Table:
employment sector
1997
2017

total employed
male
female
total employed
male
female

number
%
number
%
number
%
number
%

all employment sectors
518450
399100
77
119350
23
815100
527850
64.8
287250
35.2

four-year educational institutiona
230000
172750
75.1
57250
24.9
319400
198750
62.2
120650
37.8

other educational institutionb
16850
9950
59.2
6850
40.8
29800
14400
48.3
15400
51.7

business or industry, for profitc
166650
141150
84.7
25500
15.3
296600
215900
72.8
80700
27.2

business or industry, self-employed, nonincorporatedd
25100
15900
63.4
9200
36.6
44650
24600
55.1
20000
44.9

business or industry, nonprofit
26350
17650
67
8700
33
55150
30500
55.4
24600
44.6

federal government
38050
30900
81.2
7150
18.8
51950
33600
64.6
18400
35.4

state or local government
15450
10800
69.8
4650
30.2
17550
10100
57.5
7450
42.5

Given a table image and a set of target cells, your task is to identify their positions. Represent each cell's location as JSON in the format {'value': '<cell value>', 'location': (Row_ID, Column_ID)}, with both row and column IDs begin from 1.
Refer to the values below:
(1) '10100'
(2) '230000'
(3) '8700'
(4) '6850'
(5) '9200'
(6) 'other educational institutionb'
(7) '84.7'
(8) '815100'

Represent the location as 'DOES NOT EXIST' if a cell is not present in the table. 

The target cell locations are as follows:
(1) {'value': '10100', 'location': (11, 8)}
(2) {'value': '230000', 'location': (5, 2)}
(3) {'value': '8700', 'location': (9, 5)}
(4) {'value': '6850', 'location': (6, 5)}
(5) {'value': '9200', 'location': (8, 5)}
(6) {'value': 'other educational institutionb', 'location': (6, 1)}
(7) {'value': '84.7', 'location': (7, 4)}
(8) {'value': '815100', 'location': (4, 7)}