I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
3
9
,
No
.
1
,
Ju
ly
2
0
2
5
,
p
p
.
1
90
~
2
0
1
I
SS
N:
2502
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
3
9
.i
1
.
pp
1
90
-
2
0
1
190
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Benchm
a
rking
sp
ectr
a
l hand
o
f
f
ra
t
e perf
o
rma
nc
e in
co
g
nitive
wireless ne
tworks
wit
h
real mul
ti
-
u
ser a
ccess
Cesa
r
H
er
ná
nd
ez
,
Dieg
o
G
ira
l,
F
re
dy
M
a
rt
ínez
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
En
g
i
n
e
e
r
i
n
g
,
F
a
c
u
l
t
y
Te
c
h
n
o
l
o
g
y
,
U
n
i
v
e
r
si
d
a
d
D
i
s
t
r
i
t
a
l
F
r
a
n
c
i
s
c
o
Jo
s
é
d
e
C
a
l
d
a
s,
B
o
g
o
t
á
D
.
C
,
C
o
l
o
mb
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Au
g
24
,
2
0
2
4
R
ev
is
ed
Dec
2
,
2
0
2
4
Acc
ep
ted
Feb
28
,
2
0
2
5
Co
g
n
it
iv
e
ra
d
io
(CR)
h
a
s
p
r
o
v
e
n
to
b
e
a
n
e
x
c
e
ll
e
n
t
a
lt
e
rn
a
ti
v
e
to
t
h
e
p
ro
b
lem
o
f
i
n
e
fficie
n
t
s
p
e
c
tru
m
u
se
in
wire
les
s
n
e
two
r
k
s.
Ho
we
v
e
r
,
th
e
v
a
st
m
a
jo
rit
y
o
f
p
r
o
p
o
sa
ls
fo
u
n
d
in
th
e
c
u
rre
n
t
l
it
e
ra
tu
re
a
re
re
stricte
d
to
t
h
e
a
c
c
e
s
s
o
f
a
sin
g
le
se
c
o
n
d
a
ry
u
se
r
(S
U)
to
th
e
n
e
two
rk
,
a
n
d
t
h
e
fe
w
p
ro
p
o
sa
ls
with
m
u
lt
i
p
le
a
c
c
e
ss
d
o
n
o
t
tak
e
in
to
a
c
c
o
u
n
t
th
e
a
c
c
e
ss
o
f
o
th
e
r
p
rima
ry
u
se
rs
(P
Us
)
d
u
ri
n
g
th
e
o
p
p
o
rtu
n
i
stic
tran
sm
issio
n
o
f
t
h
e
SU
.
T
h
e
o
b
jec
ti
v
e
o
f
t
h
is
w
o
rk
is
to
p
e
rf
o
rm
a
c
o
m
p
a
ra
ti
v
e
e
v
a
l
u
a
ti
o
n
o
f
th
e
sp
e
c
tral
h
a
n
d
o
ff
(S
H)
ra
t
e
in
c
o
g
n
it
iv
e
wire
les
s
n
e
two
rk
s
with
m
u
lt
i
-
u
se
r
a
c
c
e
ss
in
a
n
e
n
v
iro
n
m
e
n
t
wit
h
o
th
e
r
P
Us
in
te
ra
c
ti
n
g
.
T
o
c
a
rry
o
u
t
t
h
is
e
v
a
lu
a
ti
o
n
,
fo
u
r
SH
m
o
d
e
ls
wit
h
b
e
tt
e
r
p
e
rf
o
rm
a
n
c
e
we
re
se
lec
ted
:
d
e
e
p
lea
rn
i
n
g
(DL)
,
fe
e
d
b
a
c
k
fu
z
z
y
a
n
a
ly
ti
c
h
iera
r
c
h
y
p
ro
c
e
ss
(
F
F
AH
P
)
,
sim
p
le
a
d
d
it
iv
e
we
ig
h
ti
n
g
(
S
AW
),
a
n
d
Na
ïv
e
Ba
y
e
s
(NB)
,
w
h
ich
we
re
v
a
li
d
a
ted
a
c
c
o
rd
in
g
to
th
e
m
e
tri
c
o
f
th
e
n
u
m
b
e
r
o
f
to
tal
h
a
n
d
o
ffs,
u
n
d
e
r
fo
u
r
sc
e
n
a
ri
o
s
g
iv
e
n
b
y
th
e
c
o
m
b
in
a
ti
o
n
o
f
t
h
e
f
o
ll
o
wi
n
g
p
a
ra
m
e
ters
:
lo
w
sp
e
c
tral
a
v
a
il
a
b
il
it
y
,
h
ig
h
sp
e
c
tral
a
v
a
il
a
b
il
it
y
,
a
c
ti
v
e
p
re
se
n
c
e
o
f
o
th
e
rs
S
Us
,
a
n
d
p
a
ss
iv
e
p
re
se
n
c
e
o
f
o
th
e
rs
S
Us
.
Th
e
re
s
u
lt
s
sh
o
w
t
h
a
t
e
a
c
h
m
o
d
e
l
p
e
rfo
rm
s
we
ll
a
c
c
o
rd
in
g
to
th
e
sc
e
n
a
rio
in
wh
ic
h
it
is
e
x
e
c
u
ted
,
su
g
g
e
stin
g
a
n
a
d
a
p
t
iv
e
m
u
lt
i
-
m
o
d
e
l
a
s
a
p
ro
p
o
sa
l.
K
ey
w
o
r
d
s
:
B
en
ch
m
ar
k
in
g
C
o
g
n
itiv
e
r
ad
io
n
etwo
r
k
s
Han
d
o
f
f
m
o
d
els
Mu
ltiu
s
er
Per
f
o
r
m
an
ce
S
p
ec
tr
u
m
allo
ca
tio
n
Sp
ec
tr
u
m
h
an
d
o
f
f
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
:
C
esar
Her
n
án
d
ez
Dep
ar
tm
en
t o
f
E
lectr
ical
E
n
g
i
n
ee
r
in
g
,
Facu
lty
T
ec
h
n
o
lo
g
y
Un
iv
er
s
id
ad
Dis
tr
ital Fr
an
cisco
J
o
s
é
d
e
C
ald
as
B
o
g
o
tá
D.
C
.
,
C
o
lo
m
b
ia
E
m
ail: c
ah
er
n
an
d
ez
s
@
u
d
is
tr
it
al.
ed
u
.
co
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
id
ea
b
eh
in
d
c
o
g
n
itiv
e
r
ad
io
(
C
R
)
s
tem
s
f
r
o
m
th
e
u
n
d
er
s
tan
d
in
g
th
at
th
e
r
ad
io
f
r
eq
u
e
n
cy
s
p
ec
tr
u
m
is
a
f
in
ite
r
eso
u
r
ce
,
wh
ich
is
o
f
ten
s
ig
n
if
ican
tl
y
u
n
d
e
r
u
tili
ze
d
.
T
h
is
u
n
d
er
u
tili
za
tio
n
r
esu
lts
in
d
im
in
is
h
ed
o
v
er
all
s
p
ec
tr
u
m
ef
f
icien
c
y
.
As
n
o
ted
in
v
ar
io
u
s
s
tu
d
ies,
CR
tech
n
o
lo
g
y
aim
s
to
f
u
lf
ill
th
e
in
cr
ea
s
in
g
b
an
d
wid
th
(
B
W
)
d
em
an
d
s
o
f
m
o
d
e
r
n
d
ev
ices
th
r
o
u
g
h
its
ab
ilit
y
to
d
y
n
am
icall
y
r
ec
o
n
f
ig
u
r
e
its
elf
.
C
o
n
s
eq
u
en
tly
,
t
h
e
o
p
er
atio
n
o
f
a
c
o
g
n
itiv
e
n
etwo
r
k
(
s
p
ec
if
i
ca
lly
r
eg
ar
d
in
g
th
e
allo
ca
tio
n
an
d
d
ea
llo
ca
t
io
n
o
f
r
ad
io
r
eso
u
r
ce
s
)
is
in
h
er
e
n
tly
co
m
p
lex
.
T
h
is
co
m
p
le
x
ity
ar
is
es
b
ec
au
s
e
th
e
n
etwo
r
k
n
o
d
es
m
u
s
t
co
n
tin
u
o
u
s
ly
ad
ap
t th
eir
b
e
h
av
io
r
b
ased
o
n
th
e
lo
ca
l in
f
o
r
m
atio
n
a
v
ailab
le
ab
o
u
t th
eir
s
u
r
r
o
u
n
d
i
n
g
en
v
ir
o
n
m
en
t [
1
]
-
[
4
]
.
C
o
g
n
itiv
e
r
ad
io
n
etwo
r
k
s
(
C
R
Ns)
h
av
e
b
ee
n
p
r
o
p
o
s
ed
as
a
v
iab
le
s
o
lu
tio
n
to
ad
d
r
ess
th
e
is
s
u
e
o
f
s
p
ec
tr
al
s
ca
r
city
b
y
allo
win
g
s
ec
o
n
d
ar
y
u
s
er
s
(
SUs
)
to
tem
p
o
r
ar
ily
u
tili
ze
u
n
u
s
ed
s
p
ec
tr
u
m
s
eg
m
en
ts
,
k
n
o
w
n
as
s
p
ec
tr
al
o
p
p
o
r
tu
n
ities
(
SO
s
)
.
T
h
is
ac
ce
s
s
is
p
r
o
v
i
d
ed
o
n
th
e
c
o
n
d
itio
n
th
at
p
r
im
ar
y
u
s
er
s
(
PUs
)
d
o
n
o
t
ex
p
er
ien
ce
an
y
d
eg
r
a
d
atio
n
in
th
eir
q
u
ality
o
f
s
er
v
ice.
