I
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s
ia
n J
o
urna
l o
f
E
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rica
l En
g
ineering
a
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m
pu
t
er
Science
Vo
l.
38
,
No
.
3
,
J
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2
0
2
5
,
p
p
.
200
1
~
201
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2001
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k
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with
th
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ev
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ev
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v
in
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tim
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[
1
]
.
Hu
m
an
ex
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as
b
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g
r
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h
a
s
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p
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ly
in
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a
r
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co
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p
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[
2
]
.
C
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h
a
v
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b
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g
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v
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r
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s
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[
3
]
.
T
ask
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Ad
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d
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lab
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[
4
]
,
[
5
]
.
T
h
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s
wif
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co
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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d
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J
E
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E
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g
&
C
o
m
p
Sci
,
Vo
l.
38
,
No
.
3
,
J
u
n
e
20
25
:
2
0
0
1
-
201
1
2002
s
ig
n
if
ican
t
in
f
lu
en
ce
o
n
v
ar
i
o
u
s
f
ac
ets
o
f
h
u
m
a
n
ex
is
ten
ce
.
Ar
tific
ial
i
n
tellig
en
ce
(
A
I
)
is
o
n
e
f
ield
o
f
co
m
p
u
ter
tech
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o
lo
g
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th
at
is
d
ev
elo
p
in
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q
u
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q
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ick
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y
[
6
]
.
W
ith
in
c
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p
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ter
tech
n
o
l
o
g
y
,
AI
is
a
f
ast
ex
p
an
d
i
n
g
f
ield
[
7
]
,
[
8
]
.
T
h
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ar
ea
o
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co
m
p
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cien
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m
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k
in
to
th
at
o
f
h
u
m
a
n
s
[
9
]
–
[
1
1
]
.
Ar
tific
ial
in
tellig
en
ce
tech
n
iq
u
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ar
e
u
s
ed
in
t
h
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d
ev
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m
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tech
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al
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etwo
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k
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e
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ize
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atter
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r
o
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d
at
a,
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ak
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p
r
ed
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s
[
1
2
]
,
[
1
3
]
.
AI
is
u
s
ed
in
m
an
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f
ield
s
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s
u
ch
as
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ata
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s
is
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im
ag
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s
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g
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v
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f
ac
ial
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o
g
n
itio
n
,
an
d
d
r
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er
less
v
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icles
[
1
4
]
,
[
1
5
]
.
On
e
n
atio
n
in
th
e
wo
r
ld
with
a
s
izab
le
am
o
u
n
t
o
f
lan
d
u
s
ed
f
o
r
ag
r
icu
ltu
r
e
is
I
n
d
o
n
esia.
Alth
o
u
g
h
th
er
e
ar
e
cu
r
r
en
tly
7
0
m
illi
o
n
h
ec
tar
es
o
f
ag
r
ic
u
ltu
r
al
lan
d
i
n
I
n
d
o
n
esia,
o
n
l
y
4
5
m
illi
o
n
h
ec
tar
es
o
f
th
at
lan
d
ar
e
ac
tu
ally
u
s
ab
le
f
o
r
a
g
r
icu
l
tu
r
al
p
r
o
d
u
ctio
n
,
ac
co
r
d
in
g
t
o
s
tatis
tic
s
f
r
o
m
th
e
co
u
n
tr
y
’
s
C
en
tr
al
B
u
r
ea
u
o
f
Statis
t
ics
(
B
P
S).
Du
e
to
th
e
co
n
v
er
s
i
o
n
o
f
th
ese
f
ield
s
in
t
o
n
o
n
-
ag
r
icu
ltu
r
al
p
r
o
p
e
r
ty
,
t
h
e
ex
ten
t
o
f
p
ad
d
y
f
ield
s
ten
d
s
to
d
im
in
is
h
an
n
u
ally
,
to
talin
g
b
etwe
en
5
0
,
0
0
0
an
d
7
0
,
0
0
0
h
ec
tar
es.
Pad
d
y
f
ield
s
ar
e
o
n
ly
ex
p
an
d
i
n
g
o
v
e
r
a
co
m
p
ar
ativ
ely
s
m
all
ar
ea
ea
ch
y
ea
r
-
b
et
wee
n
2
0
,
0
0
0
an
d
4
0
,
0
0
0
t
h
o
u
s
an
d
h
ec
tar
es
[
1
6
]
,
[
1
7
]
.
T
h
e
q
u
ality
o
f
th
e
s
o
il
o
n
an
ag
r
icu
ltu
r
al
p
lo
t
d
eter
m
in
es
its
f
er
tili
ty
[
1
8
]
–
[
2
0
]
.
T
h
e
lan
d
g
ets
m
o
r
e
p
r
o
d
u
ctiv
e
as
its
f
er
tili
ty
in
cr
ea
s
es.
Nu
m
er
o
u
s
v
ar
ieties
o
f
f
o
o
d
cr
o
p
s
ar
e
g
r
o
wn
i
n
I
n
d
o
n
esia.
I
m
ag
e
p
r
o
ce
s
s
in
g
is
a
th
o
r
o
u
g
h
p
r
o
c
ess
th
at
in
v
o
lv
es
in
-
d
e
p
th
v
is
u
al
an
aly
s
is
an
d
p
er
ce
p
tio
n
.
T
h
e
im
ag
e
t
h
at
h
as
b
ee
n
p
r
o
ce
s
s
ed
b
ec
o
m
es
a
d
i
g
ital
im
ag
e
th
at
is
s
to
r
e
d
in
a
co
m
p
u
ter
’
s
0
an
d
1
d
ata
f
o
r
m
at
[
2
1
]
–
[
2
3
]
.
I
n
p
u
t
d
ata
is
u
s
ed
in
th
is
p
r
o
ce
s
s
,
an
d
im
ag
es
ar
e
also
p
r
o
d
u
ce
d
as
o
u
tp
u
t d
ata.
No
n
eth
eless
,
wh
en
co
m
p
a
r
ed
to
t
h
e
o
r
ig
in
al
im
ag
e,
th
e
p
r
o
ce
s
s
ed
im
ag
e
h
as
a
s
u
p
e
r
io
r
q
u
ality
[
2
4
]
–
[
2
6
]
.
Dig
ital
im
ag
e
p
r
o
ce
s
s
in
g
is
m
o
r
e
b
r
o
ad
ly
d
e
f
in
ed
as
co
m
p
u
ter
-
ass
is
ted
two
-
d
im
en
s
io
n
al
p
i
ctu
r
e
p
r
o
ce
s
s
in
g
.
I
m
ag
e
p
r
o
c
ess
in
g
is
u
s
ed
b
y
r
esear
ch
er
s
to
ev
alu
ate
im
a
g
e
d
ata
f
o
r
a
v
ar
i
ety
o
f
s
tu
d
ies.
L
an
d
is
o
n
e
o
f
th
e
m
o
s
t
p
r
ec
i
o
u
s
n
atu
r
al
r
eso
u
r
ce
s
o
n
th
e
p
lan
et.
Fer
tile
s
o
il
p
lay
s
an
im
p
o
r
tan
t
r
o
le
in
s
u
p
p
o
r
tin
g
life
,
esp
ec
ially
in
th
e
co
n
tex
t
o
f
a
g
r
icu
ltu
r
e
an
d
n
atu
r
al
ec
o
s
y
s
tem
s
.
Fer
tile
s
o
ils
h
av
e
ch
ar
ac
ter
is
tic
ch
ar
ac
ter
is
tics
t
h
at
d
is
tin
g
u
is
h
th
em
,
s
u
c
h
as
h
ig
h
n
u
tr
ien
t
co
n
ten
t,
g
o
o
d
s
o
il
s
tr
u
ctu
r
e,
o
p
tim
a
l
m
o
is
tu
r
e
lev
els,
a
n
d
a
b
ala
n
ce
d
p
H.
T
h
e
p
r
esen
ce
o
f
ac
tiv
e
s
o
il
m
icr
o
b
es
is
also
an
i
n
d
ica
to
r
o
f
s
o
il
f
er
tili
ty
.
T
h
e
b
e
n
ef
its
o
f
f
er
tile
s
o
il
ar
e
v
er
y
v
a
r
ied
.
First
o
f
all,
f
e
r
ti
le
s
o
il
im
p
r
o
v
es
ag
r
icu
ltu
r
al
y
ield
s
,
en
s
u
r
es
th
at
cr
o
p
s
g
r
o
w
f
er
tile
a
n
d
p
r
o
d
u
c
e
q
u
ality
p
r
o
d
u
ce
.
M
o
r
eo
v
e
r
,
f
er
til
s
o
il
also
p
r
o
m
o
tes
b
io
d
iv
er
s
ity
b
y
p
r
o
v
i
d
in
g
a
g
o
o
d
h
ab
itat
f
o
r
v
ar
io
u
s
s
o
il
o
r
g
an
is
m
s
.
Fo
r
th
e
f
a
r
m
e
r
,
k
n
o
win
g
th
at
th
e
lan
d
is
f
er
tile
h
as
a
h
u
g
e
ad
v
an
tag
e.
T
h
e
y
ca
n
o
p
tim
ize
r
eso
u
r
ce
u
s
e,
r
ed
u
ce
th
e
u
s
e
o
f
f
e
r
tili
ze
r
s
an
d
p
esti
cid
es,
a
n
d
in
c
r
ea
s
e
h
ar
v
est
y
ield
s
.
I
n
ad
d
itio
n
,
awa
r
en
ess
o
f
th
e
im
p
o
r
tan
ce
o
f
p
r
eser
v
in
g
an
d
im
p
r
o
v
in
g
s
o
il
f
er
tili
ty
also
co
n
tr
ib
u
tes
t
o
ag
r
icu
ltu
r
al
s
u
s
tain
ab
i
lity
an
d
en
v
ir
o
n
m
e
n
tal
co
n
s
er
v
atio
n
.
