T
E
L
K
O
M
NIKA
T
elec
o
mm
un
ica
t
io
n Co
m
pu
t
i
ng
E
lect
ro
nics
a
nd
Co
ntr
o
l
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
,
p
p
.
1
7
4
3
~1
754
I
SS
N:
1
6
9
3
-
6
9
3
0
,
DOI
: 1
0
.
1
2
9
2
8
/
T
E
L
KOM
NI
K
A
.
v
23
i
6
.
27135
1743
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//jo
u
r
n
a
l.u
a
d
.
a
c.
id
/in
d
ex
.
p
h
p
/TELK
OM
N
I
K
A
Ada
ptive DIC
O
M
i
m
a
g
es en
cryp
t
io
n using
quad
tre
e and
lig
htw
eig
ht
IT
UB
ee alg
o
rith
m
M
un
t
a
ha
Abdu
lza
hra
H
a
t
e
m
1
,
B
a
ls
a
m
Ab
du
l
k
a
dh
i
m
H
a
m
ee
d
i
2
,
J
a
m
a
l N
a
s
ir
H
a
s
o
o
n
3
,
F
a
ha
d G
ha
lib
Abdu
l
k
a
dh
u
m
4
1
D
e
p
a
r
t
me
n
t
o
f
M
i
ssi
o
n
s a
n
d
C
u
l
t
u
r
a
l
R
e
l
a
t
i
o
n
s
,
M
i
n
i
st
r
y
o
f
H
i
g
h
e
r
Ed
u
c
a
t
i
o
n
a
n
d
S
c
i
e
n
t
i
f
i
c
R
e
se
a
r
c
h
,
B
a
g
h
d
a
d
,
I
r
a
q
2
P
a
l
e
st
i
n
e
H
i
g
h
S
c
h
o
o
l
f
o
r
Ex
c
e
l
l
e
n
c
e
,
M
i
n
i
s
t
r
y
o
f
Ed
u
c
a
t
i
o
n
,
B
a
g
h
d
a
d
,
I
r
a
q
3
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
,
U
n
i
v
e
r
si
t
y
o
f
M
u
st
a
n
s
i
r
i
y
a
h
,
B
a
g
h
d
a
d
,
I
r
a
q
4
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
C
o
mp
u
t
e
r
S
c
i
e
n
c
e
s a
n
d
M
a
t
h
e
mat
i
c
s
,
K
u
f
a
U
n
i
v
e
r
si
t
y
,
N
a
j
a
f
,
I
r
a
q
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
A
p
r
18
,
2
0
2
5
R
ev
i
s
ed
Oct
8
,
2025
A
cc
ep
ted
Oct
19
,
2
0
2
5
T
h
e
e
n
c
r
y
p
ti
o
n
o
f
m
e
d
ica
l
i
m
a
g
e
s p
ro
tec
ts t
h
e
p
riv
a
c
y
o
f
p
a
ti
e
n
t
in
f
o
rm
a
ti
o
n
tran
sm
it
ted
o
v
e
r
n
e
t
w
o
rk
s
a
n
d
c
o
m
m
u
n
ica
ti
o
n
s.
In
th
is
p
a
p
e
r,
a
li
g
h
tw
e
i
g
h
t
e
n
c
r
y
p
ti
o
n
m
e
th
o
d
f
o
r
m
e
d
ica
l
i
m
a
g
e
s
is
p
ro
p
o
se
d
,
c
o
m
b
in
in
g
a
q
u
a
d
tree
-
b
a
se
d
se
g
m
e
n
tatio
n
a
n
d
a
m
o
d
i
f
ied
IT
UBe
e
a
lg
o
rit
h
m
f
o
r
e
n
c
ry
p
ti
o
n
.
A
d
ig
it
a
l
im
a
g
in
g
a
n
d
c
o
m
m
u
n
ica
ti
o
n
s
in
m
e
d
icin
e
(
DICO
M
)
im
a
g
e
is
d
iv
id
e
d
in
to
v
a
riab
le
-
siz
e
b
lo
c
k
s
u
sin
g
th
e
q
u
a
d
tree
tec
h
n
iq
u
e
,
a
n
d
t
h
e
k
e
y
i
s
g
e
n
e
ra
ted
th
ro
u
g
h
a
tw
o
-
d
im
e
n
si
o
n
a
l
He
n
o
n
m
a
p
;
th
e
f
irst
d
ime
n
sio
n
is u
se
d
in
t
h
e
c
o
n
f
u
sio
n
p
ro
c
e
ss
(b
it
p
e
r
m
u
tatio
n
)
o
f
th
e
p
ix
e
l
v
a
lu
e
s,
a
n
d
th
e
se
c
o
n
d
se
q
u
e
n
c
e
is
u
se
d
to
g
e
n
e
ra
te
th
e
k
e
y
sc
h
e
d
u
le
th
r
o
u
g
h
th
e
a
p
p
li
c
a
ti
o
n
ro
u
n
d
f
u
n
c
ti
o
n
.
Dif
f
e
re
n
t
n
u
m
b
e
rs
o
f
r
o
u
n
d
s
a
re
a
p
p
li
e
d
to
th
e
IT
UBe
e
m
e
th
o
d
b
a
se
d
o
n
th
e
siz
e
o
f
th
e
se
g
m
e
n
t
s
in
th
e
q
u
a
d
tree
,
m
a
k
in
g
th
e
a
lg
o
rit
h
m
a
d
a
p
ti
v
e
b
y
in
c
re
a
sin
g
th
e
ro
u
n
d
n
u
m
b
e
r
w
h
e
n
th
e
b
l
o
c
k
siz
e
is
re
d
u
c
e
d
.
T
h
e
m
e
th
o
d
is
u
se
d
a
s
a
li
g
h
t
we
ig
h
t
e
n
c
r
y
p
ti
o
n
m
e
th
o
d
f
o
r
e
n
c
ry
p
ti
n
g
a
ll
b
lo
c
k
s,
u
ti
li
z
in
g
d
if
f
e
re
n
t
ro
u
n
d
n
u
m
b
e
rs
f
o
r
e
a
c
h
b
lo
c
k
siz
e
to
b
a
lan
c
e
th
e
d
e
g
re
e
o
f
c
o
m
p
lex
it
y
w
it
h
th
e
to
t
a
l
ti
m
e
c
o
n
su
m
p
ti
o
n
o
f
th
e
DICO
M
im
a
g
e
.
T
h
e
re
su
lt
re
in
f
o
rc
e
s
th
e
p
ro
p
o
s
e
d
m
e
th
o
d
,
w
h
ich
p
r
o
d
u
c
e
d
a
h
ig
h
m
e
a
n
sq
u
a
re
d
e
rro
r
(
MSE
)
b
e
tw
e
e
n
th
e
DICO
M
im
a
g
e
a
n
d
th
e
E
n
c
ry
p
ted
On
e
,
a
n
d
a
lo
w
e
r
p
e
a
k
sig
n
a
l
-
to
-
n
o
ise
ra
ti
o
(
P
S
NR
)
.
T
h
e
p
ro
p
o
se
d
g
e
n
e
ra
ted
n
u
m
b
e
rs
w
e
re
a
lso
tes
ted
u
si
n
g
n
a
ti
o
n
a
l
in
stit
u
te
o
f
sta
n
d
a
rd
s
a
n
d
tec
h
n
o
l
o
g
y
(
NIS
T
)
to
e
v
a
lu
a
te t
h
e
ra
n
d
o
m
n
e
ss
.
K
ey
w
o
r
d
s
:
DI
C
OM
i
m
ag
e
Hen
o
n
m
ap
I
T
U
B
ee
L
i
g
h
t
w
ei
g
h
t e
n
cr
y
p
tio
n
Me
d
ical
i
m
a
g
e
Qu
ad
tr
ee
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
:
Mu
n
tah
a
A
b
d
u
lza
h
r
a
Hate
m
Dep
ar
t
m
en
t o
f
Mis
s
io
n
s
an
d
C
u
lt
u
r
al
R
elatio
n
s
,
Mi
n
is
tr
y
o
f
Hig
h
er
E
d
u
ca
tio
n
a
n
d
Scien
t
if
ic
R
esear
ch
Al
-
R
u
s
a
f
a
-
B
a
g
h
d
ad
,
I
r
aq
E
m
ail:
m
u
n
ta
h
a.
h
a
te
m
@
s
cr
d
.
g
ate
-
g
o
v
.
iq
1.
I
NT
RO
D
UCT
I
O
N
Me
d
ical
i
m
a
g
i
n
g
,
e
n
co
m
p
a
s
s
i
n
g
co
m
p
u
ted
to
m
o
g
r
ap
h
y
(
C
T
)
,
m
ag
n
etic
r
e
s
o
n
a
n
ce
i
m
ag
i
n
g
(
MRI)
,
u
ltra
s
o
u
n
d
,
an
d
X
-
r
a
y
s
,
p
la
y
s
a
p
iv
o
tal
p
ar
t
in
d
iag
n
o
s
i
n
g
a
d
iv
er
s
e
s
p
ec
tr
u
m
o
f
d
is
ea
s
es.
T
h
e
r
ap
id
ad
v
an
ce
m
en
t
o
f
i
n
ter
n
et
tec
h
n
o
lo
g
y
h
a
s
m
ad
e
it
ea
s
ier
to
s
h
ar
e
a
n
d
m
o
v
e
lar
g
e
a
m
o
u
n
ts
o
f
m
ed
ical
d
ata
q
u
ick
l
y
an
d
ea
s
il
y
.
T
h
is
is
p
ar
ticu
lar
l
y
i
m
p
o
r
tan
t
f
o
r
th
e
g
r
o
w
t
h
o
f
tele
m
ed
ici
n
e
s
er
v
ices,
s
u
ch
as
telec
o
n
s
u
ltatio
n
an
d
tele
s
u
r
g
e
r
y
[
1
]
.
Secu
r
e
co
m
m
u
n
icatio
n
ch
an
n
el
s
ar
e
n
ec
es
s
ar
y
f
o
r
d
o
cto
r
s
,
p
at
ien
ts
,
an
d
s
ca
n
n
i
n
g
ce
n
ter
s
to
s
h
ar
e
m
ed
ical
i
m
a
g
es
s
o
th
at
p
ati
en
ts
’
p
r
iv
ate
i
n
f
o
r
m
atio
n
is
n
o
t
leak
ed
d
u
r
in
g
tr
an
s
m
is
s
io
n
[
2
]
.
A
ttac
k
er
s
m
a
y
ta
m
p
er
w
it
h
tr
an
s
m
it
ted
m
ed
ical
i
m
a
g
es,
lead
i
n
g
to
in
co
r
r
ec
t
d
iag
n
o
s
e
s
,
w
h
ic
h
u
n
d
er
s
co
r
es
th
e
c
h
alle
n
g
e
o
f
m
ai
n
tai
n
i
n
g
co
n
f
id
en
ti
alit
y
a
n
d
in
te
g
r
it
y
d
u
r
in
g
i
m
a
g
e
tr
an
s
m
is
s
io
n
[
3
]
,
[
4
]
.
T
r
an
s
f
er
o
f
m
ed
ical
i
m
a
g
es
o
v
er
p
u
b
lic
n
et
w
o
r
k
s
is
cr
i
tical,
s
o
it
r
eq
u
ir
es
e
x
tr
a
atte
n
tio
n
,
an
d
s
ta
n
d
ar
d
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
:
1
7
4
3
-
1
754
1744
m
et
h
o
d
s
(
cr
y
p
to
g
r
ap
h
y
,
s
teg
a
n
o
g
r
ap
h
y
,
a
n
d
w
ater
m
ar
k
i
n
g
)
ar
e
u
s
ed
f
o
r
th
is
.
T
h
e
f
ield
is
r
ap
id
ly
ev
o
l
v
in
g
as
m
ed
ical
co
m
p
an
ies co
n
s
is
te
n
tl
y
in
tr
o
d
u
ce
m
o
r
e
m
ed
ical
i
m
a
g
in
g
d
ev
ices a
n
d
n
e
w
tec
h
n
o
l
o
g
ies
[
5
]
.
