486 resultados para likelihood to publication
em Queensland University of Technology - ePrints Archive
Resumo:
The ultimate goal of an authorisation system is to allocate each user the level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting because on one hand employees need enough access to perform their tasks, while on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally through carelessness, losing the information or being socially engineered to give access to an adversary. With the goal of developing a more dynamic authorisation model, we have adopted a game theoretic framework to reason about the factors that may affect users’ likelihood to misuse a permission at the time of an access decision. Game theory provides a useful but previously ignored perspective in authorisation theory: the notion of the user as a self-interested player who selects among a range of possible actions depending on their pay-offs.
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One of the key trends that we currently witness not only in academic circles but also in industry - all throughout Australia at least – is that “Innovation” is becoming an important driver for business projects, for change agendas – and in turn, for Business Process Management initiatives.
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The aim of the current study was to examine the associations between a number of individual factors (demographic factors (age and gender), personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement) and how they influence the self-reported likelihood of drink driving. The second aim of this study was to examine the potential of attitudes mediating the relationship between risk-taking and self-reported likelihood of drink driving. In total, 293 Queensland drivers volunteered to participate in an online survey that assessed their self-reported likelihood to drink drive in the next month, demographics, traffic-related demographics, personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement. An ordered logistic regression analysis was utilised to evaluate the first aim of the study; at the first step the demographic variables were entered; at step two the personality and risk-taking were entered; at the third step, the attitudes and perceptions of legitimacy variables were entered. Being a younger driver and having a high risk-taking propensity were related to self-reported likelihood of drink driving. However, when the attitudes variable was entered, these individual factors were no longer significant; with attitudes being the most important predictor of self-reported drink driving likelihood. A significant mediation model was found with the second aim of the study, such that attitudes mediated the relationship between risk-taking and self-reported likelihood of drink driving. Considerable effort and resources are utilised by traffic authorities to reducing drink driving on the Australian road network. Notwithstanding these efforts, some participants still had some positive attitudes towards drink driving and reported that they were likely to drink drive in the future. These findings suggest that more work is needed to address attitudes regarding the dangerousness of drink driving.
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Most of the existing algorithms for approximate Bayesian computation (ABC) assume that it is feasible to simulate pseudo-data from the model at each iteration. However, the computational cost of these simulations can be prohibitive for high dimensional data. An important example is the Potts model, which is commonly used in image analysis. Images encountered in real world applications can have millions of pixels, therefore scalability is a major concern. We apply ABC with a synthetic likelihood to the hidden Potts model with additive Gaussian noise. Using a pre-processing step, we fit a binding function to model the relationship between the model parameters and the synthetic likelihood parameters. Our numerical experiments demonstrate that the precomputed binding function dramatically improves the scalability of ABC, reducing the average runtime required for model fitting from 71 hours to only 7 minutes. We also illustrate the method by estimating the smoothing parameter for remotely sensed satellite imagery. Without precomputation, Bayesian inference is impractical for datasets of that scale.
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This paper reports on the outcomes of a two year ALTC Competitive Research and Development Project that aimed to "Develop Strategies at the Pre-Service Level to Address Critical Teacher Attraction and Retention Issues in Australian Rural, Regional and Remote Schools". As well as developing a ‘training framework’ and teaching guides to increase the capacity and credibility of four universities to prepare educators who might venture out of the metropolitan area to teach, data were gathered from pre-service and graduate teachers to analyse regional resilience. It was found that there was a strong likelihood to participate in a regional practicum and stay in a non-metropolitan community once they graduated from university if they had a positive attitude to regional Western Australia either through a family connection or previous experience. Recommendations from this study emphasise the importance of having pre-service students participate in positive regional experiences early in their university study.
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There has been considerable interest over the years within the IS research community into how to shape articles for successful publication. Little effort has been made, however, to examine the reviewing criteria that make a difference to publication. We argue that, to provide better guidance to authors, more solid evidence is needed into the factors that contribute to acceptance decisions. This paper examines empirically the outcomes of the reviewing processes of three well-known IS conferences held in 2007. Our analyses reveal four major findings. First, the evaluation criteria that influence the acceptance/rejection decision vary by conference. Second, those differences can be explained in terms of the maturity and breadth of the specific conference of interest. Third, while objective review criteria influence acceptance/rejection decisions, subjective assessment on the part of the program committees may also play a substantial role. Fourth, while high scores on objective criteria are essential for acceptance, they do not guarantee acceptance. On the other hand, low scores on any criterion are likely to result in rejection.
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Collaboration between nurses in clinical and educational settings has been advocated as a means of ensuring nursing research is both practice oriented and scientifically valid. This paper describes a model, jointly developed by colleagues from the Nursing Departments of Alfred Hospital and La Trobe University, to foster collaborative research and steer research projects generated by clinical nurses from conceptualisation to publication.
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This article focuses on the relationship between private insurance status and dental service utilisation in Australia using data between 1995 and 2001. This article employs joint maximum likelihood to estimate models of time since last dental visit treating private ancillary health insurance (PAHI) as endogenous. The sensitivity of results to the choice between two different but related types of instrumental variables is examined. We find robust evidence in both 1995 and 2001 that individuals with a PAHI policy make significantly more frequent dental consultations relative to those without such coverage. A comparison of the 1995 and 2001 results, however, suggests that there has been an increasing role of PAHI in terms of the frequency of dental consultations over time. This seems intuitive given the trends in the price of unsubsidised private dental consultations. In terms of policy, our results suggest that while government measures to increase private health insurance coverage in Australia has been successful to a significant degree, it may have come at some cost in terms of socio-economic inequality as the privately insured are provided much better access to care and financial protection.
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Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models
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Social media is playing an ever-increasing role in both viewers engagement with television and in the television industries evaluation of programming, in Australia – which is the focus of our study - and beyond. Twitter hashtags and viewer comments are increasingly incorporated into broadcasts, while Facebook fan pages provide a means of marketing upcoming shows and television personalities directly into the social media feed of millions of users. Additionally, bespoke applications such as FanGo and ZeeBox, which interact with the mainstream social networks, are increasingly being utilized by broadcasters for interactive elements of programming (c.f. Harrington, Highfield and Bruns, 2012). However, both the academic and industry study of these platforms has focused on the measure of content during the specific broadcast of the show, or a period surrounding it (e.g. 3 hours before until 3 am the next day, in the case of 2013 Nielsen SocialGuide reports). In this paper, we argue that this focus ignores a significant period for both television producers and advertisers; the lead-up to the program. If, as we argue elsewhere (Bruns, Woodford, Highfield & Prowd, forthcoming), users are persuaded to engage with content both by advertising of the Twitter hash-tag or Facebook page and by observing their network connections engaging with such content, the period before and between shows may have a significant impact on a viewers likelihood to watch a show. The significance of this period for broadcasters is clearly highlighted by the efforts they afford to advertising forthcoming shows through several channels, including television and social media, but also more widely. Biltereyst (2004, p.123) has argued that reality television generates controversy to receive media attention, and our previous small-scale work on reality shows during 2013 and 2014 supports the theory that promoting controversial behavior is likely to lead to increased viewing (Woodford & Prowd, 2014a). It remains unclear, however, to what extent this applies to other television genres. Similarly, while networks use of social media has been increasing, best practices remain unclear. Thus, by applying our telemetrics, that is social media metrics for television based on sabermetric approaches (Woodford, Prowd & Bruns, forthcoming; c.f. Woodford & Prowd, 2014b), to the period between shows, we are able to better understand the period when key viewing decisions may be made, to establish the significance of observing discussions within your network during the period between shows, and identify best practice examples of promoting a show using social media.
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Purpose:Over the past decade, corneal nerve morphology and corneal sensation threshold have been explored as potential surrogate markers for the evaluation of diabetic neuropathy. We present the baseline findings of a Longitudinal Assessment of Neuropathy in Diabetes using novel ophthalmic Markers (LANDMark). Methods:The LANDMark Study is a 5-year, two-site, natural history (observational) study of individuals with Type 1 diabetes stratified into those with (T1W) and without (T1WO) neuropathy according to the Toronto criteria, and control subjects. All study participants undergo detailed annual assessment of neuropathy including corneal nerve parameters measured using corneal confocal microscopy and corneal sensitivity measured using non-contact corneal esthesiometry. Results:396 eligible individuals (208 in Brisbane and 188 in Manchester) were assessed: 76 T1W, 166 T1WO and 154 controls. Corneal sensation threshold (mbars) was significantly higher in T1W (1.0 ± 1.1) than T1WO (0.7 ± 0.7) and controls (0.6 ± 0.4) (P=0.002); post-hoc analysis (PHA) revealed no difference between T1WO and controls (Tukey HSD, P=0.502). Corneal nerve fiber length (mm/mm2) (CNFL) was lower in T1W (13.8 ± 6.4) than T1WO (19.1 ± 5.8) and controls (23.2 ± 6.3) (P<0.001); PHA revealed CNFL to be lower in T1W than T1WO, and lower in both of these groups than controls (P<0.001). Corneal nerve branch density (branches/mm2) (CNBD) was significantly lower in T1W (40 ± 32) than T1WO (62 ± 37) and controls (83 ± 46) (P<0.001); PHA showed CNBD was lower in T1W than T1WO, and lower in both groups than controls (P<0.001). Alcohol and cigarette consumption did not differ between groups, although age, BMI, BP, waist circumference, HbA1c, albumin-creatinine ratio, and cholesterol were slightly greater in T1W than T1WO (p<0.05). Some site differences were observed. Conclusions:The LANDMark baseline findings confirm that corneal sensitivity and corneal nerve morphometry can detect differences in neuropathy status in individuals with Type 1 diabetes and healthy controls. Corneal nerve morphology is significantly abnormal even in diabetic patients ‘without neuropathy’ compared to control participants. Results of the longitudinal trial will assess the capability of these tests for monitoring change in these parameters over time as potential surrogate markers for neuropathy.
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Purpose Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic technique, which has been shown to diagnose and stratify the severity of diabetic neuropathy. Current morphometric techniques assess individual static images of the subbasal nerve plexus; this work explores the potential for non-invasive assessment of the wide-field morphology and dynamic changes of this plexus in vivo. Methods In this pilot study, laser scanning CCM was used to acquire maps (using a dynamic fixation target and semi-automated tiling software) of the central corneal sub-basal nerve plexus in 4 diabetic patients with and 6 without neuropathy and in 2 control subjects. Nerve migration was measured in an additional 7 diabetic patients with neuropathy, 4 without neuropathy and in 2 control subjects by repeating a modified version of the mapping procedure within 2-8 weeks, thus facilitating re-identification of distinctive nerve landmarks in the 2 montages. The rate of nerve movement was determined from these data and normalised to a weekly rate (µm/week), using customised software. Results Wide-field corneal nerve fibre length correlated significantly with the Neuropathy Disability Score (r = -0.58, p < 0.05), vibration perception (r = -0.66, p < 0.05) and peroneal conduction velocity (r = 0.67, p < 0.05). Central corneal nerve fibre length did not correlate with any of these measures of neuropathy (p > 0.05 for all). The rate of corneal nerve migration was 14.3 ± 1.1 µm/week in diabetic patients with neuropathy, 19.7 ± 13.3µm/week in diabetic patients without neuropathy, and 24.4 ± 9.8µm/week in control subjects; however, these differences were not significantly different (p = 0.543). Conclusions Our data demonstrate that it is possible to capture wide-field images of the corneal nerve plexus, and to quantify the rate of corneal nerve migration by repeating this procedure over a number of weeks. Further studies on larger sample sizes are required to determine the utility of this approach for the diagnosis and monitoring of diabetic neuropathy.
