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Metric Learning to Enhance Hyperspectral Image Segmentation

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an oversegmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis.

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Numerical Simulation of Rocket Exhaust Interaction With Lunar Soil

These simulations will help predict suitable landing sites on the Moon. This technology development originated from the need to assess the debris threat resulting from soil material erosion induced by landing spacecraft rocket plume impingement on extraterrestrial planetary surfaces. The impact of soil debris was observed to be highly detrimental during NASA’s Apollo lunar missions and will pose a threat for any future landings on the Moon, Mars, and other exploration targets.

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Motion Imagery and Robotics Application (MIRA): Standards-Based Robotics

MIRA initial results have demonstrated robotic camera control that is applicable to near-Earth or distant applications. The current Mission Control Center (MCC) is dedicated to the execution of human spaceflight missions. As the future of NASA and human space evolves, it is clear that robotic artifacts will ultimately be integrated and immersed into the human mission. In order to make the evolution and integration as technically capable at a constrained risk level and with reasonable cost, the robotic elements must adhere to standards that allow not only reuse of previous work, but keep the interfaces stable and reusable.

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Particle Filtering for Model- Based Anomaly Detection in Sensor Networks

Experiments on test stand sensor data show successful detection of a known anomaly in the test data. A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that post-processes a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly.

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Modular, Autonomous Command and Data Handling Software With Built-In Simulation and Test

Commercial markets include tele- communications, remote sensing, and GIS imagers. The spacecraft system that plays the greatest role throughout the program lifecycle is the Command and Data Handling System (C&DH), along with the associated algorithms and software. The C&DH takes on this role as cost driver because it is the brains of the spacecraft and is the element of the system that is primarily responsible for the integration and interoperability of all spacecraft subsystems. During design and development, many activities associated with mission design, system engineering, and subsystem development result in products that are directly supported by the C&DH, such as interfaces, algorithms, flight software (FSW), and parameter sets.

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Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/active L-band instruments. Aquarius’s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP’s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research.

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A Posteriori Study of a DNS Database Describing Super - critical Binary-Species Mixing

Resulting flow models can be used in automotive, aircraft engine, and chemical engineering applications. Currently, the modeling of supercritical-pressure flows through Large Eddy Simulation (LES) uses models derived for atmospheric-pressure flows. Those atmospheric-pressure flows do not exhibit the particularities of high density-gradient magnitude features observed both in experiments and simulations of supercritical-pressure flows in the case of two species mixing. To assess whether the current LES modeling is appropriate and if found not appropriate to propose higher-fidelity models, a LES a posteriori study has been conducted for a mixing layer that initially contains different species in the lower and upper streams, and where the initial pressure is larger than the critical pressure of either species. An initially-imposed vorticity perturbation promotes roll-up and a double pairing of four initial span-wise vortices into an ultimate vortex that reaches a transitional state.

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