Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-03-14T13:52:48Z No. of bitstreams: 1 raphaeldefreitassaldanha.pdf: 13350574 bytes, checksum: c1efacf54b8e45ed46b5303adf0b2e11 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-03-16T13:05:45Z (GMT) No. of bitstreams: 1 raphaeldefreitassaldanha.pdf: 13350574 bytes, checksum: c1efacf54b8e45ed46b5303adf0b2e11 (MD5) / Made available in DSpace on 2017-03-16T13:05:45Z (GMT). No. of bitstreams: 1 raphaeldefreitassaldanha.pdf: 13350574 bytes, checksum: c1efacf54b8e45ed46b5303adf0b2e11 (MD5) Previous issue date: 2016-11-01 / A violência no trânsito tem apresentado números preocupantes e crescentes no contexto internacional e brasileiro, sublinhando a importância deste tema para o campo da Saúde Coletiva através do conceito de saúde ampliada. A violência no trânsito encontra raízes na formação histórica da sociedade, onde a introdução do automóvel reflete a estrutura de classes de sua época, cujos reflexos ainda são encontrados na sociedade. O acesso à automóveis e outros meios de transporte através do incremento da renda torna este fator um importante determinante social da saúde para o estudo da violência no trânsito. Este trabalho visa compreender a relação entre o crescimento econômico e a violência no trânsito nos municípios brasileiros, utilizando um painel de dados espaciais de 12 anos. Os resultadosdoModelodeErroEspacialdeDurbinapontamparaaexistênciadeumaCurva de Kuznets nesta relação, onde covariáveis relativas a frota de veículos, investimentos em transportes, urbanização e o IDH são significativas. Estes resultados indicam que a violência no trânsito pode ser influenciada através de políticas públicas que objetivem resultados nestas covariáveis, não requerendo que os municípios atinjam patamares de renda mais elevados para ocasionar a redução da mortalidade no trânsito. / There is a concerning and increasing quantity of traffic violence internationally and in Brazil, underlining the importance of this theme to Public Health through an expanded health concept. Traffic violence finds roots in the historical formation of society, where the introduction of automobiles reflects the arrangement of classes of that time, and these reflections still can be seen in today’s society. Access to automobiles and other means of transport through the increase of wealth makes income an important social determinant of health in the study of traffic violence. This study aims to understand the relationship between the increase of income and traffic violence using a spatial data panel of 12 years. The results of the Spatial Durbin Error Model point to the occurrence of a Kuznets Curve for this relation, where the factors of the vehicle fleet, investments on traffic infrastructure and urbanization and the HDI are significant. As a result, traffic violence can be affected by public policies that target these factors, instead of requiring that the municipalities reaches more elevated levels of income to observe a reduction in traffic violence.

In recent years there were many debates and different opinions whether R&D spillover effects exist or not. In 1995 Coe and Helpman published a study about this phenomenon, based on a panel dataset, that supports the position that such R&D spillover effects are existent. However, this survey was criticized and many different suggestions for improvement came from the scientific community. Some of them were selected and analysed and finally led to a new model. And even though this new model is well compatible with the data, it leads to different conclusions, namely that there does not exist an R&D spillover effect. These different results were the motivation to run a spatial analysis, which can be done by considering the countries as regions and using an adequate spatial link matrix. The used methods from the field of spatial econometrics are described briefly and quite general, and finally the results from the spatial models (the ones which correspond to the non-spatial ones) are compared with the results from the non-spatial analysis. The preferred model supports the position that R&D spillover effects exist.

The main aim of the diploma thesis is the facilitation of the monitoring in short-term and long-term migration of population by using processed data of the mobile operator. The diploma thesis is focused on creating an algorithm that allows spatial correlation of positional data from the mobile operator with specific statistical data. In the first part, the reader is introduced to the theoretical background and to the current state of knowledge of the study issues. The methodological part presents the process of designing the tool. The initial phase of the algorithm corrects inadequate topology and the incorrect geometry of input data. The secondary part of the thesis is concerned about the necessary intersection of statistical territorial units and the mobile radio cell stations. During the design of the tool we focused on the user friendliness. The resulting data layers enable the addition of another statistical data or the development of geodatabases.

