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ar
k
et,
in
clu
d
in
g
th
e
PEN3
e
-
n
o
s
e,
alp
h
a
m
etal
o
x
id
e
s
em
ico
n
d
u
cto
r
(
MO
S)
FOX
s
er
ies
[
3
]
,
[
4
]
,
an
d
ai
r
s
en
s
e
co
m
p
ac
t
e
-
n
o
s
e
[
5
]
.
T
h
ese
s
y
s
tem
s
co
m
m
o
n
ly
u
s
e
MO
S
s
en
s
o
r
ar
r
ay
s
o
r
co
n
d
u
c
tiv
e
p
o
ly
m
er
s
en
s
o
r
s
co
m
b
in
e
d
with
m
ac
h
in
e
lear
n
in
g
(
ML
)
alg
o
r
ith
m
s
f
o
r
th
e
class
if
icatio
n
o
f
o
d
o
r
s
.
B
u
t th
e
y
ar
e
m
o
s
tly
b
u
ilt f
o
r
e
x
p
en
s
iv
e
lab
u
s
e
an
d
with
m
u
ltip
le
ca
v
ea
ts
.
C
o
m
m
er
cial
m
o
d
els
co
s
t
b
etwe
en
I
NR
5
-
1
0
lak
h
s
,
wh
ich
s
m
all
-
s
ca
le
I
n
d
ian
f
ar
m
e
r
s
an
d
v
e
n
d
o
r
s
ca
n
’
t
af
f
o
r
d
.
Mo
s
t
s
y
s
tem
s
ar
e
n
o
t
p
o
r
tab
le
a
n
d
ca
n
o
n
l
y
b
e
u
s
ed
in
s
id
e
a
n
en
v
ir
o
n
m
e
n
t.
R
eq
u
ir
es
ca
lib
r
ati
o
n
an
d
o
p
er
atio
n
b
y
h
ig
h
ly
e
d
u
ca
ted
p
er
s
o
n
n
el,
th
u
s
lim
itin
g
f
ield
ap
p
licatio
n
,
a
n
d
h
as lim
ited
cu
s
to
m
izatio
n
.
T
h
e
r
ec
en
t
s
t
u
d
ies in
th
e
f
ie
ld
o
f
i
n
tel
li
g
e
n
t a
g
r
i
c
u
lt
u
r
e
t
en
d
t
o
u
til
ize
t
h
e
co
n
c
e
p
t o
f
I
o
T
,
s
e
n
s
o
r
s
,
a
n
d
d
e
ep
l
ea
r
n
i
n
g
t
o
e
n
h
a
n
c
e
t
h
e
ab
i
lit
y
t
o
m
o
n
it
o
r
th
e
q
u
a
lit
y
o
f
f
r
u
its
a
n
d
p
r
e
d
i
ct
t
h
ei
r
r
ip
e
n
ess
.
T
h
e
i
n
t
elli
g
en
t
f
r
u
i
t
q
u
alit
y
m
o
n
i
to
r
i
n
g
s
y
s
te
m
[
6
]
i
n
te
g
r
at
es
s
e
n
s
o
r
n
etw
o
r
k
a
n
d
d
ee
p
le
ar
n
i
n
g
t
o
m
o
n
i
t
o
r
th
e
f
r
esh
n
ess
a
n
d
q
u
ali
ty
o
f
f
r
u
its
i
n
r
e
al
-
ti
m
e
,
wit
h
a
f
o
cu
s
o
n
t
h
e
u
s
e
o
f
te
m
p
er
at
u
r
e
a
n
d
g
ase
o
u
s
s
e
n
s
o
r
s
a
n
d
C
N
N
-
b
ase
d
class
i
f
i
ca
t
io
n
i
n
s
tr
u
ct
u
r
e
o
f
t
h
e
q
u
ali
ty
c
o
n
t
r
o
l
o
f
d
if
f
e
r
e
n
t
f
r
u
i
ts
.
Ac
c
o
r
d
i
n
g
to
T
h
a
k
u
r
a
n
d
K
h
an
[
7
]
,
th
e
p
r
o
to
ty
p
e
h
as
g
as
s
en
s
o
r
s
(
M
Q3
,
MQ
7
)
an
d
ML
to
id
en
tif
y
f
r
esh
a
n
d
r
o
tten
f
r
u
it
with
a
h
ig
h
ac
c
u
r
ac
y
,
an
d
th
e
em
p
h
asis
is
p
lace
d
o
n
lo
w
-
co
s
t
s
p
o
ilag
e
m
o
n
ito
r
in
g
.
Ac
co
r
d
in
g
to
Hass
an
et
a
l.
[
8
]
,
s
u
s
tain
ab
le
d
ate
f
r
u
it
q
u
ality
an
aly
s
is
is
ac
h
iev
ed
th
r
o
u
g
h
atten
tio
n
-
e
n
h
an
ce
d
d
e
ep
lear
n
in
g
m
o
d
els,
wh
ich
p
r
o
m
o
te
im
ag
e
-
b
ased
d
ate
f
r
u
it
r
ip
en
ess
m
o
d
els.
Al
s
o
,
C
NN
-
b
ased
ar
tific
ially
r
ip
en
ed
m
a
n
g
o
f
r
u
it
p
r
e
d
ictio
n
s
y
s
tem
s
ex
h
ib
it
g
o
o
d
p
er
f
o
r
m
an
ce
i
n
th
e
class
if
icat
io
n
o
f
r
ip
e
n
ess
lev
els
o
f
f
r
u
it
b
ased
o
n
v
is
u
al
o
r
v
o
latile
s
ig
n
al
an
d
th
er
e
f
o
r
e
s
u
p
p
o
r
t th
e
u
s
ef
u
ln
ess
o
f
d
ee
p
lear
n
in
g
m
o
d
els in
p
r
ed
ictin
g
f
r
u
it r
ip
en
ess
an
d
f
r
u
it saf
ety
with
o
u
t th
e
n
ee
d
to
b
e
d
estru
ctiv
e
[
9
]
,
[
1
0
]
.
