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252 articles for “hybrid structure”
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Real-Time Edge Detection Camera Module Using Discrete Taylor Transform and Heat Equation (PDE): An Applied Mathematical Approach
Abstract: In modern digital signal processing, the capability for denoising and smoothing in real time is very important in scientific, engineering, and industrial applications. This paper presents an efficient hybrid framework that merges two mathematically sound methods, namely, DTT and PDE defined as the Heat Equation, to robustly denoise a signal with minimal distortion. The model addresses one of the most challenging tasks in signal restoration, which maintains the fidelity of …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 9–14 Read article
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English Literature in the Digital Era: Transformations and Trends
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 27–32 Read article
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The Role of Digital Innovations in the Transition of English Literature
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 Read article
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Design and Implementation of A 4-bit Multiplier using Wallace Tree Architecture in 180 nm Technology
Abstract: Over the period of last decade, power dissipation has become one of the most important factors for VLSI designers in the design of most digital systems. Even though the speed and area are considered to be the critical factors in design of digital systems, there is a trade of with power consumption. Adders and multipliers are the most important arithmetic units in a processor and the major sources of power …
Published in Journal of Microcontroller Engineering and Applications · Vol. 2, Issue 1, 2015 · pp. 17–23 Read article
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Robust Control System for Missiles in the Presence of Uncertainty and Disturbances: A Comprehensive Review
Abstract: In today's warfare and defense systems, when precise and quick maneuvering is essential for mission accomplishment, missiles play a critical role. Nonetheless, the intricacy of missile dynamics by itself, combined with external disruptions and unpredictabilities in operational circumstances, provides challenging but ambitious conditions for achieving precise trajectory tracking and robust flight control. Missiles perform in highly dynamic and uncertain environments where factors such as aerodynamic disturbances, various atmospheric conditions, and …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Carbon-Al Synergy: Investigation of Fiber Stacking and Orientation on the Mechanical Properties of Al-CFRP Metal Matrix Composites
Abstract: The current study examines the mechanical behaviour of Aluminum-Carbon Fiber Reinforced Polymer (Al-CFRP) composites fabricated using compression moulding technique, a novel approach combining lightweight aluminium’s ductility with CFRP’s high strength-to-weight ratio. The polymer composites were fabricated by stacking aluminum alloy sheet of 0.5mm thickness and pre-impregnated by 12 layers of carbon fiber cloth of 200 gsm, with epoxy resin between layers, followed by consolidation under controlled temperature and pressure in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 340–354 Read article
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Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
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Structure–Optical Property Correlation of Co-Doped TiO₂ and ZnO Nanofillers for Advanced Functional Composite Applications
Abstract: This study investigates the enhancement of the structural and optical properties of titanium dioxide (TiO₂) and zinc oxide (ZnO) nanoparticles through cobalt (Co) doping. Pristine TiO₂ and ZnO are widely studied metal oxides; however, their large band gaps and limited visible-light absorption restrict their performance in optoelectronic, photocatalytic, and environmental applications. Co doping is employed as an effective strategy to overcome these limitations by inducing band-gap narrowing, creating defect-related electronic …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1374–1394 Read article
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Next-Generation Conductive Polymer Composites for Flexible and Wearable Electronics
Abstract: The rising demand for flexible and wearable electronics has accelerated research into conductive polymer composites (CPCs) due to their lightweight nature, electrical conductivity, and mechanical flexibility. Despite significant advancements, challenges such as reduced conductivity under mechanical deformation and limited durability persist. This study aims to develop next-generation CPCs with enhanced conductivity, flexibility, and self-healing capabilities. Hybrid nanofillers—graphene, carbon nanotubes (CNTs), and silver nanowires (AgNWs)—were incorporated into bio-based conductive polymers through …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 550–566 Read article
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A Ventilated Dual-Function Photonic–Phononic Metasurface for Simultaneous Passive Radiative Cooling and Low-Frequency Noise Mitigation in Building Envelopes: Conceptual Design and Computational Feasibility Analysis
Abstract: Acoustic metamaterials for sound insulation and photonic/radiative-cooling metamaterials for passive thermal management have each matured separately for building-envelope retrofit, but existing studies address ventilation, acoustic damping and radiative thermal control in isolation, and no reported unit-cell architecture co-designs all three within a single shared structure. This gap persists because materials that are acoustic absorptive are generally dense and structurally opaque, whereas materials that are highly solar-reflective are conventionally applied to …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 2, 2026 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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A Review on Hybrid Inorganic–Polymer Analog Nanocomposites Incorporating Pozzolanic Wastes and nano-Additives
Abstract: The recent progress of polymer matrix nanocomposites (PMNCs) reveals that the performance of matrix and filler is at the core of matrix–filler interaction, interfacial bonding, and well-controlled distribution of nanoscale reinforcements. Applying these concepts, we consider inorganic particulate systems as hybrid nanocomposites, in which a discontinuous inorganic matrix is effectively reinforced via synergistic co-incorporation of pozzolanic wastes and nano-additives. In the composite system described above, silica-, alumina-rich pozzolanic materials serve …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 131–141 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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Evaluation of Mechanical Properties of Terminalia Chebula and Teak Wood Sawdust Reinforced Polymer Hybrid Composites
Abstract: This study examines the mechanical characteristics of polymer hybrid composites augmented with sawdust from teak wood and Terminalia chebula (Kadukkai). To examine their effects on mechanical performance, the composites were made with different percentages of biofiller (10%, 20%, 30%, 40%, and 50%) while keeping the proportions of the two reinforcements same. Tensile, flexural, and impact tests were performed to assess their strength properties. The findings showed that flexural strength varied …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 469–476 Read article
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Chemical and Electrocoagulation Methods for Polymer Synthesis and Composite Manufacturing: Recent Technological Advances and Extensive Application Analyses
Abstract: Recent years have seen big steps forward in the fields of polymer production and composite making, thanks to the development of new chemical and electrocoagulation techniques. This abstract gives a short summary of these new developments and goes into great detail about how they can be used. Chemical production of polymers has been an important part of materials science for a long time because it lets scientists precisely control the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 244–258 Read article
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Characterization and Fabrication of Particle Board from Banana Fiber and Sawdust as A Hybrid Composite
Abstract: The current global landscape emphasizes the search for eco-friendly and regenerative materials. Utilizing environmentally available fibers in conjunction with polymeric resins through efficient manufacturing processes offers a cost-effective solution with high-quality standards. Polymer matrix composites with fiber reinforcements possess several advantages, including low production costs, ease of fabrication, and improved material properties, making them applicable in a wide range of industrial contexts. This paper emphasizes the creation of Particle boards …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 192–200 Read article
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AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 8–17 Read article
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Review of Thermal Performance of Solar Air Heaters: Influence of Composite Materials and Advanced Thermal Storage Techniques
Abstract: Solar air heaters (SAHs) are essential devices for capturing solar energy and converting it into heat, finding applications in steam generation, refrigeration, agricultural drying, and space and water heating in residential and commercial environments. However, the thermal performance of SAHs is often limited by the low heat transfer coefficient of air and the absence of solar energy during nighttime, impacting efficiency and reliability. To address these challenges, this study explores …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 488–506 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article