Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Service-oriented mobility of java code in web services-based architectures

Dissertação apresentada na Faculdade de Ciências e Tecnologias da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Estimation of rotational frequency response functions

As it is widely known, in structural dynamic applications, ranging from structural coupling to model updating, the incompatibility between measured and simulated data is inevitable, due to the problem of coordinate incompleteness. Usually, the experimental data from conventional vibration testing is collected at a few translational degrees of freedom (DOF) due to applied forces, using hammer or shaker exciters, over a limited frequency range. Hence, one can only measure a portion of the receptance matrix, few columns, related to the forced DOFs, and rows, related to the measured DOFs. In contrast, by finite element modeling, one can obtain a full data set, both in terms of DOFs and identified modes. Over the years, several model reduction techniques have been proposed, as well as data expansion ones. However, the latter are significantly fewer and the demand for efficient techniques is still an issue. In this work, one proposes a technique for expanding measured frequency response functions (FRF) over the entire set of DOFs. This technique is based upon a modified Kidder's method and the principle of reciprocity, and it avoids the need for modal identification, as it uses the measured FRFs directly. In order to illustrate the performance of the proposed technique, a set of simulated experimental translational FRFs is taken as reference to estimate rotational FRFs, including those that are due to applied moments.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Evolution and biogenesis of microtubule-derived structures

Dissertação apresentada para obtenção do grau de Doutor em Biologia Celular pelo Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

System-on-chip field-programmable gate array design for onboard real-time hyperspectral unmixing

Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

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.

Liaisons dangereuses, conservation of modern and contemporary art: a study of the synthetic binding media in Portugal

Dissertação apresentada para obtenção do Grau de Doutor em Conservação e Restauro, especialidade de Ciências da Conservação, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Cyclophosphamide effect on paracoccidioidomycosis in the rat

Paracoccidioidomycosis is an endemic fungal disease widely distributed throughout Latin America. The potent immunosuppressor cyclophosphamide (CY) has been used to modulate host immune response to Paracoccidioides brasiliensis in an experimental model. Inbred male Buffalo/Sim rats weighing 250-300 g were inoculated with 5 x 10(6) P. brasiliensis cells of the yeast phase form by intracardiac route. One group of animals was treated with 20 mg/kg body weight at days +4, +5, +6, +7, +11 and +12 post-infection (pi.), while a control group was infected alone. No mortality was recorded in either group. Treated rats presented: a) a decrease in granuloma size, which contained less fungal cells; b) a lack of specific antibodies up to 35 days pi., and c) a significant increase in the footpad swelling test (DTH) against paracoccidioidin. Splenic cell transfer from CY-treated P. brasiliensis-infected donors to recipients infected alone led to a significant increase in DTH response in the latter versus untreated infected controls. Likewise, in treated infected recipients transferred with untreated infected donor spleen cells, footpad swelling proved greater than in controls. Thus, it would seem that each successive suppressor T lymphocyte subset belonging to the respective cascade may be sensitive to repeated CY doses administered up to 12 days pi.. Alternatively, such CY schedule may induce the appearance of a T cell population capable of amplifying DTH response.

Long term follow-up and patterns of response of ALT in patients with chronic hepatitis NANB/C treated with recombinant interferon-alpha

The response to interferon treatment in chronic hepatitis NANB/C has usually been classified as complete, partial or absent, according to the behavior of serum alanine aminotransferase (ALT). However, a more detailed observation of the enzymatic activity has shown that the patterns may be more complex. The aim of this study was to describe the long term follow-up and patterns of ALT response in patients with chronic hepatitis NANB/C treated with recombinant interferon-alpha. A follow-up of 6 months or more after interferon-a was achieved in 44 patients. We have classified the serum ALT responses into six patterns and the observed frequencies were as follows: I. Long term response = 9 (20.5%); II. Normalization followed by persistent relapse after IFN = 7 (15.9%); III. Normalization with transient relapse = 5 (11.9%); IV. Temporary normalization and relapse during IFN = 4 (9.1%); V. Partial response (more than 50% of ALT decrease) = 7 (15.9%); VI. No response = 12 (27.3%). In conclusion, ALT patterns vary widely during and after IFN treatment and can be classified in at least 6 types.

A middleware for service oriented computing in dynamic environments

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Desenvolvimento de Métodos de Extração de Resíduos de Antimicrobianos e Quantificação em Amostras Alimentares

O leite é um alimento complexo, pela sua composição rico em água, proteínas, lípidos, vitaminas e minerais. Devido ao seu alto valor nutricional é fundamental para a amamentação de crianças e animais em crescimento, pois fornece componentes fundamentais para o desenvolvimento e manutenção da saúde. Os antimicrobianos são amplamente utilizados como uma medida terapêutica no tratamento de infeções bacterianas, profilaxia e como promotores de crescimento (aditivos). A presença de resíduos de antimicrobianos no leite pode representar riscos para a saúde humana, como reações alérgicas em indivíduos hipersensíveis e resistências. Os objetivos deste estudo são o desenvolvimento de novos métodos de limpeza e de pré-concentração para amostras de leite, por meio de extração em fase sólida (SPE), com a finalidade de realizar uma melhor identificação e quantificação de antimicrobiana por Cromatografia Líquida de Alta Performance (HPLC). Todos os métodos desenvolvidos são de fácil execução, com taxas de recuperação dos agentes antimicrobianos viáveis, com uma percentagem de recuperação a partir de 85%. O método cromatográfico utilizado para a deteção e quantificação (HPLC-DAD) têm os limites de deteção (LD) entre 2.43ng / mL e 1.62ng / mL e os limites de quantificação (LQ) entre 7,36 ng / mL e 4.92 ng / mL, o que significa este método vai de encontro às diretrizes estipuladas pela União Europeia para os agentes antimicrobianos estudados. A combinação dos métodos propostos de limpeza e pré-concentração por SPE e multirresíduo por HPLC-DAD permite, por conseguinte, a deteção e quantificação de resíduos de antibióticos no leite, tornando esta uma alternativa importante e útil no processo de controlo de qualidade para a indústria de alimentos e outras área.

Intestinal spirochetosis: first cases reported in Brazil and the use of immunohistochemistry as an aid in histopathological diagnosis

Colonization of the colon and rectum by intestinal spirochetes is detected for the first time in Brazil in 4 of 282 (1.41%) patients who had undergone sigmoidoscopy and/or colonoscopy with a histopathological diagnosis of chronic non specific-colitis. This frequency is probably understimated, since surgically obtained specimens were not considered in the present study. Histopathological diagnosis was performed using routine stains like hematoxylin-eosin which showed the typical, of 3-µm thick hematoxyphilic fringe on the brush border of the surface epithelium, and by silver stains like the Warthin-Starry stain. Immunohistochemical procedures using two, polyclonal, primary antibodies, one against Treponema pallidum and the other against Leptospira interrogans serovar copenhageni serogroup Icterohaemorrhagiae cross-reacted with spirochetal antigen/s producing a marked contrast of the fringe over the colonic epithelium, preserving the spiral-shaped morphology of the parasite. In one case with marked diarrhea, immunohistochemistry detected spirochetal antigen/s within a cell in an intestinal crypt, thus demonstrating that the infection can be more widely disseminated than suspected using routine stains. Immunohistochemical procedures, thus, greatly facilitate the histological diagnosis of intestinal spirochetosis and may contribute to a better understanding of the pathogenesis of the disease. Transmission and scanning electron microscopy performed in one case showed that the spirochete closely resembled the species designated as Brachyspira aalborgi.

Effects of ivermectin on Culex quinquefasciatus larvae

The effects of ivermectin, a semi-synthetic drug widely used for treatment of livestock parasitic diseases, were observed on Culex quinquefasciatus larvae. Toxic effects and mortality evaluation were carried out after 5, 15, 30 and 60 minutes of exposure to 1, 5 or 10 ppm of ivermectin solutions. Observations were made 24 and 48 hours after the beginning of the experiment, and loss of mobility, progressive paralysis and high mortality of larvae were recorded. The observed effects of ivermectin on the mosquito larvae is probably correlated with chloride channel activation on cell membranes.