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o
n
l
y
e
m
p
lo
y
ed
f
o
r
5
G
ap
p
licatio
n
s
[
7
]
.
T
h
ese
s
tr
etch
f
r
o
m
t
h
e
C
-
b
an
d
to
t
h
e
u
ltra
h
i
g
h
f
r
eq
u
e
n
c
y
(
UHF
)
b
an
d
s
a
n
d
ar
e
p
ar
t
o
f
t
h
e
m
id
-
b
a
n
d
s
p
ec
tr
u
m
.
C
o
v
er
ag
e
a
n
d
th
r
o
u
g
h
p
u
t
in
5
G
n
et
w
o
r
k
s
ar
e
s
e
v
er
el
y
h
in
d
er
ed
b
y
i
n
ter
f
er
en
ce
in
t
h
is
f
r
eq
u
e
n
c
y
r
an
g
e.
I
t
s
tr
ik
es
a
m
id
d
le
g
r
o
u
n
d
b
et
w
ee
n
th
e
lar
g
er
d
ata
s
p
ee
d
s
an
d
n
ar
r
o
w
e
r
co
v
er
a
g
e
av
aila
b
le
in
th
e
m
m
-
w
av
e
f
r
eq
u
e
n
c
ies
an
d
th
e
lo
w
er
f
r
eq
u
en
c
y
b
an
d
s
(
s
u
b
-
6
GHz
)
[
8
]
.
T
h
e
n
ex
t
g
e
n
er
atio
n
(
5
G)
o
f
w
ir
eless
co
m
m
u
n
icatio
n
tec
h
n
o
lo
g
y
,
5
G
n
e
w
r
ad
io
(
5
G
N
R
)
is
th
e
b
ac
k
b
o
n
e
o
f
5
G
n
et
w
o
r
k
s
.
T
o
a
c
c
o
m
m
o
d
a
t
e
t
h
e
g
r
o
w
in
g
n
e
e
d
f
o
r
f
as
t
er
d
a
t
a
t
r
a
n
s
f
e
r
r
a
t
es
,
r
e
d
u
c
e
d
n
e
tw
o
r
k
la
t
en
cy
,
an
d
e
n
h
an
c
e
d
o
v
e
r
a
l
l
n
etw
o
r
k
p
e
r
f
o
r
m
an
c
e
,
it
in
c
lu
d
es
s
ev
e
r
al
e
n
h
an
c
em
en
ts
o
v
e
r
i
ts
p
r
e
d
e
ce
s
s
o
r
s
[
9
]
.
T
h
e
N
7
7
f
r
e
q
u
en
cy
b
an
d
is
i
d
e
a
l
f
o
r
d
e
l
iv
e
r
in
g
5
G
s
e
r
v
i
c
es
in
u
r
b
an
a
n
d
d
en
s
e
ly
p
o
p
u
l
a
te
d
a
r
e
as
,
w
h
e
r
e
e
x
t
en
s
i
v
e
c
o
v
e
r
ag
e
an
d
c
a
p
a
ci
ty
a
r
e
r
e
q
u
i
r
e
d
t
o
m
e
e
t
th
e
r
i
s
in
g
d
em
an
d
f
o
r
f
a
s
t
,
d
e
p
e
n
d
a
b
l
e
w
i
r
e
l
es
s
i
n
t
e
r
n
et
[
1
0
]
.
I
n
T
a
b
l
e
1
,
we
h
a
v
e
p
r
e
s
e
n
t
e
d
a
c
o
m
p
r
e
h
e
n
s
i
v
e
c
o
m
p
a
r
i
s
o
n
o
f
v
a
r
i
o
u
s
p
r
o
c
e
s
s
e
s
r
u
n
n
i
n
g
s
im
u
l
t
a
n
e
o
u
s
ly
.
Pr
e
v
i
o
u
s
l
i
t
e
r
a
t
u
r
e
r
e
p
o
r
t
s
i
n
d
i
c
a
t
e
d
m
i
n
im
u
m
r
e
f
l
e
c
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
o
f
-
2
7
.
5
d
B
,
-
2
0
d
B
,
-
3
4
.
9
8
d
B
,
-
2
9
.
1
7
d
B
,
-
3
7
.
4
2
d
B
,
-
1
9
d
B
,
a
n
d
-
3
1
.
2
d
B
[
1
1
]
-
[
1
8
]
.
H
o
w
e
v
e
r
,
u
p
o
n
c
o
n
d
u
c
t
i
n
g
,
c
o
m
p
u
t
e
r
s
i
m
u
l
a
t
i
o
n
t
e
c
h
n
o
l
o
g
y
(
C
S
T
)
s
i
m
u
l
a
t
i
o
n
s
f
o
r
t
h
e
s
u
g
g
e
s
t
e
d
a
n
t
e
n
n
a
,
w
e
d
i
s
c
o
v
e
r
e
d
t
h
a
t
t
h
e
m
i
n
im
u
m
r
e
f
l
e
c
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
w
e
r
e
m
e
a
s
u
r
e
d
a
t
-
2
8
.
1
3
2
d
B
,
-
3
2
.
1
1
d
B
,
a
n
d
-
2
8
.
6
0
d
B
a
t
t
h
e
r
e
s
o
n
a
n
t
f
r
e
q
u
e
n
c
i
e
s
o
f
2
.
4
G
H
z
,
3
.
