Heliyon,
Journal Year:
2024,
Volume and Issue:
10(11), P. e31762 - e31762
Published: May 23, 2024
Incorporating
sustainability
principles
into
refugee
education,
an
often
overlooked
yet
crucial
domain
is
pivotal
for
future
societal
development.
Focusing
on
UNHCR's
directive
in
Jordan,
this
research
delves
the
nuances
of
elevating
enrollment
higher
education
to
15
%
by
2030.
The
study
identifies
significant
challenges
through
empirical
and
theoretical
lenses,
such
as
financial
impediments,
infrastructural
deficits,
socio-cultural
deterrents.
A
multi-layered
solution
proposed:
instituting
targeted
scholarship
programs,
bolstering
institutional
capacities
diverse
learners,
leveraging
digital
platforms,
fostering
global
educational
partnerships.
By
strategically
enhancing
opportunities
refugees,
nations
harness
a
richer
tapestry
skilled
human
capital
underscore
commitment
holistic
sustainability,
inclusivity,
equity.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 13, 2025
Abstract
The
predictive
performance
of
probabilistic
pavement
condition
deterioration
is
critical
for
effective
maintenance
and
rehabilitation
decisions.
Currently,
numerous
improved
models
exist,
but
few
rely
on
to
improve
prediction.
Therefore,
this
study
proposed
an
model
prediction
based
the
coupling
Bayesian
neural
network
(BNN)
cuckoo
search
(CS)
algorithm.
evaluated
against
two
metrics:
determination
coefficient
(R
2
)
standard
deviation
(stability).
Finally,
data
from
management
system
in
Shanxi
Province,
it
was
verified
that
CS-BNN
outperforms
genetic
algorithm-BNN,
particle
swarm
optimization-BNN,
BNN
terms
metrics.
Sensitivity
analysis
further
confirms
robustness
model.
findings
indicate
provides
more
reliable
predictions
with
lower
uncertainty,
aiding
road
engineers
optimizing
schedules
costs.
Journal of Asian Architecture and Building Engineering,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 20
Published: March 13, 2025
Innovative
approaches
for
optimizing
earthmoving
fleets
have
been
proposed
in
the
field
of
construction
management.
Despite
emerging
productivity
analysis
and
optimization
technologies,
existing
studies
witnessed
difficulty
real-life
data
collection
on-site.
Accordingly,
this
paper
proposes
a
synthetic
generation
method
using
information
extracted
from
Korean
Construction
Standard
Productivity
Rate
(CSPR)
document.
The
was
recalculated
to
activity
times
that
were
used
as
input
Discrete
Event
Simulation
(DES)
model
WebCyclone
technique
producing
conducting
productivity-prediction
model-development
practice
an
Artificial
Neural
Network,
XGBOOST,
Random
Forest
Duration-Cost
non-dominated
Sorting
Genetic
Algorithm
II
(NSGA-II).
comparison
results
showed
all
three
methods
provide
excellent
goodness
fit
NSGA-II
can
successfully
deduce
Pareto
front
optimization.
Engineering Construction & Architectural Management,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 22, 2025
Purpose
In
high-rise
construction
projects,
the
use
of
multiple
tower
cranes
to
transport
materials
has
become
common;
however,
optimizing
their
layout
still
poses
a
challenging
problem.
Key
objectives
such
as
minimizing
costs
related
crane
operation
(such
rental,
installation,
dismantling
and
operator
wages)
while
reducing
workdays,
mitigating
interruptions
caused
by
overlapping
improving
safety
preventing
collisions
path
blockages).
Design/methodology/approach
A
mixed-integer
linear
programming
(MILP)
model
is
proposed
optimize
number,
type
location
well
number
supply
points.
The
MILP
incorporates
height
optimization
penalties
for
loading,
crossing
unloading
within
areas
tackle
interference
issues.
Additionally,
delay
penalty
introduced
into
objective
function
minimize
workdays
material
delivery
delays.
Findings
method
was
validated
with
real-world
case
study.
Results
show
that
can
manage
overlaps
optimally
assigning
tasks
ranking
heights.
Unlike
similar
works,
able
find
over
other
determining
an
optimum
height.
Applying
in
study
resulted
cost
reduction
up
49%.
Originality/value
This
extends
previous
approaches
addressing
critical
yet
underexplored
factors
capacity
points
considering
issues
like
avoidance
obstructions
collision(s)
mathematical
model.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 26, 2025
Abstract
As
tower
cranes
(TC)
getting
more
use
in
the
construction
process,
a
reliable
TC
energy
consumption
calculation
model
is
increasingly
required
for
management.
This
paper
proposed
semi-empirical
model,
which
based
on
division
of
work
cycle.
For
fitting
coefficients,
Partial
Least
Squares
Regression
(PLSR)
was
adopted.
To
simplify
variables
with
weak
regression
significance
to
were
deleted
turn.
The
best
suitable
version
achieves
Mean
Absolute
Percentage
Error
25.55%,
Root
Square
(RMSE)
1036.19
kJ,
and
Coefficient
Determination
(R
2
)
0.83,
just
one
independent
variable.
A
comparative
analysis
showed
had
highest
accuracy
degree
among
all
models
calculation.
Through
physical
transformation
several
key
engineering
parameters
(i.e.,
load
mass,
number
cycles,
hoisting
height)
affecting
extracted.
innovation
this
empirical
study
lies
confirming
feasibility
stage-based
small
sample
strategy,
providing
new
ideas
constructing
optimizing
other
machinery.
At
same
time,
lays
foundation
research
related
be
reliable.
