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Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2
502
-
47
52
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
,
V
o
l
.
19
,
N
o
.
3,
S
e
pt
e
m
b
e
r
2
020
:
163
5
-
164
2
1636
pr
o
duc
t
s
.
M
a
n
y
of
t
h
e
f
i
l
t
e
r
i
ng
m
e
t
h
o
ds
us
e
d
in
t
h
e
r
e
c
o
m
m
e
n
da
t
i
o
n
s
s
y
s
t
e
m
e
xpl
o
i
t
t
h
e
us
e
r
i
n
f
o
rm
a
t
i
o
n
to
pr
o
v
i
de
t
h
e
a
pp
r
o
p
r
i
a
t
e
e
l
e
m
e
nt
s
[5]
.
A
l
t
h
o
ug
h
t
h
e
v
a
r
i
o
us
m
e
t
h
o
ds
of
r
e
c
o
m
m
e
n
da
t
i
o
n
s
y
s
t
e
m
s
ha
v
e
be
e
n
de
ve
l
o
pe
d
in
r
e
c
e
n
t
y
e
a
r
s
,
t
hi
s
f
i
e
l
d
r
e
m
a
i
n
s
f
e
r
t
i
l
e
to
m
o
r
e
r
e
s
e
a
r
c
h
due
to
t
h
e
i
n
c
r
e
a
s
i
n
g
de
m
a
n
d
for
pra
c
t
i
c
a
l
a
pp
l
i
c
a
t
i
o
n
s
,
w
h
i
c
h
is
us
e
d
to
p
r
o
v
i
de
c
us
t
o
m
i
z
e
d
re
c
o
m
m
e
n
d
a
t
i
o
n
s
a
nd
de
a
l
s
w
i
t
h
t
h
e
i
n
f
o
r
m
a
t
i
o
n
ov
e
r
l
o
a
d
[6].
T
h
e
r
e
is
a
g
r
o
up
of
di
ff
e
r
e
n
t
t
e
c
hni
que
s
fo
r
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
s
,
o
n
e
of
t
h
e
m
o
s
t
i
m
po
rt
a
nt
of
t
h
e
s
e
m
e
t
h
o
ds
is
t
h
e
c
l
us
t
e
ri
n
g
[
7
].
T
h
e
c
l
us
t
e
ri
n
g
a
l
go
ri
t
hm
is
a
m
e
t
h
o
d
of
pa
rt
i
t
i
o
ni
n
g
a
p
h
y
s
i
c
a
l
or
t
h
e
o
r
e
t
i
c
a
l
o
b
j
e
c
t
i
nt
o
a
g
r
o
up
of
s
i
m
i
l
a
r
o
b
j
e
c
t
s
.
A
c
l
us
t
e
r
is
an
a
s
s
o
r
t
m
e
nt
of
i
n
f
o
r
m
a
t
i
o
n
o
b
j
e
c
t
s
;
th
e
obj
e
c
t
s
in
a
c
l
us
t
e
r
a
r
e
l
i
ke
o
n
e
a
n
o
t
h
e
r
a
n
d
a
r
e
n
o
t
t
h
e
s
a
m
e
obj
e
c
t
s
in
o
t
h
e
r
c
l
us
t
e
r
s
[
8
].
F
o
r
t
h
e
c
l
us
t
e
r
i
ng
m
i
s
s
i
o
n,
t
h
e
o
b
j
e
c
t
s
as
c
l
o
s
e
as
a
c
o
n
c
e
i
v
a
b
l
e
i
n
s
i
de
c
l
us
t
e
r
.
H
ow
e
v
e
r
,
t
h
e
ra
n
do
m
s
e
l
e
c
t
i
o
n
of
t
h
e
c
e
n
t
e
r
po
i
nt
of
t
h
e
s
a
m
p
l
e
w
i
l
l
m
a
ke
c
l
us
t
e
r
c
o
l
l
e
c
t
i
o
n
n
o
t
c
o
n
v
e
r
ge
[
9
].
T
h
e
m
o
s
t
c
o
m
m
o
nl
y
ut
i
l
i
z
e
d
is
t
h
e
K
-
m
e
a
n
s
c
l
us
t
e
r
i
ng
a
l
go
r
i
t
hm
b
e
c
a
us
e
of
its
e
f
fo
r
t
l
e
s
s
n
e
s
s
[
10
].
In
t
h
i
s
pa
pe
r
,
a
m
o
di
f
i
e
d
K
-
m
e
a
n
s
us
e
d
w
i
t
h
th
e
E
l
b
ow
s
t
r
a
t
e
gy
t
o
de
t
e
r
m
i
n
e
t
h
e
a
c
t
ua
l
n
u
m
b
e
r
of
c
l
us
t
e
r
s
a
pp
r
o
p
r
i
a
t
e
to
t
h
e
us
e
r
da
t
a
b
a
s
e
a
n
d
a
c
hi
e
v
e
a
hi
g
h
e
f
f
i
c
i
e
n
c
y
to
f
i
t
us
e
r
r
e
qui
r
e
m
e
nt
s
to
c
h
o
o
s
e
t
h
e
de
v
i
c
e
s
a
pp
r
o
p
r
i
a
t
e
for
b
o
t
h
w
e
a
t
h
e
r
c
o
n
di
t
i
o
n
s
,
de
v
i
c
e
pr
o
pe
rt
i
e
s
,
a
n
d
us
e
r
p
r
e
f
e
r
e
n
c
e
s
.
2.
R
ELA
TED
WO
R
K
S
R
e
c
e
n
t
l
y
,
t
h
e
r
e
a
r
e
s
o
m
e
of
r
e
s
e
a
r
c
h
e
s
i
n
v
i
s
t
i
g
a
t
i
n
g
t
h
e
de
v
e
l
o
p
m
e
n
t
of
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
s
b
a
s
e
d
on
c
l
us
t
e
r
i
ng
t
e
c
hn
i
que
s
.
A
ka
n
ks
ha
J
y
o
t
i
1
et
al
2019:
a
ppl
i
e
d
c
o
l
l
a
b
o
r
a
t
i
v
e
f
i
l
t
e
r
i
ng
to
f
i
n
d
t
h
e
us
e
r
'
s
ra
t
e
s
c
o
r
e
to
m
a
ke
r
e
l
a
t
i
o
n
s
w
i
t
h
o
t
h
e
r
us
e
r
s
a
n
d
E
uc
l
i
de
a
n
di
s
t
a
n
c
e
s
i
m
i
l
a
ri
t
y
s
c
o
r
e
di
s
t
i
n
gu
i
s
h
s
i
m
i
l
a
ri
t
y
b
e
t
w
e
e
n
us
e
r
s
.
I
n
t
e
g
ra
t
e
w
i
t
h
a
map
i
nt
e
r
f
a
c
e
to
f
i
n
d
t
h
e
s
h
o
rt
e
s
t
di
s
t
a
n
c
e
s
a
m
o
n
g
s
t
o
r
e
s
w
h
o
s
e
pr
o
duc
t
s
w
e
r
e
r
e
c
o
m
m
e
n
de
d.
T
h
e
r
e
s
ul
t
s
h
o
w
e
d
a
b
e
t
t
e
r
a
pp
r
o
a
c
h
t
ow
a
r
ds
t
h
e
r
e
c
o
m
m
e
nda
t
i
o
n
of
pr
o
duc
t
s
a
m
o
n
g
l
o
c
a
l
s
t
o
r
e
s
w
i
t
h
i
n
a
r
e
gi
o
n
[
11
].
MA
S
y
a
kur
et
al
2018
:
us
e
d
K
-
m
e
a
n
s
m
e
t
h
o
d
w
i
t
h
E
l
b
ow
to
i
m
p
r
o
v
e
e
ff
e
c
t
i
v
e
a
n
d
e
f
f
i
c
i
e
n
t
k
-
m
e
a
n
s
pe
r
f
o
r
m
a
n
c
e
of
b
i
g
qua
n
t
i
t
i
e
s
of
da
t
a
.
E
l
b
ow
a
n
d
K
-
m
e
a
n
s
m
e
t
h
o
ds
t
h
a
t
t
h
e
de
t
e
r
m
i
n
a
t
i
o
n
t
h
e
b
e
s
t
v
a
l
ue
of
t
h
e
c
l
us
t
e
r
s
[
12
].
P
h
o
ngs
a
v
a
nh
P
h
o
r
a
s
i
m
a
n
d
L
a
s
h
e
ng
Yu
2017
:
us
e
d
K
-
m
e
a
n
s
a
n
d
c
o
l
l
a
b
o
r
a
t
i
v
e
f
i
l
t
e
r
i
ng
to
m
o
v
i
e
s
r
e
c
o
m
m
e
n
d
a
t
i
o
n
p
r
o
po
s
e
d,
a
us
e
r
-
b
a
s
e
d
r
e
c
o
m
m
e
n
da
t
i
o
n
m
e
t
h
o
d
us
i
n
g
E
uc
l
i
di
a
n
di
s
t
a
n
c
e
to
c
a
l
c
ul
a
t
e
t
w
o
us
e
r
s
of
t
h
e
c
l
us
t
e
r
d
a
t
a
s
e
t
[
13
].
