Illegal,
unreported,
and
unregulated
(IUU)
fishing
practices
pose
significant
threats
to
marine
ecosystems
global
fisheries
sustainability.
The
detection
classification
of
loitering
events,
where
vessels
spend
an
extended
period
in
a
specific
area,
are
critical
for
identifying
potential
IUU
activities.
This
research
proposes
comprehensive
approach
that
combines
supervised
semi-supervised
learning
techniques
effectively
detect
classify
events.
By
leveraging
various
machine
algorithms,
including
logistic
regression,
Gaussian
mixture
models,
support
vector
machines,
random
forests,
accurate
predictions
can
be
made
enhance
surveillance
combat
fishing.
Cartoonifying
an
image
is
the
process
of
transforming
a
regular
photograph
into
cartoon-style
image.
This
research
paper
proposes
method
to
cartoonify
images
using
OpenCV,
popular
open-source
computer
vision
library
Python.
The
proposed
involves
several
steps,
including
edge
detection,
color
quantization,
and
smoothing.
detection
step
used
extract
edges
from
input
Then,
in
quantization
step,
palette
reduced
fixed
number
colors
k-means
clustering
algorithm.
Finally,
smoothed
bilateral
filter
create
cartoon-like
effect.
evaluated
on
images,
results
show
that
produces
high-quality
cartoon
with
noise
better
visual
appeal
compared
existing
methods.
has
potential
applications
various
fields,
such
as
entertainment,
advertising,
digital
art,
can
be
easily
integrated
applications.
AIP conference proceedings,
Год журнала:
2024,
Номер
3119, С. 020001 - 020001
Опубликована: Янв. 1, 2024
Deep
learning
and
machine
are
essential
since
most
companies
require
smart
analytics
to
stay
competitive.
Artificial
intelligence
gave
rise
learning,
which
in
turn
deep
learning.
Machine
Learning
still
dominates
business
with
its
algorithms,
despite
the
high-end
uses
of
areas
like
Computer
Vision
Natural
Language
Processing.
By
summarizing
numerous
models
that
currently
available
on
market,
this
survey
article
demonstrates
transition
from
It
also
provides
insight
into
methodologies,
as
well
challenges
faced
expected
future
course
A
potent,
cutting-edge
method
for
analyzing
photos,
especially
remote
sensing
(RS)
images,
is
(DL).
Remote
image
scene
classification,
attempts
assign
semantic
categories
images
based
their
contents,
has
a
variety
applications.
Thanks
powerful
feature
capabilities
DNNs,
learning-based
categorization
generated
lot
interest
made
significant
progress.
range
applications,
such
estimating
water
availability,
monitoring
change
over
time,
predicting
droughts
floods,
can
benefit
surface
mapping.
European Journal of Computer Science and Information Technology,
Год журнала:
2024,
Номер
12(3), С. 71 - 83
Опубликована: Март 15, 2024
Toll
collection
systems
utilizing
modulation
techniques
encounter
significant
challenges
related
to
signal
interference
and
environmental
conditions.
The
precise
transmission
reception
of
signals
are
critical
for
techniques,
but
they
can
be
disrupted
by
physical
obstacles,
weather
variations,
from
other
electronic
devices,
leading
degradation
potential
errors.
Moreover,
the
complexity
inherent
in
these
necessitates
advanced
infrastructure
ongoing
maintenance,
resulting
elevated
operational
expenses.
Addressing
requires
implementation
robust
technical
solutions,
rigorous
testing
procedures,
continuous
maintenance
ensure
efficient
secure
operation
toll
systems.
This
study
aims
develop
an
efficient,
cost-effective,
scalable,
system
using
Amplitude
Shift
Keying
(ASK)
modulation.
ASK
leverages
amplitude
variations
facilitate
data
between
RFID
tags
readers,
enabling
seamless
vehicle
passage
through
points.
selection
Arduino
Uno
microcontroller
is
based
on
its
affordability
reliability,
while
RC522
reader
chosen
their
compatibility
performance.
Real-time
feedback
provided
OLED
display,
MG996r
metal
gear
servo
utilized
operating
barrier.
offers
several
advantages
Its
simplicity
facilitates
easy
reduces
overall
costs,
making
it
a
financially
viable
option.
technique's
use
binary
representation
ensures
reliable
design
enhances
scalability
simplifies
requirements.
Advances in medical technologies and clinical practice book series,
Год журнала:
2024,
Номер
unknown, С. 58 - 73
Опубликована: Авг. 6, 2024
In
the
rapidly
evolving
landscape
of
healthcare,
emergence
Metaverse
presents
a
promising
yet
complex
frontier.
The
chapter
begins
by
providing
an
overview
Metaverse,
exploring
its
fundamental
concepts,
and
highlighting
potential
benefits
for
healthcare
industry.
It
then
proceeds
challenges
that
professionals,
researchers,
stakeholders
may
encounter
in
this
transformative
journey.
With
Metaverse's
immersive
interconnected
nature,
safeguarding
patient
data
ensuring
secure
communication
channels
are
paramount.
examines
vulnerabilities
explores
strategies
to
protect
sensitive
medical
information.
concludes
with
forward-looking
perspective
on
how
industry
can
harness
while
mitigating
associated
issues
challenges.
emphasizes
importance
interdisciplinary
collaboration
between
technologists,
policymakers,
ethicists
navigate
uncharted
terrain
successfully.
Advances in medical technologies and clinical practice book series,
Год журнала:
2024,
Номер
unknown, С. 74 - 88
Опубликована: Авг. 6, 2024
The
Metaverse,
often
referred
to
as
the
immersive
internet,
is
widely
considered
next
significant
technological
disruption
on
horizon,
with
potential
reshape
clinician-patient
interactions,
enhance
patient
experience,
transform
innovation
and
research
development
processes.
Metaverse
currently
in
its
developmental
phase,
establishment
of
a
definitive
framework
an
ongoing
endeavor.
In
recent
years,
concept
has
gained
substantial
traction
evolved
into
multifaceted
virtual
universe
limitless
possibilities.
This
chapter
provides
glimpse
evolving
landscape
healthcare,
where
Metaverse's
interconnected
experiences
have
power
revolutionize
how
we
perceive,
access,
deliver
healthcare
services.
From
clinics
medical
simulations
AI-assisted
diagnostics,
this
explores
ways
which
reshaping
creating
new
opportunities
for
improved
outcomes,
education,
research.
