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1.
I
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RO
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UCT
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Kn
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g
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to
in
t
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d
a
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)
.
[
1
]
F
ir
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d
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in
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k
n
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w
led
g
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i
n
ee
r
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s
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k
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w
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f
r
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m
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lar
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b
o
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to
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p
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an
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ts
.
T
h
is
d
ef
in
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n
w
a
s
ex
te
n
d
ed
b
y
[
2
]
to
in
clu
d
e
th
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n
ec
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s
s
it
y
f
o
r
g
ai
n
i
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u
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d
er
s
ta
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in
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ex
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[
3
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,
th
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ap
p
licatio
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o
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x
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tr
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n
atu
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in
t
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ast
as
to
h
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to
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in
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p
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at
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in
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p
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[
4
]
.
T
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A
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KB
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[
5
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A
ttrib
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1
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6
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I
SS
N
:
2
2
5
2
-
8776
IJ
-
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Vo
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5
,
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1
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A
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20
1
6
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–
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tr
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s
:
Sectio
n
2
tak
e
s
a
cr
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s
an
d
ar
ea
s
o
f
f
u
r
th
er
s
t
u
d
ies.
2.
ST
UDY
B
ACK
G
RO
UN
D
I
n
th
e
ea
r
l
y
d
a
y
s
,
ex
p
er
t
s
y
s
t
e
m
s
w
er
e
u
s
ed
to
s
ep
ar
ate
d
o
m
ai
n
k
n
o
w
led
g
e
f
r
o
m
g
e
n
er
a
l
r
ea
s
o
n
to
f
o
r
m
s
et
s
o
f
k
n
o
w
led
g
e
b
ase
r
u
les.
I
n
t
h
e
ea
r
l
y
1
9
8
0
s
,
s
ev
er
al
s
tu
d
ies
id
e
n
ti
f
ied
s
etb
ac
k
s
t
o
th
is
ap
p
r
o
ac
h
an
d
p
r
o
p
o
s
ed
th
e
u
s
e
o
f
a
s
y
s
te
m
a
tic
ap
p
r
o
ac
h
to
KE
.
[
6
]
n
o
ted
t
h
at
t
h
er
e
ar
e
d
if
f
er
en
t
le
v
el
s
at
w
h
ic
h
k
n
o
w
led
g
e
is
attai
n
ed
an
d
th
at
it
s
h
o
u
l
d
b
e
co
n
s
id
er
ed
w
h
e
n
s
o
lv
i
n
g
k
n
o
w
led
g
e
-
b
ased
tas
k
s
.
He
p
o
s
its
th
a
t
th
e
k
n
o
w
led
g
e
lev
el,
w
h
ic
h
is
h
ig
h
er
th
a
n
th
e
s
y
m
b
o
lic
lev
el,
ad
d
r
ess
es
is
s
u
es
r
e
g
ar
d
in
g
k
n
o
w
led
g
e
r
ep
r
esen
tatio
n
s
u
c
h
as
w
h
y
a
s
y
s
te
m
o
r
ag
en
t
p
er
f
o
r
m
s
a
n
ac
tio
n
in
d
ep
en
d
e
n
t
f
r
o
m
lo
g
ic,
s
y
m
b
o
lic
f
r
a
m
e
s
o
r
r
u
les (
s
y
m
b
o
lic
le
v
el
o
f
k
n
o
w
l
ed
g
e)
.
C
u
r
r
en
t
l
y
,
t
h
ese
d
escr
ip
tio
n
u
s
ed
b
y
[
6
]
at
th
e
k
n
o
w
le
d
g
e
lev
el
h
as s
in
ce
b
ee
n
t
h
e
b
asic
p
r
in
cip
le
s
o
n
wh
ich
k
n
o
w
led
g
e
e
n
g
in
ee
r
i
n
g
i
s
f
o
u
n
d
ed
,
a
n
d
h
a
s
p
r
o
v
o
k
ed
s
e
v
er
al
o
t
h
er
s
t
u
d
ies
s
u
c
h
as
[
7
]
in
th
i
s
r
eg
ar
d
.
[
8
]
,
[
9
]
an
d
[
1
0
]
d
is
tin
g
u
is
h
ed
b
et
w
ee
n
th
e
d
i
f
f
er
e
n
t
t
y
p
e
s
o
f
k
n
o
w
led
g
e
i
n
a
k
n
o
w
led
g
e
-
b
a
s
ed
s
y
s
te
m
a
n
d
in
a
r
elate
d
s
tu
d
y
,
[
1
1
]
p
r
o
v
id
ed
a
h
eu
r
i
s
tic
clas
s
i
f
icati
o
n
o
f
th
e
s
ta
n
d
ar
d
p
atter
n
s
u
s
ed
in
s
o
lv
i
n
g
k
n
o
w
led
g
e
-
lev
el
p
r
o
b
le
m
s
[
1
2
]
.
T
h
eir
f
in
d
i
n
g
s
later
b
ec
a
m
e
v
er
y
u
s
e
f
u
l
i
n
s
o
l
v
i
n
g
k
n
o
w
led
g
e
en
g
i
n
ee
r
in
g
p
r
o
b
l
e
m
s
r
elate
d
to
task
k
n
o
w
led
g
e.
T
h
e
1
9
9
0
s
s
a
w
a
s
h
if
t
i
n
f
o
cu
s
f
r
o
m
ta
s
k
k
n
o
w
led
g
e
to
d
o
m
ai
n
k
n
o
w
l
ed
g
e.
Kn
o
w
led
g
e
r
ep
r
ese
n
tati
o
n
to
o
k
ce
n
ter
s
tag
e
w
it
h
o
n
to
lo
g
y
ap
p
r
o
ac
h
es
b
ec
o
m
i
n
g
w
id
el
y
u
s
ed
f
o
r
r
ep
r
esen
tin
g
k
n
o
w
led
g
e
[
1
3
-
1
4
]
.
T
h
e
in
cr
ea
s
ed
u
s
e
o
f
o
n
to
lo
g
ies
f
o
r
co
n
ce
p
t
s
h
ar
i
n
g
i
n
a
d
is
tr
ib
u
ted
k
n
o
wled
g
e
d
o
m
ai
n
li
k
e
th
e
W
o
r
ld
W
id
e
W
eb
(
W
W
W
)
le
d
to
th
e
d
ev
elo
p
m
e
n
t
o
f
s
ev
er
al
m
o
d
elli
n
g
lan
g
u
a
g
es
in
cl
u
d
in
g
On
to
lo
g
y
W
eb
L
an
g
u
a
g
e
(
OW
L
)
p
r
esen
tl
y
u
s
ed
in
s
e
m
a
n
tic
w
eb
.
A
l
s
o
,
th
ese
m
o
d
ellin
g
d
o
m
ai
n
lan
g
u
a
g
es
m
a
k
e
u
s
e
o
f
p
atter
n
s
lik
e
i
n
tas
k
k
n
o
w
led
g
e.
Kn
o
w
led
g
e
r
o
le
ca
n
b
e
s
i
m
p
l
y
d
e
f
i
n
ed
as
th
e
r
o
le
a
p
ar
ticu
lar
k
n
o
w
led
g
e
d
o
m
a
in
p
la
y
s
i
n
s
o
lv
in
g
a
p
ar
ticu
lar
p
r
o
b
lem
[
9
]
.
T
h
is
h
elp
s
in
s
tr
u
ct
u
r
in
g
t
h
e
p
r
o
b
le
m
b
y
i
m
p
o
s
i
n
g
co
n
s
tr
ai
n
ts
o
n
th
e
w
a
y
a
p
ar
tic
u
la
r
k
n
o
w
led
g
e
d
o
m
ain
m
a
y
b
e
u
s
ed
in
th
e
co
u
r
s
e
o
f
r
ea
s
o
n
in
g
,
th
er
eb
y
in
cr
ea
s
in
g
t
h
e
f
ea
s
ib
ilit
y
o
f
t
h
e
p
r
o
b
le
m
s
o
lv
i
n
g
p
r
o
ce
s
s
,
u
n
li
k
e
th
e
u
n
if
o
r
m
r
ea
s
o
n
i
n
g
m
et
h
o
d
u
s
ed
in
th
e
tr
ad
itio
n
al
e
x
p
er
t
s
y
s
te
m
s
w
h
er
e
o
n
e
lar
g
e
k
n
o
w
led
g
e
b
ase
ap
p
lies
to
all
[
1
5
]
.
So
m
e
e
x
a
m
p
le
s
o
f
k
n
o
wled
g
e
r
o
le
co
m
m
o
n
l
y
u
s
ed
in
ass
es
s
m
en
t
m
et
h
o
d
in
cl
u
d
e
d
ec
is
io
n
,
n
o
r
m
,
a
n
d
ca
s
e
d
ata.
[
1
6
]
,
in
h
is
r
e
v
ie
w
o
f
KE
tech
n
iq
u
e
s
,
r
ec
o
m
m
e
n
d
ed
[
1
7
]
P
er
s
o
n
al
C
o
n
s
t
r
u
ct
P
s
y
c
h
o
lo
g
y
(
P
C
P
)
,
au
to
m
ated
b
y
[
1
8
]
an
d
m
o
d
i
f
i
ed
b
y
[
1
9
]
.
P
C
P
p
r
esen
ts
a
m
o
d
el
th
at
ad
d
r
ess
es
th
e
u
n
s
tr
u
ct
u
r
ed
n
at
u
r
e
o
f
h
u
m
an
p
s
y
c
h
o
lo
g
y
i
n
r
ep
r
esen
t
i
n
g
,
ac
q
u
ir
in
g
,
a
n
d
p
r
o
ce
s
s
in
g
o
f
k
n
o
w
led
g
e.
He
ar
g
u
e
s
th
a
t
P
E
GASUS,
a
co
m
p
u
ter
p
r
o
g
r
a
m
d
ev
elo
p
ed
b
y
[
2
0
-
2
1
]
w
er
e
m
o
r
e
s
u
itab
le
f
o
r
en
co
d
in
g
asp
ec
t
o
f
h
u
m
a
n
r
ea
s
o
n
i
n
g
b
ased
o
n
t
h
e
v
o
ca
b
u
lar
y
o
f
ex
p
er
ts
i
n
to
f
o
r
m
al
co
n
ce
p
t
s
an
d
s
tr
u
ct
u
r
e
d
k
n
o
w
led
g
e.
[
2
2
]
also
as
s
er
ted
to
t
h
is
b
y
s
u
g
g
e
s
tin
g
it
co
u
ld
al
s
o
b
e
u
s
ed
in
teac
h
i
n
g
b
y
allo
w
i
n
g
o
t
h
er
te
ac
h
er
s
m
a
k
e
u
s
e
o
f
o
n
e
ex
p
er
t‟
s
v
o
ca
b
u
lar
y
in
s
a
m
e
w
a
y
a
s
th
e
e
x
p
er
t
(
teac
h
er
in
t
h
is
ca
s
e)
.
T
h
e
m
aj
o
r
s
etb
ac
k
w
it
h
th
is
tech
n
iq
u
e
t
h
o
u
g
h
is
th
at
it
b
r
id
g
es
t
h
e
p
r
in
cip
le
s
o
f
p
s
y
c
h
o
lo
g
y
u
s
ed
i
n
P
C
P
w
ith
its
l
o
g
ics
a
n
d
s
y
s
te
m
ic
p
r
in
cip
les
w
h
en
p
r
o
d
u
cin
g
a
f
r
a
m
e
w
o
r
k
f
o
r
KE
.
A
ls
o
,
[
2
3
]
n
o
ted
th
at
v
er
b
al
r
ep
o
r
ts
h
ad
n
o
co
r
r
elatio
n
w
it
h
m
en
tal
b
eh
a
v
io
r
in
h
i
s
s
tu
d
y
o
n
p
s
y
c
h
o
lo
g
i
s
t
‟
s
att
itu
d
e
to
w
ar
d
s
v
er
b
al
d
ata
f
r
o
m
p
atie
n
ts
.
Fu
r
t
h
er
m
o
r
e,
t
h
e
h
ier
ar
ch
y
e
m
p
lo
y
ed
b
y
P
C
P
ass
u
m
e
s
a
s
tr
o
n
g
l
y
f
o
r
m
al
a
n
d
id
io
s
y
n
c
h
r
atic
p
o
s
tu
latio
n
b
ased
o
n
u
n
i
f
o
r
m
it
y
.
T
h
is
is
w
r
o
n
g
i
n
th
e
n
o
tio
n
o
f
s
o
f
t
s
y
s
te
m
s
,
w
h
ic
h
as
s
u
m
es
t
h
at
t
h
er
e
is
n
o
v
alid
“
r
ig
h
t
an
s
w
er
”
f
o
r
all
s
itu
a
tio
n
s
,
i
n
o
th
er
w
o
r
d
s
,
th
er
e
is
n
o
o
n
e
-
s
ize
-
f
its
-
all
ap
p
r
o
ac
h
.
3.
M
E
T
H
O
DO
L
O
G
Y
T
h
e
liter
atu
r
e
r
e
v
ie
w
w
a
s
b
as
ed
o
n
t
h
e
s
tr
u
ct
u
r
e
p
r
o
v
id
ed
b
y
[
2
4
]
.
T
h
e
s
tu
d
y
ad
o
p
ted
th
e
g
u
id
eli
n
e
s
s
tated
b
y
[
2
5
]
.
T
h
e
r
ev
ie
w
was
f
r
a
m
ed
b
y
th
e
q
u
esti
o
n
s
wh
ich
th
i
s
r
esear
ch
tr
ied
to
an
s
w
er
a
n
d
in
f
l
u
en
ce
d
th
e
s
ea
r
ch
cr
iter
ia
e
m
p
lo
y
ed
f
o
r
th
e
s
tu
d
y
.