G
a
r
g
a
nd
T
i
w
a
r
i
2016
:
P
r
o
po
s
e
d
an
e
f
f
i
c
i
e
n
t
M
a
s
s
i
v
e
O
n
l
i
n
e
O
pe
n
Co
u
r
s
e
s
(M
O
O
Cs
)
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
b
a
s
e
d
on
K
-
m
e
a
n
s
a
n
d
c
o
l
l
a
b
o
r
a
t
i
v
e
.
T
h
e
ra
t
i
n
g
c
r
e
a
t
e
d
f
r
o
m
t
h
e
a
c
t
i
v
i
t
y
of
us
e
r
s
.
T
h
e
s
y
s
t
e
m
pr
o
duc
e
s
t
h
e
n
e
i
g
h
b
o
rh
o
o
d
c
l
us
t
e
r
s
f
r
o
m
t
h
e
u
s
e
r
da
t
a
b
a
s
e
.
T
h
e
s
y
s
t
e
m
h
a
s
b
e
i
n
g
t
r
a
i
n
e
d
for
pr
e
di
c
t
i
n
g
t
h
e
us
e
r
[
14
].
O
y
e
l
a
de
et
al
2010:
us
e
d
a
k
-
m
e
a
n
s
c
l
us
t
e
ri
n
g
a
l
go
r
i
t
hm
w
a
s
i
m
p
l
e
m
e
nt
e
d
to
a
n
a
l
y
z
e
s
t
ude
n
t
r
e
s
ul
t
s
b
a
s
e
d
on
c
l
us
t
e
r
a
na
l
y
s
i
s
a
n
d
us
e
d
s
t
a
t
i
s
t
i
c
a
l
a
l
go
r
i
t
hm
s
to
ra
n
k
t
h
e
i
r
g
ra
de
da
t
a
a
c
c
o
r
di
n
g
to
t
h
e
i
r
l
e
v
e
l
of
pe
r
f
o
r
m
a
n
c
e
[1
5
].
F
r
o
m
t
h
e
a
b
ov
e
r
e
l
a
t
e
d
w
o
r
k,
a
c
o
m
b
i
na
t
i
o
n
of
m
o
r
e
t
h
a
n
o
n
e
a
l
go
r
i
t
h
m
a
n
d
a
c
o
m
b
i
na
t
i
o
n
of
w
e
a
t
h
e
r
c
o
n
dt
i
o
n
s
a
nd
de
v
i
c
e
fe
a
t
u
r
e
s
a
r
e
n
o
t
t
a
c
ke
l
e
d,
So
t
hi
s
r
e
s
e
a
c
h
is
p
r
o
po
s
e
d
to
a
c
h
i
e
v
e
t
h
e
obj
e
c
t
i
ve
s
of
t
h
e
c
urr
e
nt
r
e
s
e
a
r
c
h.
3.
P
R
O
B
L
EM
S
TA
TE
M
EN
T
W
i
de
v
a
r
a
i
e
t
y
of
h
o
m
e
a
ppl
i
a
n
c
e
s
de
v
e
l
o
pe
d
by
s
e
v
e
r
a
l
c
o
m
pa
n
i
e
s
,
o
f
fe
r
i
n
g
di
f
f
e
r
e
n
t
f
e
a
t
ur
e
s
of
t
h
e
s
a
m
e
de
v
i
c
e
s
b
ut
in
di
f
f
e
r
e
n
t
w
o
r
ki
n
g
c
o
n
d
i
t
i
o
n
s
,
t
ha
t
m
a
k
i
n
g
it
d
i
f
f
i
c
ul
t
to
f
i
n
d
t
h
e
b
e
s
t
de
v
i
c
e
f
i
t
.
T
h
e
pr
o
po
s
e
d
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
h
e
l
ps
us
e
r
s
to
f
i
n
d
t
h
e
b
e
s
t
f
i
t
de
v
i
c
e
s
t
h
a
t
m
a
t
c
h
t
h
e
i
r
n
e
e
ds
,
i
nt
e
r
e
s
t
s
a
n
d
w
e
a
t
h
e
r
c
o
n
di
t
i
o
n
s
.
Th
is
p
r
o
po
s
e
d
s
y
s
t
e
m
is
t
h
e
o
n
l
y
o
n
e
s
y
s
t
e
m
to
gi
v
e
r
e
c
o
m
m
e
n
da
t
i
o
n
s
t
ha
t
a
r
e
m
o
r
e
a
c
c
ur
a
t
e
us
i
ng
n
e
w
c
o
m
b
i
n
a
t
i
o
n
of
a
l
go
r
i
t
h
e
m
s
a
n
d
n
e
w
c
o
m
b
i
n
a
t
i
o
n
of
pa
r
a
m
e
t
e
r
s
to
a
c
h
i
e
v
e
t
h
e
s
e
ob
j
e
c
t
i
ve
s
.
4.
R
ES
EA
R
C
H
O
B
JEC
TI
V
ES
D
e
s
i
gn
a
n
d
i
m
p
l
e
m
e
nt
a
r
e
c
o
m
m
e
n
da
t
i
o
n
s
y
s
t
e
m
ha
s
t
h
e
a
b
i
l
i
t
y
to
de
a
l
w
i
t
h
l
a
rge
n
u
m
b
e
r
of
de
v
i
c
e
s
a
n
d
r
e
c
o
m
m
e
n
d
t
h
e
b
e
s
t
c
h
o
i
c
e
r
e
ga
r
di
ng
to
t
h
e
us
e
r
p
r
e
f
e
r
e
n
c
e
s
,
w
e
a
t
h
e
r
c
o
n
di
t
i
o
n
s
a
nd
de
v
i
c
e
s
pr
o
pe
rt
i
e
s
.
5.
R
ES
EA
R
C
H
M
ET
H
O
D
O
L
O
G
Y
To
b
ui
l
d
t
h
e
de
v
i
c
e
s
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
,
we
n
e
e
d
to
c
re
a
t
e
a
da
t
a
b
a
s
e
t
ha
t
c
o
n
t
a
i
n
s
t
h
e
de
v
i
c
e
s
pr
o
pe
rt
i
e
s
a
nd
w
e
a
t
h
e
r
c
o
n
d
i
t
i
o
n
s
(
t
e
m
pe
r
a
t
u
r
e
a
n
d
h
u
m
i
d
i
t
y
).
T
h
e
da
t
a
c
o
l
l
e
c
t
e
d
a
nd
s
t
o
r
e
d
in
t
h
e
da
t
a
b
a
s
e
de
s
i
gn
e
d
for
t
hi
s
pu
rpo
s
e
.
T
h
e
b
l
o
c
k
di
a
g
r
a
m
of
t
h
e
p
r
o
po
s
e
d
r
e
c
o
m
m
e
n
da
t
i
o
n
s
y
s
t
e
m
is
s
h
o
w
n
in
F
i
g
u
r
e
1.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
H
om
e
ap
pl
i
anc
e
s
r
e
c
om
m
e
ndat
i
on
s
y
s
t
e
m
b
as
e
d
on
w
e
at
he
r
i
nf
or
m
at
i
on
us
i
n
g
…
(
B
as
i
m
A
m
e
r
J
aa
f
ar
)
1637
F
i
g
u
r
e
1
.
B
l
o
c
k
di
a
g
r
a
m
of
t
h
e
p
r
o
po
s
e
d
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
5.
1
.
D
atab
as
e
of
d
e
v
i
c
e
s
T
h
e
d
a
t
a
b
a
s
e
c
o
n
t
a
i
n
s
a
s
e
t
of
de
v
i
c
e
s
(200
de
v
i
c
e
s
).
It
is
c
o
l
l
e
c
t
e
d
f
r
o
m
d
i
f
fe
r
e
nt
c
o
m
pa
ni
e
s
'
w
e
bs
i
t
e
s
;
e
a
c
h
de
v
i
c
e
h
a
s
a
s
e
t
of
pr
o
pe
r
t
i
e
s
,
i
n
c
l
ud
i
n
g
t
e
m
pe
ra
t
u
r
e
a
nd
h
u
m
i
d
i
t
y
of
o
pe
r
a
t
i
o
n
.
T
h
e
s
e
pr
o
pe
r
t
i
e
s
r
e
p
r
e
s
e
nt
t
h
e
s
t
a
n
d
a
r
d
c
o
n
di
t
i
o
n
s
in
w
hi
c
h
t
h
e
de
v
i
c
e
w
o
r
ks
.
