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s
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an
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lar
g
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ass
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s
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u
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x
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p
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f
tr
a
n
s
f
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r
m
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ea
lth
[
1
]
,
[
2
]
.
Var
iatio
n
s
in
o
il
tem
p
er
atu
r
e,
o
f
ten
ca
u
s
ed
b
y
th
er
m
al
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in
f
lu
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th
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m
ig
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m
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p
ap
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in
s
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r
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e
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c
o
m
p
licatin
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d
itio
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ass
es
s
m
en
t
[
3
]
.
T
h
e
d
y
n
am
ic
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ter
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b
etwe
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p
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at
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o
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d
d
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x
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n
h
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a
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t
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p
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th
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s
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p
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ag
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ate.
Un
d
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n
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cu
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p
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th
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p
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s
tr
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an
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av
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id
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p
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em
atu
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ailu
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es.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
1
-
9
2
R
ec
en
t
ad
v
an
ce
m
e
n
ts
in
a
r
tifi
cial
in
tellig
en
ce
h
a
v
e
o
p
en
e
d
n
ew
av
en
u
es
f
o
r
tr
a
n
s
f
o
r
m
e
r
d
iag
n
o
s
tics
.
Ma
ch
in
e
lear
n
i
n
g
(
ML
)
m
o
d
e
ls
,
in
p
ar
ticu
lar
,
h
a
v
e
s
h
o
w
n
p
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o
m
is
in
g
r
esu
lts
in
esti
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atin
g
m
o
is
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co
n
ten
t
an
d
in
s
u
latio
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co
n
d
itio
n
u
s
i
n
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lab
o
r
at
o
r
y
a
n
d
f
ield
d
ata
[
4
]
–
[
6
]
.
T
h
ese
m
o
d
els
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n
ca
p
tu
r
e
co
m
p
lex
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o
n
lin
ea
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r
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s
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ip
s
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o
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g
o
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atio
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ar
am
eter
s
,
s
u
c
h
as
g
as
co
n
ce
n
tr
atio
n
s
an
d
tem
p
er
atu
r
e,
wh
ich
ar
e
d
if
f
icu
lt
to
q
u
a
n
tify
u
s
in
g
tr
a
d
itio
n
al
an
aly
tical
tec
h
n
iq
u
es.
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m
e
ap
p
r
o
ac
h
es
em
p
lo
y
d
ielec
tr
ic
f
r
eq
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e
n
c
y
r
esp
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n
s
e
(
DFR
)
o
r
d
is
s
o
lv
ed
g
as
an
aly
s
is
(
DG
A)
as
in
p
u
ts
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wh
ile
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th
er
s
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s
e
n
eu
r
al
n
etw
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k
s
o
r
h
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n
ce
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e
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ictio
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cc
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r
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y
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we
v
er
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m
a
n
y
o
f
th
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s
tu
d
ies
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e
eith
er
lim
ited
in
s
ca
le,
r
ely
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s
y
n
th
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atasets
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lack
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d
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n
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er
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al
f
ield
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n
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i
tio
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s
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n
th
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ap
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we
ad
d
r
ess
th
is
g
ap
b
y
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a
co
m
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en
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s
e
s
tu
d
y
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v
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lv
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ewly
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m
m
is
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n
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o
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r
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r
ate
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at
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2
6
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at
AT
T
AR
AT
Po
wer
C
o
m
p
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n
y
(
APC
O)
,
J
o
r
d
an
.
An
o
n
lin
e
m
o
n
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r
in
g
d
ev
ice
was
in
s
talled
to
co
n
tin
u
o
u
s
ly
tr
ac
k
d
i
s
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lv
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ases
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m
o
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tu
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n
t
r
atio
n
s
o
v
er
a
th
r
ee
-
y
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r
p
er
io
d
.
Usi
n
g
th
i
s
lar
g
e
an
d
h
ig
h
-
r
eso
lu
tio
n
d
a
taset
(
o
v
er
4
8
,
0
0
0
o
b
s
er
v
atio
n
s
)
,
we
d
ev
elo
p
e
d
an
d
ev
alu
ate
d
m
u
ltip
le
m
a
ch
in
e
lear
n
in
g
m
o
d
els
to
p
r
ed
ict
th
e
le
v
els
o
f
m
o
is
tu
r
e
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d
d
is
s
o
lv
ed
o
x
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en
u
n
d
er
v
ar
y
i
n
g
o
p
er
atio
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al
co
n
d
itio
n
s
.
T
h
e
m
o
d
els
wer
e
f
u
r
t
h
er
v
alid
ated
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s
in
g
d
ata
f
r
o
m
a
s
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ter
tr
a
n
s
f
o
r
m
er
to
ass
ess
g
en
er
aliz
ab
ilit
y
an
d
r
o
b
u
s
tn
ess
.
T
h
is
ap
p
r
o
ac
h
en
h
an
ce
s
co
n
d
itio
n
-
b
ased
m
ai
n
ten
an
ce
p
r
ac
tices
an
d
p
r
o
v
id
es
v
al
u
ab
le
in
s
ig
h
ts
in
to
t
r
an
s
f
o
r
m
e
r
i
n
s
u
latio
n
b
e
h
av
io
r
u
n
d
er
d
y
n
a
m
ic
th
er
m
al
a
n
d
en
v
ir
o
n
m
e
n
tal
co
n
d
itio
n
s
[
7
]
,
[
8
]
.
2.
M
O
I
S
T
UR
E
,
D
I
SS
O
L
VE
D
O
XYG
E
N,
H
YD
RO
G
E
N
I
N
T
RAN
SFO
RM
E
R
I
NSUL
A
T
I
O
N
SYST
E
M
2
.
1
.
So
urce
s
Hig
h
-
q
u
ality
m
a
n
u
f
ac
t
u
r
in
g
o
f
p
o
wer
tr
a
n
s
f
o
r
m
e
r
s
n
ec
ess
itates
s
tr
ict
co
n
tr
o
l
o
f
m
o
is
tu
r
e
co
n
ten
t,
esp
ec
ially
d
u
r
in
g
th
e
cr
itical
d
r
y
in
g
p
h
ase
o
f
ce
llu
lo
s
e
in
s
u
latio
n
.