T
h
e
r
esear
ch
q
u
esti
o
n
s
co
v
er
ed
f
iv
e
d
i
f
f
er
e
n
t
s
u
b
d
o
m
a
i
n
s
o
f
KE
b
ased
o
n
th
e
s
co
p
e
o
f
an
d
o
b
jectiv
e
o
f
t
h
i
s
s
t
u
d
y
w
h
ic
h
b
o
r
d
er
ed
o
n
th
e
k
n
o
w
led
g
e
r
o
le
co
n
ce
p
t,
k
n
o
w
led
g
e
elicitatio
n
tec
h
n
iq
u
e
s
,
an
d
o
n
to
lo
g
ical
ap
p
r
o
ac
h
es
e
m
p
lo
y
e
d
in
k
n
o
w
led
g
e
e
n
g
i
n
ee
r
i
n
g
f
o
r
th
e
co
n
s
tr
u
c
tio
n
o
f
k
n
o
w
led
g
e
-
b
ased
s
y
s
te
m
s
(
KB
Ss
)
.
T
h
e
r
esear
ch
q
u
es
tio
n
s
ar
e:
a)
W
h
at
ar
e
t
h
e
cu
r
r
en
t
k
n
o
w
led
g
e
elicitatio
n
tec
h
n
iq
u
es
e
m
p
lo
y
ed
in
KE
?
b
)
W
h
at
ar
e
th
e
cu
r
r
en
t
m
et
h
o
d
o
lo
g
ical
ap
p
r
o
ac
h
es
u
s
ed
in
KE
?
c)
W
h
at
r
o
le
d
o
es
O
n
to
lo
g
y
p
la
y
in
KE
?
d
)
W
h
at
s
p
ec
ial
f
ea
t
u
r
es
d
is
ti
n
g
u
i
s
h
e
s
KE
f
r
o
m
o
th
er
d
is
cip
lin
e
s
?
an
d
e)
W
h
y
is
S
SM
co
n
s
id
er
ed
as
th
e
m
o
s
t
s
u
itab
le
an
d
ef
f
icie
n
t
m
et
h
o
d
f
o
r
KE
p
r
o
b
lem
-
s
o
lv
i
n
g
i
n
a
s
p
atiall
y
d
is
tr
ib
u
ted
an
d
s
h
ar
ed
d
o
m
a
in
s
p
ec
if
ic
co
n
te
x
t?
I
n
co
n
d
u
cti
n
g
th
is
liter
atu
r
e
r
e
v
ie
w
,
b
o
th
j
o
u
r
n
al
a
n
d
co
n
f
er
en
ce
ar
ticle
s
w
er
e
s
o
u
r
ce
d
m
a
n
u
al
l
y
f
r
o
m
s
ev
er
al
o
n
lin
e
d
atab
ases
an
d
s
elec
ted
b
ased
o
n
th
e
cr
iter
ia
s
tated
ab
o
v
e,
th
r
o
u
g
h
a
m
u
l
ti
-
s
tep
m
an
u
al
f
ilter
i
n
g
p
r
o
ce
s
s
w
it
h
in
d
ep
en
d
en
t
v
alid
at
io
n
at
ea
ch
s
tep
.
Du
p
licatio
n
s
an
d
o
v
er
lap
p
in
g
o
f
s
elec
ted
p
ap
er
s
w
er
e
m
a
n
u
al
l
y
s
o
r
ted
o
u
t.
T
h
e
u
s
e
o
f
m
a
n
u
al
p
r
o
ce
s
s
es
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
I
C
T
I
SS
N:
2252
-
8776
S
o
ft S
ystems
Meth
o
d
o
lo
g
y
(
S
S
M)
a
s
a
V
ia
b
le
… (
F
r
a
n
klyn
C
h
u
kwu
n
o
n
s
o
)
3
en
s
u
r
ed
r
ig
o
r
,
r
elev
a
n
ce
a
n
d
cr
ed
ib
ilit
y
w
a
s
m
ai
n
tai
n
ed
d
u
r
in
g
t
h
e
s
elec
tio
n
p
r
o
ce
s
s
.
T
h
e
f
u
ll
tex
t
s
o
f
s
elec
ted
p
ap
er
s
w
er
e
t
h
en
in
d
e
p
en
d
en
tl
y
an
a
l
y
ze
d
b
y
t
h
e
r
es
ea
r
ch
er
s
to
en
s
u
r
e
it
m
ee
t
s
t
h
e
q
u
alit
y
ass
e
s
s
m
e
n
t
cr
iter
ia
p
r
esen
ted
in
T
ab
le
1
,
f
o
r
in
clu
s
io
n
.
T
h
is
w
as
a
ls
o
u
s
ed
to
v
alid
ate
t
h
e
ar
ticles
s
ele
cted
f
o
r
th
i
s
r
ev
ie
w
s
tu
d
y
.
T
ab
le
1
.
Qu
alit
y
C
r
iter
ia
[
2
5
]
1
I
s t
h
e
p
a
p
e
r
b
a
se
d
o
n
r
e
se
a
r
c
h
(
o
r
i
s
i
t
me
r
e
l
y
a
„
„
l
e
sso
n
s l
e
a
r
n
e
d
”
r
e
p
o
r
t
b
a
se
d
o
n
e
x
p
e
r
t
o
p
i
n
i
o
n
)
?
2
I
s t
h
e
r
e
a
c
l
e
a
r
st
a
t
e
me
n
t
o
f
t
h
e
a
i
ms
o
f
t
h
e
r
e
se
a
r
c
h
?
3
I
s t
h
e
r
e
a
n
a
d
e
q
u
a
t
e
d
e
scri
p
t
i
o
n
o
f
t
h
e
c
o
n
t
e
x
t
i
n
w
h
i
c
h
t
h
e
r
e
se
a
r
c
h
w
a
s
c
a
r
r
i
e
d
o
u
t
?
4
W
a
s t
h
e
r
e
se
a
r
c
h
d
e
si
g
n
a
p
p
r
o
p
r
i
a
t
e
t
o
a
d
d
r
e
ss t
h
e
a
i
ms
o
f
t
h
e
r
e
se
a
r
c
h
?
5
W
a
s t
h
e
r
e
c
r
u
i
t
me
n
t
st
r
a
t
e
g
y
a
p
p
r
o
p
r
i
a
t
e
t
o
t
h
e
a
i
ms o
f
t
h
e
r
e
se
a
r
c
h
?
6
W
a
s t
h
e
r
e
a
c
o
n
t
r
o
l
g
r
o
u
p
w
i
t
h
w
h
i
c
h
t
o
c
o
m
p
a
r
e
t
r
e
a
t
me
n
t
s?
7
W
a
s t
h
e
d
a
t
a
c
o
l
l
e
c
t
e
d
i
n
a
w
a
y
t
h
a
t
a
d
d
r
e
sse
d
t
h
e
r
e
se
a
r
c
h
i
ssu
e
?
8
W
a
s t
h
e
d
a
t
a
a
n
a
l
y
si
s su
ffi
c
i
e
n
t
l
y
r
i
g
o
r
o
u
s?
9
H
a
s t
h
e
r
e
l
a
t
i
o
n
s
h
i
p
b
e
t
w
e
e
n
r
e
se
a
r
c
h
e
r
a
n
d
p
a
r
t
i
c
i
p
a
n
t
s
b
e
e
n
c
o
n
s
i
d
e
r
e
d
t
o
a
n
a
d
e
q
u
a
t
e
d
e
g
r
e
e
?
10
I
s t
h
e
r
e
a
c
l
e
a
r
st
a
t
e
me
n
t
o
f
fi
n
d
i
n
g
s?
11
I
s t
h
e
st
u
d
y
o
f
v
a
l
u
e
f
o
r
r
e
se
a
r
c
h
o
r
p
r
a
c
t
i
c
e
?
4.
DIS
CU
SS
I
O
N
O
F
F
I
N
DIN
G
S
T
h
is
s
ec
tio
n
d
is
c
u
s
s
e
s
th
e
f
i
n
d
in
g
s
o
f
th
i
s
liter
at
u
r
e
r
ev
ie
w
s
tu
d
y
.
T
h
e
f
i
n
d
in
g
s
ar
e
p
r
esen
ted
in
f
i
v
e
s
u
b
-
d
o
m
ai
n
s
,
g
u
id
ed
b
y
th
e
s
co
p
e
an
d
r
esear
ch
q
u
esti
o
n
s
th
e
s
tu
d
y
atte
m
p
ts
to
ad
d
r
e
s
s
;
th
e
tec
h
n
iq
u
e
s
cu
r
r
en
tl
y
u
s
ed
f
o
r
k
n
o
w
led
g
e
elicitatio
n
,
t
h
e
c
u
r
r
en
t
m
e
t
h
o
d
o
lo
g
ic
al
ap
p
r
o
ac
h
es
u
s
ed
in
KE
,
t
h
e
r
o
le
o
f
o
n
to
lo
g
y
i
n
KE
,
th
e
s
p
ec
ial
ch
ar
ac
ter
is
tic
s
o
f
KE
,
an
d
f
in
all
y
p
r
ese
n
ts
a
s
tr
o
n
g
ar
g
u
m
en
t
as
to
w
h
y
So
f
t
S
y
s
te
m
s
Me
t
h
o
d
o
lo
g
y
(
SS
M)
is
th
e
m
o
s
t
s
u
itab
le
an
d
ef
f
ic
ien
t
m
et
h
o
d
f
o
r
k
n
o
w
led
g
e
en
g
in
ee
r
i
n
g
p
r
o
b
lem
-
s
o
lv
i
n
g
i
n
a
s
p
atiall
y
d
is
tr
ib
u
t
ed
an
d
s
h
ar
ed
d
o
m
ai
n
s
p
ec
i
f
ic
co
n
tex
t.
4
.
1
.
K
no
w
ledg
e
E
licit
a
t
io
n T
ec
hn
iqu
e
s
Kn
o
w
led
g
e
elic
itatio
n
is
a
v
er
y
i
m
p
o
r
tan
t
a
s
p
ec
t
o
f
KE
.
Kn
o
w
led
g
e
elic
itatio
n
is
t
h
e
p
r
o
ce
s
s
o
f
ex
tr
ac
ti
n
g
d
o
m
ai
n
s
p
ec
i
f
ic
k
n
o
w
led
g
e
w
i
th
r
eg
ar
d
s
co
g
n
iti
v
e
is
s
u
e
s
u
n
d
er
l
y
i
n
g
h
u
m
a
n
p
er
f
o
r
m
an
ce
[
2
6
-
2
7
]
.
First
u
s
ed
i
n
ex
p
er
t
s
y
s
te
m
s
an
d
n
o
w
i
n
KE
,
s
ev
er
al
s
t
u
d
ies
h
av
e
b
ee
n
s
ee
k
i
n
g
th
e
b
est
ap
p
r
o
ac
h
to
d
ev
elo
p
in
g
k
n
o
w
led
g
e
b
ase
s
in
to
ap
p
licatio
n
s
o
r
s
y
s
te
m
s
s
u
c
h
as
i
n
tel
lig
e
n
t
t
u
to
r
in
g
s
y
s
te
m
s
,
tr
ain
i
n
g
o
r
ed
u
ca
tio
n
al
s
y
s
te
m
s
,
e
x
p
er
t
s
y
s
te
m
s
,
ad
ap
tiv
e
u
s
er
-
i
n
ter
f
ac
es,
etc.
I
n
o
th
er
w
o
r
d
s
,
k
n
o
w
l
ed
g
e
elicitatio
n
is
a
s
u
b
p
r
o
ce
s
s
o
f
k
n
o
w
led
g
e
ac
q
u
is
i
tio
n
,
ev
e
n
th
o
u
g
h
th
e
t
w
o
ar
e
in
ter
ch
an
g
ea
b
l
y
u
s
ed
,
an
d
all
o
f
w
h
ich
m
ak
e
u
p
KE
.
T
h
e
n
e
w
d
r
iv
e
f
o
r
KB
Ss
h
a
v
e
r
aised
co
n
ce
r
n
s
i
n
b
o
th
b
asic
an
d
ap
p
lied
s
cien
ce
s
o
n
th
e
b
est
w
a
y
i
n
w
h
ic
h
k
n
o
w
led
g
e
ca
n
b
e
ef
f
ec
tiv
el
y
an
d
e
f
f
icie
n
tl
y
elicited
f
r
o
m
a
n
e
x
p
er
t.
[
2
8
]
an
d
[
2
9
]
c
r
iticized
th
e
u
s
e
o
f
co
g
n
iti
v
e
t
h
eo
r
y
f
o
r
k
n
o
w
led
g
e
elicitatio
n
s
tati
n
g
t
h
at
alt
h
o
u
g
h
it
ad
d
r
ess
es
th
e
k
n
o
w
le
d
g
e
is
s
u
e,
th
e
asp
ec
t
o
f
it
s
r
ep
r
esen
tat
io
n
a
n
d
v
ar
ied
co
n
ce
p
tu
aliza
tio
n
o
f
t
h
e
s
t
r
u
ctu
r
e
o
f
t
h
e
k
n
o
w
led
g
e
(
s
c
h
e
m
a
ta,
p
r
o
to
t
y
p
es,
s
e
m
a
n
tic
n
e
t
w
o
r
k
s
,
etc.
)
w
er
e
n
o
t
ad
d
r
ess
ed
,
an
d
w
h
ich
o
f
co
u
r
s
e,
is
th
e
m
a
in
f
o
cu
s
o
f
K
E
.
E
ar
ly
s
t
u
d
ies
o
n
k
n
o
w
led
g
e
elicitatio
n
f
o
c
u
s
ed
o
n
d
ir
ec
t
ex
tr
ac
tio
n
b
u
t
t
h
i
s
w
a
s
q
u
ic
k
l
y
p
u
t
asid
e
b
ec
au
s
e
o
f
th
e
co
m
p
le
x
it
y
th
at
c
h
ar
ac
ter
ized
th
e
p
r
o
b
le
m
co
n
tex
t
[
3
0
]
.
Oth
er
li
m
ita
tio
n
s
o
f
ea
r
l
y
k
n
o
w
led
g
e
eli
citatio
n
tec
h
n
iq
u
e
s
in
cl
u
d
e
b
ias,
er
r
o
r
,
f
la
w
ed
v
er
b
al
r
ep
o
r
tin
g
o
f
e
x
p
er
ts
[
3
1
]
.
