915 resultados para Supervised pattern recognition methods
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La machine à vecteurs de support à une classe est un algorithme non-supervisé qui est capable d’apprendre une fonction de décision à partir de données d’une seule classe pour la détection d’anomalie. Avec les données d’entraînement d’une seule classe, elle peut identifier si une nouvelle donnée est similaire à l’ensemble d’entraînement. Dans ce mémoire, nous nous intéressons à la reconnaissance de forme de dynamique de frappe par la machine à vecteurs de support à une classe, pour l’authentification d’étudiants dans un système d’évaluation sommative à distance à l’Université Laval. Comme chaque étudiant à l’Université Laval possède un identifiant court, unique qu’il utilise pour tout accès sécurisé aux ressources informatiques, nous avons choisi cette chaîne de caractères comme support à la saisie de dynamique de frappe d’utilisateur pour construire notre propre base de données. Après avoir entraîné un modèle pour chaque étudiant avec ses données de dynamique de frappe, on veut pouvoir l’identifier et éventuellement détecter des imposteurs. Trois méthodes pour la classification ont été testées et discutées. Ainsi, nous avons pu constater les faiblesses de chaque méthode dans ce système. L’évaluation des taux de reconnaissance a permis de mettre en évidence leur dépendance au nombre de signatures ainsi qu’au nombre de caractères utilisés pour construire les signatures. Enfin, nous avons montré qu’il existe des corrélations entre le taux de reconnaissance et la dispersion dans les distributions des caractéristiques des signatures de dynamique de frappe.
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Introducción: La rápida detección e identificación bacteriana es fundamental para el manejo de los pacientes críticos que presentan una patología infecciosa, esto requiere de métodos rápidos para el inicio de un correcto tratamiento. En Colombia se usan pruebas microbiología convencional. No hay estudios de espectrofotometría de masas en análisis de muestras de pacientes críticos en Colombia. Objetivo general: Describir la experiencia del análisis microbiológico mediante la tecnología MALDI-TOF MS en muestras tomadas en la Fundación Santa Fe de Bogotá. Materiales y Métodos: Entre junio y julio de 2013, se analizaron 147 aislamientos bacterianos de muestras clínicas, las cuales fueron procesadas previamente por medio del sistema VITEK II. Los aislamientos correspondieron a 88 hemocultivos (60%), 28 urocultivos (19%), y otros cultivos 31 (21%). Resultados: Se obtuvieron 147 aislamientos con identificación adecuada a nivel de género y/o especie así: en el 88.4% (130 muestras) a nivel de género y especie, con una concordancia del 100% comparado con el sistema VITEK II. El porcentaje de identificación fue de 66% en el grupo de bacilos gram negativos no fermentadores, 96% en enterobacterias, 100% en gérmenes fastidiosos, 92% en cocos gram positivos, 100% bacilos gram negativos móviles y 100% en levaduras. No se encontró ninguna concordancia en bacilos gram positivos y gérmenes del genero Aggregatibacter. Conclusiones: El MALDI-TOF es una prueba rápida para la identificación microbiológica de género y especie que concuerda con los resultados obtenidos de manera convencional. Faltan estudios para hacer del MALDI-TOF MS la prueba oro en identificación de gérmenes.
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Universidade Estadual de Campinas. Faculdade de Educação Física
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The peritoneal cavity (PerC) is a singular compartment where many cell populations reside and interact. Despite the widely adopted experimental approach of intraperitoneal (i.p.) inoculation, little is known about the behavior of the different cell populations within the PerC. To evaluate the dynamics of peritoneal macrophage (Mempty set) subsets, namely small peritoneal Mempty set (SPM) and large peritoneal Mempty set (LPM), in response to infectious stimuli, C57BL/6 mice were injected i.p. with zymosan or Trypanosoma cruzi. These conditions resulted in the marked modification of the PerC myelo-monocytic compartment characterized by the disappearance of LPM and the accumulation of SPM and monocytes. In parallel, adherent cells isolated from stimulated PerC displayed reduced staining for beta-galactosidase, a biomarker for senescence. Further, the adherent cells showed increased nitric oxide (NO) and higher frequency of IL-12-producing cells in response to subsequent LPS and IFN-gamma stimulation. Among myelo-monocytic cells, SPM rather than LPM or monocytes, appear to be the central effectors of the activated PerC; they display higher phagocytic activity and are the main source of IL-12. Thus, our data provide a first demonstration of the consequences of the dynamics between peritoneal Mempty set subpopulations by showing that substitution of LPM by a robust SPM and monocytes in response to infectious stimuli greatly improves PerC effector activity.
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Activation of NF-kappa B and 5-lipoxygenase-mediated (5-LO-mediated) biosynthesis of the lipid mediator leukotriene B(4) (LTB(4)) are pivotal components of host defense and inflammatory responses. However, the role of LTB(4) in mediating innate immune responses elicited by specific TLR ligands and cytokines is unknown. Here we have shown that responses dependent on MyD88 (an adaptor protein that mediates signaling through all of the known TLRs, except TLR3, as well as IL-1 beta and IL-18) are reduced in mice lacking either 5-LO or the LTB(4) receptor BTL1, and that macrophages from these mice are impaired in MyD88-dependent activation of NF-kappa B. This macrophage defect was associated with lower basal and inducible expression of MyD88 and reflected impaired activation of STAT1 and overexpression of the STAT1 inhibitor SOCS1. Expression of MyD88 and responsiveness to the TLR4 ligand LPS were decreased by Stat1 siRNA silencing in WT macrophages and restored by Socs1 siRNA in 5-LO-deficient macrophages. These results uncover a pivotal role in macrophages for the GPCR BLT1 in regulating activation of NF-kappa B through Stat1-dependent expression of MyD88.
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A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.
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We consider brightness/contrast-invariant and rotation-discriminating template matching that searches an image to analyze A for a query image Q We propose to use the complex coefficients of the discrete Fourier transform of the radial projections to compute new rotation-invariant local features. These coefficients can be efficiently obtained via FFT. We classify templates in ""stable"" and ""unstable"" ones and argue that any local feature-based template matching may fail to find unstable templates. We extract several stable sub-templates of Q and find them in A by comparing the features. The matchings of the sub-templates are combined using the Hough transform. As the features of A are computed only once, the algorithm can find quickly many different sub-templates in A, and it is Suitable for finding many query images in A, multi-scale searching and partial occlusion-robust template matching. (C) 2009 Elsevier Ltd. All rights reserved.
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The discrete-time neural network proposed by Hopfield can be used for storing and recognizing binary patterns. Here, we investigate how the performance of this network on pattern recognition task is altered when neurons are removed and the weights of the synapses corresponding to these deleted neurons are divided among the remaining synapses. Five distinct ways of distributing such weights are evaluated. We speculate how this numerical work about synaptic compensation may help to guide experimental studies on memory rehabilitation interventions.
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In many engineering applications, the time coordination of geographically separated events is of fundamental importance, as in digital telecommunications and integrated digital circuits. Mutually connected (MC) networks are very good candidates for some new types of application, such as wireless sensor networks. This paper presents a study on the behavior of MC networks of digital phase-locked loops (DPLLs). Analytical results are derived showing that, even for static networks without delays, different synchronous states may exist for the network. An upper bound for the number of such states is also presented. Numerical simulations are used to show the following results: (i) the synchronization precision in MC DPLLs networks; (ii) the existence of synchronous states for the network does not guarantee its achievement and (iii) different synchronous states may be achieved for different initial conditions. These results are important in the neural computation context. as in this case, each synchronous state may be associated to a different analog memory information. (C) 2010 Elsevier B.V. All rights reserved.
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The concentrations of major, minor and trace metals were measured in water samples collected from five shallow Antarctic lakes (Carezza, Edmonson Point (No 14 and 15a), Inexpressible Island and Tarn Flat) found in Terra Nova Bay (northern Victoria Land, Antarctica) during the Italian Expeditions of 1993-2001. The total concentrations of a large suite of elements (Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Gd, K, La, Li, Mg, Mn, Mo, Na, Nd, Ni, Pb, Pr, Rb, Sc, Si, Sr, Ta, Ti, U, V, Y, W, Zn and Zr) were determined using spectroscopic techniques (ICP-AES, GF-AAS and ICP-MS). The results are similar to those obtained for the freshwater lakes of the Larsemann Hills, East Antarctica, and for the McMurdo Dry Valleys. Principal Component Analysis (PCA) and Cluster Analysis (CA) were performed to identify groups of samples with similar characteristics and to find correlations between the variables. The variability observed within the water samples is closely connected to the sea spray input; hence, it is primarily a consequence of geographical and meteorological factors, such as distance from the ocean and time of year. The trace element levels, in particular those of heavy metals, are very low, suggesting an origin from natural sources rather than from anthropogenic contamination.
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Activation of prophenoloxidase (proPO) in insects is a defense mechanism against intruding microorganisms and parasites. Pattern recognition molecules induce activation of an enzymatic cascade involving serine proteinases, which leads to the conversion of proPO to active phenoloxidase (PO). Phenolic compounds produced by pPO-activation are toxic to invaders. Here, we describe the isolation of a venom protein from the parasitoid, Cotesia rubecula, injected into the host, Pieris rapae, which is homologous to serine proteinase homologs (SPH). The data presented here indicate that the protein interferes with the proteolytic cascade, which under normal circumstances leads to the activation of proPO and melanin formation. (C) 2003 Elsevier Ltd. All rights reserved.
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A shift in the activation of pulmonary macrophages characterized by an increase of IL-1, INF-alpha and IL-6 production has been induced in mice infected with Paracoccidioides brasiliensis. It is still unclear whether a functional shift in the resident alveolar macrophage population would be responsible for these observations due to the expression of cell surface molecules. We investigated pulmonary macrophages by flow cytometry from mice treated with P. brasiliensis derivatives by intratracheal route. In vivo labeling with the dye PKH26GL was applied to characterize newly recruited pulmonary macrophages from the bloodstream. Pulmonary macrophages from mice inflamed with P. brasiliensis derivatives showed a high expression of the surface antigens CD11b/CD18 and CD23 among several cellular markers. The expression of these markers indicated a pattern of activation of a subpopulation characterized as CD11b(+) or CD23(+), which was modulated in vitro by IFN-gamma and IL-4. Analysis of monocytes labelled with PKH26GL demonstrated that CD11b(+) cells did infiltrate the lung exhibiting a proinflammatoni pattern of activation, whereas CD23(+) cells were considered to be resident in the lung. These findings may contribute to better understand the pathology of lung inflammation caused by P. brasiliensis infection. (C) 2010 Elsevier GmbH. All rights reserved.
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The HCI community is actively seeking novel methodologies to gain insight into the user’s experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies’ scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.
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Tese de Doutoramento, Biologia (Biologia Celular e Molecular), 18 de Novembro de 2013, Universidade dos Açores.
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In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.