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.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
,
p
p
.
44
~
55
I
SS
N:
2
2
5
2
-
8
9
3
8
,
DOI
: 1
0
.
1
1
5
9
1
/ijai.v
15
.i
1
.
p
p
44
-
55
44
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
a
i
.
ia
esco
r
e.
co
m
Securing
clo
ud
data
wit
h
ma
chine
l
ea
rning
:
t
r
ends,
g
a
ps, and
performa
nce m
et
rics
B
les
s
ing
I
f
eo
luwa
O
m
o
g
behin
,
T
s
h
ia
m
o
Sig
wele
,
T
ha
bo
Sem
o
ng
,
Ao
ne
M
a
eng
e,
Z
hiv
k
o
Nedev
,
H
lo
m
a
ni H
lo
m
a
ni
D
e
p
a
r
t
me
n
t
o
f
C
o
mp
u
t
i
n
g
a
n
d
I
n
f
o
r
m
a
t
i
c
s,
B
o
t
sw
a
n
a
I
n
t
e
r
n
a
t
i
o
n
a
l
U
n
i
v
e
r
si
t
y
o
f
S
c
i
e
n
c
e
a
n
d
Te
c
h
n
o
l
o
g
y
,
P
a
l
a
p
y
e
,
B
o
t
sw
a
n
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Sep
2
4
,
2
0
2
5
R
ev
is
ed
No
v
2
4
,
2
0
2
5
Acc
ep
ted
Dec
1
5
,
2
0
2
5
Th
e
in
c
re
a
sin
g
re
li
a
n
c
e
o
n
c
lo
u
d
c
o
m
p
u
t
in
g
h
a
s
ra
ise
d
sig
n
ifi
c
a
n
t
c
o
n
c
e
rn
s
a
b
o
u
t
t
h
e
se
c
u
rit
y
o
f
d
a
ta
a
c
c
e
ss
c
o
n
tr
o
l,
a
s
trad
it
io
n
a
l
m
o
d
e
ls
a
re
in
su
fficie
n
t
in
m
a
n
a
g
in
g
t
h
e
d
y
n
a
m
ic
a
n
d
lar
g
e
-
sc
a
le
n
a
tu
re
o
f
c
lo
u
d
e
n
v
iro
n
m
e
n
ts.
Th
is
re
v
iew
e
v
a
lu
a
tes
m
a
c
h
in
e
lea
rn
in
g
(M
L)
-
b
a
se
d
a
p
p
r
o
a
c
h
e
s
to
imp
r
o
v
e
c
l
o
u
d
d
a
ta
se
c
u
rit
y
,
wit
h
a
p
a
rti
c
u
lar
fo
c
u
s
o
n
a
d
v
a
n
c
e
m
e
n
ts
in
a
n
o
m
a
ly
d
e
tec
ti
o
n
a
n
d
i
n
sid
e
r
th
re
a
t
p
re
v
e
n
ti
o
n
.
De
e
p
lea
rn
i
n
g
(DL)
m
o
d
e
ls em
e
rg
e
a
s th
e
m
o
st
d
o
m
in
a
n
t,
u
ti
li
z
e
d
b
y
4
7
%
o
f
t
h
e
stu
d
ies
d
u
e
t
o
t
h
e
ir
s
u
p
e
rio
r
a
b
il
it
y
to
p
ro
c
e
ss
larg
e
d
a
tas
e
ts
a
n
d
a
d
a
p
t
t
o
re
a
l
-
ti
m
e
e
n
v
iro
n
m
e
n
ts.
Ra
n
d
o
m
fo
re
st
m
o
d
e
ls
a
re
a
lso
p
ro
m
i
n
e
n
t,
b
e
in
g
a
d
o
p
ted
in
2
0
%
o
f
t
h
e
stu
d
ies
fo
r
th
e
ir
stro
n
g
p
e
rfo
rm
a
n
c
e
in
a
n
o
m
a
ly
d
e
tec
ti
o
n
a
n
d
c
a
teg
o
riza
ti
o
n
.
Ten
s
o
rF
l
o
w sta
n
d
s
o
u
t
a
s
th
e
m
o
st
wi
d
e
ly
u
se
d
to
o
l,
fe
a
t
u
rin
g
i
n
n
e
a
rly
3
7
%
o
f
t
h
e
re
v
iew
e
d
wo
rk
s
,
wh
il
e
d
a
tas
e
ts
li
k
e
Am
a
z
o
n
Ac
c
e
ss
a
n
d
c
o
m
p
u
ter
e
m
e
rg
e
n
c
y
re
sp
o
n
se
tea
m
(CERT
)
a
re
e
m
p
lo
y
e
d
in
2
0
%
a
n
d
1
3
%
o
f
t
h
e
re
se
a
rc
h
,
re
sp
e
c
ti
v
e
ly
.
An
o
m
a
ly
d
e
tec
ti
o
n
a
n
d
p
re
v
e
n
ti
o
n
a
re
c
rit
i
c
a
l
p
rio
rit
ies
,
a
c
c
o
u
n
ti
n
g
f
o
r
4
1
.
2
%
o
f
th
e
re
se
a
rc
h
o
b
jec
ti
v
e
s.
H
o
we
v
e
r,
g
a
p
s
re
m
a
in
,
wi
th
2
1
.
7
%
o
f
t
h
e
st
u
d
ies
n
o
t
in
g
a
d
v
e
rsa
rial
v
u
ln
e
ra
b
i
li
ti
e
s
a
n
d
1
3
%
i
d
e
n
ti
f
y
in
g
li
m
it
a
ti
o
n
s
i
n
d
a
tas
e
t
d
i
v
e
rsity
.
Th
e
re
v
iew
re
c
o
m
m
e
n
d
s fu
rth
e
r
d
e
v
e
lo
p
m
e
n
t
o
f
M
L
m
o
d
e
ls t
o
a
d
d
r
e
ss
th
e
s
e
c
h
a
ll
e
n
g
e
s,
e
x
p
a
n
d
i
n
g
d
a
tas
e
t
d
iv
e
rsity
,
a
n
d
imp
r
o
v
in
g
re
a
l
-
ti
m
e
m
o
n
it
o
r
in
g
tec
h
n
iq
u
e
s to
e
n
h
a
n
c
e
c
lo
u
d
d
a
ta
se
c
u
rit
y
.
K
ey
w
o
r
d
s
:
Ad
v
er
s
ar
ial
attac
k
s
C
lo
u
d
co
m
p
u
tin
g
s
ec
u
r
ity
Data
ac
ce
s
s
co
n
tr
o
l
Dee
p
lear
n
in
g
Ma
ch
in
e
lear
n
in
g
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
:
T
s
h
iam
o
Sig
wele
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
Scie
n
ce
an
d
I
n
f
o
r
m
atio
n
Sy
s
tem
s
B
o
ts
wan
a
I
n
ter
n
atio
n
al
Un
iv
e
r
s
ity
o
f
Scien
ce
an
d
T
ec
h
n
o
lo
g
y
Plo
t 1
0
0
7
1
,
B
o
s
eja,
Palap
y
e,
B
o
ts
wan
a
E
m
ail: sig
wele
t@
b
iu
s
t.a
c.
b
w
1.
I
NT
RO
D
UCT
I
O
N
I
n
th
e
r
a
p
id
ly
e
v
o
lv
in
g
lan
d
s
c
ap
e
o
f
cl
o
u
d
c
o
m
p
u
tin
g
,
s
ec
u
r
in
g
d
ata
ac
ce
s
s
h
as
b
ec
o
m
e
a
p
ar
am
o
u
n
t
co
n
ce
r
n
[
1
]
,
[
2
]
.
As
o
r
g
an
izat
io
n
s
in
cr
ea
s
in
g
ly
m
ig
r
ate
th
ei
r
o
p
er
atio
n
s
to
clo
u
d
en
v
ir
o
n
m
en
ts
,
th
e
n
ee
d
f
o
r
r
o
b
u
s
t
d
ata
ac
ce
s
s
co
n
tr
o
l
m
e
ch
an
is
m
s
is
m
o
r
e
c
r
itical
th
a
n
ev
er
[
3
]
,
[
4
]
.
I
n
clo
u
d
co
m
p
u
tin
g
,
d
ata
ac
ce
s
s
co
n
tr
o
l
r
e
f
er
s
to
th
e
p
r
o
ce
s
s
es
an
d
tech
n
o
lo
g
ies
u
s
ed
to
e
n
s
u
r
e
th
at
o
n
l
y
au
th
o
r
ized
u
s
er
s
h
av
e
ac
ce
s
s
to
th
e
d
ata
s
to
r
ed
in
th
e
clo
u
d
[
5
]
,
[
6
]
.
T
h
is
in
clu
d
es
ev
e
r
y
th
in
g
f
r
o
m
au
th
en
ticatin
g
u
s
er
s
,
au
th
o
r
i
zin
g
th
em
t
o
ac
ce
s
s
s
p
ec
if
ic
d
ata,
m
o
n
ito
r
in
g
a
n
d
au
d
itin
g
ac
ce
s
s
to
en
s
u
r
e
n
o
u
n
au
th
o
r
ize
d
ac
ce
s
s
o
cc
u
r
s
[
7
]
,
[
8
]
.
I
t
is
a
tec
h
n
iq
u
e
u
s
ed
to
r
e
g
u
late
u
s
er
ac
ce
s
s
to
d
ata
ass
ets
in
th
e
clo
u
d
s
to
r
ag
e
s
y
s
tem
[
9
]
,
th
is
is
b
ec
au
s
e
a
s
in
g
le
u
n
au
th
o
r
ized
ac
ce
s
s
to
clo
u
d
d
ata
ca
n
m
ak
e
a
g
lo
b
al
h
ea
d
lin
e.
On
e
p
r
o
m
in
en
t
a
n
d
r
ec
en
t e
x
a
m
p
le
o
f
f
ailed
ac
ce
s
s
co
n
tr
o
l
in
clo
u
d
s
y
s
tem
was
th
e
Sy
n
n
o
v
is
attac
k
.
On
J
u
n
e
3
,
2
0
2
4
,
Sy
n
n
o
v
is
a
p
ath
o
lo
g
y
s
er
v
ice
p
r
o
v
id
e
r
f
o
r
m
u
ltip
le
Natio
n
al
Hea
lth
Ser
v
ice
(
NHS)
tr
u
s
t
in
Un
ited
Kin
g
d
o
m
(
UK)
ex
p
er
ie
n
ce
d
a
r
a
n
s
o
m
war
e
attac
k
[
1
0
]
,
th
e
Qilin
r
an
s
o
m
g
an
g
l
o
ck
ed
u
p
th
e
p
atien
t
d
ata
s
to
r
ed
o
n
th
e
clo
u
d
s
er
v
er
,
o
f
f
er
in
g
a
s
ev
er
e
s
er
v
ice
d
i
s
r
u
p
tio
n
.
T
h
e
Hea
lth
I
n
s
u
r
a
n
ce
Po
r
tab
ilit
y
an
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
S
ec
u
r
in
g
clo
u
d
d
a
ta
w
ith
ma
c
h
in
e
lea
r
n
in
g
:
t
r
en
d
s
,
g
a
p
s
,
a
n
d
…
(
B
less
in
g
I
feo
lu
w
a
Omo
g
b
eh
in
)
45
Acc
o
u
n
tab
ilit
y
Act
(
HI
PAA)
jo
u
r
n
al
r
e
p
o
r
ted
th
at
1
,
1
3
4
s
ch
ed
u
le
d
o
p
er
atio
n
s
wer
e
ca
n
ce
lled
,
2
,
1
9
4
o
u
tp
atien
ts
’
ap
p
o
in
tm
e
n
ts
in
th
e
f
ir
s
t
th
ir
tee
n
d
ay
s
wer
e
r
esch
ed
u
led
a
n
d
m
o
r
e
th
an
3
0
0
m
illi
o
n
p
atien
t
in
ter
ac
tio
n
in
f
o
r
m
atio
n
wer
e
l
ea
k
ed
to
th
e
d
ar
k
web
,
t
h
ese
c
o
n
s
is
t
o
f
h
i
g
h
ly
co
n
f
i
d
en
tial
d
ata
s
u
ch
as
r
esu
lt
f
o
r
h
u
m
an
im
m
u
n
o
d
ef
icien
cy
v
ir
u
s
(
HI
V)
an
d
ca
n
ce
r
,
b
lo
o
d
g
r
o
u
p
test
r
esu
lts
an
d
m
o
r
e
[
1
1
]
.
NHS
E
n
g
lan
d
an
d
Sy
n
n
o
v
is
ca
p
tu
r
e
d
in
th
eir
r
e
p
o
r
t
th
at
th
e
in
cid
e
n
t
co
s
t
a
f
in
an
cial
d
am
ag
e
o
f
3
2
.
7
m
illi
o
n
E
u
r
o
[
1
0
]
,
[
1
2
]
.
T
h
e
im
p
licatio
n
s
o
f
th
is
attac
k
wer
e
s
u
b
s
tan
tial,
th
e
r
eb
y
e
m
p
h
asizin
g
th
e
n
ec
ess
ity
f
o
r
g
r
an
u
lar
d
ata
ac
ce
s
s
co
n
tr
o
l
m
ec
h
an
is
m
s
in
clo
u
d
-
b
ased
s
y
s
tem
s
.
A
s
ig
n
if
ican
t
ad
v
an
ce
m
e
n
t
wo
u
ld
ar
is
e,
ex
p
lo
r
in
g
r
esear
ch
in
v
o
lv
in
g
ML
-
d
r
i
v
en
d
ata
ac
c
ess
co
n
tr
o
l in
clo
u
d
co
m
p
u
tin
g
.
Ma
ch
in
e
lear
n
in
g
(
ML
)
is
an
ar
ea
o
f
ar
tific
ial
in
tellig
en
ce
(
AI
)
co
n
ce
r
n
e
d
with
d
esig
n
in
g
alg
o
r
ith
m
s
th
at
en
ab
le
c
o
m
p
u
ter
s
to
lear
n
au
to
n
o
m
o
u
s
ly
f
r
o
m
ex
p
er
ien
c
e
an
d
ad
ap
t t
h
eir
b
eh
av
io
r
ac
c
o
r
d
in
g
l
y
[
1
3
]
,
[
1
4
]
.
Sin
ce
ML
s
y
s
tem
s
ar
e
in
h
er
en
tly
ad
ap
tiv
e,
th
ey
r
ef
i
n
e
th
eir
u
n
d
er
s
tan
d
i
n
g
as n
ew
d
ata
is
i
n
tr
o
d
u
ce
d
[
1
5
]
. ML
alg
o
r
ith
m
s
ar
e
tr
ain
ed
o
n
ab
u
n
d
an
t
f
lo
w
o
f
d
ata
g
ath
er
ed
o
v
e
r
tim
e,
an
d
th
ey
u
s
e
th
is
d
ata
to
id
en
tify
p
atter
n
s
an
d
m
ak
e
p
r
ed
ictio
n
s
ab
o
u
t n
e
w
d
ata
[
1
6
]
,
[
1
7
]
.
I
n
th
e
co
n
te
x
t o
f
clo
u
d
d
ata
s
ec
u
r
ity
an
d
a
cc
ess
m
an
ag
em
en
t,
ML
ca
n
b
e
u
s
ed
f
o
r
r
ea
l
tim
e
t
h
r
ea
t
d
etec
tio
n
[
1
8
]
,
p
atter
n
r
e
co
g
n
itio
n
,
a
n
o
m
aly
d
etec
tio
n
[
1
9
]
,
lo
g
m
o
n
ito
r
in
g
[
2
0
]
,
a
n
d
b
eh
av
i
o
r
al
an
aly
s
is
.
T
h
i
s
r
e
v
ie
w
p
r
o
v
i
d
es
a
c
o
m
p
r
e
h
e
n
s
i
v
e
a
n
al
y
s
is
o
f
t
h
e
a
p
p
li
ca
t
i
o
n
o
f
M
L
m
o
d
e
l
s
i
n
d
a
ta
s
ec
u
r
i
t
y
a
n
d
a
c
c
e
s
s
c
o
n
t
r
o
l
w
it
h
i
n
cl
o
u
d
c
o
m
p
u
t
i
n
g
e
n
v
i
r
o
n
m
e
n
t
s
,
f
o
c
u
s
i
n
g
o
n
c
h
a
l
l
e
n
g
es
,
a
d
v
a
n
c
e
m
e
n
ts
,
a
n
d
f
u
t
u
r
e
r
es
e
a
r
c
h
d
i
r
e
c
t
i
o
n
s
.
T
h
e
l
it
e
r
a
t
u
r
e
r
e
v
e
a
l
s
s
i
g
n
i
f
i
c
a
n
t
g
a
p
s
,
i
n
c
l
u
d
in
g
v
u
l
n
e
r
a
b
i
l
i
t
y
t
o
a
d
v
e
r
s
a
r
ia
l
a
t
t
a
c
k
s
,
d
a
t
as
e
t
l
i
m
i
t
at
i
o
n
s
,
a
n
d
c
o
m
p
u
t
a
ti
o
n
a
l
i
n
e
f
f
i
c
i
e
n
c
i
es
.
T
h
is
r
e
v
i
e
w
i
s
o
r
g
a
n
i
z
e
d
i
n
t
o
t
h
r
e
e
m
a
i
n
s
e
c
ti
o
n
s
:
T
r
a
d
i
ti
o
n
a
l
a
c
c
ess
c
o
n
t
r
o
l
m
e
c
h
a
n
i
s
m
s
,
M
L
-
b
as
ed
a
c
c
e
s
s
c
o
n
t
r
o
l
m
o
d
e
l
s
,
a
n
d
p
e
r
f
o
r
m
a
n
c
e
e
v
a
l
u
a
t
i
o
n
m
e
t
r
i
cs
.
