Difference between revisions of "IS428 AY2019-20T1 Assign Sin Myeong Eun Task3"

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<b><font size = 6; color="#FFFFFF">VAST Challenge'19 MC2:Citizen Science to the Rescue</font></b>
 
<b><font size = 6; color="#FFFFFF">VAST Challenge'19 MC2:Citizen Science to the Rescue</font></b>
 
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[[IS428_AY2019-20T1_Assign_Sin_Myeong_Eun| <font color="#FFFFFF">Overview & Data preparation</font>]]
 
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| style="vertical-align:top;width:20%;" | <div style="padding: 3px; line-height: wrap_content; border-bottom:5px #3D5480; font-family:Century Gothic"> [[IS428_AY2019-20T1_Assign_Sin_Myeong_Eun_Tasks |<font color =#FFFFFF >Task 1</font>]]
 
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=== Task 3: Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern? ===
 
=== Task 3: Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern? ===
 
==== a) Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city? ====
 
==== a) Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city? ====

Revision as of 18:39, 10 October 2019

Nuclearpowerplant.jpg VAST Challenge'19 MC2:Citizen Science to the Rescue

Overview & Data preparation

Tasks

Interactive Visualisation

References

Task 3: Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern?

a) Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city?

Above75cpm.jpg

Figure 3a

  1. In order to locate the areas that were highly contaminated, we need to study the distribution of each static sensor. A new field had to be created to contain only the readings that were above 75cpm, meaning we just want to study the readings that do not only consist of the background radiation. The new field was computed using the following equation: "if(avg([Value])>75) THEN avg([Value]) END".
  2. Moving on, boxplot was chosen as a visualisation method to show the distribution of each static sensor's readings. From figure 2b, we can compare the average value of each sensor's readings to the average value of the all the sensors' readings.
  3. By manual comparison, we can see that sensors with sensor ID 1,4,6,9,11 are the sensors that detected higher average reading than the overall average reading. Sensor 15 was not chosen because its average reading was too sensitive to the outliers when most of its data points lie below the overall average reading.
  4. By comparing with the shake map that shows the region where each static sensor is located at, we can deduce that the following list of regions are the potential locations of contamination.
    • Sensor ID 1: Palace Hills
    • Sensor ID 4: DownTown
    • Sensor ID 6: SouthWest
    • Sensor ID 9: Old Town
    • Sensor ID 11: Broadview



b) Estimate how many cars may have been contaminated when coolant leaked from the Always Safe plant. Use visual analysis of radiation measurements to determine if any have left the area.



c) Indicated where you would deploy more sensors to improve radiation monitoring in the city. Would you recommend more static sensors or more mobile sensors or both? Use your visualization of radiation measurement uncertainty to justify your recommendation.