T
ab
l
e
1
g
iv
es
a
co
m
p
ar
ativ
e
s
u
m
m
ar
y
o
f
th
e
r
ec
en
t
I
o
T
,
s
en
s
o
r
s
,
an
d
ML
-
b
ased
s
o
lu
tio
n
s
to
th
e
ass
e
s
s
m
en
t
o
f
f
r
u
it
q
u
ality
,
p
r
ec
is
e
ag
r
icu
ltu
r
e,
an
d
b
io
s
en
s
in
g
.
I
t
co
m
p
ar
es
d
o
m
ain
s
o
f
ap
p
licatio
n
,
s
en
s
o
r
m
o
d
alities
,
alg
o
r
ith
m
s
,
d
atasets
an
d
r
es
u
lts
o
f
d
if
f
er
en
t
s
tu
d
ies.
T
h
e
co
m
p
ar
is
o
n
s
h
o
ws
th
e
p
er
f
o
r
m
an
ce
im
p
r
o
v
em
en
t
g
ain
ed
with
th
e
h
elp
o
f
d
ata
-
d
r
iv
en
ap
p
r
o
ac
h
es
an
d
d
em
o
n
s
tr
ates
th
e
ty
p
ical
d
r
awb
ac
k
s
ass
o
ciate
d
with
th
e
s
ize
o
f
th
e
d
ataset,
cr
o
p
s
p
ec
if
icity
,
s
ca
lab
ilit
y
an
d
th
e
ap
p
licatio
n
to
r
ea
l
-
wo
r
ld
task
s
.
T
ab
le
1
.
C
o
m
p
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r
ativ
e
s
tu
d
y
o
f
s
en
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o
r
an
d
ML
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ased
ap
p
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h
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f
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(
Y
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r
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p
p
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t
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r
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l
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t
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/
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t
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set
u
p
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e
y
o
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t
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m
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s
Li
mi
t
a
t
i
o
n
s
G
r
z
y
w
a
c
z
e
t
a
l
.
[
1
1
]
,
2
0
2
5
F
r
u
i
t
sp
o
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l
a
g
e
mo
n
i
t
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r
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S
t
r
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r
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R
a
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M
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-
n
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o
v
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d
M
L
c
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b
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o
sm
e
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[
1
2
]
,
2
0
2
5
D
i
g
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t
a
l
sen
s
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V
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/
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V
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A
N
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DL
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e
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t
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V
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[
1
3
]
,
2
0
2
5
F
r
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p
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Te
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h
u
m
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g
a
s
sen
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s (ES
P
3
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)
C
a
t
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t
,
R
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Th
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d
S
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[
1
4
]
,
2
0
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P
r
e
c
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s
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o
n
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r
r
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g
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D
u
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(9
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t
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s)
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o
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R
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.
[
1
5
]
,
2
0
2
4
S
m
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[
1
6
]
,
2
0
2
4
B
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se
n
s
o
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s
&
d
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[
2
1
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,
[
2
2
]
.
Mo
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h
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[
2
3
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[
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4
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.
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ased
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[
2
5
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.
1
.
Circ
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wh
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1
7
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[
1
9
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.
T
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Ar
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s
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d
ar
d
MQ
s
en
s
o
r
'
s
o
u
tp
u
t
v
o
ltag
e
V
o
ut
is
m
ea
s
u
r
ed
an
d
s
en
s
o
r
r
esis
tan
ce
R
s
ch
an
g
es a
s
(
1
)
a
n
d
(
2
)
,
r
esp
ec
tiv
ely
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
5
2
-
8
9
3
8
I
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t J Ar
tif
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n
tell
,
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
26
:
2
1
1
3
-
2
1
2
4
2116
V
o
ut
=
V
cc
×
R
L
R
L
+
R
s
(
1
)
R
s
=
R
0
×
(
P
g
as
P
0
)
−
α
(
2
)
W
h
er
e
in
(
1
)
,
V
cc
is
s
u
p
p
ly
v
o
ltag
e,
R
L
is
lo
ad
r
esis
tan
ce
,
an
d
R
s
is
s
en
s
o
r
r
esis
tan
ce
,
wh
ich
v
ar
i
es
with
g
as
co
n
ce
n
tr
atio
n
.
I
n
(
2
)
,
R
0
is
r
esis
tan
ce
to
clea
n
air
,
P
g
as
is
g
as
co
n
ce
n
tr
atio
n
,
P
0
is
r
ef
er
e
n
ce
co
n
ce
n
tr
atio
n
,
an
d
α
is
g
as
s
p
ec
if
ic
s
en
s
itiv
ity
f
a
cto
r
.
T
o
ca
lcu
late
th
e
av
er
ag
e
s
en
s
o
r
r
ea
d
in
g
o
v
er
‘
n
’
in
t
er
v
als
(
e.
g
.
,
o
v
er
3
m
in
u
tes with
r
ea
d
i
n
g
s
ev
er
y
1
0
s
)
as (
3
)
.
A
ve
r
a
ge
s
e
n
s
o
r
=
1
n
∑
Se
n
s
or
i
n
i
=
1
(
3
)
2
.
2
.
P
CB
la
y
o
ut
a
nd
pro
t
o
t
y
pin
g
T
h
is
s
u
b
s
ec
tio
n
d
escr
ib
es
th
e
PC
B
d
esig
n
s
tr
ateg
y
,
f
ab
r
icatio
n
wo
r
k
f
l
o
w,
an
d
s
tr
u
ctu
r
al
i
n
teg
r
atio
n
o
f
s
en
s
o
r
s
an
d
m
icr
o
co
n
tr
o
l
ler
in
to
a
co
m
p
ac
t
d
o
u
b
le
-
s
id
ed
b
o
ar
d
.
Af
ter
v
alid
atin
g
th
e
cir
cu
it
o
n
a
b
r
ea
d
b
o
ar
d
,
we
d
esig
n
e
d
a
c
o
m
p
ac
t
d
o
u
b
le
-
s
id
ed
PC
B
.
