942 resultados para Geospatial Data Model


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Applications are subject of a continuous evolution process with a profound impact on their underlining data model, hence requiring frequent updates in the applications' class structure and database structure as well. This twofold problem, schema evolution and instance adaptation, usually known as database evolution, is addressed in this thesis. Additionally, we address concurrency and error recovery problems with a novel meta-model and its aspect-oriented implementation. Modern object-oriented databases provide features that help programmers deal with object persistence, as well as all related problems such as database evolution, concurrency and error handling. In most systems there are transparent mechanisms to address these problems, nonetheless the database evolution problem still requires some human intervention, which consumes much of programmers' and database administrators' work effort. Earlier research works have demonstrated that aspect-oriented programming (AOP) techniques enable the development of flexible and pluggable systems. In these earlier works, the schema evolution and the instance adaptation problems were addressed as database management concerns. However, none of this research was focused on orthogonal persistent systems. We argue that AOP techniques are well suited to address these problems in orthogonal persistent systems. Regarding the concurrency and error recovery, earlier research showed that only syntactic obliviousness between the base program and aspects is possible. Our meta-model and framework follow an aspect-oriented approach focused on the object-oriented orthogonal persistent context. The proposed meta-model is characterized by its simplicity in order to achieve efficient and transparent database evolution mechanisms. Our meta-model supports multiple versions of a class structure by applying a class versioning strategy. Thus, enabling bidirectional application compatibility among versions of each class structure. That is to say, the database structure can be updated because earlier applications continue to work, as well as later applications that have only known the updated class structure. The specific characteristics of orthogonal persistent systems, as well as a metadata enrichment strategy within the application's source code, complete the inception of the meta-model and have motivated our research work. To test the feasibility of the approach, a prototype was developed. Our prototype is a framework that mediates the interaction between applications and the database, providing them with orthogonal persistence mechanisms. These mechanisms are introduced into applications as an {\it aspect} in the aspect-oriented sense. Objects do not require the extension of any super class, the implementation of an interface nor contain a particular annotation. Parametric type classes are also correctly handled by our framework. However, classes that belong to the programming environment must not be handled as versionable due to restrictions imposed by the Java Virtual Machine. Regarding concurrency support, the framework provides the applications with a multithreaded environment which supports database transactions and error recovery. The framework keeps applications oblivious to the database evolution problem, as well as persistence. Programmers can update the applications' class structure because the framework will produce a new version for it at the database metadata layer. Using our XML based pointcut/advice constructs, the framework's instance adaptation mechanism is extended, hence keeping the framework also oblivious to this problem. The potential developing gains provided by the prototype were benchmarked. In our case study, the results confirm that mechanisms' transparency has positive repercussions on the programmer's productivity, simplifying the entire evolution process at application and database levels. The meta-model itself also was benchmarked in terms of complexity and agility. Compared with other meta-models, it requires less meta-object modifications in each schema evolution step. Other types of tests were carried out in order to validate prototype and meta-model robustness. In order to perform these tests, we used an OO7 small size database due to its data model complexity. Since the developed prototype offers some features that were not observed in other known systems, performance benchmarks were not possible. However, the developed benchmark is now available to perform future performance comparisons with equivalent systems. In order to test our approach in a real world scenario, we developed a proof-of-concept application. This application was developed without any persistence mechanisms. Using our framework and minor changes applied to the application's source code, we added these mechanisms. Furthermore, we tested the application in a schema evolution scenario. This real world experience using our framework showed that applications remains oblivious to persistence and database evolution. In this case study, our framework proved to be a useful tool for programmers and database administrators. Performance issues and the single Java Virtual Machine concurrent model are the major limitations found in the framework.

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Dissertação de Mestrado, Ciências Económicas e Empresariais, 18 de Julho de 2016, Universidade dos Açores.

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The paper explores the trade competitiveness of seven major shrimp exporting countries, namely Vietnam, China, Thailand, Ecuador, India, Indonesia and Mexico, to the USA. Specifically, we investigate whether the United States (US) antidumping petitions impact upon the bilateral revealed comparative advantage (RCA) indexes for each of the seven shrimp exporting countries with the USA. Monthly data from January 2003 to December 2014 and the panel data model are used to examine the determinants of the RCA for the shrimp exporting countries. The empirical results show the shrimp exporting countries have superior competitiveness against the shrimp market in the USA. Moreover, the RCA indexes are significantly negatively influenced by shrimp prices, and are positively affected by US income per capita. However, the EMS (Early Mortality Syndrome) shrimp disease, domestic US shrimp quantity, exchange rate, and US antidumping laws are found to have no significant impacts on the RCA indexes. In terms of policy implications, the USA should try to reduce production costs of shrimp in the US market instead of imposing antidumping petitions, and the shrimp exporting countries should maintain their comparative advantage and diversify into new markets.

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This study aims to investigate the influence of the asset class and the breakdown of tangibility as determinant factors of the capital structure of companies listed on the BM & FBOVESPA in the period of 2008-2012. Two current assets classes were composed and once they were grouped by liquidity, they were also analyzed by the financial institutions for credit granting: current resources (Cash, Bank and Financial Applications) and operations with duplicates (Stocks and Receivables). The breakdown of the tangible assets was made based on its main components provided as warrantees for loans like Machinery & Equipment and Land & Buildings. For an analysis extension, three metrics for leverage (accounting, financial and market) were applied and the sample was divided into economic sectors, adopted by BM&FBOVESPA. The data model in dynamic panel estimated by a systemic GMM of two levels was used in this study due its strength to problems of endogenous relationship as well as the omitted variables bias. The found results suggest that current resources are determinants of the capital structure possibly because they re characterized as proxies for financial solvency, being its relationship with debt positive. The sectorial analysis confirmed the results for current resources. The tangibility of assets has inverse proportional relationship with the leverage. As it is disintegrated in its main components, the significant and negative influence of machinery & equipment was more marked in the Industrial Goods sector. This result shows that, on average, the most specific assets from operating activities of a company compete for a less use of third party resources. As complementary results, it was observed that the leverage has persistence, which is linked with the static trade-off theory. Specifically for financial leverage, it was observed that the persistence is relevant when it is controlled for the lagged current assets classes variables. The proxy variable for growth opportunities, measured by the Market -to -Book, has the sign of its contradictory coefficient. The company size has a positive relationship with debt, in favor of static trade-off theory. Profitability is the most consistent variable in all the performed estimations, showing strong negative and significant relationship with leverage, as the pecking order theory predicts

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No âmbito das obrigações que o Estado Português tem em garantir a segurança dos seus cidadãos, é efetuada, em países ou regiões onde há comunidades nacionais, uma avaliação quanto ao risco de vida para os cidadãos nacionais que aí residam ou aí se encontrem, entendendo-se, à luz do direito internacional consuetudinário, que é legítima a eventual execução de intervenção militar de extração de nacionais não combatentes dessas zonas de risco. Este trabalho pretende contribuir para uma reflexão sobre o apoio geoespacial a uma operação de extração de cidadãos nacionais não combatentes, que se denomina NEO (non-combatant evacuation operation). Dada a importância do conhecimento holístico do ambiente operacional para os comandantes militares, os Sistemas de Informação Geográfica desempenham um papel fundamental em termos da análise, contextualização e visualização da informação geoespacial, sendo um precioso sistema de apoio à decisão. A tomada de decisão é efetuada com os contributos de várias áreas de conhecimento, sendo fundamental que o planeamento seja efetuado com base na mesma informação geoespacial, evitando a existência de uma multitude de dados geoespaciais nem sempre coerentes, atualizados e acessíveis a todos os que deles necessitam, pretendendo-se com este trabalho fornecer um contributo para resolver este problema. Aborda-se também a escassez dos dados geográficos nas zonas em que este tipo de operações se poderá desenrolar, a pertinência e a adequabilidade de utilização de dados espaciais abertos, os modelos de dados, bem como a forma como a informação pode ser disponibilizada.

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The importance of the United States' wood and wood byproducts as biomass feedstocks is increasing as the concern about security and sustainability of global energy production continues to rise. Thus, second generation woody feedstock sources in Michigan, e.g., hybrid poplar and hybrid willow (Populus spp.), are viewed as a potential source of biomass for the proposed biofuel ethanol production plant in Kinross, MI. It is important to gain an understanding of the spatial distribution of current feedstock sources, harvesting accessibility via the transportation infrastructure and land ownerships in order to ensure long-term feedstock extent. This research provides insights into the current extent of aspen and northern hardwoods, and an assessment of potential for expanding the area of these feedstock sources based on pre-European settlement conditions. A geographic information system (GIS) was developed to compile available geospatial data for 33 counties located within 150 miles of the Kinross facility. These include present day and pre-European settlement land use/cover, soils, road infrastructure, and land ownerships. The results suggest that a significant amount of northern hardwoods has been converted to other land use/cover types since European settlement, and the "scattering" of aspen stands has increased. Furthermore, a significant amount of woody biomass is available in close proximity to the existing road network, which can be effectively utilized as feedstock. Potential aspen and northern hardwoods restoration areas are identified in the vicinity of road networks which can be used for future woody feedstock production.

