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Orientador: Roberto Wagner Lourenço / Resumo: O controle dos vetores do mosquito Aedes aegypti apresenta como um dos principais problemas de saúde pública no mundo representado por duas vertentes importantes como o cuidado com o meio ambiente e pelo investimento em ciência. A preocupação com o meio ambiente é uma das maneiras mais eficazes de conter a reprodução do mosquito Aedes aegypti que, segundo Organização Mundial da Saúde, infecta cerca de 100 milhões de pessoas por ano. Esta pesquisa teve como objetivo principal analisar a distribuição espacial dos casos de dengue confirmados autóctones e importados, bem como dos recipientes de larvas do mosquito no município de Itu, São Paulo no período de 2005 a 2014. Para o desenvolvimento do trabalho foi realizada uma pesquisa junto à Vigilância Epidemiológico da área de estudo para obtenção dos dados, acompanhada de pesquisa bibliográfica e trabalho de campo. Os dados foram tratados por meio de técnicas de geoprocessamento e análise estatística exploratória. Os resultados obtidos demonstraram uma crescente alta de casos e de incidência ao longo dos anos estudados da faixa de 10 anos, sendo que os casos autóctones se sobrepõe em termos de ocorrência aos importados em 88 %. Além disso, foi possível verificar uma distribuição espacial com maiores ocorrências nas regiões centrais da área urbana do município estudado, apresentando as maiores concentrações nos anos de 2007, 2009, 20011 e 2013 do total analisado, com distribuição tendendo para a direção sudeste-noroeste da área de ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The control of the vectors of the mosquito Aedes aegypti presents as one of the main problems of public health in the world acted by two important slopes as the care with the environment and for the investment in science. The concern with the environment is one in the most effective ways of containing the reproduction of the mosquito Aedes aegypti that, second World Organization of the Health, infects about 100 million people a year. This research had as main objective to analyze the space distribution of the cases of primness confirmed autochthonous and mattered, as well as of the containers of larvas of the mosquito in the municipal district of Itu, São Paulo in the period of 2005 the 2014. For the development of the work a research was accomplished the Surveillance Epidemic of the study area close to for obtaining of the data, accompanied of bibliographical research and field work. The data were treated through geoprocessamento techniques and exploratory statistical analysis. The obtained results demonstrated a crescent high of cases and of incidence along the studied years of the 10 year-old strip, and the autochthonous cases are put upon in occurrence terms to the mattered in 88%. Besides, it was possible to verify a space distribution with larger occurrences in the central areas of the urban area of the studied municipal district, presenting the largest concentrations in the years of 2007, 2009, 20011 and 2013 of the analyzed total, with distribution tending for the sou... (Complete abstract click electronic access below) / Mestre

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This thesis discusses four novel statistical methods and approximate inference techniques for analyzing structured neural and molecular sequence data. The main contributions are new algorithms for approximate inference and learning in Bayesian latent variable models involving spatial statistics and nonlinear dynamics. First, we propose an amortized variational inference method to separate a set of overlapping signals into spatially localized source functions without knowledge of the original signals or the mixing process. In the second part of this dissertation, we discuss two approaches for uncovering nonlinear, smooth latent dynamics from sequential data. Both algorithms construct variational families on extensions of nonlinear state space models where the underlying systems are described by hidden stochastic differential equations. The first method proposes a structured approximate posterior describing spatially-dependent linear dynamics, as well as an algorithm that relies on the fixed-point iteration method to achieve convergence. The second method proposes a variational backward simulation technique from an unbiased estimate of the marginal likelihood defined through a subsampling process. In the final chapter, we develop connections between discrete and continuous variational sequential search for Bayesian phylogenetic inference. We propose a technique that uses sequential search to construct a variational objective defined on the composite space of non-clock phylogenetic trees. Each of these techniques are motivated by real problems within computational biology and applied to provide insights into the underlying structure of complex data.

