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a
)
31
c
on
t
e
n
t
g
e
n
e
r
a
t
i
o
n
,
c
r
e
a
t
i
n
g
a
d
a
p
t
i
v
e
,
a
n
d
c
h
a
l
l
e
ng
i
ng
d
yn
a
m
i
c
s
i
n
g
a
m
e
s
[1
]
.
I
n
a
dd
i
t
i
o
n,
s
e
v
e
r
a
l
s
t
u
di
e
s
us
e
ra
c
i
ng
g
a
m
e
s
a
s
re
s
e
a
r
c
h
ob
j
e
c
t
s
s
u
c
h
a
s
o
ve
rt
a
k
i
n
g
r
a
c
i
ng
ga
m
e
s
i
n
ga
m
e
s
s
u
c
h
a
s
G
r
a
n
T
ur
i
s
m
o
S
p
or
t
[
2]
a
nd
a
s
ys
t
e
m
a
t
i
c
m
o
de
l
fo
r
t
h
e
s
u
c
c
e
s
s
fu
l
i
m
p
l
e
m
e
n
t
a
t
i
o
n
of
e
du
c
a
t
i
o
na
l
r
a
c
i
n
g
ga
m
e
s
[3]
.
T
h
i
s
c
o
nc
e
pt
c
a
n
be
a
da
pt
e
d
i
n
t
h
e
d
e
s
i
gn
of
e
du
c
a
t
i
on
a
l
ra
c
i
ng
g
a
m
e
s
t
o
c
o
v
e
r
v
a
r
i
ous
us
e
r
gr
oups
.
M
e
a
nw
h
i
l
e
,
t
e
c
hn
ol
og
i
c
a
l
i
nn
ov
a
t
i
ons
s
u
c
h
a
s
3
D
s
m
a
r
t
gl
ov
e
s
c
a
n
w
o
rk
w
e
l
l
i
n
ra
c
i
ng
g
a
m
e
s
[
4]
,
op
e
n
i
n
g
up
o
ppo
rt
un
i
t
i
e
s
t
o
e
nh
a
nc
e
hu
m
a
n
-
m
a
c
hi
n
e
i
n
t
e
r
a
c
t
i
on
i
n
g
a
m
e
s
,
e
n
a
b
l
i
ng
m
o
re
i
m
m
e
rs
i
ve
a
nd
i
n
t
u
i
t
i
v
e
e
xp
e
ri
e
n
c
e
s
.
In
t
h
e
c
on
t
e
xt
of
m
e
nt
a
l
h
e
a
l
t
h
,
o
ne
s
t
udy
r
e
ve
a
l
e
d
t
ha
t
c
o
m
m
e
rc
i
a
l
ga
m
e
s
c
a
n
be
us
e
d
t
o
r
e
du
c
e
s
t
re
s
s
[5]
a
nd
re
du
c
e
a
nxi
e
t
y
i
n
c
hi
l
dre
n
[6
]
s
ugg
e
s
t
i
ng
t
h
a
t
s
i
m
i
l
a
r
t
e
c
hnol
ogi
e
s
c
a
n
be
a
ppl
i
e
d
i
n
e
du
c
a
t
i
on
a
l
ra
c
i
ng
-
b
a
s
e
d
g
a
m
e
s
t
o
c
r
e
a
t
e
a
s
upp
ort
i
ve
l
e
a
rni
n
g
e
nv
i
ron
m
e
n
t
.
W
i
t
h
t
h
e
i
nt
e
gr
a
t
i
on
of
t
h
e
s
e
e
l
e
m
e
nt
s
,
a
s
a
l
s
o
i
l
l
us
t
ra
t
e
d
i
n
"
T
h
e
r
a
c
i
ng
ga
m
e
,
"
t
he
d
e
v
e
l
op
m
e
nt
of
e
duc
a
t
i
on
a
l
r
a
c
i
ng
ga
m
e
s
c
a
n
c
r
e
a
t
e
i
nt
e
ra
c
t
i
ve
s
ol
ut
i
ons
t
ha
t
s
uppo
rt
l
e
a
rn
i
ng
w
hi
l
e
i
m
provi
ng
us
e
r
w
e
l
l
-
be
i
n
g
[7]
.
Ra
c
i
n
g
g
a
m
e
s
a
re
a
t
yp
e
of
g
a
m
e
ge
nre
[8]
i
n
w
hi
c
h
pl
a
ye
rs
c
on
t
rol
ve
h
i
c
l
e
s
t
o
c
o
m
pe
t
e
i
n
r
a
c
e
s
.
T
h
e
t
yp
e
s
of
v
e
hi
c
l
e
s
us
e
d
i
n
t
h
e
g
a
m
e
c
a
n
be
c
a
rs
,
m
ot
or
c
y
c
l
e
s
,
bo
a
t
s
a
n
d
m
a
ny
ot
he
r
v
e
hi
c
l
e
s
.
