Advances in information security, privacy, and ethics book series,
Год журнала:
2024,
Номер
unknown, С. 333 - 394
Опубликована: Июль 26, 2024
Generative
AI,
which
is
equipped
with
unique
capabilities,
about
to
put
the
world
of
secure
user
interface
(UI)
design
upside
down
and
turn
it
into
something
full
endless
possibilities
in
users
will
be
able
use
same
opportunities
experienced
solutions
protect
their
interaction
digital
from
any
future
security
threats.
This
chapter
takes
a
deep
plunge
merger
generative
AI
design,
on
whole,
presenting
complete
exposition
principals
involved,
methodologies
applied,
practical
embodiment,
ultimate
ramifications.
The
beginning
explore
building
blocks
UI
principles
user-centred
iterative
approach,
wherein
robust
framework
for
understanding
as
critical
part
secure,
intuitive,
engaging
experiences
implemented.
Further,
provides
an
overview
different
types
approaches
that
could
deployed
such
GANs,
VAEs,
autoregressive
models,
capabilities
expanding
scope
measures,
include
authentication
protocols,
encryption,
access
rights
while
retaining
usability
aesthetic
appeal.
Moreover,
surveys
instance
applications
support
Secure
GUI,
among
automatic
generation
safe
layout
patterns,
dynamic
change
according
emerging
threats,
creation
cryptographic
keys
symbols.
International Journal of Computational and Experimental Science and Engineering,
Год журнала:
2025,
Номер
11(1)
Опубликована: Янв. 9, 2025
The
rapid
advancement
of
computational
intelligence
(CI)
techniques
has
enabled
the
development
highly
efficient
frameworks
for
solving
complex
optimization
problems
across
various
domains,
including
engineering,
healthcare,
and
industrial
systems.
This
paper
presents
innovative
that
integrate
advanced
algorithms
such
as
Quantum-Inspired
Evolutionary
Algorithms
(QIEA),
Hybrid
Metaheuristics,
Deep
Learning-based
models.
These
aim
to
address
challenges
by
improving
convergence
rates,
solution
accuracy,
efficiency.
In
context
a
framework
was
successfully
used
predict
optimal
treatment
plans
cancer
patients,
achieving
92%
accuracy
rate
in
classification
tasks.
proposed
demonstrate
potential
addressing
broad
spectrum
problems,
from
resource
allocation
smart
grids
dynamic
scheduling
manufacturing
integration
cutting-edge
CI
methods
offers
promising
future
optimizing
performance
real-world
wide
range
industries.
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
This
research
paper
explores
the
transformative
possibilities
arising
from
integration
of
ChatGPT,
an
advanced
language
model,
into
domain
intelligent
manufacturing.
In
face
rapid
changes
in
manufacturing
landscape,
there
is
increasing
demand
for
adaptive
and
systems
to
elevate
efficiency,
productivity,
decision-making
processes.
study
investigates
incorporation
ChatGPT's
or
Bard
cutting-edge
natural
processing
capabilities
various
forefront
aspects
establish
a
novel
paradigm
The
ChatGPT
processes
presents
versatile
approach
tackle
challenges
seize
opportunities
within
modern
production
systems.
A
pivotal
aspect
this
lies
augmenting
human-machine
collaboration
factory.
understanding
facilitates
seamless
communication
between
human
operators
automated
systems,
fostering
more
intuitive
responsive
environment.
Additionally,
delves
utilization
predictive
maintenance
facilities.
Through
analysis
historical
data
real-time
information,
can
provide
insights
potential
equipment
failures,
enabling
proactive
strategies
that
mitigate
downtime
optimize
resource
utilization.
also
application
supply
chain
management.
model's
capacity
process
vast
amounts
textual
contributes
improved
forecasting,
inventory
optimization,
risk
results
resilient
agile
ecosystem
capable
adapting
dynamic
market
conditions.
Furthermore,
role
quality
control
defect
detection.
model
analyze
intricate
patterns
data,
identifying
anomalies
defects
with
high
degree
accuracy.
Integrating
assurance
ensures
higher
product
quality,
reducing
waste,
enhancing
overall
customer
satisfaction.
findings
highlight
revolutionize
processes,
propelling
industry
towards
greater
adaptability,
competitiveness
rapidly
evolving
global
market.
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
The
urgent
acceleration
of
climate
change
necessitates
the
development
innovative
and
adaptive
mitigation
strategies.
