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d
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f
m
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u
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.
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id
1.
I
NT
RO
D
UCT
I
O
N
P
asa
m
an
o
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an
g
e
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s
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I
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m
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ities
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ticu
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Su
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a
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n
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s
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t
h
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o
r
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ld
s
s
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g
n
i
f
ican
t
ag
r
ib
u
s
i
n
es
s
p
o
ten
tia
l
[
1
]
;
h
o
w
e
v
er
,
it
s
q
u
alit
y
v
ar
ies
g
r
ea
tl
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a
n
d
cla
s
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f
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tech
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lo
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y
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a
s
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w
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ag
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citr
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[
2
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.
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u
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tl
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clas
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f
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s
till
p
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Si
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telli
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lass
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3
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.
Field
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t
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at
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s
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elo
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to
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ated
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n
s
y
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te
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i
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tial
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im
p
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eliab
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d
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[
4
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.
R
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tech
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ased
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m
s
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to
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g
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l
t
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r
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ap
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s
[
5
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.
F
o
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in
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ta
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ce
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u
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tr
aso
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s
en
s
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tio
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ac
cu
r
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r
ip
e
n
es
s
m
ea
s
u
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m
en
t
[
6
]
,
[
7
]
.
W
h
en
co
m
b
i
n
ed
w
it
h
f
u
zz
y
lo
g
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s
u
c
h
s
y
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m
s
h
a
v
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b
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p
r
o
v
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f
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ti
v
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f
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d
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tr
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cti
v
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f
r
u
it q
u
alit
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ass
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s
s
m
en
t
[
8
]
,
[
9
]
.
T
h
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Ma
m
d
a
n
i
f
u
zz
y
i
n
f
er
e
n
ce
s
y
s
te
m
(
FI
S)
is
w
id
el
y
u
s
ed
d
u
e
to
its
in
tu
i
tiv
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r
u
le
-
b
ased
r
ea
s
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in
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d
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ec
ti
v
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n
ess
in
p
r
o
ce
s
s
in
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s
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n
s
o
r
d
ata
[
1
0
]
.
Fu
zz
y
lo
g
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c
w
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s
s
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lecte
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f
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it
s
ab
ilit
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cla
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f
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ta
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k
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[
1
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B
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teg
r
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co
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p
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t
h
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Ma
m
d
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esp
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[
1
2
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,
[
1
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u
i
t
g
r
ad
in
g
,
th
er
eb
y
s
u
p
p
o
r
tin
g
f
ar
m
er
p
r
o
d
u
ctiv
i
t
y
a
n
d
co
n
tr
i
b
u
tin
g
to
th
e
m
o
d
er
n
izatio
n
o
f
I
n
d
o
n
esia
’
s
a
g
r
icu
lt
u
r
al
s
ec
to
r
.
2.
M
E
T
H
O
D
T
h
is
s
t
u
d
y
e
m
p
lo
y
s
a
n
e
x
p
e
r
i
m
en
tal
ap
p
r
o
ac
h
ai
m
ed
at
d
esig
n
in
g
a
n
d
ev
al
u
ati
n
g
an
au
to
m
a
tic
class
i
f
icatio
n
s
y
s
te
m
f
o
r
P
asa
m
an
o
r
an
g
e
s
b
ased
o
n
s
e
n
s
o
r
-
d
er
iv
ed
d
ata.
T
h
e
m
et
h
o
d
en
ab
les
b
o
th
s
y
s
te
m
d
ev
elo
p
m
en
t
a
n
d
d
ir
ec
t
p
er
f
o
r
m
a
n
ce
tes
t
in
g
.
T
h
e
r
esear
ch
w
as
ca
r
r
ied
o
u
t
i
n
f
o
u
r
m
ain
s
ta
g
es
:
v
ar
iab
le
o
b
s
er
v
atio
n
,
f
u
zz
y
lo
g
ic
s
y
s
t
e
m
d
esi
g
n
,
p
r
o
g
r
a
m
p
er
f
o
r
m
an
ce
test
i
n
g
,
an
d
ev
al
u
atio
n
.
T
h
e
class
if
icatio
n
s
y
s
te
m
w
a
s
d
ev
elo
p
ed
o
n
th
e
E
SP
3
2
p
latf
o
r
m
u
s
i
n
g
th
e
A
r
d
u
in
o
in
te
g
r
ated
d
ev
elo
p
m
e
n
t
en
v
i
r
o
n
m
e
n
t
(
I
DE
)
s
o
f
t
w
ar
e,
w
i
th
f
u
zz
y
r
u
les
co
d
ed
u
s
in
g
a
cu
s
to
m
f
u
n
c
tio
n
b
ased
o
n
th
e
A
r
d
u
in
o
-
f
u
zz
y
l
ib
r
ar
y
f
r
a
m
e
w
o
r
k
.
