Description
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(1 point) KML File
kml file from step 5 – with the placemarks, convex hull and nearest-neighbor line segments
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First, use one of the following websites/tools:
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Go to Google Earth → Click the menu bar on the right → Click Projects → Click Open → Select “Import KML file from computer”
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Check the following
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-0.25 each for missing locations. There should be 13 location pins.
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-0.5 for incorrect convex hull (all points/pins should be within the convex hull and a few should be on the boundary)
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-0.5 for incorrect nearest neighbor (there should be a line from one point – labeled as “home” location – to the other point. Visually verify that there isn’t be any other point that is closer from their “home” point than the one with a line)
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Note: You may need to test the file on multiple websites/tools because the nearest neighbor line may not show up properly.
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(no points, but ..) Pictures of Locations
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There should be 13 images.
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-2 points if the student submits less than 6 images
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-1 point if the student submits more than 6 but less than 10 images
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Okay to miss at most 3 images (no deduction)
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(2 points) SQL Commands
A text file(s) (.txt or .sql) with your two queries (a file for each query is okay)
Computing Convex Hull (1 point)
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-1 point if no convex hull command, but only table creation and data insertion commands. Check to see if there’s a query for computing the convex_hull (e.g., ST_CONVEXHULL for POSTGRES)
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If you are not sure about the correctness of the query, please run the query
Computing the nearest neighbor (1 point)
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-1 point if no nearest neighbor command, but only table creation and data insertion commands. Check to see if there’s query for getting a nearest neighbor (e.g., ST_Distance for POSTGRES)
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-0.5 points if their query doesn’t have some sort of ordering/sorting command in it.
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If you are not sure about the correctness of the query, please run the query.
Note:
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Okay if they hardcode points
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Okay if they create and use a table to store the 13 points and write queries for the table.
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Okay if the nearest neighbor command outputs the entire table row.
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(1 point) Screenshot and JS OpenLayers Code (CodePen/jsFiddle – okay)
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-1 point if neither is submitted
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The screenshot (0.5 points)
– 0.5 points if no screenshot of Google Earth with all 13 points in it (similar to 1) – the screenshot should show all points are on/inside the convex hull and show the nearest neighbor line.
The code (0.5 points)
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If they submit the html file, make sure that you can run the file using either: https://bytes.usc.edu/~saty/tools/xem/run.html?x=OpenLayers or https://bytes.usc.edu/~saty/tools/xem/run.html?x=OpenLayers_v2
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If they give a link to CodePen/jsFiddle, follow the link and make sure that you can run the code.
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-0.25 points for each missing point in the map. You may need to zoom out to see all the points (count them)
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-0.5 points for not using localStorage (if the points directly get plotted, without being stored and retrieved). Check to see if you can something like the following
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localStorage.setItem(xxx, thedata); //– store the data
Somevar = JSON.parse(localStorage.getItem(xxx)) //parse/retrieve the data Someothervar = somevar.points //use the data
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(1 point) Visualization and R script
-0.5 points for incorrect or missing the location screenshot (e.g. wrong output points).
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-0.5 points for incorrect or missing the R script (e.g. wrong parameters or the code doesn’t run).
Sample script and output:
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(1 point) Spirograph
-0.25 for missing or incorrect screenshot. (eg. The center for the spiral should be SGM123 as the center for on campus students. For off campus/DEN students, the center of the spirograph can be their home) Note that the spirograph should contain 8 loops.
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-0.25 for missing or incorrect source code (js, py, java, cpp, etc). (e.g. the code doesn’t run or the logic/calculation is incorrect – pay close attention to the x and y calculation equations as shown in the sample pic below).
(R = 8, r = 1, a = 4) Sample: