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
.
5
,
Octo
b
er
2
0
2
5
,
p
p
.
3
9
0
6
~
3
9
1
4
I
SS
N:
2
2
5
2
-
8
9
3
8
,
DOI
: 1
0
.
1
1
5
9
1
/ijai.v
14
.i
5
.
p
p
3
9
0
6
-
3
9
1
4
3906
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
i
.
ia
esco
r
e.
co
m
User accep
tance o
f
the
g
ender
and
dev
elo
pment
mo
b
ile app
with
a
ra
ting chec
klist using
a mo
di
fied
technolo
g
y
acceptan
ce
mo
del
Ro
s
s
ia
n V.
P
er
ea
1
,
Abig
a
el
M
.
M
ira
n
da
2
1
I
n
f
o
r
mat
i
o
n
T
e
c
h
n
o
l
o
g
y
D
e
p
a
r
t
me
n
t
,
C
a
v
i
t
e
S
t
a
t
e
U
n
i
v
e
r
si
t
y
N
a
i
c
,
N
a
i
c
,
P
h
i
l
i
p
p
i
n
e
s
2
M
a
n
a
g
e
me
n
t
D
e
p
a
r
t
m
e
n
t
,
C
a
v
i
t
e
S
t
a
t
e
U
n
i
v
e
r
s
i
t
y
N
a
i
c
,
N
a
i
c
,
P
h
i
l
i
p
p
i
n
e
s
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ap
r
2
6
,
2
0
2
4
R
ev
is
ed
J
u
l 1
0
,
2
0
2
5
Acc
ep
ted
Au
g
6
,
2
0
2
5
Re
so
u
rc
e
c
e
n
ters
o
f
g
e
n
d
e
r
a
n
d
d
e
v
e
lo
p
m
e
n
t
(G
AD
)
in
l
o
c
a
l
g
o
v
e
r
n
m
e
n
t
u
se
th
e
trad
it
io
n
a
l
m
e
th
o
d
o
f
d
isse
m
in
a
ti
n
g
i
n
fo
rm
a
ti
o
n
a
b
o
u
t
G
AD
a
wa
re
n
e
ss
,
su
c
h
a
s
d
istri
b
u
t
in
g
p
ri
n
ted
c
a
m
p
a
ig
n
m
a
teria
ls
a
n
d
c
o
n
d
u
c
ti
n
g
g
e
n
d
e
r
se
n
siti
v
it
y
train
i
n
g
(G
S
T)
o
n
f
a
c
u
lt
y
a
n
d
sta
ff,
stu
d
e
n
ts,
a
n
d
se
lec
ted
b
a
ra
n
g
a
y
c
o
m
m
u
n
i
ti
e
s
in
t
h
e
P
h
il
ip
p
i
n
e
s.
S
o
m
e
re
c
ip
ien
ts
o
f
c
a
m
p
a
ig
n
m
a
teria
ls
a
re
tex
t
-
h
e
a
v
y
a
n
d
u
n
a
p
p
e
a
li
n
g
t
o
re
a
d
,
wh
ich
m
a
k
e
s
th
e
m
les
s
in
tere
ste
d
.
H
o
we
v
e
r,
fa
c
u
lt
y
a
n
d
stu
d
e
n
ts
c
o
n
d
u
c
ti
n
g
re
se
a
rc
h
a
re
n
o
t
a
wa
re
if
t
h
e
i
r
st
u
d
y
is
g
e
n
d
e
r
-
re
sp
o
n
siv
e
o
r
if
G
AD
is
in
v
isib
le.
He
n
c
e
,
th
is
st
u
d
y
e
x
a
m
in
e
s
th
e
u
se
r
a
c
c
e
p
tan
c
e
o
f
th
e
G
AD
a
p
p
m
o
b
il
e
a
p
p
li
c
a
ti
o
n
u
si
n
g
t
h
e
m
o
d
ifi
e
d
tec
h
n
o
l
o
g
y
a
c
c
e
p
tan
c
e
m
o
d
e
l
(TAM
)
with
a
m
a
c
h
in
e
lea
rn
in
g
(M
L)
a
lg
o
r
it
h
m
a
p
p
li
e
d
.
Th
e
r
e
su
lt
s
o
f
sta
ti
stics
a
n
d
a
n
a
l
y
se
s
fro
m
th
e
in
ten
d
e
d
u
se
rs
(N=
1
0
0
)
we
re
p
re
se
n
ted
i
n
c
lu
d
in
g
d
a
ta
-
d
ri
v
e
n
m
o
d
e
li
n
g
u
sin
g
a
su
p
p
o
rt
v
e
c
to
r
m
a
c
h
in
e
(S
VM)
to
sh
o
w
p
re
c
ise
fin
d
in
g
s
fo
r
th
e
re
se
a
rc
h
o
n
h
o
w
th
is
tec
h
n
o
l
o
g
y
wa
s
u
se
d
a
n
d
a
c
c
e
p
ted
.
T
h
e
stu
d
y
’s
fin
d
i
n
g
s
sh
o
w
wid
e
sp
re
a
d
a
c
c
e
p
t
a
n
c
e
a
m
o
n
g
e
x
p
e
rts
a
n
d
u
se
rs
of
t
h
e
m
o
b
i
le
a
p
p
li
c
a
ti
o
n
e
m
p
l
o
y
in
g
e
x
tern
a
l
f
a
c
to
rs
li
k
e
se
lf
-
e
ffica
c
y
(S
E)
a
n
d
sp
e
c
ifi
c
a
n
x
iety
(S
A)
a
n
d
m
o
d
e
ra
ti
n
g
v
a
ri
a
b
les
su
c
h
a
s
a
g
e
,
se
x
,
h
i
g
h
e
st
e
d
u
c
a
ti
o
n
a
l
a
tt
a
in
m
e
n
t
(
HEA),
a
n
d
k
n
o
wle
d
g
e
in
G
AD
imp
lem
e
n
tatio
n
,
wh
ich
a
re
c
ru
c
ial
fo
r
p
re
d
icti
n
g
a
n
d
u
n
d
e
r
sta
n
d
in
g
th
e
c
o
n
se
q
u
e
n
c
e
s
o
f
t
h
e
re
se
a
r
c
h
m
a
d
e
c
lea
r.
K
ey
w
o
r
d
s
:
A
n
aly
tics
D
ata
-
d
r
iv
en
G
en
d
er
an
d
d
ev
el
o
p
m
en
t
M
o
b
ile
ap
p
licatio
n
Mo
d
if
ied
tech
n
o
lo
g
y
a
cc
ep
tan
ce
m
o
d
el
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
:
Ab
ig
ae
l M
.
Mir
an
d
a
Ma
n
ag
em
en
t
Dep
a
r
tm
en
t
,
C
av
ite
State
Un
iv
er
s
ity
Naic
B
u
ca
n
a
Ma
lak
i,
Naic
,
C
av
ite,
Ph
ilip
p
in
es
E
m
ail:
am
m
ir
an
d
a
@
cv
s
u
-
n
aic
.
ed
u
.
p
h
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
Ph
ilip
p
in
es’
co
m
m
itm
en
t
to
th
e
C
o
n
v
en
tio
n
o
n
th
e
E
lim
in
atio
n
o
f
All
Fo
r
m
s
o
f
Dis
cr
im
in
atio
n
Ag
ain
s
t Wo
m
en
(
C
E
DAW)
a
n
d
th
e
1
9
9
5
B
eijin
g
Platfo
r
m
Fo
r
Actio
n
(
B
PF
A)
is
e
s
s
en
tia
l in
f
o
s
ter
in
g
g
en
d
er
s
en
s
itiv
ity
an
d
awa
r
en
ess
.
M
o
r
e
s
ig
n
if
ican
tly
,
th
is
co
m
m
itm
en
t
h
as
b
ee
n
in
s
tr
u
m
en
tal
in
s
h
ap
in
g
n
atio
n
a
l
f
r
am
ewo
r
k
s
f
o
r
g
en
d
er
-
r
elate
d
p
o
licies,
s
tan
d
a
r
d
s
,
a
n
d
g
u
i
d
elin
es
[
1
]
as
a
way
o
f
life
f
o
r
th
e
Ph
ilip
p
in
es
[
2
]
,
[
3
]
wh
ic
h
was
also
o
r
d
er
ed
b
y
th
e
C
o
m
m
is
s
io
n
o
n
Hig
h
er
E
d
u
ca
tio
n
(
C
HE
D)
Me
m
o
r
a
n
d
u
m
Or
d
er
No
.
0
1
s
er
ies
o
f
2
0
1
5
[
4
]
.
T
h
e
g
en
d
er
an
d
d
ev
elo
p
m
en
t
(
GAD)
u
n
it
u
s
es
th
e
tr
ad
itio
n
al
m
eth
o
d
o
f
d
is
s
em
in
atin
g
in
f
o
r
m
atio
n
ab
o
u
t
GAD
awa
r
en
ess
s
u
ch
as
th
e
d
is
tr
ib
u
tio
n
o
f
p
r
in
ted
ca
m
p
aig
n
m
ater
ials
an
d
co
n
d
u
ctin
g
g
en
d
er
s
en
s
itiv
ity
tr
ain
in
g
(
G
ST)
o
n
f
ac
u
lty
an
d
s
taf
f
,
s
tu
d
e
n
ts
,
an
d
s
elec
ted
b
ar
a
n
g
ay
co
m
m
u
n
ities
to
ass
ess
th
eir
k
n
o
wled
g
e
i
n
GAD.
So
m
e
r
ec
eiv
er
s
o
f
ca
m
p
aig
n
m
at
er
ials
ar
e
n
o
t
t
o
o
i
n
ter
ested
b
e
ca
u
s
e
n
o
t
attr
ac
tiv
e
to
r
ea
d
d
u
e
to
th
e
tex
t
-
h
ea
v
y
f
o
r
m
at.
T
h
e
ac
ad
e
m
e
an
d
s
tu
d
e
n
ts
wh
o
ar
e
co
n
d
u
ctin
g
r
esear
ch
ar
e
n
o
t
awa
r
e
if
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
User
a
cc
ep
ta
n
ce
o
f th
e
GA
D
mo
b
ile
a
p
p
w
ith
a
r
a
tin
g
ch
ec
klis
t u
s
in
g
a
mo
d
ified
…
(
R
o
s
s
ia
n
V
.
P
erea
)
3907
th
eir
s
tu
d
y
is
g
e
n
d
er
-
r
esp
o
n
s
i
v
e
o
r
GAD
is
in
v
is
ib
le
in
th
e
p
r
o
p
o
s
ed
p
r
o
ject
o
r
s
tu
d
y
.
Hen
ce
,
th
e
GAD
a
pp
is
a
m
o
b
ile
-
b
ased
tech
n
o
lo
g
y
d
ev
elo
p
ed
b
y
m
y
co
-
d
ev
elo
p
e
r
f
r
o
m
th
e
B
ac
h
elo
r
o
f
Scien
ce
in
I
n
f
o
r
m
atio
n
T
ec
h
n
o
lo
g
y
(
B
SIT
)
s
tu
d
en
ts
to
s
h
o
wca
s
e
GAD
awa
r
en
ess
an
d
d
is
cip
lin
es.
T
h
e
latter
is
ch
ar
ac
ter
ized
as
a
wir
eless
co
m
p
u
tin
g
d
ev
ice
th
at
is
p
o
r
tab
le
an
d
tin
y
en
o
u
g
h
to
b
e
o
p
er
ated
with
o
n
e
h
an
d
[
5
]
.
B
y
in
teg
r
atin
g
b
o
th
tech
n
ical
an
d
s
o
cial
elem
en
ts
,
th
e
GAD
a
pp
s
ee
k
s
to
ed
u
ca
te
th
e
g
en
er
al
p
u
b
lic,
in
clu
d
in
g
m
en
,
wo
m
e
n
,
s
en
io
r
citizen
s
,
ch
ild
r
en
,
an
d
p
er
s
o
n
s
with
d
is
ab
ilit
ies
(
P
W
Ds),
en
s
u
r
in
g
th
at
ev
er
y
o
n
e,
r
eg
ar
d
less
o
f
ag
e
o
r
g
en
d
er
,
h
as a
n
eq
u
al
u
n
d
e
r
s
tan
d
in
g
o
f
GAD,
wh
ich
em
p
h
asize
d
is
cip
lin
es,
law
s
,
an
d
m
an
d
ates.
I
n
th
e
p
r
o
ce
s
s
o
f
ad
o
p
tin
g
tech
n
o
lo
g
y
,
n
u
m
e
r
o
u
s
m
o
d
els
an
d
f
r
am
ewo
r
k
s
h
av
e
b
ee
n
d
ev
elo
p
e
d
to
d
escr
i
b
e
h
o
w
u
s
er
s
ad
o
p
t
n
ew
tech
n
o
lo
g
ies.
T
h
ese
m
o
d
els
em
p
lo
y
Dav
is
'
(
1
9
8
9
)
ex
is
tin
g
(
o
ld
)
th
eo
r
y
to
in
co
r
p
o
r
a
te
asp
ec
ts
th
at
ca
n
af
f
ec
t u
s
er
ac
ce
p
tan
ce
u
s
in
g
th
e
tech
n
o
lo
g
y
ac
ce
p
ta
n
ce
m
o
d
e
l
(
T
AM
)
[
6
]
–
[
8
]
.
T
h
is
s
tu
d
y
in
ten
d
s
to
in
v
esti
g
ate
th
e
in
ten
tio
n
o
f
u
s
in
g
a
m
o
b
ile
ap
p
licatio
n
f
o
r
GAD
aw
ar
en
ess
an
d
d
is
cip
lin
e
b
ased
o
n
th
e
th
eo
r
y
o
f
th
e
T
AM
.
T
h
is
d
em
o
n
s
tr
ates
th
e
ap
p
ar
en
t
n
ee
d
t
o
ac
k
n
o
wled
g
e
th
e
im
p
o
r
tan
t
r
o
le
o
f
I
T
in
m
o
d
er
n
ed
u
ca
ti
o
n
a
n
d
s
u
g
g
ests
a
p
a
r
ad
ig
m
f
o
r
ass
ess
in
g
I
T
ad
o
p
t
io
n
th
at
co
m
b
i
n
es
T
AM
an
d
s
o
cial
co
g
n
itiv
e
t
h
eo
r
y
(
SC
T
)
b
y
th
e
en
d
-
u
s
e
r
s
b
ased
o
n
th
ei
r
ag
e
,
s
ex
,
h
ig
h
est
ed
u
ca
tio
n
al
attain
m
en
t,
an
d
k
n
o
wled
g
e
o
f
th
e
GAD
im
p
lem
en
tatio
n
o
n
th
eir
wo
r
k
p
lace
.
I
t
was
d
es
ig
n
ed
esp
ec
ially
to
f
o
r
ec
ast
wh
o
is
m
o
s
t
lik
ely
to
em
b
r
ac
e
n
ew
tech
n
o
lo
g
y
in
a
p
r
o
f
ess
io
n
al
s
ettin
g
.
