StreamBoostE: A Hybrid Boosting-Collaborative Filter Scheme for Adaptive User-Item Recommender for Streaming Services
Advances in Multidisciplinary & Scientific Research Journal Publication,
Год журнала:
2024,
Номер
10(2), С. 89 - 106
Опубликована: Май 31, 2024
With
home
entertainment,
selecting
the
perfect
movie
is
a
pervasive
challenge,
amplified
by
many
streaming
platforms
like
Netflix
and
Amazon
Prime.
This
study
advances
recommender
system
with
collaborative
filtering
approach
as
implemented
in
Python
titled
StreamBoostE.
We
used
user-based
item-based
similarity
schemes
on
feature
embedding
to
aid
faster
model
construction
training
for
tree-based
gradient
boosting
ensemble.
Employing
both
user-
cosine
ease
embedding,
assesses
movies
inter-relations
via
personalized
user
interest
preferences
submitted
titles
focus
genre
classification.
Results
shows
ensemble
yields
prediction
accuracy
of
0.9984
F1
0.996.
The
major
contribution
StreamBoostE
its
capability
expedite
selection
process
when
integrated
using
flask
API
streamlit
cross-channel
integration
web-based
platforms.
It
presents
users
list
top-10
recommended
similarity.
XGBoost
performed
best
user-/item-based
scheme
fused
sampling
method.
Keywords:
Random
Forest,
SMOTE,
credit
card
fraud
detection,
selection,
imbalanced
dataset
Aims
Research
Journal
Reference
Format:
Atuduhor,
R.R.,
Okpor,
M.D.,
Yoro,
R.E.,
Odiakaose,
C.C.,
Emordi,
F.U.,
Ojugo,
A.A.,
Ako,
Geteloma,
V.O.,
Ejeh,
P.O.,
Abere,
R.A.,
Ifioko,
A.M.,
&
Brizimor,
S.E.
(2024):
StreamBoostE:
A
Hybrid
Boosting-Collaborative
Filter
Scheme
Adaptive
User-Item
Recommender
Streaming
Services.
Advances
Multidisciplinary
Scientific
Vol.
10.
No.
2.
Pp
89-106.
www.isteams.net/aimsjournal.
dx.doi.org/10.22624/AIMS/V10N2P8
Язык: Английский
WiSeCart: Sensor-based Smart-Cart with Self-Payment Mode to Improve Shopping Experience and Inventory Management
Advances in Multidisciplinary & Scientific Research Journal Publication,
Год журнала:
2024,
Номер
10, С. 53 - 74
Опубликована: Март 30, 2024
Superstores
are
often
rippled
with
people
from
a
variety
of
the
pyramid
structure
lower,
middle
and
higher-levels
pyramid.
These
malls
transform
onto
busy-bee
hub
wishing
to
explore
merits
discounted
product
prices
special
offers.
This,
however
causes
surge
in
traffic
coupled
enticing
promotions
that
then
lead
endless
queues
at
various
cash-sales
point
check-out
counters.
This
case
poses
inherent
challenges
both
for
business
owners
customers
due
time
constraint,
substitution
quantity
tracking
such
malls.
The
study
proposes
WiSeCart
–
wireless
sensor-based
shopping
cart
near
feature
compatibility
feat.
Result
shows
integration
self-payment
system
via
NFC
tech
provisions
with:
(a)
reduced
queue
so
can
finish
their
quicker
fast-paced
checkout
process,
(b)
yields
increase
inventory
management
efficiency
errors
customer
data
entry
using
communication
stickers,
(c)
improved
capability
allow
further
behaviour
experience
service
delivery,
which
will
turn
equip
owner
better
managerial
decision
support.
Keywords:
sensor-networks,
smart-carts,
trolley,
experience,
superstores
Journal
Reference
Format:
Brizimor,
S.E.,
Okpor,
M.D.,
Yoro,
R.E.,
Emordi,
F.U.,
Ifioko,
A.M.,
Odiakaose,
C.C.,
Ojugo,
A.A.,
Ejeh,
P.O.,
Abere,
R.A.,
Ako,
Geteloma,
V.O.,
(2024):
WiSeCart:
Sensor-based
Smart-Cart
Self-Payment
Mode
Improve
Shopping
Experience
Inventory
Management.
Social
Informatics,
Business,
Politics,
Law,
Environmental
Sciences
&
Technology
Journal.
Vol.
10,
No.
1.
Pp
53-74.
www.isteams/socialinformaticsjournal.
dx.doi.org/10.22624/AIMS/SIJ/V10N1P7
Язык: Английский
NiCuSBlockIoT: Sensor-based Cargo Assets Management and Traceability Blockchain Support for Nigerian Custom Services
Advances in Multidisciplinary & Scientific Research Journal Publication,
Год журнала:
2024,
Номер
15(2), С. 45 - 64
Опубликована: Май 31, 2024
As
competitive
market
and
globalization
continue
to
ripple
a
range
of
issues
across
the
asset
chain
(i.e.
safety,
quality,
tracing,
overall
management
efficiency).
