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.
7
,
No
.
2
,
A
p
r
il
201
7
,
p
p
.
85
8
~
8
6
8
I
SS
N:
2
0
8
8
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v7
i
2
.
p
p
8
5
8
-
8
6
8
858
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
jo
u
r
n
a
l.c
o
m/o
n
lin
e/in
d
ex
.
p
h
p
/I
JE
C
E
The Weig
hts
De
te
ction o
f
M
ul
ti
-
C
ri
teria by
u
sing
Sol
v
er
F
a
chrurr
a
zi
1
,
Yuw
a
ldi
Aw
a
y
2
,
Sa
if
ul H
us
in
3
1
,3
S
y
iah
Ku
a
la Un
iv
e
rsit
y
De
p
a
rtme
n
t
o
f
Civ
il
En
g
in
e
e
rin
g
,
I
n
d
o
n
e
sia
2
S
y
iah
Ku
a
la Un
iv
e
rsit
y
De
p
a
rt
m
e
n
t
o
f
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
,
I
n
d
o
n
e
sia
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Dec
13
,
2
0
1
6
R
ev
i
s
ed
Mar
16
,
2
0
1
7
A
cc
ep
ted
Mar
30
,
2
0
1
7
M
u
lt
i
c
rit
e
ria,
w
h
ich
a
re
g
e
n
e
ra
ll
y
u
se
d
f
o
r
d
e
c
isio
n
a
n
a
ly
sis,
h
a
v
e
c
e
rtain
c
h
a
ra
c
teristics
th
a
t
re
late
to
t
h
e
p
u
r
p
o
se
o
f
th
e
d
e
c
isio
n
.
M
u
lt
i
c
r
it
e
ria
h
a
v
e
c
o
m
p
lex
stru
c
tu
re
s
a
n
d
h
a
v
e
d
if
f
e
r
e
n
t
w
e
i
g
h
ts
d
e
p
e
n
d
in
g
u
p
o
n
th
e
c
o
n
sid
e
ra
ti
o
n
o
f
a
ss
e
ss
o
rs
a
n
d
t
h
e
p
u
rp
o
se
o
f
th
e
d
e
c
isio
n
a
lso
.
Ex
p
e
rt’s
ju
d
g
m
e
n
t
w
il
l
b
e
u
se
d
to
d
e
tec
t
t
h
e
c
rit
e
ria
w
e
ig
h
ts
th
a
t
a
p
p
li
e
d
b
y
a
ss
e
ss
o
rs.
T
h
e
a
i
m
o
f
th
is
stu
d
y
is
a
m
o
d
e
l
to
d
e
tec
t
th
e
c
rit
e
ria
w
e
ig
h
ts
a
n
d
b
ias
e
s
o
n
th
e
su
b
c
o
n
trac
to
r
se
lec
ti
o
n
a
n
d
d
e
tec
ti
n
g
th
e
sig
n
if
ica
n
t
w
e
i
g
h
ts,
a
s
d
e
c
isiv
e
c
rit
e
ria.
A
m
e
th
o
d
,
w
h
ich
is
u
se
d
t
o
m
o
d
e
li
n
g
t
h
e
w
e
ig
h
ts
d
e
tec
ti
o
n
,
is
th
e
S
o
lv
e
r
A
p
p
li
c
a
ti
o
n
.
Da
ta,
to
talin
g
4
0
se
ts,
h
a
s
b
e
e
n
c
o
l
lec
ted
th
a
t
c
o
n
sist
o
f
th
e
a
ss
e
ss
o
r’s as
se
s
s
m
e
n
t
a
n
d
th
e
e
x
p
e
rt’s
ju
d
g
m
e
n
t.
T
h
e
re
su
lt
is
a
p
a
tt
e
rn
o
f
w
e
i
g
h
ts
a
n
d
b
ias
e
s d
e
tec
ti
o
n
.
T
h
e
p
ro
p
o
se
d
m
o
d
e
l
h
a
v
e
b
e
e
n
a
b
le t
o
d
e
tec
t
o
f
2
0
c
rit
e
ria w
e
i
g
h
ts
a
n
d
b
ias
e
s,
th
a
t
c
o
n
sist o
f
4
c
rit
e
ria i
n
th
e
to
tal
w
e
i
g
h
ts
o
f
6
0
%
(a
s
d
e
c
isiv
e
c
rit
e
ria)
a
n
d
1
6
c
rit
e
ria
in
th
e
t
o
tal
w
e
ig
h
ts
o
f
4
0
%
.
A
m
o
d
e
l
h
a
s
b
e
e
n
b
u
i
l
t
b
y
train
in
g
p
ro
c
e
ss
p
e
rf
o
rm
e
d
b
y
th
e
S
o
lv
e
r
,
w
h
ich
th
e
re
su
lt
f
o
r
M
S
E
train
in
g
is
9
.
7
3
7
1
1
e
-
0
8
a
n
d
f
o
r
M
S
E
v
a
li
d
a
ti
o
n
is
0
.
0
0
9
0
0
5
2
8
.
N
o
v
e
lt
y
in
th
e
st
u
d
y
is
a
m
o
d
e
l
to
d
e
tec
t
p
a
tt
e
rn
o
f
w
e
ig
h
ts
c
rit
e
ria
a
n
d
b
ias
e
s
o
n
su
b
c
o
n
tra
c
to
r
se
lec
ti
o
n
b
y
tran
sfe
rri
n
g
th
e
e
x
p
e
rt'
s
ju
d
g
m
e
n
t
u
sin
g
S
o
lv
e
r
A
p
p
li
c
a
ti
o
n
.
K
ey
w
o
r
d
:
B
ias
w
ei
g
h
ts
C
r
iter
ia
w
eig
h
t
s
E
x
p
er
t
j
u
d
g
m
e
n
t
Mu
lti
c
r
iter
ia
So
lv
er
ap
p
licatio
n
Su
b
co
n
tr
ac
ts
Co
p
y
rig
h
t
©
2
0
1
7
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
:
Fach
r
u
r
r
az
i
,
L
ab
o
r
ato
r
y
o
f
C
i
v
il E
n
g
i
n
ee
r
i
n
g
Ma
n
a
g
e
m
e
n
t
,
S
y
ia
h
K
u
ala
Un
iv
er
s
it
y
,
I
n
d
o
n
esia.
E
m
ail:
f
ac
h
r
u
r
r
az
i@
u
n
s
y
iah
.
a
c.
id
;
f
ac
h
r
u
r
r
az
i.
u
n
s
y
iah
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
m
ai
n
co
n
tr
ac
to
r
as
a
co
m
p
an
y
w
h
o
is
r
esp
o
n
s
ib
le
f
o
r
co
m
p
let
in
g
th
e
co
n
s
tr
u
ct
io
n
wo
r
k
s
h
o
u
ld
b
e
ab
le
to
ac
t
ef
f
ec
tiv
e
l
y
a
n
d
ef
f
icie
n
tl
y
.
On
e
o
f
t
h
e
ac
tio
n
s
to
s
u
p
p
o
r
t
th
e
r
esu
l
t
is
b
y
p
ar
tn
er
in
g
w
i
th
t
h
e
r
ig
h
t
s
u
b
co
n
tr
ac
to
r
.
P
ar
tn
er
in
g
w
it
h
t
h
e
s
u
b
co
n
tr
ac
to
r
w
ill
p
r
o
v
id
e
g
o
o
d
r
es
u
lt
if
t
h
e
p
ar
tn
e
r
in
g
is
s
tar
ted
w
it
h
th
e
p
r
o
ce
s
s
o
f
q
u
ali
f
y
i
n
g
a
s
u
b
co
n
tr
ac
to
r
p
r
o
p
er
ly
,
b
y
ap
p
ly
in
g
t
h
e
d
ec
is
io
n
-
m
a
k
i
n
g
p
r
o
ce
d
u
r
e
co
r
r
ec
tly
[
1
]
.
T
h
e
p
r
o
ce
d
u
r
e
is
i
m
p
o
r
tan
t,
s
u
ch
as d
eter
m
i
n
i
n
g
t
h
e
w
ei
g
h
ts
an
d
d
ec
is
io
n
cr
iter
ia.
T
h
e
A
s
s
es
s
o
r
s
,
as
t
h
e
p
er
s
o
n
s
ar
e
d
o
in
g
t
h
e
e
v
al
u
atio
n
p
r
o
ce
s
s
f
o
r
th
e
s
elec
tio
n
o
f
s
u
b
co
n
tr
ac
to
r
s
,
o
f
ten
h
av
e
d
i
f
f
er
en
ce
s
i
n
d
ete
r
m
in
in
g
t
h
e
cr
iter
ia
w
ei
g
h
ts
a
n
d
s
o
m
eti
m
e
s
in
v
o
lv
e
s
u
b
j
ec
tiv
it
y
[
1
]
,
[
2
]
.
T
h
e
cr
iter
ia
an
d
it
s
w
e
ig
h
t
s
ar
e
n
o
t
tr
an
s
p
ar
en
t
i
n
t
h
e
s
elec
tio
n
p
r
o
ce
s
s
[
2
]
,
s
o
m
eti
m
e
s
,
w
il
l
m
a
k
e
s
t
u
m
p
ed
t
h
e
s
u
b
co
n
tr
ac
to
r
in
a
s
tr
ateg
y
to
w
i
n
t
h
e
b
id
d
in
g
p
r
o
p
o
s
al.
Su
b
co
n
tr
ac
to
r
as
p
o
ten
tial
p
ar
tn
er
s
m
u
s
t
p
er
f
o
r
m
t
h
e
p
r
o
p
er
an
aly
s
is
f
o
r
th
e
w
ei
g
h
ts
o
f
t
h
e
cr
iter
ia
t
h
at
m
o
s
t
d
e
ter
m
i
n
e
an
d
a
f
f
ec
t
th
e
a
s
s
e
s
s
m
en
t
o
f
a
s
s
es
s
o
r
s
.
I
n
co
m
p
lete
d
ata
in
f
o
r
m
atio
n
a
b
o
u
t th
e
w
ei
g
h
t
s
o
f
t
h
e
cr
iter
ia
w
ill ca
u
s
e
a
p
r
o
b
le
m
in
a
n
al
y
zin
g
.
B
ased
o
n
th
ese
b
ac
k
g
r
o
u
n
d
,
t
h
e
p
r
o
b
lem
s
to
b
e
an
s
w
er
ed
in
th
is
s
tu
d
y
ar
e
h
o
w
t
h
e
w
ei
g
h
ts
p
atter
n
o
f
th
e
cr
iter
ia
an
d
b
iases
in
t
h
e
d
ec
i
s
io
n
h
ier
ar
ch
y
s
tr
u
c
tu
r
e
s
o
f
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
th
at
ar
e
m
ad
e
b
y
th
e
as
s
es
s
o
r
s
an
d
h
o
w
to
d
ete
ct
th
e
s
i
g
n
i
f
ica
n
t
w
eig
h
t
s
as
d
ec
is
iv
e
cr
iter
ia.
I
m
p
le
m
en
tin
g
o
f
t
h
ese
o
b
j
ec
tiv
es,
it n
ee
d
s
t
h
e
ass
e
s
s
m
e
n
t o
f
ex
p
er
t’
s
j
u
d
g
m
e
n
ts
t
h
at
p
er
ce
iv
ed
w
ill r
ep
r
ese
n
t id
ea
l c
o
n
d
itio
n
s
[
2
]
.
Var
io
u
s
m
et
h
o
d
s
an
d
tec
h
n
i
q
u
es
h
av
e
b
ee
n
co
n
d
u
c
ted
to
ass
ess
th
e
cr
i
ter
ia
w
ei
g
h
t
s
,
s
u
c
h
as
Dec
is
io
n
S
u
p
p
o
r
t
Sy
s
te
m
s
(
D
SS
)
o
r
E
x
p
er
t
Sy
s
te
m
s
(
E
S),
g
en
er
all
y
d
o
n
o
t
s
u
cc
ee
d
in
tr
an
s
f
er
r
in
g
p
r
o
p
er
ly
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Th
e
W
eig
h
ts
De
tectio
n
o
f Mu
lti
-
C
r
ite
r
ia
b
y
Usi
n
g
S
o
lver (
F
a
ch
r
u
r
r
a
z
i
)
859
th
e
ex
p
er
ts
'
j
u
d
g
m
e
n
t,
m
ai
n
l
y
d
u
e
to
th
e
n
o
t
tr
an
s
p
ar
en
t
lo
g
ic
o
f
t
h
e
d
ec
is
io
n
p
r
o
ce
s
s
[
2
]
.
I
t
is
in
lin
e
w
it
h
o
p
in
io
n
o
f
Sai
f
SM
et.
al
s
tate
d
th
at
“
An
ex
p
er
t
s
y
s
te
m
s
h
o
u
ld
ab
le
to
ex
p
lain
th
e
s
o
l
u
tio
n
,
b
u
t
p
r
esen
tin
g
t
h
e
r
ea
s
o
n
f
o
r
t
h
e
r
es
u
lts
o
b
tain
e
d
w
it
h
a
n
e
u
r
al
n
et
w
o
r
k
is
d
if
f
icu
l
t
”
[
3
]
.