B
y
k
ee
p
in
g
th
e
s
o
il
f
er
tile,
we
ca
n
en
s
u
r
e
th
e
av
ailab
ilit
y
o
f
s
u
s
tain
ab
le
n
atu
r
al
r
eso
u
r
ce
s
an
d
en
h
a
n
ce
life
o
n
th
is
ea
r
th
.
I
n
a
r
ec
en
t
s
tu
d
y
b
y
Alm
ei
d
a
-
Nau
ñ
ay
et
a
l.
,
[
2
7
]
s
o
il
b
ac
k
g
r
o
u
n
d
r
em
o
v
al
was
o
p
tim
ized
to
en
h
an
ce
UAV
im
a
g
er
y
-
b
ased
wh
ea
t
tr
ait
p
r
ed
ictio
n
.
B
y
e
m
p
lo
y
in
g
a
c
o
n
f
id
en
ce
s
co
r
e
,
r
em
o
te
s
en
s
in
g
was
u
tili
ze
d
to
ass
ess
g
r
ain
o
u
tp
u
t
an
d
q
u
ality
ac
r
o
s
s
th
e
g
r
o
wth
cy
cle,
aid
in
g
in
ac
h
ie
v
in
g
e
f
f
icien
t
a
n
d
s
u
s
tain
ab
le
wh
ea
t c
u
ltiv
atio
n
.
T
h
e
s
tu
d
y
p
r
o
p
o
s
es o
p
tim
al
th
r
esh
o
ld
s
b
etwe
en
0
.
1
a
n
d
0
.
3
b
ased
o
n
th
e
wh
ea
t
attr
ib
u
te
b
ein
g
e
v
alu
ated
a
n
d
t
h
e
v
e
g
etatio
n
in
d
ex
(
VI
)
.
Du
r
i
n
g
th
e
s
tem
elo
n
g
atio
n
g
r
o
wth
s
tag
e
(
GS3
2
)
,
th
e
T
VO
(
T
h
r
esh
o
ld
-
Valu
e
Op
ti
m
izatio
n
)
m
eth
o
d
d
em
o
n
s
tr
a
ted
en
h
an
c
ed
y
ield
an
d
n
itr
o
g
en
(
N)
o
u
tp
u
t
esti
m
atio
n
.
Ho
wev
er
,
th
e
T
V
O
ap
p
r
o
ac
h
r
esu
l
ted
in
m
in
i
m
al
im
p
r
o
v
em
e
n
ts
in
esti
m
atin
g
an
th
esis
p
r
o
tein
co
n
ten
t
(
GS6
5
)
.
T
h
ese
f
in
d
in
g
s
s
u
g
g
est
th
at
t
h
e
T
VO
ap
p
r
o
a
ch
ca
n
h
elp
m
itig
ate
th
e
s
o
il
e
f
f
ec
t,
h
i
g
h
lig
h
tin
g
th
e
s
ig
n
if
ican
ce
o
f
s
o
il
b
ac
k
g
r
o
u
n
d
r
ef
lecta
n
ce
in
UAV
im
ag
in
g
.
So
il
b
ac
k
g
r
o
u
n
d
r
ef
lecti
o
n
in
tr
o
d
u
ce
s
u
n
ce
r
tain
ty
i
n
p
r
ed
ictin
g
g
r
ai
n
y
ield
a
n
d
q
u
ality
b
ased
o
n
VI
s
,
u
n
d
er
s
co
r
in
g
t
h
e
im
p
o
r
ta
n
ce
o
f
ac
cu
r
ate
s
o
il
b
ac
k
g
r
o
u
n
d
r
em
o
v
al
f
o
r
r
eliab
le
UAV
-
b
ased
wh
ea
t tr
ait
ass
e
s
s
m
en
t.
I
n
a
s
tu
d
y
titl
ed
“
E
s
tim
atin
g
s
o
il
p
r
o
p
er
ties
f
r
o
m
s
m
ar
tp
h
o
n
e
im
ag
er
y
in
E
th
io
p
ia,
”
M.
J
.
Aitk
en
h
ea
d
et
a
l.
[
2
8
]
wo
r
k
e
d
.
T
h
e
aim
o
f
th
is
s
tu
d
y
was
to
in
v
esti
g
ate
th
e
v
iab
ilit
y
o
f
esti
m
atin
g
s
o
i
l
p
ar
am
eter
s
in
th
e
f
ield
u
s
in
g
a
s
m
ar
tp
h
o
n
e
-
b
as
ed
s
y
s
tem
,
th
er
eb
y
d
o
in
g
aw
ay
with
th
e
n
ec
ess
ity
o
f
co
n
v
en
tio
n
al
lab
o
r
at
o
r
y
an
aly
s
is
an
d
s
am
p
lin
g
.
Usi
n
g
an
ODK
(
Op
en
Data
Kit)
in
te
r
f
ac
e
cr
ea
ted
esp
ec
ially
f
o
r
th
e
s
tu
d
y
,
p
h
o
to
s
an
d
r
elate
d
s
ite
ch
ar
ac
ter
is
tics
wer
e
tak
en
.
I
n
o
r
d
er
to
r
elate
im
ag
e
d
ata
to
s
o
il
p
ar
am
eter
s
,
two
ty
p
es
o
f
m
o
d
els
wer
e
s
tu
d
ied
:
p
ar
tial
least
s
q
u
ar
es
(
PLS)
a
n
d
b
ac
k
p
r
o
p
a
g
atio
n
n
e
u
r
al
n
etwo
r
k
s
(
NN)
.
W
h
en
c
o
lo
u
r
an
d
s
p
atial
co
v
ar
iate
in
f
o
r
m
atio
n
wer
e
co
m
b
in
e
d
,
as
o
p
p
o
s
ed
t
o
wh
en
c
o
lo
u
r
o
r
s
p
atial
co
v
ar
iates
wer
e
u
s
ed
alo
n
e,
esti
m
atio
n
ac
cu
r
ac
y
f
o
r
ch
em
ical
c
h
ar
ac
ter
is
tics
im
p
r
o
v
ed
co
n
s
is
ten
tly
f
o
r
b
o
th
N
N
an
d
PLS
m
o
d
els.
Similar
tr
en
d
s
wer
e
s
ee
n
in
th
e
p
h
y
s
ical
ch
ar
ac
ter
is
tics
,
alth
o
u
g
h
th
e
f
in
d
in
g
s
wer
e
less
ce
r
tain
an
d
th
e
ass
es
s
m
en
t o
f
p
h
y
s
ical
p
r
o
p
er
t
ies p
er
f
o
r
m
e
d
less
well
wh
en
v
alid
ated
u
s
in
g
s
tatis
tical
m
o
d
els.
T
h
is
s
tu
d
y
aim
s
to
em
p
lo
y
two
-
d
im
en
s
io
n
al
R
GB
-
co
lo
r
ed
J
PG
d
ig
ital
s
o
il
im
ag
es
to
d
is
ce
r
n
an
d
class
if
y
s
o
il
f
er
tili
ty
.
I
t
en
c
o
m
p
ass
es
two
d
is
tin
ct
ex
tr
ac
tio
n
m
eth
o
d
s
:
f
o
r
m
ex
tr
ac
tio
n
a
n
d
tex
tu
r
e
e
x
tr
ac
tio
n
.
Fo
r
m
ex
tr
ac
tio
n
f
o
cu
s
es
o
n
d
er
iv
in
g
m
atr
ic
an
d
ec
ce
n
t
r
icity
v
alu
es,
wh
ile
te
x
tu
r
e
ex
tr
ac
tio
n
aim
s
to
d
eter
m
in
e
co
r
r
elatio
n
,
en
e
r
g
y
,
an
d
h
o
m
o
g
en
eity
o
f
s
o
il
im
ag
e
v
alu
es.
T
h
e
p
r
im
ar
y
o
b
jectiv
e
o
f
th
is
id
en
tific
atio
n
p
r
o
ce
s
s
is
to
ass
is
t
f
ar
m
er
s
in
ass
ess
in
g
th
e
f
e
r
tili
ty
s
tatu
s
o
f
th
eir
la
n
d
b
ef
o
r
e
cu
ltiv
atio
n
.
B
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
mp
r
o
ve
d
fea
tu
r
e
ex
tr
a
ctio
n
m
eth
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d
a
n
d
K
-
mea
n
s
clu
s
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n
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fo
r
s
o
il ferti
l
ity
…
(
A
g
u
n
g
R
a
ma
d
h
a
n
u
)
2003
d
o
in
g
s
o
,
f
ar
m
er
s
ca
n
en
s
u
r
e
s
u
cc
ess
f
u
l
cr
o
p
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o
wth
an
d
en
h
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b
o
th
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d
p
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o
d
u
c
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ity
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th
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m
o
r
e
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b
y
in
tr
o
d
u
cin
g
n
o
v
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s
tr
ateg
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ed
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g
m
o
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p
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eliab
le
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tco
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es,
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s
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y
en
d
ea
v
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r
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c
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r
r
en
t
s
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id
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tific
a
tio
n
m
eth
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d
o
lo
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ies.
T
h
e
f
in
d
i
n
g
s
o
f
th
is
r
esear
ch
a
r
e
ex
p
ec
t
ed
to
s
ig
n
if
ican
tl
y
b
en
ef
it
f
ar
m
er
s
in
m
ak
i
n
g
in
f
o
r
m
ed
d
ec
is
io
n
s
r
eg
ar
d
in
g
lan
d
s
elec
tio
n
f
o
r
cr
o
p
cu
ltiv
a
tio
n
.