T
h
e
q
u
alit
y
p
ar
a
m
eter
s
o
f
P
asa
m
an
o
r
an
g
es
ar
e
d
eter
m
i
n
ed
b
y
d
ia
m
eter
a
n
d
co
lo
r
in
d
ex
r
ed
,
g
r
ee
n
,
a
n
d
b
lu
e
(
R
GB
)
,
p
ar
ticu
lar
l
y
th
e
r
ed
co
m
p
o
n
en
t
[
1
6
]
.
2
.
1
.
Va
ri
a
ble
o
bs
er
v
a
t
io
n
T
h
e
s
tu
d
y
b
e
g
an
w
it
h
d
ir
ec
t
o
b
s
er
v
atio
n
o
f
clas
s
i
f
icatio
n
p
r
ac
tices
a
m
o
n
g
f
ar
m
er
s
in
Nag
ar
i
Uj
u
n
g
Gad
in
g
,
W
est
P
asa
m
an
.
Far
m
er
s
t
y
p
icall
y
c
lass
if
y
o
r
an
g
es
b
ased
o
n
t
w
o
cr
iter
ia:
f
r
u
it
s
ize
(
d
iam
eter
)
an
d
s
k
i
n
co
lo
r
(
g
r
ee
n
,
s
li
g
h
tl
y
y
el
l
o
w
,
an
d
f
u
l
l
y
y
ello
w
)
.
B
ased
o
n
th
ese
p
r
ac
tice
s
,
th
e
o
r
an
g
e
s
w
er
e
g
r
o
u
p
ed
in
to
th
r
ee
q
u
alit
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clas
s
es d
er
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f
r
o
m
a
co
m
b
i
n
atio
n
o
f
s
ize
a
n
d
co
lo
r
.
C
o
lo
r
w
a
s
q
u
a
n
ti
f
ied
u
s
i
n
g
t
h
e
r
ed
(
R
)
co
m
p
o
n
e
n
t
v
al
u
e
o
f
t
h
e
f
r
u
i
t
s
k
i
n
,
as
th
e
r
ed
s
p
ec
tr
u
m
s
tr
o
n
g
l
y
i
n
f
lu
e
n
ce
s
r
ip
en
i
n
g
co
lo
r
.
T
h
e
r
e
d
co
m
p
o
n
en
t
is
a
d
eter
m
in
a
n
t
f
ac
to
r
in
citr
u
s
m
atu
r
it
y
[
1
7
]
.
P
r
i
o
r
to
d
ata
co
llectio
n
,
s
en
s
o
r
s
w
er
e
ca
lib
r
ated
:
th
e
HC
-
S
R
0
4
u
ltra
s
o
n
ic
s
e
n
s
o
r
w
a
s
v
alid
ated
ag
ain
s
t
d
ig
ital
ca
lip
er
m
ea
s
u
r
e
m
e
n
t
s
at
m
u
ltip
le
d
is
t
an
ce
s
,
w
h
ile
th
e
T
C
S3
2
0
0
s
en
s
o
r
w
as
ca
lib
r
ated
u
n
d
er
a
co
n
s
tan
t
li
g
h
t
-
e
m
itti
n
g
d
io
d
e
(
L
E
D
)
lig
h
t
s
o
u
r
ce
to
m
i
n
i
m
ize
a
m
b
ie
n
t
lig
h
ti
n
g
ef
f
ec
ts
.
T
ab
le
1
p
r
esen
ts
th
e
p
r
e
-
r
esear
ch
m
ea
s
u
r
e
m
e
n
t
s
u
s
ed
as r
ef
er
en
ce
r
an
g
es.
T
ab
le
1
.
P
r
e
-
r
esear
ch
m
ea
s
u
r
e
m
en
ts
C
l
a
ss
D
i
a
me
t
e
r
(
c
m)
R
e
d
r
a
t
i
o
A
4
–
6
0
.
3
–
0
.
46
B
5
.
3
–
7
0
.
43
–
0
.
57
C
6
–
7
.
8
0
.
54
–
0
.
6
2
.
2
.
F
uzzy
lo
g
ic
s
y
s
t
e
m
des
i
g
n
T
h
e
Ma
m
d
an
i
f
u
zz
y
lo
g
ic
m
e
th
o
d
w
as
e
m
p
lo
y
ed
to
d
eter
m
in
e
f
r
u
i
t
clas
s
es
b
ased
o
n
d
ia
m
eter
a
n
d
co
lo
r
.
T
h
is
m
et
h
o
d
is
p
ar
tic
u
l
ar
l
y
s
u
itab
le
b
ec
au
s
e
it
ca
n
p
r
o
ce
s
s
u
n
ce
r
tain
d
ata,
s
u
c
h
a
s
f
r
u
i
t
co
lo
r
,
w
h
ic
h
o
f
ten
lac
k
s
s
h
ar
p
b
o
u
n
d
ar
ies.
T
h
e
s
y
s
te
m
w
as
i
m
p
le
m
e
n
ted
o
n
th
e
E
SP
3
2
m
icr
o
co
n
tr
o
ller
f
o
r
r
ea
l
-
ti
m
e
d
ata
p
r
o
ce
s
s
in
g
.
P
r
ev
io
u
s
s
tu
d
ie
s
h
av
e
s
h
o
w
n
th
a
t
co
lo
r
s
en
s
o
r
tech
n
o
lo
g
y
co
n
tr
ib
u
te
s
s
ig
n
i
f
ica
n
tl
y
to
class
i
f
icatio
n
ac
c
u
r
ac
y
a
n
d
r
ed
u
ce
s
h
u
m
a
n
er
r
o
r
[
1
8
]
.
Mo
r
eo
v
er
,
f
u
zz
y
lo
g
ic
e
n
ab
l
es
t
h
e
h
an
d
li
n
g
o
f
lin
g
u
i
s
tic
v
ar
iab
les t
h
a
t a
r
e
d
if
f
ic
u
lt to
ad
d
r
ess
u
s
i
n
g
th
r
e
s
h
o
l
d
-
b
ased
m
et
h
o
d
s
[
1
9
]
.
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
f
o
r
b
o
th
d
iam
eter
an
d
co
lo
r
w
er
e
d
ef
i
n
ed
as
tr
ap
ez
o
i
d
al
f
u
n
c
tio
n
s
d
er
iv
ed
f
r
o
m
th
e
o
b
s
er
v
ed
r
an
g
e
s
in
T
ab
le
1
,
en
s
u
r
in
g
s
m
o
o
th
tr
an
s
it
io
n
s
b
et
w
ee
n
o
v
er
lap
p
in
g
ca
teg
o
r
ies
.
T
h
e
r
atio
n
ale
f
o
r
u
s
i
n
g
tr
ap
e
zo
id
al
s
h
ap
es
is
t
h
eir
ab
ilit
y
to
m
o
d
el
g
r
ad
u
al
r
ip
en
i
n
g
b
o
u
n
d
ar
ies
a
n
d
av
o
id
ab
r
u
p
t th
r
esh
o
ld
i
n
g
.
T
h
e
d
esig
n
p
r
o
ce
s
s
b
eg
a
n
w
it
h
co
n
v
er
ti
n
g
d
ia
m
eter
a
n
d
co
lo
r
d
ata
in
to
f
u
zz
y
v
al
u
e
s
(
f
u
z
zif
i
ca
tio
n
)
.
T
h
ese
in
p
u
t
s
w
er
e
t
h
en
p
r
o
ce
s
s
ed
th
r
o
u
g
h
a
s
et
o
f
“
i
f
–
th
en
”
r
u
le
s
co
d
ed
in
th
e
E
SP
3
2
en
v
ir
o
n
m
e
n
t.
Fo
r
ex
a
m
p
le,
i
f
th
e
s
ize
is
s
m
al
l
an
d
th
e
co
lo
r
is
g
r
ee
n
,
th
en
t
h
e
f
r
u
it
is
clas
s
i
f
ied
as
c
lass
C
;
if
th
e
s
ize
is
lar
g
e
an
d
th
e
co
lo
r
is
y
e
llo
w
,
t
h
e
n
it
b
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g
s
to
c
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A
.
Af
ter
ap
p
ly
i
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g
th
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u
le
s
,
th
e
r
es
u
lts
w
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e
co
m
b
i
n
ed
an
d
tr
an
s
f
o
r
m
ed
i
n
to
cr
is
p
o
u
tp
u
ts
(
d
ef
u
zz
i
f
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n
)
u
s
i
n
g
th
e
ce
n
tr
o
id
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f
ar
ea
(
C
O
A
)
m
et
h
o
d
to
p
r
o
v
id
e
th
e
f
in
a
l
class
i
f
icatio
n
.
