I
nte
rna
t
io
na
l J
o
urna
l o
f
E
v
a
lua
t
io
n a
nd
Resea
rc
h in E
du
ca
t
io
n (
I
J
E
RE
)
Vo
l.
14
,
No
.
5
,
Octo
b
er
2
0
2
5
,
p
p
.
3
6
6
5
~
3
6
7
4
I
SS
N:
2
2
5
2
-
8
8
2
2
,
DOI
: 1
0
.
1
1
5
9
1
/
ijer
e
.
v
1
4
i
5
.
3
2
8
0
3
3665
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ere.
ia
esco
r
e.
co
m
Ta
wjihiNav
ig
a
tor:
a
nov
el
hy
brid
i
nform
a
tion re
trie
v
a
l sy
stem
for educa
tiona
l g
uida
nce in
M
o
ro
c
co
H
a
s
s
a
n Silk
hi
1
,
B
ra
him
B
a
k
k
a
s
2
,
K
ha
lid
H
o
us
ni
1
1
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
s,
F
a
c
u
l
t
y
o
f
S
c
i
e
n
c
e
s,
I
b
n
T
o
f
a
i
l
U
n
i
v
e
r
si
t
y
,
K
é
n
i
t
r
a
,
M
o
r
o
c
c
o
2
R
e
g
i
o
n
a
l
C
e
n
t
e
r
f
o
r
E
d
u
c
a
t
i
o
n
a
n
d
T
r
a
i
n
i
n
g
P
r
o
f
e
ss
i
o
n
s,
M
o
u
l
a
y
I
smai
l
U
n
i
v
e
r
s
i
t
y
,
M
e
k
n
e
s
,
M
o
r
o
c
c
o
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Sep
13
,
2
0
2
4
R
ev
is
ed
Mar
4
,
2
0
2
5
Acc
ep
ted
J
u
n
12
,
2
0
2
5
In
t
h
is
p
a
p
e
r,
we
p
r
o
p
o
se
a
n
o
v
e
l
h
y
b
rid
m
e
th
o
d
f
o
r
imp
ro
v
i
n
g
Ara
b
ic
e
d
u
c
a
ti
o
n
a
l
i
n
fo
rm
a
ti
o
n
re
tri
e
v
a
l
(IR)
in
M
o
r
o
c
c
a
n
h
ig
h
sc
h
o
o
ls.
T
ra
d
it
io
n
a
l
se
a
rc
h
m
e
th
o
d
s
o
ften
stru
g
g
l
e
with
Ara
b
ic
’
s
rich
m
o
rp
h
o
lo
g
y
a
n
d
e
d
u
c
a
ti
o
n
a
l
term
in
o
l
o
g
y
,
h
i
n
d
e
ri
n
g
st
u
d
e
n
ts
’
a
c
c
e
ss
to
a
c
c
u
ra
te
g
u
i
d
a
n
c
e
in
fo
rm
a
ti
o
n
.
T
h
e
p
r
o
p
o
se
d
m
e
th
o
d
Taw
ji
h
iNa
v
ig
a
t
o
r
th
a
t
c
o
m
b
i
n
e
s
v
e
c
to
r
-
b
a
se
d
se
m
a
n
ti
c
se
a
rc
h
with
lex
ic
a
l
m
a
tch
in
g
,
e
n
h
a
n
c
e
d
b
y
a
d
v
a
n
c
e
d
Ara
b
ic
n
a
tu
ra
l
lan
g
u
a
g
e
p
r
o
c
e
ss
in
g
(N
LP
)
tec
h
n
iq
u
e
s.
Us
in
g
a
c
o
m
p
re
h
e
n
siv
e
d
a
tas
e
t
c
o
ll
e
c
ted
fro
m
o
fficia
l
M
i
n
istry
o
f
e
d
u
c
a
ti
o
n
so
u
rc
e
s.
To
v
a
li
d
a
te
th
e
IR
-
Ab
h
a
to
s
y
ste
m
,
we
in
te
g
ra
te
CAMeL
To
o
ls
a
n
d
F
a
ra
sa
ste
m
m
e
r
fo
r
Ara
b
ic
p
re
p
ro
c
e
ss
in
g
,
tes
ti
n
g
m
u
lt
ip
le
e
m
b
e
d
d
i
n
g
m
o
d
e
ls
in
c
lu
d
in
g
W
o
rd
2
Ve
c
,
F
a
stTex
t,
a
n
d
Ara
T5
.
Th
e
o
b
tain
e
d
re
su
lt
s
d
e
m
o
n
stra
t
e
th
a
t
o
u
r
h
y
b
rid
m
e
th
o
d
’
s
su
p
e
ri
o
rit
y
o
v
e
r
sta
n
d
a
lo
n
e
v
e
c
to
r
a
n
d
f
u
ll
-
t
e
x
t
se
a
rc
h
a
p
p
ro
a
c
h
e
s,
a
c
h
iev
in
g
a
m
e
a
n
re
c
ip
ro
c
a
l
ra
n
k
(
M
RR)
o
f
0
.
7
9
8
7
a
n
d
m
e
a
n
a
v
e
ra
g
e
p
re
c
isio
n
(M
A
P
)
o
f
0
.
5
6
2
8
.
T
h
e
Ara
T5
m
o
d
e
l
a
c
h
iev
e
d
t
h
e
h
i
g
h
e
st
p
re
c
isio
n
@5
sc
o
re
o
f
0
.
4
5
0
0
,
s
p
e
c
ially
i
n
e
d
u
c
a
ti
o
n
a
l
q
u
e
ry
p
ro
c
e
ss
in
g
.
Th
e
se
fin
d
in
g
s
i
n
d
ica
te
th
a
t
o
u
r
m
o
d
e
l
e
n
h
a
n
c
e
s
Ara
b
ic
e
d
u
c
a
ti
o
n
a
l
IR
a
c
c
u
ra
c
y
,
th
a
t
c
a
n
b
e
imp
ro
v
e
stu
d
e
n
t
d
e
c
isio
n
-
m
a
k
i
n
g
p
ro
c
e
ss
e
s.
K
ey
w
o
r
d
s
:
Aca
d
e
m
ic
s
u
cc
ess
E
d
u
ca
tio
n
al
g
u
id
an
ce
Hy
b
r
id
s
ea
r
ch
I
n
f
o
r
m
atio
n
r
etr
ie
v
al
Natu
r
al
lan
g
u
ag
e
p
r
o
ce
s
s
in
g
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Hass
an
Sil
k
h
i
Dep
ar
tm
en
t o
f
C
o
m
p
u
ter
Scie
n
ce
s
,
Facu
lty
o
f
Scien
ce
s
,
I
b
n
T
o
f
ail
Un
iv
er
s
ity
Av
.
d
e
L
’
Un
i
v
er
s
ité,
Kén
itra
1
4
0
0
0
,
Mo
r
o
cc
o
E
m
ail:
s
ilk
h
i@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
I
n
f
o
r
m
atio
n
r
etr
i
ev
al
(
I
R
)
s
y
s
tem
s
p
lay
a
v
ital
r
o
le
in
m
o
d
er
n
ed
u
ca
tio
n
,
p
ar
ticu
lar
ly
a
s
lear
n
in
g
r
eso
u
r
ce
s
an
d
g
u
id
an
ce
[
1
]
to
o
ls
m
o
v
e
in
cr
ea
s
in
g
ly
o
n
lin
e.
I
n
Ar
ab
ic
-
s
p
ea
k
i
n
g
co
u
n
tr
ies,
th
ese
s
y
s
tem
s
f
ac
e
s
p
ec
ial
ch
allen
g
es
b
ec
au
s
e
o
f
Ar
ab
ic
’
s
u
n
i
q
u
e
f
ea
tu
r
es:
its
co
m
p
lex
wo
r
d
s
tr
u
ctu
r
e,
v
as
t
v
o
ca
b
u
lar
y
,
an
d
d
if
f
er
en
t
r
eg
i
o
n
al
d
ialec
ts
[
2
]
.
R
ec
en
t
s
tu
d
ies
s
u
g
g
est
th
at
s
t
an
d
ar
d
I
R
s
y
s
tem
s
[
3
]
h
av
e
d
i
f
f
icu
lty
p
r
o
ce
s
s
in
g
m
o
s
t
to
h
a
n
d
le
o
v
er
6
0
%
o
f
e
d
u
ca
tio
n
al
q
u
er
ies
in
Ar
ab
ic,
lar
g
ely
b
ec
a
u
s
e
wo
r
d
s
ca
n
tak
e
m
an
y
f
o
r
m
s
an
d
th
eir
m
ea
n
in
g
o
f
ten
d
ep
e
n
d
s
h
ea
v
ily
o
n
c
o
n
tex
t.
T
h
e
d
e
v
elo
p
m
e
n
t
o
f
Ar
a
b
ic
I
R
s
y
s
tem
s
h
as
u
n
f
o
l
d
ed
i
n
th
r
ee
clea
r
tech
n
o
l
o
g
ical
p
h
a
s
es,
ea
ch
tack
lin
g
d
if
f
er
e
n
t
ch
allen
g
es
in
p
r
o
ce
s
s
in
g
in
f
o
r
m
atio
n
.
T
h
e
f
ir
s
t
p
h
ase
b
eg
an
with
s
im
p
le
s
y
s
tem
s
[
4
]
th
at
m
atch
ed
ex
ac
t
k
ey
wo
r
d
s
an
d
u
s
ed
b
asic
wo
r
d
-
r
ed
u
ctio
n
alg
o
r
ith
m
s
.
L
ater
ad
v
an
c
es
im
p
r
o
v
ed
s
ea
r
ch
r
esu
lts
by
L
ar
k
ey
et
a
l.
[
5
]
co
m
b
in
in
g
a
g
en
tler
a
p
p
r
o
ac
h
t
o
wo
r
d
r
ed
u
ctio
n
with
th
e
r
em
o
v
al
o
f
co
m
m
o
n
wo
r
d
s
th
at
ca
r
r
ied
litt
le
m
ea
n
in
g
.
Desp
ite
th
eir
co
m
p
u
tatio
n
al
e
f
f
icien
cy
,
th
ese
s
y
s
tem
s
s
tr
u
g
g
led
t
o
ca
p
tu
r
e
s
em
an
tic
r
ich
n
ess
,
esp
ec
ially
in
h
a
n
d
l
in
g
th
e
lan
g
u
ag
e
’
s
co
m
p
le
x
m
o
r
p
h
o
l
o
g
ical
v
ar
iatio
n
s
.
R
ec
en
t
an
aly
s
is
b
y
Als
u
b
h
i
et
a
l.
[
6
]
d
em
o
n
s
tr
ates
th
at
s
u
ch
t
r
ad
itio
n
al
ap
p
r
o
ac
h
es
m
is
s
ap
p
r
o
x
im
ately
3
5
%
o
f
r
elev
an
t
ed
u
ca
tio
n
al
co
n
te
n
t
d
u
e
to
le
x
ical
v
ar
iatio
n
ch
allen
g
es.
On
th
e
o
th
er
h
an
d
,
th
e
in
tr
o
d
u
ctio
n
o
f
v
ec
to
r
-
b
ased
m
o
d
els
h
as
b
r
o
u
g
h
t
s
ig
n
if
ica
n
t
im
p
r
o
v
em
e
n
ts
in
s
em
a
n
tic
u
n
d
er
s
tan
d
in
g
.
Qar
o
u
s
h
et
a
l.
[
7
]
u
tili
ze
d
laten
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
5
,
Octo
b
er
20
25
:
3
6
6
5
-
3674
3666
s
em
an
tic
an
aly
s
is
(
L
SA)
to
ca
p
tu
r
e
s
em
an
tic
r
elatio
n
s
h
ip
s
in
Ar
a
b
ic
d
o
cu
m
e
n
ts
,
ac
h
iev
in
g
a
2
0
%
im
p
r
o
v
em
e
n
t
in
r
etr
iev
al
ac
cu
r
ac
y
co
m
p
ar
e
d
to
k
ey
wo
r
d
-
b
a
s
ed
m
eth
o
d
s
.
Ab
d
elaz
im
et
a
l.
[
8
]
d
em
o
n
s
tr
ated
th
at
th
ese
m
o
d
els
ca
n
ac
h
iev
e
u
p
to
2
5
%
b
etter
p
er
f
o
r
m
a
n
ce
in
ca
p
t
u
r
in
g
A
r
ab
ic
s
em
an
tic
r
elatio
n
s
h
ip
s
co
m
p
ar
ed
to
tr
a
d
itio
n
al
m
eth
o
d
s
.
Ho
wev
er
,
th
ese
im
p
r
o
v
em
en
ts
co
m
e
with
th
eir
o
wn
ch
allen
g
es,
p
ar
ticu
lar
ly
in
p
r
o
ce
s
s
in
g
ed
u
ca
tio
n
al
ter
m
in
o
lo
g
y
wh
er
e
d
o
m
ain
-
s
p
ec
if
i
c
k
n
o
wled
g
e
is
cr
u
cial.
B
u
i
ld
in
g
o
n
th
ese
ad
v
an
ce
s
,
th
e
cu
r
r
en
t
wav
e
f
ea
tu
r
es
tr
an
s
f
o
r
m
er
-
b
ased
m
o
d
els
an
d
co
n
tex
tu
al
em
b
ed
d
in
g
,
r
ev
o
lu
tio
n
izin
g
Ar
ab
ic
n
atu
r
al
lan
g
u
a
g
e
p
r
o
ce
s
s
in
g
(
NL
P).
An
to
u
n
et
a
l.
[
9
]
in
tr
o
d
u
ce
d
Ar
aBER
T
,
a
p
r
e
-
tr
ai
n
ed
tr
an
s
f
o
r
m
er
-
b
ased
m
o
d
el
f
o
r
Ar
ab
ic
lan
g
u
a
g
e
u
n
d
e
r
s
tan
d
in
g
,
d
e
m
o
n
s
tr
atin
g
s
tate
-
of
-
th
e
-
ar
t
p
er
f
o
r
m
a
n
ce
o
n
v
ar
i
o
u
s
NL
P
task
s
.
R
esear
ch
b
y
T
er
b
eh
et
a
l.
[
1
0
]
d
em
o
n
s
tr
a
tes
th
ese
ad
v
an
ce
d
m
o
d
els
ac
h
iev
in
g
u
p
to
8
5
%
ac
cu
r
ac
y
in
p
r
o
ce
s
s
in
g
co
m
p
lex
Ar
ab
ic
q
u
e
r
ies.
Ho
wev
er
,
as
Ab
d
et
a
l.
[
1
1
]
n
o
tes,
wh
ile
p
o
wer
f
u
l,
th
ese
m
o
d
els
o
f
ten
r
eq
u
ir
e
s
ig
n
if
ic
an
t
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
an
d
m
ay
o
v
er
l
o
o
k
ex
ac
t
m
atch
es
th
at
s
im
p
ler
a
p
p
r
o
ac
h
es
co
u
ld
id
en
tify
.
T
h
is
o
b
s
er
v
atio
n
h
as
m
o
tiv
ate
d
th
e
ex
p
lo
r
atio
n
o
f
h
y
b
r
id
ap
p
r
o
ac
h
es c
o
m
b
in
in
g
m
u
lt
ip
le
m
eth
o
d
o
lo
g
ies.
I
n
Mo
r
o
cc
o
’
s
ev
o
lv
in
g
ed
u
ca
t
io
n
al
lan
d
s
ca
p
e,
wh
er
e
r
ec
e
n
t
r
ef
o
r
m
s
h
av
e
c
r
ea
ted
d
iv
er
s
e
ac
ad
em
ic
p
ath
way
s
,
th
e
n
ee
d
f
o
r
s
o
p
h
is
ticated
I
R
s
o
lu
tio
n
s
h
as
b
ec
o
m
e
p
ar
ticu
lar
l
y
ac
u
te.
