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ates
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t
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eth
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tr
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r
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wo
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k
ad
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p
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FADT
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at
au
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ates
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,
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d
ev
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ates
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u
tco
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e
s
u
s
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g
s
tan
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a
r
d
ized
m
etr
ic
s
.
T
h
e
f
r
am
ewo
r
k
in
teg
r
ates
an
a
u
to
m
ated
d
ep
l
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m
en
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(
AD)
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o
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el,
g
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b
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th
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u
to
m
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d
e
p
lo
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m
en
t
r
ea
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in
ess
in
d
ex
(
ADRI)
,
to
v
alid
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en
v
ir
o
n
m
en
t
p
r
ep
ar
e
d
n
ess
,
an
d
a
tim
e,
er
r
o
r
,
s
atis
f
ac
tio
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ev
alu
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n
(
T
E
SE)
m
o
d
el
th
at
m
ea
s
u
r
es
tim
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f
icien
cy
,
er
r
o
r
r
ed
u
ctio
n
,
a
n
d
u
s
er
s
atis
f
ac
tio
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.
T
h
ese
co
m
p
o
n
en
ts
g
en
er
ate
a
co
m
p
o
s
ite
sc
o
r
e
(
C
S)
th
at
s
u
m
m
ar
izes o
v
er
all
d
ep
lo
y
m
e
n
t e
f
f
ec
tiv
e
n
ess
.
a.
C
h
allen
g
es in
m
an
u
al
d
e
p
lo
y
m
en
t b
ig
d
ata
to
o
ls
Mo
d
er
n
d
atasets
in
g
en
o
m
ics
an
d
im
ag
i
n
g
co
n
tin
u
e
to
in
c
r
ea
s
e
in
s
ca
le
a
n
d
co
m
p
lex
ity
,
cr
ea
tin
g
m
ajo
r
ch
allen
g
es
f
o
r
b
ig
d
ata
an
aly
s
is
[
1
5
]
.
T
h
is
r
ap
i
d
g
r
o
w
th
h
as
also
s
h
ap
e
d
d
ata
s
cien
ce
ed
u
ca
tio
n
th
r
o
u
g
h
s
p
ec
ialized
p
r
o
g
r
am
s
in
d
ata
en
g
in
ee
r
in
g
an
d
an
aly
tics
[
1
6
]
.
B
ey
o
n
d
th
e
f
iv
e
Vs
o
f
b
ig
d
ata
(
v
o
lu
m
e,
v
elo
city
,
v
ar
iety
,
v
al
u
e,
an
d
v
er
ac
ity
)
[
1
7
]
,
is
s
u
es o
f
d
ata
q
u
ality
,
s
ca
lab
ilit
y
,
r
ea
l tim
e
p
r
o
ce
s
s
in
g
,
an
d
s
y
s
tem
in
teg
r
atio
n
p
er
s
is
t,
wh
ile
d
ee
p
lear
n
in
g
ap
p
licatio
n
s
r
eq
u
ir
e
ad
ap
tiv
e
a
n
d
s
ca
lab
le
AI
te
ch
n
iq
u
es
[
1
8
]
,
[
1
9
]
.
Ma
n
u
al
d
ep
lo
y
m
en
t
o
f
b
ig
d
ata
to
o
ls
in
ten
s
if
ies
th
ese
ch
allen
g
es,
as
Had
o
o
p
o
f
ten
en
co
u
n
ter
s
SS
H,
Nam
eNo
d
e,
Data
No
d
e,
an
d
au
th
en
ticatio
n
er
r
o
r
s
[
2
0
]
,
Sq
o
o
p
m
ay
f
ail
d
u
e
to
I
P
m
is
co
n
f
ig
u
r
atio
n
s
,
au
th
en
ticatio
n
is
s
u
es,
o
r
v
e
r
s
io
n
m
is
m
atch
es
with
J
av
a
an
d
My
SQL
[
2
1
]
,
an
d
Py
th
o
n
in
s
tallatio
n
s
ca
n
s
u
f
f
e
r
f
r
o
m
c
o
r
r
u
p
ted
d
o
wn
lo
ad
s
,
m
i
s
s
in
g
d
ep
en
d
en
cies,
o
r
m
is
co
n
f
ig
u
r
ed
en
v
ir
o
n
m
en
t
v
ar
iab
les
[
2
2
]
.
b.
Ad
v
an
tag
e
o
f
a
u
to
m
atio
n
Prio
r
r
esear
ch
h
ig
h
lig
h
ts
th
e
g
r
o
win
g
im
p
o
r
ta
n
ce
o
f
a
u
to
m
at
io
n
ac
r
o
s
s
v
ar
io
u
s
d
o
m
ain
s
.
D
ata
-
d
r
iv
en
f
r
am
ewo
r
k
s
h
av
e
b
ee
n
d
e
v
elo
p
ed
f
o
r
ad
a
p
tiv
e
KPI
g
en
er
atio
n
[
2
3
]
,
an
d
B
ash
s
cr
ip
tin
g
h
as
b
ee
n
u
s
ed
to
r
ed
u
ce
h
u
m
an
er
r
o
r
in
cy
b
er
s
ec
u
r
ity
o
p
er
atio
n
s
[
2
4
]
,
[
2
5
]
.
B
io
m
ed
ical
s
tu
d
ies
s
h
o
w
th
at
au
to
m
atio
n
m
in
im
izes
d
elay
s
an
d
m
an
u
al
d
iag
n
o
s
tic
er
r
o
r
s
[
2
6
]
,
wh
ile
b
lo
ck
c
h
ain
-
b
ased
au
to
m
atio
n
im
p
r
o
v
es
r
eg
is
tr
atio
n
,
au
th
en
ticatio
n
,
an
d
ac
ce
s
s
co
n
tr
o
l r
eliab
ilit
y
[
2
7
]
.
E
d
u
ca
tio
n
al
an
d
ad
m
in
is
tr
ativ
e
au
to
m
atio
n
h
as
also
d
em
o
n
s
tr
ated
s
u
b
s
tan
tial
tim
e
s
av
in
g
s
an
d
im
p
r
o
v
e
d
ac
cu
r
ac
y
,
as
s
ee
n
in
Py
t
h
o
n
-
b
ased
g
r
ad
i
n
g
au
to
m
atio
n
[
2
8
]
a
n
d
r
o
b
o
tic
p
r
o
ce
s
s
a
u
to
m
atio
n
,
wh
ich
ac
h
iev
ed
a
ze
r
o
-
er
r
o
r
r
ate
c
o
m
p
ar
ed
to
m
an
u
al
p
r
o
ce
d
u
r
es
[
2
9
]
.
Au
to
m
atio
n
to
o
ls
in
m
ed
ical
wo
r
k
f
lo
ws,
s
u
ch
as
th
e
au
to
m
ated
p
lan
ch
ec
k
(
APC
)
,
h
av
e
r
ed
u
ce
d
v
er
if
icatio
n
tim
e
a
n
d
s
ig
n
if
ican
tly
lo
wer
ed
er
r
o
r
r
ates
[
3
0
]
.
Similar
ly
,
au
t
o
m
ated
m
alwa
r
e
d
etec
tio
n
m
eth
o
d
s
s
u
ch
as
Sh
ellB
r
ea
k
er
o
u
tp
er
f
o
r
m
tr
ad
itio
n
al
an
tiv
ir
u
s
en
g
in
es
b
y
ac
h
iev
in
g
lo
wer
f
alse
n
eg
ativ
e
r
ates
[
3
1
]
.
C
o
llectiv
ely
,
th
ese
s
tu
d
ies
s
h
o
w
th
at
au
to
m
atio
n
en
h
an
ce
s
ef
f
icien
cy
,
co
n
s
is
ten
cy
,
r
eliab
ilit
y
,
an
d
u
s
er
s
atis
f
ac
tio
n
[
3
2
]
,
[
3
3
]
.
Ku
b
er
n
etes
f
u
r
th
e
r
s
u
p
p
o
r
ts
au
to
m
atio
n
in
clo
u
d
an
d
ed
g
e
en
v
ir
o
n
m
e
n
ts
b
y
p
r
o
v
id
i
n
g
s
ca
lab
le
co
n
tain
er
m
an
ag
em
en
t
[
3
4
]
.
c.
