Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.

Educating for digital futures : what the learning strategies of digital content professionals can teach higher education

Beginning in the second half of the 20th century, ICTs transformed many societies from industrial societies in which manufacturing was the central focus, into knowledge societies in which dealing effectively with data and information has become a central element of work (Anderson, 2008). To meet the needs of the knowledge society, universities must reinvent their structures and processes, their curricula and pedagogic practices. In addition to this, of course higher education is itself subject to the sweeping influence of ICTs. But what might effective higher education look like in the 21st century? In designing higher education systems and learning experiences which are responsive to the learning needs of the future and exploit the possibilities offered by ICTs, we can learn much from the existing professional development strategies of people who are already successful in 21st century fields, such as digital media. In this study, I ask: (1) what are the learning challenges faced by digital media professionals in the 21st century? (2) what are the various roles of formal and informal education in their professional learning strategies at present? (3) how do they prefer to acquire needed capabilities? In-depth interviews were undertaken with successful Australian digital media professionals working in micro businesses and SMEs to answer these questions. The strongest thematic grouping that emerged from the interviews related to the need for continual learning and relearning because of the sheer rate of change in the digital media industries. Four dialectical relationships became apparent from the interviewees’ commentaries around the learning imperatives arising out of the immense and continual changes occurring in the digital content industries: (1) currency vs best practice (2) diversification vs specialisation of products and services (3) creative outputs vs commercial outcomes (4) more learning opportunities vs less opportunity to learn. These findings point to the importance of ‘learning how to learn’ as a 21st century capability. The interviewees were ambivalent about university courses as preparation for professional life in their fields. Higher education was described by several interviewees as having relatively little value-add beyond what one described as “really expensive credentialling services.” For all interviewees in this study, informal learning strategies were the preferred methods of acquiring the majority of knowledge and skills, both for ongoing and initial professional development. Informal learning has no ‘curriculum’ per se, and tends to be opportunistic, unstructured, pedagogically agile and far more self-directed than formal learning (Eraut, 2004). In an industry impacted by constant change, informal learning is clearly both essential and ubiquitous. Inspired by the professional development strategies of the digital media professionals in this study, I propose a 21st century model of the university as a broad, open learning ecology, which also includes industry, professionals, users, and university researchers. If created and managed appropriately, the university learning network becomes the conduit and knowledge integrator for the latest research and industry trends, which students and professionals alike can access as needed.

Acquisition of expertise in cricket fast bowling : perceptions of expert players and coaches

Objectives: Experiential knowledge of elite athletes and coaches was investigated to reveal insights on expertise acquisition in cricket fast bowling. Design: Twenty-one past or present elite cricket fast bowlers and coaches of national or international level were interviewed using an in-depth, open-ended, semi-structured approach. Methods: Participants were asked about specific factors which they believed were markers of fast bowling expertise potential. Of specific interest was the relative importance of each potential component of fast bowling expertise and how components interacted or developed over time. Results: The importance of intrinsic motivation early in development was highlighted, along with physical, psychological and technical attributes. Results supported a multiplicative and interactive complex systems model of talent development in fast bowling, in which component weightings were varied due to individual differences in potential experts. Dropout rates in potential experts were attributed to misconceived current talent identification programmes and coaching practices, early maturation and physical attributes, injuries and lack of key psychological attributes and skills. Conclusions: Data are consistent with a dynamical systems model of expertise acquisition in fast bowling, with numerous trajectories available for talent development. Further work is needed to relate experiential and theoretical knowledge on expertise in other sports.

A grand challenge : reflecting on university science curriculum design, collaborative partnerships and integration of information literacy skills

In 2012, Queensland University of Technology (QUT) committed to the massive project of revitalizing its Bachelor of Science (ST01) degree. Like most universities in Australia, QUT has begun work to align all courses by 2015 to the requirements of the updated Australian Qualifications Framework (AQF) which is regulated by the Tertiary Education Quality and Standards Agency (TEQSA). From the very start of the redesigned degree program, students approach scientific study with an exciting mix of theory and highly topical real world examples through their chosen “grand challenge.” These challenges, Fukushima and nuclear energy for example, are the lenses used to explore science and lead to 21st century learning outcomes for students. For the teaching and learning support staff, our grand challenge is to expose all science students to multidisciplinary content with a strong emphasis on embedding information literacies into the curriculum. With ST01, QUT is taking the initiative to rethink not only content but how units are delivered and even how we work together between the faculty, the library and learning and teaching support. This was the desired outcome but as we move from design to implementation, has this goal been achieved? A main component of the new degree is to ensure scaffolding of information literacy skills throughout the entirety of the three year course. However, with the strong focus on problem-based learning and group work skills, many issues arise both for students and lecturers. A move away from a traditional lecture style is necessary but impacts on academics’ workload and comfort levels. Therefore, academics in collaboration with librarians and other learning support staff must draw on each others’ expertise to work together to ensure pedagogy, assessments and targeted classroom activities are mapped within and between units. This partnership can counteract the tendency of isolated, unsupported academics to concentrate on day-to-day teaching at the expense of consistency between units and big picture objectives. Support staff may have a more holistic view of a course or degree than coordinators of individual units, making communication and truly collaborative planning even more critical. As well, due to staffing time pressures, design and delivery of new curriculum is generally done quickly with no option for the designers to stop and reflect on the experience and outcomes. It is vital we take this unique opportunity to closely examine what QUT has and hasn’t achieved to be able to recommend a better way forward. This presentation will discuss these important issues and stumbling blocks, to provide a set of best practice guidelines for QUT and other institutions. The aim is to help improve collaboration within the university, as well as to maximize students’ ability to put information literacy skills into action. As our students embark on their own grand challenges, we must challenge ourselves to honestly assess our own work.

