I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l
E
ng
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
25
,
No
.
1
,
J
an
u
ar
y
20
22
,
p
p
.
56
1
~
5
6
8
I
SS
N:
2
5
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4
7
5
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DOI
: 1
0
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1
1
5
9
1
/ijeecs.v
25
.i
1
.
pp
561
-
5
6
8
561
J
o
ur
na
l ho
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e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Intellig
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aqua
culture
sy
st
em for
piscicultur
e simul
a
tion usin
g
deep learning
alg
o
rithm
Sh
er
win
B
.
Sa
pin
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a
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Alibu
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llen
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Veluz,
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2
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Th
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K
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s
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ith
m
Geo
g
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ap
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m
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latio
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R
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etwo
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k
T
aa
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k
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rticle
u
n
d
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r th
e
CC B
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SA
li
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se
.
C
o
r
r
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s
p
o
nd
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A
uth
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r
:
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er
win
B
.
Sap
in
C
o
lleg
e
o
f
C
o
m
p
u
ter
Stu
d
ies (
C
C
S),
L
ag
u
n
a
State
Po
ly
tech
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ic
Un
iv
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s
ity
L
o
s
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añ
o
s
,
L
ag
u
n
a,
Ph
ilip
p
in
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E
m
ail:
s
b
s
ap
in
@
ls
p
u
.
ed
u
.
p
h
1.
I
NT
RO
D
UCT
I
O
N
Fis
h
er
ies
an
d
aq
u
ac
u
ltu
r
e
p
r
o
d
u
cts
ar
e
im
p
o
r
tan
t
s
o
u
r
ce
s
o
f
p
r
o
tein
,
p
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o
v
id
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g
f
o
o
d
an
d
in
co
m
e
t
o
h
u
n
d
r
ed
s
o
f
in
d
iv
i
d
u
als
ar
o
u
n
d
th
e
wo
r
ld
.
I
n
th
e
ad
v
a
n
ce
m
en
t
o
f
a
q
u
ac
u
ltu
r
e,
tr
a
d
itio
n
al
p
r
o
d
u
ctio
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o
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els
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av
e
p
lay
ed
a
s
ig
n
if
ican
t
p
ar
t
in
th
e
f
ast
d
ev
el
o
p
m
en
t
o
f
aq
u
atic
p
r
o
d
u
ct
o
u
tp
u
t
[
1
]
.
Ho
we
v
er
,
as
co
n
s
u
m
p
tio
n
lev
el
an
d
en
v
ir
o
n
m
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tal
p
r
o
tectio
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awa
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e
n
ess
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ex
p
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d
e
d
,
d
if
f
er
en
t d
o
w
n
s
id
es
o
f
tr
ad
itio
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al
aq
u
ac
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ltu
r
e
m
o
d
els
h
a
v
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n
tin
u
o
u
s
ly
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en
.
Mo
s
t
tr
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itio
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f
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m
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m
o
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els
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eg
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estme
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t
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d
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lo
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lab
o
r
s
k
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r
eq
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.
W
ith
th
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m
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y
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ar
m
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ab
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t
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t
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ich
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e
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wd
in
g
an
d
u
n
tak
en
f
is
h
f
o
o
d
s
[
2
]
.
I
t
was
f
o
u
n
d
in
m
u
ltip
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r
esear
ch
es th
at
aq
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ac
u
ltu
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e
co
n
t
r
ib
u
tes to
th
e
u
n
co
n
tr
o
llab
le
p
o
llu
tio
n
i
n
th
e
lak
e
[
3
]
-
[
7
]
.