R
a
c
i
n
g
g
a
m
e
s
ha
v
e
s
e
v
e
ra
l
t
yp
e
s
of
ra
c
i
ng
fi
e
l
ds
s
uc
h
a
s
c
i
rc
u
i
t
s
[9
],
[10]
,
s
t
r
e
e
t
s
,
dra
g
[11]
,
a
nd
of
f
-
roa
d
[12
]
.
Ra
c
i
ng
g
a
m
e
s
r
e
qui
re
s
e
ve
r
a
l
e
l
e
m
e
n
t
s
s
uc
h
a
s
vi
s
ua
l
or
g
r
a
ph
i
c
di
s
p
l
a
ys
,
i
n
t
e
r
a
c
t
i
ons
[13]
,
a
n
d
c
ha
l
l
e
ng
e
s
i
n
t
he
g
a
m
e
pl
a
y
a
n
i
m
por
t
a
n
t
rol
e
i
n
a
t
t
r
a
c
t
i
ng
pl
a
y
e
rs
.
F
ro
m
v
a
ri
ous
t
yp
e
s
of
r
a
c
i
ng
g
a
m
e
s
,
t
he
re
i
s
us
ua
l
l
y
a
m
e
nu
for
s
e
l
e
c
t
i
ng
a
ve
h
i
c
l
e
,
w
hi
c
h
w
i
l
l
l
a
t
e
r
be
l
oc
a
t
e
d
i
n
t
h
e
m
e
nu
opt
i
ons
w
hi
c
h
w
i
l
l
l
a
t
e
r
b
e
c
o
m
e
a
n
i
m
por
t
a
nt
fa
c
t
o
r
a
s
a
d
e
t
e
r
m
i
n
a
nt
of
s
a
t
i
s
fa
c
t
i
on
a
nd
vi
c
t
ory
i
n
p
l
a
y
i
ng
.
P
l
a
y
e
rs
a
re
fa
c
e
d
w
i
t
h
va
r
i
ous
c
on
fl
i
c
t
i
ng
v
e
hi
c
l
e
c
r
i
t
e
ri
a
du
ri
ng
t
h
e
c
a
r
s
e
l
e
c
t
i
on
proc
e
s
s
.
F
or
e
x
a
m
pl
e
,
hi
gh
-
s
pe
e
d
c
a
rs
t
e
nd
t
o
h
a
ve
l
ow
e
r
c
o
nt
rol
,
w
hi
l
e
fue
l
-
e
ff
i
c
i
e
nt
c
a
rs
us
u
a
l
l
y
do
n'
t
h
a
ve
hi
gh
a
c
c
e
l
e
r
a
t
i
on.
T
h
i
s
c
o
nfl
i
c
t
be
t
w
e
e
n
p
e
rfor
m
a
n
c
e
a
t
t
r
i
but
e
s
be
c
o
m
e
s
t
he
c
or
e
i
s
s
ue
i
n
t
he
ve
h
i
c
l
e
s
e
l
e
c
t
i
on
pr
obl
e
m
.
A
p
l
a
y
e
r'
s
a
bi
l
i
t
y
t
o
w
i
n
ra
c
e
s
d
e
pe
nds
o
n
fi
nd
i
ng
t
he
r
i
gh
t
ba
l
a
nc
e
a
m
ong
t
h
e
s
e
c
ri
t
e
r
i
a
,
w
hi
c
h
va
ry
de
p
e
ndi
ng
on
g
a
m
e
p
l
a
y
s
t
y
l
e
a
nd
s
k
i
l
l
l
e
v
e
l
.
Re
s
e
a
rc
h
e
rs
c
ons
i
d
e
r
t
ha
t
r
a
t
h
e
r
t
ha
n
us
i
ng
a
ra
n
dom
i
z
e
s
ys
t
e
m
i
n
t
h
e
m
e
n
u
op
t
i
ons
,
i
t
i
s
be
t
t
e
r
t
o
us
e
a
c
a
r
s
e
l
e
c
t
i
on
i
n
t
h
e
m
e
nu
w
hi
c
h
a
i
m
s
t
o
re
c
o
m
m
e
nd
t
he
be
s
t
o
pt
i
ons
f
or
p
l
a
ye
rs
t
o
us
e
b
a
s
e
d
on
t
h
e
pl
a
y
e
r'
s
e
xpe
r
i
e
nc
e
i
n
pl
a
yi
ng
t
h
e
ga
m
e
,
w
hi
c
h
c
a
n
m
a
ke
i
t
e
a
s
i
e
r
for
pl
a
ye
rs
t
o
de
t
e
r
m
i
n
e
t
h
e
i
r
c
hoi
c
e
s
t
o
s
upport
t
he
i
r
l
e
ve
l
of
s
a
t
i
s
fa
c
t
i
on
i
n
pl
a
yi
ng
t
he
ga
m
e
.
