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1473 articles for “E-learning”
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Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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Advancements, Hurdles, and Applications in Quantum Computing
Abstract: Using the ideas of quantum mechanics, quantum computing has become a paradigm shift in computing, enabling computations to be completed tenfold quicker than with traditional computers. This study investigates the current status of quantum computing, looking at the notable advancements, ongoing difficulties, and potential uses that could completely change a range of industries. By utilizing the principles of superposition and entanglement, quantum computers can potentially solve complex problems that classical …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 11–29 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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Self-Healing Structural Polymer Composites Incorporating Bio-Inspired Nanofillers
Abstract: Self-healing polymer composites become an attractive family of intelligent materials that are capable of autonomously repairing damage, which will enhance their durability, reliability and service life in extreme engineering applications. The materials are based on the principles of nature, using the nanofillers that are derived from biological systems to improve mechanical properties and self-healing capabilities by utilizing hierarchical structures and multifunctional interface interactions. The recent developments on the formulation of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
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Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
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Experimental Validation and Implementation Framework for Optimized Methane Yield Prediction in Anaerobic Digestion
Abstract: The correct validation and realistic application of optimized anaerobic digestion (AD) models are essential steps in transferring biogas production systems to real-life. This paper outlines an experimental validation and deployment pipeline of an AI-optimized model of the methane yield prediction model based on the application of more advanced machine learning and Bayesian optimization methods. Others The validated surrogate-assisted optimization model was tested with controlled laboratory-scale AD experiments at optimized operating …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Stock Market Analysis Using Data Science
Abstract: Stock market prediction using data science has become a popular area of research and application in recent years. This is because the stock market is a complex system with many variables and factors that affect its behavior, making it difficult to predict with certainty. The stock market has always been the aggression of buyers and sellers of stocks, therefore in the global finance market, stock trading is one of the …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 1–4 Read article
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Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications
Abstract: Automation and robotics technologies have rapidly evolved, transforming modern manufacturing processes by improving productivity, quality, and operational efficiency. This review examines key advancements such as cloud robotics, machine vision, Industry 4.0 robotics, Building Information Modeling (BIM) combined with Computer Numerical Control (CNC), joystick-controlled automation, and intelligent manufacturing systems. These technologies utilize artificial intelligence (AI), machine learning (ML), digital twins, collaborative robots, programmable logic controllers (PLCs), and cyber-physical systems (CPS) to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 36–48 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Assessing the Effectiveness of Visual Stimulation on Visual Perceptual Ability Among Intellectually Disabled Children
Abstract: Every child, including those with mild mental retardation, has the right to receive an education. As like normal children, mild mentally intellectually disabled children need education that can help their growth and development and to perform their daily life activities. However, learning sources for intellectually disabled children have several obstacles, including recognition of objects. The purpose of this study is to orient the use of basic articles for mild intellectually …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 1, Issue 1, 2023 · pp. 12–22 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Copper Sulfide Semiconducting Nanoparticles for Antibacterial Applications: Synthesis Strategies, Mechanisms and Performance – A Review
Abstract: Copper sulfide nanoparticles (CuS NPs) have drawn growing attention as a next-generation antibacterial platform, owing to their tunable structural, optical, and catalytic properties. This review consolidates current evidence on CuS NP synthesis, mechanisms, and antibacterial performance, comparing chemical and green synthesis routes alongside the effects of morphology, doping, and surface modification. Mechanistically, CuS NPs act through several overlapping pathways, including reactive oxygen species generation, bacterial membrane disruption, ion release, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article