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NASA NTRS1992

Anthropomorphic teleoperation: Controlling remote manipulators with the DataGlove

A two phase effort was conducted to assess the capabilities and limitations of the DataGlove, a lightweight glove input device that can output signals in real-time based on hand shape, orientation, and movement. The first phase was a period for system integration, checkout, and familiarization in a virtual environment. The second phase was a formal experiment using the DataGlove as input device to control the protoflight manipulator arm (PFMA) - a large telerobotic arm with an 8-ft reach. The first phase was used to explore and understand how the DataGlove functions in a virtual environment, build a virtual PFMA, and consider and select a reasonable teleoperation control methodology. Twelve volunteers (six males and six females) participated in a 2 x 3 (x 2) full-factorial formal experiment using the DataGlove to control the PFMA in a simple retraction, slewing, and insertion task. Two within-subjects variables, time delay (0, 1, and 2 seconds) and PFMA wrist flexibility (rigid/flexible), were manipulated. Gender served as a blocking variable. A main effect of time delay was found for slewing and total task times. Correlations among questionnaire responses, and between questionnaire responses and session mean scores and gender were computed. The experimental data were also compared with data collected in another study that used a six degree-of-freedom handcontroller to control the PFMA in the same task. It was concluded that the DataGlove is a legitimate teleoperations input device that provides a natural, intuitive user interface. From an operational point of view, it compares favorably with other 'standard' telerobotic input devices and should be considered in future trades in teleoperation systems' designs.

Hale, J. P., II↗
NASA NTRS1990

The stability of individual patterns of autonomic responses to motion sickness stimulation

As part of a program to develop a treatment for motion sickness based on self-regulation of autonomic nervous system (ANS) activity, this study examined the stability of an individual's pattern of ANS responses to motion sickness stimulation on repeated occasions. Motion sickness symptoms were induced in 58 people during two rotating chair test. Physiological responses measured were heart rate, finger pulse volume, respiration rate, and skin conductance. Using standard scores, stability of responses of specific magnitudes across both tests is as examined. Correlational analyses, analysis of variance, and a components of variance analysis all revealed marked, but quite stable, individual differences in ANS responses to both mild and severe motion sickness. These findings confirm the prior observation that people are sufficiently unique in their ANS responses to motion sickness provocation to make it nesessary to individually tailor self-regulation training. Further, these data support the contention that individual ANS patterns are sufficiently consistent from test to test so as to serve as an objective indicator of individual motion sickness malaise levels.

Cowings, Patricia S.↗
NASA NTRS2007

Middleware Trade Study for NASA Domain

This presentation presents preliminary results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are: the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL

Bowman, Dan↗
NASA NTRS2008

NASA Constellation Distributed Simulation Middleware Trade Study

This paper presents the results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL.

Hasan, David↗
NASA NTRS2018

A Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Lessons learned from past failures of launch vehicle developments and operations were used to create a new method to predict the probability of failure of conceptual systems. Existing methods such as Probabilistic Risk Assessments and Human Risk Assessments were considered but found to be too cumbersome for this type of system-wide application for yet-to-be-flown vehicles. The basis for this methodology were historic databases of past failures, where it was determined that various faulty human-interactions were the predominant root causes of failure rather than deficient component reliabilities evaluated through statistical analysis. This methodology contains an expert scoring part which can be used in either a qualitative or a quantitative mode. The method produces two products: a numerical score of the probability of failure and guidance to program management on critical areas in need of increased focus to improve the probability of success. In order to evaluate the effectiveness of this new method, data from a concluded vehicle program (USAF's Titan IV with the Centaur G-Prime upper stage) was used as a test case. The theoretical vs. actual probability of failure was found to be 4.46% vs. 6.67% respectively. Recommendations are made for future applications of this method to ongoing launch vehicle development programs.

Launch Vehicle↗
NASA NTRS2019

Prognostic Launch Vehicle Probability of Failure Assessment Methodology for Conceptual Systems Predicated on Human Causal Factors

Lessons learned from past failures of launch vehicle developments and operations were used to create a new method to predict the probability of failure of conceptual systems. Existing methods such as Probabilistic Risk Assessments and Human Risk Assessments were considered but found to be too cumbersome for this type of system-wide application for yet-to-be-flown vehicles. The basis for this methodology were historic databases of past failures, where it was determined that various faulty human-interactions were the predominant root causes of failure rather than deficient component reliabilities evaluated through statistical analysis. This methodology contains an expert scoring part which can be used in either a qualitative or a quantitative mode. The method produces two products: a numerical score of the probability of failure or guidance to program management on critical areas in need of increased focus to improve the probability of success. In order to evaluate the effectiveness of this new method, data from a concluded vehicle program (USAF's Titan IV with the Centaur G-Prime upper stage) was used as a test case. Although the theoretical vs. actual probability of failure was found to be in reasonable agreement (4.46% vs. 6.67% respectively) the underlying sub-root cause scoring had significant disparities attributable to significant organizational changes and acquisitions. Recommendations are made for future applications of this method to ongoing launch vehicle development programs.