R
ea
d
in
ess
i
n
d
ices in
I
C
T
an
d
s
y
s
tem
s
T
h
e
tech
n
o
lo
g
y
r
ea
d
in
ess
in
d
ex
(
T
R
I
)
[
3
5
]
m
ea
s
u
r
es
in
d
iv
id
u
al
r
ea
d
in
ess
to
ad
o
p
t
tech
n
o
lo
g
y
th
r
o
u
g
h
f
o
u
r
d
im
en
s
io
n
s
an
d
co
m
p
u
tes
an
o
v
e
r
all
s
co
r
e
b
y
av
e
r
ag
in
g
s
tan
d
ar
d
ized
s
u
b
s
ca
le
v
alu
es
af
ter
r
ev
er
s
in
g
in
h
ib
ito
r
item
s
.
T
h
e
Un
ited
Natio
n
s
E
-
Go
v
er
n
m
en
t
Dev
elo
p
m
en
t
I
n
d
ex
(
E
GDI
)
[
3
6
]
ev
alu
ates
n
atio
n
al
d
ig
ital
r
ea
d
in
ess
u
s
in
g
th
e
m
ea
n
o
f
th
r
ee
n
o
r
m
alize
d
co
m
p
o
n
en
ts
:
o
n
lin
e
s
er
v
ice,
telec
o
m
m
u
n
icatio
n
in
f
r
astru
ctu
r
e,
an
d
h
u
m
an
c
ap
ita
l.
Sm
ith
’
s
Un
if
ied
C
lo
u
d
R
ea
d
in
ess
Ass
ess
m
en
t
Mo
d
el
[
3
7
]
ass
ess
es
o
r
g
an
izatio
n
al
r
ea
d
in
ess
th
r
o
u
g
h
s
ev
en
f
ac
to
r
s
s
u
c
h
as
s
tr
ateg
y
,
tech
n
o
lo
g
y
,
h
u
m
an
ca
p
ital
,
an
d
Secu
r
ity
,
p
r
o
v
id
i
n
g
th
e
c
o
n
ce
p
t
u
al
b
asis
f
o
r
th
e
r
ea
d
in
ess
s
tr
u
ctu
r
e
u
s
ed
in
th
e
ADRI
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
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r
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(
Mo
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1053
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ies
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ev
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g
h
m
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x
a
m
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ly
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k
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n
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o
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u
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ates
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r
ag
m
en
te
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m
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n
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al
p
r
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s
s
es
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3
8
]
,
wh
ile
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tu
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y
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h
o
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at
AI
b
ased
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r
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tr
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t d
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m
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l th
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ea
t r
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d
im
p
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3
9
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ates
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Evaluation Warning : The document was created with Spire.PDF for Python.
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as sh
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(
2
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:
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1
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LC
+
IC
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SV
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≥
0
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8
]
(
2
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w
h
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−
L
C
:
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C
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ile
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le
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2
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m
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m
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tem
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p
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I
ts
p
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b
lic
GitHu
b
[
4
3
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r
elea
s
e
also
s
u
p
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ts
Dev
Op
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wo
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k
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l
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3
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s
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th
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o
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m
alize
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d
im
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s
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e
ef
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icien
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,
er
r
o
r
r
ed
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ctio
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d
u
s
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ati
s
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,
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ch
s
ca
led
f
r
o
m
0
to
1
.
T
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d
er
r
o
r
m
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s
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r
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im
p
r
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v
em
e
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t
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ile
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ef
lects
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ce
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s
e
o
f
u
s
e.
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SE
s
co
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g
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m
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ate
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(
0
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5
0
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0
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7
9
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o
r
lo
w
e
f
f
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[
4
4
]
.
T
h
e
T
E
SE
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co
r
e
is
co
m
p
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ted
as:
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(
1
3
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(
−
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+
(
−
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(
−
5
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(
3
)
w
h
er
e:
−
T
h
e
B
o
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ts
tr
ap
(
)
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p
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at
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4
5
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p
lies
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0
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0
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esam
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les
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a
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5
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am
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ias.
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is
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asically
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eq
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ce
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air
ly
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al
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s
co
r
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w
T
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w
E
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S
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t
h
e
r
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ass
ig
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to
ea
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ic
(
d
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lt
=
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−
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m
,
E
m
,
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r
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tim
e,
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ate,
an
d
av
er
a
g
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s
atis
f
ac
tio
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r
atin
g
,
r
esp
ec
tiv
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.
−
T
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,
E
a
,
S
a
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t
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au
to
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d
v
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tim
e,
e
r
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d
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s
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atin
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r
esp
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2
.
4
.
Resea
rc
h
m
e
t
ho
ds
a
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pa
rt
icipa
nts
T
h
is
s
tu
d
y
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p
lo
y
ed
a
m
ix
ed
m
eth
o
d
s
em
p
ir
ical
d
esig
n
in
t
eg
r
atin
g
ex
p
er
im
en
tal,
q
u
an
tit
ativ
e,
an
d
q
u
alitativ
e
ap
p
r
o
ac
h
es
t
o
v
alid
ate
th
e
FADT
E
SE
f
r
am
ewo
r
k
[
4
6
]
.
Data
wer
e
co
ll
ec
ted
f
r
o
m
8
0
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T
p
r
ac
titi
o
n
er
s
,
d
eter
m
in
e
d
u
s
in
g
Yam
an
e’
s
f
o
r
m
u
la
[
4
7
]
,
with
4
0
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er
f
o
r
m
in
g
th
e
m
an
u
al
in
s
tallatio
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in
th
e
B
ash
s
h
ell
an
d
4
0
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ec
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tin
g
th
e
au
to
m
ated
in
s
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s
in
g
a
B
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s
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A
co
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tr
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lled
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m
p
ar
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m
eth
o
d
s
u
s
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th
e
T
E
SE
m
etr
ics,
an
d
s
tatis
tical
s
ig
n
if
ican
ce
was a
s
s
es
s
ed
u
s
in
g
a
p
air
ed
t
-
test
[
4
8
]
,
[
4
9
]
.
User
s
atis
f
ac
tio
n
was
m
ea
s
u
r
ed
u
s
in
g
a
f
iv
e
-
p
o
in
t
L
ik
er
t
s
ca
le,
an
d
o
p
en
-
e
n
d
ed
f
ee
d
b
ac
k
was
th
em
atica
lly
an
aly
ze
d
[
5
0
]
–
[
5
3
]
.
All p
ar
ticip
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ts
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o
s
s
ess
ed
b
asic L
in
u
x
co
m
m
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d
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lin
e
s
k
ills
,
m
ee
tin
g
th
e
AD
m
o
d
el
p
r
e
r
eq
u
is
ites
.
T
eleg
r
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s
u
p
p
o
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te
d
co
m
m
u
n
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,
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d
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b
h
o
s
ted
all
m
ate
r
ials
f
o
r
r
e
p
r
o
d
u
cib
ilit
y
[
4
3
]
,
i
n
clu
d
in
g
:
−
First I
n
s
tr
u
ctio
n
to
I
n
s
tall Bi
g
Data
.
p
d
f
(
m
a
n
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al
in
s
tallatio
n
g
u
id
e)
−
Seco
n
d
I
n
s
tr
u
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n
to
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n
s
tall Bi
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Data
.
p
d
f
(
au
to
m
ated
in
s
tallatio
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g
u
id
e
)
−
R
esp
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n
d
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t Satis
f
ac
tio
n
Su
r
v
e
y
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p
d
f
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T
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SE
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2
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.
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m
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s
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Per
f
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m
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s
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r
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u
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s
:
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SE
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tr
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an
d
d
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lo
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m
e
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eliab
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ics.
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co
llected
th
r
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g
h
th
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d
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s
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u
r
v
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m
ea
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tim
e
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er
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ate,
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s
in
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tim
estam
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s
,
s
elf
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ated
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tag
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d
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in
t
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item
s
.
Dep
lo
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r
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ty
[
4
3
]
w
as
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alu
ated
u
s
in
g
two
tech
n
i
ca
l
m
etr
ics.
i
)
Su
cc
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ate
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ate
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ii
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ig
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g
a
ten
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co
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eq
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p
lib
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d
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d
in
ess
.
T
h
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s
u
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ate
was c
alcu
lated
as:
(
%
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×
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(
4
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a
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d
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n
ac
cu
r
ac
y
as
:
(
%
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=
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×
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(
5
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2
.
8
.
Da
t
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c
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llect
io
n pro
ce
s
s
a
nd
a
na
ly
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is
Data
co
llectio
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f
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llo
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th
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SE
wo
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w.
