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NASA NTRS2011

Langley's DEVELOP Team Applies NASA's Earth Observations to Address Environmental Issues Across the Country and Around the Globe

The DEVELOP National Program was established over a decade ago to provide students with experience in the practical application of NASA Earth science research results. As part of NASA's Applied Sciences Program, DEVELOP focuses on bridging the gap between NASA technology and the public through projects that innovatively use NASA Earth science resources to address environmental issues. Cultivating a diverse and dynamic group of students and young professionals, the program conducts applied science research projects during three terms each year (spring, summer, and fall) that focus on topics ranging from water resource management to natural disasters.

Childs, Lauren M.↗
NASA NTRS2002

NASA Remote Sensing Data for Epidemiological Studies

In response to the need for improved observations of environmental factors to better understand the links between human health and the environment, NASA has established a new program to significantly improve the utilization of NASA's diverse array of data, information, and observations of the Earth for health applications. This initiative, lead by Goddard Space Flight Center (GSFC) has the following goals: (1) To encourage interdisciplinary research on the relationships between environmental parameters (e.g., rainfall, vegetation) and health, (2) Develop practical early warning systems, (3) Create a unique system for the exchange of Earth science and health data, (4) Provide an investigator field support system for customers and partners, (5) Facilitate a system for observation, identification, and surveillance of parameters relevant to environment and health issues. The NASA Environment and Health Program is conducting several interdisciplinary projects to examine applications of remote sensing data and information to a variety of health issues, including studies on malaria, Rift Valley Fever, St. Louis Encephalitis, Dengue Fever, Ebola, African Dust and health, meningitis, asthma, and filariasis. In addition, the NASA program is creating a user-friendly data system to help provide the public health community with easy and timely access to space-based environmental data for epidemiological studies. This NASA data system is being designed to bring land, atmosphere, water and ocean satellite data/products to users not familiar with satellite data/products, but who are knowledgeable in the Geographic Information Systems (GIS) environment. This paper discusses the most recent results of the interdisciplinary environment-health research projects and provides an analysis of the usefulness of the satellite data to epidemiological studies. In addition, there will be a summary of presently-available NASA Earth science data and a description of how it may be obtained.

Maynard, Nancy G.↗
NASA NTRS2021

Reference Guide for Project-Control Account Managers

The purpose of this guide is intended to be a quick reference for a Project-Control Account Manager (P-CAM) or technical manager empowered with a project’s cost, schedule, and technical responsibilities of a control account(s) when Earned Value Management (EVM) is required. The overall objective is to support the P-CAM in performing their responsibilities as they relate to EVM. In addition, the reference guide describes at a summary level how the scope, schedule, and budget of a project integrate for optimal planning and control of prime contracts and in-house projects. Because NASA implements a diverse and unique portfolio of projects, those projects have traditionally created project-specific systems to manage planning and performance analysis. However, establishment and implementation of a project management system that is common across all centers and mission directorates will facilitate the adoption of best business practices. In addition, the application of timely and predictive analysis, as well as, providing all stakeholders with greater insight into project performance will enhance opportunities for project success. For more detailed information, refer to the NASA EVM System Description; Integrated Baseline Review (IBR) Handbook; EVM Implementation Handbook; Schedule Management Handbook; Work Breakdown Structure (WBS) Handbook; and other agency/industry documentation. In addition, you may contact your local center’s EVM Focal Points. All this information and more can be found at and/or the NASA Engineering Network located at https://nen.nasa.gov/web/pm.

Christopher Lewis Sadler↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
NASA NTRS2005

Miniature Focusing Time-of-Flight Mass Spectrometer

An improved miniature time-of-flight mass spectrometer has been developed in a continuing effort to minimize the sizes, weights, power demands, and costs of mass spectrometers for such diverse applications as measurement of concentrations of pollutants in the atmosphere, detecting poisonous gases in mines, and analyzing exhaust gases of automobiles. Advantageous characteristics of this mass spectrometer include the following: It is simple and rugged. Relative to prior mass spectrometers, it is inexpensive to build. There is no need for precise alignment of its components. Its mass range is practically unlimited Relative to prior mass spectrometers, it offers high sensitivity (ability to measure relative concentrations as small as parts per billion). Its resolution is one dalton (one atomic mass unit). An entire mass spectrum is recorded in a single pulse. (In a conventional mass spectrometer, a spectrum is recorded mass by mass.) The data-acquisition process takes only seconds. It is a lightweight, low-power, portable instrument. Although time-of-flight mass spectrometers (TOF-MSs) have been miniaturized previously, their performances have not been completely satisfactory. An inherent adverse effect of miniaturization of a TOF-MS is a loss of resolution caused by reduction of the length of its flight tube. In the present improved TOF-MS, the adverse effect of shortening the flight tube is counteracted by (1) using charged-particle optics to constrain ion trajectories to the flight-tube axis while (2) reducing ion velocities to increase ion flight times. In the present improved TOF-MS, a stream of gas is generated by use of a hypodermic needle. The stream of gas is crossed by an energy-selected, pulsed beam of electrons (see Figure 1). The ions generated by impingement of the electrons on the gas atoms are then focused by three cylindrical electrostatic lenses, which constitute a segmented flight tube. After traveling along the flight tube, the ions enter a charged-particle detector. The output of the detector is fed to a counting circuit to obtain data on the counting rate as a function of time. Inasmuch as time of flight is directly proportional to the ion mass, a plot of the counting rate versus time of flight is equivalent to a mass spectrum (see Figure 2).

Kanik, Isik↗
NASA NTRS1973

Remote sensing in Iowa agriculture

The author has identified the following significant results. Results include the estimation of forested and crop vegetation acreages using the ERTS-1 imagery. The methods used to achieve these estimates still require refinement, but the results appear promising. Practical applications would be directed toward achieving current land use inventories of these natural resources. This data is presently collected by sampling type surveys. If ERTS-1 can observe this and area estimates can be determined accurately, then a step forward has been achieved. Cost benefit relationship will have to be favorable. Problems still exist in these estimation techniques due to the diversity of the scene observed in the ERTS-1 imagery covering other part of Iowa. This is due to influence of topography and soils upon the adaptability of the vegetation to specific areas of the state. The state mosaic produced from ERTS-1 imagery shows these patterns very well. Research directed to acreage estimates is continuing.

Mahlstede, J. P.↗
NASA NTRSDate not supplied

Methods for Developing Successful Systems Engineers

Systems Engineering (SE) is a complex and challenging field that incorporates the knowledge of systems engineering processes, the ability to synthesize a wide-range of engineering disciplines, and the ability to lead a team of people to successfully accomplish the goals of a project. It requires hard technical skills and soft-skill leadership savvy. As a result, three main development needs are identified: 1) Knowledge of SE processes, the benefits of these processes to a project and their tailored application 2) Knowledge of a wide-range of engineering disciplines, how they interrelate in a system, and the development of sound technical judgement 3) Team leadership to direct and motivate a team of subsystem and discipline experts This paper describes the establishment of a comprehensive training and development program for Systems Engineers at NASA Ames Research Center that addresses in part each of these three areas from the perspective of the implementing manager. A variety of methods have been utilized including the establishment of a SE Community of Practice, a unique and innovative web tool, on-line videos, classroom training in NASA’s 17 Common Technical Processes, guidance on the tailored application of these processes, monthly technical talks, mentoring in both technical judgment and team leadership, and NASA’s Leadership Development Programs. While much of professional SE development must come through project experience, the approaches listed above can accelerate development. The diversity of skills required of Systems Engineering demands a multi-faceted approach to successfully train and develop this critical skill.

development↗
NASA NTRSDate not supplied

Methods for Developing Successful Systems Engineers

Systems Engineering (SE) is a complex and challenging field that incorporates the knowledge of systems engineering processes, the ability to synthesize a wide-range of engineering disciplines, and the ability to lead a team of people to successfully accomplish the goals of a project. It requires hard technical skills and soft-skill leadership savvy. As a result, three main development needs are identified: 1. Knowledge of SE processes, the benefits of these processes to a project and their tailored application 2. Knowledge of a wide-range of engineering disciplines, how they interrelate in a system, and the development of sound technical judgement 3. Team leadership to direct and motivate a team of subsystem and discipline experts This paper describes the establishment of a comprehensive training and development program for Systems Engineers at NASA Ames Research Center that addresses in part each of these three areas from the perspective of the implementing manager. A variety of methods have been utilized including the establishment of a SE Community of Practice, a unique and innovative web tool, on-line videos, classroom training in NASA’s 17 Common Technical Processes, guidance on the tailored application of these processes, monthly technical talks, mentoring in both technical judgment and team leadership, and NASA’s Leadership Development Programs. While much of professional SE development must come through project experience, the approaches listed above can accelerate development. The diversity of skills required of Systems Engineering demands a multi-faceted approach to successfully train and develop this critical skill.

development↗
NASA NTRS2023

From Remotely-Sensed SIF to Ecosystem Structure, Function, and Service: Part I - Harnessing Theory

Solar-induced chlorophyll fluorescence (SIF) is a remotely sensed optical signal emitted during the light reactions of photosynthesis. The past two decades have witnessed an explosion in availability of SIF data at increasingly higher spatial and temporal resolutions, sparking applications in diverse research sectors (e.g., ecology, agriculture, hydrology, climate, and socioeconomics). These applications must deal with complexities caused by tremendous variations in scale and the impacts of interacting and superimposing plant physiology and three-dimensional vegetation structure on the emission and scattering of SIF. At present, these complexities have not been overcome. To advance future research, the two companion reviews aim to (1) develop an analytical framework for inferring terrestrial vegetation structures and function that are tied to SIF emission, (2) synthesize progress and identify challenges in SIF research via the lens of multi-sector applications, and (3) map out actionable solutions to tackle these challenges and offer our vision for research priorities over the next 5–10 years based on the proposed analytical framework. This paper is the first of the two companion reviews, and theory oriented. It introduces a theoretically rigorous yet practically applicable analytical framework. Guided by this framework, we offer theoretical perspectives on three overarching questions: (1) The forward (mechanism) question—How are the dynamics of SIF affected by terrestrial ecosystem structure and function? (2) The inference question: What aspects of terrestrial ecosystem structure, function, and service can be reliably inferred from remotely sensed SIF and how? (3) The innovation question: What innovations are needed to realize the full potential of SIF remote sensing for real-world applications under climate change? The analytical framework elucidates that process complexity must be appreciated in inferring ecosystem structure and function from the observed SIF; this framework can serve as a diagnosis and inference tool for versatile applications across diverse spatial and temporal scales.

carbon fluxes↗
NASA NTRS2019

Developing a Community of Practice for Applied Uses of Future PACE Data to Address Marine Food Security Challenges

External interaction:The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency's new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

Schollaert Uz, Stephanie↗
NASA NTRS2021

Hybrid phenology matching model for robust crop phenological retrieval

Crop phenology regulates seasonal agroecosystem carbon, water, and energy exchanges, and is a key component in empirical and process-based crop models for simulating biogeochemical cycles of farmlands, assessing gross and net primary production, and forecasting the crop yield. The advances in phenology matching models provide a feasible means to monitor crop phenological progress using remote sensing observations, with a priori information of reference shapes and reference phenological transition dates. Yet the underlying geometrical scaling assumption of models, together with the challenge in defining phenological references, hinders the applicability of phenology matching in crop phenological studies. The objective of this study is to develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models. It relaxes the geometrical scaling assumption and can characterize key phenological stages of crop cycles, ranging from farming practice-relevant stages (e.g., planted and harvested) to crop development stages (e.g., emerged and mature). To systematically evaluate the influence of phenological references on phenology matching, four representative phenological reference scenarios under varying levels of phenological calibrations in terms of time and space are further designed with publicly accessible phenological information. The results indicate that the hybrid phenology matching model can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois, particularly with the year- and region-adjusted phenological reference (R-squared higher than 0.9 and RMSE less than 5 days for most phenological stages). The inter-annual and regional phenological patterns characterized by the hybrid model correspond well with those in the crop progress reports (CPRs) from the USDA National Agricultural Statistics Service (NASS). Compared to the benchmark phenology matching model, the hybrid model is more robust to the decreasing levels of phenological reference calibrations, and is particularly advantageous in retrieving crop early phenological stages (e.g., planted and emerged stages) when the phenological reference information is limited. This innovative hybrid phenology matching model, together with CPR-enabled phenological reference calibrations, holds 3 considerable promise in revealing spatio-temporal patterns of crop phenology over extended geographical regions.

Phenology↗
NASA NTRS2010

Development of NASA's Accident Precursor Analysis Process Through Application on the Space Shuttle Orbiter

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system. APA docs more than simply track experience: it systematically evaluates experience, looking for under-appreciated risks that may warrant changes to design or operational practice. This paper presents the pilot application of the NASA APA process to Space Shuttle Orbiter systems. In this effort, the working sessions conducted at Johnson Space Center (JSC) piloted the APA process developed by Information Systems Laboratories (ISL) over the last two years under the auspices of NASA's Office of Safety & Mission Assurance, with the assistance of the Safety & Mission Assurance (S&MA) Shuttle & Exploration Analysis Branch. This process is built around facilitated working sessions involving diverse system experts. One important aspect of this particular APA process is its focus on understanding the physical mechanism responsible for an operational anomaly, followed by evaluation of the risk significance of the observed anomaly as well as consideration of generalizations of the underlying mechanism to other contexts. Model completeness will probably always be an issue, but this process tries to leverage operating experience to the extent possible in order to address completeness issues before a catastrophe occurs.

Maggio, Gaspare↗
NASA NTRS2002

Alternative Metrics for Evaluating the Resilence of Advanced Life Support Systems

Ensuring the safety of the crew is a key performance requirement of a life support system. However, a number of conceptual and practical difficulties arise when devising metrics to concretely measure the ability of a life support system to maintain critical functions in the presence of anticipated and unanticipated faults. Resilience is a dynamic property of a life support system that depends on the complex interactions between faults, controls and system hardware. We review some of the approaches to understanding the robustness or resilience of complex systems being developed in diverse fields such as ecology, software engineering and cell biology and discuss their applicability to regenerative life support systems. We also consider how approaches to measuring resilience vary depending on system design choices such as the definition and choice of the nominal operating regime. Finally, we explore data collection and implementation issues such as the key differences between the instantaneous or conditional and average or overall measures of resilience. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data are used to consider alternative measures of resilience as predictors of the system's ability to recover from component-level faults.

Bell, Ann Maria↗
NASA NTRS2003

Computational Fluid Dynamics Technology for Hypersonic Applications

Several current challenges in computational fluid dynamics and aerothermodynamics for hypersonic vehicle applications are discussed. Example simulations are presented from code validation and code benchmarking efforts to illustrate capabilities and limitations. Opportunities to advance the state-of-art in algorithms, grid generation and adaptation, and code validation are identified. Highlights of diverse efforts to address these challenges are then discussed. One such effort to re-engineer and synthesize the existing analysis capability in LAURA, VULCAN, and FUN3D will provide context for these discussions. The critical (and evolving) role of agile software engineering practice in the capability enhancement process is also noted.

Gnoffo, Peter A.↗
NASA NTRS2022

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗
NASA NTRS2007

Adapting Project Management Practices to Research-Based Projects

From dealing with the inherent uncertainties in outcomes of scientific research to the lack of applicability of current NASA Procedural Requirements guidance documentation, research-based projects present challenges that require unique application of classical project management techniques. If additionally challenged by the creation of a new program transitioning from basic to applied research in a technical environment often unfamiliar with the cost and schedule constraints addressed by project management practices, such projects can find themselves struggling throughout their life cycles. Finally, supplying deliverables to a prime vehicle customer, also in the formative stage, adds further complexity to the development and management of research-based projects. The Biomedical Research and Countermeasures Projects Branch at NASA Johnson Space Center encompasses several diverse applied research-based or research-enabling projects within the newly-formed Human Research Program. This presentation will provide a brief overview of the organizational structure and environment in which these projects operate and how the projects coordinate to address and manage technical requirements. We will identify several of the challenges (cost, technical, schedule, and personnel) encountered by projects across the Branch, present case reports of actions taken and techniques implemented to deal with these challenges, and then close the session with an open forum discussion of remaining challenges and potential mitigations.

Bahr, P.↗
NASA NTRS2009

The Long, Hard Journey: Expanding the Use of NASA Data and Models for Sustainable Development Planning Around the World

In 2007, the National Research Council's committee on Extending Observations and Research Results to Practical Applications recommended that NASA's Applied Science Program (ASP) directly engage with a broader community of users - not just federal agencies. Soon afterwards, scientists at the NASA Marshall Space Flight Center began discussions on a collaborative research project with EMBARQ - the World Resource Institute's Center for Sustainable Transport. The discussions initially focused on how best to utilize satellite observations and atmospheric models for assessing the impact of a proposed transportation project on land use and air quality. Discussions exposed the participants to a broad spectrum of science and policy challenges that these diverse organizations face on a routine basis. It brought into clear focus the need for an observation-modeling system that will allow a proactive approach towards development planning, and the fact that satellite systems do not always provide the spatial and temporal resolution useful for urban-scale applications, underscoring the need for earth system models to bridge this gap. Realizing the significant risk that unplanned urbanization and climate change pose to the social and functional stability of large cities, both organizations decided to expand the scope of their preliminary discussion to include water resources and agriculture. A pilot project, funded by NASA ASP, EMBARQ and Istanbul Technical University focused on quantifying the magnitude and extent of urbanization in Istanbul, and analyzed the combined effect of urbanization and projected climate change on local climate, air quality, and its consequent effects on agricultural productivity. Preliminary results show that Istanbul has undergone a significant amount of Land Use/Land Cover change over the past two decades. While some forested areas have been lost to urban-landscapes, urbanization has mostly occurred over former croplands due to the fact that in contrast to forested areas, croplands have flat terrain, making them a more attractive target for conversion to urban land. The reduction in land area for agricultural and increase in temperature has reduced agricultural production in the vicinity of the city. The United Nations expects the world population to reach 9.2 billion by 2050. Most of this increase will be absorbed by countries that are least able to sustain it. Rapid economic growth is likely to continue and will require massive infrastructure investments. If not properly managed, the magnitude and extent of these initiatives will overwhelm sensitive ecosystems around the world. Successful relationships such as the one described here are critically important if we are to stabilize the threatened ecosystems on which human systems ultimately rely. The challenges, needs, culture, and operating environment of development planning organizations are fundamentally different from a research organization. An appreciation of these differences is a prerequisite for any successful collaboration.

Khan, Maudood↗
NASA NTRSDate not supplied

Interface Consistency: Phase I Results & Phase II Status

Future exploration missions will rely on designing and developing vehicles and complex systems from within NASA and through multiple external commercial partners to meet mission goals. Despite existing consistency-related agency requirements, NASA’s approach to commercial spaceflight development encourages providers’ flexibility and innovation. This strategy is resulting in significant design diversity across Artemis vehicles. Design best practices and guidelines champion interface consistency to promote mental model development and knowledge transfer. However, research investigating the benefits of consistency is mixed, and little is known about its role in complex systems. Determining the level of risk that system diversity presents is difficult, as there is no established method for quantifying the degree of consistency within and across interfaces, nor is there information about the differential impacts of different types of inconsistency. Phase I of this project (Characterization and Measurement) served as a starting point to better understand the construct of consistency, its application, and the range of studies and methods for measuring it. The project team created a taxonomy of consistency to apply to interfaces as a framework to guide the development of tools to assess intersystem consistency. Checklist and cognitive walkthrough methods were developed for use by human factors (HF) and human-computer interaction (HCI) experts. The Intersystem Consistency Scale (ICS) was developed for interface evaluations with crew. A pilot study evaluated the methods’ ability to distinguish differences between Artemis-like prototype pairs exhibiting either high or low design consistency. In addition, click errors and time on task were collected within the ICS (crew-like) group. Results from our exploratory analysis and lessons learned from the pilot study will be discussed. The project team will also present the status of Phase II (Risk Assessment, Standards and Guidelines). This includes incorporating feedback to redesign the assessment tools, and inputs from displays and training Subject Matter Experts to update tasks and prototype designs. The team will present the risk assessment study design to identify the types and levels of inconsistency that pose the greatest risk to performance. Plans to apply these results toward agency standards and guideline recommendations will also be discussed.

Human-Computer Interaction↗