A
s
ig
n
if
ican
t c
h
allen
g
e
with
in
th
is
co
n
tex
t is m
an
ag
in
g
s
p
ec
tr
al
h
an
d
o
f
f
s
(
SHs
)
(
o
r
th
e
s
witch
in
g
o
f
ch
an
n
els am
o
n
g
CR
s
)
ef
f
icien
tly
,
with
th
e
ai
m
o
f
m
in
im
izin
g
th
e
f
r
eq
u
e
n
cy
o
f
th
es
e
h
an
d
o
f
f
s
d
u
r
in
g
e
x
ten
d
ed
co
m
m
u
n
icatio
n
p
er
io
d
s
[
5
]
-
[
8
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
B
en
ch
ma
r
kin
g
s
p
ec
tr
a
l h
a
n
d
o
ff ra
te
p
erfo
r
ma
n
ce
in
co
g
n
itiv
e
w
ir
ele
s
s
n
etw
o
r
k
s
…
(
C
esa
r
Hern
á
n
d
ez
)
191
Mo
r
eo
v
er
,
it
is
cr
itical
to
co
n
s
id
er
s
ce
n
ar
io
s
wh
er
e
m
u
ltip
le
SUs
s
im
u
ltan
eo
u
s
ly
s
ee
k
to
o
p
p
o
r
tu
n
is
tically
ac
ce
s
s
th
e
licen
s
ed
s
p
ec
tr
u
m
h
eld
b
y
P
Us
.
I
n
s
u
ch
ca
s
es,
ef
f
ec
tiv
e
m
u
lti
-
u
s
er
ac
ce
s
s
s
tr
ateg
ies m
u
s
t b
e
d
ev
elo
p
ed
to
ac
co
u
n
t
f
o
r
t
h
e
u
n
p
r
ed
ictab
l
e
ar
r
iv
al
an
d
d
ep
ar
t
u
r
e
o
f
PUs
d
u
r
in
g
th
e
o
n
g
o
in
g
tr
an
s
m
is
s
io
n
s
o
f
SUs
.
T
h
is
d
y
n
am
ic
b
eh
av
io
r
n
ec
ess
itates
s
o
p
h
is
ticated
ap
p
r
o
ac
h
es
to
en
s
u
r
e
s
ea
m
less
co
m
m
u
n
ica
tio
n
an
d
o
p
tim
al
u
s
e
o
f
th
e
av
ailab
l
e
s
p
ec
tr
u
m
[
9
]
-
[
1
3
]
.
B
u
ild
in
g
u
p
o
n
th
e
af
o
r
e
m
en
ti
o
n
ed
co
n
tex
t,
th
is
s
tu
d
y
aim
s
to
co
n
d
u
ct
a
c
o
m
p
ar
ativ
e
a
n
aly
s
is
o
f
th
e
SH
r
ate
in
co
g
n
itiv
e
wir
el
ess
n
etwo
r
k
s
f
ea
tu
r
i
n
g
m
u
l
ti
-
u
s
er
ac
ce
s
s
with
in
a
r
ea
l
is
tic
en
v
ir
o
n
m
e
n
t.
Sp
ec
if
ically
,
th
is
en
v
ir
o
n
m
en
t
in
clu
d
es
PUs
d
y
n
am
ically
en
ter
in
g
an
d
e
x
itin
g
th
e
licen
s
ed
s
p
ec
tr
u
m
d
u
r
i
n
g
th
e
o
p
p
o
r
t
u
n
is
tic
u
tili
za
tio
n
b
y
SUs
.
Fo
r
th
is
ev
alu
atio
n
,
f
o
u
r
SH
m
o
d
els
d
e
m
o
n
s
tr
atin
g
s
u
p
er
io
r
p
e
r
f
o
r
m
an
ce
wer
e
ch
o
s
en
:
d
ee
p
lea
r
n
in
g
(
DL
)
,
f
ee
d
b
ac
k
f
u
zz
y
an
al
y
tic
h
ier
ar
ch
y
p
r
o
ce
s
s
(
FF
AHP
)
,
s
im
p
le
ad
d
itiv
e
weig
h
tin
g
(
SAW
)
,
an
d
Naïv
e
B
ay
es
(
NB
)
.
T
h
ese
m
o
d
el
s
wer
e
ass
ess
ed
b
ased
o
n
th
e
to
tal
n
u
m
b
e
r
o
f
h
an
d
o
f
f
s
(
AAH)
u
n
d
er
f
o
u
r
d
is
tin
ct
s
ce
n
ar
io
s
,
ch
ar
ac
ter
ized
b
y
th
e
f
o
llo
win
g
co
m
b
in
ati
o
n
s
o
f
p
ar
am
eter
s
:
lo
w
s
p
ec
tr
al
av
ailab
ilit
y
(
h
ig
h
tr
af
f
ic
o
r
HT
)
,
h
ig
h
s
p
ec
tr
al
a
v
ailab
ilit
y
(
lo
w
tr
a
f
f
ic
o
r
L
T
)
,
ac
tiv
e
p
r
esen
ce
o
f
SUs
(
r
ea
l
m
o
d
e
)
,
a
n
d
p
ass
iv
e
p
r
esen
ce
o
f
SUs
(
co
n
v
en
tio
n
a
l
m
o
d
e)
.
I
n
th
e
cu
r
r
en
t
liter
atu
r
e
we
d
o
n
o
t
f
in
d
r
elate
d
wo
r
k
s
th
at
co
n
s
id
er
a
r
ea
lis
tic
m
u
lti
-
u
s
er
en
v
ir
o
n
m
e
n
t w
ith
d
y
n
am
ic
b
eh
av
io
r
o
f
th
e
PUs
.
T
h
e
s
tr
u
ctu
r
e
o
f
th
is
s
tu
d
y
is
o
r
g
an
ized
in
to
f
iv
e
s
ec
tio
n
s
.
Sectio
n
2
p
r
o
v
id
es
a
d
etailed
d
escr
ip
tio
n
o
f
th
e
r
esear
ch
m
eth
o
d
o
lo
g
y
,
in
clu
d
in
g
th
e
s
elec
tio
n
o
f
S
H
m
o
d
els,
ex
p
er
im
en
tal
d
esi
g
n
,
d
ec
is
io
n
-
m
a
k
in
g
cr
iter
ia,
an
d
p
er
f
o
r
m
an
ce
m
e
tr
ics.
Sectio
n
3
p
r
esen
ts
th
e
r
esu
lts
o
b
tain
ed
f
r
o
m
th
e
an
aly
s
is
an
d
o
f
f
er
s
a
co
m
p
ar
ativ
e
e
x
am
in
atio
n
o
f
th
e
ev
alu
atio
n
m
etr
ics.
Sectio
n
4
f
o
cu
s
es
o
n
th
e
d
is
cu
s
s
io
n
o
f
th
ese
r
esu
lts
,
in
ter
p
r
etin
g
th
e
f
in
d
in
g
s
in
th
e
co
n
tex
t
o
f
th
e
o
b
jectiv
es
s
et
f
o
r
th
.
T
h
e
f
in
al
s
ec
tio
n
s
u
m
m
ar
izes
th
e
m
ain
co
n
clu
s
io
n
s
o
f
t
h
e
s
tu
d
y
,
h
ig
h
l
ig
h
tin
g
th
e
k
ey
c
o
n
tr
ib
u
tio
n
s
a
n
d
p
o
te
n
tial a
r
ea
s
f
o
r
f
u
tu
r
e
r
e
s
ea
r
ch
.
2.
M
E
T
H
O
D
T
h
is
s
ec
tio
n
o
u
tlin
es
th
e
m
eth
o
d
o
lo
g
y
em
p
lo
y
e
d
in
th
e
r
esear
ch
.
I
t
b
e
g
in
s
with
a
d
etailed
d
escr
ip
tio
n
o
f
th
e
ex
p
er
im
en
t
al
d
esig
n
,
wh
ich
f
o
r
m
s
th
e
f
o
u
n
d
atio
n
o
f
th
e
s
tu
d
y
.
Fo
llo
w
in
g
th
is
,
th
e
cr
iter
ia
u
s
ed
f
o
r
d
ec
is
io
n
-
m
ak
i
n
g
in
s
elec
tin
g
th
e
o
p
tim
al
f
r
e
q
u
en
cy
ch
a
n
n
el
o
r
s
p
ec
tr
al
o
p
p
o
r
tu
n
ity
(
SO)
f
o
r
ex
ec
u
tin
g
t
h
e
SH
ar
e
e
x
p
lain
e
d
.
Nex
t,
t
h
e
s
ec
tio
n
p
r
o
v
i
d
e
s
an
o
v
e
r
v
iew
o
f
th
e
s
p
ec
if
ic
h
a
n
d
o
f
f
(
HS)
m
o
d
els
th
at
wer
e
c
h
o
s
en
f
o
r
ev
alu
ati
o
n
.
Fin
ally
,
it
co
n
clu
d
es
with
a
p
r
esen
tatio
n
o
f
t
h
e
p
e
r
f
o
r
m
an
ce
m
etr
ics
th
at
wer
e
ap
p
lied
to
f
ac
ilit
ate
th
e
co
m
p
ar
ativ
e
a
n
aly
s
is
o
f
th
ese
m
o
d
els.
2
.
1
.
E
x
perim
ent
d
esig
n
T
h
e
co
m
p
ar
ativ
e
e
v
alu
atio
n
o
f
th
e
s
elec
ted
SH
m
o
d
els
was
co
n
d
u
cted
u
s
in
g
a
s
im
u
latio
n
to
o
l
p
r
ev
io
u
s
ly
d
ev
elo
p
ed
f
o
r
th
i
s
p
u
r
p
o
s
e.
T
h
is
to
o
l
u
tili
ze
s
r
ea
l
s
p
ec
tr
al
o
cc
u
p
a
n
cy
d
at
a
g
ath
er
e
d
f
r
o
m
a
m
ea
s
u
r
em
en
t
ca
m
p
aig
n
ca
r
r
ie
d
o
u
t
in
B
o
g
o
tá,
C
o
lo
m
b
ia
[
1
4
]
.
T
h
e
s
im
u
latio
n
t
o
o
l
r
ec
o
n
s
tr
u
cts
th
e
s
p
ec
tr
u
m
o
cc
u
p
an
c
y
p
atter
n
s
o
v
er
tim
e
b
y
em
p
lo
y
in
g
ex
p
er
im
en
tal
d
ata
tr
ac
es
r
ec
o
r
d
e
d
in
th
e
GS
M
b
an
d
,
p
r
o
v
id
in
g
a
clo
s
e
ap
p
r
o
x
im
atio
n
o
f
th
e
r
e
al
b
eh
av
io
r
o
f
PUs
with
in
th
e
s
im
u
lated
en
v
ir
o
n
m
en
t.
T
h
is
ap
p
r
o
ac
h
en
ab
les
a
mo
r
e
ac
cu
r
ate
ass
ess
m
en
t
o
f
ea
ch
alg
o
r
ith
m
’
s
ac
tu
al
p
er
f
o
r
m
an
ce
[
1
5
]
,
[
1
6
]
.
