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li
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th
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I
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n
et
all
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e
ti
m
e
[
1
]
.
T
h
e
af
o
r
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en
tio
n
ed
w
ir
ele
s
s
tec
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n
o
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d
ev
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p
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[
2
]
.
T
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[
3
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.
T
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m
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cr
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[
1
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
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Fig
u
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N
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w
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k
s
E
n
v
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m
e
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t [
4
]
T
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etc.
[
5
-
6
]
.
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eter
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s
p
ap
er
aim
s
to
p
r
o
v
id
e
a
s
o
lu
tio
n
to
ch
o
o
s
e
th
e
b
est
s
u
i
tab
le
R
ad
io
A
cc
es
s
T
ec
h
n
o
lo
g
y
(
R
A
T
)
u
s
in
g
a
m
et
h
o
d
b
ased
o
n
Mu
lti
-
A
ttrib
u
te
Dec
is
io
n
Ma
k
in
g
(
MA
DM
)
.
M
A
DM
m
et
h
o
d
s
ar
e
co
m
m
o
n
l
y
ap
p
lied
to
s
o
lv
e
th
e
m
u
l
ti
-
cr
iter
ia
d
ec
is
io
n
p
r
o
b
lem
,
alo
n
g
w
it
h
th
e
n
et
w
o
r
k
s
elec
tio
n
p
r
o
b
lem
.
T
h
er
e
ar
e
s
o
m
e
p
o
p
u
lar
MA
DM
m
et
h
o
d
s
th
at
h
a
v
e
b
ee
n
f
o
u
n
d
in
t
h
e
liter
atu
r
e.
B
as
ed
o
n
o
u
r
f
i
n
d
in
g
s
in
liter
at
u
r
e
r
ev
ie
w
,
it
ca
n
b
e
s
aid
t
h
at
T
ec
h
n
iq
u
e
f
o
r
Or
d
er
P
r
ef
er
en
ce
b
y
Si
m
i
lar
it
y
to
I
d
ea
l
So
lu
tio
n
(
T
OP
SIS)
m
eth
o
d
i
s
r
elativ
el
y
b
etter
f
o
r
n
et
w
o
r
k
s
elec
tio
n
d
u
e
to
i
ts
h
i
g
h
s
en
s
iti
v
it
y
o
f
t
h
e
c
h
a
n
g
e
s
o
f
th
e
attr
ib
u
tes.
He
n
ce
,
T
OP
S
I
S
m
et
h
o
d
is
ap
p
lied
in
th
is
r
e
s
ea
r
ch
to
s
elec
t a
R
A
T
f
o
r
m
u
l
tip
le
cr
iter
ia.
T
h
e
r
est
o
f
th
e
p
ap
er
is
d
iv
id
ed
in
to
f
i
v
e
s
ec
tio
n
s
:
Sect
io
n
2
an
d
3
d
is
cu
s
s
Hete
r
o
g
e
n
eo
u
s
W
ir
eless
Net
w
o
r
k
s
a
n
d
Mu
lti
-
Attr
ib
u
t
e
Dec
i
s
io
n
Ma
k
i
n
g
(
M
A
D
M
)
m
e
th
o
d
s
r
esp
ec
ti
v
el
y
.
Sect
io
n
4
p
r
o
v
id
es
an
ex
p
lan
atio
n
ab
o
u
t
R
A
T
Select
io
n
Me
c
h
an
i
s
m
u
s
i
n
g
T
OP
SI
S
f
o
llo
w
ed
b
y
it
s
n
u
m
er
ical
an
al
y
s
i
s
i
n
Sect
io
n
5
.
Fin
all
y
,
Sectio
n
6
co
n
clu
d
es t
h
e
p
ap
er
.
2.
H
E
T
E
RO
G
E
N
E
O
US W
I
R
E
L
E
SS
NE
T
WO
RK
S
Hete
r
o
g
en
eo
u
s
W
ir
eless
Net
w
o
r
k
(
HW
N)
m
a
y
b
e
d
ef
i
n
e
d
as
th
e
co
m
b
in
atio
n
o
f
t
wo
o
r
m
o
r
e
w
ir
ele
s
s
r
eso
u
r
ce
s
s
u
ch
as
W
i
r
eless
Fid
elit
y
(
W
iFi
)
,
W
o
r
ld
I
n
ter
o
p
er
ab
ilit
y
f
o
r
Mic
r
o
w
av
e
A
cc
ess
(
W
iM
A
X)
an
d
Glo
b
al
S
y
s
te
m
f
o
r
Mo
b
ile
co
m
m
u
n
icatio
n
(
GSM)
i
n
a
ty
p
ica
l
ar
ea
.
A
t
y
p
ical
s
ce
n
ar
io
o
f
HW
N
h
as
b
ee
n
d
r
a
w
n
i
n
F
ig
u
r
e
1
f
o
r
b
etter
u
n
d
er
s
tan
d
i
n
g
.
Hete
r
o
g
en
eo
u
s
w
ir
ele
s
s
co
m
m
u
n
icatio
n
n
et
wo
r
k
s
ar
e
d
y
n
a
m
ic
i
n
ter
m
s
o
f
n
et
w
o
r
k
lo
ad
,
av
ai
l
a
b
ilit
y
,
e
n
er
g
y
co
n
s
er
v
a
tio
n
[
7
-
8
]
,
m
o
n
etar
y
co
s
t
an
d
n
et
w
o
r
k
co
v
er
ag
e
[
9
]
.
A
m
o
b
ile
d
ev
ice
en
ab
le
d
w
it
h
m
u
lt
ip
le
in
ter
f
ac
es
ca
n
h
a
v
e
ac
ce
s
s
to
an
y
s
u
ch
r
eso
u
r
ce
o
n
th
e
b
asis
o
f
it
s
ap
p
licatio
n
d
e
m
an
d
t
h
at
r
u
n
s
o
n
th
e
Mo
b
ile
No
d
e
(
MN
)
.
T
h
e
m
o
s
t
co
m
m
o
n
an
d
ac
ce
s
s
ib
le
w
ir
eles
s
tech
n
o
lo
g
y
co
m
p
r
is
e
s
o
f
t
h
e
ce
llu
lar
tec
h
n
o
lo
g
y
f
o
llo
w
ed
b
y
t
h
e
W
iFi
an
d
W
iM
AX
tec
h
n
o
lo
g
ies.
C
ell
u
lar
tech
n
o
lo
g
y
h
as
a
b
r
o
ad
co
v
er
ag
e
s
p
an
b
u
t
s
m
al
ler
b
an
d
w
id
th
,
W
iFi
h
as
le
s
s
er
co
v
er
a
g
e,
b
u
t
h
i
g
h
b
an
d
w
id
t
h
an
d
W
iMA
X
i
s
r
ec
o
g
n
is
ed
f
o
r
h
ig
h
b
an
d
w
id
t
h
as
w
ell
a
s
th
e
ar
ea
o
f
co
v
er
ag
e.
C
u
r
r
en
tl
y
,
v
ar
io
u
s
n
et
w
o
r
k
te
ch
n
o
lo
g
ies
li
k
e
W
iFi
o
r
I
E
E
E
8
0
2
.
1
1
a/b
/g
,
W
iMA
X
o
r
I
E
E
E
8
0
2
.
1
6
,
UM
T
S,
GP
R
S
ar
e
m
er
g
i
n
g
t
h
eir
in
f
r
as
tr
u
ct
u
r
es
w
i
th
t
h
e
co
r
e
n
et
w
o
r
k
s
o
f
I
P
v
6
o
r
I
Pv
4
.
All
t
h
e
ac
ce
s
s
tech
n
o
lo
g
ies i
n
v
o
lv
ed
w
it
h
H
W
N
p
o
s
s
ess
t
h
eir
i
n
d
iv
id
u
al
f
ea
tu
r
es s
u
c
h
as Qo
S
s
u
p
p
o
r
t,
o
p
er
atio
n
al
co
s
ts
an
d
co
v
er
a
g
e
[
1
0
]
.
T
h
e
m
o
b
ile
n
o
d
es
en
ab
led
w
it
h
m
u
ltip
le
i
n
te
r
f
ac
es
m
a
y
b
e
li
n
k
ed
to
a
p
r
o
p
er
in
ter
f
ac
e
o
n
t
h
e
b
asis
o
f
th
e
r
eq
u
ir
e
m
e
n
ts
o
f
t
h
e
ap
p
licatio
n
o
n
t
h
e
m
o
b
ile
n
o
d
e
an
d
n
et
w
o
r
k
s
tr
e
n
g
th
[
1
1
]
.
