I
AE
S In
t
er
na
t
io
na
l J
o
urna
l o
f
Art
if
icia
l In
t
ellig
ence
(
I
J
-
AI
)
Vo
l.
14
,
No
.
4
,
A
u
g
u
s
t 2
0
2
5
,
p
p
.
3
4
7
4
~
3
4
8
2
I
SS
N:
2
2
5
2
-
8938
,
DOI
: 1
0
.
1
1
5
9
1
/i
j
ai.
v
14
.i
4
.
p
p
3
4
7
4
-
3
4
8
2
3474
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
i
.
ia
esco
r
e.
co
m
G
enera
tive Indo
n
esia
n chatbo
t
for
univ
ersity
m
a
jor
selection
using
t
ra
nsfo
r
m
e
rs e
m
beddi
ng
M
utia
r
a
Auliy
a
K
ha
dija
1
,
B
a
m
ba
ng
H
a
rj
it
o
2
,
M
o
rt
ez
a
S
a
beri
3
,
Astr
id No
v
ia
na
P
a
ra
dh
it
a
1
,
Wa
hy
u
Nurha
rj
a
d
m
o
4
1
V
o
c
a
t
i
o
n
a
l
S
c
h
o
o
l
,
U
n
i
v
e
r
si
t
a
s Se
b
e
l
a
s
M
a
r
e
t
,
S
u
r
a
k
a
r
t
a
,
I
n
d
o
n
e
si
a
2
D
e
p
a
r
t
me
n
t
o
f
I
n
f
o
r
mat
i
c
s
,
F
a
c
u
l
t
y
o
f
I
n
f
o
r
mat
i
o
n
T
e
c
h
n
o
l
o
g
y
a
n
d
D
a
t
a
S
c
i
e
n
c
e
,
U
n
i
v
e
r
si
t
a
s Se
b
e
l
a
s M
a
r
e
t
,
S
u
r
a
k
a
r
t
a
,
I
n
d
o
n
e
si
a
3
S
c
h
o
o
l
o
f
C
o
mp
u
t
e
r
S
c
i
e
n
c
e
,
U
n
i
v
e
r
si
t
y
o
f
Te
c
h
n
o
l
o
g
y
S
y
d
n
e
y
,
S
y
d
n
e
y
,
A
u
st
r
a
l
i
a
4
D
e
p
a
r
t
me
n
t
o
f
P
u
b
l
i
c
A
d
mi
n
i
st
r
a
t
i
o
n
,
F
a
c
u
l
t
y
o
f
S
o
c
i
a
l
a
n
d
P
o
l
i
t
i
c
a
l
S
c
i
e
n
c
e
s,
U
n
i
v
e
r
si
t
a
s Se
b
e
l
a
s
M
a
r
e
t
,
S
u
r
a
k
a
r
t
a
,
I
n
d
o
n
e
si
a
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Au
g
6
,
2
0
2
4
R
ev
i
s
ed
J
u
n
2
4
,
2
0
2
5
A
cc
ep
ted
J
u
l 1
3
,
2
0
2
5
S
e
lec
ti
n
g
a
u
n
iv
e
rsity
m
a
jo
r
is a cru
c
ial
d
e
c
isio
n
th
a
t
im
p
a
c
ts stu
d
e
n
ts'
f
u
tu
re
c
a
re
e
r
p
a
th
s
a
n
d
p
e
rso
n
a
l
f
u
lf
il
lme
n
t.
T
ra
d
it
io
n
a
l
g
u
id
a
n
c
e
m
e
th
o
d
s
o
f
ten
lac
k
th
e
p
e
rso
n
a
li
z
a
ti
o
n
a
n
d
ti
m
e
li
n
e
ss
n
e
e
d
e
d
to
su
p
p
o
r
t
stu
d
e
n
ts
e
ffe
c
ti
v
e
l
y
.
T
h
is
stu
d
y
e
x
p
lo
re
s
t
h
e
u
se
o
f
In
d
o
n
e
sia
n
g
e
n
e
ra
ti
v
e
a
rti
f
icia
l
in
telli
g
e
n
c
e
(
AI
)
c
h
a
tb
o
ts
a
n
d
tran
sf
o
rm
e
r
e
m
b
e
d
d
in
g
s
to
e
n
h
a
n
c
e
d
e
c
isio
n
-
m
a
k
in
g
f
o
r
u
n
iv
e
rsity
m
a
jo
r
se
lec
ti
o
n
.
By
lev
e
ra
g
in
g
a
d
v
a
n
c
e
d
A
I
tec
h
n
iq
u
e
s,
su
c
h
a
s
b
i
d
irec
ti
o
n
a
l
e
n
c
o
d
e
r
re
p
re
se
n
tatio
n
s
f
ro
m
tra
n
sf
o
rm
e
r
s
(
BERT
)
a
n
d
G
e
m
in
i
e
m
b
e
d
d
in
g
s,
th
e
re
se
a
r
c
h
a
i
m
s
to
p
ro
v
id
e
p
e
rso
n
a
li
z
e
d
,
in
tera
c
ti
v
e
,
a
n
d
c
o
n
tex
tu
a
ll
y
re
l
e
v
a
n
t
g
u
id
a
n
c
e
.
Ex
p
e
rim
e
n
ts
sh
o
w
e
d
th
a
t
BERT
e
m
b
e
d
d
in
g
s
a
c
h
iev
e
d
th
e
h
ig
h
e
st
a
c
c
u
ra
c
y
,
w
it
h
re
c
u
rre
n
t
n
e
u
ra
l
n
e
tw
o
rk
(RNN
)
a
n
d
lo
n
g
sh
o
rt
-
term
m
e
m
o
r
y
(
L
S
T
M
)
m
o
d
e
ls
a
lso
p
e
rf
o
r
m
in
g
w
e
ll
b
u
t
f
a
c
in
g
is
s
u
e
s
w
it
h
o
v
e
rf
it
ti
n
g
.
G
e
m
in
i
e
m
b
e
d
d
in
g
s
p
ro
v
id
e
d
stro
n
g
p
e
rf
o
rm
a
n
c
e
b
u
t
slig
h
tl
y
les
s
e
ff
e
c
ti
v
e
th
a
n
BERT
.
T
h
e
f
in
d
in
g
s
su
g
g
e
st
th
a
t
BERT
-
b
a
se
d
m
o
d
e
ls
w
it
h
RNN
a
re
su
p
e
rio
r
f
o
r
d
e
v
e
lo
p
in
g
d
e
c
isio
n
-
su
p
p
o
rt
sy
st
e
m
s
in
9
2
%
a
c
c
u
ra
c
y
.
F
u
tu
re
w
o
rk
sh
o
u
l
d
f
o
c
u
s
o
n
f
u
rt
h
e
r
o
p
ti
m
iza
ti
o
n
a
n
d
in
teg
ra
ti
o
n
o
f
u
se
r
f
e
e
d
b
a
c
k
to
e
n
su
re
t
h
e
re
lev
a
n
c
e
a
n
d
e
ffe
c
ti
v
e
n
e
s
s o
f
th
e
se
A
I
to
o
ls i
n
e
d
u
c
a
ti
o
n
a
l
se
tt
in
g
s
.
K
ey
w
o
r
d
s
:
A
I
ch
a
tb
o
ts
B
E
R
T
Ge
m
i
n
i e
m
b
ed
d
in
g
T
r
an
s
f
o
r
m
er
s
e
m
b
ed
d
in
g
s
Un
i
v
er
s
it
y
m
aj
o
r
s
elec
tio
n
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Mu
tiar
a
Au
li
y
a
K
h
ad
ij
a
Vo
ca
tio
n
al
Sch
o
o
l,
Un
iv
er
s
ita
s
Seb
elas
Ma
r
et
Su
r
ak
ar
ta,
I
n
d
o
n
e
s
ia
E
m
ail:
m
u
tiar
aa
u
l
i
y
a
@
s
taf
f
.
u
n
s
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
C
h
o
o
s
i
n
g
a
u
n
i
v
er
s
i
t
y
m
aj
o
r
is
o
n
e
o
f
t
h
e
m
o
s
t
cr
itica
l
d
ec
is
io
n
s
s
t
u
d
en
t
s
f
ac
e
i
n
t
h
eir
ac
ad
em
ic
j
o
u
r
n
e
y
,
s
ig
n
i
f
ica
n
tl
y
i
m
p
ac
ti
n
g
t
h
eir
f
u
t
u
r
e
ca
r
ee
r
p
ath
s
an
d
p
er
s
o
n
al
f
u
lf
i
ll
m
en
t.
Ho
wev
er
,
th
e
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
is
o
f
te
n
co
m
p
lex
an
d
f
r
au
g
h
t
w
it
h
u
n
ce
r
t
ain
tie
s
,
as
s
t
u
d
en
t
s
m
u
s
t
n
av
i
g
ate
a
m
u
l
tit
u
d
e
o
f
f
ac
to
r
s
i
n
cl
u
d
in
g
th
eir
in
ter
ests
,
s
tr
en
g
t
h
s
,
j
o
b
m
ar
k
et
tr
en
d
s
,
a
n
d
ac
ad
e
m
ic
r
eq
u
ir
e
m
en
ts
[
1
]
.
W
h
ile
tr
ad
itio
n
al
g
u
id
an
ce
m
et
h
o
d
s
,
s
u
c
h
as
co
u
n
s
eli
n
g
s
es
s
io
n
s
an
d
in
f
o
r
m
atio
n
al
r
eso
u
r
ce
s
,
h
av
e
b
ee
n
w
id
el
y
u
s
ed
,
th
e
y
o
f
te
n
lack
p
er
s
o
n
al
izatio
n
an
d
r
ea
l
-
ti
m
e
s
u
p
p
o
r
t,
leav
i
n
g
s
tu
d
e
n
ts
to
m
a
k
e
d
ec
is
io
n
s
t
h
at
m
a
y
n
o
t
f
u
ll
y
a
lig
n
w
i
th
t
h
eir
lo
n
g
-
ter
m
g
o
al
s
.
R
ec
e
n
t
ad
v
a
n
ce
m
en
ts
in
ar
ti
f
ic
ial
in
telli
g
en
ce
(
AI
)
o
f
f
er
p
r
o
m
is
i
n
g
s
o
lu
tio
n
s
to
en
h
a
n
ce
t
h
e
d
ec
is
io
n
-
m
a
k
i
n
g
p
r
o
ce
s
s
f
o
r
s
t
u
d
en
ts
.
I
n
t
h
is
s
t
u
d
y
,
w
e
i
n
tr
o
d
u
ce
a
n
o
v
e
l
g
en
er
at
iv
e
A
I
c
h
atb
o
t
s
p
ec
i
f
icall
y
d
es
ig
n
ed
f
o
r
I
n
d
o
n
esia
n
s
t
u
d
en
t
s
,
le
v
er
ag
i
n
g
s
ta
te
-
of
-
th
e
-
ar
t
tr
a
n
s
f
o
r
m
er
e
m
b
ed
d
in
g
s
(
b
id
ir
ec
tio
n
al
en
co
d
er
r
ep
r
esen
tatio
n
s
f
r
o
m
tr
an
s
f
o
r
m
er
s
(
B
E
R
T
)
an
d
Ge
m
in
i)
to
p
r
o
v
id
e
p
er
s
o
n
alize
d
,
in
ter
ac
ti
v
e,
an
d
co
n
te
x
tu
a
ll
y
r
elev
an
t
g
u
id
a
n
ce
[
2
]
.
Un
lik
e
ex
i
s
ti
n
g
s
y
s
te
m
s
,
o
u
r
a
p
p
r
o
ac
h
co
m
b
in
e
s
ad
v
an
ce
d
n
at
u
r
al
lan
g
u
ag
e
p
r
o
ce
s
s
in
g
(
N
L
P
)
tech
n
i
q
u
e
s
w
i
th
a
u
s
er
-
f
r
ien
d
l
y
in
ter
f
ac
e
tai
lo
r
ed
to
th
e
u
n
iq
u
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Gen
era
tive
I
n
d
o
n
esia
n
ch
a
t
b
o
t fo
r
u
n
ivers
ity
ma
jo
r
s
elec
tio
n
u
s
in
g
tr
a
n
s
fo
r
mers
…
(
Mu
ti
a
r
a
A
u
liya
K
h
a
d
ija
)
3475
n
ee
d
s
o
f
I
n
d
o
n
esia
n
s
t
u
d
en
t
s
,
en
ab
lin
g
m
o
r
e
ac
cu
r
ate
an
d
m
ea
n
i
n
g
f
u
l
r
ec
o
m
m
en
d
atio
n
s
.
B
y
in
te
g
r
ati
n
g
tr
an
s
f
o
r
m
er
-
b
a
s
ed
m
o
d
els,
s
u
ch
as
B
E
R
T
an
d
Ge
m
i
n
i,
o
u
r
ch
atb
o
t
ca
n
s
i
m
u
late
h
u
m
a
n
-
li
k
e
in
ter
ac
tio
n
s
a
n
d
ad
ap
t
its
r
esp
o
n
s
es
to
th
e
in
d
iv
id
u
al
p
r
ef
er
en
ce
s
an
d
ac
ad
em
ic
b
ac
k
g
r
o
u
n
d
s
o
f
ea
ch
s
tu
d
e
n
t,
o
f
f
er
i
n
g
a
s
ig
n
i
f
ica
n
t i
m
p
r
o
v
e
m
e
n
t
o
v
er
tr
ad
itio
n
al
m
et
h
o
d
[
3
]
.