In
s
o
m
e
c
i
t
i
e
s
,
t
h
e
t
e
m
pe
ra
t
u
r
e
is
t
h
e
e
ff
e
c
t
i
v
e
f
a
c
t
o
r
in
t
h
e
r
e
c
o
m
m
e
n
de
d
s
y
s
t
e
m
,
a
nd
hum
i
di
t
y
is
l
e
s
s
e
ffe
c
t
i
ve
a
n
d
v
i
c
e
ve
r
s
a
.
T
h
e
r
e
f
o
r
e
,
we
n
e
e
d
to
c
a
l
c
ul
a
t
e
t
h
e
s
pe
c
i
a
l
w
e
i
ght
s
for
e
a
c
h
f
a
c
t
o
r
.
T
h
e
w
e
i
gh
t
of
t
h
e
p
r
o
pe
rt
i
e
s
of
e
a
c
h
de
v
i
c
e
is
c
a
l
c
ul
a
t
e
d
a
c
c
o
r
di
ng
to
t
h
e
a
s
s
h
o
w
n
i
n
1
.
(
(
)
(
)
)
(1)
5.
2.
G
e
o
l
o
c
ati
o
n
i
n
fo
r
m
ati
o
n
w
e
ath
e
r
T
h
e
go
a
l
s
of
da
t
a
m
i
n
i
ng
a
r
e
to
p
r
o
v
i
de
a
c
c
ur
a
t
e
k
n
o
w
l
e
dge
in
t
h
e
f
o
r
m
of
r
u
l
e
s
,
t
e
c
hn
i
q
ue
s
,
v
i
s
ua
l
c
ha
r
t
s
a
n
d
us
e
f
ul
m
o
de
l
s
fo
r
w
e
a
t
h
e
r
pa
ra
m
e
t
e
r
s
t
hr
o
ug
h
t
d
a
t
a
s
e
t
s
[16]
.
T
h
e
p
r
o
po
s
e
d
r
e
c
o
m
m
e
n
d
a
t
i
o
n
s
y
s
t
e
m
r
e
l
i
e
s
on
w
e
a
t
h
e
r
i
n
f
o
r
m
a
t
i
o
n
(t
e
m
pe
r
a
t
u
r
e
a
n
d
h
u
m
i
d
i
t
y
)
fo
r
di
f
fe
r
e
n
t
c
i
t
i
e
s
.
In
s
o
m
e
c
i
t
i
e
s
,
t
h
e
t
e
m
pe
r
a
t
u
r
e
is
t
h
e
b
i
gge
s
t
f
a
c
t
o
r
in
t
h
e
r
e
c
o
m
m
e
n
de
d
s
y
s
t
e
m
,
a
n
d
h
u
m
i
d
i
t
y
is
c
o
n
s
t
a
n
t
a
nd
v
i
c
e
v
e
r
s
a
.
T
h
e
r
e
f
o
r
e
,
we
n
e
e
d
to
c
a
l
c
ul
a
t
e
t
h
e
s
pe
c
i
a
l
w
e
i
ght
s
for
w
e
a
t
h
e
r
i
n
f
o
r
m
a
t
i
o
n
for
t
h
e
c
i
t
y
a
n
d
t
h
e
c
a
l
c
ul
a
t
i
o
n
of
t
h
e
s
pe
c
i
a
l
w
e
i
gh
t
s
for
e
a
c
h
de
v
i
c
e
(i
.
e
.
r
e
s
ul
t
i
ng
f
r
o
m
t
h
e
t
e
m
pe
r
a
t
u
r
e
a
n
d
h
u
m
i
d
i
t
y
of
t
h
e
de
v
i
c
e
)
as
in
t
h
e
a
s
s
h
o
w
n
in
2
a
n
d
F
i
g
u
r
e
2.
(
(
)
(
)
)
(2)
as
s
h
o
w
n
in
F
i
gu
r
e
2.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2
502
-
47
52
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
,
V
o
l
.
19
,
N
o
.
3,
S
e
pt
e
m
b
e
r
2
020
:
163
5
-
164
2
1638
F
i
g
u
r
e
2
.
G
e
o
l
o
c
a
t
i
o
n
i
n
f
o
r
m
a
t
i
o
n
w
e
a
t
h
e
r
e
xt
ra
c
t
i
o
n
a
nd
w
e
i
g
h
t
c
o
m
put
i
ng
5.
3.
El
b
o
w
m
e
th
o
d
T
h
e
b
a
s
i
c
c
o
n
c
e
p
t
of
t
h
e
E
l
b
o
w
m
e
t
h
o
d
is
to
ut
i
l
i
z
e
t
he
s
q
u
a
r
e
of
t
h
e
d
i
s
t
a
nc
e
b
e
t
w
e
e
n
t
h
e
s
a
m
p
l
e
po
i
nt
s
f
o
c
us
e
s
on
e
a
c
h
c
l
us
t
e
r
a
nd
t
he
c
e
nt
r
o
i
d
of
t
h
e
c
l
us
t
e
r
to
gi
v
e
a
p
r
o
g
re
s
s
i
o
n
of
K
(
i
.
e
.
nu
m
b
e
r
of
c
l
us
t
e
r)
v
a
l
ue
.
T
h
e
s
u
m
of
s
qu
a
r
e
d
e
rr
o
rs
(S
S
E
)
is
u
t
i
l
i
z
e
as
a
pe
r
f
o
rm
a
n
c
e
s
ho
w
t
ha
t
e
a
c
h
c
l
us
t
e
r
is
c
l
o
s
e
r.
At
t
h
e
po
i
nt
w
h
e
n
c
l
us
t
e
r
s
nu
m
b
e
r
is
s
e
t
c
l
o
s
e
to
t
he
nu
m
b
e
r
of
t
h
e
r
e
a
l
c
l
us
t
e
r,
S
S
E
s
h
o
w
s
q
ui
c
k
do
w
nhi
l
l
.
H
o
w
e
v
e
r
,
w
i
l
l
t
u
rn
o
ut
to
be
s
l
o
w
e
r
ra
p
i
d
l
y
[
17
].
T
he
v
a
l
ue
of
k
at
w
hi
c
h
i
m
p
ro
v
e
m
e
nt
in
di
s
t
o
rt
i
o
n
de
c
l
i
ne
s
t
he
m
o
s
t
is
c
a
l
l
e
d
t
h
e
e
l
b
o
w
,
at
w
hi
c
h
we
s
h
o
u
l
d
s
t
o
p
d
i
v
i
d
i
ng
t
h
e
d
a
t
a
i
nt
o
f
u
rt
he
r
c
l
us
t
e
r
s
as
s
h
o
w
n
in
F
i
gu
re
3
[1
8
].
F
i
g
u
r
e
3
.
E
l
b
ow
m
e
t
h
o
d
for
o
pt
i
m
a
l
v
a
l
ue
of
K
Algorithm
1:
Elbow
method
for
determining
K
1.
Initialize
k
=
1
2.
Start
3.
Increase
the
value
of
k
4.
Measure
the
cost
of
optimal
quality
solution
5.
If
the
cost
of
the
solution
at
some
point
decreases
dramatically
6.
This
is
real
k
7.
End
5
.
4
.
K
-
m
e
an
s
al
go
r
i
th
m
K
-
m
e
a
n
s
is
o
n
e
of
t
h
e
m
o
s
t
po
pul
a
r
a
n
d
o
l
de
s
t
c
l
us
t
e
ri
n
g
t
e
c
hn
i
q
ue
s
a
n
d
can
be
a
ppl
i
e
d
e
v
e
n
to
l
a
r
ge
d
a
t
a
s
e
t
s
[19
].
T
h
e
K
-
m
e
a
n
s
a
l
go
r
i
t
hm
gi
v
e
s
a
s
i
m
p
l
e
m
e
t
h
o
d
to
e
xe
c
ut
e
an
a
pp
r
o
xi
m
a
t
e
s
o
l
ut
i
o
n
.
T
h
e
pu
r
po
s
e
s
b
e
h
i
nd
t
h
e
pub
l
i
c
i
t
y
of
K
-
m
e
a
n
s
a
r
e
t
h
e
s
i
m
pl
i
c
i
t
y
a
n
d
e
a
s
i
n
e
s
s
of
e
xe
c
ut
i
o
n
,
a
da
p
t
a
b
i
l
i
t
y
to
s
pa
r
e
da
t
a
,
i
nt
e
rm
i
n
gl
i
n
g
s
pe
e
d
a
nd
s
c
a
l
a
b
i
l
i
t
y
[20].
T
h
e
di
s
t
a
n
c
e
w
i
l
l
us
e
as
t
h
e
s
c
a
l
e
gi
v
e
n
for
K
c
l
a
s
s
e
s
in
t
h
e
da
t
a
s
e
t
,
c
a
l
c
ul
a
t
e
t
h
e
di
s
t
a
n
c
e
m
e
a
n
,
t
h
e
i
ni
t
i
a
l
c
e
n
t
r
o
i
d
gi
v
e
n,
w
i
t
h
e
a
c
h
c
a
t
e
go
r
y
de
s
c
r
i
b
e
d
by
t
h
e
c
e
n
t
r
o
i
d.
