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interpret it.","correct":true,"explanation":"Bits have no inherent meaning, so software interprets them according to a defined format, such as an integer representation, character encoding or bitmap image format."},{"text":"The hardware or processor being used to store it.","correct":false,"explanation":"Hardware stores and processes bits but does not by itself determine their meaning. The software or format defines how a particular bit pattern should be interpreted."},{"text":"The length or size of the bit pattern being stored.","correct":false,"explanation":"Bit length limits the number of possible patterns, but it does not uniquely identify what they represent. The software or format determines the pattern’s meaning."},{"text":"The storage device or memory location containing it.","correct":false,"explanation":"A storage device or memory address identifies where bits are held, not what they mean. Their interpretation is determined by the software or data format."}]},{"id":"81447975-4613-4756-84e5-5e5702362fef","cardType":"basic","points":2,"front":"Contrast analogue and digital signals.","back":"

Analogue signals vary continuously.
Digital signals use discrete values (usually binary).

","mcqOptions":[{"text":"

Analogue signals vary continuously.
Digital signals use discrete values (usually binary).

","correct":true,"explanation":"An analogue signal can take any value within a continuous range, whereas a digital signal is restricted to separate, discrete levels, most commonly representing binary 0 and 1."},{"text":"

Analogue signals use discrete values.
Digital signals vary continuously (usually smoothly).

","correct":false,"explanation":"This reverses the two definitions. Analogue signals vary continuously, while digital signals use a limited set of discrete values, usually the binary levels 0 and 1."},{"text":"

Analogue signals use binary values.
Digital signals use decimal values (usually denary).

","correct":false,"explanation":"The distinction is not between binary and decimal notation. Analogue signals vary continuously, while digital signals use discrete levels that are usually represented using binary."},{"text":"

Analogue signals vary at fixed intervals.
Digital signals use continuous values (usually voltage).

","correct":false,"explanation":"Fixed intervals describe sampling rather than analogue signals, and voltage can represent either signal type. Analogue signals vary continuously, whereas digital signals use discrete values."}]},{"id":"d8ec198f-f7bc-4026-98cf-5e10fc33039a","cardType":"basic","points":1,"front":"Why are digital signals considered more reliable for storage and copying than analogue signals?","back":"Small amounts of noise can be ignored as long as the 0 or 1 remains distinguishable.","mcqOptions":[{"text":"Small amounts of noise can be ignored as long as the 0 or 1 remains distinguishable.","correct":true,"explanation":"Digital systems classify signals into discrete states. Minor noise does not alter the stored or copied value provided each state can still be reliably recognised as 0 or 1."},{"text":"Small amounts of noise are removed because every 0 or 1 is stored perfectly.","correct":false,"explanation":"Digital signals can still acquire noise, so their physical storage is not perfect. Reliability comes from recognising the intended 0 or 1 despite small disturbances."},{"text":"Small amounts of data can be lost as long as the signal remains continuous.","correct":false,"explanation":"Losing data can change the information, and continuity is a property of analogue signals. Digital reliability comes from distinguishing discrete 0 and 1 states despite noise."},{"text":"Small amounts of noise are copied exactly so that the signal remains unchanged.","correct":false,"explanation":"Copying noise exactly would preserve errors rather than improve reliability. Digital copies can regenerate clean discrete values when the noisy states remain distinguishable as 0 or 1."}]},{"id":"e683566c-27af-4a7c-8a8f-29ea945138c1","cardType":"basic","points":1,"front":"What is the function of an Analogue-to-Digital Converter (ADC)?","back":"Converts analogue signals from sensors into digital data for a computer.","mcqOptions":[{"text":"Converts analogue signals from sensors into digital data for a computer.","correct":true,"explanation":"Sensors often produce continuously varying electrical signals. An ADC samples and quantises these signals, then encodes the resulting values as digital data a computer can process."},{"text":"Converts digital data from sensors into analogue signals for a computer.","correct":false,"explanation":"This reverses the direction of conversion and describes a DAC more closely. An ADC converts analogue sensor signals into digital data that a computer can process."},{"text":"Converts analogue signals from sensors into analogue data for a computer.","correct":false,"explanation":"Leaving the information in analogue form would not make it directly usable as digital computer data. An ADC converts the sensor’s analogue signal into digital values."},{"text":"Converts digital signals from a computer into binary data for sensors.","correct":false,"explanation":"Digital signals and binary data are already digital, so this is not analogue-to-digital conversion. An ADC takes analogue sensor signals and produces digital computer data."}]},{"id":"5dac7a6e-2351-4e14-ba0a-3b9154f35258","cardType":"basic","points":3,"front":"What are the three main stages of the ADC process?","back":"

