Indonesi
an
Journa
l
of El
ect
ri
cal Engineer
ing
an
d
Comp
ut
er
Scie
nce
Vo
l.
1
3
,
No.
3
,
Ma
rch
201
9
, p
p.
1
1
3
0
~
1
1
3
5
IS
S
N: 25
02
-
4752, DO
I: 10
.11
591/ijeecs
.v1
3
.i
3
.pp
1
1
3
0
-
1
1
3
5
1130
Journ
al h
om
e
page
:
http:
//
ia
es
core.c
om/j
ourn
als/i
ndex.
ph
p/ij
eecs
Interlab
orato
ry d
ata fusi
on repos
itory sys
tem (In
DFuRS)
for
tocotri
enols
-
ba
sed
treatm
ent
No
r
ha
sli
nd
a Kam
aruddi
n
1
,
A
b
dul W
aha
b
2
1
Advanc
ed
An
aly
t
ic
s
Engi
ne
eri
n
g
Center
,
Facult
y
of
Com
pute
r
a
nd
Mathe
m
atic
al Sci
en
ce
s,
Univer
siti
Te
kno
logi
MA
RA,
Ma
lay
s
ia
2
Kulliy
ah
of
Inf
orm
at
ion
and
Co
m
m
unic
at
ion
T
e
chnol
og
y
,
Int
ern
at
ion
al
Isl
amic University
Ma
lay
sia
,
Ma
lay
si
a
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
A
ug
25
, 201
8
Re
vised
N
ov
6
, 2018
Accepte
d
Nov
14
, 201
8
Toc
otr
ie
nols
a
n
d
toc
opher
o
ls
a
re
par
t
of
th
e
vit
amin
E
famil
y
and
hav
e
show
n
to
produ
ce
lot
s
of
benef
it
s
espe
ci
a
lly
in
health
suppl
ement
produ
ct.
Both
toc
o
trienol
s
and
to
cophe
ro
ls
exi
st
in
an
e
dibl
e
o
il
but
v
a
ri
es
in
their
rat
io
.
It
is
a
lso
observe
d
that
per
ce
n
ta
g
e
of
t
ocophe
rols
is
h
ighe
r
th
an
toc
otrienols
in
m
ost
of
our
die
t
.
Recent
rese
arc
h
es
have
found
that
toc
otrienols
see
m
s
to
have
m
ore
bene
f
it
to
h
ealth
espe
ci
a
lly
fo
r
del
a
y
i
ng
neur
o
-
dege
n
erati
on
and
thi
s
h
as
le
d
rese
arc
h
ers
to
inve
stiga
t
e
t
ocot
ri
enol
s
ric
h
fr
ac
t
ion
(T
RF
)
from
pal
m
ker
nel
o
il.
To
d
a
te
,
the
toc
o
tri
en
ols
ext
ra
ct
i
on
proc
ess
is
stil
l
work
in
progre
ss
.
Henc
e,
it
is
i
m
per
at
ive
tha
t
a
ll
informati
on
and
result
s
from
the
var
ious
la
b
ora
tories
expe
ri
m
e
nts
to
be
m
a
de
ava
i
la
bl
e
thus
dat
a
anal
ysis
ca
n
be
opti
m
iz
ed
for
optim
al
toc
otri
nols
produc
ti
on.
Data
a
cqui
sit
io
n
from
int
er
-
l
abor
at
or
y
experim
ent
s
are
v
al
uab
le
for
col
l
abor
ative
res
ea
rch
es.
Eff
orts
from
m
ult
ipl
e
source
s
nee
d
to
be
combined
to
m
ake
i
t
a
cc
essible
for
d
at
a
in
te
gra
ti
on.
The
source
s
of
fused
dat
a
ca
n
b
e
emplo
y
ed
as
sec
ondar
y
bac
k
u
p
once
the
data
is
m
igra
te
d
to
a
ce
ntral
rep
ositor
y
.
Tr
aditiona
l
l
y
d
at
a
has
bee
n
residi
ng
i
n
silos
a
cro
ss
orga
nizati
on
.
Such
sce
nar
io
posed
as
a
ma
jor
proble
m
espe
ci
a
lly
wh
en
the
re
ar
e
insuffic
i
ent
hu
m
an
and
computat
ion
al
resour
ce
s
to
m
ana
ge
such
dat
a.
In
addi
tion,
long
it
udinal
da
ta
co
llections
al
wa
y
s
suffer
from
m
isma
nage
m
en
t
of
the
da
ta
wh
e
re
th
e
d
at
a
ar
e
not
l
abe
l
ed
prop
erly
using
m
isma
tc
h
ed
d
ata
form
at
ti
ng
resul
t
ing
to
poor
d
a
ta
re
ada
bi
li
t
y
.
The
ref
or
e,
a
re
positor
y
to
fac
i
li
t
at
e
d
at
a
fu
sion
using
a
s
y
stematic
cl
oud
-
b
ase
d
s
y
stem
is
proposed
t
o
ensure
th
e
da
ta
are
acce
ss
ibl
e
with
m
ai
nt
ai
n
ed
d
at
a
uniformit
y
a
nd
form
at
and
y
e
t
th
e
sec
u
rity
of
the
data
i
s
ensure
d
as
we
l
l
as
cost
eff
ec
t
iv
e
and
fau
l
t
tol
er
ant
.
It
is
e
nvisage
d
a
be
tter
soluti
on
ca
n
be
id
ent
if
ie
d
t
o
m
ini
m
iz
e
rep
etiti
on
o
f
exp
eri
m
ent
s
and
lo
oking
towar
ds
a
t
adva
n
ce
m
ent
o
f
ext
r
ac
t
ion
proc
esses.
Ke
yw
or
ds:
Bi
g
d
at
a
a
naly
ti
cs
Data
f
us
io
n
Re
po
sit
ory
Stru
ct
ur
e
d
a
nd
s
em
i
-
structu
red
d
at
a
Copyright
©
201
9
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed.
Corres
pond
in
g
Aut
h
or
:
Norhasl
ind
a
Ka
m
aru
ddin
,
Adva
nced A
na
ly
ti
cs En
gin
ee
r
ing
Ce
nter
,
Faculty
of Com
pu
te
r
an
d
Ma
them
a
ti
cal
Scie
nces,
Un
i
ver
sit
i Te
knol
og
i M
ARA
,
Sh
a
h Alam
, S
el
angor, Mal
ay
sia
.
Em
a
il
:
no
r
haslind
a
@tm
sk
.u
it
m
.ed
u.
m
y
1.
INTROD
U
CTION
Toc
otrien
ols
a
nd
t
ocop
herols
can
norm
ally
be
e
xtracted
from
edible
oils,
w
hich
a
re
their
m
ajo
r
natu
ral
dieta
ry
source
s.
Toc
ot
rieno
ls
an
d
t
oc
ophe
ro
ls
can
al
so
be
e
xtract
ed
from
plant
foo
ds
with
l
ow
li
pi
d
bu
t
with
with
ver
y
lo
w
quan
ti
ti
es.
Other
s
ources
of
e
dib
le
oil
with
reas
onable
am
ount
of
t
oco
t
rien
ols
an
d
toco
ph
e
r
ols
ar
e
from
seeds
and
oth
e
r
plant
foo
d
proce
ssin
g
by
-
pro
duct
s.
Toc
otrien
ols
s
ee
m
s
to
hav
e
s
pecial
neur
opro
te
ct
iv
e,
anti
-
cance
r
and
c
ho
le
ste
r
ol
lowe
rin
g
pro
pe
rtie
s
that
are
no
t
are
no
t
f
ound
in
toco
pher
ols
[
1
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
In
te
rla
bor
ato
r
y data f
us
io
n
r
eposi
tory syste
m
(
I
nD
F
uR
S
)
for t
oco
tri
en
ols
...
(
Nor
hasli
nd
a
K
amar
uddin
)
1131
In
ad
diti
on,
to
cotrien
ols
al
s
o
ha
ve
oth
e
r
functi
ons
that
he
lps
m
ai
ntaining
healt
h
a
nd
tr
eat
ing
disease
wh
i
c
h
toco
ph
e
r
ols
does
no
t
ex
hib
it
,
especial
ly
in
pr
e
ve
nting
bra
in
cel
l
deg
ene
rati
on
th
rou
gh
reg
ulati
ng
spe
ci
fic
m
ediat
or
s
of
c
el
l
death.
T
he
cho
le
ste
r
ol
-
l
oweri
ng
pr
opert
ie
s
and
s
uppre
sses
gro
wth
of
hu
m
an
breast
cancer
cel
ls i
n
toc
otri
eno
ls
are n
ot foun
d
in
toc
ophe
renols
[
2
]
.
Althou
gh
pal
m
ker
nal
oil
con
sist
s
of
m
ixtur
e
f
r
om
tocotrieno
ls
a
nd
to
cophe
ro
ls,
t
oc
otrien
ol
-
rich
fr
act
io
n
(TRF
)
can
extract
up
to
an
avera
ge
of
70
%
to
cotrien
ols.
I
n
bo
t
h
tocotrie
nols
and
toc
op
herols,
4
isom
ers
are
ob
s
er
ved,
nam
el
y;
al
ph
a,
bet
a,
gam
m
a,
and
delta
[
3
]
.
Al
pha
-
t
ocop
herols
has
bee
n
the
f
ocus
of
researc
h
in th
e early
d
ay
s [
4
]
. R
ecent researc
her
s
fou
nd
t
hat toco
trie
no
ls
diff
e
r
from
toco
pher
ols b
y
hav
i
ng
a
n
un
s
at
ur
at
e
d
si
de
chai
n
[
5
]
that
res
ults
in
s
ign
ific
a
ntly
dif
fer
e
nt
bi
ologica
l
act
ivit
ie
s.
In
the
e
nhance
d
TRF
,
it
is
env
isa
ge
d
that
ad
justi
ng
t
he
e
xtracti
on pro
ces
s p
aram
eter
s
ca
n
help
to
i
m
pr
ove
the
rat
io
of
t
oco
t
rien
ols
to
toco
ph
e
r
o
ls
co
ntent.
In
fact,
an
im
pr
ov
em
ent
of
toc
otrien
ols
co
ntent
bet
ween
10%
t
o
20%
has
been
r
eporte
d
after
the
e
xtr
act
ion
process
par
am
et
er
adjustm
ent,
thus
i
m
pr
ove
th
e
eff
ect
ive
nes
s
of
t
oc
otrien
ols
i
n
su
pple
m
ent.
In
so
m
e
cases,
enh
a
nce
d
f
orm
ulati
on
a
re
use
d
t
o
furthe
r
i
m
pr
ov
e
d
the
e
ff
ect
ive
ness
by
us
in
g
m
edium
-
chain
trigly
cerides
(
MC
T)
as
the
c
arr
ie
r
i
ns
te
ad
of
co
nventi
on
al
long
-
c
hain
trig
ly
cerides.
MC
T
is
a
cl
ass
of
li
pid
s
com
po
sed
of
gl
yc
erides
with
fatt
y
aci
ds
consi
st
of
C6
to
C10
in
le
ngth
a
nd
are
norm
al
ly
fo
un
d
i
n
c
ocon
ut
an
d
palm
kernel
oi
l.
MC
T
ha
s
be
en
us
e
d
for
t
he
dieta
ry
treat
m
ent
of
m
al
absorp
ti
on
sy
ndr
om
e
and
weig
ht
co
ntr
ol
[6
]
as
well
as
abs
orptio
n
en
ha
ncers
of
a
num
ber
s
of
dif
fer
e
nt
dru
gs
in
li
pi
d
-
base
d
m
ic
ro
em
ulsion
s.
On
e
of
the
li
ve
r
disease
tha
t
m
ay
sp
read
to
be
ve
ry
sev
ere
li
ver
disea
ses
su
ch
as
li
ver
fi
brosis,
ci
rr
hosis
an
d
cancer
is
the
non
-
al
co
ho
li
c
fatt
y
li
ver
disease
(NAFL
D
)
[7
]
-
[
10]
.