W
i
t
h
t
ha
t
,
t
he
d
e
ve
l
op
m
e
n
t
of
"
M
oon
l
i
g
ht
d
r
i
ve
"
n
ot
onl
y
fo
c
us
e
s
on
g
a
m
e
pl
a
y,
but
t
hi
s
ga
m
e
a
l
s
o
pr
i
ori
t
i
z
e
s
t
h
e
e
ffe
c
t
i
ve
g
a
m
e
m
e
nu
s
e
c
t
i
on
,
e
s
pe
c
i
a
l
l
y
i
n
t
e
r
m
s
of
s
e
l
e
c
t
i
ng
t
h
e
c
a
r
or
ve
h
i
c
l
e
us
e
d.
A
s
i
m
ul
a
t
i
on
ga
m
e
d
e
s
i
gne
d
e
s
p
e
c
i
a
l
l
y
for
t
h
i
s
pu
rpos
e
w
a
s
t
e
s
t
e
d
for
t
hi
s
i
nv
e
s
t
i
ga
t
i
on
.
W
i
t
h
c
r
i
t
e
ri
a
l
i
k
e
s
pe
e
d,
a
c
c
e
l
e
ra
t
i
on,
fu
e
l
c
ons
um
pt
i
on,
a
nd
a
u
t
om
obi
l
e
pri
c
e
t
ha
t
r
e
fl
e
c
t
re
a
l
-
w
orl
d
p
e
rfor
m
a
nc
e
,
t
h
e
ga
m
e
s
e
t
t
i
ng
re
p
l
i
c
a
t
e
s
a
ve
h
i
c
l
e
ra
c
i
ng
s
c
e
n
a
ri
o
.
T
o
m
a
k
e
s
ur
e
t
he
r
e
s
ul
t
s
a
re
s
t
i
l
l
a
pp
l
i
c
a
b
l
e
,
ve
hi
c
l
e
da
t
a
a
nd
e
v
a
l
u
a
t
i
on
c
ri
t
e
r
i
a
w
e
re
c
r
e
a
t
e
d
a
rt
i
fi
c
i
a
l
l
y
but
w
e
re
b
a
s
e
d
o
n
ga
m
e
l
ogi
c
a
nd
a
c
t
u
a
l
ga
m
e
pl
a
y
e
xp
e
ri
e
nc
e
.
S
e
ve
r
a
l
pr
e
vi
ous
s
t
ud
i
e
s
h
a
ve
d
e
v
e
l
op
e
d
a
rt
i
fi
c
i
a
l
i
n
t
e
l
l
i
ge
n
c
e
–
b
a
s
e
d
(A
I
-
ba
s
e
d)
a
nd
m
u
l
t
i
-
c
ri
t
e
ri
a
a
ppro
a
c
h
e
s
t
o
ga
m
e
re
c
o
m
m
e
nd
a
t
i
on
s
ys
t
e
m
s
.
F
or
e
x
a
m
pl
e
,
t
he
r
e
s
e
a
rc
h
us
e
d
t
he
pr
e
fe
r
e
nc
e
ra
n
ki
ng
orga
n
i
z
a
t
i
on
m
e
t
hod
for
e
nr
i
c
h
m
e
nt
e
v
a
l
u
a
t
i
on
(P
RO
M
E
T
H
E
E
)
m
e
t
hod
i
n
a
n
e
nd
l
e
s
s
r
unne
r
g
a
m
e
t
o
re
c
o
m
m
e
nd
c
ha
ra
c
t
e
rs
b
a
s
e
d
on
m
a
p
c
h
a
l
l
e
n
ge
s
[14]
.
T
he
r
e
c
o
m
m
e
nd
a
t
i
on
for
m
ul
t
i
-
p
l
a
ye
r
on
l
i
n
e
b
a
t
t
l
e
a
re
n
a
g
a
m
e
s
us
i
ng
gr
a
ph
c
onv
ol
u
t
i
on
ne
t
w
ork
w
i
t
h
fe
w
e
r
p
a
ra
m
e
t
e
rs
(
M
O
BA
Re
c
-
G
CN
F
P
)
s
t
u
dy
a
ppl
i
e
d
a
gra
ph
c
onvo
l
ut
i
on
n
e
t
w
ork
t
o
s
e
l
e
c
t
t
he
r
i
ght
c
h
a
m
p
i
on
i
n
a
m
ul
t
i
p
l
a
y
e
r
on
l
i
n
e
ba
t
t
l
e
a
re
n
a
(M
O
BA
)
g
a
m
e
,
c
ons
i
d
e
ri
n
g
s
yn
e
rgi
e
s
a
nd
c
o
unt
e
rpi
c
ks
[
15]
.
M
e
a
nw
h
i
l
e
,
s
t
udi
e
s
by
[16]
–
[1
8]
d
e
m
ons
t
r
a
t
e
d
t
he
i
m
por
t
a
nc
e
of
pe
rs
ona
l
i
z
a
t
i
on
i
n
e
duc
a
t
i
ona
l
ga
m
e
s
t
hro
ugh
a
d
a
pt
i
ve
s
c
e
na
r
i
os
a
nd
dyn
a
m
i
c
di
ff
i
c
ul
t
y
s
e
t
t
i
ngs
ba
s
e
d
on
pl
a
y
e
r
p
a
r
a
m
e
t
e
rs
.
