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At least 235 records · Page 13

The Knowledge-based Digital Platform Concept for Advanced Air Mobility Research and Development

National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers (SE) together across organizational boundaries. The overarching vision for the KbDP Concept for AAM R&D is a substantial undertaking. The initial concept and implementation will focus on UAM operations to tractably learn and adjust the concept with a manageable database. Lessons learned and best practices with a smaller scope will enable successful scalability to AAM R&D or even to the entire modes of transportation and logistics. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. Initial implementation of three KbDP concepts of use shows promising benefits to NASA’s Air Traffic Management-Exploration (ATM-X) UAM Airspace Subproject. It is envisioned that the KbDP will manage an information database defined by mathematical, data science, and system engineering principles. AIML algorithms play a vital role in this KbDP concept by extracting meaningful knowledge from the information database, which the human user leverages to improve the efficiency and effectiveness of their research greatly.

ATM↗

Application of flight systems methodologies to the validation of knowledge-based systems

Flight and mission-critical systems are verified, qualified for flight, and validated using well-known and well-established techniques. These techniques define the validation methodology used for such systems. In order to verify, qualify, and validate knowledge-based systems (KBS's), the methodology used for conventional systems must be addressed, and the applicability and limitations of that methodology to KBS's must be identified. The author presents an outline of how this approach to the validation of KBS's is being developed and used at the Dryden Flight Research Facility of the NASA Ames Research Center.

Duke, Eugene L.↗

Application of flight systems methodologies to the validation of knowledge-based systems

Flight and mission-critical systems are verified, qualified for flight, and validated using well-known and well-established techniques. These techniques define the validation methodology used for such systems. In order to verify, qualify, and validate knowledge-based systems (KBS's), the methodology used for conventional systems must be addressed, and the applicability and limitations of that methodology to KBS's must be identified. An outline of how this approach to the validation of KBS's is being developed and used is presented.

Duke, Eugene L.↗

Manned spaceflight activity planning with knowledge-based systems

An on-board expert system, capable of assisting with crew-activity planning and platform-status monitoring, could provide unprecedented autonomy to the crew of a permanently manned space station. To demonstrate this concept's feasibility, an existing knowledge-based system is adapted to support Space Shuttle crew-activity timeline planning. Proposed timeline changes are to be checked for compliance with crew capabilities and mission operating guidelines, so that a nonexpert can be guided through a successful plan modification. Early lessons that have been learned about the scope of the adaptation needed to achieve this objective are presented.

Mogilensky, J.↗

Data acquisition for a real time fault monitoring and diagnosis knowledge-based system for space power system

The design and implementation of the real-time data acquisition and processing system employed in the AMPERES project is described, including effective data structures for efficient storage and flexible manipulation of the data by the knowledge-based system (KBS), the interprocess communication mechanism required between the data acquisition system and the KBS, and the appropriate data acquisition protocols for collecting data from the sensors. Sensor data are categorized as critical or noncritical data on the basis of the inherent frequencies of the signals and the diagnostic requirements reflected in their values. The critical data set contains 30 analog values and 42 digital values and is collected every 10 ms. The noncritical data set contains 240 analog values and is collected every second. The collected critical and noncritical data are stored in separate circular buffers. Buffers are created in shared memory to enable other processes, i.e., the fault monitoring and diagnosis process and the user interface process, to freely access the data sets.

Wilhite, Larry D.↗

Knowledge-based requirements analysis for automating software development

We present a new software development paradigm that automates the derivation of implementations from requirements. In this paradigm, informally-stated requirements are expressed in a domain-specific requirements specification language. This language is machine-understable and requirements expressed in it are captured in a knowledge base. Once the requirements are captured, more detailed specifications and eventually implementations are derived by the system using transformational synthesis. A key characteristic of the process is that the required human intervention is in the form of providing problem- and domain-specific engineering knowledge, not in writing detailed implementations. We describe a prototype system that applies the paradigm in the realm of communication engineering: the prototype automatically generates implementations of buffers following analysis of the requirements on each buffer.

