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NASA NTRS1993

Seminar Software

The Society for Computer Simulation International is a professional technical society that distributes information on methodology techniques and uses of computer simulation. The society uses NETS, a NASA-developed program, to assist seminar participants in learning to use neural networks for computer simulation. NETS is a software system modeled after the human brain; it is designed to help scientists exploring artificial intelligence to solve pattern matching problems. Examples from NETS are presented to seminar participants, who can then manipulate, alter or enhance them for their own applications.

Source record↗

NASA NTRS2002

The footprints of visual attention in the Posner cueing paradigm revealed by classification images

In the Posner cueing paradigm, observers' performance in detecting a target is typically better in trials in which the target is present at the cued location than in trials in which the target appears at the uncued location. This effect can be explained in terms of a Bayesian observer where visual attention simply weights the information differently at the cued (attended) and uncued (unattended) locations without a change in the quality of processing at each location. Alternatively, it could also be explained in terms of visual attention changing the shape of the perceptual filter at the cued location. In this study, we use the classification image technique to compare the human perceptual filters at the cued and uncued locations in a contrast discrimination task. We did not find statistically significant differences between the shapes of the inferred perceptual filters across the two locations, nor did the observed differences account for the measured cueing effects in human observers. Instead, we found a difference in the magnitude of the classification images, supporting the idea that visual attention changes the weighting of information at the cued and uncued location, but does not change the quality of processing at each individual location.

Non-NASA Center↗

NASA NTRS2002

Retinal flow is sufficient for steering during observer rotation

How do people control locomotion while their eyes are simultaneously rotating? A previous study found that during simulated rotation, they can perceive a straight path of self-motion from the retinal flow pattern, despite conflicting extraretinal information, on the basis of dense motion parallax and reference objects. Here we report that the same information is sufficient for active control ofjoystick steering. Participants steered toward a target in displays that simulated a pursuit eye movement. Steering was highly inaccurate with a textured ground plane (motion parallax alone), but quite accurate when an array of posts was added (motion parallax plus reference objects). This result is consistent with the theory that instantaneous heading is determined from motion parallax, and the path of self-motion is determined by updating heading relative to environmental objects. Retinal flow is thus sufficient for both perceiving self-motion and controlling self-motion with a joystick; extraretinal and positional information can also contribute, but are not necessary.

Kinesthesis/physiology↗

NASA NTRS1992

Fractal mechanisms in the electrophysiology of the heart

The mathematical concept of fractals provides insights into complex anatomic branching structures that lack a characteristic (single) length scale, and certain complex physiologic processes, such as heart rate regulation, that lack a single time scale. Heart rate control is perturbed by alterations in neuro-autonomic function in a number of important clinical syndromes, including sudden cardiac death, congestive failure, cocaine intoxication, fetal distress, space sickness and physiologic aging. These conditions are associated with a loss of the normal fractal complexity of interbeat interval dynamics. Such changes, which may not be detectable using conventional statistics, can be quantified using new methods derived from "chaos theory.".

NASA Discipline Cardiopulmonary↗

NASA NTRS1991

The Space Station Freedom Flight Telerobotic Servicer: the design and evolution of a dexterous space robot

The Flight Telerobotic Servicer (FTS) Project at the Goddard Space Flight Center is developing an advanced telerobotic system to assist in and reduce crew extravehicular activity (EVA) for Space Station) Freedom (SSF). The FTS will provide a telerobotic capability to the Freedom Station in the early assembly phases of the program and will be employed for assembly, maintenance, and inspection applications throughout the lifetime of the space station. Appropriately configured elements of the FTS will also be employed for robotic manipulation in remote satellite servicing applications and possibly the Lunar/Mars Program. In mid-1989, the FTS entered the flight system design and implementation phase (Phase C/D) of development with the signing of the FTS prime contract with Martin Marietta Astronautics Group in Denver, Colorado. The basic FTS design is now established and can be reported on in some detail. This paper will describe the FTS flight system design and the rationale for the specific design approaches and component selections. The current state of space technology and the nature of the FTS task dictate that the FTS be designed with sophisticated teleoperation capabilities for its initial primary operating mode. However, there are technologies, such as advanced computer vision and autonomous planning techniques currently in research and advanced development phases which would greatly enhance the FTS capabilities to perform autonomously in less structured work environments. Therefore, a specific requirement on the initial FTS design is that it has the capability to evolve as new technology becomes available. This paper will describe the FTS design approach for evolution to more autonomous capabilities. Some specific task applications of the FTS and partial automation approaches of these tasks will also be discussed in this paper.