T
r
an
s
f
o
r
m
er
s
,
a
clas
s
o
f
d
ee
p
lear
n
in
g
m
o
d
els
k
n
o
w
n
f
o
r
th
eir
ef
f
ec
ti
v
e
n
es
s
in
N
L
P
tas
k
s
,
p
la
y
a
cr
u
cial
r
o
le
i
n
i
m
p
r
o
v
in
g
th
e
ac
cu
r
ac
y
an
d
r
ele
v
an
ce
o
f
A
I
-
d
r
iv
e
n
g
u
id
a
n
ce
s
y
s
te
m
s
.
Gu
id
eli
n
es
f
o
r
lev
er
ag
i
n
g
g
e
n
er
ati
v
e
A
I
m
o
d
els
em
p
h
asize
t
h
eir
ca
p
ab
ilit
ies
in
ad
d
r
ess
i
n
g
ac
ad
em
ic
i
n
teg
r
it
y
w
h
ile
au
g
m
e
n
ti
n
g
p
r
e
-
ex
i
s
ti
n
g
ch
at
b
o
ts
.
Dev
elo
p
in
g
an
d
r
ef
in
i
n
g
p
r
o
m
p
ts
to
g
u
id
e
C
h
a
tGP
T
i
n
p
r
o
v
id
in
g
p
r
ec
is
e
s
tatis
t
ical
te
s
t
s
u
g
g
esti
o
n
s
[
4
]
.
T
h
e
s
tu
d
y
u
n
d
er
s
co
r
es
t
h
e
p
o
ten
tial
o
f
A
I
c
h
atb
o
ts
a
s
v
al
u
ab
le
r
eso
u
r
ce
s
f
o
r
s
tu
d
e
n
ts
,
esp
ec
iall
y
t
h
o
s
e
w
i
th
li
m
ited
ex
p
er
ien
ce
i
n
s
tat
is
tics
,
b
y
s
i
m
p
li
f
y
i
n
g
t
h
e
p
r
o
ce
s
s
o
f
s
elec
ti
n
g
ap
p
r
o
p
r
iate
an
al
y
tical
m
eth
o
d
s
[
5
]
.
Gen
er
ativ
e
A
I
C
h
atGP
T
a
b
le
to
h
elp
ac
ad
em
ic
co
n
t
ex
ts
w
h
ile
s
tr
e
s
s
i
n
g
th
e
n
ee
d
f
o
r
eth
ical
co
n
s
id
er
atio
n
s
an
d
q
u
alit
y
co
n
tr
o
l
[
6
]
.
T
h
e
tr
an
s
f
o
r
m
ati
v
e
p
o
ten
tia
l
o
f
A
I
ch
atb
o
ts
i
n
ed
u
ca
tio
n
i
s
f
u
r
t
h
er
ex
p
lo
r
ed
th
r
o
u
g
h
t
h
e
d
ev
e
lo
p
m
en
t
o
f
a
b
len
d
ed
lear
n
in
g
f
r
a
m
e
w
o
r
k
.
T
h
is
f
r
a
m
e
w
o
r
k
in
te
g
r
ates
i
n
telli
g
e
n
t
ch
atb
o
ts
to
en
h
an
ce
s
tu
d
e
n
t
an
d
in
s
tr
u
cto
r
in
ter
ac
tio
n
s
,
ai
m
i
n
g
to
p
r
o
v
id
e
a
co
m
p
r
e
h
en
s
iv
e
u
n
d
er
s
ta
n
d
in
g
o
f
t
h
e
p
o
ten
tial
b
en
e
f
it
s
an
d
e
f
f
ec
tiv
e
i
m
p
le
m
e
n
tati
o
n
o
f
A
I
to
o
ls
i
n
ed
u
ca
tio
n
al
s
etti
n
g
s
.
T
h
e
p
r
o
p
o
s
ed
f
r
a
m
e
w
o
r
k
s
ee
k
s
to
ad
d
r
ess
th
e
c
h
allen
g
e
s
o
f
p
er
s
o
n
alize
d
lear
n
in
g
a
n
d
in
cr
ea
s
ed
i
n
s
tr
u
cto
r
w
o
r
k
lo
ad
b
y
le
v
er
ag
i
n
g
t
h
e
ca
p
ab
ilit
ie
s
o
f
g
en
er
ati
v
e
A
I
[
7
]
.
T
h
e
e
m
b
ed
d
in
g
tec
h
n
iq
u
e
s
u
s
ed
in
tr
an
s
f
o
r
m
er
s
en
ab
le
th
e
r
ep
r
esen
tatio
n
o
f
co
m
p
lex
r
elatio
n
s
h
ip
s
b
et
w
ee
n
w
o
r
d
s
an
d
co
n
ce
p
ts
,
allo
w
i
n
g
c
h
atb
o
ts
to
u
n
d
er
s
ta
n
d
an
d
p
r
o
ce
s
s
co
n
tex
t
m
o
r
e
ef
f
ec
ti
v
el
y
[
8
]
,
[
9
]
.
I
n
teg
r
atin
g
th
e
s
e
ad
v
a
n
ce
d
tech
n
iq
u
es
i
n
to
d
ec
is
io
n
-
s
u
p
p
o
r
t
to
o
ls
f
o
r
u
n
iv
er
s
it
y
m
aj
o
r
s
elec
tio
n
ca
n
p
o
ten
tiall
y
lea
d
to
m
o
r
e
in
f
o
r
m
ed
an
d
s
atis
f
y
in
g
c
h
o
ices
f
o
r
s
t
u
d
en
ts
.
C
h
o
o
s
in
g
a
u
n
i
v
er
s
it
y
m
aj
o
r
is
o
n
e
o
f
th
e
m
o
s
t
p
i
v
o
tal
d
ec
is
io
n
s
in
a
s
tu
d
e
n
t’
s
ac
ad
e
m
ic
ca
r
ee
r
,
s
h
ap
i
n
g
t
h
eir
ed
u
ca
t
io
n
al
tr
aj
ec
to
r
y
,
an
d
in
f
l
u
e
n
cin
g
f
u
tu
r
e
p
r
o
f
es
s
io
n
a
l
o
p
p
o
r
tu
n
itie
s
.
St
u
d
en
ts
o
f
te
n
f
ac
e
t
h
i
s
d
ec
is
io
n
w
i
th
li
m
ited
e
x
p
er
ien
ce
a
n
d
i
n
f
o
r
m
atio
n
t
h
at
ca
n
b
e
o
v
er
w
h
el
m
i
n
g
[
1
0
]
.
T
r
a
d
itio
n
al
m
et
h
o
d
s
o
f
ca
r
ee
r
co
u
n
s
eli
n
g
,
i
n
cl
u
d
in
g
f
ac
e
-
to
-
f
ac
e
m
e
etin
g
s
w
it
h
ad
v
is
o
r
s
an
d
s
ta
n
d
ar
d
ized
ass
es
s
m
e
n
t
t
o
o
ls
,
w
h
ile
u
s
e
f
u
l,
m
a
y
lac
k
t
h
e
d
y
n
a
m
ic
a
n
d
p
er
s
o
n
alize
d
ap
p
r
o
ac
h
n
ee
d
ed
to
a
d
d
r
ess
th
e
in
d
i
v
id
u
al
co
m
p
le
x
itie
s
o
f
ea
ch
s
t
u
d
en
t
’
s
s
i
tu
at
i
o
n
.
T
h
is
ca
n
r
es
u
lt
in
s
t
u
d
en
t
s
m
a
k
i
n
g
d
ec
is
io
n
s
th
at
d
o
n
o
t f
u
ll
y
ali
g
n
w
i
th
t
h
e
ir
in
ter
ests
,
s
tr
en
g
t
h
s
,
o
r
lo
n
g
-
t
er
m
ca
r
ee
r
g
o
als
[
1
1
]
.
T
h
e
in
teg
r
atio
n
o
f
g
en
er
ati
v
e
A
I
c
h
atb
o
ts
i
n
to
th
e
d
ec
i
s
io
n
-
m
a
k
i
n
g
p
r
o
ce
s
s
r
ep
r
esen
t
s
a
n
o
v
e
l
ap
p
r
o
ac
h
to
ad
d
r
ess
in
g
t
h
ese
ch
al
le
n
g
e
s
.
Ge
n
er
ati
v
e
A
I
,
p
a
r
ticu
lar
l
y
m
o
d
el
s
b
u
i
lt
o
n
ad
v
an
ce
d
tr
an
s
f
o
r
m
er
ar
ch
itect
u
r
es,
o
f
f
er
s
t
h
e
ab
ilit
y
to
s
i
m
u
late
h
u
m
a
n
-
lik
e
in
te
r
ac
tio
n
s
an
d
p
r
o
v
id
e
tailo
r
ed
ad
v
ice
b
ased
o
n
a
d
ee
p
u
n
d
er
s
ta
n
d
in
g
o
f
n
at
u
r
al
lan
g
u
a
g
e.
T
h
ese
c
h
atb
o
ts
ca
n
en
g
a
g
e
s
tu
d
e
n
ts
in
in
ter
ac
tiv
e
d
ialo
g
u
es,
h
elp
i
n
g
th
e
m
ex
p
lo
r
e
v
ar
io
u
s
m
aj
o
r
s
b
y
a
n
al
y
z
in
g
t
h
eir
r
esp
o
n
s
es,
p
r
ef
er
e
n
ce
s
,
a
n
d
asp
ir
atio
n
s
[
1
2
]
.
T
h
is
p
er
s
o
n
alize
d
in
ter
ac
tio
n
ca
n
p
o
ten
tiall
y
f
il
l
th
e
g
ap
s
le
f
t
b
y
tr
ad
itio
n
al
g
u
id
an
ce
m
et
h
o
d
s
an
d
o
f
f
er
a
m
o
r
e
n
u
a
n
ce
d
u
n
d
er
s
ta
n
d
i
n
g
o
f
th
e
o
p
tio
n
s
a
v
ailab
le.
T
r
an
s
f
o
r
m
er
-
b
ased
ar
ch
itec
tu
r
e
h
as
s
i
g
n
if
ica
n
tl
y
ad
v
a
n
ce
d
n
atu
r
al
la
n
g
u
a
g
e
p
r
o
ce
s
s
i
n
g
b
y
e
n
ab
li
n
g
m
o
r
e
n
u
an
ce
d
co
m
p
r
e
h
en
s
io
n
o
f
co
n
te
x
t
a
n
d
s
em
an
tics
[
1
3
]
.
T
h
ese
m
o
d
el
s
lev
er
a
g
e
e
m
b
ed
d
in
g
s
to
ca
p
tu
r
e
s
e
m
an
tic
r
elatio
n
s
h
ip
s
b
et
w
ee
n
co
n
ce
p
t
s
,
w
h
ich
e
n
h
an
ce
s
th
e
ch
atb
o
t’
s
ab
ilit
y
to
p
r
o
v
id
e
r
elev
an
t
an
d
co
n
te
x
tu
al
l
y
ap
p
r
o
p
r
iate
ad
v
ice.
B
y
e
m
b
ed
d
in
g
k
n
o
w
led
g
e
f
r
o
m
v
ar
io
u
s
d
o
m
ai
n
s
,
i
n
cl
u
d
in
g
ac
ad
em
ic
d
is
cip
li
n
es
a
n
d
ca
r
ee
r
p
ath
w
a
y
s
,
A
I
c
h
atb
o
ts
ca
n
o
f
f
er
in
s
i
g
h
ts
th
at
ar
e
b
o
th
co
m
p
r
e
h
en
s
iv
e
a
n
d
s
p
ec
i
f
icall
y
tailo
r
ed
to
ea
ch
s
tu
d
e
n
t
'
s
u
n
iq
u
e
p
r
o
f
ile
[
1
4
]
.
T
h
e
r
e
a
r
e
c
h
a
l
le
n
g
es
an
d
c
o
n
s
i
d
e
r
a
t
i
o
n
s
t
o
a
d
d
r
e
s
s
th
e
ch
a
t
b
o
t
.
T
h
e
ef
f
e
c
ti
v
e
n
e
s
s
o
f
A
I
-
d
r
iv
en
g
u
i
d
an
c
e
s
y
s
t
em
s
d
e
p
en
d
s
o
n
t
h
e
q
u
a
l
ity
o
f
th
e
d
a
t
a
u
s
e
d
t
o
t
r
a
in
t
h
e
m
o
d
e
ls
a
n
d
th
e
a
b
i
li
ty
o
f
th
e
ch
a
t
b
o
ts
t
o
a
d
a
p
t
t
o
d
iv
e
r
s
e
s
tu
d
e
n
t
n
e
e
d
s
[
1
5
]
.
T
h
e
c
o
m
p
l
ex
i
ty
o
f
h
u
m
a
n
d
e
ci
s
i
o
n
-
m
ak
in
g
m
ea
n
s
t
h
at
A
I
s
y
s
t
em
s
s
h
o
u
l
d
b
e
v
i
ew
e
d
a
s
c
o
m
p
l
em
en
ta
r
y
t
o
o
l
s
th
a
t
a
u
g
m
en
t
,
r
a
th
e
r
th
an
r
e
p
l
a
c
e
,
a
n
d
t
r
a
d
it
i
o
n
a
l
g
u
i
d
a
n
c
e
m
e
th
o
d
s
.
T
h
e
d
e
p
l
o
y
m
en
t
o
f
g
en
e
r
at
iv
e
A
I
ch
a
t
b
o
ts
in
e
d
u
ca
t
i
o
n
a
l
s
e
t
tin
g
s
r
e
q
u
i
r
e
s
r
ig
o
r
o
u
s
t
es
ti
n
g
an
d
v
a
li
d
a
t
i
o
n
t
o
e
n
s
u
r
e
t
h
ei
r
r
e
li
a
b
i
li
ty
an
d
ef
f
e
c
ti
v
e
n
es
s
[
1
6
]
.
R
e
s
e
a
r
c
h
m
u
s
t
f
o
cu
s
o
n
d
ev
el
o
p
i
n
g
m
o
d
e
l
s
th
at
a
r
e
n
o
t
o
n
ly
a
c
cu
r
at
e
b
u
t
a
l
s
o
f
a
i
r
an
d
u
n
b
i
as
e
d
[
1
7
]
.
E
n
s
u
r
i
n
g
th
at
t
h
e
c
h
at
b
o
t
s
p
r
o
v
i
d
e
e
q
u
i
t
a
b
le
g
u
i
d
an
c
e
t
o
s
t
u
d
en
ts
f
r
o
m
d
iv
e
r
s
e
b
a
c
k
g
r
o
u
n
d
s
is
e
s
s
en
ti
a
l
t
o
a
v
o
i
d
p
e
r
p
e
tu
at
in
g
e
x
i
s
t
in
g
in
e
q
u
a
l
it
i
es
in
a
c
ce
s
s
t
o
e
d
u
c
a
t
i
o
n
an
d
c
a
r
e
e
r
o
p
p
o
r
t
u
n
i
t
i
es
.
F
u
r
th
e
r
m
o
r
e
,
in
v
o
l
v
in
g
e
d
u
c
at
i
o
n
a
l
p
r
o
f
es
s
i
o
n
als
in
th
e
d
e
v
e
l
o
p
m
en
t
an
d
im
p
l
em
en
t
at
i
o
n
o
f
th
es
e
s
y
s
tem
s
c
an
h
el
p
a
l
ig
n
th
e
te
ch
n
o
l
o
g
y
w
i
th
p
e
d
ag
o
g
i
c
al
b
e
s
t
p
r
a
c
t
i
c
es
an
d
in
s
t
i
tu
ti
o
n
a
l
g
o
a
ls
[
1
8
]
,
[
1
9
]
.
T
h
e
p
r
im
ar
y
o
b
j
ec
tiv
e
o
f
th
i
s
s
t
u
d
y
is
to
ev
a
lu
ate
t
h
e
e
f
f
ec
tiv
e
n
ess
o
f
I
n
d
o
n
es
ian
g
en
er
ativ
e
A
I
ch
atb
o
ts
a
n
d
tr
a
n
s
f
o
r
m
er
e
m
b
ed
d
i
n
g
s
i
n
e
n
h
an
c
in
g
th
e
d
ec
is
io
n
-
m
ak
in
g
p
r
o
ce
s
s
f
o
r
u
n
iv
er
s
it
y
m
aj
o
r
s
elec
tio
n
.
Sp
ec
i
f
icall
y
,
t
h
e
r
esear
ch
ai
m
s
to
ass
e
s
s
h
o
w
th
ese
ad
v
an
ce
d
A
I
tec
h
n
o
lo
g
ies
ca
n
p
r
o
v
id
e
p
er
s
o
n
alize
d
,
in
ter
ac
ti
v
e,
an
d
co
n
tex
t
u
all
y
r
ele
v
an
t
g
u
id
an
c
e
to
s
tu
d
e
n
ts
,
h
elp
in
g
t
h
e
m
m
ak
e
m
o
r
e
i
n
f
o
r
m
ed
an
d
tailo
r
ed
d
ec
is
io
n
s
r
e
g
ar
d
in
g
t
h
eir
ac
ad
e
m
ic
p
at
h
s
.
A
d
v
an
ce
m
e
n
ts
i
n
c
h
atb
o
t
ar
ch
i
t
ec
tu
r
e,
s
p
ec
i
f
icall
y
u
s
i
n
g
tr
an
s
f
o
r
m
er
m
o
d
els,
h
a
v
e
d
e
m
o
n
s
tr
ated
s
u
p
er
io
r
p
er
f
o
r
m
a
n
ce
in
g
en
er
ati
n
g
ac
cu
r
a
te
an
d
co
n
tex
t
u
all
y
r
ele
v
an
t
r
esp
o
n
s
e
s
[
2
0
]
.
T
h
ese
tech
n
ical
i
m
p
r
o
v
e
m
e
n
ts
f
ac
i
litate
m
o
r
e
n
at
u
r
al
a
n
d
e
f
f
ec
ti
v
e
h
u
m
a
n
-
m
ac
h
i
n
e
in
ter
ac
tio
n
s
,
w
h
ich
ca
n
b
e
p
ar
ticu
lar
l
y
b
e
n
ef
icial
i
n
ed
u
ca
t
io
n
al
s
etti
n
g
s
b
y
p
r
o
v
id
in
g
p
er
s
o
n
alize
d
s
u
p
p
o
r
t
an
d
g
u
id
a
n
ce
[
2
1
]
.
T
h
e
en
h
an
ce
d
en
g
a
g
e
m
e
n
t
a
n
d
s
a
tis
f
ac
ti
o
n
r
es
u
lti
n
g
f
r
o
m
th
e
s
e
i
n
ter
a
ctio
n
s
h
i
g
h
li
g
h
t
t
h
e
tr
an
s
f
o
r
m
ati
v
e
p
o
ten
t
ial
o
f
tr
a
n
s
f
o
r
m
er
-
b
ased
ch
atb
o
ts
[
2
2
]
.
A
I
co
n
v
er
s
at
io
n
al
a
g
en
ts
h
av
e
b
ee
n
ev
al
u
ated
f
o
r
th
eir
ab
ilit
y
to
s
u
p
p
o
r
t th
e
lear
n
in
g
a
n
d
w
el
l
-
b
ei
n
g
o
f
u
n
i
v
er
s
it
y
s
t
u
d
en
ts
[
2
3
]
,
[
2
4
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
14
,
No
.
4
,
A
u
g
u
s
t 2
0
2
5
:
3
4
7
4
-
3482
3476
B
y
i
n
v
esti
g
ati
n
g
t
h
e
ca
p
ab
ilit
ies
an
d
li
m
ita
tio
n
s
o
f
t
h
ese
A
I
-
d
r
iv
e
n
to
o
ls
,
th
e
s
t
u
d
y
s
e
ek
s
to
o
f
f
er
ac
tio
n
ab
le
in
s
i
g
h
t
s
i
n
to
th
eir
p
o
ten
tial
i
m
p
ac
t
o
n
ed
u
ca
ti
o
n
al
s
u
p
p
o
r
t
s
y
s
te
m
s
an
d
to
co
n
tr
ib
u
te
to
t
h
e
d
ev
elo
p
m
en
t
o
f
m
o
r
e
ef
f
ec
ti
v
e
d
ec
is
io
n
-
s
u
p
p
o
r
t
m
ec
h
a
n
is
m
s
i
n
h
i
g
h
er
ed
u
ca
tio
n
.
I
n
r
e
latio
n
to
en
h
a
n
cin
g
s
tu
d
e
n
t
d
ec
is
io
n
-
m
a
k
i
n
g
i
n
u
n
iv
er
s
it
y
m
aj
o
r
s
elec
tio
n
,
t
h
es
e
f
i
n
d
in
g
s
h
i
g
h
l
ig
h
t
t
h
e
cr
itic
al
r
o
le
o
f
ad
v
an
ce
d
A
I
s
y
s
te
m
s
i
n
f
ac
ilit
ati
n
g
i
n
f
o
r
m
ed
d
ec
i
s
io
n
-
m
a
k
i
n
g
p
r
o
ce
s
s
es.
B
y
lev
er
a
g
i
n
g
t
h
e
p
er
s
o
n
alize
d
an
d
co
n
tex
t
u
all
y
r
elev
a
n
t
s
u
p
p
o
r
t o
f
f
er
ed
b
y
th
e
s
e
ch
atb
o
ts
,
s
t
u
d
en
ts
ca
n
m
a
k
e
m
o
r
e
in
f
o
r
m
ed
ch
o
ices
ab
o
u
t
th
eir
ac
ad
em
ic
p
ath
s
,
i
m
p
r
o
v
i
n
g
ed
u
ca
tio
n
a
l
o
u
tco
m
es
,
an
d
p
er
s
o
n
al
s
atis
f
ac
tio
n
.
T
h
is
in
te
g
r
ati
o
n
o
f
A
I
tech
n
o
lo
g
ies
n
o
t
o
n
l
y
e
n
h
a
n
ce
s
d
ec
is
io
n
-
m
a
k
i
n
g
b
u
t
a
ls
o
ad
d
r
ess
es
co
g
n
iti
v
e,
et
h
ical,
an
d
p
r
ac
tical
ch
alle
n
g
e
s
id
en
ti
f
ied
i
n
th
e
li
t
er
atu
r
e.
2.
M
E
T
H
O
D
2
.
1
.
Sy
s
t
em
o
v
er
v
iew
T
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
f
o
r
en
h
an
cin
g
s
tu
d
e
n
t
d
ec
is
io
n
-
m
a
k
i
n
g
in
u
n
iv
er
s
it
y
m
aj
o
r
s
elec
ti
o
n
th
r
o
u
g
h
g
en
er
ati
v
e
A
I
ch
a
tb
o
ts
a
n
d
tr
a
n
s
f
o
r
m
er
e
m
b
ed
d
in
g
s
in
v
o
lv
e
s
a
m
u
lti
-
s
tep
p
r
o
ce
s
s
t
h
at
in
te
g
r
ates a
d
v
an
ce
d
AI
tech
n
iq
u
es
to
p
r
o
v
id
e
p
er
s
o
n
alize
d
an
d
d
etailed
r
ec
o
m
m
e
n
d
atio
n
s
.
Fi
g
u
r
e
1
s
h
o
w
s
t
h
i
s
p
r
o
p
o
s
ed
m
e
th
o
d
ar
ch
itect
u
r
e.
T
h
e
f
lo
w
c
h
ar
t
o
u
tli
n
es
t
h
is
p
r
o
ce
s
s
,
s
tar
t
in
g
f
r
o
m
u
s
er
i
n
p
u
t
a
n
d
en
d
in
g
w
i
th
th
e
d
eli
v
er
y
o
f
a
r
ef
in
ed
a
n
d
co
n
tex
t
u
all
y
r
ele
v
an
t
r
e
s
p
o
n
s
e.
I
n
it
iall
y
,
t
h
e
s
y
s
te
m
r
ec
eiv
e
s
i
n
p
u
t
f
r
o
m
u
s
er
s
,
w
h
ic
h
t
y
p
icall
y
co
n
s
is
ts
o
f
te
x
t
-
b
ased
in
q
u
ir
ie
s
ab
o
u
t p
o
ten
tial
m
aj
o
r
s
.
Fig
u
r
e
1
.
T
h
e
ar
ch
itectu
r
e
o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
2
.
2
.
E
m
bed
din
g
t
ec
hn
i
qu
es
T
h
e
in
p
u
t
is
e
m
b
ed
d
ed
u
s
in
g
m
o
d
el
s
li
k
e
B
E
R
T
o
r
Ge
m
i
n
i
e
m
b
ed
d
in
g
.
T
h
ese
m
o
d
el
s
tr
a
n
s
f
o
r
m
th
e
tex
t
in
to
a
f
o
r
m
at
s
u
itab
le
f
o
r
f
u
r
t
h
er
an
al
y
s
i
s
.
T
h
e
em
b
ed
d
in
g
p
r
o
ce
s
s
ca
p
tu
r
es
t
h
e
s
e
m
a
n
tic
m
ea
n
i
n
g
o
f
t
h
e
u
s
er
'
s
in
p
u
t,
m
a
k
i
n
g
it
ea
s
i
er
f
o
r
th
e
s
u
b
s
eq
u
e
n
t
c
lass
i
f
icatio
n
m
o
d
el
to
u
n
d
er
s
ta
n
d
an
d
p
r
o
ce
s
s
th
e
in
f
o
r
m
atio
n
.
2
.
3
.
Cla
s
s
if
ica
t
io
n a
nd
re
s
po
ns
e
g
ener
a
t
io
n
T
h
e
n
ex
t
s
tep
is
co
m
b
in
ed
t
h
e
e
m
b
ed
d
in
g
tec
h
n
iq
u
e
s
w
i
th
clas
s
i
f
icatio
n
m
o
d
el
u
s
i
n
g
r
ec
u
r
r
en
t
n
eu
r
al
n
et
w
o
r
k
(
R
NN)
an
d
lo
n
g
s
h
o
r
t
-
ter
m
m
e
m
o
r
y
(
L
ST
M)
.
T
h
e
class
if
icat
io
n
m
o
d
el
th
en
p
r
ed
icts
t
w
o
o
r
th
r
ee
m
aj
o
r
s
th
at
b
es
t
m
atc
h
t
h
e
u
s
er
'
s
p
r
o
f
ile
a
n
d
p
r
ef
er
en
c
es
b
ased
o
n
th
e
d
ataset.
T
h
is
m
o
d
el
is
tr
ain
ed
to
an
al
y
ze
v
ar
io
u
s
f
ac
to
r
s
an
d
p
r
o
v
id
e
ac
cu
r
ate
r
ec
o
m
m
e
n
d
ati
o
n
s
.
