919 resultados para Linear network analysis
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Long-term monitoring of surface water quality has shown increasing concentrations of Dissolved Organic Carbon (DOC) across a large part of the Northern Hemisphere. Several drivers have been implicated including climate change, land management change, nitrogen and sulphur deposition and CO2 enrichment. Analysis of stream water data, supported by evidence from laboratory studies, indicates that an effect of declining sulphur deposition on catchment soil chemistry is likely to be the primary mechanism, but there are relatively few long term soil water chemistry records in the UK with which to investigate this, and other, hypotheses directly. In this paper, we assess temporal relationships between soil solution chemistry and parameters that have been argued to regulate DOC production and, using a unique set of co-located measurements of weather and bulk deposition and soil solution chemistry provided by the UK Environmental Change Network and the Intensive Forest Monitoring Level II Network . We used statistical non-linear trend analysis to investigate these relationships at 5 forested and 4 non-forested sites from 1993 to 2011. Most trends in soil solution DOC concentration were found to be non-linear. Significant increases in DOC occurred mostly prior to 2005. The magnitude and sign of the trends was associated qualitatively with changes in acid deposition, the presence/absence of a forest canopy, soil depth and soil properties. The strongest increases in DOC were seen in acidic forest soils and were most clearly linked to declining anthropogenic acid deposition, while DOC trends at some sites with westerly locations appeared to have been influenced by shorter-term hydrological variation. The results indicate that widespread DOC increases in surface waters observed elsewhere, are most likely dominated by enhanced mobilization of DOC in surficial organic horizons, rather than changes in the soil water chemistry of deeper horizons. While trends in DOC concentrations in surface horizons have flattened out in recent years, further increases may be expected as soil chemistry continues to adjust to declining inputs of acidity.
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The Team Formation problem (TFP) has become a well-known problem in the OR literature over the last few years. In this problem, the allocation of multiple individuals that match a required set of skills as a group must be chosen to maximise one or several social positive attributes. Speci�cally, the aim of the current research is two-fold. First, two new dimensions of the TFP are added by considering multiple projects and fractions of people's dedication. This new problem is named the Multiple Team Formation Problem (MTFP). Second, an optimization model consisting in a quadratic objective function, linear constraints and integer variables is proposed for the problem. The optimization model is solved by three algorithms: a Constraint Programming approach provided by a commercial solver, a Local Search heuristic and a Variable Neighbourhood Search metaheuristic. These three algorithms constitute the first attempt to solve the MTFP, being a variable neighbourhood local search metaheuristic the most effi�cient in almost all cases. Applications of this problem commonly appear in real-life situations, particularly with the current and ongoing development of social network analysis. Therefore, this work opens multiple paths for future research.
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This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.
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In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Objective. To assess factors determining growth in a group of children between 3 months and 6 years old enrolled in a public municipal (i.e., government-supported, not private) day-care center, in comparison to a group of children with similar characteristics but who were not enrolled in the center. Methods. A quasi-experimental study was designed to observe 444 children aged 3 to 72 months from a low-income neighborhood in the city of Sorocaba, in the state of São Paulo, Brazil. Two groups were studied: 164 children enrolled in a local municipal day-care center (intervention group) and 280 not receiving care at the center (nonintervention, comparison group) but instead being cared for at home. Both groups were seen four times over a period of 16 months. At each observation session, the children's weight and height were measured. Information was also collected on the mother's sociodemographic characteristics and the illnesses she had suffered as well as the child's weight and other health characteristics at birth, the child's illnesses in the 15 days before each observation, and any hospitalizations. Results. The children in both groups were from low-income families, with 65% of the families having an average monthly income below US$ 100; 80% of the mothers had received 8 years of schooling or less. Multivariate linear regression analysis showed that at the first observation (just before enrollment in the day-care center), birth weight was the only factor that explained the nutritional differences between the two groups. Subsequent analyses showed that being in day care was the factor that best explained the differences between the groups, especially in terms of the adequacy of weight for age, after controlling for birthweight, sex, age at the beginning of the study, and illnesses in the 15 days before an observation session. The nutritional impact of the intervention was significant as early as 3 months after being enrolled in day care. Conclusions. The nutritional benefits of the care provided at the center outweighed the negative effects sometimes seen in such centers, such as the greater morbidity that children in day-care centers often experience in comparison to children receiving care at home.