A
d
iv
er
s
e
r
an
g
e
o
f
m
ed
ical
i
m
ag
in
g
tec
h
n
o
lo
g
ies
w
o
r
ld
w
id
e
e
n
ab
les
p
h
y
s
ician
s
to
o
b
tain
h
i
g
h
-
q
u
a
lit
y
i
m
a
g
es,
w
h
ic
h
ar
e
cr
itical
f
o
r
ac
cu
r
ate
d
is
ea
s
e
d
iag
n
o
s
is
[
5
]
,
[
6
]
.
Ho
w
e
v
er
,
th
e
ac
ce
s
s
ib
ili
t
y
o
f
th
is
m
ed
ical
i
n
f
o
r
m
atio
n
w
it
h
o
u
t
o
w
n
er
ap
p
r
o
v
al
p
o
s
es
s
ev
er
al
co
n
ce
r
n
s
,
in
cl
u
d
i
n
g
s
ec
u
r
it
y
,
p
r
o
o
f
o
f
o
w
n
er
s
h
ip
,
an
d
co
p
y
r
i
g
h
t
p
r
o
tectio
n
.
Me
d
ical
i
m
a
g
es
h
a
v
e
a
lo
t
m
o
r
e
s
en
s
itiv
e
an
d
i
m
p
o
r
tan
t
i
n
f
o
r
m
at
io
n
t
h
an
r
eg
u
lar
i
m
ag
e
s
[
7
]
.
E
v
er
y
p
ix
el
i
n
t
h
ese
p
ictu
r
es
is
v
er
y
i
m
p
o
r
tan
t
f
o
r
d
iag
n
o
s
i
s
,
a
n
d
ch
a
n
g
in
g
a
n
y
o
f
t
h
e
m
co
u
ld
lead
to
w
r
o
n
g
d
iag
n
o
s
e
s
[
8
]
.
I
t
is
h
ar
d
to
k
e
ep
th
ese
i
m
a
g
es
s
a
f
e
b
ec
au
s
e
th
e
y
d
o
n
o
t
li
k
e
b
ei
n
g
c
h
a
n
g
ed
as
m
u
c
h
as
le
s
s
s
en
s
iti
v
e
i
m
a
g
es
d
o
.
Me
d
ical
i
m
a
g
es
t
y
p
icall
y
co
m
p
r
i
s
e
t
wo
p
ar
ts
:
th
e
r
e
g
io
n
o
f
n
o
in
ter
est
(
R
O
NI
)
an
d
t
h
e
r
eg
io
n
o
f
i
n
ter
est
(
R
OI
)
[
9
]
-
[
1
1
]
.
T
h
e
R
OI
,
w
h
ic
h
h
a
s
i
m
p
o
r
ta
n
t
an
d
s
e
n
s
iti
v
e
d
ata
th
at
is
n
ee
d
ed
f
o
r
d
iag
n
o
s
i
s
,
m
u
s
t
n
o
t
b
e
ch
a
n
g
e
d
.
T
h
e
R
ONI
,
o
n
t
h
e
o
th
er
h
a
n
d
,
s
h
o
w
s
t
h
e
b
ac
k
g
r
o
u
n
d
o
f
t
h
e
i
m
ag
e
an
d
d
o
es
n
o
t h
a
v
e
an
y
i
m
p
o
r
ta
n
t in
f
o
r
m
atio
n
,
s
o
it c
an
b
e
ch
a
n
g
e
d.
T
h
e
m
ed
ical
d
iag
n
o
s
is
p
r
o
ce
s
s
is
e
s
s
e
n
tial
f
o
r
d
eter
m
i
n
i
n
g
t
h
e
t
y
p
e
o
f
f
u
t
u
r
e
tr
ea
t
m
en
t,
wh
ich
o
f
te
n
d
ep
en
d
s
o
n
t
h
e
tr
an
s
m
itted
m
ed
ical
i
m
a
g
es
[
1
2
]
,
esp
ec
iall
y
i
f
t
h
e
p
r
ese
n
ted
ca
s
e
o
r
ig
i
n
ates
f
r
o
m
g
eo
g
r
ap
h
ical
l
y
d
i
s
ta
n
t
p
lace
s
,
m
a
k
i
n
g
it
n
ec
es
s
ar
y
to
tr
an
s
m
it
it
d
i
g
itall
y
.
T
h
er
ef
o
r
e,
it
m
u
s
t
b
e
p
r
o
tecte
d
f
r
o
m
m
an
ip
u
latio
n
an
d
f
o
r
g
er
y
.
T
h
ese
asp
ec
ts
ar
e
co
n
s
id
er
e
d
(
p
u
r
ely
m
ed
ical)
,
an
d
w
e
d
o
n
o
t ig
n
o
r
e
th
e
le
g
al
asp
ec
t
th
at
r
eq
u
ir
e
s
d
o
cto
r
s
an
d
h
ea
lth
d
ep
ar
t
m
e
n
t
s
to
m
ai
n
t
ain
t
h
e
co
n
f
id
en
t
ialit
y
o
f
i
n
f
o
r
m
atio
n
[
1
3
]
.
Fro
m
th
is
s
ta
n
d
p
o
in
t,
t
h
e
i
n
f
o
r
m
ati
o
n
(
i
m
a
g
es)
m
u
s
t
b
e
p
r
o
tec
ted
d
u
r
in
g
t
h
e
tr
a
n
s
m
is
s
io
n
p
r
o
ce
s
s
to
co
m
p
l
y
w
it
h
th
e
r
elev
a
n
t
r
eg
u
latio
n
s
an
d
la
w
s
[
1
4
]
.
Ma
n
y
i
m
ag
e
s
ar
e
ex
p
o
s
ed
to
m
an
y
r
is
k
s
th
r
o
u
g
h
th
e
ir
tr
an
s
f
er
b
et
w
ee
n
d
if
f
er
en
t
n
et
w
o
r
k
s
an
d
co
m
m
u
n
icatio
n
s
s
y
s
te
m
s
,
in
ten
t
io
n
all
y
,
s
u
ch
as
h
ac
k
in
g
o
p
er
atio
n
s
,
o
r
u
n
i
n
te
n
tio
n
all
y
,
s
u
ch
a
s
g
litch
es in
tr
a
n
s
m
i
s
s
io
n
p
r
o
ce
s
s
es o
r
lo
s
s
o
f
d
ata
d
u
r
i
n
g
tr
an
s
m
i
s
s
io
n
[
1
5
]
.
T
h
er
ef
o
r
e,
th
ese
i
m
ag
e
s
m
u
s
t
b
e
p
r
o
tecte
d
in
w
a
y
s
th
at
li
m
it
t
h
e
r
is
k
s
o
f
lo
s
s
o
r
p
ir
ac
y
w
h
e
n
tr
an
s
m
i
tted
.
E
n
cr
y
p
tio
n
[
1
6
]
is
o
n
e
o
f
th
e
m
o
s
t i
m
p
o
r
tan
t
w
a
y
s
to
k
ee
p
th
e
s
e
i
m
ag
e
s
s
af
e.
T
h
is
p
ap
er
ex
a
m
i
n
es
t
h
e
co
m
b
in
atio
n
o
f
q
u
ad
tr
ee
d
ec
o
m
p
o
s
itio
n
w
i
th
th
e
n
o
v
e
l
I
T
UB
ee
en
cr
y
p
tio
n
alg
o
r
ith
m
a
s
a
p
r
o
m
i
s
i
n
g
m
e
th
o
d
f
o
r
e
n
h
a
n
ci
n
g
t
h
e
s
ec
u
r
it
y
o
f
m
ed
ical
i
m
a
g
es
in
d
ig
ital
co
n
te
x
ts
.
T
h
is
m
et
h
o
d
ai
m
s
to
m
ak
e
s
u
r
e
t
h
at
s
en
s
iti
v
e
m
ed
ical
d
ata
s
to
r
ed
o
r
s
en
t
elec
tr
o
n
icall
y
is
b
etter
p
r
o
tecte
d
b
y
u
s
i
n
g
q
u
ad
tr
ee
’
s
ab
ili
t
y
to
d
iv
id
e
i
m
ag
e
s
i
n
to
h
ier
ar
ch
ical
s
tr
u
c
tu
r
es
a
n
d
I
T
UB
ee
’
s
s
tr
o
n
g
e
n
cr
y
p
tio
n
f
ea
tu
r
es.
q
u
ad
tr
ee
’
s
ab
ilit
y
to
ef
f
icie
n
t
l
y
o
r
g
an
ize
i
m
a
g
e
d
ata
h
ier
ar
ch
icall
y
w
o
r
k
s
w
ell
w
it
h
I
T
UB
ee
’
s
ab
ilit
y
to
en
cr
y
p
t
d
ata,
w
h
ic
h
i
m
p
r
o
v
es
th
e
i
n
te
g
r
it
y
an
d
co
n
f
id
e
n
tialit
y
o
f
m
ed
ical
i
m
a
g
e
s
.
T
h
is
co
m
b
in
ed
m
et
h
o
d
n
o
t
o
n
l
y
m
ak
e
s
s
u
r
e
th
at
m
ed
ical
i
m
ag
e
s
ar
e
s
to
r
ed
an
d
s
en
t
s
ec
u
r
el
y
,
b
u
t
it
al
s
o
m
ee
ts
t
h
e
i
m
p
o
r
tan
t
n
ee
d
f
o
r
s
tr
o
n
g
e
n
cr
y
p
tio
n
m
et
h
o
d
s
in
h
ea
lt
h
ca
r
e
d
ata
m
an
a
g
e
m
en
t.
2.
RE
L
AT
E
D
WO
RK
S
T
h
e
m
o
s
t
i
m
p
o
r
tan
t
s
c
h
o
lar
l
y
w
o
r
k
ab
o
u
t
o
u
r
r
esear
ch
is
co
v
er
ed
in
th
is
s
ec
tio
n
.
B
y
i
n
clu
d
i
n
g
a
s
ec
u
r
e
ta
m
p
er
i
n
g
d
etec
tio
n
an
d
lo
s
s
less
r
ec
o
v
er
y
m
ec
h
an
i
s
m
,
th
e
p
a
p
er
in
[
1
7
]
s
u
g
g
e
s
ts
a
w
a
y
to
s
a
f
e
g
u
ar
d
m
ed
ical
i
m
a
g
es
tr
an
s
m
itted
to
th
e
clo
u
d
.
T
h
e
m
eth
o
d
u
tili
ze
s
a
b
in
ar
y
n
u
m
b
er
s
y
s
te
m
ar
r
an
g
ed
in
a
s
p
ec
i
f
ic
o
r
d
er
.
I
t
f
ir
s
t
f
in
d
s
th
e
R
OI
in
th
e
m
ed
ical
i
m
ag
e
an
d
th
e
n
b
r
ea
k
s
it
u
p
in
to
b
lo
ck
s
th
at
d
o
n
o
t
o
v
er
lap
.
J
P
E
G
-
L
S c
o
m
p
r
es
s
io
n
i
s
u
s
ed
to
en
c
o
d
e
th
e
p
ictu
r
es in
t
h
ese
b
lo
ck
s
.
T
h
is
m
et
h
o
d
w
o
r
k
s
esp
ec
ial
l
y
w
ell
f
o
r
m
ed
ical
i
m
a
g
es.
Z
h
en
g
e
t
a
l
.
[
1
8
]
,
t
ac
k
l
e
d
th
e
i
s
s
u
e
o
f
s
t
o
r
in
g
l
a
r
g
e
am
o
u
n
t
s
o
f
m
e
d
i
c
al
im
ag
e
d
a
t
a
b
y
u
s
in
g
d
e
o
x
y
r
i
b
o
n
u
cl
e
i
c
a
c
i
d
(
DNA
)
a
s
an
e
f
f
e
c
t
iv
e
w
ay
t
o
s
to
r
e
d
a
t
a
.
I
t
p
r
es
en
ts
an
i
n
n
o
v
a
t
iv
e
D
NA
-
b
a
s
ed
c
o
m
p
r
e
s
s
i
o
n
a
n
d
en
c
r
y
p
t
i
o
n
al
g
o
r
it
h
m
s
p
ec
if
i
c
al
ly
d
es
ig
n
e
d
f
o
r
m
e
d
i
c
a
l
im
ag
es
.
