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.
24
,
No
.
2
,
A
p
r
il
20
26
,
p
p
.
599
~
607
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
24
i
2
.
27557
599
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
Low
-
c
o
st ESP32
-
ba
sed so
und da
ta
a
cquisitio
n sy
ste
m
w
ith
M
ATL
AB
integr
a
tion for real
-
ti
me no
ise
m
o
nitorin
g
Rey
m
a
r
k
-
J
o
hn
A.
M
a
ca
pa
n
a
s
1
,
Adria
n P
.
G
a
lid
o
2
,
App
l
e
Ro
s
e
B
.
Alce
3
1
D
e
p
a
r
t
me
n
t
o
f
I
n
f
o
r
mat
i
o
n
T
e
c
h
n
o
l
o
g
y
,
C
o
l
l
e
g
e
o
f
I
n
f
o
r
mat
i
o
n
T
e
c
h
n
o
l
o
g
y
a
n
d
C
o
mp
u
t
i
n
g
,
U
n
i
v
e
r
si
t
y
o
f
S
c
i
e
n
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
o
f
S
o
u
t
h
e
r
n
P
h
i
l
i
p
p
i
n
e
s
-
V
i
l
l
a
n
u
e
v
a
C
a
m
p
u
s
,
V
i
l
l
a
n
u
e
v
a
M
i
s
a
mi
s
O
r
i
e
n
t
a
l
,
P
h
i
l
i
p
p
i
n
e
s
2
D
e
p
a
r
t
me
n
t
o
f
I
n
f
o
r
mat
i
o
n
S
y
st
e
ms,
C
o
l
l
e
g
e
o
f
C
o
mp
u
t
e
r
S
t
u
d
i
e
s (CC
S
)
,
M
i
n
d
a
n
a
o
S
t
a
t
e
U
n
i
v
e
r
si
t
y
I
l
i
g
a
n
I
n
st
i
t
u
t
e
o
f
T
e
c
h
n
o
l
o
g
y
(
M
S
U
-
I
I
T)
,
I
l
i
g
a
n
C
i
t
y
,
P
h
i
l
i
p
p
i
n
e
s
3
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
A
p
p
l
i
c
a
t
i
o
n
s,
C
o
l
l
e
g
e
o
f
C
o
mp
u
t
e
r
S
t
u
d
i
e
s (C
C
S
)
,
M
i
n
d
a
n
a
o
S
t
a
t
e
U
n
i
v
e
r
si
t
y
I
l
i
g
a
n
I
n
st
i
t
u
t
e
o
f
T
e
c
h
n
o
l
o
g
y
(
M
S
U
-
I
I
T)
,
I
l
i
g
a
n
C
i
t
y
,
P
h
i
l
i
p
p
i
n
e
s
Art
icle
I
n
fo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Sep
17
,
2
0
2
5
R
ev
i
s
ed
Oct
21
,
2
0
2
5
A
cc
ep
ted
Dec
8
,
2
0
2
5
T
h
is
stu
d
y
p
re
se
n
ts
t
h
e
d
e
sig
n
a
n
d
im
p
le
m
e
n
tatio
n
o
f
a
lo
w
-
c
o
st
ES
P
3
2
-
b
a
se
d
so
u
n
d
d
a
ta
a
c
q
u
isit
io
n
sy
ste
m
(S
DA
S
)
f
o
r
re
a
l
-
ti
m
e
n
o
ise
m
o
n
it
o
rin
g
.
T
h
e
s
y
ste
m
in
teg
ra
tes
a
m
icro
-
e
lec
tro
-
m
e
c
h
a
n
ica
l
s
y
ste
m
s
(
M
EM
S
)
m
icro
p
h
o
n
e
f
o
r
a
c
c
u
ra
te
a
c
o
u
stic
d
a
ta
c
a
p
tu
r
e
,
a
n
ES
P
-
W
ROO
M
-
3
2
m
icro
c
o
n
tro
ll
e
r
f
o
r
sig
n
a
l
p
ro
c
e
ss
in
g
a
n
d
w
irele
ss
d
a
t
a
tran
sm
issio
n
,
a
n
d
M
A
T
LA
B
f
o
r
re
a
l
-
ti
m
e
v
isu
a
li
z
a
ti
o
n
a
n
d
a
n
a
ly
sis.
De
sig
n
e
d
a
n
d
sim
u
late
d
i
n
KiCA
D
8
.
0
,
t
h
e
S
DA
S
in
c
lu
d
e
s
a
m
icro
S
D
m
o
d
u
le
f
o
r
l
o
c
a
l
d
a
ta
b
a
c
k
u
p
a
n
d
o
f
f
li
n
e
a
n
a
ly
sis.
T
h
e
s
y
ste
m
w
a
s
tes
ted
in
f
o
u
r
in
d
o
o
r
l
o
c
a
ti
o
n
s
w
it
h
in
M
in
d
a
n
a
o
S
tate
Un
iv
e
rsit
y
–
Ili
g
a
n
In
stit
u
te
o
f
T
e
c
h
n
o
l
o
g
y
,
re
c
o
rd
in
g
m
e
a
n
n
o
ise
lev
e
ls
ra
n
g
in
g
f
ro
m
1
4
.
2
d
B
in
la
b
o
ra
to
ry
e
n
v
iro
n
m
e
n
ts
to
3
2
.
1
d
B
in
c
las
s
ro
o
m
s,
w
it
h
c
o
rre
sp
o
n
d
in
g
sta
n
d
a
r
d
d
e
v
iatio
n
s
o
f
1
.
2
–
7
.
0
d
B.
Ex
p
e
rt
e
v
a
lu
a
ti
o
n
f
ro
m
e
ig
h
t
a
ss
e
ss
o
rs
c
o
n
f
ir
m
e
d
th
e
s
y
ste
m
’
s
u
sa
b
il
it
y
,
d
a
ta
re
li
a
b
il
it
y
,
a
n
d
ro
b
u
stn
e
ss
.
T
h
e
sy
ste
m
d
e
m
o
n
str
a
tes
e
ff
e
c
ti
v
e
m
o
n
it
o
ri
n
g
f
o
r
b
o
th
q
u
iet
a
n
d
d
y
n
a
m
ic
se
tt
in
g
s.
L
i
m
it
a
ti
o
n
s
in
c
l
u
d
e
si
n
g
le
-
n
o
d
e
c
o
n
f
ig
u
ra
ti
o
n
,
in
d
o
o
r
-
o
n
ly
tes
ti
n
g
,
a
n
d
M
A
TL
A
B
-
b
a
se
d
US
B
d
a
ta
tran
sf
e
r.
D
e
sp
it
e
th
e
se
,
th
e
p
ro
p
o
se
d
S
DA
S
p
ro
v
id
e
s
a
sc
a
l
a
b
le
a
n
d
re
p
ro
d
u
c
ib
le
m
o
d
e
l
f
o
r
s
m
a
rt
c
a
m
p
u
s
a
n
d
u
r
b
a
n
e
n
v
iro
n
m
e
n
tal
m
o
n
it
o
ri
n
g
,
su
p
p
o
rti
n
g
su
sta
in
a
b
le
d
e
v
e
lo
p
m
e
n
t
g
o
a
ls
(S
DG
)
3
,
9
,
a
n
d
1
1
.
K
ey
w
o
r
d
s
:
E
SP
3
2
MA
T
L
A
B
M
icr
o
-
elec
tr
o
-
m
ec
h
a
n
ical
s
y
s
te
m
s
m
icr
o
p
h
o
n
e
No
is
e
p
o
llu
tio
n
R
ea
l
-
ti
m
e
m
o
n
ito
r
in
g
So
u
n
d
d
ata
ac
q
u
is
itio
n
s
y
s
te
m
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
:
R
e
y
m
ar
k
-
J
o
h
n
A
.
Ma
ca
p
an
as
Dep
ar
t
m
en
t o
f
I
n
f
o
r
m
atio
n
T
e
ch
n
o
lo
g
y
,
C
o
lle
g
e
o
f
I
n
f
o
r
m
at
io
n
T
ec
h
n
o
lo
g
y
a
n
d
C
o
m
p
u
ti
n
g
Un
i
v
er
s
it
y
o
f
Scie
n
ce
a
n
d
T
ec
h
n
o
lo
g
y
o
f
So
u
t
h
er
n
P
h
il
ip
p
in
es
-
V
illan
u
e
v
a
C
a
m
p
u
s
9
0
0
2
Villan
u
ev
a,
Mi
s
a
m
i
s
Or
i
en
tal,
P
h
ilip
p
in
e
s
E
m
ail:
r
e
y
m
ar
k
j
o
h
n
.
m
ac
ap
a
n
a
s
@
u
s
tp
.
ed
u
.
p
h
1.
I
NT
RO
D
UCT
I
O
N
No
is
e
p
o
llu
tio
n
is
a
g
r
o
w
in
g
g
lo
b
al
co
n
ce
r
n
,
esp
ec
iall
y
i
n
u
r
b
an
en
v
ir
o
n
m
e
n
ts
,
w
h
er
e
in
d
u
s
tr
ia
l
ac
tiv
itie
s
a
n
d
tr
an
s
p
o
r
tatio
n
s
y
s
te
m
s
s
i
g
n
if
ican
t
l
y
co
n
tr
ib
u
t
e
to
ac
o
u
s
tic
d
is
tu
r
b
an
ce
s
.
P
r
o
lo
n
g
ed
ex
p
o
s
u
r
e
to
h
ig
h
n
o
is
e
lev
e
ls
h
as
b
ee
n
l
in
k
ed
to
ad
v
er
s
e
h
ea
lth
ef
f
ec
t
s
,
s
u
ch
as
ca
r
d
io
v
asc
u
lar
d
is
ea
s
e
s
,
s
tr
ess
,
a
n
d
i
m
p
air
ed
co
g
n
iti
v
e
p
er
f
o
r
m
a
n
ce
,
as
n
o
ted
b
y
th
e
W
o
r
ld
Hea
lth
Or
g
an
izatio
n
(
W
HO)
.
I
n
th
e
c
o
n
tex
t
o
f
s
m
ar
t
cities
an
d
s
u
s
tai
n
ab
le
d
ev
elo
p
m
e
n
t,
r
ea
l
-
ti
m
e
e
n
v
ir
o
n
m
en
ta
l
m
o
n
ito
r
in
g
s
y
s
te
m
s
ar
e
cr
u
cial
i
n
s
u
p
p
o
r
tin
g
ev
id
en
ce
-
b
ased
p
o
licies th
at
ad
d
r
ess
th
e
s
e
ch
a
llen
g
es.
Nu
m
er
o
u
s
r
esear
c
h
i
n
itiati
v
es
h
av
e
e
x
p
lo
r
ed
th
e
u
s
e
o
f
i
n
ter
n
et
o
f
th
in
g
(
I
o
T
)
-
b
ased
n
o
is
e
m
o
n
ito
r
i
n
g
s
y
s
te
m
s
.
P
icau
t
et
a
l
.
[
1
]
r
ev
iew
ed
lo
w
-
co
s
t
u
r
b
an
n
o
is
e
m
o
n
ito
r
in
g
n
et
w
o
r
k
s
,
w
h
i
le
M
y
d
la
r
z
et
a
l
.
[
2
]
p
r
o
p
o
s
ed
s
m
ar
t
w
ir
ele
s
s
ac
o
u
s
tic
s
e
n
s
o
r
n
et
w
o
r
k
ar
ch
itect
u
r
es.
Vid
a
ñ
a
-
Vila
et
a
l
.
[
3
]
d
em
o
n
s
tr
at
ed
lo
w
-
co
s
t
u
r
b
an
ac
o
u
s
tic
m
o
n
ito
r
in
g
d
ev
ice
s
,
an
d
Fate
m
a
et
a
l
.
[
4
]
p
r
esen
te
d
a
r
ea
l
-
ti
m
e
I
o
T
-
b
ased
n
o
is
e
m
o
n
ito
r
i
n
g
s
y
s
te
m
.
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.
24
,
No
.
2
,
A
p
r
il
20
26
:
5
9
9
-
607
600
Ho
w
e
v
er
,
th
ese
s
t
u
d
ies
o
f
ten
r
el
y
o
n
h
ig
h
-
co
s
t
d
ev
ices
o
r
lack
lo
ca
lized
,
m
o
d
u
lar
i
m
p
le
m
en
tatio
n
s
tr
ate
g
ies
th
at
ar
e
ea
s
y
to
r
ep
licate
in
d
e
v
elo
p
in
g
r
eg
io
n
s
.
P
r
ev
io
u
s
s
t
u
d
ies
h
a
v
e
ac
h
ie
v
e
d
s
ig
n
i
f
ica
n
t
p
r
o
g
r
ess
in
I
o
T
-
b
ased
ac
o
u
s
tic
m
o
n
ito
r
in
g
;
h
o
wev
er
,
m
an
y
s
o
lu
tio
n
s
r
e
m
ai
n
co
s
tl
y
,
n
on
-
m
o
d
u
lar
,
o
r
co
m
p
lex
to
r
ep
lic
ate,
esp
ec
iall
y
in
d
ev
elo
p
in
g
r
eg
io
n
s
.
S
y
s
te
m
s
t
h
a
t
r
el
y
o
n
p
r
o
p
r
ietar
y
p
lat
f
o
r
m
s
o
r
h
ig
h
-
e
n
d
s
e
n
s
o
r
s
r
es
tr
ict
s
ca
lab
ilit
y
an
d
ac
ce
s
s
ib
ilit
y
.
T
o
a
d
d
r
ess
th
ese
ch
alle
n
g
e
s
,
t
h
e
p
r
o
p
o
s
ed
s
o
u
n
d
d
ata
ac
q
u
is
i
tio
n
s
y
s
te
m
(
SD
A
S)
i
n
t
r
o
d
u
ce
s
a
lo
w
-
co
s
t,
m
o
d
u
lar
,
a
n
d
r
ep
r
o
d
u
cib
le
ar
ch
itectu
r
e
th
at
in
te
g
r
ates
a
f
f
o
r
d
ab
le
h
ar
d
w
ar
e
co
m
p
o
n
en
t
s
,
s
u
ch
a
s
t
h
e
E
SP
3
2
m
icr
o
co
n
tr
o
lle
r
an
d
m
icr
o
-
elec
tr
o
-
m
ec
h
an
ical
s
y
s
te
m
s
(
ME
MS)
m
icr
o
p
h
o
n
e
,
w
ith
M
A
T
L
A
B
-
b
a
s
ed
v
is
u
ali
za
tio
n
f
o
r
ef
f
icie
n
t
d
ata
an
al
y
s
i
s
.
T
h
is
ap
p
r
o
ac
h
ai
m
s
to
b
r
id
g
e
t
h
e
g
ap
b
et
w
e
en
co
m
m
er
cial
n
o
i
s
e
m
eter
s
an
d
r
esear
ch
-
le
v
el
m
o
n
ito
r
i
n
g
s
y
s
te
m
s
,
en
ab
li
n
g
u
n
i
v
er
s
i
ties
a
n
d
lo
ca
l
in
s
tit
u
tio
n
s
to
ad
o
p
t
s
ca
lab
le
ac
o
u
s
tic
s
en
s
i
n
g
s
o
lu
t
io
n
s
f
o
r
s
m
ar
t e
n
v
ir
o
n
m
e
n
t
s
.
T
h
is
r
esear
ch
ad
d
r
ess
es
th
o
s
e
li
m
itatio
n
s
b
y
d
esig
n
in
g
a
SDAS
th
at
is
b
o
th
lo
w
-
co
s
t
an
d
m
o
d
u
lar
,
in
te
g
r
atin
g
an
E
SP
3
2
m
icr
o
co
n
tr
o
ller
,
ME
MS
m
icr
o
p
h
o
n
e
,
an
d
MA
T
L
A
B
-
b
ased
v
i
s
u
al
izatio
n
to
f
o
r
m
an
af
f
o
r
d
ab
le
y
e
t
r
o
b
u
s
t
m
o
n
ito
r
i
n
g
s
o
l
u
tio
n
.
Un
l
ik
e
p
r
ev
io
u
s
w
o
r
k
s
,
th
is
s
t
u
d
y
e
m
p
h
asize
s
r
ep
lic
ab
ilit
y
,
o
f
f
li
n
e
d
ata
b
ac
k
u
p
,
an
d
h
ar
d
w
ar
e
m
o
d
u
lar
it
y
u
s
i
n
g
KiC
AD
8
.
0
.
T
h
e
m
ai
n
co
n
tr
ib
u
tio
n
s
ar
e:
(
i)
t
h
e
d
ev
elo
p
m
e
n
t
o
f
a
s
ca
lab
le
SD
A
S
f
o
r
r
ea
l
-
ti
m
e
ac
o
u
s
tic
m
o
n
ito
r
in
g
,
(
ii)
i
n
teg
r
atio
n
o
f
E
SP
3
2
,
ME
MS
m
icr
o
p
h
o
n
e,
an
d
MA
T
L
AB
,
an
d
(
iii)
v
alid
atio
n
o
f
th
e
s
y
s
te
m
t
h
r
o
u
g
h
ex
p
er
t
ev
alu
a
tio
n
a
n
d
q
u
an
ti
tati
v
e
an
al
y
s
i
s
.
2.
M
E
T
H
O
D
T
h
e
m
et
h
o
d
o
lo
g
y
(
Fig
u
r
e
1
)
f
o
r
th
e
SDA
S
f
o
llo
w
s
a
s
ix
-
p
h
ase
s
tr
u
ct
u
r
ed
d
esig
n
p
r
o
ce
s
s
to
en
s
u
r
e
r
ep
r
o
d
u
cib
ilit
y
,
f
u
n
ctio
n
alit
y
,
an
d
r
eliab
ilit
y
.
P
h
a
s
e
0
in
v
o
lv
es
id
en
ti
f
y
in
g
t
h
e
n
o
is
e
p
o
llu
ti
o
n
p
r
o
b
lem
;
P
h
a
s
e
1
d
ef
in
es
s
y
s
te
m
o
b
j
ec
tiv
es.
P
h
ase
2
in
v
o
lv
e
s
r
eq
u
ir
e
m
e
n
t
an
al
y
s
i
s
an
d
co
m
p
o
n
e
n
t
s
elec
t
io
n
;
P
h
ase
3
ad
d
r
ess
es
s
ch
e
m
atic
d
esi
g
n
u
s
i
n
g
Ki
C
A
D
8
.
0
.
P
h
ase
4
in
te
g
r
ates
d
ata
ac
q
u
is
itio
n
w
i
th
M
A
T
L
A
B
f
o
r
r
ea
l
-
t
i
m
e
v
is
u
aliza
t
io
n
.
P
h
ases
5
an
d
6
f
o
cu
s
o
n
s
y
s
te
m
te
s
ti
n
g
a
n
d
ex
p
er
t e
v
alu
atio
n
u
n
d
er
ca
m
p
u
s
en
v
ir
o
n
m
e
n
t
s
.
2
.
1
.
Sy
s
t
em
t
o
po
lo
g
y
T
h
e
SDA
S o
p
er
ates in
f
o
u
r
s
ta
g
es: (
i)
d
ata
ac
q
u
is
itio
n
: a
ME
MS
m
icr
o
p
h
o
n
e
ca
p
t
u
r
es e
n
v
i
r
o
n
m
e
n
ta
l
n
o
is
e
i
n
r
ea
l
ti
m
e
a
n
d
f
o
r
w
a
r
d
s
th
e
s
i
g
n
a
l
f
o
r
p
r
o
ce
s
s
in
g
[
5
]
;
(
ii)
d
ata
p
r
o
ce
s
s
in
g
:
t
h
e
E
SP
-
W
R
OOM
-
32
co
n
v
er
ts
t
h
e
a
n
alo
g
s
ig
n
al
to
d
ig
ital
d
ata
f
o
r
an
a
l
y
s
is
o
r
s
to
r
ag
e
[
6
]
;
(
iii)
lo
ca
l
d
ata
s
to
r
ag
e:
p
r
o
ce
s
s
ed
d
ata
is
w
r
itte
n
to
a
m
icr
o
SD
ca
r
d
to
en
s
u
r
e
av
a
ilab
ilit
y
d
u
r
i
n
g
n
et
wo
r
k
in
ter
r
u
p
tio
n
s
a
n
d
e
n
ab
le
o
f
f
lin
e
r
etr
iev
al
[
7
]
;
an
d
(
iv
)
M
A
T
L
A
B
in
te
g
r
atio
n
:
v
ia
s
er
ial
co
n
n
ec
tio
n
,
d
ata
is
s
tr
ea
m
ed
to
M
A
T
L
A
B
f
o
r
r
ea
l
-
ti
m
e
p
lo
ttin
g
a
n
d
tr
en
d
an
al
y
s
i
s
[
8
]
.
T
h
is
to
p
o
l
o
g
y
allo
w
s
in
d
ep
en
d
e
n
t
o
p
er
atio
n
w
it
h
o
f
f
li
n
e
s
to
r
ag
e
a
n
d
MA
T
L
A
B
-
b
ased
an
al
y
s
is
f
o
r
co
m
p
r
eh
e
n
s
i
v
e
e
v
alu
a
t
io
n
[
9
]
.
Fi
g
u
r
e
2
ill
u
s
tr
ates
t
h
e
e
n
d
-
to
-
en
d
d
ata
f
lo
w
f
r
o
m
ac
q
u
i
s
itio
n
to
v
is
u
aliza
t
io
n
.
Fig
u
r
e
1
.
SDAS
m
e
th
o
d
o
lo
g
y
f
lo
w
ch
ar
t
Fig
u
r
e
2
.
S
y
s
te
m
to
p
o
lo
g
y
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
Lo
w
-
c
o
s
t E
S
P
3
2
-
b
a
s
ed
s
o
u
n
d
d
a
ta
a
c
q
u
is
itio
n
s
ystem
w
ith
MATLAB
…
(
R
ey
ma
r
k
-
Jo
h
n
A
.
Ma
ca
p
a
n
a
s
)
601
2.
2
.
H
a
rdwa
re
des
ig
n
T
h
is
s
ec
tio
n
o
u
tli
n
es
t
h
e
m
et
h
o
d
s
e
m
p
lo
y
ed
i
n
t
h
e
d
esig
n
an
d
d
ev
elo
p
m
e
n
t
o
f
t
h
e
SD
AS,
f
r
o
m
co
n
ce
p
tu
aliza
tio
n
to
s
y
s
te
m
i
n
teg
r
at
io
n
.
Fi
g
u
r
e
3
(
a)
illu
s
tr
ates
th
e
p
o
w
er
a
n
d
p
r
o
g
r
am
m
in
g
i
n
ter
f
ac
e
o
f
th
e
SD
A
S,
w
h
i
le
Fig
u
r
e
3
(
b
)
p
r
es
en
ts
t
h
e
s
o
u
n
d
m
o
d
u
le
s
ch
e
m
a
tic.
T
h
e
m
icr
o
co
n
tr
o
ller
co
n
f
i
g
u
r
atio
n
is
s
h
o
w
n
i
n
Fig
u
r
e
3
(
c)
,
th
e
m
icr
o
SD
ca
r
d
in
ter
f
ac
e
is
d
etailed
i
n
Fi
g
u
r
e
3
(
d
)
,
an
d
th
e
r
elay
co
n
tr
o
l
cir
cu
it
i
s
d
ep
icted
in
Fig
u
r
e
3
(
e)
.
T
o
g
eth
er
,
th
ese
s
u
b
-
f
i
g
u
r
e
s
p
r
esen
t
th
e
co
m
p
le
te
s
ch
e
m
atic
d
esi
g
n
o
f
t
h
e
p
r
o
p
o
s
ed
SDA
S.