Thesis (Ph.D. (Statistics)) -- University of Limpopo, 2021 / In spatial statistics, several methods have been developed to measure the extent of local and global spatial dependence (clustering) in measured data across areas in a region of research interest. These methods are now routinely implemented in most Geographical Information Systems (GIS) and statistical computer packages. However, spatial statistics for measuring joint spatial dependence of multiple spatial measurement and outcome data have not been well developed. A naive analysis would simply apply univariate spatial dependence methods to each data separately. Though this is simple and straightforward, it ignores possible relationships between multiple spatial data because they may be measuring the same phenomena. Limited work has been done on extending the Moran’s index, a commonly used and applied univariate measure of spatial clustering, to bivariate Moran’s index in order to assess spatial dependence for two spatial data. The overall aim of this PhD was to develop multivariate spatial clustering methods for multiple spatial data, especially in the health sciences. Our proposed multivariate spatial clustering statistic is based on the fundamental theory regarding canonical correlations. We firstly reviewed and applied univariate and bivariate Moran’s indexes to spatial analyses of multiple non-communicable diseases and related risk factors in South Africa. Then we derived our proposed multivariate spatial clustering method, which was evaluated by simulation studies and applied to a spatial analysis of multiple non-communicable diseases and related risk factors in South Africa. Simulation studies showed that our proposed multivariate spatial statistic was able to identify correctly clusters of areas with high risks as well as clusters with low risk.

This work presents methods used to obtain geometric models of spatial mechanisms which can be realized in hardware. Each model is created automatically from the kinematic description of a mechanism. The models are tested for interference between joints and links. Models with interfering links or joints are reshaped automatically into an interference-free configuration. An investigation of the relative efficiency of different interference detection techniques is discussed. A method for determining interferences based on vector loop equations was developed for this work. Other approaches for interference detection include parametric space and a method using parallel coordinates. 2000 line segments were randomly generated to test the three methods. No significant difference between the three techniques was found, but a coarse detection scheme was developed based on observations of intersection conditions in parallel coordinates. The coarse detection technique reduced interference detection times by 48%. The concept of joint positioning freedoms is presented formally for the first time. Using a unidirectional avoidance strategy along a straight line, these repositioning freedoms are exploited in a manner which guarantees the elimination of interferences for revolute, prismatic, and cylindric joints. A unique method for optimal orientation of spheric joint ball-cup pairs is described. Points from an inverse image of the attachment piece for the ball are mapped onto a unit sphere in the reference frame of the cup. The axis of a bounding cone is then used to align the attachment piece for the cup. The method minimizes the chances for collisions between the cup and the ball attachment piece. Elements which attach the joints are modeled as three segments. This has proven to be an optimal representation. Interferences with these elements are eliminated using the elliptical projection of circular paths onto a plane which is perpendicular to the axis of symmetry for an intruding object. Several examples are given illustrating the successful generation of interference-free spatial mechanism models. The mechanisms include an RSSR, an RPCS, an RCCC, and an RRRRRRR. / Ph. D.

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Object recognition is imperfect; often incomplete processing or deprived information yield misperceptions (i.e., misidentification) of objects. While quickly rectified and typically benign, instances of such errors can produce dangerous consequences (e.g., police shootings). Through a series of experiments, this study examined the competitive process of multiple object interpretations (candidates) during the earlier stages of object recognition process using a lexical decision task paradigm. Participants encountered low-pass filtered objects that were previously demonstrated to evoke multiple responses: a highly frequented interpretation (“primary candidates”) and a lesser frequented interpretation (“secondary candidates”). When objects were presented without context, no facilitative effects were observed for primary candidates. However, secondary candidates demonstrated evidence for being actively suppressed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

The present study identifies settlement patterns of the Manteño culture within the cloud forest of southern Manabí by surveying, recording and analyzing the stone architecture found within the drainage basin of the Las Tusas River, Ecuador. The statistical methods used were: Triangulated Irregular Networks or TIN (for topography interpretations), K-means (to determine natural groups for structures based on their dimensions, shape, and wall thickness), Ripley’s K (to determine spatial nature of these groups) and Kernel Density (to visualize their spatial organization). The cloud forest ecotone of southern Manabí was an anthropogenic landscape during the late Integration period. The alluvial valleys of the upper Rio Blanco drainage basin do not represent a hinterland or a periphery occupation but a series of Manteño nucleated settlements raised on terraces and interconnected by strings of linear settlements and dispersed settlements throughout the rugged terrain of this landscape. / Includes bibliography. / Thesis (M.A.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection