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562 articles for “combined model”
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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The Role of 3D Modeling in Additive Manufacturing: Advances and Applications
Abstract: By making it possible to create intricate, highly functional, and customized components for a range of industries, the combination of 3D modeling and additive manufacturing (AM) has completely changed contemporary production processes. With an emphasis on both the technological advancements in digital design and its real-world applications, this paper examines the critical role that 3D modeling plays in the success of additive manufacturing. 3D modeling, the cornerstone of additive manufacturing, …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 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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Implement Artificial Intelligence and Machine Learning for Engineering Design, Predictive Modeling, and Optimizing Polymer Nanocomposites
Abstract: Polymer nanocomposites are high performance engineered materials obtained by inclusion of nano-sized fillers into the polymer matrix to enhance mechanical, thermal, electrical, barrier and functional properties. However, the complex and non-linear interactions among polymer chemistry, nanofiller characteristics, filler concentration, dispersion, interfacial bonding and processing conditions make it challenging to anticipate and maximize their properties. Artificial intelligence (AI) and machine learning (ML) offer powerful data-driven solutions to these difficulties by establishing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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A Comparative Seismic Assessment of Structures Utilizing Various Angles: Shear Walls vs. Diagrid Structural Systems
Abstract: The diagrid structural system has emerged as a cutting-edge approach to designing tall buildings in recent times. It represents a significant innovation in the construction industry, combining both structural strength and striking architectural aesthetics. The versatility of the diagrid system has led to its widespread adoption in the construction of tall buildings. In-depth research into the design methodology of diagrid structures has unveiled their exceptional structural capabilities and distinctive architectural …
Published in Journal of Structural Engineering and Management · Vol. 10, Issue 2, 2023 · pp. 23–30 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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Smart Air Filtration Systems for Cities: A Technological Approach to Reducing Urban Pollution
Abstract: Urban air pollution is considered one of the main ecologically critical issues of the 21st century since it threatens citizens' health through respiratory diseases, pathologies of the cardiovascular system, and even premature death. Regarding an extremely high level of pollution in large cities, it becomes necessary to realize technological solutions which could avoid the negative impact of this phenomenon. Smart air filtration systems have emerged as promising solutions for urban …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 2, 2024 · pp. 27–42 Read article
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Advanced Perspectives on Fluid Dynamics in Environmental Systems: Interactions, Impacts, and Innovations
Abstract: Environmental fluid mechanics is a multidisciplinary field that investigates the movement and behavior of natural fluids—such as air and water—in the environment, with a particular focus on understanding and mitigating the effects of human activities and natural processes. This study presents an analysis of fluid flow phenomena relevant to environmental systems, examining the transport of momentum, heat, and contaminants in both natural and engineered environments. Emphasis is placed on the …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 1–16 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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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Application of AI Techniques in Three-phase Shunt Active Power Filter in Unbalanced and Distorted Supply Conditions
Abstract: This paper deals with a new improved model of the shunt active power filter having the control scheme using Artificial Neural Networks (ANN) technique in unbalanced and distorted supply system. In this paper, three soft computing techniques viz; Genetic algorithm, Fuzz logic, neural network are used. The simulation results using MATLAB model confirm that combination of these algorithms together create an optimum system, which clearly proves the effectiveness of the …
Published in Journal of Power Electronics and Power Systems · Vol. 3, Issue 3, 2013 · pp. 15–26 Read article
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Novel MOSFET Based Pressure Sensor That Uses Combined Channel Piezoresistance and Gate Capacitance Effects
Abstract: The paper considers modeling and analysis of a square and circular diaphragm Suspended Gate MOSFET based pressure sensor using COMSOL Multiphysics. Two structures, one a square with an n-channel MOSFET at the center and the second a circle with a p-channel MOSFET at the edge of the diaphragm were simulated. The piezoresistance effect of the channel and capacitance variation due to the suspended gate have been exploited in designing the …
Published in Recent Trends in Sensor Research & Technology · Vol. 2, Issue 2, 2015 · pp. 30–39 Read article
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Fabrication, Numerical Simulation and Compact Modeling of Ph-BTBT-C10 Organic Thin Film Transistor
Abstract: Flexible and cost-effective electronics have been necessitated by the advent of organic thin-film transistors (OTFTs). This study aims to study the performance of OTFT using a 2-decyl-7-phenyl-[1]benzothieno[3,2-b][1]benzothiophene (Ph-BTBT-C10) organic semiconductor. The paper also explore accurate device modeling for technology optimization and circuit design that supports device improvement. This research includes device fabrication, numerical simulation using TCAD, compact modeling, and parameter extraction. By combining temperature-dependent bandgap narrowing with existing theories, this …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 1–18 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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Microstructural Design and Functional Properties of Polycrystalline Materials
Abstract: Polycrystalline materials, composed of an aggregate of crystallites or grains, are foundational to modern engineering applications due to their versatile functional properties. The microstructural design—encompassing grain size, shape, orientation, phase distribution, and grain boundary characteristics—plays a pivotal role in determining mechanical, thermal, electrical, and magnetic behavior. This abstract explores the intricate relationship between microstructure and functionality, emphasizing how tailored processing techniques such as thermomechanical treatments, sintering, and additive manufacturing can …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 2, 2025 · pp. 16–20 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