Journal of Industrial Intelligence,
Год журнала:
2024,
Номер
2(2), С. 73 - 93
Опубликована: Май 24, 2024
The
rapid
advancement
of
technology
has
correspondingly
escalated
the
sophistication
cyber
threats.
In
response,
integration
artificial
intelligence
(AI)
into
cybersecurity
(CS)
frameworks
been
recognized
as
a
crucial
strategy
to
bolster
defenses
against
these
evolving
challenges.
This
analysis
scrutinizes
effects
AI
implementation
on
CS
effectiveness,
focusing
case
study
involving
company
XYZ's
adoption
an
AI-driven
threat
detection
system.
evaluation
centers
several
pivotal
metrics,
including
False
Positive
Rate
(FPR),
Detection
Accuracy
(DA),
Mean
Time
Detect
(MTTD),
and
Operational
Efficiency
(OE).
Findings
from
this
illustrate
marked
reduction
in
false
positives,
enhanced
DA,
more
streamlined
security
operations.
demonstrably
fortified
resilience
expedited
incident
response
capabilities.
Such
improvements
not
only
underscore
potential
solutions
significantly
enhance
measures
but
also
highlight
their
necessity
safeguarding
digital
assets
within
continuously
landscape.
implications
findings
are
profound,
suggesting
that
leveraging
technologies
is
imperative
for
effectively
mitigating
threats
ensuring
robust
contemporary
settings.
Information,
Год журнала:
2024,
Номер
15(5), С. 280 - 280
Опубликована: Май 14, 2024
This
research
paper
presents
a
comprehensive
study
on
optimizing
the
critical
artificial
intelligence
(AI)
factors
influencing
cost
management
in
civil
engineering
projects
using
multi-criteria
decision-making
(MCDM)
approach.
The
problem
addressed
revolves
around
need
to
effectively
manage
costs
endeavors
amidst
growing
complexity
of
and
increasing
integration
AI
technologies.
methodology
employed
involves
utilization
three
MCDM
tools,
specifically
Delphi,
interpretive
structural
modeling
(ISM),
Cross-Impact
Matrix
Multiplication
Applied
Classification
(MICMAC).
A
total
17
factors,
categorized
into
eight
broad
groups,
were
identified
analyzed.
Through
application
different
techniques,
relative
importance
interrelationships
among
these
determined.
key
findings
reveal
role
certain
such
as
risk
mitigation
components,
processes.
Moreover,
hierarchical
structure
generated
through
ISM
influential
via
MICMAC
provide
insights
for
prioritizing
strategic
interventions.
implications
this
extend
informing
decision-makers
domain
about
effective
strategies
leveraging
their
practices.
By
adopting
systematic
approach,
stakeholders
can
enhance
project
outcomes
while
resource
allocation
mitigating
financial
risks.
Spectrum of Engineering and Management Sciences,
Год журнала:
2024,
Номер
2(1), С. 46 - 55
Опубликована: Июнь 10, 2024
The
integration
of
artificial
intelligence
(AI)
into
mechanical
engineering
has
precipitated
a
profound
transformation
in
the
way
engineers
conceive,
design,
and
execute
projects.
This
paper
explores
multifaceted
impact
AI
on
innovation,
elucidating
myriad
ways
which
intelligent
machines
are
revolutionizing
traditional
practices
catalyzing
unprecedented
advancements.
In
realm
algorithms
conceptualization
optimization
processes.
By
leveraging
machine
learning
techniques,
can
explore
vast
design
spaces
with
unparalleled
efficiency,
uncovering
innovative
solutions
that
might
otherwise
remain
elusive.
These
AI-driven
tools
not
only
expedite
development
cycle
but
also
enable
creation
products
systems
enhanced
performance
characteristics,
such
as
improved
energy
structural
integrity,
functional
versatility.
Moreover,
AI's
influence
extends
beyond
phase
permeates
entire
manufacturing
ecosystem.
automation
is
reshaping
production
lines,
enabling
agile
adaptive
processes
respond
dynamically
to
changing
demands
conditions.
Through
sensors,
actuators,
AI-powered
control
systems,
factories
becoming
increasingly
autonomous,
optimizing
resource
utilization,
minimizing
waste,
maximizing
throughput.
Abstract
The
impact
of
logistics
performance
in
the
era
sustainable
mobility
on
overall
economic
development
a
country
is
inevitable.
It
can
even
be
said
to
represent
an
extremely
important
component
identifying
conditions
and
provides
possibility
defining
adequate
strategies.
In
this
article,
evaluation
member
countries
European
Union
was
carried
out
basis
index
(LPI)
according
latest
report
World
Bank
(WB).
A
unique
original
Multiple-Criteria
Decision
Making
(MCDM)
approach
has
been
created,
it
involves
application
four
methods:
Criteria
Importance
Through
Intercriteria
Correlation,
Method
based
Removal
Effects
Criteria,
Entropy
Fuzzy
ROV
(Range
Value).
weighting
coefficients
six
factors
were
obtained
with
first
three
methods
crisp
form,
so
they
converted
into
Triangular
Number.
method
created
for
time
literature
represents
great
contribution
from
methodological
aspect.
results
developed
model
applied
steps
show
that
there
are
certain
differences
rankings
compared
report,
note
best-ranked
have
maintained
their
positions.
addition,
verification
tests
originally
emphasis
importance
parameter
values
LPI
ranking.