T
h
e
A
r
ti
f
icial
Ne
u
r
al
Net
w
o
r
k
(
N
N)
[
2
]
,
Fu
zz
y
L
o
g
ic
(
F
L
)
[
1
]
ar
e
ab
le
to
s
o
lv
e
p
r
o
b
lem
s
u
n
s
tr
u
ctu
r
ab
le,
u
n
ce
r
tai
n
t
y
an
d
a
m
b
ig
u
it
y
,
s
u
b
j
ec
tiv
it
y
an
d
also
s
u
cc
ee
d
s
to
tr
an
s
f
er
ex
p
er
t
j
u
d
g
m
e
n
t
[
2
]
.
NN
m
o
d
el
an
d
F
L
m
o
d
els
ar
e
n
o
t
id
ea
l
f
o
r
a
s
tr
u
ct
u
r
ed
p
r
o
b
lem
,
s
u
c
h
as
t
h
e
p
r
o
b
lem
o
f
m
u
lti
-
cr
iter
ia
in
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
.
T
h
e
t
w
o
m
o
d
el
ar
e
p
o
s
s
ib
le
f
o
r
a
p
r
ac
tical
an
d
p
r
ag
m
at
ic
p
u
r
p
o
s
es,
o
th
er
w
is
e
it
is
n
o
t
p
o
s
s
ib
le
f
o
r
d
ec
is
io
n
s
t
h
at
r
eq
u
ir
e
a
litt
le
b
it
f
o
r
m
al
an
d
th
e
av
ailab
ilit
y
o
f
clea
r
r
u
le
s
.
NN
m
o
d
el
an
d
FL
m
o
d
el,
w
h
ich
ar
e
in
b
lack
b
o
x
,
co
u
ld
n
o
t
an
s
w
er
ab
o
u
t
th
e
f
u
n
d
a
m
e
n
tal
q
u
e
s
tio
n
s
o
r
r
ea
s
o
n
s
to
s
u
p
p
o
r
t th
e
d
ec
is
io
n
.
T
h
is
r
esear
ch
is
p
r
o
p
o
s
ed
to
an
ticip
ate
t
h
e
p
r
o
b
lem
s
o
lv
i
n
g
o
f
w
ei
g
h
ts
d
etec
tio
n
f
o
r
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
.
Data
g
e
n
e
r
atin
g
w
i
l
l
co
n
d
u
ct
to
p
atter
n
t
h
e
cr
iter
i
a
w
ei
g
h
ts
o
f
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
d
ec
i
s
io
n
an
d
to
v
is
u
alize
th
e
p
atter
n
th
e
cr
iter
ia
w
ei
g
h
ts
,
as
p
atter
n
in
t
h
e
s
tr
u
ctu
r
e
h
ier
ar
ch
y
o
f
th
e
d
ec
is
io
n
.
T
h
e
ad
v
an
ta
g
es
o
f
t
h
e
m
et
h
o
d
s
ar
e
ab
le
to
s
h
o
w
th
e
p
atter
n
o
f
t
h
e
cr
iter
ia
w
ei
g
h
ts
d
ir
ec
tl
y
(
n
o
t
in
th
e
b
lack
b
o
x
)
in
h
ier
ar
ch
y
s
tr
u
ctu
r
e
s
o
f
d
ec
is
io
n
.
T
h
e
n
o
v
elt
y
i
n
th
is
s
tu
d
y
,
as
th
e
m
o
d
eli
n
g
th
a
t
u
s
i
n
g
t
h
e
So
lv
er
A
p
p
licatio
n
,
is
ab
ilit
y
to
d
et
ec
t
th
e
cr
iter
ia
w
eig
h
t
s
an
d
b
iases
o
f
a
s
s
e
s
s
m
e
n
ts
o
f
as
s
ess
o
r
s
a
n
d
tr
an
s
f
er
ex
p
er
t's
j
u
d
g
m
en
t,
li
k
e
m
ac
h
i
n
e
lear
n
in
g
co
n
ce
p
t,
a
n
d
it
ca
n
b
e
v
i
s
u
alize
d
as
t
h
e
s
tr
u
ct
u
r
ed
lo
g
ical
m
o
d
el
o
f
w
ei
g
h
ted
cr
iter
ia
o
n
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
d
ec
is
io
n
s
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
M
e
t
ho
d Cha
ra
ct
er
is
t
ic
Dec
is
io
n
w
it
h
m
u
l
ti
cr
iter
ia
r
ep
r
esen
ts
t
h
e
s
elec
tio
n
o
f
alter
n
ati
v
es
t
h
at
s
ati
s
f
ies
th
e
o
b
j
ec
tiv
e
s
tated
in
p
r
o
b
le
m
s
tate
m
e
n
t
[
4
]
,
[
5
]
.
T
h
e
d
ec
is
io
n
alter
n
a
tiv
e
s
(
i
)
ar
e
th
e
n
u
m
b
er
o
f
s
u
b
co
n
tr
ac
to
r
s
th
at
w
ill
b
e
ev
alu
a
ted
b
y
as
s
es
s
o
r
s
.
Mu
lti
cr
iter
ia
o
f
th
e
d
ec
is
io
n
(
j
)
a
r
e
th
e
ass
e
s
s
ed
asp
ec
ts
r
eg
ar
d
in
g
th
e
p
u
r
p
o
s
e
o
f
th
e
d
ec
is
io
n
[
6
]
.
T
h
e
cr
iter
ia
w
e
ig
h
ts
o
f
d
ec
is
io
n
(
w
)
ar
e
th
e
i
m
p
o
r
tan
ce
lev
el
s
o
f
cr
iter
ia
th
at
ar
e
p
r
o
v
id
e
p
r
o
p
o
r
tio
n
o
n
r
esu
lt
s
[
7
]
.
A
s
s
ess
m
en
t
s
o
f
a
s
s
es
s
o
r
s
(
n
)
ar
e
th
e
as
s
ess
m
e
n
t
o
f
o
b
j
ec
t
th
at
is
j
u
d
g
es
b
ased
o
n
th
e
cr
iter
ia
o
f
t
h
e
d
ec
is
io
n
.
B
iases
o
f
a
s
s
es
s
o
r
s
(
b
)
ar
e
th
e
p
r
ef
er
en
ce
s
t
h
at
ar
e
th
e
e
x
p
er
ien
ce
s
,
t
h
e
v
ie
w
o
f
lif
e,
s
u
b
j
ec
tiv
it
y
,
etc,
ass
u
m
e
d
as
b
iases
in
th
is
d
ec
is
io
n
m
o
d
el.
E
x
p
er
t’
s
j
u
d
g
m
en
t
(
t)
is
th
e
j
u
d
g
m
en
t
f
r
o
m
th
e
ex
p
er
t
w
h
o
h
a
s
ex
p
er
ie
n
ce
in
t
h
e
f
ield
s
o
f
p
r
o
cu
r
em
en
t
p
r
o
ce
s
s
an
d
h
as
t
h
e
ex
p
er
tis
e
to
d
o
th
e
ass
es
s
m
en
t
s
o
n
t
h
e
s
elec
tio
n
o
f
s
u
b
co
n
tr
ac
to
r
s
.
Fra
m
e
w
o
r
k
d
iag
r
a
m
u
s
ed
to
a
n
al
y
ze
t
h
e
cr
iter
ia
w
e
ig
h
t
s
i
n
s
er
v
e
in
t
h
e
Fi
g
u
r
e
1
.
T
h
e
co
n
ce
p
t
d
escr
ib
es
ad
j
u
s
tm
en
t
o
f
th
e
cr
iter
ia
w
eig
h
t
s
an
d
b
iases
to
f
i
n
d
p
atter
n
s
o
f
e
x
p
er
t’
s
j
u
d
g
m
e
n
t,
as
th
e
b
asis
o
f
t
h
e
s
elec
tio
n
f
o
r
as
s
es
s
o
r
s
i
n
d
ec
i
d
in
g
th
e
b
est
s
u
b
co
n
tr
ac
to
r
s
.
T
h
e
d
is
co
v
er
y
o
f
a
p
atter
n
k
n
o
w
n
a
s
th
e
lear
n
i
n
g
p
r
o
ce
s
s
th
at
is
d
o
n
e
b
y
ad
j
u
s
tin
g
t
h
e
cr
iter
ia
w
ei
g
h
ts
a
n
d
b
iases
to
g
e
n
er
ate
o
u
tp
u
t.
Go
al
o
f
t
h
e
d
esire
d
o
u
tp
u
t is eq
u
al
to
t
h
e
v
al
u
e
o
f
t
h
e
tar
g
et
th
at
i
s
th
e
e
x
p
er
t j
u
d
g
m
en
t.
T
h
e
co
n
ce
p
t
ca
n
b
e
a
p
p
lied
th
e
m
o
d
elli
n
g
p
atter
n
o
f
id
en
ti
f
i
ca
tio
n
in
o
th
er
f
ield
s
.
T
h
e
ad
v
an
tag
e
o
f
th
is
m
o
d
el
is
ab
le
to
id
en
ti
f
y
t
h
e
p
atter
n
of
t
h
e
cr
iter
ia
w
ei
g
h
ts
a
n
d
to
d
etec
t
ass
es
s
o
r
s
w
h
o
h
av
e
t
h
e
d
if
f
er
en
t
p
atter
n
b
ased
o
n
ass
e
s
s
m
e
n
t
t
h
e
e
x
p
er
t’
s
j
u
d
g
m
e
nt
.
T
h
e
So
l
v
er
m
a
y
p
er
f
o
r
m
t
h
e
v
al
u
e
o
f
th
e
cr
iter
ia
w
eig
h
t
s
an
d
th
e
b
iases
,
w
h
ic
h
h
a
v
e
f
u
r
th
er
an
al
y
s
i
s
.
A
n
a
l
y
s
is
f
o
r
s
y
s
t
e
m
u
s
ed
is
b
ased
o
n
a
Ms
E
x
c
el
w
o
r
k
s
h
ee
t
.
T
h
e
b
iases
ar
e
u
s
ed
to
a
n
al
y
ze
th
e
p
atter
n
o
f
i
n
p
u
t
d
ata
t
h
at
ar
e
d
ev
iate
t
h
e
a
v
ailab
le
d
a
ta
i
n
g
en
er
al.
T
h
is
co
n
d
itio
n
i
n
d
icate
s
t
h
at
th
e
id
en
ti
f
ica
tio
n
o
f
t
h
e
m
o
d
el
w
ill
al
s
o
b
e
u
s
ed
o
n
a
d
v
an
ce
d
s
tati
s
tical
tech
n
iq
u
es [
8
]
.
2
.
2
.
Da
t
a
Set
T
h
e
4
0
d
ataset
f
o
r
th
e
ass
e
s
s
o
r
’
s
as
s
es
s
m
en
t
s
an
d
e
x
p
er
t’
s
j
u
d
g
m
en
ts
o
f
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
h
av
e
co
llec
ted
f
r
o
m
th
e
lead
f
i
r
m
s
o
f
co
n
s
tr
u
ctio
n
t
h
at
i
s
i
n
v
o
lv
ed
in
p
r
o
j
ec
t c
o
n
s
tr
u
ctio
n
i
n
B
an
d
a
A
ce
h
.
T
h
e
d
ata
ar
e
c
o
n
s
is
t
s
o
f
th
e
as
s
es
s
o
r
’
s
as
s
ess
m
e
n
ts
as
a
n
in
p
u
t
an
d
th
e
ex
p
er
t’
s
j
u
d
g
m
e
n
ts
a
s
th
e
tar
g
et
f
o
r
th
e
m
o
d
el
d
ev
elo
p
m
e
n
t.
T
h
e
d
ata
w
ill
b
e
tr
ai
n
ed
b
y
u
s
i
n
g
t
h
e
So
lv
er
A
p
p
licatio
n
to
ad
j
u
s
t
t
h
e
cr
iter
ia
w
ei
g
h
ts
,
b
iases
an
d
t
h
e
o
u
tp
u
t
o
f
th
i
s
p
r
o
p
o
s
ed
m
o
d
el
t
h
at
is
co
m
p
ar
ed
to
w
ar
d
e
x
p
er
t’
s
j
u
d
g
m
e
n
t
[
2
]
.
T
h
e
r
esu
lt
o
f
th
is
p
r
o
p
o
s
ed
m
o
d
el,
n
a
m
el
y
th
e
w
eig
h
t
s
cr
iter
ia
an
d
b
ias
es,
w
i
ll
b
e
p
r
esen
ted
in
t
h
e
f
o
r
m
o
f
a
p
air
w
is
e
m
atr
i
x
o
f
t
h
e
cr
iter
ia
an
d
alte
r
n
ativ
e
s
.
T
h
e
d
ata
ar
e
d
iv
id
ed
in
to
2
g
r
o
u
p
s
,
w
h
ic
h
co
n
s
i
s
t
o
f
2
5
d
ataset
f
o
r
lear
n
in
g
o
f
t
h
e
p
r
o
p
o
s
ed
m
o
d
e
l a
s
p
r
esen
ted
in
T
ab
le
1
(
attac
h
ed
in
ap
p
en
d
i
x
)
an
d
1
5
d
atas
et
f
o
r
v
al
id
atio
n
o
f
th
e
p
r
o
p
o
s
ed
m
o
d
el
as p
r
esen
t
ed
in
T
ab
le
2
(
attac
h
ed
in
ap
p
en
d
ix
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
2
,
A
p
r
il 2
0
1
7
:
85
8
–
8
6
8
860
Fig
u
r
e
1
.
