64 resultados para stream processing crowdsensing scheduling traffic analysis


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In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

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We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

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Vessel dynamic positioning (DP) systems are based on conventional PID-type controllers and an extended Kalman filter. However, they present a difficult tuning procedure, and the closed-loop performance varies with environmental or loading conditions since the dynamics of the vessel are eminently nonlinear. Gain scheduling is normally used to address the nonlinearity of the system. To overcome these problems, a sliding mode control was evaluated. This controller is robust to variations in environmental and loading conditions, it maintains performance and stability for a large range of conditions, and presents an easy tuning methodology. The performance of the controller was evaluated numerically and experimentally in order to address its effectiveness. The results are compared with those obtained from conventional PID controller. (c) 2010 Elsevier Ltd. All rights reserved.

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This work presents a method for predicting resource availability in opportunistic grids by means of use pattern analysis (UPA), a technique based on non-supervised learning methods. This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict the resource availability. Trace-driven simulations validate this basic assumptions, which also provide the parameter settings for the accurate learning of resource use patterns. Experiments made with an implementation of the UPA method show the feasibility of its use in the scheduling of grid tasks with very little overhead. The experiments also demonstrate the method`s superiority over other predictive and non-predictive methods. An adaptative prediction method is suggested to deal with the lack of training data at initialization. Further adaptative behaviour is motivated by experiments which show that, in some special environments, reliable resource use patterns may not always be detected. Copyright (C) 2009 John Wiley & Sons, Ltd.

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In order to protect food from pathogenic microorganisms as well as increase its shelf-life, while keeping sensorial properties (e.g., odor and taste), which are important properties required by spice buyers, it is necessary to analyze volatile formation from irradiation of medicinal and food herbs. Possible changes in the odor of these herbs are evaluated by characterizing different radiation doses and effects on sensorial properties, in order to allow better application of the irradiation technology. The aim of the present study was to analyze volatile formation on cinnamon (Laurus cinnamomum) samples after gamma irradiation. These samples were irradiated into plastic packages using a (60)Co facility. Radiation doses applied were 0, 5, 10, 15, 20 and 25 kGy. For the analysis of the samples, solid-phase microextraction (SPME) was applied, while for the analysis of volatile compounds, CG/MS. Spice irradiation showed the highest decrease in volatile compounds. For L. cinnamomum, the irradiation decreased volatile compounds by nearly 56% and 89.5%, respectively, comparing to volatile from a sample which had not been previously irradiated. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.

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The development of biomonitoring programs based on the macroinvertebrate community requires the understanding of species distribution patterns, as well as of the responses of the community to anthropogenic stressors. In this study, 49 metrics were tested as potential means of assessing the condition of 29 first- and second-order streams located in areas of differing types of land use in So Paulo State, Brazil. Of the sampled streams, 15 were in well-preserved regions in the Atlantic Forest, 5 were among sugarcane cultivations, 5 were in areas of pasture, and 4 were among eucalyptus plantations. The metrics were assessed against the following criteria: (1) predictable response to the impact of human activity; (2) highest taxonomic resolution, and (3) operational and theoretical simplicity. We found that 18 metrics were correlated with the environmental and spatial predictors used, and seven of these satisfied the selection criteria and are thus candidates for inclusion in a multimetric system to assess low-order streams in So Paulo State. These metrics are family richness; Ephemeroptera, Plecoptera and Trichoptera (EPT) richness; proportion of Megaloptera and Hirudinea; proportion of EPT; Shannon diversity index for genus; and adapted Biological Monitoring Work Party biotic index.

