Journal of Statistical Theory and Applications,
Journal Year:
2024,
Volume and Issue:
23(3), P. 275 - 289
Published: June 19, 2024
Abstract
Balanced
lattice
designs
are
vital
in
numerous
fields,
especially
experimental
design,
where
controlling
variability
among
units
is
crucial.
In
practical
experiments,
various
sources
of
uncertainty
can
lead
to
ambiguous,
vague,
and
imprecise
data,
complicating
the
analysis
process.
To
address
these
indeterminacies,
a
novel
approach
using
neutrosophic
within
balanced
design
framework
proposed,
termed
(NBLD).
This
innovative
method
employs
statistics
derive
mathematical
sums
squares
construct
variance
(NANOVA)
table.
The
effectiveness
proposed
NBLD
demonstrated
through
numerical
example,
showing
that
it
outperforms
traditional
methods
handling
uncertainty.
Journal of Statistical Theory and Applications,
Journal Year:
2023,
Volume and Issue:
22(4), P. 262 - 282
Published: Sept. 11, 2023
Abstract
Pancreatic
cancer
is
one
of
the
deadliest
carcinogenic
diseases
affecting
people
all
over
world.
The
majority
patients
are
usually
detected
at
Stage
III
or
IV,
and
chances
survival
very
low
once
late
stages.
This
study
focuses
on
building
an
efficient
data-driven
analytical
predictive
model
based
associated
risk
factors
identifying
most
contributing
influencing
times
diagnosed
with
pancreatic
using
XGBoost
(eXtreme
Gradient
Boosting)
algorithm.
grid-search
mechanism
was
implemented
to
compute
optimum
values
hyper-parameters
by
minimizing
root
mean
square
error
(RMSE).
hyperparameters
final
were
selected
comparing
243
competing
models.
To
check
validity
model,
we
compared
model’s
performance
ten
deep
neural
network
models,
grown
sequentially
different
activation
functions
optimizers.
We
also
constructed
ensemble
Boosting
Machine
(GBM).
proposed
outperformed
models
considered
regard
After
developing
individual
ranked
according
their
contribution
response
predictions,
which
extremely
important
for
research
organizations
spend
resources
causing/influencing
particular
type
cancer.
three
found
be
age
patient,
current
BMI,
cigarette
smoking
years
percentages
35.5%,
24.3%,
14.93%,
respectively.
approximately
96.42%
accurate
in
predicting
performs
excellently
test
data.
methodology
can
utilized
prediction
purposes.
It
predict
time
death
related
a
specific
cancer,
given
set
numeric,
non-numeric
features.
Applied and Computational Engineering,
Journal Year:
2024,
Volume and Issue:
57(1), P. 200 - 205
Published: April 29, 2024
This
paper
explores
the
transformative
potential
of
Collaborative
Filtering
(CF)
and
Recommender
Systems
(RS)
in
Teaching
English
to
Speakers
Other
Languages
(TESOL).
By
leveraging
data-driven
insights
from
learner
interactions,
these
technologies
offer
personalized
learning
experiences
that
significantly
enhance
language
acquisition,
engagement,
retention.
Through
empirical
evidence
quantitative
analyses,
we
demonstrate
positive
impact
CF
RS
on
learners'
proficiency,
vocabulary
communicative
competence.
The
integration
into
TESOL
not
only
facilitates
adaptive
pathways
but
also
addresses
practical
implementation
challenges,
including
privacy,
ethical
concerns,
technological
barriers.
study
underscores
efficacy
recommendations
creating
more
engaging,
efficient,
effective
environments.
Journal of Statistical Theory and Applications,
Journal Year:
2024,
Volume and Issue:
23(3), P. 275 - 289
Published: June 19, 2024
Abstract
Balanced
lattice
designs
are
vital
in
numerous
fields,
especially
experimental
design,
where
controlling
variability
among
units
is
crucial.
In
practical
experiments,
various
sources
of
uncertainty
can
lead
to
ambiguous,
vague,
and
imprecise
data,
complicating
the
analysis
process.
To
address
these
indeterminacies,
a
novel
approach
using
neutrosophic
within
balanced
design
framework
proposed,
termed
(NBLD).
This
innovative
method
employs
statistics
derive
mathematical
sums
squares
construct
variance
(NANOVA)
table.
The
effectiveness
proposed
NBLD
demonstrated
through
numerical
example,
showing
that
it
outperforms
traditional
methods
handling
uncertainty.
