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NASA NTRS2002

Automating CPM-GOMS

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.

GOMS↗

NASA NTRS2006

Using Apex To Construct CPM-GOMS Models

process for automatically generating computational models of human/computer interactions as well as graphical and textual representations of the models has been built on the conceptual foundation of a method known in the art as CPM-GOMS. This method is so named because it combines (1) the task decomposition of analysis according to an underlying method known in the art as the goals, operators, methods, and selection (GOMS) method with (2) a model of human resource usage at the level of cognitive, perceptual, and motor (CPM) operations. CPM-GOMS models have made accurate predictions about behaviors of skilled computer users in routine tasks, but heretofore, such models have been generated in a tedious, error-prone manual process. In the present process, CPM-GOMS models are generated automatically from a hierarchical task decomposition expressed by use of a computer program, known as Apex, designed previously to be used to model human behavior in complex, dynamic tasks. An inherent capability of Apex for scheduling of resources automates the difficult task of interleaving the cognitive, perceptual, and motor resources that underlie common task operators (e.g., move and click mouse). The user interface of Apex automatically generates Program Evaluation Review Technique (PERT) charts, which enable modelers to visualize the complex parallel behavior represented by a model. Because interleaving and the generation of displays to aid visualization are automated, it is now feasible to construct arbitrarily long sequences of behaviors. The process was tested by using Apex to create a CPM-GOMS model of a relatively simple human/computer-interaction task and comparing the time predictions of the model and measurements of the times taken by human users in performing the various steps of the task. The task was to withdraw $80 in cash from an automated teller machine (ATM). For the test, a Visual Basic mockup of an ATM was created, with a provision for input from (and measurement of the performance of) the user via a mouse. The times predicted by the automatically generated model turned out to approximate the measured times fairly well (see figure). While these results are promising, there is need for further development of the process. Moreover, it will also be necessary to test other, more complex models: The actions required of the user in the ATM task are too sequential to involve substantial parallelism and interleaving and, hence, do not serve as an adequate test of the unique strength of CPM-GOMS models to accommodate parallelism and interleaving.

John, Bonnie↗

NASA NTRS1991

Using GOMS models and hypertext to create representations of medical procedures for online display

This study investigated two methods to improve organization and presentation of computer-based medical procedures. A literature review suggested that the GOMS (goals, operators, methods, and selecton rules) model can assist in rigorous task analysis, which can then help generate initial design ideas for the human-computer interface. GOMS model are hierarchical in nature, so this study also investigated the effect of hierarchical, hypertext interfaces. We used a 2 x 2 between subjects design, including the following independent variables: procedure organization - GOMS model based vs. medical-textbook based; navigation type - hierarchical vs. linear (booklike). After naive subjects studies the online procedures, measures were taken of their memory for the content and the organization of the procedures. This design was repeated for two medical procedures. For one procedure, subjects who studied GOMS-based and hierarchical procedures remembered more about the procedures than other subjects. The results for the other procedure were less clear. However, data for both procedures showed a 'GOMSification effect'. That is, when asked to do a free recall of a procedure, subjects who had studies a textbook procedure often recalled key information in a location inconsistent with the procedure they actually studied, but consistent with the GOMS-based procedure.

Gugerty, Leo↗

NASA NTRS1991

Interference prediction for deep space spacecraft from ground stations - Interference to the Galileo deep space spacecraft from the GOMS geostationary network

A technique for predicting the interference power spectral density from a ground station to a spacecraft in deep space is described. The interference prediction throughout the complete mission is simulated, and distance between the ground station and the deep space spacecraft is calculated. A power spectral density from the GOMS satellite network to the Galileo spacecraft receiver is computed using the thermal noise density level at the Galileo spacecraft as the interference criterion. Data obtained indicate that all three GOMS stations cause at least 30 minutes of interference during Galileo earth flyby number one, and two GOMS ground stations cause at least four minutes of interference during Galileo earth flyby number.

Bishop, Dennis F.↗

NASA NTRS1981

Calculation of surface temperature and surface fluxes in the GLAS GOM

Because the GLAS model's surface fluxes of sensible and latent heat exhibit strong 2 delta t oscillations at the individual grid points as well as in the zonal hemispheric averages and because a basic weakness of the GLAS model lower evaporation over oceans and higher evaporation over land in a typical monthly simulation, the GLAS model PBL parameterization was changed to calculate the mixed layer temperature gradient by solution of a quadratic equation for a stable PBL and by a curve fit relation for an unstable PBL. The new fluxes without any 2 delta t oscillation. Also, the geographical distributions of the surface fluxes are improved. The parameterization presented is incorporated into the new GLAS climate model. Some results which compare the evaporation over land and ocean between old and new calculations are appended.

