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558 articles for “structural modeling”
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Thermo–Electrical Performance Enhancement of a Lightweight Polymer–Metal Hybrid Electrostatic Precipitator Using Epoxy-Based Composite Housing for Industrial Particulate Control
Abstract: Airborne particulate emissions, particularly PM₁₀ and PM₂.₅ produced by industrial activities and combustion processes, they continue to pose a significant threat to both the environment and public health. Electrostatic precipitators (ESPs) are widely recognized for their ability to achieve high collection efficiencies; however, conventional metallic constructions often lead to increased system weight, higher fabrication costs, and long-term corrosion-related challenges. In this study, a lightweight hybrid material approach is proposed by …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 652–668 Read article
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Group-Theoretic Symmetry Indices for Modular Building Layouts under Seismic Load Redistribution
Abstract: Symmetry in modular buildings operates simultaneously as an architectural language, a structural regularizer, and a computational design variable. This paper develops a group-theoretic framework for evaluating and optimizing plan symmetry in modular buildings subjected to seismic load redistribution. The building layout is modeled as a finite occupancy–stiffness field defined on a rectangular lattice, where each module encodes both mass and stiffness contributions. Planar reflections and quarter-turn rotations are represented as …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 01–07 Read article
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High-Velocity Impact Response of CFRP and Hybrid Composites: A Comprehensive Review on Ballistic Resistance and Damage Mechanisms
Abstract: This review consolidates recent advances in the study of high-velocity impact response of carbon fiber reinforced polymer and hybrid composites. Carbon fiber reinforced polymer composites are widely applied in aerospace, automotive, and defense due to their high strength-to-weight ratio, stiffness, and durability. However, their susceptibility to impact damage such as delamination, matrix cracking, and fiber breakage limits their performance under dynamic loading. To overcome these challenges, researchers have explored reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 100–122 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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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 Read article
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A Comparative Analysis of Factors Contributing to Relapse in Alcohol and Opioid Dependence Among Patients Admitted to Selected Hospitals in Ludhiana, Punjab.
Abstract: Introduction: Substance abuse involves the dangerous or detrimental use of psychoactive substances, such as alcohol and illegal drugs. The use of these substances can result in dependence syndrome, which encompasses a range of behavioral, cognitive, and physiological effects that arise from ongoing substance use. Objectives: This study was carried out to examine the factors linked to relapse in alcohol and opioid dependence among patients admitted to selected hospitals in Ludhiana, …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Association between Diabetes Type and Family History of Diabetes: A Cross-Sectional Analysis of Gender Differences and Genetic Influences
Abstract: Introduction: Diabetes mellitus DM is one of the fast-growing chronic metabolic disorder in the world, with high impact and burden in low- and middle-income country. Although genetic predisposition is a central determinant of diabetes risk, particularly for Type 2 diabetes (T2D), the contribution of familial aggregation varies across populations. In many parts of the world where diabetes is rising very fast understanding the relationship between diabetes type and family history …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 43–50 Read article
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Battery Management System (BMS)
Abstract: This review of the literature delves into the changes, structure, and the latest BMS (Battery Management Systems) technologies implemented in electric vehicles, smart grids, and energy storage, respectively. The studies emphasize the need for accurate battery modeling, advanced estimation algorithms, robust hardware design, and safety regulations. The research describes how contemporary BMSs perform integration of modeling, monitoring, control, cell balancing, and diagnostics in order to facilitate safe and energy- efficient …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 32–43 Read article
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Enhancing Image Classification Performance with Deep Neural Networks
Abstract: Classifying images is useful in many domains, including the study of plant diseases and the analysis of human expressions. Image categorization employing the idea of a “deep neural network” helps to compact otherwise cumbersome photos. It is possible to classify images by using the idea of a “deep neural network”. Self-driving cars, medical diagnosis, automatic translation, etc., all make use of Deep Neural Networks. Recently, excellent results have been achieved …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 13–23 Read article
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Integrating Plant Selection, Planting Design, and Landscape Construction for Sustainable Site Development
Abstract: This paper explores the interrelationship between plant selection, planting design, and landscape construction in achieving ecologically sustainable and aesthetically pleasing outdoor environments. Plant selection involves choosing species that are well adapted to site conditions, ecological functions, maintenance regimes, and visual preferences. Planting design refers to the arrangement, composition, and spatial organization of plant materials to meet functional, aesthetic, and environmental objectives. Landscape construction encompasses implementation—from site preparation and planting through …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 7–12 Read article
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Image-Based Quantitative Mapping of Structure Property Relationships in Polymer Composite Materials
Abstract: The performance of polymer composite materials is intrinsically governed by their microstructural architecture, which is shaped by manufacturing conditions and constituent interactions. Despite extensive experimental characterization efforts, establishing transparent and quantitative structure–property relationships from microstructural images remains a challenge. In this study, an explainable image-driven framework is developed to systematically correlate microstructural features with composite property indicators. Microstructure images are processed to identify voids, fibers, and filler phases, from which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 188–196 Read article
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InSilico Analysis and Homology Modeling of Tetrahydroprotoberberine Oxide involved in the Berberine Biosynthesis
Abstract: Objective: Berberine, a bioactive compound found in various plant species, exhibits diverse pharmacological properties with potential applications in pharmaceutical research. The biosynthesis of berberine involves several enzymatic steps, with (S)-tetrahydroprotoberberine oxidase playing a pivotal role. This study aimed to elucidate the structural and functional characteristics of (S)-tetrahydroprotoberberine oxidase to better understand its role in berberine biosynthesis and its potential biotechnological applications. Methods: Using bioinformatics tools and computational methods, the physicochemical …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 1, 2024 · pp. 7–26 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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Advanced Processing Technologies and Material Properties of Ceramic-Matrix Composites for Structural and Industrial Applications
Abstract: Ceramic-matrix composites (CMCs) are becoming more popular as building and industrial materials because they have a unique set of qualities, such as being able to withstand high temperatures and being light and strong. This brief talks about the newest improvements in processing methods and material features that have put CMCs at the top of the list of industrial materials. Using advanced processing methods like chemical vapor infiltration (CVI), polymer infiltration …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 138–151 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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A Comprehensive Study of Radial Load Fluctuation on Alloy Wheels for Electric Vehicles
Abstract: Electric Vehicle’s alloy wheels are designed to allow for better heat dissipation. Manufacturers carry out many tests of a wheel to be sure, that the wheel will fit for safety reason as also their comfortability level is even bigger. Therefore, a specific design was selected for which the simulations of alloy wheel were performed under real loading conditions. The main objective of this research is to analyze the effects of …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 47–56 Read article