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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:US-DeptOfHHS-Logo.svg|180px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Bispo-Silva Geosciences23 13-11.png|240px]]</div>
The '''[[United States Department of Health and Human Services]]''' ('''HHS'''), also known as the '''Health Department''', is a cabinet-level department of the Federal government of the United States with the goal of protecting the health of all Americans and providing essential human services. Its motto is "Improving the health, safety, and well-being of America". Before the separate federal Department of Education was created in 1979, it was called the Department of Health, Education, and Welfare (HEW).
'''"[[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]"'''


HHS is administered by the Secretary of Health and Human Services, who is appointed by the President with the advice and consent of the Senate. The United States Public Health Service (PHS) is the main division of the HHS and is led by the Assistant Secretary for Health. The current Secretary, Kathleen Sebelius is the Vice-Chair of the United States Interagency Council on Homelessness. The Department of Health and Human Services is a member of the Council, which is dedicated to preventing and ending homelessness in America.
[[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'':
As of May 2013, CMS administers 115 programs over 11 operating divisions, including the [[Centers for Disease Control and Prevention]] (CDC), the [[Centers for Medicare and Medicaid Services]] (CMS), and the [[National Institutes of Health]] (NIH). ('''[[United States Department of Health and Human Services|Full article...]]''')<br />
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* [[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'': [[Bioimage informatics]], [[Biobank]], [[Translational research]]
* [[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]]
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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...)
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