Drawing and use of auxiliary projection nets (the program STEGRAPH)

The development of an algorithm for the construction of auxiliary projection nets (conform, equivalent and orthographic), in the equatorial and polar versions, is presented. The algorithm for the drawing of the "IGAREA 220" counting net (ALYES & MENDES, 1972), is also presented. Those algorithms are the base of STEGRAPH program (vers. 2.0), for MS-DOS computers, which has other applications.

Optimal brake specific fuel consumption trajectory for stand-alone variable speed Diesel Gen-Set

Energy efficiency plays an important role to the CO2 emissions reduction, combating climate change and improving the competitiveness of the economy. The problem presented here is related to the use of stand-alone diesel gen-sets and its high specific fuel consumptions when operates at low loads. The variable speed gen-set concept is explained as an energy-saving solution to improve this system efficiency. This paper details how an optimum fuel consumption trajectory based on experimentally Diesel engine power map is obtained.

Saúde mental, qualidade de vida e acesso aos cuidados de saúde na comunidade brasileira de Lisboa

Introdução: A utilização de serviços de saúde tem implicações importantes para o estado de saúde das populações. As políticas de imigração adoptadas nos países de destino têm influência no estado de saúde das comunidades imigrantes. Políticas que limitam o acesso de imigrantes aos cuidados de saúde aumentarão a vulnerabilidade e os riscos na saúde. Apesar da imigração promover uma série de rupturas na vida do sujeito, migrar, por si só, não pode ser considerado como factor de risco no âmbito da saúde e da saúde mental. O peso dos determinantes socioeconómicos tem ganho relevância no estudo das migrações, estado de saúde geral e mental. Isto porque, em geral, os imigrantes estão em situação mais precária do que a população autóctone. O estatuto socioeconómico baixo, as condições precárias de habitação e de trabalho, a falta de suporte social e a irregularidade jurídica são indicadores de risco acrescido para a saúde mental. Neste sentido é um desafio de monta os governos estabelecerem medidas sustentadas e, simultaneamente, integradoras dos imigrantes. Em Portugal, considera-se que há escassez de estudos relacionados com a área das migrações e da saúde.Metodologia: Estudo exploratório, descritivo e transversal. A finalidade foi a de identificar o estado de saúde, saúde mental e qualidade de vida da comunidade brasileira residente em Lisboa e o seu acesso aos serviços de saúde. Este estudo teve como principais objectivos a caracterização sociodemográfica, a identificação de variáveis inerentes ao processo migratório, a identificação da auto-apreciação do estado de saúde, a caracterização do acesso aos cuidados de saúde, a identificação do grupo em provável sofrimento psicológico, a comparação entre os resultados dos imigrantes juridicamente regulares e irregulares e a comparação entre a população imigrante e a população portuguesa. Inicialmente, foi prevista a utilização da técnica de amostragem de propagação geométrica ou snowball, pois a amostra tornar-se-ia maior à medida que os próprios inquiridos identificam outros potenciais respondentes. Ao longo do estudo, a metodologia inicial mostrou-se insuficiente para estabelecer uma amostra mais representativa dos imigrantes juridicamente irregulares. Para este feito, foi utilizada a metodologia de amostragem por conveniência e o local escolhido para a recolha da amostra foi o Consulado do Brasil em Lisboa. O instrumento de recolha de dados empregue baseou-se no questionário utilizado no 4º Inquérito Nacional de Saúde. O MHI-5 (Mental Health Index 5) é um instrumento de saúde mental e é parte integrante do inquérito, sendo recomendado pela Organização Mundial de Saúde. Consta de cinco itens relativos à saúde mental e os resultados são classificados através de um indicador que mede a existência de provável sofrimento psicológico. Foram incluídos no estudo 213 brasileiros. De seguida, procedeu-se ao tratamento estatístico dos dados. Resultados: A população inquirida é jovem, a maior parte tem entre 18 e 44 anos. As mulheres representam mais de metade da amostra. A taxa de actividade é elevada e a taxa de desemprego é similar à nacional. A inserção laboral prioritária é nos segmentos pouco qualificados ou de semi-qualificação. Aproximadamente um terço dos inquiridos afirmou ser beneficiário do Sistema Nacional de Saúde. A autoapreciação do estado de saúde é classificada como bastante positiva, assim como a qualidade de vida. O provável sofrimento psicológico, definido no MHI-5 pelo ponto de corte no score 52, atinge 23,3% dos participantes. Os homens apresentam melhores resultados do que as mulheres. Além disso, para os valores mais baixos no MHI-5 foram encontradas relações com as longas jornadas de trabalho e o diagnóstico de doença crónica.Discussão: O presente estudo apresenta limitações em relação à dimensão da amostra e à provável existência de enviesamento pela ausência de aleatorização. Apesar da legislação portuguesa garantir o acesso aos serviços de saúde e garantir a equidade no caso dos imigrantes que fazem descontos para a Segurança Social, apenas um terço referiu ser beneficiário do Sistema Nacional de Saúde. Este dado pode ser justificado por factores como o cumprimento da lei por alguns serviços e, também, pela falta de conhecimento da legislação e da forma de funcionamento do Serviço Nacional de Saúde por parte dos imigrantes. O facto das mulheres representarem o maior grupo em provável sofrimento psicológico é consistente com a literatura. As hipóteses levantadas para explicar este resultado podem ser agrupadas em: artefactos metodológicos, causalidade biológica e determinação social. Em relação ao instrumento, é possível que o MHI-5 se comporte de forma diferente no que diz respeito ao género.