828 resultados para Playful Computing


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Background This paper assesses the usefulness of the Child Health Computing System as a source of information about children with cerebral palsy.

Methods A comparative survey of information held on the Child Health Computing System (CHCS) and the Northern Ireland Cerebral Palsy Register (NICPR) in one Health and Social Services Board in Northern Ireland was carried out. The sample comprised children with cerebral palsy aged 5–9 years.

Results Of the 135 cases recorded on the NICPR, 47 per cent were not found on the CHCS; the majority of these children had no computer record of any medical diagnosis. Of the 82 cases recorded on the CHCS, 10(12 per cent) were not found on the NICPR; five of these cases (6 per cent) were found on follow–up not to have CP.

Conclusions Unless improvements are made in case ascertainment, case validation and recording activities, the evidence suggests that the CHCS will not be able to provide the same quality of information for needs assessment and surveillance of very low birthweight infants in relation to cerebral palsy as is provided by a specialist case register.

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Playful structure is a new pedagogic image representing a more balanced and integrated perspective on early years pedagogy, aiming to blend apparent dichotomies and contradictions and to sustain and evolve play-based practice beyond Year 1. Playful structure invites teachers and children to initiate and maintain a degree of playfulness in the child’s whole learning experience, even when the learning intentions demand a supportive structure. Thus, playfulness becomes characteristic of the interaction between adult and the child and not just characteristic of child-initiated versus adult-initiated activities, or of play-time versus task-time. The paper is based on intensive observations and interviews with teachers in Northern Ireland who participated in a play-based and informal curriculum. This paper explains how playful structure rests on complementary processes of infusion of structure into play-based activities and infusion of playfulness into more structured activities, illustrated by cameos. ‘Infusion’ suggests the subtle blending process that allows apparent dichotomies and contradictions to be resolved in practice.

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Multicore computational accelerators such as GPUs are now commodity components for highperformance computing at scale. While such accelerators have been studied in some detail as stand-alone computational engines, their integration in large-scale distributed systems raises new challenges and trade-offs. In this paper, we present an exploration of resource management alternatives for building asymmetric accelerator-based distributed systems. We present these alternatives in the context of a capabilities-aware framework for data-intensive computing, which uses an enhanced implementation of the MapReduce programming model for accelerator-based clusters, compared to the state of the art. The framework can transparently utilize heterogeneous accelerators for deriving high performance with low programming effort. Our work is the first to compare heterogeneous types of accelerators, GPUs and a Cell processors, in the same environment and the first to explore the trade-offs between compute-efficient and control-efficient accelerators on data-intensive systems. Our investigation shows that our framework scales well with the number of different compute nodes. Furthermore, it runs simultaneously on two different types of accelerators, successfully adapts to the resource capabilities, and performs 26.9% better on average than a static execution approach.