E
ac
h
lab
eled
s
ec
tio
n
is
ex
p
lai
n
ed
as
:
2.
2.
1
.
H
a
rd
w
a
r
e
c
o
m
po
ne
nt
j
us
t
if
ica
t
io
n
T
h
e
s
y
s
te
m
d
esi
g
n
i
n
co
r
p
o
r
ates c
ar
ef
u
ll
y
s
elec
ted
h
ar
d
w
ar
e
co
m
p
o
n
e
n
t
s
:
−
ME
MS
m
icr
o
p
h
o
n
e
:
h
i
g
h
s
en
s
itiv
it
y
a
n
d
lo
w
p
o
w
er
,
ca
p
tu
r
e
s
en
v
ir
o
n
m
en
ta
l n
o
is
e
i
n
d
ec
ib
els [
1
0
]
.
−
E
SP
-
W
R
OOM
-
32
:
c
o
r
e
m
icr
o
co
n
tr
o
ller
f
o
r
ac
q
u
is
itio
n
,
an
a
l
o
g
-
to
-
d
ig
ita
l c
o
n
v
er
s
io
n
,
an
d
w
ir
ele
s
s
/
s
er
ial
d
ata
tr
an
s
f
er
to
M
A
T
L
A
B
[
1
1
]
.
−
Mic
r
o
SD
m
o
d
u
le
:
p
r
o
v
id
es
n
o
n
-
v
o
latile
lo
ca
l s
to
r
ag
e
f
o
r
b
ac
k
u
p
a
n
d
o
f
f
li
n
e
a
n
al
y
s
is
[
1
2
]
.
−
Sch
r
ac
k
R
T
1
r
elay
:
m
an
a
g
es p
o
w
er
d
is
tr
ib
u
tio
n
,
ex
te
n
d
in
g
b
atter
y
li
f
e
an
d
p
r
ev
en
t
in
g
s
u
r
g
es
[
1
3
]
.
2
.
2
.
2.
P
rint
ed
circ
uit
bo
a
rd
(
P
CB
)
a
nd
s
che
m
a
t
ic
de
s
ig
n
T
h
e
co
m
p
lete
h
ar
d
w
ar
e
d
esig
n
w
as i
m
p
le
m
en
ted
i
n
KiC
AD
8
.
0
.
T
h
e
s
ch
e
m
atic
co
n
s
is
ts
o
f
:
−
P
o
w
er
an
d
p
r
o
g
r
a
m
m
i
n
g
in
ter
f
ac
e
:
h
a
n
d
les
v
o
ltag
e
r
e
g
u
la
tio
n
an
d
f
ir
m
w
ar
e
u
p
lo
ad
[
1
4
]
.
−
Sen
s
o
r
i
n
ter
f
ac
e:
c
on
n
ec
t
s
th
e
ME
MS
m
icr
o
p
h
o
n
e
f
o
r
an
alo
g
s
i
g
n
a
l in
p
u
t [
1
5
]
.
−
Mic
r
o
co
n
tr
o
ller
i
n
ter
f
ac
e:
c
e
n
t
r
al
p
r
o
ce
s
s
in
g
u
n
i
t r
esp
o
n
s
ib
le
f
o
r
all
lo
g
ic
o
p
er
atio
n
s
.
−
Mic
r
o
SD
s
to
r
ag
e
in
ter
f
ac
e
:
m
an
ag
e
s
d
ata
w
r
it
in
g
an
d
r
etr
ie
v
al.
−
R
ela
y
co
n
tr
o
l c
ir
cu
it
:
a
u
to
m
at
es p
o
w
er
s
w
itc
h
i
n
g
.
T
h
e
P
C
B
lay
o
u
t
p
r
io
r
itizes
co
m
p
ac
tn
e
s
s
a
n
d
s
ig
n
al
i
n
te
g
r
it
y
,
w
ith
ca
r
e
f
u
l
r
o
u
ti
n
g
to
m
in
i
m
ize
i
n
ter
f
er
e
n
ce
.
T
h
e
3
D
m
o
d
el
s
h
o
w
s
co
m
p
o
n
en
t p
lace
m
e
n
t,
s
u
p
p
o
r
tin
g
ea
s
y
m
a
n
u
f
ac
tu
r
i
n
g
a
n
d
ass
e
m
b
l
y
[
1
6
]
.
T
h
e
P
C
B
d
esig
n
Fig
u
r
e
4
i
n
teg
r
ates
t
h
e
E
SP
-
W
R
OOM
-
3
2
m
icr
o
co
n
tr
o
ller
,
ME
MS
m
i
cr
o
p
h
o
n
e,
p
o
w
er
r
ela
y
,
an
d
m
icr
o
SD
s
lo
t
in
a
co
m
p
ac
t
la
y
o
u
t.
I
t
in
cl
u
d
es
co
n
n
ec
to
r
s
f
o
r
ex
ter
n
al
d
e
v
ices,
li
g
h
t
-
e
m
i
tti
n
g
d
io
d
e
(
L
E
D
)
in
d
icato
r
s
f
o
r
s
y
s
te
m
s
ta
tu
s
,
an
d
r
eg
u
lated
p
o
w
e
r
m
a
n
a
g
e
m
en
t
to
e
n
s
u
r
e
s
tab
le
o
p
er
atio
n
.
C
ar
ef
u
l
tr
ac
e
r
o
u
tin
g
m
i
n
i
m
izes
i
n
ter
f
e
r
en
ce
an
d
s
ig
n
al
lo
s
s
,
allo
w
in
g
th
e
SD
A
S
to
f
u
n
ctio
n
e
f
f
icien
tl
y
an
d
r
eliab
l
y
f
o
r
u
r
b
an
n
o
i
s
e
m
o
n
ito
r
in
g
ap
p
licatio
n
s
.
T
h
e
3
D
m
o
d
el
Fig
u
r
e
5
s
h
o
w
s
th
e
p
lace
m
e
n
t
o
f
th
e
E
SP
-
W
R
OOM
-
3
2
,
ME
MS
m
icr
o
p
h
o
n
e,
Sch
r
ac
k
R
T
1
r
elay
,
a
n
d
m
icr
o
SD
s
lo
t
o
n
th
e
P
C
B
.
I
t
al
s
o
in
cl
u
d
es
i
n
p
u
t/o
u
tp
u
t
(
I
/O
)
co
n
n
ec
to
r
s
,
L
E
D
i
n
d
icato
r
s
,
an
d
a
r
eset
b
u
tto
n
f
o
r
s
y
s
te
m
f
ee
d
b
ac
k
an
d
co
n
tr
o
l.
T
h
e
d
esig
n
en
s
u
r
es
co
m
p
ac
t
ass
e
m
b
l
y
,
d
u
r
ab
ilit
y
,
an
d
r
eliab
le
o
p
er
atio
n
f
o
r
n
o
is
e
d
ata
ac
q
u
is
itio
n
in
u
r
b
an
e
n
v
ir
o
n
m
e
n
t
s
.
2.
2
.
3
.
M
AT
L
AB
da
t
a
f
lo
w
MA
T
L
A
B
w
a
s
u
s
ed
f
o
r
s
er
ia
l
co
m
m
u
n
icatio
n
,
v
i
s
u
aliza
tio
n
,
an
d
r
ea
l
-
ti
m
e
a
n
al
y
s
i
s
(
Fi
g
u
r
e
6
)
.
T
h
e
SD
A
S
tr
a
n
s
m
it
s
d
ata
v
ia
u
n
i
v
er
s
al
s
er
ial
b
us
(
USB
)
s
er
ia
l,
w
h
ic
h
M
A
T
L
A
B
i
n
ter
p
r
ets
th
r
o
u
g
h
a
d
ef
in
ed
c
o
m
m
u
n
icatio
n
(
C
O
M
)
p
o
r
t
[
1
7
]
.
On
ce
a
s
tab
le
co
n
n
ec
tio
n
is
estab
lis
h
ed
,
in
co
m
in
g
v
al
u
es
ar
e
p
lo
tted
u
s
in
g
MA
T
L
A
B
’
s
b
u
ilt
-
i
n
to
o
ls
[
1
8
]
.
T
h
e
p
r
o
ce
s
s
r
u
n
s
co
n
ti
n
u
o
u
s
l
y
u
n
til
th
e
u
s
er
ter
m
i
n
ates
th
e
s
es
s
io
n
,
e
n
s
u
r
in
g
r
ea
l
-
ti
m
e
m
o
n
ito
r
in
g
an
d
v
is
u
aliza
tio
n
.
2
.
2
.
4
.
T
esting
a
nd
ev
a
lua
t
io
n
T
h
e
SDA
S
w
as
d
ep
lo
y
ed
in
f
o
u
r
lo
ca
tio
n
s
w
it
h
i
n
th
e
Mi
n
d
an
ao
State
U
n
iv
er
s
it
y
I
li
g
a
n
I
n
s
ti
tu
te
o
f
T
ec
h
n
o
lo
g
y
(
MSU
-
I
I
T
)
c
o
lleg
e
o
f
co
m
p
u
ter
s
t
u
d
ies
(
I
o
T
lab
,
g
r
ad
u
ate
lab
,
em
b
ed
d
ed
s
y
s
te
m
s
lab
,
an
d
a
class
r
o
o
m
)
to
ass
e
s
s
p
er
f
o
r
m
an
ce
u
n
d
er
v
ar
y
in
g
co
n
d
itio
n
s
[
1
9
]
.
No
is
e
d
ata
w
as
co
lle
cted
o
v
er
o
n
e
-
h
o
u
r
in
ter
v
a
ls
,
co
n
s
is
te
n
t
w
it
h
r
ec
o
m
m
en
d
ed
m
o
n
ito
r
in
g
p
r
ac
tice
s
to
ca
p
tu
r
e
te
m
p
o
r
al
v
ar
iab
ili
t
y
[
2
0
]
.
MA
T
L
A
B
p
lo
ts
r
ec
o
r
d
e
d
m
ea
n
,
p
ea
k
,
an
d
s
tan
d
ar
d
d
ev
iatio
n
v
al
u
e
s
.
Usab
ilit
y
an
d
ac
c
u
r
ac
y
w
er
e
v
alid
ated
b
y
ei
g
h
t
s
u
b
j
ec
t
m
a
tter
ex
p
er
ts
u
s
i
n
g
a
s
ta
n
d
ar
d
r
u
b
r
ic.
Ke
y
cr
iter
ia
in
clu
d
ed
: (
i)
ea
s
e
o
f
s
y
s
te
m
d
ep
lo
y
m
en
t,
(
ii)
ac
cu
r
ac
y
o
f
n
o
is
e
d
ata
ca
p
tu
r
ed
,
(
iii)
c
lar
it
y
o
f
M
A
T
L
A
B
v
is
u
ali
za
t
io
n
s
,
an
d
(
iv
)
p
o
w
er
ef
f
icien
c
y
an
d
r
o
b
u
s
tn
e
s
s
o
f
th
e
h
ar
d
w
ar
e.
Feed
b
ac
k
co
n
f
ir
m
ed
th
e
SDA
S to
b
e
r
eliab
le
f
o
r
m
o
n
ito
r
in
g
b
o
th
lo
w
-
ac
ti
v
it
y
an
d
d
y
n
a
m
ic
en
v
ir
o
n
m
e
n
t
s
[
2
1
].
2
.
2
.
5
.
Ca
lib
ra
t
io
n a
nd
v
a
lid
a
t
io
n
T
o
en
s
u
r
e
th
e
r
eliab
ilit
y
o
f
r
ec
o
r
d
ed
n
o
is
e
d
ata,
th
e
SDAS
o
u
tp
u
t
w
as
ca
lib
r
ated
ag
ain
s
t
a
r
ef
er
en
ce
s
o
u
n
d
lev
el
m
eter
(
SL
M)
f
o
llo
w
i
n
g
I
SO
1
9
9
6
-
2
:2
0
1
7
ac
o
u
s
tic
s
ta
n
d
ar
d
s
.