Many of the ongoing activities towards establishing SDI on a regional, national, and international level are focused on data sharing and dissemination. Next to data access and visualisation, data processing is a third important pillar of GIS which can generate new insights by creating derived data or conducting computational analyses on original data sets. Within today’s largely data-centric SDI, two major challenges were identified that stand in the way of ubiquitous geoprocessing: The ability to use and exchange implementations of geoprocessing functions as freely as geographic data and the ability to describe, communicate and catalogue existing functionality on the Web. This thesis evaluates the moving code approach as an alternative to client–server processing in a distributed SDI. While classical client–server configurations move pieces of data between remote processing services, data services, and clients over the network, moving code setups consider the transfer of portable software components to the location of data or the location of computing resources. To exchange implementations of geoprocessing functions at a larger scale, a Web based code sharing architecture is proposed. For improved descriptions of geoprocessing functions, WPS process descriptions are suggested as an interface description language. They are enhanced by a hierarchical profiling approach that permits different levels of granularity in the functional descriptions.

A co-location pattern is a set of spatial features frequently located together in space. A frequent pattern is a set of items that frequently appears in a transaction database. Since its introduction, the paradigm of frequent pattern mining has undergone a shift from candidate generation-and-test based approaches to projection based approaches. Co-location patterns resemble frequent patterns in many aspects. However, the lack of transaction concept, which is crucial in frequent pattern mining, makes the similar shift of paradigm in co-location pattern mining very difficult. This thesis investigates a projection based co-location pattern mining paradigm. In particular, a FP-tree based co-location mining framework and an algorithm called FP-CM, for FP-tree based co-location miner, are proposed. It is proved that FP-CM is complete, correct, and only requires a small constant number of database scans. The experimental results show that FP-CM outperforms candidate generation-and-test based co-location miner by an order of magnitude.

The goal of this master thesis is to construct a software system, named the LIFE Spatial Data Visualization System (LIFE-SDVS), to automatically visualize the data obtained in the LIFE project spatially. LIFE stands for the Leipzig Research Centre for Civilization Diseases. It is part of the Medical Faculty of the University of Leipzig and conducts a large medical research project focusing on civilization diseases in the Leipzig population. Currently, more than 20,000 participants have joined this population-based cohort study. The analyses in LIFE have been mostly limited to non-spatial aspects. To integrate geographical facet into the findings, a spatial visualization tool is necessary. Hence, LIFE-SDVS, an automatic map visualization tool wrapped in an interactive web interface, is constructed. LIFE-SDVS is conceptualized with a three-layered architecture: data source, functionalities and spatial visualization layers. The implementation of LIFE-SDVS was achieved by two software components: an independent, self-contained R package lifemap and the LIFE Shiny Application. The package lifemap enables the automatic spatial visualization of statistics on the map of Leipzig and to the extent of the authors knowledge, is the first R package to achieve boundary labeling for maps. The package lifemap also contains two self-developed algorithms. The Label Positioning Algorithm was constructed to find good positions within each region on a map for placing labels, statistical graphics and as starting points for boundary label leaders. The Label Alignment Algorithm solves the leader intersection problem of boundary labeling. However, to use the plotting functions in lifemap, the users need to have basic knowledge of R and it is a tedious job to manually input the argument values whenever changes on the maps are necessary. An interactive Shiny web application, the LIFE Shiny Application, is therefore built to create a user friendly data exploration and map generation tool. LIFE Shiny Application is capable of obtaining experimental data directly from the LIFE database at runtime. Additionally, a data preprocessing unit can transform the raw data into the format needed for spatial visualization. On the LIFE Shiny Application user interface, users can specify the data to display, including what data to be fetched from database and which part of the data shall be visualized, by using the filter functions provided. Many map features are also available to improve the aesthetic presentation of the maps. The resulting maps can also be downloaded for further usage in scientific publications or reports. Two use cases using LIFE hand grip strength and body mass index data demonstrate the functionalities of LIFESDVS. The current LIFE-SDVS sets a foundation for the spatial visualization of LIFE data. Suggestions on adding further functionalities into the future version are also provided.

