IEEE Sensors Journal,
Год журнала:
2023,
Номер
23(18), С. 20460 - 20472
Опубликована: Авг. 11, 2023
In
recent
years,
the
smart
electronic
nose
(E-nose)
has
witnessed
rapid
applications
in
diverse
fields.
Apart
from
sensor
arrays,
recognition
algorithm
plays
a
determinant
role
performance
of
E-nose.
Focusing
on
signal
processing
E-nose,
response
characteristic
is
introduced
first
this
article.
Based
differences
between
features,
algorithms
are
subsequently
divided
into
traditional
and
artificial
neural
networks
(ANNs)-based,
their
respective
properties
specifically
analyzed
through
application
reality.
The
evaluation
metrics
for
these
then
summarized.
Finally,
challenges
prospects
concluded.
This
article
aims
to
help
researchers
fields
employ
explore
appropriate
gas
emerging
Big Data and Cognitive Computing,
Год журнала:
2023,
Номер
7(2), С. 62 - 62
Опубликована: Март 27, 2023
ChatGPT,
a
conversational
AI
interface
that
utilizes
natural
language
processing
and
machine
learning
algorithms,
is
taking
the
world
by
storm
buzzword
across
many
sectors
today.
Given
likely
impact
of
this
model
on
data
science,
through
perspective
article,
we
seek
to
provide
an
overview
potential
opportunities
challenges
associated
with
using
ChatGPT
in
readers
snapshot
its
advantages,
stimulate
interest
use
for
science
projects.
The
paper
discusses
how
can
assist
scientists
automating
various
aspects
their
workflow,
including
cleaning
preprocessing,
training,
result
interpretation.
It
also
highlights
has
new
insights
improve
decision-making
processes
analyzing
unstructured
data.
We
then
examine
advantages
ChatGPT’s
architecture,
ability
be
fine-tuned
wide
range
language-related
tasks
generate
synthetic
Limitations
issues
are
addressed,
particularly
around
concerns
about
bias
plagiarism
when
ChatGPT.
Overall,
concludes
benefits
outweigh
costs
greatly
enhance
productivity
accuracy
workflows
become
increasingly
important
tool
intelligence
augmentation
field
science.
translation,
sentiment
analysis,
text
classification.
However,
while
save
time
resources
compared
training
from
scratch,
specific
cases,
it
may
not
perform
well
certain
if
been
specifically
trained
them.
Additionally,
output
difficult
interpret,
which
could
pose
applications.
IEEE Transactions on Artificial Intelligence,
Год журнала:
2022,
Номер
4(4), С. 799 - 819
Опубликована: Июль 28, 2022
Artificial
intelligence
(AI)
has
profoundly
changed
and
will
continue
to
change
our
lives.
AI
is
being
applied
in
more
fields
scenarios
such
as
autonomous
driving,
medical
care,
media,
finance,
industrial
robots,
internet
services.
The
widespread
application
of
its
deep
integration
with
the
economy
society
have
improved
efficiency
produced
benefits.
At
same
time,
it
inevitably
impact
existing
social
order
raise
ethical
concerns.
Ethical
issues,
privacy
leakage,
discrimination,
unemployment,
security
risks,
brought
about
by
systems
caused
great
trouble
people.
Therefore,
ethics,
which
a
field
related
study
issues
AI,
become
not
only
an
important
research
topic
academia,
but
also
common
concern
for
individuals,
organizations,
countries,
society.
This
paper
give
comprehensive
overview
this
summarizing
analyzing
risks
raised
guidelines
principles
issued
different
approaches
addressing
methods
evaluating
ethics
AI.
Additionally,
challenges
implementing
some
future
perspectives
are
pointed
out.
We
hope
work
provide
systematic
researchers
practitioners
field,
especially
beginners
discipline.
ISME Communications,
Год журнала:
2022,
Номер
2(1)
Опубликована: Окт. 6, 2022
Abstract
The
many
microbial
communities
around
us
form
interactive
and
dynamic
ecosystems
called
microbiomes.
Though
concealed
from
the
naked
eye,
microbiomes
govern
influence
macroscopic
systems
including
human
health,
plant
resilience,
biogeochemical
cycling.
Such
feats
have
attracted
interest
scientific
community,
which
has
recently
turned
to
machine
learning
deep
methods
interrogate
microbiome
elucidate
relationships
between
its
composition
function.
Here,
we
provide
an
overview
of
how
latest
studies
harness
inductive
prowess
artificial
intelligence
methods.
We
start
by
highlighting
that
data
–
being
compositional,
sparse,
high-dimensional
necessitates
special
treatment.
then
introduce
traditional
novel
discuss
their
strengths
applications.
Finally,
outlook
pipelines,
focusing
on
bottlenecks
considerations
address
them.
International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2023,
Номер
125, С. 103569 - 103569
Опубликована: Ноя. 18, 2023
Researchers
and
engineers
have
increasingly
used
Deep
Learning
(DL)
for
a
variety
of
Remote
Sensing
(RS)
tasks.
However,
data
from
local
observations
or
via
ground
truth
is
often
quite
limited
training
DL
models,
especially
when
these
models
represent
key
socio-environmental
problems,
such
as
the
monitoring
extreme,
destructive
climate
events,
biodiversity,
sudden
changes
in
ecosystem
states.
Such
cases,
also
known
small
pose
significant
methodological
challenges.
This
review
summarises
challenges
RS
domain
possibility
using
emerging
techniques
to
overcome
them.
We
show
that
problem
common
challenge
across
disciplines
scales
results
poor
model
generalisability
transferability.
then
introduce
an
overview
ten
promising
techniques:
transfer
learning,
self-supervised
semi-supervised
few-shot
zero-shot
active
weakly
supervised
multitask
process-aware
ensemble
learning;
we
include
validation
technique
spatial
k-fold
cross
validation.