Fra
m
e
w
o
r
k
o
f
d
etec
t
in
g
t
h
e
cr
iter
ia
w
ei
g
h
ts
o
f
t
h
e
d
ec
is
io
n
3.
RE
SU
L
T
S
T
h
e
w
ei
g
h
ts
of
th
e
cr
iter
ia
f
o
r
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
in
t
h
is
r
esear
ch
ar
e
o
b
tain
ed
f
r
o
m
t
h
e
tr
ain
i
n
g
p
r
o
ce
s
s
by
u
s
i
n
g
t
h
e
So
lv
er
.
R
e
s
u
lt
o
f
t
h
e
cr
ite
r
ia
w
ei
g
h
ts
s
h
o
w
ed
a
u
n
i
f
o
r
m
p
atter
n
f
o
r
ea
c
h
alter
n
ati
v
e
(
p
r
o
s
p
ec
tiv
e
p
ar
tn
e
r
)
,
as
s
h
o
w
n
in
T
ab
le
3
(
attac
h
ed
in
ap
p
en
d
ix
)
.
T
h
e
b
est
tr
ai
n
in
g
t
h
e
w
ei
g
h
ts
o
f
cr
iter
ia
D
(
e
x
ec
u
tio
n
t
i
m
e)
a
n
d
E
(
t
y
p
e
o
f
p
r
o
j
ec
t
r
ef
er
en
ce
s
)
is
s
h
o
w
n
as
a
ze
r
o
v
al
u
e
f
o
r
t
h
e
b
ia
s
es
an
d
s
tan
d
ar
d
d
ev
iatio
n
.
I
t is p
o
s
s
ib
le
in
th
e
s
e
tr
ain
in
g
d
u
e
to
th
e
s
u
b
cr
iter
ia
o
n
l
y
o
n
e.
T
h
e
b
iases
,
w
h
ich
ar
e
t
h
e
v
alu
e
o
f
t
h
e
s
u
b
j
ec
tiv
e
f
ac
to
r
,
ar
e
d
if
f
er
en
ce
b
et
w
ee
n
th
e
ass
es
s
o
r
’
s
ass
es
s
m
en
t
s
to
w
ar
d
t
h
e
e
x
p
e
r
t’
s
j
u
d
g
m
en
t.
T
h
e
b
iases
ar
e
th
e
p
ar
a
m
eter
,
w
h
ic
h
ar
e
a
co
m
p
an
io
n
o
f
t
h
e
cr
iter
ia,
in
u
n
d
er
s
tan
d
i
n
g
o
f
ex
p
er
t’
s
j
u
d
g
m
e
n
t.
T
h
e
r
esu
l
t
o
f
th
e
b
iase
s
ca
n
b
e
u
s
ed
as
b
en
ch
m
ar
k
s
to
d
eter
m
in
e
a
s
s
e
s
s
o
r
s
w
h
o
h
av
e
h
i
g
h
s
u
b
j
ec
tiv
it
y
le
v
el
a
n
d
a
d
if
f
er
e
n
t
p
atter
n
f
r
o
m
t
h
e
id
ea
l
co
n
d
itio
n
s
o
f
th
e
ex
p
er
t’
s
j
u
d
g
m
e
n
t
d
ec
is
io
n
(
th
e
tar
g
et)
.
Sta
n
d
ar
d
d
ev
iatio
n
s
ar
e
v
ar
iatio
n
o
f
t
h
e
w
ei
g
h
ts
cr
iter
ia,
w
h
ich
h
a
v
e
b
ee
n
p
atter
n
ed
o
f
t
h
e
as
s
es
s
o
r
’
s
as
s
es
s
m
en
t
s
.
T
h
e
s
ta
n
d
ar
d
d
ev
iatio
n
s
h
o
w
s
a
s
m
all
t
h
e
d
if
f
er
e
n
ce
v
alu
e
,
w
h
ic
h
in
d
icate
s
th
e
u
n
if
o
r
m
in
w
ei
g
h
tin
g
p
r
o
ce
s
s
f
o
r
all
alter
n
ati
v
es (
s
u
b
co
n
tr
ac
to
r
s
)
.
4.
DIS
CU
SS
I
O
N
4
.
1
.
M
e
a
n Squ
a
re
E
rr
o
r
(
M
SE
)
T
r
ain
in
g
p
er
f
o
r
m
an
ce
b
y
t
h
e
So
lv
er
is
q
u
ite
g
o
o
d
w
ith
r
e
s
u
lt
o
f
t
h
e
MSE
tr
ai
n
i
n
g
o
f
9
.
7
3
7
1
1
e
-
0
8
.
T
r
ain
in
g
c
u
r
v
e
of
t
h
i
s
m
o
d
el
d
escr
ib
e
ch
an
g
es
i
n
er
r
o
r
d
escen
d
in
g
of
-
0
.
0
0
4
an
d
th
e
s
ig
n
i
f
i
ca
n
t
d
escen
d
i
n
g
at
th
e
e
n
d
o
f
-
0
.
0
2
.
T
h
e
d
escen
d
in
g
o
f
MSE
in
tr
ain
i
n
g
w
a
s
o
cc
u
r
r
in
g
i
n
co
n
s
tan
t
m
an
n
e
r
an
d
s
tab
le.
T
h
is
in
d
icate
s
t
h
at
t
h
e
tr
ain
i
n
g
p
r
o
ce
s
s
to
ad
ap
t th
e
p
atter
n
w
as
s
u
cc
ess
f
u
l
,
a
s
s
h
o
w
n
in
Fi
g
u
r
e
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Th
e
W
eig
h
ts
De
tectio
n
o
f Mu
lti
-
C
r
ite
r
ia
b
y
Usi
n
g
S
o
lver (
F
a
ch
r
u
r
r
a
z
i
)
861
MSE
o
f
tr
ai
n
i
n
g
o
n
t
h
e
m
ai
n
cr
iter
ia
,
n
a
m
e
l
y
th
e
s
u
b
co
n
tr
ac
to
r
cr
ed
ib
ilit
y
(
c
u
r
v
e
1
)
,
q
u
o
tatio
n
(
cu
r
v
e
2
)
,
tech
n
ical
ca
p
ab
ilit
y
(
cu
r
v
e
3
)
,
ex
ec
u
tio
n
ti
m
e
(
c
u
r
v
e
4
)
,
k
in
d
o
f
p
r
o
j
ec
t
r
ef
er
en
ce
s
(
cu
r
v
e
5
)
ar
e
s
u
cc
e
s
s
i
v
el
y
6
.
8
9
9
0
3
e
-
0
8
,
1
.
3
7
6
2
e
-
0
7
,
1
.
1
8
9
5
2
e
-
0
7
,
9
.
7
2
2
e
-
0
8
,
7
.
9
0
9
4
6
e
-
0
8
,
as sh
o
w
n
i
n
Fig
u
r
e
2
.
T
h
e
er
r
o
r
b
o
u
n
d
,
w
h
ich
ar
e
r
ed
u
ctio
n
o
f
o
u
tp
u
t
m
o
d
el
to
t
ar
g
et,
h
a
v
e
t
w
o
ex
tr
e
m
e
d
ata
o
f
15
t
h
e
er
r
o
r
b
o
u
n
d
d
ata,
n
a
m
el
y
p
o
in
t
4
an
d
6
,
as
s
h
o
w
n
i
n
F
ig
u
r
e
3
.
Ov
er
all
er
r
o
r
b
o
u
n
d
o
f
t
h
e
m
o
d
el
p
r
o
v
id
es
r
esu
lt
s
f
o
r
MSE
v
alid
atio
n
o
f
0
.
0
0
9
0
0
5
2
8
w
it
h
a
s
ta
n
d
ar
d
d
ev
iatio
n
f
o
r
th
e
s
q
u
ar
e
er
r
o
r
is
0
.
1
3
5
0
8
,
as
s
h
o
w
n
in
F
i
g
u
r
e
4
.
T
h
e
r
esu
lts
o
f
b
o
t
h
MSE
tr
ain
in
g
an
d
MSE
v
alid
atio
n
is
in
d
icatin
g
t
h
e
So
lv
er
h
as
th
e
ab
il
it
y
to
f
i
n
d
p
atter
n
s
o
f
t
h
e
cr
iter
ia
w
ei
g
h
t
s
an
d
b
iase
s
th
a
t
is
u
s
e
d
b
y
as
s
ess
o
r
s
i
n
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
.
Fu
r
t
h
er
m
o
r
e,
th
e
m
o
d
el
s
ca
n
b
e
u
s
ed
as a
m
a
n
a
g
e
m
e
n
t
's to
o
l f
o
r
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
as
w
ell.
Fig
u
r
e
2
.
T
r
ain
in
g
C
u
r
v
e
f
o
r
Mo
d
el
o
f
Su
b
co
n
tr
ac
to
r
Select
io
n
Fig
u
r
e
3
.
E
r
r
o
r
b
o
u
n
d
o
f
Valid
atio
n
d
ata
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
2
,
A
p
r
il 2
0
1
7
:
85
8
–
8
6
8
862
Fig
u
r
e
4
.
MSE
Valid
atio
n
4
.
2
.
T
he
Crit
er
ia
Weig
hts w
it
h M
a
j
o
r
I
m
pa
ct
T
h
e
r
esu
lts
o
f
th
e
w
ei
g
h
t
s
o
f
t
h
e
m
ai
n
cr
iter
ia
i
n
d
icate
u
n
if
o
r
m
it
y
f
o
r
ev
er
y
th
e
m
ain
cr
ite
r
ia
w
h
ic
h
ar
e
m
ar
k
ed
o
n
t
h
e
v
al
u
e
o
f
t
h
e
s
m
al
l
s
ta
n
d
ar
d
d
ev
iatio
n
.
T
h
e
w
ei
g
h
ts
f
o
r
ea
ch
t
h
e
cr
iter
i
a
ar
e
esti
m
a
ted
at
±
20%
w
it
h
a
v
er
ag
e
o
f
s
ta
n
d
ar
d
d
ev
iatio
n
ab
o
u
t
0
.
0
3
7
7
.
T
h
e
se
w
eig
h
t
s
s
h
o
w
t
h
e
s
a
m
e
i
m
p
o
r
ta
n
ce
le
v
el
i
n
d
ec
is
io
n
f
o
r
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
,
as
s
h
o
w
n
in
T
ab
le
4
.
Stru
ct
u
r
e
o
f
th
e
p
r
o
p
o
s
ed
m
o
d
el
ar
e
d
iv
id
ed
in
to
f
iv
e
g
r
o
u
p
s
(
m
ai
n
cr
iter
ia)
w
it
h
th
e
s
a
m
e
w
ei
g
h
ts
i
s
±
20
%.
E
ac
h
w
ei
g
h
tin
g
o
n
t
h
e
m
a
in
cr
iter
ia
w
i
ll
b
e
d
is
tr
i
b
u
ted
to
th
e
s
u
b
-
cr
iter
ia
.
T
h
e
m
ai
n
cr
iter
ia
w
it
h
m
an
y
s
u
b
-
cr
i
ter
ia
w
ill
lead
to
s
m
all
w
ei
g
h
ts
o
f
s
u
b
cr
iter
ia
.
W
eig
h
t
s
at
th
e
s
u
b
cr
iter
ia
lev
el,
th
at
co
n
s
i
s
t
o
f
A
1
to
A
1
3
,
B
1
to
B
2
,
C
1
to
C
3
,
D1
,
an
d
E
1
,
ar
e
p
r
o
d
u
ce
d
s
u
cc
es
s
f
u
ll
y
o
f
1
.
5
4
%,
1
0
%,
6
.
6
3
%,
2
0
%
an
d
2
0
%
w
it
h
a
to
tal
o
f
1
0
0
%,
T
h
is
r
esu
lts
ar
e
ill
u
s
tr
ated
at
co
lu
m
n
o
f
g
e
n
er
all
y
w
eig
h
t
s
in
T
ab
le
5
.
T
ab
le
4
.
W
eig
h
ts
An
al
y
s
is
f
o
r
th
e
Ma
in
C
r
iter
ia
o
f
t
h
e
S
u
b
co
n
tr
ac
to
r
s
Selectio
n
M
a
i
n
C
r
i
t
e
r
i
a
o
f
S
u
b
c
o
n
t
r
a
c
t
o
r
S
e
l
e
c
t
i
o
n
W
e
i
g
h
t
s Pe
r
M
a
i
n
C
r
i
t
e
r
i
a
Est
i
m
a
t
e
o
f
W
e
i
g
h
t
s
D
e
c
i
mal
P
e
r
c
e
n
t
a
g
e
S
t
a
n
d
a
r
d
D
e
v
i
a
t
i
o
n
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
0
.
1
9
4
7
1
9
.
4
7
%
0
.
0
0
4
9
2
0
%
B
.
Q
u
o
t
a
t
i
o
n
0
.
2
0
1
8
2
0
.
1
8
%
0
.
0
1
1
8
2
0
%
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
0
.
1
9
4
6
1
9
.
4
6
%
0
.
0
0
6
7
2
0
%
D
.
Ex
e
c
u
t
i
o
n
T
i
me
0
.
2
0
8
0
2
0
.
8
0
%
0
.
0
0
5
4
2
0
%
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
0
.
2
0
0
9
2
0
.
0
9
%
0
.
0
0
8
9
2
0
%
G
r
a
n
d
T
o
t
a
l
1
.
0
0
1
0
0
%
0
.
