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309 articles for “Hybrid Optimization”
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Carbon based Supercapacitor for Electric Vehicles
Abstract: Carbon materials, like activated carbon, and graphene, are abundant and can be produced sustainably. This eco-friendliness aligns well with the overarching goals of electric vehicle manufacturers who are keen to diminish their carbon footprint. Their compatibility with renewable energy systems also opens avenues for integrated energy solutions, enhancing overall system efficiency. Carbon-based supercapacitors hold significant promises as complementary energy storage devices in the electric vehicle landscape. While challenges related to …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 3, 2024 · pp. 01–11 Read article
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Solar Thermal Energy Utilization: Design Innovations and Performance Enhancement Techniques
Abstract: The utilization of solar thermal energy has become increasingly significant in the pursuit of sustainable and low-carbon energy solutions. Unlike photovoltaic technologies that directly convert sunlight into electricity, solar thermal systems focus on harnessing solar radiation to generate heat, which can then be applied to diverse sectors such as water heating, space conditioning, industrial process heating, and power generation. In recent years, substantial research efforts have been directed toward enhancing …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Selection of Appropriate Porous Material for Designing and Developing Hybrid Absorptive Muffler: A Wave 1-D Based Approach
Abstract: In this study, glass wool and rock wool are used as sound-absorbing materials to assess the sound transmission loss (STL) of hybrid absorptive mufflers. Improving the muffler's acoustic performance and assessing how well these materials attenuate noise are the main goals. Rock wool, which offers greater thermal resistance and broader frequency absorption, is contrasted with glass wool, which is renowned for its lightweight construction and high-frequency absorption. Wave 1-D simulation …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 148–160 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Modelling and Control of Grid-Connected PV–Battery Hybrid System Using Dynamic Voltage Restorer for Enhanced Power Quality
Abstract: The integration of large-scale photovoltaic (PV) systems into modern power grids introduces significant challenges in maintaining power quality, including voltage sags, swells, and harmonics. To address these issues, this study presents a comprehensive modelling and control framework for a grid-connected PV–Battery hybrid system equipped with a Dynamic Voltage Restorer (DVR). The PV array is modelled using detailed mathematical equations, while the DC–DC converter incorporates advanced Maximum Power Point Tracking (MPPT) …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 43–58 Read article
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Hurdle and Opportunities of Electric Vehicle in India: A Review
Abstract: Air pollution has become a major concern for India. In every alternate news headline, many cities have a pollution index above the living standard. To reduce the emissions of greenhouse gases, electric vehicles are the most important option. It reduces the dependency on fossil fuels as well as reduces the impact of ozone-depleting substances and promotes large-scale renewable deployment. Despite comprehensive research on the attributes and characteristics of electric vehicles …
Published in Journal of Automobile Engineering and Applications · Vol. 10, Issue 1, 2023 · pp. 19–23 Read article
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Computational Simulations in Drug Discovery: Modeling Protein Folding and Drug Binding
Abstract: Computational simulations have become essential tools in drug discovery, offering unprecedented insights into molecular behavior at the atomic level. These simulations, particularly in the domains of protein folding and drug binding, allow for the exploration of complex biological systems that are often difficult to study experimentally. Protein folding, a critical aspect of drug discovery, involves the transition of a polypeptide chain from an unfolded to a biologically active structure. Understanding …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 23–29 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 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
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Sustainable Development of Carbon–Sisal Reinforced Polyester Composites through Green Nanotechnology
Abstract: This study presents the sustainable development of carbon–sisal fiber reinforced polyester composites enhanced through green nanotechnology for improved mechanical performance and environmental compatibility. The hybrid composites were fabricated using varying fiber ratios - C1 (70% carbon, 30% sisal), C2 (60% carbon, 40% sisal), and C3 (50% carbon, 50% sisal) - with an optimized addition of 1 wt.% nano-silica (SiO2) synthesized via a green sol–gel route. The tensile, flexural, and impact …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1179–1194 Read article
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Hybrid Additive-Subtractive Manufacturing of Multi-Material Functionally Graded Components: Integration of Laser Powder Bed Fusion with High-Speed CNC Finishing for Aerospace Applications
Abstract: The synergy involved in the merging of additive and subtractive manufacturing technologies is the game changer to generate multi-material functionally graded components to be used in the aerospace industries. The paper is an in-depth review of a proposed hybrid additive-subtractive manufacturing, which synergistically merges laser powder bed fusion (LPBF) fashioning with rapid computer numerical control finishing production processes. The multi-material deposition, thermal issues, and optimization of post-processing are the challenges …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 398–418 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Transforming Transportation in India: Exploring the Challenges and Opportunities of Electric Vehicles
Abstract: They also help lessen the impact of ozone-depleting substances and support the widespread adoption of renewable energy. Although significant research has focused on EV features, performance, and charging infrastructure, challenges in production and network modeling persist. This paper provides an overview of various EV technologies, including EVs, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), and evaluates their market penetration rates. It explores various …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 17–23 Read article
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Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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Thin Film Technology in Sensor Manufacturing – A Technical Discussion
Abstract: Thin‑film technology has become the cornerstone of modern sensor manufacturing, enabling the convergence of miniaturisation, multifunctionality, and cost‑effective mass production. This paper surveys the latest advances in deposition techniques—ranging from magnetron sputtering and chemical vapour deposition to atomic‑layer deposition (ALD) and ink‑jet‑printed sol‑gel processes—and examines how their unique material‑control capabilities translate into performance gains across the sensor spectrum (chemical, physical, and bio‑sensing). By integrating nanoscale thickness control (≤ 10 nm) …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 13, Issue 1, 2026 · pp. 47–57 Read article
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Radiopaque Polymer Composites for Improved Visualization of Interventional Devices
Abstract: Radiopaque polymer composites are increasingly important for improving the visualization of interventional medical devices under X-ray and fluoroscopic imaging while maintaining the flexibility, mechanical performance, and processability required for minimally invasive applications. This narrative review summarizes recent developments in radiopaque polymer composites, with emphasis on radiopaque filler selection, polymer–filler interactions, processing strategies, structure–property relationships, biocompatibility, and device applications. A focused literature search was conducted using PubMed, Scopus, Web of Science, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Thermoelectric Waste Heat Recovery from Industrial Exhaust Systems Using Nanostructured Hybrid Heat Exchangers
Abstract: The efficient utilization of industrial waste heat has become a critical strategy for improving energy efficiency, reducing fossil fuel consumption, and minimizing greenhouse gas emissions in modern manufacturing sectors. This study proposes a thermoelectric waste heat recovery (TWHR) system integrated with a nanostructured hybrid heat exchanger to enhance heat transfer performance and maximize electrical power generation from high-temperature industrial exhaust streams. The proposed system employs nanostructured surface modifications combined with …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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Chemical Modifications and Tensile Properties of Areca Leaf Sheath Fiber Reinforced Polymer Composites: A Comprehensive Review
Abstract: Areca leaf sheath (ALS) fiber is a promising eco-friendly material, offering a sustainable, lightweight, and cost-effective alternative for low-strength applications. Its natural biodegradability aligns well with the growing global demand for environmentally responsible materials. This review explores the transformative effects of chemical treatments, such as alkali, silane, and benzoylation, on the tensile properties of Areca leaf sheath fibers. Among these, alkali treatment consistently demonstrates the most significant improvement in tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 94–106 Read article