T
ab
le
2
s
h
o
w
s
t
h
e
f
u
zz
y
in
f
er
en
ce
r
u
les
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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T
ab
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2
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If
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T
h
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A1
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s sma
l
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c
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r
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C
l
a
ss C
A2
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s sma
l
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i
s sl
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w
C
l
a
ss C
A3
S
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s sma
l
l
a
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d
c
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s y
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l
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w
C
l
a
ss C
A4
S
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z
e
i
s me
d
i
u
m
a
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r
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C
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A5
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l
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s sl
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l
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w
C
l
a
ss B
A6
S
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z
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i
s me
d
i
u
m
a
n
d
c
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r
i
s y
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l
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w
C
l
a
ss B
A7
S
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z
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s l
a
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C
l
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A8
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C
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A9
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a
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n
d
c
o
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r
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s y
e
l
l
o
w
C
l
a
ss A
2
.
3
.
P
r
o
g
ra
m
perf
o
r
m
a
nce
t
esting
T
h
e
d
ev
elo
p
ed
p
r
o
g
r
am
w
a
s
test
ed
to
ev
a
lu
ate
clas
s
i
f
icat
io
n
p
er
f
o
r
m
a
n
ce
a
n
d
id
en
ti
f
y
p
o
ten
tial
er
r
o
r
s
.
T
h
e
s
y
s
te
m
o
u
tp
u
t
s
o
b
tain
ed
f
r
o
m
t
h
e
E
SP
3
2
m
ic
r
o
co
n
tr
o
ller
w
er
e
co
m
p
ar
ed
ag
ain
s
t
th
e
r
esu
lts
g
en
er
ated
b
y
m
atr
ix
lab
o
r
ato
r
y
(
M
A
T
L
A
B
)
s
o
f
t
w
ar
e.
T
h
is
co
m
p
ar
is
o
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e
n
s
u
r
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at
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h
e
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f
icatio
n
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s
s
i
m
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le
m
en
ted
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n
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ar
d
w
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e
c
o
r
r
esp
o
n
d
ed
w
it
h
t
h
e
estab
li
s
h
ed
FIS
i
n
M
A
T
L
A
B
.
Sen
s
o
r
s
a
m
p
li
n
g
w
a
s
p
er
f
o
r
m
ed
at
a
r
ate
o
f
1
0
Hz
to
en
s
u
r
e
s
tab
le
r
ea
d
in
g
s
.
T
h
e
E
SP
3
2
s
y
s
te
m
w
a
s
d
esig
n
ed
w
it
h
an
u
p
d
ate
c
y
cle
o
f
1
0
0
m
s
p
er
class
if
icatio
n
,
al
lo
w
i
n
g
n
ea
r
r
ea
l
-
t
i
m
e
p
er
f
o
r
m
an
ce
s
u
itab
le
f
o
r
o
n
-
f
ield
g
r
ad
in
g
.
2
.
4
.
E
v
a
lua
t
i
o
n
A
t
t
h
e
f
in
al
s
ta
g
e,
th
e
clas
s
i
f
ic
atio
n
r
esu
l
ts
w
er
e
r
e
-
e
v
al
u
ate
d
to
v
er
if
y
er
r
o
r
r
ates
d
u
r
in
g
t
h
e
g
r
ad
in
g
p
r
o
ce
s
s
.
T
h
e
MA
T
L
AB
-
b
ase
d
FIS
w
as
u
s
ed
as
a
b
en
c
h
m
ar
k
f
o
r
co
m
p
ar
is
o
n
.
T
h
e
ac
cu
r
ac
y
o
f
th
e
s
y
s
te
m
d
ep
en
d
s
s
ig
n
if
ican
t
l
y
o
n
th
e
q
u
an
t
it
y
a
n
d
d
iv
er
s
it
y
o
f
tr
ai
n
in
g
d
ata
[
2
0
]
.
T
h
e
p
er
f
o
r
m
a
n
ce
cr
iter
io
n
w
as
b
ased
o
n
th
e
co
ef
f
icie
n
t
o
f
d
eter
m
i
n
atio
n
(
R
²)
.
I
f
R
²
≤
0
.
9
0
,
s
y
s
te
m
m
o
d
i
f
icatio
n
s
w
er
e
ap
p
lied
u
n
til
th
e
v
alu
e
ex
ce
ed
ed
R
²
≥
0
.
9
0
,
en
s
u
r
i
n
g
r
eliab
le
class
i
f
icatio
n
p
er
f
o
r
m
a
n
ce
.
I
n
ad
d
itio
n
to
R
²,
co
n
f
u
s
io
n
m
atr
ices
w
er
e
g
e
n
er
ated
to
an
al
y
ze
clas
s
-
lev
e
l a
cc
u
r
ac
y
f
o
r
g
r
ad
es A
,
B
,
an
d
C
,
p
r
o
v
id
in
g
a
clea
r
er
ev
alu
a
tio
n
o
f
clas
s
i
f
icatio
n
o
u
tco
m
es.