T
h
e
c
o
n
t
r
i
b
u
t
i
o
n
s
o
f
t
h
i
s
r
e
v
i
e
w
a
r
e
:
i
)
t
h
e
s
t
u
d
y
d
e
t
er
m
i
n
e
s
g
a
p
s
as
s
o
ci
a
t
e
d
w
it
h
c
u
r
r
e
n
t
a
p
p
r
o
a
c
h
e
s
i
n
cl
o
u
d
c
o
m
p
u
t
i
n
g
a
c
c
es
s
c
o
n
t
r
o
l
s
u
c
h
a
s
a
d
v
e
r
s
a
r
i
a
l
v
u
l
n
e
r
a
b
il
i
t
i
es
,
d
at
a
s
e
t
li
m
i
ta
t
i
o
n
s
,
a
n
d
c
o
m
p
u
t
a
t
i
o
n
a
l
i
n
e
f
f
i
c
ie
n
c
i
es
,
a
n
d
g
i
v
e
s
f
u
t
u
r
e
d
i
r
e
c
t
i
o
n
s
;
ii
)
t
h
e
s
t
u
d
y
i
d
e
n
t
i
f
ie
d
a
n
d
r
e
c
o
m
m
e
n
d
e
d
k
e
y
M
L
r
e
s
e
a
r
c
h
d
at
a
s
et
s
a
n
d
t
o
o
ls
,
m
o
s
t
a
d
o
p
t
e
d
a
n
d
M
L
m
o
d
e
l
s
,
k
e
y
e
v
a
l
u
a
ti
o
n
m
e
t
r
i
cs
s
u
i
t
a
b
l
e
f
o
r
cl
o
u
d
d
a
t
a
a
c
c
es
s
co
n
t
r
o
l
;
i
i
i
)
t
h
e
s
t
u
d
y
r
e
v
i
ew
s
,
an
a
l
y
s
es
a
n
d
d
e
d
u
c
e
s
p
a
t
t
e
r
n
s
,
i
n
s
i
g
h
t
s
a
n
d
t
r
e
n
d
s
o
n
ML
-
b
a
s
e
d
a
c
c
e
s
s
c
o
n
t
r
o
l
m
o
d
e
l
s
u
s
e
d
i
n
a
c
c
es
s
c
o
n
t
r
o
l
;
a
n
d
i
v
)
t
h
e
r
e
v
i
e
w
i
d
e
n
t
i
f
i
es
a
n
d
r
e
c
o
m
m
e
n
d
s
d
e
ep
l
e
a
r
n
i
n
g
(
D
L
)
a
t
4
7
%
li
t
e
r
a
t
u
r
e
a
d
o
p
t
i
o
n
a
n
d
r
a
n
d
o
m
f
o
r
e
s
t
(
R
F
)
at
2
0
%
a
d
o
p
t
i
o
n
a
s
t
h
e
m
o
s
t
s
u
i
t
a
b
l
e
M
L
m
o
d
e
ls
f
o
r
c
l
o
u
d
d
a
t
a
a
c
c
ess
c
o
n
t
r
o
l
.
T
h
e
s
t
r
u
ct
u
r
e
o
f
t
h
i
s
a
r
t
ic
l
e
i
s
as
f
o
l
l
o
w
s
.
S
e
ct
i
o
n
1
i
s
t
h
e
i
n
t
r
o
d
u
c
t
i
o
n
.
I
n
s
e
c
t
i
o
n
2
,
t
h
e
l
i
te
r
a
tu
r
e
r
e
v
i
e
w
a
p
p
r
o
a
c
h
m
e
t
h
o
d
o
l
o
g
y
i
s
p
r
e
s
e
n
t
e
d
.
I
n
s
e
c
t
i
o
n
3
,
w
e
p
r
es
e
n
t
a
n
d
c
o
m
p
r
e
h
e
n
s
i
v
e
l
y
a
n
a
l
y
z
e
th
e
t
r
a
d
i
t
i
o
n
a
l
cl
o
u
d
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
m
o
d
e
l
s
.
I
n
s
e
c
t
i
o
n
4
,
w
e
p
r
e
s
e
n
t
a
n
d
p
e
r
f
o
r
m
s
o
m
e
a
n
a
l
y
s
is
o
n
t
h
e
M
L
b
a
s
e
d
c
l
o
u
d
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
m
o
d
e
l
s
.
Se
c
t
i
o
n
4
p
r
e
s
en
t
s
t
h
e
t
r
e
n
d
s
a
n
d
i
n
s
i
g
h
t
s
f
r
o
m
t
h
e
r
e
v
i
e
w
,
w
h
i
l
e
s
e
c
ti
o
n
5
o
f
f
e
r
s
c
o
n
c
l
u
s
i
o
n
s
.
2.
M
E
T
H
O
D:
RE
V
I
E
W
AP
P
R
O
ACH
T
h
e
ai
m
o
f
t
h
is
r
e
v
ie
w
p
a
p
er
is
t
o
o
f
f
e
r
a
co
m
p
r
eh
e
n
s
i
v
e
u
n
d
e
r
s
ta
n
d
i
n
g
o
f
t
h
e
c
u
r
r
e
n
t
r
e
s
ea
r
c
h
an
d
ad
v
a
n
ce
m
e
n
ts
i
n
ML
te
ch
n
i
q
u
es
f
o
r
d
a
ta
a
cc
ess
c
o
n
tr
o
l
in
cl
o
u
d
co
m
p
u
ti
n
g
en
v
i
r
o
n
m
en
ts
.
T
h
e
r
ev
iew
f
o
c
u
s
es
o
n
r
e
c
e
n
t
p
u
b
lic
ati
o
n
s
f
o
u
n
d
i
n
p
ee
r
-
r
e
v
iew
e
d
j
o
u
r
n
a
ls
,
co
n
f
e
r
e
n
c
e
p
r
o
c
ee
d
i
n
g
s
,
a
n
d
o
t
h
e
r
r
e
p
u
ta
b
le
s
o
u
r
ce
s
.
T
h
e
r
e
v
i
ew
p
r
o
c
ess
ad
h
er
es t
o
a
s
y
s
te
m
a
tic
a
p
p
r
o
ac
h
,
i
n
v
o
l
v
i
n
g
t
h
e
f
o
ll
o
wi
n
g
k
ey
s
t
ep
s
:
i)
L
iter
atu
r
e
s
ea
r
ch
in
g
:
u
tili
zin
g
o
n
lin
e
ac
a
d
em
ic
d
atab
ases
s
u
ch
as
Scien
ce
Dir
ec
t,
Sp
r
in
g
er
L
in
k
,
I
E
E
E
Xp
lo
r
e,
Go
o
g
le
Sch
o
lar
,
an
d
E
ls
ev
ier
’
s
Mo
b
ile
E
d
g
e
C
o
m
p
u
tin
g
j
o
u
r
n
al
to
id
en
tif
y
p
er
t
in
en
t
ar
ticles.
Key
wo
r
d
s
in
clu
d
in
g
“
m
ac
h
in
e
lear
n
in
g
,
”
“
d
ata
ac
ce
s
s
co
n
tr
o
l,
”
“
clo
u
d
co
m
p
u
tin
g
,
”
an
d
“
cl
o
u
d
s
ec
u
r
ity
,
”
wer
e
em
p
lo
y
e
d
.
ii)
I
n
clu
s
io
n
cr
iter
ia:
ar
ticles s
p
ec
if
ically
ad
d
r
ess
in
g
th
e
s
co
p
e
f
r
o
m
5
y
ea
r
s
will b
e
in
clu
d
e
d
.
iii)
E
x
clu
s
io
n
cr
iter
ia:
ar
ticles
n
o
t
f
o
cu
s
ed
o
n
d
ata
ac
ce
s
s
co
n
tr
o
l
o
r
clo
u
d
co
m
p
u
tin
g
o
r
m
ac
h
in
e
lear
n
in
g
,
o
r
th
o
s
e
u
n
r
elate
d
t
o
th
ese
ter
m
s
,
wer
e
ex
clu
d
e
d
.
iv
)
Data
ex
tr
ac
tio
n
:
k
ey
in
f
o
r
m
at
io
n
was
ex
tr
ac
te
d
f
r
o
m
s
elec
ted
ar
ticles,
en
c
o
m
p
ass
in
g
titl
e,
au
th
o
r
s
an
d
p
u
b
licatio
n
y
e
ar
s
,
ML
m
o
d
els,
r
esear
ch
o
b
jectiv
es,
e
v
alu
atio
n
m
etr
ics,
m
o
d
el
lim
itatio
n
s
,
an
d
d
atasets
an
d
to
o
ls
u
tili
ze
d
.
v)
S
y
n
t
h
e
s
i
s
:
e
x
t
r
a
c
t
e
d
i
n
f
o
r
m
a
t
i
o
n
w
a
s
o
r
g
a
n
i
z
e
d
i
n
t
o
a
s
u
m
m
a
r
i
z
e
d
t
a
b
l
e
,
f
o
l
l
o
w
e
d
b
y
t
h
e
a
n
a
l
y
s
i
s
w
i
t
h
t
h
e
e
x
t
r
a
c
t
i
o
n
o
f
t
r
e
n
d
s
a
n
d
p
a
t
t
e
r
n
s
c
o
n
c
e
r
n
i
n
g
t
h
e
m
o
s
t
a
d
o
p
t
e
d
m
o
d
e
l
s
,
o
b
j
e
c
t
i
v
e
s
,
m
e
t
r
i
c
s
,
t
o
o
l
s
,
a
n
d
d
a
t
a
s
e
t
s
.
3.
T
RAD
I
T
I
O
NAL C
L
O
UD
D
AT
A
ACC
E
S
S CO
NT
RO
L
M
O
DE
L
S
T
ab
le
1
s
h
o
ws
v
ar
io
u
s
tr
ad
itio
n
al
clo
u
d
d
ata
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
s
,
s
u
m
m
ar
izin
g
th
ei
r
r
esear
ch
o
b
jectiv
es,
lim
itatio
n
s
,
an
d
t
h
e
to
o
ls
/tech
n
iq
u
es
em
p
lo
y
e
d
f
r
o
m
c
o
n
cu
r
r
en
t
s
tu
d
ies.
T
h
ese
f
r
am
ewo
r
k
s
,
in
clu
d
in
g
in
tr
u
s
io
n
d
etec
tio
n
p
r
ev
en
tio
n
s
y
s
tem
(
I
DPS)
,
asy
m
m
etr
ic
en
cr
y
p
tio
n
m
o
d
el
(
A
E
M)
,
attr
ib
u
te
-
b
ased
ac
ce
s
s
co
n
tr
o
l
(
AB
AC
)
,
an
d
h
y
b
r
id
m
o
d
els,
aim
to
en
h
an
ce
d
ata
s
ec
u
r
ity
an
d
p
r
e
v
en
t
u
n
a
u
th
o
r
ized
ac
ce
s
s
.
T
h
e
tab
le
h
ig
h
lig
h
ts
k
ey
is
s
u
es
s
u
c
h
as
s
u
s
ce
p
tib
ilit
y
to
ad
v
er
s
ar
i
al
attac
k
s
,
im
p
lem
en
tatio
n
ch
a
lle
n
g
es,
s
ca
lab
ilit
y
co
n
ce
r
n
s
,
an
d
u
s
er
ex
p
er
ien
ce
p
r
o
b
lem
s
,
p
r
o
v
id
in
g
co
m
p
r
eh
en
s
iv
e
in
s
ig
h
ts
in
to
th
e
ef
f
ec
tiv
en
ess
an
d
d
r
awb
ac
k
s
o
f
ea
ch
m
o
d
el
in
d
if
f
er
en
t c
lo
u
d
en
v
ir
o
n
m
en
ts
.
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.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
:
44
-
55
46
T
ab
le
1
.
T
r
a
d
itio
n
al
d
ata
ac
ce
s
s
co
n
tr
o
l m
o
d
els
S
/
N
A
u
t
h
o
r
s
a
n
d
y
e
a
r
s
M
L
a
c
c
e
ss
c
o
n
t
r
o
l
m
o
d
e
l
s
M
L
m
o
d
e
l
s res
e
a
r
c
h
o
b
j
e
c
t
i
v
e
s
Ev
a
l
u
a
t
i
o
n
me
t
r
i
c
s
a
n
d
p
e
r
f
o
r
m
a
n
c
e
1.
K
u
mar
e
t
a
l
.
[
2
1
]
I
D
P
S
D
e
t
e
c
t
i
o
n
o
f
ma
l
i
c
i
o
u
s
b
e
h
a
v
i
o
r
o
v
e
r
t
h
e
n
e
t
w
o
r
k
,
En
h
a
n
c
e
t
h
e
c
o
n
f
i
d
e
n
t
i
a
l
i
t
y
,
i
n
t
e
g
r
i
t
y
a
n
d
a
v
a
i
l
a
b
i
l
i
t
y
(
C
I
A
)
.
-
P
r
o
n
e
t
o
a
d
v
e
r
s
a
r
i
a
l
a
t
t
a
c
k
s.
-
A
c
c
e
s
s
d
e
n
i
a
l
t
o
l
e
g
i
t
i
m
a
t
e
u
s
e
r
s
.
2.
B
r
a
n
d
ã
o
[
2
2
]
A
EM
P
r
e
v
e
n
t
i
o
n
o
f
u
n
a
u
t
h
o
r
i
z
e
A
c
c
e
ss
t
o
c
l
o
u
d
s
y
st
e
m.
P
r
o
n
e
t
o
a
d
v
e
r
s
a
r
i
a
l
a
t
t
a
c
k
s.
3.
K
h
a
n
[
2
3
]
A
B
A
C
P
r
o
t
e
c
t
i
o
n
o
f
f
i
l
e
u
p
l
o
a
d
,
f
i
l
e
d
o
w
n
l
o
a
d
a
n
d
f
i
l
e
d
e
l
e
t
i
o
n
.
I
g
n
o
r
e
s
so
f
t
w
a
r
e
a
n
d
n
e
t
w
o
r
k
sec
u
r
i
t
y
.
4.
H
e
e
t
a
l
.
[
2
4
]
A
B
A
C
P
r
e
v
e
n
t
i
o
n
o
f
u
n
a
u
t
h
o
r
i
z
e
d
a
c
c
e
ss
t
o
c
l
o
u
d
e
n
v
i
r
o
n
me
n
t
.
-
U
t
i
l
i
z
e
s si
n
g
l
e
a
u
t
h
o
r
i
t
y
-
P
r
o
n
e
t
o
P
r
i
v
i
l
e
g
e
e
sca
l
a
t
i
o
n
.
5.
B
h
a
t
t
a
n
d
S
a
n
d
h
u
[
2
5
]
A
B
A
C
To
sec
u
r
e
a
c
c
e
sses
a
n
d
d
a
t
a
f
l
o
w
b
e
t
w
e
e
n
v
a
r
i
o
u
s
u
s
e
r
s
i
n
t
h
e
c
y
b
e
r
sp
a
c
e
.
N
e
g
l
e
c
t
s
r
e
a
l
-
w
o
r
l
d
a
p
p
l
i
c
a
t
i
o
n
/
t
e
s
t
i
n
g
6.
P
r
a
n
t
l
e
t
a
l
.
[
2
6
]
A
B
A
C
-
To
p
r
o
v
i
d
e
d
a
t
a
c
o
n
f
i
d
e
n
t
i
a
l
i
t
y
.
-
To
p
r
e
v
e
n
t
i
l
l
e
g
a
l
s
h
a
r
i
n
g
o
f
a
u
t
h
e
n
t
i
c
a
t
i
o
n
k
e
y
s
.
-
C
o
m
p
u
t
a
t
i
o
n
a
l
l
y
i
n
t
e
n
s
i
v
e
.
-
P
o
o
r
u
s
e
r
e
x
p
e
r
i
e
n
c
e
.
7.
K
u
mar
a
n
d
V
e
r
ma
[
2
7
]
A
B
A
C
-
Ti
me
b
o
u
n
d
d
a
t
a
a
c
c
e
ss
.
-
B
i
o
me
t
r
i
c
d
e
f
e
n
se
mec
h
a
n
i
sms
.
-
P
o
o
r
u
s
e
r
e
x
p
e
r
i
e
n
c
e
.
-
U
t
i
l
i
z
e
s si
n
g
l
e
a
u
t
h
o
r
i
t
y
.
8.
C
h
o
u
d
h
a
r
y
a
n
d
S
i
n
g
h
[
2
8
]
H
y
b
r
i
d
mo
d
e
l
:
q
u
e
r
y
-
b
a
se
d
r
o
l
e
a
n
d
a
t
t
r
i
b
u
t
e
a
c
c
e
ss
c
o
n
t
r
o
l
(
Q
R
A
A
C
)
,
R
o
l
e
b
a
s
e
d
a
c
c
e
ss
c
o
n
t
r
o
l
(
R
B
A
C
)
,
t
a
s
k
-
b
a
s
e
d
a
c
c
e
ss
c
o
n
t
r
o
l
(
TB
A
C
)
En
h
a
n
c
e
t
h
e
C
I
A
t
r
i
a
d
o
f
c
l
o
u
d
’
s
d
a
t
a
.
-
A
c
c
e
s
s
d
e
n
i
a
l
t
o
l
e
g
i
t
i
mat
e
u
sers.
-
P
r
i
v
i
l
e
g
e
e
sca
l
a
t
i
o
n
.
9.
