10 resultados para Spatial Data Quality

em Universidade Federal do Rio Grande do Norte(UFRN)


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This dissertation considered the development of two papers, both related to mortality in Brazil. In the first article, "The context of mortality according to the three broad groups of causes of death in Brazilian capitals, 2000 and 2010", the objective was to analyze the mortality rate according to the three major groups of causes of death in Brazilian capitals. In the second article, "Typology and characteristics of mortality from external causes in the municipalities in the Northeast of Brazil, 2000 and 2010", it was built up a typology for the Northeastern municipalities taking into account information on mortality from external causes and a set of indicators related to socioeconomic, demographic, and infrastructure aspects of such municipalities, both articles for the years 2000 and 2010. Thus, we used data from the Mortality Information System of the Ministry of Health. Furthermore, it was used information from the Demographic Census for those years. The variables relating to socioeconomic and demographic conditions used in this study were those available on the home page of the United Nations Program for Development. The variables relating to socioeconomic and demographic conditions used in this study were those available on the home page of the United Nations Program for Development. Was used in Article 1 the pro-rata distribution method to accomplish the redistribution of ill-defined causes. Moreover, made use of the technique of cluster analysis with the aim of grouping the capital that had proportions of deaths from ill-defined causes similar to each other. Already in Section 2, we used the technique of Empirical Bayesian estimation; spatial statistics technique; and finally, the Grade of Membership method to find types of municipalities from information on mortality from external causes associated with socioeconomic, demographic and infrastructure variables. As the main results, it stands out in Article 1, in relation to data quality, we observed the formation of four groups of similar capital between themselves, as the proportion of illdefined causes. Regarding the behavior of mortality, according to the three major groups of causes of death, it was noted both for 2000 and for 2010 the prevalence of deaths from noncommunicable diseases for both sexes, although the reduction was identified rates in some of the capitals. Communicable diseases stood out as the second cause of death among women. Also, we found that deaths due to external causes are responsible for the second cause of death among men, as well as presenting an increase among women. As for the Article 2, stands out, in general, not just an extension of mortality from external causes in the municipalities, as well as an enlargement of the configurator stain existence of external cause deaths for the whole area of Northeast. Regarding the typology of municipalities, three vi extreme profiles were buit: the profile 1, which comprises municipalities with high rates of mortality from external causes and the best social indicators; the profile 2, that was composed of municipalities that are characterized by having low mortality rates from external causes and the lowest social indicators; and the profile 3, that brings together municipalities with intermediate mortality rates and median values considered in relation to social indicators. Although we have not seen changes in the characteristics of the profiles, we observed an increase in the proportion of municipalities that belong to the extreme profile 3, taking into account the mixed profiles.

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In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

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The study of complex systems has become a prestigious area of science, although relatively young . Its importance was demonstrated by the diversity of applications that several studies have already provided to various fields such as biology , economics and Climatology . In physics , the approach of complex systems is creating paradigms that influence markedly the new methods , bringing to Statistical Physics problems macroscopic level no longer restricted to classical studies such as those of thermodynamics . The present work aims to make a comparison and verification of statistical data on clusters of profiles Sonic ( DT ) , Gamma Ray ( GR ) , induction ( ILD ) , neutron ( NPHI ) and density ( RHOB ) to be physical measured quantities during exploratory drilling of fundamental importance to locate , identify and characterize oil reservoirs . Software were used : Statistica , Matlab R2006a , Origin 6.1 and Fortran for comparison and verification of the data profiles of oil wells ceded the field Namorado School by ANP ( National Petroleum Agency ) . It was possible to demonstrate the importance of the DFA method and that it proved quite satisfactory in that work, coming to the conclusion that the data H ( Hurst exponent ) produce spatial data with greater congestion . Therefore , we find that it is possible to find spatial pattern using the Hurst coefficient . The profiles of 56 wells have confirmed the existence of spatial patterns of Hurst exponents , ie parameter B. The profile does not directly assessed catalogs verification of geological lithology , but reveals a non-random spatial distribution

