PLoS Computational Biology,
Год журнала:
2024,
Номер
20(1), С. e1011796 - e1011796
Опубликована: Янв. 29, 2024
Naturally
occurring
collective
motion
is
a
fascinating
phenomenon
in
which
swarming
individuals
aggregate
and
coordinate
their
motion.
Many
theoretical
models
of
assume
idealized,
perfect
perceptual
capabilities,
ignore
the
underlying
perception
processes,
particularly
for
agents
relying
on
visual
perception.
Specifically,
biological
vision
many
animals,
such
as
locusts,
utilizes
monocular
non-stereoscopic
vision,
prevents
acquisition
distances
velocities.
Moreover,
peers
can
visually
occlude
each
other,
further
introducing
estimation
errors.
In
this
study,
we
explore
necessary
conditions
emergence
ordered
under
restricted
conditions,
using
non-stereoscopic,
vision.
We
present
model
vision-based
locust-like
agents:
elongated
shape,
omni-directional
sensor
parallel
to
horizontal
plane,
lacking
stereoscopic
depth
The
addresses
(i)
distance
velocity,
(ii)
presence
occlusions
field.
consider
compare
three
strategies
that
an
agent
may
use
interpret
partially-occluded
information
at
cost
computational
complexity
required
processes.
Computer-simulated
experiments
conducted
various
geometrical
environments
(toroidal,
corridor,
ring-shaped
arenas)
demonstrate
result
or
near-ordered
state.
At
same
time,
they
differ
rate
order
achieved.
results
are
sensitive
elongation
agents.
Experiments
geometrically
constrained
reveal
differences
between
elucidate
possible
tradeoffs
them
control
These
suggest
avenues
study
biology
robotics.
Journal of Infection and Public Health,
Год журнала:
2020,
Номер
13(7), С. 914 - 919
Опубликована: Июнь 8, 2020
The
substantial
increase
in
the
number
of
daily
new
cases
infected
with
coronavirus
around
world
is
alarming,
and
several
researchers
are
currently
using
various
mathematical
machine
learning-based
prediction
models
to
estimate
future
trend
this
pandemic.
In
work,
we
employed
Autoregressive
Integrated
Moving
Average
(ARIMA)
model
forecast
expected
COVID-19
Saudi
Arabia
next
four
weeks.
We
first
performed
different
models;
Model,
Average,
a
combination
both
(ARMA),
integrated
ARMA
(ARIMA),
determine
best
fit,
found
out
that
ARIMA
outperformed
other
models.
forecasting
results
showed
will
continue
growing
may
reach
up
7668
per
day
over
127,129
cumulative
matter
weeks
if
stringent
precautionary
control
measures
not
implemented
limit
spread
COVID-19.
This
indicates
Umrah
Hajj
Pilgrimages
two
holy
cities
Mecca
Medina
supposedly
scheduled
be
by
nearly
2
million
Muslims
mid-July
suspended.
A
set
extreme
preventive
proposed
an
effort
avoid
such
situation.
Neural Computing and Applications,
Год журнала:
2021,
Номер
35(33), С. 23671 - 23681
Опубликована: Фев. 4, 2021
The
novel
coronavirus
(COVID-19)
has
spread
to
more
than
200
countries
worldwide,
leading
36
million
confirmed
cases
as
of
October
10,
2020.
As
such,
several
machine
learning
models
that
can
forecast
the
outbreak
globally
have
been
released.
This
work
presents
a
review
and
brief
analysis
most
important
forecasting
against
COVID-19.
presented
in
this
study
possesses
two
parts.
In
first
section,
detailed
scientometric
an
influential
tool
for
bibliometric
analyses,
which
were
performed
on
COVID-19
data
from
Scopus
Web
Science
databases.
For
above-mentioned
analysis,
keywords
subject
areas
are
addressed,
while
classification
models,
criteria
evaluation,
comparison
solution
approaches
discussed
second
section
work.
conclusion
discussion
provided
final
sections
study.
Computers in Biology and Medicine,
Год журнала:
2020,
Номер
124, С. 103949 - 103949
Опубликована: Авг. 6, 2020
Currently,
physicians
are
limited
in
their
ability
to
provide
an
accurate
prognosis
for
COVID-19
positive
patients.
Existing
scoring
systems
have
been
ineffective
identifying
patient
decompensation.
Machine
learning
(ML)
may
offer
alternative
strategy.
A
prospectively
validated
method
predict
the
need
ventilation
patients
is
essential
help
triage
patients,
allocate
resources,
and
prevent
emergency
intubations
associated
risks.
In
a
multicenter
clinical
trial,
we
evaluated
performance
of
machine
algorithm
prediction
invasive
mechanical
within
24
h
initial
encounter.
We
enrolled
with
diagnosis
who
were
admitted
five
United
States
health
between
March
May
4,
2020.
197
REspirAtory
Decompensation
model
covid-19
patients:
prospective
studY
(READY)
trial.
The
had
higher
diagnostic
odds
ratio
(DOR,
12.58)
predicting
than
comparator
early
warning
system,
Modified
Early
Warning
Score
(MEWS).
also
achieved
significantly
sensitivity
(0.90)
MEWS,
which
0.78,
while
maintaining
specificity
(p
<
0.05).
first
trial
needs
among
demonstrated
h.
This
care
teams
effectively
resources.
Further,
capable
accurately
16%
more
widely
used
system
minimizing
false
results.
Biology,
Год журнала:
2020,
Номер
9(5), С. 94 - 94
Опубликована: Май 3, 2020
(1)
Background:
The
virulence
of
coronavirus
diseases
due
to
viruses
like
SARS-CoV
or
MERS-CoV
decreases
in
humid
and
hot
weather.
putative
temperature
dependence
infectivity
by
the
new
SARS-CoV-2
covid-19
has
a
high
predictive
medical
interest.
(2)
Methods:
External
cases
21
countries
French
administrative
regions
were
collected
from
public
data.
Associations
between
epidemiological
parameters
case
dynamics
examined
using
an
ARIMA
model.
(3)
Results:
We
show
that,
first
stages
epidemic,
velocity
contagion
with
country-
region-wise
temperature.
(4)
Conclusions:
Results
indicate
that
temperatures
diminish
initial
rates,
but
seasonal
effects
at
later
epidemy
remain
questionable.
Confinement
policies
other
eviction
rules
should
account
for
climatological
heterogeneities,
order
adapt
health
decisions
possible
geographic
gradients.