T
h
e
d
esig
n
o
p
tim
ized
tr
ac
e
len
g
th
s
an
d
m
i
n
im
ized
n
o
is
e
in
ter
f
er
e
n
ce
.
Ger
b
er
f
iles
wer
e
g
en
er
ate
d
f
o
r
p
r
o
f
ess
io
n
al
f
ab
r
icatio
n
,
a
n
d
t
h
e
lay
o
u
t
was
v
is
u
alize
d
in
3
D
to
en
s
u
r
e
co
m
p
atib
ilit
y
wi
th
th
e
en
clo
s
u
r
e.
T
h
is
3
D
v
ie
w
o
f
th
e
f
in
al
e
-
n
o
s
e
h
ar
d
war
e
d
esig
n
.
I
t
f
ea
tu
r
es
MQ
-
3
an
d
MQ
-
1
3
5
g
as
s
e
n
s
o
r
s
f
o
r
d
etec
tin
g
eth
y
len
e
an
d
o
th
e
r
g
ases
r
elate
d
to
f
r
u
it
r
ip
e
n
in
g
.
An
E
SP
3
2
-
W
R
OOM
-
3
2
m
icr
o
co
n
tr
o
ller
th
at
p
r
o
ce
s
s
es
s
en
s
o
r
d
ata
an
d
c
o
n
n
ec
ts
to
th
e
m
o
b
ile
ap
p
.
A
s
m
ar
tp
h
o
n
e
d
is
p
lay
o
r
OL
E
D
d
is
p
lay
f
o
r
s
h
o
win
g
r
ea
l
-
tim
e
r
ea
d
in
g
s
an
d
r
esu
lts
d
ir
e
ctly
o
n
th
e
AI
-
B
o
t.
A
b
u
zz
er
an
d
m
in
i
c
o
o
lin
g
f
an
f
o
r
aler
t
f
ee
d
b
ac
k
a
n
d
air
f
lo
w
co
n
tr
o
l.
T
h
is
co
m
p
ac
t
PC
B
-
b
ased
d
esig
n
in
teg
r
ates a
ll c
o
m
p
o
n
en
ts
n
ec
ess
ar
y
f
o
r
r
ip
e
n
ess
d
etec
tio
n
i
n
a
p
o
r
tab
le
u
n
it.
2
.
3
.
M
o
bil
e
a
pp
lica
t
io
n inte
g
ra
t
io
n
T
h
is
s
u
b
s
ec
tio
n
ex
p
lain
s
th
e
s
o
f
twar
e
d
esig
n
an
d
co
m
m
u
n
icatio
n
lo
g
ic
im
p
lem
en
ted
in
th
e
m
o
b
ile
ap
p
licatio
n
to
in
ter
f
ac
e
with
th
e
E
SP
3
2
b
ased
e
-
n
o
s
e
AI
-
B
o
t.
T
h
e
m
o
b
ile
ap
p
was d
ev
elo
p
ed
u
s
in
g
Flu
tter
f
o
r
cr
o
s
s
-
p
latf
o
r
m
d
ep
l
o
y
m
en
t.
I
t
co
n
n
ec
ts
to
th
e
e
-
n
o
s
e
AI
-
B
o
t
o
v
er
B
lu
eto
o
th
o
r
W
i
-
Fi
(
v
ia
E
SP
3
2
)
an
d
p
er
f
o
r
m
s
f
u
n
ctio
n
s
lik
e
r
ec
eiv
in
g
s
en
s
o
r
r
ea
d
in
g
s
in
r
ea
l
-
tim
e,
d
is
p
lay
in
g
liv
e
d
ata
f
r
o
m
MQ
-
1
3
5
an
d
MQ
-
3
g
as
s
en
s
o
r
s
,
class
if
y
in
g
th
e
f
r
u
it
as
n
atu
r
ally
r
ip
e
n
ed
o
r
ar
tific
ially
r
ip
en
e
d
u
s
in
g
p
r
eset
th
r
esh
o
ld
l
o
g
ic,
l
o
g
h
is
to
r
y
o
f
test
s
with
tim
e,
d
ate
,
an
d
s
en
s
o
r
v
alu
es a
n
d
v
is
u
al
aler
ts
an
d
b
u
zz
er
s
f
o
r
a
b
n
o
r
m
al
r
ea
d
in
g
s
.
Fig
u
r
e
2
s
h
o
ws
a
m
o
b
ile
ap
p
l
icatio
n
in
ter
f
ac
e
f
o
r
th
e
e
-
n
o
s
e
s
y
s
tem
th
at
d
etec
ts
ar
tific
ial
ly
r
ip
en
ed
f
r
u
its
.
T
h
e
u
s
er
s
tar
ts
th
e
s
c
an
b
y
p
r
ess
in
g
“
S
tar
t
s
ca
n
”
,
wh
ich
co
n
n
ec
ts
th
e
ap
p
to
th
e
e
-
n
o
s
e
AI
-
B
o
t.
R
ea
l
-
tim
e
g
as
s
en
s
o
r
r
ea
d
i
n
g
s
(
MQ
-
3
,
MQ
-
4
,
MQ
-
1
3
5
)
a
r
e
d
is
p
lay
ed
alo
n
g
s
id
e
a
g
r
ap
h
s
h
o
win
g
g
as
t
r
en
d
s
u
s
in
g
a
liv
e
d
ata
s
cr
ee
n
.
T
h
e
ap
p
p
r
o
ce
s
s
es
th
e
d
ata
an
d
cl
ass
if
ies
th
e
f
r
u
it
as
“
Ar
tific
ially
r
ip
en
e
d
”
with
a
co
n
f
id
en
ce
lev
el.
T
h
e
h
is
to
r
y
s
cr
ee
n
s
h
o
ws
th
e
lo
g
o
f
p
ast
test
r
esu
lts
wi
th
tim
e,
r
ip
en
ess
class
if
icatio
n
,
an
d
s
tatu
s
f
o
r
u
s
er
r
ef
e
r
en
ce
.
T
h
e
ap
p
in
te
r
f
ac
e
is
b
u
ilt
with
a
u
s
er
-
f
r
ien
d
ly
lig
h
t
th
em
e
an
d
ico
n
-
d
r
iv
e
n
m
e
n
u
s
f
o
r
ea
s
y
n
av
ig
atio
n
,
s
u
itab
le
f
o
r
f
ar
m
er
s
an
d
f
ield
o
p
e
r
ato
r
s
.
T
h
e
ML
m
o
d
el
i
n
to
th
e
m
o
b
ile
ap
p
licatio
n
was
u
s
ed
to
i
n
cr
ea
s
e
th
e
ex
ac
tn
ess
o
f
f
r
u
i
t
r
ip
en
ess
class
if
icatio
n
b
ased
o
n
th
e
h
i
s
to
r
ical
d
ata
f
r
o
m
s
en
s
o
r
s
eq
u
ip
p
ed
in
th
e
m
o
b
ile
ap
p
licat
io
n
with
tim
estam
p
.
Sen
s
o
r
r
ea
d
o
u
ts
o
f
MQ
-
3
an
d
MQ
-
1
3
5
co
n
ce
n
tr
atio
n
s
o
f
al
co
h
o
l
an
d
VOC,
r
esp
ec
tiv
ely
,
wer
e
lo
g
g
ed
an
d
lab
eled
th
r
o
u
g
h
o
u
t
d
if
f
e
r
en
t
s
tag
es
o
f
r
ip
en
ess
lev
els
(
u
n
r
ip
e,
r
ip
e,
o
v
e
r
r
i
p
e,
a
n
d
a
r
tific
ially
r
ip
en
e
d
)
.
E
ac
h
lo
g
en
tr
y
h
ad
s
en
s
o
r
v
al
u
es
an
d
th
eir
co
r
r
esp
o
n
d
in
g
tim
est
am
p
s
.
No
is
e
r
ed
u
ctio
n
b
y
m
o
v
in
g
av
er
a
g
e
f
ilter
was
p
r
o
ce
s
s
ed
to
s
tr
aig
h
ten
th
e
f
lu
ctu
atio
n
s
d
u
e
to
en
v
ir
o
n
m
en
tal
in
ter
f
er
en
ce
d
u
r
in
g
p
r
ep
r
o
ce
s
s
in
g
o
f
d
ata.
Fro
m
th
e
ab
o
v
e
-
clea
n
e
d
s
ig
n
als,
a
s
et
o
f
s
tatis
tical
an
d
t
em
p
o
r
al
f
ea
tu
r
es
was
ex
tr
ac
ted
.
T
h
ey
wer
e,
f
o
r
in
s
tan
ce
,
m
ea
n
co
n
ce
n
tr
atio
n
lev
els,
p
ea
k
v
alu
es,
v
ar
ian
ce
,
an
d
s
ig
n
al
s
lo
p
e
(
r
ate
o
f
ch
an
g
e)
,
as
well
as
th
e
tim
e
o
f
p
ea
k
em
is
s
io
n
.
Als
o
,
t
h
e
tem
p
o
r
al
d
ata
wer
e
an
aly
z
ed
o
n
a
v
er
y
s
h
o
r
t
tim
e
win
d
o
w,
i.e
.
3
0
s
ec
o
n
d
s
,
f
o
r
d
y
n
am
ic
tr
e
n
d
s
s
o
th
at
th
e
m
o
d
el
co
u
ld
d
if
f
er
en
tiate
b
etwe
en
n
atu
r
ally
r
i
p
en
in
g
an
d
ar
tific
ially
r
ip
en
ed
f
r
u
its
b
ased
u
p
o
n
th
e
em
is
s
io
n
tr
e
n
d
s
o
v
er
tim
e.
Su
p
er
v
i
s
ed
lear
n
in
g
with
th
e
u
s
e
o
f
th
e
d
ec
is
io
n
tr
ee
class
if
ier
was
ch
o
s
en
to
b
e
im
p
lem
en
ted
b
ec
a
u
s
e
o
f
its
r
ea
d
ab
ilit
y
an
d
ef
f
icien
cy
o
n
th
e
e
m
b
ed
d
e
d
s
y
s
tem
s
.
T
h
e
r
esp
ec
tiv
e
en
tr
y
o
f
ea
c
h
d
ataset
was
p
r
o
v
id
ed
with
r
ip
en
ess
s
tag
es
a
s
g
r
o
u
n
d
t
r
u
th
b
y
v
is
u
al
in
s
p
ec
tio
n
an
d
test
in
g
f
o
r
f
ir
m
n
ess
.
Fea
tu
r
e
s
elec
tio
n
was
d
o
n
e
th
r
o
u
g
h
c
o
r
r
elatio
n
to
r
em
o
v
e
ir
r
elev
an
t
in
p
u
ts
an
d
g
en
er
alize
th
e
m
o
d
el.
T
h
is
d
at
aset
was
f
ir
s
t
p
r
ep
r
o
ce
s
s
ed
to
ex
tr
ac
t
u
s
ef
u
l
f
ea
tu
r
es
s
u
ch
as
m
ag
n
itu
d
e,
r
ate
o
f
ch
an
g
e
a
n
d
tem
p
o
r
al
p
atter
n
s
.
T
h
e
m
o
d
el
was
tr
ain
e
d
o
f
f
li
n
e
an
d
th
e
n
in
te
g
r
ated
in
to
t
h
e
Flu
tter
-
b
ased
m
o
b
ile
ap
p
l
icatio
n
f
o
r
on
-
d
e
v
ice
in
f
er
e
n
ce
to
b
e
p
er
f
o
r
m
ed
i
n
r
ea
l
-
tim
e
o
n
th
e
d
e
v
ice
with
o
u
t
o
th
er
ex
ter
n
al
cl
o
u
d
co
n
n
ec
tiv
ity
o
r
in
ter
v
en
tio
n
.
On
g
ettin
g
a
s
en
s
o
r
r
ea
d
in
g
f
r
o
m
th
e
Ar
d
u
in
o
-
E
SP
3
2
co
n
f
i
g
u
r
atio
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,
th
e
a
p
p
tak
es
in
th
e
in
p
u
t,
u
tili
ze
s
th
e
tr
ain
ed
m
o
d
el
an
d
s
h
o
ws
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e
p
r
ed
icted
r
ip
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ess
lev
el
in
ad
d
itio
n
to
its
tim
estam
p
.
