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1473 articles for “E-learning”
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Cloud Enabled Machine Learning Framework for Medicine System
Abstract: The Medicine Generic App is a cutting-edge mobile application designed to empower users with information about generic medications. Given the rising expenses of healthcare and prescription medications, this app acts as a useful resource for consumers to make informed decisions regarding their medication options. The Medicine Generic App aims to promote generic drug usage, reduce healthcare costs, and improve medication management for users. By providing detailed information and price transparency, …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems
Abstract: The integration of Artificial Intelligence (AI) in nursing education offers significant potential to enhance learning experiences by personalizing education, improving knowledge retention, and developing clinical competencies. This study evaluates the effectiveness of AI-driven adaptive learning systems compared to traditional lecture-based teaching methods in nursing education. A mixed-methods approach was used, with 200 nursing students participating in a quasi-experimental design. The intervention group (100 students) used AI-powered adaptive learning platforms for …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 2, 2025 · pp. 29–34 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Machine Learning-Driven Early Prediction and Prevention of Obesity and Overweight
Abstract: Obesity has become a global health concern, with its prevalence reaching alarming levels in recent years. By classifying obesity-level, healthcare professionals can assess an individual's risk and develop appropriate treatment and prevention strategies. Healthcare professionals can customize interventions and create personalized treatment plans based on individual needs. This paper delivers a system provides an overview of obesity, highlighting the importance of accurate and standardized categorization for effective management and treatment …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 31–40 Read article
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21st Century Cognitive Landscapes: Integrating ICT-Driven Pedagogies for Holistic, Inclusive Education
Abstract: The rapid advancement of Information and Communication Technology (ICT) has revolutionized digital pedagogies, reshaping modern education by improving accessibility, learner engagement, and academic outcomes. This review critically explores the psychological ramifications of digital learning environments while assessing the effectiveness of ICT tools in fostering inclusive and sustainable education. By integrating insights from contemporary research, this paper examines the impact of digital pedagogies on cognitive function, emotional health, and social interactions …
Published in International Journal of Education Sciences · Vol. 2, Issue 2, 2025 · pp. 75–81 Read article
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Exploring the Potential of AI-Driven Personalized Learning and Cognitive Interventions for ADHD Management in Indian Children and Adolescents: A Focus on Early Intervention
Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental condition that significantly impairs attention, executive functioning, and behavioural regulation in children and adolescents. In India, the management of ADHD is particularly challenging due to low public awareness, social stigma, and a critical shortage of specialized mental health services, especially in rural areas. These systemic barriers often lead to delayed diagnoses and limited access to consistent care. However, with the rapid …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Fortifying the Blockchain Fortress: A Machine Learning Paradigm for Enhanced Security
Abstract: Blockchain technology has emerged as a revolutionary tool in the digital landscape, enabling secure and transparent transactions across a decentralized network. Despite its robust security features, blockchain systems remain vulnerable to anomalies and malicious activities. The detection of these anomalies using machine learning has become essential for protecting blockchain networks and ensuring their integrity. This project delves into the application of machine learning techniques to detect abnormal patterns within blockchain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 33–40 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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Deep Guard: A Comprehensive Deep Learning System for Unmasking Suspicious Activities in Surveillance Footage
Abstract: These days, video surveillance is quite vital. Technology has evolved considerably as machine learning, artificial intelligence, and deep learning become increasingly widespread. There are several algorithms that assist in identifying distinct kinds of suspicious behaviour from live footage by combining the techniques. A person's behaviour is the most unpredictable thing, and it can be quite challenging to determine whether it is normal or suspicious. Video surveillance is automated to address …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 23–28 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Automated Intelligence, Machine Learning, and Big Data in Education: A Practical Framework, Synthetic Demonstration, and Deployment Guidance
Abstract: Artificial intelligence (AI), machine learning (ML), and big-data methods are increasingly used to improve educational decision making through personalization, early-warning systems, scalable feedback, and operational analytics. This manuscript proposes a practical end-to-end framework for educational AI/ML projects, covering problem definition, data engineering, modeling, evaluation, intervention design, and responsible governance. To provide a complete and reproducible template without exposing sensitive student data, we present a synthetic demonstration study that mirrors typical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Navigating the Digital Frontier: An In-depth Analysis of Classroom Digitalization
Abstract: When we talk about the Internet, we think about the likes of social media, or platforms like Google which has an unfathomable archive of information which is available for any and every individual to use up to their own likings. However, there are several challenges and complexities associated with the Internet's impact on social interactions. The issues of online harassment, privacy, and the addictive nature of social media have become …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 1, Issue 2, 2023 · pp. 14–20 Read article
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Personalized Virtual Interior Design Using Generative AI
Abstract: This study presents an AI-driven virtual interior design system that allows users to effectively redesign their home or workspace with an integrated shopping experience. The system tailors designs according to room type, style, and purpose, ensuring that the created layouts are aesthetically pleasing, well-organized, and functional. In contrast to conventional interior design, which involves professional skill, hand labor, and much time consumption, this AI-based method uses technology to automate fundamental …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 07–12 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article