T
h
e
a
lg
o
r
i
t
h
m
u
s
es
th
e
f
a
ct
t
h
at
m
e
d
ic
a
l
im
ag
es
h
av
e
h
o
m
o
g
en
e
o
u
s
p
ix
e
ls
,
es
p
e
c
i
al
ly
in
th
ei
r
b
it
-
p
l
an
e
d
e
c
o
m
p
o
s
it
i
o
n
s
,
t
o
g
e
t
r
i
d
o
f
r
e
d
u
n
d
a
n
cy
d
u
r
in
g
c
o
m
p
r
es
s
io
n
.
T
h
e
p
r
o
p
o
s
e
d
D
NA
-
b
as
e
d
q
u
a
d
t
r
e
e
d
e
c
o
m
p
o
s
i
ti
o
n
a
lg
o
r
i
t
h
m
t
r
a
n
s
f
o
r
m
s
th
e
e
n
ti
r
e
im
ag
e
in
t
o
a
s
e
q
u
en
c
e
o
f
f
o
u
r
D
NA
n
u
c
l
e
o
t
i
d
e
s
,
f
a
c
il
i
t
a
tin
g
th
e
r
et
r
i
ev
a
l
o
f
th
e
o
r
ig
in
a
l
im
ag
e
th
r
o
u
g
h
d
e
c
o
d
i
n
g
.
T
h
e
D
NA
-
b
ased
ad
v
an
ce
d
en
cr
y
p
tio
n
s
tan
d
ar
d
(
A
E
S)
alg
o
r
it
h
m
i
n
cip
h
er
b
lo
ck
ch
ai
n
in
g
(
C
B
C
)
m
o
d
e
e
n
cr
y
p
ts
t
h
e
s
eq
u
en
ce
s
t
h
at
co
m
e
f
r
o
m
t
h
e
co
m
p
r
ess
io
n
p
r
o
ce
s
s
to
m
ak
e
t
h
e
m
s
a
f
er
f
r
o
m
b
ad
u
s
e.
R
ev
a
n
n
a
an
d
Kesh
a
v
a
m
u
r
t
h
y
[
1
9
]
,
d
is
cu
s
s
es
t
h
e
d
if
f
ic
u
lt
y
o
f
s
ec
u
r
el
y
m
a
n
a
g
in
g
h
ea
lth
ca
r
e
d
ata
th
at
is
s
to
r
ed
i
n
t
h
e
clo
u
d
b
ec
au
s
e
m
o
r
e
an
d
m
o
r
e
p
eo
p
le
ar
e
u
s
i
n
g
s
m
ar
t
eHe
al
th
ca
r
e,
w
h
ic
h
i
s
m
ad
e
p
o
s
s
ib
le
b
y
I
o
T
an
d
b
ig
d
ata
tec
h
n
o
lo
g
y
.
Hea
lth
ca
r
e
f
ac
ili
ties
ar
e
co
n
ce
r
n
ed
ab
o
u
t
s
e
n
s
iti
v
e
d
ata
lea
k
s
,
ev
e
n
t
h
o
u
g
h
t
h
e
clo
u
d
is
a
f
a
n
ta
s
tic
w
a
y
to
s
to
r
e
an
d
s
h
ar
e
a
lo
t
o
f
h
ea
lt
h
ca
r
e
d
ata.
T
h
ey
en
cr
y
p
t
t
h
is
d
ata
b
ef
o
r
e
tr
an
s
f
er
r
in
g
it
to
th
e
clo
u
d
to
p
r
o
tect
it.
Ho
w
e
v
er
,
tr
ad
itio
n
al
e
n
cr
y
p
tio
n
m
a
k
es
it
d
if
f
ic
u
lt
f
o
r
s
o
p
h
is
ti
ca
ted
ap
p
licatio
n
s
,
s
u
c
h
as
s
i
m
ilar
it
y
r
an
g
e
q
u
er
i
es,
to
w
o
r
k
w
it
h
en
cr
y
p
ted
d
a
ta
s
to
r
ed
in
th
e
clo
u
d
.
T
o
a
d
d
r
ess
th
i
s
li
m
itatio
n
,
th
e
p
ap
er
in
tr
o
d
u
ce
s
an
e
f
f
ic
ien
t
p
r
iv
ac
y
-
p
r
eser
v
i
n
g
s
i
m
il
ar
it
y
r
an
g
e
q
u
er
y
(
E
P
Si
m
)
s
ch
e
m
e.
I
n
o
r
d
er
to
p
r
o
v
id
e
s
elec
tiv
e
s
ec
u
r
it
y
,
t
h
e
s
c
h
e
m
e
b
eg
i
n
s
b
y
i
n
tr
o
d
u
cin
g
a
m
o
d
if
ied
a
s
y
m
m
et
r
ic
s
ca
lar
-
p
r
o
d
u
ct
-
p
r
eser
v
in
g
en
cr
y
p
t
io
n
(
A
SP
E
)
tech
n
iq
u
e.
Af
ter
t
h
at,
it
u
s
es
a
q
u
ad
tr
ee
r
ep
r
esen
t
atio
n
f
o
r
th
e
d
ata
an
d
co
m
es
u
p
w
ith
a
n
al
g
o
r
ith
m
b
ased
o
n
a
f
il
tr
atio
n
co
n
d
itio
n
to
d
o
ef
f
icie
n
t
s
i
m
ilar
it
y
r
an
g
e
q
u
er
ies
o
n
t
h
i
s
tr
ee
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
A
d
a
p
tive
DI
C
OM ima
g
es e
n
cryp
tio
n
u
s
in
g
q
u
a
d
tr
ee
a
n
d
li
g
h
tw
eig
h
t
…
(
Mu
n
ta
h
a
A
b
d
u
lz
a
h
r
a
Ha
tem
)
1745
s
tr
u
ct
u
r
e.
T
h
e
E
P
Sim
s
c
h
e
m
e
u
lti
m
atel
y
co
m
b
i
n
es
t
h
e
m
o
d
if
ied
A
SP
E
m
et
h
o
d
an
d
th
e
Qu
ad
s
ec
to
r
tr
ee
to
m
ak
e
i
t
p
o
s
s
ib
le
to
s
af
el
y
an
d
q
u
ick
l
y
s
ea
r
ch
f
o
r
s
i
m
ilar
r
an
g
es
i
n
en
cr
y
p
ted
clo
u
d
-
s
to
r
ed
h
ea
lt
h
ca
r
e
d
ata.
A
th
o
r
o
u
g
h
s
ec
u
r
it
y
a
n
al
y
s
i
s
o
f
t
h
e
p
r
o
p
o
s
ed
E
P
Sim
s
ch
e
m
e
s
h
o
w
s
t
h
at
it i
s
s
tr
o
n
g
.
T
h
e
s
tu
d
y
’
s
r
ec
o
m
m
en
d
ed
ap
p
r
o
ac
h
in
[
2
0
]
is
p
r
ed
icate
d
o
n
en
cr
y
p
tin
g
g
r
a
y
s
ca
le
d
o
cu
m
en
t
i
m
a
g
es
u
s
i
n
g
b
o
th
f
u
ll
a
n
d
p
ar
tial
en
cr
y
p
tio
n
tec
h
n
iq
u
es.
T
h
e
i
m
a
g
e
is
f
ir
s
t
d
i
v
id
ed
in
to
b
lo
ck
s
u
s
i
n
g
a
Qu
ad
-
tr
ee
d
ec
o
m
p
o
s
itio
n
b
ased
o
n
b
l
o
ck
v
ar
ian
ce
to
p
er
f
o
r
m
p
ar
tial
e
n
cr
y
p
tio
n
.
W
h
ile
s
o
m
e
b
lo
ck
s
w
it
h
u
n
i
f
o
r
m
p
ix
e
l
lev
els
ar
e
co
n
s
id
er
ed
tr
iv
ial,
o
th
er
s
ar
e
co
n
s
id
er
ed
s
u
b
s
t
an
tial.
A
1
D
S
k
e
w
te
n
t
c
h
a
o
tic
m
ap
i
s
u
s
ed
to
p
er
m
u
te
t
h
e
p
ix
els
o
f
t
h
e
i
m
p
o
r
tan
t
b
lo
ck
s
.
T
o
im
p
r
o
v
e
s
ec
u
r
it
y
,
a
2
D
Hen
o
n
m
ap
is
u
s
ed
f
o
r
ad
d
itio
n
al
p
er
m
u
tatio
n
,
cr
ea
tin
g
in
p
u
t f
o
r
to
tal
en
cr
y
p
tio
n
.
T
h
e
s
tu
d
y
i
n
[
2
1
]
d
etails
th
e
cr
ea
tio
n
o
f
a
s
p
ec
ialized
o
n
t
o
lo
g
y
t
h
at
m
a
k
e
s
it
p
o
s
s
ib
le
to
class
i
f
y
o
b
j
ec
ts
in
m
ed
ical
i
m
a
g
es
u
s
i
n
g
a
m
u
ltil
a
y
er
n
e
u
r
al
n
et
w
o
r
k
.
I
n
o
r
d
er
to
p
r
o
ce
s
s
lar
g
e
d
atasets
as
e
f
f
icie
n
tl
y
as
p
o
s
s
ib
le
an
d
en
ab
le
f
aste
r
im
a
g
e
p
r
o
ce
s
s
in
g
,
th
e
s
t
u
d
y
u
s
es
t
h
e
Ma
p
R
ed
u
ce
p
ar
ad
ig
m
i
n
a
clo
u
d
en
v
ir
o
n
m
e
n
t.
A
d
d
itio
n
all
y
,
to
s
tr
ea
m
lin
e
C
lo
u
d
n
o
d
e
co
m
m
u
n
ica
tio
n
a
n
d
r
ed
u
ce
p
r
e
-
p
r
o
ce
s
s
i
n
g
ti
m
e,
a
d
ata
co
m
p
r
es
s
io
n
m
et
h
o
d
b
ased
o
n
d
ed
u
p
licatio
n
i
s
p
r
o
p
o
s
ed
.
T
h
e
s
u
g
g
es
ted
r
e
m
ed
y
u
n
d
er
g
o
es
test
i
n
g
i
n
a
m
u
ltis
ite
clo
u
d
en
v
ir
o
n
m
e
n
t,
s
h
o
w
ca
s
i
n
g
i
m
p
r
o
v
ed
d
ata
tr
an
s
f
er
o
p
ti
m
izatio
n
,
w
it
h
an
av
er
ag
e
ti
m
e
en
h
a
n
ce
m
en
t o
f
2
7
%.
P
ad
m
av
a
ti
an
d
Me
s
h
r
a
m
[
2
1
]
,
f
o
cu
s
o
n
th
e
p
r
o
b
le
m
o
f
s
en
d
in
g
lar
g
e
m
ed
ical
i
m
a
g
es
o
v
er
th
e
i
n
ter
n
e
t,
esp
ec
iall
y
w
h
e
n
b
an
d
w
id
t
h
i
s
li
m
i
ted
.
W
e
u
s
e
i
m
ag
e
co
m
p
r
ess
io
n
m
et
h
o
d
s
to
f
ix
th
is
p
r
o
b
lem
,
w
it
h
a
f
o
cu
s
o
n
f
r
ac
tal
i
m
a
g
e
co
m
p
r
ess
io
n
.
Fra
ctal
i
m
a
g
e
co
m
p
r
ess
io
n
u
s
es
t
h
e
id
ea
o
f
s
elf
-
s
i
m
ilar
it
y
in
i
m
ag
e
s
to
g
r
ea
tl
y
s
p
ee
d
u
p
tr
an
s
m
is
s
io
n
r
ates,
ev
en
w
h
e
n
b
an
d
w
id
th
i
s
li
m
ited
.
Ho
w
e
v
er
,
alth
o
u
g
h
t
h
e
y
d
ec
o
d
e
r
ap
id
ly
,
co
n
v
e
n
tio
n
al
tech
n
iq
u
es
f
o
r
co
m
p
r
es
s
i
n
g
f
r
ac
tal
i
m
a
g
es
f
r
e
q
u
en
tl
y
ta
k
e
s
ec
o
n
d
s
to
co
m
p
lete
th
e
e
n
co
d
in
g
p
r
o
ce
s
s
.
T
h
e
p
ap
er
p
r
esen
ts
an
ar
ch
itect
u
r
e
cr
ea
ted
esp
ec
iall
y
f
o
r
f
r
ac
tal
i
m
a
g
e
co
m
p
r
es
s
io
n
in
o
r
d
er
to
g
et
ar
o
u
n
d
th
is
r
estric
tio
n
.
T
h
e
d
esig
n
is
p
u
t
i
n
to
ac
tio
n
u
s
i
n
g
an
f
ield
-
p
r
o
g
r
a
m
m
ab
le
g
ate
a
r
r
ay
(
FP
G
A
)
b
o
ar
d
ca
lled
Xilin
x
Sp
ar
tan
-
6
an
d
ev
alu
ated
w
it
h
th
e
u
s
e
o
f
m
ed
ica
l i
m
a
g
in
g
d
ata.
Fan
g
et
a
l
.
[
2
2
]
,
ad
d
r
ess
ed
th
e
g
r
o
w
i
n
g
co
n
ce
r
n
s
o
f
p
atien
t
in
f
o
r
m
atio
n
leak
a
g
e
an
d
i
m
ag
e
ta
m
p
er
in
g
i
n
clo
u
d
-
b
ased
m
ed
ical
s
y
s
te
m
s
.
T
o
ad
d
r
ess
th
ese
ch
alle
n
g
e
s
,
a
n
e
w
ze
r
o
-
w
ater
m
ar
k
i
n
g
al
g
o
r
ith
m
n
a
m
ed
B
a
n
d
elet
-
D
C
T
,
b
ased
o
n
B
an
d
elet
a
n
d
d
is
cr
ete
co
s
i
n
e
tr
an
s
f
o
rm
,
is
in
tr
o
d
u
ce
d
f
o
r
m
ed
ical
i
m
a
g
e
s
.
T
h
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
in
v
o
l
v
es
s
ev
er
al
k
e
y
s
tep
s
.
T
o
s
tar
t,
th
e
s
ca
le
in
v
ar
ia
n
t
f
ea
tu
r
e
t
r
an
s
f
o
r
m
(
SIFT
)
is
u
s
ed
to
g
et
f
ea
t
u
r
es
f
r
o
m
an
i
m
a
g
e
as
a
f
ir
s
t
s
tep
.
T
h
en
,
a
ch
ao
tic
s
y
s
te
m
te
n
t
m
ap
is
u
s
ed
to
en
cr
y
p
t
t
h
e
w
at
er
m
ar
k
th
at
co
n
tai
n
s
t
h
e
p
atien
ts
’
i
n
f
o
r
m
atio
n
.
A
f
ter
t
h
at,
t
h
e
m
ed
ical
i
m
a
g
e
s
ar
e
u
s
ed
to
g
e
t
v
i
s
u
al
f
ea
t
u
r
e
v
ec
to
r
s
w
i
th
B
a
n
d
elet
-
D
C
T
.
L
astl
y
,
t
h
e
alg
o
r
ith
m
e
m
p
lo
y
s
b
o
th
ze
r
o
-
w
ater
m
ar
k
i
n
g
a
n
d
cr
y
p
to
g
r
ap
h
ic
tech
n
iq
u
es to
a
d
d
an
d
r
em
o
v
e
t
h
e
w
ater
m
ar
k
s
ec
u
r
el
y
.
T
h
e
s
tu
d
ies
in
t
h
e
co
llectio
n
lo
o
k
ed
at
d
if
f
er
en
t
w
a
y
s
to
m
a
k
e
clo
u
d
-
b
ased
m
ed
i
ca
l
i
m
ag
e
m
an
a
g
e
m
e
n
t
s
a
f
er
an
d
m
o
r
e
ef
f
icien
t.
T
h
e
m
ai
n
g
o
al
o
f
th
e
s
e
s
tu
d
ie
s
w
a
s
to
f
in
d
an
s
w
er
s
to
p
r
o
b
lem
s
w
ith
m
ed
ical
i
m
a
g
e
s
ec
u
r
it
y
,
co
m
p
r
e
s
s
io
n
,
s
to
r
ag
e,
an
d
d
a
ta
tr
an
s
f
er
.
E
ac
h
s
t
u
d
y
p
r
esen
ted
in
n
o
v
ati
v
e
m
et
h
o
d
o
lo
g
ies
ai
m
ed
at
tack
lin
g
s
p
ec
if
ic
a
s
p
ec
ts
o
f
m
ed
i
ca
l
i
m
ag
e
m
a
n
ag
e
m
e
n
t
in
cl
o
u
d
en
v
ir
o
n
m
e
n
ts
.
T
h
er
e
is
s
till
a
lo
t to
d
o
in
th
is
ar
ea
.
3.
I
M
AG
E
SE
G
M
E
NT
A
T
I
O
N
USI
N
G
Q
UAD
T
R
E
E
A
q
u
ad
tr
ee
d
ata
s
tr
u
ct
u
r
e
d
iv
i
d
es
a
t
w
o
-
d
i
m
en
s
io
n
al
s
p
ac
e
in
to
f
o
u
r
eq
u
al
p
ar
ts
,
ca
lled
q
u
ad
r
an
ts
,
b
y
u
s
i
n
g
a
p
r
o
ce
s
s
th
at
r
ep
ea
ts
its
elf
.
T
h
e
i
m
a
g
e
s
eg
m
e
n
tatio
n
m
et
h
o
d
u
s
es
a
h
ier
ar
ch
ical
d
ata
s
tr
u
ctu
r
e
ca
lled
a
q
u
ad
tr
ee
to
d
iv
id
e
an
i
m
ag
e
in
to
p
ar
ts
o
r
ar
ea
s
.
A
q
u
ad
tr
ee
d
iv
id
es
a
t
w
o
-
d
i
m
en
s
io
n
al
s
p
ac
e
i
n
to
f
o
u
r
q
u
ad
r
an
ts
o
v
er
an
d
o
v
er
a
g
ain
u
n
ti
l
ce
r
tain
co
n
d
itio
n
s
ar
e
m
et
[
2
3
]
.
A
p
o
r
tio
n
o
f
th
e
i
m
a
g
e
is
r
ep
r
esen
ted
b
y
ea
ch
n
o
d
e
in
t
h
e
q
u
ad
tr
ee
,
as
ex
p
lain
ed
i
n
Fi
g
u
r
e
1
(
a
)
r
ep
r
esen
ted
th
e
b
lo
ck
p
ar
titi
o
n
in
g
an
d
Fi
g
u
r
e
1
(
b
)
r
ep
r
esen
ted
th
e
q
u
ad
tr
ee
s
tr
u
ct
u
r
e.
(
a)
(
b
)
Fig
u
r
e
1
.
Qu
ad
tr
ee
s
tr
u
ct
u
r
e
:
(a
)
t
h
e
s
eg
m
e
n
tatio
n
p
r
o
ce
s
s
an
d
(
b
)
t
r
ee
s
tr
u
ctu
r
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
:
1
7
4
3
-
1
754
1746
T
h
is
s
tr
u
ct
u
r
e
is
m
u
c
h
b
etter
f
o
r
s
to
r
in
g
an
d
s
h
o
w
i
n
g
s
p
ati
al
d
ata
lik
e
p
o
in
t
s
,
li
n
es,
an
d
p
o
ly
g
o
n
s
th
an
a
r
eg
u
lar
lis
t
o
r
ar
r
ay
.
E
ac
h
n
o
d
e
in
a
q
u
ad
tr
ee
ca
n
o
n
l
y
h
av
e
a
m
ax
i
m
u
m
o
f
f
o
u
r
ch
ild
r
en
.
T
h
e
en
tire
t
w
o
-
d
i
m
e
n
s
io
n
al
s
p
ac
e,
s
p
lit
in
to
f
o
u
r
eq
u
a
l
h
alv
e
s
,
i
s
s
h
o
w
n
b
y
t
h
e
r
o
o
t
n
o
d
e.
A
c
h
il
d
n
o
d
e
o
f
t
h
e
r
o
o
t
r
ep
r
esen
ts
ea
c
h
q
u
ad
r
an
t.
I
f
th
e
c
h
ild
n
o
d
es
h
a
v
e
m
o
r
e
t
h
an
o
n
e
p
o
in
t,
t
h
e
y
ca
n
ad
d
i
tio
n
all
y
b
e
f
u
r
th
er
s
ep
ar
ated
in
to
f
o
u
r
q
u
ad
r
an
ts
.
T
h
is
lo
o
p
k
ee
p
s
g
o
in
g
u
n
til
ev
er
y
p
o
in
t
is
co
n
tain
ed
i
n
a
s
ep
ar
ate
lea
f
o
f
th
e
tr
ee
.
A
q
u
ad
tr
ee
is
a
m
e
th
o
d
f
o
r
s
tr
u
ctu
r
in
g
t
w
o
-
d
i
m
e
n
s
io
n
a
l
s
p
ac
e
b
y
r
ec
u
r
s
i
v
el
y
s
u
b
d
i
v
i
d
in
g
it
i
n
to
s
m
al
ler
s
eg
m
e
n
ts
.
T
h
e
p
r
o
ce
s
s
b
eg
i
n
s
b
y
p
ar
titi
o
n
i
n
g
th
e
s
p
ac
e
in
t
o
f
o
u
r
eq
u
al
q
u
ad
r
an
ts
,
s
u
b
s
e
q
u
en
tl
y
s
u
b
d
iv
id
i
n
g
ea
ch
q
u
ad
r
an
t i
n
to
f
o
u
r
ad
d
iti
o
n
al
q
u
ad
r
an
ts
u
n
til all
s
u
b
d
iv
is
io
n
s
s
ati
s
f
y
s
p
ec
i
f
ic
cr
iter
ia.
4.
L
I
G
H
T
WE
I
G
H
T
CRYP
T
O
G
RAP
H
Y
(
I
T
UB
ee
)
T
h
e
len
g
th
o
f
t
h
e
k
e
y
a
n
d
th
e
s
ize
o
f
th
e
I
T
U
B
ee
b
lo
ck
ar
e
8
0
b
its
.
T
h
e
en
cr
y
p
tio
n
u
tili
ze
s
a
Feis
tel
s
tr
u
ct
u
r
e
co
m
p
o
s
ed
o
f
2
0
r
o
u
n
d
s
,
w
it
h
m
ain
w
h
ite
n
i
n
g
la
y
er
s
lo
ca
ted
at
th
e
to
p
an
d
b
o
tto
m
o
f
t
h
e
en
cr
y
p
t
io
n
,
as
d
ep
icted
in
Fig
u
r
e
2
.
T
h
e
f
ac
t
th
at
I
T
UB
ee
m
a
n
ag
e
s
m
e
m
o
r
y
a
n
d
en
er
g
y
co
n
s
u
m
p
tio
n
w
h
ile
m
ai
n
tai
n
in
g
a
r
esp
ec
tab
le
lev
el
o
f
s
ec
u
r
it
y
i
s
en
co
u
r
ag
i
n
g
.
Fig
u
r
e
2
.
I
T
UB
ee
f
r
am
e
w
o
r
k
5.
M
E
T
H
O
DO
L
O
G
Y
T
h
e
s
u
g
g
es
ted
m
et
h
o
d
ca
lls
f
o
r
g
at
h
er
in
g
m
ed
ical
i
m
ag
e
s
s
o
th
e
y
ca
n
b
e
m
o
v
ed
an
d
p
r
ep
ar
e
d
.
q
u
ad
tr
ee
s
d
iv
id
e
th
ese
i
m
a
g
e
s
in
to
s
m
a
ller
p
ar
ts
s
o
th
at
th
e
y
ar
e
ea
s
ier
to
m
an
a
g
e
an
d
an
al
y
ze
.
W
e
m
ak
e
p
r
im
ar
y
k
e
y
s
f
o
r
th
ese
p
ar
ts
o
f
th
e
co
llected
i
m
ag
e
s
,
an
d
w
e
u
s
e
th
ese
k
e
y
s
later
o
n
in
t
h
e
en
cr
y
p
tio
n
p
r
o
ce
s
s
.
P
ix
els
i
n
i
m
a
g
es
ar
e
r
ep
lace
d
in
s
p
ec
if
ic
p
r
o
p
o
r
tio
n
s
ac
co
r
d
in
g
to
t
h
e
s
e
g
e
n
er
ated
tas
k
s
.
R
an
d
o
m
k
e
y
s
ar
e
s
elec
ted
f
r
o
m
a
m
o
n
g
t
h
o
s
e
g
e
n
er
ated
p
r
ev
io
u
s
l
y
,
an
d
t
h
e
o
r
ig
i
n
al
p
ix
el
s
i
n
th
e
i
m
a
g
es
ar
e
r
ep
lace
d
w
i
th
t
h
e
v
alu
e
s
ass
o
ciate
d
w
it
h
t
h
ese
k
e
y
s
.
A
f
ter
t
h
e
co
d
in
g
i
s
d
o
n
e,
th
e
m
ed
ical
i
m
a
g
es
t
h
at
ar
e
n
ee
d
ed
f
o
r
th
e
r
esear
ch
ar
e
co
llected
.
T
h
ese
p
ictu
r
es
a
r
e
r
ea
d
an
d
p
r
e
-
p
r
o
ce
s
s
ed
s
o
t
h
at
t
h
e
y
ca
n
b
e
p
u
t
t
o
g
eth
er
i
n
t
h
e
b
est
w
a
y
p
o
s
s
ib
le.
T
h
e
q
u
ad
tr
ee
a
lg
o
r
ith
m
th
e
n
s
p
lit
s
th
e
m
u
p
in
to
s
q
u
ar
e
ar
ea
s
,
an
d
ea
ch
ar
ea
is
en
co
d
ed
in
a
w
a
y
t
h
at
f
it
s
it
s
o
w
n
n
ee
d
s
.
T
h
e
g
o
al
o
f
th
e
s
e
o
p
er
atio
n
s
is
t
o
ac
h
iev
e
an
o
p
ti
m
al
b
alan
ce
b
et
w
ee
n
p
r
o
ce
s
s
i
n
g
s
p
ee
d
an
d
co
n
f
id
en
tia
lit
y
.
E
n
c
r
y
p
ti
n
g
ar
ea
s
ac
co
m
p
lis
h
es
th
i
s
in
m
u
lt
ip
le
w
a
y
s
,
ac
co
r
d
in
g
to
th
eir
n
atu
r
e
a
n
d
i
m
p
o
r
tan
ce
,
w
h
ich
p
r
o
v
id
es
ad
v
an
ce
d
p
r
o
tectio
n
f
o
r
m
ed
ical
i
m
a
g
es
an
d
t
h
eir
as
s
o
ciate
d
d
ata
w
it
h
o
u
t
co
m
p
r
o
m
is
i
n
g
th
e
s
p
ee
d
an
d
ef
f
ec
t
iv
e
n
es
s
o
f
s
ea
r
c
h
i
n
g
a
n
d
th
e
r
ap
id
u
s
e
o
f
t
h
e
s
e
i
m
ag
es.
T
h
e
g
e
n
er
al
f
r
a
m
e
w
o
r
k
o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
is
ex
p
lai
n
ed
in
Fi
g
u
r
e
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
A
d
a
p
tive
DI
C
OM ima
g
es e
n
cryp
tio
n
u
s
in
g
q
u
a
d
tr
ee
a
n
d
li
g
h
tw
eig
h
t
…
(
Mu
n
ta
h
a
A
b
d
u
lz
a
h
r
a
Ha
tem
)
1747
Fig
u
r
e
3
.
T
h
e
f
r
am
e
w
o
r
k
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
5
.
1
.
Appl
y
qu
a
dtr
ee
deco
m
po
s
it
i
o
n
T
h
e
in
itial
p
h
ase
o
f
t
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
i
n
v
o
l
v
es
ap
p
l
y
i
n
g
t
h
e
s
e
g
m
e
n
tatio
n
p
r
o
ce
s
s
t
o
m
ed
ical
i
m
a
g
es
u
s
i
n
g
th
e
q
u
ad
tr
ee
tech
n
iq
u
e,
w
h
ich
i
s
ap
p
lied
to
th
e
in
p
u
t
i
m
a
g
e
(
m
ed
ical
i
m
a
g
e
)
af
ter
it
h
a
s
b
ee
n
co
n
v
er
ted
to
g
r
a
y
s
ca
le,
a
s
ill
u
s
tr
ated
in
Fig
u
r
e
4
.
T
h
is
tec
h
n
iq
u
e
id
e
n
ti
f
i
es
th
e
m
o
s
t
s
i
g
n
if
ica
n
t
ar
ea
s
i
n
t
h
e
i
m
a
g
e.
I
t iso
lates t
h
e
m
f
r
o
m
th
e
less
i
m
p
o
r
ta
n
t a
r
ea
s
t
h
r
o
u
g
h
a
s
p
ec
if
ic
t
h
r
es
h
o
ld
th
at
d
ep
en
d
s
o
n
th
e
v
ar
ian
ce
v
alu
e
in
t
h
e
r
eg
io
n
.
W
h
en
e
v
er
th
e
v
ar
ia
n
ce
v
a
lu
e
i
s
h
i
g
h
,
th
e
r
eg
io
n
is
d
i
v
id
ed
in
to
f
o
u
r
o
th
er
p
ar
ts
u
n
til
t
h
e
s
m
al
lest
p
o
s
s
ib
le
p
iece
is
r
ea
ch
ed
.
T
h
e
s
ize
o
f
th
e
b
lo
ck
is
l
ar
g
e
an
d
u
n
d
iv
id
ed
,
in
d
icati
n
g
th
at
t
h
i
s
r
eg
io
n
is
less
s
i
g
n
i
f
ican
t a
n
d
lack
s
m
an
y
d
etails.
Fig
u
r
e
4
.
DI
C
OM
q
u
ad
tr
ee
d
ec
o
m
p
o
s
i
tio
n
5
.
2
.
K
ey
g
ener
a
t
io
n
T
h
e
n
u
m
b
er
g
en
er
ati
n
g
(
k
e
y
g
en
er
atio
n
)
d
ep
en
d
s
o
n
a
t
w
o
-
d
i
m
e
n
s
io
n
al
c
h
ao
tic
m
ap
(
H
en
o
n
m
ap
)
.
T
h
e
f
ir
s
t
-
d
i
m
e
n
s
io
n
s
eq
u
e
n
ce
is
u
s
ed
i
n
th
e
p
r
o
ce
s
s
o
f
r
ed
is
tr
ib
u
tin
g
t
h
e
b
its
(
p
er
m
u
ta
tio
n
)
f
o
r
ea
ch
p
ix
el
in
th
e
ex
i
s
ti
n
g
b
lo
ck
,
as
d
i
f
f
er
e
n
t
in
itial
v
alu
e
s
ar
e
cr
ea
ted
f
o
r
ea
ch
b
lo
ck
s
ize.
T
h
u
s
,
ea
ch
b
lo
ck
is
co
m
p
leted
(
th
e
t
w
o
s
eq
u
e
n
ce
s
a
m
p
le
s
ar
e
v
is
u
a
lized
in
Fig
u
r
e
5
)
.
Fig
u
r
e
5
(
a
)
s
h
o
w
s
th
e
f
ir
s
t
s
eq
u
e
n
ce
,
w
h
ic
h
is
u
s
ed
in
th
e
b
it
-
p
er
m
u
tatio
n
p
r
o
ce
s
s
f
o
r
ea
ch
p
ix
el
w
it
h
i
n
t
h
e
b
lo
ck
.
Fig
u
r
e
5
(
b
)
s
h
o
w
s
th
e
s
ec
o
n
d
s
eq
u
en
ce
,
w
h
ic
h
i
s
u
s
ed
to
g
e
n
er
ate
th
e
k
e
y
s
c
h
ed
u
le
f
o
r
th
e
m
o
d
i
f
ied
I
T
UB
ee
en
cr
y
p
tio
n
al
g
o
r
ith
m
.
T
h
er
e
is
a
p
r
o
ce
s
s
o
f
r
ed
is
tr
ib
u
tin
g
t
h
e
b
its
,
d
if
f
er
i
n
g
in
s
ize
f
r
o
m
th
e
o
t
h
er
b
lo
ck
.
T
h
u
s
,
w
e
h
a
v
e
a
f
er
m
en
ta
tio
n
p
r
o
ce
s
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
:
1
7
4
3
-
1
754
1748
T
h
e
s
ec
o
n
d
n
u
m
b
er
g
e
n
er
atio
n
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
b
y
g
en
er
atin
g
p
r
iv
ate
k
e
y
s
f
o
r
th
e
p
r
o
p
o
s
ed
lig
h
t
w
ei
g
h
t
en
cr
y
p
t
io
n
alg
o
r
it
h
m
I
T
UB
ee
.
Fo
r
ea
ch
s
p
ec
if
i
c
b
lo
ck
s
ize,
th
er
e
is
a
d
if
f
er
en
t
k
e
y
g
e
n
er
atio
n
p
r
o
ce
s
s
(
i.e
.
,
a
d
if
f
er
en
t i
n
itial
s
tate)
.
T
h
is
in
cr
ea
s
e
s
th
e
co
m
p
lex
it
y
o
f
th
e
m
et
h
o
d
,
w
h
ic
h
g
iv
es
s
tr
en
g
t
h
to
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
.
Fig
u
r
e
5
.
Vis
u
al
izatio
n
o
f
g
e
n
er
ated
n
u
m
b
er
s
:
(
a)
f
ir
s
t seq
u
e
n
ce
an
d
(
b
)
s
ec
o
n
d
s
eq
u
en
ce
5
.
3
.
Select
t
he
nu
m
ber
o
f
ro
un
d
k
ey
s
T
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
is
n
o
w
o
b
tain
ed
f
o
r
ea
ch
d
is
t
in
ct
b
lo
ck
s
ize.
T
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
d
ec
r
ea
s
es
as
th
e
b
lo
ck
s
ize
in
cr
ea
s
es.
B
ec
au
s
e
o
f
th
is
,
th
er
e
ar
e
m
o
r
e
r
o
u
n
d
s
in
th
e
lar
g
er
,
less
d
etailed
b
lo
ck
s
,
an
d
m
o
r
e
r
o
u
n
d
s
i
n
th
e
s
m
al
ler
,
m
o
r
e
d
etailed
b
lo
ck
s
.
T
h
is
m
ak
es
t
h
e
en
cr
y
p
t
io
n
p
r
o
ce
s
s
m
o
r
e
co
m
p
le
x
i
n
th
i
s
ar
ea
,
w
h
ic
h
i
n
t
u
r
n
cr
ea
t
es
a
b
alan
ce
b
et
w
ee
n
t
h
e
d
eg
r
ee
o
f
e
n
cr
y
p
tio
n
an
d
th
e
v
al
u
e
o
f
th
e
i
n
f
o
r
m
atio
n
,
as
w
ell
a
s
b
et
w
ee
n
t
h
e
ti
m
e
it ta
k
es to
co
m
p
lete
t
h
e
e
n
cr
y
p
tio
n
p
r
o
ce
s
s
.
5
.
4
.
Appl
y
ing
m
o
difie
d IT
UB
ee
encr
y
ptio
n
T
h
e
lig
h
t
w
e
ig
h
t
e
n
cr
y
p
tio
n
a
lg
o
r
ith
m
ap
p
lied
is
a
m
o
d
i
f
i
ed
I
T
UB
ee
en
cr
y
p
tio
n
m
et
h
o
d
,
w
h
ic
h
in
v
o
l
v
es
c
h
an
g
i
n
g
th
e
n
u
m
b
er
o
f
r
o
u
n
d
s
f
o
r
ea
ch
b
lo
ck
s
ize,
as
illu
s
tr
ated
i
n
Fig
u
r
e
6
.
T
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
co
n
tr
o
ls
th
e
d
e
g
r
ee
o
f
co
m
p
l
ex
it
y
(
ti
m
e
-
co
n
s
u
m
in
g
)
an
d
t
h
e
in
f
o
r
m
a
tio
n
v
al
u
e
in
ea
c
h
r
eg
io
n
,
s
er
v
in
g
t
h
e
ad
ap
tatio
n
.
T
h
e
en
cr
y
p
tio
n
p
r
o
ce
s
s
is
d
o
n
e
d
if
f
er
en
tl
y
f
o
r
ea
ch
b
lo
ck
s
ize,
as
th
e
n
u
m
b
er
o
f
r
o
u
n
d
s
f
o
r
ea
ch
b
lo
ck
is
ch
o
s
e
n
.
T
h
e
lar
g
er
th
e
b
lo
ck
s
ize,
th
e
f
e
w
er
th
e
n
u
m
b
er
o
f
r
o
u
n
d
s
,
t
h
u
s
ac
h
ie
v
i
n
g
a
b
alan
ce
b
et
w
ee
n
th
e
co
m
p
lex
it
y
o
f
th
e
r
eg
io
n
an
d
th
e
en
cr
y
p
t
io
n
,
w
it
h
co
m
p
letel
y
d
if
f
er
en
t
r
es
u
lt
s
.
T
h
e
r
esu
lt
s
o
f
en
cr
y
p
t
in
g
th
e
s
a
m
e
i
n
p
u
t
m
es
s
ag
e
w
i
th
v
ar
y
i
n
g
n
u
m
b
er
s
o
f
r
o
u
n
d
s
,
a
s
w
e
ll
as
t
h
e
ti
m
e
r
eq
u
ir
ed
f
o
r
en
cr
y
p
tio
n
i
n
ea
c
h
s
p
ec
if
ied
r
o
u
n
d
.
Fi
n
all
y
,
th
e
d
ec
r
y
p
tio
n
p
r
o
ce
s
s
u
s
ed
t
h
e
s
a
m
e
p
r
o
ce
s
s
in
r
e
v
er
s
e
o
r
d
er
.
Fig
u
r
e
6
.
R
eg
io
n
en
cr
y
p
tio
n
u
s
in
g
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
I
n
p
u
t
Q
u
a
d
t
r
e
e
l
e
a
v
e
s
(
i
m
a
g
e
r
e
g
i
o
n
)
s
t
a
r
t
B
a
s
e
d
o
n
r
i
g
i
o
n
s
i
z
e
(
a
s
s
i
g
n
N
u
m
b
e
r
o
f
r
o
u
n
d
)
P
a
r
t
i
t
i
o
n
r
e
g
i
o
n
i
n
t
o
s
p
e
c
i
f
i
c
b
l
o
c
k
s
s
i
z
e
A
p
p
l
y
i
n
g
m
o
d
i
f
i
e
d
-
I
T
U
B
e
e
f
o
r
e
a
c
h
b
l
o
c
k
s
M
e
r
g
e
B
l
o
c
k
s
i
n
t
o
e
n
c
r
y
p
t
e
d
r
e
g
i
o
n
A
d
d
r
e
g
i
o
n
t
o
t
h
e
e
n
c
r
y
p
t
e
d
m
e
d
i
c
a
l
i
m
a
g
e
r
e
g
i
o
n
I
f
s
c
a
n
l
e
a
v
e
s
i
s
a
l
a
s
t
C
o
n
s
t
r
u
c
t
e
n
c
r
y
p
t
i
o
n
i
m
a
g
e
No
y
e
s
e
n
d
(
a)
(
b
)
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
A
d
a
p
tive
DI
C
OM ima
g
es e
n
cryp
tio
n
u
s
in
g
q
u
a
d
tr
ee
a
n
d
li
g
h
tw
eig
h
t
…
(
Mu
n
ta
h
a
A
b
d
u
lz
a
h
r
a
Ha
tem
)
1749
5
.
5
.
M
o
dified
I
T
UB
ee
encr
y
ptio
n a
lg
o
rit
h
m
T
h
e
p
r
o
p
o
s
ed
en
cr
y
p
tio
n
al
g
o
r
ith
m
is
r
ep
r
ese
n
ted
b
y
p
ar
titi
o
n
in
g
t
h
e
m
ain
i
m
a
g
e
i
n
to
s
u
b
-
i
m
a
g
es
.
T
h
e
s
u
b
-
i
m
ag
e
i
s
p
ar
titi
o
n
ed
i
n
to
80
-
b
it
b
lo
ck
s
,
ea
ch
o
f
w
h
i
ch
is
i
n
p
u
t
to
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
to
p
r
o
d
u
ce
th
e
en
cr
y
p
ted
b
lo
ck
s
,
a
s
ex
p
lai
n
e
d
in
A
l
g
o
r
ith
m
1
.
T
h
e
n
u
m
b
e
r
o
f
b
lo
ck
s
i
s
v
ar
ied
d
ep
en
d
in
g
o
n
t
h
e
s
e
g
m
en
t
s
ize,
w
h
ic
h
m
ak
e
s
it v
ar
iab
le
i
n
ti
m
e
-
co
n
s
u
m
in
g
.
Algorithm 1: Modified ITUBe
e encryption
a
lgorithm
Input: GeneratedMaster_key, plainBlock (80
-
bit), No.of rounds, RC// round constant
Output: Ec
\
\
EncryptedBlock
Steps:
1: Master key is expanded into round keys (80
-
bit sub
-
keys).
2: assigned pL
MSB(plainBlock) //first 40
-
bit
3: as
signed pR
LSB(plainBlock) // last 40
-
bit
4: assignd kL
MSB(SubKey
0
) //first 40
-
bit
5: assigned kR
LSB(SubKey
0
) // last 40
-
bit
6: Initialized X
o
pL
ꚚkL and X
1
pR
ꚚkR
7: for i
1 to No.of rounds
If reminder(i,2)=1 then
RK
kR
Else
RK
kL
End if
X
i+1
X
i+1
Ꚛ Fun(L(RKꚚRC
i
Ꚛ Fun(X
i
)))
End for
8: EcL
X
n
Ꚛ KR EcR
X
n+1
Ꚛ
K
L
9: Ec
merge(EcL,EcR)
10: return Ec
End algorithm
5
.
6
.
M
o
dified
I
T
UB
ee
decr
y
ptio
n a
lg
o
rit
h
m
T
h
e
d
ec
r
y
p
tio
n
p
r
o
ce
s
s
is
th
e
r
ev
er
s
e
o
f
th
e
en
cr
y
p
tio
n
p
r
o
ce
s
s
.
T
h
e
s
a
m
e
g
e
n
er
ated
k
e
y
is
u
s
ed
w
it
h
t
h
e
s
a
m
e
in
itial
v
a
lu
e
s
in
r
ev
er
s
e
o
r
d
er
.
T
h
e
en
cr
y
p
tio
n
alg
o
r
it
h
m
o
f
th
e
p
r
o
p
o
s
al
is
r
ep
r
esen
ted
b
y
t
h
e
s
a
m
e
s
tep
s
in
f
o
r
w
ar
d
s
tep
s
(
e
n
cr
y
p
tio
n
s
tep
s
)
in
r
ev
er
s
e
o
r
d
er
,
w
it
h
th
e
s
a
m
e
s
u
b
k
e
y
s
f
r
o
m
b
o
tto
m
to
to
p
f
o
r
r
ec
o
n
s
tr
u
cti
n
g
th
e
p
lai
n
b
lo
ck
.
6.
E
XP
E
R
I
M
E
NT
A
L
RE
SUL
T
S
T
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
w
a
s
tes
t
ed
u
s
i
n
g
a
s
et
o
f
DI
C
OM
i
m
a
g
es
a
s
m
ed
ical
i
m
a
g
es
w
it
h
a
(
5
1
2
×
5
1
2
)
s
ize
a
n
d
a
1
6
-
b
it
d
ep
th
.
T
h
e
f
i
r
s
t
p
r
o
ce
s
s
ap
p
lied
is
s
e
g
m
e
n
t
atio
n
u
s
i
n
g
t
h
e
q
u
ad
tr
ee
m
et
h
o
d
o
f
th
e
d
ataset
o
f
th
e
DI
C
OM
i
m
a
g
e,
an
d
it
s
d
e
co
m
p
o
s
i
tio
n
i
s
e
x
p
lain
ed
i
n
F
i
g
u
r
e
7
.
T
h
e
en
cr
y
p
tio
n
p
r
o
ce
s
s
o
f
m
ed
ical
i
m
a
g
es
is
ex
p
lai
n
ed
,
co
n
s
id
er
in
g
th
e
s
af
et
y
an
d
s
ec
u
r
it
y
o
f
p
ati
en
t
in
f
o
r
m
a
tio
n
.
T
h
e
ap
p
licatio
n
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
y
ield
ed
i
m
a
g
es
w
it
h
n
o
co
r
r
elate
d
in
f
o
r
m
at
io
n
,
as ill
u
s
tr
ated
in
Fig
u
r
e
8
.
Fig
u
r
e
7
.
T
h
e
DI
C
OM
d
ataset
an
d
its
d
ec
o
m
p
o
s
itio
n
ar
e
u
s
i
n
g
a
q
u
ad
tr
ee
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
:
1
7
4
3
-
1
754
1750
Fig
u
r
e
8
.
Me
d
ical
i
m
ag
e
e
n
cr
y
p
t
io
n
T
h
e
p
er
m
u
tatio
n
p
r
o
ce
s
s
e
x
a
m
p
le
is
e
x
p
lain
ed
i
n
T
ab
le
1
b
ased
o
n
th
e
g
e
n
er
ated
n
u
m
b
er
s
o
f
th
e
H
en
o
n
m
ap
.
T
h
is
p
er
m
u
tatio
n
illu
s
tr
ates
h
o
w
th
e
f
ir
s
t
-
d
i
m
e
n
s
io
n
ch
ao
tic
v
al
u
es
r
eo
r
d
er
th
e
p
ix
el
b
it
s
b
ef
o
r
e
en
cr
y
p
tio
n
,
e
n
s
u
r
in
g
in
i
tial
co
n
f
u
s
io
n
at
th
e
b
it
lev
el.
T
h
e
s
a
m
p
le
o
f
r
o
u
n
d
s
n
u
m
b
er
th
at
is
b
ased
o
n
b
lo
ck
s
ize
is
ill
u
s
tr
ated
i
n
T
ab
le
2
.
I
t
f
u
r
t
h
er
d
etails
h
o
w
d
i
f
f
er
en
t
b
lo
ck
s
ize
s
p
r
o
d
u
ce
d
b
y
th
e
q
u
ad
tr
ee
s
eg
m
e
n
tatio
n
ar
e
a
s
s
i
g
n
ed
d
if
f
er
en
t
n
u
m
b
er
s
o
f
e
n
cr
y
p
ti
o
n
r
o
u
n
d
s
.
Sin
ce
s
m
a
ller
b
l
o
ck
s
co
n
tai
n
m
o
r
e
d
etailed
in
f
o
r
m
atio
n
,
th
e
y
ar
e
ass
i
g
n
ed
h
i
g
h
er
r
o
u
n
d
co
u
n
t
s
.
Fro
m
t
h
e
p
r
ev
io
u
s
T
ab
le
2
,
ea
ch
b
lo
ck
s
ize
w
il
l
tak
e
its
co
r
r
esp
o
n
d
in
g
ti
m
e
as
ex
p
lain
ed
in
T
ab
le
3
.
I
t
s
u
m
m
ar
izes
th
e
e
n
cr
y
p
tio
n
ti
m
e
co
r
r
esp
o
n
d
in
g
to
ea
ch
r
o
u
n
d
n
u
m
b
er
,
s
h
o
w
in
g
h
o
w
in
cr
ea
s
i
n
g
t
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
in
cr
ea
s
e
s
p
r
o
ce
s
s
in
g
ti
m
e
i
n
a
p
r
ed
ictab
le
m
an
n
er
.
T
o
g
eth
er
,
th
ese
tab
l
es
d
e
m
o
n
s
tr
ate
th
e
ad
ap
tiv
e
n
atu
r
e
o
f
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
,
w
h
ic
h
b
alan
ce
s
en
cr
y
p
tio
n
s
tr
en
g
t
h
w
it
h
co
m
p
u
tatio
n
a
l c
o
s
t.
