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227 articles for “Hybrid Approach”
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Synthesis of Silver Nanoparticles of Cissus Quandrangularis and It’s Virtual Screening Against Gastric Cancer
Abstract: Gastric cancer, also known as stomach cancer, is the third leading cause of cancer-related deaths globally and remains a major health challenge due to its poor prognosis and high mortality, largely attributed to late-stage diagnosis. In this context, plant-based nanomaterials are gaining momentum for targeted therapeutic applications. Cissus quadrangularis, a medicinal plant native to India from the Vitaceae family, is traditionally used for its diverse healing properties. Its stem, in …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1551–1569 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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Impact of Self-Help Groups (SHGs) on Sustainable Livelihood Development in Rural Uttarakhand: A Study on the Influence of DAY-NRLM in Income Generation and Community Empowerment
Abstract: Self-Help Groups (SHGs) have emerged as a vital mechanism for fostering sustainable livelihoods in Uttarakhand, a region challenged by poverty, migration, and unemployment. This study examines the role of SHGs in expanding livelihood programs and empowering members, particularly in income generation, while highlighting the importance of group-based approaches for vulnerable communities like small farmers and craftsmen. Data collection for the study involved a questionnaire targeting 288 respondents across 100 SHGs …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 46–54 Read article
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Ranking of Epoxy/Kota Stone Dust/Fly Ash Composite Using Integrated AHP-TOPSIS Approach
Abstract: The generation of industrial waste is a significant contributor to environmental pollution. The stone industry is no exception to this, and it is known to produce a significant amount of waste. The Kota Stone Industry in India is one such industry that generates waste. This research article focuses on composite material selection for mechanical and structural applications by fabricating epoxy composites reinforced with Kota stone dust and fly ash using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 36–42 Read article
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Deep Learning-Enhanced Polymer-Based Wearable Biosensors for Continuous Health Tracking via IoT
Abstract: The rapid proliferation of wearable biosensor technologies has transformed approaches to real-time health monitoring, yet challenges persist in achieving both mechanical robustness and reliable, continuous data analytics in dynamic environments. Conventional polymer-based sensing systems often fall short due to limited signal fidelity, inadequate adaptive analytics, or insufficient integration with secure, low-latency IoT frameworks. Addressing these deficiencies, this work introduces a flexible, deep learning-enhanced wearable biosensor platform that combines a nanostructured …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 18–31 Read article
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Role of Functional Regenerative Trilaminar Scaffold Dressing in Wound Bed Preparation
Abstract: Advancements in wound healing have incorporated tissue regeneration therapy as a crucial tool for managing both acute and chronic wounds. Bio constructs designed to facilitate wound regeneration utilize natural, artificial, or hybrid materials, collectively referred to as regeneration scaffolds. The components of regeneration scaffolds play a crucial role in enhancing the skin's natural self-renewal abilities and accelerating the healing process. These scaffolds are designed to provide essential growth factors and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 70–75 Read article
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Green Energy and Intelligent Transportation: The Role of Composite Materials in Electric and Automotive Sectors
Abstract: The global transition toward sustainable mobility is accelerating, driven by mounting concerns over climate change, urban congestion, and the rapid development of green energy technologies. At the heart of this transformation lie intelligent transportation systems (ITS) and electric vehicles (EVs), which are collectively reshaping the future of modern transportation. Within this context, composite materials have emerged as key enablers, offering lightweight, durable, and energy-efficient solutions that enhance vehicle performance, range, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1096–1111 Read article
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Low-Grade Heat Recovery: Emerging Materials and Systems for Efficient Utilization
Abstract: Low-grade heat (LGH), generally characterized by temperatures below 200°C, constitutes a significant portion of wasted thermal energy in industrial, commercial, and even residential processes. Despite its vast availability, the efficient recovery and utilization of LGH remains underdeveloped due to its inherently low exergy content and the limitations of traditional heat recovery technologies. The creation of cutting-edge materials and creative system-level approaches for LGH recovery has accelerated significantly as companies continue …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 24–29 Read article
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A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments
Abstract: Fuzzy mathematics play an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and it signs other possible solutions in addition to fuzzy mathematics. Fuzzy models offer a versatile and precise approach to assessing complex situations through the use of fuzzy sets, membership functions, and aggregation methods. Through time, cost and quality, the project management case study illustrates how fuzzy logic works for them. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
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A Hybrid model of ResNet50 integrated U-Net for image Denoising for Polymer and Composite Microstructure Analysis
Abstract: In digital era a high-quality imaging plays a very important role in polymer and composite material characterization features such as fiber-matrix interfaces, voids, microcracks cause problems in mechanical and functional properties. Polymer imaging includes optical microscopy and scanning electron microscopy, due to sensor limitation, environmental conditions add noise to the image and reduce quality of image. The noise degrades image quality, and it leads to reduce reliability in material analysis. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 592–602 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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A Retrospective Analysis of Resin-Based Polymer Composites and Bioactive Glass-Polymer Hybrids Regarding Secondary Caries and Durability
Abstract: Aim- To compare the 2-year clinical survival and failure modes of a Resin-Based Polymer Composites and BioactiveGlass-Polymer Hybrids in Class I and II posterior restorations. Methods-A total of 550 restorations were placed in adult patients across various private dental practices in India to ensure a diverse clinical demographic. Teeth were randomly assigned and restored with either a hybrid composite (Te-Econom, IvoclarVivadent; n=275) or a Resin-Modified Glass Ionomer Cement (GC Gold …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1089–1095 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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Sustainable Innovations in Vapor Compression Systems: A Review of Heat Recovery and Environmental Performance
Abstract: Vapor compression refrigeration systems are widely used in residential, commercial, and industrial sectors, contributing significantly to global energy consumption and greenhouse gas emissions. This review explores sustainable innovations in vapor compression systems, focusing on waste heat recovery techniques and their impact on environmental performance. Key advancements include the integration of heat exchangers, ejector systems, and hybrid configurations that enhance energy efficiency while reducing refrigerant load and emissions. With a focus …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 16–21 Read article
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IT Security and Intrusion Detection Systems: An Introduction
Abstract: This article deals with the current status of IT security in an industrialized country and one of the many approaches. The emphasis is on what are known as intrusion detection systems. These enable users to detect suspicious behavior and attacks in daily IT operations by analyzing data, resources, and network flows. Based on previous research, the different variants, available detection types, and their working methods are briefly explained and presented. …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 10–17 Read article
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Design and Simulation of Low-power, High-speed Effective Area Mux Based One-bit Full Adder Using CMOS Technology
Abstract: Our findings reveal a novel kind of circuit capable of performing both XOR and XNOR operations in parallel. Power dissipation and delay are both greatly reduced in the proposed circuits due to their low output capacitance as well as minimal short-circuit power dissipation. We show six new hybrid 1-bit full-adder (FA) circuits that take use of the XOR-XNOR or XOR/XNOR gates' special full-swing function. Each potential circuit layout has both …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 1, 2023 · pp. 25–33 Read article
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Study on Partial Replacement of Cement with Pinus Fiber and Nano Silica in M30 Concrete Paver Blocks: A Fiber-Reinforced Polymer-Cement Composite Approach
Abstract: This study investigates the partial replacement of cement in M30 grade concrete paver blocks using nano silica and Pinus fiber, with a primary focus on mechanical performance, sustainability, and long-term durability and promoting sustainability. Portland cement, a major contributor to global CO₂ emissions, can be partially substituted using supplementary materials to create eco-efficient construction solutions. Nano silica, due to its high pozzolanic reactivity and ultrafine size, improves the microstructure and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 63–76 Read article
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 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