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32 articles for “quantum networks”
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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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Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
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Exploring the Viability and Implications of Quantum Communication in 6G Networks
Abstract: The development of telecommunication systems has brought us to the era of 6G, characterized by remarkable connectivity, speed and performance achievements. This article investigates the fusion of quantum communication into the architecture of 6G networks as a new approach to achieving security and efficiency. Using quantum mechanics principles, such as superposition and entanglement, quantum communication allows bloodless encryption and secure data transmission. The theoretical frameworks and quantum networks for 6G …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 01–14 Read article
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Thin-Film Quantum Photonic Technologies for Quantum Teleportation
Abstract: One of the most important protocols in distributed quantum computing and quantum communication is quantum teleportation, which allows quantum information to be sent between distant nodes without actually sending the quantum particle. The teleportation process is fundamentally based on quantum entanglement, Bell state measurements, and classical communication channels, which collectively allow the accurate reconstruction of an unknown quantum state at a remote location. In recent years, rapid progress in integrated …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 13, Issue 2, 2026 · pp. 01–19 Read article
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Comprehensive Security Frameworks for 6G Wireless Networks: Analysis and Insights
Abstract: As the transition from 5G to 6G wireless communication networks accelerates, the landscape of network security is undergoing a profound transformation. This work presents a comprehensive study of emerging security challenges associated with 6G wireless networks. With 6G anticipated to support unprecedented data rates, ultra-low-latency, and seamless integration of diverse technologies such as the Internet of Things (IoT), artificial intelligence (AI), and augmented reality (AR), the security paradigm must evolve …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 35–41 Read article
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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The Impact of High-speed Networks on HFT Performance
Abstract: This study provides an in-depth examination of the critical role that high-speed networks play in the operations of high-frequency trading (HFT) firms. High-speed networks, characterized by their low latency and high bandwidth, facilitate the rapid, efficient transmission of massive quantities of data, a capability that is vital to the success of HFT strategies. We explore the core infrastructure that enables high-speed trading, from high-performance servers and switches to network interface …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 1–8 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 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 the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 19–35 Read article
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Perturbed Quantum Computation of the Non-linear Dynamical System in Terms of Bose-Mesner Algebra Using N-Coupled Maps
Abstract: AbstractThe author has considered the non-linear dynamical system comprising of brain, heart, kidney, physiological processes, thinking mechanism and immune system. The components of the dynamical system are interconnected with each other. In the present work he has discussed the perturbation in the non-linear dynamical system due to intense BIS processes. The BIS processes occurring in the surroundings constantly affect our neural network bringing about sudden changes in nervous system. The …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 1, 2015 · pp. 27–42 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Next-generation Operating Systems: AI-driven Autonomy, Quantum Integration, and Edge Computing
Abstract: The rapid evolution of computing paradigms is driving the need for next-generation operating systems that seamlessly integrate artificial intelligence, quantum computing, and edge processing. Traditional operating systems, while efficient for classical computation, lack the necessary capabilities to handle real-time AI-driven decision-making, quantum processing, and decentralized edge networks. This study explores how future operating systems will incorporate AI-driven autonomy to enhance resource management, quantum integration to leverage superior computational power, and …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 25–36 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 · pp. 15–24 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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A Comprehensive Study of Quantum Cryptography
Abstract: Quantum cryptography has emerged as one of the most promising fields in modern information security, offering innovative solutions that have the potential to transform the future of global cyber-defense. Unlike classical cryptographic systems, which depend primarily on the computational difficulty of solving complex mathematical problems, quantum cryptography is grounded in the fundamental and unbreakable laws of quantum mechanics. Core principles such as superposition, entanglement, and the uncertainty principle form the …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 12–26 Read article
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Quantum Key Distribution in Optical Fiber Communication: A Study
Abstract: The relentless march of technological advancements, particularly in the realm of quantum computing, stances a noteworthy threat to security of existing cryptographic systems. Traditional encryption methods, like RSA and AES, trust on mathematical problems considered computationally hard for computers. However, sufficiently powerful quantum computers could render these systems vulnerable to attacks, jeopardizing the confidentiality of sensitive data transmitted over optical fiber networks. This looming threat has spurred significant research and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 1, 2025 · pp. 30–40 Read article
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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Future-Ready Communication Systems: Exploring High-Speed, Adaptive, and Secure Network Solutions
Abstract: The domain of electronics communication systems has experienced rapid transformation due to the growing demand for high-speed, reliable, and intelligent communication networks. This paper presents a comprehensive analysis of emerging trends such as Fifth Generation (5G) communication systems, Internet of Things (IoT), Artificial Intelligence (AI)-enabled networks, Software-Defined Networking (SDN), optical communication advancements, and cybersecurity mechanisms. The combination of cloud computing, edge computing, and network virtualization which improve system flexibility, allow …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article