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37
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,
Feb
r
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y
20
25
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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52
I
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d
o
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esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
37
,
No
.
2
,
Feb
r
u
a
r
y
20
25
:
1
05
3
-
1
06
3
1054
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o
n
s
e
ad
ju
s
ts
to
b
alan
ce
b
lo
wer
an
d
v
al
v
e
d
y
n
a
m
ic
r
es
p
o
n
s
es
d
ep
en
d
in
g
o
n
th
e
g
as
r
atio
.
T
h
is
d
esig
n
im
p
r
o
v
es o
v
er
all
f
lo
w
an
d
p
r
e
s
s
u
r
e
r
esp
o
n
s
iv
en
ess
ac
r
o
s
s
all
r
atio
s
ettin
g
s
a
n
d
p
atien
t
l
o
a
d
s
.
L
u
n
g
m
ec
h
an
ics
m
u
s
t
b
e
ev
alu
ated
f
ir
s
t
f
o
r
l
u
n
g
p
r
o
tectio
n
an
d
o
p
tim
u
m
b
r
ea
th
in
g
tech
n
iq
u
es.
T
h
is
r
esear
ch
in
tr
o
d
u
ce
s
m
ac
h
in
e
lear
n
in
g
f
o
r
b
ed
s
id
e
r
esp
ir
ato
r
y
r
esis
tan
ce
an
d
c
o
m
p
lian
ce
ev
alu
atio
n
[
4
]
.
I
t
u
s
es
m
ac
h
in
e
lear
n
in
g
to
p
r
ed
ict
f
r
o
m
f
lo
w
r
ate
an
d
a
ir
way
p
r
ess
u
r
e
in
r
ea
l
-
tim
e.
T
o
m
o
n
ito
r
th
e
p
atien
t'
s
b
lo
o
d
o
x
y
g
en
s
atu
r
atio
n
an
d
e
x
h
ale
d
lu
n
g
p
r
ess
u
r
e,
t
h
e
a
r
tific
ial
v
en
tilatio
n
s
y
s
tem
s
h
o
u
ld
b
e
a
b
le
to
s
e
cu
r
e
air
p
r
ess
u
r
e
b
o
t
h
a
b
o
v
e
an
d
b
elo
w
th
e
r
ec
o
m
m
en
d
e
d
lev
els.
Stan
d
a
r
d
v
en
tilato
r
s
ar
e
to
o
b
ig
to
b
e
u
s
ef
u
l
d
u
r
in
g
p
a
n
d
em
ics,
a
n
d
th
e
cu
r
r
e
n
t
tech
n
iq
u
e
n
ee
d
s
to
allo
w
f
o
r
th
e
n
ec
ess
ar
y
ad
ap
tatio
n
[
5
]
.
U
t
ilizin
g
Ar
d
u
in
o
h
as
cr
ea
ted
a
v
er
s
atile
an
d
ef
f
ec
tiv
e
v
en
tilato
r
to
h
an
d
le
p
an
d
em
ic
s
itu
atio
n
s
.
T
h
e
s
u
g
g
ested
co
n
ce
p
t
in
co
r
p
o
r
ates
a
s
ilico
n
p
ac
k
,
a
s
er
v
o
m
o
to
r
,
an
d
a
s
id
e
p
u
s
h
co
m
p
o
n
en
t
t
o
s
p
ee
d
u
p
t
h
e
r
esp
ir
ato
r
y
s
ac
k
with
o
u
t
e
n
d
an
g
e
r
in
g
t
h
e
p
atien
t.
D
u
e
to
th
e
C
OVI
D
-
1
9
e
p
id
em
ic,
m
ed
ical
p
r
o
f
ess
io
n
als
an
d
in
v
en
to
r
s
d
ev
elo
p
ed
m
o
r
e
h
ea
l
th
ca
r
e
tech
n
o
lo
g
y
[
6
]
.
I
n
Ap
r
il
2
0
2
0
,
u
n
d
er
th
e
Def
en
s
e
Pro
d
u
ctio
n
Act
[
7
]
,
Am
er
ican
m
an
u
f
ac
tu
r
in
g
was
ac
ce
ler
ated
to
s
atis
f
y
lo
ca
l
an
d
o
v
er
s
ea
s
d
em
a
n
d
s
.
Patien
ts
with
ac
u
te
r
esp
ir
ato
r
y
d
is
tr
ess
u
s
e
v
en
tilato
r
s
.
C
lin
ical
d
ec
is
io
n
s
u
p
p
o
r
t
s
y
s
tem
s
(
C
DSS)
wil
l
h
elp
p
h
y
s
ician
s
m
ak
e
b
etter
d
ec
is
io
n
s
in
f
u
tu
r
e
h
ea
lth
ca
r
e
s
y
s
tem
s
.
Du
r
i
n
g
th
e
C
OVI
D
-
1
9
ep
id
em
ic,
p
r
ed
ictin
g
ac
u
te
r
esp
ir
ato
r
y
d
is
tr
ess
s
y
n
d
r
o
m
e
(
AR
DS)
in
n
ewly
i
n
f
ec
t
ed
in
d
i
v
id
u
als
h
elp
e
d
p
r
io
r
itiz
e
tr
ea
tm
en
t
[
8
]
.
I
n
th
e
g
en
e
r
al
in
ten
s
iv
e
ca
r
e
u
n
it
(
I
C
U)
,
p
atien
ts
with
r
esp
ir
ato
r
y
s
y
s
tem
p
r
o
b
lem
s
o
f
ten
n
ee
d
ar
tific
ial
v
en
tila
tio
n
p
r
o
v
id
e
d
b
y
a
co
n
v
en
tio
n
al
p
iece
o
f
eq
u
i
p
m
e
n
t
ca
lled
an
a
u
to
m
atic
m
ec
h
a
n
ical
v
en
tilato
r
[
9
]
.
Ven
tilatio
n
is
a
co
m
p
lex
p
r
o
c
ess
th
at
r
eq
u
ir
es
r
eg
u
lar
p
r
ac
tice.
User
s
m
u
s
t
lear
n
h
o
w
to
c
o
n
f
ig
u
r
e
th
e
v
a
r
io
u
s
p
ar
am
eter
s
s
o
th
at
air
m
ay
b
e
s
u
p
p
lied
in
to
th
e
l
u
n
g
s
d
u
r
in
g
in
s
p
ir
atio
n
an
d
ex
h
ale
d
d
u
r
in
g
ex
p
ir
atio
n
.
Au
to
m
atic
v
en
tilatio
n
is
a
c
o
n
v
en
tio
n
al
th
er
ap
y
f
o
r
p
atien
t
s
with
r
esp
ir
ato
r
y
a
b
n
o
r
m
alities
o
r
s
p
o
n
ta
n
eo
u
s
b
r
ea
th
in
g
t
h
at
is
in
s
u
f
f
icien
t to
s
u
s
tain
o
x
y
g
en
ati
o
n
[
1
0
]
.
Pro
b
lem
s
tatem
en
t:
in
co
n
s
is
t
en
ci
es
in
d
ata
q
u
ality
an
d
co
m
p
u
tatio
n
al
lim
itatio
n
s
th
at
im
p
ac
t
g
en
er
aliza
b
ilit
y
ar
e
u
n
r
eso
l
v
ed
p
r
o
b
lem
s
.
I
m
p
r
o
v
e
m
en
t
p
o
ten
tial
i
n
clu
d
es
im
p
r
o
v
in
g
g
ath
er
in
g
d
ata
tech
n
iq
u
es
an
d
m
ax
im
izin
g
m
o
d
el
p
er
f
o
r
m
a
n
ce
f
o
r
a
r
an
g
e
o
f
cr
itical
ca
r
e
p
atien
t
c
o
n
d
itio
n
s
.
Pati
en
ts
in
cr
itical
ca
r
e
s
ettin
g
s
ar
e
at
r
is
k
f
o
r
p
r
o
b
lem
s
s
u
ch
as
v
en
til
ato
r
-
ass
o
ciate
d
lu
n
g
in
ju
r
y
a
n
d
ex
ten
d
ed
h
o
s
p
ital
s
tay
s
d
u
e
to
in
s
u
f
f
icien
t
v
en
t
ilato
r
co
n
tr
o
l.
C
u
r
r
e
n
t
b
r
ea
th
in
g
s
y
s
tem
s
ar
en
'
t
al
way
s
p
e
r
s
o
n
alize
d
to
ea
ch
p
atien
t'
s
u
n
iq
u
e
n
ee
d
s
,
an
d
t
h
ey
co
u
ld
m
is
s
th
e
war
n
in
g
s
ig
n
als
o
f
wo
r
s
en
in
g
,
lead
in
g
to
tr
ea
tm
en
ts
th
at
ar
e
to
o
late
an
d
wo
r
s
e
r
esu
lts
.
Als
o
,
h
ea
lth
ca
r
e
p
r
ac
titi
o
n
er
s
ca
n
o
n
ly
s
o
m
etim
es
m
ak
e
th
e
n
ec
ess
ar
y
m
o
d
if
icatio
n
s
q
u
ick
ly
s
in
ce
m
an
u
ally
in
te
r
p
r
etin
g
v
e
n
tilato
r
d
ata
is
a
co
m
p
le
x
an
d
e
r
r
o
r
-
p
r
o
n
e
p
r
o
ce
s
s
.
Fu
r
th
er
m
o
r
e
,
in
e
m
er
g
e
n
cy
ca
r
e
ca
s
es,
th
e
in
ab
ilit
y
to
co
n
d
u
ct
r
em
o
te
m
o
n
ito
r
in
g
m
ak
es
it
m
o
r
e
d
i
f
f
icu
lt
to
p
r
o
v
id
e
tim
el
y
tr
ea
tm
en
ts
.
T
o
m
ee
t
th
ese
is
s
u
es,
a
s
y
s
te
m
th
at
o
p
tim
izes
b
r
ea
th
in
g
m
eth
o
d
s
p
er
s
o
n
alize
s
p
atien
t
ca
r
e,
en
a
b
l
es
r
em
o
te
m
o
n
ito
r
in
g
,
an
d
f
ac
ilit
ates
co
n
tin
u
o
u
s
im
p
r
o
v
em
e
n
t
in
cr
itical
h
ea
lth
ca
r
e
s
ettin
g
s
.
T
h
is
s
y
s
tem
s
h
o
u
ld
h
ar
n
ess
n
ew
tech
n
o
lo
g
ies
s
u
c
h
as
d
ee
p
lear
n
in
g
(
DL
)
a
n
d
clo
u
d
c
o
m
p
u
tin
g
.
Pre
v
io
u
s
r
esear
ch
o
n
air
way
m
an
ag
em
en
t
p
r
im
ar
ily
f
o
cu
s
e
d
o
n
lin
ea
r
m
o
d
els
an
d
r
u
le
-
b
ased
m
eth
o
d
s
f
o
r
co
n
tr
o
llin
g
v
en
tilatio
n
.
C
o
m
p
lex
p
atien
t
d
y
n
am
ics
an
d
t
h
e
n
ee
d
f
o
r
r
ea
l
-
tim
e
ad
a
p
ta
tio
n
wer
e
co
m
m
o
n
ch
allen
g
es
f
o
r
th
ese
tech
n
i
q
u
es.
I
n
co
r
p
o
r
atin
g
m
ac
h
in
e
lea
r
n
in
g
tech
n
iq
u
es
lik
e
r
an
d
o
m
f
o
r
est
an
d
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
(
SVM
)
in
to
m
o
r
e
cu
r
r
en
t
a
p
p
r
o
ac
h
es
h
as
in
cr
ea
s
ed
ac
cu
r
ac
y
,
b
u
t
t
h
ese
m
eth
o
d
s
s
till
ch
allen
g
e
h
o
w
to
h
a
n
d
le
lo
n
g
-
ter
m
r
elatio
n
s
h
ip
s
an
d
in
teg
r
at
e
r
ea
l
-
tim
e
d
ata.
C
o
n
tr
ib
u
tio
n
o
f
th
e
p
a
p
er
:
t
h
is
r
esear
ch
p
r
esen
ts
a
n
ew
m
eth
o
d
f
o
r
o
p
tim
izin
g
v
en
tilatio
n
t
ec
h
n
iq
u
e
s
in
h
ig
h
-
s
tak
es
h
ea
lth
ca
r
e
en
v
i
r
o
n
m
en
ts
b
y
co
m
b
in
in
g
clo
u
d
co
m
p
u
tin
g
with
DL
,
esp
ec
ially
L
STM
n
etwo
r
k
s
.
T
h
e
s
y
s
tem
'
s
r
ea
l
-
tim
e
an
aly
s
i
s
o
f
v
en
tilato
r
d
ata,
wh
ic
h
is
m
ad
e
p
o
s
s
ib
le
b
y
u
s
in
g
clo
u
d
-
b
ased
in
f
r
astru
ctu
r
e
an
d
p
o
wer
f
u
l
alg
o
r
ith
m
s
,
allo
ws
f
o
r
p
e
r
s
o
n
alize
d
t
r
ea
tm
en
t
an
d
p
r
o
m
p
t
i
n
ter
v
en
tio
n
s
.
T
h
is
p
ap
er
p
r
o
p
o
s
es
ad
ju
s
tin
g
b
r
ea
th
in
g
tech
n
iq
u
es
ac
co
r
d
in
g
to
ea
ch
p
atien
t's
u
n
iq
u
e
d
em
an
d
s
.
B
y
ass
ess
in
g
r
esp
ir
ato
r
y
p
ar
am
eter
s
an
d
p
r
ev
io
u
s
d
ata
to
alter
v
en
tilatio
n
s
ettin
g
s
,
th
e
tech
n
o
lo
g
y
ca
n
m
a
x
im
ize
p
at
ien
t
o
u
tco
m
es
wh
ile
lo
wer
in
g
th
e
r
is
k
o
f
v
e
n
tilato
r
-
ass
o
ciate
d
p
r
o
b
lem
s
.
T
h
e
r
em
o
te
m
o
n
ito
r
in
g
ca
p
a
b
ilit
ies
ar
e
an
o
th
e
r
n
o
tewo
r
th
y
a
d
d
itio
n
;
th
is
allo
ws
h
ea
lth
ca
r
e
p
er
s
o
n
n
el
to
q
u
ick
ly
ex
am
in
e
th
eir
p
atien
ts
'
s
tate
an
d
in
ter
v
en
e,
n
o
m
atter
wh
er
e
th
e
y
ar
e
p
h
y
s
ically
lo
ca
ted
.
T
h
is
f
ea
tu
r
e
im
p
r
o
v
es
p
atien
t
ca
r
e
b
y
ea
s
i
n
g
th
e
w
o
r
k
lo
a
d
o
f
h
ea
lth
ca
r
e
p
r
o
v
id
er
s
an
d
allo
win
g
f
o
r
m
o
r
e
q
u
ick
ac
tio
n
s
.
T
h
e
s
ig
n
if
ican
ce
o
f
iter
ativ
e
lear
n
in
g
f
r
o
m
n
ew
d
ata
an
d
f
ee
d
b
ac
k
f
o
r
co
n
tin
u
al
d
ev
elo
p
m
en
t
is
h
ig
h
lig
h
ted
in
th
e
r
ese
ar
ch
.
T
h
e
p
r
o
p
o
s
e
d
s
y
s
tem
in
ten
d
s
to
im
p
r
o
v
e
its
ef
f
icac
y
an
d
c
o
n
tr
ib
u
te
to
th
e
co
n
tin
u
in
g
p
r
o
g
r
ess
in
cr
itical
h
ea
lth
ca
r
e
m
an
ag
em
en
t
b
y
co
n
tin
u
o
u
s
ly
ch
allen
g
in
g
its
alg
o
r
ith
m
s
an
d
a
d
ju
s
tin
g
t
o
ch
an
g
in
g
p
atien
t
d
em
a
n
d
s
.
I
n
co
m
p
ar
is
o
n
with
ex
is
tin
g
r
u
le
-
b
as
ed
a
n
d
lin
ea
r
m
o
d
els,
th
e
n
ew
wo
r
k
s
h
o
ws
th
at
co
m
b
in
in
g
L
STM
n
e
two
r
k
s
with
clo
u
d
co
m
p
u
tin
g
p
r
o
v
id
es
b
etter
r
e
al
-
tim
e
v
en
tilatio
n
o
p
tim
is
atio
n
an
d
p
r
ed
ictio
n
ac
c
u
r
ac
y
,
p
r
o
v
id
i
n
g
a
m
o
r
e
ac
cu
r
ate
an
d
f
lex
ib
le
s
o
lu
tio
n
f
o
r
cr
itical
ca
r
e
v
en
tilatio
n
co
n
tr
o
l.
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
d
va
n
cin
g
a
ir
w
a
y
ma
n
a
g
eme
n
t fo
r
ve
n
tila
tio
n
o
p
timiz
a
tio
n
in
crit
ica
l …
(
S
u
r
esh
K
u
ma
r
K
r
i
s
h
n
a
mo
o
r
th
i)
1055
Ma
n
y
r
esp
ir
at
o
r
y
f
ailu
r
e
p
atie
n
ts
u
tili
ze
m
ec
h
a
n
ical
v
e
n
tilatio
n
.
R
escu
e
tr
ea
tm
e
n
t f
o
r
ad
u
lt
s
in
v
o
lv
es
h
ig
h
-
f
r
eq
u
e
n
cy
o
s
cillato
r
y
b
r
e
ath
in
g
.
I
n
h
i
g
h
-
f
r
eq
u
e
n
cy
v
e
n
tilatio
n
,
ev
en
tid
al
v
o
lu
m
e
is
n
o
t
m
o
n
ito
r
e
d
[
1
1
]
.
Hig
h
-
f
r
eq
u
en
cy
o
s
cillato
r
y
v
en
tilatio
n
m
ay
b
e
b
etter
u
n
d
er
s
to
o
d
u
s
in
g
r
esp
ir
at
o
r
y
s
y
s
tem
m
o
d
els.
I
t
d
escr
ib
es
th
e
b
asic
m
o
d
el
an
d
h
o
w
lu
n
g
co
m
p
lian
ce
af
f
ec
ts
tid
al
v
o
lu
m
e
a
n
d
alv
eo
lar
p
r
ess
u
r
e
[
1
2
]
.
Un
ex
p
ec
ted
air
way
d
i
f
f
icu
ltie
s
ar
e
a
lead
in
g
ca
u
s
e
o
f
r
esp
ir
ato
r
y
is
s
u
es.
I
f
th
e
d
o
cto
r
f
ails
to
k
ee
p
th
e
air
way
o
p
en
,
th
e
p
atien
t
m
a
y
d
ie
o
r
s
u
f
f
er
last
in
g
in
j
u
r
y
f
r
o
m
in
s
u
f
f
icien
t
o
x
y
g
e
n
atio
n
.
Alth
o
u
g
h
c
o
n
tin
u
o
u
s
co
n
s
tan
t
air
f
lo
w
d
o
esn
'
t
wo
r
k
in
r
ea
l
l
if
e,
n
ewe
r
ex
p
er
i
m
en
ts
h
av
e
em
b
r
ac
e
d
it
[
1
3
]
.
T
h
is
r
esear
ch
d
ev
elo
p
s
a
m
ath
em
atica
l
m
o
d
el
b
ased
o
n
clin
ical
m
ec
h
an
ical
v
e
n
tilatio
n
to
ex
am
in
e
th
e
d
y
n
am
ic
p
r
o
p
e
r
ties
o
f
r
esp
ir
ato
r
y
ai
r
f
lo
w
an
d
s
ec
r
eti
o
n
in
th
e
air
way
s
.
A
r
esp
ir
ato
r
y
m
o
d
u
le
is
a
m
ed
ical
g
a
d
g
et
t
h
at
h
elp
s
s
o
m
eo
n
e
b
r
ea
th
e.
T
o
p
r
o
v
id
e
a
co
n
tr
o
l
s
y
s
tem
th
at
ca
n
p
r
ec
is
ely
m
o
n
ito
r
a
tar
g
et
p
r
ess
u
r
e
th
at
ch
an
g
es o
v
er
tim
e
wh
ile
also
co
n
s
id
er
in
g
th
e
p
atien
t'
s
b
r
ea
th
in
g
e
f
f
o
r
t
a
n
d
u
n
k
n
o
wn
p
ar
am
eter
s
f
o
r
th
e
h
o
s
e
leak
[
1
4
]
.
I
t
d
etails
th
e
cr
ea
tio
n
o
f
a
n
etwo
r
k
d
ata
co
llectin
g
an
d
m
o
n
ito
r
in
g
s
y
s
tem
[
1
5
]
to
tr
ac
k
,
cu
s
to
m
ize,
an
d
im
p
r
o
v
e
m
ec
h
an
ical
v
en
tilatio
n
t
r
ea
tm
en
t.
T
h
e
s
y
s
tem
co
n
s
is
ts
o
f
a
d
ata
co
llectin
g
d
e
v
ice,
a
s
er
v
er
with
an
o
n
lin
e
ap
p
licatio
n
,
an
d
s
to
r
ag
e
f
o
r
t
h
e
d
ata
[
1
6
]
.
W
ea
n
in
g
f
r
o
m
m
ec
h
a
n
i
ca
l
v
e
n
tilatio
n
r
eliev
es
th
e
p
atien
t
f
r
o
m
m
ec
h
a
n
ical
s
u
p
p
o
r
t
an
d
r
e
m
o
v
es
th
e
ass
o
ciate
d
en
d
o
tr
ac
h
ea
l
tu
b
e
[
1
7
]
.
Ma
n
ag
i
n
g
wea
n
in
g
f
r
o
m
m
ec
h
a
n
ical
v
e
n
tilatio
n
co
m
p
r
is
es
a
s
ig
n
if
ican
t
p
r
o
p
o
r
tio
n
o
f
t
h
e
ca
r
e
o
f
cr
itically
ill
in
tu
b
ated
p
atien
ts
in
t
h
e
I
C
U.
Usi
n
g
h
is
to
r
ical
I
C
U
d
ata,
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
s
(
C
NN)
will
b
e
d
ep
lo
y
ed
to
p
r
e
d
ict
th
e
m
o
s
t
ap
p
r
o
p
r
iate
tr
ea
tm
e
n
t
ac
tio
n
in
th
e
n
ex
t
h
o
u
r
f
o
r
a
g
iv
e
n
p
atie
n
t’
s
s
tate.
I
C
U
v
e
n
tilato
r
s
at
v
a
r
io
u
s
h
ea
lth
ca
r
e
in
s
titu
tio
n
s
m
ay
b
e
i
n
s
p
ec
ted
an
d
s
er
v
ice
d
u
s
i
n
g
a
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
ar
c
h
itectu
r
e
[
1
8
]
.
B
io
m
ed
ical
en
g
i
n
ee
r
s
an
d
tech
n
ician
s
m
ay
m
o
n
ito
r
d
ata
an
aly
s
is
r
esu
lts
,
I
C
U
v
en
tilato
r
h
ea
lth
p
r
ed
ictio
n
s
,
an
d
m
ain
te
n
an
ce
s
ch
ed
u
les
u
s
in
g
r
ea
l
-
tim
e
ch
ar
ts
an
d
d
ev
ice
aler
ts
with
th
e
h
elp
o
f
th
e
s
u
g
g
ested
ar
ch
it
ec
tu
r
e
[
1
9
]
.
Mo
s
t
o
f
t
h
em
,
h
o
wev
e
r
,
n
ee
d
d
ir
ec
t
p
a
tien
t
co
n
tact
o
r
ar
e
o
th
er
wis
e
in
ap
p
r
o
p
r
iate
f
o
r
u
s
e
in
a
th
er
ap
eu
tic
s
ettin
g
,
lim
i
tin
g
th
eir
u
s
ef
u
ln
ess
[
2
0
]
.
Po
o
r
p
atien
t
-
v
en
tilato
r
co
n
v
er
s
atio
n
a
n
d
th
e
p
atien
t'
s
u
n
d
er
ly
in
g
co
n
d
itio
n
m
ay
h
av
e
s
ev
er
e
im
p
licatio
n
s
o
n
d
is
ch
ar
g
ed
p
atien
ts
'
r
etu
r
n
to
r
e
g
u
lar
ac
tiv
ities
.
T
h
u
s
,
cr
itical
ca
r
e
clin
ician
s
m
u
s
t
en
h
an
ce
p
atien
t
-
v
en
tilato
r
co
n
tact
.
Ob
s
er
v
atio
n
al
s
tu
d
ies m
ay
n
o
t
b
e
ab
le
to
lin
k
p
atien
t
-
v
en
tilato
r
asy
n
ch
r
o
n
ies to
o
u
tco
m
es.
Hen
ce
,
m
u
lticen
ter
r
esear
ch
w
ith
lar
g
er
p
o
p
u
latio
n
s
is
r
eq
u
ir
ed
[
2
1
]
.
Op
tim
izin
g
m
ec
h
an
ical
v
en
til
ato
r
s
ettin
g
s
u
s
in
g
p
h
y
s
io
lo
g
i
ca
l
m
o
d
els
o
f
r
esp
ir
ato
r
y
m
ec
h
an
ics
m
ay
im
p
r
o
v
e
o
u
tc
o
m
es
f
o
r
cr
itical
ly
s
ick
p
atien
ts
[
2
2
]
.
C
o
m
m
o
n
m
eth
o
d
s
f
o
r
c
r
ea
tin
g
m
o
d
el
s
in
clu
d
e
p
h
y
s
ical
m
ea
s
u
r
es
o
r
s
im
ilar
b
eh
av
io
r
s
th
at
m
ay
p
r
ed
ict
th
e
r
esu
lts
o
f
ex
p
er
im
en
ts
.
Ho
wev
er
,
th
e
u
s
e
o
f
m
o
d
els
b
ased
ju
s
t
o
n
p
h
y
s
ical
m
ea
s
u
r
es
with
clin
ical
d
ata
is
s
o
m
ew
h
at
r
ar
e
R
esp
ir
ato
r
y
m
u
s
cle
ac
tiv
atio
n
ca
u
s
es
s
p
o
n
tan
eo
u
s
b
r
ea
th
in
g
.
Patie
n
ts
with
th
is
co
n
d
itio
n
m
ay
b
r
ea
th
e
s
p
o
n
ta
n
eo
u
s
ly
b
u
t
n
o
t
n
o
r
m
ally
[
2
3
]
.
Patien
ts
'
b
r
ea
th
-
s
p
ec
if
ic
ef
f
o
r
t
an
d
lu
n
g
s
tatu
s
m
ay
b
e
m
o
d
el
ed
u
s
in
g
a
p
o
ly
n
o
m
ial
[
2
4
]
.
T
h
e
clin
ical
v
o
lu
m
e
-
co
n
tr
o
lled
m
o
d
el
is
id
en
tifie
d
u
s
in
g
iter
ativ
e
m
u
ltip
le
lin
ea
r
r
eg
r
ess
io
n
.
Me
ch
an
ical
v
en
t
ilatio
n
f
o
r
p
atien
ts
with
ac
u
te
lu
n
g
d
am
ag
e,
ac
u
te
air
way
o
b
s
tr
u
ctio
n
s
y
n
d
r
o
m
e,
o
r
in
h
alatio
n
in
ju
r
y
is
m
o
s
tly
p
r
o
v
id
e
d
b
y
h
ig
h
-
f
r
eq
u
e
n
cy
p
er
c
u
s
s
iv
e
b
r
ea
th
in
g
in
s
o
m
e
b
u
r
n
cr
itical
ca
r
e
u
n
its
[
2
5
]
.
Un
f
o
r
tu
n
ately
,
n
o
p
r
o
s
p
ec
tiv
e
s
tu
d
ies
co
m
p
ar
ed
m
o
d
er
n
lo
w
-
tid
al
v
o
lu
m
e
v
en
ti
latio
n
tech
n
iq
u
e
s
to
h
ig
h
-
f
r
eq
u
e
n
cy
p
er
cu
s
s
iv
e
v
e
n
tilatio
n
.
T
h
is
r
esear
ch
aim
ed
to
c
o
m
p
a
r
e
th
e
two
v
en
tilato
r
m
eth
o
d
s
in
a
b
u
r
n
cr
itical
ca
r
e
u
n
it scen
ar
io
.
Prio
r
ity
-
b
ased
p
atien
t
an
al
y
s
is
an
d
clo
u
d
im
p
le
m
en
tatio
n
o
f
th
e
s
u
g
g
ested
m
et
h
o
d
[
2
6
]
.
Usi
n
g
au
to
m
a
ted
p
ea
k
d
etec
tio
n
a
n
d
r
ea
l
-
tim
e
id
en
tific
atio
n
o
f
tim
e
-
s
er
ies
wav
ef
o
r
m
s
,
it
r
ec
o
r
d
s
v
en
tilato
r
wav
ef
o
r
m
aler
t
o
cc
u
r
r
e
n
ce
s
[
2
7
]
.
