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<title>Volume 16, Issue 9 (2020) | Journal of Computer Science</title>
<description>Volume 16, Issue 9 (2020) | Journal of Computer Science</description>
<link>https://thescipub.com/jcs/issue/1254</link>
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    <title><![CDATA[Rule-Based Approach to Detect IoT Malicious Files]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1203.1211</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 15 October 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1203.1211">doi:10.3844/jcssp.2020.1203.1211</a></p>The current immersive increase of cyber-attacks requires constant evolution of the used security solutions. Current malware detection solutions are only able to identify known malwares that were previ...]]></content:encoded>
    <dc:title><![CDATA[Rule-Based Approach to Detect IoT Malicious Files]]></dc:title><dc:creator>Faisal  Alsattam</dc:creator><dc:creator>Mousa  Al-Akhras</dc:creator><dc:creator>Marwah M. Almasri</dc:creator><dc:creator>Mohammed  Alawairdhi</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1203.1211</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-10-15; | doi:10.3844/jcssp.2020.1203.1211</dc:source>
    <dc:date>2020-10-15</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1203.1211</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1203.1211</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1212.1219">
    <title><![CDATA[Harmonic Mean Projection Shape Transform for Leaf Classification]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1212.1219</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 13 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1212.1219">doi:10.3844/jcssp.2020.1212.1219</a></p>Shape feature extraction has emerged as an important part of computer vision and image processing applications. Identification of shape objects in huge data based on shape similarity still remains a c...]]></content:encoded>
    <dc:title><![CDATA[Harmonic Mean Projection Shape Transform for Leaf Classification]]></dc:title><dc:creator>Sophia Jamila Zahra</dc:creator><dc:creator>Riza  Sulaiman</dc:creator><dc:creator>Seyed M.M. Kahaki</dc:creator><dc:creator>Anton Satria Prabuwono</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1212.1219</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-13; | doi:10.3844/jcssp.2020.1212.1219</dc:source>
    <dc:date>2020-09-13</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1212.1219</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1212.1219</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1220.1228">
    <title><![CDATA[Conjugate Gradient ‎Method: A Developed Version to Resolve Unconstrained Optimization Problems]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1220.1228</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 18 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1220.1228">doi:10.3844/jcssp.2020.1220.1228</a></p>One of the important methods that are widely utilized to resolve ‎unconstrained ‎optimization problems is the Conjugate Gradient (CG) method. This paper aims to propose a new version of the CG met...]]></content:encoded>
    <dc:title><![CDATA[Conjugate Gradient ‎Method: A Developed Version to Resolve Unconstrained Optimization Problems]]></dc:title><dc:creator>Ahmad  Alhawarat</dc:creator><dc:creator>Nguyen-Thoi  Trung</dc:creator><dc:creator>Zabidin  Salleh</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1220.1228</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-18; | doi:10.3844/jcssp.2020.1220.1228</dc:source>
    <dc:date>2020-09-18</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1220.1228</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1220.1228</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1229.1236">
    <title><![CDATA[Spherical Object Tracking using Von Mises-Fisher Distribution in Catadioptric System]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1229.1236</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 20 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1229.1236">doi:10.3844/jcssp.2020.1229.1236</a></p>Tracking objects on video sequences is a very challenging task in computer vision applications. However, there is few articles that deal with this topic in catadioptric vision. This paper describes a ...]]></content:encoded>
    <dc:title><![CDATA[Spherical Object Tracking using Von Mises-Fisher Distribution in Catadioptric System]]></dc:title><dc:creator>Khald  Anisse</dc:creator><dc:creator>Radgui  Amina</dc:creator><dc:creator>Rziza  Mohamed</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1229.1236</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-20; | doi:10.3844/jcssp.2020.1229.1236</dc:source>
    <dc:date>2020-09-20</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1229.1236</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1229.1236</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1237.1249">
    <title><![CDATA[Detection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding Algorithm]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1237.1249</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 21 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1237.1249">doi:10.3844/jcssp.2020.1237.1249</a></p>In the field of agricultural information, the plant leaf disease detection is highly important for both farmer life and environment. To improve the accuracy of plant leaf disease detection and reduce ...]]></content:encoded>
