Results for “software estimation” — Page 17

NASA NTRS1993

Software engineering methodologies and tools

Over the years many engineering disciplines have developed, including chemical, electronic, etc. Common to all engineering disciplines is the use of rigor, models, metrics, and predefined methodologies. Recently, a new engineering discipline has appeared on the scene, called software engineering. For over thirty years computer software has been developed and the track record has not been good. Software development projects often miss schedules, are over budget, do not give the user what is wanted, and produce defects. One estimate is there are one to three defects per 1000 lines of deployed code. More and more systems are requiring larger and more complex software for support. As this requirement grows, the software development problems grow exponentially. It is believed that software quality can be improved by applying engineering principles. Another compelling reason to bring the engineering disciplines to software development is productivity. It has been estimated that productivity of producing software has only increased one to two percent a year in the last thirty years. Ironically, the computer and its software have contributed significantly to the industry-wide productivity, but computer professionals have done a poor job of using the computer to do their job. Engineering disciplines and methodologies are now emerging supported by software tools that address the problems of software development. This paper addresses some of the current software engineering methodologies as a backdrop for the general evaluation of computer assisted software engineering (CASE) tools from actual installation of and experimentation with some specific tools.

Wilcox, Lawrence M.↗

NASA NTRSDate not supplied

Predicting GPS Fidelity in Heavily Forested Areas

There is a compelling need to advance the safety of low altitude flight in forested areas. Signal scattering by trees can interfere with GNSS signal reception and can cause navigation loss within and adjacent to woodlands. An estimate of the signal loss vs. foliage depth is needed to quantify navigational degradation by trees at low altitudes. A previous report described a method which attempts to quantify satellite signal degradation caused by foliage by comparing carrier-to-noise ratio (C/N0) to foliage depth along geometric rays cast from the receiver location to the orbital position of GNSS satellites through a 3D matrix of terrain data. A characteristic curve of attenuation vs. foliage depth was found for both L1 and L2 signals at a single forested site. The current study replicates this result at three additional sites, describes refinements to the method, and explores inherent uncertainties that arise from radiofrequency fading and from receiver limitations for weak signals. For the sites surveyed, 60% and 90% of navigational signal is lost at 10m and 20m of foliage depth, respectively. Since this technique uses low-cost hardware and readily available data collection software, it can allow aviators to estimate GNSS position fidelity in flight ranges near trees.

GPS↗

NASA NTRSDate not supplied

Predicting GPS Fidelity in Heavily Forested Areas

There is a compelling need to advance the safety of low altitude flight in forested areas. Signal scattering by trees can interfere with GNSS signal reception and can cause navigation loss within and adjacent to woodlands. An estimate of the signal loss vs. foliage depth is needed to quantify navigational degradation by trees at low altitudes. A previous report described a method which attempts to quantify satellite signal degradation caused by foliage by comparing carrier-to-noise ratio (C/N0) to foliage depth along geometric rays cast from the receiver location to the orbital position of GNSS satellites through a 3D matrix of terrain data. A characteristic curve of attenuation vs. foliage depth was found for both L1 and L2 signals at a single forested site. The current study replicates this result at three additional sites, describes refinements to the method, and explores inherent uncertainties that arise from radiofrequency fading and from receiver limitations for weak signals. For the sites surveyed, 60% and 90% of navigational signal is lost at 10m and 20m of foliage depth, respectively. Since this technique uses low-cost hardware and readily available data collection software, it can allow aviators to estimate GNSS position fidelity in flight ranges near trees.

