# AISRP Investigators\' Meeting 2006

# 

# October 3 - 5, 2006

# Inn & Conference Center, College Park, MD

# 

# 

### Agenda & Abstracts 

#   {#section-3 .unnumbered}

# AISRP Investigators\' Meeting 2006

# 

# October 3 - 5, 2006

# Inn & Conference Center, College Park, MD

# 

### Tuesday, October 3, 2006 

### 

9:00 Joe Bredekamp NASA Science Mission Directorate Introductory Remarks

***Computing***

1 9:30 Alan Sussman University of Maryland Robust Grid Computing Using
Peer to Peer Services

2 9:45 Gabor Toth University of Michigan Block-Adaptive Parallel
Implicit Methods for Semirelativistic Multifluid Hall-MHD

3 10:00 Kenneth Mighell National Optical Astronomy Observatory
Parallel-Processing Astrophysical Image-Analysis Tools

4 10:15 Charles Norton Jet Propulsion Laboratory Enhancing the PYRAMID
Parallel Unstructured Adaptive Mesh Refinement Library

5 10:30 Claire Newman Caltech Multi-Scale Atmospheric Numerical Modeling
and Data Assimilation for Planetary Applications -- With a Focus on Mars

6 10:45 David Kaufmann Southwest Research Institute Improving Swift

7 11:00 Dae-Il Choi NASA Goddard Space Flight Center Simulations of
Binary Black Hole Mergers for LISA

**Lunch**

1:00 George Komar NASA Science Mission Directorate SMD Welcome

***High End Computing Program***

1:30 Tsengdar Lee \"NASA Science Mission Directorate, HEC High End
Computing Program

2:00 Jim Fischer NASA Goddard Space Flight Center Discussion Period:
Gaps and Opportunities for HEC

**Break**

***Autonomous Operations***

8 3:00 Paul Robertson MIT CSAIL Diagnosing Complex Software and Hardware

9 3:15 Ralph Lorenz JHU-APL Intelligent Sensor Network Study of Dust
Devils

10 3:30 Geb Thomas The University of Iowa Analyzing Rover Science
Operations

11 3:45 Tom Narock UMBC Extending Virtual Observatory Capabilities

12 4:00 Edward Belbruno \"IOD, Inc. and Princeton University\" Mission
Extension Using Sensitive Trajectories and Autonomous Control

13 4:15 James Dohm University of Arizona Application of Machine Learning
Technology to Martian Geology

14 4:30 Yanbin Xu Duke University A Numerical Simulation Tool for
Planetary Subsurface Radar

6:30 ***Group Dinner: Franklin\'s in Hyattsville***

### Wednesday, October 4, 2006 

### 

***Data Exploration 1***

15 9:00 Jeff Scargle NASA Ames Research Center The Search for Quantum
Gravity: A View of Space-Time on the Smallest Scale

16 9:15 Tamal Bose Utah State University Low Power Architectures for
Realtime Processing of Hyperspectral Images

17 9:30 Yang Cai Carnegie Mellon University Spatiotemporal Data Mining
System for Tracking and Modeling Ocean Object Movement

18 9:45 Ani Thakar JHU NO ABSTRACT

19 10:00 Timothy Newman University of Alabama in Huntsville \"Auroral
Phenomenon Localization, Classification, and Temporal Evolution
Tracking\"

**Break**

20 10:30 Tomasz Stepinski Lunar and Planetary Institute Automated
Identification and Characterization of Landforms on Mars

21 10:45 Jay Johnson Princeton University Novel Higher-Order Statistical
Method for Extracting Dependencies in Multivariate Geospace Data Sets

22 11:00 Michael Wise MIT NO ABSTRACT

23 11:15 Kevin Knuth SUNY at Albany Bayesian Source Separation for
Astrophysical Spectra: Application to PAHs

24 11:30 Phillip Webb UMBC/GEST ISIS Data Preservation and
Transformation

25 11:45 Ed Shaya UMCP Automated Data Analysis with Ontologies

**Lunch**

1:00 Virtual Observatory Discussion

**Data Exploration 2**

26 2:00 Aravind Dasu Utah State University An Integrated Software
Environment to Design Polymorphic Fault Tolerant Processors for Command
and Control Functions on RadHard FPGAs

27 2:15 Ashit Talukder Jet Propulsion Laboratory NO ABSTRACT

28 2:30 Jeff Shrager ISLE NO ABSTRACT

29 2:45 Erzsébet Merényi Rice University A Neural Map View of Planetary
Spectral Images for Precision Data Mining and Rapid Resource
Identification

30 3:00 Olfa Nasraoui University of Louisville Solar Loop Mining to
Support Studies of the Coronal Heating Problem

31 3:15 J. Peter Gogarten University of Connecticut Exploration of Novel
Methods to Visualize Genome Evolution.

**Break**

32 3:45 Susan Hojnacki Rochester Institute of Technology Automated
Classification of X-ray Sources for Very Large Datasets

33 4:00 Rahul Ramachandran Univ. of Alabama in Huntsville NO ABSTRACT

34 4:15 Le Gruenwald University of Oklahoma Estimating Missing Data in
Sensor Network Databases

35 4:30 Robin Morris USRA-RIACS Statistical Inference for Scientific
Instruments: Event Analysis for the Gamma-ray Large Area Space Telescope

36 4:45 Michael Way NASA Ames Research Center Virtual Sensors

### Thursday, October 5, 2006 

### 

***Data Interpretation***

37 8:30 Daniel Sorin Duke University Autonomic Computing via Dynamic
Self-Repair of Hardware Faults

38 8:45 Kaichang Di The Ohio State University Integration of Orbital,
Descent and Ground Imagery for Topographic Capability Analysis in Mars
Landed Missions

39 9:00 R. Daniel Bergeron University of New Hampshire Interactive
out-of-core visualization of very large multiresolution time series
scientific data

40 9:15 Leonard Strachan Harvard-Smithsonian Center for Astrophysics
Development of Innovative Techniques for Producing Line-of-sight
Corrected Synoptic Maps with an application for a UVCS Outflow Velocity
Database

41 9:30 Aaron Roberts NASA Goddard Space Flight Center Building and
Implementing a Virtual Sun-Solar System (Great) Observatory (VS3O)

42 9:45 James Head Brown University ADVISER

**Break**

43 10:15 Mike Turmon Jet Propulsion Laboratory NO ABSTRACT

44 10:30 Darren De Zeeuw University of Michigan A GUI for data and model
visualization

45 10:45 Thomas McGlynn NASA Goddard Space Flight Center SkyView: The
Visualization Portal for the Virtual Observatory

46 11:00 Creon Levit NASA Ames Research Center NO ABSTRACT

47 11:15 Jeffrey Jewell Jet Propulsion Laboratory NO ABSTRACT

48 11:30 Lucian Plesea Jet Propulsion Laboratory NO ABSTRACT

**Lunch**

***Infusion and the Future***

1:00 \"Infusion: AISRP and the Data Centers: Opportunities, Gaps and
Future Directions\"

2:00 Joe Bredekamp NASA Science Mission Directorate Wrap Up

# Abstracts of Investigator Presentations

**1 Alan Sussman**

**Robust Grid Computing Using Peer to Peer Services**

http://www.cs.umd.edu/projects/hpsl/chaos/ResearchAreas/P2PGrid/

Project in Year 1 of 3

Alan Sussman, Derek Richardson, Pete Keleher, Bobby Bhattacharjee,
Dennis Wellnitz

*University of Maryland*

We are working on algorithms for and implementations of a desktop grid
system that uses peer-to-peer technology. The project started this year,
so has not yet been applied to real problems.

The system will be used to build ad hoc desktop grid systems, to provide
access to computing resources for scientists on various NASA projects in
astronomy and space science.

One of the co-Is is on the Deep Impact team and will introduce the
technology into that mission team to enable sharing resources within the
team and with other collaborating teams. The other Astronomy co-I will
deploy the system on his machines for his funded NASA research problems
and also share resources with collaborators at other institutions.

No product yet.

We are building the prototype system, and in addition to further work on
algorithms and system design, plan to study the workload characteristics
of both our Astronomy collaborator applications and of existing desktop
Grid systems, to help optimize the overall behavior of our system.

**3 Kenneth Mighell**

**Parallel-Processing Astrophysical Image-Analysis Tools**

http://www.noao.edu/staff/mighell/aisr/

Project in Year 1 of 3

Kenneth Mighell/*National Optical Astronomy Observatory*

In a collaborative research effort with the Spitzer Space Telescope\'s
Infrared Array Camera (IRAC) instrument team, the PI has used his
AISR-funded MATPHOT algorithm for precise and accurate stellar
photometry with discrete Point Spread Functions to analyze IRAC Channel
1 data of a single bright isolated star and has demonstrated a new
analysis method which yields an improvement in photometric precision of
more than 100% over the best results obtained with aperture photometry.
The PI along with Julian Christou and Jack Drummond presented the paper
"Analysis of K-band imaging of the wide binary system sigma CrB with the
Lick Observatory NGS AO system\" at the SPIE Conference #6272 (Advances
in Adaptive Optics II) on 2006 May 31 in Orlando, Florida; they
demonstrated that the MATPHOT stellar photometry code can be used to
obtain milliarcsecond relative near-infrared astrometry from
ground-based state-of-the-art AO observations with moderate Strehl
ratios ranging from 30 to 60 percent.

This research effort has demonstrated that it is possible to enhance the
science return from existing instruments on NASA\'s Great Observatories
using software developed from applied information systems research.

The PI has worked closely with the Spitzer Space Telescope\'s Infrared
Array Camera (IRAC) instrument team to demonstrate that it is possible
to improve the photometric precsion of IRAC Ch1 point-source photometry
by 100 percent using an analysis method based on the MATPHOT stellar
photometry code.

Although no formal mechanism is used at this time to track the usage of
the software products of this research program, science results based on
actual usage of the software products has been and will continue to be
reported in the astrophysical literature.

The PI will enhance the performance of the MATPHOT stellar photometry
code by making it faster while adding the ability to robustly deal with
observations of crowded stellar fields obtained with lossy detectors.
The PI will continue collaborating with the Spitzer Space Telescope\'s
Infrared Array Camera (IRAC) instrument team with the goal of enhancing
the science return of existing NASA undersampleed infrared imagers like
the InSb detectors used in Ch1 and Ch2 of the IRAC instrument. The PI
will also develop parallel-processing code to quickly do high-quality
cosmic-ray removal from single and multiple space-based optical and
near-infrared observations.

**4 Charles Norton**

**Enhancing the PYRAMID Parallel Unstructured Adaptive Mesh Refinement
Library**

http://www.openchannelfoundation.org/projects/Pyramid

Project in Year 1 of 1

Charles D. Norton/*Jet Propulsion Laboratory*

The AISR aspect of this project is just starting at the beginning of
FY\'07. Nevertheless, this software has made contributions to analysis
of earthquake events in the So. California basin, as well as analysis of
the 1906 Great San Francisco Earthquake. Support for large-scale
modeling with high resolution for these events was enabled by this tool.

Applied to large scale modeling of scientific and engineering
applications, most recently for Solid Earth Active Tectonics modeling as
part of the Quakesim Project.

Development of this tool, in combination with the GeoFEST geophysical
modeling software is relevant to InSAR modeling and analysis. It is
currently being used by the international geophysics community for Earth
deformation analysis due to Earthquakes with complex rheology.

Through software distribution at the OCF website and the user community,
such as the Computational Infrastructure for Geodynamics (CIG), among
others.

We have a 1 year award to facilitate very specific improvements related
to improved mesh partitioning techniques and support for additional grid
generators such as NASTRAN. The award is focused on building a bridge to
future funding sources. We will also support application work in support
of InSAR modeling and analysis.

**5 Claire Newman**

**Multi-Scale Atmospheric Numerical Modeling and Data Assimilation for
Planetary Applications -- With a Focus on Mars**

www.planetWRF.com

Project in Year 2 of 3

Claire E. Newman, Mark I. Richardson/*Caltech*

Anthony D. Toigo/*Kobe University*

Shawn Ewald/*Caltech*

In the past year we have successfully validated the global version of
our new Mars atmospheric model (MarsWRF, the Mars version of our new
\"planetWRF model) against observations and other models; we have
produced a \'rotated pole\' version of planetWRF, which achieves better
accuracy at the geographic pole by rotating the model grid by 90
degrees, shifting filtered regions to the geographic equator; we have
supplied NCAR (the main developers of the original limited area WRF -
Weather Research and Forecasting - model) with our global WRF code, thus
feeding back into WRF\'s development; and we have submitted our first
paper describing the planetWRF model to JGR.

By developing an improved Mars atmosphere model (and subsequently Titan
and Venus models) we will provide NASA engineers and scientists with
valuable input data for mission and science planning, and will make the
model increasingly available to other scientists for their own studies
requiring either a global or mesoscale facsimile of the Martian
environment.

Data from the MarsWRF model have been used in two Scout mission
proposals, and are being used to provide sample profiles of atmospheric
data for testing of e.g. retrieval routines for such instruments as the
Mars Climate Sounder on MRO. Data from TitanWRF will soon be used to
simulate estimated trajectories in Titan\'s lower atmosphere for a
possible future balloon mission.

We currently hold a list of users of the MarsWRF model at Caltech.

Main tasks for this year are to ensure that nesting (static and dynamic)
of high-resolution grids within the main planetWRF model domain is
functioning correctly; to incorporate positive-definite tracer advection
within planetWRF (in collaboration with NCAR, who have already added
this to the original limited-area WRF model); to complete further papers
detailing the different planetary applications (initially Mars and
Titan) of the planetWRF model; and to bring the project website,
www.planetWRF.com, online.

**8 Paul Robertson**

**Diagnosing Complex Software and Hardware**

Project in Year 1 of 2

Brian C. Williams/*MIT*

We have begun the process of extending established technologies for
diagnosing faults in hardware systems to software systems.

Increasingly NASA relies on complex mixed hardware/software systems in
its satellites spacecraft and robotic devices. Software and hardware
systems are susceptible to failure during a mission and safe and
successful mission execution depends upon the ability to recognize and
diagnose problems when they occur.

The capability is currently under development for mixed
software/hardware systems. Similar

Not Applicable

See Proposal

**9 Ralph Lorenz**

**Intelligent Sensor Network Study of Dust Devils**

Project in Year 1 of 3

Ralph Lorenz/*Johns Hopkins University Applied Physics Lab*

Low cost and flexible meteorology packages have been developed, able to
respond to events of interest. Field deployment has not yet occurred
(project just started)

Dust Devils are an important factor in Mars surface operations. Dust
devils cause occasional damage to structures on Earth, and have been
implicated in a number of air accidents.

Project has just begun

Field tests of the instruments are planned, to refine the on-board event
detection and response algorithms

**10 Geb Thomas**

**Analyzing Rover Science Operations**

groklab.ecn.uiowa.edu

Project in Year 2 of 3

Geb Thomas/*The University of Iowa*

Nathalie Cabrol/*NASA Ames/SETI*

David Wettergreen, Peter Coppin/*Carnegie Mellon University*

Edmond Grin/*NASA Ames/SETI*

During the past year we finished our 2-year study of the performance of
a remote science team using a rover to search for life in the Atacama
Desert. We developed both practical recommendations and theoretical
contributions to improve the performance of the science team in future
missions. The practical contributions include demonstrating how to
better measure the performance of the science team during a rover field
test and suggestions for improving the reporting and software interfaces
used during these missions. The theoretical contributions include a
model of searching strategy and a corresponding model of which image
data should be returned for different search tasks, a statistical model
of the behavior of the scientists during the mission and a refinement of
an existing model of robot control.

These technologies are useful to NASA because they explain the role
technology and software development plays in the effectiveness that
these technologies enable. This will allow program managers and
scientists to evaluate the costs and benefits of technology investments
before, during and after missions to ensure that the maximum benefit is
received for technology investments.

Two primary groups benefited from our work last year: the rover
engineers and the scientists who used the rover. The rover designers
benefited from our careful analysis of which data products contributed
to scientific conclusions and what we observed to be the strengths and
weaknesses of different sensors in the development of scientific ideas.
The scientists received feedback about the accuracy and inaccuracy of
their various conclusions, as well as receiving information about how
their ideas were interpreted in the field. The scientists also benefited
from the fact that we spent two weeks in the field scouting various
locations, which saved them time in the field.

Others have asked us for copies of our data sets, copies of our papers,
and to provide details necessary for their scientific papers.

This year we discovered that the ambiguity in the scientists' language
and the lack of precision in their observations creates difficulties
when confirming or refuting these ideas in the field. This year we hope
to develop a prototype strategy and tool to allow scientists to
unambiguously make low-level observations without introducing an
irritating level of observation overhead.

**11 Tom Narock**

**Extending Virtual Observatory Capabilities**

Project in Year 1 of 3

Tom Narock/*UMBC*

Adam Szabo/*NASA/GSFC*

This project will extend the capabilities of existing and forthcoming
Virtual Observatories by providing automated data analysis and
processing services.

The NASA Space Physics data environment is expanding and embracing the
Virtual Observatory concept. This work will extend the capabilities of
the Virtual Observatories providing increases in productivity and
efficiency and also help to unify disparate disipline specific Virtual
Observatories

The space physics community will utilize these applications in their day
to day research use.

Through log records and collaborations with other groups and projects

First, to deploy a project web site and have basic examples of our tools
and software available. Additionally, to establish collaborations with
other groups working in similar areas.

**12 Edward Belbruno**

**Mission Extension Using Sensitive Trajectories and Autonomous
Control**

Project in Year 1 of 3

Edward Belbruno/*Innovative Orbital Design and Princeton University*

The project has uncovered new types of useful trajectories for the
motion of spacecraft about the Moon where the delta-V required to
perform inclination changes can be reduced by a factor of 12 from that
of standard methods. The same trajectories yield a reduction in the
delta-V required for altitude changes at the Moon by a factor of 5, and
the lunar capture delta-V into lunar orbit can be reduced by a factor of
11. The trajectories move in a region about the Moon where the motion is
dynamically sensitive. The methods for obtaining this new class of
trajectories are straight forward to implement, and based upon methods
of dynamical systems and, in particular, weak stability boundary theory.
This theory has been very successful in finding new low energy routes to
the Moon by this investigator, for both Japan\'s Hiten in 1991, and
ESA\'s SMART-1 in 2004. Thus, we know it works.

This new technology is very important for NASA\'s return to the Moon
since it enables new ways to orbit the Moon and perform a wide variety
of orbital changes for a small fraction of the fuel that would normally
be required. This low fuel usage can enable a spacecraft to remain in
lunar orbit for substantially longer periods of time thereby increasing
the mission duration. This is valuable for data mining. The ability of
the spacecraft to easily change inclination can enable the spacecraft to
visit more locations over the Moon in a shorter period of time and for
much less fuel. Also, the trajectories being used have the property that
they are ideal for communication satellites that can be in continuation
communication with the Earth from all locations on the lunar surface.
This implies that halo orbits are not necessary. The transfers from the
Earth are captured into these into these lunar orbit trajectories for
nearly zero delta-V. This technology is applicable to other planetary
bodies, and it also can save significant funds since it is much more
cost effective.

The new methodologies presented in this project are being used by
mission planners for new upcoming missions to the Moon for both lunar
orbiting satellites and lunar landers. This is being considered at NASA
Ames and GSFC for new missions within the next three years.

In order of priority:

> 1\. Phone and e-mail communications with colleagues.
>
> 2\. Conferences.
>
> 3\. Space news websites, such as space.com, nasawatch.com.
>
> 4\. Journal articles (but this is old news since they come out long
> after the work was done).

I plan to:

> 1\. Further refine the methods developed,
>
> 2\. Understand the underlying dynamics more thoroughly,
>
> 3\. Make further possible applications,
>
> 4\. Study ways to make the low energy motions about the Moon more
> autonomous in nature.

**13 James Dohm**

**Application of Machine Learning Technology to Martian Geology**

Project in Year 2 of 3

J.M. Dohm/*University of Arizona*

R. Wang/*Harvey Mudd College*

R. Castano, L. Scharenbroich/*Jet Propulsion Laboratory*

We are developing an intelligent system for robust detection and
accurate classification in multispectral remote sensing image data based
on machine learning and leveraging Geographic Information Systems (GIS).
In comparison to the existing methods commonly used in remote sensing
community, the proposed system aims at sensitive and robust detection
and accurate and effective classification of rare classes, such as rocks
with varying mineral assemblages, which may otherwise be very difficult
to detect and distinguish by conventional methods. The system will aid
the planetary science community in the investigation of the geological
history of Mars and other planetary bodies such as the Moon at local to
global scales. We have applied our methods to published geologic and
Thermal Emission Spectrometer (TES) hyperspectral image cube
information. The system, however, is not limited to one type of remotely
sensed data such as TES, but could be applied to other remotely sensed
information such as the Compact Reconnaissance Imaging Spectrometer for
Mars (CRISM) on the Mars Reconnaissance Orbiter (MRO) at local scales.
This system, for example, is helping us address whether the mountain
building rocks of the ancient Thaumasia highlands mountain range differ
from the basalt-basaltic andesite compositions inferred for much of
Mars. Determining the composition of the ancient Thaumasia highlands
mountain range is of first order importance since the range records an
ancient part of Mars' evolution, which includes possible Earth-like
evolutional phases such as plate tectonism, particularly during its
embryonic stages of evolution. Distinct characteristics of the mountain
range include magnetic signatures, complex tectonic structures, cuestas,
hog backs, and valley networks (characteristics similar to the mountain
ranges of Earth), revealed through Viking, Mars Odyssey (MO), and Mars
Global Surveyor (MGS) information. When compared to the ancient
mountain-forming materials, the younger plains-forming materials record
a different TES emissivity signature. This finding is consistent with
Viking-era, geological mapping-based interpretations that the
mountain-forming materials could be comprised of a diversity of rock
types. These may include ancient highly eroded and geochemically altered
crystalline igneous and/or metamorphic rocks that generally underlie
sedimentary rock sequences (including aeolian, fluvial, alluvial, and
colluvial deposits), known as basement complex. In contrast, the
plains-forming materials are mostly volcanic.

The objectives of the proposed research are consistent and relevant to
the goals of NASA. The results of this proposed investigation will have
a direct bearing on (1) the current understanding on the geologic
processes and events that have shaped the surface of Mars, (2) future
mission planning, interplanetary comparisons, and solar system
evolution, and (3) geologic mapping of Mars at global to local scales.
In addition, the proposed investigation is on target with the scientific
research objectives of the Mars Exploration Program (MEP), specifically
as reported by the Mars Exploration Program Analysis Group (MEPAG) and
the Space Studies Board Committee for Planetary Exploration (COMPLEX).

Though our intelligent system is still being developed, we believe that
the planetary science community (e.g., geologists, geochemists, and
spectroscopists of the Planetary Geology and Geophysics and Mars Data
Analysis Programs) will find our system useful in geologic, geochemical,
and spectroscopic investigations of Mars and other planetary bodies such
as the Moon at local to global scales.

We will work on developing this the 3rd year.

Based on our successes during the 2nd year, we will continue our
investigation (application, testing, and further refinement of our
intelligent system) of the second mountain range of Mars selected for
focused investigation, Coprates rise. Coprates rise is twice the size of
the Wind River Mountain Range in Wyoming (based on the work of James
Dohm, Co-I of this investigation), displaying distinct features
analogous to the terrestrial mountain ranges (e.g., hog backs and
cuestas). This mountain range does not appear to be as subdued/degraded
as the Thaumasia highlands. In addition, Coprates rise is approximately
twice the distance away from the giant Tharsis Montes shield volcanoes
relative to the southwest part of the Thaumasia highlands that was
investigated during the 2nd year; the volcanoes have been active during
geologically recent times (Amazonian Period), and thus the ancient rock
record of the Thaumasia highlands has a greater chance of being
subdued/concealed/destroyed when compared to Coprates rise. We therefore
will investigate Coprates rise to see whether: (1) the rocks of this
mountain range display a distinct TES signature when compared to the
Thaumasia highland mountain range, which includes investigating whether
the range is comprised of rock materials other than basaltic andesite,
and (2) the plains-forming materials that embay the eastern flank of the
Coprates rise mountain range vary from those that embay the northern
flank of the Thaumasia highland. This 3rd year of investigation is
significant, as the mountain ranges occur in separate geologic
provinces, and provide an optimal proofing scenario for further
development and refinement of our intelligent system. We will further
disseminate our results to the public through peer-reviewed journal
publication (preparing additional manuscripts for peer-review
publication) and conference presentation (e.g., the 38th Lunar and
Planetary Science Conference). Our efforts, which are showing promising
results, will be presented at the AISRP Investigators\' Meeting.

**14 Yanbin Xu**

**A Numerical Simulation Tool for Planetary Subsurface Radar**

Project in Year 2 of 3

Steven Cummer, Yanbin Xu/*Department of Electrical and Computer
Engineering, Duke University*

William Farrell/*NASA Goddard Space Flight Center*

Ground penetrating radar (GPR) is a relatively mature technology for a
variety of planetary subsurface remote sensing applications. Correct
interpretation of the planetary GPR data is hence the key to studying
the target ground parameters of the unknown planetary bodies. Because
the environment uncertainties, such as the subsurface features and the
ionosphere, will not only bring ambiguity to the collected GPR data but
also critically affect instrument performance, there is a compelling
need for meaningful quantitative simulation of the planetary GPR
problem, which can help bound the data interpretation and instrument
design. In the proposed research, we have developed a model to simulate
the complete planetary GPR problem from transionospheric pulse
propagation to subsurface electromagnetic scattering. The model is 2.5D,
with 3D electromagnetic fields and the capability for treating 2D
subsurface and surface inhomogeneities. This simulation tool can
quantify the detectability of key science targets, quantify the effect
of unknown environments on GPR instruments and help interpret planetary
GPR data. Based on the model, we place bounds on the ionospheric losses
and subsurface conductivity through which water can be detected on the
application of detecting Martian north polar subsurface water. And we
also help interpret the data from the MARSIS experiment.

The development of planetary GPR simulator is very relevant to NASA's
ongoing and future research on planet exploration. NASA's Mars
Exploration Program sends robotic explorers or satellites to study the
Red Planet roughly every two years. Current missions include Mars
Express which arrived at Mars in 2004 and brought it with Mars Advanced
Radar for Subsurface and Ionosphere Sounding (MARSIS). In later 2005,
another mission Mars Reconnaissance Orbiter (MRO) was launched and
brought it with a subsurface sounding radar SHARAD. The primary science
objective of both MARSIS and SHARAD is to use radar to probe Mars
surface and subsurface with different resolution, focusing on search for
water. Due to environment uncertainties, one should be careful to
interpret the collected GPR data. In this situation, our simulation tool
can run accurate numerical experimentation to help bound the data
interpretation and give range of subsurface parameters that is
consistent with realistically uncertain GPR data so that correct and
reasonable scientific conclusions on Mars surface and subsurface can be
drew.

We presented our model in the workshop on Radar Investigations of
Planetary and Terrestrial Environments held at Houston in February 2005.
We applied our model towards answering the question of whether key
Martian polar subsurface targets such as basal lakes are detectable
using orbital GPR. Scientists including those from the MARSIS team
expressed significant interest in using our model. Actually one of the
co-authors, who is in the MARSIS team, analyzed some data from the
MARSIS experiment that showed strong subsurface reflections from the
Martian south pole based on our model.

The initial version of codes for the model has been developed during the
past year. In the future we will set up a website like the AISRP Code
Archive Server which is maintained and supported by the NASA Applied
Information Science Research Program, where researchers in the planetary
community can download our codes and use it in their research work for
data analysis and instrument design. We will use the website to update
the simulation software. Algorithm descriptions and documentation will
also be available on the website. Researchers who use our codes can ask
questions and make comments, and discussions for further improvement of
our software can be also made on the website.

In the current version of the codes, we use the near-far field
transformation method to calculate the far fields received by the
receiver on the orbiter. This method implicitly assumes a slowly varying
medium and neglects reflections (the WKB approximation). In situations
where there are sharp ionospheric layers or a strong background magnetic
field, the WKB approximation will not be valid. We therefore plan to use
the 1D FDTD method to compute the broadband ionospheric propagation
response.

**15 Jeff Scargle**

**The Search for Quantum Gravity: A View of Space-Time on the Smallest
Scale**

Jeff Scargle, Michael Way, Pasquale Temi/*NASA Ames Research Center*

We have applied work on segmentation of multidimensional data to develop
new algorithms for the detection of time delays as a function of photon
energy, in order to search for the dispersion effects in gamma-ray burst
time series, as allowed by some flavors of quantum gravity theory. 

GLAST data will allow detection of such effects if they arise at the
Planck scale, as often assumed. We will demonstrate the algorithms on
simulated GLAST data and describe prospects for possible detection of
photon dispersion.

The talk will give an overview of the many theoretical approaches to the
topic of a unified physical theory of the large (gravity and cosmology)
and the small (quantum and particle physics), usually called quantum
gravity. The meaning and consequences of the notion that space-time may
be inherently discrete will be emphasized.

**16 Tamal Bose**

**Low Power Architectures for Realtime Processing of Hyperspectral
Images**

Project in Year 1 of 1

Tamal Bose, Jacob Gunther/*Utah State University*

Hyperspectral imagery is playing an increasingly important role in space
exploration, oceanography, environmental science, geology, and national
security. Hyperspectral image data provides detailed information about
the material composition of the objects within a given scene. However, a
single ground pixel of a high-altitude wide-area hyperspectral sensor is
usually quite large (30 x 30 meters square) so that a single pixel
usually images many different objects. As a result, hyperspectral
measurements are mixtures of the spectra corresponding to the different
objects. Information about all of the objects in the scene are contained
in the data but are obscured due to the mixing that takes place. Mixing
hampers scientific discovery and may even lead to incorrect conclusions
drawn from hyperspectral data. The key to unlock the full potential of
hyperspectral imagery is unmixing the data. This research has
investigated hyperspectral unmixing which is the process of finding a
combination of pure spectra that best explains the observed mixed data.
With unmixed spectral images in hand, scientists will understand how
specific materials or objects are distributed across a given scene.

There is a recent thrust by NASA to develop high-resolution
hyperspectral imaging systems for use in geo-stationary vehicles and
space missions. The mixing that naturally occurs in the spectral images
cause errors in the classification and scientific analysis. This
research is aimed at rectifying this problem by developing real-time
unmixing algorithms can be used onboard the spacecraft.

The developed algorithms can be used on geo-stationary vehicles and
space exploration missions. At the completion of this project, we expect
to be at TRL 1.5.

Our algorithms and software will be available on the project website.
The number of software downloads will be tracked. We will also keep a
log of the number of requests for details on our software and hardware
prototype.

**17 Yang Cai**

**Spatiotemporal Data Mining System for Tracking and Modeling Ocean
Object Movement**

http://datamining.itsc.uah.edu/meeting06/papers/cai_fu_cmu_2.pdf

Project in Year 2 of 2

Yang Cai/*Carnegie Mellon University*

Richard Stumpf, Timothy Wynne, Michelle Tomlinson/*NOAA*

Mohamed Abid/*Carnegie Mellon University*

Over the two years, we have accomplished following major tasks: First,
we have developed prototype software for object tracking. Our results
show that the computer vision based object tracking algorithm can help
to monitor the harmful algae across regions. It is able to automate the
visual oceanography process. Secondly, we have developed the prediction
models that combine images and numerical data sources. Results show that
the computer model can process more samples (over 2,384) than human
manual process (188) with better accuracy in positive detection and
positive accuracy. Thirdly, we have used co-variance matrix to verify
the correlation between the harmful algae and the anomaly of chlorophyll
in satellite images. Our findings confirmed the results from the
previous published relationship. We have also found a more precise
description of the relationship. Fourthly, we have developed the
Spatiotemporal Data Mining Library in MATLAB that can be used in NASA,
NOAA, and many field research and monitoring institutes or centers.

Over past 40 years, NASA collected massive data. Our technology would
help NASA to turn the data to higher level information products, e.g.
real-time ecological system monitoring, coastal management and energy
budget modeling, and so on.

Our MATLAB library can be inserted into GSFC\'s SeaWiFS database and
products, Giovani systems.

We are creating a user group mailing list.

Applying follow-up grants to keep the project going.

**19 Timothy Newman**

**Auroral Phenomenon Localization, Classification, and Temporal
Evolution Tracking**

Project in Year 1 of 3

Timothy Newman, Glynn Germany/*Univ. of Alabama in Huntsville*

C. C. Hung/*Southern Polytechnic State University*

J. Spann/*Marshall Space Flight Center*

We have developed a more robust method for auroral oval localization in
UVI imagery, benchmarked our method against the three other existing
methodologies, and we have developed schemes for content-based image
retrieval of theta aurora from UVI imagery.

