30 resultados para Salient Objects
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This paper discusses the technology of smart floors as a enabler of smart cities. The discussion will be based on technology that is embedded into the environment that enable location, navigation but also wireless power transmission for powering up elements siting on it, typically mobile devices. One of those examples is the smart floor, this implementation follows two paths, one where the floor is passive, and normally passive RFID's are embedded into the floor, they are used to provide intelligence into the surrounding space, this is normally complemented with a battery powered mobile unit that scans the floor for the sensors and communicates the information to a database which locates the mobile device in the environment. The other path for the smart city enabler is where the floor is active and delivers energy for the objects standing on top of it. In this paper these two approaches will be presented, by discussing the technology behind it. © 2014 IEEE.
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Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde
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Recent advances in vacuum sciences and applications are reviewed. Novel optical interferometer cavity devices enable pressure measurements with ppm accuracy. The innovative dynamic vacuum standard allows for pressure measurements with temporal resolution of 2 ms. Vacuum issues in the construction of huge ultra-high vacuum devices worldwide are reviewed. Recent advances in surface science and thin films include new phenomena observed in electron transport near solid surfaces as well as novel results on the properties of carbon nanomaterials. Precise techniques for surface and thin-film characterization have been applied in the conservation technology of cultural heritage objects and recent advances in the characterization of biointerfaces are presented. The combination of various vacuum and atmospheric-pressure techniques enables an insight into the complex phenomena of protein and other biomolecule conformations on solid surfaces. Studying these phenomena at solid-liquid interfaces is regarded as the main issue in the development of alternative techniques for drug delivery, tissue engineering and thus the development of innovative techniques for curing cancer and cardiovascular diseases. A review on recent advances in plasma medicine is presented as well as novel hypotheses on cell apoptosis upon treatment with gaseous plasma. Finally, recent advances in plasma nanoscience are illustrated with several examples and a roadmap for future activities is presented.
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Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar
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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino no 1º e no 2º Ciclos do Ensino Básico
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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e do 2.º Ciclo do Ensino Básico
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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1º e 2º Ciclo do Ensino Básico
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Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.
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Este projecto de investigação teve como objectivo avaliar - através de uma série de workshops orientados pela mestranda no Centro Cultural de Belém em Abril de 2012 - o impacto da utilização de notação musical não-convencional num contexto não escolar. Traçando possíveis paralelos com o ensino especializado da música, propuseram-se metodologias de aprendizagem que permitissem a introdução da notação, de forma inovadora, no referido contexto escolar. O processo de investigação baseou-se em observação directa, na análise dos questionários preenchidos pelos participantes dos workshops e na observação e análise das gravações em vídeo que documentaram o processo artístico, pedagógico e de investigação. Numa sala escura, 6 retroprojectores projectaram uma Partitura de Luz. Entre crianças e adultos, 120 participantes (não-músicos) criaram empiricamente as suas composições, moldando o som em função da forma e a forma em função do som. O resultado foi compensador: a criação de condições favoráveis ao desenvolvimento máximo da expressão criativa individual ou colectiva dos participantes - através da utilização irrestrita de símbolos, imagens, objectos e matérias - culminou num efectivo estabelecimento de correspondência musical, a partir de recursos vocais. Este projecto, “Partitura de Luz”, foi uma oportunidade de relacionar a vertente artística – musical, plástica e gráfica - com a vertente humana: pedagógica e social.
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Trabalho de Projecto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Teatro e Comunidade
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Taking as starting points the books The Address of the Eye: A Phenomenology of Film Experience, by Vivian Sobchak, and Les quatre concepts fondamentaux de la psychanalyse, by Jacques Lacan, this article proposes to look at two well renowned film objects – Rear Window (Alfred Hitchcock, 1954, USA) and Peeping Tom (Michael Powell, 1960, UK) – in order to equate two forms of perception that, all things considered, come together as one: the perception of the mechanical apparatuses that record and project film and the optical and mental apparatuses that operate on the human filmmakers as well as their intradiegetic protagonists. In fact, these two films not only explore the characteristics and limits of vision and affection in their diegetic world, that is part of the filmmaker’s world itself, but reveals just how much the human lives through the eye and the expression of the machine itself. Film ontology is foremost a matter of (re)production rather than creation.
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Even though Software Transactional Memory (STM) is one of the most promising approaches to simplify concurrent programming, current STM implementations incur significant overheads that render them impractical for many real-sized programs. The key insight of this work is that we do not need to use the same costly barriers for all the memory managed by a real-sized application, if only a small fraction of the memory is under contention lightweight barriers may be used in this case. In this work, we propose a new solution based on an approach of adaptive object metadata (AOM) to promote the use of a fast path to access objects that are not under contention. We show that this approach is able to make the performance of an STM competitive with the best fine-grained lock-based approaches in some of the more challenging benchmarks. (C) 2015 Elsevier Inc. All rights reserved.
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Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.
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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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The Evidence Accumulation Clustering (EAC) paradigm is a clustering ensemble method which derives a consensus partition from a collection of base clusterings obtained using different algorithms. It collects from the partitions in the ensemble a set of pairwise observations about the co-occurrence of objects in a same cluster and it uses these co-occurrence statistics to derive a similarity matrix, referred to as co-association matrix. The Probabilistic Evidence Accumulation for Clustering Ensembles (PEACE) algorithm is a principled approach for the extraction of a consensus clustering from the observations encoded in the co-association matrix based on a probabilistic model for the co-association matrix parameterized by the unknown assignments of objects to clusters. In this paper we extend the PEACE algorithm by deriving a consensus solution according to a MAP approach with Dirichlet priors defined for the unknown probabilistic cluster assignments. In particular, we study the positive regularization effect of Dirichlet priors on the final consensus solution with both synthetic and real benchmark data.