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Miller, J. J.

Publications and source records attributed to Miller, J. J..

16 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Using a Knowledge Graph to Discover Earth Science Information

Knowledge graphs link key entities within a specific domain to other entities via relationships. Researchers are able to mine these relationships from numerous sources to infer new knowledge. Text extraction from peer-reviewed papers and scientific reports are untapped resources that can be leveraged by knowledge graphs to accelerate scientific discovery.

Freitag, Brian↗
NASA NTRS2018

Deepti: Deep Learning-Based Tropical Cyclone Intensity Estimation

We present the development of a deep learning model for objective estimation of tropical cyclone intensity at a higher temporal frequency, deployment of the model in production, design and implementation of the tropical cyclone monitoring and intensity estimation system and development of an interactive portal for situational awareness and evaluation of intensity estimation.

Maskey, Manil↗
NASA NTRS2018

Earth Science Deep Learning: Applications and Lessons Learned

Deep Learning: A subfield of machine learning; Algorithms inspired by function of the brain; Scales with amount of training data; Powerful tool without the need for feature engineering; Suitable for Earth Science applications. Deep Learning for Earth science at MSFC (Marshall Space Flight Center): Phenomena identification; Hurricane intensity (wind speed) estimation; Severe storm (hailstorm) detection; Transverse bands detection; Entity extraction for knowledge graph creation; Ephemeral water detection.

Labeled Data↗
NASA NTRS2018

Earth Science Deep Learning: Applications and Lessons Learned

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. At the NASA Marshall Space Flight Center (MSFC), the Data Science and Informatics Group (DSIG) has been using deep learning for a variety of Earth science applications. This paper provides examples of the applications and also addresses some of the challenges that were encountered.

Training↗
NASA NTRS2018

NASA GNSS Activities: WG-B - Enhancement of GNSS Performance, New Services & Capabilities

NASA represents US civil space users at the United Nations International Committee on Global Navigation Satellite Systems (ICG). ICG Working Group B (WG-B) is responsible for Enhancement of Global Navigation Satellite Systems (GNSS) Performance, New Services and Capabilities. The development and characterization of the GNSS Space Service Volume (SSV) is a key area of activity for NASA within WG-B. This presentation contains NASA's contributions to the June 2018 meeting of the ICG WG-B. Topics covered include recent NASA lunar GPS analysis and results; proposed discussion topics for future SSV workshops and trade studies, an overview of the planned SSV Video, discussion of SSV Outreach, and NASA activities updates including GPS and Galileo Receiver for the International Space Station (GARISS), the International GNSS Service (IGS), Next-Generation Broadcast Services (NGBS), flight results from the Magnetospheric Multiscale (MMS) mission, flight results from the Geostationary Operational Environmental Satellite (GOES) R series, the Automated Flight Termination System (AFTS), and other topics.

NASA↗
NASA NTRS2018

WG-B - Enhancement of GNSS Performance, New Services & Capabilities

NASA represents US civil space users at the United Nations International Committee on Global Navigation Satellite Systems (ICG). ICG Working Group B (WG-B) is responsible for Enhancement of GNSS Performance, New Services and Capabilities. The development and characterization of the GNSS Space Service Volume (SSV) is a key area of activity for NASA within WG-B. This presentation contains NASA's contributions to the June 2018 meeting of the ICG WG-B. Topics covered include recent NASA lunar GPS analysis and results; proposed discussion topics for future SSV workshops and trade studies, an overview of the planned SSV Video, discussion of SSV Outreach, and NASA activities updates including GPS and Galileo Receiver for the International Space Station (GARISS), the International GNSS Service (IGS), Next-Generation Broadcast Services (NGBS), flight results from the Magnetospheric Multiscale (MMS) mission, flight results from the Geostationary Operational Environmental Satellite (GOES) R series, the Automated Flight Termination System (AFTS), and other topics.

Miller, J. J.↗
NASA NTRS2018

NASA Update: GNSS Space Service Volume Providers' Forum

NASA represents US civil space users at the United Nations International Committee on Global Navigation Satellite Systems (ICG). ICG Working Group B (WG-B) is responsible for Enhancement of GNSS Performance, New Services and Capabilities. The development and characterization of the GNSS Space Service Volume (SSV) is a key area of activity for NASA within WG-B. This presentation contains NASA's contributions to the June 2018 meeting of the ICG WG-B. Topics covered include recent NASA lunar GPS analysis and results; proposed discussion topics for future SSV workshops and trade studies, an overview of the planned SSV Video, discussion of SSV Outreach, and NASA activities updates including GPS and Galileo Receiver for the International Space Station (GARISS), the International GNSS Service (IGS), Next-Generation Broadcast Services (NGBS), flight results from the Magnetospheric Multiscale (MMS) mission, flight results from the Geostationary Operational Environmental Satellite (GOES) R series, the Automated Flight Termination System (AFTS), and other topics.

Global↗
NASA NTRS2017

Building Scalable Knowledge Graphs for Earth Science

Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

Ramachandran, Rahul↗