I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
p
ute
r
E
ng
in
ee
ring
(
I
J
E
CE
)
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
,
p
p
.
2
4
1
9
~
2
4
3
2
I
SS
N:
2
0
8
8
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v8
i
4
.
p
p
2
4
1
9
-
2432
2419
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
co
r
e
.c
o
m/
jo
u
r
n
a
ls
/in
d
ex
.
p
h
p
/
I
JE
C
E
G
o
o
d P
a
ra
m
ete
rs for P
SO
in
O
pti
m
i
z
i
ng
La
y
ing
H
e
n Diet
G
u
s
t
i A
h
m
a
d F
a
n
s
hu
ri
A
lf
a
risy
1
,
Wa
y
a
n F
irda
us
M
a
hm
ud
y
2
,
M
uh
a
m
m
a
d H
a
li
m
Na
t
s
ir
3
1,
2
F
a
c
u
lt
y
o
f
Co
m
p
u
ter S
c
ien
c
e
,
Un
iv
e
rsitas
Bra
w
ij
a
y
a
,
In
d
o
n
e
sia
3
F
a
c
u
lt
y
o
f
A
n
i
m
a
l
Hu
sb
a
n
d
ry
,
U
n
iv
e
rsitas
Bra
w
ij
a
y
a
,
In
d
o
n
e
sia
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Feb
1
1
,
2
0
1
8
R
ev
i
s
ed
Ma
y
1
2
,
2
0
1
8
A
cc
ep
ted
J
u
n
2
,
2
0
1
8
M
a
n
u
a
l
f
o
rm
u
latio
n
o
f
p
o
u
l
try
d
iet
b
y
tak
in
g
in
to
a
c
c
o
u
n
t
t
h
e
f
u
lfi
ll
m
e
n
t
o
f
a
ll
n
u
tri
e
n
ts
re
q
u
irem
e
n
t
w
it
h
le
a
st
c
o
st
is
a
d
iff
icu
lt
tas
k
.
P
a
rti
c
le
S
w
a
r
m
Op
ti
m
iza
ti
o
n
(P
S
O)
sh
o
w
s
p
ro
m
isin
g
tec
h
n
iq
u
e
to
so
lv
e
th
is
p
ro
b
lem
.
Ho
w
e
v
e
r,
th
e
re
is
a
lac
k
o
f
stu
d
y
in
g
a
g
o
o
d
p
a
ra
m
e
ter
f
o
r
P
S
O
t
o
so
lv
e
f
e
e
d
f
o
r
m
u
latio
n
p
r
o
b
lem
sin
c
e
P
S
O
is
se
n
siti
v
e
to
c
o
n
tro
l
p
a
ra
m
e
ter
w
h
ich
d
e
p
e
n
d
s
o
n
t
h
e
p
r
o
b
lem
.
T
h
e
r
e
f
o
re
,
th
is
st
u
d
y
in
v
e
stig
a
tes
g
o
o
d
s
w
a
r
m
siz
e
,
to
tal
it
e
ra
ti
o
n
s,
a
c
c
e
lera
ti
o
n
c
o
e
ff
icie
n
ts,
a
n
d
in
e
rti
a
w
e
ig
h
t
to
p
ro
d
u
c
e
a
b
e
tt
e
r
f
o
rm
u
la.
P
S
O
w
it
h
p
ro
p
o
s
e
d
g
o
o
d
p
a
ra
m
e
ters
is
c
o
m
p
a
re
d
w
it
h
o
th
e
r
p
a
ra
m
e
ters
.
T
h
e
o
b
tain
e
d
re
su
lt
s
h
o
w
s
th
a
t
P
S
O
w
it
h
g
o
o
d
p
a
ra
m
e
ters
c
h
o
ice
p
ro
d
u
c
e
s
th
e
h
ig
h
e
st
f
it
n
e
ss
.
F
u
r
th
e
rm
o
re
,
g
o
o
d
p
a
ra
m
e
ter
s
o
f
P
S
O
c
a
n
b
e
u
se
d
a
s
a
re
f
e
re
n
c
e
f
o
r
a
so
f
t
wa
re
d
e
v
e
lo
p
e
r
a
n
d
f
o
r
f
u
rth
e
r
re
se
a
rc
h
to
o
p
ti
m
ize
p
o
u
l
try
d
iet
u
sin
g
P
S
O
.
K
ey
w
o
r
d
:
Feed
Fo
r
m
u
lat
io
n
P
ar
ticle
S
w
ar
m
Op
ti
m
iza
tio
n
Go
o
d
P
ar
am
eter
Co
p
y
rig
h
t
©
2
0
1
8
In
stit
u
te o
f
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
rin
g
a
n
d
S
c
ien
c
e
.
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
W
ay
a
n
Fird
au
s
Ma
h
m
u
d
y
,
Facu
lt
y
o
f
C
o
m
p
u
ter
Scien
ce
,
Un
i
v
er
s
ita
s
B
r
a
w
ij
a
y
a,
J
ln
.
Vete
r
an
No
.
8
,
Keta
w
a
n
g
g
ed
e,
Kec
am
ata
n
L
o
w
o
k
w
ar
u
,
M
alan
g
,
I
n
d
o
n
esia.
E
m
ail:
w
a
y
a
n
f
m
@
u
b
.
ac
.
id
1.
I
NT
RO
D
UCT
I
O
N
Feed
th
at
g
i
v
en
o
n
d
ail
y
b
asis
to
p
o
u
ltr
y
li
k
e
la
y
i
n
g
h
e
n
s
i
s
ess
e
n
tial
f
o
r
g
r
o
w
t
h
,
r
ep
r
o
d
u
ctio
n
,
an
d
h
ea
lt
h
.
Feed
s
h
o
u
ld
p
r
o
v
id
e
th
e
n
u
tr
ie
n
t
s
th
a
t
f
u
l
f
ill
t
h
e
n
u
tr
ien
t
'
s
r
eq
u
ir
e
m
e
n
t
f
o
r
an
an
i
m
a
l.
I
n
p
o
u
ltr
y
d
iets
,
th
e
es
s
e
n
tial
n
u
tr
ien
t
s
ar
e
p
r
o
tein
,
a
m
i
n
o
ac
id
s
,
ca
r
b
o
h
y
d
r
a
tes,
f
at
s
,
m
i
n
er
als,
a
n
d
v
ita
m
i
n
s
.
T
h
ese
n
u
tr
ien
ts
ar
e
i
m
p
o
r
tan
t
f
o
r
p
r
o
d
u
cin
g
m
ea
t
a
n
d
eg
g
s
[
1
]
.
E
v
er
y
cla
s
s
o
f
an
i
m
a
ls
w
i
th
d
if
f
er
en
t
s
tag
e
o
r
ag
e
r
eq
u
ir
e
d
if
f
er
e
n
t
n
u
tr
ie
n
t
r
eq
u
ir
e
m
e
n
t
s
th
at
n
ee
d
s
d
i
f
f
er
en
t
f
o
r
m
u
la.
W
h
en
w
e
tak
e
in
to
ac
co
u
n
t
t
h
e
co
s
t
o
f
f
ee
d
a
n
d
s
ev
er
al
n
u
tr
ie
n
t
r
eq
u
ir
e
m
e
n
ts
,
it
b
ec
o
m
es
a
co
m
p
lica
ted
task
to
f
i
n
d
th
e
o
p
ti
m
u
m
f
o
r
m
u
la
th
at
s
at
is
f
y
all
n
u
tr
ie
n
t r
eq
u
ir
e
m
e
n
ts
w
it
h
lea
s
t c
o
s
t
[
2
]
.
A
f
ee
d
in
tak
e
b
y
la
y
i
n
g
h
en
s
w
il
l
af
f
ec
t
th
e
e
g
g
s
p
r
o
d
u
ctio
n
an
d
p
r
ice.
I
t
ca
n
b
e
o
b
tain
ed
o
n
l
y
f
r
o
m
a
g
o
o
d
f
o
r
m
u
la
w
h
ic
h
f
u
l
f
ill
s
th
e
n
u
tr
ie
n
t
r
eq
u
ir
e
m
e
n
t
s
.
U
n
f
o
r
t
u
n
ate
l
y
,
t
h
e
h
ig
h
est
co
s
t
p
r
o
d
u
ctio
n
is
in
t
h
e
f
ee
d
ap
p
r
o
x
i
m
atel
y
6
5
-
7
0
%
o
f
all
co
s
t
p
r
o
d
u
ctio
n
.
T
h
e
f
ee
d
an
d
o
th
er
co
s
t
h
a
v
e
a
p
o
s
iti
v
e
co
r
r
elatio
n
to
th
e
eg
g
s
p
r
ice.
I
f
t
h
e
p
r
o
d
u
ce
r
ca
n
lo
w
er
th
e
co
s
t
w
it
h
o
p
ti
m
u
m
f
ee
d
’
s
f
o
r
m
u
la,
it
w
ill
b
ec
o
m
e
co
s
t
-
s
a
v
in
g
f
o
r
h
i
m
a
n
d
m
a
y
d
ec
r
ea
s
e
th
e
e
g
g
s
p
r
ice
[
3
]
.
I
n
Fo
r
m
u
lati
n
g
th
e
o
p
ti
m
u
m
f
o
r
m
u
la
,
s
e
v
er
al
f
ac
to
r
s
m
u
s
t
b
e
co
n
s
id
er
ed
s
i
m
u
lta
n
eo
u
s
l
y
li
k
e
t
h
e
av
ailab
ilit
y
o
f
lo
ca
l
r
eso
u
r
ce
s
,
f
lu
ct
u
ati
n
g
p
r
ices,
an
d
p
r
o
p
er
n
u
tr
itio
n
.
A
n
u
m
b
er
o
f
m
a
n
u
al
f
o
r
m
u
latio
n
s
u
c
h
as
tr
ial
a
n
d
er
r
o
r
,
s
i
m
u
ltan
eo
u
s
alg
eb
r
aic
eq
u
a
tio
n
s
,
p
ea
r
s
o
n
’
s
s
q
u
ar
e
m
et
h
o
d
h
a
v
e
f
a
il
to
p
r
o
d
u
ce
o
p
tim
u
m
f
o
r
m
u
la
d
u
e
to
co
m
p
le
x
it
y
w
h
e
n
co
n
s
id
er
in
g
m
a
n
y
n
u
tr
ien
ts
a
n
d
tak
in
g
i
n
t
o
ac
co
u
n
t
th
e
f
ee
d
’
s
p
r
ice.
