921 resultados para Pattern recognition multivariate SIMCA


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The use of different kinds of nonlinear filtering in a joint transform correlator are studied and compared. The study is divided into two parts, one corresponding to object space and the second to the Fourier domain of the joint power spectrum. In the first part, phase and inverse filters are computed; their inverse Fourier transforms are also computed, thereby becoming the reference in the object space. In the Fourier space, the binarization of the power spectrum is realized and compared with a new procedure for removing the spatial envelope. All cases are simulated and experimentally implemented by a compact joint transform correlator.

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An algorithm for computing correlation filters based on synthetic discriminant functions that can be displayed on current spatial light modulators is presented. The procedure is nondivergent, computationally feasible, and capable of producing multiple solutions, thus overcoming some of the pitfalls of previous methods.

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We present a method to detect patterns in defocused scenes by means of a joint transform correlator. We describe analytically the correlation plane, and we also introduce an original procedure to recognize the target by postprocessing the correlation plane. The performance of the methodology when the defocused images are corrupted by additive noise is also considered.

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Pathogenicity of Chlamydia and Chlamydia-related bacteria could be partially mediated by an enhanced activation of the innate immune response. The study of this host pathogen interaction has proved challenging due to the restricted in vitro growth of these strict intracellular bacteria and the lack of genetic tools to manipulate their genomes. Despite these difficulties, the interactions of Chlamydiales with the innate immune cells and their effectors have been studied thoroughly. This review aims to point out the role of pattern recognition receptors and signal molecules (cytokines, reactive oxygen species) of the innate immune response in the pathogenesis of chlamydial infection. Besides inducing clearance of the bacteria, some of these effectors may be used by the Chlamydia to establish chronic infections or to spread. Thus, the induced innate immune response seems to be variable depending on the species and/or the serovar, making the pattern more complex. It remains crucial to determine the common players of the innate immune response in order to help define new treatment strategies and to develop effective vaccines. The excellent growth in phagocytic cells of some Chlamydia-related organisms such as Waddlia chondrophila supports their use as model organisms to study conserved features important for interactions between the innate immunity and Chlamydia.

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We report the study of the influence of optical aberrations in a joint-transform correlator: The wave aberration of the optical system is computed from data obtained by ray tracing. Three situations are explored: We consider the aberration only in the first diffraction stage (generation of power spectrum), then only in the second (transformation of the power spectrum into correlation), and finally in both stages simultaneously. The results show that the quality of the correlation is determined mostly by the aberrations of the first diffraction stage and that we can optimize the setup by moving the cameras along the optical axis to a suitable position. The good agreement between the predicted data and the experimental results shows that the method explains well the behavior of optical diffraction systems when aberrations are taken into account.

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En este artículo se presenta un estudio cuya finalidad es analizar diferentes aspectos de la utilización de pantallas de cristal líquido, extraídas de un videoproyector, en montajes de reconocimiento de formas por correlación. Se analizan las condiciones de funcionamiento de las pantallas y sus posibles modos de configuración. Se estudian dos tipos de filtros de correlación, el filtro adaptado clásico y el de sólo fase, así como la manera de codificarlos en las pantallas. Finalmente, se presentan los resultados de una serie de realizaciones experimentales utilizando un correlador de VanderLugt y diferentes configuraciones de las pantallas. De todo ello se deducen las condiciones óptimas de funcionamiento del sistema.

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Over the past three decades, pedotransfer functions (PTFs) have been widely used by soil scientists to estimate soils properties in temperate regions in response to the lack of soil data for these regions. Several authors indicated that little effort has been dedicated to the prediction of soil properties in the humid tropics, where the need for soil property information is of even greater priority. The aim of this paper is to provide an up-to-date repository of past and recently published articles as well as papers from proceedings of events dealing with water-retention PTFs for soils of the humid tropics. Of the 35 publications found in the literature on PTFs for prediction of water retention of soils of the humid tropics, 91 % of the PTFs are based on an empirical approach, and only 9 % are based on a semi-physical approach. Of the empirical PTFs, 97 % are continuous, and 3 % (one) is a class PTF; of the empirical PTFs, 97 % are based on multiple linear and polynomial regression of n th order techniques, and 3 % (one) is based on the k-Nearest Neighbor approach; 84 % of the continuous PTFs are point-based, and 16 % are parameter-based; 97 % of the continuous PTFs are equation-based PTFs, and 3 % (one) is based on pattern recognition. Additionally, it was found that 26 % of the tropical water-retention PTFs were developed for soils in Brazil, 26 % for soils in India, 11 % for soils in other countries in America, and 11 % for soils in other countries in Africa.

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Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

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Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.

