6,046 research outputs found

    DISCUSSION

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    This article argues that the use of the network metaphor can link together various different aspects of research into the use of advanced learning technologies based on computer networks. The idea of networked learning has become commonplace as an alternative to e-learning that stresses the interaction of learners, tutors and resources through networks. The arguments put in this article are firstly that learning technology needs to take account of the wider debate about networks and secondly that research in this field needs to address the theoretical and practical issues raised by advances in the field of networks. A third point is that the idea of the network acts as a powerful metaphor even if we are able to discount any particular theory generated in its support. The network metaphor can act as a unifying concept allowing us to bring together apparently disparate elements of the field. Networks are an important issue in the study of learning using advanced technologies and they speak to some of the central issues in learning theory such as virtual communities and communities of practice

    Aggregate and Sector Import Price Elasticities for a Sample of African Countries

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    This paper applies panel data methods to a simple imperfect substitutes model to estimate import demand elasticities for ten African countries. The elasticities are estimated at three levels of aggregation. Firstly, we generate aggregate elasticities for each country. Secondly, we use interactive dummy variables to create estimates for 16 sectors defined by the World Customs Organisation (WCO). Finally, we estimate elasticities for each of the 94 2-digit product lines defined by the Harmonised System (HS). In total there are 10 aggregate estimates, 158 estimates for the 16 WCO sectors; and 911 estimates at the 2-digit level. Using Fixed-Effects, the aggregate estimates do not differ significantly from unity. However, as we move to different levels of aggregation the estimates have much more variability. In general, import demand appears more elastic in sectors that have relatively high levels of domestic production or where there are exports.Imports, Import Demand Elasticities, Africa

    Two-state filtering for joint state-parameter estimation

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    This paper presents an approach for simultaneous estimation of the state and unknown parameters in a sequential data assimilation framework. The state augmentation technique, in which the state vector is augmented by the model parameters, has been investigated in many previous studies and some success with this technique has been reported in the case where model parameters are additive. However, many geophysical or climate models contains non-additive parameters such as those arising from physical parametrization of sub-grid scale processes, in which case the state augmentation technique may become ineffective since its inference about parameters from partially observed states based on the cross covariance between states and parameters is inadequate if states and parameters are not linearly correlated. In this paper, we propose a two-stages filtering technique that runs particle filtering (PF) to estimate parameters while updating the state estimate using Ensemble Kalman filter (ENKF; these two "sub-filters" interact. The applicability of the proposed method is demonstrated using the Lorenz-96 system, where the forcing is parameterized and the amplitude and phase of the forcing are to be estimated jointly with the states. The proposed method is shown to be capable of estimating these model parameters with a high accuracy as well as reducing uncertainty while the state augmentation technique fails
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