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C
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3
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lt
r
y
o
p
e
r
at
io
n
s
p
r
im
ar
i
ly
m
o
n
it
o
r
f
l
o
c
k
-
le
v
e
l
en
v
i
r
o
n
m
e
n
t
al
a
n
d
p
r
o
d
u
cti
o
n
i
n
d
ica
to
r
s
r
at
h
er
th
a
n
in
d
i
v
i
d
u
a
l
b
ir
d
p
h
y
s
i
o
l
o
g
ic
al
m
e
asu
r
em
en
ts
.
R
ec
e
n
t
a
d
v
a
n
c
es
i
n
c
o
m
p
u
t
er
v
is
i
o
n
,
m
ac
h
i
n
e
v
is
i
o
n
,
an
d
o
t
h
e
r
n
o
n
-
i
n
v
as
iv
e
m
o
n
i
to
r
i
n
g
tec
h
n
o
l
o
g
ies
h
av
e
d
e
m
o
n
s
tr
at
ed
c
o
n
s
id
e
r
a
b
le
p
o
te
n
ti
al
f
o
r
e
ar
l
y
p
o
u
lt
r
y
h
e
alt
h
p
r
e
d
ic
ti
o
n
,
wel
f
a
r
e
ass
ess
m
e
n
t
,
an
d
p
r
o
d
u
cti
o
n
m
o
n
it
o
r
in
g
w
ith
in
p
r
ec
is
io
n
p
o
u
lt
r
y
f
ar
m
i
n
g
s
y
s
te
m
s
[
9
]
,
[
1
0
]
.
Dee
p
lear
n
in
g
ap
p
r
o
ac
h
es,
p
a
r
ticu
lar
ly
co
n
v
o
lu
tio
n
al
n
eu
r
a
l
n
etwo
r
k
s
(
C
NNs),
h
av
e
d
e
m
o
n
s
tr
ated
s
tr
o
n
g
p
er
f
o
r
m
a
n
ce
in
p
o
u
lt
r
y
d
is
ea
s
e
class
if
icatio
n
u
s
i
n
g
im
ag
e
-
b
ased
an
aly
s
is
[
1
]
,
[
1
1
]
,
[
1
2
]
.
Dee
p
lear
n
in
g
-
b
ased
p
o
u
ltry
d
iag
n
o
s
tic
s
y
s
tem
s
h
av
e
in
cr
ea
s
in
g
ly
d
em
o
n
s
tr
ated
s
tr
o
n
g
p
o
te
n
tial
f
o
r
a
u
to
m
ated
d
is
ea
s
e
m
o
n
ito
r
in
g
an
d
in
tell
ig
en
t
d
ec
is
io
n
s
u
p
p
o
r
t
[
1
3
]
.
R
ec
en
t
s
tu
d
ies
h
av
e
also
e
x
p
lo
r
ed
m
u
ltimo
d
al
ap
p
r
o
ac
h
es
in
teg
r
atin
g
v
is
u
al
an
d
a
u
d
io
d
ata
f
o
r
p
o
u
ltry
h
ea
lth
m
o
n
ito
r
in
g
[
1
4
]
,
[
1
5
]
.
I
n
a
d
d
itio
n
,
o
b
ject
d
etec
tio
n
m
o
d
els
s
u
ch
as
Yo
u
On
ly
L
o
o
k
On
ce
(
YOL
O
)
h
av
e
b
ee
n
s
u
cc
ess
f
u
lly
ap
p
l
ied
f
o
r
au
to
m
ated
p
o
u
ltry
d
is
ea
s
e
d
etec
tio
n
an
d
b
eh
a
v
io
r
m
o
n
ito
r
in
g
[
1
6
]
,
[
1
7
]
.
Oth
e
r
r
ec
e
n
t
s
tu
d
ies
h
av
e
also
d
em
o
n
s
tr
ated
th
at
m
u
ltimo
d
a
l
C
NN
-
b
ased
f
ea
tu
r
e
f
u
s
io
n
tech
n
iq
u
es
ca
n
s
ig
n
if
ican
tly
im
p
r
o
v
e
p
o
u
ltry
h
ea
lth
class
if
icatio
n
p
er
f
o
r
m
an
ce
[
1
8
]
.
E
n
v
ir
o
n
m
e
n
tal
m
o
n
ito
r
in
g
s
y
s
tem
s
u
tili
zin
g
I
o
T
tech
n
o
lo
g
ies
f
u
r
t
h
er
co
n
tr
ib
u
ted
to
war
d
co
n
tin
u
o
u
s
m
o
n
ito
r
i
n
g
o
f
p
o
u
ltry
h
o
u
s
e
co
n
d
itio
n
s
in
clu
d
i
n
g
tem
p
er
atu
r
e
,
h
u
m
i
d
ity
,
am
m
o
n
ia,
an
d
ca
r
b
o
n
d
io
x
id
e
lev
els
[
7
]
,
[
4
]
.
Au
d
io
-
v
is
u
al
d
ee
p
lear
n
in
g
ap
p
r
o
ac
h
es
h
av
e
also
b
ee
n
ex
p
lo
r
ed
f
o
r
in
tellig
en
t
p
o
u
ltry
d
is
ea
s
e
m
o
n
ito
r
in
g
with
in
s
m
ar
t
f
ar
m
in
g
en
v
ir
o
n
m
en
ts
[
1
5
]
.
Ma
ch
i
n
e
lear
n
in
g
an
d
o
p
tim
izatio
n
-
b
ased
d
is
ea
s
e
p
r
ed
ictio
n
m
eth
o
d
s
h
a
v
e
also
d
em
o
n
s
tr
ated
p
r
o
m
is
in
g
ca
p
a
b
ilit
y
f
o
r
ea
r
ly
p
o
u
ltr
y
d
is
ea
s
e
d
iag
n
o
s
is
[
1
9
]
.
Desp
ite
th
ese
ad
v
an
ce
m
en
ts
,
m
o
s
t
ex
is
tin
g
s
y
s
tem
s
r
em
ain
u
n
im
o
d
al
an
d
f
o
cu
s
p
r
i
m
ar
ily
o
n
d
etec
tin
g
v
is
ib
le
s
y
m
p
to
m
s
r
ath
er
th
a
n
p
r
o
ac
tiv
ely
p
r
e
d
ictin
g
d
is
ea
s
e
o
n
s
et
[
2
]
,
[
3
]
.
Fu
r
th
e
r
m
o
r
e
,
li
m
ited
r
esear
ch
h
as
ex
p
lo
r
ed
th
e
in
teg
r
atio
n
o
f
te
m
p
o
r
al
s
eq
u
en
ce
m
o
d
elin
g
a
n
d
ex
p
lain
ab
le
a
r
tific
ial
in
tellig
en
ce
(
XAI
)
with
in
p
o
u
ltry
d
is
ea
s
e
p
r
ed
ictio
n
s
y
s
tem
s
.
E
n
s
em
b
le
C
NN
ap
p
r
o
a
ch
es
h
av
e
also
b
ee
n
e
x
p
lo
r
e
d
f
o
r
p
o
u
ltry
d
is
ea
s
e
d
etec
tio
n
f
r
o
m
f
ae
ca
l
im
ag
e
s
,
f
u
r
th
er
s
h
o
win
g
th
at
v
is
u
al
d
iag
n
o
s
tic
p
ip
elin
es
ca
n
b
en
ef
it
f
r
o
m
m
o
d
el
d
iv
er
s
ity
an
d
c
o
m
p
ar
ativ
e
b
en
ch
m
ar
k
in
g
[
2
0
]
.