Pandemics
are
bound
occur
without
warning
has
revealed
unpreparedness
many
nations.
Thus,
Nigerian
Government
aiming
shore
up
revenue/monetization
via
customs
exercise
duties
augment
nosedive
in
revenue
oil
sector
–
must
formulate
policies
adapt
technology
harness
its
inherent
benefits
therein.
Study
advances
sensor-based
blockchain
NiCuSBlockIoT,
which
will
provision
decision-support
scheme
for
cargo
goods
traceability
movement
on
value-chain
by
first
ensuring
that
accurate
records
registered,
tagged
reported
using
units.
These
then
broadcasted
NiCuSBlockIoT
as
record
and/or
blocks
P2P
network
decentralized
framework
executed
distributed
hyper-ledger
fabric
smart-contract
transaction
logic.
Result
show
model
eliminate
fraud
often
accompanies
centralized
sensor-layered
reports
all
such
errors
data
supply
value
chain.
Keywords:
BlockChain,
Food
chain,
Customs
Service,
NISBlockIoT
CISDI
Journal
Reference
Format
Obasuyi,
D.A.,
Yoro,
R.E.,
Okpor,
M.D.,
Ifioki,
A..,
Brizimor,
S..,
Ojugo,
A.A.,
Odiakaose,
C.C.,
Emordi,
F.U.,
Ako,
Geteloma,
V.C.,
Abere,
R.A.,
Atuduhor,
R.R.
&
Akiakeme,
E.
(2024):
NiCuSBlockIoT:
Sensor-based
Cargo
Assets
Management
Traceability
Blockchain
Support
Custom
Services.
Computing,
Information
Systems,
Development
Informatics
Allied
Research
Journal.
Vol
15
No
2,
Pp
45-64.
dx.doi.org/10.22624/AIMS/CISDI/V15N2P4.
Available
online
at
www.isteams.net/cisdijournal
Язык: Английский
Pilot Study on Consumer Preference, Intentions and Trust on Purchasing-Pattern for Online Virtual Shops
International Journal of Advanced Computer Science and Applications,
Год журнала:
2024,
Номер
15(7)
Опубликована: Янв. 1, 2024
User
behaviour
about
an
item
is
a
choice
predicated
on
their
perception
of
the
in
order
to
satisfy
intent
such
purchase
pattern/choice
as
made.
With
virtual
stores
improve
consumer
coverage,
monetization
and
ease
product
delivery,
users'
trust
lowered
with
non-delivery
advertised
products
items
purchased
are
often
replaced
new/similar
products.
To
resolve
issues
preference
for
via
online
shops
–
each
transaction
reflects
user
buying
behaviour.
This,
if
harnessed
will
aid
businesses
reshape
inventory
handle
various
challenges
arising
from
feature
evolution,
drift,
replacement,
concept
evolution.
Our
study
seeks
these
Bayesian
network
trust,
features
store
investigate
effectiveness
design
usefulness
promote
e-commerce
Nigeria.
Data
consists
8,693
records
collected
Google
Play
Scraper
Library
Jumia
retrieved
over
586
respondents.
Expert
evaluation
ranked
use
parameters
high.
Язык: Английский
CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier
Advances in Multidisciplinary & Scientific Research Journal Publication,
Год журнала:
2024,
Номер
10(2), С. 53 - 74
Опубликована: Май 31, 2024
The
pharma-sector
has
maintained
improved
productivity
and
profitability
via
a
concerted
effort
to
address
critical
issues
such
as
an
unorganized
regulatory
system,
lack
of
safety
data,
no
standards
in
manufacture
process,
non-adaptation
pharma-chain,
no-harmony
inventory
supports.
Study
proposes
blockchain
trace-support
ensure
drugs
quality,
consumer
safety,
its
trading
asset.
It
uses
radio-frequency
identification
sensor
register
administration
provide
databank
trace
drug
records.
Results
notes:
(a)
presents
roadmap
for
adoption
by
the
National
Agency
Food
Drug
Administration
Control
(NAFDAC)
traceable
pharmaceutical
blockchain,
(b)
show
ensemble
is
scalable
up-to
7500users
yield
performance
1138-transactions
per
seconds
with
response
time
88secs
page
retrieval
128secs
queries
respectively,
(c)
yields
slightly
longer
increased
number
users
world-state
stored
permissionless
hyper-fabric
ledger.
Thus,
framework
can
directly
query
retrieve
data
without
it
traversing
whole
This,
turn,
improves
efficiency
effectiveness
traceability
system.
