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CC B
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C
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r
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s
p
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A
uth
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r
:
J
u
d
e
He
m
an
t
h
Dep
ar
t
m
en
t o
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C
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Kar
u
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s
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ato
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n
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E
m
ail:
j
u
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a
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.
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1.
I
NT
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D
UCT
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O
N
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to
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HO,
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o
u
t
4
%
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f
th
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to
tal
p
o
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u
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i.e
.
,
2
8
5
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llio
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le)
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ated
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ab
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2
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le
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,
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n
d
3
9
m
il
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p
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ar
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l
etel
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d
[
1
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.
A
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p
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h
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s
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ies,
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.
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ar
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m
s
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m
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v
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ated
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o
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s
.
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h
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au
th
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s
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v
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m
aj
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C
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Sch
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b
y
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VSM
Ho
s
p
itals
.
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T
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h
as
to
g
u
id
e
an
d
i
m
p
r
o
v
e
tr
av
el
p
er
f
o
r
m
an
ce
th
a
n
t
h
e
e
x
is
ti
n
g
a
id
s
b
y
d
eli
v
er
in
g
m
o
r
e
in
f
o
r
m
atio
n
t
h
an
t
h
e
ex
is
t
in
g
o
n
es.
T
h
is
w
o
r
k
ai
m
s
to
d
etec
t
t
h
e
b
u
s
d
o
o
r
an
d
aler
t
th
e
v
i
s
u
a
ll
y
ch
alle
n
g
ed
p
er
s
o
n
ab
o
u
t
th
e
b
u
s
ar
r
i
v
al,
b
u
t
s
o
m
e
o
f
t
h
e
m
aj
o
r
p
r
o
b
l
e
m
s
en
co
u
n
ter
ed
ar
e
lo
ca
ti
n
g
th
e
d
o
o
r
o
f
b
u
s
es,
m
u
lt
ip
le
b
u
s
co
n
f
u
s
io
n
,
a
n
d
b
o
ar
d
in
g
in
to
th
e
d
esire
d
b
u
s
.
A
d
etec
tio
n
s
y
s
te
m
u
s
in
g
ca
m
er
a
-
b
ased
v
i
s
u
al
n
av
i
g
atio
n
h
as
b
ee
n
co
n
s
id
er
ed
to
o
v
er
co
m
e
t
h
e
m
a
n
d
s
u
p
p
o
r
ts
i
m
a
g
e
p
r
o
ce
s
s
i
n
g
to
f
i
n
d
t
h
e
b
u
s
a
n
d
r
o
u
te
i
n
f
o
r
m
atio
n
,
th
en
g
i
v
i
n
g
v
o
ice
r
esp
o
n
s
e
a
f
ter
d
etec
tio
n
,
a
n
d
i
n
p
ar
ticu
lar
,
i
t
i
s
u
s
ed
f
o
r
f
i
n
d
in
g
t
h
e
p
r
o
p
er
ties
o
f
t
h
e
b
u
s
d
o
o
r
.
T
h
e
s
y
s
te
m
is
d
esig
n
ed
to
b
e
co
s
t
ef
f
ec
ti
v
e
an
d
in
te
g
r
ated
w
it
h
t
h
e
lo
w
-
co
s
t
s
m
ar
t
ca
n
e
f
o
r
v
ib
r
atio
n
aler
ts
,
s
tair
ca
s
e
d
etec
tio
n
[
3
]
,
an
d
v
eh
icle
d
ete
ctio
n
[
4
]
.
2.
RE
L
AT
E
D
WO
RK
Fo
r
m
o
s
t
b
li
n
d
p
eo
p
le,
th
e
lo
s
s
o
f
v
i
s
io
n
is
ac
co
m
p
a
n
i
ed
b
y
a
lo
s
s
o
f
in
d
ep
en
d
en
ce
.
Of
th
e
1
.
1
m
illi
o
n
b
lin
d
p
eo
p
le
in
t
h
e
Un
ited
State
s
,
ab
o
u
t
1
0
,
0
0
0
u
s
e
g
u
id
e
d
o
g
s
,
an
d
1
0
0
,
0
0
0
[
5
]
ca
n
w
alk
in
d
ep
en
d
en
tl
y
o
n
lo
n
g
ca
n
es
[
2
]
,
leav
in
g
ab
o
u
t 1
m
il
lio
n
p
eo
p
le
d
ep
en
d
en
t o
n
o
th
er
s
f
o
r
m
o
v
e
m
e
n
t.
H
u
m
an
s
,
in
f
o
r
m
atio
n
p
r
o
ce
s
s
in
g
a
n
d
en
v
ir
o
n
m
e
n
tal
in
ter
p
r
etatio
n
.
I
n
d
ev
elo
p
in
g
co
u
n
tr
ie
s
,
th
is
r
elatio
n
s
h
ip
is
m
u
c
h
h
ig
h
er
.
O
f
all
t
h
e
d
is
ad
v
an
t
ag
es
a
s
s
o
ciate
d
w
it
h
b
li
n
d
n
e
s
s
,
t
h
e
lo
s
s
o
f
i
n
d
ep
en
d
en
ce
m
a
y
b
e
th
e
m
o
s
t
e
m
b
ar
r
ass
i
n
g
.
Ya
m
asa
k
i
et
a
l.
[
6
]
,
s
tate
th
at
th
e
p
er
s
o
n
s
w
i
th
v
i
s
u
a
l
d
is
ab
ilit
ies
ar
e
g
ett
i
n
g
d
e
m
o
ti
v
ated
f
o
r
th
e
lack
o
f
s
u
p
p
o
r
t
f
ac
ilit
ies
t
o
ac
ce
s
s
p
u
b
lic
tr
an
s
p
o
r
t,
lead
in
g
to
co
m
p
r
o
m
is
e
w
it
h
p
r
o
p
er
ed
u
ca
tio
n
,
w
o
r
k
,
an
d
s
el
f
-
d
e
v
elo
p
m
e
n
t
o
p
p
o
r
tu
n
i
ties
.