Task Performance and Analysis↗

NASA NTRS1996

Aerospace applications of virtual environment technology

The uses of virtual environment technology in the space program are examined with emphasis on training for the Hubble Space Telescope Repair and Maintenance Mission in 1993. Project ScienceSpace at the Virtual Environment Technology Lab is discussed.

Astronauts/education↗

NASA NTRS1997

Superimposition, symbology, visual attention, and the head-up display

In two experiments we examined a number of related factors postulated to influence head-up display (HUD) performance. We addressed the benefit of reduced scanning and the cost of increasing the number of elements in the visual field by comparing a superimposed HUD with an identical display in a head-down position in varying visibility conditions. We explored the extent to which the characteristics of HUD symbology support a division of attention by contrasting conformal symbology (which links elements of the display image to elements of the far domain) with traditional instrument landing system (ILS) symbology. Together the two experiments provide strong evidence that minimizing scanning between flight instruments and the far domain contributes substantially to the observed HUD performance advantage. Experiment 1 provides little evidence for a performance cost attributable to visual clutter. In Experiment 2 the pattern of differences in lateral tracking error between conformal and traditional ILS symbology supports the hypothesis that, to the extent that the symbology forms an object with the far domain, attention may be divided between the superimposed image and its counterpart in the far domain.

Attention↗

NASA NTRS2000

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service

With high-resolution network transmission required for telemedicine, education, and guided-image acquisition, the impact of errors and transmission rates on image quality needs evaluation. METHODS: We transmitted clinical echocardiograms from 2 National Aeronautics and Space Administration (NASA) research centers with the use of Motion Picture Expert Group-2 (MPEG-2) encoding and asynchronous transmission mode (ATM) network protocol over the NASA Research and Education Network. Data rates and network quality (cell losses [CLR], errors [CER], and delay variability [CVD]) were altered and image quality was judged. RESULTS: At speeds of 3 to 5 megabits per second (Mbps), digital images were superior to those on videotape; at 2 Mbps, images were equivalent. Increasing CLR caused occasional, brief pauses. Extreme CER and CDV increases still yielded high-quality images. CONCLUSIONS: Real-time echocardiographic acquisition, guidance, and transmission is feasible with the use of MPEG-2 and ATM with broadcast quality seen above 3 Mbps, even with severe network quality degradation. These techniques can be applied to telemedicine and used for planned echocardiography aboard the International Space Station.

NASA Discipline Cardiopulmonary↗

NASA NTRS1999

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

Evoked Potentials↗

NASA NTRS1996

A system for the accurate measurement of pointing responses

We present an accurate, yet relatively inexpensive, system for measuring the direction of pointing responses. This system utilizes off-the-shelf business presentation components in a novel way to help detect and quantify the pointing measurements. The system configuration, measurement features, and procedures to enhance measurement accuracy are described.

NASA Center JSC↗

NASA NTRS2003

Enabling computer decisions based on EEG input

Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

Validation Studies↗

NASA NTRS2005

Revealing Relationships among Relevant Climate Variables with Information Theory

The primary objective of the NASA Earth-Sun Exploration Technology Office is to understand the observed Earth climate variability, thus enabling the determination and prediction of the climate's response to both natural and human-induced forcing. We are currently developing a suite of computational tools that will allow researchers to calculate, from data, a variety of information-theoretic quantities such as mutual information, which can be used to identify relationships among climate variables, and transfer entropy, which indicates the possibility of causal interactions. Our tools estimate these quantities along with their associated error bars, the latter of which is critical for describing the degree of uncertainty in the estimates. This work is based upon optimal binning techniques that we have developed for piecewise-constant, histogram-style models of the underlying density functions. Two useful side benefits have already been discovered. The first allows a researcher to determine whether there exist sufficient data to estimate the underlying probability density. The second permits one to determine an acceptable degree of round-off when compressing data for efficient transfer and storage. We also demonstrate how mutual information and transfer entropy can be applied so as to allow researchers not only to identify relations among climate variables, but also to characterize and quantify their possible causal interactions.

