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elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
3
,
J
u
n
e
2
0
2
0
:
1
3
9
7
-
14
05
1398
c
o
m
m
o
n
c
a
u
s
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s
o
f
d
e
a
t
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n
I
n
d
o
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e
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i
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a
r
e
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e
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o
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u
l
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r
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r
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l
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c
k
a
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t
r
o
k
e
p
a
t
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e
n
t
s
.
I
s
c
h
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m
i
c
h
e
a
r
t
d
i
s
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a
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,
c
o
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p
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p
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r
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t
u
b
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r
c
u
l
o
s
i
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h
y
p
e
r
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e
n
s
i
o
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f
o
l
l
o
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e
d
b
y
h
i
g
h
b
l
o
o
d
p
r
e
s
s
u
r
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w
i
t
h
c
o
m
p
l
i
c
a
t
i
o
n
s
I
n
f
e
c
t
i
o
n
i
n
t
h
e
r
e
s
p
i
r
a
t
o
r
y
t
r
a
c
t
,
e
s
p
e
c
i
a
l
l
y
c
h
r
o
n
i
c
o
b
s
t
r
u
c
t
i
v
e
p
u
l
m
o
n
a
r
y
d
i
s
e
a
s
e
(
C
O
P
D
)
,
l
i
v
e
r
d
i
s
e
a
s
e
,
t
r
a
f
f
i
c
a
c
c
i
d
e
n
t
s
,
p
n
e
u
m
o
n
i
a
,
a
n
d
d
i
a
r
r
h
e
a
o
r
g
a
s
t
r
o
e
n
t
e
r
i
t
i
s
a
r
e
o
r
i
g
i
n
a
t
i
n
g
f
r
o
m
t
h
e
a
p
p
e
a
r
a
n
c
e
o
f
t
h
e
i
n
f
e
c
t
i
o
n
[
4
]
.
T
h
e
r
e
s
u
l
t
s
o
f
p
r
i
m
a
r
y
h
e
a
l
t
h
r
e
s
e
a
r
c
h
i
n
2
0
1
8
s
h
o
w
a
n
i
n
c
r
e
a
s
e
i
n
t
h
e
p
r
e
v
a
l
e
n
c
e
o
f
p
n
e
u
m
o
n
i
a
f
r
o
m
1
.
6
%
t
o
2
%
[
5
]
.
A
s
w
r
i
t
t
e
n
b
y
L
u
n
a
e
t
a
l
.
i
n
2
0
0
1
,
t
o
f
i
n
d
o
u
t
t
h
e
c
a
u
s
e
o
f
p
n
e
u
m
o
n
i
a
,
f
i
r
s
t
l
y
d
o
c
t
o
r
s
d
i
a
g
n
o
s
e
p
a
t
i
e
n
t
s
u
s
i
n
g
X
-
r
a
y
s
,
d
o
c
t
o
r
s
c
a
n
s
e
e
p
a
r
t
s
o
f
t
h
e
l
u
n
g
s
a
f
f
e
c
t
e
d
b
y
t
h
e
d
i
s
e
a
s
e
.
S
e
c
o
n
d
l
y
,
t
h
r
o
u
g
h
b
l
o
o
d
t
e
s
t
s
o
r
s
p
u
t
u
m
t
e
s
t
s
,
t
h
e
b
a
c
t
e
r
i
a
o
r
v
i
r
u
s
e
s
t
h
a
t
c
a
u
s
e
t
h
i
s
h
e
a
l
t
h
d
i
s
o
r
d
e
r
w
i
l
l
b
e
s
e
e
n
.
T
h
i
r
d
l
y
,
t
h
e
e
x
a
m
i
n
a
t
i
o
n
o
f
b
l
o
o
d
o
x
y
g
e
n
l
e
v
e
l
s
.
