Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “relational databases”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-G-201-09: Evaluation of a Novel Machine-Learning Algorithm for Permanent Prostate Brachytherapy Treatment Planning

Purpose: A novel, automated, algorithm for permanent prostate brachytherapy (PPB) treatment planning has been developed. The novel approach uses machine-learning (ML), a form of artificial intelligence, to substantially decrease planning time while simultaneously retaining the clinical intuition of plans created by radiation oncologists. This study seeks to compare the ML algorithm against expert-planned PPB plans to evaluate the equivalency of dosimetric and clinical plan quality. Methods: Plan features were computed from historical high-quality PPB treatments (N = 100) and stored in a relational database (RDB). The ML algorithm matched new PPB features to a highly similar case in the RDB; this initial plan configuration was then further optimized using a stochastic search algorithm. PPB pre-plans (N = 30) generated using the ML algorithm were compared to plan variants created by an expert dosimetrist (RT), and radiation oncologist (MD). Planning time and pre-plan dosimetry were evaluated using a one-way Student’s t-test and ANOVA, respectively (significance level = 0.05). Clinical implant quality was evaluated by expert PPB radiation oncologists as part of a qualitative study. Results: Average planning time was 0.44 ± 0.42 min compared to 17.88 ± 8.76 min for the ML algorithm and RT, respectively, a significant advantage [t(9), p = 0.01]. A post-hoc ANOVA [F(2,87) = 6.59, p = 0.002] using Tukey-Kramer criteria showed a significantly lower mean prostate V150% for the ML plans (52.9%) compared to the RT (57.3%), and MD (56.2%) plans. Preliminary qualitative study results indicate comparable clinical implant quality between RT and ML plans with a trend towards preference for ML plans. Conclusion: PPB pre-treatment plans highly comparable to those of an expert radiation oncologist can be created using a novel ML planning model. The use of an ML-based planning approach is expected to translate into improved PPB accessibility and plan uniformity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Next-generation geospatial-temporal information technologies for disaster management

Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. Here, we highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

AESD (Advanced Energy System Design) Records API [SWRs-17-50, 17-51, 17-52]

The Records API (application program interface) for Advanced Energy System Design (AESD) enables software that serves multidimensional record-oriented data to interoperate with software than uses such data. In the context of the Records API, multidimensional data records are simply tuples of real numbers, integers, and character strings, where each data value is tagged by a variable name, according to a pre-defined schema, and each record is assigned a unique integer identifier. Conceptually, these records are isomorphic to rows in a relational database, JSON objects, or key-value maps. Records servers might supply static datasets, sensor measurements that periodically update as new telemetry become available, or the results of simulations as the simulations generate new output. Records client software might display or analyze the data, but in the case of simulations the client request the creation of new ensembles for specified input parameters. It is also possible to chain records clients and servers together so that a client consuming data from a server might transform that data and serve it to additional clients. This minimalist API avoids imposing burdensome metadata, structural, or implementation requirements on developers by relying on open-source technologies that are readily available for common programming languages. In particular, the API has been designed to place the least possible burden on services that provide data. This document defines the message format for the Records API, a transport mechanism for communicating the data, and the semantics for interpreting it. The message format is specified as Google Protocol Buffers and the transport mechanism uses WebSockets. We discuss three major use cases for serving and consuming records data: (i) static data, (ii) dynamically augmented data, (iii) on-demand simulations, (iv) with filters, and (v) with bookmarks. Separate implementations of the API exist in C++, Haskell, JavaScript, Python, and R.

Bush, Brian↗
DOE OSTI2021

REST Interface Generator (RESTInG) v0.1

From a single data description file, this package generates a simple but complete RESTful web interface to a relational database, in the form of containers that run in a Docker environment. This initial version produces containers that are intended for use on the NERSC Spin platform. It was developed as a foundation for the smart catalog created for LDRD FY20 ACTS: Accelerating COVID-19 Testing with Screening.

