Spatial analysis of melioidosis distribution in a suburban area

Burkholderia pseudomallei, the causative agent of melioidosis is associated with soil. This study used a geographic information system (GIS) to determine the spatial distribution of clinical cases of melioidosis in the endemic suburban region of Townsville in Australia. A total of 65 cases over the period 1996–2008 were plotted using residential address. Two distinct groupings were found. One was around the base of a hill in the city centre and the other followed the old course of a major waterway in the region. Both groups (accounting for 43 of the 65 cases examined) are in areas expected to have particularly wet topsoils following intense rainfall, due to soil type or landscape position.

Traffic and climate change impacts on water quality : measuring build-up and wash-off of heavy metals and petroleum hydrocarbons

Understanding the impacts of traffic and climate change on water quality helps decision makers to develop better policy and plans for dealing with unsustainable urban and transport development. This chapter presents detailed methodologies developed for sample collection and testing for heavy metals and total petroleum hydrocarbons, as part of a research study to investigate the impacts of climate change and changes to urban traffic characteristics on pollutant build-up and wash-off from urban road surfaces. Cadmium, chromium, nickel, copper, lead, iron, aluminium, manganese and zinc were the target heavy metals, and selected gasoline and diesel range organics were the target total petroleum hydrocarbons for this study. The study sites were selected to encompass the urban traffic characteristics of the Gold Coast region, Australia. An improved sample collection method referred to as ‘the wet and dry vacuum system’ for the pollutant build-up, and an effective wash-off plan to incorporate predicted changes to rainfall characteristics due to climate change, were implemented. The novel approach to sample collection for pollutant build-up helped to maintain the integrity of collection efficiency. The wash-off plan helped to incorporate the predicted impacts of climate change in the Gold Coast region. The robust experimental methods developed will help in field sample collection and chemical testing of different stormwater pollutants in build-up and wash-off.

Exposure to particle number, surface area and PM concentrations in pizzerias

The aim of this work was to quantify exposure to particles emitted by wood-fired ovens in pizzerias. Overall, 15 microenvironments were chosen and analyzed in a 14-month experimental campaign. Particle number concentration and distribution were measured simultaneously using a Condensation Particle Counter (CPC), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer (APS). The surface area and mass distributions and concentrations, as well as the estimation of lung deposition surface area and PM1 were evaluated using the SMPS-APS system with dosimetric models, by taking into account the presence of aggregates on the basis of the Idealized Aggregate (IA) theory. The fraction of inhaled particles deposited in the respiratory system and different fractions of particulate matter were also measured by means of a Nanoparticle Surface Area Monitor (NSAM) and a photometer (DustTrak DRX), respectively. In this way, supplementary data were obtained during the monitoring of trends inside the pizzerias. We found that surface area and PM1 particle concentrations in pizzerias can be very high, especially when compared to other critical microenvironments, such as the transport hubs. During pizza cooking under normal ventilation conditions, concentrations were found up to 74, 70 and 23 times higher than background levels for number, surface area and PM1, respectively. A key parameter is the oven shape factor, defined as the ratio between the size of the face opening in respect

Effect of clear zone widths on run-off-road crash outcomes

Current guidelines on clear zone selection and roadside hazard management adopt the US approach based on the likelihood of roadside encroachment by drivers. This approach is based on the available research conducted in the 1960s and 70s. Over time, questions have been raised regarding the robustness and applicability of this research in Australasia in 2010 and in the Safe System context. This paper presents a review of the fundamental research relating to selection of clear zones. Results of extensive rural highway statistical data modelling suggest that a significant proportion of run-off-road to the left casualty crashes occurs in clear zones exceeding 13 m. They also show that the risk of run-off-road to the left casualty crashes was 21% lower where clear zones exceeded 8 m when compared with clear zones in the 4 – 8 m range. The paper discusses a possible approach to selection of clear zones based on managing crash outcomes, rather than on the likelihood of roadside encroachment which is the basis for the current practice. It is expected that this approach would encourage selection of clear zones wider than 8 m when the combination of other road features suggests higher than average casualty crash risk.

