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Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Framework for Citrus Grading and Yield Prediction Using Classifier-Informed RegressionLydia Dede Obeng, Isaac O. OsunmakindeAgriculture remains a cornerstone of human sustenance, yet accurate citrus fruit grading and yield predictions remain significant challenges due to visual similarities between varieties such as oranges and grapefruits. This includes the inefficiencies of manual grading. This study presents a new dual-function machine learning system that integrates classification and regression to simultaneously grade citrus fruits and forecast crop yields. This … …Journal of Computer Science, Vol. 22, Issue 4 · 24 Apr 2026 · 1,898 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntegrating Higher-Order Thinking Skills, Cognitive Load Theory, and Metacognition in Algebraic Problem-SolvingGurudeo Anand TularamThis study synthesizes 30 years of research (1990–2020) on algebraic problem-solving, integrating Higher-Order Thinking Skills (HOTS), Cognitive Load Theory (CLT), and metacognitive strategies to enhance student outcomes. Utilizing a critical synthesis approach with data from student interviews, problem-solving observations, and longitudinal tracking, the analysis reveals consistent patterns across diverse educational contexts despite limitations and variable factors like teaching styles and … …Journal of Social Sciences, Vol. 22, Issue 1 · 21 Apr 2026 · 2,025 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Network Security through Accurate Asset Discovery Using Lightweight Agent-Based ApproachIshu Sharma, Ahthasham Sajid et al.Any organization's network administrators and security professionals must have an accurate and real state of assets connected to the network to devise different policies for securing critical resources by identifying vulnerabilities. Asset discovery is a challenging and critical task in vulnerability assessment. The vulnerability of the organization’s network can be correctly analysed only with the accurate prediction of connected devices. … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Mar 2026 · 1,951 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT Anomaly Detection Using Picture Fuzzy Clustering ApproachFehmin Nadira Laskar, Vijo Arul Selvi M., Fokrul Alom Mazarbhuiya et al.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 fuzzy set-based approaches standing out for their potential. The Internet of Things (IoT) consists of many connected devices that constantly generate large amounts of data and perform tasks in real time. … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,518 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Lightweight PyBullet-Based Framework for Fast Reinforcement Learning Prototyping on 6-DOF Robotic ArmsNgoc Kim Khanh Nguyen, Anh Thu Mang, Quang NguyenControlling 6-Degree-of-Freedom (6-DOF) robotic arms for precise manipulation tasks is challenging due to kinematic redundancy and the complexity of existing simulation environments like MuJoCo or ROS-Gazebo. This paper presents ArmReach6DOFEnv, a lightweight, open-source simulation framework built on PyBullet for rapid Reinforcement Learning (RL) prototyping on 6-DOF robotic arms. Using a Universal Robot Description Format (URDF) model, the environment supports a … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 11 Feb 2026 · 3,082 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating the Usability of Model Transformations Testing Approach (MTTA)Lukman Ab. Rahim, Ziyaulhaq Aliyu, Emy E. MustaphaModel Transformation (MT) is a key component in Model Driven Development (MDD). Model transformation is used to transform source model into a target model, improve the model quality and also introduce the design pattern and refactoring. Model transformation are not free from bugs similar to other software development artifacts and it needs to be verified. Code Generators (CG) are a … …Journal of Computer Science, Vol. 13, Issue 1 · 6 Mar 2017 · 7,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractRefining Chest X-ray Interpretation with Deep Transfer Learning TechniquesR. Sriramkumar, K. Selvakumar, J. JeganChest X-rays are essential diagnostic tools for thoracic diseases, but different doctors' interpretations can differ greatly, which frequently results in inconsistent diagnoses. By using deep transfer learning techniques, this study seeks to improve the accuracy of Chest X-ray interpretations. More accurate and effective analysis can be accomplished with the growing potential of artificial intelligence (AI) in medical imaging, especially through … …Journal of Computer Science, Vol. 21, Issue 10 · 27 Nov 2025 · 2,655 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,400 accessesView PDFCite
Research ArticleOpen accessIn the abstractError Identification and Mitigation Analysis Method Using HFACS on VR HMDNkingo June Thomas, Yan SuHuman error has long been recognized as a key factor influencing safety, performance, and efficiency in complex tasks, including those involving advanced technologies. In the context of Virtual Reality (VR) Head-Mounted Displays (HMDs), which are increasingly applied in fields such as aviation maintenance, the presence of human errors can compromise both user experience and operational reliability. This paper presents a … …Journal of Aircraft and Spacecraft Technology, Vol. 9, Issue 1 · 24 Nov 2025 · 2,944 accessesView PDFCite
Research ArticleOpen accessIn the abstractSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,588 accessesView PDFCite