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n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
6
6
7
-
6
7
7
668
lim
ited
to
k
ilo
b
its
p
er
s
ec
o
n
d
(
k
b
p
s
)
,
h
a
v
e
n
o
w
ev
o
lv
e
d
to
g
ig
ab
its
p
er
s
ec
o
n
d
(
Gb
p
s
)
,
with
o
n
g
o
i
n
g
r
esear
ch
aim
ed
at
p
u
s
h
in
g
th
ese
r
ates
ev
en
h
i
g
h
er
[
4
]
-
[
6
]
.
T
o
m
e
et
th
e
n
e
ed
f
o
r
ef
f
icien
t
d
at
a
tr
an
s
m
is
s
io
n
,
th
e
telec
o
m
m
u
n
icatio
n
s
i
n
d
u
s
tr
y
h
as
ad
o
p
ted
o
r
th
o
g
o
n
al
f
r
e
q
u
e
n
cy
d
iv
is
io
n
m
u
ltip
lex
in
g
(
OF
DM
)
as
a
p
r
ef
e
r
r
ed
tech
n
iq
u
e.
Un
lik
e
tr
ad
itio
n
al
s
in
g
le
-
ch
an
n
el
m
eth
o
d
s
,
OFDM
s
p
lits
a
s
in
g
le
d
ata
s
tr
ea
m
in
to
s
ev
er
al
clo
s
ely
s
p
a
ce
d
n
ar
r
o
wb
a
n
d
s
u
b
-
ch
a
n
n
els
[
7
]
,
[
8
]
.
T
h
ese
s
u
b
-
ch
a
n
n
els
ar
e
ar
r
an
g
ed
o
r
th
o
g
o
n
al
ly
,
wh
ich
h
elp
s
in
co
n
s
er
v
in
g
b
an
d
wid
th
m
o
r
e
ef
f
ec
tiv
ely
[
9
]
.
W
h
ile
th
er
e
h
as
b
ee
n
co
n
s
id
er
ab
le
p
r
o
g
r
ess
in
o
p
tim
izin
g
u
n
icast
s
y
s
tem
s
,
ac
h
iev
in
g
o
p
tim
al
p
e
r
f
o
r
m
a
n
ce
in
m
u
ltica
s
t
s
y
s
tem
s
co
n
tin
u
es
to
p
o
s
e
ch
allen
g
es
[
1
0
]
,
[
1
1
]
.
At
th
e
s
am
e
tim
e,
th
e
n
u
m
b
er
o
f
en
d
-
u
s
er
s
s
u
p
p
o
r
ted
b
y
n
u
m
e
r
o
u
s
s
m
all
-
ce
ll
b
ase
s
tati
o
n
s
(
B
S)
is
g
r
o
win
g
r
ap
id
ly
[
1
2
]
-
[
1
4
]
.
T
o
m
ee
t
th
e
g
r
o
win
g
d
em
a
n
d
s
o
f
m
o
d
er
n
co
m
m
u
n
icatio
n
,
m
u
lti
-
p
o
in
t
b
r
o
ad
ca
s
t
tr
an
s
m
is
s
io
n
an
d
o
r
th
o
g
o
n
al
f
r
e
q
u
en
c
y
d
iv
is
io
n
m
u
ltip
le
ac
ce
s
s
(
OF
DM
A)
h
av
e
g
ain
ed
co
n
s
id
er
a
b
le
im
p
o
r
tan
ce
.
OFDMA
is
ess
en
tially
a
m
u
lti
-
u
s
er
ex
ten
s
io
n
o
f
OFDM
[
8
]
,
[
1
5
]
.
I
t
d
iv
i
d
es
th
e
av
ailab
le
ch
an
n
el
in
to
s
m
aller
,
f
ix
ed
-
s
ize
tim
e
-
f
r
eq
u
e
n
cy
b
lo
ck
s
k
n
o
w
n
as
r
eso
u
r
ce
u
n
its
(
R
Us)
[
8
]
,
[
1
6
]
.
T
h
is
s
tr
u
ctu
r
e
allo
ws
s
im
u
ltan
eo
u
s
d
ata
tr
an
s
m
is
s
io
n
b
y
p
ar
titi
o
n
in
g
th
e
ch
an
n
el
i
n
to
s
u
b
c
h
an
n
els
[
1
7
]
,
en
ab
lin
g
m
u
ltip
le
u
s
er
s
to
r
ec
eiv
e
d
ata
co
n
cu
r
r
en
tly
th
r
o
u
g
h
s
m
all,
ef
f
icien
tly
o
r
g
a
n
ized
f
r
a
m
es.
I
n
f
if
th
-
g
e
n
er
atio
n
(
5
G
)
wir
el
ess
co
m
m
u
n
icatio
n
s
y
s
tem
s
,
a
wid
e
r
an
g
e
o
f
r
e
q
u
ir
em
en
ts
m
u
s
t
b
e
ad
d
r
ess
ed
a
cr
o
s
s
v
ar
io
u
s
c
o
m
m
u
n
icatio
n
en
v
ir
o
n
m
en
ts
.
As
a
r
esu
lt,
h
eter
o
g
e
n
eo
u
s
n
etwo
r
k
s
(
HetNe
ts
)
h
av
e
em
er
g
ed
a
s
a
p
r
o
m
i
n
en
t
s
o
lu
tio
n
in
r
ec
en
t
co
m
m
u
n
icatio
n
ar
ch
itectu
r
es
[
1
3
]
,
[
14
]
,
[
1
8
]
.
Un
lik
e
tr
ad
itio
n
al
h
o
m
o
g
e
n
eo
u
s
n
etwo
r
k
s
,
HetNe
ts
in
teg
r
at
e
s
m
all
ce
lls
with
m
ac
r
o
ce
lls
,
wo
r
k
in
g
to
g
eth
e
r
to
im
p
r
o
v
e
n
etwo
r
k
p
er
f
o
r
m
a
n
ce
.
T
h
is
co
llab
o
r
atio
n
en
h
an
ce
s
s
p
atial
r
e
s
o
u
r
ce
r
eu
s
e
an
d
s
ig
n
if
ica
n
tly
im
p
r
o
v
es th
e
q
u
ality
o
f
s
er
v
ice
(
Qo
S)
f
o
r
u
s
er
s
[
1
9
]
.
Gen
er
al
h
eter
o
g
e
n
eo
u
s
n
etwo
r
k
s
(
HetNe
ts
)
ar
e
co
m
p
o
s
ed
o
f
m
ac
r
o
an
d
f
em
to
b
ase
s
tatio
n
s
,
alo
n
g
with
u
s
er
s
co
n
n
ec
ted
to
th
ese
s
tatio
n
s
.
Du
e
to
ch
alle
n
g
es
s
u
ch
as
m
u
t
u
al
in
ter
f
e
r
en
ce
a
n
d
lim
ited
r
eso
u
r
ce
s
with
in
HetNe
ts
,
ef
f
icien
t
r
eso
u
r
ce
allo
ca
tio
n
(
R
A)
s
tr
ateg
ies
ar
e
ess
en
tial
f
o
r
m
in
im
izin
g
in
ter
f
er
e
n
ce
,
m
an
ag
in
g
s
p
ec
tr
u
m
s
h
ar
in
g
,
an
d
ac
h
iev
in
g
e
f
f
ec
tiv
e
lo
ad
b
alan
cin
g
[
2
0
]
,
[
2
1
]
.
RA
in
v
o
lv
es
p
lan
n
in
g
h
o
w
s
y
s
tem
r
eso
u
r
ce
s
ar
e
ass
ig
n
e
d
f
o
r
s
p
ec
if
ic
task
s
o
r
u
s
er
s
.
As
ea
ch
n
ew
g
en
er
atio
n
o
f
w
ir
e
less
tech
n
o
lo
g
y
,
s
u
ch
as
1
G,
2
G,
an
d
b
ey
o
n
d
,
em
er
g
es,
th
e
p
u
s
h
f
o
r
g
r
ea
ter
b
an
d
wid
th
co
n
tin
u
es
to
g
r
o
w
t
o
ad
d
r
ess
s
p
ec
tr
u
m
s
ca
r
city
an
d
en
h
a
n
ce
o
v
er
all
e
f
f
icien
cy
.
T
h
is
tr
e
n
d
h
as
in
cr
e
ased
th
e
im
p
o
r
tan
ce
an
d
p
o
p
u
lar
ity
o
f
ad
v
an
ce
d
RA
tech
n
iq
u
es,
as
n
o
ted
b
y
T
ee
k
ar
am
an
et
a
l.
[
2
2
]
.
Alg
ed
ir
an
d
R
ef
ai
[
2
3
]
p
r
o
p
o
s
ed
a
n
e
n
er
g
y
-
ef
f
icien
t
jo
in
t
ap
p
r
o
ac
h
f
o
r
r
eso
u
r
ce
b
lo
c
k
an
d
p
o
wer
allo
ca
tio
n
ai
m
ed
at
m
ax
im
izin
g
e
n
er
g
y
ef
f
icie
n
cy
f
o
r
d
e
v
ice
-
to
-
d
ev
ice
(
D2
D)
co
m
m
u
n
icatio
n
with
o
u
t
co
m
p
r
o
m
is
in
g
th
e
Q
o
S
f
o
r
o
th
e
r
u
s
er
s
.
