Participation index : improved measure of transport related social exclusion?

Although transport related social exclusion has been identified through zonal accessibility measures in the recent past, the debate has shifted from zonal to individual level measures. One way to identify disadvantaged individuals is to measure their size of participation in society (activity spaces). After reviewing existing literature, this paper has found two approaches to measure the activity spaces. One approach is based on the time-geographic potential path area (PPA) concept. The size of the PPA has largely been used as an indicator to the size of potential activity spaces and consequently individual accessibility. The limitations of the PPA concept have been identified in this paper and it is argued cannot be applied as a measure of social exclusion. The other approach is based on individuals’ actual travel activity participation called actual activity spaces. The size of actual activity spaces possesses a good potential measure of social exclusion. However, the indicators to measure the size of actual activity spaces are multidimensional representing the different aspects of social exclusion. The development of a unified approach has therefore been found to be important. This paper has developed a participation index (PI) using the different dimensions of actual activity spaces encountered. A framework has also been developed to operationalise the concept in GIS. The framework, on the one hand, will visualize individuals’ actual travel behaviour in real geographic space; on the other hand, it will calculate the size of their participation in society.

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.

Industry school partnerships : real world learning through the Gateway Schools Projects

In the last decade, a gradual but significant shift in education has taken place. Schools have transformed from hermetically sealed, impermeable bureaucracies to dynamic and flexible organisations characterised by openness to local communities and connectedness to global issues and cultures. They are also more responsive to the aspirations of students and parents. A central feature of what Christian Maroy (2009) has described as the post bureaucratic era of education has been the relationships formed between schools and other organisations through formalised partnerships. Partnerships have been a significant feature of schooling in Queensland since the 1980s when schools developed Vocational Education Programs (VET) providing alternative pathways from schooling to post school training or employment. However, partnerships that have emerged in recent times have been more structured in their organisation and more targeted in terms of the outcomes they aim to achieve. Examples here have included Queensland’s District Youth Achievement plans that linked schools, business, industry bodies, training organisations and community groups to improve transition outcomes, particularly for young people at risk in their transitions from school to post-school life.

Service-learning within higher education : rhizomatic interconnections between university and the real world

This paper discusses Service-learning within an Australian higher education context as pedagogy to teach about inclusive education. Using Deleuze and Guattari’s (1987) model of the rhizome, this study conceptualises pre-service teachers’ learning experiences as multiple, hydra and continuous. Data from reflection logs of pre-service teachers highlight how the learning experience allowed them to gain insights in knowledge as socially just, ethical and inclusive. The paper concludes by arguing the need to consider Service-learning as integral to university education for pre-service teachers.

A grouping model for distributed pipeline assets maintenance decision

Distributed pipeline assets systems are crucial to society. The deterioration of these assets and the optimal allocation of limited budget for their maintenance correspond to crucial challenges for water utility managers. Decision makers should be assisted with optimal solutions to select the best maintenance plan concerning available resources and management strategies. Much research effort has been dedicated to the development of optimal strategies for maintenance of water pipes. Most of the maintenance strategies are intended for scheduling individual water pipe. Consideration of optimal group scheduling replacement jobs for groups of pipes or other linear assets has so far not received much attention in literature. It is a common practice that replacement planners select two or three pipes manually with ambiguous criteria to group into one replacement job. This is obviously not the best solution for job grouping and may not be cost effective, especially when total cost can be up to multiple million dollars. In this paper, an optimal group scheduling scheme with three decision criteria for distributed pipeline assets maintenance decision is proposed. A Maintenance Grouping Optimization (MGO) model with multiple criteria is developed. An immediate challenge of such modeling is to deal with scalability of vast combinatorial solution space. To address this issue, a modified genetic algorithm is developed together with a Judgment Matrix. This Judgment Matrix is corresponding to various combinations of pipe replacement schedules. An industrial case study based on a section of a real water distribution network was conducted to test the new model. The results of the case study show that new schedule generated a significant cost reduction compared with the schedule without grouping pipes.

Blackboard as an online learning environment : what do teacher education students and staff think?

Abstract: As online learning environments now have an established presence in higher education we need to ask the question: How effective are these environments for student learning? Online environments can provide a different type of learning experience than traditional face-to-face contexts (for on-campus students) or print-based materials (for distance learners). This article identifies teacher education student and staff perceptions of teaching and learning using the online learning management system, Blackboard. Perceptions of staff and students are compared and implications for teacher education staff interested in providing high quality learning environments within an online space are discussed.

Resident-funded retirement village valuations : complications with the application of the DCF

Retirement village assets are different from traditional residential assets due to their operation in accordance with statutory legislation. Designed for independent living, retirement villages provide either detached or semi-detached residential dwellings with car parking and small private yards with community facilities providing a shared congregational area for village activities and socialising. In essence, the village operator provides the land and buildings to the residents who pay an amount on entry for the right of occupation. On departure from the units an agreed proportion of either the original purchase price or the sale price is paid to the outgoing resident. As ongoing levies are typically offset by ongoing operational expenses the market value of the operator's interest in the retirement village is therefore predominantly based upon the estimated future income from deferred management fees and capital gain upon roll-over receivable by the operator in accordance with the respective residency agreements. Given the lumpiness of these payments, there is general acceptance that the most appropriate approach to valuation is through discounted cash flow (DCF) analysis. There is however inconsistency between valuers across Australia in how they undertake their DCF analysis, leading to differences in reported values and subsequent confusion among users of valuation services. To give guidance to valuers and enhance confidence from users of valuation services this paper investigates the five major elements of DCF methodology, namely cash flows, escalation factors, holding period, terminal value and discount rate.

Using virtual worlds for collaborative business process modeling

Purpose Process modeling is a complex organizational task that requires many iterations and communication between the business analysts and the domain specialists. The challenge of process modeling is exacerbated, when the process of modeling has to be performed in a cross-organizational, distributed environment. In this paper we suggest a 3D environment for collaborative process modeling, using Virtual World technology. Design/methodology/approach We suggest a new collaborative process modeling approach based on Virtual World technology. We describe the design of an innovative prototype collaborative process modeling approach, implemented as a 3D BPMN modeling environment in Second Life. We use a case study to evaluate the suggested approach. Findings Based on our case study application, we show that our approach increases user empowerment and adds significantly to the collaboration and consensual development of process models even when the relevant stakeholders are geographically dispersed. Research limitations implications – We present design work and a case study. More research is needed to more thoroughly evaluate the presented approach in a variety of real-life process modeling settings. Practical implications Our research outcomes as design artifacts are directly available and applicable by business process management professionals and can be used by business, system and process analysts in real-world practice. Originality/value Our research is the first reported attempt to develop a process modeling approach on the basis of virtual world technology. We describe a novel and innovative 3D BPMN modeling environment in Second Life.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

Everything is child abuse

In 2008, the Australian federal Senate held an Inquiry into the Sexualisation of Children in the Contemporary Media Environment. I made a submission to this Inquiry, noting that in public debate about this topic a number of quite distinct issues, with distinct aetiologies, were collapsed together. These included: child pornography; children being targeted by any form of marketing; young people becoming sexually active; sexual abuse of children; raunch culture; protecting children from any sexualised material in the media; and body image disorders. I suggested that commentators had collapsed these issues together because the image of the helpless child is a powerful one for critics to challenge undesirable aspects of contemporary culture. The result of many different ideological viewpoints all using the same argument - that the forms of culture they didn't like were damaging children - gives the impression that there is no element of culture today that isn't (somebody claims) causing harm to children: everything is child abuse. The danger of such discourses is that they draw attention away from the real harm that is being caused to children by sexual and other forms of maltreatment - which overwhelmingly occur within families, and for reasons ignored in these debates.

The concealed difficulties of aligning CRE decisions to corporate goals

Realisation of the importance of real estate asset strategic decision making has inspired a burgeoning corporate real estate management (CREM) literature. Much of this criticises the poor alignment between strategic business direction and the ‘enabling’ physical environment. This is based on the understanding that corporate real estate assets represent the physical resource base that supports business, and can either complement or impede that business. In the hope of resolving this problem, CRE authors advocate a deeper integration of strategic and corporate real estate decisions. However this recommendation appears to be based on a relatively simplistic theoretical approach to organization where decision-making tends to be viewed as a rationally managed event rather than a complex process. Defining decision making as an isolated event has led to an uncritical acceptance of two basic assumptions: ubiquitous, conflict-free rationality and profit maximisation. These assumptions have encouraged prescriptive solutions that clearly lack the sophistication necessary to come to grips with the complexity of the built and organizational environment. Alternatively, approaching CREM decision making from a more sophisticated perspective, such as that of the “Carnegie School”, leads to conceptualise it as a ‘process’, creating room for bounded rationality, multiple goals, intra-organizational conflict, environmental matching, uncertainty avoidance and problem searching. It is reasonable to expect that such an approach will result in a better understanding of the organizational context, which will facilitate the creation of organizational objectives, assist with the formation of strategies, and ultimately will aid decision.

A dynamic approach to forecast rental growth

Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

Remote monitoring of outdoor performance of low scale dye sensitized solar cells for nanosensors nodes

This is the first outdoor test of small-scale dye sensitized solar cells (DSC) powering a standalone nanosensor node. A solar cell test station (SCTS) has been developed using standard DSC to power a gas nanosensor, a radio transmitter, and the control electronics (CE) for battery charging. The station is remotely monitored through wired (Ethernet cable) or wireless connection (radio transmitter) in order to evaluate in real time the performance of the solar cells powering a nanosensor and a transmitter under different weather conditions. We analyze trends of energy conversion efficiency after 60 days of operation. The 408 cm2 active surface module produces enough energy to power a gas nanosensor and a radio transmitter during the day and part of the night. Also, by using a variable programmable load we keep the system working on the maximum power point (MPP) quantifying the total energy generated and stored in a battery. Although this technology is at an early stage of development, these experiments provide useful data for future outdoor applications such as nanosensor network nodes.

Implications of the National Rental Affordability Scheme on the valuation of residential property

The provision of shelter is a basic need and in Australia there has been a history of home ownership. However recent economic growth and rising construction costs, particularly over the past decade, has placed home ownership out of reach for some. In response to increased affordability pressures, the Australian Federal Government established the National Rental Affordability Scheme (NRAS) in 2008. The aim of establishing the NRAS initiative is to stimulate the supply of new affordable rental dwellings, targeting 50,000 new properties by June 2012, through the provision of a National Rental Incentive for each “approved” dwelling. To be approved the dwelling must be newly constructed and subsequently rented to eligible low and moderate income households at rentals no greater than 80 percent of market rates. There is a further requirement that the accommodation be provided as part of the scheme for no less than 10 years. The requirement to provide new residential accommodation at below market rentals for no less than 10 years has an impact on value and as such the valuation methodologies employed. To give guidance to valuers this paper investigates the scheme, the impact on value and expectations for the future.