C
alib
r
atio
n
w
as
co
n
d
u
cted
b
y
g
en
er
ati
n
g
co
n
tr
o
lled
s
o
u
n
d
le
v
els
b
et
w
ee
n
2
0
d
B
an
d
8
0
d
B
u
s
i
n
g
a
s
ta
n
d
ar
d
au
d
io
s
o
u
r
ce
.
T
h
e
SDAS
r
ea
d
in
g
s
w
er
e
co
m
p
ar
ed
to
th
e
SLM
m
ea
s
u
r
e
m
en
t
s
at
5
d
B
in
ter
v
als.
A
li
n
ea
r
r
eg
r
ess
io
n
m
o
d
el
w
a
s
ap
p
lied
,
y
ield
i
n
g
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.
24
,
No
.
2
,
A
p
r
il
20
26
:
5
9
9
-
607
602
an
R
²
v
a
lu
e
o
f
0
.
9
8
4
,
co
n
f
ir
m
i
n
g
s
tr
o
n
g
co
r
r
elatio
n
a
n
d
m
i
n
i
m
al
d
ev
iatio
n
(
<2
.
3
d
B
m
ea
n
er
r
o
r
)
.
T
h
i
s
ca
lib
r
atio
n
en
s
u
r
ed
ac
cu
r
ate
n
o
is
e
m
ea
s
u
r
e
m
en
t p
r
io
r
to
d
ep
lo
y
m
e
n
t i
n
ca
m
p
u
s
e
n
v
ir
o
n
m
e
n
ts
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
3
.
Sch
e
m
atic
d
esi
g
n
o
f
th
e
SD
AS: (
a)
p
o
w
er
an
d
p
r
o
g
r
a
m
m
in
g
i
n
ter
f
ac
e;
(
b
)
s
o
u
n
d
m
o
d
u
le;
(
c)
m
icr
o
co
n
tr
o
ller
co
n
f
ig
u
r
ati
o
n
; (
d
)
m
icr
o
SD c
ar
d
in
ter
f
ac
e
;
an
d
(
e)
r
elay
co
n
tr
o
l c
ir
cu
i
t
Fig
u
r
e
4
.
P
C
B
d
esig
n
o
f
SD
A
S
Fig
u
r
e
5
.
3
D
m
o
d
el
o
f
SD
AS
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
Lo
w
-
c
o
s
t E
S
P
3
2
-
b
a
s
ed
s
o
u
n
d
d
a
ta
a
c
q
u
is
itio
n
s
ystem
w
ith
MATLAB
…
(
R
ey
ma
r
k
-
Jo
h
n
A
.
Ma
ca
p
a
n
a
s
)
603
Fig
u
r
e
6
.
MA
T
L
A
B
d
ata
f
lo
w
3
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
SDAS
w
as
te
s
ted
ac
r
o
s
s
f
o
u
r
in
d
o
o
r
lo
ca
tio
n
s
:
t
h
e
I
o
T
l
ab
,
th
e
g
r
ad
u
ate
lab
o
r
ato
r
y
,
th
e
e
m
b
ed
d
ed
lab
o
r
ato
r
y
,
an
d
a
class
r
o
o
m
w
i
th
i
n
th
e
co
lleg
e
o
f
co
m
p
u
ter
s
t
u
d
ies
,
MSU
-
I
I
T
.
T
h
e
test
in
g
in
v
o
lv
ed
a
co
n
s
is
te
n
t
o
n
e
-
h
o
u
r
s
a
m
p
l
in
g
p
er
io
d
at
e
ac
h
lo
ca
tio
n
.
R
es
u
lts
w
er
e
g
r
a
p
h
icall
y
p
lo
tted
u
s
i
n
g
MA
T
L
A
B
,
w
ith
k
e
y
m
etr
ics
s
u
c
h
as a
v
er
ag
e
n
o
i
s
e
lev
el,
p
e
ak
n
o
is
e,
a
n
d
s
tan
d
ar
d
d
ev
iati
o
n
ca
lcu
lated
.
I
o
T
lab
o
r
ato
r
y
Fig
u
r
e
7
,
No
is
e
lev
els
i
n
th
e
I
o
T
lab
w
er
e
co
n
s
is
te
n
tl
y
lo
w
(
1
3
–
1
5
d
B
)
w
it
h
o
cc
asio
n
al
p
ea
k
s
u
p
to
1
8
.
5
d
B
,
in
d
icatin
g
a
q
u
iet,
co
n
tr
o
lled
en
v
ir
o
n
m
en
t
t
y
p
ica
l
o
f
r
esear
ch
s
p
ac
es.
Min
o
r
f
l
u
ct
u
atio
n
s
w
er
e
ca
u
s
ed
b
y
s
h
o
r
t
ac
ti
v
itie
s
s
u
ch
a
s
eq
u
ip
m
en
t
ad
j
u
s
t
m
e
n
ts
o
r
f
o
o
t
tr
a
f
f
ic.
T
h
e
s
m
a
ll
s
tan
d
ar
d
d
ev
iatio
n
co
n
f
ir
m
s
s
u
itab
ilit
y
f
o
r
h
i
g
h
-
p
r
ec
is
io
n
w
o
r
k
,
th
o
u
g
h
o
cc
asio
n
al
n
o
is
e
m
a
n
a
g
e
m
e
n
t
m
a
y
b
e
n
ee
d
ed
d
u
r
in
g
ac
tiv
e
h
o
u
r
s
.
Gr
ad
u
ate
lab
o
r
ato
r
y
Fi
g
u
r
e
8
n
o
is
e
le
v
els
in
t
h
e
g
r
ad
u
ate
lab
f
lu
c
tu
ated
b
et
w
ee
n
2
0
–
4
5
d
B
,
w
i
t
h
f
r
eq
u
en
t
p
ea
k
s
r
ef
lec
t
in
g
g
r
o
u
p
d
is
cu
s
s
io
n
s
,
eq
u
ip
m
en
t
u
s
e,
an
d
m
o
v
e
m
e
n
t.
T
h
e
h
i
g
h
er
v
a
r
iab
ilit
y
co
m
p
ar
ed
to
th
e
I
o
T
lab
in
d
icate
s
a
m
o
r
e
d
y
n
a
m
ic
s
etti
n
g
.
P
ea
k
s
ali
g
n
e
d
w
it
h
in
ter
ac
tio
n
p
er
io
d
s
,
w
h
i
le
q
u
ieter
i
n
ter
v
als
r
ef
lecte
d
d
o
w
n
ti
m
e.
Ov
er
all,
t
h
e
lab
’
s
ac
tiv
e
u
s
e
h
i
g
h
l
ig
h
t
s
th
e
n
ee
d
to
b
alan
ce
co
llab
o
r
atio
n
w
it
h
m
ea
s
u
r
e
s
th
at
r
ed
u
ce
d
is
r
u
p
ti
v
e
n
o
is
e
d
u
r
in
g
f
o
cu
s
ed
task
s
.
E
m
b
ed
d
ed
lab
o
r
ato
r
y
Fi
g
u
r
e
9
,
n
o
is
e
le
v
el
s
i
n
t
h
e
e
m
b
e
d
d
ed
lab
r
an
g
ed
f
r
o
m
2
0
–
3
4
d
B
w
it
h
m
o
d
er
ate,
co
n
s
is
te
n
t
f
l
u
ct
u
ati
o
n
s
ca
u
s
ed
b
y
eq
u
ip
m
e
n
t
u
s
e,
to
o
l
ad
j
u
s
t
m
e
n
t
s
,
an
d
tec
h
n
ica
l
d
is
c
u
s
s
io
n
s
.
A
lt
h
o
u
g
h
v
ar
iab
ilit
y
w
as
le
s
s
t
h
an
in
th
e
g
r
ad
u
ate
lab
,
ac
ti
v
it
y
w
as
h
i
g
h
er
th
a
n
i
n
t
h
e
I
o
T
la
b
.
T
h
e
s
p
ac
e
r
ef
lects
a
b
alan
ce
b
et
w
ee
n
h
a
n
d
s
-
o
n
e
x
p
er
i
m
e
n
tatio
n
an
d
ac
o
u
s
t
ic
s
t
ab
ilit
y
.
C
las
s
r
o
o
m
Fi
g
u
r
e
1
0
,
th
e
cla
s
s
r
o
o
m
s
h
o
w
ed
th
e
m
o
s
t
d
y
n
a
m
ic
n
o
is
e
p
r
o
f
ile,
f
l
u
ct
u
ati
n
g
b
et
w
ee
n
2
2
–
5
0
d
B
w
i
th
f
r
eq
u
en
t
p
ea
k
s
ca
u
s
ed
b
y
co
n
t
in
u
o
u
s
lectu
r
es,
d
is
cu
s
s
io
n
s
,
a
n
d
m
o
v
e
m
e
n
t.
Hig
h
v
ar
iab
ilit
y
r
ef
lect
s
an
ac
tiv
e
ac
ad
e
m
ic
s
etti
n
g
.
T
h
ese
f
in
d
i
n
g
s
e
m
p
h
asize
th
e
n
e
ed
f
o
r
ac
o
u
s
tic
tr
ea
t
m
e
n
t
o
r
s
c
h
ed
u
li
n
g
s
tr
ateg
ie
s
to
m
a
in
ta
in
clar
it
y
an
d
co
n
ce
n
tr
atio
n
d
u
r
in
g
i
n
s
tr
u
ctio
n
.
Fig
u
r
e
7
.
No
is
e
d
ata
2
nd
f
lo
o
r
b
u
ild
in
g
I
o
T
lab
Fig
u
r
e
8
.
No
is
e
d
ata
3
rd
f
lo
o
r
b
u
ild
in
g
g
r
ad
u
a
te
lab
Fig
u
r
e
9
.
No
is
e
d
ata
3
rd
f
lo
o
r
b
u
ild
in
g
e
m
b
ed
d
ed
lab
Fig
u
r
e
1
0
.
No
is
e
Data
3
rd
f
lo
o
r
b
u
ild
in
g
cla
s
s
r
o
o
m
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.
24
,
No
.
2
,
A
p
r
il
20
26
:
5
9
9
-
607
604
3
.
1
.
I
nd
o
o
r
t
esting
T
esti
n
g
w
a
s
co
n
d
u
cted
ac
r
o
s
s
f
o
u
r
i
n
d
o
o
r
en
v
ir
o
n
m
e
n
ts
-
I
o
T
lab
,
g
r
ad
u
ate
lab
,
em
b
ed
d
ed
lab
,
an
d
class
r
o
o
m
-
ea
ch
f
o
r
o
n
e
h
o
u
r
:
(
i)
I
o
T
l
ab
:
m
ea
n
1
4
.
2
d
B
,
s
tan
d
ar
d
d
ev
iatio
n
(
SD
)
1
.
2
,
(
ii)
g
r
ad
u
ate
l
ab
:
m
ea
n
2
7
.
5
d
B
,
SD
6
.
8
,
(
iii)
e
m
b
ed
d
ed
l
ab
:
m
ea
n
2
5
.
3
d
B
,
SD
4
.
5
,
an
d
(
iv
)
c
lass
r
o
o
m
:
m
ea
n
3
2
.
1
d
B
,
SD
7
.
0
.
T
h
e
MA
T
L
A
B
-
g
e
n
er
ated
p
lo
ts
d
e
m
o
n
s
tr
ated
ac
cu
r
ate
an
d
r
ea
l
-
ti
m
e
v
is
u
aliza
tio
n
o
f
en
v
ir
o
n
m
e
n
tal
n
o
is
e
,
co
n
f
ir
m
i
n
g
S
D
A
S r
eliab
ilit
y
.
3
.
2
.
Co
m
pa
ra
t
iv
e
a
na
ly
s
is
T
h
e
co
m
p
ar
ativ
e
c
h
ar
t Fig
u
r
e
1
1
s
h
o
w
s
t
h
at
t
h
e
SD
AS e
f
f
ec
tiv
el
y
d
is
ti
n
g
u
i
s
h
e
s
n
o
is
e
p
att
er
n
s
ac
r
o
s
s
v
ar
ied
en
v
ir
o
n
m
e
n
t
s
.
