An analysis of the variability in Queensland WiM data

The Queensland Department of Main Roads uses Weigh-in-Motion (WiM) devices to covertly monitor (at highway speed) axle mass, axle configurations and speed of heavy vehicles on the road network. Such data is critical for the planning and design of the road network. Some of the data appears excessively variable. The current work considers the nature, magnitude and possible causes of WiM data variability. Over fifty possible causes of variation in WiM data have been identified in the literature. Data exploration has highlighted five basic types of variability specifically: ----- • cycling, both diurnal and annual;----- • consistent but unreasonable data;----- • data jumps;----- • variations between data from opposite sides of the one road; and ----- • non-systematic variations.----- This work is part of wider research into procedures to eliminate or mitigate the influence of WiM data variability.

Children re-read and re-write their neighborhoods : critical literacies and identity work

This chapter considers the complex literate repertoires of 21st century children in multicultural primary classrooms in Adelaide South Australia. It draws on the curricular and pedagogical work of two experienced primary school teachers who explore culture, race and class, by positioning children as textual producers across a variety of media. In particular we discuss two child-authored texts – A is for Arndale – a local alphabet book co-authored by children aged between eight and ten, and – Cooking Afghani Style - a magazine style film produced by a multi-aged class of children (aged eight to thirteen) recently arrived in Australia. In the process of making these texts, primary children engaged in reading as a cultural practice – re-reading and re-writing their neighbourhoods and identities (both individual and collective). This involved frequent excursions to local key sites, both familiar and unfamiliar to the children. They investigated how diverse children experienced and lived their lives in particular places within changing communities.

Critical literacies in place : teachers who work for just and sustainable communities

This chapter draws upon theories of social justice, critical literacy and place-based pedagogies and two research projects to discuss how teachers are working ethically and creatively towards a sustainable and just society in their place(s).

Critical reading comprehension in an era of accountability

This paper argues for the need for critical reading comprehension in an era of accountability that often promotes reading comprehension as readily assessable through students answering multiple choice questions of unseen texts. Based upon a 1 year study investigating literacy in Years 4–9 the ways strong-performing primary schools develop serious and in-depth reading for learning are explored. School and teacher features which allow for the development of sophisticated pedagogical repertoires and space for critical reading comprehension, without losing the complexity of curriculum offerings, are outlined. How one experienced middle primary teacher operates strategically, ethically and critically in supporting her ESL students to learn to read is illustrated. The teacher’s work is situated within the complex accountability demands faced by classroom teachers. This was accomplished by a teacher whose pedagogical repertoire has been assembled across a career teaching in low-SES high ESL communities in a school with a balanced literacy program and high level of collegial support. Risks for schools and teachers whose circumstances work against their capacities for prioritisation and strategic decision-making are identified and discussed.

Development of a software model of a heavy vehicle suspension for research

A Simulink Matlab control system of a heavy vehicle suspension has been developed. The aim of the exercise presented in this paper was to develop a Simulink Matlab control system of a heavy vehicle suspension. The objective facilitated by this outcome was the use of a working model of a heavy vehicle (HV) suspension that could be used for future research. A working computer model is easier and cheaper to re-configure than a HV axle group installed on a truck; it presents less risk should something go wrong and allows more scope for variation and sensitivity analysis before embarking on further "real-world" testing. Empirical data recorded as the input and output signals of a heavy vehicle (HV) suspension were used to develop the parameters for computer simulation of a linear time invariant system described by a second-order differential equation of the form: (i.e. a "2nd-order" system). Using the empirical data as an input to the computer model allowed validation of its output compared with the empirical data. The errors ranged from less than 1% to approximately 3% for any parameter, when comparing like-for-like inputs and outputs. The model is presented along with the results of the validation. This model will be used in future research in the QUT/Main Roads project Heavy vehicle suspensions – testing and analysis, particularly so for a theoretical model of a multi-axle HV suspension with varying values of dynamic load sharing. Allowance will need to be made for the errors noted when using the computer models in this future work.

The road safety implications of illegal street racing and associated risky driving behaviours : an analysis of offences and offenders

The purpose of this study was to explore the road safety implications of illegal street racing and associated risky driving behaviours. This issue was considered in two ways: Phase 1 examined the descriptions of 848 illegal street racing and associated risky driving offences that occurred in Queensland, Australia, in order to estimate the risk associated with these behaviours; and Phase 2 examined the traffic and crash histories of the 802 male offenders involved in these offences, and compared them to those of an age-matched comparison group, in order to examine the risk associated with the driver. It was found in Phase 1 that only 3.7% of these offences resulted in a crash (none of which were fatal), and that these crashes tended to be single-vehicle crashes where the driver lost control of the vehicle and collided with a fixed object. Phase 2 found that the offender sample had significantly more traffic infringements, licence sanctions and crashes in the previous three years than the comparison group. It was concluded that while only a small proportion of racing and associated offences result in a crash, these offenders appear to be generally risky drivers that warrant special attention.

Development of an automated safety assessment framework for construction activities

This paper presents an ongoing research project concerning the development of an automated safety assessment framework for earthmoving and surface mining activities. This research seeks to determine data needs for safety assessment and investigates how to utilize collected data to promote more informed and efficient safety decision-making. The research first examined accidents and fatalities involved with earthmoving and surface mining activities—more specifically, those involving loading, hauling, and dumping operations,—investigated risk factors involved with the accidents, and finally identified data needs for safety assessment based on safety regulations and practices. An automated safety assessment method was then developed using the data needs that had been identified. This research is expected to contribute to the introduction of a fundamental framework for automated safety assessment and the systematic collection of safety-related data from construction activities. Implementation of the entire safety assessment process on actual construction sites remains a task for future research.

Critical literacy : foundational notes

This article traces the lineage of critical literacy from Freire through critical pedagogies and discourse analysis. It discusses the need for a contingent definition of critical literacy, given the increasingly sophisticated nature of texts and discourses.

Building a software architecture for a human-robot team using the ORCA framework

This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a Component-Based Software Engineering approach can address these constraints. The architecture is implemented using Orca – a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the Player software framework in the context of distributed systems.

Critical literacy finds a "Place": Writing and social action in a low-income Australian grade 2/3 classroom

In a study of socioeconomically disadvantaged children's acquisition of school literacies, a university research team investigated how a group of teachers negotiated critical literacies and explored notions of social power with elementary children in a suburban school located in an area of high poverty. Here we focus on a grade 2/3 classroom where the teacher and children became involved in a local urban renewal project and on how in the process the children wrote about place and power. Using the students' concerns about their neighborhood, the teacher engaged her class in a critical literacy project that not only involved a complex set of literate practices but also taught the children about power and the possibilities for local civic action. In particular, we discuss examples of children's drawing and writing about their neighborhoods and their lives. We explore how children's writing and drawing might be key elements in developing "critical literacies" in elementary school settings. We consider how such classroom writing can be a mediator of emotions, intellectual and academic learning, social practice, and political activism.

The development of an intervention to improve the safety of community care nurses while driving and a qualitative investigation of its preliminary effects

This paper details the development of, and perceived role and effectiveness of an innovative intervention designed to ultimately improve the safety of a group of community care (CC) nurses while driving. Recruiting participants from an Australian CC nursing car fleet, qualitative responses from a series of open-ended questions were obtained from drivers (n = 36), supervisors (n = 22), and managers (n = 6). The findings supported the effectiveness of the intervention in reducing self-reported speeding and promoting greater insight into one’s behaviour on the road. This research has important practical implications in that it highlights the value of developing an intervention based on a sound theoretical framework and which is aligned with the needs and beliefs of personnel within a particular organisation.

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.

Machine prognostics based on health state probability estimation

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

Road safety issues for older road users : CARRS-Q Monograph 1

[Selection of papers from the Older Road User Safety Symposium, 26 November 2000, Brisbane, Australia.]----- This publication is a selection of papers on older road user safety which were presented at the Older Road User Safety Symposium on Sunday 26 November 2000 at the Sheraton Brisbane Hotel, Queensland, Australia. The Symposium was held on the day before Australia’s annual Road Safety Research, Policing and Education Conference, which provided an opportunity to garner both presenters and participants from the wider road safety community in Australia. Road safety is a large and diverse area of scholarship and practice, and many disciplines are drawn on in the processes of understanding and addressing road safety problems. The safety of older road users is no different. As this selection shows, work on older road user safety can be informed by demography, research on the mental and physical effects of ageing, social research on older people as road users, evaluation of educational and behavioural interventions, road crash analysis, engineering research and practice, and reviews of policy approaches within Australia and elsewhere. It is possible to summarise these into four constellations, which are reflected in the papers selected for this publication: social impacts and responses; physical and cognitive capability; specific road use performance; and environment/ecology. Though three years have passed since the Symposium, the issues raised in these papers remain current.