Difference between revisions of "Template:Article of the week"

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text)
 
(451 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:US Navy 100714-N-3852A-118 Hull Systems Technician monitors nitrogen tank.jpg|220px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Bispo-Silva Geosciences23 13-11.png|240px]]</div>
'''[[ISO/IEC 17025]]''' is an [[International Organization for Standardization]] (ISO) standard used by testing and calibration laboratories to provide a basis for accreditation of laboratory quality systems. There are many commonalities with the [[ISO 9000]] family of standards, but ISO/IEC 17025 adds in the concept of competence to the equation, applying directly to those organizations that produce testing and calibration results.
'''"[[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]"'''


ISO/IEC 17025:1999 was issued by the ISO in late 1999 and was internationally adopted in 2000. A second release was made on May 12, 2005 after it was agreed that it needed to have its wording more closely aligned with the 2000 version of ISO 9001. The most significant changes introduced greater emphasis on the responsibilities of senior management, as well as explicit requirements for continual improvement of the management system itself, particularly communication with the customer.
[[Chromatography|Chromatographic]] oil analysis is an important step for the identification of biodegraded petroleum via peak visualization and interpretation of phenomena that explain the oil geochemistry. However, analyses of chromatogram components by geochemists are comparative, visual, and consequently slow. This article aims to improve the chromatogram analysis process performed during geochemical interpretation by proposing the use of [[convolutional neural network]]s (CNN), which are deep learning techniques widely used by big tech companies. Two hundred and twenty-one (221) chromatographic oil images from different worldwide basins (Brazil, USA, Portugal, Angola, and Venezuela) were used. The [[open-source software]] Orange Data Mining was used to process images by CNN. The CNN algorithm extracts, pixel by pixel, recurring features from the images through convolutional operations ... ('''[[Journal:Geochemical biodegraded oil classification using a machine learning approach|Full article...]]''')<br />
 
''Recently featured'':
The ISO/IEC 17025 standard itself comprises five elements: scope, normative references, terms and definitions, management requirements, and technical requirements. In particular the management and technical requirements are the most important sections, with the management requirement section detailing the operation and effectiveness of the quality management system within the laboratory and the technical requirements section detailing the factors which determine the correctness and reliability of the tests and calibrations performed in laboratory. ('''[[ISO/IEC 17025|Full article...]]''')<br />
{{flowlist |
<br />
* [[Journal:Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study|Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study]]
''Recently featured'': [[Good Automated Manufacturing Practice]], [[End-stage renal disease facility]], [[Genome informatics]]
* [[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]
* [[Journal:Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems|Why do we need food systems informatics? Introduction to this special collection on smart and connected regional food systems]]
}}

Latest revision as of 13:37, 13 May 2024

Fig1 Bispo-Silva Geosciences23 13-11.png

"Geochemical biodegraded oil classification using a machine learning approach"

Chromatographic oil analysis is an important step for the identification of biodegraded petroleum via peak visualization and interpretation of phenomena that explain the oil geochemistry. However, analyses of chromatogram components by geochemists are comparative, visual, and consequently slow. This article aims to improve the chromatogram analysis process performed during geochemical interpretation by proposing the use of convolutional neural networks (CNN), which are deep learning techniques widely used by big tech companies. Two hundred and twenty-one (221) chromatographic oil images from different worldwide basins (Brazil, USA, Portugal, Angola, and Venezuela) were used. The open-source software Orange Data Mining was used to process images by CNN. The CNN algorithm extracts, pixel by pixel, recurring features from the images through convolutional operations ... (Full article...)
Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=63551"