B
y
p
r
o
v
id
in
g
v
alu
ab
le
in
s
ig
h
ts
in
t
o
s
o
il
f
er
t
ilit
y
,
th
is
s
t
u
d
y
ca
n
p
o
te
n
tially
r
ev
o
lu
tio
n
ize
a
g
r
icu
ltu
r
al
p
r
ac
tices,
lead
in
g
t
o
in
cr
ea
s
ed
ag
r
icu
ltu
r
al
o
u
tp
u
t
an
d
s
u
s
tain
ab
ilit
y
.
Ad
d
itio
n
al
ly
,
th
e
p
r
o
p
o
s
ed
s
tr
ateg
ies
co
u
ld
co
n
tr
ib
u
te
t
o
ad
v
an
ce
m
e
n
ts
in
s
o
il m
an
ag
e
m
en
t p
r
ac
tices,
th
er
e
b
y
p
r
o
m
o
tin
g
lo
n
g
-
ter
m
s
o
il h
ea
lth
a
n
d
p
r
o
d
u
ctiv
ity
.
2.
M
E
T
H
O
D
T
h
e
m
ain
o
b
jectiv
e
o
f
th
is
r
esear
ch
is
to
im
p
r
o
v
e
th
e
f
ea
tu
r
e
ex
tr
ac
tio
n
an
d
K
-
m
ea
n
s
clu
s
ter
in
g
m
eth
o
d
to
id
en
tif
y
s
o
il
f
er
tili
ty
b
ased
o
n
2
-
d
im
en
s
io
n
al
co
lo
r
s
o
il
im
ag
es.
T
o
ac
h
iev
e
th
is
g
o
al,
s
ev
er
al
s
tag
es
o
f
r
esear
ch
m
u
s
t
b
e
ca
r
r
ied
o
u
t.
T
h
e
r
esear
ch
s
tag
es
in
th
is
s
tu
d
y
ar
e
d
ep
icted
in
th
e
r
ese
ar
ch
f
r
a
m
ewo
r
k
in
Fig
u
r
e
1
.
Fig
u
r
e
1
.
R
esear
ch
f
r
am
ewo
r
k
T
h
er
e
ar
e
f
o
u
r
ca
teg
o
r
ies
o
f
s
tu
d
y
s
tag
es
in
Fig
u
r
e
1
o
f
th
e
af
o
r
esaid
r
esear
ch
f
r
am
ewo
r
k
.
T
h
e
s
y
s
tem
m
u
s
t
f
ir
s
t
r
ec
eiv
e
an
R
GB
-
co
lo
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ed
d
ig
ital
im
a
g
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o
f
th
e
g
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o
u
n
d
as
in
p
u
t.
T
h
is
is
k
n
o
wn
as
th
e
im
ag
e
in
p
u
t
s
tep
.
T
h
e
n
ex
t
p
h
ase
is
p
r
e
-
p
r
o
ce
s
s
in
g
,
wh
ic
h
co
n
s
is
ts
o
f
th
r
ee
p
r
o
ce
s
s
es.
R
GB
-
co
lo
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ed
s
o
il
p
h
o
to
s
m
u
s
t
f
ir
s
t
b
e
co
n
v
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te
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to
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ab
-
co
lo
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ed
im
ag
es,
th
e
K
-
m
ea
n
s
m
eth
o
d
m
u
s
t
th
en
b
e
u
s
ed
to
clu
s
ter
th
e
L
ab
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co
lo
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d
im
a
g
es
an
d
th
e
th
r
ee
lay
er
s
m
ed
ia
f
ilter
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to
r
ed
u
ce
n
o
is
e
f
r
o
m
im
ag
es.
T
h
e
p
r
o
ce
s
s
s
tag
e
co
m
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
38
,
No
.
3
,
J
u
n
e
20
25
:
2
0
0
1
-
201
1
2004
n
ex
t,
wh
en
th
e
im
a
g
e
is
ex
tr
ac
ted
u
s
in
g
th
e
p
r
e
-
p
r
o
ce
s
s
in
g
o
u
tco
m
es
as
a
g
u
id
e.
T
h
er
e
ar
e
th
r
ee
d
if
f
e
r
en
t
ex
tr
ac
tio
n
m
eth
o
d
s
u
s
ed
: c
h
a
r
ac
ter
izatio
n
,
tex
tu
r
e,
an
d
s
h
a
p
es.
2
.
1
.
I
ma
g
e
inp
ut:
s
o
il im
a
g
e
ry
T
h
e
in
p
u
t
im
a
g
e
d
ata
co
n
s
is
t
s
o
f
s
o
il
p
h
o
to
g
r
ap
h
y
s
to
r
ed
in
d
ig
ital
f
iles
with
th
e
*
.
jp
g
ex
ten
s
io
n
.
T
h
ese
R
G
B
tes
t
im
ag
es
ar
e
s
t
an
d
ar
d
ized
to
a
p
ix
el
s
ize
o
f
6
5
8
×
4
7
6
to
en
s
u
r
e
d
im
en
s
io
n
al
co
n
s
is
ten
cy
d
u
r
in
g
an
aly
s
is
.
T
h
e
test
d
ataset
c
o
m
p
r
is
es
twen
ty
-
fi
v
e
s
o
il
p
h
o
to
s
,
with
f
i
v
e
im
a
g
es
s
elec
ted
as
ex
am
p
les
f
o
r
th
is
r
esear
ch
.
T
h
ese
im
ag
es
s
er
v
e
as
r
ep
r
esen
tativ
e
s
am
p
les,
o
f
f
er
in
g
in
s
ig
h
ts
in
to
s
o
il
ch
ar
ac
ter
is
tics
an
d
f
ac
ilit
atin
g
co
m
p
r
e
h
en
s
iv
e
an
a
ly
s
is
o
f
s
o
il f
er
tili
ty
lev
els in
th
e
s
tu
d
y
ar
ea
.
2
.
2
.
Pr
e
-
pro
ce
s
s
ing
:
s
eg
m
ent
a
t
io
n
T
h
e
s
e
c
o
n
d
s
t
e
p
i
n
t
h
is
r
e
s
e
ar
c
h
i
n
v
o
l
v
e
s
p
r
e
-
p
r
o
c
es
s
i
n
g
,
co
m
p
r
i
s
i
n
g
t
h
r
e
e
k
e
y
p
r
o
c
e
d
u
r
e
s
.
F
i
r
s
t
l
y
,
R
GB
t
o
L
*
a*
b
c
o
n
v
e
r
s
i
o
n
e
n
h
a
n
c
e
s
c
o
l
o
r
s
p
ac
e
f
o
r
b
et
t
e
r
a
n
a
l
y
s
is
.
N
e
x
t
,
s
e
g
m
e
n
t
at
i
o
n
v
ia
K
-
m
e
a
n
s
c
l
u
s
t
e
r
i
n
g
i
d
e
n
t
i
f
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es
d
i
s
t
i
n
c
t
r
e
g
i
o
n
s
o
f
i
n
t
e
r
e
s
t
.
F
i
n
a
ll
y
,
a
t
h
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e
e
-
l
a
y
e
r
m
e
d
i
a
n
f
i
l
t
e
r
r
e
d
u
c
es
n
o
i
s
e
w
h
i
le
p
r
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s
e
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v
i
n
g
i
m
a
g
e
d
e
t
a
i
ls
.
E
a
c
h
p
r
o
c
e
s
s
p
l
a
y
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a
v
i
t
a
l
r
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l
e
i
n
r
e
f
i
n
i
n
g
i
m
a
g
e
d
a
t
a
.
R
GB
t
o
L
*
a*
b
c
o
n
v
e
r
s
io
n
o
p
t
i
m
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z
e
s
c
o
l
o
r
r
e
p
r
e
s
e
n
t
a
ti
o
n
,
K
-
m
e
a
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s
s
e
g
m
e
n
t
a
t
i
o
n
i
d
e
n
ti
f
i
es
r
e
l
e
v
a
n
t
a
r
ea
s
,
a
n
d
t
h
e
m
e
d
i
a
n
f
i
lt
e
r
e
n
h
an
c
e
s
i
m
a
g
e
c
l
a
r
it
y
.
T
h
i
s
s
t
e
p
is
c
r
u
c
i
al
f
o
r
p
r
e
p
a
r
i
n
g
i
m
a
g
e
s
f
o
r
s
u
b
s
e
q
u
e
n
t
a
n
a
l
y
s
i
s
,
e
n
s
u
r
i
n
g
a
c
c
u
r
a
t
e
a
n
d
r
e
li
a
b
l
e
r
e
s
u
lt
s
.
2
.
2
.
1
.
Co
nv
er
t
RG
B
t
o
L
*
a
*
b
T
h
e
n
e
x
t
s
t
e
p
is
t
o
c
o
n
v
e
r
t
t
h
e
R
GB
-
c
o
l
o
r
e
d
s
o
i
l
i
m
a
g
e
i
n
t
o
L
*
a*
b
c
o
l
o
u
r
a
f
t
e
r
i
t
h
as
b
e
e
n
s
u
c
c
e
s
s
f
u
l
ly
e
n
t
e
r
e
d
i
n
t
o
t
h
e
s
y
s
t
e
m
[
2
9
]
,
[
3
0
]
.
I
n
c
o
l
o
u
r
s
c
i
e
n
c
e
,
p
h
o
t
o
g
r
a
p
h
y
,
a
n
d
g
r
a
p
h
i
c
d
e
s
i
g
n
,
c
o
l
o
u
r
s
p
a
c
e
s
o
r
c
o
l
o
u
r
m
o
d
e
l
s
a
r
e
d
es
c
r
i
b
e
d
u
s
i
n
g
t
h
e
L
*
a*
b
c
o
l
o
u
r
s
y
s
te
m
.