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This work demonstrates the importance of using tools used in geographic information systems (GIS) and spatial data analysis (SDA) for the study of infectious diseases. Analysis methods were used to describe more fully the spatial distribution of a particular disease by incorporating the geographical element in the analysis. In Chapter 1, we report the historical evolution of these techniques in the field of human health and use Hansen s disease (leprosy) in Rio Grande do Norte as an example. In Chapter 2, we introduced a few basic theoretical concepts on the methodology and classified the types of spatial data commonly treated. Chapters 3 and 4 defined and demonstrated the use of the two most important techniques for analysis of health data, which are data point processes and data area. We modelled the case distribution of Hansen s disease in the city of Mossoró - RN. In the analysis, we used R scripts and made available routines and analitical procedures developed by the author. This approach can be easily used by researchers in several areas. As practical results, major risk areas in Mossoró leprosy were detected, and its association with the socioeconomic profile of the population at risk was found. Moreover, it is clearly shown that his approach could be of great help to be used continuously in data analysis and processing, allowing the development of new strategies to work might increase the use of such techniques in data analysis in health care

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This work aims to study the problem of the formal job in the Brazilian Northeast region and its effect in the social inclusion, taking for base the analysis of variables defined in the Atlas of Social Exclusion, which is based on the 2000 Brazilian Census, choosing the county as unit of analysis. As methodological options, an exploratory data analysis was performed, followed by multivariate statistical techniques, such as weighted multiple regression analysis, cluster analysis and exploratory analysis of spatial data. The results pointed out to low rates of formal job for the active age population as well as low indexes of social inclusion in the Northeast region of Brazil. A strong association of the formal job with the indicators of social inclusion under investigation, was evidenced (schooling, inequality, poverty, youth and income form government transfers), as well as a strong association of the formal job with the new index of social inclusion (IIS), modified from the IES. At the Federative Units, in which better levels of formal job had been found, good indexes of social inclusion are also observed. Highlights for the state of the Rio Grande do Norte, with the best conditions of life, and for the states of the Maranhão and Piauí, with the worst conditions. The situation of the Northeast region, facing the indicators under study, is very precarious, claiming for the necessity of emphasizing programs and governmental actions, specially directed to the raise of formal job levels of the region, reflecting, thus, in improvements on the income inequality, as well as in the social inclusion of the population of Northeastern natives.

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Last century Six Sigma Strategy has been the focus of study for many scientists, between the discoveries we have the importance of data process for the free of error product manufactory. So, this work focuses on data quality importance in an enterprise. For this, a descriptive-exploratory study of seventeen pharmacies of manipulations from Rio Grande do Norte was undertaken with the objective to be able to create a base structure model to classify enterprises according to their data bases. Therefore, statistical methods such as cluster and discriminant analyses were used applied to a questionnaire built for this specific study. Data collection identified four group showing strong and weak characteristics for each group and that are differentiated from each other

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The use of Geographic Information Systems (GIS) has becoming very important in fields where detailed and precise study of earth surface features is required. Applications in environmental protection are such an example that requires the use of GIS tools for analysis and decision by managers and enrolled community of protected areas. In this specific field, a challenge that remains is to build a GIS that can be dynamically fed with data, allowing researchers and other agents to recover actual and up to date information. In some cases, data is acquired in several ways and come from different sources. To solve this problem, some tools were implemented that includes a model for spatial data treatment on the Web. The research issues involved start with the feeding and processing of environmental control data collected in-loco as biotic and geological variables and finishes with the presentation of all information on theWeb. For this dynamic processing, it was developed some tools that make MapServer more flexible and dynamic, allowing data uploading by the proper users. Furthermore, it was also developed a module that uses interpolation to aiming spatial data analysis. A complex application that has validated this research is to feed the system with data coming from coral reef regions located in northeast of Brazil. The system was implemented using the best interactivity concept provided by the AJAX model and resulted in a substantial contribution for efficiently accessing information, being an essential mechanism for controlling events in the environmental monitoring