Sampling: measuring at regular intervals.
Quantisation: rounding values to fixed levels.
Encoding: converting levels to binary.

","mcqOptions":[{"text":"

Sampling: measuring at regular intervals.
Quantisation: rounding values to fixed levels.
Encoding: converting levels to binary.

","correct":true,"explanation":"An ADC first samples the signal at regular times, quantises each measurement to an available level, and then encodes that level as a binary value."},{"text":"

Quantisation: measuring at regular intervals.
Sampling: rounding values to fixed levels.
Decoding: converting levels to binary.

","correct":false,"explanation":"This swaps sampling with quantisation and substitutes decoding for encoding. Sampling measures periodically, quantisation rounds measurements, and encoding represents the selected levels in binary."},{"text":"

Sampling: measuring at random intervals.
Quantisation: rounding values to continuous levels.
Encoding: converting binary to levels.

","correct":false,"explanation":"ADC samples are taken at regular intervals, quantisation uses fixed discrete levels, and encoding converts those levels into binary. Each stated direction or property here is reversed."},{"text":"

Encoding: measuring at regular intervals.
Decoding: rounding values to fixed levels.
Sampling: converting levels to binary.

","correct":false,"explanation":"These stage names are assigned to the wrong operations. The correct sequence is sampling the signal, quantising measurements to fixed levels, and encoding those levels in binary."}]},{"id":"ae362a34-81d7-43ea-9899-8272579c2b1a","cardType":"cloze","points":null,"front":"[ ] in an ADC is an approximation because several similar analogue values are rounded to the same digital code.","back":"Quantisation in an ADC is an approximation because several similar analogue values are rounded to the same digital code.","mcqOptions":[{"text":"Quantisation","correct":true,"explanation":"Quantisation maps a range of nearby sampled analogue measurements to one available discrete level, making it an approximation and introducing quantisation error."},{"text":"Sampling","correct":false,"explanation":"Sampling measures the signal at separate time intervals; it does not round several amplitudes to one code. Quantisation performs that rounding to fixed discrete levels."},{"text":"Encoding","correct":false,"explanation":"Encoding represents an already selected quantisation level in binary. Quantisation is the approximate stage because it rounds a range of analogue values to the same level."},{"text":"Amplification","correct":false,"explanation":"Amplification changes a signal’s magnitude rather than assigning it a digital code. Quantisation rounds similar sampled values to one of a limited number of discrete levels."}]},{"id":"cbef70ce-bfef-4d15-942f-bc9c178e5793","cardType":"basic","points":1,"front":"What is the function of a Digital-to-Analogue Converter (DAC)?","back":"Converts digital values into an analogue voltage (e.g., to drive speakers).","mcqOptions":[{"text":"Converts digital values into an analogue voltage (e.g., to drive speakers).","correct":true,"explanation":"A DAC turns discrete digital values into a continuously varying analogue electrical output, allowing digital audio data to operate analogue devices such as speakers."},{"text":"Converts analogue voltages into digital values (e.g., from sensors).","correct":false,"explanation":"This describes an ADC, which digitises analogue sensor signals. A DAC performs the opposite conversion, producing an analogue voltage from digital values."},{"text":"Converts digital values into a binary voltage (e.g., to read sensors).","correct":false,"explanation":"A DAC does not produce a binary voltage for reading sensors. It uses digital input values to generate a varying analogue voltage, for example for audio output."},{"text":"Converts analogue values into an analogue voltage (e.g., to store images).","correct":false,"explanation":"Converting one analogue form into another is not digital-to-analogue conversion. A DAC specifically accepts digital values and generates a corresponding analogue voltage."}]},{"id":"057ec077-e419-4222-a749-be31282555f8","cardType":"basic","points":1,"front":"Define a 'pixel' in the context of bitmap graphics.","back":"The smallest addressable picture element in a grid.","mcqOptions":[{"text":"The smallest addressable picture element in a grid.","correct":true,"explanation":"A bitmap is arranged as a grid of pixels, and each pixel is the smallest individual picture element whose colour value can be addressed and stored."