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Enterprise Model
Advanced
Statistical Theory
Distributed
Real-Time
Confirmed,
Confirmed
Rejected
Cases
Ranked
Active RT
Hypothesis
Monitoring
Data Mining
Adaptive RT Workflow Programming
• Distributed Roles, Relations, Work Orders, Flow Management
Workflow

Active surveillance, data mining and statistical
learning is a complex real-time workflow
problem. The workflow needs to be explicit
so that processes are repeatable. It requires



Meta-data: input, output, fielding, sequencing
process
Ontology, threat models and data models for data
interpretation and aggregation as each step
Adaptive configuration of roles, relations, orders
and dataflow

Model based feedback to home in on high value targets
High-Level View
Network Analysis
Hierarchical Network Views
Group
Terror Event
Fatalities
Weapon
Reason
Date
(political, religious, …)
Group Sale
Dates
Travel
Communication
Location
Toll booth events
Static View:
Long-term statistics
Location
Sales
Dealer
Victim types
(Police, civil., gov.,…)
Account
Weapon
Location
Financer
Spatio-Temporal Sequence View:
Intermediate-term sequence
Trans.
Dates
Transactions
Tripwire events
Camera events
Ticket Sensor Network Tracking View:
Counter End-game sequence
events
Sense/Act View
Location
Toll booth events
Tripwire events
Camera events
Ticket Sensor Network Tracking View:
Counter End-game sequence
events
Response
Tasks
Surveillance
Cameras
Recon.
Tripwire sensors
Ambulance resources
Network reconfiguration,
New data types
Police resources
Resource Network View
Military
Fire-fighter resources
Municipal
Sequence Extraction, Prediction,
and Feedback
Group
Sale
Date
Location
Travel Communication
Sales
Dealer
Account
Weapon
Financer
Spatio-Temporal Sequence View
Trans.
Date
Transactions
Common Sequence Model: Sales, bank transacts., travel, comm. pattern  event
RT Monitored
sequence
Prediction
Response
Task
Sequence
Sequence Extraction, Prediction,
and Feedback
Location
Toll booth events
Tripwire events
Camera events
Ticket
Sensor Network Tracking View
Counter
events
Common sequence (Tracking) Model: Sensor hits, reports, surveillance  event
RT Monitored
sequence
Prediction
Response
Task
Sequence
Putting it Together
Static
View
Network
Static
View
Network
Static
View
Network
Space/Temp
Seq. View
Network
Space/Temp
Seq. View
Network
- Network algebra (merging primitives)
- Copula models
(understanding dependencies)
- Mining algorithms
- Sequence extraction
- Prediction models
Prediction
Common sequences/prefixes
Sensor
Network
Response
Sensor
Network
Sensor
Network
Resource
Network
- Real-time
models
System View
Real Time Dynamic Network Analysis
Decision
Making
Static Network Inference & Mining
Models
Network
Control
Copula Model
Fitting
Data
Sensor
Index
Multidimensional
Index
Data
Repository
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