27 resultados para Probabilistic decision process model
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
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There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Gesture-based applications have particularities, since users interact in a natural way, much as they interact in the non-digital world. Hence, new requirements are needed on the software design process. This paper shows a software development process model for these applications, including requirement specification, design, implementation, and testing procedures. The steps and activities of the proposed model were tested through a game case study, which is a puzzle game. The puzzle is completed when all pieces of a painting are correctly positioned by the drag and drop action of users hand gesture. It also shows the results obtained of applying a heuristic evaluation on this game. © 2012 IEEE.
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O processo decisório compreende a aplicação de diferentes modelos de tomada de decisão, cada um deles pertinente a uma determinada situação. Entre eles, destacamos como principais os modelos racional, processual, anárquico e político. Para este trabalho, utilizamos os conceitos de Choo (2003), por se tratar de uma das principais obras a respeito do tema existente na literatura e, assim, analisamos cada um dos modelos propostos pelo autor. A partir da análise dos modelos, foi possível estabelecer relações entre eles e maneira pela qual a informação orgânica - produzida internamente à organização, participa do processo decisório, mais especificamente no âmbito de cada modelo. Por último, a partir das inferências realizadas, propomos um novo modelo de tomada de decisão, cuja base de sustentação é a informação orgânica.
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O surgimento de novas tecnologias e serviços vem impondo mudanças substanciais ao tradicional sistema de telecomunicações. Múltiplas possibilidades de evolução do sistema fazem da etapa de planejamento um procedimento não só desejável como necessário, principalmente num ambiente de competitividade. A utilização de metodologias abrangentes e flexíveis que possam auxiliar no processo de decisão, fundadas em modelos de otimização, parece um caminho inevitável. Este artigo propõe um modelo de programação linear inteiro misto para ajudar no planejamento estratégico de sistemas de telecomunicações, e em particular da rede de acesso. Os principais componentes de custo e receita são identificados e o modelo é desenvolvido para determinar a configuração da rede (serviços, tecnologias, etc) que maximize a receita esperada pelo operador do sistema. O conceito de números fuzzy é adotado para avaliar o risco técnico-econômico em situações de imprecisão nos dados de demanda. Resultados de experimentos computacionais são apresentados e discutidos.
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This paper presents a new model for the representation of electrodes' filaments of hot-cathode fluorescent lamps, during preheating processes based on the injection of currents with constant root mean square (rms) values. The main improvement obtained with this model is the prediction of the R-h/R-c ratio during the preheating process, as a function of the preheating time and of the rms current injected in the electrodes. Using the proposed model, it is possible to obtain an estimate of the time interval and the current that should be provided by the electronic ballast, in order to ensure a suitable preheating process. is estimate of time and current can be used as input data in the design of electronic ballasts with programmed lamp start, permitting the prediction of the R-h/R-c ratio during the initial steps of the design (theoretical analysis and digital simulation). Therefore, the use of the proposed model permits to reduce the necessity of several empirical adjustments in the prototype, in order to set the operation of electronic ballasts during the preheating process. This fact reduces time and costs associated to the global design procedure of electronic ballasts.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The implementation of an Export and Processing Zone (ZEPs) brings several benefits to the local, state and federal economy, but often, only socioeconomic factors are considered, apart from several other factors that should be analyzed, such as the environment. In this context of industrialization and the struggle for sustainable development, this work propose to incorporate the environmental variable in the decision process for establishing industrial areas, in particular, the ZPE in the city of Fernandópolis, São Paulo state, Brazil, by examining several physical and environmental factors such as slope intervals, geological features, pedological factors and land use. Developed using a multicriteria analysis, a model has been elaborated, where these factors have received a proportional value according with their importance, supported by a GIS tool (Geographical Information System) and remote sensing products, such as images from CBERS satellite and SRTM radar, showing the suited areas for industrial activities, considering environmental conditions. This model may assist to take better decision about the ZPE implementation area and to reduce the negative environmental impacts that would result of poorly planned locations
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Psychological factors are gaining more space in sports, and increasingly common related professional psychology are inserted in the sporting context. Seeking a better understanding of the manifestations of leadership in football between technicians of different categories this study aimed to verify whether there is a preferred style of leadership among the football coaches and if there are differences between the leadership style ideal and real seconded by same. The methodology used the Search Specification (CERVO and BERVIAN, 2004) relying on the implementation of the Revised Leadership Scale for Sport (ELRE), ideal and real versions Profile, With the participation of twenty football coaches in the field (n = 20), working in teams of males in the City of São Bernardo do Campo - SP, and to process the data we calculated the Cronbach alpha to verify the reliability of the scale, and the average of the results relying on the software application SPSS version 17.0 for Windows. Of the total participants 30% have a degree in Physical Education and are inserted in the football an average of 8 years in different roles and the prevalence of autocratic decision-making model, with an alpha of 0.87 results in the ideal profile and the actual profile of alpha 0.86 , So the scale is stable and reliable. We conclude that the model of autocratic decision not differ very significantly compared to the model of democratic decision. Regarding the interaction with the group of technicians the situational model is highlighted in research showing that technicians take into account situational factors.
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We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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A matrix approach is described for assessing the variance of effects in incomplete diallels designs. The method is illustrated by reference to simulated complete and incomplete diallels using different combinations of constraints, average degree of dominance and, for the incomplete diallel, number of hybrids. Our results showed that caution should be taken in working with incomplete diallels under conditions of overdominance because there were changes in the rank of the genotypes when the excluded hybrid had parents with a low frequency of the favorable allele (i.e. the allele which increases expression of a character). The expression described in this paper is a rapid and safe approach to estimate variances and covariances of the effects of contrasts of incomplete diallels. Copyright by the Brazilian Society of Genetics.
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Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.
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Pós-graduação em Geografia - FCT
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Pós-graduação em Direito - FCHS