<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:prism="http://prismstandard.org/namespaces/basic/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/"
xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns="http://purl.org/rss/1.0/" xmlns:admin="http://webns.net/mvcb/">
<channel rdf:about="https://thescipub.com/feed/jcs/issue-1368.rss">
<title>Volume 18, Issue 9 (2022) | Journal of Computer Science</title>
<description>Volume 18, Issue 9 (2022) | Journal of Computer Science</description>
<link>https://thescipub.com/jcs/issue/1368</link>
<admin:generatorAgent rdf:resource="https://thescipub.com/"/>
<admin:errorReportsTo rdf:resource="mailto:support@thescipub.com"/>
<dc:publisher>Science Publications</dc:publisher>
<dc:language>en</dc:language>
<prism:publicationName>Science Publications</prism:publicationName>
<items>
<rdf:Seq>
<rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.792.800"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.801.810"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.811.820"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.821.831"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.832.840"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.841.851"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.852.859"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.860.867"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.868.876"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.877.884"/></rdf:Seq>
</items>
</channel><item rdf:about="https://thescipub.com/jcs/jcssp.2022.792.800">
    <title><![CDATA[Boosting Arabic Named Entity Recognition with K-Fold Cross Validation on LSTM and Bi-LSTM Models ]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.792.800</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 6 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.792.800">doi:10.3844/jcssp.2022.792.800</a></p>Named-Entity-Recognition(NER) is one of the most important Information-Extraction (IE) use cases, whichis used to improve the performance of Natural Languages Processing (NLP) tasks,such as Relation-E...]]></content:encoded>
    <dc:title><![CDATA[Boosting Arabic Named Entity Recognition with K-Fold Cross Validation on LSTM and Bi-LSTM Models ]]></dc:title><dc:creator>Hamid Sadeq Mahdi Alsultani</dc:creator><dc:creator>Ahmed H. Aliwy</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.792.800</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-06; | doi:10.3844/jcssp.2022.792.800</dc:source>
    <dc:date>2022-09-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.792.800</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.792.800</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.801.810">
    <title><![CDATA[A Scalable Big Data Framework for Real-Time Traffic Monitoring System]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.801.810</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 7 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.801.810">doi:10.3844/jcssp.2022.801.810</a></p>Inthis study, a scalable and real-time intelligent transportation system based ona big data framework is presented. The proposed system allows for the use ofexisting data from road sensors to better u...]]></content:encoded>
    <dc:title><![CDATA[A Scalable Big Data Framework for Real-Time Traffic Monitoring System]]></dc:title><dc:creator>Wilfried Yves Hamilton Adoni</dc:creator><dc:creator>Wilfried Yves Hamilton Adoni</dc:creator><dc:creator>Najib Ben Aoun</dc:creator><dc:creator>Najib Ben Aoun</dc:creator><dc:creator>Tarik  Nahhal</dc:creator><dc:creator>Moez  Krichen</dc:creator><dc:creator>Moez  Krichen</dc:creator><dc:creator>Mohammed Y. Alzahrani</dc:creator><dc:creator>Franck Kalala Mutombo</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.801.810</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-07; | doi:10.3844/jcssp.2022.801.810</dc:source>
    <dc:date>2022-09-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.801.810</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.801.810</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.811.820">
    <title><![CDATA[Third-Party Logistic Selection for Logistic Aggregator Company using Multi-Criteria Decision Making]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.811.820</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 9 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.811.820">doi:10.3844/jcssp.2022.811.820</a></p>The customer of AggregatorCompany for Logistics (ACL) faces a problem when creating an order in the aggregatorlogistics platform. They have difficulty making an order as there are a lot ofthird-Party ...]]></content:encoded>
    <dc:title><![CDATA[Third-Party Logistic Selection for Logistic Aggregator Company using Multi-Criteria Decision Making]]></dc:title><dc:creator>Muhammad Khakim Hidayad</dc:creator><dc:creator>Ditdit Nugeraha Utama</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.811.820</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-09; | doi:10.3844/jcssp.2022.811.820</dc:source>
    <dc:date>2022-09-09</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.811.820</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.811.820</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.821.831">
    <title><![CDATA[A Backward Regressed Capsule Neural Network for Plant Leaf Disease Detection]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.821.831</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 8 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.821.831">doi:10.3844/jcssp.2022.821.831</a></p>This study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredo...]]></content:encoded>
    <dc:title><![CDATA[A Backward Regressed Capsule Neural Network for Plant Leaf Disease Detection]]></dc:title><dc:creator>Jennifer  Jepkoech</dc:creator><dc:creator>Benson Kipkemboi Kenduiywo</dc:creator><dc:creator>David Muchangi Mugo</dc:creator><dc:creator>Edna Chebet Tool</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.821.831</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-08; | doi:10.3844/jcssp.2022.821.831</dc:source>
    <dc:date>2022-09-08</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.821.831</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.821.831</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.832.840">
    <title><![CDATA[Psychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML Approach]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.832.840</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 14 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.832.840">doi:10.3844/jcssp.2022.832.840</a></p>In the era of the COVID-19 epidemic, governmentshave imposed nationwide lockdowns, which make a huge change to people's dailyroutines. This last impacts indirectly the well-being of people's mentalhea...]]></content:encoded>