T
h
r
e
e
el
e
m
e
n
t
s
c
o
m
b
i
n
e
t
o
f
o
r
m
c
o
l
o
u
r
a
c
c
o
r
d
i
n
g
t
o
t
h
e
L
*
a*
b
c
o
l
o
u
r
s
y
s
t
e
m
:
b
r
i
g
h
t
n
e
s
s
(
L
*
)
,
r
e
d
-
g
r
e
e
n
t
o
n
e
s
(
a
*
)
,
a
n
d
y
e
l
l
o
w
-
b
l
u
e
t
o
n
e
s
(
b
*
)
.
T
h
e
p
u
r
p
o
s
e
o
f
t
h
i
s
c
o
n
v
e
r
s
i
o
n
is
t
o
m
a
k
e
t
h
e
s
e
g
m
e
n
t
a
t
i
o
n
p
r
o
c
es
s
-
w
h
i
c
h
c
o
m
es
n
e
x
t
-
e
as
i
e
r
.
S
e
g
m
e
n
ta
t
i
o
n
i
s
u
s
e
d
i
n
t
h
i
s
s
t
u
d
y
t
o
t
r
y
a
n
d
i
s
o
l
a
te
e
a
c
h
c
o
l
o
u
r
c
o
n
s
t
it
u
e
n
t
,
w
it
h
a
f
o
c
u
s
o
n
r
e
d
-
g
r
e
e
n
t
o
n
e
s
i
n
p
a
r
ti
c
u
l
a
r
.
2
.
2
.
2
.
T
hree
-
la
y
er
m
edia
n f
il
t
er
On
e
ty
p
e
o
f
im
ag
e
p
r
o
ce
s
s
in
g
m
eth
o
d
u
s
ed
to
lo
we
r
n
o
i
s
e
in
d
ig
ital
p
h
o
to
s
is
th
e
th
r
ee
lay
er
s
m
ed
ian
f
ilter
.
I
t
is
an
ex
p
an
s
io
n
o
f
th
e
co
n
v
en
tio
n
al
m
e
d
ian
f
ilter
,
wh
ich
s
u
b
s
titu
tes
th
e
m
ed
ian
v
alu
e
o
f
ea
c
h
p
ix
el
f
o
r
th
e
v
al
u
e
o
f
th
e
p
ix
e
l
n
ex
t
to
it.
W
h
ile
it
tak
es
in
t
o
ac
co
u
n
t
m
o
r
e
th
an
o
n
e
lay
e
r
o
r
ch
an
n
el
in
th
e
im
ag
e,
th
e
th
r
ee
lay
er
s
m
ed
i
an
f
ilter
f
u
n
ctio
n
s
s
im
ilar
ly
t
o
th
e
co
n
v
en
tio
n
al
m
ed
ia
n
f
i
lter
.
Ma
n
y
d
ig
ital
p
h
o
to
s
,
p
a
r
ticu
lar
ly
c
o
lo
r
o
r
m
u
lti
-
ch
an
n
el
im
a
g
es
(
lik
e
R
GB
im
ag
es),
co
n
tain
v
alu
es
f
o
r
ea
ch
p
ix
el
th
a
t
in
d
icate
co
lo
r
o
r
in
ten
s
ity
in
v
ar
io
u
s
ch
an
n
els (
s
u
ch
r
ed
,
g
r
e
en
,
an
d
b
lu
e)
.
2
.
2
.
3
.
Seg
m
ent
a
t
io
n:
K
-
m
ea
ns
clu
s
t
er
ing
m
et
ho
d
Seg
m
en
tatio
n
,
s
o
m
etim
es
r
e
f
er
r
ed
to
as
clu
s
ter
in
g
,
c
o
m
e
s
n
ex
t
af
ter
t
h
e
R
GB
to
L
ab
co
lo
u
r
co
n
v
er
s
io
n
o
f
an
im
a
g
e
is
f
i
n
is
h
ed
.
T
h
e
K
-
m
ea
n
s
a
p
p
r
o
a
ch
is
u
s
ed
in
th
is
s
tu
d
y
to
cl
u
s
ter
d
ata.
T
o
m
ak
e
f
u
r
th
er
a
n
aly
s
is
ea
s
ier
,
th
e
p
r
im
ar
y
g
o
al
o
f
clu
s
ter
in
g
is
to
g
r
o
u
p
item
s
th
at
h
av
e
b
ee
n
r
ec
o
g
n
is
ed
in
a
p
ictu
r
e
with
th
e
im
ag
e
’
s
b
ac
k
g
r
o
u
n
d
.
T
h
e
K
-
m
ea
n
s
m
eth
o
d
’
s
s
tep
s
ar
e
lis
ted
b
elo
w
[
3
1
]
,
[
3
2
]
.
−
I
n
itializatio
n
:
t
h
e
f
ir
s
t
s
tep
is
to
f
ig
u
r
e
o
u
t
h
o
w
m
an
y
clu
s
ter
s
y
o
u
wan
t,
‘
k.
’
C
h
o
o
s
e
k
s
ites
at
r
an
d
o
m
to
b
e
th
e
s
tar
tin
g
ce
n
tr
o
id
s
.
T
h
es
e
ce
n
tr
o
id
s
m
ay
b
e
s
elec
ted
b
y
a
p
r
ed
eter
m
in
e
d
in
itializatio
n
p
r
o
ce
d
u
r
e
o
r
at
r
an
d
o
m
[
3
3
]
.
−
Step
two
(
d
is
tan
ce
ca
lcu
latio
n
)
:
d
eter
m
i
n
e
th
e
s
ep
ar
atio
n
b
e
twee
n
ev
er
y
d
ata
p
o
in
t
a
n
d
ev
er
y
ce
n
tr
o
id
b
y
u
s
in
g
a
ce
r
tain
d
is
tan
ce
m
etr
ic,
s
u
ch
as
th
e
Ma
n
h
attan
d
is
tan
ce
o
r
th
e
E
u
clid
ea
n
d
is
tan
ce
.
Nex
t,
p
lace
ev
er
y
d
ata
p
o
in
t in
th
e
clu
s
ter
th
at
h
as th
e
clo
s
est ce
n
tr
o
id
.
−
T
h
ir
d
p
h
ase
(
ce
n
tr
o
id
u
p
d
ate
)
:
d
eter
m
in
e
th
e
m
ea
n
o
f
e
v
er
y
d
ata
p
o
in
t
in
ev
er
y
clu
s
ter
.
As
th
e
n
ew
ce
n
tr
o
id
f
o
r
th
at
p
ar
ticu
lar
clu
s
ter
,
s
et
th
e
av
er
ag
e
v
al
u
e.
−
Fo
u
r
th
s
tep
(
r
ep
ea
t
s
tep
s
2
an
d
3
)
:
r
ep
ea
t
s
tep
s
2
an
d
3
u
n
til
co
n
v
er
g
e
n
ce
is
r
ea
ch
ed
,
w
h
ich
o
cc
u
r
s
wh
en
th
e
d
ata
p
o
in
t
d
is
tr
ib
u
tio
n
t
o
clu
s
ter
s
r
em
ain
s
co
n
s
tan
t
o
r
wh
en
th
e
ch
a
n
g
e
i
n
ce
n
tr
o
id
s
b
ec
o
m
es
v
er
y
m
in
im
al.
−
Fifth
s
tep
(
o
u
tp
u
t)
:
th
e
K
-
m
ea
n
s
alg
o
r
ith
m
’
s
f
in
al
r
esu
lt
will
b
e
t
h
e
clu
s
ter
s
th
at
ar
e
p
r
o
d
u
ce
d
af
ter
co
n
v
er
g
en
ce
.
B
ased
o
n
h
o
w
c
lo
s
e
a
d
ata
p
o
in
t
is
t
o
th
e
clo
s
est
ce
n
tr
o
id
,
ea
ch
d
ata
p
o
i
n
t
will
b
e
allo
ca
ted
to
a
clu
s
ter
.
2
.
4
.
P
r
o
ce
s
s
ing
:
ex
t
ra
ct
i
o
n
Fo
llo
win
g
s
u
cc
ess
f
u
l
co
m
p
leti
o
n
o
f
th
e
K
-
m
ea
n
s
clu
s
ter
in
g
p
h
ase,
im
ag
e
e
x
tr
ac
tio
n
is
in
it
iated
.
T
h
is
p
r
o
ce
s
s
en
tails
is
o
latin
g
v
ital
co
m
p
o
n
en
ts
f
r
o
m
th
e
s
tu
d
ied
im
ag
e,
en
co
m
p
ass
in
g
co
lo
r
,
f
ea
tu
r
es,
an
d
s
h
a
p
e.
T
h
r
ee
d
is
tin
ct
ex
tr
ac
tio
n
tech
n
iq
u
es
ar
e
em
p
lo
y
ed
:
s
h
ap
e,
tex
tu
r
al,
an
d
f
ea
tu
r
e
ex
t
r
ac
tio
n
.
E
ac
h
m
eth
o
d
is
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
mp
r
o
ve
d
fea
tu
r
e
ex
tr
a
ctio
n
m
eth
o
d
a
n
d
K
-
mea
n
s
clu
s
teri
n
g
fo
r
s
o
il ferti
l
ity
…
(
A
g
u
n
g
R
a
ma
d
h
a
n
u
)
2005
m
eticu
lo
u
s
ly
ex
p
lain
ed
to
el
u
cid
ate
th
eir
r
o
les
in
th
is
in
v
esti
g
atio
n
.
