Efficient Searching with Linear Constraints
... which is optimal. Numerous structures have been proposed for range searching in two and higher dimensions, for example, grid les [36], quad-trees [42, 43, 8], k-d-Btrees and variants [41, 27], hB-trees [19, 31], and R-trees and variants [7, 25, 29, 44, 9]. (More references can be found in the surve ...
... which is optimal. Numerous structures have been proposed for range searching in two and higher dimensions, for example, grid les [36], quad-trees [42, 43, 8], k-d-Btrees and variants [41, 27], hB-trees [19, 31], and R-trees and variants [7, 25, 29, 44, 9]. (More references can be found in the surve ...
CS 180 Problem Solving and OO Programming Fall 2010
... Given: Three towers A, B, and C. A contains n discs arranged from bottom to top as shown below. Problem: Find a sequence of moves such that at the end of these moves all discs are in C. No larger disc should ever be on top of a smaller disk. Only one disk can be moved at a time from one tower to ano ...
... Given: Three towers A, B, and C. A contains n discs arranged from bottom to top as shown below. Problem: Find a sequence of moves such that at the end of these moves all discs are in C. No larger disc should ever be on top of a smaller disk. Only one disk can be moved at a time from one tower to ano ...
Searching algorithms
... Selection can be reduced to sorting by sorting the list and then extracting the desired element. This method is efficient when many selections need to be made from a list, in which case only one initial, expensive sort is needed, followed by many cheap extraction operations. In general, this method ...
... Selection can be reduced to sorting by sorting the list and then extracting the desired element. This method is efficient when many selections need to be made from a list, in which case only one initial, expensive sort is needed, followed by many cheap extraction operations. In general, this method ...
2010: Dashiell Kolbe
... Finger print matching and voice recognition are both handled in a similar fashion. For each, a feature vector is established, containing values representing key structures within the object, such as whorls in a fingerprint, which is then compared with an indexed set of feature vectors to determine t ...
... Finger print matching and voice recognition are both handled in a similar fashion. For each, a feature vector is established, containing values representing key structures within the object, such as whorls in a fingerprint, which is then compared with an indexed set of feature vectors to determine t ...
Landscape Connectivity: A Graph
... matrix A, a binary matrix in which each element is defined ac = 1 if nodes i and j are connected, otherwise aij = 0. The diagonal of A, aii, is also set to 0 (graphs include no self-loops). In practice, A may be generated from either of the matrices D or P by choosing a threshold distance or probabi ...
... matrix A, a binary matrix in which each element is defined ac = 1 if nodes i and j are connected, otherwise aij = 0. The diagonal of A, aii, is also set to 0 (graphs include no self-loops). In practice, A may be generated from either of the matrices D or P by choosing a threshold distance or probabi ...
Data Structures and Analysis - Department of Computer Science
... At this point you might be thinking, “well, each number is even with probability one-half, so...” This is a nice thought, but a little premature – the first step when doing an average-case analysis is to define the possible set of inputs. For this example, we’ll start with a particularly simple set ...
... At this point you might be thinking, “well, each number is even with probability one-half, so...” This is a nice thought, but a little premature – the first step when doing an average-case analysis is to define the possible set of inputs. For this example, we’ll start with a particularly simple set ...
Data Structures
... Linked lists provide several advantages over array objects and built-in arrays. A linked list is appropriate when the number of data elements to be represented at one time is unpredictable. Linked lists are dynamic, so the length of a list can increase or decrease as necessary. The size of an array ...
... Linked lists provide several advantages over array objects and built-in arrays. A linked list is appropriate when the number of data elements to be represented at one time is unpredictable. Linked lists are dynamic, so the length of a list can increase or decrease as necessary. The size of an array ...
Data Structures
... Linked lists provide several advantages over array objects and built-in arrays. A linked list is appropriate when the number of data elements to be represented at one time is unpredictable. Linked lists are dynamic, so the length of a list can increase or decrease as necessary. The size of an array ...
... Linked lists provide several advantages over array objects and built-in arrays. A linked list is appropriate when the number of data elements to be represented at one time is unpredictable. Linked lists are dynamic, so the length of a list can increase or decrease as necessary. The size of an array ...
The Pigeonhole Principle and Hashing
... and each object is accessed by using the associated key. For example, we could have a table of motor vehicle drivers, where each object is a driver’s record having a name, address, number of points for bad driving, etc. Each of these objects has an associated key. What field below might make a suita ...
... and each object is accessed by using the associated key. For example, we could have a table of motor vehicle drivers, where each object is a driver’s record having a name, address, number of points for bad driving, etc. Each of these objects has an associated key. What field below might make a suita ...
Document
... – When building R-tree by repeated insertion first inserted rectangles are possibly badly placed • Experiment: – Make R-tree by inserting 20.000 rectangles – Delete the first inserted 10.000 and insert them again • Search time improvement of 20-50% ...
... – When building R-tree by repeated insertion first inserted rectangles are possibly badly placed • Experiment: – Make R-tree by inserting 20.000 rectangles – Delete the first inserted 10.000 and insert them again • Search time improvement of 20-50% ...
Fast computation of maximum - uni
... • This algorithm takes O(n) processors and O(log n) time. • We can reduce the processor complexity to O(n / log n). Hence the algorithm does optimal O(n) work. ...
... • This algorithm takes O(n) processors and O(log n) time. • We can reduce the processor complexity to O(n / log n). Hence the algorithm does optimal O(n) work. ...
Linked Lists
... Linked List as an ADT (continued) There are two types of linked lists: sorted and unsorted The algorithms to implement some of the operations differ for sorted and unsorted lists Therefore, define the LinkedListClass as an abstract class LinkedListClass has two derived classes UnorderedLi ...
... Linked List as an ADT (continued) There are two types of linked lists: sorted and unsorted The algorithms to implement some of the operations differ for sorted and unsorted lists Therefore, define the LinkedListClass as an abstract class LinkedListClass has two derived classes UnorderedLi ...
Heaps - CENG METU
... uses an extra array for the items exiting the heap. • We can avoid this problem as follows: – After each deleteMin, the heap shrinks by 1. – Thus the cell that was last in the heap can be used to store the element that was just deleted. – Using this strategy, after the last deleteMin, the array will ...
... uses an extra array for the items exiting the heap. • We can avoid this problem as follows: – After each deleteMin, the heap shrinks by 1. – Thus the cell that was last in the heap can be used to store the element that was just deleted. – Using this strategy, after the last deleteMin, the array will ...
Multidimensional Access Methods
... spatial proximity. In other words, there is no mapping from two- or higher-dimensional space into one-dimensional space such that any two objects that are spatially close in the higher-dimensional space are also close to each other in the one-dimensional sorted sequence. This makes the design of eff ...
... spatial proximity. In other words, there is no mapping from two- or higher-dimensional space into one-dimensional space such that any two objects that are spatially close in the higher-dimensional space are also close to each other in the one-dimensional sorted sequence. This makes the design of eff ...
lec6
... – When building R-tree by repeated insertion first inserted rectangles are possibly badly placed • Experiment: – Make R-tree by inserting 20.000 rectangles – Delete the first inserted 10.000 and insert them again • Search time improvement of 20-50% ...
... – When building R-tree by repeated insertion first inserted rectangles are possibly badly placed • Experiment: – Make R-tree by inserting 20.000 rectangles – Delete the first inserted 10.000 and insert them again • Search time improvement of 20-50% ...
Question Bank
... Ans: No. Minimal spanning tree assures that the total weight of the tree is kept at its minimum. But it doesn't mean that the distance between any two nodes involved in the minimum-spanning tree is minimum. Ques 9: What is the difference between BFS and DFS? Ans : BFS: This can be throught of as bei ...
... Ans: No. Minimal spanning tree assures that the total weight of the tree is kept at its minimum. But it doesn't mean that the distance between any two nodes involved in the minimum-spanning tree is minimum. Ques 9: What is the difference between BFS and DFS? Ans : BFS: This can be throught of as bei ...
B-tree
In computer science, a B-tree is a tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic time. The B-tree is a generalization of a binary search tree in that a node can have more than two children (Comer 1979, p. 123). Unlike self-balancing binary search trees, the B-tree is optimized for systems that read and write large blocks of data. B-trees are a good example of a data structure for external memory. It is commonly used in databases and filesystems.