5
G
H
z
,
a
n
d
3
.
7
G
H
z
,
r
e
s
p
e
c
t
i
v
e
l
y
.
A
d
d
i
t
i
o
n
a
l
l
y
,
b
a
s
e
d
o
n
t
h
e
C
S
T
s
t
u
d
y
,
w
e
d
e
t
e
r
m
i
n
e
d
t
h
a
t
t
h
e
p
r
o
p
o
s
e
d
d
e
s
i
g
n
d
e
m
o
n
s
t
r
a
t
e
s
t
h
e
h
i
g
h
e
s
t
g
a
i
n
o
f
6
.
5
6
d
B
,
s
u
r
p
a
s
s
i
n
g
t
h
e
g
a
i
n
s
a
c
h
i
e
v
e
d
i
n
t
h
e
p
r
e
v
i
o
u
s
l
y
r
e
f
e
r
e
n
c
e
d
s
t
u
d
i
e
s
.
F
u
r
t
h
e
r
m
o
r
e
,
t
h
e
r
e
l
e
v
a
n
t
a
r
t
i
c
l
e
s
[
1
4
]
-
[
1
7
]
d
e
m
o
n
s
t
r
a
t
e
r
a
d
i
a
t
i
o
n
e
f
f
i
c
i
e
n
c
i
e
s
o
f
7
3
%
,
8
0
-
9
6
%
,
7
7
.
4
4
%
,
a
n
d
8
0
%
.
H
o
w
e
v
e
r
,
o
u
r
s
u
g
g
e
s
t
e
d
m
i
c
r
o
s
t
r
i
p
p
a
t
c
h
a
n
t
e
n
n
a
r
e
c
o
r
d
e
d
r
a
d
i
a
t
i
o
n
e
f
f
i
c
i
e
n
c
i
e
s
o
f
8
4
.
1
5
%
,
8
4
.
2
7
%
,
a
n
d
8
3
.
7
9
%
i
n
C
S
T
.
I
t
’
s
i
m
p
o
r
t
a
n
t
t
o
n
o
t
e
t
h
a
t
t
h
e
r
e
f
e
r
e
n
c
e
s
d
o
n
o
t
c
o
v
e
r
t
r
i
a
l
s
i
n
v
o
l
v
i
n
g
m
a
c
h
i
n
e
-
l
e
a
r
n
i
n
g
t
e
c
h
n
i
q
u
e
s
,
e
v
e
n
t
h
o
u
g
h
t
h
e
s
e
t
e
c
h
n
i
q
u
e
s
a
r
e
e
x
t
e
n
s
i
v
e
l
y
u
s
e
d
i
n
d
e
s
i
g
n
.
F
u
r
t
h
e
r
m
o
r
e
,
w
e
i
n
te
g
r
a
t
e
d
t
h
e
r
e
s
i
s
t
o
r
,
i
n
d
u
c
t
o
r
,
a
n
d
c
a
p
a
c
i
t
o
r
(
R
L
C
)
eq
u
i
v
a
l
e
n
t
c
i
r
c
u
i
t
i
n
t
o
t
h
e
s
u
g
g
e
s
t
e
d
a
n
t
e
n
n
a
,
a
f
e
a
t
u
r
e
n
o
t
p
r
e
v
i
o
u
s
ly
d
i
s
c
u
s
s
e
d
i
n
t
h
e
c
i
t
e
d
l
i
t
e
r
a
t
u
r
e
.
T
ab
le
1
.
P
er
f
o
r
m
a
n
ce
co
m
p
ar
i
s
o
n
s
w
i
th
t
h
e
p
u
b
lis
h
ed
s
tate
o
f
th
e
ar
t
P
a
r
a
me
t
e
r
[
1
1
]
[
1
3
]
[
1
4
]
[
1
2
]
[
1
5
]
[
1
6
]
[
1
7
]
[
1
8
]
T
h
i
s
w
o
r
k
O
p
e
r
a
t
i
n
g
f
r
e
q
u
e
n
c
y
(
G
H
z
)
2
.
1
,
3
.
3
,
4
.
1
3
.
7
3
,
6
.
7
3
,
9
.
5
6
3
.
3
,
3
.
8
1
.
8
,
3
.
5
,
5
.
4
3
.
7
5
,
5
.
1
7
2
.
4
5
,
3
.
7
3
_
3
.
5
4
,
6
.
7
2
2
.
4
7
,
3
.
5
,
3
.
7
5
R
e
t
u
r
n
l
o
ss
(
d
B
)
-
2
7
.
5
,
-
2
0
.
5
,
-
2
4
.
1
-
1
1
.
8
1
-
2
0
.
1
5
-
1
3
.
0
3
−
3
1
.
1
,
−
3
4
.
9
8
_
-
1
3
.
7
,
-
2
9
.
1
7
-
3
5
.
4
7
,
-
3
7
.
4
2
-
19
-
2
1
.
4
,
-
3
1
.
2
-
2
8
.
1
3
-
3
2
.
1
1
,
-
2
8
.
6
3
B
a
n
d
w
i
d
t
h
(
M
H
z
)
2
0
0
,
1
4
0
,
2
0
0
1
0
,
2
9
,
19
7
2
0
7
2
0
1
4
0
1
8
0
2
0
0
4
0
0
7
0
0
_
8
6
7
_
1
8
7
.
5
,
3
8
7
.
