Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
Calarts? Cartoon I don’t really know but that’s all the information that I have
Answer:
A lookaside buffer translation (TLB) is a memory cache that reduces the time it takes to access a user memory place. TLB includes the most lately used page table entries.
TLB is used to overcome the issue of sizes at the time of paging. Page Table Entry (PTE) is used for framing the memory ,but it uses two references one for finding the frame number
and the other for the address specified by frame number.
<u>Formula for finding effective memory access time-</u>
Effective Memory Access Time = (TLB access_time+Memory Access Time)*hit ratio + (TLB access_time+2*Memory Access Time)*(miss ratio)
Given in question,
Hit ratio = 0.90
Memory Access Time = 150ns
TLB access time= 5ns
Effective Memory Access Time = (TLB access_time+Memory Access Time)*hit ratio + (TLB access_time+2*Memory Access Time)*(miss ratio)
=(5+150) * 0.90 + (5+2*150)*(1-0.90)
=155 * 0.90 + (305*0.1)
=139.5 + 30.5
= 170ns
You cannot create a database wurg a word processor
Answer: Acoustics
Explanation:
Acoustics is simply refered to as a branch in physics that studies sound and its wave.
Acoustics studies mechanical waves in liquid, solid state or gaseous state. Topics such as infrasound, vibration and ultrasound are studied. Someone who works in the acoustics field is referred to as an acoustician.
