The Heavy Vehicle Study : a case-control study investigating risk factors for crash in long distance heavy vehicle drivers in Australia

Background Heavy vehicle transportation continues to grow internationally; yet crash rates are high, and the risk of injury and death extends to all road users. The work environment for the heavy vehicle driver poses many challenges; conditions such as scheduling and payment are proposed risk factors for crash, yet the precise measure of these needs quantifying. Other risk factors such as sleep disorders including obstructive sleep apnoea have been shown to increase crash risk in motor vehicle drivers however the risk of heavy vehicle crash from this and related health conditions needs detailed investigation. Methods and Design The proposed case control study will recruit 1034 long distance heavy vehicle drivers: 517 who have crashed and 517 who have not. All participants will be interviewed at length, regarding their driving and crash history, typical workloads, scheduling and payment, trip history over several days, sleep patterns, health, and substance use. All participants will have administered a nasal flow monitor for the detection of obstructive sleep apnoea. Discussion Significant attention has been paid to the enforcement of legislation aiming to deter problems such as excess loading, speeding and substance use; however, there is inconclusive evidence as to the direction and strength of associations of many other postulated risk factors for heavy vehicle crashes. The influence of factors such as remuneration and scheduling on crash risk is unclear; so too the association between sleep apnoea and the risk of heavy vehicle driver crash. Contributory factors such as sleep quality and quantity, body mass and health status will be investigated. Quantifying the measure of effect of these factors on the heavy vehicle driver will inform policy development that aims toward safer driving practices and reduction in heavy vehicle crash; protecting the lives of many on the road network.

Volunteer visibility : what and how Australian not-for-profit organisations report volunteer contributions

The enhanced social profile of not-for-profit organisations (NFPs) and the role of volunteers have resulted in calls for NFPs to be more accountable and to disclose information relating to such contributions. In this study we identify, locate and categorise the extent of disclosures made in relation to volunteer contributions. We find that disclosure was more prevalent on NFP websites compared to digital annual report disclosures. We find that more NFPs provided disclosure on the activities of their volunteers than other items pertaining to volunteers. The valuation of volunteer contributions was the least likely to be disclosed. The findings contribute to international debate over the inclusion of volunteer contributions in the assessment of a NFP’s accountability over its resources and ultimately the enhancement of its sustainability.

Robust mean super-resolution for less cooperative NIR iris recognition at a distance and on the move

Less cooperative iris identification systems at a distance and on the move often suffers from poor resolution. The lack of pixel resolution significantly degrades the iris recognition performance. Super-resolution has been considered to enhance resolution of iris images. This paper proposes a pixelwise super-resolution technique to reconstruct a high resolution iris image from a video sequence of an eye. A novel fusion approach is proposed to incorporate information details from multiple frames using robust mean. Experiments on the MBGC NIR portal database show the validity of the proposed approach in comparison with other resolution enhancement techniques.

Trans digital storytelling : everyday activism, mutable identity and the problem of visibility

Mainstream representations of trans people typically run the gamut from victim to mentally ill and are almost always articulated by non-trans voices. The era of user-generated digital content and participatory culture has heralded unprecedented opportunities for trans people who wish to speak their own stories in public spaces. Digital Storytelling, as an easy accessible autobiographic audio-visual form, offers scope to play with multi-dimensional and ambiguous representations of identity that contest mainstream assumptions of what it is to be ‘male’ or ‘female’. Also, unlike mainstream media forms, online and viral distribution of Digital Stories offer potential to reach a wide range of audiences, which is appealing to activist oriented storytellers who wish to confront social prejudices. However, with these newfound possibilities come concerns regarding visibility and privacy, especially for storytellers who are all too aware of the risks of being ‘out’ as trans. This paper explores these issues from the perspective of three trans storytellers, with reference to the Digital Stories they have created and shared online and on DVD. These examplars are contextualised with some popular and scholarly perspectives on trans representation, in particular embodied and performed identity. It is contended that trans Digital Stories, while appearing in some ways to be quite conventional, actually challenge common notions of gender identity in ways that are both radical and transformative.

Employer-based support for registered nurses undertaking postgraduate study via distance education

Previous literature has focused on the need for support of undergraduate nursing students during clinical placements. Little is known about the support provided by employers for registered nurses (RNs) who pursue further education. This study sought to identify and describe the types, levels and perceived need for support in the workplace for RNs as they undertake further postgraduate nursing study by distance education (DE).Using an exploratory descriptive design a self-report questionnaire was distributed to a convenient sample of 270 RNs working in one acute care public hospital in Tasmania, Australia.92 questionnaires (response rate 34%) were returned with 26 (28%) reporting being currently enrolled in further study by DE and a further 50 (54)% of RNs planning future study. Results revealed that 100% of participants with a Masters degree completed this by DE. There were differences between the support sought by RNs to that offered by employers, and 16 (34%) who had done or were currently doing DE study, received no support to undertake DE. There was an overwhelming desire by RNs for support; 87 (94%), with a majority believing some support should be mandatory 76 (83%).This study may encourage employers to introduce structured support systems that will actively assist nurses to pursue further study. © 2010.

