4,317 research outputs found

    Empirical Bayes estimation of posterior probabilities of enrichment

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    To interpret differentially expressed genes or other discovered features, researchers conduct hypothesis tests to determine which biological categories such as those of the Gene Ontology (GO) are enriched in the sense of having differential representation among the discovered features. We study application of better estimators of the local false discovery rate (LFDR), a probability that the biological category has equivalent representation among the preselected features. We identified three promising estimators of the LFDR for detecting differential representation: a semiparametric estimator (SPE), a normalized maximum likelihood estimator (NMLE), and a maximum likelihood estimator (MLE). We found that the MLE performs at least as well as the SPE for on the order of 100 of GO categories even when the ideal number of components in its underlying mixture model is unknown. However, the MLE is unreliable when the number of GO categories is small compared to the number of PMM components. Thus, if the number of categories is on the order of 10, the SPE is a more reliable LFDR estimator. The NMLE depends not only on the data but also on a specified value of the prior probability of differential representation. It is therefore an appropriate LFDR estimator only when the number of GO categories is too small for application of the other methods. For enrichment detection, we recommend estimating the LFDR by the MLE given at least a medium number (~100) of GO categories, by the SPE given a small number of GO categories (~10), and by the NMLE given a very small number (~1) of GO categories.Comment: exhaustive revision of Zhenyu Yang and David R. Bickel, "Minimum Description Length Measures of Evidence for Enrichment" (December 2010). COBRA Preprint Series. Article 76. http://biostats.bepress.com/cobra/ps/art7

    Multi-Stream Management for Supporting Multi-Party 3D Tele-Immersive Environments

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    Three-dimensional tele-immersive (3DTI) environments have great potential to promote collaborative work among geographically distributed participants. However, extensive application of 3DTI environments is still hindered by problems pertaining to scalability, manageability and reliance of special-purpose components. Thus, one critical question is how to organize the acquisition, transmission and display of large volume real-time 3D visual data over commercially available computing and networking infrastructures so that .everybody. would be able to install and enjoy 3DTI environments for high quality tele-collaboration. In the thesis, we explore the design space from the angle of multi-stream Quality-of-Service (QoS) management to support multi-party 3DTI communication. In 3DTI environments, multiple correlated 3D video streams are deployed to provide a comprehensive representation of the physical scene. Traditional QoS approach in 2D and single-stream scenario has become inadequate. On the other hand, the existence of multiple streams provides unique opportunity for QoS provisioning. We propose an innovative cross-layer hierarchical and distributed multi-stream management middleware framework for QoS provisioning to fully enable multi-party 3DTI communication over general delivery infrastructure. The major contributions are as follows. First, we introduce the view model for representing the user interest in the application layer. The design revolves around the concept of view-aware multi-stream coordination, which leverages the central role of view semantics in 3D video systems. Second, in the stream differentiation layer we present the design of view to stream mapping, where a subset of relevant streams are selected based on the relative importance of each stream to the current view. Conventional streaming controllers focus on a fixed set of streams specified by the application. Different from all the others, in our management framework the application layer only specifies the view information while the underlying controller dynamically determines the set of streams to be managed. Third, in the stream coordination layer we present two designs applicable in different situations. In the case of end-to-end 3DTI communication, a learning-based controller is embedded which provides bandwidth allocation for relevant streams. In the case of multi-party 3DTI communication, we propose a novel ViewCast protocol to coordinate the multi-stream content dissemination upon an end-system overlay network

    A Study on Self-efficacy and Its Role in Mobile-assisted Language Learning

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    In this era of digital technology, time and place no longer limit access to information, communication, and learning. Following the trend and popularity of CALL (Computer-assisted Language Learning), MALL (Mobile-assisted Language Learning) is gaining increasing attention and application. Many teachers as well as language learners turn to these mobile devices for various language learning purposes due to easy access to resources, convenience, and less language anxiety. Despite the comprehensive functions and sophisticated devices, a high percentage of learners still lag behind and even give up the apps after some time of use. Some research shows that the unsuccessful learners’ lack of motivation constitutes a major hinderance in their self-regulated learning. This study tries to analyze an important component in learners’ motivation, that is self-efficacy (especially computer self-efficacy), and seek for good solutions to the current problems
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