International Journal of Production Research,
Journal Year:
2022,
Volume and Issue:
61(24), P. 8468 - 8492
Published: Dec. 28, 2022
Motivated
by
the
COVID-19
pandemic,
this
paper
explores
supply
chain
viability
of
medical
equipment,
an
industry
whose
was
put
under
a
crucial
test
during
pandemic.
This
includes
empirical
network-level
analysis
supplier
reachability
Random
Failure
Experiments
(RFE)
and
Intelligent
Attack
(IAE).
Specifically,
study
investigates
effect
RFE
IAE
across
multiple
tiers
scales.
The
global
data
mined
analysed
from
about
45,000
firms
with
115,000
intertwined
relationships
spanning
10
backward
equipment.
complex
network
at
four
scales,
namely:
firm,
country-industry,
industry,
country.
A
notable
contribution
is
application
tier
optimisation
tool
to
identify
lowest
that
can
provide
adequate
resolution
for
pattern.
We
also
developed
data-driven-tools
thresholds
breakdown
fragmentation
equipment
when
faced
random
failures
or
different
intelligent
attack
scenarios.
novel
tools
utilised
in
be
applied
other
industries.
Journal of Structural Engineering,
Journal Year:
2022,
Volume and Issue:
148(8)
Published: June 9, 2022
Population
growth,
economic
development,
and
rapid
urbanization
in
many
areas
have
led
to
increased
exposure
vulnerability
of
structural
infrastructure
systems
hazards.
Thus,
developing
risk-based
assessment
management
tools
is
crucial
for
stakeholders
the
general
public
make
informed
decisions
on
prehazard
planning
posthazard
recovery.
To
this
end,
risk
resilience
has
been
an
ongoing
research
topic
past
20
years.
Recently,
machine
learning
(ML)
techniques
shown
as
promising
advancing
structure
systems.
date,
however,
there
a
lack
holistic
review
ML
progress
across
various
branches
engineering;
in-depth
analysis
literature
that
can
provide
timely
evaluation
methods
built
environment,
where
different
types
facilities
are
interconnected.
For
reason,
study
conducted
comprehensive
four
main
engineering
(buildings,
bridges,
pipelines,
electric
power
systems).
cover
modules
prevailing
frameworks,
existing
thoroughly
examined
characterized
terms
six
attributes
ML,
including
method,
task
type,
data
source,
scale,
event
area.
Moreover,
limitations
challenges
identified,
future
needs
highlighted
move
forward
frontiers
assessment.
IEEE Transactions on Sustainable Energy,
Journal Year:
2022,
Volume and Issue:
14(2), P. 1230 - 1243
Published: July 28, 2022
Permanently
increasing
penetration
of
converter-interfaced
generation
and
renewable
energy
sources
(RESs)
makes
modern
electrical
power
systems
more
vulnerable
to
low
probability
high
impact
events,
such
as
extreme
weather,
which
could
lead
severe
contingencies,
even
blackouts.
These
contingencies
can
be
further
propagated
neighboring
over
coupling
components/technologies
consequently
negatively
influence
the
entire
multi-energy
system
(MES)
(such
gas,
heating
electricity)
operation
its
resilience.
In
recent
years,
machine
learning-based
techniques
(MLBTs)
have
been
intensively
applied
solve
various
problems,
including
planning,
or
security
reliability
assessment.
This
paper
aims
review
MES
resilience
quantification
methods
application
MLBTs
assess
level
future
sustainable
systems.
The
open
research
questions
are
identified
discussed,
whereas
directions
identified.
