Modelling the intention to adopt cloud computing services : a transaction cost theory perspective

This paper uses transaction cost theory to study cloud computing adoption. A model is developed and tested with data from an Australian survey. According to the results, perceived vendor opportunism and perceived legislative uncertainty around cloud computing were significantly associated with perceived cloud computing security risk. There was also a significant negative relationship between perceived cloud computing security risk and the intention to adopt cloud services. This study also reports on adoption rates of cloud computing in terms of applications, as well as the types of services used.

Decision support for the efficient annotation of bioacoustic events

Acoustic sensors allow scientists to scale environmental monitoring over large spatiotemporal scales. The faunal vocalisations captured by these sensors can answer ecological questions, however, identifying these vocalisations within recorded audio is difficult: automatic recognition is currently intractable and manual recognition is slow and error prone. In this paper, a semi-automated approach to call recognition is presented. An automated decision support tool is tested that assists users in the manual annotation process. The respective strengths of human and computer analysis are used to complement one another. The tool recommends the species of an unknown vocalisation and thereby minimises the need for the memorization of a large corpus of vocalisations. In the case of a folksonomic tagging system, recommending species tags also minimises the proliferation of redundant tag categories. We describe two algorithms: (1) a “naïve” decision support tool (16%–64% sensitivity) with efficiency of O(n) but which becomes unscalable as more data is added and (2) a scalable alternative with 48% sensitivity and an efficiency ofO(log n). The improved algorithm was also tested in a HTML-based annotation prototype. The result of this work is a decision support tool for annotating faunal acoustic events that may be utilised by other bioacoustics projects.

Practical analysis of big acoustic sensor data for environmental monitoring

Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem; the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.

Assessing driver acceptance of intelligent transport systems in the context of railway level crossings

Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. Such systems, however, will only exert an influence on driving behaviour if they are accepted by the driver. This study aimed at assessing driver acceptance of different ITS interventions designed to enhance driver behaviour at railway crossings. Fifty eight participants, divided into three groups, took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver acceptance of each ITS intervention was assessed in a questionnaire guided by the Technology Acceptance Model and the Theory of Planned Behaviour. Overall, results indicated that the strongest intentions to use the ITS devices belonged to participants exposed to the road-based valet system at passive crossings. The utility of both models in explaining drivers’ intention to use the systems is discussed, with results showing greater support for the Theory of Planned Behaviour. Directions for future studies, along with strategies that target attitudes and subjective norms to increase drivers’ behavioural intentions, are also discussed.

Napping, development and health from 0 to 5 years : a systematic review

Background Duration and quality of sleep affect child development and health. Encouragement of napping in preschool children has been suggested as a health-promoting strategy. Objectives The aim of this study is to assess evidence regarding the effects of napping on measures of child development and health. Design This study is a systematic review of published, original research articles of any design. Subjects Children aged 0–5 years. Method Electronic database search was performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and assessment of research quality was carried out following a Grading of Recommendations, Assessment, Development and Evaluations (GRADE) protocol. Results Twenty-six articles met inclusion criteria. These were of heterogeneous quality; all had observational designs (GRADE-low). Development and health outcomes included salivary cortisol, night sleep, cognition, behaviour, obesity and accidents. The findings regarding cognition, behaviour and health impacts were inconsistent, probably because of variation in age and habitual napping status of the samples. The most consistent finding was an association between napping and later onset, shorter duration and poorer quality of night sleep, with evidence strongest beyond the age of 2 years. Limitations Studies were not randomised. Most did not obtain data on the children's habitual napping status or the context of napping. Many were reliant on parent report rather than direct observation or physiological measurement of sleep behaviour. Conclusions The evidence indicates that beyond the age of 2 years napping is associated with later night sleep onset and both reduced sleep quality and duration. The evidence regarding behaviour, health and cognition is less certain. There is a need for more systematic studies that use stronger designs. In preschool children presenting with sleep problems clinicians should investigate napping patterns.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