T
h
e
d
a
ta
s
et
u
s
ed
in
th
e
s
im
u
latio
n
r
ef
lects o
n
e
m
o
n
th
o
f
co
n
tin
u
o
u
s
o
b
s
er
v
atio
n
co
ll
ec
ted
in
B
o
g
o
tá
D.
C
.
,
C
o
lo
m
b
ia
[
1
4
]
.
W
h
en
a
SU
in
ten
d
s
to
tr
an
s
m
it
f
o
r
φ
m
in
u
tes,
th
e
s
im
u
latio
n
to
o
l
f
o
llo
ws
a
s
tr
u
ctu
r
ed
s
e
q
u
en
ce
o
f
s
tep
s
.
First,
it u
p
d
ates th
e
d
ec
is
io
n
cr
iter
ia
(
DC
)
v
alu
es b
ased
o
n
in
f
o
r
m
atio
n
av
ailab
le
b
ef
o
r
e
th
e
cu
r
r
en
t tim
e
in
s
tan
t,
r
ef
er
r
ed
to
as τ
0
,
wh
en
th
e
SU r
eq
u
ests
ac
ce
s
s
to
th
e
s
p
ec
tr
al
r
eso
u
r
ce
.
Seco
n
d
,
th
e
to
o
l r
an
k
s
th
e
SO
s
ac
co
r
d
in
g
to
th
e
s
co
r
es
g
en
e
r
a
ted
b
y
th
e
d
ec
is
io
n
-
m
ak
i
n
g
al
g
o
r
ith
m
u
n
d
er
ev
alu
ati
o
n
.
T
h
i
r
d
,
th
e
SO
with
th
e
h
ig
h
est
r
an
k
is
s
elec
ted
an
d
as
s
ig
n
ed
to
th
e
SU,
in
itiatin
g
its
tr
an
s
m
is
s
io
n
.
Fo
u
r
th
,
at
tim
e
τ
1
,
th
e
t
o
o
l
c
h
ec
k
s
th
e
d
atab
ase
o
f
ca
p
tu
r
ed
a
n
d
p
r
o
ce
s
s
ed
d
ata
to
d
eter
m
in
e
wh
eth
er
th
e
s
elec
ted
SO
r
e
m
a
in
s
av
ailab
le.
Sin
ce
SH
m
o
d
els
r
ely
s
o
lely
o
n
th
e
p
r
o
b
a
b
ilit
y
o
f
av
ailab
ilit
y
(
AP)
r
ath
er
th
an
r
ea
l
-
tim
e
av
ailab
i
lity
d
ata,
if
th
e
S
O
is
s
t
ill
ac
ce
s
s
ib
le,
th
e
cu
m
u
lati
v
e
h
an
d
o
f
f
m
etr
ic
(
AAH)
is
in
cr
em
en
ted
b
y
o
n
e,
an
d
th
e
n
e
x
t
s
tep
is
ex
ec
u
ted
.
I
f
n
o
t,
t
h
e
alter
n
ativ
e
h
an
d
o
f
f
m
etr
ic
(
AAFH)
is
in
cr
em
en
ted
,
an
d
t
h
e
n
ex
t
r
an
k
e
d
SO
is
ch
o
s
en
,
r
etu
r
n
in
g
to
th
e
p
r
ev
io
u
s
s
tep
.
T
h
e
to
o
l
th
e
n
p
e
r
f
o
r
m
s
a
co
n
ti
n
u
o
u
s
ch
ec
k
at
ea
ch
tim
e
s
tep
(
T
S)
to
v
er
i
f
y
if
t
h
e
SO
cu
r
r
e
n
tly
in
u
s
e
b
y
th
e
SU
r
em
ain
s
av
ailab
le.
I
f
,
at
an
y
tim
e
τ
k
,
a
PU
d
em
an
d
s
th
e
s
elec
ted
SO,
r
en
d
er
in
g
it
u
n
av
ailab
le
ac
co
r
d
in
g
to
th
e
d
ata
b
ase,
an
d
th
e
elap
s
ed
tim
e,
ca
lcu
lated
a
s
Δ
τ
=
τ
k
–
τ
1
,
is
less
th
an
6
0
s
ec
o
n
d
s
,
th
e
s
y
s
tem
s
elec
ts
th
e
n
ex
t
SO
in
th
e
r
an
k
in
g
an
d
r
etu
r
n
s
to
th
e
p
r
io
r
s
tep
.
I
f
th
is
co
n
d
itio
n
is
n
o
t
m
et,
τ
0
is
u
p
d
ated
to
r
ef
lect
th
e
n
ew
cu
r
r
en
t
tim
e,
an
d
th
e
en
tire
p
r
o
ce
d
u
r
e
b
e
g
in
s
an
ew.
I
f
,
a
f
ter
a
d
u
r
atio
n
o
f
ζ
s
ec
o
n
d
s
,
n
o
s
u
itab
le
ch
an
n
el
is
f
o
u
n
d
,
t
h
e
co
m
m
u
n
icatio
n
is
d
ee
m
e
d
t
o
h
av
e
f
ailed
.
2
.
2
.
Dec
is
io
n
c
rit
er
ia
All
h
an
d
o
f
f
(
HS)
m
o
d
els
u
tili
ze
d
in
th
is
s
tu
d
y
r
elied
o
n
f
o
u
r
k
ey
DC
to
id
en
tify
t
h
e
o
p
tim
al
ch
an
n
el
f
o
r
SH
: th
e
AP
,
th
e
e
s
tim
ated
tim
e
o
f
av
ailab
ilit
y
(
E
T
A)
,
th
e
s
ig
n
al
-
to
-
n
o
is
e
r
atio
(
SIN
R
)
,
an
d
th
e
B
W
.
T
h
ese
cr
iter
ia
wer
e
d
er
iv
ed
f
r
o
m
s
p
ec
tr
al
d
ata
th
at
h
ad
b
ee
n
p
r
ev
io
u
s
ly
co
llected
.
T
o
ac
cu
r
ately
p
er
f
o
r
m
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
9
,
No
.
1
,
Ju
ly
20
25
:
1
90
-
2
0
1
192
ev
alu
atio
n
,
it
was
cr
u
cial
to
c
o
m
p
u
te
v
alu
es
f
o
r
ea
ch
o
f
th
e
f
o
u
r
DC
(
AP,
E
T
A,
SIN
R
,
an
d
B
W
)
f
o
r
ev
er
y
en
tr
y
in
th
e
tr
ain
in
g
m
atr
ix
,
g
iv
en
th
at
th
e
SH
alg
o
r
ith
m
s
d
id
n
o
t
h
a
v
e
an
y
p
r
e
-
e
x
is
tin
g
k
n
o
wled
g
e
o
f
th
ese
v
alu
es.
T
h
e
AP
v
ar
iab
le
o
f
f
er
s
a
n
o
r
m
alize
d
r
ep
r
esen
tatio
n
o
f
th
e
d
u
ty
cy
cle
f
o
r
ea
c
h
o
f
t
h
e
5
0
0
p
o
ten
tial
SO
s
p
r
esen
t
in
t
h
e
m
at
r
ix
.
T
h
e
E
T
A
v
ar
iab
le
ca
lcu
lates
th
e
av
er
ag
e
d
u
r
atio
n
f
o
r
wh
ich
ea
ch
ch
a
n
n
el
r
em
ain
s
co
n
tin
u
o
u
s
ly
av
ailab
le.
T
h
is
is
d
eter
m
in
ed
b
y
f
ir
s
t
id
en
tify
in
g
all
p
er
io
d
s
d
u
r
in
g
w
h
ich
a
ch
an
n
el
is
co
n
tin
u
o
u
s
ly
ac
ce
s
s
ib
le,
f
o
llo
wed
b
y
ca
lcu
latin
g
th
e
m
ea
n
o
f
th
ese
d
u
r
atio
n
s
f
o
r
ea
c
h
ch
a
n
n
el.
T
h
e
SIN
R
v
ar
iab
le
q
u
an
tifie
s
th
e
av
er
ag
e
r
ati
o
o
f
s
ig
n
al
p
o
wer
to
th
e
n
o
is
e
f
lo
o
r
,
wh
ic
h
r
ef
lects
th
e
q
u
ality
o
f
th
e
ch
a
n
n
el.
T
h
e
B
W
v
ar
iab
le
d
e
n
o
tes
th
e
av
er
a
g
e
BW
f
o
r
ea
c
h
c
h
an
n
el.
Sin
c
e
all
ch
an
n
els
h
av
e
an
id
en
tical
BW
o
f
1
0
0
k
Hz,
th
e
B
W
v
ar
iab
le
d
o
es
n
o
t
p
r
o
v
id
e
s
ig
n
if
ican
t
d
if
f
er
en
tiatio
n
in
it
s
b
asic
f
o
r
m
.
T
o
en
h
an
ce
th
e
r
elev
a
n
ce
o
f
t
h
e
BW
cr
iter
io
n
,
th
e
B
W
f
o
r
e
ac
h
p
o
te
n
tial
SO
was
ex
p
an
d
e
d
to
i
n
co
r
p
o
r
ate
u
p
to
f
o
u
r
ad
jace
n
t
ch
a
n
n
els
o
n
b
o
th
s
id
es,
ass
u
m
in
g
th
ey
wer
e
co
n
tin
u
o
u
s
ly
av
ailab
le,
th
u
s
cr
ea
tin
g
a
b
r
o
ad
e
r
,
co
m
p
o
s
ite
ch
an
n
el.
Alth
o
u
g
h
all
ch
an
n
els
in
th
e
GSM
b
a
n
d
ty
p
ically
h
av
e
a
BW
o
f
2
0
0
k
Hz,
d
u
e
to
th
e
s
p
ec
if
ic
tech
n
ical
p
ar
am
eter
s
s
et
o
n
th
e
s
p
ec
tr
u
m
a
n
aly
ze
r
d
u
r
in
g
th
e
m
ea
s
u
r
em
e
n
t
ca
m
p
aig
n
,
th
e
s
p
ec
tr
al
o
cc
u
p
an
c
y
d
ata
was c
ap
tu
r
ed
i
n
s
eg
m
en
ts
with
a
f
ix
ed
BW
o
f
1
0
0
k
Hz.
2
.
3
.