This
study
investigates
how
ChatGPT
or
Bard,
an
advanced
language
model,
enhances
efforts
to
mitigate
change.
By
leveraging
natural
processing
machine
learning,
facilitates
improved
communication,
collaboration,
decision-making
among
stakeholders,
thereby
accelerating
implementation
paper
begins
by
examining
context
change,
emphasizing
need
for
robust
measures.
It
underscores
limitations
traditional
approaches
introduces
transformative
potential
integrating
into
action
frameworks.
model's
capacity
analyze
extensive
datasets
generate
human-like
text
allows
it
comprehend
intricate
science,
distill
key
insights,
communicate
them
effectively.
research
identifies
strategies
that
benefit
from
ChatGPT's
intervention.
One
such
strategy
involves
optimizing
deployment
renewable
energy.
assists
in
identifying
optimal
locations
energy
infrastructure,
considering
geographical
climatic
factors.
Additionally,
model
aids
developing
sophisticated
management
systems,
enhancing
efficiency
reliability
sources.
In
sustainable
agriculture,
contributes
providing
real-time
data
analysis
precision
farming.
helps
farmers
optimize
resource
utilization,
minimize
environmental
impact,
adopt
climate-resilient
agricultural
practices.
Moreover,
formulating
policies
promote
land
use
forest
conservation.
also
explores
role
resilience
through
risk
assessment
adaptation
planning.
analyzing
data,
vulnerable
regions
targeted
infrastructure
resilience,
disaster
preparedness,
community
engagement.
Furthermore,
discusses
fostering
global
collaboration.
cross-border
information
exchange,
knowledge
sharing,
formulation
unified
policies.
collaborative
approach
is
essential
addressing
transboundary
nature
achieving
international
goals.
harnessing
capabilities,
stakeholders
can
unlock
new
dimensions
innovation,
paving
way
a
more
resilient
future.
IET Blockchain,
Год журнала:
2024,
Номер
4(4), С. 365 - 378
Опубликована: Май 26, 2024
Abstract
In
recent
years,
the
Metaverse
has
gained
attention
as
a
hub
for
technological
revolution.
However,
its
main
platform
suffers
from
issues
like
low‐quality
content
and
lackluster
virtual
environments,
leading
to
subpar
user
experiences.
Concerns
arise
declining
interest
in
NFTs
failed
real
estate
ventures,
casting
doubt
on
Metaverse's
future.
Artificial
intelligence
generated
(AIGC)
emerges
key
driver
of
advancement,
using
AI
create
digital
efficiently
affordably.
AIGC
also
enables
personalized
content,
enhancing
Metaverse.
This
paper
examines
link
between
AIGC,
exploring
AIGC's
applications,
underlying
technologies,
future
challenges.
It
reveals
that
while
shows
promise
improving
Metaverse,
technologies
must
better
align
with
development
needs
deliver
immersive
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
This
research
delves
into
the
utilization
of
advanced
artificial
intelligence
(AI),
specifically
ChatGPT
or
Bard,
to
improve
strategies
for
monitoring
and
controlling
water
air
pollution.
Given
escalating
concerns
surrounding
environmental
degradation
its
repercussions
on
public
health,
there
is
a
pressing
demand
innovative
pollution
management
techniques.
investigation
centers
harnessing
capabilities
ChatGPT,
an
language
model,
address
real-time
data
analysis,
decision-making,
engagement
challenges
within
realm
quality.
Incorporating
cutting-edge
methods
in
monitoring,
such
as
sensor
networks,
satellite
imagery,
IoT
devices,
this
aims
obtain
comprehensive
understanding
dynamics.
Nevertheless,
substantial
volume
presents
processing
extracting
meaningful
insights.
employed
intelligent
tool
proficient
comprehending
natural
queries
delivering
insightful
analyses.
integration
streamlines
interpretation
intricate
sets,
enabling
swift
decision-making
control
authorities.
Moreover,
assumes
pivotal
role
by
serving
user-friendly
interface
disseminating
information
levels,
regulatory
measures,
preventive
actions.
Through
interactive
conversations,
it
enhances
communication
between
agencies
general
public,
cultivating
awareness
encouraging
participation
initiatives.
paper
underscores
significance
collaborative
human-AI
approach
tackling
multifaceted
The
also
ethical
considerations
associated
with
AI-driven
emphasizing
importance
responsible
AI
implementation.