Keywords:
Blockchain,
Counterfeit
drugs,
Healthcare,
Nigeria,
CORDA,
hyper-ledger
fabric,
HIPPA
Journal
Reference
Format:
Ifioko,
A.M.,
Yoro,
R.E.,
Okpor,
M.D.,
Brizimor,
S.E,
Obasuyi,
D.,
Emordi,
F.U.,
Odiakaose,
C.C.,
Ojugo,
A.A.,
Atuduhor,
R.R,
Abere,
R.A.,
Ejeh,
P.O.,
Ako,
R.E.
&
Geteloma,
V.O.
(2024):
CoDuBoTeSS:
A
Pilot
Eradicate
Drugs
Blockchain
Tracer
Support
System
on
Nigerian
Frontier.
Behavioural
Informatics,
Digital
Humanities
Development
Rese
Vol.
10
No.
2.
Pp
53-74
https://www.isteams.net/behavioralinformaticsjournal
dx.doi.org/10.22624/AIMS/BHI/V10N2P6
Язык: Английский
CoDuBoTeSS: A Pilot Study to Eradicate Counterfeit Drugs via a Blockchain Tracer Support System on the Nigerian Frontier
Advances in Multidisciplinary & Scientific Research Journal Publication,
Год журнала:
2024,
Номер
10(2), С. 53 - 74
Опубликована: Май 31, 2024
The
pharma-sector
has
maintained
improved
productivity
and
profitability
via
a
concerted
effort
to
address
critical
issues
such
as
an
unorganized
regulatory
system,
lack
of
safety
data,
no
standards
in
manufacture
process,
non-adaptation
pharma-chain,
no-harmony
inventory
supports.
Study
proposes
blockchain
trace-support
ensure
drugs
quality,
consumer
safety,
its
trading
asset.
It
uses
radio-frequency
identification
sensor
register
administration
provide
databank
trace
drug
records.
Results
notes:
(a)
presents
roadmap
for
adoption
by
the
National
Agency
Food
Drug
Administration
Control
(NAFDAC)
traceable
pharmaceutical
blockchain,
(b)
show
ensemble
is
scalable
up-to
7500users
yield
performance
1138-transactions
per
seconds
with
response
time
88secs
page
retrieval
128secs
queries
respectively,
(c)
yields
slightly
longer
increased
number
users
world-state
stored
permissionless
hyper-fabric
ledger.
Thus,
framework
can
directly
query
retrieve
data
without
it
traversing
whole
This,
turn,
improves
efficiency
effectiveness
traceability
system.
Keywords:
Blockchain,
Counterfeit
drugs,
Healthcare,
Nigeria,
CORDA,
hyper-ledger
fabric,
HIPPA
Journal
Reference
Format:
Ifioko,
A.M.,
Yoro,
R.E.,
Okpor,
M.D.,
Brizimor,
S.E,
Obasuyi,
D.,
Emordi,
F.U.,
Odiakaose,
C.C.,
Ojugo,
A.A.,
Atuduhor,
R.R,
Abere,
R.A.,
Ejeh,
P.O.,
Ako,
R.E.
&
Geteloma,
V.O.
(2024):
CoDuBoTeSS:
A
Pilot
Eradicate
Drugs
Blockchain
Tracer
Support
System
on
Nigerian
Frontier.
Behavioural
Informatics,
Digital
Humanities
Development
Rese
Vol.
10
No.
2.
Pp
53-74
https://www.isteams.net/behavioralinformaticsjournal
dx.doi.org/10.22624/AIMS/BIJ/V10N1P6
Язык: Английский
Hypertension Detection via Tree-Based Stack Ensemble with SMOTE-Tomek Data Balance and XGBoost Meta-Learner
Journal of Future Artificial Intelligence and Technologies,
Год журнала:
2024,
Номер
1(3), С. 269 - 283
Опубликована: Дек. 1, 2024
High
blood
pressure
(or
hypertension)
is
a
causative
disorder
to
plethora
of
other
ailments
–
as
it
succinctly
masks
ailments,
making
them
difficult
diagnose
and
manage
with
targeted
treatment
plan
effectively.
While
some
patients
living
elevated
high
can
effectively
their
condition
via
adjusted
lifestyle
monitoring
follow-up
treatments,
Others
in
self-denial
leads
unreported
instances,
mishandled
cases,
now
rampant
cases
result
death.
Even
the
usage
machine
learning
schemes
medicine,
two
(2)
significant
issues
abound,
namely:
(a)
utilization
dataset
construction
model,
which
often
yields
non-perfect
scores,
(b)
exploration
complex
deep
models
have
yielded
improved
accuracy,
requires
large
dataset.
To
curb
these
issues,
our
study
explores
tree-based
stacking
ensemble
Decision
tree,
Adaptive
Boosting,
Random
Forest
(base
learners)
while
we
explore
XGBoost
meta-learner.
With
Kaggle
retrieved,
prediction
accuracy
1.00
an
F1-score
that
correctly
classified
all
instances
test
Язык: Английский