I
f
t
h
e
r
e
a
r
e
s
o
m
e
s
e
v
e
r
e
s
y
m
p
t
o
m
s
,
t
h
e
d
o
c
t
o
r
w
i
l
l
r
e
q
u
e
s
t
a
n
a
n
a
l
y
s
i
s
t
h
r
o
u
g
h
a
C
T
s
c
a
n
a
n
d
t
a
k
e
a
l
u
n
g
f
l
u
i
d
c
u
l
t
u
r
e
[
6
]
.
On
th
e
o
th
er
h
an
d
,
v
is
u
al
o
b
s
er
v
atio
n
s
b
y
m
ed
ical
a
n
aly
s
ts
n
ee
d
ed
to
id
e
n
tify
b
ac
ter
ia.
B
ased
o
n
th
e
s
e
f
in
d
in
g
s
,
th
e
c
o
n
tr
ib
u
tio
n
o
f
th
is
r
esear
ch
is
th
e
u
s
e
o
f
im
ag
e
p
r
o
ce
s
s
in
g
to
r
e
p
lace
v
is
u
al
r
ep
r
esen
tatio
n
s
u
s
in
g
m
ac
h
in
e
lear
n
in
g
.
GAP
with
p
r
ev
i
o
u
s
r
esear
ch
is
n
o
t
y
et
o
b
tain
ed
o
p
tim
al
ac
cu
r
ac
y
a
t
th
e
s
tag
e
o
f
b
ac
ter
ial
id
en
tific
atio
n
.
T
h
is
r
esear
ch
u
s
es
p
r
im
ar
y
p
atien
t
d
ata
f
r
o
m
So
eto
m
o
Ho
s
p
ital
b
ec
au
s
e
th
er
e
is
n
o
t
en
o
u
g
h
s
ec
o
n
d
ar
y
d
ata
av
ailab
le
f
r
o
m
t
h
e
in
ter
n
et.
T
h
e
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
alg
o
r
ith
m
s
elec
ts
th
r
ee
s
tag
e
s
,
in
clu
d
in
g
d
r
o
p
o
u
t,
d
ata
au
g
m
en
tatio
n
,
an
d
f
in
d
in
g
th
e
r
ig
h
t
f
in
e
-
tu
n
in
g
.
T
h
e
tech
n
ical
n
o
v
elty
is
to
o
p
tim
ize
th
e
n
u
m
b
er
o
f
p
ar
am
eter
s
an
d
g
et
t
h
e
ac
cu
r
ac
y
im
p
r
o
v
em
en
t
u
s
e
d
b
y
C
NN.
B
esid
es,
th
is
r
esear
ch
u
s
es
lig
h
tweig
h
t
s
o
f
twar
e
-
b
ased
o
n
T
e
n
s
o
r
Flo
w
an
d
Ker
as
u
s
in
g
p
y
t
h
o
n
,
with
s
u
p
p
o
r
t
f
r
o
m
th
e
g
r
ap
h
ics p
r
o
ce
s
s
in
g
u
n
it
.
2.
TH
E
P
RO
P
O
SE
D
M
E
T
H
O
D
AND
AL
G
O
RI
T
H
M
T
h
is
s
ec
tio
n
co
n
s
is
ts
o
f
b
io
lo
g
ical
in
s
tr
u
m
en
ts
u
s
ed
to
o
b
tain
p
h
o
to
g
r
ap
h
s
an
d
m
et
h
o
d
s
u
s
e
d
.
2
.
1
.
G
ra
m
s
t
a
ini
ng
Gr
am
-
n
eg
ativ
e
b
ac
te
r
ia
ar
e
b
ac
ter
ia
wh
en
Gr
am
s
tain
ed
,
ca
n
n
o
t
m
ain
tain
th
e
cr
y
s
tal
p
u
r
p
le
d
y
e
s
o
th
at
th
e
b
ac
ter
ia
r
em
ain
r
ed
wh
en
o
b
s
er
v
e
d
u
s
in
g
a
m
ic
r
o
s
co
p
e
[
7
]
.