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

A data mining approach to improve the automated quality of data

This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

Inquiry pedagogy and the Australian Curriculum

This paper explores inquiry skills in the Australian Curriculum in relation to inquiry learning pedagogy. Inquiry skills in the Australian Curriculum are represented as questioning skills (i.e. posing and evaluating questions and hypotheses), information literacy (i.e. seeking, evaluating, selecting and using information), ICT literacy (i.e. fluency with computer hardware and software) and discipline specific skills (i.e. data gathering, mathematical measurement, data analysis and presentation of data). This paper provides an explanation of inquiry learning pedagogy that complements the Australian Curriculum inquiry skills.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

Modeling predictors of risky drug use behavior among male street laborers in urban Vietnam

Background The application of theoretical frameworks for modeling predictors of drug risk among male street laborers remains limited. The objective of this study was to test a modified version of the IMB (Information-Motivation-Behavioral Skills Model), which includes psychosocial stress, and compare this modified version with the original IMB model in terms of goodness-of-fit to predict risky drug use behavior among this population. Methods In a cross-sectional study, social mapping technique was conducted to recruit 450 male street laborers from 135 street venues across 13 districts of Hanoi city, Vietnam, for face-to-face interviews. Structural equation modeling (SEM) was used to analyze data from interviews. Results Overall measures of fit via SEM indicated that the original IMB model provided a better fit to the data than the modified version. Although the former model was able to predict a lesser variance than the latter (55% vs. 62%), it was of better fit. The findings suggest that men who are better informed and motivated for HIV prevention are more likely to report higher behavioral skills, which, in turn, are less likely to be engaged in risky drug use behavior. Conclusions This was the first application of the modified IMB model for drug use in men who were unskilled, unregistered laborers in urban settings. An AIDS prevention program for these men should not only distribute information and enhance motivations for HIV prevention, but consider interventions that could improve self-efficacy for preventing HIV infection. Future public health research and action may also consider broader factors such as structural social capital and social policy to alter the conditions that drive risky drug use among these men.

Exchanging data between Digital Human Modelling systems : a review of data formats

Digital human modeling (DHM) systems underwent significant development within the last years. They achieved constantly growing importance in the field of ergonomic workplace design, product development, product usability, ergonomic research, ergonomic education, audiovisual marketing and the entertainment industry. They help to design ergonomic products as well as healthy and safe socio-technical work systems. In the domain of scientific DHM systems, no industry specific standard interfaces are defined which could facilitate the exchange of 3D solid body data, anthropometric data or motion data. The focus of this article is to provide an overview of requirements for a reliable data exchange between different DHM systems in order to identify suitable file formats. Examples from the literature are discussed in detail. Methods: As a first step a literature review is conducted on existing studies and file formats for exchanging data between different DHM systems. The found file formats can be structured into different categories: static 3D solid body data exchange, anthropometric data exchange, motion data exchange and comprehensive data exchange. Each file format is discussed and advantages as well as disadvantages for the DHM context are pointed out. Case studies are furthermore presented, which show first approaches to exchange data between DHM systems. Lessons learnt are shortly summarized. Results: A selection of suitable file formats for data exchange between DHM systems is determined from the literature review.

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.

Implementing open licensing in government open data initiatives : a review of Australian government practice

As support grows for greater access to information and data held by governments, so does awareness of the need for appropriate policy, technical and legal frameworks to achieve the desired economic and societal outcomes. Since the late 2000s numerous international organizations, inter-governmental bodies and governments have issued open government data policies, which set out key principles underpinning access to, and the release and reuse of data. These policies reiterate the value of government data and establish the default position that it should be openly accessible to the public under transparent and non-discriminatory conditions, which are conducive to innovative reuse of the data. A key principle stated in open government data policies is that legal rights in government information must be exercised in a manner that is consistent with and supports the open accessibility and reusability of the data. In particular, where government information and data is protected by copyright, access should be provided under licensing terms which clearly permit its reuse and dissemination. This principle has been further developed in the policies issued by Australian Governments into a specific requirement that Government agencies are to apply the Creative Commons Attribution licence (CC BY) as the default licensing position when releasing government information and data. A wide-ranging survey of the practices of Australian Government agencies in managing their information and data, commissioned by the Office of the Australian Information Commissioner in 2012, provides valuable insights into progress towards the achievement of open government policy objectives and the adoption of open licensing practices. The survey results indicate that Australian Government agencies are embracing open access and a proactive disclosure culture and that open licensing under Creative Commons licences is increasingly prevalent. However, the finding that ‘[t]he default position of open access licensing is not clearly or robustly stated, nor properly reflected in the practice of Government agencies’ points to the need to further develop the policy framework and the principles governing information access and reuse, and to provide practical guidance tools on open licensing if the broadest range of government information and data is to be made available for innovative reuse.

The power of hands-on exercises in SCADA cyber security education

For decades Supervisory Control and Data Acquisition (SCADA) and Industrial Control Systems (ICS) have used computers to monitor and control physical processes in many critical industries, including electricity generation, gas pipelines, water distribution, waste treatment, communications and transportation. Increasingly these systems are interconnected with corporate networks via the Internet, making them vulnerable and exposed to the same risks as those experiencing cyber-attacks on a conventional network. Very often SCADA networks services are viewed as a specialty subject, more relevant to engineers than standard IT personnel. Educators from two Australian universities have recognised these cultural issues and highlighted the gap between specialists with SCADA systems engineering skills and the specialists in network security with IT background. This paper describes a learning approach designed to help students to bridge this gap, gain theoretical knowledge of SCADA systems' vulnerabilities to cyber-attacks via experiential learning and acquire practical skills through actively participating in hands-on exercises.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution