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I
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t c
o
u
r
s
es,
clu
b
m
e
m
b
er
s
h
ip
s
,
etc.
I
n
th
e
p
ast
,
s
o
cial
d
ata
w
a
s
ch
allen
g
in
g
to
co
llect
an
d
h
ar
d
to
co
m
e
b
y
,
an
d
m
a
n
y
p
eo
p
le
in
th
e
f
ield
li
m
ited
t
h
e
m
s
el
v
es
to
u
s
i
n
g
o
n
l
y
s
m
all
a
m
o
u
n
ts
o
f
d
ata.
H
o
w
e
v
er
,
th
i
n
g
s
h
a
v
e
c
h
an
g
ed
w
it
h
t
h
e
ad
v
e
n
t
o
f
o
n
lin
e
s
o
cial
w
eb
s
ite
s
s
u
c
h
a
s
T
w
itter
,
Face
b
o
o
k
,
an
d
F
li
ck
er
th
at
g
e
n
er
ate
m
u
c
h
m
o
r
e
d
ata
th
an
an
y
o
n
e
w
o
u
ld
ex
p
ec
t.
B
ey
o
n
d
th
e
tr
ad
itio
n
al
m
et
h
o
d
s
o
f
co
llecti
n
g
s
o
cial
d
at
a,
o
n
lin
e
d
ata
ca
n
b
e
co
llected
u
s
i
n
g
A
p
p
licatio
n
P
r
o
g
r
a
m
m
in
g
I
n
ter
f
ac
es
(
A
P
I
s
)
,
w
eb
cr
a
w
le
r
s
,
o
n
li
n
e
s
u
r
v
e
y
s
,
a
n
d
d
ep
lo
y
ed
ap
p
licatio
n
s
.
Ho
w
e
v
er
,
co
llectin
g
o
n
lin
e
s
o
cial
d
ata
is
n
o
t
al
w
a
y
s
s
tr
ai
g
h
t
f
o
r
w
ar
d
as
it
f
ac
e
s
s
o
m
e
p
r
o
b
lem
s
[
5
]
s
u
c
h
a
s
d
ea
lin
g
w
it
h
u
n
s
tr
u
ct
u
r
ed
an
d
h
eter
o
g
en
eo
u
s
d
ata,
d
y
n
a
m
ic
n
et
w
o
r
k
s
,
p
r
o
ce
s
s
i
n
g
p
o
w
e
r
an
d
d
ata
s
to
r
ag
e.
Ho
w
e
v
er
,
an
d
in
s
o
m
e
ca
s
es,
tak
i
n
g
m
ea
s
u
r
e
m
en
t
s
o
n
al
l
ac
to
r
s
in
t
h
e
r
elev
a
n
t
ac
to
r
s
et
is
n
o
t
p
o
s
s
ib
le.
T
h
er
ef
o
r
e;
tak
in
g
a
s
a
m
p
le
s
et
o
f
ac
to
r
s
f
r
o
m
t
h
e
co
m
p
le
te
s
et
b
ec
o
m
e
s
e
n
o
u
g
h
,
a
n
d
i
n
f
er
e
n
ce
ab
o
u
t
th
e
p
o
p
u
latio
n
is
m
ad
e
later
b
as
ed
o
n
th
e
s
a
m
p
le
[
6
]
.
Sa
m
p
led
d
ata
in
t
h
is
ca
s
e,
w
h
ich
ca
n
b
e
v
ie
w
ed
a
s
r
ep
r
esen
tativ
e
o
f
th
e
b
r
o
ad
er
p
o
p
u
latio
n
,
is
ca
lled
t
h
e
p
r
o
b
ab
ilit
y
s
a
m
p
le.
3.
DATA P
R
E
P
RO
CE
SS
I
NG
I
n
co
n
tr
as
t
to
o
r
g
a
n
izatio
n
s
,
wh
er
e
b
o
th
t
h
e
d
ata
a
n
d
t
h
e
h
ier
ar
ch
y
o
f
k
n
o
w
led
g
e
ar
e
w
el
l
-
o
r
g
an
ized
,
o
n
lin
e
s
o
cial
d
ata
ar
e
r
ich
w
it
h
u
s
er
-
g
e
n
er
ated
an
n
o
tat
io
n
s
an
d
f
r
ee
-
s
t
y
le
h
an
d
w
r
iti
n
g
.
G
iv
en
th
at
p
eo
p
le
i
n
o
n
lin
e
s
o
cial
p
latf
o
r
m
s
ar
e
en
t
ir
el
y
f
r
ee
to
w
r
ite
w
h
at
t
h
e
y
wan
t
[
7
]
,
d
ata
q
u
alit
y
i
n
s
u
c
h
en
v
ir
o
n
m
en
ts
r
an
g
es
f
r
o
m
v
alu
ab
le
to
co
m
m
er
cials
an
d
r
u
b
b
is
h
[
8
]
.
Fo
u
r
s
tep
s
ar
e
t
y
p
icall
y
i
n
v
o
lv
ed
in
d
ata
p
r
ep
r
o
ce
s
s
i
n
g
:
d
ata
clea
n
i
n
g
,
d
ata
in
te
g
r
a
tio
n
,
d
ata
tr
an
s
f
o
r
m
atio
n
,
an
d
d
ata
r
ed
u
ctio
n
.
W
e
w
i
ll
ad
d
r
ess
ea
ch
s
tep
in
d
etail
a
n
d
s
h
o
w
h
o
w
it
ca
n
b
e
u
s
ed
f
o
r
k
n
o
w
led
g
e
d
is
co
v
er
y
.
T
h
ese
p
r
o
ce
s
s
es
ar
e
n
o
t
is
o
lated
f
r
o
m
ea
ch
o
t
h
er
b
u
t
i
n
s
tead
ar
e
in
teg
r
al
co
m
p
o
n
e
n
ts
o
f
d
ata
p
r
ep
ar
atio
n
.
I
f
an
y
o
f
th
ese
s
tep
s
ar
e
n
o
t
p
er
f
o
r
m
ed
as
p
lan
n
ed
,
d
ata
m
i
n
i
n
g
a
l
g
o
r
ith
m
s
w
ill
n
o
t
r
u
n
an
d
w
il
l
p
r
o
b
ab
ly
g
i
v
e
u
n
ex
p
ec
ted
r
esu
lts
.
W
e
m
a
y
s
a
f
el
y
s
a
y
t
h
at
h
a
v
i
n
g
g
o
o
d
an
d
r
o
b
u
s
t
d
ata
is
m
o
r
e
i
m
p
o
r
tan
t t
h
an
h
a
v
in
g
a
n
ef
f
ic
ien
t a
l
g
o
r
ith
m
t
h
at
is
ap
p
lied
to
a
lar
g
e
q
u
an
tit
y
o
f
poor
d
ata
.
3
.
1
.
Da
t
a
c
lea
nin
g
Data
clea
n
i
n
g
(
also
k
n
o
w
n
a
s
d
ata
clea
n
s
in
g
o
r
s
cr
u
b
b
in
g
)
ai
m
s
at
r
e
m
o
v
i
n
g
n
o
is
e,
f
illi
n
g
o
u
t
m
is
s
i
n
g
v
al
u
es,
a
n
d
f
i
x
i
n
g
in
c
o
n
s
is
ten
cie
s
i
n
d
ata.
Dir
t
y
d
at
a
in
t
h
e
d
atab
ase
ca
n
b
e
t
h
e
r
esu
lt
o
f
w
r
o
n
g
d
ata
en
tr
y
,
u
p
d
ate,
o
r
tr
an
s
m
is
s
io
n
[
9
]
.
T
h
is
p
h
a
s
e
al
s
o
i
n
clu
d
es
id
en
ti
f
icatio
n
a
n
d
r
e
m
o
v
al
o
f
o
u
tlier
s
[
10
]
.
P
er
f
o
r
m
i
n
g
d
ata
clea
n
i
n
g
f
o
r
s
o
cial
n
et
w
o
r
k
d
ata
is
n
o
t
al
w
a
y
s
s
tr
ai
g
h
t
f
o
r
w
ar
d
as
i
t
ca
n
f
ac
e
s
e
v
er
al
i
s
s
u
es
[
5
]
.
Fo
r
ex
am
p
le,
it
r
eq
u
ir
es
an
u
n
d
er
s
ta
n
d
in
g
an
d
r
ea
lizatio
n
o
f
th
e
d
ata.
I
m
a
g
es,
v
id
eo
,
au
d
io
,
f
ailed
HT
T
P
r
ec
o
r
d
s
,
H
T
ML
tag
s
,
a
n
d
w
h
ite
s
p
ac
es s
h
o
u
ld
b
e
r
e
m
o
v
ed
.
Sp
a
m
d
etec
tio
n
s
h
o
u
ld
a
ls
o
b
e
p
u
r
s
u
ed
.
Ma
ch
i
n
e
lear
n
in
g
m
et
h
o
d
s
h
a
v
e
b
ee
n
co
m
m
o
n
l
y
u
s
ed
to
p
er
f
o
r
m
d
ata
clea
n
i
n
g
i
n
s
o
cial
d
ata
[
11
]
.
Fo
r
ex
a
m
p
le,
e
x
p
ec
tatio
n
m
a
x
i
m
izatio
n
w
it
h
Ga
u
s
s
ian
m
i
x
tu
r
e
m
o
d
els
i
s
u
s
ed
to
m
an
ag
e
m
is
s
in
g
d
ata,
w
h
ile
B
a
y
e
s
ian
m
o
d
els
ar
e
u
s
ed
f
o
r
clea
n
in
g
d
ata.
I
n
th
e
b
l
o
g
o
s
p
h
er
e
d
o
m
ain
,
[
12
]
p
er
f
o
r
m
ed
d
ata
clea
n
in
g
:
tr
i
m
m
i
n
g
o
u
t
w
h
ite
s
p
ac
es,
p
u
n
ctu
a
tio
n
s
,
an
d
s
to
p
w
o
r
d
s
to
b
lo
g
p
o
s
ts
.
[
13
]
p
r
o
p
o
s
ed
th
e
r
e
m
o
v
al
o
f
i
n
ac
ti
v
e
u
s
er
s
f
r
o
m
t
h
e
s
o
cial
n
et
w
o
r
k
.
I
n
t
h
e
tr
u
s
t
-
b
ased
i
n
f
o
r
m
a
tio
n
p
r
o
p
ag
atio
n
m
o
d
el
t
h
e
y
b
u
ilt,
th
e
au
t
h
o
r
s
is
o
lated
in
ac
t
iv
e
u
s
er
s
f
r
o
m
o
th
er
u
s
er
s
b
ec
a
u
s
e
th
e
y
n
ev
er
o
r
r
ar
ely
s
e
n
d
m
e
s
s
a
g
es
an
d
h
ad
litt
le
in
f
l
u
e
n
ce
o
n
in
f
o
r
m
atio
n
p
r
o
p
ag
atio
n
.
T
o
d
ea
l
w
it
h
n
o
i
s
e
in
T
w
itte
r
d
ata,
th
e
au
t
h
o
r
s
i
n
[
14
]
,
a
n
d
b
ef
o
r
e
ap
p
ly
in
g
s
en
ti
m
e
n
t
a
n
al
y
s
i
s
,
r
e
m
o
v
ed
q
u
esti
o
n
s
,
U
R
L
s
,
s
p
ec
ial
c
h
ar
ac
ter
s
as
w
ell
a
s
r
et
w
ee
ts
.
T
ar
g
etin
g
T
w
i
tter
s
er
v
ice
a
ls
o
,
[
15
]
p
r
o
p
o
s
ed
th
e
u
s
e
o
f
a
n
u
m
b
er
o
f
m
et
h
o
d
s
to
clea
n
d
ata.
T
h
e
y
u
s
ed
r
eg
u
lar
ex
p
r
ess
io
n
to
o
ls
to
r
em
o
v
e
u
n
n
ec
es
s
ar
y
ta
g
s
,
E
n
g
l
is
h
le
x
ico
n
to
f
ilter
o
u
t
w
o
r
d
s
i
n
lan
g
u
ag
e
s
o
th
er
t
h
a
n
E
n
g
li
s
h
,
a
n
d
a
n
ex
ter
n
al
s
o
u
r
ce
to
eli
m
in
a
te
s
to
p
w
o
r
d
s
.
T
h
e
y
ai
m
ed
to
d
is
co
v
er
p
eo
p
les’
o
p
in
io
n
s
b
y
u
s
in
g
to
p
ic
m
o
d
els,
s
en
ti
m
e
n
t
a
n
al
y
s
is
a
s
w
ell
a
s
g
eo
lo
ca
tio
n
i
n
f
o
r
m
atio
n
.
I
n
th
e
e
m
a
il
co
m
m
u
n
icat
io
n
s
,
d
ata
clea
n
in
g
w
as
ap
p
lied
b
y
[
16
]
to
r
em
o
v
e
n
o
n
-
es
s
en
t
ial
i
n
f
o
r
m
atio
n
f
r
o
m
t
h
e
co
r
p
u
s
,
s
u
ch
a
s
m
es
s
ag
e
I
D,
m
es
s
ag
e
ti
m
e
s
ta
m
p
,
s
e
n
d
er
an
d
r
ec
eiv
e
r
in
f
o
r
m
a
t
io
n
as
w
el
l a
s
all
m
e
s
s
a
g
es
w
it
h
i
n
v
al
id
e
m
ail
ad
d
r
ess
es.
3
.
2
.
Da
t
a
i
nte
g
ra
t
io
n
I
n
co
n
s
i
s
te
n
c
y
a
n
d
r
ed
u
n
d
an
c
y
in
s
o
cial
d
ata
ar
e
v
er
y
lik
el
y
b
ec
au
s
e
u
s
er
s
h
a
v
e
d
if
f
er
e
n
t
p
er
s
p
ec
tiv
es
a
n
d
s
h
o
w
a
d
i
f
f
er
en
t
b
eh
a
v
io
u
r
[
13
]
.
Data
i
n
teg
r
at
io
n
ai
m
s
at
co
m
b
in
i
n
g
d
ata
f
r
o
m
s
e
v
er
al
s
o
u
r
ce
s
i
n
to
co
h
er
en
t
d
ata
s
to
r
ag
e
[
10
]
.
T
h
is
task
i
s
n
o
t
s
i
m
p
le
[
9
]
as
it
r
eq
u
ir
es
ac
h
iev
i
n
g
a
m
atc
h
b
et
w
ee
n
d
if
f
er
e
n
t
s
c
h
e
m
a
t
y
p
es.
I
n
co
m
p
lete
o
r
in
ef
f
icie
n
t
d
ata
in
te
g
r
atio
n
ca
n
ca
u
s
e
i
n
co
n
s
is
ten
c
y
an
d
r
ed
u
n
d
a
n
c
y
,
Evaluation Warning : The document was created with Spire.PDF for Python.
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I
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&
C
o
m
p
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g
,
Vo
l.
9
,
No
.
4
,
A
u
g
u
s
t
201
9
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2622
w
h
ile
a
p
r
o
p
er
i
m
p
le
m
en
ta
tio
n
w
i
ll
u
n
d
o
u
b
ted
l
y
e
n
h
an
ce
a
cc
u
r
ac
y
an
d
s
p
ee
d
u
p
later
p
r
o
ce
s
s
es.
T
ec
h
n
iq
u
e
s
o
f
d
ata
in
te
g
r
atio
n
i
n
cl
u
d
e
en
tit
y
id
en
ti
f
icatio
n
,
t
u
p
le
d
ed
u
p
licatio
n
,
r
ed
u
n
d
an
c
y
a
n
d
co
r
r
elatio
n
an
al
y
s
i
s
,
as
w
ell
a
s
d
ata
v
al
u
e
co
n
f
lict d
et
ec
tio
n
an
d
r
eso
lu
t
io
n
.
3
.
3
.
Da
t
a
t
ra
ns
f
o
rm
a
t
io
n
Data
tr
an
s
f
o
r
m
atio
n
ai
m
s
a
t
c
o
n
v
e
r
ti
n
g
d
ata
i
n
to
a
u
s
ab
le
a
n
d
u
n
d
er
s
ta
n
d
ab
le
f
o
r
m
a
t.
T
h
e
g
o
al
i
s
t
o
h
av
e
m
o
r
e
ef
f
icie
n
t
d
ata
m
i
n
i
n
g
o
p
er
atio
n
s
[
10
]
.
Stra
teg
ies
f
o
r
d
ata
tr
an
s
f
o
r
m
a
tio
n
i
n
cl
u
d
e
d
ata
s
m
o
o
t
h
in
g
,
f
ea
t
u
r
e
co
n
s
tr
u
ctio
n
,
n
o
r
m
aliz
atio
n
,
d
is
cr
etiza
tio
n
,
g
en
er
aliz
atio
n
,
as
w
ell
a
s
co
n
ce
p
t
h
ier
a
r
ch
y
g
en
er
atio
n
o
f
n
o
m
i
n
al
d
ata.
T
h
ese
s
u
b
ta
s
k
s
r
eq
u
ir
e
h
u
m
a
n
s
u
p
er
v
i
s
i
o
n
an
d
ar
e
h
ig
h
l
y
d
ep
en
d
e
n
t
o
n
th
e
d
ata
b
ein
g
p
r
ep
r
o
ce
s
s
ed
[
17
]
.
Ho
w
e
v
er
,
d
ata
tr
an
s
f
o
r
m
atio
n
f
o
r
s
o
cial
d
ata
f
ac
es
a
n
u
m
b
er
o
f
c
h
alle
n
g
es
[
5
]
in
cl
u
d
in
g
:
a.
Data
h
a
v
i
n
g
d
if
f
er
e
n
t
f
o
r
m
at
s
.
T
h
is
is
b
ec
au
s
e
t
h
e
s
o
cial
d
at
a
ex
tr
ac
ted
f
r
o
m
o
n
li
n
e
w
eb
s
i
tes
ca
n
b
e
b
o
t
h
ca
teg
o
r
ical
an
d
co
n
ti
n
u
o
u
s
.
A
p
r
o
p
er
co
n
v
er
s
io
n
b
et
w
ee
n
t
h
e
t
w
o
t
y
p
e
s
,
in
t
h
is
ca
s
e,
i
s
r
eq
u
ir
ed
.
b.
A
p
p
licatio
n
d
ep
en
d
en
c
y
,
w
h
ic
h
m
ea
n
s
t
h
at
ea
c
h
d
ata
m
an
a
g
e
m
en
t to
o
l h
a
s
it
s
u
s
es a
n
d
ca
n
d
ea
l
w
it
h
o
n
l
y
p
ar
ticu
lar
t
y
p
es
o
f
d
ata.
Fo
r
e
x
a
m
p
le,
s
o
m
e
to
o
ls
(
e.
g
.
,
P
a
j
e
k
an
d
UC
I
NE
T
)
ar
e
s
tan
d
alo
n
e
ap
p
licatio
n
s
,
w
h
ile
No
d
eXL
i
s
a
u
ti
lit
y
to
o
lk
it.
So
m
e
p
ac
k
ag
e
s
ar
e
p
r
o
v
i
d
ed
w
it
h
p
r
o
g
r
a
m
m
i
n
g
u
tili
t
i
es
(
e.
g
.
,
J
UNG
an
d
SN
A
P
-
G
A
U
SS
)
w
h
er
ea
s
o
th
er
s
p
r
o
v
id
e
a
g
r
ap
h
ical
u
s
e
r
in
ter
f
ac
e
th
at
r
eq
u
ir
e
s
n
o
s
cr
ip
tin
g
u
tili
ties
.
Fin
all
y
,
s
o
m
e
to
o
ls
ar
e
f
r
ee
s
o
f
t
w
ar
e
(
e.
g
.
,
ST
R
UC
T
UR
E
an
d
StO
C
NE
T
)
w
h
ile
o
t
h
er
s
h
av
e
co
m
m
er
cial
licen
s
e
s
,
s
u
ch
a
s
I
n
Flo
w
a
n
d
So
cio
Me
tr
ic
L
in
k
A
l
y
ze
r
.
c.
Data
p
r
iv
ac
y
an
d
u
s
er
p
er
s
o
n
al
in
f
o
r
m
atio
n
t
h
at
ca
n
b
e
b
r
o
k
en
th
r
o
u
g
h
o
u
t
d
ata
tr
an
s
f
o
r
m
a
tio
n
.
On
e
o
f
th
e
r
e
m
ed
ies is
to
u
s
e
d
ata
an
o
n
y
m
izatio
n
.
Sev
er
al
s
t
u
d
ies
h
av
e
ad
d
r
ess
e
d
th
is
is
s
u
e.
Fo
r
ex
a
m
p
le,
an
d
r
eg
ar
d
in
g
d
ata
tr
an
s
f
o
r
m
atio
n
o
f
e
m
ail
co
r
p
u
s
,
[
16
]
p
r
o
p
o
s
ed
th
e
tr
an
s
f
o
r
m
atio
n
o
f
d
ata
i
n
to
a
h
i
er
ar
ch
ical
s
tr
u
c
tu
r
e,
w
h
ich
ca
n
b
e
ac
h
ie
v
ed
b
y
g
r
o
u
p
in
g
th
e
o
b
j
ec
t
-
b
ased
r
elatio
n
s
h
ip
s
o
f
p
eo
p
le
in
to
a
h
ier
ar
ch
y
.
Ob
j
ec
ts
in
th
i
s
u
n
i
f
ied
s
tr
u
ct
u
r
e
r
ep
r
esen
t
e
m
ail
s
o
r
th
r
ea
d
s
,
w
h
ile
ea
ch
o
n
e
ca
n
p
er
f
o
r
m
d
if
f
er
en
t
r
o
les,
s
u
ch
a
s
a
m
ail
s
e
n
d
er
,
m
ail
r
ec
eiv
er
,
th
r
ea
d
cr
ea
to
r
o
r
th
r
ea
d
p
ar
ticip
an
t.
T
h
e
n
e
x
t s
tep
o
f
s
o
cial
d
ata
p
r
ep
r
o
ce
s
s
in
g
w
o
u
ld
in
c
lu
d
e
f
latt
en
in
g
t
h
e
h
ier
ar
ch
y
o
f
o
b
j
ec
ts
in
to
o
n
e
s
e
lecte
d
l
ev
el,
f
o
llo
w
ed
b
y
m
u
lt
i
-
la
y
er
i
n
g
o
f
t
h
e
s
o
cial
n
et
w
o
r
k
(
s
ee
th
e
s
a
m
e
p
r
e
v
io
u
s
r
ef
er
en
ce
f
o
r
m
o
r
e
d
etail
s
)
.
T
h
e
a
u
th
o
r
s
in
[
12
]
p
er
f
o
r
m
ed
d
ata
s
te
m
m
i
n
g
on
b
lo
g
p
o
s
t
s
to
tr
an
s
f
o
r
m
a
ll
t
h
e
ter
m
s
i
n
to
t
h
eir
m
o
r
p
h
o
lo
g
ica
l
r
o
o
ts
w
ith
th
e
h
elp
o
f
t
h
e
s
t
e
m
m
er
p
o
r
tal.
I
n
a
d
if
f
er
en
t
s
tu
d
y
,
[
15
]
ap
p
lied
r
eg
u
lar
ex
p
r
es
s
io
n
tech
n
iq
u
es
to
n
o
r
m
alize
s
o
m
e
w
o
r
d
s
to
th
eir
s
tan
d
ar
d
f
o
r
m
.
T
h
e
y
also
ap
p
lied
P
o
r
te
r
s
te
m
m
i
n
g
to
s
te
m
w
o
r
d
s
i
n
to
a
u
n
i
f
ied
f
o
r
m
.
3
.
4
.
Da
t
a
r
educt
io
n
D
ata
r
ed
u
ctio
n
ai
m
s
at
r
ed
u
cin
g
t
h
e
s
ize
o
f
d
ata
w
h
ile
k
ee
p
in
g
i
n
f
o
r
m
atio
n
lo
s
s
at
a
m
i
n
i
m
u
m
[
10
]
.
T
ec
h
n
iq
u
es o
f
d
ata
r
ed
u
ctio
n
i
n
clu
d
e:
a.
Di
m
e
n
s
io
n
alit
y
r
ed
u
ctio
n
:
r
ed
u
cin
g
t
h
e
n
u
m
b
er
o
f
a
ttrib
u
tes
o
r
r
an
d
o
m
v
ar
iab
les
b
y
u
s
in
g
tec
h
n
iq
u
e
s
s
u
c
h
as
p
r
in
cip
al
co
m
p
o
n
e
n
t
an
al
y
s
is
,
w
a
v
elet
tr
an
s
f
o
r
m
a
tio
n
,
attr
ib
u
te
s
u
b
s
et
s
elec
tio
n
an
d
attr
ib
u
t
e
cr
ea
tio
n
.
T
ex
t
d
ata
ex
tr
ac
te
d
f
r
o
m
o
n
l
in
e
s
o
cial
n
e
t
wo
r
k
s
ca
n
b
e
e
x
tr
e
m
el
y
s
p
a
r
s
e
an
d
h
ig
h
-
d
i
m
en
s
io
n
al
[
18
]
.
Hig
h
d
i
m
en
s
io
n
alit
y
t
y
p
ica
ll
y
m
ea
n
s
t
h
at
th
er
e
ar
e
1
6
o
r
m
o
r
e
d
ata
attr
ib
u
tes.
I
n
s
u
c
h
d
ata
o
r
ien
tatio
n
s
,
t
h
e
n
at
u
r
e
o
f
g
eo
m
etr
ical
o
b
j
ec
ts
an
d
t
h
e
co
n
ce
p
t
o
f
p
r
o
x
i
m
it
y
ar
e
n
o
t
t
h
e
s
a
m
e
as
t
w
o
o
r
th
r
ee
d
i
m
en
s
io
n
s
.
Data
cle
an
in
g
,
w
h
ic
h
ai
m
s
a
t
r
e
m
o
v
i
n
g
u
n
d
esire
d
co
n
ten
t,
ca
n
b
e
co
n
s
id
er
ed
o
n
e
m
et
h
o
d
f
o
r
r
ed
u
cin
g
d
ata
s
ize.
b.
Nu
m
er
o
s
it
y
r
ed
u
c
tio
n
:
ac
h
ie
v
in
g
s
m
al
ler
d
ata
r
ep
r
esen
tatio
n
s
b
y
u
s
i
n
g
s
p
ec
ial
tech
n
iq
u
e
s
s
u
c
h
a
s
p
ar
am
etr
ic
m
o
d
el
s
(
s
u
c
h
as
r
eg
r
ess
io
n
an
d
lo
g
-
l
in
ea
r
)
an
d
n
o
n
p
ar
a
m
etr
ic
m
o
d
els
(
s
u
c
h
as
s
a
m
p
l
in
g
,
h
is
to
g
r
a
m
s
,
clu
s
ter
in
g
,
an
d
d
at
a
cu
b
e
ag
g
r
e
g
atio
n
)
.
c.
Data
co
m
p
r
es
s
io
n
:
co
m
p
r
ess
i
n
g
d
ata
to
o
b
tai
n
a
r
ed
u
ce
d
c
o
p
y
o
f
th
e
o
r
ig
i
n
al
d
ata.
R
e
s
u
ltan
t
d
ata
ca
n
b
e
eith
er
lo
s
s
le
s
s
o
r
lo
s
s
y
,
d
ep
en
d
in
g
o
n
w
h
et
h
er
th
er
e
w
as a
lo
s
s
o
f
i
n
f
o
r
m
atio
n
d
u
r
in
g
d
ata
co
m
p
r
es
s
io
n
.
B
o
th
d
i
m
e
n
s
io
n
alit
y
r
ed
u
ctio
n
a
n
d
n
u
m
er
o
s
it
y
r
ed
u
ctio
n
ca
n
b
e
ap
p
lied
to
s
o
cial
d
ata
to
h
a
v
e
a
s
m
al
ler
d
ata
v
o
lu
m
e
w
h
ile
at
th
e
s
a
m
e
ti
m
e
p
r
o
d
u
cin
g
th
e
s
a
m
e
(
o
r
n
ea
r
th
e
s
a
m
e)
m
i
n
i
n
g
r
esu
lts
.
Fo
r
ex
a
m
p
le,
to
p
r
o
v
id
e
s
m
all
er
r
ep
r
esen
tatio
n
s
o
f
t
h
e
o
r
ig
i
n
al
d
ata,
[
13
]
p
er
f
o
r
m
ed
d
i
m
e
n
s
io
n
alit
y
r
ed
u
ctio
n
o
n
a
T
w
itter
co
r
p
u
s
to
r
em
o
v
e
u
s
eles
s
k
e
y
w
o
r
d
s
f
r
o
m
t
h
e
o
ld
m
es
s
ag
e
s
,
an
d
u
s
ed
n
u
m
e
r
o
s
it
y
tech
n
iq
u
e
s
to
r
ep
lace
u
s
er
’
s
m
ess
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es
w
it
h
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lea
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t
p
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le
k
e
y
w
o
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d
s
th
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ep
r
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t
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e
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ai
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ag
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s
.
I
n
a
d
if
f
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n
t
s
t
u
d
y
,
[
19
]
ap
p
lied
attr
ib
u
te
r
ed
u
ctio
n
to
i
m
p
r
o
v
e
th
e
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etec
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itter
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at
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b
y
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m
p
u
ti
n
g
co
r
r
elatio
n
co
ef
f
icien
ts
b
et
w
ee
n
attr
ib
u
tes
[
2
0
-
22]
.
4.
CASE
S
T
UD
Y:
F
L
I
G
H
T
M
H
3
7
0
T
h
is
s
ec
tio
n
d
is
cu
s
s
e
s
h
o
w
w
e
i
m
p
le
m
e
n
ted
p
r
ep
r
o
ce
s
s
i
n
g
to
Fli
g
h
t
MH
3
7
0
s
o
cial
d
ata.
Af
ter
p
r
ep
r
o
ce
s
s
in
g
,
w
e
u
s
ed
th
e
r
esu
l
tan
t
d
ata
to
ex
a
m
i
n
e
th
e
f
li
g
h
t
co
m
m
u
n
it
y
s
tr
u
ct
u
r
e,
d
is
co
v
er
t
y
p
es
o
f
s
o
cial
r
elatio
n
s
h
ip
s
,
r
ev
ea
l
th
e
tr
u
t
h
b
eh
i
n
d
s
o
m
e
o
f
t
h
e
u
n
u
s
u
a
l
ev
e
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ts
,
a
n
d
s
tu
d
y
p
eo
p
le
co
p
in
g
b
eh
av
io
r
(
ad
ap
tatio
n
p
atter
n
s
)
d
u
r
in
g
d
is
aster
ti
m
e
[
2
3
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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ala
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I
n
ter
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atio
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ir
p
o
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t
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KL
I
A
)
at
1
2
.
4
1
am
.
I
t
w
as
s
u
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p
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i
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it
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o
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er
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h
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Au
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Fra
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Un
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w
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A
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er
ica
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b
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escale
Se
m
ico
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ical
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A
g
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a
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h
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itio
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i
n
t
h
e
Ma
la
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s
ian
ca
p
ital,
t
h
e
m
ed
C
h
i
n
e
s
e
Dr
ea
m
:
R
ed
a
n
d
Gr
ee
n
P
ain
t
in
g
.
So
m
e
p
as
s
e
n
g
er
s
w
er
e
o
n
tr
a
v
el
f
r
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m
C
h
i
n
a
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atte
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a
B
u
d
d
h
is
t r
eli
g
io
u
s
ce
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e
m
o
n
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T
h
e
air
p
lan
e
also
ca
r
r
ied
a
g
r
o
u
p
o
f
w
o
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er
s
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h
o
w
o
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k
ed
in
Sin
g
ap
o
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e,
a
g
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p
o
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to
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r
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ts
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h
o
w
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e
o
n
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ip
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Nep
al,
a
n
u
m
b
er
o
f
f
a
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ili
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as
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ell
as
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as
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ak
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a
s
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er
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T
h
e
cr
ew
o
f
th
e
air
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lan
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as 1
2
Ma
lay
s
ia
n
citize
n
s
(
2
p
ilo
ts
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d
10
atten
d
an
ts
)
.
4
.
1
.
M
H
3
7
0
s
o
cia
l da
t
a
c
o
llect
io
n
As
w
e
s
aid
ea
r
lier
in
“
o
n
li
n
e
s
o
cial
d
ata
co
llectio
n
,”
co
llectin
g
s
o
cial
d
ata
is
n
o
t
s
tr
ai
g
h
tf
o
r
w
ar
d
an
d
r
eq
u
ir
es
m
u
c
h
e
f
f
o
r
t,
in
p
ar
tic
u
lar
,
th
a
t
s
u
c
h
d
ata
ar
e
u
n
s
tr
u
ctu
r
ed
an
d
co
m
e
f
r
o
m
v
ar
io
u
s
s
o
u
r
ce
s
,
ad
d
ed
to
o
th
er
is
s
u
es s
u
c
h
as st
o
r
a
g
e,
p
r
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ce
s
s
in
g
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an
d
d
y
n
a
m
icit
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o
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t
h
e
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et
w
o
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k
.
T
h
e
d
ataset
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at
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llected
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m
e
f
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m
te
n
s
o
f
d
i
f
f
er
en
t
o
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lin
e
n
e
w
s
w
eb
s
i
tes
(
s
u
c
h
a
s
T
h
e
Ne
w
I
n
d
ian
E
x
p
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s
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Y
A
HOO
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Ne
w
s
Ma
la
y
s
ia,
th
e
E
co
n
o
m
ic
T
im
es,
C
NN.
co
m
,
t
h
e
Dail
y
E
x
p
r
ess
,
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d
I
n
d
ia
T
o
d
ay
)
.
Data
g
a
th
er
i
n
g
w
as
d
o
n
e
o
v
er
Ma
r
ch
an
d
A
p
r
il
i
n
2
0
1
4
c
o
v
er
in
g
t
h
e
e
v
en
t
s
f
r
o
m
w
h
en
t
h
e
air
p
lan
e
d
is
ap
p
ea
r
ed
u
n
til
late
o
f
A
p
r
i
l,
w
h
e
n
m
o
s
t
o
f
th
e
i
n
ter
n
at
i
o
n
al
e
f
f
o
r
ts
to
lo
ca
te
th
e
m
is
s
in
g
f
li
g
h
t
s
to
p
p
ed
,
w
it
h
o
u
t a
ch
ie
v
i
n
g
t
h
eir
g
o
als.
On
li
n
e
n
e
w
s
m
ed
ia
ad
d
r
ess
ed
th
is
e
v
en
t
i
n
th
r
ee
d
i
f
f
er
e
n
t
w
a
y
s
:
h
o
w
th
e
air
p
lan
e
d
is
ap
p
ea
r
ed
,
th
e
b
ac
k
g
r
o
u
n
d
o
f
t
h
e
p
as
s
en
g
er
s
,
h
o
w
r
elati
v
es
w
er
e
in
ter
a
ctin
g
w
it
h
n
e
w
s
a
n
d
t
h
e
e
f
f
o
r
ts
m
ad
e
b
y
t
h
e
in
ter
n
a
tio
n
al
s
o
ciet
y
to
lo
ca
te
th
e
m
is
s
in
g
air
p
lan
e.
4
.
2
.
M
H
3
7
0
s
o
cia
l da
t
a
prepa
ra
t
io
n
As
w
e
s
aid
ea
r
lier
in
t
h
i
s
s
t
u
d
y
,
i
n
o
r
d
er
to
ef
f
icien
tl
y
m
i
n
e
an
d
an
a
l
y
ze
co
llected
d
ata,
d
ata
p
r
ep
r
o
ce
s
s
in
g
m
u
s
t
b
e
i
m
p
le
m
en
ted
as
a
s
er
ies
o
f
s
eq
u
en
tial
s
tep
s
.
Firs
t:
d
ata
clea
n
i
n
g
,
w
h
ich
ai
m
s
at
eli
m
i
n
ati
n
g
ir
r
elev
a
n
t
a
n
d
r
ed
u
n
d
a
n
t
co
n
ten
t?
Seco
n
d
:
d
ata
in
te
g
r
atio
n
,
w
h
ic
h
a
i
m
s
at
in
teg
r
ati
n
g
d
ata
f
r
o
m
d
if
f
er
e
n
t
s
o
u
r
ce
s
in
to
a
u
n
i
q
u
e
an
d
u
n
if
o
r
m
d
ata
en
d
p
o
in
t.
T
h
ir
d
:
d
ata
tr
an
s
f
o
r
m
at
io
n
,
w
h
ic
h
ai
m
s
at
co
n
v
er
ti
n
g
t
h
e
r
esu
lta
n
t
d
ata
in
to
a
f
o
r
m
at
th
at
i
s
ea
s
y
f
o
r
an
al
y
s
is
.
Fi
n
all
y
:
d
ata
r
ed
u
ctio
n
,
w
h
ic
h
ai
m
s
at
h
av
i
n
g
a
s
m
aller
(
b
o
th
in
v
o
lu
m
e
a
n
d
d
i
m
e
n
s
io
n
)
,
co
n
cis
e
an
d
clea
n
,
r
ep
r
esen
tatio
n
o
f
th
e
d
ata
t
h
at
w
il
l
u
n
d
er
g
o
a
n
al
y
s
is
la
ter
.
4
.
2
.
1
.
M
H
3
7
0
s
o
cia
l da
t
a
cle
a
nin
g
T
h
e
f
ir
s
t
s
tep
o
f
Fli
g
h
t
MH
3
7
0
d
ata
p
r
ep
r
o
ce
s
s
in
g
w
as
to
ch
ec
k
a
n
d
ev
al
u
ate
all
th
e
attr
i
b
u
tes
o
f
t
h
e
o
r
ig
in
al
d
ata.
A
s
w
e
d
o
i
n
o
th
e
r
d
ata
clea
n
i
n
g
p
r
o
ce
s
s
es,
w
e
p
r
io
r
itize
d
ata
q
u
ali
t
y
o
v
er
d
ata
s
ca
le
.
I
t
is
p
r
ef
er
ab
le
to
r
e
d
u
ce
d
ata
v
o
lu
m
e
to
h
av
e
m
o
r
e
r
ep
r
esen
tati
v
e
in
f
o
r
m
atio
n
,
r
ath
er
th
a
n
p
o
o
r
an
d
in
co
n
s
is
te
n
t d
ata.
I
n
th
e
ca
s
e
o
f
Fli
g
h
t
MH
3
7
0
,
w
h
er
e
d
ata
w
er
e
co
llected
f
r
o
m
v
ar
io
u
s
o
n
li
n
e
s
o
u
r
ce
s
,
p
ass
en
g
e
r
d
em
o
g
r
ap
h
ic
i
n
f
o
r
m
atio
n
w
a
s
m
o
s
tl
y
i
n
co
n
s
is
te
n
t,
a
m
b
i
g
u
o
u
s
o
r
m
i
s
s
i
n
g
.
A
cc
o
r
d
in
g
l
y
,
w
e
p
r
ef
er
r
ed
to
r
e
m
o
v
e
all
d
e
m
o
g
r
ap
h
ic
attr
ib
u
tes
e
x
ce
p
t
“Ag
e
.”
As
w
il
l
b
e
d
escr
ib
ed
in
s
u
b
s
eq
u
en
t
s
ec
ti
o
n
s
,
w
e
u
s
ed
ag
e
s
to
d
if
f
er
e
n
tiate
u
s
er
s
h
a
v
i
n
g
th
e
s
a
m
e
n
a
m
e
a
n
d
to
h
elp
ex
p
l
o
r
e
g
r
o
u
p
s
an
d
co
n
n
ec
tio
n
s
.
Usi
n
g
P
aj
ek
So
f
t
w
ar
e,
i
t
w
a
s
p
o
s
s
ib
le
to
d
etec
t
v
i
s
u
all
y
a
n
d
co
r
r
ec
t
s
o
m
e
o
u
tlier
s
a
n
d
in
co
n
s
is
te
n
cie
s
r
elate
d
to
th
e
p
ass
en
g
er
ag
e.
W
e
w
er
e
ab
le
to
p
r
o
b
e
s
o
m
e
d
ata
s
o
u
r
ce
s
an
d
i
d
en
ti
f
y
in
co
n
s
is
te
n
cie
s
,
an
d
u
s
i
n
g
o
t
h
er
d
ata
s
o
u
r
ce
s
an
d
r
el
y
i
n
g
o
n
m
o
s
t
co
m
m
o
n
d
ata
a
m
o
n
g
s
u
c
h
s
o
u
r
ce
s
;
we
co
u
ld
s
m
o
o
th
o
u
t n
o
i
s
y
d
at
a
lik
e
th
a
t.
I
n
th
is
p
h
a
s
e,
w
e
r
e
m
o
v
ed
u
n
w
a
n
ted
an
d
ir
r
elev
an
t
in
f
o
r
m
atio
n
f
r
o
m
d
ata.
Fo
r
a
s
tu
d
y
o
n
s
o
cia
l
n
et
w
o
r
k
s
,
w
e
w
er
e
co
n
ce
r
n
e
d
o
n
ly
w
i
th
t
h
e
in
f
o
r
m
atio
n
t
h
at
w
o
u
ld
h
elp
r
ev
ea
l
r
elatio
n
s
an
d
co
n
n
ec
tio
n
s
b
et
w
ee
n
p
ass
en
g
er
s
.
I
t
w
a
s
a
ti
m
e
-
co
n
s
u
m
in
g
tas
k
s
i
n
ce
o
n
lin
e
s
o
cial
d
ata
ten
d
to
h
av
e
n
o
is
e,
o
u
tlier
s
,
m
is
s
i
n
g
v
al
u
es
a
n
d
o
th
er
i
n
co
n
s
i
s
te
n
cies
.
Ot
h
er
m
eth
o
d
s
a
n
d
p
a
ck
ag
es
ca
n
also
b
e
u
s
ed
b
y
d
ata
s
cie
n
ti
s
ts
f
o
r
th
is
p
u
r
p
o
s
e,
s
u
c
h
th
e
R
So
f
t
war
e;
an
d
P
y
t
h
o
n
p
ac
k
a
g
es
f
o
r
d
ata
m
a
n
ip
u
latio
n
,
s
u
c
h
as P
an
d
as a
n
d
N
u
m
P
y
.
4
.
2
.
2
.
M
H
3
7
0
s
o
cia
l da
t
a
inte
g
ra
t
i
o
n
W
e
co
llected
o
u
r
d
ata
f
r
o
m
d
i
f
f
er
en
t
s
o
cial
m
ed
ia
w
eb
s
ites
o
v
er
t
w
o
m
o
n
th
s
.
B
ec
au
s
e
th
e
d
ata
w
er
e
m
o
s
tl
y
u
n
s
tr
u
ct
u
r
ed
tex
t,
w
e
h
ad
to
r
u
n
s
o
m
e
d
ata
m
a
n
ip
u
l
atio
n
s
cr
ip
ts
to
p
r
o
ce
s
s
th
e
tex
t.
T
h
e
g
o
al
w
a
s
to
ex
tr
ac
t a
s
i
m
p
le
an
d
m
o
r
e
u
n
i
f
ied
d
ata.
I
n
th
i
s
p
h
ase,
w
e
d
etec
ted
an
d
s
o
lv
ed
d
ata
v
al
u
e
co
n
f
lict
s
o
n
p
ass
e
n
g
er
d
ata
s
u
ch
as
th
e
u
s
e
o
f
d
if
f
er
e
n
t
r
ep
r
esen
ta
tio
n
s
,
an
d
d
if
f
er
e
n
t
s
ca
les
(
i.e
.
,
m
etr
ic
v
s
.
B
r
itis
h
u
n
its
,
o
r
o
th
er
s
)
.
Af
ter
w
ar
d
s
,
w
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
9
,
No
.
4
,
A
u
g
u
s
t
201
9
:
2
6
2
0
-
2626
2624
r
ef
o
r
m
u
lated
an
d
u
n
i
f
ied
t
h
e
d
ata
s
u
c
h
t
h
at
w
e
s
to
r
ed
p
ass
en
g
er
in
f
o
r
m
at
io
n
i
n
m
o
r
e
r
e
co
g
n
izab
le
f
o
r
m
at
s
.
A
ll
t
h
e
i
n
f
o
r
m
atio
n
ab
o
u
t
t
h
e
f
li
g
h
t
p
ass
en
g
er
s
a
n
d
th
eir
f
a
m
ilie
s
th
at
w
e
w
er
e
ab
le
to
in
t
eg
r
ate
ar
e
s
h
o
w
n
i
n
Fig
u
r
e
1
.
Fig
u
r
e
1
.
R
a
w
d
ata
o
f
Fli
g
h
t
MH
3
7
0
In
Fig
u
r
e
1
ab
o
v
e,
th
e
d
ata
th
at
d
escr
ib
e
n
a
m
es,
n
atio
n
al
itie
s
,
an
d
ag
es
w
er
e
ex
p
a
n
d
ed
f
r
o
m
MH
3
7
0
P
ass
en
g
er
Ma
n
i
f
est,
r
elea
s
ed
b
y
Ma
la
y
s
ia
A
ir
li
n
es
t
h
e
s
a
m
e
d
a
y
o
f
th
e
d
is
as
ter
.
C
o
lu
m
n
“Co
n
n
ec
ted
-
to
”
r
ep
r
esen
ts
th
e
p
eo
p
le
th
at
a
p
ar
ticu
lar
p
ass
en
g
er
is
co
n
n
ec
t
ed
to
.
T
h
is
in
clu
d
es
f
a
m
il
y
m
e
m
b
er
s
,
co
-
w
o
r
k
er
s
,
an
d
f
r
ien
d
s
.
T
h
e
d
ata
in
th
at
co
l
u
m
n
w
er
e
co
llected
b
ased
o
n
s
tate
m
e
n
ts
f
r
o
m
f
a
m
il
y
m
e
m
b
er
s
,
j
o
u
r
n
al
r
ep
o
r
ts
o
r
o
f
f
icial
s
.
Ho
w
e
v
er
,
o
f
f
icia
ls
w
er
e
ac
cu
s
ed
o
f
g
i
v
i
n
g
litt
le
i
n
f
o
r
m
atio
n
ab
o
u
t th
e
a
cc
id
en
t.
C
o
lu
m
n
“Alter
n
at
iv
e
Na
m
e”
h
as
t
h
e
n
a
m
es
t
h
at
w
e
u
s
ed
later
f
o
r
an
al
y
s
is
i
n
s
tead
o
f
t
h
e
lis
t
o
f
n
a
m
e
s
p
r
o
v
id
ed
b
y
t
h
e
MH
3
7
0
P
ass
en
g
er
Ma
n
if
e
s
t
w
h
ich
,
i
n
tu
r
n
,
ar
e
s
h
o
w
n
in
co
l
u
m
n
“P
ass
en
g
er
Na
m
e
.”
E
ac
h
n
a
m
e
i
n
co
l
u
m
n
“Alter
n
ati
v
e
Na
m
e”
b
eg
i
n
s
w
it
h
t
h
e
p
ass
en
g
er
’
s
f
ir
s
t
n
a
m
e
f
o
ll
o
w
ed
b
y
t
h
e
f
a
m
il
y
n
a
m
e
(
n
a
m
es
w
i
th
t
w
o
p
ar
ts
w
er
e
al
s
o
co
n
s
id
er
ed
)
.
W
e
also
r
em
o
v
ed
u
n
n
ec
e
s
s
ar
y
w
o
r
d
ca
p
italizatio
n
s
a
n
d
s
u
f
f
ix
ed
t
h
e
s
ec
o
n
d
n
a
m
e
o
f
ea
ch
p
ass
en
g
er
w
it
h
h
is
/h
er
ag
e
to
av
o
id
n
a
m
e
co
n
f
u
s
io
n
s
(
f
o
r
in
s
ta
n
ce
,
th
e
n
a
m
e
Zh
a
n
g
Ya
n
(
3
6
)
is
also
t
h
e
n
a
m
e
o
f
an
o
t
h
er
p
ass
e
n
g
er
,
Zh
a
n
g
Ya
n
(
4
5
)
)
.
Fo
r
s
im
p
lici
t
y
,
w
e
p
r
ef
er
r
ed
to
u
s
e
o
n
l
y
t
h
e
p
ass
e
n
g
er
’
s
f
ir
s
t
an
d
s
ec
o
n
d
n
a
m
e
f
o
llo
w
ed
b
y
ag
e.
C
o
lu
m
n
“S
y
m
b
o
l”
h
a
s
th
e
la
b
els
th
at
w
e
g
a
v
e
to
th
e
p
as
s
en
g
er
s
.
Fo
r
ex
a
m
p
le,
P
1
,
P
2
,
P
3
r
ef
er
,
r
esp
ec
tiv
el
y
,
to
t
h
e
f
ir
s
t
t
h
r
ee
p
ass
en
g
er
s
A
mb
r
e
W
a
tt
r
elo
s
(
1
4
)
,
A
n
W
en
la
n
(
6
5
)
a
n
d
A
n
d
r
ew
N
a
r
i
(
4
9
)
in
th
e
tab
le.
T
h
ese
s
y
m
b
o
l
s
w
er
e
u
s
ed
to
lab
el
n
o
d
es
w
h
e
n
w
e
b
u
ilt
t
h
e
g
r
ap
h
ical
r
ep
r
esen
tat
io
n
s
.
C
o
lu
m
n
“
B
ac
k
g
r
o
u
n
d
”
co
n
tain
s
in
f
o
r
m
atio
n
o
v
er
t
w
o
m
o
n
t
h
s
ab
o
u
t
th
e
p
ass
en
g
er
s
.
I
t
tells
ab
o
u
t
th
e
ca
r
ee
r
,
m
ar
ita
l
s
tatu
s
,
f
a
m
il
y
m
e
m
b
er
s
,
a
n
d
f
r
ien
d
s
h
ip
s
o
f
ea
c
h
o
n
e.
4
.
2
.
3
.
M
H
3
7
0
So
cia
l D
a
t
a
T
ra
ns
f
o
r
m
a
t
io
n
On
e
o
f
th
e
tas
k
s
th
at
w
er
e
ac
tiv
el
y
p
r
ese
n
t
w
h
e
n
w
e
b
u
ilt
o
u
r
d
atab
ase
w
a
s
d
ata
tr
an
s
f
o
r
m
atio
n
o
f
th
e
p
ass
e
n
g
er
n
a
m
e.
W
e
u
s
ed
a
s
i
m
p
le
h
e
u
r
is
tics
f
o
r
th
is
p
u
r
p
o
s
e.
T
h
e
task
in
cl
u
d
ed
r
ev
ie
w
i
n
g
t
h
e
tab
le
r
o
w
b
y
r
o
w
,
tr
a
n
s
f
o
r
m
i
n
g
ea
c
h
n
a
m
e
in
to
m
o
r
e
a
p
r
o
p
er
s
tr
u
ctu
r
e
(
i.e
.
,
alter
n
ativ
e
n
a
m
e)
,
an
d
g
iv
i
n
g
it
a
p
r
o
p
er
id
en
ti
f
ier
(
i.e
.
,
lab
el)
.
On
e
o
f
t
h
e
th
i
n
g
s
t
h
at
w
e
d
id
f
o
r
d
ata
tr
an
s
f
o
r
m
at
io
n
w
as
ad
d
in
g
ex
tr
a
n
o
d
es
th
at
s
er
v
e
p
ar
ticu
lar
p
u
r
p
o
s
es.
Fo
r
ex
a
m
p
le,
in
ad
d
itio
n
to
t
h
e
o
r
i
g
i
n
al
2
3
9
n
o
d
es,
p
ass
e
n
g
er
n
o
d
es
w
er
e
tied
to
a
ce
n
tr
al
n
o
d
e,
ca
lled
“
Fli
g
h
t
,”
to
s
h
o
w
t
h
at
all
t
h
e
p
ass
e
n
g
er
s
w
er
e
p
r
esen
t
at
t
h
e
s
a
m
e
ev
e
n
t
a
n
d
w
er
e
p
ar
t
o
f
t
h
e
f
li
g
h
t
n
et
w
o
r
k
s
tr
u
c
tu
r
e
.
An
o
th
er
n
o
d
e
“
Si
n
g
ap
o
r
e”
w
as
ad
d
ed
to
co
n
n
ec
t
th
e
C
h
i
n
ese
w
o
r
k
e
r
s
w
h
o
w
o
r
k
ed
i
n
Sin
g
ap
o
r
e
alto
g
et
h
er
.
T
h
r
ee
o
f
th
o
s
e
w
o
r
k
er
s
w
er
e
co
n
f
ir
m
ed
to
b
e
f
r
ie
n
d
s
a
n
d
to
k
n
o
w
ea
c
h
o
th
er
,
a
n
d
th
er
ef
o
r
e,
t
h
e
y
w
er
e
d
ir
ec
tl
y
c
o
n
n
ec
ted
to
ea
c
h
o
t
h
er
an
d
th
e
ce
n
tr
al
n
o
d
e
o
f
th
e
g
r
o
u
p
.
T
h
e
r
esu
lt
in
g
n
et
w
o
r
k
is
a
s
m
a
ll u
n
d
ir
ec
ted
n
et
w
o
r
k
th
at
h
a
s
n
o
lo
o
p
s
,
h
a
v
in
g
ev
er
y
t
w
o
p
ass
e
n
g
er
s
co
n
n
ec
ted
.
Sin
ce
o
u
r
d
ata
p
r
ep
r
o
ce
s
s
in
g
w
a
s
m
o
s
tl
y
i
n
v
o
l
v
ed
in
te
x
t
m
an
ip
u
latio
n
,
w
e
d
id
n
o
t
n
ee
d
to
p
er
f
o
r
m
(
ex
ce
p
t
f
o
r
f
ea
tu
r
e
co
n
s
tr
u
ct
i
o
n
)
o
th
er
t
y
p
es
o
f
d
ata
tr
an
s
f
o
r
m
atio
n
.
Nev
er
t
h
eles
s
,
an
d
d
ep
en
d
in
g
o
n
t
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
On
lin
e
d
a
ta
p
r
ep
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izatio
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ec
if
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d
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.
4
.
2
.
4
.
M
H
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7
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o
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As
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lier
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io
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itize
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at
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ata
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le
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a
y
,
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im
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ata
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lier
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g
n
o
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d
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co
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ata,
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e
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ter
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d
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d
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it si
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f
u
l,
p
ar
ticu
lar
l
y
f
o
r
v
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al
a
n
al
y
s
i
s
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h
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tab
le
d
is
cu
s
s
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ea
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lier
co
n
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s
s
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m
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r
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iled
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r
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t E
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ce
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f
ile
as sh
o
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Fi
g
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r
e
2
.
Fig
u
r
e
2
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Sa
m
p
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d
ata
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r
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F
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h
t M
H3
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ataset
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ataset
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4
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5
6
3
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d
g
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d
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n
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t
h
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lu
m
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s
:
1.
C
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ted
-
to
: i
n
d
iv
id
u
als t
h
at
a
p
ar
ticu
lar
p
ass
en
g
er
is
co
n
n
ec
ted
to
2.
Na
m
es
: n
a
m
es t
h
at
w
er
e
u
s
ed
d
u
r
in
g
d
ata
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al
y
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i
s
3.
L
ab
els
: la
b
el
s
th
at
w
e
g
a
v
e
to
th
e
p
ass
e
n
g
er
s
I
t
w
as
es
s
en
tial
to
tr
an
s
f
o
r
m
t
h
e
d
ataset
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to
th
e
“
.
n
et”
f
o
r
m
at
b
ef
o
r
e
em
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ar
k
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n
g
o
n
d
ata
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al
y
s
i
s
an
d
d
ata
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is
u
aliza
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n
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h
e
r
esu
lti
n
g
.
n
et
f
ile
h
a
s
t
w
o
p
ar
ts
:
1.
Ver
tices to
d
en
o
te
f
l
ig
h
t
p
as
s
e
n
g
er
s
.
Fo
r
d
ata
v
is
u
aliza
tio
n
,
all
th
e
v
er
tice
s
w
er
e
g
i
v
e
n
t
h
e
s
a
m
e
s
h
ap
e
an
d
th
e
s
a
m
e
s
ize,
ev
e
n
th
o
u
g
h
th
e
y
m
a
y
h
a
v
e
a
d
if
f
er
e
n
t
n
u
m
b
er
o
f
co
n
n
ec
tio
n
s
.
A
f
e
w
ad
d
itio
n
al
v
er
tice
s
w
er
e
also
ad
d
ed
to
ac
h
iev
e
p
ar
ticu
lar
b
en
e
f
its
.
2.
E
d
g
es
to
co
n
n
ec
t
th
e
m
e
m
b
er
s
o
f
th
e
s
a
m
e
g
r
o
u
p
a
n
d
to
c
o
n
n
ec
t
th
e
d
if
f
er
en
t
g
r
o
u
p
s
.
F
o
r
a
b
etter
d
ata
v
is
u
aliza
t
io
n
,
ed
g
e
lab
els
a
n
d
w
ei
g
h
ts
w
er
e
eli
m
i
n
ated
.
L
a
b
els
an
d
w
ei
g
h
t
s
ar
e
s
o
m
e
ti
m
es
u
s
ed
to
s
h
o
w
th
e
s
tr
e
n
g
t
h
(
a
m
o
n
g
o
th
er
th
i
n
g
s
)
o
f
a
co
n
n
ec
tio
n
b
et
w
ee
n
t
w
o
n
o
d
es.
Dep
en
d
in
g
o
n
h
o
w
b
i
g
th
e
d
ata
ar
e,
o
th
er
m
et
h
o
d
s
ca
n
also
b
e
ap
p
lied
f
o
r
d
ata
r
ed
u
ctio
n
s
u
c
h
as
clu
s
ter
i
n
g
(
g
r
o
u
p
in
g
s
a
m
p
le
v
alu
es
in
cl
u
s
ter
s
b
ased
o
n
a
s
i
m
ilar
it
y
m
ea
s
u
r
e)
a
n
d
s
a
m
p
li
n
g
(
tak
i
n
g
a
s
a
m
p
le
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et
o
f
ac
to
r
s
f
r
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m
t
h
e
co
m
p
let
e
s
et)
.
C
o
n
n
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ti
n
g
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h
e
n
o
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s
h
elp
ed
u
s
s
p
o
t
t
h
r
ee
lar
g
e
co
m
m
u
n
i
t
y
s
tr
u
ct
u
r
es
[
20
]
:
th
e
“
A
r
tis
t
s
Gr
o
u
p
,”
co
n
s
is
tin
g
o
f
2
9
m
e
m
b
er
s
,
th
e
“
Fre
esca
le
Se
m
ico
n
d
u
c
to
r
”
g
r
o
u
p
,
co
m
p
r
is
ed
o
f
1
5
m
e
m
b
e
r
s
an
d
th
e
“
A
ir
cr
a
f
t
C
r
e
w
”
co
n
s
is
ti
n
g
o
f
1
2
m
e
m
b
er
s
.
Oth
er
s
m
aller
g
r
o
u
p
s
in
clu
d
e
s
i
x
p
eo
p
le
an
d
f
i
v
e
p
e
o
p
le
f
a
m
i
lies
f
r
o
m
C
h
i
n
a,
f
o
u
r
p
eo
p
le
f
a
m
il
y
f
r
o
m
Ma
la
y
s
ia,
a
Fre
n
c
h
f
a
m
il
y
,
an
Au
s
tr
alian
f
a
m
il
y
,
a
n
d
o
th
er
s
.
T
h
e
an
al
y
s
is
also
s
h
o
w
ed
8
no
d
es
(
t
w
o
p
il
o
ts
,
f
i
v
e
to
d
d
ler
s
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an
d
o
n
e
p
h
y
s
ical
l
y
c
h
alle
n
g
ed
eld
er
l
y
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m
a
n
)
t
h
at
ar
e
n
o
t
d
ir
ec
tl
y
co
n
n
ec
ted
to
n
o
d
e
“
Fl
ig
h
t
.”
Evaluation Warning : The document was created with Spire.PDF for Python.
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I
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t J
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lec
&
C
o
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,
Vo
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9
,
No
.
4
,
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u
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s
t
201
9
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2
6
2
0
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2626
2626
5.
CO
NCLU
SI
O
N
T
h
e
g
o
al
o
f
t
h
i
s
s
tu
d
y
is
to
u
n
d
er
s
tan
d
d
ata
p
r
ep
r
o
ce
s
s
in
g
in
t
h
e
li
g
h
t
o
f
Fl
ig
h
t
M
H3
7
0
s
o
cial
d
ata.
Data
p
r
ep
r
o
ce
s
s
in
g
is
a
cr
it
ic
al
p
ar
t
o
f
d
ata
s
cie
n
ce
p
r
o
j
ec
ts
,
m
a
in
l
y
t
h
at
r
ea
l
-
w
o
r
ld
d
ata
o
f
ten
h
a
v
e
n
o
is
e,
o
u
tlier
s
,
m
i
s
s
in
g
v
al
u
es
a
n
d
o
th
er
in
co
n
s
is
ten
cie
s
.
T
h
e
s
tep
s
s
h
o
u
ld
b
e
in
tr
o
d
u
ce
d
ef
f
icie
n
tl
y
,
s
u
p
p
o
r
ted
b
y
h
u
m
a
n
e
x
p
er
ien
ce
,
a
n
d
to
b
e
a
p
p
lied
m
o
r
e
t
h
a
n
o
n
ce
.
I
t
i
s
co
m
m
o
n
th
at
t
h
e
p
r
ep
r
o
ce
s
s
in
g
s
tep
s
ar
e
r
eiter
ated
if
t
h
e
r
esu
l
ts
o
f
d
ata
m
in
in
g
ar
e
s
ig
n
i
f
ican
tl
y
d
i
f
f
er
en
t
f
r
o
m
w
h
at
is
e
x
p
ec
ted
.
Han
d
lin
g
o
n
li
n
e
s
o
cial
d
ata
(
r
eg
ar
d
in
g
d
ata
co
llectio
n
a
n
d
d
ata
p
r
ep
r
o
ce
s
s
in
g
)
is
a
h
ar
d
ta
s
k
a
n
d
ca
n
b
ec
o
m
e
ev
e
n
m
o
r
e
co
m
p
l
icat
ed
if
th
e
d
ata
t
h
at
w
e
ar
e
co
n
c
er
n
ed
w
it
h
co
m
e
f
r
o
m
o
n
li
n
e
n
e
w
s
p
ag
e
s
t
h
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ar
e
co
m
m
o
n
l
y
k
n
o
w
n
to
h
a
v
e
p
r
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b
le
m
s
in
cr
ed
ib
ilit
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a
n
d
ac
cu
r
ac
y
(
e
x
ce
p
t
f
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s
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m
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ca
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e
s
)
.
On
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e
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w
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f
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3
7
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o
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d
ata
p
r
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s
s
in
g
is
h
o
w
to
d
ea
l
w
it
h
m
is
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i
n
g
d
ata,
s
h
o
r
tag
e
i
n
u
n
i
f
o
r
m
it
y
,
an
d
lack
o
f
s
o
m
e
cr
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i
n
f
o
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m
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.
O
n
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o
f
th
e
r
ea
s
o
n
s
th
at
th
e
av
a
ilab
le
in
f
o
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m
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n
w
as
n
o
t
e
n
o
u
g
h
i
s
th
a
t
o
f
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icial
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ab
s
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f
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n
g
m
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c
h
i
n
f
o
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m
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e
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ce
f
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et
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n
tr
ies.
R
eg
ar
d
i
n
g
ac
c
u
r
ac
y
,
s
o
m
e
in
f
o
r
m
atio
n
th
a
t
w
as
in
cl
u
d
ed
in
t
h
e
MH
3
7
0
P
ass
en
g
er
Ma
n
i
f
est
(
r
elea
s
ed
b
y
Ma
la
y
s
ia
n
A
ir
l
in
e
s
)
w
as
n
o
t
ac
cu
r
ate.
RE
F
E
R
E
NC
E
S
[1
]
S.
Ka
d
ry
a
n
d
M
.
Z
.
A
l
-
T
a
ie,
“
S
o
c
ial
n
e
tw
o
rk
a
n
a
ly
sis:
A
n
in
tro
d
u
c
ti
o
n
w
it
h
a
n
e
x
ten
siv
e
im
p
lem
e
n
tatio
n
to
a
larg
e
-
sc
a
le o
n
li
n
e
n
e
tw
o
rk
u
sin
g
P
a
jek
,
”
Be
n
th
a
m
S
c
ien
c
e
P
u
b
l
ish
e
rs
,
2
0
1
4
.
[2
]
M
.
S
.
Bro
w
n
,
“
Da
ta m
in
in
g
f
o
r
d
u
m
m
ie
s
,
”
Jo
h
n
W
il
e
y
&
S
o
n
s
,
2
0
1
4
.
[3
]
M
.
Z.
Al
-
Taie
,
e
t
a
l
.
,
“
S
u
c
c
e
ss
f
u
l
Da
ta
S
c
ien
c
e
P
ro
jec
ts:
L
e
ss
o
n
s
L
e
a
rn
e
d
f
ro
m
Ka
g
g
le
Co
m
p
e
ti
ti
o
n
,”
Ku
rd
ista
n
J
o
u
rn
a
l
o
f
A
p
p
li
e
d
Res
e
a
rc
h
,
v
o
l
/
issu
e
:
2
(3
)
,
2
0
1
7
.
[4
]
S.
W
a
ss
e
r
m
a
n
a
n
d
K.