W
ith
th
r
esh
o
ld
alar
m
s
an
d
in
teg
r
ated
ar
tific
ial
in
tellig
e
n
ce
,
th
e
s
y
s
tem
ca
n
au
to
m
atica
lly
r
ec
o
g
n
ize
co
m
p
licated
m
ed
ical
alar
m
s
,
in
clu
d
in
g
asy
n
ch
r
o
n
y
,
ab
n
o
r
m
alit
ies,
an
d
m
ec
h
a
n
ical
is
s
u
es.
I
C
U
p
atien
ts
n
ee
d
m
e
ch
an
ical
v
en
tilatio
n
to
s
u
r
v
iv
e
[
2
8
]
.
T
h
e
p
atien
t'
s
r
eq
u
ir
e
m
en
ts
an
d
v
en
tilato
r
s
ettin
g
s
m
ay
n
o
t
m
atch
,
ca
u
s
in
g
p
atien
t
-
v
en
tilato
r
asy
n
ch
r
o
n
y
.
T
h
e
p
atien
t'
s
r
eq
u
ir
em
en
ts
an
d
v
en
tilato
r
s
ettin
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s
m
ay
n
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t
m
atch
,
ca
u
s
in
g
p
atien
t
-
v
e
n
tilato
r
asy
n
ch
r
o
n
y
.
T
h
e
R
asp
b
er
r
y
Pi
p
latf
o
r
m
v
o
l
u
n
tar
ily
in
co
r
p
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r
ates
wea
r
ab
le
s
en
s
o
r
s
,
f
o
r
e
x
am
p
le,
h
ea
r
t
r
ate
d
is
p
l
ay
,
ac
ce
ler
o
m
eter
,
s
en
s
o
r
,
an
d
g
lo
b
al
p
o
s
itio
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in
g
s
y
s
tem
elem
en
t to
n
o
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p
h
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s
ical
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tio
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,
co
n
s
er
v
atio
n
v
a
r
iab
les,
an
d
v
ig
o
r
o
u
s
s
ig
n
s
[
2
9
]
.
2.
P
RO
P
O
SE
D
M
E
T
H
O
D
2
.
1
.
M
et
ho
d
T
o
o
p
tim
ize
v
en
tilatio
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in
cr
itical
h
ea
lth
ca
r
e
s
itu
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n
s
,
th
is
s
y
s
tem
p
r
o
p
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s
es
a
co
m
p
lete
m
eth
o
d
o
l
o
g
y
t
h
at
co
m
b
in
es
cl
o
u
d
c
o
m
p
u
tin
g
with
DL
,
p
ar
ti
cu
lar
ly
L
STM
n
etwo
r
k
s
.
B
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s
u
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tin
g
iter
ativ
e
lear
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f
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s
tep
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p
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p
r
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e.
T
h
in
g
s
lik
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-
tid
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ca
r
b
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n
d
io
x
id
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x
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r
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r
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tr
a
ck
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t
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s
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s
o
r
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in
r
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tim
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T
h
elo
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-
b
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ev
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o
s
to
r
e
an
d
an
al
y
ze
th
e
d
ata
in
r
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tim
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T
o
s
to
r
e
an
d
an
aly
ze
it
i
n
r
ea
l
-
tim
e
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
37
,
No
.
2
,
Feb
r
u
a
r
y
20
25
:
1
05
3
-
1
06
3
1056
B
ef
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R
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ly
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Fig
u
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m
e
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cr
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ca
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d
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Flo
w
s
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o
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o
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cir
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en
t
ilato
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is
to
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s
e
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f
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en
s
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t
m
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s
u
r
es
th
e
p
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s
in
s
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ir
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d
e
x
p
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d
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k
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th
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y
ef
f
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t
a
n
d
th
e
v
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tilato
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s
p
er
f
o
r
m
an
ce
.
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tid
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v
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m
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y
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m
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in
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o
f
r
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m
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b
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m
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p
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s
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b
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f
lo
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en
s
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s
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en
s
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tr
an
s
d
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ay
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g
ases
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ical
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ef
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is
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as
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tem
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ay
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s
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o
w
h
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th
e
g
ases
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e.
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h
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en
s
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at
th
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g
ases
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ted
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itatio
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en
s
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s
ar
e
also
u
s
ef
u
l
in
k
ee
p
in
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th
e
r
esp
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y
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at
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id
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m
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ity
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th
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ak
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th
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s
co
m
f
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t
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d
to
av
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d
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g
o
u
t
th
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m
u
co
s
a.
T
h
ese
life
-
s
av
in
g
d
ev
ices
ar
e
ess
en
tial
in
th
e
I
C
U
to
m
o
n
ito
r
b
r
e
ath
in
g
r
ates,
p
r
o
v
id
e
m
ec
h
an
ical
v
en
tilatio
n
,
an
d
f
in
e
-
tu
n
e
v
en
tilatio
n
p
r
o
to
c
o
ls
.
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h
eir
d
ata
is
cr
u
cial
f
o
r
o
p
tim
izin
g
b
r
ea
th
in
g
b
ased
o
n
ed
u
ca
ted
ju
d
g
m
e
n
ts
an
d
im
p
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v
in
g
p
atien
t
o
u
tco
m
es.
2
.
3
.
T
ra
ini
ng
L
ST
M
m
o
del
T
r
ain
in
g
ca
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b
eg
in
a
f
ter
th
e
i
n
p
u
t
d
ata
h
as
b
ee
n
p
r
e
p
r
o
ce
s
s
ed
an
d
f
o
r
m
atted
.
Featu
r
e
en
g
in
ee
r
in
g
,
s
eq
u
en
ce
co
n
s
tr
u
ctio
n
,
an
d
n
o
r
m
aliza
tio
n
a
r
e
s
o
m
e
p
o
s
s
ib
le
p
r
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ce
d
u
r
es
in
v
o
lv
e
d
.
T
h
e
L
STM
m
o
d
el'
s
ar
ch
itectu
r
e
an
d
h
y
p
er
p
ar
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ter
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ar
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s
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ied
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a
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c
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t,
lay
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ac
tiv
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n
ctio
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g
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lar
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m
eth
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d
s
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if
icatio
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s
ar
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all
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ar
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o
f
t
h
is
.
Sev
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al
iter
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s
,
o
r
e
p
o
ch
s
,
ar
e
u
s
ed
to
tr
ain
th
e
m
o
d
el.
T
h
e
m
o
d
el
lear
n
s
f
r
o
m
th
e
tr
ain
in
g
d
ata
to
m
in
im
ize
t
h
e
lo
s
s
f
u
n
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an
d
u
p
d
ate
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e
n
etwo
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k
wei
g
h
ts
u
s
in
g
m
eth
o
d
s
lik
e
g
r
ad
ien
t
d
escen
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with
b
a
ck
p
r
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p
ag
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t
h
r
o
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g
h
o
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t
ea
c
h
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c
h
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f
o
r
m
an
c
e
m
ea
s
u
r
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lik
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ac
cu
r
ac
y
o
r
m
ea
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s
q
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ar
e
d
er
r
o
r
ass
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th
e
tr
ain
ed
m
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el
o
n
ce
tr
ai
n
in
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f
in
is
h
ed
.
I
t
also
ch
ec
k
s
its
p
er
f
o
r
m
an
ce
o
n
a
d
if
f
er
en
t
d
ataset
to
en
s
u
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t
h
e
m
o
d
el
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'
t
b
ec
o
m
e
t
o
o
h
u
n
g
u
p
o
n
th
e
tr
ain
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g
d
ata
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d
ca
n
'
t
b
e
g
en
er
alize
d
.
Fig
u
r
e
2
s
h
o
ws th
e
p
r
o
p
o
s
ed
L
STM
tr
ain
in
g
p
r
o
ce
s
s
o
f
th
is
s
y
s
tem
.
Fig
u
r
e
2
.
L
STM
m
o
d
el
tr
ain
in
g
p
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ce
s
s
T
ab
le
1
s
h
o
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e
p
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ce
s
s
f
lo
w
f
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r
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p
tim
izin
g
v
e
n
tilatio
n
,
wh
ich
e
n
tails
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ath
er
in
g
d
ata
f
r
o
m
p
atien
ts
in
r
ea
l
-
tim
e
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ia
m
o
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ito
r
s
,
v
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tilato
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s
,
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r
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,
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is
in
f
o
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m
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t
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n
s
is
ten
cy
,
th
e
d
ata
is
th
en
p
r
ep
r
o
ce
s
s
ed
L
STM
m
o
d
els
ar
e
co
n
s
tan
tly
im
p
r
o
v
ed
b
y
an
aly
zin
g
d
ata
in
r
ea
l
-
tim
e
an
d
tr
ain
e
d
u
s
in
g
p
r
ev
i
o
u
s
m
ater
ials
.
I
t
is
p
o
s
s
ib
le
to
au
to
m
atica
lly
m
o
d
if
y
th
e
v
en
tilato
r
s
ettin
g
s
b
a
s
ed
o
n
th
e
p
r
ed
icted
p
r
ed
ictio
n
s
p
r
o
v
i
d
ed
b
y
th
e
m
o
d
els.
I
t
p
r
o
v
id
es
ex
ce
llen
t
p
atien
t
ca
r
e
v
ia
r
em
o
te
m
o
n
it
o
r
in
g
,
co
n
tin
u
al
m
o
d
el
d
e
v
elo
p
m
en
t,
an
d
s
tr
in
g
en
t
d
ata
co
n
f
id
e
n
tiality
.
T
ab
le
1
.
W
o
r
k
f
lo
w
s
tep
s
f
o
r
v
en
tilatio
n
o
p
tim
izatio
n
S
t
e
p
D
e
scri
p
t
i
o
n
1
.
