Tuesday, September 25, 2018

Tuesday, September 24, 2018 Good, Better, Best. Never let it rest. 'Til your good is better and your better is best

Quotable



                                                        
Kaplan's SAT Question of the day
                                                            
MARKETING
Explore the other car sales in the US and Foreign markets
Let's go over the test....10 min. Open and read your responses...ask if questions.

I will begin in 5 or so

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2.01 Selling

EQ Have you ever purchased anything?  Did the salesperson assist you in your purchasing decision?  

Have you ever had bad service?  Was the bad experience related to a salesperson?  Briefly explain your negative experience.

Vocab 2.01 - Sept 26


Let's talk Weaver Academy!!!

and look again at ccpi.gtcc.edu

 2.01 Selling PPT
2.01 Nature and Scope of Selling [5-21]

a. Define the term selling.

b. Identify individuals, groups, or agencies that sell.

c. Explain reasons that customers buy goods and services.
d. Identify types of items that are sold.
e. Explain where selling occurs.
f. Describe how products are sold.
g. Describe the role of selling in a market economy.
h. Explain personal characteristics of salespeople that are essential to selling.




2.01 Role of Customer Service in Selling [5-23]
a. Distinguish between customer service as a process and customer service as a function.
b. Describe how businesses can use customer service to beat their competition.
c. Discuss factors that influence customer expectations of customer service.
d. Explain how customer service facilitates sales relationships.
e. Identify pre-sales opportunities for providing customer service that can facilitate sales relationships.
f. Identify post-sales opportunities when customer service can be provided to facilitate sales relationships.
g. Discuss actions a salesperson can take to make the most of her/his customer service activities.


2.01 LAP - Go Beyond the Sale - Due Monday
2.01 Go Beyond The Sale - LAP - 4 open ended questions
http://www.quia.com/quiz/6192674.html
2.01 LAP - Sell away - Due Monday - unlimited Attempts
2.01 - Sell Away - LAP - 20 Q
http://www.quia.com/quiz/6192656.html

                                                                                                                                                    
AP COMPUTER SCIENCE PRINCIPLES
Note the reopening of the Unit 1, Chapter 1 assessment - best you look over in your spare time.
Ask me - will only open for 24 hours at a time

Check out the calendar for the Unit 1, chapter 2 assessment coming up Tuesday, Sept 25.

https://studio.code.org/s/express-2018


Any Unit 2 Reflection pieces.  One shot deal.  No redos.  

Any Unit 1 redos...must be emailed no later than Thursday Evening 8pm - murphyk2@gcsnc.com
     Must be labeled:
          Original Post
          New Post.
    

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HW - Blown to Bits - pp 309-316 (The Internet Spirit)
The layers of protocols used in network communication is an example of abstraction.
Can you give other examples of abstraction in everyday life?
When you browse to a web page, maybe with some animated advertisements embedded on it,
describe in detail what happens behind the scenes to display that page on your browser.
HW - Blown to Bits - pp 73 - 77
Discuss how not knowing some basics of how a software tool or computer works, and the abstractions they use, could lead to bad outcomes.

Both Due Tuesday, Sept 25, 5pm - email to murphyk2@gcsnc.com

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2.2 Text Compression

Difference between Heuristic and Algorithm  

Harvey and Sheila Lyrics

Harvey and Sheila Song

Objectives

Students will be able to:

-Collaborate with a peer to find a solution to a text compression problem using the
Text -Compression Widget (lossless compression scheme).
-Explain why the optimal amount of compression is impossible or “hard” to identify.
-Explain some factors that make compression challenging.
-Develop a strategy (heuristic algorithm) for compressing text.
-Describe the purpose and rationale for lossless compression.

Vocabulary

Heuristic - a problem solving approach (algorithm) to find a satisfactory solution
where finding an optimal or exact solution is impractical or impossible.
Lossless Compression - a data compression algorithm that allows the original
data to be perfectly reconstructed from the compressed data.

