Estimation of Multilayered Cloud Properties from Low-Earth-Orbit Satellite Imager Data
An artificial neural network is developed and applied to satellite imagery data to identify and retrieve characteristics of multi-layered clouds for potential use in weather and c…
Geostationary Satellite Sounder Pathfinder Project for 4-D Atmospheric Thermodynamics and Winds
A k-nearest neighbors technique, coupled with an advanced data assimilation system are applied to hyperspectral infrared and geostationary satellite imager data to provide high sp…
Identifying Aerosol Subtypes from CALIPSO Lidar Profiles Using Deep Machine Learning
Applies convolutional neural networks (supervised learning) to automatically identify the presence of different aerosol species (e.g., dust and smoke) in CALIPSO lidar backscatter…
Identifying flaws in manufacturing of composites
Inspection for manufacturing flaws makes up 40% of fabrication time so if that time could be reduced it would have a significant impact on overall manufacturing time. That doesn’…
Improvements in Global Nighttime Satellite Cloud Analyses for Weather and Climate
A k-nearest neighbors method is applied to overcome nighttime infrared satellite imagery sensitivity limits that dramatically improves nighttime cloud analyses and their consisten…
Improving CERES Low-Latency Surface Radiation Fluxes with Machine/Deep Learning
In conjunction with sophisticated radiative transfer simulations, the CERES (Clouds and the Earth's Radiant Energy System) team is using machine and deep learning methods to impro…
Intelligent Contingency Management
Adapt and train AI algorithms to contribute to an autonomous vehicle mission manager for Advanced Air Mobility (Cargo, Air Taxis). At a high level, the AI must recognize contingen…
Lessons Learned Bot (LLB)
In near real-time, the Lessons Learned Bot, or LLB, brings lessons learned (LL) documents to users through a Microsoft Excel add-in application locally installed to search for LL…
Machine Learning for Advancing Risk Precursor Identification Tools in Commercial Airline Terminal Area Operations (out of D318)
This work uses a variety of machine learning techniques to recommend commercial terminal area aviation failure modes in addition to unstable vertical approach, evaluate these for…
Mitigating Problematic GOES-17 Infrared Radiances at Night for Weather and Climate Applications
A k-nearest neighbors method is applied to successfully reconstruct bad infrared radiance measurements at night caused by an instrument cooling problem on the GOES-17 (Geostationa…
NASA OCIO STI Concept Tagging Service
An API (application program interface) for exposing topic models created with the STI (Scientific & Technical Information) concept training repository.
New Skin Temperature Analyses for Satllite Cloud Retrievals
A deep neural network is applied to model analyses and satellite observations to improve skin temperature estimates needed for satellite remote sensing of cloud properties.
Nocturnal Opaque Ice Cloud Optical Depth Analyses from MODIS Multispectral Infrared Radiances
An artificial neural network is developed and applied to improve estimates of opaque ice cloud optical depths at night using MODIS (Moderate Resolution Imaging Spectroradiometer)…
PACE-MAPP
The MAPP (modeling, analysis and prediction program) remote sensing retrieval algorithm for the upcoming PACE (plankton, aerosol, cloud, ocean ecosystem) satellite mission uses ne…
Polar Nighttime Cloud Detection Using an Artificial Neural Network
An artificial neural network is applied that addresses the difficult problem of accurately detecting clouds at night over snow- and ice-covered areas in polar regions from satelli…
Probabilistic calibration framework for finite element thermal process modeling of metallic additive manufacturing. Application to promote certification/qualification of load critical aerospace flight parts.
Application of active learning paradigm to efficiently develop Gaussian Process Regression surrogate where run time for the target finite element thermal process model is signific…
Retrieving Aerosol Optical Depth and High Spatial Resolution Ocean Surface Wind Speed From CALIPSO: A Neural Network Approach
This study uses ocean surface wind speed derived from microwave radiometer to train spacebased lidar measurements to measure both wind speed and aerosol optical depth using neural…
Severe Storm Prediction via Overshooting Cloud Top and Above Anvil Cirrus Plume Image Recognition from Satellite Imager Data
Overshooting Cloud Tops (OTs) Above-Anvil Cirrus Plumes (AACPs) are indicators of especially intense thunderstorm updrafts that are precursors to severe weather including damaging…
Aero-Engines AI - a machine-learning app for aircraft engine system-performance prediction
Aero-Engines AI is a Windows app that deploys machine-learning analytics to predict aircraft engine performance.
Using Natural Language Processing to Help Automate the Standardization of PI Variable Names from ICARTT Files
Variables names of data collected from suborbital missions need mapping to the corresponding standard variable names for consistency in labelling the available science data, enhan…
Airplane detection
Deep learning-based airplane detection from high-resolution satellite imagery
Automated Dust detection in satellite imagery
Application of machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES…
Deep Learning-based Hurricane Intensity Estimator
A web-based situational awareness tool that uses deep learning on satellite images to objectively estimate windspeed of a hurricane
GCMD Keyword Recommender (GKR)
Natural Language Processing-based science keyword suggestion tool