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490 results for “E-learning system”
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Research ArticleOpen accessEvery word in the titleDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning AlgorithmsPalash Gourshettiwar, K. T. V. ReddyHydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things (IoT). This study summarises the latest research and discusses how Machine Learning and the IoT work together, focusing on nutrient optimization, plant development, and resource efficiency. The … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,046 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Intrusion Detection System Using Optimized Deep Learning for IoT NetworksChempavathy B., Mouleeswaran S. K.In the rapidly evolving landscape of Internet of Things (IoT) networks, assuring security is paramount. Cyber-attacks on IoT networks are evolving in complexity and scale. Intruders employ diverse tactics, including malware, Denial of Service (DoS) attacks, along with unauthorized access. This research aims to propose an optimized Deep Learning (DL) based Intrusion Detection System (IDS) to bolster security within IoT … …Journal of Computer Science, Vol. 21, Issue 8 · 9 Oct 2025 · 2,993 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleVirtual Learning System with Artificial Intelligence for the Academic Management ProcessLuis Lopez-Zevallos, Evellyn Navarro-Prado, Michael Cabanillas-CarbonellThe impact of the COVID-19 pandemic on global education, with the massive closure of schools and universities. It highlights the challenge of adapting to distance learning modalities and the loss of students' knowledge. In this context, the use of Artificial Intelligence (AI) has become a promising alternative to improve distance education; it is presented as a solution to automate administrative … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,366 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleHuman 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 accessEvery word in the titleCustomized Named Entity Recognition Using Bert for the Social Learning Management System Platform CourseNetworkingKayal Padmanandam, KVN Sunitha, Behafarid Mohammad Jafari et al.Named Entity Recognition (NER) is an information extraction task and one of the most researched applications to extract knowledge from massive data. Conventional NER systems identify predefined entities like name, person, location, organization, time, etc. However, there is a limitation to identifying user-defined entities that are specific to an application. This challenge introduces the concept of customized NER. For instance, … …Journal of Computer Science, Vol. 20, Issue 1 · 15 Dec 2023 · 6,985 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePedagogical Resources Indexation Based on Ontology in Intelligent Recommendation System for Contents Production in d-Learning EnvironmentBrahim Faqihi, Najima Daoudi, Imane Hilal, Rachida AjhounWe witness, today, a strong evolution of learning environments. In parallel, a problem has emerged, consisting in how to capitalize the production of resources when switching from one environment to another. The heterogeneity of the environments, the evolution of the platforms and the will to reuse the educational resources already produced pushed us to design an intelligent system based on … …Journal of Computer Science, Vol. 16, Issue 7 · 19 Aug 2020 · 6,703 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparison Study between Different Sampling Strategies for Intrusion Detection System of Active Learning ModelGhofran Mohammad Alqaralleh, Mohammad Aref Alshraideh, Ali AlrodanActive learning aims to train an accurate model with minimum cost by labeling the most informative instances without compromising the model performance. So, choosing an efficient criterion for instance selection is the most important step. Sampling stage is the main issue in active learning for many problems such as intrusion detection system. There are many methods for sampling stage to … …Journal of Computer Science, Vol. 14, Issue 8 · 26 Aug 2018 · 8,183 accessesView PDFCite