摘要 :
The Defense Language Office (DLO) tasked MITRE Corporation and the RAND National Defense Research Institute (NDRI) to jointly address questions concerning the U.S. Department of Defense's (DoD's) ability to measure and track langu...
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The Defense Language Office (DLO) tasked MITRE Corporation and the RAND National Defense Research Institute (NDRI) to jointly address questions concerning the U.S. Department of Defense's (DoD's) ability to measure and track language, regional expertise, and culture (LREC) training and capabilities for general purpose forces (GPF). The objective of this task is to provide information to policymakers about the available data to track LREC training and skills, as well as available information on how LREC affects readiness and mission accomplishment. To reach the stated objective, the following research questions were addressed: (1) According to the best available data, what is the relevance of LREC training and capabilities to overall unit readiness and mission accomplishment; (2) How does DoD currently track LREC training and capabilities of GPF; (3) To what extent does this tracking adequately reflect unit readiness and the ability to accomplish missions; and (4) How can DoD improve tracking of LREC training and capabilities to adequately reflect unit readiness. Chapter 2 describes the methodology and data used in the study. Chapter 3 addresses the first research question and uses available data to assess the importance of LREC training and skills for mission readiness and mission accomplishment. Chapter 4 addresses the second research question and addresses how DoD currently tracks LREC training and skills and whether or not that tracking adequately reflects mission readiness. Finally, Chapter 5 summarizes the findings and offers recommendations for linking LREC training and skills to mission readiness and success. In addition, we include four appendixes. Appendix A lists the policies and directives we reviewed for this analysis. Appendix B lists our interviewees, and Appendix C provides the interview questions we used. Appendix D details the confidence intervals for our analysis of the Status of Forces Survey of Active- Duty Members (SOF-A).
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摘要 :
To build a global 'Social Radar,' an integrated set of capabilities supporting strategic and operational level situation awareness, alerts, and option awareness, there is a need for an overarching enterprise approach. Social Radar...
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To build a global 'Social Radar,' an integrated set of capabilities supporting strategic and operational level situation awareness, alerts, and option awareness, there is a need for an overarching enterprise approach. Social Radar's objective is to demonstrate a useful, mission focused, end-to- end environment--a dashboard of socio-cultural indicators created from online news, blogs, and social media data processed at scale, as well as decision support tools. An enterprise focused testbed for early transition of sociocultural tools requires a data-to-decision support system. Such a system needs to provide tools to allow analysts to tailor and weight the fusion of indicators, to use online sources to update simulation model parameters to evaluate courses of action, and to use outcomes of course of action models to provide quantitative metrics for indicator integration strategies. This large scope requires an analysis environment that supports the development of common output measures, management of uncertainty analyses, and system evaluation and validation. Making these items requirements from the start ensures that Social Radar is addressing the most challenging aspects for use of sociocultural data and tools to support missions. Based on ten months of work on the Social Radar prototype, the following capabilities were built: (1) federated search of all available widgets for a topic, (2) hotspots on a globe for instability monitoring, (3) ability to analyze datasets with timelines and topic cloud visualizations, (4) news search capability, and (5) use of various other analytic drilldown tools. This demonstrated the possibilities of a Social Radar when fully mature. Business process lessons learned and next steps are shared for rigorous use of analytic tools and series of tools (workflows); data, indicator, and model outcome visualization strategies (dashboards); and supporting architecture for data processed at scale and near-real time monitoring (environments).
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