Higa, Kenneth↗
DOE OSTI2014

Advancing a Framework to Enable Characterization and Evaluation of Data Streams Useful for Biosurveillance

In recent years, biosurveillance has become the buzzword under which a diverse set of ideas and activities regarding detecting and mitigating biological threats are incorporated depending on context and perspective. Increasingly, biosurveillance practice has become global and interdisciplinary, requiring information and resources across public health, One Health, and biothreat domains. Even within the scope of infectious disease surveillance, multiple systems, data sources, and tools are used with varying and often unknown effectiveness. Evaluating the impact and utility of state-of-the-art biosurveillance is, in part, confounded by the complexity of the systems and the information derived from them. We present a novel approach conceptualizing biosurveillance from the perspective of the fundamental data streams that have been or could be used for biosurveillance and to systematically structure a framework that can be universally applicable for use in evaluating and understanding a wide range of biosurveillance activities. Moreover, the Biosurveillance Data Stream Framework and associated definitions are proposed as a starting point to facilitate the development of a standardized lexicon for biosurveillance and characterization of currently used and newly emerging data streams. Criteria for building the data stream framework were developed from an examination of the literature, analysis of information on operational infectious disease biosurveillance systems, and consultation with experts in the area of biosurveillance. To demonstrate utility, the framework and definitions were used as the basis for a schema of a relational database for biosurveillance resources and in the development and use of a decision support tool for data stream evaluation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

SECARB Project Overview Book

In 2003, the United States Department of Energy (DOE) issued awards initiating seven Regional Carbon Sequestration Partnerships (RCSP) spanning the United States and portions of Canada. Managed by DOE’s National Energy Technology Laboratory (NETL), the RCSPs currently represent more than 400 state agencies, universities, and private companies, spanning 43 states, three Native American Organizations, and four Canadian provinces. The Southern States Energy Board (SSEB) received an award on October 1, 2003, which established the Board’s overall management and administration of the Southeast Regional Carbon Sequestration Partnership, or SECARB. The geographical region currently includes 13 states and a network of more than 100 stakeholders. The Nation’s leading scientists, university researchers, national laboratories, industrial representatives, environmental organizations, and many others have taken a proactive approach at identifying and characterizing the most promising options for technology deployment and carbon dioxide (CO2) utilization and storage (CCUS) for the Southeast. The results obtained during these injections will be important to the future commercialization of CCUS technologies and the continued use of fossil fuels as a significant energy source in a manner that is environmentally responsible. Each of the six SECARB project locations has been locally coordinated by its own field team. The field teams assume responsibility for the technical scope of work, local education and outreach, permitting, monitoring, verification, and accounting (MVA), and maintaining the validation test’s schedule and budget. Each team contributes new information to the continued characterization of the region. In addition, a task is dedicated to integrating field data and filling gaps in regional characterization data sets. Data and tools developed in the Continued Characterization task are incorporated into a relational database and geographic information system (GIS). All field tests, the continued characterization project, and the cross-cutting functions are designed to support the DOE roadmap by validating technologies and identifying locations throughout the region that could support full-scale CCUS deployment opportunities. Detailed fact sheets for the SECARB projects are available on the SECARB website at www.secarbon.org (see “Projects” tab).

RCSP↗
DOE OSTI2012

Operation and Maintenance of the National Radiobiology Archives

The National Radiobiology Archives (NRA) are an archival program, started in 1989, to collect, organize and maintain data, laboratory notebooks, and animal tissue specimens from government (Department of Energy and its predecessor agencies) sponsored radiobiology life-span animal studies. These unique records, histopathology slides and paraffin embedded tissue blocks are maintained in a central facility and are available for further research study. The materials include electronic and paper records for each of more than 6,000 life-span-observations on dogs as well as details of major studies involving nearly 30,000 mice. Although these studies were performed over many years and at different laboratories with differing data management systems, the NRA has translated them into a standardized set of relational database tables. These can be distributed to interested individuals on written request. Specific Aims are: (1) To Maintain the Archive of Written Records from the Animal Experiments - The USTUR continued to maintain the NRA archives which consist of approximately 175 storage boxes containing laboratory notebooks, animal exposure records, animal pathologic records, and radiographs. These were stored in a 6,000 square foot leased facility in Richland, WA. Additionally, through a collaboration with Pacific Northwest National Laboratory's (PNNL) Low Dose Program, many of these records were scanned into digital files. These totaled 34 GB of data, which are saved in 2,407 separate PDF files that are organized by box number and animal identification number. (2) To Maintain the Archive of Animal Tissues at Washington State University - The USTUR continued to house the NRA dog tissue collection in the leased facility. The NRA tissue collection consisted of pathology slides and tissue blocks. Approximately 25% of the laboratory facility was dedicated to the storage of the NRA materials. (3) To Organize the Datasets of These Animals in the Context of Other Datasets so That They Can be Used by the Scientific Community at Large - As was reported in the FY2009 NRA progress report, Dr. Chuck Watson (NRA Database Consultant) completed his service as the US representative on the European Radiobiological Archives (ERA) Advisory Board during FY2009. Unfortunately, due to the lack of financial support during FY2010, the NRA was not able to make further contributions to the ERA's efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A Systematic Evaluation of Traditional and Non-Traditional Data Streams for Integrated Global Biosurveillance (Final Report)