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Background: Urban air pollutants are associated with cardiovascular events. Traffic controllers are at high risk for pollution exposure during outdoor work shifts. Objective: The purpose of this study was to evaluate the relationship between air pollution and systemic blood pressure in traffic controllers during their work shifts. Methods: This cross-sectional study enrolled 19 male traffic controllers from Santo Andre city (Sao Paulo, Brazil) who were 30-60 years old and exposed to ambient air during outdoor work shifts. Systolic and diastolic blood pressure readings were measured every 15 min by an Ambulatory Arterial Blood Pressure Monitoring device. Hourly measurements (lags of 0-5 h) and the moving averages (2-5 h) of particulate matter (PM(10)), ozone (O(3)) ambient concentrations and the acquired daily minimum temperature and humidity means from the Sao Paulo State Environmental Agency were correlated with both systolic and diastolic blood pressures. Statistical methods included descriptive analysis and linear mixed effect models adjusted for temperature, humidity, work periods and time of day. Results: Interquartile increases of PM(10) (33 mu g/m(3)) and O(3) (49 mu g/m(3)) levels were associated with increases in all arterial pressure parameters, ranging from 1.06 to 2.53 mmHg. PM(10) concentration was associated with early effects (lag 0), mainly on systolic blood pressure. However, O(3) was weakly associated most consistently with diastolic blood pressure and with late cumulative effects. Conclusions: Santo Andre traffic controllers presented higher blood pressure readings while working their outdoor shifts during periods of exposure to ambient pollutant fluctuations. However, PM(10) and O(3) induced cardiovascular effects demonstrated different time courses and end-point behaviors and probably acted through different mechanisms. (C) 2011 Elsevier Inc. All rights reserved.

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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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Candidemia is associated with high morbidity and mortality resulting in significant increases in the length of patients` hospitalization and in healthcare costs. Critically ill patients are at particular risk for candidemia because of their debilitated condition and frequent need for invasive procedures. The aim of this study was to characterize the incidence and epidemiology of candidemia over a seven-year period in intensive care units (ICUs) and the use of fluconazole and caspofungin in a large university-affiliated hospital. All cases of candidemia were identified by surveillance, using the Centers for Diseases Control and Prevention criteria. Demographic variables, use of antifungal (fluconazole and caspofungin) and patient outcomes were evaluated. The 2 test for linear trend was employed to evaluate the distribution of Candida spp. and the use of fluconazole and caspofungin by defined daily dose (DDD) per 1,000 patients-days during the study period. One hundred and eight episodes of candidemia were identified. The overall incidence of candidemia (P=0.20) and incidence of non-Candida albicans Candida infections (P=0.32) remained stable over the study period and ranged from 0.3-0.9 episodes per 1,000 catheter-days and 0.39-0.83 episodes per 1,000 patients-days. However, the use of fluconazole and caspofungin increased significantly (P0.001). While there were no reports of the use of fluconazole for prophylaxis in 1999, its use for this purpose increased from 3% in 2000 to 7.0% (P=0.07) in 2006. C. albicans was the most frequent specie isolated and burns and cancer were the most frequent underlying conditions. The overall mortality was 76%. There was no difference between C. albicans and non-C. albicans Candida infections when the crude and 14-day mortality rates were compared. Our data demonstrated that C. albicans is still the most frequent species causing candidemia in our intensive care units. Our rates of candidemia are lower than those reported from the region and similar to American and European hospitals. Although the incidence of blood stream infections (BSI) and candidemia remained stable, the use of fluconazole and caspofungin increased significantly over the years included in this study but had no impact on the incidence of infections caused by non-C. albicans Candida species.

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Aims: The aims of the present study were to characterize fatal traffic accident victims in a major urban center in Brazil and their association with alcohol consumption. Methods: Cross-sectional study of 907 fatal traffic accident victims in Sao Paulo, in 2005. Results: Adult males between the ages of 25 and 54 represented the majority of cases with positive blood alcohol concentrations (BAC). Overall, males had a higher proportional BAC and mean BAC than females. Pedestrians, particularly those with no detectable BAC, were typically older than other victims. Most accidents (total and BAC-positive) happened on weekends between midnight and 6 a.m. Considering all victims, 39.4% were positive (BAC over 0.1 g/l). When only drivers (automobile, motorcycle and bicycle) were evaluated. 42.3% had BAC over the legal limit (0.6 g/l). Conclusions: Alcohol is associated with nearly half of all traffic accident deaths in the city of Sao Paulo. especially for days and times associated with parties and bars (weekends between 12 a.m. and 6 a.m.). (C) 2010 Elsevier Ltd. All rights reserved.