Markosian, Lawrence Z.↗

Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

Bosworth, Edward L., Jr.↗

A knowledge based approach to matching human neurodegenerative disease and animal models

Neurodegenerative diseases present a wide and complex range of biological and clinical features. Animal models are key to translational research, yet typically only exhibit a subset of disease features rather than being precise replicas of the disease. Consequently, connecting animal to human conditions using direct data-mining strategies has proven challenging, particularly for diseases of the nervous system, with its complicated anatomy and physiology. To address this challenge we have explored the use of ontologies to create formal descriptions of structural phenotypes across scales that are machine processable and amenable to logical inference. As proof of concept, we built a Neurodegenerative Disease Phenotype Ontology (NDPO) and an associated Phenotype Knowledge Base (PKB) using an entity-quality model that incorporates descriptions for both human disease phenotypes and those of animal models. Entities are drawn from community ontologies made available through the Neuroscience Information Framework (NIF) and qualities are drawn from the Phenotype and Trait Ontology (PATO). We generated ~1200 structured phenotype statements describing structural alterations at the subcellular, cellular and gross anatomical levels observed in 11 human neurodegenerative conditions and associated animal models. PhenoSim, an open source tool for comparing phenotypes, was used to issue a series of competency questions to compare individual phenotypes among organisms and to determine which animal models recapitulate phenotypic aspects of the human disease in aggregate. Overall, the system was able to use relationships within the ontology to bridge phenotypes across scales, returning non-trivial matches based on common subsumers that were meaningful to a neuroscientist with an advanced knowledge of neuroanatomy. The system can be used both to compare individual phenotypes and also phenotypes in aggregate. This proof of concept suggests that expressing complex phenotypes using formal ontologies provides considerable benefit for comparing phenotypes across scales and species.

59 BASIC BIOLOGICAL SCIENCES↗

Clips as a knowledge based language

CLIPS is a language for writing expert systems applications on a personal or small computer. Here, the CLIPS programming language is described and compared to three other artificial intelligence (AI) languages (LISP, Prolog, and OPS5) with regard to the processing they provide for the implementation of a knowledge based system (KBS). A discussion is given on how CLIPS would be used in a control system.

Harrington, James B.↗

Knowledge Based Engineering for Spatial Database Management and Use

The use of artificial intelligence techniques that are applicable to Geographic Information Systems (GIS) are examined. Questions involving the performance and modification to the database structure, the definition of spectra in quadtree structures and their use in search heuristics, extension of the knowledge base, and learning algorithm concepts are investigated.

Peuquet, D.↗

A model for a knowledge-based system's life cycle

The American Institute of Aeronautics and Astronautics has initiated a Committee on Standards for Artificial Intelligence. Presented here are the initial efforts of one of the working groups of that committee. The purpose here is to present a candidate model for the development life cycle of Knowledge Based Systems (KBS). The intent is for the model to be used by the Aerospace Community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are detailed as are and the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

Kiss, Peter A.↗

MO-G-201-04: Knowledge-Based Planning for Single-Isocenter Stereotactic Radiosurgery to Multiple Brain Metastases

