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348 articles for “Experimental Optimization”
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Development and Performance Evaluation of Hybrid Solar Water Heating and Distillation Systems for Sustainable Water Supply: A Comprehensive Review
Abstract: This review article delves into the comprehensive examination of hybrid solar water heating and distillation systems, underscoring their pivotal role in addressing global water and energy challenges. With the increasing scarcity of clean water and the growing demand for sustainable energy solutions, these hybrid systems offer a promising dual-purpose approach. The article synthesizes the latest advancements in technology, design methodologies, and performance evaluation metrics, providing a holistic view of the …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 8–19 Read article
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Comparative Analysis of Kinetic Models for Simulation of Biogas Production from Cow Dung and Fruit Waste via Anaerobic Digestion
Abstract: This study investigates the optimization of biogas and biofertilizer production from cow dung and fruit waste through anaerobic digestion, utilizing various microbial growth kinetic models. Simulations were conducted using the Monod, Moser, Contois, and Tessier models to predict biogas yield and assess model accuracy. Results indicated that the Tessier model provided the closest fit to experimental data, with a biogas yield of 0.45 m³/kg VS, while the Monod model overestimated …
Published in International Journal of Membranes · Vol. 2, Issue 1, 2025 · pp. 47–63 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Investigation and Optimization of Resistance Spot Welding Parameters for Stainless Steel
Abstract: The present work examines the significant impact of resistance spot welding (RSW) process parameters on the properties and efficacy of connections created in sheets of 316L stainless steel. This study examines the intricate relationship between welding parameters, investigating their influence on the microstructure, mechanical characteristics, and overall efficacy of welded connections. By employing a methodical experimental methodology, this study thoroughly investigates the impact of different factors in resistance spot welding …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 15–21 Read article
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Assessing Concrete Strength Through Substituting Coarse Aggregate with Steel Slag and Cement with Bentonite Powder
Abstract: This study investigates the strength characteristics of concrete by partially replacing cement with bentonite powder and coarse aggregate with steel slag. The research aims to evaluate the mechanical performance of concrete through compressive strength, split tensile strength, and flexural strength tests. Bentonite powder is substituted at varying levels of 0, 10, 20, and 30%, while steel slag is incorporated consistently at 60% as a replacement for coarse aggregate. The objective …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 2, 2025 · pp. 1–8 Read article
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An Adaptive and Privacy-Aware Federated Learning Framework for Efficient and Secure Model Training Across Heterogeneous Datasets
Abstract: The problem of efficiency and privacy regarding heterogeneous data in modern distributed machine learning systems is a vital point that should be taken into account. The absence of IID data distribution, client heterogeneity, and privacy invasion during the aggregation model are the bane of conventional federated learning (FL) approaches to learning like FedAvg and FedProx. The paper proposes that the adaptive and privacy-aware FL framework (AFL-P) can be used to …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 16–25 Read article
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Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Enhancing Chatter Resistance in Deep Hole Boring Through Modified Tool Design: A Study on Impact of Length-To-Diameter (L/D) Ratio
Abstract: Deep hole boring is a specialized machining process crucial for creating precise bores with high length-to-diameter (L/D) ratios, particularly vital in aerospace, automotive, and oil and gas industries. The L/D ratio is pivotal for stability and performance. Chatter, a detrimental vibration phenomenon, is a significant concern in deep hole boring, influenced by the L/D ratio. Higher L/D ratios increase chatter, leading to poor surface finish and reduced tool life. Longer …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 2, 2024 · pp. 24–33 Read article
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Examining the Role of Synthetic Biology in Cellular Restoration Mechanisms
Abstract: Synthetic biology has emerged as a transformative field with the potential to revolutionize cellular repair mechanisms, offering innovative solutions to repair damaged DNA, stabilize proteins, regenerate tissues, and treat a wide range of diseases. By combining principles from genetic engineering, biotechnology, and computational biology, synthetic biology enables the design of cellular systems capable of performing functions that repair cellular damage and restore normal cellular processes. This article explores the application …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 19–29 Read article
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Polymer-Based Acousto-Optic Ultrasonic Sensor for Non-Destructive Evaluation of Dielectric Insulation
