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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

Kimes, D. S.↗
DOE OSTI2015

MO-FG-303-03: Demonstration of Universal Knowledge-Based 3D Dose Prediction

Purpose: To demonstrate a knowledge-based 3D dose prediction methodology that can accurately predict achievable radiotherapy distributions. Methods: Using previously treated plans as input, an artificial neural network (ANN) was trained to predict 3D dose distributions based on 14 patient-specific anatomical parameters including the distance (r) to planning target volume (PTV) boundary, organ-at-risk (OAR) boundary distances, and angular position ( θ,φ). 23 prostate and 49 stereotactic radiosurgery (SRS) cases with ≥1 nearby OARs were studied. All were planned with volumetric-modulated arc therapy (VMAT) to prescription doses of 81Gy for prostate and 12–30Gy for SRS. Site-specific ANNs were trained using all prostate 23 plans and using a 24 randomly-selected subset for the SRS model. The remaining 25 SRS plans were used to validate the model. To quantify predictive accuracy, the dose difference between the clinical plan and prediction were calculated on a voxel-by-voxel basis δD(r,θ,φ)=Dclin(r,θ,φ)-Dpred(r, θ,φ). Grouping voxels by boundary distance, the mean <δ Dr>=(1/N)Σ -θ,φ D(r,θ,φ) and inter-quartile range (IQR) quantified the accuracy of this method for deriving DVH estimations. The standard deviation (σ) of δ D quantified the 3D dose prediction error on a voxel-by-voxel basis. Results: The ANNs were highly accurate in predictive ability for both prostate and SRS plans. For prostate, <δDr> ranged from −0.8% to +0.6% (max IQR=3.8%) over r=0–32mm, while 3D dose prediction accuracy averaged from σ=5–8% across the same range. For SRS, from r=0–34mm the training set <δDr> ranged from −3.7% to +1.5% (max IQR=4.4%) while the validation set <δDr> ranged from −2.2% to +5.8% (max IQR=5.3%). 3D dose prediction accuracy averaged σ=2.5% for the training set and σ=4.0% over the same interval. Conclusion: The study demonstrates this technique’s ability to predict achievable 3D dose distributions for VMAT SRS and prostate. Future investigations will attempt to separate and quantify modeling error and plan quality variations in the statistical noise. Research funding support from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-BRA-01: SCIENCE COUNCIL JUNIOR INVESTIGATOR COMPETITION WINNER: Acceleration of a Limited-Angle Intrafraction Verification (LIVE) System Using Adaptive Prior Knowledge Based Image Estimation

Purpose: To develop an adaptive prior knowledge based image estimation method to reduce the scan angle needed in the LIVE system to reconstruct 4D-CBCT for intrafraction verification. Methods: The LIVE system has been previously proposed to reconstructs 4D volumetric images on-the-fly during arc treatment for intrafraction target verification and dose calculation. This system uses limited-angle beam’s eye view (BEV) MV cine images acquired from the treatment beam together with the orthogonally acquired limited-angle kV projections to reconstruct 4D-CBCT images for target verification during treatment. In this study, we developed an adaptive constrained free-form deformation reconstruction technique in LIVE to further reduce the scanning angle needed to reconstruct the CBCT images. This technique uses free form deformation with energy minimization to deform prior images to estimate 4D-CBCT based on projections acquired in limited angle (orthogonal 6°) during the treatment. Note that the prior images are adaptively updated using the latest CBCT images reconstructed by LIVE during treatment to utilize the continuity of patient motion.The 4D digital extended-cardiac-torso (XCAT) phantom was used to evaluate the efficacy of this technique with LIVE system. A lung patient was simulated with different scenario, including baseline drifts, amplitude change and phase shift. Limited-angle orthogonal kV and beam’s eye view (BEV) MV projections were generated for each scenario. The CBCT reconstructed by these projections were compared with the ground-truth generated in XCAT.Volume-percentage-difference (VPD) and center-of-mass-shift (COMS) were calculated between the reconstructed and the ground-truth tumors to evaluate the reconstruction accuracy. Results: Using orthogonal-view of 6° kV and BEV- MV projections, the VPD/COMS values were 12.7±4.0%/0.7±0.5 mm, 13.0±5.1%/0.8±0.5 mm, and 11.4±5.4%/0.5±0.3 mm for the three scenarios, respectively. Conclusion: The technique enables LIVE to accurately reconstruct 4D-CBCT images using only orthogonal 6° angle, which greatly improves the efficiency and reduces dose of LIVE for intrafraction verification.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Knowledge-based simulation using object-oriented programming

Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.

Sidoran, Karen M.↗
NASA NTRS1988

Knowledge-based zonal grid generation for computational fluid dynamics

Automation of flow field zoning in two dimensions is an important step towards reducing the difficulty of three-dimensional grid generation in computational fluid dynamics. Using a knowledge-based approach makes sense, but problems arise which are caused by aspects of zoning involving perception, lack of expert consensus, and design processes. These obstacles are overcome by means of a simple shape and configuration language, a tunable zoning archetype, and a method of assembling plans from selected, predefined subplans. A demonstration system for knowledge-based two-dimensional flow field zoning has been successfully implemented and tested on representative aerodynamic configurations. The results show that this approach can produce flow field zonings that are acceptable to experts with differing evaluation criteria.

Andrews, Alison E.↗
NASA NTRS1988

Knowledge based programming environments: A perspective

Programming environments is an area of recent origin and refers to an integrated set of tools, such as program library, text editor, compiler, and debugger, in support of program development. Understanding of programs and programming has lead to automated techniques for program development. Knowledge based programming system using program transformations offer significant impact on future program development methodologies. A review of recent developments in the area of knowledge based programming environments, from the perspective of software engineering, is presented.

Amin, Ashok T.↗
NASA NTRS1987

A formal approach to validation and verification for knowledge-based control systems

As control systems become more complex in response to desires for greater system flexibility, performance and reliability, the promise is held out that artificial intelligence might provide the means for building such systems. An obstacle to the use of symbolic processing constructs in this domain is the need for verification and validation (V and V) of the systems. Techniques currently in use do not seem appropriate for knowledge-based software. An outline of a formal approach to V and V for knowledge-based control systems is presented.

Castore, Glen↗
DOE OSTI2015

SU-E-T-332: Dosimetric Impact of Photon Energy and Treatment Technique When Knowledge Based Auto-Planning Is Implemented in Radiotherapy of Localized Prostate Cancer

Purpose: The aim of this study was to investigate the dosimetric impact of the combination of photon energy and treatment technique on radiotherapy of localized prostate cancer when knowledge based planning was used. Methods: A total of 16 patients with localized prostate cancer were retrospectively retrieved from database and used for this study. For each patient, four types of treatment plans with different combinations of photon energy (6X and 10X) and treatment techniques (7-field IMRT and 2-arc VMAT) were created using a prostate DVH estimation model in RapidPlan™ and Eclipse treatment planning system (Varian Medical System). For any beam arrangement, DVH objectives and weighting priorities were generated based on the geometric relationship between the OAR and PTV. Photon optimization algorithm was used for plan optimization and AAA algorithm was used for final dose calculation. Plans were evaluated in terms of the pre-defined dosimetric endpoints for PTV, rectum, bladder, penile bulb, and femur heads. A Student’s paired t-test was used for statistical analysis and p > 0.05 was considered statistically significant. Results: For PTV, V95 was statistically similar among all four types of plans, though the mean dose of 10X plans was higher than that of 6X plans. VMAT plans showed higher heterogeneity index than IMRT plans. No statistically significant difference in dosimetry metrics was observed for rectum, bladder, and penile bulb among plan types. For left and right femur, VMAT plans had a higher mean dose than IMRT plans regardless of photon energy, whereas the maximum dose was similar. Conclusion: Overall, the dosimetric endpoints were similar regardless of photon energy and treatment techniques when knowledge based auto planning was used. Given the similarity in dosimetry metrics of rectum, bladder, and penile bulb, the genitourinary and gastrointestinal toxicities should be comparable among the selections of photon energy and treatment techniques.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

Knowledge-Based System for Flight Information Management

The use of knowledge-based system (KBS) architectures to manage information on the primary flight display (PFD) of commercial aircraft is described. The PFD information management strategy used tailored the information on the PFD to the tasks the pilot performed. The KBS design and implementation of the task-tailored PFD information management application is described. The knowledge acquisition and subsequent system design of a flight-phase-detection KBS is also described. The flight-phase output of this KBS was used as input to the task-tailored PFD information management KBS. The implementation and integration of this KBS with existing aircraft systems and the other KBS is described. The flight tests are examined of both KBS's, collectively called the Task-Tailored Flight Information Manager (TTFIM), which verified their implementation and integration, and validated the software engineering advantages of the KBS approach in an operational environment.

Ricks, Wendell R.↗
DOE OSTI2016

SU-G-TeP4-14: Quality Control of Treatment Planning Using Knowledge-Based Planning Across a System of Radiation Oncology Practices

Purpose: There is potentially a wide variation in plan quality for a certain disease site, even for clinics located in the same system of hospitals. We have used a prostate-specific knowledge-based planning (KBP) model as a quality control tool to investigate the variation in prostate treatment planning across a network of affiliated radiation oncology departments. Methods: A previously created KBP model was applied to 10 patients each from 4 community-based clinics (Clinics A, B, C, and D). The KBP model was developed using RapidPlan (Eclipse v13.5, Varian Medical Systems) from 60 prostate/prostate bed IMRT plans that were originally planned using an in-house treatment planning system at the central institution of the community-based clinics. The dosimetric plan quality (target coverage and normal-tissue sparing) of each model-generated plan was compared to the respective clinically-used plan. Each community-based clinic utilized the same planning goals to develop the clinically-used plans that were used at the main institution. Results: Across all 4 clinics, the model-generated plans decreased the mean dose to the rectum by varying amounts (on average, 12.5, 2.6, 4.5, and 2.7 Gy for Clinics A, B, C, and D, respectively). The mean dose to the bladder also decreased with the model-generated plans (5.4, 2.3, 3.0, and 4.1 Gy, respectively). The KBP model also identified that target coverage (D95%) improvements were possible for for Clinics A, B, and D (0.12, 1.65, and 2.75%) while target coverage decreased by 0.72% for Clinic C, demonstrating potentially different trade-offs made in clinical plans at different institutions. Conclusion: Quality control of dosimetric plan quality across a system of radiation oncology practices is possible with knowledge-based planning. By using a quality KBP model, smaller community-based clinics can potentially identify the areas of their treatment plans that may be improved, whether it be in normal-tissue sparing or improved target coverage. M. Matuszak has research funding for KBP from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1989

STRUTEX: A prototype knowledge-based system for initially configuring a structure to support point loads in two dimensions

Only recently have engineers begun making use of Artificial Intelligence (AI) tools in the area of conceptual design. To continue filling this void in the design process, a prototype knowledge-based system, called STRUTEX has been developed to initially configure a structure to support point loads in two dimensions. This prototype was developed for testing the application of AI tools to conceptual design as opposed to being a testbed for new methods for improving structural analysis and optimization. This system combines numerical and symbolic processing by the computer with interactive problem solving aided by the vision of the user. How the system is constructed to interact with the user is described. Of special interest is the information flow between the knowledge base and the data base under control of the algorithmic main program. Examples of computed and refined structures are presented during the explanation of the system.

Robers, James L.↗
NASA NTRS1991

A proven knowledge-based approach to prioritizing process information

Many space-related processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect is rapid analysis of the changing process information. During a disturbance, this task can overwhelm humans as well as computers. Humans deal with this by applying heuristics in determining significant information. A simple, knowledge-based approach to prioritizing information is described. The approach models those heuristics that humans would use in similar circumstances. The approach described has received two patents and was implemented in the Alarm Filtering System (AFS) at the Idaho National Engineering Laboratory (INEL). AFS was first developed for application in a nuclear reactor control room. It has since been used in chemical processing applications, where it has had a significant impact on control room environments. The approach uses knowledge-based heuristics to analyze data from process instrumentation and respond to that data according to knowledge encapsulated in objects and rules. While AFS cannot perform the complete diagnosis and control task, it has proven to be extremely effective at filtering and prioritizing information. AFS was used for over two years as a first level of analysis for human diagnosticians. Given the approach's proven track record in a wide variety of practical applications, it should be useful in both ground- and space-based systems.

Corsberg, Daniel R.↗
NASA NTRS1987

Knowledge-based vision for space station object motion detection, recognition, and tracking

Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

Symosek, P.↗
NASA NTRS1988

Generic supervisor: A knowledge-based tool for control of space station on-board systems

The concept of a generic module for management of onboard systems grew out of the structured analysis effort for the Space Station software. Hierarchical specification of subsystems software revealed that nontrivial supervisory elements are required at all levels. The number of supervisors (and subsequent software) required to implement the hierarchical control over onboard functions comprise a large portion of the Space Station software. Thus, a generic knowledge based supervisory module significantly reduces the amount of software developed. This module, the Generic Supervisor, depends on its knowledge of control to provide direction for subordinates and feedback to superiors within a specific subsystem area. The Generic Supervisor provides an adaptable and maintainable control system. A portion of the Space Station Environmental Control and Life Support System (ECLSS) was implemented as a hierarchy of supervisors. This prototype implementation demonstrates the feasibility of a generic knowledge based supervisor, and its facility to meet complex mission requirements.

Carnes, J. R.↗
NASA NTRS1989

Knowledge-based reusable software synthesis system

The Eli system, a knowledge-based reusable software synthesis system, is being developed for NASA Langley under a Phase 2 SBIR contract. Named after Eli Whitney, the inventor of interchangeable parts, Eli assists engineers of large-scale software systems in reusing components while they are composing their software specifications or designs. Eli will identify reuse potential, search for components, select component variants, and synthesize components into the developer's specifications. The Eli project began as a Phase 1 SBIR to define a reusable software synthesis methodology that integrates reusabilityinto the top-down development process and to develop an approach for an expert system to promote and accomplish reuse. The objectives of the Eli Phase 2 work are to integrate advanced technologies to automate the development of reusable components within the context of large system developments, to integrate with user development methodologies without significant changes in method or learning of special languages, and to make reuse the easiest operation to perform. Eli will try to address a number of reuse problems including developing software with reusable components, managing reusable components, identifying reusable components, and transitioning reuse technology. Eli is both a library facility for classifying, storing, and retrieving reusable components and a design environment that emphasizes, encourages, and supports reuse.

Donaldson, Cammie↗
NASA NTRS1991

A knowledge-based expert system for inferring vegetation characteristics

A prototype knowledge-based expert system VEG is presented that focuses on extracting spectral hemispherical reflectance using any combination of nadir and/or directional reflectance data as input. The system is designed to facilitate expansion to handle other inferences regarding vegetation properties such as total hemispherical reflectance, leaf area index, percent ground cover, phosynthetic capacity, and biomass. This approach is more robust and accurate than conventional extraction techniques previously developed.

Kimes, Daniel S.↗
NASA NTRS1992

Knowledge-based assistance for science visualization and analysis using large distributed databases

Within this decade, the growth in complexity of exploratory data analysis and the sheer volume of space data require new and innovative approaches to support science investigators in achieving their research objectives. To date, there have been numerous efforts addressing the individual issues involved in inter-disciplinary, multi-instrument investigations. However, while successful in small scale, these efforts have not proven to be open and scaleable. This proposal addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within this proposal is the integration of three automation technologies, namely, knowledge-based expert systems, science visualization and science data management. This integration is based on the concept called the Data Hub. With the Data Hub concept, NASA will be able to apply a more complete solution to all nodes of a distributed system. Both computation nodes and interactive nodes will be able to effectively and efficiently use the data services (access, retrieval, update, etc.) with a distributed, interdisciplinary information system in a uniform and standard way. This will allow the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis will be on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to publishable scientific results. In addition, the proposed work includes all the required end-to-end components and interfaces to demonstrate the completed concept.

Handley, Thomas H., Jr.↗