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231 articles for “hybrid techniques”
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Machinability and Reliability Analysis of Al6063–Al2O3 Metal Matrix Composites Using Image-Based Flank Wear Evaluation
Abstract: This study explores the machinability and reliability characteristics of Al6063–Al2O3 metal matrix composites (MMCs) as analogues for polymer–metal hybrid composite systems, focusing on their potential use in lightweight structural and metal matrix composite-integrated applications. The composite specimens were fabricated through stir casting with 3% and 9% Al2O3 reinforcements, followed by mechanical characterization that confirmed significant enhancements in hardness and strength compared to unreinforced Al6063. Machining experiments were performed using a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 264–290 Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Polymer-Mediated Electron Transfer in Eco-Friendly P3HT–rGO Nanocomposites for Optoelectronic Applications
Abstract: Conducting polymer–graphene hybrid nanocomposites have emerged as promising materials for next-generation optoelectronic applications owing to their solution processability, tunable interfacial properties, and mechanical flexibility. Recent studies have highlighted the importance of graphene–polymer hybrid systems in enhancing charge transport pathways, exciton dissociation efficiency, and interfacial stability in organic optoelectronic devices. Despite these advantages, a key challenge remains the efficient production of individual graphene sheets through the reduction of graphene oxide using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 413–423 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Investigation of Mechanical Properties of Banana, Linen and Their Hybrid Reinforced Composite Laminates in Adverse Condition and Analyze Using ML
Abstract: This research investigates the mechanical performance of composite laminates reinforced with banana and linen fibers, focusing on both individual and hybrid fiber combinations. The primary objective is to assess how these natural fiber composites behave under extreme environmental conditions, particularly high humidity and fluctuating temperatures, which are common in aerospace and automotive applications.Key mechanical properties—tensile strength, flexural strength, and impact resistance—are experimentally evaluated to assess the performance and long-term reliability …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 25–31 Read article
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Advancements and Challenges of Modern Breeding over Conventional Breeding
Abstract: Plant breeding dates back thousands of years, when people first deliberately bred plants based on visually pleasing characteristics. The domestication of wild plants aided this process, resulting in the evolution of numerous breeding strategies over time. Conventional breeding, which is distinguished by selective breeding based on superior performance, used procedures such as pure-line selections, mass selection, backcross breeding, recurrent selection, and hybridization. While effective, classical breeding procedures were time-consuming and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 13, Issue 1, 2024 · pp. 1–5 Read article
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Emerging Trends in Membrane-Based Gas Separation Technologies
Abstract: Membrane technology has emerged as a groundbreaking solution in various fields, revolutionizing industries such as water treatment, energy production, biomedicine, and environmental protection. Over the past few decades, significant advancements have been made in membrane materials, fabrication techniques, and performance optimization. With the growing global demand for efficient and sustainable separation processes, research has increasingly focused on enhancing membrane permeability, selectivity, and durability to improve performance across various industries, including …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 16–22 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Exploration of Mechanical Characteristics and Microstructural Analysis of Copper Matrix Composites with Hybrid Reinforcements via Muffle Furnace Sintering
Abstract: Metal Matrix Composites (MMCs) have drawn a lot of interest in the area of innovative materials because of how widely they may be used. Due to their extraordinary qualities, such as high thermal conductivity, higher temperature endurance, improved corrosion resistance, and great weldability, copper matrix composites stand out among them. These qualities make them desirable and promising materials for uses including heat exchangers, automotive parts, and electrical components. In this …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 119–126 Read article
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Effect of Welding Factors on Nugget Size of Polymer-Metal Composite Sheets Using Computational Methods
Abstract: Resistance spot welding (RSW) is a vital technique for joining materials in industries like automotive and aerospace. This study extends the application of RSW to polymer-metal composite sheets by developing 2D axisymmetric, thermo-electro-mechanical coupled model in ANSYS. The focus is on analyzing the temperature distribution, nugget formation, and parameter optimization in hybrid composite sheets, emphasizing the unique challenges posed by polymers' thermal and electrical properties. These properties differ significantly from …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 612–623 Read article
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Zeolite-Y Encapsulated Copper (II) and Cobalt (II) Species as Hybrid Nano-catalysts: Structural and Catalytic Aspects
Abstract: Special properties inherent to zeolites in facilitating the construction of novel upramolecular assemblies by encapsulation of guest molecules (metal complexes) into their large cages can be utilized to use these assembled materials as novel catalysts. These modified solids have the advantages of both behaving as the homogeneous and the heterogeneous catalytic system. In the present work, copper (II) and cobalt (II) complexes of 2-amino ethanoic acid (2-AEA) encapsulated in the …
Published in Journal of Catalyst & Catalysis Read article
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Design and Research of Thermoelectric Energy Harvesting Methods for Instantaneous Use
Abstract: In today’s consumer-oriented market, researchers are attempting to harness energy from ambient sources for sustainable energy generation leading to reduction of dependency on conventional energy sources. Energy harvesting methods offers enormous opportunities to derive energy from our natural surroundings to directly operate self-powered devices or storing it for later use. Generating energy from our nearby environment seems to be a promising solution to address the growing concerns of powering small …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Recycling and Reinforcement of Retired EV Battery Materials in Polymer Composites for Sustainable Engineering Applications
Abstract: The rapid proliferation of electric vehicles (EVs) has led to a substantial increase in lithium-ion battery waste, necessitating sustainable strategies for material recovery and reuse. This review explores the valorization of retired Electrical Vehicle batteries within polymer and composite systems, highlighting second-life applications as a promising pathway toward circular material utilization. Batteries retaining 70–80% of their original capacity remain suitable for extended use; however, beyond conventional energy storage, their constituent …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 362–371 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Development of Biomass-Derived Composites From Commodity Plastics Via Pyrolysis For Enhanced Corrosion Protection of Metals
Abstract: Escalating environmental concerns and the depletion of fossil resources have spurred the need for sustainable and eco-friendly materials. By converting plastic waste into valuable carbonaceous materials via pyrolysis, both plastic pollution and resource scarcity can be addressed. The process involves the thermal decomposition of plastics in an inert atmosphere, producing a mixture of gases, liquids, and solid residues rich in carbon. These carbonaceous residues are then incorporated with biomass materials …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 59–70 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 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