F
a
u
st,
“
S
o
c
ial
n
e
tw
o
rk
a
n
a
l
y
sis:
M
e
th
o
d
s
a
n
d
a
p
p
l
ica
ti
o
n
s
,”
Ca
m
b
rid
g
e
u
n
iv
e
rsity
p
re
ss
,
v
o
l.
8
,
1
9
9
4
.
[5
]
P.
G
u
p
ta
a
n
d
V
.
B
h
a
tn
a
g
a
r,
“
Da
ta
p
re
p
ro
c
e
ss
in
g
f
o
r
d
y
n
a
m
i
c
so
c
ial
n
e
tw
o
rk
a
n
a
l
y
sis
,”
Da
ta
M
in
i
n
g
i
n
Dy
n
a
mic
S
o
c
ia
l
Ne
two
rk
s a
n
d
Fu
zz
y
S
y
ste
ms
,
p
p
.
2
5
-
39
,
2
0
1
3
.
[6
]
M.
Al
-
T
a
ie
a
n
d
S
.
Ka
d
ry
,
“
P
y
th
o
n
f
o
r
G
ra
p
h
a
n
d
Ne
tw
o
rk
A
n
a
l
y
si
s
,”
S
p
rin
g
e
r
,
p
p
.
1
-
1
8
4
,
20
17
.
[7
]
M.
Zu
b
e
r,
“
A
su
rv
e
y
o
f
d
a
ta
m
in
in
g
tec
h
n
iq
u
e
s
f
o
r
so
c
ial
n
e
tw
o
rk
a
n
a
ly
sis
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Res
e
a
rc
h
in
Co
mp
u
ter
E
n
g
in
e
e
rin
g
&
El
e
c
tro
n
ics
,
v
o
l/
issu
e
:
3
(6
)
,
2
0
1
4
.
[8
]
J.
Bian
,
e
t
a
l
.
,
“
F
in
d
i
n
g
th
e
rig
h
t
f
a
c
ts
in
th
e
c
ro
w
d
:
f
a
c
to
id
q
u
e
stio
n
a
n
sw
e
rin
g
o
v
e
r
so
c
ial
m
e
d
ia
,”
Pro
c
e
e
d
in
g
s
o
f
th
e
1
7
th
in
ter
n
a
ti
o
n
a
l
c
o
n
fer
e
n
c
e
o
n
W
o
rl
d
W
id
e
W
e
b
,
2
0
0
8
.
[9
]
S.
G
a
rc
ía,
e
t
a
l
.
,
“
Da
ta p
re
p
ro
c
e
ss
in
g
in
d
a
ta m
in
in
g
,”
S
p
ri
n
g
e
r
,
2
0
1
5
.
[1
0
]
J.
Ha
n
,
e
t
a
l
.
,
“
Da
ta m
in
in
g
:
c
o
n
c
e
p
ts an
d
tec
h
n
i
q
u
e
s
,”
El
se
v
ier
,
2
0
1
1
.
[1
1
]
S
.
S
.
De
a
n
d
S
.
De
h
u
ri,
“
M
a
c
h
in
e
Lea
rn
in
g
f
o
r
A
u
sp
icio
u
s
S
o
c
ial
Ne
t
w
o
rk
M
in
in
g
,
”
S
o
c
ia
l
Ne
two
rk
in
g
,
S
p
rin
g
e
r
,
p
p
.
4
5
-
83
,
2
0
1
4
.
[1
2
]
N.
Ag
a
r
w
a
l,
e
t
a
l
.,
“
Clu
ste
rin
g
o
f
b
lo
g
sites
u
sin
g
c
o
ll
e
c
ti
v
e
w
i
sd
o
m
,
”
Co
mp
u
ta
ti
o
n
a
l
S
o
c
i
a
l
Ne
two
rk
An
a
lys
is
,
S
p
rin
g
e
r
,
p
p
.
1
0
7
-
1
3
4
,
2
0
1
0
.
[1
3
]
L
.
Wen
x
u
e
a
n
d
G
.
S
u
n
,
“
A
tru
st
-
b
a
se
d
in
f
o
rm
a
ti
o
n
p
ro
p
a
g
a
ti
o
n
m
o
d
e
l
i
n
o
n
li
n
e
so
c
ial
n
e
tw
o
rk
s
,
”
v
o
l.
issu
e
:
8
(
8
)
,
p
p
.
1
7
6
7
,
2
0
1
3
.
[1
4
]
I.
He
m
a
lath
a
,
e
t
a
l
.
,
“
P
re
p
ro
c
e
ss
in
g
th
e
in
f
o
rm
a
l
tex
t
f
o
r
e
ff
icie
n
t
se
n
ti
m
e
n
t
a
n
a
l
y
sis
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Eme
rg
in
g
T
re
n
d
s &
T
e
c
h
n
o
lo
g
y
i
n
Co
m
p
u
ter
S
c
ie
n
c
e
(
IJ
ET
T
CS
)
,
v
o
l/
issu
e
:
1
(2
)
,
p
p
.
58
-
61
,
2
0
1
2
.
[1
5
]
T
.
H.
Wen
,
e
t
a
l
.
,
“
A
n
a
l
y
sis
o
f
c
o
m
b
in
in
g
T
o
p
ic
m
o
d
e
l,
S
e
n
ti
m
e
n
t,
Ge
o
lo
c
a
ti
o
n
i
n
f
o
rm
a
ti
o
n
a
p
p
r
o
a
c
h
e
s
o
n
S
o
c
ial
Ne
tw
o
rk
.
”
[1
6
]
P.
Ka
z
ien
k
o
,
e
t
a
l
.,
“
A
g
e
n
e
ri
c
m
o
d
e
l
f
o
r
m
u
lt
id
im
e
n
sio
n
a
l
tem
p
o
ra
l
so
c
ial
n
e
tw
o
rk
,”
Co
m
mu
n
ica
t
io
n
s
i
n
Co
mp
u
ter
a
n
d
In
fo
rm
a
t
io
n
S
c
ien
c
e
,
CCIS
,
v
o
l
.
1
7
1
,
p
p
.
1
-
14
,
2
0
1
1
.
[1
7
]
M.
Al
-
T
a
i
e
a
n
d
S
.
Ka
d
ry
,
“
A
p
p
ly
in
g
S
o
c
ial
Ne
t
w
o
rk
A
n
a
l
y
sis
to
A
n
a
l
y
z
e
a
W
e
b
-
Ba
s
e
d
Co
m
m
u
n
it
y
,”
a
rX
iv
p
re
p
rin
t
a
rXiv
:1
2
1
2
.
6
0
5
0
,
2
0
1
2
.
[1
8
]
C.
C.
A
g
g
a
r
w
a
l
a
n
d
C.
K.
Re
d
d
y
,
“
Da
ta clu
ste
rin
g
:
a
lg
o
rit
h
m
s a
n
d
a
p
p
li
c
a
ti
o
n
s
,”
CRC p
re
ss
,
2
0
1
3
.
[1
9
]
M.
Kla
ss
e
n
,
“
Tw
it
ter
d
a
ta
p
re
p
ro
c
e
ss
in
g
f
o
r
sp
a
m
d
e
tec
ti
o
n
,”
FUT
URE
COM
PUT
ING
2
0
1
3
,
T
h
e
Fi
f
t
h
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
F
u
t
u
re
Co
mp
u
t
a
ti
o
n
a
l
T
e
c
h
n
o
l
o
g
ies
a
n
d
A
p
p
li
c
a
ti
o
n
s
,
Cit
e
se
e
r
,
2
0
1
3
.
[2
0
]
B
.
N
.
Oc
tav
i
a
n
a
a
n
d
J
.
A
b
ra
h
a
m
,
“
T
o
lera
n
c
e
f
o
r
E
m
o
ti
o
n
a
l
In
ter
n
e
t
In
f
id
e
li
t
y
a
n
d
Its
Co
rre
lat
e
w
it
h
Re
latio
n
sh
ip
F
lo
u
r
ish
i
n
g
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
Co
mp
u
ter
En
g
i
n
e
e
ri
n
g
(
IJ
ECE
)
,
v
ol
/i
ss
u
e
:
8
(
5
)
,
p
p
.
3
1
5
8
-
3
1
6
8
,
2
0
1
8
.
[2
1
]
C
.
V
irm
a
n
i,
e
t
a
l
.
,
“
Clu
ste
rin
g
i
n
Ag
g
re
g
a
ted
Us
e
r
P
ro
f
il
e
s a
c
ro
ss
M
u
lt
i
p
le S
o
c
ial
Ne
tw
o
rk
s
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
, v
ol
/i
ss
u
e
:
7
(
6
)
,
p
p
.
3
6
9
2
-
3
6
9
9
,
2
0
1
7
.
[2
2
]
Y.
L
.
S
.
Ra
n
i,
e
t
a
l
.
,
“
Ex
ten
siv
e
A
n
a
l
y
sis
o
n
G
e
n
e
ra
ti
o
n
a
n
d
Co
n
se
n
su
s
M
e
c
h
a
n
ism
s
o
f
Clu
ste
rin
g
En
se
m
b
le:
A
S
u
rv
e
y
,”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
, v
ol
/i
ss
u
e
:
8
(
4
)
,
p
p
.
2
3
5
1
-
2
3
5
7
.
[2
3
]
M
.
Z.
Al
-
T
a
ie,
e
t
a
l
.
,
“
F
li
g
h
t
M
H3
7
0
c
o
m
m
u
n
it
y
stru
c
tu
re
,”
In
t.
J
.
Ad
v
a
n
c
e
.
S
o
ft
Co
mp
u
t.
A
p
p
l
,
v
o
l/
issu
e
:
6
(2
)
,
2
0
1
4
.
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