T
h
e
p
r
i
m
ar
y
g
o
al
o
f
t
h
e
HW
N
is
th
e
ca
p
ab
ilit
y
o
f
a
m
o
b
ile
n
o
d
e
to
r
etai
n
i
ts
p
r
ese
n
t
s
ess
io
n
a
n
d
c
h
o
o
s
e
th
e
m
o
s
t
s
u
i
tab
le
in
ter
f
ac
e
w
h
ile
i
t
i
s
co
m
m
u
n
i
ca
tin
g
.
E
v
er
y
tec
h
n
o
lo
g
y
h
as
its
p
ar
ticu
lar
s
et
o
f
p
o
licie
s
a
n
d
r
u
le
s
t
h
at
g
o
v
er
n
th
e
p
r
o
v
i
s
io
n
o
f
s
er
v
ices
a
n
d
r
eso
u
r
ce
s
to
its
u
s
er
s
.
T
h
u
s
,
a
s
ig
n
if
ican
t
is
s
u
e
i
n
HW
N
is
t
h
e
d
esig
n
o
f
a
R
ad
io
R
eso
u
r
ce
Ma
n
a
g
e
m
en
t
(
R
R
M
)
s
y
s
te
m
t
h
at
is
e
f
f
icien
t.
I
n
g
en
er
al,
th
e
R
R
M
f
r
a
m
e
w
o
r
k
m
a
y
b
e
ap
p
o
r
tio
n
ed
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
12
,
No
.
2
,
No
v
e
m
b
er
2
0
1
8
:
8
5
2
–
8
6
4
854
u
s
i
n
g
th
e
f
u
n
ctio
n
a
liti
es
v
iz.
Dec
is
io
n
E
n
f
o
r
ce
m
e
n
t,
Dec
is
io
n
Ma
k
in
g
an
d
R
e
s
o
u
r
ce
Mo
n
ito
r
in
g
.
T
h
ese
f
u
n
ctio
n
alitie
s
ar
e
i
n
ter
r
ela
ted
in
s
u
c
h
a
w
a
y
th
at
th
e
r
esu
lts
o
f
r
eso
u
r
ce
m
o
n
i
to
r
in
g
ar
e
e
m
p
lo
y
ed
i
n
d
ec
is
io
n
m
ak
in
g
af
ter
w
h
ic
h
d
ec
is
io
n
e
n
f
o
r
ce
m
en
t
ta
k
es
p
lace
.
Di
f
f
er
en
t
s
o
lu
tio
n
s
h
a
v
e
b
ee
n
ad
o
p
ted
to
tak
e
th
is
t
y
p
e
o
f
co
m
p
licated
d
ec
is
io
n
a
n
d
allo
ca
te
th
e
w
ir
eles
s
r
eso
u
r
ce
s
in
to
th
e
M
D
w
h
er
e
M
A
D
M
m
et
h
o
d
s
h
a
v
e
b
ee
n
g
iv
e
n
co
n
s
id
er
ab
le
atten
tio
n
i
n
r
ec
en
t
y
ea
r
s
p
ar
ticu
lar
l
y
,
T
OP
SIS
m
e
th
o
d
.
3.
M
UL
T
I
-
AT
T
RIB
U
T
E
D
E
C
I
SI
O
N
M
AK
I
NG
(
M
AD
M
)
M
E
T
H
O
DS
Ga
m
e
M
u
lti
-
A
ttrib
u
te
Dec
is
io
n
Ma
k
i
n
g
(
M
A
DM
)
ap
p
r
o
ac
h
es
h
a
v
e
b
ee
n
e
m
p
lo
y
ed
to
s
o
lv
e
m
u
lt
i
-
cr
iter
ia
d
ec
is
io
n
is
s
u
e
s
,
i
n
clu
d
in
g
in
t
h
e
f
ield
s
o
f
ec
o
n
o
m
ics,
p
o
liti
cs,
tr
a
n
s
p
o
r
tatio
n
an
d
h
eter
o
g
e
n
eo
u
s
w
ir
ele
s
s
n
et
w
o
r
k
s
.
So
m
e
m
et
h
o
d
s
co
m
m
o
n
l
y
u
s
ed
i
n
d
if
f
er
en
t
f
ield
s
i
n
cl
u
d
e
T
ec
h
n
iq
u
e
f
o
r
Or
d
er
P
r
ef
er
en
ce
b
y
Si
m
ilar
it
y
to
I
d
ea
l
So
l
u
tio
n
(
T
OP
SIS)
[
1
2
]
,
Sim
p
le
A
d
d
itiv
e
W
ei
g
h
tin
g
Me
t
h
o
d
(
S
A
W
)
[
1
2
]
,
Mu
ltip
licat
iv
e
E
x
p
o
n
e
n
tial
W
eig
h
ted
(
ME
W
)
[
1
3
]
,
E
lim
i
n
a
tio
n
a
n
d
C
h
o
ice
E
x
p
r
es
s
in
g
R
ea
lit
y
(
E
L
E
C
T
R
E
)
[
1
2
,
1
4
]
.
A
n
al
y
t
ic
Hier
ar
ch
y
P
r
o
ce
s
s
(
A
HP
)
an
d
Gr
e
y
R
ela
ti
o
n
al
A
n
al
y
s
is
(
GR
A
)
.
Si
m
p
le
A
d
d
itiv
e
W
eig
h
ti
n
g
(
S
A
W
)
is
o
n
e
o
f
t
h
e
p
o
p
u
lar
l
y
e
m
p
lo
y
ed
m
et
h
o
d
s
o
f
M
ADM
.
I
t
ca
n
o
b
tain
th
e
w
eig
h
ted
t
o
tal
o
f
th
e
n
o
r
m
alize
d
f
o
r
m
o
f
ev
er
y
p
ar
a
m
eter
o
n
ea
ch
ca
n
d
id
ate
n
et
w
o
r
k
.
A
cc
o
r
d
in
g
to
th
e
p
r
o
b
lem
d
ef
i
n
itio
n
,
t
h
e
n
et
w
o
r
k
w
it
h
th
e
h
ig
h
est/
lo
w
e
s
t
s
co
r
e
is
p
ick
ed
o
u
t
as
th
e
m
o
s
t
ex
ce
p
tio
n
al
n
et
w
o
r
k
in
th
e
HW
N.
T
h
e
s
co
r
es
m
a
y
b
e
ca
lcu
lated
b
ased
o
n
av
ailab
le
b
an
d
w
id
th
,
n
et
w
o
r
k
co
n
g
es
tio
n
a
n
d
d
ela
y
,
m
o
n
etar
y
co
s
ts
an
d
o
th
er
n
et
w
o
r
k
p
ar
a
m
e
ter
s
.
T
h
e
s
co
r
e
f
u
n
ct
io
n
is
o
b
tai
n
ed
b
y
ta
k
i
n
g
t
h
e
to
tal
o
f
th
e
w
ei
g
h
ted
,
n
o
r
m
a
lized
f
o
r
m
s
o
f
t
h
e
ab
o
v
e
p
a
r
am
eter
s
,
an
d
th
e
u
s
er
ca
n
m
o
d
if
y
t
h
e
w
ei
g
h
ts
b
y
ch
a
n
g
i
n
g
t
h
e
p
ar
a
m
eter
s
.
Fo
r
s
ca
lin
g
v
ar
io
u
s
f
ea
t
u
r
es
o
f
d
iv
er
s
e
u
n
it
s
in
to
an
alo
g
o
u
s
d
i
g
ital
r
ep
r
esen
tatio
n
s
,
d
is
t
in
ct
n
o
r
m
aliza
tio
n
f
u
n
ctio
n
s
ar
e
u
t
ilized
,
lik
e
lo
g
ar
it
h
m
ic,
lin
ea
r
p
iece
w
is
e
an
d
ex
p
o
n
en
t
ial
f
u
n
c
tio
n
s
[
1
5
]
.
T
h
is
is
a
s
i
m
p
le
m
et
h
o
d
an
d
p
r
im
ar
il
y
e
m
p
lo
y
ed
in
t
h
e
M
A
DM
f
ie
ld
.