D
a
y
a
n
a
a
n
d
R
a
n
i
[
2
9
]
R
B
A
C
-
T
o
p
r
e
v
e
n
t
a
c
c
e
s
s
p
o
l
i
c
y
v
i
o
l
a
t
i
o
n
.
-
P
r
e
v
e
n
t
i
o
n
o
f
d
a
t
a
l
i
n
k
a
g
e
i
n
c
l
o
u
d
e
n
v
i
r
o
n
m
e
n
t
s.
-
L
a
c
k
s
p
r
o
t
e
c
t
i
o
n
a
g
a
i
n
s
t
p
r
i
v
i
l
e
g
e
e
sc
a
l
a
t
i
o
n
.
1
0
.
K
u
mar
e
t
a
l
.
[
3
0
]
H
y
b
r
i
d
mo
d
e
l
:
s
y
mm
e
t
r
i
c
/
a
sy
mm
e
t
r
i
c
c
r
y
p
t
o
g
r
a
p
h
y
P
r
e
v
e
n
t
i
o
n
o
f
ma
l
i
c
i
o
u
s
a
c
c
e
ss
t
o
r
e
so
u
r
c
e
s
i
n
t
h
e
c
l
o
u
d
e
n
v
i
r
o
n
me
n
t
s
.
-
C
o
m
p
u
t
a
t
i
o
n
a
l
l
i
m
i
t
a
t
i
o
n
-
I
mp
l
e
me
n
t
a
t
i
o
n
p
r
o
b
l
e
m
d
u
e
t
o
t
h
e
d
y
n
a
m
i
c
i
t
y
o
f
c
l
o
u
d
p
l
a
t
f
o
r
ms
.
3
.
1
.
Ana
ly
s
is
o
f
t
r
a
ditio
na
l c
lo
ud
co
m
pu
t
ing
da
t
a
a
cc
ess
co
ntr
o
l f
ra
m
ewo
r
k
s
Fig
u
r
e
1
s
h
o
ws
th
at
AB
AC
i
s
th
e
m
o
s
t
u
tili
ze
d
m
o
d
el
f
o
r
d
ata
ac
ce
s
s
co
n
tr
o
l
in
clo
u
d
c
o
m
p
u
tin
g
,
r
ep
r
esen
tin
g
5
0
% o
f
t
h
e
u
s
ag
e
.
T
h
e
h
y
b
r
id
m
o
d
el
f
o
llo
ws
at
2
0
%,
with
R
B
AC
,
I
DPS,
an
d
AE
M
ea
ch
at
1
0
%.
AB
A
C
’
s
d
o
m
in
an
ce
is
attr
ib
u
ted
to
its
s
ca
lab
ilit
y
,
d
y
n
a
m
ic
n
atu
r
e
,
f
le
x
ib
ilit
y
in
attr
ib
u
te
-
b
ased
ac
ce
s
s
,
ef
f
icien
cy
with
attr
ib
u
te
-
b
ase
d
r
u
les
en
g
in
es,
f
in
e
-
g
r
ain
ed
co
n
tr
o
l,
an
d
r
o
b
u
s
t
s
ec
u
r
ity
in
cid
en
t
r
esp
o
n
s
e
ca
p
ab
ilit
ies.
T
h
e
s
e
f
e
at
u
r
e
s
m
ak
e
A
B
AC
p
a
r
ti
c
u
l
a
r
l
y
s
u
i
te
d
f
o
r
m
a
n
a
g
i
n
g
l
a
r
g
e
,
d
y
n
a
m
i
c
c
l
o
u
d
e
n
v
i
r
o
n
m
e
n
t
s
.
3
.
2
.
Ana
ly
s
is
o
f
t
r
a
ditio
na
l t
o
o
ls
f
o
r
clo
ud
co
m
pu
t
ing
da
t
a
a
cc
ess
co
ntr
o
l f
ra
m
ewo
r
k
s
Fig
u
r
e
2
s
h
o
ws
th
e
d
is
tr
ib
u
tio
n
o
f
to
o
ls
a
n
d
tec
h
n
iq
u
es
u
s
ed
i
n
tr
ad
itio
n
al
clo
u
d
c
o
m
p
u
tin
g
d
ata
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
s
.
I
t
in
d
icat
es
th
at
5
0
%
o
f
th
e
liter
atu
r
e
em
p
lo
y
s
th
e
u
s
e
o
f
attr
ib
u
tes,
h
ig
h
lig
h
tin
g
th
eir
im
p
o
r
tan
ce
i
n
clo
u
d
s
ec
u
r
ity
.
C
r
y
p
to
g
r
a
p
h
y
ac
co
u
n
ts
f
o
r
2
0
%,
wh
ile
in
tr
u
s
io
n
d
etec
t
io
n
s
y
s
tem
s
(
I
DS)
,
en
cr
y
p
tio
n
,
a
n
d
p
u
r
p
o
s
e
-
b
ase
d
tr
u
s
t
ac
ce
s
s
co
n
tr
o
l
(
Pb
T
AC
)
ea
ch
m
ak
e
u
p
1
0
%.
T
h
e
d
o
m
in
an
ce
o
f
attr
ib
u
te
-
b
ased
m
eth
o
d
s
u
n
d
er
s
co
r
es
th
eir
ef
f
ec
tiv
e
n
ess
in
p
r
o
v
i
d
in
g
f
in
e
-
g
r
ain
e
d
ac
ce
s
s
co
n
tr
o
l
an
d
e
n
h
a
n
cin
g
s
ec
u
r
ity
in
clo
u
d
e
n
v
ir
o
n
m
en
ts
.
Fig
u
r
e
1
.
An
al
y
s
is
o
f
tr
ad
itio
n
al
clo
u
d
co
m
p
u
tin
g
d
ata
ac
ce
s
s
co
n
tr
o
l f
r
am
ewo
r
k
s
Fig
u
r
e
2
.
An
al
y
s
is
o
f
tr
ad
itio
n
al
to
o
ls
f
o
r
clo
u
d
co
m
p
u
tin
g
d
ata
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
s
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
S
ec
u
r
in
g
clo
u
d
d
a
ta
w
ith
ma
c
h
in
e
lea
r
n
in
g
:
t
r
en
d
s
,
g
a
p
s
,
a
n
d
…
(
B
less
in
g
I
feo
lu
w
a
Omo
g
b
eh
in
)
47
3
.
3
.
Ana
ly
s
is
o
f
f
r
a
m
ewo
rk
o
bje
ct
iv
es in t
ra
ditio
na
l c
lo
ud
co
m
pu
t
ing
da
t
a
a
cc
ess
F
i
g
u
r
e
3
s
h
o
w
s
t
h
e
r
e
s
e
a
r
ch
o
b
j
e
c
t
iv
e
s
i
n
tr
a
d
i
t
io
n
a
l
c
l
o
u
d
c
o
m
p
u
t
i
n
g
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
,
w
i
th
2
8
.
6
%
f
o
c
u
s
in
g
o
n
u
n
au
t
h
o
r
ize
d
a
c
ce
s
s
r
e
s
t
r
i
c
t
io
n
,
t
h
e
m
o
s
t
d
o
m
in
an
t
o
b
j
e
c
t
iv
e
.
E
n
h
a
n
c
in
g
th
e
C
I
A
tr
i
a
d
i
s
t
h
e
f
o
c
u
s
o
f
2
1
.
4
%
,
f
o
l
l
o
w
ed
b
y
a
c
ce
s
s
s
e
c
u
r
i
t
y
an
d
d
et
e
c
t
i
o
n
o
f
m
a
l
i
c
io
u
s
b
e
h
av
i
o
r
a
t
1
4
.
3
%
e
a
c
h
.
P
r
e
v
en
t
i
o
n
o
f
ac
c
e
s
s
p
o
l
ic
y
v
i
o
l
a
t
io
n
,
i
l
l
e
g
a
l
s
h
a
r
in
g
o
f
k
e
y
s
,
an
d
p
r
o
v
i
s
i
o
n
o
f
b
io
m
e
t
r
i
c
d
ef
e
n
s
e
ea
c
h
a
c
c
o
u
n
t
f
o
r
7
.
1
%
.
T
h
i
s
d
i
s
t
r
ib
u
t
i
o
n
e
m
p
h
a
s
i
z
e
s
th
e
c
r
i
t
ic
a
l
im
p
o
r
t
a
n
c
e
o
f
r
o
b
u
s
t
a
c
c
e
s
s
co
n
t
r
o
l
m
ea
s
u
r
e
s
i
n
e
n
s
u
r
in
g
c
l
o
u
d
d
a
ta
s
e
c
u
r
i
t
y
an
d
in
t
eg
r
i
t
y
.
3
.
4
.
Ana
ly
s
is
o
f
f
r
a
m
ewo
rk
g
a
ps
in t
ra
ditio
na
l c
lo
ud
co
m
pu
t
ing
da
t
a
a
cc
ess
co
ntr
o
l
F
i
g
u
r
e
4
s
h
o
w
s
th
e
r
e
s
e
ar
ch
l
i
m
i
ta
t
i
o
n
s
in
tr
a
d
i
t
io
n
a
l
c
l
o
u
d
co
m
p
u
t
in
g
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
f
r
a
m
e
w
o
r
k
s
.
T
h
e
m
o
s
t
s
i
g
n
if
i
c
a
n
t
l
i
m
i
ta
t
i
o
n
i
s
v
u
l
n
e
r
ab
i
l
i
t
y
to
a
d
v
e
r
s
ar
i
a
l
a
t
t
a
ck
s
,
a
f
f
e
c
t
in
g
2
0
%
o
f
t
h
e
r
ev
i
e
w
ed
l
i
t
e
r
a
t
u
r
e
.
C
o
m
p
u
ta
t
i
o
n
a
l
i
n
t
en
s
i
t
y
,
p
o
o
r
u
s
e
r
ex
p
er
i
e
n
c
e
,
an
d
r
e
l
ia
n
c
e
o
n
a
s
in
g
l
e
a
u
t
h
o
r
i
ty
e
a
ch
a
cc
o
u
n
t
f
o
r
1
3
.
3
%
.
O
th
e
r
l
i
m
i
t
a
t
io
n
s
,
e
a
c
h
a
t
6
.
7
%
,
in
c
lu
d
e
f
o
c
u
s
o
n
t
h
eo
r
e
t
i
c
a
l
f
o
u
n
d
a
t
i
o
n
s
,
p
r
iv
i
l
eg
e
e
s
c
a
la
t
i
o
n
,
n
eg
l
e
c
t
o
f
n
e
t
wo
r
k
/
s
o
f
t
w
a
r
e
s
e
c
u
r
i
t
y
,
an
d
th
e
p
o
t
e
n
t
i
a
l
b
e
n
e
f
i
t
s
o
f
i
n
t
e
g
r
a
t
i
n
g
M
L
.
T
h
e
s
e
l
im
i
t
a
ti
o
n
s
h
i
g
h
l
i
g
h
t
t
h
e
n
e
c
e
s
s
i
t
y
f
o
r
m
o
r
e
r
o
b
u
s
t
,
ef
f
i
c
i
en
t
,
an
d
u
s
e
r
-
f
r
i
e
n
d
l
y
a
c
ce
s
s
c
o
n
tr
o
l
s
o
l
u
t
io
n
s
.
Fig
u
r
e
3
.
An
al
y
s
is
o
f
f
r
am
ewo
r
k
o
b
jectiv
es in
tr
ad
itio
n
al
clo
u
d
co
m
p
u
tin
g
d
ata
ac
ce
s
s
Fig
u
r
e
4
.
An
al
y
s
is
o
f
f
r
am
ewo
r
k
g
ap
s
in
tr
ad
itio
n
al
clo
u
d
co
m
p
u
tin
g
d
ata
ac
ce
s
s
co
n
tr
o
l
4.
M
ACH
I
N
E
L
E
AR
NING
B
A
SE
D
C
L
O
UD
DA
T
A
ACC
E
SS
CO
NT
RO
L
M
O
D
E
L
S
T
ab
le
2
p
r
o
v
i
d
es
a
co
m
p
r
eh
en
s
iv
e
o
v
er
v
iew
o
f
v
ar
io
u
s
ML
m
o
d
els
ap
p
lied
to
d
ata
ac
ce
s
s
co
n
tr
o
l
in
clo
u
d
co
m
p
u
tin
g
en
v
ir
o
n
m
en
t
s
.
I
t
in
clu
d
es
cu
r
r
en
t
k
ey
s
tu
d
i
es
d
etailin
g
th
e
s
p
ec
if
ic
ML
al
g
o
r
ith
m
s
u
s
ed
,
s
u
ch
as
L
ig
h
tGB
M,
m
u
ltil
ay
er
p
er
ce
p
tr
o
n
(
ML
P),
d
ec
is
io
n
tr
ee
s
(
DT
)
,
R
F,
lin
ea
r
r
eg
r
ess
io
n
(
L
R
)
,
d
ee
p
n
e
u
r
al
n
etwo
r
k
s
(
DNN)
,
an
d
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
SVM)
.
T
h
e
tab
le
o
u
tlin
es
ea
ch
s
tu
d
y
'
s
r
esear
ch
o
b
jectiv
es,
ev
alu
atio
n
m
etr
ics,
p
er
f
o
r
m
a
n
ce
o
u
tco
m
es,
a
n
d
lim
itatio
n
s
.
Ad
d
itio
n
ally
,
it
o
u
tlin
es
th
e
d
atasets
an
d
to
o
ls
u
tili
ze
d
in
th
ese
s
tu
d
ies,
h
ig
h
lig
h
tin
g
th
e
ad
v
an
ce
m
e
n
ts
an
d
c
h
allen
g
es
in
im
p
lem
en
tin
g
ML
f
o
r
en
h
a
n
cin
g
d
ata
ac
ce
s
s
s
ec
u
r
ity
in
clo
u
d
s
y
s
tem
s
.
T
h
is
s
u
m
m
ar
y
aid
s
in
u
n
d
er
s
tan
d
in
g
th
e
cu
r
r
en
t
s
tate
an
d
f
u
t
u
r
e
d
ir
ec
tio
n
s
o
f
ML
-
d
r
iv
en
clo
u
d
s
ec
u
r
ity
r
es
ea
r
ch
.
T
h
e
tab
le
will
b
e
co
m
p
r
eh
en
s
iv
ely
an
al
y
ze
d
in
th
e
s
u
b
s
eq
u
en
t
s
ec
tio
n
s
h
ig
h
lig
h
tin
g
tr
en
d
s
,
p
atter
n
s
a
n
d
in
s
ig
h
ts
.
T
h
e
f
o
llo
win
g
s
ec
tio
n
s
p
r
esen
t
an
in
-
d
ep
t
h
an
aly
s
is
o
f
th
e
li
ter
atu
r
e
r
ev
iew
in
T
a
b
le
2
.
T
h
is
s
ec
tio
n
p
r
o
v
id
es
d
etailed
d
is
cu
s
s
io
n
s
o
f
th
e
m
o
s
t
im
p
lem
en
ted
ML
m
o
d
els
u
s
ed
in
r
elate
d
wo
r
k
s
an
d
th
e
r
ea
s
o
n
s
b
eh
in
d
th
eir
ad
o
p
ti
o
n
.
I
t
also
in
clu
d
es
a
s
u
m
m
ar
y
o
f
r
esear
ch
o
b
jecti
v
es,
s
u
m
m
ar
y
o
f
s
u
m
m
a
r
y
o
f
r
esear
ch
lim
itatio
n
s
,
an
d
th
e
m
o
s
t a
d
o
p
ted
d
atasets
an
d
to
o
ls
.
4
.
1
.
Ana
ly
s
is
o
f
M
L
m
o
dels
a
do
pte
d f
ro
m
lite
r
a
t
ure
As
s
h
o
wn
in
Fig
u
r
e
5
,
au
th
o
r
s
at
d
if
f
er
en
t y
ea
r
s
u
s
ed
ML
m
o
d
els
lik
e
DT
,
DL
,
RF
,
L
R
,
an
d
SVM
to
ca
r
r
ied
o
u
t
th
eir
v
ar
io
u
s
r
esear
ch
o
b
jectiv
es.
T
h
e
ch
ar
t
s
h
o
ws
th
at
DL
is
th
e
m
o
s
t
u
tili
ze
d
M
L
m
o
d
el
i
n
r
elate
d
wo
r
k
s
,
ac
co
u
n
tin
g
f
o
r
4
7
.
0
6
%
.
RF
f
o
llo
ws
at
1
7
.
6
5
%,
with
DT
,
LR
,
an
d
SVM
ea
c
h
at
1
1
.
7
6
%.
T
h
is
i
n
d
icate
s
a
s
tr
o
n
g
p
r
e
f
er
en
ce
f
o
r
DL
d
u
e
to
it
is
ad
v
an
ce
d
ca
p
ab
il
ities
in
h
an
d
lin
g
co
m
p
lex
d
a
ta.
DL
is
id
ea
l
f
o
r
clo
u
d
d
ata
ac
ce
s
s
co
n
tr
o
l
d
u
e
to
it
is
r
ea
l
-
tim
e
d
ata
p
r
o
ce
s
s
in
g
,
f
lex
ib
ilit
y
,
a
n
d
ab
ilit
y
t
o
lea
r
n
co
m
p
lex
p
atter
n
s
[
3
1
]
,
[
3
2
]
.
I
t
ex
ce
ls
in
an
o
m
a
ly
d
etec
tio
n
,
s
ec
u
r
ity
an
al
y
s
is
[
3
3
]
,
a
n
d
cr
ea
tin
g
s
ec
u
r
e
en
c
r
y
p
tio
n
alg
o
r
ith
m
s
,
m
ak
in
g
it c
r
u
cial
f
o
r
p
r
o
tectin
g
ag
ain
s
t u
n
a
u
th
o
r
ize
d
ac
ce
s
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.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
:
44
-
55
48
T
ab
le
2
.
