Hoje, existem muitas empresas de Cartografia que utilizam sistemas CAD para produção de cartas topográficas digitais.Este trabalho tem como proposta a identificação e classificação de erros de atributo gráfico em mapeamento digital, especialmente dados construídos em CAD (Computer Aided Design). Se os dados serão utilizados posteriormente num Sistema de Informações Geográficas, os dados espaciais deverão ser coletados de tal maneira que facilitem a inserção de topologia após a transferência dos dados. Como objetivo secundário, o trabalho propõe um melhor controle de qualidade, demonstrando seqüência lógica de tarefas para revisão e correção de problemas em dados espaciais / There are many Cartography corporations wich use CAD systems to built digital Topographic maps.This research intend to identify and classify errors of graphic attribute in digital mapping, specially digital spactial data built in CAD (Computer Aided Design). If these data will be applied in a Geographic Information System, they must be designed in a way that could easily perform spatial relationships (topology) after the data transfer.As a secondary objective, there is a suggestion of a better data quality control, showing a logical sequence of tasks to check up and correct problems in spatial data

Many of the patterns of genetic variation we observe today have arisen via the complex dynamics of interactions and isolation of historic human populations. In this thesis, we focus on two important features of the genetics of populations that can be used to learn about human history: population structure and admixture. The Iberian peninsula has a complex demographic history, as well as rich linguistic and cultural diversity. However, previous studies using small genomic regions (such as Y-chromosome and mtDNA) as well as genome-wide data have so far detected limited genetic structure in Iberia. Larger datasets and powerful new statistical methods that exploit information in the correlation structure of nearby genetic markers have made it possible to detect and characterise genetic differentiation at fine geographic scales. We performed the largest and most comprehensive study of Spanish population structure to date by analysing genotyping array data for ~1,400 Spanish individuals genotyped at ~700,000 polymorphic loci. We show that at broad scales, the major axis of genetic differentiation in Spain runs from west to east, while there is remarkable genetic similarity in the north-south direction. Our analysis also reveals striking patterns of geographically-localised and subtle population structure within Spain at scales down to tens of kilometres. We developed and applied new approaches to show how this structure has arisen from a complex and regionally-varying mix of genetic isolation and recent gene-flow within and from outside of Iberia. To further explore the genetic impact of historical migrations and invasions of Iberia, we assembled a data set of 2,920 individuals (~300,000 markers) from Iberia and the surrounding regions of north Africa, Europe, and sub-Saharan Africa. Our admixture analysis implies that north African-like DNA in Iberia was mainly introduced in the earlier half (860 - 1120 CE) of the period of Muslim rule in Iberia, and we estimate that the closest modern-day equivalents to the initial migrants are located in Western Sahara. We also find that north African-like DNA in Iberia shows striking regional variation, with near-zero contributions in the Basque regions, low amounts (~3%) in the north east of Iberia, and as high as (~11%) in Galicia and Portugal. The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Understanding the role that genetics plays in phenotypic variation, and its potential interactions with other factors, provides a critical route to a better understanding of human biology and population health. As such, a key component of the UK Biobank resource has been the collection of genome-wide genetic data (~805,000 markers) on every participant using purpose-designed genotyping arrays. These data are the focus of the second part of this thesis. In particular, we designed and implemented a quality control (QC) pipeline on behalf of the current and future use of this multi-purpose resource. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestral backgrounds in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data, including population structure and familial relatedness, that can be important for downstream analyses. We find that cryptic relatedness is common among UK Biobank participants (~30% have at least one first cousin relative or closer), and a full range of human population structure is present in this cohort: from world-wide ancestral diversity to subtle population structure at sub-national geographic scales. Finally, we performed a genome-wide association scan on a well-studied and highly polygenic phenotype: standing height. This provided a further test of the effectiveness of our QC, as well as highlighting the potential of the resource to uncover novel regions of association.

Hoje, existem muitas empresas de Cartografia que utilizam sistemas CAD para produção de cartas topográficas digitais.Este trabalho tem como proposta a identificação e classificação de erros de atributo gráfico em mapeamento digital, especialmente dados construídos em CAD (Computer Aided Design). Se os dados serão utilizados posteriormente num Sistema de Informações Geográficas, os dados espaciais deverão ser coletados de tal maneira que facilitem a inserção de topologia após a transferência dos dados. Como objetivo secundário, o trabalho propõe um melhor controle de qualidade, demonstrando seqüência lógica de tarefas para revisão e correção de problemas em dados espaciais / There are many Cartography corporations wich use CAD systems to built digital Topographic maps.This research intend to identify and classify errors of graphic attribute in digital mapping, specially digital spactial data built in CAD (Computer Aided Design). If these data will be applied in a Geographic Information System, they must be designed in a way that could easily perform spatial relationships (topology) after the data transfer.As a secondary objective, there is a suggestion of a better data quality control, showing a logical sequence of tasks to check up and correct problems in spatial data

With the advent of Advanced Traveler Information Systems (ATIS), short-term travel time prediction is becoming increasingly important. Travel time can be obtained directly from instrumented test vehicles, license plate matching, probe vehicles etc., or from indirect methods such as loop detectors. Because of their wide spread deployment, travel time estimation from loop detector data is one of the most widely used methods. However, the major criticism about loop detector data is the high probability of error due to the prevalence of equipment malfunctions. This dissertation presents methodologies for estimating and predicting travel time from the loop detector data after correcting for errors. The methodology is a multi-stage process, and includes the correction of data, estimation of travel time and prediction of travel time, and each stage involves the judicious use of suitable techniques. The various techniques selected for each of these stages are detailed below. The test sites are from the freeways in San Antonio, Texas, which are equipped with dual inductance loop detectors and AVI. ?? Constrained non-linear optimization approach by Generalized Reduced Gradient (GRG) method for data reduction and quality control, which included a check for the accuracy of data from a series of detectors for conservation of vehicles, in addition to the commonly adopted checks. ?? A theoretical model based on traffic flow theory for travel time estimation for both off-peak and peak traffic conditions using flow, occupancy and speed values obtained from detectors. ?? Application of a recently developed technique called Support Vector Machines (SVM) for travel time prediction. An Artificial Neural Network (ANN) method is also developed for comparison. Thus, a complete system for the estimation and prediction of travel time from loop detector data is detailed in this dissertation. Simulated data from CORSIM simulation software is used for the validation of the results.

Les études génétiques, telles que les études de liaison ou d’association, ont permis d’acquérir une plus grande connaissance sur l’étiologie de plusieurs maladies affectant les populations humaines. Même si une dizaine de milliers d’études génétiques ont été réalisées sur des centaines de maladies ou autres traits, une grande partie de leur héritabilité reste inexpliquée. Depuis une dizaine d’années, plusieurs percées dans le domaine de la génomique ont été réalisées. Par exemple, l’utilisation des micropuces d’hybridation génomique comparative à haute densité a permis de démontrer l’existence à grande échelle des variations et des polymorphismes en nombre de copies. Ces derniers sont maintenant détectables à l’aide de micropuce d’ADN ou du séquençage à haut débit. De plus, des études récentes utilisant le séquençage à haut débit ont permis de démontrer que la majorité des variations présentes dans l’exome d’un individu étaient rares ou même propres à cet individu. Ceci a permis la conception d’une nouvelle micropuce d’ADN permettant de déterminer rapidement et à faible coût le génotype de plusieurs milliers de variations rares pour un grand ensemble d’individus à la fois. Dans ce contexte, l’objectif général de cette thèse vise le développement de nouvelles méthodologies et de nouveaux outils bio-informatiques de haute performance permettant la détection, à de hauts critères de qualité, des variations en nombre de copies et des variations nucléotidiques rares dans le cadre d’études génétiques. Ces avancées permettront, à long terme, d’expliquer une plus grande partie de l’héritabilité manquante des traits complexes, poussant ainsi l’avancement des connaissances sur l’étiologie de ces derniers. Un algorithme permettant le partitionnement des polymorphismes en nombre de copies a donc été conçu, rendant possible l’utilisation de ces variations structurales dans le cadre d’étude de liaison génétique sur données familiales. Ensuite, une étude exploratoire a permis de caractériser les différents problèmes associés aux études génétiques utilisant des variations en nombre de copies rares sur des individus non reliés. Cette étude a été réalisée avec la collaboration du Wellcome Trust Centre for Human Genetics de l’University of Oxford. Par la suite, une comparaison de la performance des algorithmes de génotypage lors de leur utilisation avec une nouvelle micropuce d’ADN contenant une majorité de marqueurs rares a été réalisée. Finalement, un outil bio-informatique permettant de filtrer de façon efficace et rapide des données génétiques a été implémenté. Cet outil permet de générer des données de meilleure qualité, avec une meilleure reproductibilité des résultats, tout en diminuant les chances d’obtenir une fausse association. / Genetic studies, such as linkage and association studies, have contributed greatly to a better understanding of the etiology of several diseases. Nonetheless, despite the tens of thousands of genetic studies performed to date, a large part of the heritability of diseases and traits remains unexplained. The last decade experienced unprecedented progress in genomics. For example, the use of microarrays for high-density comparative genomic hybridization has demonstrated the existence of large-scale copy number variations and polymorphisms. These are now detectable using DNA microarray or high-throughput sequencing. In addition, high-throughput sequencing has shown that the majority of variations in the exome are rare or unique to the individual. This has led to the design of a new type of DNA microarray that is enriched for rare variants that can be quickly and inexpensively genotyped in high throughput capacity. In this context, the general objective of this thesis is the development of methodological approaches and bioinformatics tools for the detection at the highest quality standards of copy number polymorphisms and rare single nucleotide variations. It is expected that by doing so, more of the missing heritability of complex traits can then be accounted for, contributing to the advancement of knowledge of the etiology of diseases. We have developed an algorithm for the partition of copy number polymorphisms, making it feasible to use these structural changes in genetic linkage studies with family data. We have also conducted an extensive study in collaboration with the Wellcome Trust Centre for Human Genetics of the University of Oxford to characterize rare copy number definition metrics and their impact on study results with unrelated individuals. We have conducted a thorough comparison of the performance of genotyping algorithms when used with a new DNA microarray composed of a majority of very rare genetic variants. Finally, we have developed a bioinformatics tool for the fast and efficient processing of genetic data to increase quality, reproducibility of results and to reduce spurious associations.

Made available in DSpace on 2017-07-21T14:19:32Z (GMT). No. of bitstreams: 1 Ricardo Baba.pdf: 3642224 bytes, checksum: 81e8e78f554cdf870e6f9a554b71f87a (MD5) Previous issue date: 2012-07-31 / Climatic data are more and more important to predict climate phenomena or to evaluate historical data that serve as support for decision making especially for agriculture. Ensuring the quality of these data is crucial. These data are collected by the meteorological stations, during this process some data gaps and data inconsistent may be generated. Identify suspicious or inconsistent data is very important to ensure data quality. This paper presents an approach that uses statistical and geostatistical techniques to identify incorrect and suspicious data and estimate new values to fill gaps and errors. In this research, a spatial database was used to implement these techniques (statistical and geostatistical) and to test and evaluate the weather data. To evaluate these techniques we used data from stations located in Paraná State to evaluate the temperature variable. To check the results of the estimated data, we used the mean absolute error (MAE) and the root mean square error (RMSE). As a result, the uses of these techniques have proved to be suitable to identify basic errors and historical errors. The temporal validation showed a poor performance by overestimating the amount of incorrect data. Regarding the estimation techniques applied Kriging, Inverse of Distance Weighted and Linear Regression, all showed similar performance in the error analysis. / A análise de dados climáticos serve de suporte na previsão de fenômenos relacionados, na avaliação de seus dados históricos e para a tomada de decisões, em especial na área da agricultura. Garantir a sua qualidade é fundamental. O processo de coleta desses dados, através das estações meteorológicas, pode apresentar problemas, onde dados inconsistentes podem ser geridos ou obtidos. A identificação de dados inconsistentes ou suspeitos é de fundamental importância na garantia de qualidade dos dados. Este trabalho apresenta uma abordagem para solução do problema, utilizando técnicas estatísticas e geoestatísticas na identificação de dados inconsistentes e na estimativa de dados a serem corrigidos ou preenchidos. A implementação destas técnicas em um banco de dados espacial apresentou-se como um facilitador na identificação e no preenchimento desses dados. Para avaliação destas técnicas utilizou-se de dados das estações localizadas no Estado do Paraná, para análise da variável temperatura. Para avaliar os resultados, foram utilizados os erros médio e quadrático. Como resultado, destaca-se que as técnicas de identificação de erros mostraram-se adequadas na consistência de erros básicos e históricos. A validação espacial apresentou baixo desempenho por superestimar a quantidade de dados incorretos. Quanto as técnicas utilizadas na estimativa dos dados, Krigagem, Inverso da Distância e Regressão Linear, todas apresentaram desempenho semelhantes com relação à análise dos erros.

