment Method). This paper discusses the implementation of a particular tool, ENERGY-10, where ‘basecase’ building defaults are compared to a low-energy case which has applied multiple energy-efficient strategies automatically. An annual hour-by-hour simulation provides a daylighting calculation with a subsequent thermal evaluation. Calculation results provide energy consumption, peak load equipment sizing, a RANK feature of the energy-efficient strategies, reporting of CO2, SO2 and NOx reduction, optimum glazing type as well as excellent graphic output. Consideration is given as to the approach of how such information can be introduced into the building project brief enforcing a low-energy
performance target.

Women in research? Investigating research opportunities for female academics in Australia

Women continue to be surprisingly under-represented in academia, given the increasing numbers of female postgraduate students and the flexible working conditions offered by most Australian Universities. To date, research has emphasised multiple causes for the 'gender gap' in academia, including the structural characteristics of the university system, cultural and societal barriers to the advancement of women, the influence of marital status on the productivity of women academics and the interaction of cultural, social and personality factors on women's professional careers. However, the implications of a 'gender gap' in academic rank reach beyond arguments of equality between sexes, to questions regarding consequences of a male-dominated professoriate to the nature and subjects of academic research in Australia. The aim of this paper is to investigate the factors that determine the rank of Australian academics and in part, to investigate whether there is a gender gap of rank or authority, through an analysis of data collected on all Australian academics by the Federal Department of Education, Science and Training. The implications of these findings on opportunities for female academic researchers and for research outcomes will be discussed.

Influence of stakeholder communication on consensus making in requirements negotiation

Consensus building is essential in aligning multiple stakeholder viewpoints which are commonly emerging during the process of requirements elicitation, analysis and validation [15]. In fact, agreement among diverse groups of stakeholders is deemed prerequisite to establishing project cooperation and collaboration. While individuals frequently rank the importance of their personal goals over the goals of an organisation, having an appropriate strategy for finding common ground among individuals is crucial to any project's success. This paper therefore explores factors that influence the consensus making process and develops a model that helps with understanding the role of consensus specifically during the elicitation phase of the Requirements Engineering process.

Farm-level efficiency and productivity measurement using panel data: wool production in south-west Victoria

In this article we explore some issues surrounding the use of farm-level efficiency and productivity estimates for benchmarking studies. Using an eight-year balanced panel of Victorian wool producers we analyse annual variation between estimates of farm-level technical efficiency derived using Data Envelopment Analysis and Malmquist estimates of Total Factor Productivity. We find that farms change their relative rank in terms of efficiency across years. Also, unlike aggregate studies of Total Factor Productivity, we find at best erratic and modest growth, a worrying result for this industry. However, caution is needed when interpreting these results, and for that matter, benchmarking analysis as currently practised when using frontier estimation techniques like Data Envelopment Analysis.

Families needs in emergency departments: instument development

Background. Families who accompany critically ill relatives in emergency departments (EDs) are an integral part of the care unit. However, there are few empirical data on their needs during this phase of care. In order to guide quality care, general and specific needs of families accompanying these critically ill relatives should be systematically examined.

Aim. The aim of this pilot project was to test the tool, methods and analysis plan for a study to examine the perceived needs of family members accompanying critically ill patients in EDs and their perceptions of ED staff's ability to meet these needs.

Method. Over a 6-week period in 1996, 84 relatives who met the inclusion criteria were recruited to the study. A postal questionnaire, to uncover the needs of family members, was pilot tested. The questionnaire consisted of 40 need statements reflecting five major themes: meaning, proximity, communication, comfort and support. Of the 84 relatives selected for the study, 73% returned completed questionnaires.

Results. The findings of this pilot study suggest that the questionnaire is a valid and reliable tool for researchers wishing to examine and rank the needs of family members who accompany critically ill people in EDs. In addition, the analysis plan was found to be appropriate.

Conclusions. This pilot study provides both a method and a tool for further research into family needs. Examination of the pilot data supported the reliability and validity of the tool and produced findings that challenge nurses to move beyond traditional practice that has excluded families from being an integral part of caring for critically ill patients in EDs.

Dynamical systems for discovering protein complexes and functional modules from biological networks

Recent advances in high throughput experiments and annotations via published literature have provided a wealth of interaction maps of several biomolecular networks, including metabolic, protein-protein, and protein-DNA interaction networks. The architecture of these molecular networks reveals important principles of cellular organization and molecular functions. Analyzing such networks, i.e., discovering dense regions in the network, is an important way to identify protein complexes and functional modules. This task has been formulated as the problem of finding heavy subgraphs, the Heaviest k-Subgraph Problem (k-HSP), which itself is NPhard. However, any method based on the k-HSP requires the parameter k and an exact solution of k-HSP may still end up as a “spurious” heavy subgraph, thus reducing its practicability in analyzing large scale biological networks. We proposed a new formulation, called the rank-HSP, and two dynamical systems to approximate its results. In addition, a novel metric, called the Standard deviation and Mean Ratio (SMR), is proposed for use in “spurious” heavy subgraphs to automate the discovery by setting a fixed threshold. Empirical results on both the simulated graphs and biological networks have demonstrated the efficiency and effectiveness of our proposal.

Validation of a FFQ to estimate the intake of PUFA using plasma phospholipid fatty acids and weighed foods records

Due to the growing knowledge about the role of specific fatty acids in health and disease, dietary intake measurements of individual fatty acids or classes of fatty acids are becoming increasingly important. The objective of this study was to evaluate the ability of the Nambour FFQ to estimate intakes of specific fatty acids, particularly PUFA. The study population was a sub-sample of adult participants in a randomised controlled trial of [beta]-carotene and sunscreen in the prevention of skin cancer (n 43). Dietary intake was assessed by a self-administered FFQ and a weighed food record (WFR). Non-fasting blood samples were collected and analysed for plasma phospholipid fatty acids. Median intakes on the FFQ were generally higher than the WFR except for the n-3 PUFA groups, where the FFQ estimated higher intakes. Correlations between the FFQ and WFR were moderate (r 0–32-0-59) except for trans fatty acids (r 0–03). Correlations between each of the dietary assessment methods and the plasma phospholipids were poor for all fatty acids other than the PUFA. Using the methods of triads approach, the FFQ validity coefficients for total n-3 fatty acids, total long chain n-3 fatty acids, EPA, arachidonic acid, docosapentaenoic acid and DHA were 0–50, 0–63, 0–45 and 0–62 and 0–62, respectively. For most fatty acids, the FFQ adequately estimates group mean fatty acid intakes and can adequately rank individuals; however, the ability of this FFQ to estimate trans fatty acids was poor.

An input-output approach for measuring real estate sector linkages

This research aims to measure and compare the total, backward, forward, internal and sectoral linkages of the real estate sector using the hypothetical extraction method over 30 years and explore the role of this sector in national economies and the quantitative interdependence between the real estate sector and the remaining sectors from a new angle. Empirical results show an increasing trend of these linkages, which confirms the increasing role of the real estate sector with economic maturity over the examined period. On the other hand, the significant rank correlations in the linkages imply that the importance of real estate remained fairly stable among highly developed economies over the examined period. This may supply a tool to signal the maturity of an entire economy. Furthermore, the findings can aid both governments making relative policies and businesses choosing strategic partners and location strategies.

Application of the adaptive reuse potential model in Hong Kong : a case study of Lui Seng Chun

There is an increasing complexity and interplay between all of the issues associated with property portfolio decisions. This paper explores the relationships between financial, environmental and social parameters associated with building adaptive reuse by way of a case study. A new model predicting adaptive reuse potential is applied to a heritage building in Hong Kong known as Lui Seng Chun. Such application can assist in the transformation of the building and property industry towards more sustainable practices, strategies and outcomes, by providing a means by which the industry can identify and rank existing buildings that have high potential for adaptive reuse. In Hong Kong's case it provides an ability for sustainable, responsive energy and natural resource management by allowing issues regarding excessive and inappropriate resource use to be identified and assessed, and appropriate management strategies to be implemented. Given the building's current age and condition, Lui Seng Chun has at least 25 years of physical life remaining. The further application of a multi-criteria sustainability evaluation tool supports the conclusion that an adaptive reuse strategy for this building will make a demonstrable contribution to the economic, social and environmental amenity of Hong Kong. The application of these techniques to other buildings with significant "embedded physical life" is highly recommended.