T
h
is
p
r
o
ce
s
s
aim
s
t
o
r
ed
u
ce
th
e
wate
r
co
n
ten
t
to
b
elo
w
1
.
0
%
in
ac
c
o
r
d
an
ce
with
i
n
d
u
s
tr
y
s
tan
d
a
r
d
s
[
9
]
,
[
1
0
]
.
Desp
ite
th
ese
m
ea
s
u
r
es,
th
e
wate
r
co
n
ten
t in
th
e
i
n
s
u
latio
n
s
y
s
tem
o
f
ten
in
c
r
ea
s
es p
o
s
t
-
m
an
u
f
a
ctu
r
e
d
u
e
to
s
ev
er
al
o
p
e
r
atio
n
a
l f
ac
to
r
s
.
E
x
p
o
s
u
r
e
to
am
b
ien
t
air
d
u
r
in
g
tr
an
s
p
o
r
tatio
n
,
s
to
r
ag
e,
an
d
m
ain
ten
an
ce
ca
n
lead
t
o
m
o
is
tu
r
e
i
n
g
r
ess
.
Ad
d
itio
n
ally
,
m
o
is
tu
r
e
m
ig
r
atio
n
o
cc
u
r
s
b
etwe
en
th
e
o
il
an
d
s
o
lid
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u
l
atio
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u
n
d
er
th
er
m
al
cy
clin
g
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as
th
e
s
o
lu
b
ilit
y
o
f
wate
r
in
o
il
c
h
an
g
es
with
te
m
p
er
atu
r
e.
Dis
s
o
lv
ed
o
x
y
g
en
an
d
h
y
d
r
o
g
e
n
en
te
r
th
e
t
r
an
s
f
o
r
m
er
o
il
th
r
o
u
g
h
m
u
ltip
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p
ath
way
s
,
in
clu
d
in
g
air
in
g
r
ess
f
r
o
m
m
ain
te
n
an
ce
ac
tiv
ities
,
b
r
ea
t
h
in
g
ac
tio
n
s
ca
u
s
ed
b
y
tem
p
er
atu
r
e
-
in
d
u
ce
d
o
il
ex
p
a
n
s
io
n
an
d
co
n
tr
ac
tio
n
,
leak
s
,
an
d
d
eg
r
ad
atio
n
o
f
in
s
u
latin
g
m
ater
ials
.
T
h
ese
g
ases
ca
n
also
f
o
r
m
d
u
r
in
g
th
e
o
x
id
atio
n
o
f
o
il
an
d
ce
ll
u
lo
s
e,
esp
ec
ially
in
th
e
p
r
es
en
ce
o
f
m
o
is
tu
r
e,
ac
ce
ler
atin
g
ag
in
g
an
d
d
eter
io
r
atin
g
d
ielec
tr
ic
p
e
r
f
o
r
m
an
ce
[
1
1
]
,
[
1
2
]
.
2
.
2
.
E
f
f
ec
t
o
n t
he
t
ra
ns
f
o
r
mer
ins
ula
t
io
n sy
s
t
em
Mo
is
tu
r
e
an
d
o
x
y
g
en
ar
e
am
o
n
g
th
e
m
o
s
t
in
f
lu
en
tial
f
ac
to
r
s
d
r
iv
in
g
th
e
ag
in
g
an
d
d
eg
r
ad
atio
n
o
f
b
o
th
liq
u
i
d
an
d
s
o
lid
tr
an
s
f
o
r
m
er
in
s
u
latio
n
.
Hig
h
m
o
is
tu
r
e
lev
els
r
ed
u
ce
t
h
e
b
r
ea
k
d
o
w
n
v
o
ltag
e,
in
cr
ea
s
e
d
ielec
tr
ic
lo
s
s
es,
an
d
s
ig
n
if
ican
tly
d
ec
r
ea
s
e
th
e
m
ec
h
an
i
ca
l
in
teg
r
ity
o
f
ce
llu
lo
s
e
in
s
u
latio
n
.
Pro
lo
n
g
ed
ex
p
o
s
u
r
e
lead
s
to
h
y
d
r
o
ly
tic
an
d
o
x
i
d
ativ
e
d
eg
r
ad
atio
n
,
r
esu
ltin
g
in
th
e
g
en
e
r
atio
n
o
f
ac
id
s
,
f
u
r
an
s
,
an
d
s
lu
d
g
e,
wh
ich
c
o
m
p
r
o
m
is
e
tr
a
n
s
f
o
r
m
er
r
eliab
ilit
y
[
1
1
]
,
[
1
3
]
.
Mo
is
tu
r
e
p
r
o
m
o
tes
th
e
f
o
r
m
at
io
n
o
f
p
o
lar
co
n
tam
in
an
ts
an
d
co
r
r
o
s
iv
e
b
y
p
r
o
d
u
cts,
wh
ich
n
eg
ativ
ely
af
f
ec
t
h
ea
t
d
is
s
ip
atio
n
a
n
d
i
n
s
u
latio
n
s
tr
en
g
th
.
Mo
r
e
o
v
er
,
t
h
e
p
r
esen
ce
o
f
d
is
s
o
lv
ed
o
x
y
g
en
ac
ce
ler
ates
o
il
o
x
id
atio
n
an
d
in
cr
ea
s
es
th
e
ac
id
ity
lev
el,
f
u
r
th
e
r
d
eg
r
a
d
i
n
g
th
e
d
ielec
tr
ic
p
r
o
p
er
ties
o
f
th
e
s
y
s
tem
.
T
h
is
d
eg
r
ad
atio
n
lead
s
to
in
c
r
ea
s
ed
p
o
wer
lo
s
s
es,
r
ed
u
ce
d
in
s
u
latio
n
life
,
a
n
d
a
h
ig
h
er
lik
el
ih
o
o
d
o
f
in
cip
ien
t
f
au
lts
[
7
]
.
Du
e
to
th
ese
cr
itic
al
im
p
ac
ts
,
m
o
n
ito
r
in
g
m
o
is
t
u
r
e
an
d
d
is
s
o
lv
ed
o
x
y
g
e
n
co
n
ten
t
is
ess
en
tial
in
h
ig
h
-
v
o
ltag
e
tr
an
s
f
o
r
m
er
s
to
e
n
s
u
r
e
s
af
e
o
p
e
r
atio
n
an
d
to
e
n
ab
le
tim
ely
in
ter
v
e
n
tio
n
s
[
1
1
]
,
[
1
3
]
.
2
.
3
.
M
ig
ra
t
i
o
n a
nd
equil
ibri
um
cha
ra
ct
er
is
t
ics
T
h
e
m
o
v
em
en
t o
f
m
o
is
tu
r
e
with
in
o
il
-
p
a
p
er
in
s
u
latio
n
s
y
s
tem
s
is
g
o
v
er
n
e
d
b
y
tem
p
er
at
u
r
e
g
r
ad
ien
ts
an
d
v
a
p
o
r
p
r
ess
u
r
e
d
if
f
er
en
ti
als.
T
h
ese
f
o
r
ce
s
d
r
iv
e
m
o
is
tu
r
e
m
ig
r
atio
n
b
etwe
en
s
o
lid
an
d
liq
u
i
d
p
h
ases
,
esp
ec
ially
d
u
r
in
g
d
aily
lo
ad
in
g
cy
cles.
T
h
e
r
ate
o
f
m
ig
r
atio
n
is
ch
ar
ac
ter
ized
b
y
th
e
d
if
f
u
s
io
n
co
ef
f
icien
t
(
D)
,
wh
ich
d
ep
e
n
d
s
o
n
tem
p
er
atu
r
e
an
d
in
s
u
latio
n
c
o
n
d
itio
n
.
As
th
e
tr
an
s
f
o
r
m
er
o
il
h
ea
ts
u
p
,
its
ab
ilit
y
to
d
is
s
o
lv
e
wa
ter
in
cr
ea
s
es,
tem
p
o
r
ar
ily
r
ed
u
cin
g
th
e
r
elativ
e
wate
r
s
atu
r
atio
n
in
o
il.
T
h
is
r
esu
lts
in
m
o
is
tu
r
e
b
ein
g
r
elea
s
ed
f
r
o
m
th
e
p
ap
er
in
s
u
latio
n
in
to
th
e
o
il.
Du
r
in
g
co
o
lin
g
,
th
e
r
ev
e
r
s
e
m
ig
r
atio
n
ca
n
o
cc
u
r
.
T
h
ese
c
y
clica
l
ex
ch
an
g
es
h
ig
h
lig
h
t
th
e
d
y
n
am
ic
n
atu
r
e
o
f
m
o
is
tu
r
e
d
is
tr
ib
u
tio
n
a
n
d
th
e
im
p
o
r
tan
ce
o
f
c
o
n
tin
u
o
u
s
m
o
n
i
to
r
in
g
.
Oo
m
m
en
’
s
m
o
is
tu
r
e
eq
u
ilib
r
iu
m
cu
r
v
es,
d
e
v
elo
p
ed
i
n
1
9
8
3
,
ar
e
wid
el
y
u
s
ed
to
d
e
s
cr
ib
e
th
e
r
elatio
n
s
h
ip
b
etwe
en
m
o
is
tu
r
e
co
n
ten
t
in
p
a
p
er
an
d
o
il
u
n
d
er
th
er
m
al
eq
u
ilib
r
iu
m
.
T
h
e
s
e
cu
r
v
es
f
o
r
m
th
e
b
asis
f
o
r
esti
m
atin
g
th
e
m
o
is
t
u
r
e
co
n
ten
t
in
th
e
s
o
lid
in
s
u
la
tio
n
b
ased
o
n
o
il
m
ea
s
u
r
e
m
en
ts
an
d
tem
p
e
r
atu
r
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
Ma
ch
in
e
lea
r
n
in
g
-
b
a
s
ed
p
r
ed
ictio
n
o
f m
o
is
tu
r
e
a
n
d
o
xy
g
en
in
a
la
r
g
e
p
o
w
er
…
(
Osa
ma
T.
Gh
a
z
a
l
)
3
[
1
4
]
.
T
h
ey
h
av
e
s
in
ce
b
ee
n
r
e
f
in
ed
an
d
v
alid
ate
d
th
r
o
u
g
h
b
o
th
ex
p
e
r
im
en
tal
s
tu
d
ies
an
d
f
ield
m
ea
s
u
r
em
en
ts
[
1
5
]
,
[
1
6
]
.
2
.
4
.
Wa
t
er
s
o
lub
ility
(
S)
a
nd
re
la
t
iv
e
s
a
t
ura
t
i
o
n
(
RS)
W
ater
co
n
ten
t
in
tr
an
s
f
o
r
m
er
o
il
is
ty
p
ically
m
ea
s
u
r
ed
in
p
a
r
ts
p
er
m
illi
o
n
(
p
p
m
)
u
s
in
g
K
ar
l
Fis
ch
er
titra
tio
n
,
f
o
llo
win
g
I
E
C
6
0
8
1
4
o
r
ASTM
D1
5
3
3
s
tan
d
ar
d
s
.
Ho
wev
er
,
th
is
m
eth
o
d
al
o
n
e
d
o
es
n
o
t
ac
c
o
u
n
t
f
o
r
th
e
s
atu
r
atio
n
s
tate
o
f
th
e
o
il
a
t
a
g
iv
en
tem
p
er
atu
r
e.
T
h
er
ef
o
r
e,
r
elativ
e
s
atu
r
atio
n
(
R
S)
an
d
s
o
lu
b
ilit
y
(
S)
ar
e
u
s
ed
to
b
etter
ass
ess
m
o
is
tu
r
e
r
is
k
.
So
lu
b
ilit
y
(
S)
is
d
ef
i
n
ed
as
th
e
m
ax
im
u
m
am
o
u
n
t
o
f
wate
r
t
h
at
ca
n
d
is
s
o
lv
e
in
o
il
at
a
s
p
ec
if
ic
te
m
p
er
atu
r
e
an
d
v
ar
ies
ex
p
o
n
e
n
tially
with
tem
p
er
atu
r
e
[
1
7
]
.
