Answer:
There's a parking lot that is 600m² big. The lot must be able to hold at least 3 buses and 10 cars.
Each car takes up 6m² and each bus takes up 30m².
However, there can only be 60 vehicles in the lot at any given time.
The cost to park in the lot is $2.50 per day for cars and $7.50 per day for buses. The lot must make at least $75 each day to break even.
What is a possible car to bus ratio that would allow the lot to make profit?
The answer to the question you have asked is <u><em>"B" . </em></u> Because if you really think about it, there is no possible way that "Good" can be a keyword of "Hideous".
Answer:
#include <iostream>
using namespace std;
int main()
{
float altitude;
cout<<"Enter alttitude in meter";
cin >>altitude;
if(altitude<0 || altitude > 50000)
{
cout<<"Invalid value entered";
return 0;
}
else{
if(altitude<= 10000)
{cout <<"In troposphere "<<endl;}
else if(altitude>10000 && altitude<=30000)
{cout <<"In lower stratosphere"<<endl;}
else if(altitude>30000 && altitude<=50000)
{cout <<"In upper stratosphere"<<endl;}
}
return 0;
}
Explanation:
Define a float type variable. Ask user to enter altitude in meters. Store value to altitude variable.
Now check if value entered is positive and less than 5000,if its not in the range of 0-50,000 display a termination message and exit else check if it's in less than 10000, in between 10000 and 30000 or in between 30000 and 50000.
10,000 is above sea level is troposphere.
10,000-30,000 is lower stratosphere.
30,000-50,000 is upper stratosphere.
Answer:
See explaination
Explanation:
The reasons why indexed sequential search structure is better are:
1. In index sequential search any field of the records can be used as the key. This key field can be numerical or alphanumerical.
2. Since each record has its data block address, searching for a record in larger database is easy and quick. There is no extra effort to search records. But proper primary key has to be selected to make efficient.
3. This method gives flexibility of using any column as key field and index will be generated based on that. In addition to the primary key and its index, we can have index generated for other fields too. Hence searching becomes more efficient, if there is search based on columns other than primary key.
The reasons why 5 B-tree is better:
1.The B-tree Provides support for range of queries in an efficient manner and You can iterate over an ordered list of elements.
2. B-Tree algorithms are good for accessing pages (or blocks) of stored information which are then copied into main memory for processing. In the worst case, they are designed to do dynamic set operations in O(lg n) time because of their high "branching factor" (think hundreds or thousands of keys off of any node). It is this branching factor that makes B-Trees so efficient for block storage/retrieval, since a large branching factor greatly reduces the height of the tree and thus the number of disk accesses needed to find any key.
3. It is a generalization of a BST in that a node can have more than two children. These are self-balancing and hence the average and worst complexities is logarithmic. We opt for these when the data is too huge to fit in main memory. These structures are used in database indexing and help in faster operations on disk
the additional informations is we should first decide to choose which structure is suiatable for which algoritm in terms of space and time and then use the appropriate search algorithm.
For Example,
If You Were Hosting Ark Survival And Suddenly The Server Was Off Then The Players Goes Off.The Server Is How We Connect To The Platform In Order To Do The Action Intended.