Sh
ap
e
ex
tr
ac
t
io
n
i
d
en
tifie
s
g
eo
m
etr
ic
p
r
o
p
er
ties
,
tex
tu
r
al
ex
tr
ac
tio
n
d
is
ce
r
n
s
s
u
r
f
ac
e
ch
ar
ac
ter
is
tics
,
an
d
f
ea
tu
r
e
ex
tr
ac
tio
n
q
u
an
tifie
s
im
ag
e
attr
ib
u
tes.
T
h
ese
tec
h
n
iq
u
es
co
llectiv
ely
co
n
tr
ib
u
te
to
c
o
m
p
r
eh
en
s
iv
e
im
ag
e
an
aly
s
is
,
f
ac
ilit
atin
g
d
ee
p
er
in
s
ig
h
ts
in
to
th
e
u
n
d
er
ly
in
g
p
r
o
p
er
ties
an
d
p
atter
n
s
p
r
esen
t
with
in
th
e
im
ag
es
u
n
d
er
s
cr
u
tin
y
.
T
h
e
b
asic
p
u
r
p
o
s
e
o
f
d
i
g
ital
im
ag
e
f
ea
t
u
r
e
ex
tr
ac
tio
n
is
to
r
ed
u
ce
co
m
p
licated
im
ag
e
r
e
p
r
esen
tatio
n
s
in
to
s
im
p
ler
an
d
m
o
r
e
i
n
tellig
ib
le
f
o
r
m
s
.
I
n
th
i
s
s
tu
d
y
,
s
ix
ty
p
es
o
f
f
ea
tu
r
e
e
x
tr
ac
tio
n
a
r
e
a
p
p
lied
to
s
o
il
p
h
o
to
g
r
a
p
h
s
,
n
am
ely
m
etr
ic,
ec
ce
n
tr
icity
,
c
o
n
tr
ast,
co
r
r
elatio
n
,
en
er
g
y
,
an
d
h
o
m
o
g
en
eity
.
T
o
ca
lc
u
late
th
e
v
alu
e
o
f
f
ea
tu
r
es
ex
tr
ac
tio
n
we
u
s
e
th
e
(
1
)
-
(
6
).
=
(
1
)
=
√
1
−
2
2
)
(
2
)
=
∑
∑
(
,
)
(
−
)
2
−
1
=
0
−
1
=
0
(
3
)
=
∑
∑
(
(
−
)
(
−
)
)
−
1
=
0
−
1
=
0
(
4
)
=
∑
∑
(
,
)
2
−
1
=
0
−
1
=
0
(
5
)
=
∑
∑
(
,
)
1
+
|
−
|
−
1
=
0
−
1
=
0
(
6
)
W
h
er
e:
a
r
ea
is
th
e
n
u
m
b
er
o
f
p
ix
els in
an
o
b
ject,
C
o
n
v
ex
a
r
ea
is
th
e
n
u
m
b
er
o
f
p
ix
els in
th
e
co
n
v
ex
h
u
ll o
f
an
o
b
ject,
is
th
e
s
em
i
-
m
ajo
r
(
lo
n
g
)
a
x
is
,
is
th
e
s
em
i
-
m
in
o
r
(
s
h
o
r
t)
ax
is
,
(
,
)
is
th
e
v
alu
e
in
th
e
co
-
o
cc
u
r
r
e
n
ce
m
atr
ix
at
p
o
s
itio
n
(
,
)
,
is
th
e
n
u
m
b
er
o
f
in
ten
s
ity
lev
els
in
th
e
im
ag
e,
an
d
is
th
e
av
er
ag
e
in
ten
s
ity
v
alu
e
f
o
r
r
o
w
an
d
c
o
lo
u
m
n
,
,
an
d
is
th
e
s
tan
d
ar
d
d
ev
iatio
n
o
f
th
e
in
ten
s
ity
f
o
r
r
o
w
an
d
co
lo
u
m
n
,
b
elo
w
is
Alg
o
r
ith
m
1
th
at
we
u
s
e
to
ex
t
r
ac
t c
h
ar
ac
ter
is
tics
,
tex
tu
r
es a
n
d
s
h
ap
es.
Alg
o
r
ith
m
1
.
e
x
tr
ac
tio
n
b
ased
o
n
ch
ar
ac
te
r
is
tics
,
tex
tu
r
e
an
d
s
h
ap
es
Input:
digital image (input_image
)
Output:
characteristics, textures, shapes
Initialization:
Initialize image as input_image
Initialize characteristics as empty list
Initialize textures as empty list
Initialize shapes as empty list
characteristics.append(color_histogram)
characteristics.append(edge_features)
textures.append(GLCM_features)
textures.append(LBP_features)
shapes.append(contours)
shapes.append(hough_lines)
shapes.append(hough_circles)
2
.
5
.
Resul
t
identif
ica
t
io
n
:
K
-
m
ea
ns
clus
t
er
ing
T
h
is
r
esear
ch
aim
s
to
d
is
ce
r
n
s
o
il
f
er
tili
ty
le
v
els
th
r
o
u
g
h
im
ag
e
a
n
aly
s
is
.
Utilizin
g
th
e
K
-
m
ea
n
s
clu
s
ter
in
g
m
eth
o
d
,
s
o
il
im
a
g
es
ar
e
ca
teg
o
r
ized
i
n
to
t
wo
g
r
o
u
p
s
:
f
er
tile
a
n
d
n
o
n
-
f
er
tile
s
o
ils
.
T
h
is
class
if
icatio
n
s
y
s
tem
p
r
o
v
id
es
in
s
ig
h
ts
in
to
s
o
il
q
u
ality
,
aid
in
g
in
a
g
r
icu
ltu
r
al
an
d
en
v
ir
o
n
m
en
tal
ass
ess
m
en
ts
.
B
y
ac
cu
r
ately
id
en
tify
in
g
f
er
ti
le
an
d
in
f
er
tile
s
o
il
r
eg
io
n
s
,
th
is
s
tu
d
y
co
n
tr
ib
u
tes
to
in
f
o
r
m
ed
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
es
r
eg
ar
d
in
g
lan
d
u
s
e
,
cr
o
p
s
elec
tio
n
,
an
d
s
o
il
m
an
ag
e
m
en
t
p
r
ac
tices.
T
h
e
r
esu
lts
o
f
f
er
v
alu
ab
le
in
f
o
r
m
atio
n
f
o
r
en
h
a
n
cin
g
a
g
r
icu
ltu
r
al
p
r
o
d
u
ctiv
ity
,
s
u
s
tain
a
b
ilit
y
,
an
d
e
n
v
ir
o
n
m
en
tal
co
n
s
er
v
atio
n
ef
f
o
r
ts
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
i
s
r
es
e
a
r
c
h
c
u
l
m
i
n
at
e
s
i
n
id
e
n
t
i
f
y
i
n
g
s
o
il
f
e
r
ti
l
it
y
l
e
v
el
s
w
i
t
h
i
n
l
a
n
d
i
m
a
g
e
s
.
T
h
r
o
u
g
h
s
u
c
c
es
s
i
v
e
s
t
a
g
es
o
f
a
n
a
l
y
s
i
s
,
t
h
e
d
e
s
i
r
e
d
o
u
t
c
o
m
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m
e
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t
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g
r
i
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l
t
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v
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t
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n
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a
l
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li
t
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
38
,
No
.
3
,
J
u
n
e
20
25
:
2
0
0
1
-
201
1
2006
3
.
1
.
I
ma
g
e
inp
ut:
s
o
il im
a
g
e
ry
T
h
e
test
s
et
co
m
p
r
is
es
t
wen
ty
-
f
iv
e
s
o
il
p
h
o
t
o
s
,
all
s
o
u
r
ce
d
f
r
o
m
lan
d
in
So
lo
k
R
eg
en
cy
,
W
est
Su
m
atr
a
p
r
o
v
in
ce
,
d
ed
icate
d
t
o
f
o
o
d
cr
o
p
c
u
ltiv
atio
n
.
T
o
ill
u
s
tr
ate
th
e
s
o
il
s
am
p
les,
f
iv
e
p
h
o
to
s
ar
e
p
r
esen
ted
as
s
am
p
le
im
ag
es.
T
ab
le
1
p
r
o
v
id
es
an
ex
am
p
le
o
f
a
s
o
il
p
ictu
r
e
f
r
o
m
th
e
s
tu
d
y
.
T
h
ese
im
ag
es
r
ep
r
esen
t
th
e
d
iv
er
s
e
s
o
il
co
n
d
itio
n
s
en
co
u
n
ter
ed
in
th
e
ag
r
icu
ltu
r
al
lan
d
s
ca
p
e
o
f
th
e
r
eg
io
n
,
s
er
v
in
g
a
s
es
s
en
tial
d
ata
f
o
r
th
e
r
e
s
ea
r
ch
’
s
s
o
il f
er
tili
ty
an
a
ly
s
is
.
T
ab
le
1
.
So
il
im
ag
e
r
y
in
p
u
t
S
o
i
l
i
m
a
g
e
r
y
i
n
p
u
t
S
o
i
l
i
m
a
g
e
r
y
1
S
o
i
l
i
m
a
g
e
r
y
2
S
o
i
l
i
m
a
g
e
r
y
3
S
o
i
l
i
m
a
g
e
r
y
4
S
o
i
l
i
m
a
g
e
r
y
5
I
t
is
ev
id
en
t
f
r
o
m
th
e
f
iv
e
s
am
p
le
in
p
u
t
p
h
o
to
s
o
f
th
e
ab
o
v
e
s
o
il
im
ag
e
th
at
ea
ch
o
f
th
e
f
iv
e
s
o
il
p
h
o
to
g
r
ap
h
s
is
u
n
iq
u
e.