A
s
t
u
d
y
co
n
d
u
cted
b
y
[
7
]
h
as
p
i
n
p
o
in
ted
th
e
d
ep
en
d
en
ce
o
f
v
i
s
u
a
ll
y
ch
alle
n
g
ed
p
er
s
o
n
s
f
o
r
s
i
g
h
ted
ass
is
ta
n
ce
f
o
r
ex
ter
n
al
tr
a
v
el,
w
h
ic
h
lead
s
to
f
r
u
s
tr
atio
n
.
I
d
en
tif
icat
io
n
o
f
b
u
s
a
n
d
its
r
o
u
te
is
a
p
r
o
b
le
m
th
at
s
e
v
e
r
al
r
esear
ch
er
s
h
a
v
e
ad
d
r
ess
e
d
b
ef
o
r
e.
Ho
w
e
v
er
,
p
r
ec
is
e
r
ec
o
g
n
itio
n
o
f
th
e
b
u
s
d
o
o
r
an
d
n
av
ig
a
tio
n
to
b
o
ar
d
th
e
b
u
s
h
as
n
o
t
b
ee
n
ad
d
r
ess
ed
ad
eq
u
atel
y
.
T
h
e
cu
r
r
en
t
s
ta
te
o
f
th
e
ar
t
m
e
th
o
d
s
f
o
r
r
ec
o
g
n
i
zin
g
a
b
u
s
an
d
i
ts
r
o
u
te
is
ei
t
h
er
i
m
ag
e
-
b
ased
o
r
s
en
s
o
r
-
b
ase
d
.
B
u
s
d
etec
tio
n
a
n
d
r
ec
o
g
n
itio
n
b
ased
o
n
s
a
tel
lite
s
ig
n
als
o
r
w
ir
eles
s
n
et
w
o
r
k
co
m
m
u
n
icatio
n
h
as b
ee
n
d
ev
elo
p
ed
in
s
o
m
e
b
u
s
s
tatio
n
s
.
Ma
u
r
e
et
a
l.
[
8
]
p
r
o
p
o
s
ed
a
d
u
al
en
d
s
y
s
te
m
,
a
b
u
s
s
u
b
s
y
s
te
m
,
a
n
d
a
s
tatio
n
s
u
b
s
y
s
te
m
co
n
n
ec
ted
t
o
a
d
atab
ase
an
d
all
co
m
m
u
n
icatin
g
to
o
n
e
an
o
th
er
an
d
th
e
b
lin
d
p
er
s
o
n
s
v
ia
r
ad
io
f
r
eq
u
en
c
y
id
en
ti
f
ica
tio
n
(
R
FID
)
tag
s
.
A
ll
th
r
ee
e
n
titi
e
s
,
th
e
b
li
n
d
u
s
er
,
th
e
b
u
s
s
tatio
n
,
an
d
th
e
b
u
s
its
el
f
,
h
av
e
R
FID
ta
g
s
.
T
h
e
b
u
s
s
ta
ti
o
n
an
d
b
u
s
al
s
o
h
av
e
a
n
R
FID
r
ea
d
er
.
T
h
e
b
lin
d
p
er
s
o
n
ca
n
p
u
r
ch
a
s
e
a
tick
e
t
an
d
g
e
t
b
u
s
i
n
f
o
r
m
atio
n
i
n
a
n
R
FID
tag
.
T
h
e
b
u
s
s
tat
io
n
an
d
b
u
s
ca
n
r
ea
d
th
at
i
n
f
o
r
m
atio
n
to
p
r
o
v
id
e
ap
p
r
o
p
r
iate
an
n
o
u
n
ce
m
e
n
ts
a
n
d
aler
t
t
h
e
d
r
iv
er
.
T
h
e
s
y
s
te
m
w
o
r
k
s
p
r
ec
is
el
y
,
b
u
t
n
ee
d
to
b
e
in
s
talled
o
n
ev
er
y
b
u
s
a
n
d
s
tatio
n
.
Mo
r
eo
v
er
,
th
e
b
lin
d
p
er
s
o
n
n
ee
d
s
to
c
ar
r
y
a
n
ad
d
itio
n
al
d
e
v
ice
a
n
d
g
et
tr
ai
n
ed
to
u
s
e
it.
Sti
ll,
th
e
s
y
s
te
m
m
a
y
n
o
t
h
elp
th
e
b
lin
d
p
er
s
o
n
b
o
ar
d
th
e
b
u
s
,
o
th
er
t
h
an
i
n
d
icati
n
g
w
h
ic
h
b
u
s
to
b
o
ar
d
an
d
w
h
e
n
to
g
et
d
o
w
n
f
r
o
m
th
e
b
u
s
.
He
y
es
[
9
]
p
r
esen
t
a
s
i
m
i
lar
s
y
s
te
m
at
a
m
u
c
h
lo
w
er
co
s
t
s
u
ited
to
I
n
d
ian
n
ee
d
s
.
I
t
co
m
p
r
is
es
t
h
r
ee
m
o
d
u
les,
s
u
c
h
as
u
s
er
m
o
d
u
l
e,
b
u
s
m
o
d
u
le
,
p
lace
d
in
ea
c
h
b
u
s
,
a
n
d
th
e
p
r
o
g
r
a
m
m
i
n
g
u
n
i
t
to
ch
a
n
g
e
r
o
u
te
n
u
m
b
er
s
a
t
t
h
e
d
ep
o
t.
Up
o
n
h
ea
r
in
g
a
b
u
s
s
to
p
p
in
g
t
h
e
b
u
s
s
to
p
,
a
v
is
u
all
y
c
h
alle
n
g
ed
p
er
s
o
n
ca
n
p
r
ess
a
q
u
er
y
b
u
tto
n
o
n
th
e
u
s
er
m
o
d
u
le
f
e
tch
i
n
g
th
e
r
o
u
te
n
u
m
b
er
o
f
all
b
u
s
es
i
n
t
h
e
v
ic
in
i
t
y
v
ia
r
ad
io
f
r
eq
u
en
c
y
(
R
F)
s
i
g
n
a
l,
th
e
n
s
eq
u
en
tiall
y
r
ea
d
o
u
t
b
y
th
e
u
s
er
m
o
d
u
le.
