land cover is one of basic data layers in geographic information system for physical planning and environmentalmonitoring. digital image classification is generally performed to produce land cover maps from remote sensing data,particularly for large areas. in the present study the multispectral image from irs liss-iii image along with ancillary datasuch as vegetation indices, principal componen...

A digital search tree (DST) is a fundamental data structure on words that finds myriad of applications from the popular Lempel-Ziv’78 data compression scheme to distributed hash tables. It is a digital tree in which strings (keys, words) are stored directly in (internal) nodes. The profile of a DST measures the number of nodes at the same distance from the root; it is a function of the number o...

Figure 1: a binary tree Search trees are tree-based data structures that can be used to store and search for items that satisfy a total order. There are many types of search trees designed for a wide variety of purposes. Probably, the most common use is to implement sets and tables (dictionaries, mappings). As shown on right, a binary tree is a tree in which every node in the tree has at most t...

In the next two lectures we study the question of dynamic optimality, or whether there exists a binary search tree algorithm that performs ”as well” as all other algorithms on any input string. In this lecture we will define a binary search tree as a formal model of computation, show some analytic bounds that a dynamically optimal binary search tree needs to satisfy, and show two search trees t...

In this paper, we accelerate the processing of tree-based index structures by using SIMD instructions. We adapt the B+-Tree and prefix B-Tree (trie) by changing the search algorithm on inner nodes from binary search to k-ary search. The k-ary search enables the use of SIMD instructions, which are commonly available on most modern processors today. The main challenge for using SIMD instructions ...

An optimal binary search tree is a binary search tree for which the nodes are arranged on levels such that the tree cost is minimum. For the purpose of a better presentation of optimal binary search trees, we will consider “extended binary search trees”, which have the keys stored at their internal nodes. Suppose “n” keys k1, k2, ... , k n are stored at the internal nodes of a binary search tre...

In the next two lectures we study the question of dynamic optimality, or whether there exists a binary search tree algorithm that performs ”as well” as all other algorithms on any input string. In this lecture we will define a binary search tree as a formal model of computation, show some analytic bounds that a dynamically optimal binary search tree needs to satisfy, and show two search trees t...

For an optimal binary search tree T with a subtree S(d) at a distance d from the root of T, we study the ratio of the weight of S(d) to the weight of T. The maximum possible value, which we call ρ(d), of the ratio of weights, is found to have an upper bound of 2/Fd+3 where Fi is the ith Fibonacci number. For d = 1, 2, 3, and 4, the bound is shown to be tight. For larger d, the Fibonacci bound g...