An
o
th
er
ap
p
r
o
ac
h
,
s
to
ch
a
s
ti
c
ap
p
r
o
ac
h
,
h
as
b
ee
n
e
m
p
l
o
y
ed
b
y
p
r
ev
io
u
s
r
e
s
ea
r
ch
e
s
s
u
ch
a
s
,
C
h
an
c
e
C
o
n
s
tr
ain
ed
P
r
o
g
r
a
m
m
i
n
g
(
C
C
P
)
,
Qu
ad
r
atic
P
r
o
g
r
a
m
m
i
n
g
(
QP
)
,
an
d
R
i
s
k
Fo
r
m
u
la
tio
n
(
R
P
)
.
C
C
P
i
s
n
o
n
li
n
ea
r
m
et
h
o
d
th
at
u
s
ed
f
o
r
f
ee
d
f
o
r
m
u
la
tio
n
b
u
t
co
n
s
u
m
i
n
g
ti
m
e
s
i
n
ce
tr
ial
an
d
er
r
o
r
m
et
h
o
d
is
u
s
ed
in
ea
ch
iter
atio
n
s
.
QP
is
n
o
t su
ita
b
le
o
n
th
e
lar
g
e
p
r
o
b
le
m
an
d
R
P
is
a
co
m
p
lex
m
eth
od
[
4
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t 2
0
1
8
:
2
4
1
9
–
243
2
2420
Me
ta
-
h
eu
r
i
s
tic
ap
p
r
o
ac
h
f
o
r
s
to
ch
asti
c
o
p
ti
m
izatio
n
ca
n
b
e
u
s
ed
to
f
i
n
d
o
p
ti
m
al
f
ee
d
f
o
r
m
u
latio
n
[
5
]
.
I
t
o
v
er
co
m
es
th
e
lack
o
f
h
e
u
r
is
tic
ap
p
r
o
ac
h
i
n
t
h
e
lar
g
e
s
ea
r
c
h
s
p
ac
e
[
6
]
.
I
t
in
v
o
l
v
i
n
g
th
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
to
ev
al
u
ate
th
e
f
it
n
es
s
o
f
ca
n
d
id
ate
s
o
l
u
ti
o
n
an
d
ca
n
b
e
u
s
ed
to
d
eter
m
i
n
e
t
h
e
d
ir
ec
tio
n
o
f
s
ea
r
ch
tr
aj
ec
to
r
ies f
o
r
f
in
d
i
n
g
b
etter
ca
n
d
id
ate
s
o
lu
tio
n
[
7
]
.
O
n
e
o
f
th
e
m
eta
-
h
e
u
r
is
tic
m
eth
o
d
s
t
h
at
ca
n
b
e
e
m
p
lo
y
e
d
to
o
v
er
ca
m
e
t
h
e
d
ef
icie
n
c
y
o
f
th
o
s
e
m
et
h
o
d
s
is
P
ar
ticle
S
w
ar
m
O
p
ti
m
izatio
n
(
P
SO)
.
P
SO
h
as
s
h
o
w
n
a
p
r
o
m
i
s
in
g
o
p
ti
m
izatio
n
m
e
th
o
d
to
s
o
lv
e
a
co
m
p
le
x
p
r
o
b
le
m
s
u
ch
a
s
p
o
w
er
s
y
s
te
m
[
8
]
,
elec
tr
o
n
ic
in
d
u
s
tr
y
,
w
ir
ele
s
s
s
e
n
s
o
r
n
et
w
o
r
k
,
f
ea
tu
r
e
s
elec
tio
n
[
9
]
,
cir
cu
it
d
esi
g
n
[
1
0
]
,
m
u
lt
i
-
o
b
j
ec
tiv
e
o
p
ti
m
izati
o
n
[
1
1
]
,
an
d
d
eter
m
i
n
i
n
g
n
e
u
r
o
n
w
ei
g
h
ts
in
f
u
zz
y
n
eu
r
al
n
et
w
o
r
k
s
[
1
2
]
.
I
n
p
r
ev
io
u
s
s
tu
d
ie
s
co
n
d
u
cted
b
y
A
l
tu
n
a
n
d
Şa
h
m
an
[
1
3
]
,
P
SO
is
e
m
p
lo
y
ed
to
f
o
r
m
u
lat
e
o
p
ti
m
u
m
f
ee
d
o
n
s
e
v
er
al
an
i
m
al
s
s
u
c
h
as
ca
ttle,
s
h
ee
p
,
an
d
r
ab
b
its
.
T
h
is
alg
o
r
ith
m
ca
n
h
a
n
d
le
t
h
e
co
n
s
tr
ain
t
o
f
ea
c
h
f
ee
d
an
d
ca
n
f
i
n
d
th
e
o
p
ti
m
u
m
s
o
lu
tio
n
f
o
r
co
m
p
le
x
n
u
tr
itio
n
al
n
ee
d
s
w
it
h
least c
o
s
t.
T
h
e
r
esu
lt
s
h
o
w
s
u
s
th
a
t
P
SO
is
ab
le
to
p
r
o
v
id
e
a
b
ette
r
s
o
lu
tio
n
t
h
a
n
l
in
ea
r
p
r
o
g
r
a
m
m
i
n
g
m
eth
o
d
s
an
d
g
e
n
etic
alg
o
r
ith
m
.
I
n
th
e
o
th
er
h
an
d
,
t
h
e
m
o
d
el
o
f
m
u
lt
-
o
b
j
ec
tiv
e
o
p
ti
m
iza
tio
n
b
ased
o
n
P
SO
d
ef
in
ed
i
n
Xu
s
tu
d
y
[
1
4
]
.
H
o
w
e
v
er
,
th
eir
s
t
u
d
y
d
o
es n
o
t in
v
e
s
ti
g
ate
t
h
e
g
o
o
d
p
ar
am
eter
f
o
r
P
SO.
W
h
en
e
m
p
lo
y
i
n
g
P
SO,
g
o
o
d
ch
o
ice
f
o
r
co
n
tr
o
l
p
ar
a
m
ete
r
s
u
c
h
as
i
n
er
tia
w
ei
g
h
t,
co
g
n
iti
v
e
a
n
d
s
o
cial
co
ef
f
ic
ien
t
m
a
y
e
n
h
an
c
e
th
e
p
er
f
o
r
m
an
ce
o
f
P
SO.
Fu
r
th
er
m
o
r
e,
g
o
o
d
p
ar
am
eter
in
i
tializatio
n
d
ep
en
d
s
o
n
th
e
p
r
o
b
le
m
an
d
d
i
f
f
er
e
n
t
p
r
o
b
lem
m
a
y
r
eq
u
ir
e
a
d
if
f
er
en
t
c
h
o
ice
o
f
co
n
tr
o
l
p
ar
a
m
eter
s
.
T
h
e
r
ig
h
t
p
ar
am
eter
c
h
o
ice
m
a
y
lead
p
a
r
ticle
to
ex
p
lo
it
o
r
ex
p
lo
r
e
s
ea
r
ch
tr
aj
ec
to
r
y
to
t
h
e
o
p
ti
m
u
m
s
o
lu
tio
n
.
W
h
ile
t
h
e
w
r
o
n
g
c
h
o
ice
m
a
y
a
g
g
r
a
v
ate
t
h
e
P
SO
ab
ilit
y
f
o
r
f
in
d
i
n
g
th
e
g
lo
b
al
o
p
ti
m
u
m
s
o
lu
tio
n
[
1
5
]
.
T
h
e
g
o
o
d
s
w
ar
m
s
ize
an
d
to
tal
iter
atio
n
co
u
ld
af
f
ec
t
P
SO
p
er
f
o
r
m
a
n
ce
s
ig
n
i
f
i
ca
n
tl
y
.
T
h
er
ef
o
r
e,
it
is
i
m
p
o
r
tan
t
to
c
h
o
o
s
e
g
o
o
d
co
n
tr
o
l
p
ar
am
eter
s
o
f
P
SO
f
o
r
a
p
ar
ticu
lar
p
r
o
b
lem
.
Fu
r
t
h
er
m
o
r
e
,
t
h
e
s
o
f
t
w
ar
e
d
ev
elo
p
er
ca
n
s
elec
t
t
h
e
g
o
o
d
p
ar
am
eter
f
o
r
th
eir
ap
p
licatio
n
.
I
n
t
h
e
f
ee
d
m
ix
p
r
o
b
le
m
,
t
h
e
co
m
p
lex
i
t
y
o
f
s
ea
r
ch
s
p
ac
e
d
ep
en
d
s
o
n
t
h
e
c
h
o
ice
o
f
f
ee
d
th
at
h
as
n
u
tr
ie
n
t
v
al
u
e,
s
tag
e
o
f
la
y
i
n
g
h
en
,
a
n
d
f
lu
c
tu
at
in
g
p
r
ices
.
W
h
en
p
r
o
d
u
ce
r
ch
a
n
g
es
th
e
ch
o
ices,
t
h
e
f
ee
d
co
m
p
o
s
i
tio
n
b
ased
o
n
th
e
ch
o
ice
is
also
ch
an
g
ed
.
T
h
u
s
,
it
is
i
m
p
o
r
tan
t
to
ch
o
o
s
e
g
o
o
d
p
ar
a
m
eter
b
ased
o
n
s
ev
er
al
f
o
r
m
u
lae
r
ath
er
th
a
n
j
u
s
t o
n
e.
T
h
e
o
b
j
ec
tiv
e
o
f
t
h
i
s
s
t
u
d
y
is
to
in
v
esti
g
ate
th
e
g
o
o
d
s
w
ar
m
s
ize,
a
n
u
m
b
er
o
f
iter
at
io
n
,
ac
ce
ler
atio
n
co
ef
f
icie
n
t
s
,
an
d
i
n
er
tia
w
ei
g
h
t
o
f
P
SO
i
n
o
p
ti
m
izi
n
g
la
y
in
g
h
e
n
d
iet.
T
h
e
ex
p
er
i
m
e
n
t
is
b
ased
o
n
f
i
v
e
d
if
f
er
e
n
t
f
o
r
m
u
la
t
h
at
n
ee
d
s
to
b
e
o
p
ti
m
ized
.
T
h
e
o
b
tain
ed
g
o
o
d
p
ar
a
m
eter
s
t
h
a
n
c
o
m
p
ar
ed
to
a
n
o
th
er
p
ar
am
eter
's
v
a
lu
e
in
P
SO
in
o
r
d
er
to
f
in
d
t
h
e
o
p
ti
m
u
m
f
o
r
m
u
la.
Op
ti
m
u
m
m
ea
n
s
th
a
t
t
h
e
f
ee
d
is
f
u
l
f
ill
in
g
t
h
e
n
u
tr
ie
n
t r
eq
u
ir
e
m
e
n
ts
w
it
h
lea
s
t c
o
s
t.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
s
w
ar
m
i
n
telli
g
e
n
ce
ap
p
r
o
ac
h
an
d
t
h
e
ap
p
licatio
n
to
o
p
tim
ize
la
y
in
g
h
e
n
d
iet
is
d
is
cu
s
ed
i
n
f
o
llo
w
in
g
:
2
.