Purpose: Single-isocenter, linac-based SRS for multiple brain metastases (multi-mets) can deliver highly conformal radiation doses and reduce overall patient treatment time compared to other therapy techniques. This study aims to quantify the dosimetric benefits of knowledge-based planning (KBP) for multi-met treatments. Methods: Using a previously-published KBP methodology (an artificial neural network (ANN) trained on single-target linac-based SRS plans), 3D dose distribution predictions for multi-met patients were obtained by treating each brain lesion as a solitary target and subsequently combining individual predictions into a single distribution using a dose-weighted geometric averaging to obtain the best results in the inter-target space. 17 previously-treated multi-met plans, with target numbers ranging from N=2–5, were used to validate the ANN predictions and subsequent KBP auto-planning routine. The fully-deliverable KBP plans were developed by converting dose distribution predictions into patient-specific optimization objectives while maintaining identical target normalizations (typically PTV V100%=D98%). Plan quality improvements were quantified by the difference between SRS quality metrics (QMs): δdQM=QM(clinical)-QM(KBP). QMs of interest were: gradient measure (GM), conformity index (CI), brain V10 and V5, brainstem D0.1cc and heterogeneity index (HI). Finally, overall plan quality was judged via blinded plan comparison by SRS-specializing physicians. Results: Two clinical plans were found to be significant outliers wherein plan quality was dramatically worse than KBP. Despite indicating KBP superiority, these were removed from the QM analysis to prevent skewing the results. In the remaining cases, clinical and KBP QMs were nearly identical with modest improvements in the KBP sample: δGM=0.12±0.56mm, δCI=−0.01±0.04, Brain δV10=0.8±2.6cc, brain δV5=6.3 ±10.7cc, brainstem δD0.1cc=0.06±1.19Gy and δHI= −0.04±0.05. Ultimately, 13/17 KBP plans were deemed superior to the manual plans in blinded physician review. Conclusion: The results demonstrate that KBP-driven automated planning in linac-based single-isocenter treatments for multiple brain metastases is indistinguishable from, or even better than, traditional manual planning. J. Hattangadi: Research Grant; Varian Medical Systems; K.L. Moore: Research Grant: Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

SU-E-T-97: An Analysis of Knowledge Based Planning for Stereotactic Body Radiation Therapy of the Spine

Purpose: Creating high quality SBRT treatment plans for the spine is often tedious and time consuming. In addition, the quality of treatment plans can vary greatly between treatment facilities due to inconsistencies in planning methods. This study investigates the performance of knowledge-based planning (KBP) for spine SBRT. Methods: Treatment plans were created for 28 spine SBRT patients. Each case was planned to meet strict dose objectives and guidelines. After physician and physicist approval, the plans were added to a custom model in a KBP system (RapidPlan, Varian Eclipse v13.5). The model was then trained to be able to predict estimated DVHs and provide starting objective functions for future patients based on both generated and manual objectives. To validate the model, ten additional spine SBRT cases were planned manually as well as using the model objectives. Plans were compared based on planning time and quality (ability to meet the plan objectives, including dose metrics and conformity). Results: The average dose to the spinal cord and the cord PRV differed between the validation and control plans by <0.25% demonstrating iso-toxicity. Six out of 10 validation plans met all dose objectives without the need for modifications, and overall, target dose coverage was increased by about 4.8%. If the validation plans did not meet the dose requirements initially, only 1–2 iterations of modifying the planning parameters were required before an acceptable plan was achieved. While manually created plans usually required 30 minutes to 3 hours to create, KBP can be used to create similar quality plans in 15–20 minutes. Conclusion: KBP for spinal tumors has shown to greatly decrease the amount of time required to achieve high quality treatment plans with minimal human intervention and could feasibly be used to standardize plan quality between institutions. Supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Knowledge-Based Manufacturing and Structural Design for a High Speed Civil Transport

The aerospace industry is currently addressing the problem of integrating manufacturing and design. To address the difficulties associated with using many conventional procedural techniques and algorithms, one feasible way to integrate the two concepts is with the development of an appropriate Knowledge-Based System (KBS). The authors present their reasons for selecting a KBS to integrate design and manufacturing. A methodology for an aircraft producibility assessment is proposed, utilizing a KBS for manufacturing process selection, that addresses both procedural and heuristic aspects of designing and manufacturing of a High Speed Civil Transport (HSCT) wing. A cost model is discussed that would allow system level trades utilizing information describing the material characteristics as well as the manufacturing process selections. Statements of future work conclude the paper.

