10 resultados para Probabilistic interpretation

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Dentistry currently reveals itself to be open to new ideas about the construction of meanings for oral health. This openness leads to the social production of health revealing the contextualization of the social and historical aspects of the sundry knowledge in the development of oral health for different communities. With this research, we seek to build meanings for oral health with a group of elderly people. With this objective in mind, we propose an approximation between discourses on oral health mentioned by the elderly and the Social Constructionist discourse. We interviewed 14 elderly people enrolled in a Family Health Unit in Ribeirao Preto, State of Sao Paulo, in the first semester of 2010, and identified two interpretative repertoires through Discourse Analysis, which showed the relationship between 1 Lack of information and dental assistance in childhood, and 2 - Primary Health Care building the meaning of oral health. We concluded that Social Constructionism works epistemologically for the construction of meanings for oral health and that primary health is essential for appreciation and health care that enables the construction of meanings in oral health by the elderly that create conditions for self-care and healthy attitudes.

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Patterns of species interactions affect the dynamics of food webs. An important component of species interactions that is rarely considered with respect to food webs is the strengths of interactions, which may affect both structure and dynamics. In natural systems, these strengths are variable, and can be quantified as probability distributions. We examined how variation in strengths of interactions can be described hierarchically, and how this variation impacts the structure of species interactions in predator-prey networks, both of which are important components of ecological food webs. The stable isotope ratios of predator and prey species may be particularly useful for quantifying this variability, and we show how these data can be used to build probabilistic predator-prey networks. Moreover, the distribution of variation in strengths among interactions can be estimated from a limited number of observations. This distribution informs network structure, especially the key role of dietary specialization, which may be useful for predicting structural properties in systems that are difficult to observe. Finally, using three mammalian predator-prey networks ( two African and one Canadian) quantified from stable isotope data, we show that exclusion of link-strength variability results in biased estimates of nestedness and modularity within food webs, whereas the inclusion of body size constraints only marginally increases the predictive accuracy of the isotope-based network. We find that modularity is the consequence of strong link-strengths in both African systems, while nestedness is not significantly present in any of the three predator-prey networks.

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This paper addresses the numerical solution of random crack propagation problems using the coupling boundary element method (BEM) and reliability algorithms. Crack propagation phenomenon is efficiently modelled using BEM, due to its mesh reduction features. The BEM model is based on the dual BEM formulation, in which singular and hyper-singular integral equations are adopted to construct the system of algebraic equations. Two reliability algorithms are coupled with BEM model. The first is the well known response surface method, in which local, adaptive polynomial approximations of the mechanical response are constructed in search of the design point. Different experiment designs and adaptive schemes are considered. The alternative approach direct coupling, in which the limit state function remains implicit and its gradients are calculated directly from the numerical mechanical response, is also considered. The performance of both coupling methods is compared in application to some crack propagation problems. The investigation shows that direct coupling scheme converged for all problems studied, irrespective of the problem nonlinearity. The computational cost of direct coupling has shown to be a fraction of the cost of response surface solutions, regardless of experiment design or adaptive scheme considered. (C) 2012 Elsevier Ltd. All rights reserved.

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This article develops an ecological economic interpretation of the Jevons effect. Moreover, it is argued that under the neoclassical paradigm there are no elements with which to foresee the long-term existence of this phenomenon. The objective of these arguments is to demonstrate that the Jevons effect can be used to compare the ability of neoclassical and ecological economics describing the social appropriation of nature. This is elaborated in two steps. First, we show the importance of the thesis that the economy cannot be cut off from the biophysical materiality of what is produced to give consistency to the so-called Khazzoom-Brookes postulate. It is made clear that this supposition is exogenous to the neoclassical paradigm. Second, the supposition of the biophysical materiality of what is produced is utilized to make an ecological economic interpretation of the Jevons effect. Afterwards, a comparison is made between the neoclassical and the ecological economic perspectives. This comparison leads to the following conclusions: (i) the persistent presence of the Jevons effect in the long run is an anomaly in the neoclassical paradigm; (ii) the observation of the non-existence of the Jevons effect is a refutation of the supposition that economic growth and biophysical materiality are not separable, a central thesis defended by ecological economists. This situation makes possible to use the Jevons effect as a 'laboratory test' to compare the ability of neoclassical and ecological economic paradigms to describe the social appropriation of nature. (C) 20111 Elsevier B.V. All rights reserved.