GPS↗

NASA NTRS2003

Developing fault models for space mission software

Over the past several years, we have focused on developing fault models for space mission software. In general, these models use measurable attributes of a software system and its development process to estimate the number of faults inserted into the system during its development; their outputs can be used to better estimate the resources to be allocated to fault identification and removal for all system components.

fault models software development software archite↗

NASA NTRS2014

Variation in Sleep Duration and Circadian Phase by Duty Start Time Among Short-Haul Commercial Airline Pilots

Prior studies have confirmed that commercial airline pilots experience circadian phase shifts and short sleep duration following travel with layovers in different time zones. Few studies have examined the impact of early and late starts on the sleep and circadian phase of airline pilots who return to their domicile after each duty period. We recruited 44 pilots (4 female) from a short-haul commercial airline to participate in a study examining sleep and circadian phase over four duty schedules (baseline, early starts, mid-day starts, late starts). Each duty schedule was five days long, separated by three rest days. Participants completed the rosters in the same order. Sleep outcomes were estimated using wrist-borne actigraphy (Actiware Software, Respironics, Bend, OR) and daily sleep diaries. Thirteen participants volunteered to collect urine samples for the assessment of 6-sulfatoxymelatonin (aMT6s). Urine samples were collected in four hourly bins during the day and eight-hourly bins during sleep episodes, for 24 hours immediately following each experimental duty schedule. The aMT6s results were fit to a cosine in order to obtain the acrophase to estimate circadian phase. Univariate statistics were calculated for acrophase changes, schedule start times and sleep times. All statistical analyses were computed using SAS software (Cary, IN).The mean duty start times varied as expected (baseline 10:17 [ 3:50], early starts 5:24 [ 0:30], mid-day starts 13:52 [ 1:20], late starts 16:33 [ 1:33]). Actigraphy-derived sleep duration varied between schedule types, with the shortest average sleep durations occurring during the early starts and night duty. Mean circadian phase was similar during each schedule type (baseline 26:14 [ 3:22], early starts 25:29 [2:13], mid-day starts 26:20 [ 3:16], late starts 25:49 [ 4:28]), but there were wide inter-individual differences in phase shifting from the beginning to the end of the study, with phase shifts ranging from a 5.98 hour phase advance to an 11.34 hour phase delay. Our preliminary findings suggest that early and late starts are associated with reduced sleep duration. The dispersion in inter-individual differences in circadian phase across shifting duty schedules should be further evaluated to determine how schedule-induced phase shifts may affect operational performance.

Flynn-Evans, Erin↗

NASA NTRS2016

Variations in Sleep and Performance by Duty Start Time in Short Haul Operations

Prior studies have confirmed that commercial airline pilots experience circadian phase shifts and short sleep duration following travel with layovers in different time zones. Few studies have examined the impact of early and late starts on the sleep and circadian phase of airline pilots who return to their domicile after each duty period. We recruited 44 pilots (4 female) from a short-haul commercial airline to participate in a study examining sleep and circadian phase over four duty schedules (baseline, early starts, mid-day starts, late starts). Each duty schedule was five days long, separated by three rest days. Participants completed the rosters in the same order. Sleep outcomes were estimated using wrist-borne actigraphy (Actiware Software, Respironics, Bend, OR) and daily sleep diaries. Thirteen participants volunteered to collect urine samples for the assessment of 6-sulfatoxymelatonin (aMT6s). Urine samples were collected in four-hourly bins during the day and eight-hourly bins during sleep episodes, for 24 hours immediately following each experimental duty schedule. The aMT6s results were fit to a cosine in order to obtain the acrophase to estimate circadian phase. Univariate statistics were calculated for acrophase changes, schedule start times and sleep times. All statistical analyses were computed using SAS software (Cary, IN).

fatigue↗

NASA NTRS1979

Digital adaptive controllers for VTOL vehicles. Volume 2: Software documentation

The VTOL approach and landing test (VALT) adaptive software is documented. Two self-adaptive algorithms, one based on an implicit model reference design and the other on an explicit parameter estimation technique were evaluated. The organization of the software, user options, and a nominal set of input data are presented along with a flow chart and program listing of each algorithm.

