| 000 | 03010nam a22003015i 4500 | ||
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| 001 | 402083 | ||
| 003 | DE-He213 | ||
| 005 | 20240514120046.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240307s2024 si | o |||| 0|eng d | ||
| 020 | _a9789819992195 | ||
| 024 | 7 |
_a10.1007/978-981-99-9219-5 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aTA1-2040 _b2024 EB |
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| 245 | 0 | 0 |
_aGeo-Sustainnovation for Resilient Society : _bSelect Proceedings of CREST 2023 _cedited by Hemanta Hazarika, Stuart Kenneth Haigh, Babloo Chaudhary, Masanori Murai, Suman Manandhar |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aSingapore _bSpringer International Publishing _c2024 |
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| 300 | _a1 recurso en línea | ||
| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
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| 490 | 0 |
_aLecture Notes in Civil Engineering _x2366-2565 _v446 |
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| 505 | 0 | _aPART I: Information Based (AI, IoT, VR etc.) Measures for Natural Disaster Mitigation -- Chapter 1. A Stratigraphic Classification Estimation Method by the D-Layer Neural Networks -- Chapter 2. An Approach for Evacuation Vulnerability Assessment with Consideration of Predicted Evacuation Time -- Chapter 3. Development and Applicability Assessment of a Tunnel Face Monitoring System Against Tunnel Face Collapse -- Chapter 4. Development of Real-time Measuring System of Tip Position with Deep Mixing Methods -- Chapter 5. Evaluation of Landslide Triggering Mechanism during Rainfall in Slopes Containing Vertical Cracks -- Chapter 6. Landslide Risk Prediction and Regional Dependence Evaluation Based on Disaster History Using Machine Learning and Deep Learning -- Chapter 7. Machine Learning for Estimation of Surface Ground Structure by H/V Spectral Ratio -- Chapter 8. Regular Deformation-Based Landslide Potential Detection with DInSAR - A Case Study of Taipei City -- Chapter 9. Utilization of AI-BasedDiagnostic Imaging for Advanced and Efficient Tunnel Maintenance. etc. | |
| 520 | _aThis book presents select proceedings of the 2nd International Conference on Construction Resources for Environmentally Sustainable Technologies (CREST 2023), and focuses on sustainability, promotion of new ideas and innovations in design, construction and maintenance of geotechnical structures with the aim of contributing towards climate change adaptation and disaster resiliency to meet the UN Sustainable Development Goals (SDGs). It presents latest research, information, technological advancement, practical challenges encountered, and solutions adopted in the field of geotechnical engineering for sustainable infrastructure towards climate change adaptation. This volume will be of interest to those in academia and industry alike. | ||
| 942 |
_2lcc _cLE |
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| 988 | _aSpringer_Engineering_2024 | ||
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-99-9219-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
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