R
ec
en
t
ap
p
r
o
ac
h
es
to
k
n
o
w
le
d
g
e
elicitatio
n
m
a
k
e
u
s
e
o
f
m
o
d
el
co
n
s
tr
u
cted
to
r
ef
lect
th
e
ex
p
er
t
‟
s
k
n
o
w
le
d
g
e
[
3
2
]
,
w
it
h
f
o
cu
s
o
n
f
o
r
m
al
an
d
s
y
m
b
o
lic
r
ep
r
esen
tatio
n
o
f
k
n
o
w
led
g
e,
an
d
h
o
w
s
u
c
h
r
ep
r
esen
tatio
n
s
ar
e
ac
tu
all
y
o
b
tain
ed
.
T
h
u
s
,
o
u
r
f
o
cu
s
h
er
e
s
h
al
l
be
n
ar
r
o
w
ed
to
r
ec
en
t
k
n
o
w
le
d
g
e
elicitatio
n
tec
h
n
iq
u
e
s
e
m
p
lo
y
ed
i
n
th
e
ac
q
u
is
itio
n
,
an
al
y
s
i
s
an
d
m
o
d
elli
n
g
o
f
k
n
o
w
led
g
e.
A
s
u
m
m
ar
y
o
f
th
e
s
e
tec
h
n
iq
u
e
s
i
s
p
r
ese
n
ted
in
T
ab
le
2
w
h
ile
it
s
ap
p
licab
ilit
y
is
d
ep
icted
in
Fig
u
r
e
1
.
1)
L
i
m
ited
-
in
f
o
r
m
a
tio
n
an
d
co
n
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as
t
h
e
w
id
el
y
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s
ed
C
o
m
m
o
n
KADS
[
3
5
]
[
5
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,
Gen
er
ic
T
ask
ap
p
r
o
ac
h
[
3
6
]
,
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r
o
tég
é
[
3
7
-
3
8
]
,
R
o
le
-
L
i
m
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tin
g
Me
th
o
d
s
[
3
9
-
4
0
]
,
KA
D
S
[
4
1
]
[
5
]
an
d
C
o
m
p
o
n
e
n
ts
o
f
E
x
p
er
tis
e
[
4
2
-
4
3
]
.
On
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co
m
m
o
n
ch
ar
ac
ter
is
tic
a
m
o
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g
all
t
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m
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Ag
ile
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p
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ctu
r
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t
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ar
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n
o
t
li
f
e
-
th
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te
n
i
n
g
[
4
4
-
4
5
]
.
T
h
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ee
d
f
o
r
a
m
o
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ap
tiv
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m
et
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p
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to
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Ver
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T
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to
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ar
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m
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
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2252
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8776
S
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Meth
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S
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s
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V
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F
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kwu
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m
ak
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ld
p
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b
lem
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it
u
atio
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it
h
in
a
d
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ai
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-
s
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i
f
i
c
co
n
tex
t.
Ho
w
e
v
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,
k
n
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in
g
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h
e
ap
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iate
lev
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etail
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k
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p
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ai
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ch
alle
n
g
e
i
n
th
e
u
s
e
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o
n
to
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ie
s
[
4
0
]
.
So
m
e
m
et
h
o
d
o
lo
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ies
h
av
e
h
o
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ac
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llab
o
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ativ
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is
s
u
es i
n
o
n
to
lo
g
y
co
n
s
tr
u
ctio
n
[
4
6
-
4
7
]
.
4
.
3
.
T
he
Ro
le
o
f
O
nto
lo
g
y
in K
no
w
ledg
e
E
ng
ineering
T
h
e
1
9
9
0
s
w
it
n
ess
ed
an
in
cr
e
asin
g
r
o
le
o
f
o
n
t
o
lo
g
ies
p
ar
ticu
lar
l
y
i
n
t
h
e
f
ield
o
f
co
m
p
u
te
r
s
cien
ce
.
Sev
er
al
d
e
f
i
n
itio
n
s
o
f
o
n
to
lo
g
y
e
x
is
t
b
u
t
t
h
e
m
o
s
t
co
m
m
o
n
l
y
u
s
ed
i
s
t
h
at
d
ef
i
n
ed
b
y
[
1
3
]
,
w
h
ic
h
s
tates
t
h
at
“
o
n
to
lo
g
y
is
a
n
e
x
p
licit
s
p
e
cif
icatio
n
o
f
a
s
h
ar
ed
co
n
ce
p
tu
aliza
tio
n
th
a
t
h
o
ld
s
i
n
a
p
ar
ticu
l
ar
co
n
te
x
t.”
On
to
lo
g
y
w
a
s
i
n
tr
o
d
u
ce
d
in
t
h
e
ea
r
l
y
1
9
9
0
s
to
f
ac
i
litate
k
n
o
w
led
g
e
s
h
ar
i
n
g
b
u
t
w
a
s
n
o
t
w
i
d
ely
ad
o
p
ted
in
t
h
e
k
n
o
w
led
g
e
en
g
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n
ee
r
in
g
f
ield
u
n
t
il
t
h
e
m
id
-
2
0
0
0
s
,
w
h
e
n
it
w
a
s
u
s
ed
to
ad
d
r
ess
th
e
g
r
o
w
i
n
g
n
ee
d
f
o
r
co
n
ce
p
t
s
h
ar
i
n
g
i
n
t
h
e
W
W
W
an
d
later
p
av
ed
w
a
y
f
o
r
th
e
Se
m
a
n
ti
c
W
eb
[
4
8
]
.
C
o
n
tex
t
p
la
y
s
a
v
er
y
i
m
p
o
r
tan
t
r
o
le
p
ar
ticu
lar
l
y
i
n
th
e
r
e
u
s
e
o
f
o
n
to
lo
g
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p
ar
tl
y
b
ec
au
s
e
d
if
f
er
en
t
in
d
i
v
id
u
a
ls
h
a
v
e
v
ar
ied
co
n
ce
p
tu
aliza
tio
n
s
o
f
th
e
r
ea
l
w
o
r
ld
,
th
u
s
m
ak
in
g
it
n
ec
es
s
ar
y
to
ex
p
licate
th
e
co
n
t
ex
t
w
ith
i
n
w
h
ich
t
h
e
o
n
to
lo
g
y
ex
is
ts
i
f
o
th
er
s
ar
e
to
u
n
d
er
s
ta
n
d
an
d
m
a
k
e
u
s
e
o
f
it
[
4
9
]
.
[
5
0
]
p
r
o
p
o
s
ed
a
th
eo
r
y
to
d
ef
i
n
e
co
n
te
x
t
s
p
ac
e.
Ho
w
e
v
er
,
in
r
ea
lit
y
,
m
o
s
t
h
u
m
a
n
ac
ti
v
it
y
s
y
s
te
m
s
ar
e
b
o
u
n
d
ed
w
it
h
v
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y
co
m
p
le
x
an
d
h
ig
h
l
y
u
n
s
tr
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ct
u
r
ed
co
n
t
ex
ts
.
T
h
is
i
s
a
v
er
y
li
m
it
in
g
f
ac
to
r
w
h
e
n
it
co
m
e
s
to
th
e
u
s
e
o
f
o
n
to
lo
g
y
in
s
o
lv
in
g
u
n
s
tr
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ct
u
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ed
p
r
o
b
lem
s
o
r
h
u
m
an
ac
ti
v
it
y
p
r
o
b
lem
s
it
u
atio
n
s
[
5
1
]
.
[
5
2
]
s
p
ec
if
ied
o
n
to
lo
g
y
in
to
f
iv
e
d
i
f
f
er
en
t
k
n
o
w
led
g
e
r
ep
r
esen
tati
o
n
r
o
les:
1.
A
s
u
r
r
o
g
ate
f
o
r
th
e
th
in
g
s
i
n
t
h
e
r
ea
l
w
o
r
ld
2.
A
s
e
t
o
f
o
n
to
lo
g
ical
co
m
m
it
m
en
ts
3.
A
t
h
eo
r
y
o
f
r
ep
r
esen
ta
tio
n
al
c
o
n
s
tr
u
ct
s
p
lu
s
in
f
er
e
n
ce
s
it sa
n
ctio
n
s
/r
ec
o
m
m
e
n
d
s
4.
A
m
ed
iu
m
f
o
r
ef
f
icien
t c
o
m
p
u
tatio
n
5.
A
m
ed
iu
m
f
o
r
h
u
m
a
n
ex
p
r
es
s
i
o
n
T
h
e
m
ai
n
p
r
o
b
lem
h
er
e
is
t
h
at
o
n
l
y
r
o
les
1
,
2
an
d
5
a
ctu
all
y
ap
p
l
y
to
o
n
to
lo
g
y
-
s
p
ec
if
icatio
n
lan
g
u
a
g
es
u
s
ed
i
n
k
n
o
w
led
g
e
r
ep
r
esen
tatio
n
[
5
3
]
.
T
h
is
i
m
p
lies
t
h
at
o
n
to
lo
g
y
s
p
ec
if
icat
io
n
s
d
o
n
o
t
co
n
s
id
er
an
y
s
p
ec
i
f
ic
p
ar
ad
ig
m
f
o
r
r
e
aso
n
i
n
g
.
[
1
3
]
p
r
o
p
o
s
ed
th
e
u
s
e
o
f
On
to
lin
g
u
a
o
n
KI
F
a
s
m
ed
iato
r
s
b
et
w
ee
n
d
if
f
er
e
n
t
k
n
o
w
led
g
e
r
ep
r
ese
n
tatio
n
la
n
g
u
a
g
es
to
e
n
ab
le
o
n
to
lo
g
y
f
r
a
m
e
s
t
y
le
to
b
e
d
ef
i
n
ed
in
to
clas
s
es,
s
u
b
clas
s
es,
etc
[
5
4
]
.
T
h
e
p
u
r
p
o
s
e
o
f
On
to
lin
g
u
a
w
a
s
to
en
ab
le
th
e
s
h
ar
in
g
o
f
o
n
to
lo
g
i
es
b
et
w
ee
n
u
s
er
s
b
y
p
r
o
v
id
in
g
lib
r
ar
y
s
er
v
ices.
T
h
is
co
n
ce
p
t
h
as
s
in
ce
b
ee
n
w
i
d
ely
ad
o
p
ted
in
m
a
n
y
W
3
C
p
r
o
j
ec
ts
s
u
ch
as
th
e
OW
L
u
s
ed
f
o
r
th
e
s
e
m
a
n
tic
w
eb
.
Ho
w
ev
er
,
OW
L
-
D
L
w
h
i
ch
is
a
s
u
b
s
et
o
f
OW
L
m
ak
e
s
u
s
e
o
f
f
r
ag
m
e
n
ted
d
escr
ip
tio
n
lo
g
ic
to
g
u
ar
an
tee
co
m
p
u
tab
ilit
y
a
m
o
n
g
u
s
er
s
.
T
h
is
b
r
in
g
s
u
s
b
ac
k
to
o
u
r
ea
r
lier
s
tate
m
e
n
t
t
h
a
t
o
n
to
lo
g
ies
ar
e
n
o
t
s
p
ec
if
ic
t
o
a
r
ea
s
o
n
in
g
m
ec
h
an
is
m
.
T
h
is
s
h
o
w
s
t
h
at
th
er
e
is
a
b
ias
in
th
e
r
ea
s
o
n
i
n
g
p
ar
ad
ig
m
o
f
DL
w
h
en
OW
L
is
u
s
ed
to
m
o
d
el
th
e
r
ea
l
w
o
r
ld
[
5
5
-
5
6
]
.
A
ls
o
,
ad
d
itio
n
al
r
ea
s
o
n
in
g
k
n
o
w
led
g
e
is
al
w
a
y
s
r
eq
u
ir
ed
w
h
e
n
D
L
is
u
s
ed
f
o
r
o
n
to
lo
g
y
v
alid
atio
n
[
5
7
]
.
L
astl
y
,
t
h
e
n
e
w
r
u
l
e
la
n
g
u
a
g
e
s
ep
ar
atel
y
b
ei
n
g
d
ef
in
ed
b
y
th
e
W
3
C
to
co
m
p
li
m
en
t
t
h
e
p
r
esen
t
OW
L
f
u
r
th
er
ex
p
o
s
es
t
h
ese
li
m
itatio
n
s
[
5
8
-
5
9
]
.
So
m
e
a
u
th
o
r
s
h
av
e
p
r
o
p
o
s
ed
th
e
u
s
e
o
f
[
6
0
]
KI
F
as
a
p
o
s
s
ib
le
w
a
y
o
u
t
g
iv
e
n
th
a
t
it
is
le
s
s
b
ia
s
ed
an
d
is
ab
le
to
s
p
ec
i
f
y
r
ea
s
o
n
in
g
i
n
a
s
i
n
g
le
la
n
g
u
a
g
e
[
6
1
-
6
3
]
.
Ho
w
e
v
er
,
t
h
is
is
s
t
ill
a
p
r
o
p
o
s
itio
n
as
n
o
t
m
a
n
y
s
t
u
d
ies
h
av
e
b
ee
n
co
n
d
u
cted
in
t
h
is
r
e
g
ar
d
.
4
.
4
.
Sp
ec
if
ic
Cha
ra
ct
er
is
t
ics o
f
K
no
w
ledg
e
E
ng
ineering
Kn
o
w
led
g
e
e
n
g
i
n
ee
r
i
n
g
ta
s
k
s
ar
e
ch
ar
ac
ter
ized
b
y
s
p
e
cif
ic
f
ea
tu
r
es
t
h
at
li
m
it
t
h
e
t
y
p
e
o
f
m
et
h
o
d
o
lo
g
y
t
h
at
ca
n
b
e
u
s
e
d
f
o
r
p
r
o
b
lem
s
o
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ted
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20
1
6
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1
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10
6
th
e
KB
S
f
o
r
m
a
v
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y
lar
g
e
g
r
o
u
p
o
f
s
p
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is
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er
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ed
i
n
d
iv
id
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in
teg
r
ated
th
r
o
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g
h
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llab
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r
ativ
e
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d
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ter
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ti
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e
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in
a
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ic,
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is
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ib
u
ted
an
d
s
h
ar
ed
d
o
m
ai
n
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4
.
5
.
Why
SS
M
is
a
M
o
re
Su
it
a
ble
M
et
ho
do
lo
g
y
f
o
r
K
no
w
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e
E
ng
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e
s
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ar
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g
o
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led
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e
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er
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th
e
o
f
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ice,
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class
r
o
o
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s
,
o
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m
ed
ia,
o
r
in
th
e
s
tr
ee
ts
,
h
as
b
ee
n
an
e
x
is
t
in
g
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h
en
o
m
en
o
n
s
in
ce
th
e
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ea
tio
n
o
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m
a
n
.
Ne
v
er
th
ele
s
s
,
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er
e
is
a
m
aj
o
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d
is
tin
ct
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n
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w
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k
n
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w
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e
-
g
i
v
i
n
g
(
as
i
n
th
e
a
f
o
r
e
m
e
n
tio
n
ed
)
a
n
d
k
n
o
w
led
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e
-
s
h
ar
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g
.
K
n
o
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led
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e
-
s
h
ar
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n
g
is
a
co
m
p
le
x
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s
k
th
at
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n
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o
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e
ex
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ter
ized
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r
ac
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at
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s
to
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e
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d
en
ti
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ied
an
d
o
v
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co
m
e.
So
m
e
o
f
t
h
ese
b
ar
r
ier
s
b
ec
o
m
e
m
o
r
e
p
r
o
n
o
u
n
ce
d
w
h
e
n
th
e
p
ar
ties
in
v
o
lv
ed
i
n
t
h
e
ex
c
h
a
n
g
e
o
f
k
n
o
w
led
g
e
ar
e
co
n
f
i
n
ed
in
a
s
p
atial
l
y
d
i
s
tr
ib
u
ted
d
o
m
a
in
-
s
p
ec
i
f
ic
co
n
te
x
t.
So
m
e
s
tu
d
ie
s
h
a
v
e
id
e
n
ti
f
ied
t
h
ese
b
ar
r
ier
s
to
i
n
cl
u
d
e
p
er
ce
iv
ed
p
o
w
er
lo
s
s
[
6
4
]
,
j
o
b
in
s
ec
u
r
it
y
[
6
5
]
,
lack
o
f
m
o
tiv
a
tio
n
[
6
6
]
,
r
esis
tan
ce
to
ch
an
g
e
[
6
7
]
,
an
d
in
co
n
s
id
er
a
te
lan
g
u
a
g
e
u
s
e
[
6
8
]
.
Mo
s
t
o
f
th
ese
b
ar
r
ier
s
ar
e
s
o
f
t
is
s
u
e
s
co
m
m
o
n
w
it
h
an
y
h
u
m
a
n
ac
tiv
i
t
y
s
y
s
te
m
.
T
h
er
ef
o
r
e,
th
e
ab
ilit
y
to
m
an
a
g
e
k
n
o
w
led
g
e
(
k
n
o
w
led
g
e
m
an
a
g
e
m
e
n
t)
p
la
y
s
a
v
er
y
cr
it
ical
r
o
le
in
KE
.
K
n
o
w
led
g
e
m
an
ag
e
m
e
n
t
(
KM
)
i
s
b
asicall
y
ab
o
u
t
th
e
p
r
o
ce
s
s
e
s
in
v
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l
v
ed
f
r
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m
id
en
tify
i
n
g
k
n
o
w
led
g
e
g
o
al
s
to
m
ain
tain
in
g
a
n
d
ev
al
u
ati
n
g
r
ep
o
s
ito
r
ies
o
f
k
n
o
w
led
g
e
[
6
9
]
.
A
k
e
y
p
ar
t
o
f
KM
o
r
KE
is
in
th
e
k
n
o
w
led
g
e
el
icitat
io
n
p
r
o
ce
s
s
.
T
h
ese
s
o
f
t
is
s
u
e
s
ar
e
al
w
a
y
s
an
o
b
s
tacle
to
k
n
o
w
led
g
e
elicitatio
n
.
T
h
u
s
,
th
e
ab
ilit
y
to
id
en
tify
w
h
at
k
n
o
w
led
g
e
to
elicit
an
d
p
r
o
p
er
l
y
h
i
g
h
li
g
h
tin
g
t
h
e
t
y
p
e
o
f
b
ar
r
ier
s
t
h
at
p
o
s
e
a
c
h
alle
n
g
e
to
eliciti
n
g
t
h
e
k
n
o
w
led
g
e,
is
a
b
ig
s
tep
i
n
t
h
e
r
ig
h
t
d
ir
ec
tio
n
w
it
h
r
eg
ar
d
s
to
k
n
o
w
led
g
e
el
icitati
o
n
.
Fig
u
r
e
2
.
T
h
e
Sev
en
Sta
g
es o
f
SS
M
SS
M
m
a
k
es
u
s
e
o
f
k
n
o
w
le
d
g
e
co
n
ce
p
ts
to
h
i
g
h
l
ig
h
t
n
o
n
-
tec
h
n
ical
a
n
d
f
u
zz
y
is
s
u
es
i
n
w
e
b
en
v
ir
o
n
m
e
n
t
s
[
7
0
]
.
[
7
1
]
p
r
o
p
o
s
ed
a
n
e
w
ap
p
r
o
ac
h
f
o
r
ad
d
r
ess
i
n
g
s
o
f
t
a
s
p
ec
ts
o
f
a
s
y
s
te
m
,
w
h
ich
h
e
ter
m
ed
s
o
f
t
s
y
s
te
m
s
m
eth
o
d
o
lo
g
y
(
S
SM)
,
b
ased
o
n
s
o
f
t
s
y
s
te
m
s
th
eo
r
y
(
SS
T
)
.
T
h
is
ap
p
r
o
ac
h
is
b
ased
o
n
th
e
th
eo
r
y
o
f
s
y
s
te
m
s
th
in
k
i
n
g
w
h
er
e
t
h
e
an
al
y
s
t
o
r
k
n
o
w
led
g
e
en
g
i
n
ee
r
leav
e
s
b
eh
i
n
d
h
is
p
r
ec
o
n
ce
p
tio
n
s
ab
o
u
t
t
h
e
p
r
o
b
lem
s
it
u
atio
n
an
d
tr
ie
s
t
o
d
ef
in
e
t
h
e
p
r
o
b
lem
b
a
s
ed
o
n
a
w
o
r
ld
v
ie
w
(
w
elta
n
s
c
h
a
u
u
n
g
)
.
T
h
is
th
eo
r
y
ass
u
m
e
s
t
h
at
ev
er
y
b
o
d
y
is
r
i
g
h
t
b
ased
o
n
t
h
eo
r
y
p
er
ce
p
tio
n
o
f
th
e
p
r
o
b
le
m
a
n
d
atte
m
p
t
s
to
u
n
i
f
y
all
t
h
ese
d
iv
er
g
e
n
t
v
ie
w
s
in
to
a
w
e
lta
n
s
c
h
au
u
n
g
w
h
er
e
all
th
e
ac
to
r
s
s
h
ar
e
a
co
m
m
o
n
v
ie
w
t
h
r
o
u
g
h
a
s
ev
e
n
s
ta
g
e
p
r
o
ce
s
s
(
s
ee
F
ig
u
r
e
2
)
.
T
h
e
p
r
o
b
lem
[
7
1
]
tr
ied
to
ad
d
r
ess
w
as
h
o
w
to
r
ep
r
esen
t
e
x
p
er
t
id
ea
s
in
an
u
n
s
tr
u
ct
u
r
ed
p
r
o
b
lem
s
it
u
atio
n
i
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to
a
s
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u
c
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ed
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b
y
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ak
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ict
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u
ct
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m
o
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r
a
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r
k
s
to
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r
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ld
p
r
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b
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r
d
er
to
elicit
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e
e
x
p
er
t‟
s
k
n
o
w
led
g
e.
He
ar
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u
es
t
h
at
in
d
iv
id
u
als
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n
a
h
u
m
an
ac
t
iv
i
t
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p
r
o
b
le
m
s
itu
a
tio
n
all
h
av
e
d
i
f
f
er
en
t
p
er
ce
p
tio
n
s
o
f
t
h
e
p
r
o
b
le
m
,
ap
p
r
o
ac
h
es
to
ad
d
r
ess
in
g
it,
b
en
e
f
its
a
n
d
r
is
k
s
d
er
iv
ed
as
a
r
e
s
u
lt
o
f
ad
d
r
ess
in
g
it,
a
n
d
all
w
it
h
i
n
a
c
o
n
s
ta
n
tl
y
ch
a
n
g
in
g
en
v
ir
o
n
m
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tal
co
n
te
x
t
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m
a
y
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n
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d
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h
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ical,
ec
o
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ic,
an
d
g
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ap
h
ic,
an
d
w
h
ich
t
h
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o
w
led
g
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en
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i
n
ee
r
m
u
s
t
co
n
s
id
er
ed
w
h
ile
f
i
n
d
i
n
g
a
s
o
lu
tio
n
to
t
h
e
p
r
o
b
lem
.
T
h
is
w
a
s
a
lac
k
in
g
p
h
en
o
m
e
n
o
n
in
th
e
P
C
P
h
ier
ar
ch
y
t
h
at
f
o
cu
s
ed
b
asicall
y
o
n
th
e
p
er
ce
p
tio
n
o
f
in
d
i
v
id
u
al
s
w
it
h
o
u
t
tak
in
g
i
n
to
ac
co
u
n
t
th
e
u
n
s
tr
u
ct
u
r
ed
an
d
p
r
o
lif
er
ati
n
g
en
v
ir
o
n
m
e
n
t
u
n
d
er
w
h
ic
h
s
u
ch
i
n
d
iv
id
u
als
o
p
er
ate
[
7
2
]
.
T
h
u
s
,
SS
M
p
r
o
v
id
e
s
w
id
el
y
ap
p
licab
le
tec
h
n
iq
u
es
an
d
s
tr
u
ct
u
r
es
f
o
r
k
n
o
w
led
g
e
e
n
g
i
n
ee
r
i
n
g
tas
k
s
.
Ho
w
e
v
er
,
th
e
b
u
r
d
en
o
f
an
al
y
z
in
g
t
h
ese
f
i
n
d
in
g
s
ar
e
le
f
t to
th
e
k
n
o
w
led
g
e
en
g
i
n
ee
r
o
r
an
al
y
s
t to
b
ea
r
as th
er
e
is
n
o
co
m
p
u
ter
p
r
o
g
r
a
m
av
ailab
le
to
au
to
m
ate
th
e
SS
M
p
r
o
ce
s
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
I
C
T
I
SS
N:
2252
-
8776
S
o
ft S
ystems
Meth
o
d
o
lo
g
y
(
S
S
M)
a
s
a
V
ia
b
le
… (
F
r
a
n
klyn
C
h
u
kwu
n
o
n
s
o
)
7
SS
M
w
as
f
ir
s
t
p
r
o
p
o
s
ed
b
y
[
7
1
]
,
an
d
[
7
3
]
as
an
alte
r
n
ati
v
e
m
et
h
o
d
f
o
r
s
o
lv
i
n
g
i
n
f
o
r
m
atio
n
s
y
s
te
m
s
d
ev
elo
p
m
en
t
is
s
u
e
s
.
S
SM
ad
d
r
ess
es
b
o
th
s
tr
u
ct
u
r
ed
an
d
u
n
s
tr
u
ct
u
r
ed
p
r
o
b
lem
ca
s
es.
I
t
e
m
p
lo
y
s
SS
ADM
,
a
tech
n
ical
v
er
s
io
n
o
f
SS
M,
f
o
r
ca
s
es
w
it
h
clea
r
l
y
d
e
f
i
n
ed
a
n
d
s
tr
u
ct
u
r
ed
s
y
s
te
m
i
s
s
u
es
a
n
d
SS
M
f
o
r
f
u
zz
y
,
un
d
e
f
i
n
ed
an
d
u
n
s
tr
u
ct
u
r
ed
p
r
o
b
lem
s
it
u
atio
n
s
[
7
4
]
,
th
o
u
g
h
th
e
m
ai
n
r
ea
s
o
n
f
o
r
it
s
d
ev
elo
p
m
e
n
t
w
as to
tac
k
le
th
e
s
h
o
r
tco
m
i
n
g
s
w
h
ich
ex
i
s
ti
n
g
m
e
th
o
d
o
lo
g
ies
at
t
h
e
t
i
m
e
f
ac
ed
i
n
ad
d
r
ess
i
n
g
s
o
f
t
a
n
d
c
o
m
p
le
x
i
s
s
u
es
[
7
5
]
.
SS
M
f
o
c
u
s
es
o
n
s
tak
e
h
o
ld
er
p
er
s
p
ec
tiv
es
a
n
d
en
g
a
g
es
th
e
u
s
er
r
ig
h
t
f
r
o
m
t
h
e
b
eg
i
n
n
i
n
g
o
f
th
e
p
r
o
b
le
m
-
s
o
lv
i
n
g
p
r
o
ce
s
s
,
a
lac
k
in
g
p
h
e
n
o
m
e
n
o
n
in
m
o
s
t
o
f
th
e
ap
p
r
o
ac
h
es
u
s
ed
i
n
KE
.
SS
M
m
a
k
es
u
s
e
o
f
v
er
y
ea
s
y
to
u
s
e
to
o
ls
to
ca
p
t
u
r
e
an
d
r
ep
r
esen
t
t
h
e
r
ea
l
w
o
r
ld
s
ce
n
ar
io
s
th
r
o
u
g
h
r
ic
h
p
ict
u
r
es
a
n
d
r
o
o
t
d
ef
in
itio
n
s
(
C
A
T
W
OE
)
in
s
u
ch
a
w
a
y
a
s
to
en
co
u
r
ag
e
co
n
ti
n
u
ed
u
s
e
r
en
g
ag
e
m
e
n
t.
[
7
6
]
n
o
ted
th
a
t
o
n
e
o
f
th
e
m
aj
o
r
co
n
tr
ib
u
tio
n
s
o
f
SS
M
i
n
p
r
o
b
le
m
s
o
l
v
i
n
g
i
s
i
n
th
e
p
r
o
ce
d
u
r
al
s
tag
e
s
u
s
ed
b
y
SS
M
to
tr
an
s
f
o
r
m
a
p
r
o
b
le
m
s
itu
a
tio
n
f
r
o
m
an
u
n
s
tr
u
ctu
r
e
d
,
th
r
o
u
g
h
s
tr
u
c
tu
r
ed
to
th
e
d
esira
b
le
ch
an
g
e.
A
p
r
o
ce
s
s
th
e
y
ter
m
ed
m
ir
r
o
r
in
g
s
tag
e
s
o
f
SS
M.
An
o
th
er
i
m
p
o
r
tan
t
co
n
tr
ib
u
tio
n
m
ad
e
b
y
S
S
M
is
t
h
at
u
n
li
k
e
o
t
h
er
m
eth
o
d
o
lo
g
ies,
it
d
o
es
n
o
t
la
y
e
m
p
h
a
s
is
o
n
o
n
l
y
t
h
e
tec
h
n
ical
i
s
s
u
es b
u
t r
at
h
er
en
h
a
n
ce
s
th
e
p
r
o
b
lem
s
it
u
atio
n
b
y
g
i
v
i
n
g
p
r
ec
ed
en
ce
also
to
th
e
cu
lt
u
r
al
an
d
s
o
cial
p
er
s
p
ec
tiv
es,
an
d
d
er
iv
es
t
h
e
f
in
a
l
s
o
lu
tio
n
b
ased
o
n
th
e
r
eq
u
ir
e
m
en
ts
o
f
t
h
e
u
s
er
[
6
9
]
.
T
h
e
r
o
le
o
f
u
s
er
s
in
k
n
o
w
led
g
e
elicitatio
n
an
d
KB
Ss
ca
n
n
o
t
b
e
d
o
w
n
p
la
y
ed
as
th
e
y
f
o
r
m
a
n
i
m
p
o
r
ta
n
t
g
r
o
u
p
o
f
s
ta
k
e
h
o
ld
er
s
t
h
at
s
u
p
p
ly
u
s
er
r
eq
u
ir
e
m
en
t k
n
o
w
led
g
e
[
7
7
-
7
9
]
.
5.
CO
NCLU
SI
O
N
Du
r
in
g
t
h
e
la
s
t
t
h
r
ee
d
ec
ad
es,
s
ev
er
al
s
tu
d
ie
s
h
av
e
b
ee
n
d
ev
o
ted
to
s
ee
k
i
n
g
b
etter
a
n
d
m
o
r
e
ef
f
icie
n
t
w
a
y
s
o
f
d
e
v
elo
p
in
g
KB
Ss
.
F
r
o
m
t
h
e
ea
r
l
y
d
a
y
s
o
f
A
I
an
d
ex
p
er
t
s
y
s
te
m
s
,
to
th
e
m
o
r
e
r
ec
en
t
KE
,
s
ev
er
al
m
et
h
o
d
o
lo
g
ical
ap
p
r
o
ac
h
es
h
av
e
b
ee
n
d
e
v
elo
p
ed
an
d
te
s
ted
o
n
h
o
w
b
est
to
elic
it
an
d
tr
an
s
f
er
ex
p
er
t
k
n
o
w
led
g
e
f
o
r
th
e
co
n
s
tr
u
cti
o
n
o
f
KB
Ss
.
W
it
h
th
e
p
r
o
lif
e
r
atio
n
o
f
in
f
o
r
m
a
tio
n
d
u
e
to
th
e
d
ail
y
ad
v
an
ce
s
b
ein
g
r
ec
o
r
d
ed
in
I
n
ter
n
e
t
an
d
w
eb
tec
h
n
o
lo
g
ies,
t
h
e
tr
ad
itio
n
al
co
n
ce
p
t
o
f
“k
n
o
w
led
g
e
r
o
l
e”
m
eta
m
o
r
p
h
o
s
ed
f
r
o
m
s
tatic
(
s
y
m
b
o
lic
le
v
el)
to
a
m
o
r
e
d
y
n
a
m
ic
(
k
n
o
w
l
ed
g
e
lev
el)
,
t
h
er
eb
y
r
eq
u
ir
in
g
n
e
w
m
et
h
o
d
s
o
f
k
n
o
w
led
g
e
elicitatio
n
a
n
d
r
ep
r
esen
tatio
n
tech
n
iq
u
e
s
.
T
h
e
in
tr
o
d
u
ctio
n
o
f
o
n
to
lo
g
y
i
n
th
e
KE
f
ield
atte
m
p
ted
to
ad
d
r
ess
th
is
ch
a
llen
g
e
at
t
h
e
k
n
o
w
led
g
e
le
v
el
b
u
t
w
a
s
i
n
ad
eq
u
ate
an
d
i
n
ef
f
icie
n
t
f
o
r
th
e
co
n
s
tr
u
ctio
n
o
f
KB
Ss
i
n
an
u
n
ce
r
tai
n
an
d
d
is
t
r
ib
u
ted
n
et
w
o
r
k
ed
e
n
v
ir
o
n
m
e
n
t.
A
lt
h
o
u
g
h
s
t
ill
e
v
o
lv
i
n
g
,
S
SM
ca
n
ar
g
u
ab
l
y
b
e
s
aid
to
b
e
t
h
e
m
o
s
t
ap
p
r
o
p
r
ia
te
m
e
th
o
d
f
o
r
co
n
s
tr
u
cti
n
g
K
B
Ss
t
h
r
o
u
g
h
a
k
n
o
w
led
g
e
e
n
g
in
ee
r
i
n
g
d
o
m
ai
n
-
s
p
ec
if
ic
p
r
o
b
le
m
-
s
o
lv
in
g
ap
p
r
o
ac
h
.
SS
M
h
a
s
b
ee
n
d
escr
ib
ed
in
s
ev
er
al
w
a
y
s
b
y
d
i
f
f
er
en
t
s
tu
d
ies.
A
lt
h
o
u
g
h
g
en
er
all
y
r
e
g
ar
d
ed
as
a
lear
n
i
n
g
s
y
s
te
m
,
it
s
w
id
e
ap
p
licab
il
it
y
a
n
d
ac
c
ep
tab
ilit
y
h
a
s
lar
g
e
l
y
b
ee
n
cr
ed
ited
to
its
ab
ilit
y
to
ad
d
r
ess
s
o
f
t
u
n
s
tr
u
ctu
r
ed
p
r
o
b
lem
s
itu
a
tio
n
s
in
en
v
ir
o
n
m
e
n
ts
c
h
ar
ac
ter
ized
b
y
h
ig
h
le
v
els
o
f
u
n
ce
r
tai
n
t
y
a
n
d
co
m
p
le
x
itie
s
,
w
h
ic
h
i
s
a
co
m
m
o
n
p
h
en
o
m
en
o
n
i
n
m
o
s
t
h
u
m
a
n
ac
ti
v
it
y
s
y
s
te
m
s
.
S
SM
i
s
a
v
er
y
f
le
x
ib
le
m
et
h
o
d
o
lo
g
y
,
wh
ich
ca
n
b
e
ad
ap
ted
to
s
u
it
th
e
n
at
u
r
e
an
d
co
n
tex
t
o
f
th
e
p
r
o
b
lem
b
ein
g
s
o
l
v
ed
eith
er
b
y
s
tr
u
ct
u
r
in
g
a
n
u
n
s
tr
u
ctu
r
ed
p
r
o
b
lem
o
r
s
i
m
p
l
y
b
y
r
ea
ch
in
g
a
co
n
s
en
s
u
s
a
m
o
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g
m
aj
o
r
s
tak
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o
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s
.
T
h
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p
ap
er
th
er
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o
r
e
p
r
o
p
o
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es
SS
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as
a
v
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m
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th
o
d
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tr
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v
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m
e
n
t
s
.
RE
F
E
R
E
NC
E
S
[1
]
F
e
ig
e
n
b
a
u
m
,
E.
,
“
Kn
o
w
led
g
e
En
g
in
e
e
rin
g
:
T
h
e
A
p
p
li
e
d
S
i
d
e
o
f
A
rti
f
icia
l
In
telli
g
e
n
c
e
”
,
S
TA
N
-
CS
-
80
-
8
1
2
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter S
c
ien
c
e
,
S
tan
f
o
rd
U
n
iv
e
rsity
,
1
9
8
0
.
[2
]
Ha
w
k
in
s,
D.
,
“
A
n
A
n
a
l
y
sis o
f
Ex
p
e
rt
T
h
in
k
in
g
”,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
n
-
M
a
c
h
i
n
e
S
t
u
d
ies
,
1
8
(
1
):
1
-
4
7
,
1
9
8
3
.
[3
]
No
rm
a
n
,
D.
,
“
Tw
e
l
v
e
Iss
u
e
s
f
o
r
Co
g
n
it
iv
e
S
c
ien
c
e
”
,
Co
g
n
it
ive
S
c
i
e
n
c
e
,
4
(1
):
1
-
3
2
,
1
9
8
0
.
[4
]
Ha
y
e
s
-
Ro
th
,
F
.
,
W
a
ter
m
a
n
,
D.A.,
L
e
n
a
t,
D.B.
,
“
Bu
il
d
in
g
Ex
p
e
rt
S
y
st
e
m
s
”
,
Re
a
d
in
g
,
M
a
ss
a
c
h
u
se
tt
s,
A
d
d
iso
n
-
W
e
sle
y
.
1
9
8
3
.
[5
]
W
ielin
g
a
,
B.
J.
,
“
Re
f
l
e
c
ti
o
n
s
o
n
2
5
+
Ye
a
rs
o
f
Kn
o
w
led
g
e
Ac
q
u
isit
io
”
,
In
t.
J
.
Hu
m.
-
Co
mp
u
t.
S
tu
d
.
7
1
.
(2
):
2
1
1
-
2
1
5
,
2
0
1
3
.
[6
]
Ne
w
e
ll
,
A
.
,
“
T
h
e
Kn
o
w
led
g
e
L
e
v
e
l”
Arti
fi
c
ia
l
I
n
telli
g
e
n
c
e
,
1
8
:8
7
–
1
2
7
,
1
9
8
2
.
[7
]
M
o
u
ra
o
,
K.,
a
n
d
P
e
tri
c
k
R.
P
.
,
“
L
e
a
rn
in
g
Kn
o
w
led
g
e
-
L
e
v
e
l
Do
m
a
in
Dy
n
a
m
i
c
s
”,
P
lan
n
in
g
a
n
d
L
e
a
rn
in
g
,
2
3
.
2
0
1
3
.
[8
]
Clan
c
e
y
,
W
.
J.
,
“
T
h
e
Ep
iste
m
o
lo
g
y
o
f
a
Ru
le
Ba
se
d
S
y
ste
m
-
A
F
ra
m
e
w
o
rk
f
o
r
Ex
p
lan
a
t
io
n
”
,
A
rti
f
icia
l
In
telli
g
e
n
c
e
,
2
0
:2
1
5
–
2
5
1
,
1
9
8
3
.
[9
]
Co
m
p
to
n
,
P
.
,
“
S
it
u
a
ted
C
o
g
n
it
io
n
a
n
d
Kn
o
w
led
g
e
A
c
q
u
i
siti
o
n
Re
se
a
rc
h
”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Hu
m
a
n
-
Co
mp
u
ter
S
tu
d
ies
,
7
1
(
2
):
1
8
4
-
1
9
0
,
2
0
1
3
.
[1
0
]
Ra
p
a
n
o
tt
i
,
L
.
,
Zh
a
o
,
L
.
,
Ha
ll
,
J.G
.
,
“
S
p
e
c
ial
S
e
c
ti
o
n
o
n
A
d
v
a
n
c
e
s
a
n
d
A
p
p
l
ica
ti
o
n
s o
f
P
r
o
b
lem
Orie
n
tatio
n
”
,
Ex
p
e
rt
S
y
st
e
m
s
,
3
0
(3
):
1
8
3
-
1
8
4
,
2
0
1
3
.
[1
1
]
Clan
c
e
y
,
W
.
J.
,
“
He
u
risti
c
Clas
si
f
ica
ti
o
n
”
,
Arti
f
icia
l
I
n
telli
g
e
n
c
e
,
2
7
:2
8
9
–
3
5
0
,
1
9
8
5
.
[1
2
]
G
ru
b
e
r,
T
.
R.
A
.
,
“
T
ra
n
sla
ti
o
n
A
p
p
ro
a
c
h
to
P
o
r
tab
le On
t
o
l
o
g
ies
”
,
Kn
o
wled
g
e
Ac
q
u
isit
io
n
,
5
(2
):
1
9
9
–
2
2
0
,
Ju
n
e
1
9
9
3
.
[1
3
]
L
iu
,
Y.,
Z
h
e
n
g
,
X
.
,
T
a
n
g
,
F
.
,
Ch
e
n
,
X
.
,
“
On
t
o
lo
g
y
De
sig
n
w
i
th
a
G
ra
n
u
lar
A
p
p
ro
a
c
h
”
,
Ex
p
e
rt
S
y
ste
m
s
w
it
h
A
p
p
li
c
a
ti
o
n
s
,
4
1
(
1
0
):
4
8
6
7
-
4
8
7
7
.
2
0
1
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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1
,
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p
r
il
20
1
6
:
1
–
10
8
[1
4
]
W
ielin
g
a
,
B.
J.,
J.A
.
Bre
u
k
e
r.
,
“
In
terp
re
tatio
n
o
f
V
e
rb
a
l
Da
ta
f
o
r
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
”
,
I
n
T
.
O‟Sh
e
a
,
e
d
it
o
r
,
A
d
v
a
n
c
e
s
in
A
rti
f
icia
l
In
telli
g
e
n
c
e
,
p
a
g
e
s
4
1
–
5
0
,
Am
ste
rd
a
m
,
Th
e
Ne
th
e
rlan
d
s,
1
9
8
4
.
ECA
I,
El
se
v
ier
S
c
ien
c
e
.
A
lso
a
s: Rep
o
rt
1
.
4
,
ES
P
RIT
P
ro
j
e
c
t
1
2
,
U
n
iv
e
rsity
o
f
Am
ste
rd
a
m
.
[1
5
]
W
e
lb
a
n
k
,
M
.
,
“
A
R
e
v
ie
w
o
f
Kn
o
w
led
g
e
Ac
q
u
isit
io
n
T
e
c
h
n
iq
u
e
s
f
o
r
Ex
p
e
rt
S
y
ste
m
s”
,
Ip
s
w
ich
,
UK
,
M
a
rtl
e
sh
a
m
Co
n
su
l
tan
c
y
S
e
rv
ic
e
s,
BT
R
L
,
1
9
8
3
.
[1
6
]
Ke
ll
y
,
G
.
A
.
,
“
P
e
rso
n
a
l
C
o
n
str
u
c
t
P
sy
c
h
o
lo
g
y
”
,
1
9
5
5
.
