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Biological Information Processing in Single Microtubules
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In: DTIC (2014)
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| 2 |
Using Target Network Modelling to Increase Battlespace Agility
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In: DTIC (2013)
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Abstract:
Battlespace agility is a warfighting concept defined as the speed at which the warfighting organisation is able to transform knowledge into actions for desired effects in a battlespace. If the Commander, the intelligence shop, and the operations people cannot draw a common picture of their battlespace, it is unlikely that the ensuing military operations will produce the desired effects. Ideally, the Commander, the intelligence silo, and the operations planning silo should have a common understanding of the battlespace in which they are fighting. The objective of this paper is to highlight one emerging communicative approach that has proven effective in facilitating shared situational awareness and understanding, called target network modelling (TNM). The paper will introduce readers to TNM as a communications methodology for making the military organization more agile in the battlespace by improving its ability to share situational awareness and understanding. It aspires to convince a unit's Commander, intelligence officers, and operational planners to strive for a structured set of common mental models to define the battlespace before engaging in operational planning. ; Presented at the 18th International Command and Control Research and Technology Symposium (ICCRTS) C2 in Underdeveloped, Degraded and Denied Operational Environments held in Alexandria, VA, on 19-21 June 2013. U.S. Government or Federal Rights License.
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Keyword:
*ASYMMETRIC WARFARE; *BATTLEFIELDS; *BATTLESPACE AGILITY; *COMMAND AND CONTROL SYSTEMS; *INTELLIGENCE ANALYSIS; *MILITARY INTELLIGENCE; *MILITARY PLANNING; *NETWORKS; *OPERATIONAL PLANNING; *SITUATIONAL AWARENESS; *TARGET NETWORK MODELING; *TARGETING; ADVANCED JOINT INTELLIGENCE ANALYSIS COURSE; AFGHANISTAN CONFLICT; BRIEFING CHARTS; CASE STUDIES; CENTER OF GRAVITY; Command; Control and Communications Systems; DANISH BATTLEGROUP TEAM 10; DECISION MAKING; FOREIGN REPORTS; HELMAND(AFGHANISTAN); INFORMATION EXCHANGE; INTEROPERABILITY; Military Intelligence; PMESII(POLITICAL MILITARY ECONOMIC SOCIAL INFRASTRUCTURE INFORMATION DOMAINS); PROJECT CROWS NEST; PROJECT KITAE TARGETING; SYMPOSIA; TARGET NETWORK MODELLING; Unconventional Warfare
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URL: http://www.dtic.mil/docs/citations/ADA590150
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA590150
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| 3 |
Enabling Efficient Intelligence Analysis in Degraded Environments
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In: DTIC (2013)
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| 4 |
An Approach Using MIP Products for the Development of the Coalition Battle Management Language Standard
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In: DTIC (2013)
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| 6 |
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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| 7 |
Interacting with Multi-Robot Systems Using BML
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In: DTIC (2013)
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| 8 |
QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents
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In: DTIC (2012)
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| 9 |
Conference Report: Cultural and Linguistic Advancement for Mission Success: Enhancing Language, Regional and Cultural Capabilities Across Whole of Government for an Effective COIN Strategy
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In: DTIC (2012)
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| 10 |
Compressed Domain Automatic Level Control Based on ITU-T G.722.2
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In: DTIC (2012)
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| 11 |
Trends in Human-Computer Interaction to Support Future Intelligence Analysis Capabilities
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In: DTIC (2011)
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| 12 |
An Intelligence Process Model Based on a Collaborative Approach
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In: DTIC (2011)
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| 13 |
A Smarter Common Operational Picture: The Application of Abstraction Hierarchies to Naval Command and Control
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In: DTIC (2011)
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| 14 |
Semantic Analysis of Military Relevant Texts for Intelligence Purposes
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In: DTIC (2011)
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| 15 |
Multilingual Content Extraction Extended with Background Knowledge for Military Intelligence
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In: DTIC (2011)
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| 16 |
Related Entity Finding: University of Waterloo at TREC 2010 Entity Track
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In: DTIC (2010)
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| 18 |
A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
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In: DTIC (2009)
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| 19 |
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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