W
h
ile
r
es
u
lts
i
n
d
icat
ed
h
ig
h
ac
c
u
r
ac
y
,
li
m
ita
tio
n
s
r
e
m
ai
n
i
n
ter
m
s
o
f
s
a
m
p
le
s
ize,
v
ar
iab
ilit
y
o
f
te
s
t
f
r
u
i
ts
,
an
d
p
o
ten
t
ial
en
v
ir
o
n
m
en
tal
ef
f
ec
t
s
(
e.
g
.
,
lig
h
ti
n
g
o
r
s
e
n
s
o
r
n
o
i
s
e)
.
Nev
er
th
eles
s
,
th
e
s
y
s
te
m
d
e
m
o
n
s
tr
ates
th
e
p
o
te
n
tial
o
f
Ma
m
d
a
n
i
FIS
o
n
E
SP
3
2
as
a
p
r
ac
tical
r
ea
l
-
ti
m
e
s
o
lu
t
io
n
f
o
r
citr
u
s
clas
s
i
f
icatio
n
in
I
n
d
o
n
e
s
ia
n
a
g
r
icu
l
tu
r
e.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
d
ec
is
io
n
-
m
a
k
i
n
g
s
y
s
te
m
i
n
t
h
is
s
t
u
d
y
w
as
d
es
ig
n
ed
u
s
i
n
g
Ma
m
d
a
n
i
f
u
zz
y
lo
g
ic,
w
it
h
d
ia
m
eter
an
d
co
lo
r
as
d
ec
is
io
n
v
ar
iab
les.
Ma
m
d
an
i
f
u
zz
y
lo
g
ic
w
a
s
s
elec
ted
b
ec
au
s
e
o
f
its
ab
ilit
y
t
o
h
an
d
le
u
n
ce
r
ta
in
an
d
s
u
b
j
ec
tiv
e
d
ata,
m
ak
i
n
g
i
t
s
u
itab
le
f
o
r
class
if
y
i
n
g
f
r
u
it
q
u
alit
y
w
h
er
e
v
alu
e
s
o
f
ten
o
v
er
lap
.
T
h
e
f
u
zz
y
-
b
ased
class
i
f
icatio
n
co
n
s
is
t
s
o
f
t
h
r
ee
s
ta
g
es:
f
u
zz
i
f
icatio
n
(
co
n
v
er
ti
n
g
d
ata
in
to
f
u
zz
y
s
ets
)
,
f
u
zz
y
i
n
f
er
e
n
c
e
(
d
ec
is
io
n
-
m
a
k
i
n
g
u
s
i
n
g
r
u
les),
an
d
d
ef
u
z
zi
f
icatio
n
(
co
n
v
er
ti
n
g
f
u
zz
y
r
es
u
lt
s
in
to
cr
is
p
o
u
t
p
u
ts
)
.
3
.
1
.
F
uzzif
ica
t
io
n
T
h
e
f
ir
s
t
s
tep
in
v
o
lv
ed
d
ef
i
n
i
n
g
f
u
zz
y
s
ets
f
o
r
ea
ch
in
p
u
t
an
d
o
u
tp
u
t
v
ar
iab
le.
T
h
e
class
if
i
ca
tio
n
to
o
l
e
m
p
lo
y
ed
th
r
ee
f
u
zz
y
v
ar
iab
l
es:
t
w
o
i
n
p
u
t
s
(
s
ize
an
d
co
lo
r
)
an
d
o
n
e
o
u
tp
u
t
(
q
u
alit
y
)
.
I
n
p
u
t
v
al
u
es
o
b
tain
ed
f
r
o
m
th
e
HC
-
S
R
0
4
an
d
T
C
S3
2
0
0
s
en
s
o
r
s
w
er
e
co
n
v
er
ted
in
to
f
u
zz
y
m
e
m
b
er
s
h
ip
v
al
u
es.
T
h
e
t
r
ap
ez
o
id
a
l
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
(
T
r
ap
m
f
)
w
a
s
u
s
ed
b
ec
au
s
e
it
ef
f
ec
t
iv
el
y
h
a
n
d
les
g
r
ad
u
al
v
a
lu
e
t
r
an
s
itio
n
s
w
it
h
i
n
a
d
ef
in
ed
r
an
g
e
[
2
1
]
.
T
ab
le
3
p
r
esen
t
s
th
e
f
u
zz
y
u
n
iv
er
s
e.
T
ab
le
3
.
