A REVIEW OF ACOUSTIC SPACE FILLING CURVE METAMATERIALS FOR JET ENGINE INLETS

Spatial indexes, such as those based on the Quad Tree, are important in spatial databases for the effective implementation of queries with spatial constraints, especially when queries involve spatial links. The quaternary trees are a very interesting subject, given the fact that they give the ability to solve problems in a way that focuses only on the important areas with the highest density of information. Nevertheless, it is not without the disadvantages because the search process in the quad tree suffers from the problem of repetition when reaching the terminal node and return to the behavior of another way in the search and lead to the absorption of large amounts of time and storage. In this paper, the quad tree was improved by combining it with one of the space filling curve types, resulting in reduced storage space requirements and improved implementation time

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Space-Filling Curve Tool Paths

Springer Series in Advanced Manufacturing - Advanced Numerical Methods to Optimize Cutting Operations of Five-Axis Milling Machines ◽

10.1007/978-3-540-71121-6_4 ◽

2007 ◽

pp. 73-95

Keyword(s):

Space Filling ◽

Space Filling Curve ◽

Tool Paths ◽

Filling Curve

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The LBF R-Tree

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development ◽

10.4018/978-1-60566-748-5.ch001 ◽

2010 ◽

pp. 1-27

Author(s):

Todd Eavis

Keyword(s):

Hilbert Space ◽

Data Warehousing ◽

Experimental Results ◽

Data Sets ◽

Space Filling ◽

Fully Integrated ◽

Space Filling Curve ◽

Filling Curve ◽

Common User ◽

Tree Performance

In multi-dimensional database environments, such as those typically associated with contemporary data warehousing, we generally require effective indexing mechanisms for all but the smallest data sets. While numerous such methods have been proposed, the R-tree has emerged as one of the most common and reliable indexing models. Nevertheless, as user queries grow in terms of both size and dimensionality, R-tree performance can deteriorate significantly. Moreover, in the multi-terabyte spaces of today’s enterprise warehouses, the combination of data and indexes ? R-tree or otherwise ? can produce unacceptably large storage requirements. In this chapter, the authors present a framework that addresses both of these concerns. First, they propose a variation of the classic R-tree that specifically targets data warehousing architectures. Their new LBF R-tree not only improves performance on common user-defined range queries, but gracefully degrades to a linear scan of the data on pathologically large queries. Experimental results demonstrate a reduction in disk seeks of more than 50% relative to more conventional R-tree designs. Second, the authors present a fully integrated, block-oriented compression model that reduces the storage footprint of both data and indexes. It does so by exploiting the same Hilbert space filling curve that is used to construct the LBF R-tree itself. Extensive testing demonstrates compression rates of more than 90% for multi-dimensional data, and up to 98% for the associated indexes.

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Space Filling Curve for Data Filling: An Embedded Security Approach

Research Journal of Information Technology ◽

10.3923/rjit.2014.188.197 ◽

2014 ◽

Vol 6 (3) ◽

pp. 188-197 ◽

Cited By ~ 5

Author(s):

Siva Janakirama ◽

K. Thenmozhi ◽

Sundararaman Rajagopala ◽

Har Narayan Upadhyay ◽

John Bosco Balaguru Rayappan ◽

...

Keyword(s):

Space Filling ◽

Space Filling Curve ◽

Embedded Security ◽

Filling Curve

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