T
r
an
s
f
o
r
m
e
r
a
r
ch
ite
ct
u
r
es
h
a
v
e
r
e
ce
n
tl
y
g
ai
n
ed
att
en
ti
o
n
f
o
r
t
h
e
ir
ab
ilit
y
t
o
m
o
d
el
lo
n
g
-
r
a
n
g
e
tem
p
o
r
al
d
ep
en
d
en
ci
es
u
s
i
n
g
s
el
f
-
att
en
ti
o
n
m
ec
h
a
n
is
m
s
[
2
1
]
.
T
h
e
ir
a
p
p
lic
ati
o
n
w
it
h
in
p
o
u
lt
r
y
d
is
e
ase
p
r
e
d
ic
ti
o
n
r
em
ain
s
li
m
it
ed
,
p
a
r
ti
cu
la
r
l
y
in
m
u
l
ti
m
o
d
a
l
f
r
a
m
e
wo
r
k
s
i
n
t
eg
r
a
ti
n
g
e
n
v
i
r
o
n
m
e
n
tal
,
p
r
o
d
u
ct
io
n
,
an
d
v
is
u
al
d
at
a
s
i
m
u
lta
n
e
o
u
s
l
y
.
I
n
ad
d
i
ti
o
n
,
m
a
n
y
e
x
is
ti
n
g
A
I
-
b
ase
d
p
o
u
l
tr
y
d
is
ea
s
e
s
y
s
te
m
s
l
ac
k
i
n
t
er
p
r
et
ab
ili
ty
,
r
e
d
u
ci
n
g
t
r
u
s
t
an
d
lim
iti
n
g
p
r
ac
ti
ca
l
a
d
o
p
ti
o
n
i
n
r
ea
l
-
wo
r
l
d
f
a
r
m
i
n
g
e
n
v
ir
o
n
m
e
n
ts
[
5
]
,
[
2
2
]
.
X
AI
te
ch
n
i
q
u
es
th
e
r
ef
o
r
e
p
la
y
a
n
i
m
p
o
r
t
a
n
t
r
o
l
e
i
n
im
p
r
o
v
in
g
t
r
a
n
s
p
a
r
e
n
c
y
a
n
d
s
u
p
p
o
r
ti
n
g
i
n
f
o
r
m
e
d
d
ec
is
i
o
n
-
m
a
k
i
n
g
.
C
o
n
ce
p
t
u
a
ll
y
,
th
e
p
r
o
p
o
s
e
d
m
u
lt
im
o
d
al
le
ar
n
i
n
g
a
p
p
r
o
ac
h
is
g
r
o
u
n
d
e
d
i
n
r
e
p
r
ese
n
t
ati
o
n
l
e
ar
n
i
n
g
a
n
d
in
f
o
r
m
at
io
n
f
u
s
i
o
n
th
e
o
r
y
,
wh
e
r
e
c
o
m
p
le
m
e
n
t
ar
y
d
at
a
s
tr
ea
m
s
a
r
e
tr
a
n
s
f
o
r
m
ed
in
t
o
s
h
ar
e
d
l
ate
n
t
r
e
p
r
ese
n
t
ati
o
n
s
t
h
at
im
p
r
o
v
e
p
r
e
d
i
cti
o
n
u
n
d
er
u
n
ce
r
ta
in
ty
.
I
n
c
o
m
p
u
te
r
s
ci
en
ce
te
r
m
s
,
t
h
e
t
r
a
n
s
f
o
r
m
e
r
b
r
a
n
c
h
m
o
d
els
te
m
p
o
r
al
d
e
p
e
n
d
e
n
c
ie
s
t
h
r
o
u
g
h
s
el
f
-
at
te
n
ti
o
n
,
t
h
e
C
NN
b
r
a
n
c
h
e
x
t
r
a
cts
s
p
a
tial
h
e
alt
h
f
ea
tu
r
es
f
r
o
m
im
a
g
es
,
a
n
d
t
h
e
f
u
s
i
o
n
la
y
e
r
i
n
t
eg
r
a
tes
t
h
ese
h
et
er
o
g
e
n
eo
u
s
s
i
g
n
als
i
n
t
o
a
u
n
i
f
i
ed
d
e
cisi
o
n
s
p
ac
e
.
T
h
is
th
e
o
r
e
tic
al
g
r
o
u
n
d
i
n
g
c
o
n
n
ec
ts
t
h
e
s
t
u
d
y
t
o
b
r
o
a
d
e
r
A
I
r
esea
r
c
h
o
n
m
u
lti
m
o
d
al
r
e
p
r
e
s
en
t
ati
o
n
l
ea
r
n
i
n
g
,
in
t
er
p
r
et
a
b
le
p
r
ed
ict
iv
e
m
o
d
el
l
in
g
,
a
n
d
d
ec
is
io
n
-
s
u
p
p
o
r
t s
y
s
t
e
m
s
f
o
r
i
n
f
o
r
m
ati
o
n
-
r
ic
h
en
v
i
r
o
n
m
e
n
ts
[
2
1
]
,
[
2
3
]
.
T
h
is
s
tu
d
y
p
r
o
p
o
s
ed
a
m
u
ltim
o
d
al
tr
an
s
f
o
r
m
er
–
C
NN
f
r
am
e
wo
r
k
f
o
r
ea
r
ly
f
lo
ck
-
lev
el
p
r
e
d
ictio
n
o
f
E
.
co
li
in
f
ec
tio
n
in
b
r
o
iler
ch
ick
en
s
.
T
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
in
teg
r
ate
d
f
lo
ck
-
lev
el
en
v
ir
o
n
m
en
tal,
p
r
o
d
u
ctio
n
,
an
d
v
is
u
al
d
ata
to
s
u
p
p
o
r
t
p
r
o
ac
tiv
e
in
f
ec
tio
n
r
is
k
p
r
ed
ictio
n
wh
ile
in
co
r
p
o
r
ati
n
g
XAI
tech
n
iq
u
es
to
im
p
r
o
v
e
in
ter
p
r
etab
ilit
y
an
d
tr
an
s
p
ar
en
c
y
.
A
s
tr
ea
m
lit
-
b
a
s
ed
d
ash
b
o
ar
d
p
r
o
to
ty
p
e
was a
ls
o
im
p
lem
en
ted
to
p
r
o
v
id
e
r
ea
l
-
tim
e
d
ec
is
io
n
s
u
p
p
o
r
t
f
o
r
p
o
u
ltry
h
ea
lth
m
o
n
it
o
r
in
g
.
T
h
e
m
ain
co
n
t
r
ib
u
tio
n
o
f
th
is
s
tu
d
y
lies
in
th
e
i
n
teg
r
atio
n
o
f
tr
an
s
f
o
r
m
er
-
b
ased
tem
p
o
r
al
m
o
d
elin
g
,
C
NN
-
b
ased
v
is
u
al
an
aly
s
is
,
an
d
XAI
with
in
a
u
n
if
ied
m
u
ltimo
d
al
f
r
am
ewo
r
k
f
o
r
p
r
o
ac
tiv
e
p
o
u
ltry
d
is
ea
s
e
p
r
ed
ictio
n
.
2.
M
E
T
H
O
D
2
.
1
.
Resea
rc
h
des
i
gn
T
h
is
s
tu
d
y
ad
o
p
ted
a
q
u
an
ti
tativ
e
ex
p
er
im
e
n
tal
r
esear
ch
d
esig
n
c
o
m
b
in
e
d
with
m
u
ltimo
d
al
AI
s
y
s
tem
d
ev
elo
p
m
en
t
p
r
in
cip
l
es
to
d
e
v
elo
p
an
d
e
v
alu
ate
a
c
h
ec
k
p
o
in
t
-
b
ased
p
o
u
ltry
h
ea
lth
m
o
n
it
o
r
in
g
f
r
am
ewo
r
k
f
o
r
ea
r
ly
E
.
c
o
li
in
f
ec
tio
n
r
is
k
p
r
ed
ictio
n
in
b
r
o
iler
c
h
ick
en
s
.
