144 resultados para Mathematical modeling.


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This article summarizes the implementation of an online process management, analysis, and optimization tool at Lwarcel Celulose e Papel, within the PIMS and MES philosophy, for process indicator implementation, understanding of variables, and their cause-effect relationship in the process, as well as the achievement of operational benchmarking. The process analysis, by means of statistical tools, allied to mathematical modeling algorithms used in Wedge, makes it possible to identify the relevant information for process and quality improvement with regard to efficiency, equipment maintenance, productivity, and uniformity of the end product quality, reduction of unwanted shutdowns, and quicker resolution of process problems.

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The purpose of this paper is to present a computer model that enables the operation analysis of a tuned filter as an attenuator device of harmonic generated 12 and 18-pulses converters with Y-generalized differential connection. Are presented in this study physical considerations, mathematical modeling and digital simulations in the frequency domain using the software Orcad-Pspice®, which allows a spectral analysis of the harmonic components and supports the search for an optimal filtering process. It is unequivocally demonstrated the feasibility of the application as an alternative to optimize the use of multipulse converters, and enable the operation of this device within the established regulatory standards. The validation of the proposed model is based on results obtained in the time domain using Matlab/Simulink®. © 2011 IEEE.

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This paper reveals new contributions to the analysis and development of mitigating harmonic distortion devices. Considering the variety of sequential distribution of harmonic current, in the use of passive filters, one can point out the electromagnetic blocking device, which have received particular attention due to its robustness and low cost of installation. In this context, aiming the evaluation of the reliability of the results obtained through mathematical modeling, experimental tests are carried out using a low-power prototype, highlighting particular aspects related to its function as a zero-sequence harmonic blocking. © 2011 IEEE.

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This article deals with the development of three competencies defined and studied in the context of Statistics Education (literacy, thinking and statistical reasoning). These competencies based on interpretation and understanding of critical information from real data are associated with an education geared toward the formation of critical citizenship and are in agreement with the principles that guide Critical Education. In this context, we consider Mathematical Modeling as a concrete possibility for integration between Critical Education and Education Statistics. We show that work with modeling projects in the classroom takes place in a context in which teaching is guided by the fundamentals of Critical Education. We present a project entitled Teaching Statistics and the financial market which illustrates the congruence between the objectives of Education Statistics and Critical Education.

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In this paper, we present GPIMEM, a group that has been developing research in Mathematics Education related to computers and other media since 1993 to understand how mathematical knowledge can be produced with these technological resources, in face-to-face as well as online distance education. Members of the group dialogue with different fields of knowledge such as philosophy, history, psychology, anthropology, sociology, arts and technology, among others, to inform their research. The research addresses various topics relevant to Mathematics Education, including methodological and epistemological aspects of teaching and learning, of mathematical modeling and teacher education, always within a qualitative research perspective. We begin with the historical presentation of the group, revealing its dynamics and organization of work, followed by reflections on qualitative research methodology and description of research conducted over the past five years. Finally, we present a synthesis of the theories developed by the group and expectations for the future.

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The objective of this study was to develop and evaluate a mathematical model used to estimate the daily amino acid requirements of individual growing-finishing pigs. The model includes empirical and mechanistic model components. The empirical component estimates daily feed intake (DFI), BW, and daily gain (DG) based on individual pig information collected in real time. Based on DFI, BW, and DG estimates, the mechanistic component uses classic factorial equations to estimate the optimal concentration of amino acids that must be offered to each pig to meet its requirements. The model was evaluated with data from a study that investigated the effect of feeding pigs with a 3-phase or daily multiphase system. The DFI and BW values measured in this study were compared with those estimated by the empirical component of the model. The coherence of the values estimated by the mechanistic component was evaluated by analyzing if it followed a normal pattern of requirements. Lastly, the proposed model was evaluated by comparing its estimates with those generated by the existing growth model (InraPorc). The precision of the proposed model and InraPorc in estimating DFI and BW was evaluated through the mean absolute error. The empirical component results indicated that the DFI and BW trajectories of individual pigs fed ad libitum could be predicted 1 d (DFI) or 7 d (BW) ahead with the average mean absolute error of 12.45 and 1.85%, respectively. The average mean absolute error obtained with the InraPorc for the average individual of the population was 14.72% for DFI and 5.38% for BW. Major differences were observed when estimates from InraPorc were compared with individual observations. The proposed model, however, was effective in tracking the change in DFI and BW for each individual pig. The mechanistic model component estimated the optimal standardized ileal digestible Lys to NE ratio with reasonable between animal (average CV = 7%) and overtime (average CV = 14%) variation. Thus, the amino acid requirements estimated by model are animal- and time-dependent and follow, in real time, the individual DFI and BW growth patterns. The proposed model can follow the average feed intake and feed weight trajectory of each individual pig in real time with good accuracy. Based on these trajectories and using classical factorial equations, the model makes it possible to estimate dynamically the AA requirements of each animal, taking into account the intake and growth changes of the animal. © 2012 American Society of Animal Science. All rights reserved.