0
3
7
7
1
0
0
I
n
th
i
s
h
ier
ar
ch
y
s
tr
u
ctu
r
e,
w
e
w
i
ll
d
escr
ib
e
in
d
etail
th
e
s
i
g
n
i
f
ican
t
s
u
b
cr
iter
ia
as
d
ec
is
i
v
e
cr
iter
ia.
T
h
e
s
ig
n
i
f
ican
t
s
u
b
cr
iter
ia
ar
e
o
b
tain
ed
th
e
to
tal
w
e
ig
h
t
s
6
0
%
w
h
ic
h
is
r
ea
c
h
ed
by
4
c
r
iter
ia
(
as
d
ec
is
iv
e
cr
iter
ia)
,
n
a
m
el
y
co
m
p
r
e
s
s
io
n
o
f
s
ch
ed
u
le
(
D1
)
at
2
0
%,
n
u
m
b
er
o
f
s
i
m
ilar
p
r
o
j
ec
t
(
E
1
)
at
2
0
%,
q
u
o
tatio
n
p
r
ice
(
B
1
)
at
1
0
%,
an
d
m
et
h
o
d
o
f
p
ay
m
e
n
t
(
B
2
)
at
1
0
%
r
esp
ec
tiv
el
y
.
Me
an
w
h
ile
o
th
er
s
,
1
6
cr
iter
ia
as
in
d
ec
is
i
v
e
cr
iter
ia,
o
n
l
y
r
ea
ch
th
e
to
tal
w
eig
h
t
s
4
0
%,
as
s
h
o
w
n
in
T
ab
le
5
.
T
h
e
c
r
iter
ia
w
ei
g
h
ts
w
it
h
m
aj
o
r
i
m
p
ac
t
w
ill
g
i
v
e
k
n
o
w
led
g
e
u
s
ab
o
u
t th
e
s
tr
ate
g
ic
cr
iter
ia
to
b
e
a
n
o
m
in
ated
s
u
b
co
n
tr
ac
to
r
.
Th
e
p
r
o
p
o
s
ed
m
o
d
el
b
y
u
s
i
n
g
t
h
e
So
l
v
er
h
as
ab
ilit
y
to
d
etec
t
th
e
cr
iter
ia
w
ei
g
h
ts
i
n
d
ec
is
io
n
h
ier
ar
ch
y
s
tr
u
ct
u
r
e.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
w
as
g
en
er
ated
o
f
t
h
e
as
s
es
s
o
r
’
s
a
s
s
e
s
s
m
en
ts
by
tr
an
s
f
er
r
i
n
g
th
e
ex
p
er
t's
j
u
d
g
m
e
n
ts
.
T
h
is
p
r
o
p
o
s
ed
m
o
d
el
m
o
r
e
ad
v
an
ce
d
f
r
o
m
s
tu
d
y
o
f
H
atef
i
et.
al
an
d
G
an
g
et.
al
as
w
ell
as
,
th
at
h
as
b
ee
n
d
o
n
e
t
h
e
d
is
co
v
er
y
o
f
t
h
e
cr
iter
ia
w
eig
h
t
s
t
h
r
o
u
g
h
A
HP
(
A
n
a
l
y
t
ic
Hier
ar
ch
y
P
r
o
ce
s
s
)
m
et
h
o
d
w
h
ic
h
is
b
ased
o
n
t
h
e
r
esp
o
n
d
en
t
'
s
p
er
ce
p
tio
n
ab
o
u
t
th
e
i
m
p
o
r
tan
ce
cr
iter
ia
[
6
]
,
[
9
]
.
T
h
e
co
n
ce
p
t
tr
an
s
f
er
r
i
n
g
th
e
e
x
p
er
t's
j
u
d
g
m
en
t
b
y
u
s
i
n
g
NN
th
at
b
u
i
lt
b
y
A
lb
i
n
o
an
d
Gar
a
v
elli,
t
h
e
y
d
id
n
o
t
d
escr
ib
e
in
d
etail
ab
o
u
t
th
e
p
atter
n
o
f
th
e
cr
iter
ia
w
eig
h
ts
[2
]
,
as
w
el
l
as
Ng
u
y
e
n
VU
[1
]
.
T
h
er
ef
o
r
e,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Th
e
W
eig
h
ts
De
tectio
n
o
f Mu
lti
-
C
r
ite
r
ia
b
y
Usi
n
g
S
o
lver (
F
a
ch
r
u
r
r
a
z
i
)
863
f
u
tu
r
e
r
esear
c
h
r
eg
ar
d
in
g
t
h
e
cr
iter
ia
w
ei
g
h
ts
w
ill
co
n
d
u
c
t,
b
o
th
th
e
c
r
iter
ia
w
e
ig
h
t
s
o
f
NN
lear
n
i
n
g
a
n
d
Fu
zz
y
L
o
g
ic
a
m
b
i
g
u
it
y
,
w
o
u
l
d
b
e
s
u
b
j
ec
t to
b
ein
g
co
m
p
ar
ed
to
w
ar
d
th
is
p
r
o
p
o
s
ed
m
o
d
el
r
esear
ch
.
T
ab
le
5
.
A
n
al
y
s
i
s
f
o
r
th
e
C
r
ite
r
ia
W
eig
h
ts
f
o
r
E
ac
h
I
te
m
C
r
i
t
e
r
i
a
o
f
S
u
b
c
o
n
t
r
a
c
t
o
r
S
e
l
e
c
t
i
o
n
W
e
i
g
h
t
s Pe
r
M
a
i
n
C
r
i
t
e
r
i
a
In
G
e
n
e
r
a
l
l
y
W
e
i
g
h
t
s
S
t
a
n
d
a
r
d
D
e
v
i
a
t
i
o
n
I
n
D
e
c
i
mal
Est
i
m
a
t
e
P
e
r
c
e
n
t
a
g
e
I
n
D
e
c
i
mal
Est
i
m
a
t
e
P
e
r
c
e
n
t
a
g
e
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
1
.
C
o
mp
a
n
y
P
r
o
f
i
l
e
a
.
M
a
n
a
g
e
me
n
t
C
a
p
a
b
i
l
i
t
i
e
s
•
Q
u
a
l
i
t
y
s
y
st
e
m
-
I
S
O
C
e
r
t
i
f
i
c
a
t
i
o
n
,
s
i
mi
l
a
r
A1
0
.
0
7
6
5
7
.
7
0
%
0
.
0
1
5
4
1
.
5
4
%
0
.
0
0
1
-
Q
u
a
l
i
t
y
a
ssu
r
a
n
c
e
A2
0
.
0
7
7
1
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
1
-
C
o
mp
a
n
y
p
r
o
f
i
l
e
A3
0
.
0
7
6
6
7
.
7
0
%
0
.
0
1
5
4
1
.
5
4
%
0
.
0
0
1
•
F
i
n
a
n
c
i
a
l
S
t
a
b
i
l
i
t
y
-
B
a
l
a
n
c
e
S
h
e
e
t
A4
0
.
0
7
7
3
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
2
-
B
a
n
k
g
u
a
r
a
n
t
e
e
A5
0
.
0
7
6
6
7
.
7
0
%
0
.
0
1
5
4
1
.
5
4
%
0
.
0
0
1
b
.
T
e
c
h
n
o
l
o
g
y
C
a
p
a
b
i
l
i
t
y
•
F
a
c
i
l
i
t
i
e
s
A6
0
.
0
7
7
1
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
1
•
T
r
a
n
sp
o
r
t
A7
0
.
0
7
7
1
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
1
•
Eq
u
i
p
me
n
t
A8
0
.
0
7
6
7
7
.
7
0
%
0
.
0
1
5
4
1
.
5
4
%
0
.
0
0
1
2
.
C
o
n
t
r
a
c
t
T
r
u
st
w
o
r
t
h
y
a
.
P
r
o
j
e
c
t
Ex
p
e
r
i
e
n
c
e
A9
0
.
0
7
7
0
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
2
b
.
P
r
o
j
e
c
t
a
c
h
i
e
v
e
me
n
t
A
1
0
0
.
0
7
7
2
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
1
c
.
T
y
p
e
a
n
d
a
mo
u
n
t
o
f
i
n
su
r
a
n
c
e
A
1
1
0
.
0
7
6
2
7
.
7
0
%
0
.
0
1
5
3
1
.
5
4
%
0
.
0
0
1
d
.
R
e
g
i
st
e
r
e
d
i
n
a
s
so
c
i
a
t
i
o
n
s
A
1
2
0
.
0
7
6
9
7
.
7
0
%
0
.
0
1
5
5
1
.
5
4
%
0
.
0
0
1
e
.
C
o
mp
a
n
y
l
e
g
i
t
i
mat
e
A
1
3
0
.
0
7
6
7
7
.
7
0
%
0
.
0
1
5
4
1
.
5
4
%
0
.
0
0
1
S
u
b
T
o
t
a
l
1
.
0
0
1
0
0
%
B
.
Q
u
o
t
a
t
i
o
n
1
.
Q
u
o
t
a
t
i
o
n
P
r
i
c
e
B1
0
.
5
0
3
5
5
0
%
0
.
1
0
1
2
1
0
.
0
0
%
0
.
0
9
6
2
M
e
t
h
o
d
s o
f
p
a
y
me
n
t
B2
0
.
4
8
1
4
5
0
%
0
.
0
9
6
8
1
0
.
0
0
%
0
.
0
4
4
S
u
b
T
o
t
a
l
1
.
0
0
1
0
0
%
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
1
.
Ex
p
e
r
t
i
se
o
f
p
e
r
so
n
n
e
l
C1
0
.
3
3
1
7
3
3
.
3
3
%
0
.
0
6
6
7
6
.
6
3
%
0
.
0
2
9
2
.
S
p
e
c
i
a
l
i
z
e
s i
n
w
o
r
k
i
n
g
me
t
h
o
d
s
C2
0
.
3
4
4
5
3
3
.
3
3
%
0
.
0
6
9
3
6
.
6
3
%
0
.
0
2
5
3
.
M
a
t
e
r
i
a
l
sp
e
c
i
f
i
c
a
t
i
o
n
C3
0
.
3
1
2
9
3
3
.
3
3
%
0
.
0
6
2
9
6
.
6
3
%
0
.
0
2
3
S
u
b
T
o
t
a
l
1
.
0
0
1
0
0
%
D
.
Ex
e
c
u
t
i
o
n
T
i
me
1
.
C
o
mp
r
e
ssi
o
n
o
f
s
c
h
e
d
u
l
e
D1
1
.
0
0
0
0
1
0
0
.
0
0
%
0
.
2
0
1
1
2
0
.
0
0
%
0
.
0
0
S
u
b
T
o
t
a
l
1
.
0
0
1
0
0
%
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
1
.
N
u
mb
e
r
o
f
si
m
i
l
a
r
p
r
o
j
e
c
t
i
n
l
a
st
y
e
a
r
E1
1
.
0
0
0
0
1
0
0
.
0
0
%
0
.
2
0
1
1
2
0
.
0
0
%
0
.
0
0
S
u
b
T
o
t
a
l
1
.
0
0
1
0
0
%
G
r
a
n
d
T
o
t
a
l
1
.
0
0
1
0
0
%
4
.
3
.
B
ia
s
es o
f
t
he
Crit
er
ia
Weig
hts
I
n
ad
d
itio
n
to
h
a
v
in
g
th
e
ab
ilit
y
to
d
etec
t
th
e
w
ei
g
h
t
s
cr
ite
r
ia,
th
is
p
r
o
p
o
s
ed
m
o
d
el
ca
n
also
d
etec
t
th
e
b
iase
s
o
f
t
h
e
m
ai
n
cr
iter
ia
f
o
r
ea
ch
alter
n
ati
v
e
d
ec
is
io
n
(
in
t
h
is
ca
s
e
as
t
h
e
s
u
b
co
n
tr
ac
to
r
)
.
B
iases
in
d
icat
e
th
e
v
ar
iatio
n
d
e
g
r
ee
o
f
a
s
s
es
s
o
r
s
to
w
ar
d
ex
p
er
t
'
s
j
u
d
g
m
e
n
t
s
in
g
i
v
in
g
w
e
ig
h
t
s
to
th
e
m
a
i
n
cr
iter
ia.
B
ased
o
n
th
e
v
ar
iatio
n
o
n
d
eter
m
in
in
g
t
h
e
w
ei
g
h
ts
cr
iter
ia,
a
s
s
h
o
w
n
in
T
ab
le
6
,
s
h
o
w
s
th
e
v
ar
iatio
n
o
f
th
e
q
u
o
tatio
n
th
at
is
q
u
ite
lar
g
e
t
h
a
n
th
e
o
t
h
er
m
a
in
cr
iter
ia.
T
h
e
d
if
f
er
e
n
ce
i
n
d
eter
m
in
in
g
th
e
cr
iter
ia
w
ei
g
h
ts
b
et
w
ee
n
ea
ch
as
s
es
s
o
r
co
u
ld
b
e
m
ea
s
u
r
ed
f
r
o
m
th
e
b
ia
s
es.
T
h
e
h
i
g
h
est
b
iases
,
w
h
ic
h
w
er
e
r
es
u
lted
f
r
o
m
t
h
e
tr
ai
n
i
n
g
p
r
o
ce
s
s
,
i
n
d
icate
th
e
as
s
ess
o
r
s
u
b
j
ec
tiv
it
y
i
n
t
h
e
asp
ec
t
Q
u
o
tatio
n
,
as
s
h
o
w
n
i
n
T
ab
le
6
.
