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Advances in Design by Metallic Materials: Synthesis, Characterization, Simulation and Applications
| Advances in Design by Metallic Materials: Synthesis, Characterization, Simulation and Applications |
| Autore | Fragassa Cristiano |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (234 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
material properties prediction
experimental data analysis ductile/spheroidal cast iron (SGI) compact graphite cast iron (CGI) Machine Learning (RF) pattern recognition Random Forest (RF) Artificial Neural Network (NN) k-nearest neighbours (kNN) tribology wear slurry erosion coating cermet spheroidal graphite cast iron pack aluminizing microstructure high-temperature oxidation resistance hybrid composite wear performance ZA27 alloy deflection plates stiffeners numerical simulation Constructal Design austenitic stainless steel tensile properties artificial neural network MIV analysis pallet rack moment-rotation curve connection experiment numerical analysis thermomechanical processing grain growth forging retained austenite bainitic microstructure extended finite element method (xFEM) polarization curve long-term operated metals hybrid materials fatigue crack growth stress intensity factors (SIF) linear regression micromagnetic testing hardness case hardening depth phase-field modeling modified damage model large-strain plasticity S355J2+N steel ductile fracture two-stage yield function copper coatings pulsating current (PC) composite hardness models creep resistance |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advances in Design by Metallic Materials |
| Record Nr. | UNINA-9910557726203321 |
Fragassa Cristiano
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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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Operationalization of Remote Sensing Solutions for Sustainable Forest Management
| Operationalization of Remote Sensing Solutions for Sustainable Forest Management |
| Autore | Mozgeris Gintautas |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (296 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
forest road inventory
total station global navigation satellite system point cloud precision density positional accuracy efficiency mangrove sustainability deforestation depletion anthropogenic natural water balance Southeast Asia Phoracantha spp unmanned aerial vehicle (UAV) multispectral imagery vegetation index thresholding analysis Large Scale Mean-Shift Segmentation (LSMS) Random Forest (RF) forest mask validation probability sampling remote sensing earth observations forestry accuracy assessment forest classification forested catchment hydrological modeling SWAT model DEM airborne laser scanning deep learning Landsat national forest inventory stand volume bark beetle Ips typographus L. pest change detection forest damage spruce Sentinel-2 damage mapping multi-temporal regression mangrove replanting restoration analytic hierarchy process UAV DJI drone machine learning forest canopy canopy gaps canopy openings percentage satellite indices Elastic Net beech-fir forests pixel-based supervised classification random forest support vector machine gray level cooccurrence matrix (GLCM) principal component analysis (PCA) WorldView-3 wildfires MaxENT risk modeling GIS multi-scale analysis Yakutia Artic Siberia phenology modelling forest disturbance forest monitoring bark beetle infestation forest management time series analysis satellite imagery landsat time series growing stock volume forest inventory harmonic regression |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557584103321 |
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Mozgeris Gintautas
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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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