Making the train : re-conceptualising accessibility for intra-urban rail travel

Australian authorities have set ambitious policy objectives to shift Australia’s current transport profile of heavy reliance on private motor cars to sustainable modes. Improving accessibility of public transport is a central component of that objective. Past studies on accessibility to public transport focus on walking time and/or waiting time. However, travellers’ perceptions of the interface leg journeys may depend not only on these direct and tangible factors but also on social and psychological factors. This paper extends previous research that identified five salient perspectives of rail access by means of a statement sorting activity and cluster analysis with a small sample of rail passengers in three Australian cities (Zuniga et al, 2013). This study collects a new data set including 144 responses from Brisbane and Melbourne to an online survey made up of a Likert-scaled statement sorting exercise and questionnaire. It employs factor analysis to examine the statement rankings and uncovers seven underlying factors in the exploratory manner, i.e., station, safety, access, transfer, service attitude, traveler’s physical activity levels, and environmental concern. Respondents from groups stratified by rail use frequency are compared in terms of their scores of those factors. Findings from this study indicate a need to re-conceptualize accessibility to intra-urban rail travel in agreement with current policy agenda, and to target behavioral intervention to multiple dimensions of accessibility influencing passengers’ travel choices. Arguments in this paper are not limited to intra-urban rail transit, but may also be relevant to public transport in general.

Fault detection in wind turbine : a systematic literature review

Wind power has become one of the popular renewable resources all over the world and is anticipated to occupy 12% of the total global electricity generation capacity by 2020. For the harsh environment that the wind turbine operates, fault diagnostic and condition monitoring are important for wind turbine safety and reliability. This paper employs a systematic literature review to report the most recent promotions in the wind turbine fault diagnostic, from 2005 to 2012. The frequent faults and failures in wind turbines are considered and different techniques which have been used by researchers are introduced, classified and discussed.

High efficiency auxiliary power converters

The auxiliary load DC-DC converters of the Sunshark solar car have never been examined. An analysis of the current design reveals it is complicated, and inefficient. Some simple measures to greatly improve the efficiency are present which will achieve an overall worthwhile power saving. Two switch-mode power supply DC-DC converter designs are presented. One is a constant current supply for the LED brake and turn indicators, which allows them to be powered directly from the main DC bus, and switched only as necessary. The second is a low power flyback converter, which employs synchronous rectification among other techniques to achieve good efficiency and regulation over a large range of output powers. Practical results from both converters, and an indication of the overall improvement in system efficiency will be offered.

Decision making guidelines for sustainable construction of industrialised building systems

The construction industry has an obligation to respond to sustainability expectations of our society. Solutions that integrate innovative, intelligent and sustainability deliverables are vital for us to meet new and emerging challenges. Industrialised Building Systems (IBS), or known otherwise as prefabrication, employs a combination of ready-made components in the construction of buildings. They promote quality of production, enhance simplification of construction processes and minimise waste. The unique characteristics of this construction method respond well to sustainability. Despite the promises however, IBS has yet to be effectively implemented in Malaysia. There are often misconceptions among key stakeholders about IBS applications. The existing rating schemes fail to assess IBS against sustainability measures. To ensure the capture of full sustainability potential in buildings developed, the critical factors and action plans agreeable to all participants in the development processes need to be identified. Through questionnaire survey, eighteen critical factors relevant to IBS sustainability were identified and encapsulated into a conceptual framework to coordinate a systematic IBS decision making approach. Five categories were used to separate the critical factors into: ecological performance; economic value; social equity and culture; technical quality; and implementation and enforcement. This categorisation extends the "Triple Bottom Lines" to include social, economic, environmental and institutional dimensions. Semi-structured interviews help identify strategies of actions and solutions of potential problems through a SWOT analysis framework. These tools help the decision-makers maximise the opportunities by using available strengths, avoid weaknesses, and diagnose possible threats in the examined issues. The recommendations formed an integrated action plan to present information on what and how to improve sustainability through tackling each critical factor during IBS development. It can be used as part of the project briefing documents for IBS designers. For validation and finalisation the research deliverables, three case studies were conducted. The research fills a current gap by responding to IBS project scenarios in developing countries. It also provides a balanced view for designers to better understand sustainability potential and prioritize attentions to manage sustainability issues in IBS applications.

How can Australia sustain middle school education?