F
o
r
a
gi
v
e
n
da
t
a
s
e
t
X
t
ha
t
c
o
n
t
a
i
n
s
m
ul
t
i
d
i
m
e
ns
i
o
n
a
l
da
t
a
po
i
n
t
s
a
nd
a
c
l
a
s
s
K
to
be
di
v
i
de
d,
E
uc
l
i
de
a
n
di
s
t
a
n
c
e
is
de
f
i
n
e
d
as
an
i
ndi
c
a
t
o
r
of
s
i
m
i
l
a
ri
t
y
a
n
d
g
r
o
up
t
a
r
ge
t
s
r
e
duc
e
t
h
e
s
u
m
of
s
qua
r
e
s
of
di
f
fe
r
e
nt
o
bj
e
c
t
s
;
t
h
i
s
m
e
a
n
s
t
h
a
t
it
r
e
duc
e
s
[21].
K
-
M
e
a
n
s
a
l
go
r
i
t
hm
is
a
w
i
de
l
y
us
e
d
a
l
go
r
i
t
hm
for
i
de
nt
i
fy
i
n
g
c
l
us
t
e
r
s
b
e
c
a
us
e
it
h
a
s
a
c
c
ura
t
e
c
a
l
c
ul
a
t
i
o
n
s
,
e
a
s
y
to
us
e
a
n
d
m
e
e
t
s
t
h
e
n
e
e
ds
of
us
e
b
e
c
a
us
e
it
is
f
l
e
xi
b
l
e
to
m
o
di
fy
[22].
Evaluation Warning : The document was created with Spire.PDF for Python.
In
do
n
e
s
i
a
n
J
E
l
e
c
E
ng
&
Co
m
p
S
c
i
IS
S
N
:
2502
-
4752
H
om
e
ap
pl
i
anc
e
s
r
e
c
om
m
e
ndat
i
on
s
y
s
t
e
m
b
as
e
d
on
w
e
at
he
r
i
nf
or
m
at
i
on
us
i
n
g
…
(
B
as
i
m
A
m
e
r
J
aa
f
ar
)
1639
A
c
l
us
t
e
r
i
ng
a
l
go
ri
t
hm
,
it
ga
t
h
e
r
s
v
a
r
i
o
us
i
n
f
o
r
m
a
t
i
o
n
de
pe
n
de
n
t
on
t
h
e
f
e
a
t
u
r
e
s
a
n
d
p
r
o
pe
r
t
i
e
s
of
t
h
a
t
i
n
f
o
r
m
a
t
i
o
n
a
n
d
t
h
e
c
l
us
t
e
ri
n
g
p
r
o
c
e
dur
e
by
di
m
i
n
i
s
h
i
n
g
t
h
e
s
e
pa
r
a
t
i
o
n
s
b
e
t
w
e
e
n
da
t
a
c
e
nt
e
r.
T
h
e
b
l
o
c
k
di
a
g
ra
m
of
t
h
e
K
-
m
e
a
n
s
s
h
o
w
n
in
F
i
gu
r
e
2.
Algorithm
2:
k
-
means
[23]
Input:
D
=
{d1,
d2,
d3,…,
dn}
:
set
of
n
numbers
of
data.
K:
The
number
of
desire
groups.
Output:
A
set
of
k
clusters.
Step
1:
Select
k
points
as
primary
centroids.
Step
2:
Repeat.
Step
3:
From
K
groups
by
assigning
every
data
point
to
the
nearest
centroid.
Step
4:
Calculate
the
centroid
of
each
cluster
so
that
the
centroid
does
not
change.
T
h
e
m
a
i
n
w
e
a
kn
e
s
s
e
s
of
K
-
m
e
a
n
s
t
h
e
n
um
b
e
r
of
c
l
us
t
e
r
s
to
be
d
e
t
e
r
m
i
n
e
by
t
h
e
us
e
r
a
nd
t
h
e
ra
n
do
m
num
b
e
r
s
e
l
e
c
t
i
o
n
a
f
fe
c
t
i
n
g
t
h
e
a
c
c
ura
c
y
of
t
h
e
c
l
us
t
e
r
r
e
s
ul
t
s
.
5.
4
.
1.
S
u
gge
s
te
d
s
o
l
v
i
n
g
o
f
k
-
m
e
an
s
w
e
a
k
n
e
s
s
p
o
i
n
ts
T
h
e
g
r
e
a
t
e
s
t
c
ha
l
l
e
ngi
n
g
p
r
o
b
l
e
m
in
t
h
e
p
a
t
t
e
rn
r
e
c
o
gn
i
t
i
o
n
f
i
e
l
d
ha
s
d
i
s
t
i
ngui
s
h
e
d
is
t
h
e
f
i
n
d
i
n
g
of
t
h
e
i
de
a
l
n
u
m
b
e
r
of
c
l
us
t
e
r
s
for
t
h
e
di
s
c
r
e
t
i
o
na
r
y
da
t
a
s
e
t
c
o
l
l
e
c
t
i
o
n
[2
4].
To
c
h
o
o
s
e
t
h
e
K
c
l
us
t
e
r
s
num
b
e
r
a
nd
t
h
e
c
e
n
t
r
o
i
d
of
t
h
e
pe
r
f
e
c
t
c
l
us
t
e
r
t
ha
t
can
be
pr
o
v
i
d
for
t
he
K
-
m
e
a
n
s
.
E
l
b
ow
t
e
c
h
ni
que
can
de
t
e
r
m
i
n
e
t
h
e
a
pp
r
o
pri
a
t
e
n
u
m
b
e
r
of
c
l
us
t
e
r
s
for
t
h
e
d
a
t
a
s
e
t
[2
5].
5.
4
.
2.
Th
e
p
r
o
p
o
s
e
d
al
go
r
i
th
m
(m
o
d
i
fi
e
d
k
-
m
e
an
s
c
l
u
s
te
r
i
n
g
al
go
r
i
th
m
)
M
o
de
l
b
ui
l
di
n
g
r
e
qu
i
r
e
t
h
e
us
i
n
g
of
a
m
o
di
f
i
e
d
c
l
us
t
e
r
i
n
g
a
l
go
ri
t
hm
us
e
d
to
a
gg
r
e
ga
t
e
h
o
us
e
h
o
l
d
a
ppl
i
a
n
c
e
s
fo
r
e
a
c
h
c
us
t
o
m
e
r.
T
h
e
p
r
o
po
s
e
d
m
e
t
h
o
d
w
o
r
ks
b
a
s
e
d
on
t
h
e
w
e
i
ght
s
a
v
e
r
a
ge
,
t
h
a
t
a
rra
n
ge
t
h
e
c
l
us
t
e
r
s
a
c
c
o
r
di
n
g
to
w
h
i
c
h
t
h
e
f
i
r
s
t
c
l
us
t
e
r
w
o
ul
d
c
o
n
t
a
i
n
t
h
e
m
o
s
t
s
ui
t
a
b
l
e
de
v
i
c
e
s
a
n
d
t
h
e
l
a
s
t
c
l
us
t
e
r
w
o
ul
d
c
o
n
t
a
i
n
t
h
e
l
e
a
s
t
a
pp
r
o
p
r
i
a
t
e
de
v
i
c
e
s
fo
r
t
h
e
us
e
r
.
D
u
ri
n
g
t
h
e
f
i
r
s
t
s
t
a
ge
,
a
da
t
a
p
r
e
-
p
r
o
c
e
s
s
i
n
g
t
e
c
hn
o
l
o
g
y
t
h
a
t
a
dde
d
d
a
t
a
w
e
i
ght
s
a
nd
n
o
rm
a
l
i
z
a
t
i
o
n
p
r
o
c
e
s
s
a
do
pt
e
d.
D
u
r
i
n
g
t
h
e
s
e
c
o
n
d
s
t
a
ge
,
t
h
e
a
v
e
ra
ge
w
e
i
gh
t
for
e
a
c
h
c
l
us
t
e
r
is
c
a
l
c
u
l
a
t
e
d.
D
u
r
i
ng
t
h
e
t
hi
r
d
s
t
a
ge
,
t
h
e
E
uc
l
i
de
a
n
di
s
t
a
n
c
e
w
i
t
h
ge
o
gra
p
hi
c
a
r
e
a
w
e
a
t
h
e
r
w
e
i
gh
t
s
a
ppl
i
e
d
to
a
rr
a
nge
t
h
e
s
e
c
l
us
t
e
r
s
.
F
o
u
rt
h
s
t
a
ge
t
he
t
hre
s
h
o
l
d
v
a
l
ue
a
pp
l
i
e
d
to
t
h
e
d
i
s
t
a
n
c
e
s
f
r
o
m
t
h
e
t
hi
rd
s
t
a
ge
.
