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At least 631 records · Page 35

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗

Pattern Identification - A Foundation for Research in the Emphasis of Design Patterns in Systems Engineering and Knowledge Capture

Pattern Language describes the morphology and functionality of a system in the absence of design particulars. Harnessing this capability will provide the Systems Engineering discipline a means of managing the development of increasingly complex systems with increasingly distributed design teams while capturing and retaining knowledge for future generations. Pattern Language is a syntax for describing, and structurally relating, design patterns. Design patterns contextually describe the application of domain knowledge in the engineered solution to the force balance problem. The parallels between pattern recognition and application, as a fundamental stage of human learning, and pattern observation within a complex system, suggests pattern language may be a valuable tool in the capture and dissemination of knowledge. Pattern application has enjoyed considerable study over the last several decades, however much of this work has focused on the replication of design particulars. This work returns to the roots of Pattern Language and explores the utility of patterns as an architectural description and guide, and knowledge capture method, for complex system development beginning with the identification of a time proven design pattern.

Russell, Samuel P.↗

Articulation Management for Intelligent Integration of Information

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

Maluf, David A.↗

Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA

Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm (millimeters) for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6-8 mm per day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm per day, METRIC 6 mm per day, and VISW 8 mm per day. For alfalfa, the ET values from TSEB were 8.0 mm per day, METRIC 5 mm per day, and VISW 6 mm per day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from minus 10 percent to plus 18 percent, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators - potential ET (ET (sub 0)), FAO-56 ET, and USDA-SW gravimetric-ET - showed still greater deviations, up to 35 percent of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.

Alfalfa↗

NASA GES DISC New Data Service and Data Management for the Air Quality Community

President Obama's Big Data Research and Development Initiative seeks to improve our ability to acquire knowledge and discover insights into large and complex collections of digital data. The Big Earth Data Initiative (BEDI) Invests in standardizing and optimizing the collection, management and delivery of U.S. Government's civil Earth observation data.

air pollution↗

Communicating Medical Needs to Non-Medical Managers

Differences in communication styles and languages between groups often lead to miscommunication, confusion, and/or frustration. Engineers, computer specialists, clinicians, and managers often utilize the English language in very different ways, with different groups using the same words to represent different concepts ("complaint" is a typical example). In addition, medical issues are often perceived as "off-nominal" and not "primary mission tasks" by managers, which can cause them to assign lower priorities to medical training time and resources. Knowledge bases differ due to variations in training and skill sets, and the goals (both immediate and long-term) of the communicators may also vary, with managers being primarily concerned with overall mission objectives, while clinicians focus on individual or group health issues. Furthermore, true communication is only possible when clinicians possess a deep understanding of mission requirements as well as the ability to communicate medical requirements on a priority basis using risk assessment, added value, and cost benefit analysis. These understandable differences may contribute to difficulties in expressing concerns and ideas in an efficient manner, particularly in projects, such as the space program or many military operations, where these varied groups must collaborate, and where the final decisions must be made by fully informed mission commanders. Methods: Three scenario-based approaches were developed utilizing decision trees and problem based learning, to help define and integrate these concepts. Results: Use of these techniques by NASA and military personnel will be presented. Discussion: To enhance communication, particularly of medical needs, one must identify the concerns and motivating factors for the other groups; for example, members of management may focus on financial concerns, a desire for risk mitigation, public perceptions, mission objectives, etc. Training clinicians to frame issues in these terms may lead to better understanding of the medical concerns by other groups.

Bacal, Kira↗

Overview of the Smart Network Element Architecture and Recent Innovations

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

Perotti, Jose M.↗

Final Technical Report: Center for Mechanistic Control of Unconventional Formations

The overarching mission of the Center for Mechanistic Control of Unconventional Formations (CMC-UF) was to garner cross-cutting, fundamental, geoscience knowledge to achieve mechanistic control over the strongly coupled nonequilibrium physical and geochemical processes in extreme geological environments including shale, mudstone, marls, and other tight rocks with nanoscale pores. Collectively, these are referred to as unconventional formations and they often play the role of seals for other subsurface storage formations. The fundamental knowledge garnered by CMC-UF enabled science-based management of US unconventional formations for subsurface storage of carbon dioxide and TWh quantities of renewable energy as hydrogen and/or compressed air over longer timeframes as well as for natural gas production, with reduced environmental impacts, in the short term.

58 GEOSCIENCES↗

Seventh Annual Conference on Manual Control

The Seventh Annual NASA/AF/University Conference on Manual Control was held at the University of Southern California from June 2-4, 1971. Some eighty specialists, including colleagues from Canada, Netherlands and West Germany, attended the Conference, which was organized by the authors of this Summary. Generally at this conference there was less emphasis on theory and more on applications than at some previous meetings. In addition to the well-established areas of human operator modeling and display systems, this conference devoted considerable time to the extensions of manual control theory to such diverse areas as automobile driving, air traffic control and industrial management. This interest in meaningful applications of the existing theoretical knowledge in man-machine systems is encouraging and timely.

Source record↗

The advanced technology laboratory

The Advanced Technology Laboratory (ATL) utilizes the Space Shuttle and the European Spacelab and is intended for advanced space technology. The evolution of the ATL concept is outlined along with its current status. Spacelab payload point design studies are reviewed as related to objective; physical layout; mission analysis; pointing accuracy; attitude management and fuel consumption; controls, displays, and data management; and thermal control. These studies aim at increasing the knowledge of the best techniques for integration and operation of payloads in the Spacelab and the Shuttle. ATL presents a dynamic new research potential, capable of accomodating 8 to 15 experiments per mission.

Llewellyn, C.↗

Evaluation of expert systems - An approach and case study

Techniques that were applied in defining an expert system prototype for first-cut evaluations of the software functional requirements of NASA satellite command management activities are described. The prototype was developed using the Knowledge Engineering System. Criteria were selected for evaluating the satellite software before defining the expert system prototype. Application of the prototype system is illustrated in terms of the evaluation procedures used with the COBE satellite to be launched in 1988. The limited number of options which can be considered by the program mandates that biases in the system output must be well understood by the users.

Liebowitz, J.↗

An architecture for intelligent interfaces - Outline of an approach to supporting operators of complex systems

The conceptual design of a comprehensive support system for operators of complex systems is presented. Key functions within the support system architecture include information management, error monitoring, and adaptive aiding. One of the central knowledge bases underlying this functionality is an operator model that involves a 'matrix' of algorithmic and symbolic models for assessing and predicting an operator's activities, awareness resources, intentions, and performance. Functional block diagrams are presented for the overall architecture as well as the key elements within this architecture. A variety of difficult design issues are discussed and ongoing efforts aimed at resolving these issues are noted.

Rouse, W. B.↗

The development and technology transfer of software engineering technology at NASA. Johnson Space Center

The United State's big space projects of the next decades, such as Space Station and the Human Exploration Initiative, will need the development of many millions of lines of mission critical software. NASA-Johnson (JSC) is identifying and developing some of the Computer Aided Software Engineering (CASE) technology that NASA will need to build these future software systems. The goal is to improve the quality and the productivity of large software development projects. New trends are outlined in CASE technology and how the Software Technology Branch (STB) at JSC is endeavoring to provide some of these CASE solutions for NASA is described. Key software technology components include knowledge-based systems, software reusability, user interface technology, reengineering environments, management systems for the software development process, software cost models, repository technology, and open, integrated CASE environment frameworks. The paper presents the status and long-term expectations for CASE products. The STB's Reengineering Application Project (REAP), Advanced Software Development Workstation (ASDW) project, and software development cost model (COSTMODL) project are then discussed. Some of the general difficulties of technology transfer are introduced, and a process developed by STB for CASE technology insertion is described.

Pitman, C. L.↗

Program Helps Decompose Complex Design Systems

DeMAID (A Design Manager's Aid for Intelligent Decomposition) computer program is knowledge-based software system for ordering sequence of modules and identifying possible multilevel structure for design problem. Groups modular subsystems on basis of interactions among them. Saves considerable money and time in total design process, particularly in new design problem in which order of modules has not been defined. Available in two machine versions: Macintosh and Sun.

Rogers, James L., Jr.↗

Roles, uses, and benefits of general aviation aircraft in aerospace engineering education

Many colleges and universities throughout the United States offer outstanding programs in aerospace engineering. In addition to the fundamentals of aerodynamics, propulsion, flight dynamics, and air vehicle design, many of the best programs have in the past provided students the opportunity to design and fly airborne experiments on board various types of aircraft. Sadly, however, the number of institutions offering such 'airborne laboratories' has dwindled in recent years. As a result, opportunities for students to apply their classroom knowledge, analytical skills, and engineering judgement to the development and management of flight experiments on an actual aircraft are indeed rare. One major reason for the elimination of flight programs by some institutions, particularly the smaller colleges, is the prohibitive cost of operating and maintaining an aircraft as a flying laboratory. The purpose of this paper is to discuss simple, low-cost, relevant flight experiments that can be performed using readily available general aviation aircraft. This paper examines flight experiments that have been successfully conducted on board the NASA Lewis Research Center's T-34B aircraft, as part of the NASA/AIAA/University Flight Experiment Program for Students (NAUFEPS) and discusses how similar experiments could be inexpensively performed on other general aviation aircraft.

Odonoghue, Dennis P.↗

DIAMS revisited: Taming the variety of knowledge in fault diagnosis expert systems

The DIAMS program, initiated in 1986, led to the development of a prototype expert system, DIAMS-1 dedicated to the Telecom 1 Attitude and Orbit Control System, and to a near-operational system, DIAMS-2, covering a whole satellite (the Telecom 2 platform and its interfaces with the payload), which was installed in the Satellite Control Center in 1993. The refinement of the knowledge representation and reasoning is now being studied, focusing on the introduction of appropriate handling of incompleteness, uncertainty and time, and keeping in mind operational constraints. For the latest generation of the tool, DIAMS-3, a new architecture has been proposed, that enables the cooperative exploitation of various models and knowledge representations. On the same baseline, new solutions enabling higher integration of diagnostic systems in the operational environment and cooperation with other knowledge intensive systems such as data analysis, planning or procedure management tools have been introduced.

Haziza, M.↗

Program Helps Decompose Complex Design Systems

DeMAID (Design Manager's Aid for Intelligent Decomposition) computer program is knowledge-based software system for ordering sequence of modules and identifying possible multilevel structure for design problems such as large platforms in outer space. Groups modular subsystems on basis of interactions among them. Saves considerable amount of money and time in total design process, particularly in new design problem in which order of modules has not been defined. Originally written for design problems, also applicable to problems containing modules (processes) that take inputs and generate outputs. Available in three machine versions: Macintosh written in Symantec's Think C 3.01, Sun, and SGI IRIS in C language.

Rogers, James L., Jr.↗