Ph
o
to
g
r
ap
h
s
o
f
s
m
o
o
t
h
s
o
il
with
f
ew
r
o
ck
s
,
p
h
o
to
g
r
ap
h
s
o
f
s
lig
h
tly
co
ar
s
e
s
o
il
with
s
lig
h
tly
m
o
r
e
r
o
ck
s
t
h
an
f
i
n
e
s
o
il,
an
d
im
a
g
es
o
f
c
o
ar
s
e
s
o
i
l
with
m
o
r
e
r
o
ck
s
t
h
an
f
in
e
s
o
il
ar
e
all
av
aila
b
le.
T
h
e
p
lan
ts
th
at
ar
e
ap
p
r
o
p
r
iat
e
f
o
r
p
lan
tin
g
also
d
if
f
er
d
u
e
to
th
ese
v
ar
io
u
s
s
itu
atio
n
s
.
T
h
u
s
,
co
n
d
u
ctin
g
th
is
r
esear
ch
is
ess
en
tial.
Pre
-
p
r
o
c
ess
in
g
will in
v
o
lv
e
an
an
al
y
s
is
o
f
th
e
f
iv
e
s
o
il p
h
o
to
g
r
a
p
h
s
.
3
.
2
.
P
re
-
pro
ce
s
s
ing
a)
C
o
n
v
er
t
R
GB
to
L
*
a*
b
:
i
n
t
h
is
s
tu
d
y
,
th
e
in
itial
p
r
e
-
p
r
o
ce
s
s
in
g
s
tep
is
ch
a
n
g
in
g
R
GB
s
o
il
p
ictu
r
es
t
o
L
*
a*
b
co
lo
r
s
.
T
h
e
ab
ilit
y
to
c
o
r
r
ec
tly
s
ep
ar
ate
th
e
s
o
il
im
ag
e
’
s
co
lo
r
in
to
R
ed
an
d
Gr
ee
n
in
d
icate
s
th
at
th
is
p
r
e
-
p
r
o
ce
s
s
in
g
was c
o
m
p
l
eted
.
T
h
e
R
GB
s
o
u
r
ce
im
ag
e
a
n
d
th
e
tr
an
s
f
o
r
m
ed
L
*
a*
b
im
a
g
e
ar
e
s
h
o
wn
in
T
ab
le
2
.
I
t
is
ev
id
en
t
f
r
o
m
th
e
im
ag
e
in
T
a
b
le
2
th
at
an
R
GB
co
lo
r
in
p
u
t
im
ag
e
m
ay
b
e
co
r
r
ec
tl
y
tr
an
s
f
o
r
m
ed
t
o
a
L
*
a*
b
c
o
lo
r
i
m
ag
e.
T
h
e
im
a
g
e
’
s
r
ed
-
g
r
ee
n
h
u
es
ar
e
th
e
co
l
o
r
s
th
at
ar
e
s
e
p
ar
ated
in
th
is
in
v
esti
g
atio
n
.
b)
C
lu
s
ter
in
g
u
s
in
g
t
h
e
K
-
m
ea
n
s
m
eth
o
d
.
C
lu
s
ter
in
g
b
etwe
en
th
e
id
en
tifie
d
o
b
jects
in
th
e
g
r
o
u
n
d
im
a
g
e
an
d
th
e
im
ag
e
b
ac
k
g
r
o
u
n
d
is
th
e
s
ec
o
n
d
p
r
e
-
p
r
o
ce
s
s
in
g
s
tep
.
K
-
m
ea
n
s
clu
s
ter
in
g
is
u
s
ed
in
t
h
is
p
r
e
-
p
r
o
ce
s
s
in
g
s
eg
m
en
tatio
n
.
T
h
e
R
G
B
s
o
il
im
ag
es
th
at
h
av
e
b
ee
n
tr
an
s
f
o
r
m
ed
to
L
*
a*
b
ca
n
b
e
co
r
r
ec
tl
y
s
o
r
ted
in
to
r
o
ck
y
item
s
an
d
f
i
n
e
s
o
ils
f
o
llo
win
g
th
e
p
r
e
-
p
r
o
ce
s
s
in
g
s
eg
m
en
tatio
n
u
s
ed
in
th
is
s
tu
d
y
.
T
h
e
R
GB
in
p
u
t
im
ag
e
,
th
e
c
o
n
v
er
ted
im
ag
e
to
L
*
a*
b
co
lo
r
,
a
n
d
th
e
K
-
m
ea
n
s
m
eth
o
d
-
g
en
e
r
ated
clu
s
t
er
in
g
ar
e
s
h
o
wn
in
T
a
b
le
2
.
c)
T
h
r
ee
-
lay
er
m
ed
ia
n
f
ilter
.
T
h
r
ee
-
lay
er
cl
u
s
ter
in
g
is
th
e
p
r
o
ce
s
s
o
f
r
ed
u
cin
g
n
o
is
e
f
r
o
m
t
h
e
im
ag
e
th
at
h
as
clu
s
ter
in
g
f
r
o
m
th
e
p
r
ec
e
d
in
g
s
tep
.
T
h
r
ee
lay
e
r
s
o
f
clu
s
ter
in
g
g
iv
e
th
r
ee
r
ec
o
m
m
en
d
atio
n
im
ag
es
th
a
t
h
av
e
b
ee
n
r
ed
u
ce
d
t
o
th
e
n
ex
t
p
r
o
ce
s
s
in
g
s
tep
.
T
h
e
r
esu
lt
is
o
n
e
o
f
t
h
e
b
est
n
o
is
e
r
e
d
u
ctio
n
s
f
r
o
m
th
e
th
r
ee
r
ec
o
m
m
en
d
ed
im
ag
e
s
.
T
h
e
th
r
ee
-
lay
e
r
m
ed
ian
f
ilt
er
ca
n
b
e
s
h
o
wn
in
T
a
b
le
2
.
T
ab
le
2
.
Pre
-
p
r
o
ce
s
s
in
g
r
esu
lt
No
S
o
i
l
i
m
a
g
e
r
y
i
n
p
u
t
C
o
n
v
e
r
t
R
G
B
t
o
L*
a
*
b
Th
r
e
e
-
l
a
y
e
r
me
d
i
a
f
i
l
t
e
r
C
l
u
st
e
r
i
n
g
K
_
m
e
a
n
s c
l
u
st
e
r
i
n
g
1
2
3
4
5
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
mp
r
o
ve
d
fea
tu
r
e
ex
tr
a
ctio
n
m
eth
o
d
a
n
d
K
-
mea
n
s
clu
s
teri
n
g
fo
r
s
o
il ferti
l
ity
…
(
A
g
u
n
g
R
a
ma
d
h
a
n
u
)
2007
3
.
3
.
P
r
o
ce
s
s
ing
T
h
e
p
r
o
ce
s
s
s
tep
co
m
es
n
ex
t.
T
h
e
im
ag
e
ex
tr
ac
tio
n
p
r
o
ce
d
u
r
e
was
co
m
p
leted
in
s
tag
es
f
o
r
th
is
s
tu
d
y
.
T
h
r
ee
d
if
f
er
e
n
t
m
et
h
o
d
s
o
f
im
a
g
e
e
x
tr
ac
tio
n
ar
e
ca
r
r
i
ed
o
u
t:
s
h
ap
e,
tex
tu
r
e,
a
n
d
f
ea
t
u
r
e
e
x
tr
ac
tio
n
.
On
e
ca
n
d
o
th
ese
th
r
ee
e
x
tr
ac
tio
n
m
eth
o
d
s
p
r
o
f
icien
tly
.
T
h
e
f
ea
t
u
r
es,
tex
tu
r
e,
an
d
f
o
r
m
ex
tr
ac
t
ed
f
r
o
m
s
o
il
im
ag
e
d
ata
ar
e
s
h
o
wn
i
n
T
ab
le
3
.
T
ab
le
3
.
Pro
ce
s
s
in
g
r
esu
lt
No
Pre
-
p
r
o
c
e
ssi
n
g
r
e
s
u
l
t
P
r
o
c
e
ss
i
n
g
r
e
su
l
t
C
h
a
r
a
c
t
e
r
i
s
t
i
c
s
e
x
t
r
a
c
t
i
o
n
Te
x
t
u
r
e
e
x
t
r
a
c
t
i
o
n
S
h
a
p
e
s
e
x
t
r
a
c
t
i
o
n
1
2
3
4
5
3
.
4
.
Resul
t
T
h
e
r
esu
lts
o
f
th
is
r
esear
ch
in
d
icate
wh
eth
er
th
e
s
o
il is
f
er
tile o
r
n
o
t
b
ased
o
n
t
h
e
an
aly
s
is
co
n
d
u
cte
d
.
T
h
e
class
if
icatio
n
p
r
o
ce
s
s
h
el
p
s
d
eter
m
in
e
th
e
s
o
il
’
s
f
er
tili
t
y
s
tatu
s
with
a
ce
r
tain
lev
el
o
f
ac
cu
r
ac
y
.
T
ab
le
4
p
r
esen
ts
th
e
d
etailed
o
u
tco
m
e
s
o
f
th
e
ev
a
lu
ati
o
n
,
in
clu
d
in
g
k
ey
p
ar
a
m
eter
s
u
s
ed
in
th
e
ass
es
s
m
en
t.
T
h
ese
f
in
d
in
g
s
p
r
o
v
id
e
v
alu
ab
le
i
n
s
ig
h
ts
f
o
r
a
g
r
icu
ltu
r
al
p
lan
n
in
g
an
d
s
o
il m
an
ag
e
m
en
t.
T
ab
le
4
.