},{"text":"The largest addressable picture element in a grid.","correct":false,"explanation":"A pixel is not a large region or collection of elements. It is the smallest individually addressable picture element within the grid making up a bitmap."},{"text":"The smallest scalable picture element in a vector.","correct":false,"explanation":"Vectors store mathematically defined shapes rather than grids of pixels. A pixel is the smallest addressable picture element in the grid of a bitmap image."},{"text":"The smallest printable picture element on a page.","correct":false,"explanation":"This confuses a pixel with a printer dot. A pixel is the smallest addressable picture element in a bitmap grid, independent of how the image is printed."}]},{"id":"2e4b39db-01ef-4c83-864d-e6ee362fa6c2","cardType":"basic","points":1,"front":"Define 'colour depth'.","back":"The number of bits stored for each pixel.","mcqOptions":[{"text":"The number of bits stored for each pixel.","correct":true,"explanation":"Colour depth specifies how many bits are allocated to encode each pixel’s colour. Increasing the number of bits increases the number of colours that can be represented."},{"text":"The number of pixels stored in the whole image.","correct":false,"explanation":"This describes the image’s pixel dimensions or resolution, not its colour depth. Colour depth is the number of bits stored for each individual pixel."},{"text":"The number of colours stored for each pixel.","correct":false,"explanation":"A pixel stores one selected colour, encoded as a bit pattern. Colour depth is the number of bits per pixel, which determines the available number of colours."},{"text":"The number of bytes stored for each pixel.","correct":false,"explanation":"Colour depth is conventionally measured in bits rather than bytes. The correct definition is the number of bits stored for each pixel."}]},{"id":"16cca766-8ce5-466c-966b-3afb8a222f4b","cardType":"basic","points":1,"front":"How many colours can be represented by a colour depth of $b$ bits?","back":"$$2^b$ different colours.","mcqOptions":[{"text":"$$2^b$ different colours.","correct":true,"explanation":"Each bit has two possible states, so $b$ independent bits produce $2^b$ distinct bit patterns. Each pattern can represent a different colour."},{"text":"$$2b$ different colours.","correct":false,"explanation":"This multiplies the colour depth by two instead of using it as an exponent. Since each additional bit doubles the possibilities, the correct number is $2^b$."},{"text":"$$b^2$ different colours.","correct":false,"explanation":"Squaring the number of bits does not count the possible bit patterns. Two choices for each of $b$ positions produce $2^b$ different colours."},{"text":"$$2^{b-1}$ different colours.","correct":false,"explanation":"This incorrectly reserves one bit, as might happen with a signed integer. Colour codes do not require a sign bit, so all $b$ bits provide $2^b$ combinations."}]},{"id":"c49ed755-03c3-414c-b706-9a2ed31a18b2","cardType":"cloze","points":null,"front":"In graphics, resolution is often measured in [ ] (dots per inch).","back":"In graphics, resolution is often measured in dpi (dots per inch).","mcqOptions":[{"text":"dpi","correct":true,"explanation":"The abbreviation dpi means dots per inch. It expresses graphics resolution by stating how many individual dots fit along one inch."},{"text":"ppi","correct":false,"explanation":"The abbreviation ppi means pixels per inch, not dots per inch. The term matching the expansion given in the sentence is dpi."},{"text":"bpp","correct":false,"explanation":"The abbreviation bpp means bits per pixel and is associated with colour depth. Resolution measured as dots per inch uses the abbreviation dpi."},{"text":"dpcm","correct":false,"explanation":"The abbreviation dpcm means dots per centimetre, so it uses a different unit of length. Dots per inch is abbreviated as dpi."}]},{"id":"146a720e-f613-46e1-9af2-97acaf882747","cardType":"basic","points":1,"front":"State the formula for calculating the raw storage requirement of a bitmap image.","back":"$$$\\text{width} \\times \\text{height} \\times \\text{colour depth}$$","mcqOptions":[{"text":"$$$\\text{width} \\times \\text{height} \\times \\text{colour depth}$$","correct":true,"explanation":"Multiplying width by height gives the total number of pixels. Multiplying that result by the colour depth gives the raw image size in bits."},{"text":"$$$\\text{width} \\times \\text{height} + \\text{colour depth}$$","correct":false,"explanation":"Adding colour depth applies it only once rather than to every pixel. The raw storage requirement is width multiplied by height multiplied by colour depth."