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Advanced Signal Processing in Wearable Sensors for Health Monitoring
Advanced Signal Processing in Wearable Sensors for Health Monitoring
Autore Abbod Maysam
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (206 p.)
Soggetto topico Technology: general issues
History of engineering & technology
Soggetto non controllato automated dietary monitoring
eating detection
eating timing error analysis
biomedical signal processing
smart eyeglasses
wearable health monitoring
artificial neural network
joint moment prediction
extreme learning machine
Hill muscle model
online input variables
Review
ECG
Signal Processing
Machine Learning
Cardiovascular Disease
Anomaly Detection
photoplethysmography
motion artifact
independent component analysis
multi-wavelength
continuous arterial blood pressure
systolic blood pressure
diastolic blood pressure
deep convolutional autoencoder
genetic algorithm
electrocardiography
vectorcardiography
myocardial infarction
long short-term memory
spline
multilayer perceptron
pain detection
stress detection
wearable sensor
physiological signals
behavioral signals
non-invasive system
hemodynamics
arterial blood pressure
central venous pressure
pulmonary arterial pressure
intracranial pressure
heart rate measurement
remote HR
remote PPG
remote BCG
blind source separation
drowsiness detection
EEG
frequency-domain features
multicriteria optimization
machine learning
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566462503321
Abbod Maysam  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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AI and Financial Markets
AI and Financial Markets
Autore Hamori Shigeyuki
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (230 p.)
Soggetto topico Economics, finance, business & management
Soggetto non controllato algorithmic trading
Stop Loss
Turtle
ATR
community finances
fiscal flexibility
individualized financial arrangements
sustainable financial services
price momentum
hidden markov model
asset allocation
blockchain
BlockCloud
Artificial Intelligence
consensus algorithms
exchange rates
fundamentals
prediction
random forest
support vector machine
neural network
deep reinforcement learning
financial market simulation
agent based simulation
artificial market
simulation
CAR regulation
portfolio
contract for difference
CfD
reinforcement learning
RL
neural networks
long short-term memory
LSTM
Q-learning
deep learning
uncertainty
economic policy
text mining
topic model
yield curve
term structure of interest rates
machine learning
autoencoder
interpretability
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557584903321
Hamori Shigeyuki  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
AI-Based Transportation Planning and Operation
AI-Based Transportation Planning and Operation
Autore Sohn Keemin
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (124 p.)
Soggetto topico History of engineering & technology
Soggetto non controllato autoencoder
deep learning
traffic volume
vehicle counting
CycleGAN
bottleneck and gridlock identification
gridlock prediction
urban road network
long short-term memory
link embedding
traffic speed prediction
traffic flow centrality
reachability analysis
spatio-temporal data
artificial neural network
context-awareness
dynamic pricing
reinforcement learning
ridesharing
supply improvement
taxi
preventive automated driving system
automated vehicle
traffic accidents
deep neural networks
vehicle GPS data
driving cycle
micro-level vehicle emission estimation
link emission factors
MOVES
black ice
CNN
prevention
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557486603321
Sohn Keemin  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Comminution in the Minerals Industry
Comminution in the Minerals Industry
Autore Tavares Luís Marcelo M
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (214 p.)
Soggetto topico Technology: general issues
Soggetto non controllato nanoscale talc
wet milling
high-energy ball milling
ball size
aggregation
quantitative microstructural analysis
X-ray computed tomography
selective comminution
texture
structure
mineral processing
crushing
grinding
grinding behaviors
energy consumption characterization
sulfur content
heterogeneous breakage
split energy
mining operation
ore milling
ore grinding
rock
liberation
bed breakage
iron ore
comminution
saturation
piston-and-die
compaction
compression
breakage
single particle breakage
energy input
drop-weight tester
breakage modelling
grinding prediction
jaw crusher
Discrete Element Method
Particle Replacement Model
simulation
modeling
primary crushing
particle breakage
semi-autogenous grinding mill
operational hardness
energy consumption
mining
deep learning
long short-term memory
quartz
shear stress
tribochemistry
fracturing
mixed sulfides
sphalerite
galena
VSI
DEM
sand
modelling
Vertimill
Tower Mill
liner wear
fine grinding
discrete element method
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557728203321
Tavares Luís Marcelo M  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications
Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications
Autore Vitelli Massimo
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (280 p.)