Ov
er
th
e
p
ast
f
ew
d
ec
ad
es,
n
u
m
er
o
u
s
th
eo
r
ies
o
f
tech
n
o
l
o
g
y
ac
ce
p
tan
ce
h
av
e
b
ee
n
p
u
t
u
p
an
d
d
ev
elo
p
e
d
in
th
e
liter
atu
r
e
o
n
in
f
o
r
m
atio
n
s
y
s
tem
s
r
esear
ch
[
7
]
–
[
9
]
in
cl
u
d
in
g
o
u
r
r
esear
c
h
o
u
tp
u
t
[
1
0
]
.
W
h
ile
ea
r
lier
s
tu
d
ies
h
av
e
o
n
ly
ex
p
lo
r
ed
t
h
e
v
ar
iab
les'
u
s
e
o
f
T
AM
,
th
ey
h
av
e
n
o
t
ex
p
licitly
a
d
d
r
ess
ed
th
e
in
f
lu
en
c
e
o
f
ap
p
ly
in
g
ex
ter
n
al
v
ar
iab
les
th
r
o
u
g
h
SC
T
with
m
o
d
e
r
atin
g
v
ar
iab
les
b
y
an
aly
zin
g
b
e
h
av
io
r
al
in
ten
t
(
B
I
)
o
n
t
h
e
ac
tu
al
u
s
e.
Acc
o
r
d
i
n
g
to
th
e
co
n
ce
p
t,
a
n
u
m
b
er
o
f
f
ac
t
o
r
s
,
m
o
s
t
n
o
tab
ly
p
er
ce
iv
e
d
u
s
ef
u
ln
ess
(
PU)
an
d
p
er
ce
iv
e
d
ea
s
e
o
f
u
s
e
(
P
E
U
)
,
af
f
ec
t
co
n
s
u
m
e
r
s
'
d
ec
is
io
n
s
ab
o
u
t
h
o
w
an
d
wh
en
to
ad
o
p
t
n
ew
tech
n
o
lo
g
y
[
1
1
]
.
T
AM
c
o
n
s
is
ts
o
f
two
s
id
es,
PU
an
d
P
E
U
m
ak
e
u
p
th
e
f
ir
s
t
s
et
o
f
s
o
-
ca
lled
b
elief
s
,
wh
il
e
attitu
d
e,
b
eh
av
io
r
al
in
te
n
tio
n
to
u
s
e
,
an
d
ac
tu
al
u
s
ag
e
b
eh
av
i
o
r
m
ak
e
u
p
th
e
s
e
co
n
d
s
et
[
7
]
.
T
AM
s
h
o
ws h
o
w
u
s
er
s
'
att
itu
d
es,
o
b
jectiv
es,
o
r
in
ten
tio
n
s
,
as we
ll
as
h
o
w
th
e
s
y
s
tem
is
u
s
ed
,
r
el
ate
to
th
eir
f
aith
an
d
b
elief
s
(
u
s
ef
u
ln
ess
an
d
ea
s
e
o
f
u
s
e)
.
T
h
e
d
eg
r
ee
to
wh
ich
a
p
er
s
o
n
t
h
in
k
s
th
at
u
s
in
g
a
s
y
s
tem
in
p
ar
ticu
lar
will
en
h
a
n
c
e
its
p
er
f
o
r
m
an
ce
is
k
n
o
wn
a
s
PU
.
Ad
d
itio
n
ally
,
P
E
U
is
th
e
ex
ten
t
to
wh
ich
an
in
d
iv
id
u
al
th
i
n
k
s
th
at
u
s
in
g
th
e
s
y
s
tem
in
p
ar
ticu
lar
will
r
esu
lt
in
a
b
u
s
in
ess
f
ield
[
3
]
,
[
1
2
]
,
[
1
3
]
.
SC
T
is
o
n
e
o
f
th
e
m
o
s
t
p
o
wer
f
u
l
t
h
eo
r
ies
o
f
h
u
m
a
n
b
eh
av
i
o
r
.
T
h
e
im
p
o
r
tan
t
r
o
le
th
at
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
p
la
y
s
in
co
n
tem
p
o
r
ar
y
ed
u
ca
tio
n
s
u
g
g
ests
a
p
ar
ad
ig
m
f
o
r
ass
es
s
in
g
I
T
ac
ce
p
tan
ce
th
at
co
m
b
in
es
SC
T
an
d
th
eo
r
y
o
f
ac
tio
n
T
AM
[
7
]
.
T
h
is
th
eo
r
y
o
f
lear
n
i
n
g
is
p
r
ed
icate
d
o
n
th
e
n
o
tio
n
th
at
p
eo
p
le
p
ick
u
p
k
n
o
wled
g
e
b
y
s
ee
in
g
wh
at
o
th
er
p
eo
p
le
d
o
in
t
h
e
c
o
n
tex
t
o
f
s
o
cial
in
ter
ac
tio
n
s
an
d
ex
p
er
ien
ce
s
.
I
n
th
e
co
n
tex
t
o
f
co
m
p
u
ter
u
s
e,
ce
r
tain
liter
ar
y
wo
r
k
s
ex
ten
d
e
d
an
d
ap
p
lied
SC
T
to
p
r
o
m
o
te
tech
n
o
lo
g
y
ac
ce
p
ta
n
ce
[
7
]
,
[
1
4
]
.
Fo
u
r
co
m
p
o
n
en
ts
m
ak
e
u
p
th
e
SC
T
,
s
u
ch
as
a
f
f
ec
t,
SA
,
s
elf
-
ef
f
icac
y
(
SE)
,
an
d
o
u
tco
m
e
ex
p
ec
tatio
n
s
[
4
]
,
[
5
]
.
T
h
e
r
esear
ch
'
s
d
esig
n
in
co
r
p
o
r
ates
co
n
ce
p
ts
f
r
o
m
SC
T
in
ad
d
itio
n
to
th
o
s
e
f
r
o
m
Dav
is
'
T
AM
.
Fu
r
th
er
m
o
r
e
,
wh
ile
d
ata
an
aly
tics
p
r
o
v
id
es
en
d
u
s
er
s
with
ac
ce
s
s
to
an
o
r
g
an
izatio
n
'
s
i
n
f
o
r
m
atio
n
with
o
u
t
r
eq
u
i
r
in
g
d
ir
ec
t
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
(
I
T
)
s
u
p
p
o
r
t,
it
also
r
ef
er
s
to
th
e
id
ea
s
,
tech
n
o
lo
g
ies,
to
o
ls
,
an
d
p
r
o
ce
d
u
r
es
th
at
p
r
o
v
id
e
in
-
d
ep
th
a
n
aly
s
is
an
d
th
e
d
is
co
v
er
y
o
f
ac
tio
n
ab
le
in
s
ig
h
t
in
to
d
ata
[
1
5
]
.
T
h
e
tr
ad
itio
n
al
b
en
ch
m
ar
k
s
tatis
t
ical
tech
n
iq
u
es,
in
clu
d
in
g
r
eg
r
ess
io
n
,
an
aly
s
is
o
f
v
ar
ian
ce
,
an
d
p
r
i
n
cip
a
l
co
m
p
o
n
en
t
an
aly
s
is
,
ar
e
u
s
ed
in
a
wid
e
r
an
g
e
o
f
ap
p
licatio
n
s
[
1
6
]
as
a
k
er
n
el
-
b
ased
m
ac
h
in
e
lear
n
in
g
(
ML
)
m
o
d
el
f
o
r
r
e
g
r
ess
io
n
an
d
class
if
icatio
n
task
s
[
1
7
]
.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
SVM)
h
av
e
r
ec
en
tly
attr
ac
ted
th
e
atten
tio
n
o
f
d
ata
m
i
n
in
g
,
p
atter
n
r
ec
o
g
n
itio
n
,
a
n
d
ML
c
o
m
m
u
n
ities
b
ec
a
u
s
e
o
f
th
eir
r
em
ar
k
ab
le
ca
p
ac
ity
f
o
r
d
is
cr
im
in
atio
n
,
o
p
tim
al
s
o
lu
tio
n
,
an
d
g
en
er
aliza
tio
n
.
SVM
h
as
d
em
o
n
s
tr
ated
ef
f
icac
y
in
ad
d
r
ess
in
g
p
r
ac
tical
b
in
ar
y
class
if
icatio
n
p
r
o
b
lem
s
[
1
6
]
,
[
1
8
]
,
[
1
9
]
.
T
h
er
e
ar
e
s
tu
d
ies
p
r
esen
tin
g
u
s
er
ac
ce
p
tan
ce
ex
p
lo
r
in
g
u
s
er
attitu
d
es
an
d
b
eh
av
io
r
al
i
n
ten
tio
n
s
to
war
d
s
u
s
in
g
d
if
f
er
e
n
t
f
ield
s
o
f
i
n
ter
est
u
s
ed
as
a
u
g
m
en
te
d
r
ea
lity
[
2
0
]
,
im
m
er
s
iv
e
tech
n
o
lo
g
y
[
1
2
]
,
I
o
T
[
2
1
]
,
d
if
f
er
e
n
t
m
o
b
ile
ap
p
licatio
n
s
u
s
ed
f
o
r
e
d
u
ca
tio
n
[
2
2
]
,
b
a
n
k
[
2
3
]
a
n
d
h
e
alth
f
ield
s
[
1
3
]
,
[
2
4
]
.
T
h
e
m
ain
o
b
jectiv
e
is
to
u
n
d
er
s
tan
d
th
e
f
ac
to
r
s
af
f
ec
tin
g
a
cc
ep
tan
ce
o
f
th
e
m
o
b
ile
ap
p
li
ca
tio
n
f
o
r
GAD
with
a
r
atin
g
ch
ec
k
lis
t
u
s
in
g
th
e
m
o
d
if
ied
T
AM
.
So
m
e
p
ar
ts
o
f
th
e
o
b
jectiv
e
s
u
ch
as
d
esig
n
in
g
a
n
e
w
T
AM
-
b
ased
m
o
d
el
with
ex
te
r
n
al
f
ac
to
r
s
af
f
ec
tin
g
th
e
ac
c
ep
tan
ce
o
f
th
e
s
aid
tech
n
o
lo
g
y
with
m
o
d
er
atin
g
v
ar
iab
les,
f
o
r
m
u
latin
g
h
y
p
o
t
h
eses
o
f
th
e
s
tu
d
y
d
esig
n
s
b
ased
o
n
th
e
T
AM
with
e
x
ter
n
al
f
ac
to
r
s
an
d
m
o
d
er
atin
g
v
ar
iab
les,
a
n
d
e
v
a
lu
atin
g
u
s
er
ac
ce
p
tan
ce
b
ased
o
n
th
e
r
esu
lt
o
f
t
h
e
s
u
r
v
e
y
q
u
esti
o
n
n
air
e
with
a
d
ata
-
d
r
iv
e
n
m
o
d
el
u
s
in
g
a
ML
alg
o
r
ith
m
.
L
astl
y
,
th
e
s
tu
d
y
aim
s
to
in
ter
p
r
et
t
h
e
p
o
ten
tial
ac
ce
p
tab
ilit
y
o
f
th
e
tech
n
o
lo
g
y
.
2.
M
E
T
H
O
D
T
h
e
co
n
s
tr
u
cted
r
esear
ch
f
r
am
ewo
r
k
f
o
r
th
e
ac
ce
p
tan
ce
o
f
t
h
e
s
y
s
tem
,
wh
ich
d
r
aws
o
n
an
ex
ten
s
iv
e
b
o
d
y
o
f
liter
atu
r
e
r
elate
d
t
o
tech
n
o
lo
g
y
ac
ce
p
tan
ce
,
was
ex
p
lain
ed
b
ased
o
n
th
e
ad
a
p
te
d
v
ar
io
u
s
co
n
s
tr
u
cts
f
r
o
m
th
e
in
ten
tio
n
-
attitu
d
e
m
o
d
els
th
at
wer
e
o
r
ig
in
ally
d
ev
el
o
p
ed
in
th
e
p
s
y
c
h
o
lo
g
y
an
d
in
f
o
r
m
atio
n
s
cien
ce
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
9
0
6
-
3
9
1
4
3908
d
is
cip
lin
es.
T
h
e
r
esear
ch
m
eth
o
d
s
ar
e
clea
r
ly
p
r
esen
ted
in
th
is
s
ec
t
io
n
b
y
id
en
tify
in
g
t
h
e
p
r
ed
icto
r
s
an
d
h
y
p
o
th
esis
,
id
en
tify
in
g
ex
ter
n
al
f
ac
to
r
s
f
r
o
m
SC
T
th
at
h
av
e
b
ee
n
m
er
g
e
d
with
th
e
o
r
ig
i
n
al
T
AM
,
an
d
th
e
f
o
r
m
u
lated
e
q
u
atio
n
f
o
r
a
d
at
a
-
d
r
iv
en
m
o
d
el
u
s
ed
f
o
r
tech
n
o
lo
g
y
ac
ce
p
tan
ce
th
r
o
u
g
h
m
o
d
er
atin
g
v
a
r
iab
les
s
u
ch
as a
g
e,
s
ex
,
h
i
g
h
est ed
u
c
atio
n
al
attain
m
en
t,
an
d
k
n
o
wled
g
e
o
n
GAD.
2
.
1
.
Resea
rc
h mo
del a
nd
hy
po
t
hes
es
T
h
e
co
n
s
tr
u
cted
m
o
d
el
s
h
o
wn
in
Fig
u
r
e
1
is
ad
ap
ted
f
r
o
m
p
r
e
v
io
u
s
s
tu
d
ies
a
n
d
f
o
cu
s
es
o
n
em
p
h
asizin
g
th
e
H7
c
o
n
n
ec
ti
o
n
o
n
t
h
e
s
ig
n
if
ican
t
in
f
l
u
en
c
e
b
etwe
en
th
e
BI
to
war
d
s
u
s
in
g
th
e
GAD
a
pp
o
n
ac
tu
al
s
y
s
tem
u
s
e,
co
r
r
elate
d
with
th
e
m
o
d
er
atin
g
v
a
r
iab
le
s
u
s
ed
in
th
e
s
tu
d
y
.
T
h
e
s
u
r
v
ey
in
s
tr
u
m
en
t
was
m
o
d
if
ied
to
m
ee
t
th
e
tech
n
o
l
o
g
ical
ac
ce
p
tan
ce
o
f
th
e
GA
D
a
pp
s
ettin
g
o
f
th
is
s
tu
d
y
b
ased
o
n
f
ac
to
r
s
th
at
wer
e
v
alid
ated
in
Da
v
is
[
7
]
,
[
2
5
]
.
T
h
e
co
llected
o
r
d
in
al
d
at
a
wer
e
u
s
ed
f
o
r
th
e
e
x
p
er
im
e
n
t.
A
5
-
p
o
in
t
L
ik
e
r
t
s
ca
le,
r
an
g
in
g
f
r
o
m
"stro
n
g
l
y
ag
r
ee
"
to
"stro
n
g
ly
d
is
ag
r
ee
,
"
was
u
s
ed
to
ass
ess
ea
ch
q
u
est
io
n
n
air
e
item
.
T
h
e
f
o
llo
win
g
ar
e
th
e
r
esear
ch
v
ar
i
ab
les u
s
ed
in
th
e
s
tu
d
y
s
h
o
wn
in
T
ab
le
1
.
Fig
u
r
e
1
.