R
elativ
e
s
atu
r
atio
n
(
R
S)
r
ep
r
esen
ts
th
e
p
er
ce
n
ta
g
e
o
f
th
is
s
o
lu
b
ilit
y
th
at
is
cu
r
r
en
tly
o
cc
u
p
ied
b
y
d
is
s
o
lv
ed
m
o
i
s
tu
r
e.
R
S
i
s
a
p
r
ef
er
r
ed
p
ar
am
eter
f
o
r
ev
alu
atin
g
tr
a
n
s
f
o
r
m
er
m
o
is
tu
r
e
co
n
d
itio
n
b
ec
au
s
e
it
n
o
r
m
alize
s
th
e
p
p
m
v
alu
e
ac
r
o
s
s
d
if
f
er
e
n
t
o
il
v
o
lu
m
es
an
d
tr
an
s
f
o
r
m
er
s
izes.
I
t
also
s
h
o
ws
a
s
tr
o
n
g
co
r
r
elatio
n
with
d
ielec
tr
ic
b
r
ea
k
d
o
w
n
s
tr
en
g
th
an
d
is
a
r
eliab
le
m
etr
ic
f
o
r
d
ef
in
in
g
m
o
is
tu
r
e
th
r
esh
o
ld
s
in
co
n
d
itio
n
-
b
ased
m
o
n
ito
r
in
g
s
y
s
tem
s
[
1
7
]
,
[
1
2
]
.
Fu
r
th
e
r
m
o
r
e
,
R
S
is
h
ig
h
l
y
s
en
s
itiv
e
to
tem
p
e
r
atu
r
e
f
lu
c
tu
atio
n
s
,
m
ak
in
g
it
ess
en
tial
to
in
ter
p
r
et
m
o
is
tu
r
e
d
ata
in
co
n
ju
n
ctio
n
with
th
er
m
al
p
r
o
f
iles
.
B
y
co
m
b
in
in
g
R
S
with
d
is
s
o
lv
ed
g
as
an
aly
s
is
(
DGA)
,
a
m
o
r
e
co
m
p
r
eh
en
s
iv
e
p
ictu
r
e
o
f
i
n
s
u
latio
n
h
ea
lth
ca
n
b
e
ac
h
iev
e
d
.
3.
M
ACH
I
N
E
L
E
AR
NUNG
P
RE
DI
CT
I
O
N
M
O
D
E
L
S
3
.
1
.
I
ntr
o
du
ct
io
n
Ma
ch
in
e
lear
n
in
g
(
ML
)
h
as
e
m
er
g
ed
as
a
p
o
wer
f
u
l
d
ata
-
d
r
i
v
en
ap
p
r
o
ac
h
f
o
r
p
r
ed
ictiv
e
m
ain
ten
an
ce
an
d
d
iag
n
o
s
tics
in
elec
tr
ica
l
s
y
s
tem
s
,
in
clu
d
in
g
p
o
wer
tr
an
s
f
o
r
m
er
s
.
Un
lik
e
co
n
v
en
tio
n
al
r
u
le
-
b
ase
d
m
o
d
elin
g
,
ML
alg
o
r
ith
m
s
ca
n
lear
n
co
m
p
lex
r
elatio
n
s
h
ip
s
f
r
o
m
em
p
ir
ical
d
ata
t
h
r
o
u
g
h
ad
ap
tiv
e
p
r
o
ce
s
s
es,
o
f
f
er
in
g
en
h
a
n
ce
d
ac
cu
r
ac
y
i
n
f
o
r
ec
asti
n
g
o
p
er
atio
n
al
co
n
d
itio
n
s
.
ML
f
r
am
ewo
r
k
s
ar
e
b
r
o
ad
ly
ca
te
g
o
r
ized
in
to
s
u
p
er
v
is
ed
,
u
n
s
u
p
e
r
v
is
ed
,
an
d
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
.
I
n
t
h
is
s
t
u
d
y
,
s
u
p
e
r
v
is
e
d
lea
r
n
i
n
g
was e
m
p
l
o
y
e
d
t
o
b
u
il
d
r
e
g
r
ess
i
o
n
m
o
d
e
ls
t
h
a
t p
r
e
d
i
ct
t
wo
c
r
iti
ca
l
i
n
d
ic
at
o
r
s
o
f
tr
an
s
f
o
r
m
e
r
in
s
u
l
ati
o
n
d
e
g
r
a
d
ati
o
n
: m
o
is
t
u
r
e
(
M
)
an
d
d
is
s
o
l
v
e
d
o
x
y
g
e
n
(
O₂
)
.
T
h
e
m
o
d
els
we
r
e
d
e
v
el
o
p
e
d
u
s
in
g
r
e
al
-
ti
m
e
d
ata
c
o
ll
ec
t
e
d
o
v
e
r
a
3
-
y
e
a
r
p
e
r
i
o
d
,
en
co
m
p
ass
i
n
g
4
8
,
0
0
0
+
h
i
g
h
-
f
r
e
q
u
e
n
c
y
o
b
s
er
v
a
ti
o
n
s
.
I
n
p
u
ts
i
n
cl
u
d
e
d
te
m
p
e
r
a
tu
r
e
,
h
y
d
r
o
g
e
n
c
o
n
ce
n
t
r
a
ti
o
n
,
r
el
ati
v
e
s
a
tu
r
ati
o
n
,
a
n
d
s
o
l
u
b
il
i
ty
—
f
e
at
u
r
es s
ele
cte
d
b
ase
d
o
n
p
h
y
s
ic
al
r
el
ev
an
ce
a
n
d
s
tat
is
ti
ca
l
c
o
r
r
ela
ti
o
n
.
3
.
2
.
P
er
f
o
r
m
a
nce
m
e
a
s
urem
ent
s
T
o
ev
alu
ate
t
h
e
p
e
r
f
o
r
m
an
ce
o
f
th
e
p
r
ed
ictiv
e
m
o
d
els,
s
ev
er
al
well
-
estab
lis
h
ed
r
eg
r
ess
io
n
m
etr
ics
wer
e
u
s
ed
:
a.