Our technologies enable retrieval of imagery from a very large
collection of (8M+) images, allowing scientists to locate sets of images
related to particular phenomena they wish to study.

POLAR and IMAGE missions Members of these mission teams as well as
others who utilize the data the missions produce are users of our
product.

We record site visits for our on-line search tool. We also periodically
notice citations of our work in the literature.

We will extend the methodologies we\'ve developed to FUV data and to
substorm identification. We will also incorporate the newly-developed
method for theta-aurora detection and theta aurora imagery retrieval
into the on-line search tool.

**20 Tomasz Stepinski**

**Automated Identification and Characterization of Landforms on Mars**

Project in Year 1 of 3

Tomasz F. Stepinski/*Lunar and Planetary Institute*

Michael P. Mendenhall/*Dept. of Physics, Washington Univ. in St. Louis*

Ian Molloy/*Dept. of Computer Science, Purdue Univ.*

In 2006 we have developed the two key elements of our project: (1) a
system for machine identification and characterization of Martian impact
craters, and (2) a software for automatic mapping of valley networks on
Mars. We have developed a robust two-stage system for an automated
cataloging of craters from Martian digital topography data (DEM). In the
first stage an innovative crater-finding transform is performed on a DEM
to identify centers of potential craters, their extents, and their basic
characteristics. This stage produces a preliminary catalog. In the
second stage machine learning methods are employed to eliminate false
positives. Using MOLA derived DEMs with resolution of 1/128
degrees/pixel, we have applied our system to six large sites. The system
has identified 3217 craters, 43% more than are present in the leading
manual catalog. The extra finds are predominantly small craters that are
most difficult to account for in manual surveys. Our initial
calculations yield a training set that will be used to identify craters
over the entire Martian surface with an estimated accuracy of 95%. We
have also developed a novel, terrain morphology-based algorithm for
delineation of valley networks on Mars. This algorithm relies on a
combination of methods from fields of digital terrain analysis and image
processing to produce precise and detailed maps of valley networks. The
algorithm was applied to the Mare Tyrrhenum quadrangle on Mars, yielding
a detailed map for valley networks in the region at least an order of
magnitude larger than the largest site for which valley networks were
ever manually mapped with comparable precision. The results, reported in
the upcoming issue of Geophysical Research Letters, show an omnipresence
of valley networks in Noachian terrain, even outside the highly
dissected unit. The average drainage density is an order of magnitude
higher than the value inferred from a global map based on Viking images.
Ubiquitous presence of valley networks in Noachian points to
precipitation and the warmer, wetter climate on early Mars.

The deliverables of this project can be applied to any planet for which
digital elevation data is available. By automating some of the most
tedious aspects of data analysis these deliverables increase science
return from the available data and enable qualitatively new science
(statistical studies of landforms).

Developed software has been applied to the MOLA dataset and will yield
the global catalog of large impact craters on Mars which is more
comprehensive and valuable than existing catalogs. Because our method is
scale-independent, it can be employed to identify craters in higher
resolution DEMs derived from Mars Express HRSC images. It also can be
applied to future topography data from Mars and other planets. For
example, it may be utilized to catalog craters on Mercury and the Moon
using altimetry data to be gathered by Messenger and Lunar
Reconnaissance Orbiter spacecrafts. Valley networks delineation software
will be used to obtain precise maps of these features over the entire
surface of Mars.

Our crater finding software is already in the public domain and can be
downloaded from cratermatic.sourceforge.net. Sourceforge webpage
provides an instantaneous feedback on downloads. So far our software was
downloaded 34 times. The valley delineation software is available upon
request. So far it has been provided to Dr. Wei Luo from Department of
Geography at Northern Illinois University who has been using this
successfully.

In the coming year we are planning on using our algorithm to deliver
global catalog of Martian craters and a global map of valley networks.
We will continue to work on improving our codes. The valley delineation
algorithm will be streamlined so it can be offered as a download. A
version of this algorithm applicable to terrestrial sites will be
developed.

**21 Jay Johnson**

**Novel Higher-Order Statistical Method for Extracting Dependencies in
Multivariate Geospace Data Sets**

http://w3.pppl.gov/\~jrj/cumulant.html

Project in Year 1 of 3

Jay Johnson/*Princeton University*

Simon Wing/*Johns Hopkins University*

Tomas Gedeon/*Montana State University*

Project just started.

Novel ways to analyze higher order statistical dependencies in data sets

Multi-point measurements, data reduction, dependencies of environmental
hazards to spacecraft

publication citations, website hits

dimensional reduction of data, data preparation and collection for
analysis, application of cumlant based analysis

**23 Kevin Knuth**

**Bayesian Source Separation for Astrophysical Spectra: Application to
PAHs**

Project in Year 1 of 3

Kevin H. Knuth/*Dept. of Physics, University at Albany (SUNY)*

Duane Carbon, Louis Allamandola, Els Peeters, Charles Bauschlicher/*NASA
Ames Research Center*

We have experimented with techniques for visualizing the N-dimensional
solution space for mixtures of N PAHs. In the case of simple (low N)
mixtures, we have been able to directly examine the surprisingly complex
character of the solutions and gain insight into how the components of
the mixture interact with one another. We have implemented a Bayesian
Nested Sampling algorithm that allows us to estimate the PAH components
while simultaneously providing us valuable information about the
topography of the solution space. This enables us to see what features
of the space make this problem difficult and what information helps
makes this problem solvable.

Our proposal is specifically targeted to the Pathways to Life Program
under the component: \`\`Trace the evolution of nuclei, atoms, and
molecules that become life.\'\' Polycyclic Aromatic Hydrocarbon (PAH)
molecules, ubiquitous in our Galaxy and in external galaxies, are one of
the most important molecular species in the pathway to life. Our
research is aimed at developing and applying powerful new tools from the
information sciences for unscrambling and analyzing the mixed spectra of
these critical large molecules. The techniques we are developing will be
applicable to not only many types of astrophysical and planetary
spectra, but also mixtures of chemical species in general with potential
applications ranging from chemistry to minerology.

Too early to have developed, much less distributed applications.

The applications we develop will be made available from a NASA WWW site
as source code. The site will carry the latest version of the software,
as well as track user bug reports and problems. Registered users will be
part of a mailing list for reporting problems, bugs, fixes, and new
software versions.

We plan to extend our Year 1 efforts on uniform temperature PAH mixtures
to next develop ON-OFF MCMC procedures. We will then attack the problem
of PAH species at different temperatures. At the same time we will be
closely examining how PAH identifiability depends on changing
temperature.

**24 Phillip Webb**

**ISIS Data Preservation and Transformation**

Project completed.

Phillip A. Webb/*UMBC/GEST*

Robert. F. Benson, Joseph M. Grebowsky/*NASA/GSFC*

Dieter Bilitza/*Raytheon IIS*

Xueqin Huang/*University of Massachusetts at Lowell*

Analog to Digital (A/D) conversion of Alouette and ISIS topside sounder
data to produce digital topside sounder ionograms extending over nearly
two solar cycles from the early 1960's to the 1980's.

Equivalent to a new satellite mission with old data since many of the
digital records were never processed into film ionograms.

LWS studies involving the ionosphere-thermosphere system benefit from
improved models.

NSSDC

**25 Ed Shaya**

**Automated Data Analysis with Ontologies**

Project in Year 2 of 3

Ed Shaya, Brian Thomas, Zhenping Huang, Peter Teuben/*U. of Maryland*

We have created an ontology of astronomical terms and a GUI that allows
one to graphically construct a query based on the ontology.

The application is a top level interface to the Virtual Observatory. It
will provide a means for scientists to find, reduce, and manipulate
scientific data quickly and without the pain of writing new code.

This tool will be helpful in planning a mission and/or a mission
observation. It greatly simplifies finding related observations,
creating quick simulations of observations, and finding targets in need
of further observations.

We will require users to sign in to download software.

We will incorporate more expert knowledge on scientific relationships
between classes of data. This is how the application grows intelligence
and usefulness.

**26 Aravind Dasu**

**An Integrated Software Environment to Design Polymorphic Fault
Tolerant Processors for Command and Control Functions on RadHard FPGAs**

Project in Year 1 of 3

Aravind Dasu, Jonathan Phillips,Arvind Sudarsanam

*Dept. of Electrical and Computer Engineering. Utah State University*

Our goal is to develop a set of tools to facilitate automated derivation
of reconfigurable ASIPs for dynamic mission planning/scheduling and
navigation algorithms, through hybrid compiler/EDA approaches targeted
to FPGAs. We have started developing novel compiler/EDA algorithms to
extract data flow, control flow and memory/consumer-producer core
patterns from C programs that represent simulated annealing and kalman
filter family of algorithms. We have written C programs to represent
core functionality of C&C algorithms and compiled them into suitable
intermediate representations. We have also designed the common sub-graph
extraction algorithm in C and are the process of testing it. We are in
the process of designing polymorphic matrix-matrix multiplication cores
that will most likely be one of the results of the common
control-data-flow sub-graph extraction algorithm.

Microprocessors have been the workhorse of NASA for a long time and most
C&C (command and control) software continue to be designed in high level
programming languages such as C/C++. The microprocessor approach still
offers a good value as an execution platform due to sequential
processing components in C&C applications. But newer autonomy oriented
C&C software for space missions are becoming increasingly complex in
terms of computation requirements (on-board) for traditional
microprocessors to handle, as they have started incorporating parallel
computing components. These factors in combination with the need for
custom circuit performance has lead NASA to explore the power of
commercial, and reasonable RadHard SRAM based FPGAs by deploying them on
the mars rover mission. But the efficiency (speed, power, area, fault
tolerance) of an overlying architecture almost entirely depends on how
well the architecture is tailored to the nature of the application.
Given that C&C applications require a judicious mix of sequential
processing and spatial processing architectures, achieving efficient
designs (such as a group of polymorphic soft-core microprocessor on a
chip) require skills and analysis knowledge that can connect the nature
of the applications to the fabric of the FPGA device. Therefore, to
efficiently process C&C applications that are rich in both
program-flow-control and data-computation, and are expected to operate
in radiation environments with high reliability, it is necessary to
merge conventional sequential processing techniques (microprocessors)
with polymorphic concurrent data-paths and data-driven techniques on
malleable electronic fabrics (FPGAs) in an integrated software
development environment.

Mars exploration missions beyod 2009 such as \'scout missions\' and
\'sample return missions\' as well as misisons to frequently fly
spacecraft to the moon will benefit by the fundamental computing
technology advances our project will contribute. The tools we will
develop can be used by groups to bridge the gap between existing
software such as AUTOFILTER/CASPER and deploying the filters and
schedule algorithms they generate onto COTS radhard FPGA components on
the computing systems of spacecraft.

We will set up a web page at the university lab that will provide access
to space science users as well as research engineers in the broader
community.

We will complete the testing of the common control-data-sub-graph
extraction software on multiple Kalman filter algorithms and dynamic
scheduling algorithms. We will then extend it to perform core-control
and memory access pattern extraction based on meta-data driven
approaches. We have already implemented several matrix and vector math
operation cores in Viva and VHDL. The post place and route information
will be fed back to the graph based analysis tool to derive truly
run-time adaptable/polymorphic core data, control and memory modules. We
will also send manuscripts of our research work to IEEE conferences and
journals in the coming months.

**29 Erzsebet Merenyi**

**A Neural Map View of Planetary Spectral Images for Precision Data
Mining and Rapid Resource Identification**

http://www.ece.rice.edu/\~erzsebet/HYPEREYE.html

Project in Year 2 of 3

Erzsébet Merényi/*Rice University, Houston, TX*

William H. Farrand/*Space Science Institute, Boulder, CO*

Robert H. Brown/*University of Arizona, Tucson, AZ*

Thomas Villmann/*University of Leipzig, Leipzig, Germany*

Colin Fyfe/*University of Paisley, Paisley, Scotland*

Learning the structure of high-dimensional manifolds is a difficult
problem yet key to the transformation of a deluge of data to knowledge.
Our research focuses on advanced applications of Self-Organizing Maps
for precise manifold learning, which enables the capture of intricate
cluster structure (data mining) in data of high complexity when combined
with sophisticated visualization of the learned knowledge of the SOM.
Nuanced and high-accuracy classification of large volume,
high-dimensional, many-class data is another fundamental task that SOM
manifold learning supports. This year was heavy on the theoretical and
algorithm development side. We finished the first phase of an
interesting new research component, SOM-based "relevance learning"
tailored specifically for high-dimensional data, which finds the data
dimensions relevant for a given classification without compromising
classification accuracy. This provides an intelligent compression --
very different from PCA and wavelet transforms - without loss of target
information. We also showed through this research that in wavelet space,
the n most relevant wavelet coefficients (identified with this relevance
learning) are not the same as the n largest coefficients (customarily
taken to be the best representation of the data) -- a completely new
result. In the area of clustering, we proposed an entirely new
visualization of the knowledge learned by the SOM, which enables us to
"drape" data distribution over the 2-dimensional SOM regardless of the
dimensionality of the data space. In comparison, the most advanced
visualizations attempting to represent data distribution prior to our
work were limited to 2 or 3-dimensional data. In a connecting
theoretical topic, we contributed a refinement to the best current
measure of SOM topology preservation (which is a fundamental requirement
for a healthy SOM). This year's work resulted in 5 peer reviewed
conference papers and 2 journal papers. 3 journal papers are in
preparation.

We use these capabilities for better and faster analyses of spectral and
hyperspectral images of planetary surfaces such as finding rare
geological features in large images, detecting fine spectral differences
(that can translate to important compositional differences), producing
comprehensive mapping of many materials of interest, and intelligent
compression. All of these are much-needed components of remote sensing
missions of NASA.

Mars (Imager for Mars Pathfinder and Mars Exploration Rovers, in
collaboration with Dr. Bill Farrand, PI on Mars Data Analysis projects),
and Earth (with Bill Farrand, and Larry Rudd, U AZ) are primary study
objects. We collaborate (with PI Eliot Young) on a demanding pattern
classification problem for planetary ice spectra of Pluto (with over
2,000 spectral dimensions) and other outer Solar System objects, to
infer physical parameters such as surface temperature and grain size.

Our custom developed software, HyperEye, is tied to a specific platform
and to supporting commercial packages. It requires highly educated
\"drivers\" who understand the controls of the neural algorithms
involved, which often represent new research results (not available in
text books, journal publications or other software packages). Our
technology infusion therefore has to be gradual and on a small scale.
Our collaborators can be users in our system and learn by example. We
can deploy an executable version that can be used at a collaborator\'s
site provided the collaborator purchases the commercial support
components.

We expect more emphasis on data analyses next year, MER spectral
classifications with Dr. Bill Farrand, and VIMS image analyses (with the
VIMS PI, Prof. Bob Brown). For algorithm development, we plan a second
phase of research on intelligent compression with relevance learning,
with more Earth imagery involved; and using our new concept for the
representation of the data distribution over an SOM to make a
significant step toward automated extraction of SOM clusters (still an
unsolved problem). Publications related to this project will continue to
be posted at http://www.ece.rice.edu/\~erzsebet/publications.html .

**30 Olfa Nasraoui**

**Solar Loop Mining to Support Studies of the Coronal Heating Problem**

Project in Year 2 of 3

Olfa Nasraoui/*University of Louisville*

Joan Schmelz/*University of Memphis*

As part of Phase I of the project, targeting loops that are outside the
solar disk in EIT images, we have developed a solar loop retrieval and
mining system, that is able to sift through massive data sets downloaded
from online solar image databases and automatically discover images
containing solar loops. The system includes provision for fine-tuning
the recall/precision trade offs according to the user\'s desires. Most
users will insist on high precision, so that they do not have to discard
large proportions of the retrieved images with loops, even if this means
that they have to sacrifice some recall. We have developed a system that
works in two stages. The first stage uses low level image attributes
which are fast to compute, and is intended to be tuned to yield high
recall values (\> 90%). While the second stage classifier adds more
costly shape sensitive attributes, but takes as input only the
positively classified (recalled) images from the first stage (hence
reducing the number of images that have to be processed through the
second stage), and can be tuned to yield high precision values (\> 90%).
The above results apply to general types of loops, and will later be
extended to the special types of loops distinguished by our
collaborators. The developed system consists of three main subsystems:

> • Image Acquisition Subsystem: For retrieving images by the domain
> experts from the online EIT image repository and marking the images
> with solar loops. The blocks are then automatically extracted and
> labeled to produce the training data.
>
> • Multi-stage classifier training subsystem. For training classifiers
> (using low and high level attributes) capable of detecting loops in
> images.
>
> • Loop Mining Subsystem. This is the production mode loop image
> retrieval system that uses the trained classifiers on new images
> directly downloaded from the EIT image repository.

Some of the desirable features of the developed system include:

• Automation and Streamlining of the Entire Solar Loop Mining Process:
The solar loop mining cycle has been automated all the way from the
image downloading to the marking and label extraction, region of
interest extraction, pre-processing, training, testing, and validation.
This is enabled mostly thanks to scripting and automating all the
phases, including the development of user friendly (click and drag
based) interactive or batch style (depending on the user\'s choice)
graphical tools that help download solar images in small or big batches
in specific date intervals.

• Automated and User Friendly Image Acquisition Subsystem: A tool that
allows a user to download solar images in small or big batches from
online Web databases, in specific date intervals. The download tool can
be used in the learning/training or in the testing/deployment phase.
Also, a tool used only in the training phase, that allows a user to mark
the loop positions in the images, and saves this information as an
addendum to the FITS header. After the marking is done, a set of image
blocks, tangent to the sun circle, are automatically extracted from each
preprocessed image. Only blocks that are tangent to the sun\'s
circumference are extracted since the scope of the project in Phase I is
to detect out of disk solar loops. Furthermore, the optimal block size
and block positions are determined automatically to minimize the chance
of broken loops (among several blocks). These blocks serve as the
elementary objects used in a \"learn by example\" data mining framework
in the next stages.

• A Multi-Stage Classifier: The idea of the first stage classifier is to
filter out those blocks that are unlikely to contain loops. It is very
important to have a classifier with a very low False Negative rate (or
equivalently high True Positive rate or Recall), since we don\'t want to
lose blocks containing loops in this stage. The goal of this subsystem
is to produce computational classifier models, which are able to
discriminate image blocks that contain loops from those that do not
contain loops. This process is divided in two main stages depending on
the features used: (i) Low level features : such as intensity, texture,
etc, (ii) High-level semantic structures (solar loops): Shape
recognizers, Hough transform, scalable clustering for large data sets
(single pass, robust to noise). Because of the high computational cost
of High-level features, we have restricted the first stage classifier to
use only low level features, while allowing higher level but costlier
features in the second stage, where the stream of images to be sifted
through would have at least been abated somewhat. In order to determine
the advantage of applying preprocessing, different experiments were
performed: without preprocessing, applying despeckling, and applying
both despeckling and Gradient transformation. The latter approach proved
to be the most optimal.

• A Cost-Sensitive Classifier: In general, a classification technique
tries to minimize the global error of the classifier. In our case, this
means that we will get a low recall since the negative class (no loop)
is bigger than the positive class (the positive samples account for
around a 20% of the data set). Therefore, we had to modify a given
classifier by biasing it towards producing fewer false negatives, even
at the cost of increasing the false positives. We had investigated three
main possibilities to do this: (i) Changing the decision threshold for
those classifiers that return a vector with the probability of each
class, (ii) Modifying the training algorithm to take into account the
cost of each type of error, and then giving a higher value to the cost
of producing false negatives, (iii) Using an external method (a
meta-learner) to make any learning algorithm cost-sensitive.

The search for interesting images for coronal temperature analysis (with
coronal loops) amounts to searching for a needle in a haystack, and
therefore hinders the fast progress of science in this field. The next
generation "EIT" called MAGRITE, scheduled for launch in a few years on
NASA's Solar Dynamics Observatory, will require state of the art
techniques to sift through the massive wealth of data to support
scientific discoveries. The proposed work also addresses goals 1 and 2
of the Applied Information Systems Research (AISR), since it includes
novel information technology and computational methods that promise to
increase productivity of the OSS research and public outreach endeavors,
and would benefit the state-of-practice in space science. It also
fosters interdisciplinary collaboration spanning the space science
(Co-I) and computer science (PI) disciplines. Our proposed work will
achieve objective 4 of the AISR Program, namely increasing science and
educational return from the data through advanced knowledge discovery
methodologies.

The Coronal Heating Problem is one of the longest standing unsolved
mysteries in astrophysics. Measurements of the temperature distribution
along the loop length can be used to support or eliminate various
classes of coronal temperature models. The temperature analysis of
coronal loops is a state-of-the-art astronomy. In order to make
progress, scientific analysis requires data observed by instruments such
as EIT, TRACE, and SXT. The combination of EIT, TRACE, and SXT
information provides a powerful data set that will yield unprecedented
detail on the plasma parameters of a variety of coronal loop structures.
The biggest obstacle to completing this project is putting the data set
together. The search for interesting images (with coronal loops) is by
far the most time consuming aspect of this project. Currently, this
process is performed manually, and is therefore extremely tedious, and
hinders the progress of science in this field. Our project will develop
an approach based on data mining to quickly sift through massive data
sets downloaded from the online NASA solar image databases and
automatically discover the rare but interesting images with solar loops,
which are essential in studies of the Coronal Heating Problem. In
addition to the specific problem from Astrophysics, above, Research that
advances state of the art in solar physics will have a significant
impact on society and other scientific fields because of the following
reasons: (i) The climate connection: the sun is a source of light and
heat for life on Earth. Scientists strive to understand how it works,
why it changes, and how these changes influence the Earth, (ii) Space
weather: The sun is the source of the solar wind: flow of gases from the
sun that streams past the Earth at speeds exceeding a million miles per
hour. Disturbances in the solar wind shake the Earth's magnetic field.
Space weather can change the orbits of satellites and shorten mission
lifetimes. Excess radiation can physically damage satellites and poses a
threat to astronauts, in addition to power surges and outages on Earth,
and hence needs to be predicted. (iii) The sun as a physical laboratory:
the sun produces its energy by nuclear fusion, a process that scientists
have strived for decades to reproduce by involving hot plasmas in strong
magnetic fields. Much of solar astronomy involves observing and
understanding plasmas under similar conditions.

All the results of this project: literature, software, and outputs
(labels) of the developed classification methods on tested portions of
the different instrument databases will be made available to the public
and other interested researchers via the World Wide Web. Outputs of
classification and Hough space clustering will be saved in both ASCII
column format and XML format to facilitate data interchange with and
between different research groups. The XML schema will include derived
Semantic features (Estimated number of loops/clusters and their
confidence/density) and the assigned class labels. Tracking the usage of
our products can be accomplished by monitoring the access statistics on
the project's website, as well as searching for citations on the Web.

• Investigating different shape feature extraction techniques to improve
classification • Add an additional stage of classification to
distinguish generic loops from the more rare and specific kind of loops
that are needed in astrophysics research

• Improve the automatic block extraction and labeling process

• Continue with subsequent phases targeting different kinds of solar
loops and different instruments

**31 J. Peter Gogarten**

**Exploration of Novel Methods to Visualize Genome Evolution.**

Project in Year 2 of 3

J. Peter Gogarten, Maria Poptsova/*Department of Molecular and Cell
Biology, University of Connecticut, Storrs, CT, 06269-3125, USA*

Olga Zhaxybayeva/*Department of Biochemistry and Molecular Biology,
Dalhousie University, 5850 College Street, Halifax, NS B3H 1X5, Canada*

Lutz Hamel/*Department of Computer Science and Statistics, University of
Rhode Island, Kingston, RI 02881, USA*

We developed a new algorithm for the automated selection of gene
families from large numbers (\> 300) of different genomes.
\<http://www.bioinformatics.org/branchclust\>

We developed scripts for the automated phylogenetic analysis of these
gene families and for the extraction of bipartition data for each of
these families. Self Organizing Maps (SOMs) then are used to cluster the
gene families based on the bipartition matrix
\<http://bioinformatics.cs.uri.edu/gene-vis/template/\>.

We developed quartet decomposition as tool to identify gene transfer
events \[1\] 1. Zhaxybayeva O, Gogarten JP, Charlebois RL, Doolittle WF,
Papke RT: Phylogenetic analyses of cyanobacterial genomes:
Quantification of horizontal gene transfer events. Genome Res 2006,
16:1099-1108.

Reconstructing the evolutionary history of metabolism provides clues to
the conditions under which life on Earth originated and diversified. Due
to gene transfer the history of metabolic pathways can be different for
the evolutionary history of organisms. Untangling the evolution of
metabolism will allow recognizing which biological pathways first
impacted the biosphere, and also will allow focusing on those
environmental conditions that are conductive to the origin of life.

The BranchClust algorithm allows to assemble families of corresponding
genes from a given number of different genomes, it also provides
information on gene duplication and gene loss in each of these families.
This tool facilitates tracing the origin of metabolic pathways in
different prokaryotic lineages. Knowledge of the origin and early
evolution of metabolic pathways will allow to focus the search for life
to the most promising environmental conditions. Craig Nelson group at
the University of Connecticut has used an alpha version BranchClust to
investigate gene duplication and loss in mammalian species. The SOM
algorithm developed to dissect microbial genomes has not yet been
released to the public domain.

We currently do not track the number of software downloads or the access
to our web interface (we consider this for future releases of the
software). The ultimate measure of success will be the adoption of the
developed algorithm and software by others, and this will be reflected
in the current citation index.

In addition to extracting phylogenetic information in the form of a
bipartition matrix, we will develop and apply tools to use quartet data
as input for the SOM algorithm. Quartet decomposition (Zhaxybayeva et
al. Genome Res 2006, 16:1099-1108) avoids many pitfalls associated with
bipartition based analyses; however, it results in large and sparse data
matrices. We also will explore other clustering techniques such as Local
Linear Embedding.

**32 Susan Hojnacki**

**Automated Classification of X-ray Sources for Very Large Datasets**

Project in Year 2 of 2

Susan M. Hojnacki, Joel H. Kastner, Steven M. LaLonde/*Rochester
Institute of Technology*

Giusi Micela/*Osservatorio Astronomico di Palermo, Italy*

1\. Verification of our X-ray spectral classification algorithm using
simulated X-ray spectra.

2\. Extension of the algorithm for use with other star formation
regions.

3\. Application of algorithm to several other star formation regions.

4\. Exploration of input variables describing X-ray source variability.

A large volume of low signal-to-noise data exists from the Chandra X-ray
Observatory and XMM-Newton. Much of the data consists of large datasets
from observations of star formation regions. Despite this volume of
data, many questions are still unanswered, due largely to the lack of
automated tools to sort and analyze these large datasets. For example,
there is still some debate over the role of accretion in X-ray emission
from pre-main-sequence (PMS) stars. Also, only very weak trends have
been found when attempting to correlate model parameters derived from
spectral fitting of individual sources (e.g., X-ray luminosity and
temperature; X-ray absorbing column and visual extinction). When
completed, our research will result in a tool that uses both spectral
data and temporal properties to group and classify discrete sources of
X-ray emission. This new method will handle large quantities of data and
operate independently of the requirement of source models (spectral or
temporal) and a priori knowledge concerning the nature of the sources.
This unbiased approach can be used as a data reduction technique and
could lead to the discovery of new classes of sources that do not fit
any existing models and X-ray sources that are extreme outliers in the
spectral and/or temporal domains.

Our research is currently most relevant to the data analysis needs of
researchers using NASA's Chandra X-ray Observatory. We are working with
the ANCHORS team (An Archive of Chandra Observations of Regions of Star
Formation) to include our results in the web-based archive of over
10,000 X-ray sources. In addition, during algorithm development, we
identified algorithm inputs that are specific to X-ray wavelengths.
These have been modularized so that the algorithm can be used with other
types of sources as well as spectra from other wavelength regimes.

Our product will be completed at the end of our second year. We are
looking at the tracking methods of other AISRP Projects to see which are
most successful.

1\. Analyze the results of running the spectral classification algorithm
on five additional star formation regions and compare those results to
the Orion Nebula Cluster results.

2\. Continue work on adding temporal inputs to the spectral algorithm.

3\. Continue working with the ANCHORS team to fine-tune their processing
and add our results to their database.

4\. Develop a webpage to disseminate our X-ray spectral classification
results and algorithm.

**34 Le Gruenwald**

**Estimating Missing Data in Sensor Network Databases**

Project in Year 2 of 3

Le Gruenwald/*The University of Oklahoma*

We have developed a technique, FARM, to estimate missing sensor data
taking the temporal dimension of sensor data into consideration. The
experimental results show that FARM provides better estimation accuracy
than existing techniques. We also developed a data stream mining
algorithm, called CFI-Stream, that falitates the estimation.

For sensor networks, many sensor data are expected to be late/corrupted
due to various reasons. Being able to estimate missing data with good
quality of service in terms of accuracy and time would enable many NASA
data analysis applications to be able to complete their tasks
successfully. The data used in our experiments were from the sensor webs
project conducted by NASA JPL.

The research project is in year 2; its results have not been used by
specific programs/missions; however, the experimental results using the
NASA JPL\'s sensor webs project\'s application are of interest to many
NASA programs.

Since our software product has not been completed, it has not been made
available to public, and thus no tracking has been done. However, we
have published several journal and conference articles reporting our
research results.

In the upcoming year, we plan to perform the following tasks:

> 1\. Revise FARM to include spatial data mining;
>
> 2\. Work with NASA scientists to incorporate NASA data semantics into
> FARM.
>
> 3\. Conduct a theoretical analysis of FARM.
>
> 4\. Collect additional NASA data and conduct further performance
> evaluations.
>
> 5\. Extend FARM to include distributed sensor networks.
>
> 6\. Conduct theoretical analysis and experiments comparing FARM with
> existing data estimation techniques for distributed sensor networks
> using NASA data.
>
> 7\. Incorporate classification, clustering, and frequent closed items
> association rule mining into FARM to improve data estimation.

**35 Robin Morris**

**Statistical Inference for Scientific Instruments: Event Analysis for
the Gamma-ray Large Area Space Telescope**

Project in Year 2of 3

Robin Morris/*USRA-RIACS*

Johann Cohen-Tanugi/*SLAC - Stanford University*

Added inference for electron events into the event analysis system. This
has allowed the detection of the production of photons within the LAT
tracker that are otherwise unobserved.

The technology we are developing is targetted to the GLAST LAT, a major
NASA mission. They will also be useful for other high-energy physics
detectors.

The project is focused on the GLAST mission, as an alternative method of
event analysis.

It is available on the GLAST CVS server, but has not been formally
released outside the project team.

Add further physics to the event analysis software, culminating in the
analysis of gamma-ray events. Thoroughly test and benchmark the system
against the conventional event reconstruction methodology.

**36 Michael Way**

**Virtual Sensors**

Project in Year 1 of 1

Michael Way, Ashok Srivastava, Paul Gazis/*NASA Ames Research Center*

The ability to invert large matrices, which is integral to the success
of the project. We have applied our methods to the Photometric Redshift
problem in Cosmology.

These technologies have been used to increase the amount of useful
information obtained from Earth Science satellites and high redshift
studies of the universe.

Our product has been used with MODIS and AVHRR datasets. The MODIS team
has used our Virtual Sensors technology.

Currently via publications in the literature.

To continue working on new way to invert large matrices and apply our
results to larger and more complex datasets which is difficult at
present.

**37 Daniel Sorin**

**Autonomic Computing via Dynamic Self-Repair of Hardware Faults**

http://www.ee.duke.edu/\~sorin/faultfinder/index.html

Project in Year 2 of 3

Daniel Sorin, Sule Ozev/*Duke University*

In the past year, we have made several important contributions. We
developed an efficient, low-cost mechanism for diagnosing hard faults in
microprocessors. \[Fred A. Bower, Daniel J. Sorin, and Sule Ozev. \"A
Mechanism for Online Diagnosis of Hard Faults in Microprocessors.\" 38th
Annual International Symposium on Microarchitecture (MICRO), November
2005.\] We extended our prior work on detecting and diagnosing hard
faults in microprocessor array structures. \[Fred A. Bower, Sule Ozev,
and Daniel J. Sorin. \"Autonomic Microprocessor Execution via
Self-Repairing Arrays.\" IEEE Transactions on Dependable and Secure
Computing, October-December 2005.\] We created a self-detecting and
self-diagnosing multiplier for use in fault-tolerant microprocessors.
\[Mahmut Yilmaz, Derek R. Hower, Sule Ozev, and Daniel J. Sorin.
\"Self-Detecting and Self-Diagnosing 32-bit Microprocessor Multiplier.\"
International Test Conference (ITC), October 2006.\] We developed a new
metric for comparing the ability of different microprocessor designs to
tolerate hard faults. \[Fred A. Bower, Derek H. Hower, Mahmut Yilmaz,
Daniel J. Sorin, and Sule Ozev. \"Applying Architectural Vulnerability
Analysis to Hard Faults in the Microprocessor.\" Poster and 2-page paper
in ACM SIGMETRICS, June 2006.\] Two avenues of research branched off
from the main thrust of this project and led to exciting contributions
in related areas: We designed an efficient mechanism for comprehensively
detecting all errors in the memory systems of multithreaded servers.
\[Albert Meixner and Daniel J. Sorin. \"Dynamic Verification of Memory
Consistency in Cache-Coherent Multithreaded Computer Architectures.\"
International Conference on Dependable Systems and Networks, June
2006.\] We did an experimental study that compared existing error
protection schemes for microprocessor caches, and we developed a new
scheme that achieves the best features of both common existing schemes.
\[Nathan N. Sadler and Daniel J. Sorin. \"Choosing an Error Protection
Scheme for a Microprocessor\'s L1 Data Cache.\" International Conference
on Computer Design (ICCD), October 2006.\] This project has also helped
to support the training of several students, including Mahmut Yilmaz,
Fred Bower, and Derek Hower. Mr. Hower was an undergraduate research
fellow who has graduated and is now pursuing graduate studies in
computer architecture.

NASA missions rely upon computer infrastructure. Because NASA sends
explorers on unmanned multi-year journeys, it would benefit from
computing hardware that can autonomically detect errors and recover from
them without human intervention. While simplistic solutions to this
problem exist, such as replicating the entire computer system, these
solutions are far too costly in terms of hardware (weight) and power
consumption.

None yet.

We have not yet released a product. In general, we disseminate our
research results by (a) publishing our work in the premier academic
conferences and journals, and (b) presenting our work at NASA and at
industrial research and development labs (e.g., the PI\'s upcoming
seminar at IBM TJ Watson Research Center).

We have two main research avenues that we will be pursuing.

1\) When we detect and diagnose a hard fault in a processor, we then
have a slightly degraded system. In today\'s world of multicore
processors (e.g., Sun Niagara, Intel Core, AMD, etc.), this situation
leaves us with a processor with cores of differing capabilities. An open
research question is how to manage the resources of such a
\"heterogeneous multicore\" processor. We intend to address this issue
by having the hardware present an interface to the software (operating
system) that enables it to more efficiently schedule computation on the
cores based on their relative capabilities.

2\) Our current work on self-detecting and self-diagnosing arithmetic
units (adders and multipliers) is a start, but we need to extend it to
more sophisticated structures, like reorder buffers and instruction
schedulers. We will pursue this line of research.

**38 Kaichang Di**

**Integration of Orbital, Descent and Ground Imagery for Topographic
Capability Analysis in Mars Landed Missions**

http://shoreline.ceegs.ohio-state.edu/research/aisr/aisr.htm

Project in Year 1 of 3

Rongxing (Ron) Li, Kaichang Di, Ju Won Hwangbo/*The Ohio state
University*

We have been developing methods for photogrammetric modeling and
processing of Mars orbital images since our project started in March
2006. We have processed a pair of MOC NA images and derived a 3-D model
of Victoria Crater at Meridiani Planum, which was sent to the MER (Mars
Exploration Rover) team for rover traverse planning. These orbital
images will be integrated with descent and ground images for topographic
capability analysis.

The integration of Mars orbital, descent and ground imagery has the
potential to achieve the best possible accuracy for integrated Mars
topographic mapping capability analysis. This research directly
contributes to the high priority area of AISR program "to increase
science return from data" by integrating three types of imagery and
deriving topographic products and rover localization data that are far
better than those that can be derived from a single type of imagery.

This high accurate mapping capability will be very valuable for
planetary scientists in their studies, in regional geology, crater
mechanics and modeling, cross-site geological processes, etc. It will be
very helpful for rover mobility analysis and rover navigation strategy
development for future landed missions. The developed methods can also
be used in future missions for landing-site selection.

We will track the usage of our topographic products though peer-reviewed
publications, professional conference presentations, project reports and
personal communications.

In FY07, we will perform bundle adjustment of the individual types of
images and modify the software for integrated bundle adjustment of
orbital, descent and ground imagery.

**39 R. Daniel Bergeron**

**Interactive out-of-core visualization of very large multiresolution
time series scientific data**

http://www.cs.unh.edu/starview

Project in Year 1 of 3

R. Daniel Bergeron, Ted M. Sparr, Andrew Foulks

*Computer Science, University of New Hampshire*

We have developed the first version of a multiresolution scientific data
management framework that supports the implementation of interactive
visualization software for very large three-dimensional time series data
sets. We have implemented two different rendering algorithms within this
framework: one shows a flow field using particle tracing; the other uses
volume rendering techniques to render 3D scalar fields such as pressure
or temperature. The framework provides the renderers with support for
accessing multiresolution representations of the data without the
renderers really being aware of it. Initial full views of the data use a
low resolution representation of the data; the resolution level is
chosen to satisfy a user-specified memory utilization heuristic. As the
user zooms into a subregion of the data, the framework will
automatically access finer resolutions.

One of the major challenges facing NASA scientists is effective analysis
of the explosion of data that is being generated by current science
technology. This is particularly a problem in the simulation of
time-dependent magnetohydrodynamics (mhd) phenomena that produces
enormous data sets of many hundreds of gigabytes. It is also the case
that interactive visualization of the data is still one of the most
effective techniques for gaining insight into the physical phenomenon.
The huge size of the data, however, severely limits the ability to
visualize the data in an effective interactive environment. Our
multiresolution data management framework makes it easy to develop
interactive environments for browsing such data.

Although the conceptual framework we have developed applies to a very
wide range of scientific data, the prototype visualization environment
will focus on space science applications, particularly
magnetohydrodynamics simulation and computational fluid dynamics. These
areas represent two extremely important science research domains within
the NASA research mission.

We are still in the early stages of implementation. It will be some time
before the software is distributable.

A principal goal for the coming year is to integrate our data management
framework into the Visit environment from the Lawrence Livermore
National Laboratory. Visit provides a convenient interactive environment
and a wide range of existing visualization tools. By integrating our
data management into Visit, our users will immediately gain access to a
large existing visualization code base. Not all the functionality of our
environment, however, will be available in Visit. Our data model
supports automatic caching and prefetching of data so that not all data
need be in memory at once. Because the Visit implementation is tightly
coupled with vtk, it is heavily dependent upon the vtk data model that
assumes that all data to be visualized (except for streaming
applications) is available in main memory and accessed via a void\*
pointer. Knowledge of this convention is typically scattered throughout
Visit and vtk rendering code and can only be removed by a major
re-implementation.

**40 Leonard Strachan**

**Development of Innovative Techniques for Producing Line-of-sight
Corrected Synoptic Maps with an application for a UVCS Outflow Velocity
Database**

Project in Year 1 of 3

Leonard Strachan, Alexander V. Panasyuk, John L.Kohl

*Harvard-Smithsonian Center for Astrophysics*

C. Nick Arge/*Air Force Research Laboratory*

The primary goal of this project is to develop a set of software tools
that allow researchers to obtain empirically derived plasma parameters
of the solar corona using UVCS data. We are developing user friendly
tools and a database, together which are used to produce maps of local H
I Ly-alpha and OVI emissivities, local kinetic temperatures and outflow
velocities for H atoms and O5+ ions in the solar corona. Since this is
the first year of the project, most of the activities that will be
described are still under development. By the end of the first year, we
plan to have a complete set of calibrated coronal synoptic maps and a
preliminary version of the visualization tool for interfacing with the
data.

This work addresses the problem of predicting the space environmental
conditions that will be experienced by human explorers, and demonstrates
technologies that can improve future space weather prediction
capabilities. The software tools and coronal databases that are being
developed will maximize the utility of the UVCS/SOHO synoptic data set
by producing maps which can be used as constraints for coronal and solar
wind models. This type of data is useful in that it provides information
on the physical conditions of the corona where the solar wind is
generated. The tools and datasets will make it easier to compare coronal
data with data from solar wind data from other NASA missions (e.g. SOHO,
Ulysses, WIND, and ACE). Insights gained from the line-of-sight
reconstruction techniques may be applicable to future NASA missions such
as the upcoming STEREO mission.

We plan to make these tools and results available to MHD modeling
groups, e.g. CISM, and others who may be interested. Examples of uses of
the data from this work include using it to improve the
Wang-Sheeley-Arge model which forecasts the solar wind speeds at 1 AU,
based on expected conditions at the coronal source surface. The coronal
data can also be used to test models by comparing our empirically
derived values with those produced with MHD codes that are extrapolated
back to the corona using the plasma conditions at 1 AU. In addition to
the above, there are potential education and outreach uses.

Once a working version of the product has been completed we will install
in on a Web page and keep statistics on such information as the number
of hits, number of requests for information, and number of publications
resulting from anyone who uses this product.

For the upcoming year (FY07/08) we plan to do the following: 1) complete
the development of the software for producing the outflow velocities, 2)
test the capability for producing localized kinetic temperatures, 3)
complete the interface between the different input data sets and the
visualization software, and 4) produce a paper on the initial science
results from this work.

**41 Aaron Roberts**

**Building and Implementing a Virtual Sun-Solar System (Great)
Observatory (VS3O)**

http://vspo.gsfc.nasa.gov

Project in Year 1 of 1

D. Aaron Roberts/*NASA GSFC*

Joe King/*QSS Inc*

Carl Cornwell/*Aquilent*

Added direct access to many products. Produced direct link between
visualization and data access softwawre (VSPO and ViSBARD). Developed
registry tools. Obtained approval by Senior Review to become integrated
into the Space Physics Data Facility.

Provide efficient Heliophysics data access and multispacecraft analysis
tools.

Used access data for SR&T projects. Used for finding solar data relevant
to interplanetary events.

Currently, web hits and informal feedback; to be augmented and
formalized.

Integration into the Space Physics Data Facility; adding access to more
data; seamless end-to-end registration, harvesting, and access to
products; marketing and feedback.

**42 James Head**

ADVISER

Project in Year 2 of 3

James W Head, Andrew Forsberg, Prabhat, Sam Fulcomer, Caleb
Fassett/Brown University

Our project is designed to:

> 1\) advance space science knowledge, exploration capabilities, and
> teaching and outreach,
>
> 2\) research advanced visualization tools for space science and
> education, through ADVISER (Advanced Visualization in Solar System
> Exploration and Research), a problem-solving environment (PSE) for
> planetary geosciences that will integrate and extend the state of the
> art in hardware and software technologies.

Our approach is to put geoscientists on or near planetary surfaces and
provide them with virtual, extended versions of traditional field tools
in order to solve significant scientific problems.