Algorithm
3:
Name:
Modified
K
-
Means
Clustering
Algorithm
Inputs:
Weights
of
device
calculated
from
Equation
(1),
Weights
of
weather
calculated
from
Equation
(2),
Number
of
clusters
(k)
computed
from
algorithm
(1),
Threshold
value.
Output:
clusters
that
only
contain
the
required
devices.
Strat
Step1:
Weights
reading.
Step2:
Normalization.
Step3:
A
set
of
weights
as
Centroids
of
clusters
(k)
randomly
assigned.
Step4:
Calculate
the
distance
between
each
weight
and
all
Centroids,
this
process
done
by
using
the
Euclidean
distance.
Step5:
Collect
weights
to
the
nearest
Centroids.
Step6:
Calculating
new
Centroids
for
each
cluster.
Step7:
Repeat
steps
3
through
5
until
stability
occurs.
Step8:
Calculate
the
average
weights
for
each
cluster
by
calculating
the
total
weight
of
the
cluster
divided
by
the
number
of
elements
in
the
cluster.
Step9:
use
the
Euclidean
distance
between
the
weights
generated
by
from
Equation
(2)
with
the
average
weight
for
each
cluster.
Step10:
Arrange
the
clusters
from
the
lowest
distance
to
the
largest
distance.
Step11:
Cluster
suggestion
to
the
user
where
the
distance
value
from
step
9
is
less
or
equal
to
the
threshold
value.
END
A.
Co
m
put
e
a
v
e
ra
ge
w
e
i
ght
s
for
e
a
c
h
c
l
us
t
e
r
A
f
t
e
r
de
t
e
rm
i
ni
n
g
t
h
e
a
pp
r
o
p
r
i
a
t
e
n
u
m
b
e
r
of
k
in
t
h
e
E
l
b
ow
a
l
go
r
i
t
hm
m
e
t
h
o
d
a
n
d
pe
r
f
o
r
m
i
n
g
pr
o
po
s
e
d
m
e
t
h
o
d
K
-
m
e
a
n
s
,
it
w
i
l
l
p
r
o
duc
e
a
s
e
t
of
c
l
us
t
e
r
w
i
t
h
t
h
e
s
a
m
e
p
r
e
de
f
i
n
e
d
k
n
um
b
e
r.
T
h
e
go
a
l
of
t
h
e
c
l
us
t
e
r
i
ng
p
r
o
c
e
s
s
is
t
r
e
a
t
t
h
e
de
v
i
c
e
s
as
a
gr
o
up
of
s
i
m
i
l
a
r
w
e
i
ght
de
v
i
c
e
s
i
n
s
t
e
a
d
of
t
r
e
a
t
i
n
g
t
h
e
m
i
n
di
v
i
du
a
l
l
y
.
T
h
e
s
um
of
t
h
e
w
e
i
ght
s
of
t
h
e
de
v
i
c
e
s
fo
r
e
a
c
h
c
l
us
t
e
r
a
r
e
c
a
l
c
u
l
a
t
e
d
a
n
d
t
h
e
n
d
i
v
i
de
d
by
t
h
e
n
u
m
b
e
r
of
de
v
i
c
e
s
of
e
a
c
h
c
l
us
t
e
r
to
p
r
o
duc
e
a
s
e
t
of
w
e
i
gh
t
s
for
e
a
c
h
c
l
us
t
e
r
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2
502
-
47
52
In
do
n
e
s
i
a
n
J
E
l
e
c
E
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&
Co
m
p
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c
i
,
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o
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.
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,
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gh
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c
l
us
t
e
r
,
w
h
i
c
h
c
o
n
t
a
i
n
s
t
h
e
l
a
rge
s
t
di
f
fe
r
e
n
c
e
,
w
h
i
c
h
r
e
f
l
e
c
t
s
l
e
a
s
t
f
i
t
de
v
i
c
e
s
a
nd
it
is
n
o
t
p
r
e
f
e
r
r
e
d
to
w
o
r
k
in
t
h
e
s
e
w
e
a
t
h
e
r
c
o
n
di
t
i
o
n
s
.
C.
D
e
t
e
r
m
i
n
e
t
h
e
b
e
s
t
-
f
i
t
de
v
i
c
e
s
c
l
us
t
e
r
To
de
t
e
rm
i
n
e
t
h
e
b
e
s
t
f
i
t
c
l
us
t
e
rs
,
a
t
hre
s
h
o
l
d
is
us
e
d
to
de
t
e
r
m
i
n
e
g
r
o
u
ps
t
ha
t
c
o
n
t
a
i
n
de
v
i
c
e
s
c
l
o
s
e
s
t
to
a
s
pe
c
i
f
i
c
re
g
i
o
n.
T
h
e
t
hre
s
h
o
l
d
v
a
l
ue
is
c
o
m
pu
t
e
d
a
nd
t
h
e
n
t
h
e
r
e
s
u
l
t
f
r
o
m
a
pp
l
y
i
ng
t
he
E
uc
l
i
de
a
n
d
i
s
t
a
nc
e
b
e
t
w
e
e
n
t
h
e
a
v
e
ra
ge
w
e
i
g
ht
s
of
e
a
c
h
c
l
u
s
t
e
r
a
nd
t
he
w
e
i
g
ht
of
t
h
e
s
pe
c
i
f
i
e
d
r
e
gi
o
n.
If
t
h
e
r
e
s
u
l
t
i
ng
v
a
l
ue
is
l
e
s
s
t
ha
n
or
e
qu
a
l
to
t
he
t
hre
s
h
o
l
d
v
a
l
ue
,
t
he
n
de
v
i
c
e
s
in
t
hi
s
c
l
us
t
e
r
ha
v
e
a
pp
r
o
a
c
he
d
us
e
r
re
qu
i
r
e
m
e
nt
s
.
6.
R
ES
U
LTS
A
N
D
D
I
S
C
U
S
S
I
O
N
T
h
e
p
r
o
po
s
e
d
s
y
s
t
e
m
de
ve
l
o
p
e
d
us
i
ng
C#
l
a
n
gu
a
ge
,
a
n
d
S
Q
L
da
t
a
b
a
s
e
s
us
e
d
to
s
t
o
r
e
t
h
e
i
nput
da
t
a
s
e
t
a
n
d
t
h
e
c
l
us
t
e
ri
n
g
r
e
s
ul
t
s
.
T
h
e
p
r
o
po
s
e
d
s
y
s
t
e
m
is
a
b
l
e
nd
of
m
o
di
f
i
e
d
K
-
m
e
a
n
s
a
n
d
E
l
b
ow
m
e
t
h
o
d
to
i
m
p
r
o
v
e
t
h
e
c
l
us
t
e
ri
n
g
p
r
o
c
e
s
s
to
pr
o
m
o
t
e
c
l
us
t
e
r
i
n
g
q
ua
l
i
t
y
.
T
h
e
de
v
i
c
e
s
pr
o
pe
r
t
i
e
s
da
t
a
s
e
t
is
s
ub
m
i
t
to
t
h
e
c
l
us
t
e
r
i
ng
p
r
o
c
e
s
s
,
t
h
e
i
n
t
i
a
l
n
u
m
b
e
r
of
c
l
us
t
e
r
s
(K
)
is
de
t
e
rm
i
n
d
by
E
l
b
ow
m
e
t
h
o
d
.
K
pa
s
s
e
d
to
t
h
e
m
o
di
f
i
e
d
K
-
m
e
a
n
s
c
l
us
t
e
ri
n
g
a
l
go
r
i
t
hm
.
T
h
e
m
o
di
f
i
e
d
K
-
m
e
a
n
s
a
l
go
ri
t
hm
c
a
l
c
ul
a
t
e
s
a
n
d
f
i
n
ds
t
h
e
m
o
s
t
f
i
t
t
e
d
c
l
us
t
e
r
s
of
de
v
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c
e
s
.
A
f
t
e
r
t
h
e
c
o
m
pl
e
t
i
o
n
of
t
h
e
w
o
r
k
c
l
us
t
e
r
s
for
s
i
m
i
l
a
r
de
v
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c
e
s
in
t
e
m
pe
r
a
t
u
r
e
a
nd
h
u
m
i
d
i
t
y
t
h
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n
c
a
l
c
ul
a
t
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d
,
t
h
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a
v
e
r
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ge
w
e
i
ght
of
e
a
c
h
c
l
us
t
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r
c
o
m
pa
r
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d
w
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t
h
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h
e
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v
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ra
ge
w
e
i
gh
t
of
t
h
e
r
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n
w
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a
t
h
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r
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nd
f
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n
d
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t
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l
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r
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h
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t
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nt
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n
s
t
h
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m
o
s
t
s
u
i
t
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b
l
e
de
v
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c
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s
.
