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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21

Visual discrimination in the pigeon (Columba livia): effects of selective lesions of the nucleus rotundus

The nucleus rotundus is a large thalamic nucleus in birds and plays a critical role in many visual discrimination tasks. In order to test the hypothesis that there are functionally distinct subdivisions in the nucleus rotundus, effects of selective lesions of the nucleus were studied in pigeons. The birds were trained to discriminate between different types of stationary objects and between different directions of moving objects. Multiple regression analyses revealed that lesions in the anterior, but not posterior, division caused deficits in discrimination of small stationary stimuli. Lesions in neither the anterior nor posterior divisions predicted effects in discrimination of moving stimuli. These results are consistent with a prediction led from the hypothesis that the nucleus is composed of functional subdivisions.

NASA Discipline Neuroscience↗

Hazard Analysis for Pneumatic Flipper Suitport/Z-1 Manned Evaluation, Chamber B, Building 32

One of the characteristics of an effective safety program is the recognition and control of hazards before mishaps or failures occur. Conducting potentially hazardous tests necessitates a thorough hazard analysis in order to protect our personnel from injury and our equipment from damage. The purpose of this hazard analysis is to define and address the potential hazards and controls associated with the Z1 Suit Port Test in Chamber B located in building 32, and to provide the applicable team of personnel with the documented results. It is imperative that each member of the team be familiar with the hazards and controls associated with his/her particular tasks, assignments, and activities while interfacing with facility test systems, equipment, and hardware. The goal of this hazard analysis is to identify all hazards that have the potential to harm personnel and/or damage facility equipment, flight hardware, property, or harm the environment. This analysis may also assess the significance and risk, when applicable, of lost test objectives when substantial monetary value is involved. The hazards, causes, controls, verifications, and risk assessment codes have been documented on the hazard analysis work sheets in appendix A of this document. The preparation and development of this report is in accordance with JPR 1700.1, JSC Safety and Health Handbook.

Source record↗

Trade-Space Analysis Tool for Designing Constellations (TAT-C)

While there is growing interest in implementing future NASA Earth Science missions as Distributed Spacecraft Missions (DSMs), there are currently no tool to help in the design of DSMs. The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. Our Trade-space Analysis Tool for Constellations (TAT-C) allows to investigate questions such as: "Which type of constellations should be chosen? How many spacecraft should be included in the constellation? Which design has the best cost/risk value?" This paper provides a description of the TAT-C tool and its components.

Image Processing↗

Hazard Analysis for Building 34 Vacuum Glove Box Assembly

One of the characteristics of an effective safety program is the recognition and control of hazards before mishaps or failures occur. Conducting potentially hazardous tests necessitates a thorough hazard analysis in order to prevent injury to personnel, and to prevent damage to facilities and equipment. The primary purpose of this hazard analysis is to define and address the potential hazards and controls associated with the Building 34 Vacuum Glove Box Assembly, and to provide the applicable team of personnel with the documented results. It is imperative that each member of the team be familiar with the hazards and controls associated with his/her particular tasks, assignments and activities while interfacing with facility test systems, equipment and hardware. In fulfillment of the stated purposes, the goal of this hazard analysis is to identify all hazards that have the potential to harm personnel, damage the facility or its test systems or equipment, test articles, Government or personal property, or the environment. This analysis may also assess the significance and risk, when applicable, of lost test objectives when substantial monetary value is involved. The hazards, causes, controls, verifications, and risk assessment codes have been documented on the hazard analysis work sheets in Appendix A of this document. The preparation and development of this report is in accordance with JPR 1700.1, "JSC Safety and Health Handbook" and JSC 17773 Rev D "Instructions for Preparation of Hazard Analysis for JSC Ground Operations".

Meginnis, Ian↗

Comparing viewer and array mental rotations in different planes

Participants imagined rotating either themselves or an array of objects that surrounded them. Their task was to report on the egocentric position of an item in the array following the imagined rotation. The dependent measures were response latency and number of errors committed. Past research has shown that self-rotation is easier than array rotation. However, we found that imagined egocentric rotations were as difficult to imagine as rotations of the environment when people performed imagined rotations in the midsagittal or coronal plane. The advantages of imagined self-rotations are specific to mental rotations performed in the transverse plane.

