Advances in systems analysis, software engineering, and high performance computing book series,
Год журнала:
2023,
Номер
unknown, С. 172 - 203
Опубликована: Июнь 16, 2023
Machine
learning
has
had
an
impact
in
the
area
of
microchip
design
and
was
initially
used
automation.
This
development
could
result
a
tremendous
change
realm
hardware
computation
AI's
powerful
analysis
tools.
Traffic
is
pressing
issue
densely
populated
cities.
Governments
worldwide
are
attempting
to
address
this
problem
by
introducing
various
forms
public
transportation,
including
metro.
However,
these
solutions
require
significant
investment
implementation
time.
Despite
high
cost
inherent
flaws
system,
many
people
still
prefer
use
their
personal
vehicles
rather
than
transportation.
To
issue,
authors
propose
bike-sharing
solution
which
all
processes
from
membership
registration
bike
rental
return
automated.
Bagging
ensemble
method
that
can
be
for
base
models
with
low
bias
variance.
It
uses
randomization
dataset
reduce
variance
models,
while
keeping
low.
Distributed
systems
have
become
a
tremendous
technological
force
that
could
revolutionize
company
operations
while
advancing
ethics
and
boosting
governance.
can
enable
new
business
models,
lower
costs,
boost
efficiency
by
utilizing
the
advantages
of
decentralization,
transparency,
security.
Organizations
further
ensure
distributed
are
exploited
in
responsible
long-lasting
manner
putting
ethical
governance
procedures
place.
The
main
ideas
uses
corporate
development,
ethics,
summarized
this
review
chapter.
It
defines
systems,
examines
their
key
characteristics,
discusses
benefits
using
these
development.
chapter
also
explores
relevance
to
development
role
promoting
practices.
Moreover,
its
importance,
benefits,
examples
mechanisms
be
used.
challenges
limitations
associated
with
implementing
Technical
complexity,
scalability,
interoperability,
regulatory
challenges,
all
significant
concerns
must
carefully
considered
addressed.
choose
best
way
use
governance,
encourage
drive
growth
being
aware
obstacles
constraints.
In
conclusion,
adoption
has
potential
fundamentally
alter
how
companies
created,
run,
governed,
simultaneously
encouraging
moral
behavior
raising
participant
confidence.
decide
spur
growth,
advance
improve
fast-changing
world
knowing
advantages,
drawbacks,
limitations.
Applied Sciences,
Год журнала:
2023,
Номер
13(8), С. 4861 - 4861
Опубликована: Апрель 12, 2023
In
this
paper,
a
convolved
feature
vector
based
adaptive
fuzzy
filter
is
proposed
for
impulse
noise
removal.
The
follows
traditional
approach,
i.e.,
detection
of
noisy
pixels
on
certain
criteria
followed
by
filtering
process.
the
first
step,
mechanism
initially
selects
small
layer
input
image
pixels,
convolves
it
with
set
weighted
kernels
to
form
layer.
This
features
then
passed
inference
system,
where
membership
degrees
and
reduced
rules
play
an
important
part
classify
pixel
as
noise-free,
edge
or
noisy.
Noise-free
in
phase
remain
unaffected
causing
maximum
detail
preservation
whereas
are
restored
using
filter.
process
carried
out
traditionally
starting
from
top
left
corner
bottom
right
stride
rate
one
two
during
convolution.
Convolved
very
helpful
finding
information
hidden
patterns
that
affected
noise.
performance
study
tested
large
data
standard
measures
technique
outperforms
many
existing
state
art
techniques
excellent
effective
removal
capabilities.
Advances in computational intelligence and robotics book series,
Год журнала:
2023,
Номер
unknown, С. 15 - 24
Опубликована: Июнь 30, 2023
This
chapter
provides
an
analysis
of
the
various
kinds
distracting
noise
that
can
be
seen
in
degraded
complex
images,
such
as
those
found
newspapers,
blogs,
and
websites.
A
complicated
image
had
been
deteriorated
a
result
salt
pepper
noise,
random
valued
impulse
speckle
Gaussian
amongst
others,
was
result.
There
is
extraordinarily
high
demand
for
saving
text
read
from
images
have
into
form
by
computers
later
use.
