807 resultados para Pursuit


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Relatório Final de Estágio apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Ensino de Dança.

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Conceitos como Globalização, Internacionalização, Localização e Tradução surgem, na realidade da indústria da língua, com uma grande interligação, mas com perspectivas nem sempre concordantes. O nosso trabalho analisa, por isso, as diferentes definições propostas dedicando especial atenção ao conceito de localização, uma vez que o nosso projecto analisa o processo de localização de uma página Web desenvolvido num contexto empresarial real. O nosso enfoque recai mais específicamente sobre a localização de páginas Web, objecto do nosso projecto, identificando não só as suas particularidades, como também os intervenientes e o tipo de competências necessárias para o desenvolvimento de um trabalho nesta área da tradução e as ferramentas disponíveis para o profissional da tradução/ localização, de que se destacam as freeware. O processo de localização impõe metas de qualidade exigentes, pelo que, partindo da definição do conceito de qualidade, analisamos o tipo de requisitos necessários a uma correcta definição de tarefas e objectivos no contexto da localização. Esta definição de conceitos e a análise do processo de localização suportaram, em seguida, o desenvolvimento do objecto do nosso projecto - o processo de localização da página Web da empresa Pinto & Cruz, ao mesmo tempo que permitiram uma prévia identificação de todos os passos a desenvolver e do tipo de dificuldades e problemas a enfrentar. Assim, e em função das condicionantes impostas pelo modelo de gestão da página, definimos um fluxo de trabalho, em que identificamos as diferentes fases e intervenientes, mediante a utilização de uma plataforma de trabalho disponibilizada pelo webmaster do sítio em questão. O processo seguido para a localização da página é descrito, as suas especificidades documentadas e as dúvidas e dificuldades identificadas. Pretendeu-se, com o desenvolvimento deste projecto e com a descrição feita sistematizar uma abordagem ao processo e alertar para o tipo de dificuldades inerentes à sua prossecução, sobretudo para quem se dispõem a fazê-lo pela primeira vez.

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Resumo I - O projecto “Piano e outros Instrumentos/orquestra” consiste na implementação do formato Piano e Orquestra em complemento às aulas individuais e aos ensaios de conjunto. O trabalho foi dirigido a um grupo de três alunos com idades de 9, 12 e 16 anos, do curso de Iniciação, Básico e Secundário da EMNSC (Escola de Música de Nossa Senhora do Cabo). Foram criados momentos distintos em cada fase. Estimulou-se o desenvolvimento de competências musicais e de estratégias metacognitivas visando a evolução dos alunos e a eficácia na realização do estudo individual. O Projecto foi criado com o objectivo de desenvolver as competências musicais, a motivação para realização do estudo individual e de grupo, o espírito e a audição crítica, o controlo dos factores psicológicos, a ansiedade, o aumento da autoconfiança, a aprendizagem, a melhoria da atitude positiva no momento da execução pública e o incremento do interesse pelas actividades relacionadas com a prática musical. A realização deste projecto visou analisar o grau de motivação, o desenvolvimento e a aquisição de competências musicais dos alunos de piano que frequentaram semanalmente aulas individuais, aulas extra de preparação, ensaios com Orquestra “Da Capo”, ensaios com a Orquestra Maior, duos com violoncelo e com canto. Um dos objectivos era comparar o grau de motivação e desenvolvimento dos alunos quando estudam obras nas aulas individuais que constituem o programa curricular e, por outro lado, quando o fazem em peças seleccionadas especificamente para este Projecto. Esta experiência visou proporcionar um conhecimento nos diversos domínios da música, uma visão diferente da funcionalidade do piano em conjunto com os outros instrumentos, a descoberta das sonoridades do piano contrastante e ao mesmo tempo, integrante com outros instrumentos, as formas de funcionamento dos instrumentos de corda, de sopro, dos assuntos relacionados com a afinação e pretendendo-se assim apurar o sentido de fazer parte integrante de um todo.

