Answer:
True
Explanation:
The bias value present in a floating point number deals with the positiveness and negativeness of the exponent part for a floating point number. The bias value for a floating point number is 127. It means that 127 is always needed to be added to the exponent part of any floating point number.
In a single precision floating point number, we need 8 bits to store the exponent. Rather than storing it as a signed two's complement number, it is easier to simply add 127 to the exponent (because the lowest value that can be in 8 bit signed is -127) and simply store it as an unsigned number. If the stored value is bigger than the bias then it would mean the value of the exponent is positive otherwise it is negative, but if they are equal then it is 0.
<span>Answer: Metasearch engines</span>
Answer:
i) The time taken for 1500 records = 15 seconds.
ii) The time taken for 1500 records = 50 seconds.
Explanation:
A is an O(n) algorithm.
An algorithm with O(n) efficiency is described as a linearly increasing algorithm, this mean that the rate at which the input increases is linear to the time needed to compute that algorithm with n inputs.
From the question, it is given that for 1000 records, the time required is: 10 seconds.
Algorithm time taken is O(n)
Hence,
1) For 1,500 records
=> 10/1000 = x/1500
=> 10x1500/1000 = x
x = 15 seconds
Thus, the time taken for 1500 records = 15 seconds.
2) For 5,000 records
=> 10/1000 = x/5000
=> 10x5000/1000 = x
x = 50 seconds
Thus, the time taken for 1500 records = 50 seconds.
C) fair use
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