Search NASASearch

SEARCH · Search NASA

Results for “Natural language processing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

Semantic based man-machine interface for real-time communication

A flight expert system (FLES) was developed to assist pilots in monitoring, diagnosing and recovering from in-flight faults. To provide a communications interface between the flight crew and FLES, a natural language interface (NALI) was implemented. Input to NALI is processed by three processors: (1) the semantics parser; (2) the knowledge retriever; and (3) the response generator. First the semantic parser extracts meaningful words and phrases to generate an internal representation of the query. At this point, the semantic parser has the ability to map different input forms related to the same concept into the same internal representation. Then the knowledge retriever analyzes and stores the context of the query to aid in resolving ellipses and pronoun references. At the end of this process, a sequence of retrievel functions is created as a first step in generating the proper response. Finally, the response generator generates the natural language response to the query. The architecture of NALI was designed to process both temporal and nontemporal queries. The architecture and implementation of NALI are described.

Ali, M.

A knowledge based software engineering environment testbed

The Carnegie Group Incorporated and Boeing Computer Services Company are developing a testbed which will provide a framework for integrating conventional software engineering tools with Artifical Intelligence (AI) tools to promote automation and productivity. The emphasis is on the transfer of AI technology to the software development process. Experiments relate to AI issues such as scaling up, inference, and knowledge representation. In its first year, the project has created a model of software development by representing software activities; developed a module representation formalism to specify the behavior and structure of software objects; integrated the model with the formalism to identify shared representation and inheritance mechanisms; demonstrated object programming by writing procedures and applying them to software objects; used data-directed and goal-directed reasoning to, respectively, infer the cause of bugs and evaluate the appropriateness of a configuration; and demonstrated knowledge-based graphics. Future plans include introduction of knowledge-based systems for rapid prototyping or rescheduling; natural language interfaces; blackboard architecture; and distributed processing

Gill, C.

High level cognitive information processing in neural networks

Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

Barnden, John A.

Virtual Assistant for First Responders Using Natural Language Understanding and Optical Character Recognition

Commercial deep learning capabilities are available for many applications such as computer vision processing and intelligent chat bots. The Google Cloud Platform product Google Dialogflow provides lifelike conversational artificial intelligence (AI) using machine learning (ML) to generate natural conversations between computers and humans. This ML utilizes natural language understanding (NLU) to recognize a user’s intent and extracts key information into a form of entities. We have developed a user-friendly application through understanding the hazardous material database, first aid safety guidelines and observing the process of first responders who access this information in the field. We created the Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL) virtual assistant using Dialogflow1 and TensorFlow2 paired with EasyOCR.3 The chatbot supports first responders by providing voice interaction which helps limit additional steps such as browsing through multiple categories when searching for information. Using feedback from our field interviews, the voice interface has been developed to enable the first responder to focus on the immediate emergency. With less distractions, the first responder is able to engage the incident more effectively. The partial hands-free TruePAL chatbot assistant improves the accessibility to the correct guidance by an average of 1.9 seconds compared to the widely used application, NIH WISER, which requires full attention to operate. We combined this intelligent chatbot with a separate visual processing capability to produce hazardous signage analysis and generate the proper guidance for first responders. With the evolving functionality of AI tools, the use of virtual assistants in first responder technology will be an advancement, benefiting the safety of both first responders and civilians.

Chow, Edward

A new programming metaphor for image processing procedures

Most image processing systems, besides an Application Program Interface (API) which lets users write their own image processing programs, also feature a higher level of programmability. Traditionally, this is a command or macro language, which can be used to build large procedures (scripts) out of simple programs or commands. This approach, a legacy of the teletypewriter has serious drawbacks. A command language is clumsy when (and if! it attempts to utilize the capabilities of a multitasking or multiprocessor environment, it is but adequate for real-time data acquisition and processing, it has a fairly steep learning curve, and the user interface is very inefficient,. especially when compared to a graphical user interface (GUI) that systems running under Xll or Windows should otherwise be able to provide. ll these difficulties stem from one basic problem: a command language is not a natural metaphor for an image processing procedure. A more natural metaphor - an image processing factory is described in detail. A factory is a set of programs (applications) that execute separate operations on images, connected by pipes that carry data (images and parameters) between them. The programs function concurrently, processing images as they arrive along pipes, and querying the user for whatever other input they need. From the user's point of view, programming (constructing) factories is a lot like playing with LEGO blocks - much more intuitive than writing scripts. Focus is on some of the difficulties of implementing factory support, most notably the design of an appropriate API. It also shows that factories retain all the functionality of a command language (including loops and conditional branches), while suffering from none of the drawbacks outlined above. Other benefits of factory programming include self-tuning factories and the process of encapsulation, which lets a factory take the shape of a standard application both from the system and the user's point of view, and thus be used as a component of other factories. A bare-bones prototype of factory programming was implemented under the PcIPS image processing system, and a complete version (on a multitasking platform) is under development.