Craig H Williams↗
NASA NTRS2017

Systemic Response to Microgravity: Utilizing GeneLab Datasets to Identify Molecular Targets for Future Hypotheses-Driven Spaceflight Studies

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF(beta)1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF(beta)1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales.

GeneLab↗
NASA NTRS2001

Asthenia--does it exist in space?

OBJECTIVE: First popularized as neurasthenia in the late 1800s by American George Beard, asthenia has been viewed by Russian psychologists and flight surgeons as a major problem that affects cosmonauts participating in long-duration space missions. However, there is some controversy about whether this syndrome exists in space; this controversy is attributable in part to the fact that it is not recognized in the current American psychiatric diagnostic system. METHODS: To address this issue empirically, we retrospectively examined the data from our 4 1/2-year, NASA-funded study of crew member and mission control interactions during the Shuttle/Mir space program. Three of the authors identified eight items of stage 1 asthenia from one of our measures, the Profile of Mood States (POMS). Scores on these items from 13 Russian and American crew members were compared with scores derived from the opinions of six Russian space experts. RESULTS: Crew members' scores in space were significantly lower than the experts' scores on seven of the eight items, and they generally were in the "not at all" to "a little" range of the item scales. There were no differences in mean scores before and after launch or across the four quarters of the missions. There were no differences in response between Russian and American crew members. CONCLUSIONS: We could not demonstrate the presence of asthenia in space as operationally defined using the POMS. However, the POMS addresses only emotional and not physiological aspects of the syndrome, and the subject responses in our study generally were skewed toward the positive end of the scales. Further research on this syndrome needs to be done and should include physiological measures and measures that are specific to asthenia.

Non-NASA Center↗
NASA NTRS2018

Meal Replacement Mass Reduction Integration and Acceptability Study

The Orion Multi-Purpose Crew Vehicle (MPCV) and future exploration missions are mass constrained; therefore we are challenged to reduce the mass of the food system by 10% while maintaining safety, nutrition, and acceptability to support crew health and performance for exploration missions. Meal replacement with nutritionally balanced, 700-900 calorie bars was identified as a method to reduce mass. However, commercially available products do not meet the requirements for a meal replacement in the spaceflight food system. The purpose of this task was to develop a variety of nutritionally balanced, high quality, breakfast replacement bars, which enable a 10% food mass savings. To date, six nutrient-dense meal replacement bars have been developed, all of which meet spaceflight nutritional, microbiological, sensory, and shelf-life requirements. The four highest scoring bars were evaluated based on final product sensory acceptability, nutritional stability, qualitative stability of analytical measurements (i.e. color and texture), and microbiological compliance over a period of two years to predict long-term acceptability. All bars maintained overall acceptability throughout the first year of storage, despite minor changes in color and texture. However, added vitamins C, B1, and B9 degraded rapidly in fortified samples of Banana Nut bars, indicating the need for additional development. In addition to shelf-life testing, four bar varieties were evaluated in the Human Exploration Research Analog (HERA), campaign 3, to assess the frequency with which actual meal replacement options may be implemented, based on impact to satiety and psychosocial measurements. Crewmembers (n=16) were asked to consume meal replacement bars every day for the first fifteen days of the mission and every three days for the second half of the mission. Daily surveys assessed the crew's responses to bar acceptability, mood, food fatigue and perceived stress. Preliminary results indicate that the majority of crew members were noncompliant with daily meal replacement during the first half of the mission. Several crew members chose to forgo the meal, resulting in caloric deficits that were higher on skipped-bar days. Body mass loss was significant throughout the mission. Although there was no significant difference in body mass loss overall between the first half and second half of the mission, a higher number of individual crew members lost more body mass in the first half of the mission. Analysis is still ongoing, but current trends suggest that daily involuntary meal replacement can lead to greater individual impacts on body mass and psychological factors, while meal replacement on a more limited basis may be acceptable to most crew for missions up to 30 days. This data should be considered in Orion mass trades with health and human performance.

