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4
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T
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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5
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52
In
d
o
n
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J
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&
C
o
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p
Sci
,
Vo
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3
6
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No
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2
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v
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b
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20
24
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1
3
2
9
-
133
7
1330
T
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atter
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s
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ata
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ti
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g
co
m
p
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n
en
t
in
3
D
v
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u
aliza
tio
n
[7
]
,
[
8]
in
wh
ich
th
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s
tu
d
y
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u
s
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th
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p
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ates
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.
2.
M
E
T
H
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D
T
h
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p
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ata
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p
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u
p
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e,
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ar
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itectu
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ith
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th
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k
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a
r
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itectu
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o
f
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e
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p
o
s
ed
f
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k
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o
wn
in
Fig
u
r
e
1
.
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en
tir
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ch
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is
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i
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r
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v
is
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T
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h
e
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ata
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h
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p
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at
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e
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ataset.
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h
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ata
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n
d
er
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o
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es
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ith
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ased
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Fin
ally
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t
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e
v
is
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ali
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tio
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p
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m
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m
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T
h
e
im
p
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v
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t
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th
is
lay
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ac
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iev
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in
th
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f
r
am
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m
o
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if
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g
th
e
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tin
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ith
m
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ig
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ter
p
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to
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ed
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ce
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ar
tifa
cts d
u
r
in
g
th
e
v
is
u
aliza
tio
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in
3
D
m
o
d
e.
Fig
u
r
e
1
.
Ar
c
h
itectu
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d
iag
r
a
m
o
f
th
e
p
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f
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2
.
1
.
Da
t
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T
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all
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ats.
A
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2
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Da
t
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T
h
e
d
ata
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an
a
g
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lay
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in
to
th
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ap
p
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f
o
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at.
Date
p
re
-
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s
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:
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h
is
lay
er
p
lay
s
an
im
p
o
r
tan
t
r
o
le
in
th
e
a
r
ch
itect
u
r
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-
p
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s
s
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elp
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th
at
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d
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co
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t,
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d
s
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f
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is
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clea
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to
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v
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o
r
c
o
r
r
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t
a
n
y
e
r
r
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r
s
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ata
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r
r
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r
s
ca
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cc
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m
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ter
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k
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.
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b
in
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ata
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s
s
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h
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r
ties
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r
b
y
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in
g
d
ata
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ased
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tim
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o
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tio
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.
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n
ter
p
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th
e
p
r
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ce
s
s
o
f
esti
m
atin
g
m
is
s
in
g
d
ata
p
o
in
ts
f
r
o
m
n
ea
r
b
y
d
ata
p
o
i
n
ts
.
W
h
en
th
er
e
ar
e
g
ap
s
in
t
h
e
d
ata
o
r
m
is
s
in
g
v
alu
es,
in
te
r
p
o
latio
n
is
f
r
eq
u
en
tly
r
eq
u
ir
ed
.
Fo
r
m
at
co
n
v
er
s
io
n
:
d
if
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er
en
t
f
o
r
m
ats
(
an
d
also
d
if
f
er
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t
c
o
o
r
d
in
ate
s
y
s
tem
s
)
p
o
s
e
a
ch
allen
g
e
i
n
d
ata
v
is
u
aliza
tio
n
.
T
h
e
co
m
m
o
n
d
ata
f
o
r
m
ats
wh
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ar
e
s
u
p
p
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ted
b
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th
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p
r
o
p
o
s
ed
to
o
l
in
clu
d
e
NetCDF
,
ASC
I
I
,
B
in
ar
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d
HDF.
NetCDF
i
s
th
e
m
o
s
t
wid
ely
u
s
ed
d
ata
f
o
r
m
at.
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is
m
ac
h
in
e
-
in
d
ep
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n
d
en
t
,
an
d
is
s
elf
-
d
escr
ip
tiv
e
in
n
atu
r
e
.
B
ec
au
s
e
it
is
s
im
p
le
to
ac
ce
s
s
s
u
b
s
ets
o
f
a
d
ataset,
NetCDF
d
ata
ar
e
ea
s
ily
s
ca
lab
le.
T
o
p
r
o
ce
s
s
NetCD
F
f
iles
q
u
ick
ly
an
d
ef
f
ec
tiv
ely
,
it
is
u
s
u
ally
d
esira
b
le
to
cr
ea
te
a
s
u
b
s
et
o
f
d
ata
f
r
o
m
th
e
en
o
r
m
o
u
s
f
ile.
T
h
e
to
o
l is ca
p
ab
le
o
f
c
o
n
v
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r
tin
g
th
e
u
n
s
tr
u
ctu
r
e
d
m
ea
s
u
r
ed
d
ata
to
s
tr
u
ctu
r
ed
d
ata.
2
.
3
.
Da
t
a
re
nd
er
ing
eng
ine
I
n
th
is
lay
er
,
th
e
o
ce
an
o
g
r
ap
h
ic
d
ata
is
r
en
d
er
ed
t
o
g
e
n
er
ate
2
D
an
d
3
D
im
ag
es
o
r
an
i
m
atio
n
f
r
o
m
a
3
D
s
ce
n
e.
T
h
e
r
e
n
d
er
in
g
p
ip
e
lin
e
h
as
a
s
eq
u
en
ce
o
f
s
tag
es
lik
e
g
eo
m
etr
ic
p
r
o
ce
s
s
in
g
,
r
as
ter
izatio
n
,
s
h
ad
in
g
,
tex
tu
r
in
g
a
n
d
b
len
d
in
g
to
tr
an
s
f
o
r
m
th
e
o
ce
an
o
g
r
ap
h
ic
d
ata
to
a
2
D/3
D
im
ag
e
o
r
a
n
im
atio
n
.
T
h
e
2
D
im
a
g
es
ar
e
r
en
d
er
ed
with
th
e
s
u
p
p
o
r
t
o
f
v
ec
to
r
f
ield
ex
tr
ac
tio
n
f
r
o
m
d
ata
f
o
llo
wed
b
y
lin
e
r
en
d
er
in
g
a
n
d
s
u
r
f
ac
e
r
en
d
er
in
g
.
W
h
en
3
D
im
ag
es
ar
e
r
en
d
er
ed
,
v
o
lu
m
e
r
en
d
er
i
n
g
a
n
d
is
s
u
r
f
ac
e
r
en
d
er
in
g
s
ch
em
es
ar
e
ad
o
p
ted
.
R
en
d
er
in
g
is
a
co
m
p
u
tatio
n
all
y
in
ten
s
iv
e
p
r
o
ce
s
s
an
d
,
in
th
i
s
wo
r
k
,
th
e
s
am
e
is
im
p
lem
en
ted
u
s
in
g
th
e
ce
n
tr
al
p
r
o
ce
s
s
in
g
u
n
it
(
C
PU)
o
r
th
e
g
r
ap
h
ics p
r
o
ce
s
s
in
g
u
n
it
(
GPU)
.
