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105 articles for “Adaptive Design”
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Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Occlusion Aware Facial Expression Recognition Model Using Fitness Based Cheetah Optimizer and Adaptive Multi-Scale ViT-CNN With Attention MechanismA. Reddy Prasad, A. RajeshAs a highly nuanced aspect of human communication, facial expression recognition presents a computationally complex problem, making it a prominent area of research in computer vision and affective computing. Problems like poor image quality, occlusions, inconsistent illumination, and head attitude changes are frequently observed in images taken from unstructured sources such as the internet that affect the accuracy of facial … …Journal of Computer Science, Vol. 21, Issue 12 · 29 Jan 2026 · 1,962 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Data Encryption for Securing HDFS Using DQN-Enhanced Deep Reinforcement Learning TechniquesShivani Awasthi, Narendra KohliIn the era of big data, ensuring the security of large-scale distributed storage systems like the Hadoop Distributed File System (HDFS) is critical. Traditional encryption methods often struggle to balance robust security with system performance, leading to vulnerabilities and inefficiencies. This study presents the design and implementation of an efficient data encryption algorithm for securing HDFS using Deep Q-Network (DQN) … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 6,376 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Mobile Edge Computing Efficiency through Multidimensional Generative Adversarial NetworkAnitha Premkumar, Sowmya Vemagal Lakshminarayana, Shankar Rajagopal et al.Big data Processing and the IoT have recently gained popularity as study topics in MEC and thorough research is sought for well-informed decisions. Mobile edge equipment, such as base stations, routers, and edge servers, usually have limited processing capabilities compared to traditional data centers. According to this perspective, this research constructs MEC using Intelligent Outlier Detection with a Multidimensional Generative … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 4,686 accessesView PDFCite
Research ArticleOpen accessIn the abstractIAFIR Optimization against NOMA Competitors: A Comprehensive Analysis on Energy-Efficient Non-Orthogonal Multiple AccessS. Pavithra, S. ChitraThe ever-growing demands of next-generation wireless networks necessitate the exploration of innovative technologies to enhance spectral efficiency, user experience and network performance. Non-Orthogonal Multiple Access (NOMA) has emerged as a promising candidate, offering the potential for increased capacity and improved system reliability. NOMA allows multiple users to share the same time-frequency resource, breaking away from traditional orthogonal access methods. In … …Journal of Computer Science, Vol. 20, Issue 8 · 31 May 2024 · 5,053 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Rooftop Solar Panels Efficiency using Maximum Power Point Tracking Based on an Adaptive Neural Network Fuzzy Inference SystemI Made Ari Nrartha, I Made Ginarsa, Agung Budi Muljono et al.Rooftop solar panels are a strategy for achieving Indonesia's renewable energy goals, but their non-linear characteristics make them difficult to control, especially in the face of extreme weather changes. An effective controller is needed to optimize the power output of solar panels. This study proposes a Maximum Power Point Tracking (MPPT) controller based on an Adaptive Neural network Fuzzy Inference … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 1 · 19 Jan 2023 · 5,769 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Systematic Review of Metaheuristic-Metaheuristic (MH-MH) Hybridizations for OptimizationAugustina Dede Agor, Frank Kataka Banaseka, Prince Silas Kwesi Oberko et al.This systematic review following the PRISMA framework analyzes metaheuristic-metaheuristic (MH-MH) hybridizations published between January and October 2024 to uncover patterns of algorithmic dominance, functional roles and integration strategies, metaphor-based partnerships, domain mappings and evaluation orientations. Frequency mapping of 105 canonical algorithms identified Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) as the three most recurrent … …Journal of Computer Science, Vol. 22, Issue 2 · 4 Mar 2026 · 2,183 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite
EditorialOpen accessIn the abstractVolume 2: and SGAMR Goes!Chiara Bedon, Mario D’Aniello, Flavio StochinoThe year 2018 starts with a great confirmation for SGAMR! The journal has been selected to host the extended version of some selected papers presented during the 6th International Workshop on Design in Civil and Environmental Engineering (DCEE2017), held at the University of Cagliari (Italy) during November 2017. A summary of selected papers from highly ranked, international scientists can be … …International Journal of Structural Glass and Advanced Materials Research, Vol. 4, Issue 1 · 28 Aug 2020 · 5,737 accessesView PDFCite