Table:
KLM fleet

Aircraft

In service

Orders

Passengers[122]

Notes

C

W

Y

Total

Airbus A330-200

8

—

18

36

214

268

Airbus A330-300

5

—

30

40

222

292

Airbus A350-900

—

7

TBA

Deliveries from 2021 to 2023.
Replacing Boeing 747-400 and Boeing 747-400M aircraft.

Boeing 737-700

17

—

20

6

106

132

To be retired in 2022.[123]
To be replaced by Boeing 737-800 aircraft.

Boeing 737-800

27

4

20

6

150

176

Deliveries until 2022.

Boeing 737-900

5

—

28

18

138

184

One in SkyTeam livery.

Boeing 747-400

5

—

35

36

337

408

To be replaced by Airbus A350-900 and Boeing 787-10 aircraft.
All to be retired by 2021.

Boeing 747-400M

6

—

35

36

197

268

Boeing 777-200ER

15

—

34

40

242

316

Boeing 777-300ER

14

—

34

40

334

408

One in OrangePride livery.
One in SkyTeam livery.

Boeing 787-9

13

—

30

48

216

294

Boeing 787-10

—

8

38

36

270

344[124]

Deliveries from 2019 to 2023.
Replacing Boeing 747-400 and Boeing 747-400M aircraft.

KLM Cargo fleet

Boeing 747-400ERF

3

—

Cargo

Total

119

19

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 id begin from 1.
Refer to the values below:
1. '344',
2. '242',

For the case where a cell is not contained in the table, its location should be denoted as 'DOES NOT EXIST'. 

The target cell locations are as follows:
1. {'value': '344', 'location': (14, 7)}
2. {'value': '242', 'location': (11, 6)}