965 resultados para Astronautics, Military.
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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Trabalho de projecto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação
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O presente projeto enquadra-se na área das redes de sensores sem fios, onde o seu crescente desenvolvimento permite aplicar esta tecnologia em diversas áreas, como por exemplo, na monitorização ambiental, utilização militar, domótica, saúde, entre outras. Uma rede de sensores sem fios consiste em diversos nós dispersos num campo de aplicação onde procedem à recolha de dados do ambiente em que estão inseridos, como o valor de uma temperatura, humidade ou outra grandeza física, e os transmitem para uma estação base onde podem ser monitorizados. Tendo a área da saúde uma importância significativa, este projeto focalizou-se na mesma. O projeto apresentado nesta dissertação teve como principal objetivo o desenvolvimento de uma rede de sensores sem fios, em que dois nós procedam à aquisição da temperatura corporal de uma pessoa em dois locais distintos, para posterior envio da mesma para os restantes nós da rede, onde será apresentada em estações de monitorização. Este projeto foi desenvolvido baseado num recente protocolo de redes sem fios, nomeadamente o protocolo ANTTM. Assim sendo, em primeiro lugar, serão abordados neste relatório os objetivos e a contextualização deste projeto. Em seguida, será apresentada uma comparação sobre alguns aspetos de algumas tecnologias de comunicações sem fios, nomeadamente o ZigBee, Bluetooth e ANT. Devido ao fato da tecnologia ANT ser a escolhida para o desenvolvimento deste projeto, será também apresentado um estudo mais detalhado sobre o mesmo. Depois, será apresentado o desenvolvimento e implementações efetuadas, e por último serão apresentadas as conclusões técnicas e pessoais que este projeto permitiu obter.
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Based on the paper presented at the International Conference “Autonomous Systems: inter-relations of technical and societal issues”, organized by IET with the support of the Portuguese-German collaboration project on “Technology Assessment of Autonomous Robotics” (DAAD/CRUP) at FCT-UNL, Biblioteca da UNL, Campus de Caparica on 5-6 November 2009.
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RESUMO: Desde 1976 que as Forças Armadas desenvolvem acções de prevenção do consumo de drogas e álcool. Na década de 80 foi criada capacidade laboratorial e deu-se início a um programa de rastreios toxicológicos. No quinquénio 2001 a 2005, as proporções de resultados positivos, associando todos os tipos de rastreio, variaram entre 3,7% e 1,5%. De Outubro de 2006 a Julho de 2007 realizou-se um estudo analítico transversal, para estimar a prevalência do consumo de drogas (canabinóides, opiáceos, cocaína e anfetaminas) num dos Ramos das Forças Armadas, com base nos despistes realizados pelo seu laboratório. Foi utilizada uma amostra aleatória simples de 1039 militares, profissionais (QP) e contratados (RC), no activo e de ambos os sexos. Desde a nomeação dos militares a rastrear, passando pela cadeia de custódia das amostras até à obtenção do resultado foi utilizado apoio informático específico. O processo de pesquisa utilizou duas técnicas de triagem por imunoensaio e tecnologia de confirmação por GC/MS, de acordo com as recomendações europeias, permitindo estabelecer uma metodologia standard para organizações e empresas. A prevalência estimada, de consumidores de droga, foi de 3,8/1.000, para um erro de 0,37%. O número de casos registado (4) não permitiu a utilização de testes estatísticos que conduzissem à identificação de características determinantes da positividade, mas não deixou de revelar aspectos inesperados. A observação de séries de casos e a realização regular de estudos epidemiológicos, que ajudem a redefinir grupos alvo e a perceber a dimensão, as determinantes e as consequências do consumo de drogas é sugerida, em conclusão.--------------------------------------- RÉSUMÉ: Depuis 1976, les Forces Armées mettent au point des mesures visant à prévenir la consommation de drogues et d'alcool. En 1980, fut créé capacité laboratoriel et ont ensuite commencé un programme de dépistage toxicologique. Au cours des cinq années allant de 2001 à 2005, les proportions de consommateurs, impliquant tous les types de dépistage, allaient de 3,7% à 1,5 %. D'octobre 2006 à juillet 2007, une étude analytique transversale a été organisée pour évaluer la prévalence de l’usage de drogues (cannabis, opiacés, cocaïne et amphétamines) dans une branche de les Forces Armées, basée sur les dépistages faites par un laboratoire militaire, à l'aide d'un échantillon aléatoire de 1039 militaires, professionnels (QP) et sous contract (RC), à l’actif et des deux sexes. Tout au long du procès, de la nomination des donneurs, en passant par la chaine de garde des échantillons, jusqu’à obtention du résultat, il fut employé un appui informatique sécurisé. Le processus de recherche employa deux techniques de tri par imunoessay et la technologie de confirmation GC/MS, selon les recommandations européennes, permettant d'établir une méthodologie standard pour les organisations et les entreprises. La prévalence estimée fut de 3,8/1.000 pour une marge d’erreur de 0,37%. Le nombre de cas enregistrés (4) n'autorise pas l'utilisation de testes statistiques de menant à l'identification de caractéristiques déterminant de la positivité, mais il permet à révéler des aspects inattendus. L'observation de séries de cas et la tenue régulière d’études épidémiologiques, qui contribuent à redéfinir les groupes cibles et de comprendre l'ampleur, les déterminants et les conséquences de l'usage de drogues, est suggéré, en fin de compte.