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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
41

Query-Driven Analysis and Visualization for Large-Scale Scientific Dataset using Geometry Summarization and Bitmap Indexing

Wei, Tzu-Hsuan January 2017 (has links)
No description available.
42

Distance-Based Indexing: Observations, Applications, and Improvements

Tasan, Murat January 2006 (has links)
No description available.
43

Automated knowledge extraction from text

Bowden, Paul Richard January 1999 (has links)
No description available.
44

Surface reconstruction from three dimensional range data.

Myers, Andrew January 2005 (has links)
This thesis looks at the problem of reconstructing a single surface representation from multiple range images acquired from a terrestrial laser scanner. A solution to this problem is important to industries such as mining, where accurate spatial measurement is required for mapping and volumetric calculations. Laser scanners for 3D measurement are now commercially available and software for deriving useful information from the data these devices generate is essential. A reconstruction technique based on an implicit surface representation of the range images and a polygonisation algorithm called marching triangles has been implemented in software and its performance investigated. This work improves upon the existing techniques in that it takes into account the particular differences of terrestrial range data as compared with data from small scale laser scanners. The implementation is robust with respect to noisy data and environments and requires minimal user input. A new approach to 3D spatial indexing is also developed to allow rapid evaluation of the true closest point to a surface which is the basis of the signed distance function implicit surface representation. A new technique for locating step discontinuities in the range image is presented, which caters for the varying sampling densities of terrestrial range images. The algorithm is demonstrated using representative range images acquired for surface erosion monitoring and for underground mine surveying. The results indicate that this reconstruction technique represents an improvement over current techniques for this type of range data. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1169106 / Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2005
45

Surface reconstruction from three dimensional range data.

Myers, Andrew January 2005 (has links)
This thesis looks at the problem of reconstructing a single surface representation from multiple range images acquired from a terrestrial laser scanner. A solution to this problem is important to industries such as mining, where accurate spatial measurement is required for mapping and volumetric calculations. Laser scanners for 3D measurement are now commercially available and software for deriving useful information from the data these devices generate is essential. A reconstruction technique based on an implicit surface representation of the range images and a polygonisation algorithm called marching triangles has been implemented in software and its performance investigated. This work improves upon the existing techniques in that it takes into account the particular differences of terrestrial range data as compared with data from small scale laser scanners. The implementation is robust with respect to noisy data and environments and requires minimal user input. A new approach to 3D spatial indexing is also developed to allow rapid evaluation of the true closest point to a surface which is the basis of the signed distance function implicit surface representation. A new technique for locating step discontinuities in the range image is presented, which caters for the varying sampling densities of terrestrial range images. The algorithm is demonstrated using representative range images acquired for surface erosion monitoring and for underground mine surveying. The results indicate that this reconstruction technique represents an improvement over current techniques for this type of range data. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1169106 / Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2005
46

Multi-resolution indexing method for time series

Ma, Mei January 2010 (has links)
Time series datasets are useful in a wide range of diverse real world applications. Retrieving or querying from a collection of time series is a fundamental task, with a key example being the similarity query. A similarity query returns all time series from the collection that are similar to a given reference time series. This type of query is particularly useful in prediction and forecasting applications. / A key challenge for similarity queries is efficiency and for large datasets, it is important to develop efficient indexing techniques. Existing approaches in this area are mainly based on the Generic Multimedia Indexing Method (GEMINI), which is a framework that uses spatial indexes such as the R-tree to index reduced time series. For processing a similarity query, the index is first used to prune candidate time series using a lower bounding distance. Then, all remaining time series are compared using the original similarity measure, to derive the query result. Performance within this framework depends on the tightness of the lower bounding distance with respect to the similarity measure. Indeed much work has been focused on representation and dimensionality reduction, in order to provide a tighter lower bounding distance. / Existing work, however, has not used employed dimensionality reduction in a flexible way, requiring all time series to be reduced to have the same dimension. In contrast, in this thesis, we investigate the possibility of allowing a variable dimension reduction. To this end, we develop a new and more flexible tree based indexing structure called the Multi-Resolution Index (MR-Index), which allows dimensionality to vary across different levels of the tree. We provide efficient algorithms for querying, building and maintaining this structure. Through an experimental analysis, we show that the MR-Index can deliver improved query efficiency compared to the traditional R-tree index, using both the Euclidean and dynamic time warping similarity measures.
47

Multi-resolution indexing method for time series

Ma, Mei January 2010 (has links)
Time series datasets are useful in a wide range of diverse real world applications. Retrieving or querying from a collection of time series is a fundamental task, with a key example being the similarity query. A similarity query returns all time series from the collection that are similar to a given reference time series. This type of query is particularly useful in prediction and forecasting applications. / A key challenge for similarity queries is efficiency and for large datasets, it is important to develop efficient indexing techniques. Existing approaches in this area are mainly based on the Generic Multimedia Indexing Method (GEMINI), which is a framework that uses spatial indexes such as the R-tree to index reduced time series. For processing a similarity query, the index is first used to prune candidate time series using a lower bounding distance. Then, all remaining time series are compared using the original similarity measure, to derive the query result. Performance within this framework depends on the tightness of the lower bounding distance with respect to the similarity measure. Indeed much work has been focused on representation and dimensionality reduction, in order to provide a tighter lower bounding distance. / Existing work, however, has not used employed dimensionality reduction in a flexible way, requiring all time series to be reduced to have the same dimension. In contrast, in this thesis, we investigate the possibility of allowing a variable dimension reduction. To this end, we develop a new and more flexible tree based indexing structure called the Multi-Resolution Index (MR-Index), which allows dimensionality to vary across different levels of the tree. We provide efficient algorithms for querying, building and maintaining this structure. Through an experimental analysis, we show that the MR-Index can deliver improved query efficiency compared to the traditional R-tree index, using both the Euclidean and dynamic time warping similarity measures.
48

Correlative indexing systems for the control of research records

Jahoda, Gerald, January 1900 (has links)
Thesis--Columbia University, 1960. / Bibliography: l. 170-175.
49

Data indexing in heterogeneous multiple broadcast channels environment /

Ho, Andrew Yin Fai. January 2003 (has links)
Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 101-104). Also available in electronic version. Access restricted to campus users.
50

A comparison of document clusters derived from co-cited references and co-assigned index terms

Rapp, Barbara Ann. January 1985 (has links)
Thesis (Ph. D.)--Drexel University, 1985. / Vita. Description based on print version record. Includes bibliographical references (leaves 182-185).

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