Chapter 1 #9

Question 1

Section I: Key Terms and Foundational Concepts

Question 2

Define Binary.

Answer 2

Base two number system based on the values 0 and 1.

Question 3

Define a Bit and explain why the Binary system is ideal for computers.

Answer 3

A Bit is the abbreviation for binary digit. It is the smallest unit of digital information. The system is ideal because it uses digits 0 and 1, corresponding to the simple ON/OFF switch mechanism that logic gates opperate by.

Question 4

What is a Nibble and a Byte?

Answer 4

4 bits are referred to as a Nibble. 8 bits are referred to as a Byte.

Question 5

Define Hexadecimal.

Answer 5

A base 16 number system, which uses the denary digits 0 to 9 and the letters A to F.

Question 6

Why/where is Hexadecimal used in computing?

Answer 6

1. It is easier to represent and manage compared to long binary sequences.
2. It is used in Memory Dumps and during program debugging.

Question 7

Define Memory Dump.

Answer 7

Contents of computer memory output to a screen or printer.

Question 8

What is a Character Set? How are strings converted using the character set?

Answer 8

Define character set: A list of all of the characters that can be used/represented by the computer hardware and software. Each character has a unique binary number.
How a string is converted using a character set: The characters are replaced by their binary values when used and is stored in sequence as its binary value using the character set. (answer includes definition + this)

Question 9

Define ASCII Code and specify its bit usage and character capacity.

Answer 9

ASCII is a character set for all characters on an English keyboard and control codes. It uses 7 bits, allowing for 128 different codes/characters.

Question 10

What is Extended ASCII’s bit usage and character capacity?

Answer 10

Extended ASCII uses 8 bits, allowing for 256 different codes/characters.

Question 11

Define Unicode and specify its standard bit usage and capacity.

Answer 11

Unicode is a character set which represents all languages of the world. It can use up to 4 bytes (32 bits) per character, which means that it can represent up to 2^32 unique characters.

Question 12

What is a key design feature of Unicode that correlates to ASCII?

Answer 12

The first 128 characters of Unicode are the same as ASCII.

Question 13

Compare and contrast between ASCII character set and Unicode character sets.

Answer 13

1. Unicode has greater range of characters than ASCII
2. Unicode represents most written languages in the world while ASCII does not
3. ASCII used for English only
4. ASCII uses 7 or 8 bits or one byte whereas Unicode uses up to 4 bytes per character

Question 14

Section II: Number Systems, Conversion, and Arithmetic

Question 15

List the first 12 Binary Weightings.

Answer 15

1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048

Question 16

Describe the procedure and give an example of converting Binary to Denary.

Answer 16

Successive addition.
Each ‘1’ in a column adds the column value (weighting) to the total.
Example: 01101011 = 64 + 32 + 8 + 2 + 1 = 107 (in Denary).

Question 17

Describe the procedure and give an example of converting Denary to Binary.

Answer 17

Successive subtraction.
By subtracting the binary weightings, largest (possible) to smallest, from the number unti we reach 0 and writing 1s in those columns.
Example: To convert 58: 58- 32-16-8-2=0, resulting in binary: 00111010. [If the number is odd, the rightmost bit is 1]

Question 18

Define Sign (for two’s complement) and Magnitude representation.

Answer 18

The left-most bit (MSB) is used to represent the sign (0= positive, 1= negative); the remaining bits represent the binary value.

Question 19

Define One’s Complement.

Answer 19

Each binary digit in a number is reversed (flipped) to allow both negative and positive numbers to be represented.

Question 20

Define Two’s Complement, and state when it’s positive/negative.

Answer 20

Two’s Complement is the one’s complement of a binary number plus 1 to the rightmost bit. It is used to represent negative numbers, and the most significant bit carries the negative of the equivalent value.

Question 21

List the 3 steps to convert a positive denary number (N) into its negative Two’s Complement equivalent (-N), using -13 as an example.

Answer 21

1. Take positive denary number (13) and convert to binary (00001101).
2. Flip each bit (One’s Complement): 11110010.
3. Add 1 to the One’s Complement.
   Result: 11110011 is -13 in denary.

Question 22

What is the easiest procedure for Binary Subtraction?

Answer 22

Convert the second number (the subtrahend) into its 2’s complement, and then add the two numbers together. [Both numbers must be in two’s complement, don’t include overflow bits in the final answer].

Question 23

Demonstrate the subtraction of 50 (00110010) from 103 (01100111) using 2’s Complement.

Answer 23

103 + (-50). 103 is 01100111.
2’s complement of 50 is 11001110.
Adding them gives 00110101 (53 in Denary).
[Both numbers must be in two’s complement, don’t include overflow bits in the final answer]

Question 24

What is Overflow in binary arithmetic?

Answer 24

It occurs when adding two large positive numbers in two’s complement which results in a number that is too large to be represented in the given number of bits. The result is erroneously represented as a negative number.

Question 25

Define Binary-Coded Decimal (BCD).

Answer 25

A number system that uses 4 bits (a nibble) to represent each denary digit. For example, 375 would be 0011 0111 0101.

Question 26

What is the main drawback of BCD?

Answer 26

It is not suitable to implement mathematical operations.

Question 27

Why is BCD used in Financial/Banking Calculations?

Answer 27

To ensure accuracy and prevent accumulating/rounding errors, because it is difficult to represent decimal values exactly in normal binary.

Question 28

Why is BCD used for Electronic Displays?

Answer 28

Because visual displays only need to show individual digits, and conversion between denary and BCD is straightforward.

Question 29

Section III: Memory Size Standards

Question 30

What is the Denary value and number of bytes for 1 Kibibyte (KiB)?

Answer 30

1024 bytes, 2^10 Bytes.

Question 31

What is the Denary value and number of bytes for 1 Mebibyte (MiB)?

Answer 31

1,048,576 bytes (1024 KiB), 2^20 Bytes.

Question 32

What is the Denary value and number of bytes for 1 Gibibyte (GiB)?

Answer 32

1,073,741,824 bytes (1024 MiB), 2^30 Bytes.

Question 33

What is the Denary value for 1 KiloBytes (KB)?

Answer 33

1000 Bytes

Question 34

What is the Denary value for 1 MegaBytes (MB)?

Answer 34

1000000 (1000 KB)

Question 35

What is the Denary value for 1 GigaBytes (GB)?

Answer 35

1000000000 (1000 MB)

Question 36

Section IV: Image and Video Representation

Question 37

Define a Bit-map image and a Pixel.

Answer 37

A Bit-map image consists of pixels arranged in a two-dimensional grid, each pixel has one colour and the colour of each pixel is stored as a binary number (colour depth). A Pixel is the smallest picture element on an image.

Question 38

A picture has been drawn and is saved as a monochrome bitmap image. State the number of pixels that are stored in one byte

Answer 38

8 Pixels

Question 39

Define Colour Depth and state the minimum requirements for colour and True Colour.

Answer 39

The number of bits dedicated per pixel to represent colours. Colour images need at least 8 bits (1 byte) per pixel for 256 colours. True Colour requires 24 bits (3 bytes) per pixel for over 16 million colours.

Question 40

What is the difference between Image Resolution and Screen Resolution?

Answer 40

Image Resolution is the total number of pixels that make up an image (e.g., 4096 × 3192). Screen Resolution refers to the horizontal and vertical pixels on a screen display, influencing how an image is shown (images may need resizing or cropping to fit screen resolutions).

Question 41

What is Pixel Density and how does it relate to image quality?

Answer 41

Pixels per square centimetre. Higher density equals a sharper image; lower density may cause pixelation.

Question 42

What is the consequence of scaling up a Bit-map image?

Answer 42

Scaling up maintains the same number of pixels but can lead to a loss of sharpness due to lower pixel density.

Question 43

What essential metadata is contained in the File Header?

Answer 43

Information about the file, such as file type, file size, and colour depth, date of creation.

Question 44

List the 4 steps for calculating the file size of a Bit-map image.

Answer 44

1. Convert the colour depth (in bits) to bytes (divide by 8). 2. Calculate the total number of pixels by multiplying Height × Width. 3. Multiply the total number of pixels by the bytes per pixel (from step 1) to get total bytes. 4. Convert total bytes to the required measurement unit (e.g., divide by 1000 for kilobytes).

Question 45

Define Vector Graphics and the Drawing List.

Answer 45

Vector Graphics are images using 2D points to mathematically describe lines, curves, and shapes, often designed using CAD software. The Drawing List contains the commands and data used for each individual drawing object that makes up the graphic image.

Question 46

List seven properties that define a Drawing Object in a vector graphic (in the drawing list).

Answer 46

1. Line colour 2. Line width 3. Fill colour 4. Shape 5. Outline style 6. Dimensions/size 7. Position (The relative position of each object also needs to be defined).

Question 47

What is the primary advantage of Vector Graphics concerning scaling?

Answer 47

Scaling up a vector graphic image results in no loss of quality because the computer redraws the shapes and commands upon zooming causing the image to remain sharp.

Question 48

What usually needs to be done before a vector graphic can be printed?

Answer 48

Vector Graphics often need to be converted to bit-map format before printing.

Question 49

Compare between vector graphics and bitmap images.

Answer 49

1. Vector graphics are composed of mathematical equations (the drawing list) so they can be stored on a text file and use up less storage, while bitmap images are made up of pixels so they have a larger file size 2. Vector graphics are not realistic as they are made out of geometric shapes, while bitmap images are made out of pixels and are realistic. [Past Exam Q&A adds:] 3. When a bitmap is enlarged the pixels get bigger and it pixelates; when a vector is enlarged it is recalculated and does not pixelate. 4. Bitmap images can be compressed with significant reduction in file size; vector graphic images do not compress well because of little redundant data.

Question 50

What is Sampling in sound conversion?

Answer 50

Amplitude (of the sound wave) measured at set regular time intervals and the value of the sample is recorded as a binary number. This is done by Analogue-to-Digital Converters (ADCs).

Question 51

Define Sampling Resolution and Sampling Rate.

Answer 51

Sampling Resolution (Bit Depth): The number of bits used to represent sound amplitude per sample, determining the accuracy of amplitude values. Sampling Rate: The number of sound samples taken per second.

Question 52

What are the sound quality/file size implications of higher sampling rate and resolution?

Answer 52

Sound quality: Higher accuracy, better sound quality. File size: result in larger file sizes, longer transmission time, and require higher processing power.

Question 53

List capabilities of Sound Editing Software.

Answer 53

1. Edit the start/stop times and duration of a sample. 2. Extract and save (or delete) part of a sample. 3. Alter the frequency or amplitude of a sample. 4. Mix and/or merge multiple sound tracks.

Question 54

List the 3 steps for calculating the file size of a sound track.

Answer 54

1. Convert the sampling resolution (in bits) to bytes (divide by 8). 2. Sample rate (Hz) × Sample resolution (bytes) × Duration (seconds). 3. Convert total bytes to the required measurement unit (e.g., divide by 1000 for kilobytes).

Question 55

Define Frame Rate in Digital Video (DV).

Answer 55

The number of video frames captured per second. Higher rates mean smoother videos.

Question 56

Section V: Data Compression Techniques

Question 57

What are the three main reasons for using file compression?

Answer 57

1. Less bandwidth required to transfer compressed file. 2. Less storage required. 3. Shorter transmission time.

Question 58

Define Lossy File Compression and its main characteristic.

Answer 58

A compression algorithm that involves permanently deleting some data. The file cannot be restored to its exact original state after decompression.

Question 59

What is the rationale for using Lossy Compression?

Answer 59

It achieves a greater decrease in storage size than lossless compression, and relies on the fact that images will contain less detail but without noticeable degradation in perceived quality.

Question 60

How does Lossy Compression work on images?

Answer 60

The colour depth can be reduced, or the resolution (number of pixels) can be reduced. This requires fewer bits per pixel. The algorithm can remove unnecessary bits of data, that wouldn't drasically affect quality. [Past Exam Q&A adds:] Specific lossy methods: 1. Reduce bit depth: reduces the number of bits per colour/pixel so each pixel has fewer bits. 2. Reduce colour palette (reduce number of colours): fewer colours mean fewer bits needed to store each colour. 3. Reduce image resolution: fewer pixels per unit measurement means less binary data to store.

Question 61

What mechanism is used for Lossy Compression in audio?

Answer 61

Removes sounds outside the human hearing range and softer sounds that are masked by louder, overlapping sounds.

Question 62

Name three file types that utilize Lossy Compression.

Answer 62

JPEG (stores images), MP3 (stores audio), and MP4 (stores video/multimedia).

Question 63

Define Lossless File Compression and its main characteristic.

Answer 63

A compression algorithm where no data is lost in the process, meaning the file is fully restored to its original configuration after decompression.

Question 64

What is the rationale for using Lossless Compression?

Answer 64

So that the decompressed text will be the same as the original, and because the file will not work properly if any details are lost (essential for text and program files).

Question 65

How does Lossless Compression work generally?

Answer 65

Repeated words/patterns of pixels/patterns of sound can be indexed and replaced with shorter numerical values; the number of consecutive occurrences is stored.

Question 66

Define Run-Length Encoding (RLE).

Answer 66

A simple form of lossless data compression algorithm. It stores runs of data (sequences where the same data value occurs consecutively) as a single data value and a count, rather than the original repeated sequence.

Question 67

What type of data is RLE effective for?

Answer 67

It reduces file size for images, particularly black and white or color images by encoding runs of identical colors, or strings/text with repeated characters.

Question 68

Give a specific example of RLE text reduction.

Answer 68

The text string "aaaaabbbbccddddd" (16 bytes) can be encoded to reduce it to 8 bytes as "a5b4c2d5"

Question 69

When would RLE increase the file size rather than decrease it?

Answer 69

When the number of repeated consecutive characters/pixles/samples are not many, so RLE stores them with 1s making the file and file size larger. Ex: "w1e1a1k1"

Question 70

Define Quantization Error in the context of sound file compression.

Answer 70

Quantization Error is the error that occurs when we use a low sample resolution when sampling a sound (decreasing the number of bits used to represent amplitude) OR the sampling rate (decreasing the samples take per second). The higher the sound resolution/sample rate the lower the Quantization Error. It may also occur when compressing a sound file.