Agenda

Getting Started (5-7 mins)
Prompt: (From 2.2 Text Compression)
"When you send text messages to a friend, do you spell every word correctly?"
Do you use abbreviations for common words? List as many as you can.
Write some examples of things you might see in a text message that are not proper English.
Give students a minute to write, and to share with a neighbor?
"Why do you use these abbreviations? What is the benefit?"
Possible answers??

Warm up: Abbr In Ur Txt Msgs (5-7 mins)


Activity (45 mins)

Decode this Mystery Text (10-15 mins)
    What was the original text?
    Recap: How much was it compressed?
        To answer, we need to compare the number of characters in the original
poem to the number of characters needed to represent the compressed
version.

Important Note:

The compressed poem is not just this part:
-If you were to send this to someone over the Internet they would not be able to decode it.
-The full compressed text includes BOTH the compressed text and the key to solve it.
-Thus, you must account for the total number of characters in the message plus the total
number of characters in the key to see how much you've compressed it over the original.
           
Use the Text Compression Widget

Poem Hand out
-Challenge: compress your assigned poem as much as possible.
-Compare with other groups to see if you can do better.
-Try to develop a general strategy that will lead to a good compression.

Discuss properties and challenges with compression.
Prompts:
"What makes doing this compression hard?"
"Do we think that these compression amounts that we’ve found are the the
best? Is there a way to know what the best compression is?"
"But is there a process a person can follow to find the best (or a pretty good)
compression for a piece of text?"

Activity 2 (30 mins)
Develop a heuristic for doing compression
What's best?
The point here is to establish:
-There is no real way to determine for sure that you've got the best compression besides trying everything possible by brute force.
-Heuristics are techniques for at least making progress toward a "good enough" solution.
-Following the same heuristic might lead to different results.

"Do you think it’s possible to describe (or write) a specific set of instructions
that a person could follow that would always result in better text compression
than your heuristic? Why or why not?"
"Is there a way to know that a compressed piece of text is compressed the
most possible? If yes, describe how you could determine it. If no, why not?"

Wrap-up (20 mins)
Recap Questions
"What did all groups’ processes for compression have in common?"
"Will following this process always lead to the same compression? (i.e. two
people following the process for the same poem, will result in the same
compression?)"
Terminology: Verify students know or use an *exit ticket on this vocabulary:
-lossless compression v. lossy compression
-heuristic

Compression in the Real World (.zip)

    Zip Compression
-There is a compression algorithm called LZW compression upon which the common “
zip” utility is based. Zip compression does something very similar to what you did
today with the text compression widget.
-Here is an animation of lzw in action. You can see the algorithm doesn't compress
it the most, but it is following a heuristic that will lead to better and better
compression over time.
-Do you want to use zip compression for real? Most computers have it built in:
-Windows: select a file or group of files, right-click, and choose “Send To...
Compressed (zipped) Folder.”
-Mac: select a file or group of files, ctrl+click, and choose “Compress Items.”
Warning: if you try this results may vary.
-Zip works really well for text, but only on large files. If you try to compress the
simple hello.txt file we used in a previous lesson, you'll see the resulting file is
actually bigger.
-Zip is meant for text. It might not work well on non-text files very well because
they are already compressed or don’t have the same kinds of embedded
patterns that text documents do.

Assessment
Code Studio: Assessment questions are available on the Code Studio

Extended Learning
    Real World: Zip Compression
-Experiment with zip using text files with different contents. Are the results for small
files as good as for large files? (On Macs, in the Finder choose “get info” for a file to
see the actual number of bytes in the file, since the Finder display will show 4KB for
any file that’s less than that.)
-Warning: results may vary. Zip works really well for text, but it might not compress
other files very well because they are already compressed or don’t have the same
kinds of embedded patterns that text documents do.
Challenge: Research the LZW algorithm
-.zip compression is based on the LZW Compression Scheme
-While the idea behind the text compression tool is similar to LZW (zip) algorithm,
tracing the path of compression and decompression is somewhat challenging.
Learning more about LZW and what happens in the course of this algorithm would
be an excellent extension project for some individuals.