Stu
dies
hav
e
s
hown
th
e
po
te
ntial
of
he
pato
-
protect
iv
e
eff
ect
of
t
oc
otrien
ols
in
patie
nts
with
NAFLD
seem
s
to
prov
i
de
po
sit
ive
i
m
pr
ovem
ent.
In
c
rease
d
c
omplet
e
rem
issi
on
of
fatt
y
li
ver
can
be
achie
ve
d
with
var
i
ous
m
ixed
tocot
r
ie
no
ls
(of
at
le
ast
20
0
m
g
twic
e
pe
r
day)
f
or
a
ye
ar
[11].
It
is
sti
ll
un
cl
ear
how
hep
at
o
-
pro
te
ct
ive
eff
ect
s
and
it
s
bio
lo
gical
m
ec
han
ism
s
of
toc
otrien
ols
on
N
AF
L
D
w
orks
.
It
is
assum
ed
t
o
be
la
r
gely
co
ntribute
d
due
to
th
e
anti
-
oxidati
ve
,
anti
-
inflam
m
ato
ry
a
nd
c
ho
le
s
te
ro
l
-
lo
we
rin
g
pro
per
ti
es
of
t
oco
t
rien
ols
[
12
,
13]
.
T
he
re
dox
a
nd
inflam
m
at
ion
syst
e
m
s
and
l
ipid
m
et
abo
li
sm
are
co
m
plex
path
ways
in
our
body
a
nd
el
ucidati
ng
the
m
echan
ism
of
act
ion
of
the
t
oc
otrien
ols
in
protect
ing
a
gains
t
li
ver
sti
ff
ne
ss
m
ay
pr
ov
i
de
be
tt
er
underst
an
ding
in
the
path
oge
nesis
of
t
he
disease
an
d
t
he
m
echan
ism
of
act
ion
of
t
oc
otrien
ols
in
prot
ect
ing
the
pr
ogressio
n
of N
AF
L
D.
Fr
om
the
exam
ple,
it
is
im
per
at
ive
that
a
c
om
plex
syst
e
m
i
s
re
qu
ire
d
t
o
m
anag
e
an
d
a
n
a
naly
se
huge
a
m
ou
nt
of
data
and
in
f
or
m
ation
f
r
om
the
body
to
a
dm
ini
ste
r
su
c
h
com
plex
s
upplem
e
nts
of
tocot
rieno
ls
i
n
order
f
or
it
to
be
ef
fecti
ve
a
nd
f
unct
ion
the
w
ay
it
is
suppo
sed
to
be
.
I
n
a
ddit
ion
,
ther
e
is
a
nee
d
to
unde
rstan
d
how
t
o
im
pr
ove
the
process
par
am
et
ers
so
that
eff
ect
i
ve
ways
of
e
xtrac
ti
ng
toc
otrie
nols
from
var
io
us
f
oo
d
pro
du
ct
s ca
n b
e achiev
ed
.
Ther
e
is
a
di
re n
eed
t
o
ha
ve
a com
plex
syst
em
to
m
at
ch
the
diff
e
rr
i
ng
n
ee
ds
of
dietry
s
upplem
ent
fo
r
ind
ivi
du
al
s
suc
h
that
resea
rch
e
rs
ca
n
s
ha
re
an
d
c
omplem
ent
data
from
the
oth
er
resea
rch
e
r
s
an
d
colla
borato
rs.
The
com
plexity
,
var
ia
bili
ty
of
data
an
d
th
e
locat
ion
of
the
data
is
scat
te
red
am
on
g
m
any
orga
nizat
io
nal
app
li
cat
ions
and
syst
em
s
m
akes
it
challen
gi
ng
t
o
eve
n
acce
ss
these
data.
I
nter
-
la
borato
r
y
colla
borati
on
of
te
n
has
di
ff
i
culty
in
com
m
un
ic
at
ing
be
tween
colla
bor
at
or
s
due
to
l
ack
of
perso
nnel
and
com
pu
ta
ti
on
al
resou
rces
re
qu
i
red
for
m
anag
ing
a
pro
per
data
base
of
the
e
xperim
ental
data.
The
refor
e
,
da
ta
is
of
te
n
sto
re
d
in
exter
nal
ha
r
d
dr
i
ves
by
grad
uate
stu
de
nts
work
i
ng
on
t
he
ir
thesis
a
nd
of
te
n
the
data
is
lost
wh
e
n
t
hese s
t
udents
grad
uate
d.
Ty
pical
ly
,
ther
e
is
no
sta
nd
a
r
d
data
sto
ra
ge
conve
ntion
tha
t
is
a
ccepte
d
by
the
resea
rc
he
rs
wh
e
n
t
he
data
are
bein
g
acq
uire
d
a
nd
store
d.
To
co
m
pl
ic
at
e
m
atte
rs,
e
ve
n
form
a
t
of
the
data
i
s
dif
fer
e
nt
fro
m
on
e
exp
e
rim
ent
to
ano
t
her.
For
instance,
the
dat
e
par
am
et
ers
c
an
be
store
d
usi
ng
ei
ther
D
D
-
MM
-
yy
yy
or
MM
-
DD
-
yy
yy
.
Th
us,
data
with
th
e
sam
e
info
rm
at
ion
nee
d
to
be
st
or
e
d
in
diff
e
ren
t
c
om
pu
te
r
m
e
m
or
y
locat
ion
.
As
s
uc
h
syst
em
wil
l
no
t
be
able
to
rec
ognize
the
date
form
at
since
the
MM
c
ou
l
d
be
m
or
e
tha
n
12
or
duplica
ti
on of
data. T
hus it
is
i
m
po
rtant t
hat
al
l data m
us
t be pro
per
ly
m
anag
ed
and m
ai
ntained
.
Trad
it
io
nally
data
are
colle
ct
ed
us
i
ng
a
sin
gl
e
database
that
are
store
d
phy
sic
al
ly
in
an
organ
iz
at
io
n.
Wh
il
e
this
sit
ua
ti
on
seem
s
id
eal
becau
se
th
e
data
can
be
updated
a
nd
e
asi
ly
acce
sible
,
su
c
h
sit
uatio
n
m
a
y
po
s
e
a
pro
ble
m
i
f
the
data
base
is
fa
ulty
,
co
rru
pted
or
ex
per
ie
ncin
g
the
fail
ur
e
of
c
om
pu
te
r
sy
stem.
A
distri
bu
te
d
database
m
ay
be
em
plo
ye
d
to
over
com
e
su
ch
chall
en
ge
.
Howe
ver,
the
data
m
us
t
be
reg
ula
rly
refreshe
d
a
nd
s
ynch
ronized
t
o
keep
it
up
-
to
-
date
w
hen
it
is
in
us
e
d.
He
nc
e,
a
reposit
ory
that
is
secur
e,
rob
us
t
and fa
ult t
olera
nt is a m
us
t t
o ens
ur
e t
he up
-
to
-
date
data is a
ccessi
ble for
al
l coll
aborato
rs and resea
rc
hers.
Th
us
,
we
pro
pose
d
an
I
nter
-
la
borato
ry
Data
Fu
sio
n
Re
posi
tory
Syst
e
m
(I
nDFu
RS
)
ha
vi
ng
sta
te
-
of
-
the
-
art
cl
oud
-
base
d
data
re
po
sit
or
y
f
or
da
ta
fu
si
on
fro
m
var
io
us
la
borat
or
y
data
acqu
isi
ti
on
accr
os
s
t
he
country. D
i
ff
e
r
ent d
at
a ty
pes
of
d
at
a yi
el
ded fr
om
v
arious laborat
ori
es can
b
e
m
anag
ed
a
m
d
no
rm
alized u
sing
sta
nd
a
rd
data
s
tora
ge
co
n
ver
s
ion
.
The
syst
em
pr
op
os
ed
shou
l
d
be
af
fordable,
c
om
pu
ta
ti
on
al
ly
acce
pta
ble
a
nd
pr
act
ic
al
w
it
h
ease o
f
m
ai
ntain
ance
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
1
3
0
–
1
1
3
5
1132
2.
LIT
ERATUR
E REVIE
W
Bi
g
data
anal
yt
ic
s
and
com
pu
ti
ng
is
a
n
e
m
erg
in
g
data
sci
ence
pa
ra
dig
m
of
m
ult
i
-
dim
ension
al
inf
or
m
at
ion
m
ining
f
or
sci
e
nt
ific
disco
ver
y
an
d
busi
ness
analy
ti
cs
[14].
The
data
c
ollec
te
d/p
r
oduce
d
from
sci
entifi
c
exp
l
or
at
io
ns
of
te
n
require
to
ols
to
facil
it
at
e
eff
ic
ie
nt
data
m
anag
em
ent,
analy
sis,
valid
at
ion
,
visu
al
iz
at
ion
a
nd
dissem
inatio
n,
w
hile
pre
serv
i
ng
t
he
in
trinsic
val
ue
of
t
he
data
[
15
]
.
Scie
ntist
s
an
d
researc
hers pro
du
ce
huge
am
ou
nts
of
data p
e
r
-
day v
ia
exper
i
m
ents, h
owev
er,
ext
racti
ng
use
fu
l
knowle
dg
e for
decisi
on
-
m
aking
pu
rposes
from
these
m
ass
ive,
la
r
ge
-
scal
e
data
reposit
ori
es
is
al
m
os
t
i
m
po
ssible
for
act
ual
database
m
ana
gem
ent
syst
e
m
-
ins
pire
d
analy
sis
too
ls
[16].
Ther
e
f
or
e,
an
appr
oach
t
o
ha
nd
le
t
hese
m
as
sive
data is
need
e
d.
The
a
dvancem
ent
of
te
c
hnol
og
y
i
n
the
are
as
of
netw
orking
an
d
cl
oud
com
pu
ti
ng
off
er
en
d
us
e
rs
with
seam
le
ss
m
echan
ism
s
for
creati
ng,
sto
r
ing
,
acce
ssin
g
and
m
anag
ing
their
m
assive
databases
on
r
e
m
ot
e
(d
at
a)
se
r
ver
s
.
It
is
al
so
know
n
as
Data
base
as
a
Ser
vice
(
DaaS
)
[
17
]
.
D
ue
to
the
naïve
featur
es
of
bi
g
data,
DaaS
is
the
m
os
t
ap
propriat
e
com
pu
ta
ti
on
al
data
f
ram
ewo
r
k
to
im
ple
m
ent
big
data
re
pos
it
or
ie
s
[
18]
.
Fi
gure
1
il
lustrate
s a sim
pl
ifie
d
enter
pri
se cloud ar
c
hi
te
ct
ur
e for
a bi
g
data an
d
ana
ly
ti
cs env
iro
nm
ent. Th
e arc
hi
te
ct
ur
e
has
th
ree
net
work
z
ones:
public
net
work,
prov
i
der
cl
ou
d,
a
nd
e
nter
pri
se
networ
k
[
19
]
.
No
ti
ce
f
r
om
the
diag
ram
of
Figure
1,
it
a
lso
al
lows
us
e
r
f
r
om
the
public
to
acce
ss
so
m
e
data
wh
ic
h
is
avail
able
for
public
acce
ss.
Figure
1
.
Sim
plifie
d
ente
rpris
e cloud a
rc
hitec
ture
Desk
t
op
as
a
Ser
vice
is
a
d
eskto
p
virt
ualiz
at
ion
ser
vice
that
is
ho
ste
d
on
the
cl
ou
d,
so
us
e
rs
c
a
n
acce
ss
their
vir
tual
desk
t
op
s
a
nd
a
pp
li
cat
io
ns
wh
e
rev
e
r
they
go
, u
sin
g
w
hic
hev
e
r
de
vice
th
ey
need
.
