68 resultados para Social Computing


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Doutoramento em Gestão

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Trabalho de Projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

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Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

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Single processor architectures are unable to provide the required performance of high performance embedded systems. Parallel processing based on general-purpose processors can achieve these performances with a considerable increase of required resources. However, in many cases, simplified optimized parallel cores can be used instead of general-purpose processors achieving better performance at lower resource utilization. In this paper, we propose a configurable many-core architecture to serve as a co-processor for high-performance embedded computing on Field-Programmable Gate Arrays. The architecture consists of an array of configurable simple cores with support for floating-point operations interconnected with a configurable interconnection network. For each core it is possible to configure the size of the internal memory, the supported operations and number of interfacing ports. The architecture was tested in a ZYNQ-7020 FPGA in the execution of several parallel algorithms. The results show that the proposed many-core architecture achieves better performance than that achieved with a parallel generalpurpose processor and that up to 32 floating-point cores can be implemented in a ZYNQ-7020 SoC FPGA.

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The rapidly increasing computing power, available storage and communication capabilities of mobile devices makes it possible to start processing and storing data locally, rather than offloading it to remote servers; allowing scenarios of mobile clouds without infrastructure dependency. We can now aim at connecting neighboring mobile devices, creating a local mobile cloud that provides storage and computing services on local generated data. In this paper, we describe an early overview of a distributed mobile system that allows accessing and processing of data distributed across mobile devices without an external communication infrastructure. Copyright © 2015 ICST.

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Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

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During last decades there has been a trend to build collaboration platforms as enablers for groups of enterprises to jointly provide integrated services and products. As a result, the notion of business ecosystem is getting wider acceptance. However, a critical issue that is still open, despite some efforts in this area, is the identification of adequate performance indicators to measure and motivate sustainable collaboration. This work-in-progress addresses this concern, briefly presenting the state of the art of relevant contributing areas such as, collaborative networks, business ecosystems, enterprise performance indicators, social networks analysis, and supply chains. Complementarily, through an assessment of current gaps, the research challenges are identified and an approach for further development is proposed.

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The capability to anticipate a contact with another device can greatly improve the performance and user satisfaction not only of mobile social network applications but of any other relying on some form of data harvesting or hoarding. One of the most promising approaches for contact prediction is to extrapolate from past experiences. This paper investigates the recurring contact patterns observed between groups of devices using an 8-year dataset of wireless access logs produced by more than 70000 devices. This effort permitted to model the probabilities of occurrence of a contact at a predefined date between groups of devices using a power law distribution that varies according to neighbourhood size and recurrence period. In the general case, the model can be used by applications that need to disseminate large datasets by groups of devices. As an example, the paper presents and evaluates an algorithm that provides daily contact predictions, based on the history of past pairwise contacts and their duration. Copyright © 2015 ICST.