Results for “sampling size” — Page 9

NASA NTRS2011

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R~, the correlation matrix of associated t-statistics is also studied. In general R~ depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Feiveson, Alan H.↗

NASA NTRSDate not supplied

Nutrition of Antarctic-grown Crops to Supplement the Crew Diet, with Applications for Spaceflight

The availability of fresh produce during longer-duration spaceflight missions is being explored as a countermeasure for human biobehavioral health and performance, including how fresh fruits and vegetables can supplement the crew diet with nutrients that are predicted to become deficient throughout the missions. Crop production in the Veggie and Advanced Plant Habitat vegetable production chambers on the International Space Station (ISS) have tested pick-and-eat crops in spaceflight. However, the limited plant cultivation volume of these chambers has restricted the sample sizes and biomass allocated for nutrition assessment. To gain a better understanding of the nutrient composition of pick-and-eat crops, leafy greens and fruiting plants were grown in the EDEN ISS plant cultivation facility near the German Neumayer Station III in Antarctica from March 2021 to January 2022. Target crops for nutrition sampling aligned with cultivars grown in spaceflight, including ‘Outredgeous’ red romaine lettuce, Mizuna mustard, ‘Red Robin’ dwarf cherry tomato, and NuMex ‘Española Improved’ chili pepper. Plants subsamples were taken at harvest; in the event of multiple harvests from the same plants, subsamples were taken at both the first and final harvests. ‘Outredgeous’ and Mizuna were also grown multiple times throughout the year, allowing multiple grow-outs to be analyzed for potential effects across the growing season. Subsamples were first weighed for fresh mass, dried in a dedicated oven at 70°C for 96 h, weighed again, and stored in air-tight containers inside Neumayer Station III. At the beginning of 2022, the samples were shipped to NASA’s Kennedy Space Center, where they are currently being analyzed with ion chromatography for nutrients of interest in the astronaut diet, including calcium, iron, magnesium, and potassium. This study aims to increase our understanding of how the crops that have successfully grown on the ISS can supplement the crew diet, as well as how other factors like plant age and the number of days the facility has been in operation may impact nutrient concentrations. Such findings can improve the crop selection process and how pick-and-eat crops are cultivated during spaceflight missions.

Jess M. Bunchek↗

NASA NTRSDate not supplied

Nutrition of Antarctic-grown Crops to Supplement the Crew Diet, with Applications for Spaceflight

The availability of fresh produce during longer-duration spaceflight missions is being explored as a countermeasure for human biobehavioral health and performance, including how fresh fruits and vegetables can supplement the crew diet with nutrients that are predicted to become deficient throughout the missions. Crop production in the Veggie and Advanced Plant Habitat vegetable production chambers on the International Space Station (ISS) have tested pick-and-eat crops in spaceflight. However, the limited plant cultivation volume of these chambers has restricted the sample sizes and biomass allocated for nutrition assessment. To gain a better understanding of the nutrient composition of pick-and-eat crops, leafy greens and fruiting plants were grown in the EDEN ISS plant cultivation facility near the German Neumayer Station III in Antarctica from March 2021 to January 2022. Target crops for nutrition sampling aligned with cultivars grown in spaceflight, including ‘Outredgeous’ red romaine lettuce, Mizuna mustard, ‘Red Robin’ dwarf cherry tomato, and NuMex ‘Española Improved’ chili pepper. Plants subsamples were taken at harvest; in the event of multiple harvests from the same plants, subsamples were taken at both the first and final harvests. ‘Outredgeous’ and Mizuna were also grown multiple times throughout the year, allowing multiple grow-outs to be analyzed for potential effects across the growing season. Subsamples were first weighed for fresh mass, dried in a dedicated oven at 70°C for 96 h, weighed again, and stored in air-tight containers inside Neumayer Station III. At the beginning of 2022, the samples were shipped to NASA’s Kennedy Space Center, where they are currently being analyzed with ion chromatography for nutrients of interest in the astronaut diet, including calcium, iron, magnesium, and potassium. This study aims to increase our understanding of how the crops that have successfully grown on the ISS can supplement the crew diet, as well as how other factors like plant age and the number of days the facility has been in operation may impact nutrient concentrations. Such findings can improve the crop selection process and how pick-and-eat crops are cultivated during spaceflight missions.