User
s
ca
n
s
elec
t
t
h
e
d
esire
d
r
o
u
te
b
y
p
r
ess
i
n
g
a
b
u
tto
n
a
f
ter
h
ea
r
i
n
g
t
h
e
r
o
u
te
n
u
m
b
er
an
d
in
i
tiates
a
v
o
ice
o
u
tp
u
t
at
th
e
s
elec
ted
b
u
s
'
s
en
tr
y
,
ac
ti
n
g
as
an
au
d
ito
r
y
cu
e
to
as
s
is
t i
n
m
o
v
i
n
g
to
w
ar
d
s
th
e
b
u
s
g
ate.
T
h
e
s
y
s
te
m
i
s
ef
f
ec
t
iv
e
b
u
t r
eq
u
ir
es a
s
p
ec
ial
m
o
d
u
le
to
b
e
ca
r
r
ied
b
y
t
h
e
u
s
er
.
He
y
es
[
1
0
]
u
s
e
b
lu
eto
o
t
h
d
ev
ices
o
n
b
u
s
e
s
co
m
m
u
n
ica
tin
g
w
it
h
R
a
s
p
b
er
r
y
P
i
in
s
talled
at
th
e
b
u
s
s
to
p
to
d
etec
t
an
d
an
n
o
u
n
ce
b
u
s
ar
r
iv
a
l.
A
u
d
ito
r
y
c
u
e
i
s
a
s
ig
n
if
ican
t
h
elp
f
o
r
a
v
is
u
all
y
ch
alle
n
g
ed
p
er
s
o
n
.
Var
iatio
n
s
in
s
p
atial
r
elat
io
n
s
h
ip
s
ca
n
b
e
p
er
ce
iv
ed
w
it
h
s
h
i
f
t
in
g
s
o
u
n
d
s
e
m
itted
b
y
th
e
o
b
j
e
cts i
n
t
h
e
v
ici
n
it
y
.
L
is
ten
i
n
g
to
t
h
e
ec
h
o
es
o
f
e
m
i
tted
s
o
u
n
d
s
a
n
d
s
o
u
n
d
s
m
ad
e
b
y
th
e
p
er
s
o
n
ca
n
i
n
d
icate
t
h
e
d
is
tan
ce
to
a
w
al
l
,
th
e
p
r
esen
ce
o
f
a
d
o
o
r
w
a
y
,
a
n
d
m
a
n
y
m
o
r
e
[
1
1
]
.
B
u
t o
n
ly
a
f
ter
s
o
m
e
d
ec
en
t p
r
ac
tice
ca
n
o
n
e
m
a
s
ter
th
i
s
ar
t.
An
o
th
er
c
u
e
f
o
r
d
ir
ec
tio
n
ca
n
co
m
e
f
r
o
m
d
ir
ec
tio
n
all
y
-
s
p
ec
i
f
ic
s
o
u
r
ce
s
o
f
h
ea
t
an
d
o
d
o
r
.
Go
ld
ie
[
1
2
]
s
u
g
g
e
s
t
d
etec
ti
n
g
a
n
air
-
co
n
d
itio
n
ed
b
u
s
'
s
d
o
o
r
b
y
t
h
e
co
o
l
air
th
at
f
lo
w
s
o
u
t
w
h
en
t
h
e
d
o
o
r
is
o
p
en
ed
.
Ho
w
e
v
er
,
in
I
n
d
ian
s
etti
n
g
s
,
m
o
s
t
b
u
s
e
s
ar
e
n
o
n
-
a
ir
-
co
n
d
itio
n
ed
.
Hen
ce
t
h
e
b
est
s
o
l
u
tio
n
to
d
ate
is
t
h
e
au
d
ito
r
y
s
i
g
n
a
l c
o
m
i
n
g
f
r
o
m
a
s
p
ea
k
er
m
o
u
n
ter
at
t
h
e
b
u
s
's d
o
o
r
w
a
y
.
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.
1
9
,
No
.
6
,
Decem
b
er
2021
:
1
9
2
4
-
1934
1926
Sen
s
o
r
-
b
ased
s
o
lu
tio
n
s
r
eq
u
i
r
e
p
r
e
-
in
s
talla
tio
n
o
f
t
h
e
s
e
n
s
o
r
s
an
d
p
er
io
d
ic
m
a
in
te
n
a
n
ce
.
T
h
u
s
v
is
io
n
-
b
ased
tech
n
o
lo
g
y
ca
n
p
r
o
v
id
e
an
alter
n
ativ
e
m
ea
n
s
to
d
etec
t
an
d
r
ec
o
g
n
ize
th
e
b
u
s
.
B
r
ab
y
n
[
1
3
]
d
esig
n
a
co
m
p
u
ter
v
is
io
n
-
b
as
ed
s
y
s
te
m
to
d
etec
t
a
b
u
s
.
T
h
eir
b
u
s
class
i
f
ier
e
m
p
lo
y
s
h
is
to
g
r
a
m
o
f
o
r
ien
ted
g
r
ad
ien
t
(
HO
G
)
-
b
ased
f
ea
tu
r
e
ex
tr
ac
tio
n
an
d
a
ca
s
ca
d
ed
s
u
p
p
o
r
t
v
ec
to
r
m
ac
h
i
n
e
(
SV
M
)
lear
n
in
g
m
o
d
el
.
A
l
s
o
,
th
e
y
r
ec
o
g
n
ize
b
u
s
r
o
u
t
e
n
u
m
b
er
s
v
ia
a
s
ce
n
e
tex
t
e
x
tr
ac
tio
n
al
g
o
r
it
h
m
b
a
s
ed
o
n
la
y
o
u
t
a
n
al
y
s
i
s
a
n
d
tex
t
f
ea
t
u
r
e
lear
n
i
n
g
.
