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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The Fleet Application for Scheduling and Tracking (FAST) Management Website

The FAST application was designed to replace the paper and pen method of checking out and checking in GSA Vehicles at KSC. By innovating from a paper and pen based checkout system to a fully digital one, not only the resources wasted by printing the checkout forms have been reduced, but it also reduces significantly the time that users and fleet managers need to interact with the system as well as improving the record accuracy for each vehicle. The vehicle information is pulled from a centralized database server in the SPSDL. In an attempt to add a new feature to the FAST application, the author of this report (alongside the FAST developers) has been designing and developing the FAST Management Website. The GSA fleet managers had to rely on the FAST developers in order to add new vehicles, edit vehicles and previous transactions, or for generating vehicles reports. By providing an easy-to-use FAST Management Website portal, the GSA fleet managers are now able to easily move vehicles, edit records, and print reports.

Object-Oriented Programming↗
NASA NTRS2015

An Integrated 0-1 Hour First-Flash Lightning Nowcasting, Lightning Amount and Lightning Jump Warning Capability

Lightning one of the most dangerous weather-related phenomena, especially as many jobs and activities occur outdoors, presenting risk from a lightning strike. Cloud-to-ground (CG) lightning represents a considerable safety threat to people at airfields, marinas, and outdoor facilities-from airfield personnel, to people attending outdoor stadium events, on beaches and golf courses, to mariners, as well as emergency personnel. Holle et al. (2005) show that 90% of lightning deaths occurred outdoors, while 10% occurred indoors despite the perception of safety when inside buildings. Curran et al. (2000) found that nearly half of fatalities due to weather were related to convective weather in the 1992-1994 timeframe, with lightning causing a large component of the fatalities, in addition to tornadoes and flash flooding. Related to the aviation industry, CG lightning represents a considerable hazard to baggage-handlers, aircraft refuelers, food caterers, and emergency personnel, who all become exposed to the risk of being struck within short time periods while convective storm clouds develop. Airport safety protocols require that ramp operations be modified or discontinued when lightning is in the vicinity (typically 16 km), which becomes very costly and disruptive to flight operations. Therefore, much focus has been paid to nowcasting the first-time initiation and extent of lightning, both of CG and of any lightning (e.g, in-cloud, cloud-to-cloud). For this project three lightning nowcasting methodologies will be combined: (1) a GOESbased 0-1 hour lightning initiation (LI) product (Harris et al. 2010; Iskenderian et al. 2012), (2) a High Resolution Rapid Refresh (HRRR) lightning probability and forecasted lightning flash density product, such that a quantitative amount of lightning (QL) can be assigned to a location of expected LI, and (3) an algorithm that relates Pseudo-GLM data (Stano et al. 2012, 2014) to the so-called "lightning jump" (LJ) methodology (Shultz et al. 2011) to monitor lightning trends and to anticipate/forecast severe weather (hail > or =2.5 cm, winds > or =25 m/s, tornadoes). The result will be a time-continuous algorithm that uses GOES satellite, radar fields, and HRRR model fields to nowcast first-flash LI and QL, and subsequently monitors lightning trends on a perstorm basis within the LJ algorithm for possible severe weather occurrence out to > or =3 hours. The LI-QL-LJ product will also help prepare the operational forecast community for Geostationary Lightning Mapper (GLM) data expected in late 2015, as these data are monitored for ongoing convective storms. The LI-QL-LJ product will first predict where new lightning is highly probable using GOES imagery of developing cumulus clouds, followed by n analysis of NWS (dual-polarization) radar indicators (reflectivity at the -10 C altitude) of lightning occurrence, to increase confidence that LI is immanent. Once lightning is observed, time-continuous lightning mapping array and Pseudo-GLM observations will be analyzed to assess trends and the severe weather threat as identified by trends in lightning (i.e. LJs). Additionally, 5- and 15-min GOES imagery will then be evaluated on a per-storm basis for overshooting and other cloud-top features known to be associated with severe storms. For the processing framework, the GOES-R 0-1 hour convective initiation algorithm's output will be developed within the Warning Decision Support System - Integrated Information (WDSS-II) tracking tool, and merged with radar and lightning (LMA/Psuedo-GLM) datasets for active storms. The initial focus of system development will be over North Alabama for select lightning-active days in summer 2014, yet will be formed in an expandable manner. The lightning alert tool will also be developed in concert with National Weather Service (NWS) forecasters to meet their needs for real-time, accurate first-flash LI and timing, as well as anticipated lightning trends, amounts, continuation and cessation, so to provide key situational awareness and decision support information. The NASA Short-term Prediction Research and Transition (SPoRT) Center will provide important logistical and collaborative support and training, involving interactions with the NWS and broader user community.