T
h
e
a
ppro
a
c
h
i
n
t
hi
s
s
t
udy
di
ff
e
r
e
nt
i
a
t
e
s
i
t
s
e
l
f
fro
m
pr
e
vi
o
us
re
s
e
a
r
c
h
b
y
i
nc
orp
ora
t
i
ng
t
h
e
m
ul
t
i
-
o
bj
e
c
t
i
ve
o
pt
i
m
i
z
a
t
i
on
on
t
h
e
ba
s
i
s
of
r
a
t
i
o
a
n
a
l
ys
i
s
(
M
O
O
RA
)
m
e
t
hod
t
o
s
e
l
e
c
t
v
e
hi
c
l
e
s
t
a
i
l
or
e
d
t
o
pl
a
y
e
r
pe
r
form
a
n
c
e
i
n
p
re
v
i
ous
ga
m
e
pl
a
y
s
e
s
s
i
ons
.
U
n
l
i
k
e
a
ppro
a
c
h
e
s
i
n
a
u
t
o
m
ot
i
ve
e
ngi
ne
e
ri
ng
or
v
e
hi
c
l
e
de
s
i
gn
t
h
a
t
f
oc
us
o
n
t
e
c
h
ni
c
a
l
s
pe
c
i
f
i
c
a
t
i
ons
,
t
h
i
s
a
pp
roa
c
h
pri
or
i
t
i
z
e
s
pl
a
ye
r
e
x
pe
r
i
e
n
c
e
,
g
a
m
e
p
l
a
y
ut
i
l
i
t
y
,
a
nd
pe
rs
on
a
l
us
e
r
e
nga
ge
m
e
n
t
.
T
h
e
us
e
of
t
h
e
M
O
O
R
A
m
e
t
ho
d
h
a
s
b
e
c
om
e
o
ne
of
t
h
e
p
opu
l
a
r
a
ppr
o
a
c
he
s
i
n
d
e
c
i
s
i
o
n
m
a
k
i
ng
,
e
s
p
e
c
i
a
l
l
y
i
n
t
h
e
m
a
nu
fa
c
t
ur
i
n
g
e
n
vi
r
on
m
e
n
t
[
19]
,
[2
0]
m
a
t
e
r
i
a
l
s
e
l
e
c
t
i
on
[21
]
,
s
c
ho
l
a
rs
h
i
p
r
e
c
i
p
i
e
n
t
s
[
22]
a
nd
be
s
t
t
e
c
hn
i
q
u
e
s
[2
3]
.
In
ot
he
r
s
t
u
di
e
s
,
s
e
v
e
r
a
l
c
o
l
l
a
bor
a
t
i
on
s
a
nd
c
o
m
pa
ri
s
ons
w
e
r
e
c
a
r
ri
e
d
ou
t
s
u
c
h
a
s
t
he
M
O
O
RA
m
e
t
ho
d
e
x
t
e
nd
e
d
w
i
t
h
t
h
e
fu
z
z
y
c
o
nc
e
pt
[2
4]
,
t
h
e
s
i
m
pl
e
a
dd
i
t
i
v
e
w
e
i
gh
t
i
ng
(S
A
W
)
a
nd
M
O
O
RA
m
e
t
hods
w
e
re
a
l
s
o
c
o
m
p
a
r
e
d
us
i
ng
r
a
nk
or
de
r
c
e
nt
ro
i
d
(RO
C)
,
M
O
O
RA
w
i
t
h
f
u
z
z
y
F
e
r
m
a
t
e
a
n
[25
]
,
s
h
ow
i
ng
how
RO
C
c
a
n
s
t
r
e
ng
t
h
e
n
t
h
e
d
e
t
e
r
m
i
na
t
i
on
of
a
t
t
r
i
b
ut
e
w
e
i
gh
t
s
i
n
t
he
d
e
c
i
s
i
o
n
-
m
a
ki
ng
pr
oc
e
s
s
[2
6]
.
By
c
o
m
b
i
n
i
n
g
R
O
C
ba
s
e
d
w
e
i
gh
t
i
ng
w
i
t
h
t
he
M
O
O
R
A
m
e
t
h
o
d,
t
he
s
ys
t
e
m
w
i
l
l
pr
ov
i
d
e
re
c
o
m
m
e
n
da
t
i
ons
fo
r
c
a
rs
t
h
a
t
c
a
n
be
us
e
d
by
p
l
a
y
e
rs
ba
s
e
d
on
t
he
pl
a
y
e
r'
s
a
b
i
l
i
t
y
a
n
d
p
l
a
yi
ng
s
t
y
l
e
.
F
o
c
us
i
n
g
on
t
he
c
a
r
s
e
l
e
c
t
i
on
m
e
nu
us
i
ng
a
m
or
e
m
o
de
rn
s
e
l
e
c
t
i
on
un
l
i
k
e
m
a
ny
ot
h
e
r
ga
m
e
s
w
i
l
l
gi
ve
p
l
a
ye
rs
s
a
t
i
s
f
a
c
t
i
o
n
,
w
h
i
l
e
a
l
s
o
prov
i
d
i
n
g
a
n
e
l
e
m
e
nt
o
f
s
t
r
a
t
e
gy
i
n
c
ho
os
i
ng
t
h
e
c
a
r
t
h
a
t
be
s
t
s
ui
t
s
t
h
e
c
h
a
l
l
e
n
ge
s
t
h
e
y
w
i
l
l
f
a
c
e
.