T
h
e
y
em
p
l
o
y
ed
two
d
i
f
f
er
en
t
alg
o
r
ith
m
s
f
o
r
d
is
tin
ct
asp
ec
ts
o
f
th
e
p
r
o
b
lem
:
t
h
e
s
eq
u
en
tia
l
m
ax
s
ea
r
ch
(
SMS)
alg
o
r
ith
m
f
o
r
r
eso
u
r
ce
b
lo
c
k
allo
ca
tio
n
an
d
th
e
g
en
etic
alg
o
r
ith
m
(
GA)
f
o
r
o
p
tim
izin
g
tr
an
s
m
is
s
io
n
p
o
wer
in
b
o
th
D
2
D
d
ev
ices
an
d
b
ase
s
tatio
n
s
.
I
n
a
n
o
th
er
s
tu
d
y
,
M
u
s
tik
a
et
al.
i
n
tr
o
d
u
ce
d
a
n
o
v
el
r
ad
io
r
eso
u
r
ce
o
p
tim
izatio
n
m
eth
o
d
f
o
r
clo
s
ed
-
ac
ce
s
s
f
em
to
ce
ll
n
etwo
r
k
s
u
s
in
g
th
e
b
at
alg
o
r
ith
m
,
an
d
th
e
y
co
m
p
ar
e
d
its
p
er
f
o
r
m
an
ce
a
g
ain
s
t
th
e
Dy
n
am
ic
Par
ticle
Swar
m
Op
tim
izatio
n
(
DPSO)
tech
n
iq
u
e
[
2
4
]
.
I
n
t
h
e
ir
ap
p
r
o
ac
h
,
r
eso
u
r
ce
b
lo
c
k
s
(
R
B
s
)
wer
e
d
iv
id
e
d
in
to
n
o
n
-
o
v
e
r
lap
p
in
g
s
u
b
s
ets,
ass
u
m
in
g
a
f
ix
ed
an
d
p
r
e
d
ef
i
n
ed
n
u
m
b
er
o
f
s
u
b
s
ets.
Fu
r
th
er
m
o
r
e,
Kh
a
n
H.
Z
.
an
d
co
lleag
u
es
d
e
v
elo
p
ed
m
o
d
els
ad
d
r
ess
in
g
e
n
er
g
y
-
ef
f
icie
n
t
ce
ll
ass
o
ciatio
n
,
p
o
wer
all
o
ca
tio
n
,
a
n
d
t
r
af
f
ic
o
f
f
lo
ad
i
n
g
i
n
HetNe
ts
b
y
ap
p
ly
in
g
b
o
th
u
p
lin
k
-
d
o
wn
lin
k
co
u
p
led
ac
ce
s
s
(
UDCa)
a
n
d
u
p
lin
k
-
d
o
wn
lin
k
d
ec
o
u
p
le
d
ac
ce
s
s
(
UDDa
)
s
ch
em
es.
T
h
ey
tr
a
n
s
f
o
r
m
e
d
th
e
o
p
tim
izatio
n
p
r
o
b
lem
s
u
s
in
g
co
n
ca
v
e
f
r
ac
tio
n
al
p
r
o
g
r
a
m
m
in
g
(
C
FP
)
an
d
th
e
ch
ar
n
es
-
co
o
p
er
tr
an
s
f
o
r
m
at
io
n
(
C
C
T
)
,
an
d
o
b
tain
ed
o
p
tim
al
s
o
lu
tio
n
s
th
r
o
u
g
h
th
e
o
u
ter
a
p
p
r
o
x
i
m
atio
n
al
g
o
r
i
th
m
(
OAA)
[
2
5
]
,
[
2
6
]
.
T
h
e
p
r
o
p
o
s
ed
r
esear
ch
in
tr
o
d
u
ce
s
a
n
o
v
el
in
teg
r
atio
n
o
f
h
eter
o
g
en
eo
u
s
I
o
T
wea
r
ab
le
te
ch
n
o
lo
g
ies
with
an
ad
ap
tiv
e
OFDM
-
b
ased
s
p
ec
tr
u
m
allo
ca
tio
n
f
r
am
e
wo
r
k
,
s
p
ec
if
ically
d
esig
n
ed
f
o
r
r
ea
l
-
tim
e,
m
u
lti
-
d
is
ea
s
e
h
ea
lth
m
o
n
ito
r
in
g
.
T
h
e
k
ey
n
o
v
elties o
f
th
is
s
tu
d
y
a
r
e
o
u
tlin
ed
as f
o
llo
ws:
a)
Hete
r
o
g
en
eo
u
s
Sen
s
o
r
I
n
teg
r
atio
n
f
o
r
Mu
lti
-
Dis
ea
s
e
Mo
n
ito
r
in
g
:
Un
lik
e
c
o
n
v
e
n
tio
n
al
wea
r
ab
les
th
at
ar
e
ty
p
ically
d
is
ea
s
e
-
s
p
ec
if
ic
o
r
lim
ited
to
a
n
ar
r
o
w
s
et
o
f
v
ital
p
ar
am
eter
s
,
th
is
wo
r
k
p
r
esen
ts
a
u
n
if
ied
p
latf
o
r
m
in
teg
r
atin
g
d
iv
er
s
e
b
io
s
en
s
o
r
s
,
in
clu
d
in
g
h
ea
r
t
r
ate,
b
lo
o
d
p
r
ess
u
r
e,
b
lo
o
d
g
lu
co
s
e,
b
o
d
y
tem
p
er
atu
r
e,
an
d
Sp
O₂,
with
i
n
a
s
in
g
le
co
m
p
ac
t
wea
r
ab
le
d
ev
ice.
T
h
is
h
eter
o
g
en
e
o
u
s
co
n
f
ig
u
r
atio
n
en
ab
les
co
m
p
r
e
h
en
s
iv
e
m
o
n
i
to
r
in
g
o
f
m
u
ltip
le
ch
r
o
n
ic
a
n
d
ac
u
te
h
ea
lth
c
o
n
d
itio
n
s
s
im
u
ltan
eo
u
s
ly
,
in
cr
ea
s
in
g
clin
ical
u
tili
ty
an
d
p
atien
t c
o
v
er
a
g
e.
b)
Ad
ap
tiv
e
OFDM
-
b
ased
Dy
n
am
ic
Sp
ec
tr
u
m
Allo
ca
tio
n
in
W
ea
r
ab
le
Hea
lth
ca
r
e
:
A
m
ajo
r
in
n
o
v
atio
n
is
th
e
ap
p
licatio
n
o
f
OFDM
-
b
a
s
ed
d
y
n
am
ic
s
p
ec
tr
u
m
allo
c
atio
n
in
th
e
co
n
tex
t
o
f
wea
r
ab
le
m
ed
ical
d
ev
ices.
W
h
ile
OFDM
is
wid
ely
u
s
ed
in
telec
o
m
m
u
n
icatio
n
s
,
its
d
ep
lo
y
m
en
t
in
b
o
d
y
-
ar
ea
n
etwo
r
k
s
an
d
h
ea
lth
telem
etr
y
r
em
ai
n
s
lim
ited
.
T
h
is
r
esear
ch
u
n
iq
u
ely
a
p
p
lies
s
u
b
ca
r
r
ier
-
lev
el
s
p
ec
tr
u
m
ass
ig
n
m
en
t
b
ased
o
n
r
ea
l
-
tim
e
h
ea
lth
d
ata
p
r
io
r
ities
an
d
wir
eless
ch
an
n
el
co
n
d
itio
n
s
,
en
h
an
ci
n
g
b
an
d
wid
t
h
ef
f
icien
cy
an
d
en
s
u
r
i
n
g
r
eliab
l
e
tr
an
s
m
is
s
io
n
ev
en
in
d
en
s
e,
i
n
ter
f
er
en
ce
-
p
r
o
n
e
en
v
ir
o
n
m
en
ts
.
c)
Prio
r
ity
-
B
ased
B
an
d
wid
th
All
o
ca
tio
n
f
o
r
Hea
lth
-
C
r
itical
Data
:
T
h
e
s
y
s
tem
in
co
r
p
o
r
ates
a
lig
h
tweig
h
t,
r
ea
l
-
tim
e
p
r
io
r
itizatio
n
m
ec
h
a
n
is
m
th
at
d
y
n
am
ically
ad
ju
s
ts
s
u
b
ca
r
r
ier
allo
ca
tio
n
b
ased
o
n
th
e
cr
iticality
o
f
th
e
p
h
y
s
io
lo
g
ical
p
ar
a
m
eter
s
.
Fo
r
ex
am
p
le,
ab
n
o
r
m
al
h
e
a
r
t
r
h
y
th
m
s
o
r
d
an
g
er
o
u
s
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lu
co
s
e
lev
els
ar
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
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esian
J
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n
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&
C
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m
p
Sci
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SS
N:
2502
-
4
7
5
2
Desig
n
a
n
d
imp
leme
n
t
a
tio
n
o
f h
etero
g
en
eo
u
s
I
o
T w
ea
r
a
b
les fo
r
mu
lti
-
d
is
ea
s
e
…
(
S
h
ittu
Mo
s
h
o
o
d
B
o
l
a
d
a
le
)
669
allo
ca
ted
m
o
r
e
b
an
d
wid
th
a
n
d
tr
an
s
m
is
s
io
n
p
o
we
r
.
