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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗
DOE OSTI2015

Implementation of EPICS based vacuum control system for variable energy cyclotron centre, Kolkata

The vacuum system of the Room Temperature (K = 130) Cyclotron of Variable Energy Cyclotron Centre is comprised of vacuum systems of main machine and Beam Transport System. The vacuum control system is upgraded to a PLC based Automated system from the initial relay based Manual system. The supervisory control of the vacuum system is implemented in Experimental Physics and Industrial Control System (EPICS). An EPICS embedded ARM based vacuum gauge controller is developed to mitigate the requirement of vendor specific gauge controller for gauges and also for seamless integration of the gauge controllers with the control system. A set of MS-Windows ActiveX components with embedded EPICS Channel Access interface are developed to build operator interfaces with less complex programming and to incorporate typical Windows feature, e.g., user authentication, file handling, better fonts, colors, mouse actions etc. into the operator interfaces. The control parameters, monitoring parameters, and system interlocks of the system are archived in MySQL based EPICS MySQL Archiver developed indigenously. In this paper, we describe the architecture, the implementation details, and the performance of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2012

Mining Bug Databases for Unidentified Software Vulnerabilities

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, a significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python

PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.

Barnette, DanielW.↗
DOE OSTI2013

Lightweight performance data collectors 2.0 with Eiger support.

We report on the use and design of a portable, extensible performance data collection tool motivated by modeling needs of the high performance computing systems co-design com- munity. The lightweight performance data collectors with Eiger support is intended to be a tailorable tool, not a shrink-wrapped library product, as pro ling needs vary widely. A single code markup scheme is reported which, based on compilation ags, can send perfor- mance data from parallel applications to CSV les, to an Eiger mysql database, or (in a non-database environment) to at les for later merging and loading on a host with mysql available. The tool supports C, C++, and Fortran applications.

Allan, Benjamin A.↗
DOE OSTI2019

CAASCADE: A System for Static Analysis of HPC Software Application Portfolios

With the increasing complexity of upcoming HPC systems, so-called “co-design” efforts to develop the hardware and applications in concert for these systems also become more challenging. It is currently difficult to gather information about the usage of programming model features, libraries, and data structure considerations in a quantitative way across a variety of applications, and this information is needed to prioritize development efforts in systems software and hardware optimizations. In this paper we propose CAASCADE, a system that can harvest this information in an automatic way in production HPC environments, and we show some early results from a prototype of the system based on GNU compilers and a MySQL database.

Lopez, Graham↗
DOE OSTI2024

Hydra: Computer Vision for Online Data Quality Monitoring

Hydra is a system utilizing computer vision for near real-time data quality monitoring. Currently operational across all of Jefferson Lab’s experimental halls, it reduces the workload of shift takers by autonomously monitoring diagnostic plots during experiments. Hydra uses "off-the-shelf" supervised learning technologies and is supported by a comprehensive MySQL database. To simplify access, web apps have been developed to facilitate both labeling and monitoring of Hydra’s inferences. Hydra can connect with the alarm system and incorporates complete historical tracking, enabling it to identify issues that shift takers could miss. When issues are detected, a natural first question is: "Why does Hydra think there is a problem?" To answer, Hydra employs Gradient-weighted Class Activation Maps (GradCAM) to identify regions of the image that are important for the specific classification. This interpretive layer enhances transparency and trustworthiness, which is essential for integration with experiment workflows and operation. The Hydra system, results, and sociological considerations for deployment will be discussed.

Jeske, Torri↗
DOE OSTI2024

Geant4 Monte-Carlo (GEMC) A database-driven simulation program

GEMC[1] is an application that harnesses the power of databases to execute Geant4 Monte-Carlo simulations. The databases (MYSQL, CSQL, TEXT) define the geometry, materials, digitization algorithms, readout electronics and output formats. Implemented in C++, GEMC also boasts a user-friendly Python API that facilitates detector construction and database population. GEMC can handle real-life scenarios such as geometry variations and the run number-dependent calibration constants and digitization parameters. This abstract provides an overview of GEMC, accompanied by examples that showcase its versatility. We delve into the practical application of GEMC within the the CLAS12 experimental program at Jefferson Lab.

Ungaro, Maurizio↗
DOE OSTI2012

A new information architecture, website and services for the CMS experiment

The age and size of the CMS collaboration at the LHC means it now has many hundreds of inhomogeneous web sites and services, and hundreds of thousands of documents. We describe a major initiative to create a single coherent CMS internal and public web site. This uses the Drupal web Content Management System (now supported by CERN/IT) on top of a standard LAMP stack (Linux, Apache, MySQL, and php/perl). The new navigation, content and search services are coherently integrated with numerous existing CERN services (CDS, EDMS, Indico, phonebook, Twiki) as well as many CMS internal Web services. We describe the information architecture, the system design, implementation and monitoring, the document and content database, security aspects, and our deployment strategy, which ensured continual smooth operation of all systems at all times.