},{"text":"$$$\\text{width} + \\text{height} \\times \\text{colour depth}$$","correct":false,"explanation":"Width and height must be multiplied to calculate the total number of pixels, not added. That pixel count is then multiplied by the colour depth."},{"text":"$$$\\text{width} \\times \\text{height} \\div \\text{colour depth}$$","correct":false,"explanation":"Dividing by colour depth incorrectly makes higher-quality images require less storage. Each pixel needs the stated number of bits, so colour depth must be multiplied."}]},{"id":"ed05a736-0dc9-46c3-9a20-da2d688115e5","cardType":"cloze","points":null,"front":"When calculating storage, 1 KiB is equal to [ ] bytes, whereas 1 kB is equal to 1000 bytes.","back":"When calculating storage, 1 KiB is equal to 1024 bytes, whereas 1 kB is equal to 1000 bytes.","mcqOptions":[{"text":"1024","correct":true,"explanation":"The binary prefix kibi represents $2^{10}$, which equals 1024. Therefore, one kibibyte contains exactly 1024 bytes."},{"text":"1000","correct":false,"explanation":"This confuses the binary unit KiB with the decimal unit kB. One kB is 1000 bytes, but one KiB is 1024 bytes."},{"text":"1023","correct":false,"explanation":"This is an off-by-one error from counting values between 0 and 1023. That range contains 1024 values, so one KiB equals 1024 bytes."},{"text":"2048","correct":false,"explanation":"This doubles the correct binary quantity and is equal to two KiB, not one. A single KiB contains $2^{10}$, or 1024, bytes."}]},{"id":"0961a508-3822-47d3-908e-f423efd7c0d0","cardType":"cloze","points":null,"front":"When calculating storage, 1 KiB is equal to 1024 bytes, whereas 1 kB is equal to [ ] bytes.","back":"When calculating storage, 1 KiB is equal to 1024 bytes, whereas 1 kB is equal to 1000 bytes.","mcqOptions":[{"text":"1000","correct":true,"explanation":"The decimal prefix kilo represents 1000, so one kB contains exactly 1000 bytes. The binary unit KiB instead contains 1024 bytes."},{"text":"1024","correct":false,"explanation":"This confuses decimal kilobytes with binary kibibytes. One KiB contains 1024 bytes, whereas one kB contains exactly 1000 bytes."},{"text":"8000","correct":false,"explanation":"This converts 1000 bytes into bits by multiplying by eight. The blank asks for bytes, so one kB is 1000 bytes."},{"text":"100","correct":false,"explanation":"This treats kilo as a factor of one hundred rather than one thousand. The decimal prefix kilo means 1000, so one kB contains 1000 bytes."}]},{"id":"d1e6e115-105f-4661-b2aa-c29f36d6b657","cardType":"basic","points":1,"front":"What is image metadata?","back":"Data about data, such as width, height, and colour depth.","mcqOptions":[{"text":"Data about data, such as width, height, and colour depth.","correct":true,"explanation":"Metadata describes the characteristics of an image rather than forming its visible content. Examples include its dimensions, colour depth, file type, and creation details."},{"text":"The main image content, such as individual pixel colour values.","correct":false,"explanation":"Individual pixel values form the image’s primary data rather than describing that data. Metadata includes descriptive properties such as width, height, and colour depth."},{"text":"Instructions for drawing, such as shapes, lines, and fill colours.","correct":false,"explanation":"These are the objects and properties used to represent a vector graphic, not metadata. Metadata is descriptive data such as an image’s dimensions and colour depth."},{"text":"A compressed copy of the image’s width, height, and pixels.","correct":false,"explanation":"Compression reduces the storage required for image data; it does not define metadata. Metadata is data describing the image, including width, height, and colour depth."}]},{"id":"31007f3d-3372-4bf1-83a5-0f44686132e2","cardType":"basic","points":1,"front":"How are vector graphics represented internally?","back":"As a list of objects (primitives) and their properties.","mcqOptions":[{"text":"As a list of objects (primitives) and their properties.","correct":true,"explanation":"Vector graphics store mathematical objects such as lines, curves, and shapes, together with properties such as coordinates, colours, fills, and line thicknesses."},{"text":"As a grid of pixels (samples) and their colour values.","correct":false,"explanation":"A grid of individually coloured pixels is the internal representation of a bitmap. Vector graphics instead store a list of graphical objects and their properties."},{"text":"As a stream of samples (readings) and their amplitudes.","correct":false,"explanation":"Samples and amplitudes describe digitised analogue signals, particularly audio, rather than vector graphics. Vectors are represented using graphical objects and their properties."