Ho
w
e
v
er
,
o
n
e
o
f
t
h
e
s
i
g
n
i
f
ic
an
t
S
A
W
li
m
ita
tio
n
s
is
t
h
at
th
e
d
if
f
er
e
n
ce
b
et
w
ee
n
t
w
o
p
ar
am
eter
s
m
a
y
b
e
s
ev
er
el
y
ex
ce
ed
ed
b
y
co
n
s
id
e
r
ab
ly
g
o
o
d
v
alu
e.
Fo
r
in
s
ta
n
ce
,
if
th
e
n
et
w
o
r
k
h
as
a
lo
w
t
h
r
o
u
g
h
p
u
t,
b
u
t
th
e
p
r
ice
is
eq
u
all
y
r
ea
s
o
n
ab
le,
a
n
et
w
o
r
k
w
ith
b
etter
th
r
o
u
g
h
p
u
t
ca
n
b
e
s
elec
ted
th
r
o
u
g
h
a
s
li
g
h
tl
y
m
o
r
e
ex
p
en
s
iv
e
n
et
w
o
r
k
.
Su
p
p
o
s
e
w
e
tak
e
a
ca
n
d
id
ate
n
et
w
o
r
k
a
n
d
a
lis
t
o
f
ev
er
y
n
e
t
w
o
r
k
,
s
o
w
e
s
h
a
ll
h
a
v
e
a
n
n
p
ar
am
ete
r
lis
t,
an
d
f
o
r
ev
er
y
ca
n
d
id
ate
n
et
w
o
r
k
i,
a
s
co
r
e
ca
n
b
e
f
o
u
n
d
b
y
u
tili
z
in
g
t
h
e
E
q
u
atio
n
1
.
n
j
ij
j
i
r
w
S
A
W
1
(
1
)
W
h
er
e
ij
r
r
ep
r
esen
t
s
t
h
e
n
o
r
m
alize
d
p
er
f
o
r
m
an
ce
r
ati
n
g
o
f
p
ar
a
m
eter
j
o
n
n
et
w
o
r
k
i,
a
n
d
j
w
d
en
o
tes
w
eig
h
t o
f
p
ar
a
m
eter
j
.
Gen
er
all
y
,
h
i
g
h
er
t
h
e
s
co
r
e
v
a
lu
e,
th
e
m
o
r
e
d
esira
b
le
th
e
ca
n
d
id
ate
n
et
w
o
r
k
.
T
h
e
s
y
n
t
h
etic
s
h
o
r
tco
m
i
n
g
s
h
av
e
b
ee
n
a
n
al
y
ze
d
f
r
o
m
t
h
e
SA
W
m
et
h
o
d
,
s
o
a
m
et
h
o
d
o
f
u
s
in
g
Mu
ltip
licat
iv
e
E
x
p
o
n
e
n
tial
weig
h
tin
g
(
ME
W
)
o
r
W
eig
h
te
d
P
r
o
d
u
ct
(
W
P
)
in
th
e
d
ec
is
io
n
m
ec
h
a
n
is
m
is
p
r
o
p
o
s
ed
[
1
5
]
.
On
th
e
w
h
o
le
,
ME
W
is
an
MA
DM
m
et
h
o
d
w
h
ic
h
e
m
p
lo
y
s
m
u
ltip
licat
i
o
n
to
co
n
n
ec
t
th
e
n
et
w
o
r
k
p
ar
a
m
e
ter
lev
el
s
[
1
3
]
.
T
h
e
au
th
o
r
co
n
d
u
cted
a
n
e
m
p
ir
ical
test
an
d
f
o
u
n
d
th
a
t
th
e
r
esu
lt
s
o
f
t
h
e
S
A
W
m
et
h
o
d
w
er
e
in
co
r
r
ec
t,
b
u
t
th
e
r
esu
lts
u
s
i
n
g
th
e
ME
W
m
et
h
o
d
w
er
e
ac
cu
r
ate.
I
n
t
h
e
HW
N
s
ce
n
ar
io
,
th
e
ME
W
m
et
h
o
d
h
as
b
ee
n
u
tili
ze
d
in
th
e
f
ield
o
f
e
n
er
g
y
s
av
i
n
g
ac
ce
s
s
n
et
w
o
r
k
s
elec
ti
o
n
.
T
h
e
g
r
ea
ter
th
e
v
alu
e
o
f
a
ME
W
,
t
h
e
m
o
r
e
p
r
ef
er
r
ed
alter
n
ati
v
es
ar
e
c
h
o
s
en
f
o
r
b
est
r
esu
lts
.
ME
W
i
s
n
o
t
s
e
n
s
it
iv
e
to
th
e
p
ar
am
eter
s
ch
a
n
g
i
n
g
an
d
th
er
e
f
o
r
e,
th
e
ex
p
ec
ted
r
esu
lts
ar
e
n
o
t
ac
h
iev
ed
.
Fo
r
in
s
ta
n
ce
,
a
s
co
r
e
is
o
b
tain
ed
f
o
r
ev
er
y
ca
n
d
id
ate
n
et
w
o
r
k
i
b
y
m
a
k
i
n
g
u
s
e
o
f
E
q
u
atio
n
2
.
E
q
u
atio
n
2
b
elo
w
t
h
is
li
n
e
w
h
e
r
e
ij
r
d
en
o
tes
t
h
e
n
o
r
m
alize
d
p
er
f
o
r
m
an
ce
r
ati
n
g
o
f
p
ar
am
e
ter
j
o
n
n
et
w
o
r
k
i,
an
d
j
w
s
p
ec
if
ies
th
e
w
ei
g
h
t
o
f
p
ar
a
m
eter
j
.
T
h
e
h
ig
h
er
t
h
e
s
co
r
e
v
al
u
e,
th
e
m
o
r
e
d
esira
b
le
th
e
ca
n
d
id
ate
n
et
w
o
r
k
.
n
j
w
ij
i
j
r
M
E
W
1
(
2
)
T
ec
h
n
iq
u
e
f
o
r
Or
d
er
P
r
ef
er
en
ce
b
y
S
i
m
ilar
it
y
to
I
d
ea
l
So
l
u
tio
n
(
T
OP
SIS)
[
1
2
]
,
w
h
ic
h
is
s
i
m
ilar
to
th
e
id
ea
l
s
o
lu
tio
n
,
is
an
o
t
h
er
p
o
p
u
lar
m
et
h
o
d
th
at
w
o
r
k
s
o
n
t
h
e
p
r
in
cip
le
th
at
th
e
ca
n
d
id
ate
n
et
w
o
r
k
ch
o
s
e
n
i
s
n
ea
r
est
to
th
e
id
ea
l
s
o
l
u
tio
n
p
o
s
s
ib
l
e
an
d
f
u
r
t
h
es
t
f
r
o
m
t
h
e
w
o
r
s
t
s
o
l
u
tio
n
p
o
s
s
ib
le.
T
h
e
w
o
r
s
t
an
d
id
ea
l
s
o
lu
tio
n
s
ar
e
co
m
p
u
ted
b
y
e
m
p
lo
y
i
n
g
th
e
w
o
r
s
t
a
n
d
b
est
v
a
l
u
es
p
o
s
s
ib
le
f
o
r
ev
er
y
p
ar
a
m
e
ter
an
d
is
s
h
o
w
n
i
n
E
q
u
atio
n
3
.
T
h
e
T
OP
SIS
m
et
h
o
d
w
as
u
s
ed
[
1
6
-
1
7
]
f
o
r
r
a
n
k
in
g
t
h
e
ca
n
d
id
ate
n
et
w
o
r
k
s
a
s
p
er
th
eir
p
r
o
x
i
m
it
y
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-
4752
R
a
d
io
A
cc
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Tech
n
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lo
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(
R
A
T)
S
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tio
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Mech
a
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is
m
u
s
in
g
TOPS
I
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M
eth
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(
F
a
r
h
a
t A
n
w
a
r
)
855
to
th
e
b
est
s
o
lu
tio
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.
T
h
e
p
ar
am
eter
s
t
h
at
w
er
e
tak
e
n
in
to
c
o
n
s
id
er
atio
n
f
o
r
th
e
d
ec
is
io
n
m
atr
i
x
in
cl
u
d
e
Qo
S
lev
el,
a
v
ailab
le
b
an
d
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id
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s
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it
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to
tal
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d
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t
h
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co
s
t
p
er
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y
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u
tili
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io
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lo
s
s
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j
itter
an
d
d
ela
y
[
1
6
-
1
7
]
.
