Answer:
Err. I'm getting vibes from C.
Explanation:
Janelle is organizing an outline for an investigative report about the benefits of taking a 30-minute walk each day.
Benefits - Good/Helpful
The world cyber games originated in South Korea.
Answer: Utility Software
Explanation:
Utility software is software designed to help to analyze, configure, optimize or maintain a computer. It is used to support the computer infrastructure - in contrast to application software, which is aimed at directly performing tasks that benefit ordinary users.
Answer:
//Include this header file if program is executing on //visual studio.
#include "stdafx.h";
//Include the required header file.
#include <iostream>
#include <string>
//Use the standard namespace.
using namespace std;
//Define the function rcopy.
void rcopy()
{
//Declare a string variable to store the string.
string s;
//Prompt the user to input the string.
cin >> s;
//Check if the string entered by the user reach to
//the next line character.
if (cin.get() == '\n')
{
//Display the last word in the string.
cout << s << " ";
//Return from the if statement.
return;
}
//Make a recursive call to the function rcopy.
rcopy();
//Display the remaining words in the string in
//the reverse order.
cout << s << " ";
}
//Start the execution of the main method.
int main()
{
//Call the function rcopy.
rcopy();
//Use this system command to hold the console screen //in visual studio.
system("pause");
//Return an integer value to the main function.
return 0;
}
Explanation:
See attached images for the code and output
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.
