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133 articles for “model predictive control”
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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Machining-Induced Surface Integrity Optimization of High-Carbon Alloy Steel for Enhanced Polymer–Metal Composite Interface Performance
Abstract: The functional performance and structural reliability of polymer–metal hybrid composites are strongly influenced by the surface integrity of metallic substrates used for interfacial bonding and load transfer. In this context, machining-induced surface characteristics play a critical role in determining adhesion behavior, dimensional stability, and mechanical compatibility within composite architectures. The present study investigates the hard turning performance of a newly developed high-carbon alloy steel intended for composite-integrated structural applications, with …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1531–1546 Read article
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A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection
Abstract: Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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Analyzing the Role of Fiber Composition in Drying Behavior: A Comparative and Predictive Approach
Abstract: This research presents a comprehensive analysis of the drying behavior and thermal response of three distinct fabric types: 100% Cotton, 100% Polyester, and a Polyester blend (65/35), under meticulously controlled environmental conditions. The Polyester blend (65/35) consists of 65% Polyester and 35% Cotton, combining characteristics of both fibers. The investigation focuses on understanding how fiber composition impacts drying time, moisture retention, and thermal characteristics. Experimental trials were conducted using standardized …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 1–11 Read article
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IoT and Autonomous RC Boats for Water Quality Assessment: Trends, Challenges, and Future Prospects
Abstract: Nowadays the application of Internet of things (IoT) increasing in many applications like drone, remote control vehicles, electrical vehicle, etc. In this paper we proposed a way to check quality of water present in vast water bodies by Remote Controlled (RC) Boat. This RC environmental monitor boat collects water quality data and sends it online via the Internet of Things. So that we maintain the water by clean from received …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 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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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Research Paper A Review of Symmetry in Mechanical Systems: Theoretical Systems Foundations and Engineering Applications
Abstract: In mechanical system analysis and design, symmetry is of mechanical systems. This article examines the idea of symmetry in mechanical systems, exploring its mathematical foundations (such as Lie algebras and group theory) and how these ideas help explain the behavior, stability, and control of the system. We explore the applications of symmetry in a range of mechanical systems, from basic mechanical connections to intricate multi-body dynamics, emphasizing the benefits of …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 15–19 Read article
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Fractional Calculus-Based Analysis of Magneto-Thermal Nanofluid Flow Over Stretching and Shrinking Surfaces
Abstract: This study presents a comprehensive investigation of magneto-thermal hybrid nanofluid flow over stretching and shrinking surfaces using a fractional calculus framework to capture the memory and hereditary characteristics of complex fluid transport phenomena. The proposed model incorporates the effects of magnetic field intensity, thermal radiation, viscous dissipation, Brownian motion, and thermophoretic diffusion on the velocity and temperature distributions within the boundary layer region. A fractional-order derivative formulation is employed to …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Thermal Effects in High-Power Laser Systems: Modeling and Mitigation
Abstract: High-power laser systems are increasingly employed in industrial manufacturing, defense, medical procedures, and scientific research due to their ability to deliver high energy density with excellent spatial coherence. However, the performance and reliability of these systems are significantly influenced by thermal effects arising from optical absorption, non-radiative recombination, and inefficient heat dissipation within laser gain media and optical components. These thermal phenomena lead to adverse effects such as thermal lensing, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 9–13 Read article
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Viscoelastic Behavior, Interfacial Mechanics, and Reliability of Polymer Interlayers in Laminated Glass Composites: A Comprehensive Review
Abstract: The laminated glass systems are regarded as hybrid polymer–glass composites where the viscoelastic behavior of polymer interlayers mostly controls mechanical response. These interlayers (polyvinyl butyral (PVB), ionoplast, ethylene-vinyl acetate (EVA), etc.) have time-, temperature- and rate-dependent properties which significantly affect shear transfer, energy dissipation, and fracture resistance. But the baseline polymer-relevant processes at the molecular and interfacial level are to a large extent unknown [1]. This review provides a materials-focused …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 258–268 Read article
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Comparative Performance Study: Deterministic vs. Probabilistic Models in Retail Chains
Abstract: The finished goods, raw materials, and product stock that a business has on hand for sale are referred to as inventory. They enable the companies to achieve their sales levels and are a chance to cost control and decision making. It is a huge asset to a manufacturing firm. Inventory model permits forecasting of quantities of raw material, inventory and spare parts of the equipment to a very high level …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 1–6 Read article
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Versatile CNC Machine for Tabletop Use Enhanced with Machine Learning Integration
Abstract: In the realm of tabletop multipurpose CNC machines, the integration of machine learning represents a groundbreaking advancement potentially revolutionary in the field of desktop manufacturing. This research explores the seamless incorporation of machine learning algorithms into tabletop CNC machines to enhance their capabilities, performance, and user experience. Through case studies and examples, we demonstrate the profound impact of machine learning integration in key areas of CNC machining, such as accurate …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 353–361 Read article
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Advancements in Molecular Engineering: Innovations at the Nexus of Chemistry and Technology
Abstract: Molecular engineering, a frontier of chemistry, merges precision and innovation to design and assemble molecular structures with unprecedented control. This abstract explores recent advances, highlighting key breakthroughs and their transformative impacts. Starting with its roots in chemical synthesis and materials science, it traces the evolution towards rational design driven by computational tools and advanced characterization techniques, enabling tailored molecular architectures. A focal point is programmable molecules, where DNA nanotechnology principles …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 37–43 Read article
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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Recent Advances and Future Prospects in Digital Twin Technology for Battery Management Systems of Electric Vehicles
Abstract: Digital twin technology in battery management systems (BMS) for electric cars (EVs) represents a major development in the automotive industry. Digital twins provide predictive maintenance, modelling, and real-time monitoring by creating virtual copies of real-time monitoring, actual battery systems. This paper describes the functional components, architecture, and design of Digital Twin technology along with how it may be included into BMS. Emphasizing how consistent data flow from sensors improves battery …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 Read article