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<title>Volume 22, Issue 10 (2026) | Journal of Computer Science</title>
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    <title><![CDATA[Blockchain Based Solution for Secure and Efficient Agricultural Supply Chain Systems]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 28 September 2026; <a href="https://thescipub.com/jcs/jcssp.2026.2953.2962">doi:10.3844/jcssp.2026.2953.2962</a></p>The agricultural supply chain forms the backbone for feeding the world and supporting economies, but there is always a challenge to it such as traceability, inefficiencies, fraud risk, and poor transp...]]></content:encoded>
    <dc:title><![CDATA[Blockchain Based Solution for Secure and Efficient Agricultural Supply Chain Systems]]></dc:title><dc:creator>Yassir   Farooqui</dc:creator><dc:creator>Syed Ibad Ali</dc:creator><dc:creator>Kush   Bhushanwar</dc:creator><dc:creator>Snehlata   Barde</dc:creator><dc:creator>Aparajita   Biswal</dc:creator><dc:creator>Kiran   Macwan</dc:creator><dc:creator>Asim   Makkad</dc:creator><dc:creator>Bharti   Salunke</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.2953.2962</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-09-28; | doi:10.3844/jcssp.2026.2953.2962</dc:source>
    <dc:date>2026-09-28</dc:date>
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    <title><![CDATA[An Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks Framework]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 1 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.2963.2974">doi:10.3844/jcssp.2026.2963.2974</a></p>The IoV enables the formation of VANETs that require a strong selection of CHs for effective communication within high-velocity changing traffic scenarios. Existing approaches often face issues relate...]]></content:encoded>
    <dc:title><![CDATA[An Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks Framework]]></dc:title><dc:creator>P   Subhash</dc:creator><dc:creator>Madana   Srinivas</dc:creator><dc:creator>A.   Ranjith</dc:creator><dc:creator>Ravinder Reddy Baireddy</dc:creator><dc:creator>Mohammed   Qayyum</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.2963.2974</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-01; | doi:10.3844/jcssp.2026.2963.2974</dc:source>
    <dc:date>2026-10-01</dc:date>
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    <prism:doi>10.3844/jcssp.2026.2963.2974</prism:doi>
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    <title><![CDATA[<sup>Effectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced Performance</sup>]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 3 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.2975.2991">doi:10.3844/jcssp.2026.2975.2991</a></p>In this research, a pioneer passive approach for detecting and localizing tampering in images is proposed. In the past, image forgeries have created a huge impact in the world. Developments of various...]]></content:encoded>
    <dc:title><![CDATA[<sup>Effectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced Performance</sup>]]></dc:title><dc:creator>Preeti   Dhiman</dc:creator><dc:creator>Usha   Chauhan</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.2975.2991</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-03; | doi:10.3844/jcssp.2026.2975.2991</dc:source>
    <dc:date>2026-10-03</dc:date>
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    <prism:doi>10.3844/jcssp.2026.2975.2991</prism:doi>
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    <title><![CDATA[Benchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease Detection]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.2992.3006</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 29 September 2026; <a href="https://thescipub.com/jcs/jcssp.2026.2992.3006">doi:10.3844/jcssp.2026.2992.3006</a></p>Sorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers strugg...]]></content:encoded>
    <dc:title><![CDATA[Benchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease Detection]]></dc:title><dc:creator>Prince Daughin Ngqabutho Ncube</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.2992.3006</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-09-29; | doi:10.3844/jcssp.2026.2992.3006</dc:source>
    <dc:date>2026-09-29</dc:date>
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    <prism:doi>10.3844/jcssp.2026.2992.3006</prism:doi>
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    <title><![CDATA[Evaluation of an Intelligent Electronic Prescription Ontology Using Open Source Tools: A Botswana Case Study]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3007.3014</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 29 September 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3007.3014">doi:10.3844/jcssp.2026.3007.3014</a></p>Healthcare interoperability in Botswana is hindered by fragmented information exchange across public and private providers, resulting in prescription conflicts, duplicated treatment, and delayed care....]]></content:encoded>
    <dc:title><![CDATA[Evaluation of an Intelligent Electronic Prescription Ontology Using Open Source Tools: A Botswana Case Study]]></dc:title><dc:creator>Tshiamo   Sigwele</dc:creator><dc:creator>Eunice   Okon</dc:creator><dc:creator>Tshepiso   Mokgetse</dc:creator><dc:creator>Onkemetse   Tshenyego</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3007.3014</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-09-29; | doi:10.3844/jcssp.2026.3007.3014</dc:source>
    <dc:date>2026-09-29</dc:date>
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    <title><![CDATA[Applying Dempster Shafer Theory and Causal Inference in Investigating Internet of Things Digital Forensic Challenge]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3015.3026</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 10 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3015.3026">doi:10.3844/jcssp.2026.3015.3026</a></p>The rapid growth of IoT ecosystems has transformed digital forensics, creating challenges in analyzing distributed, heterogeneous, and uncertain evidence. Conventional forensic methods often struggle ...]]></content:encoded>
    <dc:title><![CDATA[Applying Dempster Shafer Theory and Causal Inference in Investigating Internet of Things Digital Forensic Challenge]]></dc:title><dc:creator>Mohamed   El-Dosuky</dc:creator><dc:creator>Mohamed   El-Dosuky</dc:creator><dc:creator>Sherif K. Ratib</dc:creator><dc:creator>Sherif K. Ratib</dc:creator><dc:creator>Mostafa M. El-Gayar</dc:creator><dc:creator>Mostafa M. El-Gayar</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3015.3026</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-10; | doi:10.3844/jcssp.2026.3015.3026</dc:source>
    <dc:date>2026-10-10</dc:date>
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    <prism:doi>10.3844/jcssp.2026.3015.3026</prism:doi>
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    <title><![CDATA[Determination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion Techniques]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3027.3041</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 5 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3027.3041">doi:10.3844/jcssp.2026.3027.3041</a></p>Most often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framewor...]]></content:encoded>
    <dc:title><![CDATA[Determination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion Techniques]]></dc:title><dc:creator>Kutlwano   Sedimo</dc:creator><dc:creator>Rajalakshmi   Selveraj</dc:creator><dc:creator>Venumadhav   Kuthadi</dc:creator><dc:creator>Thulaganyo   Dimakatso</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3027.3041</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-05; | doi:10.3844/jcssp.2026.3027.3041</dc:source>
    <dc:date>2026-10-05</dc:date>
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    <prism:doi>10.3844/jcssp.2026.3027.3041</prism:doi>
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    <title><![CDATA[Enhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief Network]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3042.3052</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 9 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3042.3052">doi:10.3844/jcssp.2026.3042.3052</a></p>Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millio...]]></content:encoded>
    <dc:title><![CDATA[Enhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief Network]]></dc:title><dc:creator>Geetha  M. N</dc:creator><dc:creator>Barkathulla   A</dc:creator><dc:creator>S. Nandhini Devi</dc:creator><dc:creator>Garaga   Srilakshmi</dc:creator><dc:creator>K.   Swanthana</dc:creator><dc:creator>Jayaraj   Ramasamy</dc:creator><dc:creator>Mohamed  Uvaze Ahamed Ayoobkhan</dc:creator><dc:creator>V.   Bhoopathy</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3042.3052</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-09; | doi:10.3844/jcssp.2026.3042.3052</dc:source>
    <dc:date>2026-10-09</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
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    <title><![CDATA[RIA-ViT: A Residual Inception Atrous Vision Transformer for Detection of Gallbladder Cancer from CT Images]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3053.3067</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3053.3067">doi:10.3844/jcssp.2026.3053.3067</a></p>Gallbladder Cancer (GBC) is a rare but highly aggressive malignancy of the biliary system. In early-stage gallbladder cancer, there are neither overt symptoms nor specific signs. In most patients, it ...]]></content:encoded>
    <dc:title><![CDATA[RIA-ViT: A Residual Inception Atrous Vision Transformer for Detection of Gallbladder Cancer from CT Images]]></dc:title><dc:creator>Abhishek   Sehrawat</dc:creator><dc:creator>Anita   Gupta</dc:creator><dc:creator>    Vishnupriya</dc:creator><dc:creator>Varun P. Gopi</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3053.3067</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-06; | doi:10.3844/jcssp.2026.3053.3067</dc:source>
    <dc:date>2026-10-06</dc:date>
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    <title><![CDATA[Structural Barriers to the Deployment of AI Foundation Models]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3068.3081</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 5 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3068.3081">doi:10.3844/jcssp.2026.3068.3081</a></p>Artificial Intelligence (AI) foundation models excel at benchmarks but are not always cost-effective or successfully deployed in enterprise systems. This paper analyzes the failures in their deploymen...]]></content:encoded>
    <dc:title><![CDATA[Structural Barriers to the Deployment of AI Foundation Models]]></dc:title><dc:creator>Hristo   Hristov</dc:creator><dc:creator>Elena   Somova</dc:creator><dc:creator>Emil   Fuchedzhiev</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3068.3081</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-05; | doi:10.3844/jcssp.2026.3068.3081</dc:source>
    <dc:date>2026-10-05</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3068.3081</prism:doi>
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    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3082.3103">
    <title><![CDATA[A Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop Optimization]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3082.3103</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 10 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3082.3103">doi:10.3844/jcssp.2026.3082.3103</a></p>Driven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several...]]></content:encoded>
    <dc:title><![CDATA[A Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop Optimization]]></dc:title><dc:creator>Jignesh   Kariya</dc:creator><dc:creator>Pankaj   Mudholkar</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3082.3103</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-10; | doi:10.3844/jcssp.2026.3082.3103</dc:source>
    <dc:date>2026-10-10</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3082.3103</prism:doi>
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    <title><![CDATA[Advancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net Models]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3104.3132</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 8 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3104.3132">doi:10.3844/jcssp.2026.3104.3132</a></p>Forgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning ar...]]></content:encoded>
    <dc:title><![CDATA[Advancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net Models]]></dc:title><dc:creator>Preeti  Dhiman</dc:creator><dc:creator>Usha   Chauhan</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3104.3132</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-08; | doi:10.3844/jcssp.2026.3104.3132</dc:source>
    <dc:date>2026-10-08</dc:date>
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    <title><![CDATA[Modified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery Localization]]></title>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3133.3145">doi:10.3844/jcssp.2026.3133.3145</a></p>Copy-move forgery is a widely used forgery method in digital image forensics, which involves copying and pasting a part of an image into another part of the image to hide or duplicate the visual infor...]]></content:encoded>
    <dc:title><![CDATA[Modified U-Net With VGG11-BN Encoder and Frost Filter Based Pre-Processing for Copy Move Forgery Localization]]></dc:title><dc:creator>Ashutosh   Pandey</dc:creator><dc:creator>Niranjan   Lal</dc:creator><dc:creator>Ashish Kumar Chakraverti</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3133.3145</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-06; | doi:10.3844/jcssp.2026.3133.3145</dc:source>
    <dc:date>2026-10-06</dc:date>
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    <title><![CDATA[Hybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPA]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3157.3172</link>
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        <![CDATA[<p>Journal of Computer Science, Published online: 6 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3157.3172">doi:10.3844/jcssp.2026.3157.3172</a></p>The expansion of Internet of Things (IoT) deployments has motivated the Fog Computing (FC) paradigm, which brings mobile-edge and cloud resources together under a single model. Allocating and provisio...]]></content:encoded>
    <dc:title><![CDATA[Hybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPA]]></dc:title><dc:creator>Nagarjun   E</dc:creator><dc:creator>Dharamendra   Chouhan</dc:creator><dc:creator>Dilip Kumar SM</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3157.3172</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-06; | doi:10.3844/jcssp.2026.3157.3172</dc:source>
    <dc:date>2026-10-06</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3157.3172</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3157.3172</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3173.3196">
    <title><![CDATA[A Dynamically Zero Trust and Risk Aware Cryptographic Orchestration Framework of Secure Multi Cloud Electronic Health Records]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3173.3196</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 7 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3173.3196">doi:10.3844/jcssp.2026.3173.3196</a></p>The adoption of multi-cloud infrastructures for Electronic Health Records (EHRs) improves scalability and accessibility but introduces security challenges such as fragmented trust management, high cry...]]></content:encoded>
    <dc:title><![CDATA[A Dynamically Zero Trust and Risk Aware Cryptographic Orchestration Framework of Secure Multi Cloud Electronic Health Records]]></dc:title><dc:creator>D. Veerabhadra   Rao</dc:creator><dc:creator>G. Appa   Rao</dc:creator><dc:creator>S.   Anuradha</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3173.3196</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-07; | doi:10.3844/jcssp.2026.3173.3196</dc:source>
    <dc:date>2026-10-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3173.3196</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3173.3196</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3197.3203">
    <title><![CDATA[Context Tamil Llama-QA: A Question and Answering Framework for Semantic Information Retrieval Using Tamil Large Language Model]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3197.3203</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 7 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3197.3203">doi:10.3844/jcssp.2026.3197.3203</a></p>The Question Answering System (QA) is essential for effectively retrieving and providing relevant information, and its performance is heavily reliant on the efficiency of information retrieval mechani...]]></content:encoded>
    <dc:title><![CDATA[Context Tamil Llama-QA: A Question and Answering Framework for Semantic Information Retrieval Using Tamil Large Language Model]]></dc:title><dc:creator>Jeevit Davidson S.</dc:creator><dc:creator>M.   Murali</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3197.3203</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-07; | doi:10.3844/jcssp.2026.3197.3203</dc:source>
    <dc:date>2026-10-07</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3197.3203</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3197.3203</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3204.3221">
    <title><![CDATA[Integrating (OLAP) Online Analytical Processing With a Fast Algorithm for Epileptic Seizures Detection]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3204.3221</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 12 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3204.3221">doi:10.3844/jcssp.2026.3204.3221</a></p>Epilepsy is a neurological disorder characterized by recurrent seizures, significantly impacting the quality of life of patients. Effective detection and analysis of epileptic seizures are crucial for...]]></content:encoded>
    <dc:title><![CDATA[Integrating (OLAP) Online Analytical Processing With a Fast Algorithm for Epileptic Seizures Detection]]></dc:title><dc:creator>Ilyas   Zidane</dc:creator><dc:creator>Wajih   Rhalem </dc:creator><dc:creator>Nordine   Zidane</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3204.3221</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-12; | doi:10.3844/jcssp.2026.3204.3221</dc:source>
    <dc:date>2026-10-12</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3204.3221</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3204.3221</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3222.3237">
    <title><![CDATA[Metadata Stewardship and Quality in Telecom Sector]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3222.3237</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 22 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3222.3237">doi:10.3844/jcssp.2026.3222.3237</a></p>The spread of the telecom network infrastructure, constellations of satellites and the use of the Internet of Things (IoT) have brought about unprecedented volumes of heterogeneous information which f...]]></content:encoded>
    <dc:title><![CDATA[Metadata Stewardship and Quality in Telecom Sector]]></dc:title><dc:creator>Bhola Gan Chaudhuri</dc:creator><dc:creator>Shalli   Rani</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3222.3237</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-22; | doi:10.3844/jcssp.2026.3222.3237</dc:source>
    <dc:date>2026-10-22</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3222.3237</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3222.3237</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3238.3249">
    <title><![CDATA[Image Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3238.3249</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 21 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3238.3249">doi:10.3844/jcssp.2026.3238.3249</a></p>Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT i...]]></content:encoded>
    <dc:title><![CDATA[Image Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50]]></dc:title><dc:creator>Qodri   Aziz</dc:creator><dc:creator>Qodri   Aziz</dc:creator><dc:creator>Slamet   Riyadi</dc:creator><dc:creator>Slamet   Riyadi</dc:creator><dc:creator>Suzaimah Binti Ramli</dc:creator><dc:creator>Nurwahyu   Alamsyah</dc:creator><dc:creator>Shofwatul   Uyun</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3238.3249</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-21; | doi:10.3844/jcssp.2026.3238.3249</dc:source>
    <dc:date>2026-10-21</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3238.3249</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3238.3249</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3250.3267">
    <title><![CDATA[Leveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion Prediction]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3250.3267</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 8 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3250.3267">doi:10.3844/jcssp.2026.3250.3267</a></p>Liver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed...]]></content:encoded>
    <dc:title><![CDATA[Leveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion Prediction]]></dc:title><dc:creator>Sugandha   Chakraverti</dc:creator><dc:creator>Tejaswi   Khanna</dc:creator><dc:creator>Vijay   Shukla</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3250.3267</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-08; | doi:10.3844/jcssp.2026.3250.3267</dc:source>
    <dc:date>2026-10-08</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3250.3267</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3250.3267</prism:url>
    </item><item rdf:about="https://thescipub.com/jcs/jcssp.2026.3268.3281">
    <title><![CDATA[A Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud Networks]]></title>
    <link>https://thescipub.com/jcs/jcssp.2026.3268.3281</link>
    <content:encoded>
        <![CDATA[<p>Journal of Computer Science, Published online: 19 October 2026; <a href="https://thescipub.com/jcs/jcssp.2026.3268.3281">doi:10.3844/jcssp.2026.3268.3281</a></p>Distributed Denial-of-Service (DDoS) is one of the most significant threats to the security of IoT, cloud, and Software-Defined Network (SDN) environments because it can aggravate network unavailabili...]]></content:encoded>
    <dc:title><![CDATA[A Scalable Hybrid CNN-LSTM and SDN Based Architecture for Real-Time DDoS Defence in IoT and Cloud Networks]]></dc:title><dc:creator>Sujit   Sutradhar</dc:creator><dc:creator>Joy Lal Sarkar</dc:creator><dc:creator>Rajesh Kumar Verma</dc:creator><dc:identifier>doi:10.3844/jcssp.2026.3268.3281</dc:identifier>
    <dc:source>Journal of Computer Science, Published online: 2026-10-19; | doi:10.3844/jcssp.2026.3268.3281</dc:source>
    <dc:date>2026-10-19</dc:date>
    <prism:publicationName>Science Publications</prism:publicationName>
    <prism:doi>10.3844/jcssp.2026.3268.3281</prism:doi>
    <prism:url>https://thescipub.com/jcs/jcssp.2026.3268.3281</prism:url>
    </item></rdf:RDF>