<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-1328.rss">
<title>Volume 18, Issue 1 (2022) | Journal of Computer Science</title>
<description>Volume 18, Issue 1 (2022) | Journal of Computer Science</description>
<link>https://thescipub.com/jcs/issue/1328</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.2022.1.17"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.18.25"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.26.32"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.33.41"/><rdf:li rdf:resource="https://thescipub.com/jcs/jcssp.2022.42.56"/></rdf:Seq>
</items>
</channel><item rdf:about="https://thescipub.com/jcs/jcssp.2022.1.17">
    <title><![CDATA[Smart Agriculture and Food Industry with Blockchain and Artificial Intelligence]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.1.17</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 14 January 2022; <a href="https://thescipub.com/jcs/jcssp.2022.1.17">doi:10.3844/jcssp.2022.1.17</a></p>Horticulture is one of the most major human exercises everywhere. Brilliant horticulture incorporates a bunch of advances, gadgets, conventions and computational ideal models to improve farming cycles...]]></content:encoded>
    <dc:title><![CDATA[Smart Agriculture and Food Industry with Blockchain and Artificial Intelligence]]></dc:title><dc:creator>N. Nasurudeen Ahamed</dc:creator><dc:creator>R.  Vignesh</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.1.17</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-01-14; | doi:10.3844/jcssp.2022.1.17</dc:source>
    <dc:date>2022-01-14</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.1.17</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.1.17</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.18.25">
    <title><![CDATA[Topic-Transformer for Document-Level Language Understanding]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.18.25</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 22 January 2022; <a href="https://thescipub.com/jcs/jcssp.2022.18.25">doi:10.3844/jcssp.2022.18.25</a></p>As long as natural language processing applications are considered prediction problems with insufficient context, usually referred to as a single sentence or paragraph, this does not reveal how humans...]]></content:encoded>
    <dc:title><![CDATA[Topic-Transformer for Document-Level Language Understanding]]></dc:title><dc:creator>Oumaima  Hourrane</dc:creator><dc:creator>El Habib Benlahmar</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.18.25</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-01-22; | doi:10.3844/jcssp.2022.18.25</dc:source>
    <dc:date>2022-01-22</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.18.25</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.18.25</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.26.32">
    <title><![CDATA[Graph Coloring Program of Exam Scheduling Modeling Based on Bitwise Coloring Algorithm Using Python]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.26.32</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 1 February 2022; <a href="https://thescipub.com/jcs/jcssp.2022.26.32">doi:10.3844/jcssp.2022.26.32</a></p>A graph coloring is the process of assigning labels to the vertices of a graph in such a way that no two adjacent vertices have the same color. The chromatic number of a graph G is the smallest number...]]></content:encoded>
    <dc:title><![CDATA[Graph Coloring Program of Exam Scheduling Modeling Based on Bitwise Coloring Algorithm Using Python]]></dc:title><dc:creator>Samsul  Arifin</dc:creator><dc:creator>Indra Bayu Muktyas</dc:creator><dc:creator>Wikky Fawwaz Al Maki</dc:creator><dc:creator>Mohd Khairul Bazli Mohd Aziz</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.26.32</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-02-01; | doi:10.3844/jcssp.2022.26.32</dc:source>
    <dc:date>2022-02-01</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.26.32</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.26.32</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.33.41">
    <title><![CDATA[Logic and the Mathematic Model of the Subject-Area Description for Corporate Information Systems]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.33.41</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 2 February 2022; <a href="https://thescipub.com/jcs/jcssp.2022.33.41">doi:10.3844/jcssp.2022.33.41</a></p>Aiming to build and receive a logic-mathematical substantiation and model of the process of constructing the description of any subject area for corporate information systems, the authors divided the ...]]></content:encoded>
    <dc:title><![CDATA[Logic and the Mathematic Model of the Subject-Area Description for Corporate Information Systems]]></dc:title><dc:creator>Konstantin Yurievich Maslenikov</dc:creator><dc:creator>Georgiy Ivanovich Revunkov</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.33.41</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-02-02; | doi:10.3844/jcssp.2022.33.41</dc:source>
    <dc:date>2022-02-02</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.33.41</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.33.41</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2022.42.56">
    <title><![CDATA[Efficient Utilization of Mirroring Servers Using Artificial Neural Networks]]></title>
    <link>https://thescipub.com/jcs/jcssp.2022.42.56</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 2 February 2022; <a href="https://thescipub.com/jcs/jcssp.2022.42.56">doi:10.3844/jcssp.2022.42.56</a></p>Due to the fact that an enormous amount of data is available to any user on the Internet, this leads to increased requests of Internet users to download or process their data among different servers. ...]]></content:encoded>
    <dc:title><![CDATA[Efficient Utilization of Mirroring Servers Using Artificial Neural Networks]]></dc:title><dc:creator>Radwan  Al-Shalalfa</dc:creator><dc:creator>Hazzaa  Alshareef</dc:creator><dc:creator>Azzam  Sleit</dc:creator><dc:creator>Mousa  Al-Akhras</dc:creator><dc:creator>Samah  Alhazmi</dc:creator><dc:identifier>doi:10.3844/jcssp.2022.42.56</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2022-02-02; | doi:10.3844/jcssp.2022.42.56</dc:source>
    <dc:date>2022-02-02</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2022.42.56</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2022.42.56</prism:url>
    </item></rdf:RDF>