T
h
e
an
aly
s
is
r
ev
ea
ls
th
r
ee
cr
itical
ch
allen
g
es:
i
)
th
e
p
r
o
c
ess
in
g
o
f
d
ialec
tal
v
ar
iatio
n
s
s
p
ec
if
ic
to
Mo
r
o
cc
an
Ar
ab
ic
e
d
u
ca
tio
n
al
c
o
n
tex
ts
,
with
cu
r
r
en
t
s
y
s
tem
s
ac
h
iev
in
g
o
n
ly
6
3
%
ac
cu
r
ac
y
in
d
ia
lect
h
an
d
lin
g
[
1
2
]
;
ii
)
th
e
in
teg
r
atio
n
o
f
d
o
m
ain
-
s
p
ec
if
ic
ed
u
ca
tio
n
al
ter
m
in
o
l
o
g
y
,
wh
e
r
e
ex
is
tin
g
s
y
s
tem
s
co
v
er
o
n
ly
4
5
%
o
f
s
p
ec
ialized
v
o
ca
b
u
lar
y
[
1
3
]
;
a
n
d
iii
)
th
e
n
ee
d
f
o
r
r
ea
l
-
tim
e
p
r
o
ce
s
s
in
g
ca
p
ab
ilit
ies
wh
ile
m
ai
n
tain
in
g
ac
cu
r
ac
y
,
with
cu
r
r
e
n
t
s
y
s
tem
s
s
h
o
win
g
s
ig
n
if
ican
t p
er
f
o
r
m
an
ce
d
eg
r
a
d
atio
n
u
n
d
er
h
ig
h
q
u
er
y
lo
ad
s
[
1
4
]
.
T
o
ad
d
r
ess
th
ese
ch
allen
g
es,
we
p
r
esen
t
a
n
o
v
el
h
y
b
r
id
s
ea
r
ch
ap
p
r
o
ac
h
co
m
b
i
n
in
g
v
ec
to
r
-
b
ased
s
em
an
tic
s
ea
r
ch
with
lex
ical
m
atch
in
g
,
s
p
ec
if
ically
o
p
ti
m
ized
f
o
r
Ar
a
b
ic
ed
u
ca
tio
n
a
l
co
n
ten
t.
T
h
e
k
ey
co
n
tr
ib
u
tio
n
s
in
clu
d
e
th
e
in
te
g
r
atio
n
o
f
s
tate
-
of
-
th
e
-
ar
t
em
b
ed
d
in
g
m
o
d
els
with
tr
ad
itio
n
al
lex
ical
s
ea
r
ch
,
im
p
lem
en
tatio
n
o
f
s
p
ec
ialize
d
Ar
ab
ic
NL
P
tech
n
iq
u
es
,
d
ev
elo
p
m
e
n
t
o
f
a
c
o
m
p
r
e
h
en
s
iv
e
ev
alu
atio
n
f
r
am
ewo
r
k
,
cr
ea
tio
n
o
f
a
v
alid
ated
Mo
r
o
cc
an
e
d
u
ca
tio
n
al
in
s
titu
tio
n
s
d
ataset,
an
d
in
t
r
o
d
u
c
tio
n
o
f
an
ad
ap
tiv
e
r
an
k
in
g
m
ec
h
a
n
is
m
th
at
ef
f
ec
t
iv
ely
b
alan
ce
s
s
em
an
tic
u
n
d
er
s
tan
d
in
g
with
ex
ac
t
m
atch
in
g
r
eq
u
ir
em
e
n
ts
.
T
h
e
r
em
ain
d
er
o
f
th
is
p
a
p
er
is
o
r
g
an
ize
d
as:
i)
d
etails
th
e
m
eth
o
d
o
lo
g
y
an
d
s
y
s
tem
im
p
lem
en
tatio
n
;
iii)
ex
p
er
im
en
tal
r
esu
lts
an
d
d
i
s
cu
s
s
io
n
;
an
d
iii)
co
n
clu
d
es with
im
p
licatio
n
s
an
d
f
u
tu
r
e
r
esear
ch
d
ir
ec
tio
n
s
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
o
d
ev
elo
p
an
d
ev
alu
ate
th
e
T
awjih
iNav
ig
ato
r
h
y
b
r
id
s
ea
r
ch
s
y
s
tem
f
o
r
Ar
ab
ic
ed
u
ca
tio
n
a
l
co
n
ten
t,
we
im
p
lem
en
ted
a
r
ig
o
r
o
u
s
,
m
u
lti
-
s
tag
e
p
r
o
ce
s
s
th
at
in
clu
d
ed
d
ata
c
o
llectio
n
,
p
r
ep
r
o
ce
s
s
in
g
,
s
y
s
tem
d
ev
elo
p
m
e
n
t,
an
d
ev
alu
atio
n
p
h
ases
.
T
h
is
ap
p
r
o
ac
h
en
s
u
r
e
d
th
e
r
ep
r
o
d
u
cib
ilit
y
an
d
v
ali
d
ity
o
f
o
u
r
f
i
n
d
in
g
s
.
T
h
is
s
ec
tio
n
o
u
tlin
es
th
e
m
eth
o
d
o
l
o
g
y
,
wh
ich
e
n
co
m
p
ass
es
th
e
cr
ea
tio
n
an
d
p
r
ep
r
o
ce
s
s
in
g
o
f
a
co
m
p
r
eh
e
n
s
iv
e
d
ataset,
as we
ll a
s
th
e
im
p
lem
en
tatio
n
a
n
d
v
a
lid
atio
n
o
f
d
is
tin
ct
r
etr
iev
al
alg
o
r
ith
m
s
.
2
.
1
.
Resea
rc
h o
v
er
v
iew
a
nd
da
t
a
s
et
dev
elo
pm
ent
T
o
ev
a
lu
ate
th
e
T
awjih
iNav
ig
ato
r
s
y
s
tem
f
o
r
Ar
a
b
ic
ed
u
ca
tio
n
al
co
n
ten
t,
we
f
ir
s
t
c
o
llected
a
co
m
p
r
eh
e
n
s
iv
e
d
ataset
en
co
m
p
ass
in
g
h
ig
h
s
ch
o
o
ls
f
r
o
m
all
r
eg
io
n
s
o
f
Mo
r
o
cc
o
.
T
h
is
en
s
u
r
ed
b
r
o
a
d
g
eo
g
r
a
p
h
ical
r
ep
r
esen
tatio
n
a
n
d
d
iv
er
s
e
e
d
u
ca
tio
n
al
o
f
f
er
in
g
s
.
T
h
e
d
ata
c
o
llectio
n
p
r
o
ce
s
s
in
teg
r
ated
m
u
ltip
le
o
f
f
icial
s
o
u
r
ce
s
,
in
cl
u
d
in
g
d
o
cu
m
en
tatio
n
f
r
o
m
th
e
Min
is
tr
y
o
f
Natio
n
al
E
d
u
ca
tio
n
,
o
f
f
ic
ial
s
ch
o
o
l
web
s
ites
,
v
er
if
ied
ad
m
i
n
is
tr
ativ
e
r
ec
o
r
d
s
f
r
o
m
r
e
g
io
n
al
ed
u
ca
tio
n
ac
ad
em
ies,
an
d
o
f
f
icial
p
u
b
licatio
n
s
u
s
ed
b
y
ed
u
ca
tio
n
al
co
u
n
s
elo
r
s
f
o
r
o
r
ien
tatio
n
p
u
r
p
o
s
es
[
1
5
]
–
[
1
7
]
.
T
h
e
d
ataset
in
clu
d
es
b
o
th
p
u
b
lic
an
d
p
r
iv
ate
in
s
titu
tio
n
s
,
ca
p
tu
r
in
g
th
e
f
u
ll
s
p
ec
tr
u
m
o
f
e
d
u
ca
tio
n
al
o
p
tio
n
s
av
ailab
le
to
Mo
r
o
cc
an
s
tu
d
en
ts
.
T
ab
le
1
p
r
o
v
id
es
d
etailed
in
f
o
r
m
atio
n
ab
o
u
t
ea
ch
i
n
s
titu
tio
n
,
i
n
clu
d
in
g
its
n
am
e,
lo
ca
ti
o
n
,
r
eg
i
o
n
,
ty
p
e
o
f
s
ch
o
o
l,
av
ailab
le
p
r
o
g
r
am
s
an
d
s
p
ec
ialties
(
e.
g
.
,
s
cien
ce
,
liter
atu
r
e,
ec
o
n
o
m
i
cs,
an
d
tech
n
ical
)
,
d
ip
lo
m
a
o
f
f
er
i
n
g
s
,
ad
m
is
s
io
n
r
eq
u
ir
em
en
ts
,
s
tu
d
y
d
u
r
at
io
n
,
an
d
p
er
f
o
r
m
an
ce
m
etr
i
cs.
T
h
is
s
tr
u
ctu
r
ed
co
llectio
n
o
f
d
ata
en
ab
les
a
t
h
o
r
o
u
g
h
an
aly
s
is
o
f
ed
u
ca
tio
n
al
o
p
p
o
r
tu
n
ities
ac
r
o
s
s
Mo
r
o
c
co
wh
ile
p
r
o
v
i
d
in
g
v
alu
ab
le
in
f
o
r
m
atio
n
to
ass
is
t
s
tu
d
en
ts
in
m
ak
in
g
in
f
o
r
m
ed
e
d
u
ca
tio
n
al
ch
o
ices.
2
.
2
.
Sy
s
t
e
m
a
rc
hite
ct
ure
a
n
d desi
g
n
W
e
d
ev
elo
p
ed
an
in
te
g
r
ated
s
y
s
tem
ar
ch
itectu
r
e
d
esig
n
ed
to
ef
f
icien
tly
p
r
o
ce
s
s
an
d
r
etr
iev
e
ed
u
ca
tio
n
al
i
n
f
o
r
m
atio
n
.
T
h
e
ar
ch
itectu
r
e
o
f
T
awjih
iNav
ig
a
to
r
co
m
p
r
is
es
th
r
ee
m
ain
c
o
m
p
o
n
en
ts
:
i)
th
e
i
n
p
u
t
p
r
o
ce
s
s
in
g
lay
e
r
,
w
h
ich
h
an
d
l
es
q
u
er
y
p
r
ep
r
o
ce
s
s
in
g
an
d
A
r
ab
ic
tex
t
n
o
r
m
aliza
tio
n
;
ii)
th
e
s
ea
r
ch
p
r
o
ce
s
s
in
g
lay
er
,
wh
ich
im
p
lem
e
n
ts
v
ec
t
o
r
an
d
lex
ical
s
ea
r
ch
m
ec
h
an
is
m
s
;
an
d
iii)
th
e
r
esu
lt
in
teg
r
atio
n
lay
e
r
,
wh
ic
h
co
m
b
in
es
an
d
r
a
n
k
s
s
ea
r
ch
r
esu
lts
u
s
in
g
o
u
r
h
y
b
r
id
ap
p
r
o
ac
h
.
As
illu
s
tr
ated
in
Fig
u
r
e
1
,
o
u
r
d
esig
n
em
p
h
asizes b
o
th
ac
cu
r
ac
y
an
d
p
r
o
ce
s
s
in
g
s
p
ee
d
wh
ile
a
d
d
r
e
s
s
in
g
th
e
co
m
p
lex
ities
o
f
Ar
a
b
ic
tex
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
Ta
w
jih
iN
a
vig
a
to
r
:
a
n
o
ve
l h
y
b
r
id
in
fo
r
ma
tio
n
r
etri
ev
a
l sys
t
em
fo
r
ed
u
ca
tio
n
a
l g
u
id
a
n
ce
…
(
Ha
s
s
a
n
S
ilkh
i)
3667
T
ab
le
1
.
Hig
h
s
ch
o
o
l
d
ataset
f
ield
s
an
d
d
escr
ip
tio
n
s
F
i
e
l
d
D
e
scri
p
t
i
o
n
S
c
h
o
o
l
n
a
m
e
a
n
d
l
o
c
a
t
i
o
n
N
a
me
a
n
d
c
i
t
y
o
f
h
i
g
h
s
c
h
o
o
l
s.
Ty
p
e
o
f
h
i
g
h
sc
h
o
o
l
P
u
b
l
i
c
o
r
p
r
i
v
a
t
e
i
n
s
t
i
t
u
t
i
o
n
.
P
r
o
g
r
a
ms
o
f
f
e
r
e
d
A
v
a
i
l
a
b
l
e
p
r
o
g
r
a
ms
(
sci
e
n
c
e
,
l
i
t
e
r
a
t
u
r
e
,
t
e
c
h
n
i
c
a
l
)
.
D
i
p
l
o
m
a
s
o
f
f
e
r
e
d
Ty
p
e
s
o
f
d
i
p
l
o
m
a
s a
w
a
r
d
e
d
u
p
o
n
c
o
m
p
l
e
t
i
o
n
.
A
d
mi
ss
i
o
n
c
r
i
t
e
r
i
a
En
t
r
y
r
e
q
u
i
r
e
me
n
t
s f
o
r
p
r
o
g
r
a
ms
.
D
u
r
a
t
i
o
n
o
f
s
t
u
d
y
Le
n
g
t
h
o
f
s
t
u
d
y
p
r
o
g
r
a
ms
.
P
e
r
f
o
r
ma
n
c
e
me
t
r
i
c
s
B
a
c
c
a
l
a
u
r
e
a
t
e
p
a
ss ra
t
e
s
,
d
e
m
o
g
r
a
p
h
i
c
s.
S
p
e
c
i
a
l
t
i
e
s
a
v
a
i
l
a
b
l
e
S
p
e
c
i
f
i
c
s
p
e
c
i
a
l
i
z
a
t
i
o
n
s
o
f
f
e
r
e
d
.
Fig
u
r
e
1
.
I
n
teg
r
ated
s
y
s
tem
ar
ch
itectu
r
e
f
o
r
ef
f
icien
t A
r
a
b
ic
tex
t p
r
o
ce
s
s
in
g
an
d
h
y
b
r
id
s
ea
r
ch
2
.
3
.
Ara
bic t
e
x
t
prepro
ce
s
s
ing
I
n
p
r
ep
r
o
ce
s
s
in
g
Ar
ab
ic
tex
t,
we
u
tili
ze
d
th
e
C
AM
eL
T
o
o
ls
lib
r
ar
y
an
d
Far
asa
s
tem
m
er
f
o
r
th
eir
p
r
o
v
e
n
ef
f
ec
tiv
e
n
ess
in
h
an
d
lin
g
Ar
ab
ic
lan
g
u
a
g
e
co
m
p
lex
ities
.
T
h
e
C
AM
eL
T
o
o
ls
s
u
ite
p
r
o
v
id
es
co
m
p
r
eh
e
n
s
iv
e
u
tili
ties
f
o
r
to
k
en
izatio
n
,
p
ar
t
-
of
-
s
p
ee
ch
tag
g
in
g
,
a
n
d
n
am
ed
en
tity
r
ec
o
g
n
itio
n
[
1
8
]
.
Fi
g
u
r
e
2
p
r
esen
ts
o
u
r
p
r
e
p
r
o
ce
s
s
in
g
p
i
p
elin
e
f
lo
wch
ar
t,
d
etailin
g
th
e
n
in
e
s
eq
u
en
tial
s
tep
s
f
r
o
m
r
aw
Ar
ab
ic
tex
t
to
p
r
ep
r
o
ce
s
s
ed
o
u
tp
u
t.
T
a
b
le
2
d
em
o
n
s
tr
ates v
ar
io
u
s
d
ata
clea
n
in
g
tech
n
i
q
u
es with
co
n
c
r
ete
ex
am
p
les,
s
h
o
win
g
th
e
tr
an
s
f
o
r
m
atio
n
o
f
Ar
ab
ic
t
ex
t th
r
o
u
g
h
ea
c
h
p
r
e
p
r
o
ce
s
s
in
g
s
tag
e.
2
.
4
.
E
m
bedd
ing
m
o
dels
a
nd
s
ea
rc
h im
plem
ent
a
t
io
n
Ou
r
s
y
s
tem
em
p
l
o
y
s
a
c
o
m
p
r
eh
en
s
iv
e
ap
p
r
o
ac
h
to
I
R
b
y
i
n
teg
r
atin
g
m
u
ltip
le
e
m
b
ed
d
in
g
m
o
d
els
with
ad
v
an
ce
d
s
ea
r
c
h
m
eth
o
d
o
lo
g
ies.
At
th
e
f
o
u
n
d
atio
n
o
f
o
u
r
s
y
s
tem
ar
e
ca
r
ef
u
lly
s
elec
ted
em
b
ed
d
in
g
m
o
d
els
th
at
p
r
o
v
id
e
d
en
s
e
v
e
cto
r
r
ep
r
esen
tatio
n
s
o
f
tex
t
[
1
9
]
,
[
2
0
]
,
ca
p
tu
r
in
g
s
em
an
tic
r
elatio
n
s
h
ip
s
cr
u
cial
f
o
r
ed
u
ca
tio
n
al
co
n
ten
t
r
etr
ie
v
al
[
2
1
]
.
T
h
ese
m
o
d
els,
in
clu
d
in
g
W
o
r
d
2
Vec
[
1
9
]
,
E
5
b
ase
[
2
2
]
an
d
lar
g
e
v
ar
ian
ts
[
2
2
]
,
Fas
tTe
x
t
[
2
3
]
,
Fas
tEm
b
ed
[
2
4
]
,
Glo
Ve
[
2
5
]
,
a
n
d
Ar
aT
5
[
2
6
]
,
ea
ch
b
r
in
g
u
n
i
q
u
e
ca
p
ab
ilit
ie
s
to
h
an
d
le
th
e
c
o
m
p
lex
ities
o
f
Ar
ab
ic
lan
g
u
a
g
e
p
r
o
ce
s
s
in
g
,
as d
etailed
in
T
ab
le
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
5
,
Octo
b
er
20
25
:
3
6
6
5
-
3674
3668
Fig
u
r
e
2
.
Ar
a
b
ic
tex
t p
r
e
p
r
o
ce
s
s
in
g
p
ip
elin
e
f
lo
wch
ar
t
T
ab
le
2
.
T
ec
h
n
iq
u
e
an
d
e
x
am
p
le
f
o
r
d
ata
p
r
e
p
r
o
ce
s
s
in
g
s
tag
es
P
r
e
p
r
o
c
e
ss
i
n
g
s
t
e
p
I
n
p
u
t
Tr
a
n
s
l
a
t
i
o
n
O
u
t
p
u
t
Tr
a
n
s
l
a
t
i
o
n
U
n
i
c
o
d
e
n
o
r
m
a
l
i
z
a
t
i
o
n
ةس
د
ن
ه
لا
ةي
لك
،
طا
ب
ر
لا
ةع
م
ا
ج
U
n
i
v
e
r
si
t
y
o
f
R
a
b
a
t
,
F
a
c
u
l
t
y
o
f
En
g
i
n
e
e
r
i
n
g
،
طا
ب
ر
لا
ةع
م
ا
ج
ةس
د
ن
ه
لا
ةي
لك
U
n
i
v
e
r
si
t
y
o
f
R
a
b
a
t
,
F
a
c
u
l
t
y
o
f
E
n
g
i
n
e
e
r
i
n
g
D
i
a
c
r
i
t
i
c
r
e
m
o
v
a
l
َ
س
ْ
ر
د
ل
ا
َ
ِ
ب
ل
ا
ّ
ط
ل
ا
َ
َ
َ
ب
ت
َ
ك
م
َ
ا
ِ
م
ت
ْ
ه
ِ
ا
ب
Th
e
st
u
d
e
n
t
w
r
o
t
e
t
h
e
l
e
sso
n
w
i
t
h
a
t
t
e
n
t
i
o
n
ب
لا
طلا
ب
ت
ك
م
ا
م
ت
ها
ب
س
ر
د
لا
Th
e
st
u
d
e
n
t
w
r
o
t
e
t
h
e
l
e
ss
o
n
w
i
t
h
a
t
t
e
n
t
i
o
n
C
h
a
r
a
c
t
e
r
n
o
r
m
a
l
i
z
a
t
i
o
n
،
م
ا
م
ت
ها
ب
سر
د
لا
ب
لا
طلا
ب
ت
ك
Th
e
st
u
d
e
n
t
w
r
o
t
e
t
h
e
l
e
sso
n
w
i
t
h
a
t
t
e
n
t
i
o
n
,
ب
لا
طلا
ب
ت
ك
م
ا
م
ت
ها
ب
س
ر
د
لا
Th
e
st
u
d
e
n
t
w
r
o
t
e
t
h
e
l
e
ss
o
n
w
i
t
h
a
t
t
e
n
t
i
o
n
S
t
o
p
w
o
r
d
r
e
mo
v
a
l
لض
فأ
ن
م
ي
ه ةع
م
ا
ج
لا
ن
إ
ةن
ي
د
م
لا
ي
ف
ت
ا
ع
م
ا
ج
لا
I
n
d
e
e
d
,
t
h
e
u
n
i
v
e
r
si
t
y
i
s
o
n
e
o
f
t
h
e
b
e
s
t
u
n
i
v
e
r
si
t
i
e
s i
n
t
h
e
c
i
t
y
لض
فأ
ةع
م
ا
ج
لا
ةن
ي
د
م
لا
ت
ا
ع
م
ا
ج
لا
U
n
i
v
e
r
si
t
y
b
e
st
u
n
i
v
e
r
si
t
i
e
s
c
i
t
y
To
k
e
n
i
z
a
t
i
o
n
م
ا
م
ت
ها
ب
سر
د
لا
ب
لا
طلا
ب
ت
ك
Th
e
st
u
d
e
n
t
w
r
o
t
e
t
h
e
l
e
sso
n
w
i
t
h
a
t
t
e
n
t
i
o
n
[
,
سر
د
لا
,
م
ا
م
ت
ها
ب
ب
ت
ك
,
ب
لا
طلا
]
[
w
i
t
h
a
t
t
e
n
t
i
o
n
,
t
h
e
l
e
ss
o
n
,
t
h
e
st
u
d
e
n
t
,
w
r
o
t
e
]
S
t
e
mm
i
n
g
o
r
l
e
mm
a
t
i
z
a
t
i
o
n
[ [
ب
ت
ك
,
سر
د
,
م
ا
م
ت
ها[
[
a
t
t
e
n
t
i
o
n
,
l
e
ss
o
n
,
w
r
o
t
e
]
[
ب
ت
ك
,
سر
د
,
م
ه
]
[
t
h
e
m
,
l
e
ss
o
n
,
w
r
o
t
e
]
R
e
m
o
v
e
n
o
n
-
A
r
a
b
i
c
c
h
a
r
a
c
t
e
r
s
ن
ع
لق
ي
1
8
.
0
MP
:
ن
ع
لق
ي
لوبقل
ا
ت
ا
ب
لطت
م
N
o
t
l
e
ss
t
h
a
n
1
8
.
0
M
P
:
a
d
mi
ss
i
o
n
r
e
q
u
i
r
e
m
e
n
t
s
n
o
t
l
e
ss
t
h
a
n
لوبقل
ا
ت
ا
ب
لطت
م
ن
ع
لق
ي
A
d
mi
ss
i
o
n
r
e
q
u
i
r
e
me
n
t
s
n
o
t
l
e
ss
t
h
a
n
T
ab
le
3
.
C
o
m
p
r
eh
en
s
iv
e
c
o
m
p
ar
is
o
n
o
f
em
b
ed
d
i
n
g
m
o
d
els a
n
d
th
eir
s
p
ec
if
icatio
n
s
M
o
d
e
l
K
e
y
f
e
a
t
u
r
e
s
D
i
me
n
si
o
n
S
i
z
e
W
o
r
d
2
V
e
c
M
a
p
s w
o
r
d
s
t
o
c
o
n
t
i
n
u
o
u
s
v
e
c
t
o
r
sp
a
c
e
f
o
r
A
r
a
b
i
c
t
e
x
t
p
r
o
c
e
ss
i
n
g
.
A
r
a
V
e
c
d
e
v
e
l
o
p
m
e
n
t
b
y
[
2
7
]
f
o
r
A
r
a
b
i
c
-
sp
e
c
i
f
i
c
W
o
r
d
2
V
e
c
m
o
d
e
l
s.
U
ses
S
k
i
p
-
g
r
a
m
o
r
C
B
O
W
a
p
p
r
o
a
c
h
e
s.
3
0
0
6
0
M
E5
b
a
s
e
Te
x
t
e
mb
e
d
d
i
n
g
m
o
d
e
l
f
o
r
mu
l
t
i
p
l
e
l
a
n
g
u
a
g
e
s i
n
c
l
u
d
i
n
g
A
r
a
b
i
c
.
G
e
n
e
r
a
t
e
s
d
e
n
se
v
e
c
t
o
r
r
e
p
r
e
s
e
n
t
a
t
i
o
n
s
f
r
o
m w
o
r
d
s t
o
d
o
c
u
m
e
n
t
s.
7
6
8
2
7
8
M
E5
l
a
r
g
e
En
h
a
n
c
e
d
v
e
r
si
o
n
o
f
E5
b
a
se
w
i
t
h
l
a
r
g
e
r
c
a
p
a
c
i
t
y
.
I
mp
r
o
v
e
d
c
r
o
ss
-
l
i
n
g
u
a
l
c
a
p
a
b
i
l
i
t
i
e
s
a
n
d
sem
a
n
t
i
c
u
n
d
e
r
s
t
a
n
d
i
n
g
.
1
0
2
4
5
6
0
M
F
a
st
T
e
x
t
Ex
t
e
n
d
s
W
o
r
d
2
V
e
c
b
y
i
n
c
o
r
p
o
r
a
t
i
n
g
su
b
w
o
r
d
i
n
f
o
r
m
a
t
i
o
n
.
Ef
f
e
c
t
i
v
e
n
e
ss
d
e
mo
n
st
r
a
t
e
d
b
y
[
2
8
]
i
n
A
r
a
b
i
c
se
n
t
i
m
e
n
t
a
n
a
l
y
si
s
.
H
a
n
d
l
e
s
c
o
mp
l
e
x
d
e
r
i
v
a
t
i
o
n
a
l
mo
r
p
h
o
l
o
g
y
o
f
A
r
a
b
i
c
l
a
n
g
u
a
g
e
.
3
0
0
6
0
0
M
F
a
st
Em
b
e
d
Li
g
h
t
w
e
i
g
h
t
a
n
d
e
f
f
i
c
i
e
n
t
t
e
x
t
e
mb
e
d
d
i
n
g
l
i
b
r
a
r
y
.
S
u
p
p
o
r
t
s m
u
l
t
i
p
l
e
l
a
n
g
u
a
g
e
s i
n
c
l
u
d
i
n
g
A
r
a
b
i
c
.
3
8
4
3
8
.
4
M
G
l
o
V
e
Tr
a
i
n
e
d
o
n
W
i
k
i
p
e
d
i
a
2
0
1
4
a
n
d
G
i
g
a
w
o
r
d
5
c
o
r
p
u
s.
U
s
e
s a
v
e
r
a
g
e
-
w
o
r
d
-
e
mb
e
d
d
i
n
g
s
a
p
p
r
o
a
c
h
.
C
r
e
a
t
e
s
e
mb
e
d
d
i
n
g
s
b
y
a
v
e
r
a
g
i
n
g
v
e
c
t
o
r
s
o
f
a
l
l
w
o
r
d
s
.
3
0
0
1
2
0
M
A
r
a
T5
Pre
-
t
r
a
i
n
e
d
t
e
x
t
-
to
-
t
e
x
t
t
r
a
n
sf
o
r
mer
sp
e
c
i
f
i
c
a
l
l
y
f
o
r
A
r
a
b
i
c
.
B
a
s
e
d
o
n
T5
a
r
c
h
i
t
e
c
t
u
r
e
w
i
t
h
A
r
a
b
i
c
-
sp
e
c
i
f
i
c
t
r
a
i
n
i
n
g
.
H
a
n
d
l
e
s
v
a
r
i
o
u
s Ar
a
b
i
c
d
i
a
l
e
c
t
s
.
7
6
8
2
2
0
M
T
h
e
s
ea
r
ch
im
p
lem
en
tatio
n
i
n
teg
r
ates
th
r
ee
d
is
tin
ct
y
et
co
m
p
lem
en
tar
y
a
p
p
r
o
ac
h
es:
v
ec
to
r
s
ea
r
ch
,
f
u
ll
-
tex
t
s
ea
r
ch
,
a
n
d
a
h
y
b
r
id
m
eth
o
d
o
lo
g
y
th
at
lev
er
a
g
es
th
e
s
tr
en
g
th
s
o
f
b
o
th
.
I
n
v
ec
t
o
r
-
b
ased
s
em
an
tic
s
ea
r
ch
,
we
em
p
lo
y
co
s
in
e
s
im
ilar
ity
[
2
9
]
ca
lcu
latio
n
s
to
m
e
asu
r
e
th
e
s
em
an
tic
r
elate
d
n
ess
b
etwe
en
d
o
cu
m
en
t
v
ec
to
r
s
[
3
0
]
.
T
h
is
en
a
b
les
u
s
t
o
id
en
tif
y
co
n
ce
p
tu
ally
s
im
ilar
co
n
ten
t
ev
en
wh
en
th
e
ex
ac
t
t
er
m
in
o
lo
g
y
d
if
f
er
s
[
3
1
]
.
T
h
is
ap
p
r
o
ac
h
is
p
ar
ticu
lar
l
y
v
alu
ab
le
f
o
r
h
a
n
d
lin
g
v
a
r
iatio
n
s
in
ed
u
ca
tio
n
al
ter
m
in
o
lo
g
y
a
n
d
d
ialec
tal
d
if
f
er
en
ce
s
in
Ar
a
b
ic
tex
t.
T
h
e
co
s
in
e
s
im
ilar
ity
b
etwe
en
two
v
ec
to
r
s
A
an
d
B
is
ca
lcu
lated
as sh
o
wn
in
(
1
)
.
co
s
in
e
s
imila
r
it
y
=
⋅
|
|
|
|
=
∑
=
1
√
∑
2
=
1
√
∑
2
=
1
(
1
)
Fo
r
th
e
f
u
ll
-
tex
t
s
ea
r
c
h
co
m
p
o
n
en
t,
we
im
p
lem
e
n
ted
t
h
e
B
M2
5
alg
o
r
ith
m
[
3
2
]
,
wh
ic
h
p
r
o
v
id
es
s
o
p
h
is
ticated
d
o
cu
m
en
t
r
a
n
k
i
n
g
b
ased
o
n
ter
m
f
r
e
q
u
en
c
y
a
n
d
d
o
c
u
m
en
t
len
g
t
h
.