Sirmons, T.↗
NASA NTRS1995

Site selection for Mars exobiology

The selection of sites on Mars that have a high priority for exobiological research is fundamental for planning future exploration. The most immediate need is to identify targets for high resolution orbital imaging during the Mars Observer and Mars '94/'96 missions that can be used to refined site priorities for surface exploration. We present an objective approach to site selection whereby individual sites are selected and scored, based on the presence of key geological features which indicate high priority environments. Prime sites are those that show evidence for the prolonged activity of liquid water and which have sedimentary deposits that are likely to have accumulated in environments favorable for life. High priority areas include fluvio-lacustrine (stream-fed lake systems), springs, and periglacial environments. Sites where mineralization may have occurred in the presence of organisms (e.g. springs) are given high priority in the search for a fossil record on Mars. A systematic review of Viking data for 83 sites in the Mars Landing Site Catalog (MLSC) resulted in the selection of 13 as being of exobiological interest. The descriptions of these sites were expanded to address exobiological concerns. An additional five sites were identified for inclusion in the second edition of the MLSC. We plan to broaden our site selection activities to include a systematic global reconnaissance of Mars using Viking data, and will continue to refine site priorities for exobiological research based on data from future missions in order to define strategies for surface exploration.

Farmer, J.↗
NASA NTRS2014

Defining the Relationship between Biomarkers of Oxidative and Inflammatory Stress and the Risk for Atherosclerosis in Astronauts during and after Long-duration Spaceflight

Future human space travel will consist primarily of long-duration missions onboard the International Space Station (ISS) or exploration-class missions to Mars, its moons, or nearby asteroids. These missions will expose astronauts to increased risk of oxidative and inflammatory damage from a variety of sources, including radiation, psychological stress, reduced physical activity, diminished nutritional status, and hyperoxic exposure during extravehicular activity. Evidence exists that increased oxidative damage and inflammation can accelerate the development of atherosclerosis. PURPOSE The purpose of this investigation is to determine whether biomarkers of oxidative and inflammatory stress are elevated during and after long-duration spaceflight and investigate if a relation exists between levels of these biomarkers and structural and functional indices of atherosclerotic risk measured in the carotid and brachial arteries. This is the first study to propose assessing atherosclerotic risk using biochemical, structural, and functional measures before, during, and immediately after spaceflight, and structural and functional measures for up to 5 years after landing. METHODS We will study 12 astronauts before, during, and up to 5 years after long-duration ISS missions. A panel of biomarkers of oxidative and inflammatory stress will be measured twice before flight, early (flight days 15 and 60) and late (2 weeks before landing) during the mission, and early in the postflight recovery phase (approx 3 days after landing). Arterial structure and vascular compliance will be measured at the same times and also at 1, 3, and 5 years after landing (surveillance). Arterial function will be measured using the same preflight, postflight, and surveillance schedule as arterial structure and vascular compliance measures, but will not be measured inflight. Biomarkers, some of which we have previously shown to be elevated with spaceflight, will be measured in venous blood samples and 24-h (in-flight) and 48-h (pre- and post-flight) urine pools. Arterial structure will be assessed from measures of carotid intima-media thickness, which have been shown to be better indicators of atherosclerotic than the Framingham Risk Score. Arterial function will be assessed using brachial flow-mediated dilation, a well-validated measure used to assess endothelium-dependent vasodilation and is a sensitive predictor of atherosclerotic risk. Arterial pulse pressure measured in the brachial artery and stroke volume measured from cardiac ultrasound will be used to assess hemodynamic status, cardiac function, and systemic vascular compliance. Three astronauts are actively participating in the preflight data collection and training activities. One astronaut has completed all preflight activities and will participate in the first in-flight data collection sessions by the end of 2013. The first post-flight data collection sessions will occur in the spring of 2014. EXPECTED RESULTS We hypothesize that biomarkers of oxidative and inflammatory stress will increased with spaceflight and will correlate with increased carotid intima-media thickness during and after flight and with decreased flow-mediated dilation after the mission. Furthermore, we hypothesize that measures of oxidative stress will return to baseline after flight, but biomarkers of inflammatory stress and vascular indices of atherosclerotic risk will remain elevated.

Lee, Stuart M. C.↗
NASA NTRS2018

Bringing Climate Scientist's Tools into Classrooms to Improve Conceptual Understandings

Efforts to address anthropogenic global climate change (AGCC) require public understanding of Earth and climate science. To meet this need, educational reforms and prominent scientists have called for instructional approaches that teach students how climate scientists examine AGCC. Yet, only a few educational studies have reported clear empirical results on what instructional approaches and climate education technologies best accomplish this goal. This manuscript presents detailed analysis and statistically significant results on the educational impact pre to post of students learning to use a National Aeronautics and Space Administration (NASA) global climate model (GCM). This series of case studies demonstrates that differing instructional approaches and climate education technologies result in differing levels of understanding of AGCC and ability to engage with policies addressing it. Students who learned the scientific process of climate modeling scored significantly higher pre to post on exams (quantitatively) and gained more complete conceptual understandings of the issue (qualitatively). Yet, teaching students to conduct research with complex technology can be difficult. This study also found lecture-based learning better improved recall of facts about GCMs tested by multiple-choice questions. Our findings indicate what educational systems and related technologies might provide the public with the conceptual understandings necessary to engage in the political debate over AGCC.