A
f
t
e
r
c
l
us
t
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ri
ng
p
r
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c
e
s
s
,
e
f
f
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c
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e
n
c
y
t
e
s
t
do
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t
e
rm
i
ne
t
he
r
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l
t
s
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c
c
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ra
c
y
.
T
o
t
a
l
s
u
m
of
s
qu
a
re
d
e
rro
r
s
(S
S
E
)
for
e
a
c
h
c
l
us
t
e
r
s
h
o
w
t
h
e
b
i
g
ge
s
t
de
c
re
a
s
e
in
K
=
5
(
a
s
s
h
o
w
ni
n
F
i
g
u
r
e
4
a
nd
T
a
b
l
e
1)
.
In
t
hi
s
t
e
s
t
,
it
is
c
l
e
a
r
to
d
i
s
c
o
v
e
r
t
h
e
e
f
f
e
c
t
of
i
nt
i
a
l
c
l
us
t
e
rs
nu
m
b
e
r
w
hi
c
h
c
o
m
pu
t
e
d
by
E
l
b
o
w
m
e
t
ho
d
on
t
he
a
c
c
u
ra
c
y
of
c
l
u
s
t
e
ri
ng
p
ro
c
e
s
s
.
T
a
b
l
e
1
s
h
o
w
s
t
he
S
S
E
v
a
l
ue
in
t
he
t
e
s
t
nu
m
b
e
r
of
c
l
us
t
e
r
s
in
t
he
ra
ng
e
of
1
to
10
c
l
u
s
t
e
rs
.
F
i
gu
r
e
4
.
T
h
e
e
f
fe
c
t
of
K
o
n
c
l
us
t
e
r
i
ng
r
e
s
ul
t
s
(k=
5)
T
a
b
l
e
1
.
S
u
m
o
f
s
qua
r
e
e
rr
o
r
r
e
s
ul
t
s
f
r
o
m
e
a
c
h
num
b
e
r
of
c
l
us
t
e
r
s
N
u
m
b
e
r
o
f
Cl
u
s
t
e
r
s
Re
s
u
l
t
o
f
s
u
m
s
q
u
a
re
e
rr
o
r
fo
r
2
0
0
d
e
v
i
c
e
s
K
=
1
2
6
9
9
8
1
.
2
8
K
=
2
1
8
1
3
6
3
.
5
9
5
9
5
9
5
9
5
9
6
K
=
3
1
0
6
3
4
8
.
3
7
3
0
6
2
1
1
1
1
8
K
=
4
7
3
6
7
9
.
7
8
9
0
3
9
4
8
8
3
4
K
=
5
4
4
4
4
8
.
4
5
5
4
4
7
9
3
3
7
1
K
=
6
3
7
2
6
5
.
8
6
5
2
0
4
8
4
3
4
7
K
=
7
3
0
2
5
9
.
6
5
7
2
0
7
2
8
5
4
7
K
=
8
2
5
0
9
5
.
7
0
3
2
0
9
9
9
7
5
4
8
K
=
9
2
1
8
3
0
.
0
4
1
9
7
8
0
4
9
4
3
4
K
=
1
0
2
0
7
3
6
.
6
7
9
9
3
8
9
2
4
1
2
4
A
f
t
e
r
pe
r
f
o
r
m
i
n
g
t
h
e
c
l
us
t
e
ri
n
g
p
r
o
c
e
dur
e
,
t
h
e
t
hr
e
s
h
o
l
d
c
ut
s
of
f
to
f
i
v
e
c
l
us
t
e
r
s
of
de
v
i
c
e
s
.
T
h
e
a
v
e
ra
ge
w
e
i
gh
t
of
e
a
c
h
c
l
us
t
e
r
c
a
l
c
ul
a
t
e
d
by
f
i
n
di
n
g
t
he
t
o
t
a
l
w
e
i
g
h
t
s
of
de
v
i
c
e
s
t
h
e
n
di
v
i
de
d
it
by
t
h
e
n
u
m
b
e
r
of
de
v
i
c
e
s
in
e
a
c
h
c
l
us
t
e
r
a
s
s
h
o
w
n
i
n
T
a
b
l
e
2.
S
uppo
s
e
w
e
w
a
n
t
t
o
kn
o
w
w
h
a
t
t
h
e
a
pp
r
o
pri
a
t
e
de
v
i
c
e
s
fo
r
t
h
e
c
i
t
y
of
B
a
gh
da
d.
W
e
c
a
n
m
a
ke
a
que
r
y
a
bo
ut
t
h
e
t
e
m
pe
ra
t
u
r
e
a
n
d
h
u
m
i
d
i
t
y
fo
r
a
k
n
o
w
n
pe
r
i
o
d
a
n
d
go
t
t
h
e
r
e
s
ul
t
s
s
h
o
w
n
i
n
T
a
b
l
e
3
.
By
c
a
l
c
ul
a
t
i
ng
t
h
e
E
uc
l
i
de
a
n
di
s
t
a
n
c
e
b
e
t
w
e
e
n
t
h
e
w
e
i
gh
t
e
xt
ra
c
t
e
d
f
r
o
m
t
h
e
w
e
a
t
h
e
r
i
n
f
o
rm
a
t
i
o
n
a
n
d
w
e
i
gh
t
o
f
e
a
c
h
c
l
us
t
e
r
,
t
h
e
c
l
us
t
e
r
c
o
n
t
a
i
ni
n
g
t
h
e
m
i
n
i
m
um
d
i
s
t
a
n
c
e
b
e
t
w
e
e
n
o
t
h
e
r
c
l
us
t
e
r
s
w
i
l
l
b
e
t
h
e
b
e
s
t
c
l
us
t
e
r
c
o
nt
a
i
n
i
n
g
t
h
e
a
pp
r
o
pri
a
t
e
de
v
i
c
e
fo
r
t
hi
s
c
i
t
y
a
s
s
h
o
w
n
i
n
T
a
b
l
e
4.
T
h
e
r
e
s
ul
t
s
s
h
o
w
n
i
n
T
a
b
l
e
4
s
h
o
w
t
h
a
t
t
h
e
f
o
ur
t
h
g
r
o
up
c
o
n
t
a
i
n
s
l
e
s
s
t
ha
n
t
h
e
t
hr
e
s
h
o
l
d
v
a
l
ue
(t
hr
e
s
h
o
l
d
v
a
l
ue
=
5)
c
o
m
pa
r
e
d
t
o
o
t
h
e
r
gr
o
ups
r
e
s
ul
t
i
n
g
f
r
o
m
t
h
e
E
uc
l
i
de
a
n
d
i
s
t
a
n
c
e
s
i
n
c
e
t
h
e
o
t
h
e
r
gr
o
ups
h
a
v
e
a
di
s
t
a
n
c
e
g
r
e
a
t
e
r
t
ha
n
t
h
e
t
h
r
e
s
h
o
l
d
v
a
l
ue
.
A
c
c
o
r
di
ng
t
o
t
h
e
p
r
e
v
i
o
us
r
e
s
ul
t
s
,
t
h
e
da
t
a
Cl
us
t
e
r
4
c
o
n
t
a
i
n
i
ng
t
h
e
r
e
c
o
m
m
e
n
de
d
de
v
i
c
e
s
s
h
ow
n
a
c
c
o
r
di
n
g
t
o
t
h
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w
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a
t
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r
d
a
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a
f
o
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h
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c
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d
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c
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nput
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t
a
s
e
t
a
s
s
h
o
w
n
i
n
T
a
b
l
e
5.
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4
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a
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c
ul
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a
nd
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ght
w
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u
s
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r
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u
m
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r
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v
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g
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e
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g
h
t
of
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g
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t
s
Re
s
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l
t
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1
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a
b
l
e
5
.
T
h
e
de
v
i
c
e
s
in
c
l
us
t
e
r
4
D
e
v
i
c
e
n
u
m
b
e
r
T
e
m
p
e
ra
t
u
re
H
u
m
i
d
i
t
y
D
e
v
i
c
e
n
u
m
b
e
r
T
e
m
p
e
ra
t
u
re
H
u
m
i
d
i
t
y
1
15
C°
39%
14
20
C°
15%
2
16
C°
66%
15
20
C°
13%
3
17
C°
40%
16
21
C°
35%
4
18
C°
61%
17
23
C°
29%
5
33
C°
44%
18
24
C°
35%
6
34
C°
67%
19
25
C°
40%
7
37
C°
66%
20
28
C°
70%
8
38
C°
61%
21
28
C°
73%
9
39
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66%
22
29
C°
71%
10
39
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55%
23
30
C°
53%
11
39
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48%
24
33
C°
44%
12
19
C°
33%
25
24
C°
70%
13
19
C°
40%
26
24
C°
76%
7.