Data
ac
ce
s
s
co
n
tr
o
l
m
o
d
els u
s
in
g
ML
S/
N
A
u
t
h
o
r
s
a
n
d
y
ea
rs
M
L
a
c
c
e
s
s
c
o
n
t
r
o
l
m
o
d
e
l
s
ML
m
o
d
el
s
re
s
ear
ch
o
b
j
e
ct
i
v
e
s
E
v
al
u
a
t
i
o
n
me
t
r
i
c
s
an
d
p
er
fo
r
ma
n
ce
ML
m
o
d
el
l
i
mi
t
a
t
i
o
n
M
L
m
o
d
e
l
s
d
a
t
a
s
e
t
s
a
n
d
t
o
o
l
s
1
M
e
h
m
o
o
d
e
t
a
l
.
[
3
4
]
L
i
g
h
t
G
BM
al
g
o
ri
t
h
m
DT
Cl
o
u
d
i
n
s
i
d
er
/
i
n
t
e
rn
al
t
h
rea
t
d
e
t
ec
t
i
o
n
A
cc
u
r
ac
y
:
9
7
%
,
Prec
i
s
i
o
n
ra
t
e
:
9
7
%
,
F1
s
c
o
re
:
0
.
9
5
,
Reca
l
l
:
8
3
%
-
Ig
n
o
re
s
b
e
h
a
v
i
o
r
al
b
i
o
met
ri
c
a
t
t
ac
k
.
D
a
t
a
s
e
t
s
:
CE
R
T
d
a
t
a
s
et
s
.
T
o
o
l
s
:
N
o
t
s
p
ec
i
fi
ed
2
K
a
n
a
k
e
r
e
t
a
l
.
[
3
5
]
-
Mu
l
t
i
l
a
y
er
p
erc
ep
t
r
o
n
al
g
o
ri
t
h
m
DNN
-
Reg
res
s
i
o
n
mo
d
e
l
Prev
en
t
i
o
n
a
n
d
d
e
t
ec
t
i
o
n
o
f
ma
l
i
ci
o
u
s
acce
s
s
t
o
cl
o
u
d
s
t
o
r
ag
e
s
y
s
t
em
R
e
c
a
l
l
:
(
9
5
.
9
%
)
,
A
c
c
u
r
a
c
y
:
(
9
5
.
8
6
%
)
,
P
r
e
c
i
s
i
o
n
r
a
t
e
:
(
9
5
.
9
%
)
,
F
-
m
e
a
s
u
r
e
:
(
0
.
9
5
5
)
,
R
O
C
:
(
9
7
.
1
)
,
f
a
l
s
e
p
o
s
i
t
i
v
e
r
a
t
e
(
F
P
R
)
:
(
2
9
.
1
%
)
-
A
cc
u
r
ac
y
co
m
p
r
o
m
i
s
e
.
-
D
i
ffer
en
t
v
a
l
i
d
a
t
i
o
n
acc
u
rac
y
.
D
a
t
a
s
e
t
:
1
0
-
f
o
l
d
cro
s
s
-
v
al
i
d
a
t
i
o
n
d
a
t
a
s
et
.
T
o
o
l
s
:
W
e
k
a.
3
K
h
i
l
a
r
e
t
a
l
.
[
3
6
]
DT
al
g
o
ri
t
h
m
T
o
e
n
s
u
re
a
u
t
h
o
ri
z
ed
u
s
er
s
ac
ce
s
s
t
r
u
s
t
e
d
cl
o
u
d
re
s
o
u
r
ces
.
A
cc
u
r
ac
y
:
9
0
.
3
%
,
Prec
i
s
i
o
n
:
9
0
%
,
F1
-
s
c
o
re
:
0
.
9
0
,
T
i
me:
0
.
3
5
,
Reca
l
l
:
9
0
%
,
Ro
o
t
me
an
a
b
s
o
l
u
t
e
erro
r
(R
M
A
E
)
:
3
1
.
1
%
-
Pro
n
e
t
o
o
v
erf
i
t
t
i
n
g
.
-
Co
m
p
u
t
at
i
o
n
al
l
i
mi
t
a
t
i
o
n
.
D
a
t
a
s
e
t
:
A
p
a
c
h
e
s
e
r
v
e
r
l
o
g
f
o
r
d
a
t
a
.
T
o
o
l
s
:
T
en
s
o
rF
l
o
w
,
Sci
k
i
t
l
e
ar
n
4
A
k
o
t
o
a
n
d
S
al
ma
n
[3
7
]
RF
D
e
t
ec
t
i
o
n
an
d
cat
e
g
o
r
i
za
t
i
o
n
o
f
A
n
o
ma
l
i
es
i
n
cl
o
u
d
s
y
s
t
em
s
.
A
cc
u
r
ac
y
:
9
9
%
,
Prec
i
s
i
o
n
r
a
t
e
:
9
3
.
6
%
,
FPR:
1
.
9
%
,
U
n
d
et
ect
i
o
n
(
U
N
D
)
r
at
e
:
0
.
4
%
-
L
o
w
b
ac
k
d
o
o
r
at
t
ac
k
a
cc
u
rac
y
.
-
Fal
s
e
at
t
ac
k
d
e
t
ec
t
i
o
n
-
L
i
mi
t
e
d
d
a
t
a
s
e
t
.
D
a
t
a
s
e
t
:
U
N
S
W
d
a
t
a
s
et
.
T
o
o
l
s
:
n
o
t
Sp
e
ci
f
i
e
d
5
A
f
s
h
ar
et
a
l
.
[
3
8
]
-
LR
al
g
o
ri
t
h
m
-
RF
al
g
o
ri
t
h
m
-
T
o
p
r
o
t
ect
re
s
o
u
rce
s
fro
m
a
u
t
h
o
r
i
ze
d
acce
s
s
re
q
u
e
s
t
s
.
-
T
o
d
e
t
ec
t
a
n
d
p
re
v
e
n
t
i
n
t
er
n
a
l
b
r
eac
h
e
s
A
cc
u
r
ac
y
:
9
9
.
6
2
%
,
T
o
t
a
l
n
u
m
b
e
r
o
f
T
-
v
i
o
l
a
t
i
o
n
:
5
a
n
d
2
,
T
o
t
a
l
n
u
m
b
e
r
o
f
P
-
V
i
o
l
a
t
i
o
n
:
6
7
a
n
d
1
1
-
L
i
mi
t
e
d
ex
t
e
rn
al
t
h
rea
t
d
e
t
ec
t
i
o
n
w
h
i
ch
w
o
u
l
d
res
t
r
i
ct
co
m
p
r
eh
en
s
i
v
e
s
ec
u
r
i
t
y
.
D
a
t
a
s
e
t
:
A
maz
o
n
acce
s
s
s
am
p
l
e
da
t
a
s
et
.
T
o
o
l
s
:
T
e
n
s
o
r
Fl
o
w
6
N
g
u
y
e
n
e
t
a
l
.
[
3
9
]
DNN
-
A
c
c
u
r
a
t
e
d
e
t
e
c
t
i
o
n
a
n
d
p
r
e
v
e
n
t
i
o
n
o
f
m
u
l
t
i
p
l
e
c
l
o
u
d
a
t
t
a
c
k
s
i
n
r
e
a
l
t
i
m
e
w
i
t
h
s
m
a
l
l
c
o
m
p
u
t
a
t
i
o
n
.
A
c
c
u
r
a
c
y
:
9
9
.
9
3
%
,
T
r
u
e
p
o
s
i
t
i
v
e
r
a
t
e
(
T
P
R
)
/
R
e
c
a
l
l
:
9
9
.
5
7
%
,
F
P
R
:
0
.
0
4
,
t
r
u
e
n
e
g
a
t
i
v
e
r
a
t
e
(
T
N
R
)
:
9
9
.
6
%
-
L
ac
k
s
r
o
b
u
s
t
ad
v
er
s
ar
i
a
l
a
t
t
ac
k
d
efe
n
s
e
s
.
D
a
t
a
s
e
t
:
CICI
D
S
2
0
1
7
d
a
t
a
s
et
.
T
o
o
l
s
:
K
er
as
,
T
e
n
s
o
r
Fl
o
w
,
T
-
s
h
ar
k
.
7
L
i
u
e
t
a
l
.
[
4
0
]
RF
al
g
o
ri
t
h
m
-
E
n
h
an
ce
a
cce
s
s
d
ec
i
s
i
o
n
-
m
ak
i
n
g
.
-
T
o
m
ai
n
t
ai
n
s
y
s
t
em
p
erf
o
r
ma
n
ce
.
A
cc
u
r
ac
y
:
9
2
.
6
%
,
T
PR
/
R
eca
l
l
:
9
1
.
6
%
,
Prec
i
s
i
o
n
r
a
t
e
:
9
3
.
4
%
,
F
-
mea
s
u
re
:
0
.
9
2
5
-
Req
u
i
re
s
mo
re
t
ree
s
fo
r
ac
cu
rat
e
p
re
d
i
ct
i
o
n
D
a
t
a
s
e
t
:
A
m
a
z
o
n
a
c
c
e
s
s
d
a
t
a
s
e
t
.
T
o
o
l
s
:
P
y
t
h
o
n
3
.
6
8
N
o
b
i
e
t
a
l
.
[
4
1
]
DL
U
n
a
u
t
h
o
r
i
ze
d
res
t
r
i
ct
i
o
n
t
o
d
at
a
i
n
cl
o
u
d
s
t
o
ra
g
e
T
PR
/
R
eca
l
l
:
9
5
%
,
F
-
mea
s
u
re
:
0
.
9
5
,
Prec
i
s
i
o
n
:
9
5
%
,
FPR:
0
.
0
5
,
A
cc
u
r
ac
y
:
9
5
%
-
A
d
v
ers
ar
i
al
at
t
ac
k
-
Bi
a
s
an
d
h
u
m
an
erro
rs
i
n
t
ra
i
n
i
n
g
d
a
t
a
D
a
t
a
s
e
t
s
:
A
m
a
z
o
n
d
a
t
a
s
e
t
,
s
y
n
t
h
e
t
i
c
T
e
n
s
o
r
F
l
o
w
,
K
e
r
a
s
9
El
-
K
as
s
a
b
i
e
t
a
l
.
[4
2
]
DL
D
e
t
ec
t
i
o
n
o
f
a
n
o
ma
l
i
es
i
n
c
l
o
u
d
w
o
r
k
f
l
o
w
.
A
cc
u
r
ac
y
:
9
6
.
1
4
%
,
Prec
i
s
i
o
n
r
a
t
e
:
9
3
%
,
T
PR
/
R
eca
l
l
:
9
9
%
,
F1
-
s
c
o
re
:
0
.
9
6
-
L
ar
g
e
d
at
a
co
l
l
ect
i
o
n
.
-
Co
m
p
l
e
x
,
Ch
a
l
l
e
n
g
es
.
D
a
t
a
s
e
t
s
:
CO
V
I
D
-
19
.
T
o
o
l
s
:
P
y
t
o
r
ch
an
d
S
ci
k
i
t
-
l
e
ar
n
10
A
l
h
e
e
t
i
e
t
a
l
.
[
4
3
]
SV
M
a
l
g
o
ri
t
h
m
D
e
t
ec
t
i
o
n
an
d
p
re
v
e
n
t
i
o
n
o
f
mal
i
c
i
o
u
s
acce
s
s
A
cc
u
r
ac
y
:
9
9
.
9
2
%
,
Prec
i
s
i
o
n
r
a
t
e
:
9
6
%
,
Reca
l
l
:
9
7
%
,
F1
-
s
c
o
re
:
0
.
9
9
-
Co
m
p
u
t
at
i
o
n
al
-
L
i
mi
t
a
t
i
o
n
D
a
t
a
s
e
t
s
:
CI
D
D
d
a
t
a
s
et
s
)
.
T
o
o
l
s
:
Sc
i
k
i
t
-
l
ear
n
.
11
A
n
a
k
a
t
h
e
t
a
l
.
[
4
4
]
D
ee
p
b
e
l
i
e
f
n
e
u
ra
l
n
e
t
w
o
r
k
Cl
o
u
d
i
n
s
i
d
er
/
i
n
t
e
rn
al
t
h
rea
t
d
e
t
ec
t
i
o
n
A
cc
u
r
ac
y
:
9
9
%
,
F
-
mea
s
u
re
:
0
.
9
8
,
Prec
i
s
i
o
n
:
1
0
0
%
,
Reca
l
l
:
9
9
%
-
R
e
q
u
i
r
e
s
i
n
t
e
n
s
i
v
e
c
o
m
p
u
t
a
t
i
o
n
-
T
i
m
e
c
o
n
s
u
m
i
n
g
.
D
a
t
a
s
e
t
:
O
p
e
n
-
s
o
u
r
ce
d
a
t
a
s
e
t
s
.
T
o
o
l
:
T
e
n
s
o
r
Fl
o
w
12
Ch
e
h
a
b
an
d
Mo
u
ra
d
[4
5
]
DL
D
e
t
ec
t
i
o
n
an
d
Prev
en
t
i
o
n
o
f
mal
i
c
i
o
u
s
acce
s
s
A
cc
u
r
ac
y
:
9
0
%
,
Prec
i
s
i
o
n
:
9
6
%
,
Reca
l
l
:
9
6
%
,
F
-
mea
s
u
re
:
0
.
9
6
-
T
o
o
c
o
m
p
l
ex
t
o
i
m
p
l
eme
n
t
.
-
Mo
d
e
l
n
o
t
s
ca
l
a
b
l
e
.
Sy
n
t
h
e
t
i
c
d
a
t
a
s
e
t
.
T
e
n
s
o
r
Fl
o
w
,
Sc
i
k
i
t
-
l
ear
n
13
J
i
an
g
et
a
l
.
[
4
6
]
DL
A
t
t
a
ck
d
et
ec
t
i
o
n
,
cl
a
s
s
i
f
i
ca
t
i
o
n
a
n
d
p
re
v
e
n
t
i
o
n
.
A
cc
u
r
ac
y
:
9
9
.
2
3
%
,
FPR:
9
.
8
6
,
Reca
l
l
/
T
PR
:
9
9
.
2
3
%
-
L
a
c
k
s
r
o
b
u
s
t
a
d
v
e
r
s
a
r
i
a
l
d
e
f
e
n
s
e
s
.
-
D
a
t
a
s
e
t
l
i
m
i
t
a
t
i
o
n
D
a
t
a
s
e
t
:
K
D
D
9
9
d
a
t
a
s
et
,
T
o
o
l
s
:
T
e
n
s
o
r
Fl
o
w
14
Ferh
i
et
a
l
.
[
4
7
]
DL
D
e
n
i
al
o
f
S
er
v
i
c
e
d
e
t
ec
t
i
o
n
an
d
p
re
v
e
n
t
i
o
n
A
cc
u
r
ac
y
:
9
9
.
9
0
%
,
Prec
i
s
i
o
n
:
9
5
.
6
,
Reca
l
l
:
9
9
.
5
8
,
F
-
mea
s
u
re
:
9
7
.
5
8
-
Co
m
p
u
t
at
i
o
n
al
l
i
mi
t
a
t
i
o
n
.
-
H
i
g
h
t
ra
i
n
i
n
g
t
i
me.
D
a
t
a
s
e
t
:
CS
E
-
C
IC
-
ID
S
2
0
1
8
d
at
as
e
t
.
T
o
o
l
s
:
Sc
i
k
i
t
-
l
ear
n
15
Pad
ma
v
a
t
h
i
et
a
l
.
[4
8
]
SV
M
Mal
i
c
i
o
u
s
i
n
s
i
d
er
t
h
rea
t
d
e
t
ec
t
i
o
n
T
r
u
e
d
e
t
e
ct
i
o
n
ra
t
e
(T
D
R)
:
1
0
0
%
,
Prec
i
s
i
o
n
:
1
0
0
%
,
F
-
mea
s
u
re
:
1
0
0
%
,
T
h
re
s
h
o
l
d
v
a
l
u
e:
5
0
%
-
L
i
mi
t
e
d
d
a
t
a
s
e
t
D
a
t
a
s
e
t
:
C
E
R
T
d
a
t
a
s
et
T
o
o
l
s
:
Py
t
h
o
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
S
ec
u
r
in
g
clo
u
d
d
a
ta
w
ith
ma
c
h
in
e
lea
r
n
in
g
:
t
r
en
d
s
,
g
a
p
s
,
a
n
d
…
(
B
less
in
g
I
feo
lu
w
a
Omo
g
b
eh
in
)
49
Fig
u
r
e
5
.
ML
m
o
d
els ad
o
p
tio
n
o
n
clo
u
d
d
ata
ac
ce
s
s
co
n
tr
o
l
4
.
2
.
Ana
ly
s
is
o
f
M
L
da
t
a
s
et
s
a
do
pte
d f
ro
m lit
er
a
t
ure
Fig
u
r
e
6
illu
s
tr
ates
th
e
m
o
s
t
u
s
ed
d
atasets
in
r
elate
d
wo
r
k
s
,
with
th
e
Am
az
o
n
ac
ce
s
s
s
am
p
le
d
ataset
lead
in
g
at
2
0
%.
T
h
is
is
f
o
llo
wed
b
y
th
e
C
E
R
T
d
ataset
at
1
3
.
