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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Searching Across the International Space Station Databases

Data access in the enterprise generally requires us to combine data from different sources and different formats. It is advantageous thus to focus on the intersection of the knowledge across sources and domains; keeping irrelevant knowledge around only serves to make the integration more unwieldy and more complicated than necessary. A context search over multiple domain is proposed in this paper to use context sensitive queries to support disciplined manipulation of domain knowledge resources. The objective of a context search is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The search supports formally the tasks of selecting, combining, extending, specializing, and modifying components from a diverse set of domains. This paper demonstrates a new paradigm in composition of information for enterprise applications. In particular, it discusses an approach to achieving data integration across multiple sources, in a manner that does not require heavy investment in database and middleware maintenance. This lean approach to integration leads to cost-effectiveness and scalability of data integration with an underlying schemaless object-relational database management system. This highly scalable, information on demand system framework, called NX-Search, which is an implementation of an information system built on NETMARK. NETMARK is a flexible, high-throughput open database integration framework for managing, storing, and searching unstructured or semi-structured arbitrary XML and HTML used widely at the National Aeronautics Space Administration (NASA) and industry.

Maluf, David A.↗
NASA NTRS1994

Using CLIPS in the domain of knowledge-based massively parallel programming

The Program Development Environment (PDE) is a tool for massively parallel programming of distributed-memory architectures. Adopting a knowledge-based approach, the PDE eliminates the complexity introduced by parallel hardware with distributed memory and offers complete transparency in respect of parallelism exploitation. The knowledge-based part of the PDE is realized in CLIPS. Its principal task is to find an efficient parallel realization of the application specified by the user in a comfortable, abstract, domain-oriented formalism. A large collection of fine-grain parallel algorithmic skeletons, represented as COOL objects in a tree hierarchy, contains the algorithmic knowledge. A hybrid knowledge base with rule modules and procedural parts, encoding expertise about application domain, parallel programming, software engineering, and parallel hardware, enables a high degree of automation in the software development process. In this paper, important aspects of the implementation of the PDE using CLIPS and COOL are shown, including the embedding of CLIPS with C++-based parts of the PDE. The appropriateness of the chosen approach and of the CLIPS language for knowledge-based software engineering are discussed.

Dvorak, Jiri J.↗
NASA NTRS1988

Automatic acquisition of domain and procedural knowledge

The design concept and performance of AKAS, an automated knowledge-acquisition system for the development of expert systems, are discussed. AKAS was developed using the FLES knowledge base for the electrical system of the B-737 aircraft and employs a 'learn by being told' strategy. The system comprises four basic modules, a system administration module, a natural-language concept-comprehension module, a knowledge-classification/extraction module, and a knowledge-incorporation module; details of the module architectures are explored.

Ferber, H. J.↗
NASA NTRS1990

Knowledge representation for commonality

Domain-specific knowledge necessary for commonality analysis falls into two general classes: commonality constraints and costing information. Notations for encoding such knowledge should be powerful and flexible and should appeal to the domain expert. The notations employed by the Commonality Analysis Problem Solver (CAPS) analysis tool are described. Examples are given to illustrate the main concepts.

Yeager, Dorian P.↗
NASA NTRS1992

Knowledge-intensive software design systems: Can too much knowledge be a burden?

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experiences building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

Keller, Richard M.↗
NASA NTRS1992

Knowledge-intensive software design systems: Can too much knowledge be a burden?

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experience in building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

Keller, Richard M.↗
NASA NTRS2001

Articulation Management for Intelligent Integration of Information

When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This heterogeneity problem can be eliminated by mediating the conflicts and managing the intersections of the domains. For interoperation and intelligent access to heterogeneous information, the focus is on the intersection of the knowledge, since intersection will define the required articulation rules. An algebra over domain has been proposed to use articulation rules to support disciplined manipulation of domain knowledge resources. The objective of a domain algebra is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The algebra supports formally the tasks of selecting, combining, extending, specializing, and modifying Components from a diverse set of domains. This paper presents a domain algebra and demonstrates the use of articulation rules to link declarative interfaces for Internet and enterprise applications. In particular, it discusses the articulation implementation as part of a production system capable of operating over the domain described by the IDL (interface description language) of objects registered in multiple CORBA servers.

Maluf, David A.↗
NASA NTRS2021

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗
NASA NTRS1992

The KASE approach to domain-specific software systems

Designing software systems, like all design activities, is a knowledge-intensive task. Several studies have found that the predominant cause of failures among system designers is lack of knowledge: knowledge about the application domain, knowledge about design schemes, knowledge about design processes, etc. The goal of domain-specific software design systems is to explicitly represent knowledge relevant to a class of applications and use it to partially or completely automate various aspects of the designing systems within that domain. The hope is that this would reduce the intellectual burden on the human designers and lead to more efficient software development. In this paper, we present a domain-specific system built on top of KASE, a knowledge-assisted software engineering environment being developed at the Stanford Knowledge Systems Laboratory. We introduce the main ideas underlying the construction of domain specific systems within KASE, illustrate the application of the idea in the synthesis of a system for tracking aircraft from radar signals, and discuss some of the issues in constructing domain-specific systems.

Bhansali, Sanjay↗
NASA NTRS1992

Description of research interests and current work related to automating software design

Enclosed is a list of selected and recent publications. Most of these publications concern applied research in the areas of software engineering and human-computer interaction. It is felt that domain-specific knowledge plays a major role in software development. Additionally, it is believed that improvements in the general software development process (e.g., object-oriented approaches) will have to be combined with the use of large domain-specific knowledge bases.

Kaindl, Hermann↗
NASA NTRS1992

Knowledge and regularity in planning

The field of planning has focused on several methods of using domain-specific knowledge. The three most common methods, use of search control, use of macro-operators, and analogy, are part of a continuum of techniques differing in the amount of reused plan information. This paper describes TALUS, a planner that exploits this continuum, and is used for comparing the relative utility of these methods. We present results showing how search control, macro-operators, and analogy are affected by domain regularity and the amount of stored knowledge.

Allen, John A.↗
NASA NTRS1980

Problem solving with uncertain knowledge

Systems capable of expert level performance are built. The system represents domain-specific knowledge such as knowledge about geology, medicine, etc., and enables a process in which it uses such knowledge in an understandable line of reasoning. The MYCIN system, one example of such a system, is used as illustration.

Buchanan, B.↗
NASA NTRS1990

Implementation of a frame-based representation in CLIPS

Knowledge representation is one of the major concerns in expert systems. The representation of domain-specific knowledge should agree with the nature of the domain entities and their use in the real world. For example, architectural applications deal with objects and entities such as spaces, walls, and windows. A natural way of representing these architectural entities is provided by frames. This research explores the potential of using the expert system shell CLIPS, developed by NASA, to implement a frame-based representation that can accommodate architectural knowledge. These frames are similar but quite different from the 'template' construct in version 4.3 of CLIPS. Templates support only the grouping of related information and the assignment of default values to template fields. In addition to these features frames provide other capabilities including definition of classes, inheritance between classes and subclasses, relation of objects of different classes with 'has-a', association of methods (demons) of different types (standard and user-defined) to fields (slots), and creation of new fields at run-time. This frame-based representation is implemented completely in CLIPS. No change to the source code is necessary.

Assal, Hisham↗
NASA NTRS1992

Model-based software design

Domain-specific knowledge is required to create specifications, generate code, and understand existing systems. Our approach to automating software design is based on instantiating an application domain model with industry-specific knowledge and then using that model to achieve the operational goals of specification elicitation and verification, reverse engineering, and code generation. Although many different specification models can be created from any particular domain model, each specification model is consistent and correct with respect to the domain model.

Iscoe, Neil↗
NASA NTRS1994

Automated analysis of complex data

We have examined some of the issues involved in automating exploratory data analysis, in particular the tradeoff between control and opportunism. We have proposed an opportunistic planning solution for this tradeoff, and we have implemented a prototype, Igor, to test the approach. Our experience in developing Igor was surprisingly smooth. In contrast to earlier versions that relied on rule representation, it was straightforward to increment Igor's knowledge base without causing the search space to explode. The planning representation appears to be both general and powerful, with high level strategic knowledge provided by goals and plans, and the hooks for domain-specific knowledge are provided by monitors and focusing heuristics.

Saintamant, Robert↗
NASA NTRS1993

A Knowledge-Based System Developer for aerospace applications

A prototype Knowledge-Based System Developer (KBSD) has been developed for aerospace applications by utilizing artificial intelligence technology. The KBSD directly acquires knowledge from domain experts through a graphical interface then builds expert systems from that knowledge. This raises the state of the art of knowledge acquisition/expert system technology to a new level by lessening the need for skilled knowledge engineers. The feasibility, applicability , and efficiency of the proposed concept was established, making a continuation which would develop the prototype to a full-scale general-purpose knowledge-based system developer justifiable. The KBSD has great commercial potential. It will provide a marketable software shell which alleviates the need for knowledge engineers and increase productivity in the workplace. The KBSD will therefore make knowledge-based systems available to a large portion of industry.

Shi, George Z.↗
DOE OSTI2025

LLMs for Mfg.—On the State of Large Language Models and Applications to Manufacturing

Additive Manufacturing (AM), referred to as 3D printing, has emerged as a key pillar of Industry 4.0 enabling layer-by-layer fabrication of intricate geometries from CAD models. In parallel, Large Language Models (LLMs), deep learning models for natural language generation trained on vast text corpora, have demonstrated unprecedented capabilities in understanding and generating human-like text. The convergence of these trends opens new opportunities at the intersection of AM and AI/ML, where LLMs can assist engineers and researchers in design, manufacture planning, and knowledge discovery. Recent academic work has begun to explore LLM applications in AM and adjacent fields, such as material science, mechanical engineering, and design for additive manufacturing. This exploration ranges from intelligent process planning to domain-specific knowledge retrieval. This survey provides a comprehensive review of current developments, focusing on peer-reviewed literature contributions that apply, adapt, and advance LLMs in general and domain-specific domains. We analyze state-of-the-art (SOTA) techniques, such as fine-tuning foundational models for specific domains, retrieval-augmented generation (RAG) pipelines, knowledge graph integration, and delve into the architectures and evaluation methods employed. The goal of this survey is to inform researchers and practitioners of the current capabilities and limitations of LLMs in general and in domain-specific applications, and to outline how these models are being tailored to meet the requirements of these applications.

36 MATERIALS SCIENCE↗