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<title>Volume 21, Issue 7 (2025) | Journal of Computer Science</title>
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    <title><![CDATA[Review of Fault Tolerance, Replication, and Fragmentation in Grid-Cloud Distributed Systems]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 7 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1490.1503">doi:10.3844/jcssp.2025.1490.1503</a></p>The study investigates key aspects of data management in distributed systems, focusing on fragmentation, replication and fault tolerance. With the increasing complexity of modern applications, efficie...]]></content:encoded>
    <dc:title><![CDATA[Review of Fault Tolerance, Replication, and Fragmentation in Grid-Cloud Distributed Systems]]></dc:title><dc:creator>Mohammed Adam Kunna Azrag</dc:creator><dc:creator>Mohammed Adam Kunna Azrag</dc:creator><dc:creator>Mohammed Adam Kunna Azrag</dc:creator><dc:creator>Noraziah  Ahmad</dc:creator><dc:creator>Nurzety A. Azuan</dc:creator><dc:creator>Zarina  Mohamad</dc:creator><dc:creator>Julius Beneoluchi Odili</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1490.1503</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-07; | doi:10.3844/jcssp.2025.1490.1503</dc:source>
    <dc:date>2025-07-07</dc:date>
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    <title><![CDATA[Empirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction Modelling]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1504.1511</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 8 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1504.1511">doi:10.3844/jcssp.2025.1504.1511</a></p>Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convol...]]></content:encoded>
    <dc:title><![CDATA[Empirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction Modelling]]></dc:title><dc:creator>Steven  Matthew</dc:creator><dc:creator>Nur Afny Catur Andryani</dc:creator><dc:creator>    Rojali</dc:creator><dc:creator>Srie P. Gondokaryono</dc:creator><dc:creator>Srie P. Gondokaryono</dc:creator><dc:creator>Dedianto  Hidajat</dc:creator><dc:creator>Dedianto  Hidajat</dc:creator><dc:creator>July I. Rahardja</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1504.1511</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-08; | doi:10.3844/jcssp.2025.1504.1511</dc:source>
    <dc:date>2025-07-08</dc:date>
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    <prism:doi>10.3844/jcssp.2025.1504.1511</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1512.1525">
    <title><![CDATA[Enhancing Indoor Asset Tracking: IoT Integration and Machine Learning Approaches for Optimized Performance]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1512.1525</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 7 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1512.1525">doi:10.3844/jcssp.2025.1512.1525</a></p>Indoor asset tracking entails the surveillance and governance of the position and movement of tangible assets within enclosed spaces, including warehouses, hospitals, and workplaces. Indoor asset trac...]]></content:encoded>
    <dc:title><![CDATA[Enhancing Indoor Asset Tracking: IoT Integration and Machine Learning Approaches for Optimized Performance]]></dc:title><dc:creator>Rafiq Hamadamin Maulud</dc:creator><dc:creator>Sadegh Abdollah Aminifar</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1512.1525</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-07; | doi:10.3844/jcssp.2025.1512.1525</dc:source>
    <dc:date>2025-07-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1512.1525</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1526.1538">
    <title><![CDATA[Smart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine Learning]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1526.1538</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 7 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1526.1538">doi:10.3844/jcssp.2025.1526.1538</a></p>Agriculture will benefit greatly from efficient weather data sustainable management. Data can be utilized to schedule the prediction yield, crop growth, and irrigation. This paper collects real-time m...]]></content:encoded>
    <dc:title><![CDATA[Smart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine Learning]]></dc:title><dc:creator>Aishwarya V. Kadu</dc:creator><dc:creator>Kuraparthi  Tirumala V. Reddy</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1526.1538</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-07; | doi:10.3844/jcssp.2025.1526.1538</dc:source>
    <dc:date>2025-07-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1526.1538</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1539.1553">
    <title><![CDATA[Maintenance and Evolution Processes of Embedded Software: A Systematic Literature Review]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1539.1553</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 17 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1539.1553">doi:10.3844/jcssp.2025.1539.1553</a></p>The relevance of embedded systems has increased considerably due to industrial automation and the adoption of IoT and medical devices. This process demands the adaptation of software engineering techn...]]></content:encoded>
    <dc:title><![CDATA[Maintenance and Evolution Processes of Embedded Software: A Systematic Literature Review]]></dc:title><dc:creator>Aloysio Augusto Rabello de Carvalho</dc:creator><dc:creator>Luiz Eduardo Galvão Martins</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1539.1553</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-17; | doi:10.3844/jcssp.2025.1539.1553</dc:source>
    <dc:date>2025-07-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1539.1553</prism:doi>