1
.
P
a
rt
icle
s
w
a
rm
o
pt
i
m
iza
t
io
n
P
ar
ticle
S
w
ar
m
Op
ti
m
izatio
n
(
P
SO)
g
ain
i
n
g
p
o
p
u
lar
it
y
s
i
n
c
e
its
e
m
er
g
en
ce
i
n
1
9
9
5
b
y
E
b
er
h
ar
t
an
d
Ken
n
ed
y
[
1
6
]
an
d
i
n
er
tia
w
ei
g
h
t
is
ad
d
ed
b
y
Sh
i
a
n
d
E
b
er
h
ar
t
[
1
7
]
to
co
n
tr
o
l
th
e
m
o
m
e
n
tu
m
o
f
g
lo
b
al
b
est
p
o
s
itio
n
an
d
p
er
s
o
n
al
b
est
p
o
s
itio
n
.
P
SO
i
s
a
n
al
g
o
r
ith
m
t
o
f
in
d
o
p
ti
m
u
m
s
o
lu
tio
n
t
h
at
in
s
p
ir
ed
f
r
o
m
t
h
e
p
o
p
u
latio
n
-
b
ased
m
o
v
e
m
en
t o
f
s
w
ar
m
o
f
f
is
h
an
d
b
ir
d
[
1
8
]
.
T
h
e
f
ir
s
t
s
tep
is
to
g
en
er
ate
i
n
itial
s
w
ar
m
o
r
p
o
p
u
latio
n
w
h
i
ch
ea
ch
p
ar
ticle
o
r
in
d
iv
id
u
al
(
ca
n
d
id
ate
s
o
lu
tio
n
)
h
a
v
e
th
eir
o
w
n
v
elo
cit
y
a
n
d
p
o
s
itio
n
.
Ne
x
t
s
tep
i
s
to
ca
lcu
late
t
h
e
f
it
n
es
s
f
u
n
ct
i
o
n
o
f
ea
c
h
p
ar
ticle.
T
h
en
s
av
e
t
h
e
b
est
f
it
n
es
s
v
al
u
e
o
f
ea
ch
p
ar
ticle
as
P
b
est
(
b
est
p
o
s
itio
n
in
a
p
ar
ticle)
an
d
s
av
e
t
h
e
b
est
o
f
al
l
p
ar
ticles
as
Gb
es
t
(
b
est
p
o
s
iti
o
n
o
f
al
l
p
ar
ticles).
T
h
en
u
p
d
ate
th
e
v
elo
cit
y
a
n
d
p
o
s
iti
o
n
o
f
ea
ch
p
ar
ticle
w
it
h
E
q
u
atio
n
s
(
1
)
an
d
(
2
)
.
P
B
est
o
f
ea
ch
p
ar
ticle
i
s
u
p
d
ated
as
w
el
l
as
g
B
est.
T
h
is
p
r
o
ce
s
s
co
n
tin
u
es
u
n
til
th
e
ter
m
i
n
ate
co
n
d
itio
n
i
s
s
ati
s
f
ie
d
.
Fin
all
y
,
Gb
es
t
b
ec
o
m
es
t
h
e
o
p
tim
u
m
s
o
l
u
tio
n
a
m
o
n
g
all
t
h
e
p
ar
ticles.
(
)
(
)
(
(
)
(
)
)
(
(
)
)
(
1
)
(
)
(
)
(
)
(
2
)
E
ac
h
p
ar
ticle
r
ep
r
ese
n
ts
t
h
e
ca
n
d
id
ate
s
o
lu
t
io
n
w
h
ic
h
h
as
v
elo
cit
y
a
n
d
p
o
s
itio
n
r
es
p
ec
tiv
el
y
.
Velo
cit
y
u
p
d
ated
b
ased
o
n
th
e
b
est
its
o
w
n
p
ar
ticle
an
d
t
h
e
b
est
o
f
all
p
ar
ticle.
T
h
er
ef
o
r
e,
th
e
p
ar
ticle
h
as
attr
ac
tiv
e
n
es
s
to
p
er
s
o
n
al
b
est an
d
g
lo
b
a
l b
est p
o
s
itio
n
.
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:
2
0
8
8
-
8708
Go
o
d
P
a
r
a
mete
r
s
fo
r
P
S
O
in
Op
timiz
in
g
La
yin
g
Hen
Diet
(
Gu
s
ti A
h
ma
d
F
a
n
s
h
u
r
i A
lfa
r
is
y
)
2421
2
.
2
.
P
SO
Appl
ica
t
io
n t
o
o
pti
m
iza
t
io
n o
f
la
y
ing
hen d
iet
T
h
e
v
alu
e
f
o
r
ea
ch
d
i
m
e
n
s
io
n
in
a
p
ar
ticle
i
s
r
ea
l
v
al
u
e
t
h
at
m
u
s
t
s
atis
f
y
t
h
e
h
ar
d
co
n
s
tr
ai
n
t
w
h
ic
h
i
s
eq
u
al
to
1
0
0
.
(
)
d
en
o
tes
th
e
p
ar
ticle
i
-
th
a
t
t
-
iter
atio
n
th
at
co
n
t
ain
a
s
et
o
f
v
ar
io
u
s
t
y
p
es
o
f
f
e
ed
(
x
i
)
w
ith
a
s
p
ec
if
ic
p
er
ce
n
ta
g
e
an
d
D
d
e
n
o
tes
t
h
e
to
tal
t
y
p
e
o
f
f
ee
d
wh
ich
a
ls
o
d
en
o
tes
t
h
e
d
i
m
e
n
s
i
o
n
o
f
p
ar
ticles.
T
h
e
p
ar
ticle
in
p
ar
ticu
lar
iter
atio
n
ca
n
b
e
ex
p
r
ess
ed
in
f
o
llo
w
in
g
:
(
)
*
+
On
th
e
co
n
d
itio
n
th
at
to
tal
n
u
m
b
er
o
f
in
th
e
s
et
(
)
is
eq
u
al
to
1
0
0
.
T
h
u
s
,
p
ar
ticle
r
ep
r
esen
tat
io
n
o
f
i
-
th
p
ar
ticle
f
o
r
f
ee
d
f
o
r
m
u
latio
n
is
s
h
o
w
n
i
n
F
i
g
u
r
e
2
an
d
th
e
ex
a
m
p
le
o
f
p
ar
ticle
r
ep
r
esen
tatio
n
w
h
ic
h
h
av
e
D
=
3
is
s
h
o
w
n
in
F
ig
u
r
e
1
.
Du
r
in
g
p
ar
ticle
m
o
v
e
m
en
t,
to
tal
p
er
ce
n
ta
g
e
m
a
y
n
o
t
s
ati
s
f
y
1
0
0
%.
T
h
u
s
,
E
q
u
atio
n
(
3
)
is
u
s
ed
t
o
ad
j
u
s
t th
e
cu
r
r
en
t to
tal
p
er
ce
n
t
ag
e
to
1
0
0
%
.
F
e
e
d
1
F
e
e
d
2
...
F
e
e
d
j
...
F
e
e
d
D
T
o
t
a
l
p
e
r
c
e
n
t
a
g
e
...
...
∑
Fig
u
r
e
1
.
P
ar
ticle
r
ep
r
esen
tati
o
n
p
1
(
c
o
r
n
)
p
2
(
b
a
r
n
)
p
3
(
c
o
n
c
e
n
t
r
a
t
e
)
T
o
t
a
l
P
e
r
c
e
n
t
a
g
e
3
5
,
0
0
0
5
0
,
0
0
0
1
5
,
0
0
0
1
0
0
Fig
u
r
e
2
.
E
x
a
m
p
le
o
f
p
ar
ticle
r
ep
r
esen
tatio
n
(
∑
)
(
3
)
Fo
r
ex
a
m
p
le
i
n
t
-
t
h
iter
atio
n
o
f
p
ar
ticle
i,
th
e
p
ar
ticle
h
a
v
e
th
e
f
o
llo
w
in
g
v
a
lu
e
s
:
C
o
r
n
B
a
r
n
C
o
n
c
e
n
t
r
a
t
e
T
o
t
a
l
P
e
r
c
e
n
t
a
g
e
5
4
,
8
9
7
3
0
,
5
6
4
34
,
5
3
9
1
2
0
%
Sin
ce
to
tal
p
er
ce
n
ta
g
e
is
n
o
t
eq
u
al
to
1
0
0
%
,
th
is
p
ar
ticle
n
ee
d
r
ea
d
j
u
s
t
m
en
t.
An
e
x
a
m
p
le
o
f
r
ea
d
j
u
s
t
m
en
t
p
r
o
ce
s
s
o
f
t
h
e
p
a
r
ticle
ca
n
b
e
s
ee
n
i
n
f
o
llo
w
i
n
g
:
C
o
r
n
B
a
r
n
K
o
s
e
n
t
r
a
t
T
o
t
a
l
P
e
r
c
e
n
t
a
g
e
1
0
0
%
Me
asu
r
i
n
g
t
h
e
ac
c
u
r
ac
y
o
f
n
u
tr
ien
t
s
o
f
p
ar
ticle
t
h
at
f
u
l
f
il
l
th
e
n
u
tr
ie
n
t
r
eq
u
ir
e
m
e
n
t
is
u
s
in
g
th
e
d
is
tan
ce
o
r
p
en
a
lt
y
b
et
w
ee
n
n
u
tr
ie
n
t
v
al
u
e
(
s
ee
A
p
p
en
d
i
x
f
o
r
m
o
r
e
d
etail)
a
n
d
ac
t
u
al
n
u
tr
ien
t
r
eq
u
ir
e
m
en
t.
T
h
e
p
en
alt
y
m
u
s
t
b
e
n
ea
r
ze
r
o
w
h
ic
h
i
n
d
icate
th
e
f
o
r
m
u
la
tio
n
i
s
f
ea
s
ib
le
f
o
r
la
y
i
n
g
h
e
n
s
d
iets
.
L
o
n
g
d
is
ta
n
c
e
o
r
h
ig
h
er
v
a
lu
e
o
f
p
en
a
lt
y
r
ep
r
esen
t
b
ad
p
ar
ticle
as
w
ell
a
s
co
s
t
o
r
p
r
ice
.
T
h
e
m
o
r
e
d
is
ta
n
ce
of
co
s
t,
t
h
e
m
o
r
e
p
ar
ticle
is
n
o
t
o
p
ti
m
u
m
.
T
h
er
ef
o
r
e
th
e
o
b
j
ec
tiv
e
f
u
n
ctio
n
o
r
f
itn
e
s
s
f
u
n
ctio
n
in
P
SO
ca
n
b
e
d
escr
ib
ed
as
1
d
iv
id
ed
b
y
t
h
e
s
u
m
o
f
p
en
alt
y
an
d
co
s
t th
at
s
h
o
u
ld
b
e
m
a
x
i
m
ized
as sh
o
w
n
in
E
q
u
at
io
n
(
4
)
.
(
)
(
)
(
)
(
4
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t 2
0
1
8
:
2
4
1
9
–
243
2
2422
Sp
ec
if
icall
y
,
in
o
r
d
er
to
esti
m
ate
t
h
e
d
is
tan
ce
to
p
r
o
d
u
ce
a
g
o
o
d
f
itn
es
s
f
u
n
ctio
n
,
t
h
e
an
al
y
s
is
o
f
la
y
i
n
g
h
e
n
s
n
u
tr
ie
n
t
r
eq
u
ir
e
m
en
ts
is
n
ec
es
s
ar
y
.
As
s
h
o
w
n
i
n
T
ab
le
5
,
th
e
n
u
tr
ie
n
t
r
eq
u
ir
em
en
ts
ar
e
d
i
f
f
er
en
t
o
n
ea
ch
la
y
er
a
n
d
ea
ch
n
u
tr
ie
n
t
h
a
s
d
if
f
er
en
t
l
i
m
it
th
a
t
ca
n
b
e
ca
teg
o
r
ized
as
th
e
m
i
n
i
m
u
m
,
m
a
x
i
m
u
m
,
an
d
r
an
g
e
o
f
t
h
e
s
u
f
f
icie
n
t n
u
tr
ie
n
t
[
1
9
]
-
[
2
4
]
.
T
h
u
s
,
w
e
n
ee
d
a
f
u
n
ctio
n
t
h
at
ac
co
m
m
o
d
ate
n
u
tr
i
en
t p
en
alt
y
o
f
ea
c
h
fe
ed
w
h
ic
h
is
s
h
o
w
n
in
E
q
u
at
io
n
s
(
5
)
,
(
6
)
,
(
7
)
,
an
d
(
8
)
.
(
)
d
e
n
o
tes
th
e
n
u
tr
ie
n
t
a
v
alu
e
o
n
j
-
th
p
o
s
itio
n
o
r
f
ee
d
o
n
i
-
th
p
ar
ticle,
k
d
en
o
tes
th
e
a
m
o
u
n
t
o
f
n
u
tr
ien
t
r
eq
u
ir
e
m
e
n
t
o
f
la
y
i
n
g
h
en
s
o
n
p
ar
ticu
lar
la
y
er
an
d
n
u
tr
ie
n
t.
(
)
,
(
)
,
an
d
(
)
p
ar
t
icu
lar
l
y
d
en
o
te
a
f
u
n
ct
io
n
w
h
i
ch
p
r
o
d
u
ce
s
a
p
en
alt
y
as
an
o
u
tp
u
t
f
r
o
m
t
h
e
r
eq
u
ir
e
m
e
n
ts
o
f
m
i
n
i
m
u
m
n
u
tr
ie
n
t,
m
a
x
i
m
u
m
n
u
tr
ien
t,
an
d
r
an
g
e
b
et
w
ee
n
m
i
n
i
m
u
m
a
n
d
m
a
x
i
m
u
m
v
alu
e
o
f
th
e
n
u
tr
ie
n
t.
E
q
u
atio
n
(
9
)
i
s
th
e
s
u
m
m
at
io
n
o
f
all
p
en
altie
s
o
f
all
n
u
tr
i
en
ts
i
n
a
p
ar
ticle
b
ased
o
n
th
e
n
u
tr
ie
n
t
r
eq
u
ir
e
m
en
t.
E
ac
h
n
u
tr
ien
t
h
as
m
i
n
an
d
m
a
x
p
r
o
p
er
ty
th
a
t
s
h
o
w
a
m
i
n
i
m
u
m
an
d
m
a
x
i
m
u
m
v
alu
e
o
f
t
h
e
n
u
tr
ie
n
t.
I
f
m
in
a
n
d
m
ax
p
r
o
p
er
t
y
ar
e
g
r
ea
ter
t
h
an
ze
r
o
t
h
an
it
is
i
n
d
ica
ted
th
a
t
n
u
tr
ie
n
t
h
a
s
r
an
g
e
r
eq
u
ir
e
m
e
n
t
b
et
w
ee
n
m
i
n
an
d
m
ax
v
alu
e.
I
f
th
e
m
ax
p
r
o
p
er
ty
v
al
u
e
is
g
r
ea
ter
th
an
ze
r
o
an
d
m
i
n
p
r
o
p
e
r
t
y
v
al
u
e
is
eq
u
al
o
r
less
t
h
a
n
ze
r
o
,
th
e
n
it
i
s
i
n
i
n
d
icatin
g
th
a
t
n
u
tr
ie
n
t
h
as
m
i
n
i
m
u
m
r
eq
u
ir
e
m
e
n
t.
O
th
er
w
i
s
e
,
it
h
as
a
m
in
i
m
u
m
r
eq
u
ir
e
m
en
t.
T
h
e
t
o
tal
p
r
ice
o
f
a
p
ar
ticle
n
ee
d
to
b
e
n
o
r
m
alize
d
in
o
r
d
er
to
m
a
k
e
t
h
e
p
r
ice
r
a
n
g
e
is
clo
s
e
to
n
u
tr
ie
n
t
v
alu
e.
T
h
u
s
,
th
e
c
o
s
t
f
u
n
ctio
n
ca
n
b
e
d
ef
in
ed
in
E
q
u
atio
n
(
10
)
w
h
er
e
(
)
is
th
e
to
tal
p
r
ice
in
a
p
ar
ticle.
(
)
d
en
o
tes
th
e
m
a
x
i
m
u
m
p
r
ice
w
h
ile
(
)
d
en
o
tes
th
e
m
i
n
i
m
u
m
p
r
ice
o
f
all
f
ee
d
s
.
Ho
w
e
v
er
,
th
e
p
o
s
itio
n
m
a
y
h
a
v
e
n
eg
at
iv
e
v
al
u
e
d
u
r
in
g
i
ter
atio
n
.
T
o
o
v
er
co
m
e
th
is
is
s
u
e,
w
e
s
et
th
e
f
it
n
es
s
f
u
n
ctio
n
v
al
u
e
to
n
eg
ativ
e.
I
t
i
n
d
icate
s
t
h
at
th
e
p
ar
ticle
ca
n
’
t
b
e
a
s
o
l
u
tio
n
t
o
f
ee
d
f
o
r
m
u
latio
n
p
r
o
b
lem
.
D
u
r
in
g
m
o
v
e
m
e
n
t,
th
e
p
ar
ticle
s
w
ill
lear
n
f
r
o
m
t
h
eir
co
g
n
iti
v
e
a
n
d
s
o
cial
ex
p
er
ien
ce
to
w
ar
d
s
p
o
s
itiv
e
f
itn
e
s
s
v
al
u
e
w
it
h
p
o
s
itiv
e
p
o
s
itio
n
s
.
T
ab
le
1
.
L
ay
in
g
He
n
s
N
u
tr
ien
t
R
eq
u
ir
e
m
e
n
t
s
No
N
u
t
r
i
e
n
t
U
n
i
t
L
a
y
e
r
P
r
e
S
t
a
r
t
e
r
(
1
-
4
W
e
e
k
s
)
L
a
y
e
r
S
t
a
r
t
e
r
(
5
-
1
0
W
e
e
k
s
)
L
a
y
e
r
G
r
o
w
e
r
(
1
1
-
1
6
W
e
e
k
s
)
P
r
e
L
a
y
e
r
(
1
7
-
1
8
W
e
e
k
s
)
L
a
y
e
r
(
1
9
-
5
0
W
e
e
k
s
)
L
a
y
e
r
P
o
st
P
e
a
k
(
>
5
0
W
e
e
k
s
)
1
C
r
u
d
e
P
r
o
t
e
i
n
(
C
P
)
%
M
i
n
2
0
.
0
0
1
9
.
0
0
1
5
.
5
0
1
6
.
0
0
1
6
.
5
0
1
6
.
0
0
2
L
y
si
n
(
L
y
s)
%
M
i
n
1
.
0
0
0
.
9
0
0
.
7
0
0
.
7
5
0
.
8
0
0
.
7
5
3
M
e
t
h
i
o
n
i
n
e
(
M
e
t
)
%
M
i
n
0
.
5
0
0
.
4
0
0
.
3
0
0
.
3
5
0
.
4
0
0
.
3
5
4
M
e
t
h
i
o
n
i
n
e
+
C
y
st
i
n
e
(
M
e
t
+
C
y
s)
%
M
i
n
0
.
8
0
0
.
7
0
0
.
6
0
0
.
6
3
0
.
6
7
0
.
6
5
5
Tr
y
p
t
o
p
h
a
n
(
T
r
y
p
)
%
M
i
n
0
.
2
0
0
.
1
8
0
.
1
7
0
.
1
7
0
.
1
8
0
.
1
7
6
T
h
r
e
o
n
i
n
e
(
T
h
r
e
)
%
M
i
n
0
.
7
5
0
.
6
5
0
.
5
0
0
.
5
2
0
.
5
5
0
.
5
0
7
C
r
u
d
e
F
a
t
(
F
)
%
M
i
n
3
.
0
0
3
.
0
0
3
.
0
0
3
.
0
0
3
.
0
0
3
.
0
0
8
C
r
u
d
e
F
i
b
e
r
(
C
F
)
%
M
a
x
6
.
0
0
7
.
0
0
8
.
0
0
8
.
0
0
7
.
0
0
8
.
0
0
9
C
a
l
c
i
u
m (
C
a
)
%
R
a
n
g
e
0
.
8
0
-
1
.
2
0
0
.
8
0
-
1
.
2
0
0
.
8
0
-
1
.
2
0
2
.
0
0
-
2
.
7
0
3
.
2
5
-
4
.
2
5
3
.
5
0
-
4
.
5
0
10
T
o
t
a
l
P
h
o
sp
h
o
r
u
s
(P)
%
M
i
n
0
.
6
0
0
.
5
5
0
.
4
6
0
.
5
0
0
.
5
5
0
.
5
0
11
M
e
t
a
b
o
l
i
z
a
b
l
e
En
e
r
g
y
(
M
E)
K
k
a
l
/
K
g
M
i
n
2
9
0
0
.
0
0
2
8
0
0
.