T
h
e
B
u
r
ea
u
o
f
f
is
h
er
ies
an
d
a
q
u
atic
r
eso
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r
ce
s
(
B
FAR
)
in
th
e
Ph
ilip
p
in
es
g
iv
es
ef
f
o
r
t
in
m
in
im
izin
g
th
is
p
r
o
b
lem
b
y
co
n
tr
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llin
g
th
e
p
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llu
tio
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in
T
aa
l
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ak
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T
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b
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estab
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p
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tecte
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ar
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m
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ag
em
en
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r
d
(
PAMB)
wh
ich
is
r
esp
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n
s
ib
le
f
o
r
m
o
n
ito
r
in
g
a
n
d
p
r
o
tectin
g
wild
life
,
in
clu
d
in
g
th
e
T
aa
l
l
ak
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T
h
e
y
aim
to
p
r
o
m
o
te
s
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s
tain
ab
ilit
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in
aq
u
ac
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ltu
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p
r
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d
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ctio
n
in
T
aa
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with
o
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t
co
m
p
r
o
m
is
in
g
its
en
v
ir
o
n
m
en
tal
s
tatu
s
.
On
e
o
f
th
eir
m
ain
s
o
lu
tio
n
s
is
to
s
u
p
p
o
r
t
r
esear
ch
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d
d
ev
elo
p
m
e
n
t
p
r
o
g
r
am
s
in
t
h
e
ar
ea
[
3
]
.
I
n
th
is
er
a
wh
er
e
b
ig
d
ata
p
lay
s
a
s
ig
n
if
ican
t
r
o
le
in
m
o
d
ellin
g
f
o
r
m
ea
n
in
g
f
u
l
r
e
p
r
e
s
en
tatio
n
,
d
if
f
er
en
t
s
im
u
latio
n
m
o
d
ellin
g
wer
e
in
tr
o
d
u
ce
d
in
s
y
s
tem
d
ev
elo
p
m
en
t
[
8
]
.
Data
s
im
u
latio
n
ap
p
lies
d
y
n
am
ic
tech
n
iq
u
e
wh
ich
ca
n
p
r
o
v
i
d
e
a
m
o
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e
r
esp
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s
iv
e
m
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el
wh
e
r
e
attr
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u
tes
wer
e
n
o
t
o
n
l
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ta
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d
a
s
p
ar
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eter
b
u
t
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cr
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to
ad
o
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t
th
e
b
e
h
a
v
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r
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f
n
ew
d
ata
in
p
u
tted
to
th
e
in
tellig
en
t
s
y
s
tem
[
9
]
,
[
1
0
]
.
T
h
is
ap
p
r
o
ac
h
im
p
r
o
v
es th
e
e
f
f
icien
cy
o
f
d
e
v
elo
p
in
g
a
s
im
u
latio
n
m
o
d
el
[
1
1
]
.
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.
25
,
No
.
1
,
J
an
u
ar
y
20
22
:
561
-
5
6
8
562
Fo
r
th
e
p
ast
d
ec
ad
e,
th
e
r
ec
o
n
ciliatio
n
o
f
g
eo
g
r
a
p
h
ical
i
n
f
o
r
m
atio
n
s
y
s
tem
(
GI
S)
with
n
atu
r
al
d
em
o
n
s
tr
atin
g
h
as
b
ec
o
m
e
a
s
ig
n
if
ican
t
ex
p
lo
r
atio
n
th
em
e.
T
h
e
u
tili
za
tio
n
o
f
GI
S
f
o
r
d
em
o
n
s
tr
atin
g
g
i
v
es
s
tr
aig
h
tf
o
r
war
d
n
ess
an
d
ex
ac
t
n
ess
in
th
e
ad
m
in
is
tr
atio
n
an
d
s
p
atial
p
o
r
tr
ay
al
o
f
in
f
o
r
m
atio
n
[
1
2
]
.
T
h
e
u
s
ed
o
f
GI
S in
s
im
u
latin
g
d
ata
was a
lr
ea
d
y
p
r
o
v
en
to
b
e
e
f
f
icien
t a
n
d
ef
f
ec
tiv
e
f
o
r
m
o
n
ito
r
in
g
[
1
3
]
,
[
1
4
]
.
Ma
ch
in
e
lear
n
in
g
a
n
d
d
ee
p
l
ea
r
n
in
g
alg
o
r
ith
m
s
wer
e
co
n
s
is
ten
tly
u
s
ed
f
o
r
ef
f
ec
tiv
e
m
o
d
ellin
g
,
f
o
r
ec
asti
n
g
an
d
class
if
y
in
g
d
ata
[
1
5
]
.