T
h
e
o
u
tco
m
e
r
ev
ea
l
s
th
at
T
OP
SIS
is
s
en
s
iti
v
e
to
p
ar
a
m
eter
v
al
u
es a
n
d
u
s
er
p
r
ef
er
en
ce
s
.
i
i
i
i
i
on
w
or
s
t
s
ol
ut
i
on
i
deal
s
ol
ut
i
on
w
or
s
t
s
ol
ut
T
O
P
SI
S
(
3
)
T
h
e
E
li
m
i
n
atio
n
an
d
C
h
o
ice
E
x
p
r
ess
io
n
R
ea
lit
y
(
E
L
E
C
T
R
E
)
[
1
2
,
1
4
]
is
y
et
a
n
o
th
er
MA
D
M
ap
p
r
o
ac
h
th
at
is
b
u
ilt
o
n
p
air
w
i
s
e
co
m
p
ar
is
o
n
b
et
w
ee
n
ca
n
d
id
ate
n
et
w
o
r
k
p
ar
a
m
eter
s
.
T
h
e
co
n
ce
p
ts
o
f
co
n
s
is
ten
c
y
a
n
d
in
co
n
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i
s
te
n
c
y
ar
e
e
m
p
lo
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ed
f
o
r
m
ea
s
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r
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n
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t
h
e
d
is
s
atis
f
a
ctio
n
a
n
d
s
ati
s
f
ac
tio
n
o
f
d
ec
i
s
io
n
m
ak
er
s
w
h
ile
e
v
al
u
ati
n
g
th
e
ca
n
d
id
ate
n
et
w
o
r
k
s
.
Ge
n
er
ate
t
w
o
t
y
p
es
o
f
li
s
ts
,
s
u
c
h
a
s
a
C
o
n
s
is
te
n
c
y
Set
(
C
Set)
,
th
at
co
m
p
r
is
e
s
o
f
a
s
er
ies
o
f
p
ar
a
m
eter
s
w
h
ic
h
in
d
ic
ate
th
e
s
u
p
er
io
r
it
y
o
f
th
e
c
u
r
r
en
t
n
et
w
o
r
k
o
v
er
all
o
th
er
ca
n
d
id
ate
n
et
w
o
r
k
s
,
a
n
d
th
at
a
s
e
t
o
f
i
n
co
n
s
is
te
n
cie
s
(
DSet)
is
d
ef
in
ed
,
t
h
at
o
f
f
er
s
a
p
ar
am
eter
li
s
t
f
o
r
th
e
p
r
ese
n
t
n
et
w
o
r
k
w
o
r
s
e
t
h
an
th
e
r
e
m
ai
n
i
n
g
ca
n
d
id
ate
n
et
w
o
r
k
s
.
Use
C
Set
a
n
d
DSet
to
b
u
i
ld
t
w
o
co
r
r
esp
o
n
d
in
g
m
a
tr
ices.
T
o
r
ep
r
esen
t
th
e
f
av
o
u
r
ed
n
et
w
o
r
k
,
ele
m
e
n
t
s
o
f
ev
er
y
m
atr
i
x
ar
e
eq
u
ated
to
tw
o
th
r
es
h
o
ld
s
:
C
t
h
r
esh
o
ld
a
n
d
Dth
r
es
h
o
ld
.
P
air
-
w
is
e
co
m
p
a
r
is
o
n
s
ar
e
u
s
ed
s
ep
ar
atel
y
b
et
w
ee
n
t
h
e
v
ar
io
u
s
o
p
tio
n
s
o
f
ea
ch
s
tan
d
ar
d
an
d
ca
n
b
e
co
m
p
lete
o
r
in
co
m
p
lete.
T
ab
le
1
.
Su
m
m
ar
y
o
f
M
ADM
Me
th
o
d
s
N
o
.
M
A
D
M
M
e
t
h
o
d
N
a
me
M
e
t
h
o
d
s
A
d
v
a
n
t
a
g
e
s
D
i
sad
v
a
n
t
a
g
e
s
1.
S
i
mp
l
e
A
d
d
i
t
i
v
e
W
e
i
g
h
t
i
n
g
M
e
t
h
o
d
(SAW)
A
w
e
i
g
h
t
e
d
s
u
m
h
a
s
b
e
e
n
u
se
d
t
o
n
o
r
mal
i
z
e
t
h
e
f
o
r
m o
f
e
a
c
h
p
a
r
a
me
t
e
r
o
n
a
l
l
c
a
n
d
i
d
a
t
e
n
e
t
w
o
r
k
s.
T
h
i
s
i
s
a
si
m
p
l
e
me
t
h
o
d
a
n
d
p
r
i
mar
i
l
y
e
mp
l
o
y
e
d
i
n
t
h
e
f
i
e
l
d
o
f
M
A
D
M
.
Tw
o
d
i
f
f
e
r
e
n
t
p
a
r
a
me
t
e
r
s
m
a
y
d
i
f
f
e
r
se
v
e
r
e
l
y
b
y
c
o
n
si
d
e
r
a
b
l
y
g
o
o
d
v
a
l
u
e
.
2.
M
u
l
t
i
p
l
i
c
a
t
i
v
e
Ex
p
o
n
e
n
t
i
a
l
W
e
i
g
h
t
e
d
(
M
EW
)
I
t
u
se
s
mu
l
t
i
p
l
i
c
a
t
i
o
n
t
o
c
o
n
n
e
c
t
n
e
t
w
o
r
k
p
a
r
a
me
t
e
r
l
e
v
e
l
s.
T
h
e
g
r
e
a
t
e
r
t
h
e
v
a
l
u
e
o
f
a
M
EW
,
t
h
e
mo
r
e
p
r
e
f
e
r
r
e
d
a
l
t
e
r
n
a
t
i
v
e
s
a
r
e
c
h
o
se
n
f
o
r
b
e
st
r
e
su
l
t
s.
N
o
t
se
n
si
t
i
v
e
t
o
t
h
e
p
a
r
a
me
t
e
r
s
c
h
a
n
g
i
n
g
.
3.
T
e
c
h
n
i
q
u
e
f
o
r
O
r
d
e
r
P
r
e
f
e
r
e
n
c
e
b
y
S
i
mi
l
a
r
i
t
y
t
o
I
d
e
a
l
S
o
l
u
t
i
o
n
(
T
O
P
S
I
S
)
T
h
e
s
e
l
e
c
t
e
d
c
a
n
d
i
d
a
t
e
n
e
t
w
o
r
k
i
s
n
e
a
r
e
st
t
o
t
h
e
i
d
e
a
l
so
l
u
t
i
o
n
p
o
ssi
b
l
e
a
n
d
f
a
r
f
r
o
m
t
h
e
w
o
r
st
so
l
u
t
i
o
n
p
o
ssi
b
l
e
.
T
h
e
w
o
r
st
a
n
d
i
d
e
a
l
so
l
u
t
i
o
n
s
a
r
e
c
o
mp
u
t
e
d
b
y
e
mp
l
o
y
i
n
g
t
h
e
w
o
r
st
a
n
d
b
e
st
p
o
ssi
b
l
e
v
a
l
u
e
s.
T
O
P
S
I
S
i
s
se
n
si
t
i
v
e
t
o
p
a
r
a
me
t
e
r
v
a
l
u
e
s
a
n
d
u
se
r
p
r
e
f
e
r
e
n
c
e
.
4.
T
h
e
El
i
mi
n
a
t
i
o
n
a
n
d
C
h
o
i
c
e
Ex
p
r
e
ssi
n
g
R
e
a
l
i
t
y
(
E
L
EC
T
R
E)
T
h
e
c
o
n
c
e
p
t
s
o
f
c
o
n
si
st
e
n
c
y
a
n
d
i
n
c
o
n
si
s
t
e
n
c
y
a
r
e
u
t
i
l
i
z
e
d
f
o
r
me
a
su
r
i
n
g
t
h
e
d
i
ss
a
t
i
sf
a
c
t
i
o
n
a
n
d
s
a
t
i
sf
a
c
t
i
o
n
o
f
d
e
c
i
si
o
n
mak
e
r
s.
I
t
u
se
s
a
l
t
e
r
n
a
t
i
v
e
me
t
h
o
d
s
f
o
r
p
a
i
r
w
i
se
c
o
mp
a
r
i
so
n
u
n
d
e
r
e
a
c
h
st
a
n
d
a
r
d
.
O
u
t
r
a
n
k
i
n
g
r
e
l
a
t
i
o
n
s
may
b
e
c
o
mp
l
e
t
e
o
r
i
n
c
o
mp
l
e
t
e
.
