1.)
<span>((i <= n) && (a[i] == 0)) || (((i >= n) && (a[i-1] == 0))) </span>
<span>The expression will be true IF the first part is true, or if the first part is false and the second part is true. This is because || uses "short circuit" evaluation. If the first term is true, then the second term is *never even evaluated*. </span>
<span>For || the expression is true if *either* part is true, and for && the expression is true only if *both* parts are true. </span>
<span>a.) (i <= n) || (i >= n) </span>
<span>This means that either, or both, of these terms is true. This isn't sufficient to make the original term true. </span>
<span>b.) (a[i] == 0) && (a[i-1] == 0) </span>
<span>This means that both of these terms are true. We substitute. </span>
<span>((i <= n) && true) || (((i >= n) && true)) </span>
<span>Remember that && is true only if both parts are true. So if you have x && true, then the truth depends entirely on x. Thus x && true is the same as just x. The above predicate reduces to: </span>
<span>(i <= n) || (i >= n) </span>
<span>This is clearly always true. </span>
The answer is an usb port
Answer:
False
Explanation:
False, all parking revenues do not come from home team games. The home team refers to a team that plays on its ground. Parking Revenue refers to the revenue earned from the rental of parking space.
Stadium owners can generate more revenue from parking and concessions by increasing the use of their venue. Stadium parking is also one of the sources of income.
Numpy is among the most prevalent science computer science bundles in Python, and the following are the discussion on the use of transpose function:
- Transpose() is among the most important <em>matrix multiplication functions</em>.
- It is used to changes elements of the <em><u>row into column</u></em> elements and the elements of the <em><u>column into rows</u></em> elements.
- The output of this function is an original modified array.
Therefore, the transpose function in NumPy is being used to <em><u>switch positions of rows to columns or columns to rows</u></em>.
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