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Explora
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3
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Au
ti
sm
sp
e
c
tru
m
d
iso
r
d
e
r
(AS
D)
p
re
se
n
ts
a
c
o
m
p
lex
a
n
d
d
i
v
e
rse
se
t
o
f
c
h
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e
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g
e
s,
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e
c
e
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it
a
ti
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g
in
n
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a
ti
v
e
a
n
d
d
a
ta
-
d
riv
e
n
a
p
p
ro
a
c
h
e
s
fo
r
e
ffe
c
ti
v
e
u
n
d
e
rsta
n
d
i
n
g
,
d
ia
g
n
o
sis,
a
n
d
i
n
terv
e
n
ti
o
n
.
T
h
is
re
v
iew
e
x
p
l
o
r
e
s
re
c
e
n
t
a
d
v
a
n
c
e
m
e
n
ts
in
m
e
th
o
d
o
l
o
g
ies
,
tec
h
n
o
lo
g
ies
,
a
n
d
fra
m
e
wo
rk
s
a
i
m
e
d
a
t
a
d
d
re
ss
in
g
ASD
a
n
d
a
lso
h
i
g
h
l
ig
h
ts
n
o
v
e
l
d
a
ta
c
o
ll
e
c
ti
o
n
m
e
th
o
d
s
,
fo
c
u
si
n
g
o
n
th
e
in
teg
ra
ti
o
n
o
f
we
a
ra
b
le
in
tern
e
t
o
f
t
h
in
g
s
(Io
T)
se
n
so
rs
fo
r
re
a
l
-
ti
m
e
b
e
h
a
v
i
o
ra
l
m
o
n
it
o
ri
n
g
a
n
d
d
a
t
a
c
a
p
tu
re
fro
m
i
n
d
i
v
id
u
a
ls
wi
th
ASD.
Ad
d
it
i
o
n
a
ll
y
,
th
e
u
ti
li
z
a
ti
o
n
o
f
m
a
c
h
in
e
lea
rn
in
g
(
M
L),
d
e
e
p
lea
rn
in
g
(DL),
a
n
d
h
y
b
ri
d
tec
h
n
i
q
u
e
s
fo
r
d
a
ta
a
n
a
ly
sis,
fe
a
tu
re
o
p
ti
m
iza
ti
o
n
,
a
n
d
p
re
d
ictio
n
o
f
ASD
a
re
e
x
ten
siv
e
ly
d
isc
u
ss
e
d
,
sh
o
wc
a
sin
g
sig
n
ifi
c
a
n
t
p
ro
g
re
ss
in
e
a
rly
d
iag
n
o
sis
a
n
d
p
e
rso
n
a
li
z
e
d
i
n
terv
e
n
ti
o
n
p
lan
n
i
n
g
.
T
h
e
c
h
a
ll
e
n
g
e
s
su
c
h
a
s
c
las
s
imb
a
lan
c
e
,
fe
a
tu
re
se
lec
ti
o
n
,
a
n
d
d
a
ta
c
o
ll
e
c
ti
o
n
e
ffici
e
n
c
y
a
re
id
e
n
ti
fie
d
a
n
d
a
d
d
re
ss
e
d
u
sin
g
t
h
e
p
r
o
p
o
se
d
ASD
fra
m
e
wo
rk
.
T
h
e
re
v
iew
a
lso
e
m
p
h
a
siz
e
s
th
e
d
e
v
e
lo
p
m
e
n
t
o
f
re
c
o
m
m
e
n
d
a
ti
o
n
sy
ste
m
s
d
e
sig
n
e
d
t
o
th
e
u
n
i
q
u
e
b
e
h
a
v
io
ra
l
p
ro
fil
e
s
a
n
d
n
e
e
d
s
o
f
in
d
i
v
id
u
a
ls
with
ASD.
Th
e
fin
d
in
g
s
re
v
e
a
l
th
a
t
i
n
teg
ra
ti
n
g
t
h
e
se
a
d
v
a
n
c
e
d
tec
h
n
o
l
o
g
ies
a
n
d
m
e
th
o
d
o
lo
g
ies
c
a
n
lea
d
t
o
m
o
re
a
c
c
u
ra
te
d
iag
n
o
se
s
a
n
d
e
ffe
c
ti
v
e
in
terv
e
n
t
io
n
s,
c
o
n
tri
b
u
ti
n
g
to
th
e
b
ro
a
d
e
r
fiel
d
o
f
ASD
re
se
a
rc
h
.
K
ey
w
o
r
d
s
:
Au
tis
m
s
p
ec
tr
u
m
d
is
o
r
d
er
C
las
s
im
b
alan
ce
Dee
p
lear
n
in
g
Featu
r
e
s
elec
tio
n
I
n
ter
n
et
o
f
th
in
g
s
Ma
ch
in
e
lear
n
in
g
R
ec
o
m
m
en
d
atio
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
:
Kav
ith
a
Gan
g
ar
aju
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
Scie
n
ce
an
d
E
n
g
in
ee
r
in
g
,
M
S
R
a
m
aiah
I
n
s
titu
te
o
f
T
ec
h
n
o
l
o
g
y
Af
f
liated
to
Vis
v
esv
ar
ay
a
T
ec
h
n
o
lo
g
ical
U
n
iv
er
s
ity
B
elag
av
i
-
5
9
0
0
1
8
,
I
n
d
ia
E
m
ail: k
av
ith
ag
an
g
ar
aju
5
6
7
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Au
tis
m
is
a
n
eu
r
o
-
d
ev
elo
p
m
en
tal
d
is
o
r
d
er
th
at
p
r
o
f
o
u
n
d
ly
im
p
ac
ts
th
e
s
o
cial
g
r
o
wth
an
d
d
ev
elo
p
m
e
n
t
o
f
b
o
t
h
ch
ild
r
en
an
d
ad
u
lts
.
W
h
ile
a
co
m
p
lete
cu
r
e
r
em
ain
s
u
n
d
is
co
v
e
r
ed
,
ea
r
ly
d
iag
n
o
s
is
p
lay
s
a
p
iv
o
tal
r
o
le
in
e
n
ab
lin
g
m
o
r
e
ef
f
ec
tiv
e
tr
ea
tm
e
n
t
co
m
p
ar
e
d
t
o
tr
ad
itio
n
al
b
eh
a
v
io
r
al
ass
ess
m
en
ts
,
wh
ich
ar
e
o
f
ten
tim
e
-
c
o
n
s
u
m
in
g
in
id
en
tify
in
g
a
n
d
d
iag
n
o
s
in
g
au
tis
m
s
p
ec
tr
u
m
d
is
o
r
d
er
(
ASD)
t
h
r
o
u
g
h
clin
ic
-
b
ased
o
b
s
er
v
atio
n
s
[
1
]
.
Alth
o
u
g
h
ASD
is
co
m
m
o
n
ly
d
iag
n
o
s
ed
i
n
ch
ild
r
en
ar
o
u
n
d
th
e
ag
e
o
f
2
,
it
ca
n
also
b
e
id
en
tifie
d
later
d
e
p
en
d
in
g
o
n
th
e
co
m
p
le
x
ity
an
d
s
ev
er
ity
o
f
s
y
m
p
to
m
s
[
2
]
.
E
n
v
ir
o
n
m
en
tal
f
ac
to
r
s
an
d
g
en
etic
lin
k
s
ar
e
s
ig
n
if
ican
t
c
o
n
tr
ib
u
to
r
s
to
ASD,
af
f
ec
tin
g
n
o
t
ju
s
t
th
e
n
er
v
o
u
s
s
y
s
tem
b
u
t
also
s
o
cial
an
d
co
g
n
itiv
e
s
k
ills
[
3
]
.
Sy
m
p
to
m
s
v
ar
y
wid
ely
in
i
n
te
n
s
ity
an
d
p
r
esen
tatio
n
,
with
co
m
m
o
n
in
d
icato
r
s
in
cl
u
d
in
g
d
if
f
icu
lties
in
s
o
cial
co
m
m
u
n
i
ca
tio
n
,
o
b
s
ess
iv
e
in
ter
ests
,
an
d
r
ep
etitiv
e
b
eh
av
i
o
r
s
[
3
]
.
Ac
cu
r
ate
d
etec
tio
n
o
f
ASD
n
ec
ess
itate
s
co
m
p
r
eh
en
s
iv
e
ev
alu
atio
n
s
an
d
ass
ess
m
en
ts
co
n
d
u
cte
d
b
y
h
ea
lth
ca
r
e
p
r
o
f
e
s
s
io
n
als
an
d
p
s
y
ch
o
lo
g
is
ts
.
E
ar
l
y
in
ter
v
en
tio
n
an
d
d
iag
n
o
s
is
ar
e
cr
u
ci
al
as
th
ey
ca
n
id
en
tif
y
s
y
m
p
to
m
s
an
d
im
p
r
o
v
e
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:
2
5
0
2
-
4
7
52
E
xp
lo
r
a
tio
n
o
f v
a
r
io
u
s
a
p
p
r
o
a
ch
es fo
r
d
etec
tio
n
o
f
a
u
tis
m
s
p
ec
tr
u
m
d
is
o
r
d
er
(
K
a
vith
a
Ga
n
g
a
r
a
ju
)
633
o
v
er
all
q
u
ality
o
f
life
[
4
]
.
Ho
wev
er
,
th
e
d
ia
g
n
o
s
tic
p
r
o
ce
s
s
f
o
r
ASD
ca
n
b
e
tim
e
-
co
n
s
u
m
i
n
g
a
n
d
ch
allen
g
i
n
g
,
esp
ec
ially
wh
en
r
ely
in
g
s
o
l
ely
o
n
b
eh
a
v
io
r
al
o
b
s
er
v
atio
n
s
in
clin
ical
s
ettin
g
s
.
W
h
ile
v
ar
io
u
s
clin
ical
ap
p
r
o
ac
h
es
ex
is
t
f
o
r
ea
r
ly
d
et
ec
tio
n
,
th
ey
ar
e
n
o
t
f
r
eq
u
en
tl
y
u
tili
ze
d
u
n
less
th
er
e
is
a
h
ig
h
p
r
ed
ictiv
e
r
is
k
o
f
ASD
d
ev
elo
p
m
en
t [
5
]
.
Ma
ch
in
e
lear
n
i
n
g
(
ML
)
o
f
f
e
r
s
a
p
r
o
m
is
in
g
a
v
en
u
e
f
o
r
tr
ai
n
in
g
ASD
m
o
d
els
ef
f
icien
tly
with
h
ig
h
ac
cu
r
ac
y
[
6
]
,
as
p
r
esen
ted
in
Fig
u
r
e
1
.