T
h
e
ass
es
s
o
r
s
m
ig
h
t
h
av
e
d
if
f
er
en
t
p
er
ce
p
t
io
n
s
ab
o
u
t
th
e
i
m
p
o
r
tan
ce
lev
el
o
f
th
e
q
u
o
tatio
n
.
Usi
n
g
th
e
p
r
o
p
o
s
ed
m
o
d
el,
w
e
co
u
ld
d
etec
t
th
e
s
u
b
j
ec
tiv
it
y
b
y
p
r
ev
ie
w
it
b
iase
s
,
t
h
u
s
,
it
c
o
u
ld
b
e
i
m
m
ed
iatel
y
eli
m
in
a
ted
f
o
r
i
m
p
r
o
v
ed
p
er
f
o
r
m
a
n
ce
o
f
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
p
r
o
ce
s
s
.
I
t
is
i
n
li
n
e
w
it
h
t
h
e
o
p
in
io
n
o
f
A
lb
in
o
V,
Gar
av
elli
AC
s
tated
t
h
at
“T
h
e
co
m
p
lex
it
y
o
f
s
u
b
co
n
tr
ac
to
r
r
atin
g
,
d
u
e
to
th
e
u
n
ce
r
tai
n
t
y
an
d
a
m
b
i
g
u
it
y
i
n
v
o
l
v
ed
in
t
h
e
d
ec
is
io
n
m
a
k
i
n
g
p
r
o
ce
s
s
,
r
eq
u
ir
es
a
f
o
r
m
aliza
tio
n
ai
m
ed
to
r
ed
u
ce
th
e
ex
p
er
t
'
s
s
u
b
j
ec
tiv
it
y
”
[2
]
.
T
h
e
s
ig
n
i
f
ica
n
t
b
iases
i
n
alter
n
ati
v
e
7
an
d
2
0
o
f
th
e
q
u
o
tatio
n
asp
ec
t
(
B
)
ar
e
s
u
cc
ess
f
u
ll
y
0
.
1
3
9
an
d
0
.
2
3
1
,
as
s
h
o
w
n
in
tab
le
3
.
T
h
ese
b
iases
in
f
o
r
m
u
s
th
a
t
th
e
p
r
o
p
o
s
ed
m
o
d
el
b
y
u
s
in
g
t
h
e
S
o
lv
er
co
u
ld
b
e
u
s
ed
to
d
etec
t
th
e
d
ev
iatio
n
s
o
f
t
h
e
ass
es
s
o
r
’
s
a
s
s
e
s
s
m
e
n
ts
to
w
ar
d
th
e
e
x
p
er
t’
s
j
u
d
g
m
e
n
t.
T
h
is
s
ch
e
m
e
in
d
icate
t
h
e
s
i
m
ilar
l
y
to
th
e
ad
v
an
ce
d
s
tat
i
s
tical
tech
n
iq
u
e
s
[
10
],
[1
1
]
.
T
h
e
s
u
b
j
ec
tiv
it
y
in
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
ar
e
r
ea
s
o
n
ab
le
th
i
n
g
s
an
d
it
h
av
e
to
ler
an
ce
s
p
ar
e
m
o
r
e
th
an
d
ec
is
io
n
s
i
n
h
i
g
h
r
is
k
.
Ot
h
er
wis
e,
b
iases
ar
e
n
o
t
allo
w
ed
(
o
r
o
n
ly
v
er
y
s
li
g
h
t
l
y
lo
o
s
e)
w
h
e
n
f
ac
ed
w
it
h
m
aj
o
r
d
ec
is
io
n
s
in
h
ig
h
r
i
s
k
,
as
w
ell
as
o
n
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
2
,
A
p
r
il 2
0
1
7
:
85
8
–
8
6
8
864
is
s
u
es
[
1
2
]
,
[
1
3
]
.
Fu
r
th
er
m
o
r
e,
th
e
p
r
o
p
o
s
ed
m
o
d
el
ca
n
b
e
ap
p
lied
in
v
ar
io
u
s
f
ield
s
w
i
th
a
h
ig
h
er
d
eg
r
ee
o
f
r
is
k
,
w
h
er
e
s
u
b
j
ec
tiv
it
y
an
d
b
i
ases
h
ig
h
l
y
av
o
id
ab
le
[
1
4
-
1
6
]
.
T
ab
le
6.
Var
iatio
n
in
Dete
r
m
i
n
ed
th
e
C
r
iter
ia
W
ei
g
h
t
s
M
a
i
n
C
r
i
t
e
r
i
a
o
f
S
u
b
c
o
n
t
r
a
c
t
o
r
S
e
l
e
c
t
i
o
n
B
i
a
se
s o
f
W
e
i
g
h
t
s Pe
r
M
a
i
n
C
r
i
t
e
r
i
a
D
e
c
i
mal
P
e
r
c
e
n
t
a
g
e
V
a
r
i
a
t
i
o
n
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
0
.
0
0
1
4
6
2
0
.
1
5
%
S
mal
l
B
.
Q
u
o
t
a
t
i
o
n
0
.
0
5
6
1
0
9
5
.
6
1
%
mo
d
e
r
a
t
e
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
0
.
0
0
8
1
3
5
0
.
8
5
%
S
mal
l
D
.
Ex
e
c
u
t
i
o
n
T
i
me
0
.
0
0
0
0
0
0
0
.
0
0
%
S
mal
l
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
0
.
0
0
0
0
0
0
0
.
0
0
%
S
mal
l
I
n
F
i
n
a
l
D
e
c
i
si
o
n
0
.
0
1
7
0
4
4
1
.
1
7
%
S
mal
l
4
.
4
.
P
er
f
o
r
m
a
nce
o
f
t
he
So
lv
er
t
o
Weig
h De
t
ec
t
io
n
T
h
e
So
lv
er
to
o
l
co
u
ld
d
etec
t
p
atter
n
s
an
d
h
id
d
en
r
elatio
n
s
h
ip
s
in
d
ata.
Mo
d
elin
g
u
s
i
n
g
So
lv
er
,
w
e
h
av
e
d
ev
elo
p
ed
a
lo
g
ic
f
r
a
m
e
w
o
r
k
in
e
x
ce
l
s
h
ee
t
t
h
at
ca
n
b
e
u
s
ed
to
p
r
ed
ict
b
eh
a
v
io
r
an
d
m
a
k
e
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
d
ec
is
i
o
n
s
.
Z
elj
k
o
v
ić
an
d
Gać
an
o
v
ić
h
av
e
s
tated
th
a
t
“
w
h
at
is
m
o
r
e
i
m
p
o
r
tan
t,
So
lv
er
is
ca
p
ab
le
o
f
h
an
d
li
n
g
n
o
n
-
l
in
ea
r
p
r
o
b
lem
s
b
y
e
m
p
lo
y
i
n
g
a
g
en
er
alize
d
r
ed
u
ce
d
g
r
ad
ien
t
m
et
h
o
d
”
[1
7
]
.
T
h
e
p
er
f
o
r
m
an
ce
o
f
t
h
e
So
lv
er
to
d
etec
t
th
e
cr
iter
ia
w
ei
g
h
ts
,
as
in
s
h
o
w
in
T
ab
le
3
(
co
lu
m
n
o
f
cr
iter
ia
w
e
ig
h
t
s
)
w
as
d
e
m
o
n
s
tr
ated
b
y
u
s
i
n
g
tr
ai
n
in
g
c
u
r
v
e
w
it
h
t
h
e
p
ar
a
m
eter
MSE
a
n
d
it
d
ec
li
n
i
n
g
,
a
s
sh
o
w
n
in
F
i
g
u
r
e
2
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
w
ill
b
e
v
alid
ati
n
g
w
it
h
M
SE
o
f
tar
g
et
d
at
a
a
n
d
o
u
tp
u
t
d
ata,
as
s
h
o
w
n
in
F
ig
u
r
e
4
.
So
lv
er
,
w
h
ic
h
is
ab
le
to
iter
ate
th
e
s
u
b
co
n
tr
a
cto
r
d
ata,
ca
n
b
e
u
s
ed
a
s
a
t
o
o
l
to
id
en
tify
t
h
e
w
ei
g
h
ts
a
n
d
b
iases
o
f
t
h
e
s
u
b
co
n
tr
ac
to
r
s
el
ec
tio
n
p
r
o
ce
s
s
.
T
h
e
s
u
cc
es
s
r
ate
o
f
t
h
e
So
lv
e
r
ca
n
b
e
m
ea
s
u
r
ed
f
r
o
m
MSE
tr
ai
n
i
n
g
9
.
7
3
7
1
1
e
-
0
8
an
d
MSE
v
alid
atio
n
o
f
tr
ai
n
in
g
0
.
0
0
9
0
0
5
2
8
.
T
h
e
p
r
in
cip
le
o
f
d
ata
p
r
o
ce
s
s
in
g
b
y
t
h
e
So
l
v
er
to
d
etec
t
th
e
w
ei
g
h
ts
o
f
a
m
u
l
ti
-
cr
iter
ia
an
d
b
ias
es
i
n
th
e
d
ata
s
elec
tio
n
is
b
ased
o
n
p
atter
n
i
n
s
p
r
ea
d
s
h
ee
t
o
f
ex
c
el
b
ase.
I
t
is
in
li
n
e
w
it
h
Fo
n
e,
et.
al
s
tated
t
h
at
“
d
esi
g
n
ed
th
e
alg
o
r
it
h
m
s
u
s
e
d
w
it
h
i
n
a
NN
b
ec
o
m
e
g
e
n
er
ic
an
d
t
h
e
y
ar
e
tr
ain
ed
u
s
i
n
g
e
m
p
ir
ical
e
x
a
m
p
l
e
d
ata
.
I
t
h
as
p
r
o
v
ed
b
en
ef
ic
ial
t
o
d
em
o
n
s
tr
ate
t
h
e
m
ec
h
a
n
ic
s
o
f
a
n
e
u
r
o
n
a
n
d
s
i
m
p
le
NN
,
p
r
io
r
to
,
o
r
alo
n
g
s
id
e
th
e
i
n
tr
o
d
u
ctio
n
o
f
t
h
e
m
a
th
e
m
atica
l
n
o
tatio
n
s
a
n
d
th
i
s
w
as
ac
h
iev
ed
u
s
i
n
g
t
h
e
m
o
d
el
i
m
p
le
m
en
ted
u
s
i
n
g
a
n
E
x
ce
l sp
r
ea
d
s
h
ee
t”
[
18
]
.
5.
CO
NCLU
SI
O
N
A
p
r
o
p
o
s
ed
m
o
d
el
f
o
r
s
o
l
v
i
n
g
t
h
e
p
r
o
b
le
m
s
o
f
s
u
b
co
n
tr
ac
t
o
r
s
elec
tio
n
h
a
s
b
ee
n
s
u
cc
es
s
f
u
ll
y
b
u
il
t.
A
b
ilit
y
o
f
t
h
e
p
r
o
p
o
s
ed
m
o
d
el
b
y
u
s
i
n
g
t
h
e
So
l
v
er
h
as
b
ee
n
a
b
le
m
ap
p
in
g
t
h
e
a
s
s
e
s
s
o
r
’s
a
s
s
es
s
m
en
t
s
to
w
ar
d
th
e
e
x
p
er
t's
j
u
d
g
m
e
n
t.
T
h
e
s
u
cc
ess
o
f
m
ap
p
in
g
is
d
ep
icted
in
t
h
e
p
atter
n
o
f
cr
iter
ia
w
ei
g
h
ts
a
n
d
b
iases
in
th
e
h
ier
ar
ch
ical
s
tr
u
ct
u
r
e
o
f
t
h
e
m
o
d
el
d
ec
is
io
n
o
n
th
e
s
elec
t
io
n
o
f
s
u
b
co
n
tr
ac
to
r
s
.
T
r
ain
in
g
p
r
o
ce
s
s
p
er
f
o
r
m
ed
b
y
t
h
e
So
l
v
er
s
h
o
w
s
t
h
at
th
e
r
e
s
u
lts
ar
e
q
u
ite
g
o
o
d
at
tr
ain
in
g
MSE
lev
e
l
o
f
9
.
7
3
7
1
1
e
-
0
8
.
T
r
ain
in
g
c
u
r
v
e
f
o
r
t
h
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
m
o
d
els
d
e
s
c
r
ib
e
ch
an
g
es
er
r
o
r
o
f
-
0
.
0
0
4
an
d
MSE
f
o
r
v
alid
atio
n
of
0
.
0
0
9
0
0
5
2
8
.
T
h
u
s
,
it
co
u
ld
be
co
n
cl
u
d
e
th
a
t
t
h
e
m
o
d
elin
g
o
f
d
ec
i
s
io
n
s
u
p
p
o
r
t
s
y
s
te
m
f
o
r
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
b
y
u
s
i
n
g
th
e
m
et
h
o
d
o
f
th
e
So
lv
er
A
p
p
licatio
n
h
a
s
b
ee
n
w
ell
ac
h
iev
ed
.
P
atter
n
s
ar
e
dr
aw
n
f
r
o
m
a
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
m
o
d
el
is
o
u
tlin
ed
cr
iter
ia
ar
e
d
iv
id
ed
in
to
f
iv
e
g
r
o
u
p
s
(
m
ai
n
cr
iter
ia)
w
i
th
th
e
s
a
m
e
w
eig
h
t
s
is
±
20
%.
