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Un
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.
1.
I
NT
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UCT
I
O
N
T
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leg
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co
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p
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s
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as
w
ell
a
s
b
e
in
v
e
s
ti
g
ated
[
1
]
.
W
ith
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h
ea
d
w
a
y
o
f
c
u
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r
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GI
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en
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[
2
]
.
B
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m
ap
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clie
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ca
n
f
ir
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[
3
]
.
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u
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v
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to
til
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ate
[
4
]
.
T
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atab
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)
alo
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e
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attr
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s
[
5
]
.
T
h
e
in
f
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m
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is
o
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d
in
ar
il
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ec
to
r
i
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o
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at
io
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w
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h
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s
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k
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as
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o
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s
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lin
e
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d
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ly
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ap
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m
ap
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u
tti
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a
w
a
y
th
e
d
ir
ec
tio
n
s
an
d
to
p
o
lo
g
y
[
6
]
.
GI
S
u
tili
ze
s
s
co
p
e
an
d
lo
n
g
itu
d
e
o
f
s
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ts
a
s
k
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y
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ile
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s
to
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a
n
d
s
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k
to
i
n
f
o
r
m
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.
Qu
a
n
t
u
m
GI
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g
i
v
es
a
n
ef
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ec
ti
v
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GI
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a
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to
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h
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p
lex
s
p
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in
f
o
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.
L
a
n
d
co
v
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d
la
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d
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clas
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if
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tio
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L
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atellite
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KNN
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n
d
d
ec
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tr
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in
[
7
]
.
R
e
m
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d
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w
ater
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n
g
v
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h
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is
p
r
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n
ted
in
[
8
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.
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th
e
p
r
ep
ar
atio
n
s
et
to
d
is
ti
n
g
u
is
h
t
h
e
ex
a
m
p
le
s
w
h
ic
h
ar
e
r
elate
d
to
th
e
ad
m
in
i
s
tr
atio
n
a
n
d
f
u
m
b
le.
Asi
d
e
f
r
o
m
t
h
at,
OP
T
I
C
S
g
r
o
u
p
in
g
ca
lc
u
latio
n
is
co
n
n
e
cted
to
b
u
n
ch
t
h
e
p
o
p
u
lace
th
ick
n
es
s
in
v
ar
io
u
s
d
is
tr
icts
o
f
t
h
e
s
tate.
On
ce
t
h
e
f
r
a
m
e
w
o
r
k
h
as
p
ick
ed
u
p
its
in
f
o
r
m
at
io
n
ab
o
u
t
c
o
n
d
itio
n
s
p
r
o
m
p
ti
n
g
b
l
u
n
d
er
s
tate
in
t
h
e
d
is
tr
ict,
it
is
u
tili
ze
d
f
o
r
b
r
ea
k
in
g
d
o
w
n
th
e
f
u
r
t
h
er
d
ev
elo
p
in
g
p
o
p
u
lace
r
ate
an
d
o
f
f
ice
ad
m
i
n
is
tr
atio
n
.
T
h
e
ten
ets
p
r
o
d
u
ce
d
b
y
th
e
c
h
o
ic
e
tr
ee
th
en
f
ill
i
n
as
t
h
e
lear
n
in
g
b
ase
f
o
r
g
i
v
i
n
g
u
n
f
a
m
i
lia
r
ex
a
m
p
les
to
n
e
w
o
b
s
cu
r
e
in
f
o
r
m
a
tio
n
.
C
u
r
r
en
t
m
ea
s
u
r
e
s
o
f
ea
ch
o
f
th
e
p
ar
a
m
eter
s
ar
e
r
ec
o
r
d
ed
an
d
af
t
er
w
ar
d
t
h
e
m
i
x
o
f
cu
r
r
en
t q
u
ali
ties
i
s
co
n
tr
asted
an
d
th
e
te
n
ets cr
ea
ted
b
y
th
e
d
ec
is
io
n
tr
ee
.
T
h
e
last
m
o
d
u
le
i
s
p
o
in
ted
to
w
ar
d
s
b
u
ild
i
n
g
u
p
a
UI
f
o
r
s
i
m
p
le
u
til
izatio
n
o
f
t
h
e
f
r
a
m
e
w
o
r
k
f
o
r
th
e
clien
t
s
.
Ma
p
t
h
e
d
is
tr
ict
is
m
a
d
e
f
o
r
g
i
v
i
n
g
v
i
s
u
aliza
tio
n
to
th
e
v
en
tu
r
e.
S
ite
p
ag
e
s
ar
e
m
a
d
e
u
tili
zi
n
g
HT
ML
an
d
P
HP
in
d
icatin
g
d
if
f
er
en
t
q
u
er
y
o
p
er
atio
n
s
th
at
ca
n
b
e
p
er
f
o
r
m
ed
o
n
t
h
e
g
u
id
e
an
d
d
y
n
a
m
ic
g
u
id
e
h
a
s
b
ee
n
s
tack
ed
o
n
t
h
e
w
eb
s
ite
p
ag
es.
Fi
g
u
r
e
1
b
en
ea
t
h
d
e
m
o
n
s
tr
ates
t
h
e
s
tr
ea
m
ch
ar
t
f
o
r
th
e
w
o
r
k
i
n
g
o
f
th
e
m
o
d
el.
Fig
u
r
e
1
.
W
o
k
f
lo
w
Or
d
er
in
g
p
o
in
ts
to
id
en
ti
f
y
t
h
e
clu
s
ter
i
n
g
s
tr
u
ct
u
r
e
(
OP
T
I
C
S)
is
a
alg
o
r
ith
m
w
h
ic
h
is
li
k
e
DB
s
ca
n
alg
o
r
ith
m
.
T
h
e
p
o
in
t
i
s
to
d
is
co
v
er
th
ic
k
n
e
s
s
b
a
s
ed
clu
s
ter
s
in
s
p
atial
i
n
f
o
r
m
atio
n
.
T
h
e
OPT
I
C
S
alg
o
r
ith
m
h
as
b
ee
n
co
n
n
ec
ted
to
th
e
p
r
ev
io
u
s
y
ea
r
’
s
i
n
f
o
r
m
atio
n
o
f
p
o
p
u
lace
o
f
t
h
e
s
tate
s
o
t
h
at
to
w
n
i
n
s
i
g
h
tf
u
l
th
ic
k
n
e
s
s
le
v
els ca
n
b
e
r
ec
o
g
n
ized
.
3.
RE
SU
L
T
A
ND
DI
SCUS
SI
O
N
S
u
rv
e
y
s
sh
o
w
th
a
t
th
e
re
a
re
v
il
lag
e
s
h
a
v
in
g
v
e
r
y
lo
w
li
tera
c
y
ra
te.
T
a
k
in
g
p
a
ra
m
e
ter
p
o
p
u
latio
n
in
t
o
a
c
c
o
u
n
t
a
q
u
e
ry
d
riv
e
n
s
y
ste
m
is
p
ro
p
o
se
d
f
o
r
a
n
a
l
y
z
in
g
th
e
lar
g
e
sp
a
ti
a
l
d
a
tas
e
ts
a
n
d
f
in
d
in
g
re
latio
n
sh
i
p
a
m
o
n
g
d
i
ff
e
re
n
t
sp
a
ti
a
l
p
a
tt
e
rn
s.
T
h
e
re
su
lt
v
isu
a
li
z
a
ti
o
n
tak
e
p
lac
e
o
n
d
y
n
a
m
ic
m
a
p
s.
F
u
rth
e
r
th
is
c
a
n
lea
d
to
p
icto
rial
a
n
a
ly
ti
c
a
l
re
p
o
rts.
W
it
h
th
e
h
e
lp
o
f
th
e
se
re
p
o
r
ts
d
e
c
isio
n
c
a
n
b
e
tak
e
n
b
y
g
o
v
e
rn
m
e
n
t
b
o
d
i
e
s f
o
r
p
ro
p
e
r
p
lan
n
in
g
a
n
d
m
a
n
a
g
e
m
e
n
t
o
f
sta
te.
4.
CO
NCLU
SI
O
N
T
h
er
e
ar
e
n
u
m
er
o
u
s
r
u
s
t
ic
zo
n
es
w
h
ich
ar
e
u
n
d
er
ad
v
an
tag
ed
,
w
i
th
o
u
t
s
ch
o
o
ls
an
d
cli
n
ic
s
.
Stu
d
ies
d
em
o
n
s
tr
ate
t
h
at
th
er
e
ar
e
to
w
n
s
h
av
i
n
g
lo
w
ed
u
ca
tio
n
r
ate.
C
o
n
s
id
er
in
g
p
ar
a
m
eter
p
o
p
u
lace
an
d
q
u
er
y
d
eter
m
in
e
f
r
a
m
e
w
o
r
k
is
p
r
o
p
o
s
ed
f
o
r
d
is
s
ec
tin
g
th
e
ex
p
a
n
s
iv
e
s
p
atial
d
ata
s
ets
an
d
d
i
s
c
o
v
er
in
g
r
elatio
n
s
h
ip
a
m
o
n
g
v
ar
io
u
s
s
p
atial
p
atter
n
s
.
T
h
e
o
u
tco
m
e
v
is
u
aliza
t
io
n
o
cc
u
r
s
o
n
p
o
w
er
f
u
l
m
ap
s
.
F
ac
ilit
ate
w
h
ic
h
ca
n
p
r
o
m
p
t
p
icto
r
ial
lo
g
ical
r
ep
o
r
ts
.
W
ith
t
h
e
as
s
is
tan
ce
o
f
th
ese
r
ep
o
r
ts
ch
o
ice
ca
n
b
e
ta
k
en
b
y
g
o
v
er
n
m
e
n
t
b
o
d
ies f
o
r
le
g
iti
m
ate
ar
r
an
g
i
n
g
an
d
ad
m
i
n
i
s
tr
atio
n
o
f
s
tate.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
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I
n
d
o
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J
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lec
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n
g
&
C
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m
p
Sci,
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l
.
9
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.
3
,
Ma
r
ch
2
0
1
8
:
5
5
2
–
5
5
4
554
RE
F
E
R
E
NC
E
S
[1
]
Ru
tt
e
n
M
,
T
rico
c
h
e
X
,
Ba
ra
k
a
t
S
S
.
S
u
rf
a
c
e
Ba
se
d
S
tru
c
t
u
re
An
a
lys
is
a
n
d
Vi
su
a
li
z
a
ti
o
n
f
o
r
M
u
lt
if
ield
T
ime
Va
ry
in
g
Da
t
a
se
ts
,
Visu
a
li
z
a
ti
o
n
a
n
d
C
o
m
p
u
ter G
ra
p
h
ics
,
IEE
E
T
r
a
n
sa
c
ti
o
n
s
,
(
1
2
).
[2
]
E
W
e
s
Be
th
e
l,
Ke
sh
e
n
g
W
u
,
J
o
h
n
S
h
a
lf
,
Ku
rt
S
to
c
k
in
g
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r.
Qu
e
ry
Dr
ive
n
Vi
su
a
li
za
ti
o
n
o
f
L
a
r
g
e
Da
ta
S
e
ts
,
IEE
E_
V
IS
,
2
0
0
5
,
V
isu
a
l
iza
ti
o
n
Co
n
f
e
re
n
c
e
.
2
0
0
5
.
[3
]
Jo
h
n
C
A
n
d
e
rso
n
,
Ke
n
Jo
y
,
L
u
k
e
G
o
sin
k
,
W
e
s
Be
th
e
l.
Va
ria
b
le
In
ter
a
c
ti
o
n
s
in
Qu
e
ry
Dr
ive
n
Vi
su
a
li
za
ti
o
n
,
i
n
:
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Vi
su
a
li
za
t
i
o
n
a
n
d
Co
m
p
u
ter
Gr
a
p
h
ics
.
2
0
0
7
.
[4
]
Dr
Bh
a
v
a
n
i
T
h
u
ra
isin
g
h
a
m
,
Dr
G
e
o
rg
e
s
G
rin
ste
in
.
Da
t
a
M
in
i
n
g
a
n
d
Da
ta
Vi
su
a
li
za
ti
o
n
,
P
o
siti
o
n
P
a
p
e
r
f
o
r
t
h
e
S
e
c
o
n
d
IEE
E
W
o
rk
sh
o
p
o
n
Da
t
a
b
a
se
Iss
u
e
s fo
r Da
t
a
Vi
s
u
a
l
iza
ti
o
n
.
[5
]
V
ik
to
r
M
e
d
v
e
d
e
v
,
G
in
tau
tas
Dz
e
m
y
d
a
,
S
e
r
g
ė
ju
s
Iv
a
n
ik
o
v
a
s.
L
a
r
g
e
Da
ta
se
ts
Vi
su
a
li
z
a
ti
o
n
wit
h
Ne
u
ra
l
Ne
two
rk
Us
in
g
Cl
u
ste
re
d
T
ra
i
n
i
n
g
D
a
ta
,
S
p
rin
g
e
r B
e
rli
n
He
id
e
l
b
e
rg
,
S
e
rie
s
.
[6
]
S
m
it
h
S
,
De
laru
e
A
.
AUV
d
a
ta
p
ro
c
e
ss
in
g
a
n
d
v
isu
a
li
z
a
ti
o
n
u
sin
g
GI
S
a
n
d
In
ter
n
e
t
tec
h
n
i
q
u
es
,
OCEANS
'9
9
M
T
S
/IE
EE
.
Rid
i
n
g
th
e
Cre
st i
n
to
th
e
2
1
st Cen
t
u
ry
.
[7
]
Up
a
d
h
y
a
y
A
,
S
h
e
tt
y
A
,
S
in
g
h
S
K,
S
id
d
i
q
u
i
Z.
L
a
n
d
u
se
a
n
d
l
a
n
d
c
o
v
e
r
c
la
ss
if
ica
ti
o
n
o
f
L
I
S
S
-
III
sa
telli
te
im
a
g
e
u
sin
g
KNN
a
n
d
d
e
c
isio
n
tre
e
.
In
Co
m
p
u
ti
n
g
f
o
r
S
u
sta
in
a
b
le
G
lo
b
a
l
De
v
e
lo
p
m
e
n
t
(IND
I
ACo
m
),
2
0
1
6
3
r
d
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
IE
E
E.
M
a
rc
h
,
2
0
1
6
;
1
2
7
7
-
1
2
8
0
.
[8
]
Ka
rth
ik
S
.
Rem
o
te
o
p
e
ra
ted
u
n
d
e
rwa
ter
we
ld
i
n
g
v
e
h
icle
,
2
1
st
Offsh
o
re
S
y
mp
o
siu
m
2
0
1
6
:
Eme
rg
in
g
Offsh
o
re
T
e
c
h
n
o
l
o
g
y
a
n
d
De
e
p
wa
ter
T
re
n
d
s
.
2
0
1
6
;
5
3
2
-
5
3
9
.
[9
]
Ha
ss
a
n
,
W
.
,
M
.
Ak
m
a
l,
a
n
d
M
.
Ka
m
ra
n
,
“
P
o
rtab
le
a
n
d
c
o
m
p
a
c
t
g
ro
u
n
d
i
n
g
s
y
ste
m
.
In
P
o
w
e
r
En
g
in
e
e
rin
g
Co
n
f
e
re
n
c
e
(UP
EC),
”
2
0
1
3
4
8
t
h
In
tern
a
ti
o
n
a
l
U
n
iv
e
rsiti
e
s'
.
2
0
1
3
.
M
.
P
.
Bro
w
n
a
n
d
K.
A
u
stin
,
A
p
p
l.
P
h
y
s.
L
e
tt
e
r
s
8
5
,
2
5
0
3
–
2
5
0
4
(
2
0
0
4
).
Evaluation Warning : The document was created with Spire.PDF for Python.