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Advanced Process Monitoring for Industry 4.0
| Advanced Process Monitoring for Industry 4.0 |
| Autore | Reis Marco S |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (288 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
spatial-temporal data
pasting process process image convolutional neural network Industry 4.0 auto machine learning failure mode effects analysis risk priority number rolling bearing condition monitoring classification OPTICS statistical process control control chart pattern disruptions disruption management fault diagnosis construction industry plaster production neural networks decision support systems expert systems failure mode and effects analysis (FMEA) discriminant analysis non-intrusive load monitoring load identification membrane data reconciliation real-time online monitoring Six Sigma multivariate data analysis latent variables models PCA PLS high-dimensional data statistical process monitoring artificial generation of variability data augmentation quality prediction continuous casting multiscale time series classification imbalanced data combustion optical sensors spectroscopy measurements signal detection digital processing principal component analysis curve resolution data mining semiconductor manufacturing quality control yield improvement fault detection process control multi-phase residual recursive model multi-mode model process monitoring |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557491503321 |
Reis Marco S
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cognitive Robotics & Control
| Cognitive Robotics & Control |
| Autore | Angulo Cecilio |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 electronic resource (170 p.) |
| Soggetto topico | History of engineering & technology |
| Soggetto non controllato |
initial trajectory
trajectory optimization Bézier surface robotics open FPGAs robot control surgical robotics human-machine interaction autonomous guidance low-cost platform FPGA S-curve motion control SoC telemanipulation haptics machine learning gesture recognition upper limb rehabilitation robot particle swam optimization (PSO) artificial bee colony (ABC) Ziegler Nichols Maximum sensitivity ontology robot task planning knowledge base knowledge representation industrial collaborative robots shared robotic tasks physical human-robot interaction human intention recognition time series classification |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557116203321 |
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Angulo Cecilio
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Sensors for Human Motion Analysis
| Intelligent Sensors for Human Motion Analysis |
| Autore | Krzeszowski Tomasz |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (382 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
gait recognition
biometrics regularized discriminant analysis particle swarm optimization grey wolf optimization whale optimization algorithm FMCW vital sign XGBoost MFCC COVID-19 3D human pose estimation deep learning generalization optical sensing principle modular sensing unit plantar pressure measurement gait parameters 3D human mesh reconstruction deep neural network motion capture neural networks reconstruction gap filling FFNN LSTM BILSTM GRU pose estimation movement tracking computer vision artificial intelligence markerless motion capture assessment kinematics development machine learning human action recognition features fusion features selection recognition fall risk detection balance Berg Balance Scale human tracking elderly telemedicine diagnosis precedence indicator knowledge measure fuzzy inference rule induction posture detection aggregation function markerless human motion analysis gait analysis data augmentation skeletal data time series classification EMG pattern recognition robot cyber-physical systems RGB-D sensors human motion modelling F-Formation Kinect v2 Azure Kinect Zed 2i socially occupied space facial expression recognition facial landmarks action units convolutional neural networks graph convolutional networks artifact classification artifact detection anomaly detection 3D multi-person pose estimation absolute poses camera-centric coordinates deep-learning |
| ISBN | 3-0365-5074-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619469003321 |
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Krzeszowski Tomasz
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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