Answer:
- def is_prime(n):
- for i in range(2, n):
- if(n % i == 0):
- return False
- return True
-
- prime_truths = [is_prime(x) for x in range(2,101)]
- print(prime_truths)
Explanation:
The solution code is written in Python 3.
Presume there is a given function is_prime (Line 1 - 5) which will return True if the n is a prime number and return False if n is not prime.
Next, we can use the list comprehension to generate a list of True and False based on the prime status (Line 7). To do so, we use is_prime function as the expression in the comprehension list and use for loop to traverse through the number from 2 to 100. The every loop, one value x will be passed to is_prime and the function will return either true or false and add the result to prime_truth list.
After completion of loop within the comprehension list, we can print the generated prime_truths list (Line 8).
Answer:
Big Oh notation is used to asymptotically bound the growth of running time above and below the constant factor.
Big Oh notation is used to describe time complexity, execution time of an algorithm.
Big Oh describes the worst case to describe time complexity.
For the equation; T(N) = 10000*N + 0.00001*N^3.
To calculate first of all discard all th constants.
And therefore; worst case is the O(N^3).
Answer:
Pseudocode is as follows:
// below is a function that takes two parameters:1. An array of items 2. An integer for weight W
// it returns an array of selected items which satisfy the given condition of sum <= max sum.
function findSubset( array items[], integer W)
{
initialize:
maxSum = 0;
ansArray = [];
// take each "item" from array to create all possible combinations of arrays by comparing with "W" and // "maxSum"
start the loop:
// include item in the ansArray[]
ansArray.push(item);
// remove the item from the items[]
items.pop(item);
ansArray.push(item1);
start the while loop(sum(ansArray[]) <= W):
// exclude the element already included and start including till
if (sum(ansArray[]) > maxSum)
// if true then include item in ansArray[]
ansArray.push(item);
// update the maxSum
maxSum = sum(ansArray[items]);
else
// move to next element
continue;
end the loop;
// again make the item[] same by pushing the popped element
items.push(item);
end the loop;
return the ansArray[]
}
Explanation:
You can find example to implement the algorithm.
Answer:
A
Explanation:
The most likely cause of the problem is that You signed in to BIOS/UEFI with the user power-on password rather than the supervisor power-on password. The User password only enables the machine to boot while the supervisor password allows entering the BIOS settings.
The answer in the blank is files for they exist in the computer that are responsible to hold or collect different types of application that could contribute in arranging them in order or showing classifications or simply storing them to put them in one place. This is essential to the computer for they are responsible in putting them in place and showing organization.