Jess M. Bunchek↗

NASA NTRS2000

Implications from Near-Shoemaker Imaging of Eros for Small-Scale Structure and Surface Sampling

What we know about asteroids has always been bifurcated by the enormous gap between astronomical studies of small, distant bodies, and the close-up laboratory measurements of hand-sample sized meteorites. The gulf has been narrowed somewhat by improvements in Earth-based astronomical techniques (e.g. Hubble Space Telescope, radar, adaptive optics) and especially by spacecraft fly-bys of asteroids. But the Near Earth Asteroid Rendezvous (NEAR)-Shoemaker mission has gone considerably more in the direction of bridging the gap. Any consideration of intelligent sample-return from an asteroid must be based on the best possible knowledge of the asteroid at the spatial scales pertinent to operations at the asteroid and of the sample/s. Otherwise, we are in danger of succumbing to the 'Martian Horror Story' that Bruce Murray, in the 1960's, envisioned might impair our exploration of the surface of the red planet if we tried to land on it without first bolstering the information content of our database about Mars, especially at high resolutions. NEAR-Shoemaker is helping to bridge that gap in the case of Eros. The best resolution obtained by the Galileo spacecraft on Ida was 25 m/pixel. As of this writing, NEAR has already obtained images with resolutions at least five times better (information content 25 times better) and vastly better images may be available at the time of this Workshop from the late October low flyby. Already, we are seeing that the Martian horror story looks tame compared with Eros. Everywhere we have landed on Mars, the surface has been covered with rocks and boulders, with much higher spatial coverage than seen anywhere on the lunar surface. We have, in fact, been rather lucky that none of our Martian landers have tipped over so far, and there were justified fears in the early aftermath of last year's failure of Mars Polar Lander that it had suffered from inadequate high-resolution characterization of polar regions on Mars (the failure is now known to have had another cause). Eros looks potentially even more terrifying. Additional information is contained in the original extended abstract.

Chapman, C. R.↗

NASA NTRS1998

Method Developed for the High-Temperature Nondestructive Evaluation of Fiber-Reinforced Silicon Carbide Ceramic Matrix Composites

Ceramic matrix composites have emerged as candidate materials to allow higher operating temperatures (1000 to 1400 C) in gas turbine engines. A need, therefore, exists to develop nondestructive methods to evaluate material integrity at the material operating temperature by monitoring thermal and mechanical fatigue. These methods would also have potential as quality inspection tools. The goal of this investigation at the NASA Lewis Research Center is to survey and correlate the temperature-dependent damping and stiffness of advanced ceramic composite materials with imposed thermal and stress histories that simulate in-service turbine engine conditions. A typical sample size of 100 by 4 by 2 cubic millimeters, along with the specified stiffness and density, placed the fundamental vibration frequencies between 100 and 2000 Hz. A modified Forster apparatus seemed most applicable to simultaneously measure both damping and stiffness. Testing in vacuum reduced the effects of air on the measurements. In this method, a single composite sample is vibrated at its fundamental tone; then suddenly, the mechanical excitation is removed so that the sample's motion freely decays with time. Typical results are illlustrated in this paper.

Goldsby, Jon C.↗

NASA NTRS1981

The effect of abnormal cell proportion on specimen classifier performance

An analysis is presented of the results obtained from a cell classifier which is confronted with an abnormal/normal cell ratio which is different from the ratio assumed in the calibration of the classifier. False negative and false positive error rates are determined in advance for classifier operation, along with the necessary sample size in order to validate the predicted distributions. Changes are demonstrated to happen only regarding the false negative rate, where reductions in the abnormal cell rate below the expected rates would cause totally unreliable data. Substantial overproduction of abnormal cells would be quickly noticeable, while production rates beyond, but close to, the expected rates would only require more extensive sampling. Classifier systems for 10% proportions of abnormal cells are concluded to be possible, but difficulties are present with much lower rates

Castleman, K. R.↗

NASA NTRS2002

Forecasting Coronal Mass Ejections from Vector Magnetograms

In a 17 vector magnetogram study of 12 bipolar active regions (Falconer, Moore, & Gary, 2002, ApJ in press), we correlated four quantitative global magnetic measures with the Coronal Mass Ejections (CME) productivity of the active region. The global measures included a measure of active region size, the total magnetic flux phi and three measures of an active region global nonpotentiality 1) the net current (I (sub N)), 2) the length of the strong-shear, strong-field main neutral line (L(sub SS)) and 3) and the normalized twist (alpha = muIN/PHI). The CME productivity was determined from YOHKOH/SXT observations, Geostationary Operational Environmental Satellite (GOES), and when possible Solar and Heliospheric Observatory/Large Angle and Spectrometric Coronagraph Experiment (SOHO/LASCO) observations within 12 days of the day of the magnetogram. We found that the three measures of global nonpotentiality (I(sub N), L(sub SS), alpha) were all well correlated (greater than 99% confidence level) with an active region's CME productivity. The sample size was to small to confirm if there was a statistical significant correlation of the globally nonscientist measures with future CME activity (i.e. from the date of the magnetogram forward). We are doubling our sample, and will report on the statistical significance of global nonpotentiality as a predictor of future CME productivity. The new active regions are all from the first year of the upgraded MSFC vector magnetograms. This work, is funded by NSF through the Space Weather Program, by NASA through the Living with the Star, Targeted Research and Technology, and by NASA Solar Physics Supporting Research and Technology Program. The upgrade to the MSFC vector magnetograph was supported by the High Energy Solar Spectroscopic Imager (HESSI) mission.

Falconer, D. A.↗

NASA NTRS2008

Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life

Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.

Vlcek, Brian L.↗

NASA NTRS2012

Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life

Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.

Vlcek, Brian L.↗

NASA NTRS2014

Optimizing Integrated Terminal Airspace Operations Under Uncertainty

In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.

air traffic optimization↗

NASA NTRS2022

An Efficient and Effective Light Gas Gun Design for Millimeter-Scale Hypervelocity Testing

This paper serves to document a design for a light gas gun that was used for 3 decades at NASA’s Langley Research Center. By adapting readily-available equipment and supplies, this apparatus was capable of accelerating projectiles at up to 9 kilometers per second. The lack of a projectile-carrying sabot sacrifices some adaptability in projectile size, but results in a design that can be cleaned and cycled with far less labor input. Overall limitation on the projectile impact energies attainable effectively limit the applications to assessing the relatively thin shields employed for robotic spacecraft (as opposed to manned missions). The original gun has been decommissioned, but it is believed that this design has application for robotic spacecraft shield testing in the modern world, allowing cost-effective generation of larger sample sizes than with conventional sabot-based light gas guns.

Hypervelocity↗

NASA NTRSDate not supplied

An Efficient and Effective Light Gas Gun Design for Millimeter-scale Hypervelocity Testing

This paper serves to document a design for a light gas gun that was used for 3 decades at NASA’s Langley Research Center. By adapting readily-available equipment and supplies, this apparatus was capable of accelerating projectiles at up to 9 kilometers per second. The lack of a projectile-carrying sabot sacrifices some adaptability in projectile size, but results in a design that can be cleaned and cycled with far less labor input. Overall limitation on the projectile impact energies attainable effectively limit the applications to assessing the relatively thin shields employed for robotic spacecraft (as opposed to manned missions). The original gun has been decommissioned, but it is believed that this design has application for robotic spacecraft shield testing in the modern world, allowing cost-effective generation of larger sample sizes than with conventional sabot-based light gas guns.

Hypervelocity↗

NASA NTRSDate not supplied

An Efficient and Effective Light Gas Gun Design for Millimeter-Scale Hypervelocity Testing

This paper serves to document a design for a light gas gun that was used for 3 decades at NASA’s Langley Research Center. By adapting readily-available equipment and supplies, this apparatus was capable of accelerating projectiles at up to 9 kilometers per second. The lack of a projectile-carrying sabot sacrifices some adaptability in projectile size, but results in a design that can be cleaned and cycled with far less labor input. Overall limitation on the projectile impact energies attainable effectively limit the applications to assessing the relatively thin shields employed for robotic spacecraft (less useful for those used for manned missions). The original gun has been decommissioned, but it is believed that this design has application for robotic spacecraft shield testing in the modern world, allowing cost-effective generation of larger sample sizes than with conventional sabot-based light gas guns.

Scott Hull↗

NASA NTRSDate not supplied

An Efficient and Effective Light Gas Gun Design for Millimeter-scale Hypervelocity Testing

This paper serves to document a design for a light gas gun that was used for 3 decades at NASA’s Langley Research Center. By adapting readily-available equipment and supplies, this apparatus was capable of accelerating projectiles at up to 9 kilometers per second (when new). The lack of a projectile-carrying sabot sacrifices some adaptability in projectile size, but results in a design that can be cleaned and cycled with far less labor input. Overall limitation on the projectile impact energies attainable effectively limit the applications to assessing the relatively thin shields employed for robotic spacecraft (less useful for those used for manned missions). The original gun has been decommissioned, but it is believed that this design has application for robotic spacecraft shield testing in the modern world, allowing cost-effective generation of larger sample sizes than with conventional sabot-based light gas guns.