H
a
n
do
f
f
m
o
dels
A
r
ev
iew
o
f
th
e
cu
r
r
en
t
liter
at
u
r
e
o
n
SH
in
C
R
N
was
co
n
d
u
cted
to
id
en
tify
s
u
itab
le
alg
o
r
ith
m
s
f
o
r
co
m
p
ar
is
o
n
with
th
e
n
ewly
d
ev
elo
p
ed
alg
o
r
ith
m
s
p
r
esen
te
d
in
th
is
s
tu
d
y
.
T
h
e
s
elec
tio
n
p
r
o
ce
s
s
to
o
k
in
to
ac
co
u
n
t
t
h
e
p
er
f
o
r
m
an
ce
o
u
tc
o
m
es
r
ep
o
r
ted
f
o
r
th
ese
alg
o
r
ith
m
s
,
alo
n
g
with
th
eir
u
n
d
er
l
y
in
g
m
ath
em
atica
l
p
r
in
cip
les
an
d
th
e
clar
ity
o
f
th
eir
m
eth
o
d
o
l
o
g
ies,
wh
ich
f
ac
ilit
ate
r
ep
r
o
d
u
cib
ilit
y
.
Mu
lt
i
-
cr
iter
ia
d
ec
is
io
n
-
m
ak
in
g
(
MCDM)
m
eth
o
d
s
we
r
e
ch
o
s
en
as
th
ey
o
f
f
e
r
a
r
o
b
u
s
t
m
ath
em
atica
l
f
r
am
ewo
r
k
f
o
r
m
o
d
elin
g
th
e
SH
p
r
o
ce
s
s
in
s
itu
atio
n
s
in
v
o
l
v
in
g
m
u
ltip
le
v
a
r
iab
les,
p
r
o
v
id
in
g
a
h
ig
h
ly
ef
f
ec
tiv
e
ap
p
r
o
ac
h
f
o
r
e
v
alu
atin
g
an
d
s
elec
tin
g
SO
s
[
1
]
,
[
1
7
]
-
[
2
0
]
.
Du
e
to
th
eir
p
r
o
v
en
ef
f
icac
y
,
MCDM
m
eth
o
d
s
h
av
e
b
ee
n
w
id
ely
ap
p
lied
in
SH
co
n
tex
ts
.
T
h
e
s
p
ec
if
ic
alg
o
r
ith
m
s
s
elec
ted
f
o
r
c
o
m
p
a
r
is
o
n
in
th
is
s
tu
d
y
ar
e
FF
AHP,
NB
,
SAW
,
an
d
DL
[
1
]
,
[
2
1
]
-
[
2
8
]
.
2
.
3
.
1
F
F
AH
P
T
h
e
FF
AHP
alg
o
r
ith
m
is
d
esi
g
n
ed
to
e
n
h
an
ce
t
h
e
ac
cu
r
ac
y
o
f
s
elec
tin
g
SO
s
.
T
o
ac
h
iev
e
th
is
g
o
al,
FF
AHP
u
tili
ze
s
f
ee
d
b
ac
k
f
r
o
m
p
r
ev
io
u
s
ly
co
n
d
u
cted
SO
ev
alu
atio
n
s
to
r
ef
in
e
its
s
ele
ctio
n
p
r
o
ce
s
s
.
T
h
e
ch
o
ice
o
f
SO is d
eter
m
in
e
d
b
y
an
aly
zin
g
b
o
th
c
u
r
r
e
n
t sp
ec
tr
al
d
ata
an
d
h
is
to
r
ical
ass
ess
m
e
n
t r
esu
lts
.
T
h
e
s
p
ec
tr
u
m
d
ata
d
etec
tio
n
p
r
o
ce
s
s
in
v
o
l
v
es
ca
p
tu
r
i
n
g
k
e
y
p
ar
a
m
eter
s
,
s
u
ch
as
f
r
e
q
u
en
cy
,
s
ig
n
al
p
o
wer
,
a
n
d
tim
e
in
ter
v
als.
T
h
ese
m
ea
s
u
r
em
en
ts
ar
e
in
f
lu
en
ce
d
b
y
s
ettin
g
s
o
n
th
e
s
p
ec
tr
u
m
an
aly
ze
r
,
in
clu
d
in
g
th
e
r
eso
lu
ti
o
n
b
an
d
wid
th
(
R
B
W
)
,
th
e
f
r
eq
u
en
c
y
s
p
an
,
an
d
th
e
s
wee
p
tim
e
[
1
4
]
,
[
1
6
]
.
All
th
e
ac
q
u
ir
ed
d
ata
a
r
e
s
y
s
tem
atica
lly
s
to
r
ed
i
n
a
d
ed
icate
d
d
ata
b
ase.
T
h
e
p
r
o
c
ess
in
g
u
n
it
p
er
io
d
ically
ca
lcu
lates
th
e
v
alu
es
f
o
r
th
e
DC
(
s
u
ch
a
s
AP
,
E
T
A,
SIN
R
,
a
n
d
B
W
)
an
d
n
o
r
m
alize
s
th
ese
v
alu
es
o
n
a
s
ca
le
f
r
o
m
0
to
1
0
0
.
T
h
e
FF
AHP
alg
o
r
ith
m
th
en
u
tili
ze
s
th
is
n
o
r
m
alize
d
d
ata
to
ass
es
s
ea
ch
SO.
T
h
e
s
c
o
r
e
ass
ig
n
ed
to
ea
ch
SO
,
in
d
icate
d
b
y
i
,
is
d
eter
m
i
n
ed
u
s
in
g
(
1
)
,
wh
er
e
t
h
e
s
co
r
e
r
an
g
es
b
etwe
en
0
an
d
1
0
0
,
with
1
0
0
in
d
icatin
g
th
e
h
ig
h
est p
o
s
s
ib
le
s
co
r
e.
Fig
u
r
e
1
illu
s
tr
ates th
e
d
esig
n
a
n
d
wo
r
k
f
lo
w
o
f
th
e
FF
AHP
alg
o
r
ith
m
.
Fig
u
r
e
1
.
Sch
em
atic
r
ep
r
esen
t
atio
n
o
f
th
e
p
r
o
p
o
s
e
d
FF
AHP
alg
o
r
ith
m
At
th
is
s
tag
e
o
f
th
e
p
r
o
ce
s
s
,
ea
ch
SO
is
in
itially
r
an
k
ed
b
ased
s
o
lely
o
n
th
e
cu
r
r
en
t v
alu
es o
f
th
e
DC
.
Ho
wev
er
,
th
e
SO
th
at
r
a
n
k
s
h
ig
h
est
at
th
is
p
o
in
t
m
ay
n
o
t
u
ltima
tely
b
e
ch
o
s
en
,
as
t
h
e
f
in
al
e
v
alu
atio
n
in
co
r
p
o
r
ates
weig
h
ted
ad
ju
s
t
m
en
ts
u
s
in
g
h
is
to
r
ical
s
u
r
v
e
y
d
ata.
T
h
e
f
ee
d
b
ac
k
m
ec
h
a
n
is
m
in
teg
r
ates
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
B
en
ch
ma
r
kin
g
s
p
ec
tr
a
l h
a
n
d
o
ff ra
te
p
erfo
r
ma
n
ce
in
co
g
n
itiv
e
w
ir
ele
s
s
n
etw
o
r
k
s
…
(
C
esa
r
Hern
á
n
d
ez
)
193
cu
r
r
en
t
s
u
r
v
ey
r
esu
lts
(
PS
)
f
o
r
ea
ch
SO
with
b
o
th
th
e
m
o
s
t
r
ec
en
t
s
u
r
v
e
y
d
ata
(
L
S)
an
d
th
e
av
er
ag
e
s
u
r
v
e
y
r
esu
lts
(
AS)
co
llected
o
v
er
t
h
e
p
r
ec
ed
in
g
h
o
u
r
.
T
h
ese
we
ig
h
ted
i
n
p
u
ts
ar
e
th
e
n
u
s
ed
t
o
co
m
p
u
te
a
f
in
al
r
an
k
in
g
f
o
r
ea
ch
SO.
T
h
e
m
et
h
o
d
f
o
r
ca
lcu
latin
g
th
is
f
in
al
r
an
k
in
g
is
o
u
tlin
ed
in
(
1
)
.
_
=
×
+
×
+
(
1
−
−
)
×
(
1
)
Her
e,
α
an
d
β
a
r
e
c
o
ef
f
icien
ts
with
in
th
e
r
an
g
e
[
0
,
1
]
,
an
d
t
h
e
ter
m
“
Fin
al_
Sco
r
e
”
r
ep
r
esen
t
s
th
e
f
in
al
s
u
r
v
ey
v
al
u
e
ass
ig
n
ed
to
ea
c
h
SO
.
T
h
e
SO
with
th
e
h
ig
h
est
f
in
al
s
co
r
e
is
ch
o
s
en
to
in
itiate
d
ata
tr
an
s
m
is
s
io
n
f
o
r
th
e
SU.
Su
b
s
eq
u
en
tly
,
th
e
f
ee
d
b
ac
k
m
ec
h
an
is
m
u
p
d
at
es
th
e
last
s
u
r
v
ey
(
L
S)
v
alu
e
b
y
tr
an
s
f
er
r
in
g
th
e
p
r
esen
t
s
u
r
v
e
y
(
PS
)
v
alu
e
an
d
r
ec
alcu
lates
th
e
AS
v
alu
e
t
o
r
ef
lect
t
h
e
n
ew
L
S
v
alu
e.
I
f
th
e
c
h
o
s
en
SO
is
f
o
u
n
d
to
b
e
o
cc
u
p
ied
,
th
e
FF
A
HP a
lg
o
r
ith
m
r
esets
th
e
L
S v
a
lu
e
to
ze
r
o
f
o
r
t
h
at
p
ar
ticu
lar
SO [
2
1
]
.
2
.
3
.
2
.
Na
ïv
e
B
a
y
es
A
k
ey
f
ac
to
r
in
s
elec
tin
g
an
ap
p
r
o
p
r
iate
p
r
e
d
ictio
n
m
o
d
e
l
is
its
ab
ilit
y
to
i
n
co
r
p
o
r
ate
m
u
ltip
le
ch
ar
ac
ter
is
tics
o
r
cr
iter
ia
th
at
en
h
an
ce
th
e
ac
c
u
r
ac
y
o
f
p
r
ed
ictio
n
s
.