A
n
ew
ac
ce
p
tan
ce
m
o
d
el
f
o
r
th
e
GAD
a
pp
a
d
o
p
te
d
f
r
o
m
T
AM
a
n
d
SC
T
,
with
m
o
d
er
atin
g
v
a
r
iab
les
T
ab
le
1
.
L
is
t o
f
v
ar
iab
les
V
a
r
i
a
b
l
e
I
t
e
ms
P
e
r
c
e
i
v
e
d
u
s
e
f
u
l
n
e
ss (P
U
)
P
e
r
c
e
i
v
e
d
e
a
s
e
o
f
U
se
(
P
E
U
)
B
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
(
B
I
)
A
c
t
u
a
l
sy
s
t
e
m
u
s
e
(ASU)
S
p
e
c
i
f
i
c
-
a
n
x
i
e
t
y
(
S
A
)
S
e
l
f
-
e
f
f
i
c
a
c
y
(
S
E)
4
4
4
4
4
4
T
h
e
s
tu
d
y
'
s
h
y
p
o
th
eses
wer
e
d
ev
elo
p
e
d
u
tili
zin
g
th
e
T
A
M
m
o
d
el
as
a
f
o
u
n
d
atio
n
an
d
th
e
SC
T
m
o
d
el
to
ac
c
o
u
n
t f
o
r
e
x
ter
n
al
f
ac
to
r
s
.
H1
:
SE
h
as a
p
o
s
itiv
e
in
f
lu
e
n
c
e
o
n
P
E
U
o
f
t
h
e
GAD
a
pp
.
T
h
e
GAD
a
pp
SE
in
th
is
s
tu
d
y
is
ch
ar
ac
ter
ized
as
th
e
in
d
iv
i
d
u
al'
s
co
n
f
id
en
ce
in
u
tili
zin
g
t
h
is
m
o
b
ile
ap
p
licatio
n
.
T
h
e
s
u
r
v
ey
q
u
esti
o
n
s
f
o
r
th
is
d
im
en
s
io
n
will
s
ee
k
to
d
eter
m
in
e
h
o
w
r
esp
o
n
d
e
n
ts
f
ee
l
ab
o
u
t
th
eir
lev
el
o
f
ap
p
lic
atio
n
-
u
s
in
g
t
h
ei
r
p
r
o
f
icien
cy
.
H2
:
SA
h
as a
n
eg
ativ
e
in
f
l
u
en
ce
o
n
th
e
PU
o
f
th
e
GAD
a
pp
.
H3
:
SA
h
as a
n
eg
ativ
e
in
f
l
u
en
ce
o
n
th
e
P
E
U
o
f
th
e
GAD
a
pp
.
T
h
e
co
n
s
tan
t
u
s
e
o
f
tech
n
o
lo
g
y
ca
n
h
a
v
e
ad
v
er
s
e
ef
f
ec
ts
,
s
o
m
e
o
f
wh
ich
i
n
clu
d
e
s
tr
o
n
g
,
n
e
g
ativ
e
em
o
tio
n
al
s
tates.
So
m
e
s
tu
d
ie
s
d
ef
in
e
SA
as
a
m
en
tal
co
n
d
itio
n
ch
ar
ac
ter
ized
b
y
f
ee
lin
g
s
o
f
f
ea
r
o
r
u
n
ea
s
e
wh
en
u
s
in
g
o
r
t
h
in
k
in
g
ab
o
u
t
th
e
s
y
s
tem
[
7
]
.
T
h
is
s
tu
d
y
d
ef
i
n
es
SA
as
an
in
d
iv
id
u
al'
s
r
elat
io
n
s
h
ip
with
u
s
in
g
th
e
GAD
ap
p
,
en
co
m
p
ass
in
g
an
y
ass
o
ciate
d
em
o
tio
n
o
r
ten
d
en
cy
th
at
th
ey
ad
o
p
t
d
u
r
in
g
th
eir
ch
ild
h
o
o
d
[
2
6
]
o
r
in
a
s
elf
-
a
d
m
in
is
ter
ed
c
u
r
r
en
t
s
itu
atio
n
[
2
7
]
,
[
2
8
]
.
T
h
e
s
u
r
v
ey
q
u
esti
o
n
s
f
o
r
t
h
is
d
im
en
s
io
n
will
tr
y
to
d
eter
m
in
e
h
o
w
co
m
f
o
r
tab
le
o
r
ex
p
er
ien
ce
d
r
esp
o
n
d
en
ts
ar
e
with
th
e
ap
p
licatio
n
.
H4
:
P
E
U
h
as a
p
o
s
itiv
e
in
f
lu
e
n
ce
o
n
BI
to
war
d
u
s
in
g
t
h
e
G
AD
a
pp
.
H5
:
PU
h
as a
p
o
s
itiv
e
in
f
lu
en
c
e
o
n
BI
to
war
d
u
s
in
g
th
e
GAD
a
pp
.
H6
:
P
E
U
h
as a
p
o
s
itiv
e
in
f
lu
e
n
ce
o
n
PU
.
H7
:
BI
to
war
d
s
u
s
in
g
th
e
GA
D
a
pp
h
as a
p
o
s
itiv
e
in
f
lu
en
ce
o
n
ac
tu
al
s
y
s
tem
u
s
e
o
f
GAD
a
pp
.
T
h
e
f
o
r
m
u
lated
eq
u
atio
n
with
H7
to
th
e
m
o
d
er
atin
g
v
ar
iab
le
u
s
in
g
a
d
ata
-
d
r
i
v
en
m
o
d
el
f
o
r
tech
n
o
lo
g
y
ac
ce
p
ta
n
ce
is
s
h
o
wn
b
el
s
o
w.
T
r
ain
i
n
g
a
n
SV
M
r
eq
u
ir
es
a
s
et
o
f
n
ex
a
m
p
les.
Fo
r
r
ea
s
o
n
s
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
User
a
cc
ep
ta
n
ce
o
f th
e
GA
D
mo
b
ile
a
p
p
w
ith
a
r
a
tin
g
ch
ec
klis
t u
s
in
g
a
mo
d
ified
…
(
R
o
s
s
ia
n
V
.
P
erea
)
3909
v
is
u
aliza
tio
n
,
it
will
co
n
s
id
er
th
e
ca
s
e
o
f
a
two
-
d
im
en
s
io
n
al
in
p
u
t,
t
h
e
x
∈
R
^2
th
at
r
ep
r
es
en
ts
B
I
an
d
C
SU.
E
ac
h
s
am
p
le
c
o
n
s
is
ts
o
f
a
p
air
,
an
i
n
p
u
t
v
ec
to
r
xi
,
a
n
d
th
e
as
s
o
ciate
d
lab
el
yi
.
Ass
u
m
e
t
h
at
a
tr
ain
in
g
s
et
X
is
g
iv
en
as
,
(
1
,
)
,
(
2
,
2
)
⋯
(
,
)
wh
er
e
1
∈
1
∈
(
+
1
,
−
1
)
(
1
)
2
.
2
.
O
rig
ina
l
f
a
ct
o
rs
us
ed
in
t
he
T
AM
m
o
del
PU
is
th
e
d
eg
r
ee
to
wh
ich
a
p
r
o
s
p
ec
tiv
e
u
s
er
th
in
k
s
u
s
in
g
th
e
GAD
a
pp
wo
u
ld
in
cr
ea
s
e
th
eir
p
r
o
d
u
ctiv
ity
[
2
9
]
.
P
E
U
is
an
elem
en
t
o
f
PU
.
T
h
e
r
atio
n
ale
is
th
at,
u
n
d
er
n
o
r
m
al
ci
r
cu
m
s
tan
ce
s
,
co
n
s
u
m
er
s
f
in
d
a
s
y
s
tem
m
o
r
e
b
en
e
f
icial
wh
en
it
r
eq
u
ir
es
less
wo
r
k
.
T
h
is
f
ac
to
r
is
also
ca
lled
ef
f
o
r
t
ex
p
ec
tan
cy
b
ec
a
u
s
e
th
e
u
s
er
lear
n
s
h
o
w
t
o
u
s
e
th
e
GAD
ap
p
m
o
r
e
ea
s
ily
th
a
n
b
e
f
o
r
e
[
7
]
.
T
h
e
m
o
tiv
atio
n
al
ele
m
en
ts
th
at
im
p
ac
t
a
p
ar
ticu
lar
ac
tiv
ity
a
r
e
r
ef
e
r
r
ed
to
as
B
I
,
an
d
th
e
m
o
r
e
s
tr
o
n
g
l
y
o
n
e
in
ten
d
s
to
ca
r
r
y
o
u
t
th
e
b
eh
av
io
r
,
th
e
m
o
r
e
p
r
o
b
a
b
le
it
is
to
b
e
ca
r
r
ied
o
u
t
u
p
o
n
th
e
r
ea
l
u
s
e
o
f
t
h
e
GAD
a
pp
wh
ich
is
g
r
ea
tly
in
f
lu
en
c
ed
b
y
t
h
e
BI
to
u
s
e
th
em
f
o
r
i
n
f
o
r
m
atio
n
p
r
o
v
is
i
o
n
[
5
]
,
[
1
4
]
,
[
3
0
]
.
T
h
e
c
u
r
r
e
n
t
im
p
lem
en
tatio
n
o
f
th
e
n
e
w
tech
n
o
lo
g
y
th
at
s
u
p
p
o
r
ts
th
e
cr
ea
tio
n
o
f
th
e
G
AD
a
pp
is
k
n
o
wn
as th
e
ac
tu
al
s
y
s
tem
u
s
ed
(
ASU)
.
T
h
e
s
p
ec
if
ic
SE
an
d
SA th
at
ar
e
s
elec
ted
f
o
r
th
is
s
tu
d
y
ap
p
ly
to
SC
T
s
am
o
n
g
th
e
f
o
u
r
ele
m
en
ts
o
f
th
e
SC
T
p
ar
ad
ig
m
.
T
h
e
s
tu
d
y
'
s
p
r
im
ar
y
o
b
jectiv
e
is
to
f
ac
ilit
ate
th
e
ex
p
an
s
io
n
o
f
th
e
s
u
g
g
ested
f
r
am
ewo
r
k
to
in
c
o
r
p
o
r
ate
th
e
ad
o
p
tio
n
an
d
u
tili
za
tio
n
o
f
th
e
GAD
a
pp
.
T
h
er
ef
o
r
e,
i
n
ac
co
r
d
a
n
ce
with
th
e
p
r
ev
i
o
u
s
im
p
lem
en
tatio
n
o
f
T
AM
in
th
e
wo
r
k
in
g
s
ce
n
ar
i
o
s
ettin
g
,
th
e
o
u
tco
m
e
ex
p
ec
tati
o
n
s
an
d
af
f
ec
t c
o
m
p
o
n
e
n
ts
f
r
o
m
SC
T
wer
e
r
em
o
v
ed
.
2
.
3
.
Da
t
a
-
driv
en
m
o
del f
o
r
t
ec
hn
o
lo
g
y
a
cc
ept
a
nce
T
o
ex
p
er
im
e
n
tally
f
o
r
ec
ast
en
d
u
s
er
s
'
ad
o
p
tio
n
o
f
th
e
GAD
a
pp
,
th
is
r
esear
ch
d
ev
elo
p
s
a
n
o
v
el
d
ata
-
d
r
iv
en
m
eth
o
d
o
lo
g
y
th
at
m
a
k
es
u
s
e
o
f
ML
an
d
p
r
e
d
ictiv
e
a
n
aly
tics
-
b
ased
m
o
d
elin
g
.
Fu
r
t
h
er
m
o
r
e
,
p
r
ed
ictiv
e
an
aly
tics
h
as
s
ev
er
al
b
en
ef
its
,
in
clu
d
in
g
th
e
a
b
ilit
y
to
ex
am
i
n
e
an
d
co
n
f
ir
m
h
y
p
o
th
eses
,
as
well
as
ass
ess
th
eir
ap
p
licab
ilit
y
an
d
p
r
ed
icted
ac
cu
r
ac
y
.
Mo
r
e
s
ig
n
if
ican
tly
,
p
r
ed
ictiv
e
an
aly
tics
m
ay
b
r
id
g
e
th
e
g
ap
b
etwe
en
th
eo
r
y
a
n
d
r
ea
lity
b
ec
au
s
e
it
i
s
a
d
ata
-
d
r
iv
e
n
m
eth
o
d
o
lo
g
y
[
3
1
]
.
T
h
r
o
u
g
h
SVM,
p
ar
tial
t
r
ain
in
g
a
n
d
test
in
g
wer
e
p
r
esen
ted
to
o
p
tim
ize
th
e
ex
p
ec
ted
s
o
lu
tio
n
th
r
o
u
g
h
th
e
ac
cu
r
ac
y
o
f
u
s
in
g
th
e
m
o
d
er
atin
g
v
ar
iab
les.
Var
io
u
s
test
s
h
av
e
b
ee
n
co
n
d
u
cted
to
p
er
f
o
r
m
r
eg
r
ess
io
n
an
a
ly
s
is
with
d
ata
-
d
r
iv
en
ap
p
licatio
n
s.
2
.
4
.
P
a
rt
icipa
nts’
dem
o
g
r
a
ph
ics a
nd
da
t
a
co
llect
io
n
T
h
is
s
tu
d
y
was
s
u
b
jecte
d
t
o
in
s
p
ec
t
th
e
u
s
e
in
ten
tio
n
o
f
th
e
GAD
a
pp
b
ased
o
n
th
e
m
o
d
if
i
ed
m
o
d
el.
T
h
is
s
tu
d
y
ap
p
lies
r
an
d
o
m
s
am
p
lin
g
to
th
e
s
elec
tio
n
o
f
th
e
p
ar
ticip
an
ts
.
T
ab
le
2
s
h
o
ws
th
e
n
u
m
b
er
o
f
p
ar
ticip
an
ts
b
ased
o
n
ag
e
r
an
g
e,
s
ex
,
h
ig
h
est
ed
u
ca
tio
n
al
attain
m
en
t
(
HE
A
)
,
an
d
k
n
o
wle
d
g
e
lev
el
o
n
GAD
n
ee
d
ed
to
ass
ess
th
e
GAD
a
pp
th
r
o
u
g
h
a
s
u
r
v
ey
in
s
tr
u
m
en
t v
ia
Go
o
g
le
Fo
r
m
s
.
T
h
is
s
tu
d
y
in
v
o
l
v
es
p
ar
ticip
an
ts
with
ex
p
er
ien
ce
i
n
u
s
in
g
m
o
b
ile
ap
p
licatio
n
s
in
a
n
y
r
elate
d
ac
tiv
ities
,
with
d
if
f
er
en
t
r
o
les
in
th
e
o
r
g
a
n
izatio
n
,
an
d
with
k
n
o
wled
g
e
o
f
GAD
im
p
lem
e
n
tatio
n
.
T
h
e
d
ataset
co
llected
was
u
s
ed
in
d
ata
an
aly
s
is
.
T
h
e
Ph
ilip
p
in
e
L
aw
o
n
Data
Priv
ac
y
Act
o
f
2
0
1
2
was
d
is
cu
s
s
ed
with
th
e
p
ar
ticip
an
ts
b
ef
o
r
e
th
ey
co
n
s
en
ted
to
an
s
wer
in
g
th
e
s
u
r
v
ey
q
u
esti
o
n
n
air
e
with
d
ata
co
llectio
n
co
n
s
en
t
af
ter
u
s
in
g
th
e
GAD
a
pp.
