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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Flexible language constructs for large parallel programs

The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given.

Rosing, Matthew↗
NASA NTRS1993

A formal language for the specification and verification of synchronous and asynchronous circuits

A formal hardware description language for the intended application of verifiable asynchronous communication is described. The language is developed within the logical framework of the Nqthm system of Boyer and Moore and is based on the event-driven behavioral model of VHDL, including the basic VHDL signal propagation mechanisms, the notion of simulation deltas, and the VHDL simulation cycle. A core subset of the language corresponds closely with a subset of VHDL and is adequate for the realistic gate-level modeling of both combinational and sequential circuits. Various extensions to this subset provide means for convenient expression of behavioral circuit specifications.

Russinoff, David M.↗
NASA NTRS1994

SCOSII OL: A dedicated language for mission operations

The Spacecraft Control and Operations System 2 (SCOSII) is the new generation of Mission Control Systems (MCS) to be used at ESOC. The system is generic because it offers a collection of standard functions configured through a database upon which a dedicated MCS is established for a given mission. An integral component of SCOSII is the support of a dedicated Operations Language (OL). The spacecraft operation engineers edit, test, validate, and install OL scripts as part of the configuration of the system with, e.g., expressions for computing derived parameters and procedures for performing flight operations, all without involvement of software support engineers. A layered approach has been adopted for the implementation centered around the explicit representation of a data model. The data model is object-oriented defining the structure of the objects in terms of attributes (data) and services (functions) which can be accessed by the OL. SCOSII supports the creation of a mission model. System elements as, e.g., a gyro are explicit, as are the attributes which described them and the services they provide. The data model driven approach makes it possible to take immediate advantage of this higher-level of abstraction, without requiring expansion of the language. This article describes the background and context leading to the OL, concepts, language facilities, implementation, status and conclusions found so far.

Baldi, Andrea↗
NASA NTRS1997

Opus: A Coordination Language for Multidisciplinary Applications

Data parallel languages, such as High Performance fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.

Chapman, Barbara↗
NASA NTRS1998

Instrument Remote Control via the Astronomical Instrument Markup Language

The Instrument Remote Control (IRC) project ongoing at NASA's Goddard Space Flight Center's (GSFC) Information Systems Center (ISC) supports NASA's mission by defining an adaptive intranet-based framework that provides robust interactive and distributed control and monitoring of remote instruments. An astronomical IRC architecture that combines the platform-independent processing capabilities of Java with the power of Extensible Markup Language (XML) to express hierarchical data in an equally platform-independent, as well as human readable manner, has been developed. This architecture is implemented using a variety of XML support tools and Application Programming Interfaces (API) written in Java. IRC will enable trusted astronomers from around the world to easily access infrared instruments (e.g., telescopes, cameras, and spectrometers) located in remote, inhospitable environments, such as the South Pole, a high Chilean mountaintop, or an airborne observatory aboard a Boeing 747. Using IRC's frameworks, an astronomer or other scientist can easily define the type of onboard instrument, control the instrument remotely, and return monitoring data all through the intranet. The Astronomical Instrument Markup Language (AIML) is the first implementation of the more general Instrument Markup Language (IML). The key aspects of our approach to instrument description and control applies to many domains, from medical instruments to machine assembly lines. The concepts behind AIML apply equally well to the description and control of instruments in general. IRC enables us to apply our techniques to several instruments, preferably from different observatories.

Sall, Ken↗
NASA NTRS1998

An Interpreted Language and System for the Visualization of Unstructured Meshes

We present an interpreted language and system supporting the visualization of unstructured meshes and the manipulation of shapes defined in terms of mesh subsets. The language features primitives inspired by geometric modeling, mathematical morphology and algebraic topology. The adaptation of the topology ideas to an interpreted environment, along with support for programming constructs such, as user function definition, provide a flexible system for analyzing a mesh and for calculating with shapes defined in terms of the mesh. We present results demonstrating some of the capabilities of the language, based on an implementation called the Shape Calculator, for tetrahedral meshes in R^3.