O
n
ce
t
h
e
p
o
te
n
tial
m
aj
o
r
s
ar
e
id
en
tifie
d
,
th
e
s
y
s
te
m
g
e
n
er
ates
p
r
o
m
p
ts
d
esig
n
ed
to
m
ak
e
t
h
e
c
h
at
b
o
t'
s
r
esp
o
n
s
e
s
m
o
r
e
n
atu
r
a
l
an
d
h
u
m
a
n
-
li
k
e.
T
h
ese
p
r
o
m
p
ts
ar
e
s
e
n
t
t
h
r
o
u
g
h
t
h
e
Ge
m
in
i
A
P
I
,
w
h
ich
f
ac
il
itates
co
m
m
u
n
icatio
n
b
et
w
ee
n
th
e
A
I
m
o
d
el
a
n
d
th
e
u
s
er
.
I
f
u
s
er
s
s
ee
k
m
o
r
e
d
etailed
in
f
o
r
m
atio
n
ab
o
u
t
t
h
e
r
ec
o
m
m
e
n
d
ed
m
aj
o
r
s
,
th
e
y
ca
n
co
n
ti
n
u
e
t
h
e
co
n
v
er
s
atio
n
o
r
i
n
itiate
a
n
e
w
q
u
er
y
f
o
r
f
u
r
th
er
r
ec
o
m
m
e
n
d
atio
n
s
.
T
h
e
s
y
s
te
m
r
etr
ie
v
e
s
p
r
ed
ictio
n
v
al
u
es
f
r
o
m
t
h
e
class
if
icatio
n
m
o
d
el
an
d
f
ilter
s
a
d
ataset
co
n
tai
n
i
n
g
d
etailed
d
escr
ip
tio
n
s
o
f
ea
ch
m
aj
o
r
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Gen
era
tive
I
n
d
o
n
esia
n
ch
a
t
b
o
t fo
r
u
n
ivers
ity
ma
jo
r
s
elec
tio
n
u
s
in
g
tr
a
n
s
fo
r
mers
…
(
Mu
ti
a
r
a
A
u
liya
K
h
a
d
ija
)
3477
2
.
4
.
Rele
v
a
nce
f
ilte
ring
T
o
en
s
u
r
e
th
e
r
ele
v
an
ce
o
f
th
e
d
ataset
co
n
te
n
t,
th
e
s
y
s
te
m
e
m
p
lo
y
s
ter
m
f
r
eq
u
e
n
c
y
-
i
n
v
er
s
e
d
o
cu
m
en
t
f
r
eq
u
e
n
c
y
(
T
F
-
I
D
F)
f
o
r
en
co
d
in
g
t
h
e
te
x
t
d
ata.
I
t
th
en
u
s
es
co
s
i
n
e
s
i
m
ila
r
it
y
to
m
ea
s
u
r
e
th
e
r
elev
an
ce
o
f
t
h
e
co
n
te
n
t
to
t
h
e
u
s
er
'
s
q
u
er
y
.
T
h
is
co
m
b
in
at
io
n
h
elp
s
th
e
s
y
s
te
m
id
e
n
ti
f
y
th
e
m
o
s
t
r
ele
v
an
t
in
f
o
r
m
atio
n
e
f
f
icie
n
tl
y
[
2
5
]
.
2
.
5
.
Deplo
y
m
ent
a
rc
hite
ct
ur
e
Fin
all
y
,
th
e
s
y
s
te
m
g
e
n
er
ates
d
etailed
p
r
o
m
p
ts
a
n
d
s
en
d
s
th
e
m
th
r
o
u
g
h
th
e
Ge
m
in
i
A
P
I
,
p
r
o
v
id
in
g
u
s
er
s
w
i
th
r
e
f
i
n
ed
an
d
co
n
te
x
tu
a
ll
y
ap
p
r
o
p
r
iate
r
esp
o
n
s
es
.
T
h
is
iter
ativ
e
p
r
o
ce
s
s
en
h
a
n
ce
s
t
h
e
ch
a
tb
o
t'
s
ab
ilit
y
to
g
u
id
e
s
t
u
d
en
t
s
i
n
t
h
eir
m
aj
o
r
s
elec
tio
n
,
o
f
f
er
i
n
g
p
er
s
o
n
alize
d
an
d
d
etailed
r
ec
o
m
m
en
d
atio
n
s
b
ased
o
n
ad
v
an
ce
d
A
I
tech
n
iq
u
es.
T
h
is
m
et
h
o
d
lev
er
ag
e
s
th
e
p
o
w
er
o
f
tr
an
s
f
o
r
m
er
e
m
b
ed
d
in
g
s
,
clas
s
i
f
icatio
n
m
o
d
el
s
,
an
d
N
L
P
to
cr
ea
te
a
s
o
p
h
is
ticated
r
ec
o
m
m
en
d
atio
n
s
y
s
te
m
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Da
t
a
s
et
Data
is
co
llected
u
s
in
g
a
q
u
esti
o
n
n
a
ir
e
r
esu
lt
f
r
o
m
C
ar
ee
r
Dev
elo
p
m
e
n
t
C
e
n
ter
o
f
Vo
ca
tio
n
al
Sch
o
o
l,
Un
i
v
er
s
ita
s
Seb
elas
Ma
r
et
w
h
ich
ai
m
s
to
g
en
er
at
e
u
s
er
s
tate
m
e
n
ts
o
r
s
to
r
ies
r
elate
d
to
in
ter
ests
,
talen
t
s
,
an
d
d
esire
d
ca
r
ee
r
p
r
o
s
p
ec
ts
in
I
n
d
o
n
esia
n
lan
g
u
a
g
e.
T
h
er
ef
o
r
e,
1
5
,
1
3
2
d
a
ta
s
tate
m
e
n
t
s
w
er
e
g
en
er
ated
.
T
h
e
d
ata
ap
p
ea
r
s
in
Fi
g
u
r
e
2
.
Af
ter
t
h
at,
t
h
e
d
at
a
u
n
d
er
g
o
es
p
r
ep
r
o
ce
s
s
in
g
,
in
clu
d
in
g
ca
s
e
f
o
ld
i
n
g
to
co
n
v
er
t
all
le
tter
s
to
lo
w
er
ca
s
e,
clea
n
s
in
g
(
r
e
m
o
v
i
n
g
c
h
ar
ac
ter
s
)
,
an
d
r
e
m
o
v
i
n
g
p
u
n
ct
u
atio
n
.
T
h
e
d
ataset
co
n
tain
i
n
g
in
f
o
r
m
at
io
n
ab
o
u
t
ca
r
ee
r
p
r
o
s
p
ec
ts
b
ased
o
n
in
ter
ests
an
d
talen
ts
.
T
h
e
d
ataset
co
n
s
is
t
s
o
f
th
r
ee
m
ai
n
co
lu
m
n
s
:
‒
I
n
ter
ests
a
n
d
talen
ts
o
r
min
a
t
b
a
ka
t
:
de
s
cr
ib
e
th
e
in
d
iv
id
u
al's
in
ter
e
s
t
i
n
s
p
ec
if
ic
asp
ec
t
s
r
elate
d
w
it
h
in
ter
et
o
f
s
tu
d
e
n
t
.
‒
C
ar
ee
r
p
r
o
s
p
ec
ts
o
r
p
r
o
s
p
ek
k
erja
: o
u
tli
n
es p
o
ten
tia
l c
ar
ee
r
p
ath
s
b
ased
o
n
th
e
s
tated
in
ter
ests
.
‒
Ma
j
o
r
/f
ield
o
f
s
tu
d
y
o
r
ju
r
u
s
a
n
:
s
p
ec
if
ies
th
at
all
t
h
ese
in
t
er
ests
an
d
ca
r
ee
r
p
ath
s
f
all
u
n
d
er
th
e
m
aj
o
r
d
is
cip
lin
e.
Fig
u
r
e
2
.
I
n
d
o
n
esian
d
ata
s
et
o
n
ca
r
ee
r
p
r
o
s
p
ec
ts
3
.
2
.
M
o
delin
g
Mo
d
elin
g
is
co
n
d
u
cted
w
it
h
t
h
r
ee
e
x
p
er
i
m
e
n
ts
.
T
h
e
f
ir
s
t
i
n
v
o
lv
e
s
cla
s
s
i
f
icatio
n
u
s
i
n
g
T
en
s
o
r
Flo
w
'
s
b
u
ilt
-
in
e
m
b
ed
d
in
g
la
y
er
.
T
h
e
s
ec
o
n
d
u
s
e
s
e
m
b
ed
d
in
g
s
f
r
o
m
t
h
e
Ge
m
i
n
i
A
P
I
.
T
h
e
th
i
r
d
em
p
lo
y
s
B
E
R
T
s
en
te
n
ce
f
o
r
I
n
d
o
n
e
s
ian
la
n
g
u
ag
e
to
e
m
b
ed
tex
t d
ata.
T
ab
le
1
s
h
o
w
s
t
h
e
ac
cu
r
ac
y
o
f
th
e
m
o
d
el.
T
ab
le
1
.
P
er
f
o
r
m
a
n
ce
co
m
p
ar
i
s
o
n
o
f
m
o
d
el
s
w
it
h
d
if
f
er
en
t e
m
b
ed
d
i
n
g
s
A
l
g
o
r
i
t
h
ms
M
o
d
e
l
e
mb
e
d
d
i
n
g
T
r
a
i
n
i
n
g
a
c
c
u
r
a
c
y
(
%)
T
e
st
i
n
g
a
c
c
u
r
a
c
y
(
%)
T
r
a
i
n
i
n
g
l
o
ss
T
e
st
i
n
g
l
o
ss
Ep
o
c
h
N
a
me
o
f
mo
d
e
l
e
mb
e
d
d
i
n
g
R
N
N
L
a
y
e
r
e
mb
e
d
d
i
n
g
96
65
0
.
1
3
4
1
1
.
8
6
0
7
35
-
L
S
T
M
L
a
y
e
r
e
mb
e
d
d
i
n
g
78
69
0
.
7
9
6
1
1
.
0
6
4
5
35
-
R
N
N
G
e
mi
n
i
e
m
b
e
d
d
i
n
g
89
89
0
.
3
4
5
0
0
.
3
3
3
3
50
e
mb
e
d
d
i
n
g
-
001
L
S
T
M
G
e
mi
n
i
e
m
b
e
d
d
i
n
g
89
87
0
.
3
2
8
9
0
.
3
7
8
1
50
e
mb
e
d
d
i
n
g
-
001
R
N
N
B
ER
T
e
mb
e
d
d
i
n
g
91
92
0
.
3
0
9
3
0
.
2
4
4
5
25
f
i
r
q
a
a
a
/
i
n
d
o
-
se
n
t
e
n
c
e
-
b
e
r
t
-
b
a
se
L
S
T
M
B
ER
T
e
mb
e
d
d
i
n
g
93
91
0
.
3
1
5
7
0
.
2
8
3
1
25
f
i
r
q
a
a
a
/
i
n
d
o
-
se
n
t
e
n
c
e
-
b
e
r
t
-
b
a
se
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
14
,
No
.
4
,
A
u
g
u
s
t 2
0
2
5
:
3
4
7
4
-
3482
3478
3
.
3
.
No
rm
a
l la
y
er
e
m
bedd
in
g
T
h
e
R
NN
m
o
d
el
w
it
h
a
7
6
8
e
m
b
ed
d
in
g
d
i
m
e
n
s
io
n
la
y
er
e
x
h
ib
ited
o
v
er
f
i
tti
n
g
,
as
e
v
id
en
ce
d
b
y
t
h
e
s
ig
n
i
f
ica
n
t
g
ap
b
et
w
ee
n
tr
ai
n
in
g
an
d
test
i
n
g
ac
c
u
r
ac
y
.
T
h
is
h
i
g
h
li
g
h
ts
th
e
li
m
itat
i
o
n
s
o
f
tr
ad
itio
n
al
e
m
b
ed
d
in
g
s
an
d
u
n
d
er
s
co
r
es t
h
e
n
ee
d
f
o
r
m
o
r
e
ad
v
an
ce
d
tec
h
n
i
q
u
es,
s
u
c
h
as B
E
R
T
an
d
Ge
m
i
n
i e
m
b
ed
d
in
g
s
,
w
h
ic
h
d
e
m
o
n
s
tr
ated
s
u
p
er
io
r
g
en
er
aliza
tio
n
a
n
d
ac
c
u
r
ac
y
.
T
h
e
tr
ain
i
n
g
h
i
s
to
r
y
r
ev
ea
led
t
h
at
w
h
ile
t
h
e
m
o
d
e
l
ac
h
iev
ed
h
i
g
h
p
er
f
o
r
m
an
ce
o
n
th
e
tr
ai
n
in
g
s
et,
it
s
tr
u
g
g
led
w
it
h
g
e
n
er
aliza
tio
n
to
t
h
e
tes
t
s
et,
as
i
n
d
ica
ted
b
y
a
co
n
s
id
er
ab
le
g
ap
b
et
w
ee
n
th
e
t
w
o
.
I
n
co
n
tr
ast,
t
h
e
L
ST
M
m
o
d
el
w
it
h
a
s
ta
n
d
ar
d
e
m
b
ed
d
in
g
la
y
er
d
em
o
n
s
tr
ated
b
etter
p
er
f
o
r
m
an
ce
t
h
a
n
t
h
e
R
NN.
Alt
h
o
u
g
h
t
h
er
e
w
er
e
s
o
m
e
in
d
icati
o
n
s
o
f
o
v
er
f
itt
in
g
,
th
e
L
ST
M
m
o
d
el
e
x
h
ib
ited
m
o
r
e
s
tab
le
p
r
o
g
r
ess
d
u
r
i
n
g
tr
ain
i
n
g
a
n
d
te
s
ti
n
g
,
w
i
th
i
m
p
r
o
v
e
m
en
t
s
i
n
b
o
th
m
etr
ics
co
m
p
ar
ed
to
th
e
R
NN
.
T
h
e
m
o
d
el
ar
ch
itect
u
r
e
w
it
h
0
.
2
d
r
o
p
o
u
t,
So
f
tMa
x
ac
tiv
a
ti
o
n
f
u
n
ctio
n
,
A
d
a
m
o
p
tim
izer
w
ith
0
.
0
0
0
1
lear
n
in
g
r
ate.
3
.
4
.
G
e
m
in
i e
m
be
dd
ing
Usi
n
g
Ge
m
i
n
i
-
1
.
5
-
f
las
h
e
m
b
ed
d
in
g
m
o
d
el
,
th
e
R
NN
s
h
o
w
ed
s
i
g
n
if
ican
t
i
m
p
r
o
v
e
m
en
t,
w
it
h
ac
cu
r
ac
y
n
ea
r
in
g
9
0
%
i
n
b
o
th
tr
ain
i
n
g
a
n
d
test
i
n
g
p
h
a
s
es.
T
h
is
m
o
d
el
d
e
m
o
n
s
tr
ated
s
tr
o
n
g
p
er
f
o
r
m
a
n
ce
an
d
w
il
l
b
e
co
n
s
id
er
ed
as
a
v
iab
le
o
p
tio
n
f
o
r
s
elec
tio
n
.
Si
m
ilar
l
y
,
t
h
e
L
ST
M
m
o
d
el
w
ith
t
h
e
Ge
m
i
n
i
e
m
b
ed
d
in
g
m
o
d
e
l
ac
h
iev
ed
n
ea
r
9
0
%
ac
cu
r
ac
y
,
p
ar
alleli
n
g
t
h
e
R
NN's
p
er
f
o
r
m
an
ce
.
Fi
g
u
r
e
3
s
h
o
w
s
th
e
m
o
d
el
ar
ch
itect
u
r
e
w
i
th
A
d
a
m
o
p
ti
m
izer
,
0
.
0
0
0
1
lea
r
n
in
g
r
ate
w
ith
So
f
tMa
x
ac
tiv
at
io
n
f
u
n
ctio
n
.
Fig
u
r
e
3
.
Mo
d
el
ar
ch
itectu
r
e
o
f
L
ST
M
an
d
Ge
m
i
n
i e
m
b
ed
d
i
n
g
3
.
5
.
B
E
RT
e
m
be
dd
ing
W
h
en
u
tili
zi
n
g
t
h
e
B
E
R
T
e
m
b
ed
d
in
g
m
o
d
el
(
f
ir
q
aa
a/i
n
d
o
-
s
e
n
te
n
ce
-
b
er
t
-
b
ase)
w
it
h
to
k
en
izer
v
o
ca
b
u
lar
y
s
ize
3
0
,
5
2
2
to
k
en
s
a
n
d
7
6
8
e
m
b
ed
d
in
g
d
i
m
en
s
io
n
s
,
t
h
e
R
NN
ac
h
iev
ed
ev
e
n
b
etter
r
esu
lts
w
it
h
ac
cu
r
ac
y
r
ea
ch
i
n
g
9
0
%.
I
t
ca
n
b
e
d
ep
icted
in
Fig
u
r
e
4
.
T
h
e
m
o
d
el'
s
p
er
f
o
r
m
an
ce
w
a
s
s
u
p
er
io
r
to
th
at
o
f
th
e
Ge
m
i
n
i
e
m
b
ed
d
in
g
s
,
an
d
it
w
i
ll
b
e
co
n
s
id
er
ed
f
o
r
s
elec
tio
n
d
u
e
to
its
h
i
g
h
ac
c
u
r
ac
y
.
T
h
e
L
ST
M
m
o
d
el
w
it
h
th
e
B
E
R
T
e
m
b
ed
d
in
g
also
d
e
m
o
n
s
tr
ated
ex
ce
llen
t
p
er
f
o
r
m
an
ce
,
m
atch
in
g
th
e
R
N
N
'
s
ac
cu
r
ac
y
at
9
0
%.
Th
e
r
esu
lts
i
n
d
icate
t
h
at
t
h
e
L
ST
M
-
B
E
R
T
m
o
d
el
is
eq
u
al
l
y
ef
f
ec
tiv
e
a
n
d
w
ill
b
e
s
av
ed
as
a
s
tr
o
n
g
ca
n
d
id
ate
f
o
r
m
o
d
el
s
elec
tio
n
.
I
t c
an
b
e
d
ep
icted
in
Fig
u
r
e
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Gen
era
tive
I
n
d
o
n
esia
n
ch
a
t
b
o
t fo
r
u
n
ivers
ity
ma
jo
r
s
elec
tio
n
u
s
in
g
tr
a
n
s
fo
r
mers
…
(
Mu
ti
a
r
a
A
u
liya
K
h
a
d
ija
)
3479
Fig
u
r
e
4
.
His
to
r
y
tr
ain
i
n
g
o
f
R
NN
an
d
B
E
R
T
em
b
ed
d
in
g
Fig
u
r
e
5
.
His
to
r
y
tr
ain
i
n
g
o
f
L
ST
M
an
d
B
E
R
T
em
b
ed
d
in
g
3
.
6
.
Deplo
y
m
ent
T
h
e
f
o
llo
w
i
n
g
is
a
n
ex
a
m
p
l
e
p
r
o
g
r
am
f
o
r
a
m
aj
o
r
r
ec
o
m
m
en
d
atio
n
c
h
atb
o
t
f
o
r
n
e
w
s
tu
d
e
n
ts
.
T
h
e
d
em
o
ap
p
licatio
n
u
s
es
S
tr
ea
m
lit
to
f
ac
ili
tate
ap
p
licatio
n
test
in
g
.
Fi
g
u
r
e
6
s
h
o
w
s
t
h
e
d
ata
Ma
y
a
B
o
t,
w
h
ic
h
is
th
e
n
a
m
e
o
f
th
i
s
m
a
j
o
r
r
ec
o
m
m
e
n
d
atio
n
c
h
atb
o
t
f
o
r
n
e
w
s
t
u
d
en
t
s
.
I
n
th
is
Ma
y
a
B
o
t,
th
e
s
tu
d
en
t
s
co
u
ld
w
r
i
te
th
e
ir
in
ter
ests
a
n
d
ask
i
n
g
w
h
ic
h
m
aj
o
r
th
at
s
u
it
ab
le
f
o
r
th
e
m
.
I
f
w
e
p
r
o
v
id
e
an
i
n
p
u
t
o
u
ts
id
e
t
h
e
r
ec
o
m
m
e
n
d
atio
n
co
n
tex
t,
t
h
e
B
o
t
w
ill
a
u
to
m
a
ticall
y
r
esp
o
n
d
th
at
it
d
o
es
n
o
t
k
n
o
w
th
e
a
n
s
w
er
.
T
ab
le
2
s
h
o
w
s
th
e
tr
an
s
latio
n
i
n
E
n
g
li
s
h
v
er
s
i
o
n
.
Fig
u
r
e
6
.
Ma
y
a
b
o
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
14
,
No
.
4
,
A
u
g
u
s
t 2
0
2
5
:
3
4
7
4
-
3482
3480
T
ab
le
2
.
T
h
e
tr
an
s
latio
n
o
f
Ma
y
a
B
o
t (
m
aj
o
r
r
ec
o
m
m
en
d
atio
n
ch
atb
o
t f
o
r
n
e
w
s
t
u
d
en
t
s
)
M
a
y
a
B
o
t
/
u
se
r
R
e
sp
o
n
d
s
M
a
y
a
B
o
t
H
e
l
l
o
!
D
o
y
o
u
w
a
n
t
t
o
k
n
o
w
w
h
i
c
h
maj
o
r
su
i
t
s
y
o
u
b
e
st
?
I
’
m
h
e
r
e
t
o
h
e
l
p
!
F
i
r
st
,
p
l
e
a
se
t
e
l
l
me
a
b
o
u
t
y
o
u
r
i
n
t
e
r
e
st
s a
n
d
t
a
l
e
n
t
s
.
F
e
e
l
f
r
e
e
t
o
sh
a
r
e
e
v
e
r
y
t
h
i
n
g
w
i
t
h
me
!
U
se
r
I
n
p
u
t
I
w
a
n
t
t
o
w
o
r
k
a
t
P
e
r
t
a
mi
n
a
(
I
n
d
o
n
e
si
a
's
n
a
t
i
o
n
a
l
o
i
l
c
o
mp
a
n
y
)
.
D
o
y
o
u
h
a
v
e
a
n
y
r
e
c
o
mm
e
n
d
a
t
i
o
n
s
f
o
r
su
i
t
a
b
l
e
maj
o
r
s t
o
h
e
l
p
me
p
u
r
s
u
e
a
c
a
r
e
e
r
a
t
P
e
r
t
a
mi
n
a
?
M
a
y
a
B
o
t
S
u
r
e
!
I
w
i
l
l
r
e
c
o
mm
e
n
d
so
me
maj
o
r
s
f
o
r
y
o
u
!
W
o
w
,
t
h
a
t
’
s
a
n
a
m
a
z
i
n
g
d
r
e
a
m
—
w
o
r
k
i
n
g
a
t
P
e
r
t
a
m
i
n
a
!
B
a
se
d
o
n
y
o
u
r
g
o
a
l
,
I
w
o
u
l
d
r
e
c
o
mm
e
n
d
y
o
u
t
o
c
o
n
si
d
e
r
C
h
e
mi
c
a
l
En
g
i
n
e
e
r
i
n
g
o
r
M
e
c
h
a
n
i
c
a
l
En
g
i
n
e
e
r
i
n
g
.
C
h
e
mi
c
a
l
E
n
g
i
n
e
e
r
i
n
g
w
i
l
l
p
r
o
v
i
d
e
y
o
u
w
i
t
h
k
n
o
w
l
e
d
g
e
a
b
o
u
t
t
h
e
p
r
o
c
e
ssi
n
g
o
f
p
e
t
r
o
l
e
u
m,
f
r
o
m
e
x
t
r
a
c
t
i
o
n
t
o
r
e
f
i
n
i
n
g
,
t
r
a
n
sf
o
r
mi
n
g
i
t
i
n
t
o
f
u
e
l
s
a
n
d
o
t
h
e
r
c
h
e
mi
c
a
l
p
r
o
d
u
c
t
s.
Y
o
u
w
i
l
l
st
u
d
y
c
h
e
mi
c
a
l
r
e
a
c
t
i
o
n
s,
r
e
a
c
t
o
r
d
e
si
g
n
,
a
n
d
se
p
a
r
a
t
i
o
n
t
e
c
h
n
o
l
o
g
i
e
s u
se
d
i
n
t
h
e
o
i
l
a
n
d
g
a
s
i
n
d
u
st
r
y
.
M
e
c
h
a
n
i
c
a
l
En
g
i
n
e
e
r
i
n
g
w
i
l
l
e
q
u
i
p
y
o
u
w
i
t
h
k
n
o
w
l
e
d
g
e
a
b
o
u
t
t
h
e
d
e
si
g
n
,
c
o
n
s
t
r
u
c
t
i
o
n
,
a
n
d
mai
n
t
e
n
a
n
c
e
o
f
mac
h
i
n
e
r
y
a
n
d
e
q
u
i
p
me
n
t
u
se
d
i
n
t
h
e
o
i
l
a
n
d
g
a
s
i
n
d
u
s
t
r
y
.
Y
o
u
w
i
l
l
a
l
so
l
e
a
r
n
a
b
o
u
t
e
n
e
r
g
y
s
y
st
e
ms,
p
o
w
e
r
g
e
n
e
r
a
t
i
o
n
,
a
n
d
t
h
e
t
e
c
h
n
o
l
o
g
i
e
s u
se
d
i
n
o
i
l
e
x
p
l
o
r
a
t
i
o
n
a
n
d
p
r
o
d
u
c
t
i
o
n
.
C
h
o
o
se
t
h
e
maj
o
r
t
h
a
t
a
l
i
g
n
s
w
i
t
h
y
o
u
r
p
r
i
o
r
i
t
i
e
s!
I
f
y
o
u
a
r
e
mo
r
e
i
n
t
e
r
e
st
e
d
i
n
c
h
e
mi
c
a
l
p
r
o
c
e
s
se
s
a
n
d
t
h
e
t
r
a
n
sf
o
r
ma
t
i
o
n
o
f
p
e
t
r
o
l
e
u
m
i
n
t
o
p
r
o
d
u
c
t
s,
C
h
e
mi
c
a
l
E
n
g
i
n
e
e
r
i
n
g
w
o
u
l
d
b
e
a
g
r
e
a
t
c
h
o
i
c
e
.
H
o
w
e
v
e
r
,
i
f
y
o
u
a
r
e
mo
r
e
i
n
t
e
r
e
st
e
d
i
n
t
h
e
d
e
si
g
n
a
n
d
c
o
n
st
r
u
c
t
i
o
n
o
f
e
q
u
i
p
me
n
t
f
o
r
t
h
e
o
i
l
i
n
d
u
st
r
y
,
M
e
c
h
a
n
i
c
a
l
En
g
i
n
e
e
r
i
n
g
c
o
u
l
d
b
e
t
h
e
i
d
e
a
l
o
p
t
i
o
n
f
o
r
y
o
u
.
4.
CO
NCLU
SI
O
N
T
h
e
ex
p
e
r
im
en
ts
co
n
d
u
ct
ed
i
n
th
is
s
tu
d
y
d
em
o
n
s
tr
a
te
th
a
t
em
b
ed
d
in
g
m
o
d
els
,
p
a
r
ti
cu
la
r
ly
B
E
R
T
,
s
ig
n
if
ican
tly
en
h
an
ce
th
e
p
er
f
o
r
m
an
ce
o
f
d
ec
is
io
n
-
s
u
p
p
o
r
t
s
y
s
tem
s
f
o
r
u
n
iv
e
r
s
ity
m
ajo
r
s
el
e
cti
o
n
.
T
h
is
f
in
d
in
g
h
as
p
r
a
cti
ca
l
im
p
lic
ati
o
n
s
f
o
r
e
d
u
c
ati
o
n
al
in
s
ti
tu
ti
o
n
s
in
I
n
d
o
n
esi
a,
as
it
s
u
g
g
ests
th
at
A
I
-
d
r
iv
en
ch
at
b
o
ts
c
an
p
r
o
v
i
d
e
m
o
r
e
ac
cu
r
ate
an
d
p
e
r
s
o
n
ali
ze
d
r
e
co
m
m
en
d
atio
n
s
,
h
elp
in
g
s
tu
d
en
ts
m
ak
e
b
ett
er
-
in
f
o
r
m
ed
d
e
cisi
o
n
s
ab
o
u
t
th
ei
r
ac
a
d
em
ic
f
u
tu
r
es
.
Am
o
n
g
th
e
d
if
f
er
en
t
a
p
p
r
o
a
ch
es,
th
e
B
E
R
T
em
b
ed
d
i
n
g
m
o
d
el
ac
h
i
ev
e
d
th
e
h
ig
h
est
ac
cu
r
a
cy
,
w
ith
th
e
R
NN
an
d
L
STM
m
o
d
els
b
o
t
h
r
ea
ch
in
g
a
r
o
u
n
d
9
2
%
ac
cu
r
ac
y
in
tr
ain
in
g
an
d
test
in
g
p
h
ases
.
T
h
e
Gem
in
i
em
b
ed
d
in
g
m
o
d
el
als
o
s
h
o
w
ed
s
t
r
o
n
g
p
er
f
o
r
m
an
ce
,
th
o
u
g
h
s
lig
h
tly
lo
w
er
co
m
p
a
r
e
d
to
B
E
R
T
.
T
h
e
s
t
an
d
a
r
d
l
ay
er
em
b
ed
d
in
g
s
f
o
r
R
NN
an
d
L
S
T
M
m
o
d
els
in
d
ic
a
ted
ch
all
en
g
es
w
ith
o
v
e
r
f
itti
n
g
,
u
n
d
er
s
co
r
in
g
th
e
i
m
p
o
r
tan
ce
o
f
u
s
in
g
m
o
r
e
a
d
v
a
n
ce
d
em
b
e
d
d
in
g
s
f
o
r
im
p
r
o
v
e
d
g
en
er
ali
za
t
io
n
an
d
ac
cu
r
a
cy
.
B
ase
d
o
n
th
ese
f
in
d
in
g
s
,
it
is
r
ec
o
m
m
en
d
ed
t
o
u
ti
lize
th
e
B
E
R
T
em
b
ed
d
in
g
m
o
d
el
f
o
r
d
ev
el
o
p
in
g
d
e
cisi
o
n
-
s
u
p
p
o
r
t
s
y
s
tem
s
,
g
iv
en
its
s
u
p
e
r
i
o
r
p
er
f
o
r
m
an
ce
.
Fu
tu
r
e
w
o
r
k
s
h
o
u
l
d
f
o
cu
s
o
n
f
u
r
th
er
o
p
tim
izin
g
th
ese
m
o
d
e
ls
an
d
ex
p
l
o
r
in
g
a
d
d
it
io
n
a
l
en
h
an
c
em
en
ts
s
u
ch
as
f
in
e
-
tu
n
in
g
an
d
h
y
b
r
i
d
a
p
p
r
o
a
ch
es.
I
n
c
o
r
p
o
r
atin
g
u
s
er
f
e
ed
b
ac
k
an
d
co
n
t
in
u
o
u
s
ly
u
p
d
at
in
g
th
e
m
o
d
els
w
ith
n
e
w
d
at
a
w
ill
b
e
ess
en
tia
l
f
o
r
m
ain
tain
in
g
th
ei
r
r
el
ev
an
c
e
an
d
ef
f
ec
tiv
en
ess
in
g
u
id
in
g
s
tu
d
en
ts
th
r
o
u
g
h
th
e
ir
m
aj
o
r
s
ele
cti
o
n
p
r
o
ce
s
s
.
ACK
NO
WL
E
D
G
M
E
NT
S
Sp
ec
ial
th
a
n
k
s
to
C
ar
ee
r
De
v
elo
p
m
e
n
t
C
e
n
ter
o
f
Vo
ca
tio
n
al
Sch
o
o
l,
U
n
i
v
er
s
ita
s
Seb
ela
s
Ma
r
et
f
o
r
th
eir
s
u
p
p
o
r
t a
n
d
r
eso
u
r
ce
s
th
r
o
u
g
h
o
u
t t
h
is
r
esear
c
h
.
F
UNDIN
G
I
NF
O
RM
AT
I
O
N
T
h
is
r
esear
ch
w
as
f
u
n
d
ed
b
y
U
n
i
v
er
s
ita
s
Seb
elas
Ma
r
et
u
n
d
er
th
e
r
e
s
ea
r
ch
g
r
an
t
o
f
P
en
elitia
n
F
u
n
d
a
me
n
ta
l C
(
P
FC
-
UNS)
with
co
n
tr
ac
t
n
u
m
b
er
3
6
9
/UN2
7
.
2
2
/
PT
.
0
1
.
0
3
/
2
0
2
5
.
AUTHO
R
CO
NT
RIB
UT
I
O
NS ST
A
T
E
M
E
NT
T
h
is
j
o
u
r
n
al
u
s
e
s
th
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT
)
to
r
ec
o
g
n
ize
in
d
i
v
id
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
t
h
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
lla
b
o
r
atio
n
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
Mu
tia
r
a
A
u
liy
a
Kh
ad
i
ja
B
am
b
a
n
g
Har
j
ito
Mo
r
teza
Sab
er
i
A
s
t
r
i
d
N
o
v
i
a
n
a
P
a
r
a
d
h
i
t
a
W
ah
y
u
Nu
r
h
ar
j
ad
m
o
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
si
s
I
:
I
n
v
e
st
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
si
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
A
r
ti
f
I
n
tell
I
SS
N:
2252
-
8938
Gen
era
tive
I
n
d
o
n
esia
n
ch
a
t
b
o
t fo
r
u
n
ivers
ity
ma
jo
r
s
elec
tio
n
u
s
in
g
tr
a
n
s
fo
r
mers
…
(
Mu
ti
a
r
a
A
u
liya
K
h
a
d
ija
)
3481
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
t
h
o
r
s
s
tate
n
o
co
n
f
lic
t o
f
i
n
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
Data
av
ailab
ilit
y
i
s
n
o
t
ap
p
licab
le
to
th
is
p
ap
er
as
n
o
n
e
w
d
ata
w
er
e
cr
ea
ted
o
r
an
al
y
ze
d
in
th
i
s
s
tu
d
y
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
C
a
n
c
i
n
o
a
n
d
R
.
C
a
p
r
e
d
o
n
i
,
“
A
ssessi
n
g
p
r
e
-
se
r
v
i
c
e
EFL
t
e
a
c
h
e
r
s’
p
e
r
c
e
p
t
i
o
n
s
r
e
g
a
r
d
i
n
g
a
n
o
n
l
i
n
e
st
u
d
e
n
t
r
e
sp
o
n
se
s
y
st
e
m,”
T
a
i
w
a
n
J
o
u
r
n
a
l
o
f
T
E
S
O
L
,
v
o
l
.
1
7
,
n
o
.
2
,
p
p
.
9
1
–
1
1
8
,
2
0
2
0
,
d
o
i
:
1
0
.
3
0
3
9
7
/
T
JT
ESO
L
.
2
0
2
0
1
0
_
1
7
(
2
)
.
0
0
0
4
.
[
2
]
A
.
R
a
j
a
n
a
n
d
M
.
M
a
n
u
r
,
“
A
sp
e
c
t
b
a
se
d
se
n
t
i
me
n
t
a
n
a
l
y
si
s
u
si
n
g
f
i
n
e
-
t
u
n
e
d
B
ER
T
mo
d
e
l
w
i
t
h
d
e
e
p
c
o
n
t
e
x
t
f
e
a
t
u
r
e
s,”
I
AE
S
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
Ar
t
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
1
3
,
n
o
.
2
,
p
p
.
1
2
5
0
–
1
2
6
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
a
i
.
v
1
3
.
i
2
.
p
p
1
2
50
-
1
2
6
1
.
[
3
]
G
.
H
e
i
l
p
o
r
n
,
S
.
L
a
k
h
a
l
,
a
n
d
M
.
B
é
l
i
sl
e
,
“
A
n
e
x
a
mi
n
a
t
i
o
n
o
f
t
e
a
c
h
e
r
s’
st
r
a
t
e
g
i
e
s
t
o
f
o
st
e
r
st
u
d
e
n
t
e
n
g
a
g
e
me
n
t
i
n
b
l
e
n
d
e
d
l
e
a
r
n
i
n
g
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
E
d
u
c
a
t
i
o
n
a
l
T
e
c
h
n
o
l
o
g
y
i
n
H
i
g
h
e
r
E
d
u
c
a
t
i
o
n
,
v
o
l
.
1
8
,
n
o
.
1
,
2
0
2
1
,
d
o
i
:
1
0
.
1
1
8
6
/
s
4
1
2
3
9
-
021
-
0
0
2
6
0
-
3.
[
4
]
D
.
D
e
S
i
l
v
a
,
N
.
M
i
l
l
s,
M
.
El
-
A
y
o
u
b
i
,
M
.
M
a
n
i
c
,
a
n
d
D
.
A
l
a
h
a
k
o
o
n
,
“
C
h
a
t
G
P
T
a
n
d
g
e
n
e
r
a
t
i
v
e
A
I
g
u
i
d
e
l
i
n
e
s
f
o
r
a
d
d
r
e
ssi
n
g
a
c
a
d
e
mi
c
i
n
t
e
g
r
i
t
y
a
n
d
a
u
g
me
n
t
i
n
g
p
r
e
-
e
x
i
st
i
n
g
c
h
a
t
b
o
t
s
,
”
i
n
2
0
2
3
I
E
E
E
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
d
u
st
ri
a
l
T
e
c
h
n
o
l
o
g
y
,
2
0
2
3
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
I
T
5
8
4
6
5
.
2
0
2
3
.
1
0
1
4
3
1
2
3
.
[
5
]
T
.
G
o
o
d
a
l
e
,
“
U
si
n
g
g
e
n
e
r
a
t
i
v
e
A
I
t
o
h
e
l
p
w
i
t
h
st
a
t
i
s
t
i
c
a
l
t
e
st
se
l
e
c
t
i
o
n
a
n
d
a
n
a
l
y
si
s,”
M
S
O
R
C
o
n
n
e
c
t
i
o
n
s
,
v
o
l
.
2
2
,
n
o
.
3
,
p
p
.
1
0
–
1
6
,
2
0
2
4
,
d
o
i
:
1
0
.
2
1
1
0
0
/
mso
r
.
v
2
2
i
3
.
1
4
8
5
.
[
6
]
P
.
B
h
a
t
i
a
,
“
C
h
a
t
G
P
T
f
o
r
a
c
a
d
e
mi
c
w
r
i
t
i
n
g
:
a
g
a
me
c
h
a
n
g
e
r
o
r
a
d
i
s
r
u
p
t
i
v
e
t
o
o
l
?
,
”
J
o
u
rn
a
l
o
f
A
n
a
e
st
h
e
si
o
l
o
g
y
C
l
i
n
i
c
a
l
Ph
a
rm
a
c
o
l
o
g
y
,
v
o
l
.
3
9
,
n
o
.
1
,
p
p
.
1
–
2
,
2
0
2
3
,
d
o
i
:
1
0
.
4
1
0
3
/
j
o
a
c
p
.
j
o
a
c
p
_
8
4
_
2
3
.
[
7
]
G
.
I
l
i
e
v
a
,
T
.
Y
a
n
k
o
v
a
,
S
.
K
l
i
saro
v
a
-
B
e
l
c
h
e
v
a
,
A
.
D
i
mi
t
r
o
v
,
M
.
B
r
a
t
k
o
v
,
a
n
d
D
.
A
n
g
e
l
o
v
,
“
Ef
f
e
c
t
s
o
f
g
e
n
e
r
a
t
i
v
e
c
h
a
t
b
o
t
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
I
n
f
o
rm
a
t
i
o
n
,
v
o
l
.
1
4
,
n
o
.
9
,
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
i
n
f
o
1
4
0
9
0
4
9
2
.
[
8
]
D
.
S
e
b
a
st
i
a
n
,
H
.
D
.
P
u
r
n
o
mo
,
a
n
d
I
.
S
e
mb
i
r
i
n
g
,
“
B
E
R
T
f
o
r
n
a
t
u
r
a
l
l
a
n
g
u
a
g
e
p
r
o
c
e
ssi
n
g
i
n
B
a
h
a
sa
I
n
d
o
n
e
si
a
,
”
i
n
2
0
2
2
2
n
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
t
e
l
l
i
g
e
n
t
C
y
b
e
rn
e
t
i
c
s
T
e
c
h
n
o
l
o
g
y
&
Ap
p
l
i
c
a
t
i
o
n
s
(
I
C
I
C
y
T
A)
,
B
a
n
d
u
n
g
,
I
n
d
o
n
e
si
a
,
2
0
2
2
,
p
p
.
2
0
4
–
209
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
I
C
y
TA
5
7
4
2
1
.
2
0
2
2
.
1
0
0
3
8
2
3
0
.
[
9
]
U
.
L
e
ó
n
-
D
o
mí
n
g
u
e
z
,
“
P
o
t
e
n
t
i
a
l
c
o
g
n
i
t
i
v
e
r
i
sk
s
o
f
g
e
n
e
r
a
t
i
v
e
t
r
a
n
sf
o
r
me
r
-
b
a
se
d
A
I
c
h
a
t
b
o
t
s
o
n
h
i
g
h
e
r
o
r
d
e
r
e
x
e
c
u
t
i
v
e
f
u
n
c
t
i
o
n
s
,
”
N
e
u
ro
p
sy
c
h
o
l
o
g
y
,
v
o
l
.
3
8
,
n
o
.
4
,
p
p
.
2
9
3
–
3
0
8
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
3
7
/
n
e
u
0
0
0
0
9
4
8
.
[
1
0
]
C
.
E
.
S
t
o
i
a
n
,
M
.
A
.
F
ă
r
c
a
și
u
,
G
.
-
M
.
D
r
a
g
o
mi
r
,
a
n
d
V
.
G
h
e
r
h
e
ș,
“
T
r
a
n
si
t
i
o
n
f
r
o
m
o
n
l
i
n
e
t
o
f
a
c
e
-
to
-
f
a
c
e
e
d
u
c
a
t
i
o
n
a
f
t
e
r
C
O
V
I
D
-
1
9
:
t
h
e
b
e
n
e
f
i
t
s o
f
o
n
l
i
n
e
e
d
u
c
a
t
i
o
n
f
r
o
m st
u
d
e
n
t
s’
p
e
r
sp
e
c
t
i
v
e
,
”
S
u
st
a
i
n
a
b
i
l
i
t
y
,
v
o
l
.
1
4
,
n
o
.
1
9
,
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
s
u
1
4
1
9
1
2
8
1
2
.
[
1
1
]
H
.
D
i
n
g
,
K
.
C
h
e
n
,
W
.
H
u
,
M
.
C
a
i
,
a
n
d
Q
.
H
u
o
,
“
B
u
i
l
d
i
n
g
c
o
mp
a
c
t
C
N
N
-
D
B
L
S
T
M
b
a
se
d
c
h
a
r
a
c
t
e
r
mo
d
e
l
s
f
o
r
h
a
n
d
w
r
i
t
i
n
g
r
e
c
o
g
n
i
t
i
o
n
a
n
d
O
C
R
b
y
t
e
a
c
h
e
r
-
st
u
d
e
n
t
l
e
a
r
n
i
n
g
,
”
i
n
2
0
1
8
1
6
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
Fro
n
t
i
e
rs
i
n
H
a
n
d
w
r
i
t
i
n
g
Re
c
o
g
n
i
t
i
o
n
,
2
0
1
8
,
p
p
.
1
3
9
–
1
4
4
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
F
H
R
-
2
0
1
8
.
2
0
1
8
.
0
0
0
3
3
.
[
12]
A
.
N
.
A
q
i
l
,
B
.
D
i
r
g
a
n
t
a
r
a
,
I
st
i
k
mal
,
U
.
A
.
A
h
mad
,
a
n
d
R
.
R
.
S
e
p
t
i
a
w
a
n
,
“
R
o
b
o
t
c
h
a
t
sy
st
e
m
(
C
h
a
t
b
o
t
)
t
o
h
e
l
p
u
se
r
s
‘
H
o
mel
a
b
’
b
a
se
d
i
n
d
e
e
p
l
e
a
r
n
i
n
g
,
”
I
n
t
e
rn
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
d
v
a
n
c
e
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
1
2
,
n
o
.
8
,
p
p
.
5
9
9
–
6
0
4
,
2
0
2
1
,
d
o
i
:
1
0
.
1
4
5
6
9
/
I
J
A
C
S
A
.
2
0
2
1
.
0
1
2
0
8
7
0
.
[
1
3
]
A
.
B
a
b
u
a
n
d
S
.
B
.
B
o
d
d
u
,
“
B
E
R
T
-
b
a
se
d
me
d
i
c
a
l
c
h
a
t
b
o
t
:
e
n
h
a
n
c
i
n
g
h
e
a
l
t
h
c
a
r
e
c
o
mm
u
n
i
c
a
t
i
o
n
t
h
r
o
u
g
h
n
a
t
u
r
a
l
l
a
n
g
u
a
g
e
u
n
d
e
r
st
a
n
d
i
n
g
,
”
Ex
p
l
o
r
a
t
o
ry
Re
s
e
a
r
c
h
i
n
C
l
i
n
i
c
a
l
a
n
d
S
o
c
i
a
l
P
h
a
rm
a
c
y
,
v
o
l
.
1
3
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
c
so
p
.
2
0
2
4
.
1
0
0
4
1
9
.
[
1
4
]
A
.
A
.
-
A
l
r
a
z
a
q
,
Z
.
S
a
f
i
,
M
.
A
l
a
j
l
a
n
i
,
J.
W
a
r
r
e
n
,
M
.
H
o
u
se
h
,
a
n
d
K
.
D
e
n
e
c
k
e
,
“
T
e
c
h
n
i
c
a
l
me
t
r
i
c
s
u
se
d
t
o
e
v
a
l
u
a
t
e
h
e
a
l
t
h
c
a
r
e
c
h
a
t
b
o
t
s:
S
c
o
p
i
n
g
r
e
v
i
e
w
,
”
J
o
u
r
n
a
l
o
f
m
e
d
i
c
a
l
I
n
t
e
r
n
e
t
res
e
a
rc
h
,
v
o
l
.
2
2
,
n
o
.
6
,
p
p
.
1
–
1
5
,
2
0
2
0
.
[
1
5
]
O
.
A
h
a
n
e
k
u
,
M
.
S
i
e
g
l
,
S
.
S
t
r
o
mb
e
r
g
e
r
,
a
n
d
R
.
V
i
d
r
a
s
c
u
,
“
A
sca
l
a
b
l
e
A
I
-
d
r
i
v
e
n
c
h
a
t
b
o
t
f
o
r
r
e
a
l
-
t
i
me
d
i
a
g
n
o
st
i
c
s
i
n
ma
n
u
f
a
c
t
u
r
i
n
g
p
l
a
n
t
s:
me
r
g
i
n
g
g
o
o
g
l
e
d
i
a
l
o
g
f
l
o
w
,
B
ER
T
,
a
n
d
a
se
l
f
-
l
e
a
r
n
i
n
g
mo
d
u
l
e
,
”
i
n
2
0
2
3
I
EEE
1
2
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
I
n
t
e
l
l
i
g
e
n
t
D
a
t
a
A
c
q
u
i
si
t
i
o
n
a
n
d
Ad
v
a
n
c
e
d
C
o
m
p
u
t
i
n
g
S
y
s
t
e
m
s:
T
e
c
h
n
o
l
o
g
y
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
,
2
0
2
3
,
p
p
.
8
5
3
–
8
5
8
,
d
o
i
:
1
0
.
1
1
0
9
/
I
D
A
A
C
S
5
8
5
2
3
.
2
0
2
3
.
1
0
3
4
8
7
3
8
.
[
1
6
]
J.
R
u
d
o
l
p
h
,
S
.
T
a
n
,
a
n
d
S
.
T
a
n
,
“
C
h
a
t
G
P
T
:
b
u
l
l
sh
i
t
s
p
e
w
e
r
o
r
t
h
e
e
n
d
o
f
t
r
a
d
i
t
i
o
n
a
l
a
sse
ssm
e
n
t
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
?
,
”
J
o
u
r
n
a
l
o
f
Ap
p
l
i
e
d
L
e
a
r
n
i
n
g
a
n
d
T
e
a
c
h
i
n
g
,
v
o
l
.
6
,
n
o
.
1
,
p
p
.
3
4
2
–
3
6
3
,
2
0
2
3
,
d
o
i
:
1
0
.
3
7
0
7
4
/
j
a
l
t
.
2
0
2
3
.
6
.
1
.
9
.
[
1
7
]
J.
Ed
u
,
C
.
M
u
l
l
i
g
a
n
,
F
.
P
i
e
r
a
z
z
i
,
J.
P
o
l
a
k
i
s,
G
.
S
u
a
r
e
z
-
T
a
n
g
i
l
,
a
n
d
J.
S
u
c
h
,
“
Ex
p
l
o
r
i
n
g
t
h
e
se
c
u
r
i
t
y
a
n
d
p
r
i
v
a
c
y
r
i
sk
s o
f
c
h
a
t
b
o
t
s i
n
me
ss
a
g
i
n
g
se
r
v
i
c
e
s,”
i
n
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
2
2
n
d
AC
M
I
n
t
e
r
n
e
t
Me
a
s
u
r
e
m
e
n
t
C
o
n
f
e
re
n
c
e
,
2
0
2
2
,
p
p
.
5
8
1
–
5
8
8
,
d
o
i
:
1
0
.
1
1
4
5
/
3
5
1
7
7
4
5
.
3
5
6
1
4
3
3
.
[
1
8
]
G
.
K
.
D
.
G
o
p
i
se
t
t
y
,
D
.
E.
Te
j
a
,
G
.
V
.
S
.
K
u
mar,
D
.
R
.
D
i
n
e
sh
,
a
n
d
C
.
A
k
h
i
l
,
“
C
h
a
t
b
o
t
b
u
i
l
d
i
n
g
w
i
t
h
B
E
R
T
f
o
r
e
-
c
o
mm
e
r
c
e
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
f
o
r
R
e
se
a
rc
h
i
n
Ap
p
l
i
e
d
S
c
i
e
n
c
e
a
n
d
En
g
i
n
e
e
r
i
n
g
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
2
,
n
o
.
3
,
p
p
.
2
5
8
7
–
2
5
9
2
,
2
0
2
4
,
d
o
i
:
1
0
.
2
2
2
1
4
/
i
j
r
a
se
t
.
2
0
2
4
.
5
9
4
4
9
.
[
1
9
]
K
.
N
a
i
k
,
N
.
L
a
k
s
h
mi
,
B
.
H
.
N
e
h
a
,
D
.
N
i
d
h
i
,
a
n
d
R
.
G
a
t
t
i
,
“
D
e
si
g
n
o
f
a
n
A
I
c
h
a
t
b
o
t
u
si
n
g
g
e
n
e
r
a
t
i
v
e
A
I
t
o
a
c
c
e
ss
l
o
c
a
l
d
a
t
a
b
a
se
,
”
I
n
t
e
r
a
n
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
S
c
i
e
n
t
i
f
i
c
Re
s
e
a
rc
h
i
n
En
g
i
n
e
e
ri
n
g
a
n
d
Ma
n
a
g
e
m
e
n
t
,
v
o
l
.
8
,
n
o
.
5
,
p
p
.
1
–
9
,
2
0
2
4
,
d
o
i
:
1
0
.
5
5
0
4
1
/
i
j
sr
e
m3
3
8
6
3
.
[
2
0
]
C
.
K
.
Y
.
C
h
a
n
a
n
d
W
.
H
u
,
“
S
t
u
d
e
n
t
s’
v
o
i
c
e
s
o
n
g
e
n
e
r
a
t
i
v
e
A
I
:
p
e
r
c
e
p
t
i
o
n
s,
b
e
n
e
f
i
t
s
,
a
n
d
c
h
a
l
l
e
n
g
e
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
E
d
u
c
a
t
i
o
n
a
l
T
e
c
h
n
o
l
o
g
y
i
n
H
i
g
h
e
r E
d
u
c
a
t
i
o
n
,
v
o
l
.
2
0
,
n
o
.
1
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
8
6
/
s
4
1
2
3
9
-
0
2
3
-
0
0
4
1
1
-
8.
[
2
1
]
J.
E.
C
h
u
k
w
u
e
r
e
,
“
T
h
e
f
u
t
u
r
e
o
f
g
e
n
e
r
a
t
i
v
e
A
I
c
h
a
t
b
o
t
s i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
a
r
Xi
v
-
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
p
p
.
1
–
1
5
,
2
0
2
4
.
[
2
2
]
N
.
Esf
a
n
d
i
a
r
i
,
K
.
K
i
a
n
i
,
a
n
d
R
.
R
a
st
g
o
o
,
“
A
c
o
n
d
i
t
i
o
n
a
l
g
e
n
e
r
a
t
i
v
e
c
h
a
t
b
o
t
u
si
n
g
t
r
a
n
sf
o
r
me
r
mo
d
e
l
,
”
a
rXi
v
-
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
p
p
.
1
–
1
2
,
2
0
2
3
.
[
2
3
]
H
.
W
a
n
g
,
S
.
T
a
n
g
,
a
n
d
C
.
