The exercise is about filling in the gaps and is related to the History of the ARPANET.
<h3>
What is the History of the ARPANET?</h3>
From the text:
In 1972, earlier designers built the <u>ARPANET </u>connecting major universities. They broke communication into smaller chunks, or <u>packets </u>and sent them on a first-come, first-serve basis. The limit to the number of bytes of data that can be moved is called line capacity, or <u>bandwidth</u>.
When a network is met its capacity the user experiences <u>unwanted pauses</u>. When the network is "slowing down", what is happening is users are waiting for their packet to leave the <u>queue</u>.
To make the queues smaller, developers created <u>mixed </u>packets to move <u>simultaneously</u>.
Learn more about the ARPANET at:
brainly.com/question/16433876
Answer:
import numpy as np#importing numpy module with an alias np.
def c(bitstring_array):# defining function c.
num_integer=bitstring_array.dot(2**np.arange(bitstring_array.size)[::-1])#bitstring conversion.
return num_integer#returning integer array.
print("Enter bits")
Bit_l=input().split(" ")#enter space separated bitstring.
for i in range(len(Bit_l)):#iterating over the bitstring.
Bit_l[i]=int(Bit_l[i])
bitstring_array=np.array(Bit_l)
print(c(bitstring_array))#function call.
Output:
Enter bits
1 1 1 0 0 1
57
Answer:
int x;
indata.open("lottowins");
indata >> x;
cout << x << endl;
indata >> x;
cout << x << endl;
indata >> x;
cout << x << endl;
indata.close();
Answer:
b. Machine learning
Explanation:
The technique that is being described in this situation is known as Machine Learning. This is a fairly new technology that has become popular over the last decade. Machine learning uses artificial intelligence to analyze data and learn from it. Every time the system analyzes the data it learns something new, saves it, and implements it to its processes. Therefore, the more times it repeats the more it learns. These systems are continuously getting better and learning more, which makes them incredibly efficient.