E
ac
h
w
ei
g
h
ti
n
g
o
n
t
h
e
m
ai
n
cr
iter
ia
w
il
l
b
e
d
is
tr
ib
u
ted
to
th
e
s
u
b
-
cr
iter
ia
.
T
h
e
o
n
l
y
t
h
e
m
a
in
cr
iter
ia
w
h
ic
h
h
a
v
e
m
an
y
s
u
b
-
cr
iter
ia
,
w
ill
lead
to
s
m
a
ll
w
ei
g
h
ts
cr
iter
ia
v
alu
e
.
T
h
e
s
i
g
n
i
f
ica
n
t
cr
iter
ia
f
o
r
th
e
s
u
b
co
n
tr
ac
to
r
s
elec
tio
n
is
C
o
m
p
r
ess
io
n
o
f
Sc
h
ed
u
le
,
Nu
m
b
er
o
f
s
i
m
ilar
p
r
o
ject
in
last
y
ea
r
,
Qu
o
tatio
n
P
r
ice,
an
d
Me
th
o
d
s
o
f
p
a
y
m
en
t
in
t
h
e
to
tals
a
m
o
u
n
t
i
s
6
0
%
.
T
h
ey
ar
e
th
e
s
tr
ateg
ic
s
u
b
cr
iter
ia
th
at
s
h
o
u
ld
b
e
co
n
s
id
e
r
ed
b
y
th
e
s
u
b
co
n
tr
ac
to
r
s
to
o
u
tp
er
f
o
r
m
in
t
h
e
s
elec
tio
n
p
r
o
ce
s
s
.
T
h
e
n
o
v
elt
y
in
th
e
s
tu
d
y
co
n
d
u
cted
u
s
i
n
g
t
h
e
So
lv
er
A
p
p
li
ca
tio
n
is
t
h
e
ab
ilit
y
to
d
etec
t
t
h
e
cr
iter
ia
w
ei
g
h
ts
a
n
d
b
iases
o
f
t
h
e
ass
e
s
s
o
r
s
ass
e
s
s
m
e
n
ts
w
i
th
m
ac
h
i
n
e
lear
n
i
n
g
co
n
ce
p
t,
an
d
w
e
ig
h
ts
a
n
d
b
iases
co
u
ld
b
e
v
is
u
a
lized
as a
lo
g
ical
m
o
d
el
o
f
w
e
ig
h
ted
cr
iter
ia.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
is
p
ap
er
h
as
to
b
e
r
ea
lized
o
n
th
e
p
ar
ticip
atio
n
o
f
a
n
u
m
b
er
o
f
p
ar
ties
.
Fo
r
th
at,
th
e
a
u
t
h
o
r
s
w
o
u
ld
l
ik
e
to
t
h
an
k
a
n
d
a
w
ar
d
s
to
:
1
.
)
Dir
ec
to
r
o
f
PT
.
W
ask
ita
Kar
y
a
w
it
h
s
taf
f
;
2
.
)
T
h
e
lab
o
r
ato
r
y
s
ta
f
f
o
f
th
e
C
o
n
s
tr
u
ctio
n
E
n
g
in
ee
r
i
n
g
Ma
n
ag
e
m
e
n
t
L
ab
o
r
ato
r
y
i
n
C
i
v
il
E
n
g
i
n
ee
r
i
n
g
,
S
y
ia
h
Ku
a
la
Un
i
v
er
s
it
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Th
e
W
eig
h
ts
De
tectio
n
o
f Mu
lti
-
C
r
ite
r
ia
b
y
Usi
n
g
S
o
lver (
F
a
ch
r
u
r
r
a
z
i
)
865
RE
F
E
R
E
NC
E
S
[1
]
Ng
u
y
e
n
V
.
U.
,
“
T
e
n
d
e
r
Ev
a
lu
a
ti
o
n
b
y
F
u
z
z
y
S
e
ts
,”
J
Co
n
str
En
g
M
a
n
a
g
.
Ame
ric
a
n
S
o
c
iety
o
f
Civil
En
g
i
n
e
e
rs
,
v
o
l/
issu
e
:
1
1
1
(
3
)
,
p
p
.
2
3
1
–
43
,
1
9
8
5
.
[2
]
A
lb
in
o
V
.
a
n
d
G
a
ra
v
e
ll
i
A
.
C.
,
“
A
n
e
u
ra
l
n
e
tw
o
rk
a
p
p
li
c
a
ti
o
n
t
o
su
b
c
o
n
trac
t
o
r
ra
ti
n
g
in
c
o
n
stru
c
ti
o
n
f
irm
s
,”
In
t
J
Pro
j
M
a
n
a
g
,
v
o
l/
iss
u
e
:
1
6
(1
)
,
p
p
.
9
–
14
,
1
9
9
8
.
[3
]
S
a
if
S
.
M
.
,
e
t
a
l.
,
“
A
n
Ex
p
e
rt
S
y
st
e
m
w
it
h
Ne
u
ra
l
Ne
t
w
o
rk
a
n
d
De
c
isio
n
T
re
e
f
o
r
P
re
d
ic
ti
n
g
A
u
d
it
O
p
in
i
o
n
s
,”
IAE
S
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Art
if
icia
l
In
telli
g
e
n
c
e
(
IJ
-
AI)
,
p
p
.
1
5
1
–
8
,
2
0
1
3
.
[4
]
Ba
d
iru
A
.
B.
,
“
Co
m
p
re
h
e
n
siv
e
P
r
o
jec
t
M
a
n
a
g
e
m
e
n
t:
In
teg
ra
ti
n
g
Op
ti
m
iza
ti
o
n
M
o
d
e
ls,
M
a
n
a
g
e
m
e
n
t
P
ri
n
c
ip
les
,
a
n
d
Co
m
p
u
ters
,”
Pre
n
t
ice
h
a
ll
,
1
9
9
5
.
[5
]
F
a
n
g
Y
.
C
.
a
n
d
Ch
y
u
C
.
C.
,
“
A
M
u
l
ti
c
rit
e
ria
S
e
lec
ti
o
n
M
o
d
e
l
f
o
r
De
v
e
lo
p
i
n
g
Ne
w
Co
lo
r
Ca
li
b
ra
ti
o
n
De
v
ice
,”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
p
p
.
2
3
7
4
–
83
,
2
0
1
4
.
[6
]
Ha
te
f
i
S
.
M
.
,
e
t
a
l.
,
“
A
Co
m
m
o
n
W
e
ig
h
t
M
u
lt
i
-
Cri
teria
De
c
isio
n
A
n
a
l
y
si
s
-
Da
ta
En
v
e
lo
p
m
e
n
t
A
n
a
ly
sis
A
p
p
ro
a
c
h
w
it
h
A
ss
u
ra
n
c
e
Re
g
io
n
f
o
r
Weig
h
t
De
riv
a
ti
o
n
f
r
o
m
P
a
irw
ise
C
o
m
p
a
riso
n
M
a
tri
c
e
s
,”
In
t
J
En
g
-
T
ra
n
s
C
Asp
.
,
v
o
l/
issu
e
:
2
8
(1
2
)
,
p
p
.
17
46
-
1
7
5
5
,
2
0
1
5
.
[7
]
Ro
u
h
io
ly
a
e
e
F
.
,
e
t
a
l.
,
“
Util
izin
g
De
c
isio
n
M
a
k
in
g
M
e
th
o
d
s
a
n
d
O
p
ti
m
iza
ti
o
n
T
e
c
h
n
iq
u
e
s
to
De
v
e
lo
p
A
M
o
d
e
l
f
o
r
In
tern
a
ti
o
n
a
l
F
a
c
il
it
y
L
o
c
a
ti
o
n
P
r
o
b
lem
u
n
d
e
r
U
n
c
e
rtain
ty
,”
In
t
J
En
g
-
T
ra
n
s A
B
a
sic
s,
v
o
l/
issu
e
:
2
9
(1
)
,
2
0
1
5
.
[8
]
L
i
J
.
J.
,
“
Re
se
a
r
c
h
o
n
L
if
e
S
ig
n
a
ls
De
tec
ti
o
n
B
a
se
d
o
n
Hig
h
e
r
Ord
e
r
S
tatisti
c
s
,”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
p
p
.
1
2
4
2
–
8
,
2
0
1
2
.
[9
]
G
a
n
g
S
.
,
e
t
a
l.
,
“
A
p
p
li
c
a
ti
o
n
o
f
V
a
lu
e
A
ss
e
s
s
m
e
n
t
W
e
ig
h
ts
in
C
o
n
se
rv
a
ti
o
n
o
f
M
o
d
e
r
n
A
rc
h
it
e
c
t
u
ra
l
He
rit
a
g
e
,”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
p
p
.
8
3
1
2
–
8
,
2
0
1
4
.
[1
0
]
W
e
st
g
a
rd
J
.
O.
,
“
P
o
i
n
ts
o
f
Ca
re
in
u
si
n
g
S
tatisti
c
s
in
M
e
th
o
d
C
o
m
p
a
riso
n
S
tu
d
ies
,”
Cli
n
C
h
e
m
,
v
o
l/
issu
e
:
4
4
(
1
1
)
,
p
p
.
2
2
4
0
–
2
,
1
9
9
8
.
[1
1
]
L
u
y
a
n
W
.
,
e
t
a
l.
,
“
T
h
e
P
e
rf
o
r
m
a
n
c
e
A
n
a
l
y
sis
f
o
r
E
m
b
e
d
d
e
d
S
y
ste
m
s u
sin
g
S
tatisti
c
s M
e
th
o
d
s
,”
In
d
o
n
e
sia
n
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
,
p
p
.
4
0
9
9
–
1
0
3
,
2
0
1
3
.
[1
2
]
Ke
n
C.
,
“
T
h
e
Qu
a
li
t
y
E
v
a
lu
a
ti
o
n
M
e
th
o
d
o
f
In
stru
m
e
n
t
F
li
g
h
t
P
r
o
c
e
d
u
re
De
sig
n
S
c
h
e
m
e
Ba
se
d
o
n
F
u
z
z
y
L
in
g
u
isti
c
A
ss
e
ss
m
e
n
ts
,”
T
EL
KOM
NIKA
In
d
o
n
e
s J El
e
c
tr
.
,
p
p
.
7
6
1
1
-
16
,
2
0
1
3
.
[1
3
]
Zh
a
o
K.
,
“
T
h
e
Re
se
a
rc
h
o
f
G
ra
y
A
l
g
o
rit
h
m
a
n
d
In
f
o
rm
a
ti
o
n
En
tr
o
p
y
in
Ro
u
te
P
lan
n
i
n
g
Op
ti
m
iza
ti
o
n
,”
In
d
o
n
e
si
a
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
p
p
.
2
0
2
7
–
33
,
2
0
1
2
.
[1
4
]
P
a
tt
e
rso
n
D
.
W.
,
“
A
rti
f
icia
l
Ne
u
ra
l
Ne
tw
o
rk
s: T
h
e
o
r
y
a
n
d
A
p
p
li
c
a
ti
o
n
s
,”
Pre
n
ti
c
e
Ha
ll
L
T
D
,
1
9
9
6
.
[1
5
]
Ro
b
e
rt
H
.
N.
,
“
Ne
u
ro
Co
m
p
u
tt
i
n
g
,”
Ad
d
iso
n
-
W
e
sle
y
Pu
b
li
sh
i
n
g
C
o
mp
a
n
y
,
1
9
9
0
.
[1
6
]
Ha
y
k
in
S
.
,
“
Ne
u
ra
l
Ne
tw
o
rk
s:
A
Co
m
p
re
h
e
n
siv
e
F
o
u
n
d
a
ti
o
n
,”
Pre
n
ti
c
e
Ha
ll
PT
R
,
1
9
9
8
.
[1
7
]
C.
Zeljk
o
v
ić
a
n
d
M
.
G
a
ć
a
n
o
v
ić,
“
A
n
Ex
a
m
p
le
o
f
U
sin
g
M
icro
so
f
t
Ex
c
e
l
S
o
lv
e
r
f
o
r
P
o
w
e
r
Ne
t
w
o
rk
Ca
lcu
latio
n
s,”
2
0
1
6
.
Ph
d
.
e
tf
b
l.
n
e
t
.
[1
8
]
W
.
F
o
n
e
,
e
t
a
l
.
,
“
Us
in
g
a
f
a
m
il
iar
p
a
c
k
a
g
e
to
d
e
m
o
n
stra
te
a
d
iff
i
c
u
lt
c
o
n
c
e
p
t,
”
In
Pr
o
c
e
e
d
in
g
s
o
f
th
e
6
th
a
n
n
u
a
l
c
o
n
fer
e
n
c
e
o
n
I
n
n
o
v
a
ti
o
n
a
n
d
te
c
h
n
o
l
o
g
y
i
n
c
o
m
p
u
ter
sc
ien
c
e
e
d
u
c
a
t
io
n
-
IT
iC
S
E
’
0
1
,
Ne
w
Yo
rk
,
Ne
w
Yo
rk
,
USA
:
A
CM
P
re
ss
,
p
p
.
1
6
5
–
1
6
8
,
2
0
0
1
AP
P
E
NDI
X
T
ab
le
1
.
