Chapter 1 - Information representation and multimedia (AS + A2) Flashcards
test your knowledge from IGCSE CompSci with this question:
what are the column weightings for an 8-bit binary number system?
(hint: think powers of 2)
(from heaviest to lightest) 128, 64, 32, 16, 8, 4, 2, 1
attempt converting this binary number into denary:
11010010
(hint: add up the weightings of the 1-columns from left to right)
210
(from the sum of 128, 64, 16, and 2 - they were the turned-on bits here)
attempt converting this denary number into binary:
239
(hint: try denary-subtracting 128 from this number first)
111001111
(from the difference of 239-128-64-32-8-4-2-1)
use two’s-complement on this binary number:
01010111
(hint: first invert the number and then add a 1 to the rightmost bit)
10101000 -> 10101001
(the leftmost bit = -128 so the denary equivalent of this number = -87)
add these two binary numbers without converting them into denary:
01011111
00010000
(hint: two’s complement is used here so the leftmost bit = -128)
01101111
(there’s a 1+1 in the bit equivalent to 32 so a carry should occur)
subtract these two binary numbers without converting them into denary:
01100001
00010001
(hint: two’s complement is used here so invert the second number first)
01010000
(NB: any additional bits from a binary subtraction should be ignored)
list the first 3 memory superunit names with their sizes under this:
the SI system
(hint: think powers of 10)
KB (one thousand), MB (one million), GB (one billion), etc.
(NB: the SI system’s suitable for some storage devices but is less accurate - more on the next system after this card)
list the first 3 memory superunit names with their sizes under this:
the IEC system
(hint: think powers of 2)
KiB (2 to the power of 10), MiB (2 to the power of 20), GiB (2 to the power of 30), etc.
(NB: the IEC system’s accuracy makes it best for measuring RAM sizes!)
try this question out:
what are the column weightings for a 16-bit hexadecimal system?
(hint: think powers of 16)
(from heaviest to lightest) 4096, 256, 16, 1
try this question out:
what are the six hexadecimal letters used to represent digits larger than 9?
(from smallest to largest) A, B, C, D, E, F
convert this binary number into hexadecimal:
101101010001
(hint: try splitting the number into 4-bit nibbles first)
B51
(1011 = 11/B, 0101 = 5, 0001 = 1)
convert this hexadecimal number into denary:
B1A4
(hint: convert each individual digit into binary nibbles first)
45476
(Bx16(3)=45056, 1x16(2)=256, Ax16(1)=160, 4x16(0)=4)
(NB: two’s complement isn’t used here so the MSB’s a positive number)
make a list of three things that the following can be used in:
hexadecimal numbers
- memory dumps
- HTML color codes
- error messages
try this question out:
what are the 4-bit codes used as digit representatives in BCDs (binary-coded decimals)?
(hint: use 4-bit binary register tables to help with your answer)
- 0000 (0)
- 0001 (1)
- 0010 (2)
- 0011 (3)
- 0100 (4)
- 0101 (5)
- 0110 (6)
- 0111 (7)
- 1000 (8)
- 1001 (9)
add these two fixed-point BCDs up:
0000.0101 1001
0000.0100 0110
(hint: add 0110 if you spot a result that doesn’t look like a BCD digit)
0001.0000 0101
(1111 doesn’t fit into a BCD and adding 0110 to it should carry bits)
state the operation that should be done on an ASCII code for this:
switching between uppercase and lowercase letters
(hint: standard ASCII uses 7-bit codes whereas extended uses 8-bit ones)
toggling the sixth bit to the left on/off
list the advantages of the following over ASCII tables:
the Unicode standard
(hint: Unicode uses 16/32-bit codes)
- unambiguous standardization
- more efficient to code in
- permits for private-use code assignments
try this question out:
how many bits/pixel are needed for a raster image to be:
1. a monochrome image?
2. a 256-color image?
3. a true-color image?
(hint: think powers of 2)
- a single bit for a monochrome image
- 8 bits for a 256-color image (the minimum for multicolored images)
- 24 bits/3 bytes for a true-color image w/ ~1M colors
(NB: varied intensities of red, green, and blue can create different colors in 8-bit/pixel images)
consider a major impact of the following on raster image quality:
pixel density and resolution
(hint: try scaling a JPEG/PNG image up and down yourself)
blurrier results when scaling raster images up due to pixels being spread across a larger area
consider a major impact of the following on raster image size:
resolution and bit depth
(hint: consider that image resolution and bit depth are both numbers)
the more you increase any/both of them the more space an image file takes up
(this can be proven by the file size = res * bit depth equation)
calculate the file size of an image with the following properties:
- resolution: 720p x 480p
- bit depth: 24
(hint: file size = resolution * bit depth)
(720 x 480) x 24 = 8294400 B
(≈ 8.3 MB/7.91 MiB)
list the advantages of the following over raster/bitmap images:
vector graphics
(hint: this sorta image uses geometrical calculations)
- scalable w/o any noticeable loss in quality
- space-savers due to their geometric nature
(all this makes vectors less realistic than bitmaps/rasters though)
list the steps in the process of converting the following into digital:
analog sound waves
(hint: they need to go thru an ADC first)
- removing frequencies outside the normal human hearing range of 20-20000 Hz
- imprecisely sampling sound waves w/ their amplitudes at a given rate and resolution
(NB: sampling sound waves more frequently + at higher resolutions makes the resulting digital audio file larger - more on that after this flashcard)
list all the pros and cons of doing the following with recorded sound:
more frequent sampling at higher resolutions
(hint: think back to the flashcard before this)
- pros: wider dynamic ranges, higher-quality sound, clearer audio output
- cons: larger file sizes, longer audio file transmission times, more processing power used up
(NB: the parts related to file sizes and transmission times may be resolved using compression - more on that later)
(bonus) define the following:
frame rate
(hint: this has to do with videos but isn’t in the CIE syllabus at all)
the amount of video frames recorded within a single second
compare the following methods of compression against each other:
lossless and lossy
(hint: the latter compresses further than the former)
- lossless: reversibly deconstructs extra data by indexing it for later; best suited for less-destructible applications (eg. XLS/EXE)
- lossy: irreversibly deconstructs extra data in an unnoticeable manner; best suited for more-destructible applications (eg. JPEG/MP3)
consider how the following affects sound quality:
lossy audio file formats like MP3
(hint: the loss’s less noticeable than when reducing the sampling res)
- perceptually-shaped softer sound/extrahuman range elimination (not really noticeable)
- closer audio quality to that of a normal CD at higher bit rates
consider how the following affects video quality:
lossy video file formats like MP4
(hint: again the loss’s less noticeable)
smaller video files that’re faster to transmit yet still closer to their original qualities
(this is especially important for video streaming - more on that in C2)
consider how the following affects image quality:
lossy image file formats like JPEG
(hint: ditto)
smaller image files that still look closer to the originals despite being compressed by a factor of 5-15 w/ irreversible data loss
list the processes involved in the following compression method:
RLE (run-length encoding)
(hint: think of patterns)
- reversible data deletion by indexing each repeated string into two encoded values (for text)/each repeated color into an RGB code (for images)
- flagging patterns containing more than one unit/iteration
(all this makes RLE more effective on longer runs of repeated units)
list some other methods for compressing the following:
movies and images
- cropping
- decreasing resolutions/bit depths
- reducing frame rates