5.
A
n
a
l
y
t
i
c
H
i
e
r
a
r
c
h
y
P
r
o
c
e
ss (
A
H
P
)
T
h
e
A
H
P
m
e
t
h
o
d
c
a
l
c
u
l
a
t
e
s
t
h
e
r
e
l
a
t
i
v
e
w
e
i
g
h
t
s
o
f
d
i
f
f
e
r
e
n
t
p
a
r
a
me
t
e
r
s
e
mp
l
o
y
e
d
i
n
t
h
e
d
e
c
i
si
o
n
mo
d
e
l
.
I
t
c
o
mp
u
t
e
s
t
h
e
h
i
g
h
e
st
si
mi
l
a
r
i
t
y
t
o
t
h
e
b
e
st
so
l
u
t
i
o
n
a
n
d
w
a
s
c
h
o
se
n
a
s
t
h
e
t
a
r
g
e
t
n
e
t
w
o
r
k
.
I
n
c
o
n
si
st
e
n
t
r
e
su
l
t
s
c
a
n
o
c
c
u
r
w
h
e
n
t
h
e
A
H
P
i
s u
se
d
.
Th
e
o
th
er
t
w
o
co
m
m
o
n
l
y
u
s
ed
MA
DM
ap
p
r
o
ac
h
es
ar
e
Gr
e
y
R
e
latio
n
al
An
al
y
s
is
(
GR
A
)
an
d
An
al
y
tic
Hier
ar
ch
y
P
r
o
ce
s
s
(
A
HP
)
.
T
h
e
th
o
u
g
h
t
b
eh
i
n
d
th
e
an
al
y
tic
h
ier
ar
c
h
y
p
r
o
ce
s
s
is
to
d
ec
o
m
p
o
s
e
a
co
m
p
le
x
p
r
o
b
le
m
i
n
to
a
h
ier
ar
ch
ical
s
tr
u
ct
u
r
e
th
a
t
is
ea
s
y
a
n
d
s
i
m
p
le
to
s
o
l
v
e
a
s
u
b
-
p
r
o
b
lem
,
w
h
ile
t
h
e
G
R
A
m
et
h
o
d
s
o
r
ts
th
e
ca
n
d
id
ate
n
et
w
o
r
k
s
an
d
ch
o
o
s
es
t
h
e
o
n
e
w
it
h
th
e
h
ig
h
est
r
a
n
k
i
n
g
.
A
HP
is
u
s
ed
f
o
r
d
eter
m
in
i
n
g
t
h
e
w
eig
h
t
o
f
e
v
er
y
cr
iter
io
n
:
d
ela
y
,
b
an
d
w
i
d
th
,
j
itter
,
r
esp
o
n
s
e
ti
m
e,
co
s
t,
p
ac
k
et
lo
s
s
r
ate
,
b
it
er
r
o
r
r
ate
(
B
E
R
)
,
an
d
s
ec
u
r
it
y
.
Ho
w
e
v
er
,
it
h
as
b
ee
n
r
ep
o
r
ted
th
at
i
n
co
n
s
is
te
n
cie
s
m
a
y
o
cc
u
r
w
h
en
u
s
i
n
g
A
HP
[
1
8
]
.
T
h
e
A
HP
m
et
h
o
d
co
m
p
u
tes
t
h
e
r
elati
v
e
w
ei
g
h
ts
o
f
s
e
v
er
al
p
ar
a
m
eter
s
u
tili
ze
d
in
th
e
d
ec
is
io
n
m
o
d
el,
w
h
ile
G
R
A
g
i
v
es
p
r
io
r
it
y
to
t
h
e
n
et
w
o
r
k
.
T
h
e
n
e
t
wo
r
k
h
a
v
i
n
g
t
h
e
h
ig
h
es
t
v
alu
e
o
f
Gr
e
y
R
e
latio
n
al
C
o
ef
f
icie
n
t
w
as
b
eliev
ed
to
b
e
in
th
e
clo
s
es
t
p
r
o
x
i
m
it
y
to
th
e
id
ea
l
s
o
lu
tio
n
an
d
w
as
t
h
u
s
ch
o
s
en
a
s
th
e
tar
g
et
n
et
w
o
r
k
.
A
s
u
m
m
ar
y
o
f
t
h
e
M
A
DM
m
et
h
o
d
s
h
a
s
b
ee
n
lis
ted
in
T
ab
le
1
.
T
h
e
A
HP
m
et
h
o
d
is
u
til
ized
f
o
r
co
m
p
u
ti
n
g
th
e
w
ei
g
h
ts
f
o
r
v
ar
io
u
s
cr
iter
ia
li
k
e
d
ela
y
,
t
h
r
o
u
g
h
p
u
t,
p
ac
k
et
lo
s
s
,
j
itter
,
s
ec
u
r
it
y
,
co
s
t,
to
tal
b
an
d
w
id
t
h
,
co
s
t
p
er
b
y
te,
u
til
izatio
n
,
allo
w
ed
b
an
d
w
id
t
h
,
p
ac
k
et
lo
s
s
,
p
ac
k
et
j
itter
an
d
p
ac
k
et
d
elay
[
1
9
-
2
0
]
.
A
co
m
p
r
eh
e
n
s
i
v
e
r
ev
ie
w
h
as
b
ee
n
d
o
n
e
ab
o
u
t
t
h
e
s
en
s
iti
v
it
y
a
n
d
th
e
d
e
g
r
ee
o
f
i
n
f
l
u
en
ce
f
o
r
eig
h
t
cr
iter
ia
o
f
a
n
Au
s
tr
al
ian
u
n
i
v
er
s
it
y
s
t
u
d
en
t
s
'
s
c
h
o
lar
s
h
ip
d
e
cisi
o
n
m
a
k
i
n
g
u
s
i
n
g
th
e
a
f
o
r
em
en
tio
n
ed
M
ADM
m
et
h
o
d
s
s
h
o
w
n
i
n
F
i
g
u
r
e
2
[
2
0
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
12
,
No
.
2
,
No
v
e
m
b
er
2
0
1
8
:
8
5
2
–
8
6
4
856
Fig
u
r
e
2
.
A
C
o
m
p
r
eh
e
n
s
i
v
e
An
al
y
s
i
s
a
m
o
n
g
M
A
D
M
Me
th
o
d
s
[
2
0
]
Si
m
p
le
S
u
m
m
atio
n
(
SS
)
,
S
AW
,
W
eig
h
ted
P
r
o
d
u
ct
(
W
P)
o
r
ME
W
an
d
T
O
P
SIS
m
et
h
o
d
s
h
av
e
b
ee
n
u
s
ed
to
f
in
d
t
h
e
b
est
ca
n
d
id
ate
f
o
r
th
e
s
ch
o
lar
s
h
ip
.
I
t
ca
n
b
e
s
h
o
w
n
th
at
T
OP
SIS
m
et
h
o
d
h
as
th
e
r
elat
iv
e
in
f
lu
e
n
ce
d
eg
r
ee
o
f
i
n
d
i
v
id
u
al
attr
ib
u
tes
o
b
tain
ed
b
y
s
e
n
s
it
iv
i
t
y
a
n
al
y
s
i
s
co
m
p
ar
ed
to
o
th
er
m
et
h
o
d
s
.
Hen
ce
,
th
i
s
r
esear
ch
u
s
e
s
th
e
T
O
P
SIS
m
eth
o
d
f
o
r
its
e
v
al
u
a
tio
n
.
4.
RAT S
E
L
E
C
T
I
O
N
M
E
CH
ANIS
M
USI
NG
T
O
P
SI
S M
E
T
H
O
D
I
n
an
HW
N
en
v
ir
o
n
m
e
n
t,
a
m
u
lti
m
o
d
e
d
ev
ice
(
MD
)
u
s
er
ca
n
ac
ce
s
s
m
u
l
tip
le
s
er
v
ice
s
in
clu
d
i
n
g
v
o
ice,
v
id
eo
s
tr
ea
m
i
n
g
an
d
w
eb
s
es
s
io
n
s
i
m
u
lta
n
eo
u
s
l
y
th
r
o
u
g
h
av
a
ilab
le
R
A
T
s
in
th
at
p
ar
ticu
lar
ar
ea
.