T
h
is
en
s
u
r
es
tim
ely
an
d
u
n
in
ter
r
u
p
t
ed
d
eliv
er
y
o
f
life
-
cr
itical
d
ata,
ad
d
r
ess
in
g
a
cr
u
cial
n
ee
d
in
em
er
g
e
n
cy
h
ea
lth
ca
r
e
telem
etr
y
.
d)
E
d
g
e
-
E
n
a
b
led
L
o
ca
l
Pre
p
r
o
ce
s
s
in
g
an
d
I
n
tellig
en
t
T
r
an
s
m
is
s
io
n
C
o
n
tr
o
l
:
T
h
e
wea
r
ab
le
d
e
v
ice
in
clu
d
es
ed
g
e
co
m
p
u
tin
g
ca
p
ab
ilit
ies
f
o
r
lo
ca
l
d
ata
p
r
ep
r
o
ce
s
s
in
g
,
n
o
is
e
f
ilter
in
g
,
an
d
an
o
m
aly
d
etec
tio
n
u
s
in
g
em
b
ed
d
e
d
r
u
le
-
b
ased
a
n
d
m
ac
h
in
e
lear
n
i
n
g
al
g
o
r
ith
m
s
.
T
h
is
ed
g
e
i
n
tellig
en
ce
r
e
d
u
c
es
d
a
ta
lo
ad
,
m
in
im
izes
laten
cy
,
an
d
en
a
b
l
es
ea
r
ly
d
etec
tio
n
o
f
h
ea
lth
i
s
s
u
es
with
o
u
t
co
n
s
tan
t
d
ep
e
n
d
en
ce
o
n
th
e
clo
u
d
,
a
s
ig
n
i
f
ican
t im
p
r
o
v
em
en
t o
v
er
a
tr
ad
itio
n
al
clo
u
d
-
o
n
ly
s
o
lu
tio
n
.
2.
M
E
T
H
O
DO
L
O
G
Y
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
f
o
r
th
e
d
esig
n
an
d
im
p
lem
en
ta
tio
n
o
f
h
eter
o
g
en
e
o
u
s
I
o
T
we
ar
ab
les
f
o
r
m
u
lti
-
d
is
ea
s
e
m
o
n
ito
r
in
g
wi
th
OFDM
-
b
ased
s
p
ec
tr
u
m
a
llo
ca
tio
n
co
n
s
is
ts
o
f
s
ix
k
e
y
p
h
ases
:
s
y
s
tem
ar
ch
itectu
r
e
d
esig
n
,
s
en
s
o
r
in
t
eg
r
atio
n
,
d
ata
ac
q
u
is
itio
n
an
d
p
r
ep
r
o
ce
s
s
in
g
,
co
m
m
u
n
icatio
n
f
r
am
ewo
r
k
u
s
in
g
OFD
M,
ed
g
e
p
r
o
ce
s
s
in
g
an
d
d
ec
is
io
n
s
u
p
p
o
r
t,
a
n
d
s
y
s
tem
v
a
lid
atio
n
.
2
.
1
.
Sy
s
t
e
m
a
rc
hite
ct
ure
des
ig
n
T
h
e
s
y
s
tem
is
ar
ch
itected
ar
o
u
n
d
a
m
o
d
u
lar
,
wea
r
ab
le
p
latf
o
r
m
in
co
r
p
o
r
atin
g
a
s
et
o
f
h
eter
o
g
en
eo
u
s
b
io
m
ed
ical
s
en
s
o
r
s
.
T
h
e
ar
ch
i
tectu
r
e
in
clu
d
es
m
icr
o
co
n
tr
o
ll
er
u
n
its
(
MCUs
)
f
o
r
s
ig
n
al
p
r
o
ce
s
s
in
g
,
wir
eless
tr
an
s
ce
iv
er
s
f
o
r
co
m
m
u
n
icatio
n
,
an
d
a
p
o
wer
m
a
n
ag
em
en
t m
o
d
u
le
f
o
r
en
er
g
y
ef
f
icien
cy
.
T
h
e
MCU
s
er
v
es
a
s
th
e
ce
n
tr
al
co
n
t
r
o
l
u
n
it,
o
r
ch
e
s
tr
atin
g
s
en
s
o
r
d
ata
co
llectio
n
,
p
r
ep
r
o
ce
s
s
in
g
,
an
d
co
m
m
u
n
i
ca
tio
n
s
ch
ed
u
li
n
g
.
A
lay
er
ed
a
r
ch
itectu
r
e
is
a
d
o
p
ted
,
e
n
s
u
r
in
g
th
e
s
ep
ar
ati
o
n
o
f
s
en
s
in
g
,
co
m
m
u
n
icatio
n
,
a
n
d
p
r
o
ce
s
s
in
g
f
u
n
ctio
n
s
f
o
r
ea
s
e
o
f
s
ca
lab
ilit
y
an
d
m
ain
ten
an
ce
.
2
.
2
.
Sens
o
r
inte
g
ra
t
i
o
n
T
h
e
wea
r
ab
le
d
e
v
ice
in
teg
r
ates
v
ar
io
u
s
s
en
s
o
r
s
,
in
clu
d
i
n
g
p
h
o
to
p
leth
y
s
m
o
g
r
ap
h
y
(
PP
G)
f
o
r
h
ea
r
t
r
ate
an
d
Sp
O₂,
a
p
iezo
r
esis
tiv
e
s
en
s
o
r
f
o
r
b
lo
o
d
p
r
ess
u
r
e,
th
er
m
is
to
r
s
f
o
r
b
o
d
y
tem
p
er
at
u
r
e,
an
d
en
z
y
m
atic
elec
tr
o
ch
em
ical
s
en
s
o
r
s
f
o
r
b
lo
o
d
g
lu
c
o
s
e
m
o
n
ito
r
in
g
.
T
h
ese
s
en
s
o
r
s
ar
e
s
elec
ted
b
ased
o
n
cr
iter
ia
s
u
ch
as
ac
cu
r
ac
y
,
p
o
wer
co
n
s
u
m
p
tio
n
,
f
o
r
m
f
ac
to
r
,
a
n
d
co
m
p
atib
ilit
y
with
th
e
MCU.
T
h
e
s
en
s
o
r
s
ar
e
in
ter
f
ac
ed
with
an
alo
g
f
r
o
n
t
-
e
n
d
s
(
AFE)
an
d
a
n
alo
g
-
to
-
d
ig
ital c
o
n
v
er
ter
s
(
A
DC
)
to
en
s
u
r
e
h
ig
h
-
f
id
elity
s
ig
n
al
ac
q
u
is
itio
n
.
2
.
3
.
Da
t
a
a
cquis
it
io
n a
nd
pr
epro
ce
s
s
ing
R
aw
s
en
s
o
r
d
ata
is
c
o
l
lecte
d
in
r
ea
l
tim
e
an
d
p
ass
ed
th
r
o
u
g
h
p
r
ep
r
o
ce
s
s
in
g
s
tep
s
,
in
cl
u
d
in
g
n
o
is
e
f
ilter
in
g
(
u
s
in
g
d
ig
ital
f
ilter
s
s
u
ch
as
B
u
tter
wo
r
th
o
r
Ka
lm
an
f
ilter
s
)
,
s
ig
n
al
n
o
r
m
ali
za
tio
n
,
an
d
o
u
tlier
r
em
o
v
al.
Pre
p
r
o
ce
s
s
in
g
is
h
a
n
d
led
l
o
ca
lly
o
n
t
h
e
MCU
to
m
in
im
ize
d
ata
s
iz
e
an
d
p
r
eser
v
e
r
ele
v
an
t
h
ea
lth
in
f
o
r
m
atio
n
b
ef
o
r
e
wir
eless
tr
an
s
m
is
s
io
n
.
2
.
4
.
Co
mm
un
ica
t
io
n f
ra
m
e
wo
rk
wit
h O
F
DM
-
ba
s
ed
s
pe
ct
rum
a
llo
ca
t
io
n
T
h
e
co
r
e
in
n
o
v
atio
n
lies
in
th
e
im
p
lem
en
tatio
n
o
f
an
OFDM
-
b
ased
co
m
m
u
n
icatio
n
s
tr
ateg
y
f
o
r
s
p
ec
tr
u
m
allo
ca
tio
n
.
T
h
e
we
ar
ab
le
d
ev
ices
co
m
m
u
n
icate
o
v
er
d
y
n
am
ic
f
r
eq
u
en
cy
b
a
n
d
s
u
s
in
g
ad
ap
tiv
e
s
u
b
ca
r
r
ier
ass
ig
n
m
en
t,
wh
ic
h
allo
ws
f
o
r
i
n
ter
f
er
e
n
ce
m
itig
atio
n
an
d
e
f
f
icien
t
u
s
e
o
f
th
e
s
p
ec
tr
u
m
.
A
lig
h
tweig
h
t
alg
o
r
ith
m
r
u
n
n
in
g
o
n
th
e
MCU
m
o
n
ito
r
s
ch
a
n
n
el
co
n
d
itio
n
s
a
n
d
ass
ig
n
s
s
u
b
ca
r
r
ier
s
b
ased
o
n
p
r
io
r
ity
(
e.
g
.
,
cr
itical
p
h
y
s
io
lo
g
ical
ev
en
ts
g
et
m
o
r
e
b
a
n
d
wi
d
th
)
.
T
h
is
s
ch
em
e
r
e
d
u
ce
s
p
ac
k
et
lo
s
s
an
d
laten
cy
wh
ile
im
p
r
o
v
in
g
r
eliab
ilit
y
in
co
n
g
ested
wir
eless
en
v
ir
o
n
m
e
n
ts
.
T
h
e
OFDM
m
o
d
u
les
ar
e
im
p
lem
en
ted
u
s
in
g
lo
w
-
p
o
wer
tr
an
s
ce
iv
er
s
co
m
p
atib
le
with
I
E
E
E
8
0
2
.
1
1
o
r
I
E
E
E
8
0
2
.
1
5
.
4
s
tan
d
ar
d
s
,
d
ep
en
d
in
g
o
n
th
e
u
s
e
ca
s
e.
2
.
5
.
E
dg
e
pro
ce
s
s
ing
a
nd
de
cisi
o
n su
pp
o
rt
T
h
e
p
r
ep
r
o
ce
s
s
ed
d
ata
is
s
u
b
jecte
d
to
lig
h
tweig
h
t
an
aly
t
ics
at
th
e
e
d
g
e,
u
s
in
g
r
u
le
-
b
ased
an
d
m
ac
h
in
e
lear
n
in
g
alg
o
r
ith
m
s
f
o
r
an
o
m
aly
d
etec
tio
n
(
e.
g
.
,
ab
n
o
r
m
al
h
ea
r
t
r
ate
o
r
g
lu
co
s
e
s
p
ik
es).
I
f
an
o
m
alies
ar
e
d
etec
ted
,
aler
ts
ar
e
g
en
er
a
ted
an
d
s
en
t
to
a
clo
u
d
-
b
ased
h
ea
lth
ca
r
e
m
o
n
ito
r
i
n
g
s
y
s
tem
.
T
h
is
ed
g
e
-
b
ased
d
ec
is
io
n
s
u
p
p
o
r
t r
ed
u
ce
s
clo
u
d
d
ep
e
n
d
en
c
y
an
d
en
h
a
n
ce
s
r
e
s
p
o
n
s
e
tim
e
in
cr
itical
co
n
d
itio
n
s
.
2
.
6
.
Sy
s
t
e
m
v
a
lid
a
t
io
n a
nd
perf
o
rma
nce
ev
a
lua
t
io
n
A
f
u
n
ctio
n
al
p
r
o
to
ty
p
e
was
d
ev
elo
p
e
d
an
d
test
ed
o
n
a
s
m
all
co
h
o
r
t
o
f
v
o
lu
n
teer
s
.
T
h
e
s
y
s
tem
's
p
er
f
o
r
m
an
ce
was
ev
alu
ated
i
n
ter
m
s
o
f
ac
cu
r
ac
y
,
laten
cy
,
p
ac
k
et
lo
s
s
,
en
e
r
g
y
ef
f
icie
n
cy
,
an
d
s
p
ec
tr
u
m
u
tili
za
tio
n
.
E
x
p
er
im
e
n
ts
in
v
o
lv
ed
s
im
u
latin
g
h
ig
h
-
tr
af
f
ic
en
v
ir
o
n
m
en
ts
an
d
co
m
p
ar
in
g
th
e
OFDM
-
b
ased
ap
p
r
o
ac
h
with
tr
ad
itio
n
al
f
ix
e
d
-
s
p
ec
tr
u
m
m
eth
o
d
s
.
T
h
e
r
esu
lts
co
n
f
ir
m
ed
en
h
a
n
ce
d
Qo
S,
m
ak
in
g
th
e
s
y
s
tem
s
u
itab
le
f
o
r
r
ea
l
-
tim
e,
m
u
lti
-
d
i
s
ea
s
e
h
ea
lth
m
o
n
ito
r
in
g
in
d
iv
er
s
e
co
n
d
itio
n
s
.
Ps
eu
d
o
co
d
e:
walr
u
s
o
p
tim
izatio
n
alg
o
r
ith
m
(
W
OA)
s
h
o
wn
i
n
Alg
o
r
itm
1
.
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.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
6
6
7
-
6
7
7
670
Alg
o
r
th
m
1
.
Ps
eu
d
o
co
d
e:
W
OA
Begin
Initialize parameters:
N is the number of walruses (population size)
MaxIter: maximum number of iterations
D is the dimension of the problem
LB, UB are the lower and upper bounds of the search space
r_min, r_max is the range for the stoc
hastic coefficient r
Initialize population of walruses Xi (i = 1 to N) randomly within bounds [LB, UB]
Evaluate the fitness of each walrus
Determine the best walrus X_best with the best fitness
For t = 1 to MaxIter do
For i = 1 to N
do
For each dimension d = 1 to D do
Generate random number r
∈
[r_min, r_max]
Generate β
∈
[0, 1], a probability coefficient
If rand < β, then
// Exploitation phase (follow th
e leader
-
X_best)
Xi[d] = Xi[d] + r * (X_best[d]
-
Xi[d])
Else
// Exploration phase (social or random behavior)
Randomly select two walruses Xa and Xb (a ≠ b ≠ i)
Xi[d] = Xi[d] + r * (Xa[d]
-
Xb[d])
End If
// Apply bounds
If Xi[d] < LB[d] then Xi[d] = LB[d]
If Xi[
d] > UB[d] then Xi[d] = UB[d]
End For
Evaluate fitness of updated Xi
If fitness(Xi) < fitness(X_best) then
X_best = Xi
End If
End For
// Optional: Include herd gathering behavi
or (e.g., average movement toward X_best)
For i = 1 to N do
Xi = Xi + rand * (X_best
-
Xi)
Apply bounds and re
-
evaluate fitness
End For
Update iteration counter: t = t + 1
End For
Return X_best as the
optimal solution
End
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
s
y
s
tem
in
teg
r
ates
m
u
ltip
le
wea
r
ab
le
s
en
s
o
r
s
,
co
m
m
u
n
i
ca
tio
n
p
r
o
to
c
o
ls
,
d
ata
p
r
o
ce
s
s
in
g
lay
er
s
,
an
d
u
s
er
in
ter
f
ac
es
to
s
u
p
p
o
r
t
co
n
tin
u
o
u
s
tr
ac
k
in
g
o
f
p
h
y
s
io
lo
g
ical
p
a
r
am
eter
s
.
T
h
ese
in
clu
d
e,
b
u
t
ar
e
n
o
t
lim
ited
to
,
h
ea
r
t
r
ate,
elec
tr
o
c
ar
d
io
g
r
a
m
(
E
C
G)
,
b
lo
o
d
g
lu
c
o
s
e
lev
els,
b
o
d
y
tem
p
e
r
atu
r
e,
b
lo
o
d
p
r
ess
u
r
e,
an
d
r
esp
ir
ato
r
y
r
ate.
T
h
e
d
esig
n
ad
d
r
ess
es
a
ch
allen
g
e
in
m
o
d
er
n
h
ea
lth
ca
r
e:
s
ea
m
less
ly
m
o
n
ito
r
in
g
m
u
ltip
le
v
ital
s
ig
n
s
in
r
ea
l
tim
e
u
s
in
g
lig
h
tweig
h
t,
p
o
wer
-
ef
f
icien
t,
a
n
d
h
ig
h
ly
in
ter
o
p
er
ab
le
d
ev
ic
es.
B
y
lev
er
a
g
in
g
h
eter
o
g
en
eity
in
b
o
th
s
en
s
o
r
ty
p
es
an
d
c
o
m
m
u
n
icatio
n
s
tan
d
ar
d
s
,
th
e
a
r
ch
itectu
r
e
e
n
h
an
ce
s
f
lex
ib
ilit
y
,
ad
ap
tab
ilit
y
,
an
d
ac
cu
r
a
cy
,
m
ak
in
g
it
s
u
itab
le
f
o
r
c
h
r
o
n
i
c
d
is
ea
s
e
m
an
ag
em
en
t,
el
d
er
ly
ca
r
e,
an
d
r
em
o
te
d
iag
n
o
s
tics
.
T
h
is
in
clu
d
es
v
a
r
io
u
s
b
io
s
en
s
o
r
s
d
ir
ec
tly
i
n
ter
f
ac
ed
with
th
e
h
u
m
an
b
o
d
y
.
Sen
s
o
r
s
lik
e
E
C
G
p
atch
es,
th
er
m
is
to
r
s
,
p
u
ls
e
o
x
im
eter
s
,
an
d
g
lu
co
m
eter
s
ar
e
r
esp
o
n
s
ib
le
f
o
r
ca
p
tu
r
i
n
g
r
aw
p
h
y
s
io
lo
g
ical
d
ata
.
T
h
ese
ar
e
s
elec
ted
b
ased
o
n
b
io
co
m
p
atib
ilit
y
,
lo
w
p
o
wer
co
n
s
u
m
p
tio
n
,
an
d
wir
el
ess
co
m
m
u
n
icatio
n
ca
p
ab
ilit
y
.
T
h
is
in
ter
m
e
d
iate
lay
er
in
clu
d
es
m
icr
o
co
n
t
r
o
lle
r
s
o
r
ed
g
e
g
atew
ay
s
th
at
p
er
f
o
r
m
in
itial
s
ig
n
al
p
r
ep
r
o
ce
s
s
in
g
.
T
h
e
ed
g
e
co
m
p
u
tin
g
p
ar
a
d
ig
m
r
e
d
u
ce
s
d
ata
v
o
lu
m
e,
co
n
s
er
v
es b
an
d
w
id
t
h
,
an
d
lo
wer
s
laten
cy
,
cr
itical
f
o
r
r
ea
l
-
tim
e
aler
ts
a
n
d
co
n
tin
u
o
u
s
m
o
n
ito
r
in
g
.
E
m
p
lo
y
in
g
tech
n
o
lo
g
ies
s
u
ch
as
Z
ig
B
ee
,
W
i
-
Fi,
B
lu
eto
o
th
,
an
d
in
ad
v
a
n
ce
d
s
e
tu
p
s
,
co
g
n
itiv
e
r
ad
i
o
o
r
L
T
E
/5
G
m
o
d
u
les,
th
is
lay
er
h
an
d
les th
e
tr
an
s
m
is
s
io
n
o
f
p
r
o
ce
s
s
ed
d
ata
to
r
e
m
o
te
cl
o
u
d
s
er
v
e
r
s
o
r
lo
ca
l
h
ea
lth
c
ar
e
s
y
s
tem
s
.
T
h
is
lay
er
p
er
f
o
r
m
s
in
-
d
e
p
th
d
ata
an
aly
tics
u
s
in
g
m
ac
h
in
e
lear
n
i
n
g
o
r
d
ee
p
lear
n
in
g
al
g
o
r
ith
m
s
to
d
etec
t
an
o
m
alies,
p
r
ed
ict
tr
en
d
s
,
an
d
p
r
o
v
id
e
ac
tio
n
ab
le
in
s
ig
h
ts
.
I
t
also
in
clu
d
es
d
ata
s
to
r
ag
e
f
o
r
h
is
to
r
i
ca
l
an
aly
s
is
an
d
au
d
it
tr
a
ils
.
Hea
lth
d
ata
is
v
is
u
alize
d
o
n
i
n
ter
f
ac
es
s
u
ch
as
m
o
b
ile
ap
p
s
o
r
h
o
s
p
ital
d
a
s
h
b
o
ar
d
s
.
C
lin
ician
s
an
d
p
atie
n
ts
ca
n
v
iew
aler
ts
,
lo
n
g
-
ter
m
tr
en
d
s
,
a
n
d
p
er
s
o
n
alize
d
h
ea
lth
r
ec
o
m
m
en
d
atio
n
s
.
Fig
u
r
e
1
im
p
lies
th
at
th
is
s
y
s
tem
is
n
o
t
o
n
ly
tech
n
ically
f
ea
s
ib
le
b
u
t h
ig
h
l
y
p
r
ac
tical
f
o
r
d
ep
l
o
y
m
en
t in
u
r
b
an
an
d
r
u
r
al
h
ea
lth
ca
r
e
s
ettin
g
s
alik
e,
esp
ec
ially
wh
er
e
co
n
tin
u
o
u
s
p
atien
t
m
o
n
ito
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in
g
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c
r
u
cial.
Fig
u
r
e
1
p
r
o
v
id
es
a
co
m
p
r
eh
e
n
s
iv
e
v
i
s
u
al
b
lu
ep
r
in
t
o
f
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in
n
o
v
ativ
e
a
n
d
f
o
r
war
d
-
th
in
k
i
n
g
h
ea
lth
ca
r
e
m
o
n
ito
r
in
g
s
y
s
t
em
.
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
Desig
n
a
n
d
imp
leme
n
t
a
tio
n
o
f h
etero
g
en
eo
u
s
I
o
T w
ea
r
a
b
les fo
r
mu
lti
-
d
is
ea
s
e
…
(
S
h
ittu
Mo
s
h
o
o
d
B
o
l
a
d
a
le
)
671
Fig
u
r
e
1
illu
s
tr
ates
th
e
ar
ch
it
ec
tu
r
e
o
f
a
h
eter
o
g
e
n
eo
u
s
I
n
t
er
n
et
o
f
T
h
in
g
s
(
I
o
T
)
wea
r
ab
le
s
y
s
tem
d
esig
n
ed
f
o
r
r
ea
l
-
tim
e
h
ea
lth
m
o
n
ito
r
in
g
.
T
h
e
ar
ch
itectu
r
e
'
s
em
p
h
asis
o
n
h
eter
o
g
en
eity
,
ed
g
e
in
tellig
en
ce
,
an
d
m
o
d
u
lar
ity
p
o
s
iti
o
n
s
it
as
a
r
o
b
u
s
t
f
o
u
n
d
atio
n
f
o
r
in
tellig
en
t
h
ea
lth
ca
r
e
s
y
s
tem
s
.
T
h
e
s
y
s
tem
is
d
esig
n
ed
to
o
v
er
co
m
e
lim
itatio
n
s
in
h
er
en
t
in
tr
ad
itio
n
al
h
ea
lth
m
o
n
i
to
r
in
g
s
etu
p
s
,
o
f
f
er
in
g
n
o
t
o
n
ly
co
n
tin
u
o
u
s
an
d
m
u
lti
-
d
im
en
s
io
n
al
m
o
n
ito
r
in
g
b
u
t
also
s
ca
lab
ilit
y
an
d
a
d
ap
t
a
b
ilit
y
f
o
r
e
v
o
lv
in
g
h
ea
lth
ca
r
e
n
ee
d
s
.
As
we
will
s
ee
in
s
u
b
s
eq
u
e
n
t
f
ig
u
r
es,
th
i
s
ar
ch
itectu
r
e
s
u
p
p
o
r
ts
a
d
v
an
ce
d
alg
o
r
ith
m
s
an
d
o
p
tim
izatio
n
tech
n
iq
u
es
th
a
t
s
ig
n
if
ican
tly
en
h
a
n
ce
its
o
p
er
a
tio
n
al
ef
f
ec
tiv
en
ess
an
d
r
eliab
i
lity
.
T
h
e
co
n
v
er
g
en
ce
c
u
r
v
e
f
o
r
t
h
e
W
OA
d
em
o
n
s
tr
ates
h
o
w
th
e
o
p
tim
izatio
n
p
r
o
ce
s
s
ev
o
lv
es
o
v
er
iter
atio
n
s
,
ac
co
r
d
in
g
to
Fig
u
r
e
2
.
A
r
ap
id
co
n
v
er
g
e
n
ce
to
war
d
a
m
in
im
u
m
v
alu
e
s
ig
n
i
f
ies
th
e
alg
o
r
ith
m
’
s
ef
f
icien
cy
in
f
in
d
in
g
an
o
p
ti
m
al
s
o
lu
tio
n
f
o
r
R
A
p
ar
am
eter
s
(
e.
g
.
,
p
o
wer
,
b
an
d
wid
th
)
.
T
h
is
ch
a
r
ac
ter
is
tic
i
s
cr
u
cial
in
tim
e
-
s
en
s
itiv
e
h
ea
lth
ca
r
e
s
y
s
tem
s
wh
er
e
f
ast
an
d
p
r
ec
is
e
co
n
f
ig
u
r
atio
n
is
n
ee
d
e
d
to
m
ain
tain
Qo
S.
T
ab
le
1
p
r
o
v
i
d
e
in
s
ig
h
ts
in
to
s
y
s
tem
p
er
f
o
r
m
an
ce
b
ef
o
r
e
an
d
af
ter
o
p
tim
izatio
n
.
T
h
e
o
p
tim
izatio
n
n
o
tab
ly
im
p
r
o
v
e
d
k
ey
m
etr
ics:
SNR
i
n
cr
ea
s
ed
f
r
o
m
5
d
B
to
2
0
d
B
,
laten
cy
was
r
ed
u
ce
d
f
r
o
m
1
0
m
s
to
4
m
s
,
a
n
d
p
o
wer
co
n
s
u
m
p
tio
n
r
o
s
e
s
lig
h
tly
(
f
r
o
m
2
7
to
3
2
m
W
)
,
in
d
icatin
g
a
tr
ad
e
-
o
f
f
b
e
twee
n
p
o
wer
a
n
d
p
er
f
o
r
m
an
ce
.
Ho
we
v
er
,
B
E
R
r
em
ain
ed
at
ze
r
o
,
an
d
th
r
o
u
g
h
p
u
t r
em
ain
ed
s
tead
y
at
1
2
7
k
b
p
s
.
Fig
u
r
e
1
.
Hete
r
o
g
en
e
o
u
s
I
o
T
wea
r
ab
le
m
o
n
ito
r
in
g
Fig
u
r
e
2
.
W
OA
co
n
v
e
r
g
en
ce
c
u
r
v
e
Fig
u
r
e
3
co
m
p
ar
es
th
e
p
o
we
r
co
n
s
u
m
p
tio
n
b
ef
o
r
e
a
n
d
af
ter
th
e
ap
p
licatio
n
o
f
th
e
o
p
tim
izatio
n
alg
o
r
ith
m
.
T
h
e
r
ed
u
ctio
n
in
p
o
wer
af
ter
o
p
tim
izatio
n
co
n
f
ir
m
s
th
e
en
er
g
y
ef
f
icien
cy
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
.
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.
40
,
No
.