    <dc:title><![CDATA[Psychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML Approach]]></dc:title><dc:creator>Maryame  Naji</dc:creator><dc:creator>Najima  Daoudi</dc:creator><dc:creator>Rachida  Ajhoun</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.832.840</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-14; | doi:10.3844/jcssp.2022.832.840</dc:source>
    <dc:date>2022-09-14</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.832.840</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.832.840</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.841.851">
    <title><![CDATA[Determination of Optimum Alloy Sample Size for Ball Mill Abrasion Test Through Automated t-Student Distribution Analysis]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.841.851</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 14 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.841.851">doi:10.3844/jcssp.2022.841.851</a></p>Inmaterial wear experiments, such as the Ball Mill Abrasion Test (BMAT), it iscrucial to know the number of specimens to be used in each experiment toproduce accurate and reliable results. In BMAT, ho...]]></content:encoded>
    <dc:title><![CDATA[Determination of Optimum Alloy Sample Size for Ball Mill Abrasion Test Through Automated t-Student Distribution Analysis]]></dc:title><dc:creator>Carlos Daniel Garcia Mendoza</dc:creator><dc:creator>Lelly María Useche Castro</dc:creator><dc:creator>Miguel Ángel Lapo Palacios</dc:creator><dc:creator>Óscar Vargas Ortiz</dc:creator><dc:creator>Ronny Javier Maldonado Macías</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.841.851</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-14; | doi:10.3844/jcssp.2022.841.851</dc:source>
    <dc:date>2022-09-14</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.841.851</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.841.851</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.852.859">
    <title><![CDATA[Design and Analysis of SRAM Cell for Smart Application ]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.852.859</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 17 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.852.859">doi:10.3844/jcssp.2022.852.859</a></p>In today's circuittechnology, power consumption and savings are key concerns. The driving reasonsbehind these innovations are portable devices that require high throughput andlow power dissipation, su...]]></content:encoded>
    <dc:title><![CDATA[Design and Analysis of SRAM Cell for Smart Application ]]></dc:title><dc:creator>Pushkar  Praveen</dc:creator><dc:creator>Rakesh Kumar Singh</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.852.859</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-17; | doi:10.3844/jcssp.2022.852.859</dc:source>
    <dc:date>2022-09-17</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.852.859</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.852.859</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.860.867">
    <title><![CDATA[Framework for Containers Orchestration to handle the Scientific Workloads using Kubernetes]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.860.867</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 19 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.860.867">doi:10.3844/jcssp.2022.860.867</a></p>Thelightweight nature of Operating System virtualization give birth to thecontainers, and their high efficiency for application deployment prefers itsusage in Cloud computing. Containers encapsulate a...]]></content:encoded>
    <dc:title><![CDATA[Framework for Containers Orchestration to handle the Scientific Workloads using Kubernetes]]></dc:title><dc:creator>Manish Kumar Abhishek</dc:creator><dc:creator>D. Rajeswara  Rao</dc:creator><dc:creator>K.  Subrahmanyam</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.860.867</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-19; | doi:10.3844/jcssp.2022.860.867</dc:source>
    <dc:date>2022-09-19</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.860.867</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.860.867</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.868.876">
    <title><![CDATA[An Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion Detection]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.868.876</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 21 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.868.876">doi:10.3844/jcssp.2022.868.876</a></p>NetworkIntrusion Detection Systems (NIDS) can protect computer networks and computersystems by detecting abnormal network packets and taking agreed action plans,such as notifying an administrator or r...]]></content:encoded>
    <dc:title><![CDATA[An Ensemble of Gaussian Mixture Model and Support Vector Machines for Network Intrusion Detection]]></dc:title><dc:creator>Olujimi Daniel Alao</dc:creator><dc:creator>Sheriff  Alimi</dc:creator><dc:creator>Shade Oluwakemi Kuyoro</dc:creator><dc:creator>Ruth Chinkata Amanze</dc:creator><dc:creator>Adesina Kamorudeen Adio</dc:creator><dc:creator>Michael Oluwagbenga Agbaje</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.868.876</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-21; | doi:10.3844/jcssp.2022.868.876</dc:source>
    <dc:date>2022-09-21</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.868.876</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.868.876</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.877.884">
    <title><![CDATA[Smart Certificate using Blockchain]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.877.884</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 26 September 2022; <a href="https://thescipub.com/jcs/jcssp.2022.877.884">doi:10.3844/jcssp.2022.877.884</a></p>Thestudent academic records maintained by the university system manually arevulnerable to easily being modified or tampered with. These academic records ofstudents are proof of the student's performan...]]></content:encoded>
    <dc:title><![CDATA[Smart Certificate using Blockchain]]></dc:title><dc:creator>Krishna Bihari Dubey</dc:creator><dc:creator>Mukta  Goyal</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.877.884</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-09-26; | doi:10.3844/jcssp.2022.877.884</dc:source>
    <dc:date>2022-09-26</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.877.884</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.877.884</prism:url>
    </item></rdf:RDF>