955 resultados para Geomorphology -- Maps


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Clinically childhood occipital lobe epilepsy (OLE) manifests itself with distinct syndromes. The traditional EEG recordings have not been able to overcome the difficulty in correlating the ictal clinical symptoms to the onset in particular areas of the occipital lobes. To understand these syndromes it is important to map with more precision the epileptogenic cortical regions in OLE. Experimentally, we studied three idiopathic childhood OLE patients with EEG source analysis and with the simultaneous acquisition of EEG and fMRI, to map the BOLD effect associated with EEG spikes. The spatial overlap between the EEG and BOLD results was not very good, but the fMRI suggested localizations more consistent with the ictal clinical manifestations of each type of epileptic syndrome. Since our first results show that by associating the BOLD effect with interictal spikes the epileptogenic areas are mapped to localizations different from those calculated from EEG sources and that by using different EEG/fMRI processing methods our results differ to some extent, it is very important to compare the different methods of processing the localization of activation and develop a good methodology for obtaining co-registration maps of high resolution EEG with BOLD localizations.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Trabalho de Projeto apresentado como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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The geomorphological materials and forms of the Maraca area of Roraima, Brazil are described, an their sgnificance for land development examined. Significant contrasts are noted in areas presently under rainforest and savanna vegetation. Lateritic gravels and extensive shetwash accumulations in savanna areas constrast with incipient or absent plinthite development, few gravels and limited evidence of colluvium under rainforest. Terrain is in general relatively highly-dissected. Slope profiles are characterised, particularly within the savanna zone, by a relatively steep lower concavity. These contrasts are sharply-demarcated by the present savanna/rainforest bondary, unexpectedly in view of the generally accepted hypothesis of repeated contraction an expansion of Amazonian rainforest throughout the Pleistocene. It is concluded that geomorphological conditions in the Maraca area are not favorable for land develoment.

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In the past decade, the research community has been dedicating considerable effort into indoor positioning systems based on Wi-Fi fingerprinting techniques, mainly due to their capability to exploit existing infrastructures. Crowdsourcing approaches, also known as organic, have been proposed recently to address the problem of creating and maintaining the corresponding radio maps. In these organic systems, the users of the system build the radio map themselves while using it to estimate their own position/location. However, most of these collaborative methods, proposed by several authors, assume that all the users are honest and committed to contribute to a good quality radio map. In this paper we assess the quality of a radio map built collaboratively and propose a method to classify the credibility of individual contributions and the reputation of individual users. Experimental results are presented for an organic indoor location system that has been used by more than one hundred users over a period of around 12 months.

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For a given self-map f of M, a closed smooth connected and simply-connected manifold of dimension m ≥ 4, we provide an algorithm for estimating the values of the topological invariant Dm r [f], which equals the minimal number of r-periodic points in the smooth homotopy class of f. Our results are based on the combinatorial scheme for computing Dm r [f] introduced by G. Graff and J. Jezierski [J. Fixed Point Theory Appl. 13 (2013), 63–84]. An open-source implementation of the algorithm programmed in C++ is publicly available at http://www.pawelpilarczyk.com/combtop/.

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Magdeburg, Univ., Fak. für Informatik, Diss., 2015