6
P
e
a
k
g
a
i
n
(
d
B
i
)
4
.
5
,
6
.
1
,
4
.
3
2
.
8
,
2
.
9
5
,
3
.
2
2
.
5
2
.
3
4
,
5
.
2
,
1
.
4
2
4
.
3
5
4
.
7
4
,
3
.
6
2
6
.
2
1
4
.
7
8
,
4
.
6
5
6
.
5
6
R
a
d
i
a
t
i
o
n
e
f
f
i
c
i
e
n
c
y
%
_
_
_
7
3
%,
6
8
%,
5
9
%
8
0
%
7
7
.
4
4
%
,
5
8
.
9
6
%
8
0
%
_
8
4
.
1
%,
8
4
.
2
%,
8
3
.
7
%
S
u
b
s
t
r
a
t
e
m
a
t
e
r
i
a
l
R
o
g
e
r
R
T
5
8
8
0
F
R
4
FR
-
4
F
R
4
R
T
D
u
r
o
i
d
5
8
8
0
R
o
g
e
r
s
X
T
8
1
0
0
FR
-
4
FR
-
4
F
R
4
R
L
C
e
q
u
i
v
a
l
e
n
t
C
K
T
No
No
No
No
No
No
No
No
Y
es
M
a
c
h
i
n
e
l
e
a
r
n
i
n
g
(
M
L
)
a
p
p
r
o
a
c
h
No
No
No
No
No
No
No
No
Y
es
2.
M
E
T
H
O
D
T
h
e
p
r
o
p
o
s
ed
an
ten
n
a
h
as
b
e
en
d
esig
n
ed
an
d
s
i
m
u
lated
u
s
in
g
C
ST
.
T
h
is
tr
ib
an
d
m
icr
o
s
tr
ip
p
atch
an
ten
n
a
i
s
d
esig
n
ed
to
w
o
r
k
a
t
th
r
ee
d
if
f
er
en
t
f
r
eq
u
e
n
cies
:
2
.
4
GHz
,
3
.
5
GHz
,
an
d
3
.
7
G
Hz.
I
n
Fig
u
r
e
1
(
a)
,
w
e
s
ee
t
h
e
p
r
o
p
o
s
ed
an
ten
n
a
’
s
f
r
o
n
tal
g
eo
m
etr
y
.
T
h
e
h
o
r
izo
n
tal
s
lo
t,
w
h
ic
h
i
n
cl
u
d
es
s
lo
ts
1
,
2
,
an
d
3
,
h
a
s
d
i
m
en
s
io
n
s
o
f
3
.
5
5
m
m
b
y
3
9
.
1
1
m
m
.
Slo
t 2
i
s
u
s
ed
b
et
w
ee
n
s
lo
ts
1
an
d
3
,
an
d
s
lo
t 1
i
s
u
t
il
ized
in
th
e
to
p
lef
t
co
r
n
er
.
Slo
t
3
is
u
s
ed
at
th
e
b
o
tto
m
lef
t.
T
h
er
e
is
a
1
5
.
1
5
m
m
g
ap
b
et
w
ee
n
s
lo
ts
1
an
d
2
,
an
d
an
1
1
.
8
5
m
m
g
ap
b
et
w
ee
n
s
lo
ts
2
a
n
d
3
.
T
h
e
v
er
tical
s
lo
t,
w
h
ic
h
i
n
cl
u
d
es
s
lo
t
s
4
,
5
,
an
d
6
,
h
as
th
e
d
i
m
en
s
io
n
s
o
f
3
3
.
3
2
×
2
.
3
2
m
m
.
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h
e
d
is
ta
n
ce
b
et
w
ee
n
s
lo
t
s
4
an
d
6
i
s
8
.
6
8
m
m
,
an
d
t
h
e
s
lo
t
in
t
h
e
m
id
d
l
e,
s
lo
t
5
,
is
u
s
ed
at
th
e
to
p
r
ig
h
t.
Fi
g
u
r
e
1
(
b
)
s
h
o
w
s
t
h
e
p
atch
i
n
v
er
ted
a
n
d
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s
e
d
as
a
g
r
o
u
n
d
s
lo
t;
it
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ic
k
n
e
s
s
i
s
0
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0
2
m
m
,
a
n
d
it
is
co
n
s
tr
u
cted
o
f
co
p
p
er
an
n
ea
led
m
a
ter
ial.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
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elec
o
m
m
u
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Fig
u
r
e
1
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Geo
m
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tr
y
o
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p
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ed
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(
a)
f
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n
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d
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b
ac
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0
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.
5
7
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L
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.
3
2
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f
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4
5
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3
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s
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3.
RE
SU
L
T
ANAL
YSI
S
An
a
n
ten
n
a
’
s
p
ar
tic
u
lar
s
p
ec
if
icatio
n
s
e
s
s
e
n
tiall
y
d
ef
in
e
i
ts
o
p
er
atio
n
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an
g
es
a
n
d
p
er
f
o
r
m
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ce
ch
ar
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ter
is
tic
s
.
I
n
th
e
f
o
llo
w
i
n
g
a
n
al
y
s
is
,
w
e
th
o
r
o
u
g
h
l
y
e
x
a
m
in
e
t
h
ese
cr
u
cial
f
ac
to
r
s
,
em
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h
asizi
n
g
th
eir
i
m
p
o
r
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ce
i
n
d
eter
m
i
n
in
g
t
h
e
an
ten
n
a
’
s
f
u
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ctio
n
i
n
g
a
n
d
ef
f
ec
tiv
e
n
ess
at
s
p
ec
if
ic
f
r
eq
u
e
n
c
ies.
3
.
1
.
Ref
lec
t
io
n
c
o
ef
f
icient
R
ef
lec
tio
n
co
e
f
f
icien
t
i
s
o
n
e
o
f
t
h
e
m
o
s
t
i
m
p
o
r
tan
t
cr
iter
ia
to
co
n
s
id
er
w
h
e
n
a
n
a
l
y
zi
n
g
th
e
p
er
f
o
r
m
a
n
ce
o
f
an
an
te
n
n
a
s
i
n
ce
it
d
eter
m
i
n
e
s
th
e
s
tr
en
g
t
h
o
f
th
e
s
ig
n
al
b
y
co
m
p
ar
i
n
g
t
h
e
to
tal
a
m
o
u
n
t
o
f
p
o
w
er
th
at
is
r
ec
eiv
ed
b
y
th
e
an
ten
n
a
to
th
e
to
tal
am
o
u
n
t
o
f
p
o
w
er
th
at
is
r
ef
lec
ted
f
r
o
m
t
h
e
an
te
n
n
a.
T
o
ac
h
iev
e
t
h
e
ap
p
r
o
p
r
iate
lev
el
o
f
p
er
f
o
r
m
a
n
ce
,
th
e
v
al
u
e
o
f
th
e
r
et
u
r
n
lo
s
s
s
h
o
u
ld
b
e
lo
w
er
th
a
n
-
1
0
d
B
.
Fig
u
r
e
2
d
ep
icts
th
e
d
ata
th
at
s
h
o
w
s
t
h
e
f
r
eq
u
e
n
cie
s
at
w
h
ic
h
th
e
r
etu
r
n
lo
s
s
i
s
at
its
lo
w
es
t.
T
h
ese
f
r
eq
u
en
cie
s
ar
e
2
.
4
7
GHz
(
-
2
8
.
1
3
2
d
B
)
,
3
.
5
GHz
(
-
3
2
.
1
1
1
d
B
)
,
an
d
3
.
7
5
GHz
(
-
2
8
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6
0
3
d
B
)
d
e
m
o
n
s
tr
ates
t
h
at
th
e
s
u
g
g
e
s
ted
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te
n
n
a
is
s
u
itab
le
f
o
r
4
G/L
T
E
an
d
m
id
-
b
an
d
5
G
(
n
7
7
an
d
n
7
8
)
a
p
p
licatio
n
s
,
s
in
ce
th
e
s
i
m
u
lated
an
ten
n
a
ca
n
b
e
o
p
er
ated
at
th
r
ee
d
if
f
er
e
n
t f
r
eq
u
e
n
cie
s
.
Fig
u
r
e
2
.
Si
m
u
lated
r
ef
lectio
n
co
ef
f
icie
n
t o
f
th
e
p
r
o
p
o
s
ed
an
ten
n
a
3.
2
.
G
a
in a
nd
ef
f
iciency
Gain
a
n
d
ef
f
icie
n
c
y
ar
e
t
w
o
k
e
y
i
n
d
icato
r
s
o
f
a
n
an
ten
n
a
’
s
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u
alit
y
.
T
h
e
ter
m
“
g
a
in
”
r
e
f
er
s
to
th
e
a
m
p
li
f
icatio
n
o
f
t
h
e
p
r
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ar
y
b
ea
m
’
s
o
u
tp
u
t
p
o
w
er
[
1
9
]
.
T
o
d
eter
m
i
n
e
a
n
an
te
n
n
a
’
s
e
f
f
i
cien
c
y
,
w
e
co
m
p
ar
e
th
e
p
o
w
er
it e
m
its
o
r
r
ec
eiv
e
s
to
th
e
p
o
w
er
it u
s
es
[
2
0
]
.
T
h
e
an
ten
n
a
w
e
h
av
e
p
r
o
p
o
s
ed
h
as
s
h
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m
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r
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v
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an
ce
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ter
m
s
o
f
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ai
n
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d
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f
icien
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y
.
T
h
r
o
u
g
h
o
u
t o
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r
s
i
m
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la
ti
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g
,
we
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o
b
s
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ed
t
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f
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d
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to
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5
6
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B
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w
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ile
its
e
f
f
icien
c
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s
p
an
s
f
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o
m
7
9
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1
6
%
to
9
6
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6
6
%.
T
h
ese
r
es
u
lts
h
av
e
b
ee
n
v
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u
all
y
r
ep
r
ese
n
te
d
in
F
ig
u
r
e
3
.
I
t
’
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
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o
m
p
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t E
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n
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,
Vo
l.
23
,
No
.
2
,
A
p
r
il
20
25
:
5
4
3
-
552
546
w
o
r
th
n
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ti
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t
h
at
t
h
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g
ain
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s
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er
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etr
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f
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ct
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6
d
B
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p
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ticu
lar
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esp
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f
o
r
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lo
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er
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f
r
eq
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en
c
y
a
n
te
n
n
a.
Fu
r
t
h
er
m
o
r
e,
th
e
e
f
f
icie
n
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y
o
f
9
6
.