I
n
th
e
C
PU
im
p
lem
en
tatio
n
p
ar
t,
th
e
g
r
id
d
ed
d
ata
m
an
ag
e
m
en
t
s
ch
em
e
is
ad
o
p
ted
.
Fo
r
in
s
tan
ce
,
i
n
o
ce
an
o
g
r
ap
h
ic
d
ata
an
aly
s
is
,
tem
p
er
atu
r
e
r
ea
d
in
g
s
ar
e
g
ath
er
ed
at
d
if
f
er
en
t
d
ep
th
s
a
n
d
lo
ca
tio
n
s
u
s
in
g
s
en
s
o
r
s
o
r
s
atellites.
T
h
ese
d
a
ta
p
o
in
ts
ca
n
b
e
in
ter
p
o
lated
a
n
d
r
en
d
er
ed
u
s
in
g
f
in
ite
d
i
f
f
er
en
ce
m
eth
o
d
s
[
1
4
]
o
r
r
a
y
ca
s
tin
g
al
g
o
r
ith
m
[
1
5
]
.
T
h
e
r
esu
ltin
g
v
is
u
aliza
tio
n
s
ca
n
b
e
u
s
ed
to
b
etter
u
n
d
e
r
s
tan
d
th
e
t
h
er
m
al
s
tr
u
ctu
r
e
o
f
th
e
o
ce
a
n
an
d
h
el
p
to
id
en
tify
r
e
g
io
n
s
o
f
h
ea
t e
x
ch
an
g
e
b
etwe
en
th
e
o
ce
a
n
an
d
th
e
atm
o
s
p
h
er
e.
I
n
C
PU
r
en
d
er
in
g
,
th
e
co
m
p
u
ter
p
er
f
o
r
m
s
ca
lcu
latio
n
s
i
n
a
s
e
r
ial
f
ash
io
n
,
ex
ec
u
tin
g
o
n
e
in
s
tr
u
ctio
n
at
a
tim
e.
T
h
is
is
th
e
s
o
le
r
ea
s
o
n
b
eh
in
d
its
ac
cu
r
ac
y
as we
ll a
s
th
e
s
lo
w
r
en
d
er
in
g
s
p
ee
d
.
I
n
th
e
GPU
im
p
lem
en
tatio
n
p
ar
t,
th
e
g
r
id
d
ed
d
ata
is
m
an
ag
ed
u
s
in
g
an
o
ctr
ee
d
ata
s
tr
u
ct
u
r
e.
Octr
ee
[
1
6
]
is
a
d
ata
s
tr
u
ctu
r
e
th
at
ca
n
b
e
u
s
ed
to
r
ep
r
esen
t
v
o
l
u
m
e
tr
ic
d
ata
s
u
c
h
as
o
ce
an
tem
p
e
r
atu
r
e,
s
alin
ity
an
d
cu
r
r
en
ts
.
Octr
ee
s
ar
e
tr
ee
-
b
ased
d
ata
s
tr
u
ctu
r
es
th
at
r
ec
u
r
s
iv
ely
d
iv
id
e
a
3
D
s
p
ac
e
in
to
eig
h
t
eq
u
al
-
s
ized
s
u
b
s
p
ac
es,
o
r
o
ctan
ts
.
T
h
e
o
ctr
ee
s
tr
u
ctu
r
e
allo
ws
ef
f
icien
t
co
m
p
r
ess
io
n
o
f
d
ata,
b
y
s
to
r
in
g
o
n
ly
th
e
m
o
s
t
s
ig
n
if
ican
t
d
ata
v
alu
es
in
th
e
p
ar
en
t
n
o
d
es,
wh
ile
th
e
m
o
r
e
d
etailed
d
ata
v
alu
es
ar
e
s
to
r
ed
in
th
e
ch
ild
n
o
d
es.
E
ac
h
o
ctr
ee
n
o
d
e
ca
n
b
e
d
ef
in
ed
b
y
its
co
o
r
d
in
ates
in
3
D
s
p
ac
e,
r
ep
r
esen
ted
as
a
v
e
cto
r
(
x
,
y
,
z)
.
T
h
e
co
o
r
d
in
ates
o
f
th
e
r
o
o
t
n
o
d
e
ar
e
u
s
u
ally
d
e
f
in
ed
as
(
0
,
0
,
0
)
,
an
d
th
e
co
o
r
d
i
n
ates
o
f
ea
c
h
ch
ild
n
o
d
e
ca
n
b
e
ca
lcu
lated
u
s
in
g
th
e
(
1
)
:
ℎ
_
=
_
+
/
2
∗
(
2
∗
_
ℎ
−
1
)
(
1
)
wh
er
e
in
d
ex
_
c
h
ild
is
an
in
teg
er
b
etwe
en
1
an
d
8
r
ep
r
esen
t
in
g
th
e
in
d
ex
o
f
th
e
ch
ild
n
o
d
e,
an
d
s
ize
is
th
e
len
g
th
o
f
th
e
s
id
e
o
f
th
e
p
a
r
en
t
n
o
d
e.
T
h
e
r
e
p
r
esen
tatio
n
o
f
a
n
o
ctr
ee
is
in
tr
ee
f
o
r
m
is
g
i
v
e
n
in
Fig
u
r
e
2
.
T
o
co
n
s
tr
u
ct
an
o
ctr
ee
,
th
e
3
D
s
p
ac
e
is
r
ec
u
r
s
iv
ely
s
u
b
d
iv
id
ed
in
to
s
m
aller
cu
b
es
u
n
til
th
e
d
esire
d
lev
el
o
f
d
etail
is
r
ea
c
h
ed
.
T
h
e
s
u
b
d
iv
is
io
n
alg
o
r
ith
m
ty
p
icall
y
wo
r
k
s
b
y
ch
ec
k
in
g
wh
eth
er
ea
ch
cu
b
e
c
o
n
tain
s
an
y
d
ata
p
o
in
ts
,
a
n
d
if
s
o
,
d
i
v
id
in
g
it
in
to
eig
h
t
s
m
aller
c
u
b
es.
T
h
e
s
u
b
d
i
v
is
io
n
ca
n
b
e
p
e
r
f
o
r
m
e
d
u
s
in
g
th
e
f
o
llo
win
g
s
tep
s
:
i)
C
h
ec
k
if
th
e
cu
r
r
en
t c
u
b
e
co
n
tain
s
an
y
d
ata
p
o
in
ts
.
ii)
I
f
th
e
cu
b
e
is
to
o
s
m
all
o
r
c
o
n
t
ain
s
n
o
d
ata
p
o
in
ts
,
m
ar
k
it a
s
a
leaf
n
o
d
e
an
d
s
to
p
iii)
Oth
er
wis
e,
d
iv
id
e
th
e
cu
b
e
in
t
o
eig
h
t sm
aller
cu
b
es.
iv
)
R
ec
u
r
s
iv
ely
ap
p
ly
th
e
s
u
b
d
iv
i
s
io
n
alg
o
r
ith
m
t
o
ea
ch
o
f
th
e
s
m
aller
cu
b
es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
1
3
2
9
-
133
7
1332
Fig
u
r
e
2
.
Me
s
h
r
e
p
r
esen
tatio
n
o
f
an
o
ctr
ee
Fo
r
ex
am
p
le,
to
r
ep
r
esen
t
s
ea
s
u
r
f
ac
e
tem
p
er
atu
r
e
(
SS
T
)
u
s
in
g
an
o
ctr
ee
,
we
ca
n
d
iv
id
e
th
e
o
ce
a
n
s
u
r
f
ac
e
in
to
o
ctan
ts
an
d
ass
ig
n
a
tem
p
er
atu
r
e
v
alu
e
to
ea
c
h
o
ctan
t.
T
h
e
o
ctr
ee
ca
n
b
e
b
u
ilt
r
ec
u
r
s
iv
ely
b
y
d
iv
id
in
g
ea
ch
o
ctan
t
in
to
eig
h
t
s
m
aller
o
ctan
ts
u
n
til
a
d
es
ir
ed
lev
el
o
f
d
etail
is
ac
h
iev
e
d
.
On
e
a
p
p
r
o
ac
h
to
r
ep
r
esen
tin
g
SST
u
s
in
g
an
o
c
tr
ee
is
to
u
s
e
a
m
u
lti
-
r
eso
lu
tio
n
r
ep
r
esen
tatio
n
,
wh
er
e
ea
ch
lev
el
o
f
th
e
o
ctr
ee
r
ep
r
esen
ts
a
d
if
f
er
e
n
t
lev
el
o
f
d
etail.
At
th
e
h
ig
h
est
lev
el
o
f
th
e
o
ctr
ee
,
ea
ch
o
ctan
t
r
ep
r
esen
ts
a
lar
g
e
ar
ea
o
f
th
e
o
ce
an
s
u
r
f
ac
e
with
a
lo
w
l
ev
el
o
f
d
etail,
an
d
at
lo
wer
lev
els
o
f
th
e
o
ctr
ee
,
ea
ch
o
ctan
t
r
ep
r
esen
ts
a
s
m
aller
ar
ea
with
a
h
ig
h
er
le
v
el
o
f
d
e
tail.
T
o
s
to
r
e
th
e
tem
p
er
atu
r
e
v
alu
es
in
th
e
o
ctr
ee
,
a
h
ash
tab
le
ca
n
b
e
u
s
ed
to
s
to
r
e
th
e
v
alu
e
ass
o
ciate
d
w
ith
ea
ch
o
ctan
t.
Octr
ee
s
ar
e
th
u
s
u
s
ef
u
l
f
o
r
lev
el
-
of
-
d
etai
l
r
en
d
e
r
in
g
,
wh
er
e
d
if
f
er
en
t
lev
els
o
f
d
etail
ca
n
b
e
d
is
p
lay
ed
b
ased
o
n
t
h
e
d
i
s
tan
ce
f
r
o
m
th
e
o
b
s
er
v
er
.
T
h
e
lev
el
o
f
d
etail
is
d
eter
m
in
ed
b
y
th
e
d
e
p
th
o
f
t
h
e
o
ctr
ee
.
T
h
is
ca
n
b
e
p
ar
tic
u
lar
ly
u
s
ef
u
l
f
o
r
in
ter
ac
tiv
e
v
is
u
aliza
tio
n
o
f
lar
g
e
o
ce
an
o
g
r
ap
h
ic
d
atasets
.
T
h
e
o
ctr
ee
tr
av
er
s
al
tr
ac
es
th
e
r
a
y
an
d
its
co
llis
io
n
with
th
e
s
ce
n
e.
T
h
e
r
e
n
d
er
i
n
g
s
p
ee
d
in
GPU
im
p
lem
en
tatio
n
is
f
u
r
th
er
im
p
r
o
v
e
d
u
s
in
g
s
o
r
ted
s
ib
lin
g
tr
av
er
s
al
[
1
7
]
b
y
th
e
r
ay
as
d
escr
ib
ed
in
th
e
f
o
llo
win
g
s
tep
s
.
1)
Star
t a
t th
e
r
o
o
t
2)
I
f
th
e
r
a
y
in
ter
s
ec
ts
th
e
r
o
o
t
b
o
u
n
d
s
,
ch
ec
k
th
e
ch
ild
r
en
I
f
th
e
ch
ild
is
a
n
o
n
-
leaf
,
f
in
d
t
h
e
n
ea
r
est ch
ild
clo
s
est to
th
e
r
ay
o
r
i
g
in
,
b
y
co
m
p
ar
in
g
with
b
asis
x
,
y
,
an
d
z
p
lan
es
i.
T
o
d
eter
m
in
e
wh
ich
o
f
th
e
p
a
r
en
t n
o
d
e
’
s
th
r
ee
ax
is
p
lan
es th
e
r
ay
h
as c
o
llid
e
d
with
,
lo
o
k
f
o
r
th
e
n
ex
t c
lo
s
est s
ib
lin
g
.
ii.
T
h
e
en
tr
y
p
o
in
t
o
f
th
e
b
ea
m
in
to
th
e
n
ex
t c
l
o
s
est s
ib
lin
g
will
b
e
r
ev
ea
led
b
y
th
e
clo
s
est p
lan
e
th
at
is
s
tr
u
ck
.
iii.
I
f
n
o
p
lan
e
is
s
tr
u
ck
,
t
h
en
th
e
r
ay
is
h
ea
d
ed
o
u
t o
f
th
e
n
o
d
e
a
n
d
will n
o
t h
it a
n
y
o
t
h
er
ch
ild
r
en
o
f
th
e
cu
r
r
en
t
p
ar
en
t.
3)
E
ls
e,
h
alt
th
e
en
tire
p
r
o
ce
s
s
.
2
.
4
.
P
y
t
ho
n
i
nte
rf
a
ce
Py
th
o
n
h
as
a
wid
e
v
a
r
iety
o
f
p
ac
k
ag
es
th
at
ca
n
b
e
u
s
ed
to
v
i
s
u
alize
o
ce
an
p
a
r
am
eter
s
.
Dep
en
d
in
g
o
n
th
e
p
ar
ticu
lar
r
eq
u
ir
em
en
ts
,
o
n
e
o
r
m
o
r
e
o
f
th
ese
lib
r
a
r
ies
m
ay
b
e
u
s
ef
u
l.
T
h
e
k
ey
v
is
u
aliza
tio
n
to
o
ls
in
th
e
s
u
g
g
ested
f
r
am
ewo
r
k
f
o
r
d
at
a
an
aly
s
is
ar
e
Ma
tp
lo
tlib
an
d
Plo
tly
.
A
well
-
k
n
o
wn
Py
th
o
n
d
ata
v
is
u
alis
atio
n
to
o
lk
it
ca
lled
Ma
tp
lo
tlib
p
r
o
v
i
d
es
s
ev
er
al
to
o
ls
f
o
r
m
ak
in
g
p
lo
ts
,
ch
ar
ts
,
an
d
g
r
ap
h
s
.
