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691 articles for “learning environment”
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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A study in Leveraging Deep Learning and IoT Arrays for Dynamic, Hyper-Local Atmospheric Intelligence
Abstract: The critical demand for high-resolution, actionable atmospheric data is challenged by the high cost and sparse coverage of traditional regulatory monitoring stations. This paper explores the synergistic paradigm shift enabled by integrating low-cost, dense Internet of Things (IoT) sensor arrays with advanced Artificial Intelligence (AI) methodologies, specifically Deep Learning (DL) models. We address the primary limitations of low-cost sensors—inherent bias, sensitivity to environmental drift (temperature/humidity), and calibration inconsistency—by utilizing AI …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 50–62 Read article
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Harnessing the Role of Chatbot in Enhancing Educational Accessibility and Engagement
Abstract: Chatbots in education offer a valuable means to enhance accessibility and provide immediate, 24/7 support, assisting students and educators in accessing information and solving queries efficiently. They also contribute to personalized learning experiences, engaging students in interactive and informative interactions, ultimately fostering a more dynamic and effective educational environment. This research work delves into the creation and deployment of a chatbot, with a specific emphasis on its use within the …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 2, 2023 · pp. 21–30 Read article
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Peer Tutoring: Student as Teacher and Teacher as Facilitator
Abstract: Peer tutoring refers to an instructional method that uses pairings of high-performing students to tutor lower-performing students in a class-wide setting or in a common venue outside of school under the supervision of a teacher. The terms “tutoring” and “mentoring” will be used synonymously, as the role of tutor also includes maintaining a supportive and encouraging relationship with the tutee. This paper throws light on how peer tutoring promotes learning …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 5, Issue 3, 2015 · pp. 10–14 Read article
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Multimodal Data Fusion with Hybrid Machine Learning for Enhanced Prediction of Li-Ion Battery Remaining Useful Life and State of Charge
Abstract: Lithium-ion battery materials used in modern energy storage systems are required to exhibit high reliability, safety, and long lifecycle performance under varying operational and environmental conditions. Accurate prediction of Remaining Useful Life (RUL) and State of Charge (SoC) is therefore essential for understanding material degradation behavior, improving manufacturing quality, and enabling effective lifecycle management. However, nonlinear electrochemical aging, load variability, and thermal uncertainty significantly complicate accurate estimation of these parameters. …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 38–44 Read article
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Reinforcement Learning in Real World Application: A Study on Robotics; Autonomous Vehicles and Industrial Automation
Abstract: This research paper investigates the practical application of reinforcement learning (RL) in three critical domains: robotics, autonomous vehicles, and industrial automation. The study delves into the implementation of RL algorithms to enhance decision-making, adaptability, and autonomy in these real-world scenarios. Through a comprehensive review of existing literature, methodologies, and case studies, the paper addresses the challenges faced and the successes achieved in deploying RL in each domain. The findings offer …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 3, 2023 · pp. 1–15 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Digital Twin-Driven Optimization of Dynamic Covalent Polymer Networks under Real-Time IoT Monitoring
Abstract: The dynamic covalent polymer networks (DCPNs) has the highest allurement because of the reversibility of all of the chemicals and repetitive. The process of convalescence is delayed, the sense of source betrayal and acting relations is too strong. This transport to our material situation is an ever-refrigerated digital twin in this painting which was developed through repetition produced by constant synchronism sensors of the IoT that is constantly refined by …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 137–157 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Influence of SlS Parameters on Strength and Fatigue Durability of Polyamide-12
Abstract: Selective Laser Sintering (SLS), a laser-based polymer powder bed fusion process, has gained prominence in the fabrication of high-performance thermoplastics such as Polyamide-12 (PA12). This paper provides an extensive review of how key SLS process parameters—such as laser power, scan speed, hatch spacing, and energy density—affect the mechanical properties of PA12 components, with a specific focus on tensile strength and fatigue resistance. Studies demonstrate that increasing energy input enhances particle …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 178–191 Read article
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Economic Load Dispatch with PEV Using Evolutionary Techniques
Abstract: In this paper, the Economic Load Dispatch (ELD) problem is solved by using four different evolutionary techniques Social Spider Algorithm (SSA), Particle Swarm Optimization (PSO), and Teaching Learning Based Optimization (TLBO) with PEV on 20-unit thermal generation station. The most recent Self-Learning Teaching Learning Based Optimization (SL-TLBO) is introduced, including a weighting factor w for adjusting the learning range. A comprehensive study demonstrates that the unique algorithm has the potential …
Published in Journal of Thermal Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 22–33 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article
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AI and Big Data for Optimized Water Resource Management in Arid Regions
Abstract: Water scarcity in arid regions is an escalating global challenge, driven by climate change, population growth, and increasing demands from urban, industrial, and agricultural sectors. Effective water resource management (WRM) is crucial for sustaining livelihoods, economic stability, and infrastructure resilience. Emerging technologies such as artificial intelligence (AI), machine learning (ML), and big data offer innovative solutions for optimizing water use, enhancing efficiency, and improving sustainability in water-scarce environments. This paper …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–5 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Reimagining Plastic Waste: The Impact of Eco-Bricking on Student Engagement and Community Sustainability
Abstract: Plastic pollution poses a severe threat to the environment, impacting ecosystems, wildlife, and human health. With millions of tons of plastic waste generated globally each year, innovative solutions for waste management are essential. This paper explores the eco-bricking initiative at Sovanagar High School, which transforms plastic waste into eco-bricks—sustainable building materials used for constructing green walls, benches, and other structures on the school campus. By effectively reducing plastic waste, this …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 23–25 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article