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According to CONAMA Resolution No. 357, the Água Branca Creek is framed in Class 2 and along its course the characteristics should be consistent with this class. Evaluation of diffuse loads and simulation of auto-purification in the Água Branca Creek allowed evaluating the alterations in the quality of the freshwater. The major contribution of diffuse loads in the basin of the White Water Creek is related to agriculture. The QUAL2K modeling identified the autopurification zones at Água Branca Creek and indicated the necessity BDO removal of 75%.

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Background: Plasmodium vivax is a widely distributed, neglected parasite that can cause malaria and death in tropical areas. It is associated with an estimated 80-300 million cases of malaria worldwide. Brazilian tropical rain forests encompass host- and vector-rich communities, in which two hypothetical mechanisms could play a role in the dynamics of malaria transmission. The first mechanism is the dilution effect caused by presence of wild warm-blooded animals, which can act as dead-end hosts to Plasmodium parasites. The second is diffuse mosquito vector competition, in which vector and non-vector mosquito species compete for blood feeding upon a defensive host. Considering that the World Health Organization Malaria Eradication Research Agenda calls for novel strategies to eliminate malaria transmission locally, we used mathematical modeling to assess those two mechanisms in a pristine tropical rain forest, where the primary vector is present but malaria is absent. Methodology/Principal Findings: The Ross-Macdonald model and a biodiversity-oriented model were parameterized using newly collected data and data from the literature. The basic reproduction number (R0) estimated employing Ross-Macdonald model indicated that malaria cases occur in the study location. However, no malaria cases have been reported since 1980. In contrast, the biodiversity-oriented model corroborated the absence of malaria transmission. In addition, the diffuse competition mechanism was negatively correlated with the risk of malaria transmission, which suggests a protective effect provided by the forest ecosystem. There is a non-linear, unimodal correlation between the mechanism of dead-end transmission of parasites and the risk of malaria transmission, suggesting a protective effect only under certain circumstances (e.g., a high abundance of wild warm-blooded animals). Conclusions/Significance: To achieve biological conservation and to eliminate Plasmodium parasites in human populations, the World Health Organization Malaria Eradication Research Agenda should take biodiversity issues into consideration. © 2013 Laporta et al.

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Purpose: The aim of this study was to verify whether there is an association between anaerobic running capacity (ARC) values, estimated from two-parameter models, and maximal accumulated oxygen deficit (MAOD) in army runners. Methods: Eleven, trained, middle distance runners who are members of the armed forces were recruited for the study (20 ± 1 years). They performed a critical velocity test (CV) for ARC estimation using three mathematical models and an MAOD test, both tests were applied on a motorized treadmill. Results: The MAOD was 61.6 ± 5.2 mL/kg (4.1 ± 0.3 L). The ARC values were 240.4 ± 18.6 m from the linear velocity-inverse time model, 254.0 ± 13.0 m from the linear distance-time model, and 275.2 ± 9.1 m from the hyperbolic time-velocity relationship (nonlinear 2-parameter model), whereas critical velocity values were 3.91 ± 0.07 m/s, 3.86 ± 0.08 m/s and 3.80 ± 0.09 m/s, respectively. There were differences (P < 0.05) for both the ARC and the CV values when compared between velocity-inverse time linear and nonlinear 2-parameter mathematical models. The different values of ARC did not significantly correlate with MAOD. Conclusion: In conclusion, estimated ARC did not correlate with MAOD, and should not be considered as an anaerobic measure of capacity for treadmill running. © 2013 Elsevier Masson SAS. All rights reserved.

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Pós-graduação em Engenharia Elétrica - FEIS

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Elétrica - FEIS

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Pós-graduação em Engenharia Elétrica - FEIS

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)