A
d
ec
is
io
n
tr
ee
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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SS
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2252
-
8
9
3
8
A
s
ca
la
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le
lo
w
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co
s
t in
tern
et
o
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th
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g
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s
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tr
o
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ic
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e
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tifyin
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l
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(
A
mit Wele
ka
r
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2117
class
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ier
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ain
ed
o
n
th
is
c
lean
s
ed
d
ataset
with
8
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er
ce
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er
ce
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s
ed
f
o
r
tr
ai
n
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g
a
n
d
f
o
r
test
in
g
r
esp
ec
tiv
ely
.
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h
e
m
o
d
el
g
a
v
e
h
ig
h
class
if
icatio
n
ac
cu
r
ac
y
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d
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o
p
tim
ized
a
n
d
d
ep
l
o
y
ed
o
n
th
e
Flu
tter
m
o
b
ile
ap
p
licatio
n
f
o
r
r
ea
l
-
tim
e,
o
n
-
d
e
v
ice
in
f
e
r
e
n
ce
.
T
h
is
ML
in
teg
r
atio
n
e
n
ab
les
th
e
s
y
s
tem
to
co
n
f
o
r
m
to
s
u
b
tle
ch
an
g
es
in
ch
em
ical
f
in
g
er
p
r
in
ts
f
o
r
in
cr
ea
s
ed
r
eliab
ilit
y
o
f
d
etec
tio
n
co
m
p
ar
ed
to
th
r
esh
o
ld
in
g
tech
n
i
q
u
es.
Ad
d
itio
n
ally
,
th
e
ap
p
k
ee
p
s
lo
g
o
f
o
ld
class
if
icatio
n
s
,
wh
ich
allo
ws
th
e
u
s
er
s
to
h
av
e
ac
ce
s
s
to
r
ip
en
in
g
tr
e
n
d
s
an
d
p
atter
n
s
in
tim
e.
Fig
u
r
e
2
.
Mo
b
ile
Ap
p
: b
u
ilt with
f
lu
tter
,
co
n
n
ec
ted
v
ia
B
lu
eto
o
th
/W
i
-
Fi,
d
is
p
lay
in
g
r
ea
l
-
ti
m
e
g
as lev
els,
r
ip
en
ess
class
if
icatio
n
,
h
is
to
r
y
lo
g
with
tim
estam
p
s
2
.
4
.
Sy
s
t
e
m
w
o
r
k
f
lo
w
T
h
is
s
u
b
s
ec
tio
n
p
r
esen
ts
th
e
o
p
er
atio
n
al
p
ip
elin
e
g
o
v
er
n
in
g
s
en
s
o
r
in
itializatio
n
,
air
s
am
p
l
in
g
,
s
ig
n
al
ac
q
u
is
itio
n
,
ap
p
-
lev
el
p
r
o
ce
s
s
in
g
,
class
if
icatio
n
d
is
p
lay
,
ale
r
t
f
ee
d
b
ac
k
,
an
d
d
ata
tr
ac
ea
b
i
lity
.
T
h
e
ca
p
tu
r
e
d
g
as d
ata
is
an
aly
ze
d
b
y
th
e
E
S
P 3
2
co
n
tr
o
ller
,
u
s
in
g
a
n
d
p
r
in
t c
lass
if
icatio
n
m
o
d
el,
wh
ich
a
s
s
ig
n
s
th
e
r
esu
lt a
s
ar
tific
ially
r
ip
en
ed
o
r
n
at
u
r
a
lly
r
ip
en
ed
,
d
is
p
lay
e
d
wis
el
y
to
th
e
u
s
er
an
d
s
h
o
wn
in
Fig
u
r
e
3
.
Mo
b
ile
ap
p
licatio
n
in
ter
f
ac
e
as sh
o
wn
in
Fig
u
r
e
3
(
a)
an
d
s
y
s
tem
wo
r
k
f
lo
w
as sh
o
wn
in
Fig
u
r
e
3
(
b
)
.
(
a)
(
b
)
Fig
u
r
e
3
.
I
m
p
lem
en
te
d
s
y
s
tem
: (
a)
m
o
b
ile
ap
p
licatio
n
a
n
d
(
b
)
s
y
s
tem
wo
r
k
f
lo
w
T
h
e
e
-
n
o
s
e
AI
-
B
o
t
is
p
o
wer
e
d
o
n
a
n
d
i
n
itializes
th
e
g
as
s
en
s
o
r
s
.
T
h
e
in
ter
n
al
f
an
d
r
aws
ai
r
o
v
e
r
th
e
s
en
s
o
r
s
to
en
s
u
r
e
a
co
n
s
is
ten
t
VOC
s
am
p
le.
T
h
e
E
SP
3
2
r
ea
d
s
an
alo
g
s
ig
n
als
f
r
o
m
th
e
g
a
s
s
en
s
o
r
s
an
d
s
en
d
s
d
ata
to
t
h
e
m
o
b
ile
a
p
p
.
T
h
e
ap
p
p
r
o
ce
s
s
es
th
e
d
ata
u
s
in
g
p
r
e
-
ca
lib
r
ated
t
h
r
esh
o
ld
s
a
n
d
s
h
o
ws
th
e
r
esu
lt.
Aler
ts
ar
e
d
is
p
lay
ed
with
co
lo
r
-
co
d
ed
f
ee
d
b
ac
k
(
g
r
ee
n
f
o
r
s
af
ety
an
d
r
ed
f
o
r
ar
tific
ial
r
ip
en
in
g
)
.
His
to
r
ical
d
ata
ca
n
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e
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iewe
d
in
tab
u
lar
o
r
g
r
ap
h
ical
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o
r
m
at
f
r
o
m
th
e
ap
p
.
