999 resultados para Attribute-file map


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基于属性的存取,对于在包含不同来源的大量文件的系统中进行有效的信息管理来说,是一种非常具有吸引力的特性。然而尽管在相当长的一段时间内其价值已广为人知,该特性的真正有实用价值的实现仍然非常之少。本文探讨了实现该特性时面临的主要挑战,以及它们是怎样在一种专为此目的设计的文件系统中,通过成功的应用各种原则而被妥善处理。

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Este documento tiene como objeto analizar las oportunidades de Colombia frente a diferentes mercados como Japón e Israel, países con lo que desde el inicio de este proyecto se encuentran en negociaciones de acuerdos de libre comercio. Con el fin de realizar un análisis más específico, el trabajo se centra en la investigación de los productos que actualmente se exportan a dichos mercados, la participación de los mismos y la definición de aquellos que tienen potencial una vez entre en vigor el tratado. De igual forma, se examina la historia y acercamiento hasta el momento entre las economías de Japón y Colombia, como de Israel y Colombia, que permite sugerir estrategias y propuestas que potencialicen los productos con los cuales Colombia puede llegar a competir en dichos mercados. Finalmente, se evalúan perfiles de mercado de las economías de interés, con el fin de determinar y describir la situación actual en términos comerciales de Colombia y dichos países. El objetivo de este documento es servir de guía a empresarios colombianos que planean acceder a los mercados previamente mencionados.

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A variety of data structures such as inverted file, multi-lists, quad tree, k-d tree, range tree, polygon tree, quintary tree, multidimensional tries, segment tree, doubly chained tree, the grid file, d-fold tree. super B-tree, Multiple Attribute Tree (MAT), etc. have been studied for multidimensional searching and related problems. Physical data base organization, which is an important application of multidimensional searching, is traditionally and mostly handled by employing inverted file. This study proposes MAT data structure for bibliographic file systems, by illustrating the superiority of MAT data structure over inverted file. Both the methods are compared in terms of preprocessing, storage and query costs. Worst-case complexity analysis of both the methods, for a partial match query, is carried out in two cases: (a) when directory resides in main memory, (b) when directory resides in secondary memory. In both cases, MAT data structure is shown to be more efficient than the inverted file method. Arguments are given to illustrate the superiority of MAT data structure in an average case also. An efficient adaptation of MAT data structure, that exploits the special features of MAT structure and bibliographic files, is proposed for bibliographic file systems. In this adaptation, suitable techniques for fixing and ranking of the attributes for MAT data structure are proposed. Conclusions and proposals for future research are presented.

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Several techniques are known for searching an ordered collection of data. The techniques and analyses of retrieval methods based on primary attributes are straightforward. Retrieval using secondary attributes depends on several factors. For secondary attribute retrieval, the linear structures—inverted lists, multilists, doubly linked lists—and the recently proposed nonlinear tree structures—multiple attribute tree (MAT), K-d tree (kdT)—have their individual merits. It is shown in this paper that, of the two tree structures, MAT possesses several features of a systematic data structure for external file organisation which make it superior to kdT. Analytic estimates for the complexity of node searchers, in MAT and kdT for several types of queries, are developed and compared.

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This document provides a brief introduction to the River Lune catchment and the role that the National Rivers Authority plays in catchment management. Included are a map of the catchment and short introductions to fisheries and characteristics of the catchment.

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The Document Map makes it very easy get an overview of the heading structure of a long document and to navigate aroiund the file quickly. If you watch this video also watch the ones on Using Heading and Contents Styles as well as on Tables of Content. For best viewing Download the video.

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Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.​cheminfo.​org/​pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.

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Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.

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Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.

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Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (height differences) are accurate to approximately ±10 m.

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Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.

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Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.