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259 articles for “metric”
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Characterization and Performance of a Multiphase Lignocellulosic-Polymeric Composite Growth Media in an IoT-Automated NFT Hydroponic System
Abstract: Hydroponics utilizing the Nutrient Film Technique (NFT) entails a type of soilless agriculture involving the delivery of a continuously flowing and thin film of nutrient-filled solution onto the roots of plants. With the move toward sustainable and efficient urban agriculture in the contemporary world and need to produce more effective and resource-efficient solutions, there have been significant efforts aimed at improving these techniques through advanced materials and automation. A consistent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 542–555 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Looking into new ideas in green chemistry
Abstract: Green chemistry has become a revolutionary way to change chemical processes such that they have less of an effect on the environment while still being efficient and cost-effective. This article looks at new developments in green chemistry that go beyond small changes and offer completely new ways to build chemicals that are good for the environment. There is a lot of focus on innovative catalytic systems, sustainable feedstocks, reaction pathways …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 10–18 Read article
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Designing Ventilation Systems That Can Handle Extreme Weather
Abstract: Climate change is making extreme weather events like heat waves, cold spells, hurricanes, and wildfire smoke episodes more common and stronger. This is a big problem for traditional ventilation systems. This paper analyses the concepts and efficacy of resilient ventilation design in structures subjected to fluctuating and extreme environmental conditions. The research assesses the capacity of ventilation systems to uphold indoor air quality, thermal comfort, and operational continuity during extreme …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 1–14 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Investigations of A Solar Dryer With Thermal Storage
Abstract: This study presents the design, building, and performance evaluation of a low-cost mixed-mode natural convection solar cabinet dryer in conjunction with a latent heat thermal energy storage system. The work's goal is to reduce post-harvest losses in rural and semi-urban areas by offering an effective and reasonably priced method of preserving agricultural goods. The dryer is made out of a transparent polycarbonate lid to allow for solar heat gain, an …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 Read article
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Today’s Status of Digital Resources in Medical College Libraries
Abstract: Digital resources have become integral to the advancement of medical education and research, enabling access to current scientific evidence, clinical guidelines, e-books, e-journals, and multimedia learning tools. Medical college libraries worldwide are transitioning from traditional print repositories to hybrid digital knowledge hubs. This transformation is driven by the evolution of Information and Communication Technology (ICT), rising expectations of learners and educators, institutional mandates for evidence-based practice, and the diffusion of …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 85–94 Read article
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Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing
Abstract: Fibre orientation and void distribution are critical microstructural features that govern the mechanical performance and reliability of polymer composite materials. Accurate and simultaneous characterisation of these features remains challenging due to their complex spatial interactions and dependence on processing conditions. In this work, an integrated image-processing framework is proposed for the quantitative analysis of fiber orientation and void distribution in polymer composite structures. High-resolution composite microstructure images are processed through …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 925–933 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Image-Based Evaluation of Implant Tissue Interface Integrity in Polymer Orthopaedic Devices
Abstract: Polymer orthopedic implants offer radiolucency and mechanical compatibility with bone, but long-term success depends on maintaining a stable implant–tissue interface. Routine imaging is widely available for follow-up, yet interface integrity is commonly judged qualitatively, limiting early detection of fixation compromise and reducing comparability across devices and time points. This work presents an image-based methodology to quantify interface integrity by extracting interpretable interface descriptors from a standardized interface belt around the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 170–179 Read article
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Physicochemical Transitions and Polymerization Dynamics in Multi-Generational Dentin Adhesives: A Critical Review of the Resin-Dentin Composite Interface
Abstract: Adhesive dentistry has undergone a transformative refinement over the past three decades, transitioning from technique-sensitive, multi-step etch-and-rinse protocols to streamlined universal formulations. This narrative review critically synthesizes evidence from thirty peer-reviewed investigations to evaluate the evolution of dentin bonding agents from the fourth through the eighth generations. The analysis places particular emphasis on the physicochemical dynamics of the resin-dentin interface, including interfacial bond strength metrics, marginal integrity, and microleakage behavior. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 209–228 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Eco-Efficient Skies: Life Cycle Assessment and Carbon Footprint Minimization of Fiber-Reinforced Polymer Composites in Aerospace Application
Abstract: The increasing integration of fiber-reinforced polymer (FRP) composites in aerospace structures necessitates a rigorous evaluation of their environmental sustainability throughout their entire life cycle. This study presents a comprehensive life cycle assessment (LCA) and carbon footprint analysis of carbon fiber-reinforced polymer (CFRP) and glass fiber-reinforced polymer (GFRP) composites applied to structural and semi-structural components in commercial aerospace applications. Following ISO 14040/14044 standards and employing the ReCiPe 2016 Midpoint (H) impact …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 147–160 Read article
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Dynamic Vibration and Damping Analysis of Sustainable Nano-Reinforced Polymer Composite Elements for Vehicle Suspension Applications
Abstract: This paper presents an analytical investigation into the dynamic vibration characteristics of nano-reinforced polymer composite elements intended for vehicle suspension applications. A single-degree-of-freedom (SDOF) quarter-car model is employed to derive fundamental expressions for natural frequency, damping ratio, logarithmic decrement, and displacement transmissibility. The primary contribution lies in establishing explicit analytical linkages between material-level viscoelastic properties specifically storage modulus and loss modulus and system-level suspension parameters including stiffness and damping coefficients. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 561–570 Read article