T
ab
le
1
.
T
h
e
p
er
m
u
tat
io
n
p
r
o
ce
s
s
i
n
th
e
p
ix
e
l b
its
ex
a
m
p
le
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
0
0
0
0
0
1
0
0
1
1
0
0
0
0
0
1
6
3
16
11
7
14
8
5
15
1
2
4
13
9
10
12
1
0
1
0
0
0
0
0
0
0
0
0
0
1
1
0
T
ab
le
2
.
Sp
ec
if
y
in
g
t
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
o
f
ea
ch
b
lo
ck
s
ize
B
l
o
c
k
s
i
z
e
2
5
6
×
2
5
6
1
2
8
×
1
2
8
6
4
×
6
4
3
2
×
3
2
1
6
×
1
6
8
×
8
4
×
4
N
o
.
o
f
r
o
u
n
d
s
4
6
8
10
12
16
20
T
ab
le
3
.
T
h
e
en
cr
y
p
tio
n
ti
m
e
o
f
ea
ch
s
p
ec
i
f
ies t
h
e
n
u
m
b
er
o
f
r
o
u
n
d
s
H
e
x
.
samp
l
e
i
s
‘
0
1
2
3
4
5
6
7
8
9
A
B
C
D
E
F
1
2
3
4
’
N
o
.
o
f
r
o
u
n
d
s
H
e
x
.
e
n
c
r
y
p
t
i
o
n
El
a
p
se
d
t
i
me
o
f
t
h
e
b
l
o
c
k
8
‘
E7
7
A
3
6
3
E6
A
3
C
A
B
7
EF
0
ED
’
0
.
0
0
6
1
4
8
10
‘
6
F
6
7
9
7
C
C
6
3
D
D
B
9
B
9
1
D
A
8
’
0
.
0
0
8
5
3
8
12
‘
5
D
0
E
5
2
7
2
9
3
D
6
0
A
F
D
D
B
6
D
’
0
.
0
0
9
9
8
4
14
‘
0
0
F
9
7
F
1
1
C
EA
7
C
0
E
5
F
C
6
B
’
0
.
0
1
0
3
2
1
16
‘
9
6
5
2
6
2
D
E
7
D
6
9
5
5
4
7
3
A
8
4
’
0
.
0
1
1
4
9
3
18
‘
4
C
D
D
5
B
3
0
0
1
3
1
6
7
6
B
2
1
7
4
’
0
.
0
1
2
9
9
4
20
‘
A
A
8
0
6
4
6
B
A
3
D
D
4
0
1
1
1
C
3
8
’
0
.
0
1
3
4
5
6
T
h
e
f
ir
s
t
e
x
p
er
i
m
e
n
t,
w
h
ic
h
a
p
p
lies
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
,
ai
m
s
to
d
eter
m
i
n
e
t
h
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
an
d
p
ea
k
s
ig
n
al
-
to
-
n
o
is
e
r
atio
o
f
th
e
en
cr
y
p
ted
i
m
a
g
e
co
m
p
ar
ed
t
o
th
e
r
ef
er
en
ce
i
m
ag
e
[
2
4
]
,
as
o
u
tlin
ed
in
T
ab
le
4
.
It
r
e
p
o
r
ts
th
e
MSE
an
d
P
SNR
v
alu
es
f
o
r
all
en
cr
y
p
ted
DI
C
OM
i
m
a
g
es.
T
h
e
r
esu
lts
s
h
o
w
co
n
s
is
ten
tl
y
h
ig
h
MSE
an
d
lo
w
P
SNR
v
alu
e
s
,
in
d
icat
i
n
g
a
s
ig
n
i
f
ica
n
t
v
i
s
u
a
l
d
if
f
er
en
ce
b
et
w
ee
n
th
e
o
r
ig
in
a
l
an
d
en
cr
y
p
ted
i
m
ag
e
s
.
T
h
ese
f
in
d
i
n
g
s
co
n
f
ir
m
th
a
t
th
e
p
r
o
p
o
s
ed
en
cr
y
p
tio
n
m
et
h
o
d
ef
f
ec
ti
v
el
y
e
li
m
in
a
tes
m
ea
n
in
g
f
u
l v
i
s
u
al
i
n
f
o
r
m
atio
n
f
r
o
m
th
e
i
m
a
g
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
A
d
a
p
tive
DI
C
OM ima
g
es e
n
cryp
tio
n
u
s
in
g
q
u
a
d
tr
ee
a
n
d
li
g
h
tw
eig
h
t
…
(
Mu
n
ta
h
a
A
b
d
u
lz
a
h
r
a
Ha
tem
)
1751
T
ab
le
4
.
I
m
ag
e
q
u
al
it
y
te
s
t
f
o
r
DI
C
OM
d
ata
s
et
u
s
in
g
a
p
r
o
p
o
s
ed
en
cr
y
p
tio
n
al
g
o
r
ith
m
#
M
S
E
P
S
N
R
#
M
S
E
P
S
N
R
1
1
.
4
7
6
7
3
E+
0
9
4
.
1
7
7
9
9
7
1
.
3
2
1
7
7
E+
0
9
4
.
7
4
6
3
3
2
1
.
4
5
9
6
4
E+
0
9
4
.
5
0
8
0
8
8
1
.
4
9
4
6
7
E+
0
9
4
.
5
1
0
8
0
3
1
.
4
4
3
2
8
E+
0
9
4
.
3
0
5
3
7
9
1
.
4
0
5
1
3
E+
0
9
4
.
7
5
1
6
4
4
1
.
4
2
2
4
9
E+
0
9
4
.
7
9
9
3
5
10
1
.
2
9
7
3
1
E+
0
9
4
.
2
0
8
3
6
5
1
.
4
3
5
3
9
E+
0
9
4
.
6
8
8
7
9
11
1
.
4
5
6
7
3
E+
0
9
3
.
9
2
3
3
8
6
1
.
4
3
8
1
3
E+
0
9
4
.
3
5
3
9
2
12
1
.
3
1
4
4
6
E+
0
9
4
.
0
0
0
2
7
Fro
m
T
ab
le
4
,
th
e
v
alu
es
o
f
MSE
an
d
P
SNR
in
d
icate
s
ig
n
if
ica
n
t
d
if
f
er
en
ce
s
b
et
w
ee
n
t
h
e
r
ef
er
en
ce
i
m
a
g
es
an
d
t
h
e
en
cr
y
p
ted
i
m
ag
es.
T
h
e
co
r
r
elatio
n
ch
ec
k
r
esu
lt
s
f
o
r
ea
ch
i
m
a
g
e
ar
e
p
r
e
s
en
ted
i
n
T
ab
le
5
,
w
h
ic
h
in
cl
u
d
es
t
h
e
i
m
a
g
e
s
u
s
ed
to
ev
alu
ate
th
e
o
u
tco
m
es
[
2
5
]
.
W
ith
th
ese
i
m
a
g
es,
t
h
e
co
r
r
elatio
n
b
et
w
ee
n
th
e
p
h
o
to
g
r
ap
h
s
ta
k
e
n
b
ef
o
r
e
an
d
af
ter
th
e
e
n
cr
y
p
tio
n
p
r
o
ce
d
u
r
e
w
a
s
e
x
a
m
in
ed
.
B
ef
o
r
e
en
cr
y
p
tio
n
,
it
w
a
s
o
b
s
er
v
ed
th
at
t
h
e
i
m
ag
e
s
e
x
h
i
b
ited
a
s
tr
o
n
g
co
r
r
elatio
n
(
al
m
o
s
t o
n
e)
.
Ho
w
e
v
er
,
th
is
co
r
r
elatio
n
w
as d
i
s
r
u
p
ted
,
r
esu
lti
n
g
in
v
al
u
es t
h
at
ar
e
n
o
w
clo
s
e
to
ze
r
o
o
r
n
eg
ati
v
e
in
all
d
ir
ec
tio
n
s
.
T
ab
le
5
.
T
h
e
co
r
r
elatio
n
te
s
t o
f
all
t
h
e
DI
C
OM
i
m
a
g
e
d
atase
ts
#
C
o
r
r
e
l
a
t
i
o
n
#
C
o
r
r
e
l
a
t
i
o
n
1
-
0
.
1
2
5
8
7
4
7
0
1
7
-
0
.
0
5
8
5
4
6
4
5
1
2
-
0
.
1
7
7
1
2
5
3
2
5
8
-
0
.
0
6
4
5
3
0
2
2
5
3
-
0
.
1
9
1
7
8
6
3
9
6
9
-
0
.
0
5
7
3
8
7
0
5
4
4
-
0
.
0
3
0
7
3
7
9
1
1
10
-
0
.
1
6
3
0
6
9
0
8
2
5
-
0
.
0
7
3
6
4
0
8
5
11
-
0
.
0
3
1
3
9
4
5
7
7
6
-
0
.
1
2
8
2
5
6
2
3
2
12
-
0
.
1
7
2
0
5
0
5
3
8
A
v
.
-
0
.
1
0
6
1
9
9
9
4
5
NI
ST
test
s
ar
e
e
m
p
lo
y
ed
,
w
h
i
ch
ar
e
e
x
e
m
p
li
f
ied
b
y
a
s
tan
d
ar
d
test
[
2
6
]
.
E
v
er
y
tes
t
w
a
s
co
n
d
u
cted
o
n
s
eq
u
en
ce
s
o
f
th
e
k
e
y
g
e
n
er
atio
n
u
s
i
n
g
th
e
He
n
o
n
m
ap
.
Acc
o
r
d
in
g
to
T
ab
le
6
,
th
e
-
v
al
u
es
o
f
all
test
s
ar
e
m
o
r
e
s
ig
n
i
f
ica
n
t
t
h
an
0
.
1
,
in
d
i
ca
tin
g
th
a
t
all
t
h
e
r
esu
l
ts
e
x
ce
ed
th
e
th
r
es
h
o
ld
v
al
u
e.
T
h
e
d
if
f
er
en
tial
at
tack
o
n
i
m
a
g
es,
to
ass
e
s
s
h
o
w
r
esi
lie
n
t
p
ictu
r
e
en
cr
y
p
tio
n
tec
h
n
iq
u
es
ar
e
to
d
if
f
er
e
n
tial
as
s
au
lt
s
,
n
u
m
b
er
o
f
p
ix
el
ch
an
g
e
r
ate
(
NP
C
R
)
,
an
d
u
n
if
ied
co
n
f
u
s
io
n
–
a
v
alan
c
h
e
i
n
d
icato
r
(
UC
A
I
)
,
is
cr
u
cial.
W
h
ile
lo
w
n
u
m
b
er
s
m
a
y
in
d
icate
f
la
w
s
t
h
at
co
u
ld
b
e
ex
p
l
o
ited
,
h
ig
h
v
al
u
es
in
b
o
th
m
etr
ics
i
n
d
icate
a
s
ec
u
r
e
en
cr
y
p
t
io
n
m
et
h
o
d
.
T
h
e
UC
A
I
an
d
NP
C
R
ar
e
ex
p
lai
n
e
d
in
T
ab
le
7
.
T
h
e
tim
e
co
n
s
u
m
p
tio
n
f
o
r
ea
ch
DI
C
OM
i
m
a
g
e
is
r
ec
o
r
d
ed
t
o
ev
alu
ate
t
h
e
alg
o
r
it
h
m
’
s
s
u
c
ce
s
s
.
T
h
e
ti
m
e
n
ee
d
ed
to
u
tili
ze
th
e
r
ec
o
m
m
en
d
ed
al
g
o
r
i
th
m
f
o
r
th
e
e
n
cr
y
p
tio
n
an
d
d
ec
r
y
p
tio
n
o
f
t
h
e
5
1
2
×
5
1
2
DI
C
OM
i
m
a
g
e
s
izes
is
e
x
p
lain
ed
a
n
d
m
ea
s
u
r
ed
in
T
ab
le
8
,
w
h
ich
c
o
m
p
ar
es
th
e
r
es
u
lts
o
b
tain
ed
b
y
ap
p
l
y
i
n
g
th
e
A
E
S
alg
o
r
ith
m
to
th
e
s
a
m
e
DI
C
O
M
im
a
g
e
s
.
