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At least 1,639 records · Page 91

The Cosmic Radiation Symphony: Soundtrack for a Journey to Mars

Space radiation (SR) is a constant threat to astronauts who journey away from the Earth’s protective magnetosphere. Galactic cosmic rays (GCR) are atomic nuclei from remnants of supernovae and are omnipresent in outer space. These ionized particles travel close to the speed of light and when they traverse biological material,they leave behind a path of damage. Another space radiation threat is from our sun when solar particle events (SPEs), or bursts of energetic protons,occur. Exposure to space radiation can lead to cancer, cardiovascular disease,immune dysfunction, and cognitive and behavioral decrements. Yet humans cannot see, smell, taste, hear,or feel radiation, making it less tangible than other health threats and much more difficult to describe.This is an important gap in risk communication that the Space Radiation Element is working to close within NASA’s Human Research Program. Music and art are powerful means of communicating human emotions and feelings and are effective and creative ways to convey other types of information. In this work, the sonification process was used to transcribe or translate the physical nature of the SR environment on a 3-year mission to Mars into sound, a format perceptible to the human ear. A visual representation for the journey was also developed so the audience can both hear and envision the chronic presence of GCR and the acute and large bursts of energy present in SPEs. Data for this project were derived from the Radiation Assessment Detector on the NASA Curiosity Rover during its outbound cruise to Mars and on the Martian surface, as well as from models of the space radiation environment behind spacecraft shielding. Our data-driven audiovisual composition was realized using custom programmed digital signal processing and graphic design in the programming languages Pure Data and Processing. The data sonification was contextualized in time and space by calculating and visualizing the location of the spacecraft in relation to the other planets during the Mars mission. The finished work is a unique and powerful means of communicating the presence and risk of space radiation, accessible by people of all ages and scientific backgrounds

Richard Snow↗

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented.

Lucas, S. H.↗

A Dynamo Simulation Generating Saturn-Like Small Magnetic Dipole Tilts

Abstract Among planetary dynamos, the magnetic field of Saturn stands out in its exceptional level of axisymmetry. One of its peculiar features is that the magnetic dipole mode is tilted with respect to the planetary rotation axis by only ≈0.007° or less. Numerical dynamo simulations performed in this context have had great difficulty in producing such small dipole tilt angles without introducing ad hoc ingredients such as a latitudinally varying heat flux pattern in the outer layers or stably stratified layers (SSLs). Here we present a numerical dynamo simulation that generates a highly axisymmetric dynamo with a dipole tilt of about ≈0.0008° on average. The model consists of a deep dynamo layer and an overlying low-conductivity layer but without any SSLs. We highlight a novel mechanism where strong differential rotation generated in the atmospheric layer penetrates into the dynamo region, helping to maintain a very small magnetic dipole tilt. Plain Language Summary Saturn's dipole-dominant magnetic field exhibits a very peculiar feature: the dipole component of the planetary magnetic field is tilted by less than ≈0.007° with respect to the planetary spin axis. Numerical simulations performed in this context suggest that if a spatial heat-flux variation is imposed, along with a stably stratified region, on top of an active dynamo layer, then small dipole tilt values can be realized. Here we present a model where extremely small dipole tilt values can be achieved without these ad hoc ingredients. Our simulations demonstrate that dynamo theory allows extremely small dipole tilt values in a relatively simple model configuration.

Rakesh Kumar Yadav↗

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach

Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia. A novel natural language processing approach is developed and validated to identify different stages of dementia based on automated transcription of digital voice recordings of subjects’ neuropsychological tests conducted by the Framingham Heart Study (n = 1084). Transcribed sentences from the test were encoded into quantitative data and several models were trained and tested using these data and the participants’ demographic characteristics. Average area under the curve (AUC) on the held-out test data reached 92.6%, 88.0%, and 74.4% for differentiating Normal cognition from Dementia, Normal or Mild Cognitive Impairment (MCI) from Dementia, and Normal from MCI, respectively. The proposed approach offers a fully automated identification of MCI and dementia based on a recorded neuropsychological test, providing an opportunity to develop a remote screening tool that could be adapted easily to any language.

neuropsychological↗

EHR-BERT: A BERT-based model for effective anomaly detection in electronic health records