ML
tech
n
iq
u
es
s
tr
e
am
lin
e
ASD
r
is
k
ass
ess
m
en
t
an
d
th
e
d
iag
n
o
s
tic
p
r
o
ce
s
s
,
ac
ce
ler
atin
g
ac
ce
s
s
to
cr
itical
th
er
ap
ies
f
o
r
af
f
ec
te
d
in
d
iv
id
u
als
an
d
th
eir
f
am
ilie
s
[
7
]
.
C
lass
if
ica
tio
n
m
o
d
els
in
ML
ca
n
aid
in
ea
r
l
y
p
r
e
d
ictio
n
o
f
au
tis
m
,
p
r
ev
en
tin
g
lo
n
g
-
ter
m
e
f
f
ec
ts
in
b
o
th
ch
ild
r
en
a
n
d
a
d
u
lts
[
8
]
.
Ad
d
itio
n
ally
,
co
m
p
u
tatio
n
al
tech
n
iq
u
es su
ch
as in
ter
n
et
o
f
th
in
g
s
(
I
o
T
)
-
b
ased
s
o
lu
tio
n
s
an
d
d
ee
p
lear
n
in
g
(
DL
)
m
o
d
els
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
f
o
r
ASD
d
etec
tio
n
a
n
d
h
ea
lth
ca
r
e
m
an
a
g
em
en
t
[
9
]
-
[
1
1
]
.
Desp
ite
th
ese
ad
v
an
ce
m
e
n
ts
,
ch
allen
g
es
p
er
s
is
t
in
ac
q
u
ir
in
g
lar
g
e
d
atasets
f
o
r
m
o
d
el
t
r
ain
in
g
d
u
e
to
d
at
a
p
r
iv
ac
y
c
o
n
ce
r
n
s
an
d
r
eg
u
lato
r
y
b
ar
r
ie
r
s
[
1
2
]
.
Secu
r
ity
an
d
p
r
iv
ac
y
is
s
u
es
s
u
r
r
o
u
n
d
in
g
d
ata
tr
an
s
m
is
s
io
n
also
p
o
s
e
ad
d
itio
n
al
h
u
r
d
les
in
d
ep
lo
y
in
g
ML
m
o
d
els
f
o
r
ASD
d
iag
n
o
s
is
[
1
3
]
,
[
1
4
]
.
Ho
wev
er
,
th
is
s
u
r
v
ey
f
o
cu
s
es
o
n
lev
er
ag
i
n
g
wea
r
ab
le
in
ter
n
et
-
of
-
th
in
g
s
(
W
I
o
T
s
)
to
co
llect
s
en
s
o
r
y
an
d
b
eh
a
v
io
r
al
d
ata
f
r
o
m
au
tis
m
p
atien
ts
ef
f
icien
tly
,
with
m
in
im
al
laten
cy
an
d
e
n
er
g
y
co
n
s
u
m
p
tio
n
[
1
5
]
.
W
I
o
T
s
f
ac
ilit
ate
wir
eles
s
co
n
n
ec
tiv
ity
in
b
o
d
y
ar
ea
n
etwo
r
k
s
,
en
h
a
n
cin
g
r
em
o
te
h
ea
lth
ca
r
e
an
d
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
f
o
r
au
tis
m
p
atien
ts
[
1
6
]
.
Fig
u
r
e
1
.
ML
ASD
d
etec
tio
n
a
n
d
p
r
e
d
ictio
n
T
o
ad
d
r
ess
lim
itatio
n
s
in
cu
r
r
e
n
t M
L
an
d
DL
m
eth
o
d
o
lo
g
ies r
elate
d
to
f
ea
tu
r
e
s
elec
tio
n
,
d
a
taset si
ze
,
an
d
ac
cu
r
ac
y
ac
r
o
s
s
d
if
f
er
e
n
t
n
eu
r
o
lo
g
ical
d
is
o
r
d
er
s
,
th
is
s
u
r
v
ey
tr
ies
to
id
en
tify
th
e
g
ap
s
,
is
s
u
es
an
d
ch
allen
g
es
o
f
t
h
e
cu
r
r
en
t
e
x
is
tin
g
ap
p
r
o
ac
h
es.
M
o
r
eo
v
er
,
th
i
s
wo
r
k
p
r
o
p
o
s
es
a
n
en
s
em
b
le
lear
n
in
g
a
p
p
r
o
a
ch
with
ef
f
ec
tiv
e
f
ea
tu
r
e
s
elec
tio
n
tech
n
iq
u
e.
T
h
e
g
o
al
is
to
d
e
v
elo
p
a
r
o
b
u
s
t
f
ea
tu
r
e
-
b
ased
c
lass
if
ier
u
s
in
g
ML
to
im
p
r
o
v
e
class
if
icatio
n
ac
cu
r
ac
y
in
ca
teg
o
r
izin
g
p
atien
t
s
as
ei
th
er
h
av
in
g
o
r
n
o
t
h
a
v
in
g
ASD
,
ac
r
o
s
s
d
if
f
er
en
t
ag
e
g
r
o
u
p
s
.
Ultim
ately
,
th
e
aim
is
to
cr
ea
te
an
ef
f
icien
t
r
ec
o
m
m
e
n
d
er
s
y
s
tem
f
o
r
ca
teg
o
r
izin
g
au
tis
m
p
atien
ts
(
ch
ild
r
en
,
ad
o
lescen
ts
,
an
d
ad
u
lts
)
b
ased
o
n
n
o
v
el
f
ea
t
u
r
es
ex
tr
ac
ted
f
r
o
m
wea
r
ab
le
I
o
T
d
ev
ices.
T
h
e
co
n
tr
ib
u
tio
n
o
f
th
is
s
u
r
v
ey
is
as f
o
llo
ws
:
−
T
h
e
s
u
r
v
ey
cr
itically
ex
am
in
es
cu
r
r
en
t
ML
an
d
DL
m
eth
o
d
o
lo
g
ies,
h
ig
h
lig
h
tin
g
th
eir
lim
itatio
n
s
in
f
ea
tu
r
e
s
elec
tio
n
,
d
ataset
s
ize,
an
d
ac
cu
r
ac
y
ac
r
o
s
s
v
ar
io
u
s
n
eu
r
o
lo
g
ical
d
is
o
r
d
er
s
,
in
clu
d
in
g
ASD.
−
T
h
is
s
u
r
v
ey
ex
am
in
es
en
s
em
b
le
lear
n
in
g
ap
p
r
o
ac
h
es
co
m
b
i
n
ed
with
ef
f
ec
tiv
e
f
ea
tu
r
e
s
ele
ctio
n
tech
n
iq
u
es
to
ad
d
r
ess
th
e
id
en
tifie
d
g
ap
s
an
d
ch
allen
g
es in
ex
is
tin
g
m
et
h
o
d
o
lo
g
ies.
−
T
h
is
s
u
r
v
ey
aim
s
to
d
e
v
elo
p
a
f
r
am
ewo
r
k
u
s
in
g
ML
,
s
p
ec
if
i
ca
lly
d
esig
n
ed
f
o
r
ca
teg
o
r
izin
g
p
atien
ts
with
ASD
ac
r
o
s
s
d
if
f
er
en
t
a
g
e
g
r
o
u
p
s
.
T
h
is
cla
s
s
if
ier
is
d
esig
n
ed
t
o
en
h
an
ce
class
if
icati
o
n
ac
cu
r
ac
y
in
d
is
tin
g
u
is
h
in
g
b
etwe
en
i
n
d
iv
i
d
u
als with
an
d
with
o
u
t A
SD.
−
Mo
r
eo
v
er
,
th
e
u
ltima
te
g
o
al
o
f
th
e
wo
r
k
is
to
cr
ea
te
an
ef
f
i
cien
t
r
ec
o
m
m
en
d
e
r
s
y
s
tem
.
T
h
is
s
y
s
tem
will
u
tili
ze
n
o
v
el
f
ea
tu
r
es
ex
tr
ac
ted
f
r
o
m
wea
r
ab
le
I
o
T
d
ev
ices,
en
ab
lin
g
ac
cu
r
ate
ca
teg
o
r
iz
atio
n
o
f
au
tis
m
p
atien
ts
,
in
clu
d
in
g
c
h
ild
r
en
,
a
d
o
lescen
ts
,
an
d
ad
u
lts
.
Ov
er
all,
th
e
co
n
tr
ib
u
tio
n
lies
in
b
r
id
g
in
g
th
e
ex
is
tin
g
g
ap
s
in
ML
an
d
DL
m
eth
o
d
o
lo
g
ies
r
elate
d
to
ASD
d
iag
n
o
s
is
,
lead
in
g
to
t
h
e
d
e
v
elo
p
m
en
t
o
f
a
m
o
r
e
ac
cu
r
ate
an
d
ef
f
icien
t
class
if
icatio
n
s
y
s
tem
f
o
r
au
tis
m
p
atien
ts
ac
r
o
s
s
v
ar
io
u
s
a
g
e
g
r
o
u
p
s
.
Hen
ce
,
in
th
e
n
e
x
t
s
e
ctio
n
,
a
s
u
r
v
ey
h
as
b
ee
n
co
n
d
u
cted
o
n
v
ar
io
u
s
ap
p
r
o
ac
h
es f
o
r
ASD
d
etec
tio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
1
,
Ap
r
il
20
2
5
:
63
2
-
6
40
634
2.
L
I
T
E
R
AT
U
RE
SU
RVE
Y
I
n
th
e
liter
atu
r
e
s
u
r
v
ey
s
ec
t
io
n
,
we
h
av
e
s
tr
u
ctu
r
ed
o
u
r
in
v
esti
g
atio
n
in
to
f
o
u
r
d
is
tin
ct
ar
ea
s
p
er
tain
in
g
to
ASD.
T
h
e
f
ir
s
t
s
ec
tio
n
d
elv
es
in
to
ex
is
tin
g
m
eth
o
d
o
lo
g
ies
aim
ed
at
co
llectin
g
d
ata
ef
f
icien
tly
,
p
ar
ticu
lar
ly
f
o
c
u
s
in
g
o
n
ef
f
ici
en
t
ap
p
r
o
ac
h
es
d
esig
n
e
d
f
o
r
ASD
-
r
elate
d
s
tu
d
ies.
Mo
v
in
g
f
o
r
war
d
,
th
e
s
u
r
v
e
y
an
aly
s
es
ML
an
d
DL
ap
p
r
o
ac
h
es
em
p
lo
y
ed
in
th
e
d
etec
tio
n
an
d
class
if
icatio
n
o
f
ASD.
F
u
r
th
er
,
th
e
liter
atu
r
e
s
u
r
v
ey
d
el
v
es
in
to
r
ec
o
m
m
e
n
d
atio
n
ap
p
r
o
ac
h
es d
esig
n
ed
s
p
e
cif
ically
f
o
r
ASD.
Fin
ally
,
th
e
co
m
p
lete
f
i
n
d
in
g
s
f
r
o
m
th
e
s
tu
d
y
ar
e
d
is
cu
s
s
ed
.
2
.
1
.
E
f
f
icient
da
t
a
co
llect
io
n
a
pp
ro
a
ches
I
n
r
ec
en
t
r
esear
ch
w
o
r
k
,
a
d
i
v
er
s
e
ar
r
ay
o
f
in
n
o
v
ativ
e
m
e
th
o
d
o
lo
g
ies
is
p
r
o
p
o
s
ed
to
c
o
llect
d
ata
f
r
o
m
i
n
d
iv
id
u
als
wh
ich
ar
e
e
f
f
icien
t.
T
o
im
p
lem
en
t
a
p
o
wer
-
s
av
in
g
r
o
u
tin
g
s
y
s
tem
f
o
r
tr
ac
k
in
g
th
e
well
-
b
ein
g
an
d
b
e
h
av
io
r
o
f
ca
ttle,
[
1
7
]
laid
o
u
t
an
ev
o
l
u
tio
n
ar
y
m
eth
o
d
f
o
r
ch
o
o
s
in
g
th
e
b
est
clu
s
ter
ed
g
r
o
u
p
s
in
wir
eless
b
o
d
y
-
ar
ea
-
n
etwo
r
k
s
(
W
B
AN
s
)
.
W
ith
th
e
ass
is
tan
ce
o
f
an
t
-
lio
n
-
o
p
tim
izer
(
AL
O)
,
th
e
s
u
g
g
ested
m
eth
o
d
to
o
k
u
s
er
ch
o
ices
r
eg
ar
d
in
g
cl
u
s
ter
d
en
s
ities
in
to
ac
co
u
n
t
wh
ile
ch
o
o
s
in
g
t
h
e
b
e
s
t
clu
s
ter
ed
g
r
o
u
p
s
f
o
r
v
ar
io
u
s
f
o
o
d
s
izes,
all
w
h
ile
u
tili
zin
g
s
en
s
o
r
s
with
v
a
r
y
in
g
co
m
m
u
n
icatio
n
r
a
n
g
es.
T
h
is
s
tu
d
y
u
s
ed
a
r
an
d
o
m
l
y
g
en
er
ate
d
way
p
o
i
n
t
m
o
v
em
en
t
a
p
p
r
o
ac
h
(
s
im
u
latio
n
)
an
d
e
x
am
in
ed
n
o
d
e
s
.
R
e
ce
n
t
m
eth
o
d
s
in
clu
d
in
g
m
o
th
-
f
lam
e
o
p
tim
i
za
tio
n
(
MFO)
,
g
r
ass
h
o
p
p
e
r
o
p
tim
izatio
n
(
GO)
an
d
an
t
-
c
o
lo
n
y
o
p
tim
izatio
n
(
AC
O)
wer
e
co
m
p
ar
e
d
alo
n
g
s
id
e
th
e
s
u
g
g
ested
AL
O.
T
h
e
s
tu
d
y
’
s
f
in
d
i
n
g
s
d
em
o
n
s
tr
ated
th
e
u
s
ef
u
l
n
ess
o
f
th
e
s
u
g
g
ested
ap
p
r
o
ac
h
,
ac
h
ie
v
in
g
b
etter
r
o
u
tin
g
.
Z
eb
et
a
l.
[
1
8
]
,
s
u
g
g
ested
d
y
n
am
ic
tim
e
-
s
ch
ed
u
lin
g
m
e
d
ia
-
ac
ce
s
s
-
co
n
tr
o
l
(
DT
-
MA
C
)
as
an
im
p
r
o
v
ed
v
ar
ian
t
b
ased
o
n
th
e
p
o
p
u
lar
m
eth
o
d
m
o
b
i
lity
-
awa
r
e
ti
m
eo
u
t
MA
C
(
MT
-
MA
C
)
ap
p
r
o
ac
h
f
o
r
th
e
p
u
r
p
o
s
e
o
f
m
ain
tain
in
g
co
m
m
u
n
icatio
n
r
eliab
ilit
y
.
T
h
e
s
y
s
tem
’
s
s
tab
ilit
y
was
en
s
u
r
ed
b
y
co
n
s
id
er
in
g
a
n
o
d
e
h
an
d
o
v
er
m
eth
o
d
b
etwe
en
v
ir
tu
al
clu
s
ter
in
g
g
r
o
u
p
s
.
P
r
o
m
in
en
t
m
eth
o
d
s
,
lik
e
MT
-
MA
C
,
wer
e
s
u
b
s
eq
u
en
tly
test
ed
ag
ai
n
s
t
DT
-
MA
C
.
T
h
is
s
tu
d
y
u
s
ed
a
s
im
u
lated
f
r
am
ew
o
r
k
t
h
at
in
clu
d
ed
5
0
n
o
d
es,
a
1
5
0
×
1
5
0
m
a
r
ea
,
an
d
a
2
-
s
ec
o
n
d
p
au
s
e
f
o
r
its
p
ar
am
eter
s
.
T
h
e
f
in
d
in
g
s
f
r
o
m
th
e
ex
p
er
im
en
ts
d
em
o
n
s
tr
ated
th
a
t
DT
-
MA
C
im
p
r
o
v
ed
t
h
e
M
T
-
MA
C
’
s
p
ac
k
et
tr
an
s
m
is
s
io
n
b
y
ap
p
r
o
x
im
ately
13%
-
1
7
% a
n
d
r
esp
o
n
s
es b
y
ap
p
r
o
x
im
ately
1
5
% with
a
r
is
e
i
n
s
m
all
d
elay
o
f
ap
p
r
o
x
im
atel
y
3
%.
A
d
is
tr
ib
u
ted
-
e
n
er
g
y
-
ef
f
icien
t
two
-
hop
-
b
ased
clu
s
ter
in
g
an
d
r
o
u
tin
g
(
DE
C
R
)
ap
p
r
o
ac
h
was
s
u
g
g
ested
in
[
1
9
]
f
o
r
u
s
e
wit
h
W
I
o
T
-
en
ab
led
W
B
AN.
Du
r
in
g
th
e
clu
s
ter
’
s
cr
ea
tio
n
s
tag
e
o
f
DE
C
R
,
ev
er
y
n
o
d
e
r
ec
eiv
e
d
a
two
-
h
o
p
r
a
n
g
e
o
f
d
ata
f
r
o
m
its
n
eig
h
b
o
r
in
g
n
o
d
es.
W
h
en
o
p
tim
izin
g
tr
an
s
m
is
s
io
n
an
d
s
elec
tin
g
clu
s
ter
-
h
ea
d
s
(
C
Hs),
th
ey
u
s
ed
a
n
alter
ed
v
a
r
ian
t
o
f
th
e
g
r
e
y
-
wo
lf
-
o
p
tim
izatio
n
m
eth
o
d
.
T
h
e
DE
C
R
co
n
d
u
cte
d
a
s
im
u
latio
n
wh
ic
h
in
to
ac
co
u
n
t
n
o
d
e
s
izes
r
an
g
in
g
f
r
o
m
5
0
to
2
0
0
,
r
e
g
io
n
s
m
ea
s
u
r
in
g
1
0
0
×
1
0
0
m
an
d
2
0
0
×
2
0
0
m
,
an
d
a
r
an
d
o
m
ized
wa
y
p
o
in
t
m
o
v
e
m
en
t
f
r
am
ewo
r
k
.
Sev
er
al
p
er
f
o
r
m
an
ce
p
ar
a
m
eter
s
,
in
clu
d
in
g
en
er
g
y
c
o
n
s
u
m
p
ti
o
n
,
n
o
d
e
life
tim
e,
o
v
er
h
ea
d
,
e
n
d
-
to
-
e
n
d
d
elay
(
E
E
D)
a
n
d
p
ac
k
et
d
eliv
er
y
r
atio
(
PDR
)
,
wer
e
s
u
r
p
ass
ed
i
n
c
o
m
p
ar
is
o
n
with
e
x
is
tin
g
r
o
u
t
in
g
an
d
cl
u
s
ter
in
g
a
p
p
r
o
ac
h
e
s
ac
co
r
d
in
g
to
th
e
s
im
u
latio
n
f
in
d
in
g
s
.
Fo
r
1
0
0
×
100
m
an
d
2
0
0
×
2
0
0
m
,
th
e
DE
C
R
attain
ed
a
PDR
o
f
9
6
%
a
n
d
9
3
%,
r
esp
ec
tiv
ely
.
Usi
n
g
ML
,
[
2
0
]
s
u
g
g
ested
an
I
o
T
s
y
s
tem
th
at
wo
u
ld
allo
w
ch
ild
r
en
with
s
p
ee
ch
im
p
air
m
en
ts
to
u
s
e
a
v
ar
iety
o
f
s
en
s
o
r
s
att
ac
h
ed
t
o
th
eir
b
o
d
ies
to
co
m
m
u
n
icate
.
T
h
ey
co
llected
s
en
s
o
r
s
tim
e
s
er
ies
in
f
o
r
m
atio
n
,
ex
tr
ac
ted
c
h
ar
ac
ter
is
tics
f
r
o
m
b
o
th
th
e
tem
p
o
r
al
d
o
m
ain
s
alo
n
g
with
f
r
eq
u
en
cy
d
o
m
ai
n
s
,
an
d
test
ed
m
u
ltip
le
class
if
ier
s
to
s
ee
wh
ich
o
n
es
co
u
ld
b
est
id
e
n
tify
th
e
h
a
n
d
m
o
tio
n
s
u
s
ed
b
y
k
id
s
with
ASD.
W
h
en
it
ca
m
e
tim
e
to
id
en
tify
th
e
m
o
v
em
en
ts
u
s
ed
b
y
k
id
s
with
ASD,
th
e
f
in
d
in
g
s
d
em
o
n
s
tr
ated
an
ac
cu
r
ate
r
ec
o
g
n
itio
n
r
ate
o
f
9
6
%
wh
en
u
s
in
g
K
-
n
ea
r
est
n
eig
h
b
o
r
(
KNN)
,
r
an
d
o
m
-
f
o
r
est
(
R
F),
d
ec
is
io
n
-
tr
ee
(
DT
)
,
a
n
d
ar
tific
ial
-
n
eu
r
al
-
n
etwo
r
k
(A
N
N)
class
if
icatio
n
ap
p
r
o
ac
h
es.
Am
it
et
a
l.
[
2
1
]
,
co
llected
d
ata
f
r
o
m
a
to
tal
o
f
1
,
1
8
7
,
3
9
7
ch
ild
r
e
n
,
6
1
0
,
5
8
8
(
o
r
5
1
.