Moran, Patrick J.↗
NASA NTRS2002

DPADL: An Action Language for Data Processing Domains

This paper presents DPADL (Data Processing Action Description Language), a language for describing planning domains that involve data processing. DPADL is a declarative object-oriented language that supports constraints and embedded Java code, object creation and copying, explicit inputs and outputs for actions, and metadata descriptions of existing and desired data. DPADL is supported by the IMAGEbot system, which will provide automation for an ecosystem forecasting system called TOPS.

Golden, Keith↗
NASA NTRS2005

Comparison of Grammar-Based and Statistical Language Models Trained on the Same Data

This paper presents a methodologically sound comparison of the performance of grammar-based (GLM) and statistical-based (SLM) recognizer architectures using data from the Clarissa procedure navigator domain. The Regulus open source packages make this possible with a method for constructing a grammar-based language model by training on a corpus. We construct grammar-based and statistical language models from the same corpus for comparison, and find that the grammar-based language models provide better performance in this domain. The best SLM version has a semantic error rate of 9.6%, while the best GLM version has an error rate of 6.0%. Part of this advantage is accounted for by the superior WER and Sentence Error Rate (SER) of the GLM (WER 7.42% versus 6.27%, and SER 12.41% versus 9.79%). The rest is most likely accounted for by the fact that the GLM architecture is able to use logical-form-based features, which permit tighter integration of recognition and semantic interpretation.

Hockey, Beth Ann↗
NASA NTRS2005

Applying Standard Interfaces to a Process-Control Language

A method of applying open-operating-system standard interfaces to the NASA User Interface Language (UIL) has been devised. UIL is a computing language that can be used in monitoring and controlling automated processes: for example, the Timeliner computer program, written in UIL, is a general-purpose software system for monitoring and controlling sequences of automated tasks in a target system. In providing the major elements of connectivity between UIL and the target system, the present method offers advantages over the prior method. Most notably, unlike in the prior method, the software description of the target system can be made independent of the applicable compiler software and need not be linked to the applicable executable compiler image. Also unlike in the prior method, it is not necessary to recompile the source code and relink the source code to a new executable compiler image. Abstraction of the description of the target system to a data file can be defined easily, with intuitive syntax, and knowledge of the source-code language is not needed for the definition.

Berthold, Richard T.↗
NASA NTRS2005

Task Description Language

Task Description Language (TDL) is an extension of the C++ programming language that enables programmers to quickly and easily write complex, concurrent computer programs for controlling real-time autonomous systems, including robots and spacecraft. TDL is based on earlier work (circa 1984 through 1989) on the Task Control Architecture (TCA). TDL provides syntactic support for hierarchical task-level control functions, including task decomposition, synchronization, execution monitoring, and exception handling. A Java-language-based compiler transforms TDL programs into pure C++ code that includes calls to a platform-independent task-control-management (TCM) library. TDL has been used to control and coordinate multiple heterogeneous robots in projects sponsored by NASA and the Defense Advanced Research Projects Agency (DARPA). It has also been used in Brazil to control an autonomous airship and in Canada to control a robotic manipulator.

Simmons, Reid↗
NASA NTRS2013

Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

This paper describes the core framework used to implement a Goal-Function Tree (GFT) based systems engineering process using the Systems Modeling Language. It defines a set of principles built upon by the theoretical approach described in the InfoTech 2013 ISHM paper titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management" presented by Dr. Stephen B. Johnson. Using the SysML language, the principles in this paper describe the expansion of the SysML language as a baseline in order to: hierarchically describe a system, describe that system functionally within success space, and allocate detection mechanisms to success functions for system protection.

Breckenridge, Jonathan T.↗
NASA NTRS2018

Trajectory Specification Language for Air Traffic Control

Trajectory Specification is a method of specifying aircraft trajectories with tolerances such that the position at any instant in time is constrained to a precisely defined bounding space. The bounding space at any instant in time is defined by tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and are based on the aircraft navigation capabilities and the traffic situation. This paper proposes a standard Trajectory Specification Language (TSL) based on the Extensible Markup Language (XML) to represent these specifications and to communicate them by datalink. The language can be used to downlink trajectory requests from air to ground and to uplink trajectory assignments from ground to air. The XML format can be converted to binary for operational use, if necessary, using Efficient XML Interchange (EXI) or Abstract Syntax Notation (ASN.1).

XM↗
NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗
NASA NTRS2020

Julia Language 1.1 Ephemeris Reader and Gravitational Modeling Program for Solar System Bodies

This paper analyzes the advancements to the Julia Language 1.1 Ephemeris and Physical constants Reader including the addition of gravitational modeling. Originally written in MATLAB, this Julia Language program is intended to be used in for trajectory design. Written in an open-source coding language, this ephemeris reader can output the state of planetary bodies including asteroids as well as other constants such as gravitational parameters. Two primary methods were chosen to calculate the gravitational potentials which include polyhedral modeling and spherical harmonics.

Gray, Brennan↗
NASA NTRS2021

A Short Glossary of Inclusive Language

Words matter—that old adage that many of us may have heard as children, Sticks and stones may break my bones, but words will never hurt me, is a harmful fallacy. In reality, the language we use has tremendous power to alienate, exclude, deride, humiliate, and wound. On the other hand, thoughtful use of language can signal openness, inclusivity, admiration, and celebration, or simply be an expression of empathy and care for our fellow humans. As part of The Oceanography Society (TOS) Justice, Equity, Diversity, and Inclusion Committee’s series of columns in Oceanography, here we provide a glossary of terms that are often used while discussing topics such as race, ethnicity, gender, sexual orientation, and gender identity. It should be explicitly stated that this list is neither definitive nor exhaustive. Indeed, the terms included here are likely heavily influenced by the authors’ own lived experiences and the lenses through which we see the world. Language is a living entity, a fluid social construct subject to rapid changes and overlaid with regional nuances. Indeed, what may be accurate and acceptable terminology for one person may be entirely unacceptable for another. Keeping this in mind, the following glossary is an attempt to group together some of the acronyms and phrases that are most commonly used today in social justice studies and bodies of work and that may have particular relevance to our community of ocean-related scientists, technologists, and stakeholders. We have borrowed heavily from a wide range of excellent existing scholarship and activism and have cited all sources used. We encourage the reader to follow the links to these multimedia resources and, perhaps, use them as teaching and discussion materials with your students, colleagues, and mentees. Finally, it is our hope that this glossary, along with the links provided to more comprehensive definitions and discussions, helps to define terms that you may have heard used, but not understood, and that it will serve to remind us of the power of the words we use in our everyday professional and personal lives. We begin by defining the very words that form the name of our committee: Justice, Equity, Diversity, and Inclusion (JEDI)

Susanne E. Craig↗
NASA NTRS2024

Hierarchical Semantic Frames for Grounding Language in Robot Control Primitives

As robots become increasingly present in human environments, we need robots to be intuitively commanded by and effectively communicate with humans. In particular, non-expert users should be able to communicate task goals with robots. Language emerges as a logical mode of interaction due to its ubiquity in human environments and, more importantly, as the way humans naturally express tasks. Natural language commands present challenges in that robots must reason over ambiguous language probabilistically and reason over commands they may not be able to execute. We present hierarchical semantic frames , which ground commands in robot control primitives through hierarchies that construct high-level commands from lower-level commands. We demonstrate that hierarchical semantic frames allow robots to understand and execute a variety of commands, such as those involving multiple verb meanings, command variations, and compound nouns. The robot quickly processes hierarchical semantic frames and accurately grounds and executes the commanded tasks, demonstrating the power of hierarchical semantic frames for allowing users to intuitively interact with robots.

Emily Sheetz↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