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f
o
llo
w
s
:
Fir
s
t,
b
ac
k
g
r
o
u
n
d
an
d
ex
is
ti
n
g
m
et
h
o
d
s
.
R
elate
d
W
o
r
k
s
in
Sectio
n
2
.
T
h
e
p
r
o
p
o
s
ed
NI
L
M
ev
en
t
d
etec
tio
n
m
et
h
o
d
is
d
is
cu
s
s
ed
in
Sec
tio
n
3
an
d
E
x
p
er
i
m
e
n
tal
r
es
u
lts
a
n
d
d
is
cu
s
s
io
n
ar
e
s
h
o
w
n
in
Sectio
n
4
.
So
m
e
co
n
c
lu
s
io
n
s
ar
e
d
is
cu
s
s
ed
i
n
Se
c
tio
n
5.
2.
RE
L
AT
E
D
WO
RK
S
So
m
e
e
v
en
t
-
b
ased
m
et
h
o
d
u
s
in
g
al
g
o
r
ith
m
f
o
r
r
ea
l
-
t
i
m
e
ev
en
t
d
etec
tio
n
s
u
ch
a
s
c
h
an
g
e
p
o
i
n
t
d
etec
tio
n
[
6
]
,
Gen
er
alize
d
L
i
k
eli
h
o
o
d
R
atio
(
G
L
R
)
[
7
]
,
t
h
e
ch
i
-
s
q
u
ar
e
g
o
o
d
n
e
s
s
-
of
-
f
it
t
est
(
X2
GO
F)
[
8
]
,
th
e
C
u
m
u
lat
iv
e
SUM
(
C
U
SU
M)
f
ilter
in
g
[
9
]
,
an
d
ce
p
s
tr
u
m
a
n
al
y
s
i
s
[
1
0
]
-
[
1
3
]
.
C
h
an
g
e
p
o
in
t
d
etec
tio
n
to
d
etec
t
ab
r
u
p
t
ch
an
g
es
i
n
ti
m
e
s
er
ies
d
ata
an
d
to
id
en
tify
th
e
s
p
ec
if
ic
ti
m
e
in
s
tan
ce
w
h
en
t
h
e
ch
an
g
e
o
cc
u
r
s
.
I
n
GL
R
ap
p
r
o
ac
h
,
a
d
ec
is
io
n
s
t
atis
tic
w
a
s
ca
lc
u
lated
b
y
th
e
n
atu
r
al
lo
g
o
f
a
r
ati
o
o
f
p
r
o
b
ab
ilit
y
d
is
tr
ib
u
tio
n
b
ef
o
r
e
an
d
a
f
ter
t
h
e
p
o
ten
tial
ch
an
g
e
in
m
ea
n
.
T
h
is
ap
p
r
o
ac
h
r
eq
u
ir
es
s
o
m
e
p
ar
a
m
e
ter
to
b
e
tr
ain
ed
,
s
u
ch
as
th
e
m
o
v
i
n
g
w
i
n
d
o
w
s
,
t
h
e
p
o
w
er
d
ata
a
n
d
a
t
h
r
es
h
o
ld
f
o
r
d
etec
tio
n
s
tat
is
tic.
T
h
e
X2
G
OF
tes
t
to
d
ec
id
e
t
h
e
d
etec
tio
n
d
e
cisi
o
n
th
r
es
h
o
ld
w
h
ic
h
d
ep
en
d
s
o
n
th
e
d
ata
w
i
n
d
o
w
s
s
ize.
T
h
is
m
et
h
o
d
d
eter
m
in
e
s
d
ec
is
io
n
b
et
w
ee
n
t
w
o
h
y
p
o
t
h
eses
.
I
f
t
h
e
n
u
ll
h
y
p
o
t
h
esi
s
is
r
ej
ec
ted
th
en
ass
u
m
ed
t
h
at
a
n
ap
p
lian
c
e
ev
e
n
t
o
cc
u
r
s
.
T
h
e
X2
d
escr
ib
es
d
ec
is
io
n
th
r
es
h
o
ld
th
at
d
ep
en
d
s
o
n
w
in
d
o
ws
s
iz
e
an
d
d
etec
tio
n
co
n
f
id
en
ce
lev
e
l.
C
US
UM
d
eter
m
in
e
c
h
an
g
e
s
o
f
tr
a
n
s
ie
n
ts
i
n
s
eq
u
en
ce
d
ata
i
n
t
h
e
av
er
ag
e
a
n
d
p
r
o
v
id
es
cr
iter
ia
th
at
h
elp
m
a
k
e
d
ec
is
io
n
s
.