0
0
2
7
0
0
.
0
0
2
7
0
0
.
0
0
2
7
0
0
.
0
0
2
6
5
0
.
0
0
L
et
as
s
u
m
e
t
h
at
w
e
u
s
e
3
n
u
t
r
ien
t,
f
ir
s
t
n
u
tr
ien
t
u
s
i
n
g
th
e
m
ax
i
m
u
m
f
u
n
ctio
n
,
t
h
e
s
ec
o
n
d
n
u
tr
ien
t
u
s
i
n
g
th
e
m
in
i
m
u
m
f
u
n
ctio
n
,
an
d
th
e
th
ir
d
n
u
tr
ien
t
u
s
in
g
r
an
g
e
f
u
n
ctio
n
.
T
h
en
th
e
f
i
tn
ess
f
u
n
ctio
n
ca
n
b
e
d
ef
in
ed
in
E
q
u
at
io
n
(
9
)
.
Nu
tr
ien
ts
t
h
at
u
s
ed
in
th
i
s
s
t
u
d
y
ar
e
s
a
m
e
w
it
h
th
e
n
u
tr
ie
n
t
r
eq
u
i
r
e
m
en
t
s
in
T
ab
le
1
an
d
ex
a
m
p
le
o
f
f
ee
d
n
u
tr
ien
ts
is
s
h
o
w
n
i
n
T
ab
le
2
.
T
h
er
ef
o
r
e,
th
e
f
it
n
es
s
f
u
n
c
tio
n
ca
n
b
e
d
ef
in
e
d
in
E
q
u
atio
n
(
1
0
).
T
ab
le
2
.
E
x
am
p
le
o
f
Feed
Nu
t
r
ien
ts
No
N
u
t
r
i
e
n
t
U
n
i
t
B
r
a
n
Y
e
l
l
o
w
C
o
r
n
S
o
y
b
e
a
n
s
C
o
c
o
n
u
t
M
e
a
l
1
C
r
u
d
e
P
r
o
t
e
i
n
(
C
P
)
%
1
0
.
2
8
.
5
4
38
1
8
.
5
2
L
y
si
n
(
L
y
s)
%
0
.
7
1
0
.
2
2
.
4
0
.
6
4
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:
2
0
8
8
-
8708
Go
o
d
P
a
r
a
mete
r
s
fo
r
P
S
O
in
Op
timiz
in
g
La
yin
g
Hen
Diet
(
Gu
s
ti A
h
ma
d
F
a
n
s
h
u
r
i A
lfa
r
is
y
)
2423
No
N
u
t
r
i
e
n
t
U
n
i
t
B
r
a
n
Y
e
l
l
o
w
C
o
r
n
S
o
y
b
e
a
n
s
C
o
c
o
n
u
t
M
e
a
l
3
M
e
t
h
i
o
n
i
n
e
(
M
e
t
)
%
0
.
2
7
0
.
1
8
0
.
5
1
0
.
2
9
4
M
e
t
h
i
o
n
i
n
e
+
C
y
st
i
n
e
(
M
e
t
+
C
y
s)
%
0
.
6
4
0
.
3
6
1
.
1
5
0
.
5
9
5
Tr
y
p
t
o
p
h
a
n
(
T
r
y
p
)
%
0
.
0
9
0
.
1
0
.
5
5
0
.
2
6
T
h
r
e
o
n
i
n
e
(
T
h
r
e
)
%
0
.
5
7
0
.
4
1
.
5
0
.
6
5
7
C
r
u
d
e
F
a
t
(
F
)
%
7
2
.
6
1
18
2
.
5
8
C
r
u
d
e
F
i
b
e
r
(
C
F
)
%
3
0
.
0
2
5
15
9
C
a
l
c
i
u
m (
C
a
)
%
0
.
0
4
0
.
0
2
0
.
2
5
0
.
2
10
T
o
t
a
l
P
h
o
sp
h
o
r
u
s
(
P
)
%
0
.
1
6
0
.
1
0
.
2
5
0
.
5
7
11
M
e
t
a
b
o
l
i
z
a
b
l
e
En
e
r
g
y
(
M
E)
K
k
a
l
/
K
g
2
8
6
0
3
3
7
0
2
8
6
0
2
2
0
0
12
C
o
st
R
u
p
i
a
h
/
K
g
3
0
0
0
3
7
0
0
5
0
0
0
4
2
0
0
(
)
∑
(
)
(5
)
(
)
{
(
)
(
)
(
)
(6
)
(
)
{
(
)
(
)
(
)
(
7
)
(
)
{
(
)
(
)
(
)
(
)
(
)
(
8
)
(
)
∑
{
(
)
(
)
(
)
(
9
)
(
)
(
)
(
)
(
)
(
)
(
1
0
)
2
.
3
.
E
x
peri
m
e
nta
l s
et
up
I
n
th
i
s
s
t
u
d
y
,
w
e
p
er
f
o
r
m
4
test
in
g
s
ce
n
ar
io
th
at
ai
m
to
g
et
i
n
s
i
g
h
t
ab
o
u
t
g
o
o
d
s
w
ar
m
s
ize,
th
e
g
o
o
d
n
u
m
b
er
o
f
iter
ati
o
n
,
g
o
o
d
ac
ce
ler
atio
n
co
ef
f
icie
n
ts
,
g
o
o
d
in
er
tia
w
ei
g
h
t
an
d
p
er
f
o
r
m
a
n
ce
o
f
g
o
o
d
p
ar
am
eter
s
in
P
SO
f
o
r
f
ee
d
f
o
r
m
u
la
tio
n
in
la
y
in
g
h
e
n
d
iets
.
Fir
s
t
co
n
t
r
o
l
p
ar
am
eter
ch
o
ices
ar
e
0
.
6
f
o
r
in
er
tia
w
eig
h
t
co
ef
f
icie
n
t a
n
d
1
.
7
f
o
r
b
o
th
ac
ce
ler
atio
n
co
ef
f
icien
ts
.
A
ll e
x
p
er
im
e
n
t i
s
u
s
in
g
g
r
o
w
er
p
h
a
s
e
o
f
la
y
i
n
g
h
e
n
.
I
n
th
e
f
ir
s
t
s
ce
n
ar
io
,
w
e
ex
p
e
r
i
m
en
t
w
ith
5
d
if
f
er
en
t
f
o
r
m
u
la
th
at
ca
n
b
e
s
ee
n
i
n
T
ab
le
3
to
f
in
d
a
g
o
o
d
s
w
ar
m
s
ize.
Fo
r
all
f
o
r
m
u
la
,
w
e
r
u
n
P
SO
w
it
h
d
i
f
f
er
e
n
t
s
w
ar
m
s
ize
th
at
h
a
s
r
an
g
ed
b
et
w
ee
n
1
0
an
d
1
0
0
b
y
1
0
w
it
h
1
0
,
0
0
0
iter
atio
n
s
.
T
h
is
s
ce
n
ar
io
d
esi
g
n
ed
to
f
ig
u
r
e
o
u
t
t
h
e
ef
f
ec
t
o
f
t
h
e
d
if
f
er
en
t
co
m
b
i
n
atio
n
o
f
f
ee
d
to
w
ar
d
s
b
est s
w
ar
m
s
ize
f
o
r
f
o
r
m
u
lati
n
g
o
p
ti
m
u
m
d
iet.
I
n
th
e
s
ec
o
n
d
s
ce
n
ar
io
,
th
e
s
a
m
e
f
ee
d
co
m
b
in
a
tio
n
f
r
o
m
s
ce
n
ar
io
1
is
u
s
ed
w
h
ich
u
s
in
g
d
if
f
er
e
n
t
to
tal
ite
r
atio
n
th
at
h
as
r
an
g
ed
b
et
w
ee
n
1
,
0
0
0
to
1
0
,
0
0
0
b
y
1
,
0
0
0
an
d
b
est
s
w
ar
m
s
ize
i
s
u
s
ed
t
h
at
d
er
iv
ed
f
r
o
m
s
ce
n
ar
io
1
.
T
h
is
s
ce
n
ar
io
is
in
ten
d
ed
to
f
i
g
u
r
e
o
u
t
t
h
e
b
est
n
u
m
b
er
o
f
iter
atio
n
to
w
ar
d
s
d
if
f
er
e
n
t
f
ee
d
co
m
b
i
n
atio
n
s
.
I
n
th
ir
d
s
ce
n
ar
i
o
,
w
e
t
u
n
i
n
g
co
g
n
iti
v
e
an
d
s
o
cial
co
ef
f
icie
n
ts
to
g
et
th
e
b
est
co
n
tr
o
l
p
ar
a
m
eter
f
o
r
P
SO
in
ca
s
e
o
f
f
ee
d
f
o
r
m
u
la
t
io
n
p
r
o
b
lem
.
T
h
e
v
alu
e
b
etw
ee
n
0
.
1
to
2
.
0
an
d
in
cr
ea
s
ed
b
y
0
.
1
f
o
r
b
o
th
co
ef
f
icie
n
t
is
tes
ted
.
W
e
u
s
e
th
e
g
o
o
d
s
w
ar
m
s
ize
an
d
g
o
o
d
n
u
m
b
er
o
f
it
er
atio
n
s
d
er
iv
e
d
f
r
o
m
s
ce
n
ar
io
1
an
d
2
.
I
n
th
e
f
o
u
r
t
h
s
ce
n
ar
io
,
w
e
tu
n
in
g
d
i
f
f
er
en
t
v
alu
e
o
f
co
n
s
ta
n
t
in
er
tia
w
eig
h
t
f
o
r
all
d
if
f
er
en
t
f
o
r
m
u
la.
T
h
e
v
alu
e
b
et
w
ee
n
0
.
1
to
0
.
9
b
y
0
.
1
.
W
e
u
s
e
th
e
g
o
o
d
s
war
m
s
ize,
iter
atio
n
,
a
n
d
ac
ce
l
er
atio
n
co
ef
f
icie
n
t
s
d
er
iv
ed
f
r
o
m
s
ce
n
ar
io
1
,
2
,
an
d
3
.
I
n
th
e
f
i
f
t
h
s
ce
n
ar
io
,
w
e
u
s
e
th
e
g
o
o
d
s
w
ar
m
s
ize
d
er
iv
e
d
f
r
o
m
s
ce
n
ar
io
1
,
g
o
o
d
to
ta
l
iter
atio
n
s
d
er
iv
ed
f
r
o
m
s
ce
n
ar
io
2
,
g
o
o
d
ac
ce
ler
atio
n
co
ef
f
icie
n
ts
d
e
r
iv
ed
f
r
o
m
s
ce
n
ar
io
3
,
an
d
g
o
o
d
in
er
tia
w
eig
h
t
d
er
iv
ed
f
r
o
m
s
ce
n
ar
io
4
.