Middle school is a crucial area of education where adolescents experiencing physiological and psychological changes, and require expert guidance. As more research evidence is provided about adolescent learning, teachers are considered pivotal to adolescents’ educational development. Reform measures need to be targeted at the inservice and preservice teacher levels. This quantitative study employs a 40-item, five part Likert scale survey to understand preservice teachers’ (n = 142) perceptions of their confidence to teach in a middle school at the conclusion of their tertiary education. The survey instrument was developed from the literature, with connections to the Queensland College of Teachers' professional standards. Results indicated that they perceived themselves as capable of creating a positive classroom environment with seven items greater than 80%, except with behaviour management (< 80% for two items), and they considered their pedagogical knowledge to be adequate (i.e., 7 out of 8 items > 84%). Items associated with implementing a middle school curriculum had varied responses (e.g., implementing literacy and numeracy were 74%, while implementing learning with real world connections was 91%). This information may assist coursework designers. For example, if a significant percentages of preservice teachers indicate that they believe they were not well prepared for assessment and reporting at the middle school level, then course designers can target these areas more effectively.

Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS)

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

Ensuring sessional academic success by rethinking the place of academic development

There has been growing recognition of the contribution that Sessional Academics make to student learning in higher education; with recent studies concluding that around half Australian university teaching is now performed by casual staff [Red Report 2008; May, 2013]. However, sector-wide research and institutional audits continue to raise concerns about academic development and quality assurance, as well as the recognition and retention of Sessional Academics. In response, universities offer academic development programs. However, while such centrally offered programs are undoubtedly useful, they are necessarily generic and cannot address the local contexts of faculties or provide ‘on the ground’ support. This paper presents a new, distributed model of academic support and development for Sessional academics at Queensland University of Technology. Entitled the Sessional Academic Success program, it employs the principles of distributed leadership. Experienced Sessional academics are trained and supported to assume roles as Sessional Academic Success Advisors within their schools. Complementing our central programs, they design bespoke, locally situated, peer-to-peer academic development for new Sessional teachers; provide ‘just in time’, safe and reliable advice; and build supportive communities of teaching practice in their local contexts. This distributed model re-envisages the forms and places of academic development and support. It helps ensure that new Sessional Academics are embraced by faculty life. And, recognizing that experienced Sessional Academics have much to contribute to the advancement of learning and teaching, it builds their capacity through leadership opportunities. As the designer/facilitator of the program and a Sessional Academic Success Advisor, the authors take a dialogic approach and together describe the design, implementation and outcomes of the program.

A methodology for estimating exposure-controlled crash risk using traffic Police crash data

Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Swimmer localization from a moving camera

At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

Spin-coated carbon

We describe a novel and facile approach to covalently graft molecules containing stable free radicals onto carbon surfaces including graphene, carbon nanotubes, glassy carbon and carbon fibres. The new technique employs a stable aryl nitroxide radical diazonium tetrafluoroborate salt. The salt may be isolated and added to carbon surfaces in solution, suspension or electrochemically and represents a convenient, versatile and highly efficient means to adorn graphitic materials with large numbers of free radical spin systems

Process mining for clinical processes: A comparative analysis of four Australian hospitals

Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

How to guarantee compliance between workflows and product lifecycles?

Product Lifecycle Management (PLM) systems are widely used in the manufacturing industry. A core feature of such systems is to provide support for versioning of product data. As workflow functionality is increasingly used in PLM systems, the possibility emerges that the versioning transitions for product objects as encapsulated in process models do not comply with the valid version control policies mandated in the objects’ actual lifecycles. In this paper we propose a solution to tackle the (non-)compliance issues between processes and object version control policies. We formally define the notion of compliance between these two artifacts in product lifecycle management and then develop a compliance checking method which employs a well-established workflow analysis technique. This forms the basis of a tool which offers automated support to the proposed approach. By applying the approach to a collection of real-life specifications in a main PLM system, we demonstrate the practical applicability of our solution to the field.

A recommendation approach dealing with multiple market segments

A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

A web-based approach to data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Moreover, several optimization techniques are also proposed to reduce the cost of estimating the confidence of imputation queries at both the tuple-level and the database-level. Experiments based on several real-world data collections demonstrate not only the effectiveness of WebPut compared to existing approaches, but also the efficiency of our proposed algorithms and optimization techniques.