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742 articles for “Network Model”
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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Immunological Mechanisms Underlying Autoimmune Disorders: Recent Advances and Therapeutic Implications
Abstract: A diverse range of illnesses known as autoimmune disorders are typified by dysregulated immune responses against self-antigens, which result in tissue damage and persistent inflammation. Understanding the genetic, epigenetic, and environmental variables that contribute to autoimmune pathogenesis has advanced significantly during the last ten years. Current disease models have been transformed by new understandings of immunological tolerance mechanisms such as the functions of regulatory T cells, cytokine networks, and the …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 1, 2026 · pp. 21–25 Read article
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Ethical AI and Data Protection in the Era of Industry 5.0
Abstract: This paper provides a comprehensive analysis of the critical intersection between Responsible AI (RAI), data privacy, and the Industry 5.0 paradigm. Industry 5.0, defined by its human-centric, sustainable, and resilient pillars, introduces a fundamental paradox: its core requirement for human-AI collaboration necessitates the collection and processing of granular human data, creating direct conflicts with emerging global data privacy and AI regulations. This research utilizes a systematic integrative review methodology, analyzing …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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State Space Modeling and Robust Wind Power Generation System
Abstract: AbstractAs producing power from renewable energy is increasing, facing new problems emerging from this phenomenon is becoming a good challenge for power system engineers. One of these problems is the dynamic and transient stability of such systems when they are connected to a power network. In this paper, a variable speed cage machine wind generation system is considered as the case study. The concept of power system stabilizer, which has …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 8, Issue 2, 2017 · pp. 24–39 Read article
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Hybrid Numerical–Artificial Neural Network Study of Chemically Reactive MHD Nanofluid Flow Incorporating Thompson–Troian Slip and Stefan Blowing
Abstract: Boundary layer behaviour in chemically reactive nanoliquid is significantly affected by surface conditions, magnetic fields, heat and mas transfer mechanisms. However, the combined impact of Stefan blowing and nonlinear Thompson–Troian slip under inclined magnetic fields remains mostly unexplored, particularly in mixed convection flows. In this research work, the flow of a chemically reactive nanoliquid over a permeable surface is investigated by considering the Troian slip, inclined magnetic fields, Stefan blowing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 409–425 Read article
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Study of Global Solar Radiation Estimation based on Artificial Neural Networks Techniques
Abstract: AbstractSolar Radiation data received by earth in the form of x-rays, UV-rays, infrared rays is a prominent and useful data as it gives the information about the amount of energy received from sun at the earth. Artificial Neural Network (ANN) is brain inspired technology which learns and performs in a way similar to the way our human brain performs. Sun’s energy is of utmost importance and is freely available in …
Published in Recent Trends in Electronics Communication Systems · Vol. 7, Issue 1, 2020 · pp. 26–31 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Fabrication and drilling characterization of Hemp & Grewia-Optiva hybrid composite and comparison with ANN model
Abstract: In recent days the use of natural fibers has increased over synthetic fibers due to various advantages. The alkali treatment for these natural fibers further improves the adhesion between fiber and matrix and greatly enhances the mechanical properties of the composite. The present study involves the fabrication of a hybrid composite using the alkali-treated (5% NaOH concentration) natural fibers – Hemp &Grewia-optiva as reinforcement material and epoxy as a matrix …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 138–146 Read article
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BER Improvement in Fading Conditions Using QAM
Abstract: AbstractThe future mobile network requires huge capacity, coverage, energy efficiency and spectral efficiency. In different fading conditions, like Gaussian noise channel, Rician fading and Rayleigh fading conditions, higher order QAM can improve spectral efficiency by improving bit error rate. Additive white Gaussian noise model describes the effect of random processes in nature. Rayleigh distribution has static time varying nature on the receiver side. The envelope of Rician fading is small …
Published in Trends in Opto-electro & Optical Communication · Vol. 7, Issue 2, 2017 · pp. 1–6 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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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Zero Trust Security Governance by Utilizing Identity and Access Management
Abstract: The Zero Trust Paradigm, a more stringent approach to network security, operates on the fundamental concept of “Never Assume, Always Authenticate.” It is currently being implemented in different countries to align with their national cybersecurity and access management governance policies. The differentiation of these Zero Trust systems is contingent upon factors such as awareness, infrastructure, expenses, and security demand. Additionally, the identity-based access management models within the Zero Trust system …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 2, 2023 · pp. 6–17 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Blockchain-Enabled Secure Wireless Communication IoT Networks
Abstract: Cloud-native environments with their distributed environments and transient workloads raise the intrinsic problem of traditional intrusion detection and response systems to unprecedented levels. Modern cloud platforms have rapid elasticity, microservice orientation, and dynamic scaling, which usually exceed the range of centralized security services, contributing to the problem of slower threat detection and a poor ability to contain the threat. The proliferation of the Internet of Things (IoT) gadgets across different …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 10–14 Read article
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Mechatronics Robot Navigation using Machine Learning through Prolog Programming Language
Abstract: A basic decision-making system is developed in this paper using Neural Network in Machine learningto explore a robot in concealed condition. The robot can move out of explicit labyrinths effectivelythrough modifying its bearing and speed persistently via the neural system model for machinelearning. Over the past several years, navigation tasks for mobile robots have been widely studied.There have been many attempts to introduce the usage of machine learning algorithms. Excellentperformance …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 1, 2021 · pp. 39–47 Read article
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Performance Analysis of Flying Ad Hoc Network with Different Antennas Using Ricean Fading
Abstract: AbstractWith regards to FANET, utilization of directional antenna can to a great extent decrease the radio interference, in this way enhancing the use of wireless medium and thus the system throughput. Execution of FANET is low under the omnidirectional antenna system contrasted with smart antenna system when Ricean fading model is utilized. Directional antenna covers huge zone and transmits extensive no. of packets, since it centers in the desired direction …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 5, Issue 2, 2018 · pp. 1–7 Read article
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A Study of DCGAN-Based Generative Models for Anime Character Face Generation
Abstract: Artificial intelligence, or AI, has in recent years moved from simple rule-based systems to models that are now fully capable of creative content generation and are referred to as generative AI. One such approach for content generation, introduced in the year 2014, is called generative adversarial networks (GANs), which consists of training a generator to create fake content that tries to mimic real content as closely as possible and a …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 31–41 Read article
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Adversarial Attacks on Machine Learning Models in Cybersecurity: A Systematic Literature Review
Abstract: Adversarial machine learning (AML) is a field that is growing swiftly, especially as machine learning models are employed more and more in places where security is critical. This review goes into great depth over 746 publications from the Scopus database, with an emphasis on the connection between AML and network security. Using Biblioshiny and Scopus tools, we looked at trends in publications, study fields, productive authors, collaboration networks, and theme …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 23–38 Read article