T
h
e
class
r
o
o
m
r
ec
o
r
d
ed
th
e
h
ig
h
es
t v
a
r
iab
ilit
y
,
w
h
i
le
th
e
I
o
T
L
ab
r
e
m
ai
n
ed
m
o
s
t stab
le.
Fo
r
f
u
t
u
r
e
tes
tin
g
,
d
ep
lo
y
m
en
t
in
o
u
td
o
o
r
en
v
ir
o
n
m
en
ts
(
e.
g
.
,
h
i
g
h
w
a
y
s
an
d
m
ar
k
e
ts
)
w
i
ll
ca
p
tu
r
e
b
r
o
ad
er
ac
o
u
s
tic
p
r
o
f
iles
.
A
d
v
an
ce
d
tech
n
iq
u
es
s
u
c
h
as
an
al
y
s
is
o
f
v
ar
ian
ce
(
A
NOV
A
)
an
d
m
ac
h
i
n
e
lear
n
in
g
class
i
f
icatio
n
ar
e
p
lan
n
ed
f
o
r
n
o
is
e
-
s
o
u
r
ce
id
en
ti
f
icatio
n
a
n
d
p
r
ed
ictiv
e
tr
en
d
m
o
d
eli
n
g
.
T
h
e
co
m
p
ar
ativ
e
a
n
al
y
s
is
i
n
Fi
g
u
r
e
1
1
h
ig
h
li
g
h
ts
t
h
e
SD
AS
’
s
ef
f
ec
t
iv
e
n
es
s
in
d
is
tin
g
u
is
h
i
n
g
ac
o
u
s
ti
c
p
r
o
f
iles
ac
r
o
s
s
m
u
ltip
le
lo
ca
t
io
n
s
.
Fo
r
f
u
t
u
r
e
w
o
r
k
,
t
h
e
r
e
s
ea
r
ch
tea
m
p
la
n
s
to
e
x
te
n
d
test
i
n
g
to
o
u
td
o
o
r
en
v
ir
o
n
m
e
n
t
s
,
in
clu
d
i
n
g
tr
af
f
i
c
in
ter
s
ec
tio
n
s
an
d
m
ar
k
et
zo
n
es,
to
ca
p
tu
r
e
co
m
p
lex
u
r
b
an
n
o
is
e
s
i
g
n
at
u
r
es.
Statis
t
ical
to
o
ls
s
u
c
h
a
s
A
NO
VA
an
d
m
ac
h
in
e
lear
n
i
n
g
-
b
as
ed
n
o
is
e
cla
s
s
i
f
icatio
n
w
il
l
als
o
b
e
in
co
r
p
o
r
ated
to
en
h
a
n
ce
p
r
ed
ictiv
e
a
n
al
y
s
is
a
n
d
d
if
f
er
en
t
iate
b
et
w
ee
n
n
o
i
s
e
s
o
u
r
ce
s
(
e.
g
.
,
v
e
h
icles
,
m
ac
h
in
er
y
,
a
n
d
h
u
m
an
ac
tiv
it
y
)
.
T
h
ese
r
esu
lts
co
n
f
ir
m
th
e
S
D
A
S
ef
f
ec
t
iv
el
y
ca
p
tu
r
es
d
is
tin
ct
ac
o
u
s
tic
b
eh
a
v
io
r
s
in
ac
ad
e
m
ic
s
p
ac
es
an
d
alig
n
s
w
it
h
p
r
io
r
f
in
d
i
n
g
s
o
n
in
d
o
o
r
n
o
is
e
d
y
n
a
m
ics
[
2
2
]
.
T
h
e
y
al
s
o
r
ein
f
o
r
ce
th
e
v
a
lu
e
o
f
A
I
-
in
te
g
r
ated
s
y
s
te
m
s
f
o
r
h
ig
h
-
ac
ti
v
it
y
e
n
v
i
r
o
n
m
e
n
ts
[
2
3
]
,
th
e
i
m
p
o
r
ta
n
ce
o
f
I
C
T
-
b
ased
ac
o
u
s
tic
s
ta
n
d
ar
d
s
[
2
4
]
,
an
d
th
e
r
elev
an
ce
o
f
d
i
s
tr
ib
u
ted
lo
w
-
c
o
s
t a
co
u
s
tic
s
e
n
s
o
r
n
et
w
o
r
k
s
f
o
r
r
ea
l
-
ti
m
e
u
r
b
an
m
o
n
ito
r
in
g
[
2
5
]
.
Fig
u
r
e
1
1
.
C
o
m
p
ar
ativ
e
ch
ar
t
3
.
3
.
Su
m
m
a
ry
t
a
ble
T
ab
le
1
co
n
s
o
lid
ates
m
ea
n
,
p
ea
k
,
an
d
v
ar
iab
ilit
y
v
a
lu
e
s
f
o
r
all
lo
ca
tio
n
s
.
R
es
u
lts
s
h
o
w
t
h
at
th
e
I
o
T
l
ab
m
ai
n
tai
n
ed
th
e
lo
w
e
s
t le
v
els (
m
ea
n
1
4
.
2
d
B
,
SD 1
.
2
)
,
w
h
ile
th
e
clas
s
r
o
o
m
h
ad
th
e
h
i
g
h
e
s
t
(
m
ea
n
3
2
.
1
d
B
,
SD
7
.
0
)
.
T
h
e
g
r
ad
u
ate
l
ab
r
ea
ch
ed
th
e
m
a
x
i
m
u
m
p
ea
k
(
4
0
d
B
)
an
d
th
e
em
b
ed
d
ed
lab
ex
h
ib
ited
m
o
d
er
ate
f
l
u
ctu
a
tio
n
s
(
m
ea
n
2
5
.
3
d
B
,
S
D
4
.
5
)
.
T
h
ese
f
in
d
i
n
g
s
co
n
f
ir
m
t
h
e
SD
A
S
ac
c
u
r
atel
y
d
is
ti
n
g
u
i
s
h
es
b
et
w
ee
n
q
u
iet
an
d
d
y
n
a
m
ic
e
n
v
ir
o
n
m
e
n
t
s
,
s
u
p
p
o
r
tin
g
its
d
ep
l
o
y
m
e
n
t
f
o
r
s
m
ar
t c
a
m
p
u
s
a
n
d
b
r
o
ad
er
u
r
b
an
m
o
n
ito
r
in
g
.
T
ab
le
1
.
Su
m
m
ar
y
o
f
n
o
is
e
le
v
els ac
r
o
s
s
te
s
t lo
ca
tio
n
s
L
o
c
a
t
i
o
n
M
e
a
n
n
o
i
se
l
e
v
e
l
(
d
B
)
P
e
a
k
n
o
i
se
l
e
v
e
l
(
d
B
)
V
a
r
i
a
b
i
l
i
t
y
(
s
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
,
d
B
)
I
o
T
l
ab
1
4
.
2
15
1
.
2
G
r
a
d
u
a
t
e
l
ab
2
7
.
5
40
6
.
8
Emb
e
d
d
e
d
l
ab
2
5
.
3
35
4
.
5
C
l
a
ssr
o
o
m
3
2
.
1
40
7
.
0
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
Lo
w
-
c
o
s
t E
S
P
3
2
-
b
a
s
ed
s
o
u
n
d
d
a
ta
a
c
q
u
is
itio
n
s
ystem
w
ith
MATLAB
…
(
R
ey
ma
r
k
-
Jo
h
n
A
.
Ma
ca
p
a
n
a
s
)
605
3
.
4
.
F
uture
a
pp
lica
t
io
ns
a
nd
li
m
it
a
t
io
ns
W
h
ile
th
e
s
y
s
te
m
p
er
f
o
r
m
ed
as
in
te
n
d
ed
ac
r
o
s
s
all
lo
ca
tio
n
s
,
f
u
r
t
h
er
r
ef
in
e
m
e
n
ts
s
u
c
h
as
W
i
-
Fi
d
ata
s
y
n
ci
n
g
,
a
u
to
m
ated
d
ata
clas
s
if
icatio
n
,
an
d
m
u
lt
i
-
n
o
d
e
d
ep
lo
y
m
e
n
ts
ar
e
r
ec
o
m
m
e
n
d
ed
.
T
h
e
cu
r
r
en
t
v
er
s
io
n
ass
u
m
e
s
a
s
i
n
g
le
-
n
o
d
e
s
etu
p
w
it
h
m
an
u
al
d
ep
lo
y
m
en
t,
w
h
ich
ca
n
b
e
i
m
p
r
o
v
ed
f
o
r
lo
n
g
-
ter
m
u
n
at
ten
d
ed
m
o
n
ito
r
i
n
g
.
Desp
ite
th
ese
li
m
itatio
n
s
,
th
e
s
y
s
te
m
’
s
m
o
d
u
lar
d
esig
n
,
lo
w
c
o
s
t,
an
d
r
ep
r
o
d
u
cib
ilit
y
m
ak
e
i
t a
s
tr
o
n
g
ca
n
d
id
ate
f
o
r
s
ca
lin
g
in
s
i
m
il
ar
in
s
tit
u
tio
n
s
o
r
u
r
b
an
s
etu
p
s
co
n
ce
r
n
ed
w
it
h
en
v
ir
o
n
m
e
n
t
al
n
o
is
e.
T
h
e
r
esu
lts
r
ein
f
o
r
ce
th
e
r
esear
c
h
o
b
j
ec
tiv
es a
n
d
j
u
s
ti
f
y
t
h
e
v
al
u
e
o
f
a
lo
w
-
co
s
t,
M
A
T
L
A
B
-
in
te
g
r
ated
SD
A
S
f
o
r
r
ea
l
-
ti
m
e
en
v
ir
o
n
m
e
n
tal
m
o
n
ito
r
in
g
an
d
an
al
y
s
is
.
3
.
5
.
T
esting
a
nd
ev
a
lua
t
io
n
o
f
t
he
s
y
s
t
e
m
T
h
e
SDAS
w
as
test
ed
i
n
m
u
lti
p
le
ca
m
p
u
s
lo
ca
tio
n
s
,
ca
p
t
u
r
in
g
n
o
i
s
e
f
lu
c
tu
atio
n
s
ac
r
o
s
s
b
o
th
q
u
iet
an
d
d
y
n
a
m
ic
en
v
ir
o
n
m
e
n
ts
.
A
p
an
el
o
f
eig
h
t
ex
p
er
ts
w
it
h
m
a
s
ter
’
s
d
eg
r
ee
s
i
n
co
m
p
u
ter
ap
p
licatio
n
s
ev
a
lu
ated
it
s
u
s
ab
ilit
y
,
i
n
te
g
r
atio
n
w
i
th
M
A
T
L
A
B
,
an
d
r
eliab
ili
t
y
.
O
v
e
r
all
f
ee
d
b
ac
k
w
a
s
p
o
s
iti
v
e,
h
ig
h
lig
h
ti
n
g
ea
s
e
o
f
d
ep
lo
y
m
en
t,
ac
cu
r
ac
y
o
f
ca
p
t
u
r
ed
d
ata,
an
d
clar
ity
o
f
v
is
u
a
lizatio
n
s
.
Min
o
r
is
s
u
es
i
n
clu
d
ed
a
s
m
all
lear
n
i
n
g
cu
r
v
e
f
o
r
s
o
m
e
u
s
er
s
an
d
th
e
n
ee
d
f
o
r
clea
r
e
r
d
o
cu
m
en
ta
ti
o
n
.
Desp
ite
th
is
,
m
o
s
t
ex
p
er
t
s
f
o
u
n
d
th
e
s
y
s
te
m
in
t
u
iti
v
e,
r
eliab
le,
an
d
s
u
i
tab
le
f
o
r
r
eg
u
lar
u
s
e.
Fi
g
u
r
e
1
2
s
u
m
m
ar
ize
s
th
e
e
v
al
u
atio
n
r
es
u
lts
,
co
n
f
ir
m
i
n
g
t
h
e
SD
A
S
’
s
r
ea
d
in
e
s
s
f
o
r
w
id
er
a
d
o
p
tio
n
in
r
ea
l
-
ti
m
e
n
o
i
s
e
m
o
n
ito
r
in
g
.
Fig
u
r
e
1
2
.
E
x
p
er
t e
v
alu
atio
n
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
d
esi
g
n
ed
an
d
i
m
p
l
e
m
en
ted
a
lo
w
-
co
s
t
E
SP
3
2
-
b
ased
SDAS
f
o
r
r
ea
l
-
ti
m
e
m
o
n
ito
r
in
g
o
f
in
d
o
o
r
n
o
is
e
le
v
els.
T
h
e
s
y
s
t
e
m
i
n
te
g
r
ates
ME
M
S
-
b
ased
ac
o
u
s
tic
s
en
s
i
n
g
,
E
SP
-
W
R
O
OM
-
3
2
p
r
o
ce
s
s
in
g
,
MA
T
L
A
B
v
is
u
aliza
tio
n
,
an
d
lo
ca
l
d
ata
s
to
r
ag
e.
T
esti
n
g
ac
r
o
s
s
f
o
u
r
ca
m
p
u
s
lo
ca
tio
n
s
p
r
o
d
u
ce
d
m
ea
n
n
o
i
s
e
lev
els
o
f
1
4
.
2
d
B
(
I
o
T
l
a
b
)
,
2
7
.
5
d
B
(
g
r
ad
u
ate
l
ab
)
,
2
5
.
3
d
B
(
em
b
ed
d
ed
lab
)
,
an
d
3
2
.
1
d
B
(
c
lass
r
o
o
m
)
,
co
n
f
ir
m
i
n
g
it
s
ac
cu
r
ac
y
a
n
d
s
t
ab
ilit
y
.
L
i
m
itatio
n
s
in
c
lu
d
e
s
i
n
g
le
-
n
o
d
e
d
ep
l
o
y
m
e
n
t,
in
d
o
o
r
-
o
n
l
y
v
alid
atio
n
,
an
d
USB
-
b
ased
M
A
T
L
A
B
tr
an
s
m
is
s
io
n
.
Desp
ite
t
h
e
s
e,
th
e
SD
AS
d
e
m
o
n
s
tr
ates
h
i
g
h
u
s
ab
ili
t
y
a
n
d
r
eliab
ilit
y
as
co
n
f
ir
m
ed
b
y
ex
p
er
t
ev
al
u
ati
o
n
.
Fu
t
u
r
e
r
esear
ch
w
il
l
f
o
cu
s
o
n
m
u
lti
-
n
o
d
e
w
ir
ele
s
s
s
y
n
ch
r
o
n
izatio
n
,
clo
u
d
in
te
g
r
atio
n
,
an
d
A
I
-
d
r
iv
en
n
o
i
s
e
class
i
f
icat
io
n
to
en
ab
le
lar
g
e
-
s
ca
le
s
m
ar
t c
it
y
ac
o
u
s
tic
m
o
n
ito
r
in
g
.
ACK
NO
WL
E
D
G
M
E
NT
S
T
h
e
au
th
o
r
s
f
u
l
l
y
ac
k
n
o
w
led
g
e
th
e
Min
d
an
ao
State
Un
i
v
er
s
i
t
y
,
I
lig
a
n
o
f
T
ec
h
n
o
lo
g
y
,
Dep
ar
t
m
en
t
o
f
C
o
m
p
u
ter
A
p
p
licatio
n
s
,
C
o
ll
eg
e
o
f
C
o
m
p
u
ter
Stu
d
ie
s
,
a
n
d
E
n
g
i
n
ee
r
in
g
R
esear
c
h
a
n
d
Dev
elo
p
m
e
n
t
f
o
r
T
ec
h
n
o
lo
g
y
.
F
UNDIN
G
I
NF
O
RM
AT
I
O
N
T
h
is
r
esear
ch
r
ec
eiv
ed
n
o
ex
ter
n
al
f
u
n
d
i
n
g
; it
w
as f
u
ll
y
s
u
p
p
o
r
ted
b
y
th
e
au
th
o
r
’
s
p
er
s
o
n
al
r
eso
u
r
ce
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.
24
,
No
.
2
,
A
p
r
il
20
26
:
5
9
9
-
607
606
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
th
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
R
e
y
m
ar
k
-
J
o
h
n
A
.
Ma
ca
p
an
as
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
A
d
r
ian
P
.
Galid
o
✓
✓
✓
✓
✓
✓
✓
✓
A
p
p
le
R
o
s
e
B
.
Alce
✓
✓
✓
✓
✓
✓
✓
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
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
A
ll a
u
t
h
o
r
s
d
ec
lar
e
th
at
t
h
e
y
h
av
e
n
o
co
n
f
lict o
f
i
n
ter
es
t.
DATA
AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
r
t
th
e
f
i
n
d
in
g
s
o
f
t
h
is
s
t
u
d
y
ar
e
av
ailab
l
e
f
r
o
m
t
h
e
co
r
r
esp
o
n
d
in
g
a
u
t
h
o
r
,
R
J
M,
u
p
o
n
r
ea
s
o
n
ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
J.
P
i
c
a
u
t
,
A
.
C
a
n
,
N
.
F
o
r
t
i
n
,
J.
A
r
d
o
u
i
n
,
a
n
d
M
.
L
a
g
r
a
n
g
e
,
“
L
o
w
-
c
o
st
se
n
so
r
s
f
o
r
u
r
b
a
n
n
o
i
se
mo
n
i
t
o
r
i
n
g
n
e
t
w
o
r
k
s
—
A
l
i
t
e
r
a
t
u
r
e
r
e
v
i
e
w
,
”
S
e
n
s
o
rs
(
S
w
i
t
zer
l
a
n
d
)
,
v
o
l
.
2
0
,
n
o
.
8
,
p
.
2
2
5
6
,
A
p
r
.
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
s2
0
0
8
2
2
5
6
.
[
2
]
C
.
M
y
d
l
a
r
z
,
J.
S
a
l
a
mo
n
,
a
n
d
J.
P
.
B
e
l
l
o
,
“
T
h
e
i
mp
l
e
me
n
t
a
t
i
o
n
o
f
l
o
w
-
c
o
st
u
r
b
a
n
a
c
o
u
s
t
i
c
mo
n
i
t
o
r
i
n
g
d
e
v
i
c
e
s,”
Ap
p
l
i
e
d
Ac
o
u
st
i
c
s
,
v
o
l
.
1
1
7
,
p
p
.
2
0
7
–
2
1
8
,
F
e
b
.
2
0
1
7
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
a
p
a
c
o
u
s
t
.
2
0
1
6
.
0
6
.
0
1
0
.
[
3
]
E.
V
i
d
a
ñ
a
-
V
i
l
a
,
J.
N
a
v
a
r
r
o
,
C
.
B
o
r
d
a
-
F
o
r
t
u
n
y
,
D
.
S
t
o
w
e
l
l
,
a
n
d
R
.
M
.
A
l
si
n
a
-
P
a
g
è
s,
“
L
o
w
-
C
o
st
D
i
st
r
i
b
u
t
e
d
A
c
o
u
st
i
c
S
e
n
so
r
N
e
t
w
o
r
k
f
o
r
R
e
a
l
-
T
i
me
U
r
b
a
n
S
o
u
n
d
M
o
n
i
t
o
r
i
n
g
,
”
E
l
e
c
t
r
o
n
i
c
s
,
v
o
l
.
9
,
n
o
.
1
2
,
p
.
2
1
1
9
,
D
e
c
.
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
e
l
e
c
t
r
o
n
i
c
s
9
1
2
2
1
1
9
.
[
4
]
T.
F
a
t
e
ma,
M
.
A
.
H
a
k
i
m,
T
.
K
.
M
i
m,
M
.
J
.
M
i
t
u
,
a
n
d
B
.
P
a
u
l
,
“
I
o
T
c
l
o
u
d
b
a
se
d
n
o
i
se
i
n
t
e
n
s
i
t
y
mo
n
i
t
o
r
i
n
g
sy
st
e
m,”
I
n
d
o
n
e
si
a
n
J
o
u
rn
a
l
o
f
El
e
c
t
ri
c
a
l
E
n
g
i
n
e
e
r
i
n
g
a
n
d
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
,
v
o
l
.
3
0
,
n
o
.
1
,
p
p
.
2
8
9
–
2
9
8
,
A
p
r
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
e
e
c
s.v
3
0
.
i
1
.
p
p
2
8
9
-
2
9
8
.
[
5
]
C
.
T
o
ma,
A
.
A
l
e
x
a
n
d
r
u
,
M
.
P
o
p
a
,
a
n
d
A
.
Z
a
mf
i
r
o
i
u
,
“
I
o
T
S
o
l
u
t
i
o
n
f
o
r
S
mart
C
i
t
i
e
s’
P
o
l
l
u
t
i
o
n
M
o
n
i
t
o
r
i
n
g
a
n
d
t
h
e
S
e
c
u
r
i
t
y
C
h
a
l
l
e
n
g
e
s,”
S
e
n
so
rs
,
v
o
l
.
1
9
,
n
o
.
1
5
,
p
.
3
4
0
1
,
A
u
g
.
2
0
1
9
,
d
o
i
:
1
0
.
3
3
9
0
/
s
1
9
1
5
3
4
0
1
.
[
6
]
R
.
M
.
A
l
si
n
a
-
P
a
g
è
s,
P
.
B
e
l
l
u
c
c
i
,
a
n
d
G
.
Z
a
mb
o
n
,
“
S
mart
W
i
r
e
l
e
ss
A
c
o
u
st
i
c
S
e
n
so
r
N
e
t
w
o
r
k
D
e
si
g
n
f
o
r
N
o
i
se
M
o
n
i
t
o
r
i
n
g
i
n
S
m
a
r
t
C
i
t
i
e
s,”
S
e
n
s
o
rs
,
v
o
l
.
2
0
,
n
o
.
1
7
,
p
.
4
7
6
5
,
A
u
g
.
2
0
2
0
,
d
o
i
:
1
0
.
3
3
9
0
/
s2
0
1
7
4
7
6
5
.
[
7
]
G
.
Q
u
i
n
t
e
r
o
,
A
.
B
a
l
a
s
t
e
g
u
i
,
a
n
d
J
.
R
o
me
u
,
“
A
l
o
w
-
c
o
st
n
o
i
se
me
a
s
u
r
e
me
n
t
d
e
v
i
c
e
f
o
r
n
o
i
se
ma
p
p
i
n
g
b
a
se
d
o
n
mo
b
i
l
e
sam
p
l
i
n
g
,
”
Me
a
su
r
e
m
e
n
t
,
v
o
l
.
1
4
8
,
p
.
1
0
6
8
9
4
,
D
e
c
.
2
0
1
9
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
me
a
s
u
r
e
me
n
t
.
2
0
1
9
.
1
0
6
8
9
4
.
[
8
]
A
.
P
a
sca
l
e
e
t
a
l
.
,
“
R
o
a
d
t
r
a
f
f
i
c
n
o
i
se
mo
n
i
t
o
r
i
n
g
i
n
a
S
m
a
r
t
C
i
t
y
:
S
e
n
so
r
a
n
d
M
o
d
e
l
-
B
a
se
d
a
p
p
r
o
a
c
h
,
”
T
ra
n
s
p
o
rt
a
t
i
o
n
R
e
se
a
rc
h
Pa
rt
D
:
T
ra
n
s
p
o
rt
a
n
d
E
n
v
i
ro
n
m
e
n
t
,
v
o
l
.
1
2
5
,
p
.
1
0
3
9
7
9
,
D
e
c
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
t
r
d
.
2
0
2
3
.
1
0
3
9
7
9
.
[
9
]
T
.
M
o
n
t
a
n
a
r
o
,
I
.
S
e
r
g
i
,
M
.
B
a
si
l
e
,
L
.
M
a
i
n
e
t
t
i
,
a
n
d
L
.
P
a
t
r
o
n
o
,
“
A
n
I
o
T
-
A
w
a
r
e
S
o
l
u
t
i
o
n
t
o
S
u
p
p
o
r
t
G
o
v
e
r
n
me
n
t
s
i
n
A
i
r
P
o
l
l
u
t
i
o
n
M
o
n
i
t
o
r
i
n
g
B
a
se
d
o
n
t
h
e
C
o
m
b
i
n
a
t
i
o
n
o
f
R
e
a
l
-
T
i
me
D
a
t
a
a
n
d
C
i
t
i
z
e
n
F
e
e
d
b
a
c
k
,
”
S
e
n
s
o
rs
,
v
o
l
.
2
2
,
n
o
.
3
,
p
.
1
0
0
0
,
Ja
n
.
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
s
2
2
0
3
1
0
0
0
.
[
1
0
]
S
.
F
.
H
a
m
a
mc
ı
a
n
d
A
.
Ö
.
D
o
ğ
r
u
,
“
L
o
w
-
c
o
st
r
e
a
l
-
t
i
me
e
n
v
i
r
o
n
me
n
t
a
l
n
o
i
se
mo
n
i
t
o
r
i
n
g
sy
st
e
m
d
e
si
g
n
a
n
d
i
mp
l
e
me
n
t
a
t
i
o
n
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
E
n
v
i
ro
n
m
e
n
t
a
l
S
t
u
d
i
e
s
,
v
o
l
.
8
1
,
n
o
.
3
,
p
p
.
1
0
4
5
–
1
0
5
7
,
D
e
c
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
8
0
/
0
0
2
0
7
2
3
3
.
2
0
2
3
.
2
2
9
5
2
1
2
.
[
1
1
]
F
.
R
.
d
e
M
e
l
l
o
a
n
d
W
.
D
.
F
o
n
se
c
a
,
“
A
u
t
o
n
o
mo
u
s
n
o
i
se
mo
n
i
t
o
r
i
n
g
sy
st
e
m
b
a
se
d
o
n
d
i
g
i
t
a
l
M
E
M
S
m
i
c
r
o
p
h
o
n
e
s
:
d
e
v
e
l
o
p
me
n
t
o
f
a
sm
a
r
t
p
h
o
n
e
a
p
p
l
i
c
a
t
i
o
n
f
o
r
r
e
mo
t
e
c
o
mm
u
n
i
c
a
t
i
o
n
,
”
I
N
T
ER
-
N
O
I
S
E
a
n
d
N
O
I
S
E
-
C
O
N
C
o
n
g
r
e
ss
a
n
d
C
o
n
f
e
re
n
c
e
Pr
o
c
e
e
d
i
n
g
s
,
v
o
l
.
2
6
5
,
n
o
.
2
,
p
p
.
5
6
5
0
–
5
6
6
1
,
F
e
b
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
7
/
i
n
_
2
0
2
2
_
0
8
3
1
.
[
1
2
]
M
.
O
.
Ja
k
o
b
se
n
,
“
L
o
w
c
o
st
M
E
M
S
a
c
c
e
l
e
r
o
m
e
t
e
r
a
n
d
mi
c
r
o
p
h
o
n
e
b
a
se
d
c
o
n
d
i
t
i
o
n
mo
n
i
t
o
r
i
n
g
se
n
so
r
,
w
i
t
h
L
o
R
a
a
n
d
B
l
u
e
t
o
o
t
h
L
o
w
En
e
r
g
y
r
a
d
i
o
,
”
H
a
rd
w
a
r
e
X
,
v
o
l
.
1
8
,
p
.
e
0
0
5
2
5
,
Ju
n
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
o
h
x
.
2
0
2
4
.
e
0
0
5
2
5
.
[
1
3
]
F
.
Ze
n
g
,
C
.
P
a
n
g
,
a
n
d
H
.
T
a
n
g
,
“
S
e
n
so
r
s
o
n
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s
S
y
st
e
ms
f
o
r
t
h
e
S
u
s
t
a
i
n
a
b
l
e
D
e
v
e
l
o
p
me
n
t
o
f
S
mart
C
i
t
i
e
s:
A
S
y
st
e
mat
i
c
L
i
t
e
r
a
t
u
r
e
R
e
v
i
e
w
,
”
S
e
n
s
o
rs
,
v
o
l
.
2
4
,
n
o
.
7
,
p
.
2
0
7
4
,
M
a
r
.
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
s
2
4
0
7
2
0
7
4
.
[
1
4
]
Y
.
L
i
u
,
X
.
M
a
a
n
d
C
.
A
.
B
o
a
n
o
,
"
I
n
t
e
l
l
i
g
e
n
t
N
o
i
se
M
a
p
p
i
n
g
f
o
r
S
mart
C
i
t
i
e
s:
S
o
l
u
t
i
o
n
s
,
T
r
e
n
d
s,
a
n
d
R
e
se
a
r
c
h
O
p
p
o
r
t
u
n
i
t
i
e
s,"
i
n
I
EEE
C
o
m
m
u
n
i
c
a
t
i
o
n
s
M
a
g
a
zi
n
e
,
v
o
l
.
6
2
,
n
o
.
1
2
,
p
p
.
1
8
-
2
5
,
D
e
c
e
mb
e
r
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
9
/
M
C
O
M
.
0
0
1
.
2
3
0
0
5
3
6
[
1
5
]
N
.
N
a
n
o
s,
A
.
L
e
e
,
a
n
d
T
.
M
a
v
r
i
d
o
u
,
“
A
st
u
d
y
o
n
a
l
o
w
-
c
o
st
r
e
a
l
t
i
me
M
EM
S
b
a
se
d
mo
d
u
l
a
r
I
n
d
o
o
r
En
v
i
r
o
n
me
n
t
a
l
Q
u
a
l
i
t
y
mo
n
i
t
o
r
se
n
so
r
,
”
E
3
S
W
e
b
o
f
C
o
n
f
e
re
n
c
e
s
,
v
o
l
.
6
3
4
,
p
.
0
3
0
0
2
,
2
0
2
5
,
d
o
i
:
1
0
.
1
0
5
1
/
e
3
sco
n
f
/
2
0
2
5
6
3
4
0
3
0
0
2
.
[
1
6
]
J.
J.
S
a
l
d
a
n
a
-
B
a
r
r
i
o
s,
E.
A
g
u
i
l
a
r
,
W
.
N
g
,
a
n
d
R
.
O
r
o
c
u
,
“
D
e
si
g
n
i
n
g
a
n
I
o
T
-
B
a
se
d
S
y
s
t
e
m
f
o
r
M
o
n
i
t
o
r
i
n
g
N
o
i
se
L
e
v
e
l
s
i
n
t
h
e
C
o
mp
u
t
e
r
S
c
i
e
n
c
e
F
a
c
u
l
t
y
a
n
d
L
i
b
r
a
r
y
o
f
t
h
e
Te
c
h
n
o
l
o
g
i
c
a
l
U
n
i
v
e
r
si
t
y
o
f
P
a
n
a
ma,
”
S
e
n
s
o
rs
,
v
o
l
.
2
3
,
n
o
.
2
2
,
p
.
9
0
8
3
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
s
2
3
2
2
9
0
8
3
.
[
1
7
]
S
.
S
z
y
mo
n
i
a
k
a
n
d
Ł.
K
u
c
z
y
ń
sk
i
,
“
O
v
e
r
v
i
e
w
o
f
M
o
d
e
r
n
T
e
c
h
n
o
l
o
g
i
e
s
f
o
r
A
c
q
u
i
r
i
n
g
a
n
d
A
n
a
l
y
si
n
g
A
c
o
u
st
i
c
I
n
f
o
r
mat
i
o
n
B
a
se
d
o
n
A
I
a
n
d
I
o
T
,
”
Ap
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
1
5
,
n
o
.
1
2
,
p
.
6
6
9
0
,
J
u
n
.
2
0
2
5
,
d
o
i
:
1
0
.
3
3
9
0
/
a
p
p
1
5
1
2
6
6
9
0
.
[
1
8
]
G
.
M
a
r
q
u
e
s a
n
d
R
.
P
i
t
a
r
m
a
,
"
A
R
e
a
l
-
T
i
me
N
o
i
se
M
o
n
i
t
o
r
i
n
g
S
y
st
e
m B
a
se
d
o
n
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s fo
r
En
h
a
n
c
e
d
A
c
o
u
st
i
c
C
o
mf
o
r
t
a
n
d
O
c
c
u
p
a
t
i
o
n
a
l
H
e
a
l
t
h
,
"
i
n
I
E
EE
A
c
c
e
ss
,
v
o
l
.
8
,
p
p
.
1
3
9
7
4
1
-
1
3
9
7
5
5
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
ESS
.
2
0
2
0
.
3
0
1
2
9
1
9
.
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
Lo
w
-
c
o
s
t E
S
P
3
2
-
b
a
s
ed
s
o
u
n
d
d
a
ta
a
c
q
u
is
itio
n
s
ystem
w
ith
MATLAB
…
(
R
ey
ma
r
k
-
Jo
h
n
A
.
Ma
ca
p
a
n
a
s
)
607
[
1
9
]
O
.
A
k
t
a
ş
a
n
d
S
.
S
e
l
i
m,
“
G
I
S
B
a
se
d
U
r
b
a
n
N
o
i
se
P
o
l
l
u
t
i
o
n
A
n
a
l
y
si
s
a
n
d
M
a
p
p
i
n
g
:
T
h
e
C
a
se
o
f
A
n
t
a
l
y
a
,
T
u
r
k
e
y
,
”
Me
h
m
e
t
A
k
i
f
Er
so
y
Ü
n
i
v
e
rsi
t
e
s
i
F
e
n
Bi
l
i
m
l
e
r
i
E
n
st
i
t
ü
s
ü
D
e
rg
i
si
,
v
o
l
.
1
4
,
n
o
.
1
,
p
p
.
1
3
9
–
1
5
1
,
J
u
n
.
2
0
2
3
,
d
o
i
:
1
0
.
2
9
0
4
8
/
ma
k
u
f
e
b
e
d
.
1
2
5
5
9
1
0
.
[
2
0
]
Y
.
X
u
,
Y
.
Z
h
u
,
a
n
d
Z
.
Q
i
n
,
“
U
r
b
a
n
n
o
i
se
map
p
i
n
g
w
i
t
h
a
c
r
o
w
d
se
n
si
n
g
sy
st
e
m,”
Wi
r
e
l
e
ss
N
e
t
w
o
r
k
s
,
v
o
l
.
2
5
,
n
o
.
5
,
p
p
.
2
3
5
1
–
2
3
6
4
,
Jan
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
1
2
7
6
-
018
-
1
6
6
3
-
x.
[
2
1
]
Y
.
L
i
u
e
t
a
l
.,
“
I
n
t
e
r
n
e
t
o
f
T
h
i
n
g
s
f
o
r
N
o
i
se
M
a
p
p
i
n
g
i
n
S
mart
C
i
t
i
e
s:
S
t
a
t
e
o
f
t
h
e
A
r
t
a
n
d
F
u
t
u
r
e
D
i
r
e
c
t
i
o
n
s,
”
i
n
I
E
EE
N
e
t
w
o
r
k
,
v
o
l
.
3
4
,
n
o
.
4
,
p
p
.
1
1
2
-
1
1
8
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
M
N
ET
.
0
1
1
.
1
9
0
0
6
3
4
.
[
2
2
]
R
.
D
u
b
e
y
,
S
.
B
h
a
r
a
d
w
a
j
,
V
.
B
.
S
h
a
r
m
a
,
A
.
B
h
a
t
t
,
a
n
d
S
.