Soggetto topico History of engineering & technology
Soggetto non controllato sensor network
data fusion
complex network analysis
fault prognosis
photovoltaic plants
ANFIS
statistical method
gradient descent
photovoltaic system
sustainable development
PV power prediction
artificial neural network
renewable energy
environmental parameters
multiple regression model
moth-flame optimization
parameter extraction
photovoltaic model
double flames generation (DFG) strategy
Solar cell parameters
single-diode model
two-diode model
COA
photovoltaic systems
maximum power point tracking
single stage grid connected systems
solar concentrator
spectral beam splitting
diffractive optical element
diffractive grating
PVs power output forecasting
adaptive neuro-fuzzy inference systems
particle swarm optimization-artificial neural networks
solar irradiation
photovoltaic power prediction
publicly available weather reports
machine learning
long short-term memory
integrated energy systems
smart energy management
PV fleet
clustering-based PV fault detection
unsupervised learning
self-imputation
implicit model solution
photovoltaic array
series–parallel
global optimization
partial shading
deterministic optimization algorithm
metaheuristic optimization algorithm
genetic algorithm
solar cell optimization
finite difference time domain
optical modelling
thermal image
photovoltaic module
hot spot
image processing
deterioration
linear approximation
MPPT algorithm
duty cycle
global horizontal irradiance
mathematical modeling
feed-forward neural networks
recurrent neural networks
LSTM cell
performances evaluation
clear sky irradiance
persistent predictor
photovoltaics
artificial neural networks
national power system
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557297703321
Vitelli Massimo  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Deep Learning Applications with Practical Measured Results in Electronics Industries
Deep Learning Applications with Practical Measured Results in Electronics Industries
Autore Kung Hsu-Yang
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 electronic resource (272 p.)
Soggetto non controllato faster region-based CNN
visual tracking
intelligent tire manufacturing
eye-tracking device
neural networks
A*
information measure
oral evaluation
GSA-BP
tire quality assessment
humidity sensor
rigid body kinematics
intelligent surveillance
residual networks
imaging confocal microscope
update mechanism
multiple linear regression
geometric errors correction
data partition
Imaging Confocal Microscope
image inpainting
lateral stage errors
dot grid target
K-means clustering
unsupervised learning
recommender system
underground mines
digital shearography
optimization techniques
saliency information
gated recurrent unit
multivariate time series forecasting
multivariate temporal convolutional network
foreign object
data fusion
update occasion
generative adversarial network
CNN
compressed sensing
background model
image compression
supervised learning
geometric errors
UAV
nonlinear optimization
reinforcement learning
convolutional network
neuro-fuzzy systems
deep learning
image restoration
neural audio caption
hyperspectral image classification
neighborhood noise reduction
GA
MCM uncertainty evaluation
binary classification
content reconstruction
kinematic modelling
long short-term memory
transfer learning
network layer contribution
instance segmentation
smart grid
unmanned aerial vehicle
forecasting
trajectory planning
discrete wavelet transform
machine learning
computational intelligence
tire bubble defects
offshore wind
multiple constraints
human computer interaction
Least Squares method
ISBN 3-03928-864-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910404080403321
Kung Hsu-Yang  
MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment
Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment
Autore Fuentes Sigfredo
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (114 p.)
Soggetto topico Research & information: general
Biology, life sciences
Technology, engineering, agriculture
Soggetto non controllato sensory
physicochemical measurements
artificial neural networks
near infra-red spectroscopy
wine quality
machine learning modeling
weather
consumer acceptance prediction
data fusion
emotion recognition
facial expression recognition
galvanic skin response
machine learning
neural networks
sensory analysis
avocado
cultivars
preference mapping
sensory evaluation
sensory descriptive analysis
consumer science
unifloral honeys
botanical origin
physicochemical parameters
classification
natural language processing
deep learning
sensory science
flavor lexicon
long short-term memory
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566478503321
Fuentes Sigfredo  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Implementation of Digital Technologies on Beverage Fermentation
Implementation of Digital Technologies on Beverage Fermentation
Autore Viejo Claudia Gonzalez
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (220 p.)
