849 resultados para Computed Based Assessment


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Understanding the dynamics of disease spread is of crucial importance, in contexts such as estimating load on medical services to risk assessment and intervention policies against large-scale epidemic outbreaks. However, most of the information is available after the spread itself, and preemptive assessment is far from trivial. Here, we investigate the use of agent-based simulations to model such outbreaks in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena.Presented in this paper is the initial framework for such a model, detailing implementation of geographical features and generation of social structures. Preliminary results are a promising step towards large-scale simulations and evaluation of potential intervention policies.

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Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

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Access to the right information at the right time is a challenge facing health professionals across the globe. HEART Online (www.heartonline.org.au) is a website designed to support the delivery of evidence based care for the prevention and rehabilitation of heart disease. It was developed by the Queensland Government and the National Heart Foundation of Australia and launched May 2013.

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Structural Health Monitoring (SHM) schemes are useful for proper management of the performance of structures and for preventing their catastrophic failures. Vibration based SHM schemes has gained popularity during the past two decades resulting in significant research. It is hence evitable that future SHM schemes will include robust and automated vibration based damage assessment techniques (VBDAT) to detect, localize and quantify damage. In this context, the Damage Index (DI) method which is classified as non-model or output based VBDAT, has the ability to automate the damage assessment process without using a computer or numerical model along with actual measurements. Although damage assessment using DI methods have been able to achieve reasonable success for structures made of homogeneous materials such as steel, the same success level has not been reported with respect to Reinforced Concrete (RC) structures. The complexity of flexural cracks is claimed to be the main reason to hinder the applicability of existing DI methods in RC structures. Past research also indicates that use of a constant baseline throughout the damage assessment process undermines the potential of the Modal Strain Energy based Damage Index (MSEDI). To address this situation, this paper presents a novel method that has been developed as part of a comprehensive research project carried out at Queensland University of Technology, Brisbane, Australia. This novel process, referred to as the baseline updating method, continuously updates the baseline and systematically tracks both crack formation and propagation with the ability to automate the damage assessment process using output only data. The proposed method is illustrated through examples and the results demonstrate the capability of the method to achieve the desired outcomes.

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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

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Purpose/Objectives: To examine and compare the reliability of four body composition methods commonly used in assessing breast cancer survivors. Design: Cross-sectional. Setting: A rehabilitation facility at a university-based comprehensive cancer center in the southeastern United States. Sample: 14 breast cancer survivors aged 40-71 years. Methods: Body fat (BF) percentage was estimated via bioelectric impedance analysis (BIA), air displacement plethysmography (ADP), and skinfold thickness (SKF) using both three- and seven-site algorithms, where reliability of the methods was evaluated by conducting two tests for each method (test 1 and test 2), one immediately after the other. An analysis of variance was used to compare the results of BF percentage among the four methods. Intraclass correlation coefficient (ICC) was used to test the reliability of each method. Main Research Variable: BF percentage. Findings: Significant differences in BF percentage were observed between BIA and all other methods (three-site SKF, p < 0.001; seven-site SKF, p < 0.001; ADP, p = 0.002). No significant differences (p > 0.05) in BF percentage between three-site SKF, seven-site SKF, and ADP were observed. ICCs between test 1 and test 2 for each method were BIA = 1, ADP = 0.98, three-site SKF = 0.99, and seven-site SKF = 0.94. Conclusions: ADP and both SKF methods produce similar estimates of BF percentage in all participants, whereas BIA overestimated BF percentage relative to the other measures. Caution is recommended when using BIA as the body composition method for breast cancer survivors who have completed treatment but are still undergoing adjuvant hormonal therapy. Implications for Nursing: Measurements of body composition can be implemented very easily as part of usual care and should serve as an objective outcome measure for interventions designed to promote healthy behaviors among breast cancer survivors. - See more at: https://onf.ons.org/onf/38/4/comparison-body-composition-assessment-methods-breast-cancer-survivors#sthash.5djfTS1Q.dpuf

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This paper presents a multi-criteria based approach for nondestructive diagnostic structural integrity assessment of a decommissioned flatbed rail wagon (FBRW) used for road bridge superstructure rehabilitation and replacement applications. First, full-scale vibration and static test data sets are employed in a FE model of the FBRW to obtain the best ‘initial’ estimate of the model parameters. Second, the ‘final’ model parameters are predicted using sensitivity-based perturbation analysis without significant difficulties encountered. Consequently, the updated FBRW model is validated using the independent sets of full-scale laboratory static test data. Finally, the updated and validated FE model of the FBRW is used for structural integrity assessment of a single lane FBRW bridge subjected to the Australian bridge design traffic load.

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There is debate around the scope of physical assessment skills that should be taught in undergraduate nursing programs. Yet this debate is largely uninformed by evidence on what is learned and practiced by nursing students. This study examined the pattern and correlates of physical assessment skill utilization by 208 graduating nursing students at an Australian university, including measures of knowledge, frequency of use and perceived barriers to physical assessment skills during clinical practice. Of the 126 skills surveyed, on average only five were used every time students practiced. Core skills reflected inspection or general observation of the patient; none involved complex palpation, percussion or auscultation. Skill utilization was also shaped by specialty area. Most skills (70%) were, on average, never performed or learned and students perceived nursing physical assessment was marginalized in both university and workplace contexts. Lack of confidence was thus a significant barrier to use of skills. Based on these findings we argue that the current debate must shift to how we might best support students to integrate comprehensive physical assessment into nursing practice.

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This paper examines the effect of individual transferable quota regimes on technology choice, such as choice of vessel size, by using the laboratory experiment method. We find that even if vessel sizes change over time, the quota price can converge to the fundamental value conditioned on the vessels chosen. We also find that subjects choose their vessel type to maximise their profits based on the quota trading prices in the previous period. This result implies that the efficiency of quota markets in the beginning period is important because any inefficiency in quota markets may affect vessel sizes in ensuing periods. Moreover, we find that the initial allocations may significantly influence vessel sizes through two channels: first, a higher initial allocation to a subject increases the likelihood that the subject invests in a large-sized vessel; second, the quota price may be higher and more unstable under unequal allocation than under equal allocation; thus, whether the allocation is equal influences subjects' choice of vessel type. © 2014 Australian Agricultural and Resource Economics Society Inc.

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In 2005, Ginger Myles and Hongxia Jin proposed a software watermarking scheme based on converting jump instructions or unconditional branch statements (UBSs) by calls to a fingerprint branch function (FBF) that computes the correct target address of the UBS as a function of the generated fingerprint and integrity check. If the program is tampered with, the fingerprint and integrity checks change and the target address will not be computed correctly. In this paper, we present an attack based on tracking stack pointer modifications to break the scheme and provide implementation details. The key element of the attack is to remove the fingerprint and integrity check generating code from the program after disassociating the target address from the fingerprint and integrity value. Using the debugging tools that give vast control to the attacker to track stack pointer operations, we perform both subtractive and watermark replacement attacks. The major steps in the attack are automated resulting in a fast and low-cost attack.

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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.

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Background The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance. Methods This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann–Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups. Results The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). With eyes closed and feet in tandem, the greatest differences found between the groups were in the minimum peak acceleration in the lateral axis (p < 0.01). Conclusions The accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.

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We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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Information from the full diffusion tensor (DT) was used to compute voxel-wise genetic contributions to brain fiber microstructure. First, we designed a new multivariate intraclass correlation formula in the log-Euclidean framework. We then analyzed used the full multivariate structure of the tensor in a multivariate version of a voxel-wise maximum-likelihood structural equation model (SEM) that computes the variance contributions in the DTs from genetic (A), common environmental (C) and unique environmental (E) factors. Our algorithm was tested on DT images from 25 identical and 25 fraternal twin pairs. After linear and fluid registration to a mean template, we computed the intraclass correlation and Falconer's heritability statistic for several scalar DT-derived measures and for the full multivariate tensors. Covariance matrices were found from the DTs, and inputted into SEM. Analyzing the full DT enhanced the detection of A and C effects. This approach should empower imaging genetics studies that use DTI.