Fu
zz
y
u
n
i
v
er
s
e
F
u
n
c
t
i
o
n
V
a
r
i
a
b
l
e
U
n
i
v
e
r
se
o
f
d
i
sco
u
r
se
I
n
p
u
t
S
i
z
e
[0
–
1
0
]
C
o
l
o
r
[0
–
1]
O
u
t
p
u
t
Q
u
a
l
i
t
y
[0
–
1]
3
.
1
.
1
.
Size
v
a
ria
ble (
f
ruit
dia
m
et
er
)
Fru
it
d
ia
m
eter
w
as
u
s
ed
as
th
e
p
r
im
ar
y
p
ar
a
m
eter
f
o
r
class
if
icatio
n
.
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
f
o
r
s
ize
w
er
e
d
iv
id
ed
in
to
t
h
r
ee
lin
g
u
i
s
tic
v
al
u
es:
s
m
al
l,
m
ed
i
u
m
,
a
n
d
lar
g
e.
Fi
g
u
r
e
1
s
h
o
w
s
th
e
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
f
o
r
th
e
s
ize
v
ar
iab
le.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
R
ea
l
-
time
cla
s
s
ifica
tio
n
o
f P
a
s
a
ma
n
o
r
a
n
g
es u
s
in
g
Ma
md
a
n
i
fu
z
z
y
in
feren
ce
s
ystem
…
(
F
a
h
mi
F
itr
io
F
a
u
z
i
)
1061
Fig
u
r
e
1
.
Me
m
b
er
s
h
ip
f
u
n
ctio
n
g
r
ap
h
f
o
r
s
ize
v
ar
iab
le
B
ased
o
n
Fig
u
r
e
1
,
th
e
r
an
g
es
w
er
e:
s
m
all
(
5
.
1
2
–
6
.
3
5
c
m
)
,
m
ed
iu
m
(
6
.
2
3
–
6
.
5
9
cm
)
,
an
d
lar
g
e
(
6
.
7
5
–
7
.
8
0
cm
)
.
Am
b
ig
u
it
ies
o
cc
u
r
r
ed
w
h
e
n
a
d
ia
m
eter
o
v
er
lap
p
ed
tw
o
class
e
s
(
e.
g
.
,
6
.
3
c
m
f
it
s
b
o
th
s
m
all
an
d
m
ed
i
u
m
)
.
Fu
zz
y
lo
g
ic
r
es
o
lv
ed
s
u
c
h
o
v
er
lap
s
b
y
a
s
s
i
g
n
in
g
m
e
m
b
er
s
h
ip
d
eg
r
ee
s
to
m
u
ltip
le
ca
te
g
o
r
ies.
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
w
e
r
e
ex
p
r
ess
ed
as:
(
1
)
=
{
1
,
5
.
735
6
.
35
−
6
.
35
−
5
,
735
,
5
.
735
<
<
6
.
35
0
,
6
.
35
(
2
)
=
{
0
,
≤
6
.
230
−
6
.
23
6
.
59
−
6
,
23
,
6
.
23
<
<
6
.
59
1
,
6
.
59
≤
≤
6
.
79
7
.
15
−
7
.
15
−
6
.
79
,
6
.
79
<
<
7
.
15
0
,
7
.
15
(
3
)
=
{
0
,
6
.
75
−
6
.
75
7
.
15
−
6
.
75
,
6
.
75
<
≤
7
.
275
1
,
7
.
275
T
h
e
MA
T
L
A
B
s
i
m
u
lat
io
n
c
o
n
f
ir
m
ed
th
at
t
h
e
i
m
p
le
m
e
n
t
ed
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
m
atch
ed
th
e
d
esig
n
ed
g
r
ap
h
(
F
ig
u
r
e
2
)
.
T
h
e
h
o
r
izo
n
tal
ax
is
s
h
o
w
s
t
h
e
m
ea
s
u
r
e
m
e
n
t
s
a
m
p
le
s
,
w
h
er
ea
s
th
e
v
er
tical
ax
i
s
r
ep
r
esen
ts
th
e
d
etec
ted
d
is
ta
n
c
e
v
alu
e
s
in
ce
n
ti
m
eter
s
o
b
tain
ed
f
r
o
m
u
ltra
s
o
n
ic
s
e
n
s
o
r
s
.
Fig
u
r
e
2
.
Size
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
i
n
M
A
T
L
A
B
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
24
,
No
.
3
,
J
u
n
e
20
26
:
1
058
-
1
0
67
1062
3
.
1
.
2
.
