D. Por el uso de tubos de vacio.
Answer:
C
Explanation:
what types of loop will be used.
Answer:
<h3>Connector names are written below Picture vise:</h3>
<h3 />
Explanation:
Following is the brie Illustration of the terms used:
It is the newest connector in the market with the reversible/symmetrical design. It can be adapted to work with the legacy connectors such as USB-A, USB-B, USB-C and Micro USB.
It is used mostly in the connections of electronic devices such as printers and smartphones. It has A to B connectors as well as micro USB connectors and mini USB connectors.
It is used for the connection o compact devices such as smartphone and mp3 players. They are further grouped into three categories: Micro A, Micro B and micro USB 3.
<h3>
I hope it will help you!</h3>
Answer:
Giant Tech Company mostly
Explanation:
they used it as their server or storing data, right now example we googling by that we send the requests from our computer to supercomputers and those computer will find that information your and send back the respond (e.g. website Brainly). Supercomputers = computers sample as that.
Answer:
See explaination for the program code
Explanation:
The code below
Pseudo-code:
//each item ai is used at most once
isSubsetSum(A[],n,t)//takes array of items of size n, and sum t
{
boolean subset[n+1][t+1];//creating a boolean mtraix
for i=1 to n+1
subset[i][1] = true; //initially setting all first column values as true
for i = 2 to t+1
subset[1][i] = false; //initialy setting all first row values as false
for i=2 to n
{
for j=2 to t
{
if(j<A[i-1])
subset[i][j] = subset[i-1][j];
if (j >= A[i-1])
subset[i][j] = subset[i-1][j] ||
subset[i - 1][j-set[i-1]];
}
}
//returns true if there is a subset with given sum t
//other wise returns false
return subset[n][t];
}
Recurrence relation:
T(n) =T(n-1)+ t//here t is runtime of inner loop, and innner loop will run n times
T(1)=1
solving recurrence:
T(n)=T(n-1)+t
T(n)=T(n-2)+t+t
T(n)=T(n-2)+2t
T(n)=T(n-3)+3t
,,
,
T(n)=T(n-n-1)+(n-1)t
T(n)=T(1)+(n-1)t
T(n)=1+(n-1)t = O(nt)
//so complexity is :O(nt)//where n is number of element, t is given sum