Our
particular
contribution
was
develop
flowchart
helps
users
select
which
use
given
by
answering
few
questions.
hope
our
article
facilitate
applications
tackle
societally
important
environmental
problems
with
reference
data.
Computer Science & IT Research Journal,
Год журнала:
2024,
Номер
5(2), С. 415 - 431
Опубликована: Фев. 18, 2024
In
the
contemporary
business
landscape,
proliferation
of
Big
Data
has
revolutionized
way
organizations
gather,
process,
and
utilize
information
for
strategic
decision-making.
This
paper
provides
a
comprehensive
overview
evolving
role
Business
Intelligence
(BI)
in
harnessing
potential
subsequent
impact
on
gaining
competitive
advantage.
The
review
delves
into
arsenal
analytical
tools
that
have
emerged
to
handle
vast
volumes
data
generated
digital
age.
From
traditional
reporting
querying
advanced
analytics,
machine
learning,
predictive
modeling,
now
myriad
options
extract
valuable
insights
from
their
reservoirs.
investigates
efficiency,
scalability,
adaptability
these
context
Data,
emphasizing
transforming
raw
actionable
intelligence.
Furthermore,
explores
how
integration
BI
analytics
contributes
development
edge
businesses.
ability
harness
diverse
sources
with
holistic
view
market
trends,
consumer
behavior,
operational
efficiency.
This,
turn,
empowers
decision-makers
make
informed
timely
choices,
enhancing
overall
organizational
agility
responsiveness
dynamics.
study
also
highlights
challenges
associated
implementing
era
including
issues
related
quality,
security,
need
skilled
professionals.
Effective
solutions
are
discussed,
importance
robust
governance
framework
continuous
investment
talent
development.
underscores
pivotal
leveraging
As
navigate
complexities
modern
judicious
use
stand
as
key
drivers
decision-making
sustainable
success.
Keywords:
Intelligence,
Analytical
Tool,
Business,
AI,
Review.
IEEE Access,
Год журнала:
2024,
Номер
12, С. 25553 - 25579
Опубликована: Янв. 1, 2024
In
the
context
of
a
more
linked
and
globalized
society,
significance
proficient
cross-cultural
communication
has
been
increasing
to
position
utmost
importance.
Language
functions
as
crucial
medium
that
establishes
connections
among
people,
corporations,
countries,
thus
demanding
implementation
precise
effective
translation
systems.
This
comprehensive
review
paper
aims
contribute
evolving
landscape
AI-driven
language
by
critically
examining
existing
literature,
identifying
key
debates,
uncovering
areas
innovation
limitations
where
primary
objective
-is
provide
nuanced
understanding
current
state
translation,
along
with
emphasizing
advancements,
challenges,
ethical
considerations.
this
review,
ongoing
debates
surrounding
translations
were
actively
involved.
By
evaluating
different
viewpoints
methodologies,
insights
into
unresolved
questions
broader
discourse
in
field
provided.
The
future
trajectory
study
is
incorporation
cross-lingual
dialect
adaptability
advancement
Artificial
Intelligence
systems,
focus
on
prioritizing
inclusion
cultural
understanding.
Computer Science & IT Research Journal,
Год журнала:
2024,
Номер
5(3), С. 562 - 575
Опубликована: Март 9, 2024
In
today's
data-driven
world,
the
ability
to
effectively
leverage
big
data
and
analytics
has
become
a
key
driver
of
business
development
across
sectors.
This
comprehensive
review
explores
strategies
for
leveraging
drive
development,
focusing
on
trends,
challenges,
best
practices.
The
begins
by
highlighting
importance
in
enabling
companies
gain
actionable
insights
from
vast
amounts
data.
It
then
examines
various
analytics,
including
collection,
processing,
analysis,
visualization.
Key
trends
field
are
discussed,
such
as
increasing
use
artificial
intelligence
machine
learning
automate
analysis
processes.
also
addresses
challenges
associated
with
privacy
security
concerns,
offers
solutions
overcome
these
challenges.
Best
practices
outlined,
quality,
governance,
collaboration
departments.
Case
studies
sectors,
healthcare,
finance,
retail,
presented
illustrate
successful
implementations
strategies.
conclusion,
emphasizes
competitive
landscape.
highlights
need
adopt
strategic
approach
management
unlock
full
potential
their
edge
respective
industries.
Keywords:
Strategies,
Big
Data,
Analytics,
Business
Development:
Leveraging.
Artificial Intelligence Review,
Год журнала:
2024,
Номер
57(8)
Опубликована: Июль 23, 2024
Abstract
Prognostics
and
health
management
(PHM)
is
critical
for
enhancing
equipment
reliability
reducing
maintenance
costs,
research
on
intelligent
PHM
has
made
significant
progress
driven
by
big
data
deep
learning
techniques
in
recent
years.
However,
complex
working
conditions
high-cost
collection
inherent
real-world
scenarios
pose
small-data
challenges
the
application
of
these
methods.
Given
urgent
need
data-efficient
academia
industry,
this
paper
aims
to
explore
fundamental
concepts,
ongoing
research,
future
trajectories
small
domain.
This
survey
first
elucidates
definition,
causes,
impacts
tasks,
then
analyzes
current
mainstream
approaches
solving
problems,
including
augmentation,
transfer
learning,
few-shot
techniques,
each
which
its
advantages
disadvantages.
In
addition,
summarizes
benchmark
datasets
experimental
paradigms
facilitate
fair
evaluations
diverse
methodologies
under
conditions.
Finally,
some
promising
directions
are
pointed
out
inspire
research.