Qu
an
titativ
e
m
eth
o
d
o
l
o
g
y
was
s
elec
ted
b
ec
au
s
e
th
e
s
tu
d
y
r
elied
o
n
m
ea
s
u
r
ab
le
e
n
v
ir
o
n
m
e
n
tal,
p
r
o
d
u
ctio
n
,
b
eh
av
io
u
r
al,
an
d
v
is
u
al
p
o
u
ltr
y
v
ar
iab
les
to
tr
ai
n
an
d
e
v
alu
ate
d
ee
p
lear
n
in
g
m
o
d
els
ca
p
ab
le
o
f
id
en
tify
in
g
d
is
ea
s
e
-
r
elate
d
f
lo
ck
d
eter
io
r
atio
n
p
atter
n
s
[
4
]
,
[
7
]
,
[
2
4
]
.
T
h
e
s
tu
d
y
f
u
r
th
er
ad
o
p
ted
a
n
ex
p
er
im
en
tal
m
o
d
ellin
g
a
p
p
r
o
ac
h
in
v
o
lv
i
n
g
d
ataset
d
ev
elo
p
m
e
n
t,
p
r
ep
r
o
ce
s
s
in
g
,
m
o
d
el
tr
ai
n
in
g
,
m
u
ltimo
d
al
f
u
s
io
n
,
s
y
s
tem
test
in
g
,
an
d
d
ash
b
o
ar
d
d
ep
lo
y
m
en
t.
T
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
i
n
teg
r
ated
tr
a
n
s
f
o
r
m
er
-
b
ased
tem
p
o
r
al
m
o
d
ellin
g
with
C
NN
-
b
ased
v
is
u
al
p
o
u
ltr
y
ass
es
s
m
en
t
to
im
p
r
o
v
e
f
l
o
ck
-
lev
el
d
is
ea
s
e
s
u
r
v
eillan
ce
c
ap
ab
ilit
y
with
in
co
m
m
er
cial
b
r
o
iler
p
r
o
d
u
ctio
n
en
v
ir
o
n
m
en
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
3
2
2
1
C
o
m
p
u
t Sci
I
n
f
T
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h
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o
l
,
Vo
l.
7
,
No
.
3
,
No
v
em
b
er
20
26
:
3
1
4
-
324
316
2
.
2
.
Da
t
a
a
cquis
it
io
n a
nd
da
t
a
s
et
dev
elo
pm
ent
E
n
v
ir
o
n
m
en
tal,
p
r
o
d
u
ctio
n
,
an
d
b
eh
a
v
io
u
r
al
p
o
u
ltry
m
o
n
ito
r
in
g
d
ata
wer
e
ac
q
u
ir
ed
f
r
o
m
co
m
m
er
cial
b
r
o
iler
p
r
o
d
u
ctio
n
cy
cles
r
ec
o
r
d
e
d
b
etwe
en
2
0
2
2
an
d
2
0
2
5
.
Mo
n
ito
r
in
g
f
o
cu
s
ed
o
n
s
ix
p
r
o
d
u
ctio
n
ch
ec
k
p
o
in
ts
:
d
ay
3
,
d
ay
7
,
d
ay
1
4
,
d
ay
2
1
,
d
ay
2
8
,
an
d
d
ay
3
1
.
E
n
v
ir
o
n
m
e
n
tal
v
ar
iab
les
in
clu
d
ed
tem
p
er
atu
r
e,
h
u
m
id
ity
,
am
m
o
n
ia
co
n
ce
n
tr
atio
n
,
an
d
ca
r
b
o
n
d
io
x
id
e
le
v
els,
wh
ile
p
r
o
d
u
ctio
n
v
ar
ia
b
les
in
clu
d
ed
f
lo
c
k
weig
h
t,
f
ee
d
i
n
tak
e,
wate
r
in
tak
e,
cu
m
u
lativ
e
m
o
r
tality
p
er
ce
n
tag
e
,
an
d
f
ee
d
co
n
v
e
r
s
io
n
r
atio
(
FC
R
)
.
B
eh
av
io
u
r
al
in
d
icato
r
s
ca
p
tu
r
e
d
ac
tiv
ity
an
d
v
e
n
tilatio
n
s
tatu
s
.
T
h
e
ch
ec
k
p
o
in
t
r
ec
o
r
d
s
wer
e
co
n
v
er
ted
in
t
o
ap
p
r
o
x
im
atel
y
9
0
,
0
0
0
lo
n
g
-
f
o
r
m
at
tem
p
o
r
al
o
b
s
er
v
atio
n
s
f
o
r
tr
an
s
f
o
r
m
er
m
o
d
ellin
g
,
s
u
p
p
o
r
tin
g
an
8
0
:2
0
s
p
lit o
f
7
2
,
0
0
0
tr
ain
in
g
r
ec
o
r
d
s
an
d
1
8
,
0
0
0
test
in
g
r
e
c
o
r
d
s
.
2
.
3
.
Da
t
a
prepro
ce
s
s
ing
B
ef
o
r
e
m
o
d
el
d
e
v
elo
p
m
e
n
t,
th
e
d
atasets
u
n
d
er
wen
t
p
r
ep
r
o
ce
s
s
in
g
to
im
p
r
o
v
e
d
ata
q
u
ality
an
d
tr
ain
in
g
s
tab
ilit
y
.
E
n
v
ir
o
n
m
e
n
tal
an
d
p
r
o
d
u
ctio
n
v
a
r
iab
les
wer
e
clea
n
ed
to
r
em
o
v
e
in
c
o
n
s
is
ten
t
r
ec
o
r
d
s
a
n
d
m
is
s
in
g
v
alu
es,
wh
ile
n
u
m
er
i
ca
l
f
ea
tu
r
es
s
u
ch
as
tem
p
er
atu
r
e,
am
m
o
n
ia
co
n
ce
n
t
r
atio
n
,
m
o
r
tality
p
er
ce
n
ta
g
e,
an
d
FC
R
wer
e
n
o
r
m
alize
d
to
en
s
u
r
e
co
n
s
is
ten
t
f
ea
tu
r
e
r
e
p
r
esen
tatio
n
d
u
r
i
n
g
tr
ain
in
g
.
T
h
e
p
o
u
ltr
y
im
ag
e
d
ataset
u
n
d
er
wen
t
p
r
e
p
r
o
ce
s
s
in
g
p
r
o
ce
d
u
r
es
in
clu
d
in
g
r
es
izin
g
,
n
o
r
m
aliz
atio
n
,
au
g
m
en
tatio
n
,
an
d
ten
s
o
r
co
n
v
er
s
io
n
[
5
]
,
[
1
4
]
.
I
m
ag
es
wer
e
r
esized
to
s
tan
d
ar
d
ized
d
im
en
s
io
n
s
co
m
p
atib
le
with
t
h
e
C
NN
ar
ch
itectu
r
e,
wh
ile
au
g
m
en
tatio
n
tech
n
iq
u
e
s
s
u
ch
as
im
ag
e
r
o
tatio
n
,
h
o
r
i
zo
n
tal
f
lip
p
in
g
,
an
d
b
r
ig
h
t
n
ess
ad
ju
s
tm
en
t
wer
e
ap
p
lied
to
im
p
r
o
v
e
d
ataset
v
ar
iab
ilit
y
an
d
r
ed
u
ce
o
v
e
r
f
itti
n
g
.
Fo
llo
win
g
p
r
e
p
r
o
ce
s
s
in
g
,
t
h
e
f
lo
ck
d
ataset
was
co
n
v
er
ted
f
r
o
m
wid
e
c
h
ec
k
p
o
in
t
f
o
r
m
at
in
to
lo
n
g
-
f
o
r
m
at
s
eq
u
en
tial
o
b
s
er
v
atio
n
s
to
s
u
p
p
o
r
t
tr
an
s
f
o
r
m
er
-
b
ased
tem
p
o
r
al
lear
n
in
g
.
C
h
e
ck
p
o
in
t
-
b
ased
tem
p
o
r
al
s
eq
u
e
n
ce
s
en
ab
led
th
e
tr
a
n
s
f
o
r
m
er
m
o
d
el
to
an
al
y
s
e
p
r
o
g
r
ess
iv
e
en
v
ir
o
n
m
en
tal
an
d
p
r
o
d
u
ctio
n
ch
an
g
es a
cr
o
s
s
th
e
m
o
n
ito
r
ed
b
r
o
iler
p
r
o
d
u
ctio
n
s
tag
es.
2
.
4
.
P
r
o
po
s
ed
m
ultim
o
da
l f
r
a
m
ewo
r
k
T
h
e
p
r
o
p
o
s
ed
f
r
am
ewo
r
k
ad
o
p
ted
a
ch
ec
k
p
o
in
t
-
b
ased
m
u
ltimo
d
al
ar
c
h
itectu
r
e
i
n
teg
r
atin
g
tr
an
s
f
o
r
m
er
-
b
ased
tem
p
o
r
al
m
o
d
ellin
g
with
C
NN
-
b
ased
v
is
u
al
p
o
u
ltr
y
ass
ess
m
en
t.
T
h
e
s
y
s
tem
was
d
esig
n
ed
to
co
m
b
in
e
en
v
ir
o
n
m
e
n
tal
m
o
n
ito
r
in
g
,
p
r
o
d
u
ctio
n
an
al
y
s
is
,
b
eh
av
io
u
r
al
ass
ess
m
en
t,
an
d
p
o
u
ltry
im
ag
e
class
if
icatio
n
with
in
a
u
n
if
ied
f
lo
ck
-
lev
e
l
p
r
ed
ictio
n
f
r
am
ewo
r
k
.
T
h
e
tr
a
n
s
f
o
r
m
er
m
o
d
el
f
u
n
ctio
n
ed
as
th
e
p
r
im
ar
y
tem
p
o
r
al
p
r
e
d
ictio
n
e
n
g
in
e
r
esp
o
n
s
ib
le
f
o
r
lear
n
in
g
s
eq
u
en
tial
f
lo
ck
p
r
o
g
r
ess
io
n
p
atter
n
s
ass
o
ciate
d
with
en
v
ir
o
n
m
e
n
tal
d
eter
io
r
a
tio
n
,
m
o
r
tality
p
r
o
g
r
ess
io
n
,
d
ec
lin
in
g
p
r
o
d
u
ctio
n
p
er
f
o
r
m
an
ce
,
an
d
elev
ate
d
in
f
ec
tio
n
r
is
k
co
n
d
itio
n
s
.
Si
m
u
ltan
eo
u
s
ly
,
th
e
C
NN
co
m
p
o
n
en
t
f
u
n
ctio
n
ed
as
a
s
u
p
p
o
r
tiv
e
v
is
u
al
p
o
u
ltry
ass
es
s
m
en
t
m
ec
h
an
is
m
r
esp
o
n
s
ib
le
f
o
r
id
e
n
tify
in
g
v
is
ib
le
p
o
u
ltry
ab
n
o
r
m
alities
ass
o
ciate
d
with
u
n
h
ea
lth
y
f
lo
ck
co
n
d
itio
n
s
[
2
]
,
[
5
]
,
[
1
5
]
.
Ou
tp
u
ts
g
en
er
ated
f
r
o
m
t
h
e
tr
an
s
f
o
r
m
er
a
n
d
C
NN
b
r
an
ch
es
wer
e
in
teg
r
ated
th
r
o
u
g
h
a
m
u
ltimo
d
al
f
u
s
io
n
lay
er
r
esp
o
n
s
ib
le
f
o
r
g
e
n
er
ati
n
g
f
in
al
f
l
o
ck
-
lev
el
in
f
ec
tio
n
r
is
k
class
if
icatio
n
s
ca
teg
o
r
ized
in
to
lo
w
-
r
is
k
,
m
e
d
iu
m
-
r
is
k
,
an
d
h
ig
h
-
r
is
k
co
n
d
iti
o
n
s
.
2
.
5
.
T
ra
ns
f
o
rm
er
-
ba
s
ed
t
empo
ra
l m
o
delli
ng
T
h
e
tr
an
s
f
o
r
m
e
r
m
o
d
el
was
im
p
lem
en
ted
to
an
al
y
s
e
ch
ec
k
p
o
in
t
-
b
ased
en
v
ir
o
n
m
en
tal,
p
r
o
d
u
ctio
n
,
an
d
b
eh
av
io
u
r
al
p
o
u
ltr
y
m
o
n
i
to
r
in
g
d
ata.
T
h
e
m
o
d
el
u
tili
ze
d
s
elf
-
atten
tio
n
m
ec
h
a
n
is
m
s
ca
p
ab
le
o
f
lear
n
in
g
tem
p
o
r
al
r
elatio
n
s
h
ip
s
b
etwe
e
n
h
is
to
r
ical
c
h
ec
k
p
o
in
t
o
b
s
er
v
atio
n
s
an
d
f
u
tu
r
e
in
f
ec
tio
n
r
is
k
o
u
tco
m
es
[
2
3
]
.
I
n
p
u
t
f
ea
tu
r
es
in
clu
d
ed
tem
p
e
r
atu
r
e,
h
u
m
id
ity
,
am
m
o
n
ia
co
n
ce
n
tr
atio
n
,
ca
r
b
o
n
d
io
x
id
e
le
v
els,
f
lo
ck
weig
h
t
p
r
o
g
r
ess
io
n
,
f
ee
d
in
tak
e
,
cu
m
u
lativ
e
m
o
r
tality
p
e
r
ce
n
tag
e,
FC
R
,
an
d
f
lo
ck
ac
tiv
ity
i
n
d
icato
r
s
.
Se
q
u
en
tial
ch
ec
k
p
o
i
n
t
o
b
s
er
v
atio
n
s
wer
e
tr
an
s
f
o
r
m
ed
in
to
tem
p
o
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al
f
ea
tu
r
e
r
ep
r
esen
tatio
n
s
b
ef
o
r
e
b
ein
g
p
r
o
ce
s
s
ed
th
r
o
u
g
h
th
e
t
r
an
s
f
o
r
m
e
r
en
c
o
d
er
lay
e
r
s
.
T
h
e
s
elf
-
atten
ti
o
n
ar
c
h
itectu
r
e
en
a
b
led
th
e
m
o
d
el
to
id
en
tify
im
p
o
r
tan
t
s
eq
u
en
tial
r
elatio
n
s
h
ip
s
ass
o
ciat
ed
with
en
v
ir
o
n
m
en
tal
s
tr
ess
,
d
ec
lin
in
g
p
r
o
d
u
ctio
n
p
er
f
o
r
m
an
ce
,
an
d
elev
ated
f
lo
c
k
h
ea
lth
r
is
k
co
n
d
itio
n
s
.
