Spatial access method for urban geospatial database management: An efficient approach of 3D vector data clustering technique

2014 ◽  
Author(s):  
Suhaibah Azri ◽  
Uznir Ujang ◽  
Alias Abdul Rahman ◽  
Francois Anton ◽  
Darka Mioc
Keyword(s):  
Data Clustering ◽  
Database Management ◽  
Vector Data ◽  
Spatial Access ◽  
Access Method ◽  
Efficient Approach ◽  
Clustering Technique ◽  
Geospatial Database

Operating Point Estimation for an Absorption Process using Data Clustering Technique

2013 ◽  
Vol 13 (3) ◽  
pp. 377-384
Author(s):  
M. Amin A. Majid ◽  
Shaharin A. Sulaima ◽  
Hamdan Mokhtar ◽  
A.L. Tamiru
Keyword(s):  
Data Clustering ◽  
Point Estimation ◽  
Operating Point ◽  
Absorption Process ◽  
Clustering Technique ◽  
Using Data

Spatial Access Method for Flash Memory Embedded Systems

2011 ◽  
Vol 403-408 ◽  
pp. 4311-4317
Author(s):  
Ki Young Lee ◽  
Joung Joon Kim ◽  
Myung Jae Lim ◽  
Kyu Ho Kim ◽  
Jeong Lae Kim
Keyword(s):  
Embedded Systems ◽  
Spatial Data ◽  
Flash Memory ◽  
Operation Technique ◽  
Spatial Access ◽  
Compression Technique ◽  
Access Method ◽  
Memory Space ◽  
Relative Coordinates ◽  
Redundant Storage

This paper proposed an efficient spatial Access method, called MDR-Tree (Mbr compression and Delayed write operation based R-Tree), that uses the node compression technique and the delayed write operation technique for flash memory embedded systems. The node compression technique of MDR-Tree increased the utilization of flash memory space by compressing the MBR of spatial data using relative coordinates and MBR size. Moreover, the delayed write operation technique reduced the number of write operations in flash memory by temporarily storing spatial data in the buffer and by reflecting them in flash memory at once instead of reflecting the insert, update and delete of spatial data in flash memory for each operation. Especially, the utilization of buffer space was enhanced by preventing the redundant storage of the same spatial data in the buffer.

IQRAM: a high dimensional data clustering technique

2012 ◽  
Vol 2 (2/3) ◽  
pp. 117
Author(s):  
Dharmveer Singh Rajput ◽  
Pramod Kumar Singh ◽  
Mahua Bhattacharya
Keyword(s):  
Data Clustering ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Clustering Technique
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