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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

Tilton, James C.↗
NASA NTRS1986

An Expert-System Engine With Operative Probabilities

Program enables proof-of-concepts tests of expert systems under development. AESOP is rule-based inference engine for expert system, which makes decisions about particular situation given user-supplied hypotheses, rules, and answers to questions drawn from rules. If knowledge base containing hypotheses and rules governing environment is available to AESOP, almost any situation within that environment resolved by answering questions asked by AESOP. Questions answered with YES, NO, MAYBE, DON'T KNOW, DON'T CARE, or with probability factor ranging from 0 to 10. AESOP written in Franz LISP for interactive execution.

Orlando, N. E.↗
NASA NTRS1992

Detecting opportunities for parallel observations on the Hubble Space Telescope

The presence of multiple scientific instruments aboard the Hubble Space Telescope provides opportunities for parallel science, i.e., the simultaneous use of different instruments for different observations. Determining whether candidate observations are suitable for parallel execution depends on numerous criteria (some involving quantitative tradeoffs) that may change frequently. A knowledge based approach is presented for constructing a scoring function to rank candidate pairs of observations for parallel science. In the Parallel Observation Matching System (POMS), spacecraft knowledge and schedulers' preferences are represented using a uniform set of mappings, or knowledge functions. Assessment of parallel science opportunities is achieved via composition of the knowledge functions in a prescribed manner. The knowledge acquisition, and explanation facilities of the system are presented. The methodology is applicable to many other multiple criteria assessment problems.

Lucks, Michael↗
NASA NTRS1984

A relational approach to the development of expert diagnostic systems

The proposition that, given a structural and/or functional description of any real or abstract system, an expert system can be built based on this description is examined. First, a model is developed for a microprocessor-controlled end effector/sensor system using a modeling approach called a relational Knowledge-Base Machine (RKBM). Next, an explanation of how the end effector model could be used for the error diagnosis on the operational end effector is given and two versions of an error diagnosis algorithm based on the model are presented. Finally, areas of further research are described that are necessary before an expert system using this approach becomes a reality.

Ames, K. R.↗
NASA NTRS1990

An expert system for geologic mapping with imaging spectrometers

Techniques have been developed for the extraction and characterization of absorption features from visible and infrared reflectance spectra and an expert system has been designed, implemented, and successfully tested that allows automated identification of minerals based on their spectral characteristics. A suite of laboratory spectra of common minerals was analyzed and the absorption band characteristics tabulated and used to develop a generalized knowledge base for analysis of the reflectance spectra. A tree hierarchy was designed to emulate the decision process followed by an experienced analyst for analysis of laboratory and field reflectance spectra and aircraft imaging spectrometer spectra. Good results were obtained with the expert system for all three types of spectra, with the critical factor in the analysis being the signal-to-noise ratio of the spectral data.

Kruse, F. A.↗
NASA NTRS1992

AXAF user interfaces for heterogeneous analysis environments

The AXAF Science Center (ASC) will develop software to support all facets of data center activities and user research for the AXAF X-ray Observatory, scheduled for launch in 1999. The goal is to provide astronomers with the ability to utilize heterogeneous data analysis packages, that is, to allow astronomers to pick the best packages for doing their scientific analysis. For example, ASC software will be based on IRAF, but non-IRAF programs will be incorporated into the data system where appropriate. Additionally, it is desired to allow AXAF users to mix ASC software with their own local software. The need to support heterogeneous analysis environments is not special to the AXAF project, and therefore finding mechanisms for coordinating heterogeneous programs is an important problem for astronomical software today. The approach to solving this problem has been to develop two interfaces that allow the scientific user to run heterogeneous programs together. The first is an IRAF-compatible parameter interface that provides non-IRAF programs with IRAF's parameter handling capabilities. Included in the interface is an application programming interface to manipulate parameters from within programs, and also a set of host programs to manipulate parameters at the command line or from within scripts. The parameter interface has been implemented to support parameter storage formats other than IRAF parameter files, allowing one, for example, to access parameters that are stored in data bases. An X Windows graphical user interface called 'agcl' has been developed, layered on top of the IRAF-compatible parameter interface, that provides a standard graphical mechanism for interacting with IRAF and non-IRAF programs. Users can edit parameters and run programs for both non-IRAF programs and IRAF tasks. The agcl interface allows one to communicate with any command line environment in a transparent manner and without any changes to the original environment. For example, the authors routinely layer the GUI on top of IRAF, ksh, SMongo, and IDL. The agcl, based on the facilities of a system called Answer Garden, also has sophisticated support for examining documentation and help files, asking questions of experts, and developing a knowledge base of frequently required information. Thus, the GUI becomes a total environment for running programs, accessing information, examining documents, and finding human assistance. Because the agcl can communicate with any command-line environment, most projects can make use of it easily. New applications are continually being found for these interfaces. It is the authors' intention to evolve the GUI and its underlying parameter interface in response to these needs - from users as well as developers - throughout the astronomy community. This presentation describes the capabilities and technology of the above user interface mechanisms and tools. It also discusses the design philosophies guiding the work, as well as hopes for the future.