Soggetto topico Research & information: general
Biology, life sciences
Technology, engineering, agriculture
Soggetto non controllato sensor networks
automation
beer acceptability
beer fermentation
RoboBEER
machine learning
ultrasonic measurements
long short-term memory
industrial digital technologies
yeast morphology
automated image analysis
heat stress
vacuoles
cell size
computer vision
foam stability
image analysis
lager beer
foam retention
polyphenols
LC-ESI-QTOF-MS/MS
HPLC
medicinal plants
ginger
lemon
mint
herbal tea infusion
antioxidants
black pepper
focus group
hops
Kawakawa
off aromas
gas sensors
robotic pourer
aroma thresholds
climate change
artificial neural networks
volatile phenols
glycoconjugates
bushfires
sparkling wine
fermentation
biogenic amines
wine quality
liquid chromatography
principal component analysis
augmented reality
non-dairy yogurt
contexts
consumer acceptability
emotional responses
Fermentation
Olea europaea
respiration rate
storage conditions
transport
TeeBot
high throughput
liquid handling robot
metabolite analysis
stochastic dynamic optimisation
uncertainty
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566460503321
Viejo Claudia Gonzalez  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Information Theory and Machine Learning
Information Theory and Machine Learning
Autore Zheng Lizhong
Pubbl/distr/stampa MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (254 p.)
Soggetto topico Technology: general issues
History of engineering & technology
Soggetto non controllato supervised classification
independent and non-identically distributed features
analytical error probability
empirical risk
generalization error
K-means clustering
model compression
population risk
rate distortion theory
vector quantization
overfitting
information criteria
entropy
model-based clustering
merging mixture components
component overlap
interpretability
time series prediction
finite state machines
hidden Markov models
recurrent neural networks
reservoir computers
long short-term memory
deep neural network
information theory
local information geometry
feature extraction
spiking neural network
meta-learning
information theoretic learning
minimum error entropy
artificial general intelligence
closed-loop transcription
linear discriminative representation
rate reduction
minimax game
fairness
HGR maximal correlation
independence criterion
separation criterion
pattern dictionary
atypicality
Lempel–Ziv algorithm
lossless compression
anomaly detection
information-theoretic bounds
distribution and federated learning
ISBN 3-0365-5308-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910619463403321
Zheng Lizhong  
MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Innovative Topologies and Algorithms for Neural Networks
Innovative Topologies and Algorithms for Neural Networks
Autore Xibilia Maria Gabriella
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 electronic resource (198 p.)
Soggetto topico Information technology industries
Soggetto non controllato facial image analysis
facial nerve paralysis
deep convolutional neural networks
image classification
Chinese text classification
long short-term memory
convolutional neural network
Arabic named entity recognition
bidirectional recurrent neural network
GRU
LSTM
natural language processing
word embedding
CNN
object detection network
attention mechanism
feature fusion
LSTM-CRF model
elements recognition
linguistic features
POS syntactic rules
action recognition
fused features
3D convolution neural network
motion map
long short-term-memory
tooth-marked tongue
gradient-weighted class activation maps
ship identification
fully convolutional network
embedded deep learning
scalability
gesture recognition
human computer interaction
alternative fusion neural network
deep learning
sentiment attention mechanism
bidirectional gated recurrent unit
Internet of Things
convolutional neural networks
graph partitioning
distributed systems
resource-efficient inference
pedestrian attribute recognition
graph convolutional network
multi-label learning
autoencoders
long-short-term memory networks
convolution neural Networks
object recognition
sentiment analysis
text recognition
IoT (Internet of Thing) systems
medical applications
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557553903321
Xibilia Maria Gabriella  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui