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Data Structures for Mobile Data
Data Structures for Mobile Data

Historical Queries Along Multiple Lines of Time Evolution
Historical Queries Along Multiple Lines of Time Evolution

... The Vertical Query is an extension of the single-line historical queries to the case of multiple lines of evolution. The state of the evolving system and the notion of a state change can be defined in various ways, depending on the application. In the example above, the state is defined as a collect ...
Document
Document

Cache-Oblivious Dynamic Search Trees Zardosht Kasheff
Cache-Oblivious Dynamic Search Trees Zardosht Kasheff

... memory is the bottleneck and optimize accordingly. To program efficiently under a multilevel memory hierarchy requires the user to consider multiple block sizes B1 , B2 , . . . , Bn . To create a tree that is aware of these blocks sizes, aware of the number of memory levels, and performs optimally i ...
Chapter 15
Chapter 15

Skew Heaps
Skew Heaps

Trees
Trees

Interval Sequences: An Object-Relational Approach to
Interval Sequences: An Object-Relational Approach to

Chapter x - CHAPTER TITLE
Chapter x - CHAPTER TITLE

... It is very important that the student understand that linked lists have this in common with strings: there is a NULL terminator for each. Even though they are spelled differently, they are both 0. (‘\0’ is one spelling for 0, and is a character. NULL is another spelling for 0; this one is an integer ...
Directed Edges | A Scalable Representation for Triangle Meshes
Directed Edges | A Scalable Representation for Triangle Meshes

Data structure - E
Data structure - E

Concurrency and Recovery in Generalized Search Trees
Concurrency and Recovery in Generalized Search Trees

... access. Furthermore, the access method also should support the degrees of transactional isolation offered by the query language of the DBMS. Finally, the access method must fit in with the recovery mechanism that guarantees the integrity of the DBMS’s data. Most research on novel access methods comp ...
CSE 326: Data Structures Lecture #7 Branching Out
CSE 326: Data Structures Lecture #7 Branching Out

... Everything inside the cloud has the correct shortest path Proof is by induction on the # of nodes in the cloud: – initial cloud is just the source with shortest path 0 – inductive step: once we prove the shortest path to G is correct, we add it to the cloud ...
Balanced Search Trees
Balanced Search Trees

... – A 2-node (has two children) must contain single data item greater than left child’s item(s) and less than right child’s item(s) – A 3-node (has three children) must contain two data items, S and L , such that • S is greater than left child’s item(s) and less than middle child’s item(s); • L is gre ...
IOSR Journal of Computer Engineering (IOSR-JCE)
IOSR Journal of Computer Engineering (IOSR-JCE)

SigMatch*Fast and Scalable Multi
SigMatch*Fast and Scalable Multi

... The sigMatch method is a generic filtering technique that can be plugged in as a pre-processing step for any existing multi-pattern matching system. ...
Parallel and Distributed Branch-and-Bound/A* Algorithms
Parallel and Distributed Branch-and-Bound/A* Algorithms

... To forbid the creation of a cycle of processors waiting for resources (deadlocks), we have to force each processor to follow a speci c locking scheme. A simple scheme of this top-down method can be described as follows. Each operating window will be moved down the path, from the root to a leaf. Nota ...
Chapter 2: Advanced Data Structures
Chapter 2: Advanced Data Structures

... • If the tree is nonempty, the root must have at least one key. • Every node can contain at most 2t − 1 keys. Therefore, an internal node can have at most 2t children. • We say that a node is full if it contains exactly 2t − 1 keys. Jaruloj Chongstitvatana Chapter 2: Advanced Data Structures ...
Lecture 6: Intro to Data Structures and the Standard Template Library
Lecture 6: Intro to Data Structures and the Standard Template Library

ELEMENTARY DATA STRUCTURES
ELEMENTARY DATA STRUCTURES

... Inserting at the Tail create a new node head tail ...
Dynamic Connectivity
Dynamic Connectivity

Worst Case Efficient Data Structures for Priority Queues and Deques
Worst Case Efficient Data Structures for Priority Queues and Deques

A Representation:  Fast  Algorithm Optimal  Kernel  Design for
A Representation: Fast Algorithm Optimal Kernel Design for

LECT#23
LECT#23

Heaviest Induced Ancestors and Longest Common Substrings
Heaviest Induced Ancestors and Longest Common Substrings

< 1 ... 37 38 39 40 41 42 43 44 45 ... 95 >

Quadtree



A quadtree is a tree data structure in which each internal node has exactly four children. Quadtrees are most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions. The regions may be square or rectangular, or may have arbitrary shapes. This data structure was named a quadtree by Raphael Finkel and J.L. Bentley in 1974. A similar partitioning is also known as a Q-tree. All forms of quadtrees share some common features: They decompose space into adaptable cells Each cell (or bucket) has a maximum capacity. When maximum capacity is reached, the bucket splits The tree directory follows the spatial decomposition of the quadtree.
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