--------------------------------------- ABSTRACT: Since 1976, the Armed Forces, have been developing measures to prevent the use of drugs and alcohol. In 1980, was created laboratory facility which then started a program of toxicological screenings. In the five years running from 2001 to 2005, the proportions of consumers, involving all types of screening, ranged from 3,7% to 1,5%. From October 2006 to July 2007, a cross-sectional study was held to estimate the prevalence of drug use (cannabinoids, opiates, cocaine and amphetamines) in one branch of the Portuguese Armed Forces, based on laboratory screenings, using a random sample of 1039 military, professional (QP) and enlisted (RC), active-duty and of both sexes. Specific computer support was used all the way, from the appointment, including the chain of custody of samples, to the obtaining of the result. The process of search used two techniques for sorting by immunoassay and confirmation technology GC/MS, according to European recommendations, allowing to establish a standard methodology for organizations and companies. The estimated prevalence of drug users was 3.8/1.000 for a 0.37% error (95% confidence interval). The number of cases registered (4) does not permit use of statistical testing leading to the identification of characteristics weighing in the establishing to extrapolate for the population, but it allows revealing unexpected aspects. The observation of series of cases and the regular holding of epidemiological studies, which help redefine target groups and to understand the extent, the determinants and consequences of drug use, is suggested, in conclusion.
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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 Publicidade e Marketing.
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Different anthropogenic sources of metals can result from agricultural, industrial, military, mining and urban activities that contribute to environmental pollution. Plants can be grown for phytoremediation to remove or stabilize contaminants in water and soil. Copper (Cu), manganese (Mn) and zinc (Zn) are trace essential metals for plants, although their role in homeostasis in plants must be strictly regulated to avoid toxicity. In this review, we summarize the processes involved in the bioavailability, uptake, transport and storage of Cu, Mn and Zn in plants. The efficiency of phytoremediation depends on several factors including metal bioavailability and plant uptake, translocation and tolerance mechanisms. Soil parameters, such as clay fraction, organic matter content, oxidation state, pH, redox potential, aeration, and the presence of specific organisms, play fundamental roles in the uptake of trace essential metals. Key processes in the metal homeostasis network in plants have been identified. Membrane transporters involved in the acquisition, transport and storage of trace essential metals are reviewed. Recent advances in understanding the biochemical and molecular mechanisms of Cu, Mn and Zn hyperaccumulation are described. The use of plant-bacteria associations, plant-fungi associations and genetic engineering has opened a new range of opportunities to improve the efficiency of phytoremediation. The main directions for future research are proposed from the investigation of published results.
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In this paper the history of 115 recruits that had bathed simultaneously in streams contaminated with Schistosoma mansoni, during military maneuvers, is reported. Thirty four of the infected patients presented the initial phase of the infection diagnosed through epidemiologic, clinical and laboratorial parameters. Three out of the 34 patients did not reveal the clinical picture of the infection, thus being considered representatives of the non-apparent form of the disease. Differences between the intensity of blood eosinophilia, the area of immediate cutaneous reaction and the number of Schistosoma eggs eliminated in the stools proved not to be statistically significant (p>0.05) when the non-apparent and acute cases of schistosomiasis were compared. These cases actually may be considered evidences of the non-apparent form hitherto merely taken for granted in the literature.
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Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações
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European Master’s Degree in Human Rights and Democratisation Academic Year 2005/2006
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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. 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. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.