Integrative
analyses of large scale spatio-temporal datasets play increasingly important roles in many areas of science and engineering. Our recent work in this area is motivated by application scenarios involving complementary digital microscopy, Radiology and "omic"
analyses in cancer research. In these scenarios, our objective is to use a coordinated set of image analysis, feature extraction and machine learning methods to predict disease progression and to aid in targeting new therapies.
We describe methods
we have developed for extraction, management and analysis of features along with the systems software methods for optimizing execution on high end CPU/GPU platforms. We will also describe biomedical results obtained from these studies and extensions of the
computational methods to broader application areas.
IBM Research: IBM 2010 Investor BriefingIBM Research
IBM 2010 Investor Briefing
Date/time: 12 May 2010, 10:00 AM Eastern
Location: New York, NY
Join Sam Palmisano, IBM Chairman, President and CEO, and senior IBM management for a presentation to IBM's investors.
This three-day course is designed for engineers, scientists, project managers and other professionals who design, build, test or sell complex systems. Each topic is illustrated by real-world case studies discussed by experienced CONOPS and requirements professionals. Key topics are reinforced with small-team exercises. Over 200 pages of sample CONOPS (six) and templates are provided. Students outline CONOPS and build OpCons in class. Each student gets instructor’s slides; college-level textbook; ~250 pages of case studies, templates, checklists, technical writing tips, good and bad CONOPS; Hi-Resolution personalized Certificate of CONOPS Competency and class photo, opportunity to join US/Coalition CONOPS Community of Interest.
Integrative
analyses of large scale spatio-temporal datasets play increasingly important roles in many areas of science and engineering. Our recent work in this area is motivated by application scenarios involving complementary digital microscopy, Radiology and "omic"
analyses in cancer research. In these scenarios, our objective is to use a coordinated set of image analysis, feature extraction and machine learning methods to predict disease progression and to aid in targeting new therapies.
We describe methods
we have developed for extraction, management and analysis of features along with the systems software methods for optimizing execution on high end CPU/GPU platforms. We will also describe biomedical results obtained from these studies and extensions of the
computational methods to broader application areas.
IBM Research: IBM 2010 Investor BriefingIBM Research
IBM 2010 Investor Briefing
Date/time: 12 May 2010, 10:00 AM Eastern
Location: New York, NY
Join Sam Palmisano, IBM Chairman, President and CEO, and senior IBM management for a presentation to IBM's investors.
This three-day course is designed for engineers, scientists, project managers and other professionals who design, build, test or sell complex systems. Each topic is illustrated by real-world case studies discussed by experienced CONOPS and requirements professionals. Key topics are reinforced with small-team exercises. Over 200 pages of sample CONOPS (six) and templates are provided. Students outline CONOPS and build OpCons in class. Each student gets instructor’s slides; college-level textbook; ~250 pages of case studies, templates, checklists, technical writing tips, good and bad CONOPS; Hi-Resolution personalized Certificate of CONOPS Competency and class photo, opportunity to join US/Coalition CONOPS Community of Interest.
1. HEOMD and Code T Perspectives @
ARCtek
Eugene L. Tu
Director for Exploration Technology
NASA Ames Research Center
Jan. 18, 2012
2. Human Exploration & Operations Mission Directorate
Organizational Structure
Public
Affairs/Communica8ons
Chief
Technologist
Legisla8ve
Affairs
Chief
Scien8st
Human
Explora-on
&
Opera-ons
Mission
Chief
Engineer
Int’l/Interagency
Rela8ons
Directorate
Safety
&
Mission
Assurance
General
Counsel
Chief
Health
&
Medical
Officer
Strategic
Analysis
&
Mission
Support
Resources
Management
Space
Comm
&
Launch
Integra8on
Services
Naviga8on
Services
• HR
• Architecture
studies
and
• E
&
PO
analysis
• IT
• Mission
analysis
• Management
• Risk
and
requirements
processes
&
coordina8on
internal
controls
Space
Explora8on
Human
ISS
Commercial
Advanced
Space
Life
&
ShuUle
Systems
Spaceflight
Spaceflight
Explora8on
Physical
Development
•
System
O&M
Capabili8es
• Crew
&
Cargo
Development
Systems
Sciences
•
MPCV
Transporta8on
Research
&
• Core
Capabili8es
• Commercial
• AES
•
SLS
(MAF,
MOD,
SFCO,
Services
Crew
• Robo8c
Applica8ons
• GSDO
EVA)
• COTS
precursor
• RPT
measurements
• HRP,
CHS
• Fund.
Space
Bio
• Physical
Sciences
For NASA Internal Use Only – Pre-Decisional ISS
Nat’l
Lab
Mgt.
2
3. Common
Capabili8es
Iden8fied
for
Explora8on
Capability Driven Human Space Exploration
Capability Driven Architecture Elements (Building Blocks)
c
Ground
Commercial
MPCV
Robo-c
SEV
EVA
CPS
DSH
Des-na-on
Advanced
Mission
Opera-ons
Cargo/Crew
SLS
Systems
Systems
Systems
Propulsion
Opera-ons
Small
Payload
Robo-c
Free
Satellite
Standardized
Cross Cutting Systems Modular
Light
Weight
Long-‐Life
Suit
Port
Logis-cs
to
Prop.
Mgt
Power
Radia-on
Comm/
Return
Flyer
Servicing
Energy
Storage
ECLSS
Solar
ISRU
Universal
Living
and
Module
Protec-on
Nav
inspec-on
Robot
Arrays
Docking
Storage
System
Personal
Space
Prop
from
Asteroid
Self-‐ Thermo-‐electric
Modeling
Mobility
Robo-c
EP
EVA
Suit
EVA
Suit
Autonomous
Surface
Stairs
/
Waste
Anchoring
Tools
Healing
Genera-on
and
System
Assistant
Thrusters
Exoskeleton
Ops
Ramp
System
Gasses
Systems
Simula-on
Technologies, Research, and Science
OCT Cross Cutting Technology Developments Human Exploration Specific Research
(such as ECLSS, EVA)
Human Exploration Specific Technologies 3
HEO and SMD Cross Cutting Research & Science
4. Proposed
Top-‐Level
Figures
of
Merit
• Probability
of
Loss
of
Mission
• Determine
the
degree
to
which
the
technology
op8ons
ensure
reliability
for
all
mission
phases
• Effec4veness
and
Performance
• Determine
the
degree
to
which
the
technology
op8ons
effec8vely
meet
mission
needs
and
improve
mission
performance
• Extensibility
to
Other
Missions
• Determine
the
degree
to
which
the
technology
op8ons
could
be
used
for
other
missions
or
customers
• Programma4c
Risk
• Determine
the
degree
to
which
technology
op8ons
affect
programma8c
cost
and
schedule
risks
• Affordability
and
Life
Cycle
Cost
• Determine
the
degree
to
which
the
technology
op8ons
reduce
technology/system
development
and
recurring
costs
5. Explora8on
Technology
Directorate
TOTAL WORKFORCE: 670 (~280 FTE & ~390 WYE); 50 Projects (~$140M) All Mission Directorates, SCAP, and NESC
R&T Development and Applications; Largest ARCJET Complex; Fastest Supercomputers
Intelligent Systems Human Systems Entry Systems NASA Advanced
Integration and Technology Supercomputing
H Mission Operation Tools Information Systems MPCV Heatshield Engineering Risk Assessment
E
O
Habitat ISHM Human Performance ARCJET Testing SLS Flame Trench Analysis
M Intelligent Ground Ops Launch Vibration Analysis Aerothermal Analysis Launch/Ascent CFD Modeling
D
Exploration Telerobotics Human-Robotic Ops Entry Systems New High-Fidelity CFD Tools
O Materials
C Autonomous Systems
T Adaptive Deployable
Human-Robotics Systems
Entry Systems
Science Planning & Viz Solar System Modeling
S MER Surface Ops
M MSL Surface Operations MSL Heatshield Heliophysics Modeling
Wildfire Response Ops
D Planning Materials for Venus, Earth Science Modeling &
Sample Return, etc. Prediction
A Integrated Intelligent Fundamental Aeronautics
R Resilient Flight Control Flight Deck Hypersonics Research
M High-Fidelity Aero Modeling
Integ. Vehicle Health Mgmt. Human-in-the-loop and Simulation
D
simulation evaluation
5
6. Assets - Expertise and Capabilities
Risk Assessment
Autonomy &
Robotics
Systems Health
Entry Systems &
Technologies
Computational
Aerosciences
Human-Systems Human
Nanotechnology Integration Performance
Collaborative Planning &
Environments Scheduling
1/20/12 6
Supercomputing Information Management Software Reliability
7. Key
Facili8es
High-end Computing and Networking
Systems, Mass Storage, and
ARCJET Facility, Ballistic Range, Advanced Visualization Lab
Shock Tube and Advanced
Materials Lab
Intelligent Systems and Human System Integration Labs
8. HEOMD
Challenges
for
ARCtek
• How
will
we
ensure
the
health
and
produc8vity
of
the
crew
for
long
dura8on
and
long
distance
spaceflight
missions?
• How
will
we
operate
a
spacecra]
with
less
ground-‐
based
resources,
significant
communica8ons
delays,
and
limited
or
no
rapid
return
capabili8es?
• How
will
we
enable
effec8ve
and
coordinated
Human-‐
robo8c
explora8on
in
extreme
environments
and
with
limited
resources?
• How
will
we
design,
develop,
test
and
cer8fy
a
Human
space
transporta8on
system
with
limited
budgets
and
tes8ng
capabili8es?