Catching drink drivers in Queensland through Random Breath Testing : what does the last decade of data tell us

Background Random Breath Testing (RBT) has proven to be a cornerstone of enforcement attempts to deter (as well as apprehend) motorists from drink driving in Queensland (Australia) for decades. However, scant published research has examined the relationship between the frequency of implementing RBT activities and subsequent drink driving apprehension rates across time. Aim This study aimed to examine the prevalence of apprehending drink drivers in Queensland over a 12 year period. It was hypothesised that an increase in breath testing rates would result in a corresponding decrease in the frequency of drink driving apprehension rates over time, which would reflect general deterrent effects. Method The Queensland Police Service provided RBT data that was analysed. Results Between the 1st of January 2000 and 31st of December 2011, 35,082,386 random breath tests (both mobile and stationary) were conducted in Queensland, resulting in 248,173 individuals being apprehended for drink driving offences. A total of 342,801 offences were recorded during this period, representing an intercept rate of .96. Of these offences, 276,711 (80.72%) were recorded against males and 66,024 (19.28%) offences committed by females. The most common drink driving offence was between 0.05 and 0.08 BAC limit. The largest proportion of offences was detected on the weekends, with Saturdays (27.60%) proving to be the most common drink driving night followed by Sundays (21.41%). The prevalence of drink driving detection rates rose steadily across time, peaking in 2008 and 2009, before slightly declining. This decline was observed across all Queensland regions and any increase in annual figures was due to new offence types being developed. Discussion This paper will further outline the major findings of the study in regards to tailoring RBT operations to increase detection rates as well as improve the general deterrent effect of the initiative.

Visual control for automated aircraft collision avoidance systems

This thesis presents a new vision-based decision and control strategy for automated aircraft collision avoidance that can be realistically applied to the See and Avoid problem. The effectiveness of the control strategy positions the research as a major contribution toward realising the simultaneous operation of manned and unmanned aircraft within civilian airspace. Key developments include novel classical and visual predictive control frameworks, and a performance evaluation technique aligned with existing aviation practise and applicable to autonomous systems. The overall approach is demonstrated through experimental results on a small multirotor unmanned aircraft, and through high fidelity probabilistic simulation studies.

Automated counting of the Northern Pacific Sea Star in the Derwent using shape recognition

A novel shape recognition algorithm was developed to autonomously classify the Northern Pacific Sea Star (Asterias amurenis) from benthic images that were collected by the Starbug AUV during 6km of transects in the Derwent estuary. Despite the effects of scattering, attenuation, soft focus and motion blur within the underwater images, an optimal joint classification rate of 77.5% and misclassification rate of 13.5% was achieved. The performance of algorithm was largely attributed to its ability to recognise locally deformed sea star shapes that were created during the segmentation of the distorted images.

Automated sensory data alignment for environmental and epidermal change monitoring

In this paper we present research adapting a state of the art condition-invariant robotic place recognition algorithm to the role of automated inter- and intra-image alignment of sensor observations of environmental and skin change over time. The approach involves inverting the typical criteria placed upon navigation algorithms in robotics; we exploit rather than attempt to fix the limited camera viewpoint invariance of such algorithms, showing that approximate viewpoint repetition is realistic in a wide range of environments and medical applications. We demonstrate the algorithms automatically aligning challenging visual data from a range of real-world applications: ecological monitoring of environmental change, aerial observation of natural disasters including flooding, tsunamis and bushfires and tracking wound recovery and sun damage over time and present a prototype active guidance system for enforcing viewpoint repetition. We hope to provide an interesting case study for how traditional research criteria in robotics can be inverted to provide useful outcomes in applied situations.