I
t
m
a
y
s
h
o
w
a
v
a
r
iety
o
f
o
ce
an
p
a
r
am
eter
s
,
in
clu
d
in
g
t
em
p
er
atu
r
e,
s
alin
ity
,
s
ea
lev
e
l,
an
d
c
u
r
r
en
ts
.
A
Py
t
h
o
n
m
o
d
u
le
ca
lled
Plo
tly
en
ab
les
u
s
to
m
a
k
e
in
te
r
ac
tiv
e,
web
-
b
ased
v
is
u
aliza
tio
n
s
.
Ma
k
in
g
i
n
ter
ac
tiv
e
m
ap
s
,
s
ca
t
ter
p
lo
ts
,
lin
e
p
l
o
ts
,
an
d
o
th
e
r
v
is
u
aliza
tio
n
s
is
p
o
s
s
ib
le
with
it.
Py
th
o
n
Qt
is
u
s
ed
as
th
e
g
r
ap
h
ical
u
s
er
in
ter
f
ac
e
(
GUI
)
f
o
r
in
ter
ac
tiv
e
v
is
u
aliza
tio
n
.
C
r
ea
tin
g
h
ig
h
-
q
u
ality
,
n
ativ
e
-
l
o
o
k
in
g
ap
p
s
with
a
co
n
s
is
ten
t u
s
er
in
ter
f
ac
e
an
d
b
eh
a
v
io
u
r
ac
r
o
s
s
p
latf
o
r
m
s
is
s
tr
aig
h
tf
o
r
war
d
with
Qt
’
s
wid
e
r
an
g
e
o
f
to
o
l
s
an
d
m
o
d
u
les.
Py
th
o
n
p
r
o
g
r
am
m
er
s
ca
n
u
s
e
th
e
Py
Qt
o
r
Py
Sid
e
lib
r
ar
ies
to
ac
ce
s
s
th
e
Qt
f
r
am
ewo
r
k
.
Py
Sid
e
is
an
alter
n
ate
s
et
o
f
b
in
d
in
g
s
th
at
is
o
n
l
y
p
ar
tially
c
o
m
p
atib
le
with
Py
Qt,
wh
ich
is
a
s
et
o
f
Py
t
h
o
n
b
in
d
i
n
g
s
f
o
r
th
e
Qt
f
r
am
ewo
r
k
.
T
h
e
Qt
f
r
am
ewo
r
k
in
clu
d
es
ess
en
tial
elem
en
ts
s
u
ch
as
Qt
C
o
r
e,
Qt
GUI
,
an
d
Qt
W
id
g
ets.
Qt
C
o
r
e
p
r
o
v
i
d
es
n
o
n
-
GUI
f
ea
tu
r
es
lik
e
ev
e
n
t
m
an
ag
em
en
t,
d
ata
s
to
r
ag
e,
n
etwo
r
k
in
g
,
a
n
d
th
r
e
ad
in
g
.
Qt
GUI
o
f
f
e
r
s
to
o
ls
f
o
r
b
u
ild
in
g
g
r
ap
h
ical
u
s
er
i
n
ter
f
ac
es,
in
clu
d
i
n
g
wid
g
ets,
lay
o
u
ts
,
an
d
ev
en
t
h
an
d
lin
g
,
wh
ile
Qt
w
id
g
ets
co
n
tain
s
r
eu
s
ab
le
UI
elem
en
ts
l
ik
e
m
en
u
s
,
b
u
tto
n
s
,
an
d
tex
t e
d
ito
r
s
,
alo
n
g
with
lay
o
u
t m
a
n
ag
er
s
f
o
r
o
r
g
an
izin
g
wid
g
ets.
2
.
5
.
Vis
ua
liza
t
io
n
l
a
y
er
T
h
e
o
b
jectiv
e
o
f
v
is
u
aliza
tio
n
lay
er
is
to
p
r
o
v
id
e
u
n
i
v
ar
i
ate
an
d
m
u
ltiv
ar
iate
v
is
u
aliza
tio
n
o
f
th
e
o
ce
an
o
g
r
ap
h
ic
d
ataset.
T
h
e
u
n
iv
ar
iate
v
is
u
aliza
tio
n
tech
n
iq
u
es
ar
e
av
ailab
le
in
d
if
f
er
en
t
m
eth
o
d
s
lik
e
(
a)
co
lo
r
m
ap
s
,
(
b
)
v
ec
to
r
p
lo
ts
,
(
c)
co
n
to
u
r
p
lo
ts
,
(
d
)
s
tick
p
l
o
t
,
(
e)
s
tr
ea
m
lin
e
p
lo
ts
,
an
d
(
f
)
r
o
s
e
p
lo
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
in
tera
ctive
visu
a
liz
a
tio
n
to
o
l fo
r
th
e
ex
p
lo
r
a
tio
n
a
n
d
…
(
P
r
ee
th
a
K
.
G
.
)
1333
T
h
e
m
atp
l
o
tlib
lib
r
ar
y
in
Py
th
o
n
in
cl
u
d
es
th
e
‘
cm
o
ce
an
’
m
o
d
u
le,
wh
ic
h
co
n
tain
s
co
lo
r
m
a
p
s
tailo
r
ed
to
s
p
ec
if
ic
o
ce
an
o
g
r
a
p
h
ic
v
a
r
iab
les,
s
u
ch
as
th
er
m
al,
h
alin
e,
ice,
o
x
y
,
a
n
d
alg
ae
.
Fo
r
e
x
am
p
le,
th
e
‘
alg
ae
’
co
lo
r
m
ap
in
s
h
a
d
es
o
f
g
r
ee
n
r
ep
r
esen
ts
ch
lo
r
o
p
h
y
ll,
wh
ile
th
e
‘
th
er
m
al
’
c
o
lo
r
m
a
p
tr
an
s
itio
n
s
f
r
o
m
d
ar
k
b
l
u
e
to
y
ello
w
f
o
r
tem
p
e
r
atu
r
e
v
al
u
es.
T
h
ese
c
o
lo
r
m
a
p
s
ar
e
p
r
e
f
er
r
ed
o
v
er
co
n
v
en
tio
n
al
o
n
es
lik
e
‘
r
ain
b
o
w
’
an
d
‘
jet
’
f
o
r
b
etter
co
g
n
itio
n
in
o
ce
an
o
g
r
a
p
h
ic
d
ata
v
is
u
aliza
tio
n
.
Fo
r
v
is
u
alizin
g
o
ce
an
o
g
r
ap
h
ic
d
ata
with
m
ag
n
itu
d
e
an
d
d
ir
e
ctio
n
,
s
u
c
h
as
win
d
an
d
c
u
r
r
en
t,
v
ec
t
o
r
p
lo
ts
,
s
tick
p
lo
ts
,
an
d
s
tr
ea
m
lin
e
p
lo
ts
ar
e
u
s
ed
.
T
h
e
‘
q
u
i
v
er
’
f
u
n
ctio
n
i
n
Py
t
h
o
n
h
el
p
s
p
lo
t
v
ec
to
r
a
n
d
s
tick
r
ep
r
esen
tatio
n
s
,
an
d
th
e
‘
s
tr
ea
m
p
lo
t
’
f
u
n
ctio
n
p
r
o
v
id
es
s
tr
ea
m
lin
e
p
l
o
ts
illu
s
tr
atin
g
th
e
v
elo
city
f
ield
’
s
d
en
s
ity
an
d
m
ag
n
itu
d
e.
A
d
d
itio
n
a
lly
,
th
e
‘
b
ar
_
p
o
lar
’
f
u
n
ctio
n
in
m
atp
lo
tlib
ca
n
p
l
o
t
r
o
s
e
ch
ar
ts
to
v
is
u
alize
win
d
s
p
ee
d
an
d
d
ir
ec
tio
n
d
is
tr
ib
u
tio
n
s
at
a
g
iv
en
lo
ca
tio
n
.
W
h
ile
r
en
d
er
in
g
c
o
n
to
u
r
p
lo
ts
in
2
D
an
d
3
D
v
is
u
aliza
tio
n
,
t
h
e
r
e
n
d
er
in
g
s
p
ee
d
s
u
f
f
e
r
s
as
th
er
e
ar
e
n
o
t
s
u
f
f
icien
t
p
o
in
ts
av
ailab
le
as
s
am
p
les
in
th
e
s
p
atial
a
r
ea
co
n
s
id
er
ed
.
T
h
u
s
,
th
e
o
c
ea
n
o
g
r
a
p
h
ic
d
ata
is
ch
ar
ac
ter
ized
o
f
n
o
n
-
u
n
if
o
r
m
s
ec
tio
n
in
ter
v
al
(
e
g
-
d
ep
t
h
s
at
n
o
n
-
u
n
if
o
r
m
in
te
r
v
als
in
Ar
g
o
f
lo
at)
.
Hen
ce
,
to
s
p
ee
d
u
p
th
e
r
a
y
-
ca
s
tin
g
alg
o
r
ith
m
f
o
r
v
o
lu
m
e
r
e
n
d
er
in
g
,
ap
p
r
o
p
r
iate
s
p
atial
in
ter
p
o
latio
n
tech
n
iq
u
e
is
to
b
e
ad
o
p
ted
.
T
h
e
s
p
atial
in
ter
p
o
la
tio
n
m
eth
o
d
c
h
o
s
en
is
k
r
ig
in
g
[
1
8
]
.
Kr
ig
in
g
u
s
es
a
lin
ea
r
co
m
b
in
atio
n
o
f
th
e
o
b
s
er
v
ed
v
al
u
es
in
th
e
ad
jace
n
t
n
o
d
es
o
f
th
e
o
ctr
ee
,
with
weig
h
ts
d
eter
m
in
ed
b
y
th
eir
s
p
atial
co
r
r
elatio
n
,
g
iv
en
as
(
2
)
.
(
)
=
∑
(
)
(
2
)
wh
er
e
Z
(
x
)
is
th
e
esti
m
ated
v
alu
e
o
f
th
e
v
ar
iab
le
at
th
e
tar
g
et
lo
ca
tio
n
x
,
λ
i
is
th
e
weig
h
t
ass
ig
n
ed
to
th
e
i
-
th
o
b
s
er
v
atio
n
at
lo
ca
tio
n
x
i
,
a
n
d
th
e
s
u
m
m
atio
n
is
tak
en
o
v
er
all
th
e
o
b
s
er
v
atio
n
s
wi
th
in
th
e
s
p
ec
if
ie
d
n
eig
h
b
o
r
h
o
o
d
ar
o
u
n
d
th
e
tar
g
et
lo
ca
tio
n
.
T
h
e
weig
h
ts
ar
e
d
eter
m
in
ed
b
y
a
v
ar
i
o
g
r
a
m
th
at
d
escr
ib
es
th
e
s
p
atial
co
r
r
elatio
n
b
etwe
en
th
e
v
ar
iab
le
at
d
if
f
er
en
t
lo
ca
tio
n
s
.
T
h
e
s
elec
tio
n
o
f
th
e
v
ar
io
g
r
am
to
b
e
u
s
ed
in
k
r
ig
in
g
f
o
r
a
p
ar
ticu
lar
v
ar
iab
le,
s
ay
,
SS
T
d
ata
is
in
f
lu
en
ce
d
b
y
a
n
u
m
b
er
o
f
v
ar
iab
les,
i
n
clu
d
in
g
t
h
e
s
p
atial
s
ca
le
o
f
th
e
SS
T
v
ar
iab
ilit
y
,
th
e
s
am
p
lin
g
d
en
s
ity
o
f
th
e
d
ata,
an
d
th
e
u
n
d
e
r
ly
in
g
p
h
y
s
ical
p
r
o
ce
s
s
es
th
at
p
r
o
d
u
ce
th
e
SS
T
v
ar
iab
ilit
y
.
I
n
th
is
im
p
lem
en
tatio
n
,
an
is
o
tr
o
p
ic
v
ar
io
g
r
am
is
ch
o
s
en
,
as
th
e
SS
T
d
ata
v
ar
ies
in
d
if
f
er
e
n
t d
ir
ec
tio
n
s
[
1
9
]
,
[
2
0
]
.
T
h
e
an
is
o
tr
o
p
ic
v
ar
io
g
r
am
is
ex
p
r
ess
ed
as
(
3
)
.
(
ℎ
)
=
1
/
2
∗
[
(
(
)
−
(
+
ℎ
)
)
^
2
]
(
3
)
wh
er
e
h
is
th
e
lag
d
is
tan
ce
,
Z
(
x
)
is
th
e
v
ar
iab
le
o
f
i
n
ter
est at
lo
ca
tio
n
x
,
an
d
E
[
2
1
]
d
e
n
o
tes th
e
ex
p
ec
ted
v
al
u
e
o
p
er
ato
r
.
T
h
e
lag
d
is
tan
ce
,
h
,
ca
n
b
e
r
ep
lace
d
b
y
a
lag
v
ec
to
r
h
=(
h
₁,
h
₂,
h
₃)
an
d
th
e
co
v
a
r
ian
ce
b
etwe
en
two
lo
ca
tio
n
s
is
a
f
u
n
ctio
n
o
f
th
e
l
ag
v
ec
to
r
an
d
th
e
o
r
ien
tatio
n
o
f
th
e
an
is
o
tr
o
p
y
.
A
r
o
tatio
n
m
atr
ix
R
ca
n
b
e
u
s
ed
to
tr
an
s
f
o
r
m
th
e
lag
v
ec
to
r
,
h
,
in
to
a
n
ew
co
o
r
d
in
ate
s
y
s
tem
as
(
4
)
.
(
ℎ
)
=
1
/
2
∗
[
(
(
)
−
(
+
ℎ
)
)
^
2
]
(
4
)
wh
er
e
R
h
is
th
e
lag
v
ec
to
r
in
t
h
e
n
ew
co
o
r
d
in
ate
s
y
s
tem
.
T
h
u
s
,
with
k
r
ig
in
g
,
th
e
s
am
p
lin
g
s
tep
o
f
r
ay
ca
s
tin
g
al
g
o
r
ith
m
r
esu
lts
in
less
ar
tif
ac
ts
.
T
h
e
v
is
u
aliza
tio
n
lay
er
also
p
r
o
v
id
es
m
u
ltiv
ar
iate
v
is
u
aliza
tio
n
o
f
th
e
o
ce
an
o
g
r
ap
h
ic
d
at
a,
wh
ich
h
elp
s
to
u
n
d
er
s
tan
d
th
e
ca
u
s
al
r
elatio
n
s
h
ip
b
etwe
en
th
e
d
if
f
er
e
n
t
p
ar
am
eter
s
u
n
d
er
c
o
n
s
id
er
atio
n
.
T
h
e
m
u
ltiv
ar
iate
v
is
u
aliza
tio
n
[
2
2
]
,
[
2
3
]
p
r
o
v
id
es
th
e
s
im
u
ltan
eo
u
s
v
is
u
aliza
tio
n
o
f
m
u
ltip
le
v
ar
ia
b
les.
Fo
r
ex
am
p
le,
th
e
f
o
u
n
d
atio
n
lay
e
r
o
f
a
m
u
ltiv
ar
iate
m
ap
m
ig
h
t
b
e
t
h
e
SST
,
w
ith
ad
d
itio
n
al
la
y
er
s
s
h
o
win
g
b
ath
y
m
etr
y
,
o
ce
a
n
cu
r
r
en
ts
,
an
d
ch
lo
r
o
p
h
y
ll
co
n
ce
n
tr
atio
n
.
T
h
is
wo
u
ld
g
iv
e
a
co
m
p
lete
p
ictu
r
e
o
f
wh
er
e
h
is
th
e
lag
d
is
tan
ce
,
Z
(
x
)
is
th
e
v
ar
iab
le
o
f
in
ter
est
at
lo
ca
tio
n
x
,
an
d
t
h
e
ec
o
lo
g
i
ca
l
an
d
p
h
y
s
ical
ch
ar
ac
ter
is
tic
s
o
f
th
e
o
ce
an
in
a
p
ar
ticu
lar
ar
ea
.
An
ex
ten
s
iv
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p
er
s
p
ec
tiv
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o
f
th
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v
er
tical
s
tr
u
ctu
r
e
o
f
th
e
o
ce
a
n
ca
n
b
e
o
b
tain
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b
y
u
tili
s
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g
a
v
er
tical
p
r
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f
ile
m
a
p
o
r
a
c
o
n
t
o
u
r
p
lo
t,
w
h
er
e
th
e
v
a
r
io
u
s
c
h
ar
ac
ter
is
tics
ar
e
s
tack
ed
o
n
to
p
o
f
o
n
e
an
o
th
er
[
2
4
]
,
[
2
5
]
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
Py
th
o
n
is
u
s
ed
to
im
p
lem
e
n
t
th
e
s
y
s
tem
s
in
ce
it
h
as
an
ad
eq
u
ate
d
ata
p
r
o
ce
s
s
in
g
p
ac
k
a
g
e.
Py
th
o
n
m
o
d
u
les
lik
e
Ma
tp
l
o
tlib
,
B
asem
ap
,
an
d
Nu
m
p
y
ar
e
ess
en
t
ial
co
m
p
o
n
en
ts
o
f
th
e
p
r
o
g
r
a
m
.
User
s
h
av
e
t
h
e
o
p
tio
n
t
o
s
elec
t
f
r
o
m
a
v
ar
iety
o
f
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lo
t
ty
p
es
f
o
r
a
s
in
g
le
v
ar
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le
s
tu
d
y
,
in
clu
d
in
g
c
o
n
to
u
r
p
lo
ts
,
v
ec
to
r
p
lo
ts
,
s
tr
ea
m
lin
e
p
lo
ts
,
an
d
co
lo
r
m
ap
s
.
Plo
ts
ca
n
b
e
cu
s
to
m
ized
in
a
v
ar
iety
o
f
way
s
,
in
clu
d
in
g
lo
ca
tio
n
an
d
co
lo
r
s
elec
tio
n
s
.
T
h
e
f
r
am
ewo
r
k
o
f
f
er
s
alter
n
ativ
es
f
o
r
m
u
ltiv
ar
iate
v
is
u
aliza
tio
n
b
y
o
v
e
r
lay
in
g
th
e
m
an
y
f
u
n
d
am
e
n
tal
p
l
o
ts
.
T
h
e
in
itial
lau
n
ch
p
a
g
e
o
f
t
h
e
f
r
am
ewo
r
k
wh
ich
p
r
o
v
id
es
t
h
e
d
ata
co
n
v
er
ter
is
g
iv
en
i
n
Fig
u
r
e
3
.
T
h
e
in
ter
f
ac
e
o
f
t
h
e
s
y
s
tem
p
r
o
v
id
es
o
p
tio
n
s
t
o
im
p
o
r
t
d
ata
in
t
o
th
e
f
r
a
m
ewo
r
k
a
n
d
p
r
o
v
id
es
an
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
In
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
3
6
,
No
.
2
,
No
v
em
b
er
20
24
:
1
3
2
9
-
133
7
1334
in
ter
f
ac
e
f
o
r
d
ata
m
an
ag
e
m
en
t
.
T
h
e
f
r
am
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r
k
is
test
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n
th
e
s
y
s
tem
with
s
p
ec
if
icatio
n
o
f
8
GB
R
AM
an
d
a
g
r
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h
ics ca
r
d
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f
NVI
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1
to
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4
G
Hz
p
r
o
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s
s
o
r
.
Fig
u
r
e
3
.
Data
co
n
v
er
ter
in
d
at
a
m
an
ag
em
e
n
t la
y
er
3
.
1
.
B
a
s
ic
p
lo
t
s
T
h
e
b
asic
p
lo
ts
im
p
lem
e
n
ted
in
th
is
f
r
am
ewo
r
k
in
clu
d
e
p
r
o
f
ile
p
lo
ts
,
v
ec
to
r
p
lo
ts
,
c
o
lo
r
m
ap
s
,
an
d
s
tr
ea
m
lin
e
p
lo
ts
.
User
s
ar
e
p
r
o
v
id
ed
with
d
if
f
e
r
en
t
o
p
tio
n
s
to
cu
s
to
m
ize
th
e
p
l
o
ts
.
Sam
p
le
ex
am
p
les
o
f
cu
s
to
m
izatio
n
f
r
a
m
es
f
o
r
p
lo
ts
ar
e
d
is
p
lay
ed
in
Fig
u
r
e
4
.
T
h
e
v
ec
to
r
p
lo
t
i
n
ter
f
ac
e
i
n
clu
d
es
o
p
tio
n
s
f
o
r
p
r
o
v
id
i
n
g
,
tim
e
an
d
d
e
p
th
in
d
ex
,
as
well
as
lo
ca
tio
n
s
p
ec
if
icatio
n
s
.
T
h
e
ar
r
o
w
s
ettin
g
s
p
r
o
v
id
e
t
h
e
u
s
er
o
p
tio
n
s
to
cu
s
to
m
ize
th
e
s
ca
le,
s
h
af
t
an
d
h
ea
d
wid
th
an
d
h
ea
d
len
g
th
,
an
d
h
ea
d
ax
is
len
g
th
f
o
r
th
e
v
ec
to
r
p
lo
t.
T
h
e
co
lo
r
s
ettin
g
o
p
tio
n
s
ar
e
also
p
r
o
v
id
ed
f
o
r
t
h
e
v
ec
to
r
p
lo
t.
Similar
ly
,
t
h
e
c
o
n
to
u
r
p
lo
t
o
f
f
er
s
cu
s
to
m
izatio
n
in
ter
m
s
o
f
tim
e
an
d
d
ep
th
in
d
ices,
as
well
as
lo
ca
tio
n
p
r
ef
er
en
ce
s
.
User
s
ca
n
s
elec
t
th
e
r
elev
an
t
p
ar
am
eter
a
n
d
s
p
ec
if
y
th
e
p
ar
am
eter
’
s
r
an
g
e
th
r
o
u
g
h
th
e
co
n
t
o
u
r
p
lo
t
in
ter
f
ac
e.
T
h
e
co
n
to
u
r
lin
es
ca
n
b
e
cu
s
to
m
ized
in
ter
m
s
o
f
co
lo
r
,
s
ty
le,
a
n
d
th
ick
n
ess
.
T
h
e
co
lo
r
m
a
p
also
p
r
o
v
id
es
s
i
m
ilar
ch
o
ices
al
o
n
g
with
o
p
tio
n
s
to
ex
ten
d
th
e
c
o
lo
r
b
ar
r
a
n
g
e
ac
co
r
d
in
g
to
t
h
e
u
s
er
’
s
p
r
ef
er
en
ce
.
A
s
am
p
le
p
lo
t
g
en
er
ated
b
y
th
e
d
ata
r
en
d
e
r
in
g
en
g
in
e
in
th
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
,
u
tili
zin
g
t
h
e
C
PU
im
p
lem
en
tatio
n
,
is
d
e
p
icted
in
Fig
u
r
e
5
.
T
h
e
b
asic
2
D
p
lo
ts
th
u
s
p
r
o
v
id
e
a
co
n
tin
u
o
u
s
s
p
atial
u
n
d
er
s
tan
d
in
g
o
f
th
e
p
a
r
a
m
eter
u
n
d
er
s
tu
d
y
.
Ad
d
itio
n
ally
,
a
s
am
p
le
3
D
p
lo
t
f
o
r
th
e
v
ar
iab
le
u
n
d
er
in
v
esti
g
atio
n
is
p
r
esen
ted
in
F
ig
u
r
e
6
,
wh
ic
h
is
im
p
lem
en
ted
u
s
in
g
t
h
e
o
ctr
ee
co
n
ce
p
t
m
en
ti
o
n
ed
ea
r
lier
.
User
s
ca
n
en
h
a
n
ce
th
e
v
is
u
al
izatio
n
s
m
o
o
th
n
ess
u
s
in
g
th
e
in
ter
ac
tio
n
tech
n
iq
u
es p
r
o
v
id
ed
b
y
t
h
e
Py
th
o
n
in
te
r
f
ac
e.
Fig
u
r
e
4
.
C
u
s
to
m
izatio
n
o
p
tio
n
s
f
o
r
b
asic p
lo
ts
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2
5
0
2
-
4
7
52
A
n
in
tera
ctive
visu
a
liz
a
tio
n
to
o
l fo
r
th
e
ex
p
lo
r
a
tio
n
a
n
d
…
(
P
r
ee
th
a
K
.
G
.
)
1335
Fig
u
r
e
5
.
B
asic 2
D
p
lo
ts
-
co
n
t
o
u
r
p
l
o
t,
v
ec
to
r
p
lo
t
,
a
n
d
c
o
lo
u
r
m
ap
Fig
u
r
e
6
.
3
D
p
lo
t f
o
r
tem
p
e
r
at
u
r
e
3
.
2
.
O
v
er
la
y
plo
t
s
Mu
ltip
le
d
ata
s
ets
ar
e
d
is
p
lay
ed
o
n
o
n
e
g
r
ap
h
in
an
o
v
er
la
y
p
lo
t,
en
ab
lin
g
d
ir
ec
t
c
o
m
p
a
r
is
o
n
an
d
th
e
d
etec
tio
n
o
f
tr
e
n
d
s
,
p
atter
n
s
,
an
d
c
o
r
r
elatio
n
s
b
etwe
en
v
ar
i
ab
les.
W
ith
th
e
u
s
e
o
f
o
v
e
r
lay
p
lo
ts
,
n
u
m
e
r
o
u
s
d
atasets
o
r
v
ar
iab
les
ca
n
b
e
co
m
p
ar
ed
v
is
u
ally
at
o
n
ce
.
T
h
e
ch
ar
ts
aid
in
ex
am
in
i
n
g
th
e
r
el
atio
n
s
h
ip
s
b
etwe
en
v
ar
io
u
s
f
ac
to
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s
.
W
e
ca
n
s
ee
co
r
r
elatio
n
s
,
d
ep
en
d
en
cies,
o
r
ca
u
s
al
lin
k
s
b
y
o
v
er
lay
in
g
two
o
r
m
o
r
e
b
asic
g
r
ap
h
s
.
Fig
u
r
e
7
r
ep
r
e
s
en
ts
th
e
ex
am
p
le
o
v
er
la
y
p
lo
ts
.
Fig
u
r
e
s
7
(
a
)
a
n
d
7
(
b
)
d
is
p
lay
s
s
am
p
le
g
r
ap
h
s
o
f
win
d
o
v
er
laid
o
n
tem
p
e
r
atu
r
e
a
n
o
m
aly
an
d
s
alin
ity
o
v
er
laid
o
n
te
m
p
er
atu
r
e.
(
a)
(
b
)
Fig
u
r
e
7
.
E
x
am
p
les o
f
o
v
er
la
y
(
a)
win
d
o
v
er
laid
o
n
tem
p
er
at
u
r
e
an
o
m
aly
an
d
(
b
)
s
alin
ity
o
v
er
laid
o
n
tem
p
er
atu
r
e
4.
CO
NCLU
SI
O
N
T
h
e
m
ain
ch
allen
g
e
i
n
an
aly
zi
n
g
lar
g
e
v
o
lu
m
es
o
f
o
ce
an
d
at
a
is
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t
co
m
p
le
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NC
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[
1
]
C
.
X
i
e
,
M
.
Li
,
H
.
W
a
n
g
,
a
n
d
J.
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o
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[
4
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7
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C
.
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a
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.
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h
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,
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8
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J.
Li
,
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,
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9
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.
M
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
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J
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lec
E
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g
&
C
o
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p
Sci
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N:
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5
0
2
-
4
7
52
A
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in
tera
ctive
visu
a
liz
a
tio
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to
o
l fo
r
th
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ex
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lo
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(
P
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.
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.
)
1337
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Dr
.
Pre
e
th
a
K
.
G
.
c
o
m
p
lete
d
h
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r
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h
.
D
.
in
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o
b
il
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Ad
h
o
c
Ne
two
rk
s
fro
m
Co
c
h
in
Un
iv
e
rsity
o
f
S
c
ien
c
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h
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g
y
in
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0
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.
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h
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c
u
rre
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tl
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rk
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r
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p
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rtme
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t
o
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m
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g
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rin
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a
t
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jag
iri
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c
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f
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g
i
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rin
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d
Tec
h
n
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g
y
i
n
Ke
ra
la,
I
n
d
ia.
S
h
e
h
a
s
a
ro
u
n
d
2
2
y
e
a
rs
o
f
a
c
a
d
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m
ic
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x
p
e
rien
c
e
.
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r
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se
a
rc
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in
tere
sts
in
c
lu
d
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d
a
ta
a
n
a
ly
ti
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m
a
c
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m
o
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les
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two
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a
n
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a
d
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S
h
e
c
a
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b
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c
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n
tac
ted
a
t
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m
a
il
:
p
re
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th
a
_
k
g
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jag
iri
tec
h
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e
d
u
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in
.
Dr
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a
r
ith
a
S
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re
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h
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.
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n
g
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rin
g
fro
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Co
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h
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n
Un
iv
e
rsity
o
f
S
c
ien
c
e
a
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d
En
g
in
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ri
n
g
,
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ra
la,
In
d
ia
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S
h
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is
c
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rre
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tl
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se
rv
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g
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s
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ro
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jag
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g
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to
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u
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i
n
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ra
la,
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n
d
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h
e
h
a
s
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lso
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tri
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ted
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m
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r
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o
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r
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a
l
a
rti
c
les
,
c
o
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re
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c
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p
a
p
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rs,
b
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k
c
h
a
p
ters
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a
n
d
p
a
ten
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re
flec
ti
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g
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h
e
in
n
o
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a
ti
v
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c
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n
tri
b
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ti
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iffere
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fiel
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s
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ter
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g
in
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g
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sa
rit
h
a
_
s@
ra
jag
iri
tec
h
.
e
d
u
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i
n
.
Mr
.
J
ish
n
u
J
e
e
v
a
n
c
o
m
p
lete
d
h
is
B.
Tec
h
in
C
o
m
p
u
ter
S
c
ien
c
e
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n
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En
g
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rin
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fro
m
Th
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Alb
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rti
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n
stit
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te
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S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
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ra
la,
In
d
ia
in
2
0
1
8
.
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c
o
m
p
lete
d
h
is
M
.
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h
in
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m
p
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ter
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n
d
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n
f
o
rm
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ti
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c
ien
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fro
m
t
h
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De
p
a
r
tme
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t
o
f
C
o
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p
u
ter
S
c
ien
c
e
,
CUSAT,
in
2
0
2
1
.
Cu
rre
n
tl
y
h
e
is
wo
rk
in
g
a
s
Ju
n
i
o
r
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se
a
rc
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As
s
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c
iate
,
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ro
-
M
e
d
it
e
rra
n
e
a
n
Ce
n
ter
o
n
Cl
ima
te
Ch
a
n
g
e
(CM
CC),
Italy
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ji
sh
n
u
jee
v
a
n
@g
m
a
il
.
c
o
m
.
Dr
.
Chi
n
n
u
S
a
c
h
i
d
a
n
a
n
d
a
n
i
s
a
n
o
c
e
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g
ra
p
h
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r
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d
m
a
rin
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sc
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ti
st
fr
o
m
I
n
d
ia.
S
h
e
h
a
s
c
o
m
p
lete
d
h
e
r
g
ra
d
u
a
te
stu
d
ies
i
n
o
c
e
a
n
o
g
ra
p
h
y
fr
o
m
C
o
c
h
in
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i
v
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rsity
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f
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c
ien
c
e
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n
d
Tec
h
n
o
lo
g
y
(CUSAT)
a
n
d
we
n
t
o
n
t
o
p
u
rsu
e
d
o
c
t
o
ra
l
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se
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rc
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m
a
rin
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sc
ien
c
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t
th
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p
re
stig
i
o
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s
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ti
o
n
a
l
In
stit
u
te
o
f
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e
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n
o
g
ra
p
h
y
.
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u
rre
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tl
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wo
rk
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g
a
s
a
re
se
a
rc
h
fe
ll
o
w
in
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jag
iri
S
c
h
o
o
l
o
f
En
g
in
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e
rin
g
a
n
d
Tec
h
n
o
lo
g
y
,
i
n
Ke
ra
la,
In
d
ia
.
He
r
re
se
a
rc
h
e
x
p
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rti
se
li
e
s
in
th
e
f
ield
o
f
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c
e
a
n
o
g
ra
p
h
y
a
n
d
m
a
rin
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sc
ien
c
e
s,
with
a
fo
c
u
s
o
n
th
e
p
h
y
sic
a
l
p
r
o
c
e
ss
e
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th
a
t
sh
a
p
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o
c
e
a
n
s.
S
h
e
c
a
n
b
e
c
o
n
tac
t
e
d
a
t
e
m
a
il
:
c
h
in
n
u
.
sa
c
h
i
7
@g
m
a
il
.
c
o
m
.
Dr
.
P
.
A
.
Ma
h
e
sw
a
r
a
n
o
b
tai
n
e
d
h
is
M
a
ste
rs
a
n
d
P
h
.
D.
in
Oc
e
a
n
o
g
ra
p
h
y
fro
m
Co
c
h
in
Un
i
v
e
rsity
o
f
S
c
ien
c
e
a
n
d
Tec
h
n
o
l
o
g
y
,
Ko
c
h
i
,
Ke
ra
la.
H
e
is
c
u
rre
n
t
ly
wo
rk
in
g
a
s
a
S
c
ien
ti
st
a
t
DRD
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v
a
l
P
h
y
sic
a
l
a
n
d
Oc
e
a
n
o
g
ra
p
h
ic
Lab
o
ra
to
r
y
,
Ko
c
h
i
.
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re
se
a
rc
h
a
re
a
s
in
c
lu
d
e
,
M
i
x
e
d
lay
e
r
d
y
n
a
m
ics
,
th
e
rm
o
h
a
li
n
e
stru
c
t
u
re
,
s
o
n
a
r
o
c
e
a
n
o
g
ra
p
h
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
m
a
h
e
sw
a
ra
n
.
n
p
o
l@
g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.