Advances in wireless technologies and telecommunication book series,
Год журнала:
2024,
Номер
unknown, С. 230 - 250
Опубликована: Июнь 28, 2024
The
chapter
explores
the
use
of
machine
learning
(ML)
in
detecting
and
addressing
anomalies
advanced
6G
communication
systems.
It
emphasizes
drawbacks
conventional
approaches
delves
into
ML
algorithms
that
are
appropriate
for
identifying
anomalies,
such
as
clustering,
classification,
deep
learning.
study
focuses
on
difficulties
choosing
important
features
from
various
data
sources
networks,
including
network
traffic
device
behavior.
also
possible
attacks
models
suggests
ways
to
improve
their
resilience.
Exploring
integration
with
slicing
highlighting
adaptability
dynamic
virtualized
networks.
highlights
importance
ML-based
anomaly
detection
strengthening
security
areas
future
research.
Managing
sensitive
data
and
ensuring
its
security
are
critical
components
of
modern
organizational
processes.
However,
conventional
centralized
systems
have
significant
limitations
in
transparency
security.
To
address
these
issues,
the
emergence
blockchain
technology
(BT)
distribution
(DSs)
presents
a
promising
approach.
This
chapter
aims
to
explore
potential
benefits
combining
BT
DS
enhance
management
(DM)
Initially,
it
provides
an
overview
current
state
DM
security,
emphasizing
their
importance
organizations.
The
then
delves
into
concepts
DS,
highlighting
unique
features
advantages
Moreover,
discusses
challenges
BT,
including
scalability
interoperability
weighs
disadvantages
We
analyze
DSs
enhancing
identifying
opportunities
that
arise
from
use.
Finally,
insights
future
research
directions
highlights
impact
technologies
on
serves
as
valuable
resource
for
researchers,
practitioners,
decision-makers
who
wish
possibilities
With
this
new
approach,
we
can
anticipate
with
greater
transparency,
efficiency
managing
data.
Due
to
the
prevalence
of
various
financial
crimes
worldwide,
fraud
in
sector
is
a
growing
concern.
Maintaining
integrity
and
shielding
organizations
people
from
losses
now
depend
heavily
on
detection
(
FD
)
prevention.
The
ability
distributed
system
s
DSs
process
massive
volumes
data
perform
real-time
analysis
has
made
them
promising
prevention
option.
To
finish
specific
activity,
DSs,
network
computers,
work
together.
They
offer
many
advantages,
such
as
scalability,
fault
tolerance,
high
performance.
can
be
used
get
around
drawbacks
traditional
techniques,
including
rule-based
machine
learning-based
systems.
preventive
strategies
–
rule-based,
learning-based,
hybrid
systems
well
their
advantages
disadvantages
are
covered
this
chapter.
It
then
examines
how
leveraged
for
using
Finally,
chapter
highlights
challenges
implementing
future
trends
area.
use
significantly
improve
accuracy
efficiency
these
systems,
leading
better
security
reduced
losses.
However,
also
presents
several
challenges,
privacy
concerns,
risks,
need
specialized
skills
resources.
Future
research
area
will
focus
overcoming
further
enhancing
capabilities
The
chapter
examines
how
DSs
might
improve
the
efficiency
of
financial
transactions
(FT)
and
procedures.
efficiency,
security,
transparency,
cost-effectiveness
FT
processes
could
be
increased
with
use
distributed
systems
(DSs),
such
as
supply
chain
(SC)
blockchain
technology
(BT).
This
provides
an
overview
procedures,
including
their
definition,
difficulties,
contemporary
solutions.
highlights
advantages
in
finance
offers
illustrations
several
contexts,
payment
processing,
digital
identity
verification,
SC
finance,
insurance.
These
systems'
implementation
problems
shortcomings
include
scalability,
interoperability,
legal
compliance,
user
acceptance.
a
comprehensive
review
traits,
advantages,
cases
BT
SC,
focus
on
applications
finance.
also
looks
at
potential
paths
difficulties
applying
to
will
helpful
resource
for
researchers,
programmers,
practitioners
who
are
interested
using
processes.
identifies
these
barriers
shows
eliminate
them
so
that
can
used
full
potential.
