49 resultados para GNSS, Ambiguity resolution, Regularization, Ill-posed problem, Success probability

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil

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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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Background - Image blurring in Full Field Digital Mammography (FFDM) is reported to be a problem within many UK breast screening units resulting in significant proportion of technical repeats/recalls. Our study investigates monitors of differing pixel resolution, and whether there is a difference in blurring detection between a 2.3 MP technical review monitor and a 5MP standard reporting monitor. Methods - Simulation software was created to induce different magnitudes of blur on 20 artifact free FFDM screening images. 120 blurred and non-blurred images were randomized and displayed on the 2.3 and 5MP monitors; they were reviewed by 28 trained observers. Monitors were calibrated to the DICOM Grayscale Standard Display Function. T-test was used to determine whether significant differences exist in blurring detection between the monitors. Results - The blurring detection rate on the 2.3MP monitor for 0.2, 0.4, 0.6, 0.8 and 1 mm blur was 46, 59, 66, 77and 78% respectively; and on the 5MP monitor 44, 70, 83 , 96 and 98%. All the non-motion images were identified correctly. A statistical difference (p <0.01) in the blurring detection rate between the two monitors was demonstrated. Conclusions - Given the results of this study and knowing that monitors as low as 1 MP are used in clinical practice, we speculate that technical recall/repeat rates because of blurring could be reduced if higher resolution monitors are used for technical review at the time of imaging. Further work is needed to determine monitor minimum specification for visual blurring detection.

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Dissertação apresentada à Escola Superior de Educação de Lisboa para Obtenção de Grau de Mestre em Ciências da Educação - Especialização em Supervisão da Educação

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This paper presents a new generalized solution for DC bus capacitors voltage balancing in back-to-back m level diode-clamped multilevel converters connecting AC networks. The solution is based on the DC bus average power flow and exploits the switching configuration redundancies. The proposed balancing solution is particularized for the back-to-back multilevel structure with m=5 levels. This back-to-back converter is studied working with bidirectional power flow, connecting an induction machine to the power grid.

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Formaldehyde was the first air pollutant, which already in the 1970s emerged as a specifically non-industrial indoor air quality problem. Yet formaldehyde remained an indoor air quality issue and the formaldehyde level in residential indoor air is among the highest of any indoor air contaminant. Formaldehyde concentrations in 4 different indoor settings (schools, office buildings, new dwellings and occupied dwellings) in Portugal were measured using Photo Ionization Detection (PID) equipment (11,7 eV lamps). All the settings presented results higher than the reference value proposed by Portuguese legislation. Furthermore, occupied dwellings showed 3 units with results above the reference. We could conclude that formaldehyde presence is a reality in monitored indoor settings. Concentration levels are higher than the Portuguese reference value for indoor settings and these can indicate health problems for occupants.

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A presente tese teve por base a identificação e resolução de um problema existente no tratamento de efluentes provenientes dos processos de tratamento de superfícies por galvanoplastia, na OGMA – Indústria Aeronáutica de Portugal S.A.. Observou-se a ocorrência, esporádica, de crómio hexavalente, (Cr (VI)), em valor superior ao valor limite de emissão (VLE). Os resultados foram monitorizados e os dados recolhidos no decorrer da actividade de tratamento de efluentes, durante o período de, aproximadamente, 5 anos (2006 a 2011). A recolha de resultados decorreu no âmbito da actividade profissional da mestranda, que, para além da responsabilidade técnica dos processos de galvanoplastia na empresa, é também responsável pelo suporte técnico ao processo de tratamento de efluentes resultantes da actividade de tratamento de superficies por processos de galvanoplastia. A empresa OGMA – Indústria Aeronáutica de Portugal S.A., é uma empresa de actividade aeronáutica dedicada à Fabricação e Manutenção de aeronaves, nomeadamente a prestação de serviços de Manutenção, Revisão e Modernização de, Aeronaves, Motores e Componentes, bem como Fabricação e Montagem de Aeroestruturas. Integrada na OGMA, S.A. encontra-se a área de tratamentos electroquímicos, onde são realizados processos de tratamento de materiais metálicos por electrodeposição, deposição química e conversão química. Desta actividade resulta uma quantidade considerável de efluentes líquidos que necessitam de tratamento adequado previamente à sua descarga em cursos de água. Devido ao tipo de contaminantes que estes efluentes possuem, o tratamento dos mesmos é realizado em várias etapas, passando pela oxidação de cianetos, a redução de cromatos e a neutralização. Posteriormente segue-se uma sedimentação e a remoção de lamas. De modo a garantir um controlo dos parâmetros de descarga dos efluentes tratados, de acordo com a legislação ambiental em vigor, o efluente obtido é analisado periodicamente em laboratório acreditado. Na perspectiva de solucionar o problema em questão, procedeu-se à realização de ensaios experimentais utilizando os efluentes provenientes dos tanques de reacção da redução de cromatos e da oxidação de cianetos da linha com cádmio, com especial incidência na variação dos intervalos de pH recomendados para cada uma das fases do tratamento de efluentes, e observação do comportamento das misturas em termos de presença de Cr (VI), quando sujeitos a variações de pH. Após análise dos dados disponíveis e realização de todos os ensaios, conclui-se que, o processo de oxidação de cianeto da linha com cádmio e o processo de redução de cromatos na mesma linha estão a funcionar adequadamente. Concluiu-se que o reaparecimento de Cr (VI) ocorre devido à existência de hipoclorito de sódio, em excesso, no tanque de oxidação de cianeto que, quando passa para o tanque de neutralização e entra em contacto com o efluente proveniente do tanque de redução de cromatos, oxida parte do crómio trivalente, (Cr (III)), existente, a Cr (VI). Para impedir a ocorrência deste fenómeno separou-se todo o efluente contendo crómio que passou a ser tratado na linha de tratamento de efluentes isenta de cádmio, não entrando assim em contacto com o efluente que contém hipoclorito não reagido, evitando a oxidação do Cr (III) a Cr (VI).