T
h
e
Gr
am
-
n
eg
ati
v
e
d
if
f
er
e
n
ce
with
Gr
am
-
p
o
s
itiv
e
is
b
ased
o
n
d
if
f
er
en
ce
s
in
th
e
ce
ll
wall
s
tr
u
ctu
r
e
an
d
ca
n
b
e
ap
p
lied
u
s
in
g
th
e
Gr
am
s
tain
in
g
p
r
o
ce
d
u
r
e
[
8
]
.
2.
2.
E
x
t
r
a
ct
io
n
o
f
s
ha
pe
f
ea
t
ures in im
a
g
e
pro
ce
s
s
ing
Dig
ital
im
ag
e
p
r
o
c
ess
in
g
,
as
s
aid
b
y
C
r
o
m
e
y
in
2
0
1
3
in
h
is
r
esear
ch
,
is
a
f
ield
o
f
im
a
g
e
p
r
o
ce
s
s
in
g
r
esear
ch
th
at
s
tu
d
ies
h
o
w
an
i
m
ag
e
is
o
b
tain
ed
,
p
r
o
ce
s
s
ed
,
an
d
a
n
aly
ze
d
s
o
th
at
it
ca
n
f
o
r
m
in
f
o
r
m
atio
n
th
at
ca
n
b
e
u
n
d
e
r
s
to
o
d
b
y
h
u
m
a
n
s
[
9
]
.
Per
im
eter
is
an
o
b
ject
b
o
u
n
d
ar
y
th
at
is
ca
lcu
lated
b
ase
d
o
n
th
e
n
u
m
b
er
o
f
p
ix
els ar
o
u
n
d
th
e
o
b
ject.
I
t c
al
cu
lated
u
s
in
g
a
r
atio
b
etwe
en
cir
cu
m
f
er
en
ce
(
P
)
t
o
len
g
th
(
Lp
)
an
d
wid
th
(
Wp
)
.
=
(
+
)
(
1
)
T
h
e
n
u
m
b
e
r
o
f
p
i
x
e
l
s
i
n
t
h
e
o
b
j
e
c
t
c
a
l
c
u
l
a
t
e
d
.
I
t
t
o
g
e
t
t
h
e
a
r
e
a
v
a
l
u
e
.
T
h
e
s
h
a
p
e
o
f
t
h
e
o
b
j
e
c
t
i
s
i
n
t
h
e
s
a
m
p
l
e
i
m
a
g
e
.
M
e
t
r
i
c
i
s
a
f
o
r
m
f
a
c
t
o
r
/
r
o
u
n
d
n
e
s
s
c
i
r
c
l
e
.
S
l
i
m
n
e
s
s
i
s
a
r
a
t
i
o
o
f
l
e
n
g
t
h
a
n
d
w
i
d
t
h
.
(
)
=
4
2
(
2
)
A
is
th
e
ar
ea
o
f
t
h
e
o
b
ject
an
d
p
is
th
e
cir
cu
m
f
er
en
ce
[
10
]
.
E
cc
en
tr
icity
is
th
e
n
u
m
b
er
o
f
s
p
atial
v
alu
es
o
f
th
e
m
in
o
r
ellip
s
e
with
th
e
f
o
c
u
s
d
is
tan
ce
o
f
th
e
ce
n
tr
al
o
v
a
l
o
n
th
e
cir
cle
o
b
ject.
E
cc
e
n
tr
icity
r
an
g
e
v
alu
es
r
an
g
e
b
etwe
en
0
an
d
1
[
11
]
.
T
h
e
m
eth
o
d
f
o
r
ca
lcu
latin
g
th
e
E
cc
en
tr
icity
illu
s
tr
ated
v
alu
e
is
to
lo
o
k
at
th
e
illu
s
tr
atio
n
Fig
u
r
e
1
.
Fig
u
r
e
1
.
