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343 articles for “optimization framework”
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Harnessing Sustainable Technologies: Advancing Renewable Energy for Climate Change Mitigation
Abstract: Climate change poses a significant threat to global ecosystems, economies, and human livelihoods, necessitating urgent action to transition toward sustainable technologies. Renewable energy systems have emerged as a cornerstone of this effort, offering clean, efficient, and scalable alternatives to fossil fuels. This paper explores the critical role of sustainable technologies in mitigating climate change, focusing on advancements in solar, wind, hydroelectric, and biomass energy systems. Key innovations, such as high-efficiency …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 11–18 Read article
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Integrated Perspectives on Fluid Mechanics and Energy Transport in Complex Flow Systems
Abstract: Fluid mechanics plays a central role in understanding the transport of mass, momentum, and energy in complex flow systems encountered in both natural and engineered environments. This review presents an integrated perspective on fluid behavior by combining fundamental principles with modern approaches to energy transport analysis. The study emphasizes the significance of conservation laws and their application to diverse flow regimes, including laminar, turbulent, compressible, and multiphase flows. Energy transport …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 22–31 Read article
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Analysis of Machine Learning in Metal Processing: A Novel Prospect
Abstract: Metal is processed by a wide range of procedures, from forming and casting to machining and riveting. Metal processing is a crucial part of modern manufacturing. The application of machine learning (ML) is driving a significant change in the sector, which has historically depended on empirical knowledge and trial-and-error techniques. Increased production, improved product quality, and resource optimization are expected outcomes of this action. This study aims to explore the …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 40–51 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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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Reduction of Air Pollutants of Urban Canyons through Management of Particulate Matters 2.5 in the Streets
Abstract: Urban canyons are long and high sky-scrappers closely to narrow streets result in very different microclimate challenges. These spaces often trap pollutants and restrict air circulation and intensify more retention of heat making them very uncomfortable for pedestrians. In order to resolve this issue a strong set of design guidelines and frameworks were needed which can balance out the human comfort and environmental aspects. This research studies strategies to improve …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–23 Read article
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Optimization and Structural Integrity of Truck Chassis Using Finite Element Analysis
Abstract: The chassis of a truck is a crucial component, and it acts as a framework for the body and other components of the truck. It must also be strong enough to withstand pressures like shock, twisting, vibration, and more. When building a chassis, having enough bending stiffness for better handling characteristics is just as important as strength. Deflection, maximum stress, and maximum equilateral stress are crucial design factors for the …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article
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Exploring the Future of Operating Systems: Architectural Innovations and Kernel Development Trends
Abstract: Modern applications and the rapid evolution of hardware technologies are challenging operating system (OS) design. This paper speculates the future of OS based on revolutionary architecture advancements and emerging possibilities in kernel construction. The growth of multi-core processors, spread-bound processing, and edge architectures have challenged traditional OS paradigms. The paper provides an analysis of the progress in microkernel and monolithic kernel structures, discussing the bandwidth capacity as well as security …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 38–47 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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AI-Driven Sustainable Supply Chain Framework for Polymer Composite Production
Abstract: As polymer composite processes become more difficult and environmental concerns increase, old supply chain models that just look at cost and operations have shown significant weaknesses when it comes to sustainability. The rising demand for environmentally friendly practices throughout a product’s life cycle requires a new process that makes sustainability a key element in making supply chain choices. The proposed framework was developed in response to this need by using …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 219–235 Read article
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Role of Therapeutic Index for Local Infections Score in Wound Assessment
Abstract: Local wound infections pose a significant challenge, often detected later, leading to complications like systemic infections. Global nomenclature lacks uniformity, resulting in varied treatments for similar diagnoses. Early intervention is crucial, advocating for local antimicrobial therapy with diverse active agents to avoid systemic antibiotics and mitigate bacterial resistance. The Therapeutic Index for Local Infections (TILI) score, innovated by the German society Initiative Chronis Che Wenden (ICW), emerges as a pivotal …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 44–48 Read article
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Design, Mathematical Modeling, and Dynamic Optimization of a Speed Breaker-Based Vehicular Kinetic Energy Harvester
Abstract: Decentralized energy harvesting methods are becoming more popular due to rapid urbanization and the rising need for sustainable infrastructure. The road-embedded vehicle kinetic energy harvester (VKEH) design, mathematical modelling, and experimental validation are presented in this work. This paper presents the structural engineering, continuum mathematical modeling, and experimental validation of an optimized road-embedded vehicular kinetic energy harvester (VKEH). The mechanism utilizes a spring- loaded, low-friction rack-and-pinion transmission coupled with a …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
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Secure Framework for Government Tender Allocation
Abstract: Governments and public sector entities worldwide are actively seeking innovative strategies to adapt to rapid technological progress, aiming to enhance governance effectiveness, streamline work processes, and optimize expenditure. Blockchain technology stands out as a prime example, captivating the interest of governments globally in recent years. Its ability to offer heightened security, enhanced traceability, and cost-efficient infrastructure positions blockchain as a versatile solution applicable across diverse sectors. Typically, governments engage third-party …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 23–27 Read article
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Optimizing Mango Harvest Timing in the Nasik Region (Maharashtra, India) by CNNs (Residual Network 101)
Abstract: The determination of optimal harvest timing is one of the most critical decisions in mango production, directly affecting postharvest quality, market value, transportation resilience, and export readiness. In regions such as Nashik, Maharashtra—one of India’s major fruit- producing belts—the climatic variability, cultivar differences, monsoon patterns, and market- driven pressures make accurate harvest timing essential. Traditional maturity assessment relies on subjective visual inspection, specific gravity, or destructive testing, each of which …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article