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It is believed that the dissolution of chalcopyrite (CuFeS2) in acid medium can be accelerated by the addition of Cl- ions, which modify the electrochemical reactions in the leaching system. Electrochemical noise analysis (ENA) was utilized to evaluate the effect of the Cl- ions and Acidithiobacillus ferrooxidans on the oxidative dissolution of a CPE-chalcopyrite (carbon paste electrode modified with chalcopyrite) in acid medium. The emphasis was on the analysis of the admittance plots (Ac) calculated by ENA. In general, a stable passive behavior was observed, mainly during the initial stages of CPE-chalcopyrite immersion, characterized by a low passive current and a low dispersion of the Ac plots, mainly after bacteria addition. This can be explained by the adhesion of bacterial cells on the CPE-chalcopyrite surface acting as a physical barrier. The greater dispersions in the Ac plots occurred immediately after the Cl- ions addition, in the absence of bacteria characterizing an active-state. In the presence of bacteria the addition of Clions only produced some effect after some time due to the barrier effect caused by bacteria adhesion. © (2009) Trans Tech Publications.
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This paper considers the importance of using a top-down methodology and suitable CAD tools in the development of electronic circuits. The paper presents an evaluation of the methodology used in a computational tool created to support the synthesis of digital to analog converter models by translating between different tools used in a wide variety of applications. This tool is named MS 2SV and works directly with the following two commercial tools: MATLAB/Simulink and SystemVision. Model translation of an electronic circuit is achieved by translating a mixed-signal block diagram developed in Simulink into a lower level of abstraction in VHDL-AMS and the simulation project support structure in SystemVision. The method validation was performed by analyzing the power spectral of the signal obtained by the discrete Fourier transform of a digital to analog converter simulation model. © 2011 IEEE.
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This paper presents the study of the so called Generalized Symmetrical Components, proposed by Tenti et. al. to the analysis of unbalanced periodic non sinusoidal three phase systems. As a result, it was possible to establish a proper relationship between such of generalized symmetrical components and Fortescue symmetrical components to the harmonic frequencies that compose a generic periodic non sinusoidal three phase system. © 2011 IEEE.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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A radial basis function network (RBFN) circuit for function approximation is presented. Simulation and experimental results show that the network has good approximation capabilities. The RBFN was a squared hyperbolic secant with three adjustable parameters amplitude, width and center. To test the network a sinusoidal and sine function,vas approximated.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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In epidemiology, the basic reproduction number R-0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition. R-0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R-0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R-0 >1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable: when R-0 <1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R-0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptibleinfective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R-0 obtained from both approaches are compared, showing good agreement. (C) 2012 Elsevier B.V. All rights reserved.
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Concentrations of 39 organic compounds were determined in three fractions (head, heart and tail) obtained from the pot still distillation of fermented sugarcane juice. The results were evaluated using analysis of variance (ANOVA), Tukey's test, principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). According to PCA and HCA, the experimental data lead to the formation of three clusters. The head fractions give rise to a more defined group. The heart and tail fractions showed some overlap consistent with its acid composition. The predictive ability of calibration and validation of the model generated by LDA for the three fractions classification were 90.5 and 100%, respectively. This model recognized as the heart twelve of the thirteen commercial cachacas (92.3%) with good sensory characteristics, thus showing potential for guiding the process of cuts.
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L'indagine condotta, avvalendosi del paradigma della social network analysis, offre una descrizione delle reti di supporto personale e del capitale sociale di un campione di 80 italiani ex post un trattamento terapeutico residenziale di lungo termine per problemi di tossicodipendenza. Dopo aver identificato i profili delle reti di supporto sociale degli intervistati, si è proceduto, in primis, alla misurazione e comparazione delle ego-centered support networks tra soggetti drug free e ricaduti e, successivamente, all'investigazione delle caratteristiche delle reti e delle forme di capitale sociale – closure e brokerage – che contribuiscono al mantenimento dell'astinenza o al rischio di ricaduta nel post-trattamento. Fattori soggettivi, come la discriminazione pubblica percepita e l'attitudine al lavoro, sono stati inoltre esplorati al fine di investigare la loro correlazione con la condotta di reiterazione nell'uso di sostanze. Dai risultati dello studio emerge che un più basso rischio di ricaduta è positivamente associato ad una maggiore attitudine al lavoro, ad una minore percezione di discriminazione da parte della società, all'avere membri di supporto con un più alto status socio-economico e che mobilitano risorse reputazionali e, infine, all'avere reti più eterogenee nell'occupazione e caratterizzate da più elevati livelli di reciprocità. Inoltre, il capitale sociale di tipo brokerage contribuisce al mantenimento dell'astinenza in quanto garantisce l'accesso del soggetto ad informazioni meno omogenee e la sua esposizione a opportunità più numerose e differenziate. I risultati dello studio, pertanto, dimostrano l'importante ruolo delle personal support networks nel prevenire o ridurre il rischio di ricaduta nel post-trattamento, in linea con precedenti ricerche che suggeriscono la loro incorporazione nei programmi terapeutici per tossicodipendenti.