3
%,
an
d
s
ev
er
al
d
atasets
lik
e
Ap
ac
h
e
s
er
v
er
l
o
g
d
ata,
UNSW
d
ataset
s
,
1
0
-
f
o
ld
cr
o
s
s
-
v
alid
atio
n
d
at
aset,
C
I
C
I
DS2
0
1
7
,
C
OVI
D
-
1
9
,
C
I
DD,
o
p
en
-
s
o
u
r
ce
d
atasets
,
s
y
n
th
etic
d
atasets
,
KDD9
9
,
a
n
d
C
SE
-
C
I
C
I
DS2
0
1
8
ea
ch
u
s
ed
at
6
.
7
%.
T
h
is
d
is
tr
ib
u
tio
n
in
d
icate
s
a
d
iv
er
s
e
u
s
ag
e
o
f
d
atasets
in
r
esear
ch
,
with
a
s
ig
n
if
ican
t
p
r
ef
er
en
ce
f
o
r
Am
az
o
n
ac
ce
s
s
s
am
p
le
d
at
asets
,
f
o
llo
wed
b
y
C
E
R
T
d
ataset
s
.
Am
az
o
n
ac
ce
s
s
s
am
p
le
d
ataset
p
r
ev
ailed
d
u
e
to
it
is
co
m
p
r
eh
e
n
s
iv
e,
r
ep
r
e
s
en
tativ
e
n
atu
r
e
o
f
r
ea
l
-
wo
r
ld
d
ata
a
n
d
r
elev
an
ce
to
ac
ce
s
s
co
n
tr
o
l
r
u
le
an
d
p
o
licy
[
1
9
]
.
I
t
is
s
tan
d
a
r
d
ized
f
o
r
ea
s
y
c
o
m
p
ar
is
o
n
,
co
m
es
with
d
etailed
d
escr
ip
tio
n
s
,
an
d
is
p
u
b
licly
an
d
f
r
ee
ly
av
ailab
le,
m
ak
in
g
it
ac
ce
s
s
ib
le
an
d
attr
ac
tiv
e
t
o
r
esear
ch
er
s
o
n
a
b
u
d
g
et.
4
.
3
.
Ana
ly
s
is
o
f
M
L
t
o
o
ls
a
d
o
pte
d f
ro
m
lite
r
a
t
ure
Fig
u
r
e
7
illu
s
tr
ates
th
e
d
is
tr
ib
u
tio
n
o
f
ML
to
o
ls
em
p
lo
y
ed
i
n
r
elate
d
s
tu
d
ies
o
n
d
ata
ac
ce
s
s
co
n
tr
o
l.
T
en
s
o
r
Flo
w
em
er
g
es a
s
th
e
m
o
s
t w
id
ely
u
s
ed
f
r
a
m
ewo
r
k
,
a
p
p
ea
r
in
g
in
3
6
.
8
4
%
o
f
th
e
r
ev
i
ewe
d
wo
r
k
s
.
T
h
is
is
f
o
llo
wed
b
y
Scik
it
-
lear
n
at
2
6
.
3
2
%,
wh
ile
b
o
t
h
Ker
as
an
d
P
y
th
o
n
a
r
e
ea
ch
u
tili
ze
d
in
1
0
.
5
3
%
o
f
th
e
s
tu
d
ies.
Py
T
o
r
ch
,
T
-
Sh
ar
k
,
a
n
d
W
ek
a
ar
e
less
f
r
eq
u
en
tly
ad
o
p
ted
,
ea
ch
f
ea
tu
r
in
g
in
5
.
2
6
%
o
f
th
e
c
ases
.
T
h
ese
f
in
d
in
g
s
u
n
d
er
s
co
r
e
T
e
n
s
o
r
Flo
w’
s
p
r
o
m
in
en
ce
in
th
is
ar
ea
o
f
r
esear
ch
.
T
en
s
o
r
Flo
w
ca
n
d
ev
elo
p
s
y
s
t
em
s
to
g
en
er
ate
s
ec
u
r
ity
aler
ts
,
m
o
n
ito
r
an
d
ad
ju
s
t
ac
ce
s
s
p
o
licies,
an
d
m
o
d
if
y
p
r
iv
ileg
es
b
ased
o
n
b
eh
av
io
r
[
3
6
]
,
[
3
8
]
.
C
o
m
p
atib
le
with
Go
o
g
le
C
lo
u
d
,
AW
S,
an
d
Azu
r
e,
it
c
r
ea
tes
ef
f
icien
t
m
o
d
els.
I
t
id
e
n
tifie
s
an
d
b
l
o
ck
s
m
alicio
u
s
ac
tiv
ities
,
p
r
o
ce
s
s
es r
ea
l
-
tim
e
d
ata,
h
an
d
les lar
g
e
d
atasets
,
an
d
ca
teg
o
r
izes d
ata
b
y
s
en
s
itiv
ity
[
4
1
]
.
Fig
u
r
e
6
.
An
al
y
s
is
o
f
ML
-
b
as
ed
clo
u
d
ac
ce
s
s
co
n
tr
o
l d
atasets
ad
o
p
te
d
f
r
o
m
liter
atu
r
e
Fig
u
r
e
7
.
An
al
y
s
is
o
f
ML
-
b
as
ed
clo
u
d
ac
ce
s
s
co
n
tr
o
l to
o
ls
ad
o
p
ted
f
r
o
m
liter
atu
r
e
4
.
4
.
Ana
ly
s
is
o
f
M
L
f
ra
m
ew
o
rk
s
o
bje
ct
iv
es a
do
pte
d f
r
o
m
lite
ra
t
ure
F
i
g
u
r
e
8
s
h
o
ws
t
h
e
v
a
r
i
o
u
s
r
e
s
e
a
r
c
h
o
b
j
e
c
t
i
v
es
a
d
o
p
t
e
d
i
n
t
h
e
l
i
t
e
r
a
t
u
r
e
c
o
n
c
e
r
n
i
n
g
M
L
f
r
am
e
w
o
r
k
s
.
T
h
e
p
r
i
m
a
r
y
f
o
c
u
s
i
s
o
n
a
n
o
m
a
l
i
es
d
e
t
e
ct
i
o
n
a
n
d
p
r
e
v
e
n
tio
n
(
4
1
.
2
%
)
,
i
n
d
i
c
a
t
i
n
g
a
s
i
g
n
if
i
c
a
n
t
e
m
p
h
as
is
o
n
i
d
e
n
t
i
f
y
i
n
g
a
n
d
m
i
t
i
g
a
ti
n
g
u
n
u
s
u
a
l
b
e
h
a
v
i
o
r
s
i
n
cl
o
u
d
e
n
v
i
r
o
n
m
e
n
t
s
.
U
n
a
u
t
h
o
r
i
z
e
d
a
cc
e
s
s
r
e
s
t
r
i
ct
i
o
n
a
n
d
d
e
n
i
a
l
o
f
s
e
r
v
i
c
e
d
e
t
ec
t
i
o
n
a
n
d
p
r
e
v
en
t
i
o
n
e
a
c
h
a
c
c
o
u
n
t
f
o
r
1
7
.
6
%
,
h
i
g
h
l
i
g
h
t
i
n
g
t
h
e
i
m
p
o
r
t
a
n
c
e
o
f
s
a
f
e
g
u
a
r
d
i
n
g
c
l
o
u
d
r
e
s
o
u
r
c
e
s
f
r
o
m
u
n
a
u
t
h
o
r
i
ze
d
ac
c
e
s
s
a
n
d
s
e
r
v
i
c
e
d
i
s
r
u
p
t
i
o
n
s
.
C
l
o
u
d
i
n
s
i
d
e
r
/
i
n
t
e
r
n
a
l
t
h
r
e
a
t
d
e
t
e
c
t
i
o
n
,
e
n
h
a
n
c
i
n
g
d
e
c
i
s
i
o
n
-
m
a
k
i
n
g
i
n
g
r
a
n
t
i
n
g
a
cc
e
s
s
,
b
e
h
a
v
i
o
r
a
l
a
t
t
ac
k
p
r
e
v
e
n
t
io
n
,
a
n
d
p
e
r
f
o
r
m
a
n
c
e
o
p
t
i
m
i
z
a
t
io
n
o
f
c
l
o
u
d
a
c
c
e
s
s
c
o
n
t
r
o
l
e
a
c
h
r
e
p
r
e
s
e
n
t
5
.
9
%
.
T
h
i
s
d
is
t
r
i
b
u
t
i
o
n
u
n
d
e
r
s
c
o
r
es
t
h
e
d
i
v
e
r
s
e
c
h
al
l
e
n
g
e
s
i
n
c
l
o
u
d
s
e
c
u
r
i
t
y
,
wi
t
h
a
p
r
e
d
o
m
i
n
a
n
t
f
o
c
u
s
o
n
a
n
o
m
a
l
y
d
e
t
e
c
t
i
o
n
a
n
d
p
r
e
v
e
n
t
i
v
e
m
e
asu
r
e
s
t
o
e
n
s
u
r
e
r
o
b
u
s
t
d
a
t
a
a
c
ce
s
s
c
o
n
t
r
o
l
.
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.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
:
44
-
55
50
4
.
5
.
Ana
ly
s
is
o
f
M
L
clo
ud
a
cc
ess
co
ntr
o
l g
a
ps
f
ro
m
lite
r
a
t
ure
Fig
u
r
e
9
s
h
o
ws k
ey
r
esear
ch
g
ap
s
in
ML
-
b
ased
clo
u
d
ac
ce
s
s
co
n
tr
o
l,
with
ad
v
e
r
s
ar
ial
v
u
ln
e
r
ab
ilit
ies
at
2
1
.
7
%,
c
o
m
p
lex
ity
at
1
7
.
4
%,
an
d
d
ataset
lim
itatio
n
s
at
1
3
%.
Acc
u
r
ac
y
co
m
p
r
o
m
i
s
e,
o
v
er
f
itti
n
g
,
an
d
co
m
p
u
tatio
n
al
lim
itatio
n
s
ea
ch
ac
co
u
n
t
f
o
r
8
.
7
%.
C
h
alle
n
g
es
in
im
p
le
m
en
tatio
n
,
f
alse
attac
k
d
etec
tio
n
,
b
eh
av
io
r
al
b
io
m
etr
ics attac
k
s
,
an
d
lim
ited
ex
ter
n
al
th
r
ea
t
d
etec
tio
n
ea
ch
r
ep
r
esen
t 4
.
3
%.
T
h
e
m
o
s
t sig
n
if
ican
t
g
ap
is
ad
v
er
s
ar
ial
v
u
ln
er
ab
ilit
ies,
d
u
e
to
th
e
in
cr
ea
s
in
g
s
o
p
h
is
ticatio
n
o
f
attac
k
s
th
at
ca
n
ex
p
lo
it
m
o
d
el
wea
k
n
ess
es a
n
d
th
e
cr
itical
n
e
ed
f
o
r
r
o
b
u
s
t
d
ef
en
s
es
.
Fig
u
r
e
8
.
An
al
y
s
is
o
f
ML
-
b
as
ed
clo
u
d
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
o
b
jectiv
es f
r
o
m
lit
er
atu
r
e
Fig
u
r
e
9
.
An
al
y
s
is
o
f
ML
clo
u
d
ac
ce
s
s
co
n
tr
o
l
g
ap
s
f
r
o
m
liter
atu
r
e
4
.
6
.
P
er
f
o
r
m
a
nces m
et
rics f
o
r
M
L
-
ba
s
ed
clo
u
d da
t
a
a
cc
ess
co
ntr
o
l f
ra
m
ewo
r
k
s
T
a
b
l
e
3
s
h
o
w
s
c
r
i
t
ic
a
l
p
e
r
f
o
r
m
a
n
c
e
m
e
tr
i
c
s
f
o
r
ML
-
b
a
s
e
d
c
l
o
u
d
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
f
r
am
e
w
o
r
k
s
,
s
u
m
m
ar
i
z
i
n
g
th
e
ir
d
e
f
in
i
t
i
o
n
s
,
eq
u
a
t
io
n
s
,
an
d
r
e
f
er
e
n
ce
d
a
u
t
h
o
r
s
.
M
e
tr
i
c
s
l
ik
e
a
c
cu
r
ac
y
,
p
r
e
c
i
s
i
o
n
,
FPR
,
F
-
m
e
a
s
u
r
e
,
r
e
c
a
l
l,
T
N
R
,
R
M
A
E
,
f
a
l
s
e
n
e
g
a
t
iv
e
r
a
t
e
(
F
N
R
)
,
T
D
R
,
r
e
c
e
iv
e
r
-
o
p
e
r
a
t
i
n
g
ch
ar
a
c
t
e
r
i
s
t
i
c
s
(
R
O
C
)
,
t
i
m
e
-
v
io
l
a
t
io
n
(
T
-
v
i
o
la
t
i
o
n
)
,
p
r
i
v
a
c
y
-
v
io
l
a
t
i
o
n
(
P
-
v
io
l
a
t
i
o
n
)
,
t
r
a
in
i
n
g
t
i
m
e
,
an
d
th
r
e
s
h
o
ld
v
a
l
u
e
a
r
e
e
s
s
e
n
t
i
a
l
f
o
r
e
v
a
l
u
a
t
in
g
m
o
d
e
l
e
f
f
e
c
t
iv
e
n
e
s
s
an
d
r
e
l
i
ab
i
l
i
t
y
.
T
h
e
s
e
m
e
t
r
ic
s
h
e
lp
an
a
ly
z
e
an
d
i
d
en
t
i
f
y
p
a
t
te
r
n
s
,
p
r
o
v
i
d
in
g
i
n
s
ig
h
t
s
i
n
to
m
o
d
e
l
p
e
r
f
o
r
m
a
n
c
e
a
n
d
d
a
t
a
p
r
o
t
e
c
t
io
n
,
a
s
d
e
f
in
ed
an
d
s
u
p
p
o
r
t
ed
b
y
v
ar
i
o
u
s
s
t
u
d
i
e
s
.
P
e
r
f
o
r
m
an
c
e
m
e
t
r
ic
s
a
r
e
m
ea
s
u
r
e
s
th
a
t
ar
e
u
s
e
d
t
o
e
v
a
lu
a
t
e
th
e
ef
f
i
ca
c
y
o
f
a
M
L
m
o
d
e
l
i
n
m
ak
i
n
g
p
r
ed
i
c
t
i
o
n
s
[
4
9
]
,
[
5
0
]
.
T
ab
l
e
3
i
l
lu
s
t
r
a
t
e
s
th
e
v
ar
i
o
u
s
m
e
t
r
ic
s
u
s
e
d
t
o
q
u
an
t
i
f
y
h
o
w
e
f
f
ec
t
i
v
e
th
e
d
if
f
er
e
n
t
m
o
d
e
l
s
u
s
e
d
i
n
r
e
l
a
te
d
wo
r
k
s
.
Fig
u
r
e
1
0
s
h
o
ws
th
e
m
o
s
t
ad
o
p
ted
ML
p
er
f
o
r
m
a
n
ce
m
etr
ics
in
r
elate
d
wo
r
k
s
.
ML
-
b
ased
c
lo
u
d
d
ata
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
s
,
with
ac
cu
r
ac
y
b
ei
n
g
t
h
e
m
o
s
t
u
tili
ze
d
at
2
2
%,
f
o
llo
we
d
b
y
p
r
ec
i
s
io
n
at
2
0
%,
r
ec
all
at
1
8
%,
an
d
F
-
m
ea
s
u
r
e
at
1
7
%
.
T
h
ese
m
etr
ics
ar
e
cr
itical
f
o
r
ev
alu
atin
g
th
e
ef
f
ec
tiv
e
n
ess
o
f
d
ata
ac
ce
s
s
co
n
tr
o
l
m
o
d
els
in
clo
u
d
co
m
p
u
tin
g
.
Acc
u
r
ac
y
en
s
u
r
es
co
r
r
ec
t
p
r
e
d
ictio
n
s
an
d
m
in
im
izes
m
is
ca
lcu
latio
n
s
th
at
co
u
ld
lead
to
d
ata
b
r
ea
ch
es
[
4
6
]
,
[
4
7
]
,
[
5
1
]
.
Pre
cisi
o
n
f
o
cu
s
es
o
n
th
e
q
u
ality
o
f
p
o
s
itiv
e
p
r
e
d
ictio
n
s
,
m
in
im
izin
g
f
alse
alar
m
s
[
4
4
]
,
[
4
5
]
.
R
ec
all
ca
p
t
u
r
es
u
n
a
u
th
o
r
ize
d
ac
ce
s
s
ev
en
ts
ef
f
icien
tly
[
4
6
]
,
[
4
7
]
,
an
d
F
-
m
ea
s
u
r
e
b
ala
n
ce
s
p
r
ec
is
io
n
an
d
r
ec
all,
o
p
tim
izin
g
o
v
er
all
m
o
d
el
p
e
r
f
o
r
m
an
ce
[
4
2
]
,
[
4
3
]
.
Fig
u
r
e
1
0
.
Mo
s
t a
d
o
p
te
d
ML
p
er
f
o
r
m
an
ce
m
etr
ics
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
S
ec
u
r
in
g
clo
u
d
d
a
ta
w
ith
ma
c
h
in
e
lea
r
n
in
g
:
t
r
en
d
s
,
g
a
p
s
,
a
n
d
…
(
B
less
in
g
I
feo
lu
w
a
Omo
g
b
eh
in
)
51
T
ab
le
3
.
Per
f
o
r
m
an
ce
s
m
etr
ics
f
o
r
ML
-
b
ased
clo
u
d
d
ata
ac
ce
s
s
co
n
tr
o
l f
r
am
ewo
r
k
s
N
o
.
