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Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : [email protected]) 1

Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : [email protected]) 1

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Page 1: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Chapter 11

Fluency with Information Technology4th edition

by Lawrence Snyder(slides by Deborah Woodall : [email protected])

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Page 2: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Its about Bits…

1 High circuit Magnetized spot bump0 Low circuit Demagnetized spot land

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Page 3: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

And Mostly Manipulating Bits…

• ASCII characters– Bit patterns assigned arbitrarily.– Bits are not manipulated.

• Numbers, colors, images, video– Bit patterns are not arbitrary.– Bits are manipulated with mathematics.

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Page 4: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Remember the Number Systems?

• Decimal number system– We know this!– base 10– 10 symbols 0 - 9– e.g. 1,375

The place values of 1, 3 7 5 are…

103 102 101 100

And it can be written in expanded form as

(1 * 103) + (3 * 102) + (7 * 101) + (5 * 100)

• Binary number system– Remember this?– base 2– 2 symbols 0 – 1– e.g. 1001Similarly the place values of 1001

are… 23 22 21 20

And it can be written in expanded form as

(1 * 23) + ( 0 * 22) + (0 * 21) + ( 1 * 20)

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Page 5: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Colors

• A color code is 3 bytes: RGB (byte 1 for Red, byte 2 for Green, byte 3 for Blue)

• 3 bytes = _________bits

• The lower the number in the byte, the lower the intensity of that color.

• The fact that a color is a group of bits means we can handle a color like a number – doing arithmetic to manipulate the color.

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Page 6: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Colors

• Black Red byte Green byte Blue byte

Binary: 0000 0000 0000 0000 0000 0000Hexadecimal: 00 00 00Decimal: 0 : 0 : 0

• WhiteBinary: 1111 1111 1111 1111 1111 1111Hexadecimal: FF FF FFDecimal: 255 : 255 : 255

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Page 7: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Colors

• RGB values where R = G = B are gray

• If we ADD the same value to each byte we get a lighter gray.

• If we SUBTRACT the same value from each byte we get a darker gray.

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Page 8: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Adding Binary Numbers

Addition Facts

0+0 0

0+1 1

1+0 1

1+1 10

11

+111

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Page 9: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Adding Binary Numbers

1 01 11 1 0 01 1 1+0 0 1 1 1 0 1 0 1 1 1 0 1 1 0 1

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Page 10: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Adding to Gray

Gray: 0011 1001 0010 1001 0010 1001 +0111 1010 +0111 1010 +0111 1010Lighter Gray: 1011 0011 1011 0011 1011 0011

Look at the Moon Photo discussion in the text.

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Page 11: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Overflow

• Overflow occurs when the computer does arithmetic and the answer will not fit where it needs to go.

• Software should handle overflow in a reasonable manner.

• Allowing sufficient bytes for the answer is a common way to handle it.

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Page 12: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

File Compression

• To compress a file means to reduce the number of bits in the file, thereby making it take up less space.

• Mathematics is used to do file compression.

• This is especially important for files downloaded over the Web, or those stored in limited space like a CD or DVD or camera memory card.

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Page 13: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Sound

• Mathematics is used to compress, clean up and change sound.

• Sound is a continuous vibration causing a pressure wave.

• The input device samples the wave at regular intervals storing a long sequence of bytes in memory.

• Sampling Rate=the number of samples taken per second

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Page 14: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Sound

Sound In• The sound wave is detected

by a microphone.• The microphone converts

the sound wave into an equivalent electrical wave.

• The electrical wave goes into an analog-to-digital converter for sampling.

• The binary samples go into RAM.

Sound Out• The binary samples come

from RAM.• They go into a digital-to-

analog converter.• The DAC creates an

electrical wave using interpolation.

• The electrical wave goes to a speaker which vibrates creating the sound wave.

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Page 15: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Sound

MP3 (MPEG level 3) compression• One of the most popular compression

techniques for music• Removes sounds we cannot hear and noise• Resulting file is about 1/10 the size of the

original• A lossy compression technique

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Page 16: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Images

An image file is a long sequence of RGB pixel data.

Mathematics is used to manipulate and compress image files.

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Page 17: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Images

JPEG compression– One of the more common compression

techniques for images– Best for photos and complex graphics– The resulting file is about 1/20 the size of the

original file– Amount can be controlled– An overall lossy compression technique

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Page 18: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Run-Length Compression

Which representation takes up less space?r1g1b1 r2g2b2 r2g2b2 r2g2b2 r2g2b2 r2g2b2 r2g2b2 r2g2b2

r2g2b2 r2g2b2 r2g2b2 r2g2b2 r2g2b2 r2g2b2 r3g3b3

Or

r1g1b1 [13 * r2g2b2] r3g3b3

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Page 19: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Images

GIF compression• Another commonly used compression technique

for images

• A lossless compression technique

• Best for icons, cartoons, and simple graphics

• Strictly uses run-length encoding.

• PNG format may eventually replace GIF

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Page 20: Chapter 11 Fluency with Information Technology 4 th edition by Lawrence Snyder (slides by Deborah Woodall : woodall@mc.edu) 1

Video

MPEG ( MPEG-2, MPEG-4 ) compression• A commonly used compression technique for

video

• Records differences between frames

• A lossy compression technique

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