T
h
is
is
im
p
o
r
tan
t
b
ec
au
s
e
d
u
r
in
g
t
h
e
tr
ain
in
g
p
h
ase,
v
a
r
io
u
s
cr
iter
i
a
s
u
ch
as
AP
,
E
T
A,
SIN
R
,
a
n
d
B
W
ca
n
b
e
u
s
ed
,
all
o
f
wh
ich
co
n
t
r
ib
u
te
to
im
p
r
o
v
in
g
th
e
p
r
ed
ictio
n
p
er
f
o
r
m
an
ce
[
2
2
]
,
[
2
5
]
.
Giv
en
th
is
c
o
n
tex
t
an
d
th
e
p
r
in
cip
les
o
f
NB
th
eo
r
em
,
it
ca
n
b
e
co
n
clu
d
ed
th
at
th
e
in
d
ep
en
d
e
n
t
v
ar
iab
les,
o
r
p
r
ed
icto
r
s
,
in
th
i
s
s
p
ec
if
ic
s
ce
n
ar
io
ar
e
AP
an
d
E
T
A,
wh
ile
th
e
d
e
p
en
d
e
n
t
v
ar
iab
le,
o
r
th
e
class
to
b
e
p
r
ed
icted
,
is
ch
an
n
el
av
a
ilab
ilit
y
.
T
h
e
NB
m
o
d
el
is
p
ar
ticu
lar
ly
ef
f
ec
tiv
e
f
o
r
p
r
ed
icti
n
g
m
u
ltip
le
class
es
b
ec
au
s
e
it
o
p
er
ates
u
n
d
er
th
e
ass
u
m
p
tio
n
th
at
ea
ch
p
r
ed
icto
r
is
i
n
d
ep
en
d
en
t
o
f
th
e
o
th
er
s
.
I
n
o
th
er
wo
r
d
s
,
a
NB
class
if
ier
as
s
u
m
es
th
at
th
e
p
r
esen
ce
o
r
a
b
s
en
ce
o
f
a
p
ar
ticu
lar
f
ea
tu
r
e
is
n
o
t
in
f
lu
e
n
ce
d
b
y
a
n
y
o
th
er
f
ea
tu
r
e.
E
v
en
wh
e
n
s
o
m
e
f
ea
t
u
r
es
m
ay
h
av
e
d
ep
en
d
en
cies,
t
h
e
m
o
d
el
tr
ea
ts
all
th
ese
ch
ar
a
cter
is
tics
as
if
t
h
ey
co
n
tr
ib
u
te
in
d
ep
e
n
d
en
tly
to
t
h
e
o
u
tc
o
m
e.
O
n
e
o
f
th
e
m
a
in
b
en
e
f
its
o
f
th
is
a
p
p
r
o
ac
h
is
its
ca
p
ac
ity
to
ef
f
icien
tly
h
an
d
le
v
er
y
lar
g
e
d
atasets
.
B
ay
es
’
th
eo
r
em
o
f
f
e
r
s
a
f
r
a
m
ewo
r
k
t
o
ca
lcu
late
th
e
p
o
s
ter
io
r
p
r
o
b
a
b
ilit
y
P
(
c
∣
x
)
u
s
in
g
th
e
p
r
io
r
p
r
o
b
a
b
ilit
ies
P
(
c
)
,
P
(
x
)
,
a
n
d
th
e
lik
elih
o
o
d
P
(
x
∣
c
)
,
as sh
o
wn
i
n
(
2
)
.
P
(
c
|
x
)
=
P
(
x
|
c
)
P
(
c
)
P
(
x
)
(
2
)
W
h
er
e:
−
P
(
c
∣
x
)
r
ep
r
esen
ts
th
e
p
o
s
ter
io
r
p
r
o
b
a
b
ilit
y
o
f
t
h
e
class
c
(
th
e
tar
g
et
v
ar
iab
le)
g
iv
en
th
e
p
r
e
d
icto
r
x
(
th
e
in
p
u
t f
ea
tu
r
es).
−
P
(
c
)
d
en
o
tes th
e
p
r
io
r
p
r
o
b
ab
il
ity
o
f
th
e
class
.
−
P
(
x
∣
c
)
is
th
e
lik
elih
o
o
d
,
o
r
t
h
e
p
r
o
b
a
b
ilit
y
o
f
th
e
p
r
ed
icto
r
g
i
v
en
th
at
th
e
class
is
k
n
o
wn
.
−
P
(
x
)
in
d
icate
s
th
e
p
r
io
r
p
r
o
b
a
b
ilit
y
o
f
th
e
p
r
ed
icto
r
.
Usi
n
g
(
2
)
an
d
co
n
s
id
er
in
g
th
e
in
d
ep
en
d
en
t v
ar
iab
les (
AP
an
d
E
T
A)
as o
u
tlin
ed
in
ea
r
lier
p
ar
ag
r
ap
h
s
,
alo
n
g
with
t
h
e
d
e
p
en
d
e
n
t
v
a
r
iab
le
o
r
class
,
wh
ich
in
t
h
is
co
n
tex
t
is
th
e
ch
a
n
n
el
’
s
s
tatu
s
(
e
ith
er
“
o
cc
u
p
ied
”
o
r
“
av
ailab
le
”
)
,
we
ca
n
d
er
iv
e
th
e
ex
p
r
ess
io
n
s
p
r
esen
ted
in
(
3
)
an
d
(
4
)
.
Poste
r
ior
(
oc
c
upie
d
)
=
P
(
o
ccu
p
i
ed
)
p
(
TED
|
oc
uppie
d
)
p
(
PD
|
oc
c
upie
d
)
ev
i
d
e
n
ce
(
3
)
Poste
r
ior
(
a
va
il
a
b
l
e
)
=
P
(
av
a
i
l
ab
l
e
)
p
(
TED
|
a
va
il
a
b
l
e
)
p
(
PD
|
a
va
il
a
b
l
e
)
ev
i
d
e
n
ce
(
4
)
W
h
er
e
“
ev
id
en
ce
”
wo
u
ld
b
e
g
iv
en
b
y
(
5
)
.
e
vide
n
c
e
=
P
(
oc
c
upie
d
)
p
(
TED│ocu
pp
ie
d
)
p
(
PD│
oc
c
upie
d
)
+
P
(
a
va
il
a
b
l
e
)
p
(
TED
|
a
va
il
a
b
l
e
)
p
(
PD
|
a
va
il
a
b
l
e
)
(
5
)
2
.
3
.
3
Si
m
ple a
dd
it
iv
e
weig
hting
T
h
e
alg
o
r
ith
m
c
r
ea
tes
a
d
ec
is
io
n
m
atr
ix
th
at
in
co
r
p
o
r
ates
m
u
ltip
le
attr
ib
u
tes
an
d
p
o
s
s
ib
le
alter
n
ativ
es.
Fo
r
ea
ch
i
n
ter
s
ec
tio
n
with
in
th
is
m
atr
ix
,
a
weig
h
t
is
allo
ca
ted
ac
co
r
d
in
g
to
th
e
d
esig
n
er
’
s
p
r
ed
ef
in
e
d
cr
iter
ia.
T
h
is
p
r
o
c
ess
o
f
ass
ig
n
in
g
weig
h
ts
en
ab
les
th
e
ca
lcu
latio
n
o
f
a
s
co
r
e
f
o
r
ea
ch
SO
u
n
d
er
ev
alu
atio
n
,
r
esu
ltin
g
in
a
p
r
io
r
itized
r
an
k
i
n
g
o
f
all
p
o
ten
tia
l
a
lter
n
ativ
es.
T
h
e
SO
th
at
ac
h
iev
es
th
e
h
i
g
h
est
s
co
r
e
in
t
h
is
r
an
k
i
n
g
is
s
elec
t
ed
as
th
e
o
p
tim
al
ch
o
ice.
T
h
e
m
ath
em
atica
l
r
e
p
r
esen
tatio
n
o
f
an
alter
n
ativ
e,
d
en
o
ted
as
A
i
,
is
p
r
esen
ted
in
(
6
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
9
,
No
.
1
,
Ju
ly
20
25
:
1
90
-
2
0
1
194
=
∑
=
1
,
∀
∈
1
,
.
.
.
,
(
6
)
Her
e,
r
i,
j
r
ep
r
esen
ts
an
elem
en
t
with
in
th
e
m
atr
ix
,
an
d
th
e
to
tal
o
f
all
as
s
ig
n
ed
weig
h
ts
eq
u
als
1
.
T
h
e
s
tep
s
in
v
o
lv
ed
in
d
e
v
elo
p
in
g
th
is
alg
o
r
ith
m
ar
e
as
f
o
ll
o
ws:
(
1
)
id
en
tify
th
e
o
b
ject
iv
es
an
d
p
o
ten
tial
alter
n
ativ
es;
(
2
)
p
er
f
o
r
m
a
n
ev
alu
atio
n
o
f
t
h
ese
alter
n
ativ
es;
(
3
)
ass
ig
n
w
eig
h
ts
to
ea
ch
c
o
m
b
in
atio
n
b
ased
o
n
th
eir
im
p
o
r
tan
ce
;
(
4
)
ca
lcu
la
te
th
e
ag
g
r
eg
ated
v
al
u
es
ac
co
r
d
in
g
to
t
h
e
estab
lis
h
ed
p
r
ef
er
en
ce
s
;
an
d
(
5
)
co
n
d
u
ct
a
s
en
s
itiv
ity
an
aly
s
is
to
ass
es
s
th
e
r
o
b
u
s
tn
ess
o
f
th
e
r
esu
lts
.
I
n
s
ev
er
al
s
tu
d
ies,
th
e
SAW
m
eth
o
d
h
as
b
ee
n
ap
p
lied
to
id
e
n
tify
t
h
e
o
p
tim
al
SO
with
in
a
GSM
f
r
eq
u
en
cy
b
an
d
,
to
ass
ess
th
e
n
u
m
b
er
o
f
h
an
d
o
f
f
s
ex
ec
u
ted
,
a
n
d
to
c
o
m
p
ar
e
th
e
p
er
f
o
r
m
an
ce
with
th
at
o
f
o
t
h
er
s
p
ec
tr
u
m
allo
ca
tio
n
al
g
o
r
ith
m
s
[
1
]
.
2
.
3
.