T
ab
le
2
.
C
ateg
o
r
ies o
f
p
ar
ticip
an
ts
(
N=
1
0
0
)
P
a
r
t
i
c
i
p
a
n
t
s
F
r
e
q
u
e
n
c
y
GAD
c
o
o
r
d
i
n
a
t
o
r
s a
n
d
a
l
t
e
r
n
a
t
e
Te
c
h
n
i
c
a
l
e
x
p
e
r
t
s
GAD
a
d
v
o
c
a
t
e
s
i
n
LG
U
,
D
e
p
Ed
,
D
o
H
U
n
i
v
e
r
si
t
y
e
m
p
l
o
y
e
e
s
S
t
u
d
e
n
t
/
f
a
c
u
l
t
y
r
e
s
e
a
r
c
h
e
r
s
10
5
50
10
25
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
co
n
tain
s
th
e
s
u
m
m
ar
y
o
f
th
e
r
esu
lts
o
f
all
s
tati
s
tical
an
aly
s
es,
th
e
d
em
o
g
r
ap
h
ics
p
r
o
f
ile
o
f
th
e
p
ar
ticip
an
ts
,
a
n
d
d
ata
an
aly
s
is
co
n
d
u
cted
to
h
av
e
d
ata
-
d
r
iv
en
m
o
d
elin
g
b
ased
o
n
th
e
m
eth
o
d
o
lo
g
ies
an
d
aim
s
.
T
h
e
s
elec
tio
n
o
f
h
y
p
o
th
eses
was
p
r
e
d
icate
d
o
n
ch
ar
ac
ter
is
tics
,
cir
cu
m
s
tan
ce
s
,
is
s
u
es,
an
d
o
th
er
elem
en
ts
th
at
wer
e
d
is
co
v
er
ed
in
th
e
liter
atu
r
e
to
b
e
p
er
tin
e
n
t
to
th
e
an
aly
s
is
o
f
th
e
elem
en
ts
in
f
lu
en
cin
g
th
e
u
s
er
ac
ce
p
tab
ilit
y
o
f
t
h
e
GAD
a
pp
in
th
e
f
u
tu
r
e.
3
.
1
.
De
m
o
g
r
a
ph
ic
pro
f
ile
his
t
o
ry
T
h
e
d
em
o
g
r
ap
h
ic
s
u
m
m
ar
y
o
f
th
e
p
ar
ticip
a
n
ts
(
N=
1
0
0
)
o
f
th
e
s
tu
d
y
p
r
esen
ts
th
e
u
s
er
’
s
k
n
o
wled
g
e
o
f
GAD
b
y
s
ex
,
ag
e
r
an
g
e,
a
n
d
HE
A
s
h
o
wn
in
Fig
u
r
e
2
.
T
h
e
to
tal
o
f
p
ar
ticip
a
n
ts
was
ass
es
s
ed
b
y
ag
e
an
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
9
0
6
-
3
9
1
4
3910
s
ex
,
th
e
co
u
n
t
o
f
f
em
ales
(
n
=2
7
)
an
d
m
ales
(
n
=
1
2
)
wer
e
a
d
v
an
ce
d
b
eg
i
n
n
er
s
(
n
=
3
9
)
,
a
n
d
f
em
ales
(
n
=3
6
)
an
d
m
ales
(
n
=1
1
)
wer
e
at
th
e
p
r
o
f
icien
t
lev
el
(
n
=4
7
)
r
esp
ec
tiv
ely
,
with
m
ajo
r
ity
ag
e
r
an
g
e
to
1
8
to
3
9
o
r
y
o
u
n
g
ad
u
lts
.
T
h
e
HE
A
s
h
o
ws
th
a
t
th
e
ter
tiar
y
d
e
g
r
ee
/with
u
n
its
(
n
=4
7
)
a
p
p
ea
r
m
o
s
t
o
f
t
en
,
as
a
m
aster
’
s
d
eg
r
ee
/with
u
n
its
(
n
=
2
0
)
,
an
d
d
o
cto
r
al
d
e
g
r
ee
/with
u
n
its
(
n
=
1
8
)
r
esp
ec
tiv
ely
.
Fig
u
r
e
2
.
Dem
o
g
r
ap
h
ic
p
r
o
f
ile
b
y
m
o
d
er
atin
g
v
ar
iab
les
3
.
2
.
St
a
t
is
t
ics a
nd
a
na
ly
s
es
T
h
e
an
aly
s
is
to
o
l
is
v
er
y
im
p
o
r
tan
t
to
in
c
o
r
p
o
r
ate
in
to
th
e
r
esear
ch
m
eth
o
d
to
m
ea
s
u
r
e
a
n
d
g
iv
e
a
f
ac
tu
al
in
ter
p
r
etatio
n
o
f
ea
c
h
r
esu
lt
o
f
test
in
g
a
n
d
tr
ain
in
g
p
r
o
ce
d
u
r
es o
n
t
h
e
p
r
e
-
p
r
o
ce
s
s
ed
d
ataset.
T
h
e
o
p
e
n
-
s
o
u
r
ce
an
d
u
s
er
-
f
r
ien
d
ly
s
tatis
tical
s
o
f
twar
e
ca
lled
J
ASP
h
a
s
b
ee
n
u
s
ed
in
d
ata
m
o
d
elin
g
.
T
h
e
f
in
d
in
g
s
o
f
all
s
tatis
t
ics
an
d
an
aly
s
es
b
ased
o
n
th
e
s
tu
d
y
'
s
m
eth
o
d
o
lo
g
y
a
n
d
o
b
jectiv
es
ar
e
co
v
e
r
ed
in
t
h
is
p
ar
t.
T
h
e
r
esu
lts
o
f
th
e
s
tu
d
y
ar
e
i
n
ter
p
r
eted
u
s
in
g
a
v
ar
iety
o
f
s
tatis
tics
,
in
cl
u
d
in
g
d
escr
ip
ti
v
e
s
tatis
tic
s
,
r
eliab
ilit
y
co
n
s
tr
u
cts,
co
r
r
elatio
n
m
atr
ices,
a
n
d
an
al
y
s
is
o
f
th
e
g
iv
en
h
y
p
o
th
eses
.
3
.
2
.
1
.
F
re
qu
ent
is
t
s
ca
le
re
lia
bil
it
y
s
t
a
t
is
t
ics
Dev
elo
p
ed
b
y
L
ee
C
r
o
n
b
ac
h
in
1
9
5
1
,
C
r
o
n
b
ac
h
'
s
alp
h
a,
o
f
t
en
k
n
o
wn
as
co
ef
f
icie
n
t
alp
h
a
o
r
α
,
is
a
m
ea
s
u
r
e
o
f
in
ter
n
al
co
n
s
is
ten
cy
o
r
r
eliab
ilit
y
.
T
h
e
ab
ilit
y
o
f
a
test
o
r
s
u
r
v
ey
to
m
ea
s
u
r
e
w
h
at
it
is
in
ten
d
ed
to
ev
alu
ate
is
k
n
o
wn
as
in
ter
n
al
co
n
s
is
ten
cy
r
eliab
ilit
y
[
3
2
]
,
[
3
3
]
.
A
r
eliab
ilit
y
test
o
r
in
ter
n
a
l
ac
cu
r
ac
y
ch
ec
k
er
is
u
s
ed
to
d
eter
m
in
e
th
e
ac
c
u
r
ac
y
o
f
L
ik
er
t
m
u
lti
-
q
u
esti
o
n
s
u
r
v
ey
s
.
T
ab
le
3
d
is
p
lay
s
th
e
r
esu
lts
,
wh
ich
d
em
o
n
s
tr
ate
t
h
at
th
e
B
I
,
AS
U,
SA,
an
d
SE
h
ad
α
≥
0
.
9
,
in
d
icatin
g
e
x
ce
llen
t
q
u
esti
o
n
n
air
e
co
n
s
is
ten
cy
,
wh
er
ea
s
th
e
r
em
ain
in
g
item
s
PU a
n
d
P
E
U
h
ad
less
th
an
0
.
9
>
α
≥
0
.
8
,
s
h
o
win
g
g
o
o
d
co
n
s
tr
u
c
t c
o
n
s
is
ten
cy
.
T
ab
le
3
.
R
eliab
ilit
y
c
o
n
s
tr
u
ct
V
a
r
i
a
b
l
e
C
r
o
n
b
a
c
h
's α
I
t
e
ms
PU
0
.
8
5
4
P
E
U
0
.
8
6
1
4
BI
0
.
9
3
5
4
A
S
U
0
.
9
1
4
4
SA
0
.
9
1
6
4
SE
0
.
9
5
4
4
3
.
2
.
2
.
Descript
iv
e
s
t
a
t
is
t
ics
T
h
e
f
ac
to
r
s
u
tili
ze
d
t
o
in
ter
p
r
et
th
e
s
tu
d
y
'
s
f
in
d
in
g
s
ar
e
s
h
o
wn
in
T
ab
le
4
as
d
escr
ip
tiv
e
s
tatis
tic
s
.
T
h
e
2
4
-
item
q
u
esti
o
n
s
h
av
e
a
m
in
im
u
m
v
alu
e
o
f
1
,
wh
ich
in
d
icate
s
s
tr
o
n
g
ly
d
is
ag
r
e
e
r
em
ar
k
s
,
f
o
r
th
e
Per
ce
iv
ed
ea
s
e3
,
Per
ce
iv
ed
ea
s
e4
,
B
eh
av
io
r
aln
ten
t1
,
B
eh
av
i
o
r
alI
n
ten
t
3
,
B
eh
av
io
r
alI
n
te
n
t
4
,
a
n
d
Sp
ec
i
f
ic
-
an
x
iety
1
item
s
o
n
t
h
e
lis
t
.
T
h
ese
item
s
also
h
av
e
a
m
ax
im
u
m
v
alu
e
o
f
5
,
i
n
d
icatin
g
s
tr
o
n
g
ly
ag
r
ee
r
em
a
r
k
s
,
with
n
o
m
is
s
in
g
v
alu
es.
0
10
20
30
40
Novi
c
e
Adva
n
c
e
d
B
e
ginn
e
r
P
r
of
i
c
ient
E
xpe
r
t
Nu
m
be
r
of
pa
r
ti
c
i
pa
n
ts
K
n
owl
e
dg
e
l
e
v
e
l
i
n
GA
D
'A
g
e
R
a
n
g
e
'
b
y
'K
n
o
w
l
e
d
g
e
L
e
v
e
l
i
n
G
A
D
'
a
n
d
'S
e
x
'
ma
l
e
f
e
ma
l
e
0
20
40
60
Te
r
t
i
a
r
y
…
M
ast
er
s…
D
o
c
t
o
r
a
l
…
S
e
c
o
n
d
a
r
y
…
P
o
st
-
d
o
c
t
o
r
a
t
e
…
Te
r
t
i
a
r
y
…
S
e
c
o
n
d
a
r
y
…
P
r
i
ma
r
y
…
A
g
e
r
a
n
g
e
H
i
g
h
e
s
t
e
du
c
a
ti
on
a
l
a
tt
a
i
n
m
e
nt
'H
i
g
h
e
st
Ed
u
c
a
t
i
o
n
a
l
A
t
t
a
i
n
me
n
t
':
T
e
r
t
i
a
r
y
(
d
e
g
r
e
e
/
w
i
t
h
u
n
i
t
s)
a
p
p
e
a
r
s
mo
st
o
f
t
e
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
User
a
cc
ep
ta
n
ce
o
f th
e
GA
D
mo
b
ile
a
p
p
w
ith
a
r
a
tin
g
ch
ec
klis
t u
s
in
g
a
mo
d
ified
…
(
R
o
s
s
ia
n
V
.
P
erea
)
3911
T
ab
le
4
.
Descr
ip
tiv
e
s
tatis
tics
V
a
l
i
d
M
i
ss
i
n
g
M
e
a
n
S
t
d
.
D
e
v
i
a
t
i
o
n
M
I
N
M
A
X
P
e
r
c
e
i
v
e
d
u
se
1
1
0
0
0
4
.
7
3
0
.
4
6
8
3
5
P
e
r
c
e
i
v
e
d
u
se
2
1
0
0
0
4
.
8
0
.
4
2
6
3
5
P
e
r
c
e
i
v
e
d
u
se
3
1
0
0
0
4
.
7
3
0
.
4
6
8
3
5
P
e
r
c
e
i
v
e
d
u
se
4
1
0
0
0
4
.
6
9
0
.
5
2
6
2
5
P
e
r
c
e
i
v
e
d
e
a
se
1
1
0
0
0
4
.
5
7
0
.
5
9
3
5
P
e
r
c
e
i
v
e
d
e
a
se
2
1
0
0
0
4
.
5
8
0
.
6
0
6
3
5
P
e
r
c
e
i
v
e
d
e
a
se
3
1
0
0
0
4
.
5
5
0
.
7
0
2
1
5
P
e
r
c
e
i
v
e
d
e
a
se
4
1
0
0
0
4
.
6
1
0
.
7
3
7
1
5
B
e
h
a
v
i
o
r
a
l
I
n
t
e
n
t
1
1
0
0
0
4
.
5
3
0
.
7
5
8
1
5
B
e
h
a
v
i
o
r
a
l
I
n
t
e
n
t
2
1
0
0
0
4
.
6
1
0
.
6
8
2
5
B
e
h
a
v
i
o
r
a
l
I
n
t
e
n
t
3
1
0
0
0
4
.
5
7
0
.
7
5
6
1
5
B
e
h
a
v
i
o
r
a
l
I
n
t
e
n
t
4
1
0
0
0
4
.
6
5
0
.
7
4
4
1
5
A
c
t
u
a
l
U
s
a
g
e
1
1
0
0
0
4
.
5
3
0
.
7
1
7
2
5
A
c
t
u
a
l
U
s
a
g
e
2
1
0
0
0
4
.
6
6
0
.
6
0
7
2
5
A
c
t
u
a
l
U
s
a
g
e
3
1
0
0
0
4
.
5
9
0
.
6
3
7
2
5
A
c
t
u
a
l
U
s
a
g
e
4
1
0
0
0
4
.
5
8
0
.
6
8
4
2
5
S
p
e
c
i
f
i
c
-
a
n
x
i
e
t
y
1
1
0
0
0
4
.
5
7
0
.
6
5
5
1
5
S
p
e
c
i
f
i
c
-
a
n
x
i
e
t
y
2
1
0
0
0
4
.
5
1
0
.
6
4
3
2
5
S
p
e
c
i
f
i
c
-
a
n
x
i
e
t
y
3
1
0
0
0
4
.
4
3
0
.
6
5
5
2
5
S
p
e
c
i
f
i
c
-
a
n
x
i
e
t
y
4
1
0
0
0
4
.
5
3
0
.
6
7
4
2
5
S
e
l
f
-
e
f
f
i
c
a
c
y
1
1
0
0
0
4
.
5
9
0
.
6
3
7
2
5
S
e
l
f
-
e
f
f
i
c
a
c
y
2
1
0
0
0
4
.
6
1
0
.