4
%
o
f
th
e
to
tal)
wer
e
b
o
y
s
an
d
4
8
.
6
%
wer
e
g
ir
ls
.
Pre
d
ictio
n
ag
e
was
a
s
ig
n
if
ican
t
f
ac
to
r
in
th
e
ASD
d
iag
n
o
s
is
ap
p
r
o
ac
h
ef
f
icien
c
y
,
wh
ich
b
eg
a
n
to
s
h
o
w
s
ig
n
s
o
f
im
p
r
o
v
em
en
t
at
twelv
e
m
o
n
th
s
o
f
ag
e.
B
etwe
en
1
8
an
d
2
4
m
o
n
th
s
o
f
a
g
e,
a
f
r
am
ewo
r
k
th
at
in
clu
d
ed
a
s
m
all
s
et
o
f
d
em
o
g
r
a
p
h
ic
d
ata
al
o
n
g
with
lo
n
g
-
ter
m
ev
alu
atio
n
s
o
f
m
i
lest
o
n
es
in
g
r
o
wth
p
r
o
d
u
ce
d
an
ar
ea
-
u
n
d
er
th
e
r
ec
eiv
er
-
o
p
er
atin
g
-
c
h
ar
ac
ter
is
tic
(
AUC
-
R
O
C
)
cu
r
v
e
o
f
8
3
.
Alth
o
u
g
h
r
esear
c
h
u
s
in
g
an
id
en
tical
s
tr
u
ctu
r
e
f
o
u
n
d
th
at
M
-
C
HAT
h
ad
a
c
o
m
b
in
ed
ef
f
ec
tiv
e
n
ess
o
f
0
.
4
0
o
f
s
en
s
itiv
ity
an
d
0
.
9
5
o
f
s
p
ec
if
icity
,
th
e
to
p
f
u
n
ctio
n
in
g
p
r
ed
ictiv
e
m
o
d
els o
u
tp
er
f
o
r
m
ed
it.
2
.
2
.
M
a
chine
lea
rning
a
nd
deep
lea
rning
a
pp
ro
a
ches
I
n
r
ec
en
t
s
tu
d
ies,
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
ts
h
av
e
b
ee
n
m
a
d
e
in
th
e
r
ea
lm
o
f
ASD
d
ete
ctio
n
an
d
class
if
icatio
n
,
u
tili
zin
g
ad
v
an
ce
d
tech
n
iq
u
es
r
a
n
g
in
g
f
r
o
m
ML
to
DL
an
d
h
y
b
r
id
a
p
p
r
o
ac
h
es.
Su
b
ah
et
a
l.
[
2
2
]
,
an
ap
p
r
o
ac
h
f
o
r
th
e
id
en
tif
icatio
n
o
f
ASD
b
ased
o
n
f
u
n
ctio
n
ally
co
n
n
ec
ted
asp
ec
ts
o
f
r
esti
n
g
-
s
tate
f
-
MRI
(
f
u
n
ctio
n
al
-
m
a
g
n
etic
-
r
eso
n
an
ce
-
im
ag
in
g
)
d
ata
was
s
u
g
g
ested
.
T
o
ca
r
r
y
o
u
t
t
h
e
id
e
n
tific
atio
n
p
r
o
ce
s
s
,
a
d
ee
p
n
eu
r
al
-
n
etwo
r
k
(
DNN)
class
if
ier
was
em
p
lo
y
ed
.
T
h
e
au
tis
m
-
b
r
ain
im
ag
in
g
-
d
ata
-
e
x
ch
an
g
e
(
AB
I
DE
)
d
ataset
[
2
3
]
,
[
2
4
]
was
u
s
ed
f
o
r
th
e
ev
alu
atio
n
.
W
h
ile
cu
r
r
en
t
m
eth
o
d
s
h
ad
an
av
er
ag
e
ac
cu
r
ac
y
o
f
6
7
%
to
8
5
%,
th
e
s
u
g
g
ested
ap
p
r
o
ac
h
ac
h
iev
ed
a
n
av
e
r
ag
e
ac
c
u
r
ac
y
o
f
0
.
8
8
.
Ma
k
h
n
y
tk
in
a
et
a
l.
[
2
5
]
,
th
e
o
u
tc
o
m
es
o
f
an
au
to
m
ated
ML
-
b
ased
co
n
v
er
s
atio
n
ca
teg
o
r
izatio
n
o
f
ty
p
i
ca
lly
d
ev
elo
p
in
g
an
d
aty
p
icall
y
d
ev
elo
p
in
g
ASD
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:
2
5
0
2
-
4
7
52
E
xp
lo
r
a
tio
n
o
f v
a
r
io
u
s
a
p
p
r
o
a
ch
es fo
r
d
etec
tio
n
o
f
a
u
tis
m
s
p
ec
tr
u
m
d
is
o
r
d
er
(
K
a
vith
a
Ga
n
g
a
r
a
ju
)
635
in
R
u
s
s
ian
-
s
p
ea
k
in
g
ch
ild
r
en
was
p
r
esen
ted
.
T
o
ev
alu
ate
v
ar
iatio
n
s
am
o
n
g
t
h
e
s
p
ee
ch
’
s
s
em
an
tic
f
ea
tu
r
es,
th
e
Ma
n
n
-
W
h
itn
ey
U
-
T
est
w
as
em
p
lo
y
ed
.
ML
tech
n
iq
u
es
lik
e
R
F,
Ad
aBo
o
s
t
(
AB
)
,
a
n
d
g
r
a
d
ien
t
-
b
o
o
s
tin
g
(
GB
)
wer
e
em
p
l
o
y
ed
to
co
n
s
t
r
u
ct
class
if
icatio
n
alg
o
r
ith
m
s
b
ased
o
n
th
ese
tr
aits
.
T
h
er
e
w
as
an
8
8
%
s
u
cc
ess
r
ate
in
class
if
y
in
g
th
e
s
p
ee
ch
p
atter
n
s
o
f
b
o
y
s
d
iag
n
o
s
ed
with
d
if
f
er
en
t
ASDs
.
T
h
r
ee
ar
tific
ial
-
in
tellig
en
ce
(
AI
)
m
eth
o
d
s
DL
,
ML
alo
n
g
with
a
h
y
b
r
id
m
eth
o
d
th
at
co
m
b
in
ed
th
e
two
wer
e
cr
ea
ted
f
o
r
th
e
p
u
r
p
o
s
e
o
f
in
itial
ASD
d
etec
tio
n
in
[
2
6
]
.
T
h
ey
m
ad
e
u
s
e
o
f
a
d
ataset
th
at
in
clu
d
ed
5
4
7
im
a
g
es
s
p
lit
ev
en
ly
b
etwe
en
two
ca
teg
o
r
ies.
I
n
th
e
in
itial
a
p
p
r
o
ac
h
,
n
e
u
r
al
n
etwo
r
k
s
(
b
o
th
A
NNs
an
d
f
ee
d
-
f
o
r
war
d
n
e
u
r
al
-
n
etwo
r
k
s
(
FF
NNs))
wer
e
u
s
ed
to
class
if
y
f
ea
tu
r
e
s
.
T
h
e
ap
p
r
o
ac
h
u
s
ed
was
a
co
m
b
in
atio
n
o
f
g
r
ay
-
lev
el
c
o
-
o
cc
u
r
r
e
n
ce
m
atr
ix
(
GL
C
M)
an
d
lo
ca
l
-
b
in
ar
y
-
p
atter
n
(
L
B
P)
m
eth
o
d
s
.
Fo
r
ANNs
an
d
FF
NNs,
th
is
m
eth
o
d
attain
e
d
an
o
u
ts
tan
d
in
g
0
.
9
9
8
o
f
ac
cu
r
ac
y
.
T
h
e
s
ec
o
n
d
m
eth
o
d
r
elied
o
n
d
ee
p
m
a
p
p
in
g
o
f
f
ea
tu
r
es
ex
t
r
ac
tio
n
to
em
p
lo
y
a
p
r
e
-
tr
ain
ed
co
n
v
o
l
u
tio
n
al
-
n
e
u
r
al
-
n
etwo
r
k
(
C
NN)
ap
p
r
o
ac
h
,
lik
e
Go
o
g
leNe
t
an
d
R
esNet
-
1
8
.
M
o
d
els
tr
ain
e
d
u
s
in
g
R
esNet
-
1
8
an
d
G
o
o
g
le
Net
b
o
th
p
er
f
o
r
m
e
d
ad
m
ir
ab
l
y
,
with
0
.
9
7
6
an
d
0
.
9
3
6
ac
c
u
r
ac
y
,
r
esp
ec
tiv
ely
.
T
h
ir
d
ly
,
th
er
e
was
a
h
y
b
r
id
a
p
p
r
o
ac
h
th
at
co
m
b
in
ed
DL
(
u
s
in
g
Go
o
g
leNe
t
an
d
R
esNet
-
1
8
)
with
ML
(
u
s
in
g
s
u
p
p
o
r
t
-
v
ec
to
r
-
m
ac
h
in
e
(
SV
M)
)
,
wh
ich
was
k
n
o
w
n
as
R
esNet
-
1
9
+SVM
an
d
Go
o
g
le
Net+
SVM.
T
h
e
f
ir
s
t
s
ec
tio
n
em
p
lo
y
ed
C
NNs
to
d
er
iv
e
d
ee
p
m
ap
p
in
g
s
o
f
f
ea
t
u
r
e
s
,
an
d
th
e
s
u
b
s
eq
u
en
t
s
ec
tio
n
u
tili
ze
d
SVMs
f
o
r
f
ea
tu
r
e
class
if
icatio
n
.
W
ith
ac
cu
r
ac
ies
o
f
0
.
9
4
.
5
f
o
r
R
esNet
-
1
8
+
SVM
a
n
d
0
.
9
5
5
f
o
r
Go
o
g
leNe
t+SVM
,
th
is
ap
p
r
o
ac
h
d
em
o
n
s
tr
ated
its
g
r
ea
t
d
iag
n
o
s
in
g
ca
p
ab
ilit
y
.
T
h
e
u
s
e
o
f
co
m
p
u
ter
ized
M
L
wh
en
co
m
b
in
ed
alo
n
g
s
id
e
f
ea
tu
r
e
class
if
icatio
n
alg
o
r
ith
m
s
to
p
r
o
v
id
e
m
ea
n
i
n
g
f
u
l
f
ea
t
u
r
e
p
atter
n
s
f
o
r
in
iti
al
au
tis
m
s
cr
ee
n
in
g
was
h
ig
h
lig
h
ted
i
n
[
2
7
]
.