Les études génétiques, telles que les études de liaison ou d’association, ont permis d’acquérir une plus grande connaissance sur l’étiologie de plusieurs maladies affectant les populations humaines. Même si une dizaine de milliers d’études génétiques ont été réalisées sur des centaines de maladies ou autres traits, une grande partie de leur héritabilité reste inexpliquée. Depuis une dizaine d’années, plusieurs percées dans le domaine de la génomique ont été réalisées. Par exemple, l’utilisation des micropuces d’hybridation génomique comparative à haute densité a permis de démontrer l’existence à grande échelle des variations et des polymorphismes en nombre de copies. Ces derniers sont maintenant détectables à l’aide de micropuce d’ADN ou du séquençage à haut débit. De plus, des études récentes utilisant le séquençage à haut débit ont permis de démontrer que la majorité des variations présentes dans l’exome d’un individu étaient rares ou même propres à cet individu. Ceci a permis la conception d’une nouvelle micropuce d’ADN permettant de déterminer rapidement et à faible coût le génotype de plusieurs milliers de variations rares pour un grand ensemble d’individus à la fois. Dans ce contexte, l’objectif général de cette thèse vise le développement de nouvelles méthodologies et de nouveaux outils bio-informatiques de haute performance permettant la détection, à de hauts critères de qualité, des variations en nombre de copies et des variations nucléotidiques rares dans le cadre d’études génétiques. Ces avancées permettront, à long terme, d’expliquer une plus grande partie de l’héritabilité manquante des traits complexes, poussant ainsi l’avancement des connaissances sur l’étiologie de ces derniers. Un algorithme permettant le partitionnement des polymorphismes en nombre de copies a donc été conçu, rendant possible l’utilisation de ces variations structurales dans le cadre d’étude de liaison génétique sur données familiales. Ensuite, une étude exploratoire a permis de caractériser les différents problèmes associés aux études génétiques utilisant des variations en nombre de copies rares sur des individus non reliés. Cette étude a été réalisée avec la collaboration du Wellcome Trust Centre for Human Genetics de l’University of Oxford. Par la suite, une comparaison de la performance des algorithmes de génotypage lors de leur utilisation avec une nouvelle micropuce d’ADN contenant une majorité de marqueurs rares a été réalisée. Finalement, un outil bio-informatique permettant de filtrer de façon efficace et rapide des données génétiques a été implémenté. Cet outil permet de générer des données de meilleure qualité, avec une meilleure reproductibilité des résultats, tout en diminuant les chances d’obtenir une fausse association. / Genetic studies, such as linkage and association studies, have contributed greatly to a better understanding of the etiology of several diseases. Nonetheless, despite the tens of thousands of genetic studies performed to date, a large part of the heritability of diseases and traits remains unexplained. The last decade experienced unprecedented progress in genomics. For example, the use of microarrays for high-density comparative genomic hybridization has demonstrated the existence of large-scale copy number variations and polymorphisms. These are now detectable using DNA microarray or high-throughput sequencing. In addition, high-throughput sequencing has shown that the majority of variations in the exome are rare or unique to the individual. This has led to the design of a new type of DNA microarray that is enriched for rare variants that can be quickly and inexpensively genotyped in high throughput capacity. In this context, the general objective of this thesis is the development of methodological approaches and bioinformatics tools for the detection at the highest quality standards of copy number polymorphisms and rare single nucleotide variations. It is expected that by doing so, more of the missing heritability of complex traits can then be accounted for, contributing to the advancement of knowledge of the etiology of diseases. We have developed an algorithm for the partition of copy number polymorphisms, making it feasible to use these structural changes in genetic linkage studies with family data. We have also conducted an extensive study in collaboration with the Wellcome Trust Centre for Human Genetics of the University of Oxford to characterize rare copy number definition metrics and their impact on study results with unrelated individuals. We have conducted a thorough comparison of the performance of genotyping algorithms when used with a new DNA microarray composed of a majority of very rare genetic variants. Finally, we have developed a bioinformatics tool for the fast and efficient processing of genetic data to increase quality, reproducibility of results and to reduce spurious associations.