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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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NASA NTRS1993

Alterations in skeletal muscle related to impaired physical mobility: an empirical model

The objective of this investigation was to study impaired physical mobility and the resulting skeletal muscle atrophy. An animal model was used to study morphological adaptations of the soleus and plantaris muscles to decreased loading induced by hindlimb suspension of an adult rat for 7, 14, and 28 consecutive days. Alterations in weight, skeletal muscle growth, and changes in fiber type composition were studied in synergistic plantar flexors of the rat hindlimb. Body weight and the soleus muscle mass to body mass ratio demonstrated significant progressive atrophy over th 28-day experimental period with the most significant changes occurring in the first 7 days of hindlimb suspension. Hindlimb suspension produced atrophy of Type I and Type IIa muscle fibers as demonstrated by significant decreases in fiber cross-sectional area (micron 2). These latter changes account for the loss of contractile force production reported in the rat following hindlimb unloading. When compared to traditional models of hindlimb suspension and immobilization, the ISC model produces a less severe atrophy while maintaining animal mobility and health. We conclude that it is the preferred animal model to address nursing questions of impaired physical mobility.

Non-NASA Center↗

NASA NTRS1993

Evidence for reduced cancellous bone mass in the spontaneously hypertensive rat

The histomorphometric changes in the proximal tibial metaphysis and epiphyseal growth plate and midtibial shaft of 26-week-old spontaneously hypertensive rats (SHR) compared with those of the corresponding normotensive Wistar-Kyoto (WKY) rats were studied. A decrease in body weight, growth plate thickness, and longitudinal growth rate of the proximal tibial epiphysis, trabecular bone volume, trabecular thickness and number, the number of osteoblasts and osteoprogenitor cells per millimeter square surface of the proximal tibial metaphysis, periosteal and endocortical apposition rate and bone formation rate of the tibial diaphysis were observed in the SHR. Additionally, systolic blood pressure, the number of osteoclasts per millimeter square surface and average number of nuclei per osteoclast of the proximal tibial metaphysis were significantly increased. Thus, osteoclastic activity is dominant over osteoblastic and chondroblastic activity in the SHR that results in a cancellous bone deficit in the skeleton. It will require additional work to ascertain the underlying cause for this condition as several factors in the SHR with a potential for causing this change are present, including elevated parathyroid hormone (PTH), depressed 1,25-(OH)2D3, low calcium absorption, reduced body weight (reduced loading) elevated blood pressure and possibly other direct cell differences in the mutant strain. At present elevated PTH and adaptation to underloading from reduced weight are postulated to be a likely cause, but additional studies are required to test this interpretation.

NASA Discipline Musculoskeletal↗

NASA NTRS2004

Subjective response of people to simulated sonic booms in their homes

In order to determine the effect of the number of sonic boom occurrences on annoyance, a computer-based system was developed for studying the subjective response of people to the occurrence of simulated sonic booms in their homes. The system provided a degree of control over the noise exposure not found in community surveys and a degree of situational realism not available in the laboratory. A system was deployed for eight weeks in each of 33 homes. Each day from 4 to 63 sonic booms were played as the test subject went about his or her normal activities. At the end of the day, the test subjects rated their annoyance to the sonic booms heard during the day. The sonic booms consisted of different combinations of waveforms, levels, and occurrence rates. The experiment confirmed that the increase in annoyance resulting from multiple occurrences can be modeled by the addition of the term "10 * log(number of occurrences)" to the sonic boom level. Of several noise metrics considered, perceived level was the best annoyance predictor. Comparisons of the subjective responses to the different sonic boom waveforms found no differences that were not accounted for by the noise metrics.

Noise, Transportation/adverse effects↗

NASA NTRS1980

As-built design specification for proportion estimate software subsystem

The Proportion Estimate Processor evaluates four estimation techniques in order to get an improved estimate of the proportion of a scene that is planted in a selected crop. The four techniques to be evaluated were provided by the techniques development section and are: (1) random sampling; (2) proportional allocation, relative count estimate; (3) proportional allocation, Bayesian estimate; and (4) sequential Bayesian allocation. The user is given two options for computation of the estimated mean square error. These are referred to as the cluster calculation option and the segment calculation option. The software for the Proportion Estimate Processor is operational on the IBM 3031 computer.