6
6
%
is
also
r
e
m
ar
k
ab
le,
esp
ec
iall
y
w
i
th
in
t
h
e
co
n
tex
t
o
f
lo
w
-
f
r
eq
u
e
n
c
y
an
ten
n
a
s
.
Fig
u
r
e
3
.
Si
m
u
lated
g
ai
n
a
n
d
ef
f
icien
c
y
o
f
t
h
e
p
r
o
p
o
s
ed
an
ten
n
a
3.
3
.
Ra
dia
t
io
n pa
t
t
er
n
Fig
u
r
e
4
is
a
r
ep
r
esen
tatio
n
o
f
th
e
f
ield
s
(
b
o
th
elec
tr
ic
a
n
d
m
ag
n
etic)
at
a
n
an
g
le
o
f
0
d
e
g
r
ee
s
an
d
9
0
d
eg
r
ee
s
[
2
1
]
.
T
h
e
m
a
g
n
it
u
d
es
o
f
th
e
m
ag
n
etic
f
ield
ar
e
-
3
3
.
3
d
B
A
/
m
at
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eg
r
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s
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d
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8
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r
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f
ield
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1
8
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2
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B
V/m
at
an
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f
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d
eg
r
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s
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d
1
9
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7
d
B
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d
eg
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5
d
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f
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r
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7
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.
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h
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lf
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r
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.
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9
0
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eg
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e
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e
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2
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n
d
th
e
3
d
B
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g
u
lar
b
ea
m
wid
th
is
6
6
.
9
.
Fo
r
a
r
eso
n
an
t
f
r
eq
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e
n
c
y
o
f
3
.
7
GHz
,
th
e
m
a
g
n
itu
d
es
o
f
t
h
e
e
l
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tr
ic
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ield
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e
1
6
.
0
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eg
r
ee
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n
d
1
7
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2
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9
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eg
r
ee
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h
er
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s
th
e
m
ag
n
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u
d
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o
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th
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m
ag
n
etic
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ield
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e
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3
5
.
5
d
B
A
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at
0
d
eg
r
ee
s
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d
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3
4
.
3
d
B
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at
9
0
d
eg
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ee
s
.
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h
e
s
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e
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o
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e
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3
d
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d
th
e
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alf
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o
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er
b
ea
m
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eg
r
ee
s
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8
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6
d
eg
r
ee
s
.
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m
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ar
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n
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9
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eg
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ee
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e
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5
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e
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B
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lar
b
ea
m
w
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t
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is
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5
.
Fig
u
r
e
4
.
Si
m
u
lated
r
ad
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n
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atter
n
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o
f
t
h
e
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r
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p
o
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4
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1
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[
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ets
[
2
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4
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3
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Dec
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re
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[
2
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4
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4
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2
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]
.
4
.
5
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Ra
ns
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o
m
s
a
m
p
le
co
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n
s
u
s
(
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is
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ter
ativ
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tech
n
iq
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e
u
s
ed
f
o
r
r
o
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u
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ar
tic
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in
th
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esen
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f
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tlier
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d
n
o
is
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d
ata.
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o
esti
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ate
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o
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el
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ar
am
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ter
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w
h
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n
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r
in
g
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r
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n
w
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g
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ti
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g
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t
lier
s
,
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S
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ca
n
b
e
ap
p
lied
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w
id
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ar
iet
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o
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r
eg
r
es
s
io
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tas
k
s
.
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h
en
r
o
b
u
s
t
p
ar
a
m
eter
esti
m
ate
is
n
ee
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ed
,
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ANS
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is
o
f
te
n
e
m
p
lo
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ed
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n
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m
p
u
ter
v
is
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n
an
d
i
m
ag
e
p
r
o
ce
s
s
i
n
g
[
2
7
]
.
4
.
6
.
P
er
f
o
rm
a
nce
m
ea
s
ure
ment
m
et
ric
s
E
r
r
o
r
is
th
e
m
o
s
t
t
y
p
ical
r
eg
r
ess
io
n
s
u
cc
e
s
s
in
d
icato
r
.
E
ac
h
s
tr
ateg
y
w
a
s
co
m
p
ar
ed
u
s
in
g
s
tatis
tical
m
ar
k
er
s
.
T
h
e
alg
o
r
ith
m
s
’
p
er
f
o
r
m
a
n
ce
w
a
s
ev
al
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ated
u
s
in
g
s
ev
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al
s
ta
tis
tica
l
m
etr
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a
n
d
co
m
p
ar
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.
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e
e
m
p
lo
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ed
f
i
v
e
s
tat
is
tic
s
to
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alu
ate
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r
m
o
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els
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p
r
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ictio
n
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er
f
o
r
m
a
n
ce
:
r
o
o
t
m
ea
n
s
q
u
ar
ed
er
r
o
r
(
R
MSE
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,
R
2
,
v
ar
ian
ce
s
co
r
e,
an
d
m
ea
n
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
[
2
8
]
.
T
h
e
MA
E
s
tatis
t
ic
m
ea
s
u
r
es
h
o
w
f
ar
o
f
f
th
e
p
r
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icted
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alu
e
s
ar
e
f
r
o
m
th
e
ac
t
u
al
v
alu
es
i
n
a
r
eg
r
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n
p
r
o
b
lem
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lo
w
MA
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s
u
g
g
est
s
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o
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d
d
ep
en
d
e
n
t
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r
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c
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.