T
h
e
u
tili
za
tio
n
o
f
a
m
ac
h
in
e
lear
n
in
g
al
g
o
r
ith
m
is
p
o
p
u
lar
in
th
e
d
ev
elo
p
m
e
n
t
o
f
ar
tific
ial
in
tellig
en
ce
f
o
r
co
m
p
u
ter
s
y
s
tem
s
[
1
4
]
,
[
1
6
]
,
[
1
7
]
.
Ma
ch
in
e
lea
r
n
in
g
was
u
s
ed
in
d
if
f
er
en
t
d
is
cip
lin
e
s
u
ch
as
f
i
r
e
in
cid
en
ts
,
h
ea
lth
,
ed
u
c
atio
n
an
d
ev
e
n
in
en
v
ir
o
n
m
en
tal
m
o
d
ellin
g
.
W
ith
th
is
tech
n
o
lo
g
y
,
i
t
is
p
o
s
s
ib
le
to
p
r
o
v
id
e
d
e
cisi
o
n
m
ak
in
g
th
r
o
u
g
h
p
atter
n
r
ec
o
g
n
itio
n
an
d
t
im
e
s
er
ies
an
aly
s
i
s
[
1
8
]
-
[
2
0
]
.
R
ec
u
r
r
e
n
t
n
eu
r
al
n
etwo
r
k
s
(
R
NNs)
ar
e
d
esig
n
e
d
to
o
p
er
ate
u
p
o
n
s
eq
u
en
ce
s
o
f
d
ata.
T
h
ey
h
av
e
p
r
o
v
e
n
to
b
e
v
er
y
ef
f
ec
tiv
e
f
o
r
n
atu
r
al
lan
g
u
ag
e
p
r
o
ce
s
s
in
g
p
r
o
b
lem
s
wh
er
e
s
eq
u
en
ce
s
o
f
tex
t
ar
e
p
r
o
v
id
e
d
as
in
p
u
t
to
th
e
m
o
d
el.
R
NNs
h
av
e
also
s
ee
n
s
o
m
e
m
o
d
est
s
u
cc
ess
f
o
r
tim
e
s
er
ie
s
f
o
r
ec
asti
n
g
an
d
s
p
ee
ch
r
ec
o
g
n
itio
n
[
2
1
]
.
T
h
is
p
ap
er
m
ain
ly
aim
s
to
d
ev
elo
p
an
in
tellig
en
t
aq
u
ac
u
ltu
r
e
s
y
s
tem
f
o
r
p
is
cicu
ltu
r
e
s
im
u
l
atio
n
u
s
in
g
d
ee
p
lear
n
in
g
alg
o
r
ith
m
.
2.
M
E
T
H
O
DO
L
O
G
Y
I
n
d
ev
el
o
p
in
g
th
e
s
y
s
tem
,
s
o
f
twar
e
d
ev
el
o
p
m
en
t
life
cy
cle
was
ad
o
p
ted
an
d
m
o
d
if
i
ed
.
B
ef
o
r
e
id
en
tify
in
g
wo
r
k
s
f
o
r
ea
c
h
p
h
ase,
a
s
y
s
tem
a
r
ch
itectu
r
e
was
cr
ea
ted
to
h
a
v
e
a
clea
r
v
is
u
aliza
tio
n
o
f
th
e
p
r
o
ject.
I
t
is
s
h
o
wn
in
F
ig
u
r
e
1
th
at
th
e
in
tellig
en
t
aq
u
ac
u
l
tu
r
e
s
y
s
tem
is
co
n
s
is
ts
o
f
f
o
u
r
(
4
)
m
ai
n
m
o
d
u
les
s
u
ch
as
u
s
er
m
an
ag
e
m
en
t m
o
d
u
le,
m
o
n
ito
r
in
g
m
o
d
u
le,
ca
g
e
m
an
ag
em
en
t
m
o
d
u
le
an
d
GI
S
mo
d
u
le.
Fig
u
r
e
1
.
Sy
s
tem
a
r
c
h
itectu
r
e
2
.
1
.
P
l
a
nn
ing
a
nd
da
t
a
g
a
t
h
er
ing
All
th
e
r
eq
u
ir
ed
m
ate
r
ials
wer
e
id
en
tifie
d
in
th
is
p
h
as
e
s
u
ch
as
d
ata,
s
o
f
twar
e
an
d
h
ar
d
war
e
r
eq
u
ir
em
e
n
ts
.
An
in
ter
v
iew
to
th
e
B
u
r
ea
u
o
f
f
is
h
er
ies an
d
aq
u
atic
r
eso
u
r
ce
s
I
V
-
A
-
p
r
o
tecte
d
ar
ea
m
an
ag
em
en
t
b
o
ar
d
(
B
FAR
I
VA
-
PAMB
)
was
co
n
d
u
cted
to
u
n
d
er
s
tan
d
th
eir
in
f
o
r
m
atio
n
g
ath
e
r
in
g
an
d
p
r
o
ce
s
s
in
g
.
T
h
e
r
esu
lt
o
f
in
ter
v
iew
is
u
s
ed
as
b
asis
f
o
r
d
ev
elo
p
in
g
t
h
e
in
tell
ig
en
t
s
y
s
tem
.
Fo
r
m
o
d
el
d
ev
e
lo
p
m
en
t,
th
e
th
r
ee
(
3
)
y
ea
r
s
r
ec
o
r
d
s
o
f
PAMB
wer
e
co
llected
.
T
h
e
attr
ib
u
t
es
in
s
id
e
th
e
d
atab
ase
we
r
e
all
co
n
s
id
er
e
d
f
o
r
f
o
r
e
ca
s
tin
g
o
r
tim
e
s
er
ies
an
al
y
s
is
.
T
ab
le
1
r
ep
r
esen
ts
th
e
attr
ib
u
tes
an
d
its
d
escr
ip
tio
n
an
d
will
b
e
u
s
ed
as
th
e
d
ataset
f
o
r
m
o
d
el
d
e
v
elo
p
m
e
n
t.
L
ik
ewise,
th
e
em
p
lo
y
ee
s
o
f
th
e
s
aid
d
ep
ar
tm
e
n
t
wer
e
th
e
o
n
es
to
ev
alu
ate
th
e
d
ev
elo
p
e
d
an
d
s
y
s
tem
f
o
r
u
s
ab
ilit
y
an
d
ac
ce
p
ta
b
ilit
y
test
in
g
.
Fig
u
r
e
2
is
u
s
ed
as
r
ep
r
esen
t
atio
n
o
f
m
o
d
u
les
in
ter
ac
tio
n
in
ev
er
y
tar
g
et
u
s
er
o
f
t
h
e
s
y
s
tem
.
I
t
is
s
h
o
wn
in
th
e
f
ig
u
r
e
t
h
at
th
e
ad
m
in
is
tr
ato
r
o
r
th
e
B
u
r
ea
u
o
f
f
is
h
er
ies
an
d
aq
u
atic
r
eso
u
r
ce
s
(
B
FAR
)
was
ca
p
ab
le
o
f
ac
ce
s
s
in
g
ea
ch
m
o
d
u
le
in
clu
d
e
d
in
th
e
s
y
s
tem
.
Hen
ce
,
th
e
u
s
er
s
o
r
th
e
f
is
h
ca
g
e
o
p
er
ato
r
ca
n
o
n
ly
ac
ce
s
s
th
e
f
is
h
ca
g
e
m
an
ag
em
en
t
m
o
d
u
le.
Ho
wev
e
r
,
th
e
f
is
h
ca
g
e
o
p
er
ato
r
is
s
till
ca
p
a
b
le
o
f
v
iewin
g
th
e
g
eo
g
r
a
p
h
ical
r
e
p
r
esen
tatio
n
s
tatu
s
o
f
T
aa
l
lak
e
b
u
t
was
n
o
t
allo
wed
to
ed
it.
T
h
e
u
s
e
ca
s
e
d
iag
r
am
p
r
o
v
id
es
a
g
r
ea
t h
elp
in
th
e
d
e
v
elo
p
m
e
n
t
o
f
th
e
s
y
s
tem
.
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
n
tellig
en
t a
q
u
a
cu
ltu
r
e
s
ystem
fo
r
p
is
cicu
ltu
r
e
s
imu
la
tio
n
u
s
in
g
d
ee
p
lea
r
n
in
g
a
lg
o
r
ith
m
(
S
h
erw
in
B
.
S
a
p
in
)
563
T
ab
le
1
.
Attr
ib
u
tes o
f
d
ata
f
r
o
m
PAMB
d
atab
ase
A
t
t
r
i
b
u
t
e
s
D
e
scri
p
t
i
o
n
s
D
i
sast
e
r
T
y
p
e
Ty
p
e
s
o
f
D
i
sas
t
e
r
K
i
n
d
s
o
f
S
p
e
c
i
e
s
F
i
sh
sp
e
c
i
e
s
A
mo
u
n
t
o
f
D
a
ma
g
e
Ex
a
c
t
n
u
m
b
e
r
o
f
d
a
m
a
g
e
s
Lo
c
a
t
i
o
n
B
a
r
a
n
g
a
y
A
r
e
a
Fig
u
r
e
2
.
Pis
cicu
ltu
r
e
web
s
y
s
tem
u
s
e
ca
s
e
d
iag
r
am
2
.
2
.
St
a
t
is
t
ica
l
t
re
a
t
m
ent
L
ik
er
t
s
ca
lar
tech
n
iq
u
e
is
u
s
e
d
to
m
ea
s
u
r
e
th
e
c
h
ar
ac
ter
is
tics
o
f
t
h
e
in
tellig
en
t
s
y
s
tem
.
T
h
e
s
u
r
v
ey
q
u
esti
o
n
n
air
es
wer
e
an
s
wer
ed
b
y
f
o
u
r
d
if
f
e
r
en
t
r
esp
o
n
s
es
o
r
im
p
r
ess
io
n
s
ac
co
r
d
in
g
to
its
i
n
ten
s
ity
,
m
ea
s
u
r
e
d
b
y
:
f
o
u
r
(
4
)
s
tr
o
n
g
ly
ac
ce
p
tab
le,
th
r
ee
(
3
)
ac
ce
p
tab
le,
two
(
2
)
d
is
ag
r
ee
an
d
o
n
e
(
1
)
as
s
tr
o
n
g
ly
d
is
ag
r
ee
as
s
h
o
wn
in
T
a
b
le
2
.
T
h
e
u
n
d
e
cid
ed
o
r
th
e
u
n
ce
r
tain
r
esp
o
n
s
e
was
elim
in
ated
in
th
e
i
m
p
r
ess
io
n
s
to
av
o
id
p
ar
tialiti
es a
n
d
co
n
f
u
s
io
n
s
o
f
d
ata.
T
ab
le
2
.
L
ik
e
r
t
s
ca
le
R
a
t
i
n
g
M
e
a
n
R
a
n
g
e
I
n
t
e
r
p
r
e
t
a
t
i
o
n
4
3
.
5
1
-
4
.
0
0
S
t
r
o
n
g
l
y
a
c
c
e
p
t
a
b
l
e
3
2
.
5
1
-
3
.
5
0
A
c
c
e
p
t
a
b
l
e
2
1
.
5
1
-
2
.
5
0
D
i
sag
r
e
e
1
1
.
0
-
1
.
5
0
S
t
r
o
n
g
l
y
d
i
sa
g
r
e
e
2
.
3
.
M
o
del dev
elo
pm
ent
A
m
o
d
el
was
d
ev
elo
p
ed
b
y
m
o
d
if
y
in
g
th
e
s
tag
e
o
f
k
n
o
wl
ed
g
e
d
is
co
v
er
y
in
d
atab
ases
(
KDD)
.
T
h
e
ty
p
ical
s
tag
e
o
f
th
e
KDD
m
o
d
el
was
tr
im
m
ed
in
to
th
r
ee
(
3
)
p
h
ases
n
am
ely
;
s
elec
tio
n
,
p
r
ep
r
o
ce
s
s
in
g
an
d
k
n
o
wled
g
e
d
ev
elo
p
m
en
t.
T
h
is
m
o
d
el
is
in
teg
r
ated
to
th
e
s
y
s
t
em
u
s
in
g
ten
s
o
r
f
l
o
w
an
d
k
er
as
.
2
.
3
.
1
.
Select
io
n
I
n
s
elec
tio
n
s
tag
e,
th
e
d
ataset
s
h
o
wn
in
T
ab
le
1
was
u
s
ed
.
Sin
ce
th
e
d
ataset
is
r
ea
l
in
n
atu
r
e,
th
e
p
o
s
s
ib
le
r
esu
lt
o
f
m
o
d
el
d
ev
elo
p
m
en
t
is
r
eliab
le
en
o
u
g
h
to
in
teg
r
ate
in
th
e
in
tellig
e
n
t
s
y
s
tem
.
All
th
e
attr
ib
u
tes s
h
o
wn
in
T
ab
le
1
ar
e
co
n
s
id
er
ed
i
n
d
ev
el
o
p
in
g
th
e
m
o
d
el.
2
.
3
.
2
.
P
re
pro
ce
s
s
ing
T
h
e
d
ataset
was
f
ir
s
t
u
n
d
er
g
o
n
e
clea
n
in
g
wh
er
ein
ea
ch
in
s
t
an
ce
was
tr
an
s
f
o
r
m
ed
in
to
lo
wer
ca
s
e
to
m
ak
e
s
u
r
e
t
h
at
th
er
e
was
n
o
n
o
is
e
in
q
u
an
tif
y
in
g
ea
ch
d
ata.
Sp
ec
ial
ch
ar
ac
t
er
s
s
u
ch
as
wh
ite
s
p
ac
e
an
d
s
y
m
b
o
ls
wer
e
also
r
em
o
v
ed
to
m
ak
e
a
m
o
r
e
m
ea
n
i
n
g
f
u
l
d
ata
.
Fu
r
th
er
,
all
th
e
s
tr
in
g
s
d
ata
wer
e
co
n
v
e
r
ted
in
to
in
teg
er
to
m
ak
e
it e
asier
to
m
ac
h
in
e
to
an
aly
ze
d
th
e
d
ataset.
L
astl
y
,
th
e
d
ataset
was d
iv
id
e
d
in
to
two
p
ar
ts
,
th
e
tr
ain
d
ataset
an
d
th
e
test
d
atas
et
wh
er
ea
s
th
e
tr
ain
d
ataset
i
s
th
e
8
0
%
o
f
th
e
d
ataset
wh
ile
t
h
e
r
em
ain
in
g
2
0
%
is
u
s
ed
as th
e
test
d
ataset.
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.
25
,
No
.
1
,
J
an
u
ar
y
20
22
:
561
-
5
6
8
564
2
.
3
.
3
.
K
no
wledg
e
dev
elo
pm
e
nt
Sin
ce
th
e
r
ec
u
r
r
en
t
n
eu
r
al
n
etwo
r
k
was
alr
ea
d
y
p
r
o
v
en
ef
f
e
ctiv
e
in
tim
e
s
er
ies
an
aly
s
is
[
1
4
]
,
[
1
8
]
,
it
was
ch
o
s
en
in
th
is
p
r
o
ject
as
th
e
d
ee
p
lear
n
in
g
alg
o
r
ith
m
t
o
u
s
e
in
k
n
o
wled
g
e
d
ev
elo
p
m
en
t.
R
NN
is
th
o
u
g
h
t
f
o
r
m
a
n
ag
in
g
s
eq
u
en
tial
s
tatis
tics
.
I
t
is
a
s
o
r
t
o
f
n
e
u
r
al
n
et
wo
r
k
th
at
h
as
a
“m
em
o
r
y
”
w
h
ich
r
em
em
b
er
s
all
in
f
o
r
m
atio
n
ap
p
r
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ay
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ases
[
2
2
]
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[
2
4
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.