I
ts
d
etec
tio
n
b
o
th
b
eg
in
n
i
n
g
an
d
th
e
en
d
o
f
t
h
e
tr
an
s
ie
n
t
is
b
ased
o
n
a
s
i
m
p
le
r
u
le.
Sin
ce
s
to
p
r
u
le
o
cc
u
r
s
in
th
e
s
tead
y
s
tate
t
h
e
n
th
e
b
eg
i
n
n
in
g
o
f
a
tr
an
s
ie
n
t
h
ap
p
en
s
an
d
th
e
s
to
p
r
u
le
o
cc
u
r
s
in
t
h
e
tr
an
s
ie
n
t
s
tate
t
h
e
n
t
h
e
e
n
d
o
f
a
tr
a
n
s
ien
t
o
cc
u
r
s
.
T
h
e
p
r
ev
io
u
s
m
eth
o
d
in
v
es
tig
a
ted
th
e
p
o
w
er
s
i
g
n
al
i
n
t
h
e
t
i
m
e
d
o
m
ai
n
.
Mo
r
eo
v
er
,
an
a
n
al
y
s
i
s
ca
n
b
e
p
er
f
o
r
m
ed
i
n
t
h
e
f
r
eq
u
en
c
y
d
o
m
ai
n
,
e.
g
.
,
ce
p
s
tr
u
m
an
al
y
s
is
.
C
ep
s
tr
u
m
an
al
y
s
is
i
s
u
s
ed
to
d
er
iv
e
th
e
r
esu
lt
o
f
ta
k
in
g
t
h
e
Fo
u
r
ier
T
r
an
s
f
o
r
m
o
f
th
e
lo
g
s
p
ec
tr
u
m
.
T
h
e
m
eth
o
d
w
il
l
p
r
o
d
u
ce
th
e
ce
p
s
tr
u
m
p
ar
a
m
e
ter
as
o
n
e
o
f
t
h
e
c
h
ar
ac
ter
is
ti
cs
o
f
th
e
s
i
g
n
al.
T
o
g
et
th
e
v
alu
e
o
f
ce
p
s
tr
u
m
it
m
u
s
t
p
ass
s
o
m
e
s
eq
u
en
ce
b
lo
ck
p
r
ev
io
u
s
d
ia
g
r
a
m
t
h
at
i
s
f
r
o
m
t
h
e
p
r
o
ce
s
s
o
f
F
FT
w
h
ic
h
p
r
o
d
u
ce
s
p
ec
tr
u
m
m
u
s
t
a
t
f
ir
s
t
in
v
er
s
e
to
ch
a
n
g
e
elec
tr
ical
s
ig
n
al
f
r
o
m
f
r
eq
u
en
c
y
d
o
m
ai
n
b
ec
o
m
e
ti
m
e
d
o
m
ai
n
,
a
n
d
ce
p
s
tr
u
m
v
alu
e
t
h
at
r
es
u
lt
s
f
r
o
m
s
p
ec
tr
u
m
in
v
er
s
e
v
al
u
e
p
r
o
ce
s
s
.
A
ce
p
s
tr
u
m
-
s
m
o
o
t
h
in
g
-
b
ased
m
et
h
o
d
is
p
r
o
p
o
s
ed
to
im
p
r
o
v
e
ce
p
s
tr
u
m
p
er
f
o
r
m
a
n
ce
b
y
c
o
n
s
id
er
in
g
s
i
m
u
lta
n
eo
u
s
ON/O
FF
tr
a
n
s
it
io
n
s
[
1
2
]
.
T
h
is
m
e
th
o
d
ca
p
ab
le
o
f
d
etec
tin
g
ON/
OFF
ap
p
l
ian
ce
s
a
n
d
ca
n
b
e
u
s
ed
to
h
an
d
le
th
e
s
i
m
i
lar
p
ea
k
s
iz
e
o
f
ch
ar
ac
ter
is
t
ic
s
ig
n
als
f
r
o
m
d
if
f
er
en
t
ap
p
lian
c
es.
T
h
e
s
m
o
o
th
e
d
ce
p
s
tr
u
m
ex
tr
ac
t
t
h
e
u
s
e
f
u
l
f
ea
tu
r
es
f
r
o
m
th
e
cu
r
r
en
t
s
i
g
n
al
g
en
er
ated
b
y
a
h
o
m
e
ap
p
lian
ce
.