Pseudoseeds : investigating long-distance, ocean seed dispersal with wireless sensors

Recent theoretical research has shown that ocean currents and wind interact to disperse seeds over long distances among isolated landmasses. Dispersal of seeds among isolated oceanic islands, by birds, oceans and man, is a well-known phenomenon, and many widespread island plants have traits that facilitate this process. Crucially, however, there have been no mechanistic vector-based models of long-distance dispersal for seeds among isolated oceanic islands based on empirical data. Here, we propose a plan to develop seed analogues, or pseudoseeds, fitted with wireless sensor technology that will enable high-fidelity tracking as they disperse across the ocean. The pseudoseeds will be precisely designed to mimic actual seed buoyancy and morphology enabling realistic and accurate, vector-based dispersal models of ocean seed dispersal over vast geographic scales.

Modelling the activation of words in human memory : the spreading activation, spooky-activation-at-a-distance and the entanglement models compared

Modelling how a word is activated in human memory is an important requirement for determining the probability of recall of a word in an extra-list cueing experiment. The spreading activation, spooky-action-at-a-distance and entanglement models have all been used to model the activation of a word. Recently a hypothesis was put forward that the mean activation levels of the respective models are as follows: Spreading � Entanglment � Spooking-action-at-a-distance This article investigates this hypothesis by means of a substantial empirical analysis of each model using the University of South Florida word association, rhyme and word norms.

Aggregate distance based clustering using Fibonacci Series -FIBCLUS

This paper proposes an innovative instance similarity based evaluation metric that reduces the search map for clustering to be performed. An aggregate global score is calculated for each instance using the novel idea of Fibonacci series. The use of Fibonacci numbers is able to separate the instances effectively and, in hence, the intra-cluster similarity is increased and the inter-cluster similarity is decreased during clustering. The proposed FIBCLUS algorithm is able to handle datasets with numerical, categorical and a mix of both types of attributes. Results obtained with FIBCLUS are compared with the results of existing algorithms such as k-means, x-means expected maximization and hierarchical algorithms that are widely used to cluster numeric, categorical and mix data types. Empirical analysis shows that FIBCLUS is able to produce better clustering solutions in terms of entropy, purity and F-score in comparison to the above described existing algorithms.

Multifractal characterisation and analysis of complex networks

Complex networks have been studied extensively due to their relevance to many real-world systems such as the world-wide web, the internet, biological and social systems. During the past two decades, studies of such networks in different fields have produced many significant results concerning their structures, topological properties, and dynamics. Three well-known properties of complex networks are scale-free degree distribution, small-world effect and self-similarity. The search for additional meaningful properties and the relationships among these properties is an active area of current research. This thesis investigates a newer aspect of complex networks, namely their multifractality, which is an extension of the concept of selfsimilarity. The first part of the thesis aims to confirm that the study of properties of complex networks can be expanded to a wider field including more complex weighted networks. Those real networks that have been shown to possess the self-similarity property in the existing literature are all unweighted networks. We use the proteinprotein interaction (PPI) networks as a key example to show that their weighted networks inherit the self-similarity from the original unweighted networks. Firstly, we confirm that the random sequential box-covering algorithm is an effective tool to compute the fractal dimension of complex networks. This is demonstrated on the Homo sapiens and E. coli PPI networks as well as their skeletons. Our results verify that the fractal dimension of the skeleton is smaller than that of the original network due to the shortest distance between nodes is larger in the skeleton, hence for a fixed box-size more boxes will be needed to cover the skeleton. Then we adopt the iterative scoring method to generate weighted PPI networks of five species, namely Homo sapiens, E. coli, yeast, C. elegans and Arabidopsis Thaliana. By using the random sequential box-covering algorithm, we calculate the fractal dimensions for both the original unweighted PPI networks and the generated weighted networks. The results show that self-similarity is still present in generated weighted PPI networks. This implication will be useful for our treatment of the networks in the third part of the thesis. The second part of the thesis aims to explore the multifractal behavior of different complex networks. Fractals such as the Cantor set, the Koch curve and the Sierspinski gasket are homogeneous since these fractals consist of a geometrical figure which repeats on an ever-reduced scale. Fractal analysis is a useful method for their study. However, real-world fractals are not homogeneous; there is rarely an identical motif repeated on all scales. Their singularity may vary on different subsets; implying that these objects are multifractal. Multifractal analysis is a useful way to systematically characterize the spatial heterogeneity of both theoretical and experimental fractal patterns. However, the tools for multifractal analysis of objects in Euclidean space are not suitable for complex networks. In this thesis, we propose a new box covering algorithm for multifractal analysis of complex networks. This algorithm is demonstrated in the computation of the generalized fractal dimensions of some theoretical networks, namely scale-free networks, small-world networks, random networks, and a kind of real networks, namely PPI networks of different species. Our main finding is the existence of multifractality in scale-free networks and PPI networks, while the multifractal behaviour is not confirmed for small-world networks and random networks. As another application, we generate gene interactions networks for patients and healthy people using the correlation coefficients between microarrays of different genes. Our results confirm the existence of multifractality in gene interactions networks. This multifractal analysis then provides a potentially useful tool for gene clustering and identification. The third part of the thesis aims to investigate the topological properties of networks constructed from time series. Characterizing complicated dynamics from time series is a fundamental problem of continuing interest in a wide variety of fields. Recent works indicate that complex network theory can be a powerful tool to analyse time series. Many existing methods for transforming time series into complex networks share a common feature: they define the connectivity of a complex network by the mutual proximity of different parts (e.g., individual states, state vectors, or cycles) of a single trajectory. In this thesis, we propose a new method to construct networks of time series: we define nodes by vectors of a certain length in the time series, and weight of edges between any two nodes by the Euclidean distance between the corresponding two vectors. We apply this method to build networks for fractional Brownian motions, whose long-range dependence is characterised by their Hurst exponent. We verify the validity of this method by showing that time series with stronger correlation, hence larger Hurst exponent, tend to have smaller fractal dimension, hence smoother sample paths. We then construct networks via the technique of horizontal visibility graph (HVG), which has been widely used recently. We confirm a known linear relationship between the Hurst exponent of fractional Brownian motion and the fractal dimension of the corresponding HVG network. In the first application, we apply our newly developed box-covering algorithm to calculate the generalized fractal dimensions of the HVG networks of fractional Brownian motions as well as those for binomial cascades and five bacterial genomes. The results confirm the monoscaling of fractional Brownian motion and the multifractality of the rest. As an additional application, we discuss the resilience of networks constructed from time series via two different approaches: visibility graph and horizontal visibility graph. Our finding is that the degree distribution of VG networks of fractional Brownian motions is scale-free (i.e., having a power law) meaning that one needs to destroy a large percentage of nodes before the network collapses into isolated parts; while for HVG networks of fractional Brownian motions, the degree distribution has exponential tails, implying that HVG networks would not survive the same kind of attack.

Three carrier ambiguity resolution : distance-independent performance demonstrated using semi-generated triple frequency GPS signals

In spite of significant research in the development of efficient algorithms for three carrier ambiguity resolution, full performance potential of the additional frequency signals cannot be demonstrated effectively without actual triple frequency data. In addition, all the proposed algorithms showed their difficulties in reliable resolution of the medium-lane and narrow-lane ambiguities in different long-range scenarios. In this contribution, we will investigate the effects of various distance-dependent biases, identifying the tropospheric delay to be the key limitation for long-range three carrier ambiguity resolution. In order to achieve reliable ambiguity resolution in regional networks with the inter-station distances of hundreds of kilometers, a new geometry-free and ionosphere-free model is proposed to fix the integer ambiguities of the medium-lane or narrow-lane observables over just several minutes without distance constraint. Finally, the semi-simulation method is introduced to generate the third frequency signals from dual-frequency GPS data and experimentally demonstrate the research findings of this paper.

Perceptions of visibility and conspicuity of biomotion clothing configurations for road workers at road work sites

Aims: This study determined whether the visibility benefits of positioning retroreflective strips in biological motion configurations were evident at real world road worker sites. Methods: 20 visually normal drivers (M=40.3 years) participated in this study that was conducted at two road work sites (one suburban and one freeway) on two separate nights. At each site, four road workers walked in place wearing one of four different clothing options: a) standard road worker night vest, b) standard night vest plus retroreflective strips on thighs, c) standard night vest plus retroreflective strips on ankles and knees, d) standard night vest plus retroreflective strips on eight moveable joints (full biomotion). Participants seated in stationary vehicles at three different distances (80m, 160m, 240m) rated the relative conspicuity of the four road workers using a series of a standardized visibility and ranking scales. Results: Adding retroreflective strips in the full biomotion configuration to the standard night vest significantly (p<0.001) enhanced perceptions of road worker visibility compared to the standard vest alone, or in combination with thigh retroreflective markings. These visibility benefits were evident at all distances and at both sites. Retroreflective markings at the ankles and knees also provided visibility benefits compared to the standard vest, however, the full biomotion configuration was significantly better than all of the other configurations. Conclusions: These data provide the first evidence that the benefits of biomotion retroreflective markings that have been previously demonstrated under laboratory and closed- and open-road conditions are also evident at real work sites.