174 resultados para Accelerated storages
Resumo:
The use of graphical processing unit (GPU) parallel processing is becoming a part of mainstream statistical practice. The reliance of Bayesian statistics on Markov Chain Monte Carlo (MCMC) methods makes the applicability of parallel processing not immediately obvious. It is illustrated that there are substantial gains in improved computational time for MCMC and other methods of evaluation by computing the likelihood using GPU parallel processing. Examples use data from the Global Terrorism Database to model terrorist activity in Colombia from 2000 through 2010 and a likelihood based on the explicit convolution of two negative-binomial processes. Results show decreases in computational time by a factor of over 200. Factors influencing these improvements and guidelines for programming parallel implementations of the likelihood are discussed.
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We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.
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Background Despite the widely recognised importance of sustainable health care systems, health services research remains generally underfunded in Australia. The Australian Centre for Health Services Innovation (AusHSI) is funding health services research in the state of Queensland. AusHSI has developed a streamlined protocol for applying and awarding funding using a short proposal and accelerated peer review. Method An observational study of proposals for four health services research funding rounds from May 2012 to November 2013. A short proposal of less than 1,200 words was submitted using a secure web-based portal. The primary outcome measures are: time spent preparing proposals; a simplified scoring of grant proposals (reject, revise or accept for interview) by a scientific review committee; and progressing from submission to funding outcomes within eight weeks. Proposals outside of health services research were deemed ineligible. Results There were 228 eligible proposals across 4 funding rounds: from 29% to 79% were shortlisted and 9% to 32% were accepted for interview. Success rates increased from 6% (in 2012) to 16% (in 2013) of eligible proposals. Applicants were notified of the outcomes within two weeks from the interview; which was a maximum of eight weeks after the submission deadline. Applicants spent 7 days on average preparing their proposal. Applicants with a ranking of reject or revise received written feedback and suggested improvements for their proposals, and resubmissions composed one third of the 2013 rounds. Conclusions The AusHSI funding scheme is a streamlined application process that has simplified the process of allocating health services research funding for both applicants and peer reviewers. The AusHSI process has minimised the time from submission to notification of funding outcomes.
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The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.
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This thesis synthesises advancements made in the method of assessment of emergency patients with possible acute cardiac disease and has defined new assessment strategies that supports the safe early discharge of patients at low risk for acute coronary syndromes. These important findings have informed clinicians and health services about improvements that can be made at this current time in the process of care of ED patients, and the studies have had local, national and international influence.
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At a campus in a low socioeconomic (SES) area, our University allows enrolled nurses entry into the second year of a Bachelor of Nursing, but attrition is high. Using the factors, described by Yorke and Thomas (2003) to have a positive impact on the attrition of low SES students, we developed strategies to prepare the enrolled nurses for the pharmacology and bioscience units of a nursing degree with the aim of reducing their attrition. As a strategy, the introduction of review lectures of anatomy, physiology and microbiology, was associated with significantly reduced attrition rates. The subsequent introduction of a formative website activity of some basic concepts in bioscience and pharmacology, and a workshop addressing study skills and online resources, were associated with a further reduction in attrition rates of enrolled nursing students in a Bachelor of Nursing.
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Background: Recently there have been efforts to derive safe, efficient processes to rule out acute coronary syndrome (ACS) in emergency department (ED) chest pain patients. We aimed to prospectively validate an ACS assessment pathway (the 2-Hour Accelerated Diagnostic Protocol to Assess Patients with Chest Pain Symptoms Using Contemporary Troponins as the Only Biomarker (ADAPT) pathway) under pragmatic ED working conditions. Methods: This prospective cohort study included patients with atraumatic chest pain in whom ACS was suspected but who did not have clear evidence of ischaemia on ECG. Thrombolysis in myocardial infarction (TIMI) score and troponin (TnI Ultra) were measured at ED presentation, 2 h later and according to current national recommendations. The primary outcome of interest was the occurrence of major adverse cardiac events (MACE) including prevalent myocardial infarction (MI) at 30 days in the group who had a TIMI score of 0 and had presentation and 2-h TnI assays <99th percentile. Results: Eight hundred and forty patients were studied of whom 177 (21%) had a TIMI score of 0. There were no MI, MACE or revascularization in the per protocol and intention-to-treat 2-h troponin groups (0%, 95% confidence interval (CI) 0% to 4.5% and 0%, 95% CI 0% to 3.8%, respectively). The negative predictive value (NPV) was 100% (95% CI 95.5% to 100%) and 100% (95% CI 96.2% to 100%), respectively. Conclusions: A 2-h accelerated rule-out process for ED chest pain patients using electrocardiography, a TIMI score of 0 and a contemporary sensitive troponin assay accurately identifies a group at very low risk of 30-day MI or MACE.
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Objective Risk scores and accelerated diagnostic protocols can identify chest pain patients with low risk of major adverse cardiac event who could be discharged early from the ED, saving time and costs. We aimed to derive and validate a chest pain score and accelerated diagnostic protocol (ADP) that could safely increase the proportion of patients suitable for early discharge. Methods Logistic regression identified statistical predictors for major adverse cardiac events in a derivation cohort. Statistical coefficients were converted to whole numbers to create a score. Clinician feedback was used to improve the clinical plausibility and the usability of the final score (Emergency Department Assessment of Chest pain Score [EDACS]). EDACS was combined with electrocardiogram results and troponin results at 0 and 2 h to develop an ADP (EDACS-ADP). The score and EDACS-ADP were validated and tested for reproducibility in separate cohorts of patients. Results In the derivation (n = 1974) and validation (n = 608) cohorts, the EDACS-ADP classified 42.2% (sensitivity 99.0%, specificity 49.9%) and 51.3% (sensitivity 100.0%, specificity 59.0%) as low risk of major adverse cardiac events, respectively. The intra-class correlation coefficient for categorisation of patients as low risk was 0.87. Conclusion The EDACS-ADP identified approximately half of the patients presenting to the ED with possible cardiac chest pain as having low risk of short-term major adverse cardiac events, with high sensitivity. This is a significant improvement on similar, previously reported protocols. The EDACS-ADP is reproducible and has the potential to make considerable cost reductions to health systems.
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For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold: - (i) incorporating within-cluster ranks in censored data analysis, and; - (ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience. Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.
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Accelerated students in nursing have their first experience of university entering into second year subjects such as pharmacology. These accelerated students may have a Diploma of Nursing or equivalent experience or may be domestic or international graduates in any subject area. We have previously shown that the withdrawal rates are higher for accelerated than traditional students. We now show that of the accelerated students, it is only the diploma students that have difficulty transitioning to a BN.
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In order to reduce the attrition of accelerated nursing students in bioscience/pharmacology, we introduced an innovation to help these students. Although this innovation was associated with reduced attritions from the units in their first year at university, we now show that there was a reduced graduation rate of the accelerated students who survived pharmacology, compared to the traditional students.