876 resultados para Model-based bootstrap
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We discuss the well-posedness of a mathematical model that is used in the literature for the simulation of lithium-ion batteries. First, a mathematical model based on a macrohomogeneous approach is presented, following previous work. Then it is shown, from a physical and a mathematical point of view, that a boundary condition widely used in the literature is not correct. Although the errors could be just sign typos (which can be explained as carelessness in the use of d/dx versus d/dn, with n the outward unit vector) and authors using this model probably use the correct boundary condition when they solve it in order to do simulations, readers should be aware of the right choice. Therefore, the deduction of the correct boundary condition is done here, and a mathematical study of the well-posedness of the corresponding problem is presented.
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Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.
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A reduced set of measurement geometries allows the spectral reflectance of special effect coatings to be predicted for any other geometry. A physical model based on flake-related parameters has been used to determine nonredundant measurement geometries for the complete description of the spectral bidirectional reflectance distribution function (BRDF). The analysis of experimental spectral BRDF was carried out by means of principal component analysis. From this analysis, a set of nine measurement geometries was proposed to characterize special effect coatings. It was shown that, for two different special effect coatings, these geometries provide a good prediction of their complete color shift.
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Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.
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The cell concentration and size distribution of the microalgae Nannochloropsis gaditana were studied over the whole growth process. Various samples were taken during the light and dark periods the algae were exposed to. The distributions obtained exhibited positive skew, and no change in the type of distribution was observed during the growth process. The size distribution shifted to lower diameters in dark periods while in light periods the opposite occurred. The overall trend during the growth process was one where the size distribution shifted to larger cell diameters, with differences between initial and final distributions of individual cycles becoming smaller. A model based on the Logistic model for cell concentration as a function of time in the dark period that also takes into account cell respiration and growth processes during dark and light periods, respectively, was proposed and successfully applied. This model provides a picture that is closer to the real growth and evolution of cultures, and reveals a clear effect of light and dark periods on the different ways in which cell concentration and diameter evolve with time.
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The aim of this work is to improve students’ learning by designing a teaching model that seeks to increase student motivation to acquire new knowledge. To design the model, the methodology is based on the study of the students’ opinion on several aspects we think importantly affect the quality of teaching (such as the overcrowded classrooms, time intended for the subject or type of classroom where classes are taught), and on our experience when performing several experimental activities in the classroom (for instance, peer reviews and oral presentations). Besides the feedback from the students, it is essential to rely on the experience and reflections of lecturers who have been teaching the subject several years. This way we could detect several key aspects that, in our opinion, must be considered when designing a teaching proposal: motivation, assessment, progressiveness and autonomy. As a result we have obtained a teaching model based on instructional design as well as on the principles of fractal geometry, in the sense that different levels of abstraction for the various training activities are presented and the activities are self-similar, that is, they are decomposed again and again. At each level, an activity decomposes into a lower level tasks and their corresponding evaluation. With this model the immediate feedback and the student motivation are encouraged. We are convinced that a greater motivation will suppose an increase in the student’s working time and in their performance. Although the study has been done on a subject, the results are fully generalizable to other subjects.
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This paper presents a theoretical model for the analysis of decisions regarding farm household labour allocation. The agricultural household model is selected as the most appropriate theoretical framework; a model based on the assumption that households behave to maximise utility, which is a function of consumption and leisure, and is subject to time and budget constraints. The model can be used to describe the role of government subsidies in farm household labour allocation decisions; in particular the impact of decoupled subsidies on labour allocation can be examined. Decoupled subsidies are a labour-free payment and as such represent an increase in labour-free income or wealth. An increase in wealth allows farm households to work less while maintaining consumption. On the other hand, decoupled subsidies represent a decline in the return to farm labour and may lead to a substitution effect, i.e., farmers may choose to substitute non-farm work for farm work. The theoretical framework proposed in this paper allows for the examination of these two conflicting effects.
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Thesis (Master's)--University of Washington, 2016-06
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In a previous paper, Hoornaert et al. (Powder Technol. 96 (1998); 116-128) presented data from granulation experiments performed in a 50 L Lodige high shear mixer. In this study that same data was simulated with a population balance model. Based on an analysis of the experimental data, the granulation process was divided into three separate stages: nucleation, induction, and coalescence growth. These three stages were then simulated separately, with promising results. it is possible to derive a kernel that fit both the induction and the coalescence growth stage. Modeling the nucleation stage proved to be more challenging due to the complex mechanism of nucleus formation. From this work some recommendations are made for the improvement of this type of model.
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We examine the event statistics obtained from two differing simplified models for earthquake faults. The first model is a reproduction of the Block-Slider model of Carlson et al. (1991), a model often employed in seismicity studies. The second model is an elastodynamic fault model based upon the Lattice Solid Model (LSM) of Mora and Place (1994). We performed simulations in which the fault length was varied in each model and generated synthetic catalogs of event sizes and times. From these catalogs, we constructed interval event size distributions and inter-event time distributions. The larger, localised events in the Block-Slider model displayed the same scaling behaviour as events in the LSM however the distribution of inter-event times was markedly different. The analysis of both event size and inter-event time statistics is an effective method for comparative studies of differing simplified models for earthquake faults.
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Background Reliable information on causes of death is a fundamental component of health development strategies, yet globally only about one-third of countries have access to such information. For countries currently without adequate mortality reporting systems there are useful models other than resource-intensive population-wide medical certification. Sample-based mortality surveillance is one such approach. This paper provides methods for addressing appropriate sample size considerations in relation to mortality surveillance, with particular reference to situations in which prior information on mortality is lacking. Methods The feasibility of model-based approaches for predicting the expected mortality structure and cause composition is demonstrated for populations in which only limited empirical data is available. An algorithm approach is then provided to derive the minimum person-years of observation needed to generate robust estimates for the rarest cause of interest in three hypothetical populations, each representing different levels of health development. Results Modelled life expectancies at birth and cause of death structures were within expected ranges based on published estimates for countries at comparable levels of health development. Total person-years of observation required in each population could be more than halved by limiting the set of age, sex, and cause groups regarded as 'of interest'. Discussion The methods proposed are consistent with the philosophy of establishing priorities across broad clusters of causes for which the public health response implications are similar. The examples provided illustrate the options available when considering the design of mortality surveillance for population health monitoring purposes.
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Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.
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The ‘leading coordinate’ approach to computing an approximate reaction pathway, with subsequent determination of the true minimum energy profile, is applied to a two-proton chain transfer model based on the chromophore and its surrounding moieties within the green fluorescent protein (GFP). Using an ab initio quantum chemical method, a number of different relaxed energy profiles are found for several plausible guesses at leading coordinates. The results obtained for different trial leading coordinates are rationalized through the calculation of a two-dimensional relaxed potential energy surface (PES) for the system. Analysis of the 2-D relaxed PES reveals that two of the trial pathways are entirely spurious, while two others contain useful information and can be used to furnish starting points for successful saddle-point searches. Implications for selection of trial leading coordinates in this class of proton chain transfer reactions are discussed, and a simple diagnostic function is proposed for revealing whether or not a relaxed pathway based on a trial leading coordinate is likely to furnish useful information.
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Many developing south-east Asian governments are not capturing full rent from domestic forest logging operations. Such rent losses are commonly related to institutional failures, where informal institutions tend to dominate the control of forestry activity in spite of weakly enforced regulations. Our model is an attempt to add a new dimension to thinking about deforestation. We present a simple conceptual model, based on individual decisions rather than social or forest planning, which includes the human dynamics of participation in informal activity and the relatively slower ecological dynamics of changes in forest resources. We demonstrate how incumbent informal logging operations can be persistent, and that any spending aimed at replacing the informal institutions can only be successful if it pushes institutional settings past some threshold. (C) 2006 Elsevier B.V. All rights reserved.