Community engagement and groundwater investigation in a rural/peri urban basaltic aquifier system, Tamborine Mountain, South East Queensland

The Tamborine Mt area is a popular residential and tourist area in the Gold Coast hinterland, SE Qld. The 15km2 area occurs on elevated remnant Tertiary Basalts of the Beechmont Group, which comprise a number of mappable flow units originally derived from the Tweed volcanic centre to the south. The older Albert Basalt (Tertiary), which underlies the Beechmont Basalt at the southern end of the investigation area, is thought to be derived from the Focal Peak volcanic centre to the south west. The Basalts contain a locally significant ‘un-declared’ groundwater resource, which is utilised by the Tamborine Mt community for: • domestic purposes to supplement rainwater tank supplies, • commercial scale horticulture and • commercial export off-Mountain for bottled water. There is no reticulated water supply, and all waste water is treated on-site through domestic scale WTPs. Rainforest and other riparian ecosystems that attract residents and tourist dollars to the area, are also reliant on the groundwater that discharges to springs and surface streams on and around the plateau. Issues regarding a lack of compiled groundwater information, groundwater contamination, and groundwater sustainability are being investigated by QUT, utilising funding provided by the Federal Government’s ‘Caring for our Country’ programme through SEQ Catchments Ltd. The objectives of the two year project, which started in April 2009, are to: • Characterise the nature and condition of groundwater / surface water systems in the Tamborine Mountain area in terms of the issues being raised; • Engage and build capacity within the community to source local knowledge, encourage participation, raise awareness and improve understanding of the impacts of land and water use; • Develop a stand-alone 3D Visualisation model for dissemination into the community and use as a communication tool.

The impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE and GAIA. Initial analyses established high, low and moderate traffic scenarios as well as low, low to moderate, moderate, high and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75µm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 µm, whereas metal concentrations in finer size range of <1-75 µm were not affected. As practical implications, solids <1 µm and organic matter from 1 - >300 µm can be targeted for removal of Ni, Cu, Pb, Cd, Cr and Zn from build-up whilst organic matter from <1 - >300 µm can be targeted for removal of Cd, Cr, Pb and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

Risky business : making decisions off the cuff

In line with accepted decision making theory, individuals engage in rational decision making. Decisions made under conditions of bounded rationality may have serious adverse consequences. Employees making decisions on behalf of their employer are often faced with situations where perfect and complete information is not available, and time is limited. Under such conditions, we posit that employees will make decisions that are increasingly bounded. At its most extreme neither time nor information is available to make a decision and rational decision making, bounded or not, reaches its limits. Many authors suggest that this is the point at which improvisation takes place. Although opinion in the literature is mixed regarding the efficacy of improvised decisions, we argue that improvised decisions place the organisation at considerable risk and as a consequence are undesirable.

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

AITPM national newsletter President's report June 2010

This is my penultimate report as National President of the Australian Institute of Traffic Planning and Management, Inc. As an academic, I would like to take this opportunity to raise some issues and challenges I see in transport professional education in Australia. My general view is that the transport profession has until recently been less conspicuous to others as an identifiable discipline. This is both a blessing and somewhat of a curse. People mostly enter, or sometimes fall into, the transport profession having taken a degree in civil engineering, other engineering, urban and regional planning, economics, industrial psychology, business, followed by the less obvious disciplines. This order is probably about relative to the proportion of members’ background qualifications in our ranks too. However, once a graduate destined to become a transport professional has spent about five years or so out of the academic estuary, they tend to specialise in an area that cannot necessarily be easily correlated to the well known courses I have rattled off above. I can say from experience that it is not out of the question to see SIDRA models having been prepared by a transport professional who did not take traffic engineering as part of a civil engineering degree. So I see a couple of key challenges for the transport profession, which happens to be represented by a number of bodies, with our AITPM perhaps being the peak body, into the future,

Interpreting regional frequencies from synchronized phasor measurement in multi-area power systems

In this paper a new approach is proposed for interpreting of regional frequencies in multi machine power systems. The method uses generator aggregation and system reduction based on coherent generators in each area. The reduced system structure is able to be identified and a kalman estimator is designed for the reduced system to estimate the inter-area modes using the synchronized phasor measurement data. The proposed method is tested on a six machine, three area test system and the obtained results show the estimation of inter-area oscillations in the system with a high accuracy.

Waist circumference cut-off values for the prediction of cardiovascular risk factors clustering in Chinese school-aged children : a cross-sectional study

Background: Waist circumference has been identified as a valuable predictor of cardiovascular risk in children. The development of waist circumference percentiles and cut-offs for various ethnic groups are necessary because of differences in body composition. The purpose of this study was to develop waist circumference percentiles for Chinese children and to explore optimal waist circumference cut-off values for predicting cardiovascular risk factors clustering in this population.----- ----- Methods: Height, weight, and waist circumference were measured in 5529 children (2830 boys and 2699 girls) aged 6-12 years randomly selected from southern and northern China. Blood pressure, fasting triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and glucose were obtained in a subsample (n = 1845). Smoothed percentile curves were produced using the LMS method. Receiver-operating characteristic analysis was used to derive the optimal age- and gender-specific waist circumference thresholds for predicting the clustering of cardiovascular risk factors.----- ----- Results: Gender-specific waist circumference percentiles were constructed. The waist circumference thresholds were at the 90th and 84th percentiles for Chinese boys and girls respectively, with sensitivity and specificity ranging from 67% to 83%. The odds ratio of a clustering of cardiovascular risk factors among boys and girls with a higher value than cut-off points was 10.349 (95% confidence interval 4.466 to 23.979) and 8.084 (95% confidence interval 3.147 to 20.767) compared with their counterparts.----- ----- Conclusions: Percentile curves for waist circumference of Chinese children are provided. The cut-off point for waist circumference to predict cardiovascular risk factors clustering is at the 90th and 84th percentiles for Chinese boys and girls, respectively.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Secure data aggregation in wireless sensor networks

A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomena and processing them. They communicate in a multihop manner, due to a short radio range, to form an Ad Hoc network capable of reporting network activities to a data collection sink. Recent advances in WSNs have led to several new promising applications, including habitat monitoring, military target tracking, natural disaster relief, and health monitoring. The current version of sensor node, such as MICA2, uses a 16 bit, 8 MHz Texas Instruments MSP430 micro-controller with only 10 KB RAM, 128 KB program space, 512 KB external ash memory to store measurement data, and is powered by two AA batteries. Due to these unique specifications and a lack of tamper-resistant hardware, devising security protocols for WSNs is complex. Previous studies show that data transmission consumes much more energy than computation. Data aggregation can greatly help to reduce this consumption by eliminating redundant data. However, aggregators are under the threat of various types of attacks. Among them, node compromise is usually considered as one of the most challenging for the security of WSNs. In a node compromise attack, an adversary physically tampers with a node in order to extract the cryptographic secrets. This attack can be very harmful depending on the security architecture of the network. For example, when an aggregator node is compromised, it is easy for the adversary to change the aggregation result and inject false data into the WSN. The contributions of this thesis to the area of secure data aggregation are manifold. We firstly define the security for data aggregation in WSNs. In contrast with existing secure data aggregation definitions, the proposed definition covers the unique characteristics that WSNs have. Secondly, we analyze the relationship between security services and adversarial models considered in existing secure data aggregation in order to provide a general framework of required security services. Thirdly, we analyze existing cryptographic-based and reputationbased secure data aggregation schemes. This analysis covers security services provided by these schemes and their robustness against attacks. Fourthly, we propose a robust reputationbased secure data aggregation scheme for WSNs. This scheme minimizes the use of heavy cryptographic mechanisms. The security advantages provided by this scheme are realized by integrating aggregation functionalities with: (i) a reputation system, (ii) an estimation theory, and (iii) a change detection mechanism. We have shown that this addition helps defend against most of the security attacks discussed in this thesis, including the On-Off attack. Finally, we propose a secure key management scheme in order to distribute essential pairwise and group keys among the sensor nodes. The design idea of the proposed scheme is the combination between Lamport's reverse hash chain as well as the usual hash chain to provide both past and future key secrecy. The proposal avoids the delivery of the whole value of a new group key for group key update; instead only the half of the value is transmitted from the network manager to the sensor nodes. This way, the compromise of a pairwise key alone does not lead to the compromise of the group key. The new pairwise key in our scheme is determined by Diffie-Hellman based key agreement.

Profiling off-road motorcycle and all-terrain riders in Queensland, Australia

The current research aimed to profile off-road riders to identify specific sub-groups in relation to their risk-related behaviours and perceptions. A total of 235 adults from the Australian state of Queensland who had ridden a motorcycle or ATV off-road in the last 12 months were recruited. A cluster analysis was applied to the survey data. Two distinct clusters of riders were identified, which corresponded with the self-report of injury from an off-road riding crash in the prior 12 months. The injured cluster had a significantly higher mean risk propensity and use of safety equipment, though did not differ on self-reported risk taking. The injured cluster as a whole included a higher percentage of males, was younger, and rode more often for recreational or competitive purposes than the non-crash involved cluster. The results indicate that the crash cluster may be both more aware of the potential risks of riding and more willing to ride in a riskier manner.

Property Agents and Motor Dealers Act (Qld) : disclosure, cooling-off and marketeers

The Property Agents and Motor Dealers Act 2000 commenced on 1 July 2001. Significant changes have now been made to the Act by the Property Agents and Motor Dealers Amendment Act 2001 (“the amending Act”). The amending Act contains two distinct parts. First, ss 11-19 of the amending Act provide for increased disclosure obligations on real estate agents, property developers and lawyers together with an extension of the 5 business day cooling-off period imposed by the original Act to all residential property (other than contracts formed on a sale by auction). These provisions are expected to commence on 29 October 2001. The remaining provisions of the amending Act provide for increased jurisdiction and powers to the Property Agents and Motor Dealers Tribunal (“the Tribunal”) enabling the Tribunal to deal with claims against marketeers. These provisions commenced on the date of assent (21 September 2001).