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198 articles for “device modeling”
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Smart Polymer Composites with Multifunctional Capabilities Integrating Electroactive Polymers Conductive Nanofillers and Flexible Electronics for Advanced Sensing and Actuation Systems
Abstract: Smart polymer composites have gained significant attention to their ability to integrate polymer matrices with conductive nanofillers, offering tunable electrical, mechanical, and electroactive properties. These composites are highly responsive to external stimuli such as electrical fields, mechanical stress, and temperature variations, making them ideal for applications in flexible electronics, soft robotics, and adaptive sensing systems. This research investigates the effect of nanofiller dispersion on the performance of polymer composites, optimizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 946–965 Read article
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Revolutionizing Artificial Organs: Next-Generation Membrane Technologies for Precision Medicine and Global Health
Abstract: Membrane technology has emerged as a cornerstone in the advancement of artificial organ systems, offering critical functionalities in selective molecular filtration, tissue scaffolding, and controlled therapeutic delivery. Recent innovations have propelled the field beyond traditional polymeric membranes to include nanostructured, biomimetic, and stimuli-responsive materials, significantly enhancing biocompatibility, selectivity, and durability. The integration of smart technologies, such as AI-driven membrane design, bioelectronic sensors, and personalized fabrication via 3D printing, is ushering …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 29–39 Read article
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Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
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An Interoperability on the Internet of Things (IoT): A Review
Abstract: With technological advancement growing at a rapid rate, we are presented with numerous ways of connecting ourselves to the rest of the world. The Internet of Things, or IoT, is now a reality, even at the minuscule level. With ubiquitous computing, we can stay in constant communication with the outside world. As such there are several types of devices capable of monitoring, measuring, and sending data back and forth from …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 40–53 Read article
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Animal Detection in Farms Using Opencv
Abstract: Agriculture plays a fundamental role in sustaining the Indian economy, providing employment and livelihood to a large portion of the population. Despite advancements in farming techniques, one of the persistent challenges faced by farmers is the intrusion of wild animals into agricultural fields. Such intrusions often lead to large-scale crop damage, financial loss, and emotional distress for farmers. Traditional animal deterrent methods, such as manual patrolling, fences, or scarecrows, have …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Driver Anti-Sleep Alarming and Protection
Abstract: Road accidents due to driver drowsiness is one of the biggest problems worldwide, which kills thousands of people every year. Fatigue slows the reaction time, reduces the concentration, and, most importantly, impairs the judgment, thus making drowsy driving as dangerous as drunk driving. To reduce such accidents, various technologies have been employed to develop driver anti-sleep devices. These include sensor-based detection, camera-based eye monitoring, EEG analysis, and real-time alert systems. …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 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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R-M and M-R Model for Interpreting Logic State of Memristor Aided NOR with Enhanced Noise Margin
Abstract: Memristive crossbar arrays are one of the fascinating subjects in the field of nanoelectronics and memory devices. The arrangement of arrays consists of grid-like structure with rows and columns of memristors which are resistive devices that can preserve their resistance state even after power is turned OFF. They have now emerged as a promising alternative to traditional memory technologies due to their high density, non-volatility and low power consumption. This …
Published in Recent Trends in Mathematics · Vol. 1, Issue 1, 2024 · pp. 35–41 Read article
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KVS Approach for IoT Network Security: A Novel Approach to IoT Network Security With B-Cell Inspired Models
Abstract: Internet of Things (IoT) is rapidly expanding, connecting billions of devices that collect, process, and transmit data. This interconnectedness, while offering immense opportunities, also presents significant security challenges. Customary security mechanisms often scuffle to retain stride with the vibrant and assorted form of IoT environments. In response, innovative security concepts are being explored, and one promising approach is the B-Cell concept called as KVS approach for IoT security. In immunology, …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 16–25 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Understanding Side-wind Dynamics and Deciphering Ringsail Parachute Drift
Abstract: The geometric complication caused by the "rings" and "sails" used to make the parachutist's canopy provides a considerable computationally problem, which is the focus of this paper's fluid–structure interaction (FSI) modeling of ringsail parachutes. Based on the sustained space-time FSI (SSTFSI) method, we have developed an FSI simulation of ringsail jumping devices. The FSI Geometric Smoothing Technique and the Homogenized Modeling of Geometric Porosity represent a pair of the above …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 1, 2024 · pp. 1–12 Read article
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Phygital: An Innovative Model for Developing Receptive Skills in English Through Learner Autonomy
Abstract: The study named “Phygital: An Innovative Model for Developing Receptive Skills in English through Learner Autonomy” tries to establish that it is an innovative scientific model, evidently distinguished from other prototypes such as blended learning, e-learning, flip learning, online learning, hybrid learning etc. The paper also tries to emphasize that it is best suited for the new age learners and that it enhances the receptive skills (listening and reading) in …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 1–9 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Advancements in Material Design and Motion Control: Integrating Additive Manufacturing, Fused Deposition Modeling, and Precision Systems in Modern Applications
Abstract: The interaction between material design, mechanical properties, and advanced motion control systems is vital in a range of engineering domains, including robotics, electronics, and manufacturing. This article examines two key areas: the mechanical properties and design of cutting-edge materials, focusing on composites, polymers, ceramics, and fibers, and the integration of advanced motion control systems in hand-held electronic and photographic devices. The first section delves into the mechanical behavior of various …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 26–30 Read article
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Overview of Ionic Polarization: A Model Based Novel Approach
Abstract: This study presents a comprehensive analysis of ionic polarization through a novel model-based approach that integrates theoretical, computational, and experimental methodologies. Ionic polarization, which significantly influences the dielectric properties of materials, is examined through the lens of the Clausius-Mossotti equation and the Debye relaxation model, providing a theoretical framework for understanding the relationship between ionic displacement and dielectric behavior. To explore ionic displacement and polarization at the atomic level, advanced …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 18–25 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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IoT Network Security Employing KVS Approach: Novel Approach to IoT Security with B-Cell Inspired Models Implemented using Artificial Intelligence
Abstract: The Internet of Things (IoT), which links billions of devices that gather, analyse, and send data, is growing quickly. Although there are many benefits to this interconnection, there are also serious security risks. Conventional security measures frequently struggle to keep up with the dynamic and diverse nature of IoT environments. Innovative security ideas are being investigated in response, and the B-Cell concept, also known as the Kutubuddin Vahida Sultana (KVS) …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 36–46 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article