A
cc
o
r
d
in
g
to
T
ab
le
8
,
th
e
av
er
ag
e
ti
m
e
co
n
s
u
m
p
tio
n
is
5
.
6
6
9
5
7
s
ec
o
n
d
s
f
o
r
en
cr
y
p
tio
n
.
I
n
co
m
p
ar
i
s
o
n
,
5
.
0
2
5
4
1
s
ec
o
n
d
s
a
r
e
r
eq
u
ir
ed
f
o
r
th
e
d
ec
r
y
p
tio
n
p
r
o
ce
s
s
,
w
h
ic
h
is
les
s
th
an
t
h
e
ti
m
e
co
n
s
u
m
p
tio
n
o
f
t
h
e
s
a
m
e
DI
C
I
M
u
s
i
n
g
t
h
e
A
E
S st
an
d
ar
d
alg
o
r
it
h
m
.
T
ab
le
6
.
T
h
e
NI
S
T
test
r
esu
lts
o
f
th
e
p
r
o
p
o
s
ed
s
y
s
te
m
#
T
e
s
t
P
-
v
a
l
u
e
S
t
a
t
u
s
#
T
e
st
P
-
v
a
l
u
e
S
t
a
t
u
s
1
R
u
n
t
e
st
0
.
5
6
9
0
4
P
a
ss
8
M
a
u
r
e
r
’
s u
n
i
v
e
r
sal
t
e
st
0
.
9
6
9
5
7
7
P
a
ss
2
S
e
r
i
a
l
t
e
st
0
.
8
0
7
7
3
P
a
ss
9
T
h
e
l
o
n
g
e
st
r
u
n
o
f
o
n
e
0
.
9
0
6
5
3
1
P
a
ss
3
R
a
n
d
o
m e
x
c
u
r
si
o
n
v
a
r
i
a
n
t
t
e
st
0
.
8
0
8
9
4
1
P
a
ss
10
L
i
n
e
a
r
c
o
mp
l
e
x
i
t
y
t
e
st
0
.
5
9
8
9
6
8
P
a
ss
4
R
a
n
d
o
m e
x
c
u
r
si
o
n
t
e
st
0
.
7
2
5
0
5
3
P
a
ss
11
F
r
e
q
u
e
n
c
y
t
e
st
w
i
t
h
i
n
a
b
l
o
c
k
t
e
st
0
.
8
7
5
7
8
2
P
a
ss
5
O
v
e
r
l
a
p
p
i
n
g
t
e
mp
l
a
t
e
ma
t
c
h
i
n
g
t
e
st
0
.
9
4
4
7
2
P
a
ss
12
D
i
scre
t
e
f
o
u
r
i
e
r
t
r
a
n
sf
o
r
m
t
e
st
0
.
6
3
3
7
9
2
P
a
ss
6
N
o
n
-
o
v
e
r
l
a
p
p
i
n
g
t
e
m
p
l
a
t
e
ma
t
c
h
i
n
g
t
e
st
0
.
9
6
3
3
7
2
P
a
ss
13
C
u
m
u
l
a
t
i
v
e
s
u
ms
t
e
st
0
.
9
7
1
5
8
4
P
a
ss
7
F
r
e
q
u
e
n
c
y
m
o
n
o
b
i
t
t
e
st
0
.
9
3
9
9
1
1
P
a
ss
T
ab
le
7
.
T
h
e
d
if
f
er
en
tial te
s
t (
UC
A
I
an
d
P
C
NR
)
#
U
C
A
I
N
P
C
R
#
U
C
A
I
N
P
C
R
1
3
2
.
6
3
2
8
1
9
8
.
2
1
2
5
5
7
3
2
.
1
2
3
0
2
9
9
.
0
3
9
7
4
2
3
2
.
2
2
4
5
5
9
8
.
1
7
5
9
8
3
3
.
7
2
3
7
3
9
8
.
4
5
1
4
8
3
3
2
.
2
2
3
5
5
9
8
.
4
5
9
4
1
9
3
2
.
5
6
7
3
1
9
8
.
7
7
6
4
3
3
.
7
9
1
7
5
9
8
.
6
3
6
7
8
10
3
1
.
9
7
2
0
7
9
8
.
4
0
4
9
5
3
2
.
9
3
4
4
1
9
8
.
0
4
0
9
7
11
3
3
.
1
9
2
2
8
9
8
.
4
4
1
3
2
6
3
3
.
0
6
8
4
9
8
.
1
7
4
6
3
12
3
4
.
2
2
9
8
9
9
.
1
6
3
3
2
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6930
T
E
L
KOM
NI
K
A
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l
C
o
n
tr
o
l
,
Vo
l.
23
,
No
.
6
,
Dec
em
b
er
20
25
:
1
7
4
3
-
1
754
1752
T
ab
le
8
.
C
o
m
p
ar
is
o
n
o
f
th
e
ti
m
e
co
n
s
u
m
p
tio
n
o
f
t
h
e
p
r
o
p
o
s
ed
m
et
h
o
d
w
ith
t
h
e
A
E
S
al
g
o
r
ith
m
P
r
o
p
o
se
d
me
t
h
o
d
A
ES
me
t
h
o
d
#
En
c
r
y
p
t
i
o
n
t
i
me
D
e
c
r
y
p
t
i
o
n
t
i
me
#
En
c
r
y
p
t
i
o
n
t
i
me
D
e
c
r
y
p
t
i
o
n
t
i
me
1
5
.
9
7
3
5
.
0
7
2
1
8
.
8
6
5
6
.
1
0
5
2
5
.
2
2
2
4
.
6
9
7
2
7
.
6
0
2
6
.
2
9
8
3
6
.
1
4
5
5
.
3
8
7
3
8
.
0
9
3
7
.
3
8
8
4
5
.
7
7
9
4
.
9
0
9
4
8
.
5
5
1
6
.
1
6
8
5
5
.
0
4
1
4
.
3
4
4
5
6
.
7
2
6
5
.
9
9
6
6
5
.
9
3
6
5
.
8
4
9
6
8
.
7
1
2
7
.
4
8
4
7
6
.
0
0
5
5
.
0
5
8
7
8
.
2
1
1
6
.
0
8
0
8
5
.
2
7
4
4
.
6
9
8
8
7
.
4
4
3
6
.
3
8
4
9
6
.
0
5
3
5
.
2
5
3
9
8
.
4
8
9
6
.
9
3
6
10
5
.
6
9
2
4
.
7
3
0
10
7
.
4
1
0
6
.
1
4
6
11
4
.
8
4
0
4
.
4
2
8
11
6
.
2
9
8
6
.
1
6
7
12
6
.
0
7
4
5
.
8
8
1
12
8
.
0
8
7
7
.
2
3
3
7.
CO
NCLU
SI
O
N
T
h
e
en
cr
y
p
tio
n
tec
h
n
iq
u
e
th
a
t
w
o
r
k
s
w
ell
f
o
r
m
ed
ical
f
ac
i
liti
es
t
h
at
o
f
f
er
elec
tr
o
n
ic
s
er
v
ices
a
n
d
m
ed
ical
s
y
s
te
m
s
h
a
s
b
ec
o
m
e
cr
u
cial.
T
h
e
s
u
g
g
ested
tec
h
n
i
q
u
e
r
elies
o
n
a
l
ig
h
t
w
ei
g
h
t
en
cr
y
p
tio
n
o
f
DI
C
O
M
i
m
a
g
es,
b
ased
o
n
a
s
p
ec
if
ic
d
ec
o
m
p
o
s
i
tio
n
tec
h
n
iq
u
e
ca
lle
d
th
e
q
u
ad
tr
ee
tech
n
iq
u
e,
w
h
i
ch
s
p
lits
t
h
e
i
m
a
g
e
in
to
b
lo
ck
s
o
f
v
ar
y
i
n
g
s
izes.
T
h
e
Hen
o
n
m
ap
(
2
D
f
u
n
ctio
n
)
is
u
s
ed
to
g
e
n
er
ate
th
e
k
e
y
s
.
T
h
e
f
ir
s
t
s
et
o
f
g
en
er
ated
n
u
m
b
er
s
i
s
u
s
ed
in
th
e
p
er
m
u
tatio
n
o
f
t
h
e
p
ix
e
l
v
alu
es
’
b
its
,
a
n
d
th
e
s
ec
o
n
d
s
e
t
is
e
m
p
lo
y
ed
in
t
h
e
s
u
g
g
e
s
ted
en
cr
y
p
t
io
n
tec
h
n
iq
u
e.
T
h
e
ex
p
er
i
m
en
ts
,
w
h
ich
ex
p
lain
t
h
e
h
ig
h
MSE
a
n
d
lo
w
P
SNR
,
i
n
d
icate
s
ig
n
i
f
ica
n
t
d
if
f
er
en
ce
s
b
et
w
e
en
th
e
i
n
p
u
t
a
n
d
o
u
tp
u
t
DI
C
OM
i
m
a
g
es,
as
w
el
l
as
t
h
e
r
an
d
o
m
n
e
s
s
o
f
t
h
e
g
en
er
ated
k
e
y
,
an
d
ar
e
test
ed
u
s
i
n
g
a
s
tan
d
ar
d
test
(
NI
S
T
te
s
t)
.
T
h
e
co
r
r
elatio
n
s
o
f
en
cr
y
p
ted
im
a
g
es
ar
e
v
er
y
lo
w
,
in
d
icati
n
g
t
h
at
th
er
e
is
n
o
co
r
r
elatio
n
b
etw
ee
n
p
ix
el
s
in
th
e
en
cr
y
p
ted
i
m
a
g
es.
,
an
d
th
e
d
if
f
er
e
n
tial
attac
k
s
tes
ted
(
NP
C
R
an
d
UC
A
I
)
,
w
h
ich
ar
e
ap
p
r
o
x
i
m
a
te
l
y
3
3
.
3
%
an
d
9
9
.
5
%,
r
esp
ec
tiv
el
y
,
d
en
o
ti
n
g
h
ig
h
r
esis
ta
n
ce
to
d
if
f
er
en
t
ial
attac
k
s
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
co
u
ld
b
e
d
ev
elo
p
ed
to
en
cr
y
p
t
o
t
h
er
t
y
p
es
o
f
m
ed
ia,
s
u
c
h
as a
u
d
io
o
r
v
id
eo
,
in
an
ef
f
icien
t
m
a
n
n
er
.
ACK
NO
WL
E
D
G
M
E
NT
S
T
h
e
au
th
o
r
s
w
o
u
ld
lik
e
to
th
a
n
k
t
h
e
Un
iv
er
s
it
y
o
f
Di
y
ala
(
U
OD)
,
p
ar
ticu
lar
l
y
Ali H
u
s
s
e
in
Fad
h
il,
f
o
r
p
r
o
v
id
in
g
t
h
e
ti
m
e
an
d
f
ac
ilit
i
es n
ec
es
s
ar
y
to
co
m
p
lete
t
h
is
s
tu
d
y
.
F
UNDIN
G
I
NF
O
RM
AT
I
O
N
T
h
is
s
tu
d
y
w
as sel
f
-
f
u
n
d
ed
b
y
th
e
au
t
h
o
r
s
.
AUTHO
R
CO
NT
RIB
UT
I
O
NS ST
A
T
E
M
E
NT
T
h
is
j
o
u
r
n
al
u
s
e
s
t
h
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT
)
to
r
ec
o
g
n
ize
in
d
i
v
id
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
t
h
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
lla
b
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
Mu
n
tah
a
A
b
d
u
lza
h
r
a
Hate
m
✓
✓
✓
✓
✓
B
alsa
m
A
b
d
u
l
k
ad
h
i
m
Ha
m
ee
d
i
✓
✓
✓
✓
✓
J
am
al
Na
s
ir
Haso
o
n
✓
✓
✓
✓
✓
✓
Fah
ad
Gh
a
lib
A
b
d
u
l
k
ad
h
u
m
✓
✓
✓
✓
✓
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
si
s
I
:
I
n
v
e
st
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
si
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
Evaluation Warning : The document was created with Spire.PDF for Python.