Network Centric Command Decision Services Netcds For The Component Numbered Air Force 7th Air Force Korea And 13th Air Force


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Network-Centric Command Decision Services (netCDS) for the Component Numbered Air Force (7th Air Force Korea and 13th Air Force).


Network-Centric Command Decision Services (netCDS) for the Component Numbered Air Force (7th Air Force Korea and 13th Air Force).

Author:

language: en

Publisher:

Release Date: 2008


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The structure of the United States Air Force is changing with Headquarters United States Air Force Program Directive 06-09, entitled "Implementation of the Chief of Staff of the Air Force Direction to Establish Force Component Organization," As Component Number Air Forces (C-NAF) operationalize the directive, Command and Control systems must adapt with a network centric environment that supports distributed operations between the tactical and operational levels of war, to include reachback for shared resources and capabilities. C2 systems are required to enable the commanders to quickly focus on priority issues with appropriate and sufficient information to make decisions or to monitor tasks that the AFFOR Staff is executing. The AFFOR Staff requires enhanced situational awareness and collaboration capability to plan, monitor, and sustain operations. This requirement will enable the AFFOR staff to actively think and innovate with a focus on airpower analysis, planning, and execution - not a battle rhythm synchronized around static tools such as briefing slides and spreadsheets. This paper reports an action research case analysis of the employment of a network centric command decision service (netCDS) at the 7th and 13th Air Forces over an 18 to 24 month period. Critical guiding principals for this case analysis are the Network Centric Operations (NCO) framework, technology adoption and the Technology Transition Model as well as decision-making and human communication theories that can be used to examine and explain the behavior of users of network centric operation systems.

Risk Modeling for Hazards and Disasters


Risk Modeling for Hazards and Disasters

Author: Gero Michel

language: en

Publisher: Elsevier

Release Date: 2017-08-29


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Risk Modeling for Hazards and Disasters covers all major aspects of catastrophe risk modeling, from hazards through to financial analysis. It explores relevant new science in risk modeling, indirect losses, assessment of impact and consequences to insurance losses, and current changes in risk modeling practice, along with case studies. It also provides further insight into the shortcomings of current models and examines model risk and ideas to diversify risk assessment. Risk Modeling for Hazards and Disasters instructs readers on how to assess, price and then hedge the losses from natural and manmade catastrophes. This book reviews current model development and science and explains recent changes in the catastrophe modeling space, including new initiatives covering uncertainty and big data in the assessment of risk for insurance pricing and portfolio management. Edited by a leading expert in both hazards and risk, this book is authored by a global panel including major modeling vendors, modeling consulting firms, and well-known catastrophe modeling scientists. Risk Modeling for Hazards and Disasters provides important insight into how models are used to price and manage risk. - Includes high profile case studies such as the Newcastle earthquake, Hurricane Andrew and Hurricane Katrina - Provides crucial information on new ideas and platforms that will help address the new demands for risk management and catastrophe risk reporting - Presents the theory and practice needed to know how models are created and what is and what is not important in the modeling process - Covers relevant new science in risk modeling, indirect losses, assessment of impact and consequences to insurance losses, and current changes in risk modeling practice, along with case studies

Internet of Things and Big Data Technologies for Next Generation Healthcare


Internet of Things and Big Data Technologies for Next Generation Healthcare

Author: Chintan Bhatt

language: en

Publisher: Springer

Release Date: 2017-01-01


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This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the context of e-health. Moreover, the book addresses healthcare systems that handle large volumes of data driven by patients’ records and health/personal information, including big-data-based knowledge management systems to support clinical decisions. Several of the issues faced in storing/processing big data are presented along with the available tools, technologies and algorithms to deal with those problems as well as a case study in healthcare analytics. Addressing trust, privacy, and security issues as well as the IoT and big-data challenges, the book highlights the advances in the field to guide engineers developing different IoT devices and evaluating the performance of different IoT techniques. Additionally, it explores the impact of such technologies on public, private, community, and hybrid scenarios in healthcare. This book offers professionals, scientists and engineers the latest technologies, techniques, and strategies for IoT and big data.