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311 articles for “Network optimization”
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In-Situ Polymerized GO/PANI Composites: Structural Evolution, Optical Modulation, and NH₃ Sensing at Room Temperature
Abstract: Graphene oxide (GO)/polyaniline (PANI) composites with varying PANI contents (20, 40, and 60 wt%) were synthesized via in-situ oxidative polymerization and systematically investigated for their structural, morphological, optical, and gas-sensing properties. X-ray diffraction (XRD) confirmed a progressive increase in interlayer spacing and partial exfoliation of GO layers with increasing PANI content, indicating intercalation-assisted hybridization. Fourier transform infrared (FTIR) spectroscopy revealed the characteristic vibrational bands of both constituents and confirmed strong …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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The Role of IoT in Sustainable Agriculture: Leveraging Big Data for Precision Farming
Abstract: Precision farming combined with the Internet of Things (IoT) is transforming the agricultural industry by boosting productivity and encouraging sustainable practices.. This paper explores the transformative impact of IoT technologies on modern agriculture, focusing on how big data analytics can be leveraged to optimize farming practices, reduce waste, and conserve resources. The Internet of Things (IoT) offers real-time data on a range of agricultural characteristics, including soil moisture, temperature, humidity, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 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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Self Healing Material: An Introduction
Abstract: Self-healing materials have emerged as a transformative innovation for sustainable infrastructure and advanced applications such as wearable electronics and smart transportation systems. These materials possess the intrinsic ability to repair damage autonomously or with minimal external intervention, thereby extending service life and reducing maintenance costs. Inspired by biological systems, self-healing mechanisms are broadly classified into extrinsic approaches, such as microcapsule and vascular networks based healing, and intrinsic mechanisms involving reversible …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 604–611 Read article
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Fertilizer Prediction Using Machine Learning
Abstract: Fertilizer prediction is a critical aspect of modern agriculture, aimed at optimizing resource utilization while maximizing crop yields. In recent years, machine learning (ML) techniques have emerged as powerful tools for addressing this challenge by leveraging data-driven approaches to predict the optimal type and quantity of fertilizer required for different crops and soil conditions. This research paper provides a comprehensive review of the existing literature and methodologies employed in fertilizer …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 26–35 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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An Examination of Energy-Saving Techniques for UAV Communication
Abstract: Unmanned aerial vehicles (UAVs), or drones, have become essential in various industries due to their low deployment costs and exceptional versatility. As a result, they are widely used in industries like mining, agriculture, logistics, and search and rescue. The effectiveness of UAV applications is largely dependent on robust communication technology, which is crucial for control, data transmission, and coordination. However, the limited capacity of the low-power batteries used in UAVs …
Published in International Journal on Drones · Vol. 1, Issue 1, 2025 · pp. 1–7 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Optimization of Supply Chain Management Cost Reduction and Delivery Time Improvement
Abstract: Management of the supply chain is vital for every company's success. Businesses can cut expenses and speed up delivery by effectively regulating the flow of goods and services. In this study, we will explore the various strategies and best practices in supply chain management that can help achieve these objectives. We will delve into the importance of efficient sourcing, inventory management, and logistics to streamline operations and optimize the supply …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 15–21 Read article
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Microstructural Characterisation and Analysis of Mechanical Behaviour of Hybrid AA 7075/7178 Fabricated Using Die Casting Technique
Abstract: AA are being increasingly used in the field of structural engineering owing to their desirable mechanical properties coupled with their recyclable and sustainable nature, thus contributing significantly towards reduction of carbon footprints and development of circular economy. Till date numerous research projects have been prompted to investigate the structural performance of aluminium alloy structures and develop alternatives with enhanced performance parameters. AA 7xxx (Al-Zn-Mg-Cu) are being widely used in variety …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 441–451 Read article
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Integration of Semi-Interpenetrating Polymer Networks and Quantum Dot–Polymer Nanocomposites for Low-Cost, Flexible OLED Display
Abstract: Flexible OLED displays need advanced material systems to integrate capabilities for mechanical flexibility as well as thermal stability and environmental durability at low costs. Semi-interpenetrating polymer networks (SIPNs) combined with quantum dot (QD)-polymer nanocomposites serve to improve OLED performance capabilities. They combine a stable structural design along with a flexible matrix through the matrix capabilities of SIPNs which result in efficient luminescence and pure color output courtesy of CdSe/ZnS QDs …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 919–932 Read article
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Machine Learning-Driven Force Analysis for Tool Wear Prediction Systems
Abstract: A system designed to forecast tool wear by utilizing a force sensor to monitor the wear of the tool's flank and applying a Convolutional Neural Network (CNN) for forecasting purposes. The methodology is demonstrated through experiments in milling, utilizing dry machining with a ball endmill on a stainless-steel component. The flank wear of the tool is directly assessed using a digital microscope throughout the operation. The forecasts produced by the …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 16–25 Read article
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Kinetics of Crystallization and Microstructural Evolution of Commercial Fluorophlogopite Machinable Glass- Ceramics in the System SrO∙4MgO∙Al2O3∙ 6SiO2∙2MgF2 with Varying in B2O3
Abstract: Glass materials based on fluorophlogopite stoichiometry with varying concentrations of B₂O₃ were synthesized using the melt-casting method, followed by heat treatment at different crystallization temperatures. The resulting glass and glass–ceramic samples were characterized using differential thermal analysis (DTA), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared (FT-IR) spectroscopy. Kinetic analysis revealed that the activation energies required for the formation of glass–ceramics were 192.77 kJ mol⁻¹ and 210.47 kJ …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 1–16 Read article
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Polymeric Emulsion Composite System Enriched with Eggshell-Derived Biominerals for Dermal Delivery
Abstract: This study describes the development and characterization of a sustainable polymeric water-in-oil (W/O) emulsion composite designed for dermal delivery and skin repair applications. The formulation was prepared using a lipid-rich biopolymeric matrix containing glyceryl stearate, beeswax, and plant-derived ingredients, which acted as the continuous phase for stabilizing and dispersing inorganic mineral fillers. Eggshell waste was utilized as a natural calcium source and combined with magnesium and zinc oxide to create …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Structure-Property-Process Relationships in BNNS-Modified PEEK Nanocomposites for High-Performance Applications
Abstract: This study reports the design and performance evaluation of boron nitride nanosheet (BNNS)-reinforced polyetheretherketone (PEEK) nanocomposites fabricated using melt compounding and high-temperature Fused Filament Fabrication (FFF). PEEK, a high-performance thermoplastic, was reinforced with BNNS at 0.5–5wt.% to enhance mechanical, thermal, and tribological functionalities for advanced engineering use. Composite filaments were extruded and printed using a modified Bambu Lab FFF printer. Mechanical testing revealed a peak tensile strength of 108 MPa …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 867–888 Read article
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Autonomous Agentic AI for Adaptive Cure Optimization and Defect Prevention in Thermoset Polymer Composite Manufacturing
Abstract: Thermoset polymer composites occupy a central position in modern structural manufacturing, from aircraft fuselages to wind-turbine blades. Despite progress in resin chemistry and fiber architecture, the “cure process” that transforms compliant preforms into load-bearing structures remains difficult to manage. Manufacturers encounter ‘voids’, “interlaminar delaminations”, and “spring-back distortion” when curing complex or thick-section parts. The cause is not ignorance of the relevant physics, but rather that ‘temperature’, ‘chemistry’, ‘rheology’, and ‘mechanics’ …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 301–320 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article