Mecikalski, John↗
NASA NTRS2020

Central Valley Water Resources II: Groundwater Sustainability Management Support in the California Central Valley using GRACE and InSAR Datasets

California’s Central Valley is one of the most productive agricultural regions in the United States, producing a fourth of the nation’s food supply. The water demand in this region is heavily dependent on groundwater resources, resulting in over pumping of aquifers at unsustainable rates during recent periods of severe drought. Over the past century, Central Valley aquifers have experienced a significant decline in groundwater levels, resulting in land subsidence and irreversible loss in groundwater storage. In 2014, the state enacted the Sustainable Groundwater Management Act, requiring high and medium priority subbasins to suspend overdraft and achieve sustainable levels of pumping and recharge by 2042.The California Department of Water Resources (DWR) oversees subbasin groundwater management; however, monitoring remains challenging due to sparse and inconsistent in situ data. To assist the DWR, this project developed a user-friendly executable application and an interactive visualization tool to quantify groundwater storage and land subsidence trends using remotely sensed and in situ data. The team utilized NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) interferograms, and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2) interferograms in conjunction with well and GPS measurements to analyze groundwater and subsidence trends. GRACE and well data returns produced a strong Pearson correlation of .84, while Sentinel-1 and GPS data returns produced a Pearson correlation of .41 over the entire Central Valley. These findings suggest remotely sensed GRACE and interferometric SAR data can be used in the absence of in situ data.

DEVELOP Project Summary↗
NASA NTRS1996

Trials and Tribulations of Implementing Intranet Technology: The Cassini Information Access System

The Cassini Information Access System (IAS) was built to provide Cassini Integration and Test engineers with ready access to current technical and logistical project information. World Wide Web (WWW) technology was used to provide a consistent user interface to pre-existing interactive systems as well as new repositories and interactive services developed specifically for Cassini.

Cassini↗
NASA NTRSDate not supplied

Higher-Order Approximations for Stabilizing Zero-Energy Modes in Peridynamics Crystal Plasticity Models with Large Horizon Interactions

The non-ordinary state-based peridynamics theory combines non-local dynamic techniques with a desirable correspondence material principle, allowing for the use of continuum mechanics constitutive models. Such an approach presents a unique capability for solving problems involving discontinuities (e.g., strain localization, fracture, and fragmentation). However, the correspondence-based peridynamics models often suffer from zero-energy mode instabilities in numerical implementation, primarily due to the approximations of the non-local deformation gradient tensor. This paper focuses on a computational scheme for eliminating the zero-energy mode oscillations using a choice of influence functions that improve the truncation error in a higher-order Taylor series expansion of the deformation gradient. The novelty here is a tensor-based derivation of the linear constraint equations, which can be used to systematically identify the particle interaction weight functions for various user-specified horizon radii. In this paper, the proposed higher-order stabilization scheme is demonstrated for multi-dimensional examples involving polycrystalline and composite microstructures, along with comparisons against conventional finite element methods. The proposed stabilization scheme is shown to be highly effective in suppressing the spurious zero-energy mode oscillations in all numerical examples while enabling efficient simulations of strain localizations across material interfaces.

Non-Ordinary State-Based Peridynamics↗
NASA NTRS2021

Southern California Health & Air Quality: Using Remote Sensing to Detect the Frequency and Drivers of Red Tide Blooms in California to Assist in the Management of Human and Marine Exposure to Algal Toxins

In 2020, the dinoflagellate species Lingulodinium polyedra was measured at unprecedented levels off the southern California coast, raising concern for local communities. At high levels, L. polyedra can cause marine life mortality, food-borne illness, and respiratory-related health risks in humans. In partnership with the California Office of Environmental Health Hazard Assessment, the National Oceanic and Atmospheric Administration Southwest Fisheries Science Center, the California Department of Public Health, and the University of California San Diego’s Scripps Institution of Oceanography, this project utilized satellite imagery to visualize and analyze spatiotemporal trends of historical red tide events associated with L. polyedra. Using the Suomi National Polar-orbiting Partnership’s (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), Aqua’s Moderate Resolution Imaging Spectroradiometer (MODIS), and Global Change Observation Mission – Climate (GCOM-C) Second Generation Global Imager (SGLI), the team assessed the validity of using multiple sensors in detecting chlorophyll-a as a proxy for dinoflagellate dominated-algal blooms. The results suggest that VIIRS imagery processed using the Color Index algorithm from Hu et al. (2013), amongst all other algorithms and Earth observations assessed, shows the most promise in identifying L. polyedra blooms. The end products included an ArcGIS Dashboard and Google Earth Engine tool that when combined, provided users with spatial and temporal trends, interactive interfaces to analyze the effectiveness of various sensors and algorithms, and an overall contribution to aid in the management of human health and the economy impacted by harmful algal blooms.

Harmful algal bloom↗
NASA NTRS2023

TRACER Lightning Mapping Array Field Campaign Report

Our observational contribution to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Tracking Aerosol Convection Interactions Experiment (TRACER) was the deployment of additional Lightning Mapping Array sensors to provide enhanced capability to the Houston Lightning Mapping Array (HLMA) during the TRACER intensive operational period. To that end, the Texas Tech University personnel (Professor Bruning and Dr. Brunner, and graduate students Jessica Souza, David Singewald, Stephanie Weiss, and Matthew Miller) deployed two portable LMA antennae at locations G and B shown in the map below. The map also shows the predicted lightning flash detection efficiency in black contours, as well as color-shaded very-high-frequency (VHF) source detection efficiency, which roughly corresponds to the sensitivity to lightning channel detail.

Tracking Aerosol Convection Interactions Experimen↗
NASA NTRS2023

The UCLA Cosmochemistry Database

The UCLA Cosmochemistry Database was initiated as part of a data-rescue and -storage project aimed at archiving a variety of cosmochemical data acquired at University of California, Los Angeles (UCLA). The data collection includes elemental compositions of extraterrestrial materials analyzed by UCLA cosmochemists over the last five decades. The analytical techniques include atomic absorption spectrometry (AAS) and neutron activation analysis (NAA) at UCLA. The data collection is stored on the Astromaterials Data System (Astromat). We provide both interactive tables and downloadable datasheets for users to access all data. The UCLA Cosmochemistry Database archives cosmochemical data that are essential tools for increasing our understanding of the nature and origin of extraterrestrial materials. Future studies can reference the data collection in the examination, analysis, and classification of newly acquired extraterrestrial samples.

Bidong Zhang↗
NASA NTRS2024

Enhancing Metal Additive Manufacturing Training with the Advanced Vision Language Model: A Pathway to Immersive Augmented Reality Training for Non-Experts

This paper introduces an innovative training system for the Renishaw AM400 metal printer, leveraging the synergy of the advanced Vision Language Model (VLM) with Augmented Reality (AR) within the Digital Twins (DT) framework. Aimed at overcoming the limitations of conventional training methods in metal additive manufacturing (AM), our system integrates AR to provide an immersive learning environment, enhancing the real-world experience with interactive digital overlays. The core of the system lies in its use of VLM, which, pre-trained on diverse datasets, excels in processing multi-modal data, thereby offering nuanced and contextually relevant guidance for trainees. Key experiments demonstrate the system’s effectiveness, particularly highlighting the usage of VLM as an Artificial Intelligence (AI) agent to integrate external tools like YOLO-v7 for valve state classification and CRAFT for control panel text recognition. This approach significantly improves recognition accuracy, operational understanding, and human–machine interaction, especially for non-expert users, making complex metal AM operations more accessible. The research not only showcases the potential of AR and VLM in industrial training but also sets a new standard for smart manufacturing practices, indicating broader applications in various industrial domains.

Metal additive manufacturing↗
DOE OSTI2014

Effects of Granular Control on Customers’ Perspective and Behavior with Automated Demand Response Systems

Automated demand response (Auto-DR) is expected to close the loop between buildings and the grid by providing machine-to-machine communications to curtail loads without the need for human intervention. Hence, it can offer more reliable and repeatable demand response results to the grid than the manual approach and make demand response participation a hassle-free experience for customers. However, many building operators misunderstand Auto-DR and are afraid of losing control over their building operation. To ease the transition from manual to Auto-DR, we designed and implemented granular control of Auto-DR systems so that building operators could modify or opt out of individual load-shed strategies whenever they wanted. This paper reports the research findings from this effort demonstrated through a field study in large commercial buildings located in New York City. We focused on (1) understanding how providing granular control affects building operators’ perspective on Auto-DR, and (2) evaluating the usefulness of granular control by examining their interaction with the Auto-DR user interface during test events. Through trend log analysis, interviews, and surveys, we found that: (1) the opt-out capability during Auto-DR events can remove the feeling of being forced into load curtailments and increase their willingness to adopt Auto-DR; (2) being able to modify individual load-shed strategies allows flexible Auto-DR participation that meets the building’s changing operational requirements; (3) a clear display of automation strategies helps building operators easily identify how Auto-DR is functioning and can build trust in Auto-DR systems.

Schetrit, Oren↗
DOE OSTI2016

PREP: Portal for Readiness Exercises & Planning v. 1.0

The software includes a web-based template for recording actions taken during emergency preparedness exercises and planning workshops. In addition, a virtual outbreak prevention simulation exercise is also included. Both tools interact with a server which records user decisions and communications.

Noel, Todd↗
DOE OSTI2021

Design Considerations for the Field Use of International Nuclear Safeguards Technology

The process of developing and deploying safeguards technology should be carried out in such a way that it supports the International Atomic Energy Agency’s (IAEA’s) international safeguards verification mission, while also being efficient in terms of both cost and time. This process, however, may be hindered by a general lack of nuclear facility operating experience among the scientists or engineers designing safeguards technology, or the inability to interact with the IAEA inspector end user. As a result, equipment designers may have difficulty understanding inspector needs and the limitations of using safeguards technology in the field, often leading to inefficiencies (in the form of increased cost and time spent) in the safeguards technology design process. Here, to mitigate this knowledge gap, the Y-12 National Security Complex in Oak Ridge, Tennessee, has developed design considerations that should be incorporated into safeguards technologies, focusing on non-destructive assay equipment. Timelines for integration of these considerations into the design process are also discussed.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Novel Serpentine Robot Combinations for Inspection in Hard-to-Reach Areas of Damaged or Decommissioned Structures - 17335

U.S. government agencies, particularly the Dept. of Energy, need robotic tools to handle and inspect high-consequence materials - materials for which mishandling would result in great risk to both application operators and the general public. The remediation and documentation of nuclear waste has become a problem of national significance and it cannot be addressed without robotic tools. The use of robots bypasses the danger and decreases the preparation time to handle harmful materials. In the 1980's and 90's, the US Dept. of Energy (DOE) invested heavily in robotic technologies as part of a comprehensive program of research and development aimed at enabling safer and more efficient cleanup of nuclear waste sites. For the next generation of harder, more complex clean-up problems, there is a clear need for more R and D. There is a clear need for flexible, quickly deployable robotic technologies that can be configured to respond to unforeseen situations -- or can be purpose-built for planned activities -- while keeping human workers safe, yet effective. Modularity and inter-operability are core capabilities for inspection tasks in contaminated facilities with a large variety of inspection problems. With any tool, familiarity breeds ingenuity, and ingenuity leads to new innovations in efficiency, effectiveness, safety, and performance. For example, the simple screwdriver can be held fourteen different ways by an experienced machinist who knows exactly what he or she wants to accomplish at any given moment. As a tool, robots are no different. To maximize the efficiency, effectiveness, safety and performance, redeployment and reuse of familiar tools is essential. Modularity can assist with re-deployment and modularity manifests itself in both hardware and software. In some applications of inspection of high-consequence materials, a common concern has been the simplicity of the tool -- often correlated with cost (which is not always accurate) -- in case it becomes unrecoverable. In the case of robots, which have complex user interfaces and complex dynamics of interaction, the lack of familiarity can lead to clumsy operations and reduced accumulation of knowledge. As a result, while incremental successes may be achieved with sequential uses of different robots, there often is little knowledge gain that is generalizable across multiple uses. Total cost often goes down when a more sophisticated, but more familiar tool, can be used more frequently.An example is the inspection of the H-Canyon Exhaust Air Tunnel at the Savannah River Site nuclear waste facility in the United States [1]. This is a particularly nasty environment, due to the acidic gases, large amounts of erosion and debris, and wet, mucky puddles. Over the past twelve years, six inspections have been attempted with five different robotic vehicles. In fact, these inspections have been successful with their limited, but progressively increasing objectives, although most robots have been abandoned in the tunnel. While each vehicle has cost less than $75,000 (the sacrificial part), the total costs of development have been much higher. The robots used to investigate changed much from iteration to iteration and it is not clear a strong body of generalizable expertise was built up across trials. The authors of this study demonstrated the combination of two types of modular, serpentine, re-configurable robots for locomotion over complex terrains and the inspection of hard-to-reach areas. The MOTHERSHIP is a tread/limb/serpentine hybrid robot design for locomotion over complex terrains, while the CMU snake robot provides highly articulated inspection of highly confined spaces. The demonstration at the Portsmouth Gaseous Diffusion Plant involves a combination of the two whereby gross locomotion is achieved with the MOTHERSHIP and the CMU Snake deploys a sensor package to gather data from behind and under obstacles. Although statically configured in its present state, the combined robot is built of individual modules for which reconfiguration has been demonstrated in both labs at Purdue and CMU. In future work, much higher degrees of reconfiguration and re-purposing of both software and hardware are easily achievable with these unique platforms. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Geant4Reweight: a framework for evaluating and propagating hadronic interaction uncertainties in Geant4