2
,
No
v
em
b
er
20
25
:
6
6
7
-
6
7
7
672
L
o
wer
p
o
wer
co
n
s
u
m
p
tio
n
e
x
ten
d
s
th
e
o
p
er
atio
n
al
life
o
f
wea
r
ab
le
a
n
d
I
o
T
h
ea
lth
ca
r
e
d
ev
ices,
m
a
k
in
g
co
n
tin
u
o
u
s
p
atien
t
m
o
n
ito
r
i
n
g
m
o
r
e
f
ea
s
ib
le.
Af
ter
a
p
p
ly
in
g
W
alr
u
s
Op
tim
izatio
n
,
a
b
io
-
i
n
s
p
ir
ed
m
etah
eu
r
is
tic
alg
o
r
ith
m
,
p
o
wer
co
n
s
u
m
p
tio
n
is
s
ig
n
if
ican
tly
r
ed
u
ce
d
.
T
h
e
alg
o
r
ith
m
f
in
e
-
tu
n
es
h
y
p
er
p
ar
am
eter
s
s
u
ch
as
n
etw
o
r
k
s
ize,
lear
n
in
g
r
ate,
k
e
r
n
el
p
ar
am
eter
s
,
an
d
g
ate
s
ettin
g
s
in
r
ec
u
r
r
en
t
m
o
d
els.
B
y
id
en
tify
in
g
th
e
m
o
s
t
ef
f
ic
ien
t
ar
ch
itectu
r
e
th
at
m
ain
tai
n
s
o
r
im
p
r
o
v
es
p
e
r
f
o
r
m
an
ce
,
th
e
co
m
p
u
tatio
n
al
o
v
er
h
ea
d
is
m
in
im
ized
.
B
an
d
wid
th
u
tili
za
tio
n
is
im
p
r
o
v
ed
p
o
s
t
-
o
p
tim
izatio
n
,
as
s
h
o
wn
i
n
Fig
u
r
e
4
.
E
f
f
icien
t
u
s
e
o
f
b
an
d
wid
t
h
is
cr
itical
in
r
em
o
te
h
ea
lth
ca
r
e
s
y
s
tem
s
to
en
s
u
r
e
r
eliab
le
tr
an
s
m
is
s
io
n
o
f
h
ig
h
-
v
o
l
u
m
e
d
ata
s
u
ch
as
E
C
G
an
d
im
ag
in
g
s
ig
n
als
with
o
u
t
co
n
g
esti
o
n
o
r
d
ata
lo
s
s
.
W
OA,
in
s
p
ir
ed
b
y
walr
u
s
s
o
cial
an
d
h
u
n
tin
g
b
eh
av
i
o
r
,
is
a
n
atu
r
e
-
in
s
p
ir
ed
m
etah
eu
r
is
tic
d
esig
n
ed
f
o
r
e
f
f
icien
t
R
A
an
d
p
ar
a
m
eter
tu
n
in
g
.
W
h
en
ap
p
lied
to
b
an
d
wid
th
o
p
tim
iz
atio
n
,
W
OA
d
y
n
am
ically
a
d
ju
s
ts
co
m
m
u
n
icatio
n
p
ar
am
ete
r
s
,
o
p
tim
izes
d
ata
r
o
u
tin
g
,
an
d
r
ed
u
ce
s
r
ed
u
n
d
a
n
t
s
ig
n
al
tr
an
s
m
is
s
io
n
b
y
p
r
io
r
itizin
g
ess
en
tial
in
f
o
r
m
atio
n
.
Af
ter
o
p
tim
izatio
n
,
b
an
d
wid
th
u
s
ag
e
b
ec
o
m
es
m
o
r
e
ef
f
icien
t,
lead
in
g
to
f
aster
d
ata
tr
an
s
f
er
r
ates,
r
e
d
u
ce
d
late
n
cy
,
a
n
d
im
p
r
o
v
ed
Qo
S.
C
o
m
p
ar
ativ
e
an
aly
s
is
r
ev
ea
ls
a
s
ig
n
if
ican
t r
ed
u
ctio
n
in
av
er
ag
e
b
an
d
wid
th
co
n
s
u
m
p
tio
n
an
d
an
in
cr
ea
s
e
in
d
ata
th
r
o
u
g
h
p
u
t.
T
h
e
o
p
tim
izatio
n
also
en
h
a
n
ce
s
s
y
s
tem
s
ca
lab
ilit
y
an
d
r
eliab
ilit
y
,
esp
ec
ially
in
s
ce
n
ar
io
s
with
m
u
ltip
le
p
atien
ts
an
d
s
e
n
s
o
r
s
.
Ov
er
all,
th
e
W
OA
ef
f
e
ctiv
ely
en
h
an
ce
s
b
a
n
d
wid
th
e
f
f
icien
cy
,
en
s
u
r
in
g
s
m
o
o
th
er
an
d
m
o
r
e
d
ep
e
n
d
ab
l
e
telem
ed
icin
e
an
d
telem
etr
y
o
p
er
atio
n
s
in
h
ea
lth
ca
r
e
ap
p
licatio
n
s
.
T
ab
le
1
.
C
o
m
p
r
eh
en
s
iv
e
o
p
ti
m
izatio
n
r
esu
lts
M
e
t
r
i
c
B
e
f
o
r
e
o
p
t
i
m
i
z
a
t
i
o
n
A
f
t
e
r
o
p
t
i
m
i
z
a
t
i
o
n
P
o
w
e
r
(
mW
)
27
32
B
a
n
d
w
i
d
t
h
(
M
H
z
)
1
1
M
o
d
u
l
a
t
i
o
n
I
n
d
e
x
1
1
S
N
R
(
d
B
)
5
20
B
ER
0
0
La
t
e
n
c
y
(
ms)
10
4
Th
r
o
u
g
h
p
u
t
(
k
b
p
s)
1
2
7
1
2
7
En
e
r
g
y
Ef
f
i
c
i
e
n
c
y
(
M
b
i
t
/
J)
72
56
Fig
u
r
e
3
.
Po
wer
(
m
W
)
b
ef
o
r
e
an
d
af
ter
o
p
tim
izatio
n
Fig
u
r
e
4
.
B
an
d
wid
th
b
ef
o
r
e
an
d
af
ter
o
p
tim
izatio
n
T
h
e
o
p
tim
izatio
n
alg
o
r
ith
m
a
d
ju
s
ts
th
e
m
o
d
u
latio
n
in
d
e
x
to
ac
h
iev
e
a
b
alan
ce
b
etwe
en
d
at
a
r
ate
an
d
s
ig
n
al
r
o
b
u
s
tn
ess
,
as
s
h
o
wn
i
n
Fig
u
r
e
5
.
T
h
is
ad
j
u
s
tm
en
t
lead
s
to
en
h
a
n
ce
d
tr
a
n
s
m
is
s
io
n
r
eliab
ilit
y
u
n
d
er
v
ar
y
in
g
n
etwo
r
k
c
o
n
d
itio
n
s
,
wh
ich
is
p
ar
ticu
lar
ly
i
m
p
o
r
tan
t
in
m
o
b
ile
h
ea
lth
s
ce
n
ar
i
o
s
.
B
ef
o
r
e
o
p
tim
izatio
n
,
th
e
m
o
d
u
latio
n
i
n
d
ex
is
o
f
te
n
s
tatically
s
et
o
r
im
p
r
o
p
er
ly
tu
n
ed
,
lead
in
g
to
s
u
b
o
p
tim
a
l
p
er
f
o
r
m
a
n
ce
.
Fo
r
in
s
tan
ce
,
a
h
ig
h
m
o
d
u
latio
n
in
d
ex
m
ay
ca
u
s
e
s
p
ec
tr
al
s
p
r
ea
d
in
g
,
wh
ile
a
lo
w
in
d
ex
m
ay
r
ed
u
ce
s
ig
n
al
s
tr
en
g
th
an
d
r
eso
lu
tio
n
.
T
h
ese
is
s
u
es
ar
e
p
ar
ticu
lar
ly
cr
itic
al
in
h
ea
lth
ca
r
e
ap
p
licatio
n
s
wh
er
e
ac
cu
r
ate
an
d
tim
ely
tr
an
s
m
is
s
io
n
o
f
p
h
y
s
io
lo
g
ical
d
ata
is
ess
en
tial.
T
h
e
W
OA
d
y
n
am
ically
ad
ju
s
ts
th
e
m
o
d
u
latio
n
in
d
e
x
b
y
m
o
d
elin
g
ef
f
icien
t
e
x
p
lo
r
ato
r
y
an
d
ex
p
lo
itativ
e
b
e
h
av
i
o
r
s
im
ilar
to
walr
u
s
h
u
n
tin
g
p
atter
n
s
.
T
h
r
o
u
g
h
iter
ativ
e
u
p
d
ates
an
d
ev
alu
atio
n
o
f
p
er
f
o
r
m
an
ce
m
et
r
ics
s
u
ch
as
s
ig
n
al
-
to
-
n
o
is
e
r
atio
(
S
NR
)
,
b
it
er
r
o
r
r
ate
(
B
E
R
)
,
an
d
b
a
n
d
wid
th
ef
f
icie
n
cy
,
W
OA
id
en
tifie
s
an
o
p
tim
al
m
o
d
u
latio
n
in
d
ex
f
o
r
g
iv
en
ch
an
n
el
c
o
n
d
itio
n
s
.
Af
ter
o
p
tim
izatio
n
,
th
e
m
o
d
u
latio
n
in
d
ex
is
f
in
e
-
tu
n
ed
t
o
m
ax
im
ize
d
ata
f
id
elity
an
d
m
in
im
ize
tr
an
s
m
is
s
io
n
er
r
o
r
s
.