Multiple-criteria decision analysis for integrated catchment management

Implementation of integrated catchment management (ICM) is hampered by the lack of a conceptual framework for explaining how landowners select farming systems for their properties. Benefit–cost analysis (a procedure that estimates the costs and benefits of alternative actions or policies) has limitations in this regard, which might be overcome by using multiple-criteria decision analysis (MCDA). MCDA evaluates and ranks alternatives based on a landowner's preferences (weights) for multiple-criteria and the values of those criteria. A MCDA approach to ICM is superior to benefit–cost analysis which focuses only on the monetary benefits and costs, because it: 1) recognizes that human activities within a catchment are motivated by multiple and often competing criteria and/or constraints; 2) does not require monetary valuation of criteria; 3) allows trade-offs between criteria to be measured and evaluated; 4) explicitly considers how the spatial configuration of farming systems in a catchment influences the values of criteria; 5) is comprehensive, knowledge-based, and stakeholder oriented which greatly increases the likelihood of resolving catchment problems; and 6) allows consideration of the fairness and sustainability of land and water resource management decisions. A MCDA based on an additive, multiple-criteria utility function containing five economic and environmental criteria was used to score and rank five farming systems. The rankings were based on the average criteria weights for a sample of 20 farmers in a US catchment. The most profitable farming system was the lowest-ranked farming system. Three possible reasons for this result are evaluated. First, the MCDA method might cause respondents to express socially acceptable attitudes towards environmental criteria even when they are not important from a personal viewpoint. Second, the MCDA method could inflate the ranks of less profitable farming systems for the simple reason that it allows the respondent to assign non-zero weights to non-economic criteria. Third, the MCDA might provide a better framework for evaluating a landowner's selection of farming systems than the profit maximization model.

Prevention of type 2 diabetes by lifestyle intervention in an Australian primary health care setting : Greater Green Triangle (GGT) Diabetes Prevention Project

Background
Randomised controlled trials demonstrate a 60% reduction in type 2 diabetes incidence through lifestyle modification programmes. The aim of this study is to determine whether such programmes are feasible in primary health care.

Methods
An intervention study including 237 individuals 40–75 years of age with moderate or high risk of developing type 2 diabetes. A structured group programme with six 90 minute sessions delivered during an eight month period by trained nurses in Australian primary health care in 2004–2006. Main outcome measures taken at baseline, three, and 12 months included weight, height, waist circumference, fasting plasma glucose and lipids, plasma glucose two hours after oral glucose challenge, blood pressure, measures of psychological distress and general health outcomes. To test differences between baseline and follow-up, paired t-tests and Wilcoxon rank sum tests were performed.

Results
At twelve months participants' mean weight reduced by 2.52 kg (95% confidence interval 1.85 to 3.19) and waist circumference by 4.17 cm (3.48 to 4.87). Mean fasting glucose reduced by 0.14 mmol/l (0.07 to 0.20), plasma glucose two hours after oral glucose challenge by 0.58 mmol/l (0.36 to 0.79), total cholesterol by 0.29 mmol/l (0.18 to 0.40), low density lipoprotein cholesterol by 0.25 mmol/l (0.16 to 0.34), triglycerides by 0.15 mmol/l (0.05 to 0.24) and diastolic blood pressure by 2.14 mmHg (0.94 to 3.33). Significant improvements were also found in most psychological measures.

Conclusion
This study provides evidence that a type 2 diabetes prevention programme using lifestyle intervention is feasible in primary health care settings, with reductions in risk factors approaching those observed in clinical trials.

Trial Number
Current Controlled Trials ISRCTN38031372

Adaptive spike detection for resilient data stream mining

Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure, adaptive spike detection is attribute ranking and selection without class-labels. The first part of adaptive spike detection requires weighing all attributes for spiky-ness to rank them. The second part involves filtering some attributes with extreme weights to choose the best ones for computing each example’s suspicion score. Within an identity crime detection domain, adaptive spike detection is validated on a few million real credit applications with adversarial activity. The results are F-measure curves on eleven experiments and relative weights discussion on the best experiment. The results reinforce adaptive spike detection’s effectiveness for class-label-free attribute ranking and selection.