R
esu
lt:
id
en
tific
atio
n
No
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o
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m
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p
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t
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o
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i
f
i
c
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No
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o
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l
i
m
a
g
e
r
y
i
n
p
u
t
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o
i
l
i
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e
n
t
i
f
i
c
a
t
i
o
n
1
4
2
5
3
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
38
,
No
.
3
,
J
u
n
e
20
25
:
2
0
0
1
-
201
1
2008
4.
CO
NCLU
SI
O
N
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h
e
p
r
im
ar
y
o
b
jectiv
e
o
f
th
is
s
tu
d
y
is
to
ascer
tain
th
e
f
er
ti
lity
o
f
s
o
il.
T
h
r
o
u
g
h
an
an
aly
s
is
o
f
th
e
r
esu
lts
an
d
s
u
b
s
eq
u
en
t
d
is
cu
s
s
io
n
s
,
we
aim
to
d
r
aw
c
o
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cl
u
s
io
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s
r
eg
ar
d
i
n
g
th
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ac
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m
en
t
o
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u
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n
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v
el
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ed
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s
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r
ac
y
o
f
id
en
tify
in
g
o
b
jects
with
in
s
o
il
im
ag
es.
T
h
r
o
u
g
h
e
x
p
er
i
m
en
tatio
n
with
a
d
ataset
c
o
m
p
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g
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5
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n
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u
t
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s
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r
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r
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ate
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%.
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h
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ea
n
s
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o
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r
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r
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tly
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s
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wh
ile
in
c
o
r
r
ec
tly
id
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t
if
y
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g
o
b
jects
in
5
im
ag
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h
is
s
u
cc
ess
d
em
o
n
s
tr
ates
th
e
ef
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icac
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o
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r
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r
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h
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ac
cu
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ately
d
is
ce
r
n
in
g
s
o
il
p
r
o
p
e
r
ties
.
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r
th
er
m
o
r
e
,
th
e
v
er
s
atility
o
f
o
u
r
m
eth
o
d
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o
r
its
ap
p
licatio
n
to
o
th
er
p
h
o
t
o
g
r
ap
h
s
,
f
ac
ilit
atin
g
th
e
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en
tific
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o
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d
if
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er
en
t
o
b
je
cts
with
in
th
e
s
o
il.
T
h
is
s
u
g
g
e
s
ts
p
o
ten
tial
f
o
r
b
r
o
a
d
er
u
s
e
i
n
s
o
il
an
aly
s
is
an
d
ch
ar
ac
ter
izatio
n
b
ey
o
n
d
t
h
e
s
co
p
e
o
f
th
is
s
tu
d
y
.
As
s
u
ch
,
o
u
r
f
in
d
in
g
s
n
o
t
o
n
ly
co
n
tr
i
b
u
te
to
u
n
d
er
s
tan
d
i
n
g
s
o
il
f
er
tili
ty
b
u
t
also
o
f
f
er
a
p
r
o
m
is
in
g
to
o
l
f
o
r
f
u
tu
r
e
r
esea
r
ch
an
d
p
r
ac
tical
ap
p
licatio
n
s
in
ag
r
icu
ltu
r
al
a
n
d
en
v
ir
o
n
m
en
tal
s
cien
ce
s
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
wo
u
ld
lik
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to
ex
p
r
ess
th
eir
s
in
ce
r
e
g
r
atitu
d
e
to
Pro
f
.
Dr
.
Sar
jo
n
Def
it,
S.Ko
m
.
,
M.
Ko
m
.
as
R
ec
to
r
o
f
Un
i
v
er
s
itas
Pu
tr
a
I
n
d
o
n
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YPTK
Pad
an
g
a
n
d
Ass
o
c.
Pro
f
.
Dr
.
Mu
h
am
m
ad
R
id
wan
,
S.E
.
,
M.
M.
,
as
th
e
th
e
f
o
u
n
d
atio
n
’
s
p
r
esid
en
t
o
f
Yay
asan
Per
g
u
r
u
a
n
T
in
g
g
i
Ko
m
p
u
ter
(
YPTK
)
Pad
an
g
f
o
r
p
r
o
v
id
i
n
g
th
e
n
ec
ess
ar
y
f
ac
ilit
ies an
d
s
u
p
p
o
r
t th
r
o
u
g
h
o
u
t th
i
s
r
esear
ch
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
is
r
esear
ch
was
n
o
t
s
u
p
p
o
r
t
ed
b
y
a
n
y
g
r
an
ts
f
r
o
m
f
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n
d
in
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b
o
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ies
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th
e
p
u
b
lic,
p
r
iv
ate,
o
r
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-
p
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o
f
it secto
r
s
.
AUTHO
R
CO
NT
RI
B
UT
I
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NS ST
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Vi
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u
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u
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Hen
d
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i
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g
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✓
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Sil
f
ia
An
d
in
i
✓
✓
✓
✓
R
etn
o
Dev
ita
✓
✓
✓
✓
✓
E
v
a
R
ian
ti
✓
✓
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✓
C
:
C
o
n
c
e
p
t
u
a
l
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z
a
t
i
o
n
M
:
M
e
t
h
o
d
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g
y
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:
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f
t
w
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r
e
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l
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t
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Fo
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mal
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y
s
i
s
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:
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n
v
e
s
t
i
g
a
t
i
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n
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:
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e
so
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r
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e
s
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a
t
a
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u
r
a
t
i
o
n
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:
W
r
i
t
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n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
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:
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r
i
t
i
n
g
-
R
e
v
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e
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&
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t
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g
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:
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a
l
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z
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t
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:
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p
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v
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s
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r
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M
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Au
th
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r
s
s
tate
n
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co
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f
lict o
f
in
t
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est.
I
NF
O
RM
E
D
CO
NS
E
N
T
W
e
h
av
e
o
b
tain
ed
in
f
o
r
m
ed
c
o
n
s
en
t f
r
o
m
all
in
d
iv
id
u
als in
c
lu
d
ed
in
t
h
is
s
tu
d
y
.
E
T
H
I
CAL AP
P
RO
V
AL
T
h
e
r
esear
ch
r
elate
d
to
a
n
im
a
l
u
s
e
h
as
b
ee
n
c
o
m
p
lied
with
all
th
e
r
elev
an
t
n
atio
n
al
r
e
g
u
l
atio
n
s
an
d
in
s
titu
tio
n
al
p
o
licies f
o
r
th
e
ca
r
e
an
d
u
s
e
o
f
an
im
als.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
r
t
th
e
f
i
n
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
a
v
ailab
le
f
r
o
m
th
e
c
o
r
r
esp
o
n
d
in
g
au
t
h
o
r
,
[
AR
]
,
u
p
o
n
r
ea
s
o
n
ab
le
r
eq
u
est.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
I
mp
r
o
ve
d
fea
tu
r
e
ex
tr
a
ctio
n
m
eth
o
d
a
n
d
K
-
mea
n
s
clu
s
teri
n
g
fo
r
s
o
il ferti
l
ity
…
(
A
g
u
n
g
R
a
ma
d
h
a
n
u
)
2009
RE
F
E
R
E
NC
E
S
[
1
]
J.
G
a
l
o
s
a
n
d
X
.
W
a
n
g
,
“
D
e
mo
n
st
r
a
t
i
o
n
o
f
c
o
m
p
u
t
e
r
v
i
si
o
n
f
o
r
v
o
i
d
c
h
a
r
a
c
t
e
r
i
s
a
t
i
o
n
o
f
3
D
-
p
r
i
n
t
e
d
c
o
n
t
i
n
u
o
u
s
c
a
r
b
o
n
f
i
b
r
e
c
o
m
p
o
si
t
e
s,
”
R
e
su
l
t
s
i
n
Ma
t
e
r
i
a
l
s
,
v
o
l
.
2
2
,
n
o
.
M
a
r
c
h
,
p
.
1
0
0
5
6
6
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
i
n
ma
.
2
0
2
4
.
1
0
0
5
6
6
.
[
2
]
C
.
H
a
l
l
a
n
d
M
.
Lu
n
d
i
n
,
“
Te
c
h
n
o
l
o
g
y
i
n
t
h
e
c
l
a
ssr
o
o
m:
P
e
r
so
n
a
l
c
o
m
p
u
t
e
r
s a
n
d
l
e
a
r
n
i
n
g
o
u
t
c
o
mes
i
n
p
r
i
mary
sc
h
o
o
l
,
”
Ec
o
n
o
m
i
c
s
o
f
Ed
u
c
a
t
i
o
n
Re
v
i
e
w
,
v
o
l
.
1
0
0
,
n
o
.
M
a
r
c
h
,
p
.
1
0
2
5
3
6
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
c
o
n
e
d
u
r
e
v
.
2
0
2
4
.
1
0
2
5
3
6
.
[
3
]
M
.
D
e
s
i
m
o
n
i
,
D
.
P
a
p
a
,
C
.
L
a
s
o
r
sa,
M
.
M
i
l
i
o
n
i
,
a
n
d
R
.
C
e
r
a
v
o
l
o
,
“
C
o
m
p
u
t
e
r
u
ser
p
r
o
f
i
l
e
s
i
n
e
a
r
l
y
a
d
o
l
e
s
c
e
n
c
e
a
n
d
d
i
g
i
t
a
l
l
y
a
ssesse
d
ma
t
h
e
ma
t
i
c
s:
a
l
a
t
e
n
t
c
l
a
ss
a
n
a
l
y
si
s
,
”
C
o
m
p
u
t
e
rs
i
n
H
u
m
a
n
B
e
h
a
v
i
o
r
Re
p
o
rt
s
,
v
o
l
.
1
3
,
n
o
.
D
e
c
e
m
b
e
r
2
0
2
3
,
p
.
1
0
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6
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,
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4
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o
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:
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0
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j
.
c
h
b
r
.