Hen
ce
,
a
g
r
o
u
p
R
A
T
s
elec
t
io
n
p
r
o
b
le
m
is
f
o
llo
w
ed
w
h
e
n
an
i
n
d
iv
i
d
u
al
R
A
T
is
to
b
e
c
h
o
s
en
f
o
r
m
u
lt
ip
le
s
er
v
ices
o
f
class
e
s
f
r
o
m
s
ev
er
al
MD
s
.
I
t
is
k
n
o
w
n
t
h
at
th
e
c
ap
ab
ilit
ies
o
f
R
A
T
s
u
c
h
as
b
atter
y
,
d
ela
y
,
s
ec
u
r
it
y
lev
el
p
r
o
v
id
ed
,
b
atter
y
p
o
w
er
co
n
s
u
m
p
tio
n
,
av
ai
lab
le
b
an
d
w
id
t
h
,
etc.
v
ar
y
f
r
o
m
o
n
e
to
a
n
o
th
er
.
C
o
n
s
id
er
i
n
g
all
th
ese
i
s
s
u
es,
s
e
lecti
n
g
a
R
A
T
is
a
g
r
ea
t c
h
al
len
g
e
f
o
r
m
u
ltip
le
ca
lls
f
r
o
m
MD
s
i
n
an
H
W
N.
Mu
ltip
le
C
r
iter
ia
Desi
g
n
M
ak
in
g
(
M
C
DM
)
tech
n
iq
u
e
h
as
b
ee
n
ad
o
p
ted
f
r
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m
a
co
llectio
n
o
f
alter
n
ati
v
es,
all
o
f
w
h
ic
h
ar
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ev
alu
a
ted
in
co
n
tr
as
t
to
m
u
ltip
l
e
cr
iter
ia
f
o
r
a
s
in
g
le
ca
l
l
o
p
er
atio
n
f
r
o
m
M
Ds
i
n
HW
N
th
r
o
u
g
h
m
u
ltip
le
R
A
T
s
.
Fo
r
a
g
r
o
u
p
ca
ll
o
p
er
atio
n
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lti
C
r
iter
ia
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o
u
p
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is
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n
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k
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n
g
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C
GDM
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s
e
s
t
h
e
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r
ef
er
e
n
ce
i
n
f
o
r
m
ati
o
n
o
n
alter
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at
iv
e
s
s
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p
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lied
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y
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n
m
ak
er
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o
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ex
p
er
ts
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n
d
g
a
th
er
ed
to
estab
lis
h
a
co
llectiv
e
o
p
in
io
n
.
Ma
th
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m
atica
ll
y
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GDM
ca
n
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d
esig
n
ed
u
s
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n
g
a
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k
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m
w
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est,
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ased
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cr
iter
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h
o
n
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f
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s
e
i
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m
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ec
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p
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d
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r
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le
m
s
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T
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SIS
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ca
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cr
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m
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ap
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th
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ca
ll(s)
f
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n
d
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esia
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lec
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N:
2502
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4752
R
a
d
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cc
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lo
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iter
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t
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ig
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elati
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g
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o
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y
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f
o
r
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y
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te
g
o
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f
ca
ll
to
th
e
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t.
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eig
h
t
m
a
y
b
e
s
ca
led
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n
a
1
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p
o
in
t
s
ca
le
(
0
-
9
)
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it
h
0
r
ep
r
esen
tin
g
t
h
e
m
i
n
i
m
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m
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d
9
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ll.
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ll
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,
{
|
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t
S
t
i
t
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P
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d
en
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th
e
p
r
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ity
o
f
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ll
in
t
S
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h
e
v
alu
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o
f
ca
l
l
p
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ity
ar
e
lis
ted
i
n
T
ab
le
2
.
T
ab
le
2
.
C
all
P
r
io
r
ity
Sca
le
C
a
l
l
P
r
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r
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t
y
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a
l
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e
s
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w
1
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o
w
2
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e
d
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u
m
3
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i
g
h
4
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e
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y
h
i
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h
5
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h
e
co
m
p
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p
r
o
ce
s
s
is
clas
s
i
f
ied
in
to
s
o
m
e
p
h
ase
s
lis
ted
b
elo
w
.
P
h
ase
1
:
Sp
ec
if
y
t
h
e
ca
ll
s
et,
t
S
,
f
r
o
m
t
M
f
o
r
w
h
ich
a
R
A
T
is
t
o
b
e
ch
o
s
en
.
Fo
r
ex
a
m
p
le,
v
o
ice
ca
ll,
f
ile
d
o
w
n
lo
ad
in
g
a
n
d
v
id
eo
s
tr
ea
m
in
g
co
u
ld
b
e
t
y
p
es o
f
ca
ll.
T
h
en
,
s
p
ec
if
y
t
h
e
t
P
an
d
i
t
W
,
.
P
h
ase
2
: B
u
ild
t
h
e
d
ec
is
io
n
m
atr
ix
,
t
D
f
o
r
|
t
R
|
R
A
T
s
av
a
ilab
le
b
as
ed
o
n
|
C
|
R
A
T
cr
iter
ia.
A
g
e
n
e
r
al
d
ec
is
io
n
m
a
tr
ix
h
as b
ee
n
co
n
s
t
r
u
cted
in
th
e
E
q
u
atio
n
4
.
|
||
|
2
|
|
1
|
|
|
|
1
|
|
1
32
31
|
|
1
22
21
|
|
1
12
11
|
|
3
2
1
|
|
2
1
...
...
..
..
...
...
...
..
C
R
R
R
C
C
C
C
R
t
t
t
t
C
t
t
t
t
m
m
m
m
m
m
m
m
m
m
m
m
m
r
r
r
r
D
c
c
c
(
4
)
W
h
er
e
u
j
m
,
d
en
o
tes
t
h
e
p
er
f
o
r
m
a
n
ce
r
atin
g
o
f
R
A
T
,
|)
|
.....
3
,
2
,
1
(
t
t
j
R
j
r
o
n
d
if
f
er
en
t
cr
iter
ia
|)
|
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3
,
2
,
1
(
C
u
c
u
.
I
t
ca
n
b
e
n
o
ted
th
at
t
h
e
v
alu
es
o
f
d
ec
is
io
n
m
atr
ix
co
u
ld
b
e
b
o
th
li
n
g
u
i
s
tic
an
d
n
u
m
er
ical
v
a
lu
e
s
w
h
er
e
th
e
li
n
g
u
i
s
tic
ter
m
s
w
ill
b
e
co
n
v
er
ted
in
to
cr
is
p
v
alu
es
u
s
i
n
g
s
t
an
d
ar
d
f
u
zz
y
lo
g
ic
f
o
r
m
u
las t
h
at
h
as b
ee
n
li
s
ted
i
n
T
ab
le
3
.
T
ab
le
3
.
Fu
zz
y
Valu
e
s
C
o
n
v
er
ted
I
n
to
C
r
is
p
Nu
m
b
er
s
F
u
z
z
y
N
a
me
F
u
z
z
y
V
a
l
u
e
s
V
e
r
y
H
i
g
h
0
.
9
0
9
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i
g
h
0
.
7
1
7
M
e
d
i
u
m
0
.
5
0
L
o
w
0
.
2
8
3
V
e
r
y
L
o
w
0
.
0
9
1
P
h
ase
3
:
T
h
e
d
e
cisi
o
n
m
at
r
ix
n
ee
d
s
to
b
e
n
o
r
m
alize
d
d
u
e
to
m
ea
s
u
r
e
ev
er
y
cr
iter
io
n
in
d
i
m
en
s
io
n
le
s
s
ap
p
r
o
ac
h
.
E
ac
h
o
f
t
h
e
n
o
r
m
al
ized
v
ec
to
r
s
ca
n
b
e
d
ef
in
ed
a
s
u
j
t
m
,
o
f
t
h
e
d
ec
is
io
n
m
atr
i
x
t
D
th
at
ca
n
b
e
co
m
p
u
ted
in
t
h
e
f
o
llo
w
i
n
g
E
q
u
atio
n
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
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J
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C
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2
,
No
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m
b
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2
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1
8
:
8
5
2
–
8
6
4
858
|
|
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3
,
2
,
1
|,
|
,...
3
,
2
,
1
,
|
|
1
2
,
,
,
C
u
R
j
m
m
m
t
R
x
u
j
u
j
u
j
t
(
5
)
W
h
er
e
u
j
t
m
,
s
p
ec
if
ies t
h
e
n
o
r
m
alize
d
p
er
f
o
r
m
a
n
ce
v
al
u
ed
o
f
R
A
T
t
j
r
o
n
cr
iter
io
n
.