Co
lo
r
v
a
ria
ble (
re
d r
a
t
io
)
T
h
e
co
lo
r
v
ar
iab
le
w
a
s
o
b
tain
ed
f
r
o
m
t
h
e
r
ed
r
atio
o
f
th
e
T
C
S3
2
0
0
s
en
s
o
r
o
u
tp
u
t.
T
h
r
ee
f
u
zz
y
s
et
s
w
er
e
d
ef
i
n
ed
: g
r
ee
n
,
s
li
g
h
tl
y
y
ello
w
,
an
d
y
ello
w
(
Fi
g
u
r
e
3
)
.
Fig
u
r
e
3.
Me
m
b
er
s
h
ip
f
u
n
ctio
n
g
r
ap
h
f
o
r
co
lo
r
v
ar
iab
le
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ct
io
n
s
f
o
r
co
lo
r
ar
e
d
ef
in
ed
as:
(
1
)
=
{
1
,
0
.
367
0
.
431
−
0
.
431
−
0
.
367
,
0
.
367
<
<
0
.
431
0
,
0
.
431
ℎ
(
2
)
=
{
0
,
≤
0
.
404
−
0
.
404
0
.
421
−
0
.
404
,
0
.
404
<
<
0
.
421
1
,
0
.
421
≤
≤
0
.
471
0
.
488
−
0
.
488
−
0
.
471
,
0
.
471
<
<
0
.
488
0
,
0
.
488
(
3
)
=
{
0
,
0
.
478
−
0
.
478
0
.
507
−
0
.
478
,
0
.
478
<
≤
0
.
507
1
,
0
.
507
T
h
e
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
s
w
e
r
e
d
ef
in
ed
s
i
m
i
lar
l
y
a
n
d
v
er
i
f
i
ed
in
M
A
T
L
A
B
(
Fi
g
u
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ile
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u
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ip
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ip
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ig
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e
6
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u
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e
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u
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if
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SS
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3
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uzzif
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g
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g
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g
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T
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.
Def
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ased
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[
2
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]
,
class
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icatio
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r
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p
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[
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n
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g
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S
[
1
]
C
.
V
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.
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mr
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6
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M
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.
[
1
9
]
R
.
F
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C
á
d
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“
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B
I
O
G
RAP
H
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E
S O
F
AUTH
O
RS
Fa
h
m
i
Fi
tr
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o
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u
z
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re
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iv
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d
th
e
B.
En
g
.
d
e
g
re
e
(S
.
T
.
)
in
A
g
ricu
lt
u
ra
l
En
g
i
n
e
e
rin
g
f
ro
m
th
e
De
p
a
rt
m
e
n
t
o
f
A
g
ri
c
u
lt
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ra
l
E
n
g
in
e
e
rin
g
,
F
a
c
u
l
ty
o
f
Ag
ricu
lt
u
ra
l
T
e
c
h
n
o
lo
g
y
,
Un
iv
e
rsitas
A
n
d
a
las
,
P
a
d
a
n
g
,
I
n
d
o
n
e
sia
,
in
2
0
2
3
.
He
is
c
u
rre
n
tl
y
p
u
rsu
i
n
g
th
e
M
.
E
n
g
.
d
e
g
re
e
in
A
g
ricu
lt
u
ra
l
E
n
g
in
e
e
rin
g
a
t
Un
iv
e
rsitas
A
n
d
a
las
sin
c
e
2
0
2
3
.
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c
u
rre
n
t
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
p
e
rf
o
rm
a
n
c
e
a
n
a
l
y
sis
o
f
a
g
ricu
lt
u
ra
l
m
a
c
h
in
e
r
y
a
n
d
th
e
d
e
sig
n
a
n
d
e
n
g
i
n
e
e
rin
g
o
f
a
g
ricu
lt
u
ra
l
m
a
c
h
in
e
ry
te
c
h
n
o
lo
g
ies
.
He
is
a
c
ti
v
e
l
y
in
v
o
lv
e
d
in
stu
d
ies
to
im
p
ro
v
e
th
e
e
ff
ici
e
n
c
y
a
n
d
e
ff
e
c
ti
v
e
n
e
ss
o
f
m
a
c
h
in
e
ry
u
se
d
in
m
o
d
e
rn
a
g
ricu
lt
u
re
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
f
a
h
m
i
f
it
rio
0
2
@g
m
a
il
.
c
o
m
.
If
m
a
li
n
d
a
re
c
e
iv
e
d
th
e
P
h
.