2
0
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4
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0
0
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6
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.
[
4
]
S
.
A
h
ma
d
i
,
“
N
e
t
w
o
r
k
i
n
t
r
u
s
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o
n
d
e
t
e
c
t
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n
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n
c
l
o
u
d
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n
v
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r
o
n
me
n
t
s
:
a
c
o
m
p
a
r
a
t
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v
e
a
n
a
l
y
si
s
o
f
a
p
p
r
o
a
c
h
e
s,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
Ad
v
a
n
c
e
d
C
o
m
p
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t
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r
S
c
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e
n
c
e
a
n
d
A
p
p
l
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c
a
t
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o
n
s
(
I
J
AC
S
A)
,
v
o
l
.
1
5
,
n
o
.
3
,
p
p
.
1
–
8
,
2
0
2
4
.
[
5
]
N
.
A
.
M
a
sh
u
d
i
,
M
.
A
.
M
.
I
z
h
a
r
,
a
n
d
S
.
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.
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.
A
r
i
s,
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H
u
m
a
n
-
c
o
m
p
u
t
e
r
i
n
t
e
r
a
c
t
i
o
n
i
n
m
o
b
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l
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l
e
a
r
n
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n
g
:
a
r
e
v
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e
w
,
”
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n
t
e
rn
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t
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o
n
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l
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u
rn
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l
o
f
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g
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m
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wo
r
k
s
a
t
Un
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e
rsitas
P
u
tra
In
d
o
n
e
sia
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K
P
a
d
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g
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il
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M
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ro
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o
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a
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ter
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d
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b
a
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s,
m
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ste
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’
s,
a
n
d
d
o
c
to
ra
l
d
e
g
re
e
a
t
Un
iv
e
rsitas
P
u
tr
a
In
d
o
n
e
sia
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K
P
a
d
a
n
g
.
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a
t
u
n
iv
e
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a
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rd
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im
a
S
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m
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,
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.
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m
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,
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n
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n
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ter
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c
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n
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e
re
a
c
h
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d
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y
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il
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t
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ra
m
a
d
h
a
n
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@u
p
iy
p
tk
.
a
c
.
i
d
.
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o
ffic
e
is
lo
c
a
ted
in
Lu
b
u
k
Be
g
a
lu
n
g
S
tr
e
e
t,
P
a
d
a
n
g
,
S
u
m
a
tera
Ba
ra
t,
I
n
d
o
n
e
sia
,
a
t
Un
i
v
e
rsitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
.
His
a
re
a
s
o
f
sp
e
c
ialisa
ti
o
n
a
re
ima
g
e
p
ro
c
e
ss
in
g
a
n
d
a
rt
ifi
c
ial
in
telli
g
e
n
c
e
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
g
u
n
g
_
ra
m
a
d
h
a
n
u
@u
p
i
y
p
t
k
.
a
c
.
id
.
H
a
li
fia
H
e
n
d
r
i
is
a
d
e
d
ica
te
d
lec
tu
re
r
in
t
h
e
Co
m
p
u
ter
S
y
ste
m
De
p
a
rtem
e
n
t
in
F
a
c
u
lt
y
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
t
Un
iv
e
rsitas
P
u
tra
I
n
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
,
S
u
m
a
tera
Ba
ra
t,
In
d
o
n
e
sia
.
He
e
a
rn
e
d
h
is
Ba
c
h
e
lo
r
’
s
De
g
re
e
fro
m
Un
iv
e
rsitas
N
e
g
e
ri
P
a
d
a
n
g
(UN
P
)
in
t
h
e
El
e
c
tro
n
ics
E
n
g
i
n
e
e
rin
g
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u
c
a
ti
o
n
p
ro
g
ra
m
in
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a
c
u
lt
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h
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ics
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h
e
n
h
e
p
u
rsu
e
d
a
M
a
ste
r
’
s
De
g
re
e
a
t
Un
iv
e
rsitas
P
u
tra
I
n
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
,
sp
e
c
ializin
g
in
Co
m
p
u
ter
S
c
ien
c
e
.
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rre
n
tl
y
,
Ha
li
fia
is
e
n
g
a
g
e
d
i
n
d
o
c
to
ra
l
stu
d
ies
a
t
U
n
iv
e
r
sitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
,
f
o
c
u
sin
g
o
n
In
f
o
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
with
i
n
th
e
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m
p
u
te
r
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c
ien
c
e
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a
c
u
lt
y
.
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li
fia
’
s
u
n
i
q
u
e
i
d
e
n
ti
fier,
S
c
o
p
u
s
ID,
i
s
5
7
2
0
7
6
2
8
3
6
2
.
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re
se
a
rc
h
e
n
d
e
a
v
o
rs
tra
v
e
rse
d
iv
e
rse
d
o
m
a
in
s,
wit
h
p
a
rti
c
u
lar
e
x
p
e
rti
s
e
in
ima
g
e
p
ro
c
e
ss
in
g
,
d
a
ta
m
in
i
n
g
,
a
n
d
p
a
tt
e
rn
re
c
o
g
n
it
i
o
n
.
Ha
li
fia
He
n
d
ri
we
lco
m
e
s
c
o
m
m
u
n
ica
ti
o
n
a
n
d
c
o
ll
a
b
o
ra
ti
o
n
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
h
a
li
fia_
h
e
n
d
ri@
u
p
i
y
p
tk
.
a
c
.
i
d
.
S
o
fik
a
E
n
g
g
a
r
i
is
a
d
e
d
ica
ted
lec
tu
re
r
i
n
t
h
e
I
n
fo
rm
a
ti
o
n
S
y
ste
m
S
tu
d
y
P
ro
g
ra
m
with
in
th
e
F
a
c
u
lt
y
o
f
C
o
m
p
u
ter
S
c
ien
c
e
a
t
U
n
iv
e
rsitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
,
S
u
m
a
tera
Ba
ra
t,
In
d
o
n
e
sia
.
He
e
a
rn
e
d
h
is
Ba
c
h
e
lo
r
’
s,
M
a
ste
r
a
n
d
Do
c
t
o
r
De
g
re
e
fro
m
Un
iv
e
rsitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
in
t
h
e
In
fo
rm
a
ti
o
n
S
y
ste
m
p
ro
g
ra
m
u
n
d
e
r
th
e
F
a
c
u
lt
y
o
f
Co
m
p
u
ter
S
c
ien
c
e
.
En
g
g
a
ri
u
n
i
q
u
e
id
e
n
ti
fier,
S
c
o
p
u
s
ID,
is
5
7
2
1
3
5
2
0
4
0
4
.
His
re
se
a
rc
h
e
n
d
e
a
v
o
rs
trav
e
rse
d
iv
e
rse
d
o
m
a
in
s,
with
p
a
rti
c
u
lar
e
x
p
e
rti
se
in
ima
g
e
p
ro
c
e
ss
in
g
,
in
fo
rm
a
ti
o
n
s
y
ste
m
,
a
n
d
we
b
d
e
sig
n
.
S
o
fi
k
a
E
n
g
g
a
ri
we
lc
o
m
e
s
c
o
m
m
u
n
ica
ti
o
n
a
n
d
c
o
ll
a
b
o
ra
ti
o
n
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
so
fi
k
a
_
e
n
g
g
a
ri@u
p
i
y
p
tk
.
a
c
.
id
.
S
il
fia
And
i
n
i
is
a
d
e
d
ica
ted
lec
tu
re
r
in
th
e
In
f
o
rm
a
ti
o
n
S
y
ste
m
S
tu
d
y
P
ro
g
ra
m
with
in
th
e
F
a
c
u
lt
y
o
f
C
o
m
p
u
ter
S
c
ien
c
e
a
t
U
n
iv
e
rsitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
,
In
d
o
n
e
sia
.
S
h
e
e
a
rn
e
d
h
is
Ba
c
h
e
lo
r
’
s
De
g
re
e
fro
m
UPI
YPT
K
in
th
e
In
fo
rm
a
ti
o
n
S
y
ste
m
p
ro
g
ra
m
.
S
u
b
se
q
u
e
n
tl
y
,
s
h
e
p
u
rsu
e
d
a
M
a
ste
r
’
s
De
g
re
e
a
t
UPI
Y
P
TK
P
a
d
a
n
g
.
An
d
ri
g
h
t
n
o
w
,
sh
e
c
o
n
ti
n
u
e
d
a
d
o
c
t
o
ra
l
d
e
g
re
e
fro
m
UPI
YPT
K
P
a
d
a
n
g
.
C
u
rre
n
t
ly
,
S
il
fia
An
d
in
i
is
He
a
d
o
f
Div
isio
n
Trac
e
r
S
tu
d
y
fro
m
Un
iv
e
rsitas
P
u
tra
In
d
o
n
e
sia
YPT
K
P
a
d
a
n
g
.
S
il
fia
An
d
in
i
u
n
i
q
u
e
i
d
e
n
ti
fier,
S
c
o
p
u
s
ID,
i
s
5
7
2
0
2
9
5
8
8
1
8
.
He
r
re
se
a
rc
h
e
n
d
e
a
v
o
rs
trav
e
rse
d
i
v
e
rse
d
o
m
a
in
s,
with
p
a
rti
c
u
lar
e
x
p
e
rti
se
in
ima
g
e
p
r
o
c
e
ss
in
g
a
n
d
in
fo
rm
a
ti
o
n
s
y
ste
m
.
S
il
f
ia
we
lco
m
e
s
c
o
m
m
u
n
ica
ti
o
n
a
n
d
c
o
l
lab
o
ra
ti
o
n
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
silfi
a
a
n
d
in
i6
8
@u
p
iy
p
tk
.
a
c
.
id
.
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