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The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

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The impact of particle emissions by biomass burning is increasing throughout the world. We explored the toxicity of particulate matter produced by sugar cane burning and compared these effects with equivalent mass of traffic-derived particles. For this purpose, BALB/c mice received a single intranasal instillation of either distilled water (C) or total suspended particles (15 mu g) from an urban area (SP group) or biomass burning-derived particles (Bio group). Lung mechanical parameters (total, resistive and viscoelastic pressures, static elastance, and elastic component of viscoelasticity) and histology were analyzed 24h after instillation. Trace elements and polycyclic aromatic hydrocarbons (PAHs) metabolites of the two sources of particles were determined. All mechanical parameters increased similarly in both pollution groups compared with control, except airway resistive pressure, which increased only in Bio. Both exposed groups showed significantly higher fraction area of alveolar collapse, and influx of polymorphonuclear cells in lung parenchyma than C. The composition analysis of total suspended particles showed higher concentrations of PAHs and lower concentration of metals in traffic than in biomass burning-derived particles. In conclusion, we demonstrated that a single low dose of ambient particles, produced by traffic and sugar cane burning, induced significant alterations in pulmonary mechanics and lung histology in mice. Parenchymal changes were similar after exposure to both particle sources, whereas airway mechanics was more affected by biomass-derived particles. Our results indicate that biomass particles were at least as toxic as those produced by traffic. (C) 2008 Elsevier Inc. All rights reserved.

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The Canoparmelia texana epiphytic lichenized fungi was used to monitor atmospheric pollution in the Sao Paulo metropolitan region, SP, Brazil. The cluster analysis applied to the element concentration values confirmed the site groups of different levels of pollution due to industrial and vehicular emissions. In the distribution maps of element concentrations, higher concentrations of Ba and Mn were observed in the vicinity of industries and of a petrochemical complex. The highest concentration of Co found in lichens from the Sao Miguel Paulista site is due to the emissions from a metallurgical processing plant that produces this element. For Br and Zn, the highest concentrations could be associated both to vehicular and industrial emissions. Exploratory analyses revealed that the accumulation of toxic elements in C. texana may be of use in evaluating the human risk of cardiopulmonary mortality due to prolonged exposure to ambient levels of air pollution. (c) 2007 Elsevier Ltd. All rights reserved.

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Objectives: The purpose of this study was to explore the clinical relevance of chronic exposure to ambient levels of traffic derived air pollution on the ocular surface. Methods: A panel study involving 55 volunteers was carried out in Sao Paulo, Brazil. We measured the mean individual levels of nitrogen dioxide (NO(2)) exposure for 7 days. All subjects answered the Ocular Symptom Disease Index (OSDI) and a symptoms inventory. Subsequently, subjects underwent Schirmer I test, biomicroscopy, vital staining and tear breakup time (TOUT) assessment. Subject`s mean daily exposure to NO(2) was categorized in quartiles. Statistical analysis was performed using one-way ANOVA, Tukey HSD and Chi-Square tests. Results: A dose-response pattern was detected between OSDI scores and NO(2) quartiles (p < 0.05). There was a significant association between NO(2) quartiles and reported ocular irritation (X(2) = 9.2, p < 0.05) and a significant negative association between TBUT and NO(2) exposure (p < 0.05, R = -0.316. Spearman`s correlation). There was a significant increase in the frequency of meibomitis in subjects exposed to higher levels of NO(2) (p < 0.05). Conclusions: Subjects exposed to higher levels of traffic derived air pollution reported more ocular discomfort symptoms and presented greater tear film instability, suggesting that the ocular discomfort symptoms and tear breakup time could be used as convenient bioindicators of the adverse health effects of traffic derived air pollution exposure. (C) 2010 Elsevier Inc. All rights reserved.

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Cells produce and use peptides in distinctive ways. In the present report, using isotope labeling plus semi-quantitative mass spectrometry, we evaluated the intracellular peptide profile of TAP1/beta 2m(-/-) (transporter associated with antigen-processing 1/beta 2 microglobulin) double-knockout mice and compared it with that of C57BL/6 wild-type animals. Overall, 92 distinctive peptides were identified, and most were shown to have a similar concentration in both mouse strains. However, some peptides showed a modest increase or decrease (similar to 2-fold), whereas a glycine-rich peptide derived from the C-terminal of neurogranin (KGPGPGGPGGAGGARGGAGGGPSGD) showed a substantial increase (6-fold) in TAP1/beta 2m(-/-) mice. Thus, TAP1 and beta 2microglobulin have a small influence on the peptide profile of neuronal tissue, suggesting that the presence of peptides derived from intracellular proteins in neuronal tissue is not associated with antigens of the class I major histocompatibility complex. Therefore, it is possible that these intracellular peptides play a physiological role.