T
h
ei
r
r
esear
ch
u
tili
ze
d
o
p
e
n
-
ac
ce
s
s
d
atasets
th
at
wer
e
co
n
s
tr
u
ct
ed
u
p
o
n
th
e
Q
-
ch
at
r
atin
g
s
o
f
p
e
r
s
o
n
s
f
r
o
m
d
if
f
er
en
t
ag
es,
in
clu
d
i
n
g
ad
u
lts
,
ad
o
lescen
ts
,
ch
ild
r
en
an
d
to
d
d
le
r
s
[
2
8
]
,
[
2
9
]
.
A
ML
f
r
am
ewo
r
k
was
s
u
g
g
ested
f
o
r
ev
alu
atin
g
th
e
p
o
s
s
ib
le
n
o
n
clin
ical
au
tis
m
in
d
icato
r
s
,
w
h
ich
wer
e
ca
n
te
r
ed
u
p
o
n
a
u
to
m
atic
o
p
tim
izin
g
h
y
p
er
p
ar
am
eter
.
T
h
e
s
u
g
g
este
d
s
y
s
tem
ac
h
iev
ed
o
v
er
all
ac
cu
r
ac
y
o
f
ar
o
u
n
d
0
.
9
5
in
all
f
o
u
r
ag
e
ca
teg
o
r
ies o
f
au
tis
m
d
atasets
.
Fu
r
th
er
,
Alk
ah
tan
i
et
a
l.
[
3
0
]
e
m
p
lo
y
ed
s
ev
er
al
ty
p
es o
f
d
ee
p
C
NN
tr
an
s
f
er
lear
n
in
g
(TL)
t
ec
h
n
iq
u
es
to
id
en
tify
au
tis
tic
ch
ild
r
en
u
s
in
g
f
ac
e
lan
d
m
ar
k
d
etec
tio
n
.
T
o
in
cr
ea
s
e
th
e
C
NN
alg
o
r
ith
m
’
s
ac
cu
r
ac
y
in
p
r
ed
ictio
n
s
,
an
ex
p
er
im
e
n
t
was
ca
r
r
ied
o
u
t
to
f
in
d
th
e
o
p
tim
al
o
p
tim
izatio
n
an
d
h
y
p
er
p
a
r
am
eter
co
n
f
ig
u
r
atio
n
s
.
Sev
er
al
ML
to
o
ls
wer
e
u
tili
ze
d
,
in
clu
d
in
g
h
y
b
r
id
v
is
u
al
g
eo
m
etr
y
g
r
o
u
p
-
1
9
(
VGG1
9
)
,
Mo
b
ileNetV2
,
lo
g
is
tic
-
r
eg
r
ess
io
n
(
L
R
)
,
m
u
lti
-
lay
e
r
p
er
ce
p
tr
o
n
(
ML
P),
KNN,
DT
,
SVM,
a
n
d
GB
.
I
n
o
r
d
e
r
t
o
test
th
e
DL
ap
p
r
o
ac
h
es,
r
esear
ch
er
s
u
s
ed
a
Kag
g
le
b
aselin
e
d
ataset
th
at
in
clu
d
ed
2
,
9
4
0
p
ictu
r
es
o
f
ch
ild
r
en
with
ASD
an
d
th
o
s
e
with
o
u
t
ASD
[
3
1
]
.
A
9
2
%
s
u
cc
ess
r
ate
u
p
o
n
th
e
test
d
ataset
w
as
attain
ed
b
y
th
e
Mo
b
ileNetV2
ap
p
r
o
ac
h
.
B
as
ed
o
n
th
e
f
in
d
in
g
s
f
r
o
m
th
e
s
u
g
g
ested
s
tu
d
y
,
Mo
b
ileNetV2
T
L
alg
o
r
ith
m
s
o
u
tp
er
f
o
r
m
ed
p
r
ev
i
o
u
s
v
er
s
io
n
s
in
cu
r
r
en
t
p
latf
o
r
m
s
.
T
o
tak
e
ad
v
an
ta
g
e
o
f
ML
’
s
ca
p
ab
il
ities
wh
ile
k
ee
p
in
g
th
e
ev
alu
atio
n
to
o
l
’
s
m
ed
ical
s
ig
n
if
ican
ce
,
th
ey
p
r
o
v
id
ed
g
u
id
an
ce
to
war
d
s
th
e
cr
ea
tio
n
o
f
ML
-
b
ased
test
in
g
an
d
d
iag
n
o
s
in
g
p
r
o
ce
d
u
r
es
[
3
2
]
.
Su
n
d
as
et
a
l.
[
3
3
]
,
p
r
esen
t
ed
a
co
m
p
r
e
h
en
s
iv
e
o
v
e
r
v
iew
o
f
ASD
ap
p
r
o
ac
h
es
in
th
e
co
n
tex
t
o
f
I
o
T
d
e
v
ices.
T
h
e
m
ain
p
u
r
p
o
s
e
o
f
th
e
s
t
u
d
y
was
to
r
ec
o
g
n
ize
im
p
o
r
tan
t
d
ev
elo
p
m
e
n
ts
in
m
ed
ical
r
esear
ch
th
at
was
d
e
p
en
d
en
t
o
n
I
o
T
.
B
y
lo
ca
lly
c
o
n
s
tr
u
ctin
g
two
ML
class
if
ier
s
,
i.e
.
,
SVM
an
d
L
R
f
o
r
th
e
class
if
icatio
n
o
f
AS
D
v
ar
iab
les
an
d
id
en
tify
i
n
g
in
s
tan
ce
s
o
f
ASD
in
k
id
s
a
n
d
ad
u
lts
alik
e,
th
e
f
ed
er
ated
-
lear
n
in
g
(
FL)
ap
p
r
o
ac
h
was
u
s
ed
f
o
r
ASD
d
etec
tio
n
in
[
3
4
]
.
T
h
e
r
esear
ch
er
s
u
s
ed
two
p
u
b
licly
av
ailab
le
d
atasets
o
n
au
tis
m
:
o
n
e
f
o
r
ch
ild
r
e
n
[
3
5
]
,
[
3
6
]
a
n
d
an
o
th
er
f
o
r
a
d
u
lts
[
3
7
]
,
[
3
8
]
in
t
h
eir
a
n
aly
s
is
.
I
n
o
r
d
er
to
f
in
d
o
u
t w
h
ich
m
et
h
o
d
is
m
o
s
t s
u
cc
ess
f
u
l in
d
etec
ti
n
g
ASD
in
b
o
th
k
i
d
s
an
d
ad
u
lts
,
th
e
o
u
tp
u
ts
o
f
th
e
af
o
r
em
en
tio
n
ed
class
if
icatio
n
s
wer
e
s
en
t
to
a
ce
n
tr
aliz
ed
s
er
v
er
u
s
in
g
FL,
wh
er
e
b
y
an
ad
d
itio
n
al
class
if
icatio
n
ap
p
r
o
ac
h
was
tr
ain
ed
.
T
h
e
y
ex
tr
ac
ted
f
ea
tu
r
es
f
r
o
m
f
o
u
r
s
ep
ar
ate
ASD
in
d
i
v
id
u
al
d
atasets
,
ev
er
y
s
in
g
le
o
f
w
h
ich
h
ad
o
v
er
6
0
0
e
n
tr
ies
o
f
af
f
ec
ted
k
id
s
an
d
ad
u
lts
,
s
o
u
r
ce
d
f
r
o
m
v
ar
io
u
s
r
ep
o
s
ito
r
ies.
W
ith
an
ac
cu
r
ac
y
o
f
0
.
9
8
in
k
id
s
an
d
0
.
8
1
in
a
d
u
lts
,
th
e
s
u
g
g
ested
ap
p
r
o
ac
h
ac
cu
r
ate
ly
p
r
ed
icted
ASD.
T
h
e
s
tu
d
y
co
n
d
u
cted
in
[
3
9
]
a
im
ed
to
ass
es
s
th
e
ef
f
ec
t
iv
en
ess
o
f
a
g
r
o
u
p
o
f
in
d
iv
id
u
al
class
if
icatio
n
alg
o
r
ith
m
s
in
c
o
m
p
a
r
is
o
n
to
v
ar
io
u
s
n
u
m
er
o
u
s
class
if
icati
o
n
alg
o
r
ith
m
s
in
t
h
e
co
n
tex
t
o
f
e
x
am
in
in
g
an
d
an
ticip
atin
g
ASD
t
r
aits
(
ASDT
)
.
T
h
e
d
ataset
was
d
er
iv
ed
f
r
o
m
3
,
0
0
0
ex
er
cises
an
d
3
0
0
h
o
u
r
s
o
f
co
llected
in
f
o
r
m
atio
n
,
in
v
o
lv
in
g
a
t
o
tal
o
f
6
1
ASD
c
h
ild
r
en
.
T
h
is
d
ataset
is
co
m
m
o
n
ly
r
ef
er
r
e
d
t
o
as
th
e
DR
E
AM
d
ataset
[
4
0
]
.
T
h
e
f
in
d
i
n
g
s
o
f
th
e
s
tu
d
y
in
d
icate
th
at
b
o
o
s
tin
g
an
d
b
ag
g
in
g
en
s
em
b
le
l
ea
r
n
in
g
tech
n
i
q
u
es
ex
h
ib
it
s
tr
o
n
g
p
er
f
o
r
m
an
ce
in
f
o
r
ec
asti
n
g
ASDT
,
p
ar
ticu
lar
l
y
wh
en
u
tili
ze
d
with
in
a
m
u
lti
-
s
tag
e
d
ev
elo
p
m
en
t
f
r
am
ewo
r
k
.
2
.
3
.
Rec
o
mm
enda
t
io
n
s
y
s
t
em
s
f
o
r
a
utism
a
pp
ro
a
ches
I
n
r
ec
en
t
r
esear
c
h
wo
r
k
s
f
o
cu
s
ed
o
n
ASD,
in
n
o
v
ativ
e
ap
p
r
o
ac
h
es
h
av
e
b
ee
n
d
ev
elo
p
ed
to
au
to
m
ate
p
r
o
ce
s
s
es,
im
p
r
o
v
e
r
ec
o
m
m
e
n
d
atio
n
s
y
s
tem
s
,
an
d
en
h
an
c
e
tr
ea
tm
en
t
p
er
s
o
n
aliza
tio
n
u
s
in
g
ad
v
an
ce
d
ML
tech
n
iq
u
es.
B
alaji
an
d
R
aja
[
4
1
]
,
th
e
aim
was
in
ten
d
ed
to
au
to
m
atin
g
th
e
m
eth
o
d
b
y
id
en
ti
f
y
in
g
th
e
attr
ib
u
tes
th
at
wer
e
m
o
s
t
s
ig
n
if
ica
n
t
u
tili
zin
g
K
-
m
ea
n
s
-
clu
s
ter
in
g
(
KM
C
)
a
n
d
class
if
icatio
n
ap
p
r
o
ac
h
es.