T
h
e
f
in
al
tr
an
s
f
o
r
m
er
o
u
tp
u
t
g
e
n
er
ated
tem
p
o
r
al
f
ea
tu
r
e
em
b
ed
d
in
g
s
u
s
ed
d
u
r
in
g
m
u
ltimo
d
al
f
u
s
io
n
an
d
f
in
al
f
lo
c
k
-
l
ev
el
r
is
k
p
r
ed
ictio
n
.
2
.
6
.
CNN
-
ba
s
ed
v
is
ua
l po
ultr
y
a
s
s
ess
m
ent
T
h
e
C
NN
co
m
p
o
n
e
n
t
was
in
co
r
p
o
r
ate
d
to
s
u
p
p
o
r
t v
is
u
al
p
o
u
ltry
h
ea
lth
ass
ess
m
en
t
u
s
in
g
i
m
ag
e
d
ata
g
r
o
u
p
ed
in
to
f
iv
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class
es:
h
ea
lth
y
,
lo
w
-
r
is
k
,
m
e
d
iu
m
-
r
is
k
,
h
ig
h
-
r
is
k
,
an
d
n
o
n
-
b
r
o
iler
.
I
m
a
g
es
wer
e
r
esized
to
224
×
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2
4
p
ix
els,
n
o
r
m
alize
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,
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d
au
g
m
e
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ted
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r
o
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h
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o
tatio
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f
lip
p
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zo
o
m
in
g
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an
d
b
r
i
g
h
tn
ess
ad
ju
s
tm
en
t.
T
h
e
C
NN
f
o
cu
s
ed
o
n
v
is
u
al
cu
es
s
u
ch
as
wea
k
p
o
s
tu
r
e,
f
ea
th
er
d
eter
io
r
atio
n
,
s
wellin
g
,
lo
w
ac
tiv
ity
,
an
d
p
o
u
ltry
d
is
tr
ess
in
d
icato
r
s
.
Gr
ad
ien
t
-
weig
h
te
d
class
ac
tiv
atio
n
m
a
p
p
in
g
(
Gr
ad
-
C
AM
)
ex
p
lain
ab
ilit
y
v
is
u
aliza
tio
n
s
wer
e
in
co
r
p
o
r
at
ed
to
s
h
o
w
im
ag
e
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eg
io
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s
th
at
co
n
tr
ib
u
ted
m
o
s
t stro
n
g
l
y
to
C
NN
p
r
ed
ictio
n
s
.
2
.
7
.
M
ultim
o
da
l
f
us
io
n pro
c
edure
T
h
e
o
u
tp
u
ts
g
en
er
ated
b
y
th
e
tr
an
s
f
o
r
m
er
a
n
d
C
NN
m
o
d
el
s
wer
e
co
m
b
in
ed
th
r
o
u
g
h
d
ec
is
io
n
-
lev
el
m
u
ltimo
d
al
f
u
s
io
n
.
T
h
e
tr
an
s
f
o
r
m
er
p
r
o
d
u
ce
d
p
r
o
b
ab
ilit
y
s
co
r
es
f
o
r
lo
w
-
,
m
ed
iu
m
-
,
a
n
d
h
ig
h
-
r
is
k
f
lo
c
k
Evaluation Warning : The document was created with Spire.PDF for Python.
C
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m
p
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I
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f
T
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I
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2722
-
3
2
2
1
E
a
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ly
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s
ch
erich
ia
co
li p
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ed
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b
r
o
iler
ch
icke
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s
(
N
ico
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C
h
imw
a
ma
fu
ku
)
317
ca
teg
o
r
ies
f
r
o
m
c
h
ec
k
p
o
in
t
m
o
n
ito
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ata,
wh
ile
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NN
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ab
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ag
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f
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al
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ass
if
icatio
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h
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f
u
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io
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tr
ateg
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p
r
eser
v
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in
te
r
p
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wh
ile
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m
b
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i
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o
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al
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id
e
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ce
f
o
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d
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is
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u
p
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r
t.
2
.
8
.
M
o
del
t
ra
ini
ng
a
nd
t
est
ing
pro
ce
du
re
T
h
e
ch
ec
k
p
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in
t
-
b
ased
tem
p
o
r
al
d
ataset
was
d
iv
id
ed
u
s
in
g
an
8
0
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ain
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test
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p
lit,
r
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in
7
2
,
0
0
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tr
ain
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g
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ec
o
r
d
s
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d
1
8
,
0
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0
test
in
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r
ec
o
r
d
s
f
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ap
p
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im
ately
9
0
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0
0
0
lo
n
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-
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o
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at
o
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s
er
v
a
tio
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s
.
T
h
e
tr
an
s
f
o
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m
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m
o
d
el
was
tr
ain
ed
with
th
e
Ad
am
o
p
tim
iz
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o
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s
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NN
m
o
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el
was
ev
alu
ated
o
n
2
4
9
im
a
g
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ac
r
o
s
s
h
ea
lth
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,
h
i
g
h
-
r
is
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,
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r
i
s
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,
m
ed
iu
m
-
r
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,
an
d
n
o
n
-
b
r
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iler
class
es.
Mo
d
el
p
er
f
o
r
m
an
ce
was
ev
alu
ated
u
s
in
g
ac
cu
r
ac
y
,
p
r
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io
n
,
r
ec
all,
F1
-
s
co
r
e,
co
n
f
u
s
io
n
m
atr
ices,
co
n
f
id
en
ce
s
co
r
es,
an
d
Gr
ad
-
C
AM
v
is
u
al
ex
p
lan
atio
n
o
u
tp
u
ts
.
2
.
9
.
Da
s
hb
o
a
rd
im
plem
ent
a
t
io
n
T
h
e
d
ev
elo
p
ed
m
u
ltimo
d
al
p
o
u
ltry
h
ea
lth
m
o
n
ito
r
in
g
f
r
am
ewo
r
k
was
im
p
lem
en
ted
with
in
a
s
tr
ea
m
l
it
-
b
ased
d
ash
b
o
ar
d
en
v
ir
o
n
m
en
t
d
esig
n
ed
to
s
u
p
p
o
r
t
p
r
ac
tical
f
lo
ck
m
o
n
ito
r
i
n
g
a
n
d
in
tellig
en
t
d
is
ea
s
e
s
u
r
v
eillan
ce
.
T
h
e
d
ash
b
o
ar
d
en
ab
led
u
s
er
s
to
in
p
u
t
f
lo
ck
-
lev
e
l
en
v
ir
o
n
m
en
tal
an
d
p
r
o
d
u
ctio
n
v
a
r
iab
les,
u
p
lo
ad
p
o
u
ltr
y
im
ag
es
f
o
r
v
is
u
al
ass
ess
m
en
t,
an
d
r
ec
eiv
e
f
l
o
ck
-
lev
el
in
f
ec
tio
n
r
is
k
p
r
ed
ic
tio
n
s
to
g
eth
er
with
en
v
ir
o
n
m
en
tal
aler
ts
an
d
v
e
ter
in
ar
y
a
d
v
is
o
r
y
p
r
o
m
p
ts
.
Ad
d
itio
n
al
f
u
n
ctio
n
alities
in
co
r
p
o
r
ated
in
t
o
th
e
d
ash
b
o
ar
d
in
clu
d
ed
c
h
ec
k
p
o
in
t
p
r
o
g
r
ess
io
n
m
o
n
ito
r
in
g
,
co
n
f
id
en
ce
s
co
r
in
g
,
Gr
a
d
-
C
AM
ex
p
lain
ab
ilit
y
o
u
tp
u
ts
,
an
d
em
er
g
en
cy
r
ea
s
s
es
s
m
en
t
ca
p
ab
ilit
y
.
T
h
ese
f
ea
tu
r
es
im
p
r
o
v
ed
th
e
p
r
a
ctica
l
u
s
ab
ilit
y
an
d
in
ter
p
r
etab
ilit
y
o
f
th
e
d
e
v
elo
p
ed
f
r
am
ewo
r
k
with
in
c
o
m
m
er
ci
al
p
o
u
ltry
p
r
o
d
u
ctio
n
e
n
v
ir
o
n
m
en
ts
.
2
.
1
0
.
M
et
ho
do
lo
g
ica
l
lim
it
a
t
i
o
ns
a
nd
v
a
lid
a
t
io
n sco
pe
T
h
e
s
tu
d
y
r
elied
o
n
ch
ec
k
p
o
in
t
-
b
ased
p
r
o
d
u
ctio
n
r
ec
o
r
d
s
an
d
m
an
u
ally
co
llected
m
o
n
ito
r
in
g
v
ar
iab
les,
wh
ich
m
ay
in
tr
o
d
u
c
e
s
am
p
lin
g
b
ias,
o
b
s
er
v
er
b
ias,
an
d
s
ite
-
s
p
ec
if
ic
m
an
a
g
em
en
t
ef
f
ec
ts
.
Alth
o
u
g
h
co
n
v
er
s
io
n
to
lo
n
g
-
f
o
r
m
at
s
e
q
u
en
tial
o
b
s
er
v
atio
n
s
i
n
cr
ea
s
e
d
th
e
n
u
m
b
er
o
f
tr
ain
in
g
s
am
p
les,
it
d
id
n
o
t
r
em
o
v
e
th
e
n
ee
d
f
o
r
lar
g
er
m
u
lti
-
f
ar
m
v
alid
atio
n
u
s
in
g
i
n
d
ep
en
d
en
tly
co
llected
co
m
m
e
r
cial
d
atasets
.
Fu
tu
r
e
wo
r
k
s
h
o
u
ld
r
e
p
licate
th
e
f
r
am
ewo
r
k
u
s
in
g
au
to
m
ate
d
I
o
T
s
en
s
o
r
s
tr
ea
m
s
,
co
n
tin
u
o
u
s
en
v
ir
o
n
m
e
n
tal
lo
g
g
in
g
,
an
d
lar
g
er
im
a
g
e
d
atasets
co
llected
ac
r
o
s
s
d
if
f
er
en
t
b
r
e
ed
s
,
h
o
u
s
in
g
s
y
s
tem
s
,
p
r
o
d
u
ctio
n
s
ea
s
o
n
s
,
an
d
g
eo
g
r
a
p
h
ic
r
e
g
io
n
s
.
C
o
m
p
ar
a
tiv
e
ev
alu
atio
n
a
g
ain
s
t
lo
n
g
s
h
o
r
t
-
ter
m
m
em
o
r
y
(
L
STM
)
n
etwo
r
k
s
,
tem
p
o
r
al
co
n
v
o
l
u
tio
n
al
n
etwo
r
k
s
,
atte
n
tio
n
-
b
ased
h
y
b
r
id
s
,
an
d
f
e
d
er
ated
lear
n
in
g
ar
ch
itectu
r
es
wo
u
ld
f
u
r
th
er
s
tr
en
g
th
en
m
eth
o
d
o
lo
g
ical
r
ig
o
r
an
d
clar
i
f
y
t
h
e
r
elativ
e
ad
v
an
tag
e
o
f
th
e
p
r
o
p
o
s
ed
tr
an
s
f
o
r
m
er
-
C
NN
f
u
s
io
n
s
tr
ateg
y
.
3.
RE
SU
L
T
S
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
ex
p
er
im
en
tal
r
esu
lts
o
b
tain
ed
f
r
o
m
ev
alu
atin
g
th
e
p
r
o
p
o
s
ed
c
h
ec
k
p
o
i
n
t
-
b
ased
m
u
ltimo
d
al
tr
a
n
s
f
o
r
m
er
-
C
NN
p
o
u
ltry
h
ea
lth
m
o
n
ito
r
in
g
f
r
am
ewo
r
k
.
R
esu
lts
ar
e
r
ep
o
r
ted
f
ir
s
t,
f
o
llo
wed
b
y
a
s
ep
ar
ate
d
is
cu
s
s
io
n
th
at
in
ter
p
r
ets
th
e
f
in
d
in
g
s
in
r
elatio
n
t
o
p
r
io
r
w
o
r
k
,
m
eth
o
d
o
lo
g
ical
lim
itatio
n
s
,
ex
p
lain
ab
ilit
y
,
an
d
p
r
ac
ti
ca
l d
ep
lo
y
m
en
t.
3
.
1
.
Da
t
a
s
et
risk
dis
t
ributio
n a
na
ly
s
is
T
h
e
d
ataset
r
is
k
d
is
tr
ib
u
tio
n
an
aly
s
is
r
ev
ea
led
th
at
th
e
c
h
e
ck
p
o
in
t
-
b
ased
f
lo
c
k
m
o
n
ito
r
i
n
g
d
ataset
co
n
tain
ed
v
a
r
y
in
g
p
r
o
p
o
r
tio
n
s
o
f
lo
w
-
r
is
k
,
m
e
d
iu
m
-
r
is
k
,
an
d
h
ig
h
-
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m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
,
Vo
l.
7
,
No
.
3
,
No
v
em
b
er
20
26
:
3
1
4
-
324
320
Am
m
o
n
ia
c
o
n
ce
n
tr
atio
n
d
e
m
o
n
s
tr
ated
p
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ticu
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ly
s
tr
o
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g
r
elatio
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h
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with
ca
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b
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n
d
io
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m
u
latio
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d
m
o
r
tality
p
r
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r
ess
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,
s
u
g
g
est
in
g
th
at
in
ad
eq
u
ate
v
en
tilatio
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d
p
o
o
r
en
v
ir
o
n
m
en
tal
m
an
ag
em
en
t
co
n
tr
ib
u
te
s
ig
n
if
ican
tly
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war
d
d
ec
lin
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co
n
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itio
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s
.
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lev
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tem
p
er
atu
r
e
lev
els
also
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em
o
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tr
ated
p
o
s
itiv
e
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elatio
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s
h
ip
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with
in
cr
ea
s
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g
m
o
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tality
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n
tag
e
an
d
wo
r
s
en
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g
p
r
o
d
u
ctio
n
ef
f
icien
cy
.
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h
ese
f
i
n
d
in
g
s
r
ei
n
f
o
r
ce
th
e
b
io
lo
g
ical
r
elev
a
n
ce
o
f
en
v
ir
o
n
m
e
n
tal
m
o
n
ito
r
i
n
g
v
ar
iab
les
with
in
in
tellig
en
t
p
o
u
ltry
d
is
ea
s
e
s
u
r
v
eillan
ce
s
y
s
tem
s
an
d
s
u
p
p
o
r
t
th
e
in
cl
u
s
io
n
o
f
e
n
v
ir
o
n
m
en
t
al
in
d
icato
r
s
with
i
n
th
e
p
r
o
p
o
s
ed
m
u
ltim
o
d
al
tr
an
s
f
o
r
m
er
–
C
NN
f
r
am
ewo
r
k
.
T
h
e
co
r
r
elatio
n
a
n
aly
s
is
f
u
r
th
er
d
em
o
n
s
tr
ated
th
at
en
v
ir
o
n
m
en
tal
s
tr
ess
co
n
d
itio
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s
ar
e
clo
s
ely
in
ter
co
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n
ec
ted
with
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u
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d
ec
lin
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an
d
f
lo
ck
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eter
io
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n
.
C
o
n
s
eq
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n
tly
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o
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tal
m
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ay
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id
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ly
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m
atio
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p
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le
o
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u
p
p
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tin
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ac
tiv
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ltr
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ci
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s
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es
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co
m
m
er
cial
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r
o
iler
f
ar
m
in
g
en
v
ir
o
n
m
en
ts
.
Fig
u
r
e
5
.
E
n
v
ir
o
n
m
en
tal
co
r
r
e
lat
io
n
3
.
6
.
A
m
mo
nia
co
ncent
ra
t
i
o
n a
nd
m
o
rt
a
lity
re
la
t
io
ns
hip
T
h
e
am
m
o
n
ia
co
n
ce
n
tr
atio
n
an
d
m
o
r
tality
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elatio
n
s
h
ip
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aly
s
is
d
em
o
n
s
tr
ated
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at
in
cr
ea
s
in
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am
m
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ia
lev
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wer
e
g
e
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er
al
ly
ass
o
ciate
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l
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ck
m
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ce
n
ta
g
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ac
r
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s
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th
e
m
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ito
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ed
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ctio
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ec
k
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i
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ts
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ill
u
s
tr
ated
in
Fig
u
r
e
6
,
lo
wer
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m
m
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ia
co
n
ce
n
tr
atio
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wer
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r
im
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ile
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m
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ia
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em
o
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ated
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ar
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n
d
wo
r
s
en
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g
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k
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o
n
d
itio
n
s
.
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h
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m
o
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o
n
c
en
t
r
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lev
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e
co
m
m
o
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l
y
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ciate
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ess
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ity
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am
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tif
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atin
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f
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n
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p
ab
le
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co
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tr
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b
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elev
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in
f
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tio
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with
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m
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b
r
o
iler
p
r
o
d
u
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n
en
v
ir
o
n
m
en
ts
.
Evaluation Warning : The document was created with Spire.PDF for Python.
C
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m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
I
SS
N:
2722
-
3
2
2
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Fig
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6
.
Am
m
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m
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3
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7
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la
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u
r
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.
Flo
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atr
ix
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
7
2
2
-
3
2
2
1
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
,
Vo
l.
7
,
No
.
3
,
No
v
em
b
er
20
26
:
3
1
4
-
324
322
T
h
e
lo
w
-
r
is
k
tem
p
o
r
al
ca
teg
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r
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lib
r
ated
d
ec
is
io
n
th
r
esh
o
ld
s
,
an
d
atte
n
tio
n
-
weig
h
t
an
al
y
s
is
to
im
p
r
o
v
e
s
ep
ar
atio
n
o
f
in
ter
m
e
d
iate
an
d
s
ev
er
e
r
is
k
co
n
d
itio
n
s
.
4.
DIS
CU
SS
I
O
N
4
.
1
.
I
nte
rpre
t
a
t
io
n
o
f
o
v
er
a
l
l f
ind
ing
s
Ov
er
all,
th
e
ex
p
e
r
im
en
tal
ev
a
lu
atio
n
d
em
o
n
s
tr
ated
th
at
ch
e
ck
p
o
in
t
-
b
ased
tem
p
o
r
al
m
o
d
e
llin
g
was
h
ig
h
ly
ef
f
ec
tiv
e
f
o
r
f
lo
c
k
-
lev
el
r
is
k
p
r
ed
ictio
n
,
with
th
e
tr
an
s
f
o
r
m
er
ac
h
iev
in
g
9
9
.
9
6
%
ac
cu
r
ac
y
o
n
1
8
,
0
0
0
test
in
g
o
b
s
er
v
atio
n
s
.
T
h
e
C
N
N
co
n
tr
ib
u
ted
c
o
m
p
lem
e
n
tar
y
v
is
u
al
ev
id
en
ce
,
ac
h
iev
in
g
9
5
.
5
8
%
ac
cu
r
ac
y
o
n
2
4
9
im
ag
es
an
d
p
er
f
o
r
m
in
g
s
tr
o
n
g
est
o
n
h
ea
lth
y
,
h
ig
h
-
r
is
k
,
an
d
n
o
n
-
b
r
o
iler
class
es.
T
o
g
eth
er
,
t
h
e
m
o
d
els
ca
p
tu
r
ed
r
elatio
n
s
h
ip
s
b
etwe
e
n
en
v
ir
o
n
m
e
n
tal
d
eter
io
r
atio
n
,
p
r
o
d
u
ctio
n
d
ec
lin
e,
b
eh
a
v
io
u
r
al
ab
n
o
r
m
aliti
es,
an
d
v
is
ib
le
h
ea
lth
c
u
es.
T
h
e
r
esu
lts
f
u
r
t
h
er
d
e
m
o
n
s
tr
ated
th
e
p
r
ac
tical
f
ea
s
ib
ilit
y
o
f
ap
p
ly
in
g
m
u
ltimo
d
al
AI
t
ec
h
n
iq
u
es
with
in
p
r
ec
is
io
n
p
o
u
ltry
f
a
r
m
in
g
an
d
in
tellig
en
t
liv
esto
ck
h
ea
lth
m
o
n
ito
r
in
g
s
y
s
tem
s
.
T
h
e
d
ev
elo
p
ed
f
r
am
ewo
r
k
th
er
e
f
o
r
e
p
r
o
v
id
e
s
s
t
r
o
n
g
p
o
ten
tial
f
o
r
s
u
p
p
o
r
tin
g
p
r
o
ac
tiv
e
f
l
o
ck
h
ea
lth
m
an
ag
em
en
t,
ea
r
l
y
d
is
ea
s
e
s
u
r
v
eillan
ce
,
an
d
in
tellig
en
t
p
o
u
ltry
p
r
o
d
u
ctio
n
d
ec
i
s
io
n
-
m
ak
in
g
with
in
c
o
m
m
er
ci
al
b
r
o
iler
f
ar
m
i
n
g
en
v
ir
o
n
m
en
ts
.
C
o
m
p
ar
ed
wit
h
p
r
io
r
p
o
u
ltry
AI
s
tu
d
ies
th
a
t
em
p
h
asize
s
in
g
le
d
at
a
s
tr
ea
m
s
s
u
ch
as
im
ag
es,
au
d
io
,
o
r
en
v
ir
o
n
m
en
tal
s
en
s
o
r
s
,
th
e
p
r
esen
t
f
r
am
ewo
r
k
c
o
n
tr
ib
u
tes
a
ch
ec
k
p
o
i
n
t
-
b
ased
m
u
ltimo
d
al
d
esig
n
th
at
lin
k
s
tem
p
o
r
al
p
r
o
d
u
ctio
n
p
r
o
g
r
ess
io
n
with
C
N
N
-
b
ased
v
is
u
al
ass
e
s
s
m
en
t
an
d
XAI
o
u
tp
u
ts
[
1
3
]
–
[
1
8
]
.
T
h
is
in
teg
r
atio
n
is
th
e
m
ain
n
o
v
elty
o
f
th
e
s
tu
d
y
:
it
s
h
if
ts
t
h
e
p
r
ed
ictio
n
task
f
r
o
m
late
s
y
m
p
to
m
r
ec
o
g
n
itio
n
to
war
d
p
r
o
ac
tiv
e
f
lo
c
k
-
lev
el
r
i
s
k
esti
m
atio
n
s
u
p
p
o
r
ted
b
y
i
n
ter
p
r
etab
le
ev
i
d
en
ce
.
T
h
e
ex
p
lain
ab
ilit
y
o
u
tp
u
ts
s
h
o
u
ld
b
e
in
ter
p
r
eted
alo
n
g
s
id
e
th
e
n
u
m
er
ical
r
is
k
p
r
ed
ictio
n
s
r
a
th
er
th
an
as
s
ep
ar
ate
v
is
u
al
ar
tifa
cts.
Gr
ad
-
C
AM
v
is
u
aliza
tio
n
s
ca
n
in
d
icate
wh
eth
e
r
th
e
C
NN
b
r
an
c
h
f
o
c
u
s
es
o
n
b
io
lo
g
ically
m
ea
n
in
g
f
u
l
r
eg
i
o
n
s
s
u
ch
as
p
o
s
tu
r
e
,
f
ea
t
h
e
r
co
n
d
itio
n
,
an
d
v
is
ib
le
d
is
tr
ess
,
wh
ile
tem
p
o
r
al
atten
tio
n
p
atter
n
s
ca
n
h
elp
id
e
n
tify
wh
ich
ch
ec
k
p
o
in
t v
ar
ia
b
les co
n
tr
ib
u
te
m
o
s
t stro
n
g
ly
to
th
e
f
in
al
r
is
k
class
.
C
o
m
b
in
in
g
th
ese
ex
p
lan
atio
n
ch
a
n
n
els
s
u
p
p
o
r
ts
tr
u
s
t,
en
ab
les
v
eter
in
a
r
y
r
ev
iew,
an
d
h
elp
s
f
a
r
m
er
s
u
n
d
er
s
tan
d
wh
eth
er
r
is
k
is
d
r
iv
en
p
r
im
ar
ily
b
y
en
v
i
r
o
n
m
en
tal
d
eter
io
r
atio
n
,
p
r
o
d
u
ctio
n
d
ec
lin
e,
o
r
v
is
u
al
ab
n
o
r
m
ality
.
Fro
m
a
d
ep
lo
y
m
en
t
p
er
s
p
ec
t
iv
e,
th
e
f
r
am
ew
o
r
k
ca
n
in
f
o
r
m
I
o
T
-
e
n
ab
led
p
o
u
ltr
y
m
o
n
ito
r
in
g
b
y
co
n
n
ec
tin
g
a
m
m
o
n
ia,
te
m
p
er
a
tu
r
e,
h
u
m
i
d
i
ty
,
ca
r
b
o
n
d
io
x
id
e,
wate
r
in
tak
e,
f
ee
d
i
n
tak
e,
m
o
r
tality
,
an
d
im
a
g
e
f
ee
d
s
to
a
clo
u
d
-
b
ased
d
ash
b
o
ar
d
f
o
r
r
ea
l
-
tim
e
aler
ts
.
Su
c
h
a
s
y
s
tem
co
u
ld
s
u
p
p
o
r
t
f
ar
m
-
lev
el
in
ter
v
en
tio
n
d
ec
is
io
n
s
,
r
eg
io
n
al
d
is
ea
s
e
s
u
r
v
eillan
ce
,
an
d
n
atio
n
al
liv
esto
ck
h
ea
lth
p
o
licy
b
y
g
en
e
r
atin
g
ea
r
lier
war
n
i
n
g
s
ig
n
als
f
o
r
en
v
ir
o
n
m
en
tal
s
tr
e
s
s
an
d
p
o
s
s
ib
le
b
ac
ter
ial
d
is
ea
s
e
p
r
o
g
r
ess
io
n
.
C
lo
u
d
d
e
p
lo
y
m
en
t
an
d
f
ed
er
ate
d
lear
n
in
g
co
u
l
d
f
u
r
t
h
er
allo
w
f
ar
m
s
to
im
p
r
o
v
e
s
h
ar
ed
m
o
d
e
ls
with
o
u
t
ex
p
o
s
in
g
s
en
s
itiv
e
p
r
o
d
u
ctio
n
r
ec
o
r
d
s
,
wh
ile
r
ein
f
o
r
ce
m
en
t
lear
n
in
g
m
ay
s
u
p
p
o
r
t
f
u
tu
r
e
d
ec
is
io
n
r
u
les
f
o
r
v
en
tilatio
n
ad
j
u
s
tm
en
t,
litt
er
m
an
ag
e
m
en
t
,
an
d
v
eter
in
a
r
y
r
esp
o
n
s
e
s
tr
ateg
ies [
2
5
]
.
5.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
d
ev
elo
p
e
d
an
d
ev
alu
ated
a
ch
ec
k
p
o
in
t
-
b
ased
m
u
ltimo
d
al
tr
an
s
f
o
r
m
e
r
-
C
NN
f
r
am
ewo
r
k
f
o
r
ea
r
ly
f
lo
c
k
-
lev
el
p
r
ed
ictio
n
o
f
E
.
co
li
in
f
ec
tio
n
in
b
r
o
i
ler
ch
ick
en
s
.
T
h
e
f
in
d
in
g
s
s
u
p
p
o
r
t
th
e
v
alu
e
o
f
m
u
ltimo
d
al
lear
n
in
g
,
XAI
,
an
d
d
ash
b
o
ar
d
-
b
ased
d
ec
is
io
n
s
u
p
p
o
r
t
f
o
r
p
r
o
ac
tiv
e
p
o
u
ltry
h
ea
lth
m
an
ag
em
en
t.
T
h
e
f
r
am
ewo
r
k
ca
n
b
e
ad
a
p
t
ed
b
ey
o
n
d
E
.
c
o
li
p
r
e
d
ictio
n
to
o
th
e
r
p
o
u
ltry
d
is
ea
s
es
wh
er
e
en
v
ir
o
n
m
en
tal
s
tr
ess
,
p
r
o
d
u
ctio
n
d
ec
lin
e,
b
eh
av
io
u
r
al
ch
an
g
es,
an
d
v
is
ib
le
s
y
m
p
to
m
s
d
ev
elo
p
p
r
o
g
r
ess
iv
ely
o
v
er
tim
e
,
in
clu
d
in
g
r
esp
ir
ato
r
y
d
is
ea
s
e,
av
ian
in
f
lu
en
za
r
is
k
m
o
n
ito
r
i
n
g
,
an
d
b
r
o
a
d
er
f
lo
ck
welf
ar
e
s
u
r
v
ei
llan
ce
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
v
alid
ate
th
e
a
p
p
r
o
ac
h
o
n
lar
g
er
m
u
lti
-
f
ar
m
d
atasets
,
in
teg
r
ate
au
to
m
ated
I
o
T
an
d
clo
u
d
-
b
ased
d
ata
s
tr
ea
m
s
,
co
m
p
ar
e
ad
d
iti
o
n
al
d
ee
p
lear
n
in
g
ar
c
h
itectu
r
es
s
u
ch
as
L
STM
s
an
d
h
y
b
r
id
atten
tio
n
m
o
d
els,
an
d
s
tr
en
g
th
e
n
ex
p
lain
ab
ilit
y
o
u
tp
u
ts
f
o
r
p
r
ac
tical
v
eter
i
n
ar
y
an
d
p
o
licy
u
s
e.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
e
au
th
o
r
s
r
ec
eiv
ed
n
o
f
in
a
n
cial
s
u
p
p
o
r
t
f
o
r
th
e
r
esear
ch
,
au
th
o
r
s
h
ip
,
an
d
/o
r
p
u
b
licatio
n
o
f
th
is
ar
ticle.
Evaluation Warning : The document was created with Spire.PDF for Python.
C
o
m
p
u
t Sci
I
n
f
T
ec
h
n
o
l
I
SS
N:
2722
-
3
2
2
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a
r
ly
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s
ch
erich
ia
co
li p
r
ed
ictio
n
in
b
r
o
iler
ch
icke
n
s
(
N
ico
le
C
h
imw
a
ma
fu
ku
)
323
AUTHO
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u
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C
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to
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a
x
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y
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th
o
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Aut
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[
1
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