Public understanding↗
NASA NTRS2019

Space Research Project Management Can Benefit from Engineering Technology Selection Methods

Many engineering methods have been developed to help management select technology for a system design or further research. The simplest way to compare technologies is to use a checklist containing all the more or less important selection criteria, so that nothing is overlooked. The criteria usually include cost, safety, reliability and maintainability, and potential problems such as noise generation and microgravity sensitivity. The next step typically is to weight and score all the criteria. The process of weighting and scoring is helpful in bringing out different priorities and reaching a shared point of view. Group technology selection methods are designed to highlight initial disagreements and produce a shared consensus. Often a frank discussion led by management rather than decision analysts can be more effective. The final selection depends on management and engineering judgment and may include programmatic and organizational factors that are beyond the engineering checklist. The objective of engineering technology selection methods is to provide engineering information to assist management in making sound decisions. Project management and technology selection are assumed to use rational engineering analytic methods, but they often do not. The reason is that human insight, intuition, and “gut feel,” rather than logic, more frequently determine our decisions. Project selection and management are strongly influenced by nonrational psychological influences, which can produce unjustified confidence and determination. Nevertheless, there is a strong need for space projects to do rational project analysis and selection. Demonstrating a rational spirit is necessary for a scientific and technical organization. Professional ethics at its best requires an open, honest, and fair process, without damaging politics. Rational analysis can help improve good projects and avoid selecting bad ones. A sanity check using rational analysis guided by a checklist can help avoid egregious and damaging errors.

Jones, Harry W.↗
NASA NTRS2017

Application of Machine Learning to Rotorcraft Health Monitoring

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

machine learning↗
NASA NTRS2018

Predicting the Operational Acceptance of Airborne Flight Reroute Requests Using Data Mining

For tools that generate more efficient flight routes or reroute advisories, it is important to ensure compatibility of automation and autonomy decisions with human objectives so as to ensure acceptability by the human operators. In this paper, the authors developed a proof of concept predictor of operational acceptability for route changes during a flight. Such a capability could have applications in automation tools that identify more efficient routes around airspace impacted by weather or congestion and that better meet airline preferences. The predictor is based on applying data mining techniques, including logistic regression, a decision tree, a support vector machine, a random forest and Adaptive Boost, to historical flight plan amendment data reported during operations and field experiments. Cross validation was used for model development, while nested cross validation was used to validate the models. The model found to have the best performance in predicting air traffic controller acceptance or rejection of a route change, using the available data from Fort Worth Air Traffic Control Center and its adjacent Centers, was the random forest, with an F-score of 0.77. This result indicates that the operational acceptance of reroute requests does indeed have some level of predictability, and that, with suitable data, models can be trained to predict the operational acceptability of reroute requests. Such models may ultimately be used to inform route selection by decision support tools, contributing to the development of increasingly autonomous systems that are capable of routing aircraft with less human input than is currently the case.

Operational Acceptability↗
NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗
NASA NTRS1973

Intelligibility improvement of analog communication systems using an amplitude control technique.

An amplitude control technique has been employed for use with analog voice communication systems, which improves low-level phoneme reception and eliminates the received noise between words and syllables. Tests were conducted on a narrow-band frequency-modulation simplex voice communication channel employing the amplitude control technique. Presented for both the modified rhyme word tests and the phonetically balanced word tests are a series of graphical plots of the tests' score distribution, mean, and standard deviation as a function of received carrier-to-noise power density ratio. At low received carrier-to-noise power density ratios, a significant improvement in the intelligibility was obtained. A voice intelligibility improvement of more than 2 dB was obtained for the modified rhyme test words, and a voice intelligibility improvement in excess of 4 dB was obtained for the phonetically balanced word tests.

Wishna, S.↗
NASA NTRS2004

The Airline Quality Rating 2004

The Airline Quality Rating (AQR) was developed and first announced in early 1991 as an objective method of comparing airline quality on combined multiple performance criteria. This current report, the Airline Quality Rating 2004, reflects monthly Airline Quality Rating scores for 2003. AQR scores for the calendar year 2003 are based on 15 elements in four major areas that focus on airline performance aspects important to air travel consumers. The Airline Quality Rating 2004 is a summary of month-by-month quality ratings for U.S. airlines that have at least 1 % of domestic passenger volume during 2003. Using the Airline Quality Rating system of weighted averages and monthly performance data in the areas of on-time arrivals, involuntary denied boardings, mishandled baggage, and a combination of 12 customer complaint categories, airlines comparative performance for the calendar year of 2003 is reported. This research monograph contains a brief summary of the AQR methodology, detailed data and charts that track comparative quality for domestic airline operations for the 12-month period of 2003, and industry results. Also, comparative Airline Quality Rating data for 2002 are included, where available, to provide historical perspective regarding performance quality in the industry.

Fink, Mary M.↗