T
s
ai
an
d
Yeh
[
1
4
]
Used
a
s
ce
n
e
te
x
t
e
x
tr
ac
tio
n
al
g
o
r
ith
m
to
lo
ca
lize
an
d
r
ec
o
g
n
ize
t
h
e
tex
t
in
f
o
r
m
at
io
n
o
f
th
e
b
u
s
r
o
u
te.
T
h
is
s
y
s
te
m
ac
h
iev
ed
h
i
g
h
ac
cu
r
ac
y
o
f
b
u
s
r
eg
io
n
d
etec
tio
n
.
Fu
r
t
h
er
m
o
r
e,
th
e
s
ce
n
e
te
x
t
ex
tr
ac
tio
n
al
g
o
r
ith
m
s
u
cc
ess
f
u
ll
y
r
etr
iev
e
s
t
h
e
b
u
s
r
o
u
te
n
u
m
b
er
'
s
te
x
t
i
n
f
o
r
m
atio
n
.
T
s
ai
an
d
Yeh
[
1
4
]
p
r
o
p
o
s
ed
a
tex
t
d
ete
ctio
n
m
eth
o
d
to
d
etec
t
t
h
e
b
u
s
r
o
u
te
n
u
m
b
er
in
th
e
tex
t
r
eg
io
n
o
n
t
h
e
b
u
s
to
p
p
an
el.
T
h
e
y
u
s
e
t
h
e
b
ac
k
g
r
o
u
n
d
d
is
tr
ib
u
tio
n
a
n
d
th
e
th
r
es
h
o
ld
s
o
f
t
h
e
b
o
u
n
d
ar
y
to
f
in
d
t
h
e
ar
ea
o
f
tex
t
th
a
t
b
ec
o
m
e
s
a
v
o
ice
an
n
o
u
n
ce
m
e
n
t.
Ho
w
ev
er
,
th
e
ir
m
et
h
o
d
o
n
l
y
d
etec
ts
t
h
e
tex
t
ar
ea
o
n
t
h
e
f
r
o
n
t
p
an
el
o
f
t
h
e
b
u
s
a
n
d
d
o
es
n
o
t
e
x
tr
ac
t
th
e
r
o
u
te
n
u
m
b
er
o
f
t
h
e
b
u
s
.
Gr
a
n
th
a
m
[
1
5
]
u
s
e
s
a
n
M
SER
-
b
ased
tex
t
d
etec
tio
n
alg
o
r
ith
m
co
m
b
i
n
ed
w
it
h
M
SER
s
e
g
m
en
tatio
n
to
o
b
tain
ea
ch
ch
ar
ac
ter
.
T
h
e
ex
tr
ac
t
ed
ch
ar
ac
ter
s
ar
e
r
ec
o
g
n
ized
b
y
a
w
e
ll
-
tr
ain
ed
co
n
v
o
lu
tio
n
al
n
e
u
r
al
n
et
w
o
r
k
(
C
NN)
.
G
u
id
a
e
t
a
l.
[
1
6
]
p
r
o
p
o
s
es
b
u
s
n
u
m
b
er
d
etec
tio
n
an
d
r
ec
o
g
n
itio
n
b
y
ca
s
ca
d
in
g
A
d
ab
o
o
s
t
-
b
ased
cla
s
s
i
f
ier
s
,
an
d
th
e
n
u
s
es
r
o
b
u
s
t
g
eo
m
etr
ic
m
atch
in
g
to
i
m
p
r
o
v
e
m
atc
h
i
n
g
.
T
h
e
a
ctu
al
d
i
g
ital
s
e
g
m
e
n
tat
io
n
i
s
d
o
n
e
th
r
o
u
g
h
p
er
s
p
ec
ti
v
e
c
o
r
r
ec
tio
n
,
an
d
th
e
n
co
n
v
er
ted
to
hue
-
s
atu
r
atio
n
-
v
a
lu
e
(
HSV)
co
lo
r
s
p
ac
e
an
d
th
r
esh
o
ld
.
Fin
a
ll
y
,
O
C
R
is
u
s
ed
to
id
en
t
if
y
n
u
m
b
er
s
.
P
an
et
a
l.
[
1
7
]
u
s
e
HOG
a
n
d
SVM
to
d
etec
t
b
u
s
p
o
s
itio
n
.
Fo
r
b
u
s
r
o
u
te
d
etec
tio
n
,
th
e
y
u
s
e
ad
j
ac
en
t
ch
ar
ac
ter
g
r
o
u
p
i
n
g
a
n
d
in
telli
g
e
n
t
ed
g
e
d
etec
ti
o
n
to
f
in
d
ca
n
d
id
ate
r
eg
io
n
s
,
e
x
tr
ac
t
Haa
r
lik
e
f
ea
tu
r
es
f
r
o
m
t
h
e
m
,
an
d
e
n
ter
t
h
e
m
in
to
A
d
ab
o
o
s
t
to
cla
s
s
i
f
y
ea
c
h
co
m
p
o
n
e
n
t
[
1
8
]
,
[
1
9
]
.
Fin
all
y
,
t
h
e
y
u
s
ed
o
p
tical
ch
ar
ac
ter
r
ec
o
g
n
itio
n
(
OC
R
)
s
o
f
t
w
ar
e
co
m
b
in
ed
w
it
h
a
tex
t
-
to
-
s
p
ee
c
h
s
y
n
t
h
esizer
to
g
e
n
er
ate
a
u
d
io
.
On
e
i
s
s
u
e
w
i
th
v
is
io
n
-
b
ased
a
p
p
r
o
ac
h
es
is
t
h
at
th
e
y
v
io
late
p
r
iv
ac
y
.
