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155 results for “e-learning challenges”
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Research ArticleOpen accessEvery word in the titleAddressing Emergency Communication Challenges: Deep Learning Solutions for the Speech and Hearing- ImpairedPoornima B V, Srinath S et al.Emergency communication plays a very important role in ensuring that help reaches people promptly and safely in case of any emergency. However, the biggest problem faced by those who cannot speak and hear properly is to convey their message clearly and understand others. In this regard, the proposed research work focuses on recognizing emergency gestures made in the Indian Sign … …Journal of Computer Science, Vol. 22, Issue 5 · 1 Jun 2026 · 1,063 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPersistent Misconceptions in Algebra: A Critical Analysis of Errors with Implications for Teaching and Further ResearchGurudeo Anand Tularam, Omar Moalin HassanThis study explores the persistent challenges students face in learning algebra, with a focus on prevalent errors observed in secondary education worldwide. This study highlights the complex interplay between conceptual and procedural knowledge in algebraic reasoning through a comprehensive review of theoretical frameworks and empirical studies by influential scholars such as Kieran, Shard, Booth and Koedinger. As students transition from … …Journal of Social Sciences, Vol. 21, Issue 1 · 22 Mar 2025 · 10,091 accessesView PDFCite
Research ArticleOpen accessIn the keywordsReview of E-Learning and ICT Infrastructure in Developing Countries (Case Study of Iran)Siavash Omidinia, Maslin Masrom, Harihuddin SelamatProblem statement: E-Learning aims to apply information and communications technology to enhance and/or support learning process. Today E-Learning is one of tools for education justice. This study attempts to review on challenges and infrastructure of e-learning in developing countries specially Iran and to know what have been developed in Iran, what issues and challenges exists and what solutions make e-Learning … …American Journal of Economics and Business Administration, Vol. 3, Issue 1 · 31 Jan 2011 · 10,267 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 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 abstractA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractFL-CARE: Federated Learning-Based Contention-Aware and Energy-Balanced Routing for Dense FANETsHalimjon Khujamatov, Elyanora Jolimbetova et al.In dense multi-drone FANET environments, routing efficiency is often reduced due to constant competition for a wireless channel, frequent changes in network topology, and uneven energy consumption between UAV nodes. These factors lead to a decrease in the packet delivery ratio, an increase in delays on the busiest or most unstable routes, and a reduction in the total network lifespan. … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnxiety-Focused Classification Using Smartphone-Based Gait Analysis and Deep Learning ModelsMinchan Kang, Gou-Sung Degbey, Hyunhwa Lee et al.Mood disorders, such as anxiety, significantly impact individual well-being and present challenges to healthcare systems globally. Traditional screening methods, including self-administered symptom questionnaires, provide valuable insights into symptoms but may miss dynamic fluctuations. This study explores the potential of smartphone inertial sensors and deep learning models for anxiety risk classification. Using gait data from 36 participants, collected via smartphone accelerometers … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 821 accessesView PDFCite
Research ArticleOpen accessIn the abstractMCWDRL: Multi-Cloud Workflow Scheduling Using Deep Reinforcement Learning and Improved Workflow Segmentation for Multi-Cloud EnvironmentsS. Gowri, A. SumathiThe rapid growth of cloud computing has led to complex workflow scheduling challenges in multi-cloud environments, where efficient resource utilization, minimized makespan, and reduced costs are paramount. Traditional scheduling algorithms often struggle to adapt to the dynamic nature of cloud resources and workflows, leading to suboptimal performance. To overcome this issue, the paper proposed a novel Multi-Cloud Workflow Scheduling using … …Journal of Computer Science, Vol. 22, Issue 6 · 1 Jul 2026 · 933 accessesView PDFCite