T
h
is
p
ap
er
f
o
cu
s
es
o
n
t
h
e
d
ev
elo
p
m
e
n
t
o
f
ev
e
n
t
d
etec
tio
n
m
et
h
o
d
s
.
T
h
e
m
eth
o
d
is
ad
o
p
ted
f
r
o
m
t
h
e
ce
p
s
tr
u
m
a
n
al
y
s
i
s
tech
n
iq
u
e
[
1
2
]
to
ex
tr
ac
t
u
s
ef
u
l
f
ea
tu
r
e
u
s
i
n
g
s
m
o
o
t
h
in
g
f
r
eq
u
en
c
y
co
m
p
o
n
e
n
t.
Ho
w
e
v
er
,
ce
p
s
tr
u
m
e
s
ti
m
ato
r
b
ased
o
n
th
e
p
er
io
d
o
g
r
a
m
s
u
f
f
er
s
f
r
o
m
lar
g
e
v
ar
ia
n
ce
an
d
th
is
w
i
ll
ca
u
s
e
lar
g
e
est
i
m
atio
n
er
r
o
r
s
in
t
h
e
ce
p
s
tr
u
m
co
e
f
fi
cie
n
t
s
.
T
h
e
c
o
n
tr
ib
u
tio
n
o
f
o
u
r
p
ap
er
co
n
ce
r
n
o
n
d
ev
elo
p
in
g
a
r
o
b
u
s
t
s
m
o
o
t
h
i
n
g
ap
p
r
o
ac
h
b
ased
o
n
lo
ca
l lin
ea
r
r
eg
r
ess
io
n
[
1
4
]
,
[
1
5
]
to
r
ed
u
ce
v
ar
ian
ce
an
d
i
m
p
r
o
v
e
lo
ad
ev
en
t id
e
n
ti
f
icatio
n
.
3.
L
O
AD
E
V
E
N
T
DE
T
E
CT
I
O
N
C
ep
s
tr
u
m
m
et
h
o
d
u
s
ed
to
e
x
t
r
ac
t
th
e
c
h
ar
ac
ter
is
tic
s
o
f
e
lectr
ical
s
i
g
n
al
o
n
h
o
m
e
ap
p
lia
n
ce
s
.
L
o
ad
s
ig
n
al
s
o
f
ap
p
lian
ce
s
s
i
m
u
late
d
an
d
m
ea
s
u
r
ed
th
r
o
u
g
h
t
h
e
s
i
m
u
lato
r
to
o
l.
C
u
r
r
en
t
s
i
g
n
al
d
ata
f
r
o
m
ap
p
lian
ce
s
ar
e
u
s
ed
to
ex
tr
ac
t
its
f
ea
tu
r
e
s
.
So
m
e
n
o
i
s
e
in
t
h
e
C
u
r
r
en
t
s
ig
n
al
w
ill
a
f
f
ec
t
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
e
v
en
t
d
etec
tio
n
r
esu
lt,
s
o
it
n
ee
d
s
t
o
b
e
r
em
o
v
ed
.
T
h
is
ch
ap
ter
d
is
cu
s
s
e
s
th
e
lo
ad
m
o
d
eli
n
g
o
f
h
o
m
e
ap
p
lian
ce
s
,
n
o
is
e
r
e
m
o
v
al
p
r
o
ce
s
s
e
s
,
d
etec
tio
n
p
r
o
ce
s
s
o
f
c
h
a
n
g
e
s
i
n
t
h
e
C
u
r
r
en
t
a
m
p
lit
u
d
es
a
n
d
t
h
e
p
r
o
ce
s
s
o
f
s
i
g
n
al
ex
tr
ac
tio
n
u
s
i
n
g
th
e
C
ep
s
tr
u
m
m
et
h
o
d
.
3
.
1
.
H
o
m
e
a
pp
lia
nce
lo
a
d
mo
delin
g
R
esid
en
tial
elec
tr
ical
n
et
w
o
r
k
an
d
s
o
m
e
lo
ad
s
o
f
ap
p
lia
n
ce
s
w
er
e
s
i
m
u
lated
u
s
in
g
MA
T
L
A
B
Si
m
u
li
n
k
m
o
d
el.
