995 resultados para Sample heating


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Computer Experiments, consisting of a number of runs of a computer model with different inputs, are now common-place in scientific research. Using a simple fire model for illustration some guidelines are given for the size of a computer experiment. A graph is provided relating the error of prediction to the sample size which should be of use when designing computer experiments. Methods for augmenting computer experiments with extra runs are also described and illustrated. The simplest method involves adding one point at a time choosing that point with the maximum prediction variance. Another method that appears to work well is to choose points from a candidate set with maximum determinant of the variance covariance matrix of predictions.

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Iris based identity verification is highly reliable but it can also be subject to attacks. Pupil dilation or constriction stimulated by the application of drugs are examples of sample presentation security attacks which can lead to higher false rejection rates. Suspects on a watch list can potentially circumvent the iris based system using such methods. This paper investigates a new approach using multiple parts of the iris (instances) and multiple iris samples in a sequential decision fusion framework that can yield robust performance. Results are presented and compared with the standard full iris based approach for a number of iris degradations. An advantage of the proposed fusion scheme is that the trade-off between detection errors can be controlled by setting parameters such as the number of instances and the number of samples used in the system. The system can then be operated to match security threat levels. It is shown that for optimal values of these parameters, the fused system also has a lower total error rate.

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The field of cyberbullying is relatively new and there is no universal consensus on its definition, measurement and intervention. Authors agree that bullying has entered into the digital domain and professionals require the skills to help identify and prevent these behaviours. Ninety two students were surveyed to determine their experience with different types of bullying behaviors (face-to-face, cyberbullying or both), as bully, victim or witness. Our objective was to explore the association between those types of bullying and anxiety. The results suggest a significant association between face-to-face bullying and anxiety. Similarly, there was significant association between experiencing both types of bullying and anxiety. Further studies are required with larger and more diverse samples in order to verify current findings and to test for additional associations.

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In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels.

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Classifier selection is a problem encountered by multi-biometric systems that aim to improve performance through fusion of decisions. A particular decision fusion architecture that combines multiple instances (n classifiers) and multiple samples (m attempts at each classifier) has been proposed in previous work to achieve controlled trade-off between false alarms and false rejects. Although analysis on text-dependent speaker verification has demonstrated better performance for fusion of decisions with favourable dependence compared to statistically independent decisions, the performance is not always optimal. Given a pool of instances, best performance with this architecture is obtained for certain combination of instances. Heuristic rules and diversity measures have been commonly used for classifier selection but it is shown that optimal performance is achieved for the `best combination performance' rule. As the search complexity for this rule increases exponentially with the addition of classifiers, a measure - the sequential error ratio (SER) - is proposed in this work that is specifically adapted to the characteristics of sequential fusion architecture. The proposed measure can be used to select a classifier that is most likely to produce a correct decision at each stage. Error rates for fusion of text-dependent HMM based speaker models using SER are compared with other classifier selection methodologies. SER is shown to achieve near optimal performance for sequential fusion of multiple instances with or without the use of multiple samples. The methodology applies to multiple speech utterances for telephone or internet based access control and to other systems such as multiple finger print and multiple handwriting sample based identity verification systems.

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Morphology changes induced in polycrystalline silver catalysts as a result of heating in either oxygen, water or oxygen-methanol atmospheres have been investigated by environmental scanning electron microscopy (ESEM), FT-Raman spectroscopy and temperature programmed desorption (TPD). The silver catalyst of interest consisted of two distinct particle types, one of which contained a significant concentration of sub-surface hydroxy species (in addition to surface adsorbed atomic oxygen). Heating the sample to 663 K resulted in the production of 'pin-holes' in the silver structure as a consequence of near-surface explosions caused by sub-surface hydroxy recombination. Furthermore, 'pin-holes' were predominantly found in the vicinity of surface defects, such as platelets and edge structures. Reaction between methanol and oxygen also resulted in the formation of 'pin-holes' in the silver surface, which were inherently associated with the catalytic process. A reaction mechanism is suggested that involves the interaction of methanol with sub-surface oxygen species to form sub-surface hydroxy groups. The sub-surface hydroxy species subsequently erupt through the silver surface to again produce 'pin-holes'.

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This study assessed the extent to which child-related factors had an impact on teacher-child relationships in Australian childcare settings. Analyses used data from Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC). The sample consisted of 1577 two to three year old children (M= 33.9 months, SD=2.93; 51.5% male). Two separate hierarchical multiple regression analyses were conducted to examine the relation between teachers’ perceptions of their relationships with children and (a) gender, (b), indigenous status, (c), language background other than English, (d), socio-economic position, (e) special health care needs, (f) expression and receptive language concerns, (g) psychosocial competence and problems and (h) temperament factors (approach, persistence and reactivity). Results indicated that special health care needs, receptive language concerns and all three temperament scales (approach, persistence and reactivity) significantly predicted conflict in teacher-child relationships. Close relationships were predicted by being female, indigenous status, higher socio-economic position, not having a special health care need and no expressive language concerns.

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The first version of the Standard PREanalytical Code (SPREC) was developed in 2009 by the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group to facilitate documentation and communication of the most important preanalytical quality parameters of different types of biospecimens used for research. This same Working Group has now updated the SPREC to version 2.0, presented here, so that it contains more options to allow for recent technological developments. Existing elements have been fine tuned. An interface to the Biospecimen Reporting for Improved Study Quality (BRISQ) has been defined, and informatics solutions for SPREC implementation have been developed. A glossary with SPRECrelated definitions has also been added.

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Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.

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Background The Environments for Healthy Living (EFHL) study is a repeated sample, longitudinal birth cohort in South East Queensland, Australia. We describe the sample characteristics and profile of maternal, household, and antenatal exposures. Variation and data stability over recruitment years were examined. Methods Four months each year from 2006, pregnant women were recruited to EFHL at routine antenatal visits on or after 24 weeks gestation, from three public maternity hospitals. Participating mothers completed a baseline questionnaire on individual, familial, social and community exposure factors. Perinatal data were extracted from hospital birth records. Descriptive statistics and measures of association were calculated comparing the EFHL birth sample with regional and national reference populations. Data stability of antenatal exposure factors was assessed across five recruitment years (2006–2010 inclusive) using the Gamma statistic for ordinal data and chi-squared for nominal data. Results Across five recruitment years 2,879 pregnant women were recruited which resulted in 2904 live births with 29 sets of twins. EFHL has a lower representation of early gestational babies, fewer still births and a lower percentage of low birth weight babies, when compared to regional data. The majority of women (65%) took a multivitamin supplement during pregnancy, 47% consumed alcohol, and 26% reported having smoked cigarettes. There were no differences in rates of a range of antenatal exposures across five years of recruitment, with the exception of increasing maternal pre-pregnancy weight (p=0.0349), decreasing rates of high maternal distress (p=0.0191) and decreasing alcohol consumption (p<0.0001). Conclusions The study sample is broadly representative of births in the region and almost all factors showed data stability over time. This study, with repeated sampling of birth cohorts over multiple years, has the potential to make important contributions to population health through evaluating longitudinal follow-up and within cohort temporal effects.

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This study identified the key self-regulated learning (SRL) strategies and their sources for nine school-aged adolescent males aged 15 to 17 years. The Self-Regulated Learning Interview Schedule (SRLIS) was used along with semi-structured interviews with the participants and their parents to elicit information on SRL strategies and contexts for the formation of self-regulatory habits. Early habit-forming experiences of the family home in relation to homework and study routines were found to form an important base for effective SRL. Teachers were identified as the most common source of SRL strategies with important formative experiences occurring during the first two years of high school.

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Microwave power is used for heating and drying processes because of its faster and volumetric heating capability. Non-uniform temperature distribution during microwave application is a major drawback of these processes. Intermittent application of microwave potentially reduces the impact of non-uniformity and improves energy efficiency by redistributing the temperature. However, temperature re-distribution during intermittent microwave heating has not been investigated adequately. Consequently, in this study, a coupled electromagnetic with heat and mass transfer model was developed using the finite element method embedded in COMSOL-Multyphysics software. Particularly, the temperature redistribution due to intermittent heating was investigated. A series of experiments were performed to validate the simulation. The test specimen was an apple and the temperature distribution was closely monitored by a TIC (Thermal Imaging Camera). The simulated temperature profile matched closely with thermal images obtained from experiments.

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Bisphenol A (BPA or 4,4’-(propane-2,2-diyl)diphenol) is a chemical intermediate in the production of polycarbonate and epoxy resins, and used in a wide range of applications. BPA has attracted significant attention in the past decade due to its frequency of detection in human populations worldwide, demonstrated animal toxicity and potential impact on human health, particularly during critical periods of development. The aim of this study was to perform a preliminary assessment of age-related trends in urinary concentration and to estimate daily excretion of BPA in Australian children (aged (>0 – <5 years) and adults (≥15 – <75 years). This was achieved using 79 samples pooled by age and gender, created from 868 individual samples of convenience collected as part of routine, community-based pathology testing. Total BPA was analyzed using online-SPE-LC-MS/MS and detected in all samples with a range of 0.65 – 265 ng/ml. No significant differences were observed between males and females. A urine flow model was constructed from published values and used to provide an estimate of daily excretion per unit bodyweight for each pooled sample. The daily excretion estimates ranged from 26.2 – 18200 ng/kg-d for children; and 20.1 – 165 ng/kg-d for adults. Urinary concentrations and estimated excretion rates were inversely associated with age, and estimated daily excretion rates in infants and young children were significantly higher than in adults (geometric mean: 107 and 47.0 ng/kg-d, respectively). Higher excretion of BPA in children may be explained by their higher food consumption relative to body weight compared to adults and adolescents, and may also reflect alternative exposure pathways and sources. Keywords: bisphenol A, biomonitoring, children, urine flow, Australia