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    <title><![CDATA[A Designing Framework for Ant Colony Algorithm for Managing Cognitive Insomnia]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1554.1564</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 7 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1554.1564">doi:10.3844/jcssp.2025.1554.1564</a></p>Insomnia, a condition characterized by poor sleep quality, significantly impacts cognitive function, mood, and overall well-being. Traditional treatments like medication and psychological therapies, w...]]></content:encoded>
    <dc:title><![CDATA[A Designing Framework for Ant Colony Algorithm for Managing Cognitive Insomnia]]></dc:title><dc:creator>Roqia  Rateb</dc:creator><dc:creator>Amal  Shorman</dc:creator><dc:creator>Ahmad Sami Al-Shamayleh</dc:creator><dc:creator>Areej  Alshorman</dc:creator><dc:creator>Laith H. Baniata</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1554.1564</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-07; | doi:10.3844/jcssp.2025.1554.1564</dc:source>
    <dc:date>2025-07-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1554.1564</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1565.1575">
    <title><![CDATA[Enhancing Quality of Service of Video Streaming Applications Over Vehicular Ad-Hoc Networks]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1565.1575</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 30 June 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1565.1575">doi:10.3844/jcssp.2025.1565.1575</a></p>Vehicular ad-hoc networks play quite an important role in communication as it is challenging to have communication across VANET nodes because of high mobility. Video streaming applications over ad-hoc...]]></content:encoded>
    <dc:title><![CDATA[Enhancing Quality of Service of Video Streaming Applications Over Vehicular Ad-Hoc Networks]]></dc:title><dc:creator>Pooja  Sharma</dc:creator><dc:creator>Ajay  Kaul</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1565.1575</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-06-30; | doi:10.3844/jcssp.2025.1565.1575</dc:source>
    <dc:date>2025-06-30</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1565.1575</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1576.1585">
    <title><![CDATA[MFQ: Network Bandwidth Utilization among Data Centers on Software Defi ned Network Using Multilevel-Feedback Queue]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1576.1585</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 29 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1576.1585">doi:10.3844/jcssp.2025.1576.1585</a></p>The growing complexity of network traffic patterns and congestion within data centers necessitate innovation in traditional network infrastructure. While advancements in storage, computing, and applic...]]></content:encoded>
    <dc:title><![CDATA[MFQ: Network Bandwidth Utilization among Data Centers on Software Defi ned Network Using Multilevel-Feedback Queue]]></dc:title><dc:creator>R  Shanthy</dc:creator><dc:creator>K  Sutha</dc:creator><dc:creator>J Emerson Raja</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1576.1585</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-29; | doi:10.3844/jcssp.2025.1576.1585</dc:source>
    <dc:date>2025-07-29</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1576.1585</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1586.1593">
    <title><![CDATA[Leveraging Computational Models to Analyze the Impact of Co-Branding on Brand Equity and Consumer Loyalty Across Generations]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1586.1593</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 11 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1586.1593">doi:10.3844/jcssp.2025.1586.1593</a></p>This study examines the effect of co-branding on brand equity and consumer loyalty in the Indonesian cosmetics sector, specifically analyzing the partnership between Mizzu, a cosmetics brand, and Khon...]]></content:encoded>
    <dc:title><![CDATA[Leveraging Computational Models to Analyze the Impact of Co-Branding on Brand Equity and Consumer Loyalty Across Generations]]></dc:title><dc:creator>Yana  Erlyana</dc:creator><dc:creator>Yana  Erlyana</dc:creator><dc:creator>Lim Jing Yi</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1586.1593</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-11; | doi:10.3844/jcssp.2025.1586.1593</dc:source>
    <dc:date>2025-07-11</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1586.1593</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1594.1605">
    <title><![CDATA[Hybrid SIFT-DCT Approach for Face Matching of BuddhaStatues: Addressing Negative Similarity Metrics with SHashing]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1594.1605</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 29 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1594.1605">doi:10.3844/jcssp.2025.1594.1605</a></p>Art and cultural heritage rely on image processing techniques forpreservation and analysis. A key challenge in this study is accuratelydetecting highly similar Buddha faces despite variations in light...]]></content:encoded>
    <dc:title><![CDATA[Hybrid SIFT-DCT Approach for Face Matching of BuddhaStatues: Addressing Negative Similarity Metrics with SHashing]]></dc:title><dc:creator>Linda   Marlinda</dc:creator><dc:creator>Linda   Marlinda</dc:creator><dc:creator>Fikri   Budiman</dc:creator><dc:creator>Ruri Suko Basuki</dc:creator><dc:creator>Ahmad Zainul Fanani</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1594.1605</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-29; | doi:10.3844/jcssp.2025.1594.1605</dc:source>