P
h
ase
4
:
T
h
e
w
eig
h
i
n
g
v
ec
to
r
,
i
t
W
,
ca
n
b
e
d
ef
in
ed
as
f
o
llo
w
s
:
}
,
,
.
.
.
.
.
.
.
.
.
,
{
|
|
,
,
1
,
,
C
i
t
u
i
t
i
t
i
t
w
w
w
W
(
6
)
T
h
e
u
s
er
s
p
ec
if
ied
w
ei
g
h
t c
r
iter
ia
n
ee
d
to
b
e
n
o
r
m
alize
d
an
d
ca
n
b
e
d
ef
in
ed
as.
i
t
C
i
t
u
i
t
i
t
w
w
w
w
,
|
|
,
,
1
,
..
..
.
,.
..
..
..
..
,.
..
..
..
.,
(
7
)
|
|
,.......
3
,
2
,
1
,
|
|
1
,
,
,
C
u
w
w
W
C
x
i
t
x
u
i
t
u
i
t
(
8
)
P
h
ase
5
:
No
w
,
w
e
n
ee
d
to
n
o
r
m
alize
t
h
e
p
r
io
r
it
y
v
ec
to
r
:
}
,
,
.
.
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.
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.
.
.
,
{
|
|
1
t
S
t
i
t
t
t
p
p
p
P
(
9
)
T
h
e
ca
ll p
r
io
r
ity
v
ec
to
r
s
ar
e
n
o
r
m
al
ized
as f
o
llo
w
s
:
|
|
1
,
..
..
.
,.
..
..
..
..
,.
..
..
..
.,
t
S
t
t
i
t
i
t
p
p
p
P
(
1
0
)
|
|
,.......
3
,
2
,
1
,
|
|
1
t
S
x
t
x
i
t
i
t
S
i
w
p
P
t
(
1
1
)
P
h
ase
6
:
Ag
g
r
e
g
ate
t
h
e
n
o
r
m
a
lized
w
ei
g
h
t a
n
d
n
o
r
m
alize
d
p
r
io
r
ity
.
|
|
,.......
3
,
2
,
1
|
|
1
,
,
C
u
p
w
S
x
i
t
i
t
u
t
u
t
(
1
2
)
T
h
e
g
r
o
u
p
w
ei
g
h
t
in
g
v
ec
to
r
,
ca
n
b
e
co
m
p
u
ted
as f
o
llo
w
s
.
(
1
3
)
P
h
ase
7
:
C
o
m
b
in
e
t
h
e
n
o
r
m
alize
d
d
ec
is
io
n
m
atr
i
x
,
an
d
g
r
o
u
p
w
ei
g
h
ti
n
g
v
ec
to
r
,
to
g
et
w
ei
g
h
ted
n
o
r
m
al
ized
d
ec
is
io
n
m
atr
i
x
,
as s
h
o
w
n
i
n
E
q
u
atio
n
i
n
1
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
R
a
d
io
A
cc
ess
Tech
n
o
lo
g
y
(
R
A
T)
S
elec
tio
n
Mech
a
n
is
m
u
s
in
g
TOPS
I
S
M
eth
o
d
i
n
…
(
F
a
r
h
a
t A
n
w
a
r
)
859
|
||
|
2
|
|
1
|
|
|
|
1
|
|
1
32
31
|
|
1
22
21
|
|
1
12
11
|
|
3
2
1
|
|
2
1
...
...
..
..
...
...
...
..
C
R
R
R
C
C
C
C
R
t
t
t
t
t
C
t
t
t
t
h
h
h
h
h
h
h
h
h
h
h
h
h
r
r
r
r
H
c
c
c
(
1
4
)
W
h
er
e,
|
|
,.......
1
,
|
|
,.......
1
.
,
C
u
R
j
m
h
t
u
j
u
t
P
h
ase
8
:
Ob
tain
th
e
id
ea
l so
l
u
t
io
n
,
A*
a
n
d
th
e
n
e
g
ati
v
e
id
ea
l
s
o
lu
tio
n
A
-
o
f
Ht.
*
|
|
*
2
*
1
*
.,
,.........
,
C
h
h
h
A
(
1
5
)
)}
|
m
i
n
(
),
|
m
a
x
{(
'
'
'
*
C
u
h
C
u
h
A
u
j
R
j
u
j
R
j
t
t
(
1
6
)
|
|
2
1
.,
,.
...
..
...
,
C
h
h
h
A
(
1
7
)
)}
|
m
a
x
(
),
|
m
i
n
{(
'
'
'
*
C
u
h
C
u
h
A
u
j
R
j
u
j
R
j
t
t
(
1
8
)
P
h
ase
9
:
|
|
,.
.
..
..
..
1
|,
|
,.
.
..
..
,
1
,
)
(
|
|
1
2
*
,
*
,
C
u
R
j
h
h
d
t
C
j
u
u
j
j
t
(
1
9
)
|
|
,.
..
..
.
..
1
|,
|
,.
..
..
.
,
1
,
)
(
|
|
1
2
,
,
C
u
R
j
h
h
d
t
C
j
u
u
j
j
t
(
2
0
)
|
|
....
3
,
2
,
1
,
,
*
,
,
t
j
t
j
t
j
t
j
t
R
j
d
d
d
f
(
2
1
)
P
h
ase
1
0
:
T
h
e
h
ig
h
es
t
clo
s
e
n
es
s
co
ef
f
ici
en
t
R
A
T
s
h
all
b
e
ch
o
s
e
n
f
o
r
t
h
e
i
n
d
iv
id
u
al
o
r
g
r
o
u
p
o
f
ca
ll
s
i
n
HW
N
en
v
ir
o
n
m
e
n
t.
5.
NUM
E
RICAL
AN
AL
Y
SI
S
USI
N
G
T
O
P
S
I
S M
E
T
H
O
D
Fo
r
n
u
m
er
ical
a
n
al
y
s
i
s
,
th
e
f
o
llo
w
i
n
g
s
ce
n
ar
io
s
h
a
v
e
b
ee
n
co
n
s
id
er
ed
to
s
elec
t
a
s
u
itab
le
R
A
T
in
HW
N.
P
h
ase
1
:
T
h
r
ee
t
y
p
es
o
f
s
er
v
i
ce
s
ar
e
co
n
s
id
er
ed
,
v
iz
v
id
eo
s
tr
ea
m
i
n
g
(
vi
s
)
,
f
ile
d
o
w
n
lo
ad
in
g
(
dl
s
)
an
d
v
o
ice
ca
ll
(
vo
s
)
.
Fiv
e
cr
iter
ia
h
av
e
b
ee
n
r
ec
o
g
n
ized
f
o
r
th
e
b
est
s
u
itab
le
R
A
T
s
ele
ctio
n
f
o
r
ev
er
y
ca
teg
o
r
y
o
f
ca
l
ls
i
n
HW
N.
T
h
e
r
eq
u
ir
em
e
n
t
s
ar
e
class
if
i
ed
as
s
er
v
ice
p
r
ice
(
C
s
p
)
,
n
e
t
w
o
r
k
d
ela
y
(
C
n
d
)
,
p
o
w
er
c
o
n
s
u
m
p
tio
n
(
C
p
c)
,
s
ec
u
r
it
y
(
C
s
e)
an
d
d
ata
r
ate
(
C
d
r
)
.
P
h
ase
2
:
T
h
e
R
A
T
s
elec
tio
n
cr
iter
ia
u
tili
ze
d
in
th
i
s
n
u
m
er
ical
an
al
y
s
is
ar
e
g
i
v
en
i
n
E
q
u
atio
n
2
2
in
th
e
f
o
r
m
o
f
th
e
d
ec
is
io
n
m
atr
i
x
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
12
,
No
.
2
,
No
v
e
m
b
er
2
0
1
8
:
8
5
2
–
8
6
4
860
l
o
w
h
i
g
h
h
i
g
h
70
m
e
d
i
u
m
h
i
g
h
m
e
d
i
u
m
l
o
w
54
l
o
w
6
.
