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45 results for “Learning Analytics”
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Research ArticleOpen accessIn the abstractEnhanced RoBERTa Model for OCR-Based EHR Parsing and Information ExtractionBalaji Ganesh Rajagopal, Amarnath C, Chidambaram Sawri Rajan, Deebalakshmi RamalingamHealthy source data for medical research and health analytics in general can be obtained from Electronic Health Records (EHRs). Nevertheless, due to the complexities of the design and especially the unstructured nature of them, it is not easy to extract important information from digital documents. This paper proposes a fundamentally new approach to the problem of interpreting EHRs obtained by … …Journal of Computer Science, Vol. 22, Issue 4 · 5 May 2026 · 1,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Analytics and Procurement Visibility: A Big-Data-Driven Approach to Customer Satisfaction in Supply Chain ManagementDevendra Nath Pathak, Rakesh Kumar Yadav, Hitendra SinghIn the current dynamic and consumer driven market environment, supply chains need to move out of reactive to the proactive ecosystems. One of the most urgent requirements is increasing procurement visibility and the development of better order planning for the inventory to meet the products’ demand with continued high customer satisfaction. This paper is an agenda of big-data-driven predictive analytics … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,442 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractMERAKI: An Online Collaborative Learning Platform Developed Using the UWE MethodologyPercy De-la-Cruz-VdV, Yesenia Torres-Donayre, Hugo Vega-Huerta et al.In the digital era, education has evolved with the integration of technologies that optimize the teaching-learning process. This article presents the need for more efficient online collaborative environments that overcome the limitations of traditional platforms, fostering meaningful interaction between students and teachers. To address this need, the collaborative platform “MERAKI” was developed using the UML-Based Web Engineering (UWE) methodology. This … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,142 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Public Sentiment on Demonetization Using SVM: A Machine Learning ApproachKaliappan M, Guruprakash B, Rajalakshmi et al.The Indian economy experienced significant disruption following the implementation of demonetization, a policy initiative aimed at eliminating black money, controlling inflation, and promoting financial inclusion. However, this currency ban generated widespread debate and polarized public opinion. This study analyzes public sentiment toward demonetization using social media data, specifically Twitter posts characterized by mixed sentiments, sarcasm, and nuanced linguistic expressions. We … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,235 accessesView PDFCite
Review ArticleOpen accessIn the abstractComparative Analysis of Classical Feature Detection Methods for UAV-Based Tomato DetectionMuhammad Sarwar Jahan Morshed, Md. Nasim Adnan, Md. Rafiqul IslamRemote sensing technologies, especially Unmanned Aerial Vehicles (UAVs), become crucial for Precision Agriculture (PA) to perform different tasks such as crop detection, yield prediction, leaf disease diagnosis, weed detection, and harvest forecasting to ensure higher productivity. Therefore, using various image analytics methods feature detection from the UAV-captured images plays a vital role for conducting these PA tasks. To enhance the … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,404 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,111 accessesView PDFCite