Factors influencing the provision of end-of-life care in critical care settings : development and testing of a survey instrument

Aim. To develop and psychometrically test a survey instrument to identify the factors influencing the provision of end-of-life care by critical care nurses. Background. Following a decision to withdraw life-sustaining treatment, critical care nurses remain with the patient and their family providing end-of-life care. Identification of factors influencing the provision of this care can give evidence to inform practice development and support nurses. Design. A cross-sectional survey of critical care nurses. Method. An online survey was developed, reviewed by an expert panel and pilot tested to obtain preliminary evidence of its reliability and validity. In May 2011, a convenience sample of critical care nurses (n = 392, response rate 25%) completed the survey. The analytical approach to data obtained from the 58 items measured on a Likert scale included exploratory factor analysis and descriptive statistics. Results. Exploratory factor analysis identified eight factors influencing the provision of end-of-life care: emotional support for nurses, palliative values, patient and family preferences, resources, organizational support, care planning, knowledge and preparedness. Internal consistency of each latent construct was deemed satisfactory. The results of descriptive statistics revealed a strong commitment to the inclusion of families in end-of-life care and the value of this care in the critical care setting. Conclusion. This paper reports preliminary evidence of the psychometric properties of a new survey instrument. The findings may inform practice development opportunities to support critical care nurses in the provision of endof- life care and improve the care that patients and their families receive.

Stability analysis and implementation of Power-Hardware-in-the-Loop for power system testing

This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

Evolutionary game design : automated game design comes of age

The "Humies" awards are an annual competition held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO), in which cash prizes totalling $10,000 are awarded to the most human-competitive results produced by any form of evolutionary computation published in the previous year. This article describes the gold medal-winning entry from the 2012 "Humies" competition, based on the LUDI system for playing, evaluating and creating new board games. LUDI was able to demonstrate human-competitive results in evolving novel board games that have gone on to be commercially published, one of which, Yavalath, has been ranked in the top 2.5% of abstract board games ever invented. Further evidence of human-competitiveness was demonstrated in the evolved games implicitly capturing several principles of good game design, outperforming human designers in at least one case, and going on to inspire a new sub-genre of games.

Hand, foot and mouth disease in China: Evaluating an automated system for the detection of outbreaks

Objective To evaluate the performance of China’s infectious disease automated alert and response system in the detection of outbreaks of hand, foot and mouth (HFM) disease. Methods We estimated size, duration and delay in reporting HFM disease outbreaks from cases notified between 1 May 2008 and 30 April 2010 and between 1 May 2010 and 30 April 2012, before and after automatic alert and response included HFM disease. Sensitivity, specificity and timeliness of detection of aberrations in the incidence of HFM disease outbreaks were estimated by comparing automated detections to observations of public health staff. Findings The alert and response system recorded 106 005 aberrations in the incidence of HFM disease between 1 May 2010 and 30 April 2012 – a mean of 5.6 aberrations per 100 days in each county that reported HFM disease. The response system had a sensitivity of 92.7% and a specificity of 95.0%. The mean delay between the reporting of the first case of an outbreak and detection of that outbreak by the response system was 2.1 days. Between the first and second study periods, the mean size of an HFM disease outbreak decreased from 19.4 to 15.8 cases and the mean interval between the onset and initial reporting of such an outbreak to the public health emergency reporting system decreased from 10.0 to 9.1 days. Conclusion The automated alert and response system shows good sensitivity in the detection of HFM disease outbreaks and appears to be relatively rapid. Continued use of this system should allow more effective prevention and limitation of such outbreaks in China.

Testing times for the implementation of curriculum change: Analysis and extension of a curriculum change model

School curriculum change processes have traditionally been managed internally. However, in Queensland, Australia, as a response to the current high-stakes accountability regime, more and more principals are outsourcing this work to external change agents (ECAs). In 2009, one of the authors (a university lecturer and ECA) developed a curriculum change model (the Controlled Rapid Approach to Curriculum Change (CRACC)), specifically outlining the involvement of an ECA in the initiation phase of a school’s curriculum change process. The purpose of this paper is to extend the CRACC model by unpacking the implementation phase, drawing on data from a pilot study of a single school. Interview responses revealed that during the implementation phase, teachers wanted to be kept informed of the wider educational context; use data to constantly track students; relate pedagogical practices to testing practices; share information between departments and professional levels; and, own whole school performance. It is suggested that the findings would be transferable to other school settings and internal leadership of curriculum change. The paper also strikes a chord of concern – Do the responses from teachers operating in such an accountability regime live their professional lives within this corporate and globalised ideology whether they want to or not?