L
ea
r
n
in
g
Data
f
o
r
t
h
e
A
s
s
es
s
m
en
t o
f
Su
b
co
n
tr
ac
to
r
s
an
d
E
x
p
er
t
J
u
d
g
m
en
t a
s
T
ar
g
et
C
r
i
t
e
r
i
a
o
f
t
h
e
D
e
c
i
si
o
n
D
a
t
a
f
o
r
T
r
a
i
n
i
n
g
A
l
t
e
r
n
a
t
i
v
e
(
N
u
m
b
e
r
o
f
S
u
b
c
o
n
t
r
a
c
t
o
r
s)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
1
.
C
o
mp
a
n
y
p
r
o
f
i
l
e
a.
M
a
n
a
g
e
me
n
t
C
a
p
a
b
i
l
i
t
i
e
s
•
Q
u
a
l
i
t
y
sy
st
e
m
-
I
S
O
c
e
r
t
i
f
i
c
a
t
i
o
n
,
si
mi
l
a
r
A1
0
.
8
1
.
0
0
.
8
0
.
5
0
.
9
0
.
6
0
.
6
0
.
9
0
.
6
0
.
6
0
.
5
1
.
0
0
.
8
0
.
5
0
.
2
0
.
5
0
.
6
0
.
5
0
.
8
0
.
9
0
.
5
0
.
5
0
.
8
0
.
7
1
.
0
-
Q
u
a
l
i
t
y
a
ss
u
r
a
n
c
e
A1
1
.
0
0
.
5
0
.
6
1
.
0
0
.
5
0
.
5
0
.
7
0
.
5
0
.
5
0
.
4
0
.
5
0
.
3
0
.
5
0
.
1
0
.
3
0
.
5
0
.
3
0
.
8
0
.
6
1
.
0
0
.
6
0
.
5
0
.
6
0
.
9
1
.
0
-
C
o
mp
a
n
y
p
r
o
f
i
l
e
A3
0
.
5
1
.
0
0
.
6
1
.
0
0
.
8
0
.
4
0
.
8
0
.
6
0
.
5
0
.
7
0
.
6
0
.
5
0
.
2
0
.
5
0
.
2
0
.
8
0
.
8
0.
6
0
.
2
1
.
0
0
.
7
1
.
0
0
.
8
0
.
7
1
.
0
•
F
i
n
a
n
c
i
a
l
S
t
a
b
i
l
i
t
y
-
B
a
l
a
n
c
e
S
h
e
e
t
A4
0
.
9
0
.
6
0
.
3
0
.
9
0
.
5
0
.
6
0
.
6
0
.
6
0
.
6
0
.
3
0
.
6
0
.
7
0
.
2
0
.
5
0
.
8
0
.
9
0
.
3
0
.
5
0
.
2
0
.
5
0
.
3
0
.
2
0
.
8
0
.
8
1
.
0
-
B
a
n
k
g
u
a
r
a
n
t
e
e
A5
0
.
4
0
.
9
0
.
3
1
.
0
0
.
8
0
.
7
0
.
7
0
.
2
0
.
8
0
.
3
0
.
3
0
.
7
0
.
8
0
.
7
0
.
6
1
.
0
0
.
8
0
.
9
0
.
3
0
.
6
0
.
9
0
.
9
0
.
3
0
.
9
1
.
0
b
.
T
e
c
h
n
o
l
o
g
y
c
a
p
a
b
i
l
i
t
y
•
F
a
c
i
l
i
t
i
e
s
A6
1
.
0
0
.
7
0
.
5
0
.
6
0
.
9
0
.
3
0
.
6
0
.
8
0
.
5
0
.
2
0
.
7
0
.
9
0
.
6
0
.
4
0
.
6
0
.
5
0
.
5
0
.
3
0
.
1
0
.
8
0
.
7
0
.
5
0
.
5
0
.
6
0
.
5
•
T
r
a
n
sp
o
r
t
A7
0
.
5
0
.
6
0
.
6
0
.
7
0
.
5
0
.
1
0
.
8
0
.
2
0
.
4
0
.
5
0
.
6
0
.
2
0
.
5
0
.
9
0
.
7
1
.
0
0
.
4
0
.
4
0
.
7
0
.
3
0
.
9
0
.
6
0
.
8
0
.
6
0
.
6
•
Eq
u
i
p
me
n
t
A8
0
.
5
0
.
7
0
.
6
0
.
8
0
.
7
0
.
1
0
.
5
0
.
8
0
.
4
0
.
5
1
.
0
0
.
4
0
.
9
0
.
7
0
.
2
1
.
0
0
.
8
0
.
2
0
.
9
0
.
3
0
.
8
0
.
9
0
.
6
0
.
5
0
.
7
2
.
C
o
n
t
r
a
c
t
T
r
u
st
w
o
r
t
h
y
a
.
P
r
o
j
e
c
t
Ex
p
e
r
i
e
n
c
e
A9
0
.
4
1
.
0
0
.
5
0
.
9
0
.
4
0
.
9
0
.
3
0
.
3
0
.
6
0
.
3
0
.
5
0
.
3
1
.
0
0
.
8
0
.
6
0
.
3
0
.
8
0
.
1
0.
3
0
.
5
0
.
6
0
.
7
0
.
9
0
.
6
1
.
0
b
.
P
r
o
j
e
c
t
a
c
h
i
e
v
e
me
n
t
A
1
0
0
.
5
1
.
0
0
.
9
0
.
2
0
.
2
0
.
3
0
.
7
0
.
7
0
.
3
0
.
5
1
.
0
0
.
8
1
.
0
0
.
5
0
.
4
0
.
5
0
.
5
0
.
5
0
.
3
0
.
4
0
.
4
0
.
8
0
.
5
0
.
3
1
.
0
c.
T
y
p
e
,
a
mo
u
n
t
o
f
i
n
s
u
r
a
n
c
e
A
1
1
1
.
0
0
.
6
0
.
9
0
.
3
0
.
5
0
.
8
0
.
5
0
.
6
0
.
5
0
.4
1
.
0
1
.
0
1
.
0
0
.
3
0
.
5
1
.
0
1
.
0
0
.
6
0
.
9
0
.
9
0
.
9
0
.
4
0
.
6
0
.
5
1
.
0
d
.
R
e
g
i
st
e
r
e
d
i
n
a
sso
c
i
a
t
i
o
n
s
A
1
2
0
.
8
0
.
2
0
.
9
0
.
5
0
.
2
0
.
6
0
.
4
0
.
5
0
.
5
0
.
2
0
.
5
1
.
0
1
.
0
0
.
7
0
.
6
1
.
0
0
.
8
0
.
8
0
.
1
0
.
3
0
.
8
0
.
6
0
.
5
0
.
8
0
.
9
e
.
C
o
mp
a
n
y
l
e
g
i
t
i
mat
e
A
1
3
0
.
6
0
.
9
1
.
0
0
.
5
0
.
5
1
.
0
0
.
6
0
.
2
0
.
5
0
.
8
0
.
4
1
.
0
1
.
0
0
.
2
0
.
5
0
.
8
0
.
8
0
.
4
0
.
8
0
.
2
0
.
4
0
.
9
0
.
3
0
.
6
1
.
0
B
.
Q
u
o
t
a
t
i
o
n
1
.
Q
u
o
t
a
t
i
o
n
P
r
i
c
e
B1
0
.
6
0
.
3
0
.
5
0
.
6
0
.
4
0
.
7
0
.
7
0
.
4
0
.
3
0
.
1
0
.
2
0
.
1
0
.
7
0
.
6
0
.
4
0
.
3
0
.
6
0
.
5
0
.
7
0
.
3
0
.
2
0
.
5
0
.
3
0
.
4
0
.
2
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
2
,
A
p
r
il 2
0
1
7
:
85
8
–
8
6
8
866
2
M
e
t
h
o
d
s o
f
P
a
y
me
n
t
B2
0
.
6
0
.
3
0
.
2
0
.
3
0
.
6
0
.
4
0
.
1
0
.
5
1
.
0
1
.
0
1
.
0
0
.
2
0
.
4
0
.
6
0
.
3
0
.
3
0
.
3
0
.
8
0
.
6
0
.
4
0
.
2
0
.
2
0
.
2
0
.
4
0
.
4
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
1
.
Ex
p
e
r
t
i
se
o
f
p
e
r
so
n
n
e
l
C1
0
.
4
0
.
1
0
.
5
0
.
3
0
.
5
1
.
0
0
.
1
0
.
2
0
.
7
0
.
8
0
.
9
0
.
3
0
.
7
0
.
5
0
.
9
0
.
6
0
.
7
0
.
6
0
.
8
0
.
9
1
.
0
0
.
5
0
.
6
0
.
8
0
.
6
2
.
S
p
e
c
i
a
l
i
z
e
s i
n
w
o
r
k
i
n
g
me
t
h
o
d
s
C2
0
.
8
0
.
6
0
.
4
0
.
1
0
.
1
0
.
8
0
.
4
0
.
7
0
.
5
0.
2
0
.
3
0
.
8
0
.
5
0
.
3
0
.
8
0
.
4
0
.
7
0
.
3
0
.
3
0
.
2
0
.
6
0
.
7
0
.
5
1
.
0
0
.
4
3
.
M
a
t
e
r
i
a
l
s
p
e
c
i
f
i
c
a
t
i
o
n
C3
0
.
7
0
.
6
0
.
9
0
.
9
0
.
5
0
.
9
0
.
9
0
.
8
0
.
6
0
.
9
0
.
7
0
.
9
0
.
6
0
.
9
0
.
6
0
.
5
0
.
7
0
.
8
0
.
8
0
.
5
0
.
7
0
.
9
0
.
6
0
.
7
0
.
8
D
.
Ex
e
c
u
t
i
o
n
T
i
me
1
.
C
o
mp
r
e
ssi
o
n
o
f
sc
h
e
d
u
l
e
D1
0
.
3
0
.
3
0
.
4
0
.
1
0
.
3
0
.
2
0
.
6
0
.
3
0
.
1
0
.
2
0
.
5
0
.
6
0
.
1
0
.
2
0
.
3
0
.
5
0
.
5
0
.
2
0
.
1
0
.
2
0
.
3
0
.
4
0
.
6
0
.
5
0
.
6
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
1
.
N
u
m
b
e
r
o
f
si
mi
l
a
r
p
r
o
j
e
c
t
s
E1
0
.
8
0
.
6
0
.
9
0
.
8
0
.
7
0
.
3
0
.
1
0
.
2
0
.
5
0
.
6
0
.
5
0
.
7
0
.
3
0
.
7
0
.
7
0
.
1
0
.
6
0
.
4
0
.
4
0
.
3
0
.
2
0
.
2
0
.
3
0
.
5
0
.
6
M
A
I
N
C
R
I
T
ER
I
A
O
F
D
EC
I
S
I
O
N
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
A
0
.
7
0
.
8
0
.
6
0
.
7
0
.
6
0
.
5
0
.
6
0
.
6
0
.
5
0
.
4
0
.
6
0
.
7
0
.
7
0
.
5
0
.
5
0
.
8
0
.
6
0
.
5
0
.
5
0
.
7
0
.
7
0
.
6
0
.
6
0
.
7
0
.
9
B
.
Q
u
o
t
a
t
i
o
n
B
0
.
6
0
.
3
0
.
5
0
.
6
0
.
4
0
.
7
0
.
6
0
.
4
0
.
4
0
.
3
0
.
3
0
.
1
0
.
6
0
.
6
0
.
4
0
.
3
0
.
5
0
.
6
0
.
7
0
.
7
0
.
2
0
.
5
0
.
3
0
.
4
0
.
2
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
C
0
.
6
0
.
4
0
.
6
0
.
4
0
.
4
0
.
9
0
.
5
0
.
6
0
.
6
0
.
6
0
.
6
0
.
7
0
.
7
0
.
6
0
.
8
0
.
5
0
.
7
0
.
6
0
.
6
0
.
5
0
.
8
0
.
7
0
.
8
0
.
8
0
.
6
D
.
Ex
e
c
u
t
i
o
n
T
i
me
D
0
.
3
0
.
3
0
.
4
0
.
1
0
.
3
0
.
2
0
.
6
0
.
3
0
.
1
0
.
2
0
.
5
0.
6
0
.
1
0
.
2
0
.
3
0
.
5
0
.
5
0
.
2
0
.
1
0
.
2
0
.
3
0
.
4
0
.
6
0
.
5
0
.
6
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
E
0
.
8
0
.
6
0
.
9
0
.
8
0
.
7
0
.
3
0
.
1
0
.
2
0
.
5
0
.
6
0
.
5
0
.
7
0
.
3
0
.
7
0
.
7
0
.
1
0
.
6
0
.
4
0
.
4
0
.
3
0
.
2
0
.
2
0
.
3
0
.
5
0
.
6
EX
P
ER
T
JU
D
G
M
EN
T
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
A
0
.
7
0
.
8
0
.
6
0
.
7
0
.
6
0
.
5
0
.
6
0
.
6
0
.
5
0
.
4
0
.
6
0
.
7
0
.
7
0
.
5
0
.
5
0
.
8
0
.
6
0
.
5
0
.
5
0
.
7
0
.
7
0
.
6
0
.
6
0
.
7
0
.
9
B
.
Q
u
o
t
a
t
i
o
n
B
0
.
6
0
.
3
0
.
5
0
.
6
0
.
4
0
.
7
0
.
6
0
.
4
0
.
4
0
.
3
0
.
3
0
.