4
Dee
p lea
rning
A
c
o
m
p
r
e
h
e
n
s
i
v
e
d
e
s
c
r
i
p
t
i
o
n
o
f
t
h
e
DL
a
l
g
o
r
i
t
h
m
e
m
p
l
o
y
e
d
i
n
t
h
i
s
s
t
u
d
y
c
a
n
b
e
f
o
u
n
d
i
n
r
e
f
e
r
e
n
c
e
[
2
4
]
.
2
.
4
.
E
v
a
lua
t
i
o
n
T
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
s
elec
ted
h
an
d
o
f
f
(
HS)
m
o
d
els
was
e
v
alu
ated
u
s
in
g
f
o
u
r
s
p
ec
if
ic
m
etr
ics:
th
e
to
tal
n
u
m
b
er
o
f
ch
a
n
n
el
ch
an
g
es
(
AAH)
,
th
e
n
u
m
b
e
r
o
f
in
ter
f
er
in
g
ch
a
n
n
el
ch
a
n
g
es
(
A
AI
)
,
th
e
n
u
m
b
er
o
f
an
ticip
ated
ch
a
n
n
el
c
h
an
g
es
(
AAU)
,
an
d
t
h
e
n
u
m
b
er
o
f
p
e
r
f
ec
t
ch
an
n
el
ch
a
n
g
es
(
AAP)
.
T
h
ese
m
etr
ics
wer
e
ass
es
s
ed
u
n
d
er
two
tr
af
f
ic
lev
els
(
h
ig
h
(
HT
)
an
d
lo
w
(
L
T
)
)
as
well
a
s
f
o
r
two
ty
p
es
o
f
SU
b
eh
av
io
r
:
p
ass
iv
e
(
co
n
v
e
n
tio
n
al
m
o
d
e)
a
n
d
ac
tiv
e
(
r
ea
l m
o
d
e)
.
T
o
co
n
d
u
ct
a
co
m
p
r
eh
en
s
iv
e
m
u
lti
-
u
s
er
ev
alu
atio
n
,
th
e
s
elec
ted
SH
m
o
d
els
wer
e
a
p
p
lied
ac
r
o
s
s
f
o
u
r
d
if
f
er
en
t
s
ce
n
ar
io
s
:
(
1
)
c
o
n
v
e
n
tio
n
al
m
o
d
e
with
HT
,
(
2
)
r
ea
l
m
o
d
e
with
H
T
,
(
3
)
co
n
v
en
ti
o
n
al
m
o
d
e
with
lo
w
tr
af
f
ic
(
L
T
)
,
a
n
d
(
4
)
r
ea
l
m
o
d
e
with
lo
w
tr
af
f
ic
(
L
T
)
.
Fo
r
e
ac
h
s
ce
n
ar
io
,
th
e
p
e
r
f
o
r
m
an
c
e
o
f
th
e
SH
m
o
d
el
was
an
aly
ze
d
with
v
ar
y
in
g
n
u
m
b
er
s
o
f
s
im
u
ltan
eo
u
s
u
s
er
s
,
s
p
ec
if
ically
f
o
r
1
,
2
,
4
,
6
,
8
,
an
d
1
0
u
s
er
s
.
Giv
en
th
e
v
o
lu
m
e
o
f
d
ata,
co
m
p
lete
r
esu
lts
ar
e
s
u
m
m
ar
ized
in
tab
les
p
r
o
v
id
ed
in
th
e
r
esu
lts
s
ec
tio
n
,
w
h
ile
th
e
f
ig
u
r
es p
r
im
a
r
ily
illu
s
tr
ate
th
e
b
eh
av
io
r
f
o
r
th
e
ca
s
e
o
f
1
0
u
s
er
s
.
T
ab
le
1
o
u
tlin
es
th
e
ev
al
u
atio
n
m
etr
ics
u
s
ed
to
ass
ess
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
SH
m
o
d
els,
in
clu
d
in
g
AAH,
AAI
,
AAU,
an
d
AAP.
T
h
e
tab
le
d
etails th
e
ac
r
o
n
y
m
s
,
d
ef
in
itio
n
s
,
d
escr
ip
tio
n
s
,
an
d
ty
p
es o
f
ev
al
u
atio
n
m
etr
ics,
in
d
icatin
g
wh
eth
er
a
m
etr
ic
r
ep
r
esen
ts
a
b
e
n
ef
it
(
w
h
er
e
a
h
ig
h
er
v
alu
e
is
b
etter
)
o
r
a
co
s
t
(
wh
e
r
e
a
lo
wer
v
alu
e
is
p
r
ef
er
r
ed
)
.
T
h
e
ter
m
“
av
er
ag
e
”
in
th
e
co
n
tex
t
o
f
ev
alu
atio
n
m
etr
ics
r
ef
lect
s
th
at
th
ese
r
esu
lt
s
ar
e
b
ased
o
n
th
e
m
ea
n
v
alu
es
o
b
tain
ed
f
r
o
m
m
u
ltip
le
ex
p
er
im
en
ts
.
W
h
ile
th
e
AAH
m
etr
i
c
ap
p
lies
to
all
HS
m
o
d
els,
th
e
o
th
e
r
m
etr
ics ar
e
s
p
ec
if
ic
to
th
e
NB
p
r
ed
ictio
n
m
o
d
el.
T
ab
le
1
.
E
v
alu
ati
o
n
m
et
r
ics f
o
r
HS m
o
d
els
A
c
r
o
n
y
m
N
a
me
D
e
sc
r
i
p
t
i
o
n
E
v
a
l
u
a
t
i
o
n
me
t
r
i
c
t
y
p
e
AAH
C
u
m
u
l
a
t
i
v
e
a
v
e
r
a
g
e
h
a
n
d
o
f
f
n
u
m
b
e
r
T
h
i
s
i
s
t
h
e
t
o
t
a
l
n
u
m
b
e
r
o
f
h
a
n
d
o
f
f
s
p
e
r
f
o
r
m
e
d
d
u
r
i
n
g
t
h
e
9
mi
n
u
t
e
s
o
f
S
U
t
r
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3.
RE
SU
L
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Fig
u
r
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d
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e
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lts
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o
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ea
ch
o
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HS
m
o
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el
s
.
Fig
u
r
e
2
s
h
o
ws
d
ee
p
lear
n
i
n
g
with
1
0
SUs
in
HT
with
an
d
with
o
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t
ad
d
itio
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
2
(
a)
c
o
n
v
e
n
tio
n
al
m
o
d
e
in
HT
an
d
Fig
u
r
e
2
(
b
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r
ea
l
m
o
d
e
in
HT
.
Fig
u
r
e
3
s
h
o
ws
d
ee
p
lear
n
in
g
with
1
0
SUs
in
L
T
with
a
n
d
with
o
u
t
ad
d
itio
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
3
(
a)
c
o
n
v
e
n
tio
n
al
m
o
d
e
in
L
T
an
d
Fig
u
r
e
3
(
b
)
r
ea
l
m
o
d
e
in
L
T
.
Fig
u
r
e
4
s
h
o
ws
FF
AHP
with
1
0
SU
s
in
HT
with
an
d
with
o
u
t
ad
d
it
io
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
4
(
a
)
c
o
n
v
en
tio
n
al
m
o
d
e
in
HT
a
n
d
Fig
u
r
e
4
(
b
)
r
e
al
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
B
en
ch
ma
r
kin
g
s
p
ec
tr
a
l h
a
n
d
o
ff ra
te
p
erfo
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ma
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ce
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g
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itiv
e
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o
r
k
s
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C
esa
r
Hern
á
n
d
ez
)
195
m
o
d
e
in
HT
;
Fig
u
r
e
5
s
h
o
ws
FF
AH
P
with
1
0
SUs
in
L
T
with
an
d
with
o
u
t
ad
d
it
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n
al
r
an
d
o
m
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Fig
u
r
e
5
(
a)
c
o
n
v
e
n
tio
n
al
m
o
d
e
in
L
T
an
d
Fig
u
r
e
5
(
b
)
r
ea
l
m
o
d
e
in
L
T
.
Fig
u
r
e
6
s
h
o
ws
Naïv
e
B
ay
es
AAH
with
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0
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in
HT
with
an
d
with
o
u
t
ad
d
itio
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
6
(
a)
c
o
n
v
en
tio
n
a
l
m
o
d
e
in
HT
an
d
Fig
u
r
e
6
(
b
)
r
ea
l
m
o
d
e
in
HT
;
Fig
u
r
e
7
s
h
o
ws
Naïv
e
B
ay
es
AAH
wi
th
1
0
SUs
in
L
T
with
an
d
with
o
u
t
ad
d
itio
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
7
(
a)
c
o
n
v
en
tio
n
al
m
o
d
e
i
n
L
T
an
d
Fig
u
r
e
7
(
b
)
r
ea
l
m
o
d
e
in
L
T
;
Fig
u
r
e
8
s
h
o
ws
SAW
AAH
with
1
0
SUs
in
HT
with
a
n
d
with
o
u
t
a
d
d
itio
n
al
r
a
n
d
o
m
SUs
,
Fig
u
r
e
8
(
a)
c
o
n
v
en
tio
n
a
l
m
o
d
e
in
HT
an
d
Fig
u
r
e
8
(
b
)
r
ea
l
m
o
d
e
in
HT
;
Fig
u
r
e
9
s
h
o
ws
SA
W
AA
H
with
1
0
S
Us
in
L
T
with
an
d
with
o
u
t
ad
d
itio
n
al
r
an
d
o
m
SUs
,
Fig
u
r
e
9
(
a
)
c
o
n
v
en
tio
n
al
m
o
d
e
in
L
T
an
d
Fig
u
r
e
9
(
b
)
r
ea
l
m
o
d
e
i
n
L
T
.
E
ac
h
f
ig
u
r
e
s
h
o
ws
th
e
SH
m
o
d
el
s
’
r
esu
lts
d
u
r
in
g
a
9
-
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i
n
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te
tr
an
s
m
is
s
io
n
,
with
a
tr
ac
e
o
f
HT
an
d
L
T
i
n
co
n
v
en
tio
n
al
an
d
r
ea
l m
o
d
es o
n
a
GSM
n
etwo
r
k
.
(
a)
(
b
)
Fig
u
r
e
2
.
Dee
p
l
ea
r
n
in
g
with
1
0
SUs
in
HT
with
an
d
with
o
u
t
ad
d
itio
n
al
r
a
n
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
HT
a
n
d
(
b
)
r
ea
l m
o
d
e
in
HT
(
a)
(
b
)
Fig
u
r
e
3
.