Be
cau
se
a
virtu
al
des
ktop
is
sto
red
on
a
rem
ote
serv
e
r,
it
is
separ
at
e
d
from
the
physi
cal
de
vice
that
is
us
e
d
to
acc
ess
it
.
W
it
h
Des
ktop
as
a
Se
r
vice,
da
ta
gets
sa
ve
d
autom
at
ic
ally
fr
om
the
virtu
al
des
ktop
beca
use
it
is
synce
d
with
the
Cl
ou
d.
Cu
stom
ers
gen
er
al
ly
m
anag
e
their
ap
plica
ti
on
s
an
d
des
ktop
i
m
ages,
wh
il
e
the
serv
ic
e
pro
vid
e
r
handles
al
l
the b
ack
-
e
nd
i
nfra
structu
re
a
nd m
ai
ntenan
ce.
This
is
pa
rtic
ul
arly
i
m
po
rtant so
that researc
her
s
a
nd
colla
borato
rs
can
acce
ss
dat
a
anyw
he
re
th
ey
wan
t
us
i
ng
any
dev
ic
es
of
t
heir
c
hoic
e.
I
n
t
he
la
bo
ratory
env
i
ronm
ent
data
can
be
coll
ect
ed
an
d
store
d
into
the
cl
oud,
w
hile
in
the p
la
nt
m
anu
fact
ur
i
ng
the
t
oco
t
rien
ols
from
the RTF
can
know the
ki
nd
of toc
otrie
no
ls
n
ee
de
d
f
or the
p
at
ie
nt
supp
le
m
ent.
Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
In
te
rla
bor
ato
r
y data f
us
io
n
r
eposi
tory syste
m
(
I
nD
F
uR
S
)
for t
oco
tri
en
ols
...
(
Nor
hasli
nd
a
K
amar
uddin
)
1133
Hen
ce
,
the
im
ple
m
entat
ion
of
the
re
posit
or
y
us
in
g
cl
ou
d
-
ba
sed
syst
em
can
m
ini
m
iz
e
t
he
i
ssu
es
s
uc
h
as
data
is
scat
te
red
am
on
g
m
any
organ
iz
a
ti
on
a
pp
li
cat
io
ns
a
nd
syst
em
s,
data
not
pr
op
e
rly
m
anag
ed
a
nd
m
ai
ntained
an
d
data
not
up
-
to
-
date
for
anal
ysi
s.
This
is
cru
ci
al
in
ensuring
the
la
te
st
inform
ation
is
av
ai
la
ble
on
t
he
cl
oud
s
o
that
al
l
pa
rtie
s
will
hav
e
t
he
la
te
st
infor
m
at
ion
and
a
r
e
able
to
pe
rfor
m
ta
sk
acco
rd
i
ng
ly
.
In
a
ddit
ion
,
se
cur
it
y
of
t
he
da
ta
is
al
so
gua
ren
te
e
d
since
pr
i
vate
cl
oud
will
ensure
co
rr
ect
use
r
will
get
the
correct
in
form
at
ion
a
nd d
at
a
.
3.
RESEA
R
CH MET
HO
DOL
OGY
3.1.
Data
Ac
quisi
ti
on
and
Analys
is
This phase is c
arr
ie
d o
ut to
id
entify
and understan
d
the
go
a
ls and
the
nee
ds of
us
er
s.
Bot
h
qual
it
at
ive
and
qua
ntit
at
i
ve
re
searc
h
m
ay
need
to
be
car
ried
out
to
ha
ve
a
be
tt
er
unde
rsta
nd
i
ng
of
the
var
i
ous
requirem
ents
and
nee
ds
f
or
s
tora
ge
a
nd
a
na
ly
sing
the
data
an
d
the
dif
fere
nt
ty
pes
of
da
ta
to
be
sto
re
d
a
nd
analy
se.
T
his
ph
a
se
in
volves
resea
rch
an
d
analy
sis
of
e
xisti
ng
data
incl
ud
i
ng
sur
vey
a
nd
inter
view
with
the
colla
borato
rs
and
resea
rch
e
r
s.
This
ph
a
se
can
de
finite
ly
help
in
def
i
ning
the
product
visio
n,
a
sh
are
d
unde
rstan
ding
of the e
nd
products a
nd servic
es.
A
ta
ble
will
be
de
velo
ped
li
sti
ng
a
nd
c
ompari
ng
dif
fer
e
nt
ta
rg
et
groups
,
their
nee
ds
a
nd
va
rio
us
featur
e
s
incl
uding
t
he
data
ty
pes
t
o
be
sto
re
d
a
nd
val
ue
use
d.
I
n
ad
diti
on
,
visi
on
boar
d
can
ta
ke
the
f
orm
of
po
st
-
it
s
stuck
on
a
wall
bu
t
as
we
are
base
d
in
dif
fer
e
nt
faci
li
ti
es,
we
will
hav
e
t
o
us
e
a
di
gital
bo
ar
d
suc
h
as
Trell
o
in
this
ph
a
se
to
anal
yz
e
var
io
us
f
orm
s
of
need
s
and
diff
e
re
nt
us
ers
.
Com
m
o
n
chec
klist
will
be
gen
e
rat
ed
t
o
e
ns
ure
al
l
pa
rtie
s
involed
has
the
sam
e
the
check
li
st
an
d
will
be
us
e
d
t
o
ide
ntify
nee
ds
of
al
l
par
ti
es in
term
s of
data sto
rage an
d
a
naly
ti
cs.
3.2.
Design
Con
c
rete
un
de
rstan
ding
of
th
e
us
er
s’
requir
e
m
ents
hav
e
t
o
be
determ
ined
and
ag
reed
wi
th
al
l
par
ti
es
pr
i
or
to
s
ketc
hin
g
t
he
wir
ef
ra
m
es. I
te
rati
ng
qu
ic
kly from
t
he
us
e
rs
’
fee
dback,
to
reac
h
a
desig
n
that
work
s ca
n
be
carrie
d
out
by
sk
et
chi
ng
th
e
wirefram
es.
On
ce
c
onsens
us
on
the b
asi
c
desig
n
has
bee
n
ag
reed,
th
e
w
ork
on
high
-
fideli
ty
ver
sio
ns
of
al
l
the
dif
fer
e
nt
co
ntent
ty
pes
wi
ll
be
carried
out.
This
sta
ge
will
undergo
a
fe
w
it
erati
on
s
as
w
el
l,
it
will
be
i
ncor
porati
ng
ot
her
fee
db
a
cks
to
ensure
ther
e
are
no
blind
sp
ots.
Si
nce
this
a
qu
ic
k
tu
rn
a
r
ound
pro
j
ect
(
Q
TAP)
s
of
twa
re
avail
abili
ty
beco
m
es
crit
ic
a
l
and
im
po
rta
nt
rather
t
hen
de
sign
from
gr
ound
z
ero.
The
best
c
ho
ic
e
will
be
to
us
e
open
sou
rce
avail
able
s
of
t
war
e
that
w
orks
with
pu
blic
cl
oud
al
tho
ug
h pr
i
vate cl
oud wil
l be
ideal b
ut c
os
tl
y.
At
this
sta
ge
it
is
aso
i
m
po
rtant
to
co
ns
ide
r
data
secu
rity
a
nd
inte
gr
it
y
as
this
will
def
ine
d
then
ty
pe
of
a
vaila
ble
s
of
t
war
e
to
be
inco
rpor
at
e
d
with
res
pect
t
o
co
st
an
d
av
ai
la
bili
ty
.
Perh
aps
a
m
or
e
strin
gent
secur
it
y
syst
e
m
with
loggin
g
acce
ss
th
rou
gh
cl
oud
is
in
evita
ble
a
n
d
c
an
help
bri
ng
dow
n
the
c
os
t
an
d
ye
t
eff
ect
ive
eno
ugh f
or d
at
a
sec
ur
it
y an
d
i
nteg
rity
.
3.3.
Dev
el
op
me
nt
In
this
w
ork,
t
he
a
ppr
oach
of
data
reserv
oir
reposit
ory
by
[
20
]
will
be
ad
op
te
d.
It
is
im
per
at
ive
tha
t
wh
e
ne
ver
a
ny
researc
he
rs
update
d,
or
any
new
data
is
a
vaila
ble
the
e
ntire
com
m
un
it
y
need
to
be
awar
e
.
This app
ro
ac
h wil
l
m
ake su
re
that al
l par
ti
es w
il
l be m
ade aw
are
of
a
vaila
il
it
y of
n
ew or update
d data t
hro
ug
h
the use
of
cata
l
og and a
dverti
s
e m
od
ule.
The
act
ivit
ie
s i
den
ti
fie
d
in
Fi
gure
2
a
re
desc
ribe
d
as
f
ollows:
Adve
rtise
:
Whenev
e
r
there
is
a
new
source
of
data
to
ad
d
to
the
data
r
eservoir
or
an
y
up
dates
of
current a
vaila
bl
e d
at
a, it i
s ad
ver
ti
sed
i
n
the
data rese
rvoir
’
s cata
log
. T
his
is t
o
ens
ur
e t
ha
t al
l par
ti
es are
m
ade
awar
e
of a
vaila
bili
ty
o
f ne
w
dat
a.
Ca
ta
log
:
The
cat
al
og
de
scribe
d
the
dat
a
in
the
da
ta
re
servoir
i
nd
ic
at
ing
preci
se
arra
ng
em
ent
of
ho
w
data
is
m
anaged
a
nd
govern
ed.
I
n
this
cas
e
al
l
par
ti
es
i
nvol
ved
ca
n
the
n
locat
e
an
d
m
anag
e
t
he
da
ta
they
need.
Th
us
ha
vi
ng
data
cat
al
og
hel
p
orga
ni
z
ed
cl
assifi
ed
da
ta
into
var
i
ous
ways
m
aking
it
easy
fo
r
al
l
par
ti
es
to f
i
nd what t
he
y req
uire.
Pr
ovisi
on
:
To
ens
ur
e
al
l
cha
ng
e
s
m
ade
to
the
or
i
gin
al
source
of
data
are
sync
hron
iz
e
d
with
t
he
cop
ie
s
in
t
he
da
ta
reserv
oir,
pro
visio
n
is
i
nc
orp
or
at
ed
int
o
the
data
rese
rvoir.
Th
us,
fl
ow
of
data
into
th
e
data
reserv
oir
ca
n b
e pro
per
ly
regu
la
te
d.
Disco
ver
:
T
he
disco
v
e
ry
will
ensure
th
at
locat
ion
of
data
can
be
m
ade
know
n
th
rou
gh
the
dat
a
cat
al
og
. T
he
who
le
i
dea
of cat
al
og
in
g
is
sm
ilar
to
t
hat
of
t
he
li
br
ary cat
al
oging
.
Ex
plo
re:
The
e
xp
l
or
at
io
n
of
da
ta
is
then
car
r
ie
d
out
by
ver
i
fyi
ng
that
the
data
va
lues
a
re
co
rr
ect
a
nd
the d
at
a ty
pe
al
so
m
at
ched
.
Access:
On
c
e
exp
l
or
e
d
a
nd
ve
rified
data
ca
n
now
be
acce
ssed
directl
y
or
c
op
ie
d
int
o
a
san
dbox
f
or
us
e
by a
n
a
naly
sis t
oo
l.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2502
-
4752
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci,
Vo
l.
1
3
, N
o.
3
,
Ma
rc
h
201
9
:
1
1
3
0
–
1
1
3
5
1134
Figure
2
.
Data
reserv
oir rep
osi
tory appr
oac
h
3.4.
Te
sting
Tech
no
l
og
ic
al
advancem
ent
and
t
he
fast
-
pa
ce
of
ch
urnin
g
out
new
sof
tware
has
m
ade
it
alm
os
t
i
m
po
ssible
t
o
t
est
a
softwa
re
pro
du
ct
rig
oro
us
ly
to
e
nsure
qu
al
it
y
of
the
s
of
t
war
e
pro
duc
e.
