Consider the following database schema for tracking peoples whereabouts in order to find those who may have been in contact with corona virus carriers.

In each GPS coordinate pair (ns, ew), ns is longitude and ew is latitude, and both are in degrees (in unit).

For simplicity, assume that

• a visit is on a single day
• distance(ns1, ew1, ns2, ew2) returns the Euclidean distance between (ns1, ew1) and (ns2, ew2)
• (ns, ew) in city table is the geometric center of the city and the citys border is defined by radius
• a place or person's residence belongs to one city

(c) In an effort to find potential super-spreaders, find the people who have tested positive and the total number of places s/he visited during the 8 days prior to the positive test date, inclusive. List the uID, name, and phone number, and the # of visited places and order them in decreasing order of the # of visited places.

For example, if Raven tested positive on Oct-13-2020, you need to count all places she had visited from Oct-6 to Oct-13, inclusive. If Raven visited the same place multiple times, count the place only once.

person (ulD, email, name, phone, ns, ew) place (pID, name, ns, ew) visit (VID, uID, PID, to, from) city (name, state, ns, ew, radius) tested (uID, when, result) (ns, ew): GPS coordinates of person's residence (ns, ew): GPS coordinates of place to/from: datetime (e.g., 2020-04-15 16:53:30') (ns, ew): GPS coordinates of city (geometric) center when: datetime, result: 'P' (positive)or 'N' (negative) person (ulD, email, name, phone, ns, ew) place (pID, name, ns, ew) visit (VID, uID, PID, to, from) city (name, state, ns, ew, radius) tested (uID, when, result) (ns, ew): GPS coordinates of person's residence (ns, ew): GPS coordinates of place to/from: datetime (e.g., 2020-04-15 16:53:30') (ns, ew): GPS coordinates of city (geometric) center when: datetime, result: 'P' (positive)or 'N' (negative)