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155 results for “e-learning challenges”
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Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Review ArticleOpen accessIn the abstractDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Telecommunication Network Management with Autonomous Optimization Agents and Machine LearningDanny Adil Sibarani, Evaristus Didik MadyatmadjaThis study explores the integration of Machine Learning (ML) and Autonomous Optimization Agents (AOAs) in the management and optimization of Radio Access Networks (RAN). The research addresses the growing challenges posed by the need for skilled network experts capable of managing and analyzing large-scale network data, including Key Performance Indicators (KPIs) and thousands of network configuration parameters. To overcome these … …Journal of Computer Science, Vol. 21, Issue 2 · 4 Mar 2025 · 7,041 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 abstractFew-shot Fine-tuning of BERT Multilingual for Hindi Word Sense DisambiguationShailendra Kumar Patel, Rakesh Kumar, Anuj Kumar SirohiWord Sense Disambiguation (WSD) is a fundamental task in Natural Language Processing (NLP), addressing the challenge of identifying correct word meanings in context. This task is particularly complex for morphologically rich and resource-limited languages like Hindi, which exhibit significant lexical ambiguity compounded by limited availability of annotated corpora. To address these challenges, we propose a supervised approach combining the multilingual … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,250 accessesView PDFCite
Review ArticleOpen accessIn the abstractCybercrime in the AI Era: Definitions, Classification, Severity Assessment and the Role of AI in Combating ThreatsNorah Sultan Alshahrani, Fahd Saleh Alotaibi, Khaled Hamed Alyoubi, Muhammad Sher RamzanThe growing prevalence, complexity and financial impact of cybercrimes pose significant challenges for law enforcement agencies worldwide. Many organizations are utilizing different technologies such as cloud technology to improve speed, accuracy, and reliability. However, without proper security measures, the risk is still vital against cyberattacks. Cybercrime can lead to various negative outcomes, including theft, fraud, financial losses, a decline in … …Journal of Computer Science, Vol. 21, Issue 3 · 12 Feb 2025 · 7,155 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,821 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Transformer Model for Data-Driven Requirement Engineering: A Case Study of NLP4RE E-Commerce Business Apps in Malaysia and IndonesiaDevi Yurisca Bernanda, Dayang Norhayati Abang Jawawi, Shahliza Abd Halim et al.Data-Driven Requirement Engineering (DDRE) marks a departure from conventional methods, embracing dynamic, user-centric strategies with the help of machine learning and artificial intelligence. As software systems grow more intricate and demand adaptability, a continuous software engineering approach becomes crucial. However, this shift poses challenges in handling data inconsistencies during the elicitation process, leading to software development shortcomings. This study tackles … …Journal of Computer Science, Vol. 20, Issue 11 · 2 Oct 2024 · 5,131 accessesView PDFCite
Research ArticleOpen accessIn the abstractAspect Category Detection Using Bi-LSTM-Based Deep Learning for Sentiment Analysis for HindiAshwani Gupta, Utpal SharmaIn the field of sentiment analysis, the notion of aspect category identification lays emphasis on identifying the aspect categories in a specific review phrase. The purpose of this research is to propose a novel approach to the identification of aspect categories in reviews that are published in Hindi. The training and evaluation of a supervised model that is based on … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Sep 2024 · 4,606 accessesView PDFCite