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2.3 Encoding B&W Images

Objectives

Students will be able to:

-Explain how images are encoded with pixel data.
-Describe a pixel as an element of a digital image.
-Encode a B&W image in binary representing both the pixel data (intensity) and metadata (width, height).
-Create the necessary metadata to represent the width and height of a digital image, using a computational tool.
-Explain why image width and height are metadata for a digital image.

Vocabulary

-Image - A type of data used for graphics or pictures.
-metadata - is data that describes other data. For example, a digital image my include metadata that describe the size of the image, number of colors, or resolution.
-Pixel - short for "picture element", the fundamental unit of a digital image, typically a tiny square or dot that contains a single point of color of a larger image.

Agenda

  • Getting Started (10 mins)
Back in the Internet Unit you encoded a line-drawing image as a list of numbers that made up the coordinates of the points in the image. That works for line drawings, but how might you encode a different kind of image? Today we’re going to consider how you might use bits to encode a photographic image, or if you like: how could I encode vision?
Today, we're going to start to learn about images, but we're going to start simple, with black and white images.
  • Invent An Encoding Scheme for B&W Images
Distribute Invent a B&W image encoding scheme - Activity Guide
Prompts:
  • -How have you encoded white and black portions of your image, what do 0 and 1 stand for in your encoding?
  • -Are your encodings flexible enough to accommodate images of any size? * How do they accomplish this?
  • -Is your encoding intuitive and easy to use?
  • -Is your encoding efficient?

-Vocabulary: each little dot that makes up a picture like this is called a pixel. Where did this word pixel come from? It turns out that originally the dots were referred to as "picture elements", that got shortened to "pict-el" and eventually "pixel".
-What we've discovered is that the data for our image file must contain more than just a 0 or 1 for every pixel. It must contain other data that describes the pixel data.
-This is called metatdata. In this case the metadata encodes the width and height of the image.
-We've seen forms of metadata before. For example: an internet packet. The packet contains the data that needs to be sent, but also other data like the to and from an address and packet number.

  • Activity (40 mins)
-The pixelation widget in Code Studio will allow us to play with these ideas a little more.
-This widget follows a particular encoding scheme for images that you'll have to follow.

  • Video: The Pixelation widget
Code.or Unit 2: Lesson 3: Encoding B&W Images
Task 1: Make a 3x5 letter 'A'
Task 2: Oh no! An image got messed up during transmission!
Task 3 - Create your own

  • Wrap-up (10 mins)
  • The image file protocol we used contains “metadata”: the width and height. Metadata is “data about the data” that might be required to encode or decode the bits.
  • For example, you couldn’t render the B&W image properly without somehow including the dimensions.

  • Prompts:
-What other examples of metadata have we seen in the course so far?
-What other types of data might we want to send that would require metadata?

  • Assessment
Code.org  U2L3 5 and 6

  • Extended Learning
  • Check out the "Color by Numbers" from CS Unplugged (csunplugged.org) which uses a different clever encoding scheme for B&W images.
-Do the Extension: Magnify an Image (optional) - Activity Guide activity (double the size of an image on the Pixelation Tool).
  • Have students research raster graphics in anticipation of the subsequent lesson.
  • Attempting to communicate with possible intelligent life beyond our solar system has been a dream for humans and the goal of scientists for many years. Questions about messages to send, as well as how to send messages deep into space to unknown recipients have been debated. In 1974, scientists sent the Arecibo message to the star cluster M13 some 25,000 light years away. Read about the message they sent using 1,679 binary digits (https://en.m.wikipedia.org/wiki/Arecibo_message).
-How would you change the content of the message? What would you delete and add? Why would your change be significant in a communication to other intelligent beings?
-Sketch the segment of the design you would alter. Remember, you must retain the original number of bits.
-List the details in this article that you understand more deeply because of what you have learned in this class up to this point.
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