    <dc:title><![CDATA[Detection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding Algorithm]]></dc:title><dc:creator>Kittipol  Wisaeng</dc:creator><dc:creator>Worawat  Sa–Ngiamvibool</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1237.1249</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-21; | doi:10.3844/jcssp.2020.1237.1249</dc:source>
    <dc:date>2020-09-21</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1237.1249</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1237.1249</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1250.1257">
    <title><![CDATA[A Framework for Real-Time Healthcare System Performance in Developing Countries]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1250.1257</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 24 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1250.1257">doi:10.3844/jcssp.2020.1250.1257</a></p>This study proposes a conceptual structure for the success of the real-time healthcare program in developing countries. Whilst developing and some developed countries face a significant challenge in a...]]></content:encoded>
    <dc:title><![CDATA[A Framework for Real-Time Healthcare System Performance in Developing Countries]]></dc:title><dc:creator>Razi  Ahmed</dc:creator><dc:creator>Eiad  Yafi</dc:creator><dc:creator>Mazliham Mohd Su’ud</dc:creator><dc:creator>Muhammad Mansoor Alam</dc:creator><dc:creator>Muhammad  Faizan</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1250.1257</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-24; | doi:10.3844/jcssp.2020.1250.1257</dc:source>
    <dc:date>2020-09-24</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1250.1257</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1250.1257</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1258.1267">
    <title><![CDATA[Sentiment Analysis of Arabic Reviews for Saudi Hotels Using Unsupervised Machine Learning]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1258.1267</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 25 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1258.1267">doi:10.3844/jcssp.2020.1258.1267</a></p>Virtual worlds such as social networking sites, blogs and content communities are extremely becoming one of the most powerful sources for news, markets, industries etc. These virtual worlds can be use...]]></content:encoded>
    <dc:title><![CDATA[Sentiment Analysis of Arabic Reviews for Saudi Hotels Using Unsupervised Machine Learning]]></dc:title><dc:creator>Samar  Alosaimi</dc:creator><dc:creator>Maram  Alharthi</dc:creator><dc:creator>Khloud  Alghamdi</dc:creator><dc:creator>Tahani  Alsubait</dc:creator><dc:creator>Tahani  Alqurashi</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1258.1267</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-25; | doi:10.3844/jcssp.2020.1258.1267</dc:source>
    <dc:date>2020-09-25</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1258.1267</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1258.1267</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1268.1277">
    <title><![CDATA[Prediction of Data Traffic in Telecom Networks based on Deep Neural Networks]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1268.1277</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 30 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1268.1277">doi:10.3844/jcssp.2020.1268.1277</a></p>Accurate prediction of data traffic in telecom network is a challenging task for a better network management. It advances dynamic resource allocation and power management. This study employs deep neur...]]></content:encoded>
    <dc:title><![CDATA[Prediction of Data Traffic in Telecom Networks based on Deep Neural Networks]]></dc:title><dc:creator>Quang Hung Do</dc:creator><dc:creator>Thi Thanh Hang Doan</dc:creator><dc:creator>Thi Van Anh Nguyen</dc:creator><dc:creator>Nguyen Tung Duong</dc:creator><dc:creator>Vu Van Linh</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1268.1277</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-30; | doi:10.3844/jcssp.2020.1268.1277</dc:source>
    <dc:date>2020-09-30</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1268.1277</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1268.1277</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1278.1290">
    <title><![CDATA[A Time Series Forecasting for the Cumulative Confirmed and Critical Cases of the Covid-19 Pandemic in Saudi Arabia using Autoregressive Integrated Moving Average (ARIMA) Model]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1278.1290</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 30 September 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1278.1290">doi:10.3844/jcssp.2020.1278.1290</a></p>Reviews at present, different machine learning techniques and algorithms have been applied for predicting significant factors of the Coronavirus Disease-2019 (COVID-19) such as the outbreak and diagno...]]></content:encoded>
    <dc:title><![CDATA[A Time Series Forecasting for the Cumulative Confirmed and Critical Cases of the Covid-19 Pandemic in Saudi Arabia using Autoregressive Integrated Moving Average (ARIMA) Model]]></dc:title><dc:creator>Samer H. Atawneh</dc:creator><dc:creator>Osamah A.M. Ghaleb</dc:creator><dc:creator>Ahmad MohdAziz Hussein</dc:creator><dc:creator>Mohammad  Al-Madi</dc:creator><dc:creator>Bilal  Shehabat</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1278.1290</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-09-30; | doi:10.3844/jcssp.2020.1278.1290</dc:source>
    <dc:date>2020-09-30</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1278.1290</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1278.1290</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1291.1305">
    <title><![CDATA[Covid-19 Global Spread Analyzer: An ML-Based Attempt]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1291.1305</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 2 October 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1291.1305">doi:10.3844/jcssp.2020.1291.1305</a></p>The novel Coronavirus 2019 (COVID-19) has caused a pandemic disease over 200 countries, influencing billions of humans. In this consequence, it is very much essential to the identify factors that corr...]]></content:encoded>
    <dc:title><![CDATA[Covid-19 Global Spread Analyzer: An ML-Based Attempt]]></dc:title><dc:creator>Rana Husni Al Mahmoud</dc:creator><dc:creator>Eman  Omar</dc:creator><dc:creator>Khaled  Taha</dc:creator><dc:creator>Mahmoud  Al-Sharif</dc:creator><dc:creator>Abdullah  Aref</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1291.1305</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-10-02; | doi:10.3844/jcssp.2020.1291.1305</dc:source>
    <dc:date>2020-10-02</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1291.1305</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1291.1305</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1306.1318">
    <title><![CDATA[Preliminary Analysis of Malware Detection in Opcode Sequences within IoT Environment]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1306.1318</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 5 October 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1306.1318">doi:10.3844/jcssp.2020.1306.1318</a></p>With the technological development and means of communication, the Internet of Things (IoT) has become an essential role in providing many services in daily life through millions of heterogeneous but ...]]></content:encoded>
    <dc:title><![CDATA[Preliminary Analysis of Malware Detection in Opcode Sequences within IoT Environment]]></dc:title><dc:creator>Firas Shihab Ahmed</dc:creator><dc:creator>Norwati  Mustapha</dc:creator><dc:creator>Aida  Mustapha</dc:creator><dc:creator>Mohsen  Kakavand</dc:creator><dc:creator>Cik Feresa Mohd Foozy</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1306.1318</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-10-05; | doi:10.3844/jcssp.2020.1306.1318</dc:source>
    <dc:date>2020-10-05</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1306.1318</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1306.1318</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1319.1324">
    <title><![CDATA[Algorithm for Compressing/Decompressing Sudoku Grids]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1319.1324</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 3 October 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1319.1324">doi:10.3844/jcssp.2020.1319.1324</a></p>We describe a way to transfer efficiently Sudoku grids through the Internet. This is done by using linearization together with compression and decompression that use the information structure present ...]]></content:encoded>
    <dc:title><![CDATA[Algorithm for Compressing/Decompressing Sudoku Grids]]></dc:title><dc:creator>Zhivko  Nedev</dc:creator><dc:creator>Murtala Adamu Zungeru</dc:creator><dc:creator>Suykhun  Khov</dc:creator><dc:creator>Daravisal  Dy</dc:creator><dc:creator>Kimkhung  Sov</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1319.1324</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-10-03; | doi:10.3844/jcssp.2020.1319.1324</dc:source>
    <dc:date>2020-10-03</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1319.1324</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1319.1324</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2020.1325.1333">
    <title><![CDATA[IoT-Fog based Smart-Building Security System Design and Performance Evaluation]]></title>
    <link>https://thescipub.com/jcs/jcssp.2020.1325.1333</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 3 October 2020; <a href="https://thescipub.com/jcs/jcssp.2020.1325.1333">doi:10.3844/jcssp.2020.1325.1333</a></p>This paper aims to develop a smart building-security system utilizing fog technology. Fog computing is an innovative solution to reduce latency and network congestion, in which the cloud is extended t...]]></content:encoded>
    <dc:title><![CDATA[IoT-Fog based Smart-Building Security System Design and Performance Evaluation]]></dc:title><dc:creator>Maha  Medhat</dc:creator><dc:creator>Khaled  El-Shafey</dc:creator><dc:creator>Ali  Rashed</dc:creator><dc:identifier>doi:10.3844/jcssp.2020.1325.1333</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2020-10-03; | doi:10.3844/jcssp.2020.1325.1333</dc:source>
    <dc:date>2020-10-03</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2020.1325.1333</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2020.1325.1333</prism:url>
    </item></rdf:RDF>