[1
7
]
S
h
a
w
,
M
.
L
.
G
.
,
“
On
Be
c
o
m
in
g
a
P
e
rso
n
a
l
S
c
ien
t
ist:
In
tera
c
ti
v
e
Co
m
p
u
ter
El
icitatio
n
o
f
P
e
rso
n
a
l
M
o
d
e
ls
o
f
th
e
W
o
rld
”
,
A
c
a
d
e
m
ic P
re
ss
,
In
c
.
,
1
9
8
0
.
[1
8
]
M
a
n
c
u
so
,
J.C.
,
A
d
a
m
s
-
W
e
b
b
e
r,
J.R.
,
e
d
s.
,
“
T
h
e
Co
n
str
u
in
g
P
e
rso
n
”,
P
ra
e
g
e
r
P
u
b
li
sh
e
rs,
1
9
8
2
.
[1
9
]
S
h
a
w
,
M
.
L
.
G
.
,
G
a
in
e
s,
B.
R.
,
“
Kn
o
w
led
g
e
in
it
iatio
n
a
n
d
tran
sf
e
r
to
o
ls
f
o
r
e
x
p
e
rts
a
n
d
n
o
v
ice
s
”,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
n
-
M
a
c
h
in
e
S
tu
d
ies
,
2
7
(
3
),
2
5
1
-
2
8
0
.
1
9
8
7
.
[2
0
]
S
h
a
w
,
M
il
d
re
d
L
G
,
Bri
a
n
R.
,
G
a
in
e
s.
,
“
KI
TT
EN:
Kn
o
w
l
e
d
g
e
In
it
iatio
n
a
n
d
T
ra
n
sf
e
r
T
o
o
ls
f
o
r
Ex
p
e
rts
a
n
d
No
v
ice
s
”,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
n
-
M
a
c
h
i
n
e
S
t
u
d
ies
,
2
7
(3
):
2
5
1
-
2
8
0
,
1
9
8
7
.
[2
1
]
S
o
w
a
,
J.F
.
,
“
Co
n
c
e
p
tu
a
l
S
tr
u
c
tu
r
e
s:
In
f
o
r
m
a
ti
o
n
P
ro
c
e
ss
in
g
in
M
in
d
a
n
d
M
a
c
h
in
e
”,
A
d
d
iso
n
-
W
e
sle
y
L
o
n
g
m
a
n
P
u
b
l
ish
i
n
g
Co
.
,
In
c
.
,
1
9
8
4
.
[2
2
]
Ba
in
b
ri
d
g
e
,
L.
,
“
V
e
rb
a
l
Re
p
o
rts
a
s
Ev
id
e
n
c
e
o
f
th
e
P
ro
c
e
ss
Op
e
ra
to
r‟s
Kn
o
w
led
g
e
”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
M
a
n
-
M
a
c
h
in
e
S
t
u
d
ies
,
1
1
(4
)
4
1
1
-
4
3
6
,
1
9
7
9
.
[2
3
]
Co
h
e
n
,
L
.
,
M
a
n
i
o
n
,
L
.
,
M
o
rriso
n
,
K.
,
“
Re
se
a
rc
h
M
e
th
o
d
s in
Ed
u
c
a
ti
o
n
”,
R
o
u
t
led
g
e
,
2
0
1
1
.
[2
4
]
Cre
s
w
e
ll
,
J.W
.
,
“
Re
se
a
rc
h
De
sig
n
:
Qu
a
l
it
a
ti
v
e
,
Qu
a
n
t
it
a
ti
v
e
,
a
n
d
M
ix
e
d
M
e
th
o
d
s
A
p
p
ro
a
c
h
e
s
”,
S
a
g
e
P
u
b
li
c
a
ti
o
n
s,
In
c
o
rp
o
ra
ted
,
2
0
1
3
.
[2
5
]
Dia
p
e
r,
D.
,
“
Kn
o
w
led
g
e
El
icitatio
n
:
P
ri
n
c
ip
le,
T
e
c
h
n
iq
u
e
s
a
n
d
A
p
p
li
c
a
ti
o
n
s
”
S
p
ri
n
g
e
r
-
V
e
rlag
Ne
w
Yo
rk
,
In
c
.
,
1
9
8
9
.
[2
6
]
W
a
n
g
,
H.,
G
a
il
li
o
t
A
.
,
H
y
d
e
n
D.
,
“
A
Kn
o
w
le
d
g
e
El
icitatio
n
S
t
u
d
y
f
o
r
Co
ll
a
b
o
ra
ti
v
e
Dia
lo
g
u
e
S
tr
a
teg
ies
u
se
d
to
Ha
n
d
le
Un
c
e
rtain
ti
e
s
i
n
S
p
e
e
c
h
Co
m
m
u
n
ica
ti
o
n
w
h
il
e
Us
in
g
G
IS
.
Hu
m
a
n
-
Co
m
p
u
ter
In
tera
c
ti
o
n
”,
I
n
tera
c
ti
o
n
M
o
d
a
li
t
ies
a
n
d
T
e
c
h
n
i
q
u
e
s
,
S
p
ri
n
g
e
r
Be
rli
n
He
id
e
lb
e
rg
:
1
3
5
-
1
4
4
,
2
0
1
3
.
[2
7
]
M
c
A
n
d
re
w
,
C.
,
G
o
re
,
J.
,
“
Un
d
e
rsta
n
d
in
g
P
re
f
e
re
n
c
e
s
in
Ex
p
e
rien
c
e
-
Ba
se
d
Ch
o
i
c
e
A
S
tu
d
y
o
f
C
o
g
n
it
io
n
i
n
t
h
e
W
il
d
”,
J
o
u
rn
a
l
o
f
C
o
g
n
it
ive
En
g
i
n
e
e
rin
g
a
n
d
De
c
isio
n
M
a
k
in
g
,
7
(
2
):
1
7
9
-
1
9
7
,
2
0
1
3
.
[2
8
]
Ch
irav
u
ri,
A
.
,
Na
z
a
re
th
,
D.,
Ra
m
a
m
u
rth
y
,
K.
,
“
Co
g
n
it
iv
e
Co
n
f
l
ict
a
n
d
Co
n
se
n
su
s
G
e
n
e
ra
ti
o
n
in
V
irt
u
a
l
T
e
a
m
s
d
u
ri
n
g
Kn
o
w
led
g
e
C
a
p
tu
re
:
Co
m
p
a
ra
ti
v
e
E
ff
e
c
ti
v
e
n
e
ss
o
f
Tec
h
n
i
q
u
e
s
”,
J
o
u
rn
a
l
o
f
M
a
n
a
g
e
me
n
t
In
fo
rm
a
ti
o
n
S
y
ste
ms
,
2
8
(
1
):
3
1
1
-
3
5
0
,
2
0
1
1
.
[2
9
]
Je
tt
e
r,
A
.
J.,
Ko
k
,
K.
,
“
F
u
z
z
y
Co
g
n
it
iv
e
M
a
p
s
f
o
r
F
u
t
u
re
s
S
tu
d
ies
-
A
M
e
th
o
d
o
lo
g
ica
l
A
ss
e
s
s
m
e
n
t
o
f
Co
n
c
e
p
ts
a
n
d
M
e
th
o
d
s”
,
Fu
tu
re
s,
2
0
1
4
.
[3
0
]
Clark
,
M
.
,
Kim
,
Y.,
Kru
sc
h
w
it
z
,
U.,
S
o
n
g
,
D.,
A
lb
a
k
o
u
r,
D.,
Dig
n
u
m
,
S
.
,
De
Ro
e
c
k
,
A
.
,
“
A
u
to
m
a
ti
c
a
ll
y
S
tru
c
tu
rin
g
Do
m
a
in
Kn
o
w
led
g
e
f
ro
m
Tex
t:
A
n
Ov
e
r
v
ie
w
o
f
Cu
rr
e
n
t
Re
se
a
rc
h
”,
In
f
o
rm
a
ti
o
n
P
r
o
c
e
ss
in
g
a
n
d
M
a
n
a
g
e
m
e
n
t,
4
8
(3
)
:
5
5
2
-
5
6
8
,
2
0
1
2
.
[3
1
]
S
tarr,
R.
R.
,
P
a
re
n
te
d
e
Ol
iv
e
ira,
J.M
.
,
“
C
o
n
c
e
p
t
M
a
p
s
a
s
t
h
e
F
irst
S
tep
i
n
a
n
O
n
to
lo
g
y
Co
n
str
u
c
ti
o
n
M
e
th
o
d
”
,
In
f
o
rm
a
ti
o
n
S
y
ste
m
s
,
3
8
(5
):
7
7
1
-
7
8
3
,
2
0
1
3
.
[3
2
]
d
e
l
Á
g
u
il
a
,
I.
M
.
,
P
a
lm
a
,
J.,
T
ú
n
e
z
,
S
.
,
“
M
il
e
st
o
n
e
s in
S
o
f
tw
a
r
e
En
g
in
e
e
rin
g
a
n
d
Kn
o
w
le
d
g
e
En
g
in
e
e
rin
g
Histo
ry
:
A
Co
m
p
a
ra
ti
v
e
Re
v
ie
w
”,
T
h
e
S
c
ien
t
if
ic W
o
rld
J
o
u
rn
a
l
,
2
0
1
4
.
[3
3
]
S
c
h
re
ib
e
r,
G
.
,
“
Kn
o
w
led
g
e
En
g
in
e
e
rin
g
a
n
d
M
a
n
a
g
e
m
e
n
t:
T
h
e
Co
m
m
o
n
K
A
DS
M
e
th
o
d
o
lo
g
y
”,
M
IT
p
re
ss
,
2
0
0
0
.
[3
4
]
Co
c
k
b
u
rn
,
A
.
,
“
S
e
l
e
c
ti
n
g
a
P
r
o
jec
t
‟s M
e
th
o
d
o
lo
g
y
”
,
IEE
E
S
o
f
twa
r
e
,
1
7
(
4
),
2
0
0
0
.
[3
5
]
P
u
e
rta,
A
.
R.
,
Eg
a
r,
J.W
.
,
T
u
,
S
.
W
.
,
M
u
se
n
,
M
.
A
.
,
“
A
M
u
lt
ip
le
-
M
e
th
o
d
S
h
e
ll
f
o
r
th
e
A
u
to
m
a
ti
c
G
e
n
e
ra
ti
o
n
o
f
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
T
o
o
ls”
,
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
,
4
:1
7
1
–
1
9
6
,
1
9
9
2
.
[3
6
]
F
a
to
n
a
d
e
,
O.
V.
,
“
T
h
e
A
p
p
li
c
a
ti
o
n
o
f
Kn
o
w
led
g
e
Ba
se
d
S
y
ste
m
s
t
o
th
e
A
b
stra
c
ti
o
n
o
f
De
sig
n
a
n
d
Co
stin
g
Ru
les
i
n
Be
sp
o
k
e
P
i
p
e
Jo
i
n
ti
n
g
S
y
ste
m
s
”
,
2
0
1
2
.
[3
7
]
M
c
De
r
m
o
tt
,
J.
,
“
P
re
li
m
in
a
r
y
S
tep
s
T
o
w
a
rd
s
a
T
a
x
o
n
o
m
y
o
f
P
r
o
b
lem
-
so
lv
in
g
M
e
th
o
d
s”
,
I
n
S
.
M
a
rc
u
s,
e
d
it
o
r
,
A
u
to
m
a
ti
n
g
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
f
o
r
Ex
p
e
rt
S
y
ste
m
s
,
p
a
g
e
s 2
2
5
–
2
5
5
.
Kl
u
w
e
r,
B
o
sto
n
,
1
9
8
8
.
[3
8
]
M
o
tt
a
,
E.
,
“
2
5
Ye
a
rs
o
f
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
”,
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
H
u
ma
n
-
C
o
mp
u
ter
S
t
u
d
ies
,
7
1
(
2
):
1
3
1
-
1
3
4
,
2
0
1
3
.
[3
9
]
W
ielin
g
a
,
B.
J.,
S
c
h
re
ib
e
r,
A
.
T
.
,
Bre
u
k
e
r,
J.
A
.
,
“
K
A
D
S
:
A
m
o
d
e
ll
in
g
a
p
p
ro
a
c
h
to
k
n
o
w
led
g
e
e
n
g
in
e
e
rin
g
”,
Kn
o
w
led
g
e
A
c
q
u
isit
io
n
,
4
(
1
):
5
-
5
3
,
1
9
9
2
.
[4
0
]
S
tee
ls,
L
.
,
“
Co
m
p
o
n
e
n
ts
o
f
Ex
p
e
rti
se
”
,
A
I
M
a
g
a
z
in
e
,
S
u
m
m
e
r,
1
9
9
0
.
[4
1
]
V
o
sk
o
g
lo
u
,
M
.
G
.
,
S
a
lem
,
A
.
B.
M
.
,
“
A
n
a
lo
g
y
-
Ba
s
e
d
a
n
d
Ca
se
-
Ba
se
d
Re
a
so
n
in
g
:
Tw
o
sid
e
s
o
f
th
e
S
a
m
e
Co
in
”,
a
r
X
iv
p
re
p
rin
t
a
rX
iv
:1
4
0
5
.
7
5
6
7
,
2
0
1
4
.
[4
2
]
S
é
g
u
in
,
N.,
T
re
m
b
la
y
,
G
.
,
Ba
g
a
n
e
,
H.
,
“
A
g
il
e
P
rin
c
i
p
les
a
s
S
o
f
t
wa
re
En
g
in
e
e
rin
g
P
rin
c
i
p
les
:
A
n
An
a
ly
sis
”
,
Ag
il
e
P
r
o
c
e
ss
e
s in
S
o
f
tw
a
re
En
g
in
e
e
rin
g
a
n
d
Ex
trem
e
P
ro
g
ra
m
m
in
g
,
S
p
r
in
g
e
r
Be
rli
n
He
id
e
lb
e
rg
,
1
-
1
5
,
2
0
1
2
.
[4
3
]
Din
g
sø
y
r,
T
.
,
Ne
ru
r,
S
.
,
Ba
li
jep
a
ll
y
,
V
.
,
M
o
e
,
N.B.