2.
M
ET
H
O
D
A
m
a
j
o
r
ob
s
t
a
c
l
e
i
n
d
e
c
i
s
i
on
-
m
a
k
i
ng
p
ro
c
e
d
ur
e
s
i
s
m
u
l
t
i
-
c
r
i
t
e
ri
a
d
e
c
i
s
i
on
-
m
a
k
i
ng
(M
CD
M
)
[2
7
]
,
[2
8]
w
hi
c
h
s
e
e
ks
t
o
de
t
e
r
m
i
n
e
t
he
b
e
s
t
op
t
i
on
by
t
a
ki
n
g
i
n
t
o
a
c
c
o
unt
a
n
um
b
e
r
of
c
ri
t
e
r
i
a
.
T
o
prov
i
de
a
s
ys
t
e
m
a
t
i
c
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2722
-
3221
Com
pu
t
S
c
i
Inf
T
e
c
h
nol
,
V
o
l
.
7
,
N
o
.
1
,
M
a
rc
h
202
6
:
30
-
45
32
a
nd
s
t
ru
c
t
ur
e
d
a
p
proa
c
h
,
t
hi
s
s
t
ud
y
us
e
s
a
c
o
m
bi
n
a
t
i
on
of
RO
C
[29]
m
e
t
hodo
l
ogy
us
e
d
t
o
m
e
a
s
ur
e
a
nd
de
t
e
rm
i
ne
t
he
w
e
i
gh
t
of
e
a
c
h
r
e
s
e
a
rc
h
v
a
ri
a
bl
e
or
i
n
t
hi
s
s
t
u
dy
r
e
fe
rre
d
t
o
a
s
c
r
i
t
e
ri
a
i
n
ord
e
r
t
o
f
a
c
i
l
i
t
a
t
e
t
he
us
e
of
t
he
m
a
i
n
m
e
t
hod
de
c
i
s
i
o
n,
n
a
m
e
l
y
M
O
O
RA
a
s
a
m
ul
t
i
-
c
r
i
t
e
ri
a
pr
oc
e
s
s
op
t
i
m
i
z
e
r
s
i
m
ul
t
a
n
e
ous
l
y.
T
h
i
s
m
e
t
hod
e
ff
e
c
t
i
v
e
l
y
c
o
m
bi
ne
s
pos
i
t
i
ve
a
s
pe
c
t
s
(be
n
e
fi
c
i
a
l
c
r
i
t
e
ri
a
)
a
nd
n
e
ga
t
i
v
e
a
s
pe
c
t
s
(
a
dv
e
rs
e
c
ri
t
e
ri
a
)
i
n
a
n
e
va
l
ua
t
i
on
t
o
d
e
t
e
rm
i
ne
t
he
be
s
t
c
hoi
c
e
.
B
e
ne
fi
c
i
a
l
c
r
i
t
e
ri
a
,
s
uc
h
a
s
e
ffi
c
i
e
nc
y
a
nd
pr
ofi
t
a
b
i
l
i
t
y
,
t
h
e
hi
ghe
r
t
he
va
l
u
e
t
h
e
be
t
t
e
r.
C
onve
rs
e
l
y
,
d
e
t
r
i
m
e
nt
a
l
c
ri
t
e
r
i
a
,
s
uc
h
a
s
c
o
s
t
a
nd
t
i
m
e
,
t
he
l
ow
e
r
t
he
v
a
l
u
e
t
h
e
be
t
t
e
r.
T
hus
,
M
O
O
RA
i
s
a
bl
e
t
o
c
h
oos
e
t
h
e
m
os
t
op
t
i
m
a
l
a
l
t
e
rn
a
t
i
ve
by
c
o
ns
i
de
r
i
ng
a
l
l
re
l
e
v
a
nt
f
a
c
t
ors
.
2.
1
.
R
an
k
o
r
d
e
r
c
e
n
t
r
oi
d
T
he
RO
C
m
e
t
hod
i
s
one
of
t
he
de
c
i
s
i
on
-
m
a
k
i
ng
t
e
c
h
ni
q
ue
s
t
ha
t
c
a
n
b
e
us
e
d
t
o
d
e
t
e
rm
i
n
e
t
he
ra
nki
ng
or
pri
ori
t
y
of
s
e
v
e
ra
l
a
l
t
e
rn
a
t
i
ve
s
ba
s
e
d
on
pre
de
t
e
r
m
i
n
e
d
w
e
i
gh
t
s
.
T
h
e
w
e
i
gh
t
i
ng
i
n
RO
C
i
nvo
l
ve
s
t
he
us
e
of
r
e
l
a
t
i
ve
r
a
nki
n
gs
of
e
a
c
h
a
l
t
e
rna
t
i
v
e
ba
s
e
d
on
c
e
rt
a
i
n
c
ri
t
e
ri
a
[3
0]
.
In
t
he
c
ont
e
xt
of
d
e
t
e
rm
i
n
i
ng
w
e
i
gh
t
s
,
RO
C
i
s
us
e
d
t
o
e
va
l
ua
t
e
h
ow
w
e
l
l
t
he
c
r
i
t
e
ri
a
c
a
n
di
s
t
i
ngu
i
s
h
e
a
c
h
e
x
i
s
t
i
ng
a
l
t
e
rn
a
t
i
ve
,
w
hi
c
h
i
s
de
s
i
r
e
d
a
nd
w
hi
c
h
i
s
n
ot
.
In
(1
)
RO
C
t
o
d
e
t
e
r
m
i
n
e
t
he
w
e
i
gh
t
of
t
h
e
i
-
t
h
c
ri
t
e
ri
on
.
=
1
(
1
+
1
+
1
+
…
+
1
)
(1)
W
he
r
e
Wi
is
w
e
i
ght
for
t
he
i
-
t
h
c
ri
t
e
ri
on
;
k
i
s
t
ot
a
l
nu
m
b
e
r
of
c
ri
t
e
r
i
a
;
i
i
s
r
a
nk
of
t
h
e
i
-
t
h
c
ri
t
e
ri
on
(fro
m
hi
ghe
s
t
t
o
l
ow
e
s
t
r
a
nk)
;
a
nd
n
i
s
t
ot
a
l
nu
m
be
r
o
f
a
l
t
e
rn
a
t
i
ve
s
or
c
ri
t
e
ri
a
2.
2
.
M
u
l
ti
-
ob
j
e
c
ti
v
e
op
t
i
m
i
z
ati
on
on
th
e
b
as
i
s
of
r
at
i
o
an
al
ys
i
s
In
t
hi
s
s
t
udy
,
t
he
a
ut
h
or
us
e
s
a
qua
n
t
i
t
a
t
i
v
e
m
e
t
hod
,
na
m
e
l
y
a
m
e
t
hod
t
h
a
t
i
s
c
a
rr
i
e
d
ou
t
s
ys
t
e
m
a
t
i
c
a
l
l
y
a
nd
a
l
s
o
c
ol
l
e
c
t
s
d
a
t
a
a
nd
a
na
l
yz
e
s
t
he
s
e
l
e
c
t
i
on
i
n
t
h
e
for
m
of
nu
m
e
r
i
c
a
l
va
l
ue
s
t
ha
t
c
a
n
l
a
t
e
r
be
c
a
l
c
ul
a
t
e
d
[31]
.
T
h
e
M
O
O
RA
m
e
t
hod
i
s
a
m
e
t
h
od
i
n
t
rod
uc
e
d
b
y
Bra
u
e
rs
a
n
d
Z
a
va
dk
a
s
[32]
.
Bra
ue
rs
[33]
i
ni
t
i
a
l
l
y
us
e
d
t
h
e
n
e
w
l
y
de
v
e
l
o
pe
d
m
e
t
h
od
i
n
t
e
r
m
s
of
m
ul
t
i
-
c
r
i
t
e
ri
a
s
e
l
e
c
t
i
on
.
T
h
i
s
m
e
t
hod
i
s
a
ppl
i
e
d
a
s
a
s
ol
ut
i
on
t
o
va
r
i
ous
t
y
pe
s
of
c
o
m
pl
e
x
d
e
c
i
s
i
on
-
m
a
k
i
ng
p
ro
bl
e
m
s
i
n
t
he
m
a
nufa
c
t
uri
ng
e
nv
i
ron
m
e
n
t
us
i
ng
m
a
t
he
m
a
t
i
c
a
l
for
m
ul
a
c
a
l
c
ul
a
t
i
ons
w
i
t
h
pr
e
c
i
s
e
re
s
u
l
t
s
[34
]
.
T
he
M
O
O
RA
m
e
t
hod
i
s
a
n
i
nnov
a
t
i
ve
m
e
t
hod
t
ha
t
h
a
s
good
po
t
e
n
t
i
a
l
t
o
s
o
l
v
e
v
a
ri
ous
c
h
a
l
l
e
n
ge
s
c
ons
i
s
t
i
n
g
of
a
nu
m
b
e
r
o
f
a
t
t
r
i
bu
t
e
s
a
nd
a
l
s
o
c
onfl
i
c
t
i
ng
w
i
t
h
e
a
c
h
ot
h
e
r
.
T
he
pe
r
for
m
a
n
c
e
of
e
a
c
h
a
l
t
e
rna
t
i
v
e
i
s
d
e
t
e
r
m
i
n
e
d
b
y
c
a
l
c
u
l
a
t
i
ng
t
h
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di
ff
e
re
nc
e
b
e
t
w
e
e
n
t
h
e
t
ot
a
l
s
t
a
n
da
rd
v
a
l
u
e
s
a
s
s
oc
i
a
t
e
d
w
i
t
h
e
a
c
h
e
xi
s
t
i
ng
c
r
i
t
e
ri
o
n
[
35]
.
A
l
s
o,
t
he
re
f
e
r
e
nc
e
p
oi
n
t
a
ppro
a
c
h
c
a
n
h
e
l
p
i
de
n
t
i
fy
m
o
re
opt
i
m
a
l
a
l
t
e
r
na
t
i
v
e
c
om
b
i
na
t
i
o
ns
.
T
he
s
t
e
ps
for
s
ol
vi
ng
t
h
e
M
O
O
RA
m
e
t
hod
a
c
c
ord
i
ng
t
o
pre
vi
ous
s
t
u
dy
a
r
e
a
s
fo
l
l
ow
s
.
P
ri
o
r
w
or
ks
i
n
t
h
e
a
r
e
a
o
f
g
a
m
e
p
e
rs
on
a
l
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z
a
t
i
o
n
ha
ve
m
os
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l
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f
oc
us
e
d
on
a
da
pt
i
v
e
d
i
ff
i
c
u
l
t
y
l
e
v
e
l
s
[36
]
a
nd
r
e
a
l
-
t
i
m
e
be
ha
v
i
or
-
dr
i
v
e
n
a
dj
us
t
m
e
nt
s
[37
]
.
Re
s
e
a
rc
h
o
n
m
u
l
t
i
-
obj
e
c
t
i
v
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op
t
i
m
i
z
a
t
i
on
i
n
g
a
m
e
s
h
a
s
a
l
s
o
be
e
n
c
ondu
c
t
e
d
,
t
houg
h
t
yp
i
c
a
l
l
y
us
i
ng
fe
w
e
r
a
l
t
e
rna
t
i
ve
s
or
s
i
m
pl
e
r
c
ri
t
e
ri
a
.
T
h
e
m
a
i
n
di
s
t
i
n
c
t
i
on
i
n
t
hi
s
s
t
udy
l
i
e
s
i
n
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he
l
a
rge
r
nu
m
be
r
of
v
e
h
i
c
l
e
a
l
t
e
rn
a
t
i
ve
s
(15
o
p
t
i
ons
)
a
nd
t
h
e
m
ore
c
o
m
pr
e
he
ns
i
ve
a
nd
do
m
a
i
n
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s
pe
c
i
fi
c
c
r
i
t
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ri
a
(11
i
n
t
o
t
a
l
)
us
e
d
i
n
t
h
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M
O
O
RA
e
va
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on.
W
hi
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t
he
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pt
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m
i
z
a
t
i
o
n
m
e
t
h
od
i
t
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f
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nove
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,
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bi
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pra
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om
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ys
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m
s
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ra
c
i
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g
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m
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s
.
2.
2
.
1.
F
or
m
ati
on
of
mu
l
t
i
-
ob
je
c
ti
ve
op
ti
mi
z
ati
on
on
th
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b
as
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s
of
r
at
i
o
an
al
ys
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s
m
a
tr
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x
A
ft
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r
c
ol
l
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c
t
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t
h
e
c
r
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t
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ri
a
va
l
ue
s
on
a
l
t
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rn
a
t
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d
a
t
a
,
t
he
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xt
s
t
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p
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s
t
o
c
re
a
t
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a
M
O
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d
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c
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s
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on
m
a
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x
.
T
h
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X
m
a
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x
ha
s
di
m
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×
n,
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xpre
s
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(
2)
.
X
=
|
11
12
…
21
…
2
2
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.
.
.
1
2
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(2)
W
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is
1,
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m
;
a
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j
is
1
,
.
.
.
,
n
.
2.
2
.
2.
D
e
t
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r
mi
n
i
n
g
mu
l
ti
-
ob
j
e
c
t
i
v
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op
t
i
mi
z
at
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on
on
th
e
b
a
s
i
s
of
r
at
i
o
an
al
ys
i
s
n
or
mal
i
z
ati
on
T
he
ne
x
t
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e
p
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s
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rm
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t
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m
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on
,
w
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a
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a
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m
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m
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t
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m
e
va
l
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or
on
e
uni
fo
rm
.
T
hi
s
i
s
s
how
n
i
n
(3)
.
∗
=
√
|
∑
2
=
|
(3)
W
he
r
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x
i
j
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t
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t
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but
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
Com
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c
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Inf
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IS
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2722
-
3221
Car
s
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33
2.
2
.
3.
M
u
l
ti
-
ob
je
c
ti
v
e
op
ti
m
i
z
ati
on
on
th
e
b
as
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s
of
r
at
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o
a
n
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ys
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s
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mi
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on
c
al
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u
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at
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on
T
h
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l
a
s
t
s
t
a
g
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i
s
t
he
s
t
a
ge
t
o
c
a
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l
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t
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t
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v
a
l
u
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of
t
he
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s
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a
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=
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T
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.
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(5)
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1
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W
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pr
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be
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of
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c
c
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t
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yp
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of
a
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,
t
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de
a
l
po
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nt
s
of
t
h
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j
t
h
a
t
t
r
i
but
e
a
r
e
de
d
uc
t
e
d
fr
o
m
a
l
l
va
l
u
e
s
of
t
he
j
t
h
a
t
t
r
i
bu
t
e
.
S
o
t
ha
t
l
a
t
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r
t
h
e
r
e
s
ul
t
s
of
t
he
opt
i
m
i
z
a
t
i
on
c
a
n
be
s
ort
e
d
fro
m
t
h
e
h
i
gh
e
s
t
va
l
ue
t
o
t
he
l
ow
e
s
t
va
l
ue
.
2.
2
.
4.
Th
e
f
i
n
al
r
an
k
i
n
g
of
al
te
r
n
ati
v
e
s
Ba
s
e
d
on
t
he
pr
e
c
e
di
ng
s
t
e
p'
s
c
o
m
pu
t
a
t
i
ons
i
n
(5
),
t
he
m
a
xi
m
u
m
va
l
u
e
s
of
Y
1
for
e
a
c
h
ve
hi
c
l
e
a
l
t
e
rn
a
t
i
ve
a
re
e
s
t
a
b
l
i
s
h
e
d.
T
o
a
l
l
ow
for
d
i
re
c
t
p
e
rfor
m
a
n
c
e
c
o
m
p
a
ri
s
ons
,
t
h
e
s
e
da
t
a
a
re
t
he
n
s
or
t
e
d
i
n
de
s
c
e
ndi
n
g
ord
e
r.
A
s
a
r
e
s
ul
t
,
t
he
a
l
t
e
rna
t
i
v
e
w
i
t
h
t
he
hi
gh
e
s
t
num
e
ri
c
a
l
v
a
l
u
e
i
s
a
s
s
i
gn
e
d
t
he
h
i
gh
e
s
t
r
a
nk
,
s
ugge
s
t
i
ng
t
ha
t
i
t
i
s
t
h
e
m
os
t
opt
i
m
um
opt
i
on
for
t
h
e
p
l
a
y
e
r.
F
rom
t
he
s
e
c
a
l
c
ul
a
t
i
ons
,
t
hi
s
opt
i
on
w
i
l
l
b
e
s
e
l
e
c
t
e
d
b
y
t
h
e
g
a
m
e
s
ys
t
e
m
.
W
h
e
r
e
t
he
m
u
l
t
i
-
c
r
i
t
e
ri
a
us
e
d
a
s
t
h
e
b
a
s
i
s
for
c
a
l
c
ul
a
t
i
on
ha
s
p
rovi
d
e
d
a
c
ho
i
c
e
t
ha
t
m
us
t
be
p
a
s
s
e
d
by
t
he
g
a
m
e
pl
a
ye
r
.
2.
3
.
F
i
n
i
t
e
s
tat
e
mac
h
i
n
e
In
c
o
m
pu
t
e
r
s
c
i
e
n
c
e
,
t
h
e
f
i
n
i
t
e
s
t
a
t
e
m
a
c
h
i
n
e
(F
S
M
)
i
s
a
fu
nd
a
m
e
nt
a
l
c
o
n
c
e
p
t
f
or
m
o
d
e
l
i
n
g
s
ys
t
e
m
b
e
h
a
vi
o
r
.
E
xp
e
rt
s
ro
u
t
i
n
e
l
y
a
p
p
l
y
d
e
c
o
m
p
os
i
t
i
o
n
pr
i
n
c
i
p
l
e
s
us
i
ng
F
S
M
s
t
o
s
i
m
p
l
i
fy
c
o
m
p
l
e
x
l
o
gi
c
d
ur
i
ng
s
of
t
w
a
r
e
d
e
v
e
l
op
m
e
nt
[
38
]
.
T
h
e
s
t
a
t
e
-
a
c
t
i
o
n
d
e
c
i
s
i
on
d
i
a
g
r
a
m
d
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p
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t
s
a
s
i
m
p
l
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f
l
ow
c
h
a
r
t
w
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t
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a
d
d
i
t
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o
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l
bu
bb
l
e
s
d
e
p
i
c
t
i
n
g
p
e
n
d
i
n
g
i
np
u
t
s
t
a
t
e
s
,
w
h
i
l
e
c
o
m
m
a
nd
h
i
e
ra
r
c
hy
a
n
a
l
y
s
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s
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c
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k
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out
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or
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t
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pa
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a
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d
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a
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o
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e
how
t
h
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y
c
o
m
pa
r
e
:
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S
pe
e
d
vs
c
on
t
rol
:
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a
s
t
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h
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c
l
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s
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pe
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on
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or
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t
ra
c
ks
.
ii)
A
c
c
e
l
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ra
t
i
on
vs
fu
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l
e
ffi
c
i
e
nc
y:
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c
l
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s
w
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t
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h
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gh
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c
c
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Evaluation Warning : The document was created with Spire.PDF for Python.
Com
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Evaluation Warning : The document was created with Spire.PDF for Python.
IS
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2722
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3221
Com
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Evaluation Warning : The document was created with Spire.PDF for Python.