NASA Center ARC↗

Space station evolution: Planning for the future

The need for permanently manned presence in space has been recognized by the United States and its international partners for many years. The development of this capability was delayed due to the concurrent recognition that reusable earth-to-orbit transportation was also needed and should be developed first. While the decision to go ahead with a permanently manned Space Station was on hold, requirements for the use of the Station were accumulating as ground-based research and the data from unmanned spacecraft sparked the imagination of both scientists and entrepreneurs. Thus, by the time of the Space Station implementation decision in the early 1980's, a variety of disciplines, with a variety of requirements, needed to be accommodated on one Space Station. Additional future requirements could be forecast for advanced missions that were still in the early planning stages. The logical response was the development of a multi-purpose Space Station with the ability to evolve on-orbit to new capabilities as required by user needs and national or international decisions, i.e., to build an evolutionary Space Station. Planning for evolution is conducted in parallel with the design and development of the baseline Space Station. Evolution planning is a strategic management process to facilitate change and protect future decisions. The objective is not to forecast the future, but to understand the future options and the implications of these on today's decisions. The major actions required now are: (1) the incorporation of evolution provisions (hooks and scars) in the baseline Space Station; and (2) the initiation of an evolution advanced development program.

Diaz, Alphonso V.↗

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗

Thermal Characterization of Fe3O4 Nanoparticles Formed from Poorly Crystalline Siderite

Increasing interest in environmental geochemistry has led to the recognition that crystals with sizes in the nanometer range (e.g., colloids and nanoscale precipitates) and poorly crystalline compounds (e.g., ferrihydrites) may comprise the majority of reactive mineral surface area near the Earth s surface. When the diameters of individual particles are in the range of 100 nm or less, the surface energy contribution to the free energy modifies phase stability. This results in stabilization of polymorphs not normally encountered in the macrocrystal domain. These phases potentially have very different surface-site geometries, adsorptive properties, and growth mechanisms, and exhibit size-dependent kinetic behavior. Thus nanophases dramatically modify the physical and chemical properties of soils and sediments. In a more general sense, the characteristics of nanocrystals are of intense technological interest because small particle size confers novel chemical, optical, and electronic properties. Thus, nanocrystalline materials are finding applications as catalytic substrates, gas phase separation materials, and even more importantly in the field of medicine. This is an opportune time for mineral physicists working on nanocrystalline materials to develop collaborative efforts with materials scientists, chemists, and others working on nanophase materials of technological interest (e.g., for magnetic memories). Our objective in this study was to synthesize submicron (<200 nm) magnetite and to study their thermal and particle size properties.

Lauer, H. V., Jr.↗

DNA in a Tunnel: A Comfy Spot for Recognition - or -The Structure of BsoBI Complexed with DNA. What can we Learn about Function via Structure Determination and how can this be Applied to Bone or Muscle Biology?

The structure and function of a biologically active molecule are related. To understand its function, it is necessary (but not always sufficient) to know the structure of the molecule. There are many ways of relating the molecular function with the structure. Mutation analysis can identify pertinent amino acids of an enzyme, or alternatively structure comparison of the of two similar molecules with different function may lead to understanding which parts are responsible for a functional aspect, or a series of "structural cartoons" - enzyme structure, enzyme plus substrate, enzyme with transition state analog, and enzyme with product - may give insight in the function of a molecule. As an example we will discuss the structure and function of the restriction enzyme BsoBI from Bacillus stearothemzophilus in complex with its cognate DNA. The enzyme forms a unique complex with DNA in that it completely encircles the DNA. The structure reveals the enzyme-DNA contacts, how the DNA is distorted compared with the canonical forms, and elegantly shows how two distinct DNA sequences can be recognized with the same efficiency. Based on the structure we may also propose a hypothesis how the enzymatic mechanism works. The knowledge gained thru studies such as this one can be used to alter the function by changing the molecular structure. Usually this is done by design of inhibitors specifically active against and fitting into an active site of the enzyme of choice. In the case of BsoBI one of the objectives of the study was to alter the enzyme specificity. In bone biology there are many candidates available for molecular study in order to explain, alter, or (temporarily) suspend activity. For example, the understanding of a pathway that negatively regulates bone formation may be a good target for drug design to stimulate bone formation and have good potential as the basis for new countermeasures against bone loss. In principle the same approach may aid muscle atrophy, radiation damage, immune response changes and other risks identified for long-duration Space travel.

vanderWoerd, Mark↗

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗

Possibilistic clustering for shape recognition

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, the clustering problem was cast into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. An appropriate objective function whose minimum will characterize a good possibilistic partition of the data was constructed, and the membership and prototype update equations from necessary conditions for minimization of our criterion function were derived. The ability of this approach to detect linear and quartic curves in the presence of considerable noise is shown.

Keller, James M.↗

Possibilistic clustering for shape recognition

Clustering methods have been used extensively in computer vision and pattern recognition. Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering in that total commitment of a vector to a given class is not required at each iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from Bezdek's Fuzzy C-Means (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Unfortunately, the memberships resulting from FCM and its derivatives do not correspond to the intuitive concept of degree of belonging, and moreover, the algorithms have considerable trouble in noisy environments. Recently, we cast the clustering problem into the framework of possibility theory. Our approach was radically different from the existing clustering methods in that the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We constructed an appropriate objective function whose minimum will characterize a good possibilistic partition of the data, and we derived the membership and prototype update equations from necessary conditions for minimization of our criterion function. In this paper, we show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Keller, James M.↗

A dissociation between attention and selection

It is widely assumed that the allocatian of spatial attention results in the "selection" of attended objects or regions of space. That is, once a stimulus is attended, all its feature dimensions are processed irrespective of their relevance to behavioral goals. This assumption is based in part on experiments showing significant interference for attended stimuli when the response to an irrelevant dimension conflicts with the response to the relevant dimension (e.g., the Stroop effect). Here we show that such interference is not due to attending per se. In two spatial cuing experiments, we found that it was possible to restrict processing of attended stimuli to task-relevant dimensions. This new evidence supports two novel conclusions: (a) Selection involves more than the focusing of attention per se: and (b) task expectations play a key role in detertnining the depth of processing of the elementary feature dimensions of attended stimuli.

Attention↗

Simulation of the Aerosol Size Distribution Using a Neural Network Surrogate for the Modal Aerosol Module (MAM7)

One objective of atmospheric simulations is to quantify the distribution of aerosols and their properties. Accurate parameterizations of the processes governing aerosol mass, particle number, and particle size distribution are important for predicting the Earth’s net radiative balance and aerosol-cloud interactions. The Modal Aerosol Module (MAM7) is a two-moment aerosol model that simulates mass, number, and size distribution of seven modes comprised of internally mixed aerosol species. The two-moment scheme adds significant computational expense but allows for the prediction of varying particle size distribution relative to the bulk method which predicts only total mass. In this work, we developed a neural network surrogate model for MAM7 (MAMnet) to predict the aerosol number concentration in NASA’s Global Earth Observing System (GEOS) without adding prohibitive computational expense. MAMnet, can be driven by output from a single moment, mass-based, aerosol scheme (Goddard Chemistry Aerosol and Radiation model (GOCART)) or from reanalysis products (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)). MAMnet was trained using number concentrations from a 5-year GEOS/MAM7 simulation at 1-degree horizontal resolution and using the total mass calculated across modes as inputs, as well as temperature and air density. The model architecture for MAMnet was based on AlexNet, the 2012 winner of the ImageNet Large Scale Visual Recognition Challenge. While some modifications were necessary to accommodate our problem, important aspects of the network were preserved. MAMnet was able to reproduce zonal dynamics and spatial distributions of the aerosol number concentration however predictability in the upper troposphere was poor.

Katherine H Breen↗

Two New Aircraft Traffic Surveillance Symbology Concepts: Range Filter and Inboard Field-of-View Symbology

The objective of this preliminary experiment was to investigate two head-up surveillance symbology (HUSS) display issues. The first issue was concerned with the benefits of adding a range filter to the current HUSS concept. A range filter limits the amount of traffic symbols displayed head-up by setting a range boundary (e.g., 7-nmi) around the ownship. The second issue was concerned with the need to incorporate HUSS in the inboard field-of-view (IFOV) display of the eXternal Visibility System (XVS) concept. The hypothesis tested was that adding a range filter to the XVS display and HUSS to the IFOV display would enhance the pilot's effectiveness in traffic surveillance tasks. Using a high-resolution graphics flight simulator, each of three pilots flew departure and arrival scenarios under visual meteorological conditions. The pilots' main tasks, while managing flight path, were to detect and assess potential airborne traffic hazards and to maintain overall situation awareness. Upon completing all the runs, each pilot completed a subjective questionnaire. Results showed that having both the HUSS on the IFOV and the range filter on each of the XVS displays enhanced the effectiveness of the XVS surveillance display concept. This configuration had the least head down time and the lowest mental workload. Combining both features gave the best target detection and, the earliest threat recognition performances, and enabled the pilots to create a better strategy for evasive action when it became necessary.

Wong, Douglas T.↗

Two Aircraft Head-Up Traffic Surveillance Symbology Issues: Range Filter and Inboard Field-of-View Symbology

The purpose of the eXternal Visibility System (XVS) effort for NASA s High-Speed Research Program was to determine and to provide required pilot visual information for a High Speed Civil Transport vehicle concept to allow safe and efficient operation in the absence of forward windows. The objective of this preliminary experiment conducted at NASA Langley Research Center was to investigate two head-up surveillance symbology (HUSS) display issues. The first issue was concerned with the benefits of adding a range filter to the current HUSS concept. A range filter limits the amount of traffic symbols displayed head-up by setting a range boundary (e.g. 7-nmi) around the ownship. The second issue was concerned with the need to incorporate HUSS in the inboard field-of-view (IFOV) display of the XVS concept. The hypothesis tested was that adding a range filter to the XVS display and HUSS to the IFOV display would enhance the pilot s effectiveness of traffic surveillance tasks. Using a high-resolution graphics flight simulator, each of three pilots flew departure and arrival scenarios under visual meteorological conditions. The pilots main tasks, while managing flight path, were to detect and assess potential airborne traffic hazards and to maintain overall situation awareness. Upon completing all the runs, each pilot completed a subjective questionnaire. Results showed that having both the HUSS on the IFOV and the range filter on each of the XVS displays enhanced the effectiveness of the XVS surveillance display concept. This configuration had the least head down time and the lowest mental workload. Combining both features gave the best target detection, the earliest threat recognition, and enabled the pilots to create a better strategy for evasive action when it became necessary.

Wong, Douglas T.↗

Real-time three-dimensional color doppler evaluation of the flow convergence zone for quantification of mitral regurgitation: Validation experimental animal study and initial clinical experience

BACKGROUND: Pitfalls of the flow convergence (FC) method, including 2-dimensional imaging of the 3-dimensional (3D) geometry of the FC surface, can lead to erroneous quantification of mitral regurgitation (MR). This limitation may be mitigated by the use of real-time 3D color Doppler echocardiography (CE). Our objective was to validate a real-time 3D navigation method for MR quantification. METHODS: In 12 sheep with surgically induced chronic MR, 37 different hemodynamic conditions were studied with real-time 3DCE. Using real-time 3D navigation, the radius of the largest hemispherical FC zone was located and measured. MR volume was quantified according to the FC method after observing the shape of FC in 3D space. Aortic and mitral electromagnetic flow probes and meters were balanced against each other to determine reference MR volume. As an initial clinical application study, 22 patients with chronic MR were also studied with this real-time 3DCE-FC method. Left ventricular (LV) outflow tract automated cardiac flow measurement (Toshiba Corp, Tokyo, Japan) and real-time 3D LV stroke volume were used to quantify the reference MR volume (MR volume = 3DLV stroke volume - automated cardiac flow measurement). RESULTS: In the sheep model, a good correlation and agreement was seen between MR volume by real-time 3DCE and electromagnetic (y = 0.77x + 1.48, r = 0.87, P <.001, delta = -0.91 +/- 2.65 mL). In patients, real-time 3DCE-derived MR volume also showed a good correlation and agreement with the reference method (y = 0.89x - 0.38, r = 0.93, P <.001, delta = -4.8 +/- 7.6 mL). CONCLUSIONS: real-time 3DCE can capture the entire FC image, permitting geometrical recognition of the FC zone geometry and reliable MR quantification.

Validation Studies↗

Helicopter Field Testing of NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System fully integrated with the Morpheus Vertical Test Bed Avionics

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project was chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with real-time terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. This is accomplished with the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN). The NASA plan for the ALHAT technology is to perform the TRL6 closed loop demonstration on the Morpheus Vertical Test Bed (VTB). The first Morpheus vehicle was lost in August of 2012 during free-flight testing at Kennedy Space Center (KSC), so the decision was made to perform a helicopter test of the integrated ALHAT System with the Morpheus avionics over the ALHAT planetary hazard field at KSC. The KSC helicopter tests included flight profiles approximating planetary approaches, with the entire ALHAT system interfaced with all appropriate Morpheus subsystems and operated in real-time. During these helicopter flights, the ALHAT system imaged the simulated lunar terrain constructed in FY2012 to support ALHAT/Morpheus testing at KSC. To the best of our knowledge, this represents the highest fidelity testing of a system of this kind to date. During this helicopter testing, two new Morpheus landers were under construction at the Johnson Space Center to support the objective of an integrated ALHAT/Morpheus free-flight demonstration. This paper provides an overview of this helicopter flight test activity, including results and lessons learned, and also provides an overview of recent integrated testing of ALHAT on the second Morpheus vehicle.

Rutishauser, David↗