,
“
A
D
e
c
a
d
e
o
f
Ag
il
e
M
e
t
h
o
d
o
l
o
g
ies
:
T
o
wa
rd
s
Ex
p
lai
n
in
g
A
g
il
e
S
o
f
tw
a
r
e
De
v
e
lo
p
m
e
n
t”,
J
o
u
rn
a
l
o
f
S
y
ste
ms
a
n
d
S
o
ft
wa
re
,
8
5
(
6
):
1
2
1
3
-
1
2
2
1
,
2
0
1
2
.
[4
4
]
P
i
n
t
o
,
H.S
.
,
S
taa
b
,
S
.
,
T
e
m
p
ic
h
,
C.
,
“
DIL
IG
EN
T
:
T
o
w
a
rd
s
a
F
in
e
-
g
ra
in
e
d
M
e
th
o
d
o
l
o
g
y
fo
r
Distrib
u
ted
,
L
o
o
se
l
y
c
o
n
tro
ll
e
d
a
n
d
Ev
o
lv
in
g
En
g
in
e
e
r
in
g
o
f
On
to
lo
g
ies
”,
In
E
CAI
,
p
a
g
e
s 3
9
3
–
3
9
7
,
2
0
0
4
.
[4
5
]
De
b
ru
y
n
e
,
Ch
risto
p
h
e
,
P
iete
r
D
e
L
e
e
n
h
e
e
r,
“
Us
in
g
a
M
e
th
o
d
a
n
d
T
o
o
l
f
o
r
Hy
b
rid
On
t
o
l
o
g
y
E
n
g
in
e
e
rin
g
:
A
n
Ev
a
lu
a
ti
o
n
i
n
t
h
e
F
lem
ish
Re
se
a
r
c
h
In
f
o
rm
a
ti
o
n
S
p
a
c
e
”
,
J
o
u
r
n
a
l
o
f
T
h
e
o
re
ti
c
a
l
a
n
d
Ap
p
li
e
d
El
e
c
tro
n
ic
Co
mm
e
rc
e
Res
e
a
rc
h
,
9
(2
)
:
4
8
-
6
3
,
2
0
1
4
.
[4
6
]
A
u
th
o
r
e
t
a
l.
,
2
0
1
3
)
Evaluation Warning : The document was created with Spire.PDF for Python.
IJ
-
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N:
2252
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o
d
o
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F
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klyn
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kwu
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)
9
[4
7
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Jo
s
e
p
h
,
M
,
Ku
p
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r,
G
.
,
S
e
ra
f
in
i,
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,
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Qu
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Ex
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:1
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[4
8
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a
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,
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h
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m
e
n
sio
n
s
o
f
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URI:
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:
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p
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[4
9
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Ho
w
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ll
,
D.,
W
in
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a
h
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C.
,
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e
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e
l,
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it
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In
ter
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a
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o
jec
t
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a
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me
n
t
,
2
8
(
3
):
2
5
6
-
2
6
4
,
2
0
1
0
.
[5
0
]
Da
v
is,
R.
,
S
h
r
o
b
e
,
H.
,
S
z
o
l
o
v
it
s,
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.
,
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W
h
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t
is
a
Kn
o
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led
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e
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tatio
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a
g
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z
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e
,
S
p
ri
n
g
:
1
7
–
3
3
,
1
9
9
3
.
[5
1
]
d
e
Ca
r
v
a
lh
o
,
V
.
A
.
,
A
l
m
e
id
a
,
J.P
.
A
.
,
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u
izz
a
rd
i,
G
.
,
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Us
in
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e
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in
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”,
Ad
v
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d
In
fo
rm
a
ti
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En
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In
tern
a
ti
o
n
a
l
P
u
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l
ish
i
n
g
,
2
0
1
4
.
[5
2
]
Du
o
n
g
,
T
.
H.,
Ng
u
y
e
n
,
N.T
.
,
N
g
u
y
e
n
,
D.C.
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A
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d
in
g
”
,
Cy
b
e
rn
e
ti
c
s a
n
d
S
y
ste
ms
,
4
5
(2
)
:
1
4
6
-
1
6
4
,
2
0
1
4
.
[5
3
]
Bra
c
h
m
a
n
,
R.
J.
,
S
c
h
m
o
lze
,
J.G
.
,
“
A
n
Ov
e
r
v
ie
w
o
f
th
e
KL
-
ON
E
Kn
o
w
led
g
e
Re
p
re
s
e
n
tatio
n
S
y
ste
m
”
,
Co
g
n
it
iv
e
S
c
ien
c
e
,
9
:1
7
1
–
2
1
6
,
1
9
8
5
.
[5
4
]
R
y
b
a
k
o
v
,
V
.
,
“
M
u
lt
i
-
a
g
e
n
t
No
n
-
l
in
e
a
r
T
e
m
p
o
ra
l
L
o
g
ic
w
it
h
E
m
b
o
d
i
e
d
A
g
e
n
t
De
sc
rib
in
g
Un
c
e
rtain
ty
”
,
Ag
e
n
t
a
n
d
M
u
lt
i
-
Ag
e
n
t
S
y
ste
ms
:
T
e
c
h
n
o
lo
g
i
e
s a
n
d
Ap
p
li
c
a
t
io
n
s
,
S
p
rin
g
e
r
In
te
rn
a
ti
o
n
a
l
P
u
b
li
s
h
in
g
,
8
7
-
9
6
,
2
0
1
4
.
[5
5
]
T
a
n
w
a
r,
P
.
,
P
ra
sa
d
,
T
.
V
.
,
Da
tt
a
,
K.
,
“
A
n
E
ff
e
c
ti
v
e
Re
a
so
n
in
g
A
lg
o
rit
h
m
f
o
r
Qu
e
stio
n
A
n
sw
e
rin
g
S
y
st
e
m
”,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Ad
v
a
n
c
e
d
Co
mp
u
ter
S
c
ien
c
e
a
n
d
A
p
p
li
c
a
ti
o
n
s,
S
p
e
c
ia
l
Iss
u
e
o
n
Na
t
u
ra
l
L
a
n
g
u
a
g
e
Pr
o
c
e
ss
in
g
.
5
2
-
5
7
,
2
0
1
4
.
[5
6
]
T
e
k
li
,
J.,
Rjeily
,
A
.
A
.
,
Ch
b
e
ir,
R.
,
T
e
k
li
,
G
.
,
Ho
u
n
g
u
e
,
P
.
,
Ye
to
n
g
n
o
n
,
K.,
A
b
e
b
e
,
M
.
A
.
,
“
S
e
ma
n
ti
c
to
In
telli
g
e
n
t
W
e
b
Era
:
Bu
il
d
in
g
Bl
o
c
k
s,
A
p
p
li
c
a
ti
o
n
s,
a
n
d
Cu
rr
e
n
t
T
re
n
d
s
”,
P
r
o
c
e
e
d
in
g
s
o
f
th
e
F
if
th
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
M
a
n
a
g
e
m
e
n
t
o
f
Eme
rg
e
n
t
Dig
it
a
l
Eco
S
y
ste
m
,
ACM
,
2
0
1
3
.
[5
7
]
F
re
it
a
s,
H.,
Cu
ry
,
D
.,
d
e
M
e
n
e
z
e
s,
C.
S
.
,
“
F
ro
m
On
to
lo
g
ies
to
Q
u
e
stio
n
-
A
n
sw
e
r
P
a
irs
-
A
T
e
m
p
lat
e
Lan
g
u
a
g
e
f
o
r
A
u
to
m
a
ted
a
n
d
Cu
st
o
m
iza
b
le
Tran
sf
o
r
m
a
ti
o
n
s
”,
Ne
w
P
e
rsp
e
c
ti
v
e
s
in
In
f
o
rm
a
ti
o
n
S
y
ste
m
s
a
n
d
T
e
c
h
n
o
lo
g
ies
,
V
o
l
u
m
e
1
.
S
p
r
in
g
e
r
In
tern
a
ti
o
n
a
l
P
u
b
l
ish
i
n
g
,
6
1
-
7
0
,
2
0
1
4
.
[5
8
]
G
in
sb
e
rg
,
M
.
L
.
,
“
Kn
o
w
led
g
e
In
ter
c
h
a
n
g
e
F
o
rm
a
t:
T
h
e
KIF
o
f
De
a
th
”
,
AI
m
a
g
a
zin
e
,
1
2
(
3
3
)
:5
7
–
6
3
,
1
9
9
1
.
[5
9
]
S
a
li
n
a
s,
S
.
O.
,
G
e
lb
u
k
h
,
A
.
,
“
Re
p
r
e
se
n
tac
ió
n
Co
m
p
u
tac
io
n
a
l
De
l
L
e
n
g
u
a
je Na
tu
ra
l
Esc
rit
o
”
,
I
n
g
e
n
ier
ía
1
5
(1
)
,
2
0
1
0
.
[6
0
]
S
a
li
n
a
s,
S
.
O.
,
“
T
ra
n
sf
o
r
m
a
c
ió
n
A
u
to
m
á
ti
c
a
De
T
e
x
to
A
G
r
a
f
o
s
Co
n
c
e
p
tu
a
les
”
,
Diss
.
Un
iv
e
rsid
a
d
Na
c
io
n
a
l
d
e
Co
lo
m
b
ia,
2
0
1
1
.
[6
1
]
L
e
y
b
o
u
rn
e
,
S
.
A
.
a
n
d
S
a
in
ter,
P
.
A
d
v
a
n
c
in
g
P
ro
jec
t
M
a
n
a
g
e
m
e
n
t:
A
u
th
e
n
ti
c
a
ti
n
g
th
e
S
h
if
t
F
r
o
m
P
ro
c
e
ss
to
“
Nu
a
n
c
e
d
”
P
ro
jec
t
Ba
se
d
M
a
n
a
g
e
m
e
n
t
in
th
e
Am
b
id
e
x
tro
u
s
Org
a
n
iza
ti
o
n
.
Pro
jec
t
M
a
n
a
g
e
me
n
t
J
o
u
rn
a
l
,
4
3
(
6
):
5
-
1
5
,
2
0
1
2
.
[6
2
]
Ku
o
,
Y.K.,
K
u
o
,
T
.
H.
a
n
d
Ho
,
L
.
A
.
En
a
b
li
n
g
In
n
o
v
a
ti
v
e
A
b
il
it
y
:
Kn
o
w
led
g
e
S
h
a
rin
g
a
s
a
M
e
d
iato
r.
I
n
d
u
stria
l
M
a
n
a
g
e
me
n
t
a
n
d
D
a
ta
S
y
ste
ms
,
1
1
4
(
5
):
6
9
6
-
7
1
0
,
2
0
1
4
.
[6
3
]
Ch
a
e
,
H.C.
,
Ko
h
,
C.
E.
a
n
d
P
ry
b
u
to
k
,
V
.
R.
,
“
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
Ca
p
a
b
il
it
y
A
n
d
F
irm
P
e
rf
o
rm
a
n
c
e
:
Co
n
trad
icto
ry
F
in
d
i
n
g
s an
d
T
h
e
ir
P
o
ss
ib
le Ca
u
se
s”
,
M
IS
Qu
a
rte
rly
,
3
8
(1
),
2
0
1
4
.
[6
4
]
Niss
e
n
,
H.A
.
,
Ev
a
ld
,
M
.
R.
,
Clark
e
,
A
.
H.
,
“
Kn
o
w
led
g
e
S
h
a
rin
g
in
He
tero
g
e
n
e
o
u
s
T
e
a
m
s
th
ro
u
g
h
C
o
ll
a
b
o
ra
ti
o
n
a
n
d
Co
o
p
e
ra
ti
o
n
:
Ex
e
m
p
li
f
i
e
d
th
ro
u
g
h
P
u
b
li
c
–
P
r
iv
a
te
-
In
n
o
v
a
ti
o
n
P
a
rtn
e
rsh
ip
s
”
,
I
n
d
u
strial
M
a
rk
e
ti
n
g
M
a
n
a
g
e
m
e
n
t
,
2
0
1
4
.
[6
5
]
Du
rm
u
so
g
lu
,
S
.
,
Ja
c
o
b
s,
M
.
,
Na
y
ir,
D.
Z.
,
Kh
il
ji
,
S
.
,
W
a
n
g
,
X
.
,
“
T
h
e
Qu
a
si
-
m
o
d
e
ra
ti
n
g
Ro
le
o
f
Org
a
n
iza
ti
o
n
a
l
Cu
lt
u
re
in
t
h
e
Re
latio
n
s
h
ip
b
e
t
w
e
e
n
Re
w
a
rd
s
a
n
d
Kn
o
w
led
g
e
S
h
a
re
d
a
n
d
G
a
in
e
d
”
,
J
o
u
rn
a
l
o
f
Kn
o
w
led
g
e
M
a
n
a
g
e
me
n
t
,
1
8
(1
)
:
2
-
2
,
2
0
1
4
.
[6
6
]
P
a
rk
,
J.G
.
,
L
e
e
,
J.
,
“
Kn
o
w
led
g
e
S
h
a
rin
g
in
In
f
o
rm
a
ti
o
n
S
y
ste
m
s
De
v
e
lo
p
m
e
n
t
P
r
o
jec
ts:
Ex
p
li
c
a
ti
n
g
t
h
e
Ro
le
o
f
De
p
e
n
d
e
n
c
e
a
n
d
T
ru
st”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Pro
jec
t
M
a
n
a
g
e
me
n
t
,
3
2
(1
)
:
1
5
3
-
1
6
5
,
2
0
1
4
.
[6
7
]
Big
g
a
m
,
J.
,
“
Exp
lo
it
i
n
g
S
o
ft
S
y
ste
ms
M
e
th
o
d
o
l
o
g
y
(
S
S
M
)
a
n
d
K
n
o
wled
g
e
T
y
p
e
s
to
F
a
c
il
it
a
te
Kn
o
wled
g
e
Ca
p
t
u
re
Iss
u
e
s
in
a
W
e
b
S
it
e
En
v
i
ro
n
me
n
t.
S
y
ste
m
S
c
ien
c
e
s,
HICS
S
”,
P
r
o
c
e
e
d
in
g
s
o
f
th
e
3
5
th
A
n
n
u
a
l
Ha
wa
ii
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
.
IEE
E
,
2
0
0
2
.
[6
8
]
He
r
m
a
n
,
H.,
Ra
h
m
a
n
,
A
.