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Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

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Although increasing our knowledge of the properties of networks of cities is essential, these properties can be measured at the city level, and must be assessed by analyzing actor networks. The present volume focuses less on individual characteristics and more on the interactions of actors and institutions that create functional territories in which the structure of existing links constrains emerging links. Rather than basing explanations on external factors, the goal is to determine the extent to which network properties reflect spatial distributions and create local synergies at the meso level that are incorporated into global networks at the macro level where different geographical scales occur. The paper introduces the way to use the graphs structure to identify empirically relevant groups and levels that explain dynamics. It defines what could be called âeurooemulti-levelâeuro, âeurooemulti-scaleâeuro, or âeurooemultidimensionalâeuro networks in the context of urban geography. It explains how the convergence of the network multi-territoriality paradigm collaboratively formulated, and manipulated by geographers and computer scientists produced the SPANGEO project, which is exposed in this volume.

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The theory of small-world networks as initiated by Watts and Strogatz (1998) has drawn new insights in spatial analysis as well as systems theory. The theoryâeuro?s concepts and methods are particularly relevant to geography, where spatial interaction is mainstream and where interactions can be described and studied using large numbers of exchanges or similarity matrices. Networks are organized through direct links or by indirect paths, inducing topological proximities that simultaneously involve spatial, social, cultural or organizational dimensions. Network synergies build over similarities and are fed by complementarities between or inside cities, with the two effects potentially amplifying each other according to the âeurooepreferential attachmentâeuro hypothesis that has been explored in a number of different scientific fields (Barabási, Albert 1999; Barabási A-L 2002; Newman M, Watts D, Barabàsi A-L). In fact, according to Barabási and Albert (1999), the high level of hierarchy observed in âeurooescale-free networksâeuro results from âeurooepreferential attachmentâeuro, which characterizes the development of networks: new connections appear preferentially close to nodes that already have the largest number of connections because in this way, the improvement in the network accessibility of the new connection will likely be greater. However, at the same time, network regions gathering dense and numerous weak links (Granovetter, 1985) or network entities acting as bridges between several components (Burt 2005) offer a higher capacity for urban communities to benefit from opportunities and create future synergies. Several methodologies have been suggested to identify such denser and more coherent regions (also called communities or clusters) in terms of links (Watts, Strogatz 1998; Watts 1999; Barabási, Albert 1999; Barabási 2002; Auber 2003; Newman 2006). These communities not only possess a high level of dependency among their member entities but also show a low level of âeurooevulnerabilityâeuro, allowing for numerous redundancies (Burt 2000; Burt 2005). The SPANGEO project 2005âeuro"2008 (SPAtial Networks in GEOgraphy), gathering a team of geographers and computer scientists, has included empirical studies to survey concepts and measures developed in other related fields, such as physics, sociology and communication science. The relevancy and potential interpretation of weighted or non-weighted measures on edges and nodes were examined and analyzed at different scales (intra-urban, inter-urban or both). New classification and clustering schemes based on the relative local density of subgraphs were developed. The present article describes how these notions and methods contribute on a conceptual level, in terms of measures, delineations, explanatory analyses and visualization of geographical phenomena.

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BACKGROUND AND AIMS: Mannan-binding lectin (MBL) and ficolins are microbial pattern recognition molecules that activate the lectin pathway of complement. We previously reported the association of MBL deficiency with anti-Saccharomyces cerevisiae antibodies (ASCA) in patients with Crohn's disease (CD). However, ASCA are also frequently found in MBL-proficient CD patients. Here we addressed expression/function of ficolins and MBL-associated serine protease-2 (MASP-2) regarding potential association with ASCA. METHODS: ASCA titers and MBL, ficolin and MASP-2 concentrations were determined by ELISA in the serum of patients with CD, ulcerative colitis (UC), and in healthy controls. MASP-2 activity was determined by measuring complement C4b-fixation. Anti-MBL autoantibodies were detected by ELISA. RESULTS: In CD and UC patients, L-ficolin concentrations were significantly higher compared to healthy controls (p<0.001 and p=0.029). In contrast, H-ficolin concentrations were slightly reduced in CD and UC compared to healthy controls (p=0.037 for UC vs. hc). CD patients with high ASCA titers had significantly lower H-ficolin concentrations compared to ASCA-low/negative CD patients (p=0.009). However, MASP-2 activity was not different in ASCA-negative and ASCA-positive CD patients upon both, ficolin- or MBL-mediated MASP-2 activation. Finally, anti-MBL autoantibodies were not over-represented in MBL-proficient ASCA-positive CD patients. CONCLUSIONS: Our results suggest that low expression of H-ficolin may promote elevated ASCA titers in the ASCA-positive subgroup of CD patients. However, unlike MBL deficiency, we found no evidence for low expression of serum ficolins or reduced MASP-2 activity that may predispose to ASCA development.