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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 19 records

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NASA NTRS2001

Report on Automated Semantic Analysis of Scientific and Engineering Codes

The loss of the Mars Climate Orbiter due to a software error reveals what insiders know: software development is difficult and risky because, in part, current practices do not readily handle the complex details of software. Yet, for scientific software development the MCO mishap represents the tip of the iceberg; few errors are so public, and many errors are avoided with a combination of expertise, care, and testing during development and modification. Further, this effort consumes valuable time and resources even when hardware costs and execution time continually decrease. Software development could use better tools! This lack of tools has motivated the semantic analysis work explained in this report. However, this work has a distinguishing emphasis; the tool focuses on automated recognition of the fundamental mathematical and physical meaning of scientific code. Further, its comprehension is measured by quantitatively evaluating overall recognition with practical codes. This emphasis is necessary if software errors-like the MCO error-are to be quickly and inexpensively avoided in the future. This report evaluates the progress made with this problem. It presents recommendations, describes the approach, the tool's status, the challenges, related research, and a development strategy.

Stewart. Maark E. M.↗

NASA NTRS1998

A Semantic Analysis Method for Scientific and Engineering Code

This paper develops a procedure to statically analyze aspects of the meaning or semantics of scientific and engineering code. The analysis involves adding semantic declarations to a user's code and parsing this semantic knowledge with the original code using multiple expert parsers. These semantic parsers are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. In practice, a user would submit code with semantic declarations of primitive variables to the analysis procedure, and its semantic parsers would automatically recognize and document some static, semantic concepts and locate some program semantic errors. A prototype implementation of this analysis procedure is demonstrated. Further, the relationship between the fundamental algebraic manipulations of equations and the parsing of expressions is explained. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Stewart, Mark E. M.↗

NASA NTRS1998

An Experiment in Scientific Code Semantic Analysis

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, distributed expert parsers. These semantic parser are designed to recognize formulae in different disciplines including physical and mathematical formulae and geometrical position in a numerical scheme. The parsers will automatically recognize and document some static, semantic concepts and locate some program semantic errors. Results are shown for a subroutine test case and a collection of combustion code routines. This ability to locate some semantic errors and document semantic concepts in scientific and engineering code should reduce the time, risk, and effort of developing and using these codes.

Stewart, Mark E. M.↗

NASA NTRS2000

Progress in The Semantic Analysis of Scientific Code

This paper concerns a procedure that analyzes aspects of the meaning or semantics of scientific and engineering code. This procedure involves taking a user's existing code, adding semantic declarations for some primitive variables, and parsing this annotated code using multiple, independent expert parsers. These semantic parsers encode domain knowledge and recognize formulae in different disciplines including physics, numerical methods, mathematics, and geometry. The parsers will automatically recognize and document some static, semantic concepts and help locate some program semantic errors. These techniques may apply to a wider range of scientific codes. If so, the techniques could reduce the time, risk, and effort required to develop and modify scientific codes.

Stewart, Mark↗

NASA NTRS2005

Semantic Analysis of Email Using Domain Ontologies and WordNet

The problem of capturing and accessing knowledge in paper form has been supplanted by a problem of providing structure to vast amounts of electronic information. Systems that can construct semantic links for natural language documents like email messages automatically will be a crucial element of semantic email tools. We have designed an information extraction process that can leverage the knowledge already contained in an existing semantic web, recognizing references in email to existing nodes in a network of ontology instances by using linguistic knowledge and knowledge of the structure of the semantic web. We developed a heuristic score that uses several forms of evidence to detect references in email to existing nodes in the Semanticorganizer repository's network. While these scores cannot directly support automated probabilistic inference, they can be used to rank nodes by relevance and link those deemed most relevant to email messages.