Living in a closely connected and highly mobile world presents many new mechanisms for rapid disease spread and in recent years, global disease surveillance has become a high priority. In addition, much like the contribution of non-traditional medicine to curing diseases, non-traditional data streams are being considered of value in disease surveillance. Los Alamos National Laboratory (LANL) was tasked by the Defense Threat Reduction Agency (DTRA)-Joint Science and Technology Office (JSTO) to determine the relevance of data streams for an integrated global biosurveillance system through the use of defined metrics and methodologies. The long-term, broad objective of this project was to provide information and analysis that can be leveraged from existing and developing national and international disease surveillance systems and methodologies, to create a global disease monitoring system, ultimately providing decision makers with timely information to prepare for and mitigate the spread of disease. Specifically, this project evaluated data streams that are currently being used in surveillance systems and data streams that had the potential for being used in surveillance to enable early disease detection. LANL’s focus was on infectious disease surveillance and the term “biosurveillance” will be used to refer to this scope hereafter. Data stream evaluation was conducted using two different methods: Multi criteria decision analysis (MCDA) using a tool called Logical Decisions ® that assigns utility scores to data streams based on weighted metrics and assigned values specific to data stream categories; and a Surveillance Window concept developed at LANL that assigns a window or windows of time specific to a disease within which information coming from various data streams can be determined to have utility. A cross method analysis was performed between the surveillance window based evaluation and the MCDA-based evaluation to identify data stream categories that showed high utility for both methods. In addition, algorithms that can integrate useful data streams to facilitate early disease detection were also examined. This project provided an understanding of data streams relevant to early warning, early detection and monitoring of disease outbreaks. The report describes the results of LANL’s evaluation of 16 data stream categories using the two methods, and recommendations for next steps. The project evolved significantly over its course, and significant improvements in our approaches were made compared to the initial proposed processes. A key outcome of this effort was that LANL was able to bring together several diverse entities involved in disease surveillance and lay the foundation for new collaborations that straddled military and civilian health surveillance. The robust evaluation framework developed by LANL has generated significant interest and there is interest in adopting this framework for various applications both within disease surveillance as well as other public health initiatives. Finally, LANL developed the Biosurveillance Resource Directory (BRD), a relational database that underwent pilot testing by members of the human, plant and animal disease surveillance community. The BRD is intended to be a global resource to facilitate rapid information access.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Analysis of Subject Matter Expert (SME) Feedback on the First Version of the Biosurveillance Analytics Resource directory (BaRD)

As part of a recently funded project, LANL was tasked with the development of the BaRD, a reference tool in support of the Biosurveillance Ecosystem (BSVE) that will serve to enhance situational awareness during an infectious disease outbreak and provide timely and relevant information to support effective decision making to prevent, stop or control an outbreak or epidemic. The BaRD is being designed to enable rapid selection of appropriate models for use in disease prediction, monitoring, or forecasting at various population levels. It is a searchable, relational database that catalogs and classifies model specific information to allow facile reporting on tools of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A Client/Server Architecture for Supporting Science Data Using EPICS Version 4

The Phase 1 grant that serves as a precursor to this proposal, prototyped complex storage techniques for high speed structured data that is being produced in accelerator diagnostics and beam line experiments. It demonstrates the technologies that can be used to archive and retrieve complex data structures and provide the performance required by our new accelerators, instrumentations, and detectors. Phase 2 is proposed to develop a high-performance platform for data acquisition and analysis to provide physicists and operators a better understanding of the beam dynamics. This proposal includes developing a platform for reading 109 MHz data at 10 KHz rates through a multicore front end processor, archiving the data to an archive repository that is then indexed for fast retrieval. The data is then retrieved from this data archive, integrated with the scalar data, to provide data sets to client applications for analysis, use in feedback, and to aid in identifying problem with the instrumentation, plant, beam steering, or model. This development is built on EPICS version 4 , which is being successfully deployed to implement physics applications. Through prior SBIR grants, EPICS version 4 has a solid communication protocol for middle layer services (PVAccess), structured data representation and methods for efficient transportation and access (PVData), an operational hierarchical record environment (JAVA IOC), and prototypes for standard structured data (Normative Types). This work was further developed through project funding to successfully deploy the first service based physics application environment with demonstrated services that provide arbitrary object views, save sets, model, lattice, and unit conversion. Thin client physics applications have been developed in Python that implement quad centering, orbit display, bump control, and slow orbit feedback. This service based architecture has provided a very modular and robust environment that enables commissioning teams to rapidly develop and deploy small scripts that build on powerful services. These services are all built on relational database data stores and scalar data. The work proposed herein, builds on these previous successes to provide data acquisition of high speed data for online analysis clients.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Advanced Energy System Design (AESD): Technical Manual for the Records API

The Records API (application program interface) for Advanced Energy System Design (AESD) enables software that serves multidimensional record-oriented data to interoperate with software than uses such data. In the context of the Records API, multidimensional data records are simply tuples of real numbers, integers, and character strings, where each data value is tagged by a variable name, according to a pre-defined schema, and each record is assigned a unique integer identifier. Conceptually, these records are isomorphic to rows in a relational database, JSON objects, or key-value maps. Records servers might supply static datasets, sensor measurements that periodically update as new telemetry become available, or the results of simulations as the simulations generate new output. Records client software might display or analyze the data, but in the case of simulations the client request the creation of new ensembles for specified input parameters. It is also possible to chain records clients and servers together so that a client consuming data from a server might transform that data and serve it to further clients. This minimalist API avoids imposing burdensome metadata, structural, or implementation requirements on developers by relying on open-source technologies that is readily available for common programming languages. In particular, the API has been designed to place the smallest possible burden on services that provide data. This document defines the message format for the Records API, a transport mechanism for communicating the data, and semantics for interpreting it. The message format is specified as Google Protocol Buffers and the transport mechanism uses WebSockets. We discuss three major use cases for serving and consuming records data: (i) static data, (ii) dynamically augmented data, (iii) on-demand simulations, (iv) with filters, and (v) with bookmarks. Separate implementations of the API exist in C++, Haskell, JavaScript, Python, and R.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The U.S. Nuclear Test History

This paper describes a desktop application designed to introduce users to unclassified information for the series of nuclear experiments conducted by the United States, colloquially referred to within the nuclear weapons design community as simply, the “Test History.” The application facilitates simple browsing (by name, by date, and MMDD date code), and more complex analyses based on user-defiend relational database queries.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

The Fermilab Accelerator Division Electronic Logbook (ADEL) at 10 Years

The current Fermilab Accelerator Division (AD) Electronic Logbook (ADEL) wasfirst released in 2013. It’s creation a decade ago represented a markedimprovement over the previous electronic logbook (eLog) and brought about the first consolidated Fermilab AD eLog built upon a relational database. Over the past ten years, ADEL has performed admirably, logging nearly one million user entered entries, comments and files, undergoing a revision and adding many additional features. However, as the work of Fermilab has changed, so has theuse of ADEL, some of which it had not been designed for.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Retrieval Augmented Generation for Robust Cyber Defense

In cybersecurity, the ability to efficiently analyze and respond to vulnerabilities, weaknesses, attack patterns, and threat tactics is critical for effective defense strategies. With the increasing complexity and volume of cybersecurity data, traditional methods of querying and retrieving information are often inadequate. To address this challenge, we implemented Retrieval-Augmented Generation (RAG) systems—CyRAG and GraphCyRAG—that integrate large language models (LLMs) with both structured data from relational databases and knowledge graphs such as Neo4j. CyRAG is designed to handle structured data, focusing on CVE (Common Vulnerabilities and Exposures) and CWE (Common Weakness Enumeration) entities to generate accurate and context-rich responses. In contrast, GraphCyRAG leverages Neo4j knowledge graphs to retrieve interconnected information from CVE, CWE, CAPEC (Common Attack Pattern Enumeration and Classification), and ATT&CK (Adversarial Tactics, Techniques, and Common Knowledge) datasets. By utilizing Neo4j’s graph-based framework, GraphCyRAG enables deeper traversal of relationships between vulnerabilities and attack patterns, providing cybersecurity analysts with more comprehensive insights into potential attack vectors and mitigation strategies. Our preliminary results demonstrate that integrating knowledge graphs with RAG significantly enhances both the accuracy and depth of threat analysis, allowing for the retrieval of dynamic, real-time data and the generation of contextually aware responses. This approach helps analysts uncover hidden relationships between cyber entities, predict exploit paths, and prioritize mitigation efforts effectively. The integration of RAG with cybersecurity knowledge graphs represents a significant advancement in cybersecurity threat intelligence, enabling more informed decision-making and stronger defense strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CLEAP Project: OR-SAGE Analysis for MT, UT, and CO States

The OR-SAGE tool is designed to use industry-accepted practices in screening sites and then employ the proper array of data sources through the considerable computational capabilities of GIS technology available at ORNL. The tool was developed to screen the potential for NPP siting on a national and regional basis. However, because of the tool granularity, it is often focused specifically on the immediate area around user sites of interest. If data center siting parameters can be added to OR-SAGE, the ability to evaluate data center siting on a localized scale will be beneficial.1 More than 60 data sets have been collected and processed by ORNL to develop exclusionary, avoidance, and suitability criteria for screening sites for a variety of power generation types, including nuclear power plants. Available site evaluation parameters include population density, slope, seismic activity, proximity to cooling-water sources, proximity to hazard facilities, avoidance of protected lands and floodplains, susceptibility to landslide hazards, and many others. All siting parameters should be considered as flags to inform siting decisions and should not be used to rule in or rule out any NPP site. Once data center siting parameters are identified, appropriate data sets will be collected and processed. The OR-SAGE process is very versatile. Essentially, OR-SAGE is a visual, relational database. The database partitions the contiguous United States, a total of 720 million hectares (~1.8 billion acres), into 100-m by 100-m (1 hectare or ~2.5 acre) cells. The database is tracking just under 700 million individual land cells. Successive suitability criterion is applied to each cell in the database. User-specified thresholds can be applied to each siting parameter data layer. In this manner, a variety of scenarios can be quickly and thoroughly evaluated. Data can be added and/or revised within OR-SAGE to address user interests. Siting security assessment capability is currently being added to OR-SAGE. Security is expected to be of concern at data centers whether it is collocated with a nuclear power generating technology or not. If data center is collocated with a nuclear power generating source, the security threat attractiveness level of both will likely increase. It will be of additional benefit if a potential data center site is also assessed for security vulnerability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Enabling Efficient Sparse Computations using Linear Algebra Aware Compilers

This project developed the LAPIS compiler framework, built on the Multilevel Intermediate Representation (MLIR), to optimize sparse linear algebra operations and support performance portability across diverse architectures. The main innovation of LAPIS is the Kokkos dialect, which allows for lowering codes from a high productivity language to different architectures in an elegant way. The dialect also allows the conversion of lower-level MLIR code to C++ Kokkos code, facilitating the integration of scientific machine learning (SciML) models into applications. To extend LAPIS for distributed memory architectures, a new partition dialect was created to manage the distribution of sparse tensors and express communication patterns for sparse linear algebra operations. This dialect also supports the distributed execution of operators and includes algorithmic optimizations to minimize communication to improve performance. The project also demonstrates that MLIR can enable effective linear algebra-level optimizations, improving performance on different GPUs for both sparse and dense linear algebra kernels. Key applications of LAPIS include sparse linear algebra and graph kernels, TenSQL, a relational database management solution built on GraphBLAS, and the development of subgraph isomorphism and monomorphism kernels, showcasing performance portability. In summary, the LAPIS framework supports productivity, performance, portability, and distributed memory execution, while also enabling linear algebra-level optimizations that are challenging in traditional programming languages, with successful applications ranging from simple sparse linear algebra to complex graph kernels.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The Supernovae Analysis Application (SNAP)

The SuperNovae Analysis aPplication (SNAP) is a new tool for the analysis of SN observations and validation of SN models. SNAP consists of a publicly available relational database with observational light curve, theoretical light curve, and correlation table sets with statistical comparison software, and a web interface available to the community. The theoretical models are intended to span a gridded range of parameter space. The goal is to have users upload new SN models or new SN observations and run the comparison software to determine correlations via the website. There are problems looming on the horizon that SNAP is beginning to solve. For example, large surveys will discover thousands of SNe annually. Frequently, the parameter space of a new SN event is unbounded. SNAP will be a resource to constrain parameters and determine if an event needs follow-up without spending resources to create new light curve models from scratch. Second, there is no rapidly available, systematic way to determine degeneracies between parameters, or even what physics is needed to model a realistic SN. The correlations made within the SNAP system are beginning to solve these problems.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

Microvax-based data management and reduction system for the regional planetary image facilities

Presented is a progress report for the Regional Planetary Image Facilities (RPIF) prototype image data management and reduction system being jointly implemented by Washington University and the USGS, Flagstaff. The system will consist of a MicroVAX with a high capacity (approx 300 megabyte) disk drive, a compact disk player, an image display buffer, a videodisk player, USGS image processing software, and SYSTEM 1032 - a commercial relational database management package. The USGS, Flagstaff, will transfer their image processing software including radiometric and geometric calibration routines, to the MicroVAX environment. Washington University will have primary responsibility for developing the database management aspects of the system and for integrating the various aspects into a working system.

Arvidson, R.↗