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Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.

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Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner-Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner-Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner-Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB: moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.

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Amorphous glass/ZnO-Al/p(a-Si:H)/i(a-Si:H)/n(a-Si1-xCx:H)/Al imagers with different n-layer resistivities were produced by plasma enhanced chemical vapour deposition technique (PE-CVD). An image is projected onto the sensing element and leads to spatially confined depletion regions that can be readout by scanning the photodiode with a low-power modulated laser beam. The essence of the scheme is the analog readout, and the absence of semiconductor arrays or electrode potential manipulations to transfer the information coming from the transducer. The influence of the intensity of the optical image projected onto the sensor surface is correlated with the sensor output characteristics (sensitivity, linearity blooming, resolution and signal-to-noise ratio) are analysed for different material compositions (0.5 < x < 1). The results show that the responsivity and the spatial resolution are limited by the conductivity of the doped layers. An enhancement of one order of magnitude in the image intensity signal and on the spatial resolution are achieved at 0.2 mW cm(-2) light flux by decreasing the n-layer conductivity by the same amount. A physical model supported by electrical simulation gives insight into the image-sensing technique used.

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Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.

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Exposure to certain fungi can cause human illness. Fungi cause adverse human health effects through three specific mechanisms: generation of a harmful immune response (e.g., allergy or hypersensitivity pneumonitis); direct infection by the fungal organism; by toxic-irritant effects from mold byproducts, such as mycotoxins. In Portugal there is an increasingly industry of large facilities that produce whole chickens for domestic consumption and only few investigations have reported on fungal contamination of the poultry litter. The material used for poultry litter is varied but normally can be constitute by: pine shavings; sawdust of eucalyptus; other types of wood; peanut; coffee; sugar cane; straw; hay; grass; paper processed. Litter is one of the most contributive factors to fungal contamination in poultries. Spreading litter is one of the tasks that normally involve higher exposure of the poultry workers to dust, fungi and their metabolites, such as VOC’s and mycotoxins. After being used and removed from poultries, litter is ploughed into agricultural soils, being this practice potentially dangerous for the soil environment, as well for both humans and animals. The goal of this study was to characterize litter’s fungal contamination and also to report the incidence of keratinophilic and toxigenic fungi.

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Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular. Área de especialização: Intervenção Cardiovascular.

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Lidar com as problemáticas da saúde, implica um domínio dos processos cognitivos (raciocínio, resolução de problemas e tomada de decisão) e de desempenhos práticos, o que obriga a afectação de um conjunto de atitudes e comportamentos específicos. Este estudo, implementou e avaliou o impacto de experiências pedagógicas desenvolvidas com os estudantes da unidade curricular Radiologia do Sistema Nervoso (RSN) da Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL). Aplicaram-se metodologias de ensino mistas (presenciais e virtuais) utilizadas na leccionação teórica e prática no ano curricular 2008/2009. Para a avaliação do perfil de aprendizagem dos estudantes foi aplicado o método de Honey & Munford e para a avaliação e monitorização dos conhecimentos aplicaram-se check list baseadas nos conteúdos programáticos. A monitorização das ferramentas da plataforma moodle complementaram a restante informação. Verificou-se uma progressão de aprendizagem positiva para um grupo de estudantes maioritariamente do estilo reflexivo (média=10,6 estudantes). As conclusões apontaram para um impacto positivo quanto à aplicação das metodologias híbridas com maior índice de sucesso para a metodologia assíncrona. Verificou-se também mais flexibilidade no acesso aos conteúdos porém com algumas limitações tais como residência inicial por parte dos estudantes, maior carga de trabalho para os docentes, falta de terminais para acesso à plataforma e pouca experiência de todos os envolvidos no domínio e manipulação da plataforma. ABSTRACT - This study focused on the role of cognitive processes (reasoning, problem solving and decision making) and performance practice in the formation of attitudes and behaviours relating to health issues. It was conducted to evaluate the effects of pedagogical experiences on students who participated in the course in radiography in the Nervous System Imaging Unit (RSN) of the Lisbon Health School of Technology. Mixed (face-to-face and virtual) teaching methodologies were used in theory and practice sessions. Honey and Munford’s method was used to evaluate the learning profile of students. To monitor and evaluate students’ knowledge acquisition, check lists based on program topics were applied. Other information was supplied through the learning platform of Moodle. The student group with mostly a reflective learning style increased their knowledge. The asynchronous method was shown to produce a higher success rate and more flexibility in accessing content but also registered some limitations such as resistance by students, increased workload for teachers, lack of access to the platform and inexperience of all involved in handling the platform.

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Chromium dioxide (CrO2) has been extensively used in the magnetic recording industry. However, it is its ferromagnetic half-metallic nature that has more recently attracted much attention, primarily for the development of spintronic devices. CrO2 is the only stoichiometric binary oxide theoretically predicted to be fully spin polarized at the Fermi level. It presents a Curie temperature of ∼ 396 K, i.e. well above room temperature, and a magnetic moment of 2 mB per formula unit. However an antiferromagnetic native insulating layer of Cr2O3 is always present on the CrO2 surface which enhances the CrO2 magnetoresistance and might be used as a barrier in magnetic tunnel junctions.