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AQA Comp Sci paper 2 > Fundamentals of Data Representation > Flashcards

Fundamentals of Data Representation Flashcards

1
Q

Natural Numbers

A

The set of positive integers and 0. A subset of Integer Numbers.

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2
Q

Integer Numbers

A

The set of numbers with no fractional part.

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3
Q

Rational Numbers

A

The set of numbers that can be represented as the ratio of two integers.

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4
Q

Irrational numbers

A

The set of numbers which cannot be represented as a ratio of two integers.

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5
Q

Ordinal Numbers

A

Natural numbers used to describe numerical position or order of objects

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6
Q

Binary

A

A number system with base 2.

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7
Q

Decimal

A

A number system with base 10.

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8
Q

Hexadecimal

A

A number system with base 16

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9
Q

Number base

A

The number of unique digits used by a particular number system to represent numbers.

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10
Q

Bit

A

A binary digit used by computers as the fundamental unit of information. Either 1 or 0.

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11
Q

Byte

A

A group of 8 bits

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12
Q

Nibble

A

A group of 4 bits

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13
Q

Binary prefix

A

A prefix to a unit representing a power of 2. Kibi = power of 10, Mebi = 20, Gibi= 30, Tebi = 40

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14
Q

Decimal Prefix

A

A prefix to a unit representing a power of 10

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15
Q

Signed binary

A

A binary system capable of representing negative and positive numbers

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16
Q

Unsigned binary

A

A binary system that can only represent positive numbers.

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17
Q

Two’s complement

A

Coding scheme used to represent negative or positive number. If most significant bit is 1 = negative

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18
Q

Exponent

A

Stores number of positions to move the decimal point

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19
Q

Fixed point form

A

Decimal point is at a fixed position.

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20
Q

Floating point form

A

Radix point moved by exponant and uses normalisation. Number before and after decimal point have to be opposite. ie 1.0… or 0.1…

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21
Q

Mantissa

A

Component of floating point that stores the significant figures of the floating point

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22
Q

Absolute error

A

Difference between correct value and rounded value (ie stored in binary)

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23
Q

Relative error

A

The percentage difference between the exact value and rounded value

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24
Q

Underflow

A

The misrepresentation of a numeric value because it is too small to be represented by allocated exponent.

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25
Q

Overflow

A

Incapability to store a number in assigned bits because it is too large

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26
Q

Character code

A

A unique binary representation of a character

27
Q

ASCII

A

character set used to represent alphanumerical values or symbols as a set of 8 bits (used to be 7)

28
Q

Unicode

A

Superset of ASCII. Uses 16 or 32 bits instead of 8, where first 8 bits are the same symbols as in ASCII, 32 bits includes thigs such as chinese characters. Good for multilingual data. Needs much more storage space and higher transmission time than ASCII.

29
Q

Check digit

A

Method of error checking during data transmission by adding an extra digit at the end calculated from digits in code itself, usually mod 10.

30
Q

Check sum

A

Checks for transmission errors by calculating sum of transmitted digits

31
Q

Majority voting

A

Sending each bit thrice and then taking majority as correct digit. Error checking and correction during transmission.

32
Q

Parity bits

A

Most significant bit used to make number of 1’s sent in data packet either even or odd.

33
Q

Bitmapped Graphics

A

Image composed of an array of pixels with allocated number of bits arranged to form an image.

34
Q

Bitmap resolution/Size

A

Width in pixels * height in pixels

35
Q

Bitmap storage requirements

A

Amount of storage required for image = bitmap resolution * colour depth

36
Q

Colour depth

A

Number of bits per pixel where n bits can store 2^n colours

37
Q

Metadata

A

Data related to image file itself ie pixel width, depth, location

38
Q

Bitmap Density

A

Number of pixels per inch, used to describe computer screen

39
Q

Vector image

A

stores image as drawing list instead of pixels, can be scaled up without loss of detail, needs less storage space unless many tiny details.

40
Q

Image manipulation

A

You can change individual pixels easily in bitmap images and individual objects but not pixels in vector images

41
Q

Sound conversion to digital

A

Continuous analogue data converted to discrete digital data format where sampling frequency is measured in Hertz

42
Q

Sampling rate

A

The frequency at which you record the amplitude of the sound, higher sampling rate equals smoother sounding playback, however needs a lot of storage

43
Q

Sample size

A

num of bits per sec * length of recording in sec * num of bits per sample

44
Q

Analogue data

A

Analogue technology records wave in original format, for ex signal in microscope can be copied onto tape, read, amplified and sent to a speaker, quantities are measured

45
Q

Digital signal

A

Digital technology samples analogue waveforms in intervals and stores it on a digital device, quantities rather counted than measured

46
Q

Analogue to digital

A

Microphone turns sound energy into electrical energy, ADC samples data and turns it into binary

47
Q

Digital to Analogue

A

DAC converts binary back into a sound wave which then gets amplified which is connected to a speaker

48
Q

Interpreting frequency

A

Higher frequency means higher pitch and vise versa

49
Q

Nyquist theorem

A

Sampling rate should be at least double of the maximum frequency in original analogue signal

50
Q

Sound sampling

A

The process of converting analogue sound waves to a digital waveform

51
Q

Midi controller

A

Musical digital Instrument interface is a protocol for ADC audio transmission to a digital interface used for the majority of electronical musical instruments and computers

52
Q

Event messages

A

Bidary data transmitted between midi device and computer processor that carries properties controlling when and how sound is produced

53
Q

lossy compression

A

Removes non-essential information, data loss is non-recoverable

54
Q

lossless compression

A

records patterns of data instead of actual data, no data is lost

55
Q

Run-Length encoding

A

A type of lossless compression where repeated occurrences of the same data re stored as single data values with their counts

56
Q

Dictionary based encoding

A

Lossless compression where often reoccurring words are stored in dictionary and those words in the text replaced with the dictionary code

57
Q

Encryption

A

process of converting original data (plaintext) into a form which cannot be understood by unauthorised users (ciphertext) using an encryption algorithm (cipher)

58
Q

Caeser cipher

A

shifts alphabet and number shifted by is the key

59
Q

Vernam Cipher

A

Chiper that uses a one time pad to convert each each character to cipher text, computationally secure, uses XOR

60
Q

Brute force attack

A

Try until code has been deciphered

61
Q

Cryptanalysis

A

Uses for example frequency analysis to decode a cipher

62
Q

One time pad

A

A secret random key which is only used once

63
Q

Computationally secure

A

When time needed to decipher a code is unreasonable for data encrypted

AQA Comp Sci paper 2 (9 decks)

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