We
test
th
e
s
e
p
ar
a
m
eter
s
to
o
th
e
r
p
ar
am
eter
s
etti
n
g
s
s
u
ch
as
l
in
ea
r
l
y
d
ec
r
ea
s
in
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t 2
0
1
8
:
2
4
1
9
–
243
2
2424
in
er
tia
w
ei
g
h
t
w
i
th
m
a
x
=
0
.
9
an
d
m
in
=
0
.
4
s
i
n
ce
it
is
co
n
s
id
er
ed
m
o
s
tl
y
u
s
ed
in
P
SO
ap
p
licatio
n
s
[
2
5
]
an
d
w
=
0
.
7
2
9
,
c
1
=
1
.
4
9
4
,
c
2
=
1
.
4
9
4
[
2
6
]
u
s
in
g
f
o
r
m
u
lae
i
n
T
ab
le
4
.
Sin
ce
P
SO
is
s
to
ch
asti
c
o
p
tim
izat
io
n
th
a
t
p
r
o
d
u
ce
f
lu
ct
u
ati
n
g
r
es
u
lt
s
,
we
r
u
n
P
SO te
n
ti
m
e
s
f
o
r
f
air
a
n
al
y
s
i
s
.
T
ab
le
3
.
T
est Fo
r
m
u
lae
f
o
r
Go
o
d
P
a
r
am
eter
s
F
o
r
mu
l
a
F
e
e
d
5A
3
,
4
,
5
,
2
5
,
2
6
6A
2
,
4
,
1
0
,
1
7
,
2
4
,
2
6
8A
1
,
3
,
8
,
1
0
,
1
1
,
1
5
,
1
8
,
2
1
11A
2
,
4
,
8
,
1
3
,
1
5
,
1
6
,
1
9
,
2
0
,
2
1
,
2
2
,
2
6
15A
0
,
2
,
5
,
6
,
7
,
8
,
9
,
1
0
,
1
9
,
2
5
,
2
2
,
2
3
,
2
4
,
2
6
,
2
7
T
ab
le
4
.
T
est Fo
r
m
u
lae
f
o
r
C
o
m
p
ar
i
s
o
n
F
o
r
mu
l
a
F
e
e
d
1
1
B
0
,
1
,
3
,
1
1
,
1
3
,
1
6
,
2
0
,
2
2
,
2
3
,
2
6
,
3
0
1
2
B
0
,
2
,
3
,
8
,
1
0
,
1
5
,
1
7
,
1
9
,
2
0
,
2
1
,
2
4
,
2
6
1
3
B
1
,
3
,
5
,
8
,
9
,
1
0
,
1
3
,
1
7
,
1
9
,
2
0
,
2
4
,
2
7
,
3
0
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
A
ll
t
h
e
te
s
ti
n
g
s
ce
n
ar
io
s
ar
e
i
m
p
le
m
e
n
ted
u
s
in
g
Scala
p
r
o
g
r
a
m
m
in
g
la
n
g
u
a
g
e
th
a
t
co
m
b
i
n
es
o
b
j
ec
t
-
o
r
ien
ted
an
d
f
u
n
ctio
n
al
p
ar
ad
ig
m
.
T
h
e
r
esu
lts
f
o
r
ea
ch
s
ce
n
a
r
io
is
d
is
cu
s
s
ed
in
t
h
e
f
o
llo
w
i
n
g
s
ec
tio
n
:
3
.
1
.
G
o
o
d sw
a
r
m
s
ize
T
h
e
ef
f
ec
t
o
f
an
in
cr
ea
s
e
in
s
w
ar
m
s
ize
f
o
r
all
f
o
r
m
u
la
is
s
h
o
w
n
i
n
F
ig
u
r
e
3
.
I
t
is
s
h
o
w
n
th
at
ea
c
h
f
o
r
m
u
la
r
eq
u
ir
es
d
if
f
er
e
n
t
m
i
n
i
m
u
m
s
w
ar
m
s
ize
to
f
o
u
n
d
th
e
o
p
tim
u
m
f
o
r
m
u
la.
Fo
r
m
u
la
5
A
an
d
6
A
n
ee
d
at
least
2
0
s
w
ar
m
s
ize,
f
o
r
m
u
la
8
A
n
ee
t
at
least
5
0
s
w
ar
m
s
iz
e,
f
o
r
m
u
la
1
1
A
n
ee
d
at
lea
s
t
3
0
s
w
ar
m
s
ize,
a
n
d
f
o
r
m
u
la
1
5
A
n
ee
d
at
least
1
8
0
s
w
ar
m
s
ize.
I
n
1
5
A
,
i
n
cr
ea
s
in
g
s
w
ar
m
s
ize
ab
o
v
e
1
8
0
c
o
u
ld
n
o
t
g
i
v
e
an
y
s
ig
n
i
f
ica
n
t i
m
p
r
o
v
e
m
e
n
t
f
o
r
th
e
av
er
ag
e
f
itn
e
s
s
v
al
u
e.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
3
.
E
f
f
ec
t o
f
s
w
ar
m
s
ize
to
av
er
ag
e
f
it
n
e
s
s
o
n
f
o
r
m
u
la
:
(
a)
5A
,
(
b
)
6A
,
(
c)
8A
,
(
d
)
11A
,
a
n
d
(
e)
15A
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:
2
0
8
8
-
8708
Go
o
d
P
a
r
a
mete
r
s
fo
r
P
S
O
in
Op
timiz
in
g
La
yin
g
Hen
Diet
(
Gu
s
ti A
h
ma
d
F
a
n
s
h
u
r
i A
lfa
r
is
y
)
2425
E
ac
h
m
in
i
m
u
m
s
w
ar
m
s
ize
g
iv
e
s
u
s
i
n
s
ig
h
t
t
h
at
t
h
e
n
u
m
b
er
o
f
f
ee
d
s
in
ea
c
h
f
o
r
m
u
la
is
n
o
t
ass
o
ciate
d
w
ith
t
h
e
m
in
i
m
u
m
s
w
ar
m
s
ize.
W
ith
5
an
d
6
d
if
f
er
en
t
f
ee
d
co
m
b
i
n
atio
n
,
th
e
y
r
eq
u
ir
e
m
i
n
i
m
u
m
2
0
s
w
ar
m
s
ize
a
n
d
t
h
e
m
i
n
i
m
u
m
v
alu
e
is
i
n
cr
ea
s
ed
w
it
h
8
d
if
f
er
en
t
co
m
b
i
n
atio
n
s
t
h
at
n
ee
d
at
least
5
0
s
w
ar
m
s
ize.
Ho
w
ev
er
,
w
h
en
th
e
n
u
m
b
er
o
f
f
ee
d
s
is
in
cr
ea
s
ed
to
1
1
d
if
f
er
en
t
co
m
b
i
n
atio
n
s
,
it
r
eq
u
ir
es
les
s
s
w
ar
m
s
ize
th
a
n
8
A
w
h
ic
h
at
leas
t
3
0
s
w
ar
m
s
ize.
T
h
u
s
,
t
h
e
co
m
p
lex
it
y
o
f
s
ea
r
ch
s
p
ac
e
is
n
o
t
ass
o
ciate
d
w
i
th
t
h
e
n
u
m
b
er
o
f
f
ee
d
s
T
h
en
,
I
t
i
s
v
er
y
d
if
f
ic
u
lt
to
f
in
d
m
i
n
i
m
u
m
s
w
ar
m
s
ize
f
o
r
ev
er
y
co
m
b
i
n
atio
n
o
f
f
ee
d
s
.
Si
n
ce
t
h
e
n
u
m
b
er
o
f
co
m
b
in
atio
n
is
v
er
y
lar
g
e
an
d
th
e
co
s
t
o
f
f
e
ed
is
f
lu
ct
u
ati
n
g
t
h
at
in
cr
ea
s
e
th
e
co
m
b
i
n
atio
n
co
m
p
le
x
it
y
t
h
r
o
u
g
h
ti
m
e
(
th
e
co
s
t
al
w
a
y
s
c
h
a
n
g
e)
.
Ho
w
ev
er
,
w
it
h
a
s
m
all
s
a
m
p
le
o
f
e
x
p
er
i
m
e
n
tatio
n
,
w
e
ca
n
ch
o
o
s
e
t
h
e
h
i
g
h
e
s
t
s
w
ar
m
s
ize
to
b
e
t
h
e
g
o
o
d
p
ar
am
e
ter
.
T
h
e
h
i
g
h
est
s
w
ar
m
s
ize
ca
n
m
a
k
e
p
ar
ticles co
n
v
er
g
e
o
n
all
f
o
r
m
u
la.
I
t
is
h
ig
h
l
y
li
k
el
y
t
h
at
t
h
i
s
g
o
o
d
p
ar
am
eter
is
n
o
t
g
o
o
d
f
o
r
an
o
th
er
f
o
r
m
u
la
o
u
ts
id
e
o
f
th
e
s
a
m
p
le.
T
h
er
ef
o
r
e,
w
e
p
r
o
p
o
s
e
to
ad
d
a
d
d
itio
n
al
s
w
ar
m
s
ize
f
o
r
th
e
h
i
g
h
e
s
t
s
w
ar
m
s
iz
e
f
o
u
n
d
i
n
a
s
m
a
ll
s
a
m
p
le.
I
n
th
is
ca
s
e,
th
e
h
i
g
h
est
s
w
ar
m
s
ize
is
1
8
0
,
th
e
n
t
h
e
g
o
o
d
s
w
ar
m
s
ize
w
o
u
ld
b
e
1
8
0
+
X
w
h
ich
X
is
th
e
ar
b
itra
r
y
n
u
m
b
er
o
f
s
w
ar
m
s
ize
th
at
p
o
s
s
ib
l
y
ca
n
h
elp
p
ar
ticles co
n
v
er
g
e
i
n
a
b
etter
s
o
lu
tio
n
.
Fo
r
th
e
n
ex
t
e
x
p
er
i
m
e
n
t,
w
e
ch
o
o
s
e
ar
b
itra
r
y
v
a
lu
e
X
=
5
0
a
n
d
th
e
n
th
e
g
o
o
d
s
w
ar
m
s
ize
=
2
3
0
.
T
h
e
d
eter
m
in
at
io
n
o
f
t
h
is
v
al
u
e
is
an
o
th
er
p
r
o
b
lem
t
h
at
i
s
n
o
t d
is
cu
s
s
ed
in
t
h
is
p
ap
er
.
3
.
2
.
G
o
o
d nu
m
b
er
o
f
it
er
a
t
io
n
Fo
r
f
o
r
m
u
la
5
A
an
d
6
A
,
1
,
0
0
0
iter
atio
n
s
ar
e
ad
eq
u
a
te
to
m
ak
e
p
ar
ticle
to
co
n
v
er
g
e
as
s
h
o
w
n
i
n
Fig
u
r
e
4
.
B
y
in
cr
ea
s
in
g
t
h
e
d
i
m
en
s
io
n
,
8
A
r
eq
u
ir
e
m
i
n
i
m
u
m
iter
atio
n
s
o
f
4
,
0
0
0
,
1
1
A
r
eq
u
ir
e
m
i
n
i
m
u
m
iter
atio
n
s
o
f
5
,
0
0
0
,
w
h
ile
1
5
A
r
eq
u
ir
e
m
i
n
i
m
u
m
iter
atio
n
s
o
f
1
4
,
0
0
0
.
E
ac
h
f
o
r
m
u
la
s
h
o
w
s
d
i
f
f
er
en
t
to
tal
iter
atio
n
s
.
W
ith
a
s
m
al
l
s
a
m
p
le
o
f
5
d
if
f
er
en
t
f
o
r
m
u
la,
t
h
e
h
ig
h
e
s
t
n
u
m
b
er
o
f
iter
at
io
n
s
i
s
f
o
u
n
d
in
f
o
r
m
u
l
a
1
1
A
.
I
f
t
h
is
v
al
u
e
is
u
s
ed
as
a
g
o
o
d
n
u
m
b
er
o
f
iter
atio
n
s
it
c
an
m
a
k
e
p
ar
ticle
co
n
v
er
g
e
i
n
all
s
a
m
p
le
f
o
r
m
u
la.
T
h
u
s
,
w
e
p
r
o
p
o
s
e
an
ad
d
itio
n
al
n
u
m
b
er
o
f
i
ter
atio
n
s
in
ac
c
o
u
n
ti
n
g
f
ee
d
co
m
b
i
n
atio
n
o
u
t
s
id
e
o
f
s
a
m
p
le.
T
h
e
g
o
o
d
n
u
m
b
er
o
f
iter
at
io
n
s
s
h
o
u
ld
b
e
1
4
,
0
0
0
+
Y
w
h
ich
Y
i
s
th
e
ar
b
itra
r
y
n
u
m
b
er
o
f
iter
ati
o
n
s
.
Fo
r
th
e
ex
p
er
i
m
e
n
t
o
f
ac
ce
ler
atio
n
co
ef
f
icien
t,
w
e
ch
o
o
s
e
a
r
b
itra
r
y
Y
=
5
,
0
0
0
,
g
o
o
d
n
u
m
b
er
o
f
iter
ati
o
n
s
=
1
9
,
0
0
0
.
T
h
is
d
eter
m
i
n
atio
n
is
an
o
th
er
p
r
o
b
lem
t
h
at
i
s
n
o
t d
is
cu
s
s
ed
in
t
h
is
p
ap
er
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
4
.
E
f
f
ec
t o
f
n
u
m
b
er
o
f
iter
atio
n
s
to
av
er
a
g
e
f
i
tn
e
s
s
o
n
f
o
r
m
u
la:
(
a)
5
A
,
(
b
)
6
A
,
(
c)
8
A
,
(
d
)
1
1
A
,
an
d
(
e)
1
5
A
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t 2
0
1
8
:
2
4
1
9
–
243
2
2426
3
.3
.
G
o
o
d a
cc
eler
a
t
io
n c
o
ef
f
icien
t
s
T
h
e
ef
f
ec
t
o
f
ac
ce
ler
atio
n
co
ef
f
icien
ts
to
a
v
er
ag
e
f
it
n
es
s
v
al
u
e
is
s
h
o
w
n
i
n
Fig
u
r
e
5
.
T
h
e
in
cr
ea
s
e
o
f
s
o
cial
co
ef
f
icie
n
t
g
iv
e
s
s
i
g
n
i
f
i
ca
n
t
i
m
p
r
o
v
e
m
e
n
t
to
a
v
er
ag
e
f
it
n
es
s
f
o
r
all
f
o
r
m
u
lae.
W
h
ile
u
s
i
n
g
s
m
all
s
o
cial
co
ef
f
icie
n
t
w
i
th
h
i
g
h
co
g
n
iti
v
e
co
ef
f
icie
n
t
ca
n
’
t
i
m
p
r
o
v
e
av
er
ag
e
f
it
n
es
s
w
h
ich
lead
s
t
o
b
ad
ch
o
ices.
T
h
e
s
o
cial
co
ef
f
ic
ien
t
ab
o
v
e
1
.
0
w
it
h
a
s
m
a
ll
v
al
u
e
o
f
th
e
co
g
n
iti
v
e
co
ef
f
icie
n
t
is
e
n
o
u
g
h
to
p
r
o
d
u
ce
o
p
tim
u
m
f
o
r
m
u
la.
Ho
w
ev
er
,
w
it
h
th
is
s
m
all
s
a
m
p
le
o
f
e
x
p
er
im
e
n
tat
io
n
,
it
is
s
a
f
e
to
c
h
o
o
s
e
a
h
i
g
h
v
alu
e
f
o
r
b
o
th
a
cc
eler
atio
n
co
ef
f
ici
en
t.
T
h
u
s
,
i
n
t
h
is
s
tu
d
y
,
w
e
ch
o
o
s
e
co
g
n
iti
v
e
co
ef
f
icie
n
t
o
f
2
.
0
an
d
s
o
cial
co
ef
f
icie
n
t o
f
2
.
0
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
5
.
E
f
f
ec
t o
f
ac
ce
ler
atio
n
co
ef
f
icie
n
ts
to
av
er
a
g
e
f
i
tn
e
s
s
o
n
f
o
r
m
u
la
:
(
a)
5
A
,
(
b
)
6
A
,
(
c)
8
A
,
(
d
)
1
1
A
,
an
d
(
e)
1
5
A
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:
2
0
8
8
-
8708
Go
o
d
P
a
r
a
mete
r
s
fo
r
P
S
O
in
Op
timiz
in
g
La
yin
g
Hen
Diet
(
Gu
s
ti A
h
ma
d
F
a
n
s
h
u
r
i A
lfa
r
is
y
)
2427
3
.
4
.
G
o
o
d inert
ia
w
eig
ht
T
h
e
ef
f
ec
t
o
f
i
n
er
tia
w
e
ig
h
t
v
alu
e
to
av
er
a
g
e
f
it
n
e
s
s
is
s
h
o
w
n
in
Fi
g
u
r
e
6
.
I
n
all
f
o
r
m
u
la,
ex
ce
p
t
f
o
r
m
u
la
8
A
,
a
h
i
g
h
v
alu
e
o
f
i
n
er
tia
w
ei
g
h
t
d
ec
r
ea
s
e
t
h
e
av
er
ag
e
f
itn
e
s
s
.
I
n
f
o
r
m
u
la
5
A
a
n
d
6
A
,
i
n
er
tia
w
ei
g
h
t
o
f
0
.
1
to
0
.
7
d
o
es
n
o
t
in
cr
e
ase
o
r
d
ec
r
ea
s
e
av
er
ag
e
f
it
n
ess
s
i
g
n
i
f
ican
t
l
y
a
n
d
it
is
co
n
s
id
er
ed
as
a
g
o
o
d
p
ar
am
eter
i
n
5
A
a
n
d
6
A
.
W
h
i
le
in
8
A
,
i
n
er
t
ia
w
ei
g
h
t
o
f
0
.
1
to
0
.
9
d
o
es
n
o
t
d
ec
r
ea
s
e
th
e
av
er
ag
e
f
it
n
es
s
an
d
co
n
s
id
er
ed
as
a
s
af
e
v
alu
e
to
ch
o
o
s
e
as
a
g
o
o
d
p
ar
am
eter
.
I
n
1
1
A
,
in
er
tia
w
ei
g
h
t
o
f
0
.
1
to
0
.
6
is
a
s
af
e
ch
o
ice
to
ch
o
o
s
e.
I
n
f
o
r
m
u
la
5
A
,
6
A,
8
A
,
a
n
d
1
1
A
,
t
h
e
i
n
cr
e
m
en
t
o
f
in
er
t
ia
w
ei
g
h
t
i
n
s
a
f
e
v
al
u
e
d
o
es
n
o
t
i
m
p
r
o
v
e
s
ig
n
i
f
ica
n
tl
y
to
av
er
a
g
e
f
itn
e
s
s
.
Ho
w
e
v
er
,
i
n
1
5
A
,
a
v
er
ag
e
f
it
n
es
s
g
r
ad
u
a
ll
y
in
cr
ea
s
ed
f
r
o
m
0
.
1
to
0
.
7
an
d
d
ec
r
ea
s
ed
s
ig
n
i
f
ica
n
tl
y
ab
o
v
e
0
.
7
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
6
.
E
f
f
ec
t o
f
i
n
er
tia
w
ei
g
h
t to
a
v
er
ag
e
f
it
n
ess
o
n
f
o
r
m
u
la:
(
a)
5
A
,
(
b
)
6
A
,
(
c)
8A
,
(
d
)
1
1
A
,
(
e)
an
d
1
5
A
T
h
e
s
i
m
u
la
tio
n
r
esu
lts
s
h
o
w
u
s
t
h
at
a
g
o
o
d
p
ar
am
eter
o
f
in
er
tia
w
eig
h
t
d
if
f
er
s
f
r
o
m
f
o
r
m
u
la
to
an
o
th
er
f
o
r
m
u
la.
T
h
e
ch
o
ice
s
h
o
u
ld
b
e
b
elo
w
0
.
7
s
in
ce
it
is
th
e
s
a
f
e
c
h
o
ice
to
c
h
o
o
s
e
th
a
t
n
o
t
d
ec
r
ea
s
in
g
t
h
e
av
er
ag
e
f
it
n
e
s
s
t
h
at
f
o
u
n
d
in
f
o
r
m
u
la
5
A
,
6
A
,
8
A
,
a
n
d
1
5
A
.
Ho
w
e
v
er
,
0
.
7
is
co
n
s
id
er
e
d
to
b
e
a
b
ad
ch
o
ice
b
ec
au
s
e
it
w
ill
d
ec
r
ea
s
e
th
e
av
er
ag
e
f
it
n
es
s
i
n
f
o
r
m
u
la
1
1
A
.
W
it
h
a
s
m
a
ll
s
a
m
p
le,
t
h
e
in
er
tia
w
eig
h
t
in
[0
.
5
,
0
.
6
]
s
h
o
u
ld
b
e
ch
o
s
en
a
s
a
g
o
o
d
ch
o
ice
p
ar
a
m
eter
s
i
n
ce
it
i
s
s
a
f
e
to
ch
o
o
s
e
i
n
t
h
e
s
m
al
l
s
a
m
p
le
o
f
ex
p
er
i
m
e
n
tatio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t 2
0
1
8
:
2
4
1
9
–
243
2
2428
3
.
5.
Co
m
pa
riso
n r
esu
lt
s
T
h
e
g
o
o
d
p
ar
am
eter
ch
o
ices
o
f
P
SO
w
h
ic
h
ar
e
s
w
ar
m
s
iz
e
=
2
3
0
,
iter
atio
n
s
=
1
9
,
0
0
0
,
c1
=
2
,
0
,
c2
=
2
,
0
,
an
d
w
=
0
,
6
is
co
m
p
ar
ed
to
o
th
er
P
SO
p
ar
am
e
ter
s
.
T
h
e
co
m
p
ar
is
o
n
is
s
i
m
u
lated
w
it
h
th
e
s
a
m
e
s
w
ar
m
s
ize
a
n
d
iter
atio
n
s
in
o
r
d
er
to
k
n
o
w
h
o
w
ac
ce
ler
atio
n
co
ef
f
icie
n
ts
an
d
i
n
er
tia
w
ei
g
h
t
co
u
ld
a
f
f
ec
t
th
e
P
SO
p
er
f
o
r
m
an
ce
an
d
f
o
r
a
f
a
ir
co
m
p
ar
is
o
n
.
As
s
h
o
w
n
in
T
ab
le
5
,
all
f
o
r
m
u
lae
p
r
o
d
u
ce
d
b
y
P
SO
-
1
h
a
v
e
t
h
e
h
ig
h
e
s
t
f
it
n
es
s
v
al
u
e
t
h
an
P
SO
-
2
an
d
P
SO
-
3
.
T
h
e
i
n
er
tia
w
ei
g
h
t
o
f
P
SO
-
2
a
n
d
P
SO
-
3
m
a
y
r
ed
u
ce
th
e
av
er
a
g
e
f
it
n
es
s
s
i
n
ce
as
f
o
u
n
d
i
n
i
n
e
r
tia
w
ei
g
h
t
e
x
p
er
i
m
e
n
tatio
n
;
th
e
i
n
er
tia
w
ei
g
h
t
ab
o
v
e
0
.
7
co
u
ld
r
ed
u
ce
th
e
av
er
ag
e
f
it
n
es
s
.
Ho
w
e
v
er
,
P
SO
-
3
is
m
o
r
e
s
tab
le
t
h
an
P
SO
-
1
an
d
P
SO
-
2
as
s
h
o
w
n
in
t
h
e
lo
w
es
t
s
ta
n
d
ar
d
d
ev
iatio
n
t
h
at
f
o
u
n
d
i
n
1
1
A
an
d
1
3
A
.
T
h
e
s
i
m
u
latio
n
r
es
u
lts
s
h
o
w
u
s
t
h
at
g
o
o
d
p
ar
a
m
eter
c
h
o
ice
co
u
ld
i
m
p
r
o
v
e
t
h
e
f
it
n
es
s
o
r
s
o
l
u
ti
o
n
q
u
alit
y
r
at
h
er
t
h
an
j
u
s
t
p
i
ck
s
o
m
e
s
w
ar
m
s
ize,
a
n
u
m
b
er
o
f
iter
atio
n
,
a
n
d
co
n
tr
o
l
p
ar
am
eter
r
ec
o
m
m
en
d
atio
n
.
T
h
is
p
ar
am
eter
ca
n
b
e
u
s
ed
as
a
r
ef
er
en
ce
f
o
r
P
SO
to
s
o
lv
e
p
o
u
ltr
y
d
iet
f
o
r
m
u
latio
n
p
r
o
b
le
m
.
T
ab
le
5
.
T
h
e
co
m
p
ar
is
o
n
r
es
u
l
ts
o
f
P
SO
w
it
h
g
o
o
d
p
ar
am
ete
r
(
P
SO
-
1
)
,
P
SO
w
it
h
li
n
ea
r
d
ec
r
ea
s
in
g
in
er
tia
w
ei
g
h
t (
P
SO
-
2
)
,
an
d
P
SO
w
i
t
h
p
r
o
p
o
s
ed
p
a
r
am
eter
[
2
6
]
(
P
S
O
-
3)
F
o
r
mu
l
a
PSO
-
1
PSO
-
2
PSO
-
3
A
v
e
r
a
g
e
F
i
t
n
e
ss
S
t
a
n
d
a
r
d
D
e
v
i
a
t
i
o
n
A
v
e
r
a
g
e
F
i
t
n
e
ss
S
t
a
n
d
a
r
d
D
e
v
i
a
t
i
o
n
A
v
e
r
a
g
e
F
i
t
n
e
ss
S
t
a
n
d
a
r
d
D
e
v
i
a
t
i
o
n
11A
3
.
7
0
1
3
7
7
1
3
1
0
.
1
0
1
2
2
3
2
5
3
3
.
6
9
1
5
2
9
0
6
2
0
.
0
7
9
9
0
4
6
1
2
3
.
6
9
7
4
8
2
2
6
4
0
.
0
7
1
7
2
4
4
4
2
12A
7
.
2
8
7
6
5
5
9
9
9
0
.
0
6
3
3
7
0
1
2
1
7
.
2
8
2
5
6
4
8
0
.
0
5
4
0
8
3
7
3
2
7
.
2
8
5
0
4
3
8
6
7
0
.
0
8
8
0
0
6
5
3
9
13A
6
.
7
0
7
8
2
3
3
2
6
0
.
5
1
2
7
9
3
2
8
5
6
.
6
9
8
1
3
1
6
7
0
.
4
7
4
6
4
9
4
1
3
6
.
5
3
3
6
2
7
6
6
3
0
.
4
3
5
7
9
9
3
5
4
3
.
6
.
F
o
r
m
ula
t
io
n r
es
ult
T
h
is
s
ec
tio
n
p
r
ese
n
ts
t
h
e
f
o
r
m
u
latio
n
r
es
u
l
t
a
f
ter
all
g
o
o
d
p
ar
am
eter
w
er
e
o
b
tain
ed
.
T
en
d
if
f
er
en
t
in
g
r
ed
ie
n
ts
w
er
e
s
elec
ted
an
d
f
o
r
m
u
lated
b
y
P
SO
i
n
g
r
o
w
e
r
p
h
ase.
T
h
e
co
m
p
o
s
itio
n
o
f
e
ac
h
i
n
g
r
ed
ien
t
an
d
th
e
a
m
o
u
n
t
o
f
ea
c
h
n
u
tr
ien
t
ar
e
s
h
o
w
n
i
n
T
ab
le
6
an
d
7
r
es
p
ec
tiv
el
y
.
I
n
T
ab
le
6
,
n
o
t
all
i
n
g
r
ed
i
e
n
ts
ar
e
u
s
ed
w
h
ic
h
P
SO
ca
n
s
elec
t
iv
el
y
d
eter
m
i
n
e
p
r
ec
is
e
co
m
p
o
s
itio
n
.
W
h
ile
in
T
ab
le
7
,
all
n
u
tr
ien
t
r
eq
u
ir
e
m
e
n
t
s
ar
e
s
atis
f
ied
.
T
h
is
s
i
m
u
latio
n
s
h
o
w
s
t
h
at
P
SO
as
p
r
o
m
is
i
n
g
alg
o
r
ith
m
to
s
o
lv
e
f
ee
d
f
o
r
m
u
la
tio
n
p
r
o
b
le
m
,
p
ar
ticu
lar
l
y
i
n
la
y
in
g
h
e
n
s
.
T
ab
le
5
.
I
n
g
r
ed
ien
ts
C
o
m
p
o
s
it
io
n
an
d
C
o
s
t
I
n
g
r
e
d
i
e
n
t
C
o
mp
o
si
t
i
o
n
C
o
st
/
K
g
.
C
o
r
n
B
r
a
n
2
4
.
1
6
6
%
I
D
R
9
6
6
.
6
4
W
h
e
a
t
0%
I
D
R
0
M
e
n
i
r
1
5
.
1
1
8
%
I
D
R
9
0
7
.
0
8
P
o
l
l
a
r
d
7
.
5
3
1
%
I
D
R
1
7
3
.
2
1
3
C
o
t
t
o
n
S
e
e
d
M
e
a
l
4
.
5
5
3
%
I
D
R
1
1
3
.
8
2
5
S
o
y
b
e
a
n
M
e
a
l
5
.
3
6
9
%
I
D
R
1
6
1
.
0
7
F
o
k
a
4
2
.
4
2
8
%
I
D
R
8
4
8
.
5
6
M
B
M
0
.
1
4
6
%
I
D
R
7
.
3
B
l
o
o
d
F
l
o
u
r
0
.
3
3
3
%
I
D
R
1
6
.
6
5
B
o
n
e
F
l
o
u
r
0
.
3
5
6
%
I
D
R
2
1
.
3
6
T
O
TA
L
I
D
R
3
,
2
1
5
.
6
9
8
T
ab
le
6
.
Nu
tr
ien
t P
en
alt
y
N
u
t
r
i
e
n
t
A
mo
u
n
t
R
e
q
u
i
r
e
me
n
t
D
e
scri
p
t
i
o
n
M
e
t
0
.
3
M
i
n
.
0
.
3
0
S
a
t
i
sf
i
e
d
P
0
.
4
6
M
i
n
.
0
.
4
6
S
a
t
i
sf
i
e
d
L
y
s
0
.
7
M
i
n
.
0
.
7
0
S
a
t
i
sf
i
e
d
CF
0
.
0
M
a
x
.
8
.
0
0
S
a
t
i
sf
i
e
d
C
P
1
5
.
5
M
i
n
.
1
5
.
5
0
S
a
t
i
sf
i
e
d
T
h
r
e
0
.
5
M
i
n
.
0
.
5
0
S
a
t
i
sf
i
e
d
T
r
y
p
0
.
1
7
M
i
n
.
0
.
1
7
S
a
t
i
sf
i
e
d
Ca
0
.
8
0
.
8
0
–
1
.
2
0
S
a
t
i
sf
i
e
d
M
e
t
+
C
y
s
0
.
6
M
i
n
.
0
.
6
0
S
a
t
i
sf
i
e
d
N
u
t
r
i
e
nt
A
mo
u
n
t
R
e
q
u
i
r
e
me
n
t
D
e
scri
p
t
i
o
n
F
3
.
0
M
i
n
.
3
.
0
0
S
a
t
i
sf
i
e
d
EM
2
,
7
0
0
M
i
n
.
2
,
7
0
0
S
a
t
i
sf
i
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.