Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Identifying programs to reduce road trauma to A.C.T. motorcyclists

A broad range of motorcycle safety programs and systems exist in Australia and New Zealand. These vary from statewide licensing and training systems run by government licensing and transport agencies to safety programs run in small communities and by individual rider groups. While the effectiveness of licensing and training has been reviewed and recommendations for improvement have been developed (e.g. Haworth & Mulvihill, 2005), little is known about many smaller or innovative programs, and their potential to improve motorcycle safety in the ACT.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

Opportunities for enhancing the Australian national road safety strategy

With the current National Road Safety Strategy [1] coming to the end of its term, it is timely to consider ways in which the next iteration of this strategy can be enhanced. Strategic planning should be a cyclic process in which learning and adaptation are just as important as planning and implementation. It will always be the case that some actions are not as effective as expected, or that barriers to effective implementation will emerge. Rather than being setbacks, these are opportunities for learning about the validity of our assumptions. They are also opportunities for us to adapt to meet unanticipated or emerging challenges. One of the positive aspects of the implementation of the first and second National Road Safety Strategies has been the willingness of road safety agencies to critically assess progress and to identify where and how actions would be better focused. This has been reflected in the evolving nature of the periodic National Road Safety Action Plans. As the decade of the current Strategy reaches an end, there is a need to take this process further, and undertake a thorough critical evaluation of the Strategy development and implementation. While not an attempt to be exhaustive, the following article will identify some key priorities for consideration as part of this process.

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

Protecting the most vulnerable in consumer credit transactions

There are two key ways in which the Australian Uniform Consumer Credit Code seeks to protect consumers in relation to consumer credit transactions. The first is by means of disclosure regulation where information is required to be disclosed to the consumer before the credit contract is entered into and the second is by way of “safety net” provisions, where contracts can be varied or set aside in the event of hardship, a finding that the transaction was unjust, or a finding of unconscionable fees or charges. This article explores the limitations of both of these means of protection, particularly in the case of vulnerable, low-income consumers. In order to highlight the inadequacies of these forms of consumer protection and the need for regulatory reform, we draw on interviews conducted with 30 low-income consumers who had recently signed a credit contract, focusing on their understanding of information disclosed in the contract, as well as their responses to hypothetical unfair terms and their understanding of their rights, for example in the event of an unjust transaction. These interviews were conducted as part of a joint research project between Brotherhood of St Laurence and Griffith University’s Centre for Credit and Consumer Law, funded by Consumer Affairs Victoria.

From Prosumer to Produser: Understanding User-Led Content Creation

Alvin Toffler’s image of the prosumer (1970, 1980, 1990) continues to influence in a significant way our understanding of the user-led, collaborative processes of content creation which are today labelled “social media” or “Web 2.0”. A closer look at Toffler’s own description of his prosumer model reveals, however, that it remains firmly grounded in the mass media age: the prosumer is clearly not the self-motivated creative originator and developer of new content which can today be observed in projects ranging from open source software through Wikipedia to Second Life, but simply a particularly well-informed, and therefore both particularly critical and particularly active, consumer. The highly specialised, high end consumers which exist in areas such as hi-fi or car culture are far more representative of the ideal prosumer than the participants in non-commercial (or as yet non-commercial) collaborative projects. And to expect Toffler’s 1970s model of the prosumer to describe these 21st-century phenomena was always an unrealistic expectation, of course. To describe the creative and collaborative participation which today characterises user-led projects such as Wikipedia, terms such as ‘production’ and ‘consumption’ are no longer particularly useful – even in laboured constructions such as ‘commons-based peer-production’ (Benkler 2006) or ‘p2p production’ (Bauwens 2005). In the user communities participating in such forms of content creation, roles as consumers and users have long begun to be inextricably interwoven with those as producer and creator: users are always already also able to be producers of the shared information collection, regardless of whether they are aware of that fact – they have taken on a new, hybrid role which may be best described as that of a produser (Bruns 2008). Projects which build on such produsage can be found in areas from open source software development through citizen journalism to Wikipedia, and beyond this also in multi-user online computer games, filesharing, and even in communities collaborating on the design of material goods. While addressing a range of different challenges, they nonetheless build on a small number of universal key principles. This paper documents these principles and indicates the possible implications of this transition from production and prosumption to produsage.

Evaluation of valuation of noise amelioration treatments within and outside the road reserve

In urban environments road traffic volumes are increasing and the density of living is becoming higher. As a consequence the urban community is being exposed to increasing levels of road traffic noise. It is also evident that the noise reduction potential of within-the-road-reserve treatments such as noise barriers, mounding and pavement surfacing has been exhausted. This paper presents a strategy that involves the comparison of noise ameliorative treatments both within and outside the road reserve. The noise reduction resulting from the within-the-road-reserve component of treatments has been evaluated using a leading application of the CoRTN Model, developed by the UK Department of Transport 1988 [1], and the outside road reserve treatment has been evaluated in accordance with the Australian Standard 3671, Acoustics – Road traffic noise intrusion – Building sitting and construction [5]. The evaluation of noise treatments has been undertaken using a decision support tool (DST) currently being developed under the research program conducted at RMIT University and Department of Main Roads, Queensland. The case study has been based on data from a real project in Queensland, Australia. The research described here was carried out by the Australian Cooperative Research Centre for Construction Innovation [9], in collaboration with Department of Main Roads, Queensland, Department of Public Works, Queensland, Arup Pty. Ltd., Queensland University of technology and RMIT University.