M
e
t
r
i
c
s
D
e
f
i
n
i
t
i
o
n
Eq
u
a
t
i
o
n
A
u
t
h
o
r
s
1
A
c
c
u
r
a
c
y
M
e
a
su
r
e
s
t
h
e
p
r
e
d
i
c
t
i
v
e
p
o
w
e
r
o
f
t
h
e
mo
d
e
l
e
.
g
.
a
b
i
l
i
t
y
t
o
p
r
e
d
i
c
t
u
n
a
u
t
h
o
r
i
z
e
a
c
c
e
ss
t
o
d
a
t
a
i
n
c
l
o
u
d
st
o
r
a
g
e
s
y
s
t
e
ms
[
5
1
]
.
Th
e
b
e
st
v
a
l
u
e
w
h
e
n
me
a
su
r
e
d
i
n
p
e
r
c
e
n
t
a
g
e
i
s
1
0
0
%
.
+
[
3
4
]
,
[
3
5
]
,
[
3
6
]
,
[
3
7
]
[
3
8
]
,
[
3
9
]
,
[
4
0
]
,
[
4
1
]
[
4
2
]
,
[
4
3
]
,
[
4
4
]
,
[
4
5
]
[
4
6
]
,
[
4
7
]
2
P
r
e
c
i
s
i
o
n
M
e
a
su
r
e
s
t
h
e
q
u
a
l
i
t
y
o
f
a
p
o
s
i
t
i
v
e
p
r
e
d
i
c
t
i
o
n
m
a
d
e
b
y
t
h
e
m
o
d
e
l
t
h
a
t
’
s
,
t
h
e
p
o
r
t
i
o
n
o
f
t
h
e
d
a
t
a
p
o
i
n
t
o
u
r
mo
d
e
l
say
s
e
x
i
st
e
d
i
n
t
h
e
r
e
l
e
v
a
n
t
c
l
a
ss
t
h
a
t
a
r
e
i
n
d
e
e
d
r
e
l
e
v
a
n
t
[
2
0
]
.
+
[
3
4
]
,
[
3
5
]
,
[
3
6
]
,
[
3
7
]
[
3
9
]
,
[
4
0
]
,
[
4
1
]
,
[
4
2
]
[
4
3
]
,
[
4
4
]
,
[
4
5
]
,
[
4
7
]
[
4
8
]
3
F
P
R
a
l
so
k
n
o
w
n
a
s
f
a
l
se
a
l
a
r
m ra
t
e
(
F
A
R
)
M
e
a
s
u
r
e
s
t
h
e
f
r
a
c
t
i
o
n
o
f
n
e
g
a
t
i
v
e
a
c
c
e
s
s
t
h
a
t
a
r
e
m
i
s
c
l
a
s
s
i
f
i
e
d
a
s
p
o
s
i
t
i
v
e
a
c
c
e
s
s
t
o
d
a
t
a
i
n
t
h
e
c
l
o
u
d
s
t
o
r
a
g
e
.
T
h
i
s
m
e
t
r
i
c
e
v
a
l
u
a
t
e
s
t
h
e
r
a
t
e
a
t
w
h
i
c
h
a
n
a
c
c
e
s
s
c
o
n
t
r
o
l
s
y
s
t
e
m
g
e
n
e
r
a
t
e
s
F
A
R
[
5
2
]
.
+
[
3
5
]
,
[
3
7
]
,
[
3
9
]
,
[
4
1
]
[
4
6
]
,
[
4
8
]
4
F
-
mea
su
r
e
M
e
a
su
r
e
s
t
h
e
a
v
e
r
a
g
e
o
f
p
r
e
c
i
si
o
n
a
n
d
r
e
c
a
l
l
,
t
h
e
b
e
st
v
a
l
u
e
o
f
F
-
sc
o
r
e
i
s
o
n
e
(
1
)
a
n
d
i
t
s
w
o
r
st
v
a
l
u
e
i
s
Z
e
r
o
(
0
)
.
I
t
sh
o
w
s
t
h
e
a
c
t
u
a
l
p
e
r
f
o
r
m
a
n
c
e
o
f
a
mo
d
e
l
e
sp
e
c
i
a
l
l
y
i
n
t
h
e
c
a
se
o
f
i
mb
a
l
a
n
c
e
d
a
t
a
s
e
t
[
1
4
]
.
2
×
×
+
[
3
4
]
,
[
3
5
]
,
[
3
6
]
,
[
4
0
]
[
4
1
]
,
[
4
2
]
,
[
4
3
]
,
[
4
4
]
[
4
5
]
,
[
4
7
]
5
R
e
c
a
l
l
/
TP
R
d
e
t
e
c
t
i
o
n
r
a
t
e
(
D
R
)
M
e
a
s
u
r
e
s
t
h
e
f
r
a
c
t
i
o
n
o
f
p
o
s
i
t
i
v
e
a
c
c
e
s
s
t
h
a
t
a
r
e
c
o
r
r
e
c
t
l
y
c
l
a
s
s
i
f
i
e
d
a
s
p
o
s
i
t
i
v
e
a
c
c
e
s
s
t
o
d
a
t
a
i
n
c
l
o
u
d
s
t
o
r
a
g
e
[
4
6
]
,
[
4
7
]
.
+
[
3
4
]
,
[
3
5
]
,
[
3
6
]
,
[
3
9
]
[
4
0
]
,
[
4
1
]
,
[
4
2
]
,
[
4
3
]
[
4
4
]
,
[
4
5
]
,
[
4
6
]
,
[
4
7
]
6
TN
R
M
e
a
su
r
e
s
t
h
e
f
r
a
c
t
i
o
n
o
f
n
e
g
a
t
i
v
e
a
c
c
e
ss
(
u
n
a
u
t
h
o
r
i
z
e
d
a
c
c
e
ss)
t
h
a
t
a
r
e
c
o
r
r
e
c
t
l
y
c
l
a
ssi
f
i
e
d
[
1
5
]
.
+
[
3
9
]
7
R
M
A
E
En
s
u
r
e
s
t
h
a
t
mo
d
e
l
p
e
r
f
o
r
ma
n
c
e
i
s
a
c
c
e
sse
d
a
c
c
u
r
a
t
e
l
y
w
h
i
l
e
a
d
h
e
r
i
n
g
t
o
d
a
t
a
p
r
i
v
a
c
y
a
n
d
c
o
mp
l
i
a
n
c
e
w
i
t
h
a
c
c
e
ss
p
o
l
i
c
y
[
5
3
]
.
√
1
∑
|
,
−
,
|
−
1
[
3
6
]
8
F
N
R
u
n
d
e
t
e
c
t
e
d
r
a
t
e
M
e
a
su
r
e
s
t
h
e
f
r
a
c
t
i
o
n
o
f
p
o
s
i
t
i
v
e
a
c
c
e
ss
t
h
a
t
a
r
e
mi
s
c
l
a
ssi
f
i
e
d
a
s
n
e
g
a
t
i
v
e
a
c
c
e
ss
t
o
d
a
t
a
i
n
t
h
e
c
l
o
u
d
st
o
r
a
g
e
[
1
5
]
,
[
3
7
]
.
+
[
3
7
]
9
TD
R
M
e
a
su
r
e
s
t
h
e
p
r
o
p
o
r
t
i
o
n
o
f
p
o
s
i
t
i
v
e
i
n
s
t
a
n
c
e
s
t
h
a
t
a
r
e
n
o
t
i
n
c
o
r
r
e
c
t
l
y
c
l
a
ss
i
f
i
e
d
a
s
n
e
g
a
t
i
v
e
.
I
t
i
s
t
h
e
c
o
m
p
l
e
me
n
t
o
f
t
h
e
F
N
R
[
1
7
]
.
1
-
F
N
R
[
4
8
]
10
R
O
C
M
e
a
su
r
e
s
t
h
e
t
r
a
d
e
-
o
f
f
b
e
t
w
e
e
n
F
P
R
a
n
d
TP
R
o
f
t
h
e
se
c
u
r
i
t
y
s
y
st
e
m
[
5
4
]
.
N
o
s
p
e
c
i
f
i
c
f
o
r
m
u
l
a
f
o
r
c
a
l
c
u
l
a
t
i
o
n
.
[
3
5
]
11
T
-
v
i
o
l
a
t
i
o
n
M
e
a
su
r
e
s
t
h
e
r
i
s
k
o
f
a
s
e
c
u
r
i
t
y
s
y
st
e
m
b
e
i
n
g
c
o
m
p
r
o
m
i
se
d
b
y
a
n
a
t
t
a
c
k
e
r
e
x
p
l
o
i
t
i
n
g
a
d
i
scre
p
a
n
c
y
i
n
t
h
e
t
i
m
i
n
g
o
f
e
v
e
n
t
s
[
5
5
]
.
N
o
s
p
e
c
i
f
i
c
f
o
r
m
u
l
a
f
o
r
c
a
l
c
u
l
a
t
i
o
n
.
[
3
8
]
12
P
-
v
i
o
l
a
t
i
o
n
M
e
a
su
r
e
s
t
h
e
a
c
t
i
o
n
o
r
b
e
h
a
v
i
o
r
t
h
a
t
v
i
o
l
a
t
e
s
a
c
c
e
ss p
o
l
i
c
y
e
.
g
.
p
r
i
v
a
c
y
o
f
a
u
ser.
(
w
h
e
t
h
e
r
i
n
t
e
n
t
i
o
n
a
l
o
r
u
n
i
n
t
e
n
t
i
o
n
a
l
)
[
5
6
]
.
N
o
s
p
e
c
i
f
i
c
f
o
r
m
u
l
a
f
o
r
c
a
l
c
u
l
a
t
i
o
n
[
3
8
]
13
Tr
a
i
n
i
n
g
t
i
me
M
e
a
su
r
e
s
t
h
e
a
m
o
u
n
t
o
f
t
i
me
t
h
a
t
i
t
t
a
k
e
s
t
o
t
r
a
i
n
a
m
o
d
e
l
[
5
7
]
.
D
e
p
e
n
d
s
o
n
:
d
a
t
a
s
e
t
s
i
z
e
,
m
o
d
e
l
t
y
p
e
,
C
P
U
a
v
a
i
l
a
b
l
e
,
o
p
t
i
m
i
z
a
t
i
o
n
t
e
c
h
n
i
q
u
e
s
[
3
6
]
14
Th
r
e
s
h
o
l
d
v
a
l
u
e
H
e
l
p
s
d
e
t
e
r
mi
n
e
t
h
e
c
u
t
-
o
f
f
p
o
i
n
t
f
o
r
d
e
c
i
d
i
n
g
b
e
t
w
e
e
n
g
r
a
n
t
i
n
g
o
r
d
e
n
y
i
n
g
a
c
c
e
ss
[
5
8
]
.
N
o
s
p
e
c
i
f
i
c
f
o
r
m
u
l
a
f
o
r
c
a
l
c
u
l
a
t
i
o
n
[
4
8
]
TP=t
r
u
e
p
o
si
t
i
v
e
,
F
N
=
f
a
l
se
n
e
g
a
t
i
v
e
,
N
=
t
o
t
a
l
n
u
mb
e
r
s o
f
sam
p
l
e
s,
Y
_
p
r
e
d
=
p
r
e
d
i
c
t
e
d
l
a
b
e
l
,
TN
=
t
r
u
e
n
e
g
a
t
i
v
e
,
F
P
=
f
a
l
se
p
o
s
i
t
i
v
e
,
Y
_
t
r
u
e
=
t
r
u
e
l
a
b
e
l
5.
T
RE
NDS,
P
AT
T
E
RNS
A
N
D
I
NSI
G
H
T
S
T
h
i
s
s
ec
t
i
o
n
h
i
g
h
l
i
g
h
ts
k
e
y
t
r
e
n
d
s
,
p
a
t
t
e
r
n
s
,
a
n
d
i
n
s
i
g
h
t
s
i
d
en
t
i
f
i
e
d
f
r
o
m
t
h
e
l
i
t
e
r
a
t
u
r
e
r
e
v
ie
w
o
n
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
i
n
c
l
o
u
d
c
o
m
p
u
t
i
n
g
u
s
i
n
g
M
L
m
o
d
e
l
s
.
T
h
e
s
e
in
s
i
g
h
t
s
p
r
o
v
i
d
e
a
c
o
m
p
r
e
h
e
n
s
iv
e
u
n
d
e
r
s
t
a
n
d
i
n
g
o
f
t
h
e
c
u
r
r
e
n
t
s
t
at
e
o
f
r
e
s
e
a
r
c
h
a
n
d
t
h
e
p
r
e
v
a
i
l
i
n
g
d
i
r
e
c
t
i
o
n
s
i
n
th
i
s
f
i
e
l
d
.
T
h
e
y
a
r
e
as
f
o
l
l
o
ws
;
i
)
t
h
e
r
e
i
s
a
g
r
o
w
i
n
g
p
r
e
f
e
r
e
n
c
e
f
o
r
DL
m
o
d
e
ls
d
u
e
t
o
t
h
e
i
r
s
u
p
e
r
i
o
r
a
b
i
li
t
y
t
o
p
r
o
c
e
s
s
l
a
r
g
e
d
a
ta
s
et
s
a
n
d
a
d
a
p
t
t
o
d
y
n
a
m
i
c
c
l
o
u
d
e
n
v
i
r
o
n
m
e
n
t
s
;
ii
)
n
u
m
e
r
o
u
s
s
tu
d
i
e
s
h
i
g
h
li
g
h
t
t
h
e
c
r
it
i
c
al
i
m
p
o
r
t
a
n
c
e
o
f
d
e
te
c
t
i
n
g
a
n
o
m
a
l
i
es
a
n
d
i
n
s
i
d
e
r
t
h
r
e
a
t
s
,
s
h
o
w
c
as
i
n
g
a
p
r
o
a
c
t
i
v
e
a
p
p
r
o
a
c
h
t
o
e
n
h
a
n
c
i
n
g
c
l
o
u
d
s
e
c
u
r
i
t
y
;
iii
)
t
h
e
e
m
p
l
o
y
m
e
n
t
o
f
v
a
r
i
o
u
s
d
a
t
a
s
e
ts
a
n
d
t
o
o
l
s
u
n
d
e
r
s
c
o
r
e
s
t
h
e
n
e
c
e
s
s
it
y
f
o
r
c
o
m
p
r
e
h
e
n
s
i
v
e
d
a
t
a
t
o
e
f
f
e
c
t
i
v
e
ly
t
r
a
i
n
M
L
m
o
d
e
l
s
a
n
d
d
e
m
o
n
s
t
r
a
t
e
s
t
h
e
v
e
r
s
a
t
il
i
t
y
o
f
t
o
o
l
s
li
k
e
T
e
n
s
o
r
F
l
o
w
,
K
e
r
a
s
,
a
n
d
Sc
i
k
i
t
-
l
e
a
r
n
;
a
n
d
iv
)
ac
c
u
r
a
c
y
a
n
d
p
r
e
c
i
s
i
o
n
a
r
e
p
r
i
o
r
i
t
i
z
e
d
as
t
h
e
m
o
s
t
e
s
s
e
n
t
i
a
l
m
e
t
r
i
cs
,
i
n
d
i
ca
t
i
n
g
t
h
e
n
e
e
d
f
o
r
r
e
l
i
a
b
l
e
a
n
d
p
r
e
c
is
e
m
o
d
e
l
s
t
o
e
f
f
e
ct
i
v
e
l
y
p
r
e
v
e
n
t
u
n
a
u
t
h
o
r
i
z
e
d
a
c
c
e
s
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.
1
5
,
No
.
1
,
Feb
r
u
ar
y
2
0
2
6
:
44
-
55
52
6.
CO
NCLU
SI
O
N
T
h
e
liter
atu
r
e
r
ev
iew
o
n
d
ata
a
cc
ess
co
n
tr
o
l
in
clo
u
d
co
m
p
u
ti
n
g
r
ev
ea
ls
s
ig
n
if
ican
t
tr
en
d
s
an
d
in
s
ig
h
ts
in
th
e
ap
p
licatio
n
o
f
ML
m
o
d
els.
DL
m
o
d
els,
esp
ec
ially
n
e
u
r
al
n
etwo
r
k
s
,
d
o
m
in
ate
ML
-
b
ased
f
r
am
ewo
r
k
s
,
co
m
p
r
is
in
g
4
7
.
0
6
%
o
f
th
e
m
o
d
els
u
s
ed
,
d
u
e
t
o
th
eir
r
o
b
u
s
t
p
er
f
o
r
m
an
ce
i
n
h
an
d
lin
g
lar
g
e
d
atasets
,
r
ea
l
-
tim
e
p
r
o
ce
s
s
in
g
,
a
n
d
a
n
o
m
aly
d
etec
tio
n
.
T
h
e
Am
az
o
n
ac
ce
s
s
s
am
p
le
d
ataset
is
th
e
m
o
s
t f
r
eq
u
en
tly
u
s
ed
,
r
ef
lectin
g
a
p
r
ef
er
en
ce
f
o
r
c
o
m
p
r
e
h
en
s
iv
e,
r
ea
l
-
wo
r
ld
d
ata.
T
en
s
o
r
Fl
o
w
is
th
e
lead
in
g
to
o
l,
u
s
ed
in
3
6
.
8
4
%
o
f
s
tu
d
ies,
h
ig
h
lig
h
tin
g
its
ca
p
a
b
ilit
y
to
d
ev
elo
p
an
d
d
e
p
lo
y
co
m
p
lex
ML
m
o
d
els
ac
r
o
s
s
v
ar
io
u
s
c
lo
u
d
p
latf
o
r
m
s
.
I
n
tr
ad
itio
n
al
d
ata
ac
ce
s
s
co
n
tr
o
l
f
r
am
ewo
r
k
s
,
AB
AC
is
p
r
ed
o
m
in
an
t,
r
ep
r
esen
tin
g
5
0
%
o
f
u
s
ag
e
f
r
o
m
2
0
1
3
to
2
0
2
3
,
o
win
g
t
o
its
s
ca
lab
ilit
y
,
f
lex
ib
ilit
y
,
an
d
f
in
e
-
g
r
ain
ed
co
n
tr
o
l.
T
h
is
m
eth
o
d
e
f
f
ec
tiv
ely
m
an
ag
es
lar
g
e
,
d
y
n
am
ic
clo
u
d
en
v
ir
o
n
m
en
ts
b
y
in
co
r
p
o
r
atin
g
d
etailed
attr
ib
u
te
-
b
ased
r
u
les
an
d
r
o
b
u
s
t
in
cid
en
t
r
esp
o
n
s
e
m
ec
h
an
is
m
s
.
Attr
ib
u
te
-
b
ased
m
eth
o
d
s
,
u
s
ed
in
5
0
%
o
f
tr
a
d
itio
n
al
f
r
am
ewo
r
k
s
,
em
p
h
asize
p
r
ec
is
e
co
n
tr
o
l
o
v
e
r
d
ata
ac
ce
s
s
.
T
h
e
p
r
im
a
r
y
r
es
ea
r
ch
o
b
jectiv
e
in
tr
a
d
itio
n
al
f
r
am
ewo
r
k
s
is
u
n
au
th
o
r
ized
ac
ce
s
s
r
estrictio
n
,
co
m
p
r
is
in
g
2
8
.
6
%
o
f
th
e
o
b
je
ctiv
es,
u
n
d
er
s
co
r
in
g
t
h
e
n
ee
d
f
o
r
r
o
b
u
s
t
ac
ce
s
s
co
n
tr
o
l
m
ea
s
u
r
es.
Per
f
o
r
m
a
n
ce
m
etr
ics
f
o
r
ML
-
b
ased
f
r
am
ew
o
r
k
s
h
ig
h
lig
h
t
th
e
cr
itical
im
p
o
r
tan
ce
o
f
ac
c
u
r
ac
y
,
ad
o
p
ted
i
n
2
2
%
o
f
s
tu
d
ies,
en
s
u
r
in
g
p
r
ec
is
e
p
r
e
d
ictio
n
s
an
d
m
in
im
izin
g
er
r
o
r
s
.
Pre
cisi
o
n
an
d
r
ec
all,
u
s
ed
in
2
0
%
a
n
d
1
8
%
o
f
s
tu
d
ies
r
esp
ec
tiv
ely
,
s
tr
ess
th
e
b
alan
ce
b
etwe
en
r
ed
u
cin
g
f
alse
p
o
s
itiv
es
an
d
co
m
p
r
eh
en
s
iv
e
th
r
ea
t
d
etec
tio
n
.
T
h
e
F
-
m
ea
s
u
r
e,
ad
o
p
ted
in
1
7
%
o
f
s
tu
d
ies,
p
r
o
v
id
es
a
b
ala
n
ce
d
v
i
ew
o
f
m
o
d
el
p
er
f
o
r
m
an
ce
,
cr
u
cial
f
o
r
o
p
tim
izin
g
s
ec
u
r
ity
in
clo
u
d
en
v
ir
o
n
m
e
n
ts
.
R
esear
ch
d
ir
ec
tio
n
s
in
clu
d
e
en
h
an
cin
g
DL
m
o
d
els,
d
ef
en
d
in
g
ag
ain
s
t
ad
v
er
s
ar
ial
attac
k
s
,
in
teg
r
atin
g
m
o
r
e
r
o
b
u
s
t
ML
with
tr
ad
itio
n
al
m
eth
o
d
s
,
im
p
r
o
v
in
g
d
a
tasets
,
o
p
tim
izin
g
p
er
f
o
r
m
an
ce
,
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
,
en
s
u
r
in
g
e
x
p
lain
ab
ilit
y
,
a
n
d
s
ca
lab
ilit
y
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
ex
p
r
ess
th
eir
s
in
c
er
e
ap
p
r
ec
iatio
n
t
o
th
e
B
o
ts
wan
a
I
n
ter
n
atio
n
al
Un
iv
er
s
ity
o
f
Scien
ce
an
d
T
ec
h
n
o
lo
g
y
f
o
r
p
r
o
v
id
i
n
g
ac
ce
s
s
to
v
ital r
eso
u
r
ce
s
an
d
f
ac
ilit
ies.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
Au
th
o
r
s
s
tate
n
o
f
u
n
d
in
g
in
v
o
lv
ed
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
I
n
an
ef
f
o
r
t
to
ac
k
n
o
wled
g
e
th
e
d
is
tin
ct
co
n
tr
ib
u
tio
n
s
o
f
ea
ch
au
th
o
r
,
p
r
o
v
id
e
tr
a
n
s
p
ar
en
cy
i
n
au
th
o
r
s
h
ip
a
n
d
s
tr
en
g
th
en
c
o
l
lab
o
r
ativ
e
r
esear
ch
,
th
is
jo
u
r
n
al
im
p
lem
en
ts
th
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT)
.
E
ac
h
au
th
o
r
’
s
co
n
tr
ib
u
tio
n
is
as f
o
llo
ws
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
B
les
s
in
g
I
f
eo
lu
wa
Om
o
g
b
eh
in
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
T
s
h
iam
o
Sig
wele
✓
✓
✓
✓
✓
✓
✓
✓
✓
T
h
ab
o
Sem
o
n
g
✓
✓
✓
✓
✓
Ao
n
e
Ma
en
g
e
✓
✓
✓
Z
h
iv
k
o
Ne
d
ev
✓
✓
✓
✓
Hlo
m
an
i H
lo
m
an
i
✓
✓
✓
✓
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
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
No
n
ew
d
ata
was c
o
llected
o
r
an
aly
ze
d
f
o
r
th
is
s
tu
d
y
.
T
h
e
ar
ticle
is
b
ased
en
tire
ly
o
n
p
r
ev
i
o
u
s
ly
p
u
b
lis
h
ed
liter
atu
r
e,
all
o
f
wh
i
ch
is
ap
p
r
o
p
r
iately
cited
in
th
e
R
ef
er
en
ce
s
s
ec
tio
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
S
ec
u
r
in
g
clo
u
d
d
a
ta
w
ith
ma
c
h
in
e
lea
r
n
in
g
:
t
r
en
d
s
,
g
a
p
s
,
a
n
d
…
(
B
less
in
g
I
feo
lu
w
a
Omo
g
b
eh
in
)
53
RE
F
E
R
E
NC
E
S
[
1
]
R
.
S
i
k
k
a
a
n
d
M
.
O
j
h
a
,
“
A
n
o
v
e
r
v
i
e
w
o
f
c
l
o
u
d
c
o
mp
u
t
i
n
g
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
I
n
n
o
v
a
t
i
v
e
R
e
se
a
rc
h
i
n
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
5
,
n
o
.
3
,
p
p
.
1
3
5
–
1
3
8
,
2
0
2
1
,
d
o
i
:
1
0
.
5
5
5
2
4
/
i
j
i
r
c
s
t
.
2
0
2
1
.
9
.
6
.
3
1
.
[
2
]
S
.
A
b
o
u
k
a
d
r
i
,
A
.
O
u
a
d
d
a
h
,
a
n
d
A
.
M
e
z
r
i
o
u
i
,
“
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
b
a
s
e
d
i
d
e
n
t
i
t
y
a
n
d
a
c
c
e
s
s
m
a
n
a
g
e
m
e
n
t
s
y
s
t
e
m
s
(
M
L
I
&
A
M
)
:
a
t
a
x
o
n
o
m
y
,
”
C
o
l
l
o
q
u
i
u
m
i
n
I
n
f
o
r
m
a
t
i
o
n
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
C
I
S
T
,
p
p
.
6
5
7
–
6
6
2
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
C
i
S
t
5
6
0
8
4
.
2
0
2
3
.
1
0
4
0
9
8
7
2
.
[
3
]
O
.
D
.
S
e
g
u
n
-
F
a
l
a
d
e
,
O
.
S
.
O
s
u
n
d
a
r
e
,
W
.
E.
K
e
d
i
,
P
.
A
.
O
k
e
l
e
k
e
,
T
.
I
.
I
j
o
mah
,
a
n
d
O
.
Y
.
A
b
d
u
l
-
A
z
e
e
z
,
“
A
ss
e
ssi
n
g
t
h
e
t
r
a
n
sf
o
r
m
a
t
i
v
e
i
mp
a
c
t
o
f
c
l
o
u
d
c
o
mp
u
t
i
n
g
o
n
so
f
t
w
a
r
e
d
e
p
l
o
y
m
e
n
t
a
n
d
ma
n
a
g
e
m
e
n
t
,
”
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
I
T
Re
se
a
r
c
h
J
o
u
r
n
a
l
,
v
o
l
.
5
,
n
o
.
8
,
p
p
.
2
0
6
2
–
2
0
8
2
,
2
0
2
4
,
d
o
i
:
1
0
.
5
1
5
9
4
/
c
si
t
r
j
.
v
5
i
8
.
1
4
9
2
.
[
4
]
O
.
C
.
A
d
e
u
si
,
Y
.
O
.
A
d
e
b
a
y
o
,
P
.
A
.
A
y
o
d
e
l
e
,
T.
T
.
O
n
i
k
o
y
i
,
K
.
B
.
A
d
e
b
a
y
o
,
a
n
d
I
.
O
.
A
d
e
n
e
k
a
n
,
“
I
T
st
a
n
d
a
r
d
i
z
a
t
i
o
n
i
n
c
l
o
u
d
c
o
m
p
u
t
i
n
g
:
S
e
c
u
r
i
t
y
c
h
a
l
l
e
n
g
e
s,
b
e
n
e
f
i
t
s,
a
n
d
f
u
t
u
r
e
d
i
r
e
c
t
i
o
n
s,
”
W
o
rl
d
J
o
u
r
n
a
l
o
f
Ad
v
a
n
c
e
d
R
e
se
a
rc
h
a
n
d
Re
v
i
e
w
s
,
v
o
l
.
2
2
,
n
o
.
3
,
p
p
.
2
0
5
0
–
2
0
5
7
,
2
0
2
4
,
d
o
i
:
1
0
.
3
0
5
7
4
/
w
j
a
r
r
.
2
0
2
4
.
2
2
.
3
.
1
9
8
2
.
[
5
]
O
.
G
o
d
w
i
n
a
n
d
M
.
O
.
M
u
s
a
,
“
C
h
a
l
l
e
n
g
e
s
a
n
d
s
t
r
a
t
e
g
i
e
s
f
o
r
e
n
h
a
n
c
i
n
g
I
C
T
sec
u
r
i
t
y
i
n
p
u
b
l
i
c
i
n
st
i
t
u
t
i
o
n
s
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
I
n
n
o
v
a
t
i
v
e
S
c
i
e
n
c
e
a
n
d
R
e
se
a
rc
h
T
e
c
h
n
o
l
o
g
y
(
I
J
I
S
RT)
,
p
p
.
2
1
8
5
–
2
1
9
0
,
2
0
2
4
,
d
o
i
:
1
0
.
3
8
1
2
4
/
i
j
i
sr
t
/
i
j
i
sr
t
2
4
j
u
l
1
0
2
4
.
[
6
]
S
.
N
a
mas
u
d
r
a
,
“
D
a
t
a
a
c
c
e
ss
c
o
n
t
r
o
l
i
n
t
h
e
c
l
o
u
d
c
o
mp
u
t
i
n
g
e
n
v
i
r
o
n
me
n
t
f
o
r
b
i
o
i
n
f
o
r
mat
i
c
s
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
p
p
l
i
e
d
Re
se
a
rc
h
i
n
Bi
o
i
n
f
o
rm
a
t
i
c
s
,
v
o
l
.
1
1
,
n
o
.
1
,
p
p
.
4
0
–
5
0
,
2
0
2
1
,
d
o
i
:
1
0
.
4
0
1
8
/
i
j
a
r
b
.
2
0
2
1
0
1
0
1
0
5
.
[
7
]
A
.
A
.
S
.
A
l
q
a
h
t
a
n
i
a
n
d
T
.
A
l
s
h
a
y
e
b
,
“
Ze
r
o
-
e
f
f
o
r
t
t
w
o
-
f
a
c
t
o
r
a
u
t
h
e
n
t
i
c
a
t
i
o
n
u
si
n
g
w
i
-
f
i
r
a
d
i
o
w
a
v
e
t
r
a
n
s
mi
ss
i
o
n
a
n
d
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
,
”
i
n
2
0
2
3
I
EE
E
1
3
t
h
A
n
n
u
a
l
C
o
m
p
u
t
i
n
g
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
W
o
rk
sh
o
p
a
n
d
C
o
n
f
e
re
n
c
e
,
C
C
WC
2
0
2
3
,
2
0
2
3
,
p
p
.
3
1
3
–
3
1
8
.
d
o
i
:
1
0
.
1
1
0
9
/
C
C
W
C
5
7
3
4
4
.
2
0
2
3
.
1
0
0
9
9
1
2
4
.
[
8
]
P
.
K
a
m
b
o
j
,
S
.
K
h
a
r
e
,
a
n
d
S
.
P
a
l
,
“
U
s
e
r
a
u
t
h
e
n
t
i
c
a
t
i
o
n
u
si
n
g
B
l
o
c
k
c
h
a
i
n
b
a
sed
smar
t
c
o
n
t
r
a
c
t
i
n
r
o
l
e
-
b
a
s
e
d
a
c
c
e
s
s
c
o
n
t
r
o
l
,
”
Pe
e
r
-
to
-
P
e
e
r
N
e
t
w
o
rk
i
n
g
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
1
4
,
n
o
.
5
,
p
p
.
2
9
6
1
–
2
9
7
6
,
2
0
2
1
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
2
0
8
3
-
021
-
0
1
1
5
0
-
1.
[
9
]
M
.
M
o
r
a
v
c
i
k
a
n
d
L
.
Zi
d
e
k
o
v
a
,
“
O
v
e
r
v
i
e
w
o
f
a
c
c
e
ss
c
o
n
t
r
o
l
me
c
h
a
n
i
sms
i
n
c
l
o
u
d
e
n
v
i
r
o
n
me
n
t
s,”
i
n
I
C
ETA
2
0
2
4
-
2
2
n
d
Y
e
a
r
o
f
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
Em
e
r
g
i
n
g
e
L
e
a
rn
i
n
g
T
e
c
h
n
o
l
o
g
i
e
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s,
Pr
o
c
e
e
d
i
n
g
s
,
I
EEE,
2
0
2
4
,
p
p
.
4
6
5
–
4
7
0
.
d
o
i
:
1
0
.
1
1
0
9
/
I
C
ETA
6
3
7
9
5
.
2
0
2
4
.
1
0
8
5
0
8
0
6
.
[
1
0
]
M
.
D
o
l
l
a
r
,
“
0
1
J
u
l
y
2
0
2
4
:
u
p
d
a
t
e
o
n
c
y
b
e
r
i
n
c
i
d
e
n
t
,
”
S
y
n
n
o
v
i
s
.
A
c
c
e
sse
d
:
M
a
r
.
2
9
,
2
0
2
5
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
sy
n
n
o
v
i
s.c
o
.
u
k
/
c
y
b
e
r
a
t
t
a
c
k
-
i
n
f
o
r
m
a
t
i
o
n
-
c
e
n
t
r
e
[
1
1
]
S
.
A
l
d
e
r
,
“
N
H
S
P
a
t
h
o
l
o
g
y
P
r
o
v
i
d
e
r
sy
n
n
o
v
i
s
n
o
t
i
f
i
e
s
o
r
g
a
n
i
z
a
t
i
o
n
s
a
f
f
e
c
t
e
d
b
y
Ju
n
e
2
0
2
4
r
a
n
so
mw
a
r
e
a
t
t
a
c
k
,”
T
h
e
H
I
PAA
J
o
u
r
n
a
l
.
A
c
c
e
ss
e
d
:
M
a
r
.
3
0
,
2
0
2
4
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
h
i
p
a
a
j
o
u
r
n
a
l
.
c
o
m
/
c
a
r
e
-
d
i
sr
u
p
t
e
d
-
at
-
l
o
n
d
o
n
-
h
o
s
p
i
t
a
l
s
-
d
u
e
-
to
-
r
a
n
s
o
mw
a
r
e
-
a
t
t
a
c
k
-
on
-
p
a
t
h
o
l
o
g
y
-
v
e
n
d
o
r
/
[
1
2
]
N
H
S
En
g
l
a
n
d
,
“
S
y
n
n
o
v
i
s
r
a
n
s
o
mw
a
r
e
c
y
b
e
r
-
a
t
t
a
c
k
,
”
N
H
S
E
n
g
l
a
n
d
-
L
o
n
d
o
n
.
A
c
c
e
ss
e
d
:
M
a
r
.
2
9
,
2
0
2
4
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
e
n
g
l
a
n
d
.
n
h
s
.
u
k
/
l
o
n
d
o
n
/
s
y
n
n
o
v
i
s
-
r
a
n
so
mw
a
r
e
-
c
y
b
e
r
-
a
t
t
a
c
k
/
[
1
3
]
N
.
T.
G
.
A
n
t
h
o
n
y
,
M
.
S
h
a
f
i
k
,
F
.
K
u
r
u
g
o
l
l
u
,
a
n
d
H
.
F
.
A
t
l
a
m,
“
A
n
o
ma
l
y
d
e
t
e
c
t
i
o
n
s
y
st
e
m
f
o
r
e
t
h
e
r
e
u
m b
l
o
c
k
c
h
a
i
n
u
s
i
n
g
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
,
”
A
d
v
a
n
c
e
s
i
n
T
r
a
n
s
d
i
sci
p
l
i
n
a
ry
En
g
i
n
e
e
r
i
n
g
,
v
o
l
.
2
5
,
p
p
.
3
1
1
–
3
1
6
,
2
0
2
2
,
d
o
i
:
1
0
.
3
2
3
3
/
A
TD
E2
2
0
6
0
8
.
[
1
4
]
T.
A
.
A
l
-
S
h
e
h
a
r
i
e
t
a
l
.
,
“
E
n
h
a
n
c
i
n
g
i
n
s
i
d
e
r
t
h
r
e
a
t
d
e
t
e
c
t
i
o
n
i
n
i
mb
a
l
a
n
c
e
d
c
y
b
e
r
sec
u
r
i
t
y
se
t
t
i
n
g
s
u
si
n
g
t
h
e
d
e
n
s
i
t
y
-
b
a
sed
l
o
c
a
l
o
u
t
l
i
e
r
f
a
c
t
o
r
a
l
g
o
r
i
t
h
m,”
I
EEE
Ac
c
e
ss
,
v
o
l
.
1
2
,
p
p
.
3
4
8
2
0
–
3
4
8
3
4
,
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
4
.
3
3
7
3
6
9
4
.
[
1
5
]
H
.
N
a
n
d
a
n
w
a
r
a
n
d
R
.
K
a
t
a
r
y
a
,
“
D
e
e
p
l
e
a
r
n
i
n
g
e
n
a
b
l
e
d
i
n
t
r
u
s
i
o
n
d
e
t
e
c
t
i
o
n
s
y
st
e
m f
o
r
I
n
d
u
st
r
i
a
l
I
o
T
e
n
v
i
r
o
n
me
n
t
,
”
E
x
p
e
rt
S
y
st
e
m
s
w
i
t
h
Ap
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
2
4
9
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
sw
a
.
2
0
2
4
.
1
2
3
8
0
8
.
[
1
6
]
J
.
S
u
e
t
a
l
.
,
“
L
a
r
g
e
l
a
n
g
u
a
g
e
m
o
d
e
l
s
f
o
r
f
o
r
e
c
a
s
t
i
n
g
a
n
d
a
n
o
m
a
l
y
d
e
t
e
c
t
i
o
n
:
a
s
y
s
t
e
m
a
t
i
c
l
i
t
e
r
a
t
u
r
e
r
e
v
i
e
w
,
”
a
r
x
i
v
:
2
4
0
2
.
1
0
3
5
0
,
2
0
2
4
.
[
1
7
]
S
.
A
h
ma
d
,
S
.
M
e
h
f
u
z
,
S
.
U
r
o
o
j
,
a
n
d
N
.
A
l
s
u
b
a
i
e
,
“
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
-
b
a
s
e
d
i
n
t
e
l
l
i
g
e
n
t
se
c
u
r
i
t
y
f
r
a
mew
o
r
k
f
o
r
s
e
c
u
r
e
c
l
o
u
d
k
e
y
man
a
g
e
me
n
t
,
”
C
l
u
s
t
e
r
C
o
m
p
u
t
i
n
g
,
v
o
l
.
2
7
,
n
o
.
5
,
p
p
.
5
9
5
3
–
5
9
7
9
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
0
5
8
6
-
0
2
4
-
0
4
2
8
8
-
8.
[
1
8
]
D
.
A
.
W
i
n
k
l
e
r
,
“
R
o
l
e
o
f
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
a
n
d
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
i
n
n
a
n
o
s
a
f
e
t
y
,
”
S
m
a
l
l
,
v
o
l
.
1
6
,
n
o
.
3
6
,
p
p
.
1
–
6
,
2
0
2
0
,
d
o
i
:
1
0
.
1
0
0
2
/
sml
l
.
2
0
2
0
0
1
8
8
3
.
[
1
9
]
B
.
I
.
O
mo
g
b
e
h
i
n
,
T.
S
i
g
w
e
l
e
,
a
n
d
T.
S
e
mo
n
g
,
“
Le
v
e
r
a
g
i
n
g
d
e
e
p
l
e
a
r
n
i
n
g
f
o
r
a
c
c
e
ss
c
o
n
t
r
o
l
a
n
d
d
a
t
a
sec
u
r
i
t
y
i
n
c
l
o
u
d
e
n
v
i
r
o
n
m
e
n
t
s,
”
i
n
2
0
2
4
I
E
EE
4
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
i
n
B
u
s
i
n
e
ss
I
n
d
u
s
t
ry
a
n
d
G
o
v
e
r
n
m
e
n
t
,
I
C
T
BI
G
2
0
2
4
,
I
n
d
o
r
e
,
I
n
d
i
a
,
2
0
2
4
,
p
p
.
1
–
5
.
d
o
i
:
1
0
.
1
1
0
9
/
I
C
TB
I
G
6
4
9
2
2
.
2
0
2
4
.
1
0
9
1
1
8
5
5
.
[
2
0
]
P
.
S
r
i
n
i
v
a
s,
F
.
H
u
s
a
i
n
,
A
.
P
a
r
a
y
i
l
,
A
.
C
h
o
u
r
e
,
C
.
B
a
n
s
a
l
,
a
n
d
S
.
R
a
j
mo
h
a
n
,
“
I
n
t
e
l
l
i
g
e
n
t
m
o
n
i
t
o
r
i
n
g
f
r
a
mew
o
r
k
f
o
r
c
l
o
u
d
serv
i
c
e
s:
a
d
a
t
a
-
d
r
i
v
e
n
a
p
p
r
o
a
c
h
,
”
i
n
A
C
M
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
Pro
c
e
e
d
i
n
g
S
e
ri
e
s
,
2
0
2
4
,
p
p
.
3
8
1
–
3
9
1
.
d
o
i
:
1
0
.
1
1
4
5
/
3
6
3
9
4
7
7
.
3
6
3
9
7
5
3
.
[
2
1
]
K
.
K
u
mar,
G
.
N
a
n
a
k
,
a
n
d
K
.
K
u
m
a
r
,
“
I
n
t
r
u
si
o
n
d
e
t
e
c
t
i
o
n
a
n
d
p
r
e
v
e
n
t
i
o
n
s
y
st
e
m
i
n
e
n
h
a
n
c
i
n
g
s
e
c
u
r
i
t
y
o
f
c
l
o
u
d
e
n
v
i
r
o
n
me
n
t
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
d
v
a
n
c
e
d
Re
sea
r
c
h
i
n
C
o
m
p
u
t
e
r
E
n
g
i
n
e
e
r
i
n
g
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
6
,
n
o
.
8
,
p
p
.
2
2
7
8
–
1
3
2
3
,
2
0
1
7
.
[
2
2
]
P
.
R
.
B
r
a
n
d
ã
o
,
“
T
h
e
i
m
p
o
r
t
a
n
c
e
o
f
a
u
t
h
e
n
t
i
c
a
t
i
o
n
a
n
d
e
n
c
r
y
p
t
i
o
n
i
n
c
l
o
u
d
c
o
mp
u
t
i
n
g
f
r
a
mew
o
r
k
se
c
u
r
i
t
y
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
n
D
a
t
a
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
4
,
n
o
.
1
,
2
0
1
8
,
d
o
i
:
1
0
.
1
1
6
4
8
/
j
.
i
j
d
st
.
2
0
1
8
0
4
0
1
.
1
1
.
[
2
3
]
A
.
R
.
K
h
a
n
,
“
A
c
c
e
ss
c
o
n
t
r
o
l
i
n
c
l
o
u
d
c
o
m
p
u
t
i
n
g
e
n
v
i
r
o
n
me
n
t
,
”
A
RPN
J
o
u
r
n
a
l
o
f
En
g
i
n
e
e
r
i
n
g
a
n
d
Ap
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
7
,
n
o
.
5
,
p
p
.
6
1
3
–
6
1
5
,
2
0
1
2
.
[
2
4
]
H
.
H
e
,
L
.
h
a
n
Z
h
e
n
g
,
P
.
L
i
,
L
.
D
e
n
g
,
L
.
H
u
a
n
g
,
a
n
d
X
.
C
h
e
n
,
“
A
n
e
f
f
i
c
i
e
n
t
a
t
t
r
i
b
u
t
e
-
b
a
s
e
d
h
i
e
r
a
r
c
h
i
c
a
l
d
a
t
a
a
c
c
e
s
s
c
o
n
t
r
o
l
s
c
h
e
m
e
i
n
c
l
o
u
d
c
o
m
p
u
t
i
n
g
,
”
H
u
m
a
n
-
c
e
n
t
r
i
c
C
o
m
p
u
t
i
n
g
a
n
d
I
n
f
o
r
m
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
1
0
,
n
o
.
1
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
8
6
/
s
1
3
6
7
3
-
0
2
0
-
0
0
2
5
5
-
5.
[
2
5
]
S
.
B
h
a
t
t
a
n
d
R
.
S
a
n
d
h
u
,
“
A
B
A
C
-
C
C
:
A
t
t
r
i
b
u
t
e
-
b
a
se
d
a
c
c
e
ss
c
o
n
t
r
o
l
a
n
d
c
o
m
mu
n
i
c
a
t
i
o
n
c
o
n
t
r
o
l
f
o
r
i
n
t
e
r
n
e
t
o
f
t
h
i
n
g
s,”
A
C
M
S
y
m
p
o
s
i
u
m
o
n
Ac
c
e
ss
C
o
n
t
ro
l
Mo
d
e
l
s
a
n
d
T
e
c
h
n
o
l
o
g
i
e
s,
S
AC
MA
T
,
2
0
2
0
,
p
p
.
2
0
3
–
2
1
2
.
d
o
i
:
1
0
.
1
1
4
5
/
3
3
8
1
9
9
1
.
3
3
9
5
6
1
8
.
[
2
6
]
T.
P
r
a
n
t
l
e
t
a
l
.
,
“
T
o
w
a
r
d
s a
c
r
y
p
t
o
g
r
a
p
h
y
e
n
c
y
c
l
o
p
e
d
i
a
:
a
s
u
r
v
e
y
o
n
a
t
t
r
i
b
u
t
e
-
b
a
se
d
e
n
c
r
y
p
t
i
o
n
,
”
J
o
u
r
n
a
l
o
f
S
u
rv
e
i
l
l
a
n
c
e
,
S
e
c
u
ri
t
y
a
n
d
S
a
f
e
t
y
,
v
o
l
.
4
,
n
o
.
4
,
p
p
.
1
2
9
–
5
4
,
2
0
2
3
,
d
o
i
:
1
0
.
2
0
5
1
7
/
j
sss.
2
0
2
3
.
3
0
.
[
2
7
]
A
.
K
u
m
a
r
a
n
d
G
.
V
e
r
m
a
,
“
S
e
c
u
r
i
n
g
c
l
o
u
d
a
c
c
e
ss
w
i
t
h
e
n
h
a
n
c
e
d
a
t
t
r
i
b
u
t
e
-
b
a
s
e
d
c
r
y
p
t
o
g
r
a
p
h
y
,
”
C
o
m
p
u
t
i
n
g
,
v
o
l
.
1
0
6
,
n
o
.
1
2
,
p
p
.
4
1
9
3
–
4
2
0
7
,
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s
0
0
6
0
7
-
0
2
3
-
0
1
2
1
2
-
7.
[
2
8
]
S
.
C
h
o
u
d
h
a
r
y
a
n
d
N
.
S
i
n
g
h
,
“
A
n
a
l
y
s
i
s
o
f
se
c
u
r
i
t
y
-
b
a
se
d
a
c
c
e
ss
c
o
n
t
r
o
l
m
o
d
e
l
s
f
o
r
c
l
o
u
d
c
o
m
p
u
t
i
n
g
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
C
l
o
u
d
Ap
p
l
i
c
a
t
i
o
n
s
a
n
d
C
o
m
p
u
t
i
n
g
,
v
o
l
.
1
2
,
n
o
.
1
,
p
p
.
1
–
1
9
,
2
0
2
2
,
d
o
i
:
1
0
.
4
0
1
8
/
I
JC
A
C
.
2
0
2
2
0
1
0
1
0
4
.
[
2
9
]
K
.
R
.
D
a
y
a
n
a
a
n
d
P
.
S
.
R
a
n
i
,
“
Tr
u
st
a
w
a
r
e
c
r
y
p
t
o
g
r
a
p
h
i
c
r
o
l
e
b
a
s
e
d
a
c
c
e
ss
c
o
n
t
r
o
l
sc
h
e
m
e
f
o
r
s
e
c
u
r
e
c
l
o
u
d
d
a
t
a
st
o
r
a
g
e
,
”
Au
t
o
m
a
t
i
k
a
,
v
o
l
.
6
4
,
n
o
.
4
,
p
p
.
1
0
7
2
–
1
0
7
9
,
2
0
2
3
,
d
o
i
:
1
0
.
1
0
8
0
/
0
0
0
5
1
1
4
4
.
2
0
2
3
.
2
2
4
3
1
4
4
.
[
3
0
]
S
.
K
u
m
a
r
,
G
.
K
a
r
n
a
n
i
,
M
.
S
.
G
a
u
r
,
a
n
d
A
.
M
i
s
h
r
a
,
“
C
l
o
u
d
s
e
c
u
r
i
t
y
u
s
i
n
g
h
y
b
r
i
d
c
r
y
p
t
o
g
r
a
p
h
y
a
l
g
o
r
i
t
h
m
s
,
”
i
n
2
0
2
1
2
n
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
t
e
l
l
i
g
e
n
t
E
n
g
i
n
e
e
r
i
n
g
a
n
d
M
a
n
a
g
e
m
e
n
t
,
I
C
I
E
M
2
0
2
1
,
2
0
2
1
,
p
p
.
5
9
9
–
6
0
4
.
d
o
i
:
1
0
.
1
1
0
9
/
I
C
I
E
M
5
1
5
1
1
.
2
0
2
1
.
9
4
4
5
3
7
7
.
[
3
1
]
A
.
Tu
o
r
,
S
.
K
a
p
l
a
n
,
B
.
H
u
t
c
h
i
n
so
n
,
N
.
N
i
c
h
o
l
s,
a
n
d
S
.
R
o
b
i
n
so
n
,
“
D
e
e
p
l
e
a
r
n
i
n
g
f
o
r
u
n
s
u
p
e
r
v
i
s
e
d
i
n
si
d
e
r
t
h
r
e
a
t
d
e
t
e
c
t
i
o
n
i
n
st
r
u
c
t
u
r
e
d
c
y
b
e
r
se
c
u
r
i
t
y
d
a
t
a
s
t
r
e
a
ms,
”
AA
AI
W
o
rks
h
o
p
-
T
e
c
h
n
i
c
a
l
Re
p
o
rt
,
p
p
.
2
2
4
–
2
3
4
,
2
0
1
7
.
[
3
2
]
M
.
Y
.
S
h
a
k
o
r
a
n
d
M
.
I
b
r
a
h
i
m
K
h
a
l
e
e
l
, “
M
o
d
e
r
n
d
e
e
p
l
e
a
r
n
i
n
g
t
e
c
h
n
i
q
u
e
s f
o
r
b
i
g
me
d
i
c
a
l
d
a
t
a
p
r
o
c
e
ss
i
n
g
i
n
c
l
o
u
d
,
”
I
EEE
Ac
c
e
ss,
v
o
l
.
1
3
,
p
p
.
6
2
0
0
5
-
6
2
0
2
8
,
2
0
2
5
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
5
.
3
5
5
6
3
2
7
.
[
3
3
]
A
.
R
.
A
l
-
G
h
u
w
a
i
r
i
,
Y
.
S
h
a
r
r
a
b
,
D
.
A
l
-
F
r
a
i
h
a
t
,
M
.
A
l
E
l
a
i
m
a
t
,
A
.
A
l
s
a
r
h
a
n
,
a
n
d
A
.
A
l
g
a
r
n
i
,
“
I
n
t
r
u
s
i
o
n
d
e
t
e
c
t
i
o
n
i
n
c
l
o
u
d
c
o
m
p
u
t
i
n
g
b
a
s
e
d
o
n
t
i
m
e
s
e
r
i
e
s
a
n
o
m
a
l
i
e
s
u
t
i
l
i
z
i
n
g
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
,
”
J
o
u
r
n
a
l
o
f
C
l
o
u
d
C
o
m
p
u
t
i
n
g
,
v
o
l
.
1
2
,
n
o
.
1
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
8
6
/
s
1
3
6
7
7
-
0
2
3
-
0
0
4
9
1
-
x.
[
3
4
]
M
.
M
e
h
m
o
o
d
,
R
.
A
m
i
n
,
M
.
M
.
A
.
M
u
sl
a
m,
J.
X
i
e
,
a
n
d
H
.
A
l
d
a
b
b
a
s,
“
P
r
i
v
i
l
e
g
e
e
s
c
a
l
a
t
i
o
n
a
t
t
a
c
k
d
e
t
e
c
t
i
o
n
a
n
d
m
i
t
i
g
a
t
i
o
n
i
n
c
l
o
u
d
u
si
n
g
ma
c
h
i
n
e
l
e
a
r
n
i
n
g
,
”
I
EE
E
A
c
c
e
s
s
,
v
o
l
.
1
1
,
p
p
.
4
6
5
6
1
–
4
6
5
7
6
,
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
3
.
3
2
7
3
8
9
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.