Dee
p
l
ea
r
n
in
g
with
1
0
SUs
in
L
T
with
an
d
with
o
u
t
ad
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
L
T
a
n
d
(
b
)
r
ea
l m
o
d
e
in
L
T
(
a)
(
b
)
Fig
u
r
e
4
.
FF
AHP
with
1
0
SUs
in
HT
with
an
d
with
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
H
T
an
d
(
b
)
r
ea
l m
o
d
e
in
H
T
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
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9
,
No
.
1
,
Ju
ly
20
25
:
1
90
-
2
0
1
196
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a)
(
b
)
Fig
u
r
e
5
.
FF
AHP
with
1
0
SUs
in
L
T
with
an
d
with
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
L
T
a
n
d
(
b
)
r
ea
l m
o
d
e
in
L
T
(
a)
(
b
)
Fig
u
r
e
6
.
Naïv
e
B
ay
es
AAH
with
1
0
SUs
in
HT
with
an
d
w
ith
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
H
T
an
d
(
b
)
r
ea
l m
o
d
e
in
H
T
(
a)
(
b
)
Fig
u
r
e
7
.
Naïv
e
B
ay
es
AAH
with
1
0
SUs
in
L
T
with
an
d
with
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
L
T
a
n
d
(
b
)
r
ea
l m
o
d
e
in
L
T
(
a)
(
b
)
Fig
u
r
e
8
.
SAW
AAH
with
1
0
SUs
in
HT
with
an
d
with
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
H
T
an
d
(
b
)
r
ea
l m
o
d
e
in
H
T
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
B
en
ch
ma
r
kin
g
s
p
ec
tr
a
l h
a
n
d
o
ff ra
te
p
erfo
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ma
n
ce
in
co
g
n
itiv
e
w
ir
ele
s
s
n
etw
o
r
k
s
…
(
C
esa
r
Hern
á
n
d
ez
)
197
(
a)
(
b
)
Fig
u
r
e
9
.
SAW
AAH
with
1
0
SUs
in
L
T
with
an
d
with
o
u
t a
d
d
itio
n
al
r
an
d
o
m
SUs
(
a)
co
n
v
en
tio
n
al
m
o
d
e
i
n
L
T
a
n
d
(
b
)
r
ea
l m
o
d
e
in
L
T
3
.
1
.
M
ulti
-
us
er
benchm
a
rk
ing
T
ab
le
s
2
-
5
p
r
esen
t
th
e
co
m
p
a
r
ativ
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p
er
ce
n
tag
es
o
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th
e
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er
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o
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m
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h
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o
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ith
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f
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th
e
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i
r
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n
m
e
n
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al
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o
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e
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d
th
e
r
ea
l
m
o
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e
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o
r
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2
,
4
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6
,
8
,
an
d
1
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s
er
s
.
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h
e
ab
o
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e
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s
to
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aly
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o
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el
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s
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eh
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i
o
r
as
th
e
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u
m
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er
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ltan
eo
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ce
s
s
es
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th
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E
D
in
cr
ea
s
es.
T
ab
le
2
an
d
T
ab
le
3
p
r
esen
t th
e
m
u
lti
-
u
s
er
b
en
ch
m
ar
k
in
g
f
o
r
HT
a
n
d
L
T
in
co
n
v
e
n
tio
n
al
an
d
r
ea
l m
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d
e
s
.
T
ab
le
4
p
r
esen
ts
th
e
o
v
er
all
b
e
n
ch
m
a
r
k
in
g
b
y
tr
af
f
ic
ty
p
e
f
o
r
HT
a
n
d
L
T
in
co
n
v
en
tio
n
al
a
n
d
r
ea
l
m
o
d
es.
Fin
ally
,
T
ab
le
5
p
r
esen
ts
th
e
m
u
lt
i
-
u
s
er
b
e
n
ch
m
ar
k
in
g
f
o
r
t
h
e
p
r
e
d
ictio
n
m
et
r
ics f
o
r
NB
.
T
ab
le
2
.
Mu
lti
-
u
s
er
b
en
ch
m
ar
k
in
g
f
o
r
HT
M
u
l
t
i
-
u
s
e
r
f
e
a
t
u
r
e
s
D
e
e
p
l
e
a
r
n
i
n
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DIS
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I
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th
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m
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b
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C
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f
FF
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d
er
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th
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v
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n
tio
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d
r
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m
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co
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f
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v
a
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u
s
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ts
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s
p
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r
1
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2
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4
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6
,
8
,
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1
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u
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er
s
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e
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im
a
r
y
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ed
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m
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h
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o
f
f
(
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m
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r
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s
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ased
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ty
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m
u
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al)
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e
n
u
m
b
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o
f
u
s
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s
,
a
r
e
p
r
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ted
in
T
ab
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2
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h
e
f
in
d
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g
s
i
n
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icate
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h
at
as
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n
u
m
b
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f
s
im
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s
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es,
th
e
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m
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te
n
d
s
t
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d
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lin
e,
as th
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SOs
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o
m
e
m
o
r
e
lim
ited
an
d
ch
all
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g
in
g
t
o
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en
tify
.
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r
d
in
g
t
o
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e
s
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r
e
o
b
tain
ed
in
T
ab
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2
f
o
r
HT
,
in
co
n
v
en
tio
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al
m
o
d
e,
th
e
b
est
p
er
f
o
r
m
an
ce
is
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,
with
a
s
co
r
e
o
f
9
6
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2
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f
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d
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o
n
av
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ag
e;
th
e
av
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ag
e
d
if
f
er
en
ce
o
f
ea
ch
m
o
d
el
c
o
m
p
ar
e
d
to
NB
is
1
3
.
6
5
%.
Fo
r
th
e
r
ea
l
m
o
d
e,
Naiv
e
B
ay
as
co
n
tin
u
es
to
b
e
th
e
m
o
d
el
with
th
e
b
est
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er
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m
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,
h
o
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e
r
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th
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e
is
v
ar
iatio
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with
r
esp
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t
to
th
e
s
co
r
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o
f
th
e
o
th
er
tech
n
i
q
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es,
DL
d
r
o
p
s
i
n
p
o
s
itio
n
an
d
is
lo
ca
ted
in
th
e
f
o
u
r
th
s
co
r
e
,
FF
AHP
an
d
SAW
in
cr
ea
s
e
in
p
o
s
itio
n
m
ain
tai
n
in
g
th
e
o
r
d
e
r
o
f
th
e
class
if
icatio
n
; th
e
av
er
ag
e
d
if
f
er
en
ce
o
f
ea
ch
m
o
d
el
with
r
es
p
ec
t to
NB
is
1
7
.
4
8
%.
Acc
o
r
d
in
g
to
th
e
s
co
r
e
o
b
tain
ed
in
T
ab
le
3
f
o
r
L
T
,
in
c
o
n
v
en
tio
n
al
m
o
d
e,
th
e
b
est
p
er
f
o
r
m
an
ce
is
o
b
tain
ed
b
y
m
u
lti
-
cr
iter
ia
tech
n
iq
u
e
s
,
u
n
lik
e
HT
,
DL
,
an
d
th
e
NB
p
r
ed
ictiv
e
m
o
d
el
ar
e
n
o
t
lo
ca
ted
in
th
e
f
ir
s
t
p
lace
s
,
in
th
e
s
am
e
wa
y
.
R
e
g
ar
d
in
g
th
e
m
u
lti
-
cr
iter
ia
tec
h
n
iq
u
e,
SAW
o
b
tain
s
th
e
h
i
g
h
est
s
co
r
e,
wh
ile
FF
AHP
i
s
in
s
ec
o
n
d
p
o
s
itio
n
.
T
h
e
b
est
p
er
f
o
r
m
er
is
SAW
,
with
a
s
co
r
e
o
f
9
8
.
7
5
%
f
o
llo
wed
b
y
FF
AHP
with
7
6
.
5
7
%;
th
e
l
o
west
s
co
r
es
ar
e
f
o
r
NB
a
n
d
DL
b
elo
w
1
7
%;
th
e
d
if
f
e
r
en
ce
o
f
ea
ch
m
o
d
el
wit
h
r
esp
ec
t
to
SAW
is
b
elo
w
2
2
.
1
8
%
f
o
r
FF
AHP,
f
o
r
NB
7
5
.
4
6
%
,
an
d
f
o
r
DL
7
8
.
9
2
%.
Fo
r
th
e
r
ea
l
m
o
d
e
th
e
b
eh
a
v
io
r
is
p
r
o
p
o
r
tio
n
al,
th
e
b
est
p
er
f
o
r
m
an
ce
is
SAW
,
with
a
s
co
r
e
o
f
9
3
.
0
8
%
f
o
llo
wed
b
y
FF
AHP
with
6
9
.
0
2
%,
th
e
lo
west
s
co
r
es
ar
e
f
o
r
NB
an
d
DL
with
s
co
r
es
b
elo
w
2
0
%;
th
e
d
if
f
e
r
en
ce
o
f
ea
c
h
m
o
d
el
with
r
esp
ec
t
to
SAW
is
b
elo
w
2
0
%
f
o
r
m
u
lti
-
cr
iter
ia
tech
n
iq
u
es
an
d
7
5
.
4
6
%
an
d
7
8
.
9
2
%
f
o
r
p
r
ed
ictiv
e
m
o
d
el
an
d
DL
r
esp
ec
tiv
ely
.
T
ab
le
4
p
r
esen
ts
th
e
co
m
p
ar
at
iv
e
ev
alu
atio
n
ac
co
r
d
in
g
to
th
e
n
u
m
b
er
o
f
Han
d
o
f
f
s
f
o
r
HT
an
d
L
T
,
in
co
n
v
en
tio
n
al
an
d
r
ea
l
m
o
d
es.
Fo
r
HT
th
e
h
ig
h
est
s
co
r
e
is
NB
,
ad
d
itio
n
ally
,
th
is
p
r
ed
ictio
n
tech
n
iq
u
e
h
as
an
o
th
er
r
elev
an
t
ch
a
r
ac
ter
is
tic
co
m
p
ar
e
d
to
th
e
o
th
er
s
,
p
er
f
o
r
m
a
n
ce
in
cr
ea
s
es
f
o
r
a
r
ea
lis
tic
m
o
d
el,
as
ex
p
ec
ted
in
a
r
ea
lis
tic
s
ce
n
ar
i
o
,
with
u
s
er
s
en
ter
in
g
an
d
leav
in
g
in
r
an
d
o
m
tim
e,
th
e
p
r
o
f
it
m
etr
ics
s
h
o
u
ld
d
ec
r
ea
s
e,
h
o
wev
er
,
alth
o
u
g
h
th
er
e
is
an
in
cr
ea
s
e
in
p
er
f
o
r
m
an
ce
,
i
t
is
o
n
ly
0
.