I
n
o
r
d
er
to
f
in
d
th
e
m
o
s
t
ef
f
ec
tiv
e
class
if
icati
o
n
ap
p
r
o
ac
h
to
u
s
e
with
th
e
b
in
ar
y
d
atasets
,
th
ey
ex
am
in
e
d
ASD
d
atab
ases
o
f
ch
ild
r
en
an
d
to
o
k
m
is
tak
en
c
lass
if
icatio
n
in
to
ac
co
u
n
t.
T
h
e
AB
I
DE
d
ataset
was
u
tili
ze
d
in
th
eir
r
esear
ch
.
T
h
eir
m
eth
o
d
was
9
8
.
8
1
%
ac
cu
r
ate,
ac
co
r
d
in
g
to
th
e
r
esu
lts
.
Hao
an
d
Hu
[
4
2
]
,
p
r
esen
t
ed
an
a
p
p
r
o
ac
h
f
o
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
1
,
Ap
r
il
20
2
5
:
63
2
-
6
40
636
en
h
an
ce
d
n
e
u
r
al
-
n
etwo
r
k
m
atr
ix
-
f
ac
to
r
izatio
n
(
Neu
MF)
th
at
was
d
er
iv
ed
f
r
o
m
c
o
llab
o
r
ativ
e
-
f
ilter
in
g
ap
p
r
o
ac
h
.
B
y
in
co
r
p
o
r
atin
g
te
m
p
o
r
al
in
f
o
r
m
atio
n
an
d
u
tili
zin
g
th
e
KM
C
tech
n
iq
u
e,
th
e
ap
p
r
o
ac
h
was
f
u
r
th
er
en
h
an
ce
d
.
Usi
n
g
Py
th
o
n
’
s
Scr
ap
y
,
r
esear
ch
er
s
in
th
is
wo
r
k
cr
awle
d
2
8
9
,
3
3
3
en
tr
ies
f
r
o
m
m
ass
iv
e
o
p
en
o
n
lin
e
co
u
r
s
e
(
MO
OC
)
d
atab
ases
[
4
3
]
.
T
h
ey
u
s
ed
a
n
u
m
b
er
o
f
ass
ess
m
en
t
in
d
ices,
in
clu
d
in
g
m
ea
n
-
ab
s
o
lu
te
-
er
r
o
r
(
MA
E
)
an
d
r
o
o
t
-
m
ea
n
s
q
u
ar
e
-
er
r
o
r
(
R
MSE
)
to
m
ea
s
u
r
e
h
o
w
well
th
e
s
u
g
g
ested
ap
p
r
o
ac
h
wo
r
k
ed
.
C
o
m
p
ar
ed
to
th
e
a
p
p
r
o
ac
h
es
u
s
in
g
c
o
llab
o
r
ativ
e
f
ilter
in
g
an
d
C
NN
f
ac
to
r
izatio
n
,
t
h
e
en
h
an
ce
d
Neu
MF
ap
p
r
o
ac
h
ac
h
iev
e
d
im
p
r
o
v
e
d
o
u
tco
m
es
with
R
MSE
o
f
1
.
2
5
1
an
d
MA
E
o
f
0
.
6
2
5
.
K
o
h
li
e
t
a
l.
[
4
4
]
u
s
ed
two
ML
tech
n
iq
u
es
to
d
eter
m
in
e
t
h
e
b
est
co
u
r
s
e
o
f
ap
p
lied
-
b
eh
av
io
r
-
an
al
y
s
is
(
AB
A)
th
er
ap
y
f
o
r
2
9
in
d
i
v
id
u
als
d
iag
n
o
s
ed
with
ASD.
On
av
er
ag
e,
th
e
AB
A
th
er
ap
y
s
u
g
g
esti
o
n
s
m
ad
e
b
y
clin
ician
s
wer
e
8
1
-
4
0
%
ac
cu
r
ate,
wh
ile
t
h
e
co
llab
o
r
ativ
e
f
iltra
tio
n
an
d
i
n
d
iv
id
u
al
m
atch
in
g
ap
p
r
o
ac
h
es
ac
h
iev
ed
a
n
o
r
m
alize
d
-
d
is
co
u
n
ted
cu
m
u
lativ
e
-
g
ain
(
NDCG)
o
f
7
9
-
8
1
%.
Ma
u
r
o
et
a
l.
[
4
5
]
,
p
r
esen
ted
an
a
p
p
r
o
ac
h
f
o
r
ex
tr
ac
tin
g
s
en
s
o
r
y
an
aly
s
is
f
r
o
m
p
o
in
ts
-
of
-
in
ter
e
s
t
(
Po
I
)
ev
alu
atio
n
s
an
d
in
teg
r
a
tin
g
it
in
to
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
in
o
r
d
er
to
f
o
r
ec
ast
p
r
o
d
u
ct
ev
alu
atio
n
s
b
y
tak
in
g
co
n
s
u
m
er
p
r
ef
er
en
ce
s
.
T
wo
d
atasets
,
o
n
e
g
en
er
ate
d
f
r
o
m
T
r
ip
Ad
v
is
o
r
r
ev
iews
alo
n
g
s
id
e
an
o
t
h
er
g
at
h
er
ed
f
r
o
m
a
cr
o
w
d
s
o
u
r
cin
g
i
n
itiativ
e,
wer
e
u
tili
ze
d
f
o
r
th
e
p
u
r
p
o
s
e
o
f
t
esti
n
g
[
4
6
]
,
[
4
7
]
.
Usi
n
g
T
r
i
p
Ad
v
is
o
r
in
f
o
r
m
atio
n
allo
wed
th
e
ap
p
r
o
ac
h
es
to
ac
h
ie
v
e
th
e
b
est
a
cc
u
r
ac
y
an
d
r
atin
g
ab
ilit
y
,
ac
co
r
d
in
g
to
t
h
e
f
in
d
i
n
g
s
.
A
r
ec
o
m
m
e
n
d
atio
n
s
y
s
tem
f
o
r
s
en
s
o
r
y
m
a
n
ag
em
en
t
was
cr
ea
ted
an
d
ev
alu
ate
d
in
[
4
8
]
to
ass
is
t
s
tu
d
en
ts
with
ASD
in
co
p
in
g
wi
th
th
eir
u
n
iq
u
e
s
en
s
o
r
y
r
e
ac
tio
n
s
in
th
e
class
r
o
o
m
.
T
h
e
s
y
s
tem
’
s
u
n
iq
u
e
s
en
s
o
r
y
co
n
tr
o
l
s
y
s
tem
u
s
ed
a
f
u
zz
y
lo
g
ic
co
m
p
o
n
en
t
th
at
al
er
ted
ca
r
eg
i
v
er
s
an
d
in
s
tr
u
cto
r
s
to
k
id
’
s
em
o
tio
n
s
an
d
p
o
ten
tially
d
an
g
er
o
u
s
en
v
ir
o
n
m
e
n
tal
co
n
d
itio
n
s
;
th
is
was
ad
d
itio
n
al
in
n
o
v
ativ
e
f
ea
tu
r
e.
T
h
eir
an
aly
s
is
was
b
ased
o
n
th
e
d
ataset
p
r
o
v
id
ed
in
[
4
9
]
.
B
ased
o
n
th
e
ass
es
s
m
en
t
’
s
f
in
d
in
g
s
,
it
s
ee
m
ed
th
at
th
e
to
o
l
was
ea
s
y
to
u
tili
ze
an
d
im
p
r
o
v
ed
th
e
k
id
s
’
ef
f
icien
cy
.
Fo
r
m
o
r
e
ac
cu
r
ate
ASD
f
o
r
ec
asti
n
g
,
i
n
[
5
0
]
,
th
e
y
b
u
ilt
a
r
ec
o
m
m
en
d
er
s
y
s
tem
u
s
in
g
m
u
lti
-
class
if
ier
s
.
T
o
test
h
o
w
w
ell
th
e
class
if
ier
s
wo
r
k
ed
,
th
e
y
u
s
ed
a
n
u
m
b
er
o
f
d
if
f
er
en
t
ML
tech
n
iq
u
es.
T
o
a
s
s
es
s
th
eir
p
er
f
o
r
m
an
ce
,
th
e
y
u
tili
ze
d
a
d
ataset
p
r
o
v
i
d
ed
i
n
[
5
1
]
th
at
was
b
ased
o
n
q
u
esti
o
n
n
air
es.
W
h
en
co
m
p
ar
ed
with
d
if
f
er
en
t
m
eth
o
d
s
u
s
in
g
r
ec
all,
F
-
s
co
r
e,
p
r
ec
is
io
n
an
d
ac
cu
r
ac
y
as
ass
es
s
m
en
t
m
ea
s
u
r
es,
th
ey
d
e
m
o
n
s
tr
ated
th
at
DT
an
d
R
F
p
er
f
o
r
m
e
d
b
etter
.
T
h
is
s
tu
d
y
’
s
b
ig
g
est
s
h
o
r
tco
m
in
g
was
its
p
er
f
ec
t
ac
cu
r
ac
y
,
th
at
was
attain
ed
b
y
u
s
in
g
a
d
ata
s
et
with
a
co
m
p
ar
ab
le
p
er
ce
n
tag
e
o
f
in
d
iv
i
d
u
als
with
an
d
with
o
u
t A
SD.
T
h
is
w
as b
ec
au
s
e
th
ey
h
a
v
e
n
o
t a
d
d
r
ess
ed
th
e
class
im
b
alan
ce
is
s
u
e.
2
.
4
.
F
ind
ing
s
T
h
e
liter
atu
r
e
s
u
r
v
ey
r
e
v
ea
ls
s
ig
n
if
ican
t
ad
v
an
ce
m
en
ts
an
d
d
iv
er
s
e
m
eth
o
d
o
lo
g
ies
in
th
e
s
tu
d
y
o
f
ASD.
R
esear
ch
er
s
h
av
e
ex
p
l
o
r
ed
v
ar
io
u
s
d
atasets
,
f
ea
tu
r
e
s
,
an
d
e
v
alu
atio
n
m
etr
ics
to
d
ev
elo
p
in
n
o
v
ativ
e
ap
p
r
o
ac
h
es
f
o
r
ASD
d
etec
tio
n
an
d
i
n
ter
v
en
tio
n
.
E
ac
h
s
tu
d
y
co
n
tr
ib
u
tes
to
a
d
ee
p
er
u
n
d
er
s
tan
d
in
g
o
f
ASD,
em
p
lo
y
in
g
u
n
iq
u
e
d
atasets
an
d
m
eth
o
d
o
l
o
g
ies
to
a
d
d
r
ess
s
p
ec
if
ic
asp
ec
ts
o
f
th
e
d
is
o
r
d
er
.