LI
M
I
TA
TI
O
N
S
O
F
P
R
O
P
O
S
ED
S
Y
S
TE
M
A
m
o
n
g
t
h
e
di
f
f
i
c
ul
t
i
e
s
e
n
c
o
un
t
e
r
e
d
in
t
h
e
pa
pe
r
is
t
h
e
a
b
s
e
n
c
e
of
a
s
t
a
n
d
a
r
d
da
t
a
b
a
s
e
a
nd
of
t
e
n
t
h
e
c
h
a
ra
c
t
e
ri
s
t
i
c
s
of
t
h
e
de
v
i
c
e
s
(t
e
m
pe
r
a
t
u
r
e
a
n
d
hum
i
di
t
y
)
a
r
e
n
o
t
a
v
a
i
l
a
b
l
e
in
s
t
a
n
d
a
r
di
z
e
d
uni
t
s
of
m
e
a
s
u
r
e
m
e
nt
,
so
t
h
e
r
e
s
e
a
r
c
h
r
e
qu
i
r
e
s
de
s
i
g
n
,
i
m
p
l
e
m
e
nt
a
t
i
o
n,
a
n
d
da
t
a
c
o
l
l
e
c
t
i
o
n
of
t
a
r
ge
t
e
d
de
v
i
c
e
s
.
O
n
e
of
t
h
e
w
e
a
kn
e
s
s
po
i
n
t
s
of
t
h
i
s
s
y
s
t
e
m
is
t
h
a
t
it
n
e
gl
e
c
t
e
d
t
h
e
c
o
n
s
um
pt
i
o
n
of
e
l
e
c
t
r
i
c
a
l
e
n
e
rgy
a
n
d
t
h
e
pr
i
c
e
of
e
a
c
h
de
v
i
c
e
.
T
hi
s
i
m
p
r
o
v
e
m
e
n
t
m
us
t
be
m
a
ke
to
t
h
e
s
y
s
t
e
m
to
be
m
o
r
e
i
n
c
l
us
i
v
e
of
t
h
e
v
a
r
i
a
b
l
e
s
t
h
a
t
p
l
a
y
a
r
o
l
e
in
de
t
e
r
m
i
n
i
ng
t
h
e
us
e
r
r
e
qu
i
r
e
m
e
n
t
s
for
t
h
e
de
v
i
c
e
s
.
8.
C
O
N
C
LU
S
I
O
N
A
N
D
F
U
TU
R
E
W
O
R
K
S
T
h
i
s
pa
pe
r
p
r
e
s
e
nt
a
r
e
c
o
m
m
e
n
da
t
i
o
n
s
y
s
t
e
m
fo
r
t
h
e
b
e
s
t
e
l
e
c
t
r
i
c
a
l
a
pp
l
i
a
n
c
e
s
s
ui
t
a
b
l
e
fo
r
a
s
pe
c
i
f
i
c
c
i
t
y
b
a
s
e
d
on
w
e
a
t
h
e
r
i
n
f
o
r
m
a
t
i
o
n,
de
v
i
c
e
pr
o
pe
r
t
i
e
s
,
a
n
d
us
e
r
p
r
e
f
e
r
e
n
c
e
s
.
T
h
e
s
y
s
t
e
m
t
e
s
t
e
d
on
a
s
e
t
of
de
v
i
c
e
s
(200
de
v
i
c
e
s
),
w
h
e
r
e
t
h
e
r
e
s
ul
t
s
o
b
t
a
i
n
e
d
f
r
o
m
t
h
e
s
y
s
t
e
m
s
h
o
w
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d
t
ha
t
t
h
e
y
a
r
e
m
o
r
e
a
c
c
ur
a
t
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t
ha
n
t
r
a
d
i
t
i
o
n
a
l
a
l
go
r
i
t
hm
s
.
T
h
e
r
e
s
ul
t
s
of
t
h
e
s
y
s
t
e
m
t
e
s
t
e
d
w
i
t
h
o
n
e
of
t
h
e
m
e
t
h
o
ds
for
e
v
a
l
ua
t
i
n
g
t
h
e
c
l
us
t
e
r
,
w
h
i
c
h
is
t
h
e
S
i
l
h
o
ue
t
t
e
t
hr
o
ug
h
t
h
e
c
a
l
c
ul
a
t
i
o
n
of
i
n
t
e
r
a
n
d
i
nt
r
a
c
l
us
t
e
r
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n
d
g
a
v
e
a
v
a
l
ue
(0.
60
9)
w
i
t
h
a
s
m
a
l
l
r
u
n
t
i
m
e
(8.
45
s
e
c
o
n
ds
).
T
h
e
i
nt
i
a
l
num
b
e
r
of
c
l
us
t
e
r
s
e
ffe
c
t
s
c
l
e
a
r
l
y
t
h
e
c
l
us
t
e
ri
n
g
r
e
s
ul
t
s
a
n
d
t
h
e
n
t
h
e
a
c
c
ur
a
c
y
of
s
y
s
t
e
m
r
e
c
o
m
m
a
n
d
a
t
i
o
n
s
.
It
is
n
e
c
e
s
s
a
r
y
to
t
e
s
t
t
h
e
s
y
s
t
e
m
on
a
h
uge
da
t
a
b
a
s
e
of
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v
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c
e
s
to
pr
o
v
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t
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e
f
f
i
c
i
e
n
c
y
of
t
h
e
s
y
s
t
e
m
.
R
EF
ER
EN
C
ES
[
1]
L
u,
J
i
e
,
et
a
l
.
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e
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m
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m
s
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,
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-
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,
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.
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2]
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put
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l
.
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-
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IS
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In
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1642
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3]
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.
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.
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.
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a
m
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h,
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.
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.
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a
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r
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l
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(
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[
4]
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a
w
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w
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.
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2,
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o
.
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,
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.
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-
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,
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[
5]
S
ha
h
,
J
a
i
m
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e
l
M
.
,
a
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o
ke
s
h
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a
h
u.
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h
y
br
i
d
b
a
s
e
d
r
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c
o
m
m
e
nda
t
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o
n
s
y
s
t
e
m
ba
s
e
d
on
c
l
us
t
e
r
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a
nd
a
s
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o
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a
t
i
o
n
,
"
B
i
na
r
y
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ou
r
na
l
of
D
a
t
a
M
i
n
i
ng
&
N
e
t
w
or
k
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ng
,
v
o
l
5
,
no
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1
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p
p.
36
-
40
,
20
15
.
[
6]
S
ha
r
m
a
,
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a
l
i
t
a
,
a
nd
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nj
u
G
e
r
a
.
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s
ur
v
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y
of
r
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c
o
m
m
e
nda
t
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o
n
s
y
s
t
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m
:
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s
e
a
r
c
h
c
ha
l
l
e
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e
s
,
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I
n
t
e
r
na
t
i
o
nal
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our
nal
of
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i
ne
e
r
i
ng
T
r
e
nd
s
a
nd
T
e
c
hno
l
og
y
(
I
J
E
T
T
)
,
v
o
l
.
4
,
no
.
5
,
pp
.
1
989
-
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,
201
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.
[
7]
R
i
c
c
i
,
F
r
a
nc
e
s
c
o
,
L
i
o
r
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o
ka
c
h,
a
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B
r
a
c
ha
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ha
pi
r
a
.
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nt
r
o
duc
t
i
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n
to
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e
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o
m
m
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nde
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s
y
s
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e
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s
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n
dbo
o
k
,
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Spr
i
nge
r
,
B
o
s
t
o
n,
M
A
,
pp
.
1
-
35
,
2
011
.
[
8]
D
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e
pa
na
,
R.
"
O
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m
pl
e
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e
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A
l
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M
a
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bi
s
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s
,
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l
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12
,
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,
pp
.
4
21
-
430
,
2
017
.
[
9]
Y
ua
n,
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h
unhu
i
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a
nd
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a
i
t
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o
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a
ng
.
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r
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h
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p
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p.
22
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.
[
10]
O
r
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r
l
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s
.
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r
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a
m
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m
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r
oc
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ngs
of
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he
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nt
h
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C
M
SI
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K
D
D
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n
t
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r
nat
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o
nal
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onf
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now
l
e
dge
di
s
c
ov
e
r
y
a
nd
da
t
a
m
i
ni
n
g
,
pp
.
823
-
8
28
,
2
004
.
[
11]
J
y
o
t
i
,
A
ka
nks
ha
,
et
a
l
.
"
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e
a
r
by
P
r
o
duc
t
R
e
c
o
m
m
e
nda
t
i
o
n
S
y
s
t
e
m
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a
s
e
d
on
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s
e
r
s
R
a
t
i
ng
,
"
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n
t
.
J
.
S
c
i
.
R
e
s
.
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om
p
ut
.
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i
.
E
ng
.
I
n
f
.
T
e
c
hn
ol
,
v
o
l
.
5
,
p
p.
96
3
-
968
,
2019
.
[
12]
S
y
a
kur
,
M.
A
.
,
et
a
l
.