Abstract: A dual-polymer fiber-optic sensor for monitoring partial discharge (PD) activity in high-voltage polymeric insulation is presented in this work for non-destructive evaluation and dielectric testing applications. Dielectric weakness within polymeric insulation leads to partial discharge activity, generating ultrasonic acoustic waves that propagate through the medium. The developed sensing assembly comprises a conical polymer-based horn that gathers and concentrates the ultrasonic acoustic emission energy generated by dielectric weakness, and a single-mode …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 11–24 Read article
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Particle Swarm Optimization Framework for Accurate Battery State-of-Charge and Remaining Useful Life Estimation
Abstract: Accurate estimation of the State of Charge (SOC) and State of Health (SOH) of a battery is key to safe and efficient management of batteries in electric vehicles and energy-storage systems. However, it is challenging due to high nonlinearity, varying operating conditions, measurement noise, and limited access to comprehensive electrochemical parameters. Traditional data-driven models often generalize poorly and require heavy tuning, which can produce unstable predictions. To address these problems, …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 53–64 Read article
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Impact of Lubricant Additives on Friction Reduction and Wear Prevention in Machinery
Abstract: Lubrication is essential for ensuring the lifespan and operating efficiency of machinery because it minimizes wear and reduces friction. Modern lubricants are made up of several chemical compounds called lubricant additives, which are essential to boost the lubricant's ability to reduce wear and friction. This study thoroughly examines how lubricant additives affect wear prevention and friction reduction in equipment. This work attempts to break down the principles behind the efficacy …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 2, 2023 · pp. 1–6 Read article
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Optimizing Manufacturing Processes with Taguchi Method in Production Engineering
Abstract: The Taguchi Method, pioneered by Genichi Taguchi, stands as a powerful optimization tool within the realm of production engineering. This paper delves into the principles, applications, and significance of the Taguchi Method in enhancing manufacturing processes. With a focus on minimizing variation and improving performance, this methodology plays a crucial role in addressing challenges faced by industries in their pursuit of operational excellence. The core components of the Taguchi Method, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Optimizing Parameters for Dry Sliding Wear Control in Stir-Cast AA7050/SiC Composites
Abstract: Using a pin-on-disc tribometer, this study examined the dry sliding wear behavior of AA7050/SiC composites. The production of this metal matrix composite was achieved through the stir-casting process, which involved an initial step of melting the AA7050 alloy, followed by the careful introduction of silicon carbide (SiC) particles, stirring to achieve uniform dispersion, and finally, casting the molten mixture. Wear rate (WR) was determined by three operational parameters: SiC reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1624–1635 Read article
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Maximizing Flow and Ensuring Leak Tightness Through Design and Development of a Unidirectional Check Valve
Abstract: The check valve market, valued at USD 6.5 billion in 2024, is expected to grow at a 4.1% CAGR. Challenges in valve seat materials, particularly SS304 and PTFE (Teflon), contribute to a 0.5% leak rate, which leads to helium gas loss, reduced efficiency, and higher operational costs. While various sealing techniques, including hard-on-soft methods, have been explored, few have been applied to poppet check valves. This study focuses on improving …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 10–18 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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A Secure Storage Model with Authentication and Optimal Key Generation Based Encryption
Abstract: In digital forensics, ensuring the secure storage of digital evidence is crucial. This paper introduces a new method that uses advanced encryption and key generation techniques to protect digital evidence throughout an investigation. Cloud forensics, a modern approach to digital forensics, aims to safeguard evidence from online hacking. However, storing all evidence in one central location can reduce its reliability. To address this, we propose a digital forensics architecture for …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 7–13 Read article
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Optimal Abrasive Jet Machining Parameters for Glass Fiber Reinforced Plastics
Abstract: Abrasive jet machining (AJM) is a best choice for processing of glass fiber reinforced plastics (GFRP). Inherent to the nonlinear behavior of performance characteristics during repeated experiments are inevitable variations, attributed to measurement errors and unknown influencing input variables. This study employs the Taguchi method with an orthogonal array to systematically identify optimal input variables through a limited number of experiments. The paper introduces a direct and reliable Taguchi-based multi-objective …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 247–255 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article