D.
d
e
g
re
e
in
A
g
ricu
lt
u
ra
l
En
g
in
e
e
rin
g
f
ro
m
Un
iv
e
rsita
s
P
a
d
jad
jara
n
,
Ba
n
d
u
n
g
,
I
n
d
o
n
e
si
a
,
w
it
h
a
d
isse
rtatio
n
i
n
t
h
e
f
ield
o
f
I
m
a
g
e
P
ro
c
e
ss
in
g
in
A
g
ricu
lt
u
ra
l
E
n
g
i
n
e
e
rin
g
.
S
h
e
is
c
u
rre
n
tl
y
a
l
e
c
tu
re
r
w
it
h
th
e
De
p
a
rtme
n
t
o
f
A
g
ri
c
u
lt
u
ra
l
a
n
d
B
io
sy
ste
m
s
En
g
in
e
e
rin
g
,
F
a
c
u
lt
y
o
f
A
g
ricu
lt
u
ra
l
T
e
c
h
n
o
lo
g
y
,
Un
iv
e
rsitas
A
n
d
a
las
,
P
a
d
a
n
g
,
In
d
o
n
e
sia
,
w
h
e
re
sh
e
h
a
s
a
lso
se
r
v
e
d
a
s
S
e
c
re
tar
y
o
f
th
e
Ac
a
d
e
m
ic
S
e
n
a
te
a
n
d
S
e
c
re
tary
o
f
th
e
De
p
a
rtme
n
t
o
f
A
g
ricu
lt
u
ra
l
En
g
in
e
e
rin
g
.
He
r
c
u
rre
n
t
re
se
a
rc
h
i
n
tere
sts
in
c
l
u
d
e
im
a
g
e
p
ro
c
e
ss
in
g
,
a
g
ricu
lt
u
ra
l
m
e
c
h
a
n
iza
ti
o
n
,
a
n
d
a
g
ricu
lt
u
ra
l
sy
ste
m
s
e
n
g
in
e
e
rin
g
.
S
h
e
h
a
s
b
e
e
n
a
c
ti
v
e
l
y
in
v
o
lv
e
d
in
a
c
a
d
e
m
i
c
tea
c
h
in
g
,
re
se
a
rc
h
,
a
n
d
o
rg
a
n
iza
ti
o
n
a
l
ro
les
w
it
h
in
th
e
f
a
c
u
lt
y
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ifma
li
n
d
a
@a
e
.
u
n
a
n
d
.
a
c
.
id
.
Az
r
ifi
r
w
a
n
re
c
e
iv
e
d
th
e
P
h
.
D.
d
e
g
re
e
in
A
g
ricu
lt
u
ra
l
E
n
g
i
n
e
e
rin
g
f
ro
m
IP
B
Un
iv
e
rsit
y
,
Bo
g
o
r,
In
d
o
n
e
sia
,
w
it
h
a
d
isse
rtatio
n
re
late
d
t
o
th
e
d
e
sig
n
a
n
d
o
p
ti
m
iza
ti
o
n
o
f
a
g
ricu
lt
u
ra
l
m
a
c
h
in
e
r
y
s
y
ste
m
s,
a
n
d
t
h
e
M
.
En
g
.
d
e
g
re
e
in
I
n
d
u
str
ial
A
g
ricu
lt
u
ra
l
T
e
c
h
n
o
lo
g
y
f
ro
m
th
e
A
sia
n
In
stit
u
te
o
f
T
e
c
h
n
o
lo
g
y
(
A
IT
),
P
a
th
u
m
T
h
a
n
i,
T
h
a
il
a
n
d
.
He
is
c
u
rre
n
tl
y
a
l
e
c
tu
re
r
w
it
h
th
e
De
p
a
rtm
e
n
t
o
f
Ag
ricu
lt
u
ra
l
a
n
d
Bi
o
sy
ste
m
s
En
g
in
e
e
rin
g
,
F
a
c
u
lt
y
o
f
Ag
ricu
lt
u
ra
l
T
e
c
h
n
o
l
o
g
y
,
Un
iv
e
r
sitas
A
n
d
a
las
,
P
a
d
a
n
g
,
In
d
o
n
e
sia
,
w
h
e
re
h
e
a
lso
se
rv
e
d
a
s
V
ice
De
a
n
f
o
r
S
tu
d
e
n
t
A
ff
a
irs
(V
ice
De
a
n
III)
f
ro
m
2
0
1
8
t
o
2
0
2
2
.
His
c
u
r
re
n
t
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
a
g
ricu
lt
u
ra
l
m
a
c
h
in
e
r
y
d
e
sig
n
,
in
d
u
strial
s
y
ste
m
s
e
n
g
in
e
e
rin
g
,
a
n
d
p
o
sth
a
rv
e
st
tec
h
n
o
l
o
g
y
.
He
is
a
c
t
iv
e
l
y
e
n
g
a
g
e
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