Marx, William J.↗

Comparison of Planning Quality and Efficiency Between Conventional and Knowledge-based Algorithms in Nasopharyngeal Cancer Patients Using Intensity Modulated Radiation Therapy

Purpose: Intensity modulated radiation therapy (IMRT) is widely used to achieve a highly conformal dose and improve treatment outcome. However, plan quality and planning time are institute and planner dependent, and no standardized tool exists to recognize an optimal plan. RapidPlan, a knowledge-based algorithm, can generate constraints to assist optimization and produce high-quality IMRT plans. This report evaluated the quality and efficiency of using RapidPlan in nasopharyngeal carcinoma (NPC) IMRT planning. Methods and Materials: RapidPlan was configured using 79 radical IMRT plans for NPC; 20 consecutive NPC patients indicated for radical radiation therapy between October 2014 and May 2015 were then recruited to assess its performance. The ability of RapidPlan to produce acceptable plans was evaluated. For plans that could not achieve clinical acceptance, manual touch-up was performed. The IMRT plans produced without RapidPlan (manual plans) and with RapidPlan (RP-2 plans, including those with manual touch-up) were compared in terms of dosimetric quality and planning efficiency. Results: RapidPlan by itself could produce clinically acceptable plans for 9 of the 20 patients; manual touch-up increased the number of acceptable plans (RP-2 plans) to 19. The target dose coverage and conformity were very similar. No difference was found in the maximum dose to the brainstem and optic chiasm. RP-2 plans delivered a higher maximum dose to the spinal cord (46.4 Gy vs 43.9 Gy, P=.002) but a lower dose to the parotid (mean dose to right parotid, 37.3 Gy vs 45.4 Gy; left, 34.4 Gy vs 43.1 Gy; P<.001) and the right cochlea (mean dose, 48.6 Gy vs 52.6 Gy; P=.02). The total planning time for RP-2 plans was significantly less than that for manual plans (64 minutes vs 295 minutes, P<.001). Conclusions: This study shows that RapidPlan can significantly improve planning efficiency and produce quality IMRT plans for NPC patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Optimization of knowledge-based systems and expert system building tools

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Yasuda, Phyllis↗

Knowledge-based graphical interfaces for presenting technical information

Designing effective presentations of technical information is extremely difficult and time-consuming. Moreover, the combination of increasing task complexity and declining job skills makes the need for high-quality technical presentations especially urgent. We believe that this need can ultimately be met through the development of knowledge-based graphical interfaces that can design and present technical information. Since much material is most naturally communicated through pictures, our work has stressed the importance of well-designed graphics, concentrating on generating pictures and laying out displays containing them. We describe APEX, a testbed picture generation system that creates sequences of pictures that depict the performance of simple actions in a world of 3D objects. Our system supports rules for determining automatically the objects to be shown in a picture, the style and level of detail with which they should be rendered, the method by which the action itself should be indicated, and the picture's camera specification. We then describe work on GRIDS, an experimental display layout system that addresses some of the problems in designing displays containing these pictures, determining the position and size of the material to be presented.

Feiner, Steven↗

An approach to knowledge engineering to support knowledge-based simulation of payload ground processing at the Kennedy Space Center

Planning for processing payloads was always difficult and time-consuming. With the advent of Space Station Freedom and its capability to support a myriad of complex payloads, the planning to support this ground processing maze involves thousands of man-hours of often tedious data manipulation. To provide the capability to analyze various processing schedules, an object oriented knowledge-based simulation environment called the Advanced Generic Accomodations Planning Environment (AGAPE) is being developed. Having nearly completed the baseline system, the emphasis in this paper is directed toward rule definition and its relation to model development and simulation. The focus is specifically on the methodologies implemented during knowledge acquisition, analysis, and representation within the AGAPE rule structure. A model is provided to illustrate the concepts presented. The approach demonstrates a framework for AGAPE rule development to assist expert system development.

Mcmanus, Shawn↗