Answer: Between Layers 2 and 3
Explanation:
In between Layer 2 and Layer 3 the MPLS header is present and is known as Shim header. It is also said to be in 2.5.
The programmer solves the problems of a user by expressing an algorithm in a programming language to make a program that can run on a computer.
Answer:
The solution is written using Python as it has a simple syntax.
- def getHighScores(gameScores, minScore):
- meetsThreshold = []
- for score in gameScores:
- if(score > minScore):
- meetsThreshold.append(score)
- return meetsThreshold
- gameScores = [2, 5, 7, 6, 1, 9, 1]
- minScore = 5
- highScores = getHighScores(gameScores, minScore)
- print(highScores)
Explanation:
Line 1-8
- Create a function and name it as <em>getHighScores</em> which accepts two values, <em>gameScores</em> and <em>minScore</em>. (Line 1)
- Create an empty list/array and assign it to variable <em>meetsThreshold</em>. (Line 2)
- Create a for loop to iterate through each of the score in the <em>gameScores</em> (Line 4)
- Set a condition if the current score is bigger than the <em>minScore</em>, add the score into the <em>meetsThreshold</em> list (Line 5-6)
- Return <em>meetsThreshold</em> list as the output
Line 11-12
- create a random list of <em>gameScores</em> (Line 11)
- Set the minimum score to 5 (Line 12)
Line 13-14
- Call the function <em>getHighScores()</em> and pass the<em> gameScores</em> and <em>minScore </em>as the arguments. The codes within the function <em>getHighScores()</em> will run and return the <em>meetsThreshold </em>list and assign it to <em>highScores.</em> (Line 13)
- Display <em>highScores</em> using built-in function print().
Answer:
I don't know if this is right output is {1,3}
Explanation:
Answer: Machine learning
Explanation:
The technology that could be combined with the current solution to do this is the machine learning.
Machine learning refers to the use and development of the computer systems which can learn and adapt without them following explicit instructions. This is done through the use of statistical models and algorithms in order to analyse inferences from the patterns in data.
Since the bank wants to streamline their operations for the receiving and processing checks while also enhancing the solution to recognize signs of potential check fraud, then the machine learning can be used.