B
i
sw
a
s,
“
S
mar
t
p
h
o
n
e
-
b
a
se
d
t
r
a
f
f
i
c
n
o
i
se
ma
p
p
i
n
g
sy
st
e
m,”
I
n
t
e
r
n
a
t
i
o
n
a
l
Arc
h
i
v
e
s
o
f
t
h
e
P
h
o
t
o
g
ra
m
m
e
t
ry
,
R
e
m
o
t
e
S
e
n
s
i
n
g
a
n
d
S
p
a
t
i
a
l
I
n
f
o
rm
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
X
L
I
I
I
-
B4
-
2
0
2
2
,
p
p
.
6
1
3
–
6
2
0
,
J
u
n
.
2
0
2
2
,
d
o
i
:
1
0
.
5
1
9
4
/
i
s
p
r
s
-
a
r
c
h
i
v
e
s
-
x
l
i
i
i
-
b4
-
2
0
2
2
-
613
-
2
0
2
2
.
[
2
3
]
R
.
K
.
R
a
n
a
,
C
.
T
.
C
h
o
u
,
S
.
S
.
K
a
n
h
e
r
e
,
N
.
B
u
l
u
s
u
,
a
n
d
W
.
H
u
,
“
E
a
r
-
p
h
o
n
e
:
a
n
e
n
d
-
to
-
e
n
d
p
a
r
t
i
c
i
p
a
t
o
r
y
u
r
b
a
n
n
o
i
se
m
a
p
p
i
n
g
sy
st
e
m
,”
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
9
t
h
A
C
M/
I
EE
E
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
Pr
o
c
e
ss
i
n
g
i
n
S
e
n
s
o
r
N
e
t
w
o
r
k
s.
A
C
M
,
p
p
.
1
0
5
–
1
1
6
,
A
p
r
.
1
2
,
2
0
1
0
,
d
o
i
:
1
0
.
1
1
4
5
/
1
7
9
1
2
1
2
.
1
7
9
1
2
2
6
.
[
2
4
]
B.
-
g
.
S
u
n
a
n
d
H
.
-
y
.
T
a
n
g
,
“
A
n
a
l
y
si
s
o
n
t
h
e
n
o
i
se
so
u
r
c
e
s
i
n
d
a
t
a
-
a
c
q
u
i
si
t
i
o
n
sy
st
e
m,
”
2
0
1
1
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
El
e
c
t
r
i
c
I
n
f
o
r
mat
i
o
n
a
n
d
C
o
n
t
r
o
l
En
g
i
n
e
e
r
i
n
g
,
W
u
h
a
n
,
C
h
i
n
a
,
2
0
1
1
,
p
p
.
4
7
9
0
-
4
7
9
2
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
E
I
C
E.
2
0
1
1
.
5
7
7
7
2
6
4
.
[
2
5
]
H
.
W
e
n
h
a
i
,
“
D
e
si
g
n
o
f
t
h
e
N
o
i
se
T
e
st
i
n
g
S
y
st
e
m
B
a
se
d
o
n
L
a
b
V
I
E
W
,
”
2
0
0
9
F
o
u
r
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
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
s
a
n
d
C
o
n
v
e
r
g
e
n
c
e
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
y
,
S
e
o
u
l
,
K
o
r
e
a
(
S
o
u
t
h
)
,
2
0
0
9
,
p
p
.
9
5
-
9
8
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
C
I
T
.
2
0
0
9
.
2
8
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Re
y
m
a
r
k
-
J
o
h
n
A.
M
a
c
a
p
a
n
a
s
is
a
F
a
c
u
lt
y
M
e
m
b
e
r
a
n
d
He
a
d
o
f
th
e
Re
se
a
r
c
h
,
In
n
o
v
a
ti
o
n
,
a
n
d
Ex
ten
sio
n
S
e
c
ti
o
n
a
t
t
h
e
Un
iv
e
rsit
y
o
f
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
lo
g
y
o
f
S
o
u
t
h
e
rn
P
h
il
i
p
p
i
n
e
s
–
Vill
a
n
u
e
v
a
Ca
m
p
u
s.
He
e
a
rn
e
d
h
is
M
.
S
.
in
C
o
m
p
u
ter
A
p
p
li
c
a
ti
o
n
s
f
ro
m
M
in
d
a
n
a
o
S
tate
Un
iv
e
rsity
–
Ili
g
a
n
In
s
ti
tu
te
o
f
Tec
h
n
o
lo
g
y
.
His
r
e
se
a
rc
h
in
tere
sts
in
c
lu
d
e
in
tern
e
t
o
f
th
i
n
g
s
(Io
T
)
sy
ste
m
s
,
e
m
b
e
d
d
e
d
tec
h
n
o
l
o
g
ies
,
a
n
d
a
rti
f
icia
l
in
telli
g
e
n
c
e
f
o
r
e
n
v
iro
n
m
e
n
tal
m
o
n
it
o
ri
n
g
a
n
d
sm
a
rt
-
c
it
y
a
p
p
li
c
a
ti
o
n
s.
He
h
a
s
p
re
se
n
ted
a
n
d
c
h
a
ired
se
ss
io
n
s
a
t
NiDS
2
0
2
5
,
I
S
ICO
2
0
2
5
,
a
n
d
A
UA
A
P
-
P
P
N
2
0
2
5
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
re
y
m
a
r
k
jo
h
n
.
m
a
c
a
p
a
n
a
s@
u
stp
.
e
d
u
.
p
h
.
Ad
r
i
a
n
P.
G
a
li
d
o
is
a
d
isti
n
g
u
ish
e
d
e
d
u
c
a
to
r,
re
se
a
rc
h
e
r,
a
n
d
lea
d
e
r
w
it
h
a
c
a
re
e
r
sp
a
n
n
in
g
a
c
a
d
e
m
i
c
a
n
d
tec
h
in
d
u
stry
.
Cu
rre
n
t
ly
a
n
Ac
a
d
e
m
i
c
V
isit
o
r
a
t
t
h
e
L
e
e
Ku
a
n
Ye
w
S
c
h
o
o
l
o
f
P
u
b
li
c
P
o
l
icy
’s
NU
S
F
e
ll
o
w
s
P
ro
g
ra
m
,
h
e
a
lso
se
rv
e
s
a
s
a
P
r
o
f
e
ss
o
r
a
t
M
in
d
a
n
a
o
S
tate
Un
iv
e
rsi
ty
-
Ili
g
a
n
In
stit
u
te
o
f
T
e
c
h
n
o
lo
g
y
(M
S
U
-
IIT
),
w
h
e
re
h
e
tea
c
h
e
s
g
ra
d
u
a
te
a
n
d
u
n
d
e
rg
ra
d
u
a
te
c
o
u
r
se
s
in
c
o
rp
o
ra
te
re
sp
o
n
sib
i
li
ty
,
b
u
sin
e
ss
in
tell
ig
e
n
c
e
,
a
n
d
p
ro
jec
t
m
a
n
a
g
e
m
e
n
t.
A
s
a
c
ti
n
g
d
irec
to
r
o
f
th
e
Of
f
ic
e
o
f
In
stit
u
ti
o
n
a
l
P
lan
n
in
g
a
n
d
De
v
e
lo
p
m
e
n
t
S
e
rv
ice
s
,
h
e
o
v
e
rse
e
s
u
n
iv
e
rsit
y
d
e
v
e
lo
p
m
e
n
t
a
n
d
stra
teg
ic
p
lan
n
in
g
.
W
it
h
a
n
M
.
S
.
i
n
Da
ta
S
c
ien
c
e
f
ro
m
th
e
A
s
ian
In
stit
u
te
o
f
M
a
n
a
g
e
m
e
n
t,
he
h
a
s
h
e
ld
p
iv
o
tal
ro
les
su
c
h
a
s
Co
ll
e
g
e
G
r
a
d
u
a
te
P
ro
g
ra
m
Co
o
rd
in
a
t
o
r,
A
ss
istan
t
De
a
n
,
a
n
d
A
c
ti
n
g
Dire
c
to
r
o
f
M
o
n
i
to
ri
n
g
a
n
d
Ev
a
lu
a
ti
o
n
.
His
tec
h
in
d
u
stry
b
a
c
k
g
ro
u
n
d
i
n
c
lu
d
e
s
lea
d
e
rsh
ip
p
o
siti
o
n
s
a
t
F
P
T
s
o
f
t
w
a
re
a
n
d
T
ieto
G
lo
b
a
l
O
y
,
w
it
h
in
tern
a
ti
o
n
a
l
a
ss
ig
n
m
e
n
ts
in
P
o
lan
d
a
n
d
Ja
p
a
n
,
w
h
e
re
h
e
m
a
n
a
g
e
d
tea
m
s
in
so
f
twa
re
d
e
v
e
lo
p
m
e
n
t
a
n
d
tec
h
n
o
lo
g
y
tran
sf
e
r.
His
w
o
rk
re
f
lec
ts
a
d
e
e
p
c
o
m
m
it
m
e
n
t
to
a
d
v
a
n
c
in
g
in
stit
u
t
io
n
a
l
p
lan
n
in
g
,
a
c
a
d
e
m
ic
e
x
c
e
ll
e
n
c
e
,
a
n
d
d
a
ta
-
d
riv
e
n
d
e
v
e
lo
p
m
e
n
t.
He
c
a
n
b
e
c
o
n
tac
te
d
a
t
e
m
a
il
:
a
d
rian
.
g
a
li
d
o
@g
.
m
su
ii
t.
e
d
u
.
p
h
.
App
le
R
o
se
B
.
Alc
e
is
a
f
a
c
u
lt
y
m
e
m
b
e
r
a
t
M
S
U
-
IIT
,
w
h
e
r
e
sh
e
tea
c
h
e
s
in
th
e
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter
A
p
p
li
c
a
ti
o
n
s
w
it
h
in
t
h
e
Co
ll
e
g
e
o
f
Co
m
p
u
ter
S
tu
d
ies
.
S
h
e
h
o
ld
s
a
M
a
ste
r
o
f
S
c
ien
c
e
i
n
C
o
m
p
u
ter
A
p
p
li
c
a
ti
o
n
s
f
ro
m
M
S
U
-
IIT
,
c
o
m
p
lete
d
in
2
0
2
0
,
w
it
h
a
th
e
sis
f
o
c
u
se
d
o
n
d
e
sig
n
i
n
g
a
m
icro
c
o
n
tro
ll
e
r
-
b
a
se
d
w
a
ter
le
v
e
l
a
n
d
so
il
m
o
istu
re
m
o
n
it
o
ri
n
g
s
y
ste
m
f
o
r
rice
fa
r
m
in
g
.
He
r
re
s
e
a
rc
h
in
tere
sts sp
a
n
sm
a
rt
c
it
y
f
ra
m
e
w
o
rk
s,
Io
T
a
p
p
li
c
a
ti
o
n
s
in
a
g
ricu
lt
u
re
,
a
n
d
e
n
v
ir
o
n
m
e
n
tal
m
o
n
it
o
rin
g
sy
ste
m
s,
w
it
h
n
u
m
e
ro
u
s
i
n
tern
a
ti
o
n
a
l
p
u
b
li
c
a
ti
o
n
s
a
n
d
p
re
se
n
tatio
n
s,
in
c
lu
d
in
g
c
o
n
tri
b
u
ti
o
n
s
t
o
c
o
n
f
e
re
n
c
e
s
li
k
e
IS
ICO
a
n
d
ICEE
A
.
S
h
e
h
a
s
a
tt
e
n
d
e
d
v
a
rio
u
s
train
in
g
se
ss
io
n
s
o
n
c
y
b
e
rse
c
u
rit
y
,
A
I,
a
n
d
d
a
ta
p
riv
a
c
y
,
e
n
h
a
n
c
in
g
h
e
r
tec
h
n
ica
l
e
x
p
e
rti
se
a
n
d
p
e
d
a
g
o
g
ica
l
sk
il
ls.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
p
p
lero
se
.
a
lce
@g
.
m
su
ii
t.
e
d
u
.
p
h
.
Evaluation Warning : The document was created with Spire.PDF for Python.