Employee perceptions of alcohol and drug policy effectiveness: Policy features, concerns about drug testing, and the key role of preventative measures

As negative employee attitudes towards alcohol and other drug (AOD) policies may have serious consequences for organizations, the present study examined demographic and attitudinal dimensions leading to employees’ perceptions of AOD policy effectiveness. Survey responses were obtained from 147 employees in an Australian agricultural organization. Three dimensions of attitudes towards AOD policies were examined: knowledge of policy features, attitudes towards testing, and preventative measures such as job design and organizational involvement in community health. Demographic differences were identified, with males and blue-collar employees reporting significantly more negative attitudes towards the AOD policy. Attitude dimensions were stronger predictors of perceptions of policy effectiveness than demographics, and the strongest predictor was preventative measures. This suggests that organizations should do more than design adequate and fair AOD policies, and take a more holistic approach to AOD impairment by engaging in workplace design to reduce AOD use and promote a consistent health message to employees and the community.

Learning to lead: The development and testing of a model of leadership learning

Drawing upon an action learning perspective, we hypothesized that a leader’s learning of project leadership skills would be related to facilitative leadership, team reflexivity, and team performance. Secondly, we proposed that new and experienced leaders would differ in the amount they learn from their current and recent experience as project managers, and in the strength of the relationship between their self-reported learning, facilitative leadership, and team reflexivity. We conducted a 1-year longitudinal study of 50 R&D teams, led by 25 new and 25 experienced leaders, with 313 team members and 22 project customers, collecting both quantitative and qualitative data. We found evidence of a significant impact of the leader’s learning on subsequent facilitative leadership and team performance 8 and 12 months later, suggesting a lag between learning leadership skills and translating these skills into leadership behavior. The findings contribute to an understanding of how leaders consolidate their learned experience into facilitative leadership behavior.

A nationwide web-based automated system for early outbreak detection and rapid response in China

Timely reporting, effective analyses and rapid distribution of surveillance data can assist in detecting the aberration of disease occurrence and further facilitate a timely response. In China, a new nationwide web-based automated system for outbreak detection and rapid response was developed in 2008. The China Infectious Disease Automated-alert and Response System (CIDARS) was developed by the Chinese Center for Disease Control and Prevention based on the surveillance data from the existing electronic National Notifiable Infectious Diseases Reporting Information System (NIDRIS) started in 2004. NIDRIS greatly improved the timeliness and completeness of data reporting with real time reporting information via the Internet. CIDARS further facilitates the data analysis, aberration detection, signal dissemination, signal response and information communication needed by public health departments across the country. In CIDARS, three aberration detection methods are used to detect the unusual occurrence of 28 notifiable infectious diseases at the county level and to transmit that information either in real-time or on a daily basis. The Internet, computers and mobile phones are used to accomplish rapid signal generation and dissemination, timely reporting and reviewing of the signal response results. CIDARS has been used nationwide since 2008; all Centers for Disease Control and Prevention (CDC) in China at the county, prefecture, provincial and national levels are involved in the system. It assists with early outbreak detection at the local level and prompts reporting of unusual disease occurrences or potential outbreaks to CDCs throughout the country.

Achieving intention-centric BPM through automated planning

As a result of the more distributed nature of organisations and the inherently increasing complexity of their business processes, a significant effort is required for the specification and verification of those processes. The composition of the activities into a business process that accomplishes a specific organisational goal has primarily been a manual task. Automated planning is a branch of artificial intelligence (AI) in which activities are selected and organised by anticipating their expected outcomes with the aim of achieving some goal. As such, automated planning would seem to be a natural fit to the BPM domain to automate the specification of control flow. A number of attempts have been made to apply automated planning to the business process and service composition domain in different stages of the BPM lifecycle. However, a unified adoption of these techniques throughout the BPM lifecycle is missing. As such, we propose a new intention-centric BPM paradigm, which aims on minimising the specification effort by exploiting automated planning techniques to achieve a pre-stated goal. This paper provides a vision on the future possibilities of enhancing BPM using automated planning. A research agenda is presented, which provides an overview of the opportunities and challenges for the exploitation of automated planning in BPM.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.