Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution.
The mechanism of ionic conduction through polymer coatings has been investigated. The presence of highly permeable areas in the coating (designated as D type areas), impose an electrochemical inhomogeneity which is identified by change in the ionic resistance as measured by DC method. The effect of coating thickness was studied on D type behaviour of coatings. A structural model is proposed to explain the changes in conduction mechanism by variation of coating thickness. Statistical models based on numerical (simulation-based) and analytical (
In a free viewpoint video system, the scene is captured by a number of cameras and it would be desirable to optimize the configuration of cameras, such as their location or orientation, to improve the rendering quality. This paper introduces a mathematical representation of the multi-camera geometry, called the correspondence field (CF), which can be used to quantify the suitability of a camera configuration for a given arrangement of objects in the scene. The correspondence field describes the spatial topology of the intersecting rays of cameras, arranged as a number of layers or surfaces in the field of view of cameras. The paper derives the topology of CF for certain camera arrangements and analyzes the impact of changes in camera location or orientation on this topology. It demonstrates that CF can be used to find the optimum camera configuration for a given objective. It also presents simulation results of this method using our light field simulator. In a free viewpoint video system, the scene is captured by a number of cameras and it would be desirable to optimize the configuration of cameras, such as their location or orientation, to improve the rendering quality. This paper introduces a mathematical representation of the multi camera geometry, called the correspondence field (CF), which can be used to quantify the suitability of a camera configuration for a given arrangement of objects in the scene. The correspondence field describes the spatial topology of the intersecting rays of cameras, arranged as a number of layers or surfaces in the field of view of cameras. The paper derives the topology of CF for certain camera arrangements and analyzes the impact of changes in camera location or orientation on this topology. It demonstrates that CF can be used to find the optimum camera configuration for a given objective. It also presents simulation results of this method using our light field simulator.
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