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h
is
en
d
-
to
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en
d
wo
r
k
f
lo
w
en
s
u
r
es
ac
cu
r
ate,
r
ea
l
-
tim
e
f
r
u
it testi
n
g
th
at
is
f
a
s
t,
af
f
o
r
d
ab
le
,
an
d
s
ca
lab
le
f
o
r
ag
r
icu
ltu
r
al
u
s
e
ac
r
o
s
s
I
n
d
ia.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
9
3
8
I
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tif
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n
tell
,
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
26
:
2
1
1
3
-
2
1
2
4
2118
2
.
5
.
E
x
perim
ent
a
l
s
et
up
Acc
o
r
d
in
g
to
Fig
u
r
e
4
,
th
e
s
etu
p
o
f
th
e
ex
p
er
im
en
t
in
clu
d
es
a
clo
s
ed
test
ch
am
b
er
th
at
wa
s
m
ad
e
to
b
e
ab
le
to
ac
co
m
m
o
d
ate
s
o
m
e
f
r
u
it
s
am
p
le
an
d
co
n
ce
n
tr
ate
an
y
g
as
th
at
is
em
itted
s
o
th
at
it
ca
n
b
e
d
etec
ted
.
C
o
n
tr
o
lled
ch
am
b
e
r
-
b
ased
g
a
s
s
en
s
in
g
ex
p
er
im
en
ts
ar
e
co
m
m
o
n
ly
u
s
ed
to
e
v
alu
ate
f
r
u
it
r
ip
en
in
g
b
e
h
av
io
u
r
u
n
d
er
s
tan
d
ar
d
ize
e
n
v
ir
o
n
m
e
n
tal
co
n
d
itio
n
s
[
2
2
]
,
[
2
3
]
.
T
h
e
s
y
s
tem
co
n
s
is
ts
o
f
th
e
f
u
ll
y
ass
em
b
led
e
-
n
o
s
e
AI
-
B
o
t
in
th
e
ch
am
b
e
r
,
a
s
m
a
ll
ex
h
au
s
t
f
an
to
ac
h
iev
e
u
n
i
f
o
r
m
cir
cu
latio
n
o
f
air
,
test
f
r
u
it
s
am
p
les
f
ix
ed
at
a
m
in
im
u
m
d
is
tan
ce
o
f
s
en
s
o
r
s
,
tem
p
er
atu
r
e
a
n
d
h
u
m
id
ity
k
ep
t
at
am
b
ien
t
lab
co
n
d
itio
n
s
(
2
5
°C
±
2
°C
)
an
d
d
ata
r
ec
o
r
d
e
d
th
r
o
u
g
h
t
h
e
m
o
b
ile
ap
p
licatio
n
in
in
ter
v
als
o
f
2
m
in
u
tes
s
ca
n
n
in
g
.
Sev
er
al
ex
p
er
im
en
ts
wer
e
d
o
n
e
o
n
b
a
n
an
as,
m
a
n
g
o
es
,
an
d
p
ap
ay
as
b
o
th
n
atu
r
ally
r
ip
en
ed
an
d
ar
tific
ially
r
ip
en
ed
(
u
s
in
g
ca
lciu
m
ca
r
b
id
e)
.
E
ac
h
f
r
u
it
was
test
ed
in
is
o
latio
n
to
a
v
o
id
g
as
m
i
x
in
g
e
f
f
ec
ts
.
T
h
e
AI
-
B
o
t
was
r
ec
alib
r
ated
b
ef
o
r
e
ea
ch
test
was
r
u
n
.
Sen
s
o
r
r
ea
d
in
g
s
wer
e
r
ec
o
r
d
e
d
a
n
d
a
v
er
ag
ed
to
f
o
r
m
d
etec
tio
n
p
r
o
f
iles
.
B
ased
o
n
th
r
esh
o
l
d
v
alu
es
an
d
VOC
p
atter
n
s
,
th
e
ap
p
d
eter
m
in
ed
th
e
r
ip
en
in
g
s
tatu
s
.
C
r
o
s
s
-
v
alid
atio
n
with
lab
o
r
ato
r
y
ch
r
o
m
ato
g
r
ap
h
y
co
n
f
ir
m
e
d
th
e
r
eliab
ilit
y
o
f
th
e
r
esu
lts
.
Fig
u
r
e
4
.
E
x
p
er
im
e
n
tal
s
etu
p
:
ch
am
b
er
at
2
5
±
2
°C
,
2
-
m
in
s
c
an
s
; f
r
u
its
v
alid
ated
with
ch
r
o
m
ato
g
r
ap
h
y
2
.
6
.
M
o
bil
e
a
pp
ps
eudo
co
de
s
t
eps
T
h
is
s
u
b
s
ec
tio
n
p
r
esen
ts
th
e
lo
g
ical
s
eq
u
en
ce
im
p
lem
e
n
te
d
in
th
e
m
o
b
ile
ap
p
licatio
n
t
o
in
ter
f
ac
e
with
th
e
E
SP
-
3
2
b
ased
e
-
n
o
s
e
AI
-
B
o
t.
T
h
e
s
tep
s
o
u
tlin
e
m
o
d
u
le
in
itializatio
n
s
en
s
in
g
s
ess
io
n
co
n
tr
o
l,
r
ea
l
tim
e
d
ata
ca
p
tu
r
e,
th
r
esh
o
l
d
co
m
p
ar
is
o
n
,
r
esu
lt
lo
g
g
in
g
,
an
d
h
is
to
r
y
v
is
u
aliza
tio
n
.
T
h
r
esh
o
ld
-
b
ase
d
class
if
icatio
n
co
m
b
in
ed
with
s
tati
s
tical
av
er
ag
in
g
is
a
co
m
m
o
n
ly
ad
o
p
ted
ap
p
r
o
ac
h
i
n
em
b
ed
d
e
d
e
-
n
o
s
e
s
y
s
tem
s
d
u
e
to
it
s
co
m
p
u
tatio
n
al
ef
f
icien
cy
[
5
]
,
[
7
]
.
T
h
e
p
s
eu
d
o
co
d
e
also
s
u
m
m
ar
izes
o
p
tio
n
al
u
s
er
-
co
n
f
ig
u
r
ab
le
f
ea
tu
r
es
ex
p
o
s
ed
in
th
e
ap
p
s
ettin
g
.
T
h
e
m
o
b
ile
ap
p
licatio
n
th
at
in
ter
f
a
ce
s
with
th
e
e
-
n
o
s
e
AI
-
B
o
t f
o
llo
ws a
clea
r
s
tep
-
by
-
s
tep
lo
g
f
o
r
id
en
tif
y
in
g
a
r
tific
ially
r
ip
en
ed
f
r
u
its
.
Step
1
: Star
t a
p
p
licatio
n
1
.
1
.
L
a
u
n
ch
t
h
e
m
o
b
ile
ap
p
1
.
2
.
I
n
itialize
B
lu
eto
o
th
/W
i
-
Fi
m
o
d
u
le
1
.
3
.
Scan
a
n
d
co
n
n
ec
t
to
th
e
E
SP
3
2
-
b
ased
e
-
n
o
s
e
AI
-
B
o
t
Step
2
: T
r
ig
g
er
test
s
ess
io
n
2
.
1
.
W
ait
f
o
r
t
h
e
u
s
er
to
p
r
ess
“Star
t T
est.”
2
.
2
.
Sen
d
th
e
“star
t”
co
m
m
a
n
d
to
E
SP
3
2
2
.
3
.
Dis
p
lay
m
ess
ag
e:
“Co
llectin
g
Data
…
Please
wait
2
m
in
u
tes.”
Step
3
: Co
llect
s
en
s
o
r
d
ata
3
.
1
.
Star
t 3
-
m
in
u
te
tim
er
3
.
2
.
R
ep
ea
t e
v
e
r
y
1
0
s
ec
o
n
d
s
u
n
til th
e
tim
er
ex
p
ir
es:
a.
R
ec
eiv
e
d
ata
f
r
o
m
MQ
-
3
an
d
MQ
-
1
3
5
b
.
Sto
r
e
r
ea
d
in
g
s
in
d
ata
L
o
g
[
]
c.
Up
d
ate
UI
with
liv
e
g
r
ap
h
Step
4
: A
n
aly
ze
d
ata
4
.
1
.
C
o
m
p
u
te
av
er
a
g
e
v
alu
es:
av
g
_
MQ
3
=
m
ea
n
(
d
ataL
o
g
.
MQ
3
)
av
g
_
MQ
1
3
5
=
m
ea
n
(
d
ataL
o
g
.
MQ
1
3
5
)
4
.
2
.
R
etr
iev
e
th
r
esh
o
ld
v
al
u
es:
T
_
MQ
3
,
T
_
MQ
1
3
5
Step
5
: Cl
ass
if
y
r
ip
en
ess
5
.
1
.
I
f
(
a
v
g
_
MQ
3
>
T
_
MQ
3
)
OR
(
av
g
_
MQ
1
3
5
>
T
_
MQ
1
3
5
)
:
→
Di
s
p
lay
:
“Ar
tific
ially
R
ip
en
ed
”
(
R
ed
aler
t
+
s
o
u
n
d
)
E
ls
e
→
Di
s
p
lay
:
“Na
tu
r
ally
R
ip
en
ed
”
(
Gr
ee
n
ch
ec
k
m
ar
k
)
Step
6
: L
o
g
a
n
d
s
to
r
e
r
esu
lt
6
.
1
.
Sav
e
th
e
r
esu
lt to
th
e
l
o
ca
l d
atab
ase
-
T
im
estam
p
-
Sen
s
o
r
av
er
ag
es
-
C
las
s
if
icatio
n
Step
7
: V
is
u
alize
h
is
to
r
y
7
.
1
.
Allo
w
th
e
u
s
er
to
v
iew
th
e
lo
g
in
His
to
r
y
tab
7
.
2
.
Dis
p
lay
tim
e
-
s
tam
p
ed
r
e
s
u
lt
+
g
r
a
p
h
f
o
r
ea
ch
en
tr
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Step
8
: O
p
tio
n
al
f
ea
tu
r
es
8
.
1
.
I
f
clo
u
d
s
y
n
c
is
en
ab
led
,
→
Up
lo
ad
th
e
r
esu
lt
to
th
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clo
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d
8
.
2
.
Allo
w
u
s
er
s
to
u
p
d
ate
th
r
esh
o
ld
s
,
th
em
es,
o
r
lan
g
u
ag
e
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n
s
ettin
g
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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tif
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tell
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SS
N:
2252
-
8
9
3
8
A
s
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la
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w
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co
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tern
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o
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tr
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mit Wele
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2119
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u
r
e
5
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e
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o
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ile
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p
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ter
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u
r
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5
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R
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cr
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p
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r
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r
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it r
ip
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ess
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icatio
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RE
SU
L
T
S AN
D
D
I
SCU
SS
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h
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ter
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ep
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ield
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esh
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ased
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io
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ec
tio
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3
.
1
.
Sens
o
r
da
t
a
a
na
ly
s
is
:
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v
er
a
g
e
ca
lcula
t
io
n
T
h
is
s
ec
tio
n
d
escr
ib
es th
e
s
tati
s
tical
co
m
p
etitio
n
ap
p
lied
to
R
AW
an
d
Alo
k
r
ea
d
in
g
s
f
r
o
m
MQ
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3
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d
MQ
-
1
3
5
d
u
r
in
g
ea
c
h
s
en
s
in
g
s
ess
io
n
.
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s
tical
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er
ag
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s
e
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d
im
p
r
o
v
e
class
if
icatio
n
r
eliab
ilit
y
in
elctr
o
n
ic
n
o
s
e
s
y
s
tem
s
[
5
]
,
[
1
7
]
.
I
n
d
iv
id
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al
tim
e
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ex
s
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les
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ated
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m
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ter
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als
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m
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iles
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h
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m
p
u
ted
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ea
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v
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es
ar
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u
s
ed
f
o
r
th
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esh
o
ld
co
m
p
ar
is
o
n
an
d
class
if
icatio
n
.
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h
e
f
o
r
m
u
las
a
r
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u
s
ed
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te
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tlin
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g
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3
=
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3
=
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d
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g
-
135
=
1
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(
-
135
=
1
)
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h
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n
=1
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n
r
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ter
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ab
le
2
.
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s
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r
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ata
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r
tim
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me
(
sec
)
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-
3
(
p
p
m)
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1
3
5
(
p
p
m)
0
1
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0
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0
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0
0
2
6
0
20
2
1
0
2
7
5
----
----
----
1
7
0
1
9
0
2
8
0
Af
ter
co
llectin
g
all
v
alu
es:
av
g
-
3
=
180
+
200
+
210
+
⋯
+
1
90
18
an
d
av
g
-
135
=
250
+
260
+
275
+
⋯
+
280
18
T
h
ese
av
er
ag
e
v
alu
es
ar
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en
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ar
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r
esh
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s
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s
3
an
d
4
p
r
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t
th
e
p
r
ed
ef
in
e
d
g
as th
r
esh
o
ld
s
f
o
r
r
ip
en
ess
class
if
icat
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n
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d
clas
s
if
icatio
n
lo
g
ic
b
ased
o
n
g
as l
ev
els r
esp
ec
tiv
ely
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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2
2
5
2
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9
3
8
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20
26
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3
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2120
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3
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ased
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els
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Q
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x
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is
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2
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1
.
L
ine
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ra
ph
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f
s
ens
o
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re
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o
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er
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im
e
T
h
is
s
u
b
s
ec
tio
n
v
is
u
aliza
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f
MQ
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3
a
n
d
MQ
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1
3
5
m
ea
s
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r
ed
in
a
3
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m
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te
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n
wi
n
d
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w.
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h
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g
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h
s
h
o
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tr
en
d
s
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f
t
h
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eth
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an
d
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M
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g
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in
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icate
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v
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iatio
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tim
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d
af
ter
s
ig
n
al
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r
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-
p
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ce
s
s
in
g
.
Fig
u
r
e
6
s
h
o
ws
th
e
s
im
u
lated
s
en
s
o
r
r
ea
d
in
g
s
o
v
er
tim
e.
Gr
a
p
h
:
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-
ax
is
=
PP
M
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X
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ax
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=
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im
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s
ec
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3
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3
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r
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n
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Fi
g
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s
h
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tific
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ip
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p
les.
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o
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ce
n
tr
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p
p
m
)
,
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a
x
is
=
s
am
p
le
ty
p
e
,
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3
lev
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1
3
5
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t
h
r
esh
o
ld
lin
es (
e.
g
.
,
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3
>
0
.
5
0
,
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1
3
5
>0
.
4
0
tr
ig
g
er
s
ar
tific
ial
class
if
icatio
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)
.
T
o
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u
r
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er
co
n
f
ir
m
s
en
s
o
r
r
es
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o
n
s
e
s
tab
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,
tem
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o
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as
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is
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io
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atter
n
s
wer
e
ex
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i
o
r
t
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ig
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al
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r
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s
in
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te
r
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ig
n
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r
o
ce
s
s
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g
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e
p
r
e
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io
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s
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ch
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icate
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th
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eth
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o
l
s
p
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d
VOC
in
cr
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e
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ep
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le
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ip
en
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g
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p
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ticu
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ly
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ter
ic
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m
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g
o
a
n
d
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a
n
a.
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h
e
o
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s
er
v
ed
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as
em
is
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io
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p
atter
n
s
alig
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with
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r
e
v
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u
s
ly
r
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ted
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tu
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ies
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g
th
at
eth
an
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l
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d
VOC
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n
ce
n
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atio
n
s
ar
e
k
ey
in
d
ica
to
r
s
o
f
f
r
u
it
r
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en
i
n
g
s
tag
es
[
1
9
]
,
[
2
2
]
.
M
o
v
in
g
av
e
r
ag
e
p
r
ep
r
o
ce
s
s
in
g
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r
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t
a
n
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h
a
n
ce
s
th
e
r
eliab
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f
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icatio
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em
b
e
d
d
ed
e
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n
o
s
e
s
y
s
tem
s
.
3
.
3
.
Dis
cus
s
io
n
T
h
e
f
o
llo
win
g
s
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tio
n
b
r
in
g
s
to
g
eth
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if
icatio
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m
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tak
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at
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e
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s
er
v
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r
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f
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t
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s
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n
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ac
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tern
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o
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o
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itiv
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u
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e
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atu
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en
tatio
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elea
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ch
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en
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tem
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x
ce
s
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u
r
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o
t
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le.
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n
d
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u
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g
g
est
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clu
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m
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ts
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l
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n
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R
es
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ch
o
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r
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f
8
8
-
9
4
%
in
co
n
tr
o
lled
ch
am
b
er
s
[
1
7
]
,
[
1
9
]
wh
ich
d
e
m
o
n
s
tr
ate
s
th
at
o
u
r
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w
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co
s
t
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s
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r
m
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is
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p
etitiv
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en
with
a
s
m
aller
s
en
s
o
r
co
u
n
t.
Fig
u
r
e
6
.
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s
o
r
r
ea
d
in
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o
v
er
tim
e
Fig
u
r
e
7
.
T
h
r
esh
o
ld
c
o
m
p
a
r
is
o
n
b
etwe
en
n
atu
r
ally
a
n
d
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tifi
cially
r
ip
en
ed
s
am
p
les
4.
CO
NCLU
SI
O
N
T
h
is
p
ap
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p
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r
o
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u
s
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n
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s
e
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y
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tem
o
f
r
ap
id
i
d
en
tific
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o
f
ar
tific
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ip
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e
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y
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tem
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m
p
o
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ed
o
f
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s
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as
s
en
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SP
3
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ased
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o
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o
l,
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h
t
m
o
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ile
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wh
ich
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ies
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r
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it
r
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ess
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ased
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ased
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ak
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r
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m
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in
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ased
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r
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tio
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ate
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is
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tem
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n
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e
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p
to
9
0
%.
T
h
e
s
en
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itiv
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o
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e
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ath
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atica
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