Objective: Physicians and clinicians rely on data contained in electronic health records (EHRs), as recorded by health information technology (HIT), to make informed decisions about their patients. The reliability of HIT systems in this regard is critical to patient safety. Consequently, better tools are needed to monitor the performance of HIT systems for potential hazards that could compromise the collected EHRs, which in turn could affect patient safety. In this paper, we propose a new framework for detecting anomalies in EHRs using sequence of clinical events. This new framework, EHR-Bidirectional Encoder Representations from Transformers (BERT), is motivated by the gaps in the existing deep-learning related methods, including high false negatives, sub-optimal accuracy, higher computational cost, and the risk of information loss. EHR-BERT is an innovative framework rooted in the BERT architecture, meticulously tailored to navigate the hurdles in the contemporary BERT method; thus, enhancing anomaly detection in EHRs for healthcare applications.Methods: The EHR-BERT framework was designed using the Sequential Masked Token Prediction (SMTP) method. This approach treats EHRs as natural language sentences and iteratively masks input tokens during both training and prediction stages. This method facilitates the learning of EHR sequence patterns in both directions for each event and identifies anomalies based on deviations from the normal execution models trained on EHR sequences.Results: Extensive experiments on large EHR datasets across various medical domains demonstrate that EHR-BERT markedly improves upon existing models. It significantly reduces the number of false positives and enhances the detection rate, thus bolstering the reliability of anomaly detection in electronic health records. This improvement is attributed to the model’s ability to minimize information loss and maximize data utilization effectively.Conclusion: EHR-BERT showcases immense potential in decreasing medical errors related to anomalous clinical events, positioning itself as an indispensable asset for enhancing patient safety and the overall standard of healthcare services. The framework effectively overcomes the drawbacks of earlier models, making it a promising solution for healthcare professionals to ensure the reliability and quality of health data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Weather from 250 Miles Up: Visualizing Precipitation Satellite Data (and Other Weather Applications) Using CesiumJS

Geospatial weather visualization remains predominately a two-dimensional endeavor. Even popular advanced tools like the Nullschool Earth display 2-dimensional fields on a 3-dimensional globe. Yet much of the observational data and model output contains detailed three-dimensional fields. In 2014, NASA and JAXA (Japanese Space Agency) launched the Global Precipitation Measurement (GPM) satellite. Its two instruments, the Dual-frequency Precipitation Radar (DPR) and GPM Microwave Imager (GMI) observe much of the Earth's atmosphere between 65 degrees North Latitude and 65 degrees South Latitude. As part of the analysis and visualization tools developed by the Precipitation Processing System (PPS) Group at NASA Goddard, a series of CesiumJS [Using Cesium Markup Language (CZML), JavaScript (JS) and JavaScript Object Notation (JSON)] -based globe viewers have been developed to improve data acquisition decision making and to enhance scientific investigation of the satellite data. Other demos have also been built to illustrate the capabilities of CesiumJS in presenting atmospheric data, including model forecasts of hurricanes, observed surface radar data, and gridded analyses of global precipitation. This talk will present these websites and the various workflows used to convert binary satellite and model data into a form easily integrated with CesiumJS.

web applications↗

Autonomous Controls For Reactor Technologies (acorn)

ACORN (Autonomous Controls fOr Reactor techNologies) software utilizes data, obtained from an experimental test bed and/or simulation, to implement a control command for microreactor operation. Command examples include a change to the temperature profile, power profiles, heat fluxes, etc. The control command recommended by the code is derived based on future predicted states of a microreactor, allowing proactive optimal and autonomous microreactor operation. The software is written in Python languages. The current software supports autonomous temperature controls of heat pipe simulator and autonomous heat flux controls of a 37 heat pipe non-nuclear testbed simulator (or its surrogate models).

Lin, Linyu [Idaho National Laboratory (INL), Idaho↗

Environment parameters and basic functions for floating-point computation

A language-independent proposal for environment parameters and basic functions for floating-point computation is presented. Basic functions are proposed to analyze, synthesize, and scale floating-point numbers. The model provides a small set of parameters and a small set of axioms along with sharp measures of roundoff error. The parameters and functions can be used to write portable and robust codes that deal intimately with the floating-point representation. Subject to underflow and overflow constraints, a number can be scaled by a power of the floating-point radix inexpensively and without loss of precision. A specific representation for FORTRAN is included.

Brown, W. S.↗

Parallel processor engine model program

The Parallel Processor Engine Model Program is a generalized engineering tool intended to aid in the design of parallel processing real-time simulations of turbofan engines. It is written in the FORTRAN programming language and executes as a subset of the SOAPP simulation system. Input/output and execution control are provided by SOAPP; however, the analysis, emulation and simulation functions are completely self-contained. A framework in which a wide variety of parallel processing architectures could be evaluated and tools with which the parallel implementation of a real-time simulation technique could be assessed are provided.

Mclaughlin, P.↗

Sensing and perception research for space telerobotics at JPL

PIFLEX is a pipelined-image processor that can perform elaborate computations whose exact nature is not fixed in the hardware, and that can handle multiple images. A wire-wrapped prototype PIFEX module has been produced and debugged, using a version of the convolver composed of three custom VLSI chips (plus the line buffers). A printed circuit layout is being designed for use with a single-chip convolver, leading to production of a PIFEX with about 120 modules. A high-level language for programming PIFEX has been designed, and a compiler will be written for it. The camera calibration software has been completed and tested. Two more terms in the camera model, for lens distortion, probably will be added later. The acquisition and tracking system has been designed and most of it has been coded in Pascal for the MicroVAX-II. The feature tracker, motion stereo module and stereo matcher have executed successfully. The model matcher is still under development, and coding has begun on the tracking initializer. The object tracker was running on a different computer from the VAX, and preliminary runs on real images have been performed there. Once all modules are working, optimization and integration will begin. Finally, when a sufficiently large PIFEX is available, appropriate parts of acquisition and tracking, including much of the feature tracker, will be programmed into PIFEX, thus increasing the speed and robustness of the system.

Gennery, Donald B.↗

Qualitative models for space system engineering

The objectives of this project were: (1) to investigate the implications of qualitative modeling techniques for problems arising in the monitoring, diagnosis, and design of Space Station subsystems and procedures; (2) to identify the issues involved in using qualitative models to enhance and automate engineering functions. These issues include representing operational criteria, fault models, alternate ontologies, and modeling continuous signals at a functional level of description; and (3) to develop a prototype collection of qualitative models for fluid and thermal systems commonly found in Space Station subsystems. Potential applications of qualitative modeling to space-systems engineering, including the notion of intelligent computer-aided engineering are summarized. Emphasis is given to determining which systems of the proposed Space Station provide the most leverage for study, given the current state of the art. Progress on using qualitative models, including development of the molecular collection ontology for reasoning about fluids, the interaction of qualitative and quantitative knowledge in analyzing thermodynamic cycles, and an experiment on building a natural language interface to qualitative reasoning is reported. Finally, some recommendations are made for future research.

Forbus, Kenneth D.↗

Systems Architecture for Fully Autonomous Space Missions

The NASA Goddard Space Flight Center is working to develop a revolutionary new system architecture concept in support of fully autonomous missions. As part of GSFC's contribution to the New Millenium Program (NMP) Space Technology 7 Autonomy and on-Board Processing (ST7-A) Concept Definition Study, the system incorporates the latest commercial Internet and software development ideas and extends them into NASA ground and space segment architectures. The unique challenges facing the exploration of remote and inaccessible locales and the need to incorporate corresponding autonomy technologies within reasonable cost necessitate the re-thinking of traditional mission architectures. A measure of the resiliency of this architecture in its application to a broad range of future autonomy missions will depend on its effectiveness in leveraging from commercial tools developed for the personal computer and Internet markets. Specialized test stations and supporting software come to past as spacecraft take advantage of the extensive tools and research investments of billion-dollar commercial ventures. The projected improvements of the Internet and supporting infrastructure go hand-in-hand with market pressures that provide continuity in research. By taking advantage of consumer-oriented methods and processes, space-flight missions will continue to leverage on investments tailored to provide better services at reduced cost. The application of ground and space segment architectures each based on Local Area Networks (LAN), the use of personal computer-based operating systems, and the execution of activities and operations through a Wide Area Network (Internet) enable a revolution in spacecraft mission formulation, implementation, and flight operations. Hardware and software design, development, integration, test, and flight operations are all tied-in closely to a common thread that enables the smooth transitioning between program phases. The application of commercial software development techniques lays the foundation for delivery of product-oriented flight software modules and models. Software can then be readily applied to support the on-board autonomy required for mission self-management. An on-board intelligent system, based on advanced scripting languages, facilitates the mission autonomy required to offload ground system resources, and enables the spacecraft to manage itself safely through an efficient and effective process of reactive planning, science data acquisition, synthesis, and transmission to the ground. Autonomous ground systems in turn coordinate and support schedule contact times with the spacecraft. Specific autonomy software modules on-board include mission and science planners, instrument and subsystem control, and fault tolerance response software, all residing within a distributed computing environment supported through the flight LAN. Autonomy also requires the minimization of human intervention between users on the ground and the spacecraft, and hence calls for the elimination of the traditional operations control center as a funnel for data manipulation. Basic goal-oriented commands are sent directly from the user to the spacecraft through a distributed internet-based payload operations "center". The ensuing architecture calls for the use of spacecraft as point extensions on the Internet. This paper will detail the system architecture implementation chosen to enable cost-effective autonomous missions with applicability to a broad range of conditions. It will define the structure needed for implementation of such missions, including software and hardware infrastructures. The overall architecture is then laid out as a common thread in the mission life cycle from formulation through implementation and flight operations.

Esper, Jamie↗

An Agent-Based Interface to Terrestrial Ecological Forecasting

This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

Golden, Keith↗

Let’s speak FRETish

FRET (https://github.com/NASA-SW-VnV/fret [github.com]) is a framework for the elicitation, formalization and analysis of requirements. FRET allows its user to enter requirements in a structured natural language called FRETish. Requirements written in FRETish are assigned unambiguous semantics. FRET supports its users in understanding this semantics and repairing requirements if applicable, by utilizing a variety of forms for each requirement: natural language description, formal mathematical logics, diagrams, and interactive simulation. FRET exports requirements into forms that can be used by a variety of analysis tools, including state-of-the-art model checkers and runtime monitoring tools. The talk will cover some of the theory behind the framework, present case studies from the aerospace and robotics domains, as well as current work on extending FRET for specifying requirements for software that learns.

FRET↗

Particle Acceleration by Dense Impulsive Structures Moving in Ambient Magnetospheric Plasma. 3-D Hybrid Kinetic Modeling and MMS Observations

High resolution observations of dense plasma impulsive structures moving through an ambient background magnetospheric flows were captured by the Magnetospheric Multiscale mission. The observations show particle heating and acceleration, shock-like wave formation, and whistler wave excitation inside the interface between the dense impulsive plasma structures and the ambient plasma. A multiscale hybrid kinetic simulation provides an explanation of the observed wave-particle interactions with the assumption that the dense plasma structures may be represented by plasma clouds which are formed at the magnetopause layer due to reconnection processes. Plain Language Summary: Dense, impulsive plasma structures moving through a background plasma were captured by the NASA Magnetospheric Multiscale mission. The observations show that the dense structures can generate strong perturbations in the electromagnetic field and shock-like waves. Interactions between these electromagnetic waves and the particles results in particle acceleration. 3-D hybrid kinetic modeling (particle description for ions and fluid description for electrons) was used to investigate the plasma physics of the observed structures. It was assumed that the plasma clouds were formed by magnetic field reconnection inside the magnetopause, which is the interface between the solar wind particles and the cold low-density magnetospheric plasma. The work helps us understand the plasma environment at the interface between the Earth and solar wind, near planetary moons, within astrophysical explosions, and possibly at the interface between the solar wind and local interstellar medium.

A. S. Lipatov↗

Brahms Mobile Agents: Architecture and Field Tests

We have developed a model-based, distributed architecture that integrates diverse components in a system designed for lunar and planetary surface operations: an astronaut's space suit, cameras, rover/All-Terrain Vehicle (ATV), robotic assistant, other personnel in a local habitat, and a remote mission support team (with time delay). Software processes, called agents, implemented in the Brahms language, run on multiple, mobile platforms. These mobile agents interpret and transform available data to help people and robotic systems coordinate their actions to make operations more safe and efficient. The Brahms-based mobile agent architecture (MAA) uses a novel combination of agent types so the software agents may understand and facilitate communications between people and between system components. A state-of-the-art spoken dialogue interface is integrated with Brahms models, supporting a speech-driven field observation record and rover command system (e.g., return here later and bring this back to the habitat ). This combination of agents, rover, and model-based spoken dialogue interface constitutes a personal assistant. An important aspect of the methodology involves first simulating the entire system in Brahms, then configuring the agents into a run-time system.

Clancey, William J.↗

Automatic log analysis with NLP for the CMS workflow handling

The central Monte-Carlo production of the CMS experiment utilizes the WLCG infrastructure and manages daily thousands of tasks, each up to thousands of jobs. The distributed computing system is bound to sustain a certain rate of failures of various types, which are currently handled by computing operators a posteriori. Within the context of computing operations, and operation intelligence, we propose a Machine Learning technique to learn from the operators with a view to reduce the operational workload and delays. This work is in continuation of CMS work on operation intelligence to try and reach accurate predictions with Machine Learning. We present an approach to consider the log files of the workflows as regular text to leverage modern techniques from Natural Language Processing (NLP). In general, log files contain a substantial amount of text that is not human language. Therefore, different log parsing approaches are studied in order to map the log files’ words to high dimensional vectors. These vectors are then exploited as feature space to train a model that predicts the action that the operator has to take. This approach has the advantage that the information of the log files is extracted automatically and the format of the logs can be arbitrary. In this work the performance of the log file analysis with NLP is presented and compared to previous approaches.

Layer, Lukas↗

Operational procedure for computer program for design point characteristics of a compressed-air generator with through-flow combustor for V/STOL applications

The computer program described in this report calculates the design-point characteristics of a compressed-air generator for use in V/STOL applications such as systems with a tip-turbine-driven lift fan. The program computes the dimensions and mass, as well as the thermodynamic performance of a model air generator configuration which involves a straight through-flow combustor. Physical and thermodynamic characteristics of the air generator components are also given. The program was written in FORTRAN IV language. Provision has been made so that the program will accept input values in either SI units or U.S. customary units. Each air generator design-point calculation requires about 1.5 seconds of 7094 computer time for execution.

Krebs, R. P.↗