Change Detection in Social Networks

Abstract

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)July 2008 ARL-TR-4514 SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR/MONITOR'S ACRONYM(S) SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution is unlimited. SUPPLEMENTARY NOTES ABSTRACTThis report describes further development in the formulation of a primer model that is compatible with the ARL-NGEN3 code and smallcaliber weapons that takes in account multidimensional, multiphase interior ballistics codes, which employ coupled Eulerian-Lagrangian schemes to explicitly treat both the gas and solid phase. The model is based on the One Dimensional Turbulence modeling approach that has recently emerged as a powerful tool in multiphase simulations. Initial results are shown for the model run as a stand-alone code and are compared to recent experiments with small-caliber primers. Integration of the primer model with the Army's ARL-NSRG computational fluid dynamics code is presented and the results are compared to experiments with small-caliber primers fired into empty test chambers. It is proposed that this further progress sets the stage for coupling the primer model to the ARL-NGEN3 code.

An overview and perspective on social network monitoring

“…In their papers, McCulloh and Carley (2008a, b), McCulloh et al (2008) and McCulloh and Carley (2011) used monitoring methods such as the cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) charts to detect changes in the network as a whole. For information on these two types of charts, we recommend Hawkins (2014).…”

Monitoring dynamic networks: A simulation‐based strategy for comparing monitoring methods and a comparative study

“…A reasonably straightforward and intuitive approach for monitoring network change is to monitor summary statistics that describe the network over time. In a series of papers, McCulloh and Carley 27,28,24 and McCulloh et al 29 use control charts such as the cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts to monitor global network summary statistics. In particular, global network summaries such as average betweenness and average closeness are used as inputs to these control charts.…”