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NASA NTRS2018

K-Means Cluster Study for Radiofrequency Propagation Characterization

The objective of this study is to design a simple method for mining radio frequency (RF) propagation data. The study explored the characteristics of a large dataset of propagation experiments conducted over the span of years and using several ground stations around the world. Furthermore, this study developed simple predictive models that can be used for link characterization and overall propagation behavior description, without the need for physical measurements on-site. It is understood that such statistical learning has several drawbacks in terms of accuracy and precision. K-means clustering was used to characterize the data set in a way never explored before in an attempt to create useful tools that reduce cost, time and risk. K-means clustering was used to characterize the data set. Cosine distance was used as a method to determine the optimal number for clustering each feature. Dependence and independence analysis was performed to explore intra and inter-sensitivity between the presented features, with respect to each other and time. Several predicative models were generated and evaluated with respect to a test set to assess a measure of prediction accuracy and precision. A simple method for data analysis was developed and tested as the basis for further studies and future refinement to produce optimal performing models.

Cognitive↗

NASA NTRS1993

Adaptive fuzzy system for 3-D vision

An adaptive fuzzy system using the concept of the Adaptive Resonance Theory (ART) type neural network architecture and incorporating fuzzy c-means (FCM) system equations for reclassification of cluster centers was developed. The Adaptive Fuzzy Leader Clustering (AFLC) architecture is a hybrid neural-fuzzy system which learns on-line in a stable and efficient manner. The system uses a control structure similar to that found in the Adaptive Resonance Theory (ART-1) network to identify the cluster centers initially. The initial classification of an input takes place in a two stage process; a simple competitive stage and a distance metric comparison stage. The cluster prototypes are then incrementally updated by relocating the centroid positions from Fuzzy c-Means (FCM) system equations for the centroids and the membership values. The operational characteristics of AFLC and the critical parameters involved in its operation are discussed. The performance of the AFLC algorithm is presented through application of the algorithm to the Anderson Iris data, and laser-luminescent fingerprint image data. The AFLC algorithm successfully classifies features extracted from real data, discrete or continuous, indicating the potential strength of this new clustering algorithm in analyzing complex data sets. The hybrid neuro-fuzzy AFLC algorithm will enhance analysis of a number of difficult recognition and control problems involved with Tethered Satellite Systems and on-orbit space shuttle attitude controller.

Mitra, Sunanda↗

NASA NTRS2011

The Effect of Different Operations Modes on Science Capabilities During the 2010 Desert-RATS Test: Insights from the Geologist Crewmembers

The 2010 Desert RATS field test utilized two Space Exploration Vehicles (prototype planetary rovers) and four crewmembers (2 per rover) to conduct a geologic traverse across northern Arizona while testing continuous and twice-per-day communications paired with operation modes of separating and exploring individually (Divide & Conquer) and exploring together (Lead & Follow), respectively. This report provides qualitative conclusions from the geologist crewmembers involved in this test as to how these modes of communications and operations affected our ability to conduct field geology. Each mode of communication and operation provided beneficial capabilities that might be further explored for future Human Spaceflight Missions to other solar system objects. We find that more frequent interactions between crews and an Apollo-style Science Team on the Earth best enables scientific progress during human exploration. However, during multiple vehicle missions, this communication with an Earth-based team of scientists, who represent "more minds on the problem", should not come at the exclusion of (or significantly decrease) communication between the crewmembers in different vehicles who have the "eyes on the ground". Inter-crew communications improved when discussions with a backroom were infrequent. Both aspects are critical and cannot be mutually exclusive. Increased vehicle separation distances best enable encounters with multiple geologic units. However, seemingly redundant visits by multiple vehicles to the same feature can be utilized to provide improved process-related observations about the development and modification of the local terrain. We consider the value of data management, transfer, and accessibility to be the most important lesson learned. Crews and backrooms should have access to all data and related interpretations within the mission in as close to real-time conditions as possible. This ensures that while on another planetary surface, crewmembers are as educated as possible with respect to the observations and data they will need to collect at any moment.

Bleacher, Jacob E.↗

NASA NTRS2008

Lessons Learned from Previous Space-Borne Sounders as a Guide to Future Sounder Development

Space-borne radio sounding is considered to be the gold standard for electron-density (N(sub e)) measurements compared to other techniques even under low-density conditions, such as N(sub e) < 1/cu cm, when other techniques are known to experience difficulties. These reliable measurements are not restricted to in-situ N(sub e) determinations since a spaceborne sounder can provide vertical N(sub e) profiles (N(sub e)(h)) from the spacecraft altitude to the altitude of maximum N(sub e). Near-conjunction studies involving the International Satellites for Ionospheric Studies (ISIS) satellites in the topside ionosphere and Dynamics Explorer 2 (DE 2) near the altitude of the F-region peak density have verified that, even at the greatest distance from the sounder, the ISIS-derived N(sub e)(h) profiles agree with the DE-2 Langmuir-probe measurements to within about 30% over a density range of more than two decades. Space-borne sounders can also provide N(sub e) profiles along the magnetic-field B, by inverting echoes that are ducted along field-aligned irregularities (FAI), and can provide information about the terrain beneath the satellite by examining surface reflections in the frequency range above the ionospheric penetration frequency. Many nations have launched rocket and satellite radio sounders in geospace over more than 4 decades and there have been sounders on space-probes and in orbit around other planets. Here we will summarize some of the lessons learned from these accomplishments by analyzing data from radio sounders on the Alouette and ISIS satellites and the OEDIPUS and other rockets in the terrestrial ionosphere, the IMAGE satellite in the terrestrial magnetosphere, the Ulysses space probe in Jupiter's 10 plasma torus and the MARSIS satellite in orbit around Mars. The emphasis will be on information deduced concerning (1) fundamental plasma processes and gradients in N, and B in the vicinity of the sounders from sounder-stimulated plasma resonances and short-range echoes involving ion as well as electron motions, (2) the importance of the antenna orientation relative to B for the detection of different plasma resonances, (3) sounder-stimulated plasma phenomena, including FAI, when special plasma conditions are satisfied, (4) the minimum power required for long-range echoes, as indicated by echoes from frequency components of the transmitted pulse and by multiple ducted echoes, and (5) the terrain beneath the satellite from surface reflections. Knowledge of these results should enable the optimum design of a future sounder to satisfy specific science requirements with minimal spacecraft resources.

Benson, Robert F.↗

NASA NTRS2023

Exploration Medical Capability Clinical Decision Support System Architecture Recommendation

A new era in space exploration has arrived with the goal of establishing a long-term presence on the Moon and using those learning to take the next giant leap: sending the first astronauts to Mars. These ambitious goals will require significant changes in in-flight medical care due to constraints on mass, volume, power, crew time, and medical evacuation capabilities. Furthermore, while crews currently rely on real-time communications with ground-based medical providers, as distance from Earth increases, so do communication delays and disruptions. The crew will need to autonomously detect, diagnose, treat, and prevent medical events. These constraints require development of transformative solutions and new technologies. Through participation in the Human Research Program’s (HRP) Exploration Medical Capability (ExMC) research, NASA has developed and demonstrated a Medical Data Architecture (MDA), a platform upon which a robust capability of Clinical Decision Support (CDS) can be built. As a result, NASA is now positioned to build an advanced autonomous CDS System (CDSS) which will aid in crew health decision-making. The CDSS combines data management aspects of a system that would lead to the autonomy required by NASA-STD-3001, Section 3, Health and Medical Care Standards. The project addresses the ExMC gap Medical-701: We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources. This architecture recommendation document introduces an integrated data architecture that provides self-sufficient medical care for crews on long-duration spaceflight missions.

ExMC↗

NASA NTRS2011

Debris Disks in Aggregate: Using Hubble Space Telescope Coronagraphic Imagery to Understand the Scattered-Light Disk Detection Rate

Despite more than a decade of coronagraphic imaging of debris disk candidate stars, only 16 have been imaged in scattered light. Since imaged disks provide our best insight into processes which sculpt disks, and can provide signposts of the presence of giant planets at distances which would elude radial velocity and transit surveys, we need to understand under what conditions we detect the disks in scattered light, how these disks differ from the majority of debris disks, and how to increase the yield of disks which are imaged with 0.1" angular resolution. In this talk, I will review what we have learned from a shallow HSTINICMOS NIR survey of debris disks, and present first results from our on-going HST /STIS optical imaging of bright scattered-light disks.

Grady, Carol A.↗

NASA NTRS2021

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Zishuo Zeng↗

NASA NTRS2012

Direct Imaging of Extra-Solar Planets in Star Forming Regions: Lessons Learned from a False Positive Around IM Lup

Context. Most exoplanet imagers consist of ground-based adaptive optics coronagraphic cameras which are currently limited in contrast, sensitivity and astrometric precision, but advantageously observe in the near-infrared window (1 5 m). Because of these practical limitations, our current observational aim at detecting and characterizing planets puts heavy constraints on target selection, observing strategies, data reduction, and follow-up. Most surveys so far have thus targeted young systems (1 100 Myr) to catch the putative remnant thermal radiation of giant planets, which peaks in the near-infrared. They also favor systems in the solar neighborhood (d less than 80 pc), which eases angular resolution requirements but also ensures a good knowledge of the distance and proper motion, which are critical to secure the planet status, and enable subsequent characterization. Aims. Because of their youth, it is very tempting to target the nearby star forming regions, which are typically twice as far as the bulk of objects usually combed for planets by direct imaging. Probing these interesting reservoirs sets additional constraints that we review in this paper by presenting the planet search that we initiated in 2008 around the disk-bearing T Tauri star IM Lup, which is part of the Lupus star forming region (140-190 pc). Methods. We show and discuss why age determination, the choice of evolutionary model for both the central star and the planet, precise knowledge of the host star proper motion, relative or absolute (between different instruments) astrometric accuracy (including plate scale calibration), and patience are the key ingredients for exoplanet searches around more distant young stars. Results. Unfortunately, most of the time, precision and perseverance are not paying off: we discovered a candidate companion around IM Lup in 2008, which we report here to be an unbound background object. We nevertheless review in details the lessons learned from our endeavor, and additionally present the best detection limits ever calculated for IM Lup. We also accessorily report on the successful use of innovative data reduction techniques, such as the damped-LOCI and iterative roll subtraction.

D Mawet↗

NASA NTRSDate not supplied

Electrified Aircraft Propulsion Integration Concepts: Primary Fuel Cells and Cryogenic Hydrogen Storage

This presentation leverages lessons learned from the multiple activities funded by the National Aeronautics and Space Agency (NASA) to convey development paths for implementing an Electrified Aircraft Propulsion (EAP) system powered by primary fuel cells systems and fueled by cryogenically stored hydrogen. To reduce greenhouse gas emissions associated with all aspects of hydrogen-fueled aviation, this work minimizes required energy and time per payload distance at take-off so as to reduce emissions associated with ground operations and the production, liquefaction, transfer, and storage of hydrogen. The approach targets efficient system integration, maximizing hydrogen utilization efficiency, maximizing power system efficiency, and viable operational concepts for delivered payload distances. The discussion outlines the performance and compliance challenges revealed by analyses of current fuel cell and cryogenic management technologies. The conclusion offers potential mitigation strategies to the identified the performance and compliance challenges.

Fuel Cell↗

NASA NTRS2020

Object and Gas Source Detection with Robotic Platforms in Perceptually-Degraded Environments

In exploration-oriented robotic missions for disaster relief in unknown subterranean environments, it is of prime importance for a human supervisor to rapidly gain situational awareness of salient objects within the environment. In this paper we present an automated object detection pipeline that is adaptable to heterogeneous robots with arbitrary sensor configurations. It has been deployed in time-critical scenarios with multiple collaborative robots in a variety of demanding underground environments. For visually observable objects, detections are made in both the visible and thermal spectra using a state-of-the-art machine learning framework for object detection and classification. Our pipeline can be rapidly adapted to a specific task by using a small, structured dataset to fine-tune a pre-trained convolutional neural network (CNN). Relative localization is separated from the CNN for speed of operation. A robust architecture for localization is used with outlier rejection and a hierarchy of fall-back distance measurement methods. Point-source objects such as gas and WiFi hotspots can also be detected, by tracking signal strength over time and presenting an intuitive visualization on a map. Observations of each object types are presented to the operator in ranked confidence order for final evaluation.

Agha-mohammadi, Ali-akbar↗

NASA NTRSDate not supplied

Global Landslide Hazard Assessment for Situational Awareness (LHASA) Version 2: New Activities and Future Plans

A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.

Dalia Kirschbaum↗

NASA NTRS1999

Comets: Very Eccentric Characters

Astronomical distances, even within our own solar system, are very difficult for anyone, let alone children, to imagine. In this month's space-program-related activity, students have the opportunity to create a visual and kinesthetic model of the solar system on a scale that may begin to inspire an awed comprehension of how big space is and how small Earth is. In addition, they will learn a little basic geometry in demonstrating for themselves the difference between a circular planetary orbit and an elongated elliptical cometary orbit. As a space exploration first the Jet Propulsion Laboratory (JPL), under contract to the National Aeronautics and Space Administration (NASA), is planning to send a spacecraft to rendezvous with and land on a comet. The Space Technology 4/Champollion mission is part of NASA's New Millennium Program, the primary goal of which is to test new technologies for use in 21st century planetary and earth observing missions.

Kwok, Enoch↗

NASA NTRS1977

Scientific rationale and strategies for a first comet mission: Report of the Comet Halley science working group

The science objectives of a first comet mission are reviewed and related to what is known or can be expected to be learned in the near future from ground-based and near earth observations. A set of instruments and their science objectives are defined for a mission to Comet Halley during its 1985/86 apparition. The benefits from a fast flyby, a slow flyby, or a rendezvous mission and the relative impact of each on the instrument payload were assessed. The relative scientific value of encounters with the comet at distances from the sun ranging from 1 AU to 2.5 AU, including possible tradeoffs between flyby velocity and distance was considered. Pre- and post-perihelion encounters were likewise evaluated.

Source record↗

NASA NTRS1972

Sky-wave backscatter - A means for observing our environment at great distances.

During the last five years, much progress has been made in the understanding of sky-wave backscatter. An explanation of the various interacting phenomena is presented, as is a review of the current state of knowledge reflecting recent advances in observational methods and analytic techniques. New narrow-beam antennas, coupled with signal modulations that permit fine resolution in time delay, are beginning to yield information concerning the character of the scatterers, which now can be separately discerned. These narrow beams also permit study of polarization fading from small regions, and this shows promise as a means for learning the distant sea state. Doppler shifts of a fraction of a hertz on signals of tens of megahertz are separable, permitting isolation of sea returns from ground returns by virtue of the Doppler effect resulting from sea-wave speed; this also suggests a potential sea-monitoring principle. Despite these advances, there is little practical application of sky-wave backscatter as a means of environmental monitoring. This lack is attributed to the large remaining gaps in our understanding of the echoes and our inability to interpret the forms of data that can be acquired with equipment of reasonable cost.

Croft, T. A.↗

NASA NTRS1991

Efficient visual grasping alignment for cylinders

Monocular information from a gripper-mounted camera is used to servo the robot gripper to grasp a cylinder. The fundamental concept for rapid pose estimation is to reduce the amount of information that needs to be processed during each vision update interval. The grasping procedure is divided into four phases: learn, recognition, alignment, and approach. In the learn phase, a cylinder is placed in the gripper and the pose estimate is stored and later used as the servo target. This is performed once as a calibration step. The recognition phase verifies the presence of a cylinder in the camera field of view. An initial pose estimate is computed and uncluttered scan regions are selected. The radius of the cylinder is estimated by moving the robot a fixed distance toward the cylinder and observing the change in the image. The alignment phase processes only the scan regions obtained previously. Rapid pose estimates are used to align the robot with the cylinder at a fixed distance from it. The relative motion of the cylinder is used to generate an extrapolated pose-based trajectory for the robot controller. The approach phase guides the robot gripper to a grasping position. The cylinder can be grasped with a minimal reaction force and torque when only rough global pose information is initially available.

Nicewarner, Keith E.↗

NASA NTRS1992

Efficient visual grasping alignment for cylinders

Nicewarner, Keith E.↗

NASA NTRS1933

A simple method for increasing the lift of airplane wings by means of flaps

Aerodynamic considerations led us, not long ago, to investigate a device which seemed to promise a contribution to the problem of reducing the landing speed of an airplane. We have subsequently learned that similar devices had already been proposed and investigated by others, but it seems advisable, nevertheless, to report our results. The problem is to create, in landing, a region of turbulence on the lower side of the wing near the trailing edge by some obstacle to the air flow. The devices tested by us consisted of flaps of varying chord and position, the chord s being equal to the distance of the pivot from the trailing edge.

Gruschwitz, Eugen↗

NASA NTRS1976

DHARMA - Discriminant hyperplane abstracting residuals minimization algorithm for separating clusters with fuzzy boundaries

Learning of discriminant hyperplanes in imperfectly supervised or unsupervised training sample sets with unreliably labeled samples along the fuzzy joint boundaries between sample clusters is discussed, with the discriminant hyperplane designed to be a least-squares fit to the unreliably labeled data points. (Samples along the fuzzy boundary jump back and forth from one cluster to the other in recursive cluster stabilization and are considered unreliably labeled.) Minimization of the distances of these unreliably labeled samples from the hyperplanes does not sacrifice the ability to discriminate between classes represented by reliably labeled subsets of samples. An equivalent unconstrained linear inequality problem is formulated and algorithms for its solution are indicated. Landsat earth sensing data were used in confirming the validity and computational feasibility of the approach, which should be useful in deriving discriminant hyperplanes separating clusters with fuzzy boundaries, given supervised training sample sets with unreliably labeled boundary samples.

Dasarathy, B. V.↗