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Purpose : To investigate the application of retinal nerve fibre layer (RNFL) thickness as a marker for severity of diabetic peripheral neuropathy (DPN) in people with Type 2 diabetes. Methods : This was a cross-sectional study whereby 61 participants (mean age 61 [41-75 years], mean duration of diabetes 14 [1-40 years], 70% male) with Type 2 diabetes and DPN underwent optical coherence tomography (OCT) scans. Global and 4 quadrant (TSNI) RNFL thicknesses were measured at 3.45mm around the optic nerve head of one eye. Neuropathy disability score (NDS) was used to assess the severity of DPN on a 0 to 10 scale. Participants were divided into three age-matched groups representing mild (NDS=3-5), moderate (NDS=6-8) and severe (NDS=9-10) neuropathy. Two regression models were fitted for statistical analysis: 1) NDS scores as co-variate for global and quadrant RNFL thicknesses, 2) NDS groups as a factor for global RNFL thickness only. Results : Mean (SD) RNFL thickness (µm) was 103(9) for mild neuropathy (n=34), 101(10) for moderate neuropathy (n=16) and 95(13) in the group with severe neuropathy (n=11). Global RNFL thickness and NDS scores were statistically significantly related (b=-1.20, p=0.048). When neuropathy was assessed across groups, a trend of thinner mean RNFL thickness was observed with increasing severity of neuropathy; however, this result was not statistically significant (F=2.86, p=0.065). TSNI quadrant analysis showed that mean RNFL thickness reduction in the inferior quadrant was 2.55 µm per 1 unit increase in NDS score (p=0.005). However, the regression coefficients were not statistically significant for RNFL thickness in the superior (b=-1.0, p=0.271), temporal (b=-0.90, p=0.238) and nasal (b=-0.99, p=0.205) quadrants. Conclusions : RNFL thickness was reduced with increasing severity of DPN and the effect was most evident in the inferior quadrant. Measuring RNFL thickness using OCT may prove to be a useful, non-invasive technique for identifying severity of DPN and may also provide additional insight into common mechanisms for peripheral neuropathy and RNFL damage.
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Research publication is one of the final steps in the research process, which begins with development of a research idea. Moving through the process of bringing together collaborators, design of the study protocol, securing of grant or study funding, and obtaining ethic(s) approval to conduct the research, and implementation of the research, analysis and drawing of conclusions based on the data leads to publication of the study results. Although a final step in the research process entails dissemination of the results, many studies go unreported or are improperly reported. Indeed, reviewers have suggested that many randomized controlled trials, observational studies, and qualitative studies lack crucial methodological features or details that lend credibility to study results (Simera et al., 2010).
Resumo:
Sleepy driving and drink driving are two risky driving behaviours that substantially contribute to road crashes. Several studies demonstrate equivalent levels of impairment from both sleepy and drink driving. Yet, drivers perceive sleepy and drink driving distinctly different, with younger and older drivers engaging in these two risky driving behaviours at different rates. The current study sought to examine the sleepy and drink driving behaviours and perceptions in a sample of 114 younger (17-29 years) and 177 older (30+ years) drivers. Compared to older drivers, younger drivers reported more positive attitudes toward sleepy and drink driving behaviours, as well as more negative views regarding perceived legitimacy of sleepy driving enforcement. Younger drivers were also more likely to report performing sleepy driving behaviours than older drivers. Younger drivers reported greater likelihood to drive while sleepy, lower perceptions of legitimacy for sleepy driving, and more positive attitudes towards sleepy driving when compared to drink driving and the same pattern was found for older drivers as well. Subsequently, the self-reported likelihood of driving while sleepy was greater than drink driving in both age groups. Overall, the results suggest that sleepy driving is not viewed as equally dangerous as drink driving with younger drivers’ perceptions being more lenient than older drivers’ perceptions. It is likely that change is needed regarding the perceptions of dangerousness of sleepy driving with a particular focus on younger drivers seemingly needed.