Geant4Reweight is an open-source C++ framework that allows users to weight tracks produced by the Geant4 particle transport Monte Carlo simulation according to hadron interaction cross section variations and estimate uncertainties in Geant4 interaction models by comparing the simulation’s hadron interaction cross section predictions to data. The ability to weight hadron transport as simulated by Geant4 is crucial to the propagation of systematic uncertainties related to secondary hadronic interactions in current and upcoming neutrino oscillation experiments, including MicroBooNE, NOvA, and DUNE, aswell as hadron test beam experiments such as ProtoDUNE. Here, we provide motivation for weighting hadron tracks in Geant4 in the context of systematic uncertainty propagation, a description of Geant4’s transport simulation technique, and a description of our weighting technique and fitting framework in the momentum range 0–10 GeV/c, which is typical for the hadrons produced by neutrino interactions in these experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Interactive XCMS Online: Simplifying Advanced Metabolomic Data Processing and Subsequent Statistical Analyses

XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process and visualize mass-spectrometry-based, untargeted metabolomic data. Initially, the platform was developed for two-group comparisons to match the independent, “control” versus “disease” experimental design. Here, we introduce an enhanced XCMS Online interface that enables users to perform dependent (paired) two-group comparisons, meta-analysis, and multigroup comparisons, with comprehensive statistical output and interactive visualization tools. Newly incorporated statistical tests cover a wide array of univariate analyses. Multigroup comparison allows for the identification of differentially expressed metabolite features across multiple classes of data while higher order meta-analysis facilitates the identification of shared metabolic patterns across multiple two-group comparisons. Given the complexity of these data sets, we have developed an interactive platform where users can monitor the statistical output of univariate (cloud plots) and multivariate (PCA plots) data analysis in real time by adjusting the threshold and range of various parameters. On the interactive cloud plot, metabolite features can be filtered out by their significance level (p-value), fold change, mass-to-charge ratio, retention time, and intensity. The variation pattern of each feature can be visualized on both extracted-ion chromatograms and box plots. The interactive principal component analysis includes scores, loadings, and scree plots that can be adjusted depending on scaling criteria. The utility of XCMS functionalities is demonstrated through the metabolomic analysis of bacterial stress response and the comparison of lymphoblastic leukemia cell lines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Single-cell isotope tracing reveals functional guilds of bacteria associated with the diatom Phaeodactylum tricornutum

Abstract Bacterial remineralization of algal organic matter fuels algal growth but is rarely quantified. Consequently, we cannot currently predict whether some bacterial taxa may provide more remineralized nutrients to algae than others. Here, we quantified bacterial incorporation of algal-derived complex dissolved organic carbon and nitrogen and algal incorporation of remineralized carbon and nitrogen in fifteen bacterial co-cultures growing with the diatom Phaeodactylum tricornutum at the single-cell level using isotope tracing and nanoSIMS. We found unexpected strain-to-strain and cell-to-cell variability in net carbon and nitrogen incorporation, including non-ubiquitous complex organic nitrogen utilization and remineralization. We used these data to identify three distinct functional guilds of metabolic interactions, which we termed macromolecule remineralizers, macromolecule users, and small-molecule users, the latter exhibiting efficient growth under low carbon availability. The functional guilds were not linked to phylogeny and could not be elucidated strictly from metabolic capacity as predicted by comparative genomics, highlighting the need for direct activity-based measurements in ecological studies of microbial metabolic interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1985

Intelligent data management

Intelligent data management is the concept of interfacing a user to a database management system with a value added service that will allow a full range of data management operations at a high level of abstraction using human written language. The development of such a system will be based on expert systems and related artificial intelligence technologies, and will allow the capturing of procedural and relational knowledge about data management operations and the support of a user with such knowledge in an on-line, interactive manner. Such a system will have the following capabilities: (1) the ability to construct a model of the users view of the database, based on the query syntax; (2) the ability to transform English queries and commands into database instructions and processes; (3) the ability to use heuristic knowledge to rapidly prune the data space in search processes; and (4) the ability to use an on-line explanation system to allow the user to understand what the system is doing and why it is doing it. Additional information is given in outline form.

Campbell, William J.↗