International Journal on Advanced Science Engineering and Information Technology,
Год журнала:
2024,
Номер
14(6), С. 2121 - 2129
Опубликована: Дек. 25, 2024
In
today's
rapidly
evolving
landscape
of
higher
education,
the
effective
management
and
analysis
academic
data
have
become
increasingly
challenging,
particularly
in
context
3Vs
Big
Data:
volume,
variety,
velocity.
The
amount
produced
by
educational
institutions
has
increased
dramatically,
including
student
records.
This
flood
originates
from
various
sources
takes
several
forms,
such
as
learning
systems
information
systems.
Hence,
analytics
predictive
modeling
significant
acquiring
insights
into
performance,
identifying
at-risk
students
who
are
most
likely
to
fail
their
courses.
study
proposes
a
novel
approach
for
predicting
students,
leveraging
lake
architecture.
proposed
methodology
comprises
ingestion,
transformation,
quality
assessment
combined
source
Universiti
Putra
Malaysia's
Student
Information
System
system
within
environment.
With
its
parallel
processing
capabilities,
this
centralized
repository
facilitates
training
evaluation
machine
models
prediction.
addition
forecasting
appropriate
algorithms
Support
Vector
Classifier,
Naive
Bayes,
Decision
Trees
used
build
prediction
using
lake's
scalability
capabilities.
laid
solid
groundwork
architecture
improve
students'
performance.
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(10), С. 1860 - 1860
Опубликована: Окт. 17, 2024
This
paper
addresses
the
scheduling
problem
of
a
mixed
fleet
passing
through
river
bottleneck
in
multiple
ways,
considering
impact
streamflow
velocity,
fuel
cost
with
different
sailing
speeds,
and
potential
opportunity
various
types
sizes
vessels.
From
perspective
centralized
management
by
authorities,
unified
approach
is
proposed,
nonlinear
model
constructed,
where
total
are
minimized.
To
handle
terms
model,
an
outer
approximation
technique
applied
to
linearize
while
ensuring
error
remains
controlled.
The
optimal
value
range
variables
also
proven
ensure
solution
speed.
Furthermore,
applicability
effectiveness
method
validated
real-world
case
study
on
Yangtze
River.
results
show
following:
(1)
Unified
collaborative
authorities
can
effectively
met
that
vessels
arranged
under
rational
ways.
(2)
When
consumption
same
as
traditional
oil-fuelled
vessels,
giving
priority
liquefied
natural
gas
(LNG)-fuelled
pass
reduce
reasonably.
(3)
In
accordance
changes
price,
proportion
LNG-fuelled
timely
adjusting
expectations,
vessel
arrival
time,
service
times
ways
crucial
for
shipowners
waiting
at
bottleneck,
delay
cost.
International Journal on Advanced Science Engineering and Information Technology,
Год журнала:
2024,
Номер
14(6), С. 2121 - 2129
Опубликована: Дек. 25, 2024
In
today's
rapidly
evolving
landscape
of
higher
education,
the
effective
management
and
analysis
academic
data
have
become
increasingly
challenging,
particularly
in
context
3Vs
Big
Data:
volume,
variety,
velocity.
The
amount
produced
by
educational
institutions
has
increased
dramatically,
including
student
records.
This
flood
originates
from
various
sources
takes
several
forms,
such
as
learning
systems
information
systems.
Hence,
analytics
predictive
modeling
significant
acquiring
insights
into
performance,
identifying
at-risk
students
who
are
most
likely
to
fail
their
courses.
study
proposes
a
novel
approach
for
predicting
students,
leveraging
lake
architecture.
proposed
methodology
comprises
ingestion,
transformation,
quality
assessment
combined
source
Universiti
Putra
Malaysia's
Student
Information
System
system
within
environment.
With
its
parallel
processing
capabilities,
this
centralized
repository
facilitates
training
evaluation
machine
models
prediction.
addition
forecasting
appropriate
algorithms
Support
Vector
Classifier,
Naive
Bayes,
Decision
Trees
used
build
prediction
using
lake's
scalability
capabilities.
laid
solid
groundwork
architecture
improve
students'
performance.