Scott Hull↗

NASA NTRSDate not supplied

Increasing accessibility to deep learning-based analytics for space biology: pretrained models, transfer learning, and analytics platform development

Biological systems react in complex ways to the stressors of spaceflight, and the data capturing these relationships is concomitantly high-dimensional and complex. Deep learning and machine learning approaches are increasingly popular as an analytical approach for space biosciences, due to their ability to model complex relationships in complex data. However, such approaches often require large datasets and extensive computational resources. New approaches that minimize data sizes and computational power needed to leverage machine learning, and resources that make these approaches accessible, are needed to increase accessibility and adoption of machine learning in the space biosciences. Transfer learning, in which a pretrained model of broad utility is trained on a large dataset, and subsequently reused on downstream applications for which data is more limited, is one approach to minimizing data and computational intensity of deep learning applications. This transfer learning approach results in more performant models in high-dimensional, low-sample-size settings such as space biology, as compared to training models on limited data from scratch. This presentation will outline efforts to generate pretrained models for the space biology community, and highlight transfer learning applications modeling microbial antibiotic resistance during spaceflight. Finally, in order to increase accessibility of these models and tools, as well as others, for the broader space biology community, we present a modeling and analysis platform facilitating machine learning applications in space biology. This platform streamlines machine learning training and analysis in a notebook format, facilitates download and use of space biology data from the NASA GeneLab database, and can be utilized on NASA-hosted servers or downloaded and hosted locally. This effort, as part of the AI4LS (Artificial Intelligence for Life in Space) working group, will increase accessibility, feasibility, and performance of machine learning approaches for the space biology community.

Adrienne Hoarfrost↗

NASA NTRS2005

Microfabricated Genomic Analysis System

Genetic sequencing and many genetic tests and assays require electrophoretic separation of DNA. In this technique, DNA fragments are separated by size as they migrate through a sieving gel under the influence of an applied electric field. In order to conduct these analyses on-orbit, it is essential to acquire the capability to efficiently perform electrophoresis in a microgravity environment. Conventional bench top electrophoresis equipment is large and cumbersome and does not lead itself to on-orbit utilization. Much of the previous research regarding on-orbit electrophoresis involved altering conventional electrophoresis equipment for bioprocessing, purification, and/or separation technology applications. A new and more efficient approach to on-orbit electrophoresis is the use of a microfabricated electrophoresis platform. These platforms are much smaller, less expensive to produce and operate, use less power, require smaller sample sizes (nanoliters), and achieve separation in a much shorter distance (a few centimeters instead of 10 s or 100 s of centimeters.) In contrast to previous applications, this platform would be utilized as an analytical tool for life science/medical research, environmental monitoring, and medical diagnoses. Identification of infectious agents as well as radiation related damage are significant to NASA s efforts to maintain, study, and monitor crew health during and in support of near-Earth and interplanetary missions. The capability to perform genetic assays on-orbit is imperative to conduct relevant and insightful biological and medical research, as well as continuing NASA s search for life elsewhere. This technology would provide an essential analytical tool for research conducted in a microgravity environment (Shuttle, ISS, long duration/interplanetary missions.) In addition, this technology could serve as a critical and invaluable component of a biosentinel system to monitor space environment genotoxic insults to include radiation.

Gonda, Steve↗

NASA NTRS1999

Influence of Specimen Preparation and Specimen Size on the Transverse Tensile Strength and Scatter of Glass Epoxy Laminates

The influence of specimen polishing, specimen configuration, and specimen size on the transverse tension strength of two glass epoxy materials loaded in three and four point bending was evaluated. Polishing machined edges, and/or tension side failure surfaces, was detrimental to specimen strength characterization instead of yielding a higher, more accurate, strength as a result of removing inherent manufacture and handling flaws. Transverse tension strength was sensitive to span length due to the classical weakest link effect. However, strength was less sensitive to volume changes achieved by increasing specimen width. The Weibull scaling law over-predicted changes in transverse tension strengths in three point bend tests and under-predicted changes in transverse tension strengths in four point bend tests. Furthermore, the Weibull slope varied with specimen configuration, volume, and sample size. Hence, the utility of this scaling law for predicting transverse tension strength is unclear.

OBrien, T. Kevin↗

NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