R
o
o
t
m
ea
n
s
q
u
a
r
ed
e
r
r
o
r
(
R
MSE
)
:
Me
asu
r
es
th
e
s
q
u
ar
e
r
o
o
t
o
f
th
e
a
v
er
ag
e
s
q
u
ar
e
d
p
r
ed
ictio
n
er
r
o
r
s
;
p
en
alize
s
lar
g
e
d
ev
iatio
n
s
.
b.
Me
an
ab
s
o
lu
te
er
r
o
r
(
MA
E
)
:
C
o
m
p
u
tes
th
e
av
er
ag
e
o
f
ab
s
o
lu
te
d
if
f
er
en
ce
s
b
etwe
en
p
r
e
d
icted
an
d
ac
tu
al
v
alu
es; in
ter
p
r
etab
le
a
n
d
less
s
en
s
itiv
e
to
o
u
tlier
s
.
c.
Me
an
s
q
u
ar
ed
e
r
r
o
r
(
MSE
)
: Sq
u
ar
e
o
f
R
MSE
; p
r
o
v
id
es scale
-
d
ep
en
d
en
t e
r
r
o
r
m
a
g
n
itu
d
e
.
d.
C
o
ef
f
icien
t
o
f
d
eter
m
i
n
atio
n
(
R
²)
:
I
n
d
icate
s
th
e
p
r
o
p
o
r
t
io
n
o
f
v
a
r
ian
ce
i
n
th
e
d
e
p
en
d
en
t
v
ar
iab
le
ex
p
lain
ed
b
y
th
e
m
o
d
el.
R
²
v
alu
es
clo
s
e
to
1
r
ef
lect
s
t
r
o
n
g
m
o
d
el
p
er
f
o
r
m
a
n
ce
.
All
m
etr
ics
wer
e
co
m
p
u
ted
u
s
in
g
cr
o
s
s
-
v
alid
atio
n
to
en
s
u
r
e
r
o
b
u
s
tn
ess
an
d
p
r
e
v
en
t
o
v
er
f
itti
n
g
[
1
8
]
–
[
2
0
]
.
3
.
3
.
M
o
del v
a
lid
a
t
io
n
T
o
en
s
u
r
e
r
eliab
ilit
y
an
d
g
en
er
aliza
tio
n
,
two
v
alid
atio
n
tec
h
n
iq
u
es we
r
e
im
p
lem
en
ted
:
a.
Ho
ld
-
o
u
t
v
alid
atio
n
: th
e
d
ataset
was
in
itially
s
p
lit in
to
tr
ain
in
g
(
8
0
%)
an
d
test
in
g
(
2
0
%)
s
e
ts
.
b.
K
-
Fo
ld
cr
o
s
s
-
v
alid
atio
n
:
th
e
t
r
ain
in
g
d
ata
was
f
u
r
th
e
r
ev
al
u
ated
u
s
in
g
5
-
f
o
ld
cr
o
s
s
-
v
alid
a
tio
n
,
wh
er
e
th
e
d
ata
was
d
iv
id
ed
in
to
f
iv
e
s
u
b
s
ets.
T
h
e
m
o
d
el
was
iter
ativ
el
y
tr
ain
ed
o
n
f
o
u
r
s
u
b
s
ets
an
d
v
alid
ated
o
n
th
e
f
if
th
.
T
h
is
p
r
o
ce
s
s
m
itig
ates m
o
d
el
v
ar
ian
ce
an
d
e
n
s
u
r
es c
o
n
s
is
ten
t e
v
alu
atio
n
[
2
1
]
.
All
m
o
d
elin
g
a
n
d
v
alid
atio
n
p
r
o
ce
s
s
es
wer
e
co
n
d
u
cted
u
s
in
g
MA
T
L
AB
’
s
r
eg
r
ess
io
n
lear
n
er
ap
p
,
wh
ic
h
s
u
p
p
o
r
ts
s
tr
ea
m
lin
ed
m
o
d
el
co
m
p
ar
is
o
n
,
h
y
p
er
p
ar
am
eter
t
u
n
in
g
,
an
d
v
is
u
aliza
tio
n
[
2
2
]
.
3
.
4
.
M
a
chine
lea
rning
a
lg
o
ri
t
hm
s
R
eg
r
ess
io
n
an
aly
s
is
i
s
u
s
ed
t
o
in
v
esti
g
ate
th
e
r
elatio
n
s
h
ip
f
u
n
ctio
n
b
etwe
en
v
ar
iab
les,
wh
ich
is
ex
p
r
ess
s
ev
er
al
r
eg
r
ess
io
n
alg
o
r
ith
m
s
wer
e
ev
alu
ated
to
id
e
n
tify
th
e
o
p
tim
al
m
o
d
el
f
o
r
ea
ch
r
esp
o
n
s
e
v
ar
iab
le
(
m
o
is
tu
r
e
an
d
o
x
y
g
en
)
.
T
h
ese
in
clu
d
e:
a.
L
in
ea
r
m
o
d
els
L
in
ea
r
r
eg
r
ess
io
n
(
L
R
)
an
d
its
v
ar
ian
ts
(
in
ter
ac
tio
n
,
r
o
b
u
s
t,
an
d
s
tep
wis
e
lin
ea
r
)
ar
e
in
ter
p
r
etab
le
an
d
co
m
p
u
tatio
n
ally
ef
f
icien
t.
T
h
e
y
m
o
d
el
t
h
e
r
esp
o
n
s
e
as a
lin
ea
r
co
m
b
in
atio
n
o
f
p
r
e
d
icto
r
s
[
2
0
]
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
1
6
,
No
.
1
,
Feb
r
u
ar
y
20
2
6
:
1
-
9
4
ŷ
=
(
1
,
2
,
…
,
)
+
ℇ
(
1
)
wh
er
ea
s
;
ŷ
is
r
esp
o
n
s
e
v
ar
iab
le
,
1
,
2
,
…
,
ar
e
p
r
e
d
icto
r
s
,
an
d
ℇ
is
r
an
d
o
m
er
r
o
r
.
b.
