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1732 articles for “Predicting”
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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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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Polymer Encapsulants for Photovoltaic Modules: Electrical Insulation Performance and Long-Term Durability under Accelerated UV Exposure
Abstract: Influence on the reliability and service life of PV modules is a major issue, which is influenced by the encapsulant degradation in long-term exposure to the sun's ultraviolet (UV) radiation. A systematic accelerated UV aging study of Ethylene Vinyl Acetate (EVA), Polyolefin Elastomer (POE), and Polyvinyl Butyral (PVB) films under IEC 61215-2:2021 specified test chamber conditions of Q-UV is conducted. The material properties were tested at various exposure intervals including …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 384–408 Read article
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Climate Change Threat in Jaipur: Mitigating and Sustainable Attributes Through Carbon Footprint Reduction
Abstract: Challenges of climate change are significantly increasing on a forward time scale. Such a phenomenon is predominantly seen in urban sectors where population is rapidly increasing, thereby resulting in extensive resource consumption leading to release of significant carbon footprint. An attempt has been made in the present paper by the authors initially to assess the carbon footprint of Jaipur, Rajasthan on a backward and forward time scale partly to suggest …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 35–50 Read article
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Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely unsustainable as the urban regions were growing rapidly. Manual digitization was expensive and lacked geometric precision. This paper introduces an automated, end-to-end GEO AI-powered framework for high-end fidelity building footprint extraction from Google Satellite Data. Our approach for this …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Integrated Explainable Forecasting and Metaheuristic PI Optimization for LFC/AGC
Abstract: Since the last decade world has seen a paradigm shift towards alternate sources of energy, due to significant increase in population and ever-rising demand. However, the traditional systems were not designed to cope with these alternate sources and on the other hand these systems are posed with the challenges of efficiency and intermittency. So, it is inevitable that we need to design a system wherein forecasting data has to be …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 · pp. 26–32 Read article
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Advancements in Battery Storage Technology for Renewable Energy Systems: Improving Reliability and Efficiency of Sustainable Energy
Abstract: Advances in battery storage technology are critical to improved reliability and efficiency of renewable energy systems, underpinning a sustainable energy future. Innovations exist in many different kinds of battery technologies- being developed and tested, and the leading contenders include innovations such as lithium-ion and sodium-ion, and much newer entrants like the solid-state and lithium-sulfur batteries. These developments respond to growing needs for sustainable solutions towards better integration of intermittent renewable …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 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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Viscoelastic Behavior, Interfacial Mechanics, and Reliability of Polymer Interlayers in Laminated Glass Composites: A Comprehensive Review
Abstract: The laminated glass systems are regarded as hybrid polymer–glass composites where the viscoelastic behavior of polymer interlayers mostly controls mechanical response. These interlayers (polyvinyl butyral (PVB), ionoplast, ethylene-vinyl acetate (EVA), etc.) have time-, temperature- and rate-dependent properties which significantly affect shear transfer, energy dissipation, and fracture resistance. But the baseline polymer-relevant processes at the molecular and interfacial level are to a large extent unknown [1]. This review provides a materials-focused …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 258–268 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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NeoVax: Smart Child Vaccination and Monitoring Platform
Abstract: Child vaccination plays a crucial role in preventing life-threatening diseases and ensuring long-term public health. Despite the availability of structured immunization programs, many children miss scheduled vaccinations due to lack of awareness, busy lifestyles of parents and absence of effective reminder systems. This research paper presents NeoVax, a smart and user-friendly child vaccination reminder and management system designed to address these challenges using digital technology.NeoVax is an Application that enables …
Published in International Journal of Children · Vol. 3, Issue 2, 2026 · pp. 14–20 Read article
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Robotics and Automation in Mechanical Engineering: Transforming Modern Manufacturing Systems
Abstract: Robotics and automation have significantly transformed mechanical engineering, particularly in manufacturing, precision assembly, and intelligent systems integration. With the advancement of sensors, control systems, artificial intelligence, and mechatronics, robotic systems are now capable of performing complex tasks with high accuracy, repeatability, and efficiency. This article explores the role of robotics in modern mechanical applications, including industrial automation, collaborative robots, predictive maintenance, and smart manufacturing. It also discusses design considerations, challenges, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 27–33 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article