955 resultados para Temporal Information Extraction


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OBJETIVO: Analisar a tendência da mortalidade por diarreia entre menores de 5 anos, no município de Osasco (SP), entre 1980 e 2000. MÉTODOS: Trata-se de estudo observacional com dois delineamentos. Um descritivo, que toma o indivíduo como unidade do estudo, e outro ecológico, analisando agregado populacional que incluiu análise de séries temporais. A fonte de dados foi o sistema de informação de mortalidade do Estado de São Paulo e censos de 1980, 1991 e 2000. Descreveu-se a variação sazonal e para a análise de tendência aplicaram-se modelos log lineares de regressão polinomiais, utilizando-se variáveis sociodemográficas da criança e da mãe. Foram analisadas a evolução de indicadores sociodemográficos do município de 1980 a 2000, as taxas médias de mortalidade por diarreia nos menores de 5 anos e seus diferenciais por distrito nos anos 90. RESULTADOS: Dos 1.360 óbitos, 94,3 e 75,3% atingiram, respectivamente, menores de 1 ano e de 6 meses. O declínio da mortalidade foi de 98,3%, com deslocamento da sazonalidade do verão para o outono. A mediana da idade elevou-se de 2 meses nos primeiros períodos para 3 meses no último. O resíduo de óbitos manteve-se entre filhos de mães de 20 a 29 anos e escolaridade < 8 anos. O risco relativo entre o distrito mais atingido e a taxa média do município diminuiu de 3,4 para 1,3 do primeiro para o segundo quinquênio dos anos 90. CONCLUSÃO: Nossos resultados apontam uma elevação da idade mais vulnerável e a provável mudança do agente mais frequentemente associado ao óbito por diarreia.

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Objetivo: Analisar a tendência da mortalidade por diarreia entre menores de 5 anos, no município de Osasco (SP), entre 1980 e 2000. Métodos: Trata-se de estudo observacional com dois delineamentos. Um descritivo, que toma o indivíduo como unidade do estudo, e outro ecológico, analisando agregado populacional que incluiu análise de séries temporais. A fonte de dados foi o sistema de informação de mortalidade do Estado de São Paulo e censos de 1980, 1991 e 2000. Descreveu-se a variação sazonal e para a análise de tendência aplicaram-se modelos log lineares de regressão polinomiais, utilizando-se variáveis sociodemográficas da criança e da mãe. Foram analisadas a evolução de indicadores sociodemográficos do município de 1980 a 2000, as taxas médias de mortalidade por diarreia nos menores de 5 anos e seus diferenciais por distrito nos anos 90. Resultados: Dos 1.360 óbitos, 94,3 e 75,3% atingiram, respectivamente, menores de 1 ano e de 6 meses. O declínio da mortalidade foi de 98,3%, com deslocamento da sazonalidade do verão para o outono. A mediana da idade elevou-se de 2 meses nos primeiros períodos para 3 meses no último. O resíduo de óbitos manteve-se entre filhos de mães de 20 a 29 anos e escolaridade < 8 anos. O risco relativo entre o distrito mais atingido e a taxa média do município diminuiu de 3,4 para 1,3 do primeiro para o segundo quinquênio dos anos 90. Conclusão: Nossos resultados apontam uma elevação da idade mais vulnerável e a provável mudança do agente mais frequentemente associado ao óbito por diarreia

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This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.

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This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

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The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. (C) 2011 Elsevier Inc. All rights reserved.

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Computer modelling has shown that electrical characteristics of individual pixels may be extracted from within multiple-frequency electrical impedance tomography (MFEIT) images formed using a reference data set obtained from a purely resistive, homogeneous medium. In some applications it is desirable to extract the electrical characteristics of individual pixels from images where a purely resistive, homogeneous reference data set is not available. One such application of the technique of MFEIT is to allow the acquisition of in vivo images using reference data sets obtained from a non-homogeneous medium with a reactive component. However, the reactive component of the reference data set introduces difficulties with the extraction of the true electrical characteristics from the image pixels. This study was a preliminary investigation of a technique to extract electrical parameters from multifrequency images when the reference data set has a reactive component. Unlike the situation in which a homogenous, resistive data set is available, it is not possible to obtain the impedance and phase information directly from the image pixel values of the MFEIT images data set, as the phase of the reactive reference is not known. The method reported here to extract the electrical characteristics (the Cole-Cole plot) initially assumes that this phase angle is zero. With this assumption, an impedance spectrum can be directly extracted from the image set. To obtain the true Cole-Cole plot a correction must be applied to account for the inherent rotation of the extracted impedance spectrum about the origin, which is a result of the assumption. This work shows that the angle of rotation associated with the reactive component of the reference data set may be determined using a priori knowledge of the distribution of frequencies of the Cole-Cole plot. Using this angle of rotation, the true Cole-Cole plot can be obtained from the impedance spectrum extracted from the MFEIT image data set. The method was investigated using simulated data, both with and without noise, and also for image data obtained in vitro. The in vitro studies involved 32 logarithmically spaced frequencies from 4 kHz up to 1 MHz and demonstrated that differences between the true characteristics and those of the impedance spectrum were reduced significantly after application of the correction technique. The differences between the extracted parameters and the true values prior to correction were in the range from 16% to 70%. Following application of the correction technique the differences were reduced to less than 5%. The parameters obtained from the Cole-Cole plot may be useful as a characterization of the nature and health of the imaged tissues.

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Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

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OBJECTIVE: We present observations of the anatomy of the sylvian fissure region and their clinical application in neuroimaging, microsurgery for middle cerebral artery aneurysms and insular lesions, frontobasal resections, and epilepsy Surgery. METHODS: Sixty adult cadaveric hemispheres and 12 adult cadaveric heads were studied after perfusion of the arteries and veins with colored latex. The anatomic information was applied in more than 200 microsurgeries in and around the sylvian fissure region in the past 15 years. RESULTS: The sylvian fissure extends from the basal to the lateral surface of the brain and presents 2 compartments on each surface, I superficial (temporal stem and its ramii) and 1 deep (anterior and lateral operculoinsular compartments). The temporal operculum is in opposition to the frontal and parietal opercula (planum polare versus inferior frontal and precentral gyri, Heschl`s versus postcentral gyri, planum temporale versus supramarginal gyrus). The inferior frontal, precentral, and postcentral gyri cover the anterior, middle, and posterior thirds of the lateral surface of the insula, respectively. The pars triangularis covers the apex of the insula, located immediately distal to the genu of the middle cerebral artery. The clinical application of the anatomic information presented in this article is in angiography, middle cerebral artery aneurysm surgery, insular resection, frontobasal resection, and amygdalohippocampectomy, and hemispherotomy. CONCLUSION: The anatomic relationships of the sylvian fissure region can be helpful in preoperative planning and can serve as reliable intraoperative navigation landmarks in microsurgery involving that region.

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The Wisconsin Card Sorting Test (WCST) is the gold standard in the evaluation of executive dysfunction (ED) in patients with temporal lobe epilepsy (TLE). We evaluated 35 children with TLE and 25 healthy controls with the WCST and with a more comprehensive battery. Among the children with TLE, 77.14% showed impairment on the WCST. On other tests (Wechsler Intelligence Scale for Children-Digit Forward, Matching Familiar Figures Test, Trail Making Test, Word Fluency, Finger Windows, and Number-Letter Memory), impairment was demonstrated in 94.29%. The authors concluded that the WCST is a good paradigm to measure executive impairment in children with TLE: however, it may be not enough. Evaluation performed only with the WCST not only underestimated the number of patients with ED, but also missed relevant information regarding the type of ED. (C) 2009 Elsevier Inc. All rights reserved.