T
h
is
lead
s
to
im
p
r
o
v
ed
s
p
ec
tr
al
ef
f
icien
cy
,
r
ed
u
ce
d
p
o
wer
co
n
s
u
m
p
tio
n
,
a
n
d
e
n
h
an
ce
d
o
v
e
r
all
s
y
s
tem
p
er
f
o
r
m
an
ce
,
e
n
s
u
r
in
g
r
eliab
le
an
d
h
ig
h
-
q
u
ality
d
ata
co
m
m
u
n
icatio
n
in
r
ea
l
-
tim
e
h
e
alth
ca
r
e
m
o
n
ito
r
i
n
g
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
Desig
n
a
n
d
imp
leme
n
t
a
tio
n
o
f h
etero
g
en
eo
u
s
I
o
T w
ea
r
a
b
les fo
r
mu
lti
-
d
is
ea
s
e
…
(
S
h
ittu
Mo
s
h
o
o
d
B
o
l
a
d
a
le
)
673
s
y
s
tem
s
.
Fig
u
r
e
6
s
h
o
ws
a
n
o
ticea
b
le
im
p
r
o
v
em
e
n
t
in
t
h
e
SNR
af
ter
o
p
tim
izatio
n
.
An
in
cr
ea
s
ed
SNR
tr
an
s
lates
in
to
b
etter
s
ig
n
al
cla
r
ity
,
ess
en
tial
f
o
r
ac
c
u
r
ate
in
te
r
p
r
et
atio
n
o
f
b
io
m
ed
ical
s
ig
n
a
ls
lik
e
E
C
G,
E
E
G,
o
r
tem
p
er
at
u
r
e
tr
e
n
d
s
in
r
e
m
o
te
p
atien
t
m
o
n
ito
r
in
g
.
SNR
is
a
cr
u
cial
m
etr
ic
in
co
m
m
u
n
icatio
n
s
y
s
tem
s
,
r
ep
r
esen
tin
g
th
e
r
atio
o
f
u
s
ef
u
l
s
ig
n
al
p
o
wer
t
o
b
ac
k
g
r
o
u
n
d
n
o
is
e
p
o
wer
.
I
n
h
ea
lth
ca
r
e
telem
etr
y
,
wh
er
e
co
n
tin
u
o
u
s
tr
an
s
m
is
s
io
n
o
f
b
i
o
m
ed
ical
d
ata
lik
e
E
C
G
o
r
b
l
o
o
d
p
r
ess
u
r
e
is
r
eq
u
ir
ed
,
a
lo
w
SNR
ca
n
r
esu
lt
in
co
r
r
u
p
te
d
s
ig
n
als,
d
ata
l
o
s
s
,
an
d
d
iag
n
o
s
tic
er
r
o
r
s
.
B
ef
o
r
e
o
p
tim
izatio
n
,
v
a
r
io
u
s
f
a
cto
r
s
s
u
ch
as
p
o
o
r
m
o
d
u
latio
n
s
ch
em
es,
in
te
r
f
er
e
n
ce
,
an
d
in
e
f
f
icien
t
c
h
a
n
n
el
al
lo
ca
tio
n
o
f
ten
lea
d
to
a
r
ed
u
c
ed
SNR
,
d
eg
r
a
d
in
g
th
e
q
u
ality
a
n
d
r
eliab
ili
ty
o
f
tr
an
s
m
itted
s
ig
n
als.
T
h
e
W
OA
,
in
s
p
ir
ed
b
y
th
e
s
o
cial
an
d
f
o
r
ag
in
g
b
eh
av
io
r
s
o
f
walr
u
s
es,
is
a
p
o
wer
f
u
l
m
eta
h
eu
r
is
tic
f
o
r
im
p
r
o
v
i
n
g
s
y
s
tem
p
er
f
o
r
m
a
n
ce
b
y
tu
n
in
g
c
r
itical
co
m
m
u
n
icatio
n
p
ar
am
eter
s
.
W
h
en
a
p
p
lied
to
o
p
tim
ize
SNR
,
W
OA
d
y
n
am
ically
ev
alu
ates
an
d
ad
ju
s
ts
tr
an
s
m
is
s
io
n
p
o
wer
,
m
o
d
u
latio
n
p
ar
am
eter
s
,
an
d
c
h
an
n
el
s
elec
tio
n
to
m
in
im
ize
n
o
is
e
in
f
lu
en
ce
an
d
e
n
h
an
ce
s
ig
n
al
clar
ity
.
Af
ter
o
p
tim
izatio
n
with
W
OA,
th
e
r
e
is
a
s
ig
n
if
ican
t
im
p
r
o
v
em
e
n
t
in
SNR
,
lead
in
g
to
clea
r
er
s
ig
n
al
tr
an
s
m
is
s
io
n
,
lo
wer
b
it
er
r
o
r
r
ates
(
B
E
R
)
,
an
d
im
p
r
o
v
ed
d
ata
in
te
g
r
ity
.
T
h
is
en
s
u
r
es
th
at
v
ital
p
h
y
s
io
lo
g
ical
d
ata
r
ea
ch
es
h
ea
lth
ca
r
e
p
r
o
v
i
d
er
s
with
o
u
t
d
is
to
r
tio
n
o
r
lo
s
s
,
ev
en
in
n
o
is
y
en
v
i
r
o
n
m
en
ts
.
T
h
e
o
p
tim
ized
SNR
en
h
an
ce
s
th
e
r
eliab
ilit
y
an
d
ef
f
ec
tiv
en
ess
o
f
telem
ed
icin
e
an
d
r
em
o
te
m
o
n
ito
r
in
g
s
y
s
tem
s
,
m
ak
in
g
th
em
m
o
r
e
r
o
b
u
s
t
f
o
r
cr
itical,
r
ea
l
-
tim
e
h
ea
lth
ca
r
e
a
p
p
licatio
n
s
.
Fig
u
r
e
5
.
Mo
d
u
latio
n
i
n
d
ex
b
e
f
o
r
e
an
d
af
ter
o
p
tim
izatio
n
Fig
u
r
e
6
.
SNR
b
ef
o
r
e
an
d
A
f
ter
o
p
tim
izatio
n
Fig
u
r
e
7
s
h
o
ws
L
aten
cy
b
ef
o
r
e
an
d
af
ter
Op
tim
izatio
n
.
L
ate
n
cy
r
ed
u
ctio
n
p
o
s
t
-
o
p
tim
izati
o
n
en
s
u
r
es
th
e
tim
ely
d
eliv
er
y
o
f
cr
itical
h
ea
lth
ca
r
e
d
ata.
L
o
w
laten
cy
is
cr
u
cial
in
em
er
g
en
cy
aler
t
s
(
e.
g
.
,
h
ea
r
t
attac
k
d
etec
tio
n
)
,
wh
er
e
ev
en
m
illi
s
e
co
n
d
s
ca
n
d
ete
r
m
in
e
th
e
o
u
tc
o
m
e.
B
ef
o
r
e
o
p
tim
izatio
n
,
lat
en
cy
in
cr
ea
s
ed
d
u
e
to
in
ef
f
icien
t
d
ata
r
o
u
tin
g
,
n
etwo
r
k
c
o
n
g
esti
o
n
,
p
o
o
r
b
an
d
wid
th
m
a
n
ag
em
e
n
t,
an
d
u
n
o
p
tim
ized
s
ig
n
al
p
r
o
ce
s
s
in
g
alg
o
r
ith
m
s
.
T
h
ese
d
elay
s
co
m
p
r
o
m
i
s
e
th
e
s
p
ee
d
an
d
r
esp
o
n
s
iv
en
ess
o
f
h
ea
lth
ca
r
e
s
y
s
tem
s
,
esp
ec
ially
in
r
em
o
te
p
atien
t
m
o
n
ito
r
in
g
o
r
e
m
er
g
e
n
cy
ca
r
e.
Af
ter
ap
p
ly
i
n
g
W
OA,
laten
cy
is
s
ig
n
if
ican
tly
r
ed
u
ce
d
.
Data
p
ac
k
ets
r
ea
c
h
t
h
eir
d
esti
n
atio
n
f
aster
,
im
p
r
o
v
in
g
th
e
r
esp
o
n
s
iv
en
ess
o
f
th
e
s
y
s
tem
.
T
h
is
lead
s
to
m
o
r
e
tim
ely
aler
ts
,
f
aster
d
ata
a
n
aly
s
is
,
an
d
b
etter
clin
ical
d
ec
is
io
n
-
m
ak
in
g
.
Op
tim
ized
laten
cy
is
esp
ec
ially
cr
itical
in
ap
p
licati
o
n
s
s
u
ch
as
co
n
tin
u
o
u
s
E
C
G
m
o
n
ito
r
in
g
o
r
r
ea
l
-
tim
e
v
id
e
o
co
n
s
u
ltatio
n
s
.
T
h
u
s
,
W
alr
u
s
Op
tim
izatio
n
en
h
an
ce
s
th
e
o
v
er
all
ef
f
icien
cy
a
n
d
r
e
liab
ilit
y
o
f
h
ea
lth
ca
r
e
co
m
m
u
n
icatio
n
s
y
s
tem
s
b
y
en
s
u
r
in
g
lo
w
-
laten
c
y
p
e
r
f
o
r
m
an
ce
.