T
h
e
c
o
m
p
lete
f
in
d
in
g
s
f
r
o
m
th
e
ab
o
v
e
liter
atu
r
e
s
u
r
v
e
y
h
av
e
b
ee
n
f
o
r
m
u
lated
in
T
ab
le
1
in
Ap
p
en
d
ix
.
3.
G
AP
S,
I
SS
U
E
S
,
AND
CH
A
L
L
E
NG
E
S
T
h
e
g
ap
s
,
is
s
u
es a
n
d
ch
allen
g
es id
en
tifie
d
f
r
o
m
th
e
ab
o
v
e
li
ter
atu
r
e
s
u
r
v
e
y
is
as f
o
llo
ws
:
−
Sen
s
o
r
p
lace
m
en
t
o
p
tim
izatio
n
:
th
e
r
e
’
s
a
n
ee
d
f
o
r
r
esear
ch
in
to
o
p
tim
al
s
en
s
o
r
p
lace
m
en
t
to
en
s
u
r
e
ac
cu
r
ate
an
d
c
o
m
p
r
e
h
en
s
iv
e
d
ata
co
llectio
n
,
esp
ec
ially
in
s
ce
n
ar
io
s
in
v
o
lv
in
g
ASD
in
d
iv
id
u
als
wh
er
e
d
elica
te
b
eh
av
io
r
al
in
d
icatio
n
s
ar
e
cr
u
cial.
−
Data
s
y
n
ch
r
o
n
izatio
n
:
ch
alle
n
g
es
m
ay
a
r
is
e
in
s
y
n
ch
r
o
n
i
zin
g
d
ata
f
r
o
m
m
u
ltip
le
s
en
s
o
r
s
to
cr
ea
te
a
co
h
esiv
e
an
d
m
ea
n
in
g
f
u
l
p
ict
u
r
e
o
f
a
n
in
d
iv
id
u
al
’
s
b
eh
av
i
o
r
,
n
ec
ess
itatin
g
ad
v
an
ce
m
en
t
s
in
d
ata
f
u
s
io
n
tech
n
iq
u
es.
−
Featu
r
e
s
elec
tio
n
an
d
e
x
tr
ac
tio
n
:
d
ev
el
o
p
in
g
ro
b
u
s
t
alg
o
r
it
h
m
s
f
o
r
f
ea
tu
r
e
s
elec
tio
n
a
n
d
ex
tr
ac
tio
n
f
r
o
m
b
eh
av
io
r
d
ata
is
ess
en
tial
to
i
d
en
tify
m
ea
n
in
g
f
u
l
p
atter
n
s
a
n
d
ch
a
r
ac
ter
is
tics
in
d
icativ
e
o
f
ASD
o
r
o
th
er
co
n
d
itio
n
s
.
−
Data
p
r
ep
r
o
ce
s
s
in
g
:
ad
d
r
ess
i
n
g
ch
allen
g
es
r
elate
d
to
n
o
is
e,
o
u
tlier
s
,
an
d
m
is
s
in
g
d
ata
th
r
o
u
g
h
ef
f
ec
tiv
e
p
r
ep
r
o
ce
s
s
in
g
tech
n
iq
u
es is
cr
u
cial
f
o
r
ac
c
u
r
ate
an
aly
s
is
an
d
m
o
d
el
d
e
v
elo
p
m
e
n
t.
−
I
n
ter
p
r
etab
ilit
y
v
s
.
co
m
p
le
x
ity
: b
alan
cin
g
th
e
i
n
ter
p
r
etab
ilit
y
o
f
b
eh
av
io
r
al
f
e
atu
r
es with
th
e
co
m
p
lex
ity
o
f
m
o
d
els,
esp
ec
ially
in
DL
ap
p
r
o
ac
h
es,
r
em
ain
s
a
ch
allen
g
e
f
o
r
r
esear
ch
er
s
.
−
I
m
b
alan
ce
d
d
atasets
:
m
an
y
s
tu
d
ies
f
ac
e
th
e
ch
allen
g
e
o
f
im
b
alan
ce
d
d
atasets
,
p
ar
ticu
lar
ly
in
ASD
d
etec
tio
n
,
wh
e
r
e
th
e
n
u
m
b
er
o
f
af
f
ec
ted
i
n
d
iv
id
u
als
m
ay
b
e
s
ig
n
if
ican
tly
lo
wer
t
h
an
n
o
n
-
af
f
ec
ted
o
n
es,
lead
in
g
to
b
iased
m
o
d
e
l
p
er
f
o
r
m
an
ce
.
−
I
m
p
ac
t
o
n
m
o
d
el
p
er
f
o
r
m
an
ce
:
class
im
b
alan
ce
ca
n
s
k
ew
ev
alu
atio
n
m
etr
ics
s
u
ch
as
ac
cu
r
ac
y
,
p
r
ec
is
io
n
,
r
ec
all,
an
d
F1
-
s
co
r
e,
n
ec
ess
itatin
g
tech
n
iq
u
es
lik
e
r
esam
p
lin
g
,
co
s
t
-
s
en
s
itiv
e
lear
n
in
g
,
o
r
en
s
em
b
le
m
eth
o
d
s
to
m
itig
ate
th
ese
ef
f
e
cts.
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:
2
5
0
2
-
4
7
52
E
xp
lo
r
a
tio
n
o
f v
a
r
io
u
s
a
p
p
r
o
a
ch
es fo
r
d
etec
tio
n
o
f
a
u
tis
m
s
p
ec
tr
u
m
d
is
o
r
d
er
(
K
a
vith
a
Ga
n
g
a
r
a
ju
)
637
−
Gen
er
aliza
b
ilit
y
:
m
o
d
els
tr
ain
ed
o
n
im
b
alan
ce
d
d
ata
m
a
y
s
tr
u
g
g
le
to
g
en
er
alize
well
to
r
ea
l
-
wo
r
ld
s
ce
n
ar
io
s
,
h
ig
h
lig
h
tin
g
th
e
im
p
o
r
tan
ce
o
f
ad
d
r
ess
in
g
class
im
b
alan
ce
f
o
r
r
o
b
u
s
t a
n
d
r
eliab
le
p
r
ed
ictio
n
s
.
−
Ad
v
an
ce
d
s
en
s
o
r
tech
n
o
lo
g
ie
s
:
in
v
est
in
r
esear
ch
an
d
d
e
v
e
lo
p
m
en
t
o
f
a
d
v
an
ce
d
s
en
s
o
r
tech
n
o
lo
g
ies
th
at
o
f
f
er
im
p
r
o
v
e
d
ac
cu
r
ac
y
,
s
e
n
s
itiv
ity
,
an
d
d
ata
s
y
n
c
h
r
o
n
i
za
tio
n
ca
p
ab
ilit
ies
f
o
r
b
e
h
av
io
r
in
f
o
r
m
atio
n
co
llectio
n
.
−
Alg
o
r
ith
m
ic
ad
v
an
ce
m
e
n
ts
:
co
n
tin
u
o
u
s
ly
r
ef
in
e
alg
o
r
ith
m
s
f
o
r
f
ea
tu
r
e
o
p
tim
izatio
n
,
d
at
a
p
r
ep
r
o
ce
s
s
in
g
,
an
d
class
im
b
alan
ce
h
a
n
d
lin
g
,
lev
er
ag
in
g
tech
n
iq
u
es
s
u
ch
a
s
f
ea
tu
r
e
en
g
i
n
ee
r
in
g
,
an
o
m
al
y
d
etec
tio
n
,
an
d
en
s
em
b
le
lear
n
in
g
.
−
C
o
llab
o
r
ativ
e
r
esear
ch
:
f
o
s
ter
in
ter
d
is
cip
lin
ar
y
co
llab
o
r
atio
n
b
etwe
en
ex
p
er
ts
in
p
s
y
ch
o
lo
g
y
,
d
ata
s
cien
ce
,
an
d
h
ea
lth
ca
r
e
to
lev
e
r
ag
e
d
o
m
ain
k
n
o
wled
g
e
f
o
r
m
o
r
e
e
f
f
ec
tiv
e
d
ata
c
o
llectio
n
,
an
al
y
s
is
,
an
d
m
o
d
e
l
d
ev
elo
p
m
e
n
t.
B
y
ad
d
r
ess
in
g
th
ese
g
a
p
s
,
is
s
u
es,
an
d
ch
allen
g
es
an
d
im
p
le
m
en
tin
g
th
e
r
ec
o
m
m
e
n
d
ed
s
tr
ateg
ies,
r
esear
ch
er
s
ca
n
co
n
tr
ib
u
te
to
m
o
r
e
ac
cu
r
ate,
r
eliab
le,
a
n
d
eth
icall
y
s
o
u
n
d
ap
p
r
o
ac
h
es
in
u
tili
zin
g
s
en
s
o
r
an
d
b
eh
av
io
r
in
f
o
r
m
atio
n
f
o
r
ass
is
tin
g
in
d
iv
id
u
als,
p
ar
ticu
lar
l
y
th
o
s
e
with
ASD,
in
d
iv
e
r
s
e
h
ea
lth
ca
r
e
a
n
d
s
u
p
p
o
r
t
s
ettin
g
s
.
T
o
ad
d
r
ess
all
th
e
ab
o
v
e
is
s
u
e
s
,
a
n
o
v
el
ap
p
r
o
ac
h
is
p
r
esen
te
d
in
th
e
n
ex
t sectio
n
.
4.
P
RO
P
O
SE
D
AP
P
RO
ACH
T
h
is
s
ec
tio
n
in
tr
o
d
u
ce
s
a
n
o
v
el
f
r
am
ewo
r
k
d
esig
n
e
d
s
p
ec
if
ically
f
o
r
ASD.
T
h
e
f
r
am
ewo
r
k
en
co
m
p
ass
es
s
ev
er
al
k
ey
s
te
p
s
aim
ed
at
lev
er
ag
in
g
tech
n
o
lo
g
y
to
im
p
r
o
v
e
ass
is
tan
c
e
an
d
s
u
p
p
o
r
t
f
o
r
in
d
iv
id
u
als
with
ASD.
T
h
e
co
m
p
lete
f
lo
w
o
f
th
e
f
r
am
e
wo
r
k
is
p
r
esen
ted
in
Fig
u
r
e
2
.
T
h
e
f
ir
s
t
s
tep
i
n
v
o
lv
es
th
e
co
llectio
n
o
f
d
ata
d
ir
ec
tly
f
r
o
m
ASD
in
d
iv
id
u
als
th
r
o
u
g
h
th
e
u
tili
za
tio
n
o
f
W
I
o
T
s
en
s
o
r
s
.
