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    <title><![CDATA[A Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event Handling]]></title>
    <link>https://thescipub/abstract/jcssp.2026.747.765</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 5 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.747.765">doi:10.3844/jcssp.2026.747.765</a></p>Water replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compr...]]></content:encoded>
    <dc:title><![CDATA[A Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event Handling]]></dc:title><dc:creator>    Yaddarabullah</dc:creator><dc:creator>Inanpi Hidayati Sumiasih</dc:creator><dc:creator>Mutiara Dewi Puspitawati</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.747.765</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-05; | doi:10.3844/jcssp.2026.747.765</dc:source>
    <dc:date>2026-03-05</dc:date>
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    <title><![CDATA[LSTM-Based AI Model for Sinkhole Attack Detection With Legal Basis in an Ecuadorian Public Institution]]></title>
    <link>https://thescipub/abstract/jcssp.2026.766.777</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 4 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.766.777">doi:10.3844/jcssp.2026.766.777</a></p>Wireless Sensor Networks (WSN) are an essential component of the Internet of Things (IoT). However, their decentralized nature, data transmission over unencrypted channels, and the physical exposure o...]]></content:encoded>
    <dc:title><![CDATA[LSTM-Based AI Model for Sinkhole Attack Detection With Legal Basis in an Ecuadorian Public Institution]]></dc:title><dc:creator>Estefanía Alejandra Mora Parra</dc:creator><dc:creator>Rubén Nogales Portero</dc:creator><dc:creator>Moisés Toapanta T.</dc:creator><dc:creator>Estefanía Monge Martínez</dc:creator><dc:creator>Santiago Vayas Castro</dc:creator><dc:creator>Jeanette Elizabeth Jordán Buenaño</dc:creator><dc:creator>Juan Escobar Naranjo</dc:creator><dc:creator>Diego Gustavo Andrade Armas</dc:creator><dc:creator>Rodrigo Del Pozo Durango</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.766.777</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-04; | doi:10.3844/jcssp.2026.766.777</dc:source>
    <dc:date>2026-03-04</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.766.777</prism:doi>
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    <title><![CDATA[Edge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNN]]></title>
    <link>https://thescipub/abstract/jcssp.2026.787.799</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.787.799">doi:10.3844/jcssp.2026.787.799</a></p>Human Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote serve...]]></content:encoded>
    <dc:title><![CDATA[Edge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNN]]></dc:title><dc:creator>Suresh   Kumar</dc:creator><dc:creator>M Y. Mohamed Parvees</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.787.799</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-06; | doi:10.3844/jcssp.2026.787.799</dc:source>
    <dc:date>2026-03-06</dc:date>
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    <title><![CDATA[A Novel Time-Based Switch Migration Method (TSSM) for Load Balancing in Distributed Software-Defined Networking]]></title>
    <link>https://thescipub/abstract/jcssp.2026.800.812</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.800.812">doi:10.3844/jcssp.2026.800.812</a></p>Switch migration is predominantly used for workload balancing in distributed Software Defined Network (SDN) controllers. The Time-Sharing Switch Migration (TSSM) technique allowed the switch&#039;s re...]]></content:encoded>
    <dc:title><![CDATA[A Novel Time-Based Switch Migration Method (TSSM) for Load Balancing in Distributed Software-Defined Networking]]></dc:title><dc:creator>Thangaraj   E</dc:creator><dc:creator>Dinesh   K</dc:creator><dc:creator>Prabhakaran   Paulraj</dc:creator><dc:creator>A   Barkathulla</dc:creator><dc:creator>Margaret   Flora</dc:creator><dc:creator>Karthik   Elangovan</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.800.812</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-06; | doi:10.3844/jcssp.2026.800.812</dc:source>
    <dc:date>2026-03-06</dc:date>
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    <prism:doi>10.3844/jcssp.2026.800.812</prism:doi>
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    <title><![CDATA[Hybrid Deep Learning for Kidney Stone Detection in CT Scans With Noise Reduction and Feature Enhancement]]></title>
    <link>https://thescipub/abstract/jcssp.2026.813.825</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 10 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.813.825">doi:10.3844/jcssp.2026.813.825</a></p>The identification of kidney stones using CT scans is an essential but difficult effort in medical diagnostics, frequently obstructed by imaging noise and the complexity of manual interpretation. Alth...]]></content:encoded>
    <dc:title><![CDATA[Hybrid Deep Learning for Kidney Stone Detection in CT Scans With Noise Reduction and Feature Enhancement]]></dc:title><dc:creator>U. M. Fernandes Dimlo</dc:creator><dc:creator>Sreenu   Banoth</dc:creator><dc:creator>Priti   Bihade</dc:creator><dc:creator>Yahia   Mjery</dc:creator><dc:creator>K. Jayaram Kumar</dc:creator><dc:creator>Umanesan   R</dc:creator><dc:creator>A. Saran Kumar</dc:creator><dc:creator>V.   Bhoopathy</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.813.825</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-10; | doi:10.3844/jcssp.2026.813.825</dc:source>
    <dc:date>2026-03-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.813.825</prism:doi>
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    <title><![CDATA[IoT Anomaly Detection Using Picture Fuzzy Clustering Approach]]></title>
    <link>https://thescipub/abstract/jcssp.2026.826.839</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.826.839">doi:10.3844/jcssp.2026.826.839</a></p>Improving the effectiveness of security systems without slowing them down is a major challenge in cybersecurity. Many methods have been explored for detecting anomalous behaviour in network data, with...]]></content:encoded>
    <dc:title><![CDATA[IoT Anomaly Detection Using Picture Fuzzy Clustering Approach]]></dc:title><dc:creator>Fehmin Nadira Laskar</dc:creator><dc:creator>Vijo Arul Selvi M.</dc:creator><dc:creator>Fokrul Alom Mazarbhuiya</dc:creator><dc:creator>Mohamed   Shenify</dc:creator><dc:creator>Vijay   Prasad</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.826.839</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-06; | doi:10.3844/jcssp.2026.826.839</dc:source>
    <dc:date>2026-03-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.826.839</prism:doi>
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    <title><![CDATA[Chatbot for Academic Advising: Case Study at Saudi Electronic University]]></title>
    <link>https://thescipub/abstract/jcssp.2026.840.859</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 7 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.840.859">doi:10.3844/jcssp.2026.840.859</a></p>Student support solutions in higher education are evolving, with an increasing focus on making services more accessible and providing individual assistance. Chatbots are emerging as powerful tools for...]]></content:encoded>
    <dc:title><![CDATA[Chatbot for Academic Advising: Case Study at Saudi Electronic University]]></dc:title><dc:creator>Madawi Faisal Alsoyohi</dc:creator><dc:creator>Nahlah   Algethami</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.840.859</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-07; | doi:10.3844/jcssp.2026.840.859</dc:source>
    <dc:date>2026-03-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.840.859</prism:doi>
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    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.860.877">
    <title><![CDATA[Enhancing Video Tampering Detection Using Dynamic Temporal LSTM With Adaptive CNN]]></title>
    <link>https://thescipub/abstract/jcssp.2026.860.877</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 7 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.860.877">doi:10.3844/jcssp.2026.860.877</a></p>In the domain of information technology, video tampering detection has become hyper critical principally with the increase in deep fake as everyone is having affordable access to the internet. The lon...]]></content:encoded>
    <dc:title><![CDATA[Enhancing Video Tampering Detection Using Dynamic Temporal LSTM With Adaptive CNN]]></dc:title><dc:creator>Gurpreet Kour Khalsa</dc:creator><dc:creator>Rakesh   Ahuja</dc:creator><dc:creator>Rattan Deep Aneja </dc:creator><dc:identifier>doi:10.3844/jcssp.2026.860.877</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-07; | doi:10.3844/jcssp.2026.860.877</dc:source>
    <dc:date>2026-03-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.860.877</prism:doi>
    <prism:url>https://thescipub/abstract/jcssp.2026.860.877</prism:url>
    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.878.885">
    <title><![CDATA[Predictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning Techniques]]></title>
    <link>https://thescipub/abstract/jcssp.2026.878.885</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 10 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.878.885">doi:10.3844/jcssp.2026.878.885</a></p>This study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform....]]></content:encoded>
    <dc:title><![CDATA[Predictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning Techniques]]></dc:title><dc:creator>Mohammad Subhi Al-Batah</dc:creator><dc:creator>Mowafaq Salem Alzboon</dc:creator><dc:creator>Hamzeh   Zureigat</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.878.885</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-10; | doi:10.3844/jcssp.2026.878.885</dc:source>
    <dc:date>2026-03-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.878.885</prism:doi>
    <prism:url>https://thescipub/abstract/jcssp.2026.878.885</prism:url>
    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.886.897">
    <title><![CDATA[Senior Expertise and Peer Consensus: A Comparative Analysis of AI and Clinician Measurements in Multi-Curve Scoliosis Assessment]]></title>
    <link>https://thescipub/abstract/jcssp.2026.886.897</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 9 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.886.897">doi:10.3844/jcssp.2026.886.897</a></p>Given the scarcity in the literature, this study explored the use of AI for multi-curve scoliosis assessment. Its performance was analyzed through comparison against a group of clinicians composed of ...]]></content:encoded>
    <dc:title><![CDATA[Senior Expertise and Peer Consensus: A Comparative Analysis of AI and Clinician Measurements in Multi-Curve Scoliosis Assessment]]></dc:title><dc:creator>Frank Ibañez Elijorde</dc:creator><dc:creator>Joselito F. Villaruz</dc:creator><dc:creator>Ma Beth S. Concepcion</dc:creator><dc:creator>Mylo N. Soriaso</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.886.897</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-09; | doi:10.3844/jcssp.2026.886.897</dc:source>
    <dc:date>2026-03-09</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.886.897</prism:doi>
    <prism:url>https://thescipub/abstract/jcssp.2026.886.897</prism:url>
    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.919.937">
    <title><![CDATA[Transfer Learning-Driven Binary Classification of Chest X-ray for Pneumonia Using Deep Convolutional Architectures]]></title>
    <link>https://thescipub/abstract/jcssp.2026.919.937</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 10 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.919.937">doi:10.3844/jcssp.2026.919.937</a></p>Pneumonia is the most common infectious cause of lung inflammation, resulting from the presence of viruses or bacteria in the microscopic air sacs. In recent years, artificial intelligence, particular...]]></content:encoded>
    <dc:title><![CDATA[Transfer Learning-Driven Binary Classification of Chest X-ray for Pneumonia Using Deep Convolutional Architectures]]></dc:title><dc:creator>Nusrath   Fathima</dc:creator><dc:creator>Pradeep   Kumar</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.919.937</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-10; | doi:10.3844/jcssp.2026.919.937</dc:source>
    <dc:date>2026-03-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.919.937</prism:doi>
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    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.938.946">
    <title><![CDATA[Exploring University Students&#039; Perceptions of AI Tools in Programming Education: An Extended TAM Approach]]></title>
    <link>https://thescipub/abstract/jcssp.2026.938.946</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 11 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.938.946">doi:10.3844/jcssp.2026.938.946</a></p>Generative Artificial Intelligence (AI) is commonly used in programming education. Tools such as ChatGPT and GitHub Copilot aid in code generation, debugging, and explanation. The benefits are clear, ...]]></content:encoded>
    <dc:title><![CDATA[Exploring University Students&#039; Perceptions of AI Tools in Programming Education: An Extended TAM Approach]]></dc:title><dc:creator>Areej Abdullah Alfuhaid</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.938.946</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-11; | doi:10.3844/jcssp.2026.938.946</dc:source>
    <dc:date>2026-03-11</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.938.946</prism:doi>
    <prism:url>https://thescipub/abstract/jcssp.2026.938.946</prism:url>
    </item><item rdf:about="https://thescipub/abstract/jcssp.2026.947.959">
    <title><![CDATA[Adopting Artificial Intelligence in ERP Systems as an Innovation to Support Business Growth: A Systematic Literature Review]]></title>
    <link>https://thescipub/abstract/jcssp.2026.947.959</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 11 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.947.959">doi:10.3844/jcssp.2026.947.959</a></p>Digital transformation is driving the integration of Artificial Intelligence (AI) into Enterprise Resource Planning (ERP) systems as an innovative strategy to improve organizational competitiveness. H...]]></content:encoded>
    <dc:title><![CDATA[Adopting Artificial Intelligence in ERP Systems as an Innovation to Support Business Growth: A Systematic Literature Review]]></dc:title><dc:creator>Amalia Sulfinita Lawendatu</dc:creator><dc:creator>Fajar   Hidayat</dc:creator><dc:creator>Fathy   Radhia</dc:creator><dc:creator>Sugiarto   Hartono</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.947.959</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-11; | doi:10.3844/jcssp.2026.947.959</dc:source>
    <dc:date>2026-03-11</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.947.959</prism:doi>
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    <title><![CDATA[IoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning Algorithms]]></title>
    <link>https://thescipub/abstract/jcssp.2026.960.980</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 11 March 2026; <a href="https://thescipub.com/abstract/jcssp.2026.960.980">doi:10.3844/jcssp.2026.960.980</a></p>Hydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitate...]]></content:encoded>
    <dc:title><![CDATA[IoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning Algorithms]]></dc:title><dc:creator>Palash   Gourshettiwar</dc:creator><dc:creator>K. T. V.   Reddy</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.960.980</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-03-11; | doi:10.3844/jcssp.2026.960.980</dc:source>
    <dc:date>2026-03-11</dc:date>
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