Sud, Y. C.↗

DOE OSTI2025

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗

NASA NTRS2024

Satellite NO 2 Trends and Hotspots Over Offshore Oil and Gas Operations in the Gulf of Mexico

The Outer Continental Shelf of the Gulf of Mexico (GOM) is populated with numerous oil and natural gas (ONG) platforms which produce NO x (NO x = NO + NO 2 ), a major component of air pollution. The Bureau of Ocean Energy Management (BOEM) is mandated to ensure that the air quality of coastal states is not degraded by these emissions. As part of a NASA-BOEM collaboration, we conducted a satellite data-based analysis of nitrogen dioxide (NO 2 ) patterns and trends in the GOM. Data from the OMI and TROPOMI sensors were used to obtain 18+ year records of tropospheric column (TrC) NO 2 in three GOM regions: (a) Houston urban area, (b) near shore area off the Louisiana coast, and a (c) deepwater area off the Louisiana coast. The 2004–2022 time series show a decreasing trend for the urban (−0.027 DU/decade) and near shore (−0.0022 DU/decade) areas, and an increasing trend (0.0019 DU/decade) for the deepwater area. MERRA-2 wind and TROPOMI NO 2 data were used to reveal several NO2 hotspots (up to 25% above background values) under calm wind conditions near individual platforms. The NO 2 signals from these deepwater platforms and the high density of shallow water platforms closer to shore were confirmed by TrC NO 2 anomalies of up to 10%, taking into account the monthly TrC NO 2 climatology over the GOM. The results presented in this study establish a baseline for future estimates of emissions from the ONG hotspots and provide a methodology for analyzing NO 2 measurements from the new geostationary TEMPO instrument.

NO2↗

NASA NTRS2004

Anticipatory Eye Movements in Interleaving Templates of Human Behavior

Performance modeling has been made easier by architectures which package psychological theory for reuse at useful levels of abstraction. CPM-GOMS uses templates of behavior to package at a task level (e.g., mouse move-click, typing) predictions of lower-level cognitive, perceptual, and motor resource use. CPM-GOMS also has a theory for interleaving resource use between templates. One example of interleaving is anticipatory eye movements. This paper describes the use of ACT-Stitch, a framework for translating CPM-GOMS templates and interleaving theory into ACT-R, to model anticipatory eye movements in skilled behavior. The anticipatory eye movements explain performance in a well-practiced perceptual/motor task, and the interleaving theory is supported with results from an eye-tracking experiment.

Matessa, Michael↗

NASA NTRS1992

SAR observations in the Gulf of Mexico

The Gulf of Mexico (GOM) exhibits a wealth of energetic ocean features; they include the Loop Current with velocities of about 2 m/s and strong shear fronts, mesoscale eddies, double vortices, internal waves, and the outflow of the 'Mighty Mississippi' river. These energetic features can have a strong impact on the economies of the states surrounding the Gulf. Large fisheries, oil and gas production as well as pollution transport are relevant issues. These circulation features in the Gulf are invisible to conventional IR and visible satellite imagery during the Summer months due to cloud cover and uniform surface temperatures. Synthetic Aperture Radar (SAR) imagery of the Gulf does penetrate the cloud cover and shows a rich assembly of features there year-round. Below are preliminary results from GOM SAR imagery taken by SEASAT in 1978 and by the AIRSAR program in 1991.

Sheres, David↗

NASA NTRS2013

Surface Ocean pCO2 Seasonality and Sea-Air CO2 Flux Estimates for the North American East Coast

Underway and in situ observations of surface ocean pCO2, combined with satellite data, were used to develop pCO2 regional algorithms to analyze the seasonal and interannual variability of surface ocean pCO2 and sea-air CO2 flux for five physically and biologically distinct regions of the eastern North American continental shelf: the South Atlantic Bight (SAB), the Mid-Atlantic Bight (MAB), the Gulf of Maine (GoM), Nantucket Shoals and Georges Bank (NS+GB), and the Scotian Shelf (SS). Temperature and dissolved inorganic carbon variability are the most influential factors driving the seasonality of pCO2. Estimates of the sea-air CO2 flux were derived from the available pCO2 data, as well as from the pCO2 reconstructed by the algorithm. Two different gas exchange parameterizations were used. The SS, GB+NS, MAB, and SAB regions are net sinks of atmospheric CO2 while the GoM is a weak source. The estimates vary depending on the use of surface ocean pCO2 from the data or algorithm, as well as with the use of the two different gas exchange parameterizations. Most of the regional estimates are in general agreement with previous studies when the range of uncertainty and interannual variability are taken into account. According to the algorithm, the average annual uptake of atmospheric CO2 by eastern North American continental shelf waters is found to be between 3.4 and 5.4 Tg C/yr (areal average of 0.7 to 1.0 mol CO2 /sq m/yr) over the period 2003-2010.

interannual variability↗

NASA NTRS1993

The use of analytical models in human-computer interface design

Recently, a large number of human-computer interface (HCI) researchers have investigated building analytical models of the user, which are often implemented as computer models. These models simulate the cognitive processes and task knowledge of the user in ways that allow a researcher or designer to estimate various aspects of an interface's usability, such as when user errors are likely to occur. This information can lead to design improvements. Analytical models can supplement design guidelines by providing designers rigorous ways of analyzing the information-processing requirements of specific tasks (i.e., task analysis). These models offer the potential of improving early designs and replacing some of the early phases of usability testing, thus reducing the cost of interface design. This paper describes some of the many analytical models that are currently being developed and evaluates the usefulness of analytical models for human-computer interface design. This paper will focus on computational, analytical models, such as the GOMS model, rather than less formal, verbal models, because the more exact predictions and task descriptions of computational models may be useful to designers. The paper also discusses some of the practical requirements for using analytical models in complex design organizations such as NASA.

Gugerty, Leo↗

NASA NTRS1990

Improving the human factors of software with CLIPS

The use of CLIPS has transformed a conventional graduate course on the human factors of software. Previously, the class centered on lectures and discussions of a mix of ideas for improving the user-friendliness of software. By using CLIPS, the course can focus instead on teaching students to build three rule-based projects in CLIPS for improving the human factors of software. For the first project, students construct a friendly CLIPS front-end to existing software. For the second project students build a CLIPS expert system to help comply with user-interface guidelines. Alternatively, students may build an expert system to assist in detecting discrepancies between user-interfaces and guidelines. For the third project, students use CLIPS to implement a GOMS Model Methodology to assess the human performance impacts of given user-interfaces. Feedback on the projects from the students' colleagues and superiors in the workplace confirm the effectiveness of this CLIPS project-oriented approach to teaching the human factors of user-computer systems. Future refinements are described. Suggestions for those wishing to try this approach are outlined.

Nagy, Thomas J.↗

NASA NTRS1998

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

Freed, Michael↗

NASA NTRS2005

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗

NASA NTRS2010

Seagrass Health Modeling and Prediction with NASA Science Data

Previous research has demonstrated that MODIS data products can be used as inputs into the seagrass productivity model developed by Fong and Harwell (1994). To further explore this use to predict seagrass productivity, Moderate Resolution Imaging Spectroradiometer (MODIS) custom data products, including Sea Surface Temperature, Light Attenuation, and Chlorophyll-a have been created for use as model parameter inputs. Coastal researchers can use these MODIS data products and model results in conjunction with historical and daily assessment of seagrass conditions to assess variables that affect the productivity of the seagrass beds. Current monitoring practices involve manual data collection (typically on a quarterly basis) and the data is often insufficient for evaluating the dynamic events that influence seagrass beds. As part of a NASA-funded research grant, the University of Mississippi, is working with researchers at NASA and Radiance Technologies to develop methods to deliver MODIS derived model output for the northern Gulf of Mexico (GOM) to coastal and environmental managers. The result of the project will be a data portal that provides access to MODIS data products and model results from the past 5 years, that includes an automated process to incorporate new data as it becomes available. All model parameters and final output will be available through the use National Oceanic and Atmospheric Administration?s (NOAA) Environmental Research Divisions Data Access Program (ERDDAP) tools as well as viewable using Thematic Realtime Environmental Distributed Data Services (THREDDS) and the Integrated Data Viewer (IDV). These tools provide the ability to create raster-based time sequences of model output and parameters as well as create graphs of model parameters versus time. This tool will provide researchers and coastal managers the ability to analyze the model inputs so that the factors influencing a change in seagrass productivity can be determined over time.

Robinson, Harold D.↗

NASA NTRS2006

NASA Tech Briefs, November 2006

Topics include: Simulator for Testing Spacecraft Separation Devices; Apparatus for Hot Impact Testing of Material Specimens; Instrument for Aircraft-Icing and Cloud-Physics Measurements; Advances in Measurement of Skin Friction in Airflow; Improved Apparatus for Testing Monoball Bearings; High-Speed Laser Scanner Maps a Surface in Three Dimensions; Electro-Optical Imaging Fourier-Transform Spectrometer; Infrared Instrument for Detecting Hydrogen Fires; Modified Coaxial Probe Feeds for Layered Antennas; Detecting Negative Obstacles by Use of Radar; Cryogenic Pound Circuits for Cryogenic Sapphire Oscillators; PixelLearn; New Software for Predicting Charging of Spacecraft; Conversion Between Osculating and Mean Orbital Elements; Generating a 2D Representation of a Complex Data Structure; Making Activated Carbon by Wet Pressurized Pyrolysis; Composite Solid Electrolyte Containing Li+- Conducting Fibers; Electrically Conductive Anodized Aluminum Surfaces; Rapid-Chill Cryogenic Coaxial Direct-Acting Solenoid Valve; Variable-Tension-Cord Suspension/Vibration- Isolation System; Techniques for Connecting Superconducting Thin Films; Versatile Friction Stir Welding/Friction Plug Welding System; Thermal Spore Exposure Vessels; Enumerating Spore-Forming Bacteria Airborne with Particles; Miniature Oxidizer Ionizer for a Fuel Cell; Miniature Ion-Array Spectrometer; Promoted-Combustion Chamber with Induction Heating Coil; Miniature Ion-Mobility Spectrometer; Mixed-Salt/Ester Electrolytes for Low-Temperature Li+ Cells; Miniature Free-Space Electrostatic Ion Thrusters; Miniature Bipolar Electrostatic Ion Thruster; Holographic Plossl Retroreflectors; Miniature Electrostatic Ion Thruster With Magnet; Using Apex To Construct CPM-GOMS Models; Sequence Detection for PPM Optical Communication With ISI; Algorithm for Rapid Searching Among Star-Catalog Entries; Expectation-Based Control of Noise and Chaos; Radio Heating of Lunar Soil to Release Gases; Using Electrostriction to Manipulate Ullage in Microgravity; Equations for Scoring Rules When Data Are Missing; Insulating Material for Next-Generation Spacecraft; and Pseudorandom Switching for Adding Radar to the AFF Sensor.

Source record↗

NASA NTRS2011

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Peddle, Derek R.↗

NASA NTRS2017

Cloud and Sun-Glint Statistics Derived from GOES and MODIS Observations Over the Intra-Americas Sea for GEO-CAPE Mission Planning

Knowledge of cloud cover, frequency, and duration is not only important to study cloud dynamics, but also critical in determining when and where to take ocean measurements from geostationary orbits such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission due to the challenges in achieving complete hemispheric coverage of coastal oceans, estuaries, and inland waters at hourly frequency. Using GOES hourly measurements at 4 km nadir resolution between 2006 and 2011, the number of cloud-free hourly observations per day (N(sub cf)) for solar zenith angle Theta(sub 0) less than 80 degrees was estimated for each 0.1 degree location of the Intra-Americas Sea. The number of Sun-glint-affected hourly observations per day [Ns(sub sg)] was also calculated based on the planned GEO-CAPE observation geometry and realistic wind speed. High-latitude and equatorial oceans showed the lowest N(sub cf) (less than 2.4) in all climatological months, and highest N(sub cf) was observed in the Gulf of Mexico (GoM) and Caribbean (greater than 4.5). Different regions showed differences in seasonality of cloud-free conditions and also showed differences in the hour of a day at which the satellite observations would have the maximal cloud-free and glint-free probability (Temperature maximum). Cloud cover from Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km measurements are greater than 10 degrees higher than those from the MODIS 250 m measurements, supporting ocean color missions at subkilometer resolutions to enhance both spatial coverage and temporal frequency. These findings provide valuable information for GEO-CAPE mission planning to maximize its science value through minimizing the impacts of clouds and Sun glint.

Feng, Lian↗