},{"text":"As a single bit pattern (bitmap) and its compression ratio.","correct":false,"explanation":"A bitmap is based on stored pixel values, while compression ratio only describes size reduction. Vector graphics store a list of objects and their properties."}]},{"id":"22a431f8-26cd-4b71-a5da-e3113aa33e20","cardType":"basic","points":1,"front":"List three examples of vector primitives.","back":"Any three of: line, rectangle, circle, polygon, curve, or text.","mcqOptions":[{"text":"Any three of: line, rectangle, circle, polygon, curve, or text.","correct":true,"explanation":"Vector graphics are constructed from mathematically defined primitives, including lines, rectangles, circles, polygons, curves and text. Any three of these are valid examples."},{"text":"Any three of: pixel, resolution, colour depth, sampling, compression, or metadata.","correct":false,"explanation":"Pixels, resolution and colour depth describe bitmap graphics rather than vector primitives. Valid vector primitives include lines, rectangles, circles, polygons, curves and text."},{"text":"Any three of: JPEG, PNG, GIF, BMP, TIFF, or WebP.","correct":false,"explanation":"JPEG, PNG and GIF are graphics file formats, while BMP, TIFF and WebP are also raster formats rather than drawable vector primitives. Vector primitives include lines, circles and polygons."},{"text":"Any three of: red, green, blue, hue, saturation, or brightness.","correct":false,"explanation":"Red, green and blue are colour channels, while hue, saturation and brightness are colour properties. They are not vector primitives such as lines, rectangles or curves."}]},{"id":"c814e08c-6fab-4575-809a-907fd7905814","cardType":"basic","points":2,"front":"Explain why vector graphics are used for logos rather than bitmaps.","back":"Vectors can be scaled smoothly without pixelation.","mcqOptions":[{"text":"Vectors can be scaled smoothly without pixelation.","correct":true,"explanation":"Vector images store shapes using mathematical definitions, so their coordinates and dimensions can be recalculated at any size without revealing pixels or producing jagged edges."},{"text":"Vectors can show photorealistic detail without compression.","correct":false,"explanation":"Vectors are not necessarily more photorealistic; bitmaps usually represent photographs more effectively. Logos favour vectors because they can be scaled smoothly without pixelation."},{"text":"Vectors always have a smaller file size than bitmaps.","correct":false,"explanation":"Vector files are not guaranteed to use less storage, especially when an image contains many objects. Their main advantage for logos is smooth scaling without pixelation."},{"text":"Vectors can be edited pixel-by-pixel without distortion.","correct":false,"explanation":"Pixel-by-pixel editing is a characteristic of bitmap graphics, not the reason vectors suit logos. Vectors allow separate objects to be edited and scaled without pixelation."}]},{"id":"7e2c9ec1-ae00-4ddb-8771-1982587e2595","cardType":"basic","points":2,"front":"Why is a bitmap better than a vector for a high-quality photograph?","back":"Bitmaps can represent fine detail and continuous colour variation more realistically.","mcqOptions":[{"text":"Bitmaps can represent fine detail and continuous colour variation more realistically.","correct":true,"explanation":"A photograph contains subtle textures, shading and gradual colour changes. A bitmap records colours across a dense grid of pixels, representing these features more realistically."},{"text":"Bitmaps can provide smooth scaling and resolution-independent shapes more realistically.","correct":false,"explanation":"Smooth scaling is an advantage of vectors, not bitmaps, and does not explain photographic quality. Bitmaps are preferred because they represent fine detail and continuous colour variation realistically."},{"text":"Bitmaps can store independent objects and mathematical coordinates more realistically.","correct":false,"explanation":"Independent objects and mathematical coordinates describe vector graphics. Photographs are better represented by bitmaps because pixel grids capture fine detail and continuous colour variation."},{"text":"Bitmaps can represent geometric shapes and editable paths more realistically.","correct":false,"explanation":"Simple geometric shapes and editable paths are strengths of vector graphics rather than photographic bitmaps. Bitmaps instead reproduce fine detail and continuous colour variation more realistically."}]},{"id":"3ced30f9-32f2-4c74-a47e-6b931ea5f2fe","cardType":"basic","points":2,"front":"Compare the editing of bitmaps versus vector graphics.","back":"