Mandel, Eric↗
NASA NTRS2001

Protein Crystal Based Nanomaterials

This is the final report on a NASA Grant. It concerns a description of work done, which includes: (1) Protein crystals cross-linked to form fibers; (2) Engineering of protein to favor crystallization; (3) Better knowledge-based potentials for protein-protein contacts; (4) Simulation of protein crystallization.

Bell, Jeffrey A.↗
NASA NTRSDate not supplied

A Knowledge Graph Framework for Organizing Heterogeneous Datasets for Utilization in Classical and Quantum Computing: Current Challenges and Future Directions

"The escalating impact of climate change induced extreme weather events in urban, suburban, and rural environments demands a rethink of how we have been using the single event-based or use-case-based knowledge graph models. The lack of representation in interaction within environmental variables found in literature led to the development of a novel framework that reflects the true nature of the interconnectedness in our environment. We propose an Environmental Interaction Knowledge Graph (EIKG) framework. This general EIKG framework works as the basis for interconnected environmental events by knitting interrelated events such as hurricanes leading to storm surges, which lead to flood events that could cause mudslides, landslides, etc., The cascading nature of one event leading to another related event in the environment requires an adequate understanding of each event using contextual information before conducting any data-driven analytics. This vision paper showcases how the EIKG:floods, EIKG:wildfire EIKG:landslides, etc, can be derived from a base case framework of EIKG as those individual events are interconnected with some common denominator variables. As an example, the precipitation variable is used in the flood case study as well as in the wildfire case study, as excessive precipitation levels lead to floods, and lack of precipitation leads to droughts and wildfires. We identify the precipitation variable as a “common-denominator-variable” in extreme weather events that play a key role in modeling the environment leading to different extreme weather events based on the variability of that variable (varying values where low precipitation leads to drought, and high values lead to floods). We use the insights gained from EIKG to conduct classical and Quantum Machine Learning (QML) based data analysis on the research questions developed. Our preliminary study shows how the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC) are used along with the classical machine learning models to compare the model accuracies. Our study elaborates on how a quantitative analysis uses state-of-the-art machine learning techniques that include implementing both classical and quantum machine learning models and developing the knowledge graph. The EIKG is used to organize heterogeneous datasets and integrate the relations to case-specific extreme weather events such as floods. The study uses datasets such as county-to-country residential mobility data, socioeconomic datasets from the US Census Bureau, climate and weather-related Earth Observational data from NASA, and critical infrastructure data from the Homeland Infrastructure datasets."

Knowledge Graphs, Quantum Computing, Heterogenous ↗
NASA NTRS1989

Perceptual telerobotics

A sensory world modeling system, congruent with a human expert's perception, is proposed. The Experiential Knowledge Base (EKB) system can provide a highly intelligible communication interface for telemonitoring and telecontrol of a real time robotic system operating in space. Paradigmatic acquisition of empirical perceptual knowledge, and real time experiential pattern recognition and knowledge integration are reviewed. The cellular architecture and operation of the EKB system are also examined.

Ligomenides, Panos A.↗
NASA NTRS1991

Distributed semantic networks and CLIPS

Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

Snyder, James↗
NASA NTRS1993

Limitations to the study of man in space in the U.S. space program

Research on humans conducted during spaceflight is fraught both with great opportunities and great obstacles. The purpose of this paper is to review some of the limitations to research in space in the United States with hope that an informed scientific community may lead to more rapid and efficient solution of these problems. Limitations arise because opportunities to study the same astronauts in well-controlled situations on repeated spaceflights are practically non-existent. Human research opportunities are further limited by the necessity of avoiding simultaneous mutually-interfering experiments. Environmental factors, including diet and other physiological perturbations concomitant with spaceflight, also complicate research design and interpretation. Technical limitations to research methods and opportunities further restrict the development of the knowledge base. Finally, Earth analogues of space travel all suffer from inadequacies. Though all of these obstacles will eventually be overcome, creativity, diligence, and persistence are required to further our knowledge of humans in space.

Bishop, Phillip A.↗
NASA NTRS1992

Limitations to the study of man in the United States space program

Research on humans conducted during space flight is fraught both with great opportunities and great obstacles. The purpose of this paper is to review some of the limitations to United States research in space in the hope that an informed scientific community may lead to more rapid and efficient solution of these problems. Limitations arise because opportunities to study the same astronauts in well-controlled situations on repeated space flights are practically non-existent. Human research opportunities are further limited by the necessity of avoiding simultaneous mutually-interfereing experiments. Environmental factors including diet and other physiological perturbations concomitant with space flight also complicates research design and interpretation. Technical limitations to research methods and opportunities further restrict the development of the knowledge base. Finally, earth analogues of space travel all suffer from inadequacies. Though all of these obstacles will eventually be overcome; creativity, diligence, and persistence are required to further our knowledge of humans in space.

Bishop, Phillip A.↗
NASA NTRS1991

Testing validation tools on CLIPS-based expert systems

The Expert Systems Validation Associate (EVA) is a validation system which was developed at the Lockheed Software Technology Center and Artificial Intelligence Center between 1986 and 1990. EVA is an integrated set of generic tools to validate any knowledge-based system written in any expert system shell such as C Language Integrated Production System (CLIPS), ART, OPS5, KEE, and others. Many validation tools have been built in the EVA system. In this paper, we describe the testing results of applying the EVA validation tools to the Manned Maneuvering Unit (MMU) Fault Diagnosis, Isolation, and Reconfiguration (FDIR) expert system, written in CLIPS, obtained from the NASA Johnson Space Center.

Chang, C. L.↗
NASA NTRS1992

Expert system-based mineral mapping using AVIRIS

Integrated analysis of imaging spectrometer data and field spectral measurements were used in conjunction with conventional geologic field mapping to characterize bedrock and surficial geology at the northern end of Death Valley, California and Nevada. A knowledge-based expert system was used to automatically produce image maps from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data showing the principal surface mineralogy. The imaging spectrometer data show the spatial distribution of spectrally distinct minerals occurring both as primary rock-forming minerals and as alteration and weathering products. Field spectral measurements were used to verify the mineral maps and field mapping was used to extend the remote sensing results. Geographically referenced image-maps produced from these data form new base maps from which to develop improved understanding of the processes of deposition and erosion affecting the present land surface. The 'northern Grapevine Mountains' (NGM) study area was reported on in numerous papers. This area is an unnamed northwestward extension of the range. Most of the research here has concentrated on mapping of Jurassic-age plutons and associated hydrothermal alteration, however, the nature and scope of these studies is much broader, pertaining to the geologic history and development of the entire Death Valley region. AVIRIS data for the NGM site were obtained during May 1989. Additional AVIRIS data were acquired during September 1989 as part of the Geologic Remote Sensing Field Experiment (GRSFE). The area covered by these data overlaps slightly with the May 1989 data. Three and one-half AVIRIS scenes total were analyzed.

Kruse, Fred A.↗
NASA NTRS1991

Long duration human exposure to microgravity

Looking toward the era of long duration manned spaceflight, questions remain regarding human adaptation to the weightless environment. In particular, bone calcium loss, cardiovascular deconditioning, and effects of radiation require further study. NASA has undertaken a series of experiments to increase the knowledge base of human adaptation to spaceflight. To date, results in the area of cardiovascular deconditioning countermeasures are the furthest advanced. The results from the upcoming SLS-1 mission will enhance knowledge in all areas. With continued research, there is every confidence that astronauts will be able to be kept healthy for long periods of time.

Huntoon, C. L.↗
NASA NTRS1990

Interpretation of Space Shuttle telemetry

This paper describes the Payload Deployment and Retrieval System (PDRS) Failure Analysis and Diagnosis problem, our planned use of an expert system employing the C Language Integrated Production System (CLIPS) language to solve it, and our progress to date. In addition, it will address the importance of the overall design within the context of automation in the RTDS architecture, the methodology used, and the validation approach taken. The Decision Support System will evolve as a modularized rule-based system programmed in the CLIPS expert system language. Each of five modules represents a subsystem of the RMS and includes the positioning and retention hardware (MPM/MRL), the Display & Control panel (D8C), the Arm Based Electronics (ABE), the End Effector (EE), and the Orbiter to RMS data interface unit (MCIU). The MPM/MRL subsystem was chosen as the target of a prototype development and its knowledge base is completed. Testing and validation of the software is conducted by experienced mission controllers. The initial design stages for the D&C panel module are beginning.

Culp, Donald R.↗
NASA NTRS1982

Multilevel semantic analysis and problem-solving in the flight domain

A computer based cockpit system which is capable of assisting the pilot in such important tasks as monitoring, diagnosis, and trend analysis was developed. The system is properly organized and is endowed with a knowledge base so that it enhances the pilot's control over the aircraft while simultaneously reducing his workload.

Chien, R. T.↗
NASA NTRS1987

SOLON: An autonomous vehicle mission planner

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Dudziak, M. J.↗