T
h
er
ef
o
r
e,
s
m
ar
t
m
ec
h
a
n
i
s
m
s
m
u
s
t
b
e
in
teg
r
ated
i
n
to
th
e
m
o
n
ito
r
in
g
s
y
s
te
m
s
o
t
h
at
th
e
y
ca
n
f
o
cu
s
o
n
th
e
p
r
o
m
in
e
n
t
ev
en
t
s
o
f
i
n
ter
est
(
d
etec
tio
n
d
o
o
r
s
)
w
it
h
o
u
t
p
r
o
v
id
i
n
g
an
y
o
t
h
er
ir
r
elev
an
t
v
i
s
u
al
in
f
o
r
m
atio
n
,
t
h
u
s
m
ai
n
tai
n
in
g
p
r
iv
ac
y
.
R
ec
en
t
l
y
,
t
h
e
lite
r
atu
r
e
h
as
p
r
o
p
o
s
ed
clea
r
v
is
u
al
in
f
o
r
m
ati
o
n
f
o
r
d
etec
tin
g
d
o
o
r
s
.
Fe
w
m
et
h
o
d
s
ar
e
b
ased
o
n
esti
m
ati
n
g
h
u
m
a
n
m
o
tio
n
u
n
d
er
co
m
p
lex
b
ac
k
g
r
o
u
n
d
co
n
d
itio
n
s
,
s
u
ch
as
t
h
o
s
e
f
o
u
n
d
i
n
h
ea
v
y
tr
af
f
ic
[
2
0
]
-
[
2
3
]
.
I
n
ad
d
itio
n
,
th
ese
m
et
h
o
d
s
also
i
n
cl
u
d
e
m
a
ch
in
e
lear
n
i
n
g
[
2
4
]
an
d
co
n
g
e
s
tio
n
al
g
o
r
ith
m
s
to
d
is
tin
g
u
is
h
b
u
s
d
o
o
r
s
f
r
o
m
o
t
h
er
d
o
o
r
s
.
3.
M
E
T
H
O
DO
L
O
G
Y
T
h
i
s
w
o
r
k
'
s
m
ai
n
m
o
ti
v
e
i
s
t
o
d
e
t
e
c
t
th
e
b
u
s
d
o
o
r
a
n
d
a
l
e
r
t
t
h
e
v
is
u
a
l
ly
ch
al
l
en
g
e
d
p
e
r
s
o
n
a
b
o
u
t
th
e
b
u
s
a
r
r
iv
a
l
an
d
g
u
i
d
e
h
im
in
b
o
a
r
d
i
n
g
t
h
e
b
u
s
.
Ne
v
e
r
th
e
l
es
s
,
s
o
m
e
o
f
t
h
e
m
a
jo
r
p
r
o
b
l
em
s
e
n
c
o
u
n
t
e
r
e
d
d
u
r
i
n
g
t
h
is
p
r
o
c
e
s
s
a
r
e
l
o
c
a
t
in
g
th
e
d
o
o
r
o
f
b
u
s
es
,
m
u
lt
i
p
l
e
b
u
s
c
o
n
f
u
s
i
o
n
,
r
e
c
o
g
n
i
z
in
g
th
e
s
t
a
i
r
c
as
e
t
o
b
o
a
r
d
t
h
e
b
u
s
,
a
n
d
b
o
a
r
d
in
g
in
t
o
t
h
e
d
esire
d
b
u
s
.
I
n
th
i
s
w
o
r
k
,
a
d
e
te
c
t
i
o
n
s
y
s
tem
u
s
in
g
ca
m
e
r
a
-
b
a
s
e
d
v
is
u
a
l
n
av
ig
at
i
o
n
h
a
s
b
e
e
n
c
o
n
s
i
d
e
r
e
d
f
o
r
o
v
e
r
c
o
m
in
g
th
o
s
e
p
r
o
b
l
em
s
an
d
s
u
p
p
o
r
t
s
im
ag
e
p
r
o
c
es
s
i
n
g
,
w
h
i
ch
is
u
s
e
d
t
o
p
r
o
c
e
s
s
im
ag
es
,
t
h
e
n
g
iv
in
g
v
o
i
c
e
r
e
s
p
o
n
s
e
af
t
e
r
d
et
e
c
ti
o
n
,
an
d
in
p
ar
t
i
cu
l
a
r
,
i
t
is
u
s
e
d
f
o
r
f
in
d
in
g
th
e
p
r
o
p
e
r
t
ie
s
o
f
th
e
d
o
o
r
o
f
t
h
e
b
u
s
an
d
s
t
a
i
r
c
as
e
in
t
h
e
b
u
s
.
3
.
1
.
S
y
s
t
em
a
r
ch
i
t
ec
t
u
r
e
T
h
e
e
n
ti
r
e
p
r
o
c
e
s
s
o
f
b
o
a
r
d
in
g
th
e
b
u
s
b
y
a
v
i
s
u
al
ly
im
p
a
i
r
e
d
p
e
r
s
o
n
c
an
b
e
d
iv
i
d
e
d
in
t
o
3
d
i
f
f
e
r
en
t
p
h
a
s
e
s
,
R
ec
o
g
n
it
i
o
n
o
f
in
t
en
d
e
d
b
u
s
,
i
d
en
tif
y
in
g
th
e
b
u
s
d
o
o
r
a
n
d
b
u
s
b
o
a
r
d
in
g
/
d
i
s
em
b
a
r
k
in
g
.
T
h
e
p
r
o
p
o
s
e
d
m
o
d
e
l
h
a
s
b
e
en
d
em
o
n
s
t
r
a
te
d
i
n
th
e
Fi
g
u
r
e
1
.
T
h
e
F
ig
u
r
e
1
d
e
p
i
c
d
t
s
th
e
en
t
i
r
e
w
o
r
k
in
g
m
o
d
e
l
o
f
t
h
e
p
r
o
p
o
s
e
d
s
y
s
tem
.
T
h
e
F
ig
u
r
e
1
c
le
a
r
ly
d
e
p
i
c
t
s
th
e
l
o
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2
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Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
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r
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2
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[
2
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.
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.
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
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1
9
,
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6
,
Decem
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er
2021
:
1
9
2
4
-
1934
1928
3
.
5
.
B
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Fig
u
r
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3
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[
2
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p
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ith
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th
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s
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r
k
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th
e
b
u
s
i
s
d
e
te
c
t
e
d
u
s
in
g
[
2
5
]
m
u
l
t
iv
a
r
i
a
t
e
g
en
e
r
al
i
z
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d
G
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ly
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.
F
ig
u
r
e
3
.
B
u
s
d
o
o
r
d
e
t
e
c
t
i
o
n
p
r
o
c
e
s
s
H
o
u
g
h
T
r
a
n
s
f
o
r
m
A
l
g
o
r
i
th
m
1. Initi
alize
H [d,
θ] =
0
2. for e
very e
dge p
oint I
[
x, y] in
the i
mage
F
o
r
θ
=
[
θm
i
n
t
o
θ
m
a
x
]
d = x co
s θ
–
y
s
i
n
θ
H
[
d,
θ
]
+
=
1
3. Find
the va
lues
of (d,
θ) where
, H [d
, θ]
is max
i
mum.
4. The d
etecte
d lin
e
f
r
o
m
t
h
e
i
m
a
ge
i
s
gi
v
e
n
b
y
d = x co
s θ
–
y
s
i
n
θ
T
h
e
m
a
in
r
e
a
s
o
n
f
o
r
c
h
o
o
s
i
n
g
t
h
e
H
o
u
g
h
t
r
a
n
s
f
o
r
m
i
s
th
at
t
h
e
H
o
u
g
h
t
r
an
s
f
o
r
m
i
s
a
g
l
o
b
a
l
m
e
th
o
d
f
o
r
d
e
t
e
c
t
in
g
s
t
r
aig
h
t
lin
e
s
.
On
c
e
th
e
a
n
a
ly
s
i
s
in
d
i
c
at
e
s
th
e
b
u
s
o
b
je
c
t
i
s
d
e
t
e
c
te
d
,
a
r
e
l
ev
an
t
v
o
i
c
e
m
es
s
a
g
e
w
il
l
b
e
s
en
t
t
o
th
e
u
s
e
r
,
s
p
e
c
if
y
in
g
th
e
b
u
s
d
o
o
r
'
s
l
o
c
at
i
o
n
,
th
e
p
a
th
t
o
t
h
e
b
u
s
th
at
th
e
u
s
e
r
w
an
ts
t
o
b
o
a
r
d
,
a
n
d
b
o
a
r
d
in
g
t
h
e
b
u
s
.
T
h
e
p
r
o
c
es
s
o
f
b
o
ar
d
i
n
g
th
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b
u
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v
o
lv
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s
i
d
en
t
if
y
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g
th
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s
t
ai
r
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e
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n
th
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w
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a
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at
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G
au
s
s
i
a
n
m
ix
t
u
r
e
m
o
d
e
l
[
2
6
]
.
I
n
th
e
n
ex
t
s
e
c
t
i
o
n
,
th
e
e
x
p
e
r
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t
a
t
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d
.
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
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t E
l
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n
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o
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A
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s
s
is
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g
mo
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el
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e
visu
a
lly
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a
llen
g
ed
to
d
etec
t b
u
s
d
o
o
r
a
cc
u
r
a
tely
(
S
r
ee
n
u
P
o
n
n
a
d
a
)
1929
4.
CASE
S
T
UD
Y
T
h
is
w
o
r
k
ai
m
s
to
d
etec
t
th
e
b
u
s
o
b
j
ec
t
in
th
e
cu
r
r
en
t
s
ce
n
ar
io
,
d
etec
t
its
d
o
o
r
,
an
d
f
in
all
y
,
th
e
p
at
h
to
b
o
ar
d
th
e
b
u
s
v
ia
th
e
s
tair
c
ase
as
o
u
tp
u
t
i
n
t
h
e
f
o
r
m
o
f
r
elev
an
t
v
o
ice
s
i
g
n
al
s
.
T
h
u
s
,
t
h
e
cu
r
r
e
n
t
s
ce
n
ar
io
ca
p
tu
r
ed
th
r
o
u
g
h
a
m
o
b
ile
ca
m
er
a
is
f
ed
as
in
p
u
t
f
o
r
th
e
s
y
s
te
m
f
o
r
ev
er
y
ca
s
e.
T
h
e
i
n
p
u
t
v
id
eo
s
eq
u
e
n
ce
b
u
s
is
d
etec
ted
u
s
i
n
g
MG
GM
M,
an
d
th
e
n
w
e
f
i
n
d
th
e
b
u
s
d
o
o
r
u
s
i
n
g
t
h
e
Ho
u
g
h
tr
an
s
f
o
r
m
.
A
f
ter
d
etec
tin
g
t
h
e
b
u
s
d
o
o
r
,
w
e
w
ill
m
ea
s
u
r
e
th
e
d
o
o
r
'
s
d
is
ta
n
ce
f
r
o
m
t
h
e
u
s
er
'
s
p
o
s
itio
n
a
n
d
g
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e
t
h
e
d
ir
ec
tio
n
s
to
r
ea
ch
th
e
d
o
o
r
s
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el
y
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h
r
o
u
g
h
v
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es
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ag
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o
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tp
u
t.
Up
o
n
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ch
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g
th
e
b
u
s
,
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h
e
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s
er
n
ee
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s
to
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e
g
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o
r
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o
ar
d
in
g
th
e
b
u
s
v
ia
t
h
e
s
tair
ca
s
e
d
etec
ted
u
s
i
n
g
t
h
e
b
iv
ar
iate
Gau
s
s
ia
n
m
i
x
t
u
r
e
m
o
d
el.
T
h
e
Fi
g
u
r
es
4
to
7
d
em
o
n
s
tr
ate
s
th
e
ca
s
e
s
t
u
d
y
-
I
&
I
I
o
f
ex
p
er
i
m
e
n
tatio
n
.
Fig
u
r
e
4
.
B
u
s
d
etec
ted
af
ter
p
er
f
o
r
m
i
n
g
MG
GM
M
m
et
h
o
d
f
r
o
m
t
h
e
v
i
d
eo
s
eq
u
en
ce
Fig
u
r
e
5
.
