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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

NASA NTRS1994

Using graphics and expert system technologies to support satellite monitoring at the NASA Goddard Space Flight Center

At NASA's Goddard Space Flight Center, fault-isolation expert systems have been developed to support data monitoring and fault detection tasks in satellite control centers. Based on the lessons learned during these efforts in expert system automation, a new domain-specific expert system development tool named the Generic Spacecraft Analysts Assistant (GenSAA), was developed to facilitate the rapid development and reuse of real-time expert systems to serve as fault-isolation assistants for spacecraft analysts. This paper describes GenSAA's capabilities and how it is supporting monitoring functions of current and future NASA missions for a variety of satellite monitoring applications ranging from subsystem health and safety to spacecraft attitude. Finally, this paper addresses efforts to generalize GenSAA's data interface for more widespread usage throughout the space and commercial industry.

Hughes, Peter M.↗

NASA NTRS1990

Rule groupings in expert systems

Currently, expert system shells do not address software engineering issues for developing or maintaining expert systems. As a result, large expert systems tend to be incomprehensible, difficult to debug or modify, and almost impossible to verify or validate Partitioning rule-based systems into rule groups which reflect the underlying subdomains of the problem should enhance the comprehensibility, maintainability, and reliability of expert-system software. In this paper, we investigate methods to semi-automatically structure a CLIPS rule base e into groups of rules that carry related information. We discuss three different distance metrics for measuring the relatedness of rules and describe two clustering algorithms based on these distance metrics. The results of our experiment with three sample rule bases are also presented.

Mehrotra, Mala↗

NASA NTRS1990

A CLIPS expert system for maximizing alfalfa (Medicago Sativa L.) production

An alfalfa management expert system originally developed by Purdue University agricultural scientists on the PC Plus expert system shell from Texas Instrument has been updated and successfully converted to CLIPS (C Language Integrated Production System). This reduces the cost and legal restrictions associated with making the expert system available to agribusiness industries, extension personnel and farm managers and operators. The expert system includes recommendations concerning soil drainage, liming, P and K fertilization, weed control, variety selection and seeding rate including pure live seeds.

Engel, B. A.↗

NASA NTRS1990

Embedding CLIPS-based expert systems in a real-time object-oriented simulation

This paper describes our continuing work embedding CLIPS-based expert systems into the System Test Environment (STE). We are embedding simple, compact rule engines in STE to simulate the actions of Naval platform commanders and equipment operators. Our eventual goal is to implement expert system modules that will replace all human participants and some of the equipment present in the simulation. This paper will briefly describe STE and then discuss its structure and implementation in more detail. Next, we will consider how expert systems could enhance STE's current capabilities. This will be followed by the examination of a specific CLIPS-based expert system model to be embedded in STE. Finally, a summary of our experience and a discussion of anticipated work on this project will close this paper.

Mcconagha, Patrick↗

NASA NTRS1996

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Penaloza, Mauel A.↗

NASA NTRS1998

User Directed Tools for Exploiting Expert Knowledge in an Immersive Segmentation and Visualization Environment

Volumetric data sets have become common in medicine and many sciences through technologies such as computed x-ray tomography (CT), magnetic resonance (MR), positron emission tomography (PET), confocal microscopy and 3D ultrasound. When presented with 2D images humans immediately and unconsciously begin a visual analysis of the scene. The viewer surveys the scene identifying significant landmarks and building an internal mental model of presented information. The identification of features is strongly influenced by the viewers expectations based upon their expert knowledge of what the image should contain. While not a conscious activity, the viewer makes a series of choices about how to interpret the scene. These choices occur in parallel with viewing the scene and effectively change the way the viewer sees the image. It is this interaction of viewing and choice which is the basis of many familiar visual illusions. This is especially important in the interpretation of medical images where it is the expert knowledge of the radiologist which interprets the image. For 3D data sets this interaction of view and choice is frustrated because choices must precede the visualization of the data set. It is not possible to visualize the data set with out making some initial choices which determine how the volume of data is presented to the eye. These choices include, view point orientation, region identification, color and opacity assignments. Further compounding the problem is the fact that these visualization choices are defined in terms of computer graphics as opposed to language of the experts knowledge. The long term goal of this project is to develop an environment where the user can interact with volumetric data sets using tools which promote the utilization of expert knowledge by incorporating visualization and choice into a tight computational loop. The tools will support activities involving the segmentation of structures, construction of surface meshes and local filtering of the data set. To conform to this environment tools should have several key attributes. First, they should be only rely on computations over a local neighborhood of the probe position. Second, they should operate iteratively over time converging towards a limit behavior. Third, they should adapt to user input modifying they operational parameters with time.