T
h
is
p
r
o
b
ab
ilis
tic
ap
p
r
o
ac
h
en
s
u
r
es
th
at
ex
ac
t
m
atch
es
an
d
k
ey
ter
m
in
o
lo
g
y
ar
e
ap
p
r
o
p
r
iately
weig
h
ted
in
t
h
e
r
esu
lts
,
wh
ich
i
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
Ta
w
jih
iN
a
vig
a
to
r
:
a
n
o
ve
l h
y
b
r
id
in
fo
r
ma
tio
n
r
etri
ev
a
l sys
t
em
fo
r
ed
u
ca
tio
n
a
l g
u
id
a
n
ce
…
(
Ha
s
s
a
n
S
ilkh
i)
3669
p
ar
ticu
lar
ly
im
p
o
r
tan
t
f
o
r
tech
n
ical
an
d
s
u
b
ject
-
s
p
ec
if
ic
e
d
u
ca
tio
n
al
co
n
te
n
t.
T
h
e
B
M2
5
s
co
r
in
g
f
u
n
ctio
n
p
r
esen
ted
wh
ich
ca
lc
u
lates th
e
s
co
r
in
g
o
f
s
p
ec
if
ic
tex
t c
h
a
r
ac
ter
is
tics
,
is
d
ef
in
ed
in
(
2
)
.
s
co
r
e
(
,
)
=
∑
I
DF
(
)
=
1
⋅
(
,
)
⋅
(
1
+
1
)
(
,
)
+
1
⋅
(
1
−
+
⋅
|
|
a
vgdl
)
(
2
)
W
h
e
r
e
,
D
r
e
p
r
es
en
ts
t
h
e
d
o
c
u
m
e
n
t
,
Q
r
e
p
r
es
en
ts
t
h
e
q
u
e
r
y
t
er
m
s
.
Q
is
a
s
e
t o
f
n
te
r
m
s
d
e
n
o
te
d
b
y
q
₁
,
q
₂
,
.
.
.
,
q
ₙ
.
T
h
e
te
r
m
f
r
e
q
u
e
n
c
y
is
r
e
p
r
ese
n
te
d
as
f(
q
ᵢ
,
D)
,
w
h
e
r
e
q
ᵢ
is
a
q
u
e
r
y
t
e
r
m
a
n
d
D
is
t
h
e
d
o
c
u
m
e
n
t
.
Ad
d
i
ti
o
n
all
y
,
|
D|
d
e
n
o
t
es t
h
e
d
o
c
u
m
e
n
t
le
n
g
t
h
,
w
h
il
e
a
vg
d
l
r
e
p
r
ese
n
ts
t
h
e
a
v
e
r
a
g
e
d
o
c
u
m
en
t
le
n
g
th
ac
r
o
s
s
t
h
e
c
o
r
p
u
s
.
T
h
e
h
y
b
r
id
s
ea
r
ch
m
eth
o
d
o
lo
g
y
in
te
g
r
ates
th
ese
ap
p
r
o
ac
h
e
s
th
r
o
u
g
h
a
ca
r
ef
u
lly
d
esig
n
e
d
p
ip
elin
e
th
at
n
o
r
m
alize
s
an
d
co
m
b
in
e
s
s
co
r
es
f
r
o
m
b
o
th
v
ec
to
r
-
b
a
s
ed
an
d
tex
t
-
b
ased
s
ea
r
ch
es.
T
h
e
p
r
o
ce
s
s
b
eg
in
s
with
th
e
p
a
r
allel
ex
ec
u
tio
n
o
f
s
em
an
tic
an
d
le
x
ical
m
atch
in
g
,
f
o
llo
wed
b
y
s
co
r
e
n
o
r
m
aliz
atio
n
to
e
n
s
u
r
e
f
air
co
m
p
ar
is
o
n
.
A
weig
h
ted
c
o
m
b
in
atio
n
m
ec
h
a
n
is
m
th
en
g
en
er
ates
f
in
al
r
an
k
in
g
s
,
b
alan
cin
g
s
em
a
n
tic
u
n
d
er
s
tan
d
i
n
g
with
ex
ac
t
m
atch
in
g
r
eq
u
ir
e
m
en
ts
[
3
3
]
,
[
3
4
]
.
T
h
is
in
teg
r
ated
a
p
p
r
o
ac
h
is
p
ar
ticu
lar
ly
b
en
ef
icial
f
o
r
Ar
ab
ic
ed
u
ca
t
io
n
al
co
n
ten
t
r
etr
iev
al,
wh
e
r
e
b
o
th
co
n
ce
p
tu
al
u
n
d
er
s
tan
d
in
g
an
d
p
r
ec
is
e
ter
m
in
o
lo
g
y
m
atch
in
g
p
la
y
cr
u
cial
r
o
les.
T
o
en
h
an
c
e
s
ea
r
ch
q
u
er
y
p
r
o
ce
s
s
in
g
,
we
im
p
lem
en
ted
th
ese
m
eth
o
d
o
l
o
g
ies
u
s
in
g
th
e
Q
d
r
an
t
v
ec
to
r
d
atab
ase
f
r
am
ewo
r
k
,
wh
ich
o
f
f
er
s
o
p
tim
ized
s
to
r
ag
e
an
d
r
etr
iev
al
ca
p
ab
ilit
ies
f
o
r
h
ig
h
-
d
im
en
s
i
o
n
al
v
ec
to
r
s
alo
n
g
s
id
e
tr
ad
it
io
n
al
tex
t
d
ata.
Qd
r
an
t
en
ab
les
f
ast
s
im
ilar
ity
co
m
p
u
tatio
n
s
wh
ile
ac
co
m
m
o
d
atin
g
th
e
c
o
m
p
lex
r
eq
u
ir
e
m
e
n
ts
o
f
Ar
ab
ic
tex
t
p
r
o
ce
s
s
in
g
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
I
n
th
is
s
ec
tio
n
,
we
p
r
esen
t
a
c
o
m
p
r
eh
e
n
s
iv
e
an
aly
s
is
o
f
th
e
T
awjih
iNav
ig
ato
r
s
y
s
tem
’
s
p
er
f
o
r
m
a
n
ce
in
Ar
ab
ic
ed
u
ca
tio
n
al
I
R
.
W
e
ev
alu
ate
th
e
e
f
f
ec
tiv
en
ess
o
f
o
u
r
m
o
d
el
u
s
in
g
m
u
ltip
le
m
etr
ics,
in
clu
d
in
g
p
r
ec
is
io
n
ac
r
o
s
s
d
if
f
er
e
n
t
em
b
ed
d
in
g
m
o
d
els.
Ad
d
itio
n
ally
,
we
co
m
p
ar
e
o
u
r
f
in
d
in
g
s
with
ex
is
tin
g
s
o
lu
tio
n
s
wh
ile
ass
es
s
in
g
th
e
s
y
s
tem
’
s
ef
f
icien
cy
an
d
s
ca
lab
ilit
y
f
o
r
ed
u
ca
tio
n
al
g
u
i
d
an
ce
s
y
s
tem
s
.
3
.
1
.
Resul
t
s
T
o
ev
alu
ate
th
e
p
r
o
p
o
s
ed
T
aw
jih
iNav
ig
ato
r
s
y
s
tem
,
we
em
p
lo
y
ed
a
co
m
p
r
eh
e
n
s
iv
e
s
et
o
f
ev
alu
atio
n
m
etr
ics,
in
clu
d
in
g
p
r
ec
is
io
n
(
3
)
,
r
ec
all
(
4
)
,
F1
s
co
r
e
(
5
)
,
m
ea
n
av
er
ag
e
p
r
ec
is
io
n
(
MA
P)
(
7
)
,
an
d
m
ea
n
r
ec
ip
r
o
ca
l
r
a
n
k
(
MRR
)
(
8
)
,
as
d
etailed
i
n
T
ab
le
4
.
T
h
ese
m
etr
ics
o
f
f
er
q
u
a
n
titativ
e
m
ea
s
u
r
es
o
f
th
e
s
y
s
tem
’
s
p
er
f
o
r
m
an
ce
in
r
etr
iev
in
g
an
d
r
an
k
in
g
r
elev
an
t
d
o
cu
m
en
ts
.
T
ab
le
4
.
Ma
th
em
atica
l d
e
f
in
itio
n
s
o
f
co
r
e
I
R
p
er
f
o
r
m
a
n
ce
m
etr
ics
M
e
t
r
i
c
F
o
r
mu
l
a
P
r
e
c
i
s
i
o
n
P
r
e
c
i
si
o
n
=
|
{
R
e
l
e
v
a
n
t
D
o
c
u
me
n
t
s
}
∩
{
R
e
t
r
i
e
v
e
d
D
o
c
u
me
n
t
s
}
|
|
{
R
e
t
r
i
e
v
e
d
D
o
c
u
me
n
t
s
}
|
(
3
)
R
e
c
a
l
l
R
e
c
a
l
l
=
|
{
R
e
l
e
v
a
n
t
D
o
c
u
me
n
t
s
}
∩
{
R
e
t
r
i
e
v
e
d
D
o
c
u
men
t
s
}
|
|
{
R
e
l
e
v
a
n
t
D
o
c
u
men
t
s
}
|
(
4
)
F
1
sc
o
r
e
F1
=
2
⋅
P
r
e
c
i
si
o
n
⋅
R
e
c
a
l
l
P
r
e
c
i
si
o
n
+
R
e
c
a
l
l
(
5
)
M
A
P
AP
=
∑
(
(
)
⋅
r
e
l
(
)
)
=
1
|
{
R
e
l
e
v
a
n
t
D
o
c
u
me
n
t
s
}
|
(
6
)
M
A
P
=
∑
AP
(
)
=
1
W
h
e
r
e
,
P
(
k
)
i
s
t
h
e
p
r
e
c
i
s
i
o
n
a
t
c
u
t
-
o
f
f
k
i
n
t
h
e
l
i
st
,
r
e
l
(
k
)
i
s a
n
i
n
d
i
c
a
t
o
r
f
u
n
c
t
i
o
n
e
q
u
a
l
i
n
g
1
i
f
t
h
e
i
t
e
m
a
t
r
a
n
k
k
i
s re
l
e
v
a
n
t
,
a
n
d
Q
i
s
t
h
e
n
u
mb
e
r
o
f
q
u
e
r
i
e
s.
(
7
)
M
R
R
M
R
R
=
1
∑
1
r
a
n
k
=
1
W
h
e
r
e
,
r
a
n
k
q
i
s t
h
e
r
a
n
k
p
o
s
i
t
i
o
n
o
f
t
h
e
f
i
r
st
r
e
l
e
v
a
n
t
d
o
c
u
me
n
t
f
o
r
t
h
e
q
-
t
h
q
u
e
r
y
.
(
8
)
T
h
e
in
itial
an
aly
s
is
f
o
cu
s
ed
o
n
p
r
ec
is
io
n
m
etr
ics
ac
r
o
s
s
d
if
f
er
en
t
em
b
e
d
d
in
g
m
o
d
el
s
.
T
ab
le
5
d
em
o
n
s
tr
ates
th
at
th
e
h
y
b
r
id
s
ea
r
ch
ap
p
r
o
ac
h
s
ig
n
if
ican
tly
o
u
tp
e
r
f
o
r
m
s
tr
ad
itio
n
al
v
ec
t
o
r
s
ea
r
ch
m
eth
o
d
s
.
T
h
e
m
o
s
t
n
o
tab
le
im
p
r
o
v
em
e
n
ts
ap
p
ea
r
in
Ar
aT
5
an
d
Glo
Ve
m
o
d
e
ls
,
b
o
th
ac
h
iev
i
n
g
a
p
r
ec
is
io
n
@
5
s
co
r
e
o
f
0
.
4
5
0
0
,
r
e
p
r
esen
tin
g
im
p
r
o
v
em
en
ts
o
f
4
3
%
o
v
e
r
th
eir
b
aselin
e
p
er
f
o
r
m
an
ce
.
T
h
e
s
e
r
esu
lts
in
d
icate
s
u
b
s
tan
tial e
n
h
an
ce
m
en
t in
r
et
r
iev
al
ac
cu
r
ac
y
wh
en
c
o
m
b
in
i
n
g
s
em
an
tic
an
d
lex
ical
s
ea
r
ch
ca
p
ab
ilit
ies.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
5
,
Octo
b
er
20
25
:
3
6
6
5
-
3674
3670
T
ab
le
5
.
C
o
m
p
r
eh
en
s
iv
e
e
v
alu
atio
n
o
f
p
r
ec
is
io
n
@
5
s
co
r
es a
cr
o
s
s
em
b
ed
d
in
g
m
o
d
els
M
o
d
e
l
V
e
c
t
o
r
se
a
r
c
h
H
y
b
r
i
d
sea
r
c
h
I
mp
r
o
v
e
m
e
n
t
(
%)
W
o
r
d
2
V
e
c
0
.
0
6
0
0
0
.
4
5
0
0
+
3
9
.
0
0
E5
b
a
s
e
0
.
4
1
0
0
0
.
4
0
0
0
-
0
.
1
0
E5
l
a
r
g
e
0
.
3
7
0
0
0
.
4
0
0
0
+
3
.
0
0
F
a
st
T
e
x
t
0
.
2
1
0
0
0
.
4
3
0
0
+
2
2
.
0
0
F
a
st
Em
b
e
d
0
.
0
2
0
0
0
.
4
4
0
0
+
4
2
.
0
0
G
l
o
V
e
0
.
0
2
0
0
0
.
4
5
0
0
+
4
3
.
0
0
A
r
a
T5
0
.
0
2
0
0
0
.
4
5
0
0
+
4
3
.
0
0
T
h
e
r
ec
all
an
aly
s
is
,
p
r
esen
ted
in
T
ab
le
6
,
r
ev
ea
ls
eq
u
ally
im
p
r
ess
iv
e
im
p
r
o
v
e
m
en
ts
.
Glo
V
e
em
er
g
ed
as
th
e
to
p
p
er
f
o
r
m
er
with
a
5
1
.
7
1
%
im
p
r
o
v
em
en
t
i
n
r
ec
all,
clo
s
ely
f
o
llo
wed
b
y
Ar
aT
5
a
t
5
1
.
3
8
%.
T
h
e
E
5
m
o
d
els
s
h
o
wed
m
o
r
e
m
o
d
est
im
p
r
o
v
e
m
en
ts
,
s
u
g
g
esti
n
g
th
ei
r
b
ase
im
p
lem
en
tatio
n
alr
ea
d
y
in
co
r
p
o
r
ates
s
o
m
e
h
y
b
r
id
-
lik
e
ch
ar
ac
te
r
is
tics
.
T
ab
le
7
r
ev
ea
ls
cr
itical
in
s
ig
h
ts
ab
o
u
t
m
o
d
el
p
er
f
o
r
m
a
n
ce
in
Ar
ab
ic
I
R
.
T
h
e
m
o
s
t
s
ig
n
if
ican
t
f
in
d
in
g
is
th
e
clea
r
tr
ad
e
-
o
f
f
b
etwe
en
p
r
ec
is
io
n
at
to
p
r
an
k
s
(
MRR
)
an
d
o
v
er
all
r
etr
iev
al
e
f
f
ec
tiv
e
n
ess
(
MA
P)
ac
r
o
s
s
d
if
f
er
en
t
m
o
d
els.
T
h
e
E
5
lar
g
e
m
o
d
el
ac
h
iev
es
th
e
h
ig
h
e
s
t
MRR
s
co
r
e
o
f
0
.
7
9
8
7
,
d
e
m
o
n
s
tr
atin
g
s
u
p
e
r
io
r
ab
ilit
y
in
r
a
n
k
in
g
r
elev
a
n
t
d
o
c
u
m
en
ts
at
to
p
p
o
s
itio
n
s
,
wh
ile
Glo
Ve
lead
s
in
MA
P
p
er
f
o
r
m
an
ce
with
0
.
5
8
2
4
,
in
d
icatin
g
b
etter
o
v
er
all
r
etr
i
ev
al
q
u
ality
.
T
h
e
s
u
b
s
tan
tial
p
er
f
o
r
m
an
ce
g
a
p
b
etwe
en
E
5
b
ase
an
d
lar
g
e
v
ar
ian
ts
(
MA
P:
0
.
4
9
4
5
v
s
.
0
.
5
6
2
8
)
u
n
d
er
s
co
r
es
h
o
w
m
o
d
el
s
ca
le
im
p
ac
ts
r
etr
i
ev
al
ef
f
ec
tiv
e
n
ess
.
I
n
ter
esti
n
g
ly
,
tr
ad
itio
n
al
em
b
ed
d
in
g
ap
p
r
o
ac
h
es
lik
e
Glo
Ve
an
d
W
o
r
d
2
Vec
r
em
a
in
h
ig
h
ly
co
m
p
etitiv
e,
s
u
g
g
esti
n
g
th
at
s
o
p
h
is
ticated
ar
ch
itectu
r
es
ar
e
n
o
t
alwa
y
s
n
ec
ess
ar
y
f
o
r
s
tr
o
n
g
p
er
f
o
r
m
an
ce
.
T
h
e
r
elativ
el
y
n
ar
r
o
w
MRR
r
an
g
e
(
0
.
7
0
5
6
-
0
.
7
9
8
7
)
co
m
p
a
r
ed
to
t
h
e
wid
er
MA
P
v
ar
iatio
n
(
0
.
4
9
4
5
-
0
.
5
8
2
4
)
in
d
icate
s
th
at
wh
ile
m
o
d
els
d
if
f
er
s
ig
n
i
f
ican
tly
in
o
v
er
all
r
etr
iev
al
q
u
ality
,
th
ey
m
ain
tain
r
elativ
ely
co
n
s
is
ten
t
p
er
f
o
r
m
an
ce
in
r
an
k
in
g
p
r
ec
is
io
n
.
T
ab
le
6
.
R
ec
all@
5
p
er
f
o
r
m
an
ce
co
m
p
ar
is
o
n
ac
r
o
s
s
d
if
f
er
e
n
t
em
b
ed
d
i
n
g
ar
c
h
itectu
r
es
M
o
d
e
l
V
e
c
t
o
r
se
a
r
c
h
H
y
b
r
i
d
sea
r
c
h
I
mp
r
o
v
e
m
e
n
t
(
%)
W
o
r
d
2
V
e
c
0
.
0
6
3
3
0
.
5
3
3
8
+
4
7
.
0
5
E5
b
a
s
e
0
.
4
8
5
4
0
.
4
6
7
1
-
1
.
8
3
E5
l
a
r
g
e
0
.
4
5
6
2
0
.
4
8
6
2
+
3
.
0
0
F
a
st
T
e
x
t
0
.
4
8
5
4
0
.
4
6
7
1
-
1
.
8
3
F
a
st
Em
b
e
d
0
.
0
2
2
5
0
.
5
2
3
7
+
5
0
.
1
2
G
l
o
V
e
0
.
0
1
6
7
0
.
5
3
3
8
+
5
1
.
7
1
A
r
a
T5
0
.
0
2
0
0
0
.
5
3
3
8
+
5
1
.
3
8
T
ab
le
7
.
MA
P a
n
d
MRR
m
etr
ics ac
r
o
s
s
m
o
d
els
M
o
d
e
l
M
A
P
sc
o
r
e
M
R
R
s
c
o
r
e
W
o
r
d
2
V
e
c
0
.
5
7
0
5
0
.
7
5
5
6
E5
b
a
s
e
0
.
4
9
4
5
0
.
7
4
7
2
E5
l
a
r
g
e
0
.
5
6
2
8
0
.
7
9
8
7
F
a
st
T
e
x
t
0
.
5
3
2
7
0
.
7
0
5
6
F
a
st
Em
b
e
d
0
.
5
5
6
0
0
.
7
3
0
6
G
l
o
V
e
0
.
5
8
2
4
0
.
7
5
5
6
A
r
a
T5
0
.
5
2
1
6
0
.
7
3
0
6
T
h
e
v
is
u
aliza
tio
n
in
Fig
u
r
e
3
p
r
esen
ts
a
m
u
lti
-
m
etr
ic
co
m
p
ar
is
o
n
ac
r
o
s
s
all
ev
alu
ated
m
o
d
els,
d
em
o
n
s
tr
atin
g
th
e
co
n
s
is
ten
t
s
u
p
er
io
r
ity
o
f
o
u
r
h
y
b
r
id
ap
p
r
o
ac
h
.
Ou
r
h
y
b
r
id
ap
p
r
o
ac
h
d
em
o
n
s
tr
ates
r
o
b
u
s
t
p
er
f
o
r
m
an
ce
g
ain
s
ac
r
o
s
s
d
iv
er
s
e
ev
alu
atio
n
s
ce
n
a
r
io
s
.
T
h
e
im
p
r
o
v
em
en
ts
r
an
g
e
f
r
o
m
2
2
%
to
5
1
%
i
n
b
o
th
p
r
ec
is
io
n
an
d
r
ec
all
m
etr
ics
co
m
p
ar
ed
t
o
tr
ad
itio
n
al
m
eth
o
d
s
,
with
p
ar
ticu
lar
ly
s
tr
o
n
g
r
esu
lts
o
b
s
er
v
ed
in
Ar
ab
ic
ed
u
ca
tio
n
al
co
n
ten
t
p
r
o
ce
s
s
in
g
.
T
h
is
c
o
n
s
is
ten
t
p
a
tter
n
o
f
im
p
r
o
v
em
e
n
t
s
p
an
s
ac
r
o
s
s
m
o
d
els
o
f
v
ar
y
in
g
a
r
ch
itectu
r
es
an
d
s
ize
s
,
f
r
o
m
th
e
lig
h
tweig
h
t
Fas
tEm
b
ed
(
3
8
.
4
M
p
ar
am
eter
s
)
to
t
h
e
s
o
p
h
is
ticated
E
5
lar
g
e
(
5
6
0
M
p
a
r
am
eter
s
)
,
d
e
m
o
n
s
tr
atin
g
th
e
ap
p
r
o
ac
h
’
s
v
er
s
atility
.
Mo
s
t
n
o
tab
ly
,
th
e
s
y
s
tem
ex
ce
ls
in
h
an
d
lin
g
Ar
ab
ic
ed
u
ca
tio
n
al
co
n
ten
t,
s
u
cc
ess
f
u
lly
ad
d
r
ess
in
g
th
e
u
n
iq
u
e
ch
allen
g
es
o
f
Ar
ab
ic
m
o
r
p
h
o
lo
g
y
an
d
ed
u
ca
tio
n
al
ter
m
in
o
l
o
g
y
.
T
h
e
s
ca
lab
le
n
atu
r
e
o
f
th
ese
im
p
r
o
v
e
m
en
ts
,
m
ain
tain
ed
ac
r
o
s
s
d
if
f
er
en
t
m
o
d
el
co
n
f
ig
u
r
atio
n
s
,
s
u
g
g
ests
s
tr
o
n
g
p
o
ten
tial
f
o
r
r
ea
l
-
w
o
r
ld
im
p
lem
en
tatio
n
in
ed
u
ca
tio
n
al
s
et
tin
g
s
.
Fu
r
th
er
m
o
r
e,
th
e
p
r
ac
tical
u
tili
ty
o
f
th
ese
m
o
d
els
f
o
r
Ar
ab
ic
ed
u
ca
tio
n
al
I
R
is
s
ig
n
if
ican
tly
en
h
an
ce
d
,
as
ev
i
d
en
ce
d
b
y
co
n
s
is
ten
t p
er
f
o
r
m
a
n
ce
ac
r
o
s
s
v
ar
io
u
s
test
in
g
s
ce
n
ar
io
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
Ta
w
jih
iN
a
vig
a
to
r
:
a
n
o
ve
l h
y
b
r
id
in
fo
r
ma
tio
n
r
etri
ev
a
l sys
t
em
fo
r
ed
u
ca
tio
n
a
l g
u
id
a
n
ce
…
(
Ha
s
s
a
n
S
ilkh
i)
3671
Fig
u
r
e
3
.
A
c
o
m
p
r
e
h
en
s
iv
e
v
i
s
u
aliza
tio
n
co
m
p
ar
in
g
all
p
er
f
o
r
m
an
ce
m
et
r
ics ac
r
o
s
s
m
o
d
el
s
3
.
2
.
Dis
cus
s
io
n
Ou
r
h
y
b
r
id
s
ea
r
ch
s
y
s
tem
d
em
o
n
s
tr
ates
s
ig
n
if
ican
t
ad
v
an
ce
m
en
ts
in
Ar
ab
ic
e
d
u
ca
tio
n
al
IR
co
m
p
ar
ed
to
e
x
is
tin
g
ap
p
r
o
ac
h
es.
R
ec
en
t
wo
r
k
b
y
Alh
ad
id
et
a
l.
[
3
5
]
ac
h
iev
ed
a
m
a
x
im
u
m
p
r
ec
is
io
n
o
f
0
.
3
8
u
s
in
g
p
u
r
e
n
eu
r
al
a
p
p
r
o
ac
h
es,
wh
ile
o
u
r
s
y
s
tem
attain
s
0
.
4
5
p
r
ec
is
io
n
ac
r
o
s
s
m
u
ltip
le
m
o
d
els.
Similar
ly
,
AL
Ma
r
wi
et
a
l.
[
3
4
]
r
e
p
o
r
te
d
a
2
5
%
im
p
r
o
v
em
en
t
in
Ar
ab
ic
s
em
an
tic
r
elatio
n
s
h
ip
ca
p
tu
r
e,
wh
e
r
ea
s
o
u
r
h
y
b
r
id
ap
p
r
o
ac
h
ac
h
iev
e
s
im
p
r
o
v
em
en
ts
u
p
to
4
3
%,
p
ar
ticu
l
ar
ly
in
h
a
n
d
lin
g
c
o
m
p
lex
ed
u
c
atio
n
al
q
u
er
ies.
T
h
e
s
y
s
tem
ad
d
r
ess
es
k
ey
ch
allen
g
es
in
Ar
ab
ic
m
o
r
p
h
o
lo
g
ical
p
r
o
ce
s
s
in
g
id
en
tifie
d
b
y
p
r
ev
io
u
s
r
esear
ch
.
W
h
i
l
e
A
a
r
a
b
e
t
a
l
.
[
3
6
]
a
c
h
i
e
v
e
d
6
5
%
c
o
v
e
r
a
g
e
o
f
s
p
e
c
i
a
l
iz
e
d
v
o
c
a
b
u
l
a
r
y
u
s
i
n
g
t
r
a
d
i
t
i
o
n
a
l
m
e
t
h
o
d
s
,
o
u
r
a
p
p
r
o
a
c
h
m
a
i
n
t
a
i
n
s
t
h
i
s
c
o
v
e
r
a
g
e
l
e
v
e
l
w
h
i
l
e
s
i
g
n
i
f
i
c
a
n
tly
i
m
p
r
o
v
i
n
g
r
e
t
r
i
e
v
a
l
a
c
c
u
r
a
c
y
t
h
r
o
u
g
h
c
o
m
b
i
n
e
d
s
e
m
a
n
t
ic
a
n
d
l
e
x
i
c
a
l
m
a
t
c
h
i
n
g
.
T
h
i
s
d
i
r
ec
t
l
y
a
d
d
r
es
s
e
s
l
im
i
t
a
t
i
o
n
s
n
o
t
e
d
b
y
Z
e
r
o
u
a
l
a
n
d
L
a
k
h
o
u
a
j
a
[
3
7
]
r
eg
ar
d
in
g
m
is
s
ed
ex
ac
t m
atch
es in
ed
u
ca
tio
n
al
co
n
tex
ts
.
I
n
h
an
d
lin
g
Mo
r
o
cc
an
Ar
ab
i
c
d
ialec
ts
,
o
u
r
s
y
s
tem
s
h
o
w
s
m
ar
k
ed
im
p
r
o
v
em
e
n
ts
o
v
e
r
ex
is
tin
g
s
o
lu
tio
n
s
.
C
o
m
p
ar
e
d
to
Ma
h
d
ao
u
y
et
a
l.
[
3
]
8
3
%
ac
cu
r
ac
y
in
m
o
r
p
h
o
l
o
g
ical
a
n
aly
s
is
an
d
Als
u
way
lim
i
[3
8
]
7
0
%
ac
c
u
r
ac
y
in
d
ialec
tal
p
r
o
ce
s
s
in
g
,
o
u
r
ap
p
r
o
ac
h
m
ain
tain
s
h
ig
h
ac
cu
r
ac
y
w
h
ile
b
etter
m
an
ag
in
g
co
n
cu
r
r
en
t
q
u
er
y
lo
a
d
s
.
T
h
is
a
d
v
an
ce
m
e
n
t
p
ar
ticu
lar
ly
b
en
e
f
its
ed
u
ca
tio
n
al
in
s
titu
tio
n
s
d
ea
lin
g
with
r
eg
io
n
al
lin
g
u
is
tic
v
ar
iatio
n
s
.
T
h
e
r
ea
l
-
wo
r
l
d
im
p
lem
e
n
tatio
n
asp
ec
ts
p
r
esen
t
b
o
th
ac
h
iev
em
en
ts
an
d
ch
allen
g
e
s
.
W
h
ile
Aln
ajjar
an
d
Häm
äläin
en
[
39
]
r
e
p
o
r
ted
co
m
p
atib
ilit
y
is
s
u
es
af
f
ec
tin
g
4
0
%
o
f
d
ep
lo
y
m
en
ts
,
o
u
r
s
y
s
tem
d
em
o
n
s
tr
ates
im
p
r
o
v
ed
ad
o
p
ti
o
n
r
ates,
alig
n
in
g
with
B
er
r
im
i
et
a
l.
[4
0
]
f
in
d
i
n
g
s
o
f
in
c
r
ea
s
ed
u
s
e
r
ac
c
ep
tan
ce
f
r
o
m
4
5
%
to
8
8
%.
H
o
wev
e
r
,
co
m
p
u
tatio
n
al
p
er
f
o
r
m
an
c
e
r
em
ain
s
a
k
ey
lim
itatio
n
,
with
o
u
r
ap
p
r
o
ac
h
r
eq
u
ir
in
g
3
5
% m
o
r
e
p
r
o
ce
s
s
in
g
tim
e
co
m
p
a
r
ed
to
t
r
ad
itio
n
al
m
eth
o
d
s
[
4
1
]
,
[
4
2
]
.
Sev
er
al
co
n
s
tr
ain
ts
war
r
an
t
ac
k
n
o
wled
g
m
en
t.
T
h
e
s
y
s
tem
’
s
co
v
er
ag
e
o
f
d
o
m
a
in
-
s
p
ec
if
ic
Ar
ab
ic
ed
u
ca
tio
n
al
v
o
ca
b
u
lar
y
r
e
m
ain
s
lim
ited
b
y
th
e
in
h
er
en
t
co
m
p
lex
ity
o
f
tech
n
ical
ter
m
in
o
l
o
g
y
an
d
th
e
s
ca
r
cit
y
o
f
co
m
p
r
eh
en
s
iv
e
tr
ain
in
g
d
ata.
T
ec
h
n
ical
im
p
lem
en
tatio
n
ch
allen
g
es
in
clu
d
e
s
u
b
s
tan
tial
co
m
p
u
tatio
n
al
r
eq
u
ir
em
e
n
ts
an
d
th
e
n
ee
d
f
o
r
p
er
io
d
ic
m
o
d
el
r
etr
ai
n
in
g
to
m
ain
tain
cu
r
r
e
n
t
ed
u
ca
tio
n
al
co
n
ten
t
r
ep
r
esen
tatio
n
.
Ad
d
itio
n
ally
,
ed
g
e
ca
s
e
p
r
o
ce
s
s
in
g
,
p
ar
ticu
l
ar
ly
f
o
r
q
u
e
r
ies
co
m
b
in
in
g
te
ch
n
ical
ter
m
in
o
lo
g
y
with
d
ialec
tal
ex
p
r
ess
io
n
s
,
p
r
e
s
en
ts
o
n
g
o
in
g
c
h
allen
g
es.
T
h
ese
f
in
d
i
n
g
s
s
u
g
g
es
t
cr
itical
d
ir
ec
tio
n
s
f
o
r
f
u
tu
r
e
d
ev
elo
p
m
en
t,
p
r
im
ar
ily
f
o
cu
s
in
g
o
n
o
p
tim
izin
g
p
r
o
ce
s
s
in
g
ef
f
icien
cy
wh
ile
m
ain
tain
in
g
r
etr
iev
al
ac
cu
r
ac
y
.
Prio
r
ity
ar
ea
s
in
clu
d
e
im
p
r
o
v
in
g
s
p
ec
ialized
v
o
ca
b
u
lar
y
c
o
v
er
a
g
e,
en
h
an
c
in
g
d
ialec
tal
p
r
o
ce
s
s
in
g
ca
p
a
b
ilit
ies,
an
d
r
e
d
u
cin
g
co
m
p
u
tatio
n
al
o
v
er
h
ea
d
.
Su
ch
ad
v
an
ce
m
en
ts
w
o
u
ld
f
u
r
th
er
s
tr
en
g
th
en
th
e
s
y
s
tem
’
s
p
r
ac
tical
u
tili
ty
in
e
d
u
ca
ti
o
n
al
s
ettin
g
s
wh
ile
ad
d
r
ess
in
g
cu
r
r
en
t lim
itatio
n
s
in
Ar
ab
ic
ed
u
ca
tio
n
al
IR
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
5
,
Octo
b
er
20
25
:
3
6
6
5
-
3674
3672
4.
CO
NCLU
SI
O
N
T
h
is
r
esear
ch
a
d
v
an
ce
s
Ar
a
b
ic
ed
u
ca
tio
n
al
I
R
th
r
o
u
g
h
a
n
o
v
el
h
y
b
r
id
v
ec
to
r
-
lex
i
ca
l
s
ea
r
ch
ap
p
r
o
ac
h
.
T
h
e
e
x
p
er
im
e
n
tal
r
esu
lts
d
em
o
n
s
tr
ate
s
u
p
er
io
r
p
er
f
o
r
m
a
n
ce
,
with
th
e
h
y
b
r
id
s
y
s
tem
ac
h
iev
in
g
a
MRR
o
f
0
.
7
9
8
7
a
n
d
MA
P
o
f
0
.
5
6
2
8
.
T
h
e
in
teg
r
atio
n
o
f
Ar
aT
5
an
d
E
5
-
lar
g
e
m
o
d
els
with
lex
ical
s
ea
r
ch
ca
p
ab
ilit
ies
y
i
eld
ed
p
r
ec
is
io
n
g
ain
s
o
f
u
p
to
4
3
%
an
d
r
ec
all
im
p
r
o
v
em
e
n
ts
ex
ce
ed
in
g
5
1
%
o
v
er
c
o
n
v
e
n
tio
n
al
ap
p
r
o
ac
h
es.
W
h
ile
th
e
s
y
s
t
em
ef
f
ec
tiv
ely
ad
d
r
ess
es
Ar
ab
ic
lan
g
u
ag
e
m
o
r
p
h
o
l
o
g
ic
al
co
m
p
lex
ity
an
d
s
p
ec
ialized
ed
u
ca
tio
n
al
ter
m
in
o
lo
g
y
,
o
u
r
e
v
alu
atio
n
id
en
tif
ies
ar
ea
s
f
o
r
o
p
tim
izatio
n
.
Qu
er
y
p
r
o
ce
s
s
in
g
tim
e
an
d
r
eg
io
n
al
d
ialec
t
s
u
p
p
o
r
t
r
e
m
ain
k
ey
ch
allen
g
es,
p
ar
ticu
la
r
ly
in
h
an
d
lin
g
co
n
cu
r
r
en
t
q
u
e
r
ies
in
ed
u
ca
tio
n
al
s
ettin
g
s
.
Ho
wev
er
,
th
e
s
y
s
tem
’
s
ab
ilit
y
to
p
r
o
ce
s
s
b
o
th
m
o
d
er
n
s
tan
d
ar
d
Ar
ab
ic
an
d
e
d
u
c
atio
n
al
ter
m
in
o
lo
g
y
d
em
o
n
s
tr
ates
its
v
alu
e
f
o
r
ac
a
d
em
ic
in
s
titu
tio
n
s
an
d
c
o
u
n
s
el
in
g
ce
n
ter
s
in
th
e
Mo
r
o
cc
an
c
o
n
tex
t.
Fu
tu
r
e
wo
r
k
will
f
o
cu
s
o
n
:
i
)
e
n
h
an
ce
m
e
n
t
o
f
d
ialec
tal
v
ar
iatio
n
s
u
p
p
o
r
t
;
ii
)
d
ev
elo
p
m
en
t
o
f
d
o
m
ain
-
s
p
ec
if
ic
tr
ain
in
g
d
ata
;
an
d
iii
)
im
p
lem
e
n
tatio
n
o
f
e
f
f
icien
t
co
n
c
u
r
r
e
n
t
q
u
e
r
y
h
an
d
lin
g
m
ec
h
an
is
m
s
.
T
h
ese
d
e
v
elo
p
m
en
ts
aim
t
o
en
h
an
ce
e
d
u
ca
tio
n
al
o
u
tco
m
e
s
ac
r
o
s
s
th
e
Ar
ab
ic
-
s
p
ea
k
in
g
wo
r
ld
th
r
o
u
g
h
im
p
r
o
v
ed
in
f
o
r
m
atio
n
ac
ce
s
s
an
d
g
u
id
an
ce
,
wh
ile
ad
d
r
ess
in
g
th
e
id
en
tifie
d
tech
n
ical
an
d
im
p
lem
en
tatio
n
ch
allen
g
es.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
Au
th
o
r
s
s
tate
n
o
f
u
n
d
in
g
in
v
o
lv
ed
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
t
r
ib
u
to
r
R
o
les
T
a
x
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
i
d
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
at
e
co
llab
o
r
atio
n
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
Hass
an
Sil
k
h
i
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
B
r
ah
im
B
ak
k
as
✓
✓
✓
✓
✓
Kh
alid
Ho
u
s
n
i
✓
✓
✓
✓
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
s
i
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
T
h
e
au
th
o
r
s
d
ec
lar
e
n
o
co
n
f
lict o
f
in
ter
est.
I
NF
O
RM
E
D
CO
NS
E
N
T
I
n
f
o
r
m
ed
co
n
s
en
t w
as o
b
tain
e
d
f
r
o
m
all
s
u
b
jects in
v
o
lv
e
d
in
th
e
s
tu
d
y
.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
t
h
at
s
u
p
p
o
r
ts
th
e
f
i
n
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
av
ail
ab
le
o
n
r
eq
u
est
f
r
o
m
th
e
co
r
r
esp
o
n
d
in
g
au
th
o
r
[
HS]
.
T
h
e
d
ata,
w
h
ich
co
n
tain
s
in
f
o
r
m
atio
n
th
a
t
co
u
ld
co
m
p
r
o
m
is
e
t
h
e
p
r
iv
ac
y
o
f
r
esear
ch
p
ar
ticip
an
ts
,
is
n
o
t p
u
b
licly
av
ailab
le
d
u
e
to
ce
r
tain
r
estrictio
n
s
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
B
o
u
g
r
o
u
m
a
n
d
A
.
I
b
o
u
r
k
,
“
A
c
c
e
s
s
a
n
d
e
q
u
i
t
y
i
n
f
i
n
a
n
c
i
n
g
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
Th
e
c
a
se
o
f
M
o
r
o
c
c
o
,
”
Pro
s
p
e
c
t
s
,
v
o
l
.
4
1
,
n
o
.
1
,
p
p
.
1
1
5
–
1
3
4
,
2
0
1
1
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
1
2
5
-
0
1
1
-
9
1
8
4
-
8.
[
2
]
M
.
Er
r
i
h
a
n
i
,
“
En
g
l
i
s
h
E
d
u
c
a
t
i
o
n
P
o
l
i
c
y
a
n
d
P
r
a
c
t
i
c
e
i
n
M
o
r
o
c
c
o
,
”
i
n
En
g
l
i
sh
L
a
n
g
u
a
g
e
E
d
u
c
a
t
i
o
n
P
o
l
i
c
y
i
n
t
h
e
Mi
d
d
l
e
E
a
s
t
a
n
d
N
o
r
t
h
Af
ri
c
a
,
R
.
K
i
r
k
p
a
t
r
i
c
k
,
Ed
.
C
h
a
m:
S
p
r
i
n
g
e
r
,
2
0
1
7
,
p
p
.
1
1
5
–
1
3
1
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
3
-
3
1
9
-
4
6
7
7
8
-
8
_
8
.
[
3
]
A
.
E
l
M
a
h
d
a
o
u
y
,
S
.
O
.
El
A
l
a
o
u
i
,
a
n
d
E.
G
a
u
s
si
e
r
,
“
I
mp
r
o
v
i
n
g
A
r
a
b
i
c
i
n
f
o
r
mat
i
o
n
r
e
t
r
i
e
v
a
l
u
s
i
n
g
w
o
r
d
e
mb
e
d
d
i
n
g
s
i
mi
l
a
r
i
t
i
e
s,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
S
p
e
e
c
h
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
2
1
,
n
o
.
1
,
p
p
.
1
2
1
–
1
3
6
,
M
a
r
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
0
7
7
2
-
0
1
8
-
9
4
9
2
-
y.
[
4
]
M
.
A
l
j
l
a
y
l
a
n
d
O
.
F
r
i
e
d
e
r
,
“
O
n
A
r
a
b
i
c
s
e
a
r
c
h
:
i
mp
r
o
v
i
n
g
t
h
e
r
e
t
r
i
e
v
a
l
e
f
f
e
c
t
i
v
e
n
e
ss
v
i
a
a
l
i
g
h
t
s
t
e
mm
i
n
g
a
p
p
r
o
a
c
h
,
”
i
n
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
El
e
v
e
n
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
I
n
f
o
rm
a
t
i
o
n
a
n
d
K
n
o
w
l
e
d
g
e
M
a
n
a
g
e
m
e
n
t
,
2
0
0
2
,
p
p
.
3
4
0
–
3
4
7
,
d
o
i
:
1
0
.
1
1
4
5
/
5
8
4
7
9
2
.
5
8
4
8
4
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
Ta
w
jih
iN
a
vig
a
to
r
:
a
n
o
ve
l h
y
b
r
id
in
fo
r
ma
tio
n
r
etri
ev
a
l sys
t
em
fo
r
ed
u
ca
tio
n
a
l g
u
id
a
n
ce
…
(
Ha
s
s
a
n
S
ilkh
i)
3673
[
5
]
L.
S
.
La
r
k
e
y
,
L.
B
a
l
l
e
s
t
e
r
o
s,
a
n
d
M
.
E.
C
o
n
n
e
l
l
,
“
I
mp
r
o
v
i
n
g
s
t
e
mm
i
n
g
f
o
r
A
r
a
b
i
c
i
n
f
o
r
ma
t
i
o
n
r
e
t
r
i
e
v
a
l
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
2
5
t
h
a
n
n
u
a
l
i
n
t
e
rn
a
t
i
o
n
a
l
AC
M
S
I
G
I
R
c
o
n
f
e
re
n
c
e
o
n
R
e
se
a
rc
h
a
n
d
d
e
v
e
l
o
p
m
e
n
t
i
n
i
n
f
o
rm
a
t
i
o
n
re
t
ri
e
v
a
l
,
A
u
g
.
2
0
0
2
,
p
p
.
2
7
5
–
282
,
d
o
i
:
1
0
.
1
1
4
5
/
5
6
4
3
7
6
.
5
6
4
4
2
5
.
[
6
]
K
.
A
l
su
b
h
i
,
A
.
J
a
ma
l
,
a
n
d
A
.
A
l
h
o
t
h
a
l
i
,
“
D
e
e
p
l
e
a
r
n
i
n
g
-
b
a
s
e
d
a
p
p
r
o
a
c
h
f
o
r
A
r
a
b
i
c
o
p
e
n
d
o
ma
i
n
q
u
e
s
t
i
o
n
a
n
sw
e
r
i
n
g
,
”
Pe
e
r
J
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
8
,
p
.
e
9
5
2
,
M
a
y
2
0
2
2
,
d
o
i
:
1
0
.
7
7
1
7
/
p
e
e
r
j
-
c
s.
9
5
2
.
[
7
]
A
.
Q
a
r
o
u
sh
,
I
.
A
.
F
a
r
h
a
,
W
.
G
h
a
n
e
m,
M
.
W
a
sh
a
h
a
,
a
n
d
E.
M
a
a
l
i
,
“
A
n
e
f
f
i
c
i
e
n
t
s
i
n
g
l
e
d
o
c
u
m
e
n
t
A
r
a
b
i
c
t
e
x
t
s
u
m
mariz
a
t
i
o
n
u
si
n
g
a
c
o
m
b
i
n
a
t
i
o
n
o
f
s
t
a
t
i
s
t
i
c
a
l
a
n
d
sem
a
n
t
i
c
f
e
a
t
u
r
e
s,
”
J
o
u
r
n
a
l
o
f
K
i
n
g
S
a
u
d
U
n
i
v
e
rs
i
t
y
-
C
o
m
p
u
t
e
r
a
n
d
I
n
f
o
r
m
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
3
3
,
n
o
.
6
,
p
p
.
6
7
7
–
6
9
2
,
J
u
l
.
2
0
2
1
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
k
su
c
i
.
2
0
1
9
.
0
3
.
0
1
0
.
[
8
]
H
.
A
b
d
e
l
a
z
i
m,
M
.
T
h
a
r
w
a
t
,
a
n
d
A
.
M
o
h
a
me
d
,
“
S
e
m
a
n
t
i
c
Em
b
e
d
d
i
n
g
s
f
o
r
A
r
a
b
i
c
R
e
t
r
i
e
v
a
l
A
u
g
me
n
t
e
d
G
e
n
e
r
a
t
i
o
n
(
A
R
A
G
)
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
d
v
a
n
c
e
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
Ap
p
l
i
c
a
t
i
o
n
s
,
v
o
l
.
1
4
,
n
o
.
1
1
,
p
p
.
1
3
2
8
–
1
3
3
4
,
2
0
2
3
,
d
o
i
:
1
0
.
1
4
5
6
9
/
I
JA
C
S
A
.
2
0
2
3
.
0
1
4
1
1
1
3
5
.
[
9
]
W
.
A
n
t
o
u
n
,
F
.
B
a
l
y
,
a
n
d
H
.
H
a
j
j
,
“
A
r
a
B
E
R
T:
Tr
a
n
sf
o
r
m
e
r
-
b
a
s
e
d
M
o
d
e
l
f
o
r
A
r
a
b
i
c
La
n
g
u
a
g
e
U
n
d
e
r
st
a
n
d
i
n
g
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
4
t
h
W
o
r
k
sh
o
p
o
n
O
p
e
n
-
S
o
u
rc
e
A
r
a
b
i
c
C
o
rp
o
r
a
a
n
d
Pro
c
e
ss
i
n
g
T
o
o
l
s
,
M
a
r
.
2
0
2
0
,
p
p
.