The ADVISER PSE has four basic parts:

> 1\) Geoscientist on or near the surface,
>
> 2\) Importation and visualization of \'multiple, integrated data sets,
>
> 3\) Field kit development, and 4) Ancillary virtual field instrument
> development.

In the past year we have:

1\) Imported and visualized multiple data sets, including MOLA altimetry
and Viking, MOC, THEMIS and HRSC image data sets, and introduced wind
vectors and values for different seasonal atmospheric and climate
conditions.

2\) Placed 30 geoscientists on the surface of Mars to address scientific
problems.

3\) Prototyped important aspects of the Field Kit (field location,
strike and dip determination, instant altimetry and profiles, traverse
recording and note-taking, etc.) and provided the geoscientists with
these tools in the IVR environment.

4\) Prototyped Ancillary field instruments (e.g., virtual photography,
virtual GPS, and the PDA field notebook) and provided the geoscientists
with these tools in the IVR environment.

5\) Integrated ROAM 3 rendering system into the IVR environment; built
toolkit on top of it.

6\) Provided support for non-immersive desktop and immersive display
environments.

7\) Integrated ArcMap to formalize the initial correlation of data sets
for enhancing data preparation for importing to the immersive
environment.

8\) Developed tablet PC pen-based UI to traverse planning application of
ADVISER

9\) New Science Results: These activities contributed significantly to
the analysis of the North Polar layered deposits on Mars. Deposits were
analyzed and strata were correlated and traced; their strikes and dips
were assessed. This information was applied to an understanding of the
nature of polar cap layer emplacement and to the origin of climate
change on Mars. (Milkovich, S. M. and J. W. Head, North polar cap of
Mars: Polar layered deposit characterization and identification of a
fundamental climate signal, J. Geophys. Res., Vol. 110, No. E1, E01005,
10.1029/2004JE002349, 2005).

10\) New Science Results: Antarctic Dry Valley Field Preparation and
Planning: In preparing for deployment for the six week field season in
the Antarctic Dry Valleys, we imported digital topography and IKONOS
image data to the IVR environment and planned camp locations and field
traverses. Results from this season are being placed in this environment
for further correlation and analysis.

11\) New Science Results: Explored glacial deposits on Mars using IVR
and made critical observations and measurements. (Shean, D. E., J. W.
Head, and D. R. Marchant, Origin and evolution of a cold-based tropical
mountain glacier on Mars: The Pavonis Mons fan-shaped deposit, J.
Geophys. Res., 110, E05001, doi:10.1029/2004JE002360, 2005; Shean, D.
E., J. W. Head, J. L. Fastook, and D. R. Marchant, Recent glaciation at
high elevations on Arsia Mons, Mars: Implications for the formation and
evolution of large tropical mountain glaciers, J. Geophys. Res, in
press, 2006; Milkovich, S. M., J. W. Head and D. R. Marchant,
Debris-covered piedmont glaciers along the northwest flank of the
Olympus Mons scarp: Evidence for low-latitude ice accumulation during
the Late Amazonian of Mars, Icarus 181, 388-407, 2006.) 12) Introduced
IVR-derived animations in the literature. (Ivanov, M. A. and J. W. Head,
Alba Patera, Mars: Topography, Structure, and Evolution of a Unique Late
Hesperian-Early Amazonian Shield Volcano, J. Geophys. Res., 111, doi:
10.1029/2005JE002469, 2006). 13) A second paper describing our efforts
was published this year (Forsberg, A., Prabhat, G. Haley, A. Bragdon, J.
Levy, C. Fassett, D. Shean, J. Head, S. Milkovich and M. Duchaineau,
ADVISER: Immersive Field Work for Planetary Geoscientists, IEEE CG&A
special issue on Exploring GeoVisualization 26:4, 46-54, 2006. 14)

Two classes of over 100 university students used the facility during
their course to plan the choice and exploration of scientifically
interesting places on Mars.

1\) These efforts fulfill the fundamental goals and objectives of the
NASA AISR Program, and address the major goals of NASA as an Agency,
including the President\'s Exploration Initiative. 2) Relevant
technologies: Interactive 3D terrain visualization with very large data
sets (high-resolution topography, image and related data) and user
interface development

1\) Application to NASA Office of Space Science research programs as
described above.

2\) Direct application to Palmer Quest, a NASA Nuclear Mission Design
Study in conjunction with the NASA Jet Propulsion Laboratory. The
facility was used to site landing sites on the North Polar Cap of Mars,
to design traverses with the companion rover, to verify design and
traverse trafficability and capability, and to analyze MLS landing site,

3\) Initiation of application to NASA Astronaut Candidate Training: Used
for site selection and traverse planning for a human reference mission
to Mars for broad concept certification for NASA Astronaut training.

1\) Undergraduate university students filled out forms on their use and
analysis of the facility and made suggestions for improvement.

2\) Graduate students have discussed and described their experiences
with students and faculty with all IVR facility personnel in attendance.
More detailed reports are underway.

3\) Interested undergraduates are doing hands-on work to help explore
optimal user interface ideas (e.g., hand-held PDA device controls and
applying the latest \'video-game-like\' rapid response controls).

1\) Incorporation of the IVR facility for an Engineering course on
mission design.

2\) Integration with navigation system: How to plan for field work and
establish traverse planning highlights with ArcGIS in order to optimize
the planned input to the IVR facility.

3\) Develop tool functionality in desktop version.

> a\) to bring ADVISER capabilities to the GeoScience lab
>
> b\) to enable comparison of ADVISER tasks done in Cave and at
> conventional desktop

4\) Develop initial mechanisms for tele-robotic viewing within Brown.

5\) Develop initial mechanisms for tele-robotic viewing outside of Brown
at NASA and with other users.

6\) Develop data management solutions for \'out of core\' data sets.

7\) Develop techniques so that large data sets have low impact on
interactivity (high frame rate and low latency).

8\) Continue to develop advanced visualization and rendering techniques
so that large geology data sets can be viewed in immersive VR (i.e.,
high frame rate, low latency, without inducing cybersickness).

9\) Continue debriefing by user systems.

10\) Complete Education and Public Outreach proposal and submit.

11\) Extend to additional science themes and topics.

44 Darren De Zeeuw

**A GUI for data and model visualization**

http://csem.engin.uich.edu

Darren De Zeeuw, Tamas Gombosi, Aaron Ridley, Gabor Toth/*University of
Michigan*

The Space Weather Modeling Framework (SWMF) is a powerful tool to model
much of the space environment. A graphical user interface (GUI) has been
developed as a simple way to install, configure, compile, and run the
SWMF. Of special interest is the visualization of the vast amount of
model output. This tool is web based, allowing the user to easily a
large combination of customized plots.

NASA is a strong supporter of numerical modeling efforts in space
physics. Easy to use visualization of output that can pull in
appropriate data will make the models useful to a wider pool of
scientists and their research efforts.

Data visualization tools can be added to the GUI to visualize data from
nearly all NASA missions. Putting that data into the context of a global
model can give further insight into environment of the spacecraft.

The SWMF usage is tracked by requiring users to register before
downloading the code. The GUI will be released soon, and will require a
similar registration process.

We plan to further develop the GUI through user feedback. In addition,
we plan to add a wide array of data visualizations that can be
integrated with model output.

**45 Thomas McGlynn**

**SkyView: The Visualization Portal for the Virtual Observatory**

http://skyview.gsfc.nasa.gov

Project in Year 1 of 1

Thomas A. McGlynn, Laura McDonald/*NASA/GSFC*

Distribution of powerful resampling library. Full integration of SkyView
and the Virtual Observatory.

Easy intercomparison and integration of multi-mission data in astronomy
and other fields. Higher quality image image analysis capabilities.

Generation of thosands of finding charts from 2MASS data. Publication of
slew survey data from XTE mission. Mosaicking of XMM OM data.

SkyView requests on SkyView web page. Download requests for SkyView
software.

Development of survey/image collection framework for SkyView.

# Abstracts Only

**Developing and Deploying Advanced Astrophysical Algorithms to Novel
Supercomputing Hardware**

Project in Year 1 of 3

Robert J. Brunner/*Department of Astronomy & National Center for
Supercomputing Applications*

Volodymyr Kindratenko/*National Center for Supercomputing Applications*

Adam Myers, Nick Ball

*Department of Astronomy & National Center for Supercomputing
Applications*

We have implemented a brute-force implementation of the two-point
correlation algorithm, which is the Fourier transform of the angular
power spectrum, on both a traditional architecture and a reconfigurable
computing (RC) platform manufactured by SRC computers, Inc. The RC
system has shown an 80 times speed-up over the traditional PC, through
FPGA architecture specific speed-ups, and by using a fixed-point
precision. We have verified all calculations with a previously written
and tested correlation analysis code, and published these results at the
Reconfigurable Systems Summer Institute, and submitted a more formal
analysis to a computing science journal.

Improved algorithm throughput is essential to a number of current and
forthcoming NASA missions. Furthermore, the path to Petascale computing
is not clearly illuminated, and exploring alternative technologies, such
as the ones we are using, is essential step in moving to the next
generation of supercomputers.

Our work is currently not available outside the Innovative Systems
Laboratory at NCSA.

Over the next year we will extend our two-point correlation analysis to
incorporate an optimized tree-based data structure, which will allow us
to extend our benchmark test to also compare with state-of-the-art
correlation codes. We also will tackle two additional algorithms for
porting to the RC system, specifically an instance-based classification
algorithm and a full three-point correlation algorithm.

**Block-Adaptive Parallel Implicit Methods for Semirelativistic
Multifluid Hall-MHD**

http://csem.engin.umich.edu/

Project in Year 2 of 3

Gabor Toth, Yingjuan Ma, Tamas Gombosi, Igor Sokolov/*University of
Michigan*

We have developed a 2nd order accurate discretization for the Hall MHD
on block-adaptive grids. Both explicit and implicit time integrations
are implemented. This work required several novel algorithmic solutions.
The algorithm is implemented into the BATSRS MHD code which is part of
the Space Weather Modeling Framework (SWMF).

Magnetic reconnection is a very important process of space physics. It
occurs in the magnetosphere of planets and in the solar corona. The
reconnection is especially important in eruptive events and magnetic
storms. Successful numerical simulation of the reconnection process
helps to understand the observations as well as developing predictive
capabilities. Hall MHD is a very efficient way of describing magnetic
reconnection with reasonable realism (better than ideal MHD) but without
the computational needs of partical simulations.

This work is relevant to the Cassini, Mars missions and Cluster. It will
also be relevant to SMART and Stereo. All these missions study magnetic
reconnection that can be modeled efficiently with our Hall MHD code. We
are going to compare simulation results with the observations provided
by these missions.

The external use of the SWMF is tracked by registration at the CSEM
website. Use through the CCMC is tracked by the CCMC. Publications using
the SWMF have to reference and acknowledge the use of our code.

Further improvement of the algorithm. Adding more physics.
Magnetospheric and solar application, making available the code as part
of the SWMF to the space science community.