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A
E
i
s
v
is
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all
y
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o
w
n
in
(
1
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=
1
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|
=
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1
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er
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is
n
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m
b
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r
s
a
n
d
|
Pi
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Oi
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is
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te
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s
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u
ar
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r
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r
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m
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t
t
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m
p
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h
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lo
s
s
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er
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b
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i
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g
th
e
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ce
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et
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n
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er
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ed
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d
an
ticip
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alu
e
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o
v
er
all
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ata
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o
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ts
.
In
(
2
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s
h
o
w
s
th
e
in
ten
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ed
m
ea
n
s
q
u
ar
e
er
r
o
r
(
MSE
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f
o
r
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u
latio
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.
=
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̂
−
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2
=
1
(
2
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a
f
r
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n
t
s
ta
tis
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ed
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e
s
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io
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al
y
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i
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ea
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u
r
e
p
r
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m
o
d
el
ac
cu
r
ac
y
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t
esti
m
ate
s
th
e
t
y
p
ical
m
a
g
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itu
d
e
o
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er
r
o
r
s
o
r
r
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et
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a
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ticip
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ataset.
=
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On
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ell
t
h
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m
o
d
el
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i
n
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ep
en
d
en
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e
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d
en
t
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eg
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m
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el
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s
u
all
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o
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e
m
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el
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s
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t
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ep
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s
v
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iatio
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h
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p
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h
e
m
o
d
el
f
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ll
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ep
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en
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ar
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p
er
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−
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−
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(
4
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Evaluation Warning : The document was created with Spire.PDF for Python.
T
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elec
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“
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atch
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Resul
t
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ly
s
is
M
/L
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ab
le
2
s
u
m
m
ar
ize
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co
m
p
ar
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t
h
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p
r
ed
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ab
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o
f
f
iv
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r
eg
r
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n
m
o
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el
s
f
o
r
d
ir
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tio
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alit
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i
v
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a
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u
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e
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c
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,
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it
h
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ea
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et
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est
p
er
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o
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m
a
n
ce
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s
s
ee
n
in
LR
,
w
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th
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n
R
2
o
f
9
8
.
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v
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ian
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o
f
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0
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lt
s
f
r
o
m
s
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m
o
d
els
ar
e
co
m
p
ar
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in
Fig
u
r
e
7
,
w
h
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e
Fig
u
r
e
7
(
a)
s
h
o
w
s
t
h
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er
r
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r
m
atr
ic
b
ar
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t
f
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li
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(
g
ai
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d
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u
r
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(
b
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s
h
o
w
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cu
r
ac
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co
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p
ar
ati
v
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ar
ch
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t
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lin
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r
r
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ir
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s
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ap
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Fi
g
u
r
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R
w
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tili
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d
f
o
r
f
o
r
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asti
n
g
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u
r
p
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ab
le
2
.
Gain
p
r
ed
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p
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f
o
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m
an
ce
A
l
g
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r
i
t
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ms
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(
%)
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S
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(
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M
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(
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-
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q
u
a
r
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(
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V
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r
sco
r
e
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1
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Fig
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r
e
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Evaluation Warning : The document was created with Spire.PDF for Python.
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A.
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.
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1
2
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.
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k
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lan
i3
3
-
4
5
4
3
@d
i
u
.
e
d
u
.
b
d
.
Lito
n
Cha
n
d
r
a
Pa
u
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h
o
ld
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th
e
p
o
siti
o
n
o
f
A
ss
istan
t
P
r
o
f
e
ss
o
r
i
n
t
h
e
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e
c
tri
c
a
l,
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e
c
tro
n
ic,
a
n
d
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m
m
u
n
ica
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g
in
e
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rin
g
d
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p
a
rtm
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n
t
a
t
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a
b
n
a
Un
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f
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h
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UST
).
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c
o
m
p
lete
d
h
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a
ste
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s
d
e
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re
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in
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m
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g
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t
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h
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h
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f
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g
in
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rin
g
a
n
d
T
e
c
h
n
o
lo
g
y
(RUET
)
in
2
0
1
2
a
n
d
2
0
1
5
,
re
s
p
e
c
ti
v
e
l
y
.
Du
rin
g
h
is
a
c
a
d
e
m
ic
jo
u
r
n
e
y
,
h
e
a
c
ti
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l
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p
a
rti
c
ip
a
ted
in
v
a
rio
u
s
n
o
n
-
p
ro
f
it
so
c
ial
w
e
l
fa
re
o
rg
a
n
iza
ti
o
n
s,
m
a
k
in
g
sig
n
if
ica
n
t
c
o
n
tri
b
u
ti
o
n
s
t
o
t
h
e
ir
e
n
d
e
a
v
o
rs.
Cu
rre
n
tl
y
,
h
e
is
a
c
ti
n
g
a
s
a
n
a
d
v
iso
r
f
o
r
t
h
e
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UST
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tu
d
e
n
t
Bra
n
c
h
,
a
n
a
d
v
iso
r
f
o
r
th
e
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A
P
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S
B
Ch
a
p
ter,
a
n
d
a
stu
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t
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it
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rd
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n
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o
r
th
e
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EE
A
P
S
-
M
TT
S
BD
Jo
in
t
Ch
a
p
ter.