Hartmann, G. L.↗

NASA NTRS1977

Identification of Spey engine dynamics in the augmentor wing jet STOL research aircraft from flight data

The development and validation of a spey engine model is described. An analysis of the dynamical interactions involved in the propulsion unit is presented. The model was reduced to contain only significant effects, and was used, in conjunction with flight data obtained from an augmentor wing jet STOL research aircraft, to develop initial estimates of parameters in the system. The theoretical background employed in estimating the parameters is outlined. The software package developed for processing the flight data is described. Results are summarized.

Dehoff, R. L.↗

NASA NTRS1993

SAR terrain classifier and mapper of biophysical attributes

In preparation for the launch of SIR-C/X-SAR and design studies for future orbital SAR, a program has made considerable progress in the development of an SAR terrain classifier and algorithms for quantification of biophysical attributes. The goal of this program is to produce a generalized software package for terrain classification and estimation of biophysical attributes and to make this package available to the larger scientific community. The basic elements of the SAR (Synthetic Aperture Radar) terrain classifier are outlined. An SAR image is calibrated with respect to known system and processor gains and external targets (if available). A Level 1 classifier operates on the data to differentiate: urban features, surfaces and tall and short vegetation. Level 2 classifiers further subdivide these classes on the basis of structure. Finally, biophysical and geophysical inversions are applied to each class to estimate attributes of interest. The process used to develop the classifiers and inversions is shown. Radar scattering models developed from theory and from empirical data obtained by truck-mounted polarimeters and the JPL AirSAR are validated. The validated models are used in sensitivity studies to understand the roles of various scattering sources (i.e., surface trunk, branches, etc.) in determining net backscatter. Model simulations of sigma (sup o) as functions of the wave parameters (lambda, polarization and angle of incidence) and the geophysical and biophysical attributes are used to develop robust classifiers. The classifiers are validated using available AirSAR data sets. Specific estimators are developed for each class on the basis of the scattering models and empirical data sets. The candidate algorithms are tested with the AirSAR data sets. The attributes of interest include: total above ground biomass, woody biomass, soil moisture and soil roughness.

Ulaby, Fawwaz T.↗

NASA NTRS1999

Software Evolution and the Fault Process

In developing a software system, we would like to estimate the way in which the fault content changes during its development, as well determine the locations having the highest concentration of faults. In the phases prior to test, however, there may be very little direct information regarding the number and location of faults. This lack of direct information requires developing a fault surrogate from which the number of faults and their location can be estimated. We develop a fault surrogate based on changes in the fault index, a synthetic measure which has been successfully used as a fault surrogate in previous work. We show that changes in the fault index can be used to estimate the rates at which faults are inserted into a system between successive revisions. We can then continuously monitor the total number of faults inserted into a system, the residual fault content, and identify those portions of a system requiring the application of additional fault detection and removal resources.

Nikora, Allen P.↗

NASA NTRS2001

The Propulsive Small Expendable Deployer System (ProSEDS)

This is the Annual Report #2 entitled "The Propulsive Small Expendable Deployer System (ProSEDS)" prepared by the Smithsonian Astrophysical Observatory for NASA Marshall Space Flight Center. This report covers the period of activity from 1 August 2000 through 30 July 2001. The topics include: 1) Updated System Performance; 2) Mission Analysis; 3) Updated Dynamics Reference Mission; 4) Updated Deployment Control Profiles and Simulations; 5) Comparison of ED tethers and electrical thrusters; 6) Kalman filters for mission estimation; and 7) Delivery of interactive software for ED tethers.

Lorenzini, Enrico C.↗

NASA NTRS2003

SMC-IT cost risk tutorial part 1 : incorporating risk

Explore the source record for details and available documents.

software↗

NASA NTRS2009

Alternative Determination of Density of the Titan Atmosphere

An alternative has been developed to direct measurement for determining the density of the atmosphere of the Saturn moon Titan as a function of altitude. The basic idea is to deduce the density versus altitude from telemetric data indicative of the effects of aerodynamic torques on the attitude of the Cassini Saturn orbiter spacecraft as it flies past Titan at various altitudes. The Cassini onboard attitude-control software includes a component that can estimate three external per-axis torques exerted on the spacecraft. These estimates are available via telemetry.