E
cc
e
n
tr
icity
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
imp
r
o
ve
men
t o
f G
r
a
m
-
n
eg
a
tive
b
a
cteria
id
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tifi
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tio
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tio
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(
B
u
d
i D
w
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a
to
to
)
1399
I
t is a
m
ea
s
u
r
e
o
f
th
e
s
lo
p
e
o
f
an
ellip
s
e.
T
h
e
ec
ce
n
tr
icity
f
o
r
m
u
la
wr
o
te
as
(
3
)
:
=
c
a
=
√
−
(
3
)
w
ith
e
=
ec
ce
n
tr
icity
,
c
is
th
e
d
is
tan
ce
f
r
o
m
t
h
e
ce
n
ter
o
f
t
h
e
cir
cle
to
f
o
c
u
s
,
2
=
2
−
2
,
a
=
m
ajo
r
ax
is
,
b
=
m
in
o
r
a
x
is
.
B
y
p
a
y
in
g
att
en
tio
n
to
th
e
s
h
ap
e
o
f
o
b
jects
th
at
ar
e
o
v
al
a
n
d
el
o
n
g
ated
t
o
f
o
r
m
lin
ea
r
lin
es.
I
f
th
e
ec
ce
n
t
r
icity
v
alu
e
a
p
p
r
o
ac
h
e
s
o
n
e
th
e
n
th
e
o
b
ject
h
as a
n
o
v
al
o
r
elo
n
g
ated
s
h
a
p
e,
w
h
ile
th
e
p
u
r
p
o
s
e
h
as
a
r
o
u
n
d
s
h
ap
e,
t
h
e
ec
ce
n
tr
icity
v
alu
e
is
clo
s
e
to
0
[
12
]
.
2.
3.
Co
nv
o
lutio
n
neura
l net
wo
rk
VG
G
-
16
C
N
N
i
s
a
f
o
r
m
o
f
d
e
v
e
l
o
p
i
n
g
m
u
l
t
i
-
l
a
y
e
r
p
e
r
c
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a
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i
o
n
a
s
s
h
o
w
n
i
n
F
i
g
u
r
e
2
[
13
]
.
I
n
th
e
f
u
lly
co
n
n
ec
ted
lay
e
r
ar
ch
itectu
r
e
in
VGG1
6
,
3
x
4
0
9
6
n
eu
r
o
n
s
ar
e
in
a
h
id
d
e
n
lay
er
[
14
]
.
T
h
e
k
er
n
el
co
r
e
in
s
id
e
C
NN
alwa
y
s
s
h
if
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s
with
th
e
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ag
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atr
ix
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r
in
th
e
k
e
r
n
el
is
a
s
k
ip
p
in
g
f
ac
to
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[
15
]
.
T
h
e
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tp
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t
v
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f
t
h
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m
ap
p
in
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s
s
s
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o
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in
(
4
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.
=
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4
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Featu
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Fu
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u
r
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2
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r
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T
h
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f
ea
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r
e
m
a
p
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av
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a
lo
wer
r
eso
lu
tio
n
[
16
]
.
T
h
e
n
ew
m
ax
-
p
o
o
lin
g
f
ea
tu
r
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m
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:
=
ma
x
(
,
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(
5
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w
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=
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v
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f
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t
h
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h
e
r
l
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r
[
17
]
.
I
n
g
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n
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r
a
l
,
i
t
h
a
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t
h
e
s
a
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w
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l
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(
M
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P
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n
e
u
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t
w
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k
s
[
18
]
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T
h
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m
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[
19
]
.
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r
[
20
]
.
2
.
3
.
1
.
Dro
po
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Dr
o
p
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is
a
p
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in
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etwo
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[
21
]
.
T
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will b
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b
ab
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,
wh
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is
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etwe
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0
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d
1
[
22
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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2
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Da
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Data
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k
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[
23
]
.
T
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s
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ig
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2
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3
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3
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F
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latin
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lear
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in
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ate
[
24
]
.
T
h
e
p
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s
s
o
f
f
in
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in
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[
25
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(
t
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W
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Evaluation Warning : The document was created with Spire.PDF for Python.