03877nam 2200481 450 991042768640332120210210164651.03-030-48099-210.1007/978-3-030-48099-8(CKB)4100000011457732(DE-He213)978-3-030-48099-8(MiAaPQ)EBC6350705(PPN)250222779(EXLCZ)99410000001145773220210210d2020 uy 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierBig data in emergency management exploitation techniques for social and mobile data /Rajendra Akerkar, editor1st ed. 2020.Cham, Switzerland :Springer,[2020]©20201 online resource (XVIII, 183 p. 97 illus., 79 illus. in color.) 3-030-48098-4 1. Introduction to Emergency Management -- 2. Big Data -- 3. Learning Algorithms for Emergency Management -- 4. Knowledge Graphs and Natural-Language Processing -- 5. Social Media Mining for Disaster Management and Community Resilience -- 6. Big Data-Driven Citywide Human Mobility Modeling for Emergency Management -- 7. Smartphone based Emergency Communication -- 8. Emergency Information Visualisation. .This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field. Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community’s vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies. Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.Emergency managementData processingBig dataNatural disastersEmergency managementData processing.Big data.Natural disasters.363.340285Akerkar RajendraMiAaPQMiAaPQMiAaPQBOOK9910427686403321Big data in emergency management2047299UNINA03065nam 2200469 450 991058305640332120230120002718.00-323-49604-00-323-48563-4(CKB)4100000000972639(MiAaPQ)EBC5253007(EXLCZ)99410000000097263920180221h20182018 uy 0engurcnu||||||||rdacontentstirdacontentrdamediardacarrierSkull base imaging /Vincent ChongSt. Louis, Missouri :Elsevier,2018.©20181 online resource (ix, 410 pages) illustrations (some color)Includes bibliographical references at the end of each chapters and index.Anterior skull base / David SY Sia, Clement Yong, James TPD Hallinan, Vincent Chong -- Imaging of the paranasal sinuses and their surgical relevance / Clement Yong, David SY Sia, James TPD Hallinan, Vincent Chong -- The sphenoid bone / James TPD Hallinan, David SY Sia, Clement Yong, Vincent Chong -- Imaging in endoscopic endonasal skull base surgery / Eric YS Ting, Fiona Ting, Ghim Song Chia, Vincent Chong -- Temporal bone inflammatory and infectious diseases / Marc Lemming -- Temporal bone tumors / Bert De Foer, Laura Wuyts, Anja Bernaerts, Joost van Dithers, Erwin Offeciers, Jan W. Casselman -- Temporal bone trauma / Bert De Foer, Abdellatif, Anja Bernaerts, Joost van Dinther, Erwin Offeciers, Jan W. Casselman -- Update on imaging of hearing loss / Lubdha M. Shah, Richard H. Wiggins III -- Imaging of the facial nerve / Theresa Kouo, Robert E. Morales, Prashant Raghavan -- Imging of the postoperative middle ear, mastoid, and internal auditory canal / Timothy L. Larson, Matthew L. Wong -- Petrous apex / Ilona M. Schmalfuss -- Imging of the cerebellopontine angle / Margaret N. Chapman, Osamu Sakai -- Jugular foramen / Chih Ching Choong, Eric T.Y. Ting, Vincent Chong -- Imaging of the craniovertebral junction / Hon-Man Liu, Ya-Fang Chen -- Skull base bone lesions i / Alexandra Borges -- Skull base bone lesions ii / Alexandra Borges -- Neurointerventional radiology for skull base lesions / Hon-Man Liu, Yen-Heng Lin."Use today's latest technology and methods to optimize imaging of complex skull base anatomy. This practical reference offers expert guidance on accurate preoperative lesion localization and the evaluation of its relationship with adjacent neurovascular structures"--Publisher's description.Skull baseEndoscopic surgerySkull baseImagingSkull Base NeoplasmsSkull baseEndoscopic surgery.Skull baseImaging.Skull Base Neoplasms617.5140592Chong Vincent886543Chong VincentMiAaPQMiAaPQMiAaPQBOOK9910583056403321Skull base imaging1979758UNINA