Smirnov, O. M.

Topic Modeling of NASA Space System Problem Reports: Research in Practice

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

Data Mining

The proposal entry processor: Telescience applications for Hubble Space Telescope science operations

The Proposal Entry Processor (PEP) System supports the submission, entry, technical evaluation review, selection and implementation of Hubble Space Telescope (HST) observing proposals. The PEP system is described concentrating on features which illustrate principles of telescience as applied to the HST. These principles are applicable to other observatories, both space and ground based. The PEP proposal forms allow a scientist to specify scientific objectives without becoming needlessly involved in implementation details. The Remote Proposal Submission System (RPSS) allows proposers to submit proposals electronically via Telenet, SPAN, and other networks. The RPSS performs syntax and sematic checks on proposals. The PEP uses a fourth generation database system to store proposal information and to allow general queries and reports. The Transformation subsystem uses an expert system written in OPS5 to cast a scientific description of an observing program into parameters used by the planning and scheduling system. The TACOS system is a natural language database which supports the proposal selection process. Technical evaluations for resource usage and duplicate science are performed using rulebased systems.

Jackson, Robert

KARL: A Knowledge-Assisted Retrieval Language. Presentation visuals

A collection of presentation visuals associated with the companion report entitled KARL: A Knowledge-Assisted Retrieval Language, is presented. Information is given on data retrieval, natural language database front ends, generic design objectives, processing capababilities and the query processing cycle.

Dominick, Wayne D.

A natural language query system for Hubble Space Telescope proposal selection

The proposal selection process for the Hubble Space Telescope is assisted by a robust and easy to use query program (TACOS). The system parses an English subset language sentence regardless of the order of the keyword phases, allowing the user a greater flexibility than a standard command query language. Capabilities for macro and procedure definition are also integrated. The system was designed for flexibility in both use and maintenance. In addition, TACOS can be applied to any knowledge domain that can be expressed in terms of a single reaction. The system was implemented mostly in Common LISP. The TACOS design is described in detail, with particular attention given to the implementation methods of sentence processing.

Hornick, Thomas

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Recent Advancements in spoken language processing technologies have enabled the development of reliable automation tools to assist air traffic control (ATC) operations. These advancements present a unique opportunity to strategically implement digital taxi instructions for aircraft movement on the ground. Digital taxi instructions issue taxiing procedures to pilots as textual or graphical instructions. There are several benefits of digital instructions, including a reduction in radio congestion, elimination of communication errors, and improved aircraft monitoring capabilities. Natural language understanding (NLU) models can extract digital taxi instructions from verbal instructions issued by air traffic controllers. This capability enables the implementation of a digital taxi communication framework with minimal changes to the existing air traffic controller operational environment. We explore a novel application for NLU: automatically generating digital taxi instructions from air traffic controller speech. We describe the development of an annotation scheme to represent (aircraft) ground traffic communications in the US National Airspace System (NAS).Our annotation scheme uses intent classification and slot filling to extract taxi instructions, enabling NLU models to leverage syntactic information. Several neural network models were trained to categorize the controller’s intent and label information relevant to his or her intent.Our research demonstrates that it is feasible to use NLU to automatically generate digitaltaxi instructions, suggesting that it is a powerful tool for the implementation of digital taxi communications.

Hillel Steinmetz

Bridging the Gap Between Requirements and Model Analysis : Evaluation on Ten Cyber-Physical Challenge Problems

Formal verfication and simulation are powerful tools to validate requirements against complex systems. [Problem] Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. [Principal idea] We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. [Contribution] We have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written in structured natural language. Our framework is built in the Formal Requirements Elicitation Tool (fret); we use fret's requirements language named fretish, and formalization of fretish requirements in temporal logics. Our proposed framework contributes the following features: 1) automatic extraction of Simulink model information and association of fretish requirements with target model signals and components; 2) translation of temporal logic formulas into synchronous dataflow cocospec specifications as well as Simulink monitors, to be used by verification tools; we establish correctness of our translation through extensive automated testing; 3) interpretation of counterexamples produced by verification tools back at requirements level. These features support a tight integration and feedback loop between high level requirements and their analysis. We demonstrate our approach on a major case study: the Ten Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems.