Fig
u
r
e
3
s
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r
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u
r
e
3
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R
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u
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4
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1
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4
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ik
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u
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5
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Dash
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u
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6
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ig
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I
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CO
NCLU
SI
O
NAN
D
F
UT
U
RE
WO
RK
S
As
p
r
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v
e
n
b
y
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th
er
r
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ch
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s
f
o
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n
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ap
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,
th
e
r
ec
u
r
r
en
t
n
eu
r
al
n
etwo
r
k
(
R
NN)
was
a
g
o
o
d
d
ee
p
lear
n
in
g
alg
o
r
ith
m
f
o
r
tim
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is
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r
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r
a
p
h
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i
n
f
o
r
m
atio
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s
y
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tem
(
GI
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was
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s
p
icio
u
s
tech
n
o
lo
g
y
th
at
ca
n
b
e
u
s
ed
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ata
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d
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s
im
u
latio
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cr
ea
te
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m
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e
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icien
t d
ata
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aly
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is
.
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p
is
cicu
ltu
r
e
in
tellig
en
t
s
y
s
te
m
is
n
ee
d
ed
an
d
ac
ce
p
tab
le
to
an
o
r
g
a
n
izatio
n
th
at
was
m
ai
n
tain
in
g
a
lak
e’
s
en
v
ir
o
n
m
en
tal
s
tatu
s
th
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u
g
h
ef
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icien
t a
n
d
e
f
f
ec
tiv
e
m
o
n
ito
r
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g
.
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t
is
s
u
g
g
ested
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h
at
th
e
d
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ed
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tem
m
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s
t b
e
im
p
lem
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ted
in
th
e
B
FAR
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V
-
A
to
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elp
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em
m
o
n
ito
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th
e
T
aa
l
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e.
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ik
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th
e
u
s
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e
o
f
d
ee
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lear
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o
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ith
m
,
R
NN
in
p
ar
ticu
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m
u
s
t
b
e
p
r
ac
tice
in
in
f
o
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m
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th
at
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s
tatu
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th
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h
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ata
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im
u
latio
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.
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astl
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th
e
au
th
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f
th
is
p
ap
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r
wo
u
ld
lik
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to
g
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s
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f
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im
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al
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ce
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o
f
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est.
ACK
NO
WL
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DG
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T
h
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iece
o
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k
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m
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lis
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ed
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o
u
t
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o
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th
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L
ag
u
n
a
State
P
o
ly
tech
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ic
Un
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ity
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d
th
e
B
u
r
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o
f
Fis
h
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atic
R
e
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s
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Pro
tectiv
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Ar
ea
Ma
n
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en
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o
ar
d
(
B
FAR
-
PAMB)
R
eg
io
n
I
V
-
A
an
d
s
o
,
th
e
au
th
o
r
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wer
e
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leh
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te
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ly
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ten
d
i
n
g
th
eir
p
r
o
f
o
u
n
d
g
r
atitu
d
e
to
th
e
s
aid
o
r
g
an
izatio
n
s
.
RE
F
E
R
E
NC
E
S
[
1
]
K
.
Y
u
e
a
n
d
Y
.
S
h
e
n
,
“
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n
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a
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d
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tern
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l
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n
a
ls
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sb
sa
p
i
n
@lsp
u
.
e
d
u
.
p
h
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
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4
7
5
2
I
n
d
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n
esian
J
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lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
25
,
No
.
1
,
J
an
u
ar
y
20
22
:
561
-
5
6
8
568
Br
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A.
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h
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.
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ra
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stu
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rsity
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to
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e
c
a
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tl
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c
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c
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t
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m
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il
:
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m
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h
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s
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m
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rre
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tl
y
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s
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m
p
u
s,
M
a
li
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ta,
Lo
s
Ba
ñ
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s
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La
g
u
n
a
,
P
h
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p
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n
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s.
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rc
h
stu
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y
f
o
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s
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t
h
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ti
m
iza
ti
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n
a
n
d
u
sa
g
e
o
f
m
a
c
h
in
e
lea
rn
i
n
g
a
lg
o
rit
h
m
a
n
d
k
n
o
wle
d
g
e
d
isc
o
v
e
ry
in
d
a
tab
a
se
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
so
r.
jo
n
a
rd
o
@lsp
u
.
e
d
u
.
p
h
Evaluation Warning : The document was created with Spire.PDF for Python.