T
h
is
m
o
d
el
co
n
s
i
s
ts
o
f
th
r
ee
p
h
ase
s
o
f
t
h
e
p
o
w
er
s
o
u
r
ce
,
th
r
ee
-
p
h
a
s
e
m
ea
s
u
r
e
m
e
n
t
a
n
d
h
o
m
e
ap
p
lian
ce
.
E
ac
h
p
h
ase
c
o
n
n
ec
ted
to
ea
ch
h
o
m
e
'
s
ap
p
lian
ce
,
ie
P
h
ase
A
to
h
o
m
e
1
,
P
h
ase
B
to
h
o
m
e
2
an
d
P
h
ase
C
to
h
o
m
e
3
as
s
h
o
w
n
in
t
h
e
f
o
llo
w
i
n
g
Fi
g
u
r
e
1
.
A
p
p
lian
ce
s
i
n
ea
ch
h
o
u
s
e
a
m
o
u
n
ts
f
o
u
r
ap
p
lian
ce
s
w
it
h
B
r
ea
k
er
C
o
n
tr
o
l to
tu
r
n
o
n
/ o
f
f
th
e
ir
o
p
er
atio
n
.
A
p
p
lian
ce
in
ea
c
h
h
o
u
s
e
w
a
s
s
i
m
u
lated
n
o
n
-
l
in
ea
r
l
y
alo
n
g
w
it
h
T
HD
an
al
y
s
i
s
.
So
m
e
n
o
n
-
li
n
ea
r
elec
tr
ical
ap
p
lian
ce
s
ar
e
m
o
d
e
led
b
y
r
ef
er
s
to
t
h
e
[
1
6
]
-
[
1
8
]
m
o
d
el
as
f
o
llo
w
s
P
er
s
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RE
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NC
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S
[1
]
S
.
S
e
m
w
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l
e
R.
S
.
P
ra
sa
d
“
I
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s ”
In
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C
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En
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(
IJ
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v
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4
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6
,
p
p
.
9
0
9
-
9
2
2
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2
0
1
4
.
[2
]
N.
Ik
sa
n
S
.
H.
S
u
p
a
n
g
k
a
t
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I.
B.
Nu
g
ra
h
a
“
Ho
m
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En
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rg
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M
a
n
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g
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m
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S
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In
ter
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IC
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fo
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ma
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o
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Ja
k
a
rta,
2
0
1
3
.
[3
]
Zeifm
a
n
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No
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i
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tru
siv
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L
o
a
d
M
o
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it
o
ri
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g
:
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v
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n
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k
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IEE
E
tra
n
s.
C
o
n
su
m.
El
e
c
tro
n
,
2
0
1
1
.
[4
]
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Ik
sa
n
e
S
.
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u
p
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g
k
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t
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d
a
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-
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tru
siv
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o
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d
M
o
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it
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rin
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m
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d
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l
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si
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Ba
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lea
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”
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m
In
ter
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t
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l
C
o
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fer
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n
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n
ICT
Fo
r S
m
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o
c
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(
ICIS
S
)
,
Ba
n
d
u
n
g
,
2
0
1
4
.
[5
]
Ha
rt
“
No
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in
tru
siv
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A
p
p
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n
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L
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m
IEE
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,
1
9
9
2
.
[6
]
Ba
ss
e
v
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De
te
c
ti
o
n
o
f
A
b
ru
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t
C
h
a
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e
s: T
h
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a
n
d
A
p
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ti
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P
re
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ti
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Ha
ll
,
1
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9
3
.
[7
]
K.
D.
A
n
d
e
rso
n
,
M
.
E
.
Be
rg
é
s,
A
.
Oc
n
e
a
n
u
,
D.
Be
n
it
e
z
e
J.
M
.
M
o
u
ra
“
Ev
e
n
t
De
tec
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f
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n
In
tr
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siv
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to
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m
IECON
2
0
1
2
-
3
8
th
An
n
u
a
l
Co
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fer
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c
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o
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IEE
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d
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stri
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l
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c
tro
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,
2
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]
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rg
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T
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-
F
re
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y
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p
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ro
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c
h
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Ev
e
n
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De
t
e
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ti
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n
No
n
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In
tru
siv
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L
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,
”
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m
Pro
c
.
S
PIE
8
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0
,
S
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l
Pro
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S
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F
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,
a
n
d
T
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rg
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t
R
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it
i
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,
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lo
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2
0
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1
.
Evaluation Warning : The document was created with Spire.PDF for Python.