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CompSci > 3.5 Fundamentals of data representation > Flashcards

3.5 Fundamentals of data representation Flashcards

1
Q

Natural numbers (symbol, what they are)

A

N, positive integers including 0

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2
Q

Integers (symbol, what they are)

A

Z, positive and negative whole numbers including 0

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3
Q

Real numbers (symbol, what they are)

A

R, any positive or negative number and includes both irrational and rational numbers

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4
Q

Rational numbers (symbol, what they are)

A

Q, ratio between two integers

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5
Q

Irrational numbers (what they are, example)

A

can not be represented as a fraction, pi

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6
Q

Ordinal numbers (what they are)

A

a natural number that describes the numerical position of a value

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7
Q

denary (base-10) numbers

A

using 0-9 to represent a number, power of 10

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8
Q

binary (base-2) numbers

A

using 0 or 1 to represent a number, power of 2

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9
Q

most significant and least significant bit

A

most significant is leftmost and least significant is rightmost

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10
Q

hexadecimal (base-16) numbers

A

0-9 then A-F, power of 16

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11
Q

why is hexadecimal used as a shorthand for binary?

A

long sequences of binary are hard to read and understand for humans

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12
Q

how many different values can be represented with n bits?

A

2^n

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13
Q

kilobytes

A

1000 bytes, 10^3

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14
Q

megabyte

A

1 million bytes, 10^6

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15
Q

gigabyte

A

1 billion bytes, 10^9

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16
Q

terabyte

A

1 trillion bytes, 10^12

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17
Q

kibibyte

A

1024 bytes, 2^10

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18
Q

mebibyte

A

2^20 bytes

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19
Q

gibibyte

A

2^30 bytes

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20
Q

tebibyte

A

2^40

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21
Q

ascii

A

used 7 bits to represent characters, common language for computers

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22
Q

extended ascii

A

8 bit character set containing 256 characters

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23
Q

unicode

A

supports languages that use a different language, uses up to 32 bits to represent a character

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24
Q

what is a parity bit?

A

extra bit added depending on the total number of 1s

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25
Q

why are parity bits used?

A

to allow the receiving end to detect errors in data transmission

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26
Q

even parity

A

number of 1s add up to an even number

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27
Q

odd parity

A

number of 1s add up to an odd number

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28
Q

parity bit disadvantage

A

multiple errors wont show

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29
Q

majority voting

A

every bit is replicated an odd number of times, does not require a person to check

30
Q

majority voting disadvantages

A

if two bits are transmitted incorrectly it will take the error as being correct, data is sent multiple times slowing down transmission time

31
Q

analogue data

A

continuous data, needs to be converted into an electrical analogue signal

32
Q

digital data

A

discrete data

33
Q

digital signal

A

discrete values over time

34
Q

analogue to digital conversion

A

continuous signal needs to be converted into discrete binary values through an ADC

35
Q

how does an ADC work?

A

converts analogue electrical signals into digital data that can be stored

36
Q

digital to analogue DAC

A

converts digital data stored on a computer into analogue electrical signals

37
Q

bitmap image is made of

A

grid of pixels

38
Q

colour depth

A

bit per pixel, 2^number

39
Q

image resolution

A

clarity of an image, size of image

40
Q

calculating image resolution

A

width in pixels x height in pixels

41
Q

calculating bitmap file size

A

width in pixels x height in pixels x colour depth

42
Q

reducing colour depth and effect on image quality

A

poorer quality as humans can see so many colours it doesn’t look realistic

43
Q

reducing colour depth and effect on file size

A

file size also reduces, less bits used saves more storage, quicker download time

44
Q

metadata

A

data about image that is not included in the image

45
Q

examples of metadata

A

location of creation, camera settings, date and time of creation, file format

46
Q

how are bitmapped graphics created?

A

image will be stored as a grid of pixels, where each one represents a colour

47
Q

sound processing

A

sound waves picked up by microphone, signals processed by ADC converting electrical signals into digital values (sampling), assigned a binary pattern

48
Q

sampling (sound)

A

taking measurements of the levels of the analogue signal at regular intervals

49
Q

playing a digital audio file

A

DAC to convert digital values into analogue electrical signals, signals are passed onto a speaker, vibrating the speaker cone making sound waves

50
Q

sampling rate

A

number of samples taken per second, measured in hertz

51
Q

sample resolution

A

number of bits used to represent a sample

52
Q

nyquist theorem

A

in order to have an accurate representation of a signal, the sampling rate has to be at least twice the highest frequency present

53
Q

calculating sound file size (in bits)

A

sampling rate x seconds x sample resolution

54
Q

stereo sound files

A

multiply sound file size by two, left and right side

55
Q

MIDI

A

does not store a digital representation of an analogue, hold signals to produce sound

56
Q

MIDI advantages

A

uses less storage space, performance can be manipulated

57
Q

MIDI disadvantages

A

does not sound as realistic

58
Q

compression does not

A

change the fundamental properties of the file, e.g. music will still last the same amount of time

59
Q

lossy compression

A

data is permanently removed, approximation of the original, might remove unnecessary data

60
Q

lossy compression can not be applied to

A

word files

61
Q

lossless compression

A

no data is lost, get back exactly what you started with when you decompress, RLE or dictionary based

62
Q

RLE (run length encoding)

A

finds runs of repeated binary patterns and replaces them with a single instance of a pattern

63
Q

dictionary based encoding

A

finds common strings and assigns that a code which is stored instead

64
Q

plaintext

A

message that has not been encrypted

65
Q

symmetric methods

A

same key is used to encrypt and decrypt

66
Q

asymmetric methods

A

sender and recipient use a key pair

67
Q

caesar cipher

A

shifts each letter of the plaintext by a number specified by the key

68
Q

vernam cipher encrypting

A

a message is encrypted using a key of the same length, binary ascii for each letter of plaintext and key, XOR corresponding pair of bits

69
Q

vernam cipher decryption

A

binary code for each character of the cipher text and key, XOR

70
Q

XOR operations

A

0 + 0 = 0, 0 + 1 = 1, 1 + 0 = 1, 1 +1 = 0

71
Q

analogue to digital conversion 2

A

analogue recorded via amplifier, each sample is quantised into integer, integer into binary

CompSci (8 decks)

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