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Background: In normal aging, the decrease in the syntactic complexity of written production is usually associated with cognitive deficits. This study was aimed to analyze the quality of older adults' textual production indicated by verbal fluency (number of words) and grammatical complexity (number of ideas) in relation to gender, age, schooling, and cognitive status. Methods: From a probabilistic sample of community-dwelling people aged 65 years and above (n = 900), 577 were selected on basis of their responses to the Mini-Mental State Examination (MMSE) sentence writing, which were submitted to content analysis; 323 were excluded as they left the item blank or performed illegible or not meaningful responses. Education adjusted cut-off scores for the MMSE were used to classify the participants as cognitively impaired or unimpaired. Total and subdomain MMSE scores were computed. Results: 40.56% of participants whose answers to the MMSE sentence were excluded from the analyses had cognitive impairment compared to 13.86% among those whose answers were included. The excluded participants were older and less educated. Women and those older than 80 years had the lowest scores in the MMSE. There was no statistically significant relationship between gender, age, schooling, and textual performance. There was a modest but significant correlation between number of words written and the scores in the Language subdomain. Conclusions: Results suggest the strong influence of schooling and age over MMSE sentence performance. Failing to write a sentence may suggest cognitive impairment, yet, instructions for the MMSE sentence, i.e. to produce a simple sentence, may limit its clinical interpretation.

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Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

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Structural durability is an important criterion that must be evaluated for every type of structure. Concerning reinforced concrete members, chloride diffusion process is widely used to evaluate durability, especially when these structures are constructed in aggressive atmospheres. The chloride ingress triggers the corrosion of reinforcements; therefore, by modelling this phenomenon, the corrosion process can be better evaluated as well as the structural durability. The corrosion begins when a threshold level of chloride concentration is reached at the steel bars of reinforcements. Despite the robustness of several models proposed in literature, deterministic approaches fail to predict accurately the corrosion time initiation due the inherent randomness observed in this process. In this regard, structural durability can be more realistically represented using probabilistic approaches. This paper addresses the analyses of probabilistic corrosion time initiation in reinforced concrete structures exposed to chloride penetration. The chloride penetration is modelled using the Fick's diffusion law. This law simulates the chloride diffusion process considering time-dependent effects. The probability of failure is calculated using Monte Carlo simulation and the first order reliability method, with a direct coupling approach. Some examples are considered in order to study these phenomena. Moreover, a simplified method is proposed to determine optimal values for concrete cover.

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Semi-qualitative probabilistic networks (SQPNs) merge two important graphical model formalisms: Bayesian networks and qualitative probabilistic networks. They provade a very Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks and qualitative probabilistic networks. They provide a very general modeling framework by allowing the combination of numeric and qualitative assessments over a discrete domain, and can be compactly encoded by exploiting the same factorization of joint probability distributions that are behind the bayesian networks. This paper explores the computational complexity of semi-qualitative probabilistic networks, and takes the polytree-shaped networks as its main target. We show that the inference problem is coNP-Complete for binary polytrees with multiple observed nodes. We also show that interferences can be performed in time linear in the number of nodes if there is a single observed node. Because our proof is construtive, we obtain an efficient linear time algorithm for SQPNs under such assumptions. To the best of our knowledge, this is the first exact polynominal-time algorithm for SQPn. Together these results provide a clear picture of the inferential complexity in polytree-shaped SQPNs.

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Due to the growing interest in social networks, link prediction has received significant attention. Link prediction is mostly based on graph-based features, with some recent approaches focusing on domain semantics. We propose algorithms for link prediction that use a probabilistic ontology to enhance the analysis of the domain and the unavoidable uncertainty in the task (the ontology is specified in the probabilistic description logic crALC). The scalability of the approach is investigated, through a combination of semantic assumptions and graph-based features. We evaluate empirically our proposal, and compare it with standard solutions in the literature.

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To interpret the mean depth of cosmic ray air shower maximum and its dispersion, we parametrize those two observables as functions of the rst two moments of the lnA distribution. We examine the goodness of this simple method through simulations of test mass distributions. The application of the parameterization to Pierre Auger Observatory data allows one to study the energy dependence of the mean lnA and of its variance under the assumption of selected hadronic interaction models. We discuss possible implications of these dependences in term of interaction models and astrophysical cosmic ray sources.