Berrios, Daniel C.↗

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 NTRS1982

Multilevel semantic analysis and problem-solving in the flight-domain

The use of knowledge-base architecture and planning control; mechanisms to perform an intelligent monitoring task in the flight domain is addressed. The route level, the trajectory level, and parts of the aerodynamics level are demonstrated. Hierarchical planning and monitoring conceptual levels, functional-directed mechanism rationalization, and using deep-level mechanism models for diagnoses of dependent failures are discussed.

Chien, R. T.↗

NASA NTRS1977

A survey of compiler development aids

A theoretical background was established for the compilation process by dividing it into five phases and explaining the concepts and algorithms that underpin each. The five selected phases were lexical analysis, syntax analysis, semantic analysis, optimization, and code generation. Graph theoretical optimization techniques were presented, and approaches to code generation were described for both one-pass and multipass compilation environments. Following the initial tutorial sections, more than 20 tools that were developed to aid in the process of writing compilers were surveyed. Eight of the more recent compiler development aids were selected for special attention - SIMCMP/STAGE2, LANG-PAK, COGENT, XPL, AED, CWIC, LIS, and JOCIT. The impact of compiler development aids were assessed some of their shortcomings and some of the areas of research currently in progress were inspected.

Buckles, B. P.↗

NASA NTRS2009

Semantic Theme Analysis of Pilot Incident Reports

Pilots report accidents or incidents during take-off, on flight and landing to airline authorities and Federal aviation authority as well. The description of pilot reports for an incident contains technical terms related to Flight instruments and operations. Normal text mining approaches collect keywords from text documents and relate them among documents that are stored in database. Present approach will extract specific theme analysis of incident reports and semantically relate hierarchy of terms assigning weights of themes. Once the theme extraction has been performed for a given document, a unique key can be assigned to that document to cross linking the documents. Semantic linking will be used to categorize the documents based on specific rules that can help an end-user to analyze certain types of accidents. This presentation outlines the architecture of text mining for pilot incident reports for autonomous categorization of pilot incident reports using semantic theme analysis.

Thirumalainambi, Rajkumar↗

NASA NTRSDate not supplied

Formal Methods in the Development of Highly Assured Software for Unmanned Aircraft Systems

In traditional software development methodologies, operational and functional requirements of systems are often specified in structured natural language notations. These restricted notations provide good documentation support, but only provide limited support for semantic analysis. These notations are generally not rich enough to unambiguously specify the requirements of safety-critical systems that, for example, involve complex numerical computations or that interact with the physical environment. Examples of these safety-critical systems are autonomous vehicles such as unmanned aircraft systems. This talk advocates the use of expressive formal logics, such as higher-order logic, to specify the operational and functional requirement of unmanned systems and to prove the correctness of these requirements. Semantic analysis of requirements written in higher-order logic is supported through the use of interactive theorem provers. Formal models serve as ideal reference implementations of functional requirements. Hence, formal logics enable software validation techniques where software implementations can be checked against functional requirements in a mechanical way. The Formal Methods group in the Safety-Critical Avionics Systems Branch at NASA Langley Research Center has conducted research on the development and application of formal verification techniques to safety-critical applications of interest to NASA for more than 30 years. This talk illustrates the use of formal methods in the development of highly-assured autonomous unmanned aircraft systems.

Formal Methods↗

NASA NTRS2018

Trusted Communication: Utilizing Speech Communication to Enhance Human-Machine Teaming Success

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such an integration requires humans to work closely with autonomous systems, forming teams. Our hypothesis is that a team composed of both humans and autonomous systems will operate better than either entity alone. We have existing procedures for certifying pilots to operate in the national airspace and are currently working on methods for validating the function of autonomous systems, however we have no method in place for assessing the interaction of these two disparate systems. Communication is one avenue. This paper will examine the use of language as a metric for ascertaining human-machine teaming effectiveness. A proof-of-concept of the application of two communication-based analysis techniques, Linguistic Inquiry and Word Count (LIWC) and Latent Semantic Analysis (LSA), for the prediction of success in human/chatbot teaming was conducted. By running these analyses over data from the 2014 and 2015 Loebner Prize competitions of human/chatbot teaming, numerical scores were obtained that can be associated with scores provided by human judges during the competition. Correlating their LIWC and LSA data with the scores provided by the judges, and using linear regression over this correlation, formulae were obtained that predict the score of human/chatbot interaction. These formulae were tested over the 2013 Loebner Prize transcripts, determining that, though there was strong correlation between predicted and actual scores, the predictive success of this method was not strong. However, with specialized topic spaces and lexica, as well as larger data sets, the predictive power of these metrics will improve. Given the importance of providing metrics for human-machine system team success and given the promise shown by the communication-basedLIWCand LSAmethods, continuing research in this area is necessary. After examining the potential for using communication and spoken language as a metric for the success of human/autonomous system teaming, this paper then examines aspects inherent to communication systems that may contribute to unreliability and reduced trust. Modern natural language processing tools rely on deep learning algorithms to create language rules that produce accurate results, but these rules are uninterpretable. The resulting blackbox system lacks transparency necessary for full validation and complete trust. Additionally, speech-based interfaces pose other difficulties to developing coordinated teamwork between humans and autonomous systems. Human communication is infrequently limited to speech only, instead usually relying on a combination of verbal, gestural, and general body language communication. Reducing an analysis of team effectiveness to a study of spoken language alone is problematic as it leaves these other equally important forms of communication out. This paper will examine these problems and the general deficiencies in speech-based metrics for human-machine teaming.

E L Meszaros↗

NASA NTRS1982

Automatic photointerpretation via texture and morphology analysis

Computer-based techniques for automatic photointerpretation based upon information derived from texture and morphology analysis of images are discussed. By automatic photointerpretation, is meant the determination of semantic descriptions of the content of the images by computer. To perform semantic analysis of morphology, a heirarchical structure of knowledge representation was developed. The simplest elements in a morphology are strokes, which are used to form alphabets. The alphabets are the elements for generating words, which are used to describe the function or property of an object or a region. The words are the elements for constructing sentences, which are used for semantic description of the content of the image. Photointerpretation based upon morphology is then augmented by textural information. Textural analysis is performed using a pixel-vector approach.

Tou, J. T.↗

NASA NTRS2012

An Ontology for State Analysis: Formalizing the Mapping to SysML

State Analysis is a methodology developed over the last decade for architecting, designing and documenting complex control systems. Although it was originally conceived for designing robotic spacecraft, recent applications include the design of control systems for large ground-based telescopes. The European Southern Observatory (ESO) began a project to design the European Extremely Large Telescope (E-ELT), which will require coordinated control of over a thousand articulated mirror segments. The designers are using State Analysis as a methodology and the Systems Modeling Language (SysML) as a modeling and documentation language in this task. To effectively apply the State Analysis methodology in this context it became necessary to provide ontological definitions of the concepts and relations in State Analysis and greater flexibility through a mapping of State Analysis into a practical extension of SysML. The ontology provides the formal basis for verifying compliance with State Analysis semantics including architectural constraints. The SysML extension provides the practical basis for applying the State Analysis methodology with SysML tools. This paper will discuss the method used to develop these formalisms (the ontology), the formalisms themselves, the mapping to SysML and approach to using these formalisms to specify a control system and enforce architectural constraints in a SysML model.

Wagner, David A.↗

DOE OSTI2024

PhysBERT: A text embedding model for physics scientific literature

The specialized language and complex concepts in physics pose significant challenges for information extraction through Natural Language Processing (NLP). Central to effective NLP applications is the text embedding model, which converts text into dense vector representations for efficient information retrieval and semantic analysis. In this work, we introduce PhysBERT, the first physics-specific text embedding model. Pre-trained on a curated corpus of 1.2 × 106 arXiv physics papers and fine-tuned with supervised data, PhysBERT outperforms leading general-purpose models on physics-specific tasks, including the effectiveness in fine-tuning for specific physics subdomains.

Hellert, Thorsten (ORCID:0000000227970926)↗

NASA NTRS1976

HAL/S-FC and HAL/S-360 compiler system program description

The compiler is a large multi-phase design and can be broken into four phases: Phase 1 inputs the source language and does a syntactic and semantic analysis generating the source listing, a file of instructions in an internal format (HALMAT) and a collection of tables to be used in subsequent phases. Phase 1.5 massages the code produced by Phase 1, performing machine independent optimization. Phase 2 inputs the HALMAT produced by Phase 1 and outputs machine language object modules in a form suitable for the OS-360 or FCOS linkage editor. Phase 3 produces the SDF tables. The four phases described are written in XPL, a language specifically designed for compiler implementation. In addition to the compiler, there is a large library containing all the routines that can be explicitly called by the source language programmer plus a large collection of routines for implementing various facilities of the language.

Source record↗

NASA NTRS1985

PCG: A prototype incremental compilation facility for the SAGA environment, appendix F

A programming environment supports the activity of developing and maintaining software. New environments provide language-oriented tools such as syntax-directed editors, whose usefulness is enhanced because they embody language-specific knowledge. When syntactic and semantic analysis occur early in the cycle of program production, that is, during editing, the use of a standard compiler is inefficient, for it must re-analyze the program before generating code. Likewise, it is inefficient to recompile an entire file, when the editor can determine that only portions of it need updating. The pcg, or Pascal code generation, facility described here generates code directly from the syntax trees produced by the SAGA syntax directed Pascal editor. By preserving the intermediate code used in the previous compilation, it can limit recompilation to the routines actually modified by editing.

Kimball, Joseph John↗

NASA NTRS2006

Open Microphone Speech Understanding: Correct Discrimination Of In Domain Speech

An ideal spoken dialogue system listens continually and determines which utterances were spoken to it, understands them and responds appropriately while ignoring the rest This paper outlines a simple method for achieving this goal which involves trading a slightly higher false rejection rate of in domain utterances for a higher correct rejection rate of Out of Domain (OOD) utterances. The system recognizes semantic entities specified by a unification grammar which is specialized by Explanation Based Learning (EBL). so that it only uses rules which are seen in the training data. The resulting grammar has probabilities assigned to each construct so that overgeneralizations are not a problem. The resulting system only recognizes utterances which reduce to a valid logical form which has meaning for the system and rejects the rest. A class N-gram grammar has been trained on the same training data. This system gives good recognition performance and offers good Out of Domain discrimination when combined with the semantic analysis. The resulting systems were tested on a Space Station Robot Dialogue Speech Database and a subset of the OGI conversational speech database. Both systems run in real time on a PC laptop and the present performance allows continuous listening with an acceptably low false acceptance rate. This type of open microphone system has been used in the Clarissa procedure reading and navigation spoken dialogue system which is being tested on the International Space Station.

Hieronymus, James↗

NASA NTRS2006

To the North Coast of Devon: Collaborative Navigation While Exploring Unfamiliar Terrain

Navigation-knowing where one is and finding a safe route-is a fundamental aspect of all exploration. In unfamiliar terrain, one may use maps and instruments such as a compass or binoculars to assist, and people often collaborate in finding their way. This paper analyzes a group of people driving a humvee from a base camp to the north coast of Devon Island in the High Canadian Arctic. A complete audio recording and video during most stops allows a quantitative and semantic analysis of the conversations when the team stopped to take bearings and replan a route. Over a period of 2 hours, the humvee stopped 20 times, with an average duration of 3.15 min/pause and 3.85 min moving forward. The team failed to reach its goal due to difficult terrain causing mechanical problems. The analysis attempts to explain these facts by considering a variety of complicating factors, especially the navigation problem of relating maps and the world to locate the humvee and to plan a route. The analysis reveals patterns in topic structure and turn-taking, supporting the view that the collaboration was efficient, but the tools and information were inadequate for the task. This work is relevant for planning and training for planetary surface missions, as well as developing computer systems that could aid navigation.

Clancey, William J.↗