Humanities & Social Sciences Reviews,
Год журнала:
2024,
Номер
12(2), С. 54 - 60
Опубликована: Сен. 6, 2024
Purpose
of
the
study:
The
purpose
this
study
is
to
review
and
analyze
current
automated
techniques
for
monitoring
chatbot
conversations
in
field
Conversational
Artificial
Intelligence.
It
aims
highlight
challenges
limitations
these
provide
insights
into
various
metrics
used
measure
performance,
with
goal
enhancing
it.
Methodology:
employs
a
comprehensive
literature
existing
conversations.
Then,
focusing
on
state-of-the-art
approaches,
introduces
division
numerical
(performance
statistics
user
engagement)
linguistic
(conversation
analysis).
Within
conversation
analysis,
which
crucial
improving
responses
accurately
recognizing
intentions,
identifies
presents
three
leading
methods.
Main
Findings:
paper
highlights
that,
while
allow
continuous
enhancement
there
still
room
improvement
analysis
Furthermore,
an
automatic
way
order
implement
adequate
corrective
actions,
essential
task
refining
efficiency
through
learning
adaptation.
Applications
findings
have
practical
applications
businesses
employing
chatbots.
By
understanding
potential
addressing
their
limitations,
commercial
systems
can
be
improved
benefit
customer
satisfaction.
Novelty/Originality
provides
readers
novel
knowledge
necessary
understand
key
from
both
perspectives.
adds
value
by
guiding
how
helps
interactions
explains
content
utilized
approaches.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),
Год журнала:
2024,
Номер
unknown, С. 1781 - 1786
Опубликована: Фев. 28, 2024
The
term
"metaverse"
is
being
spoken
around
often
in
the
IT
sector.
Investments,
startups
constructing
components,
new
platform
announcements,
and
major
corporations
joining
this
realm
of
digital
interaction
are
constantly
news.
There
a
great
deal
momentum
towards
nearly
natural
3D
virtual
environment,
clarion
cry
may
have
led
to
Facebook
renaming
as
Meta,
which
be
recognized
watershed
point
development
Metaverse.
One
can
work,
play,
socialize
Metaverse
at
any
time,
from
location,
using
whatever
device
you
want.
Users
engage
real-time
interactions
by
merging
physical,
augmented,
realities.
It
game-changer
connection,
with
boundless,
unrealized
potential
enormous
commercial
prospects.
In
chapter,
researchers
explore
meaning
metaverse,
its
use
different
fields,
advantages.
This
chapter
assist
people
organizations
better
preparing
themselves
for
possibilities
difficulties
that
today's
state-of-the-art
technology
brings.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),
Год журнала:
2024,
Номер
unknown, С. 100 - 105
Опубликована: Фев. 28, 2024
Rapid
technological
advances
have
significantly
improved
our
ability
to
analyse
video
data.
This
comprehensive
review
examines
machine
learning
(ML)
models
applied
event
detection
and
classification,
including
CNNs,
deep
neural
networks
(DNNs),
RNNs.
When
evaluated
on
benchmark
datasets
for
accuracy,
these
approaches
demonstrate
their
relative
strengths
weaknesses.
Researchers
encountered
numerous
challenges
in
detection,
which
are
addressed
throughout
the
review.
However,
achieving
high
precision
remains
challenging
due
diverse
types,
quality
issues,
model
over
fitting
risks,
lack
of
large
labeled
training
datasets.
Background
scenes,
lighting,
object
occlusion
further
complicate
accurate
identification.
As
computational
power
grow,
stands
gain
significantly.
assessed
action
recognition
trained
UCF-101
CCV
databases.
On
CCV,
a
2-stage
network
achieved
75%
accuracy;
while
multi-stream
(DL)
system
obtained
77.5%.
For
larger
UCF101,
2-stream
RNN
architectures
realized
92%
89%
accuracy
using
video-level
prediction.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),
Год журнала:
2024,
Номер
unknown, С. 1792 - 1797
Опубликована: Фев. 28, 2024
This
paper
discusses
the
significance
of
Machine
Learning
(ML)
and
Deep
(DL)
techniques
for
structured
unstructured
healthcare
data.
As
data
is
increasing
tremendously,
it
difficult
to
identify
hidden
patterns
in
huge
amounts
DL
handles
a
massive
amount
clinical
provides
better
outcomes.
A
novel
competitive
ensemble
deep
learning
model
has
been
proposed
improve
classification
performance
However,
dealing
with
data,
work
highlights
Twitter
sentiment
analysis.
In
addition,
this
Competitive
Ensemble
(CEPL)
algorithm
text
The
compared
traditional
evaluate
model's
range
0.2%-0.5%.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),
Год журнала:
2024,
Номер
unknown, С. 1072 - 1077
Опубликована: Фев. 28, 2024
Technological
innovation
has
created
"digital
twins,"
which
can
replicate
and
synchronize
digital
physical
things
in
(almost)
real-time,
assess
situations
from
multiple
perspectives,
optimize
objects
by
predicting
how
they
will
behave
the
future
based
on
these
analyses.
This
study
delves
deeply
into
Digital
Twin
technology,
covering
its
origins
as
a
game-changing
link
between
real
virtual.
It
explores
diverse
models,
dissecting
their
functionalities
predictive
capacities.
Through
comparative
lens,
it
evaluates
prominent
platforms
Oracle
Twin,
ANSYS
Builder,
Siemens
-
examining
features
adaptability
across
industries.
Extensive
applications
Manufacturing,
Energy,
Automotive,
Logistics
underscore
technology's
optimization
potential
operational
enhancements.
Lastly,
discusses
challenges
perspectives
for
twin
offering
insight
breakthroughs
areas
of
exploration
this
rapidly
evolving
sector.
2022 9th International Conference on Computing for Sustainable Global Development (INDIACom),
Год журнала:
2024,
Номер
unknown, С. 1225 - 1229
Опубликована: Фев. 28, 2024
The
culture
and
modern-day
society
reflect
their
attributes
with
style
of
architecture.
A
particular
holds
value
certain
characteristics.
In
today's
world,
concrete
is
a
common
factor
across
nations
cultures.
It
has
proven
to
be
fundamental
component
construction.
so
far
become
the
most
used
man-made
material.
Concrete
made
by
mixing
aggregates
like
cement,
water,
sand,
gravel,
other
strength-boosting
materials,
later
hydration
process
that
converts
moldable
mixture
into
solid.
Statistical
metrics
such
as
mean
absolute
error,
squared
root
square
coefficient
determination
are
test
learning
models.
To
create
ensemble
models,
several
techniques
were
examined
used,
including
support
vector
regression,
random
forest,
k-nearest
neighbors.
using
0.98,
stacking-based
regression
neighbor
final
estimator
beat
models
in
study,
bagging
forest.
Furthermore,
web
application
was
created
trained
machine
for
user-friendliness.