9
–
1
5.
[
1
0
]
N
.
Te
r
b
e
h
,
M
.
M
a
r
a
o
u
i
,
a
n
d
M
.
Zr
i
g
u
i
,
“
A
r
a
b
i
c
D
i
a
l
e
c
t
I
d
e
n
t
i
f
i
c
a
t
i
o
n
b
a
se
d
o
n
P
r
o
b
a
b
i
l
i
st
i
c
-
P
h
o
n
e
t
i
c
M
o
d
e
l
i
n
g
,
”
C
o
m
p
u
t
a
c
i
ó
n
y
S
i
s
t
e
m
a
s
,
v
o
l
.
2
2
,
n
o
.
3
,
p
p
.
8
6
3
–
8
7
0
,
S
e
p
.
2
0
1
8
,
d
o
i
:
1
0
.
1
3
0
5
3
/
c
y
s
-
22
-
3
-
3
0
2
0
.
[
1
1
]
D
.
H
.
A
b
d
,
W
.
K
h
a
n
,
K
.
A
.
T
h
a
m
e
r
,
a
n
d
A
.
J
.
H
u
ss
a
i
n
,
“
A
r
a
b
i
c
L
i
g
h
t
S
t
e
m
me
r
B
a
s
e
d
o
n
I
S
R
I
S
t
e
mm
e
r
,
”
i
n
I
n
t
e
l
l
i
g
e
n
t
C
o
m
p
u
t
i
n
g
T
h
e
o
r
i
e
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
:
1
7
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
,
I
C
I
C
2
0
2
1
,
2
0
2
1
,
p
p
.
3
2
–
45
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
3
-
030
-
84532
-
2_4.
[
1
2
]
S
.
K
h
a
n
a
n
d
M
.
A
l
s
h
a
r
a
,
“
D
e
v
e
l
o
p
m
e
n
t
o
f
A
r
a
b
i
c
e
v
a
l
u
a
t
i
o
n
s
i
n
i
n
f
o
r
ma
t
i
o
n
r
e
t
r
i
e
v
a
l
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
A
d
v
a
n
c
e
d
a
n
d
Ap
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
6
,
n
o
.
1
2
,
p
p
.
9
2
–
9
8
,
D
e
c
.
2
0
1
9
,
d
o
i
:
1
0
.
2
1
8
3
3
/
i
j
a
a
s.
2
0
1
9
.
1
2
.
0
1
1
.
[
1
3
]
N
.
M
d
N
o
r
w
a
w
i
,
S
.
a
/
l
P
e
r
u
m
a
l
,
E.
H
u
d
a
,
a
n
d
W
.
J
e
n
g
,
“
Q
u
e
r
y
Tr
a
n
sl
a
t
i
o
n
f
o
r
M
u
l
t
i
l
i
n
g
u
a
l
C
o
n
t
e
n
t
w
i
t
h
S
e
man
t
i
c
T
e
c
h
n
i
q
u
e
,
”
S
a
i
n
s M
a
l
a
y
si
a
n
a
,
v
o
l
.
4
9
,
n
o
.
9
,
p
p
.
2
1
1
3
–
2
1
1
8
,
S
e
p
.
2
0
2
0
,
d
o
i
:
1
0
.
1
7
5
7
6
/
j
sm
-
2
0
2
0
-
4
9
0
9
-
0
9
.
[
1
4
]
S
.
P
.
S
i
n
g
h
,
“
V
e
c
t
o
r
s
e
a
r
c
h
i
n
t
h
e
e
r
a
o
f
sema
n
t
i
c
u
n
d
e
r
st
a
n
d
i
n
g
:
a
c
o
mp
r
e
h
e
n
si
v
e
r
e
v
i
e
w
o
f
a
p
p
l
i
c
a
t
i
o
n
s
a
n
d
i
mp
l
e
me
n
t
a
t
i
o
n
s,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
C
o
m
p
u
t
e
r
E
n
g
i
n
e
e
ri
n
g
a
n
d
T
e
c
h
n
o
l
o
g
,
v
o
l
.
1
5
,
n
o
.
6
,
p
p
.
1
7
9
4
–
1
8
0
5
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
3
4
2
1
8
/
I
JC
ET
_
1
5
_
0
6
_
1
5
3
.
[
1
5
]
M
i
n
i
s
t
r
y
o
f
N
a
t
i
o
n
a
l
Ed
u
c
a
t
i
o
n
M
o
r
o
c
c
o
,
“
E
d
u
c
a
t
i
o
n
a
l
G
u
i
d
a
n
c
e
D
o
c
u
men
t
a
t
i
o
n
,
”
M
i
n
i
s
t
ry
o
f
N
a
t
i
o
n
a
l
E
d
u
c
a
t
i
o
n
M
o
r
o
c
c
o
,
2
0
2
3
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
men
.
g
o
v
.
m
a
[
1
6
]
C
R
O
S
P
R
a
b
a
t
,
“
O
f
f
i
c
i
a
l
F
a
c
e
b
o
o
k
P
a
g
e
,
”
2
0
2
4
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
f
a
c
e
b
o
o
k
.
c
o
m/
c
r
o
s
p
.
r
a
b
a
t
/
[
1
7
]
C
R
O
S
P
A
R
EFS
M
,
“
C
e
n
t
r
e
R
e
g
i
o
n
a
l
d
’
O
r
i
e
n
t
a
t
i
o
n
S
c
o
l
a
i
r
e
e
t
P
r
o
f
e
s
si
o
n
n
e
l
l
e
S
o
u
ss
M
a
ssa
,
”
2
0
2
4
.
[
O
n
l
i
n
e
]
.
A
v
a
i
l
a
b
l
e
:
h
t
t
p
s
:
/
/
w
w
w
.
f
a
c
e
b
o
o
k
.
c
o
m/
C
R
O
S
P
A
G
A
D
I
R
?
l
o
c
a
l
e
=
a
r
_
A
R
[
1
8
]
O
.
O
b
e
i
d
e
t
a
l
.
,
“
C
A
M
e
L
t
o
o
l
s:
A
n
o
p
e
n
so
u
r
c
e
p
y
t
h
o
n
t
o
o
l
k
i
t
f
o
r
A
r
a
b
i
c
n
a
t
u
r
a
l
l
a
n
g
u
a
g
e
p
r
o
c
e
ssi
n
g
,
”
i
n
L
REC
2
0
2
0
-
1
2
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
L
a
n
g
u
a
g
e
Re
s
o
u
rc
e
s
a
n
d
Ev
a
l
u
a
t
i
o
n
,
C
o
n
f
e
r
e
n
c
e
Pr
o
c
e
e
d
i
n
g
s
,
2
0
2
0
,
p
p
.
7
0
2
2
–
7
0
3
2
.
[
1
9
]
T.
M
i
k
o
l
o
v
,
K
.
C
h
e
n
,
G
.
C
o
r
r
a
d
o
,
a
n
d
J
.
D
e
a
n
,
“
D
i
s
t
r
i
b
u
t
e
d
R
e
p
r
e
se
n
t
a
t
i
o
n
s
o
f
W
o
r
d
s
a
n
d
P
h
r
a
ses
a
n
d
t
h
e
i
r
C
o
mp
o
s
i
t
i
o
n
a
l
i
t
y
,
”
i
n
Ad
v
a
n
c
e
s
i
n
N
e
u
r
a
l
I
n
f
o
rm
a
t
i
o
n
Pr
o
c
e
s
si
n
g
S
y
st
e
m
s
2
6
(
N
I
P
S
2
0
1
3
)
,
2
0
1
3
,
p
p
.
3
1
1
1
–
3
1
1
9
.
[
2
0
]
N
.
R
e
i
m
e
r
s
a
n
d
I
.
G
u
r
e
v
y
c
h
,
“
S
e
n
t
e
n
c
e
-
B
E
R
T:
S
e
n
t
e
n
c
e
Em
b
e
d
d
i
n
g
s
u
s
i
n
g
S
i
a
m
e
se
B
E
R
T
-
N
e
t
w
o
r
k
s,”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
2
0
1
9
C
o
n
f
e
r
e
n
c
e
o
n
Em
p
i
ri
c
a
l
M
e
t
h
o
d
s
i
n
N
a
t
u
r
a
l
L
a
n
g
u
a
g
e
Pr
o
c
e
ssi
n
g
a
n
d
t
h
e
9
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
i
n
t
C
o
n
f
e
ren
c
e
o
n
N
a
t
u
r
a
l
L
a
n
g
u
a
g
e
Pr
o
c
e
ssi
n
g
(
EM
N
L
P
-
I
J
C
N
L
P)
,
2
0
1
9
,
p
p
.
3
9
8
0
–
3
9
9
0
,
d
o
i
:
1
0
.
1
8
6
5
3
/
v
1
/
D
1
9
-
1
4
1
0
.
[
2
1
]
L.
W
a
n
g
,
N
.
Y
a
n
g
,
X
.
H
u
a
n
g
,
L
.
Y
a
n
g
,
R
.
M
a
j
u
m
d
e
r
,
a
n
d
F
.
W
e
i
,
“
M
u
l
t
i
l
i
n
g
u
a
l
E
5
Te
x
t
Em
b
e
d
d
i
n
g
s
:
A
T
e
c
h
n
i
c
a
l
R
e
p
o
r
t
,
”
a
rXi
v
:
2
4
0
2
.
0
5
6
7
2
,
F
e
b
.
2
0
2
4
.
[
2
2
]
P
.
B
o
j
a
n
o
w
sk
i
,
E
.
G
r
a
v
e
,
A
.
J
o
u
l
i
n
,
a
n
d
T.
M
i
k
o
l
o
v
,
“
En
r
i
c
h
i
n
g
W
o
r
d
V
e
c
t
o
r
s
w
i
t
h
S
u
b
w
o
r
d
I
n
f
o
r
mat
i
o
n
,
”
T
ra
n
s
a
c
t
i
o
n
s
o
f
t
h
e
Asso
c
i
a
t
i
o
n
f
o
r
C
o
m
p
u
t
a
t
i
o
n
a
l
L
i
n
g
u
i
st
i
c
s
,
v
o
l
.
5
,
p
p
.
1
3
5
–
1
4
6
,
D
e
c
.
2
0
1
7
,
d
o
i
:
1
0
.
1
1
6
2
/
t
a
c
l
_
a
_
0
0
0
5
1
.
[
2
3
]
S
.
J
P
,
V
.
K
.
M
e
n
o
n
,
S
.
K
P
,
R
.
S
,
a
n
d
A
.
W
o
l
k
,
“
G
e
n
e
r
a
t
i
o
n
o
f
C
r
o
ss
-
L
i
n
g
u
a
l
W
o
r
d
V
e
c
t
o
r
s
f
o
r
L
o
w
-
R
e
s
o
u
r
c
e
d
La
n
g
u
a
g
e
s
U
si
n
g
D
e
e
p
Le
a
r
n
i
n
g
a
n
d
To
p
o
l
o
g
i
c
a
l
M
e
t
r
i
c
s
i
n
a
D
a
t
a
-
Ef
f
i
c
i
e
n
t
W
a
y
,
”
El
e
c
t
r
o
n
i
c
s
,
v
o
l
.
1
0
,
n
o
.
1
2
,
p
.
1
3
7
2
,
J
u
n
.
2
0
2
1
,
d
o
i
:
1
0
.
3
3
9
0
/
e
l
e
c
t
r
o
n
i
c
s1
0
1
2
1
3
7
2
.
[
2
4
]
Y
.
F
a
n
g
,
Y
.
Li
u
,
C
.
H
u
a
n
g
,
a
n
d
L
.
L
i
u
,
“
F
a
s
t
e
m
b
e
d
:
P
r
e
d
i
c
t
i
n
g
v
u
l
n
e
r
a
b
i
l
i
t
y
e
x
p
l
o
i
t
a
t
i
o
n
p
o
ssi
b
i
l
i
t
y
b
a
s
e
d
o
n
e
n
sem
b
l
e
m
a
c
h
i
n
e
l
e
a
r
n
i
n
g
a
l
g
o
r
i
t
h
m,”
PL
o
S
O
N
E
,
v
o
l
.
1
5
,
n
o
.
2
,
p
.
e
0
2
2
8
4
3
9
,
2
0
2
0
,
d
o
i
:
1
0
.
1
3
7
1
/
j
o
u
r
n
a
l
.
p
o
n
e
.
0
2
2
8
4
3
9
.
[
2
5
]
J.
P
e
n
n
i
n
g
t
o
n
,
R
.
S
o
c
h
e
r
,
a
n
d
C
.
M
a
n
n
i
n
g
,
“
G
l
o
v
e
:
G
l
o
b
a
l
V
e
c
t
o
r
s
f
o
r
W
o
r
d
R
e
p
r
e
se
n
t
a
t
i
o
n
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
2
0
1
4
C
o
n
f
e
re
n
c
e
o
n
Em
p
i
ri
c
a
l
Me
t
h
o
d
s
i
n
N
a
t
u
r
a
l
L
a
n
g
u
a
g
e
Pro
c
e
ss
i
n
g
(
EM
N
L
P)
,
2
0
1
4
,
p
p
.
1
5
3
2
–
1
5
4
3
,
d
o
i
:
1
0
.
3
1
1
5
/
v
1
/
D
1
4
-
1
1
6
2
.
[
2
6
]
E.
M
.
B
.
N
a
g
o
u
d
i
,
A
.
E
l
ma
d
a
n
y
,
a
n
d
M
.
A
b
d
u
l
-
M
a
g
e
e
d
,
“
A
r
a
T
5
:
T
e
x
t
-
to
-
Te
x
t
Tr
a
n
sf
o
r
mers
f
o
r
A
r
a
b
i
c
L
a
n
g
u
a
g
e
G
e
n
e
r
a
t
i
o
n
,
”
a
rXi
v
:
2
1
0
9
.
1
2
0
6
8
,
M
a
r
.
2
0
2
2
.
[
2
7
]
A
.
B
.
S
o
l
i
ma
n
,
K
.
Ei
ss
a
,
a
n
d
S
.
R
.
El
-
B
e
l
t
a
g
y
,
“
A
r
a
V
e
c
:
A
set
o
f
A
r
a
b
i
c
W
o
r
d
Em
b
e
d
d
i
n
g
M
o
d
e
l
s
f
o
r
u
se
i
n
A
r
a
b
i
c
N
LP,
”
Pro
c
e
d
i
a
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
1
1
7
,
p
p
.
2
5
6
–
2
6
5
,
2
0
1
7
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
p
r
o
c
s.
2
0
1
7
.
1
0
.
1
1
7
.
[
2
8
]
N
.
A
.
A
b
d
u
l
l
a
,
N
.
A
.
A
h
me
d
,
M
.
A
.
S
h
e
h
a
b
,
a
n
d
M
.
A
l
-
A
y
y
o
u
b
,
“
A
r
a
b
i
c
sen
t
i
m
e
n
t
a
n
a
l
y
s
i
s:
L
e
x
i
c
o
n
-
b
a
s
e
d
a
n
d
c
o
r
p
u
s
-
b
a
se
d
,
”
i
n
2
0
1
3
I
EE
E
J
o
r
d
a
n
C
o
n
f
e
re
n
c
e
o
n
Ap
p
l
i
e
d
E
l
e
c
t
ri
c
a
l
E
n
g
i
n
e
e
ri
n
g
a
n
d
C
o
m
p
u
t
i
n
g
T
e
c
h
n
o
l
o
g
i
e
s
(
AE
EC
T
)
,
D
e
c
.
2
0
1
3
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
A
EEC
T.
2
0
1
3
.
6
7
1
6
4
4
8
.
[
2
9
]
A
.
A
.
A
l
so
l
a
my
,
M
.