9
5
%,
wh
ich
allo
ws
u
s
to
estab
lis
h
th
at
th
is
s
tr
ateg
y
is
n
o
t
af
f
ec
ted
b
y
th
e
in
co
r
p
o
r
atio
n
o
f
r
an
d
o
m
u
s
er
s
.
Fo
r
th
e
r
est
o
f
th
e
s
tr
ateg
ies,
th
e
v
ar
iatio
n
o
f
th
e
r
ea
lis
tic
s
ce
n
ar
io
with
r
esp
ec
t
to
th
e
co
n
v
en
tio
n
al
o
n
e
is
less
th
an
2
%
f
o
r
SAW
an
d
f
o
r
FF
AHP
i
t is 3
.
5
2
%
,
an
d
f
in
ally
,
th
e
g
r
ea
test
v
ar
iatio
n
is
DL
with
7
.
9
6
%.
I
n
L
T
th
e
b
est
s
co
r
es
ar
e
f
o
r
t
h
e
m
u
lti
-
cr
iter
ia
tech
n
iq
u
es
S
AW
an
d
FF
AHP
with
9
5
.
9
2
%
an
d
7
2
.
8
%
r
esp
ec
tiv
ely
,
DL
a
n
d
NB
o
b
t
ain
s
co
r
es
b
elo
w
2
0
%,
with
r
esp
ec
t
to
th
e
v
ar
iatio
n
s
o
f
th
e
r
ea
l
is
tic
s
ce
n
ar
io
v
er
s
u
s
th
e
co
n
v
e
n
tio
n
al
o
n
e,
th
e
g
r
ea
test
v
ar
iatio
n
is
p
r
ese
n
ted
in
th
e
m
u
lti
-
c
r
iter
ia
tech
n
iq
u
es,
7
.
5
5
%
f
o
r
FF
AHP
an
d
5
.
6
7
%
f
o
r
SAW
,
th
e
v
ar
iatio
n
s
o
f
DL
a
n
d
NB
a
r
e
b
elo
w
1
%,
alth
o
u
g
h
as
in
HT
,
NB
p
r
esen
ts
an
in
cr
ea
s
e
in
p
er
f
o
r
m
an
ce
.
B
ased
o
n
th
e
cu
m
u
lativ
e
c
o
s
t
m
etr
ic
an
aly
ze
d
ac
r
o
s
s
v
ar
io
u
s
d
ec
is
io
n
-
m
ak
i
n
g
m
o
d
els
d
u
r
in
g
th
e
n
in
e
-
m
in
u
te
tr
an
s
m
is
s
io
n
p
er
io
d
,
b
o
th
in
co
n
v
en
tio
n
al
a
n
d
r
ea
l
m
o
d
es,
th
er
e
is
a
n
o
t
ab
le
d
ec
lin
e
in
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
m
u
lti
-
cr
ite
r
ia
tech
n
iq
u
es
as
th
e
n
u
m
b
er
o
f
u
s
er
s
in
cr
ea
s
es.
T
h
e
s
ce
n
ar
io
with
a
s
in
g
le
SU
d
em
o
n
s
tr
ates
th
e
b
est
p
er
f
o
r
m
an
ce
,
with
th
e
f
ewe
s
t
ac
cu
m
u
lated
h
an
d
o
f
f
s
,
wh
ile
th
e
s
ce
n
ar
io
with
ten
SUs
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
B
en
ch
ma
r
kin
g
s
p
ec
tr
a
l h
a
n
d
o
ff ra
te
p
erfo
r
ma
n
ce
in
co
g
n
itiv
e
w
ir
ele
s
s
n
etw
o
r
k
s
…
(
C
esa
r
Hern
á
n
d
ez
)
199
s
h
o
ws
th
e
p
o
o
r
est
p
er
f
o
r
m
a
n
ce
,
with
th
e
h
ig
h
est
n
u
m
b
e
r
o
f
ac
c
u
m
u
lated
h
an
d
o
f
f
s
.
Fo
r
s
ce
n
ar
io
s
with
in
ter
m
e
d
iate
n
u
m
b
er
s
o
f
u
s
er
s
,
th
e
o
r
d
er
o
f
p
er
f
o
r
m
an
ce
f
lu
ctu
ates
d
u
r
in
g
th
e
f
ir
s
t
th
r
ee
m
in
u
tes;
h
o
wev
er
,
b
ey
o
n
d
th
is
p
o
in
t,
s
ce
n
ar
i
o
s
in
v
o
lv
in
g
2
to
5
SUs
ex
p
er
ien
ce
th
e
m
o
s
t
s
ig
n
if
ican
t
a
v
er
ag
e
in
cr
ea
s
e
i
n
h
an
d
o
f
f
s
.
Per
f
o
r
m
an
ce
in
r
ea
l
m
o
d
e
is
co
n
s
is
ten
tly
lo
wer
th
an
in
c
o
n
v
en
tio
n
al
m
o
d
e,
p
r
im
ar
ily
d
u
e
to
th
e
in
tr
o
d
u
ctio
n
o
f
r
an
d
o
m
u
s
er
s
,
wh
ich
d
im
in
is
h
es
th
e
n
u
m
b
er
o
f
av
ailab
le
SOs
,
m
ak
in
g
th
em
m
o
r
e
ch
allen
g
in
g
to
id
en
tify
.
I
t
is
clea
r
f
r
o
m
t
h
e
r
esu
lts
th
at
as
th
e
n
u
m
b
er
o
f
u
s
er
s
r
is
es,
th
e
ef
f
ec
tiv
en
ess
o
f
t
h
e
MCD
M
m
o
d
els
d
ec
r
ea
s
es,
u
n
d
er
s
co
r
in
g
th
e
lim
itatio
n
s
o
f
th
ese
tech
n
iq
u
es
in
en
v
ir
o
n
m
e
n
ts
with
h
ig
h
e
r
u
s
er
d
en
s
ities
.
5.
CO
NCLU
SI
O
N
W
ith
r
esp
ec
t
to
th
e
m
u
lti
-
u
s
er
en
v
ir
o
n
m
e
n
t,
it
was
ev
id
en
t
t
h
at
as
th
e
n
u
m
b
er
o
f
u
s
er
s
in
cr
ea
s
es,
th
e
p
er
f
o
r
m
an
ce
o
f
ea
ch
o
f
th
e
m
o
d
els
d
ec
r
ea
s
es.
NB
r
esp
o
n
d
s
v
er
y
well
to
m
u
lti
-
u
s
er
tr
a
f
f
ic,
DL
is
n
o
t
af
f
ec
ted
b
y
r
ea
lis
tic
s
ce
n
ar
io
s
an
d
th
e
m
u
lti
-
cr
iter
ia
FF
AHP
an
d
SA
W
tech
n
iq
u
es
p
er
f
o
r
m
well
f
o
r
s
ce
n
ar
io
s
with
lo
w
tr
af
f
ic.
I
t is also
in
ter
esti
n
g
to
n
o
te
h
o
w
at
HT
lev
els th
e
p
er
f
o
r
m
an
ce
o
f
th
e
e
v
alu
ated
s
tr
at
eg
ies is
r
ed
u
ce
d
b
y
ar
o
u
n
d
2
5
%
wh
en
i
n
co
r
p
o
r
ati
n
g
r
a
n
d
o
m
u
s
er
s
,
wh
ile
f
o
r
lo
w
tr
af
f
ic
p
e
r
f
o
r
m
an
ce
i
s
o
n
ly
af
f
ec
ted
b
y
ab
o
u
t
1
2
%
in
th
e
s
am
e
s
ce
n
ar
io
o
f
r
an
d
o
m
u
s
er
s
.
T
h
is
s
h
o
ws
th
e
im
p
o
r
tan
ce
o
f
ca
r
r
y
i
n
g
o
u
t
s
im
u
latio
n
s
in
en
v
ir
o
n
m
en
ts
clo
s
er
t
o
r
ea
lity
,
s
in
ce
th
e
r
esu
lts
ca
n
b
e
af
f
e
cted
b
y
s
ig
n
if
ican
t
m
ag
n
itu
d
e
s
.
No
w,
tak
in
g
in
t
o
ac
co
u
n
t
o
n
ly
th
e
n
u
m
b
e
r
o
f
s
im
u
ltan
eo
u
s
u
s
er
s
,
it
is
ev
id
en
t
th
at
in
ef
f
ec
t
th
e
g
r
e
ater
th
e
n
u
m
b
er
o
f
u
s
er
s
,
th
e
lo
wer
th
e
lev
el
o
f
p
er
f
o
r
m
an
c
e,
h
o
wev
e
r
,
th
e
r
ed
u
ctio
n
in
th
is
ca
s
e
is
b
etter
th
an
th
at
o
b
s
er
v
ed
in
th
e
ca
s
e
o
f
r
an
d
o
m
u
s
er
s
,
f
o
r
HT
it
is
o
n
ly
1
0
%
an
d
f
o
r
lo
w
tr
a
f
f
ic
th
er
e
is
n
o
e
v
id
en
ce
o
f
a
n
y
af
f
e
ctatio
n
.
I
n
g
en
er
al,
ea
ch
s
tr
ateg
y
p
er
f
o
r
m
s
s
atis
f
ac
to
r
ily
in
ce
r
tain
s
ce
n
ar
io
s
,
to
im
p
r
o
v
e
p
er
f
o
r
m
a
n
ce
in
m
u
lti
-
u
s
er
ac
ce
s
s
,
an
in
ter
esti
n
g
p
r
o
p
o
s
al
wo
u
ld
b
e
to
h
y
b
r
id
ize
th
e
im
p
lem
e
n
t
ed
s
tr
ateg
ies
o
r
d
e
v
elo
p
a
m
u
lti
-
mod
el
with
an
ad
ap
tiv
e
m
o
d
u
le
th
at
s
elec
ts
th
e
b
est
s
tr
ateg
y
b
ased
o
n
t
h
e
s
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