Lee, Allan↗

NASA NTRS2005

NASA Tech Briefs, March 2005

Topics covered include: Scheme for Entering Binary Data Into a Quantum Computer; Encryption for Remote Control via Internet or Intranet; Coupled Receiver/Decoders for Low-Rate Turbo Codes; Processing GPS Occultation Data To Characterize Atmosphere; Displacing Unpredictable Nulls in Antenna Radiation Patterns; Integrated Pointing and Signal Detector for Optical Receiver; Adaptive Thresholding and Parameter Estimation for PPM; Data-Driven Software Framework for Web-Based ISS Telescience; Software for Secondary-School Learning About Robotics; Fuzzy Logic Engine; Telephone-Directory Program; Simulating a Direction-Finder Search for an ELT; Formulating Precursors for Coating Metals and Ceramics; Making Macroscopic Assemblies of Aligned Carbon Nanotubes; Ball Bearings Equipped for In Situ Lubrication on Demand; Synthetic Bursae for Robots; Robot Forearm and Dexterous Hand; Making a Metal-Lined Composite-Overwrapped Pressure Vessel; Ex Vivo Growth of Bioengineered Ligaments and Other Tissues; Stroboscopic Goggles for Reduction of Motion Sickness; Articulating Support for Horizontal Resistive Exercise; Modified Penning-Malmberg Trap for Storing Antiprotons; Tumbleweed Rovers; Two-Photon Fluorescence Microscope for Microgravity Research; Biased Randomized Algorithm for Fast Model-Based Diagnosis; Fast Algorithms for Model-Based Diagnosis; Simulations of Evaporating Multicomponent Fuel Drops; Formation Flying of Tethered and Nontethered Spacecraft; and Two Methods for Efficient Solution of the Hitting- Set Problem.

Source record↗

NASA NTRS2012

Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-filled MODIS Data

Smoothed and gap-filled VI provides a good base for estimating vegetation phenology metrics. The TIMESAT software was improved by incorporating the ancillary information from MODIS products. A simple assessment of the association between retrieved greenup dates and ground observations indicates satisfactory result from improved TIMESAT software. One application example shows that mapping Nectar Flow Phenology is tractable on a continental scale using hive weight and satellite vegetation data. The phenology data product is supporting more researches in ecology, climate change fields.

Tan, Bin↗

NASA NTRS2023

EVA Task and 3D Pose Recognition from Video

Extravehicular Activity (EVA) has been known to involve potential risks of biomechanical stresses and injuries to crewmembers. Gathering of EVA motion patterns is necessary for risk analysis and mitigation. However, many existing techniques, such as motion capture systems, are not only cost-prohibitive but are impractical for retrospective analysis of past missions. In this work, a software tool was developed, which can estimate the 3D poses of a spacesuit from photographs or videos, without using special sensors or equipment. The tool is based on the state-of-the-art artificial intelligence and machine learning (AI/ML) system, which was trained by studying and capturing motion patterns of past and current spacesuit test data. The AI/ML tool was further enhanced using synthetically generated data, in which the suit postures, backgrounds, camera angles and illumination conditions were parametrically adjusted and rendered for training. The tool, incorporated the methodologies of Convolutional Neural Network (CNN), was trained, and tested in the cloud computing environment. The trained model was then applied on new imagery and video to extract estimated joint positions and suit outlines. The joint positions were further processed to capture activity (“digging”), pose labels (“bending”), and other useful downstream information. The model performance on new imagery and video was successfully assessed for accuracy and reliability. This AI/ML based posture recognition tool thus allows for the quantification of injury risk and task performance characterization for both current and past missions and training, which can immensely help to improve EVA task and suit design.

Kyung Han Kim↗

NASA NTRSDate not supplied

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗

NASA NTRS2004

Software Quality Assurance Metrics

Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.

McRae, Kalindra A.↗