Xem 1-15 trên 15 kết quả Geographic data models
  • All geographic information systems (GIS) are built using formal models that describe how things are located in space. A formal model is an abstract and well-defined system of concepts. It defines the vocabulary that we can use to describe and reason about things. A geographic data model defines the vocabulary for describing and reasoning about the things that are located on the earth. Geographic data models serve as the foundation on which all geographic information systems are built. We are all familiar with one model for geographic information—the map.

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  • After this lecture you should be able to: Describe the primary Vector data models used in GIS and give examples, describe raster data models and give examples, describe TIN data models, explain “topology”, describe the main file formats used in GIS.

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  • Geographic Information Systems (GIS) has emerged as one of the most important and widely used softwares for the social scientists in last two decades. Economists, sociologists, political scientists, public administrators, and geographers alike use GIS for capturing, storing, analyzing, and presenting spatially referenced socio-economic data. Election campaigns have been using GIS in a rapidly increasing manner. It has also been substantially used by urban and regional planners, natural resources scientists, and civil engineers.

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  • The explosive growth in geographical information systems (GIS) in the last decade has resulted in considerable debate about which particular definition most accurately describes the activities of GIS research, and whether these diverse activities constitute a science of geographic information (Rhind et al., 1991). There is now widespread acceptance in the research community that the strengths of GIS lie in its diversity and the research area has correspondingly evolved to encompass an increasing range of geographical and spatially oriented analytical and modelling processes.

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  • After reading this chapter, you should be able to answer the following questions: Why is it hard for people to make good decisions? How do models help managers make better decisions? What are the key elements of decision support systems? How is data mining different from traditional statistical analysis? What is the purpose of OLAP? What is a digital dashboard? What are the advantages of an EIS? How can a GIS help managers make better decisions?

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  • We construct optimal portfolios of equity funds by combining historical returns on funds and passive indexes with prior views about asset pricing and skill. By including both benchmark and nonbenchmark indexes, we distinguish pricing-model inaccuracy from managerial skill. Even modest con¯dence in a pricing model helps construct portfolios with high Sharpe ratios. Investing in active mutual funds can be optimal even for investors who believe active managers cannot outperform passive indexes. Optimal portfolios exclude hot-hand funds even for investors who believe momentum is priced.

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  • The following points support our choice of methods. First, the specification of the stochastic process is complex due to the variety of possible parameterisations 9 and requires a considerable number of parameters, which increases the potential impact of estimation errors. Second, the estimation by means of finite differences requires equally spaced strike prices. For our sample, this is a considerable difficulty in the implementation, as section 2.2 demonstrates. Third, regarding the performance of the tree approach, there is little evidence of superior results 10 .

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  • We know how to fix the problem of childhood hunger, and we have an opportunity now to build a prosperous future for us all by doing that. Over the past century Americans have built marvelous networks and systems of infrastructure that are necessary to our economy and quality of life. Through creativity, inventiveness, ingenuity and hard work we have made our country a model of success in many areas. For example, we have built a national power grid, telecommunication systems, water systems, transportation systems, and internet systems that are peerless, to list just a few.

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  • The simplest way to think of Oracle’s implementation of read consistency is to imagine each user operating a private copy of the database, hence the multiversion consistency model. Read Consistency, Undo Records, and Transactions To manage the multiversion consistency model, Oracle must create a read-consistent set of data when a table is queried (read) and simultaneously updated (written). When an update occurs, the original data values changed by the update are recorded in the database undo records.

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  • "cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms" presents the background information on various elements that form the basis for architecting Cloud computing systems. It also presents the requirements of elastic or malleable applications that need to scale across multiple, geographically distributed data centers that are owned by one or more Cloud service providers.

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  • Language variationists study how languages vary along geographical or social lines or along lines of age and gender. Variationist data is available and challenging, in particular for DIALECTOLOGY, the study of geographical variation, which will be the focus of this paper, although we present approaches we expect to transfer smoothly to the study of variation correlating with other extralinguistic variables.

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  • Several countries present a series of urban problems, such as: dwelling deficit, infrastructure problems, inefficient services, environmental pollution, etc. Urban Engineering searches solution for these problems, by using a conjoined system of planning, management and technology. Many researches are related to application of instruments, methodologies and tools for monitoring and acquisition of data, based on the factual experience and computational modelling.

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  • There is one reported proposed entry – of Schroder Investment Management through the acquisition of a significant minority stake in an existing AMCor trust company and also one reported proposed exit, viz. Fidelity This growth serves to demonstrate that, at a fundamental level, there are many significant global and local players that consider the Indian mutual fund industry to be attractive. It is necessary to understand the mix of investors, distributors, types and number of schemes as factors that contribute to a sustainable and profitable operating model.

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  • Both versions of synthesis allow inclusion and estimation of spawner-recruitment functions. When detailed age composition data are lacking, the estimated spawner-recruitment curve can be used to generate the entire time series of recruitments, thus turning synthesis into a simple production model. At the other extreme, inclusion of the spawner-recruitment curve in data-rich models allows estimation of this curve while taking into account all available information.

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  • Geographic structure is not yet included in the size model. In both configurations, synthesis maintains a full age-structured description of the population and employs conventional equations to describe the population dynamics. A wide hierarchical range of model complexity can be defined for either version (Methot 1998). At one extreme, the model can be used with no age or size data (with external estimation of selectivity and weight-at-age) and the est imation process can be condensed to a few stock-recruitment parameters that mimic stock-reduction analysis (Kimura and Tagart 1982).

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