1
0
.
6
0
.
6
0
.
4
0
.
3
0
.
5
0
.
6
0
.
7
0
.
7
0
.
2
0
.
5
0
.
3
0
.
4
0
.
2
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
C
0
.
6
0
.
4
0
.
6
0
.
4
0
.
4
0
.
9
0
.
5
0
.
6
0
.
6
0
.
6
0
.
6
0
.
7
0
.
7
0
.
6
0
.
8
0
.
5
0
.
7
0
.
6
0
.
6
0
.
5
0
.
8
0
.
7
0
.
8
0
.
8
0
.
6
D
.
Ex
e
c
u
t
i
o
n
T
i
me
D
0
.
3
0
.
3
0
.
4
0
.
1
0
.
3
0
.
2
0
.
6
0
.
3
0
.
1
0
.
2
0
.
5
0
.
6
0
.
1
0
.
2
0
.
3
0
.
5
0
.
5
0
.
2
0
.
1
0
.
2
0
.
3
0
.
4
0
.
6
0
.
5
0
.
6
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
E
0
.
8
0
.
6
0
.
9
0
.
8
0
.
7
0
.
3
0
.
1
0
.
2
0
.
5
0
.
6
0
.
5
0
.
7
0
.
3
0
.
7
0
.
7
0
.
1
0
.
6
0
.
4
0
.
4
0
.
3
0
.
2
0
.
2
0
.
3
0
.
5
0
.
6
T
o
t
a
l
Ex
p
e
r
t
Ju
d
g
me
n
t
o
f
e
a
c
h
A
l
t
e
r
n
a
t
i
v
e
s
0
.
6
0
.
4
0
.
5
0
.
6
0
.
4
0
.
6
0
.
5
0
.
4
0
.
4
0
.
4
0
.
4
0
.
3
0
.
6
0
.
5
0
.
5
0
.
4
0
.
6
0
.
5
0
.
6
0
.
6
0
.
3
0
.
5
0
.
4
0
.
5
0
.
4
T
ab
le
2
.
Valid
atio
n
Data
f
o
r
th
e
A
s
s
ess
m
e
n
t o
f
S
u
b
co
n
tr
ac
t
o
r
s
an
d
E
x
p
er
t
J
u
d
g
m
e
n
t a
s
T
ar
g
et
C
r
i
t
e
r
i
a
o
f
t
h
e
D
e
c
i
si
o
n
Da
t
a
f
o
r
V
a
l
i
d
a
t
i
o
n
A
l
t
e
r
n
a
t
i
v
e
(
N
u
m
b
e
r
o
f
S
u
b
c
o
n
t
r
a
c
t
o
r
s)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
1
.
C
o
mp
a
n
y
p
r
o
f
i
l
e
a
.
M
a
n
a
g
e
me
n
t
C
a
p
a
b
i
l
i
t
i
e
s
•
Q
u
a
l
i
t
y
s
y
st
e
m
-
I
S
O
c
e
r
t
i
f
i
c
a
t
i
o
n
,
si
mi
l
a
r
A1
1
.
0
1
.
0
0
.
0
0
.
8
0
.
6
0
.
6
0
.
0
1
.
0
0
.
5
0
.
2
1
.
0
0
.
1
0
.
5
0
.
9
0
.
4
-
Q
u
a
l
i
t
y
a
ssu
r
a
n
c
e
A1
1
.
0
1
.
0
1
.
0
0
.
6
0
.
3
0
.
9
0
.
9
0
.
0
0
.
0
0
.
3
1
.
0
0
.
6
0
.
3
0
.
4
0
.
5
-
C
o
mp
a
n
y
p
r
o
f
i
l
e
A3
0
.
6
0
.
7
0
.
3
1
.
0
0
.
2
0
.
4
0
.
6
0
.
5
0
.
5
0
.
5
1
.
0
0
.
2
0
.
5
0
.
8
0
.
8
•
F
i
n
a
n
c
i
a
l
S
t
a
b
i
l
i
t
y
-
B
a
l
a
n
c
e
S
h
e
e
t
A4
0
.
7
0
.
5
0
.
8
0
.
7
0
.
8
0
.
6
0
.
1
0
.
1
0
.
6
0
.
5
1
.
0
0
.
8
0
.
2
0
.
5
0
.
6
-
B
a
n
k
g
u
a
r
a
n
t
e
e
A5
1
.
0
1
.
0
1
.
0
0
.
5
0
.
8
0
.
5
0
.
9
0
.
5
0
.
2
0
.
3
1
.
0
0
.
4
0
.
3
0
.
3
0
.
8
b
.
T
e
c
h
n
o
l
o
g
y
c
a
p
a
b
i
l
i
t
y
•
F
a
c
i
l
i
t
i
e
s
A6
0
.
2
0
.
5
0
.
6
0
.
5
0
.
8
0
.
8
0
.
9
0
.
6
0
.
7
0
.
8
0
.
8
0
.
3
0
.
4
0
.
8
0
.
5
•
T
r
a
n
sp
o
r
t
A7
1
.
0
1
.
0
0
.
3
1
.
0
0
.
8
0
.
5
0
.
5
0
.
3
0
.
8
0
.
6
0
.
7
0
.
2
0
.
8
0
.
6
0
.
5
•
Eq
u
i
p
me
n
t
A8
0
.
8
0
.
5
0
.
3
0
.
6
0
.
8
0
.
5
0
.
7
0
.
5
0
.
1
0
.
3
0
.
5
0
.
5
0
.
9
0
.
3
0
.
5
2
.
C
o
n
t
r
a
c
t
T
r
u
st
w
o
r
t
h
y
a
.
P
r
o
j
e
c
t
Ex
p
e
r
i
e
n
c
e
A9
1
.
0
0
.
5
0
.
7
1
.
0
0
.
6
0
.
3
0
.
8
0
.
5
0
.
5
0
.
4
0
.
9
0
.
6
1
.
0
0
.
5
0
.
7
b
.
P
r
o
j
e
c
t
a
c
h
i
e
v
e
me
n
t
A
1
0
0
.
5
0
.
1
0
.
4
0
.
2
0
.
4
0
.
3
0
.
7
0
.
6
0
.
8
0
.
5
0
.
8
0
.
2
0
.
5
0
.
7
0
.
5
c
.
T
y
p
e
,
a
mo
u
n
t
o
f
i
n
s
u
r
a
n
c
e
A
1
1
0
.
5
1
.
0
0
.
6
1
.
0
0
.
9
0
.
5
0
.
9
0
.
7
0
.
3
0
.
2
1
.
0
0
.
7
0
.
9
0
.
6
0
.
6
d
.
R
e
g
i
st
e
r
e
d
i
n
a
s
so
c
i
a
t
i
o
n
s
A
1
2
1
.
0
1
.
0
0
.
3
1
.
0
1
.
0
0
.
5
0
.
8
0
.
5
0
.
1
0
.
9
1
.
0
0
.
2
0
.
4
0
.
8
0
.
6
e
.
C
o
mp
a
n
y
l
e
g
i
t
i
mat
e
A
1
3
0
.
7
1
.
0
0
.
5
1
.
0
0
.
5
0
.
8
0
.
5
0
.
4
0
.
8
0
.
5
1
.
0
0
.
5
0
.
6
0
.
6
0
.
3
B
.
Q
u
o
t
a
t
i
o
n
1
.
Q
u
o
t
a
t
i
o
n
P
r
i
c
e
B1
0
.
6
0
.
6
0
.
2
0
.
1
0
.
4
0
.
8
0
.
6
0
.
5
0
.
3
0
.
4
0
.
6
0
.
2
0
.
7
0
.
6
0
.
6
2
M
e
t
h
o
d
s o
f
P
a
y
me
n
t
B2
0
.
0
0
.
0
0
.
0
0
.
2
0
.
0
0
.
8
0
.
5
0
.
0
0
.
0
0
.
0
0
.
5
0
.
7
0
.
9
1
.
0
0
.
0
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
1
.
Ex
p
e
r
t
i
se
o
f
p
e
r
so
n
n
e
l
C1
0
.
9
0
.
8
0
.
5
0
.
6
0
.
8
0
.
9
0
.
9
0
.
8
0
.
5
0
.
3
0
.
2
0
.
6
0
.
4
0
.
6
0
.
5
2
.
S
p
e
c
i
a
l
i
z
e
s i
n
w
o
r
k
i
n
g
me
t
h
o
d
s
C2
0
.
5
0
.
6
0
.
9
0
.
6
0
.
5
0
.
6
0
.
7
0
.
6
0
.
6
0
.
5
0
.
8
0
.
6
0
.
5
0
.
8
0
.
5
3
.
M
a
t
e
r
i
a
l
sp
e
c
i
f
i
c
a
t
i
o
n
C3
0
.
8
0
.
9
0
.
6
0
.
8
0
.
7
0
.
9
0
.
6
0
.
8
0
.
7
0
.
6
0
.
9
0
.
5
0
.
6
0
.
9
0
.
8
D
.
Ex
e
c
u
t
i
o
n
T
i
me
1
.
C
o
mp
r
e
ssi
o
n
o
f
s
c
h
e
d
u
l
e
D1
0
.
1
0
.
2
0
.
3
0
.
3
0
.
2
0
.
0
0
.
5
0
.
4
0
.
6
0
.
4
0
.
3
0
.
2
0
.
2
0
.
4
0
.
3
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
1
.
N
u
mb
e
r
o
f
si
m
i
l
a
r
p
r
o
j
e
c
t
s
E1
0
.
8
0
.
5
0
.
6
0
.
9
0
.
8
0
.
7
0
.
0
0
.
4
0
.
6
0
.
0
0
.
0
0
.
3
0
.
6
0
.
2
0
.
4
M
A
I
N
C
R
I
T
ER
I
A
O
F
D
EC
I
S
I
O
N
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
A
0
.
8
0
.
8
0
.
6
0
.
8
0
.
7
0
.
6
0
.
6
0
.
5
0
.
5
0
.
4
0
.
9
0
.
4
0
.
6
0
.
6
0
.
6
B
.
Q
u
o
t
a
t
i
o
n
B
0
.
5
0
.
5
0
.
2
0
.
1
0
.
3
0
.
8
0
.
6
0
.
4
0
.
2
0
.
3
0
.
6
0
.
2
0
.
7
0
.
6
0
.
5
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
C
0
.
7
0
.
8
0
.
7
0
.
7
0
.
7
0
.
8
0
.
7
0
.
7
0
.
6
0
.
5
0
.
6
0
.
6
0
.
5
0
.
8
0
.
6
D
.
Ex
e
c
u
t
i
o
n
T
i
me
D
0
.
1
0
.
2
0
.
3
0
.
3
0
.
2
0
.
0
0
.
5
0
.
4
0
.
6
0
.
4
0
.
3
0
.
2
0
.
2
0
.
4
0
.
3
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
E
0
.
8
0
.
5
0
.
6
0
.
9
0
.
8
0
.
7
0
.
0
0
.
4
0
.
6
0
.
0
0
.
0
0
.
3
0
.
6
0
.
2
0
.
4
EX
P
ER
T
JU
D
G
M
EN
T
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
Th
e
W
eig
h
ts
De
tectio
n
o
f Mu
lti
-
C
r
ite
r
ia
b
y
Usi
n
g
S
o
lver (
F
a
ch
r
u
r
r
a
z
i
)
867
A
.
S
u
b
c
o
n
t
r
a
c
t
o
r
C
r
e
d
i
b
i
l
i
t
y
A
0
.
8
0
.
8
0
.
6
0
.
8
0
.
7
0
.
6
0
.
6
0
.
5
0
.
5
0
.
4
0
.
9
0
.
4
0
.
6
0
.
6
0
.
6
B
.
Q
u
o
t
a
t
i
o
n
B
0
.
5
0
.
5
0
.
2
0
.
1
0
.
3
0
.
8
0
.
6
0
.
4
0
.
2
0
.
3
0
.
7
0
.
3
0
.
7
0
.
6
0
.
5
C
.
T
e
c
h
n
i
c
a
l
C
a
p
a
b
i
l
i
t
i
e
s
C
0
.
7
0
.
8
0
.
7
0
.
7
0
.
7
0
.
8
0
.
7
0
.
7
0
.
6
0
.
5
0
.
6
0
.
6
0
.
5
0
.
8
0
.
6
D
.
Ex
e
c
u
t
i
o
n
T
i
me
D
0
.
1
0
.
2
0
.
3
0
.
3
0
.
2
0
.
0
0
.
5
0
.
4
0
.
6
0
.
4
0
.
3
0
.
2
0
.
2
0
.
4
0
.
3
E.
K
i
n
d
o
f
P
r
o
j
e
c
t
R
e
f
e
r
e
n
c
e
E
0
.
8
0
.
5
0
.
6
0
.
9
0
.
8
0
.
7
0
.
0
0
.
4
0
.
6
0
.
0
0
.
0
0
.
3
0
.
6
0
.
2
0
.
4
T
o
t
a
l
Ex
p
e
r
t
Ju
d
g
me
n
t
o
f
e
a
c
h
A
l
t
e
r
n
a
t
i
v
e
0
.
6
0
.
6
0
.
3
0
.
4
0
.
4
0
.
7
0
.
5
0
.
5
0
.
4
0
.
3
0
.
6
0
.
3
0
.
6
0
.
6
0
.
5
Evaluation Warning : The document was created with Spire.PDF for Python.