6
8
2
5
S
e
l
f
-
e
f
f
i
c
a
c
y
3
1
0
0
0
4
.
6
2
0
.
6
7
8
2
5
S
e
l
f
-
e
f
f
i
c
a
c
y
4
1
0
0
0
4
.
6
2
0
.
6
7
8
2
5
3
.
2
.
3
.
Co
rr
ela
t
io
n
a
na
ly
s
is
C
o
m
p
ar
ed
with
o
th
er
p
ap
er
s
,
th
e
p
o
s
itiv
e
an
d
n
eg
ativ
e
d
ata
ar
e
class
if
ied
as
v
ali
d
,
an
d
th
e
co
r
r
elatio
n
o
f
all
r
elate
d
v
ar
ia
b
les
id
en
tifie
d
th
e
s
ig
n
if
ican
t
r
elatio
n
s
h
ip
s
b
etwe
en
all
o
f
th
e
co
n
s
tr
u
cts.
Sin
ce
th
e
p
-
v
alu
e
o
f
0
.
0
0
1
is
b
elo
w
th
e
s
ig
n
if
ican
ce
lev
el
(
p
<0
.
0
1
)
,
th
e
s
tu
d
y
co
n
clu
d
ed
th
at
all
in
d
icato
r
s
,
in
clu
d
in
g
PU,
P
E
U
,
B
I
,
AS
U,
SA,
an
d
SE,
co
r
r
elate
an
d
h
av
e
a
s
ig
n
if
ican
t
co
r
r
elatio
n
.
I
t
s
h
o
ws
th
at
ea
ch
o
f
th
e
cr
iter
ia
h
as
a
clo
s
e
r
elatio
n
s
h
ip
with
t
h
e
o
th
er
.
Ad
d
itio
n
ally
,
T
a
b
le
5
d
is
p
lay
s
t
h
e
c
o
r
r
elatio
n
a
n
aly
s
is
o
f
th
e
h
y
p
o
t
h
esis
b
ased
o
n
th
e
ap
p
lied
m
o
d
el.
T
o
f
o
r
ec
ast
th
e
lin
k
b
etwe
en
th
e
s
p
ec
if
ied
v
ar
iab
les,
a
m
u
ltip
le
r
eg
r
ess
io
n
an
aly
s
i
s
was
co
n
d
u
cted
.
F(
6
,
9
5
)
=p
<
0
0
0
5
w
as
s
tatis
tically
s
u
b
s
tan
tially
p
r
ed
icted
b
y
t
h
ese
v
ar
iab
les.
I
t said
th
at
a
p
-
v
alu
e
o
f
.
0
0
1
s
u
p
p
o
r
ted
th
e
eq
u
iv
ale
n
t in
ter
p
r
etatio
n
o
f
ea
c
h
h
y
p
o
t
h
esis
.
T
ab
le
5
.
C
o
r
r
elatio
n
an
aly
s
is
o
f
th
e
h
y
p
o
t
h
eses
H
y
p
o
t
h
e
s
e
s
a
n
d
s
t
a
t
e
m
e
n
t
P
a
t
h
P
e
a
r
so
n
r
C
o
r
r
e
l
a
t
i
o
n
P
-
v
a
l
u
e
R
e
s
u
l
t
H
1
:
S
e
l
f
-
e
f
f
i
c
a
c
y
h
a
s
a
p
o
s
i
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
t
h
e
p
e
r
c
e
i
v
e
d
e
a
s
e
o
f
u
s
e
o
f
G
A
D
a
pp
SE
→
P
EU
0
.
7
4
6
.
0
0
1
S
u
p
p
o
r
t
e
d
H
2
:
S
p
e
c
i
f
i
c
a
n
x
i
e
t
y
h
a
s
a
n
e
g
a
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
t
h
e
p
e
r
c
e
i
v
e
d
u
sef
u
l
n
e
ss
o
f
t
h
e
G
A
D
a
pp
SA
→
PU
0
.
7
0
9
.
0
0
1
S
u
p
p
o
r
t
e
d
H
3
:
S
p
e
c
i
f
i
c
a
n
x
i
e
t
y
h
a
s
a
n
e
g
a
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
t
h
e
p
e
r
c
e
i
v
e
d
e
a
s
e
o
f
u
s
e
o
f
t
h
e
G
A
D
a
pp
SA
→
P
EU
0
.
5
0
8
.
0
0
1
S
u
p
p
o
r
t
e
d
H
4
:
P
e
r
c
e
i
v
e
d
e
a
se
o
f
u
se
h
a
s
a
p
o
si
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
t
o
w
a
r
d
s
u
s
i
n
g
t
h
e
G
A
D
a
pp
P
EU
→
BI
0
.
7
3
3
.
0
0
1
S
u
p
p
o
r
t
e
d
H
5
:
P
e
r
c
e
i
v
e
d
u
sef
u
l
n
e
ss
h
a
s
a
p
o
s
i
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
t
o
w
a
r
d
s
u
s
i
n
g
t
h
e
G
A
D
a
pp
PU
→
BI
0
.
7
8
5
.
0
0
1
S
u
p
p
o
r
t
e
d
H
6
:
P
e
r
c
e
i
v
e
d
e
a
se
o
f
u
se
h
a
s
a
p
o
si
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
p
e
r
c
e
i
v
e
d
u
sef
u
l
n
e
ss
.
P
EU
→
PU
0
.
8
1
2
.
0
0
1
S
u
p
p
o
r
t
e
d
H
7
:
B
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
t
o
w
a
r
d
s
u
si
n
g
t
h
e
G
A
D
a
pp
h
a
s
a
p
o
s
i
t
i
v
e
i
n
f
l
u
e
n
c
e
o
n
a
c
t
u
a
l
s
y
s
t
e
m
u
s
e
o
f
t
h
e
G
A
D
a
pp
BI
→
A
S
U
0
.
6
7
8
.
0
0
1
S
u
p
p
o
r
t
e
d
3
.
3
.
Da
t
a
-
driv
en
m
o
del us
in
g
SVM
Af
ter
d
ata
p
r
ep
r
o
ce
s
s
in
g
an
d
ac
ce
s
s
in
g
co
r
r
elatio
n
an
aly
s
es,
th
e
n
ex
t
s
tep
is
to
ex
p
er
im
en
t
u
s
in
g
th
e
SVM
alg
o
r
ith
m
with
o
u
t
o
p
tim
izatio
n
b
y
u
tili
zin
g
th
e
v
alid
at
io
n
m
eth
o
d
to
s
ep
ar
ate
th
e
d
at
a
in
to
tr
ain
in
g
an
d
test
in
g
s
ets
[
3
4
]
.
T
h
is
will
g
iv
e
a
p
r
ed
icted
v
alu
e
o
n
th
e
c
o
n
clu
d
ed
d
ataset
af
f
ec
tin
g
B
I
an
d
ASU
v
ar
iab
les
b
y
in
co
r
p
o
r
atin
g
th
e
m
o
d
er
atin
g
v
ar
iab
les.
T
h
is
s
tu
d
y
ex
am
in
e
s
h
o
w
p
r
ed
ictiv
e
an
aly
tics
m
i
g
h
t
im
p
r
o
v
e
T
AM
b
y
r
ev
iewin
g
ex
is
tin
g
f
r
am
e
wo
r
k
s
,
in
tr
o
d
u
cin
g
n
ew
ele
m
en
ts
,
an
d
ass
ess
in
g
p
r
ed
ic
tiv
e
p
o
wer
,
wh
ic
h
ass
es
s
ed
th
e
SVM
class
if
icati
o
n
s
o
f
m
o
d
er
atin
g
v
a
r
iab
les
u
s
ed
in
T
ab
le
6
.
I
n
o
r
d
e
r
to
im
p
r
o
v
e
th
e
SVM
alg
o
r
ith
m
'
s
ca
p
ac
ity
f
o
r
g
en
e
r
aliza
tio
n
,
its
g
o
al
is
to
en
h
an
ce
th
e
m
ar
g
in
b
etwe
en
th
e
h
y
p
er
p
lan
e
an
d
th
e
clo
s
est d
ata
p
o
in
ts
.
W
e
r
ef
er
t
o
th
ese
s
ites
as su
p
p
o
r
t v
ec
to
r
s
[
3
5
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
9
0
6
-
3
9
1
4
3912
T
ab
le
6
.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
class
if
icatio
n
M
o
d
e
r
a
t
i
n
g
v
a
r
i
a
b
l
e
S
u
p
p
o
r
t
v
e
c
t
o
r
s
n
(
Tr
a
i
n
)
n
(
Te
s
t
)
Te
st
a
c
c
u
r
a
c
y
(
%)
A
ge
49
80
20
75
S
ex
47
80
20
80
H
EA
59
80
20
45
K
n
o
w
l
e
d
g
e
l
e
v
e
l
i
n
G
A
D
78
80
20
55
T
h
e
n
u
m
b
e
r
o
f
s
u
p
p
o
r
t
v
ec
to
r
s
d
ep
en
d
s
o
n
h
o
w
m
u
ch
s
lack
we
allo
w
an
d
th
e
d
is
tr
ib
u
t
io
n
o
f
th
e
d
ata,
wh
er
ein
a
lar
g
e
am
o
u
n
t
o
f
s
lack
will h
av
e
m
an
y
s
u
p
p
o
r
t v
ec
to
r
s
th
at
s
h
o
w
th
e
d
ata
p
o
in
ts
(
o
b
s
er
v
atio
n
s
)
th
at
lie
clo
s
est
to
th
e
d
ec
is
io
n
b
o
u
n
d
ar
y
.
T
h
e
s
lack
s
ar
e
o
n
ly
u
s
ed
in
th
e
tr
ain
in
g
s
tag
e
,
b
u
t
n
o
t
in
th
e
test
p
h
ase.
I
n
o
r
d
er
to
tr
ai
n
an
SVM
an
d
p
r
o
d
u
ce
s
u
p
p
o
r
t
v
e
cto
r
s
,
an
o
p
tim
izatio
n
is
s
u
e
in
v
o
lv
in
g
q
u
ad
r
ati
c
p
r
o
g
r
a
m
m
in
g
m
u
s
t
b
e
s
o
lv
ed
,
wh
ich
p
r
esen
ts
a
co
m
p
u
tin
g
ch
allen
g
e
as
th
e
n
u
m
b
er
o
f
t
r
a
in
in
g
s
am
p
les,
n
,
is
s
p
ec
if
ied
[
3
6
]
.
B
ased
o
n
th
e
r
esu
lts
,
af
ter
r
u
n
n
in
g
th
e
SVM
th
r
o
u
g
h
th
e
m
ain
v
ar
iab
les
u
s
ed
in
T
AM
,
f
em
ale
p
ar
ticip
an
ts
ar
e
th
e
m
ain
co
n
tr
ib
u
to
r
s
in
t
h
e
s
u
r
v
ey
e
x
p
er
im
e
n
ts
th
at
ac
q
u
ir
e
d
8
0
%
ac
cu
r
ac
y
with
SVM.
4
7
i
n
th
e
s
ex
v
ar
iab
le.
M
o
r
eo
v
er
,
m
o
s
t
o
f
th
e
ag
e
r
an
g
e
o
f
p
ar
tici
p
an
ts
was
f
r
o
m
1
8
-
3
9
o
r
y
o
u
n
g
ad
u
lts
with
s
v.
4
9
s
h
o
win
g
7
5
%
ac
c
u
r
ac
y
.
T
h
e
f
in
d
in
g
s
also
ass
ess
ed
th
e
p
a
r
ticip
an
ts
'
/u
s
er
s
’
k
n
o
wled
g
e
o
f
GAD,
with
5
5
%
ac
cu
r
ac
y
s
h
o
win
g
t
h
e
h
ig
h
est
s
v
o
f
7
8
.
T
h
is
s
h
o
ws
th
at
th
e
h
ig
h
er
s
u
p
p
o
r
t
v
ec
t
o
r
v
alu
e
is
g
iv
en
f
r
o
m
th
e
tr
ain
in
g
d
ata,
s
h
o
win
g
d
ata
p
o
in
ts
th
at
ar
e
clo
s
er
to
th
e
d
ec
is
io
n
b
o
u
n
d
ar
y
,
th
at
m
a
n
y
o
f
th
e
p
ar
ticip
an
ts
h
a
v
e
d
ir
ec
t
k
n
o
wled
g
e
in
GAD
th
at
r
elate
s
th
r
o
u
g
h
th
e
ac
ce
p
tan
c
e
o
f
th
e
m
o
b
ile
ap
p
licatio
n
co
n
tain
in
g
d
is
cip
lin
es
an
d
in
f
o
r
m
atio
n
.
4.
CO
NCLU
SI
O
N
T
h
is
r
esear
ch
co
n
clu
d
ed
all
f
i
n
d
in
g
s
an
d
ev
id
e
n
ce
th
at
th
is
p
h
en
o
m
en
o
n
is
ass
o
ciate
d
wit
h
in
cr
ea
s
ed
k
n
o
wled
g
e
o
f
em
b
r
ac
i
n
g
th
e
n
ew
tech
n
o
lo
g
y
f
o
r
d
is
s
em
in
atin
g
awa
r
en
ess
o
n
GAD
th
r
o
u
g
h
u
s
er
ac
ce
p
tan
ce
.
Fu
r
th
er
,
th
is
m
ay
ad
v
a
n
ce
o
u
r
k
n
o
wled
g
e
o
f
h
o
w
to
u
s
e
th
is
tech
n
o
lo
g
y
as
a
s
tan
d
-
alo
n
e
in
f
o
r
m
atio
n
s
o
u
r
ce
ab
o
u
t
GAD.
T
h
e
n
ewly
d
esig
n
ed
T
AM
-
b
ased
m
o
d
el
with
e
x
ter
n
al
f
ac
to
r
s
f
o
r
th
e
ac
ce
p
ta
n
ce
o
f
th
e
GAD
a
pp
with
m
o
d
er
atin
g
v
a
r
iab
les
s
u
ch
as
ag
e,
s
ex
,
HE
A,
an
d
k
n
o
wled
g
e
o
f
GAD
im
p
lem
en
tatio
n
in
th
eir
en
v
ir
o
n
m
en
t
f
o
u
n
d
t
h
at
th
e
lo
ca
ls
ar
e
willin
g
to
u
tili
ze
th
e
s
aid
tech
n
o
lo
g
y
o
v
er
th
e
b
eh
a
v
io
r
al
in
ten
tio
n
s
o
f
th
e
u
s
er
s
to
a
d
o
p
t
th
e
GAD
a
pp
in
ac
t
u
al
u
s
e
s
ce
n
ar
i
o
.
T
h
e
c
o
n
clu
d
e
d
d
ataset
ab
o
u
t
th
e
u
s
er
ac
ce
p
tan
ce
f
r
o
m
th
e
co
n
d
u
cted
s
u
r
v
ey
q
u
esti
o
n
n
air
e
af
ter
u
s
in
g
th
e
GAD
a
pp
g
av
e
th
e
f
ac
tu
al
r
esu
lts
an
d
f
in
d
in
g
s
th
r
o
u
g
h
s
tatis
t
ics
an
d
an
aly
s
es
p
r
o
v
id
ed
with
a
d
ata
-
d
r
iv
en
m
o
d
el
v
ia
u
s
in
g
th
e
ML
ap
p
r
o
ac
h
th
r
o
u
g
h
SVM.
