Consider the half-precision floating-point format, which has five bits for the exponent and ten bits for the significand. Find the decimal (i.e., base 10) number represented by the following bits in the half-precision floating- point format: (a) 0100110001110000. (b) 1000001111111111. (c) 0111110000000000.

Here is an encoded message in ASCII using eight bits per character. What does it say?

Consider a 16-bit binary floating point number representation system: + SE E EEEE m m m m The first bit of the exponent is dedicated to its sign. Assume that the mantissa must start with a '1'. Use this system to answer the following questions: 1. What is the smallest (magnitude) number that can be represented with this system? 2. Calculate the relative round-off error introduced when this system tries to represent e = 2.718281828459045235360287 .. using rounding.

Our everyday number system in the UK and many other parts of the world is a base-10 system using Arabic numerals, namely the digits 0, 1, 9. Integers larger than 9 are represented by sequences of these elementary numerals. The numerical value encoded by such a sequence is determined by multiplying each numeral by 10k, where k is the position of the numeral counted from the back and starting at zero, and then summing together the contributions from all numerals. For example, 5207 = 5 × 10³ +2×10² +0×10¹ + 7×10⁰ The built-in int function in Python can take a string (type str) representing such a number and convert it to a Python integer (type int). Write a similar function base14_convert that takes a string and converts it to a Python integer according to the following number system: • the base is 14, i.e., the individual digits have to be multiplied by powers of 14 to obtain the numerical value; digits are represented by lower-case letters 'a', 'b', 'c', 'd', ..., i.e., 'a' is…