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The advent of Wireless Sensor Network (WSN) technologies is paving the way for a panoply of new ubiquitous computing applications, some of them with critical requirements. In the ART-WiSe framework, we are designing a two-tiered communication architecture for supporting real-time and reliable communications in WSNs. Within this context, we have been developing a test-bed application, for testing, validating and demonstrating our theoretical findings - a search&rescue/pursuit-evasion application. Basically, a WSN deployment is used to detect, localize and track a target robot and a station controls a rescuer/pursuer robot until it gets close enough to the target robot. This paper describes how this application was engineered, particularly focusing on the implementation of the localization mechanism.

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The ART-WiSe (Architecture for Real-Time communications in Wireless Sensor Networks) framework aims at the design of new communication architectures and mechanisms for time-sensitive Wireless Sensor Networks (WSNs). We adopted a two-tiered architecture where an overlay Wireless Local Area Network (Tier 2) serves as a backbone for a WSN (Tier 1), relying on existing standard communication protocols and commercial-off-the-shell (COTS) technologies – IEEE 802.15.4/ZigBee for Tier 1 and IEEE 802.11 for Tier 2. In this line, a test-bed application is being developed for assessing, validating and demonstrating the ART-WiSe architecture. A pursuit-evasion application was chosen since it fulfils a number of requirements, namely it is feasible and appealing and imposes some stress to the architecture in terms of timeliness. To develop the testbed based on the previously referred technologies, an implementation of the IEEE 8021.5.4/ZigBee protocols is being carried out, since there is no open source available to the community. This paper highlights some relevant aspects of the ART-WiSe architecture, provides some intuition on the protocol stack implementation and presents a general view over the envisaged test-bed application.

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This report describes the development of a Test-bed Application for the ART-WiSe Framework with the aim of providing a means of access, validate and demonstrate that architecture. The chosen application is a kind of pursuit-evasion game where a remote controlled robot, navigating through an area covered by wireless sensor network (WSN), is detected and continuously tracked by the WSN. Then a centralized control station takes the appropriate actions for a pursuit robot to chase and “capture” the intruder one. This kind of application imposes stringent timing requirements to the underlying communication infrastructure. It also involves interesting research problems in WSNs like tracking, localization, cooperation between nodes, energy concerns and mobility. Additionally, it can be easily ported into a real-world application. Surveillance or search and rescue operations are two examples where this kind of functionality can be applied. This is still a first approach on the test-bed application and this development effort will be continuously pushed forward until all the envisaged objectives for the Art-WiSe architecture become accomplished.

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Dissertation submitted to Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa for the achievement of Integrated Master´s degree in Industrial Management Engineering

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Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

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Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006

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Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale, Lyon, France August 23-26, 2007

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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 Gestão Estratégica das Relações Públicas.

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Projecto elaborado com vista à obtenção do Grau de Mestre em Teatro, área de especialização em Artes Performativas – Interpretação.

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This paper studies several topics related with the concept of “fractional” that are not directly related with Fractional Calculus, but can help the reader in pursuit new research directions. We introduce the concept of non-integer positional number systems, fractional sums, fractional powers of a square matrix, tolerant computing and FracSets, negative probabilities, fractional delay discrete-time linear systems, and fractional Fourier transform.

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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

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When China launched an anti-satellite (ASAT) weapon in January 2007 to destroy one of its inactive weather satellites, most reactions from academics and U.S. space experts focused on a potential military “space race” between the United States and China. Overlooked, however, is China’s growing role as global competitor on the non-military side of space. China’s space program goes far beyond military counterspace applications and manifests manned space aspirations, including lunar exploration. Its pursuit of both commercial and scientific international space ventures constitutes a small, yet growing, percentage of the global space launch and related satellite service industry. It also highlights China’s willingness to cooperate with nations far away from Asia for political and strategic purposes. These partnerships may constitute a challenge to the United States and enhance China’s “soft power” among key American allies and even in some regions traditionally dominated by U.S. influence (e.g., Latin America and Africa). Thus, an appropriate U.S. response may not lie in a “hard power” counterspace effort but instead in a revival of U.S. space outreach of the past, as well as implementation of more business-friendly export control policies.