The report deals with creating applications for Pocket PC, designed to aid with terrain mapping process. Topic falls within the field of geographic information systems (GIS), so the text begins with an analysis of related topics such as GIS itself, processed data characteristics or global positioning systems (GPS). Available handheld platforms are discussed and based on analysis of existing commercial application, the requirements on developed program are set. Description of application architecture and some implementation details follow. The conclusion is devoted to testing functionality by mapping the real geospatial object.

Comparing to traditional cartography, big data geographic information processing is not a simple task at all, it requires special methods and methods. When existing geovisualization systems face millions of data, the zoom function and the dynamical data adding function usually cannot be satisfied at the same time. This research classify the existing methods of geovisualization, then analyze its functions and bottlenecks, analyze its applicability in the big data environment, and proposes a method that combines spatial data structure and iterative calculation on demand. It also proves that this method can effectively balance the performance of scaling and new data, and it is significantly better than the existing library in the time consumption of new data and scaling<br>

Many of the ongoing activities towards establishing SDI on a regional, national, and international level are focused on data sharing and dissemination. Next to data access and visualisation, data processing is a third important pillar of GIS which can generate new insights by creating derived data or conducting computational analyses on original data sets. Within today’s largely data-centric SDI, two major challenges were identified that stand in the way of ubiquitous geoprocessing: The ability to use and exchange implementations of geoprocessing functions as freely as geographic data and the ability to describe, communicate and catalogue existing functionality on the Web. This thesis evaluates the moving code approach as an alternative to client–server processing in a distributed SDI. While classical client–server configurations move pieces of data between remote processing services, data services, and clients over the network, moving code setups consider the transfer of portable software components to the location of data or the location of computing resources. To exchange implementations of geoprocessing functions at a larger scale, a Web based code sharing architecture is proposed. For improved descriptions of geoprocessing functions, WPS process descriptions are suggested as an interface description language. They are enhanced by a hierarchical profiling approach that permits different levels of granularity in the functional descriptions.

<div>The proliferation of GPS-enabled devices has led to the development of numerous location-based services. These services need to process massive amounts of spatial data in real-time with high-throughput and low response time. The current scale of spatial data cannot be handled using centralized systems. This has led to the development of distributed spatial streaming systems. The performance of distributed streaming systems relies on how even the workload is distributed among their machines. However, the real-time streamed spatial data and query follow non-uniform spatial distributions that are continuously changing over time. Therefore, Distributed spatial streaming systems need to track the changes in the distribution of spatial data and queries and redistribute their workload accordingly. This thesis addresses the challenges of adapting to workload changes in distributed spatial streaming systems to improve the performance while preserving the system's security. </div><div>The thesis proposes TrioStat, an online workload estimation technique that relies on a probabilistic model for estimating the cost of partitions and machines of distributed spatial streaming systems. TrioStat has a decentralised technique to collect and maintain the required statistics in real-time with minimal overhead. In addition, this thesis introduces SWARM, a light-weight adaptive load-balancing protocol that continuously monitors the data and query workloads across the distributed processes of spatial data streaming systems, and redistribute the workloads soon as performance bottlenecks get detected. SWARM uses TrioStat to estimate the workload of the system's machines. Although using adaptive load-balancing techniques significantly improves the performance of distributed streaming systems, they make the system vulnerable to attacks. In this thesis, we introduce a novel attack model that targets adaptive load-balancing mechanisms of distributed streaming systems. The attack reduces the throughput and the availability of the system by making it stay in a continuous state of rebalancing. The thesis proposes Guard, a component that detects and blocks attacks that target the adaptive load balancing of distributed streaming systems. Guard is deployed in SWARM to develop an attack-resilient adaptive load balancing mechanism for Distributed spatial streaming systems.<br></div>