Obrien, S.↗

NASA NTRS1991

A distributed scheduling algorithm for heterogeneous real-time systems

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Zeineldine, Osman↗

NASA NTRS1977

Optimal spatial sampling techniques for ground truth data in microwave remote sensing of soil moisture

The paper examines optimal sampling techniques for obtaining accurate spatial averages of soil moisture, at various depths and for cell sizes in the range 2.5-40 acres, with a minimum number of samples. Both simple random sampling and stratified sampling procedures are used to reach a set of recommended sample sizes for each depth and for each cell size. Major conclusions from statistical sampling test results are that (1) the number of samples required decreases with increasing depth; (2) when the total number of samples cannot be prespecified or the moisture in only one single layer is of interest, then a simple random sample procedure should be used which is based on the observed mean and SD for data from a single field; (3) when the total number of samples can be prespecified and the objective is to measure the soil moisture profile with depth, then stratified random sampling based on optimal allocation should be used; and (4) decreasing the sensor resolution cell size leads to fairly large decreases in samples sizes with stratified sampling procedures, whereas only a moderate decrease is obtained in simple random sampling procedures.

Rao, R. G. S.↗

NASA NTRS2001

Empirical Analysis of EEG and ERPs for Psychophysiological Adaptive Task Allocation

The present study was designed to test the efficacy of using Electroencephalogram (EEG) and Event-Related Potentials (ERPs) for making task allocation decisions. Thirty-six participants were randomly assigned to an experimental, yoked, or control group condition. Under the experimental condition, a tracking task was switched between task modes based upon the participant's EEG. The results showed that the use of adaptive aiding improved performance and lowered subjective workload under negative feedback as predicted. Additionally, participants in the adaptive group had significantly lower RMSE and NASA-TLX ratings than participants in either the yoked or control group conditions. Furthermore, the amplitudes of the N1 and P3 ERP components were significantly larger under the experimental group condition than under either the yoked or control group conditions. These results are discussed in terms of the implications for adaptive automation design.

Prinzel, Lawrence J., III↗

NASA NTRS1982

Linear discriminant analysis with misallocation in training samples

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Chhikara, R.↗

NASA NTRS2019

PACE Technical Report Series, Volume 6: Data Product Requirements and Error Budgets Consensus Document

This chapter summarizes ocean color science data product requirements for the Plankton, Aerosol, Cloud,ocean Ecosystem (PACE) mission's Ocean Color Instrument (OCI) and observatory. NASA HQ delivered Level-1 science data product requirements to the PACE Project, which encompass data products to be produced and their associated uncertainties. These products and uncertainties ultimately determine the spectral nature of OCI and the performance requirements assigned to OCI and the observatory. This chapter ultimately serves to provide context for the remainder of this volume, which describes tools developed that allocate these uncertainties into their components, including allowable OCI systematic and random uncertainties, observatory geo location uncertainties, and geophysical model uncertainties.

Cetinic, Ivona↗

NASA NTRS1981

Evaluation of the procedure 1A component of the 1980 US/Canada wheat and barley exploratory experiment

Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.

Chapman, G. M.↗

NASA NTRS1980

Dynamic decisions and work load in multitask supervisory control

A paradigm is developed for the problem of allocating in time a single resource to multiple simultaneous task demands which appear randomly, last for various periods, and offer varying rewards for service. Based upon a dynamic optimizing algorithm plus an estimator, and including response time and future discounting constraints, a model of the human decisionmaker is compared to experimental results for human subjects performing such a task at a computer-graphics terminal. Results indicate a reasonable fit, under various model parameters and task conditions, and suggest interesting hypotheses about the nature of human 'planning ahead' and mental work load.

Tulga, M. K.↗

NASA NTRS1991

A Dynamic Testing Complexity Metric

This paper introduces a dynamic metric that is based on the estimated ability of a program to withstand the effects of injected "semantic mutants" during execution by computing the same function as if the semantic mutants had not been injected. Semantic mutants include: (1) syntactic mutants injected into an executing program and (2) randomly selected values injected into an executing program's internal states. The metric is a function of a program, the method used for injecting these two types of mutants, and the program's input distribution; this metric is found through dynamic executions of the program. A program's ability to withstand the effects of injected semantic mutants by computing the same function when executed is then used as a tool for predicting the difficulty that will be incurred during random testing to reveal the existence of faults, i.e., the metric suggests the likelihood that a program will expose the existence of faults during random testing assuming faults were to exist. If the metric is applied to a module rather than to a program, the metric can be used to guide the allocation of testing resources among a program's modules. In this manner the metric acts as a white-box testing tool for determining where to concentrate testing resources. Index Terms: Revealing ability, random testing, input distribution, program, fault, failure.