R
eg
r
ess
io
n
tr
ee
s
(
R
T
s
)
Fin
e,
m
ed
iu
m
,
a
n
d
c
o
ar
s
e
d
ec
is
io
n
tr
ee
s
s
p
lit
th
e
d
ataset
b
ased
o
n
p
r
ed
icto
r
th
r
esh
o
ld
s
.
T
h
ese
m
o
d
els ar
e
ea
s
y
to
in
te
r
p
r
et
b
u
t m
ay
o
v
er
f
it sma
ll d
atasets
.
c.
E
n
s
em
b
les o
f
tr
ee
s
(
E
o
T
s
)
B
ag
g
ed
tr
ee
s
an
d
b
o
o
s
ted
tr
ee
s
co
m
b
in
e
m
u
ltip
le
d
ec
is
io
n
tr
ee
s
to
im
p
r
o
v
e
p
r
e
d
ictiv
e
ac
cu
r
ac
y
.
B
ag
g
in
g
r
ed
u
ce
s
v
ar
ian
ce
,
wh
ile
b
o
o
s
tin
g
r
e
d
u
ce
s
b
ias
—
th
o
u
g
h
b
o
th
in
c
r
ea
s
e
co
m
p
u
tatio
n
tim
e.
d.
Su
p
p
o
r
t
v
ec
to
r
m
ac
h
in
es
(
SVMs)
L
in
ea
r
,
p
o
l
y
n
o
m
ial
(
q
u
ad
r
at
ic/cu
b
ic)
,
an
d
Ga
u
s
s
ian
k
er
n
el
SVMs
m
ap
in
p
u
ts
in
to
h
ig
h
er
-
d
im
en
s
io
n
al
s
p
ac
es
to
f
in
d
o
p
tim
al
r
eg
r
ess
io
n
b
o
u
n
d
ar
ies.
W
h
ile
p
o
wer
f
u
l,
SVMs
ar
e
m
o
r
e
co
m
p
u
tatio
n
ally
d
em
an
d
in
g
an
d
s
en
s
itiv
e
to
p
a
r
am
eter
tu
n
in
g
.
e.
Gau
s
s
ian
p
r
o
ce
s
s
r
eg
r
ess
io
n
(
GPR
)
GPR
m
o
d
els
u
s
e
k
er
n
el
-
b
ased
B
ay
esian
lear
n
in
g
to
m
ak
e
p
r
o
b
a
b
ilis
tic
p
r
ed
ictio
n
s
.
De
s
p
ite
th
eir
h
ig
h
ac
c
u
r
ac
y
,
esp
ec
ially
with
lim
ited
n
o
is
y
d
ata,
th
ey
in
cu
r
h
ig
h
c
o
m
p
u
tatio
n
al
co
s
t,
p
ar
t
icu
lar
ly
with
lar
g
e
d
atasets
[
2
2
]
.
4.
CASE
S
T
UD
Y
AND
R
E
SU
L
T
S
4
.
1
.
T
ra
ns
f
o
rm
er
un
der
s
t
u
dy
T
h
is
ca
s
e
s
tu
d
y
f
o
cu
s
es
o
n
th
e
g
en
er
ato
r
s
tep
-
u
p
tr
an
s
f
o
r
m
er
u
n
it
1
(
GSUT
1
)
at
Attar
at
p
o
wer
co
m
p
an
y
(
APC
O)
,
J
o
r
d
an
,
a
n
ewly
co
m
m
is
s
io
n
ed
u
n
it
en
e
r
g
ized
in
J
u
ly
2
0
2
0
.
T
h
e
tr
an
s
f
o
r
m
er
is
r
ated
at
3
4
0
MV
A,
with
a
v
o
ltag
e
r
atin
g
o
f
(
4
2
0
±
8
×
1
.
2
5
%)/2
0
k
V,
an
d
em
p
lo
y
s
a
YNd
1
1
v
ec
to
r
g
r
o
u
p
with
ONAN
/ONA
F
co
o
lin
g
.
I
t
is
f
illed
with
ap
p
r
o
x
im
ately
7
0
,
2
3
0
k
g
o
f
n
a
p
h
th
e
n
ic
-
b
ased
in
s
u
latin
g
o
il
a
n
d
m
an
u
f
ac
tu
r
ed
b
y
T
B
E
A.
De
tailed
tech
n
ical
s
p
ec
if
icatio
n
s
ar
e
p
r
esen
ted
in
T
a
b
le
1
,
p
r
o
v
id
in
g
a
clea
r
o
p
er
atio
n
al
a
n
d
s
tr
u
ctu
r
al
p
r
o
f
ile
o
f
th
e
tr
an
s
f
o
r
m
er
.
T
h
e
GSUT
1
is
eq
u
ip
p
ed
with
an
a
d
v
an
ce
d
o
n
lin
e
m
o
n
ito
r
i
n
g
s
y
s
tem
(
HAOZ
HI
E
L
E
C
T
R
I
C
m
o
d
el
W
-
PD2
M)
as
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
is
d
ev
ice
co
n
tin
u
o
u
s
ly
t
r
ac
k
s
k
ey
f
au
lt
g
ases
an
d
m
o
i
s
tu
r
e
co
n
ten
t
in
th
e
o
il,
in
clu
d
in
g
:
Hy
d
r
o
g
e
n
(
H₂)
,
C
ar
b
o
n
Mo
n
o
x
id
e
(
C
O)
,
Me
th
an
e
(
C
H₄)
,
Ace
ty
len
e
(
C
₂H₂
)
,
E
th
y
len
e
(
C
₂H₄
)
,
E
th
an
e
(
C
₂H₆
)
,
C
ar
b
o
n
Dio
x
id
e
(
C
O₂)
,
an
d
Ox
y
g
en
(
O₂)
.
I
t
also
m
o
n
ito
r
s
o
il
tem
p
e
r
atu
r
e
an
d
r
elativ
e
h
u
m
id
ity
.
I
ts
co
m
p
ac
t
s
ize,
lo
w
co
s
t,
an
d
h
ig
h
d
ata
r
eso
lu
ti
o
n
m
a
k
e
it
well
-
s
u
ited
f
o
r
p
r
e
d
ictiv
e
m
ain
ten
an
ce
ap
p
licatio
n
s
.
T
ab
le
1
.
Un
it1
GSUT
tech
n
ical
d
ata
R
a
t
e
d
P
o
w
e
r
3
4
0
M
V
A
V
o
l
t
a
g
e
R
a
t
i
n
g
(
4
2
0
±
8
×
1
.
2
5
%)/
2
0
k
V
V
e
c
t
o
r
G
r
o
u
p
Y
N
d
1
1
R
a
t
e
d
F
r
e
q
u
e
n
c
y
5
0
H
z
C
o
o
l
i
n
g
M
o
d
e
O
N
A
N
/
O
N
A
F
(
6
2
/
1
0
0
%)
M
a
n
u
f
a
c
t
u
r
e
TB
EA
I
n
su
l
a
t
i
o
n
o
i
l
mass
7
0
2
3
0
k
g
O
i
l
B
a
s
e
N
a
p
h
t
h
e
n
i
c
(
a)
(
b
)
Fig
u
r
e
1
.
AT
T
AR
AT
p
o
wer
p
lan
t
(
a)
u
n
it g
en
er
ato
r
s
tep
-
u
p
tr
an
s
f
o
r
m
er
GSUT
an
d
(
b
)
o
n
l
in
e
k
ey
f
a
u
lt g
as
an
d
m
o
is
tu
r
e
m
o
n
ito
r
i
n
g
d
e
v
i
ce
Evaluation Warning : The document was created with Spire.PDF for Python.
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8
7
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ch
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e
lea
r
n
in
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a
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ed
p
r
ed
ictio
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o
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n
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en
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a
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Osa
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T.
Gh
a
z
a
l
)
5
4
.
2
.
DG
A
a
nd
m
o
is
t
ure
m
o
n
it
o
ring
dev
ice
T
h
e
m
o
n
ito
r
in
g
d
ev
ice
ca
p
tu
r
es
r
ea
d
in
g
s
e
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er
y
3
0
m
in
u
te
s
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en
er
atin
g
o
v
e
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0
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o
b
s
er
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atio
n
s
s
p
an
n
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f
r
o
m
J
u
ly
2
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2
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to
Au
g
u
s
t
2
0
2
3
.
R
aw
p
ar
am
e
ter
s
in
clu
d
e:
d
is
s
o
lv
ed
o
x
y
g
en
(
O₂)
,
d
is
s
o
lv
ed
h
y
d
r
o
g
en
(
H₂)
,
m
o
is
tu
r
e
(
M)
,
an
d
o
il tem
p
e
r
atu
r
e
(
OT
)
.
T
o
en
h
a
n
ce
th
e
f
ea
t
u
r
e
s
et,
two
d
er
iv
e
d
v
ar
ia
b
les we
r
e
ca
lcu
lated
:
a.
S
o
l
u
b
i
l
it
y
(
S
)
[
p
p
m
]
:
T
h
e
m
a
x
i
m
u
m
w
a
t
e
r
s
o
l
u
b
i
l
it
y
i
n
o
i
l
a
t
a
g
i
v
e
n
t
e
m
p
e
r
a
t
u
r
e
,
c
a
l
c
u
l
a
t
e
d
u
s
i
n
g
e
m
p
i
r
i
c
al
t
e
m
p
e
r
a
t
u
r
e
-
s
o
l
u
b
il
i
t
y
r
el
a
t
i
o
n
s
[
1
7
]
.
b.
R
elativ
e
s
atu
r
atio
n
(
R
S)
[
%]:
I
n
d
icate
s
m
o
is
tu
r
e
lev
el
as
a
f
r
ac
tio
n
o
f
s
atu
r
atio
n
,
p
r
o
v
id
in
g
tem
p
e
r
atu
r
e
-
n
o
r
m
alize
d
in
s
ig
h
t.
T
h
ese
f
ea
tu
r
es
o
f
f
er
a
d
ee
p
er
r
ep
r
esen
tatio
n
o
f
tr
a
n
s
f
o
r
m
er
in
ter
n
al
co
n
d
itio
n
s
an
d
wer
e
in
teg
r
ated
as
p
r
ed
icto
r
s
in
th
e
ML
m
o
d
el.
4
.
3
.
O
bs
er
v
a
t
io
ns
s
t
a
t
is
t
ica
l a
na
ly
s
is
B
asic
s
tatis
t
ical
d
escr
ip
to
r
s
f
o
r
th
e
m
o
n
ito
r
e
d
v
a
r
iab
les
ar
e
s
u
m
m
ar
ized
i
n
T
ab
le
2
,
in
clu
d
in
g
m
in
im
u
m
,
m
e
d
ian
,
m
a
x
im
u
m
,
an
d
p
e
r
ce
n
tag
e
o
f
o
u
tlier
v
alu
es.
Key
o
b
s
er
v
atio
n
s
:
a.
Mo
is
tu
r
e
(
M)
ex
h
i
b
ited
a
n
a
r
r
o
w
o
p
er
atio
n
al
r
an
g
e
(
4
.
8
8
to
1
2
.
6
p
p
m
)
,
with
m
in
im
al
o
u
tlier
s
(
0
.
6
5
%).
b.
So
lu
b
ilit
y
(
S)
an
d
o
il tem
p
er
at
u
r
e
(
OT
)
s
h
o
wed
wid
e
v
a
r
iab
i
lity
,
r
ef
lectin
g
f
lu
ctu
atin
g
en
v
i
r
o
n
m
en
tal/lo
ad
co
n
d
itio
n
s
.
c.
R
e
l
at
i
v
e
s
a
t
u
r
a
ti
o
n
(
R
S
)
d
i
s
p
l
ay
e
d
h
i
g
h
s
t
a
b
i
li
t
y
a
n
d
c
o
n
s
is
t
en
c
y
,
s
u
g
g
e
s
t
i
n
g
e
f
f
e
ct
i
v
e
m
o
is
tu
r
e
e
q
u
i
l
i
b
r
i
u
m
.
d.