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re
se
a
rc
h
in
tere
sts
a
re
RF
IC,
M
IM
O,
m
a
c
h
in
e
lea
rn
in
g
,
b
i
o
-
e
lec
tro
m
a
g
n
e
ti
c
s,
m
icro
wa
v
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tec
h
n
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l
o
g
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a
n
ten
n
a
s,
p
h
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se
d
a
rra
y
s,
m
m
Wav
e
,
m
e
t
a
m
a
teria
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a
b
so
rb
e
r,
m
e
tas
u
r
f
a
c
e
s,
a
n
d
w
irele
ss
se
n
so
rs.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
li
to
n
p
a
u
lete
@g
m
a
il
.
c
o
m
.
Ra
je
r
m
a
n
i
Th
in
a
k
a
r
a
n
h
o
ld
s
a
Do
c
t
o
r
d
e
g
re
e
f
ro
m
Un
iv
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rsiti
T
e
k
n
o
lo
g
i
M
a
lay
si
a
(UT
M
),
M
a
la
y
si
a
in
2
0
1
9
.
S
h
e
a
lso
re
c
e
iv
e
d
h
e
r
M
a
ste
r
in
I
T
f
ro
m
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iv
e
r
siti
Ke
b
a
n
g
sa
a
n
M
a
la
y
sia
(UK
M
)
a
n
d
Ba
c
h
e
lo
r
in
S
c
ien
c
e
(Co
m
p
u
ter
S
c
ien
c
e
)
f
ro
m
U
T
M
in
2
0
1
2
a
n
d
1
9
9
5
,
re
sp
e
c
ti
v
e
l
y
.
S
h
e
is
c
u
rre
n
tl
y
a
se
n
io
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lec
tu
re
r
a
t
F
a
c
u
lt
y
o
f
Da
ta
S
c
ien
c
e
a
n
d
In
f
o
rm
a
ti
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n
T
e
c
h
n
o
lo
g
y
in
INT
I
In
tern
a
ti
o
n
a
l
Un
iv
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rsit
y
,
Ne
g
e
ri
S
e
m
b
il
a
n
,
M
a
la
y
sia
.
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r
re
s
e
a
rc
h
in
tere
sts li
e
in
th
e
a
re
a
o
f
a
rti
f
icia
l
in
telli
g
e
n
t,
a
ss
isti
v
e
te
c
h
n
o
l
o
g
y
in
e
m
p
o
we
r
in
g
d
isa
b
led
st
u
d
e
n
ts,
e
lea
rn
in
g
a
n
d
g
a
m
m
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ra
n
g
in
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f
ro
m
th
e
o
ry
to
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e
sig
n
t
o
im
p
le
m
e
n
tatio
n
.
S
h
e
h
a
s
m
o
re
th
a
n
3
0
p
a
p
e
rs
in
in
tern
a
ti
o
n
a
l
a
n
d
l
o
c
a
l
jo
u
r
n
a
ls,
i
n
tern
a
ti
o
n
a
l
a
n
d
n
a
ti
o
n
a
l
c
o
n
f
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re
n
c
e
p
ro
c
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d
in
g
s
a
s
w
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ll
a
s
b
o
o
k
c
h
a
p
ters
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d
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tu
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o
tes
.
S
h
e
a
lso
se
rv
e
s
a
s
a
m
e
m
b
e
r
o
f
th
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e
d
it
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rial
b
o
a
rd
a
n
d
tec
h
n
ica
l
re
v
ie
w
e
r
f
o
r
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c
a
l
a
n
d
i
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tern
a
ti
o
n
a
l
jo
u
r
n
a
ls
a
s
w
e
ll
a
s
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o
n
f
e
re
n
c
e
s
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ra
jer
m
a
n
i.
th
in
a
@n
e
w
in
ti
.
e
d
u
.
m
y
or
ra
jerm
a
n
i@
y
a
h
o
o
.
c
o
m
.
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a
la
th
y
B
a
tu
m
a
l
a
y
h
o
l
d
s
a
B.
En
g
.
(El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
)
f
o
r
m
Un
iv
e
r
sit
y
T
u
n
Hu
ss
e
in
On
n
,
M
.
En
g
.
(T
e
lec
o
m
m
u
n
ica
ti
o
n
)
f
ro
m
Un
iv
e
rsit
y
M
a
l
a
y
a
a
n
d
P
h
.
D.
(
P
h
o
to
n
ics
)
f
ro
m
Un
iv
e
rsit
y
M
a
la
y
a
.
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rre
n
tl
y
sh
e
is
a
tt
a
c
h
e
d
a
s
A
ss
o
c
iate
P
ro
f
e
ss
o
r
w
it
h
th
e
F
a
c
u
lt
y
o
f
Da
t
a
S
c
ien
c
e
a
n
d
I
n
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
in
INT
I
In
tern
a
t
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n
a
l
Un
iv
e
rsity
,
Ne
g
e
ri
S
e
m
b
il
a
n
,
M
a
lay
sia
.
S
h
e
f
o
c
u
se
s
o
n
th
e
re
se
a
rc
h
o
f
p
h
o
t
o
n
ics
e
n
g
in
e
e
rin
g
,
f
ib
e
r
o
p
ti
c
s,
a
n
d
las
e
rs
tec
h
n
o
lo
g
y
.