Taylor, Lucas↗
DOE OSTI2014

Grids, virtualization, and clouds at Fermilab

Fermilab supports a scientific program that includes experiments and scientists located across the globe. To better serve this community, in 2004, the (then) Computing Division undertook the strategy of placing all of the High Throughput Computing (HTC) resources in a Campus Grid known as FermiGrid, supported by common shared services. In 2007, the FermiGrid Services group deployed a service infrastructure that utilized Xen virtualization, LVS network routing and MySQL circular replication to deliver highly available services that offered significant performance, reliability and serviceability improvements. This deployment was further enhanced through the deployment of a distributed redundant network core architecture and the physical distribution of the systems that host the virtual machines across multiple buildings on the Fermilab Campus. In 2010, building on the experience pioneered by FermiGrid in delivering production services in a virtual infrastructure, the Computing Sector commissioned the FermiCloud, General Physics Computing Facility and Virtual Services projects to serve as platforms for support of scientific computing (FermiCloud 6 GPCF) and core computing (Virtual Services). Lastly, this work will present the evolution of the Fermilab Campus Grid, Virtualization and Cloud Computing infrastructure together with plans for the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and welldefined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Laboratory Studies of Particle Cementation and PV Module Soiling

Monitoring of photovoltaic (PV) systems can maintain efficient operations. However, extensive monitoring of large quantities of data can be a cumbersome process. The present work introduces a simple, inexpensive, yet effective data monitoring strategy for detecting faults and determining lost revenues automatically. This was achieved through the deployment of Raspberry Pi (RPI) device at a PV system's combiner box. The RPI was programmed to collect PV data through Modbus communications, and store the data locally in a MySQL database. Then, using a Gaussian Process Regression algorithm the RPI device was able to accurately estimate string level current, voltage, and power values. The device could also detect system faults using a Support Vector Novelty Detection algorithm. Finally, the RPI was programmed to output the potential lost revenue caused by the abnormal condition. The system analytics information was then displayed on a user interface. The interface could be accessed by operations personal to direct maintenance activity so that critical issues can be solved quickly.

14 SOLAR ENERGY↗
DOE OSTI2021

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

Abstract In this paper, the design and performance differences between Relational Database Management Systems (RDBMS) and NoSQL Database Systems are examined, with attention to their applicability for real-world Internet of Things for manufacturing (IoTfM) data. While previous work has extensively compared SQL and NoSQL for both generalized and IoT uses, this work specifically examines the tradeoffs and performance differences for manufacturing applications by using a high-fidelity data set collected from a large US manufacturing firm. Growing an IoT system beyond the pilot stage requires scalable data storage; this work seeks to determine the impact of selected database systems on data write performance at scale. Payload size and message frequency were used as the primary characteristics to maintain model fidelity in simulated clients. As the number of simulated asset clients grow, the data write latency was calculated to determine how both database systems’ performance were affected. To isolate the RDBMS and NoSQL differences, a cloud environment was created using Amazon Web Services (AWS) with two identical data ingestion pipelines: writing data to an RDMBS (1) using AWS Aurora MySQL, and (2) using AWS DynamoDB NoSQL. The findings may provide guidance for further experimentation in large-scale manufacturing IoT implementations.

Gamero, David↗
DOE OSTI2014

SU-E-T-641: Development and Verification of Automatic Reading Dose of Interest From Eclipse's DVH

Purpose: According to clinical and research requirement, we develop a function of automatic reading dose of interest from dose volume histogram(DVH), to replace the traditional method with a mouse one by one point, and it's also verified. Methods: The DVH automatic reading function will be developed in an in-house developed radiotherapy information management system(RTIMS), which is based on Apache+PHP+MySQL. A DVH ASCII file is exported from Varian Eclipse V8.6, which includes the following contents: 1. basic information of patient; 2. dose information of plan; 3. dose information of structures, including basic information and dose volume data of target volume and organ at risk. And the default exported dose volume data also includes relative doses by 1% step and corresponding absolute doses and cumulative relative volumes, and the volumes are 4 decimal fraction. Clinically, we often need read the doses of some integer percent volumes, such as D50 and D30. So it couldn't be directly obtained from the above data, but we can use linear interpolation bye the near volumes and doses: Dx=D2−(V2−Vx)*(D2−D1)/(V2−V1), and program a function to search, read and calculate the corresponding data. And the doses of all preseted volume of interest of all structures can be automatically read one by one patient, and saved as a CSV file. To verify it, we select 24 IMRT plans for prostate cancer, and doses of interest are PTV D98/D95/D5/D2, bladder D30/D50, and rectum D25/D50. Two groups of data, using the automatic reading method(ARM) and pointed dose method(PDM), are analyzed with SPSS 16. The absolute difference=D-ARM-D-PDM, relative difference=absolute difference*100%/prescription dose(7600cGy). Results: The differences are as following: PTV D98/D95/D5/D2: −0.04%/− 0.04%/0.13%/0.19%, bladder D30/D50: −0.02%/0.01%, and rectum D25/D50: 0.03%/0.01%. Conclusion: Using this function, the error is very small, and can be neglected. It could greatly improve the efficiency of clinical work. Project supported by the National Natural Science Foundation of China (Grant No.81101694)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-240: Design and Implement of An Electronic Records Function for Treatment Plan Checked Meeting

Purpose: To replace the paper records, we designed an electronic records function for plan checked meeting in our in-house developed radiotherapy information management system(RTIMS). Methods: Since 2007, the RTIMS has been developed on a database and web service of Apache+PHP+MySQL, and almost all computers and smartphones could access the RTIMS through IE browser, to input, search, count, and print the data. In 2012, we also established an radiation therapy case conference multi-media system(RTCCMMS) based on Windows Remote Desktop feature. Since 2013, we have carried out the treatment plan checked meeting of the physics division in every afternoon for about half an hour. In 2014, we designed an electronic records function, which includes a meeting information record and a checked plan record. And the meeting record includes the following items: meeting date, name, place, length, status, attendee, content, etc. The plan record includes the followings: meeting date, meeting name, patient ID, gender, age, patient name, course, plan, purpose, position, technique, CTsim type, plan type, primary doctor, other doctor, primary physicist, other physicist, difficulty, quality, score, opinion, status, note, etc. Results: In the past year, the electronic meeting records function has been successfully developed and implemented in the division, and it could be accessed from an smartphone. Almost all items have the corresponding pull-down menu selection, and each option would try to intelligently inherit default value from the former record or other form. According to the items, we could do big data mining to the input data. It also has both Chinese and English two versions. Conclusion: It was demonstrated to be user-friendly and was proven to significantly improve the clinical efficiency and quality of treatment plan. Since the RTIMS is an in-house developed system, more functions can be added or modified to further enhance its potentials in research and clinical practice. Project supported by the National Natural Science Foundation of China (Grant No.81101694)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-241: Design and Implement of An Information Management System for Radiation Workers in a Hospital

Purpose: To meet the special needs of Medical Administration Division, an information management system for radiation workers in a hospital(IMSRWH) has been developed. Methods: There are about 200 radiation workers in 20 departments, such as department of radiology, department of radiation oncology, department of nuclear medicine, and so on. An IMSRWH server was used to run a database and web service of Apache+PHP+MySQL. The IMSRWH web service could be accessed with Internet Explorer(IE) to input, search, count, and print the radiation workers’ data. Every worker’s data information includes the following tables: registration, personal dose monitoring records, personnel certificate, training certificate, personnel license, medical examination, etc, and each table includes more optional detail information. Results: In the past year, the IMSRWH has been successfully developed and implemented in the hospital. According to the needs, the user rights are divided into: the system administrator, office manager, department manager and radiation worker. The different users have the different interfaces, and the appropriate authority permissions mean corresponding operations. The administrator and office manager could manage all personnel information, department manager could manage the staff information of his department, and the workers could view or modify their own information. Because information updates, involving hundreds of each entry and modification are complicated, each table information of all workers can be batch import from or export to a Microsoft Excel CSV format file, to update all together. However, it has only Chinese version now. Conclusion: It was demonstrated to be user-friendly and was proven to significantly improve the efficiency of the hospital management. Since it is an in-house developed system, more functions can be added or modified to further enhance its potentials in research and clinical practice.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-F-CAMPUS-I-05: Semi-Automated, Open Source MRI Quality Assurance and Quality Control Program for Multi-Unit Institution

Purpose: Phantom measurements allow for the performance of magnetic resonance (MR) systems to be evaluated. Association of Physicists in Medicine (AAPM) Report No. 100 Acceptance Testing and Quality Assurance Procedures for MR Imaging Facilities, American College of Radiology (ACR) MR Accreditation Program MR phantom testing, and ACR MRI quality control (QC) program documents help to outline specific tests for establishing system performance baselines as well as system stability over time. Analyzing and processing tests from multiple systems can be time-consuming for medical physicists. Besides determining whether tests are within predetermined limits or criteria, monitoring longitudinal trends can also help prevent costly downtime of systems during clinical operation. In this work, a semi-automated QC program was developed to analyze and record measurements in a database that allowed for easy access to historical data. Methods: Image analysis was performed on 27 different MR systems of 1.5T and 3.0T field strengths from GE and Siemens manufacturers. Recommended measurements involved the ACR MRI Accreditation Phantom, spherical homogenous phantoms, and a phantom with an uniform hole pattern. Measurements assessed geometric accuracy and linearity, position accuracy, image uniformity, signal, noise, ghosting, transmit gain, center frequency, and magnetic field drift. The program was designed with open source tools, employing Linux, Apache, MySQL database and Python programming language for the front and backend. Results: Processing time for each image is <2 seconds. Figures are produced to show regions of interests (ROIs) for analysis. Historical data can be reviewed to compare previous year data and to inspect for trends. Conclusion: A MRI quality assurance and QC program is necessary for maintaining high quality, ACR MRI Accredited MR programs. A reviewable database of phantom measurements assists medical physicists with processing and monitoring of large datasets. Longitudinal data can reveal trends that although are within passing criteria indicate underlying system issues.

60 APPLIED LIFE SCIENCES↗