Senger, Steven O.↗

NASA NTRS2000

Lay and Expert Perceptions of Planetary Protection

As space scientists and engineers plan new missions to Mars and other planets in our solar system, they will face critical questions about the potential for biological contamination of planetary surfaces. In a society that places ever-increasing importance on the role of public involvement in science and technology policy, questions about risks of biological contamination will be examined and debated in the media, and will lead to the formation of public perceptions of planetary-contamination risks. These perceptions will, over time, form an important input to the development of space policy. Previous research in public and expert perceptions of technological risks and hazards has shown that many of the problems faced by risk-management organizations are the result of differing perceptions of risk (and risk management) between the general public and scientific and technical experts. These differences manifest themselves both as disagreements about the definition (and level) of risk associated with a scientific, technological or industrial enterprise, and as distrust about the ability of risk-management organizations (both public and private) to adequately protect people's health and safety. This report presents the results of a set of survey studies designed to reveal perceptions of planetary exploration and protection from a wide range of respondents, including both members of the general public and experts in the life sciences. The potential value of this research lies in what it reveals about perceptions of risk and benefit that could improve risk-management policies and practices. For example, efforts to communicate with the public about Mars sample return missions could benefit from an understanding of the specific concerns that nonscientists have about such a mission by suggesting areas of potential improvement in public education and information. Assessment of both public and expert perceptions of risk can also be used to provide an advanced signal of aspects of planetary exploration and protection that may be particularly sensitive or controversial and that could prove problematic from a risk-management standpoint, perhaps warranting a more stringent risk-management approach than would otherwise be the case based on technical considerations alone. The design of the study compares perceptions and attitudes about space exploration relevant to a Mars sample return mission between three respondent groups: (1) members of The Planetary Society, a group representing individuals with a strong interest in space-related issues, (2) a group of university-aged students, representing a population relatively sensitive to environmental hazards, and (3) a group of life scientists outside of the space research community. Members of The Planetary Society received the survey as part of a special issue of The Planetary Report on planetary protection, which contained a number of background articles on planetary protection and related topics. A synopsis of the issue was prepared as an introduction to the survey for the other two groups.

Race, Margaret S.↗

NASA NTRS1994

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Herrin, Stephanie↗

NASA NTRS2003

Web-based Weather Expert System (WES) for Space Shuttle Launch

The Web-based Weather Expert System (WES) is a critical module of the Virtual Test Bed development to support 'go/no go' decisions for Space Shuttle operations in the Intelligent Launch and Range Operations program of NASA. The weather rules characterize certain aspects of the environment related to the launching or landing site, the time of the day or night, the pad or runway conditions, the mission durations, the runway equipment and landing type. Expert system rules are derived from weather contingency rules, which were developed over years by NASA. Backward chaining, a goal-directed inference method is adopted, because a particular consequence or goal clause is evaluated first, and then chained backward through the rules. Once a rule is satisfied or true, then that particular rule is fired and the decision is expressed. The expert system is continuously verifying the rules against the past one-hour weather conditions and the decisions are made. The normal procedure of operations requires a formal pre-launch weather briefing held on Launch minus 1 day, which is a specific weather briefing for all areas of Space Shuttle launch operations. In this paper, the Web-based Weather Expert System of the Intelligent Launch and range Operations program is presented.

Bardina, Jorge E.↗

NASA NTRS2004

Development of an Expert Judgement Elicitation and Calibration Methodology for Risk Analysis in Conceptual Vehicle Design

A comprehensive expert-judgment elicitation methodology to quantify input parameter uncertainty and analysis tool uncertainty in a conceptual launch vehicle design analysis has been developed. The ten-phase methodology seeks to obtain expert judgment opinion for quantifying uncertainties as a probability distribution so that multidisciplinary risk analysis studies can be performed. The calibration and aggregation techniques presented as part of the methodology are aimed at improving individual expert estimates, and provide an approach to aggregate multiple expert judgments into a single probability distribution. The purpose of this report is to document the methodology development and its validation through application to a reference aerospace vehicle. A detailed summary of the application exercise, including calibration and aggregation results is presented. A discussion of possible future steps in this research area is given.

Unal, Resit↗

NASA NTRS2009

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an ''expert system'' which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the ''expert system'' remotely, to assess activity within the growth chamber, and can override the ''expert system''.

May, George A.↗

NASA NTRS2011

Expert system for controlling plant growth in a contained environment

In a system for optimizing crop growth, vegetation is cultivated in a contained environment, such as a greenhouse, an underground cavern or other enclosed space. Imaging equipment is positioned within or about the contained environment, to acquire spatially distributed crop growth information, and environmental sensors are provided to acquire data regarding multiple environmental conditions that can affect crop development. Illumination within the contained environment, and the addition of essential nutrients and chemicals are in turn controlled in response to data acquired by the imaging apparatus and environmental sensors, by an "expert system" which is trained to analyze and evaluate crop conditions. The expert system controls the spatial and temporal lighting pattern within the contained area, and the timing and allocation of nutrients and chemicals to achieve optimized crop development. A user can access the "expert system" remotely, to assess activity within the growth chamber, and can override the "expert system".

May, George A.↗

NASA NTRS2015

Engaging Students with Subject Matter Experts and Science Content Through Classroom Connection Webinars

Connecting students and teachers in classrooms with science, technology, engineering, and mathematics (STEM) experts provides an invaluable opportunity. Subject matter experts can share exciting science and science-related events as well as help to "translate" science being conducted by professionals. The Expedition Earth and Beyond (EEAB) Program, facilitated by the Astromaterials Research and Exploration Science (ARES) Division at the NASA Johnson Space Center, has been providing virtual access to subject matter experts through classroom connection webinars for the last five years. Each year, the reach of these events has grown considerably, especially over the last nine months. These virtual connections not only help engage students with role models, but are also designed to help teachers address concepts and content standards they are required to teach. These events also enable scientists and subject matter experts to help "translate" current science in an engaging and understandable manner while actively involving classrooms in the journey of science and exploration.

Graff, P. V.↗

NASA NTRS2015

Building the Next Generation of Scientific Explorers through Active Engagement with STEM Experts and International Space Station Resources

Connecting students and teachers in classrooms with science, technology, engineering, and mathematics (STEM) experts provides an invaluable opportunity for all. These experts can share the benefits and utilization of resources from the International Space Station (ISS) while sharing and "translating" exciting science being conducted by professional scientists. Active engagement with these STEM experts involves students in the journey of science and exploration in an enthralling and understandable manner. This active engagement, connecting classrooms with scientific experts, helps inspire and build the next generation of scientific explorers in academia, private industry, and government.

Graff, P. V.↗

NASA NTRS1993

Exercise countermeasure protocol management expert system

Exercise will be used primarily to countermeasure against deconditioning on extended space flight. In this paper we describe the development and evaluation of an expert system for exercise countermeasure protocol management. Currently, the system includes two major subsystems: baseline prescription and prescription adjustment. The baseline prescription subsystem is designed to provide initial exercise prescriptions while prescription adjustment subsystem is designed to modify the initial prescription based on the exercised progress. The system runs under three different environments: PC, SUN workstation, and Symbolic machine. The inference engine, baseline prescription module, prescription adjustment module and explanation module are developed under the Symbolic environment by using the ART (Automated Reasoning Tool) software. The Sun environment handles database management features and interfaces with PC environment to obtain physical and physiological data from exercise units on-board during the flight. Eight subjects' data have been used to evaluate the system performance by comparing the prescription of nine experienced exercise physiologists and the one prescribed by the expert system. The results of the validation test indicated that the performance of the expert system was acceptable.

NASA Discipline Data Analysis↗

NASA NTRS1975

The use of subjective expert opinions in cost optimum design of aerospace structures

The results of two questionnaires sent to engineering experts are statistically analyzed and compared with objective data from Saturn V design and testing. Engineers were asked how likely it was for structural failure to occur at load increments above and below analysts' stress limit predictions. They were requested to estimate the relative probabilities of different failure causes, and of failure at each load increment given a specific cause. Three mathematical models are constructed based on the experts' assessment of causes. The experts' overall assessment of prediction strength fits the Saturn V data better than the models do, but a model test option (T-3) based on the overall assessment gives more design change likelihood to overstrength structures than does an older standard test option. T-3 compares unfavorably with the standard option in a cost optimum structural design problem. The report reflects a need for subjective data when objective data are unavailable.

Thomas, J. M.↗

NASA NTRS1975

Register of hydrogen technology experts

This register presents the names of approximately 235 individuals who are considered experts, or very knowledgeable, in various fields of technology related to hydrogen. Approximately 90 organizations are represented. Each person is listed by organizational affiliation, address, and principal area of expertise. The criteria for selection of names for the register are extensive experience in a given field of work, participation in or supervision of relevant research programs, contributions to the literature, or being recognized as an expert in a particular field. The purpose of the register is to present, in easy form, sources of dependable information regarding highly technical areas of hydrogen technology, with particular emphasis on safety. The register includes two indexes: an alphabetical listing of the experts and an alphabetical listing of the organizations with which they are affiliated.

Ludtke, P. R.↗

NASA NTRS1982

An overview of expert systems

An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.

Gevarter, W. B.↗