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Improving Disaster Resilience and Mitigation - IT Means and Tools [Paperback]

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  • Category: Books (Computers)
  • ISBN-10:  9401791384
  • ISBN-10:  9401791384
  • ISBN-13:  9789401791380
  • ISBN-13:  9789401791380
  • Publisher:  Springer
  • Publisher:  Springer
  • Pages:  344
  • Pages:  344
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Mar-2014
  • Pub Date:  01-Mar-2014
  • SKU:  9401791384-11-SPRI
  • SKU:  9401791384-11-SPRI
  • Item ID: 100970882
  • List Price: $169.99
  • Seller: ShopSpell
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  • Delivery by: Dec 31 to Jan 02
  • Notes: Brand New Book. Order Now.

The focus of this volume is comprised of the fundamentals, models, and information technologies (IT) methods and tools for disaster prediction and mitigation. A more detailed list of topics includes mathematical and computational modeling of processes leading to or producing disasters, modeling of disaster effects, IT means for disaster mitigation, including data mining tools, knowledge-based and expert systems for use in disaster circumstances, GIS-based systems for disaster prevention and mitigation and equipment for disaster-prone areas. A specific type or class of disasters (natural or human-made), however will not be part of the main focus of this work. Instead, this book was conceived to offer a comprehensive, integrative view on disasters, seeking to determine what various disasters have in common. Because disaster resilience and mitigation involve humans, societies and cultures, not only technologies and economic models, special attention was paid in this volume to gain a comprehensive view on these issues, as a foundation of the IT tool design.

Part I: Fundamentals and Modeling.- Survey of IC&T in disaster mitigation and disaster situation management; H.-N. L. Teodorescu.- Organizations under siege: innovative adaptive behaviors in work organizations; A.Kirschenbaum, C. Rapaport.- Risk perception and communication; F. Bouder.- Establishing social resilience with (public-private partnership)-based BCM (Business Continuity Management); K. Watanabe.- A model for the spatio-temporal distribution of population using country-wide statistical data and its application to the estimation of human exposure to disasters; K. Himoto, J. Kimata.- From noise to knowledge: smart city-responses to disruption; J. Noennig, P. Schmiedgen.- Challenges of image-based crowd-sourcing for situation awareness in disaster management; G. Moreau et al.-Foresight and forecast for prevention, mitigation and recovering after social, technical and environml³-

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