Mavridou, Anastasia

Formalizing and Analyzing Requirements with FRET

Formal verification and simulation are powerful tools to validate requirements against complex systems. Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. To this end, we have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written structured natural language.

Mavridou, Anastasia

A natural language interface for real-time dialogue in the flight domain

A flight expert system (FLES) is being developed to assist pilots in monitoring, diagnosisng and recovering from in-flight faults. To provide a communications interface between the flight crew and FLES, a natural language interface, has been implemented. Input to NALI is processed by three processors: (1) the semantic parser, (2) the knowledge retriever, and (3) the response generator. The architecture of NALI has been designed to process both temporal and nontemporal queries. Provisions have also been made to reduce the number of system modifications required for adapting NALI to other domains. This paper describes the architecture and implementation of NALI.

Ali, M.

Conversing with Computers

I/NET, Inc., is making the dream of natural human-computer conversation a practical reality. Through a combination of advanced artificial intelligence research and practical software design, I/NET has taken the complexity out of developing advanced, natural language interfaces. Conversational capabilities like pronoun resolution, anaphora and ellipsis processing, and dialog management that were once available only in the laboratory can now be brought to any application with any speech recognition system using I/NET s conversational engine middleware.

Source record

Integrating Micro-computers with a Centralized DBMS: ORACLE, SEED AND INGRES

Users of ADABAS, a relational-like data base management system (ADABAS) with its data base programming language (NATURAL) are acquiring microcomputers with hopes of solving their individual word processing, office automation, decision support, and simple data processing problems. As processor speeds, memory sizes, and disk storage capacities increase, individual departments begin to maintain "their own" data base on "their own" micro-computer. This situation can adversely affect several of the primary goals set for implementing a centralized DBMS. In order to avoid this potential problem, these micro-computers must be integrated with the centralized DBMS. An easy to use and flexible means for transferring logic data base files between the central data base machine and micro-computers must be provided. Some of the problems encounted in an effort to accomplish this integration and possible solutions are discussed.

Hoerger, J.

Intelligent interfaces for expert systems

Vital to the success of an expert system is an interface to the user which performs intelligently. A generic intelligent interface is being developed for expert systems. This intelligent interface was developed around the in-house developed Expert System for the Flight Analysis System (ESFAS). The Flight Analysis System (FAS) is comprised of 84 configuration controlled FORTRAN subroutines that are used in the preflight analysis of the space shuttle. In order to use FAS proficiently, a person must be knowledgeable in the areas of flight mechanics, the procedures involved in deploying a certain payload, and an overall understanding of the FAS. ESFAS, still in its developmental stage, is taking into account much of this knowledge. The generic intelligent interface involves the integration of a speech recognizer and synthesizer, a preparser, and a natural language parser to ESFAS. The speech recognizer being used is capable of recognizing 1000 words of connected speech. The natural language parser is a commercial software package which uses caseframe instantiation in processing the streams of words from the speech recognizer or the keyboard. The systems configuration is described along with capabilities and drawbacks.

Villarreal, James A.

Design of a Formation of Earth-Orbiting Satellites: The Auroral Lites Mission

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer, was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer is used for these analyses.

Hametz, Mark E.

Design of a Formation of Earth Orbiting Satellites: The Auroral Lites Mission

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has proposed a set of spacecraft flying in close formation around the Earth in order to measure the behavior of the auroras. The mission, named Auroral Lites, consists of four spacecraft configured to start at the vertices of a tetrahedron, flying over three mission phases. During the first phase, the distance between any two spacecraft in the formation is targeted at 10 kilometers (km). The second mission phase is much tighter, requiring satellite interrange spacing targeted at 500 meters. During the final phase of the mission, the formation opens to a nominal 100-km interrange spacing. In this paper, we present the strategy employed to initialize and model such a close formation during each of these phases. The analysis performed to date provides the design and characteristics of the reference orbit, the evolution of the formation during Phases I and II, and an estimate of the total mission delta-V budget. AI Solutions' mission design tool, FreeFlyer(R), was used to generate each of these analysis elements. The tool contains full force models, including both impulsive and finite duration maneuvers. Orbital maintenance can be fully modeled in the system using a flexible, natural scripting language built into the system. In addition, AI Solutions is in the process of adding formation extensions to the system facilitating mission analysis for formations like Auroral Lites. We will discuss how FreeFlyer(R) is used for these analyses.

Hametz, Mark E.