984 resultados para knowledge modeling


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OBJECTIVE To analyze Brazilian literature on body image and the theoretical and methodological advances that have been made. METHODS A detailed review was undertaken of the Brazilian literature on body image, selecting published articles, dissertations and theses from the SciELO, SCOPUS, LILACS and PubMed databases and the CAPES thesis database. Google Scholar was also used. There was no start date for the search, which used the following search terms: “body image” AND “Brazil” AND “scale(s)”; “body image” AND “Brazil” AND “questionnaire(s)”; “body image” AND “Brazil” AND “instrument(s)”; “body image” limited to Brazil and “body image”. RESULTS The majority of measures available were intended to be used in college students, with half of them evaluating satisfaction/dissatisfaction with the body. Females and adolescents of both sexes were the most studied population. There has been a significant increase in the number of available instruments. Nevertheless, numerous published studies have used non-validated instruments, with much confusion in the use of the appropriate terms (e.g., perception, dissatisfaction, distortion). CONCLUSIONS Much more is needed to understand body image within the Brazilian population, especially in terms of evaluating different age groups and diversifying the components/dimensions assessed. However, interest in this theme is increasing, and important steps have been taken in a short space of time.

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OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

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The growing heterogeneity of networks, devices and consumption conditions asks for flexible and adaptive video coding solutions. The compression power of the HEVC standard and the benefits of the distributed video coding paradigm allow designing novel scalable coding solutions with improved error robustness and low encoding complexity while still achieving competitive compression efficiency. In this context, this paper proposes a novel scalable video coding scheme using a HEVC Intra compliant base layer and a distributed coding approach in the enhancement layers (EL). This design inherits the HEVC compression efficiency while providing low encoding complexity at the enhancement layers. The temporal correlation is exploited at the decoder to create the EL side information (SI) residue, an estimation of the original residue. The EL encoder sends only the data that cannot be inferred at the decoder, thus exploiting the correlation between the original and SI residues; however, this correlation must be characterized with an accurate correlation model to obtain coding efficiency improvements. Therefore, this paper proposes a correlation modeling solution to be used at both encoder and decoder, without requiring a feedback channel. Experiments results confirm that the proposed scalable coding scheme has lower encoding complexity and provides BD-Rate savings up to 3.43% in comparison with the HEVC Intra scalable extension under development. © 2014 IEEE.

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Time-sensitive Wireless Sensor Network (WSN) applications require finite delay bounds in critical situations. This paper provides a methodology for the modeling and the worst-case dimensioning of cluster-tree WSNs. We provide a fine model of the worst-case cluster-tree topology characterized by its depth, the maximum number of child routers and the maximum number of child nodes for each parent router. Using Network Calculus, we derive “plug-and-play” expressions for the endto- end delay bounds, buffering and bandwidth requirements as a function of the WSN cluster-tree characteristics and traffic specifications. The cluster-tree topology has been adopted by many cluster-based solutions for WSNs. We demonstrate how to apply our general results for dimensioning IEEE 802.15.4/Zigbee cluster-tree WSNs. We believe that this paper shows the fundamental performance limits of cluster-tree wireless sensor networks by the provision of a simple and effective methodology for the design of such WSNs.

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Dragonflies demonstrate unique and superior flight performances than most of the other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper, the dynamics of a dragonfly-inspired robot is studied. The system performance is analyzed in terms of time response and robustness. The development of computational simulation based on the dynamics of the robotic dragonfly allows the test of different control algorithms. We study different movements, the dynamics, and the level of dexterity in wing motion of the dragonfly. The results are positive for the construction of flying platforms that effectively mimic the kinematics and dynamics of dragonflies and potentially exhibit superior flight performance than existing flying platforms.

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It is generally agreed that major changes in work are taking place in the organisation of work as corporate structures are transformed in the context of economic globalisation and rapid technological change. But how can these changes be understood? And what are the impacts on social institutions and on workers and their families? The WORKS project brought together 17 research institutes in 13 European countries to investigate these important issues through a comprehensive four year research programme.