S
h
e
is
c
u
rre
n
tl
y
c
o
ll
a
b
o
ra
ti
n
g
w
it
h
lo
c
a
l
Un
iv
e
rsiti
e
s
to
f
u
rth
e
r
e
n
h
a
n
c
e
th
e
p
e
rf
o
rm
a
n
c
e
o
f
se
n
so
rs
f
o
r
se
v
e
r
a
l
a
p
p
li
c
a
ti
o
n
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
a
lath
y
.
b
a
tu
m
a
la
y
@n
e
w
in
ti
.
e
d
u
.
m
y
.
J
o
se
p
h
Ng
Po
h
S
o
o
n
g
ra
d
u
a
ted
w
it
h
a
P
h
DIT
,
M
a
ste
r
’
s
in
I
n
f
o
r
m
a
ti
o
n
T
e
c
h
n
o
lo
g
y
(A
u
s),
M
a
ste
r
’
s
in
B
u
si
n
e
ss
A
d
m
in
istratio
n
(A
u
s)
a
n
d
A
ss
o
c
iat
e
Ch
a
rted
S
e
c
re
tary
(UK
)
w
it
h
v
a
rio
u
s
in
str
u
c
to
r
q
u
a
li
f
ica
ti
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n
s,
p
r
o
f
e
ss
io
n
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l
c
e
rti
f
ica
ti
o
n
s,
a
n
d
in
d
u
stry
m
e
m
b
e
rsh
ip
s.
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isted
n
u
m
e
ro
u
s
ti
m
e
s
a
s
th
e
W
o
rld
’
s
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o
p
2
%
S
c
ien
ti
st
in
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rti
f
icia
l
In
telli
g
e
n
c
e
a
n
d
Im
a
g
e
P
ro
c
e
ss
in
g
b
y
S
tan
f
o
rd
Un
iv
e
rsity
,
US
A
a
n
d
w
it
h
h
is
b
len
d
e
d
tec
h
n
o
c
ra
t
m
ix
o
f
b
o
th
b
u
sin
e
ss
se
n
se
s
a
n
d
tec
h
n
ica
l
sk
il
ls,
h
a
s
h
e
l
d
m
a
n
y
m
u
lt
in
a
ti
o
n
a
l
c
o
rp
o
ra
ti
o
n
se
n
i
o
r
m
a
n
a
g
e
m
e
n
t
p
o
sit
io
n
s,
g
lo
b
a
l
p
o
sti
n
g
a
n
d
lea
d
s
n
u
m
e
ro
u
s
2
4
×
7
g
lo
b
a
l
m
issio
n
-
c
rit
ica
l
sy
ste
m
s.
H
e
h
a
s
a
p
p
e
a
r
e
d
i
n
l
i
v
e
n
a
t
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o
n
a
l
t
e
l
e
v
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s
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o
n
p
r
im
e
t
im
e
Cy
b
e
r
se
c
u
r
i
ty
t
a
lk
s
h
o
w
s
a
n
d
o
v
e
r
se
a
s
te
a
c
h
i
n
g
e
x
p
o
s
u
r
e
.
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i
s
c
u
r
r
e
n
t
re
se
a
rc
h
i
s
o
n
s
t
r
a
t
e
g
i
c
d
i
g
i
ta
l
t
r
a
n
sf
o
rm
a
t
i
o
n
.
H
e
c
a
n
b
e
c
o
n
t
a
c
te
d
a
t
e
m
a
i
l
:
j
o
s
e
p
h
.
n
g
@
n
e
w
i
n
t
i
.
e
d
u
.
m
y
.
De
sh
i
n
ta
Ar
r
o
v
a
De
w
i
h
a
s
sta
rted
h
e
r
a
c
a
d
e
m
ic
c
a
r
e
e
r
in
In
d
o
n
e
sia
a
n
d
M
a
lay
si
a
s
i
n
c
e
2
0
0
3
.
S
h
e
o
b
tain
e
d
h
e
r
P
h
.
D.
f
ro
m
th
e
Na
ti
o
n
a
l
Un
iv
e
rsity
o
f
M
a
lay
sia
(UK
M
)
in
2
0
1
9
.
S
h
e
jo
in
e
d
INT
I
In
tern
a
ti
o
n
a
l
Un
iv
e
rsity
M
a
la
y
sia
in
2
0
1
0
a
n
d
is
c
u
rre
n
tl
y
p
ro
m
o
ted
to
A
ss
o
c
iate
P
r
o
f
e
ss
o
r
w
it
h
th
e
F
a
c
u
lt
y
o
f
Da
ta
S
c
ien
c
e
a
n
d
IT
.
He
r
re
se
a
rc
h
in
tere
sts
i
n
c
lu
d
e
a
rti
f
icia
l
in
telli
g
e
n
c
e
,
d
a
ta
sc
ien
c
e
,
a
n
d
s
o
f
twa
re
e
n
g
in
e
e
rin
g
.
S
h
e
h
a
s
m
o
re
th
a
n
3
0
p
a
p
e
rs
in
S
c
o
p
u
s
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u
rn
a
ls
a
n
d
h
o
l
d
s
a
p
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sit
io
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s
m
a
n
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g
in
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d
it
o
r
f
o
r
th
e
Jo
u
r
n
a
l
o
f
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ta
S
c
ien
c
e
(Jo
DS).
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
d
e
sh
in
ta.ad
@n
e
w
in
ti
.
e
d
u
.
m
y
o
r
d
e
sh
in
ta2
0
1
7
@g
m
a
il
.
c
o
m
.
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