D
a
t
a
A
c
q
u
i
si
t
i
o
n
C
o
l
l
e
c
t
r
e
a
l
-
t
i
me
d
a
t
a
f
r
o
m
me
d
i
c
a
l
d
e
v
i
c
e
s
(
v
e
n
t
i
l
a
t
o
r
,
p
u
l
se
o
x
i
m
e
t
e
r
,
e
t
c
.
)
2
.
C
l
o
u
d
D
a
t
a
P
r
o
c
e
ss
i
n
g
P
r
e
p
r
o
c
e
ss
a
n
d
e
x
t
r
a
c
t
f
e
a
t
u
r
e
s fr
o
m
t
h
e
c
o
l
l
e
c
t
e
d
d
a
t
a
i
n
t
h
e
c
l
o
u
d
.
3
.
M
a
c
h
i
n
e
Le
a
r
n
i
n
g
M
o
d
e
l
Tr
a
i
n
i
n
g
Tr
a
i
n
t
h
e
LST
M
m
o
d
e
l
u
si
n
g
h
i
s
t
o
r
i
c
a
l
a
n
d
p
r
e
p
r
o
c
e
ss
e
d
d
a
t
a
.
4
.
R
e
a
l
-
t
i
me
P
r
e
d
i
c
t
i
o
n
M
a
k
e
p
r
e
d
i
c
t
i
o
n
s
f
o
r
v
e
n
t
i
l
a
t
i
o
n
s
e
t
t
i
n
g
s
b
a
s
e
d
o
n
c
u
r
r
e
n
t
d
a
t
a
.
5
.
R
e
m
o
t
e
M
o
n
i
t
o
r
i
n
g
a
n
d
I
n
t
e
r
v
e
n
t
i
o
n
M
o
n
i
t
o
r
p
a
t
i
e
n
t
st
a
t
u
s re
mo
t
e
l
y
a
n
d
i
n
t
e
r
v
e
n
e
i
f
n
e
c
e
ssar
y
.
L
S
T
M
T
r
a
i
n
i
n
g
P
r
o
c
e
s
s
D
a
t
a
P
r
e
p
a
r
a
t
i
o
n
D
e
f
i
n
e
L
S
T
M
M
o
d
e
l
T
r
a
i
n
i
n
g
I
t
e
r
a
t
i
o
n
s
M
o
d
e
l
E
v
a
l
u
a
t
i
o
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
37
,
No
.
2
,
Feb
r
u
a
r
y
20
25
:
1
05
3
-
1
06
3
1058
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
f
in
d
i
n
g
s
a
n
d
d
is
c
u
s
s
i
o
n
a
r
e
c
r
u
cia
l
i
n
ass
ess
in
g
t
h
e
m
et
h
o
d
'
s
e
f
f
ic
ac
y
a
n
d
p
in
p
o
i
n
ti
n
g
im
p
r
o
v
e
m
e
n
t
a
r
ea
s
i
n
t
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
f
o
r
o
p
ti
m
iz
in
g
v
e
n
t
ila
ti
o
n
i
n
c
r
it
ic
al
h
e
alt
h
ca
r
e
u
ti
liz
in
g
cl
o
u
d
co
m
p
u
ti
n
g
a
n
d
DL
.
C
li
n
i
ca
l
o
u
tc
o
m
es
a
n
d
p
at
ie
n
t
ca
r
e
i
n
i
n
t
e
n
s
i
v
e
c
a
r
e
u
n
its
i
m
p
r
o
v
ed
af
te
r
u
s
in
g
th
e
v
e
n
ti
lat
io
n
o
p
ti
m
iz
ati
o
n
s
y
s
t
e
m
.
D
ev
el
o
p
i
n
g
L
STM
n
e
tw
o
r
k
s
f
o
r
p
r
e
d
ic
ti
v
e
m
o
d
el
li
n
g
,
r
e
g
u
la
r
v
en
til
ati
o
n
s
en
s
o
r
s
,
a
n
d
cl
o
u
d
-
b
as
e
d
p
la
t
f
o
r
m
s
f
o
r
r
e
al
-
ti
m
e
d
at
a
p
r
o
c
ess
in
g
c
o
m
p
r
is
ed
t
h
e
ex
p
er
i
m
e
n
ta
l
s
et
u
p
.
Da
ta
s
am
p
li
n
g
,
cle
an
s
in
g
,
m
o
d
el
t
r
a
in
i
n
g
,
an
d
v
al
id
ati
o
n
we
r
e
all
p
a
r
t
o
f
t
h
e
m
e
th
o
d
o
l
o
g
ies
.
Me
d
ic
al
p
r
o
f
ess
i
o
n
a
ls
co
u
l
d
p
r
o
m
p
tl
y
m
a
k
e
e
d
u
ca
t
e
d
j
u
d
g
m
e
n
ts
a
b
o
u
t
t
h
e
p
at
ie
n
t'
s
b
r
ea
th
in
g
,
r
e
d
u
ci
n
g
th
e
p
o
t
en
ti
al
o
f
p
r
o
b
l
em
s
li
k
e
h
y
p
er
o
x
i
a
a
n
d
v
e
n
t
ila
to
r
-
ass
o
ciat
e
d
l
u
n
g
d
a
m
a
g
e
w
h
ile
m
a
in
t
ai
n
i
n
g
a
p
p
r
o
p
r
ia
te
o
x
y
g
e
n
a
tio
n
.
T
h
e
s
y
s
te
m
'
s
ca
p
ac
it
y
t
o
le
ar
n
a
n
d
a
d
ap
t
in
r
ea
l
-
ti
m
e
f
u
r
t
h
e
r
h
ig
h
l
ig
h
t
s
p
r
o
m
is
e
f
o
r
o
p
tim
izi
n
g
b
r
ea
t
h
i
n
g
t
ec
h
n
i
q
u
es
d
y
n
am
ica
ll
y
in
r
es
p
o
n
s
e
t
o
ev
o
l
v
i
n
g
p
ati
en
t
ci
r
c
u
m
s
ta
n
c
es
an
d
c
li
n
ic
al
n
ee
d
s
.
T
h
r
o
u
g
h
an
i
te
r
a
ti
v
e
DL
ap
p
r
o
ac
h
,
t
h
e
L
ST
M
m
o
d
el
c
an
i
d
e
n
t
if
y
i
n
t
r
ic
at
e
tr
en
d
s
a
n
d
p
a
tte
r
n
s
i
n
v
e
n
t
ila
ti
o
n
d
at
a,
all
o
wi
n
g
f
o
r
in
d
i
v
i
d
u
ali
ze
d
v
e
n
til
ati
o
n
c
o
n
t
r
o
l
b
as
e
d
o
n
ea
ch
p
at
ie
n
t'
s
s
p
e
cif
ic
p
h
y
s
i
o
l
o
g
y
a
n
d
cli
n
i
ca
l
c
o
u
r
s
e.
Secu
r
e
p
atien
t
d
ata
p
r
o
ce
s
s
in
g
an
d
s
h
ar
i
n
g
b
y
leg
al
r
e
g
u
latio
n
s
s
u
ch
as
th
e
h
ea
lth
in
s
u
r
an
ce
p
o
r
tab
ilit
y
an
d
ac
c
o
u
n
ta
b
ilit
y
ac
t
n
ec
ess
itate
s
s
tr
o
n
g
d
ata
g
o
v
er
n
an
ce
a
n
d
p
r
i
v
ac
y
s
tan
d
ar
d
s
.
I
t
is
ess
en
tia
l
to
v
alid
ate
an
d
co
n
tin
u
o
u
s
ly
m
o
d
if
y
th
e
DL
alg
o
r
ith
m
s
to
en
h
an
ce
th
e
ac
cu
r
ac
y
an
d
g
en
er
aliza
b
ilit
y
o
f
th
e
p
r
ed
ictio
n
s
,
esp
ec
ially
in
v
ar
i
ed
p
atien
t
g
r
o
u
p
s
an
d
clin
ical
co
n
d
itio
n
s
.
T
o
m
a
x
im
ize
th
e
s
y
s
tem
'
s
in
f
lu
en
ce
o
n
p
atien
t
ca
r
e
an
d
clin
ical
r
esu
lts
,
it
is
cr
u
ci
al
th
at
h
ea
lth
ca
r
e
p
er
s
o
n
n
el
u
n
d
er
g
o
u
s
er
tr
ain
in
g
an
d
ed
u
ca
tio
n
.
On
ly
th
en
ca
n
th
e
s
y
s
tem
b
e
u
s
ed
s
u
cc
ess
f
u
lly
an
d
its
o
u
t
p
u
ts
u
n
d
er
s
to
o
d
co
r
r
ec
tly
.
T
a
b
le
2
s
h
o
ws
a
tim
e
s
er
ies
d
ata
co
llectio
n
th
at
in
clu
d
es
m
an
y
v
en
tilato
r
-
a
n
d
p
h
y
s
io
lo
g
ical
-
r
elate
d
f
ac
to
r
s
f
o
r
o
p
tim
izin
g
v
en
tilatio
n
.
T
h
er
e
is
a
r
elatio
n
s
h
ip
b
etwe
en
th
e
r
o
ws
an
d
t
h
e
f
ea
tu
r
es
m
ea
s
u
r
ed
at
ea
ch
tim
e
s
tep
,
with
th
e
co
lu
m
n
s
r
e
f
lectin
g
th
e
v
ar
i
o
u
s
ch
ar
ac
ter
is
tics
.
I
n
in
ten
s
iv
e
ca
r
e
u
n
its
,
th
ese
m
etr
ics
ar
e
v
ital
f
o
r
d
eter
m
in
in
g
th
e
p
atien
t'
s
r
es
p
ir
ato
r
y
c
o
n
d
i
tio
n
,
p
e
r
s
o
n
alizin
g
v
en
tilato
r
s
ettin
g
s
,
an
d
d
e
v
elo
p
in
g
th
e
b
est
v
en
tilatio
n
p
lan
p
o
s
s
ib
le.
T
h
e
h
y
p
o
th
etica
l
d
e
m
o
n
s
tr
ates
h
o
w
d
ata
m
i
g
h
t
b
e
o
r
g
a
n
ized
to
tr
ai
n
DL
m
o
d
els.
T
h
e
g
o
al
is
to
d
em
o
n
s
tr
ate
h
o
w
in
d
iv
id
u
alize
d
v
en
tilatio
n
c
o
n
tr
o
l c
a
n
en
h
an
ce
p
atien
t o
u
tco
m
es.
T
ab
le
2
.
T
im
e
-
s
er
ies d
ataset
f
o
r
v
en
tilatio
n
o
p
tim
izatio
n
Ti
me
s
t
e
p
Te
mp
e
r
a
t
u
r
e
(
C
e
l
s
i
u
s)
P
a
t
i
e
n
t
a
g
e
(
y
e
a
r
s)
R
e
s
p
i
r
a
t
o
r
y
r
a
t
e
(
b
r
e
a
t
h
s
p
e
r
m
i
n
u
t
e
)
B
l
o
o
d
p
r
e
ss
u
r
e
(
mi
l
l
i
me
t
e
r
s
o
f
mer
c
u
r
y
)
H
e
a
r
t
r
a
t
e
(
b
e
a
t
s
p
e
r
mi
n
u
t
e
)
O
x
y
g
e
n
s
a
t
u
r
a
t
i
o
n
(
p
e
r
c
e
n
t
a
g
e
)
C
O
2
l
e
v
e
l
s
(
p
e
r
c
e
n
t
a
g
e
)
F
l
o
w
(
l
i
t
e
r
p
e
r
mi
n
u
t
e
)
V
e
n
t
i
l
a
t
o
r
S
e
t
t
i
n
g
s
c
e
n
t
i
met
e
r
o
f
w
a
t
e
r
(
c
mH
2
O)
1
2
5
.
6
45
20
1
2
0
/
8
0
80
95
4
.
2
8
10
2
2
6
.
3
45
22
1
2
2
/
7
8
82
94
4
.
5
9
12
3
2
7
.
1
46
24
1
1
8
/
7
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84
93
4
.
8
10
14
4
2
6
.
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46
25
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2
0
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85
92
5
.
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11
13
5
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6
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23
1
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8
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8
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83
94
4
.
9
1
0
.
5
11
Ov
er
th
e
tim
e
o
f
th
e
p
r
o
p
o
s
e
d
s
y
s
tem
'
s
tim
e
s
tep
s
,
th
e
p
r
e
d
icted
an
d
ac
t
u
al
v
e
n
tilatio
n
lev
els
ar
e
s
h
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g
r
ap
h
Fig
u
r
e
3
.
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o
o
b
s
er
v
e
h
o
w
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e
m
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el'
s
p
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ed
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m
atch
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e
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v
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es
o
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er
tim
e,
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is
g
r
ap
h
will
d
is
p
lay
two
lin
es:
o
n
e
f
o
r
p
r
ed
icted
v
en
tilatio
n
l
ev
els
an
d
o
n
e
f
o
r
ac
tu
al
v
en
ti
latio
n
lev
els.
W
ith
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ticip
ated
lev
els
clo
s
ely
m
at
ch
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g
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al
lev
els,
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e
s
am
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le
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th
at
th
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y
s
tem
f
u
n
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ef
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ec
tiv
ely
,
p
r
o
v
in
g
th
at
th
e
L
STM
-
b
ased
tech
n
iq
u
e
is
b
en
e
f
icial
in
o
p
ti
m
izin
g
v
en
tilatio
n
.
Fig
u
r
e
3
.
L
STM
p
r
ed
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n
f
o
r
v
en
tilatio
n
o
p
tim
izatio
n
o
v
e
r
tim
e
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
d
va
n
cin
g
a
ir
w
a
y
ma
n
a
g
eme
n
t fo
r
ve
n
tila
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p
timiz
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crit
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(
S
u
r
esh
K
u
ma
r
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r
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s
h
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a
mo
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th
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1059
T
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e
x
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x
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s
h
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e
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u
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e
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o
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ile
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ax
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tilatio
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alu
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in
liter
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te.
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h
e
p
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e
d
icted
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alu
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is
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STM
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el'
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tp
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t,
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t
ca
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w
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e
L
STM
m
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el
p
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ed
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til
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n
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y
n
am
ics
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o
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izes
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eth
o
d
s
b
y
co
m
p
ar
in
g
th
e
r
esu
lts
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is
u
ally
.
T
ab
l
e
3
s
h
o
ws
th
e
co
n
f
u
s
io
n
m
atr
ix
,
wh
ic
h
s
h
o
ws
h
o
w
well
a
class
if
icati
o
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el
p
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e
d
icts
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o
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a
n
d
b
ad
v
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r
esu
lts
.
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h
e
m
o
d
el'
s
p
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ar
e
s
h
o
wn
in
th
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c
o
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m
n
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ile
th
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ac
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tatu
s
es
ar
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h
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wn
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th
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T
h
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th
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ep
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m
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o
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h
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teg
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izatio
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lt.
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h
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g
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h
ical
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ep
ictio
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el
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if
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tiates b
etwe
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an
d
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ad
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tilatio
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co
n
tr
o
l
o
p
tio
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s
.
T
ab
le
3
.
C
o
n
f
u
s
io
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atr
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air
way
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t c
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A
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0
30
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t
i
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n
40
2
1
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T
h
e
L
STM
m
o
d
el'
s
tr
ain
in
g
lo
s
s
(
er
r
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r
)
d
im
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r
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h
s
in
Fig
u
r
e
4
.
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h
e
tr
ain
in
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lo
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s
will
d
ec
r
ea
s
e
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u
r
in
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wn
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th
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.
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h
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in
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icate
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th
at
th
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m
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etter
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ak
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.
An
ef
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h
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L
STM
m
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f
lo
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izatio
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d
ata,
w
h
ich
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tly
s
h
o
ws a
d
ec
r
ea
s
e
in
tr
a
in
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s
.
Fig
u
r
e
4
.
L
STM
m
o
d
el
p
e
r
f
o
r
m
an
ce
o
f
t
r
ain
in
g
l
o
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s
cu
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v
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T
h
e
X
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ax
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s
h
o
ws
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o
w
m
an
y
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th
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m
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as
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On
e
wh
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le
iter
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o
f
t
h
e
tr
ain
in
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d
ataset
is
r
ep
r
esen
ted
b
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h
ep
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ch
.
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e
tr
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in
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s
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atch
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e
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.
Fig
u
r
e
5
s
h
o
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th
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im
p
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e
L
STM
m
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el'
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t tr
ain
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p
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h
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h
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an
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Fig
u
r
e
5
.
L
STM
m
o
d
el
p
e
r
f
o
r
m
an
ce
o
f
ac
c
u
r
ac
y
cu
r
v
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
52
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
,
Vo
l.
37
,
No
.
2
,
Feb
r
u
a
r
y
20
25
:
1
05
3
-
1
06
3
1060
T
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(
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ab
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4
.
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h
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s
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en
co
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ag
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e
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.
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STM
m
o
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els
ar
e
u
s
ed
,
t
h
e
s
y
s
tem
im
p
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o
v
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its
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o
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ast
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est
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ch
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eg
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all,
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d
F1
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etter
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o
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s
tatu
s
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aster
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s
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g
s
ar
e
m
ad
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p
o
s
s
ib
le
b
y
L
STM
's
ca
p
ac
it
y
to
g
r
asp
co
m
p
licated
tem
p
o
r
al
co
r
r
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s
in
p
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d
ata.
Scalab
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s
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le
b
y
th
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s
y
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s
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o
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s
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f
m
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am
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o
f
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ata,
w
h
ich
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en
tial
f
o
r
m
ak
in
g
r
ea
l
-
tim
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.
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tco
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s
u
lt
f
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th
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s
y
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'
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in
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ed
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lab
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w
h
ich
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to
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etter
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t
o
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if
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er
en
t c
lin
ical
e
n
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ir
o
n
m
en
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s
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d
p
atien
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em
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n
d
s
.
T
h
e
r
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lts
s
h
o
w
th
at
in
co
m
p
ar
is
o
n
with
tr
a
d
itio
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al
m
eth
o
d
s
,
r
ea
l
-
tim
e
v
en
tilatio
n
o
p
tim
izatio
n
is
m
u
ch
im
p
r
o
v
ed
b
y
m
er
g
in
g
L
STM
n
etwo
r
k
s
with
clo
u
d
co
m
p
u
tin
g
.
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m
p
r
o
v
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g
p
r
ed
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ilit
y
an
d
f
lex
ib
ilit
y
is
in
ac
co
r
d
an
ce
with
th
is
o
b
j
ec
tiv
e.
T
h
is
ap
p
r
o
ac
h
p
r
o
v
id
e
s
b
etter
m
an
ag
em
en
t
o
f
lo
n
g
-
ter
m
s
u
p
p
o
r
t
th
an
p
r
ev
io
u
s
s
tu
d
ies.
C
o
m
p
u
tatio
n
al
lim
itatio
n
s
a
n
d
p
o
ten
ti
al
p
r
o
b
lem
s
with
d
ata
q
u
ali
ty
ar
e
ex
am
p
les
o
f
lim
itatio
n
s
wh
ich
m
ay
im
p
ac
t
g
en
er
aliza
b
ilit
y
.
I
t
h
as
b
ee
n
o
b
s
er
v
ed
th
at
L
STM
n
etwo
r
k
s
g
r
ea
tly
en
h
a
n
ce
r
ea
l
-
tim
e
v
en
tilatio
n
o
p
tim
iz
atio
n
.
T
im
e
-
s
er
ies
p
lo
ts
th
at
d
em
o
n
s
tr
ate
f
lex
ib
ilit
y
,
p
r
e
d
ictio
n
g
r
ap
h
s
th
at
d
em
o
n
s
tr
ate
im
p
r
o
v
ed
p
r
ed
i
ctio
n
ac
cu
r
ac
y
,
a
n
d
p
e
r
f
o
r
m
an
ce
ch
ar
t
s
co
m
p
ar
in
g
L
ST
M
with
tr
ad
itio
n
al
m
eth
o
d
s
ar
e
in
s
tan
ce
s
o
f
s
u
p
p
o
r
tin
g
d
ata.
T
h
er
e
ar
e
also
id
en
tifie
d
lim
itatio
n
s
r
elate
d
to
d
ata
q
u
ality
an
d
d
eter
m
in
in
g
lim
itatio
n
s
.
4.
CO
NCLU
SI
O
N
Op
tim
izin
g
v
e
n
tilatio
n
a
n
d
a
ir
way
co
n
tr
o
l
i
n
h
ea
lth
ca
r
e
e
n
v
ir
o
n
m
en
ts
o
f
g
r
ea
t
s
ig
n
if
ic
an
ce
m
a
y
g
r
ea
tly
b
e
n
ef
it
f
r
o
m
in
c
o
r
p
o
r
atin
g
in
n
o
v
ativ
e
tech
n
o
lo
g
y
,
in
clu
d
in
g
clo
u
d
co
m
p
u
tin
g
a
n
d
DL
,
esp
ec
ially
L
STM
alg
o
r
ith
m
s
.
T
h
e
s
y
s
tem
'
s
ca
p
ac
ity
to
ca
p
tu
r
e
co
m
p
licated
tem
p
o
r
al
r
elatio
n
s
h
ip
s
in
p
atien
t
d
ata
allo
ws
it
to
ac
h
iev
e
g
r
ea
te
r
p
er
f
o
r
m
a
n
ce
in
p
r
e
d
ictin
g
ap
p
r
o
p
r
iate
b
r
ea
th
in
g
m
eth
o
d
s
v
ia
t
h
e
d
e
p
lo
y
m
en
t
o
f
L
STM
m
o
d
els.
T
h
e
s
y
s
tem
ca
n
b
e
ea
s
ily
ad
ju
s
ted
to
d
i
f
f
er
en
t
p
atie
n
t
d
em
an
d
s
an
d
clin
ical
s
itu
atio
n
s
b
ec
au
s
e
o
f
th
e
f
lex
ib
ilit
y
o
f
clo
u
d
c
o
m
p
u
tin
g
r
eso
u
r
ce
s
.
T
h
is
allo
ws
f
o
r
b
etter
p
a
tien
t
o
u
tco
m
es
an
d
r
ea
l
-
tim
e
d
ec
is
io
n
-
m
ak
in
g
.
C
lin
ician
s
ca
n
m
ak
e
ed
u
ca
ted
ju
d
g
m
e
n
ts
ab
o
u
t
v
e
n
tilatio
n
m
an
ag
e
m
en
t
b
ec
a
u
s
e
th
e
g
r
a
p
h
ical
u
s
er
in
ter
f
ac
e
g
iv
es
th
em
ea
s
y
ac
ce
s
s
to
v
en
tilatio
n
d
ata
an
d
m
o
d
el
p
r
ed
ictio
n
s
.
T
h
e
s
y
s
tem
is
a
h
u
g
e
s
tep
f
o
r
war
d
in
ai
r
way
m
an
ag
em
en
t.
I
t
p
r
o
v
id
es
co
m
p
r
eh
e
n
s
iv
e
s
o
lu
tio
n
s
f
o
r
im
p
r
o
v
in
g
p
atien
t
ca
r
e
in
em
er
g
en
cies
with
u
s
er
in
ter
f
ac
es.
Ad
d
itio
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al
ad
v
an
ce
m
en
ts
in
t
h
is
ar
ea
m
ig
h
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s
ig
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if
ican
tly
alter
air
wa
y
m
a
n
ag
em
en
t
m
eth
o
d
s
in
th
e
f
u
tu
r
e,
lead
in
g
to
b
etter
p
atien
t o
u
tco
m
es
an
d
life
s
av
i
n
g
s
d
u
e
to
tech
n
o
l
o
g
ical
p
r
o
g
r
ess
.
RE
F
E
R
E
NC
E
S
[
1
]
H
.
Y
.
A
l
-
H
e
t
a
r
i
,
Y
.
A
l
g
i
n
a
h
i
,
M
.
N
.
K
a
b
i
r
,
N
.
Q
.
A
l
-
N
a
g
g
a
r
,
M
.
A
.
A
l
-
R
u
mai
m
a
,
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.
M
.
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a
sa
n
,
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M
o
d
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l
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f
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I
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En
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T
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I
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0
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0
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.
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[
2
]
B
.
A
.
A
d
mass
,
N
.
S
.
En
d
a
l
e
w
,
H
.
Y
.
Ta
w
y
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,
D
.
Y
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M
e
l
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sse
,
M
.
M
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W
o
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k
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,
a
n
d
T.
D
.
F
i
l
a
t
i
e
,
“
E
v
i
d
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n
c
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-
b
a
se
d
a
i
r
w
a
y
man
a
g
e
me
n
t
p
r
o
t
o
c
o
l
f
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r
a
c
r
i
t
i
c
a
l
i
l
l
p
a
t
i
e
n
t
i
n
me
d
i
c
a
l
i
n
t
e
n
si
v
e
c
a
r
e
u
n
i
t
:
sy
s
t
e
m
a
t
i
c
r
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v
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w
,
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An
n
a
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o
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Me
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ry
,
v
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.
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,
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j
.
a
msu
.
2
0
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2
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4
.
[
3
]
M
.
B
o
r
r
e
l
l
o
a
n
d
P
.
H
e
a
l
t
h
c
a
r
e
,
“
O
x
y
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r
a
t
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o
c
o
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t
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l
i
n
c
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t
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c
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mp
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e
sse
d
o
x
y
g
e
n
a
n
d
b
l
o
w
e
r
g
a
s
so
u
r
c
e
s,
”
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
Am
e
r
i
c
a
n
C
o
n
t
r
o
l
C
o
n
f
e
re
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e
,
v
o
l
.
2
0
2
0
-
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y
,
p
p
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.
[
4
]
N
.
H
e
z
a
r
j
a
r
i
b
i
e
t
a
l
.
,
“
M
o
n
i
t
o
r
i
n
g
l
u
n
g
me
c
h
a
n
i
c
s
d
u
r
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n
g
mec
h
a
n
i
c
a
l
v
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n
t
i
l
a
t
i
o
n
u
s
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n
g
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
a
l
g
o
r
i
t
h
ms,”
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
An
n
u
a
l
I
n
t
e
r
n
a
t
i
o
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l
C
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f
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c
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t
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EE
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E
n
g
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ri
n
g
i
n
Me
d
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c
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n
e
a
n
d
B
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y
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t
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,
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MB
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,
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2
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p
p
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B
C
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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d
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J
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&
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N:
2
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52
A
d
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cin
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a
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w
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timiz
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K
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ma
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1061
[
5
]
A
.
D
e
e
p
a
,
M
.
N
K
,
R
.
La
t
h
a
,
J.
P
r
e
e
t
h
a
,
T
.
S
.
K
u
mar,
a
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d
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.
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u
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a
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,
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so
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safe
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v
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t
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2
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t
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6
.
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.
[
6
]
K
.
Y
.
P
.
A
l
meri
a
,
M
.
J.
D
.
C
o
ma
d
r
e
,
S
.
M
.
U
y
,
M
.
T
.
M
a
r
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a
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t
o
,
a
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d
J.
R
.
C
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l
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o
,
“
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ma
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2
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1
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I
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7
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S
.
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l
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u
,
K
.
B
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sh
k
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n
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y
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d
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T
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6
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9
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52
I
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Vo
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37
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No
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2
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Feb
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20
25
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1062
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e
a
d
d
e
p
a
rtme
n
t
o
f
in
f
o
rm
a
ti
o
n
tec
h
n
o
lo
g
y
a
t
S
a
v
e
e
th
a
E
n
g
i
n
e
e
rin
g
C
o
ll
e
g
e
o
f
En
g
i
n
e
e
rin
g
,
Ch
e
n
n
a
i
-
6
0
2
1
0
5
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
m
o
b
il
e
Ad
Ho
c
,
c
lo
u
d
c
o
m
p
u
ti
n
g
,
n
e
tw
o
rk
se
c
u
ri
ty
,
m
a
c
h
in
e
lea
rn
i
n
g
a
n
d
ima
g
e
p
r
o
c
e
ss
in
g
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
k
su
re
sh
n
tec
h
@
g
m
a
il
.
c
o
m
.
Dr
.
G
o
v
in
d
h
a
r
a
j
u
K
a
r
th
i
re
c
e
iv
e
d
h
is
u
n
d
e
rg
ra
d
u
a
te
d
e
g
re
e
B.
Tec
h
.
in
in
fo
rm
a
ti
o
n
tec
h
n
o
l
o
g
y
d
isc
ip
li
n
e
fro
m
P
o
n
d
ich
e
rr
y
Un
i
v
e
rsity
.
He
fin
ish
e
d
h
is
p
o
stg
ra
d
u
a
te
d
e
g
re
e
M
.
Tec
h
.
i
n
i
n
fo
rm
a
ti
o
n
se
c
u
rit
y
a
t
P
o
n
d
ich
e
rry
En
g
in
e
e
rin
g
Co
ll
e
g
e
a
n
d
i
t
wa
s
sp
o
n
s
o
re
d
b
y
t
h
e
d
e
p
a
rtme
n
t
o
f
i
n
fo
rm
a
ti
o
n
tec
h
n
o
l
o
g
y
,
I
n
d
ia.
I
n
2
0
1
9
,
h
e
c
o
m
p
lete
d
d
o
c
to
ra
l
d
e
g
re
e
Ph
.
D
.
i
n
C
o
m
p
u
ter
S
c
ien
c
e
a
n
d
E
n
g
i
n
e
e
rin
g
Disc
ip
li
n
e
fr
o
m
P
o
n
d
ic
h
e
rry
U
n
iv
e
rsit
y
.
No
w
h
e
is
c
u
rre
n
tl
y
wo
r
k
in
g
a
s
A
ss
o
c
iate
P
ro
fe
ss
o
r
i
n
t
h
e
d
e
p
a
rtm
e
n
t
o
f
Artifi
c
ial
In
telli
g
e
n
c
e
a
n
d
Da
ta
S
c
ien
c
e
a
t
S
a
v
e
e
th
a
E
n
g
i
n
e
e
rin
g
C
o
ll
e
g
e
.
He
h
a
s
p
u
b
l
ish
e
d
c
o
n
sid
e
ra
b
le
re
p
u
te
d
Jo
u
rn
a
ls
i
n
d
e
x
e
d
i
n
S
c
o
p
u
s
,
S
CI,
a
n
d
S
CIE
.
He
is
a
l
ife
m
e
m
b
e
r
o
f
IS
TE
,
In
d
ia.
His
a
re
a
s
o
f
in
tere
st
a
re
ima
g
e
p
ro
c
e
ss
in
g
,
b
io
m
e
tri
c
s,
a
rti
ficia
l
in
telli
g
e
n
c
e
,
m
a
c
h
in
e
lea
rn
in
g
,
d
a
ta
sc
ien
c
e
a
n
d
c
y
b
e
r
se
c
u
rit
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
g
k
a
rt
h
i@sa
v
e
e
th
a
.
a
c
.
in
.
Ms.
Mo
o
r
th
y
R
a
d
h
i
k
a
S
h
e
is
a
n
As
sista
n
t
P
ro
fe
ss
o
r
in
De
p
a
rtme
n
t
o
f
In
fo
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
a
t
R.
M
.
D.
En
g
in
e
e
rin
g
Co
ll
e
g
e
.
S
h
e
o
b
tain
e
d
h
e
r
Ba
c
h
e
lo
r’s
o
f
Tec
h
n
o
l
o
g
y
d
e
g
re
e
i
n
I
n
fo
rm
a
ti
o
n
Tec
h
n
o
lo
g
y
fro
m
Bh
a
jara
n
g
En
g
in
e
e
rin
g
C
o
ll
e
g
e
a
n
d
M
a
ste
r
o
f
En
g
i
n
e
e
rin
g
d
e
g
re
e
in
C
o
m
p
u
ter
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
rin
g
fro
m
Ve
lam
m
a
l
En
g
i
n
e
e
rin
g
Co
ll
e
g
e
.
S
h
e
c
u
rre
n
t
ly
p
u
rsu
i
n
g
h
e
r
P
h
.
D d
e
g
re
e
fro
m
An
n
a
Un
iv
e
rsity
.
He
r
a
re
a
s
o
f
in
tere
st
in
c
lu
d
e
Big
Da
ta,
M
a
c
h
in
e
Lea
rn
i
n
g
,
Da
tab
a
se
M
a
n
a
g
e
m
e
n
t
S
y
ste
m
,
Da
ta
stru
c
tu
re
.
S
h
e
h
a
s
p
u
b
l
ish
e
d
5
p
a
p
e
rs
in
In
ter
n
a
t
io
n
a
l
Jo
u
r
n
a
l
a
n
d
C
o
n
fe
re
n
c
e
.
Sh
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ra
d
i
k
a
m
o
o
rt
h
i
@g
m
a
il
.
c
o
m
.
Dr
.
Ana
n
th
a
Ra
m
a
n
Ra
t
h
in
a
m
is
a
n
As
so
c
iate
P
r
o
fe
ss
o
r
in
t
h
e
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
En
g
in
e
e
ri
n
g
a
t
K
L
Un
i
v
e
rsity
-
Vijay
a
wa
d
a
,
wh
e
re
h
e
h
a
s
b
e
e
n
sin
c
e
M
a
rc
h
,
2
0
2
3
.
F
r
o
m
2
0
1
7
t
o
F
e
b
,
2
0
2
3
h
e
se
rv
e
d
a
s
De
p
a
rtme
n
t
He
a
d
in
M
a
ll
a
Re
d
d
y
I
n
stit
u
te
o
f
En
g
i
n
e
e
rin
g
a
n
d
Tec
h
n
o
l
o
g
y
,
Hy
d
e
ra
b
a
d
.
Du
ri
n
g
2
0
0
9
to
2
0
1
7
h
e
se
rv
e
d
a
s
As
so
c
iate
p
ro
fe
ss
o
r
i
n
th
e
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
En
g
in
e
e
ri
n
g
,
A
d
h
i
y
a
m
a
a
n
Co
ll
e
g
e
o
f
En
g
i
n
e
e
rin
g
,
H
o
su
r.
He
re
c
e
iv
e
d
IAS
TE
B
ES
T
DIRECTOR
A
WARD
in
2
0
1
8
,
a
n
d
a
n
h
e
Ap
p
o
i
n
ted
a
s
I
n
d
ia
n
Ex
a
m
in
e
r
fo
r
P
h
.
D.
VIV
A
VO
CE
b
y
An
n
a
U
n
iv
e
rsit
y
fr
o
m
las
t
6
Ye
a
rs.
He
wo
rk
e
d
a
s
Re
se
a
rc
h
c
o
o
rd
i
n
a
to
r
fo
r
P
h
.
D.
P
a
rt
ti
m
e
Re
se
a
rc
h
S
c
h
o
lar
b
y
S
R
M
Un
i
v
e
rsit
y
a
n
d
h
e
a
p
p
o
i
n
ted
a
s
t
h
e
Bo
a
rd
s
o
f
S
t
u
d
ies
(Bo
S
)
m
e
m
b
e
r
fo
r
v
a
rio
u
s
E
n
g
i
n
e
e
rin
g
c
o
ll
e
g
e
s
fro
m
2
0
1
9
o
n
wa
rd
s.
His
re
se
a
rc
h
in
tere
sts
sp
a
n
b
o
t
h
c
o
m
p
u
t
e
r
n
e
two
rk
in
g
a
n
d
Cl
o
u
d
Co
m
p
u
ti
n
g
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
g
ra
n
a
n
t
h
a
.
ra
m
a
n
@g
m
a
il
.
c
o
m
.
Dr
.
Ay
a
la
p
o
g
u
Ra
t
n
a
Ra
ju
re
c
e
iv
e
d
h
is
Un
d
e
r
g
ra
d
u
a
te
De
g
re
e
B.
Tec
h
.
,
i
n
In
fo
rm
a
ti
o
n
Tec
h
n
o
lo
g
y
Disc
ip
li
n
e
fro
m
Ja
wa
h
a
rlal
Ne
h
r
u
Tec
h
n
o
lo
g
ica
l
Un
iv
e
rsity
,
Hy
d
e
ra
b
a
d
a
n
d
P
o
stg
ra
d
u
a
te
De
g
re
e
M
.
E.
i
n
CS
E
fr
o
m
An
n
a
m
a
lai
Un
iv
e
rsity
,
Tam
il
n
a
d
u
.
In
d
ia.
I
n
2
0
2
4
,
h
e
c
o
m
p
lete
d
D
o
c
to
ra
l
De
g
re
e
P
h
D
in
C
o
m
p
u
ter
S
c
ien
c
e
a
n
d
E
n
g
in
e
e
rin
g
Disc
ip
li
n
e
fro
m
Ja
wa
h
a
rlal
Ne
h
r
u
Tec
h
n
o
lo
g
ica
l
Un
i
v
e
rsity
,
Hy
d
e
ra
b
a
d
.
No
w
h
e
is
c
u
rre
n
tl
y
wo
rk
i
n
g
a
s
As
sista
n
t
P
r
o
fe
ss
o
r
in
t
h
e
d
e
p
a
rtme
n
t
o
f
C
S
E
a
t
M
a
h
a
tma
G
a
n
d
h
i
In
sti
tu
te
o
f
Tec
h
n
o
l
o
g
y
,
Hy
d
e
ra
b
a
d
.
He
h
a
s
p
u
b
l
ish
e
d
c
o
n
si
d
e
ra
b
le
re
p
u
te
d
Jo
u
rn
a
ls
in
d
e
x
e
d
i
n
sc
o
p
u
s,
S
CI,
a
n
d
S
CIE
.
He
is
a
li
fe
m
e
m
b
e
r
o
f
IAENG
.
His
a
re
a
s
o
f
in
tere
st
a
re
m
e
d
ica
l
ima
g
e
p
ro
c
e
ss
in
g
,
a
rt
ifi
c
ial
in
tell
ig
e
n
c
e
,
m
a
c
h
in
e
lea
rn
in
g
,
d
a
ta
sc
ien
c
e
a
n
d
c
y
b
e
r
se
c
u
rit
y
.
He
c
a
n
b
e
c
o
n
tac
t
a
t
e
m
a
il
:
a
ra
tn
a
ra
ju
_
c
se
@m
g
it
.
a
c
.
in
.
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