Fig
u
r
e
8
s
h
o
ws
th
e
T
h
r
o
u
g
h
p
u
t
b
ef
o
r
e
an
d
af
te
r
o
p
tim
izatio
n
.
T
h
r
o
u
g
h
p
u
t
en
h
an
ce
m
e
n
ts
r
ef
lect
th
e
s
y
s
tem
'
s
ab
ilit
y
to
h
an
d
le
m
o
r
e
d
ata
e
f
f
icien
tly
,
s
u
p
p
o
r
tin
g
m
u
ltip
le
u
s
er
s
o
r
s
en
s
o
r
s
i
n
r
ea
l
-
tim
e
with
o
u
t
d
eg
r
ad
atio
n
in
s
er
v
ice
q
u
al
ity
,
v
ital
in
h
o
s
p
ital
an
d
h
o
m
e
h
ea
lth
ca
r
e
m
o
n
ito
r
i
n
g
s
y
s
tem
s
.
B
ef
o
r
e
o
p
tim
izatio
n
,
t
h
r
o
u
g
h
p
u
t
is
o
f
ten
lim
ited
d
u
e
to
n
etwo
r
k
co
n
g
esti
o
n
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in
ef
f
icien
t
r
o
u
tin
g
,
s
u
b
o
p
tim
al
m
o
d
u
latio
n
,
an
d
p
o
o
r
b
a
n
d
wid
th
u
tili
za
tio
n
.
T
h
is
r
esu
lts
in
d
elay
ed
o
r
i
n
co
m
p
lete
d
ata
tr
an
s
m
is
s
io
n
,
af
f
ec
tin
g
th
e
q
u
ality
an
d
r
elia
b
ilit
y
o
f
telem
ed
icin
e
an
d
r
em
o
te
m
o
n
ito
r
in
g
s
er
v
ices.
T
h
e
W
OA
,
in
s
p
ir
ed
b
y
th
e
co
o
p
er
ativ
e
an
d
s
tr
ateg
ic
b
eh
av
io
r
s
o
f
walr
u
s
es,
is
a
m
eta
h
eu
r
is
tic
m
eth
o
d
th
at
ef
f
icien
tly
tu
n
es
n
etwo
r
k
p
ar
am
eter
s
to
m
ax
im
ize
p
er
f
o
r
m
an
ce
.
W
h
en
ap
p
lied
to
o
p
ti
m
ize
th
r
o
u
g
h
p
u
t,
W
OA
ad
ju
s
t
s
d
ata
tr
an
s
m
is
s
io
n
r
ates,
o
p
tim
izes
p
ac
k
et
r
o
u
tin
g
,
r
ed
u
ce
s
co
llis
io
n
s
,
an
d
p
r
io
r
itizes
cr
itical
h
ea
lth
d
ata.
I
t
iter
ativ
ely
s
ea
r
ch
es
f
o
r
o
p
tim
al
c
o
n
f
ig
u
r
atio
n
s
t
h
a
t
allo
w
th
e
m
ax
im
u
m
v
o
lu
m
e
o
f
d
ata
to
b
e
t
r
an
s
m
itted
with
m
in
im
al
d
elay
an
d
er
r
o
r
.
Af
ter
o
p
tim
izatio
n
wit
h
W
OA,
th
er
e
is
a
n
o
ticea
b
le
in
cr
ea
s
e
in
s
y
s
tem
th
r
o
u
g
h
p
u
t.
T
h
e
n
etwo
r
k
b
ec
o
m
es
ca
p
a
b
le
o
f
h
a
n
d
l
in
g
m
o
r
e
d
ata
tr
af
f
ic
ef
f
icien
tly
,
e
n
s
u
r
in
g
t
h
e
tim
ely
d
eliv
er
y
o
f
h
ea
lth
in
f
o
r
m
atio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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&
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2
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v
em
b
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20
25
:
6
6
7
-
6
7
7
674
T
h
is
im
p
r
o
v
em
en
t
is
cr
itical
in
s
ce
n
ar
io
s
in
v
o
lv
in
g
m
u
lt
ip
le
p
atien
ts
an
d
h
ig
h
-
f
r
e
q
u
e
n
cy
d
ata
s
tr
ea
m
s
.
Ov
er
all,
W
OA
en
h
an
ce
s
th
r
o
u
g
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p
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t
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lin
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s
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aster
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d
m
o
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e
r
eliab
le
co
m
m
u
n
icatio
n
in
h
ea
lth
ca
r
e
telem
etr
y
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d
telem
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icin
e
ap
p
licatio
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s
.
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ab
les
2
an
d
3
illu
s
tr
ate
th
e
Per
f
o
r
m
an
ce
Me
tr
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f
th
e
AI
m
eth
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d
s
.
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ab
les
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an
d
5
r
ev
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l
th
e
ad
v
a
n
tag
es
o
f
co
m
b
in
in
g
AI
m
eth
o
d
s
with
th
e
W
OA
.
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OA
-
AN
N
ac
h
iev
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a
n
SNR
o
f
3
1
d
B
,
W
OA
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SVM
r
ea
ch
ed
3
2
d
B
,
an
d
all
h
y
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r
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o
d
els
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tain
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a
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wid
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ab
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z,
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ef
lectin
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h
a
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n
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a
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c
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m
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t
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8
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-
6
,
w
h
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e
l
a
te
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c
y
v
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d
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p
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c
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.
Fig
u
r
e
7
.
L
ate
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b
e
f
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a
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d
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f
ter
o
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Fig
u
r
e
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.
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h
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t b
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Evaluation Warning : The document was created with Spire.PDF for Python.
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cr
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allen
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k
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in
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o
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i
n
tr
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d
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ce
d
in
th
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wo
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k
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th
e
ap
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licatio
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f
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a
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atu
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s
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o
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ate
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ce
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etr
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wh
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u
cial
f
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im
e
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s
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o
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with
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ith
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s
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f
u
r
th
er
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y
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s
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ec
t
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al
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tili
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tio
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r
ed
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ce
d
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R
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all
wh
ile
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t
ain
in
g
o
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p
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e
r
g
y
ef
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.
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h
e
h
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h
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er
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f
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r
ec
o
r
d
ed
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2
2
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its
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in
d
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th
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p
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e
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lth
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e
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e
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y
s
tem
d
em
o
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s
tr
ated
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ess
in
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m
u
ltip
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d
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s
tr
ea
m
s
co
n
cu
r
r
en
tly
,
a
c
r
itical
f
ea
tu
r
e
f
o
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m
u
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-
p
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o
r
h
o
s
p
ital
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wid
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lo
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en
ts
.
T
h
e
in
tellig
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t
allo
ca
tio
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o
f
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s
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n
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ten
t
ev
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in
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n
am
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n
etwo
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co
n
d
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s
.
Fin
ally
,
th
e
p
r
o
p
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s
ed
s
y
s
tem
s
u
cc
ess
f
u
lly
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teg
r
ates
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m
m
u
n
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n
,
d
ata
p
r
o
ce
s
s
in
g
,
a
n
d
o
p
tim
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tio
n
in
a
u
n
if
ied
f
r
am
ewo
r
k
ta
ilo
r
ed
f
o
r
m
o
d
er
n
h
ea
lth
ca
r
e
n
ee
d
s
.
I
ts
a
b
ilit
y
to
d
eliv
er
ac
cu
r
ate,
lo
w
-
laten
c
y
,
an
d
en
er
g
y
-
ef
f
icien
t
p
er
f
o
r
m
an
ce
m
ak
es
it
h
ig
h
ly
s
u
itab
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f
o
r
r
ea
l
-
wo
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ld
d
ep
lo
y
m
e
n
t.
T
h
e
in
c
o
r
p
o
r
ati
o
n
o
f
W
OA
as
an
o
p
tim
iza
tio
n
b
ac
k
b
o
n
e
en
h
an
ce
s
n
o
t
o
n
ly
th
e
s
y
s
tem
'
s
o
p
er
atio
n
al
e
f
f
icien
cy
b
u
t
also
its
ad
ap
tab
ilit
y
to
ev
o
l
v
in
g
t
ec
h
n
o
l
o
g
ical
an
d
h
ea
lt
h
ca
r
e
d
em
an
d
s
.
T
h
is
wo
r
k
lay
s
a
s
o
lid
f
o
u
n
d
atio
n
f
o
r
f
u
t
u
r
e
ad
v
a
n
ce
m
en
ts
in
s
m
ar
t
h
e
alth
ca
r
e
s
y
s
tem
s
,
o
f
f
er
in
g
a
b
lu
ep
r
in
t
f
o
r
s
ca
lab
le,
in
tellig
en
t,
an
d
s
u
s
tain
ab
le
tel
em
ed
icin
e
an
d
telem
etr
y
in
f
r
a
s
tr
u
ctu
r
e.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
Au
th
o
r
s
s
tate
n
o
f
u
n
d
in
g
in
v
o
lv
ed
.
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
Data
av
ailab
ilit
y
is
n
o
t
ap
p
li
ca
b
le
to
th
is
p
ap
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n
o
n
e
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cr
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ted
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ti
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)
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t
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Un
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Nig
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ria.
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c
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l:
m
o
sh
o
o
d
sh
it
tu
@g
m
a
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l.
c
o
m
.
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