9
c
c
c
m
a
x
se
dr
sp
l
o
w
v
er
y
h
i
g
h
h
i
g
h
v
er
y
h
i
g
h
R
R
R
D
c
c
t
wi
t
w
i
f
i
t
g
s
m
t
nd
pc
(
2
2
)
T
h
e
lin
g
u
is
t
ic
ter
m
s
ca
n
b
e
co
n
v
er
ted
i
n
to
cr
is
p
v
al
u
es
b
y
m
ak
in
g
u
s
e
o
f
t
h
e
f
u
zz
y
co
n
v
er
s
io
n
s
ca
l
e
d
escr
ib
ed
in
T
a
b
le
3
,
an
d
th
e
n
u
m
er
ical
v
al
u
es h
a
v
e
b
ee
n
li
s
ted
in
E
q
u
atio
n
2
3
.
0
.2
8
3
0
.7
1
7
0
.7
1
7
70
0
.5
0
0
.7
1
7
0
.5
0
0
.2
8
3
54
0
.2
8
3
0
9
1
.
0
7
1
7
.
0
9
0
9
.
0
6
.
9
7
1
7
.
0
c
c
c
m
ax
se
dr
sp
t
wi
t
w
i
f
i
t
g
s
m
t
nd
pc
R
R
R
D
c
c
(
2
3
)
P
h
ase
3
:
T
h
e
d
ec
is
io
n
m
atr
i
x
h
as
b
ee
n
n
o
r
m
alize
d
ac
co
r
d
in
g
to
th
e
f
o
r
m
u
la
3
.
9
.
Af
ter
ap
p
ly
in
g
t
h
e
n
o
r
m
alize
d
d
ec
is
io
n
m
atr
i
x
,
th
e
n
e
w
m
atr
i
x
is
f
o
r
m
ed
an
d
m
en
tio
n
ed
i
n
E
q
u
atio
n
2
4
.
0
.3
6
4
6
0
.6
3
4
2
0
.6
0
1
6
0
.7
8
7
2
0
.5
4
4
2
0
.9
2
3
8
0
.4
4
2
3
0
.2
3
7
4
0
.6
0
7
2
0
.3
0
8
0
0
.1
1
7
2
0
.6
3
4
2
0
.7
6
2
7
0
.1
0
8
0
0
.7
8
0
4
R
R
R
D
c
c
c
c
c
t
w
i
m
a
x
t
w
i
f
i
t
g
s
m
t
nd
pc
se
dr
sp
(
2
4
)
P
h
ase
4
:
T
h
e
u
s
er
s
p
ec
if
ied
w
eig
h
t
h
a
s
b
ee
n
li
s
ted
in
T
ab
le
4
f
o
r
th
r
ee
t
y
p
es
o
f
s
er
v
ice
s
,
v
o
ice
ca
ll
s
er
v
ice
(
vo
s
)
,
f
ile
d
o
w
n
lo
ad
in
g
s
e
r
v
ice
(
dl
s
)
,
an
d
v
id
eo
s
tr
ea
m
i
n
g
s
er
v
ice
(
vi
s
)
.
T
ab
le
4
.
C
r
iter
ia
W
eig
h
t Sca
le
P
r
e
f
e
r
e
n
c
e
f
o
r
v
o
i
c
e
c
a
l
l
se
r
v
i
c
e
(
vo
s
),
C
r
i
t
e
r
i
a
W
e
i
g
h
t
S
e
r
v
i
c
e
P
r
i
c
e
(
C
sp
)
5
D
a
t
a
R
a
t
e
(
C
dr
)
4
S
e
c
u
r
i
t
y
(
C
se
)
8
P
o
w
e
r
C
o
n
su
mp
t
i
o
n
(
C
pc
)
4
N
e
t
w
o
r
k
D
e
l
a
y
(
C
nd
)
9
P
r
e
f
e
r
e
n
c
e
f
o
r
f
i
l
e
d
o
w
n
l
o
a
d
i
n
g
se
r
v
i
c
e
(
dl
s
)
S
e
r
v
i
c
e
P
r
i
c
e
(
C
sp
)
4
D
a
t
a
R
a
t
e
(
C
dr
)
5
S
e
c
u
r
i
t
y
(
C
se
)
9
P
o
w
e
r
C
o
n
su
mp
t
i
o
n
(
C
pc
)
7
N
e
t
w
o
r
k
D
e
l
a
y
(
C
nd
)
6
P
r
e
f
e
r
e
n
c
e
f
o
r
v
i
d
e
o
st
r
e
a
mi
n
g
se
r
v
i
c
e
(
vi
s
)
S
e
r
v
i
c
e
P
r
i
c
e
(
C
sp
)
5
D
a
t
a
R
a
t
e
(
C
dr
)
7
S
e
c
u
r
i
t
y
(
C
se
)
8
P
o
w
e
r
C
o
n
su
mp
t
i
o
n
(
C
pc
)
7
N
e
t
w
o
r
k
D
e
l
a
y
(
C
nd
)
6
T
h
e
w
ei
g
h
t
h
a
s
b
ee
n
n
o
r
m
ali
ze
d
ac
co
r
d
in
g
to
th
e
f
o
r
m
u
la
3
.
1
2
an
d
f
o
r
m
ed
a
n
e
w
d
ata
lis
ted
in
eq
u
atio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
R
a
d
io
A
cc
ess
Tech
n
o
lo
g
y
(
R
A
T)
S
elec
tio
n
Mech
a
n
is
m
u
s
in
g
TOPS
I
S
M
eth
o
d
i
n
…
(
F
a
r
h
a
t A
n
w
a
r
)
861
0
.1
8
1
8
0
.2
1
2
1
0
.2
4
2
4
0
.2
1
2
1
0
.1
5
1
5
0
.1
9
3
5
0
.2
2
5
8
0
.2
9
0
3
0
.1
6
1
3
0
.1
2
9
0
0
.3
0
0
0
0
.1
3
3
3
0
.2
6
6
7
0
.1
3
3
3
0
.1
6
6
7
c
c
c
se
dr
sp
vi
dl
vo
t
nd
pc
s
s
s
w
c
c
(
2
5
)
P
h
ase
5
:
A
cc
o
r
d
in
g
to
T
ab
l
e
5
,
th
e
ca
ll
p
r
io
r
ity
v
ec
to
r
f
o
r
th
r
ee
ty
p
es
o
f
s
er
v
ices
h
av
e
b
ee
n
n
o
r
m
alize
d
.
Fi
v
e
t
y
p
es
o
f
s
ce
n
ar
io
s
h
av
e
b
ee
n
co
n
s
id
er
e
d
,
an
d
o
n
ly
f
ir
s
t
ca
ll
p
r
io
r
ity
v
al
u
es
h
av
e
b
ee
n
n
o
r
m
alize
d
ac
co
r
d
in
g
to
th
e
E
q
u
atio
n
3
.
1
5
.
T
ab
le
5
.
C
al
l P
r
io
r
ity
Sca
le
C
a
l
l
P
r
i
o
r
i
t
y
V
a
l
u
e
s
V
e
r
y
h
i
g
h
5
H
i
g
h
4
M
e
d
i
u
m
3
L
o
w
2
V
e
r
y
l
o
w
1
Fiv
e
s
a
m
p
le
s
ce
n
ar
io
s
h
av
e
b
ee
n
co
n
s
id
er
ed
in
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le
6
f
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r
ity
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ty
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;
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f
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d
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h
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as
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in
A
p
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en
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x
I
.
T
ab
le
6
.
A
Sa
m
p
le
Sce
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f
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all
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1
5
1
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1
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5
Fo
r
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io
1
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a
s
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n
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0
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2
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4
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p
(
2
6
)
P
h
ase
6
:
T
h
e
v
alu
es
o
f
n
o
r
m
a
lized
w
eig
h
t
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r
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th
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E
q
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atio
n
4
.
4
an
d
n
o
r
m
alize
d
ca
ll
p
r
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ity
f
r
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th
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E
q
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atio
n
2
6
(
f
o
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th
e
1
st
s
c
en
ar
io
)
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a
v
e
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ee
n
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r
eg
ated
ac
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r
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g
to
th
e
E
q
u
atio
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.
1
6
,
an
d
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to
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h
as b
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ed
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3
4
6
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c
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c
se
dr
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vi
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pc
s
s
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X
c
c
(
2
7
)
P
h
ase
7
:
T
h
e
ag
g
r
eg
ated
v
al
u
e
s
o
f
X
f
r
o
m
t
h
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q
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atio
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2
7
a
n
d
f
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q
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at
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.
3
h
a
v
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m
u
ltip
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,
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n
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f
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o
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a
tr
ix
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as b
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n
f
o
r
m
ed
as
s
h
o
w
n
in
E
q
u
a
tio
n
2
8
.
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