As
technologies
progress,
proposed
framework
contribute
ongoing
discourse
sustainable
involvement.
By
synergizing
state-of-the-art
techniques,
seeks
offer
efficacious
solution
advancing
contemporary
landscape.
SSRN Electronic Journal,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
The
infusion
of
generative
artificial
intelligence
(AI)
stands
out
as
a
transformative
influence
in
civil
engineering,
reshaping
conventional
methodologies
and
elevating
the
effectiveness
precision
across
various
domains.
This
study
delves
into
nuanced
impact
ChatGPT,
potent
language
model,
key
realms
within
engineering:
Structural
Engineering,
Geotechnical
Transportation
Environmental
Water
Resources
Urban
Regional
Planning,
Materials
Coastal
Earthquake
Engineering.
Within
ChatGPT
assumes
central
role
formulating
refining
structural
designs.
By
deciphering
intricate
engineering
concepts
proposing
inventive
solutions,
assists
engineers
crafting
structures
that
not
only
exhibit
resilience
but
also
optimize
resource
utilization.
Its
proficiency
scrutinizing
extensive
datasets
delivering
insights
positions
it
an
invaluable
tool
for
augmenting
integrity
safety.
Engineering
benefits
from
ChatGPT's
aptitude
processing
interpreting
geological
geophysical
data.
Through
generation
reports
analyses,
aids
recognizing
potential
risks
suggesting
mitigation
strategies,
thereby
expediting
decision-making
geotechnical
projects.
In
realm
application
involves
streamlining
traffic
flow,
devising
intelligent
transportation
systems,
overall
infrastructure
planning.
natural
capabilities
facilitate
seamless
communication
collaboration
among
diverse
stakeholders
engaged
contributes
to
evaluation
environmental
studies,
assisting
planners
making
well-informed
decisions
prioritizing
sustainability.
Moreover,
its
capability
simulate
scenarios
formulation
effective
pollution
control
measures.
leverages
data
interpretation
modeling,
enabling
precise
predictions
water
flow
patterns
aiding
design
efficient
management
systems.
extends
contributions
where
urban
development
optimizing
land
use,
addressing
challenges
associated
with
population
growth
urbanization.
prowess
analysis
materials
enhanced
properties,
resilient
coastal
structures,
creation
earthquake-resistant
infrastructure.
research
paper
scrutinizes
how
integration
these
disciplines
heightens
efficiency
practices
unlocks
new
avenues
innovation,
sustainability,
face
evolving
challenges.
AI
advances
integrate
generative
design
tools
in
architecture,
providing
architects
with
sophisticated
options.
It
enables
the
creation
of
intricate,
high-performing
projects
by
exploring
diverse
possibilities
and
algorithms.
Generative
empower
to
create
better-performing,
sustainable,
efficient
solutions
explore
possibilities.
This
paper
leverages
multimodal
enhance
creativity
combining
textual
visual
inputs.
Blockchain
technology
converts
metadata
into
NFTs,
ensuring
secure,
authentic,
traceable
data
storage.
The
framework
addresses
ownership,
legal
adherence,
client-architect
collaboration
is
entirely
scalable
for
digital
authentication.
research
exemplifies
pragmatic
fusion
blockchain
applied
architectural
more
transparent,
effective
results.
study
provides
a
strategy
that
uses
technologies
achieve
an
creative
workflow
early
stages
design.
International Journal of Computational and Experimental Science and Engineering,
Год журнала:
2025,
Номер
11(1)
Опубликована: Фев. 5, 2025
In
the
evolving
landscape
of
e-learning,
delivering
personalized
content
that
aligns
with
learners'
needs
and
preferences
is
crucial.
This
study
proposes
a
Context-Aware
Content
Recommendation
Engine
(CACRE)
utilizes
Hybrid
Reinforcement
Learning
(HRL)
technique
to
optimize
learning
experiences.
The
engine
incorporates
contextual
data,
such
as
pace,
preferences,
performance,
deliver
tailored
recommendations.
proposed
HRL
model
combines
Deep
Q-Learning
for
dynamic
selection
Policy
Gradient
Methods
adapt
individual
trajectories.
Experimental
results
demonstrate
significant
improvements
in
learner
engagement,
relevance,
knowledge
retention.
approach
underscores
potential
context-aware
recommendation
systems
revolutionize
education
by
fostering
adaptive
interactive
environments.