Voas, Jeffrey↗

NASA NTRS1992

Sharing Resources In Mobile/Satellite Communications

Report presents preliminary theoretical analysis of several alternative schemes for allocation of satellite resource among terrestrial subscribers of landmobile/satellite communication system. Demand-access and random-access approaches under code-division and frequency-division concepts compared.

Yan, Tsun-Yee↗

NASA NTRS1997

Two Extremely Red Galaxies

This report concerns one of the major observational studies in the ISO Central Programme, the ISO Normal Galaxy Survey. This is a survey of an unbiased sample of spiral and lenticular galaxies selected from the Revised Shapley-Ames Catalog. It is therefore optically-selected, with a brightness limit of blue magnitude = 12, and otherwise randomly chosen. The original sample included 150 galaxies, but this was reduced to 74 when the allocated observing time was expended because the ISO overheads encountered in flight were much larger than predicted.

Joseph, Robert D.↗

NASA NTRS1987

The correspondence of surface climate parameters with satellite and terrain data

One of the goals of the research was to develop a ground sampling stragegy for calibrating remotely sensed measurements of surface climate parameters. The initial sampling strategy involved the stratification of the terrain based on important ancillary surface variables such as slope, exposure, insolation, geology, drainage, fire history, etc. For a spatially heterogeneous population, sampling error is reduced and efficiency increased by stratification of the landscape into more homogeneous sub-areas and by employing periodic random spacing of samples. These concepts were applied in the initial stratification of the study site for the purpose of locating and allocating instrumentation.

Dozier, Jeff↗

NASA NTRS2021

Scheduling the NASA Deep Space Network with Deep Reinforcement Learning

With three complexes spread evenly across the Earth, NASA’s Deep Space Network (DSN) is the primary means of communications as well as a significant scientific instrument for dozens of active missions around the world. A rapidly rising number of spacecraft and increasingly complex scientific instruments with higher bandwidth requirements have resulted in demand that exceeds the network’s capacity across its 12 antennae. The existing DSN scheduling process operates on a rolling weekly basis and is time-consuming; for a given week, generation of the final baseline schedule of spacecraft tracking passes takes roughly 5 months from the initial requirements submission deadline, with several weeks of peer-to-peer negotiations in between. This paper proposes a deep reinforcement learning (RL) approach to generate candidate DSN schedules from mission requests and spacecraft ephemeris data with demonstrated capability to address real-world operational constraints. A deep RL agent is developed that takes mission requests for a given week as input, and interacts with a DSN scheduling environment to allocate tracks such that its reward signal is maximized. A comparison is made between an agent trained using Proximal Policy Optimization and its random, untrained counterpart. The results represent a proof-of-concept that, given a well-shaped reward signal, a deep RL agent can learn the complex heuristics used by experts to schedule the DSN. A trained agent can potentially be used to generate candidate schedules to bootstrap the scheduling process and thus reduce the turnaround cycle for DSN scheduling.

Wilson, Brian↗

NASA NTRS1985

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.↗

NASA NTRS1992

Learning and optimization with cascaded VLSI neural network building-block chips

To demonstrate the versatility of the building-block approach, two neural network applications were implemented on cascaded analog VLSI chips. Weights were implemented using 7-b multiplying digital-to-analog converter (MDAC) synapse circuits, with 31 x 32 and 32 x 32 synapses per chip. A novel learning algorithm compatible with analog VLSI was applied to the two-input parity problem. The algorithm combines dynamically evolving architecture with limited gradient-descent backpropagation for efficient and versatile supervised learning. To implement the learning algorithm in hardware, synapse circuits were paralleled for additional quantization levels. The hardware-in-the-loop learning system allocated 2-5 hidden neurons for parity problems. Also, a 7 x 7 assignment problem was mapped onto a cascaded 64-neuron fully connected feedback network. In 100 randomly selected problems, the network found optimal or good solutions in most cases, with settling times in the range of 7-100 microseconds.

Duong, T.↗