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  <doi_batch_id>aspg-3-3450-1791419435</doi_batch_id>
  <timestamp>20261008003035</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>Fusion: Practice and Applications</full_title>
    <abbrev_title>FPA</abbrev_title>
    <issn media_type="print">2770-0070</issn>
    <issn media_type="electronic">2692-4048</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>18</volume>
    </journal_volume>
    <issue>1</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>CORRECTED VERSION: A System of Human Biometric-Fusion Authentication Security Improvement Using Hybrid Technique</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Salwa Mohammed</given_name>
      <surname>Nejrs</surname>
      <affiliations>
       <institution>
        <institution_name>University of Mustansiriya, College of Art, Baghdad, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Azmi Shawkat</given_name>
      <surname>Abdulbaqi</surname>
      <affiliations>
       <institution>
        <institution_name>Renewable Energy Research Center, University of Anbar, Ramadi, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>The collected information from the environment in WSN continuously sends from one node to another until it reaches the main collector or server, where processing is done. The transferred data volume will be greater when the network grows. Medical images will also contribute to network traffic. To alleviate this challenge, this research has developed an interlayer transmission protocol for WSNs. This protocol uses the construction of medical images with pixel-based data. In the analysis, a gray-scale medical image 512x512 in size, provided by Brain, is utilized. The image was compressed by the protocol from 256 KB to 192 KB with a percentage of 25%. As a result, the structural similarity index measure showed the SSIM at 51.1365, while the PSNR is at 0.9976; therefore, the quality of the medical image remains unchanged. The protocol uses the AES encryption method for strong data protection to improve security during transmission. Results show that this protocol reduces data transmission in WSNs by 12.5 to 25% without affecting the integrity of the medical image, which is indicative of the efficiency of the protocol in enhancing network performance while ensuring data safety.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>66</first_page>
     <last_page>75</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3450</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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     <doi>10.54216/FPA.180106</doi>
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