-------------------------------------------Introduction: The utilization of health services has important implications for the health state of the populations. The immigration policies adopted in the destiny countries are going to influence the health state of immigrant communities. Policies that limit the access of immigrants to health care are going to increase the vulnerability and the risk factor in health. Although immigration promotes several disruptive actions in ones life, migrating, on its own, cannot be considered as a risk factor for health and mental health. The preponderance of the socioeconomic factors has gained relevance in the study of migrations and also in the study of general health state and mental health. This happens because, in general, immigrants are in a more unfavorable situation compared with the destiny country population. The low socioeconomic status, the poor working and housing conditions, the lack of social support and the juridical irregularity are indicators of the incremented risk to mental health. Therefore, it is a major challenge for governments to find sustainable, and simultaneously, integrative measures for the immigrants. The studies related with the migrations and health in Portugal were considered to be few.Methods: It is an exploratory, descriptive and transversal study. The purpose is to identify the health state, mental health, quality of life and the access to health care of the Brazilian community resident in Lisbon. In addition, this study has as main goals the sociodemographic characterization, the variables identification inherent to the migrating process, the identification of the self-appreciation of health state, the characterization of the access to health care, the identification of the group in probable psychological suffer, the comparison between the results of regular and irregular immigrants and the comparison between the immigrant population and the Portuguese population. Initially it was predicted the utilization of the geometric propagation or “snowball”, as sampling technique, because the sample becomes larger as one answerer identify other potential answering persons. Along with the study, the methodology has shown insufficient to establish a more representative sample of the irregular immigrants. For this latter case, it was used a convenient sample methodology and the place chosen for the sample gathering was the “Consulate of Brazil in Lisbon”. The instrument was based in the questionnaire used in the “4th National Health Inquiry”. The MHI-5 (Mental Health Index 5) is a mental health instrument which is part of the enquiry and it is recommended by the World Health Organization. There are five items related to mental health and the results are classified through an indicator which measures the existence of a probable psychological suffer. It were included 213 Brazilian in the study. After, the statistical treatment of the data took place.Results: The answering population is young and the majority is between the 18 and 44 years of age. The women represent more than one half of the sample. The activity rate is high and the unemployment rate is similar to the national one. The priority labor insertion is in the few qualified or of semi-qualification segments. Approximately, one third of the answering people has stated to be beneficiary of the National Health System. The self-appreciation of the health state as well as the quality of life are classified as fairly positive ones. The probable psychological suffer, as defined in the MHI-5 through the cut point in the score below or equal to 52, reaches 23,3% of the sample population. Men show the better results than women. Further, for the lower values of MHI-5 it was found a relation with the long work periods and chronic disease diagnostic. Discussion: The present study evidences limitations in relation to the sample dimension and in relation to the existence of biases due to the lack of randomness. Although the Portuguese legislation guarantees the access to health services and the equality in the cases of the immigrants that do their Social Security discounts, only one third has mentioned to be beneficiary of the National Health System. This can be justified by several facts such as the non-fulfillment of law by some national services or the lack of knowledge of the legislation or the functioning process of the National Health System. Women representing the bigger group in probable psychological suffer has been coherent with the literature review. The hypothesis set to explain this result might be grouped in: methodological artifacts, biologic cause and social determination. In relation to the instrument used, it may be that MHI-5 behaves in a different way in respect to gender.