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Background: Examination of the epidemiology and timing of trauma deaths has been deemed a useful method to evaluate the quality of trauma care. Objective: The purpose of this study was to evaluate the quality of trauma care in a regional trauma system and in a university hospital in Brazil by comparing the timing of deaths in the studied prehospital and in-hospital settings to those published for trauma systems in other areas. Methods: We analyzed the National Health Minister`s System of Deaths Information for the prehospital mortality and we retrospectively collected the demographics, timelines, and trauma severity scores of all in-hospital patients who died after admission through the Emergency Unit of Hospital das Clinicas de Ribeirao Preto between 2000 and 2001. Results. During the study period, there were 787 trauma fatalities in the city: 448 (56.9%) died in the prehospital setting and 339 (43.1%) died after being admitted to a medical facility. In 2 years, 238 trauma deaths occurred in the studied hospital, and we found a complete clinical set of data for 224 of these patients. The majority of deaths in the prehospital setting were caused by penetrating injuries (66.7%), whereas in-hospital mortality was mainly because of blunt traumas (59.1%). The largest number of in-hospital deaths occurred beyond 72 hours of stay (107 patients-47%). Conclusions: The region studied showed some deficiencies in prehospital and in-hospitals settings, in particular in the critical care and short-term follow-up of trauma patients when compared with the literature. Particularly, the late mortality may be related to training and human resources deficiency. Based on the timeline of trauma deaths, we can suggest that the studied region needs improvements in the prehospital trauma system and in hospital critical care.

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Given the dynamic nature of cardiac function, correct temporal alignment of pre-operative models and intraoperative images is crucial for augmented reality in cardiac image-guided interventions. As such, the current study focuses on the development of an image-based strategy for temporal alignment of multimodal cardiac imaging sequences, such as cine Magnetic Resonance Imaging (MRI) or 3D Ultrasound (US). First, we derive a robust, modality-independent signal from the image sequences, estimated by computing the normalized crosscorrelation between each frame in the temporal sequence and the end-diastolic frame. This signal is a resembler for the left-ventricle (LV) volume curve over time, whose variation indicates di erent temporal landmarks of the cardiac cycle. We then perform the temporal alignment of these surrogate signals derived from MRI and US sequences of the same patient through Dynamic Time Warping (DTW), allowing to synchronize both sequences. The proposed framework was evaluated in 98 patients, which have undergone both 3D+t MRI and US scans. The end-systolic frame could be accurately estimated as the minimum of the image-derived surrogate signal, presenting a relative error of 1:6 1:9% and 4:0 4:2% for the MRI and US sequences, respectively, thus supporting its association with key temporal instants of the cardiac cycle. The use of DTW reduces the desynchronization of the cardiac events in MRI and US sequences, allowing to temporally align multimodal cardiac imaging sequences. Overall, a generic, fast and accurate method for temporal synchronization of MRI and US sequences of the same patient was introduced. This approach could be straightforwardly used for the correct temporal alignment of pre-operative MRI information and intra-operative US images.

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One of the most efficient approaches to generate the side information (SI) in distributed video codecs is through motion compensated frame interpolation where the current frame is estimated based on past and future reference frames. However, this approach leads to significant spatial and temporal variations in the correlation noise between the source at the encoder and the SI at the decoder. In such scenario, it would be useful to design an architecture where the SI can be more robustly generated at the block level, avoiding the creation of SI frame regions with lower correlation, largely responsible for some coding efficiency losses. In this paper, a flexible framework to generate SI at the block level in two modes is presented: while the first mode corresponds to a motion compensated interpolation (MCI) technique, the second mode corresponds to a motion compensated quality enhancement (MCQE) technique where a low quality Intra block sent by the encoder is used to generate the SI by doing motion estimation with the help of the reference frames. The novel MCQE mode can be overall advantageous from the rate-distortion point of view, even if some rate has to be invested in the low quality Intra coding blocks, for blocks where the MCI produces SI with lower correlation. The overall solution is evaluated in terms of RD performance with improvements up to 2 dB, especially for high motion video sequences and long Group of Pictures (GOP) sizes.

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This paper analyzes the risk-return trade-off in European equities considering both temporal and cross-sectional dimensions. In our analysis, we introduce not only the market portfolio but also 15 industry portfolios comprising the entire market. Several bivariate GARCH models are estimated to obtain the covariance matrix between excess market returns and the industrial portfolios and the existence of a risk-return trade-off is analyzed through a cross-sectional approach using the information in all portfolios. It is obtained evidence for a positive and significant risk-return trade-off in the European market. This conclusion is robust for different GARCH specifications and is even more evident after controlling for the main financial crisis during the sample period.

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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.