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Engaging researchers with data management : the cookbook / / Connie Clare [and seven others]
| Engaging researchers with data management : the cookbook / / Connie Clare [and seven others] |
| Autore | Clare Cassandra |
| Pubbl/distr/stampa | Open Book Publishers, 2019 |
| Descrizione fisica | 1 online resource (xiv, 153 pages) : illustrations |
| Disciplina | 004 |
| Collana | Open Reports series |
| Soggetto topico | Electronic data processing |
| Soggetto non controllato |
Effective Research Data Management
RDM data research integrity reproducible research support to researchers |
| ISBN | 1-78374-799-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Acknowledgements -- Foreword -- I. Introduction -- II. Methodology -- III. How to Use this Cookbook -- CASE STUDIES -- 1. Research Data Management Policy: The Holy Grail of Data Management Support? -- 2. Finding Triggers for Engagement -- 3. Engagement through Training -- 4. Dedicated Events to Gauge Interest and Build Networks -- 5. Networks of Data Champions -- 6. Dedicated Consultants to Offer One-to-One Support with Data -- 7. Interviews and Case Studies -- 8. Engage with Senior Researchers through Archiving -- Contributors -- List of Illustrations and Tables. |
| Record Nr. | UNINA-9910342949903321 |
Clare Cassandra
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| Open Book Publishers, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing
| Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing |
| Autore | Lee Saro |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (438 p.) |
| Soggetto non controllato |
artificial neural network
model switching sensitivity analysis neural networks logit boost Qaidam Basin land subsidence land use/land cover (LULC) naïve Bayes multilayer perceptron convolutional neural networks single-class data descriptors logistic regression feature selection mapping particulate matter 10 (PM10) Bayes net gray-level co-occurrence matrix multi-scale Logistic Model Trees classification Panax notoginseng large scene coarse particle grayscale aerial image Gaofen-2 environmental variables variable selection spatial predictive models weights of evidence landslide prediction random forest boosted regression tree convolutional network Vietnam model validation colorization data mining techniques spatial predictions SCAI unmanned aerial vehicle high-resolution texture spatial sparse recovery landslide susceptibility map machine learning reproducible research constrained spatial smoothing support vector machine random forest regression model assessment information gain ALS point cloud bagging ensemble one-class classifiers leaf area index (LAI) landslide susceptibility landsat image ionospheric delay constraints spatial spline regression remote sensing image segmentation panchromatic Sentinel-2 remote sensing optical remote sensing materia medica resource GIS precise weighting change detection TRMM traffic CO crop training sample size convergence time object detection gully erosion deep learning classification-based learning transfer learning landslide traffic CO prediction hybrid model winter wheat spatial distribution logistic alternating direction method of multipliers hybrid structure convolutional neural networks geoherb predictive accuracy real-time precise point positioning spectral bands |
| ISBN | 3-03921-216-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367564103321 |
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Lee Saro
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Reproducibility and Rigour in Computational Neuroscience
| Reproducibility and Rigour in Computational Neuroscience |
| Autore | Crook Sharon |
| Pubbl/distr/stampa | Frontiers Media SA, 2020 |
| Descrizione fisica | 1 electronic resource (279 p.) |
| Soggetto topico |
Science: general issues
Neurosciences |
| Soggetto non controllato |
reproducible research
model sharing model validation replicability code generation model parameterization |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557251203321 |
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Crook Sharon
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| Frontiers Media SA, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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