Buildings,
Год журнала:
2025,
Номер
15(9), С. 1544 - 1544
Опубликована: Май 3, 2025
Dealing
with
solid
waste
has
always
been
a
global
concern,
and
construction
is
one
of
the
most
important
parts.
Addressing
how
to
properly
dispose
waste,
reduce
its
negative
environmental
impact,
achieve
effective
resource
recycling
emerged
as
an
urgent
problem
be
solved.
Technological
innovation
underpins
efficient
reduction,
reuse,
recycling,
but
existing
research
often
overlooks
systematic
quantitative
measurements
initiatives.
This
study
uncovers
development
status
trends
(CWR)
technology,
identifies
key
points
potential
directions
for
technological
development,
also
explores
practical
strategies
promote
industrial
growth.
Through
patent
analysis,
this
current
within
China’s
CWR
industry.
A
text
mining
approach
employed
analyze
texts
related
core
technologies,
explore
topic
contents,
identify
intensities
evolution
trends.
comparative
analysis
between
China
dominant
countries
in
reveals
strengths
weaknesses.
The
results
indicate
that
applications
industry
are
substantial,
rapid
growth
rate,
while
competitiveness
remains
weak.
applicants
widely
distributed,
traditional
enterprises
demonstrating
strong
capabilities,
emerging
small-to-medium
lack
vitality.
advantages
developing
devices
wastewater
treatment
foundation
some
other
technologies
offers
overview
initiatives
industry,
representing
breakthrough
research.
findings
will
assist
policymakers
formulating
evidence-driven
CWR.
Engineering Research Express,
Год журнала:
2024,
Номер
6(3), С. 035209 - 035209
Опубликована: Июнь 28, 2024
Abstract
Arrhythmia,
a
common
cardiovascular
disorder,
refers
to
the
abnormal
electrical
activity
within
heart,
leading
irregular
heart
rhythms.
This
condition
affects
millions
of
people
worldwide,
with
severe
implications
on
cardiac
function
and
overall
health.
Arrhythmias
can
strike
anyone
at
any
age
which
is
significant
cause
morbidity
mortality
global
scale.
About
80%
deaths
related
disease
are
caused
by
ventricular
arrhythmias.
research
investigated
application
an
optimized
multi-objectives
supervised
Machine
Learning
(ML)
models
for
early
arrhythmia
diagnosis.
The
authors
evaluated
model’s
performance
dataset
from
UCI
ML
repository
varying
train-test
splits
(70:30,
80:20,
90:10).
Standard
preprocessing
techniques
such
as
handling
missing
values,
formatting,
balancing,
directory
analysis
were
applied
along
Pearson
correlation
feature
selection,
all
aimed
enhancing
model
performance.
proposed
RF
achieved
impressive
metrics,
including
accuracy
(95.24%),
precision
(100%),
sensitivity
(89.47%),
specificity
(100%).
Furthermore,
study
compared
approach
existing
models,
demonstrating
improvements
across
various
measures.
Engineering Applications of Artificial Intelligence,
Год журнала:
2024,
Номер
136, С. 108877 - 108877
Опубликована: Июль 8, 2024
In
recent
years,
there
has
been
a
growing
interest
in
analyzing
text
data
from
different
scientific
fields.
The
significant
advancement
of
Artificial
Intelligence
Natural
Language
Processing
enables
systematic
categorization
the
wealth
papers
into
fundamental
thematic
clusters.
this
context,
topic
modeling
is
playing
crucial
role.
Unfortunately,
comparative
analysis
between
traditional
and
advanced
methods,
including
well-established
techniques
like
Latent
Dirichlet
Allocation
(LDA)
newer
approaches
BERTopic,
remains
significantly
underexplored.
This
study
addresses
gap
by
conducting
comprehensive
extensive
focused
on
sustainable
energy
research.
To
achieve
this,
we
compile
unique
dataset
consisting
thousands
abstracts
sourced
PubMed,
Scopus,
Web
Science.
Our
involves
comparison
LDA
transformer
model
BERTopic.
Importantly,
introduce
novel
approach
to
determine
optimal
number
topics,
achieved
through
maximization
combined
semantic
scores,
show
that
topics
considerably
lower
than
previous
approaches.
Overall,
our
not
only
contributes
methodologically
but
also
enhances
understanding
principal
International Journal of Intelligent Systems,
Год журнала:
2024,
Номер
2024, С. 1 - 26
Опубликована: Март 14, 2024
Artificial
intelligence
(AI)
has
emerged
as
a
transformative
technology
with
applications
across
multiple
domains.
The
corpus
of
work
related
to
the
field
AI
grown
significantly
in
volume
well
terms
application
wider
However,
given
wide
diverse
areas,
measurement
and
characterization
span
research
is
often
challenging
task.
Bibliometrics
well-established
method
scientific
community
measure
patterns
impact
research.
It
however
also
received
significant
criticism
for
its
overemphasis
on
macroscopic
picture
inability
provide
deep
understanding
growth
thematic
structure
knowledge-creation
activities.
Therefore,
this
study
presents
framework
comprising
two
techniques,
namely,
Bradford’s
distribution
path
analysis
characterize
evolution
discipline.
While
Bradford
provides
view
artificial
growth,
microscopic
evolutionary
trajectories,
thereby
completing
analytical
framework.
Detailed
insights
into
each
subdomain
are
drawn,
major
techniques
employed
various
identified,
some
relevant
implications
discussed
demonstrate
usefulness
analyses.