T
h
e
h
o
lis
tic
in
ter
p
r
etatio
n
o
f
th
e
p
o
ten
tial
ac
ce
p
tab
ilit
y
o
f
th
e
tech
n
o
lo
g
y
is
g
iv
en
an
d
p
r
o
v
en
af
ter
a
s
er
ies
o
f
p
r
e
-
p
r
o
ce
s
s
in
g
,
tr
ain
i
n
g
,
an
d
t
esti
n
g
o
f
d
ata
th
at
g
av
e
m
ea
n
i
n
g
f
u
l
r
esu
lts
th
at
th
e
ac
ce
p
tan
ce
o
f
th
e
GAD
a
p
p
will
b
e
u
s
ed
al
s
o
as
an
in
f
o
r
m
atio
n
,
ed
u
ca
tio
n
,
an
d
co
m
m
u
n
icatio
n
(
I
E
C
)
m
ater
ial
f
o
r
GST
in
th
e
f
u
tu
r
e.
Fu
r
th
er
m
o
r
e
,
f
o
r
p
o
ten
tial
I
n
tellectu
al
Pro
p
er
ty
,
th
e
s
tu
d
y
wo
u
ld
h
av
e
th
e
p
o
ten
tial
to
ap
p
ly
a
co
p
y
r
ig
h
t
ap
p
licatio
n
to
s
o
f
twar
e,
p
u
b
licatio
n
o
f
th
e
m
an
u
s
cr
ip
t,
an
d
a
p
aten
t
a
p
p
licatio
n
f
o
r
a
p
r
o
c
ess
m
o
d
el.
Desp
ite
th
e
co
n
tr
ib
u
tio
n
s
o
f
th
is
s
tu
d
y
,
it
is
also
n
o
t
f
r
ee
f
r
o
m
li
m
itatio
n
s
.
T
h
is
s
tu
d
y
ex
p
lo
r
e
d
a
co
m
p
r
eh
e
n
s
iv
e
ex
p
er
im
en
t w
ith
a
d
ata
-
d
r
iv
e
n
ap
p
r
o
ac
h
.
Ho
wev
er
,
f
u
r
th
er
a
n
d
in
-
d
e
p
th
s
tu
d
ies m
ay
b
e
n
ee
d
ed
to
r
ec
o
m
m
e
n
d
g
ath
er
in
g
d
ata
with
a
lar
g
e
n
u
m
b
er
o
f
r
esp
o
n
d
en
ts
to
b
ette
r
u
n
d
er
s
tan
d
u
s
er
ac
ce
p
tan
ce
th
r
o
u
g
h
th
e
u
n
if
ied
th
eo
r
y
o
f
ac
ce
p
tan
ce
an
d
u
s
e
o
f
tech
n
o
l
o
g
y
(
UT
AUT
)
.
A
n
o
th
er
,
th
is
also
n
ee
d
s
to
u
n
d
er
s
tan
d
th
e
in
s
ig
h
ts
o
f
p
ar
ticip
an
ts
,
th
r
o
u
g
h
a
q
u
alitativ
e
s
tu
d
y
to
p
r
o
v
id
e
a
h
o
lis
tic
v
iew
o
f
GAD
a
pp
ad
o
p
tio
n
an
d
m
ak
e
th
is
s
tu
d
y
th
e
b
aselin
e
f
o
r
f
u
tu
r
e
wo
r
k
s
as
a
s
u
p
p
lier
o
f
GAD
in
f
o
r
m
atio
n
.
L
astl
y
,
a
co
m
p
ar
is
o
n
o
f
d
if
f
er
e
n
t
ML
alg
o
r
ith
m
s
m
ay
b
e
u
s
ed
to
co
m
p
ar
e
d
if
f
er
en
t
d
ata
-
d
r
iv
e
n
m
o
d
els f
o
r
th
is
s
tu
d
y
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
wo
u
l
d
lik
e
to
ex
p
r
ess
th
eir
s
in
ce
r
e
g
r
atitu
d
e
an
d
ap
p
r
ec
iatio
n
to
th
e
p
eo
p
le
wh
o
ex
ten
d
ed
th
eir
u
n
tirin
g
an
d
wh
o
leh
ea
r
ted
s
u
p
p
o
r
t
to
m
a
k
e
th
is
s
tu
d
y
p
o
s
s
ib
le:
(
1
)
t
o
th
e
C
av
ite
Sta
te
Un
iv
er
s
ity
(
C
v
SU)
Naic
R
DE
S;
(
2
)
to
o
u
r
C
am
p
u
s
Ad
m
in
is
tr
ato
r
,
an
d
s
o
m
e
co
lleag
u
es
in
th
e
I
n
f
o
r
m
atio
n
T
ec
h
n
o
lo
g
y
De
p
ar
tm
en
t,
an
d
th
e
Ma
n
a
g
em
en
t
Dep
ar
tm
en
t
;
(
3
)
to
m
y
c
o
-
d
e
v
elo
p
er
s
a
n
d
co
-
a
u
th
o
r
s
o
f
th
e
p
r
ev
io
u
s
s
tu
d
y
n
am
ely
Gr
eg
o
r
io
Salas,
B
la
s
s
Per
ez
,
an
d
J
o
h
n
R
o
s
s
Alca
n
tar
a
f
r
o
m
B
SIT
I
V
s
tu
d
en
ts
an
d
Dr
.
Sh
er
r
ly
n
M.
R
asd
as
as
T
ec
h
n
ical
C
r
itic;
an
d
(
4
)
to
th
e
s
elec
ted
lo
ca
l
g
o
v
er
n
m
en
t
u
n
i
t,
Dep
E
d
,
s
elec
ted
f
ac
u
lty
,
an
d
s
tu
d
en
ts
o
f
C
v
SU
Naic
,
C
C
AT
,
T
r
ec
e,
B
ac
o
o
r
,
an
d
I
n
d
an
g
ca
m
p
u
s
in
C
av
ite,
Ph
ilip
p
in
es
f
o
r
th
e
r
esp
o
n
s
e
g
iv
en
in
s
u
p
p
o
r
t o
f
c
o
llectin
g
s
u
r
v
ey
d
ata
r
elatin
g
to
th
is
r
esear
ch
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
is
r
esear
ch
was f
u
n
d
e
d
b
y
t
h
e
C
av
ite
State
Un
iv
er
s
ity
Naic
ca
m
p
u
s
,
u
n
d
er
t
h
e
lo
ca
l r
ese
ar
ch
f
u
n
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
User
a
cc
ep
ta
n
ce
o
f th
e
GA
D
mo
b
ile
a
p
p
w
ith
a
r
a
tin
g
ch
ec
klis
t u
s
in
g
a
mo
d
ified
…
(
R
o
s
s
ia
n
V
.
P
erea
)
3913
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
t
r
ib
u
to
r
R
o
les
T
a
x
o
n
o
m
y
(
C
R
ed
iT
)
to
r
ec
o
g
n
ize
in
d
iv
i
d
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
llab
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
R
o
s
s
ian
V.
Per
ea
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Ab
ig
ae
l M
.
Mir
an
d
a
✓
✓
✓
✓
✓
✓
✓
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
s
i
s
I
:
I
n
v
e
s
t
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
s
i
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
DATA AV
AI
L
AB
I
L
I
T
Y
D
a
t
a
a
v
a
il
a
b
i
li
t
y
is
n
o
t
a
p
p
l
i
ca
b
l
e
t
o
t
h
is
p
a
p
e
r
a
s
n
o
n
e
w
d
at
a
w
e
r
e
c
r
e
a
t
e
d
o
r
a
n
al
y
z
e
d
i
n
t
h
is
s
t
u
d
y
.
RE
F
E
R
E
NC
E
S
[
1
]
C
.
C
.
M
a
d
u
k
a
a
n
d
D
.
A
l
h
e
r
i
,
“
G
e
n
d
e
r
mai
n
st
r
e
a
mi
n
g
a
s a
t
o
o
l
f
o
r
a
c
h
i
e
v
i
n
g
i
n
c
l
u
s
i
v
e
n
a
t
i
o
n
a
l
d
e
v
e
l
o
p
m
e
n
t
,
”
Re
sea
r
c
h
G
a
t
e
,
p
p
.
1
–
1
3
,
2
0
2
4
,
d
o
i
:
1
0
.
1
3
1
4
0
/
R
G
.
2
.
2
.
2
3
4
0
4
.
1
7
2
8
5
.
[
2
]
S
I
D
A
,
“
G
e
n
d
e
r
a
n
a
l
y
si
s
-
p
r
i
n
c
i
p
l
e
s
&
e
l
e
me
n
t
s
:
S
I
D
A
d
e
f
i
n
i
t
i
o
n
s,
”
G
e
n
d
e
r
T
o
o
l
Bo
x
,
p
p
.
1
–
4
,
2
0
1
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
c
d
n
.
si
d
a
.
se
/
p
u
b
l
i
c
a
t
i
o
n
s/
f
i
l
e
s
/
si
d
a
6
1
8
5
3
e
n
-
g
e
n
d
e
r
-
a
n
a
l
y
s
i
s
-
p
r
i
n
c
i
p
l
e
s
-
e
l
e
m
e
n
t
s.
p
d
f
[
3
]
C
o
mm
i
ss
i
o
n
o
n
H
i
g
h
e
r
E
d
u
c
a
t
i
o
n
,
“
C
H
ED
memo
r
a
n
d
u
m o
r
d
e
r
N
o
.
0
1
,
ser
i
e
s o
f
2
0
1
5
:
Es
t
a
b
l
i
sh
i
n
g
t
h
e
p
o
l
i
c
i
e
s a
n
d
g
u
i
d
e
l
i
n
e
s
o
n
g
e
n
d
e
r
a
n
d
d
e
v
e
l
o
p
me
n
t
i
n
t
h
e
c
o
m
mi
ssi
o
n
o
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
a
n
d
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
i
n
s
t
i
t
u
t
i
o
n
s
(
H
EI
s)
,
”
i
n
R
e
p
u
b
l
i
c
o
f
t
h
e
Ph
i
l
i
p
p
i
n
e
s
,
2
0
1
5
.
[
4
]
B
.
M
.
S
h
k
u
r
t
i
,
“
Th
e
n
a
t
i
o
n
a
l
a
n
d
i
n
t
e
r
n
a
t
i
o
n
a
l
l
e
g
a
l
f
r
a
mew
o
r
k
r
e
l
a
t
e
d
t
o
f
a
mi
l
y
r
e
l
a
t
i
o
n
s
see
n
f
r
o
m
t
h
e
p
e
r
s
p
e
c
t
i
v
e
o
f
g
e
n
d
e
r
e
q
u
a
l
i
t
y
,
”
I
n
t
e
rd
i
sc
i
p
l
i
n
a
ry
J
o
u
r
n
a
l
o
f
Re
se
a
r
c
h
a
n
d
D
e
v
e
l
o
p
m
e
n
t
,
v
o
l
.
1
1
,
n
o
.
1
,
2
0
2
4
,
d
o
i
:
1
0
.
5
6
3
4
5
/
i
j
r
d
v
1
1
n
1
0
7
.
[
5
]
J.
S
t
a
l
a
n
d
G
.
P
.
P
ę
k
o
s
z
,
“
M
o
b
i
l
e
t
e
c
h
n
o
l
o
g
y
a
c
c
e
p
t
a
n
c
e
mo
d
e
l
:
A
n
e
m
p
i
r
i
c
a
l
s
t
u
d
y
o
n
u
sers’
a
c
c
e
p
t
a
n
c
e
a
n
d
u
sa
g
e
o
f
mo
b
i
l
e
t
e
c
h
n
o
l
o
g
y
f
o
r
k
n
o
w
l
e
d
g
e
p
r
o
v
i
d
i
n
g
,
”
L
e
c
t
u
re
N
o
t
e
s
i
n
Bu
s
i
n
e
ss
I
n
f
o
rm
a
t
i
o
n
Pr
o
c
e
ssi
n
g
,
v
o
l
.
3
4
1
,
p
p
.
5
4
7
–
5
5
9
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
3
-
0
3
0
-
1
1
3
9
5
-
7
_
4
2
.
[
6
]
F
.
W
e
n
g
,
R
.
J.
Y
a
n
g
,
H
.
J
.
H
o
,
a
n
d
H
.
M
.
S
u
,
“
A
t
a
m
-
b
a
se
d
st
u
d
y
o
f
t
h
e
a
t
t
i
t
u
d
e
t
o
w
a
r
d
s
u
s
e
i
n
t
e
n
t
i
o
n
o
f
m
u
l
t
i
m
e
d
i
a
a
mo
n
g
sch
o
o
l
t
e
a
c
h
e
r
s,
”
A
p
p
l
i
e
d
S
y
s
t
e
m
I
n
n
o
v
a
t
i
o
n
,
v
o
l
.
1
,
n
o
.
3
,
p
p
.
1
–
9
,
2
0
1
8
,
d
o
i
:
1
0
.
3
3
9
0
/
a
si
1
0
3
0
0
3
6
.
[
7
]
A
.
A
t
i
f
a
n
d
D
.
R
i
c
h
a
r
d
s,
“
A
t
e
c
h
n
o
l
o
g
y
a
c
c
e
p
t
a
n
c
e
m
o
d
e
l
f
o
r
u
n
i
t
g
u
i
d
e
i
n
f
o
r
ma
t
i
o
n
s
y
s
t
e
ms
,
”
i
n
Pro
c
e
e
d
i
n
g
s
-
P
a
c
i
f
i
c
As
i
a
C
o
n
f
e
re
n
c
e
o
n
I
n
f
o
rm
a
t
i
o
n
S
y
st
e
m
s
,
PAC
I
S
2
0
1
2
,
2
0
1
2
.
[
8
]
J.
T.
M
a
r
c
h
e
w
k
a
a
n
d
K
.
K
o
st
i
w
a
,
“
A
n
a
p
p
l
i
c
a
t
i
o
n
o
f
t
h
e
U
TA
U
T
m
o
d
e
l
f
o
r
u
n
d
e
r
s
t
a
n
d
i
n
g
s
t
u
d
e
n
t
p
e
r
c
e
p
t
i
o
n
s
u
s
i
n
g
c
o
u
r
se
man
a
g
e
me
n
t
so
f
t
w
a
r
e
,
”
C
o
m
m
u
n
i
c
a
t
i
o
n
s
o
f
t
h
e
I
I
MA
,
v
o
l
.
7
,
n
o
.
2
,
2
0
1
4
,
d
o
i
:
1
0
.
5
8
7
2
9
/
1
9
4
1
-
6
6
8
7
.
1
0
3
8
.
[
9
]
F
.
W
.
D
u
l
l
e
a
n
d
M
.
K
.
M
i
n
i
s
h
i
-
M
a
j
a
n
j
a
,
“
Th
e
s
u
i
t
a
b
i
l
i
t
y
o
f
t
h
e
u
n
i
f
i
e
d
t
h
e
o
r
y
o
f
a
c
c
e
p
t
a
n
c
e
a
n
d
u
s
e
o
f
t
e
c
h
n
o
l
o
g
y
(
u
t
a
u
t
)
m
o
d
e
l
i
n
o
p
e
n
a
c
c
e
ss
a
d
o
p
t
i
o
n
s
t
u
d
i
e
s,
”
I
n
f
o
rm
a
t
i
o
n
D
e
v
e
l
o
p
m
e
n
t
,
v
o
l
.