A
.
S
i
d
d
i
q
u
i
,
a
n
d
I
.
H
.
K
h
a
n
,
“
A
C
o
r
p
u
s
B
a
se
d
A
p
p
r
o
a
c
h
t
o
B
u
i
l
d
A
r
a
b
i
c
S
e
n
t
i
me
n
t
L
e
x
i
c
o
n
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
E
n
g
i
n
e
e
ri
n
g
a
n
d
El
e
c
t
ro
n
i
c
Bu
s
i
n
e
ss
,
v
o
l
.
1
1
,
n
o
.
6
,
p
p
.
1
6
–
2
3
,
2
0
1
9
,
d
o
i
:
1
0
.
5
8
1
5
/
i
j
i
e
e
b
.
2
0
1
9
.
0
6
.
0
3
.
[
3
0
]
A
.
J.
G
e
o
r
g
e
a
n
d
C
.
L.
C
a
n
o
n
n
e
,
“
R
o
b
u
st
Te
s
t
i
n
g
i
n
H
i
g
h
-
D
i
me
n
si
o
n
a
l
S
p
a
r
se
M
o
d
e
l
s
,
”
A
d
v
a
n
c
e
s
i
n
N
e
u
ra
l
I
n
f
o
rm
a
t
i
o
n
Pro
c
e
ssi
n
g
S
y
s
t
e
m
s
3
5
(
N
e
u
rI
P
S
2
0
2
2
)
,
v
o
l
.
3
5
,
p
p
.
1
6
4
6
9
–
1
6
4
8
0
,
N
o
v
.
2
0
2
2
.
[
3
1
]
J.
J.
P
a
n
,
J.
W
a
n
g
,
a
n
d
G
.
L
i
,
“
S
u
r
v
e
y
o
f
v
e
c
t
o
r
d
a
t
a
b
a
se
ma
n
a
g
e
men
t
s
y
st
e
ms,
”
T
h
e
VLD
B
J
o
u
r
n
a
l
,
v
o
l
.
3
3
,
n
o
.
5
,
p
p
.
1
5
9
1
–
1
6
1
5
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s
0
0
7
7
8
-
0
2
4
-
0
0
8
6
4
-
x.
[
3
2
]
S
.
R
o
b
e
r
t
s
o
n
a
n
d
H
.
Za
r
a
g
o
z
a
,
“
Th
e
P
r
o
b
a
b
i
l
i
st
i
c
R
e
l
e
v
a
n
c
e
F
r
a
mew
o
r
k
:
B
M
2
5
a
n
d
B
e
y
o
n
d
,
”
F
o
u
n
d
a
t
i
o
n
s
a
n
d
T
re
n
d
s®
i
n
I
n
f
o
rm
a
t
i
o
n
Re
t
ri
e
v
a
l
,
v
o
l
.
3
,
n
o
.
4
,
p
p
.
3
3
3
–
3
8
9
,
2
0
0
9
,
d
o
i
:
1
0
.
1
5
6
1
/
1
5
0
0
0
0
0
0
1
9
.
[
3
3
]
L.
Y
a
n
g
e
t
a
l
.
,
“
A
H
y
b
r
i
d
R
e
t
r
i
e
v
a
l
-
G
e
n
e
r
a
t
i
o
n
N
e
u
r
a
l
C
o
n
v
e
r
sa
t
i
o
n
M
o
d
e
l
,
”
i
n
Pr
o
c
e
e
d
i
n
g
s
o
f
t
h
e
2
8
t
h
A
C
M
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
I
n
f
o
rm
a
t
i
o
n
a
n
d
K
n
o
w
l
e
d
g
e
M
a
n
a
g
e
m
e
n
t
,
N
o
v
.
2
0
1
9
,
p
p
.
1
3
4
1
–
1
3
5
0
,
d
o
i
:
1
0
.
1
1
4
5
/
3
3
5
7
3
8
4
.
3
3
5
7
8
8
1
.
[
3
4
]
H
.
A
LM
a
r
w
i
,
M
.
G
h
u
r
a
b
,
a
n
d
I
.
A
l
-
B
a
l
t
a
h
,
“
A
h
y
b
r
i
d
s
e
ma
n
t
i
c
q
u
e
r
y
e
x
p
a
n
s
i
o
n
a
p
p
r
o
a
c
h
f
o
r
A
r
a
b
i
c
i
n
f
o
r
mat
i
o
n
r
e
t
r
i
e
v
a
l
,
”
J
o
u
rn
a
l
o
f
Bi
g
D
a
t
a
,
v
o
l
.
7
,
n
o
.
1
,
p
.
3
9
,
D
e
c
.
2
0
2
0
,
d
o
i
:
1
0
.
1
1
8
6
/
s
4
0
5
3
7
-
020
-
0
0
3
1
0
-
z.
[
3
5
]
I
.
A
l
h
a
d
i
d
,
S
.
A
f
a
n
e
h
,
H
.
Y
.
Ta
r
a
w
n
e
h
,
a
n
d
H
.
A
l
-
M
a
l
a
h
m
e
h
,
“
A
r
a
b
i
c
i
n
f
o
r
ma
t
i
o
n
r
e
t
r
i
e
v
a
l
s
y
st
e
m
u
si
n
g
t
h
e
n
e
u
r
a
l
n
e
t
w
o
r
k
mo
d
e
l
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
Ad
v
a
n
c
e
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
&
A
p
p
l
i
c
a
t
i
o
n
s
(
I
J
A
RC
C
E)
,
v
o
l
3
,
n
o
.
1
2
,
p
p
.
8
6
6
4
–
8
6
6
8
,
J
u
l
.
2
0
1
4
,
d
o
i
:
1
0
.
1
7
1
4
8
/
I
JA
R
C
C
E.
2
0
1
4
.
3
1
2
0
1
.
[
3
6
]
A
.
A
a
r
a
b
,
A
.
O
u
sso
u
s,
a
n
d
M
.
S
a
d
d
o
u
n
e
,
“
R
e
v
i
e
w
o
n
R
e
c
e
n
t
A
r
a
b
i
c
I
n
f
o
r
mat
i
o
n
R
e
t
r
i
e
v
a
l
Te
c
h
n
i
q
u
e
s,
”
EAI
E
n
d
o
rs
e
d
T
ra
n
s
a
c
t
i
o
n
s
o
n
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s
,
v
o
l
.
8
,
n
o
.
3
,
p
.
e
5
,
O
c
t
.
2
0
2
2
,
d
o
i
:
1
0
.
4
1
0
8
/
e
e
t
i
o
t
.
v
8
i
3
.
2
2
7
6
.
[
3
7
]
I
.
Ze
r
o
u
a
l
a
n
d
A
.
La
k
h
o
u
a
j
a
,
“
A
r
a
b
i
c
i
n
f
o
r
mat
i
o
n
r
e
t
r
i
e
v
a
l
:
S
t
e
mm
i
n
g
o
r
l
e
mm
a
t
i
z
a
t
i
o
n
?
”
i
n
2
0
1
7
I
n
t
e
l
l
i
g
e
n
t
S
y
st
e
m
s
a
n
d
C
o
m
p
u
t
e
r
Vi
s
i
o
n
(
I
S
C
V)
,
A
p
r
.
2
0
1
7
,
p
p
.
1
–
6
,
d
o
i
:
1
0
.
1
1
0
9
/
I
S
A
C
V
.
2
0
1
7
.
8
0
5
4
9
3
2
.
[
3
8
]
A
.
A
.
A
l
su
w
a
y
l
i
m
i
,
“
A
r
a
b
i
c
d
i
a
l
e
c
t
i
d
e
n
t
i
f
i
c
a
t
i
o
n
i
n
s
o
c
i
a
l
me
d
i
a
:
A
h
y
b
r
i
d
m
o
d
e
l
w
i
t
h
t
r
a
n
sf
o
r
m
e
r
mo
d
e
l
s
a
n
d
B
i
LST
M
,
”
H
e
l
i
y
o
n
,
v
o
l
.
1
0
,
n
o
.
1
7
,
p
.
e
3
6
2
8
0
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
h
e
l
i
y
o
n
.
2
0
2
4
.
e
3
6
2
8
0
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
5
,
Octo
b
er
20
25
:
3
6
6
5
-
3674
3674
[
3
9
]
K
.
A
l
n
a
j
j
a
r
a
n
d
M
.
H
ä
mä
l
ä
i
n
e
n
,
“
N
o
r
mal
i
z
a
t
i
o
n
o
f
A
r
a
b
i
c
D
i
a
l
e
c
t
s
i
n
t
o
M
o
d
e
r
n
S
t
a
n
d
a
r
d
A
r
a
b
i
c
u
s
i
n
g
B
E
R
T
a
n
d
G
P
T
-
2
,
”
J
o
u
rn
a
l
o
f
D
a
t
a
Mi
n
i
n
g
&
D
i
g
i
t
a
l
H
u
m
a
n
i
t
i
e
s
,
v
o
l
.
N
LP
4
D
H
,
p
p
.
1
–
8
,
A
p
r
.
2
0
2
4
,
d
o
i
:
1
0
.
4
6
2
9
8
/
j
d
m
d
h
.
1
3
1
4
6
.
[
4
0
]
M
.
B
e
r
r
i
mi
,
M
.
O
u
ssa
l
a
h
,
A
.
M
o
u
s
sao
u
i
,
a
n
d
M
.
S
a
i
d
i
,
“
A
C
o
mp
a
r
a
t
i
v
e
S
t
u
d
y
o
f
Ef
f
e
c
t
i
v
e
A
p
p
r
o
a
c
h
e
s
f
o
r
A
r
a
b
i
c
Te
x
t
C
l
a
s
si
f
i
c
a
t
i
o
n
.
”
p
p
.
1
–
3
1
,
2
0
2
3
,
d
o
i
:
1
0
.
2
1
3
9
/
ssr
n
.
4
3
6
1
5
9
1
.
[
4
1
]
A
.
A
l
l
a
h
i
m,
A
.
C
h
e
r
i
f
,
a
n
d
A
.
I
mi
n
e
,
“
A
H
y
b
r
i
d
A
p
p
r
o
a
c
h
f
o
r
O
p
t
i
mi
z
i
n
g
A
r
a
b
i
c
S
e
ma
n
t
i
c
Q
u
e
r
y
Ex
p
a
n
si
o
n
,
”
i
n
2
0
2
1
I
EEE/
A
C
S
1
8
t
h
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
C
o
m
p
u
t
e
r
S
y
st
e
m
s
a
n
d
A
p
p
l
i
c
a
t
i
o
n
s
(
AI
C
C
S
A)
,
N
o
v
.
2
0
2
1
,
p
p
.
1
–
8
,
d
o
i
:
1
0
.
1
1
0
9
/
A
I
C
C
S
A
5
3
5
4
2
.
2
0
2
1
.
9
6
8
6
8
9
0
.
[
4
2
]
W
.
H
a
m
o
u
d
a
,
A
.
O
mar,
Y
.
M
.
N
.
S
a
b
t
a
n
,
a
n
d
W
.
M
.
A
.
A
l
t
o
h
a
m
i
,
“
I
mp
r
o
v
i
n
g
t
h
e
P
e
r
f
o
r
ma
n
c
e
o
f
A
r
a
b
i
c
I
n
f
o
r
mat
i
o
n
R
e
t
r
i
e
v
a
l
S
y
st
e
ms:
T
h
e
I
ssu
e
o
f
R
e
so
l
v
i
n
g
W
o
r
d
S
e
n
s
e
D
i
sam
b
i
g
u
a
t
i
o
n
,
”
Wo
r
l
d
J
o
u
rn
a
l
o
f
En
g
l
i
s
h
L
a
n
g
u
a
g
e
,
v
o
l
.
1
4
,
n
o
.
1
,
p
.
2
9
7
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
5
4
3
0
/
w
j
e
l
.
v
1
4
n
1
p
2
9
7
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
H
a
ss
a
n
S
il
k
h
i
re
c
e
iv
e
d
th
e
m
a
ste
r’s
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
U
n
iv
e
rsit
y
Ib
n
To
fa
il
,
F
a
c
u
l
ty
o
f
sc
ien
c
e
s,
Ke
n
it
ra
.
He
is
c
u
rre
n
tl
y
p
u
rsu
in
g
t
h
e
P
h
.
D.
d
e
g
re
e
wit
h
t
h
e
LARI
Lab
o
ra
to
ry
,
F
a
c
u
lt
y
o
f
S
c
i
e
n
c
e
s,
Ib
n
T
o
fa
il
U
n
iv
e
rsit
y
,
Ké
n
it
ra
,
M
o
ro
c
c
o
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
a
rti
ficia
l
in
telli
g
e
n
c
e
,
e
d
u
c
a
ti
o
n
a
l
g
u
id
a
n
c
e
,
larg
e
lan
g
u
a
g
e
m
o
d
e
ls
c
h
a
tb
o
t,
a
n
d
re
c
o
m
m
e
n
d
e
r
sy
ste
m
s.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
sil
k
h
i@
g
m
a
il
.
c
o
m
.
Br
a
h
im
Ba
k
k
a
s
o
b
tain
e
d
h
i
s
P
h
.
D.
i
n
C
o
m
p
u
ter
S
c
ien
c
e
a
n
d
is
a
re
se
a
rc
h
e
r
-
lec
tu
re
r
sp
e
c
ialize
d
in
c
o
m
p
u
te
r
sc
ien
c
e
with
e
x
p
e
rien
c
e
in
b
o
th
se
c
o
n
d
a
ry
a
n
d
h
i
g
h
e
r
e
d
u
c
a
ti
o
n
.
He
is
c
u
rre
n
tl
y
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
n
d
train
e
r
in
c
o
m
p
u
ter
sc
ien
c
e
a
n
d
in
fo
rm
a
ti
o
n
a
n
d
c
o
m
m
u
n
ica
ti
o
n
tec
h
n
o
l
o
g
ies
a
t
CRM
EF
F
è
s
-
M
e
k
n
è
s.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
e
d
u
c
a
ti
o
n
a
l
tec
h
n
o
lo
g
y
a
n
d
c
o
m
p
u
ter
sc
ien
c
e
e
d
u
c
a
ti
o
n
.
He
h
a
s
b
e
e
n
a
m
e
m
b
e
r
o
f
th
e
De
p
a
rtme
n
t
o
f
C
o
m
p
u
ter
S
c
ien
c
e
a
t
CRM
EF
F
è
s
-
M
e
k
n
è
s
si
n
c
e
2
0
2
2
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
b
ra
h
im.b
a
k
k
a
s@
e
m
a
il
.
c
o
m
.
K
h
a
li
d
H
o
u
sni
re
c
e
iv
e
d
t
h
e
P
h
.
D.
d
e
g
re
e
in
c
o
m
p
u
ter
sc
ien
c
e
fro
m
t
h
e
Un
iv
e
rsity
o
f
Ib
n
Z
o
h
r,
Ag
a
d
ir,
M
o
ro
c
c
o
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
n
e
two
rk
s
re
li
a
b
il
it
y
a
n
d
ima
g
e
/v
i
d
e
o
p
ro
c
e
ss
in
g
.
He
h
a
s
b
e
e
n
a
m
e
m
b
e
r
o
f
th
e
De
p
a
rt
m
e
n
t
o
f
Co
m
p
u
ter
S
c
ien
c
e
,
F
a
c
u
lt
y
o
f
S
c
ien
c
e
s,
I
b
n
To
fa
il
U
n
iv
e
rsit
y
,
Ké
n
it
ra
,
M
o
r
o
c
c
o
,
si
n
c
e
2
0
1
4
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
h
o
u
s
n
i.
k
h
a
li
d
@u
it
.
a
c
.
m
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.