Knuth, Kevin H.↗

NASA NTRS2008

MCNPX Cosmic Ray Shielding Calculations with the NORMAN Phantom Model

The United States is planning manned lunar and interplanetary missions in the coming years. Shielding from cosmic rays is a critical aspect of manned spaceflight. These ventures will present exposure issues involving the interplanetary Galactic Cosmic Ray (GCR) environment. GCRs are comprised primarily of protons (approx.84.5%) and alpha-particles (approx.14.7%), while the remainder is comprised of massive, highly energetic nuclei. The National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has commissioned a joint study with Los Alamos National Laboratory (LANL) to investigate the interaction of the GCR environment with humans using high-fidelity, state-of-the-art computer simulations. The simulations involve shielding and dose calculations in order to assess radiation effects in various organs. The simulations are being conducted using high-resolution voxel-phantom models and the MCNPX[1] Monte Carlo radiation-transport code. Recent advances in MCNPX physics packages now enable simulated transport over 2200 types of ions of widely varying energies in large, intricate geometries. We report here initial results obtained using a GCR spectrum and a NORMAN[3] phantom.

James, Michael R.↗

NASA NTRS2010

Miniature Bioreactor System for Long-Term Cell Culture

A prototype miniature bioreactor system is designed to serve as a laboratory benchtop cell-culturing system that minimizes the need for relatively expensive equipment and reagents and can be operated under computer control, thereby reducing the time and effort required of human investigators and reducing uncertainty in results. The system includes a bioreactor, a fluid-handling subsystem, a chamber wherein the bioreactor is maintained in a controlled atmosphere at a controlled temperature, and associated control subsystems. The system can be used to culture both anchorage-dependent and suspension cells, which can be either prokaryotic or eukaryotic. Cells can be cultured for extended periods of time in this system, and samples of cells can be extracted and analyzed at specified intervals. By integrating this system with one or more microanalytical instrument(s), one can construct a complete automated analytical system that can be tailored to perform one or more of a large variety of assays.

Gonda, Steve R.↗

NASA NTRS2019

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

NASA NTRS1994

(abstract) Modeling Protein Families and Human Genes: Hidden Markov Models and a Little Beyond

We will first give a brief overview of Hidden Markov Models (HMMs) and their use in Computational Molecular Biology. In particular, we will describe a detailed application of HMMs to the G-Protein-Coupled-Receptor Superfamily. We will also describe a number of analytical results on HMMs that can be used in discrimination tests and database mining. We will then discuss the limitations of HMMs and some new directions of research. We will conclude with some recent results on the application of HMMs to human gene modeling and parsing.

Hidden Markov Models HMMs proteins computational m↗

NASA NTRS2013

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Feiveson, Alan↗

NASA NTRS1994

A comparison of paper and computer procedures in a Shuttle flight environment

The Electronic Procedures Experiment (EPROC) was flown as part of the Human Factors Assessment (HFA) experiment aboard the SpaceHab-1/STS-57 mission. EPROC is concerned with future, longer-duration missions which will increasingly rely on electronic procedures since they are more easily launched, updated in-flight, and offer automatic or on-request capabilities not available with paper. A computer-based task simulating a Space Station Propulsion System task was completed by one crewmember. The crewmember performed the task once using paper and once using computer procedures. A soldering and desoldering task was performed by another crewmember. Soldering was completed with paper procedures and desoldering was completed using computer procedures. Objective data was collected during each task session from the computer programs, videotapes, and crew notations in the paper and computer procedures. After each task session, subjective data was collected through the use of a computer-based questionnaire program. Resultant recommendations will be made available to future designers of electronic procedures systems for manned-space missions and other related uses.

Michael O'Neal↗