    <dc:date>2025-07-29</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1594.1605</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1606.1612">
    <title><![CDATA[Based Approach to Improve the All-Pair Shortest Path Computation]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1606.1612</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 30 June 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1606.1612">doi:10.3844/jcssp.2025.1606.1612</a></p>This paper presents the development of a centralized algorithm for finding the shortest path between all pairs of vertices on a graph, utilizing the basic structure of the Floyd-Warshall sequential al...]]></content:encoded>
    <dc:title><![CDATA[Based Approach to Improve the All-Pair Shortest Path Computation]]></dc:title><dc:creator>Lau Nguyen Dinh</dc:creator><dc:creator>Le Thanh Tuan</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1606.1612</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-06-30; | doi:10.3844/jcssp.2025.1606.1612</dc:source>
    <dc:date>2025-06-30</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1606.1612</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1613.1620">
    <title><![CDATA[Anomaly Detection Based on Vision Transformer Model and Texture Features]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1613.1620</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 10 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1613.1620">doi:10.3844/jcssp.2025.1613.1620</a></p>Anomaly detection is one of the video surveillance applications,which aims to detect and analyze abnormal behaviors and risky situations inorder to prevent accidents. Various deep learning models have...]]></content:encoded>
    <dc:title><![CDATA[Anomaly Detection Based on Vision Transformer Model and Texture Features]]></dc:title><dc:creator>Mohammed   Lahraichi</dc:creator><dc:creator>Abdelhafid   Berroukham</dc:creator><dc:creator>Khalid   Housni</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1613.1620</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-10; | doi:10.3844/jcssp.2025.1613.1620</dc:source>
    <dc:date>2025-07-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1613.1620</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1621.1636">
    <title><![CDATA[Optimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer Classification]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1621.1636</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 17 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1621.1636">doi:10.3844/jcssp.2025.1621.1636</a></p>Breast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classificat...]]></content:encoded>
    <dc:title><![CDATA[Optimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer Classification]]></dc:title><dc:creator>Satyabrata   Patro</dc:creator><dc:creator>Satyabrata   Patro</dc:creator><dc:creator>Jyotirmaya   Mishra</dc:creator><dc:creator>Bhavani Sankar Panda</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1621.1636</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-17; | doi:10.3844/jcssp.2025.1621.1636</dc:source>
    <dc:date>2025-07-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1637.1650">
    <title><![CDATA[Towards a Human-Like AGI Architecture: General Intelligence Framework (GIF)]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1637.1650</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 13 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1637.1650">doi:10.3844/jcssp.2025.1637.1650</a></p>Artificial Intelligence (AI) has achieved significant breakthroughs but remains limited by its specialization and inability to generalize across domains, unlike human cognition. Current models such as...]]></content:encoded>
    <dc:title><![CDATA[Towards a Human-Like AGI Architecture: General Intelligence Framework (GIF)]]></dc:title><dc:creator>Jiran Kurian Puliyanmakkal</dc:creator><dc:creator>Rohini   V</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1637.1650</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-13; | doi:10.3844/jcssp.2025.1637.1650</dc:source>
    <dc:date>2025-07-13</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1637.1650</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1637.1650</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1651.1661">
    <title><![CDATA[A Developed Version of Conjugate Gradient Method With a New Parameter for Dai-Liao Conjugacy Condition With an Application to Solar Panel]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1651.1661</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 15 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1651.1661">doi:10.3844/jcssp.2025.1651.1661</a></p>Conjugate Gradient (CG) methods are broadly employed in solving bigger-scale unconstrained optimization problems. Two famous methods are the Hestenes–Stiefel (HS) as well as Polak–Ribière–Poly...]]></content:encoded>
    <dc:title><![CDATA[A Developed Version of Conjugate Gradient Method With a New Parameter for Dai-Liao Conjugacy Condition With an Application to Solar Panel]]></dc:title><dc:creator>Ahmad   Alhawarat</dc:creator><dc:creator>Ramadan   Sabra</dc:creator><dc:creator>Mehiddin   Al-Baali</dc:creator><dc:creator>Hamid   El Hor</dc:creator><dc:creator>Shahrina   Ismail</dc:creator><dc:creator>Shahrina   Ismail</dc:creator><dc:creator>Ali   Jaradat</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1651.1661</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-15; | doi:10.3844/jcssp.2025.1651.1661</dc:source>
    <dc:date>2025-07-15</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1651.1661</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1651.1661</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1662.1676">
    <title><![CDATA[Predicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature Selection]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1662.1676</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 17 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1662.1676">doi:10.3844/jcssp.2025.1662.1676</a></p>This Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, ...]]></content:encoded>
    <dc:title><![CDATA[Predicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature Selection]]></dc:title><dc:creator>Ashwini   S.</dc:creator><dc:creator>Minu   R. I.</dc:creator><dc:creator>Jeevan   Kumar</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1662.1676</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-17; | doi:10.3844/jcssp.2025.1662.1676</dc:source>
    <dc:date>2025-07-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1662.1676</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1662.1676</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1677.1687">
    <title><![CDATA[Sparse Partial Optimal Transport via Quadratic Regularization]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1677.1687</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 17 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1677.1687">doi:10.3844/jcssp.2025.1677.1687</a></p>Partial Optimal Transport (POT) has recently emerged as a central tool in various Machine Learning (ML) applications. It lifts the stringent assumption of the conventional Optimal Transport (OT) that ...]]></content:encoded>
    <dc:title><![CDATA[Sparse Partial Optimal Transport via Quadratic Regularization]]></dc:title><dc:creator>Khang   Tran</dc:creator><dc:creator>Khoa   Nguyen</dc:creator><dc:creator>Anh   Nguyen</dc:creator><dc:creator>Thong   Huynh</dc:creator><dc:creator>Son   Pham</dc:creator><dc:creator>Sy-Hoang   Nguyen-Dang</dc:creator><dc:creator>Manh   Pham</dc:creator><dc:creator>Manh   Pham</dc:creator><dc:creator>Bang   Vo</dc:creator><dc:creator>Mai Ngoc   Tran</dc:creator><dc:creator>Mai Ngoc Tran</dc:creator><dc:creator>Dung   Luong</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1677.1687</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-17; | doi:10.3844/jcssp.2025.1677.1687</dc:source>
    <dc:date>2025-07-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1677.1687</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1677.1687</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1688.1704">
    <title><![CDATA[Enhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated Learning]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1688.1704</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 18 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1688.1704">doi:10.3844/jcssp.2025.1688.1704</a></p>The escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billi...]]></content:encoded>
    <dc:title><![CDATA[Enhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated Learning]]></dc:title><dc:creator>Shahad   Alahmari</dc:creator><dc:creator>Noura   Aleisa</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1688.1704</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-18; | doi:10.3844/jcssp.2025.1688.1704</dc:source>
    <dc:date>2025-07-18</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1688.1704</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1688.1704</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1705.1718">
    <title><![CDATA[Predicting CO<sub>2</sub> Emissions Using Multivariate Regression: Assessing the Impact of Pandemics and Industrial Revolutions]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1705.1718</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 23 July 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1705.1718">doi:10.3844/jcssp.2025.1705.1718</a></p>This paper explores the prediction of CO2 emissions usingMultivariate Regression models, incorporating the influence of significanthistorical events such as pandemics and industrial revolutions. While...]]></content:encoded>
    <dc:title><![CDATA[Predicting CO<sub>2</sub> Emissions Using Multivariate Regression: Assessing the Impact of Pandemics and Industrial Revolutions]]></dc:title><dc:creator>Youssef   Mekki</dc:creator><dc:creator>Chouaib   Moujahdi</dc:creator><dc:creator>Noureddine   Assad</dc:creator><dc:creator>Aziz   Dahbi</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1705.1718</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-07-23; | doi:10.3844/jcssp.2025.1705.1718</dc:source>
    <dc:date>2025-07-23</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1705.1718</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1705.1718</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2025.1719.1740">
    <title><![CDATA[Cloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird  Optimization-Based Optimal Key Generation]]></title>
    <link>https://thescipub.com/jcs/jcssp.2025.1719.1740</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 20 August 2025; <a href="https://thescipub.com/jcs/jcssp.2025.1719.1740">doi:10.3844/jcssp.2025.1719.1740</a></p>Maintaining privacy in the cloud is critical, which implies reliable and effective models that are adapted to the difficulties presented by cloud settings. This paper introduces a comprehensive privac...]]></content:encoded>
    <dc:title><![CDATA[Cloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird  Optimization-Based Optimal Key Generation]]></dc:title><dc:creator> Smita   Sharma</dc:creator><dc:creator>Sanjay   Tyagi</dc:creator><dc:identifier>doi:10.3844/jcssp.2025.1719.1740</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2025-08-20; | doi:10.3844/jcssp.2025.1719.1740</dc:source>
    <dc:date>2025-08-20</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2025.1719.1740</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2025.1719.1740</prism:url>
    </item></rdf:RDF>