T
h
e
b
u
s
d
o
o
r
s
o
f
th
e
d
etec
ted
b
u
s
af
ter
p
er
f
o
r
m
in
g
u
s
i
n
g
t
h
e
Ho
u
g
h
tr
an
s
f
o
r
m
Fig
u
r
e
6
.
B
u
s
d
etec
ted
af
ter
p
er
f
o
r
m
i
n
g
MG
GM
M
m
et
h
o
d
f
r
o
m
th
e
v
id
eo
s
eq
u
e
n
ce
Fig
u
r
e
7
.
B
u
s
d
etec
ted
af
ter
p
er
f
o
r
m
i
n
g
MG
GM
M
m
et
h
o
d
f
r
o
m
th
e
v
id
eo
s
eq
u
e
n
ce
4
.
1
.
Ca
s
e
s
t
ud
y
–
I
I
n
th
i
s
ca
s
e
s
t
u
d
y
,
w
e
h
a
v
e
u
tili
ze
d
m
u
lti
v
ar
iate
g
en
er
a
lized
Gau
s
s
ian
m
i
x
tu
r
e
m
o
d
el
m
et
h
o
d
(
MG
GM
M)
m
et
h
o
d
f
o
r
d
etec
tin
g
th
e
b
u
s
i
n
itiall
y
a
n
d
th
e
n
i
d
en
tify
t
h
e
b
u
s
d
o
o
r
s
w
h
e
n
t
h
e
b
u
s
is
i
n
r
u
n
n
in
g
co
n
d
itio
n
o
n
th
e
r
o
ad
s
a
n
d
is
h
alted
at
b
u
s
s
to
p
.
T
h
e
Fig
u
r
e
4
d
em
o
n
s
tr
ate
s
t
h
at
t
h
e
b
u
s
i
s
in
itia
ll
y
id
en
ti
f
ied
.
L
ater
i
n
Fi
g
u
r
e
5
clea
r
l
y
id
e
n
tif
ie
s
t
h
e
b
u
s
d
o
o
r
s
an
d
i
s
m
a
r
k
ed
as
b
o
u
n
d
i
n
g
b
o
x
.
I
n
p
u
t:
th
e
e
n
v
ir
o
n
m
en
tal
s
ce
n
ar
io
.
I
n
p
u
t
i
m
a
g
e
as s
h
o
wn
in
Fig
u
r
e
4
an
d
o
u
tp
u
t i
m
a
g
e
as sh
o
w
n
in
Fig
u
r
e
5
4
.
2
.
Ca
s
e
s
t
ud
y
–
II
I
n
th
i
s
ca
s
e
s
t
u
d
y
,
w
e
h
a
v
e
u
tili
ze
d
m
u
lti
v
ar
iate
g
en
er
a
lized
Gau
s
s
ian
m
i
x
tu
r
e
m
o
d
el
m
et
h
o
d
(
MG
GM
M)
m
et
h
o
d
f
o
r
d
etec
tin
g
th
e
b
u
s
i
n
itiall
y
a
n
d
th
e
n
i
d
en
tify
t
h
e
b
u
s
d
o
o
r
s
w
h
e
n
t
h
e
b
u
s
is
s
tatio
n
ed
at
th
e
b
u
s
d
ep
o
t
f
o
r
p
ass
en
g
er
s
t
o
b
o
ar
d
th
e
b
u
s
.
T
h
e
Fig
u
r
e
4
d
em
o
n
s
tr
ate
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RE
F
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R
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NC
E
S
[1
]
K
.
Li
,
“
El
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[3
]
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.
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lal,
a
n
d
S
.
M
o
o
re
,
“
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ra
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in
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l
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6
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.
[4
]
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g
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g
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u
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.
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ip
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,
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S
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m
,
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IEE
E.
Co
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n
1
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5
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9
4
,
1
9
9
4
,
pp
.
4
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0
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1
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.
[5
]
W
.
Ba
r
f
ield
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n
d
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.
Ca
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ll
,
"
F
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n
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tals
o
f
W
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r
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ters
a
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d
A
u
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Re
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li
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,
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L
a
wre
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Erlb
a
u
m
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.
[6
]
H.
Ya
m
a
s
a
k
i,
H.
Ha
sh
im
o
to
,
K.
M
a
g
a
tan
i
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a
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d
K.
Ya
n
a
sh
im
a
,
"
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o
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th
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m
f
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ll
y
im
p
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ired
,
"
Pro
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e
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d
in
g
s
o
f
t
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e
2
2
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d
An
n
u
a
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ter
n
a
t
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l
Co
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n
c
e
o
f
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h
e
IEE
E
En
g
in
e
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M
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d
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o
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[7
]
R.
G
.
G
o
ll
e
d
g
e
,
J.
R
.
M
a
rsto
n
,
a
n
d
C
.
M
.
Co
sta
n
z
o
,
“
A
tt
it
u
d
e
s
o
f
v
isu
a
ll
y
i
m
p
a
ired
p
e
rso
n
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u
se
o
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p
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li
c
tran
sp
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rtati
o
n
,
”
J
o
u
rn
a
l
o
f
Vi
su
a
l
Imp
a
irme
n
t
a
n
d
Bl
i
n
d
n
e
ss
,
pp
.
4
4
6
–
4
5
9
,
1
9
9
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
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(
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1933
[8
]
D.
R.
M
a
u
re
,
C.
M.
M
e
ll
o
r
,
a
n
d
M
.
Us
lan
,
"
A
F
B'
s
c
o
m
p
u
teriz
e
d
trav
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l
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id
:
Ex
p
e
rim
e
n
ters
wa
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,
"
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su
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l
Imp
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ir
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in
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[9
]
A
.
D.
He
y
e
s,
“
A
P
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lar
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id
u
lt
ra
so
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trav
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id
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,
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[1
0
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A
.
D.
H
e
y
e
s,
"
T
h
e
so
n
ic
p
a
th
f
in
d
e
r:
A
n
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w
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trav
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id
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"
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o
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Imp
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in
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,
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[1
1
]
W
.
A
ll
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n
,
A
.
G
ri
ff
it
h
,
a
n
d
M
.
Ya
b
lo
n
sk
i,
"
Re
a
li
stic o
rien
tatio
n
a
n
d
m
o
b
il
it
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e
ld
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li
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rso
n
,
"
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h
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L
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Ca
n
e
Ne
wsle
tt
e
r (
win
ter
)
,
1
9
7
6
.
[1
2
]
D.
G
o
ld
ie,
“
Us
e
o
f
th
e
C
-
5
L
a
s
e
r
Ca
n
e
b
y
sc
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g
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il
d
re
n
,
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J
o
u
rn
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l
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f
Vi
su
a
l
Imp
a
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n
t
a
n
d
Bl
in
d
n
e
ss
,
v
o
l.
71
,
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o
.
8
,
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.
3
4
6
–
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4
9
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7
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o
i
:
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4
5
4
8
2
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7
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7
1
0
0
8
0
2
.
[1
3
]
J.
A
.
Bra
b
y
n
,
"
Ne
w
De
v
e
lo
p
m
e
n
ts
in
M
o
b
il
it
y
a
n
d
Orie
n
tati
o
n
A
id
s
f
o
r
th
e
Bli
n
d
,
"
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Bi
o
me
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l
En
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in
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g
,
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l.
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E
-
2
9
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o
.
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,
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p
.
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E.
1
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2
.
3
2
4
9
4
5
.
[1
4
]
C.
M
.
T
sa
i
a
n
d
Z.
M
.
Ye
h
,
“
De
tec
ti
o
n
o
f
Bu
s
Ro
u
tes
Nu
m
b
e
r
in
Bu
s
P
a
n
e
l
v
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L
e
a
rn
in
g
A
p
p
ro
a
c
h
”,
In
telli
g
e
n
t
In
fo
rm
a
t
io
n
a
n
d
Da
t
a
b
a
se
S
y
ste
ms
.
ACIID,
L
e
c
tu
re
No
tes
i
n
Co
mp
u
ter
S
c
ien
c
e
,
2
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4
,
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o
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1
0
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1
0
0
7
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7
8
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3
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9
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2
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.
[1
5
]
D.
W
.
G
ra
n
th
a
m
,
“
S
p
a
ti
a
l
h
e
a
ri
n
g
,
a
n
d
re
late
d
p
h
e
n
o
m
e
n
a
,
”
E.
Ca
rte
re
tt
e
&
M
.
Fried
ma
n
(
S
e
rie
s
Ed
s.)
&
B.
M
o
o
re
(
Vo
l.
Ed
.
),
H
a
n
d
b
o
o
k
o
f
p
e
rc
e
p
ti
o
n
a
n
d
c
o
g
n
it
io
n
:
He
a
rin
g
(
2
n
d
e
d
.
)
,
Ne
w
Yo
rk
:
Ac
a
d
e
m
ic
P
re
ss
,
p
p
.
2
9
7
-
3
4
5
,
1
9
9
5
.
[1
6
]
C.
G
u
id
a
,
D.
Co
m
a
n
d
u
c
c
i,
a
n
d
C.
Co
lo
m
b
o
,
“
A
u
to
m
a
ti
c
Bu
s
L
in
e
Nu
m
b
e
r
L
o
c
a
li
z
a
ti
o
n
a
n
d
Re
c
o
g
n
it
io
n
o
n
M
o
b
i
le
P
h
o
n
e
s
—
A
Co
m
p
u
ter
Vi
sio
n
A
id
f
o
r
t
h
e
V
isu
a
ll
y
Im
p
a
ire
d
,
”
M
a
i
n
o
G.
,
F
o
re
sti
G.L
.
(
e
d
s)
Ima
g
e
A
n
a
lys
is
a
n
d
Pro
c
e
ss
in
g
-
L
e
c
tu
re
No
tes
i
n
Co
mp
u
ter
S
c
ien
c
e
,
2
0
1
1
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
3
-
6
4
2
-
2
4
0
8
8
-
1
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3
4
.
[1
7
]
H.
P
a
n
,
C.
Yi,
a
n
d
Y.
T
ian
,
"
A
p
rim
a
r
y
tra
v
e
li
n
g
a
s
sista
n
t
s
y
st
e
m
o
f
b
u
s
d
e
tec
ti
o
n
a
n
d
re
c
o
g
n
it
i
o
n
f
o
r
v
isu
a
ll
y
im
p
a
ired
p
e
o
p
le
,
"
2
0
1
3
IEE
E
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
u
l
ti
me
d
ia
a
n
d
Exp
o
W
o
rk
sh
o
p
s
(
I
CM
EW
),
2
0
1
3
,
p
p
.
1
–
6
,
d
o
i:
1
0
.
1
1
0
9
/IC
M
EW
.
2
0
1
3
.
6
6
1
8
3
4
6
.
[1
8
]
T
.
L
in
d
e
b
e
rg
,
"
S
c
a
le
S
e
le
c
ti
o
n
P
ro
p
e
rti
e
s
o
f
G
e
n
e
ra
li
z
e
d
S
c
a
le
-
S
p
a
c
e
In
tere
st
P
o
in
t
De
tec
to
rs
,
"
J
o
u
rn
a
l
o
f
M
a
t
h
.
Ima
g
.
a
n
d
Vi
s.
,
v
o
l.
4
6
,
no.
2
,
p
p.
177
-
2
1
0
,
2
0
1
3
,
d
o
i:
1
0
.
1
0
0
7
/s1
0
8
5
1
-
0
1
2
-
0
3
7
8
-
3
.
[1
9
]
T
.
L
in
d
e
b
e
rg
,
“
I
m
a
g
e
M
a
tch
in
g
Us
in
g
G
e
n
e
ra
li
z
e
d
S
c
a
le
-
S
p
a
c
e
I
n
tere
st
P
o
in
ts
,
”
Ku
ij
p
e
r
A.
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in
ter
n
a
ti
o
n
a
l
jo
u
rn
a
ls.
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