2
7
,
n
o
.
1
,
p
p
.
3
2
–
4
5
,
2
0
1
1
,
d
o
i
:
1
0
.
1
1
7
7
/
0
2
6
6
6
6
6
9
1
0
3
8
5
3
7
5
.
[
1
0
]
R
.
V
.
P
e
r
e
a
a
n
d
A
.
I
.
R
e
g
l
a
,
“
A
n
a
l
y
s
i
s
o
f
t
h
e
u
se
o
f
i
n
f
o
r
ma
t
i
o
n
sy
s
t
e
m
f
o
r
a
c
c
u
m
u
l
a
t
i
n
g
se
x
-
d
i
sa
g
g
r
e
g
a
t
e
d
d
a
t
a
w
i
t
h
a
n
a
l
y
t
i
c
s o
f
t
h
e
b
a
r
a
n
g
a
y
c
o
n
st
i
t
u
e
n
t
s
u
s
i
n
g
t
h
e
t
e
c
h
n
o
l
o
g
y
a
c
c
e
p
t
a
n
c
e
mo
d
e
l
,
”
i
n
9
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
C
T
f
o
r
S
m
a
rt
S
o
c
i
e
t
y
:
Re
c
o
v
e
r
T
o
g
e
t
h
e
r,
Re
c
o
v
e
r
S
t
r
o
n
g
e
r
a
n
d
S
m
a
r
t
e
r
S
m
a
r
t
i
z
a
t
i
o
n
,
G
o
v
e
r
n
a
n
c
e
a
n
d
C
o
l
l
a
b
o
r
a
t
i
o
n
,
I
C
I
S
S
2
0
2
2
-
Pro
c
e
e
d
i
n
g
,
2
0
2
2
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
I
S
S
5
5
8
9
4
.
2
0
2
2
.
9
9
1
5
2
2
0
.
[
1
1
]
O
.
M
ü
l
l
e
r
,
I
.
Ju
n
g
l
a
s
,
J
.
V
.
B
r
o
c
k
e
,
a
n
d
S
.
D
e
b
o
r
t
o
l
i
,
“
U
t
i
l
i
z
i
n
g
b
i
g
d
a
t
a
a
n
a
l
y
t
i
c
s
f
o
r
i
n
f
o
r
m
a
t
i
o
n
s
y
s
t
e
ms
r
e
se
a
r
c
h
:
C
h
a
l
l
e
n
g
e
s,
p
r
o
m
i
ses
a
n
d
g
u
i
d
e
l
i
n
e
s,”
E
u
ro
p
e
a
n
J
o
u
r
n
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
S
y
st
e
m
s
,
v
o
l
.
2
5
,
n
o
.
4
,
p
p
.
2
8
9
–
3
0
2
,
2
0
1
6
,
d
o
i
:
1
0
.
1
0
5
7
/
e
j
i
s.
2
0
1
6
.
2
.
[
1
2
]
A
.
A
.
A
.
A
l
-
Z
o
u
b
a
a
n
d
S
.
A
.
S
a
mi
k
o
n
,
“
Th
e
u
ser
mo
t
i
v
a
t
i
o
n
f
a
c
t
o
r
s
i
mp
a
c
t
o
n
i
mm
e
r
si
v
e
t
e
c
h
n
o
l
o
g
y
a
c
c
e
p
t
a
n
c
e
,
”
Re
v
i
s
t
a
d
e
G
e
st
a
o
S
o
c
i
a
l
e
Am
b
i
e
n
t
a
l
,
v
o
l
.
1
8
,
n
o
.
4
,
2
0
2
4
,
d
o
i
:
1
0
.
2
4
8
5
7
/
r
g
sa.
v
1
8
n
4
-
1
2
9
.
[
1
3
]
C
.
W
a
n
g
a
n
d
H
.
Q
i
,
“
I
n
f
l
u
e
n
c
i
n
g
f
a
c
t
o
r
s
o
f
a
c
c
e
p
t
a
n
c
e
a
n
d
u
s
e
b
e
h
a
v
i
o
r
o
f
mo
b
i
l
e
h
e
a
l
t
h
a
p
p
l
i
c
a
t
i
o
n
u
s
e
r
s:
S
y
st
e
mat
i
c
r
e
v
i
e
w
,
”
H
e
a
l
t
h
c
a
re
(
S
w
i
t
z
e
rl
a
n
d
)
,
v
o
l
.
9
,
n
o
.
3
,
2
0
2
1
,
d
o
i
:
1
0
.
3
3
9
0
/
h
e
a
l
t
h
c
a
r
e
9
0
3
0
3
5
7
.
[
1
4
]
E.
T
.
C
a
s
t
r
o
a
n
d
A
.
A
.
H
e
r
n
a
n
d
e
z
,
“
U
ser
a
c
c
e
p
t
a
n
c
e
o
f
a
b
u
s
e
r
e
p
o
r
t
i
n
g
sy
s
t
e
m
o
n
w
o
m
e
n
a
n
d
c
h
i
l
d
r
e
n
w
i
t
h
a
n
a
l
y
t
i
c
s
u
si
n
g
u
n
i
f
i
e
d
t
h
e
o
r
y
o
f
a
c
c
e
p
t
a
n
c
e
a
n
d
u
se
o
f
t
e
c
h
n
o
l
o
g
y
:
Ev
i
d
e
n
c
e
f
r
o
m
t
h
e
P
h
i
l
i
p
p
i
n
e
s,
”
i
n
2
0
1
9
I
EE
E
9
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
S
y
st
e
m
E
n
g
i
n
e
e
r
i
n
g
a
n
d
T
e
c
h
n
o
l
o
g
y
,
I
C
S
ET
2
0
1
9
-
Pro
c
e
e
d
i
n
g
,
2
0
1
9
,
p
p
.
1
3
8
–
1
4
3
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
S
En
g
T
.
2
0
1
9
.
8
9
0
6
3
9
4
.
[
1
5
]
B
.
Zo
h
u
r
i
a
n
d
M
.
M
o
g
h
a
d
d
a
m,
“
F
r
o
m
b
u
s
i
n
e
ss
i
n
t
e
l
l
i
g
e
n
c
e
t
o
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
,
”
M
o
d
e
r
n
Ap
p
r
o
a
c
h
e
s
o
n
Ma
t
e
r
i
a
l
S
c
i
e
n
c
e
,
v
o
l
.
2
,
n
o
.
3
,
p
p
.
2
3
1
–
2
4
0
,
2
0
2
0
,
d
o
i
:
1
0
.
3
2
4
7
4
/
M
A
M
S
.
2
0
2
0
.
0
2
.
0
0
0
1
3
7
.
[
1
6
]
J.
C
e
r
v
a
n
t
e
s
,
F
.
G
.
La
mo
n
t
,
L.
R
.
M
a
z
a
h
u
a
,
a
n
d
A
.
L
o
p
e
z
,
“
A
c
o
m
p
r
e
h
e
n
si
v
e
s
u
r
v
e
y
o
n
su
p
p
o
r
t
v
e
c
t
o
r
m
a
c
h
i
n
e
c
l
a
ss
i
f
i
c
a
t
i
o
n
:
A
p
p
l
i
c
a
t
i
o
n
s
,
c
h
a
l
l
e
n
g
e
s a
n
d
t
r
e
n
d
s,
”
N
e
u
ro
c
o
m
p
u
t
i
n
g
,
v
o
l
.
4
0
8
,
p
p
.
1
8
9
–
2
1
5
,
S
e
p
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
n
e
u
c
o
m.
2
0
1
9
.
1
0
.
1
1
8
.
[
1
7
]
R
.
D
e
v
i
,
“
T
h
e
a
sce
n
d
a
n
c
y
o
f
b
i
g
d
a
t
a
a
n
a
l
y
t
i
c
s
f
o
r
a
g
r
i
c
u
l
t
u
r
a
l
c
o
m
p
e
t
i
t
i
v
e
n
e
ss:
t
h
e
t
h
e
o
r
e
t
i
c
a
l
f
r
a
m
e
w
o
r
k
t
o
a
u
g
me
n
t
t
h
e
a
g
r
i
c
u
l
t
u
r
a
l
m
a
n
a
g
e
me
n
t
sy
st
e
m,”
J
o
u
rn
a
l
o
f
Ma
n
a
g
e
m
e
n
t
,
v
o
l
.
4
,
n
o
.
2
,
p
p
.
3
7
3
–
3
8
1
,
2
0
1
7
.
[
1
8
]
P
.
O
d
y
a
,
F
.
G
o
r
s
k
i
,
a
n
d
A
.
C
z
y
z
e
w
sk
i
,
“
U
s
e
r
a
u
t
h
e
n
t
i
c
a
t
i
o
n
b
y
e
y
e
mo
v
e
me
n
t
f
e
a
t
u
r
e
s
e
m
p
l
o
y
i
n
g
S
V
M
a
n
d
X
G
B
o
o
st
c
l
a
ss
i
f
i
e
r
s,”
I
EEE
Ac
c
e
ss
,
v
o
l
.
1
1
,
p
p
.
9
3
3
4
1
–
9
3
3
5
3
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
3
.
3
3
0
9
0
0
0
.
[
1
9
]
D
.
A
.
P
i
sn
e
r
a
n
d
D
.
M
.
S
c
h
n
y
e
r
,
“
S
u
p
p
o
r
t
v
e
c
t
o
r
m
a
c
h
i
n
e
,
”
M
a
c
h
i
n
e
L
e
a
rn
i
n
g
:
Me
t
h
o
d
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
t
o
Bra
i
n
D
i
s
o
r
d
e
rs
,
p
p
.
1
0
1
–
1
2
1
,
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/
B
9
7
8
-
0
-
12
-
8
1
5
7
3
9
-
8
.
0
0
0
0
6
-
7.
[
2
0
]
F
.
W
a
n
,
J.
Te
n
g
,
a
n
d
L
.
F
e
n
g
,
“
E
x
p
l
o
r
i
n
g
u
ser
a
t
t
i
t
u
d
e
s
a
n
d
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
s
t
o
w
a
r
d
s
a
u
g
me
n
t
e
d
r
e
a
l
i
t
y
a
u
t
o
m
o
t
i
v
e
a
ssi
s
t
a
n
t
s
:
a
mi
x
e
d
-
me
t
h
o
d
s
a
p
p
r
o
a
c
h
,
”
Wo
r
l
d
El
e
c
t
ri
c
V
e
h
i
c
l
e
J
o
u
r
n
a
l
,
v
o
l
.
1
5
,
n
o
.
6
,
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
w
e
v
j
1
5
0
6
0
2
5
8
.
[
2
1
]
A
.
E.
E
v
w
i
e
k
p
a
e
f
e
a
n
d
O
.
F
.
A
mr
e
v
u
a
w
h
o
,
“
A
c
c
e
p
t
a
n
c
e
o
f
I
o
T
t
e
c
h
n
o
l
o
g
y
a
mo
n
g
s
t
u
d
e
n
t
s
a
n
d
st
a
f
f
o
f
t
e
r
t
i
a
r
y
i
n
s
t
i
t
u
t
i
o
n
s
i
n
K
a
d
u
n
a
S
t
a
t
e
,
N
i
g
e
r
i
a
,
”
D
u
t
se
J
o
u
r
n
a
l
o
f
P
u
re
a
n
d
Ap
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
9
,
n
o
.
1
a
,
p
p
.
1
1
7
–
1
2
6
,
2
0
2
3
,
d
o
i
:
1
0
.
4
3
1
4
/
d
u
j
o
p
a
s
.
v
9
i
1
a
.
1
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
:
3
9
0
6
-
3
9
1
4
3914
[
2
2
]
N
.
A
.
V
a
n
e
sh
a
,
R
.
R
i
z
k
y
,
a
n
d
A
.
P
u
r
w
a
n
t
o
,
“
C
o
m
p
a
r
i
s
o
n
b
e
t
w
e
e
n
u
sa
b
i
l
i
t
y
a
n
d
u
ser
a
c
c
e
p
t
a
n
c
e
t
e
s
t
i
n
g
o
n
e
d
u
c
a
t
i
o
n
a
l
g
a
m
e
a
ssessm
e
n
t
,
”
J
u
r
n
a
l
S
i
s
f
o
k
o
m
(
S
i
st
e
m
I
n
f
o
rm
a
si
d
a
n
K
o
m
p
u
t
e
r)
,
v
o
l
.
1
3
,
n
o
.
2
,
p
p
.
2
1
0
–
2
1
5
,
2
0
2
4
,
d
o
i
:
1
0
.
3
2
7
3
6
/
si
sf
o
k
o
m.
v
1
3
i
2
.
2
0
9
9
.
[
2
3
]
A
.
R
o
f
i
’
i
,
D
.
R
.
F
i
r
d
a
u
s,
a
n
d
I
.
M
o
r
i
d
u
,
“
T
h
e
a
n
a
l
y
si
s
o
f
u
ser a
c
c
e
p
t
a
n
c
e
u
s
i
n
g
U
TA
U
T
a
n
d
D
e
l
o
n
e
& M
c
Le
a
n
mo
d
e
l
:
s
t
u
d
y
c
a
s
e
o
f
b
a
n
k
i
n
g
mo
b
i
l
e
a
p
p
l
i
c
a
t
i
o
n
,
”
J
o
u
r
n
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
S
y
s
t
e
m
,
T
e
c
h
n
o
l
o
g
y
a
n
d
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
,
n
o
.
1
,
p
p
.
2
1
–
2
5
,
2
0
2
3
,
d
o
i
:
1
0
.
6
1
4
8
7
/
j
i
s
t
e
.
v
1
i
1
.
1
1
.
[
2
4
]
A
.
W
.
D
e
msas
h
,
M
.
H
.
K
a
l
a
y
o
u
,
a
n
d
A
.
D
.
W
a
l
l
e
,
“
H
e
a
l
t
h
p
r
o
f
e
ssi
o
n
a
l
s’
a
c
c
e
p
t
a
n
c
e
o
f
m
o
b
i
l
e
-
b
a
se
d
c
l
i
n
i
c
a
l
g
u
i
d
e
l
i
n
e
a
p
p
l
i
c
a
t
i
o
n
i
n
a
r
e
s
o
u
r
c
e
-
l
i
m
i
t
e
d
se
t
t
i
n
g
:
u
s
i
n
g
a
mo
d
i
f
i
e
d
U
TA
U
T
mo
d
e
l
,
”
BM
C
Me
d
i
c
a
l
E
d
u
c
a
t
i
o
n
,
v
o
l
.
2
4
,
n
o
.
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
8
6
/
s
1
2
9
0
9
-
0
2
4
-
0
5
6
8
0
-
z.
[
2
5
]
A
.
S
.
G
.
Er
i
c
k
so
n
a
n
d
P
.
M
.
N
o
o
n
a
n
,
“
S
e
l
f
-
r
e
g
u
l
a
t
i
o
n
a
ssessm
e
n
t
s
u
i
t
e
:
T
e
c
h
n
i
c
a
l
r
e
p
o
r
t
,
”
C
o
l
l
e
g
e
&
C
a
ree
r
C
o
m
p
e
t
e
n
c
y
Fra
m
e
w
o
rk
,
2
0
2
3
,
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s:
/
/
w
w
w
.
c
c
c
f
r
a
m
e
w
o
r
k
.
o
r
g
/
w
p
-
c
o
n
t
e
n
t
/
u
p
l
o
a
d
s/
S
e
l
f
-
R
e
g
u
l
a
t
i
o
n
A
ss
e
s
sS
u
i
t
e
T
e
c
h
.
p
d
f
[
2
6
]
D
.
J.
C
.
A
r
c
i
n
u
e
a
n
d
M
.
J.
B
.
S
i
l
a
o
,
“
P
r
e
v
a
l
e
n
c
e
o
f
a
n
x
i
e
t
y
a
n
d
d
e
p
r
e
ss
i
o
n
a
mo
n
g
P
C
O
S
p
a
t
i
e
n
t
s
s
e
e
n
i
n
a
t
e
r
t
i
a
r
y
g
o
v
e
r
n
m
e
n
t
h
o
s
p
i
t
a
l
u
si
n
g
t
h
e
h
o
s
p
i
t
a
l
a
n
x
i
e
t
y
a
n
d
d
e
p
r
e
ssi
o
n
sca
l
e
-
E
n
g
l
i
sh
/
P
i
l
i
p
i
n
o
v
e
r
si
o
n
(
H
A
D
S
/
H
A
D
S
-
P
)
,
”
Ac
t
a
M
e
d
i
c
a
P
h
i
l
i
p
p
i
n
a
,
v
o
l
.
5
8
,
n
o
.
1
1
,
p
p
.
2
9
–
3
8
,
2
0
2
4
,
d
o
i
:
1
0
.
4
7
8
9
5
/
a
m
p
.
v
5
8
i
1
1
.
8
9
7
7
.
[
2
7
]
S
.
M
e
n
g
e
t
a
l
.
,
“
T
h
e
e
f
f
e
c
t
s
o
f
m
o
b
i
l
e
p
h
o
n
e
a
d
d
i
c
t
i
o
n
o
n
b
e
d
t
i
m
e
p
r
o
c
r
a
st
i
n
a
t
i
o
n
i
n
u
n
i
v
e
r
s
i
t
y
s
t
u
d
e
n
t
s:
t
h
e
mask
i
n
g
e
f
f
e
c
t
o
f
p
h
y
s
i
c
a
l
a
c
t
i
v
i
t
y
a
n
d
a
n
x
i
e
t
y
,
”
BM
C
Psy
c
h
o
l
o
g
y
,
v
o
l
.
1
2
,
n
o
.
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
8
6
/
s
4
0
3
5
9
-
0
2
4
-
0
1
8
9
9
-
z.
[
2
8
]
A
.
Jasi
e
l
s
k
a
,
M
.
W
o
j
c
i
e
c
h
o
w
sk
a
,
a
n
d
R
.
A
.
M
a
k
sy
mi
u
k
,
“
P
o
m
i
a
r
l
ę
k
u
p
o
p
o
r
o
d
z
i
e
–
p
o
l
s
k
a
w
e
r
sj
a
p
o
st
p
a
r
t
u
m
sp
e
c
i
f
i
c
a
n
x
i
e
t
y
sca
l
e
-
r
e
s
e
a
r
c
h
s
h
o
r
t
f
o
r
m,”
C
z
ł
o
w
i
e
k
i
S
p
o
ł
e
c
z
e
ń
s
t
w
o
,
v
o
l
.
5
7
,
p
p
.
2
1
–
4
1
,
2
0
2
4
,
d
o
i
:
1
0
.
1
4
7
4
6
/
c
i
s.
2
0
2
4
.
5
7
.
2
.
[
2
9
]
E.
T
.
C
a
s
t
r
o
a
n
d
A
.
A
.
H
e
r
n
a
n
d
e
z
,
“
U
ser
a
c
c
e
p
t
a
n
c
e
o
f
p
r
e
d
i
c
t
i
v
e
a
n
a
l
y
t
i
c
s
o
n
v
i
o
l
e
n
c
e
a
g
a
i
n
s
t
w
o
me
n
a
n
d
c
h
i
l
d
r
e
n
a
t
r
i
s
k
:
A
f
i
e
l
d
s
u
r
v
e
y
i
n
t
h
e
P
h
i
l
i
p
p
i
n
e
s,
”
i
n
2
0
1
9
I
EEE
9
t
h
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
S
y
st
e
m
En
g
i
n
e
e
r
i
n
g
a
n
d
T
e
c
h
n
o
l
o
g
y
(
I
C
S
ET)
,
O
c
t
.
2
0
1
9
,
v
o
l
.
1
7
,
p
p
.
1
3
2
–
1
3
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
S
En
g
T.
2
0
1
9
.
8
9
0
6
3
4
0
.
[
3
0
]
N
.
K
u
b
o
t
a
a
n
d
H
.
M
a
s
u
t
a
,
“
A
c
t
i
o
n
l
e
a
r
n
i
n
g
o
f
a
mo
b
i
l
e
r
o
b
o
t
b
a
se
d
o
n
p
e
r
c
e
i
v
i
n
g
-
a
c
t
i
n
g
c
y
c
l
e
,
”
I
EEE
I
n
t
e
r
n
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
R
o
b
o
t
s
a
n
d
S
y
st
e
m
s
,
v
o
l
.
2
,
p
p
.
1
2
2
2
–
1
2
2
7
,
2
0
0
3
,
d
o
i
:
1
0
.
1
1
0
9
/
i
r
o
s.
2
0
0
3
.
1
2
4
8
8
1
2
.
[
3
1
]
A
.
S
.
A
.
A
l
w
a
b
e
l
a
n
d
X
.
J.
Ze
n
g
,
“
D
a
t
a
-
d
r
i
v
e
n
m
o
d
e
l
i
n
g
o
f
t
e
c
h
n
o
l
o
g
y
a
c
c
e
p
t
a
n
c
e
:
A
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
p
e
r
sp
e
c
t
i
v
e
,
”
Ex
p
e
r
t
S
y
s
t
e
m
s
w
i
t
h
A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
1
8
5
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
sw
a
.
2
0
2
1
.
1
1
5
5
8
4
.
[
3
2
]
I
.
Š
e
r
b
e
t
a
r
a
n
d
I
.
S
e
d
l
e
r
,
“
A
ss
e
ssi
n
g
r
e
l
i
a
b
i
l
i
t
y
o
f
a
m
u
l
t
i
-
d
i
m
e
n
s
i
o
n
a
l
sc
a
l
e
b
y
c
o
e
f
f
i
c
i
e
n
t
a
l
p
h
a
,
”
Re
v
i
j
a
za
e
l
e
m
e
n
t
a
r
n
o
i
zo
b
r
a
žev
a
n
j
e
š
t
.
,
v
o
l
.
2
9
,
p
p
.
1
8
9
–
1
9
5
,
2
0
0
9
.
[
3
3
]
S
.
G
l
e
n
,
“
C
r
o
n
b
a
c
h
’
s a
l
p
h
a
:
S
i
m
p
l
e
d
e
f
i
n
i
t
i
o
n
,
u
s
e
a
n
d
i
n
t
e
r
p
r
e
t
a
t
i
o
n
,
”
S
c
r
i
b
d
,
p
p
.
1
–
9
,
2
0
2
3
.
[
3
4
]
M
.
D
e
s
i
a
w
a
n
a
n
d
A
.
S
o
l
i
c
h
i
n
,
“
S
V
M
o
p
t
i
m
i
z
a
t
i
o
n
w
i
t
h
g
r
i
d
sea
r
c
h
c
r
o
ss
v
a
l
i
d
a
t
i
o
n
f
o
r
i
m
p
r
o
v
i
n
g
a
c
c
u
r
a
c
y
o
f
sch
i
z
o
p
h
r
e
n
i
a
c
l
a
ss
i
f
i
c
a
t
i
o
n
b
a
se
d
o
n
EEG
si
g
n
a
l
,
”
J
u
rn
a
l
T
e
k
n
i
k
I
n
f
o
rm
a
t
i
k
a
,
v
o
l
.
1
7
,
n
o
.
1
,
p
p
.
1
0
–
2
0
,
2
0
2
4
,
d
o
i
:
1
0
.
1
5
4
0
8
/
j
t
i
.
v
1
7
i
1
.
3
7
4
2
2
.
[
3
5
]
M
.
S
h
a
l
a
b
y
,
M
.
F
a
r
o
u
k
,
a
n
d
H
.
A
.
K
h
a
t
e
r
,
“
D
a
t
a
r
e
d
u
c
t
i
o
n
f
o
r
S
V
M
t
r
a
i
n
i
n
g
u
si
n
g
d
e
n
s
i
t
y
b
a
se
d
b
o
r
d
e
r
i
d
e
n
t
i
f
i
c
a
t
i
o
n
,
”
PL
o
S
O
N
E
,
v
o
l
.
1
9
,
n
o
.
4
A
p
r
i
l
,
2
0
2
4
,
d
o
i
:
1
0
.
1
3
7
1
/
j
o
u
r
n
a
l
.
p
o
n
e
.
0
3
0
0
6
4
1
.
[
3
6
]
M
.
A
s
l
a
n
i
a
n
d
S
.
S
e
i
p
e
l
,
“
Ef
f
i
c
i
e
n
t
a
n
d
d
e
c
i
si
o
n
b
o
u
n
d
a
r
y
a
w
a
r
e
i
n
s
t
a
n
c
e
sel
e
c
t
i
o
n
f
o
r
su
p
p
o
r
t
v
e
c
t
o
r
ma
c
h
i
n
e
s,”
I
n
f
o
rm
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
5
7
7
,
p
p
.
5
7
9
–
5
9
8
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
n
s.
2
0
2
1
.
0
7
.
0
1
5
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Ro
ss
ia
n
V.
Per
e
a
h
o
l
d
s
a
Do
c
to
r
in
In
f
o
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
d
e
g
re
e
fr
o
m
t
h
e
Tec
h
n
o
l
o
g
ica
l
I
n
stit
u
te
o
f
t
h
e
P
h
il
i
p
p
i
n
e
s
in
2
0
2
2
u
n
d
e
r
t
h
e
Ca
v
it
e
S
tate
U
n
iv
e
rsit
y
sc
h
o
lars
h
ip
p
r
o
g
ra
m
.
Re
c
e
iv
e
d
a
m
a
ste
r’s
d
e
g
re
e
in
in
f
o
rm
a
ti
o
n
tec
h
n
o
l
o
g
y
i
n
2
0
1
4
a
t
t
h
e
Tec
h
n
o
l
o
g
ica
l
Un
iv
e
rsity
o
f
t
h
e
P
h
il
i
p
p
i
n
e
s.
A
m
u
lt
i
-
tas
k
in
g
re
se
a
rc
h
a
d
v
o
c
a
te
a
n
d
a
ss
o
c
iate
p
ro
fe
ss
o
r
wi
th
tec
h
n
ica
l
e
x
p
e
rti
s
e
in
re
se
a
rc
h
,
c
o
m
p
u
ter
sc
ien
c
e
,
a
n
d
i
n
fo
rm
a
ti
o
n
tec
h
n
o
lo
g
y
d
isc
ip
li
n
e
s.
S
h
e
is
c
u
rre
n
tl
y
se
rv
in
g
a
s
a
n
IT
P
r
o
g
ra
m
Co
o
rd
in
a
t
o
r.
As
a
re
se
a
rc
h
a
d
v
o
c
a
te,
sh
e
m
a
d
e
p
a
ten
ted
I
T
-
re
late
d
i
n
v
e
n
ti
o
n
s,
p
re
se
n
ted
,
a
n
d
p
u
b
l
ish
e
d
d
if
fe
re
n
t
re
se
a
rc
h
p
a
p
e
rs
b
o
t
h
n
a
ti
o
n
a
l
a
n
d
in
ter
n
a
ti
o
n
a
l
in
so
ftwa
re
a
n
d
c
o
m
p
u
ti
n
g
tr
a
c
k
s,
a
n
d
h
o
l
d
s
d
iffere
n
t
c
o
p
y
ri
g
h
ted
s
o
ftwa
re
a
n
d
o
p
e
ra
t
io
n
a
l
m
a
n
u
a
ls,
a
n
d
ICT
b
o
o
k
s
wh
ich
a
ll
re
c
o
g
n
ize
d
a
n
d
su
b
m
it
ted
a
t
th
e
P
h
il
i
p
p
i
n
e
Na
ti
o
n
a
l
Li
b
ra
ry
a
n
d
I
n
tellec
tu
a
l
P
ro
p
e
rt
y
Offic
e
o
f
th
e
P
h
il
i
p
p
i
n
e
s
(IP
OPHIL)
.
T
h
e
m
a
in
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
b
io
e
n
g
i
n
e
e
rin
g
,
t
h
e
in
ter
n
e
t
o
f
th
in
g
s
(Io
T),
m
a
c
h
in
e
lea
rn
in
g
,
d
a
ta
m
in
i
n
g
wi
th
a
n
a
ly
ti
c
s,
d
a
ta
sc
ien
c
e
,
a
n
d
n
e
two
r
k
m
a
n
a
g
e
m
e
n
t
a
n
d
in
f
o
rm
a
ti
o
n
s
e
c
u
rit
y
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
rv
p
e
re
a
@c
v
su
-
n
a
ic.ed
u
.
p
h
.
Abi
g
a
e
l
M.
Mi
r
a
n
d
a
a
g
ra
d
u
a
te
o
f
Do
c
to
r
o
f
P
h
i
lo
so
p
h
y
in
Bu
si
n
e
ss
M
a
n
a
g
e
m
e
n
t
m
a
jo
r
in
In
ter
n
a
ti
o
n
a
l
T
o
u
rism
a
n
d
Ho
s
p
it
a
li
t
y
M
a
n
a
g
e
m
e
n
t
a
t
P
h
il
ip
p
i
n
e
Ch
risti
a
n
Un
iv
e
rsit
y
(
P
CU)
M
a
n
il
a
fro
m
2
0
2
1
u
n
d
e
r
th
e
C
HED
S
IKA
P
sc
h
o
lars
h
i
p
.
P
re
se
n
ted
re
se
a
rc
h
in
v
a
rio
u
s
y
e
a
rs
lo
c
a
ll
y
a
n
d
in
tern
a
ti
o
n
a
ll
y
.
T
h
e
m
a
in
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
tec
h
n
o
l
o
g
y
a
c
c
e
p
tan
c
e
m
o
d
e
ls,
c
li
m
a
te
c
h
a
n
g
e
,
a
n
d
b
u
sin
e
ss
m
a
n
a
g
e
m
e
n
t
c
o
n
c
e
p
ts
a
n
d
d
isc
ip
li
n
e
s.
S
h
e
c
a
n
b
e
c
o
n
ta
c
ted
a
t
e
m
a
il
:
a
m
m
iran
d
a
@c
v
su
-
n
a
ic.ed
u
.
p
h
.
Evaluation Warning : The document was created with Spire.PDF for Python.