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Global restructuring processes have not only strong implications for European working and living realities, but also have specific outcomes with regard to gender relations. The following contribution analyses in which way global restructuring shapes current gender relations in order to identify important trends and developments for future gender (in)equalities at the workplace. On the basis of a large qualitative study on global restructuring and impacts on different occupational groups it argues that occupational belonging in line with skill and qualification levels are crucial factors to assess the further development of gender relations at work. Whereas global restructuring in knowledge-based occupations may provide new opportunities for female employees, current restructuring is going to deteriorate female labour participation in service occupations. In contrast, manufacturing occupations can be characterised by persistent gender relations, which do not change in spite of major restructuring processes at the work place. Taking the institutional perspective into account, it seems to be crucial to integrate the occupational perspective in order to apply adequate policy regulations to prevent the reinforcement of gender related working patterns in the near future.

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The self similar branching arrangement of the airways makes the respiratory system an ideal candidate for the application of fractional calculus theory. The fractal geometry is typically characterized by a recurrent structure. This study investigates the identification of a model for the respiratory tree by means of its electrical equivalent based on intrinsic morphology. Measurements were obtained from seven volunteers, in terms of their respiratory impedance by means of its complex representation for frequencies below 5 Hz. A parametric modeling is then applied to the complex valued data points. Since at low-frequency range the inertance is negligible, each airway branch is modeled by using gamma cell resistance and capacitance, the latter having a fractional-order constant phase element (CPE), which is identified from measurements. In addition, the complex impedance is also approximated by means of a model consisting of a lumped series resistance and a lumped fractional-order capacitance. The results reveal that both models characterize the data well, whereas the averaged CPE values are supraunitary and subunitary for the ladder network and the lumped model, respectively.

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This article addresses the problem of obtaining reduced complexity models of multi-reach water delivery canals that are suitable for robust and linear parameter varying (LPV) control design. In the first stage, by applying a method known from the literature, a finite dimensional rational transfer function of a priori defined order is obtained for each canal reach by linearizing the Saint-Venant equations. Then, by using block diagrams algebra, these different models are combined with linearized gate models in order to obtain the overall canal model. In what concerns the control design objectives, this approach has the advantages of providing a model with prescribed order and to quantify the high frequency uncertainty due to model approximation. A case study with a 3-reach canal is presented, and the resulting model is compared with experimental data. © 2014 IEEE.

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This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

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A mathematical model that simulates the operation of a solid-state bipolar Marx modulator topology, including the influence of parasitic capacitances is presented and discussed as a tool to analyze the circuit behavior and to assist the design engineer to select the semiconductor components and to enhance the operating performance. Simulations show good agreement with experimental results, considering a four stage circuit assembled with 1200 V isolated gate bipolar transistors and diodes, operating at 1000 V dc input voltage and 1-kHz frequency, giving 4 kV and 10-mu s output pulses into several resistive loads. Results show that parasitic capacitances between Marx cells to ground can significantly load the solid-state switches, adding new operating circuit conditions.

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This text is based on a research, which is still in progress, whose main objective is to identify and understand what are the main difficulties of future mathematics teachers of basic education are, regarding their content knowledge in geometry in the context of the curricular unit of Geometry during their undergraduate degree. We chose a qualitative approach in the form of case study, in which data collection was done through observation, interviews, a diverse set of tasks, a diagnostic test and other documents. This paper focuses on the test given to prospective teachers at the beginning of the course. The preliminary analysis of the data points to a weak performance of preservice teachers in the test issues addressing elementary knowledge of Geometry

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Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

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We prove existence, uniqueness, and stability of solutions of the prescribed curvature problem (u'/root 1 + u'(2))' = au - b/root 1 + u'(2) in [0, 1], u'(0) = u(1) = 0, for any given a > 0 and b > 0. We also develop a linear monotone iterative scheme for approximating the solution. This equation has been proposed as a model of the corneal shape in the recent paper (Okrasinski and Plociniczak in Nonlinear Anal., Real World Appl. 13:1498-1505, 2012), where a simplified version obtained by partial linearization has been investigated.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores