CURRENT WORK
Benchmarking and Performance Evaluation
February 2010 - Present
TBD
PREVIOUS WORK
Data Collection and Analysis Tool (DCAT)
September 2008 - March 2010
In parallel computing, many tasks can be performed
simultaneously. However, performance factors such
as communication, synchronization, and computation
can negatively impact the performance of parallel
machines. Current methods for locating bottlenecks
and points of failure on parallel machines can generate
a tremendous amount of data. The objective of the Data
Collection and Analysis Tool (DCAT) is to provide a
foundation for the analysis of large data sets and a
framework for network analysis.
[Thanks to
Dr. Line C. Pouchard
and Dr. Stephen Poole]
Oak Ridge Content Analysis Tool (ORCAT)
May 2008 - August 2008
ORCAT is the cousin of GeoCAT and the precursor of DCAT.
ORCAT enables the collection, storage, analysis, and display of
text and sensor data. Text data is gathered from news sources,
blogs, and aggregated searches. Sensor data comes from a
collection of MODIS
files - containing pixel readings for vegetation indices, surface
reflectance, leaf area index, temperature, and net photosynthesis.
ORCAT utilizes the same Natural Language Processing technology
as GeoCAT to annotate each text document or MODIS file with city
names and coordinates. It takes the coordinate list one step
further by plotting each point on a map.
[Thanks to
Dr. Line C. Pouchard,
Dr. Stephen Poole, Joseph Trien, and Stephenie Brown]
Geographic Coordinate Annotation Tool (GeoCAT)
May 2007 - August 2007
One of the most valuable sources of intelligence for
military agencies today is open source intelligence (OSINT).
OSINT embodies all publicly available information.
It is becoming increasingly important to intelligence analysts
as knowledge becomes globally available via the Internet.
However, the problem with OSINT is that it is so time consuming
and inefficient for an analyst to sort through all the available
information on any given subject. The goal of this project was
to use Semantic Web technologies and Natural Language Processing
(NLP) to enhance the search capabilities of software tools used
by intelligence analysts. GeoCAT utilizes NLP to find city names
within documents and annotate each document with a list of the
cities and coordinates found.
[Thanks to
Dr. Line C. Pouchard
and Joseph Trien]