Experimental comparison of odometry approaches

Odometry is an important input to robot navigation systems, and we are interested in the performance of vision-only techniques. In this paper we experimentally evaluate and compare the performance of wheel odometry, monocular feature-based visual odometry, monocular patch-based visual odometry, and a technique that fuses wheel odometry and visual odometry, on a mobile robot operating in a typical indoor environment.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

Behavioural changes add validity to the construct of posttraumatic growth

The research aimed to identify positive behavioural changes that people may make as a result of negotiating the aftermath of a traumatic experience, thereby extending the current cognitive model of posttraumatic growth (PTG). It was hypothesised that significant others would corroborate survivor’s cognitive and behavioural reports of PTG. The sample comprised 176 participants; 88 trauma survivors and 88 significant others. University students accounted for 64% of the sample and 36% were from the broader community. Approximately one third were male. All participants completed the Posttraumatic Growth Inventory [PTGI] and open ended questions regarding behavioural changes. PTGI scores in the survivor sample were corroborated by the significant others with only the Appreciation of Life factor of the PTGI differing between the two groups (e.g., total PTGI scores between groups explained 33.64% of variance). Nearly all of the survivors also reported positive changes in their behaviour and these changes were also corroborated by the significant others. Results provide validation of the posttraumatic growth construct and the PTGI as an instrument of measurement. Findings may also influence therapeutic practice for example, the potential usefulness of corroborating others.

Not all older adults have insight into their driving abilities : evidence from an on-road assessment and implications for policy

Purpose To compare self-reported driving ability with objective measures of on-road driving performance in a large cohort of older drivers. Methods 270 community-living adults aged 70 – 88 years recruited via the electoral roll completed a standardized assessment of on-road driving performance and questionnaires determining perceptions of their own driving ability, confidence and driving difficulties. Retrospective self-reported crash data over the previous five years were recorded. Results Participants reported difficulty with only selected driving situations, including driving into the sun, in unfamiliar areas, in wet conditions, and at night or dusk. The majority of participants rated their own driving as good to excellent. Of the 47 (17%) of drivers who were rated as potentially unsafe to drive, 66% rated their own driving as good to excellent. Drivers who made critical errors, where the driving instructor had to take control of the vehicle, had no lower self-rating of driving ability then the rest of the group. The discrepancy in self-perceptions of driving and participants’ safety rating on the on-road assessment was significantly associated with self-reported retrospective crash rates, where those drivers who displayed greater overconfidence in their own driving were significantly more likely to report a crash. Conclusions This study demonstrates that older drivers with the greatest mismatch between actual and self-rated driving ability pose the greatest risk to road safety. Therefore licensing authorities should not assume that when older individuals’ driving abilities begin to decline they will necessarily be aware of these changes and adopt appropriate compensatory driving behaviours; rather, it is essential that evidence-based assessments are adopted.

Educational technology in medical imaging education

Purpose The emergence of digital technologies has created enthusiasm for their application to student learning. An evolving issue in medical imaging is how these technologies might be implemented within programs. Method A review of the literature was performed to explore applications and issues of educational technology in medical imaging Results There are a range of applications for educational technology within medical imaging education however limitations do exist. Learners must be supported by the development of skills to utilize education technologies. The digital picture archival and communication environment presents an ideal opportunity to enhance student learning through interaction and engagement with images. Implementation of education technologies to support student placement activities is an area for future development provided equity of access is addressed. Conclusion Education technologies have specific application to medical imaging education as part of a blended curriculum.

Driver sleepiness self-regulation : physiological and subjective evidence

Introduction: Sleepiness contributes to a substantial proportion of fatal and severe road crashes. Efforts to reduce the incidence of sleep-related crashes have largely focussed on driver education to promote self-regulation of driving behaviour. However, effective self-regulation requires accurate self-perception of sleepiness. The aim of this study was to assess capacity to accurately identify sleepiness, and self-regulate driving cessation, during a validated driving simulator task. Methods: Participants comprised 26 young adult drivers (20-28 years) who had open licenses. No other exclusion criteria where used. Participants were partially sleep deprived (05:00 wake up) and completed a laboratory-based hazard perception driving simulation, counterbalanced to either at mid-morning or mid-afternoon. Established physiological measures (i.e., EEG, EOG) and subjective measures (Karolinska Sleepiness Scale), previously found sensitive to changes in sleepiness levels, were utilised. Participants were instructed to ‘drive’ on the simulator until they believed that sleepiness had impaired their ability to drive safely. They were then offered a nap opportunity. Results: The mean duration of the drive before cessation was 36.1 minutes (±17.7 minutes). Subjective sleepiness increased significantly from the beginning (KSS=6.6±0.7) to the end (KSS=8.2±0.5) of the driving period. No significant differences were found for EEG spectral power measures of sleepiness (i.e., theta or alpha spectral power) from the start of the driving task to the point of cessation of driving. During the nap opportunity, 88% of the participants (23/26) were able to reach sleep onset with an average latency of 9.9 minutes (±7.5 minutes). The average nap duration was 15.1 minutes (±8.1 minutes). Sleep architecture during the nap was predominately comprised of Stages I and II (combined 92%). Discussion: Participants reported high levels of sleepiness during daytime driving after very moderate sleep restriction. They were able to report increasing sleepiness during the test period despite no observed change in standard physiological indices of sleepiness. This increased subjective sleepiness had behavioural validity as the participants had high ‘napability’ at the point of driving cessation, with most achieving some degree of subsequent sleep. This study suggests that the nature of a safety instruction (i.e. how to view sleepiness) can be a determinant of driver behaviour.

A framework for cost-aware process management : generation of accurate and timely management accounting cost reports

Organisations are constantly seeking efficiency improvements for their business processes in terms of time and cost. Management accounting enables reporting of detailed cost of operations for decision making purpose, although significant effort is required to gather accurate operational data. Business process management is concerned with systematically documenting, managing, automating, and optimising processes. Process mining gives valuable insight into processes through analysis of events recorded by an IT system in the form of an event log with the focus on efficient utilisation of time and resources, although its primary focus is not on cost implications. In this paper, we propose a framework to support management accounting decisions on cost control by automatically incorporating cost data with historical data from event logs for monitoring, predicting and reporting process-related costs. We also illustrate how accurate, relevant and timely management accounting style cost reports can be produced on demand by extending open-source process mining framework ProM.