User behaviours and intentions with digital news media in Australia

This paper summarises findings from a survey of user behaviors and intentions towards digital media and information in Australia. It was undertaken in the first quarter of 2009 by the Queensland University of Technology Creative Industries Faculty and was funded by the Smart Services Cooperative Research Centre. The survey targeted users of 2 news and information sites that are available online only. Findings highlighted differences between the 18-24 year age segment and older users. Social networks (specifically friends and family) were rated as the least reliable, relevant and accurate sources of news. Other findings indicate online news sources that are associated with an established newspaper are highly valued as reliable, relevant and accurate news sources by most people. While most people prefer to use online news sources, there is a great deal of variation in the ways in which people actually use online news. From a total of 524 respondents to the survey it was possible to identify three main types of online news consumers: convenience, loyal and customising users.

Decision - Support Software Tool Handbook

The road and transport industry in Australia and overseas has come a long way to understanding the impact of road traffic noise on the urban environment. Most road authorities now have guidelines to help assess and manage the impact of road traffic noise on noise-sensitive areas and development. While several economic studies across Australia and overseas have tried to value the impact of noise on property prices, decision-makers investing in road traffic noise management strategies have relatively limited historic data and case studies to go on. The perceived success of a noise management strategy currently relies largely on community expectations at a given time, and is not necessarily based on the analysis of the costs and benefits, or the long-term viability and value to the community of the proposed treatment options. With changing trends in urban design, it is essential that the 'whole-of-life' costs and benefits of noise ameliorative treatment options and strategies be identified and made available for decisionmakers in future investment considerations. For this reason, CRC for Construction Innovation Australia funded a research project, Noise Management in Urban Environments to help decision-makers with future road traffic noise management investment decisions. RMIT University and the Queensland Department of Main Roads (QDMR) have conducted the research work, in collaboration with the Queensland Department of Public Works, ARUP Pty Ltd, and the Queensland University of Technology. The research has formed the basis for the development of a decision-support software tool, and helped collate technical and costing data for known noise amelioration treatment options. We intend that the decision support software tool (DST) should help an investment decision-maker to be better informed of suitable noise ameliorative treatment options on a project-by-project basis and identify likely costs and benefits associated with each of those options. This handbook has been prepared as a procedural guide for conducting a comparative assessment of noise ameliorative options. The handbook outlines the methodology and assumptions adopted in the decision-support framework for the investment decision-maker and user of the DST. The DST has been developed to provide an integrated user-friendly interface between road traffic noise modelling software, the relevant assessment criteria and the options analysis process. A user guide for the DST is incorporated in this handbook.

Risk assessment in life-cycle costing for road asset management

Queensland Department of Main Roads, Australia, spends approximately A$ 1 billion annually for road infrastructure asset management. To effectively manage road infrastructure, firstly road agencies not only need to optimise the expenditure for data collection, but at the same time, not jeopardise the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates could be accurately estimated. And finally, the prediction of budgets for maintenance and rehabilitation must provide a certain degree of reliability. This paper presents the results of case studies in using the probability-based method for an integrated approach (i.e. assessing optimal costs of pavement strength data collection; calibrating deterioration prediction models that suit local condition and assessing risk-adjusted budget estimates for road maintenance and rehabilitation for assessing life-cycle budget estimates). The probability concept is opening the path to having the means to predict life-cycle maintenance and rehabilitation budget estimates that have a known probability of success (e.g. produce budget estimates for a project life-cycle cost with 5% probability of exceeding). The paper also presents a conceptual decision-making framework in the form of risk mapping in which the life-cycle budget/cost investment could be considered in conjunction with social, environmental and political issues.

Road Asset Management Investment

Australias civil infrastructure assets of roads, bridges, railways, buildings and other structures are worth billions of dollars. To effectively manage road infrastructures, road agencies firstly need to optimise the expenditure for data collection whilst not jeopardising the reliability in using the optimised data to predict maintenance and rehabilitation costs. Secondly, road agencies need to accurately predict the deterioration rates of infrastructures to reflect local conditions so that the budget estimates can be accurately calculated. Finally, the prediction of budgets for maintenance and rehabilitation must be reasonably reliable.

The user-led disruption : self-(re)broadcasting at Justin.tv and elsewhere

The rise of videosharing and self-(re)broadcasting Web services is posing new threats to a television industry already struggling with the impact of filesharing networks. This paper outlines these threats, focussing especially on the DIY re-broadcasting of live sports using Websites such as Justin.tv and a range of streaming media networks built on peer-to-peer filesharing technology.