A
.
,
S
y
a
h
b
a
n
a
,
Y.A
.
,
“
A
C
a
se
o
f
S
o
ft
S
y
ste
m
M
e
th
o
d
o
lo
g
y
(
S
S
M
):
In
t
e
ra
c
ti
n
g
Asp
e
c
t
M
o
d
e
ll
in
g
o
f
C
u
sto
me
r
S
a
t
isfa
c
ti
o
n
i
n
Vi
d
e
o
S
tre
a
m
S
e
rv
ice
o
v
e
r
W
ir
e
les
s
a
n
d
M
o
b
il
e
Ne
two
rk
”,
Co
m
p
u
ter
M
o
d
e
li
n
g
a
n
d
S
im
u
latio
n
(EM
S
)
,
F
if
th
UK
S
im
Eu
ro
p
e
a
n
S
y
m
p
o
siu
m
o
n
IEE
E
,
2
0
1
1
.
[6
9
]
Ch
e
c
k
lan
d
,
P
.
B.
,
“
S
y
ste
m
s
T
h
in
k
in
g
:
S
y
ste
m
s P
ra
c
ti
c
e
”,
W
il
e
y
,
Ch
ich
e
ste
r,
1
9
8
1
.
[7
0
]
S
o
ti
r
o
p
o
u
l
o
s,
M
.
T
.
,
“
T
h
e
M
a
th
e
m
a
ti
c
s
o
f
th
e
Co
g
n
it
io
n
a
n
d
o
f
th
e
Bra
in
”,
In
tern
a
ti
o
n
a
l
M
a
th
e
m
a
ti
c
a
l
F
o
ru
m
,
9
(8
),
2
0
1
4
.
[7
1
]
Ch
e
c
k
lan
d
,
P
.
B.
,
S
c
h
o
les
,
J
.
,
“
S
o
f
t
S
y
ste
m
s M
e
th
o
d
o
lo
g
y
in
A
c
ti
o
n
”
,
W
il
e
y
,
Ch
ich
e
ste
r,
1
9
9
1
.
[7
2
]
A
sh
w
o
rth
,
C.
,
G
o
o
d
lan
d
,
M
.
,
“
S
S
ADM
A
Pra
c
ti
c
a
l
Ap
p
ro
a
c
h
”
,
M
c
G
r
a
w
-
Hill
In
tern
a
ti
o
n
a
l
S
e
ri
e
s
in
S
o
f
t
w
a
re
En
g
in
e
e
rin
g
,
L
o
n
d
o
n
,
1
9
9
0
.
[7
3
]
Zaie
d
,
A
.
NH
.
,
A
a
l,
S
.
I.
A
.
,
Ha
ss
a
n
,
M
.
M
.
,
“
Ru
le
-
b
a
se
d
Ex
p
e
rt
S
y
ste
m
s
f
o
r
S
e
lec
ti
n
g
In
f
o
r
m
a
ti
o
n
S
y
ste
m
s
De
v
e
lo
p
m
e
n
t
M
e
th
o
d
o
lo
g
ies
”,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
In
tell
ig
e
n
t
S
y
ste
ms
a
n
d
Ap
p
li
c
a
t
io
n
s
,
5
(
9
),
2
0
1
3
.
[7
4
]
Big
g
a
m
,
J.,
Ho
g
a
rth
,
A
.
,
“
S
o
f
t
S
y
ste
m
s
M
e
th
o
d
o
lo
g
y
(S
S
M
):
F
u
n
d
a
m
e
n
tal
Is
su
e
s
”,
W
o
o
d
-
Ha
rp
e
r
e
t
a
l.
:
2
4
9
-
2
5
5
,
1
9
9
4
.
[7
5
]
A
d
a
m
s,
A
.
,
S
a
ss
e
,
M
.
A
.
,
“
Us
e
rs
a
re
n
o
t
t
h
e
En
e
m
y
:
W
h
y
Us
e
rs
Co
m
p
ro
m
ise
S
e
c
u
rit
y
m
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c
h
a
n
ism
s
a
n
d
Ho
w
to
T
a
k
e
Re
m
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d
ial
M
e
a
su
re
s”
,
Co
m
m
u
n
ica
ti
o
n
s o
f
th
e
A
CM
,
4
2
(1
2
),
p
p
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4
0
-
4
6
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1
9
9
9
.
[7
6
]
Ra
n
n
e
n
b
e
rg
,
K.
,
“
M
u
lt
il
a
ter
a
l
S
e
c
u
rity
–
A
Co
n
c
e
p
t
a
n
d
Exa
mp
le
s
fo
r
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la
n
c
e
d
S
e
c
u
rit
y
”
,
P
ro
c
e
e
d
in
g
s
o
f
th
e
9
t
h
A
CM
Ne
w
S
e
c
u
rit
y
P
a
ra
d
ig
m
s
W
o
rk
sh
o
p
2
0
0
0
,
S
e
p
tem
b
e
r,
Co
rk
,
Ire
lan
d
,
A
CM
P
re
ss
,
2
0
0
0
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
5
2
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Vo
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5
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p
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20
1
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:
1
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10
[7
7
]
S
tew
a
rt,
G
.
,
L
a
c
e
y
,
D.
,
“
De
a
th
b
y
a
T
h
o
u
sa
n
d
F
a
c
ts:
Cr
it
icisin
g
t
h
e
T
e
c
h
n
o
c
ra
ti
c
A
p
p
ro
a
c
h
t
o
I
n
f
o
rm
a
ti
o
n
S
e
c
u
ri
ty
Aw
a
re
n
e
ss
”
,
In
fo
rm
a
ti
o
n
M
a
n
a
g
e
me
n
t
a
n
d
C
o
mp
u
ter
S
e
c
u
rity,
2
0
(
1
):
2
9
-
3
8
,
2
0
1
2
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
F
ra
n
k
ly
n
Ch
u
k
w
u
n
o
n
so
is
a
se
a
s
o
n
e
d
re
se
a
rc
h
e
r
w
it
h
se
v
e
r
a
l
y
e
a
r
s
o
f
w
o
rk
in
g
e
x
p
e
rien
c
e
in
th
e
ICT
in
d
u
stry
a
n
d
Un
iv
e
rsity
l
e
c
tu
rin
g
.
He
h
a
s
a
B.
T
e
c
h
a
n
d
M
.
T
e
c
h
d
e
g
re
e
s
in
In
f
o
rm
a
t
io
n
M
a
n
a
g
e
m
e
n
t
T
e
c
h
n
o
lo
g
y
a
n
d
Op
e
ra
ti
o
n
s
Re
se
a
rc
h
,
re
sp
e
c
ti
v
e
l
y
a
n
d
p
re
se
n
tl
y
p
u
rsu
i
n
g
a
P
h
D
d
e
g
re
e
in
In
f
o
rm
a
ti
o
n
S
y
ste
m
s
a
t
th
e
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
si
a
.
His
re
se
a
rc
h
in
tere
sts
ra
n
g
e
f
ro
m
e
-
lea
rn
in
g
,
in
f
o
rm
a
ti
o
n
sy
s
tem
s,
k
n
o
w
led
g
e
-
b
a
s
e
d
s
y
ste
m
s,
k
n
o
w
led
g
e
e
n
g
in
e
e
rin
g
,
so
f
t
s
y
ste
m
s
m
e
th
o
d
o
l
o
g
y
,
ICT
in
e
d
u
c
a
ti
o
n
,
o
rg
a
n
a
iza
ti
o
n
a
l
a
n
d
re
so
u
rc
e
m
a
n
a
g
e
m
e
n
t,
h
u
m
a
n
re
so
u
rc
e
m
a
n
a
g
e
m
e
n
t,
e
tc.
His
late
st
w
o
rk
is
o
n
d
e
v
e
lo
p
i
n
g
a
n
o
v
e
l
k
n
o
w
led
g
e
-
b
a
se
d
p
e
rso
n
a
li
z
e
d
e
-
lea
rn
i
n
g
sy
ste
m
.
He
h
a
s
p
re
se
n
ted
in
s
o
m
a
n
y
in
t
e
rn
a
ti
o
n
a
l
c
o
n
f
e
re
n
c
e
s
w
it
h
so
m
a
n
y
p
u
b
li
c
a
ti
o
n
s t
o
h
is
n
a
m
e
.
He
lo
v
e
s p
lay
in
g
c
h
e
ss
,
s
w
i
m
m
in
g
,
trav
e
ll
in
g
&
re
se
a
rc
h
Ro
li
a
n
a
Bi
n
ti
I
b
ra
h
im
is
a
S
e
n
io
r
L
e
c
tu
re
r
w
it
h
F
a
c
u
lt
y
o
f
Co
m
p
u
ti
n
g
,
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
la
y
sia
.
S
h
e
re
c
e
i
v
e
d
h
e
r
Hig
h
e
r
Na
ti
o
n
a
l
Dip
l
o
m
a
in
Co
m
p
u
ti
n
g
(1
9
9
4
)
a
n
d
Ba
c
h
e
lo
r
o
f
S
c
ien
c
e
(Ho
n
s)
in
Co
m
p
u
ter
S
tu
d
ies
(1
9
9
8
)
b
o
th
f
ro
m
L
iv
e
rp
o
o
l
Jo
h
n
M
o
o
re
s
Un
iv
e
rsity
,
U
K.
M
a
ste
r
o
f
S
c
ien
c
e
(M
.
S
c
.
)
i
n
C
o
m
p
u
ter
S
c
ien
c
e
(2
0
0
1
)
f
ro
m
U
n
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
sia
.
Do
c
to
r
o
f
P
h
il
o
so
p
h
y
(P
h
.
D)
i
n
S
y
st
e
m
s
S
c
ien
c
e
(2
0
0
8
)
f
ro
m
Lo
u
g
h
b
o
r
o
u
g
h
U
n
iv
e
rsity
,
UK
.
S
h
e
h
a
s
re
c
e
iv
e
d
se
v
e
ra
l
d
isti
n
g
u
ish
e
d
p
a
p
e
r
a
wa
rd
s
in
c
o
n
f
e
re
n
c
e
s
a
n
d
e
x
h
ib
it
io
n
s.
Re
se
a
rc
h
in
tere
st
s
a
re
in
f
o
rm
a
ti
o
n
a
n
d
k
n
o
w
led
g
e
m
a
n
a
g
e
m
e
n
t,
d
a
tab
a
se
s
a
n
d
d
a
ta
m
in
in
g
,
sy
ste
m
th
in
k
in
g
t
h
e
o
ries
a
n
d
m
e
th
o
d
o
l
o
g
ies
f
o
r
c
o
m
p
lex
s
y
st
e
m
s
e
n
g
in
e
e
r
in
g
,
v
iab
le
sy
st
e
m
m
o
d
e
l
a
n
d
in
f
o
rm
a
ti
o
n
re
tri
e
v
a
l.
S
h
e
lo
v
e
s stu
d
y
in
g
d
u
ri
n
g
h
e
r
sp
a
re
ti
m
e
.
A
li
S
e
la
m
a
t
re
c
e
iv
e
d
B.
S
c
.
(H
o
n
s.)
in
IT
f
ro
m
T
e
e
ss
id
e
Un
iv
e
rsit
y
,
U.K.
a
n
d
M
.
S
c
.
in
Distrib
u
te
d
M
u
lt
im
e
d
ia
I
n
tera
c
ti
v
e
S
y
ste
m
s
f
ro
m
L
a
n
c
a
ste
r
Un
iv
e
r
sity
,
U.K.
in
1
9
9
7
a
n
d
1
9
9
8
,
re
sp
e
c
ti
v
e
l
y
.
Dr.
En
g
.
d
e
g
r
e
e
f
ro
m
Os
a
k
a
P
re
f
e
c
tu
re
Un
iv
e
rsit
y
,
J
a
p
a
n
in
2
0
0
3
.
Cu
rre
n
tl
y
,
h
e
is
th
e
De
a
n
o
f
Re
se
a
rc
h
A
ll
ian
c
e
i
n
Kn
o
w
l
e
d
g
e
Eco
n
o
m
y
(K
-
Eco
n
o
m
y
R
A
)
U
T
M
.
He
is
a
l
so
a
p
ro
f
e
ss
o
r
a
t
th
e
S
o
f
t
w
a
r
e
En
g
i
n
e
e
rin
g
De
p
a
rt
m
e
n
t,
F
a
c
u
l
ty
o
f
Co
m
p
u
ti
n
g
UT
M
.
H
e
a
d
o
f
S
o
f
tw
a
r
e
En
g
in
e
e
rin
g
Re
se
a
rc
h
G
ro
u
p
(S
ERG
),
K
-
Eco
n
o
m
y
Re
s
e
a
rc
h
A
ll
ian
c
e
,
U
T
M
.
He
is
th
e
e
d
it
o
rs
o
f
In
tern
a
ti
o
n
a
l
Jo
u
rn
a
l
o
f
Dig
it
a
l
Co
n
ten
t
T
e
c
h
n
o
lo
g
y
a
n
d
it
s
A
p
p
l
ica
ti
o
n
s
(JD
CTA
)
,
In
tern
a
ti
o
n
a
l
Jo
u
r
n
a
l
o
f
A
d
v
a
n
c
e
m
e
n
ts
in
Co
m
p
u
ti
n
g
T
e
c
h
n
o
l
o
g
y
(IJ
AC
T
)
a
n
d
In
tern
a
ti
o
n
a
l
Jo
u
n
a
l
o
f
In
telli
g
h
e
n
t,
In
f
o
rm
a
ti
o
n
a
n
d
Da
tab
a
se
S
y
ste
m
s
(IJIID
S
).
His
re
se
a
rc
h
in
tere
sts
a
r
e
so
f
t
w
a
re
e
n
g
in
e
e
rin
g
,
so
f
t
w
a
re
a
g
e
n
ts,
we
b
e
n
g
in
e
e
rin
g
,
in
f
o
rm
a
ti
o
n
re
tr
iev
a
l
s,
p
a
tt
e
rn
re
c
o
g
n
it
io
n
s,
g
e
n
e
ti
c
a
l
g
o
rit
h
m
s,
n
e
u
ra
l
n
e
tw
o
rk
s an
d
so
f
t
-
c
o
m
p
u
ti
n
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.