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Tables from \ NIST -- National Institute of Standards and Technology, data

.nist.gov (Standard Reference / public data, DCAT/NERDm). {"@context":["https://data.nist.gov/od/dm/nerdm-pub-context.jsonld",{"@base":"ark:/88434/mds10zmhdk"}],"_schema":"https://data.nist.gov/od/dm/nerdm-schema/v0.7#","_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/pub/v0.7#/definitions/PublicDataResource"],"@type":["nrdp:PublicDataResource"],"@id":"ark:/88434/mds10zmhdk","doi":"doi:10.18434/T4/1423308","title":"Tables from \"Analysis of Pipeline Steel Corrosion Data From NBS (NIST) Studies Conducted Between 1922-1940 and Relevance to Pipeline Management\" (NISTIR 7415)","contactPoint":{"fn":"Richard Ricker","hasEmail":"mailto:richard.ricker@nist.gov","name":"Richard Ricker"},"modified":"2007-01-01","ediid":"576CE869311197F3E0531A570681C5C71857","landingPage":"https://data.nist.gov/od/id/576CE869311197F3E0531A570681C5C71857","description":["Between 1922 and 1940, the National Bureau of Standards (NBS) conducted a long-term investigation into the corrosion of bare steel and iron, pipes buried underground at 47 sites representing different soil types in the United States. Following the passage of the 2004 Pipeline Safety Improvement Act, the Department of Transportation's Office of Pipeline Safety requested that NIST review and reanalyze the data from the NBS study using modern statistical analysis tools. For this analysis, NIST compiled an updated database from the data in the publications by K. H. Logan (i.e. NBS C450, 1945), M. Romanoff (i.e. NBS C579, 1957), and others, including examination of original logbooks. NIST published a report analyzing this data with modern computer assisted statistical analysis tools (doi.org/10.6028/NIST.IR.7415) and an archival paper summarizing the findings (doi:10.6028/jres.115.026). This data is provided in this format so that others will have the best available data from this research for future analyses."],"keyword":["corrosion","pipeline","steel","underground"],"theme":["Materials:Materials characterization","Materials:Metals"],"topic":[],"references":[{"@type":["deo:BibliographicReference"],"@id":"#ref:10.6028/jres.115.026","refType":"IsReferencedBy","location":"http://dx.doi.org/10.6028/jres.115.026","_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/bib/v0.7#/definitions/DCiteReference"]},{"@type":["deo:BibliographicReference"],"@id":"#ref:10.6028/NIST.IR.7415","refType":"IsReferencedBy","location":"https://dx.doi.org/10.6028/NIST.IR.7415","_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/bib/v0.7#/definitions/DCiteReference"]}],"accessLevel":"public","license":"https://www.nist.gov/open/license","components":[{"accessURL":"https://doi.org/10.18434/T4/1423308","format":"text/html","description":"DOI Access to Tables from Analysis of Pipeline Steel Corrosion Data From NBS (NIST) Studies Conducted Between 1922-1940 and Relevance to Pipeline Management (NISTIR 7415)","title":"DOI Access to Tables from Analysis of Pipeline Steel Corrosion Data From NBS (NIST) Studies Conducted Between 1922-1940 and Relevance to Pipeline Management (NISTIR 7415)","@type":["nrd:Hidden","dcat:Distribution"],"@id":"#doi:10.18434/T4/1423308"},{"filepath":"NISTIR 7415_Appendix C.xlsx","checksum":{"hash":"dbdbcfef4f1091720119b9ac1d14b11a7a96db6ce22c62d13c2a7eb33a9a81a1","algorithm":{"tag":"sha256","@type":"Thing"}},"mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","downloadURL":"https://data.nist.gov/od/ds/576CE869311197F3E0531A570681C5C71857/NISTIR%207415_Appendix%20C.xlsx","size":26715,"@id":"cmps/NISTIR 7415_Appendix C.xlsx","@type":["nrdp:DataFile","nrdp:DownloadableFile","dcat:Distribution"],"_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/pub/v0.7#/definitions/DataFile"]},{"description":"SHA-256 checksum value for NISTIR 7415_Appendix C.xlsx","@id":"cmps/NISTIR 7415_Appendix C.xlsx.sha256","valid":true,"_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/pub/v0.7#/definitions/ChecksumFile"],"algorithm":{"@type":"Thing","tag":"sha256"},"filepath":"NISTIR 7415_Appendix C.xlsx.sha256","checksum":{"hash":"500915456c71a11d8a92b4e83d750d98aec79ad17484db3d65a49c6f3cf71a5b","algorithm":{"tag":"sha256","@type":"Thing"}},"mediaType":"text/plain","downloadURL":"https://data.nist.gov/od/ds/576CE869311197F3E0531A570681C5C71857/NISTIR%207415_Appendix%20C.xlsx.sha256","describes":"cmps/NISTIR 7415_Appendix C.xlsx","size":64,"@type":["nrdp:ChecksumFile","nrdp:DownloadableFile","dcat:Distribution"]}],"publisher":{"name":"National Institute of Standards and Technology","@type":"org:Organization"},"language":["en"],"bureauCode":["006:55"],"programCode":["006:052"],"version":"1.0.1","releaseHistory":{"@id":"ark:/88434/mds10zmhdk/pdr:v","@type":["nrdr:ReleaseHistory"],"hasRelease":[{"version":"1.0.0","issued":"2007-01-01","@id":"ark:/88434/mds10zmhdk/pdr:v/1.0.0","location":"https://data.nist.gov/od/id/ark:/88434/mds10zmhdk/pdr:v/1.0.0","description":"initial release"},{"version":"1.0.1","issued":"2007-01-01","@id":"ark:/88434/mds10zmhdk/pdr:v/1.0.1","location":"https://data.nist.gov/od/id/ark:/88434/mds10zmhdk/pdr:v/1.0.1","description":"metadata update"}]}},{"landingPage":"https://pages.nist.gov/mumpce_py/","bureauCode":["006:55"],"modified":"2017-09-14","@id":"ark:/88434/mds01c89cp","keyword":["experimental database; experimental design; optimization; outlier detection; uncertainty analysis."],"doi":"doi:10.18434/M3WT1B","@context":["https://data.nist.gov/od/dm/nerdm-pub-context.jsonld",{"@base":"ark:/88434/mds01c89cp"}],"@type":["nrdp:PublicDataResource"],"contactPoint":{"fn":"David Sheen","hasEmail":"mailto:david.sheen@nist.gov"},"description":["The Method of Uncertainty Minimization using Polynomial Chaos Expansions (MUM-PCE) was developed as a software tool to constrain physical models against experimental measurements. These models contain parameters that cannot be easily determined from first principles and so must be measured, and some which cannot even be easily measured. In such cases, the models are validated and tuned against a set of global experiments which may depend on the underlying physical parameters in a complex way. 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Example measurements of the M2E latency of VHF and UHF land mobile radios (LMR) operating in both direct mode and in trunked mode were performed. 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This code is utilized by the measurement systems described in NIST IR 8206 and NIST IR 8275. The code is written for the TI MSP430F5529 processor and was developed using a MSP EXP430F5529LP LaunchPad board. The code was compiled and loaded using TI Code Composer Studio (CCS) IDE, available here: http://www.ti.com/tool/CCSTUDIO.","title":"Microcontroller Firmware"},{"@id":"cmps/Processed-Audio.zip","@type":["nrdp:DataFile","nrdp:DownloadableFile","dcat:Distribution"],"_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/pub/v0.7#/definitions/DataFile"],"filepath":"Processed-Audio.zip","downloadURL":"https://s3.amazonaws.com/nist-midas/1865/Processed-Audio.zip","mediaType":"application/zip"},{"@id":"cmps/NIST.IR.8206","@type":["nrdp:DataFile","nrdp:DownloadableFile","dcat:Distribution"],"_extensionSchemas":["https://data.nist.gov/od/dm/nerdm-schema/pub/v0.7#/definitions/DataFile"],"filepath":"NIST.IR.8206","downloadURL":"https://doi.org/10.6028/NIST.IR.8206","mediaType":"application/pdf","format":{"description":"PDF"},"description":"Mouth-to-ear (M2E) latency describes the time it takes speech input in a voice communication transmit device to be output from a receiving device, and has been identifed as a key component of quality of experience (QoE) in communications. NIST?s PSCR division developed a method to measure and quantify the M2E latency of any communications system transmitting audio, with specifc emphasis on push to talk (PTT) devices. This measurement method is the frst step in establishing QoE key performance indicators (KPI) for mission critical voice (MCV) and a measurement system to quantify these QoE KPIs. Additional measurement methods will be established and published in the near future. The measurement system provides a fair platform for the comparisons of M2E latency across radio communications technologies. Both single and two location measurement systems were developed. The single location measurement system is a simpler setup ideal for measurements performed in a single, controlled setting. The two location system allows for the measurement of M2E latency between devices in two distinct locations and adds the capability to see potential effects of distance and signal propagation on the latency a user experiences. Example measurements of the M2E latency of VHF and UHF land mobile radios (LMR) operating in both direct mode and in trunked mode were performed. These tests demonstrated that both the single and two location tests return consistent measurement results. 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