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641 articles for “technique optimization”
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Troubleshooting CSS: Common Issues and Effective Solutions for Web Development
Abstract: Many modern websites suffer from bloated and ineffective stylesheets, despite the fact that CSS is crucial for user experience and web performance. The effects of CSS optimization strategies, including minification, modularization, critical CSS extraction, lazy loading, and unused rule elimination, are simulated and assessed in this study on four representative web platform types: news portals, e-learning platforms, e-commerce sites, and SaaS dashboards. Using a controlled experimental environment and common auditing …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 44–57 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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Multi Objective Optimization of Aluminium (AA6061-SiC-Flyash) Metal Matrix Composites using TOPSIS Method
Abstract: Metal Matrix Composites (MMCs) have significant interest due to their superior mechanical properties, including improved strength, hardness, and fracture resistance. This study investigates the optimization of the mechanical and fracture behaviour of casted AA6061-SiC-Fly Ash (FA) MMCs using the TOPSIS method. Silicon carbide(SiC) and fly ash (FA) reinforcements, with different weight percentages of 5%, 10%, and 15% were fabricated through sand casting method. Total 10 combinations of composites are prepared …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 459–469 Read article
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Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Performance, Combustion and Emission analysis of Sunflower oil based Biodiesel using Non-Dominated Sorting Genetic Algorithm-II
Abstract: Biodiesel is used as alternate fuel of I. C. Engines for so many years. It is obtained from various edible and non-edible oils including waste cooking oils through trans-esterification process in the presence of catalyst. The suitable amount of biodiesel mix with commercial diesel can be used to run the compression ignition engines. The optimum combination of engine input parameters is the challenging task as required by the design engineer …
Published in International Journal of Energy and Thermal Applications · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Design and Optimization of Domain-Specific Languages for High-Performance Computing Applications
Abstract: The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven High-Performance Computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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A Comprehensive Review of CMOS Analog Circuit Design Techniques for Low-Power VLSI Systems
Abstract: CMOS analog circuit design plays a significant role in the development of modern low-power Very Large-Scale Integration (VLSI) systems used in wireless communication, biomedical devices, portable electronics, embedded systems, and Internet of Things (IoT) applications. Research on low-power CMOS analogue design methodologies has intensified because to the growing need for high-performance, small, and energy-efficient electronic products. However, reducing power consumption while maintaining signal accuracy, noise performance, stability, bandwidth, and overall …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Thermal Performance Analysis and Optimization of Pin-Fin Heat Sink Using CFD, Taguchi Method, and Machine Learning
Abstract: Efficient thermal management is essential for improving the performance and reliability of modern engineering systems and electronic devices. This study presents the design, simulation, and optimization of a pin-fin heat sink using SolidWorks for three-dimensional modeling and ANSYS for thermal and computational fluid dynamics (CFD) analysis. Four different pin-fin geometries, namely square, pentagon, octagon, and circular fins, are considered to evaluate their thermal performance under varying operating conditions. Aluminum is …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Nanofluids: Advanced Synthesis Methods, Innovative Applications, and Future Directions
Abstract: Nanofluids, a novel mixture of nanoparticles and base fluids, is an innovative blend that has appeared as a transformative advancement in heat transfer and thermal management technologies. This study is going to discuss advanced synthesis methods, properties, and extensive applications of nanofluids in various fields, such as biomedical engineering, electronics cooling, solar energy, and machining. Optimization techniques such as nanoparticle selection, concentration control, and computational fluid dynamics modelling are also …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Investigative Study of Adaptive Fault Tolerance in Optical Networks
Abstract: Optical networks have become the backbone of modern telecommunications infrastructure, enabling high-speed data transmission across global networks. However, these networks face significant reliability challenges due to component failures, signal degradation, and environmental factors. This investigative study examines adaptive fault tolerance mechanisms in optical networks, focusing on emerging technologies and methodologies that enhance network resilience. The research analyzes various fault detection techniques, including machine learning-based approaches, self-healing protocols, and dynamic reconfiguration …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 24–30 Read article