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katrin [286]
4 years ago
12

Someone else can drive your car if _____.

Computers and Technology
2 answers:
SVETLANKA909090 [29]4 years ago
6 0

Answer:

C. you have proof of insurance

Explanation:

Residency has nothing to do with permission to drive a car. For example, someone may have residency, but be with a license suspended. So they can't drive.

Usually, also the insurance covers the CAR and not the person. So the general rule is:

Someone else can drive your car if you have proof of insurance

Sloan [31]4 years ago
4 0

Answer:

D

Explanation:

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_________ involves connecting geographically remote computers into a single network and combining the computational power of all
galben [10]

Answer:

Grid computing involves connecting geographically remote computers into a single network to create a computational grid that combines the computing power of all the computers on the network to attack large computing problems.

7 0
3 years ago
Read 2 more answers
g write a recursive function that prints out all the even numbers between x and y inclusive if x is odd then the print out will
Reil [10]

Answer:

The function written in python is as follows:

def EvenNumbers(x, y):

    if (y < x):

         return

    if (y % 2 == 0):

         EvenNumbers(x, y - 2)

    else:

         EvenNumbers(x, y - 1)

    if (y % 2 == 0):

         print(y)

Explanation:

x represents the lower limit while y represents the upper limit.

So, the recursion will be repeated as long as x <= y

This defines the function

def EvenNumbers(x, y):

This checks if y < x. If yes, the recursion stops execution and return to the main

<em>     if (y < x): </em>

<em>          return </em>

The following if and else condition checks determines the appropriate range of the recursion.

<em>     if (y % 2 == 0): </em>

<em>          EvenNumbers(x, y - 2) </em>

<em>     else: </em>

<em>          EvenNumbers(x, y - 1) </em>

The above takes care of printing starting at x + 1 if x is odd

This checks and prints the even numbers in the range

<em>     if (y % 2 == 0): </em>

<em>          print(y)</em>

<em />

To call the function from main, make use of

EvenNumbers(x, y)

Where x and y are integers

e.g EvenNumbers(2,10), EvenNumbers(1,17), EvenNumbers(3,21)

<em>See attachment</em>

3 0
3 years ago
I
Naily [24]

Answer:

True

Explanation:

Not(False) OR False = True OR False = True

4 0
3 years ago
My friend Leo wants to have an emergency plan for his final exams on University of Southern Algorithmville. He has N subjects to
leonid [27]

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.

6 0
3 years ago
Question 1(Multiple Choice Worth 5 points)
aleksley [76]

Answer:

b

Explanation:

it's not a c or d and now I have to make it 20 characters long so I will do this

3 0
3 years ago
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