790 resultados para Multiagent architecture
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This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.
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Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.
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Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.
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20th International Conference on Reliable Software Technologies - Ada-Europe 2015 (Ada-Europe 2015), Madrid, Spain.
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Demo in Workshop on ns-3 (WNS3 2015). 13 to 14, May, 2015. Castelldefels, Spain.
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Poster presented in 28th GI/ITG International Conference on Architecture of Computing Systems (ARCS 2015). 25 to 28, Mar, 2015, Poster Session. Porto, Portugal.
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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Covilhã, Portugal.
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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Portugal.
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Near real time media content personalisation is nowadays a major challenge involving media content sources, distributors and viewers. This paper describes an approach to seamless recommendation, negotiation and transaction of personalised media content. It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources, providing viewers, on the business-to-consumer (B2C) side, with a personalised electronic programme guide (EPG) containing the set of recommended items after negotiation. In this setup, when a viewer connects, the distributor looks up and invites sources to negotiate the contents of the viewer personal EPG. The proposed multi-agent brokerage platform is structured in four layers, modelling the registration, service agreement, partner lookup, invitation as well as item recommendation, negotiation and transaction stages of the B2B processes. The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. The rule-based system selects, at runtime, the filter(s) to apply as well as the final set of recommendations to present. The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer. Additionally, this module implements (i) a novel item stereotype to represent newly arrived items, (ii) a standard user stereotype for new users, (iii) a novel passive user tag cloud stereotype for socially passive users, and (iv) a new content-based filter named the collinearity and proximity similarity (CPS). At the end of the paper, we present off-line results and a case study describing how the recommendation service works. The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents.
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Crowdsourcing is evolving into powerful outsourcing options for organizations by providing access to the intellectual capital within a vast knowledge community. Innovation brokering services have emerged to facilitate crowdsourcing projects by connecting up companies with potential solution providers within the wider ‘crowd’. Most existing innovation brokering services are primarily aimed at larger organizations, however, Small and Medium Enterprises (SMEs) offer considerable potential for crowdsourcing activity since they are typically the innovation and employment engines in society; they are typically more nimble and responsive to the business environment than the larger companies. SMEs have very different challenges and needs to larger organizations since they have fewer resources, a more limited knowledge and skill base, and immature management practices. Consequently, innovation brokering for SMEs require considerably more support than for larger organizations. This paper identifies the crowdsourcing innovation brokerage facilities needed by SMEs, and presents an architecture that encourages knowledge sharing, development of community, support in mixing and matching capabilities, and management of stakeholders’ risks. Innovation brokering is emerging as a novel business model that is challenging concepts of the traditional value chain and organizational boundaries.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores Especialidade: Robótica e Manufactura Integrada
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A fundação de uma missão jesuita no Norte da Etiópia em 1603, na província do Tigré, pelo enérgico Pe. Pero Pais, S. J. teólogo, construtor e historiador vindo de Goa, tomou um forte impulso com a aliança pretendida com os Portugueses pelo imperador Susénios (1619-20) para o apoio militar contra os muçulmanos; e, sobretudo, após a sua conversão oficial à Igreja Católica Romana, em 1626. Uma dúzia de inovadores edifícios foram então construídos pelos Jesuítas na região paradisíaca em torno do Lago Tana: basílicas, igrejas, palácios e jardins, complexos palatinos e eclesiásticos, colégios, etc. A tipologia em cruz latina e ornatos incisos é deliberadamente diferente das igrejas ortodoxas etíopes, circulares e em madeira. A técnica de construção em pedra e cal, ignorada na Etiópia, significou uma revolução. No presente texto procura-se determinar a quem deve ser atribuído este inédito surto construtivo, deixando de lado as teorias tradicionais de pedreiros vindos de Portugal ou de construtores locais. Com base na evidência estilística e em referências de textos da época, atribui-se a inovação a padres e “irmãos” jesuitas com experiência de arquitectos na Índia portuguesa e a construtores de Goa e de Diu, definindo a arte portuguesa na Etiópia como uma província da arquitectura indo-portuguesa na Índia, prosseguida após a expulsão dos Jesuítas (1633) com os “castelos portugueses”, ou paços acastelados da nova capital, Gondar.