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v
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m
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ass
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v
alid
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(
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0
.
8
)
,
p
ar
ticip
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n
ts
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m
an
u
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an
d
a
u
to
m
ated
in
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tallatio
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s
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er
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tical
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d
itio
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s
.
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ata
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s
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th
e
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en
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r
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d
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tallatio
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tim
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n
tin
g
er
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o
r
s
,
a
n
d
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p
tu
r
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n
g
u
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er
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n
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s
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g
f
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p
o
in
t
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item
s
.
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en
t
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eliab
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ata
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e
co
llected
u
s
in
g
th
e
d
ep
lo
y
m
en
t
r
eliab
ilit
y
ch
ec
k
lis
t
,
co
n
s
is
tin
g
o
f
a
f
iv
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-
item
s
u
cc
ess
r
ate
s
ec
tio
n
an
d
a
ten
-
item
co
n
f
i
g
u
r
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n
ac
cu
r
a
cy
s
ec
tio
n
v
er
if
y
in
g
J
av
a,
S
SH,
Had
o
o
p
,
Sq
o
o
p
,
Py
th
o
n
,
p
ip
,
an
d
r
eq
u
ir
ed
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
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8
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I
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1
6
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2
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Ap
r
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2
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1056
lib
r
ar
ies.
C
h
ec
k
lis
t
r
esu
lts
w
er
e
co
n
v
er
ted
to
p
er
ce
n
tag
es
u
s
in
g
(
4
)
an
d
(
5
)
.
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ed
t
-
test
s
an
d
B
o
o
ts
tr
ap
r
esam
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lin
g
(
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0
0
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les,
9
5
%
C
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)
wer
e
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p
p
lied
t
o
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E
SE
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Op
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e
n
d
e
d
co
m
m
e
n
ts
wer
e
th
em
atica
lly
an
aly
ze
d
.
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SS
an
d
E
x
ce
l
s
u
p
p
o
r
ted
s
tatis
tical
test
in
g
,
co
n
f
id
en
ce
-
in
ter
v
al
esti
m
atio
n
,
an
d
v
is
u
aliza
tio
n
u
s
ed
to
d
e
r
iv
e
th
e
C
S.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Ca
s
e
s
t
ud
ies a
nd
a
pp
lic
a
t
io
n scena
rio
s
T
wo
ca
s
e
s
tu
d
ies
co
m
p
ar
ed
m
an
u
al
an
d
au
to
m
ated
in
s
t
allatio
n
m
eth
o
d
s
.
I
n
th
e
m
a
n
u
al
ca
s
e,
p
ar
ticip
an
ts
f
o
llo
wed
th
e
f
ir
s
t in
s
tr
u
ctio
n
g
u
id
e
a
n
d
ty
p
ed
m
u
ltip
le
B
ash
co
m
m
an
d
s
to
i
n
s
tall
Had
o
o
p
,
Sq
o
o
p
,
an
d
Py
th
o
n
,
r
esu
ltin
g
i
n
lo
n
g
er
in
s
tallatio
n
tim
es,
h
ig
h
er
e
r
r
o
r
r
ates,
an
d
g
r
ea
ter
f
ac
ilit
a
to
r
s
u
p
p
o
r
t.
I
n
th
e
au
to
m
ated
ca
s
e,
p
ar
ticip
an
ts
u
s
ed
th
e
FADT
E
SE
s
cr
ip
t
f
r
o
m
th
e
s
ec
o
n
d
i
n
s
tr
u
ctio
n
g
u
id
e
to
in
s
talled
th
e
s
am
e
to
o
ls
u
s
in
g
a
s
in
g
le
B
ash
co
m
m
an
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5
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3
3
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t FADT
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alu
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is
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8
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ir
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Usi
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E
SE
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im
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o
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t
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T
=
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=
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41
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28
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6304
E
r
r
o
r
r
ed
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ctio
n
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E
=
−
=
27
.
00
−
5
.
10
27
.
00
=
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90
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.
00
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0
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8111
Satis
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ac
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ain
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=
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.
070
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2
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3
92
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3364
Fig
u
r
es 2
an
d
3
s
h
o
w
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e
ADRI
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ec
k
an
d
d
ep
lo
y
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en
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u
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t c
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ir
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r
er
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Ap
p
ly
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o
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ap
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% C
I
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,
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p
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6304
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0
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5926
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5941
C
o
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r
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m
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ate
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9
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4
1
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Su
b
s
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tin
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e
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n
d
T
E
SE
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alu
es
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to
(
1
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co
n
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ir
m
s
m
o
d
er
ate
o
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er
all
ef
f
ec
tiv
en
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u
ll r
ea
d
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ess
.
CS
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5941
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5941
or
59
.
41%
3
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9
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P
r
a
ct
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l i
m
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it
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Alth
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th
e
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SE
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r
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o
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ate
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e
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C
S
=
5
9
.
4
1
%),
s
ev
er
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itatio
n
s
r
em
ain
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T
h
e
m
o
d
el
is
p
latf
o
r
m
-
d
ep
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n
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en
t
a
n
d
u
s
es
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al
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weig
h
t
in
d
ices
t
h
at
m
ay
n
o
t
r
ef
lect
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
F
A
DTES
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A
fr
a
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ep
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(
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1059
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iv
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o
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atio
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ts
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o
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n
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tr
ain
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y
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ize
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u
r
e
2
.
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ea
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in
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er
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icatio
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Fig
u
r
e
3
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t
o
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ated
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en
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tp
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t
4.
CO
NCLU
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O
N
T
h
is
s
tu
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y
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r
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ted
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a
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n
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f
r
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m
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k
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at
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r
ates
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ate
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tr
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f
f
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ig
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ata
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in
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ated
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el
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er
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r
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l,
th
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f
r
am
e
wo
r
k
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r
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a
co
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lete
ap
p
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ep
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es,
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d
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n
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t
r
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ty
p
ically
o
b
s
er
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m
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al
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s
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er
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o
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ated
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at
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u
lly
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ep
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o
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to
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ig
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ati
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co
r
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0
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4
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f
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n
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m
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g
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n
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e
n
t.
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h
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f
in
d
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v
alid
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f
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am
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k
d
em
o
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tr
at
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th
at
a
co
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b
in
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to
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a
n
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ep
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t
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ce
s
s
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o
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ig
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en
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.
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th
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f
r
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m
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s
r
em
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in
p
latf
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r
m
d
ep
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en
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,
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o
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r
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k
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f
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n
d
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ed
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etr
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c
weig
h
tin
g
.
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tu
r
e
en
h
an
ce
m
e
n
ts
will
in
clu
d
e
ex
p
an
d
in
g
p
latf
o
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m
s
u
p
p
o
r
t,
in
te
g
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atin
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ia
g
n
o
s
tic
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d
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ec
o
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er
y
m
ec
h
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is
m
s
,
an
d
v
alid
atin
g
th
e
ap
p
r
o
ac
h
in
b
r
o
ad
er
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n
d
u
s
tr
ial
co
n
tex
ts
to
f
u
r
th
er
s
tr
en
g
th
en
th
e
r
o
b
u
s
tn
es
s
an
d
s
ca
lab
ilit
y
o
f
FADT
E
SE.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
e
au
th
o
r
s
th
a
n
k
t
h
ei
r
c
o
-
a
u
th
o
r
s
f
o
r
g
u
id
a
n
ce
,
p
ee
r
r
ev
iewe
r
s
f
o
r
v
alu
ab
le
f
ee
d
b
ac
k
.
T
h
ey
also
ac
k
n
o
wled
g
e
th
e
s
u
p
p
o
r
t o
f
th
e
L
in
co
ln
Un
iv
e
r
s
ity
C
o
lleg
e
Do
cto
r
al
Pro
g
r
a
m
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
is
r
esear
ch
r
ec
eiv
ed
n
o
e
x
te
r
n
al
f
u
n
d
in
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
2
,
Ap
r
il
20
2
6
:
1
0
5
1
-
1
0
6
2
1060
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
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
id
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
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ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
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ate
co
llab
o
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atio
n
.
Na
m
e
o
f
Aut
ho
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So
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Vi
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Fu
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k
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g
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p
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y
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Mid
h
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C
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f
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ter
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DATA AV
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av
ailab
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in
GitHu
b
[
4
3
]
.
T
h
e
d
ataset
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ated
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d
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f
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p
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n
r
ea
s
o
n
ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
T.
H
.
D
a
v
e
n
p
o
r
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