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Méthodologie: Modèle de régression quantile de variable instrumentale pour données de Panel utilisant la fonction de production partielle

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Este trabajo presenta un estudio retrospectivo de los orígenes y evolución de la aplicación de Sistemas de  Información Geográfca  (SIG) y Teledetección  (TD) en nuestro país. Se  inicia por el  rol desempeñado del Profesor Merrill Lyew dentro de  la Escuela de Ciencias Geográfcas de la Universidad Nacional, pasando luego por una breve descripción del proceso de implementación de SIG y TD en los centros de enseñanza superior estatales.En esta breve descripción se analiza cómo diferentes unidades académicas han ido incorporando la tecnología SIG y TD en sus planes de estudio.Posteriormente, se presenta una aproximación de la situación actual SIG y TD en las instituciones públicas y privadas y cómo ellas han venido incorporando estas tecnologías en su quehacer diario. Se hace alusión a diferentes eventos que se han llevado en Costa Rica con el objetivo de compartir experiencias en las más diversas aplicaciones.De la misma manera se citan algunas de las principales empresas privadas que se dedican a la venta de insumos, aplicaciones, capacitaciones y software en el campo SIG y TD. En el camino óptimo se visualizan dos opciones por seguir:  la consolidación ofcial de un organismo, comisión o secretaría que tenga bajo su responsabilidad la organización de la Infraestructura Nacional de Datos Geoespaciales. La segunda versa sobre el esfuerzo realizado por las Escuelas de Geografía de la Universidad de Costa Rica y Universidad Nacional para ofrecer a partir del 2008 el Programa de Maestría Profesional en Sistemas de Información Geográfca y Teledetección. Palabras claves: Sistemas de Información Geográfca (SIG), Teledetección, Evolución, Historia, Costa Rica.Abstract This work is a retrospective study of the origins and evolution of the applications of Geographic Information Systems (GIS) and Remote Sensing in our country. It begins with the work of Prof. Merryl Lyew of the School of Geographic Sciences at Universidad Nacional and continues with a brief description of the GIS and Remote Sensing implementation process at state centers of higher education.It  also  analyzes  how  different  academic  departments  have  incorporated GIS  and Remote Sensing technology in their courses of study.Subsequently, this work presents an approximation of the actual situation regarding GIS and remote sensing  in public and private  institutions and how  these  technologies have become incorporated in their daily work. It also refers to the different events that have been carried on in Costa Rica with the objective of sharing experiences in the most diverse applications. In the same way, this work cites some of the principal private businesses dedicated to the sale of supplies, applications, training and software in the feld of GIS and remote sensing. Two options are seen as the best way to pursue the offcial consolidation of an agency, commission  or  administrative  department  to  have  under  its  responsibility  organization  of  the National Infrastructure of Geospatial Data. The second deals with the successful effort by the School of Geographic Sciences at Universidad Nacional of Costa Rica as of 2008 to offer the Professional Master’s program in Geographic Information Systems and Remote Sensing.KEyWordS: Geographic Information Systems (GIS), Remote Sensing, Origin, Evolution, Costa Rica, Universidad Nacional

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As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

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Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

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Geospatial clustering must be designed in such a way that it takes into account the special features of geoinformation and the peculiar nature of geographical environments in order to successfully derive geospatially interesting global concentrations and localized excesses. This paper examines families of geospaital clustering recently proposed in the data mining community and identifies several features and issues especially important to geospatial clustering in data-rich environments.

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Historically, the cure rate model has been used for modeling time-to-event data within which a significant proportion of patients are assumed to be cured of illnesses, including breast cancer, non-Hodgkin lymphoma, leukemia, prostate cancer, melanoma, and head and neck cancer. Perhaps the most popular type of cure rate model is the mixture model introduced by Berkson and Gage [1]. In this model, it is assumed that a certain proportion of the patients are cured, in the sense that they do not present the event of interest during a long period of time and can found to be immune to the cause of failure under study. In this paper, we propose a general hazard model which accommodates comprehensive families of cure rate models as particular cases, including the model proposed by Berkson and Gage. The maximum-likelihood-estimation procedure is discussed. A simulation study analyzes the coverage probabilities of the asymptotic confidence intervals for the parameters. A real data set on children exposed to HIV by vertical transmission illustrates the methodology.

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When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.