Di
giti
sat
ion
of
the
industries
a
nd
the
us
e
of
I
nte
rn
et
of
T
hings
(IoT),
has
m
ad
e
it
eve
n
w
or
st
that
new
s
of
t
war
e
an
d
pro
duct
are
pro
du
ce
d
al
m
os
t
insta
ntly
.
Nu
m
erous
te
sti
ng
a
uto
m
at
ion
s
of
t
war
e
a
r
e
al
so
a
vaila
bl
e
bu
t
woul
d
require
par
am
et
er
tun
i
ng
to
opti
m
iz
e
it
s
us
a
ge.
Nonetheless
f
un
ct
io
nalit
y
and
us
er
acce
pt
ance
te
sti
ng
m
us
t
be
cond
ucted
to
m
easur
e
usa
bil
it
y
and
how
w
el
l
the
researc
her
s
util
iz
ed
the
pro
pose
d
s
yst
e
m
.
Thu
s
a
con
ci
se
and
preci
se
de
finiti
on
of
the
requirem
ent
m
us
t
be
well
est
ablishe
d
to
e
nsure
t
he
us
er
a
ccepta
nce
te
st
m
eet
wh
at
eve
r
ha
ve
bee
n
s
et
up
ea
rlie
r
as
th
e
syst
e
m
requirem
ents
an
d
t
his
is
c
r
it
ic
al
to
the
s
uc
cess
of
t
he
pro
du
ct
and ser
vices.
4.
CONCL
US
I
O
N AND
SIG
N
IFIC
AN
T
OF T
HE RESE
R
ACH
The
com
plexity
of
adm
inistering
any
su
pple
m
ent
eff
ectively
has
al
ways
been
a
big
quest
io
n.
The
huim
an
body
is
a
c
om
plex
pla
nt
a
nd
cannot
be
ea
sil
y
gen
e
rali
zed
as
eac
h
of
us
react
dif
fer
e
nt
ly
to
do
s
age
of
dru
gs.
I
n
this
case
we
pro
pose
d
the
use
of
bi
g
da
ta
analy
ti
cs
to
colle
ct
,
acq
uir
e,
store
a
nd
an
al
yz
e
data
in
t
he
cl
oud
syst
em
fo
r
ease
on
m
ai
n
ta
inance
a
nd
m
anag
in
g
th
e
data
co
m
plexity
.
A
pr
e
de
fine
d
a
nd
agr
ee
d
data
str
uctu
re
shou
l
d
pro
vid
e
an
eas
ie
r
env
ir
onm
e
nt
for
analy
zi
ng
data
with
st
and
a
r
ds
open
so
urce
app
li
cat
io
ns
.
T
he
us
e
of
Des
kt
op
as
a
se
rv
ic
e
an
d
D
at
a
as
a
ser
vice
can
al
low
the
syst
em
to
be
af
ford
a
bl
e
an
d
avail
able
on
t
im
e
for
the
pro
j
ect
.
If
data
ca
n
be
s
ha
red
a
nd
m
ade
avail
a
ble
to
al
l
pa
rtie
s
co
nce
rn
eas
il
y
then
patie
nts
m
at
ch
ing
of
var
i
ou
s
su
pple
m
ent
t
o
opti
m
iz
e
int
erv
e
ntio
n
can
be
achie
ved
w
it
h
gr
eat
possi
bili
ti
es,
thu
s
im
pr
ov
in
g t
he
s
upplem
ent o
f
drug
with
pr
i
or
i
kn
owle
dge
of the
dru
g
i
nter
ven
ti
on a
nd
reacti
on.
ACKN
OWLE
DGE
MENT
The
aut
hors
would
li
ke
to
thank
Un
i
ve
rsiti
Teknolo
gi
MARA
(U
i
TM),
I
nter
national
Islam
i
c
Un
i
ver
sit
y
Ma
la
ysi
a
(I
I
UM)
and
Mi
nistry
of
Hi
gh
e
r
E
du
cat
ion
Ma
la
ysi
a
(MO
HE
)
for
pro
vid
i
ng
fin
ancial
su
p
port
t
hro
ugh
the
MITR
A
gr
a
nt
(
600
-
IR
MI/PER
D
ANA
5/3
/M
ITR
A
(
007/20
18)
-
3)
to
c
onduct
th
e
w
or
k
publishe
d
i
n
th
is pa
per
.
REFERE
NCE
S
[1]
T.
R
.
Selv
ara
ju
,
et
a
l.
,
“
The
n
eur
oprotect
iv
e
e
ffe
ct
s
of
toc
o
trienol
ri
ch
fr
ac
t
i
on
and
a
lpha
to
cophe
rol
against
glut
amat
e
in
jur
y
in astrocy
t
es
,”
Bosnian
Journal
of Basic
Me
di
ca
l
Sc
ie
nc
es
,
vo
l.
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4,
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[2]
K.
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tn
am,
et
al
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,
“
Toc
otr
ienols
and
br
ea
st
c
anc
er
:
Th
e
evi
de
nce
to
da
te
,”
Ge
nes
and
Nutrit
io
n
,
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/i
ss
ue:
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2012
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an
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al.
,
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Pharm
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te
nt
ial
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ew
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ti
o
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Me
tabol
ism
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Alpha
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nol
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ost
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nt
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ri
enol
isom
er
ci
rc
ula
t
ed
in
pla
sm
a
and
li
poprotein
s
aft
er
postprand
ial
to
cot
ri
enol
-
ri
ch
vitam
in
E
suppl
ementa
t
ion
,
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trit
ion Journal
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,
“
Vita
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in
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Toc
oph
ero
ls
an
d
toc
otr
ie
no
ls
as
pote
nt
ia
l
rad
ia
t
i
on
count
e
rm
ea
sures
,”
Journal
o
f
Radi
ati
on
R
ese
a
rch
,
vol
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54
,
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973
–
988
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2013
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Evaluation Warning : The document was created with Spire.PDF for Python.
Ind
on
esi
a
n
J
E
le
c Eng &
Co
m
p
Sci
IS
S
N:
25
02
-
4752
In
te
rla
bor
ato
r
y data f
us
io
n
r
eposi
tory syste
m
(
I
nD
F
uR
S
)
for t
oco
tri
en
ols
...
(
Nor
hasli
nd
a
K
amar
uddin
)
1135
[6]
N.
D.
Shah
and
B.
N.
Li
m
ket
k
ai,
“
The
Us
e
of
Me
dium
-
Chai
n
Tr
ig
l
y
ce
r
ide
s
in
Gast
roint
esti
n
al
disor
der
s
,”
Nu
trit
ion
Iss
ues
in
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troent
erolog
y
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28
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2017
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L.
A.
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al.
, “
The
Natu
ral Histor
y
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Nonalc
oholic
Fatty
L
i
ver
Disea
se:
A Popula
ti
on
-
B
ase
d
Cohort
Stud
y
,”
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troent
erology
,
vo
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113
-
121
,
2005
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[8]
G.
Marc
h
esini
,
et
al
.
,
“
Nonalc
oholic
fa
tty
liver
dis
e
ase
and
the
m
et
abo
li
c
s
y
ndrom
e
,”
C
urr
ent
Opinion
i
n
Lipidol
ogy
,
vol
/is
sue:
16(4)
,
pp.
421
-
427
,
2005
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[9]
B.
A.
Neuschwa
nder
-
Tetri
,
“
Nonalc
oho
l
ic
St
eato
hepa
t
it
is
and
the
Meta
bol
ic
S
y
nd
rom
e
,”
The
Ame
rican
Journal
o
f
the
M
edi
ca
l
S
cie
nce
s
,
vo
l/
issue:
330(6)
,
pp
.
326
-
335
,
2005
.
[10]
G.
Kanuri
and
I.
Bergh
ei
m
,
“
In
Vitro
and
in
Vivo
Models
of
Non
-
Alcoho
li
c
Fatty
L
ive
r
Di
sea
se
(NA
FLD)
,”
Inte
rnational
Jo
urnal
of
Mo
lecul
ar Sc
ie
n
ce
s
,
vol/is
sue:
14(6)
,
pp.
11963
,
2013
.
[11]
E.
Magoss
o,
et
al.
,
“
Toc
otr
ie
nol
s
for
norm
al
isation
of
hep
at
i
c
e
choge
ni
c
respon
se
in
nona
lc
oho
li
c
f
at
t
y
li
v
er:
a
ran
dom
ised
plac
ebo
-
cont
ro
ll
ed
c
l
ini
c
al
tri
a
l
,”
Nu
t
riti
on
Journal
,
v
ol/
issue:
1
2(1)
,
p
p.
1
-
8
,
2013
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P.
Letté
ron
,
et
al.
,
“
Acute
and
chr
onic
hepati
c
stea
tosis
l
ea
d
to
in
vivo
li
p
id
p
ero
xidation
in
m
ic
e
,”
Journal
of
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ogy
,
vo
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sue:
24(2)
,
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208
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E.
Albano
,
et
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,
“
Revi
ew
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of
oxid
at
iv
e
stress
in
the
pr
ogre
s
sio
n
of
non
-
al
coho
li
c
st
ea
to
sis
,”
Al
im
ent
ary
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&
T
herape
uti
cs
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Kune,
et
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,
“
The
Anatom
y
of
Big
Data
Com
puti
ng
,”
So
ft
w
are:
Pract
ice
and
Ex
perie
n
ce
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vo
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B.
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,
“
Mining
El
e
ct
roni
c
Hea
l
th
R
ec
ords:
Towa
rds
Bet
t
er
Research
Applic
a
ti
ons
an
d
Cli
nical
C
are,
”
Nature
R
ev
i
ews
Gene
tics
,
vo
l/
issue:
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,
pp
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39
5
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Cuzz
ocr
ea,
et
al.
,
“
Anal
y
tics
over
La
rg
e
-
sca
l
e
Multi
dimensional
Data:
The
Big
Data
Revol
ut
io
n!
”
Proceedi
ngs
of
th
e
ACM
14t
h
Inte
rnat
ional
Workshop
on
Data
Warehousin
g
and
OL
AP
(
DO
LAP
'11)
.
AC
M,
New
Y
ork
,
N
Y
,
USA
,
pp
.
101
-
10
4
,
2011
.
[17]
C
loud
Data
b
ase
,
“
Defi
nition
fr
om
W
hat
Is.c
om
,”
h
tt
p://s
ea
r
chclouda
pplica
ti
ons
.
techta
rg
et.c
om
/
def
ini
t
ion/cloud
-
dat
ab
ase
,
Ret
r
ieved
9
O
ct
2017
.
[18]
D.
Agrawal
,
et
al.
,
“
Big
Dat
a
a
nd
Cloud
Com
puti
ng:
Curre
n
t
St
ate
and
F
uture
Opportunit
ie
s
,”
Proce
ed
ings
of
t
he
14th
Int
ernati
on
al
Conf
ere
nce o
n
Exten
ding
Dat
abase
Technol
og
y
,
pp
.
530
-
5
33
,
2
011
.
[19]
M.
Gupta,
et
al
.
,
“
Ho
w
IBM
le
ad
s
in
Buil
ding
Big
Data
Anal
y
tics
Soluti
ons
in
the
Cloud:
Im
ple
me
nti
ng
the
CS
C
C
Custom
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te
ct
ure
f
or
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ti
cs
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”
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htt
ps://
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w.i
bm
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r
works
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loud/
li
br
ar
y
/cl
-
ibm
-
le
ads
-
buil
ding
-
big
-
d
a
ta
-
an
aly
t
ic
s
-
solu
ti
ons
-
cl
oud
-
trs/i
ndex
.
html
,
R
et
ri
eve
d
9
Oct
2
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[20]
M.
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et
al.
,
“
Governi
ng
and
Mana
ging
Big
Data
fo
r
Anal
y
tics
and
De
cis
ion
Make
rs
,”
I
BM
Re
dgu
ide
s
f
or
Busi
ness Leade
r
s
,
2014
.
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