"
I
nt
e
g
r
a
t
i
o
n
k
-
m
e
a
ns
c
l
us
t
e
r
i
ng
m
e
t
ho
d
a
n
d
e
l
bo
w
m
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t
ho
d
f
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d
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c
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t
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he
be
s
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l
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l
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t
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r
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O
P
C
o
nf
e
r
e
nc
e
Se
r
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e
s
:
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a
t
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r
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al
s
S
c
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nc
e
and
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ne
e
r
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ng
,
V
o
l
.
336
,
N
o
.
1
,
2
018
.
[
13]
P
ho
r
a
s
i
m
,
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ho
ng
s
a
v
a
nh,
a
nd
L
a
s
he
ng
Y
u.
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o
v
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e
s
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o
m
m
e
nda
t
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n
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y
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m
us
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bo
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m
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ns
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n
t
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on
al
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our
n
al
of
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dv
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nc
e
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om
put
e
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ar
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h
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v
ol
.
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,
no
.
29
,
p
.
52
,
2
017
.
[
14]
G
a
r
g
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s
h
a
l
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nd
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t
u
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i
w
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r
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.
"
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y
br
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d
m
a
s
s
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v
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pe
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ne
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ur
s
e
(
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O
C
)
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m
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y
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t
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m
u
s
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a
c
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ne
l
e
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r
ni
ng
,
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E
T
C
o
nf
e
r
e
nc
e
P
r
oc
e
e
di
ng
s
,
p
.
11
(
5
.
)
-
11
(
5.
)
,
2016
.
[
15]
O
y
e
l
a
de
,
O.
J
.
,
O.
O.
O
l
a
di
pupo
,
a
nd
I.
C.
O
ba
g
buw
a
.
"
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ppl
i
c
a
t
i
o
n
of
k
M
e
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ns
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l
us
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pr
e
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c
t
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n
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ude
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t
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a
r
X
i
v
pr
e
pr
i
nt
a
r
X
i
v
:
1002.
24
25
,
20
10.
[
16]
T
a
l
i
b
,
M.
R
a
m
z
a
n
,
et
a
l
.
"
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ppl
i
c
a
t
i
o
n
of
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a
t
a
M
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ni
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T
e
c
hni
q
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in
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h
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a
t
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A
na
l
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s
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n
t
e
r
na
t
i
ona
l
J
our
nal
of
C
om
pu
t
e
r
S
c
i
e
nc
e
and
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e
t
w
or
k
Se
c
u
r
i
t
y
,
v
o
l
.
17
,
no
.
6
,
pp.
22
-
28
,
201
7
.
[
17]
K
o
di
na
r
i
y
a
,
T
r
upt
i
M
.
,
a
nd
P
r
a
s
ha
nt
R.
M
a
kw
a
na
.
"
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e
v
i
e
w
on
de
t
e
r
m
i
n
i
ng
num
be
r
of
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l
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-
M
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n
s
C
l
us
t
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r
i
ng
,
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n
t
e
r
na
t
i
ona
l
J
ou
r
na
l
,
v
o
l
.
1
,
no
.
6
,
p
p.
90
-
95
,
20
13
.
[
18]
L
a
ng
t
a
ng
e
n,
H
a
ns
P
e
t
t
e
r
.
"
N
um
e
r
i
c
a
l
c
o
m
put
i
ng
in
py
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ho
n
,
"
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y
t
hon
s
c
r
i
pt
i
ng
f
or
c
om
p
ut
a
t
i
ona
l
s
c
i
e
nc
e
,
pp.
13
1
-
181
,
2
006
.
[
19]
D
a
ng
a
na
n
,
A
l
v
i
nc
e
nt
E
.
,
A
r
i
e
l
M.
S
i
s
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a
n
d
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u
j
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P.
M
e
d
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n
a
.
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C
A
:
ov
e
r
l
a
p
pi
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c
l
us
t
e
r
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a
p
pl
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c
a
t
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o
n
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up
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r
v
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s
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d
a
pp
r
o
a
c
h
f
o
r
da
t
a
a
n
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l
y
s
i
s
,
"
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n
done
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i
an
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our
na
l
of
E
l
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c
t
r
i
c
al
E
ng
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ne
e
r
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ng
and
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om
pu
t
e
r
S
c
i
e
nc
e
(
I
J
E
E
C
S)
,
v
o
l
.
14
,
no
.
3
,
pp
.
147
1
-
1478
,
201
9
.
[
20]
M
o
ha
m
m
e
d
I
br
a
hi
m
a
nd
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a
h
di
N
s
a
i
f
J
a
s
i
m
.
"
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e
w
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o
di
f
i
e
d
D
y
na
m
i
c
C
l
us
t
e
r
i
ng
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l
go
r
i
t
hm
,
"
J
our
na
l
of
E
ngi
ne
e
r
i
n
g
and
A
pp
l
i
e
d
Sc
i
e
nc
e
s
,
v
o
l
.
14
,
no
.
18
,
pp
.
6
742
-
67
46
,
2019
.
[
21]
M
a
hd
i
,
M
u
ha
m
m
e
d
U.
"
D
e
t
e
r
m
i
n
i
ng
N
um
be
r
&
I
ni
t
i
a
l
S
e
e
ds
of
K
-
M
e
a
ns
C
l
u
s
t
r
i
ng
U
s
i
ng
GA
,
"
J
ou
r
na
l
of
B
aby
l
on
U
ni
v
e
r
s
i
t
y
a
nd
A
pp
l
i
e
d
Sc
i
e
nc
e
s
,
v
o
l
.
18
,
no
.
3
,
p
p
1
-
6
,
20
10.
[
2
2
]
L
a
i
l
i
y
a
h
,
S
i
t
i
,
E
k
a
w
a
t
i
Y
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l
s
i
l
v
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a
n
a
,
a
n
d
R
e
z
a
A
n
d
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e
a
.
"
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l
u
s
t
e
r
i
n
g
a
n
a
l
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s
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s
of
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e
a
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n
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s
t
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e
on
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n
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g
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n
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h
i
g
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s
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ho
o
l
s
t
u
d
e
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t
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T
E
L
K
O
M
N
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K
A
(
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l
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o
m
m
u
n
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c
a
t
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o
n
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o
m
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l
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t
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o
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c
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n
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o
n
t
r
o
l
)
,
v
o
l
.
17
,
n
o
.
3
,
p
p
.
1
4
0
9
-
1416
,
2
0
1
9
.
[
23]
K
a
r
r
a
r
,
A
bde
l
r
a
hm
a
n
E
l
s
h
a
r
i
f
,
M
a
r
w
a
A
bde
l
h
a
m
e
e
d
A
bda
l
r
a
hm
a
n,
a
nd
M
o
e
z
M
ut
a
s
i
m
A
l
i
.
"
A
ppl
y
i
ng
K
-
M
e
a
n
s
C
l
us
t
e
r
i
ng
A
l
go
r
i
t
hm
to
D
i
s
c
o
v
e
r
K
no
w
l
e
dg
e
f
r
o
m
I
ns
ur
a
nc
e
D
a
t
a
s
e
t
U
s
i
ng
W
E
K
A
T
oo
l
,
"
T
he
I
nt
e
r
nat
i
ona
l
J
our
nal
of
E
ng
i
ne
e
r
i
ng
and
S
c
i
e
nc
e
,
v
o
l
.
5
,
no
.
10
,
pp.
35
-
39
,
20
16
.
[
24]
A
r
e
l
l
a
no
-
V
e
r
de
j
o
,
J
a
v
i
e
r
,
et
a
l
.
"
E
f
f
i
c
i
e
nt
l
y
f
i
ndi
ng
t
he
o
pt
i
m
um
n
um
be
r
of
c
l
us
t
e
r
s
in
a
da
t
a
s
e
t
w
i
t
h
a
ne
w
hy
br
i
d
c
e
l
l
u
l
a
r
e
v
o
l
ut
i
o
na
r
y
a
l
g
o
r
i
t
hm
,
"
C
om
pu
t
ac
i
ón
y
S
i
s
t
e
m
as
,
v
o
l
.
18
,
no
.
2
,
pp.
3
13
-
327
,
2014
.
[
25]
B
ho
l
o
w
a
l
i
a
,
P
u
r
n
i
m
a
,
a
n
d
A
r
v
i
nd
K
um
a
r
.
"
E
B
K
-
m
e
a
n
s
:
A
c
l
us
t
e
r
i
ng
t
e
c
hni
q
ue
b
a
s
e
d
on
e
l
bo
w
m
e
t
ho
d
a
nd
k
-
m
e
a
ns
in
W
S
N
,
"
I
nt
e
r
n
at
i
ona
l
J
o
ur
na
l
of
C
om
put
e
r
A
pp
l
i
c
a
t
i
ons
,
v
o
l
.
1
05
,
no
.
9
,
2014
.
Evaluation Warning : The document was created with Spire.PDF for Python.