Ox
y
g
en
(
O₂)
r
an
g
ed
s
ig
n
if
ica
n
tly
(
5
1
4
.
6
to
1
0
2
3
.
8
p
p
m
)
with
h
ig
h
e
r
o
u
tlier
p
r
esen
ce
(
2
4
%).
T
h
is
s
tatis
tical
f
o
u
n
d
atio
n
s
u
p
p
o
r
ts
th
e
d
ev
el
o
p
m
en
t
o
f
r
o
b
u
s
t
p
r
ed
ictiv
e
m
o
d
els
an
d
h
ig
h
l
ig
h
ts
k
ey
d
y
n
am
ic
p
ar
am
eter
s
.
T
ab
le
2
.
Un
it1
GSUT
d
ata
s
tat
is
tical
s
u
m
m
ar
y
M
i
n
M
e
d
i
a
n
M
a
x
O
u
t
l
i
e
r
s
[
%]
H
2
[
p
p
m]
0
.
1
1
.
4
1
1
.
3
2
5
.
7
O
2
[
p
p
m]
5
1
4
.
6
4
6
3
5
.
1
2
1
0
2
3
.
8
24
M
[
p
p
m]
4
.
8
8
7
.
6
6
1
2
.
6
0
.
6
5
O
T
[
°
C
]
2
4
.
4
8
3
0
.
2
7
4
8
.
7
4
25
S
[
p
p
m]
6
6
.
3
6
2
8
3
.
6
5
4
1
6
5
.
6
2
2
4
.
6
R
S
[
%]
6
.
3
9
9
9
8
.
4
6
5
1
0
.
6
6
9
0
4
.
4
.
O
bs
er
v
a
t
io
ns
co
rr
ela
t
io
n a
nd
m
o
is
t
ure
equil
ibr
ium
T
o
i
d
e
n
ti
f
y
in
te
r
d
e
p
e
n
d
e
n
ci
es
am
o
n
g
p
a
r
a
m
et
er
s
,
a
P
ea
r
s
o
n
c
o
r
r
elat
io
n
m
at
r
i
x
w
as
g
e
n
er
ate
d
T
a
b
l
e
3
.
No
tab
le
f
in
d
in
g
s
:
a.
Ox
y
g
en
(
O₂)
ex
h
i
b
ited
s
tr
o
n
g
p
o
s
itiv
e
co
r
r
elatio
n
s
with
m
o
is
tu
r
e
(
r
=
0
.
7
7
2
)
,
tem
p
e
r
atu
r
e
(
r
=
0
.
9
9
9
)
,
an
d
s
o
lu
b
ilit
y
(
r
=
0
.
9
9
6
)
.
b.
Mo
is
tu
r
e
(
M)
co
r
r
elate
d
m
o
d
e
r
ately
with
o
il
tem
p
er
atu
r
e
(
r
=
0
.
7
4
6
)
an
d
s
o
lu
b
ilit
y
(
r
=
0
.
7
4
4
)
,
s
u
g
g
esti
n
g
a
th
er
m
al
co
u
p
lin
g
ef
f
ec
t.
c.
Hy
d
r
o
g
e
n
(
H₂)
h
ad
m
o
d
est
co
r
r
elatio
n
s
with
o
th
e
r
v
ar
ia
b
les,
r
ef
lectin
g
its
p
o
s
s
ib
le
g
en
er
atio
n
f
r
o
m
s
ep
ar
ate
f
au
lt m
ec
h
a
n
is
m
s
.
d.
R
elativ
e
s
atu
r
atio
n
(
R
S)
s
h
o
wed
wea
k
n
eg
ativ
e
co
r
r
elatio
n
s
with
all
o
th
er
p
ar
a
m
eter
s
,
p
ar
ticu
lar
ly
with
tem
p
er
atu
r
e
a
n
d
s
o
lu
b
ilit
y
,
co
n
s
is
ten
t w
ith
m
o
is
tu
r
e
eq
u
ilib
r
iu
m
b
eh
a
v
io
r
.
T
o
f
u
r
th
er
in
v
esti
g
ate
m
o
is
tu
r
e
b
alan
ce
in
t
h
e
o
il
–
p
ap
er
in
s
u
latio
n
s
y
s
tem
,
v
alu
es
wer
e
p
r
o
jecte
d
o
n
Oo
m
m
en
’
s
eq
u
ilib
r
iu
m
cu
r
v
e
f
o
r
lo
w
-
m
o
is
tu
r
e
r
e
g
io
n
s
Fig
u
r
e
2
.
T
h
is
illu
s
tr
ates
h
o
w
m
o
is
tu
r
e
c
o
n
ten
t
f
o
llo
ws
p
r
ed
ictab
le
th
er
m
al
d
y
n
am
ics
b
ased
o
n
eq
u
ilib
r
i
u
m
th
eo
r
y
[
2
3
]
,
[
2
4
]
.
T
h
e
c
u
r
v
e
r
ein
f
o
r
ce
s
th
e
in
ter
p
r
etatio
n
th
at
in
cr
ea
s
ed
tem
p
er
atu
r
e
d
r
i
v
es
m
o
is
tu
r
e
in
to
th
e
o
il
p
h
ase,
wh
ich
is
th
e
n
ca
p
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I
n
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C
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p
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n
g
I
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N:
2088
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[
1
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S
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3
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.
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8
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[
9
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0
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l
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o
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4
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4
4
5
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5
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[
1
5
]
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I
G
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E
,
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I
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E,
n
o
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9
,
2
0
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[
1
6
]
S
.
T
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.
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o
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1
7
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L.
R
.
L
e
w
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,
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[
1
8
]
J.
B
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o
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c
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a
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y
,
2
0
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6
.
[
1
9
]
T.
C
h
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a
n
d
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.
R
.
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0
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.
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.
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.
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o
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.
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2
2
]
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a
t
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,
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s:
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[
2
3
]
O
.
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.
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[
2
4
]
B
.
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a
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J.
C
.
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.
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jo
.
Evaluation Warning : The document was created with Spire.PDF for Python.