Materials selection for a set of multiple parts considering manufacturing costs and weight reduction with structural isoperformance using direct multisearch optimization

Materials selection is a matter of great importance to engineering design and software tools are valuable to inform decisions in the early stages of product development. However, when a set of alternative materials is available for the different parts a product is made of, the question of what optimal material mix to choose for a group of parts is not trivial. The engineer/designer therefore goes about this in a part-by-part procedure. Optimizing each part per se can lead to a global sub-optimal solution from the product point of view. An optimization procedure to deal with products with multiple parts, each with discrete design variables, and able to determine the optimal solution assuming different objectives is therefore needed. To solve this multiobjective optimization problem, a new routine based on Direct MultiSearch (DMS) algorithm is created. Results from the Pareto front can help the designer to align his/hers materials selection for a complete set of materials with product attribute objectives, depending on the relative importance of each objective.

Welfare regimes, work-life balance public policies and gender equality - parental leaves in Portugal and Sweden

Comunicação apresentada na "European Sociological Association Conference" em Lisboa de 2 a 5 de Setembro de 2009.

Promotion of gender equality and social inclusion of unemployed groups in Portuguese European Founds Frameworks (1990-2007): overview and critical reflection

Comunicação apresentada no 38º Congresso Mundial do Instituto Internacional de Sociologia, em Budapeste, Hungria, de 26 a 30 de Junho de 2008.

Study of a 9th century silver earrings set from Mikulčice: corrosion, conservation and maintenance

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro

Unmixing hyperspectral data: independent and dependent component analysis

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.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

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.

Constraint-based modeling of minimum set covering: application to species differentation

Work presented in the context of the European Master in Computational Logics, as partial requisit for the graduation as Master in Computational Logics

Database repairs with answer set programming

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Avaliação da Morbilidade e Mortalidade no Serviço de Ginecologia da Maternidade Dr. Alfredo da Costa. Jan/Set 1991

Foram avaliados todos os internamentos no Serviço de Ginecologia da MAC de 2 de Janeiro a 19 de Setembro de 1991. O critério de selecção baseou-se no registo de morbilidade intra-operatória e no prolongamento de tempo de internamento. Foram estudados os dados relativos à idade, factores de risco associados, risco anestésico, tipo de intervenção cirúrgica, tempo operatório, tipo de complicações e média de tempo de internamento. Verificou-se uma morbilidade global de 5,6%, tendo-se constatado uma maior incidência de complicações no grupo das histerectomias abdominais (16,8%). Nos casos com morbilidade 72% apresentavam um ou mais factores de risco associados. Ocorreram 5 lesões de órgão (0,73%), 33 complicações pós-operatórias (4,8%) e 7 reintervenções (1%). A média de internamento neste grupo de doentes foi de 11 dias.

EDP InovCity pilot study proposal: A set-top box interface

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Calibration, selection and mosaicing of SMART-1 AMIE images

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Reconceptualising public spaces of (IN)equality: sensing and creating layers of visibility

Tese apresentada para cumprimento dos requisitos necessários à obtenção do grau de Doutor em Geografia e Planeamento Territorial - Especialidade: Geografia Humana