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22 results for “Dataset Generation”
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Research ArticleOpen accessIn the keywordsGenerating IoT Specific Anomaly Datasets Using Cooja Simulator (Contiki-OS) and Performance Evaluation of Deep Learning Model Coupled with Aquila OptimizerVandana Choudhary, Sarvesh Tanwar, Tanupriya ChoudhuryIn recent times, the massive expansion of the Internet of Things (IoT) has transformed various facets of everyday life and industries. The compelling cause behind the widespread adoption of IoT is the increasing availability of affordable, compact, and energy-efficient computing devices. While these devices offer significant benefits, they also raise substantial security and privacy challenges. Consequently, safeguarding IoT networks and … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 6,850 accessesView PDFCite
Research ArticleOpen accessIn the abstractHMA-RAG: A Hierarchical Memory Augmented Retrieval Augmented Generation Framework for Fake News DetectionAfnan Altarjami, Sawsan AlshattnawiExisting methods for detecting fake news, such as traditional machine learning and transformer-based models, often work as separate classifiers that do not use outside evidence, historical knowledge, or ways to make the results easier to understand. This paper presents a framework that combines retrieval augmentation and hierarchical memory to overcome three primary constraints: Insufficient external evidence, the absence of memory, … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 735 accessesView PDFCite
Research ArticleOpen accessIn the abstractHindi Poetry Translation Using Neural Machine TranslationPragya Tewari, Anurag Singh BaghelNeural Machine Translation (NMT) has become an essential tool in Natural Language Processing (NLP), enabling the automatic translation of text across languages. However, translating poetry remains a relatively unexplored and complex task. Unlike general text, poetry carries multiple layers of meaning, emotion, rhythm, and cultural nuance, making it difficult to capture in another language through standard translation techniques. This study … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 1,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeneration Z Health Trends: Data Mining of Sleep and Lifestyle PatternsFrancka Sakti Lee, Johanes Fernandes Andry, Kevin Christianto et al.This study analyzes sleep health and lifestyle data among Generation Z using RapidMiner to identify key issues such as insomnia and stress within this demographic. The research is motivated by the increasing concerns surrounding sleep health and lifestyle choices that significantly impact overall well-being. The primary objective is to identify patterns and correlations in health data to inform targeted interventions … …Journal of Computer Science, Vol. 21, Issue 9 · 19 Oct 2025 · 3,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomatic Skin Lesion Diagnosis and Medical ReportGeneration Based on Image CaptioningAbdelouahed Sabri, Chaimae Zouitni, Hamza El Medhoune, Abdellah AarabCaptioning or textual description of the visual content of imagesinvolves generating meaningful words and sentences to describe the contentof an image. This work lies at the crossroads of Natural LanguageProcessing (NLP) and computer vision. When dealing with medical imagesand especially skin lesions, it goes beyond simple classification to generatedetailed textual reports describing the skin lesion's conditioncomprehensively. Such reports are crucial … …Journal of Computer Science, Vol. 21, Issue 5 · 13 May 2025 · 5,422 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 670 accessesView PDFCite
Research ArticleOpen accessIn the abstractAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 403 accessesView PDFCite
Research ArticleOpen accessIn the abstractRadial Basis Function Neural Networks Towards Electronic Trust QuantificationSmitha Zacaria, Tiny du ToitTrust is a broad term applicable in various contexts. Trust between electronic entities is complex to quantify, particularly in intricate networks. Traditional trust algorithms rely on historical trust values, requiring storage and access to past transaction details. Contextual variations further complicate trust calculation. Challenges in calculating trust include heightened computational complexities, managing information storage, and securing access to extensive datasets … …Journal of Computer Science, Vol. 20, Issue 11 · 26 Sep 2024 · 4,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractA GUI-Enabled, Automated LSTM-Based Inverse Kinematics Pipeline for 6-DOF Robotic Arms Using MATLAB and CoppeliaSimWaleed Abdulrahman Saleh Al-Akwa, Mohammed Abdulwahab Ahmed DabaExisting deep learning-based inverse kinematics (IK) solutions often target specific robotic arms and require significant modifications when applied to different configurations. To support early-phase design and testing of 6-degree-of-freedom (6-DOF) robotic arms, this study presents a fast and adaptable IK solution through a user-friendly interface. Unlike traditional numerical methods that are computationally intensive, sensitive to initial conditions, and may not … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 26 May 2025 · 8,252 accessesView PDFCite