T
h
ese
s
en
s
o
r
s
ar
e
s
tr
ateg
ically
p
lace
d
to
ca
p
tu
r
e
a
wid
e
r
an
g
e
o
f
b
eh
av
io
r
al
d
ata
an
d
in
ter
ac
tio
n
s
in
r
ea
l
-
tim
e,
p
r
o
v
id
in
g
a
co
m
p
r
eh
e
n
s
iv
e
v
iew
o
f
th
e
in
d
iv
id
u
al
’
s
ac
tiv
ities
an
d
r
esp
o
n
s
es.
On
ce
th
e
d
ata
is
co
llect
ed
,
th
e
n
ex
t
p
h
ase
in
v
o
lv
es
ex
tr
ac
tin
g
b
eh
av
i
o
r
al
p
atter
n
s
an
d
in
s
ig
h
ts
f
r
o
m
th
e
d
ataset.
T
h
is
p
r
o
ce
s
s
en
tails
i
d
en
tify
in
g
r
elev
an
t
b
eh
av
io
r
d
ata
p
o
i
n
ts
th
at
ar
e
in
d
icativ
e
o
f
ASD
-
r
elate
d
ch
ar
ac
ter
is
tics
o
r
ten
d
en
cies.
T
h
is
s
tep
is
cr
u
cial
as
it
f
o
r
m
s
th
e
b
asis
f
o
r
s
u
b
s
eq
u
en
t
an
aly
s
is
an
d
d
ec
is
io
n
-
m
ak
in
g
with
in
th
e
f
r
am
ewo
r
k
.
Fo
llo
win
g
th
e
ex
t
r
ac
tio
n
o
f
b
eh
av
i
o
r
d
ata,
th
e
f
r
am
ew
o
r
k
f
o
cu
s
es
o
n
f
ea
tu
r
e
s
elec
tio
n
an
d
o
p
tim
izatio
n
.
T
h
is
in
v
o
lv
es
id
en
tify
in
g
th
e
m
o
s
t
r
elev
an
t
an
d
in
f
o
r
m
ati
v
e
f
ea
tu
r
es
f
r
o
m
th
e
b
eh
a
v
i
o
r
s
d
ata
th
at
co
n
tr
ib
u
te
s
ig
n
if
ican
tly
to
ASD
p
r
ed
ictio
n
.
Ad
v
a
n
ce
d
tech
n
iq
u
es
s
u
ch
as
f
ea
tu
r
e
en
g
i
n
ee
r
in
g
an
d
d
im
en
s
io
n
ality
r
ed
u
ctio
n
m
ay
b
e
em
p
l
o
y
e
d
to
en
h
a
n
ce
t
h
e
q
u
ality
a
n
d
ef
f
icien
cy
o
f
f
ea
tu
r
e
s
elec
tio
n
.
W
ith
o
p
tim
ized
f
ea
tu
r
es
in
h
an
d
,
t
h
e
f
r
am
ewo
r
k
will
in
co
r
p
o
r
ate
u
s
in
g
ML
o
r
DL
ap
p
r
o
ac
h
es
to
p
r
ed
ict
wh
eth
er
an
in
d
iv
id
u
al
h
as
ASD
o
r
n
o
t.
T
h
ese
p
r
ed
ictiv
e
m
o
d
els
lev
er
ag
e
th
e
s
elec
ted
f
ea
tu
r
es
to
m
ak
e
a
cc
u
r
ate
an
d
r
eliab
le
ass
ess
m
en
ts
r
eg
ar
d
in
g
ASD
d
iag
n
o
s
is
,
co
n
tr
ib
u
tin
g
to
ea
r
ly
d
etec
tio
n
an
d
in
ter
v
e
n
tio
n
ef
f
o
r
ts
.
Fin
ally
,
b
ased
o
n
th
e
ASD
p
r
ed
ictio
n
r
esu
lts
,
th
e
f
r
am
ewo
r
k
in
teg
r
ates
a
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
d
esig
n
ed
to
ass
is
t
ASD
in
d
iv
id
u
a
ls
.
T
h
is
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
u
tili
ze
s
th
e
in
s
ig
h
ts
g
ain
e
d
f
r
o
m
b
eh
av
io
r
al
d
ata
a
n
aly
s
is
an
d
ASD
p
r
ed
ictio
n
t
o
o
f
f
er
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
,
in
ter
v
e
n
tio
n
s
,
o
r
s
u
p
p
o
r
t
s
tr
ateg
ies.
T
h
ese
r
ec
o
m
m
en
d
atio
n
s
m
ay
s
p
an
v
ar
io
u
s
d
o
m
ain
s
s
u
ch
as
th
er
a
p
y
,
e
d
u
ca
t
io
n
,
s
o
cial
in
ter
ac
ti
o
n
s
,
an
d
d
aily
liv
in
g
ac
tiv
ities
,
aim
in
g
to
im
p
r
o
v
e
o
v
er
all
q
u
ality
o
f
life
an
d
well
-
b
ein
g
f
o
r
i
n
d
iv
id
u
als
with
ASD.
Ov
er
all,
th
is
n
o
v
el
ASD
f
r
am
ewo
r
k
r
ep
r
esen
ts
an
in
teg
r
ated
an
d
t
ec
h
n
o
lo
g
y
-
d
r
iv
en
a
p
p
r
o
ac
h
f
o
r
ad
d
r
ess
in
g
th
e
u
n
iq
u
e
c
h
allen
g
es
f
ac
ed
b
y
ASD
in
d
iv
id
u
als,
o
f
f
er
in
g
p
e
r
s
o
n
ali
ze
d
ass
is
tan
ce
an
d
s
u
p
p
o
r
t
th
r
o
u
g
h
d
ata
-
d
r
iv
en
in
s
ig
h
ts
,
p
r
e
d
ictiv
e
m
o
d
ellin
g
,
an
d
d
esig
n
e
d
r
ec
o
m
m
en
d
atio
n
s
.
Fig
u
r
e
2
.
Pro
p
o
s
ed
ASD
f
r
am
ewo
r
k
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
8
,
No
.
1
,
Ap
r
il
20
2
5
:
63
2
-
6
40
638
5.
CO
NCLU
SI
O
N
T
h
e
co
m
p
r
eh
en
s
iv
e
ex
p
lo
r
ati
o
n
o
f
v
ar
io
u
s
m
eth
o
d
o
l
o
g
ies,
tech
n
o
lo
g
ies,
an
d
f
r
am
ew
o
r
k
s
p
r
esen
ted
in
th
is
liter
atu
r
e
s
u
r
v
ey
u
n
d
er
s
co
r
es
th
e
o
n
g
o
in
g
ef
f
o
r
ts
a
n
d
ad
v
a
n
ce
m
en
ts
in
ad
d
r
ess
in
g
ASD
f
r
o
m
m
u
ltip
le
p
er
s
p
ec
tiv
es.
T
h
e
k
ey
f
in
d
in
g
s
an
d
i
n
s
ig
h
ts
co
llected
f
r
o
m
th
e
s
u
r
v
ey
ed
wo
r
k
s
p
a
v
e
th
e
way
f
o
r
a
d
ee
p
e
r
u
n
d
er
s
tan
d
i
n
g
o
f
ef
f
ec
tiv
e
s
tr
ateg
ies
f
o
r
d
ata
co
llectio
n
,
an
aly
s
is
,
p
r
ed
ictio
n
,
a
n
d
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
tailo
r
ed
to
ass
is
t
in
d
iv
id
u
als
w
ith
ASD.
On
e
o
f
th
e
n
o
tab
le
tr
en
d
s
o
b
s
er
v
ed
is
th
e
i
n
teg
r
atio
n
o
f
W
I
o
T
s
en
s
o
r
s
f
o
r
d
ata
co
llectio
n
,
allo
win
g
f
o
r
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
an
d
ca
p
tu
r
e
o
f
b
e
h
av
io
r
al
p
att
er
n
s
an
d
r
esp
o
n
s
es.
T
h
is
n
o
t
o
n
ly
f
ac
ilit
ates
m
o
r
e
ac
cu
r
ate
an
d
d
etailed
d
ata
co
llectio
n
b
u
t
also
en
ab
les
th
e
d
ev
elo
p
m
en
t
o
f
p
er
s
o
n
alize
d
in
ter
v
en
tio
n
s
a
n
d
s
u
p
p
o
r
t
s
y
s
tem
s
b
ased
o
n
in
d
iv
id
u
alize
d
b
eh
a
v
io
r
al
p
r
o
f
iles
.
Fu
r
th
er
m
o
r
e
,
th
e
ad
o
p
tio
n
o
f
ML
,
DL
,
an
d
h
y
b
r
id
tech
n
i
q
u
es
h
as
d
em
o
n
s
tr
ated
s
ig
n
if
ican
t
p
r
o
g
r
ess
in
ASD
d
etec
tio
n
,
class
if
icatio
n
,
an
d
p
r
ed
ictio
n
.
T
h
ese
ad
v
an
ce
d
co
m
p
u
tatio
n
al
ap
p
r
o
ac
h
es,
c
o
m
b
in
e
d
with
o
p
tim
ized
f
ea
tu
r
e
s
elec
tio
n
an
d
m
o
d
el
tr
ain
in
g
,
co
n
tr
ib
u
te
to
ea
r
ly
d
iag
n
o
s
is
,
in
ter
v
en
tio
n
p
lan
n
in
g
,
an
d
p
er
s
o
n
alize
d
r
ec
o
m
m
en
d
atio
n
s
y
s
tem
s
aim
ed
at
im
p
r
o
v
in
g
o
u
tc
o
m
es
f
o
r
ASD
in
d
iv
id
u
als.
T
h
e
em
p
h
asis
o
n
ad
d
r
ess
in
g
ch
allen
g
es
s
u
ch
as
class
im
b
ala
n
ce
,
f
ea
tu
r
e
o
p
tim
izatio
n
,
an
d
d
ata
co
llectio
n
ef
f
icie
n
cy
h
ig
h
lig
h
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h
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c
a
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b
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n
tac
ted
a
t
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m
a
il
:
k
a
v
it
h
a
g
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srit.
e
d
u
.
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.
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ish
a
H
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wo
rk
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s
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ro
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ted
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ti
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in
ter
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s/jo
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m
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g
2
5
p
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rs
we
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d
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x
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COPU
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,
1
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a
n
d
t
h
re
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p
a
p
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in
DBLP
.
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p
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n
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p
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r
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it
.
As
so
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d
with
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a
n
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ro
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a
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b
o
d
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-
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TE
,
CS
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a
n
d
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v
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g
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rsiti
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s.
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c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
y
o
g
is
h
h
k
@m
srit.
e
d
u
.
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