U
.
L
e
i
,
“
A
I
c
o
n
v
e
r
sat
i
o
n
a
l
a
g
e
n
t
d
e
si
g
n
f
o
r
su
p
p
o
r
t
i
n
g
l
e
a
r
n
i
n
g
a
n
d
w
e
l
l
-
b
e
i
n
g
o
f
u
n
i
v
e
r
si
t
y
st
u
d
e
n
t
s,
”
Ed
Ar
Xi
v
Pre
p
r
i
n
t
s
,
p
p
.
1
–
1
4
,
2
0
2
4
,
d
o
i
:
1
0
.
3
5
5
4
2
/
o
sf
.
i
o
/
w
4
r
t
f
.
[
2
4
]
L
.
J.
Q
u
i
n
t
a
n
s
-
J
ú
n
i
o
r
,
R
.
Q
.
G
u
r
g
e
l
,
A
.
A
.
d
e
S
.
A
r
a
ú
j
o
,
D
.
C
o
r
r
e
i
a
,
a
n
d
P
.
R
.
M
a
r
t
i
n
s
-
F
i
l
h
o
,
“
C
h
a
t
G
P
T:
t
h
e
n
e
w
p
a
n
a
c
e
a
o
f
t
h
e
a
c
a
d
e
mi
c
w
o
r
l
d
,
”
J
o
u
r
n
a
l
o
f
t
h
e
Bra
zi
l
i
a
n
S
o
c
i
e
t
y
o
f
T
r
o
p
i
c
a
l
Me
d
i
c
i
n
e
,
v
o
l
.
5
6
,
2
0
2
3
,
d
o
i
:
1
0
.
1
5
9
0
/
0
0
3
7
-
8
6
8
2
-
0
0
6
0
-
2
0
2
3
.
[
2
5
]
A
.
M
a
t
h
a
r
a
a
r
a
c
h
c
h
i
e
t
a
l
.
,
“
O
p
t
i
mi
z
i
n
g
g
e
n
e
r
a
t
i
v
e
A
I
c
h
a
t
b
o
t
s
f
o
r
n
e
t
-
z
e
r
o
e
mi
ssi
o
n
s
e
n
e
r
g
y
i
n
t
e
r
n
e
t
-
of
-
t
h
i
n
g
s
i
n
f
r
a
s
t
r
u
c
t
u
r
e
,
”
En
e
r
g
i
e
s
,
v
o
l
.
1
7
,
n
o
.
8
,
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
7
0
8
1
9
3
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8938
I
n
t J
A
r
ti
f
I
n
tell
,
Vo
l.
14
,
No
.
4
,
A
u
g
u
s
t 2
0
2
5
:
3
4
7
4
-
3482
3482
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
M
u
tia
r
a
A
u
li
y
a
K
h
a
d
ija
is a
d
a
ta an
a
ly
st,
d
a
ta sc
ien
ti
st
,
a
n
d
lec
tu
re
r
w
it
h
a
so
li
d
b
a
c
k
g
ro
u
n
d
in
I
n
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
f
ro
m
th
e
F
a
c
u
lt
y
o
f
En
g
i
n
e
e
rin
g
,
Un
iv
e
rsitas
G
a
d
jah
M
a
d
a
,
In
d
o
n
e
sia
.
He
r
e
x
p
e
rti
se
sp
a
n
s
a
c
ro
ss
m
a
c
h
in
e
lea
rn
in
g
,
b
u
sin
e
ss
in
telli
g
e
n
c
e
,
b
ig
d
a
ta
re
se
a
rc
h
,
a
n
d
sm
a
rt
c
it
y
d
e
v
e
lo
p
m
e
n
t
.
W
it
h
o
v
e
r
f
iv
e
y
e
a
rs
o
f
e
x
p
e
rien
c
e
in
d
a
ta
sc
ien
c
e
c
o
n
su
lt
i
n
g
a
n
d
p
r
o
f
e
ss
io
n
a
l
m
e
n
t
o
rsh
ip
,
sh
e
h
a
s
su
c
c
e
ss
f
u
ll
y
l
e
d
a
n
d
c
o
n
tri
b
u
ted
t
o
n
u
m
e
ro
u
s
AI
-
d
riv
e
n
p
ro
jec
ts,
in
c
l
u
d
i
n
g
n
a
tu
ra
l
lan
g
u
a
g
e
p
ro
c
e
ss
in
g
(NL
P
)
a
p
p
l
ica
ti
o
n
s,
se
n
ti
m
e
n
t
a
n
a
ly
sis,
a
n
d
p
re
d
ictiv
e
m
o
d
e
li
n
g
.
S
h
e
is
a
lso
a
n
a
c
ti
v
e
m
e
m
b
e
r
o
f
th
e
A
ss
o
c
iatio
n
o
f
In
d
o
n
e
sia
n
Co
m
p
u
ter an
d
In
f
o
rm
a
ti
c
s Co
ll
e
g
e
s (
A
P
T
IKO
M
)
a
n
d
t
h
e
In
stit
u
te o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
E
n
g
in
e
e
rs
(IE
EE
),
f
u
rth
e
r
d
e
m
o
n
stra
ti
n
g
h
e
r
c
o
m
m
it
m
e
n
t
to
p
r
o
f
e
ss
io
n
a
l
a
n
d
a
c
a
d
e
m
ic co
ll
a
b
o
ra
ti
o
n
a
t
b
o
th
n
a
ti
o
n
a
l
a
n
d
in
tern
a
ti
o
n
a
l
lev
e
ls.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
u
ti
a
ra
a
u
li
y
a
@
sta
ff
.
u
n
s.a
c
.
id
.
Pro
f.
Dr
s.
B
a
m
b
a
n
g
H
a
r
jito
is
a
se
n
io
r
lec
tu
re
r
in
th
e
De
p
a
rt
m
e
n
t
o
f
In
f
o
rm
a
ti
c
s,
F
a
c
u
lt
y
o
f
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
a
n
d
Da
ta
S
c
ien
c
e
,
Un
iv
e
rsitas
S
e
b
e
las
M
a
re
t,
S
u
ra
k
a
rta,
In
d
o
n
e
sia
.
He
e
a
rn
e
d
h
is
M
a
ste
r'
s
d
e
g
re
e
in
Co
m
p
u
ter
S
c
ien
c
e
f
ro
m
J
a
m
e
s
Co
o
k
Un
iv
e
rsit
y
in
2
0
0
0
a
n
d
h
is
P
h
.
D.
in
I
n
f
o
rm
a
ti
o
n
S
y
ste
m
s
f
ro
m
Cu
rti
n
Un
iv
e
rsity
,
P
e
rth
,
A
u
stra
li
a
,
in
2
0
1
4
.
His
re
se
a
rc
h
f
o
c
u
se
s
o
n
d
a
ta
p
r
o
te
c
ti
o
n
,
p
riv
a
c
y
p
ro
tec
ti
o
n
,
i
n
f
o
rm
a
ti
o
n
h
id
i
n
g
,
c
ry
p
to
g
ra
p
h
y
,
a
n
d
c
y
b
e
rs
e
c
u
rit
y
.
He
is
a
lso
a
n
a
c
ti
v
e
m
e
m
b
e
r
o
f
th
e
A
ss
o
c
iatio
n
o
f
In
d
o
n
e
sia
n
Co
m
p
u
ter
a
n
d
In
f
o
rm
a
ti
c
s
Co
ll
e
g
e
s
(
A
P
T
IKO
M
).
H
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
b
a
m
b
a
n
g
_
h
a
rji
to
@s
taff
.
u
n
s.a
c
.
id
.
Dr
.
M
o
r
te
z
a
S
a
b
e
r
i
is
c
u
rre
n
tl
y
a
S
e
n
io
r
L
e
c
tu
re
r
(A
ss
o
c
iate
P
ro
f
e
ss
o
r)
a
t
th
e
S
c
h
o
o
l
o
f
Co
m
p
u
ter
S
c
ien
c
e
,
Un
iv
e
rsit
y
o
f
Tec
h
n
o
lo
g
y
S
y
d
n
e
y
.
He
h
a
s
a
n
o
u
tsta
n
d
i
n
g
re
se
a
rc
h
re
c
o
rd
a
n
d
sig
n
if
ica
n
t
c
a
p
a
b
il
it
ies
i
n
t
h
e
a
re
a
o
f
b
u
si
n
e
ss
in
telli
g
e
n
c
e
,
d
a
ta
m
in
in
g
a
n
d
a
p
p
li
e
d
m
a
c
h
in
e
lea
rn
in
g
.
H
e
h
a
s
p
u
b
li
sh
e
d
m
o
re
th
a
n
2
3
0
p
a
p
e
rs
in
re
p
u
tab
le
a
c
a
d
e
m
ic
jo
u
r
n
a
ls
a
n
d
c
o
n
f
e
re
n
c
e
p
ro
c
e
e
d
i
n
g
s.
His
G
o
o
g
le
S
c
h
o
lar
c
it
a
ti
o
n
s
a
n
d
h
-
in
d
e
x
a
re
6
1
0
0
a
n
d
3
8
,
re
sp
e
c
ti
v
e
ly
.
P
re
v
io
u
sly
h
e
wa
s
a
lec
tu
re
r
a
t
th
e
U
NSW
,
Bu
si
n
e
ss
sc
h
o
o
l
f
o
r
a
b
o
u
t
t
h
re
e
y
e
a
rs.
H
e
h
a
s
w
o
n
o
v
e
r
3
5
n
a
ti
o
n
a
l
a
n
d
in
tern
a
ti
o
n
a
l
re
se
a
rc
h
a
w
a
r
d
s a
n
d
re
c
o
g
n
it
i
o
n
s ti
ll
d
a
te
f
ro
m
h
is
re
se
a
rc
h
.
He
h
a
s
a
b
ro
a
d
in
tere
st
in
th
e
e
m
e
rg
in
g
f
o
rm
s
o
f
so
c
ieta
l
-
sc
a
l
e
h
u
m
a
n
-
c
o
m
p
u
ter
s
y
ste
m
s
th
a
t
c
u
rre
n
tl
y
g
o
v
e
rn
a
n
d
f
a
c
il
it
a
te
k
n
o
w
led
g
e
e
x
c
h
a
n
g
e
a
m
o
n
g
in
d
iv
id
u
a
l
s
a
n
d
o
rg
a
n
iza
ti
o
n
s
.
Ex
isti
n
g
re
se
a
rc
h
h
a
s
p
rim
a
ril
y
f
o
c
u
se
d
o
n
e
n
h
a
n
c
in
g
th
e
p
e
rf
o
r
m
a
n
c
e
o
f
th
e
se
s
y
st
e
m
s
th
ro
u
g
h
th
e
d
e
v
e
lo
p
m
e
n
t
o
f
m
a
c
h
in
e
lea
rn
in
g
m
o
d
e
ls.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
o
rtez
a
.
sa
b
e
ri@u
ts.ed
u
.
a
u
.
As
tr
id
No
v
ia
n
a
Pa
r
a
d
h
ita
h
o
ld
s
a
M
a
ste
r
o
f
Co
m
p
u
ter
S
c
ien
c
e
(M
.
S
c
.
)
in
Un
iv
e
rsitas
G
a
d
jah
M
a
d
a
,
In
d
o
n
e
sia
.
S
h
e
is
c
u
rre
n
tl
y
lec
tu
rin
g
in
Un
iv
e
rsitas
S
e
b
e
las
M
a
re
t,
S
u
ra
k
a
rta,
In
d
o
n
e
sia
.
He
r
re
s
e
a
rc
h
a
re
a
s
o
f
in
tere
st
in
c
lu
d
e
d
e
c
isio
n
su
p
p
o
r
t
sy
ste
m
,
a
rti
f
icia
l
in
telli
g
e
n
t,
a
n
d
b
u
si
n
e
ss
in
telli
g
e
n
c
e
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
strid
.
n
o
v
ian
a
@s
taff
.
u
n
s.a
c
.
id
.
Wa
h
y
u
N
u
r
h
a
r
ja
d
m
o
is
a
lec
tu
re
r
a
t
F
a
c
u
lt
y
o
f
S
o
c
ial
a
n
d
P
o
li
ti
c
a
l
S
c
ien
c
e
s,
Un
iv
e
rsitas
S
e
b
e
las
M
a
re
t,
In
d
o
n
e
sia
.
He
e
a
rn
e
d
h
is
M
a
ste
r'
s
d
e
g
r
e
e
in
P
u
b
li
c
A
d
m
in
istratio
n
f
ro
m
Un
iv
e
r
sitas
Ga
d
jah
M
a
d
a
,
In
d
o
n
e
sia
.
His
re
se
a
r
c
h
in
tere
sts
f
o
c
u
s
o
n
th
e
a
p
p
li
c
a
ti
o
n
o
f
p
u
b
li
c
p
o
li
c
y
,
p
u
b
li
c
a
d
m
in
istrati
o
n
,
e
lec
tro
n
ic
g
o
v
e
rn
m
e
n
t,
a
n
d
s
m
a
rt
c
it
y
.
He
is
a
m
e
m
b
e
r
o
f
th
e
In
d
o
n
e
sia
n
A
ss
o
c
iatio
n
f
o
r
P
u
b
li
c
A
d
m
in
istratio
n
(IA
P
A
).
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
w
a
h
y
u
n
u
rh
a
rjad
m
o
@s
ta
ff
.
u
n
s.a
c
.
id
.
Evaluation Warning : The document was created with Spire.PDF for Python.