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The objective of this work is to identify, to chart and to explain the evolution of the soil occupation and the envirionment vulnerability of the areas of Canto do Amaro and Alto da Pedra, in the city of Mossoró-RN, having as base analyzes it multiweather of images of orbital remote sensors, the accomplishment of extensive integrated works of field to a Geographic Information System (GIS). With the use of inserted techniques of it analyzes space inserted in a (GIS), and related with the interpretation and analyzes of products that comes from the Remote Sensoriamento (RS.), make possible resulted significant to reach the objectives of this works. Having as support for the management of the information, the data set gotten of the most varied sources and stored in digital environment, it comes to constitute the geographic data base of this research. The previous knowledge of the spectral behavior of the natural or artificial targets, and the use of algorithms of Processing of Digital images (DIP), it facilitates the interpretation task sufficiently and searchs of new information on the spectral level. Use as background these data, was generated a varied thematic cartography was: Maps of Geology, Geomorfológicals Units soils, Vegetation and Use and Occupation of the soil. The crossing in environment SIG, of the above-mentioned maps, generated the maps of Natural and Vulnerability envirionmental of the petroliferous fields of I Canto do Amaro and Alto da Pedra-RN, working in an ambient centered in the management of waters and solid residuos, as well as the analysis of the spatial data, making possible then a more complex analysis of the studied area

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This work focuses the geomorphological characterization and spatial data modeling in the shallow continental shelf within the Folha Touros limits (SB-25-CV-II), based on bathymetric data analysis and remote sensing products interpretation. The Rio Grande do Norte state is located in northeastern Brazil and the work area is located at the transition region between the eastern and northern portions of their coast. The bathymetric surveys were conduced between march and may 2009, using a 10 meters long vessel and 0.70 meters draught, equipped with global positioning system and echo sounder (dual beam, 200KHz , 14°). The fieldwork resulted in 44 bathymetric profiles espaced 1.5 km and 30 km average length. The bathymetric data amount were 111,200 points and were navigated 1395.7 km within na area about 1,850 km2. The bathymetric data were corrected for the tide level, vessel draught and were subsequently entered into a geographic information system for further processing. Analysis of remote sensing products was carried out using Landsat 7/ETM + band 1, from november 1999. The image was used for visualization and mapping submerged features. The results showed the presence of geomorphological features within the study area. Were observed, from the analysis of local bathymetry and satellite image, seven types of geomorphological features. The channels, with two longitudinals channels (e. g. San Roque and Cioba channels) and other perpendicular to the coast (e. g. Touros, Pititinga and Barretas). Coastal reef formations (Maracajaú, Rio do Fogo and Cioba). Longitudinal waves, described in the literature as longitudinal dunes. The occurrence of a transverse dune field. Another feature observed was the oceanic reefs, an rock alignment parallel to the coast. Were identified four riscas , from north to south: risca do Liso, Gameleira, Zumbi, Pititinga (the latter being described for the first time). Finally, an oceanic terrace was observed in the deepest area of study. Image interpretation corroborated with the in situ results, enabling visualization and description for all features in the region. The results were analysed in an integrating method (using the diferent methodologies applied in this work) and it was essential to describe all features in the area. This method allowed us to evaluate which methods generated better results to describe certain features. From these results was possible to prove the existence of submerged features in the eastern shallow continental shelf of Rio Grande do Norte. In this way, the conclusions was (1) this study contributed to the provision of new information about the area in question, particularly with regard to data collection in situ depths, (2) the method of data collection and interpretation proves to be effective because, through this, it was possible to visualize and interpret the features present in the study area and (3) the interpretation and discussion of results in an integrated method, using different methodologies, can provide better results

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This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation