970 resultados para Error in essence


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The development of computer-based devices for music control has created a need to study how spectators understand new performance technologies and practices. As a part of a larger project examining how interactions with technology can be communicated to spectators, we present a model of a spectator's understanding of error by a performer. This model is broadly applicable throughout HCI, as interactions with technology are increasingly public and spectatorship is becoming more common.

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Microsatellite genotyping is a common DNA characterization technique in population, ecological and evolutionary genetics research. Since different alleles are sized relative to internal size-standards, different laboratories must calibrate and standardize allelic designations when exchanging data. This interchange of microsatellite data can often prove problematic. Here, 16 microsatellite loci were calibrated and standardized for the Atlantic salmon, Salmo salar, across 12 laboratories. Although inconsistencies were observed, particularly due to differences between migration of DNA fragments and actual allelic size ('size shifts'), inter-laboratory calibration was successful. Standardization also allowed an assessment of the degree and partitioning of genotyping error. Notably, the global allelic error rate was reduced from 0.05 ± 0.01 prior to calibration to 0.01 ± 0.002 post-calibration. Most errors were found to occur during analysis (i.e. when size-calling alleles; the mean proportion of all errors that were analytical errors across loci was 0.58 after calibration). No evidence was found of an association between the degree of error and allelic size range of a locus, number of alleles, nor repeat type, nor was there evidence that genotyping errors were more prevalent when a laboratory analyzed samples outside of the usual geographic area they encounter. The microsatellite calibration between laboratories presented here will be especially important for genetic assignment of marine-caught Atlantic salmon, enabling analysis of marine mortality, a major factor in the observed declines of this highly valued species.

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This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

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Social work in the United Kingdom remains embroiled in concerns about child protection error. The serious injury or death of vulnerable children continues to evince much consternation in the public and private spheres. Governmental responses to these concerns invariably draw on technocratic solutions involving more procedures, case management systems, information technology and bureaucratic regulation. Such solutions flow from an implicit use of instrumental rationality based on a ‘means-end’ logic. While bringing an important perspective to the problem of child protection error, instrumental rationality has been overused limiting discretion and other modes of rational inquiry. This paper argues that the social work profession should apply an enlarged form of rationality comprising not only the instrumental-rational mode but also the critical-rational, affective-rational and communicative-rational forms. It is suggested that this combined, conceptual arsenal of rational inquiry leads to a gestalt which has been termed the holistic-rational perspective. It is also argued that embracing a more rounded perspective such as this might offer greater opportunities for reducing child protection error.

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To estimate the prevalence of refractive error in adults across Europe. Refractive data (mean spherical equivalent) collected between 1990 and 2013 from fifteen population-based cohort and cross-sectional studies of the European Eye Epidemiology (E3) Consortium were combined in a random effects meta-analysis stratified by 5-year age intervals and gender. Participants were excluded if they were identified as having had cataract surgery, retinal detachment, refractive surgery or other factors that might influence refraction. Estimates of refractive error prevalence were obtained including the following classifications: myopia ≤−0.75 diopters (D), high myopia ≤−6D, hyperopia ≥1D and astigmatism ≥1D. Meta-analysis of refractive error was performed for 61,946 individuals from fifteen studies with median age ranging from 44 to 81 and minimal ethnic variation (98 % European ancestry). The age-standardised prevalences (using the 2010 European Standard Population, limited to those ≥25 and <90 years old) were: myopia 30.6 % [95 % confidence interval (CI) 30.4–30.9], high myopia 2.7 % (95 % CI 2.69–2.73), hyperopia 25.2 % (95 % CI 25.0–25.4) and astigmatism 23.9 % (95 % CI 23.7–24.1). Age-specific estimates revealed a high prevalence of myopia in younger participants [47.2 % (CI 41.8–52.5) in 25–29 years-olds]. Refractive error affects just over a half of European adults. The greatest burden of refractive error is due to myopia, with high prevalence rates in young adults. Using the 2010 European population estimates, we estimate there are 227.2 million people with myopia across Europe.

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The World Health Organization estimates that 13 million children aged 5-15 years worldwide are visually impaired from uncorrected refractive error. School vision screening programs can identify and treat or refer children with refractive error. We concentrate on the findings of various screening studies and attempt to identify key factors in the success and sustainability of such programs in the developing world. We reviewed original and review articles describing children's vision and refractive error screening programs published in English and listed in PubMed, Medline OVID, Google Scholar, and Oxford University Electronic Resources databases. Data were abstracted on study objective, design, setting, participants, and outcomes, including accuracy of screening, quality of refractive services, barriers to uptake, impact on quality of life, and cost-effectiveness of programs. Inadequately corrected refractive error is an important global cause of visual impairment in childhood. School-based vision screening carried out by teachers and other ancillary personnel may be an effective means of detecting affected children and improving their visual function with spectacles. The need for services and potential impact of school-based programs varies widely between areas, depending on prevalence of refractive error and competing conditions and rates of school attendance. Barriers to acceptance of services include the cost and quality of available refractive care and mistaken beliefs that glasses will harm children's eyes. Further research is needed in areas such as the cost-effectiveness of different screening approaches and impact of education to promote acceptance of spectacle-wear. School vision programs should be integrated into comprehensive efforts to promote healthy children and their families.

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Letter to S.D. Woodruff from an illegible signature stating that he suspects a clerical error in one of the columns, n.d.

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Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

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Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

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The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden’s index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel–Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden’s index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention.