66 resultados para Error-correcting codes (Information theory)


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Seamless phase II/III clinical trials in which an experimental treatment is selected at an interim analysis have been the focus of much recent research interest. Many of the methods proposed are based on the group sequential approach. This paper considers designs of this type in which the treatment selection can be based on short-term endpoint information for more patients than have primary endpoint data available. We show that in such a case, the familywise type I error rate may be inflated if previously proposed group sequential methods are used and the treatment selection rule is not specified in advance. A method is proposed to avoid this inflation by considering the treatment selection that maximises the conditional error given the data available at the interim analysis. A simulation study is reported that illustrates the type I error rate inflation and compares the power of the new approach with two other methods: a combination testing approach and a group sequential method that does not use the short-term endpoint data, both of which also strongly control the type I error rate. The new method is also illustrated through application to a study in Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

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To improve the quantity and impact of observations used in data assimilation it is necessary to take into account the full, potentially correlated, observation error statistics. A number of methods for estimating correlated observation errors exist, but a popular method is a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. The accuracy of the results it yields is unknown as the diagnostic is sensitive to the difference between the exact background and exact observation error covariances and those that are chosen for use within the assimilation. It has often been stated in the literature that the results using this diagnostic are only valid when the background and observation error correlation length scales are well separated. Here we develop new theory relating to the diagnostic. For observations on a 1D periodic domain we are able to the show the effect of changes in the assumed error statistics used in the assimilation on the estimated observation error covariance matrix. We also provide bounds for the estimated observation error variance and eigenvalues of the estimated observation error correlation matrix. We demonstrate that it is still possible to obtain useful results from the diagnostic when the background and observation error length scales are similar. In general, our results suggest that when correlated observation errors are treated as uncorrelated in the assimilation, the diagnostic will underestimate the correlation length scale. We support our theoretical results with simple illustrative examples. These results have potential use for interpreting the derived covariances estimated using an operational system.

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Background  Access to, and the use of, information and communication technology (ICT) is increasingly becoming a vital component of mainstream life. First-order (e.g. time and money) and second-order factors (e.g. beliefs of staff members) affect the use of ICT in different contexts. It is timely to investigate what these factors may be in the context of service provision for adults with intellectual disabilities given the role ICT could play in facilitating communication and access to information and opportunities as suggested in Valuing People. Method  Taking a qualitative approach, nine day service sites within one organization were visited over a period of 6 months to observe ICT-related practice and seek the views of staff members working with adults with intellectual disabilities. All day services were equipped with modern ICT equipment including computers, digital cameras, Internet connections and related peripherals. Results  Staff members reported time, training and budget as significant first-order factors. Organizational culture and beliefs about the suitability of technology for older or less able service users were the striking second-order factors mentioned. Despite similar levels of equipment, support and training, ICT use had developed in very different ways across sites. Conclusion  The provision of ICT equipment and training is not sufficient to ensure their use; the beliefs of staff members and organizational culture of sites play a substantial role in how ICT is used with and by service users. Activity theory provides a useful framework for considering how first- and second-order factors are related. Staff members need to be given clear information about the broader purpose of activities in day services, especially in relation to the lifelong learning agenda, in order to see the relevance and usefulness of ICT resources for all service users.

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We present an account of semantic representation that focuses on distinct types of information from which word meanings can be learned. In particular, we argue that there are at least two major types of information from which we learn word meanings. The first is what we call experiential information. This is data derived both from our sensory-motor interactions with the outside world, as well as from our experience of own inner states, particularly our emotions. The second type of information is language-based. In particular, it is derived from the general linguistic context in which words appear. The paper spells out this proposal, summarizes research supporting this view and presents new predictions emerging from this framework.

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This paper describes new advances in the exploitation of oxygen A-band measurements from POLDER3 sensor onboard PARASOL, satellite platform within the A-Train. These developments result from not only an account of the dependence of POLDER oxygen parameters to cloud optical thickness τ and to the scene's geometrical conditions but also, and more importantly, from the finer understanding of the sensitivity of these parameters to cloud vertical extent. This sensitivity is made possible thanks to the multidirectional character of POLDER measurements. In the case of monolayer clouds that represent most of cloudy conditions, new oxygen parameters are obtained and calibrated from POLDER3 data colocalized with the measurements of the two active sensors of the A-Train: CALIOP/CALIPSO and CPR/CloudSat. From a parameterization that is (μs, τ) dependent, with μs the cosine of the solar zenith angle, a cloud top oxygen pressure (CTOP) and a cloud middle oxygen pressure (CMOP) are obtained, which are estimates of actual cloud top and middle pressures (CTP and CMP). Performances of CTOP and CMOP are presented by class of clouds following the ISCCP classification. In 2008, the coefficient of the correlation between CMOP and CMP is 0.81 for cirrostratus, 0.79 for stratocumulus, 0.75 for deep convective clouds. The coefficient of the correlation between CTOP and CTP is 0.75, 0.73, and 0.79 for the same cloud types. The score obtained by CTOP, defined as the confidence in the retrieval for a particular range of inferred value and for a given error, is higher than the one of MODIS CTP estimate. Scores of CTOP are the highest for bin value of CTP superior in numbers. For liquid (ice) clouds and an error of 30 hPa (50 hPa), the score of CTOP reaches 50% (70%). From the difference between CTOP and CMOP, a first estimate of the cloud vertical extent h is possible. A second estimate of h comes from the correlation between the angular standard deviation of POLDER oxygen pressure σPO2 and the cloud vertical extent. This correlation is studied in detail in the case of liquid clouds. It is shown to be spatially and temporally robust, except for clouds above land during winter months. The analysis of the correlation's dependence on the scene's characteristics leads to a parameterization providing h from σPO2. For liquid water clouds above ocean in 2008, the mean difference between the actual cloud vertical extent and the one retrieved from σPO2 (from the pressure difference) is 5 m (−12 m). The standard deviation of the mean difference is close to 1000 m for the two methods. POLDER estimates of the cloud geometrical thickness obtain a global score of 50% confidence for a relative error of 20% (40%) of the estimate for ice (liquid) clouds over ocean. These results need to be validated outside of the CALIPSO/CloudSat track.

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Compared with younger adults, older adults have a relative preference to attend to and remember positive over negative information. This is known as the “positivity effect,” and researchers have typically evoked socioemotional selectivity theory to explain it. According to socioemotional selectivity theory, as people get older they begin to perceive their time left in life as more limited. These reduced time horizons prompt older adults to prioritize achieving emotional gratification and thus exhibit increased positivity in attention and recall. Although this is the most commonly cited explanation of the positivity effect, there is currently a lack of clear experimental evidence demonstrating a link between time horizons and positivity. The goal of the current research was to address this issue. In two separate experiments, we asked participants to complete a writing activity, which directed them to think of time as being either limited or expansive (Experiments 1 and 2) or did not orient them to think about time in a particular manner (Experiment 2). Participants were then shown a series of emotional pictures, which they subsequently tried to recall. Results from both studies showed that regardless of chronological age, thinking about a limited future enhanced the relative positivity of participants’ recall. Furthermore, the results of Experiment 2 showed that this effect was not driven by changes in mood. Thus, the fact that older adults’ recall is typically more positive than younger adults’ recall may index naturally shifting time horizons and goals with age.