Bitmaps: edited pixel-by-pixel or by region.
Vectors: individual objects can be edited independently.

","mcqOptions":[{"text":"

Bitmaps: edited pixel-by-pixel or by region.
Vectors: individual objects can be edited independently.

","correct":true,"explanation":"A bitmap consists of a grid of pixels, so editing changes individual pixels or selected regions. A vector consists of separate objects whose properties can be altered independently."},{"text":"

Bitmaps: individual objects can be edited independently.
Vectors: edited pixel-by-pixel or by region.

","correct":false,"explanation":"This reverses the two editing models. Bitmaps are edited at pixel or region level, whereas vector shapes are stored as separate objects and can be edited independently."},{"text":"

Bitmaps: edited pixel-by-pixel or by region.
Vectors: edited pixel-by-pixel or by region.

","correct":false,"explanation":"Treating both formats as pixel grids overlooks the object-based structure of vectors. Bitmaps are edited pixel-by-pixel or by region, while vector objects are edited independently."},{"text":"

Bitmaps: individual objects can be edited independently.
Vectors: individual objects can be edited independently.

","correct":false,"explanation":"Treating both formats as collections of independent objects overlooks the fixed pixel grid of a bitmap. Only vectors inherently allow individual shapes to be selected and edited independently."}]},{"id":"c2a2fd6c-10f4-43ae-8e4b-9d66d25e85f7","cardType":"basic","points":2,"front":"When might a vector graphic have a larger file size than a bitmap?","back":"When the image is highly complex with a very large number of objects.","mcqOptions":[{"text":"When the image is highly complex with a very large number of objects.","correct":true,"explanation":"Each vector object requires its mathematical properties and styling to be stored. With sufficiently many objects, this data can exceed the storage needed for a comparable bitmap."},{"text":"When the image is extremely simple with a very small number of objects.","correct":false,"explanation":"Simple vector images usually need only a few object definitions and therefore tend to have small files. A vector can become larger when it contains very many complex objects."},{"text":"When the image has very few colours with a limited range of shades.","correct":false,"explanation":"Using few colours does not itself make a vector larger; it may reduce the amount of styling data required. High complexity and numerous objects can increase vector file size."},{"text":"When the image has small dimensions with a very low output resolution.","correct":false,"explanation":"A small canvas does not necessarily produce a large vector file because vector storage primarily depends on object definitions, not pixel dimensions. Numerous complex objects can make it larger."}]}]}],"examCountdown":{"examDate":"2027-06-07","paperLabel":"Paper 1"},"heading":"Bit patterns, analogue/digital conversion and graphics","title":"Bit patterns, analogue/digital conversion and graphics Flashcards","topbar":{"backHref":"/a-level/computer-science/aqa/flashcards"},"topicSidebar":"$L39"}]}],"topicId":"719c54a4-6d70-50db-8124-b709339169bc","walled":"$L3a"}],"$L3b","$L3c"]