Cloud
computing
has
changed
the
way
is
executed.
It
gives
centralized
statistics
storage
and
gets
entry
to
software
services,
meaning
that
more
companies
individuals
can
shop
get
right
of
records
from
a
far-flung
region.
However,
with
this
improved
admission
facts,
there
may
be
an
ever-developing
challenge
regarding
personalization
privacy
cloud
services.
That
allows
you
ensure
facts;
it
essential
implement
green
mechanisms
for
customization
management.
Assist
Vector
Machines
(SVMs)
have
emerged
as
effective
efficient
protection
approach.
SVMs
provide
excessive
by
training
version
handiest
applicable
user,
which
means
used
filter
out
inappropriate
data
model.
Furthermore,
offer
advanced
level
safety
information
anonymized
thru
usage
version.
This
paper
proposes
SVM-based
privateness
management
machine
excessively
dense
networks.
system
based
on
distributed
gaining
knowledge
of,
query-primarily
facts
choice,
version-primarily
mechanism.
The
proposed
gadget
designed
handle
large
amount
generated
in
Help
are
supervised
studying
method
category
regression
obligations.
beneficial
highly
networks,
where
massive
quantity
customers
desires
equal
assets
immediately.
explores
use
reinforcing
control
privacy-by
using-design
shield
consumer
unauthorized
access
aid
SVMs.
includes
two
elements:
first,
using
totally
method,
categorized
into
different
stages
consistent
person's
choices.
Second,
profiles
create
customized
views
data,
growing
user's
same
time
permitting
its
entry.
evaluated
simulated
high-dense
community,
outcomes
show
presents
higher
results
than
traditional
strategies..
RSC Advances,
Год журнала:
2024,
Номер
14(13), С. 9003 - 9019
Опубликована: Янв. 1, 2024
The
waste
management
industry
uses
an
increasing
number
of
mathematical
prediction
models
to
accurately
forecast
the
behavior
organic
pollutants
during
catalytic
degradation.
Water,
Год журнала:
2023,
Номер
15(20), С. 3573 - 3573
Опубликована: Окт. 12, 2023
Increasing
levels
of
bisphenol
A
(BPA),
classified
as
an
endocrine-disrupting
compound,
in
the
environment
have
raised
concerns
because
its
detrimental
impact
on
human
and
animal
health.
BPA
has
been
detected
soil
water
even
a
volatile
compound
air
primarily
improper
disposal
extensive
use
production
polycarbonate
plastics
epoxy
resins.
This
review
comprehensively
surveyed
recent
research
focusing
removal
from
through
physicochemical
biological
treatments,
covering
articles
published
2002
to
2023.
range
conventional
non-conventional
methods
employed
for
is
examined,
their
limitations
completely
degrading
are
acknowledged.
Hybrid
or
integrated
treatment
systems
explored,
capitalising
distinctive
potential
various
processes.
The
literature
spanning
2023
underscores
efficacy
hybrid
yielding
promising
results
water.
Furthermore,
future
directions
outlined,
advancements
technologies
developed
over
past
decade
incorporated.
International Journal of Science and Research Archive,
Год журнала:
2024,
Номер
11(1), С. 1830 - 1842
Опубликована: Фев. 17, 2024
Anaerobic
membrane
bioreactors
(AnMBRs)
represent
an
innovative
approach
to
wastewater
treatment,
combining
anaerobic
digestion
with
filtration
achieve
efficient
organic
pollutant
removal
and
resource
recovery.
This
review
critically
examines
the
potential
of
AnMBRs
in
highlighting
their
principles,
advantages,
challenges,
recent
advancements,
future
prospects.
offer
several
advantages
over
traditional
aerobic
treatment
methods,
including
higher
loading
rates,
reduced
energy
requirements,
biogas
production
through
methane
generation.
However,
challenges
such
as
fouling,
reactor
complexity,
operational
costs
have
limited
widespread
adoption.
Recent
advancements
materials,
fouling
mitigation
strategies,
process
optimization
improved
AnMBR
performance
feasibility.
Novel
materials
enhanced
resistance
durability
been
developed,
while
cleaning
techniques
protocols
implemented
mitigate
prolong
lifespan.
Process
design
modifications
parameter
adjustments,
efficiency
consumption
AnMBRs.
Future
research
directions
technology
focus
on
optimizing
configurations,
exploring
novel
control
conducting
comprehensive
techno-economic
assessments
evaluate
environmental
economic
sustainability
Integration
emerging
technologies
distillation,
forward
osmosis,
bioelectrochemical
systems
holds
promise
for
further
enhancing
recovery
capabilities.
Additionally,
addressing
knowledge
gaps
mechanisms,
microbial
community
dynamics,
long-term
system
stability
is
crucial
advancing
facilitating
its
implementation
treatment.
Overall,
significant
sustainable
providing
opportunities
removal,
recovery,
reuse.
By
technical
parameters,
interdisciplinary
research,
can
contribute
development
efficient,
cost-effective,
environmentally
friendly
solutions,
ultimately
supporting
goal
achieving
cleaner
water
resources
a
more
future.
Membranes,
Год журнала:
2024,
Номер
14(3), С. 69 - 69
Опубликована: Март 20, 2024
A
simple
model
is
developed
for
membrane
fouling,
taking
into
account
two
main
fouling
phenomena:
cake
formation,
due
to
attached
solids
on
the
surface,
and
pore
clogging,
retained
compounds
inside
pores.
The
coupled
with
a
anaerobic
digestion
describing
dynamics
of
an
bioreactor
(AnMBR).
In
simulations,
we
investigate
its
qualitative
behavior:
it
shown
that
exhibits
satisfying
properties
in
terms
flux
decrease
fouling.
Comparing
simulation
experimental
data,
predict
quite
well
AnMBR.
simulated
best
fits
correlation
coefficient
r2=0.968
calibration
data
set
r2=0.938
validation
set.
General
discussions
are
given
possible
control
strategies
limit
optimize
production.
We
show
simulations
these
allow
one
increase
mean
production
33
L/(h·m
ChemEngineering,
Год журнала:
2024,
Номер
8(2), С. 42 - 42
Опубликована: Апрель 6, 2024
Coaxial
bioreactors
are
known
for
effectively
dispersing
gas
inside
non-Newtonian
fluids.
However,
due
to
their
design
complexity,
many
aspects
of
and
function,
including
the
relationship
between
hydrodynamics
bioreactor
efficiency,
remain
unexplored.
Nowadays,
various
numerical
models,
such
as
computational
fluid
dynamics
(CFD)
artificial
intelligence
provide
exceptional
opportunities
investigate
performance
coaxial
bioreactors.
For
first
time,
this
study
applied
machine
learning
both
classifiers
regressors,
predict
torque
generated
by
a
bioreactor.
In
regard,
500
CFD
simulations
at
different
aeration
rates,
central
impeller
speeds,
anchor
rotating
modes
were
conducted.
The
results
obtained
from
used
train
test
models.
Careful
feature
scaling
k-fold
cross-validation
performed
enhance
all
models’
prevent
overfitting.
A
key
finding
was
importance
selecting
right
features
model.
It
turns
out
that
just
knowing
speed
bioreactor,
mode
can
be
labelled
with
perfect
accuracy
using
k-nearest
neighbors
(kNN)
or
support
vector
Moreover,
regression
multi-layer
perceptron,
kNN,
random
forest,
examined
impellers.
showed
forest
model
outperformed
other
Finally,
analysis
indicated
most
significant
parameter
in
determining
value.