MITIE C-Arm - Advanced innovation in education

Aim: In 2013 QUT introduced the Medical Imaging Training Immersive Environment (MITIE) as a virtual reality (VR) platform that allowed students to practice general radiography. The system software has been expanded to now include C-Arm. The aim of this project was to investigate the use of this technology in the pedagogy of undergraduate medical imaging students who have limited to no experience in the use of the C-Arm clinically. Method: The Medical Imaging Training Immersive Environment (MITIE) application provides students with realistic and fully interactive 3D models of C-Arm equipment. As with VR initiatives in other health disciplines (1–2) the software mimics clinical practice as much as possible and uses 3D technology to enhance 3D spatial awareness and realism. The application allows students to set up and expose a virtual patient in a 3D environment as well as creating the resultant “image” for comparison with a gold standard. Automated feedback highlights ways for the student to improve their patient positioning, equipment setup or exposure factors. The students' equipment knowledge was tested using an on line assessment quiz and surveys provided information on the students' pre-clinical confidence scale, with post-clinical data comparisons. Ethical approval for the project was provided by the university ethics panel. Results: This study is currently under way and this paper will present analysis of initial student feedback relating to the perceived value of the application for confidence in a high risk environment (i.e. operating theatre) and related clinical skills development. Further in-depth evaluation is ongoing with full results to be presented. Conclusion: MITIE C-Arm has a development role to play in the pre-clinical skills training for Medical Radiation Science students. It will augment their theoretical understanding prior to their clinical experience. References 1. Bridge P, Appleyard R, Ward J, Phillips R, Beavis A. The development and evaluation of a virtual radiotherapy treatment machine using an immersive visualisation environment. Computers and Education 2007; 49(2): 481–494. 2. Gunn T, Berry C, Bridge P et al. 3D Virtual Radiography: Development and Initial Feedback. Paper presented at the 10th Annual Scientific Meeting of Medical Imaging and Radiation Therapy, March 2013 Hobart, Tasmania.

The on-road experiences and awareness of sleepiness in a sample of Australian highway drivers: A roadside driver sleepiness study

Objective Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers’ on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness. Methods Participants were a random selection of 92 drivers travelling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 minutes prior to being stopped by police. Results Participants rating of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers’ level of sleep debt. Conclusions The results suggest the participants had moderate experience of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety – increased education regarding the dangers of sleepy driving seems warranted.

A three dimensional virtual medical imaging computed tomography suite: Innovation in education

Aims: The Medical Imaging Training Immersive Environment(MITIE) Computed Tomography(CT) system is an innovative virtual reality (VR) platform that allows students to practice a range of CT techniques. The aim of this pilot study was to harvest user feedback about the educational value of teh application and inform future pedagogical development. This presentation explores the use of this technology for skills training. Background: MITIE CT is a 3D VR environment that allows students to position a patient,and set CT technical parameters including IV contrast dose and dose rate. As with VR initiatives in other health disciplines the software mimics clinical practice as much as possible and uses 3D technology to enhance immersion and realism. The software is new and was developed by the Medical Imaging Course Team at a provider University with funding from a Health Workforce Australia 'Simulated Learning Environments' grant Methods: Current third year medical imaging students were provided with additional 1 hour MITIE laboratory tutorials and studnet feedback was collated with regard to educational value and performance. Ethical approval for the project was provided by the university ethics panel Results: This presentation provides qualitative analysis of student perceptions relating to satisfaction, usability and educational value. Students reported high levels of satisfaction and both feedback and assessment results confirmed the application's significance as a pre-clinical tool. There was a clear emerging theme that MITIE could be a useful learning tool that students could access to consolidate their clinical learning, either on campus or during their clinical placement. Conclusion: Student feedback indicates that MITIE CT has a valuable role to play in the clinial skills training for medical imaging students both in the academic and clinical environment. Future work will establish a framework for an appropriate supprting pedagogy that can cross the boundary between the two environments

Do-Rank: DCG optimization for learning-to-rank in tag-based item recommendation systems

Discounted Cumulative Gain (DCG) is a well-known ranking evaluation measure for models built with multiple relevance graded data. By handling tagging data used in recommendation systems as an ordinal relevance set of {negative,null,positive}, we propose to build a DCG based recommendation model. We present an efficient and novel learning-to-rank method by optimizing DCG for a recommendation model using the tagging data interpretation scheme. Evaluating the proposed method on real-world datasets, we demonstrate that the method is scalable and outperforms the benchmarking methods by generating a quality top-N item recommendation list.

Numeracy and statistical reasoning on entering university

The relationship between mathematics and statistical reasoning frequently receives comment (Vere-Jones 1995, Moore 1997); however most of the research into the area tends to focus on mathematics anxiety. Gnaldi (2003) showed that in a statistics course for psychologists, the statistical understanding of students at the end of the course depended on students’ basic numeracy, rather than the number or level of previous mathematics courses the student had undertaken. As part of a study into the development of statistical thinking at the interface between secondary and tertiary education, students enrolled in an introductory data analysis subject were assessed regarding their statistical reasoning, basic numeracy skills, mathematics background and attitudes towards statistics. This work reports on some key relationships between these factors and in particular the importance of numeracy to statistical reasoning.

Driving simulator evaluation of the failure of an audio in-vehicle warning for railway level crossings

It is impracticable to upgrade the 18,900 Australian passive crossings as such crossings are often located in remote areas, where power is lacking and with low road and rail traffic. The rail industry is interested in developing innovative in-vehicle technology interventions to warn motorists of approaching trains directly in their vehicles. The objective of this study was therefore to evaluate the benefits of the introduction of such technology. We evaluated the changes in driver performance once the technology is enabled and functioning correctly, as well as the effects of an unsafe failure of the technology? We conducted a driving simulator study where participants (N=15) were familiarised with an in-vehicle audio warning for an extended period. After being familiarised with the system, the technology started failing, and we tested the reaction of drivers with a train approaching. This study has shown that with the traditional passive crossings with RX2 signage, the majority of drivers complied (70%) and looked for trains on both sides of the rail track. With the introduction of the in-vehicle audio message, drivers did not approach crossings faster, did not reduce their safety margins and did not reduce their gaze towards the rail tracks. However participants’ compliance at the stop sign decreased by 16.5% with the technology installed in the vehicle. The effect of the failure of the in-vehicle audio warning technology showed that most participants did not experience difficulties in detecting the approaching train even though they did not receive any warning message. This showed that participants were still actively looking for trains with the system in their vehicle. However, two participants did not stop and one decided to beat the train when they did not receive the audio message, suggesting potential human factors issues to be considered with such technology.

Self-reported circumstances and consequences of driving while sleepy

Driver surveys are indispensable sources of information when estimating the role of sleepiness in crash causation. The purpose of the study was to (1) identify the prevalence of driving while sleepy among Finnish drivers, (2) determine the circumstances of such instances, and (3) identify risk factors and risk groups. Survey data were collected from a representative sample of active Finnish drivers (N = 1121). One-fifth of the drivers (19.5%) reported having fallen asleep at the wheel during their driving career, with 15.9% reporting having been close to falling asleep or having difficulty staying awake when driving during the previous twelve months. Epworth Sleepiness Scale scores were found to be associated with both types of sleepiness-related driving instances, while sleep quality was associated only with the latter. Compared to women, men more often reported falling asleep at the wheel; the differences were somewhat smaller with respect to fighting sleep while driving during the previous twelve months. The reported discrepancy in sleepiness-related instances (high prevalence of fighting sleep while driving during the previous twelve months and lower proportion of actually falling asleep) identifies young men (⩽25 years) as one of the main target groups for safety campaigns. Approximately three-quarters of drivers who had fallen asleep while driving reported taking action against falling asleep before it actually happened. Furthermore, almost all drivers who had fallen asleep while driving offered at least one logical reason that could have contributed to their falling asleep. These data indicate some degree of awareness about driving while sleepy and of the potential pre-trip factors that could lead to sleepiness while driving, and supports the notion that falling asleep at the wheel does not come as a (complete) surprise to the driver.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.